Differential Patterns Research Articles

Dissecting the Mechanisms of Intestinal Immune Homeostasis by Analyzing T-Cell Immune Response in Crohn's Disease and Colorectal Cancer.

Crohn's disease (CD) and colorectal cancer (CRC) represent a group of intestinal disorders characterized by intricate pathogenic mechanisms linked to the disruption of intestinal immune homeostasis. Therefore, comprehending the immune response mechanisms in both categories of intestinal disorders is of paramount significance in the prevention and treatment of these debilitating intestinal ailments. IIn this study, we conducted single-cell analysis on paired samples obtained from primary colorectal tumors and individuals with Crohn's disease, which was aimed at deciphering the factors influencing the composition of the intestinal immune microenvironment. By aligning T cells across different tissues, we identified various T cell subtypes, such as γδ T cell, NK T cell, and regulatory T (Treg) cell, which maintained immune system homeostasis and were confirmed in enrichment analyses. Subsequently, we generated pseudo-time trajectories for subclusters of T cells in both syndromes to delineate their differentiation patterns and identify key driver genes Result: Furthermore, cellular communication and transcription factor regulatory networks are all essential components of the intricate web of mechanisms that regulate intestinal immune homeostasis. The identified complex cellular interaction suggested potential T-lineage immunotherapeutic targets against epithelial cells with high copy number variation (CNV) levels in CD and CRC. Finally, the analysis of regulon networks revealed several promising candidates for cell-specific transcription factors (TFs). This study focused on the immune molecular mechanism under intestinal diseases. It contributed to the novel insight of depicting a detailed immune landscape and revealing T-cell responding mechanisms in CD and CRC.

P53 mutation biases squamocolumnar junction progenitor cells towards dysplasia rather than metaplasia in Barrett’s oesophagus

BackgroundWhile p53 mutations occur early in Barrett’s oesophagus (BE) progression to oesophageal adenocarcinoma (EAC), their role in gastric cardia stem cells remains unclear.ObjectiveThis study investigates the impact of p53 mutation...

Daily Activity Rhythm of Sympatric Ungulate Species in Fanjingshan Reserve, China

Sympatric species inhabiting similar ecological niches can coexist by partitioning aspects of available ecological resources, such as temporal, spatial, and nutritional niches. Ungulates often coexist in the same habitat, resulting in temporal partitioning and divergence in foraging strategies and spatial utilization. To understand the temporal patterns of ecological differentiation and coexistence mechanisms among sympatric ungulates, we analyzed the monitoring data in Fanjingshan National Nature Reserve, Guizhou, China, from 2017 to 2022. Kernel density estimation was used to scrutinize disparities in diurnal activity patterns among four ungulates [tufted deer (Elaphodus cephalophus), Reeves' muntjac (Muntiacus reevesi), wild boar (Sus scrofa), and mainland serow (Capricornis milneedwardsii)] as well as the interspecies variances during different seasons, at diverse altitudes, and between breeding and non-breeding periods. Daily activity patterns differed significantly among four species, with those of tufted deer, Reeves' muntjac, and wild boar affected significantly by season and breeding cycle. In addition, the daily activity rhythms of four species were affected by altitude. Thus, the daily activity rhythms of these ungulates were resulted from a combination of environmental factors and interspecific competitive interactions, as well as the reproductive cycle of each species. Our results provided a scientific reference for the effective management of wildlife and forest ecosystems, and we suggest that knowledge of temporal dynamics should be integrated into conservation planning for these sympatric species.

Limited Migration From Physiological Refugia Constrains the Rescue of Native Gastropods Facing an Invasive Predator.

Biological invasions have caused the loss of freshwater biodiversity worldwide. The interplay between adaptive responses and demographic characteristics of populations impacted by invasions is expected to be important for their resilience, but the interaction between these factors is poorly understood. The freshwater gastropod Amnicola limosus is native to the Upper St. Lawrence River and distributed along a water calcium concentration gradient within which high-calcium habitats are impacted by an invasive predator fish (Neogobius melanostomus, round goby), whereas low-calcium habitats provide refuges for the gastropods from the invasive predator. Our objectives were to (1) test for adaptation of A. limosus to the invasive predator and the low-calcium habitats, and (2) investigate if migrant gastropods could move from refuge populations to declining invaded populations (i.e., demographic rescue), which could also help maintain genetic diversity through gene flow (i.e., genetic rescue). We conducted a laboratory reciprocal transplant of wild F0 A. limosus sourced from the two habitat types (high calcium/invaded and low calcium/refuge) to measure adult survival and fecundity in home and transplant treatments of water calcium concentration (low/high) and round goby cue (present/absent). We then applied pooled whole-genome sequencing of 12 gastropod populations from across the calcium/invasion gradient. We identified patterns of life-history traits and genetic differentiation across the habitats that are consistent with local adaptation to low-calcium concentrations in refuge populations and to round goby predation in invaded populations. We also detected restricted gene flow from the low-calcium refugia towards high-calcium invaded populations, implying that the potential for demographic and genetic rescue is limited by natural dispersal. Our study highlights the importance of considering the potentially conflicting effects of local adaptation and gene flow for the resilience of populations coping with invasive predators.

Characterising the Genomic Landscape of Differentiation Between Annual and Perennial Rye.

Annuality and perenniality represent two different life-history strategies in plants, and an analysis of genomic differentiation between closely related species of different life histories bears the potential to identify the underlying targets of selection. Additionally, understanding the interactions between patterns of recombination and signatures of natural selection is a central aim in evolutionary biology, because patterns of recombination shape the evolution of genomes by affecting the efficacy of selection. Here, our aim was to characterise the landscape of genomic differentiation between weedy annual rye (Secale cereale L.) and wild perennial rye (Secale strictum C. Presl), and explore the extent to which signatures of selection are influenced by recombination rate variation. We used population-level sequence data of annual and perennial rye to analyse population structure and their demographic history. Based on our analyses, annual and perennial rye diverged approximately 26,500 years ago (ya) from an ancestral population size of ~85,000 individuals. We analysed patterns of genetic diversity and genetic differentiation, and found highly differentiated regions located in low-recombination regions, indicative of linked selection. Although all highly differentiated regions, as revealed by F ST-outlier scans, were located in low-recombining regions, not all chromosomes showed this tendency. We therefore performed a gene ontology enrichment analysis, which showed that highly differentiated regions comprise genes involved in photosynthesis. This enrichment was confirmed when F ST outlier scans were performed separately in low- and intermediate-recombining regions, but not in high-recombining regions, suggesting that local recombination rate variation in rye affects outlier scans. Cultivated rye is an annual crop, but the introduction of perenniality may be advantageous in regions with poor soil quality or under low-input farming. Although the resolution of our analysis is limited to a broad-scale, knowledge about the evolutionary divergence between annual and perennial rye might support breeding efforts towards perennial rye cultivation.

Metabolite concentrations and the expression profiles of the corresponding metabolic pathway genes in eggplant (Solanum melongena L.) fruits of contrasting colors.

Eggplant (Solanum melongena L.) ranks fifth in importance among vegetable crops of the Solanaceae family, in part due to the high antioxidant properties and polyphenol content of the fruit. Along with the popular purple-fruited varieties of S. melongena, there are cultivars, the fruits of which are rich in phenolic compounds, but are white-colored due to the lack of anthocyanin biosynthesis. Determination of the amount of anthocyanins and other phenolic compounds, as well as carotenoids and sugars, is included in the assessment of the quality of eggplant fruits of commercial (technical) ripeness. In addition to antioxidant and taste properties, these metabolites are associated with fruit resistance to various stress factors. In this study, a comparative analysis of the content of anthocyanins, carotenoids and soluble sugars (sucrose, glucose, fructose) in the peel and pulp of the fruit of both technical and biological ripeness was carried out in purple-fruited (cv. Vlas) and white-fruited (cv. Snezhny) eggplant accessions of domestic selection. The peel and pulp of biologically ripe fruits of the cvs Vlas and Snezhny were used for comparative transcriptomic analysis. The key genes of the flavonoid and carotenoid metabolism, sucrose hydrolysis, and soluble sugar transport were shown to be differentially expressed between fruit tissues, both within each cultivar and between them. It has been confirmed that the purple color of the peel of the cv. Vlas fruit is due to substantial amounts of anthocyanins. Flavonoid biosynthesis genes showed a significantly lower expression level in the ripe fruit of the cv. Vlas in comparison with the cv. Snezhny. However, in both cultivars, transcripts of anthocyanin biosynthesis genes (DFR, ANS, UFGT) were not detected. Additionally, the purple fruit of the cv. Vlas accumulated more carotenoids and sucrose and less glucose and fructose than the white fruit of the cv. Snezhny. Biochemical data corresponded to the differential expression pattern of the key genes encoding the structural proteins of metabolism and transport of the compounds analyzed.

OA15.04 Multi-Omic Profiling of Paired Non-Small Cell Lung Cancer and Draining Lymph Nodes Reveals Novel T-Cell Differentiation Patterns

OA15.04 Multi-Omic Profiling of Paired Non-Small Cell Lung Cancer and Draining Lymph Nodes Reveals Novel T-Cell Differentiation Patterns

Genome-wide differentiation corresponds to climatic niches in two species of lichen-forming fungi.

Lichens can withstand fluctuating environmental conditions such as hydration-desiccation cycles. Many species distribute across climate zones, suggesting population-level adaptations to conditions such as freezing and drought. Here, we aim to understand how climate affects population genomic patterns in lichenized fungi. We analysed population structure along elevational gradients in closely related Umbilicaria phaea (North American; two gradients) and Umbilicaria pustulata (European; three gradients). All gradients showed clear genomic breaks splitting populations into low-elevation (Mediterranean zone) and high-elevation (cold temperate zone). A total of 3301 SNPs in U. phaea and 138 SNPs in U. pustulata were driven to fixation between the two ends of the gradients. The difference between the species is likely due to differences in recombination rate: the sexually reproducing U. phaea has a higher recombination rate than the primarily asexually reproducing U. pustulata. Cline analysis revealed allele frequency transitions along all gradients at approximately 0°C, coinciding with the transition between the Mediterranean and cold temperate zones, suggesting freezing is a strong driver of population differentiation. Genomic scans further confirmed temperature-related selection targets. Both species showed similar differentiation patterns overall, but different selected alleles indicate convergent adaptation to freezing. Our results enrich our knowledge of fungal genomic functions related to temperature and climate, fungal population genomics, and species responses to environmental heterogeneity.

Differential patterns of antibody response against SARS-CoV-2 nucleocapsid epitopes detected in sera from patients in acute phase of COVID-19, convalescents and pre-pandemic individuals.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have already infected more than 0.7 billion people and caused over 7 million deaths worldwide. At the same time, our knowledge about this virus is still incipient. In some cases, there is a pre-pandemic immunity, however its source is unknown. The analysis of patients' humoral responses might shed a light on this puzzle. In this paper, we evaluated the antibody recognition of nucleocapsid protein, one of the structural proteins of SARS-CoV-2. For this purpose, we used pre-pandemic, acute COVID-19 and convalescent patients' sera to identify and map nucleocapsid protein epitopes. We identified a common epitope KKSAAEASKKPRQKRTATKA recognized by sera antibodies from all three groups. Some motifs of this sequence are widespread among various coronaviruses, plant or human proteins indicating that there might be more sources of nucleocapsid-reactive antibodies than previous infection with seasonal coronavirus. The two sequences MSDNGPQNQRNAPRITFGGP and KADETQALPQRQKKQQTVTL were detected as specific for sera from patients in acute phase of infection and convalescents making them suitable for future development of vaccine against SARS-CoV-2. Knowledge of the humoral response to SARS-CoV-2 infection is essential for the design of appropriate diagnostic tools and vaccine antigens.

Characterization of ATP-dependent phosphofructokinase genes during ripening and their modulation by phytohormones during postharvest storage of citrus fruits (Citrus reticulata Blanco.)

The level of sweetness in citrus fruit is crucial for consumer appeal and market competitiveness, determined mainly by soluble sugars and organic acids. ATP-dependent 6-phosphofructokinase is central to regulating sugar metabolism, yet its role in citrus fruit ripening and postharvest storage remains underexplored. We characterized phosphofructokinase genes in citrus, identifying eight genes classified into pyrophosphate-dependent phosphofructokinase (PFP) and ATP-dependent 6-phosphofructokinase (PFK) subgroups using phylogenetic analysis, genomic architectures, and protein motifs. Comparative genomic analysis with other plants highlighted significant protein homology among CitPFKs. The motif analysis indicated conserved phosphofructokinase domains in CitPFK sequences, with upstream promoter regions containing diverse cis-regulatory elements, most notably light-responsive (LREs). The gene expression profiling throughout fruit development and ripening revealed differential patterns, with responses to gibberellic acid and salicylic acid phytohormones during postharvest indicating their roles in regulating CitPFK genes. The analysis of the transcriptome showed high expression of ATP-dependent 6-phosphofructokinase 3 (CitPFK3) during fruit development, indicating a positive role in fruit maturation. Consequently, silencing CitPFK3 through virus-induced gene silencing (VIGS) increased hexose sugar content, suggesting its function in sugar accumulation. These findings improve our understanding of PFKs in citrus, particularly CitPFK3's pivotal role in regulating hexose sugar dynamics and their modulation by exogenous phytohormones after harvest. This study provides a foundation for optimizing soluble sugar regulation to enhance fruit quality and postharvest handling in citrus production.

Exploratory analysis of the variable response to an intensive lifestyle change program for metabolic syndrome

BackgroundSubstantial variability in response to lifestyle interventions has been recognized for many years, and researchers have begun to disentangle sources of error from inherent differences in individual responsiveness. The objective of this secondary analysis of an intensive lifestyle intervention (diet and exercise) for metabolic syndrome (MetS) was to identify potentially important differences among study completers grouped by treatment response as measured by change in a continuous metabolic syndrome score (Gurka/MetS).MethodsAll study completers from a 12-month primary care study were categorized into one of five groups according to change in the Gurka/MetS score. A change of 0.4 in z-score defined clinically relevant change in line with results of previous studies. Repeated measures analysis of variance was used to examine cardiovascular disease risk and individual clinical indicators of MetS over 12 months, looking for differences in response over time by the five groups.ResultsOf 176 participants, 50% (n = 88) had stable scores, 10% (n = 18) had relevant change scores in the first 3 months only and reverted toward baseline, 20% (n = 35) achieved meaningful change over the whole study, 11% (n = 20) had a delayed response at 3–12 months, and 9% (n = 15) demonstrated worsening scores. Significant differential patterns were noted for groups over the duration of the intervention (p < .001). Improvement in diet quality and fitness scores were similar across all groups. Other available variables were tested and did not account for the differences.ConclusionWork is needed to identify key factors that account for differences in responses to lifestyle interventions that can be used to guide treatment decisions for intensive lifestyle interventions for this common condition.Trial RegistrationClinicalTrials.gov Identifier: NCT01616563; first registered June 12, 2012.

Temperature-mortality associations by age and cause: a multi-country multi-city study.

Heterogeneity in temperature-mortality relationships across locations may partly result from differences in the demographic structure of populations and their cause-specific vulnerabilities. Here we conduct the largest epidemiological study to date on the association between ambient temperature and mortality by age and cause using data from 532 cities in 33 countries. We collected daily temperature and mortality data from each country. Mortality data was provided as daily death counts within age groups from all, cardiovascular, respiratory, or noncardiorespiratory causes. We first fit quasi-Poisson regression models to estimate location-specific associations for each age-by-cause group. For each cause, we then pooled location-specific results in a dose-response multivariate meta-regression model that enabled us to estimate overall temperature-mortality curves at any age. The age analysis was limited to adults. We observed high temperature effects on mortality from both cardiovascular and respiratory causes compared to noncardiorespiratory causes, with the highest cold-related risks from cardiovascular causes and the highest heat-related risks from respiratory causes. Risks generally increased with age, a pattern most consistent for cold and for nonrespiratory causes. For every cause group, risks at both temperature extremes were strongest at the oldest age (age 85 years). Excess mortality fractions were highest for cold at the oldest ages. There is a differential pattern of risk associated with heat and cold by cause and age; cardiorespiratory causes show stronger effects than noncardiorespiratory causes, and older adults have higher risks than younger adults.

Prefrontal oxygenation during experimental pain in adolescents engaging in non-suicidal self-injury

BackgroundThe intricate role of pain in non-suicidal self-injury (NSSI) makes the investigation of alterations in brain function during pain processing a critical yet underexplored topic. The aim of this study was to investigate fNIRS correlates of experimental pain and how these differed between adolescent patients engaging in NSSI and healthy controls. Methods154 adolescent patients with NSSI and 48 healthy controls underwent a heat pain stimulation with linearly increasing temperature from 32 °C to max. 50 °C, during which fNIRS activity was recorded. Associations between fNIRS activity and pain perception (i.e. pain threshold, pain tolerance and pain intensity) were examined using linear mixed models and linear regression analyses. ResultsAcross groups, we found a decrease in prefrontal oxygenation during increasing pain stimulation: Oxygenated hemoglobin was higher during baseline than during pain threshold (b = −0.36, p < .001) and higher during pain threshold than during pain tolerance (b = −0.10, p < .001). We did not find differential patterns of prefrontal oxygenation across the pain assessment between patients and healthy controls. Also, no association between pain intensity and fNIRS activity was found. LimitationsfNIRS was only recorded in prefrontal regions and our design did not include a non-painful stimulation as a control condition. ConclusionWhile our study adds to the understanding of prefrontal hemodynamic changes associated with pain processing, it did not contribute further evidence to the few existing findings regarding altered neural processing of pain in adolescents engaging in NSSI.

Spatial patterns of electoral support in the 2023 general election in Poland

RESEARCH OBJECTIVE: This article focuses on identifying the spatial patterns of electoral support for the main political actors, and searching for adequate determinants that explain this distribution of support, based on the results of the 2023 general election in Poland. THE RESEARCH PROBLEM AND METHODS: Is there a relationship between the basic morphological features of the voting space in Poland and the hierarchy of the settlement structure, along with the arrangement of regions associated with the country’s historical and political heritage? The methods used in the study include analysis of descriptive statistics, estimation of spatial autocorrelation, discriminant analysis, and cartographic methods. PROCESS OF ARGUMENTATION: The research process involves a two-stage procedure: 1) identifying a general picture of spatial variation in electoral support for selected groupings, and basic clustering patterns of electoral support; and 2) estimating links between the observed patterns of support and their presumed determinants; that is, the country’s settlement hierarchy and historical-political divisions. RESEARCH RESULTS: The spatial variability of the support indicators is characterised by a distinctive territorial distribution, based on the units of the settlement system and the boundaries of former historical divisions. The nature of this linkage indicates the changing layout of the voting space, associated with the increasing polarisation of citizens’ political preferences. CONCLUSIONS, INNOVATIONS, AND RECOMMENDATIONS: The current pattern of urban-rural differentiation is related to the different preferences of metropolitan (over 20,000 inhabitants) and rural or small-town (up to 20,000 inhabitants) communities. The east-west heterogeneity of Poland’s voting space is increasing due to similarities of preferences among the inhabitants of former Austrian and Russian Poland, on the one hand, and Prussian Poland and the Recovered Territories, on the other.

Screening of differential gene expression patterns through survival analysis for diagnosis, prognosis and therapies of clear cell renal cell carcinoma.

Clear cell renal cell carcinoma (ccRCC) is the most prevalent subtype of kidney cancer. Although there is increasing evidence linking ccRCC to genetic alterations, the exact molecular mechanism behind this relationship is not yet completely known to the researchers. Though drug therapies are the best choice after the metastasis, unfortunately, the majority of the patients progressively develop resistance against the therapeutic drugs after receiving it for almost 2 years. In this case, multi-targeted different variants of therapeutic drugs are essential for effective treatment against ccRCC. To understand molecular mechanisms of ccRCC development and progression, and explore multi-targeted different variants of therapeutic drugs, it is essential to identify ccRCC-causing key genes (KGs). In order to obtain ccRCC-causing KGs, at first, we detected 133 common differentially expressed genes (cDEGs) between ccRCC and control samples based on nine (9) microarray gene-expression datasets with NCBI accession IDs GSE16441, GSE53757, GSE66270, GSE66272, GSE16449, GSE76351, GSE66271, GSE71963, and GSE36895. Then, we filtered these cDEGs through survival analysis with the independent TCGA and GTEx database and obtained 54 scDEGs having significant prognostic power. Next, we used protein-protein interaction (PPI) network analysis with the reduced set of 54 scDEGs to identify ccRCC-causing top-ranked eight KGs (PLG, ENO2, ALDOB, UMOD, ALDH6A1, SLC12A3, SLC12A1, SERPINA5). The pan-cancer analysis with KGs based on TCGA database showed the significant association with different subtypes of kidney cancers including ccRCC. The gene regulatory network (GRN) analysis revealed some crucial transcriptional and post-transcriptional regulators of KGs. The scDEGs-set enrichment analysis significantly identified some crucial ccRCC-causing molecular functions, biological processes, cellular components, and pathways that are linked to the KGs. The results of DNA methylation study indicated the hypomethylation and hyper-methylation of KGs, which may lead the development of ccRCC. The immune infiltrating cell types (CD8+ T and CD4+ T cell, B cell, neutrophil, dendritic cell and macrophage) analysis with KGs indicated their significant association in ccRCC, where KGs are positively correlated with CD4+ T cells, but negatively correlated with the majority of other immune cells, which is supported by the literature review also. Then we detected 10 repurposable drug molecules (Irinotecan, Imatinib, Telaglenastat, Olaparib, RG-4733, Sorafenib, Sitravatinib, Cabozantinib, Abemaciclib, and Dovitinib.) by molecular docking with KGs-mediated receptor proteins. Their ADME/T analysis and cross-validation with the independent receptors, also supported their potent against ccRCC. Therefore, these outputs might be useful inputs/resources to the wet-lab researchers and clinicians for considering an effective treatment strategy against ccRCC.

Combined LC-MS/MS feature grouping, statistical prioritization, and interactive networking in msFeaST.

Computational metabolomics workflows have revolutionized the untargeted metabolomics field. However, the organization and prioritization of metabolite features remains a laborious process. Organizing metabolomics data is often done through mass fragmentation-based spectral similarity grouping, resulting in feature sets that also represent an intuitive and scientifically meaningful first stage of analysis in untargeted metabolomics. Exploiting such feature sets, feature-set testing has emerged as an approach that is widely used in genomics and targeted metabolomics pathway enrichment analyses. It allows for formally combining groupings with statistical testing into more meaningful pathway enrichment conclusions. Here, we present msFeaST (mass spectral Feature Set Testing), a feature-set testing and visualization workflow for LC-MS/MS untargeted metabolomics data. Feature-set testing involves statistically assessing differential abundance patterns for groups of features across experimental conditions. We developed msFeaST to make use of spectral similarity-based feature groupings generated using k-medoids clustering, where the resulting clusters serve as a proxy for grouping structurally similar features with potential biosynthesis pathway relationships. Spectral clustering done in this way allows for feature group-wise statistical testing using the globaltest package, which provides high power to detect small concordant effects via joint modeling and reduced multiplicity adjustment penalties. Hence, msFeaST provides interactive integration of the semi-quantitative experimental information with mass-spectral structural similarity information, enhancing the prioritization of features and feature sets during exploratory data analysis. The msFeaST workflow is freely available through https://github.com/kevinmildau/msFeaST and built to work on MacOS and Linux systems.

Genome-wide analysis of fatty acid desaturase (FAD) gene family in Camellia sinensis: Identification, expression and their biochemical functions in low temperature resistance

Fatty acid desaturase (FAD) is critical for unsaturated fatty acids (UFAs) biosynthesis and plays crucial roles in plants' response to low temperature. Nevertheless, a comprehensive genomic analysis of the FAD gene family in Camellia sinensis remain unreported. This study employed bioinformatics to identify 17 CsFAD genes, which are unequally distributed across 9 chromosomes. CsFAD proteins are localized to chloroplasts and/or endoplasmic reticulum (ER) by subcellular localization predictions. Phylogenetic categorization divides CsFADs into six subfamilies. The cis-elements are related to hormonal regulation and adversity response. Additionally, differential expression patterns of CsFADs across various tissues were observed. qRT-PCR analysis revealed a marked upregulation in the expression of CsSLD3 and CsSLD4 (encoding sphingolipid Δ8 desaturase) under cold stress conditions. Moreover, subcellular localization assays in tobacco leaves confirmed the presence of CsSLD3 and CsSLD4 within ER. Yeast heterologous expression demonstrated the capacity of CsSLD3/4 to transform ceramide(t18:0) into ceramide(t18:1), and overexpression of CsSLD3/4 enhanced yeast tolerance to low temperature. Thus, this comprehensive analysis of the CsFAD gene family furnishes a robust foundation for future study into the biological functions of CsFAD genes, and offers a profound insight into their regulatory roles in stress resilience.

The biogeographic patterns of the olive fly and its primary symbiont Candidatus Erwinia dacicola across the distribution area of the olive tree.

The olive fly, Bactrocera oleae (Rossi, 1790), is the major insect pest of olives attacking both cultivated and wild olive. Bactrocera oleae carries a primary and vertically transmitted symbiont, the bacterium Candidatus Erwinia dacicola. As any primary symbiont, it plays an important role in the reproduction and lifespan of the fly. The genetic 16S rRNA diversity of the primary symbiont and the mitochondrial haplotype variation of the insect host were simultaneously examined in 54 olive fly populations. The aim was to unravel the biogeographic patterns of this economically relevant host-bacteria interaction across a wide distribution area. Three symbiont haplotypes were identified. The primary symbiont showed a lower haplotype diversity than that of its host, a characteristic indicative of a long-term interaction. A significant genetic and geographic association between host and primary symbiont was observed, with an East-West genetic differentiation pattern in the Mediterranean basin, coinciding with the historical genetic distribution of the olive tree. The study shows promise, informing and aiding the development of future tools for the control of the olive fly.

Unveiling the glycolysis in sepsis: Integrated bioinformatics and machine learning analysis identifies crucial roles for IER3, DSC2, and PPARG in disease pathogenesis.

Sepsis, a multifaceted syndrome driven by an imbalanced host response to infection, remains a significant medical challenge. At its core lies the pivotal role of glycolysis, orchestrating immune responses especially in severe sepsis. The intertwined dynamics between glycolysis, sepsis, and immunity, however, have gaps in knowledge with several Crucial genes still shrouded in ambiguity. We harvested transcriptomic profiles from the peripheral blood of 107 septic patients juxtaposed against 29 healthy controls. Delving into this dataset, differential expression analysis shed light on genes distinctly linked to glycolysis in both cohorts. Harnessing the prowess of LASSO regression and SVM-RFE, we isolated Crucial genes, paving the way for a sepsis risk prediction model, subsequently vetted via Calibration and decision curve analysis. Using the CIBERSORT algorithm, we further mapped 22 immune cell subtypes within the septic samples, establishing potential interactions with the delineated Crucial genes. Our efforts unveiled 21 genes intricately tied to glycolysis that exhibited differential expression patterns. Gene set enrichment analysis (GSEA) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses offered insights, spotlighting pathways predominantly associated with oxidative phosphorylation, PPAR signaling pathway, Glycolysis/Gluconeogenesis and HIF-1 signaling pathway. Among the myriad genes, IER3, DSC2, and PPARG emerged as linchpins, their prominence in sepsis further validated through ROC analytics. These sentinel genes demonstrated profound affiliations with various immune cell facets, bridging the complex terrain of glycolysis, sepsis, and immune responses. In line with our endeavor to "unveil the glycolysis in sepsis," the discovery of IER3, DSC2, and PPARG reinforces their cardinal roles in sepsis pathogenesis. These revelations accentuate the intricate dance between glycolysis and immunological shifts in septic conditions, offering novel avenues for therapeutic interventions.

Distinct connectivity patterns in bipolar and unipolar depression: a functional connectivity multivariate pattern analysis study

BackgroundPatients with bipolar disorder (BD) and major depressive disorder (MDD) exhibit depressive episodes with similar symptoms despite having different and poorly understood underlying neurobiology, often leading to misdiagnosis and improper treatment. This exploratory study examined whole-brain functional connectivity (FC) using FC multivariate pattern analysis (fc-MVPA) to identify the FC patterns with the greatest ability to distinguish between currently depressed patients with BD type I (BD I) and those with MDD.MethodologyIn a cross-sectional design, 41 BD I, 40 MDD patients and 63 control participants completed resting state functional magnetic resonance imaging scans. Data-driven fc-MVPA, as implemented in the CONN toolbox, was used to identify clusters with differential FC patterns between BD patients and MDD patients. The identified cluster was used as a seed in a post hoc seed-based analysis (SBA) to reveal associated connectivity patterns, followed by a secondary ROI-to-ROI analysis to characterize differences in connectivity between these patterns among BD I patients, MDD patients and controls.ResultsFC-MVPA identified one cluster located in the right frontal pole (RFP). The subsequent SBA revealed greater FC between the RFP and posterior cingulate cortex (PCC) and between the RFP and the left inferior/middle temporal gyrus (LI/MTG) and lower FC between the RFP and the left precentral gyrus (LPCG), left lingual gyrus/occipital cortex (LLG/OCC) and right occipital cortex (ROCC) in MDD patients than in BD patients. Compared with the controls, ROI-to-ROI analysis revealed lower FC between the RFP and the PCC and greater FC between the RFP and the LPCG, LLG/OCC and ROCC in BD patients; in MDD patients, the analysis revealed lower FC between the RFP and the LLG/OCC and ROCC and greater FC between the RFP and the LI/MTG.ConclusionsDifferences in the RFP FC patterns between currently depressed patients with BD and those with MDD suggest potential neuroimaging markers that should be further examined. Specifically, BD patients exhibit increased FC between the RFP and the motor and visual networks, which is associated with psychomotor symptoms and heightened compensatory frontoparietal FC to counter distractibility. In contrast, MDD patients exhibit increased FC between the RFP and the default mode network, corresponding to sustained self-focus and rumination.