Hematological index 	Formula

Mentzer index (MI) (1973)	MCV/RBC

RDWI (1987)	MCV × RDW/RBC

Shine and Lal (S and L) (1977)	MCV × MCV × MCH/100

Srivastava (1973)	MCH/RBC

Green and King (G and K) (1989)	MCV × MCV × RDW/Hb × 100

Sirdah (2007)	MCV − RBC − (3 × Hb)

Ehsani (2005)	MCV − (10 × RBC)

England and Fraser (E and F) (1973)	MCV − (5 × Hb) − RBC − 3.4

Ricerca (1987)	RDW/RBC

MDHL (1999)	(MCH/MCV) × RBC

MCHD (1999)	MCH/MCV


EXPREF	Total	N (case)	N (control)	Disease Case	Disease Control	Source	Detection Method	Reference

Exp25666440	23	11	12	naïve Fabry patients	ERT	urine	nanoLC-ESI-MS/MS	[25]

Exp17301227	13	N/A	N/A	6 months of ERT	before treatment (baseline)	blood	nanoLC-ESI-MS/MS	[26]

Exp18339188a	13	N/A	N/A	6 months of ERT	before treatment (baseline)	blood	microarray	[27]

Exp18339188b	13	N/A	N/A	naïve Fabry patients	healthy	blood	microarray	[27]

Exp20954982	30	20	10	Fabry	healthy	urine	MALDI-TOF MS	[28]

Exp23385635	14	8	6	Fabry	healthy	blood	MALDI-TOF MS	[29]

Exp23464927	10	N/A	N/A	12 months of ERT	before treatment (baseline)	urine	QTOF MS/MS	[30]

Exp25619383	46	32	14	Fabry	healthy	blood	LC-MS/MS	[31]

Exp21698285	124	35	89	naïve female Fabry	healthy	urine	CE-MS	[32]

Exp26490183	6	N/A	N/A	short term of ERT	before treatment (baseline)	blood	Illumina MiSeq instrument	[8]

Exp25582508	32	16	16	untreated Fabry males	healthy	urine	UPLC-ESI-TOF-MS	[33]


Technique	Type	Comments	References

Specific gene promoter: indicator protein fusions [i.e. beta-glucuronidase (GUS) or fluorescent proteins]	1, B	Long lead times of >2 months to get stably expressed genes, homozygous gene expression, sequences other than the promoter may control gene expression, no guarantee that promoter fragment chosen is correct, not suitable for plants that cannot be transformed.	[5]

Laser Capture Microdissection (LCM) and Single Cell Sampling (SiCSA)	2, A	Difficulty in isolating certain cell-types (e.g. vascular cells using SiCSA), long tissue prep (~2 weeks) for LCM, need for specialised equipment	[6,7]

in situ PCR	3, B	No specialised equipment required apart from vibratome, simple and fast method. No detailed protocol for plants until this manuscript, especially for agarose- embedded vibratome- sectioned in tube PCR. Can be performed on plants that are difficult to, or cannot be transformed. We do not recommend fluorescence detection of in situ PCR products due to interference with autofluorescence from plant tissue. As it is possible to do separate PCRs on adjoining tissue sections or replicate tissues from other plants we see no great advantage in multiplexing in situ PCR as it causes multiple complications to what is a robust and relatively simple technique. We do not recommend multiplexing in situ PCR due to the differential abundance of transcripts in the same cell and consequently the saturation of products, generation of non-specific products and problems with signal separation.

in situ hybridisation (ISH)	3, B	High detection threshold (10–20 copies per cell for ISH vs 1–2 copies per cell for in situ PCR), need to design a specific probe that hybridises to RNA while in situ PCR uses the same primers as qPCR, much cheaper. The View RNA Assay (Affymetrix) enables automated multiple transcript detection using fluorescence by employing the principles of ISH to detect nucleic acid targets within specific cells/cell-types. Its use is limited to abundant transcripts and laboratories equipped with and/or experienced in FFPE (formalin-fixed paraffin embedded) and frozen tissue preparation.	[8]

Protoplasting of fluorescently labelled cells and single cell sorting (FACS)	4, A	Can assay multiple transcripts at the same time. Potential damage responses of tissue. Needs specialised sorting flow cytometer. Limited to analysis of cells that are fluorescently labelled. Cannot give detail of all cells in which a particular gene is expressed.	[9,10]

Nuclear sorting, INTACT (isolation of nuclei tagged in specific cell types) or ribosomal binding techniques	4, A	When combined with microarrays or RNAseq can assay multiple transcripts at the same time. Limited to analysis of cells that are fluorescently labelled. Cannot give detail of all cells in which a particular gene is expressed. Not easily replicated.	[11-13]

In situ RNA sequencing	3, B	Offers the prospect of obtaining whole transcriptomes and more from single cells in tissue sections. Not yet optimised in any tissue. Has not been performed for plant tissue.	[14]


 	Breakfast eatersa	Breakfast skippersb	P valuec

n, %	4188, 90.4	443, 9.6

Men, %	78.2	73.8	0.04

Age, year	47.8 (7.1)	46.0 (6.8)	<0.001

Body mass index, kg/m2	22.9 (2.8)	22.9 (3.0)	0.78

Smoking status, %

 Current	26.7	44.9	<0.001

 Former	23.4	14.2

 Never	49.9	40.9

Leisure-time physical activity, %d

 ≥3 days/week	75.5	84.2	<0.001

 <3 days/week	16.0	9.5

Work-time physical activity, yes, %	5.3	7.7	<0.01

Family history of diabetes mellitus, yes, %	14.8	17.4	0.14

Fasting blood glucose, mg/dLe	92.3 (92.0–92.6)	92.5 (91.5–93.4)	0.74

Perceived stress, %d

 Very much	11.0	13.8	0.02

 Much	40.1	39.7

 Ordinary	43.8	39.1

 Little	4.9	6.8

Sleep duration, %d

 <7 hours/day	52.9	61.6	<0.001

 ≥7 hours/day	45.5	35.7

Work schedule, %d

 Without shift work or night shifts	84.6	78.3	<0.001

 With shift work but without night shifts	1.9	1.4

 Without shift work but with night shifts	6.8	7.9

 With shift work including night shifts	4.9	11.3

Total energy intake, kcal/day	1942 (538)	1740 (553)	<0.001

Alcohol consumption, g/day	13.6 (19.2)	18.1 (26.4)	<0.001

Eating speed, %d

 Very fast	11.4	12.9	0.67

 Relatively fast	35.8	37.9

 Medium	38.5	35.2

 Slow	12.6	12.4

Satiation eater, %	61.2	59.1	0.24

Fruits and vegetables intake, g/1000 kcal/day	142.3 (67.0)	118.7 (61.2)	<0.001

Fish intake, g/1000 kcal/day	84.1 (41.9)	84.8 (39.4)	0.74

Frequency of whole-grain cereals intake, %

 Always	8.5	5.7	0.10

 Sometimes	9.2	8.1

 Rarely	14.9	12.6

 No	67.4	73.6

Frequency of coffee intake, %d

 ≥4 cups/day	6.6	10.6	0.02

 2–3 cups/day	39.0	39.1

 1 cup/day	24.3	23.7

 <1 cup/day	28.8	25.1

Frequency of sugar-sweetened beverages intake, %d

 ≥1 serving/day	5.5	9.3	<0.001

 4–6 servings/week	5.3	7.0

 1–3 servings/week	29.9	36.3

 Never or rarely	57.6	45.1

Snack intake, yes, %	95.3	94.8	0.61


Recalled receiving information on:	CPan=106n (%)	PEan=619n (%)	p-value

Appropriate amount of weight gain	89 (84.0)	473 (76.4)	0.085

Exercise or active living during pregnancy	83 (78.3)	434 (70.1)	0.085

Nutrition	92 (86.8)	453 (73.2)	0.003

Taking vitamins or mineral supplements	92 (86.8)	543 (87.7)	0.789

Taking prescription or non-prescription drugs	75 (70.8)	430 (69.5)	0.790

Alcohol consumption during pregnancy	77 (72.6)	350 (56.5)	0.002

Cigarette smoking and second hand smoke	71 (67.0)	299 (48.3)	<0.001

Working during pregnancy	65 (61.3)	343 (55.4)	0.257


Population	Sample	Average	Standard deviation	Percentile 25%	Percentile 50%	Percentile 75%

General population	4176	59.3125	30.99565	40	70	80

General population (men)	1739	64.64347	29.17882	50	75	85

General population(women)	2437	55.50841	31.69165	30	60	80

General populationAge 16-44	2128	65.04229	31.28681	50	80	90

General populationAge 45-65	1130	56.4177	30.0071	40	65	80

General populationAge ≥ 65	918	49.59368	28.5296	25	50	70

General populationSeniors IAge 65-74	568	50.27641	28.75174	30	55	70

General populationSeniors IIAge 75-84	300	49.15	28.46545	20	55	70

General populationSeniors IIIAge ≥ 85	50	44.5	26.25172	20	50	63


Activity	Annual average E (mSv/yr)	Radiation source

Natural background due to external exposure (cosmic rays; terrestrial radionuclides)	0.9 (0.4; 0.5)	Cosmic rays, terrestrial radionuclides

Natural background due to internal exposure (inhalation; ingestion)	1.5 (1.2; 0.3)	Terrestrial radionuclides

Total natural background, worldwide	2.4	Cosmic rays, terrestrial radionuclides

Natural background due to cosmic rays, world average	0.380	Cosmic rays

Natural background due to cosmic rays, sea level	0.270	Cosmic rays

Natural background due to cosmic rays, 1600 m amsl	0.570	Cosmic rays

Natural background due to cosmic rays, 2200 m amsl	0.820	Cosmic rays

Natural background due to cosmic rays, 3900 m amsl	2.020	Cosmic rays

8 hours of flight (London-New York)	0.030 – 0.045 per flight	Cosmic rays


Characteristics	Hazard Ratio (95% Confidence Interval)a

Age (continuous)	1.01 (1.001–1.02)*

Sex, female (versus male)	1.05 (0.80–1.37)

Charlson Comorbidity Index

 0	Reference

 1	0.90 (0.62–1.29)

≥ 2	0.94 (0.68–1.31)

Observation periodb

 Period 1 in Pre-Campaign Year (weeks 1–5)	3.22 (0.88–11.7)

 Period 2 in Pre-Campaign Year (weeks 6–10)	0.97 (0.20–4.80)

 Period 3 in Pre-Campaign Year (weeks 11–15)	2.27 (0.59–8.77)

 Period 4 in Pre-Campaign Year (weeks 16–20)	0.98 (0.20–4.85)

 Period 5 in Pre-Campaign Year (weeks 21–25)	0.98 (0.20–4.85)

 Period 6 in Pre-Campaign Year (weeks 26–30)	2.29 (0.59–8.87)

 Period 7 in Pre-Campaign Year (weeks 31–35)	0.99 (0.20–4.89)

 Period 8 in Pre-Campaign Year (weeks 36–40)	3.31 (0.91–12.0)

 Period 9 in Pre-Campaign Year (weeks 41–45)	1.00 (0.20–4.94)

 Period 10 in Pre-Campaign Year (weeks 46–50)	Reference

 Period 1 in Year 1 (weeks 1–5)	2.99 (0.81–11.1)

 Period 2 in Year 1 (weeks 6–10)	1.34 (0.30–5.98)

 Period 3 in Year 1 (weeks 11–15)	1.34 (0.30–6.00)

 Period 4 in Year 1 (weeks 16–20)	7.09 (2.11–23.8)**

 Period 5 in Year 1 (weeks 21–25)	13.6 (4.21–44.1)***

 Period 6 in Year 1 (weeks 26–30)	4.27 (1.20–15.1)*

 Period 7 in Year 1 (weeks 31–35)	3.23 (0.87–11.9)

 Period 8 in Year 1 (weeks 36–40)	2.16 (0.54–8.66)

 Period 9 in Year 1 (weeks 41–45)	1.45 (0.32–6.48)

 Period 10 in Year 1 (weeks 46–50)	2.55 (0.66–9.86)

 Period 1 in Year 2 (weeks 1–5)	2.91 (0.77–11.0)

 Period 2 in Year 2 (weeks 6–10)	3.30 (0.89–12.2)

 Period 3 in Year 2 (weeks 11–15)	1.84 (0.44–7.72)

 Period 4 in Year 2 (weeks 16–20)	1.48 (0.33–6.62)

 Period 5 in Year 2 (weeks 21–25)	1.49 (0.33–6.65)

 Period 6 in Year 2 (weeks 26–30)	2.24 (0.56–8.97)

 Period 7 in Year 2 (weeks 31–35)	1.50 (0.34–6.72)

 Period 8 in Year 2 (weeks 36–40)	1.13 (0.23–5.60)

 Period 9 in Year 2 (weeks 41–45)	1.89 (0.45–7.91)

 Period 10 in Year 2 (weeks 46–50)	1.90 (0.45–7.95)


Concept given to justify why brain death is death	Neurologist responses (n = 192) [n (%; 95% confidence interval)]	Neurologists who agreed the conceptual basis makes brain death equivalent to death (n = 133) [n (%; 95% confidence interval)]

Higher brain concept	63 (33%; 27-40%)	52 (39%; 31-48%)

 Loss of integration of body concept	15 (8%; 5-13%)	13 (10%; 6-16%)

 Loss of integration alone	7 (4%; 2-7%)	7 (5%; 2-11%)

 Loss of integration combined with higher brain concept	8 (4%; 2-8%)	6 (5%; 2-10%)

Prognosis concept	9 (5%; 2-9%)	5 (4%; 1-9%)

 Prognosis of death certain	7 (4%; 2-7%)	3 (2%; 1-7%)

 Quality of life statement	2 (1%; 0-4%)	2 (2%; 0-6%)

No concept given	96 (50%; 43-57%)	59 (44%; 36-53%)

 Re-statement only: loss of brain function (the criterion)	32 (17%; 12-23%)	23 (17%; 12-25%)

 No response (blank)	64 (33%; 27-40%)	36 (27%; 20-35%)

Vital work of organism concepta	4 (2%; 1-5%)	0 (0%; 0-2%)

Other	9 (5%; 2-9%)	4 (3%; 1-8%)


SNP	LVRS Response Phenotype	All subjects(n = 203)	Upper lobe, low exercise(n = 59)	Upper lobe, high exercise(n = 84)	Non-upper lobe, low exercise(n = 23)	Non-upper lobe, high exercise(n = 37)

		β	p	β	p	β	p	β	p	β	p

rs3753658	BODE	-0.8	0.008	-1.3	0.01

	UCSD SOBQ	-7.7	0.02	-11.7	0.05

rs1877724	Post-BD FEV1, liters	-0.06	0.04	-0.13	0.01

rs2234922	BODE	0.5	0.02					1.6	0.02

	Max work, watts	-3.7	0.05

rs1051741	Max work, watts	-5.9	0.01					-8.4	0.09	-10.2	0.09

rs2292558	Max work, watts	-5.1	0.03					-8.4	0.09	-10.2	0.09


Round 1

Communicating about symptoms and quality of life	(1) Tell us about a time when you told your doctor or nurse about a symptom that was bothering you—like trouble sleeping or being sick to your stomach. What was difficult or easy about this time?

(2) How do you usually let your doctor or nurse know about these things? How does speaking Spanish affect what you do or do not tell your doctor or nurse?

(3) Here is a list of symptoms and quality of life issues common for people during treatment for cancer. Is there anything missing? Is there anything on the list that is not easy to understand?

Using the Internet	(4) How often do you use the Internet, and how do you access it—for example, from a computer, your phone? Do you know how to access the Internet yourself, or does someone help you?

(5) Are there websites or applications that you use to learn about health information or to track your activities, like exercise? What do you like about these websites or applications?

Responding to Spanish ESRA-C mock website	(6) Why do you think this website would, or would not, be interesting or useful for you?

(7) Do you think most people can understand these questions clearly and give answers?

(8) What do you think patients and their families would find most helpful about this information? How can we make it better?

Round 2

Review of new patient narration	(1) How well does this new version meet the ideas you had about hearing from a patient's point of view?

(2) What thoughts did you have about the patient shown in the pictures who was telling her story? How similar are her concerns to the ones that you thought about when you were going to start treatment?

Review of new website home page and introduction	(3) You saw the woman using the website to learn about getting help and then telling her nurse about problems she was having. How much does this encourage you to talk to your nurse or doctor?

(4) Did we explain well enough for you to understand that the answers you give on this website will go to your doctors and nurses?

Review of messages in revised patient education and communication coaching	(5) If you put these three messages in order from most to least important for new patients to hear, what order would you put them in? Why?

(6) Are there any words in the website that do not sound right to you, or do you think we could say better?

Working with interpreters	(7) If you have used professional interpreters, what have you learned about the process that you wish you had known before you started your treatment? If you have not, what would you like to know about using interpreters?

Emailing providers	(8) Have you had experience emailing your providers, and if so, how well did that work?

(9) How would you feel about being able to email a question in Spanish to a translator or bilingual provider who could ask your doctor or nurse and reply to you?

Prioritizing future revisions	(10) The last thing we want to show you is a list of things that people suggested should be added to the website. If you like any of these ideas, or another idea you have, which of these should we work on first?


Subjects	27

Sex	14 (51.8%) male

Age (years)	7.92 (±2.52)

Weight (kilograms)	34.89±14.89

Height (meters)	1.34±0.15

BMI (kg/m2), z-score	18.63±14.92, 0.09±1.88

Tonsil size	Grades 3 and 4

Tonsil volume, mean (cm3) ± standarddeviation	7.41±3.77


Gene	Forward primer (5′ to 3′)	Reverse primer (5′ to 3′)

MeCWINV1	CGCGGATCCAAAATAGAGATGGAAGCAAT	CGCGTCGACATCATTTCTCAAACATACCC

MeCWINV2	CATGCCATGGTCTTCTTCATCTTCAGTC	CGGGTTACCTTTTATCTTTAGCTCAGC

MeCWINV3	TCAATCAAAGGAGCTATGGACA	GCACTGGCTTCTTTTATTTCATC

MeCWINV4	TATGGATCCCTCACCAGCATGGCTATCA	CATGTCGACTGTCAACCCTGGCTATTTCTCA

MeCWINV5	TCATCCCGCAAATTCAACATT	GCTTACTTCTTTTCCACCTTATTTTTT

MeCWINV6	CTCATTATCCCAAACAGATCAACC	ATTCTCACTTCTTTAAGCAGTCTCA


	HRCT score	MRI score

		0	1	2	3	4

Consolidation	52					52

Alteration consistent with caseosis	undetermined					4

Cavitation	39					39

Ground glass	6			2	1	4

Nodule	43					43

Tree in bud	33					29

Interstitial changes	14			1	4	13

Lymph nodes	(Short axis > 10 mm) 38					56

Edema	undetermined					50

Alteration consistent with colliquative necrosis	undetermined					2

Alteration consistent with caseosis	undetermined					4

Pleural involvement	10					21


Term	Genes	p-value

hsa05214:Glioma	CDKN1A, CDK6	0.018

hsa04115:p53 signaling pathway	CDKN1A, CDK6	0.019

hsa05218:Melanoma	CDKN1A, CDK6	0.02

hsa05220:Chronic myeloid leukemia	CDKN1A, CDK6	0.02

hsa04066:HIF-1 signaling pathway	CDKN1A, TFRC	0.028

hsa04110:Cell cycle	CDKN1A, CDK6	0.035

hsa05161:Hepatitis B	CDKN1A, CDK6	0.041


	Model 1	Model 2	Model 3	Model 4

Independence	1076	1076	717	279

Chi-square	(378 df)	(378 df)	(171)	(55 df)

Average standardised residuals	0.11	0.09	0.09	0.09

Average off-diagonal st. residuals	0.12	0.10	0.10	0.11

Chi-squared fit	534.7	520	213	67.7

(df)s	(347 df)	(347 df)	(150 df)	(43)

P-value	0.00001	0.00001	0.001	0.01

Free parameters	59	57	40	23

Akaike's information criterion (AIC)	-193	-173	-87	-18

Bozodgan's version of AIC (C-AIC)	(-1437)	(-1424)	(-627)	(-173)

Comparative Fit Index (CFI)	0.73	0.75	0.89	0.90

Normed Fit Index (NFI)	0.50	0.52	0.70	0.76

Non-normed Fit Index (NNFI)	0.71	0.73	0.87	0.86


Themes	Categories	Definitions

Development of national maternal healthguidelines	 · Development Process	· the steps taken to develop and produce guidelines

	 · Stakeholder participation	· level of involvement of stakeholders in guideline development

	 · National guidelines' relation to WHO recommendations	· how contents of national CPGs compare with WHO PCPNC guidelines

Health workers' access to guidelines	Perceived access barriers

	 · Distribution	· physical distribution of printed guidelines

	 · Staff mobility	· frequent changes of work-place displaces guidelines from health facilities

	 · Health workers' participation in training courses	· course curricula frequently used as CPGs, health workers dependent on courses to obtain up-to-date guidelines

	<underline>Perceived solutions to improve access:</underline>

	 · Pocket sized guidelines	· personal portable guidelines for every health worker

	 · Wall posters	· guidelines in a poster format increases availability for everybody working in the health facility

Health workers' use of guidelines	 · Low levels of guideline adherence	· perception among key informants of an overall low use of guidelines by front-line health workers

	<underline>Perceived reasons for low guideline adherence:</underline>

	 · Attitudes towards continuing education	· health workers do not usually update their knowledge independently from organised training

	 · Effects of training	· limited change in clinical practice following courses

	 · Format of guidelines - lack of usability	· presence of flow-charts, algorithms etc.

	 · Negative beliefs about using guidelines during patient consultations	· perception that patients' trust will be undermined if health workers use CPGs during consultations


Effect	Data structure	Type of test	Power	df (between)	df (within)	F	χ2	p

Pairwise discrimination phase (d)	Normally distributed	Two-factor repeated-measures ANOVA	0.96	1	9	17.58		0.002

Pairwise discrimination genotype (d)	Normally distributed	Two-factor repeated-measures ANOVA	0.41	1	9	3.78		0.08

Pairwise discrimination interaction (d)	Normally distributed	Two-factor repeated-measures ANOVA with post hoc Bonferroni correction	0.13	1	9	0.83		0.4

Pairwise discrimination phase (trials)	Normally distributed	Two-factor repeated-measures ANOVA	0.62	1	9	6.45		0.03

Pairwise discrimination genotype (trials)	Normally distributed	Two-factor repeated-measures ANOVA	0.16	1	9	1.10		0.3

Pairwise discrimination interaction (trials)	Normally distributed	Two-factor repeated-measures ANOVA	0.06	1	9	0.13		0.7

Pairwise discrimination (survival curve)	Normally distributed	Mantel–Cox test	0.06	1			0.53	0.5

Pairwise discrimination reversal (survival curve)	Normally distributed	Mantel–Cox test	0.07	1			0.48	0.5


Authors/Year	Country	Design	Valable	OR (95% CI)

Chen 1995 [17]	England	Case–control	Severe life events	11.64 (3.10-43.66)

Protheroe 1999 [19]	Australia	Case–control	Severe life events	0.91 (0.47-1.81)

Kruk 2012 [20]	Poland	Case–control	Major life events	5.33 (4.01-8.21)

Helgesson 2003 [21]	Sweden	Prospective	Stressful events	2.1 (1.2-3.7)

Lillberg 2003 [22]	Finland	Prospective	Major life events	1.35 (1.09-1.67)

Michael2009 [23]	America	Prospective	≥4 life events	0.91 (0.77-1.08)


Adverse reactions and treatment	Ketotifen	Placebo

Total no. of doses of OIT, n	36	18

Total no. of patients reporting symptoms	3/4	2/2

Total no. of doses with symptoms, n (% of total OIT doses)	8/36 (22%)	12/18 (67%)

Anaphylaxis, n (% of total OIT doses)	-*	1 (5%)

Symptoms n, (% of OIT doses)	Ketotifen	Placebo

Gastrointestinal	6/36 (17%)	11/18 (61%)

Cutaneous	-	1/18 (6%)

Lower respiratory	2/36 (6%)	1/18 (6%)

Oropharyngeal	-	2/18 (11%)

Upper respiratory	-	-

Cardiovascular	-	-

OtherA	-	2/18 (11%)

Treatment n, (% of OIT doses)	Ketotifen	Placebo

Epinephrine	-	-

Diphenhydramine	-	-

Cetirizine or other**	-	1/18 (6%)

Prednisone	-	-

Salbutamol or other inhaled medication	-	1/18 (6%)


Condition	Test	Absolute error (95% CI)	Symptomatic diagnosis-Tariff method with health care experience absolute error (95% CI)

Asthma	World Health Survey (WHS): Doctor (MD) diagnosis (Dx) [34]	0.023 (0.020, 0.025)	0.014 (0.012, 0.016)

WHS MD Dx OR asthma medications (Rx) [34]	0.023 (0.020, 0.025)

WHS MD Dx OR asthma Rx OR wheezing/whistling attacks [34]	0.092 (0.087, 0.095)

Angina pectoris	Rose questionnaire [35,36]	0.082 (0.073, 0.088)	0.020 (0.018, 0.022)

Depression	Composite international diagnostic interview questionnaire [37]	0.059 (0.054, 0.064)	0.016 (0.015, 0.017)


	Topic

Week 1

Day 1	An Overview of Maternal-Infant Care

Day 2	The Role of the Birth Attendant, Health Care Resources, and the Emergency Plan

Week 2

Day 3	Sexual Organs, Sexual Desire, and Menstruation, Ovulation, and Fertilization

Day 4	The Natural Development of Pregnancy

Week 3

Day 5	The Choice of Motherhood, The Importance of Prenatal Care—Part 1

Day 6	The Importance of Prenatal Care—Part 2

Week 4

Day 7	Pregnancy Complications, Part 1

Day 8	Pregnancy Complications, Part 2

Week 5

Day 9	Signs and Symptoms of Danger during Pregnancy

Day 10	Case Studies on Prenatal Care, Exam 1

Week 6

Day 11	Review Exam 1

Day 12	Tetanus Vaccine, Introduction to Stages of Labor

Week 7

Day 13	Uncomplicated Labor: Stage One and Two

Day 14	Uncomplicated Labor: Stage Two and Three

Week 8

Day 15	Review of Stages of Labor, Basic Care of the Newborn

Day 16	Complications during Labor and Delivery

Week 9

Day 17	When to Refer during Labor

Day 18	Neonatal Resuscitation, Immediate Post-Partum Care, Maternal Lactation

Week 10

Day 19	Maternal Lactation Review, Post-Partum Care: Day 1 & 4

Day 20	Review of Normal and Complicated Labor, Exam 2

Week 11

Day 21	Medicinal Plants, Sharing of Experiences during Labor

Day 22	Infection Prevention and Management, Sterilization of Birth Tools

Week 12

Day 23	Family Planning Methods

Day 24	Case Studies: Family Planning, Self Breast Exam

Week 13

Day 25	Vaginal Infections and STIs

Day 26	Nutrition and Malnutrition

Week 14

Day 27	Complicated Labor

Day 28	Cumulative Review, Final Exam


Ergonomic problems

Categories	Working posture and type of examination	Equipment and physical factors	The patient’s physique and health	Work experience and knowledge

Subcategories	-Echocardiography-Vascular examinations-Bedside examination	-Ultrasonic device-Examination room including table and equipment to assist patients-Physical factors including light, noise and ventilation	-Patient constitution-Inpatients	-Lack of skills


Variables	Chi Square	95% C.I.	Hazard Ratio	P Value

DFS

1. Cellular differentiation	10.51	4.20 – 463.30	0.3101	0.005*

OS

1. Tumor Grade	6.08	1.41 – 3.07	0.2741	0.01*


 	Number of people	Percentage (%)

Before preferences learning	3	7.65%

After preferences learning	14	82.35%

Total number of people and percentage	17	100%


 	Patients (n)	HSR (n)	HSR (%)	p value1

Sex

Female	113	16	14.2	0,0147

Male	78	1	1.3

Prior exposure to platinum salts

Yes	45	8	17.8	0,0220

No	146	9	6.2

Atopic background

Yes	32	4	12.5	0,4367

No	159	13	8.2


	Oromia	SNNP	All

	n = 57	n = 73	n = 130

	n	%	n	%	n	%

Training Received by HEWsa	In past 3 years	In past 3 years	In past 3 years

Integrated refresher training	56	98%	67	92%	123	95%

Possible severe bacterial infections management	53	93%	66	90%	119	92%

Integrated community case management	56	98%	60	82%	116	89%

Maternal, newborn, and child health	52	91%	57	78%	109	84%

Health management information system	30	53%	72	99%	102	78%

Tuberculosis prevention and control	36	63%	62	85%	98	75%

Nutrition	41	72%	54	74%	95	73%

Family planning	36	63%	54	74%	90	69%

Malaria prevention and control	41	72%	31	42%	72	55%

HIV/AIDS and sexually transmitted infections	35	61%	31	42%	66	51%

Hygiene and environmental sanitation	32	56%	31	42%	63	48%

Immunization	32	56%	28	38%	60	46%

Adolescent reproductive health	24	42%	31	42%	55	42%

First aid	15	26%	9	12%	24	18%

Supervision and Technical Support Received	In past 3 months	In past 3 months	In past 3 months

Any supervision or technical supportb	54	95%	73	100%	127	98%

By Primary Health Care Unit (PHCU)c	53	93%	67	92%	120	92%

By Woreda Health Office (WoHO)d	43	75%	58	79%	101	78%

	Median	IQR	Median	IQR	Median	IQR

If supervised by PHCU, times in past 3 months	4.5	(2–8)	5	(3–8)	5	(2–8)

If supervised by WoHO, times in past 3 months	1	(1–2)	2	(1–2)	1	(1–2)


Items	Mean age	Diagnosis	ACF	PIF + PD	One stage of ACF and PIF + PD

Present study	67.6 y/o	Degenerative cervical kyphosis with stenosis	ABL: 135.2 ± 85.2 ml	ABL: 307.7 ± 92.3 ml	ABL: 442.9 ± 236.0 ml

MST: 136.8 ± 52.3 min	MST: 139.3 ± 50.4 min	MST: 314.5 ± 51.2 min

Du et al. [2]	59.6 y/o	CSM/OPLL/cervical stenosis	None	ABL: 650 mL MST: 150 min	None

Epstein et al. [20]	54.0 y/o	OPLL	None	None	ABL: 500 ml

MST: 522 min


Characteristic	Cluster 1 Most Severe (n = 30)	Cluster 2 Intermediate (n = 67)	Cluster 3 Least Severe (n = 67)

 SF-36 Scales (mean ± sd)

Physical function	49.5 ± 21.8	71.8 ± 20.1	91.0 ± 10.3

Role physical	12.5 ± 26.9	48.1 ± 36.0	92.5 ± 19.5

Bodily pain	39.5 ± 18.3	53.7 ± 16.5	79.4 ± 15.6

General health	45.4 ± 19.3	67.4 ± 13.8	85.3 ± 12.6

Vitality	14.3 ± 11.0	34.6 ± 15.8	69.6 ± 16.0

Social function	45.4 ± 24.0	67.9 ± 18.4	96.3 ± 8.7

Role emotional	47.8 ± 41.7	74.1 ± 35.2	96.0 ± 13.6

Mental health	61.5 ± 19.5	74.4 ± 13.5	86.9 ± 9.1

 MFI Scales (mean ± sd)

General fatigue	18.4 ± 1.4	15.1 ± 2.7	8.7 ± 3.2

Physical fatigue	15.4 ± 2.7	11.6 ± 2.8	6.7 ± 2.1

Mental fatigue	15.9 ± 3.5	10.3 ± 3.9	6.6 ± 2.7

Reduced motivation	13.4 ± 4.0	10.3 ± 3.0	6.2 ± 2.0

Reduced activity	15.8 ± 3.3	11.9 ± 3.5	5.9 ± 2.0

Symptom Inventory (mean ± sd)	52.2 ± 24.8	21.6 ± 12.6	7.0 ± 8.5


Class	Biophysical Features	Geographical Regions

1	lowest temperature and high chlorophyll a	south side of Bali, Sumbawa, Fores and Sumba

2	moderate biophysical conditions	Savu Sea (in the west) and Arafura Sea (in the east)

3	high chlorophyll a and high salinity	Van Dieman Gulf and Beagle Gulf (out of the SBS)

4	low chlorophyll a and high salinity	Timor Sea

5	the lowest chlorophyll a and the highest currents	Banda Sea, Molucca Sea (to the north), Ceram Sea (to the east), Flores Sea (to the southwest).

6	low chlorophyll a and medium currents	Bali Sea, Flores Sea and Gulf of Boni

7	the second highest overall temperature	Halmahera Sea and Molucca Sea

8	highest overall temperature	Gulf of Tomini and Makassar Strait (northeast of the SBS, south to the Equator)

9	high chlorophyll a and low salinity	Java Sea


Gene name	Primers	Annealing temperature

hHSF4F	CCCCCTCAAGAAAGTGTGGAA	60°C

hHSF4R	GAACCAAGGGCTGCATCAAG	60°C

mHSF4F	GGCACCAGCTTCCTCGTAAG	60°C

mHSF4R	CCTTCCGAAAACCATACATGTTG	60°C

hCrygsF	CCCAACTTTGCTGGGTACATG	60°C

hCrygsR	GGCCTCCACTAGGCAGATGA	60°C

mCrygsF	AGCGTTGGATGGGCCTTAAT	60°C

mCrygsR	GTTTCGTACATCTGACCGTTGAAG	60°C

hBFSP1F	TTCAGTGGGAGAGAGATGTTGAAA	60°C

hBFSP1R	CTCCTGGGTCTGGGACATGT	60°C

mBfsp1F	AGACGCCCATCTCTCTGATCA	60°C

mBfsp1R	AGGGCCTTCTGTCTCGGTTT	60°C

hBFSP2F	TTCAGTGGGAGAGAGATGTTGAAA	60°C

hBFSP2R	CTCCTGGGTCTGGGACATGT	60°C

mBfsp2F	GCACCGGTCTGGATGATGTC	60°C

mBfsp2R	ACGTGGACCACCTCTGTCTG T	60°C

mLp82F	ATTGGCTTCGCCATCTACGA	60°C

mLp82R	CCCGCATGTTGATGTAGGTTT	60°C

mCalpain2F	ATGCGGAAAGCACTGGAAGA	60°C

mCalpain2R	CCAAACACCGCACAAAATTG	60°C


Animal models	Polyurethane scaffolds	Major conclusions	Reference

Iliac crest (sheep)	Porous scaffolds synthesized from HMDI, PEO-PPO-PEO, and PCL at various ratios. Pore size, 300 to 2,000 μm; porosity, 85%	At 18 and 25 months, all the defects in the ilium implanted with polyurethane bone substitutes had healed with new bone.	Gogolewski and Gorna ([2007]), Gogolewski et al. ([2006])

The extent of bone healing depended on the chemical composition of the polymer from which the implant was made.

The implants from polymers with the incorporated calcium-complexing additive were the most effective promoters of bone healing, followed by those with vitamin D and polysaccharide-containing polymer.

There was no bone healing in the control defects.

Bone marrow stromal cells	BDI with PCL films	Bone marrow stromal cells were cultured on rigid polymer films under osteogenic conditions for up to 21 days. This study demonstrated the suitability of this family of PEUUs for bone tissue engineering applications.	Kavlock et al. ([2007])

Femoral condyle	LTI with PCL-co-PGA-co-PDLLA	Extensive cellular infiltration deep to the implant and new bone formation at 6 weeks	Dumas et al. ([2010])

Chondrocytes	Porous scaffolds synthesized from HMDI with PCL and ISO	Although the covalent incorporation of the isoprenoid molecule into the polyurethane chain modified the surface chemistry of the polymer, it did not affect the viability of attached chondrocytes.	Eglin et al. ([2010])

		The change of surface characteristics and the more open pore structure of the scaffolds produced from the isoprenoid-modified polyurethane are beneficial for the seeding efficiency and the homogeneity of the tissue-engineered constructs.


Central cardiologist

 	 	No RV dysfunction (n)	RV dysfunction (n)	Total (n)

Local cardiologist	No RV dysfunction (n)	55	4	59

RV dysfunction (n)	3	11	14

Total (n)	58	15	73


Label	Predicted function	Activity present in the following species	Activity suspected in T. maritimum

Iron uptake

MARIT_0169-0174	Siderophore biosynthesis system, Tbs	Deep sea metagenome (Fujita et al., 2012)	Avendaño-Herrera et al., 2005b

MARIT_1312-1313	Heme uptake mechanism, HmuYR	Porphyromonas gingivalis (Olczak et al., 2008; Wójtowicz et al., 2009)	Avendaño-Herrera et al., 2005b

MARIT_0141 – 0142	Fe2+ uptake system, FeoAB	Porphyromonas gingivalis (Lau et al., 2016)	Avendaño-Herrera et al., 2005b

MARIT_1664	Iron acquisition, uptake or storage, imelysin family protein	Synechococcus elongatus (Xu et al., 2011)	Avendaño-Herrera et al., 2005b

MARIT_1661	Iron acquisition, uptake or storage, imelysin family protein	Synechococcus elongatus (Xu et al., 2011)	Avendaño-Herrera et al., 2005b

Stress resistance

MARIT_3105	Superoxide dismutase [Mn/Fe], SodA	Staphylococcus carnosus (Barrière et al., 2001)	Suzuki et al., 2001

MARIT_1670	Superoxide dismutase [Fe], SodB	Legionella pneumophila (Amemura-Maekawa et al., 1996)	Suzuki et al., 2001

MARIT_1821	Superoxide dismutase [Cu–Zn], SodC	Schistosoma mansoni (da Silva et al., 1992)	Suzuki et al., 2001

MARIT_0946	KatG catalase	Geobacillus stearothermophilus (Singh et al., 2008)	Suzuki et al., 2001

MARIT_2408	KatA catalase	Pseudomonas aeruginosa (Brown et al., 1995)	Suzuki et al., 2001

Toxins

MARIT_0124	Cholesterol-dependent cytolysin	Capnocytophaga canimorsus (Gilbert, 2010)	Baxa et al., 1988

MARIT_1085	Collagenase	Cytophaga sp. (Sasagawa et al., 1995)	Baxa et al., 1988

MARIT_1748	Sphingomyelinase	Bacillus cereus (Oda et al., 2010)

MARIT_2033	Ceramidase	Pseudomonas aeruginosa (Ito et al., 2014)

MARIT_2107	Chondroitin AC lyase	Flavobacterium columnare (Suomalainen et al., 2006)	Rahman et al., 2014

MARIT_2328	Streptopain family protease	Streptococcus pyogenes (Nelson et al., 2011)	Wakabayashi et al., 1986; Baxa et al., 1988

MARIT_2678 - 2687	Sialoglycan degradation and uptake	Capnocytophaga canimorsus (Mally et al., 2008)


Sample items	%Agree

I am worried that other people might realize that I am HIV + if they see me taking my HIV medications.	52

I get frustrated taking my HIV medications because I have to plan my life around them.	40

I don’t like taking my HIV medications because they remind me that I am HIV + .	40

I feel that my healthcare provider takes my needs into account when making recommendations about which HIV medications to take.	84

Most people who are important to me who know I’m HIV positive support me in taking my HIV medications.	88

My healthcare provider doesn’t give me enough support when it comes to taking my medications as prescribed.	24

It frustrates me to think that I will have to take these HIV medications every day for the rest of my life.	44

I am worried that the HIV medications I have been prescribed will hurt my health.	56

It upsets me that the HIV medications I have been prescribed can affect the way I look.	52

It upsets me that the HIV medications I have been prescribed can cause side effects.	64


Smoking habit	Frequency among patients	Percentage	95% Confidence interval

No	106	77.9	70.1-84.2

Yes	27	19.9	13.9-27.5

Unknown	3	2.2	0.7-6.7


	Mean (standard deviation)	Min value	Max value

CGI-S	4.16 (0.92)	2	6

PANSS total score	79.4 (16.34)	45	140

PANSS positive score	16.46 (5.15)	7	33

PANSS negative score	23.19 (5.68)	10	43

PANSS general score	39.75 (9.77)	18	76

V-SIR	24.32 (7.82)	9.4	49.19

SCD total score	7.6 (4.1)	0	18


Features	Patients

n	Frequency %

Gender

 Males	344	82.3

 Females	74	17.7

Age (years)

 Min	31

 Max	93

 Mean ± SD	 	66.7 ± 10.9

 Median	67

Smoking

 Smokers	283	67.7

 Nonsmokers	117	28.0

 Not specified	18	4.3

Tumor stages

 TIS	1	0.2

 Ta	91	21.8

 T1	198	47.4

 T2	72	17.2

 T3	27	6.5

 T4	27	6.5

 Not specified	2	0.4

Tumor grades

 1973

CIS	1	0.2

G1	139	33.3

G2	186	44.5

G3	86	20.6

Not specified	6	1.4

 2004

PUNLMP	11	2.6

CIS	1	0.2

Low	241	57.7

High	156	37.3

Not specified	9	2.2

Recurrence

 No	268	64.1

 Yes	150	35.9


	Final grade

	Grade	1	2	3

Predicted grade	1	21	0	0

	2	5	35	9

	3	1	6	7

	1 or 2	7	1	1

	2 or 3	0	2	8

	Not predicted	1	1	0


	Nurse/midwives n = 13	Doctors n = 05	Administrators n = 06

Age (years)

<30	6	1	0

30-39	3	3	0

40-49	2	0	1

≥50	2	1	5

Marital status

Single	1	0	0

Married	12	5	6

Widowed	0	0	0

Gender

Female	13	0	0

Male	0	5	6

Years of experience

0-4	5	2	1

5-9	5	2	0

10-15	1	0	0

15+	2	1	5

Hospital location

Urban	8	4	3

Peri-urban	5	1	3


	Total	N/100 orders	N/100 admissions	N/1000 patient-days

Orders	4942	NA*	7844	9709

Medication error	492	10	780	967

Adverse drug events	8	0.16	12.6	15.7

Potential adverse drug events	113	2.28	179.3	222


Parameters	Value

Plant life	30 years

Discount rate	10%

Financing	40% equity

Loan terms	10-year loan at 8% APR

General plant depreciation	200% declining balancea

General plant recovery period	7 years

Steam plant depreciation	150% declining balance

Steam plant recovery period	20 years

Construction period	3 years

0-12 months	8% of project cost

12-24 months	60% of project cost

24-36 months	32% of project cost

Working capital	5% of fixed capital investment

Start-up time	3 months

Revenues during start-up	50%

Variable costs incurred during start-up	75%

Fixed costs incurred during start-up	100%


 Patient characteristics

Male/female	49 (63.6%)/28 (36.4%)

Birth weight (gr)	2930 ± 485 (range 4300-1800)

Gestational age at delivery (wk)	37 ± 2 (range 42–32)

Term/preterm delivery	40 (52%)/37 (48%)

Left/right side	67 (87%)/10 (13%)

Inborn/outborn	71 (92.2%)/6 (7.8%)

Prenatal diagnosis	68 (88.3%)

Associated anomalies	18 (23.4%)

Associated congenital heart diseases	4 (5.2%)


date (day of chth)

(I day)	1.	Doxorubicin 80 mg i.v.

	2.	Cis-Platinium 40 mg i.v.

	3.	5-FU 800 mg i.v.

	4.	Roferon 9 MU

(II day)	1.	Cis-Platinium 40 mg i.v.

	2.	5-FU 800 mg i.v.

	3.	Roferon 9 M U

(III day)	1.	Cis-Platinium 40 mg i.v.

	2.	5-FU 800 mg i.v.

	3.	Roferon 9 M U

(IV day)	1.	Cis-Platinium 40 mg i.v.

	2.	5-FU 800 mg i.v.

	3.	Roferon 9 M U


Characteristics	Patients

Median age (y) (range)	52 (36–76)

Median parity (range)	3 (0–9)

Median BMI (range)	31.2 (21.4–41.5)

Prior surgery for prolapse including hysterectomy (n, %) 	3 (15)

Prior hysterectomy for benign tumor (n, %)	4 (20)

Stage of prolapse

  Stage II (n, %)	6 (30)

  Stage III (n, %)	12 (60)

  Stage IV (n, %)	2 (10)

Urinary incontinence (n, %)	16 (80)


Activities	Advantages	Specific challenges	Response

School meetings	• Easy to organize	• Low attendance	• Follow-up school meetings organized

• Resource and time efficient	• Consenting decisions may be influenced by other parents	• Meetings held outside classrooms to minimize disruption

• Follow-up consent meetings allowed time for consultations	• Disruption to school schedules	• Insistence on parental consent

 	• Danger of proxy consent from relatives	• Household visits

Household visits	• Allows for more in-depth and one-on-one discussions of the study	• Difficulties in tracking households	• Use of village elders/community health workers to track parents

• Eliminates pressure and influence associated with school meetings	• Unavailability of parents at home	• Field workers sent to households early in the morning or late in the evening

• Can allow joint decision-making to participate in research	• Time consuming

 	• Resource intensive


Fluorescent real-time PCR	Orientation	Sequencea (5'---3')	Amplicon length (bp)

TaqMan	Sense	CCGCCTTTGAGTGAGCTGATA	210

	Anti-sense	TGTAGACAACATCCCCTCCCC

	Probe	FAM CGCCGCAGCCGAACGACCGAG TAMRA

	Sense	GTATTACCGCCTTTGAGTGAGCT	510

	Anti-sense	ATGACAATCAGCTACTTCACTGTTG

	Probe	FAM CGCCGCAGCCGAACGACCGAG TAMRA

	Sense	CCGCCTTTGAGTGAGCTGATA	992

	Anti-sense	CTCCGCTGGTCCGATTGAAC

	Probe	FAM CGCCGCAGCCGAACGACCGAG TAMRA

	Sense	CCGCCTTTGAGTGAGCTGATA	1596

	Anti-sense	AATGGTTTCTGACGTATGTGCTTAG

	Probe	FAM CGCCGCAGCCGAACGACCGAG TAMRA

UTa	Sense	taggaacaggcggcgacgaATACAA CATCCGCTTGCCCTCATC	195

	Anti-sense	TGCCAAAGGGTTCGTGTAG

	Sense	taggaacaggcggcgacga ATACAA CATCCGCTTGCCCTCATC	546

	Anti-sense	GGGATAACGCAGGAAAGAACAT

	Sense	CAGACGTGAAACCCAACATACC	1032

	Anti-sense	Taggaacaggcggcgacga ATACAA CCCAATAGCAGCCAGTCCCT

	Sense	taggaacaggcggcgacga ATACAA TCTGCTGTAGTGAGTGGGTTGC	1630

	Anti-sense	GCCGATTGTCTGTTGTGCC

	UT probe	FAM TCGTCGCCGCCTGTTCCTA TAMRA

AUDP probeb	Sense	taggaacaggcggcgacgagcgtgggacataAAACTCCATCCGCTTGCCCTCATC	195

	Anti-sense	TGCCAAAGGGTTCGTGTAG

	Sense	taggaacaggcggcgacgagcgtgggacataAAACTCCATCCGCTTGCCCTCATC	546

	Anti-sense	GGGATAACGCAGGAAAGAACAT

	Sense	CAGACGTGAAACCCAACATACC	1032

	Anti-sense	taggaacaggcggcgacgagcgtgggacataAAACTCCCCAATAGCAGCCAGTCCCT

	Sense	taggaacaggcggcgacgagcgtgggacataAAACCTCTCTGCTGTAGTGAGTGGGTTGC	1630

	Anti-sense	GCCGATTGTCTGTTGTGCC

	FP	FAM TAGGAACAGGCGGCGACGAGCGTGGGACATA

	QP	AGTCGTCGCCGCCTGTTCCTA Dabcyl


Variables	Univariate analysis

HR	95% CI	P

Age (< 65 vs. ≥65)	1.47	0.68–3.17	NS

Gender (female vs. male)	0.74	0.29–1.84	NS

Stage (I vs. II vs. III)	1.64	1.00–2.69	0.049

Histology (adeno vs. other)	1.50	0.69–3.27	NS

Lymph node status (negative vs. positive)	2.09	0.95–4.60	NS

pT status (pT1a-2b vs. pT3–4)	2.65	1.25–5.62	0.011

Differentiation (poor vs. well-moderate)	0.80	0.37–1.75	NS

Smoking (smokers vs. nonsmokers)	0.48	0.18–1.23	NS

COPD (present vs. absent)	1.17	0.54–2.55	NS

M1 macrophages in islets (high vs. low)	2.83	1.20–6.68	0.017

M1 macrophages in stroma (high vs. low)	1.91	0.86–4.25	NS

Total M1 macrophages (high vs. low)	1.43	0.63–3.21	NS

M2 macrophages in islets (high vs. low)	1.43	0.66–1.43	NS

M2 macrophages in stroma (high vs. low)	1.00	0.73–1.37	NS

Total M2 macrophages (high vs. low)	0.31	0.13–0.75	0.009

IL-10	0.74	0.35–1.55	NS

TNF-α	1.16	0.55–2.45	NS

IFN-γ	0.67	0.31–1.43	NS


Characteristics (Total n = 126)

Maternal

Age, year	32.8 ± 5.0

Ethnicity

European	104 (83%)

Maori	8 (6%)

Pacific	1 (1%)

Other	13 (10%)

Skin color 2

Very light	67 (53%)

Light	51 (41%)

Intermediate	5 (4%)

Dark	3 (2%)

Primiparous	37 (29%)

Tertiary education 3	90 (71%)

Pre-pregnancy BMI, kg/m2 Primiparous	25.0 ± 6.2

Smoker	9 (7%)

Antenatal vitamin D supplement use 4	35 (28%)

Supplement intake IU/day 4

Consumers only	339 ± 269

Infant

Gestation, week	39.3 ± 1.1

Gender, male	61 (48%)

Birth weight, g	3506 ± 495

Birth Season

Spring	30 (24%)

Summer	28 (22%)

Autumn	28 (22%)

Winter	40 (32%)

Skin color 2

Very light	2 (2%)

Light	64 (50%)

Intermediate	51 (40%)

Dark	9 (7%)

Exclusive breast feeding 5	90 (71%)

Breastfeeding at week 20	110 (87%)

Infant vitamin D intake, 6 IU/day

Consumers only	96 ± 146


Primer	Sequence (5' - 3')	Product size	Position in coding sequence	Reference

erm(A)-F	CCCGAAAAATACGCAAAATTTCAT	590	15-38	[23]

erm(A)-R	CCCTGTTTACCCATTTATAAACG		604-582

erm(B)-F	TGGTATTCCAAATGCGTAATG	745	203-183

erm(B)-R	CTGTGGTATGGCGGGTAAGT		541-522

mef(A)-F*	CAATATGGGCAGGGCAAG	317	38-55

mef(A)-R*	AAGCTGTTCCAATGCTACGG		352-333

tet(M)-F	GTGGACAAAGGTACAACGAG	406	106-125

tet(M)-R	CGGTAAAGTTCGTCACACAC		511-492

tet(O)- F	AACTTAGGCATTCTGGCTCAC	515	13-43

tet(O)- R	TCCCACTGTTCCATATCGTCA		527-507

tet(K)-F	GATCAATTGTAGCTTTAGGTGAAGG	155	344-368

tet(K)-R	TTTTGTTGATTTACCAGGTACCATT		498-474

tet(L)-F	TGGTGGAATGATAGCCCATT	229	384-403

tet(L)-R	CAGGAATGACAGCACGCTAA		612-593

16S-rDNA-F	GAGTACGACCGCAAGGTTGA	100	886-905

16S-rDNA -R	CTGGTAAGGTTCTTCGCGTTG		985-964

ss-Tn916-1	GCCATGACCTATCTTATA	476	16083-16100	[24]

ss-Tn916-2	CTAGATTGCGTCCAA		16559-16545

tet(32)For	GAACCAGATGCTGCTCTT	620	619-637	[28]

Tet(32)Rev	CATAGCCACGCCCACATGAT		1239-1220

SScps2J-F	CAAACGCAAGGAATTACGGTATC	236	209-231	[29,30]

SScps2J-R	CATTTCCTAAGTCTCGCACC		445-426

tet(L)Ng-F	TCGTTAGCGTGCTGTCATTC	698	680-700	[31]

tet(L)-R-pDG364	CTTAGAAATCCCTTTGAGAAT		1378-1358	This study

tet(W)- F	TTGGAATTCTTGCCCATGTAGACGC	1872	18-42	This study

tet(W)- R	TTGTCCAGGCGGTTGTTTGGAC		1889-1868

tet(W)-F-HN	GGTGCAGTTGGAGGTTGTTT	410	1179-1198

tet(W)-R-HN	CCTTCAATGCCTGTTCCAAT		1569-1588

tet(O)-F-pDG364	ATGAAAATAATTAACTTAGG	1920	1-19

tet(O)-R-pDG364	TTAAGCTAACTTGTGGAACA		1920-1901

ss-tet(M)-whole-F	ACAGACAAAGAACTATCCTTAATG	2500	419-396

ss-tet(M)-whole-R	GTACCCAGTTTAAGAATACCTTTATC		161-136

Additional primers used for sequencing

tet(O)-2-F	TTCAAGACGCCTCCCTGTTC		679-698	This study

tet(O)-2-R	ATTTGGCGGGACTTCTATGTGG		1318-1296

ss-tet(M)-Fseq1	GTTAAATCACTACGATAT		1763-1745

ss-tet(M)-Rseq1	ATAGTGTTCTTGGAGATA		906-929

ss-tet(M)-Fseq2	GTATAATTTCATGTGTCG		1162-1144

ss-tet(M)-Rseq2	AGATGGCGTACAAGCACA		305-323

ss-PAI-P8-tet(M)-R	GCCCTTTTGGGTTTTTGAAT		-33- -14

ss-PAItetM-P9over F	GGGAATCCCCATTTTCCTAA		366-347


Initial Experiment Results	Enhanced Results

Total Length Ratio	RMSE (m)	Total Length Ratio	RMSE (m)

0.94	3.2	0.96	0.93


	AIM HI	CPRT

Initial didactic training—lecture material, video examples, case illustrations, and hands-on practice with coaching and discussion	12 h (over 2 days)	8 h

Ongoing consultation/coaching—occurs while provider delivers intervention to target child and includes video-based feedback1	11 1-h sessions over 6 months (9 group, 2 indiv.)	4 1-h group sessions and 6 individual coaching sessions over 5 months

Total length of training	22 h/6 months	18 h/6 months


Compound	Description	Applications	Remarks

In111-Capromab pendetide (ProstaScint)	A conjugation between the murine antibody 7E11.C5.3 and 111Inin the source of 111InCl3 by the action of the GYK-DTPA as a chelating agent.	Indicated for use in immunoscintigraphy, proven prostate carcinoma and patients who have undergone a prostatectomy and have rising prostate specific antigen (PSA) values and equivocal nonevidenced metastasis.	It is not indicated with patients with a high clinical suspicion of occult metastatic disease or for screening of prostate carcinoma.

In111-Satumomab pendetide (OncoScint)	It contains the murine MAb B72.3 which is directed to tumor-associated glycoprotein. It is labeled with 111InCl3 by conjugation with the chelating agent, GYK-DTPA.HCl.	Used for the detection of colorectal and ovarian cancers [35].	After an incubation time of 30 min, the labeled mixture is suitable for use in the first 8 hours.

In111-Imciromab pentetate (MyoScint)	An antibody produced against myosin in the cell culture, and therefore binds to the heavy chain of myosin after in vivo administration.	Detection of myocardial infarction.	Contains the Fab fragment of a murine monoclonal antibody that is covalently bound to DTPA giving 111In -Imciromab pentetate.

In-111 and Y90-ibritumomab tiuxetan (Zevalin)	Zevalin consists of a murine monoclonal anti-CD20 antibody covalently conjugated to the metal chelator DTPA, which forms a stable complex with 111Infor imaging and with 90Y for therapy.	90Y-ibritumomab tiuxetan is used for the treatment of some forms of B cell non-Hodgkin's lymphoma, a myeloproliferative disorder of the lymphatic system while its 111Inderivative is used to scan the predicted distribution of a therapeutic dosage of 90Y-ibritumomab in the body [36].	The antibody binds to the CD20 antigen found on the surface of normal and malignant B cells (but not B cell precursors) allowing radiation from the attached isotope (Yetrium-90) and the cytotoxicity induced by the antibody serve to eliminate B cells from the body allowing a new population of healthy B cells to develop from lymphoid stem cells [37].

Rituximab	An earlier version of anti-CD20 antibody and has also been approved under the brand name Rituxan for the treatment of non-Hodgkin's lymphoma (NHL).	It was approved for the treatment of patients with relapsed or refractory, lowgrade or follicular Bcell NHL, including patients with rituximab refractory follicular NHL.	In September 2009, ibritumomab received approval from the FDA for an expanded label for the treatment of patients with previously untreated follicular NHL, who achieve a partial or complete response to first-line chemotherapy.


Questions	Sub-questions

1. What is the first thing that comes to mind when you hear the phrase “oral health”?	a. aWhat does “good oral health” mean to you?i. bWhen you think of your child, would you say that he or she has “good oral health”?ii. bHow would you describe a child who has good oral health?iii. bThink about your child’s friends, how would you describe those that have good oral health?

2. What comes to mind when you hear the phrase “poor oral health”?	a. aWhen you think of your child, what could be thought of as poor oral health?i. bWhat could be thought as the worst thing for poor oral health?ii. bHow would you describe a child with poor oral health?b. aHow much of a problem is this among children in your family?i. bHow common is it among children in other families who live in this community? Among your friends?ii. bHow concerned are you about your son or daughter developing dental problems (dental decay)?

3. As parents, how do you help your child have healthy teeth?	a. aWhat do you think parents can do (or you as a parent can do) to prevent dental problems in kids (your kids)?b. aAs a parent, what do you think are the most important ways to help a child have good oral health?c. bWhat activities can you do to improve your child’s oral health?d. cWhat about diet and oral health?e. cWhat about flouride and oral health?f. cWhat about the experiences of your other children?

4. Tell me whether you think you can control your child’s oral health?	a. bAre there oral health problems that you feel you can control?i. cWhat would they be?ii. cWhat steps can you take to control the problem?iii. cYourself?iv. cWhat about other people? Can they do anything to control the problem?b. bWhen you can control an oral health problem, how does you child respond?c. bWhen you dealt with an oral health problem, how successful were you?d. cSo, you could not control a problem, then what did you do?i. bWhat was your child’s response?ii. bWhen you think about it now, does the problem still exist?

5. Other than your family and those who provide care, is there anyone else that you think should or could have an important role in your child’s oral health?	a. bWhy? What do you think they can do to help?i. cWhat about role models in entertainment?ii. cWhat about advertising and media messages?iii. cWhat about public policies?iv. cWhat about insurance?

6. What concerns do you have about your child’s future oral health?	a. bAs your child grows older, what oral health problems can affect him/her?i. cHow can poor oral health affect a child’s social and psychological well-being?ii. cHow can it affect a person’s chances of economic success?iii. cHow can it affect one’s general health over a lifetime?

7. Tell me whether you think you can control your child’s oral health?	a. bAre there oral health problems that you feel you can control?i. cWhat would they be?ii. cWhat steps can you take to control the problem?iii. cYourself?iv. cWhat about other people? Can they do anything to control the problem?b. bWhen you can control an oral health problem, how does you child respond?c. bWhen you can dealt an oral health problem, how successful were you?d. cSo, you could not control a problem, then what did you do?i. bWhat was your child’s response?ii. bWhen you think about it now, does the problem still exist?

8. Other than your family and those who provide care, is there anyone else that you think should or could have an important role in your child’s oral health?	a. bWhy? What do you think they can do to help?i. cWhat about role models in entertainment?ii. cWhat about advertising and media messages?iii. cWhat about public policies?iv. cWhat about insurance?

9. What concerns do you have about your child’s future oral health?	a. bAs your child grows older, what oral health problems can affect him/her?


Dependent variable	Explanatory variable	Beta	Chi‐square	p value	OR (95% confidence interval [CI])

	Female gender	1.13	5.18	.023	3.08 (95% CI [1.17, 8.11])

MMP‐13 saliva

	CAL	1.27	4.35	.037	3.57 (95% CI [1.08, 11.82])


Patient code	Age (years)	Sex	Clinical form	Location of lesion/Code

 	Cutaneous	Mucosal

1	52	M	MCL	Arm/1MCL-C	Oral / 1MCL-O

2	48	M	MCL	Nostril/2MCL-C	Oral/2MCL-O

3	25	M	MCL	Arm/3MCL-C	Nasal/3MCL-N

4	54	M	MCL	ND	Oral/4MCL-O

5	47	M	MCL	Arm/5MCL-C	Nasal/5MCL-N

Oral/5MCL-O

6	16	M	MCL	ND	Nasal/6MCL-N

7	50	M	MCL	Face/7MCL-C	Nasal/7MCL-N

8	29	M	MCL	Trunk/8LMC-C	Nasal/8MCL-N

9	55	M	MCL	ND	Oral/9MCL-O

10	42	M	MCL	ND	Nasal/10MCL-N

11	52	F	MCL	Arm/11MCL-C	Nasal/11MCL-N

12	25	M	MCL	Trunk/12MCL-C	Oral/12MCL-O

13	52	F	MCL	ND	Oral/13MCL-O

14	54	M	MCL	Upper lip/14MCL-C	Nasal/14MCL-N

15	69	M	MCL	ND	Nasal/15MCL-N

16	65	M	MCL	ND	Oral/16MCL-O

17	63	F	ML	A	Nasal/17ML-N

18	53	M	ML	A	Nasal/18ML-N

19	66	F	ML	A	Nasal/19ML-N

20	71	M	ML	A	Nasal/20ML-N

21	12	M	ML	A	Nasal/21ML-N

22*	49	F	ML	A	Nasal/22ML-N

23*	69	M	ML	A	Nasal/23ML-N

24*	60	M	ML	A	Nasal/24ML-N

25*	77	M	ML	A	Nasal/25ML-N

26*	72	M	ML	A	Nasal/26ML-N

27*	71	F	ML	A	Nasal/27ML-N

28*	39	M	ML	A	Nasal/28ML-N

29*	63	M	ML	A	Nasal/29ML-N

30*	44	F	ML	A	Nasal/30ML-N

31*	31	F	ML	A	Nasal/31ML-N1

Nasal/31ML-N2

32*	29	F	ML	A	Nasal/32ML-N1

Nasal/32ML-N2

33*	72	F	ML	A	Oral/33LM-O

34	49	M	DL	Arm/ 34DL-C1	Nasal/34DL-N

Trunk/34DL-C2

Leg/34DL-C3

35	41	M	DL	Nose/35DL-C	Nasal/35DL-N

 	 	 	 	 	Oral/35DL-O


Diagnosis	n	Percent

Small for gestational age	11	26.8

Disseminated intravascular coagulation	5	12.2

Respiratory distress syndrome	7	17.1

Sepsis	21	51.2

Anemia	2	4.9

Shock	5	12.2

Meconium aspiration syndrome	2	4.9

Hypoxic ischaemic encephalopathy	19	46.3

Acute kidney injury	7	17.1

Meningitis	2	4.9

Pulmonary hemorrhage	2	4.9

Hyperbilirubinemia	3	7.3

Necrotising enterocolitis	1	2.4

Persistent pulmonary hypertension	3	7.3

Intracranial haemorrhage	1	2.4

Congenital heart disease	6	14.6


Gastric ulcer model	Treatments (p.o.)	Dose (g/kg)	n	Ulcer index (mm)	Inhibition (%)

Ethanol-induced	Saline	–	8	14.37 ± 2.88	–

Ranitidine	0.04	8	11.27 ± 2.49∗∗	29.01

AIG	1.50	8	3.11 ± 0.47∗∗	80.43

AIG	0.75	8	4.46 ± 0.51∗∗	71.93

Pylorus ligature-induced	Saline	–	8	11.33 ± 3.78	–

Ranitidine	0.03	8	3.55 ± 0.63∗∗	68.68

AIG	1.0	8	2.76 ± 0.67∗∗	75.63

AIG	0.5	8	3.36 ± 0.78∗∗	70.33

Acetic acid-induced	Saline	–	8	10.26 ± 1.52	–

Ranitidine	0.03	8	3.89 ± 0.48∗∗	64.37

AIG	1.0	8	2.84 ± 0.53∗∗	72.49

AIG	0.5	8	3.38 ± 0.64∗∗	63.15


Most significant GO Biological Processes

GO Term	GO ID	Changed Genes	Total Genes in Class	P-Value	Fraction

Cholesterol biosynthesis	GO:0006695	12	20	7.04E-09	0.600

Nuclear mRNA splicing, via spliceosome	GO:0000398	29	110	9.77E-09	0.264

glycolysis	GO:0006096	14	39	1.16E-07	0.359

Protein biosynthesis	GO:0006412	38	247	8.00E-07	0.154

transport	GO:0006810	50	415	8.94E-07	0.120

Protein metabolism	GO:0019538	9	17	4.90E-06	0.529

Protein folding	GO:0006457	28	174	5.59E-06	0.161

Ribosome biogenesis	GO:0007046	6	14	3.22E-05	0.429

metabolism	GO:0008152	39	316	9.36E-05	0.123

tRNA processing	GO:0008033	8	33	5.32E-04	0.242

Regulation of the cyclin dependent protein kinase activity	GO:0000079	8	34	9.72E-04	0.235

Amino acid biosynthesis	GO:0008652	6	22	1.01E-03	0.273

Lipid metabolism	GO:0006629	24	193	1.02E-03	0.124

Regulation of progression through cell cycle	GO:0000074	27	200	1.14E-03	0.135

Cell cycle	GO:0007049	41	338	1.64E-03	0.121

Regulation of translational initiation	GO:0006446	7	22	1.88E-03	0.318

Most significant GO Molecular Function.

GO Term	GO ID	Changed Genes	Total Genes in Class	P-Value	Fraction

Nucleotide binding	GO:0000166	173	1405	6.92E-11	0.123

RNA binding	GO:0003723	78	389	4.22E-10	0.201

Oxidoreductase activity	GO:0016491	61	382	6.44E-10	0.160

ATP binding	GO:0005524	123	1116	1.20E-09	0.110

Unfolded protein binding	GO:0051082	28	143	2.68E-08	0.196

Protein binding	GO:0005515	220	2514	1.77E-07	0.088

Transferase activity	GO:0016740	101	958	1.86E-07	0.105

L-ascorbic acid binding	GO:0031418	6	11	1.65E-05	0.545

Lyase activity	GO:0016829	16	89	1.37E-04	0.180

binding	GO:0005488	47	399	2.37E-04	0.118

ATP-dependent RNA helicase activity	GO:0004004	7	18	4.61E-04	0.389

Isomerase activity	GO:0016853	15	90	5.54E-04	0.167

Ligase activity	GO:0016874	27	184	5.54E-04	0.147

Oxidoreductase activity	GO:0016702	6	18	6.72E-04	0.333

NAD binding	GO:0051287	8	24	7.05E-04	0.333

Catalytic activity	GO:0003824	27	192	7.40E-04	0.141

Transporter activity	GO:0005215	29	281	1.50E-03	0.103

Kinase activity	GO:0016301	22	163	1.65E-03	0.135

tRNA binding	GO:0000049	5	13	1.87E-03	0.385

Most significant GO Cellular Component

GO Term	GO ID	Changed genes	Total genes in class	P-value	Fraction

cytoplasm	GO:0005737	114	895	5.00E-10	0.127

nucleus	GO:0005634	281	2999	5.00E-10	0.094

mitochondrion	GO:0005739	70	528	1.01E-09	0.133

endoplasmic reticulum	GO:0005783	49	405	2.47E-06	0.121

mitochondrial inner membrane presequence translocase complex	GO:0005744	5	11	2.82E-04	0.455

soluble fraction	GO:0005625	24	194	3.22E-04	0.124

nucleolus	GO:0005730	12	59	1.09E-03	0.203


Feature	Control group (A)	Study group (B)

Number of pin-sites	268	368

AO tubular external fixation	43	41

Unilateral rail	0	2

Ilizarov device	6	8

Pin tract infection (patients)a	11 (22.5 %)	2 (4.1 %)

Pin tract infection (pin-sites)a	38 (14.2 %)	7 (1.9 %)


Trials	 	Intervention (n/N)	Control (n/N)	RR (95% CI)	P value

LWDHW plus enalapril versus enalapril	1	34/42	21/36	3.04 (1.10, 8.38)	0.03

Meta-analysis	1	34/42	21/36	3.04 (1.10, 8.38)	0.03


Isolate	Collection	Country	Yr of entry into collection	Sequencing technology	Reference

NCTC86_Dunne	NCTC	England	1920	Pacific Biosciences RS II, Illumina	2

NCTC86_Meric	NCTC	England	1920	Illumina MiSeq	4

NCTC86	NCTC	England	1920	Illumina MiSeq	This study

CIP61.11	Centre de Ressources Biologiques de l’Institut Pasteur	France	1961	Illumina MiSeq	This study

ATCC 4157	ATCC	United States	Unknown	Illumina MiSeq	This study

DSM301	DSMZ	Germany	1970	Illumina MiSeq	This study


Prevalence of elevated CRP (>10 mg/L)

Group		%	Univariate p-value	Multivariate OR *	Multivariate p-value**

Age	<50	14	0.49

	50–59	13

	60–69	13

	70+	18

Sex	Male	14	0.28

	Female	18

NIHSS	<7	13	0.015	(ref)	0.03

	7–13	25		2.15

	14+	21		1.89

OCSP classification	LACI	15	0.005

	TACI	26

	PACI	10

	POCI	19

Prior Cerebrovascular disease	No	16	0.97

	Yes	16

Pre-existing diabetes mellitus	No	14	0.01	(ref)	0.04

	Yes	27		1.96

Smoking habits	Never smoker	19	0.29

	Former smoker	14

	Current smoker	12

Time to hospital	<3 hours	13	0.20

	3–5.9 hours	20

	6–11.9 hours	10

	12–23.9 hours	18

	Woke up with Stroke (<24 hours)	17

	Other (<24 hours)	26


	Odds ratio	95% Confidentialinterval	P-value

Laboratory variables

Gamma-glutamyltranspeptidase, IU/L	1.009	0.953, 1.068	0.757

Cumulative dose of medications, mg

Leflunomide (53 patients)	1.000	1.000, 1.000	0.007

Prednisolone (89 patients)	1.000	1.000, 1.000	0.547


Clinical presentatiton	No. of patients	No. of episods	Time* (median/month)	Treatment

Cholangitis	5	9	19.5 (14–47)	Medical

 -without real stricture	3	3	28.3	Medical

 -with real stricture	2	6	15.5	Endoscopic (dilatation and/or stenting)

CBD stone	2	2	21.5 (16–27)	Endoscopic (stone extraction)

Total	7	11


Type of model or algorithm	Target product	Model-based target: knockout gene A or overexpress gene B	References

Dynamic flux balance analysis	Ethanol	Ethanol production pathway after 20 h	[163]

Genome-scale metabolic model	Prediction of growth rate with respect to photosynthetic quotient for ethanol and butanol production	Double reaction knock out of hydrolyase and dehydrogenase	[164]

In vivo carbon flux analysis	Homolanthionine	Deletion of methionine and cysteine biosynthesis repressor protein	[165]

Metabolic flux analysis	Hydrogen production	Deletion and addition of GAP1 and dehydrogenase, respectively	[166]

Metabolic flux analysis	Astaxanthin synthesis	–	[167]

Metabolic flux analysis	Fixed more CO2 and had a higher biomass yield	Alternate pathway for isoleucine synthesis (via citramalate synthase, CimA	[168]

Metabolic net fluxes	Hydrogen production	Disruption of hydrogenase and poly-β-hydroxybutyrate synthase	[169]


Severity of stress

n = 85	%

Severe	33

Moderate	27

Extreme	22

None/light	8

Catastrophic	6


	Input type	Database update	Functional Database support	Multiple organism support	Limitations for input genes	Statistics

GeneSCF v1.1	List of genes	Real-time	KEGG, GO, Reactome and NCG	Yes	No upper or lower limit	FE test a & FDR b

GeneSCF v1.0	List of genes	Manual (preparation needed)	KEGG, GO, Reactome and NCG	No (Homo sapiens)	No upper or lower limit	FE test & FDR

GOrilla	List of genes	Weekly auto-update	GO	Yes	No upper limit but has lower limit	FE test & FDR

DAVID 6.7	List of genes	Last known update 2010)	KEGG, GO, Reactome and Biocarta	Yes	Upper limit 3000 and no lower limit	FE test & FDR


Items	Cronbach’s alpha if items were deleted

Physical functioning	0.845

Mental health	0.847

Vitality	0.849

Role physical	0.858

General health	0.853

Bodily pain	0.857

Role emotional	0.862

Social functioning	0.856

Educational rescue policy	0.871

Orphan rescue policy	0.871

Employment rescue policy	0.871

Poverty rescue policy	0.871

Social security policy	0.872

Legal rescue policy	0.872


Crude extracta	Yieldb(g)	Yieldc(% of pollen sample)	Appearance

Corn bee pollen extracts

CMEb	35.29	8.40	Dark brown sticky solid

CDEb	2.40	0.57	Dark brown solid

CHEb	18.13	4.32	Yellow solid

Floral corn pollen extracts

CMEp	9.02	2.15	Dark brown solid

CDEp	4.82	1.15	Brown solid

CHEp	7.87	1.87	Dark green oil/wax


The Job stress Survey (JSS) Items	Lack of support leaders	Demanding job tasks	Time pressure	Lack of support co-workers

No participating in decisions	0.84	0.20	0.03	0.04

Lack recognition for good work	0.80	0.14	0.03	0.28

Poor or inadequate supervision	0.61	0.28	0.13	0.18

Difficult working with superior	0.81	0.16	0.17	0.19

Inadequate support by supervisor	0.57	0.24	0.19	0.25

Difficulty getting along with supervisor	0.79	0.01	0.19	0.22

Working overtime	0.16	0.56	0.05	0.12

Critical on the spot decisions	0.20	0.73	0.16	0.10

Assigned increased responsibility	0.32	0.62	0.19	0.11

Assignment of new duties	0.11	0.75	0.24	0.03

Perform duties not in job description	0.04	0.67	0.33	0.16

Frequent interruptions	0.26	0.28	0.53	0.42

Frequent change simple to demanding tasks	0.06	0.44	0.61	0.16

Excessive paperwork	0.09	0.19	0.79	0.12

Meeting deadline	0.06	0.20	0.82	0.14

Insufficient personal time	0.24	0.12	0.66	0.04

Fellow workers not doing job	0.26	0.21	0.01	0.77

Covering work for others	0.31	0.18	0.27	0.56

Poorly motivated co-workers	0.26	0.05	0.24	0.79

Sums of squared loadings	3.9	2.9	2.9	2.1

% variance	20.4	15.3	15.1	11.0

The Norwegian Ambulance Stress Survey (NASS)	Non-Emergency tasks	Serious operational tasks	Physical demands

Hide feelings towards patients and relatives		0.83	0.13	0.16

Not being able to express own opinion to patients or relatives		0.82	0.08	0.19

Medical responsibility in the vehicle		0.63	0.34	0.17

Negative attitude from relatives about the job you are doing		0.60	0.29	0.07

The cumulative effect of frequently driving chronically ill patients		0.54	0.25	0.24

Take care of seriously injured and dying patients		0.52	0.57	0.15

Uncertainty about what you will meet on the scene of accident		0.51	0.60	0.11

Incident with seriously injured friend or people you know		0.19	0.73	0.12

Incident with seriously injured children		0.09	0.83	0.15

Deal with acting-out and threatening patients		0.18	0.70	0.22

Driving under difficult conditions		0.34	0.62	0.18

Heavy lifting		0.22	0.12	0.91

Carrying out the work under difficult conditions		0.20	0.22	0.91

Working in bent or twisted positions		0.18	0.25	0.87

Sums of squared loadings		3.3	3.2	2.7

% variance		23.3	22.7	19.3


 	Men	Women	p-value*

Number of patients	289	284

Number of deaths	41	21

Number of admissions	1924	3139

Total time of follow-up (person-years)	3420	3204

Follow-up time in years (mean, SD)	11.8 (7.4)	11.3 (7.4)	0.37

Age at first admission in years (mean, SD)	31.2 (9.9)	30.2(12.2)	0.28

Total number of days admitted (median, 1 and 3 quartile)	70 (18.0, 214.5)	111 (25.3, 293.0)	0.013

Number of admissions (median, 1 and 3 quartile)	3 (1,8)	4 (2,1)	0.004

% with personality disorder as only diagnosis (N)	30.1 (89)	23.9 (68)	0.07


PBMS	DMT status

Domains	pre-test	RCT	pos-	p-value

 	Sub-domains	without /with	without /with	sible range	pre	RCT

1: Attitude	2.1 / 4.6	2.4 / 4.1	0-9	<.01	<.01

 	a: expectations regarding outcomes	1.4 / 2.0	1.5 / 1.9	0-3	<.01	<.01

 	b: values of expected outcomes	1.4 / 2.2	1.5 / 2.1	0-3	<.01	<.01

2: Social norm	1.2 / 1.8	1.5 / 2.4	0-9	.23	<.01

 	a: assumed attitudes of important others	1.2 / 2.0	1.5 / 2.2	0-3	<.01	<.01

 	b: motivation to comply with these norms	1.0 / .9	1.0 / 1.1	0-3	<.01	.34

3: Control beliefs	1.6 / 4.7	2.1 / 4.1	0-9	<.01	<.01

 	a: assumed facilitators or barriers	1.0 / 2.1	1.2 / 1.9	0-3	<.01	<.01

 	b: perceived power of these factors	1.4 / 2.2	1.5 / 2.0	0-3	<.01	<.01

Intention estimate	4.8 / 11.1	6.0 / 10.1	0-27	<.01	<.01


Characteristics	Yes (%)	No (%)

Ever received an introduction into work place ergonomics	24 (14.7%)	136 (83.4%)

Ever experienced work-related musculoskeletal problems	123 (75.5%)	40 (24.5%)

Musculoskeletal problems in the last four weeks (n=123)	69 (56.1%)	53 (43.1%)

Signed off due musculoskeletal problems last year (n=123)	11 (8.9%)	112 (91.1%)

Doing regularly short breaks for stretching exercises	36 (22.1%)	124 (76.1%)

Any known ametropia	145 (89.0%)	17 (10.4%)

Aggravation of ametropia since working in pathology (n=145)	82 (56.6%)	58 (40.0%)

Eye fatigue symptoms in the last month	90 (55.2%)	68 (41.7%)

Ever experienced occupational injuries in pathology	135 (82.8%)	28 (17.2%)

Experienced such injuries in the last year (n=135)	37 (27.4%)	95 (70.4%)

Remaining permanent damages from such injuries (n=135)	5 (3.7%)	127 (94.1%)

Ever experienced intolerance reactions against formalin	41 (25.2%)	118 (72.4%)

Any known allergy	55 (33.7%)	105 (64.4%)

Since working in pathology ever diseased with...

Tuberculosis	2 (1.2%)	153 (93.9%)

Positive tuberculin test only	31 (19.0%)	119 (73.0%)

Hepatitis B	1 (0.6%)	154 (94.5%)

Hepatitis C	0 (0.0%)	155 (95.1%)

HIV	0 (0.0%)	154 (94.5%)

Burnout	14 (8.6%)	141 (86.5%)

Depression	11 (6.7%)	144 (88.3%)

Hypertension	11 (6.7%)	144 (88.3%)

Diabetes mellitus type II	3 (1.8%)	152 (93.2%)

Malignancies	3 (1.8%)	149 (91.4%)

Sufficient hepatitis B immunisation	153 (93.9%)	9 (5.5%)

Ever received BCG (tuberculosis) immunisation	128 (78.5%)	31 (19.0%)

Smoking	17 (10.4%)	145 (89.0%)

Cut-resistant gloves available at workplace	99 (60.7%)	60 (36.8%)

Regular personal use of cut-resistant gloves at dissections/autopsies	39 (23.9%)	108 (66.3%)

Extraction of air in the dissection room considered sufficient	94 (57.7%)	66 (40.5%)


Method Label	Method Description	Library used within R statistical software	Number of iterations

CC	Complete case analysis: Analyses only cases with complete data for all covariates		-

SI	Single imputation performed using PMM	'pmm' function in 'mice'	20

MI-NORM	Multiple imputation (MI) using data augmentation approach [31] with a multivariate normal assumption for all variables	'norm' [41]	100

MI-MIX	MI using data augmentation approach using a general location model	'mix' [42]	100

MI-MIX-no truncating	MI using data augmentation approach using a general location model, but imputed values are not truncated to within plausible range	'mix' [42]	100

MI-MICE	MI using regression switching imputation [9]. Linear model are used for continuous covariates and logistic model for binary covariates and dummy variables for categorical covariates	'mice' [43]	20

MI-MICE-PMM	MI using MICE with PMM	'pmm' function in 'mice' [43]	20

MI-MICE-PMM-no transformation	MI using MICE with PMM without transforming the incomplete covariates	'pmm' function in 'mice' [43]	20

MI-Aregimpute	MI using flexible additive imputation models [20] with PMM	'aregImpute' function in 'Hmisc' [44]	1


Case No.	Age(yrs)	FIGO score	AP	Interval time (mons)	Pretreatment serum β-hCG level	Site of metastases	Chemotherapy	Cause of death

1	53	15	Abortion	180	99000.0	Lung/brain/kidney	Not done	Brain hemorrhage, respiratory failure

2	30	21	Abortion	10	906720.0	Lung/brain/liver/kidney	Not done	Septic shock

3	31	8	Mole	32	80.0	Lung/brain	5-FU*1d	Brain herniation

4	25	12	Mole	27	57380.0	Lung/brain	EMA*1	Brain herniation

5	32	12	Term	6	200000.0	Lung/brain/kidney	FAEV*2d	Respiratory failure, cardiac arrest

6	36	13	Mole	56	9306.0	Lung/brain/bladder	FAEV*1d	Multiple organ failure

7	26	15	Term	3	60436.5	Lung/brain	FAEV*3d	Brain stem hemorrhage

8a	33	17	Mole	36	2400.0	Lung/brain	FAEV*4d	Brain herniation


Clinical features

Number of patients	13

Women/men	7/6

Age (years), mean ± SD	52.02 ± 19.01

Triggering factor

 AOSD flare, number (%)	13 (100)

 Lymphoma, number (%)	0

 Infectious disease, number (%)	0

Laboratory features

 WBC (103/mL), mean ± SD	3.28 ± 1.36

 RBC (103/mL), mean ± SD	3.31 ± 0.69

 HB (gr/dL), mean ± SD	9.19 ± 2.05

 PLT (103/mL), mean ± SD	55.52 ± 46.54

 Serum Ferritin (ng/mL), mean ± SD	4362.15 ± 7569.70

 ESR (mm/hour), mean ± SD	71.23 ± 30.19

 CRP (mg/L), mean ± SD	74.76 ± 46.92

 Triglycerides (mg/dL), mean ± SD	183.12 ± 69.33

 ASAT (IU/L), mean ± SD	74.59 ± 41.89

 ALAT (IU/L), mean ± SD	129.98 ± 91.21

Treatments

 High dosage steroid pulses, number (%)	13 (100)

 Immunosuppressive drugs, number (%)	7 (53.84)

 Cyclosporine A, number (%)	5 (38.46)

 Methotrexate, number (%)	2 (15.38)

 Etoposide	0

 Biologic drugs	2 (15.38)

Deaths, number (%)	10 (76.92)

Number of relapses in MAS-survivors patients, mean ± SD	2.66 ± 1.69


Domain	Scale/items	Parent-report	Self-report

Sexual socialization	Friendship skills of child	5 items	5 items

	Social acceptance by peers	3 items	6 items

	Romantic ability of child	-	3 items

	Openness about intimacy	4 items	3 items

	Adequate dealing with boundaries	8 items	-

Sexual selfhood	Bodily perception	3 items	6 items

	Self-esteem	-	12 items

	Perceived social competence	-	12 items

	Sexual knowledge of the child according to parent	9 items	-

Sexual behavior	Separate items on age or context appropriate behaviors, intimate experiences including age of onset and sexual orientation	33 items	41 items


Species	Ratio Gavage/i.p.	Mean Ratio

G. pacificus	>800, >1000, >340	>713

G. honu	395, 500	448

G. australes	54, 108, 80, 94, 126, 79, 100	92

G. cheloniae	369, 170	270

G. carpenteri	>16	-

F. paulensis	>63	-

G. polynesiensis	1.7	-


Up-regulated miRNAs	Down-regulated miRNAs

mmu-miR-2137	mmu-miR-1199-3p

mmu-miR-5131	mmu-miR-218-5p

mmu-miR-680	mmu-miR-7a-5p

mmu-miR-5130	mmu-miR-374c-5p

mmu-miR-144	mmu-miR-449c-5p

mmu-miR-486	mmu-miR-450a-2-3p

mmu-miR-711	mmu-miR-696

mmu-miR-449a

mmu-miR-193

mmu-miR-34c-5p

mmu-miR-2861

mmu-miR-211-3p

mmu-miR-763

mmu-miR-128-2-5p

mmu-miR-542-5p

mmu-miR-3473

mmu-miR-511-3p

mmu-miR-34c-5p

mmu-miR-143-5p

mmu-miR-5115


Data source	Exhaustive search	KL1LR

		# of GO terms (# in union)	AUC	# of GO terms (# in union)	AUC	NCG

Protein-protein interactions	OPHID	192		0.82	201		0.89	83

Protein domain	Interpro	522	(697)	0.87	408	(518)	0.89	266

	Pfam	600		0.86	311		0.89	210

Phenotype	MGI	213		0.87	346		0.90	129

Phylogenetic profile	BioMart	33	(95)	0.83	59	(166)	0.88	4

	Inparanoid	70		0.84	124		0.88	22

Disease	OMIM	41		0.85	32		0.88	3

Gene expression	Zhang et al.	28		0.81	147		0.90	10

	Su et al.	21	(55)	0.82	158	(309)	0.89	8

	Sage et al.	16		0.83	113		0.90	7


 Criterion	Score

No	Yes

Tortuous vessels	0	1

Large vessels	0	1

Leakage	0	1

Defective flux	0	1


BMI classes	Mean	95% C.I	N

Normal Weight	21.7	20.8–22.6	84

Overweight	19.1	18.3–19.8	123

Obese Class I	18.2	17.3–19.1	77

Obese Class II	17.4	16.3–18.7	37

Obese Class III	17.0	15.9–18.1	59


Characteristics	n	P-valuea,b	Hazard ratioa,b	95% CIa,b

Age

< 20	18 (82%)

> 20	4 (18%)	0.06	0.16	2.3 × 10−10–1.3

Median	13

Gender

Male	15 (68%)	0.05	0.20	1.9 × 10−10–1.2

Female	7 (32%)

Tumor volume (cm3)

Median	1,476	0.40	0.48	0.04–3.0

Range	85–10,590

Tumor surface (cm2)

Median	19.2	0.43	0.50	0.02–3.3

Range	3.2–57.7

Pattern on MRI

Concentric	19 (86%)	0.72	0.47	0.10–2.1

Longitudinal	3 (14%)

Histologic response

Good	12 (54%)	–	–	–

Poor	10 (46%)	–	–	–

Pathologic subtype

Osteoblastic	10 (46%)	–	–	–

Chondroblastic	6 (27%)	–	–	–

Fibroblastic	4 (18%)	–	–	–

Other	2 (9%)	–	–	–

Location

Distal femur	22 (100%)	–	–	–

Metastatic disease

No	22 (100%)	–	–	–


Date	Advance	Applications

1670s	Microscope invented by Leeuwenhoek	Visualize bacteria, protozoa

1850s	Puerperal fever identified as infectious and interventions implemented by Semmelweis [23]	Hospital infection control motivated by growing understanding of microbial etiology

1864	Cholera transmission by water proven by Snow	Risk factor (mode of transmission) and prevention measure for specific infectious syndrome

1890s	Proof of parasitic origin (Grassi) and mosquito transmission (Ross) of malaria	Vector control

1890s	Identification of microbial etiologies for tuberculosis, anthrax, and so on; Koch’s postulates	Targeted diagnostics, therapeutics, and move from syndromic diagnosis to pathogen identification

1900-1930s	Discovery of filterable animal viruses [24]	Influenza etiology settled (previously thought bacterial) [25]

1910s-1950s	Phenotypic subspecies taxonomy: serotyping [26,27], phage typing [28]	Association of particular types with prognosis [27,29], drug resistance

1944	Discovery of DNA as the genetic material [30]	Basis for genotyping tools for molecular epidemiology

1970	Restriction enzymes [31]	Basis for restriction fragment length polymorphism approaches, including pulsed field gel electrophoresis

1975-1985	Sanger DNA sequencing [32], PCR [33]	Basis for variable number tandem repeat (VNTR) and multilocus sequence typing (MLST) approaches to characterize microbes and their genetic relatedness

2000s-now	High-throughput rapid sequencing technologies	Microbial genome sequencing


Conditions	Biological Process	FDRp-value	Molecular Function	FDRp-value

Control	response to abiotic or biotic stimulus	2.8e-19	transcription factor activity	3.4e-04

	response to stress	1.6e-13	other enzyme activity	2.1e-03

	other biological processes	7.7e-10	other molecular functions	4.5e-02

Cold	response to stress	4.9e-08	transcription factor activity	1.7e-07

	other biological processes	1.3e-07	receptor binding or activity	3.8e-03

	response to abiotic or biotic stimulus	8.1e-06	kinase activity	2.9e-02

	transcription	3.3e-04

	signal transduction	3.2e-03

Genotoxic	response to abiotic or biotic stimulus	2.9e-20	kinase activity	7.6e-06

	response to stress	3.8e-16	transcription factor activity	8.9e-04

	other biological processes	1.8e-11	transferase activity	1.7e-03

	signal transduction	7.3e-03	transporter activity	1.4e-02

Osmotic	response to stress	1.4e-16	transferase activity	7.0e-04

	response to abiotic or biotic stimulus	1.4e-14	kinase activity	1.4e-03

	other biological processes	1.3e-08	transcription factor activity	1.3e-02

	signal transduction	1.3e-02	other molecular functions	4.3e-02

Salt	response to abiotic or biotic stimulus	3.0e-12	structural molecule activity	1.1e-13

	response to stress	6.0e-07	transferase activity	2.3e-03

	other biological processes	3.3e-03	other enzyme activity	2.4e-02

UV-B	response to abiotic or biotic stimulus	3.1e-12	transferase activity	1.3e-02

	response to stress	2.3e-11	kinase activity	1.4e-02

	other biological processes	1.6e-08

Wounding	response to abiotic or biotic stimulus	1.4e-17	other enzyme activity	6.3e-06

	response to stress	1.0e-15	transferase activity	2.1e-03

	other biological processes	1.1e-10	transcription factor activity	2.1e-03

	other metabolic processes	4.7e-02	hydrolase activity	1.2e-02

			transporter activity	4.1e-02

Drought	response to abiotic or biotic stimulus	2.8e-19	structural molecule activity	7.9e-18

	response to stress	6.0e-19	transferase activity	6.7e-05

	other biological processes	6.4e-10	other enzyme activity	3.8e-04

	other metabolic processes	1.8e-02

Heat	other biological processes	7.0e-12	transferase activity	9.3e-04

	response to abiotic or biotic stimulus	7.7e-10	other enzyme activity	2.1e-03

	response to stress	3.4e-08	hydrolase activity	3.1e-02

	electron transport or energy pathways	9.5e-03

Oxidative	response to abiotic or biotic stimulus	7.3e-17	transcription factor activity	2.2e-03

	other biological processes	6.5e-14	other enzyme activity	5.7e-03

	response to stress	7.7e-10	kinase activity	1.4e-02

			transferase activity	1.6e-02


	Did not require ICU(n = 249)	Required ICU (severe)(n = 18)	Pb value

N (%)	N (%)

Any medical risk factor a	115 (46.2)	11 (61.1)	.22

Influenza B strain	47 (19.0)	7 (38.9)	.04

Iron‐deficient anaemia	21 (8.4)	5 (27.8)	.01

Food allergy	6 (2.4)	2 (11.1)	.09

Proportion less than 2 y of age 	150 (60.2)	14 (77.8)	.14

Antiviral prescribed	34 (13.7)	2 (11.8)	.82

Antibiotic prescribed	121 (48.8)	9 (52.9)	.74

Co‐infection identified	99 (39.8)	8 (47.1)	.55


Explanatory variable	Coefficient ± Standar Error	P

Body Fat at follow-up equation, kg

 Leisure time physical activity at follow-up, METs/wk	−0.215 ± 0.091	0.019

 Calorie Intake at follow-up, 100 kcal	0.328 ± 0.142	0.021

 Age at follow-up	0.115 ± 0.036	0.001

 Height at follow-up	0.520 ± 0.092	< 0.001

 Constant	28.399 ± 0.425	< 0.001

Leisure time physical activity at follow-up equation, METs/wk

 Body fat at follow-up, kg	1.059 ± 0.456	0.020

 Depression score at follow-up, CES-D*	−0.191 ± 0.095	0.045

 Age at follow-up	−0.025 ± 0.071	0.722

 Constant	−30.038 ± 12.750	0.018

Calorie Intake at follow-up equation, 100 kcal

 Body fat at follow-up, kg	−0.341 ± 0.183	0.063

 Depression score at follow-up, CES-D*	0.188 ± 0.048	< 0.001

 Age at follow-up	−0.067 ± 0.035	0.057

 Constant	9.630 ± 5.285	0.068

Error Covariances

 Calorie intake with physical activity	−26.882 ± 20.302	0.185


Brain regions	 	Voxels	X (MNI)	Y (MNI)	Z (MNI)	T value

High BrAC group < control

 Superior frontal gyrus	R	750	15	21	57	−4.6134

R	39	12	39	−24	−3.7952

 Inferior frontal gyrus	R 	37	54	21	18	−4.4388

 Hippocampal gyrus	R	39	18	−6	−33	−4.6794

 Inferior temporal gyrus	R	30	33	9	−45	−4.2946

High BrAC group > control

 Middle frontal gyrus	L	100	−27	45	3	4.7207

R	42	12	−21	60	6.4199

 Basal ganglia	L	468	−27	12	−3	5.7696

 Cerebellum 	R	114	9	48	−24	6.8909

 Internal capsule	R	39	9	0	6	3.9489


Gene	Acc. No	Primer sequence (5′ to 3′)

Pparg (mouse)	NM_001127330	F: GACCACTCGCATTCCTTT

 	 	R: CCACAGACTCGGCACTCA

Fabp4 (mouse)	NM_024406	F: AAATCACCGCAGACGACA

 	 	R: CACATTCCACCACCAGCT

Runx2 (mouse)	NM_001146038	F: ACTTCCTGTGCTCCGTGCTG

 	 	R: TCGTTGAACCTGGCTACTTGG

Osterix (mouse)	NM_130458	F: ACCAGGTCCAGGCAACAC

 	 	R: GCAAAGTCAGATGGGTAAGTAG

Tmem64 (mouse)	NM_181401	F: AGGAAGCGGCCTGAAGGT

 	 	R: GAAGGAAGAGCCACTGGGAT

β-actin (mouse)	NM_007393	F: CTGTCCCTGTATGCCTCTG

 	 	R: TGATGTCACGCACGATTT


	Girls	Boys

Goodness-of-fit statistics	1-factor model	2- factor model	1-factor model

χ2	8.13	4.41	4.44

df	5	4	5

p	.15	.35	.49

RMSEA	.028	.018	.00

CFI	.98	.99	1.00

TLI	.97	.98	1.02

r		.61


			First outbreak (October 2013)		Second outbreak (July 2014)

Water temperature: 23 °C	Water temperature: 26 °C

Cage	Date stocked	Age at stocking (months)	Average weight at first outbreak (g)	Cumulative mortality (%)	Average weight at second outbreak (g)	Cumulative mortality (%)

1	April 2012	2	323	4,82	336	4,86

2	April 2012	2	319	5,30	440	5,3

3	July 2012	5	292	4,76	441	4,76

4	April 2013	2	84	2,23	274	2,23


Brain region	BA	Cluster sizes	t-value	P value	Peak MNI coodinate

(voxels)	(Corr.)	X	Y	Z

R medial prefrontal cortex	8	12	6.02	<.05	9	27	57

R middle frontal gyrus	9	211	10.87	<.05	3	48	21

L middle temporal gyrus	21	14	−5.49	<.05	−66	−54	3

R superior temporal gyrus	38	12	−5.59	<.05	54	12	−18

L primary somatosensory cortex	2	19	−3.88	<.05	−60	−21	42

R inferior parietal lobule	40	10	−10.94	<.05	66	−36	21

L parahippocampal gyrus	―	11	−5.62	<.05	−9	−3	−21

R parahippocampal gyrus	35	29	9.51	<.05	30	−6	−21

L anterior cingulate cortex	32	12	−4.74	<.05	−6	21	39

R precuneus	7	14	4.70	<.05	18	−66	33

R insula	13	10	5.47	<.05	39	0	18

R cerebellar tonsil	―	13	5.30	<.05	9	−60	−48


Category	Treatment adherence barriers

Stigma related factors	▪ Fear of disclosure of child’s status to the teachers and family members by parents

▪ Segregation by teachers and other children

Lack of supportive environment at home	▪ Inadequate support from parents

➢ Parents move to farming areas without one to follow up on child’s treatment schedule

➢ Men do not provide enough treatment adherence support

➢ Extended family members do not provide support

Lack of supportive environment from school	▪ Teachers do not provide adequate support to children on ART

Health service delivery factors	▪ Lack of child friendly counseling services

▪ Inconvenient treatment schedule

▪ Longevity of treatment

Patient factor	▪ Forgetfulness

▪ Feeling better


	Factor

1

Me siento cansado y desanimado cuando me levanto por las mañanas	0.612

Mis músculos están tensos y doloridos	0.650

Tengo ataques de pánico	0.388

Rechino los dientes o aprieto la mandíbula	0.342

Tengo problemas de diarrea o estreñimiento	0.400

Necesito ayuda pare realizar mis actividades diarias	0.476

Soy sensible a la luz brillante	0.440

Me canso fácilmente cuando estoy físicamente activo	0.724

Siento dolor en todo mi cuerpo	0.582

Tengo dolores de cabeza	416

Tengo molestia en mi vejiga o sensación de quemazón al orinar	0.294

No duermo bien	0.504

Tengo dificultad para concentrarme	0.436

Tengo problemas en la piel como resequedad, picor o sarpullido	0.299

El estrés hace que mis síntomas físicos empeoren	0.587

Me siento triste o deprimido	0.621

Me siento con poca energía	0.718

Tengo tensión muscular en mi cuello y hombros	0.555

Tengo dolor en mi mandíbula	0.426

Algunos olores, como perfumes, me hacen sentir náuseas.	0.269

Tengo que orinar frecuentemente	0.276

Mis piernas se sienten incómodas e inquietas cuando intento dormir por la noche	0.476

Tengo dificultad para recordar cosas	0.482

Sufrí algún trauma cuando era niño (a)	0.120

Tengo dolor en mi zona pélvica	0.289


Patient Safety Culture Composite	Definition: The extent to which....	Number of Survey Items

1. Communication openness	Staff will freely speak up if they see something that may negatively affect patient care, and feel free to question those with more authority	3

2. Feedback & communication about error	Staff are informed about errors that happen, given feedback about changes put into place based on event reports, and discuss ways to prevent errors	3

3. Frequency of events reported	Mistakes of the following types are reported:1) mistakes caught and corrected before affecting the patient, 2) mistakes with no potential to harm the patient, and 3) mistakes that could harm the patient, but do not	3

4. Handoffs & transitions	Important patient care information is transferred across hospital units and during shift changes	4

5. Management support for patient safety	Hospital management provides a work climate that promotes patient safety and shows that patient safety is a top priority	3

6. Nonpunitive response to error	Staff feel that their mistakes are not held against them, and mistakes are not kept in their personnel file	3

7. Organizational learning--Continuous improvement	Mistakes have led to positive changes and changes are evaluated for their effectiveness	3

8. Overall perceptions of patient safety	Procedures and systems are good at preventing errors and there is a lack of patient safety problems	4

9. Staffing	There are enough staff to handle the workload and work hours are appropriate to provide the best care for patients	4

10. Supervisor/manager expectations and actions promoting safety	Supervisors/managers consider staff suggestions for improving patient safety, praise staff for following patient safety procedures, and do not overlook patient safety problems	4

11. Teamwork across units	Hospital units cooperate and coordinate with one another to provide the best care for patients	4

12. Teamwork within units	Staff support one another, treat each other with respect, and work together as a team	4


Oligonucleotide	Sequence

NUCKS F (forward)	5'-AATTCACAGGAAGATAGTGAGG-3'

NUCKS R (reverse)	5'-TCACTGTAG CCTTTAGTCTGGG-3'

GAPDH forward	5'-ATGGGGAAGGTGAAGGTCGGAGTC-3'

GAPDH reverse	5'-GAACATGGGGGCGTCAGCAGAG-3'

NUCKS Fq (forward, real-time PCR)	5'-TCTGATGATGCAGATGAAGATTA-3'

NUCKS Rq (reverse, real-time PCR)	5'-CTGCTGAGTGAGAATCATCC-3'

NUCKS FL probe	5'-TCTTGGTCTTCACATCTTTGTCTTCT-FL-3'

NUCKS LC probe	5'-LC640-AGTCCTCACTATCTTCCTGTGAATTCTTT-3'


Characteristics of the partner at the first sexual relation	Sex (%)

Women	Men

Type of relationship

Namorado (steady boyfriend/girlfriend)	86	45

Husband/wife/living together	4	1

Eventual partner	9	48

Prostitute	—	5

Was it also the partner's first sexual relation?

Yes	14	37

No	83	57

Do not know	3	6

Age difference between the interviewee and the partner

The partner is younger	2	10

Same age (±1 year)	24	52

The partner is older (2–4 years)	36	24

The partner is much older (5 years and more)	38	15

The partner was in school

Yes	50	76

No	50	24


Demographic	Number (%)

Gender

Male	64 (43.2)

Female	84 (56.8)

Marital status

Single	57 (38.5)

Married	44 (29.7)

Widowed	10 (6.8)

Divorced	36 (24.3)

Unknown	1 (0.7)

Educational level

None	6 (4.1)

Primary	45 (30.4)

Secondary	83 (56.1)

University/post graduate	13 (8.8)

Unknown	1 (0.7)

Diagnosis

Schizophrenia	53 (35.8)

Paranoid Schizophrenia	35 (23.6)

Delusional disorder	10 (6.8)

Bipolar affective disorder (BPAD)	15 (10.1)

Psychotic depression	23 (15.5)

Other (i.e. schizoaffective disorder; non-specified psychosis)	10 (6.8)

Unknown	2 (1.4)

Employment status

Unemployed	68 (45.9)

Employed	39 (26.3)

Homemaker	35 (23.6)

Retired/other	5 (3.4)

Unknown	1 (0.7)


Indices of clinical burden of Sickle Cell Disease	Children

n	%

Duration of care since diagnosis

≤ 6 months	22	9.8

> 6 months	203	90.2

Previous hospitalisation (range = 0–24)

No hospitalisation	16	7.1

Once	32	14.2

Twice	85	37.8

> twice	92	40.9

Previous blood transfusion (range = 0–10)

None	67	29.8

Once	53	23.6

Twice	70	31.1

> twice	35	15.6

Significant bone pain episodes

None	13	5.8

One	41	18.2

Twice	25	11.1

> twice	146	64.9


	(A) 176 drug products	(B) 45 drug products	(C) 162 drug products

Therapeutic group

 A—alimentary tract and metabolism	18	8	17

 B—blood and blood-forming organs	9	3	8

 C—cardiovascular system	20	3	20

 D—dermatologicals	6	3	5

 G—genitourinary system and sex hormones	13	1	13

 H—systemic hormonal preparations, excluding sex hormones and insulins	7	1	6

 J—anti-infectives for systemic use	25	5	23

 L—anti-neoplastic and immunomodulating agents	10	3	10

 M—musculoskeletal system	6	3	6

 N—nervous system	24	8	23

 P—anti-parasitic products, insecticides, and repellents	2	0	1

 R—respiratory system	15	4	10

 S—sensory organs	6	1	6

 V—various	15	2	14

Re-examination dates

 January 2009 to December 2009	45	6	42

 January 2010 to December 2010	44	13	42

 January 2011 to December 2011	30	9	27

 January 2012 to December 2012	21	5	20

 January 2013 to December 2013	19	8	16

 January 2014 to December 2014	17	4	15


Variables	Mean±SD

BMI (Kg/m2)	43.40 ± 20.20

Post-Load PG (mg/dL)	80.00±15.80

SBP (mmHg)	127.60 ± 26.70

DBP (mmHg)	80.00 ± 15.80

FPG (mg/dL)	93.40 ± 19.80

Waist Circumference (CM)	182.84 ± 101.10


Indication for surgery	Frequency	Percentage

Bleeding duodenal ulcers not responding to either medical or endoscopic treatment	5	26.3

Gastric malignancy	6	31.6

Gastrointestinal stroma tumour	8	42.1


Subfamily	Gene identification		Domain organisation	Amino acids

ABCB

 ABCB1	PFE1150w	PfMDR1	(MSD-NBD)2	1419

 ABCB2	PF14_0455	PfMDR2	MSD-NBD	1024

 ABCB3	PF11_0466		MSD-NBD	872

 ABCB4	PFC0125w		MSD-NBD	1365

 ABCB5	PF13_0218		MSD-NBD	925

 ABCB6	PF13_0271		MSD-NBD	1049

 ABCB7	PFL0495c		MSD-NBD	855

ABCC

 ABCC1	PFA0590w	PfMRP1	(MSD-NBD)2	1822

 ABCC2	PFL1410c	PfMRP2	(MSD-NBD)2	2108

ABCE

 ABCE1	MAL13 P1.344		(NBD)2	619

ABCF

 ABCF1	PF11_0225		(NBD)2	815

 ABCF2	pfGCN20PF08_0078		(NBD)2	1419

ABCG

 ABCG1	PF14_0244		NBD-MSD	660

ABCI

 ABCI1	PF14_0133		NBD	347

 ABCI2	PF14_0321		NBD	171

 ABCI3	PFC0875w		MSD-NBD-MSD	3133


Patient	Gene	Varianta	Patient cancer historyb

Discovered cancer gene mutations (163 disease-gene panel)c

BRCA1.60	CHEK2	c.573+1G>A	Breast-47, 49

BRCA1.61	ATM	p.Glu2290⁎	Unaffected-24

BRCA2.7	RAD50	c.3G>A	Breast-49

BRCA2.13	ATM	p.Glu1978⁎	Breast-28, 39, 55; Skin-49

BRCA2.65	CDKN2B	p.Glu35⁎	Melanoma-50

BRCA2.93	CHEK2	p.Gln20⁎	Breast-37, 61; Ovarian-56

Discovered cancer gene mutations (ClinVar)c

BRCA1.48	ERCC3	p.Arg109⁎	Breast-39; Skin-61, 66

BRCA1.73	DLEC1	c.2436-2A>G	Breast-32

BRCA1.74	FANCC	p.Arg548⁎	Breast-42, 53, 55


DPC*	Type	Pathological findings†

		Lung	Inguinal Lymph Nodes	Heart

14	I	Moderate focal/multifocal bronchointerstitial pneumonia (3/3)	Lymphadenopathy (3/3)	Mild multifocal perivascular lymphohistiocytic myocarditis (1/3)

	II	Moderate diffuse/multifocal bronchointerstitial pneumonia (2/3)	Lymphadenopathy (3/3)	Mild multifocal perivascular lymphohistiocytic myocarditis. (3/3)

	Control	No lesions (2/2)	No lesions (2/2)	No lesions (2/2)

21	I	Moderate diffuse interstitial pneumonia (2/2), moderate peribronchiolar and perivascular lymphohistiocytic cuffing (2/2)	Lymphadenopathy (2/2)	Mild multifocal perivascular lymphohistiocytic myocarditis (1/2)

	II	Mild to moderate diffuse interstitial pneumonia (2/2), severe peribronchiolar and perivascular lymphohistiocytic cuffing (1/2)	Lymphadenopathy (2/2)	Very mild multifocal perivascular lymphohistiocytic myocarditis (1/2)

	Control	No lesions (1/1)	No lesions (1/1)	No lesions (1/1)


 	Believes PPM has exposed him/her to hazardous chemicals	Felt he/she was coughing, breathless or wheezing due to something in the air	Believes the industry will affect children born in the future in the community	Believes the industry will expose him/her to hazards if it opens in the future	Worries about getting health problems in the future because of a polluted environment

OR	95% CI	OR	95% CI	OR	95% CI	OR	95% CI	OR	95% CI

Demographic	Distance from PPM	2.747*	1.199-6.295	1.039‡	0.560-1927	1.132‡	0.502-2.554

Presence of a child in the HH	34.769*	1.390-869.96

Respondent completed HS	3.105*	1.394-6.918	 	 	 	 	 	 	2.553*	1.086-6.004

Employment Status	 	 	 	 	0.434‡	0.188-1.004	0.383*	0.167-0.879	0.365*	0.150-0.886

HH health Indicators	Perception of health	0.527‡	0.239-1.162	0.479*	0.261-0.878	0.299*	0.135-0.660	0.237**	0.108-0.517	0.332*	0.149-0.738

Somebody in the HH has one of the conditions (heart, respiratory or skin disease)	1.788‡	0.755-4.237	1.980*	1.031-3.802	2.192‡	0.963-4.990	 	 	2.594*	1.096-6.143

Respiratory symptoms	Coughed phlegm daily for ≥ 2 months, 2 yrs in a row	 	 	2.907*	1.127-7.498

Had an attack of whistling or noisy sound in the chest when breathing	 	 	2.881*	1.402-5.920

Role of Industrial plant	Family depended on industry	 	 	 	 	2.287*	1.001-5.228	2.792*	1.234-6.319

Community benefited from industry	 	 	 	 	 	 	 	 	2.289*	0.997-5.257

Environmental awareness/knowledge	Ever actively looked for environmental health information	 	 	1.883*	1.002-3.537

Willing to participate in environmental campaigns	 	 	2.297‡	0.713-7.396	2.985*	1.031-8.645	 	 	3.127*	1.100-8.888

Main Information source	Friends/relatives	2.553*	1.198-5.438	 	 	0.411*	0.180-0.937	0.451*	0.207-0.981

Church/Community leaders	 	 	 	 	3.148*	1.303-7.602	2.368*	1.090-5.147	2.447*	1.089-5.499

Omnibus Tests of Model Coefficients	Model (Sig.)	<0.001	<0.001	<0.001	<0.001	<0.001

Correctly predicted observations on average	 	85.6%	79.7%	84.6%	86%	84.4%


Hemi	Region	ß	SE	p-value (uncorrected)	FDR-corrected p-value

R	Nucleus accumbens	−0.23	0.058	0.000077	0.0055

L	Inferior parietal cortex	−0.38	0.10	0.00014	0.0055

R	Superior parietal cortex	−0.42	0.12	0.00056	0.011

R	Caudate nucleus	−0.28	0.081	0.00064	0.011

L	Putamen	−0.24	0.071	0.00068	0.011

L	Caudate nucleus	−0.23	0.071	0.0011	0.014

R	Amygdala	−0.21	0.064	0.0012	0.014

L	Supramarginal gyrus	−0.26	0.098	0.0076	0.076

R	Supramarginal gyrus	−0.27	0.10	0.0090	0.076


	Sanger technology	454 FLX technology	Sanger + 454 FLX

Total number of reads	14,120	789,105	-

Average length of read (bases)	780	218	-

Total number of reads in the assembly	12,032	466,737	478,769

Total number of contigs	2,120	22,203	18,690

Total number of singlets	4,775	25,604	-

Number of unique sequences	6,895	47,807	-

Average/Largest contig size	995/3,560	1132/4,762	1180/4,762


		B2	HTK	Euro Collins

Osmolality (mosm/kg)		323	310	406

Ions (mmol/l)	Na+	22	15	10

	K+	150	9	115

	Mg++	10	4

	Cl-	10	50	15

	SO4-	85

Buffers (mmol/l)	PO4---	6

	HPO4--			43

	H2PO4-			15

	HCO3-			10

	Histidin		198

Osmotics (mmol/l)	Glucose			198

	Mannitol		30

	Saccharin	40

Colloids (mmol/l)	PEG	25


Primer name	Oligonucleotide	Product length	Product name

crdPG-1	GTACTCGAGATTGTCGGCAGTCCAG	607	crdP

crdPG-2	AGCTCCTCGCCCTTGCTCACCATGAAATCAACTCCTCTGT

GFP-1	ACAGAGGAGTTGATTTCATGGTGAGCAAGGGCGAGGAGCT	746	GFP

GFP-2	CGCGGATCCTTACTTGTACAGCTCGTCCATG		crdP

crdP-1	TCACCAACACCAACTCTGGA

crdP-2	CATGAAATCAACTCCTCTGT	607	crdP

crdP142-1	ATCGTCAGATGCCTATTTGT	537	crdP

crdP108-1	AAATTAGTTAATGCAAT	503	crdP

crdP98-1	TTAATGCAATTTTTACTATGTT	493	crdP

crdP53-1	CCATTTCAATACTGCGGGAGG	448	crdP

crdP13-1	AGGAGTTGATTTCATGCTGTT	408	crdP

crdP1-1	ATGCTGTTCCGCAATAAG	395	crdA

crdA395-2	TCGGTCCGCAGCAGCAAAG

q-crdA-1	CAAGGCATAAGCGAAGACATC	227	crdA

q-crdA-2	CTCCGTGTTTCAAGTGTGGTC

q-crdS-1	AACCTGACGATTGCGATTGGG	179	crdS

q-crdS-2	GTGTAGCACCAGAGCGTTTCG

q-crdC-1	GTTCGGTCAGGATGCTCAAC	248	crdC

q-crdC-2	GCCAAAGTTCGGAATCAATG

crdR-1	GCCAGATCTATGACCGAGAATAAGAAAAAGCCT	437	crdR

crdR-2	TTGAGCTCTTACTCGGCGTCGCCTTCG

NcrdR-1	ACACTCGAGATACACCCGGTCCCTACCAGCATT		crdR

NcrdR-2	TTTGAGCTCCTTGTCCTTCTTCAGAAGCGTGT	1302	crdR

q-crdR-1	TCGGAATGAGCCAGGAGAAGC	238	crdR

q-crdR-2	TCAGCCGAGGACAGAAAGTCG

crdRup-1	TCTGAGCTCTTCGGCGTTTCGGAATGGTTG	2533	CrdR

crdRdown-2	CAACACAAGCTTAACCGTCACCTGGCTCTTGGCA

crdRcheckGm-2	TTGGGCATACGGGAAGAAGT	558	Gm

crdRcheckGm-1	CGGCTGATGTTGGGAGTAGG	577

Rep-Kan-1	ACGCGTCGACCTTGCCAGCCCGTGGATAT	3266	Km

Rep-Kan-2	ACGCGTCGACTCTGTGATGGCTTCCATGTC

Gm-1	ATAGTTGTCGAGATATTCACTAGTCGTCAGGTGGCACTTTTCG	1302	Gm

Gm-2	CGCGGATCCGCTCTGCTGAAGCCAGTTAC

celAP1	ACCCGGTCTATCCCATGA

celAP-2	CATCCAGAAACTTTCCGT	441	celAP

relAP-1	CCAGATTTCTCAAGGGTC

RelAP-2	CATCATGCGATATTCCACA	443	relAP

crdRP-1	GCGGCGATCCTAAATGTGAC

crdRP-2	CATGCGGTCCTGACACTCG	466	crdRP

crdSP-1	TCGGTCGGCACATGGGTCAAT

crdSP-2	CATCGCCCTAACCTCGCAGT	446	crdSP


Preparation	Average finish line width (mm)

CCC 46	0.5

MCC 24	(0.5 + 1.2)/2 = 0.85

MCC 46	(0.5 + 0.8)/2 = 0.65

ACC 21	1


Peptide	COX-1	COX-2

be	ir	hb	be	ir	hb

GMD	−1.20	23	1	−39.87	21	3

GHE	−0.56	25	0	−42.15	26	5

YYV	—	—	—	—	—	—


TB CX-test	AFB staining (+)	AFB staining (−)	Totals

TB CX-test(+)	12	1*	13

TB CX-test(−)	0	83	83

Totals	12	84	96


Variables	Mean	95% CI of the mean	Statistics (P values)

IBS symptom score	1.57	0.10; 3.05	P = 0.04

Bacteroides	−0.01	−0.11; 0.08	ns (P = 0.77)

Faecalibacterium	−0.03	−0.18; 0.12	ns (P = 0.63)

Lachnospiraceae	0.05	−0.03; 0.13	ns (P = 0.18)

“Common” Simpson's D	−0.04	−0.15; 0.08	ns (P = 0.50)


Reason	No. of patients	% patients

Presence of any types of primary disease progression (n = 26)

Enlargement of tumor	14	47

Elevation of tumor marker	7	23

Carcinomatous pain	5	17

Obstructive jaundice	5	17

Duodenal hemorrhage	2	7

Absence of disease progression (n = 4)

Interstitial pneumonia	4	13


Antibodies	Manufacturer	Source	Reactivity	Dilution

CD34	Sigma	Mouse	Rat	1:100

5-HT	Immunostar	Rabbit	Rat	1:20,000

GFAP	Millipore	Rabbit	Rat	1:50

APC	Calbiochem	Mouse	Rat	1:200

NeuN	Immunostar	Rabbit	Rat	1:500


sTNF/TNFR1 signaling

sTNF is necessary for the induction of autoimmune diseases [160]

Association of TNF and TNFR1 polymorphisms with PD risk [14, 163]

Association of TNFR1 polymorphism with MS risk [164]

TNFR1 promotes neurodegeneration in retinal ischemia [165]

TNFR1 mediates development of pain-induced depressive behavior [166]

TNFR1 is essential for the development of MOG35–55 induced EAE [167–169]

Inhibition of TNFR1 signaling strongly ameliorates EAE development [169]

Blocking of sTNF improves functional outcome in EAE [170, 171]

Blocking sTNF attenuates neurodegeneration in AD and PD models [172–174]

TNFR1 mediates direct apoptosis of neurons via caspase 8 [175]

memTNF/TNFR2 signaling

TNFR2−/− mice show exacerbated neurodegeneration in EAE model [167–169]

TNFR2−/− mice show exacerbated neurodegeneration in retinal ischemia [165]

TNFR2 promotes OPC proliferation and remyelination [176]

TNFR2 protects neurons against glutamate-induced excitotoxicity [142, 143]

memTNF dependent activation of NFkB is neuroprotective in EAE [171]

TNFR2 rescues neurons from oxidative stress-induced cell death [144]

TNFR2 promotes oligodendrocyte maturation [177]

TNFR2 promotes oligodendrocyte proliferation and maturation [178]

TNFR2 protects OPCs against oxidative stress [179]


Structure	Damage Scale	Stiffness Adjustment	Flatfoot Stiffness (N/mm)

Superomedial spring	Stage IV	−7/8th	39

Inferomedial spring	Stage II	−3/8th	94

Talocalcaneal interosseus	Stage I	−1/8th	236

Plantar fascia	Stage I	−1/8th	175

Plantar metatarsocuneiform	Stage 0	None	90

Plantar naviculocuneiform	Stage 0	None	180

Long and short plantar	Stage 0	None	240

Deep deltoid	Stage 0	None	200

Anterior superficial deltoid	Stage I	−1/8th	70

Posterior superficial deltoid	Stage 0	None	117


Usage	AAindex ID	Physicochemical properties

100%	MEEJ800102	Retention coefficient in HPLC, pH2.1

91%	WOLS870102	Principal property value z2

87%	CASG920101	Hydrophobicity scale from native proteins

84%	NAKH900110	Normalized composition of membrane proteins

81%	FASG760105	pK-C

79%	FAUJ880105	STERIMOL minimum width of the side chain

76%	CHAM830107	A parameter of charge transfer capability

61%	QIAN880127	Weights for coil at the window position of -6

59%	RACS820108	Average relative fractional occurrence in AR (i-1)

58%	DIGM050101	Hydrostatic pressure asymmetry index, PAI

56%	TANS770109	Normalized frequency of coil


Treatment groups	Continuous exposure profile	Cross-over exposure profile

CC	TT	CT	TC

CC		42	53	42

TT	42		36	31

CT	53	36		39

TC	42	31	39


XXY ID	Sequence (XX_Y)	N Species	freq (%)	N changes*

1	AAaTGAAGAAAAcGAAGA_ATGAAGA	2	2.11	2

2	AAaTGAAGAAAATGAAGA_ATGAAGA	27	28.42	1

3	AAaTGAAGAAAATGAAGA_ATGAgGA	2	2.11	2

4	AAaTGAAGAcAATGAAGA_ATGAAGA	3	3.16	2

5	AAaTGAgGAAAATGAAGA_ATGAAGA	1	1.05	2

6	AACaGAAGAAAAcGAAGA_ATGAAGA	2	2.11	2

7	AACcGAAGAAAAcGAAGA_ATGAAGA	1	1.05	2

8	AACTGAAGAAAAcGAAGA_ATGAAGA	11	11.58	1

9	AACTGAAGAAAATGAAGA_AcGAAGA	1	1.05	1

10	AACTGAAGAAAATGAAGA_ATGAAGA	40	42.11	0

11	AACTGAAGAcAATGAAGA_ATGAAGA	3	3.16	1

12	cAgTGAAGAAAATGAAGA_ATGAAGA	1	1.05	2

13	cAgTGAAGAtAAcGAAGA_ATGAAGA	1	1.05	4


Participants	Nationality	Sex	Age category	Migratory status	Health complaints	Received treatments while undocumented migrant in Denmark

P01	Bangladeshi	Male	31-40	Failed asylum seeker	Dental problems, mental health problems	None

P02	Bangladeshi	Male	31-40	Failed asylum seeker	Superficial wounds after assault, asthma	Prescription for medication fromgeneral practitioner

P03	Bangladeshi	Male	21-30	Failed asylum seeker	Psoriasis, mental health problems	Treatment for psoriasis throughinformal networks of healthcare professionals and at a hospitaldermatology department

P04	Bangladeshi	Male	41-50	Failed asylum seeker	Leg fracture, mental health problems, cancer suspicion	Treatment for a leg fracture at hospital ER, check-up athospital oncology department

P05	Indian	Male	41-50	Failed asylum seeker	Diabetes, high blood pressure, heart disease, mental health problems	Treatment for depressionthrough informal networks ofhealthcare professionals. Medical supplies throughpersonal networks

P06	Indian	Male	31-40	Overstayer	Dental problems, ulcer, sprained foot,mental health problems	Treatment for a sprained foot at hospital ER

P07	Nepali	Male	21-30	Overstayer	None	None

P08	Nepali	Male	31-40	Overstayer	Dental problems, mental health problems	None

P09	Nepali	Male	21-30	Overstayer	Sprained hand, skin allergy	None

P10	Nepali	Male	21-30	Overstayer	Mental health problems	None


	Linear model	Ordered probit model

Men 15-44

Gap in VAS	0.196	0.186

Prevalence effect	-0.082	-0.102

Severity effect	0.239	0.030

Interaction	0.038	-0.012

Women 65-74

Difference	-0.902	-0.664

Prevalence effect	-0.575	-0.699

Severity effect	0.305	0.372

Interaction	-0.632	-0.646

Women 75 & more

Difference	-1.205	-1.182

Prevalence effect	-1.117	-1.189

Severity effect	-0.839	-0.088

Interaction	-0.049	-0.905