Search Results (20,774)

Background: Hashimoto’s thyroiditis (HT) is the result of a complex interplay between genetic, environmental, and epigenetic factors. The role of cellular and humoral immunity in the pathogenesis of the disease is well-established. Inflammatory infiltration of T and B lymphocytes is a key feature identified on ultrasound examination. The lack of data on the effect of L-thyroxine (LT-4) doses on the level of anti-TPO and anti-TG antibodies in Hashimoto’s thyroiditis and the relationship with anthropometric measurements resulted in the desire to fill this niche. Methods: A total of 70 Caucasian patients diagnosed with Hashimoto’s thyroiditis within the past two years were examined. The participants were divided into three groups based on their L-thyroxine dosage (≤50, 50–100, >100 μg). Results: The results revealed no correlation between the dosage of L-thyroxine and anthropometric measurements (age, height, body weight, and body fat content). No correlation was identified between the levels of anti-TPO and anti-TG and the dose of L-thyroxine in patients with Hashimoto’s thyroiditis. Conclusions: The mechanism regulating the levels of anti-TPO and anti-TG appears to be associated with a more advanced thyroid inflammation and disease process. Long-term observation of patients would be advisable. We present evidence of no effect of hormone dose on antibody levels in Hashimoto’s thyroiditis. Regardless of disease severity, immune regulation remains outside the scope of hormonal regulation. Full article

Unmanned aerial vehicles open new possibilities for developing technologies that support more sustainable and efficient agriculture. This paper presents a non-invasive method for repelling rodents from crop fields using ultrasound. The proposed system is implemented as a spherical-cap ultrasound loudspeaker array consisting of eight transducers, mounted on a drone that overflies the field while emitting sound in the 20–70 kHz range. The hardware design includes both the loudspeaker array and a custom printed circuit board hosting power amplifiers and a signal generator tailored to drive multiple ultrasonic transducers. In parallel, a genetic algorithm is used to compute flight paths that maximize coverage and increase the probability of driving rodents away from the protected area. As part of the validation phase, artificial intelligence models for rodent detection using a thermal camera are developed to provide quantitative feedback on system performance. The complete prototype is evaluated through a series of experiments conducted both in controlled laboratory conditions and in the field. Field trials highlight which parts of the concept are already effective and identify open challenges that need to be addressed in future work to move from a research prototype toward a deployable product. Full article

The increasing biomedical and conservation interest in porcine species has driven the development of advanced in vitro follicle culture systems designed to preserve genetic diversity and accurately model key stages of folliculogenesis. This study assessed a three-dimensional (3D) alginate-based system for the in vitro culture of porcine preantral follicles, aiming to overcome the structural limitations of conventional two-dimensional (2D) methods. A total of six experimental groups were established, consisting of group-cultured (four follicles/well) or individually cultured (one follicle/well) follicles maintained either without alginate (0%) or encapsulated in 0.5% or 1% alginate for 14 days in media supplemented with FSH, EGF, and IGF-I, with LH added from day 9. Follicular development was assessed by morphometric evaluation, image-based and histological analyses, and quantification of steroid hormones in media collected every 48 h. Group-cultured follicles encapsulated in 0.5% alginate most effectively maintained their 3D architecture, reached the largest diameters, and progressed more uniformly compared with other groups. In contrast, follicles cultured without alginate rapidly lost structural integrity, showed granulosa cell migration, and decreased in size, whereas those encapsulated in 1% alginate exhibited restricted growth. Estradiol and testosterone concentrations increased over time in the 0.5% alginate group, were lowest without alginate, and intermediate in 1% alginate. Individually cultured follicles exhibited reduced growth and lower total hormone production compared with group-cultured follicles; however, when normalized per-follicle, steroid secretion, particularly in the 0.5% alginate group, was enhanced, indicating increased steroidogenic efficiency on a per-follicle basis. These findings indicate that 0.5% alginate provides an optimal balance between structural support and physiological steroidogenesis during preantral follicle culture. This 3D system improves the biological relevance of porcine follicle culture and may support future applications in reproductive biology, conservation, and genetic resource preservation. Full article

Microbial fuel cells (MFCs) have attracted increasing attention due to their potential applications in renewable energy generation, waste utilization, and biomass upgrading, offering a promising alternative to traditional fossil fuels. By directly converting carbon-rich wastes into electricity, MFCs provide a unique approach to simultaneously address energy demand and waste management challenges. This review systematically examines the effects of various carbon-rich substrates on MFC performance, including lignocellulosic biomasses, molasses, lipid waste, crude glycerol, and C1 compounds. These substrates, characterized by wide availability, low cost, and high carbon content, have demonstrated considerable potential for efficient bioelectricity generation and resource recovery. Particular emphasis is placed on the roles of microbial community regulation and genetic engineering strategies in enhancing substrate utilization efficiency and power output. Additionally, the application of carbon-rich wastes in electrode fabrication is discussed, highlighting their contributions to improved electrical conductivity, sustainability, and overall system performance. The integration of carbon-rich substrates into MFCs offers promising prospects for alleviating energy shortages, improving wastewater treatment efficiency, and reducing environmental pollution, thereby supporting the development of a circular bioeconomy. Despite existing challenges related to scalability, operational stability, and system cost, MFCs exhibit strong potential for large-scale implementation across diverse industrial sectors. Full article

Mouse models of genetic diseases are important research tools. However, the genetic background of the mouse strain can significantly influence how a genetic mutation is expressed. Studies on preclinical models of phenylketonuria (PKU), an inherited metabolic disorder, have used two strains, BTBR and C57Bl/6, created via a chemically induced point mutation in the gene encoding the enzyme phenylalanine hydroxylase (BTBR^enu2 and C57^enu2, respectively). Despite having the same levels of hyperphenylalaninemia (HPA), published results indicate differences in neural and behavioral phenotypes between the two backgrounds. To explore this difference further, the current study examines the genome-wide transcriptome of the prefrontal cortex (pFC), the brain region which is the most vulnerable to the negative effects of HPA. Regardless of the strain, the enu2 mutation upregulated the expression of several aminoacyl-tRNA synthetases and eukaryotic translation initiation factors, suggesting an essential modification in the protein translation process and supporting the downregulation of gene programs related to myelination. Accordingly, we deepened the exploration of cognitive dysfunctions in C57^enu2− mice, showing a previously unreported working memory impairment under increasing information load. These findings identify convergent pFC molecular and cognitive alterations induced by HPA across distinct genetic backgrounds, providing clinically relevant insights into mechanisms that may contribute to executive dysfunctions in PKU. Full article

Genome-wide studies have identified significant allelic associations between genetic variants in or near the IKZF1 gene and multiple autoimmune disorders. IKZF1, encoding the transcription factor IKAROS, produces at least 10 distinct transcripts. To explore the impact of alternative splicing of IKZF1 on the function of mature T cells and the risk of autoimmunity, we generated a panel of human T-cell clones with truncating mutations in IKZF1 exons 4, 6, or both. Differences in gene expression, chromatin accessibility, and protein abundance among clones were assessed by RNA-seq, ATAC-seq, and immunoblotting. Clones with single targeting events clustered separately from double-targeted clones on multiple parameters, but overall, clone responses were highly heterogeneous. Perturbation of IKZF1 splicing resulted in significant differences in expression and chromatin accessibility of other autoimmunity-associated genes and elicited compensatory expression changes in other IKAROS family members. Our results suggest that even modest alterations of IKZF1 splicing can have significant effects on gene expression and function in mature T cells, potentially contributing to autoimmunity in susceptible individuals. Full article

Cereal vinegar sediment (CVS), a byproduct of traditional vinegar fermentation, has been regarded as a health-promoting product. However, its role in genetically induced hyperlipidemia remains unclear. This study systematically evaluated the effects of Dade-CVS (DD-CVS) and Hengshun-CVS (HS-CVS) on apolipoprotein-E-deficient (Apoe^−/−) mice. Both CVS varieties significantly improve certain serological parameters of Apoe^−/− mice, although the overall impact on serum indicators remains limited. Nevertheless, 16S rRNA sequencing revealed that CVS treatment reshaped gut microbial communities to a notable extent. Compared with the Apoe^−/− mice, the DD-CVS treatment significantly increased the relative abundance of Dubosiella while reducing the genus Desulfovibrio, whereas the HS-CVS treatment inhibited the growth of Bifidobacterium and Akkermansia. The pathways predicted in the KO-DD group included vitamin, amino acid, and energy metabolism, while HS-CVS treatment was associated with bile acid biosynthesis and energy pathways. Metabolomic analysis showed that several key metabolites, including N1-acetylspermidine, succinic acid, and 25-hydroxycholesterol, were significantly altered following CVS supplementation. Correlation analysis revealed significant associations between serum indicators and these metabolites. Alistipes, Enterorhabdus, and Romboutsia were also correlated with serum indicators. Overall, these findings indicate that CVS primarily modulated the gut microbiota–metabolite axis and partial lipid modulation in hyperlipidemic mice. The study provides a reference for studies on the beneficial functions of CVS in hyperlipidemia. Full article

Background: Catechol-O-methyltransferase (COMT) catalyzes catecholamine O-methylation and contributes to dopamine turnover, potentially influencing levodopa requirements in Parkinson’s disease (PD). We evaluated whether the Gothelf COMT haplotype—and its constituent variants rs2075507, rs4680 (Val158Met), and rs165599—differ in frequency between PD cases and controls. We then tested associations between these variants and clinical phenotypes, with a prespecified focus on levodopa equivalent daily dose (LEDD). Finally, we examined whether haplotype structure and allele-specific context (e.g., background-dependent effects) help explain observed genotype–phenotype relationships in the PD cohort. Aim: Analysis of the rs2075507, rs4680 and rs165599 at individual and haplotype level between control and diseased groups. Furthermore, analysis of association of individual SNPs or haplotype level with clinical outcomes. Subjects and methods: Fifty-five individuals with Parkinson’s disease (PD) and fifty-three neurologically healthy controls were enrolled at a single center. Genomic DNA was isolated from peripheral blood, and three COMT variants—rs2075507 (promoter), rs4680/Val158Met (coding), and rs165599 (3′UTR)—were genotyped by Sanger sequencing. Allele, genotype, and tri-marker haplotype frequencies were estimated, and case–control differences were evaluated. Within the PD cohort, associations with clinical outcomes—primarily levodopa equivalent daily dose (LEDD)—were analyzed using multivariable linear models. Statistical tests were two-sided, with multiplicity control as specified in the corresponding tables. Results: The rs2075507 polymorphism showed a robust additive association with LEDD; each A allele predicted higher dose (LEDD ≈ +1331 mg/day, p = 0.001) after adjusting for age and sex. The tri-haplotype test did not show significant association with LEDD. Nevertheless, rs2075507 SNP strongly marked downstream backgrounds: in AA carriers, rs4680–rs165599 haplotypes were enriched for Val (G) and rs165599-G; in GG carriers, for rs165599-A with mixed Val/Met; and GA was A-loaded at both loci. Exact tests confirmed that AA and GG differed in rs4680–rs165599 composition, whereas GA vs. GG was not significant. Conclusions: The promoter variation at rs2075507 may represent the genetic contributor to levodopa dose requirements when modeled with SNP–SNP interactions, with its effect is modified mostly by rs165599 polymorphism. Tri-haplotypes do not independently predict LEDD. The rs4680 (coding) and rs165599 (3′UTR) context appears to fine-tune rather than determine dosing needs, mainly via interaction with rs2075507 SNP. Full article

Epilepsy remains an active and important area of research due to its complex etiology, significant global burden, and variable response to treatment. Current knowledge has provided valuable insights into the underlying molecular mechanisms of the disease and continues to guide the development of novel therapeutic strategies. This review presents a comprehensive overview of the etiologies of epilepsy, as well as traditional and modern medical and surgical treatment approaches, while highlighting future research directions. Peer-reviewed articles retrieved from PubMed and Google Scholar were analyzed and synthesized to produce this review. The etiological complexity of epilepsy arises from genetic, metabolic, structural, and inflammatory mechanisms, which often coexist rather than act independently. A wide range of anti-seizure drugs (ASDs) is currently available, with many new agents targeting novel mechanisms under development. Surgical approaches, including resection, disconnection, corpus callosotomy, and neuromodulation, are widely used for patients with drug-resistant epilepsy and result in variable seizure outcomes. In addition, minimally invasive techniques such as laser interstitial thermal therapy (LITT), stereoelectroencephalography-guided radiofrequency thermocoagulation, gamma knife radiosurgery, and high-intensity focused ultrasound have gained clinical relevance and continue to be explored. Emerging technologies, including artificial intelligence, machine learning, and precision medicine, offer promising directions for future research. Although several potential biomarkers have been identified, none are yet established for routine clinical use. Continued investigation is essential to improve understanding of epileptogenesis and to develop safer, more effective therapies. Full article

During rotary tillage operations, the draft force is jointly affected by operating parameters and soil conditions, exhibiting pronounced nonlinearity, time-varying behavior, and historical dependence, which all impose higher requirements on tractor operating parameter matching and traction performance analysis. A draft force prediction method that is based on a long short-term memory (LSTM) neural network jointly optimized by a genetic algorithm (GA) and the bald eagle search (BES) algorithm, termed GABES-LSTM, is proposed to address the limited prediction accuracy and stability of traditional empirical models and single data-driven approaches under complex field conditions. First, on the basis of the mechanical characteristics of rotary tillage operations, a time-series mathematical description of draft force is established, and the prediction problem is formulated as a multi-input single-output nonlinear temporal mapping driven by operating parameters such as travel speed, rotary speed, and tillage depth. Subsequently, an LSTM-based draft force prediction model is constructed, in which GA is employed for global hyperparameter search and BES is integrated for local fine-grained optimization, thereby improving the effectiveness of model parameter optimization. Finally, a dataset is established using measured field rotary tillage data to train and test the proposed model, and comparative analyses are conducted against LSTM, GA-LSTM, and BES-LSTM models. Experimental results indicate that the GABES-LSTM model outperforms the comparison models in terms of mean absolute percentage error, mean relative error, relative analysis error, and coefficient of determination, effectively capturing the dynamic variation characteristics of draft force during rotary tillage operations while maintaining stable prediction performance under repeated experimental conditions. This method provides effective data support for draft force prediction analysis and operating parameter adjustment during rotary tillage operations. Full article

Against the backdrop of intensifying global population aging, lower-limb exoskeleton robots serve as core devices for rehabilitation and power assistance. Their control accuracy and motion smoothness rely on precise dynamic models. However, parameter uncertainties caused by variations in human lower limbs, assembly errors, and wear pose a critical bottleneck for accurate modeling. Aiming to achieve high-precision dynamic modeling for a two-degree-of-freedom lower-limb exoskeleton, this paper proposes a parameter identification method named Tent-GA-GWO. A dynamic model incorporating joint friction and link inertia was constructed and linearized. An excitation trajectory based on Fourier series, conforming to human physiological constraints, was designed. To enhance algorithm performance, Tent chaotic mapping was employed to optimize population initialization, a nonlinear control parameter was used to balance search behavior, and genetic algorithm operators were integrated to increase population diversity. Simulation results show that, compared to the traditional GWO algorithm, Tent-GA-GWO improved convergence efficiency by 32.1% and reduced the fitness value by 0.26%, demonstrating superior identification accuracy over algorithms such as GA and LIL-GWO. Validation on a physical prototype indicated a close agreement between the computed torque based on the identified parameters and the actual output torque, confirming the method’s effectiveness and engineering feasibility. This work provides support for precise control of exoskeletons. Full article

To accurately investigate the loss characteristics of fuel cell vehicles (FCVs) under actual operating conditions and enhance their power performance and economic efficiency, this study establishes a numerical model of the proton exchange membrane fuel cell (PEMFC) stack based on real-world data from the second-generation Mirai. The stack model incorporates leakage current losses and imposes a limit on maximum current density. Besides, this study analyzes the effects of operating parameters (PEM water content, hydrogen partial pressure, current density, oxygen partial pressure, and operating temperature) on stack power output, efficiency, and eco-performance coefficient (ECOP). Furthermore, Non-Dominated Sequential Genetic Algorithm (NSGA-II) is employed to optimize the PEMFC stack performance, yielding the optimal operating parameter set for FCV operation. Further simulations are conducted on dynamic performance characteristics of the second-generation Mirai under two typical driving cycles, evaluating the power performance and economy of the FCV before and after optimization. Results demonstrate that the established PEMFC stack model accurately analyzes the output performance of an actual FCV when compared with real-world performance test data from the second-generation Mirai. Through optimization, output power increases by 7.4%, efficiency improves by 1.95%, and ECOP rises by 3.84%, providing guidance for enhancing vehicle power performance and improving overall vehicle economy. This study provides a practical framework for enhancing the power performance and overall energy sustainability of fuel cell vehicles, contributing to the advancement of sustainable transportation. Full article

This study aimed to assess the variation, genetic architecture, and genome-enabled prediction of traits with nutritional and health relevance in 156 pea (Pisum sativum L.) accessions of diverse geographic origins. The traits included the total phenolic compounds (TPCs), two saponins (Ssβg, Ss1), sucrose, three raffinose-family oligosaccharides (RFOs), and the in vitro antioxidant activity (AA). An analysis of variance revealed significant effects of regional germplasm pools for all traits. Accessions from West Asia showed the highest TPC and AA levels, while those from the East Balkans and the UK displayed the lowest values. High saponin and RFO concentrations characterized accessions from Germany and the UK. Correlation and PCA analyses highlighted strong associations within compound classes and an overall negative relationship between TPCs/AA and saponins/RFOs. The accessions were clustered into seven metabolically distinct groups, partially reflecting their geographic origin. The linkage disequilibrium decayed rapidly (average of 4.7 kb). A GWAS based on 10,249 SNP markers identified 37 significant SNPs, 35 within annotated genes, associated with the metabolites, indicating a polygenic genetic architecture. Genomic prediction models showed a moderately high predictive ability (>0.40) for all traits except the raffinose content. Our findings can support line selection and the identification of genetic resources with a desired level of secondary metabolites. Full article

Semen cryopreservation is a critical biotechnological approach for preserving superior genetic resources in livestock. Spermatozoa are particularly vulnerable to cryogenic stress during the freeze–thaw process, resulting in impaired structure and function. Therefore, the development of effective cryoprotective additives is essential for improving yak semen cryopreservation. In this study, ginseng peptide (GFREH) was incorporated into the freezing extender at different concentrations (0, 0.25, 0.5, 0.75, and 1.0 mg/mL) to evaluate its effects on post-thaw sperm quality, in vitro fertilization (IVF) capacity, and the underlying regulatory mechanisms. Semen samples treated with 0 and 0.75 mg/mL GFREH were further subjected to proteomic analysis to elucidate the molecular basis of its cryoprotective action. The results demonstrated that GFREH significantly increased total motility (TM), progressive motility (PM), straight-line velocity (VSL), curvilinear velocity (VCL), average path velocity (VAP), as well as plasma membrane and acrosome integrity of frozen–thawed yak spermatozoa (p < 0.05). GFREH also significantly reduced malondialdehyde (MDA) levels while enhancing antioxidant enzyme activities, mitochondrial membrane potential (MMP), and ATP content (p < 0.05). Moreover, GFREH at concentrations of 0.5, 0.75, and 1.0 mg/mL significantly improved IVF and blastocyst formation rates compared with the control (p < 0.05), with the 0.75 mg/mL group exhibiting the highest fertilization and blastocyst rates. Proteomic analysis further revealed that GFREH modulated the PI3K/AKT signaling pathway and downregulated FOXO1 expression. Collectively, these findings indicate that ginseng peptides enhance yak sperm cryotolerance by coordinating oxidative balance, mitochondrial energy metabolism, and survival-related signaling, with 0.75 mg/mL representing an optimal effective concentration within the functional dose range tested. Full article

This study aimed to evaluate four different models for the genetic evaluation of sixteen conformation traits, milking ease, and milking temperament in Dairy Gir cattle. The models vary based on whether they include only statistically significant fixed effects or all recorded effects, along with contemporary groups (CGs) treated as fixed or random effects. Categorical traits were also analyzed using a threshold model. The adjusted R-squared ($R_{adj}^2$) was used to compare the goodness-of-fit of the linear models. Spearman’s rank correlation and the average accuracy of bull estimated breeding values (EBVs) with at least 20 phenotyped daughters were compared. Models fitting CG as a random effect performed better based on their $R_{adj}^2$ values and had a greater average accuracy of EBVs for most traits. Spearman’s rank correlation coefficients indicated low to medium bull EBV re-ranking between most of the models. The linear models performed better than threshold models for almost all traits. When possible, more parsimonious linear models fitting only significant fixed effects should be used to reduce the standard error of estimation. Additionally, fitting CGs as a random effect seems more beneficial for the genetic evaluation of conformation and milking traits in Dairy Gir cattle in Brazil. Full article