dataesr/scientific-paragraphs-categorization huggingface dataset:
Sex differences in association of DHEA-S with RV function In healthy subjects DHEA-S levels were associated with larger RV volumes and mass but worse RV function in females, however not in males. 10 6] [17]  In experimental studies, DHEA-S has shown to prevent pulmonary vascular changes and may thereby positively affect the right ventricle. 7] [28]  In our study, we could confirm reduced expression of DHEA-S in a Dutch cohort of male and female PAH-patients across a wide range of ages. This further supports the rationale of a phase 2 clinical trial currently conducted to study effects of DHEA supplementation on RV functional parameters (EDIPHY trial: NCT03648385). Interestingly, in our cohort the relation of DHEA-S with RV dysfunction was more pronounced in male PAH-patients. Therefore, sex-specific analyses of treatment effects of DHEA-S supplementation are of interest.
Disclosure statement This research was financially supported by the  Netherlands Organization for Scientific Research :  NWO-VICI num. 918. 16. 610  ( J. A. Groeneveldt ,  B. E. Westerhof  and  A. Vonk Noordegraaf ) and  NWO-VIDI  num. 917. 18. 338 (F. S. de Man). The work was also funded by the  Dutch Heart Foundation   Dekker senior post-doc grant num. 2018T059  ( J. van Wezenbeek  and  F. S. de Man ) and Dekker Senior Clinical Scientist  2020T058  ( M. L. Handoko ), and the  Netherlands CardioVascular Research Initiative :  CVON-2017-10 DOL-PHIN-GENESIS  ( A. Vonk Noordegraaf ,  F. S. de Man ,  H. J. Bogaard  and MJ Goumans), and CVON-2018-29  PHAE-DRA-IMPACT  ( A. Lluci a-Valldeperas ,  A. Vonk Noordegraaf ,  F. S. de Man ,  H. J. Bogaard  and MJ Goumans). (TUNEL, gray) and vessels (Ulex, green).
Literature Screening: A systematic search was conducted for studies on predation of mosquitoes that were published between 1970 and July 1, 2019 using both PubMed® and Web of Science TM search engines, according to the PRISMA protocol  (Moher et al. , 2009). Mosquito vectors of the Anopheles and Aedes genera were specifically highlighted in our search terms because these genera contain the vector species that transmit malaria, yellow fever, and dengue -the three most deadly mosquito-borne diseases worldwide  (Hill et al. , 2005). Searches included 18 combinations of three vector predation terms (mosquito predat*, Anopheles predat*, Aedes predat*) and six trait terms (survival, mortality, development, fecundity, dispers*, host preference). Abstracts from the 1,136 studies were each screened by two different co-authors, using the "metagear" package in R  (Lajeunesse, 2016 , R Core Team, 2020).
If either screener thought the study had information relevant to predation of mosquitoes, or both screeners thought the abstract was ambiguous, the study was read in full. This resulted in 306 studies that were fully reviewed to determine if any predation data could be extracted (Fig  1). Data were extracted from studies that collected data on non-consumptive and/or consumptive effects of predators on mosquitoes. Studies were required to have a mean, error measurement, and at least two replicates for both control and predator treatments. The control treatment was required to have all the same conditions as the predator treatment, such as prey density and type of water, without the predators. Studies that were not published in English and studies that did not differentiate between predators of multiple families were excluded.
, 1995). Under low resource conditions, female mosquitoes are likely to maximize body mass by extending their development time, whereas males tend to minimize their development time at the expense of lower body mass  (Kleckner et al. , 1995). Observations of mosquito development time and body size in our database that were not sexspecific were excluded so that these vector traits could be analyzed while controlling for sex. In addition, among the observations of development time and body size, some predator means did not necessarily represent an evenly weighted average of the replicates. For example, if a total of twenty mosquitoes from three different predator replicates survived to adulthood, the mean development time and size of those twenty individuals may have been reported. To represent an evenly weighted average of the replicates, it is necessary to first calculate summary statistics among multiple individuals that emerge from the same replicate, and then report the average of the replicate-specific means.
Observations that might have been influenced by uneven representation of replicates were excluded to prevent pseudoreplication from altering later meta-analyses. For consumptive observations where life stage-specific survival was reported after more than 10 days of predator exposure, only data on survival marked by adult emergence were included for analysis. Effects observed among immature vector stages after such a long period of predator exposure were not analyzed because they could have resulted from a combination of non-consumptive effects on development, and consumptive effects on survival. Development time observations that were reported as the inverse of development time (units of days -1 ) were excluded because although their means could be converted to units of days, their standard deviations could not be converted to match units of days.
In cases where multiple body sections of the same mosquitoes were measured to produce multiple size observations, only the wing measurement was included in the analysis to prevent pseudoreplication. Observations in which both the control and the predator treatments had standard deviations of zero were excluded because the meta-analysis methods did not support nonpositive sampling variances. One study that was included in our database reported egg survival data as the hatch rate of field collected Culex pervigilans rafts  (Zuharah et al. , 2013). However, mosquitoes have been shown to lay eggs independent of mating (O'Meara, 1979), and hatch rates of zero have previously been observed in rafts laid by Culex females that were held separately from males  (Su and Mulla, 1997). Thus, hatch rates of zero were excluded from further analysis because these values may represent unfertilized egg rafts, rather than a strong impact of predators on survival.
Twenty of the 187 consumptive survival observations had a predation mean of zero, and each of these zeros resulted from experiments that began with a specified number of live larvae. Consumptive survival zeros were each replaced with 0. 5% of the starting number of mosquito prey to avoid undefined effect sizes. In addition, there was one zero out of the 36 oviposition predation means; this value had units of "number of egg rafts laid" and was replaced with 0. 5 rafts. Similar methods for replacing zero values in the treatment mean with small non-zero values have previously been employed  (Thapa et al. , 2018). The final analysis dataset included seven subsets: consumptive effects on survival, nonconsumptive effects on survival, oviposition, development (female and male), and size (female and male).
Assessing Publication Bias Publication bias was assessed by visually inspecting funnel plots and conducting Egger's regression test ("regtest" function) with standard error as the predictor  (Sterne and Egger, 2001, Viechtbauer, 2010). If the Egger's regression test showed significant evidence of publication bias based on funnel plot asymmetry, the "trim and fill" method ("trimfill" function) was used to estimate how the predation effect size might change after imputing values from missing studies  (Duval and Tweedie, 2000b , Duval and Tweedie, 2000a , Viechtbauer, 2010). The trim and fill method has previously been recommended for testing the robustness of conclusions related to topics in ecology and evolution  (Jennions and Moller, 2002). Of the two trim and fill estimators, R0 and L0, that were originally recommended  (Duval and Tweedie, 2000b, Duval and Tweedie, 2000a) , the L0 estimator was used in this study because it is more appropriate for smaller datasets  (Shi and Lin, 2019).
Testing Moderators Data subsets that had high heterogeneity, observations from at least 10 studies, and no evidence of publication bias according to Egger's regression results were analyzed further using multilevel mixed effects models with the "rma. mv" function  (Viechtbauer, 2010 , Higgins et al. , 2020). All multilevel mixed effects models had normal error distributions, REML estimators for τ 2 , and accounted for two random factors: effect size ID, and experiment ID nested within study ID. Moderators, such as predator family, vector genus, larval instar (directly correlated to prey size), and temperature, were tested within each data subset to determine if they affected the observed heterogeneity in ROM effect sizes. For categorical moderators, the intercept of the multilevel mixed effects model was removed, allowing an analysis of variance (ANOVA) referred to as the "test of moderators" to indicate if any of the categories had an effect size different than zero.
For data subsets with observations from 10 to 29 studies, only one moderator was tested at a time to account for sample size constraints. For subsets with observations from a higher number of studies (30 or more), up to two moderators were tested at once, and interaction between moderators was also tested. The small sample corrected Akaike Information Criterion (AICc) was used to compare multilevel mixed effects models and to select the model of best fit within each data subset; differences in AICc greater than two were considered meaningful  (Burnham and Anderson, 2004). Both the database and the R code file showing all analyses are publicly accessible from the Dryad Digital Repository.
Discussion In this study, laboratory and semi-field empirical data were obtained through a systematic literature review and used to conduct a meta-analysis that assessed consumptive and nonconsumptive effects of predators on mosquito prey. Some results agree with previously observed trends, such as greater consumptive effects from larger predators  (Kumar et al. , 2008 , Peters, 1983)  and no oviposition response to predator cues among container-breeding Aedes mosquitoes (Vonesh and  Blaustein, 2010). However, this meta-analysis revealed additional trends. Mosquito larval instar had an important role in moderating consumptive effects of predators, likely because of its direct correlation to prey size. Furthermore, a small, but significant, decrease in mosquito survival due to non-consumptive effects of predators was observed, suggesting that mosquitoes can be "scared to death" by predators  (Preisser et al.
Conversely, it is likely that an oviposition response to predation is not particularly advantageous for Aedes because the delayed hatching of their eggs  (Day, 2016)  can prevent the level of predation risk at the time of oviposition from matching the level of predation risk present in the eventual larval environment (Vonesh and  Blaustein, 2010). The predator avoidance response in Aedes species that lay their eggs above the water's edge in containers has previously been described as "non-existent" (Vonesh and  Blaustein, 2010). Both Aedes species included in this study's oviposition data subset, Ae. albopictus and Ae. aegypti, meet the criterion of ovipositing above water in containers  (Juliano, 2009). Predator avoidance during oviposition has previously been found to increase the mosquito population size at equilibrium  (Spencer et al.
Future directions: Modelling efforts that aim to optimize the application of biocontrol predators should also consider incorporating predator effects on vector survival, fecundity, and lifespan. These additions to predictive models of various biocontrol interventions are likely to help public health officials choose the most cost-effective strategies for limiting disease transmission. In the sixty-study database that was compiled, only one study was designed to directly measure the effect of larval-stage predation on vector competence  (Roux et al. , 2015). Therefore, future efforts to assess the impact of predators on mosquito-borne disease transmission should prioritize experimental studies in which infected mosquito larvae are observed throughout an initial period of aquatic exposure to predators, followed by a period of bloodfeeding in the adult stage.
Two studies from the compiled database examined the compatibility of predators with Bacillus thuringiensis var. israelensis (Bti), a commonly used bacterial biocontrol agent  (Chansang et al. , 2004 , Op de Beeck et al. , 2016). Previous studies have supported the simultaneous application of cyclopoid copepod predators and Bti  (Marten et al. , 1993 , Tietze et al. , 1994) , but additional analyses are needed on the use of Bti with other families of mosquito predators. Populations of other insect pests, such as the southern green stink bug (Nezara viridula), are known to be regulated by both predators and parasites  (Ehler, 2002). The literature search conducted for this meta-analysis returned studies on water mite parasites  (Rajendran and Prasad, 1994)  and nematode parasitoids  (de Valdez, 2006)  of mosquitoes, and ascogregarine parasites have previously been evaluated as biocontrol agents against Aedes mosquitoes  (Tseng, 2007).
A more thorough review of the impacts of parasites and parasitoids on vector traits, such as survival, fecundity, and lifespan, is needed before incorporating these potential biocontrol agents into integrated vector control plans. Three studies in the sixty-study database included experiments where two mosquito prey species were made available to the predator species  (Grill and Juliano, 1996 , Griswold and Lounibos, 2005b , Micieli et al. , 2002). In these cases, the effect size measurement for each mosquito species could be influenced by interspecific competition, or a preference of the predator species for a certain prey species. Hetero-specific prey observations were excluded from this meta-analysis, but future analyses centered on the concepts of interspecific competition or predator preferences might further evaluate these data.
Acknowledgements We are grateful to  Dr. Lauren Cator  for facilitating the early stages of this project and helping to edit this manuscript. We also thank  Dr. Peter Hudson  for his helpful advice in early discussions about the project's aims. In addition, we thank all members of the VectorBiTE RCN (https://vectorbite. org/) for taking the initiative to forge productive collaborations between empiricists and modelers in vector ecology. This work was funded by  NIH  grant  1R01AI122284-01  and  BBSRC  grant  BB/N013573/1  as part of the joint ( NIH-NSF-USDA-BBSRC )  Ecology and Evolution of Infectious Diseases program. It was also funded by a  President 's PhD Scholarship from  Imperial College London  awarded to  Marie C. Russell.
Test of Moderators (degrees of freedom, p-value) AICc ΔAICc Table4). The mean oviposition effect size was not significantly different than zero for Aedes: 0. 32 (95% CI -2. 14, 2. 79), p-value = 0. 7970, or Culiseta: -0. 61 (95% CI -1. 83, 0. 62), p-value = 0. 3329, but for Culex mosquitoes, oviposition was significantly decreased by predator presence: -1. 69 (95% CI -2. 82, -0. 56), p-value = 0. 0033 (Fig 4). vector genus 3, 0. 0149 122. 1 0 none ---- 125. 2 3. 1 predator family 12, 0. 8855 167. 9 45. 8 Table4: Candidate multilevel mixed effects models of non-consumptive effects of predators on mosquito oviposition behavior, fitted to dataset of effect sizes (n = 36 from 12 studies), and ranked by corrected Akaike's information criterion (AICc). Moderator(s).
Ascertainment of Macrovascular and Microvascular Outcomes Ascertainment of CVD events and their dates was based on data linkage to records from hospitalizations through the NHS Hospital Episode Statistics database for nonfatal CVD as a primary or secondary diagnosis and to the Office for National Statistics death registry by use of the NHS identification number. The main outcome for CVD was the first incident or recurrent CVD event (main analysis) and the first incident or recurrent CHD or incident CHD/CVD event (sensitivity analyses) after baseline. 21 erum creatinine was measured with a kinetic colorimetric (Jaffe) method. 22 eGFR was calculated with the CKD Epidemiology Collaboration creatinine equation based on sex, age, race, and serum creatinine. 23 ncident CKD was defined using data from a minimum of 2 repeated measurements of eGFR assuming a linear decline in eGFR with age.
Acknowledgments The authors thank all of the participating civil service departments and their welfare, personnel, and establishment officers; the  British Occupational Health  and Safety Agency; the  British Council of Civil Service Unions ; all participating civil servants in the Whitehall II study; and all members of the Whitehall II study team. The Whitehall II study team comprises research scientists, statisticians, study coordinators, nurses, data managers, administrative assistants, and data entry staff, who make the study possible. A. G. T. and M. K. developed the hypothesis and study design. A. G. T. did the statistical analysis. A. G. T. and M. K. wrote the first and successive drafts of the manuscript. All authors conceived and designed the study, analyzed and interpreted the data, and drafted or critically revised the manuscript for important intellectual content or, in addition, acquired data.
Procedure for BP Measurements and Data Collection The validation procedure began with the patient seated comfortably and relaxed for at least 5 minutes, the back and the arm supported with the middle of the upper arm at heart level, legs uncrossed and feet flat on the floor. BP measurements were performed according to the "same arm, sequential measurements" method on the left arm supported at heart level as described in the AAMI/ESH/ISO Universal Standard. 7 Measurements by the tested device were performed on the same arm supported at heart level as recommended by the manufacturer. As required, nine consecutive BP measurements at 1 minute intervals were performed in each participant using the mercury sphygmomanometers (5 times: R0, R1, R2, R3, R4) and the tested device (4 times: T0, T1, T2, T3) beginning with the standard mercury sphygmomanometer.
Acknowledgments Our heartfelt thanks to all of the patients who took part in the study. Our grateful thanks to the  Foundation-Medical Research Institutes ® (F-MRI)  and the  International Society of Vascular Health  for their support. The study was supported by  Withings ® SA France , the  International Society of Vascular Health (ISVH ® ) France  and the  Foundation-Medical Research Institutes (F-MRI) ® Switzerland.
The GCCR registration process is based on daily reporting by all paediatric haematology-oncology units in Germany, with virtually complete registration  [12]. For this study, we used the most up-todate status of the GCCR database, including late reports received by 15 March 2022. We calculated age-standardized (ASR; using the Segi 1960 World Standard Population)  [13]  and age-specific incidence rates per 1 000 000 person-years. Due to the fact that BCP-ALL markedly peaks in 2-6 year-olds, we used two different age strata, namely ages 2-6 years and 7-14 years with the latter Table  1. Estimated age-standardized and age-specific incidence rates of B-cell precursor acute lymphoblastic leukaemia in children aged 0-14 years in Germany in 2020 and 2021 (by applying different hypothetical scenarios of additional cases due to late reporting) in comparison to previous years.
ACKNOWLEDGEMENTS The  German Childhood Cancer Registry  is funded by the  Federal Ministry of Health  and the  Health Ministries of the 16 federal states of Germany. The funding sources were not involved in the conceptualisation, design, content, or preparation of the manuscript, nor the decision to submit for publication. The authors are grateful to the  German Society for Paediatric Oncology and Haematology (GPOH)  and the paediatric haematology-oncology units for their data contributions to the  German Childhood Cancer Registry. The authors wish to thank  Dr. Melina Mescher ,  Düsseldorf, Germany , for her editorial and administrative support. Where authors are identified as personnel of the  International Agency for Research on Cancer/ World Health Organization , the authors alone are responsible for the views expressed in this article and they do not necessarily represent the decisions, policy, or views of the  International Agency for Research on Cancer/ World Health Organization.
We have developed deep learning models for automatic identification of the maternal heart rate (MHR) and, more generally, false signals (FSs) on fetal heart rate (FHR) recordings. The models can be used to preprocess FHR data prior to automated analysis or as a clinical alert system to assist the practitioner. Three models were developed and used to detect (i) FSs on the MHR channel (the FSMHR model), (ii) the MHR and FSs on the Doppler FHR sensor (the FSDop model), and (iii) FSs on the scalp ECG channel (the FSScalp model). The FSDop model was the most useful because FSs are far more frequent on the Doppler FHR channel. All three models were based on a multilayer, symmetric, GRU, and were trained on data recorded during the first and second stages of delivery. The FSMHR and FSDop models were also trained on antepartum recordings.
The training dataset contained 1030 expert-annotated periods (mean duration: 36 min) from 635 recordings. In an initial evaluation of routine clinical practice, 30 fully annotated recordings for each sensor type (mean duration: 5 h for MHR and Doppler sensors, and 3 h for the scalp ECG sensor) were analyzed. The sensitivity, positive predictive value (PPV) and accuracy were respectively 62. 20%, 87. 1% and 99. 90% for the FSMHR model, 93. 1%, 95. 6% and 99. 68% for the FSDop model, and 44. 6%, 87. 2% and 99. 93% for the FSScalp model. We built a second test dataset with a more solid ground truth by selecting 45 periods (lasting 20 min, on average) on which the Doppler FHR and scalp ECG signals were recorded simultaneously. Using scalp ECG data, the experts estimated the true FHR value more reliably and thus annotated the Doppler FHR channel more precisely.
The models achieved a sensitivity of 53. 3%, a PPV of 62. 4%, and an accuracy of 97. 29%. In comparison, two experts (blinded to the scalp ECG data) respectively achieved a sensitivity of 15. 7%, a PPV of 74. 3%, and an accuracy of 96. 91% and a sensitivity of 60. 7%, a PPV of 83. 5% and an accuracy of 98. 24%. Hence, the models performed at expert level (better than one expert and worse than the other), although a well-trained expert with good knowledge of FSs could probably do better in some cases. The models and datasets have been included in the Fetal Heart Rate Morphological Analysis open-source MATLAB toolbox and can be used freely for research purposes.
Using the raw data from the Doppler sensor or the scalp ECG sensor, the FHR is calculated on the cardiotocograph (CTG) monitor by applying a proprietary algorithm based on autocorrelation. The details of these proprietary algorithms have not been published by the manufacturers. The algorithms can often output false values that correspond to a harmonic of the true FHR value: double the rate, half the rate, or (more rarely) triple the rate. Moreover, the Doppler FHR sensor often records the maternal heart rate (MHR) or a harmonic of the latter, rather than the FHR; the signal is then considered to be false. Lastly, noisy raw data can give rise to random values -albeit only for a few seconds. All these signals will be referred to here as FSs. Although scalp ECG sensors can reportedly sometimes measure the MHR (particularly in cases of fetal death)  [5] , we have not found any examples in our dataset.
All heart rate signals were acquired at a frequency of 4 Hz and a resolution of 0. 25 bpm (or 1 bpm, for MHRs recorded with an oximeter). The tocometer signal was recorded at a frequency of 4 Hz and a resolution of 0. 5 mmHg. MHR signals have only been recorded in our maternity hospital since April 2015; given the importance of the MHR for detecting FS, we did not include data recorded before this date.