bluuebunny/crossref_metadata_2025_split huggingface dataset:
Robust inference of historical human generation times
Authors: Wang Richard J. , Rogers Jeffrey , Hahn Matthew W. 
Published: July 2023

AbstractRagsdale and Thornton (2023) raise concerns about our recent estimates of historical human generation times, concluding that our results were “predominantly driven by nonbiological artifacts.” While we believe these authors have pointed out several important sources of uncertainty, we show here that their main concerns are either not relevant to our study or support our conclusions as much as they cast doubt on them. In particular, the demographic simulations carried out by Ragsdale and Thornton assume all individuals with recent African ancestry are from West Africa, which is not appropriate for our sample. In contrast to the lack of visual concordance between predictions and data cited by these authors as evidence for a lack of fit, we demonstrate that our model provides a good statistical fit to data on the overall historical mutation spectrum, though one particular mutation type is an outlier. Furthermore, we show that the historical generation times inferred when using alternative methods for estimating the ages of individual alleles are largely in agreement with our results, particularly so when using results from Relate. Importantly, these analyses, as well as recent work from an independent group, confirm the idea that a model built onde novomutations and applied to polymorphism data provides useful and reliable estimates of generation times in widely distant mammals.
Epigenetic insights into neuropsychiatric and cognitive symptoms in Parkinson’s disease: A DNA co-methylation network analysis
Authors: Harvey Joshua , Smith Adam R. , Weymouth Luke S. , Smith Rebecca G. , Castanho Isabel , Hubbard Leon , Creese Byron , Bresner Kate , Williams Nigel , Pishva Ehsan , Lunnon Katie 
Published: July 2023

AbstractParkinson’s disease is a highly heterogeneous disorder, encompassing a complex spectrum of clinical presentation including motor, sleep, cognitive and neuropsychiatric symptoms. We aimed to investigate genome-wide DNA methylation networks in post-mortem Parkinson’s disease brain samples and test for region-specific association with common neuropsychiatric and cognitive symptoms. Of traits tested, we identify a co-methylation module in the substantia nigra with significant correlation to depressive symptoms and with ontological enrichment for terms relevant to neuronal and synaptic processes. Notably, expression of the genes annotated to the methylation loci present within this module are found to be significantly enriched in neuronal subtypes within the substantia nigra. These findings highlight the potential involvement of neuronal-specific changes within the substantia nigra with regard to depressive symptoms in Parkinson’s disease.
A Novel Genome Optimization Tool for Chromosome-Level Assembly across Diverse Sequencing Techniques
Authors: Chuang Wei-Hsuan , Cheng Hsueh-Chien , Chang Yu-Jung , Fu Pao-Yin , Huang Yi-Chen , Hsieh Ping-Heng , Chen Shu-Hwa , Kwok Pui-Yan , Lin Chung-Yen , Ho Jan-Ming 
Published: July 2023

AbstractThis paper introduces a novel genome assembly optimization tool named LOCLA, which stands for “Local Optimization for Chromosome-Level Assembly”. It identifies reads and contigs aligned locally with high quality on gap flanks or scaffold boundaries of draft assemblies for gap filling and scaffold connection. LOCLA applies to both de novo and reference-based assemblies. It can also utilize reads produced by diverse sequencing techniques, e.g., 10x Genomics (10xG) Linked-Reads, and PacBio HiFi reads.We validated LOCLA on three human samples and one non-model organism. For the first two human samples, LLD0021C and CHM13, we generated de novo draft assemblies from 10xG Linked-Reads. On LLD0021C, LOCLA improves the draft assembly by adding 23.3 million bases using only 10xG Linked-Reads. These additional bases cover 28,746 protein-coding regions, particularly in pericentromeric and telomeric regions. On the CHM13 sample, we took 10xG Linked-Reads and PacBio HiFi reads as input. As a result, LOCLA added 46.2 million bases to the draft assembly. The increased content enables us to identify genes linked to complex diseases (e.g., ARHGAP11A) and critical biological pathways. We created two reference-guided draft assemblies on the third human sample, HG002, using contigs assembled from PacBio HiFi reads. LOCLA enhances the two draft assemblies by recovering 27.9 million bases (22.26%) and 35.7 million bases (30.93%) of the sequences discarded by the reference-guided assembly tool. The results indicate the robustness of LOCLA’s contig detection algorithm on gap flanks. Furthermore, we show that 95% of the sequences filled in by LOCLA have over 80% accuracy compared with the HG002 reference genome published by the Human Pan-genome Reference Consortium. On the non-model organism, LOCLA enhanced the genome assembly of Bruguiera sexangula (JAHLGP000000000) by decreasing 41.4% of its gaps and raising the Benchmarking Universal Single-Copy Orthologs (BUSCO) analysis score to 98.10%.LOCLA can optimize de novo and reference-guided assemblies using varied sequencing reads. The final assemblies produced by LOCLA have improved in both quantity and quality. The increased gene content may provide a valuable resource in advancing personalized medicine.
A molecular toolbox to study progesterone receptor signaling
Authors: Aarts Marleen T. , Wagner Muriel , van der Wal Tanne , van Boxtel Antonius L. , van Amerongen Renée 
Published: July 2023

AbstractProgesterone receptor (PR) signaling is required for mammary gland development and homeostasis. A major bottleneck in studying PR signaling is the lack of sensitive assays to measure and visualize PR pathway activity both quantitatively and spatially. Here, we develop new tools to study PR signaling in human breast epithelial cells. First, we generate optimized Progesterone Responsive Element (PRE)-luciferase constructs and demonstrate that these new reporters are a powerful tool to quantify PR signaling activity across a wide range of progesterone concentrations in two luminal breast cancer cell lines, MCF7 and T47D. We also describe a fluorescent lentiviral PRE-GFP reporter as a novel tool to visualize PR signaling at the single-cell level. Our reporter constructs are sensitive to physiological levels of progesterone. Second, we show that low background signaling, and high levels of PR expression are a prerequisite for robustly measuring PR signaling. Increasing PR expression by transient transfection, stable overexpression in MCF7 or clonal selection in T47D, drastically improves both the dynamic range of luciferase reporter assays, and the induction of endogenous PR target genes as measured by qRT-PCR. We find that the PR signaling response differs per cell line, target gene and hormone concentration used. Taken together, our tools allow a more rationally designed approach for measuring PR signaling in breast epithelial cells.
Physical fitness and motor competence performance characteristics of elite Chinese youth athletes from four track and field throwing disciplines – a cross sectional study
Authors: Zhao Kewei , Siener Maximilian , Zhao Yifan , Hohmann Andreas 
Published: July 2023

PurposeSystematic athletic training during adolescence may facilitate the development of sport-specific skills and the expression of sport-specific physical characteristics in young athletes. The aim of this study was to differentiate male athletes aged 14-17 years from four different throwing disciplines using anthropomorphic measurements and motor competence performance tests, in order to test whether athletes from different disciplines have physical form and fitness characteristics consistent with the sport-specific demands of each throwing discipline.MethodsThe sample consisted of 289 male youth athletes belonging to the four different throwing disciplines: shot put (n=101), hammer throw (n=16), discus throw (n=63), and javelin throw (n=109). The performance diagnosis comprised three anthropometric measurements, and twelve physical fitness tests. Discriminant analysis and neural network (Multilayer Perceptron) were used to test whether it is possible to discriminate between athletes of the four sports.ResultsThe results of this study show that for male throwing athletes aged 14-17 years, differences in generic anthropometric and sport performance tests distinguish the talent of more than two-thirds of young athletes based on individual sport (DA: 68.7%; MLP: 72.2%), regardless of the classification method used.ConclusionThe relevance of the three anthropometric parameters and twelve physical fitness measures for talent identification and training monitoring in the track and field throwing disciplines was confirmed. The discus throwers had a height advantage, the shot putters and hammer throwers had better arm strength, while the javelin throwers had better explosive strength and sprint speed. All events, except the hammer throwers, showed a high level of explosive power in the medicine ball forward or backward throw test. This was particularly important for the shot put and discus athletes.
Development of selection strategies for genetic improvement in production traits of Mecheri sheep based on a Bayesian multi trait evaluation
Authors: Balasundaram Balakrishnan , Muralidharan Jaganadhan , Murali Nagarajan , Cauveri Doraiswamy , Raja Angamuthu , Okpeku Moses , Thiruvenkadan Aranganoor Kannan 
Published: July 2023

AbstractThe progression of genetic selection techniques to enhance farm animal performance traits is guided by the present level of genetic variation and maternal impact in each trait, as well as the genetic association between traits. This study was conducted on a population of Mecheri sheep maintained from 1980 to 2018 at Mecheri Sheep Research Station, Pottaneri, India, to determine variance and covariance components, as well as genetic parameters for various production performance traits. The production traits of Mecheri sheep assessed include: birth weight (BW), weaning weight (WW), six-month weight (SMW), nine-month weight (NMW) and yearling weight (YW). The Bayesian approach using the Gibbs sampler analyzed six animal models with different combinations of additive direct and maternal additive effects was used. Direct genetics, maternal genetics and residual effects models were the major significantly contributors to total phenotypic variation for all the production traits studied. Direct heritability estimates of birth weight, WW, SMW, NMW and YW were 0.25, 0.20, 0.12, 0.14 and 0.13, respectively. The maternal heritability estimated for BW, WW, SMW, NMW and YW were 0.17, 0.10, 0.12, 0.14 and 0.14, respectively. The maternal effects had a major impact on the pre-weaning production traits. The genetic correlations estimated between different pairs of production traits studied ranged from 0.19 to 0.93. The body weight at birth exhibited higher genetic relationship with weaning weight than post-weaning growth characteristics, and the genetic correlation between weaning weight and post-weaning attributes was moderate to high (0.52 to 0.72). Based on the additive genetic variance in weaning weight and the correlation estimates of weaning weight with post-weaning traits, the weaning weight was proposed as a selection criterion for improving growth traits in Mecheri sheep.
Mitochondrial dysfunction underlies impaired neurovascular coupling following traumatic brain injury
Authors: van Hameren Gerben , Muradov Jamil , Minarik Anna , Aboghazleh Refat , Orr Sophie , Cort Shayna , Andrews Keiran , McKenna Caitlin , Pham Nga Thy , MacLean Mark A. , Friedman Alon 
Published: July 2023

AbstractTraumatic brain injury (TBI) involves an acute injury (primary damage), which may evolve in the hours to days after impact (secondary damage). Seizures and cortical spreading depolarization (CSD) are metabolically demanding processes that may worsen secondary brain injury. Metabolic stress has been associated with mitochondrial dysfunction, including impaired calcium homeostasis, reduced ATP production, and elevated ROS production. However, the association between mitochondrial impairment and vascular function after TBI is poorly understood. Here, we explored this association using a rodent closed head injury model. CSD resulted in neurobehavioral decline after TBI. Craniotomy was performed to elicit CSD via electrical stimulation or to induce seizures via 4-aminopyridine application. We measured vascular dysfunction following CSDs and seizures in TBI animals using laser doppler flowmetry. We observed a more profound reduction in local cortical blood flow in TBI animals compared to healthy controls. Following TBI, CSD resulted in mitochondrial dysfunction and pathological signs of increased oxidative stress adjacent to the vasculature. We explored these findings further using electron microscopy and found that TBI and CSDs resulted in vascular morphological changes and mitochondrial cristae damage in astrocytes, pericytes and endothelial cells. Overall, we provide evidence that CSDs induce mitochondrial dysfunction, impaired cortical blood flow, and neurobehavioral deficits in the setting of TBI.HighlightsCortical spreading depolarization after TBI causes behavioral decline in rats.Vasoconstriction and oligemia after cortical spreading depolarization is worse in TBI brains.Spreading depolarization causes impaired mitochondrial function.TBI and spreading depolarization result in constricted vessels and increased pericyte size.TBI and spreading depolarization result in mitochondrial damage in vascular cells.Graphical abstract
The balance between shear flow and extracellular matrix in ovarian cancer-on-chip
Authors: Chen Changchong , Boché Alphonse , Lopez Elliot , Peng Juan , Carreiras Franck , Schanne-Klein Marie-Claire , Chen Yong , Lambert Ambroise , Aimé Carole 
Published: July 2023

AbstractOvarian cancer is the most lethal gynecologic cancer in developed countries. Silent onset of the metastatic activity of ovarian tumor cells is factor for poor outcomes. In the tumor microenvironment, the extracellular matrix (ECM) and flow shear stress are known to play key roles in directing cell invasion. Hence, acute and tunable tools are critical to mimic scaffold and fluid for building clinically relevantin vitromodels. We have built an ovarian tumor-on-chip where tunable ECM models are easily seeded with tumor spheroids and integrated within a microfluidic chip. This allows the investigation of the crosstalk between the characteristics of the ECM models and shear stress on the migratory behavior and cellular heterogeneity of ovarian tumor cells. We vary the composition of the ECM playing with type I and IV collagens and laminin, and control the shear stress in the chip. This work shows that in the shear stress regime of the peritoneal cavity, the ECM plays a major role in driving individual or collective modes of migration. In the presence of basement membrane proteins, migration is more collective that on type I collagen regardless of shear stress level. In addition, with increasing shear stress, individual cell migration was enhanced, while no significant impact on collective migration could be measured. This highlights our ability to discriminate relevant parameters for onset and shifts of cell behavior using our in vitro models. Furthermore, we described the ability to shift cells from an epithelial phenotype to a more mesenchymal phenotype, which could allow us to describe the role of these parameters during epithelial-to-mesenchymal (EMT) transition as a continuous process. Finally, we conclude that the ECM should hold a central position inin vitrocancer models, to understand cell response and develop platforms for therapeutic development.
Detection and localization of conspecifics in ghost knifefish are influenced by the relationship between the spatial organization of receptors and signals
Authors: Ramachandra Keshav L , Milam Oak E , Pedraja Federico , Cornett Jenna , Marsat Gary 
Published: July 2023

ABSTRACTThe detection and localization of signals relies on arrays of receptors and their spatial organization plays a key role in setting the accuracy of the system. Electrosensory signals in weakly electric ghost knifefish are captured by an array of receptors covering their body. While we know that spatial resolution for small objects, such as prey, is enhanced near the head due to a high receptor density, it is not clear how receptor organization influences the processing of global and diffuse signals from conspecifics. We investigated the detection and localization accuracy for conspecific signals and determined how they are influenced by the organization of receptors. To do so we modeled the signal, its spatial pattern as it reaches the sensory array, and the responses of the heterogeneous population of receptors. Our analysis provides a conservative estimate of the accuracy of detection and localization (specifically azimuth discrimination) of a conspecific signal. We show that beyond 20 cm the conspecific signal is less than a few percent the strength of the baseline self-generated signal. As a result, detection and localization accuracy decreases quickly for more distant sources. Detection accuracy at distances above 40 cm decreases rapidly and detection at the edge of behaviorally observed ranges might require attending to the signal for several seconds. Angular resolution starts to decrease at even shorter distances (30 cm) and distant signals might require behavioral or neural coding mechanisms that have not been considered here. Most importantly, we show that the higher density of receptors rostrally enhances detection accuracy for signal sources in front of the fish, but contributes little to the localization accuracy of these conspecific signals. We discuss parallels with other sensory systems and suggest that our results highlight a general principle. High receptor convergence in systems with spatially diffuse signals contributes to detection capacities, whereas in systems with spatially delineated signals, receptor density is associated with better spatial resolution.
Sensory symptoms across the lifespan in people with cerebral palsy
Authors: Lyons-Warren Ariel M , Guez-Barber Danielle , Thomas Sruthi P. , Tantry Evelyne K , Mahat Aditya , Aravamuthan Bhooma ,   Cerebral Palsy Research Network
Published: July 2023

Structured AbstractAIMTo estimate prevalence of sensory symptoms in people with cerebral palsy (CP) across the lifespan.METHODIn this cross-sectional study, the self-reported Sensory Processing Scale Inventory (SPS-I) was administered via REDCap between 2/1/22 and 8/15/22 to people with CP or their caregivers enrolled in the online MyCP Community Registry. We determined the association between SPS-I scores and age (Pearson correlation) and functional status as assessed using five validated functional classification systems for CP (ANOVA). We hypothesized that sensory symptoms would differ between younger and older individuals with CP.RESULTSOf 155 responses (28% response rate, age 1-76 years, 34% male), 97% reported at least one bothersome sensory symptom. Total sensory symptoms decreased with age (R2=0.12, p<0.0001), driven by decreases in hyposensitivity symptoms (R2=0.32, p<0.0001), primarily tactile hyposensitivity (R2=0.29, p<0.0001). Sensory symptoms increased with greater functional impairment across all functional domains (ANOVA, p<0.0001). However, the age-specific decrease in hypo-sensitivities was most pronounced in people with the greatest gross motor functional impairment (R2=0.70, p=0.0004).INTERPRETATIONOur findings suggest that hypo-sensitivity, primarily tactile sensitivity, decreases with age in people with CP. Future work should assess whether decreased hyposensitivity contributes to other age-related changes in CP like increased pain.What this paper addsIndividuals with CP exhibit both hyper- and hypo-sensitivity across all sensory modalitiesHyposensitivity decreases with age in people with CP, independent of GMFCS levelLess hyposensitivity correlates with greater functional ability in people with CPOf all sensory modalities, tactile hyposensitivity correlates most strongly with age.
A Natural Language Processing Algorithm for Classifying Suicidal Behaviors in Alzheimer’s Disease and Related Dementia Patients: Development and Validation Using Electronic Health Records Data
Authors: Zandbiglari Kimia , Hasanzadeh Hamid Reza , Kotecha Pareeta , Sajdeya Ruba , Goodin Amie J , Jiao Tianze , Adiba Farzana I , Mardini Mamoun T. , Bian Jiang , Rouhizadeh Masoud 
Published: July 2023

ABSTRACTThis study aimed to develop a natural language processing algorithm (NLP) using machine learning (ML) and Deep Learning (DL) techniques to identify and classify documentation of suicidal behaviors in patients with Alzheimer’s disease and related dementia (ADRD). We utilized MIMIC-III and MIMIC-IV datasets and identified ADRD patients and subsequently those with suicide ideation using relevant International Classification of Diseases (ICD) codes. We used cosine similarity with ScAN (Suicide Attempt and Ideation Events Dataset) to calculate semantic similarity scores of ScAN with extracted notes from MIMIC for the clinical notes. The notes were sorted based on these scores, and manual review and categorization into eight suicidal behavior categories were performed. The data were further analyzed using conventional ML and DL models, with manual annotation as a reference. The tested classifiers achieved classification results close to human performance with up to 98% precision and 98% recall of suicidal ideation in the ADRD patient population. Our NLP model effectively reproduced human annotation of suicidal ideation within the MIMIC dataset. These results establish a foundation for identifying and categorizing documentation related to suicidal ideation within ADRD population, contributing to the advancement of NLP techniques in healthcare for extracting and classifying clinical concepts, particularly focusing on suicidal ideation among patients with ADRD. Our study showcased the capability of a robust NLP algorithm to accurately identify and classify documentation of suicidal behaviors in ADRD patients.