bluuebunny/crossref_metadata_2025_split huggingface dataset:
Semi-supervised Omics Factor Analysis (SOFA) disentangles known and latent sources of variation in multi-omic data
Authors: Capraz Tümay , Vöhringer Harald , Kruger Serrano Klaus Sebastian Augusto , Ramirez Flores Ricardo Omar , Saez-Rodriguez Julio , Huber Wolfgang 
Published: October 2024

AbstractA fundamental design pattern in biomolecular studies is to assay the same set of samples (organisms, tissue biopsies, or individual cells) by multiple different ‘omics assays. Group Factor Analysis (GFA) and its adaptation to high-dimensional settings, Multi-Omics Factor Analysis (MOFA), are widely used as a first-line approach to analyse such data and are effective in detecting patterns of correlation, organize them into so-called latent factors, and identify common and assay-specific factors. However, in many applications a subset of the found factors just rediscovers already known covariates (e.g., disease subtypes, environmental covariates) while others may represent genuine novelty.Here, we present Semi-supervised Omics Factor Analysis (SOFA), a method that incorporates known covariates into the model upfront and focuses the factor discovery on novel sources of variation. We show SOFA’s effectiveness for discovering novel patterns by applying it to cancer, brain development and heart failure multi-omic data sets.
Small amounts of misassembly can have disproportionate effects on pangenome-based metagenomic analyses
Authors: Majernik Stephanie N. , Beaver Larry , Bradley Patrick H. 
Published: October 2024

AbstractIndividual genes from microbiomes can drive host-level phenotypes. To help identify such candidate genes, several recent tools estimate microbial gene copy numbers directly from metagenomes. These tools rely on alignments to pangenomes, which in turn are derived from the set of all individual genomes from one species. While large-scale metagenomic assembly efforts have made pangenome estimates more complete, mixed communities can also introduce contamination into assemblies, and it is unknown how robust pangenome-based metagenomic analyses are to these errors. To gain insight into this problem, we re-analyzed a case-control study of the gut microbiome in cirrhosis, focusing on commensal Clostridia previously implicated in this disease. We tested for differentially prevalent genes in theLachnospiraceae, then investigated which were likely to be contaminants using sequence similarity searches. Out of 86 differentially prevalent genes, we found that 33 (38%) were probably contaminants originating in taxa such asVeillonellaandHaemophilus, unrelated genera that were independently correlated with disease status. Our results demonstrate that even small amounts of contamination in metagenome assemblies, below typical quality thresholds, can threaten to overwhelm gene-level metagenomic analyses. However, we also show that such contaminants can be accurately identified using a method based on gene-to-species correlation. After removing these contaminants, we observe that several flagellar motility gene clusters in theLachnospira eligenspangenome are associated with cirrhosis status. We have integrated our analyses into an analysis and visualization pipeline, PanSweep, that can automatically identify cases where pangenome contamination may bias the results of gene-resolved analyses.ImportanceMetagenome-assembled genomes, or MAGs, can be constructed without pure cultures of microbes. Large scale efforts to build MAGs have yielded more complete pangenomes (i.e., sets of all genes found in one species). Pangenomes allow us to measure strain variation in gene content, which can strongly affect phenotype. However, because MAGs come from mixed communities, they can contaminate pangenomes with unrelated DNA, and how much this impacts downstream analyses has not been studied. Using a metagenomic study of gut microbes in cirrhosis as our test case, we investigate how contamination affects analyses of microbial gene content. Surprisingly, even small, typical amounts of MAG contamination (<5%) result in disproportionately high levels of false positive associations (38%). Fortunately, we show that most contaminants can be automatically flagged, and provide a simple method for doing so. Furthermore, applying this method reveals a new association between cirrhosis and gut microbial motility.
Identification of key genes and enriched biological processes in diabetes-associated traumatic brain injury through weighted gene correlation network and bioinformatics analysis
Authors: Saidu Umar Faruk , Bulama Ibrahim 
Published: October 2024

AbstractTraumatic brain injury (TBI) is a significant cause of morbidity and mortality worldwide, with long-term neurological and psychological impacts. Recent studies have indicated that diabetes (T1DM) exacerbates the outcomes of TBI, leading to more severe cognitive deficits and increased risk of complications. This study investigated the underlying molecular mechanisms and potential therapeutic targets for T1DM-associated TBI. Four mRNA datasets (GSE4745, GSE125451, GSE173975, and GSE80174) downloaded from GEO repository were used in this study. Using limma, a total of 284 differentially expressed genes (DEGs) were identified in T1DM, of which 11 were upregulated and 9 were downregulated. GSEA showed that these DEGs were significantly enriched in cell communication, lipid metabolic process, and PPAR signaling. A total of 584 DEGs were identified in TBI, of which 186 were upregulated and 9 were downregulated. GSEA showed that these DEGs were mainly enriched in immune response-regulating signaling pathway. WGCNA identified 122 significant genes in TIDM-related modules and 368 significant genes in TBI-related module. GO and KEGG enrichment analysis showed that T1DM module genes were significantly correlated with lipid metabolic process and ribosome biogenesis, while TBI module genes were significantly correlated with inflammation and immune response, including leukocyte mediated immunity, lymphocyte mediated immunity, and cytokine mediated receptor activity. PPI network analysis of T1DM module genes identified 20 hub genes, including 14 ribosomal genes: Rpl23, Rps3a, Rps6, Rpl5, Rpl17, Rps24, Rpl23a, Rps4x, Rpl9, Rps15a14, Rpl30, Rpl31, Rps25, and Rps27a-2. The hub genes were primarily related to ribosome biogenesis and RNA post-transcriptional regulation. PPI network analysis of TBI module genes identified 20 hub genes: Ptprc, Tp53, Stat1, Stat3, Tyrobp, Itgad, Csf1r, Itgb2, Rac2, Icam1, Myd88, Cd44, Vav1, Aif1, C1qa, Laptm5, B2m, Fcer1g, and Lyn. The hub genes were primarily related to inflammatory mediators and immune response. Based on the overlap of T1DM module genes and TBI module genes, Cmklr1, Mgst1, and Plin2, were identified as key genes of T1DM-associated TBI. Functional enrichment analysis showed that they were primarily enriched in the cellular response to hydroperoxide, cytokine-mediated receptor signaling activity, regulation of sequestering of triglyceride, negative regulation of IL-12 production, and positive regulation of macrophage chemotaxis. Using Reactome, Cmklr1, Mgst1, and Plin2 were related to cytokine signaling activity, neutrophil degranulation, and lipid storage, respectively. We concluded that Lipid droplet dysregulation and Neuroinflammation are the potential molecular mechanisms of T1DM-associated TBI. Cmklr1, Mgst1, and Plin2 are positively correlated with T1DM-associated TBI and may be important biomarkers and potential treatment targets for diabetic TBI.
A versatile protocol for purifying recombinant proteins fromNicotiana benthamianafor structural studies
Authors: Lawson Aaron W. , Macha Arthur , Neumann Ulla , Gunkel Monika , Chai Jijie , Behrmann Elmar , Schulze-Lefert Paul 
Published: October 2024

AbstractStructural biology is an essential tool for understanding the molecular basis of biological processes. Although predicting protein structures by fold recognition algorithms has become increasingly powerful, especially with the integration of deep-learning approaches, experimentally resolved structures are indispensable for guiding structure-function studies and for improving modelling. However, experimental structural studies of protein complexes are still challenging, owing to, for example, the necessity for high protein concentrations and purity for downstream analyses such as cryogenic electron microscopy (cryo-EM). The use ofNicotiana benthamianaleaves as a transient expression system for recombinant proteins has become an increasingly attractive approach as the plant is inexpensive to cultivate, grows rapidly, allows fast experimental turnaround and is easily scalable compared to other established systems such as insect cell cultures. UsingN. benthamianaas an expression system, we present here a robust and versatile protocol for the purification of five heterocomplexes with sizes ranging from ∼140 kDa to ∼660 kDa consisting of immunoreceptors and their associated pathogen effectors, followed by electron microscopy. The plant-based protocol was applied to verify the structure of the insect cell-derived wheat Sr35 resistosome and to co-purify and co-resolve a ∼140 kDa homodimer of the AvrSr35 effector from the fungusPuccinia graminisf sptritici(Pgt). In several cases, only a single epitope tag is needed for complex purification, reducing complications that come with multiple epitope tags and two-step affinity purifications. We identify codon usage, signal peptide fusion, epitope tag choice and detergents as critical factors for expression and purification of recombinant protein fromN. benthamianaleaves.
X-ray Diffraction Reveals Periodicity in Murine Neocortex
Authors: Murokh Sasha , Willerson Ezekiel , Lazarev Alexander , Lazarev Pavel , Brumberg Joshua C. 
Published: October 2024

AbstractBackgroundSensory experience impacts brain development. In the mouse somatosensory cortex, sensory deprivation via whisker trimming induces reductions in the perineuronal net (PNN), the size of neuronal cell bodies, the size and orientation of dendritic arbors, the density of dendritic spines, and the level of myelination, among other effects.New MethodsHere, we measured the X-ray diffraction patterns of mouse brain tissue to establish a novel method for examining nanoscale brain structures. Two groups of mice were examined: a control group and one that underwent 30 days of whisker-trimming from birth - an established method of sensory deprivation that affects the mouse barrel cortex (whisker sensory processing region of the primary somatosensory cortex). Mice were perfused, and primary somatosensory cortices (barrel cortex) were isolated for immunocytochemistry and X-ray diffraction imaging.ResultsX-ray images were characterized using a specially developed machine-learning approach, and the clusters that correspond to the two groups are well separated in the space of the principal components. The obtained values for sensitivity/specificity are 1/0.93, and the receiver operator curve classifier is 0.99.ConclusionsWe hypothesize that such separation is related to the development of different nanoscale structural components in the brains of control and sensory deprived mice. The effects of these nanoscale structural formations can be seen in PNN and other micro- and macro-scale structures and assemblies.
Suppression of Visceral Nociception by Selective C-Fiber Transmission Block Using Temporal Interference Sinusoidal Stimulation
Authors: Zhang Shaopeng , Chen Longtu , Woon Eric , Liu Jia , Ryu Jaehyeon , Chen Hsin , Fang Hui , Feng Bin 
Published: October 2024

AbstractChronic visceral pain management remains challenging due to limitations in selective targeting of C-fiber nociceptors. This study investigates temporal interference stimulation (TIS) on dorsal root ganglia (DRG) as a novel approach for selective C-fiber transmission block. We employed (1) GCaMP6 recordings in mouse whole DRG using a flexible, transparent microelectrode array for visualizing L6 DRG neuron activation, (2) ex vivo single-fiber recordings to assess sinusoidal stimulation effects on peripheral nerve axons, (3) in vivo behavioral assessment measuring visceromotor responses (VMR) to colorectal distension in mice, including a TNBS-induced visceral hypersensitivity model, and (4) immunohistological analysis to evaluate immediate immune responses in DRG following TIS. We demonstrated that TIS (2000 Hz and 2020 Hz carrier frequencies) enabled tunable activation of L6 DRG neurons, with the focal region adjustable by altering stimulation amplitude ratios. Low-frequency (20-50 Hz) sinusoidal stimulation effectively blocked C-fiber and Aδ-fiber transmission while sparing fast-conducting A-fibers, with 20 Hz showing highest efficacy. TIS of L6 DRG reversibly suppressed VMR to colorectal distension in both control and TNBS-induced visceral hypersensitive mice. The blocking effect was fine-tunable by adjusting interfering stimulus signal amplitude ratios. No apparent immediate immune responses were observed in DRG following hours-long TIS. In conclusion, TIS on lumbosacral DRG demonstrates promise as a selective, tunable approach for managing chronic visceral pain by effectively blocking C-fiber transmission. This technique addresses limitations of current neuromodulation methods and offers potential for more targeted relief in chronic visceral pain conditions.
STOPS and multivariate hierarchical aglomerative clustering: segmentation of the public regarding children’s vaccinaton communication in Slovenia
Authors: Kropivnik Samo , Vrdelja Mitja 
Published: October 2024

PurposeFrom a public health perspective, vaccination programmes significantly add to long-term, safe co-existence. However, because there is no social consensus about their benefits and risks, the promotion of vaccinations is difficult. Based on Kim and Grunig’s situational theory of problem solving (STOPS), including communicative action in problem solving (CAPS), this paper both proposes a model for identifying the involvement of mothers of young children in communication regarding vaccination and advocates for a novel approach to STOPS and CAPS data analyses.Design/methodology/approachThe methodological design develops empirical analyses of the data yielded by the STOPS model. Two approaches to determining associations between situational-motivational variables and communicative-action variables in random-sample survey data obtained in Slovenia in 2016 (N = 1704) are implemented – i.e. visual methods and multivariate agglomerative clustering algorithm.FindingsThe STOPS model has been confirmed and both data-analyses approaches have shown potential by clearly demonstrating associations and patterns in the data. Based on these findings, we conclude that they have the potential to be the norm in analysing STOPS models.Research limitations/implicationsLimitations of the study, which are still to be overcome, involve drawing on one sample in one country and testing only one set of indicators.Practical implicationsFrom an academic point of view, confirmation of both the model and the analytical power of the pragmatic data-analyses methods significantly add to communication studies. From practical and social points of view, relationships among attitudes and communication behaviour, as outlined in the exposed segments of the public, enable the improvement of every step in strategic-communication planning and implementation.Originality/valueThis paper fulfils an identified need to establish a theoretical framework and methodology of segmentation in vaccination-communication studies.
Knowledge towards health impacts of climate change among Amhara Sayint community, Northeastern Ethiopia
Authors: Kassaw Genanew Mulugeta , Malede Asmamaw , Gizeyatu Adinew , Adane Metadel , Embrandiri Asha , Keleb Awoke , Berihun Gete , Geto Abebe Kassa , Wogayehu Belachew Tekleyohannes , Abebe Gebremeskel Kibret , Zewde Tibebu Habtie , Debela Sisay Abebe , Seyoum Solomon , Luke Amana Ogeto , Wondaya Gashaw , Kide Atitegeb Abera , Moges Mekonnen , Metoyer Denise , Gebrehiwot Mesfin 
Published: October 2024

Purpose
This study aims to assess the knowledge of Amhara Sayint district community in Northeastern Ethiopia towards the health impacts of climate change.

Design/methodology/approach
A community-based cross-sectional study was conducted from 20 July to 5 September 2022, involving 605 randomly selected households in Amhara Sayint district, Northeastern Ethiopia. Data were collected through face-to-face interviews using a pilot-tested and content-validated questionnaire administered via Kobo Collect survey tool. The data were then exported to STATA for management and analysis. A proportional odds approach of ordinal logistic regression model was fitted with a 95% confidence level to identify factors associated with the community’s knowledge towards the health impacts of climate change.

Findings
Of the total respondents, 3.47% (95% confidence interval [CI]: 2.1, 5.3) and 42.98% (95% CI: 38.9, 47) had inadequate and medium levels of knowledge towards the health impacts of climate change, respectively. Proportional odds model analysis result indicated that gender (female) (adjusted odds ratio [AOR] = 1.49; 95% CI: 1.053, 2.13), wealth status (poorest) (AOR = 1.97; 95% CI: 1.01, 3.83), educational status (unable to read and write) (AOR = 4.13; 95% CI: 1.25, 13.68) and participation status in environmental protection activities (not) (AOR = 1.78; 95% CI: 1.17, 2.71) were factors that significantly associated with inadequate and medium levels of knowledge towards the health impacts of climate change.

Research limitations/implications
The result of this research is not supported by qualitative methods.

Practical implications
Residents of the study area know the climate is changing; however, they lack adequate knowledge towards the health impacts of climate change.

Social implications
Significant number of people have inadequate level of knowledge about health impacts of climate change so relevant health education is needed.

Originality/value
This research is original in its focus on assessing public knowledge about the health impacts of climate change in the Amhara Sayint district, northeastern Ethiopia, a perspective often overlooked in existing studies. Its findings are crucial for guiding future research and developing targeted public health strategies and educational initiatives.
Exploring diabetic patients’ intention to switch POCT self-monitoring glucose devices: investigating influence of perceived usefulness and perceived ease of use
Authors: Krishnan Geetha , J.N.V. Raghuram 
Published: October 2024

Purpose
The study aims to examine diabetic patients’ switching intentions toward self-monitoring blood glucose devices, incorporating perceived usefulness and perceived ease of use, with switching cost as a moderator.

Design/methodology/approach
A self-administered questionnaire was developed using established measuring scales. Data from 321 respondents was collected and analyzed using the partial least squares structural equation modeling approach.

Findings
Results indicate that perceived usefulness and perceived ease of use influence switching intention. Switching cost does not moderate the perceived usefulness, perceived ease of use and switching intention. This study reveals important information for healthcare practitioners and device manufacturers.

Originality/value
The significance and originality of this study stem from its pioneering investigation into the switching intentions of diabetic patients regarding self-monitoring glucose devices through the application of the technology acceptance model, thereby addressing a notable gap in the existing literature on diabetes management and technology adoption, which has lacked comprehensive examination of patients’ transition behaviors in this specific context.
Leadership essential to steer success within the retail sector
Authors: Bhasin Sanjay 
Published: October 2024

PurposeThe purpose of this investigation was to determine the leadership necessary for the retail sector which is having to embrace complexity induced through accelerating changes in consumer behaviour and expanding information accessibility.Design/methodology/approachSemi-structured interviews were used for across 10 disparate retail organisations deployed as case studies safeguarding all quality considerations were fully integrated.FindingsThe findings reveal brands are coping with greater complexity than before. Loyalty is eroding whilst social media increases the complexity for brands to uphold control of their image. Developing the market without sacrificing exclusivity or alienating core consumers necessitates effective leadership. The deductions revealed that despite some leadership styles seemingly more conducive, that specific qualities are more important for the retail sector.Research limitations/implicationsBy selecting ten organisations every effort was made to ensure a greater degree of credibility in the findings. It is acknowledged that this investigation is sector specific. Nonetheless, there exists considerable transferability value as the role of leadership within the retail sector can mirror expectations within other environments.Originality/valueIt was validated that leaders need to foster an organisational culture promoting continuous learning whilst introducing a consumer-first perspective across the business. The findings reinforce how specific traits, behaviours and styles are imperative amongst leaders preserving the success of the retail organisation with less focus on specific leadership styles.
Exploring the dynamics of firm growth: the interplay of decision-making logic
Authors: Farokhmanesh Taraneh , Davari Ali , Baghersad Vajihe , Sajadi Seyed Mojtaba 
Published: October 2024

Purpose
This paper investigates how various emergent theoretical perspectives in entrepreneurship research, representing diverse decision-making logics, influence firm growth and evolution. It explores the interaction among decision-making logics, including experimentation, affordable loss, flexibility and pre-commitment as components of effectuation, alongside causation and bricolage and their synergistic effects on firm growth.

Design/methodology/approach
This study uses a multi-phase, discovery-oriented approach. Initially, insights from existing literature on decision-making logic were combined with in-depth interviews with 10 Iranian entrepreneurs within the food sector. This phase used alternative template research to evaluate the principles of effectuation, causation and bricolage within case study data depicting firm growth. Subsequently, a self-administered survey was developed based on these insights and distributed to 205 entrepreneurs in Iran. The survey data was analysed using fuzzy-set qualitative comparative analysis (fsQCA) to identify key factors and pathways influencing firm growth.

Findings
Using a discovery-oriented approach, this study formulates a comprehensive framework detailing decision-making logics that influence firm growth. Through fsQCA, 12 distinct paths are identified, highlighting the complex interplay of causation, effectuation and bricolage in high-growth firms within the food sector.

Research limitations/implications
This study has limitations. FsQCA identifies only logically sufficient combinations, suggesting potential for exploring alternative pathways in future research. Given COVID-19’s impact on the food sector, examining decision-making logic across diverse contexts and industries is advisable. Additionally, exploring how bricolage, causation and effectuation affect outcomes like new product development and innovation is essential in a growth-focused context. It is also important to consider environmental and organizational factors influencing growth.

Originality/value
This paper pioneers the examination of emerging theoretical paradigms in entrepreneurship and their impact on firm growth. It identifies critical configurations of causation, effectuation and bricolage, providing actionable insights for navigating dynamic business environments.