bluuebunny/crossref_metadata_2025_split huggingface dataset:
A New Approach for Discovering Functional Links Connecting Non-Coding Regulatory Variants to Gene Targets
Authors: Farooq Hammad , Du Lin , Delafrouz Pourya , Jiang Wei , Chronis Constantinos , Liang Jie 
Published: June 2024

AbstractGenome-wide association studies (GWAS) have linked thousands of genetic variants to various complex traits or diseases. However, most identified variants have weak individual effects, are correlated with nearby polymorphisms due to linkage disequilibrium (LD), and are located in non-coding cis-regulatory elements (CREs). These characteristics complicate the assessment of the direct impact of each variant on tissue specific gene expression and phenotype. To address this challenge, we have developed a novel algorithm that leverages polymer folding and 3D chromatin interactions to prioritize and identify putative causal variants and their target genes. From the millions of eQTL-Gene pairs identified by GTEx in human somatic tissues, we classify only ∼10-20% as putative functional eQTL-Gene pairs supported by phenotypic associations confirmed through CRISPR deletion experiments. Our findings show that unlike most variants, functional eQTL-Gene pairs predominantly reside within the same topologically associating domain (TAD) and have strong associations with cell-type specific cis-regulatory elements (CREs), enriched for binding sites of tissue-specific transcription factors. Unlike most approaches that rely on linear distance or other chromatin features (histone code, accessibility), our algorithm emphasizes the importance of physical interactions and 3D chromatin folding in gene regulation, as the identified eQTL-Gene pairs are all among the small fraction of physical chromatin interactions sufficient for chromatin locus folding. Overall, our algorithm reduces false positive associations between DNA variants and genes identified by eQTL analysis and uncovers novel variant-gene pair associations. These findings suggest a mechanism where a small number of regulatory variants control tissue specific gene expression via their physical association with target genes confined within the same TAD. Our approach provides new insights into the molecular mechanisms driving GWAS phenotypes.
Microglia target synaptic sites early during excitatory circuit disassembly in neurodegeneration
Authors: Yu Alfred , Tan Li Xuan , Lakkaraju Aparna , Santina Luca Della , Ou Yvonne 
Published: June 2024

SummaryDuring development, microglia prune excess synapses to refine neuronal circuits. In neurodegeneration, the role of microglia-mediated synaptic pruning in circuit remodeling and dysfunction is important for developing therapies aimed at modulating microglial function. Here we analyzed the role of microglia in the synapse disassembly of degenerating postsynaptic neurons in the inner retina. After inducing transient intraocular pressure elevation to injure retinal ganglion cells, microglia increase in number, shift to ameboid morphology, and exhibit greater process movement. Furthermore, due to the greater number of microglia, there is increased colocalization of microglia with synaptic components throughout the inner plexiform layer and with excitatory synaptic sites along individual ganglion cell dendrites. Microglia depletion partially restores ganglion cell function, suggesting that microglia activation may be neurotoxic in early neurodegeneration. Our results demonstrate the important role of microglia in synapse disassembly in degenerating circuits, highlighting their recruitment to synaptic sites early after neuronal injury.HighlightsEarly after transient intraocular pressure elevation:Microglia increase in number, complexity, and process movementMicroglia-synaptic contacts increase in the inner plexiform layerMicroglia-synaptic contacts increase on retinal ganglion cell dendritesMicroglia depletion partially restores ganglion cell function
Unveiling stem cell induction mechanisms from spatiotemporal cell-type-specific gene regulatory networks in postembryonic root organogensis
Authors: Cabrera Javier , Sanchez-Corrionero Álvaro , de Luis Balaguer Angels , Serrano-Ron Laura , del Barrio Cristina , Cubas Pilar , Perez-Garcia Pablo , Sozzani Rosangela , Moreno-Risueno Miguel 
Published: June 2024

SUMMARYPlants grow continuously by developing new organs, a complex process that requires the formation of specific and functional tissue patterns. Tap root systems, as observed inArabidopsis thaliana, undergo lateral root formation, a developmental mechanism that necessitates the establishment of stem cell lineages. However, the underlying mechanisms remain poorly understood. We have reconstructed a spatiotemporal cell-type-specific transcriptional map of early lateral root organogenesis in Arabidopsis, profiling single and double fluorescent markers across 8 different cell types in the root stem cell lineage. Employing dynamic Bayesian network inference, based on time-course experiments and developmental time, alongside tree-based methods, we investigated lineage developmental progression and precursor stem-cell specification. Our results reveal a morphogenic cascade of hierarchical interdependent transcription factors driving stem cell initiation, and identify the QC/Endodermis transitioning cells as root stem cell progenitors. The associated formative program involves a profound transcriptomic re-arrangement, which, remarkably, precedes the activation of known stem-cell transcriptional signatures. Our data support a model in which root-stem-cell networks do not initiate stem formation, although various stem cell regulators are involved. Collectively, our study identifies core transcriptional signatures associated with stem cell induction and elucidates the dynamic regulatory mechanism driving early stem cell lineage establishment.
Flow-Mediated Modulation of the Endothelial Cell Lipidome
Authors: Hong Soon-Gook , Kennelly John P. , Williams Kevin J. , Bensinger Steve J. , Mack Julia J. 
Published: June 2024

ABSTRACTThe luminal surface of the endothelium is exposed to dynamic blood flow patterns that are known to affect endothelial cell phenotype. While many studies have documented the phenotypic changes by gene or protein expression, less is known about the role of blood flow pattern on the endothelial cell (EC) lipidome. In this study, shotgun lipidomics was conducted on human aortic ECs (HAECs) exposed to unidirectional laminar flow (UF), disturbed flow (DF), or static conditions for 48 hrs. A total of 520 individual lipid species from 17 lipid subclasses were detected. Total lipid abundance was significantly increased for HAECs exposed to DF compared to UF conditions. Despite the increase in the total lipid abundance, HAECs maintained equivalent composition of each lipid subclass (% of total lipid) under both DF and UF. However, by lipid composition (% of total subclass), 28 lipid species were significantly altered between DF and UF. Complimentary RNA sequencing of HAECs exposed to UF or DF revealed changes in transcripts involved in lipid metabolism. Shotgun lipidomics was also performed on HAECs exposed to pro-inflammatory agonists lipopolysaccharide (LPS) or Pam3CSK4 (Pam3) for 48 hrs. Exposure to LPS or Pam3 reshaped the EC lipidome in both unique and overlapping ways. In conclusion, exposure to flow alters the EC lipidome and ECs undergo stimulus-specific lipid reprogramming in response to pro-inflammatory agonist exposure. Ultimately, this work provides a resource to profile the transcriptional and lipidomic changes that occur in response to applied flow that can be accessed by the vascular biology community to further dissect and extend our understanding of endothelial lipid biology.
ANTIMICROBIAL ACTIVITY OF CLOVE EXTRACTS AGAINST MICROORGANISMS ISOLATED FROM VAGINAL DISCHARGE
Authors: Omoniyi Aishat Taiye , Yaqub Muneer 
Published: June 2024

ABSTRACTInfections of the genitourinary and reproductive tracts pose significant health concerns for women, particularly those of reproductive age. These infections often manifest as vaginal discharge and can be caused by a variety of microorganisms, including pathogenic bacteria and fungi. Traditional antibiotic treatments are increasingly challenged by the rise of antibiotic-resistant strains, underscoring the need for alternative therapies. This study aimed to isolate and identify microorganisms from vaginal swab samples and evaluate the antimicrobial efficacy of clove (Eugenia caryophyllata) extracts against these isolates. Using CLED agar, nutrient agar, and Sabouraud dextrose agar, a diverse range of bacterial and fungal flora were isolated from eight vaginal swab samples. The primary bacterial isolates included Proteus mirabilis, Escherichia coli, Staphylococcus aureus, and Lactobacillus spp., while Candida albicans was the main fungal isolate. Biochemical tests confirmed the identity of these microorganisms. The study found that ethanol clove extract exhibited significant antimicrobial activity, particularly against Staphylococcus aureus and Candida albicans, with the minimum inhibitory concentration (MIC) values being 20 mg/ml and 10 mg/ml, respectively. Additionally, ciprofloxacin, used as a control antibiotic, showed maximum inhibition against Lactobacillus spp., highlighting a potential risk for disrupting beneficial vaginal flora when using conventional antibiotics. The findings suggest that ethanol clove extract could serve as an effective alternative antimicrobial agent, reducing the risk of antibiotic resistance and preserving the balance of the vaginal microbiome. This research emphasizes the importance of exploring plant-based antimicrobial agents as viable alternatives to traditional antibiotics. The significant antimicrobial properties of clove extract against common vaginal pathogens offer promising implications for future therapeutic applications in managing vaginal infections.
Expanding salivary biomarker detection by creating a synthetic neuraminic acid sensor via chimeragenesis
Authors: Verzino Samuel J. , Priyev Sharona A. , Estrada Valeria A. Sánchez , Crowley Gemma X. , Rutkowski Alexandra , Lam Amelia C. , Nazginov Elizabeth S. , Kotemelo Paola , Bacelo Agustina , Sukhram Desiree T. , Vázquez Frank X. , Juárez Javier F. 
Published: June 2024

ABSTRACTAccurate and timely diagnosis of oral squamous cell carcinoma (OSCC) is crucial in preventing its progression to advanced stages with a poor prognosis. As such, the construction of sensors capable of detecting previously established disease biomarkers for the early and non-invasive diagnosis of this and many other conditions has enormous therapeutic potential. In this work, we apply synthetic biology techniques for the development of a whole-cell biosensor (WCB) that leverages the physiology of engineered bacteriain vivoto promote the expression of an observable effector upon detection of a soluble molecule. To this end, we have constructed a bacterial strain expressing a novel chimeric transcription factor (Sphnx) for the detection of N-acetylneuraminic acid (Neu5Ac), a salivary biomolecule correlated with the onset of OSCC. This WCB serves as the proof-of-concept of a platform that can eventually be applied to clinical screening panels for a multitude of oral and systemic medical conditions whose biomarkers are present in saliva.
Inverse Reinforcement Learning to Study Motivation in Mouse Behavioral Paradigms
Authors: Telfer Andre , Shamsabadi Afsoon Alidadi , Savin George , Wen Junfeng , Abizaid Alfonso 
Published: June 2024

AbstractMotivation describes the underlying goals that drive animal and agent behavior. In Neuroscience, behavioral paradigms are used to quantify the motivations of mice and used to gain insights into traits and diseases which can be translated to humans. In recent years, Computer Vision models are becoming widely adopted by Neuroscientists to score mouse behavior associated with motivations such as hunger and anxiety. However, a single motivation can be expressed by multiple different behaviors, and a single behavior can be linked to multiple motivations. Therefore the ideal analysis of motivational paradigms would attempt to directly recover the underlying motivations guiding behavior, rather than indirectly score their associated behaviors. In this paper, we move towards this goal by applying Inverse Reinforcement Learning to study the underlying motivations that drive mouse behavior.
Physiological Evaluation of Far Infrared-Emitting Garments on Sleep and Thermoregulation
Authors: Nishida Masaki , Nishii Taku , Suyama Shutaro , Youn Sumi , Funayama Kenta 
Published: June 2024

AbstractGarments engineered to emit far-infrared (FIR) spectral frequencies have potential conditioning benefits. This study aimed to explore the physiological effects of FIR-emitting clothes on sleep propensities involving thermoregulation and autonomic nervous function. In this double-blind, randomized, placebo-controlled, crossover study, fifteen healthy male participants (age 21.6 ± 1.5 years, body mass index 23.1 ± 1.9, Pittsburgh Sleep Quality Index 5.0 ± 2.0) wore a whole-body FIR garment (wavelength: 5–20 μm at 40°C), while a total body garment with the 100% polyester fiber without ceramic components was used as control for the intervention. To compare the physiological variables between the two electroencephalograms, the tympanic membrane temperature, sweating rate, skin temperature, and humidity were measured during sleep. Heart rate variability during sleep was also calculated. The percentage of rapid eye movement (REM) sleep was significantly higher in the FIR compared than in control (p= 0.027). We found a significant main effect of tympanic membrane temperature in time, equivalent to core body temperature. (2-way ANOVA; (F(26, 234)=4.046,p<0.001). Furthermore, the sweating rate was significantly lower when sleeping with FIR predominantly in the final phase of sleep (garment × time interaction (F(26,572)=55.05,p<0.001). Although there were no significant differences in skin surface temperature between the two garments, FIR provided significantly lower skin humidity during the middle of night sleep compared with the control. Regarding LF, a significant garment type x time interaction (F(1.87, 48.57)=3.36,p=0.046). Post-hoc analysis revealed that the LF value of FIR was higher in the final phase of sleep than that of control (p=0.027). Then present results suggest that sleeping with FIR in comparison to with control, has a beneficial effect to facilitate restorative sleep, presumably involving proper thermoregulation.
Maternal total sleep deprivation causes oxidative stress and mitochondrial dysfunction in oocytes associated with fertility decline in mice
Authors: Yi Zi-Yun , Liang Qiu-Xia , Zhou Qian , Yang Lin , Meng Qing-Ren , Li Jian , Lin Yi-hua , Cao Yan-pei , Zhang Chun-Hui , Schatten Heide , Qiao Jie , Sun Qing-Yuan 
Published: June 2024

AbstractPrevious studies have shown sleep deprivation has an impact on several aspects of health and disease. Sleep deprivation suppresses melatonin production and excessive HPA activation in women, which may reduce the chances of fertility. However, little is known about how and by what relevant mechanisms it affects female fertility. In this study, female mice underwent 72 hours of total sleep deprivation (TSD) caused by rotating wheel or 2 different controls: a stationary wheel, or forced movement at night. Even though, there was no evident anomaly of natural ovulation, the TSD female mice showed impaired early embryo development . Overall levels of estrogen and FSH were lower throughout the estrus cycle (especially in proestrus). RNA Sequencing (RNA-Seq) was used to discover differentially expressed genes (DEGs) that might be involved in oocyte quality after TSD. A total of 42 genes showed significant differential expression in GV oocytes after TSD. These included genes such asUsmg5, Atp5k, Ccnd2andTpm3, which were enriched in gene ontology terms of mitochondrial protein complex, oxidoreductase activity, cell division, cell cycle G1/S phase transition, as well as others. The increased concentrations of reactive oxygen species (ROS) in germinal vesicle (GV) and metaphase II (MII) oocytes from TSD mice were observed, which might be induced by impaired mitochondrial function caused by TSD. The GV oocytes displayed increased mitochondrial DNA (mtDNA) copy number and a significant transient increase in inner mitochondrial membrane potential (△ψm) from the TSD mice probably due to compensatory effect. In contrast, MII oocytes in the TSD group showed a decrease in the mtDNA copy number and a lower △ ψm compared with the controls. Furthermore, abnormal distribution of mitochondria in the GV and MII oocytes was also observed in TSD mice, suggesting mitochondrial dysfunction. In addition, abnormal spindle and abnormal arrangement of chromosomes in MII oocytes were markedly increased in the TSD mice compared with the control mice. In conclusion, our results suggest that TSD significantly alters the oocyte transcriptome, contributing to oxidative stress and disrupted mitochondrial function, which then resulted in oocyte defects and impaired early embryo development in female mice.
Occurrence, risk assessment of antibiotics and antimicrobial resistance inEscherichia coliin typical rivers of Sichuan
Authors: Sha Jingzhou , Wu Minghao , Zhou Yaliang , Chen Tao , Liu Haisha , Zhang Jingjing , Luo Wan , Huang Yi , Liu Yinshan , Wang Baoming , Song Tao , Lin Jiafu 
Published: June 2024

AbstractWorldwide interest has been generated by the presence and distribution of antibiotics and antibiotic resistance genes (ARGs) in rivers. However, there was a dearth of research on the contamination of Sichuan province’s typical rivers with antibiotics. In this study, the residual level of antibiotics in 42 national/provincial sites of 9 rivers was analyzed by UPLC-MS/MS, the ecological risk level was evaluated using risk assessment method, and the drug resistance ofE. coliin water was evaluated by Kirby-Bauer method. Redundancy analysis demonstrated how residual antibiotics affect the structure of the microbial community in the Minjiang River basin (RDA). Nine rivers all contained antibiotics. Among them, the MinJiang, TuoJiang, and JiaLingJiang rivers were severely contaminated with antibiotic concentrations ranging from 0.29 to 2233.71 ng/L. The Sichuan Basin’s antibiotic pollution level was significantly higher when compared to other Sichuan zones, which was consistent with the region’s high population density. Additionally, it was discovered that 9.77% of theE. coliisolated from 9 rivers had antibiotic resistance, and more than 5.8% of them had multidrug resistance. Moreover, Norfloxacin, amoxicillin, ampicillin, and tetracycline were the main risk factors for high ecological risk in 26 of the 42 monitoring sites. Additionally, there is a strong correlation between the microbial community change and residual antibiotic. These results offered some reference information regarding the distribution of antibiotics and ARGs in typical rivers in the Chinese province of Sichuan, and this study showed that more attention needs to be paid to antibiotic pollution in Sichuan’s typical rivers.
The Utility of Long-Read Sequencing in Diagnosing Genetic Autosomal Recessive Parkinson’s Disease: a genetic screening study
Authors: Daida Kensuke , Yoshino Hiroyo , Malik Laksh , Baker Breeana , Ishiguro Mayu , Genner Rylee , Paquette Kimberly , Li Yuanzhe , Nishioka Kenya , Masuzugawa Satoshi , Hirano Makito , Takahashi Kenta , Kolmogolv Mikhail , Billingsley Kimberley J , Funayama Manabu , Blauwendraat Cornelis , Hattori Nobutaka 
Published: June 2024

AbstractBackgroundMutations within the genesPRKNandPINK1are the leading cause of early onset autosomal recessive Parkinson’s disease (PD). However, the genetic cause of most early-onset PD (EOPD) cases still remains unresolved. Long-read sequencing has successfully identified many pathogenic structural variants that cause disease, but this technology has not been widely applied to PD. We recently identified the genetic cause of EOPD in a pair of monozygotic twins by uncovering a complex structural variant that spans over 7 Mb, utilizing Oxford Nanopore Technologies (ONT) long-read sequencing. In this study, we aimed to expand on this and assess whether a second variant could be detected with ONT long-read sequencing in other unresolved EOPD cases reported to carry one heterozygous variant inPRKNorPINK1.MethodsONT long-read sequencing was performed on patients with one reportedPRKN/PINK1pathogenic variant. EOPD patients with an age at onset younger than 50 were included in this study. As a positive control, we also included EOPD patients who had already been identified to carry two knownPRKNpathogenic variants. Initial genetic testing was performed using either short-read targeted panel sequencing for single nucleotide variants and multiplex ligation-dependent probe amplification (MLPA) for copy number variants.Results48 patients were included in this study (PRKN“one-variant” n = 24,PINK1“one-variant” n = 12,PRKN“two-variants” n = 12). Using ONT long-read sequencing, we detected a second pathogenic variant in sixPRKN“one-variant” patients (26%, 6/23) but none in thePINK1“one-variant” patients (0%, 0/12). Long-read sequencing identified one case with a complex inversion, two instances of structural variant overlap, and three cases of duplication. In addition, in the positive controlPRKN“two-variants” group, we were able to identify both pathogenic variants inPRKNin all the patients (100%, 12/12).ConclusionsThis data highlights that ONT long-read sequencing is a powerful tool to identify a pathogenic structural variant at thePRKNlocus that is often missed by conventional methods. Therefore, for cases where conventional methods fail to detect a second variant for EOPD, long-read sequencing should be considered as an alternative and complementary approach.
Enhancing genotype-phenotype association with optimized machine learning and biological enrichment methods
Authors: Jangale Vaishnavi , Sharma Jyoti , Shekhawat Rajveer Singh , Yadav Pankaj 
Published: June 2024

Genome-wide association studies (GWAS) are surging again owing to newer high-quality T2T-CHM13 and human pangenome references. Conventional GWAS methods have several limitations, including high false negatives. Non-conventional machine learning-based methods are warranted for analyzing newly sequenced, albeit complex, genomic regions.We present a robust machine learning-based framework for feature selection and association analysis, incorporating functional enrichment analysis to avoid false negatives. We benchmarked four popular single nucleotide polymorphism (SNP) feature selection methods: least absolute shrinkage and selection operator, ridge regression, elastic-net, and mutual information. Furthermore, we evaluated four association methods: linear regression, random forest, support vector regression (SVR), and XGBoost. We assessed proposed framework on diverse datasets, including subsets of publicly available PennCATH datasets as well as imputed, rare-variants, and simulated datasets. Low-density lipoprotein (LDL) cholesterol level was used as a phenotype for illustration. Our analysis revealed elastic-net combined with SVR consistently outperformed other methods across various datasets. Functional annotation of top 100 SNPs from PennCATH-real dataset revealed their expression in LDL cholesterol-related tissues. Our analysis validated three previously known genes (APOB, TRAPPC9, and EEPD1) implicated in cholesterol-regulated pathways. Also, rare-variant dataset analysis confirmed 37 known genes associated with LDL cholesterol. We identified several important genes, including APOB (familial-hypercholesterolemia), PTK2B (Alzheimer’s disease), and PTPN12 (myocardial ischemia/reperfusion injuries) as potential drug targets for cholesterol-related diseases.Our comprehensive analyses highlight elastic-net combined with SVR for association analysis could overcome limitations of conventional GWAS approaches. Our framework effectively detects common and rare variants associated with complex traits, enhancing the understanding of complex diseases.