Specific Expression Research Articles

Biomechanical and machine learning approaches to automating the identification of musical styles and emotions through human motion analysis

This study explores the intricate relationship between biomechanical movements and musical expression, focusing on the identification of musical styles and emotions. Violin performance is characterized by complex interactions between physical actions—such as bowing techniques, finger placements, and posture—and the resulting acoustic output. Recent advances in motion capture technology and sound analysis have enabled a more objective examination of these processes. However, the current literature frequently addresses biomechanics and acoustic features in isolation, lacking an integrated understanding of how physical movements translate into specific musical expressions. Machine Learning (ML), particularly Long Short-Term Memory (LSTM) networks, provides a promising avenue for bridging this gap. LSTM models are adept at capturing temporal dependencies in sequential data, making them suitable for analyzing the dynamic nature of violin performance. In this work, they have proposed a comprehensive model that combines biomechanical analysis with Mel-spectrogram-based LSTM modeling to automate the identification of musical styles and emotions in violin performances. Using motion capture systems, Inertial Measurement Units (IMUs), and high-fidelity audio recordings, we collected synchronized biomechanical and acoustic data from violinists performing various musical excerpts. The LSTM model was trained on this dataset to learn the intricate connections between physical movements and the acoustic features of each performance. Key findings from the study demonstrate the effectiveness of this integrated approach. The LSTM model achieved a validation accuracy of 92.5% in classifying musical styles and emotions, with precision, recall, and F1-score reaching 94.3%, 92.6%, and 93.4%, respectively, by the 100th epoch. The analysis also revealed strong correlations between specific biomechanical parameters, such as shoulder joint angle and bowing velocity, and acoustic features, like sound intensity and vibrato amplitude.

Specific human gene expression in response to infection is an effective marker for diagnosis of latent and active tuberculosis

RNA sequencing and microarray analysis revealed transcriptional markers expressed in whole blood can differentiate active pulmonary TB (ATB) from other respiratory diseases (ORDs), and latent TB infection (LTBI) from healthy controls (HC). Here we describe a streamlined reverse transcriptase quantitative polymerase chain reaction (RT-qPCR) assay that could be applied at near point-of-care for diagnosing and distinguishing ATB from ORDs and LTBI from HC. A literature review was undertaken to identify the most plausible host-gene markers (HGM) of TB infection. Primers, and dual labelled hydrolysis probes were designed and analytically evaluated for accuracy in an in-vitro model of infection using a lung fibroblast cell-line. Best performing genes were multiplexed into panels of 2–4 targets and taken forward for clinical evaluation. Mycobacteria Growth Indicator Tube and QuantiFERON-TB Gold Plus were used as reference tests for ATB and LTBI respectively. A total of 16 HGM were selected and incorporated into five multiplex RT-qPCR panels. PCR assay efficiency of all evaluated targets was ≥ 90% with a median analytical sensitivity of 292 copies/µl [IQR: 215.0-358.3 copies/µl], and a median limit of quantification of 61.7 copies/µl [IQR: 29.4-176.3 copies/µl]. Clinically, ATB was characterised by higher gene expression than ORDs, while LTBI was associated with lower gene expression than HC, Kruskal-Wallis p < 0.0001. Crucially, BATF2, CD64, GBP5, C1QB, GBP6, DUSP3, and GAS6 exhibited high differentiative ability for ATB from ORDs, LTBI or HC while KLF2, PTPRC, NEMF, ASUN, and ZNF296 independently discriminated LTBI from HC. Our results show that different HGM maybe required for ATB and LTBI differentiation from ORDs or HC respectively and demonstrate the feasibility of host gene-based RT-qPCR to diagnose ATB and LTBI at near point-of-care.

Transforming Cardiotoxicity Detection in Cancer Therapies: The Promise of MicroRNAs as Precision Biomarkers

Cardiotoxicity (CDTX) is a critical side effect of many cancer therapies, leading to increased morbidity and mortality if not addressed. Early detection of CDTX is essential, and while echocardiographic measures like global longitudinal strain offer promise in identifying early myocardial dysfunction, the search for reliable biomarkers continues. MicroRNAs (miRNAs) are emerging as important non-coding RNA molecules that regulate gene expression post-transcriptionally, influencing key biological processes such as the cell cycle, apoptosis, and stress responses. In cardiovascular diseases, miRNAs have demonstrated potential as biomarkers due to their stability in circulation and specific expression patterns that reflect pathological changes. Certain miRNAs have been linked to CDTX and hold promise for early detection, prognosis, and therapeutic targeting. These miRNAs not only assist in identifying early cardiac injury, but also offer opportunities for personalized interventions by modulating their expression to influence disease progression. As research advances, integrating miRNA profiling with traditional diagnostic methods could enhance the management of CDTX in cancer patients, paving the way for improved patient outcomes and more tailored therapeutic strategies. Further clinical studies are essential to validate the clinical utility of miRNAs in managing CDTX.

Expression Analysis of the Extensive Regulation of Mitogen-Activated Protein Kinase (MAPK) Family Genes in Buckwheat (Fagopyrum tataricum) During Organ Differentiation and Stress Response

The mitogen-activated protein kinase (MAPK) signaling cascade is a unique and relatively conserved signaling pathway in eukaryotes, transmitting extracellular signals into cells through successive phosphorylation and eliciting appropriate responses from the organism. While its mechanism in plant immune response has been partially elucidated in Arabidopsis, it has been rarely examined in Tartary buckwheat (Fagopyrum tataricum). Based on the conserved MAPK domain, we identified 16 MAPK family genes in Tartary buckwheat. The FtMAPKs have similar structures and motif compositions, indicating that this gene family is conserved yet functionally diverse. Using quantitative reverse transcription polymerase chain reaction (qRT-PCR) analysis, we observed significant expression variation in 15 genes across different organs, except for FtMAPK12. FtMAPK9 showed specific expression in vegetative organs, FtMAPK4 in reproductive organs, and FtMAPK1 and FtMAPK10 in leaves and flowers, respectively, indicating their regulatory roles in Tartary buckwheat development. Following drought and salt stress treatments, 12 and 14 FtMAPKs, respectively, showed significantly altered expression in leaves exhibiting notable biological oxidation. Among these, FtMAPK3, FtMAPK4, and FtMAPK8 demonstrated highly significant changes across both treatments. Transcriptome analysis confirmed these findings, suggesting that these three genes play pivotal roles in Tartary buckwheat’s response to abiotic stress and hold potential for molecular breeding improvements.

Exploring Extracellular Vesicle Surface Protein Markers Produced by Glioblastoma Tumors: A Characterization Study Using In Vitro 3D Patient-Derived Cultures

Background/Objectives: Glioblastoma (GBM) is an aggressive brain cancer with limited treatment options. Extracellular vesicles (EVs) derived from GBM cells contain important biomarkers, such as microRNAs, proteins, and DNA mutations, which are involved in tumor progression, invasion, and resistance to treatment. Identifying surface markers on these EVs is crucial for their isolation and potential use in noninvasive diagnosis. This study aimed to use tumor-derived explants to investigate the surface markers of EVs and explore their role as diagnostic biomarkers for GBM. Methods: Tumor explants from nine GBM patients without IDH1/IDH2 mutations or 1p-19q co-deletion were cultured to preserve both tumor viability and cytoarchitecture. EVs were collected from the tumor microenvironment using differential centrifugation, filtration, and membrane affinity binding. Their surface protein composition was analyzed through multiplex protein assays. RNA-Seq data from TCGA and GTEx datasets, along with in silico single-cell RNA-seq data, were used to assess EV surface biomarker expression across large GBM patient cohorts. Results: The in vitro model successfully replicated the tumor microenvironment and produced EVs with distinct surface markers. Biomarker analysis in large datasets revealed specific expression patterns unique to GBM patients compared with healthy controls. These markers demonstrated potential as a GBM-specific signature and were correlated with clinical data. Furthermore, in silico single-cell RNA-seq provided detailed insights into biomarker distribution across different cell types within the tumor. Conclusions: This study underscores the efficacy of the tumor-derived explant model and its potential to advance the understanding of GBM biology and EV production. A key innovation is the isolation of EVs from a model that faithfully mimics the tumor’s original cytoarchitecture, offering a deeper understanding of the cells involved in EV release. The identified EV surface markers represent promising targets for enhancing EV isolation and optimizing their use as diagnostic tools. Moreover, further investigation into their molecular cargo may provide crucial insights into tumor characteristics and evolution.

Genome-wide comparative analysis of photosynthetic enzymatic genes provides novel insights into foxtail millet and other cereals

C4 crops have more efficient photosynthetic pathways that enable their higher photosynthetic capacities as well as nitrogen and water use efficiencies than C3 crops. Previous research has demonstrated that the genomes of C3 species include and express every gene needed for the C4 photosynthesis pathway. However, very little is known about the dynamics and evolutionary history of such genetic evolution in C4 plants. In this study, the genes encoding five key photosynthetic pathway enzymes in the genomes of C3 (rice), C4 (maize, sorghum, and foxtail millet), and CAM (pineapple) crops were identified and compared systematically. The numbers of genes in these photosynthetic enzymes were highest in the C4 crops like sorghum and foxtail millet, while only eight genes were identified in the CAM plant. However, 16 genes were identified in the C3 crop rice. Furthermore, we performed physical, chemical, gene structure and, cis-element analyses to obtain complete insights into these key genes. Tissue-specific expressions showed that most of the photosynthetic genes are expressed in the leaf tissues. Comparisons of the expression characteristics confirmed that the expression patterns of non-photosynthetic gene copies were relatively conserved among the species, while the C4 gene copies in the C4 species acquired new tissue expression patterns during evolution. Additionally, multiple sequence features that could affect C4 gene expressions and subcellular localization were found in the coding and promoter regions. Our research also highlights the variations in how different genes have evolved within the C4 photosynthetic pathway, and we confirmed that specific high expressions in the leaves and right distribution within the cells were crucial for the development of the C4 photosynthetic abilities. The findings of this study are expected to aid in understanding the evolutionary process of the C4 photosynthetic pathway in grasses as well as offer insights for modifying the C4 photosynthetic pathways in wheat, rice, and other significant C3 cereal crops.

Integrative analysis of transcriptome and proteome wide association studies prioritized functional genes for obesity.

Genome-wide association studies have identified dozens of genomic loci for obesity. However, functional genes and their detailed genetic mechanisms underlying these loci are mainly unknown. In this study, we conducted an integrative study to prioritize plausibly functional genes by combining information from genome-, transcriptome- and proteome-wide association analyses. We first conducted proteome-wide association analyses and transcriptome-wide association analyses for the six obesity-related traits. We then performed colocalization analysis on the identified loci shared between the proteome- and transcriptome-association analyses. Finally, we validated the identified genes with other plasma/blood reference panels. The highlighted genes were assessed for expression of other tissues, single-cell and tissue specificity, and druggability. We prioritized 4 high-confidence genes (FASN, ICAM1, PDCD6IP, and YWHAB) by proteome-wide association studies, transcriptome-wide association studies, and colocalization analyses, which consistently influenced the variation of obesity traits at both mRNA and protein levels. These 4 genes were successfully validated using other plasma/blood reference panels. These 4 genes shared regulatory structures in obesity-related tissues. Single-cell and tissue-specific analyses showed that FASN and ICAM1 were explicitly expressed in metabolism- and immunity-related tissues and cells. Furthermore, FASN and ICAM1 had been developed as drug targets. Our study provided novel promising protein targets for further mechanistic and therapeutic studies of obesity.

Fixation patterns in pairs of facial expressions—preferences of self-critical individuals

So far, studies have revealed some differences in how long self-critical individuals fixate on specific facial expressions and difficulties in recognising these expressions. However, the research has also indicated a need to distinguish between the different forms of self-criticism (inadequate or hated self), the key underlying factor in psychopathology. Therefore, the aim of the current research was to explore fixation patterns for all seven primary emotions (happiness, sadness, fear, disgust, contempt, anger, and surprise) and the neutral face expression in relation to level of self-criticism by presenting random facial stimuli in the right or left visual field. Based on the previous studies, two groups were defined, and the pattern of fixations and eye movements were compared (high and low inadequate and hated self). The research sample consisted of 120 adult participants, 60 women and 60 men. We used the Forms of Self-Criticizing and Self-Reassuring Scale to measure self-criticism. As stimuli for the eye-tracking task, we used facial expressions from the Umeå University Database of Facial Expressions database. Eye movements were recorded using the Tobii X2 eye tracker. Results showed that in highly self-critical participants with inadequate self, time to first fixation and duration of first fixation was shorter. Respondents with higher inadequate self also exhibited a sustained pattern in fixations (total fixation duration; total fixation duration ratio and average fixation duration)—fixation time increased as self-criticism increased, indicating heightened attention to facial expressions. On the other hand, individuals with high hated self showed increased total fixation duration and fixation count for emotions presented in the right visual field but did not differ in initial fixation metrics in comparison with high inadequate self group. These results suggest that the two forms of self-criticism - inadequate self and hated self, may function as distinct mechanisms in relation to emotional processing, with implications for their role as potential transdiagnostic markers of psychopathology based on the fixation eye-tracking metrics.

Integrative epidemiology and immuno-transcriptomics uncover a risk and potential mechanism for cutaneous lymphoma unmasking or progression with dupilumab therapy

There have been multiple reports of the anti-IL4Rα agent, dupilumab, as associated with the onset and/or progression of cutaneous T-cell lymphoma (CTCL). We sought to evaluate safety signals associated with dupilumab, with a focus on CTCL, and to evaluate possible underlying mechanism(s) for the potential association. First, we used the FDA pharmacovigilance database, FAERS, to evaluate if dupilumab was associated with CTCL including both positive controls (conjunctivitis, eosinophilia, and arthralgia) and exposure controls (other medications with similar indications including JAK-inhibitors and the anti-IL13, tralokinumab,) to reduce and evaluate confounding bias. Thereafter, we used publicly available bulk and single cell-RNA seq datasets to probe possible underlying mechanisms through which dupilumab might be associated with CTCL. Between January 2019 and Q2 of 2023, there were 181,575 unique reports of dupilumab related adverse events (AE) in FAERS with 606 of these being for a neoplasm. Dupilumab had 30.0 times the proportional reporting ratio (PRR) (95% CI: 25.0 - 35.9) for CTCL compared to all other medications in FAERS. The risk was highest in males aged 45-65. The PRR for conjunctivitis, eosinophilia, and arthralgia, known side effects of dupilumab, were 35.6 (34.4 - 36.8), 2.15 (2.00 - 2.31), and 2.14 (2.07 - 2.18) respectively. Using the log-count normalized PRR (AE score) to account for PRR inflation when reports were small, the top safety signals included conjunctivitis (AEscore 8.3) and CTCL (AEscore 4.9). Bulk RNA sequencing data showed changes in IL4RA and IL13RA1 expression in CTCL and in epidermal layers of atopic dermatitis (AD) biopsies. Single-cell transcriptomic studies revealed that this change was similar in AD and CTCL, and that keratinocytes seemed to be the most divergent cell type with regards to IL4R and IL13RA1. An effect on keratinocyte specific gene expression was also independently observed in available bulk RNA sequencing data. These data suggest that dupilumab might be causing an unmasking or progression of CTCL via the same mechanism through which it improves atopic dermatitis: IL13 receptor blockade, which leads to increased IL13 in the local milieu, driving CTCL stimulation and progression. However, these associations need further evaluation given the inherent limitations of the FAERS database and our non-experimental approach.

Leveraging deep learning for identification and segmentation of “CAF-1/p60-positive” nuclei in oral squamous cell carcinoma tissue samples

In the current study, we introduced a unique method for identifying and segmenting oral squamous cell carcinoma (OSCC) nuclei, concentrating on those predicted to have significant CAF-1/p60 protein expression. Our suggested model uses the StarDist architecture, a deep-learning framework designed for biomedical image segmentation tasks. The training dataset comprises painstakingly annotated masks created from tissue sections previously stained with hematoxylin and eosin (H&E) and then restained with immunohistochemistry (IHC) for p60 protein. Our algorithm uses subtle morphological and colorimetric H&E cellular characteristics to predict CAF-1/p60 IHC expression in OSCC nuclei. The StarDist-based architecture performs exceptionally well in localizing and segmenting H&E nuclei, previously identified by IHC-based ground truth. In summary, our innovative approach harnesses deep learning and multimodal information to advance the automated analysis of OSCC nuclei exhibiting specific protein expression patterns. This methodology holds promise for expediting accurate pathological assessment and gaining deeper insights into the role of CAF-1/p60 protein within the context of oral cancer progression.

Identification of lncRNA in circulating exosomes as potential biomarkers for MCI among the elderly

BackgroundThe abnormal expression of lncRNA in elderly patients with mild cognitive impairment (MCI), and the ability of exosomes to stably carry non-coding RNAs provide a reliable physiological basis for exosomal lncRNA in plasma as a biomarker of MCI. MethodsThis case-control study enrolled 155 patients with MCI and 155 healthy controls from a community-based population aged≥60 years. The expression profiles of lncRNA and mRNA in plasma exosomes were analyzed and validated using high-throughput RNA sequencing and qRT-PCR. Pathway enrichment analysis were performed on differentially expressed transcripts to screen for target lncRNAs and genes. Multivariate logistic regression models were used to construct clinical predictive models. The receiver operating characteristic curve was used to analyze the predictive value, with an 184-sample external database validated. Results132 lncRNAs and 459 mRNAs were significantly changed in plasma exosomes of MCI patients compared to healthy controls. LINC001380, ENST00000484033, and ENST00000531087 were screened as candidate exo-lncRNAs for predicting MCI. In logistic regression models, odds ratios and 95%CI for target exo-IncRNAs in MCI patients compared to healthy controls were 1.15(1.03–1.28) for LINC001380, 1.21(1.10–1.34) for ENST00000484033, and 1.23(1.08–1.40) for ENST00000531087, respectively. ROC curve analysis showed that the AUC of the combined predicted probability of target lncRNAs was 70.0 %(64.1 %–76.0 %). In the external database, the AUC for the target genes ATP2A2 and PSEN1 was 69.5 %(61.8 %–77.15 %). ConclusionThis study provided evidence for the specific expression of plasma exosomal lncRNAs in MCI and its possible biological mechanism. The combined detection of the expression levels of lncRNA-LINC001380, lncRNA-ENST00000484033, and lncRNA-ENST00000531087 in plasma exosomes may provide early diagnosis and prevention of cognitive impairment.

Identification of extracellular matrix proteins in plasma as a potential biomarker for intervertebral disc degeneration.

Recently, there has been significant focus on extracellular matrix proteolysis due to its importance in the pathological progression of intervertebral disc degeneration (IVDD). The present study investigates the circulating levels of extracellular matrix proteins in the plasma of IVDD and determines their potential relevance as biomarkers in disc degeneration. Global proteomic analysis was performed in the plasma samples of 10 healthy volunteers (HV) and 10 diseased subjects (DS) after depletion of highly abundant proteins such as albumin and IgG. We identified 144 and 135 matrix-associated proteins in plasma samples from healthy volunteers (HV) and patients with disc degeneration (DS), respectively. Among these, 49 of the matrix-associated proteins were identical to the proteins found in intervertebral disc (IVD) tissues retrieved from the in-house library. Applying stringent parameters, we selected 28 proteins, with 26 present in DS and 21 in HV. 19 proteins were found common between the groups, two of which-aggrecan (ACAN) and fibulin 1 (FBLN1) - showed statistically significant differences. Specifically, ACAN was up-regulated and FBLN1 was down-regulated in the DS-plasma. In particular, DS-plasma exhibited specific expression of collagen type 2a1 (COL2A1), native to the nucleus pulposus. The distinct presence of collagen type 2a1 and the elevated expression of aggrecan in IVDD plasma may serve as the basis for the development of a potential biomarker for monitoring the progression of disc degeneration.

A compendium of methods: Searching allele specific expression via RNA sequencing

A compendium of methods: Searching allele specific expression via RNA sequencing

Metabolomic Analysis of Elymus sibiricus Exposed to UV-B Radiation Stress.

Plants cultivated on the Qinghai-Tibet Plateau (QTP) are exposed to high ultraviolet radiation intensities, so they require effective mechanisms to adapt to these stress conditions. UV-B radiation is an abiotic stress factor that affects plant growth, development, and environmental adaptation. Elymus sibiricus is a common species in the alpine meadows of the QTP, with high-stress resistance, large biomass, and high nutritional value. This species plays an important role in establishing artificial grasslands and improving degraded grasslands. In this study, UV-B radiation-tolerant and UV-B radiation-sensitive E. sibiricus genotypes were subjected to simulated short-term (5 days, 10 days) and long-term (15 days, 20 days) UV-B radiation stress and the metabolite profiles evaluated to explore the mechanism underlying UV-B radiation resistance in E. sibiricus. A total of 699 metabolites were identified, including 11 primary metabolites such as lipids and lipid-like molecules, phenylpropanoids and polyketides, organic acids and their derivatives, and organic oxygen compounds. Principal component analysis distinctly clustered the samples according to the cultivar, indicating that the two genotypes exhibit distinct response mechanisms to UV-B radiation stress. The results showed that 14 metabolites, including linoleic acid, LPC 18:2, xanthosine, and 23 metabolites, including 2-one heptamethoxyflavone, glycyrrhizin, and caffeic acid were differentially expressed under short-term and long-term UV-B radiation stress, respectively. Therefore, these compounds are potential biomarkers for evaluating E. sibiricus response to UV-B radiation stress. Allantoin specific and consistent expression was up-regulated in the UV-B radiation-tolerant genotype, thereby it can be used to identify varieties resistant to UV-B radiation. Different metabolic profiles and UV-B radiation response mechanisms were observed between the UV-B radiation-tolerant and UV-B radiation-sensitive E. sibiricus genotypes. A model for the metabolic pathways and metabolic profiles was constructed for the two genotypes. This metabolomic study on the E. sibiricus response to UV-B radiation stress provides a reference for the breeding of new UV-B radiation-tolerant E. sibiricus cultivars.

SHORT-ROOT specifically functions in the chalazal region to modulate assimilate partitioning into seeds.

Nourishing the embryo with endosperm and enclosing both embryo and endosperm in the seed coat are two important evolutionary innovations. Seed coat is conventionally viewed as a protective layer that functions after the seed has matured. Here, we challenge this notion by showing that a subregion of the seed coat, termed the chalazal seed coat (CZSC), is geared to gate seed nutrition loading in developing seeds. The CZSC develops the coordinative system comprising the apoplastic isolation, mediated by the restricted suberization, and the active transport, mediated by the specific expression of a variety of transporters, at as early as the globular embryo stage in both Arabidopsis and soybean seeds. This coordinated system in the CZSC disrupts the vascular continuum to the maternal tissues and forces the nutrient transport into selective and active absorption. We further reveal that the precision of the spatiotemporal suberin deposition and transporter expression is controlled by the regulatory hierarchy of SHR-MYBs cascades. Our results provide a mechanistic insight into the assimilate accumulation in dicot seeds.

The hybrid immunity defined by weaker immune imprinting of people living with HIV has a stronger neutralizing response against Omicron variants. A suggested explanation for fewer symptoms in people living with HIV after SARS-CoV-2 variants breakthrough infection

AimsHuman immunodeficiency virus(HIV) co-infection may cause different immune imprinting, which leads to different hybrid immunity and clinical manifestations of coronavirus disease 2019. This study aims to evaluate the immune imprinting from wild-type(WT) vaccination in people living with HIV(PLWH) and analyze its effect on hybrid immunity and clinical manifestations. Materials and methodsWe enrolled 118 PLWH to compared the differences of BA.5-specific immune response in different immune modes. 20 vaccinated healthy individuals(HC) and 30 vaccinated PLWH were matched to compare the differences of the status of Omicron infection, serum neutralizing antibody levels against WT and BA.5, and specific lymphocytes expression, separately. Key findingsHybrid immunity had a higher level of BA.5 IgG than either vaccine immunity only or natural immunity only in PLWH but didn't have a higher level of BA.5-specific lymphocytes responses. PLWH had fewer symptoms than HC after breakthrough infection. The neutralizing inhibition rate of PLWH was higher for BA.5 and lower for WT, while the neutralizing inhibition rate of HC was higher for WT and lower for BA.5. The difference value of specific B lymphocytes/memory B cells/follicular helper T cells of PLWH was greater than that of HC. SignificanceHybrid immunity of PLWH has a higher level of Omicron-specific IgG without a higher level of Omicron-specific lymphocytes due to immune imprinting. However, there is a stronger neutralizing ability against variants of PLWH due to the weaker immune imprinting of PLWH than that of healthy people, which may lead to fewer symptoms in PLWH after breakthrough infection.

Distinct Hippocampal Expression Profiles of lncRNAs in Obese Type 2 Diabetes Mice Exhibiting Cognitive Impairment.

Cognitive dysfunction has been accepted as a possible complication of type 2 diabetes (T2D), but few studies revealed the potential roles of Long non‑coding RNAs (lncRNAs) in cognitive dysfunction in T2D. The current research aims to demonstrate the specific expression patterns of lncRNA-mRNA in the hippocampi of T2D db/db mice exhibiting cognitive impairment. In this study, the results from behavioral tests showed that T2D db/db mice displayed short-term and spatial working memory deficits compared to db/m mice. Furthermore, western blot analysis demonstrated that compared with db/m mice, p-GSK3β (ser9) protein levels were markedly elevated in T2D db/db mice (P < 0.01). In addition, though not statistically significant, the ratio of p-Tau (Ser396) to Tau 46, α-Synuclein expression, and p-GSK3α (ser21) expression were also relatively higher in T2D db/db mice than in db/m mice. The microarray profiling revealed that 75 lncRNAs and 26 mRNAs were dysregulated in T2D db/db mice (> 2.0 fold change, P < 0.05). GO analysis demonstrated that the differentially expressed mRNAs participated in immune response, extracellular membrane-bounded organelle, and extracellular region. KEGG analysis revealed that the differentially expressed mRNAs were mainly involved in one carbon pool by folate, glyoxylate and dicarboxylate metabolism, autophagy, glycine, serine and threonine metabolism, and B cell receptor signaling pathway. A lncRNA‑mRNA coexpression network containing 71 lncRNAs and 26 mRNAs was built to investigate the interaction between lncRNA and mRNA. Collectively, these results revealed the differential hippocampal expression profiles of lncRNAs in T2D mice with cognitive dysfunction, and the findings from this study provide new clues for exploring the potential roles of lncRNAs in the pathogenesis of cognitive dysfunction in T2D.

Exploring tumor endothelial cells heterogeneity in hepatocellular carcinoma: insights from single-cell sequencing and pseudotime analysis.

This study aimed to explore the heterogeneity of tumor endothelial cells (TECs) in hepatocellular carcinoma (HCC) and their role in tumor progression, with the goal of identifying new therapeutic targets and strategies to improve patient prognosis. Single-cell RNA sequencing data from nine primary liver cancer samples were analyzed, obtained from the Gene Expression Omnibus (GEO) database. Data preprocessing, normalization, dimensionality reduction, and batch effect correction were performed based on the Seurat package. HCC cell types were identified using uniform manifold approximation and projection (UMAP) and cluster analysis, and the different cell types were annotated using the CellMarker database. Pseudotime trajectory analysis was conducted with Monocle to explore the differentiation trajectory of TECs. MAPK signaling pathway activity and copy number variations (CNV) in TECs were analyzed in conjunction with data from The Cancer Genome Atlas (TCGA), the trans-well and wound healing assay was used for cell invasion and migration activity assessment. Two subgroups of TECs (TECs 1 and TECs 2) were identified, exhibiting distinct functional activities and signaling pathways. Specifically, TECs 1 may be involved in tumor cell proliferation and inflammatory responses, whereas TECs 2 is not only involved in cell proliferation pathways, but also enriched in pathways such as metabolic synthesis. Pseudotime analysis revealed dynamic changes in TECs subgroups during HCC progression, correlating specific gene expressions (such as PDGFRB, PGF, JUN, and NR4A1). Subsequently, the JUN gene was predicted by performing binding sites and was shown to act as a transcription factor that may regulate the expression of the PGF gene. CNV analysis highlighted key genes and pathways in TECs that might influence HCC progression, and the PGF as key regulatory factor mediated cell proliferation and migration. The study revealed the heterogeneity of TECs in HCC and their potential roles in tumor progression, offering new perspectives and potential therapeutic targets for HCC molecular mechanisms. The findings emphasize the importance of further exploring TECs heterogeneity for understanding HCC pathogenesis and developing personalized treatment strategies.

Glial 'omics in ischemia: Acute stroke and chronic cerebral small vessel disease.

Vascular injury and pathologies underlie common diseases including ischemic stroke and cerebral small vessel disease (CSVD). Prior work has identified a key role for glial cells, including microglia, in the multifaceted and temporally evolving neuroimmune response to both stroke and CSVD. Transcriptional profiling has led to important advances including identification of distinct gene expression signatures in ischemia-exposed, flow cytometrically sorted microglia and more recently single cell RNA sequencing-identified microglial subpopulations or clusters. There is a reassuring degree of overlap in the results from these two distinct methodologies with both identifying a proliferative and a separate type I interferon responsive microglial element. Similar patterns were later seen using multimodal and spatial transcriptomal profiling in ischemia-exposed microglia and astrocytes. Methodological advances including enrichment of specific neuroanatomic/functional regions (such as the neurovascular unit) prior to single cell RNA sequencing has led to identification of novel cellular subtypes and generation of new credible hypotheses as to cellular function based on the enhanced cell sub-type specific gene expression patterns. A ribosomal tagging strategy focusing on the cellular translatome analyses carried out in the acute phases post stroke has revealed distinct inflammation-regulating roles for microglia and astrocytes in this setting. Early spatial transcriptomics experiments using cerebral ischemia models have identified regionally distinct microglial cell clusters in ischemic core versus penumbra. There is great potential for combination of these methods for multi-omics approaches to further elucidate glial responses in the context of both acute ischemic stroke and chronic CSVD.

Functional investigation and two-sample Mendelian randomization study of primary biliary cholangitis hub genes.

The identification of specific gene expression patterns is crucial for understanding the mechanisms underlying primary biliary cholangitis (PBC) and finding relevant biomarkers for diagnosis and therapeutic evaluation. To determine PBC-associated hub genes and assess their clinical utility for disease prediction. PBC expression data were obtained from the Gene Expression Omnibus database. Overlapping genes from differential expression analysis and weighted gene co-expression network analysis (WGCNA) were identified as key genes for PBC. Kyoto Encyclopedia of Genes and Genomes and Gene Ontology analyses were performed to explore the potential roles of key genes. Hub genes were identified in protein-protein interaction (PPI) networks using the Degree algorithm in Cytoscape software. The relationship between hub genes and immune cells was investigated. Finally, a Mendelian randomization study was conducted to determine the causal effects of hub genes on PBC. We identified 71 overlapping key genes using differential expression analysis and WGCNA. These genes were primarily enriched in pathways related to cytokine-cytokine receptor interaction, and Th1, Th2, and Th17 cell differentiation. We utilized Cytoscape software and identified five hub genes (CD247, IL10, CCL5, CCL3, and STAT3) in PPI networks. These hub genes showed a strong correlation with immune cell infiltration in PBC. However, inverse variance weighting analysis did not indicate the causal effects of hub genes on PBC risk. Hub genes can potentially serve as valuable biomarkers for PBC prediction and treatment, thereby offering significant clinical utility.