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As an indigenous goat breed unique to southern China, Leizhou Black Goats (LZBGs) are highly valued for their rapid growth, high reproductive performance, and superior meat quality. However, their offspring frequently exhibit symptoms of muscle atrophy and malnutrition, suggesting potential genetic defects underlying these adverse phenotypes. As a unique extracellular matrix component, collagen Q (COLQ) is specifically enriched within the synaptic basal lamina at vertebrate neuromuscular junctions (NMJs), where it anchors acetylcholinesterase (AChE) to facilitate efficient acetylcholine hydrolysis, ensuring precise neuromuscular signaling. The current investigation sought to characterize the spectrum of genetic polymorphisms within the COLQ gene and assess their correlation with key production traits, including growth performance and meat quality parameters, in the LZBG population. Previously, through whole-genome sequencing and transcriptome sequencing analyses of an LZBG population, we identified four SNPs in the COLQ gene, namely, two missense mutations (SNP1: p.238A/S and SNP3: p.47G/S), one intronic variant (SNP2), and one synonymous mutation (SNP4: p.101P/P). Population genetic analysis revealed strong linkage disequilibrium between SNP1 and SNP2. Computational modeling of protein structures predicted that the identified missense mutations may lead to alterations in protein conformation. Association analyses demonstrated significant correlations of SNP1 and SNP3 with growth and meat quality traits (p < 0.05), where SNP3 reduced COLQ expression by 0.64-fold in homozygotes. Association analysis revealed that both SNP1 and SNP3 showed significant correlations with growth and meat quality traits in LZBGs (p < 0.05). Notably, SNP3 (p.47G/S) was found to regulate COLQ gene expression, reducing its levels by 0.64-fold in homozygous individuals, suggesting its potential as a genetic marker for selecting goats with superior growth performance and muscular development characteristics. The identified genetic variants establish a foundation for marker-assisted selection in LZBG breeding programs with particular relevance to growth performance enhancement, while also advancing the understanding of COLQ’s functional mechanisms in muscle development. Full article

The rapid and sensitive detection of regulatory elements within transgenic constructs of genetically modified organisms (GMOs) is essential for effective monitoring and control of their distribution. In this study, we present several innovative electrochemical biosensing platforms for the detection of regulatory sequences in genetically modified (GM) plants, combining the loop-mediated isothermal amplification (LAMP) method with electrodes functionalized by two-dimensional (2D) nanomaterials. The sensor design exploits the high surface area and excellent conductivity of reduced graphene oxide, Ti₃C₂T_x, and molybdenum disulfide (MoS₂) to enhance signal transduction. Furthermore, we used a “green synthesis” method for Ti₃C₂T_x preparation that eliminates the use of hazardous hydrofluoric acid (HF) and hydrochloric acid (HCl), providing a safer and more sustainable approach for nanomaterial production. Within this framework, the performance of various custom-fabricated electrodes, including laser-patterned gold leaf films, physical vapor deposition (PVD)-deposited gold electrodes, and screen-printed gold electrodes, is evaluated and compared with commercial screen-printed gold electrodes. Additionally, gold and carbon electrodes were electrochemically covered by gold nanoparticles (AuNPs), and their properties were compared. Several electrochemical methods were used during the DNA detection, and their importance and differences in excitation signal were highlighted. Electrochemical properties, sensitivity, selectivity, and reproducibility are characterized for each electrode type to assess the influence of fabrication methods and material composition on sensor performance. The developed biosensing systems exhibit high sensitivity, specificity, and rapid response, highlighting their potential as practical tools for on-site GMO screening and regulatory compliance monitoring. This work advances electrochemical nucleic acid detection by integrating environmentally-friendly nanomaterial synthesis with robust biosensing technology. Full article

Background/Objectives: The effects of PD-L1 are mediated via its binding to the PD-1 receptor, which mediates the signals intracellularly to suppress T-cell responses. The expression levels of PD-L1 on cancer cells are an important indicator of immunosuppression and cause poor prognosis in several types of cancers. Therefore, the identification and characterization of mechanisms that regulate the expression of PD-L1 in cancer patients is very critical. Method: Our experiment was designed to determine the impact of histone deacetylase (HDAC) inhibitor on PD-L1 expression to reverse tumor-induced immunosuppression using H460 and HCC827 lung cancer cell lines. These cells were treated with the HDAC inhibitor suberoylanilide hydroxamic acid (SAHA). PD-L1 expression levels were assessed along with key regulatory proteins, including p53, p21, acetyl-histones, DNMT3B, MGMT, and trimethyl histones. Results: In our experiments, suberoylanilide hydroxamic acid (SAHA) was able to reduce the expression of PD-L1 by 60% in a dose-dependent manner. While the level of PD-L1 was significantly reduced, a concurrent increase in levels of p53, p21, and acetyl histone levels were observed in H460 and HCC827 cells following SAHA treatment. Furthermore, SAHA treatment was able to decrease the levels of DNMT3B, MGMT, and tri-methyl histones. It appears that the decrease in PD-L1 expression observed is solely because of p53 or p21WAF1/CIP1-mediated negative control on the transcription process. Conclusion: Our results suggest that SAHA can be used along with immune checkpoint inhibitors to potentiate the therapeutic outcomes in patients with excessive immunosuppression due to PD-L1 expression. Full article

Vitiligo is an acquired depigmentation disorder characterized by the selective destruction of melanocytes, resulting in the progressive loss of pigment in the skin and hair. This condition frequently leads to significant psychological distress. Its pathogenesis is complex and multifactorial, involving a combination of genetic susceptibility, metabolic derangement related to oxidative stress, defective melanocyte adhesion to the basal epidermis, and dysregulated innate and adaptive immune responses, ultimately converging in the targeted elimination of melanocytes. Despite the availability of several therapeutic modalities, current corrective options are often limited in efficacy and are associated with high relapse rates. There remains a pressing need for novel, safe, and more effective therapeutic strategies to improve patients’ quality of life. Growing evidence indicates that the immune system plays a pivotal role in vitiligo onset and progression, as most triggers converge on inflammatory and autoimmune pathways targeting melanocytes. However, immunosuppressive therapies alone have shown limited effectiveness in halting disease progression and achieving lasting repigmentation. Targeting only immunological processes without addressing the underlying triggers of their activation likely represents a significant limitation in restoring pigmentation. In contrast, interventions aimed at upstream events may help prevent the initiation of the immune response. Consequently, combinatorial therapeutic approaches that target multiple pathogenic pathways and incorporate diverse pharmacological agents are being explored to improve clinical outcomes. This review aims to re-evaluate the intrinsic cellular abnormalities and associated dysregulated signaling pathways in vitiligo, with the goal of identifying novel, effective, nonimmunological treatment strategies. Full article

MYCN amplification without concurrent RB1 mutations characterizes a rare yet highly aggressive subtype of retinoblastoma; however, its precise developmental origins and therapeutic vulnerabilities remain incompletely understood. Here, we modeled this subtype by lentiviral-mediated MYCN overexpression in human pluripotent stem cell-derived retinal organoids, revealing a discrete developmental window (days 70–120) during which retinal progenitors showed heightened susceptibility to transformation. Tumors arising in this period exhibited robust proliferation, expressed SOX2, and lacked CRX, consistent with origin from primitive retinal progenitors. MYCN-overexpressing organoids generated stable cell lines that reproducibly gave rise to MYCN-driven tumors when xenografted into immunodeficient mice. Transcriptomic profiling demonstrated that MYCN-overexpressing organoids closely recapitulated molecular features of patient-derived MYCN-amplified retinoblastomas, particularly through activation of MYC/E2F and mTORC1 signaling pathways. Pharmacological screening further identified distinct therapeutic vulnerabilities, demonstrating distinct subtype-specific sensitivity of MYCN-driven cells to transcriptional inhibitors (THZ1, Flavopiridol) and the cell-cycle inhibitor Volasertib, indicative of a unique oncogene-addicted state compared to RB1-deficient retinoblastoma cells. Collectively, our study elucidates the developmental and molecular mechanisms underpinning MYCN-driven retinoblastoma, establishes a robust and clinically relevant human retinal organoid platform, and highlights targeted transcriptional inhibition as a promising therapeutic approach for this aggressive pediatric cancer subtype. Full article

An estimated 2.6 billion individuals are currently living with overweight or obesity, and this number is projected to exceed 4 billion by 2035. Consequently, unless this increasing trajectory is effectively addressed, the trend is expected to continue in the coming years. The gut microbiome has emerged as a central regulator of host metabolism and energy homeostasis, making its detailed characterization crucial for the advancement of innovative therapeutic strategies and for elucidating mechanisms underlying metabolic health and disease. This review examines human obesity through the lens of the gut microbiome, providing a comprehensive overview of its role by addressing gut microbiome alterations, microbiome-driven mechanisms, dietary influences, prebiotic effects, microbiome-based therapeutics, and other approaches in the treatment of obesity and related metabolic disorders. The composition of the gut microbiome is altered in obesity and characterized by reduced microbial diversity and inconsistent shifts in dominant bacterial phyla, which collectively contribute to metabolic dysregulation. The gut microbiome influences obesity through multiple mechanisms. These include regulating energy balance and insulin sensitivity via short-chain fatty acids, inducing chronic inflammation, modulating metabolic and appetite genes, altering bile acid signaling, and promoting fat storage by inhibiting fasting-induced adipose factor. Dietary patterns exert a profound influence on gut microbiome composition and function, with plant-based diets conferring protective effects against obesity and its comorbidities. Microbiome-based therapeutics, including probiotics, synbiotics, and fecal microbiota transplantation, have demonstrated potential in modulating key metabolic and inflammatory pathways associated with obesity. As the scientific understanding of the human gut microbiome continues to advance, the integration of microbiome-based therapies into standard clinical practice is poised to become increasingly feasible and therapeutically transformative, particularly for obesity, a complex condition that demands innovative and customized interventions. Full article

To address the challenges of dynamic coupling interference and time-frequency feature degradation in current approaches to Ultra-High-Frequency Radio-Frequency Identification (UHF RFID) behavior recognition, this study proposes a novel behavior recognition method integrating multi-feature analysis with a dual-path residual network. The proposed method mitigates interference by using phase difference methods to eliminate signal errors and cross-correlation, as well as adaptive equalization algorithms to decouple interfering signals. To identify the target tags participating in behavioral interactions, we construct a three-dimensional feature space and apply an improved weighted isolated forest algorithm to detect active tags during interactions. Subsequently, Doppler shift analysis extracts behavioral features, and multiscale wavelet-packet decomposition generates time-frequency representations. The dual-path residual network then fuses global and local features from these time-frequency representations for behavioral classification, thereby identifying interaction behaviors such as ‘taking away’, ‘putting back’, and ‘hesitation’ (characterized by picking up, then putting back). Experimental results demonstrate that the proposed scheme achieves behavioral recognition accuracy of 94% in complex scenarios, significantly enhancing the overall robustness of interaction behavior recognition. Full article

The 2022 global mpox outbreak highlighted the risk of sustained human-to-human transmission of monkeypox virus (MPXV) in non-endemic regions, yet genomic surveillance in Asia, particularly in China, remains limited. This study conducted horizontal genomic surveillance of MPXV in Shenzhen from 2023 to 2024 to characterize the phylogenetic structure, mutational patterns, and adaptive evolution of locally circulating strains. Phylogenetic analysis showed 95.2% of strains belonged to the dominant lineage C.1.1, with 4.8% in lineage E.3, forming three distinct genetic clusters that indicate multiple independent introductions and established local transmission chains. Whole-genome mutational analysis identified 146 single-nucleotide polymorphisms (SNPs), 81.5% of which carried APOBEC3-mediated mutation signatures (TC > TT and GA > AA), reflecting host-driven antiviral editing. Notably, dynamic changes in low-complexity regions (LCRs) were observed, implying potential roles in genome plasticity and adaptive evolution. Functional analysis revealed non-synonymous substitution biases in host-interacting proteins OPG064, OPG145, and OPG210, while replication protein OPG105 remained conserved. Structural modeling identified critical substitutions in OPG002 (S54F), OPG016 (R84K), and OPG036 (R48C) that may enhance immune evasion by modulating TNF-α signaling, NKG2D engagement, and Type I interferon antagonism. These findings illuminate unique MPXV evolutionary dynamics in Shenzhen, emphasizing continuous genomic surveillance for non-endemic outbreak preparedness. Full article

The low immunogenicity and immune escape are bottlenecks for effective hepatocellular carcinoma (HCC) immunotherapy. We prepared and characterized a dual-target liposome complex, XA5508, by encapsulating the STING agonist cGAMP in liposomes and conjugating an anti-PD-L1 nanobody to the liposome surface. The anti-tumor effect and pharmacological mechanism of XA5508 were investigated using an in situ HCC mouse model. XA5508 can effectively inhibit in situ HCC with the characteristics of tumor-targeted delivery and sustained release of STING agonist cGAMP. The pharmacological mechanism study indicates that XA5508 activates the STING signaling pathway, increases the cytotoxicity of CD8⁺ T cells, reverses the immunosuppressive tumor microenvironment (TME) represented by M2-type macrophages, and transforms cold tumors into hot tumors. On the other hand, cGAMP induces the upregulation of PD-L1 expression in HCC, enhances the response of anti-PD-L1 nanobody (Nb) and the escape blockade of immune checkpoint PD-1/PD-L1. XA5508 shows remarkable anti-tumor effects of STING agonist and anti-PD-L1 nanobody against HCC, providing an innovative strategy for the development of new drugs for HCC. Full article

Acute lymphoblastic leukemia (ALL) remains a formidable therapeutic challenge, particularly within high-risk cohorts. Advances in next-generation sequencing have elucidated critical mutations that significantly influence prognosis and therapeutic decision-making. Tyrosine kinase inhibitors (TKIs) have significantly improved treatment outcomes in Philadelphia chromosome-positive (Ph+) ALL. Meanwhile, emerging therapies such as monoclonal antibodies and chimeric antigen receptor (CAR) T-cell therapies show promise for B-cell ALL, although they are associated with considerable toxicities. These developments underscore the persistent need for alternative therapeutic strategies that can benefit a wider range of patients. In this study, human ALL cell lines—characterized by either wild-type or mutant tumor protein p53 (TP53) status—were treated with RG7388 (an MDM2 (mouse double minute 2 homolog) inhibitor) and BBI608 (a STAT3 (signal transducer and activator of transcription 3) inhibitor), both as single agents and in combination. Cell viability was quantified using XTT assays, while apoptosis was assessed via flow cytometry. Additionally, immunoblotting and qRT-PCR were employed to evaluate changes in protein and gene expression, respectively. RG7388 demonstrated potent growth inhibition in the majority of ALL cell lines, with p53-mutant cell lines exhibiting resistance. BBI608 reduced cell viability across all tested cell lines, though with variable sensitivity. Notably, the combination of RG7388 and BBI608 elicited synergistic anti-proliferative effects in p53 wild-type and partially functional p53-mutant cells, enhancing apoptosis and stabilizing p53 protein levels. In contrast, MOLT-4 cells, which harbor concurrent TP53 and STAT3 mutations, did not benefit from the combination treatment, indicating an inherent resistance phenotype within this subset. Collectively, these findings highlight the therapeutic potential of combined MDM2 and STAT3 inhibition in ALL, particularly in p53 wild-type and partially functional p53-mutant contexts. This combinatorial approach augments apoptosis and tumor growth suppression, offering a promising avenue for expanding treatment options for a broader patient population. Further investigation is warranted to validate these preclinical findings and to explore translational implications in genetically diverse ALL subsets. Full article

Background: Pancreatic ductal adenocarcinoma (PDAC) is a highly heterogeneous malignancy, characterized by low tumor cellularity, a dense stromal response, and intricate cellular and molecular interactions within the tumor microenvironment (TME). Although bulk omics technologies have enhanced our understanding of the molecular landscape of PDAC, the specific contributions of non-malignant immune and stromal components to tumor progression and therapeutic response remain poorly understood. Methods: We explored genome-wide DNA methylation and transcriptomic data from the Cancer Genome Atlas Pancreatic Adenocarcinoma cohort (TCGA-PAAD) to profile the immune composition of the TME and uncover gene co-expression networks. Bioinformatic analyses included DNA methylation profiling followed by hierarchical deconvolution, epigenetic age estimation, and a weighted gene co-expression network analysis (WGCNA). Results: The unsupervised clustering of methylation profiles identified two major tumor groups, with Group 2 (n = 98) exhibiting higher tumor purity and a greater frequency of KRAS mutations compared to Group 1 (n = 87) (p < 0.0001). The hierarchical deconvolution of DNA methylation data revealed three distinct TME subtypes, termed hypo-inflamed (immune-deserted), myeloid-enriched, and lymphoid-enriched (notably T-cell predominant). These immune clusters were further supported by co-expression modules identified via WGCNA, which were enriched in immune regulatory and signaling pathways. Conclusions: This integrative epigenomic–transcriptomic analysis offers a robust framework for stratifying PDAC patients based on the tumor immune microenvironment (TIME), providing valuable insights for biomarker discovery and the development of precision immunotherapies. Full article

The transforming growth factor β (TGFβ) signaling axis plays a pivotal role in orchestrating a wide array of biological functions, encompassing cellular growth, proliferation, and differentiation. The aim of the present study was to identify the members of TGFβ signaling pathway and their expression patterns in large yellow croaker (Larimichthys crocea) under different culture modes. TGFβ signaling pathway and their expression patterns in fish reared under two different culture modes: Group N (2400 fish in a 120 m³ cage) and Group V (168,000 fish in a 5600 m³ aquaculture vessel). After 120 days, we analyzed 15 fish from each group and found that Group V exhibited faster growth and a slender body shape compared to Group N. Bioinformatics analysis identified 48 TGFβ superfamily members in L. crocea, including 21 ligands, 10 receptors, and 3 Smads. mRNA expression levels indicated that these signaling molecules influence growth rate and body shape through five distinct ligand–receptor–R-Smad pathways, with the INHBB-, Nodal-, and GDF3-ACVR2A-ALK4-Smad2 axis playing a predominant role in regulating these traits. Full article

In this paper, three alternative solutions to the problem of detecting and cleaning anomalies in soil signal time series, involving the use of artificial neural networks deployed on in situ data measurement end devices, are proposed and investigated. These models are designed to perform calculations on MCUs, characterized by significantly limited computing capabilities and a limited supply of electrical power. Training of neural network models is carried out based on data from multiple sensors in the supporting computing cloud instance, while detection and removal of anomalies with a trained model takes place on the constrained end devices. With such a distribution of work, it is necessary to achieve a sound compromise between prediction accuracy and the computational complexity of the detection process. In this study, neural-primed heuristic (NPH), autoencoder-based (AEB), and U-Net-based (UNB) approaches were tested, which were found to vary regarding both prediction accuracy and computational complexity. Labeled data were used to train the models, transforming the detection task into an anomaly segmentation task. The obtained results reveal that the UNB approach presents certain advantages; however, it requires a significant volume of training data and has a relatively high time complexity which, in turn, translates into increased power consumption by the end device. For this reason, the other two approaches—NPH and AEB—may be worth considering as reasonable alternatives when developing in situ data cleaning solutions for IoT measurement systems. Full article

Irritable Bowel Syndrome (IBS) and Metabolic dysfunction-associated fatty liver disease (MAFLD) have traditionally been viewed as disorders of distinct organ systems. IBS is a gut–brain axis disorder characterized by abdominal pain, altered bowel habits, and psychological comorbidities. MAFLD, recently redefined to emphasize its metabolic underpinnings, is the hepatic manifestation of systemic metabolic dysfunction. Growing evidence suggests that these conditions share overlapping pathophysiological mechanisms linked through disruption of the gut–liver–brain axis (GLBA), including psychological stress, gut dysbiosis, impaired intestinal permeability, systemic inflammation, and altered neuroendocrine signaling. Neuroimaging studies further reveal functional alterations in brain regions responsible for interoception, emotional regulation, and stress responsiveness in both disorders. This narrative review explores how psychological distress influences the onset and progression of IBS and MAFLD via GLBA dysfunction and stress-induced epigenetic reprogramming. A targeted literature search of major biomedical databases, supplemented by manual screening, identified relevant observational, clinical, neuroimaging, and molecular studies. Findings indicate that chronic psychological distress activates the hypothalamic–pituitary–adrenal (HPA) axis, elevates cortisol, disrupts gut microbiota, and reduces vagal tone; amplifying intestinal permeability and microbial translocation. These changes promote hepatic inflammation and gastrointestinal symptoms. Stress-related epigenetic modifications further impair GLBA communication, while psychological and lifestyle interventions may reverse some of these molecular imprints. Recognizing the shared neuromodulation and epigenetic mechanisms that link IBS and MAFLD opens promising avenues for integrated therapeutic strategies targeting the GLBA to improve outcomes across both conditions. Full article

The orbital fat of bighead carp (Hypophthalmichthys nobilis) represents a structural fat deposit located posterior to the eyes and constitutes an important edible component of the head region. Nevertheless, molecular mechanisms governing lipid accumulation during ontogenetic development remain insufficiently characterized. Here, we performed RNA-Seq on orbital fat tissues from 6-month-old (juvenile) and 18-month-old (market-size) bighead carp. A total of 1042 DEGs were identified, with 807 up-regulated and 235 down-regulated in the 6-month-old stage. Functional enrichment revealed key pathways including fatty acid metabolism, PPAR signaling, and glycolysis/gluconeogenesis. qRT-PCR validation confirmed RNA-Seq reliability. Notably, the differential expression patterns of genes such as cpt1a, cpt1b, slc27a1, fads2, and scd suggest their association with an elevated capacity for lipid synthesis in the orbital fat of 18-month-old bighead carp. This study presents the first transcriptome analysis of orbital fat development in a freshwater fish, offering insights into the genetic improvement of head meat quality traits and growth in bighead carp head. Full article