bluuebunny/crossref_metadata_2025 huggingface dataset:
cisDynet: an integrated platform for modeling gene-regulatory dynamics and networks
Authors: Zhu Tao , Zhou Xinkai , You Yuxin , Wang Lin , He Zhaohui , Chen Dijun
Published: November 2023

Chromatin accessibility sequencing has been widely used for uncovering genetic regulatory mechanisms and inferring gene regulatory networks. However, effectively integrating large-scale chromatin accessibility datasets has posed a significant challenge. This is due to the lack of a comprehensive end-to-end solution, as many existing tools primarily emphasize data pre-processing and overlook downstream analyses. To bridge this gap, we have introduced cisDynet, a holistic solution that combines streamlined data pre-processing using Snakemake and R functions with advanced downstream analysis capabilities. cisDynet excels in conventional data analyses, encompassing peak statistics, peak annotation, differential analysis, motif enrichment analysis and more. Additionally, it allows to perform sophisticated data exploration such as tissue-specific peak identification, time-course data fitting, integration of RNA-seq data to establish peak-to-gene associations, constructing regulatory networks, and conducting enrichment analysis of GWAS variants. As a proof of concept, we applied cisDynet to re-analyze the comprehensive ATAC-seq datasets across various tissues from the ENCODE project. The analysis successfully delineated tissue-specific open chromatin regions (OCRs), established connections between OCRs and target genes, and effectively linked these discoveries with 1,861 GWAS variants. Furthermore, cisDynet was instrumental in dissecting the time-course open chromatin data of mouse embryonic development, revealing the dynamic behavior of OCRs over time and identifying key transcription factors governing differentiation trajectories. In summary, cisDynet offers researchers a user-friendly solution that minimizes the need for extensive coding, ensures the reproducibility of results, and greatly simplifies the exploration of epigenomic data.

Graphical Abstract

cisDynet enables the exploration of the cis-regulatory chromatin dynamics and networks. It offers a streamlined preprocessing pipeline built on Snakemake, along with an R package for advanced downstream data analysis and visualization. It is free to access on GitHub (https://github.com/tzhu-bio/cisDynet).

Highlights

The cisDynet enables comprehensive and efficient processing of chromatin accessibility data, including pre-processing, advanced downstream data analysis and visualization.

cisDynet provides a range of analytical features such as processing of time course data, co-accessibility analysis, linking OCRs to genes, building regulatory networks, and GWAS variant enrichment analysis.

cisDynet simplifies the identification of tissue/cell type-specific OCRs or dynamic OCR changes over time and facilitates the integration of RNA-seq data to depict temporal trajectories.
Widespread changes in gene expression accompany body size evolution in nematodes
Authors: Woodruff Gavin C. , Willis John H. , Johnson Erik , Phillips Patrick C.
Published: November 2023

Body size is a fundamental trait that drives multiple evolutionary and ecological patterns.Caenorhabditis inopinatais a fig-associated nematode that is exceptionally large relative to other members of the genus, includingC. elegans. We previously showed thatC. inopinatais large primarily due to postembryonic cell size expansion that occurs during the larval-to-adult transition. Here, we describe gene expression patterns inC. elegansandC. inopinatathroughout this developmental period to understand the transcriptional basis of body size change. We performed RNA-seq in both species across the L3, L4, and adult stages. Most genes are differentially expressed across all developmental stages, consistent withC. inopinata’s divergent ecology and morphology. We also used a model comparison approach to identify orthologs with divergent dynamics across this developmental period between the two species. This included genes connected to neurons, behavior, stress response, developmental timing, and small RNA/chromatin regulation. Multiple hypodermal collagens were also observed to harbor divergent developmental dynamics across this period, and genes important for molting and body morphology were also detected. Genes associated with TGF-β signaling revealed idiosyncratic and unexpected transcriptional patterns given their role in body size regulation inC. elegans. Widespread transcriptional divergence between these species is unexpected and may be a signature of the ecological and morphological divergence ofC. inopinata. Alternatively, transcriptional turnover may be the rule in theCaenorhabditisgenus, indicative of widespread developmental system drift among species. This work lays the foundation for future functional genetic studies interrogating the bases of body size evolution in this group.
FlyVISTA, an Integrated Machine Learning Platform for Deep Phenotyping of Sleep inDrosophila
Authors: Keleş Mehmet F. , Sapci Ali Osman Berk , Brody Casey , Palmer Isabelle , Le Christin , Taştan Öznur , Keleş Sündüz , Wu Mark N.
Published: November 2023

Animal behavior depends on internal state. While subtle movements can signify significant changes in internal state, computational methods for analyzing these “microbehaviors” are lacking. Here, we present FlyVISTA, a machine-learning platform to characterize microbehaviors in freely-moving flies, which we use to perform deep phenotyping of sleep. This platform comprises a high-resolution closed-loop video imaging system, coupled with a deep-learning network to annotate 35 body parts, and a computational pipeline to extract behaviors from high-dimensional data. FlyVISTA reveals the distinct spatiotemporal dynamics of sleep-associated microbehaviors in flies. We further show that stimulation of dorsal fan-shaped body neurons induces micromovements, not sleep, whereas activating R5 ring neurons triggers rhythmic proboscis extension followed by persistent sleep. Importantly, we identify a novel microbehavior (“haltere switch”) exclusively seen during quiescence that indicates a deeper sleep stage. These findings enable the rigorous analysis of sleep inDrosophilaand set the stage for computational analyses of microbehaviors.
Ultrahigh Resolution Lipid Mass Spectrometry Imaging of High-Grade Serous Ovarian Cancer Mouse Models
Authors: Ma Xin , Botros Andro , Yun Sylvia R. , Park Eun Young , Kim Olga , Chen Ruihong , Palaniappan Murugesan , Matzuk Martin M. , Kim Jaeyeon , Fernández Facundo M.
Published: November 2023

No effective screening tools for ovarian cancer (OC) exist, making it one of the deadliest cancers among women. Considering little is known about the detailed progression and metastasis mechanism of OC at a molecular level, it is crucial to gain more insights on how metabolic and signaling alterations accompany its development. Herein, we present a comprehensive study using ultra-high-resolution Fourier transform ion cyclotron resonance matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) to investigate the spatial distribution and alterations of lipids in ovarian tissues collected from double knockout (n= 4) and a triple mutant mouse models (n= 4) of high-grade serous ovarian cancer (HGSC). Lipids belonging to a total of 15 different classes were annotated and their abundance changes compared to those in healthy mouse reproductive tissue (n= 4), mapping onto major lipid pathways involved in OC progression. From intermediate-stage OC to advanced HGSC, we provide a direct visualization of lipid distributions and their biological links to inflammatory response, cellular stress, cell proliferation, and other processes. We also show the ability to distinguish tumors at different stages from healthy tissuesviaa number of highly specific lipid biomarkers, providing targets for future panels that could be useful in diagnosis.
Nuclear deformation and dynamics of migrating cells in 3D confinement reveal adaptation of pulling and pushing forces
Authors: Stöberl Stefan , Flommersfeld Johannes , Kreft Maximilian M. , Benoit Martin , Broedersz Chase P. , Rädler Joachim O.
Published: November 2023

Eukaryotic cells show an astounding ability to migrate through pores and constrictions smaller than their nuclear diameter. However, the forces engaged in nuclear deformation and their effect on confined cell dynamics remain unclear. Here, we study the mechanics and dynamics of nuclei of mesenchymal cancer cells as they spontaneously and repeatedly transition through 3D compliant hydrogel channels. We find a biphasic dependence of migration speed and transition frequency on channel width, revealing maximal transition rates at widths comparable to the nuclear diameter. Using confocal imaging and hydrogel bead displacement, we determine the nuclear deformation and corresponding forces during spontaneous confined migration. We find the nucleus to reversibly deform with an elastic modulus not adapting to the confinement. Instead, with decreasing channel width, the nuclear shape during transmigration changes biphasically concomitant with the transitioning dynamics. The nucleus exhibits a prolate form along the migration direction in wide channels and a more compressed oblate shape in narrow channels. We propose a physical model for confined cell migration that explains the observed nuclear shapes and slowing down in terms of the cytoskeletal force-generation adapting from a pulling-to a pushing-dominated mechanism with increasing nuclear confinement.
Looking for a needle in a haystack: de novo phenotypic target identification reveals Hippo pathway-mediated miR-202 regulation of egg production
Authors: Janati-Idrissi Sarah , Roza de Abreu Mariana , Guyomar Cervin , de Mello Fernanda , Nguyen Thaovi , Mechkouri Nazim , Gay Stéphanie , Montfort Jérôme , Gonzalez Anne Alicia , Abbasi Marzieh , Bugeon Jérôme , Thermes Violette , Seitz Hervé , Bobe Julien
Published: November 2023

Understanding microRNA (miRNA) functions has been hampered by major difficulties in identifying their biological target(s). Currently, the main limitation is the lack of a suitable strategy to identify biologically relevant targets among a high number of putative targets. Here we provide a proof of concept of successfulde novo(i.e., without prior knowledge of its identity) miRNA phenotypic target (i.e., target whose de-repression contributes to the phenotypic outcomes) identification from RNA-seq data. Using the medakamir-202knock-out (KO) model in which inactivation leads to a major organism-level reproductive phenotype, including reduced egg production, we introduced novel criteria including limited fold-change in KO and low interindividual variability in gene expression to reduce the list of 2,853 putative targets to a short list of 5. We selectedtead3b,a member of the evolutionarily-conserved Hippo pathway, known to regulate ovarian functions, due to its remarkably strong and evolutionarily conserved binding affinity for miR-202-5p. Deleting the miR-202-5p binding site in the 3’ UTR oftead3b, but not of other Hippo pathway memberssav1andvgll4b, triggered a reduced egg production phenotype. This is one of the few successful examples ofde novofunctional assignment of a miRNA phenotypic targetin vivoin vertebrates.
Unusual 1-3 peptidoglycan cross-links inAcetobacteraceaeare made by L,D-transpeptidases with a catalytic domain distantly related to YkuD domains
Authors: Alaman-Zarate Marcel G , Rady Brooks J , Evans Caroline A , Pian Brooke , Greetham Darren , Marecos-Ortiz Sabrina , Dickman Mark J , Lidbury Ian DEA , Lovering Andrew L , Barstow Buz M , Mesnage Stéphane
Published: November 2023

Peptidoglycan is an essential component of the bacterial cell envelope that contains glycan chains substituted by short peptide stems. Peptide stems are polymerized by D,D-transpeptidases, which make bonds between the amino acid in position 4 of a donor stem and the third residue of an acceptor stem (4-3 cross-links). Some bacterial peptidoglycans also contain 3-3 cross-links that are formed by another class of enzymes called L,D-transpeptidases. In this work, we investigate the formation of unusual bacterial 1-3 peptidoglycan cross-links. We describe a version of the PGFinder software which can identify 1-3 cross-links and report the high-resolution peptidoglycan structure ofGluconobacter oxydans(a model organism within theAcetobacteraceaefamily). We reveal thatG. oxydanspeptidoglycan contains peptide stems made of a single alanine as well as several dipeptide stems with unusual amino acids at their C-terminus. Using a Sudoku transposon library, we identified aG. oxydansmutant with a drastic reduction in 1-3 cross-links. Through complementation experiments inG. oxydansand recombinant protein production in a heterologous host, we identify an L,D-transpeptidase enzyme with a domain distantly related to the YkuD domain responsible for these non-canonical reactions. This work revisits the enzymatic capabilities of L,D-transpeptidases, a versatile family of enzymes that play a key role in bacterial peptidoglycan remodelling.
Revealing motor behavior patterns and functional improvement trajectories following spinal cord injury using unsupervised machine learning
Authors: Eisdorfer Jaclyn Taylor , Lin Sherry , Thackray Joshua K , Theis Thomas , Vivinetto Ana , Oputa Olisemeka , Martinez Alana M , Nacht Hannah D , Tschang Monica , Mahmood Malaika , Tucker Ashley , Ruven Carolin , Pusuloori Shailee , Zmoyro Lance , Kumar Suneel ,   Abraira Lab Computational Group, Schachner Melitta , Sahni Vibhu , Popovich Phillip , Ferguson Adam R. , McTigue Dana , Tysseling Vicki M , Dulin Jennifer , Hollis Edmund , Datta Sandeep Robert , Abraira Victoria Eugenia Guadalupe
Published: November 2023

Spinal cord injury (SCI) disrupts motor function, with recovery involving complex adaptive motor behaviors that cannot be fully assessed with traditional manual recovery assessments and their predefined recovery criteria. To move beyond these constraints, we employed motion sequencing (MoSeq), a machine learning-driven framework that automatically segments freely moving mouse behavior into discrete, repeated behavioral “syllables”, effectively capturing entire behavioral repertoires and dynamic behavioral sequences observed throughout SCI recovery. We observed that functional improvements involved the reemergence of preinjury behaviors, emergence of adaptive behaviors, and subtle individual differences between mice. Interestingly, the temporal organization of behavioral sequences evolved consistently across injury severities, suggesting a ceiling effect in sequence reorganization. MoSeq syllables also correlated with the Basso Mouse Scale (BMS) and outperformed BMS in correlation to several injury-related histological findings. We also introduced the “Recovery Score,” a new metric derived from aggregated MoSeq data that quantifies recovery based on syllable usage patterns. The Recovery Score identified clusters of syllables with high usages, which highlights the potential of using hallmark syllables as behavioral biomarkers for assessing recovery and informing therapies. Future research should incorporate more complex experimental designs to refine this aggregation approach and advance the pursuit of a new gold standard in recovery assessment.
Swine influenza A virus infection dynamics and evolution in intensive pig production systems
Authors: Lagan Paula , Hamil Michael , Cull Susan , Hanrahan Anthony , Wregor Rosanna M. , Lemon Ken
Published: November 2023

Swine influenza A virus is one of the main viral pathogens responsible for respiratory disease in farmed pigs. Whilst outbreaks are often epidemic in nature, increasing reports suggest that continuous, endemic infection of herds is now common. The move towards larger herd sizes and increased intensification in the commercial pig industry may promote endemic infection, however, the impact that intensification has on swine influenza A virus infection dynamics and evolution is unclear. We carried out a longitudinal surveillance study over 18 months on two endemically infected, intensive pig farms. Frequent sampling of all production stages using individual and group sampling methods was performed, followed by virological and immunological testing and whole genome sequencing. We identified weaned pigs between 4-12 weeks old as the main reservoir of swine influenza A virus on the farms, with continuous, year-round infection. Despite the continuous nature of viral circulation, infection levels were not uniform, with increasing immunity at the herd level associated with reduced viral prevalence followed by subsequent rebound infection. A single virus subtype persisted on each farm for the entire duration of the study. Viral evolution was characterised by long periods of stasis punctuated by periods of rapid change coinciding with increasing immunity within the herd. An accumulation of mutations in the surface glycoproteins consistent with antigenic drift was observed, in addition to amino acid substitutions in the internal gene products as well as reassortment exchange of internal gene segments from newly introduced strains. These data demonstrate that long-term, continuous infection of herds with a single subtype is possible and document the evolutionary mechanisms utilised to achieve this.

Author Summary

Infection with influenza A virus is widespread in pigs and contributes towards poor health and loss of productivity. Effective infection control measures are necessary to limit the impact of influenza on farms. However, modern farming practices are increasingly characterised by larger herd sizes and higher stocking densities. It is unclear how the move towards increased intensification impacts infectious diseases such as influenza. Accumulating evidence suggests that long-term infection of herds may be common. How influenza A virus can persist long-term is poorly understood. The aim of the current study was to monitor the infection status of pigs at each stage of the production process, measure the extent of the developing immune response and to characterise the evolutionary changes in the circulating influenza A viruses over time. Our findings provide insights into the dynamics of viral infection and evolution and may contribute to improved infection control strategies.
Meta-Analysis of EEG Findings on Pain Perception: Exploring Nociceptive and Neuropathic Pain Response Patterns
Authors: Mikhail Lipnitskii
Published: November 2023

This article presents a meta-analysis of research articles focusing on the use of electroencephalography (EEG) in the study of nociceptive and neuropathic pain perception. The objective of the study is to compare the findings of the reviewed articles with the three-route model of pain perception, which posits that specific brain regions are responsible for interpreting different aspects of pain. The articles included in the analysis were sourced from reputable databases such as Scopus, Google Scholar, and Pubmed. The selection criteria for these articles was based on the explicit demonstration of changes in EEG rhythms in response to pain sensations. This served as an important factor in determining their inclusion for further analysis. The results of the meta-analysis provide insights into the changes observed in EEG rhythms across different brain regions. By examining the location of these characteristic changes, the study makes assumptions about potential interrelationships between the observed EEG rhythms and the activity of specific brain regions discussed in the articles. Ultimately, this meta-analysis contributes to our understanding of the relationship between pain perception and EEG activity, shedding light on the potential role of distinct brain areas in processing different aspects of pain.
Extremely oligotrophic and complex carbon degrading microaerobic bacteria from Arabian Sea oxygen minimum zone sediments
Authors: Sarkar Jagannath , Mondal Mahamadul , Bhattacharya Sabyasachi , Dutta Subhajit , Chatterjee Sumit , Mondal Nibendu , N Saran , Peketi Aditya , Mazumdar Aninda , Ghosh Wriddhiman
Published: November 2023

Sediments underlying marine hypoxic zones are huge sinks of unreacted complex organic matter, where despite acute O2-limitation obligately aerobic bacteria thrive, and steady depletion of organic carbon takes place within a few meters below the seafloor. However, little knowledge exists about the sustenance and complex carbon degradation potentials of aerobic chemoorganotrophs in these sulfidic ecosystems. We isolated and characterized a number of aerobic bacterial chemoorganoheterotrophs from across a ∼3 m sediment horizon underlying the perennial hypoxic zone of the eastern Arabian Sea. High levels of sequence correspondence between the isolates’ genomes and the habitat’s metagenomes and metatranscriptomes illustrated that the strains were widespread and active across the sediment-cores explored. The isolates catabolized several complex organic compounds of marine and terrestrial origins in the presence of high or low, but not zero, O2. Some of them could also grow anaerobically on yeast extract or acetate by reducing nitrate and/or nitrite. Fermentation did not support growth, but enabled all the strains to maintain a fraction of their cell populations over prolonged anoxia. Under extreme oligotrophy, limited growth followed by protracted stationary phase was observed for all the isolates at low cell density, amid high or low, but not zero, O2concentration. While population control and maintenance could be particularly useful for the strains’ survival in the critically carbon-depleted layers below the explored sediment-depths (core-bottom organic carbon: 0.5-1.0 % w/w), metagenomic data suggested thatin situanoxia could be surmounted via potential supplies of cryptic O2from previously-reported sources such asNitrosopumilusspecies.
Supplementation with short-chain fatty acids and the prebiotic 2FL improves clinical outcome in PD
Authors: Hegelmaier Tobias , Duscha Alexander , Desel Christiane , Fuchs Sabrina , Shapira Michal , Shan Qihao , Stangl Gabriele I , Hirche Frank , Kempa Stefan , Maifeld András , Würtele Lisa-Marie , Peplinski Jana , Jauk Diana , Dumitru Claudia A. , Obermüller-Jevic Ute , Hustvedt Svein-Olaf , Timmesfeld Nina , Gold Ralf , Zapf Antonia , Sandalcioglu Ibrahim E. , Mostaghim Sanaz , Przuntek Horst , Segal Eran , Yissachar Nissan , Haghikia Aiden
Published: November 2023

Background

Parkinson’s disease (PD) is associated with dysbiosis, proinflammatory gut microbiome, disruptions to intestinal barrier functions, and immunological imbalance. Microbiota-produced short-chain fatty acids promote gut barrier integrity and immune regulation, but their impact on PD pathology remains mostly unknown.

Objectives

To evaluate supplementation with short-chain fatty acids as an add-on intervention in PD.

Methods

In a randomized double-blind prospective study, 72 PD patients received short-chain fatty acids and/or the prebiotic fiber 2′-fucosyllactose supplementation over 6 months.

Results

We observed improvement in motor and nonmotor symptoms, in addition to modulation of peripheral immunity and improved mitochondrial respiration in immunocytes. The supplementation had no effect on microbiome diversity or composition. Finally, multiobjective analysis and comprehensive immunophenotyping revealed parameters associated with an optimal response to short-chain fatty acids and/or 2′-fucosyllactose supplementation.

Conclusion

Short-chain fatty acids ameliorate clinical symptoms in Parkinson’s disease patients and modulate mitochondrial function and peripheral immunity.
Global solidarity in genomic surveillance improves early detection of respiratory virus threats
Authors: de Jong Simon P.J. , Nichols Brooke E. , de Ruijter Anniek , Parker Edyth , Mitesser Vera , Happi Christian , de Jong Menno D. , Han Alvin X. , Russell Colin A.
Published: November 2023

Public health decision-making for respiratory virus outbreaks relies heavily on genomic sequencing to detect new (variant) viruses. However, respiratory virus sequencing infrastructure is highly unequally distributed globally, potentially limiting the efficiency and effectiveness of surveillance efforts and raising concerns about preparedness for future threats. Using mathematical models, we demonstrate that relative to global sequencing efforts during the COVID-19 pandemic, increased global solidarity in respiratory virus genomic surveillance would vastly improve the capacity to rapidly detect novel threats, even with a substantially reduced number of viruses sequenced globally, leading to improved effectiveness and efficiency. As a result, the time between a (variant) virus’ first global detection and first local case would increase in all countries, allowing for more time to design and implement global and local public health measures to mitigate the threat’s potential public health impacts. Our results show that operationalizing global health solidarity is key to guiding investment in preparedness for future pandemic threats.
Prevalence and causes of blindness and visual impairment in Kogi state, Nigeria – Findings from a Rapid Assessment of Avoidable Blindness survey
Authors: Penzin Selben , Jolley Emma , Ogundimu Kolawole , Mpyet Caleb , Ibrahim Nazaradden , Owoeye Foluso , Isiyaku Sunday , Shu’aibu Joy , Schmidt Elena
Published: November 2023

Purpose

To determine the prevalence and causes of blindness and visual impairment among adults in Kogi, Nigeria.

Methods

A Rapid assessment of avoidable blindness (RAAB) protocol was used with additional tools measuring disability and household wealth to measure the prevalence of blindness and visual impairment (VI) and associations with sex, disability, wealth, cataract surgical coverage and its effectiveness.

Results

Age- and sex-adjusted all-cause prevalence of bilateral blindness was 3.6% (95%CI 3.0-4.2%), prevalence of blindness among people living with additional, non-visual disabilities was 38.3% (95% CI 29.0-48.6%) compared to 1.6% (95%CI 1.2-2.1%; 𝜒2= 771.9, p<0.001) among people without additional disabilities. Cataract was the principal cause of bilateral blindness (55.3%). Cataract surgical coverage (CSC) at visual acuity (VA) 3/60 was 48.0%, higher among men than women (53.7% vs 40.3%); 12.0% among people with non-visual disabilities; 66.9% among people without non-visual disabilities, higher among people in the wealthiest two quintiles (41.1%) compared to the lowest three (24.3%).

Effective Cataract Surgical Coverage at Visual Acuity 6/60 was 31.0%, higher among males (34.9%) than females (25.5%), low among people with additional, non-visual disabilities (1.9%) compared to people with no additional disabilities (46.2%), higher among people in the wealthiest two quintiles (411%) compared to the poorest three (24.3%).

Good surgical outcome (VA>6/18) was seen in 61 eyes (52.6%) increasing to 71 (61.2%) eyes with best correction. Cost was identified as the main barrier to surgery.

Conclusion

Findings suggest there exists inequalities in eye care with women, poorer people and people with disabilities having a lower Cataract Surgical Coverage, thereby, underscoring the importance of eye care programs to address these inequalities.
Detecting Alzheimer Disease in EEG Data with Machine Learning and the Graph Discrete Fourier Transform
Authors: Mootoo Xavier S. , Fours Alice , Dinesh Chinthaka , Ashkani Mohammad , Kiss Adam , Faltyn Mateusz
Published: November 2023

Abstract

Alzheimer Disease (AD) poses a significant and growing public health challenge worldwide. Early and accurate diagnosis is crucial for effective intervention and care. In recent years, there has been a surge of interest in leveraging Electroen-cephalography (EEG) to improve the detection of AD. This paper focuses on the application of Graph Signal Processing (GSP) techniques using the Graph Discrete Fourier Transform (GDFT) to analyze EEG recordings for the detection of AD, by employing several machine learning (ML) and deep learning (DL) models. We evaluate our models on publicly available EEG data containing 88 patients categorized into three groups: AD, Frontotemporal Dementia (FTD), and Healthy Controls (HC). Binary classification of dementia versus HC reached a top accuracy of 85% (SVM), while multiclass classification of AD, FTD, and HC attained a top accuracy of 44% (Naive Bayes). We provide novel GSP methodology for detecting AD, and form a framework for further experimentation to investigate GSP in the context of other neurodegenerative diseases across multiple data modalities, such as neuroimaging data in Major Depressive Disorder, Epilepsy, and Parkinson disease.
Mental disorders and discrimination: a prospective cohort study of young twin pairs in Germany
Authors: Calais-Ferreira Lucas , Armstrong Greg , Hahn Elisabeth , Newton-Howes Giles , Foulds James , Hopper John L , Spinath Frank M , Kurdyak Paul , Young Jesse T
Published: November 2023

Background

Mental disorders and discrimination share common risk factors. The association between having a mental disorder and experiencing discrimination is well-known, but the extent to which familial factors, such as genetic and shared environmental factors, might confound this association, including gender differences in familial confounding, remains unexplored.

Aims

We investigated potential unmeasured familial confounding in the relationship between mental disorders and discrimination.

Method

We examined 2,044 same-sex twin pairs aged 16–25 years from the German population-based study’TwinLife’. We used a matched design and random-effects regression applied to within-individual and within-and-between pair models for the association between mental disorder and discrimination, and used likelihood ratio tests (LRTs) to compare these models. Multivariable models were adjusted for body-mass-index, educational attainment, and global life satisfaction.

Results

Mental disorder and discrimination were associated in the adjusted within-individual model (adjusted odds ratio=2.19, 95% Confidence Interval:1.42–3.39,P<0.001). However, the within-and-between pair model showed that this association was explained by the within-pair mean (aOR=4.24, 95%CI:2.17–8.29,P<0.001) and not the within-pair difference (aOR=1.26, 95%CI:0.70–2.28,P=0.4) of mental disorder. Therefore, this association was mostly explained by familial confounding, which is also supported by the LRTs for the unadjusted and adjusted models (P<0.001 andP=0.03, respectively). This familial confounding was more prominent for males than females.

Conclusions

Our findings show that the association between mental disorder and discrimination is almost fully explained by unmeasured familial factors. Incorporating family members in interventions targeted at ameliorating mental ill-health and experiences of discrimination among adolescents may improve efficacy.
Automatic Detection of Cardiac Conditions from Photos of Electrocardiogram (ECG) Captured by Smartphones
Authors: Wong Chun-Ka , Lau Yuk-Ming , Lui Hin-Wai , Chan Wai-Fung , San Wing-Chun , Zhou Mi , Cheng Yangyang , Huang Duo , Lai Wing-Hon , Lau Yee-Man , Siu Chung-Wah
Published: November 2023

Background

Artificial intelligent electrocardiogram (ECG) diagnostic algorithms can achieve cardiologist-level accuracy, but their clinical use is limited as they cannot be installed in older ECG machines.

Objective

To develop a smartphone application that extracts and analyzes ECG waveforms from photos using machine learning techniques.

Methods

A smartphone application was developed to automatically extract ECG waveforms from photos taken by clinicians using computer vision and machine learning. Custom designed machine learning models were developed to perform waveform identification, gridline removal, and scale calibration. The extracted voltage-time series waveforms were analyzed using a pre-trained machine learning-based diagnostic algorithms, and the accuracy of the proof-of-concept application was assessed.

Results

Waveforms from 40,516 scanned and 444 photographed ECGs were automatically extracted. 12,828 of 13,258 (96.8%) scanned and 5,399 of 5,743 (94.0%) photographed waveforms were correctly cropped and labelled. 11,604 of 12,735 (91.1%) scanned and 5,062 of 5,752 (88.0%) photographed waveforms achieved successful voltage-time signal extraction after automatic gridline and background noise removal. The AF diagnostic algorithm achieved 91.3% sensitivity, 94.2% specificity, 95.6% positive predictive value, 88.6% negative predictive value and 93.4% F1 score.

Conclusion

Using computer vision and machine learning techniques to detect cardiac conditions from photos of ECGs taken with smartphones is feasible. This platform can enable widespread deployment of the latest machine learning-based ECG diagnostic algorithms.
SARS-CoV-2 spike protein induces the cytokine release syndrome by stimulating T cells to produce more IL-2
Authors: Niu Chao , Liang Tingting , Chen Yongchong , Zhu Shan , Zhou Lei , Chen Naifei , Qian Lei , Wang Yufeng , Li Min , Zhou Xin , Cui Jiuwei
Published: November 2023

Cytokine release syndrome (CRS) is one of the leading causes of mortality in COVID-19 patients caused by the SARS-CoV-2 coronavirus. However, the mechanism of CRS induced by SARS-CoV-2 is vague. This study shows that dendritic cells loaded with spike protein of SARS-CoV-2 stimulate T cells to release much more IL-2, which subsequently cooperates with spike protein to facilitate peripheral blood mononuclear cells to release IL-1β, IL-6, and IL-8. These effects are achieved via IL-2 stimulation of NK cells to release TNF-α and IFN-γ, as well as T cells to release IFN-γ. Mechanistically, IFN-γ and TNF-α enhance the transcription of CD40, and the interaction of CD40 and its ligand stabilizes the membrane expression of TLR4 which serves as a receptor of spike protein on the surface of monocytes. As a result, there is a constant interaction between spike protein and TLR4, leading to continuous activation of NF-κB. Furthermore, TNF-α also activates NF-κB signaling in monocytes, which further cooperates with IFN-γ and spike protein to modulate NF-κB-dependent transcription of CRS-related inflammatory cytokines. Targeting TNF-α/IFN-γ in combination with TLR4 may represent a promising therapeutic approach for alleviating CRS in individuals with COVID-19.
The Microbiome of Bioreactors Containing Mass-Cultivated Marine Diatoms for Industrial Carbon Capture and Utilization
Authors: Aalto Nerea Johanna , Giæver Ingeborg Hulda , Eriksen Gunilla Kristina , Israelsen Linn , Krsmanovic Stina , Petters Sebastian , Bernstein Hans C.
Published: November 2023

Marine microalgae are a promising innovation platform for carbon capture and utilization (CCU) biotechnologies to mitigate industrial greenhouse gas emissions. However, industrial-scale cultivation of algal mono-cultures is challenging and often unscalable. Non-axenic microalgae in large semi-open photobioreactors lead to the co-cultivation of diverse microbial communities. There is limited knowledge about the “bioreactor ecology” involving microalgae interacting with the microbiome and its subsequent impact on process stability and productivity. In this study, we describe the semi-continuous industrial mass cultivation of the cold-adapted marine diatom,Porosira glacialisUiT201, by investigating the prokaryotic and microeukaryotic (phytoplankton and heterotrophic protist) communities. Data were collected in two consecutive time series experiments, representing the initiation and operation of an preindustrial scale CCU photobioreactor (300,000 liters). The first experiment experienced a culture “crash” of the focal strain after 39 days, while the second culture remained stable and “healthy” for 60 days. The results highlight that this mass cultivation system represents a unique industrial marine microbial ecosystem. The succession of the prokaryotic community was primarily driven by species replacement, indicating turnover due to selective bioreactor conditions and/or biological interactions. Nonetheless, the bioreactor consistently harbors a recurring and abundant core microbiome, suggesting that the closely associated bacterial community is influenced by microalgae-specific properties and can endure a dynamic and variable environment. The observed culture collapse ofP. glacialiscoincided with changes in the core microbiome structure and different environmental growth conditions compared to the stable and “healthy” experiment. These findings imply that cohabiting microbial taxa within industrial microalgae cultivation likely play a critical role in stabilizing the conversion of industrial CO2into marine biomass, and changes in community structure serve as an indicator of process stability.
Structural insights into viral hijacking of p53 by E6 and E6AP
Authors: Sandate Colby R. , Chakraborty Deyasini , Kater Lukas , Kempf Georg , Thomä Nicolas H.
Published: November 2023

The E3-ubiquitin ligase E6AP degrades p53 when complexed with the viral protein E6 from human papilloma virus (HPV), which contributes to the transformation of cells in HPV-related cancers. Previous crystal structures of the E6AP-E6-p53 ternary complex have implicated a peptide containing an LxxLL motif from E6AP as the interface between the three proteins. However, the contributions to the ternary complex from the remainder of the E6AP protein remain unknown. We reexamined this complex using cryo-EM and full-length proteins and find additional protein interaction interfaces involving a previously uncharacterized domain of E6AP. Additionally, we observe that the ternary complex forms both 1:1:1 and 2:2:2 stochiometric complexes comprised of E6AP, E6 and p53.
Crystal structure of CaSiF6·2H2O(mP2) and reevaluation of the SiIV–F bond-valence parameter R
0
Authors: Motaln Klemen , Lozinšek Matic
Published: November 2023

The structure of a second polymorph of CaSiF6·2H2O [calcium hexafluoridosilicate dihydrate; space group P2/c (No. 13), Pearson symbol mP2] was elucidated by single-crystal X-ray diffraction. It arose as an unexpected product when soda-lime glass was attacked by HF. Its crystal structure consists of infinite ∞
2[Ca(H2O)2/1(SiF6)4/4] layers oriented parallel to the bc-crystallographic plane, a unique motif among structurally characterized hydrated hexafluoridosilicates. The crystal structure also exhibits inter- and intralayer hydrogen bonds, with the interlayer O—H...O hydrogen bonds involving a disordered hydrogen atom. The large deviation between the calculated bond-valence sum for Si and the expected value prompted a redetermination of the empirical SiIV–F bond-valence parameter R
0. Based on a data set of 42 high-quality crystal structures containing 49 independent SiIV coordination environments, a revised value of 1.534 Å was derived for R
0.
Working capital policy of newly incorporated firms
Authors: Desai Rajesh , Mehta Bhoomi
Published: November 2023

Purpose

The present study examines the initial working capital policy (WCP) and its evolution for newly established manufacturing firms.

Design/methodology/approach

Using panel data of 162 firms over a period of 10 years, the study analyses the persistence-cum-convergence in WCP over the subsequent years through descriptive analysis and difference of means test. Further, the prevalence of ß – convergence, and σ-convergence has been examined using standard least squares regression, dynamic panel analysis and the Wald test.

Findings

The results indicate that sample firms continue to follow the initial WCP in the subsequent years with a gradual convergence in the WCP. Alternatively, the firms with aggressive (conservative) WCP at the time of incorporation will continue following it. Further, the firms with aggressive initial WCP have witnessed higher growth than those with conservative initial WCP.

Research limitations/implications

Findings will assist managers and practitioners to understand the dynamics of WCP over the life cycle of the firm and select appropriate WCP as certain policies lead to certain growth paths.

Originality/value

Though working capital management has been recognized as a critical managerial decision, limited research is available on its evolution, especially for newly established manufacturing companies in an emerging economy. Current research attempts to fill this gap and provide valuable insights for the effective management of liquidity.
Development and comparison of double-stator memory machines with parallel hybrid magnets
Authors: Peng Cheng , Cheng He , Zhang Tong , Wu Jing , Lin Fandi , Chu Jinglong
Published: November 2023

Purpose

This paper aims to further develop stator permanent magnet (PM) type memory machines by providing generalized design guidelines for double-stator memory machines (DSMMs) with hybrid PMs. This paper discusses the design experience of DSMMs and presents a comparative study of radial magnetization (RM) and circumferential magnetization (CM) types.

Design/methodology/approach

It begins with an introduction to RM and CM operating principles and magnetization mechanisms. Then, a comparative study is conducted for one of the RM-DSMM rotor pole pairs, inner and outer stator clamping angles and low coercive force PMs thickness. Finally, the two machines’ finite element simulation performance is compared. The validity of the proposed machine structure is demonstrated.

Findings

In this paper, the double-stator structure is extended to parallel hybrid PM memory machines, and two novel DSMMs with RM and CM configurations are proposed. Two types of DSMMs have PMs and magnetizing windings on the inner stator and armature windings on the outer stator. The main difference between the two is the arrangement of PMs on the inner stator.

Originality/value

Conventional stator PM memory machines have geometrical space conflicts between the PM and armature windings. The proposed double-stator structure can alleviate these conflicts and increase the torque density accordingly. In addition, this paper contributes to comparing the arrangement of hybrid PMs for DSMMs.
Impact of earnings management on dividend policy: does board independence matter?
Authors: Javaid Aisha , Fatima Kaneez , Karamat Musarrat
Published: November 2023

Purpose

This paper empirically examines whether sophisticated governance mechanism affects the relationship between earnings management and dividend policy of non-financial firms.

Design/methodology/approach

The sample of the study includes non-financial firms listed on the stock exchanges of twenty developed and developing economies from the period 2005–2017. The Generalized Method of Moments (GMM) was applied to estimate the econometric models.

Findings

The results confirm the positive association between earning management and the dividend payout ratio of the sample firms. These findings are in line with the signaling theory, which suggests that firms engage in earnings manipulation to signal to the market that they can maintain a smooth dividend distribution. Moreover, findings suggest that board independence, being a mechanism of corporate governance, significantly negatively moderated the relationship between earnings management and the dividend payout ratio of non-financial firms.

Practical implications

The findings provide valuable suggestions to government bodies, regulatory authorities and corporate managers to focus on the effectiveness of governance mechanisms to improve the reliability of financial reports.

Originality/value

These findings imply that the effect of earning management on the dividend payout ratio is less pronounced in firms with more independent directors on the company board.
Corporate governance and family business: a perspective article
Authors: Nakpodia Franklin
Published: November 2023

Purpose

The governance of family businesses has attracted considerable scrutiny among scholars and practitioners. This paper explores influences that have defined corporate governance practices in family firms in the last century and reflects on the possible direction of research and practice in the next century.

Design/methodology/approach

This manuscript undertakes a literature review of past and recent literature investigating corporate governance practices within family businesses.

Findings

The evolution of corporate governance in the family business literature is underpinned by centralised decision-making structures, the need to overcome fundamental corporate governance challenges, the increasing relevance of family governance models and the recognition and adoption of contemporary trends in the corporate governance space. The review also suggests that corporate governance and family business research in the next century will be dominated by technology-based governance, sustainable governance, globalisation and the validation for multi-board structures, greater attention to succession planning and diversity, and channelling significant resources to innovation.

Originality/value

The paper synthesises developments in the corporate governance–family business literature and proposes a future perspective.
Exploring drivers of ecosystem-based livelihood diversification engagement: experiences from women in agri-based economy in Sri Lanka
Authors: Sachitra Vilani , Hettiarachchi Kanchana
Published: November 2023

Purpose

Ecosystem-based livelihood diversification (ESLD) approaches have been identified as one of the best solutions to alleviate poverty and improve living standards in rural communities in developing nations. This study aims to elucidate the motivations that drive Sri Lankan women in rural agri-based community to adopt ESLD activities.

Design/methodology/approach

The sustainable livelihood approach (SLA) five pillars were used as a theoretical framework. This study was carried out with women living in farmer families located in Anuradhapura District, Sri Lanka. A purposive sampling technique was used, and semistructured interviews were performed with 46 women in a noncontrived setting. Deductive content analysis approach was used for answering research questions.

Findings

Making handcrafts using different plants, composting and home gardening are the major sources of ESLD of women in the study areas. Under the SLA factors, human resources include family size, education, vocational training, age and attitude. Social resources like participation in community work, family support received and becoming members in cooperatives encourage the women to partake in ESLD. Nonagriculture natural resources were considered as an incentive to engage in ESLD. Satisfaction with the income generated by the livelihood, other income sources and loans from the informal sector were the vital financial resources. Regarding the physical resources, the respondents were profound with infrastructure, marketplaces, training centers and tools/equipment.

Practical implications

Knowing the existing ESLD strategies and pointing out the determinant factors affecting women in practicing ESLD activities are unquestionably important in the provision of information to formulate an appropriate strategy for the development of the rural agri-based community.

Originality/value

Little is known about the ESLD efforts and the extent of adoption of ESLD practices by women in rural communities. The findings based on the SLA framework help to understand what is happening in livelihood diversifications in agri-based community and suggest important implications for the development of ESLD for the future.