Search Results (3,856)

Mycotoxin contamination in agricultural products poses a serious challenge to food safety, severely threatening human and animal health and causing significant economic losses. This study aimed to investigate the degradation and detoxification capabilities of Trichoderma reesei GG-T40 against two representative mycotoxins—aflatoxin B₁ (AFB₁) and zearalenone (ZEN). The results showed that the degradation rates of AFB₁ and ZEN by this strain reached 98.6% and 88.4%, respectively. Using ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF MS), the degradation products were systematically characterized, leading to the identification of six AFB₁ degradation products (C₁₇H₁₄O₇, AFD₁: C₁₆H₁₄O₅, C₁₁H₁₀O₄, C₁₄H₁₆O₄, C₁₅H₁₀O₄, and C₁₇H₁₄O₅) and two ZEN degradation products (α-ZOL and β-ZOL). Toxicity evaluation revealed that the key toxic structures of AFB₁ were disrupted, significantly reducing or even eliminating the toxicity of its degradation products; ZEN was mainly converted into β-ZOL (accounting for 91.5%), which has lower estrogenic activity. Further toxicological experiments in mice confirmed that the degradation products were non-toxic and non-pathogenic under actual testing conditions, demonstrating systematic verification of their safety. In conclusion, T. reesei GG-T40 can efficiently and safely degrade AFB₁ and ZEN, showing great potential for developing green control technologies for mycotoxin contamination in food and feed raw materials, with important application value for ensuring food safety. Full article

Background/Objectives: The global fight against cancer persists despite advances in prevention and treatment. The current study investigated the phytochemical constituents, antioxidant, anti-inflammatory, and anticancer properties of Eucomis comosa, traditionally used in South Africa to treat elephantiasis and cancer-related conditions. Methods: Phytochemical screening, Fourier transform infrared spectroscopy (FTIR), and liquid chromatography–mass spectrometry (LC-MS) analyses were conducted. Antioxidant activity was measured through DPPH and nitric oxide (NO) radical scavenging assays. The anticancer activity was assessed using the MTT assay. Results: Phytochemical screening confirmed the presence of alkaloids, cardiac glycosides, terpenoids, flavonoids, saponins, and phlobatannins. FTIR analysis of the aqueous extract displayed characteristic peaks at 3278.92 cm⁻¹ for O–H stretch, at 2930.67 cm⁻¹ for C–H stretch, at 1623.97 cm⁻¹ for C=O stretch, 1410.24 cm⁻¹ for C=C stretch and at 931.17 cm⁻¹ for =C–H, while LC-MS identified diverse metabolites, including polyphenols such as flavan-3-ols, flavone glycosides, and chalcones. Among the extracts, methanol showed the strongest DPPH scavenging activity (IC₅₀ = 972.73 µg/mL), followed by ethanol (1296.36 µg/mL). For NO scavenging, methanol again outperformed ethanol, with IC₅₀ values of 1301 µg/mL and 2890 µg/mL, respectively. Cytotoxicity assays demonstrated that the ethanol extract completely inhibited cell growth at concentrations of 100 and 200 µg/mL. Methanol, ethanol, and hexane extracts significantly suppressed cell proliferation in DU-145, PC-3, and SKU-T-1 cancer cell lines at higher concentrations, with IC₅₀ values ranging between 0.2 and 2.5 µg/mL. Conclusions: These findings indicate that the phytochemicals and functional groups present in E. comosa extracts contribute to their dose-dependent antioxidant and anticancer activities, supporting their ethnomedicinal use. Full article

Testosterone (T) produced by Leydig cells (LCs) is essential for male reproduction; yet, the regulatory mechanisms underlying steroidogenesis remain incompletely understood. Here, we investigated the role of cyclin-dependent kinase 5 regulatory subunit-associated protein 3 (CDK5RAP3) in Leydig cell development and steroidogenesis, based on its identification by immunoprecipitation-mass spectrometry (IP-MS) as a protein associated with steroidogenesis and cholesterol metabolism in mouse testicular tissue. Using human samples, we found that CDK5RAP3 expression was significantly reduced in Leydig cells from patients with spermatogenic failure (T < 10.4 nmol/L). Notably, CDK5RAP3 expression increased during mouse postnatal Leydig cell maturation and regeneration in an ethane dimethanesulfonate (EDS)-induced rat model. Functional analyses in primary LCs and MLTC-1 cells showed that hCG stimulation triggered CDK5RAP3 nuclear translocation without altering its overall expression, while CDK5RAP3 knockdown markedly impaired hCG-induced testosterone production and reduced the expression of the steroidogenic regulator steroidogenic acute regulatory (STAR) protein, as well as key steroidgenic enzymes, including cytochrome P450 family 11 subfamily A member 1 (CYP11A1), 17a-hydroxylase (CYP17A1), and 3β-hydroxysteroid dehydrogenase (HSD3B). Conversely, CDK5RAP3 overexpression enhanced testosterone production in the absence of hCG. In vivo, AAV2/9-mediated CDK5RAP3 silencing in adult mouse testes resulted in a significant reduction in serum testosterone levels compared with controls (3.60 ± 0.38 ng/mL vs. 1.83 ± 0.37 ng/mL). Mechanistically, CDK5RAP3 interacted with SMAD4 and CEBPB, and BMP pathway inhibition by Noggin rescued the testosterone deficit caused by CDK5RAP3 loss. Together, these findings identify CDK5RAP3 as an essential regulator of Leydig cell steroidogenesis and provide insight into its potential relevance to male infertility associated with low testosterone. Full article

Multiple sclerosis (MS) is a chronic, heterogeneous, multifactorial, immune-mediated neurodegenerative disease of the central nervous system that affects the working-age population. Its development is influenced by both genetic and environmental factors. A pathological hallmark of MS is the formation of demyelinating lesions in the brain and spinal cord, which are associated with neuronal damage caused by autoaggressive immune factors (T cells, B cells, and myeloid cells). Focal lesions are believed to be caused by the infiltration of immune cells into the central nervous system (CNS) parenchyma with concomitant tissue damage. Multiple sclerosis represents a significant social problem due to the high cost of available treatments, as well as the deterioration of employment prospects and job retention for both patients and their caregivers. Advances in MS diagnostic methods have enabled disease detection at early stages and correction of immune response impairments. Concurrently, treatments for MS patients are actively being studied, with the ongoing development of novel methods for targeted and cellular immunotherapy. This review primarily discusses approaches to cellular immunotherapy and methods of influencing the cellular arm of immunopathogenesis in multiple sclerosis. Full article

Background: Interindividual differences in statin efficacy and tolerability are partly determined by genetic and metabolic factors. The SLCO1B1 c.521T>C polymorphism affects hepatic statin transport, while vitamin D deficiency may influence lipid metabolism and muscular tolerance. This study aimed to assess the impact of SLCO1B1 genotype and vitamin D status on lipid-lowering response and adverse events in postmenopausal women treated with atorvastatin or rosuvastatin. Methods: A total of 145 Croatian postmenopausal women were prospectively followed for 16 weeks. Participants received atorvastatin or rosuvastatin with dose titration to achieve low-density lipoprotein cholesterol (LDL-C) targets. Serum lipids, liver enzymes, and creatine kinase were monitored monthly. Serum levels of 25-hydroxyvitamin D were quantified by LC–MS/MS, while SLCO1B1 c.521T>C genotyping was performed using real-time PCR. Results: Rosuvastatin achieved a higher LDL-C target attainment rate compared with atorvastatin (81.1% vs. 67.6%, p = 0.02). The SLCO1B1 genotype was not associated with lipid response but was significantly associated with adverse effects. In multivariable regression analysis, patients with the T/C genotype had a significantly higher risk of developing adverse effects compared with those with the T/T genotype (OR 7.4, 95% Cl 2.1–26.7, p = 0.002). Vitamin D status showed no significant association with lipid outcomes or adverse events, although participants with severe deficiency exhibited a weaker LDL-C response. Conclusions: Rosuvastatin demonstrated superior lipid-lowering efficacy and tolerability compared with atorvastatin in postmenopausal women. The SLCO1B1 c.521T>C variant primarily affected safety rather than efficacy, while severe vitamin D deficiency might contribute to diminished statin response. Integrating pharmacogenetic and endocrine profiling could enhance individualized statin therapy and cardiovascular prevention in women. Full article

The use of metalworking fluid (MWF) in surface grinding is essential, but its supply contributes notably to the process energy demand. This study investigates the effect of the fluid jet to wheel speed ratio q_s on specific grinding energy and associated CO₂ emissions. Experiments with grinding wheels of different grit sizes (F60–F120) were conducted at cutting speeds of 35 and 60 m/s. Critical specific material removal rates Q’_{w, crit} were determined by taper grinding, with the onset of grinding burn identified by Barkhausen noise analysis. Based on these values and the grinding wheel width, specific process energies e_total were derived from grinding, pump, and machine base load. F120 wheels showed no systematic dependence of Q’_{w, crit} on q_s, whereas for coarser F80 and F60 wheels, decreasing q_s from 1.0 to 0.6 increased Q’_{w, crit} by 13–27% at 35 m/s and decreased it by 33–35% at 60 m/s. The most efficient process (F60, 35 m/s, q_s = 0.6) required 152.8 J/mm³, the least efficient (F120, 60 m/s, q_s = 0.8) 333.1 J/mm³. Because CO₂ emissions scale with e_total, the relative differences in energy directly indicate relative differences in CO₂ output. An illustrative case study shows that adjusting q_s alone (F80, 35 m/s) lowers annual emissions from 0.284 t to 0.206 t, a reduction of approximately 27%. These findings highlight the influence of q_s on grinding efficiency and process energy demand. Full article

The convergence of Artificial Intelligence (AI) and the Internet of Things (IoT) is enabling a new class of intelligent applications. Specifically, Large Language Models (LLMs) are emerging as powerful tools not only for natural language understanding but also for enhancing IoT security. However, the integration of these computationally intensive models into resource-constrained IoT environments presents significant challenges. This paper provides an in-depth examination of how LLMs can be adapted to secure IoT ecosystems. We identify key application areas, discuss major challenges, and propose optimization strategies for resource-limited settings. Our primary contribution is a novel collaborative embeddings offloading mechanism for IoT intrusion detection named SEED (Semantic Embeddings for Efficient Detection). This system leverages a lightweight, fine-tuned BERT model, chosen for its proven contextual and semantic understanding of sequences, to generate rich network embeddings at the edge. A compact neural network deployed on the end-device then queries these embeddings to assess network flow normality. This architecture alleviates the computational burden of running a full transformer on the device while capitalizing on its analytical performance. Our optimized BERT model is reduced by approximately 90% from its original size, now representing approximately 41 MB, suitable for the Edge. The resulting compact neural network is a mere 137 KB, appropriate for the IoT devices. This system achieves 99.9% detection accuracy with an average inference time of under 70 ms on a standard CPU. Finally, the paper discusses the ethical implications of LLM-IoT integration and evaluates the resilience of LLMs in dynamic and adversarial environments. Full article

Various TinyML models face a constantly challenging environment when running on emerging sixth-generation (6G) edge networks, with volatile wireless environments, limited computing power, and highly constrained energy use. This paper introduces DRL-TinyEdge, a latency- and energy-sensitive deep reinforcement learning (DRL) platform optimised for the 6G edge of adaptive TinyML. The suggested on-device DRL controller autonomously decides on the execution venue (local, partial, or cloud) and model configuration (depth, quantization, and frequency) in real time to trade off accuracy, latency, and power savings. To assure safety during adaptation to changing conditions, the multi-objective reward will be a combination of p95 latency, per-inference energy, preservation of accuracy and policy stability. The system is tested under two workloads representative of classical applications, including image classification (CIFAR-10) and sensor analytics in an industrial IoT system, on a low-power platform (ESP32, Jetson Nano) connected to a simulated 6G mmWave testbed. Findings indicate uniform improvements, with up to a 28 per cent decrease in p95 latency and a 43 per cent decrease in energy per inference, and with accuracy differences of less than 1 per cent compared to baseline models. DRL-TinyEdge offers better adaptability, stability, and scalability when using a CPU < 5 and a decision latency < 10 ms, compared to Static-Offload, Heuristic-QoS, or TinyNAS/QAT. Code, hyperparameter settings, and measurement programmes will also be published at the time of acceptance to enable reproducibility and open benchmarking. Full article

Background: Despite existing proteomics studies of other cell types, a comprehensive proteome of mesothelial cells has not been characterized. This study establishes a crucial baseline proteome for mesothelial cells to better understand their fundamental bioprocesses in healthy and injured states. Methods: Using mass spectrometry-based shotgun proteomics, we characterized the cellular fraction (CF) and conditioned medium (CM) proteomes of mesothelial cell line MeT-5A. The datasets were analyzed for Gene Ontology (GO) terms and canonical pathway enrichments to identify biological themes. Results: Our analysis identified 5087 protein groups, including 1532 shared proteins, 3122 unique to the CF and 433 exclusive to the CM. GO annotation revealed distinct functional enrichment profiles, reflecting the differing roles of intracellular and secreted proteins. While intracellular proteins were linked to core cellular functions, the extracellular proteome was enriched for signaling and cell-to-cell interaction pathways. The proteins shared by both compartments provided an integrated view of the molecular coordination between the cellular and extracellular environments. Conclusions: This study provides the first comprehensive baseline proteome for mesothelial cells and their secreted medium, offering a vital resource for future investigations into the mesothelium, particularly in the context of disease or injury. Full article

Background/Objectives: Klebsiella pneumoniae is a major Gram-negative pathogen associated with community-acquired pneumonia (CAP) and a critical contributor to antimicrobial resistance (AMR). Culture-based diagnostics remain the clinical standard but may underestimate microbial diversity and resistance gene profiles. This pilot study compared pathogen detection and antimicrobial resistance gene (ARG) repertoires in matched K. pneumoniae pure cultures and primary sputum samples using targeted next-generation sequencing (tNGS). Methods: We analyzed 153 sputum samples from patients with CAP. Among 48 culture-positive cases, 22 (14% overall; 54% culture-positive) yielded K. pneumoniae. MALDI-TOF MS, phenotypic drug susceptibility testing, and tNGS were conducted on both culture isolates and matched sputum specimens. Microbial composition, ARG diversity, and method concordance were evaluated, with focused analysis of discordant and fatal cases. Results: K. pneumoniae was detected in 14.4% of all CAP cases and accounted for 54.2% of culture-positive samples. Identification rates differed across methods: 35% by MALDI-TOF MS, 45% by culture tNGS, and 29% by sputum tNGS. Sputum tNGS revealed substantially higher microbial diversity than cultures (3.04 vs. 1.42 species per sample) and detected more than sixfold unique ARGs (38 vs. 7), including clinically relevant determinants that were absent from culture isolates. Concordance was high between MALDI-TOF MS and culture tNGS (κ = 0.712), but low between sputum and culture tNGS (κ = 0.279). Among twelve K. pneumoniae isolates included in AMR analysis, all showed resistance to β-lactams, and two-thirds exhibited MDR/XDR phenotypes. Genotypic screening identified seven ARGs, but major ESBL and carbapenemase genes were not detected, suggesting the presence of alternative resistance mechanisms. Overall, sputum tNGS provided additional etiological and resistome information not captured by cultivation and complemented classical diagnostics in CAP involving K. pneumoniae. Conclusions: Culture-based diagnostics and tNGS provide complementary insights into the detection and resistance profiling of K. pneumoniae in CAP, with sputum tNGS revealing broader microbial and resistome information than pure cultures, while classical methods remain essential for species confirmation and phenotypic AST. An integrated diagnostic approach combining both methodologies may improve pathogen detection, guide antimicrobial therapy, and enhance AMR surveillance in K. pneumoniae-associated CAP. Full article

Change-of-direction (COD) capacity is a key performance metric in football due to the high volume of COD actions occurring during match play. This study aimed to (i) evaluate the repeatability of the 5-0-5 test and (ii) examine the relationship between acceleration and deceleration profiles of the 5-0-5 test and in-season peak performance. Nineteen national-level Portuguese football players competing in the under-23 Portuguese National Championship were analysed. Repeatability analysis was conducted using intraclass correlation coefficients (ICC). Paired-samples t-tests and Pearson correlations (r) were employed to assess within-subject differences and associations between 5-0-5 measures (highest accelerations from a standing start [ACC_S], deceleration prior to the change in direction (DEC_COD), acceleration after decelerating and changing direction [ACC_COD]) and seasonal peak performances (ACC_max). The in-season peak values were determined from the average of the three maximal values that occurred either in training sessions or in matches. Normalized (relative to seasonal performance) parameters showed good repeatability (ICC = 0.76–0.85). The best ACC_COD and DEC_COD were not significantly different from ACC_max [ACC_COD] vs. ACC_max: (5.04 ± 0.39 m/s² vs. 5.36 ± 0.54 m/s²; p > 0.05) and DEC_max [DEC_COD] vs. DEC_max: (−6.47 ± 0.26 m/s² vs. −6.35 ± 0.61 m/s²; p > 0.05), respectively. The average and best 5-0-5 ACC_S performances showed significant, moderate correlations (r = 0.48; p = 0.040 and r = 0.50; p = 0.028, respectively) with the players’ peak in-season acceleration performance. Therefore, the best ACC_S and ACC_COD attempts can reflect values above 90% of ACC_max, while DEC_COD reflects values above 100% of DEC_max and may assist in monitoring and tailoring training for this capacity on an individual basis. Full article

Industrial Internet of Things (IIoT) deployments increasingly rely on low-cost microcontrollers and single-board computers to stream operational telemetry for monitoring, control, and predictive maintenance, yet the canonical “TLS-to-broker” model does not protect message content from a compromised or curious MQTT broker. This study therefore designs and implements a practical, application-layer end-to-end (E2E) encryption pipeline spanning an ESP32 data client (C++/mbedTLS), an untrusted MQTT broker, and a Raspberry Pi gateway (Python/PyCryptodome) using AES-256-GCM with Additional Authenticated Data (AAD). Sensor measurements are serialized as compact JSON, encrypted and authenticated on the ESP32, framed into a binary record, Base64-encoded for MQTT payload carriage, and verified/decrypted only at the gateway. Experiments on ESP32-WROOM-32 and Raspberry Pi 4 show an average ESP32 packet-preparation latency of 41.754 ms (JSON 1.0 ms; AES-GCM 29.5 ms; Base64 11.2 ms), robust rejection of ciphertext tampering and unauthorized devices via MAC verification and whitelist checks, and 99.72% decrypt-and-store success over a one-hour run (718/720 messages). These results indicate that commodity IIoT hardware can support practical and replicable E2E confidentiality and integrity without sacrificing operational throughput, while eliminating the MQTT broker as a de facto man-in-the-middle. Full article

Chagas disease remains a major public health challenge due to the limited effectiveness and considerable side effects of existing treatments, particularly during the chronic stage. Açaí (Euterpe oleracea) seeds have gained increasing attention as a source of bioactive compounds with potential therapeutic applications. In this study, hydroalcoholic extracts and solvent fractions obtained from açaí seeds were chemically characterized by ESI/MS and HPLC–MS/MS and evaluated for their cytotoxicity and antiparasitic activity against different developmental stages of Trypanosoma cruzi (Y strain). Chemical profiling revealed a predominance of phenolic compounds, particularly catechins and procyanidins, which were identified as major constituents of the hydroalcoholic extract and the ethyl acetate fraction. Cytotoxicity assays performed on murine peritoneal macrophages demonstrated low toxicity, with CC₅₀ values exceeding 500 µg/mL for most samples, indicating a favorable in vitro safety profile. Antiparasitic assays showed weak activity against epimastigote forms; however, significant inhibitory effects were observed against bloodstream trypomastigotes, cell culture-derived trypomastigotes, and intracellular amastigotes. Notably, the hydroalcoholic extract exhibited the highest selectivity against intracellular amastigotes, with a selectivity index greater than 10, fulfilling key criteria proposed by the Drugs for Neglected Diseases initiative (DNDi) for early-stage hit compounds. Flow cytometry analysis showed that both the hydroalcoholic extract and the ethyl acetate fraction induced parasite cell death through late apoptosis-like and necrosis. Together, these findings highlight the antiparasitic potential of E. oleracea seed extracts, particularly against clinically relevant stages of T. cruzi, and support further investigation of these bioproducts as promising candidates for the development of new therapeutic strategies for Chagas disease. Full article

Microbial volatile metabolites can enhance plant growth, yet the mechanisms by which plants perceive and transduce these signals are unknown. Growth of Arabidopsis thaliana Col-0 seedlings was found to be stimulated by volatiles from the soil bacterium Streptomyces coelicolor. To investigate volatile-responding candidate signaling molecules and genes, cultivation of seedlings in gas-phase contact with S. coelicolor genotypes was combined with GC-MS and plant transcriptomics. Components potentially involved were further studied using pure compounds and A. thaliana T-DNA mutants. Application of volatiles from S. coelicolor enhanced the growth of A. thaliana seedlings primarily by stimulating lateral root growth rate and inhibiting primary root extension. Concurrently, a family-wide induction of the Kelch-repeat F-box gene family KISS ME DEADLY (KMD) was observed. A. thaliana genotypes with a loss of function for the KMD family or other alterations of auxin/cytokinin signaling homeostasis suppressed the root response to both S. coelicolor total volatiles and the common microbial volatile 3-octanone. The results reveal a novel function of KMDs in mediating plant growth stimulation in response to volatile stimulation that alters auxin/cytokinin signaling and emphasize rhizospheric microbials as potential indicators of soil status to plants. Full article

Amazonian fruits are increasingly recognized for their functional properties due to their rich composition of bioactive metabolites. While species such as Euterpe oleracea Mart., Euterpe precatoria Mart., Mauritia flexuosa L., and Theobroma grandiflorum (Wild. ex Spreng.) have been extensively studied in countries like Brazil, research on these fruits in Colombia remains limited. This study aimed to characterize the secondary metabolites in freeze-dried pulp and seed samples of açaí, mirití, and cupuassu at different ripening stages, collected in Mitú (Vaupés, Colombia). Eleven samples of different fruits were collected and analyzed by untargeted metabolomics. Untargeted metabolomic profile was performed using LC-QTOF-MS and GC-QTOF-MS techniques. The pulp of M. flexuosa showed high concentrations of galacturonic acid. In T. grandiflorum, both pulp and seeds contained significant levels of galactose and citric acid. Notably, flavonoids such as fisetin and kaempferol-O-rutinoside were abundant in the pulp of E. oleracea and E. precatoria. Additionally, quinic acid and mannitol were detected in the unripe stages of Euterpe and Mauritia species. The diverse profile of secondary metabolites identified in these Colombian Amazonian fruits underscores their functional and nutritional potential. These findings support further exploration of native species for food, nutraceutical, and industrial applications, contributing to the valorization of Amazonian biodiversity. Full article