Search Results (127)

This narrative review aims to summarize, synthesize, and organize current knowledge on the adaptation of sheep and goats to stressful environments and to discuss how these adaptations contribute to food security in vulnerable communities. A structured search of Web of Science, Scopus, PubMed, and Google Scholar was conducted using combinations of terms related to sheep and goats, harsh environments (e.g., arid and semi-arid regions, heat stress, water restriction, poor-quality forage), and adaptation or resilience, combined with Boolean operators. A total of 1718 research publications were found, of which 86 were retained as the most relevant because they provided direct and detailed evidence on anatomical, physiological, digestive–microbiome, behavioral, and genomic adaptations of sheep and goats to stressful environments. The selected studies describe a wide range of phenotypic and integumentary traits, thermoregulatory and endocrine responses, digestive and microbial adjustments, behavioral strategies, and genomic signatures that, together, allow small ruminants to maintain basic functions, reproduction, and production under conditions of climatic and nutritional stress. Evidence from these studies also highlights how adaptive traits support herd productivity, economic stability of households, and the sustainable use of natural resources in regions where climatic variability and resource scarcity are common. Overall, the synthesis presented here underscores the importance of conserving and strategically using locally adapted sheep and goat breeds, incorporating resilience-related traits into breeding and management programs, and prioritizing further research on genomic, microbiome, and epigenetic mechanisms that underpin adaptation to harsh environments. Full article

Background: Periodontitis is a chronic inflammatory disease mostly associated with Porphyromonas gingivalis infection and characterized by progressive destruction of the supporting structures of the tooth, including the gingiva, periodontal ligament and alveolar bone. However, the impact of other members of the periodontal microbiome on stage of the severity of the periodontitis remains largely uncharacterized. Methods: This exploratory study employs whole-genome shotgun (WGS) metagenomics to characterize the periodontal microbiome in patients suffering from mild and severe periodontitis, aiming to identify microbial signatures linked to disease severity via analysis of taxonomic composition, predicted metabolic pathways and metagenome-assembled genomes (MAGs). After initial selection, 28 adult patients with a computer tomography (CT)-confirmed diagnosis of mild and severe stage of periodontitis from 2 clinics were included in the research project. Results: Taxonomic analysis confirms the presence of various commensal and pathogenic bacteria detectable at the species level, especially belonging to so-called “red, orange and green periodontal complexes”—P. gingivalis, T. forsythia, C. rectus, and Capnocytophaga spp. that may contribute to disease heterogeneity. The conducted investigation suggests that non-microbial factors such as cardiovascular diseases and antibiotic usage in the last 6 months prior to the hospital admission could explain variance of disease progression and impact on severity. Analysis of microbial functional composition revealed metabolic traits showing positive correlations with severe stage of periodontitis. Robust network analysis suggested interactions between pathogenic bacteria of the red complex and other members of the periodontal microbiome. Conclusions: These findings underscore the multifactorial nature of periodontitis pathogenesis, highlighting the need for integrated approaches combining microbial, host, and environmental data to unravel drivers of disease progression. The study provides a foundation for future large-scale investigations into personalized diagnostic or therapeutic strategies. Full article

Toxin–antitoxin (TA) modules represent sophisticated regulatory networks that have evolved from simple plasmid maintenance factors into multifunctional genetic modules orchestrating bacterial stress responses, pathogenesis, and ecological adaptation. This review highlights a compelling correlation between the abundance of toxin–antitoxin (TA) modules and bacterial pathogenicity, as exemplified by Mycobacterium tuberculosis (M.tb), which encodes 118 TA loci—significantly more than the fewer than 10 found in closely related saprophytic species. The clinical significance of TA modules extends beyond traditional stress response roles to encompass antimicrobial persistence, where systems like VapBC and MazEF facilitate dormant subpopulations that survive antibiotic therapy while maintaining chronic infections. Recent discoveries have revealed TA modules as sophisticated bacterial defense mechanisms against bacteriophage infection, with DarTG and ToxIN systems representing novel antiviral immunity components that complement CRISPR-Cas and restriction–modification systems. The immunomodulatory capacity of TA modules demonstrates their role in host–pathogen interactions, where systems such as VapC12 in M.tb promote macrophage polarization toward permissive M2 phenotypes while inducing anti-inflammatory cytokine production. Large-scale genomic analyses reveal that TA modules function as drivers of horizontal gene transfer networks, with their signatures enabling accurate prediction of plasmid community membership and serving as determinants of microbial community structure. The biotechnological applications of TA modules have expanded to include genetic circuit stabilization, biocontainment device construction, and multi-species microbial community engineering, while therapeutic strategies focus on developing multi-target inhibitors against conserved TA protein families as promising approaches for combating drug-resistant bacterial infections. The evolutionary conservation of TA modules across diverse bacterial lineages underscores their fundamental importance as central organizing principles in bacterial adaptation strategies, where their multifunctional nature reflects complex selective pressures operating across environmental niches and host-associated ecosystems. This review provides an integrated perspective on TA modules as dynamic regulatory elements that support bacterial persistence, immune evasion, and ecological versatility, establishing them as genetic elements with truly “many faces and functions” in prokaryotic biology. Full article

Background: Butana are native Sudanese Bos indicus cattle that are well adapted to arid environments and valued for their relatively high milk performance and resilience under harsh conditions. Despite their adaptive advantages, Butana cattle face the risk of genetic erosion due to low production performance and the absence of structured breeding programs underscoring the urgent need to conserve their unique genetic potential for climate-resilient livestock development. Methods: In this study, we analyzed whole-genome sequencing data from 40 Butana cattle to assess their genetic diversity, population structure, signatures of selection, and potential pathogen load. Results: Butana cattle exhibited high nucleotide diversity and low levels of inbreeding, indicating a stable gene pool shaped by natural selection rather than by intensive breeding. Signatures of selection and functional variant analysis revealed candidate genes involved in heat stress adaptation (COL6A5, HSPA1L, TUBA8, XPOT), metabolic processes (G6PD, FAM3A, SLC10A3), and immune regulation (IKBKG, IRAK3, IL18RAP). Enrichment analyses and RoH island mapping consistently highlighted immune and thermoregulatory pathways as key selection targets, distinguishing Butana from both the geographically neighbored Kenana cattle and the specialized dairy cattle breed Holstein. Furthermore, metagenomic screening of unmapped reads detected the tick-borne parasite Theileria annulata and the opportunistic pathogen Burkholderia cenocepacia in all animals, underscoring the importance of integrating pathogen surveillance into genomic studies. Conclusions: Taken together, our findings highlight the distinct adaptive genomic profile of Butana cattle and reinforce their value in breeding programs aimed at improving climate resilience and disease resistance in livestock through the utilization of local breeds. Full article

This study presents the design, modeling, and experimental validation of a frequency-tuned mechanical sensor (MS) integrating a fiber bragg grating (FBG) for the detection of leak-induced vibrations in pressurized steel pipelines. Unlike conventional bonded FBGs—which directly follow the local wall deformation—the proposed MS consists of a base-fiber-mass transducer geometrically tuned so that its natural frequencies coincide with the dominant vibration modes of the pipe in the 5–7 kHz range. A combined framework of finite element analysis (FEA), computational fluid dynamics (CFD), and laboratory measurements was developed to assess the coupling between the pipe and the sensor. Results show that the MS behaves as a selective mechanical amplifier, enhancing strain sensitivity and signal-to-noise ratio (SNR) by up to 15 dB compared to a directly bonded FBG. The workflow integrates modal tuning, an equivalent harmonic excitation derived from CFD-based pressure fields, and frequency–response validation, leading to a mechanically optimized FBG transducer capable of discriminating high-frequency leak signatures. The excellent agreement between the simulation and experiment confirms that geometric resonance coupling provides an effective route to amplify leak-induced strain, offering a compact, scalable, and high-sensitivity solution for vibration-based leak detection in industrial pipelines. Full article

Ferroptosis is a novel iron-sensitive subtype of regulated cell death (RCD), persisting under extreme lipid peroxidation and iron/redox imbalances. Unlike apoptosis, necroptosis, and pyroptosis, ferroptosis is a signaling-driven process mediated through iron metabolism imbalance, polyunsaturated fatty acid (PUFA) exceeding oxidation, and defects in its protective systems like Xc-/GSH/GPx4. Specifically, this review establishes that iron-driven ferroptosis is a central underlying pathomechanistic factor in a broad range of human diseases. Significantly, whether its modulation is therapeutic, it is entirely conditional on the specific disease context. Thus, its induction can provide a promising antidote for destructive cancer cells when conjoined with immuno-therapies to boost anticancer immunity. Conversely, iron-mediated ferroptosis suppression is a key factor in countering destructive changes in a whole range of degenerative and acute injuries. Current therapeutic approaches include iron chelators, lipid oxidation inhibitors, GPx4 activators, natural and active compounds, and novel drug delivery systems. However, against all odds and despite its intense therapeutic promise, its translation into a practical medicinal strategy faces many difficulties. Thus, a therapeutic agent specifically focused on its modulation is still lacking. The availability of selective biologic markers is a concern. The challenges in the direct pathologic identification of ferroptosis in a complex in vivo systemic scenario remain. Current avenues for its future development are pathogen infections, the discovery of novel regulating factors, and novel approaches to personalized medicine centered on its organ-level in vivo signatures. Full article

This study investigates the genetic architecture of Salsk sheep—a long-established Russian Merino-type breed from the southern steppes—highlighting their broad genetic diversity, resilience to cold and drought, and dual-purpose (wool and meat) productivity as a unique gene pool shaped by natural and artificial selection. The study used data from 96 sheep. Genotyping was carried out on the Illumina Ovine Infinium^® HD BeadChip platform, and after filtering, 511,145 SNPs were retained. We assessed population structure and genetic diversity using principal component analysis (PCA), Fst, and linkage disequilibrium (LD) in comparison with four reference European breeds. To detect selection signatures, we employed a combination of complementary methods, including intra-population statistics (iHS, nSL, iHH12) and inter-population comparisons (XP-EHH). This integrated approach identified genomic regions under positive selection, reflecting the breed’s evolutionary response to both natural and artificial selection pressures. Strong selection signals were detected in genes associated with production traits like fertility and growth (CCSER1, SOX6), as well as fundamental adaptive functions, including immune response (IL6R, NLRP1) and energy metabolism (ACSL5, FANCA). These results elucidate the genetic basis of the Salsk breed’s high resilience and highlight its potential as a valuable genetic resource for improving this trait in other sheep populations. Full article

Traumatic spinal cord injury (SCI) is a devastating complication of trauma, causing long-term disability and significant socioeconomic burden. Beyond the primary mechanical insult, secondary injury cascades involving apoptosis, oxidative stress, and inflammation amplify tissue damage. MicroRNAs (miRNAs) regulate these processes at the post-transcriptional level, yet data on circulating miRNAs in human SCI remain scarce. This study aimed to characterize acute plasma miRNA expression patterns in isolated traumatic SCI that may indicate SCI-specific signatures. Plasma was collected from five SCI patients at admission and 48 h post-injury and five healthy controls (HCs), and next-generation sequencing (NGS) was performed on plasma RNAs. Differentially expressed miRNAs were identified, and selected candidate miRNAs were validated by droplet digital PCR (ddPCR) in an expanded cohort of SCI patients, polytrauma patients without neurotrauma (PT), and HC (each n = 8). Pathway enrichment and validated target analysis were performed to assess biological relevance of candidate miRNAs. At emergency room admission, 46 miRNAs were differentially expressed in SCI plasma (18 upregulated, 28 downregulated). By 48 h, a global downregulation was observed, with 47 miRNAs significantly decreased compared with HC. ddPCR validation revealed markedly stronger suppression of miR-182-5p, miR-190a-5p, miR-144-5p, and miR-30c-5p expression levels in SCI compared with PT. Pathway analysis indicated enrichment of mitochondrial oxidative phosphorylation pathways, and target prediction suggested that the identified miRNAs may be linked to neuroprotective and regenerative functions. Our findings demonstrate early and profound alterations in circulating miRNAs after acute SCI. The downregulation of the identified miRNAs may reflect maladaptive changes that promote neuroinflammation and hinder axonal regeneration, although the exact functional consequences remain to be clarified. These data suggest that circulating miRNAs could hold promise as diagnostic and prognostic biomarkers and, potentially, as therapeutic targets to influence secondary injury processes. However, given the exploratory nature and limited sample size of this study, the findings should be validated in larger, sufficiently powered cohorts to robustly delineate differences between patient groups. Full article

Background: Oncolytic virus (OV) therapy couples direct tumor lysis with systemic immune priming, yet clinical benefit remains heterogeneous and the predictive biomarker landscape is poorly defined. We undertook a systematic review and meta-analysis to quantify the efficacy and safety of OV therapy in solid tumors and to synthesize current evidence on response-modulating biomarkers. Methods: Following PRISMA 2020 guidelines, MEDLINE, Embase, Cochrane CENTRAL, ProQuest and Scopus were searched from inception to May 2025. Phase II–III randomized trials of genetically engineered or naturally occurring OV reporting objective response rate (ORR), progression-free survival (PFS), overall survival (OS) or biomarker data were eligible. Hazard ratios (HRs) or odds ratios (OR) were pooled with random-effects models; heterogeneity was assessed with I² statistics. Qualitative synthesis integrated genomic, immunologic and microbiome biomarkers. Results: Thirty-six trials encompassing around 4190 patients across different tumor types met inclusion criteria. Compared with standard therapy, OV-based regimens significantly improved ORR nearly three-fold (pooled OR = 2.77, 95% CI 1.85–4.16), prolonged PFS by 11% (HR = 0.89, 95% CI 0.80–0.99) and reduced mortality by 16% (OS HR = 0.84, 95% CI 0.72–0.97; I² = 59%). Benefits were most pronounced in melanoma (ORR 26–49%; OS HR 0.57–0.79) and in high-dose vaccinia virus for hepatocellular carcinoma (HR = 0.39). Grade ≥ 3 adverse events were not increased versus control (risk ratio 1.05, 95% CI 0.89–1.24); common toxicities were transient flu-like symptoms and injection-site reactions. Biomarker synthesis revealed that high tumor mutational burden, interferon-pathway loss-of-function mutations, baseline CD8⁺ T-cell infiltration, post-OV upregulation of IFN-γ/PD-L1, and favorable gut microbial signatures correlated with response, whereas intact antiviral signaling, immune-excluded microenvironments and myeloid dominance predicted resistance. Conclusions: OV therapy confers clinically meaningful improvements in tumor response, PFS and OS with a favorable safety profile. Integrating composite genomic–immune–microbiome biomarkers into trial design is critical to refine patient selection and realize precision viro-immunotherapy. Future research should prioritize biomarker-enriched, rational combination strategies to overcome resistance and extend benefit beyond melanoma. Full article

Campylobacter hepaticus is the etiological agent of Spotty Liver Disease (SLD), a newly emerging bacterial disease of laying hens resulting in significant mortality and production losses primarily in free-range systems. Although its economic impact continues to grow, the molecular basis of C. hepaticus pathogenesis remains poorly understood. In this study, we conducted transcriptomic profiling of C. hepaticus in three host-relevant conditions, exposure to chicken bile, infection of a chicken liver hepatocellular carcinoma (LMH) cell line, and isolation from liver lesions of naturally infected chickens. Through RNA-seq analysis, we found unique gene expression signatures in each environment. In the bile, C. hepaticus exhibited differential expression of 412 genes, with upregulation of genes related to motility, cell envelope remodeling, glycosylation, nitrate respiration, and multidrug efflux systems, indicating a stress-adaptive, metabolically active lifestyle. In LMH, on the other hand, 125 genes were differentially expressed, primarily reflecting downregulation of motility, oxidative stress response, chaperones, and core metabolic processes, suggesting that these cells adopt a less active, intracellular dormant lifestyle. Transcriptomic analysis of C. hepaticus isolated from the liver identified 26 differentially expressed genes, featuring selective upregulation of genes associated with nitrate respiration, sulfur metabolism, and pyridoxal 5’ phosphate homeostasis, alongside downregulation of the major outer membrane porin (momp), stress response chaperones (dnaK, groL), and genes involved in oxidative stress defense and energy production. Furthermore, the immune evasion-related gene cmeA and a glycosyltransferase gene were found to be highly upregulated. This study presents the first in-depth transcriptomic exploration of C. hepaticus in multiple host relevant niches. Our findings reveal niche-specific gene expression profiles and highlight metabolic and structural adaptations that enable C. hepaticus to survive during bile exposure, persist within host cells, and contribute to liver pathology. These insights provide a basis for identifying novel virulence determinants and may inform the development of targeted interventions, including vaccines or antimicrobial therapy, to control SLD in commercial poultry operations. Full article

Tumor-infiltrating lymphocytes (TILs) are thought to play important roles in tumor shrinkage and survival prolongation in patients with breast cancer receiving neoadjuvant chemotherapy (NAC). TILs are mononuclear immune cells such as lymphocytes and plasma cells, including CD4+ and CD8+ T cells, natural killer cells, B cells, macrophages, regulatory T cells (Tregs), and myeloid/dendritic cells. The pre-NAC presence of more T cells and fewer Tregs in biopsy samples of primary breast tumors is known to contribute to tumor shrinkage and prolonged survival. This review was conducted to elucidate these roles in patients with breast cancer treated with NAC. Publications selected for inclusion in this review were identified by a PubMed search for articles published in English, performed using the terms “breast cancer”, “neoadjuvant chemotherapy”, “tumor-infiltrating lymphocyte”, “pathological complete response”, and “immune response”. The search was completed in July 2024. The functional roles of TILs in the achievement of these outcomes may vary by tumor subtype; increases and decreases in TIL levels before and after NAC have been shown to have conflicting effects. Biomarkers have been reported to predict local responses in the tumor microenvironment (e.g., immune-related gene signatures) and systemic immune responses (e.g., neutrophil-to-lymphocyte and platelet-to-lymphocyte ratios). Immune gene signatures and immune cell infiltration do not appear to be universally associated with tumor response or outcome in patients with breast cancer treated with NAC. The functional roles of TILs in breast tumor response and breast cancer survival may vary by tumor subtype, and conflicting results for the same subtypes may be due to differences in NAC regimens, immune responses, tumor heterogeneity, sample size, and the technical methods used to evaluate TILs in tumor samples. Full article

This work presents a proof of concept including simulation and experimental validations of acoustic gas sensor prototypes for trace CO₂ detection up to 1 ppm. For the detection of lower gas concentrations especially, the dependency of acoustic resonances on the molecular weights and, consequently, the speed of sound of the gas mixture, is exploited. We explored two resonator types: a cylindrical acoustic resonator and a Helmholtz resonator intrinsic to the MEMS microphone’s geometry. Both systems utilized mass flow controllers (MFCs) for precise gas mixing and were also modeled in COMSOL Multiphysics 6.2 to simulate resonance shifts based on thermodynamic properties of binary gas mixtures, in this case, N₂-CO₂. We performed experimental tracking using Zurich Instruments MFIA, with high-resolution frequency shifts observed in µHz and mHz ranges in both setups. A compact and geometry-independent nature of MEMS-based Helmholtz tracking showed clear potential for scalable sensor designs. Multiple experimental trials confirmed the reproducibility and stability of both configurations, thus providing a robust basis for statistical validation and system reliability assessment. The good simulation experiment agreement, especially in frequency shift trends and gas density, supports the method’s viability for scalable environmental and industrial gas sensing applications. This resonance tracking system offers high sensitivity and flexibility, allowing selective detection of low CO₂ concentrations down to 1 ppm. By further exploiting both external and intrinsic acoustic resonances, the system enables highly sensitive, multi-modal sensing with minimal hardware modifications. At microscopic scales, gas detection is influenced by ambient factors like temperature and humidity, which are monitored here in a laboratory setting via NDIR sensors. A key challenge is that different gas mixtures with similar sound speeds can cause indistinguishable frequency shifts. To address this, machine learning-based multivariate gas analysis can be employed. This would, in addition to the acoustic properties of the gases as one of the variables, also consider other gas-specific variables such as absorption, molecular properties, and spectroscopic signatures, reducing cross-sensitivity and improving selectivity. This multivariate sensing approach holds potential for future application and validation with more critical gas species. Full article

Ecology and adaptive differentiation of Epimedium are central to understanding both its taxonomic complexity and medicinal value. In this study, we integrate transcriptomic and plastid data from four natural populations of E. brevicornu (HZ, QLH, TS, WD) to reconstruct their phylogenetic relationships, estimate divergence times, and identify candidate genes associated with local adaptation. Nuclear gene-based phylogenies provide higher resolution and greater topological consistency than plastid data, underscoring the utility of nuclear data in lineages affected by hybridization and incomplete lineage sorting. Molecular dating indicated that major intraspecific divergence occurred during the mid-Quaternary (0.61–0.45 Ma), coinciding with climatic oscillations and montane isolation. Population structure showed strong correlations with temperature and precipitation gradients, suggesting environmentally driven selection. Signatures of positive selection and accelerated evolutionary rates revealed population-specific enrichment of genes involved in stress response, protein modification, signaling, and carbohydrate metabolism—key pathways linked to high-elevation adaptation. Protein–protein interaction networks further indicated a two-tier adaptation mechanism: ancestral network rewiring combined with population co-evolution of interacting genes. Together, these findings advance our understanding of alpine plant adaptation and provide candidate genes for further functional and breeding studies in Epimedium. Full article

Driven by the demand for cost-effective vehicle access, enhanced flexibility, and sustainable transportation practices, smart car-sharing has emerged as a prominent alternative to traditional vehicle rental systems. Leveraging the Internet of Vehicles (IoV) and wireless communication, these systems feature dynamic renter-vehicle mappings, enabling users to access any available vehicle rather than being restricted to a specific one pre-assigned by the service provider. However, many existing schemes in the IoV field conflate users and vehicles, complicating the identification and tracking of the vehicle’s actual driver. Moreover, most current authentication protocols rely on a strict, initial binding between a user and a vehicle, rendering them unsuitable for the dynamic nature of car-sharing environments. To address these challenges, we propose an enhanced certificateless signature scheme tailored for smart car-sharing. By employing a biometric fuzzy extractor and the Chinese Remainder Theorem, our scheme provides a fine-grained authentication mechanism that eliminates the need for local computations on the user’s side, meaning users do not require a smartphone or other digital device. Furthermore, our scheme introduces category identifiers to facilitate vehicle selection based on specific classes within car-sharing contexts. A formal security analysis demonstrates that our scheme is existentially unforgeable against adversaries under the random oracle model. Finally, a comprehensive evaluation shows that our proposed scheme achieves competitive performance in terms of computational and communication overhead while offering enhanced practical functionalities. Full article

A unique line of Holstein cattle has been maintained without selection in Minnesota since 1964. After many generations, unselected cattle produce less milk, but have better reproductive performance and health traits when compared with contemporary cows. Comparisons between this line of unselected Holstein and those under selection provide useful insights that connect selection and complex traits in cattle. Utilizing these unique resources and sequence data, we sought to identify genome changes due to selection. We sequenced 30 unselected and 54 selected Holstein cattle and compared their sequence variants to identify selection signatures. After many years, the two populations showed completely different patterns in their genome-level population structures and linkage disequilibrium. By integrating signals from five different detection methods, we detected consensus selection signatures from at least four methods covering 14,533 SNPs and 155 protein-coding genes. An integrated analysis of selection signatures with gene annotation, pathways, and the cattle QTL database demonstrated that the genomic regions under selection are related to milk productivity, health, and reproductive efficiency. The polygenic nature of these complex traits is evident from hundreds of selection signatures and candidate genes, suggesting that long-term artificial selection has acted on the whole genome rather than a few major genes. In summary, our study identified candidate selection signatures underlying phenotypic differences between unselected and selected Holstein cows and revealed insights into the genetic basis of complex traits in cattle. Full article