dataesr/scientific-paragraphs-categorization huggingface dataset:
org/10. 5281/zenodo. 2535761). While we conducted tests to ensure that our power simulation was not itself biased (supplementary Discussion, doi. org/10. 5281/zenodo. 2535761), a postmarketing study could still be biased in real life, if the historical controls used do not accurately estimate the true hazard rates facing the trial participants. 32 There are no environmental, demographic, or non-PRNP genetic factors known to affect prion disease risk or age at onset, although these might nonetheless exist. 33, 34 erhaps of greater concern is that most of our historical controls were collected retrospectively-individuals are only ascertained if they become sick-and may overestimate the hazard rates for individuals followed prospectively. 25 To assess this possible source of bias, we compared the survival of the limited number of individuals followed prospectively in our dataset (n = 24 individuals, with a cumulative 145 personyears of follow-up), conditioned on their ages at first ascertainment, to those of individuals with no prospective followup.
4 to ±8. 6 years  36, 37  ). In addition, an individual's age at onset in genetic AD is reported to be correlated with parental age at onset,  37  and this property has been used to attempt to enrich for high-hazard individuals in trials,  38  whereas we have found no evidence that parent and child age at onset are correlated in genetic prion disease (table  S7 , doi. org/10. 5281/zenodo. 2535761, and reference 25). Second, genetic prion disease is rarer. The PSEN1 preventive trial recruited from a single pedigree of ;5,000 individuals 39 from which 1,065 living individuals with the mutation have been enrolled in a registry. 40 here is no known genetic prion disease family this large. Third, genetic prion disease offers more limited financial incentives for a pharmaceutical sponsor. The cost of the PSEN1 preventive trial has been estimated at $96 million,  38, 41  and while this price may be tenable for sponsors in view of potential for an expanded AD indication, no similar potential exists for prion disease.
Second, although our dataset is, to our knowledge, the largest ever reported for genetic prion disease age at onset, our statistical power to detect genetic modifiers, which might aid in age at onset prediction, is limited. Third, although we have attempted to select a reasonable set of assumptions for modeling clinical trials, we have by no means exhaustively sampled the set of possible trial designs and measures. Fourth, powering a postmarketing study will require a good historical control dataset to compare to, and our dataset, which was collected mostly retrospectively, may or may not be adequate. We found no evidence that our dataset overestimates the hazards facing prospectively followed individuals, but this could be due to a lack of power in our analysis. Fifth, the ascertainment of genetic prion disease by prion surveillance centers may be biased towards rapidly progressive phenotypes, meaning that the prevalence of more slowly progressive forms might be underestimated.
Variability in age at onset in genetic prion disease Hazards and survival for the most common PRNP mutationsThe hazard, or probability of disease onset, in each year of life (y axis) is plotted against age (x axis) with curve thickness representing the proportion of individuals still living at each age, which is the product of age-dependent survival and mutation prevalence. Supplementary mutations, and conventional survival curves and hazard plots, are included in figureS3(doi. org/10. 5281/zenodo. 2535761).
PRNP mutation. We also used a simulation to account for the full shape of the hazard curve and diversity of genetic mutations, but the simulated power results were similar to those in table 2 (see table S6, doi. org/10. 5281/zenodo. 2535761). Stratification by PRNP mutation did not improve power in our simulations (supplementary discussion, doi. org/10. 5281/ zenodo. 2535761), perhaps because age at onset distributions (table 1) are wide and overlapping, such that PRNP mutation explains only a minority of the overall variance in age at onset (adjusted R 2 = 0. 15, linear regression, p < 1 × 10 -32 ).
Study funding E. V. M. is supported by the  NIH  ( F31 AI122592 ), S. M. V. is supported by the  National Science Foundation  ( GRFP 2015214731 ), and both are supported by an anonymous organization. S. H. and J. -P. B. are supported by  Santé Publique France by the program  " Investissement avenir "  ANR-10-IAIHU-06. Work at the  NHS National Prion Clinic  was supported by the  UK National Institute of Health Research's Biomedical Research Centre at University College London Hospitals NHS Foundation Trust. Japanese prion surveillance is funded by a  grant-in-aid  from the  Research Committee of Prion Disease and Slow Virus Infection , the  Ministry of Health, Labour and Welfare of Japan , and the  Research Committee of Surveillance and Infection Control of Prion Disease , the  Ministry of Health, Labour and Welfare of Japan.
S. C. is supported in part by an  NHMRC Practitioner Fellowship  (# APP1105784 ) and the  Australian National Creutzfeldt-Jakob Disease Registry  is funded by the  Commonwealth Department of Health. Data collection in Germany was supported by grant  1369-341  by  Bundesministerium für Gesundheit through Robert Koch Institute. Work in Italy was partially supported by  Fondazione Telethon  ( GGP10208 ). M. D. G. was supported by  NIH/NIA   R01 AG-031189 ,  NIH/ NIA   R01 AG032289 , the  Michael J. Homer Family Fund , and  Alliance BioSecure. Disclosure E. Minikel  has received research support from  Charles River Laboratories  via charitable donations to  Prion Alliance. S. Vallabh  has received research support from  Charles River Laboratories  via charitable donations to  Prion Alliance. M.
Censored data include individuals who were either alive and well at last follow-up or had died of an unrelated cause, and whose genetic status was known either through predictive testing or due to obligate carrier status. For D178N and E200K, because the majority of individuals have disease duration ≤1 year (figureS2, doi. org/10. 5281/zenodo. 2535761),ageatdeath is used where age at onset is unavailable. For P102L, which more often has a longer disease duration, only age at onset is used. Range indicates highest and lowest observed age at onset, except where a the longest survival is a censored data point. diseaseprevalencethat1-2peopleper100,000 in the general population harbor high-penetrance PRNP mutations (reference 4 and supplementary Discussion, doi. org/10. 5281/zenodo. 2535761),butatpresent,manyremainunaware of their risk due to underdiagnosis of affected family members,23and few choose predictive testing15as the results are currently considered medically unactionable.
Based on predictive test results, we estimate there are currently ;60 people in the United States who are age 40 or older and hold a positive predictive test for a highly penetrant PRNP variant (see Methods). individuals. For context, we also determined the effect size, in median years of healthy life added, to which each hazard ratio (HR) corresponds (table2). The calculations are sensitive to which mutations are included, the run-in period, the number of years of follow-up, and the assumed withdrawal rate, but we explored a range of different assumptions and none supports a different overall interpretation of the data (tableS5, doi. org/ 10. 5281/zenodo. 2535761,and Discussion). In particular, the assumption of a 15. 2% annual withdrawal rate means that only 44% of original participants remain after 5 years, but even reducing the withdrawal rate to zero only lowers the number of participants required by one-third (table S5, doi.
PRNP mutation. We also used a simulation to account for the full shape of the hazard curve and diversity of genetic mutations, but the simulated power results were similar to those in table 2 (see table S6, doi. org/10. 5281/zenodo. 2535761). Stratification by PRNP mutation did not improve power in our simulations (supplementary discussion, doi. org/10. 5281/ zenodo. 2535761), perhaps because age at onset distributions (table 1) are wide and overlapping, such that PRNP mutation explains only a minority of the overall variance in age at onset (adjusted R 2 = 0. 15, linear regression, p < 1 × 10 -32 ). Statistical power might be improved by stratifying clinical trial analysis by relevant additional variables, but there are cur- rently no variables that help to explain age at onset (supple- mentary Discussion, table S7, and figures S4 and S5, doi.
org/ 10. 5281/zenodo. 2535761). For instance, we found no sex effect, and no evidence that parent and child age at onset are correlated after controlling for PRNP mutation and for child's year of birth, a variable that captures some effects of ascer- tainment bias 25 (table S7, doi. org/10. 5281/zenodo. 2535761). A common genetic variant, PRNP M129V, is known to affect the clinical and pathologic presentation of many forms of prion disease 26 as well as the risk of sporadic and acquired prion disease. For D178N, our data are suggestive that a 129VV genotype may predispose to earlier onset than MM or MV genotypes (figure S4 and supplementary Discussion, doi. org/10. 5281/ zenodo. 2535761), but in the overall dataset, codon 129 failed to explain additional variance in age at onset (supplementary Discussion, doi.
org/10. 5281/zenodo. 2535761). 21,25,28,29ividuals never become sick, thus, the increase in median age at onset (the age where 50% of people have had onset) is undefined. e128Neurology| Volume 93, Number 2 | July 9, 2019Neurology. org/N 27his variant has previously been reported to affect age at onset in some forms of genetic prion disease but not others. 21,25,28,29We found no evidence that codon 129 affects age at onset for P102L or E200K individuals (table S7 and figure S4, doi. org/10. 5281/zenodo. 2535761).
Sample size An explorative strategy was used to determine an appropriate sample size, since both, data on the nutritional status of Cambodian garment workers and data on the effects of lunch provision in this context were largely missing at time of trial implementation. G*Power (v. 3. 1. 9. 2, University of Kiel, Germany) was used to carry out the calculation. At a two-tailed 5% level of significance (alpha = 0. 05) and a statistical power of 80% (beta = 0. 20) to detect a small to medium standardized effect size of 0. 35 (Cohen's d) between both arms  [37] , 130 subjects in each group were required at follow-up. Considering a 20% loss to follow up, it was aimed at recruiting a total of 330 participants (165 subjects in each arm).
Randomization Simple randomization with a 1:1 ratio into an intervention arm (access to six-month lunch provision through local canteen during workdays) and a control arm (equal monetary compensation at the end of the trial) was conducted via assigning a computer-generated random number for each subject (identifying the allocation to intervention or control) by making use of the random number generator within SPSS (v. 22. 0. 0. 1, IBM Corp. , USA) (prepared by study coordinator). Enrolled participants were individually assigned to groups by an assistant who was neither involved in the enrollment procedure nor in the assessments.
Statistical analysis Data of questionnaires and anthropometry sheets were double-entered by trained assistants using EpiData (v. 3. 1, EpiData Association, Denmark). Overall data management and statistical analyses were executed using SPSS (v. 22. 0. 0. 1, IBM Corp. , USA). Evaluation only included participants who completed the follow-up, regardless of the actual individual adherence of intervention subjects to daily eating lunch at the staff canteen. Detailed baseline findings among all originally enrolled subjects can be found in a previously published paper  [4]. A wealth index was computed to assess the socio-economic status of subjects' households using principal component analysis  [38]. The index was based on the following variables: number of rooms per household, people per room, main place of cooking, main type of fuel, main material of the floor, and ownership of a bank account, latrine, electricity, and several household assets (radio, television, non-mobile telephone, wardrobe, sewing machine, DVD player, generator, watch, motorcycle, motorcycle cart, car, and boat).
Baseline characteristics Between 14 March and 4 April 2015, a total of 267 female workers signed the informed consent prior to enrollment (Fig. 1 ). At the enrollment procedure, which took place from 21 to 29 April 2015, 229 workers were present whereas 38 were not (n = 30 ceased to work and n = 8 refused to participate). Further six workers were excluded from participation at the clinical screening (n = 2 with Hb < 7. 0 g/dL, n = 2 not nulliparous, n = 1 with physical handicap, and n = 1 with chronic disease). The remaining 223 women were randomly assigned and access to free lunch provision for the intervention group started in early May 2015. The follow-up assessment took place from 1 to 10 October 2015. One hundred seventy-two women (77%) completed the follow-up (n = 50 ceased to work and n = 1 became pregnant), with endline data available for anthropometry.
As the number of data sets was smaller than targeted, this clearly limited the statistical power and the effect sizes that could be measured. In line with guidelines for exploratory studies, no corrections for multiple comparisons have been made  [63]. Only a part of the enrolled workers where actually affected by underweight, anemia and/or micronutrient deficiencies. However, direct improvements can only be expected in malnourished individuals. The subgroup analysis was based on relatively small sample sizes, holding a descriptive character, and indicating trends only. The calculation of the sample size of future studies may consider the initial prevalence of malnutrition. The prevalence of hemoglobinopathies, which are likely to be a contributing factor to anemia, was not measured. Inherited hemoglobin disorders are also known to impact on markers of iron status  [16, 64].
Acknowledgements We thank  Khov Chhay  (Managing Director) and the management of  Apsara Garment Co. Ltd. , Phnom Penh, Cambodia , for their unrestricted help to implement the study;  Rapytha Bonamy  (Managing Director) and the staff of  Hagar Catering  and  Facilities Management Ltd. , Phnom Penh, Cambodia , for the collaboration in establishing and operating the staff canteen;  Juergen Erhardt, VitMin Laboratory, Willstaett, Germany , and the  Pasteur Institute, Phnom Penh, Cambodia , for conducting the serum biomarker analyses; staff at the  Department of Fisheries Post-Harvest Technologies and Quality Control, Fisheries Administration, Ministry of Agriculture, Forestry and Fisheries ,  Phnom Penh ,  Cambodia , and  Hanna MSc  student at  Justus Liebig University, Giessen, Germany , for their support in implementation and data collection.
E. coli Bacterial Culture and Macronutrient Supplementation E. coli K12 bacteria were cultured for 48 h at 37 • C in 40 mL of Mueller-Hinton (MH) medium (Sigma-Aldrich, St. Louis, MO, USA) composed of beef infusion solids (2. 0 g/L), casein hydrolysate (17. 5 g/L), starch (1. 5 g/L) at pH 7. 4. Every 12 h, after a centrifugation step (4300 rpm, 5 min), the supernatant was discarded, and bacteria were supplemented by an equivalent volume of MH medium imitating two daily meals (Figure  1 ). Bacterial growth rate was monitored every hour by measuring the optical density using a spectrophotometer (BioMate, ThermoElectron Corporation, Waltham, MA, USA). The bacterial growth dynamics using the 12-hourly MH culture medium provision data are shown in Figure  1. It shows the acceleration of the onset of the stationary phase after the third nutrient provision as previously reported  [3].
Two drops of 4 ,6-diamidino-2-phenylindole (DAPI) (Sigma) were added to each slide to counterstain the bacterial DNA. The ClpB-immunofluorescence and DAPI staining were observed under a fluorescence microscope (Zeiss, Oberkochen, Germany) and images were taken using ×100 objective from five areas/slide. The presence of ClpB was analyzed by quantifying the relative number of ClpB positive bacteria on the total number of DAPI stained bacteria on the visual field using ImageJ ® software (LOCI, University of Wisconsin-Madison).
FUNDING The  UMR1136  is supported by a grant overseen by the  French National Research Agency (ANR)  as part of the  "Investissements d'Avenir" program  ( ANR-11-LABX-0002-01 ,  Lab of Excellence ARBRE ). The work on plant GRX and BOLA proteins was supported by the  Agence Nationale de la Recherche  (Grant No. 2010BLAN1616 ).
Image regions were analyzed in the entire z axis with 3-μm step intervals, and images were reconstituted by using the maximumintensity projection tool of Zen software. c-Fos + , AR + , and AR/c-Fos + cells were counted automatically by using the particle analyzer plugin of Fiji. For combined Ca 2+ imaging and immunocytochemistry, dissociated VNO cells were fixed by using PBS solution containing 4% PFA (10 min), permeabilized and incubated for 10 min in blocking solution (TST, i. e. , 0. 1% Triton X-100, 1% FBS, 50 mM NaCl, 100 mM Tris•HCl, pH 7. 5), incubated with anti-PDE4A (1:500; 30 min, RT) and anti-Gαo (1:50; 30 min, RT), and washed in TST (5 min), followed by an incubation (30 min, RT) in secondary antibodies (Alexa Fluor 488 goat anti-rabbit, Alexa Fluor 647 goat antimouse, 1:500; Invitrogen).
Each sample was run in triplicate, and data were analyzed with the CFX Manager 3. 0 Software (Bio-Rad) normalized to Hprt-1 expression level to obtain a ΔCt and expressed as 2 ΔCt. VNO cDNAs were used to assess V1re6, V1re2, V1rf3, V1rj2, Vmn2r1, Vmn2r65, Trpc2, and Plcb2 expression by endpoint PCR with GoTaq G2 Master Mix. Primer sequences are shown in SI Appendix, Table  S2. PCR conditions for all primers were 95 °C for 3 min, followed by 39 cycles (95 °C for 45 s, 58 °C for 30 s, and 72 °C for 60 s), and 72 °C for 10 min. Products were run on a 1% agarose gel. Ca 2+ Imaging. Ca 2+ imaging of freshly dissociated VSNs was performed as described previously  (15, 16). VNO epithelium was detached from the cartilage and minced in PBS solution at 4 °C. The tissue was incubated (20 min at 37 °C) in PBS solution supplemented with papain (0.
e. , ΔF/F0 (F0 was the average of the fluorescence values 10 s before stimulation). Images were acquired at 1 Hz and analyzed by using a combination of Zen (Zeiss), ImageJ (NIH), and Igor (Wavemetrics) software. To identify and mark responding VSNs, ΔF images (F-F0) were overlaid onto transmitted light images (Fig. 2C ) by using Adobe Photoshop's difference tool and slightly adjusting the exposure settings. Original ΔF images of ligandinduced VSN responses are shown in SI Appendix, Fig. S2D. VNO slices were stimulated successively and in random order by using bath application. The following criteria for stimulus-induced Ca 2+ responses were applied. (i) A response was defined as a stimulus-dependent deviation of GCaMP6f fluorescence that exceeded twice the SD of the mean of the baseline fluorescence noise.
Mice were categorized as aggressive if they presented aggressive behavior (e. g. , biting, killing) toward a pup, as parental if they retrieved a pup into their nest, and as neutral if they were indifferent to a pup. Latencies to attack a pup and pup grooming time were scored. Statistics. Statistical analyses were performed by using GraphPad Prism 7. 0 (GraphPad Software), OriginPro 2016G, and OriginPro 2017G (OriginLab). Assumptions of normality and homogeneity of variance were tested before conducting the following statistical approaches. Student's t test was used to measure the significance of the differences between two distributions. In case the results failed the test of normality, a Mann-Whitney U test was performed. For paired data comparisons, we used the Wilcoxon signed-ranks test, and, for categorical data, we used the Fisher's exact test.
Multiple groups were compared by using a one-way or two-way ANOVA with Tukey's multiple comparison test as a post hoc comparison or Kruskal-Wallis ANOVA for nonnormal distributions. The probability of error level (i. e. , α) was chosen to be 0. 05. Unless otherwise stated, results are presented as means ± SEM and documentation of individual data points. Further details on testosterone measurements, stimulus delivery, and other behavioral tests are provided in SI Appendix, Materials and Methods. The datasets generated and/or analyzed during the present study are available from the Data Inra Dataverse portal (https://data. inra. fr/).
The trials were generally small and weak methodologically. Meta-analyses provided low-quality evidence that STD multi-nutrient fortification of HM, in comparison to the unfortified HM, improved in-hospital weight gain, linear growth, and head circumference growth. Only very little data were available for growth and developmental outcomes beyond infancy and these did not show long-term advantage. However, when comparisons are made between fortified HM in STD fashion and preterm formula (PF) (83-85) the findings indicate that despite fortification, HM fed preterm infants continue to grow more slowly than PF fed infants. Henriksen et al. (86) reported that 58% of VLBW infants fed predominantly fortified HM had EUGR at discharge. Maas et al. (87) evaluated in-hospital growth of 206 very preterm infants and found that standard deviation score for weight from birth to day 28 decreased more in infants with a cumulative milk intake >75% of all enteral feeds compared to those <25% HM intake.
Multi-nutrient fortification of human milk for preterm infants. Cochr Database Syst Rev. (2016) 8:CD000343. doi: 10. 1002/14651858. CD000343. pub3 • Randomized trials comparing the efficacy and safety of ADJ vs. 83. O'Connor DL, Jacobs J, Hall R, Adamkin D, Auestad N, Castillo M, Targeted Fortification 84. et al. Growing and development of premature infants fed predominantly human milk, predominantly premature infant formula, or a combination of human milk and premature formula. J Pediatr Gastr Nutr. (2003) 37:437-46. doi: 10. 1097/00005176-200310000-00008 • Defining including large cohorts the neurocognitive reasonable • Optimization of the quality of fortifiers (amount and quality and replicable study endpoints outcomes, body composition in of protein, source of energy, EFA content) while considering ethical dilemmas.
Data source Data used in this analysis were obtained from the ANRS-PEDIACAM, an ongoing prospective observational study based in three referral hospitals in Cameroon (The Maternity of the Central hospital/Mother and Child Center of the Chantal Biya Foundation (MCH/MCC-CBF) in Yaounde, the Essos Hospital Center in Yaounde(EHC) and the Laquintinie Hospital in Douala (LH)) under the coordination of the Centre Pasteur of Cameroon. The ANRS-PEDIACAM cohort study was designed to assess the feasibility of early HIV diagnosis and access of HIVinfected infants to antiretroviral multi-therapy and evaluate infant response to vaccines of the Expanded Program on Immunisation (EPI). A synthesis of the study protocol was described elsewhere  [17]. Briefly, infant inclusion into the ANRS-PEDIACAM study was conducted in two consecutive phases.