bluuebunny/crossref_metadata_2025_split huggingface dataset:
No Relationship between Male Pubertal Timing and Depression – New Insights from Epidemiology and Mendelian Randomization
Authors: Hirtz Raphael , Grasemann Corinna , Hölling Heike , Albers Nicola , Hinney Anke , Hebebrand Johannes , Peters Triinu 
Published: May 2023

AbstractBackgroundIn males, the relationship between pubertal timing and depression is understudied and less consistent than in females, likely for reasons of unmeasured confounding. To clarify this relationship, a combined epidemiological and genetic approach was chosen to exploit the methodological advantages of both approaches.MethodsData from 2,026 males from a nationwide study (KiGGS) were used to investigate the non-/linear relationship between pubertal timing defined by the age at voice break and major depressive disorder (MDD), considering a multitude of potential confounders and their interactions with pubertal timing. This analysis was complemented by Mendelian Randomization (MR), which is robust to inferential problems inherent to epidemiological studies. We used 71 single nucleotide polymorphisms related to pubertal timing in males as instrumental variable to clarify its causal relationship with MDD based on data from 807,553 individuals (246,363 cases and 561,190 controls) by univariable and multivariable MR, including BMI as pleiotropic phenotype.ResultsUnivariable MR indicated a causal effect of pubertal timing on MDD risk (inverse-variance weighted: OR=0.93, 95%-CI [0.87–0.99)], p=.03). However, this was not confirmed by multivariable MR (inverse-variance weighted: OR=0.95, 95%-CI [0.88–1.02)], p=.13), consistent with the epidemiological approach (OR=1.01, 95%-CI [0.81–1.26], p=.93). Instead, the multivariable MR study indicated a causal relationship of BMI with MDD by two of three methods.ConclusionsPubertal timing is not related to MDD risk in males. Considering the adverse health outcomes of higher BMI levels, our findings support the rationale for preventive measures to address obesity and its related risk factors.
Aging affects ciliated cells development in the human endometrial epithelium
Authors: Loid Marina , Obukhova Darina , Kask Keiu , Meltsov Alvin , Derks Kasper , Altmäe Signe , Saare Merli , Peters Maire , Minajeva Ave , Adler Priit , Krjutškov Kaarel , Esteki Masoud Zamani , Salumets Andres 
Published: May 2023

AbstractThe twenties are typically considered the prime reproductive years for women. However, in today’s modern world, many women are choosing to delay family planning, resulting in an increase of females in their forties seeking fertility treatment. Althoughin vitrofertilization (IVF) with donated oocytes and preimplantation genetic testing may help to address the impact of maternal age, the success rate for IVF treatment in this age group is still significantly lower. While endometrial changes, such as abnormal endometrial thickness, inflammatory background, and altered hormone response signaling, are associated with aging, little is known about the molecular features of endometrial aging and their impact on the ability to support embryo implantation. To better understand age-specific changes, we performed endometrial transcriptome profiling of young and advanced age females, undergoing hormonal replacement therapy (HRT) before frozen embryo transfer, followed by immunohistology analysis and single-cell-based deconvolution. Here, we identified 491 differentially expressed genes pointing to the effect of aging on decidualization, cell signaling, inflammation and endometrial receptivity. Our results indicate that p16INK4amay be involved in cellular senescence and the suppression of metabolic and inflammatory processes essential for endometrial preparation for embryo implantation. We have also shown that the proportion of ciliated cells along with ciliary processes is affected by endometrial aging. These findings have important implications for future strategies aimed at improving infertility treatment in women of advanced reproductive age.
Pandemic Lessons of Sustainability: Higher Covid-19 Mortality in Less Sustainable US States
Authors: Liu Lee 
Published: May 2023

AbstractThis paper intends to contribute to the current debate over what lessons the United States should take away from the Covid-19 pandemic. It focuses on the role that sustainability played in shaping different pandemic outcomes among the 50 states. By the end of 2021, Mississippi reported the highest standardized death rate from Covid-19 in the country, more than five times higher than Vermont, which reported the lowest standardized death rate. If Mississippi had the same rate as Vermont, approximately 83% of the lives lost (7,958 individuals) could have been saved. If all 50 states had the same rate as Vermont, approximately 583,296 individuals (76% of the total deceased) would have survived. The inter-state difference in excess death rates was even larger. It was 18.19% in Arizona, 8.5 times as high as in Hawaii. Political ideology is currently a popular possible explanation for discrepancies among states in pandemic outcomes, given that Republican states tended to have higher death rates compared to Democratic ones. Additionally, partisan politics have been criticized for hindering the US pandemic response, especially in the early stages of the pandemic. However, the current debate lacks an attention to sustainability. This study demonstrates that indicators of sustainability may serve as more significant predictors of the death rates among the US states than political affiliation. Using the percentage of votes for Trump per state in 2020 as a proxy variable, this study found that the correlation between political affiliation and the death rates was significant only when it was the lone parameter. Its effects were overshadowed when vaccination rates and eco-friendliness were included in the equation. Above all, when the Sustainable Development Goal (SDG) index was added to the regression, it became the only significant predictor of the death rates. This suggests that it was not “red” or “blue,” but rather “green” that was the most important factor in determining Covid-19 mortality. Pandemic lessons are lessons of sustainability.
The benefit of hypothermic targeted temperature management decreases when post-arrest care improves
Authors: Chen Wei-Ting , Tien Yu-Tzu , Huang Chien-Hua , Wang Chih-Hung , Chang Wei-Tien , Ong Hooi-Nee , Chen Wen-Jone , Tsai Min-Shan 
Published: May 2023

AbstractBackgroundSeveral clinical trials and cohort studies in the past two decades have demonstrated inconsistent results regarding survival and neurologic recovery benefits for patients undergoing targeted temperature management (TTM) at 33℃ as compared to those undergoing TTM at 36℃ or normothermia. Whether the improved quality of post-arrest care over time contributes to diminishing benefit of TTM at 33℃ remains un-investigated.MethodsThere were 1,809 adult non-traumatic cardiac arrest survivors during 2011-2020. After excluding patients with pre-arrest poor conscious level defined as Glasgow-Pittsburgh Cerebral Performance Category (CPC) >2 (n=258), patients who regained clear consciousness after return of spontaneous circulation (ROSC) (n=300), patients with active bleeding or intracranial hemorrhage (n=48) and patients who underwent TTM of 36℃ due to unstable hemodynamic (n=11), a total of 1,192 eligible candidates for TTM of 33℃ were finally enrolled and classified into Period 1 (during 2011-2015, n = 449) and Period 2 (during 2016-2020, n = 693).ResultsPatients in Period 2 received more diagnostics procedures and specific therapies than those in Period 1. The proportion of patients with good neurological recovery at hospital discharge in Period 2 is significantly higher than that in Period 1 (21.4% vs.14.0%, adjusted odds ratio [aOR] 1.60, 95% confidence interval [CI] 1.14-2.26). TTM was beneficial for the outcomes in both Period 1 and 2, with patients in Period 1 having higher chances of survival and good neurological outcome than those in Period 2 (survival: aOR 5.66, 95% CI 3.49-9.18 vs. aOR 2.91, 95% CI 1.98-4.28; good neurological recovery: aOR 3.92, 95% CI 2.12-7.25 vs. aOR 2.19, 95% CI 1.43-3.34). Among patients with low-risk and medium-risk severity of illness, TTM benefited survival and neurological outcomes, regardless of time period. But the chance of beneficial outcomes decreased consistently from Period 1 to Period 2.ConclusionAmong cardiac arrest survivors, improvement in the quality of post-cardiac arrest care over time is associated with better neurological recovery. TTM remains beneficial for survival and neurological outcomes following cardiac arrest, regardless of the time period. However, the benefit of TTM may diminish when post-cardiac arrest care improves.
Compositionally aware estimation of cross-correlations for microbiome data
Authors: Jensen Ib Thorsgaard , Janss Luc , Radutoiu Simona , Waagepetersen Rasmus 
Published: May 2023

AbstractIn the field of microbiome studies, it is of interest to infer correlations between abundances of different microbes (here referred to as operational taxonomic units, OTUs). Several methods taking the compositional nature of the sequencing data into account exist. However, these methods cannot infer correlations between OTU abundances and other variables. In this paper we introduce the methods SparCEV (Sparse Correlations with External Variables) and SparXCC (Sparse Cross-Correlations between Compositional data) for quantifying correlations between OTU abundances and either continuous phenotypic variables or components of other compositional datasets, such as transcriptomic data. We compare these new methods to empirical Pearson cross-correlations after applying naive transformations of the data (log and log-TSS). Additionally, we test the centered log ratio transformation (CLR) and the variance stabilising transformation (VST). We find that CLR and VST outperform naive transformations, except when the correlation matrix is dense. For large numbers of OTUs, SparCEV and SparXCC perform similarly to CLR and VST. SparCEV outperforms all other tested methods when the number of OTUs is small (less than 100). SparXCC outperforms all tested methods when at least one of the compositional datasets has few variables (less than 50), and more so when both datasets have few variables.Author summarySequencing data of the microbiome posses a unique and challenging structure that renders many standard statistical tools invalid. Features such as compositionality and sparsity complicates statistical analysis, and as a result, specialized tools are needed. Practitioners have long been interested in the construction of correlation networks within the microbiome, and several methods for accomplishing this exist. However, less attention has been paid to the estimation of cross-correlations between microbial abundances and other variables (such as gene expression data or environmental and phenotypic variables). Here, we introduce novel approaches, SparCEV and SparXCC, for inferring such cross-correlations, and compare these to transformation-based approaches, namely log, log-TSS, CLR and VST. In some cases, SparCEV and SparXCC yield superior results, while in other cases, a simpler transformation-based approach suffices. The methods are used to study cross-correlations between bacterial abundances in the skin microbiome and the severity of atopic dermatitis, as well as cross-correlations between fungal and bacterial OTUs in the root microbiome of the legumeLotus japonicus.
BioModelsML: Building a FAIR and reproducible collection of machine learning models in life sciences and medicine for easy reuse
Authors: Tiwari Divyang Deep , Hoffmann Nils , Didi Kieran , Deshpande Sumukh , Ghosh Sucheta , Nguyen Tung V. N. , Raman Karthik , Hermjakob Henning , Sheriff Rahuman 
Published: May 2023

AbstractMachine learning (ML) models are widely used in life sciences and medicine; however, they are scattered across various platforms and there are several challenges that hinder their accessibility, reproducibility and reuse. In this manuscript, we present the formalisation and pilot implementation of community protocol to enable FAIReR (Findable, Accessible, Interoperable, Reusable, and Reproducible) sharing of ML models. The protocol consists of eight steps, including sharing model training code, dataset information, reproduced figures, model evaluation metrics, trained models, Dockerfiles, model metadata, and FAIR dissemination. Applying these measures we aim to build and share a comprehensive public collection of FAIR ML models in the BioModels repository through incentivized community curation. In a pilot implementation, we curated diverse ML models to demonstrate the feasibility of our approach and we discussed the current challenges. Building a FAIReR collection of ML models will directly enhance the reproducibility and reusability of ML models, minimising the effort needed to reimplement models, maximising the impact on the application and significantly accelerating the advancement in the field of life science and medicine.
Saxitoxin potentiates Zika virus-induced cell death in human neurons but not in neural progenitors and astrocytes
Authors: Souza Leticia R. Q. , Pedrosa Carolina da S. G. , Puig-Pijuan Teresa , dos Santos Camila da Silva , Vitória Gabriela , Higa Luiza M. , Tanuri Amilcar , Guimarães Marília Zaluar P. , Rehen Stevens Kastrup 
Published: May 2023

ABSTRACTThe Zika virus (ZIKV) outbreak in Brazil between 2015 and 2016 was associated with an increased prevalence of severe congenital malformations, including microcephaly. Notably, the distribution of microcephaly cases was not uniform across the country, with a disproportionately higher incidence recorded in the Northeast region (NE). Our previous work demonstrated that saxitoxin (STX), a toxin ubiquitously present in the drinking water reservoirs of the NE, exacerbated the damaging effects of ZIKV on the developing brain. In the present study, we hypothesized that STX’s impact might vary among different neural cell types. Our experimental observations suggest that exposure to STX potentiates the neurotoxic effect of Zika Virus (ZIKV) on human neuronal cells. However, while ZIKV infection demonstrated severe impacts on astrocytes and neural stem cells (NSCs), the addition of STX did not exacerbate these effects. We observed that neurons subjected to STX exposure were more prone to apoptosis and displayed a higher number of ZIKV-infected cells. These findings suggest that STX exacerbates the harmful effects of ZIKV on neurons, thereby providing a plausible explanation for the heightened severity of ZIKV-induced congenital malformations observed in Brazil’s NE. This study underscores the importance of understanding the interactive effects of environmental toxins and infectious pathogens on neural development, with potential implications for public health policies and interventions.
Disease associated human TCR characterization by deep-learning framework TCR-DeepInsight
Authors: Xue Ziwei , Wu Lize , Tian Ruonan , Liu Zuozhu , Bai Yadan , Sun Di , Guo Yixin , Chen Pengwei , Zhao Yu , He Bing , Wang Lie , Yao Jianhua , Lu Linrong , Liu Wanlu 
Published: May 2023

SUMMARYT cell function is defined by both T cell receptors (TCR) and T cell gene expression (GEX). Although single-cell technology enables the simultaneous capture of TCR and GEX information, the lack of a reference atlas and computational tools hinders our ability to uncover the fundamental TCR usage rules and to efficiently characterize disease-associated TCRs (dTCR). Here, through the collection of million-scale single-cell GEX-TCR reference atlas comprising 20 diverse disease conditions, we revealed the intrinsic features of TCR-MHC (Major Histocompatibility Complex) restriction in CD4/CD8 lineages. We observed the higher coherence for TCRα/β chains in memory T cells, and detected widely-existing public TCRα/β pairs across individuals. Building upon the reference atlas, we introduced TCR- DeepInsight, a deep-learning framework featuring a disease specificity scoring system that enables the characterization of dTCR clusters with similar GEX-TCR. Our study provides a valuable tool for researchers to analyze single-cell GEX-TCR data and identify dTCRs comprehensively and robustly.
Rational screening for cooperativity in small-molecule inducers of protein–protein associations
Authors: Liu Shuang , Tong Bingqi , Mason Jeremy W. , Ostrem Jonathan M. , Tutter Antonin , Hua Bruce K. , Tang Sunny A. , Bonazzi Simone , Briner Karin , Berst Frédéric , Zécri Frédéric J. , Schreiber Stuart L. 
Published: May 2023

AbstractThe hallmark of a molecular glue is its ability to induce cooperative protein–protein interactions, leading to the formation of a ternary complex, despite weaker binding towards one or both individual proteins. Notably, the extent of cooperativity distinguishes molecular glues from bifunctional compounds, a second class of inducers of protein–protein interactions. However, apart from serendipitous discovery, there have been limited rational screening strategies for the high cooperativity exhibited by molecular glues. Here, we propose a binding-based screen of DNA-barcoded compounds on a target protein in the presence and absence of a presenter protein, using the “presenter ratio”, the ratio of ternary enrichment to binary enrichment, as a predictive measure of cooperativity. Through this approach, we identified a range of cooperative, noncooperative, and uncooperative compounds in a single DNA-encoded library screen with bromodomain (BRD)9 and the VHL–elongin C–elongin B (VCB) complex. Our most cooperative hit compound,13-7, exhibits micromolar binding affinity to BRD9 but nanomolar affinity for the ternary complex with BRD9 and VCB, with cooperativity comparable to classical molecular glues. This approach may enable the discovery of molecular glues for pre-selected proteins and thus facilitate the transition to a new paradigm of molecular therapeutics.
p120 RasGAP and ZO-2 are essential for Hippo signaling and tumor suppressor function mediated by p190A RhoGAP
Authors: Ouyang Hanyue , Li Wangji , Hansen Steen H. 
Published: May 2023

SummaryARHGAP35, which encodes p190A RhoGAP (p190A), is a major cancer gene. p190A is a tumor suppressor that activates the Hippo pathway. p190A was originally cloned via direct binding to p120 RasGAP (RasGAP). Here, we determine that a novel interaction of p190A with the tight junction-associated protein ZO-2 is dependent on RasGAP. We establish that both RasGAP and ZO-2 are necessary for p190A to activate LATS kinases, elicit mesenchymal-to-epithelial transition, promote contact inhibition of cell proliferation and suppress tumorigenesis. Moreover, RasGAP and ZO-2 are required for transcriptional modulation by p190A. Finally, we demonstrate that lowARHGAP35expression is associated with shorter survival in patients with high, but not low, transcript levels ofTJP2encoding ZO-2. Hence, we define a tumor suppressor interactome of p190A that includes ZO-2, an established constituent of the Hippo pathway, and RasGAP, which despite strong association with Ras signaling, is essential for p190A to activate LATS kinases.
Multiple mechanisms contribute to isolation-by-environment in the redheaded pine sawfly,Neodiprion lecontei
Authors: Bagley Robin K. , Hurst Melanie N. , Frederick Jeremy , Wolfe Jordan , Terbot John W. , Frost Christopher J. , Linnen Catherine R. 
Published: May 2023

AbstractIsolation by environment (IBE) is a population genomic pattern that arises when ecological barriers reduce gene flow between populations. Although current evidence suggests IBE is common in nature, few studies have evaluated the underlying mechanisms that generate IBE patterns. In this study, we evaluate five proposed mechanisms of IBE (natural selection against immigrants, sexual selection against immigrants, selection against hybrids, biased dispersal, environment-based phenological differences) that may give rise to host-associated differentiation within a sympatric population of the redheaded pine sawfly,Neodiprion lecontei, a species for which IBE has previously been detected. We first characterize the three pine species used byN. leconteiat the site, finding morphological and chemical differences among the hosts that could generate divergent selection on sawfly host-use traits. Next, using morphometrics and ddRAD sequencing, we detect modest phenotypic and genetic differentiation among sawflies originating from different pines that is consistent with recent,in situdivergence. Finally, via a series of laboratory assays – including assessments of larval performance on different hosts, adult mate and host preferences, hybrid fitness, and adult eclosion timing – we find evidence that multiple mechanisms contribute to IBE inN. lecontei. Overall, our results suggest IBE can emerge quickly, possibly due to multiple mechanisms acting in concert to reduce migration between different environments.
One size does not fit all: Family specific differences in seasonal patterns of abundance and behavior in butterfly communities
Authors: Hirzel Grace E. , Anderson Ashlyn E. , Westerman Erica L. 
Published: May 2023

AbstractAnimal communities can undergo seasonal shifts in assemblage, responding to changes in their environment. Animal behavior can also shift due to seasonal environmental variation, with the potential to shape ecosystems. However, it is unclear if similar environmental factors and time scales affect both abundance and behavior. We examined how butterfly abundance and behavior change seasonally in temperate prairies and a butterfly garden, and if the factors driving variation differ between taxonomic families. We conducted monthly abundance surveys year-round and biweekly abundance and behavior surveys during the summer and fall, in 2017-2021 and 2018-2020 respectively. We also determined how ambient light, temperature, precipitation, and time of year interact to affect butterfly abundance and behavior. We found increased temperature and light levels correlate with increases in general butterfly abundance. Unlike the greater community, Lycaenidae abundance decreased as weekly precipitation increased, and Papilionidae abundance did not respond to changes in environmental factors. Only Nymphalidae changed behavior in response to environmental factors, increasing thermoregulatory behaviors as temperature and light levels decreased. These results indicate that lineages may differ in their sensitivity to environmental factors, which could result in disproportionate changes in their abundances in response to future climate change and anthropogenic-driven disturbance.