bluuebunny/crossref_metadata_2025_split huggingface dataset:
Convolutional neural network models of the primate retina reveal adaptation to natural stimulus statistics
Authors: Vystrčilová Michaela , Sridhar Shashwat , Burg Max F. , Gollisch Tim , Ecker Alexander S. 
Published: March 2024

AbstractThe diverse nature of visual environments demands that the retina, the ﬁrst stage of the visual system, encodes a vast range of stimuli with various statistics. The retina adapts its computations to some speciﬁc features of the input, such as brightness, contrast or motion. However, it is less clear whether it also adapts to the statistics of natural scenes compared to white noise, the latter of which is often used to infer models of retinal computation. To address this question, we analyzed neural activity of retinal ganglion cells (RGCs) in response to both white noise and naturalistic movie stimuli. We performed a systematic comparative analysis of traditional linear-nonlinear (LN) and recent convolutional neural network (CNN) models and tested their generalization across stimulus domains. We found that no model type trained on one stimulus ensemble was able to accurately predict neural activity on the other, suggesting that retinal processing depends on the stimulus statistics. Under white noise stimulation, the receptive ﬁelds of the neurons were mostly lowpass, while under natural image statistics they exhibited a more pronounced surround resembling the whitening ﬁlters predicted by efficient coding. Together, these results suggest that retinal processing dynamically adapts to the stimulus statistics.
Sexual Dimorphism in Age-Dependent Neurodegeneration After Mild Head Trauma inDrosophila: Unveiling the Adverse Impact of Female Reproductive Signaling
Authors: Ye Changtian , Ho Ryan , Moberg Kenneth H. , Zheng James Q. 
Published: March 2024

ABSTRACTEnvironmental insults, including mild head trauma, significantly increase the risk of neurodegeneration. However, it remains challenging to establish a causative connection between early-life exposure to mild head trauma and late-life emergence of neurodegenerative deficits, nor do we know how sex and age compound the outcome. Using aDrosophilamodel, we demonstrate that exposure to mild head trauma causes neurodegenerative conditions that emerge late in life and disproportionately affect females. Increasing age-at-injury further exacerbates this effect in a sexually dimorphic manner. We further identify Sex Peptide (SP) signaling as a key factor in female susceptibility to post-injury brain deficits. RNA sequencing highlights a reduction in innate immune defense transcripts specifically in mated females during late life. Our findings establish a causal relationship between early head trauma and late-life neurodegeneration, emphasizing sex differences in injury response and the impact of age-at-injury. Finally, our findings reveal that reproductive signaling adversely impacts female response to mild head insults and elevates vulnerability to late-life neurodegeneration.
A truncation mutant of adenomatous polyposis coli (APC) impairs apical cell extrusion through elevated epithelial tissue tension
Authors: Gan Wan J. , Giri Rabina , Begun Jakob , Abud Helen E. , Hardeman Edna C. , Gunning Peter W. , Yap Alpha S. , Noordstra Ivar 
Published: March 2024

ABSTRACTTissue tension encompasses the mechanical forces exerted on solid tissues within animal bodies, originating from various sources such as cellular contractility, interactions with neighbouring cells and the extracellular matrix. Emerging evidence indicates that an imbalance in tissue tension can influence structural organisation, homeostasis and potentially contribute to disease. For instance, heightened tissue tension can impede apical cell extrusion, leading to the retention of apoptotic or transformed cells. In this study, we investigate the potential role of adenomatous polyposis coli (APC) in modulating tissue tension. Our findings reveal that expression of an APC truncation mutant elevates epithelial tension via the RhoA/ROCK pathway. This elevation induces morphological alterations and hampers apoptotic cell extrusion in cultured epithelial cells and organoids, both of which could be mitigated by pharmacologically restoring the tissue tension. This raises the possibility that APC mutations may exert pathogenetic effects by altering tissue mechanics.
Graph connection Laplacian allows for enhanced outcomes of consumer camera based photoplethysmography imaging
Authors: Borik Stefan , Wu Hau-Tieng , Shelley Kirk H. , Alian Aymen A. 
Published: March 2024

AbstractObjectThis work introduces a novel method to minimize the effect of global phase deviation that is inherent in photoplethysmographic images (PPGI) captured by video.MethodWe analyzed the facial vascular network obtained from a consumer camera as a two-dimensional manifold. Subtle phase variations across skin sites are due to complex dynamics of the vascular tree. Utilizing PPGI, the phase is modeled as a vector field of the facial manifold. The phase variations over different skin sites are caused by different blood volume modulations. We propose using the Graph Connection Laplacian (GCL) technique to quantify the global phase deviation, with the hope that correcting for this deviation could improve the quality of the PPGI signal. It is also postulated that study of this phase deviation might reveal valuable anatomical and physiological information.ResultThe proposed algorithm appears to yield a higher-quality global PPGI signal. By correcting the global phase deviation estimated by GCL waveform features such as the dicrotic notch are emphasized. The perfusion map, with the global phase deviation (estimated by GCL as intensity), appears to reflect skin perfusion dynamics.ConclusionThis algorithm enhances the quality of the global PPGI signal, facilitating the analysis of morphological parameters and showing promise for advancing PPGI applications in scientific research and clinical practice.
Zapping the brain to enhance sport performance? Evidence from an umbrella review of the effect of transcranial direct current stimulation on physical performance
Authors: Holgado Darías , Sanabria Daniel , Vadillo Miguel A. , Román-Caballero Rafael 
Published: March 2024

AbstractConcepts such as "neuro-doping" or brain doping have contributed to an expansion in the area of transcranial direct current stimulation (tDCS) and its impact over exercise and physical performance in recent years. Here we assess the evidence supporting the healthy population using an umbrella review of meta-analyses investigating the role of tDCS to enhance exercise performance. We identified 9 meta-analyses encompassing 50 crossover studies and 683 participants that met our inclusion criteria. Despite the fact that most meta-analyses reported a positive effect of tDCS, our analyses revealed overly low statistical power in the primary studies, publication bias, and large variability in pre-processing and analytic decisions. Indeed, a specification-curve analysis showed that the final effect could range fromg= −0.23 tog= 0.33, depending on decisions such as the formula used for estimating the effect size and multiple additional analytic steps. Moreover, a meta-analysis of all the primary studies included in the umbrella review showed a small effect of tDCS (gz= 0.28, 95%CI [0.18, 0.39]) that became substantially smaller and inconclusive after accounting for publication bias,grm= 0.10, 95%CrI [−0.04, 0.20],BF10= 0.99. In summary, our findings highlight that current evidence, from both individual studies and meta-analyses, does not conclusively support the idea that tDCS enhances performance outcomes.
Lipoprotein(a) testing in Patients with Atherosclerotic Cardiovascular Disease in Five Large U.S. Health Systems
Authors: Shah Nishant P. , Mulder Hillary , Lydon Betsy , Chiswell Karen , Hu Xingdi , Lampron Zachary , Cohen Lauren , Patel Manesh R. , Taubes Susan , Song Wenliang , Mulukutla Suresh R. , Saeed Anum , Morin Daniel P. , Bradley Steven M. , Hernandez Adrian F. , Pagidipati Neha J. 
Published: March 2024

AbstractIntroductionLipoprotein (a) [Lp(a)] is an independent, causal risk factor for atherosclerotic cardiovascular disease (ASCVD). However, testing patterns remain variable and it is unclear what patient level factors are associated with Lp(a) testing, and if testing changes clinical management.MethodsA retrospective study using electronic medical record data from five health systems in the CardioHealth Alliance identified an ASCVD cohort that was divided into those with a Lp(a) test and those without a Lp(a) test between 2019-2021. Baseline characteristics and initiation of lipid lowering therapy (LLT) was assessed. Multivariable regression modeling was used to determine factors associated with Lp(a) testing.ResultsAmong 595,684 ASCVD patients, only 2,587 (0.4%) were tested for Lp(a) between 2019 and 2021. In adjusted models, those who were older or Black were less likely to have Lp(a) testing, while those with familial hypercholesterolemia, ischemic stroke/TIA, PAD, prior LLT, or LDL-C ≥130mg/dL were more likely to be tested. Those with a Lp(a) test, regardless of the Lp(a) value, were more frequently initiated on any statin therapy (30.3% vs. 10.6%, p<0.001), ezetimibe (7.65 vs. 0.8%, p <0.001), or PCSK9i (6.7% vs. 0.3%, p <0.001) compared with those without a test. Those with an elevated Lp(a) level more frequently initiated ezetimibe (11.5% vs. 5.9%, P <0.001) or PCSK9i (10.9% vs. 4.8%, P <0.001), but not statin therapy.ConclusionsLp(a) testing in ASCVD patients is infrequent, with evidence of disparities among older or Black individuals. Testing for Lp(a), regardless of level, is associated with greater initiation of any LLT, while elevated Lp(a) is associated with greater initiation of non-statin LLT. Overall, initiation of LLT remained low, despite guideline indications for LLT in ASCVD patients. There is a critical need for multidisciplinary and inclusive approaches to raise awareness for Lp(a) testing and its implications on management.
Setting up a Hospital Based Diarrhoea Surveillance System in a Low- and Middle-Income Country: Lessons Learned
Authors: Miti Sam , Chisenga Caroline C , Mubanga Cynthia , Msimuko Lusungu , Manda Chipo , Zulu Catherine , Kalaba Naomi Muleba , Niyongabo Christian Musilikare , Chisapi Lydia , Thole David , Nachamba Mwizukanji , Moono Roy , Chakopo Moses , Chibwe Dorcas , Kabungo Theresa , Chibesa Kayayi , Nanyangwe Vivian , Nduna Bwendo , Chongwe Gershom , Chileshe Justine , Cohen Dani , Chilengi Roma , Siziya Seter , Simuyandi Michelo 
Published: March 2024

AbstractBackgroundAcute diarrhoea is a major cause of morbidity and mortality among children in low-resource settings. Establishing effective surveillance systems is crucial for monitoring and responding to diarrhoeal outbreaks.ObjectiveThis manuscript presents the lessons learned during the setup of a hospital-based diarrhoea surveillance system at Arthur Davison Children’s Hospital in Ndola, Zambia. Specifically, the reasons for the delays in processing stool samples from collection to reporting of laboratory results were explored.MethodsThe setup of the surveillance system involved several key steps, including stakeholder engagement, training of healthcare workers, development of data collection tools, and establishment of reporting mechanisms. The system aims to capture data on diarrhoea cases admitted to the hospital, including demographic information, clinical presentation and laboratory results.ResultsNumerous obstacles were encountered during the implementation of the surveillance. There were three points of delay identified in the ADCH diarrhoea sample handling process from collection to processing: 1) Stool sample collection and packaging 2) Sample transfer from the clinical area to the laboratory 3) Handling and processing in the laboratory. Gaps identified in the three delays related to 1) Staff attitudes and perceptions 2) Health systems infrastructure 3) Operational issues 4) Data management. The following key elements are recommended for setting up a robust, locally owned diarrhoea surveillance system: Implementation of cross-cutting intervention across domains, and a human-centered approach targeted at behavioral change, creating local leadership and ownership of surveillance activities, systematic capacity building through ongoing training/orientation/local data sharing platforms for healthcare personnel, establishing reliable data collection and reporting procedures, addressing infrastructure limitations, and integrating the surveillance system into existing health information systems.ConclusionWe established a hospital-based diarrhoea surveillance system at ADCH in Ndola, Zambia. Several obstacles were identified and resolved, which provide valuable lessons for future implementing of diarrhoea surveillance systems in low resource settings. Successful implementation requires engaging of hospital and laboratory staff, adaptable and easy to use surveillance tools including entering sample information in an electronic laboratory information system and committed leadership.
WITHDRAWN: Let’s talk about sex: college students’ attitudes towards Sexuality Education in a Spanish University
Authors: Lahoz-García Clara , Jimenez José María , Castro María José , Parejo José-Luis 
Published: March 2024

Withdrawal StatementThe authors have withdrawn this manuscript because since its initial submission, the manuscript has undergone substantial modifications, including an expansion of the study, refinement of the methodology, and revisions to the conclusions. These changes have resulted in a different version of the work, which is now being submitted as an original and unpublished manuscript for peer review in a scientific journal. Given that the preprint no longer reflects the findings and conclusions we stand by, we respectfully request its withdrawal.We fully acknowledge MedRxiv’s policy that preprints remain part of the scientific record and appreciate that the original manuscript will remain accessible with a “Withdrawn” watermark.Therefore, the authors do not wish this work to be cited as reference for the project. If you have any questions, please contact the corresponding author.
Estimation equation of limb lean soft tissue mass in Asian athletes using bioelectrical impedance analysis
Authors: Lai Yeong-Kang , Ho Chu-Ying , Huang Ai-Chun , Lu Hsueh-Kuan , Hsieh Kuen-Chang 
Published: March 2024

AbstractBackgroundThe lean soft tissue mass (LSTM) of the limbs is approximately 63% of total skeletal muscle mass. For athletes, measurement of limb LSTM is the basis for rapid estimation of skeletal muscle mass. This study aimed to establish the estimation equation of LSTM in Asian athletes using bioelectrical impedance analysis (BIA).MethodsA total of 198 athletes (121 males, 77 females; mean age 22.04 ± 5.57 years) from different sports in Taiwan were enrolled. A modeling group (MG) of 2/3 (n = 132) of subjects and a validation group (VG) of 1/3 (n = 68) were randomly assigned. Resistance (R) and reactance (Xc) were measured using 50KHz current measurement in whole-body mode. Predictor variables were height (h), weight (W), age, gender, Xc, resistance index (RI; RI = h2/ R). LSTM of arms and legs measured by dual-energy X-ray absorptiometry (DXA) was the response variable. Multivariate stepwise regression analysis method was used to establish BIA estimation equations as ArmsLSTMBIA-Asianand LegsLSTMBIA-Asian. Estimation equations performance was confirmed by cross-validation.ResultsEstimation equation “ArmsLSTMBIA-Asian= 0.096 h2/R – 1.132 gender + 0.030 Weight + 0.022 Xc – 0.022 h + 0.905, r2= 0.855, SEE = 0.757 kg, n = 132” and “LegsLSTMBIAAsian= 0.197h2/R” + 0.120 h – 1.242 gender + 0.055 Weight – 0.052 Age + 0.033 Xc –16.136, r2= 0.916, SEE = 1.431 kg, n = 132” were obtained from MG. Using DXA measurement results of VG for correlation analysis and Limit of Agreement (LOA) of Bland-Altman Plot, ArmsLST is 0.924, -1.53 to 1.43 kg, and LegsLST is 0.957, -2.68 to 2.90 kg.ConclusionThe established single-frequency BIA hand-to-foot estimation equation quickly and accurately measures LSTM of the arms and legs of Asian athletes.
Iron status in a representative sample of US pregnant women is not associated with pre-pregnancy BMI: results from the NHANES (1999-2010) study
Authors: Ciulei Mihaela A. , Gallagher Kelly , Ba Djibril , Beck Celeste , Pobee Ruth A. , Gernand Alison D. , Walker Rachel E. 
Published: March 2024

AbstractIron deficiency in pregnancy is related to many poor health outcomes, including anemia and low birth weight. A small number of previous studies have identified maternal body mass index (BMI) as potential risk factors for poor iron status. Our objective was to examine the association between pre-pregnancy BMI and iron status in a nationally representative sample of US adult women. We used data from the National Health and Nutrition Examination Survey (NHANES; 1999-2010) for pregnant women ages 18-49 years (n=1156). BMI (kg/m2) was calculated using pre-pregnancy weight (self-reported) and height (measured at examination). Iron deficiency (ID) was defined as total body iron (calculated from serum ferritin and transferrin receptor using Cook’s equation) < 0 mg/kg and anemia as hemoglobin < 11 g/dL. Associations were examined using weighted Poisson regression models, adjusted for confounders (age, race/ethnicity, education, family income, and trimester). Approximately 14% of pregnant women had ID and 8% had anemia in this sample. There were no differences in the prevalence of ID or anemia in women with pre-pregnancy overweight and obesity (ID: overweight, adjusted prevalence ratio (PR)=1.28, 95%CI: 0.89-1.83; obesity, PR=0.75, 95%CI: 0.39-1.45; anemia: overweight, PR=1.08, 95%CI: 0.53-2.19; obesity, PR=0.99, 95%CI: 0.49-2.01) compared to women with a normal BMI. Findings from these US nationally representative data indicate that iron status in pregnancy does not differ by pre-pregnancy BMI. Since iron deficiency during pregnancy remains a significant public health concern, NHANES should consider measuring current iron status in upcoming cycles.
Advancing Rheumatology Practice: Systematic Review of Natural Language Processing Applications
Authors: Omar Mahmud , Glicksberg Benjamin S. , Reuveni Hagar , Nadkarni Girish N. , Klang Eyal 
Published: March 2024

AbstractBackgroundWith the advent of large language models (LLM), such as ChatGPT, natural language processing (NLP) is revolutionizing healthcare. We systematically reviewed NLP’s role in rheumatology and assessed its impact on diagnostics, disease monitoring, and treatment strategies.MethodsFollowing PRISMA guidelines, we conducted a systematic search to identify original research articles exploring NLP applications in rheumatology. This search was performed in PubMed, Embase, Web of Science, and Scopus until January 2024.ResultsOur search produced 17 studies that showcased diverse applications of NLP in rheumatology, addressing disease diagnosis, data handling, and monitoring.Notably, GPT-4 demonstrated strong performance in diagnosing and managing rheumatic diseases. Performance metrics indicated high accuracy and reliability in various tasks. However, challenges like data dependency and limited generalizability were noted.ConclusionNLP, and especially LLM, show promise in advancing rheumatology practice, enhancing diagnostic precision, data handling, and patient care. Future research should address current limitations, focusing on data integrity and model generalizability.
Multifaceted Representation of Genes via Deep Learning of Gene Expression Networks
Authors: Su Zheng , Fang Mingyan , Smolnikov Andrei , Dinger Marcel E. , Oates Emily C. , Vafaee Fatemeh 
Published: March 2024

AbstractAccurate predictive modeling of human gene relationships would fundamentally transform our ability to uncover the molecular mechanisms that underpin key biological and disease processes. Recent studies have employed advanced AI techniques to model the complexities of gene networks using large gene expression datasets1–11. However, the extent and nature of the biological information these models can learn is not fully understood. Furthermore, the potential for improving model performance by using alternative data types, model architectures, and methodologies remains underexplored. Here, we developed GeneRAIN models by training on a large dataset of 410K human bulk RNA-seq samples, rather than single-cell RNA-seq datasets used by most previous studies. We showed that although the models were trained only on gene expression data, they learned a wide range of biological information well beyond gene expression. We introduced GeneRAIN-vec, a state-of-the-art, multifaceted vectorized representation of genes. Further, we demonstrated the capabilities and broad applicability of this approach by making 4,797 biological attribute predictions for each of 13,030 long non-coding RNAs (62.5 million predictions in total). These achievements stem from various methodological innovations, including experimenting with multiple model architectures and a new ‘Binning-By-Gene’ normalization method. Comprehensive evaluation of our models clearly demonstrated that they significantly outperformed current state-of-the-art models3,12. This study improves our understanding of the capabilities of Transformer and self-supervised deep learning when applied to extensive expression data. Our methodological advancements offer crucial insights into refining these techniques. These innovations are set to significantly advance our understanding and exploration of biology.
Differentiating specific and non-specific protein-metabolite interactions using gradient open port probe electrospray ionization mass spectrometry
Authors: Tian Xiaobo , Hopfgartner Gérard 
Published: March 2024

ABSTRACTNative electrospray ionization mass spectrometry (ESI-MS) using nano ESI or desorption electrospray ionization (DESI) has been widely used to study interactions between macromolecules and ligands, usually protein-metabolite interactions (PMIs). In MS spectra the charge state distributions (CSD) of proteins differ between native and non-native conditions and based on this, we report a method that can differentiate specific protein-metabolite interactions from non-specific binding. Our approach is based on a 3D-printed open port probe electrospray system (gOPP-ESI) using mobile phase gradients (aqueous to methanol) for the ionization of protein/protein-metabolite complex. Notably, we found that a true protein-metabolite complex is more resistant to the denaturing effect of methanol compared to the free protein. This is corroborated by the observation that forming high charge states of protein-metabolite complexes requires higher proportions of methanol than free protein while, for non-specific complexes, there is no obvious difference in the CSD. Therefore, by comparing the changes in the CSD of free protein and protein-metabolite complex versus the increase of methanol, we can distinguish metabolites that specifically interact with the target protein. The approach is evaluated with well-characterized protein-ligand pairs, and we confirmed that cytidine phosphates,N, N′, N″-triacetylchitotriose, and fluvastatin are specific ligands for ribonuclease A, lysozyme, and beta-lactoglobulin respectively. However, cytidine-5’-triphosphate (CTP) interacts non-specifically with lysozyme and beta-lactoglobulin. We believe that after first-round native-MS assays to identify which metabolites cause mass shifts to the free protein, the gOPP-ESI-MS could be used as a quick second-round check to exclude non-specific binding and discover metabolites truly interacting with the protein of interest, reducing the number of candidates for subsequent validation experiments.Abstract Figure