Unbiased Approach Research Articles

Enteric glia regulate Paneth cell secretion and intestinal microbial ecology.

Glial cells of the enteric nervous system (ENS) interact closely with the intestinal epithelium and secrete signals that influence epithelial cell proliferation and barrier formation in vitro. Whether these interactions are important in vivo, however, is unclear because previous studies reached conflicting conclusions (Prochera and Rao, 2023). To better define the roles of enteric glia in steady state regulation of the intestinal epithelium, we characterized the glia in closest proximity to epithelial cells and found that the majority express the gene Proteolipid protein 1 (PLP1) in both mice and humans. To test their functions using an unbiased approach, we genetically depleted PLP1+ cells in mice and transcriptionally profiled the small and large intestines. Surprisingly, glial loss had minimal effects on transcriptional programs and the few identified changes varied along the gastrointestinal tract. In the ileum, where enteric glia had been considered most essential for epithelial integrity, glial depletion did not drastically alter epithelial gene expression but caused a modest enrichment in signatures of Paneth cells, a secretory cell type important for innate immunity. In the absence of PLP1+ glia, Paneth cell number was intact, but a subset appeared abnormal with irregular and heterogenous cytoplasmic granules, suggesting a secretory deficit. Consistent with this possibility, ileal explants from glial-depleted mice secreted less functional lysozyme than controls with corresponding effects on fecal microbial composition. Collectively, these data suggest that enteric glia do not exert broad effects on the intestinal epithelium but have an essential role in regulating Paneth cell function and gut microbial ecology.

Enteric glia regulate Paneth cell secretion and intestinal microbial ecology

Glial cells of the enteric nervous system (ENS) interact closely with the intestinal epithelium and secrete signals that influence epithelial cell proliferation and barrier formation in vitro. Whether these interactions are important in vivo, however, is unclear because previous studies reached conflicting conclusions (Prochera and Rao, 2023). To better define the roles of enteric glia in steady state regulation of the intestinal epithelium, we characterized the glia in closest proximity to epithelial cells and found that the majority express the gene Proteolipid protein 1 (PLP1) in both mice and humans. To test their functions using an unbiased approach, we genetically depleted PLP1+ cells in mice and transcriptionally profiled the small and large intestines. Surprisingly, glial loss had minimal effects on transcriptional programs and the few identified changes varied along the gastrointestinal tract. In the ileum, where enteric glia had been considered most essential for epithelial integrity, glial depletion did not drastically alter epithelial gene expression but caused a modest enrichment in signatures of Paneth cells, a secretory cell type important for innate immunity. In the absence of PLP1+ glia, Paneth cell number was intact, but a subset appeared abnormal with irregular and heterogenous cytoplasmic granules, suggesting a secretory deficit. Consistent with this possibility, ileal explants from glial-depleted mice secreted less functional lysozyme than controls with corresponding effects on fecal microbial composition. Collectively, these data suggest that enteric glia do not exert broad effects on the intestinal epithelium but have an essential role in regulating Paneth cell function and gut microbial ecology.

Image reconstruction of ultrasonic transmission tomography using spectral-based graph convolution network

Abstract Ultrasonic transmission tomography (UTT) is a crucial imaging modality for non-destructive testing and quality assessment in industrial settings. The reconstruction of high-quality images from limited, irregular, and noisy measurement of ultrasound measurements poses a significant challenge due to the ill-posed nature of the inverse problem. Therefore, the proposed method involves formulating the UTT image reconstruction problem into a graph-based learning task. In this task, nodes symbolize locations on the inspected object, while edges illustrate the connections between those locations. Furthermore, it employs the graph Laplacian function to inject graph structure into the learning algorithm to extract the structural details of the acoustic parameter distribution from the ultrasound measurements. The spectral graph convolutional neural networks (SGCNN) enforce smoothness across the graph. The unbiased risk estimation-based spectral approach efficiently shapes the irregularity graph structure. The proposed SGCNN is tailored to effectively learn and exploit the complex relationships between transmitted ultrasound measurements and the underlying substantial properties in an ultrasound spectrum. Simulation and experimental tests are carried out to validate the proposed algorithm’s performance. In addition, the SGCNN algorithm is compared to graph convolution neural network (GCNN) and traditional reconstruction methods, showcasing its superior ability to reconstruct detailed and accurate images by evaluating performance metrics.

An unbiased genomewide screen uncovers 7 genes that drive hematopoietic stem cell fate from mouse embryonic stem cells.

An unbiased genomewide screen uncovers 7 genes that drive hematopoietic stem cell fate from mouse embryonic stem cells.

Aging, mitochondrial dysfunction, and cerebral microhemorrhages: a preclinical evaluation of SS-31 (elamipretide) and development of a high-throughput machine learning-driven imaging pipeline for cerebromicrovascular protection therapeutic screening.

Cerebral microhemorrhages (CMHs, also known as cerebral microbleeds) contribute to vascular cognitive impairment and dementia (VCID), with aging and hypertension being key risk factors. Mitochondrial oxidative stress is a hallmark of cerebrovascular aging, leading to endothelial dysfunction. This study tests the hypothesis that increased mitochondrial oxidative stress contributes to age-related CMH susceptibility and evaluates the mitochondrial-targeted antioxidative peptide SS-31 (elamipretide) as a potential protective agent in an aged, hypertensive mouse model. Concurrently, we developed a high-throughput, machine learning-driven imaging pipeline to enhance CMH quantification and facilitate the screening of anti-aging vasoprotective interventions. To detect CMHs, brain sections were labeled with diaminobenzidine (DAB) and digitized using a slide scanner-based imaging platform. We developed multiple quantification tools, including color space transformation for enhanced contrast separation and a supervised machine-learning approach utilizing a random forest algorithm to generate whole-brain 3D reconstructions and precisely localize CMHs. We optimized a semi-automated detection method integrating color space transformation and machine learning, benchmarking it against traditional manual counting and color deconvolution-based approaches. While SS-31 treatment did not significantly mitigate hypertension-induced CMH burden in aged mice, our high-throughput imaging pipeline provided a reliable, scalable, and unbiased approach to CMH detection, reducing processing time while improving accuracy. This methodological advancement paves the way for future preclinical studies evaluating therapeutic strategies for cerebrovascular protection in aging. Our findings underscore the need for multi-targeted interventions to mitigate CMH-related neurovascular impairments and prevent VCID.

Transcriptomics in the era of long-read sequencing.

Transcriptome sequencing revolutionized the analysis of gene expression, providing an unbiased approach to gene detection and quantification that enabled the discovery of novel isoforms, alternative splicing events and fusion transcripts. However, although short-read sequencing technologies have surpassed the limited dynamic range of previous technologies such as microarrays, they have limitations, for example, in resolving full-length transcripts and complex isoforms. Over the past 5 years, long-read sequencing technologies have matured considerably, with improvements in instrumentation and analytical methods, enabling their application to RNA sequencing (RNA-seq). Benchmarking studies are beginning to identify the strengths and limitations of long-read RNA-seq, although there remains a need for comprehensive resources to guide newcomers through the intricacies of this approach. In this Review, we provide a comprehensive overview of the long-read RNA-seq workflow, from library preparation and sequencing challenges to core data processing, downstream analyses and emerging developments. We present an extensive inventory of experimental and analytical methods and discuss current challenges and prospects.

MOTHER–DAUGHTER RELATIONSHIP IN ALI SMITH’S NOVEL «AUTUMN»

This study scrutinizes mother-daughter relationship theory through literary analysis, focusing on the primary female characters in Ali Smith’s novel «Autumn»: the mother, Wendy, and the daughter, Elisabeth. It seeks to explore and comprehend the roles of these women as portrayed by the contemporary Scottish writer. Mothers exert significant influence on their children from birth, shaping their mental, physical, gender identification and personal identity. Moreover, the perception of the relationship between the same genders boils down to the mother’s unbiased approach to it. Consequently, the nature of maternal relationships can profoundly impact children’s societal roles and self-perceptions. The primary objective is to uncover Ali Smith’s portrayal of mother and daughter roles through language and culture, particularly her treatment of enmeshed mother-daughter relationships in contemporary English literature. The data is derived from «Autumn», using conversational analysis as the principal method to meticulously examine the mother-daughter dyads and their interactions in the novel. Keywords: mother-daughter relationship theory, Ali Smith, English fiction, contemporary novel, independence.

Zika but not Dengue virus infection limits NF-κB activity in human monocyte-derived dendritic cells and suppresses their ability to activate T cells

Understanding flavivirus immunity is critical for the development of pan-flavivirus vaccines. Dendritic cells (DC) coordinate antiviral innate and adaptive immune responses, and they can be targeted by flaviviruses as a mechanism of immune evasion. Using an unbiased genome-wide approach designed to specifically identify flavivirus-modulated pathways, we found that, while dengue virus (DENV) robustly activates DCs, Zika virus (ZIKV) causes minimal activation of genes involved in DC activation, maturation, and antigen presentation, reducing cytokine secretion and the stimulation of allogeneic and peptide-specific T cell responses. Mechanistically, ZIKV inhibits DC maturation by suppressing NF-κB p65 recruitment and the subsequent transcription of proinflammatory and DC maturation-related genes. Thus, we identify a divergence in the effects of ZIKV and DENV on the host T cell response, highlighting the need to factor such differences into the design of anti-flavivirus vaccines.

FTO suppresses DNA repair by inhibiting PARP1

Maintaining genomic integrity and faithful transmission of genetic information is essential for the survival and proliferation of cells and organisms. DNA damage, which threatens the integrity of the genome, is rapidly sensed and repaired by mechanisms collectively known as the DNA damage response. The RNA demethylase FTO has been implicated in this process; however, the underlying mechanism by which FTO regulates DNA repair remains unclear. Here, we use an unbiased quantitative proteomic approach to identify the proximal interactome of endogenous FTO protein. Our results demonstrate a direct interaction with the DNA damage sensor protein PARP1, which dissociates upon ultraviolet stimulation. FTO inhibits PARP1 catalytic activity and controls its clustering in the nucleolus. Loss of FTO enhances PARP1 enzymatic activity and the rate of PARP1 recruitment to DNA damage sites, accelerating DNA repair and promoting cell survival. Interestingly, FTO regulates PARP1 function and DNA damage response independent of its catalytic activity. We conclude that FTO is an endogenous negative regulator of PARP1 and the DNA damage response in cells beyond its role as an RNA demethylase.

Simulation and Quantitative Analysis of Spatial Centromere Distribution Patterns.

A prominent feature of eukaryotic chromosomes are centromeres, which are specialized regions of repetitive DNA required for faithful chromosome segregation during cell division. In interphase cells, centromeres are non-randomly positioned in the three-dimensional space of the nucleus in a cell type-specific manner. The functional relevance and the cellular mechanisms underlying this localization are unknown, and quantitative methods to measure distribution patterns of centromeres in 3D space are needed. Here, we developed an analytical framework that combines sensitive clustering metrics and advanced modeling techniques for the quantitative analysis of centromere distributions at the single-cell level. To identify a robust quantitative measure for centromere clustering, we benchmarked six metrics for their ability to sensitively detect changes in centromere distribution patterns from high-throughput imaging data of human cells, both under normal conditions and upon experimental perturbation of centromere distribution. We found that Ripley's K function has the highest accuracy with minimal sensitivity to variations in the number of centromeres, making it the most suitable metric for measuring centromere distributions. As a complementary approach, we also developed and validated spatial models to replicate centromere distribution patterns, and we show that a radially shifted Gaussian distribution best represents the centromere patterns seen in human cells. Our approach creates tools for the quantitative characterization of spatial centromere distributions with applications in both targeted studies of centromere organization and unbiased screening approaches.

Recruitment Process using Federated AI: An Unbiased Approach

Recruitment Process using Federated AI: An Unbiased Approach

DiCE: differential centrality-ensemble analysis based on gene expression profiles and protein-protein interaction network.

Uncovering key genes that drive diseases and cancers is crucial for advancing understanding and developing targeted therapies. Traditional differential expression analysis often relies on arbitrary cutoffs, missing critical genes with subtle expression changes. Some methods incorporate protein-protein interactions (PPIs) but depend on prior disease knowledge. To address these challenges, we developed DiCE (Differential Centrality-Ensemble), a novel approach that combines differential expression with network centrality analysis, independent of prior disease annotations. DiCE identifies candidate genes, refines them with an information gain filter, and reconstructs a condition-specific weighted PPI network. Using centrality measures, DiCE ranks genes based on expression shifts and network influence. Validated on prostate cancer datasets, DiCE identified genes over-represented in key pathways and cancer fitness genes, significantly correlating with disease-free survival (DFS), despite DFS not being used in selection. DiCE offers a comprehensive, unbiased approach to identifying disease-associated genes, advancing biomarker discovery and therapeutic development.

Defining lipedema's molecular hallmarks by multi-omics approach for disease prediction in women.

Defining lipedema's molecular hallmarks by multi-omics approach for disease prediction in women.

The added value of metagenomic next-generation sequencing in central nervous system infections: a systematic review of case reports.

The diversity of pathogens causing central nervous system (CNS) infections presents a diagnostic challenge. Patient demographics and geographical location affect the likelihood of certain pathogens causing infection. Current diagnostic methods rely on labour-intensive cultivation or targeted detection. Metagenomic next-generation sequencing (mNGS) is a promising tool for detecting pathogens in CNS infections, offering an unbiased approach. To enhance our understanding of patient demographics and the range of pathogens identified through mNGS, we conducted a systematic review of case reports. The PubMed database was searched in March 2024. Case reports on CNS infections and mNGS published from January 2014 through February 2024 were included based on predefined criteria. The search yielded 649 articles, of which 76 were included, encompassing 104 patients. Most patients were male (75%), the median age was 31,5 years [0-75] and 28% were immunocompromised. The most common diagnosis was encephalitis (36%), followed by meningitis (23%) and meningoencephalitis (22%). 53 unique pathogens were identified, comprising 27 different viruses, 19 bacteria, 5 parasites, and 2 fungi. Syndromic encephalitis/meningitis panels would only have detected four of the viruses and five of the bacteria. Additionally, 14 of the bacterial species are considered slow-growing or fastidious and could be challenging to detect by culture. The application of mNGS in diagnosing CNS infections reveals the diversity of pathogens responsible for these severe infections, thereby improving diagnostics and facilitating targeted treatment. While case reports may be subjected to bias, they provide valuable insights into the use of mNGS in this clinical context.

Changes in iPSC-astrocyte morphology reflect Alzheimer's disease patient clinical markers.

Human induced pluripotent stem cells (iPSCs) provide powerful cellular models of Alzheimer's disease (AD) and offer many advantages over non-human models, including the potential to reflect variation in individual-specific pathophysiology and clinical symptoms. Previous studies have demonstrated that iPSC-neurons from individuals with Alzheimer's disease (AD) reflect clinical markers, including β-amyloid (Aβ) levels and synaptic vulnerability. However, despite neuronal loss being a key hallmark of AD pathology, many risk genes are predominantly expressed in glia, highlighting them as potential therapeutic targets. In this work iPSC-derived astrocytes were generated from a cohort of individuals with high versus low levels of the inflammatory marker YKL-40, in their cerebrospinal fluid (CSF). iPSC-derived astrocytes were treated with exogenous Aβ oligomers and high content imaging demonstrated a correlation between astrocytes that underwent the greatest morphology change from patients with low levels of CSF-YKL-40 and more protective APOE genotypes. This finding was subsequently verified using similarity learning as an unbiased approach. This study shows that iPSC-derived astrocytes from AD patients reflect key aspects of the pathophysiological phenotype of those same patients, thereby offering a novel means of modelling AD, stratifying AD patients and conducting therapeutic screens.

Construction of a Single-cell Atlas of Thyroid Cancer

Introduction: Differentiated thyroid cancer generally has a favorable prognosis; however, the cure rate remains low for patients with metastatic or undifferentiated thyroid cancer. Moreover, this group of patients exhibits diverse responses to different treatments. To address this, single- cell RNA sequencing (scRNA-seq) offers an unbiased approach to reveal the heterogeneity within and between tumor cells. Using, scRNA-seq, we aimed to explore the intricate ecosystem of thyroid cancer, potentially providing novel insights into clinical cancer staging and treatment strategies. Methods: We conducted a thorough analysis by screening thyroid cancer and paraneoplastic tissues from 20 patients sourced from the Gene Expression Omnibus database. The dataset comprised 11 primary tumor tissues, 6 paraneoplastic tissues, 8 metastatic lymph nodes, and 2 distant metastases of papillary thyroid cancer. Through comprehensive bioinformatic analyses, we constructed a panoramic single-cell atlas of thyroid cancer (THCA). Results: Our findings revealed significant heterogeneity in gene expression among tumor cells from different patients with THCA, contributing to the development of a comprehensive single-- cell landscape. Notably, the long noncoding RNA (lncRNA) gene XIST exhibited higher abundance in anaplastic thyroid cancer (ATC) tumor cells. Additionally, we identified an enriched m6A locus in lncRNA XIST and observed high expression of the m6A “reader” IGF2BP3, as well as low expression of the “encoder” VIRMA. Based on these observations, we hypothesized that IGF2BP3 and VIRMA could augment the expression of lncRNA XIST, thereby promoting the malignant proliferation and invasion of ATC. Conclusion: By leveraging scRNA-seq technology, our study sheds light on the intricate molecular characteristics of THCA lesions. These findings have the potential to revolutionize our understanding of thyroid cancer pathogenesis and pave the way for innovative therapeutic interventions.

When Rivals Are Absent: Male Aggression Towards Females in Bluefin Killifish.

The process of obtaining mates, mating, and (potentially) caring for offspring is costly. While there are inherent costs to reproduction, behavioral interactions among individuals are often the primary drivers of reproductive costs. In many species, males frequently compete for territories and females; females may compete for food or males; males often harass females. Here, we sought to determine whether reproductive costs were primarily due to male/male competition, female/female competition, or male/female interactions in the bluefin killifish (Lucania goodei) using an unbiased approach that examined aggressive behaviors and interactions in both sexes. In this species, males hold small spawning territories during the breeding season, which they guard from competitors. Females visit the territories daily to spawn. To manipulate the potential for male and female competition and male/female interactions, we altered the sex ratio and density of each sex across four treatments (1 male: 1 female, 1 male: 3 females, 3 males: 1 female, 3 males: 3 females). Female mortality was higher than male mortality. Surprisingly, female mortality and male aggressive behaviors towards females (i.e., chases) were highest in treatments with a single male. Male-male aggression was present, but males often resolved these disputes via signaling by flaring their fins. There was little evidence for overt aggression among females. When males lack rivals, they turn their territorial defense towards females. These costs help explain why, in nature, females promptly leave male territories following spawning and join loose shoals with conspecific females and minnows.

Redefining macrophage phenotypes after spinal cord injury: An open data approach.

Redefining macrophage phenotypes after spinal cord injury: An open data approach.

Handling of missing component information for common composite score outcomes used in axial spondyloarthritis research when complete-case analysis is unbiased

BackgroundObservational data on composite scores often comes with missing component information. When a complete-case (CC) analysis of composite scores is unbiased, preferable approaches of dealing with missing component information should also be unbiased and provide a more precise estimate. We assessed the performance of several methods compared to CC analysis in estimating the means of common composite scores used in axial spondyloarthritis research.MethodsIndividual mean imputation (IMI), the modified formula method (MF), overall mean imputation (OMI), and multiple imputation of missing component values (MI) were assessed either analytically or by means of simulations from available data collected across Europe. Their performance in estimating the means of the Bath Ankylosing Spondylitis Disease Activity Index (BASDAI), the Bath Ankylosing Spondylitis Functional Index (BASFI), and the Ankylosing Spondylitis Disease Activity Score based on C-reactive protein (ASDAS-CRP) in cases where component information was set missing completely at random was compared to the CC approach based on bias, variance, and coverage.ResultsLike the MF method, IMI uses a modified formula for observations with missing components resulting in modified composite scores. In the case of an unbiased CC approach, these two methods yielded representative samples of the distribution arising from a mixture of the original and modified composite scores, which, however, could not be considered the same as the distribution of the original score. The IMI and MF method are, thus, intrinsically biased. OMI provided an unbiased mean but displayed a complex dependence structure among observations that, if not accounted for, resulted in severe coverage issues. MI improved precision compared to CC and gave unbiased means and proper coverage as long as the extent of missingness was not too large.ConclusionsMI of missing component values was the only method found successful in retaining CC’s unbiasedness and in providing increased precision for estimating the means of BASDAI, BASFI, and ASDAS-CRP. However, since MI is susceptible to incorrect implementation and its performance may become questionable with increasing missingness, we consider the implementation of an error-free CC approach a valid and valuable option.Trial registrationNot applicable as study uses data from patient registries.

Teaching Academic Writing Skills: A Narrative Literature Review of Unifying Academic Values through Academic Integrity

Academic integrity continues to concern educators worldwide. Furthermore, general guidelines for ensuring academic integrity do not seem to encompass all the angles that are required to be taken into consideration when exploring the factors that contribute to multicultural students’ decision to adhere to the norms and values of academic integrity. This literature review focuses on how academic values can be unified through academic integrity, and specifically explores factors and perspectives of utilising academic integrity to unify academic values when teaching academic writing. The dimensions of academic values explored in this paper are: a) beliefs and attitudes of multicultural undergraduate students and the theory of planned behaviour (TPB), b) the value of academic performance in academic writing classes, c) exploring the development of multicultural students’ authorial voice while maintaining academic integrity, and d) using technology to encourage academic integrity in academic writing classes. Over 56 identified sources were chosen carefully to ensure unbiased approaches to the issues of academic integrity and development of academic writing skills. The authors explored the issues from a variety of perspectives. The gap noticed in the review of literature is the disconnection between academic values and academic integrity. The authors make recommendations for future research.