Search Results (13,176)

Cuticular proteins (CPs)—key components of the insect exoskeleton—not only regulate development but also serve as structural barriers that enhance resistance against environmental stressors. This study identified CP gene families in Apis mellifera and analyzed their expression patterns during the worker capped brood development stages from mature larva to pre-eclosion. Using a comprehensive genome-wide bioinformatic approach, we identified 85 CP genes in A. mellifera which comprise six families: CPR (n = 43), CPAPs (n = 27), CPF (n = 2), Tweedle (n = 2), CPLCP (n = 8) and Apidermin (n = 3). Analysis of CP gene evolutionary relationship revealed that each CP family forms a distinct, relatively independent clade. Domain and motif analyses confirmed that all CPR members harbor a conserved Chitin_Bind_4 domain, consistent with CPR family structures in other taxa. Additionally, CPAP members possess one or three Chitin-binding Peritrophin-A domain (CBM_14), CPF members possess a conserved Pupal cuticle protein C1 domain (Cuticle_3), and Tweedle members contain a conserved domain of unknown function (DUF243). In addition, the analysis found no conserved domain within the CPLCP and Apidermin families. RNA-seq data revealed dynamic expression patterns of AmCPs during pupal development, with each gene family displaying a relatively characteristic temporal profile. Quantitative PCR validation of eight highly expressed CPR genes at 9 days post-capping confirmed the RNA-seq results. This work provides a comprehensive bioinformatic characterization and transcriptional analysis of CP genes in A. mellifera, offering a foundation for future functional studies on cuticle formation and identifying candidate genes potentially involved in cuticle development in honeybees. This work relies on transcriptomic data and in silico analyses. All proposed biological roles are hypothetical and require experimental validation. Full article

Background/Objectives: Alzheimer’s disease (AD), the most prevalent form of dementia, is characterized by an overall decline in cognitive functioning and represents a major public health crisis. It remains critical to be able to accurately and quickly diagnose patients with AD; however, recent deep learning approaches using MRI data do not provide sample generalization, have high computational requirements, and offer little interpretability. Methods: In this study, we present a new framework called eXplorative ViT-CNN (X-ViTCNN) that combines a customized Vision Transformer model with two previously trained CNNs (DenseNet201 and MobileNetV2). With our proposed preprocessing approach using contrast-enhanced preprocessing to highlight neuroanatomical features as well as Bayesian Optimization to tune hyperparameters, we fuse local structural features originating from the CNNs with global representations from the transformer and feed the final result to fully connected dense layers for multi-stage classification. We also use Grad-CAM visualizations to provide insight into how our model arrived at its classification. Results: Experiments conducted on ADNI and OASIS datasets demonstrate the superiority of X-ViTCNN, achieving accuracies of 97.98% and 94.52%, respectively. The model outperformed individual baselines and other pre-trained architectures, showing balanced sensitivity and specificity across all AD stages. Conclusions: The proposed X-ViTCNN framework is a powerful, interpretable method for predicting the development of multi-stage Alzheimer’s disease using MRI scans. The combination of complementary feature learning, automatic hyperparameter optimization and interpretability through visualization make it an excellent potential tool for clinicians to support their decision making in the early diagnosis and ongoing monitoring of persons with Alzheimer’s disease. Full article

Multiple sclerosis (MS) is a highly disabling chronic autoimmune disease of the central nervous system with neuroinflammatory and neurodegenerative alterations found in the white and grey matter of the brain. The pathogenesis of MS is complex and not fully understood. Mitochondrial dysfunctions are suspected to play an important role. The visual system is often affected in MS. Optic neuritis is a frequent symptom, but also the retina itself, including retinal synapses appear compromised in MS independent from demyelination of the optic nerve. A previous study demonstrated synapse-specific alterations of mitochondria in photoreceptor synapses in the Experimental Autoimmune Encephalomyelitis (EAE) mouse model of MS at day 9 after injection, an early time point in pre-clinical EAE. In the present study, we analysed even earlier stages of pre-clinical EAE for possible alterations of synaptic mitochondria. For this purpose, we performed qualitative and quantitative immunolabelling analyses of the mitochondrial cristae organising protein MIC60 at retinal synapses and functional analyses by measuring synaptic mitochondrial membrane potential (during rest and depolarisation-induced exocytosis) and visually guided behaviour (optometry analyses). At day 3 after injection, morphological and functional data were indistinguishable between MOG/CFA-injected EAE mice and CFA-injected control mice. But already on day 5 after injection, we observed a decreased expression of the mitochondrial MIC60 protein at synaptic mitochondria, a decreased synaptic mitochondrial membrane potential at rest, an enhanced drop of mitochondrial membrane potential during stimulated exocytosis and a decreased visual performance of the respective EAE mice. These data argue that synaptic pathology in the EAE retina begins as early as day 5 after injection. Our data propose that dysfunctions of mitochondria play an important role already at the very early stages of synaptic pathology in EAE. Full article

Colorectal cancer (CRC) develops through both conventional adenoma–carcinoma and serrated neoplasia pathways, yet noninvasive screening still under-detects the advanced precursor lesions that enable true cancer prevention. Stool-based screening reduces CRC mortality, but its preventive impact remains constrained by limited detection of advanced precancerous lesions (APLs), including advanced adenomas and sessile serrated lesions. Next-generation multitarget stool DNA assays (mt-sDNA; e.g., Cologuard Plus) have established high sensitivity for CRC and specificity approaching 94%, leaving improved APL detection as the principal opportunity for innovation. This review presents a consensus framework for a multi-omic stool screening paradigm that integrates host epigenetic markers (DNA methylation) with gut microbiome features using artificial intelligence (AI). Multi-omics capture complementary layers of early tumor biology: epithelial shedding and field effects reflected in host methylation signals together with luminal ecological and inflammatory changes represented by microbial features. Evidence from cross-cohort microbiome studies indicates that microbial signatures provide an additive—rather than standalone—axis of information for CRC and its precursor lesions. Because microbiome-based models are highly susceptible to batch effects arising from collection devices, extraction chemistry, sequencing platforms, and bioinformatic pipelines, practical mitigation strategies are outlined, including harmonized pre-analytics, batch-aware study design, leakage-resistant validation, and computational harmonization. A translational roadmap linking analytical validity, locked-model development, and prospective colonoscopy-verified clinical validation is proposed, aligned with TRIPOD + AI, STARD, PROBAST-AI, SPIRIT-AI, CONSORT-AI, and DECIDE-AI reporting standards. Scenario modeling using BLUE-C prevalence estimates suggests that improving APL sensitivity from approximately 43% to 55–65% at ~94% specificity could translate to detecting roughly 13–23 additional advanced precancerous lesions per 1000 individuals screened, highlighting the potential prevention impact of a multi-omic approach. This framework aims to guide developers and clinical investigators toward next-generation stool tests capable of materially improving precursor-lesion detection while maintaining clinically acceptable specificity. Full article

Irrigation-driven greening is essential for northwest China’s dryland ecosystems, where vegetation growth depends on key hydrological factors, including precipitation (PRE), evapotranspiration (ET), soil moisture (SM), and irrigation water use (IWU), which affect water availability to a certain extent. To assess greening sustainability, a 1 km IWU dataset was created for 2001–2022 by combining remote sensing and ancillary data using machine learning, overcoming limited irrigation records. By linking IWU with the normalized difference vegetation index (NDVI) and analyzing trends in irrigated areas, we implemented a regional zonation approach to identify specific risk areas and evaluated both greening sustainability and vegetation responses using water balance (WB) and various hydrological variables. The results show that NDVI has increased widely over the past two decades, with sustained positive WB and stable irrigation, indicating improved water availability. However, spatial differences exist: 35.98% of irrigated areas have rising NDVI but falling IWU, especially in the east, where higher NDVI, IWU, WB, PRE, and ΔSM (soil moisture difference between growing season end and start) reflect favorable climate and hydrology; attention should also be directed toward potential deep percolation and saline sinks. In contrast, areas with high IWU often displayed elevated NDVI but declining water availability, suggesting unsustainable greening due to excessive irrigation. In addition, the SCD_IWU-SCD_NDVI class dominates among significant NDVI-IWU trends, indicating potential for sustainable irrigation under certain drought and climate conditions. Overall, the northwestern portion of the study area exhibits the lowest water availability; cities such as Urumqi warrant particular attention. These findings identify at-risk areas and those with better water resilience, supporting targeted water–vegetation management. Full article

Background/Objectives: Acute radiotherapy-induced skin toxicity is a common complication in breast cancer treatment, with marked interindividual variability not fully explained by clinical factors. This study investigated the contribution of germline mutations in DNA repair and tumor suppressor genes to acute radiodermatitis in a homogeneous cohort treated with hypofractionated intensity-modulated radiotherapy with inverse planning, with adjustment for potential lifestyle confounders. Methods: Mutations were grouped into four functional categories: homologous recombination repair (HRR), Fanconi anemia (FA), DNA damage response (DDR), and tumor suppressor (TS) genes. Ordinal logistic regression models adjusted for clinical covariates evaluated pooled and functional category-specific mutation effects. Results: Overall, any mutation significantly increased the risk of higher-grade acute radiodermatitis (OR = 2.24, p = 0.003), an effect driven primarily by HRR and FA mutations, as exclusion of these mutations rendered the association non-significant (OR = 1.785, p = 0.064). Functional category-based analyses showed that HRR (OR = 2.60, p = 0.002) and FA (OR = 2.62, p = 0.002) mutations were the strongest predictors, reflecting overlapping roles in double-strand break and interstrand crosslink repair. DDR and TS mutations showed no significant effect. Conclusions: These results highlight the key role of high-fidelity DNA repair in normal tissue radiosensitivity and demonstrate that functional genetic stratification has diagnostic value as a pre-treatment predictive biomarker framework, enabling identification of patients at increased risk of acute skin toxicity and supporting personalized radiotherapy planning. Full article

Mulberry (Morus alba) is an economically important forest tree species, yet cutting propagation is constrained by low adventitious rooting efficiency. Although ABT, a composite rooting promoter, can improve cutting survival, its molecular basis remains unclear. Here, cuttings of the cultivar Qiangsang 1 were treated with ABT, NAA, or IAA (200–1000 mg/L) and subjected to transcriptome profiling to elucidate how ABT enhances rooting. Hormone-related analyses showed that ABT upregulated GH3 (auxin-amido synthetase) at days 0 and 20, implicating auxin homeostasis. ERF1/2 (ethylene response factors) exhibited a temporal oscillation, with induction at day 10 followed by repression from days 20 to 30, consistent with a shift from developmental programs to defense-related processes. In parallel, JAZ (jasmonate ZIM-domain) genes were downregulated at day 0 and subsequently upregulated; together with CYP94C1, these changes may attenuate jasmonate-associated defense signaling. For cell remodeling and defense coordination, ABT reduced the expression of genes associated with cell-wall rigidity while inducing EXPA11 (expansin) at day 20, potentially facilitating root primordium emergence. Meanwhile, PR-1 (pathogenesis-related protein 1) was transiently upregulated at days 0, 20, and 30, and the concomitant modulation of WRKY transcription factors and RPM1 suggests enhanced defense readiness. Integrative network analysis further indicated that a GH3–ERF1/2–PR-1 module links hormonal and defense cues and may activate BAT1 (energy metabolism) and RBOHB (ROS production) to support adventitious root elongation. Collectively, these results suggest that ABT improves rooting efficiency by reshaping hormonal homeostasis and coordinating cell-wall reconstruction with a pre-activated defense state, thereby providing a conceptual framework for balancing root induction and defense responses during vegetative propagation in forest trees. Full article

Fermentation is a widely utilized technology that efficiently enriches bioactive compounds, thereby enhancing the bioactivity of food. This study aimed to investigate the release of the total polyphenol content (TPC) and flavonoid content (TFC),changes in antioxidant activity, and in vitro relative abundance trends of phenolic metabolites in the fermented composite juice of kidney beans and mulberries. An in vitro simulated gastric and intestinal digestion method was employed to examine the release patterns of polyphenols and flavonoids, along with alterations in antioxidant activity during the gastrointestinal digestion of the fermented composite juice. Non-targeted metabolomics LC-MS technology was employed to detect changes in the relative abundance and enrichment of phenolic metabolites during fermentation and digestion stages. The results indicated that after simulated digestion, the polyphenol content increased by 1.42-fold and the flavonoid content by 2.53-fold compared to pre-digestion. The scavenging rates for DPPH radicals, hydroxyl radicals, and ABTS radicals reached 85.44%, 94.77%, and 76.12%, respectively. Non-targeted metabolomic investigation through KEGG pathway enrichment showed associations between phenolic metabolites and antioxidant activity. During fermentation and digestion, daidzein, genistein, quercetin, and catechin may be the potential compounds contributing to the enhanced antioxidant activity of FBMJ. Among these, phenolic metabolites are significantly enriched in the biosynthetic pathways of flavonoids and flavanols. This study has elucidated the metabolic variations between the fermentation and digestion stages of fermented composite juice from a metabolomics perspective, providing preliminary in vitro research evidence and theoretical clues for developing it as a functional food with antioxidant potential. Full article

Background/Objectives: Hepatocellular carcinoma (HCC) is a primary malignancy often driven by metabolic syndrome, fatty liver disease, and chronic hepatitis. These conditions foster a pro-inflammatory microenvironment that promotes tumor progression. Viniferin, a natural oligostilbene, has gained attention for its potential bioactivity. This study utilized an in silico network pharmacology approach to elucidate the pharmacokinetic properties and molecular mechanisms of ε- and δ-viniferin against HCC within the context of metabolic and inflammatory liver pathologies. Methods: ADMET profiles were characterized using SwissADME and pkCSM. Therapeutic targets were identified by intersecting viniferin-associated molecules with disease genes from GeneCards. A protein–protein interaction (PPI) network was constructed, supplemented by GO and KEGG enrichment analyses. Molecular docking and 200 ns of molecular dynamics (MD) simulations evaluated the binding affinity and structural stability between viniferin isomers and identified hub proteins. Results: Both ε- and δ-viniferin showed favorable drug-like properties, including high gastrointestinal absorption and low hepatotoxicity. We identified 247 overlapping targets, with network analysis highlighting ten essential hub genes, including AKT1, HSP90AA1, ESR1, HIF1A, NFKB1, GSK3B, PTGS2, APP, MTOR, and PIK3CA. Enrichment analysis confirmed their involvement in critical oncogenic pathways. Molecular docking showed strong interactions with APP, HSP90AA1, and AKT1, while MD simulations validated the long-term stability of ε-viniferin within the APP binding pocket. Conclusions: These findings provide mechanistic insights into viniferin as a multi-target agent for HCC, justifying further experimental validation in pre-clinical models. Full article

Background/Objectives: Despite recent advances in breast cancer diagnostics, therapies and personalized medicine through genetic profiling, effective treatment of aggressive subtypes, particularly triple-negative breast cancer (TNBC), remains a considerable clinical challenge. MicroRNAs (miRNAs) are post-transcriptional regulators of gene expression that influence tumor progression and are detectable extracellularly in biofluids, where they are typically protected within extracellular vesicles (e.g., exosomes) or associated with RNA-binding proteins and lipoprotein complexes. This review integrates current evidence on oncogenic and tumor-suppressive extracellular miRNAs in breast cancer, with emphasis on subtype-specific functions and potential clinical relevance as liquid-biopsy biomarkers and therapeutic targets. Methods: A PubMed-based literature review (January 2000–February 2026) was conducted using search terms combining “breast cancer” with “miRNA/microRNA” and “circulating/plasma/serum/exosomal/extracellular vesicle.” Studies were prioritized if they provided validated targets/mechanisms and/or human clinical evidence for diagnostic, prognostic, or predictive utility; discrepant findings were evaluated in a subtype-aware framework. Findings were organized into functional categories (e.g., EMT/metastasis, cell-cycle/DNA damage, immune modulation, and hormone/growth factor signaling). Clinical and translational studies evaluating circulating miRNAs for diagnosis, prognosis, treatment response, and toxicity prediction were synthesized, together with key pre-analytical and analytical variables that affect reproducibility. Results: Across mechanistic and clinical studies, miR-21 and miR-155 recur as prominent oncogenic miRNAs, whereas miR-205 is frequently reported as a tumor-suppressive miRNA that is reduced in breast cancer and in circulation in several cohorts. Panels combining these miRNAs show promise for sensitive and specific breast cancer diagnostics. Additionally, several miRNAs show context- or subtype-dependent effects, with opposing activities reported between TNBC and estrogen receptor (ER)-positive disease (e.g., miR-17-92, miR-425, miR-181 family members, miR-31, and miR-24). Conclusions: Circulating miRNAs represent a promising class of minimally invasive biomarkers and potential therapeutic targets; however, translation is constrained by biological context dependence and by pre-analytical and analytical variability. Standardized protocols and rigorously validated, subtype-aware biomarker panels will be essential for clinical implementation and for enabling miRNA-informed precision oncology in breast cancer. Full article

Adoptive immunotherapy using ex-vivo-amplified autologous αβ T cells has achieved notable success in the treatment of diverse cancer types. Pre-eminent among these developments has been the advent of chimeric antigen receptor (CAR) T cell therapy, which has revolutionised the treatment of selected haematological malignancies. However, autologous CAR T cell immunotherapy is poorly scalable and has demonstrated limited efficacy against solid tumours. Accordingly, there has been significant interest in alternative strategies that may bridge these gaps. The use of γδ T cells is an attractive alternative since they possess intrinsic anti-tumour activity and do not elicit graft versus host disease (GvHD) when employed as an allogeneic drug product. In this review, we evaluate the potential use of γδ T cells for cancer immunotherapy and how manufacturing and genetic engineering refinements can be used to potentiate this activity. We also summarise current clinical experience with CAR γδ T cell therapies and discuss the implications of these findings for the next generation of cellular immunotherapies. Full article

Tart cherry is an important fruit crop in Utah, where irrigation is essential due to arid conditions. Precision irrigation requires reliable indicators of plant water status, and stem water potential (Ψ_stem), is among the most sensitive though labor-intensive and spatially limited. This study develops Ψ_stem estimation models using high-resolution multispectral Unmanned Aerial Vehicle (UAV) imagery combined with meteorological and soil moisture data, applying Symbolic Regression (SR). Results show a stronger correlation between optical bands and Ψ_stem during the pre-harvest period. Among 85 vegetation indices, the Red Chromatic Coordinate (RCC) index performed best (R² = 0.67). Six equations were generated for different data-availability scenarios and validated using a leave-one-tree-out (modified k-fold) approach, resulting in Ψ_stem estimates with R² values ranging from 0.67 to 0.80 and root mean square errors (RMSE) ranging from 0.11 to 0.08 MPa. Notably, SR was able to produce interpretable equations that enhance model transparency and transferability. Model robustness was further confirmed using an independent dataset from a different location. To our knowledge, this is the first application of SR for Ψ_stem estimation, offering a scalable and interpretable tool to support irrigation management in tart cherry orchards. Full article

Oxidation of oils is a free-radical cascade of reactions leading to the formation of undesirable odors and tastes, nutrient degradation, and potentially harmful compounds. To better understand the oxidation process, the kinetic parameters were examined depending on the degree of conversion (0 ≤ α ≤ 1) in this study. This approach provides insight into the complexity of the oxidative mechanism and allows a more reliable evaluation of the oxidative stability of nettle seed oil and its behavior during thermal treatment. A non-isothermal DSC method was applied, and kinetic parameters including the activation energy (Ea), the pre-exponential factor (A), and the reaction rate constant (k) were evaluated by applying the isoconversional Ozawa–Flynn–Wall method. Based on kinetic parameters, a simulation of oil oxidation at constant temperature (22 °C) was performed and the oil induction time was estimated. This value was compared to the ones obtained by OXITEST method. The observed conversion-dependent kinetic parameters demonstrate the complex oxidation behavior of nettle seed oil and justify the application of conversion-sensitive kinetic models to accurately describe its thermal stability. The induction period obtained under accelerated oxidation conditions suggests satisfactory oxidative stability of oil and highlights its potential suitability for nutritional and functional applications. Full article

Antitubercular drug-induced liver injury (ATDILI) poses a significant obstacle to successful tuberculosis treatment, including for tuberculous lymphadenitis. Its global incidence varies considerably, typically ranging from 2% to 30%, influenced by factors like patient demographics, co-morbidities, and geographical context. Despite some findings suggesting potentially lower rates in tuberculous lymphadenitis, the inherent hepatotoxic nature of standard anti-TB drugs means the risk remains clinically relevant. Key risk factors for ATDILI encompass older age, female gender, pre-existing liver conditions, HIV co-infection, malnutrition, alcoholism, and genetic polymorphisms, particularly in N-acetyltransferase 2 which affects isoniazid metabolism. The mechanisms of injury are drug-specific: isoniazid primarily causes hepatocellular damage via oxidative stress from toxic metabolites, while rifampicin induces cholestasis and endoplasmic reticulum stress, and pyrazinamide is linked to mitochondrial dysfunction. Management involves prompt withdrawal of antitubercular therapy when liver enzyme thresholds are exceeded, followed by careful reintroduction. Challenges are amplified in resource-limited settings due to higher prevalence of risk factors and limited access to consistent monitoring and sophisticated diagnostics. Promising advancements include safer regimens like the 3-month once-weekly isoniazid-rifapentine (3HP) for latent TB, which significantly reduces hepatotoxicity. The development of shorter active TB regimens and novel anti-TB drugs with improved safety profiles further aims to enhance treatment adherence and reduce ATDILI incidence, ultimately improving patient outcomes globally. Full article

Crossbreeding indigenous goats with exotic meat breeds is a common strategy to improve production performance, but its combined effects on growth and reproductive traits and the potential contribution of the gut microbiota have not been systematically evaluated in Chinese goat populations. This study used high-prolific Jining Grey (JJ) does mated with Nubian (N) bucks to establish three genetic groups: purebred Jining Grey (JJ), F1 Nubian × Jining Grey (NJ), and backcross offspring (Nubian × (Nubian × Jining Grey); NJJ). Body weight from birth to 12 months and average daily gain were recorded, reproductive traits (lambing rate, litter size, and kid survival) of primiparous and multiparous does were analyzed, and litter total birth weight and weaning weight per lambing were calculated. Fecal samples from JJ and NJJ goats were subjected to 16S rRNA gene sequencing to characterize gut bacterial communities. Body weight differed significantly among the three genetic groups at all ages (p < 0.01). Crossbred kids (NJ and NJJ) were about 30% heavier at birth and showed higher body weight and average daily gain during pre- and post-weaning periods than JJ kids (p < 0.05), representing a consistent growth advantage. In contrast, lambing rate, litter size and kid survival did not differ among genotypes (p > 0.05), whereas litter total birth weight and weaning weight were higher in crossbred than in purebred does (p < 0.05). Alpha-diversity indices were similar between JJ and NJJ goats (p > 0.05), but community structure was significantly distinct (PERMANOVA, p = 0.001), characterized by an increased Firmicutes-to-Bacteroidota ratio and shifts in several energy metabolism-related genera (p < 0.05). In conclusion, introgression of Nubian genetics into Jining Grey goats improves growth performance and litter weight while maintaining high prolificacy; these improvements are accompanied by a restructured gut microbiota that is associated with these growth patterns. Full article