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PubMed2026

Factors associated with additional intervention requirement following ESWL in pediatric patients with urolithiasis.

OBJECTIVE: To identify predictors of additional intervention following extracorporeal shock wave lithotripsy (ESWL) in pediatric patients and to develop a clinically applicable predictive model. MATERIALS AND METHODS: This retrospective cohort study included 647 pediatric patients who underwent ESWL between 2015 and 2025. Demographic, clinical, and radiological variables were analyzed. Univariable and multivariable logistic regression analyses were performed to identify independent predictors of additional intervention. Model performance was evaluated using receiver operating characteristic curve analysis. RESULTS: Additional intervention was required in 65 patients (10.0%). On multivariable analysis, stone size 10-20 mm (OR: 3.04, p = 0.003), moderate (OR: 2.16, p = 0.049) and severe hydronephrosis (OR: 6.05, p < 0.001), and multiple stones (OR: 3.52, p = 0.030) were identified as independent risk factors. Increasing age (OR: 0.84, p = 0.026), history of urolithiasis (OR: 0.41, p = 0.006), and lower calyx location (OR: 0.14, p = 0.034) were associated with a reduced risk. The model demonstrated good discriminative performance (AUC: 0.794), with a sensitivity of 72% and specificity of 75%. Internal validation using bootstrap resampling demonstrated stable model performance, yielding a corrected AUC of 0.732. CONCLUSION: Stone burden, hydronephrosis severity, and stone multiplicity are key determinants of additional intervention after ESWL in pediatric patients. The proposed model shows good predictive performance and may support individualized risk stratification and clinical decision-making.

Humans↗

PubMed2026

Transcriptomic analysis provides molecular insights into the innate immune defense of Mactra veneriformis against Vibrio alginolyticus infection.

Mactra veneriformis is an economically important bivalve mollusc in China, but its aquaculture is frequently threatened by Vibrio infections, particularly Vibrio alginolyticus. To investigate the molecular immune response of M. veneriformis to V. alginolyticus, we performed RNA-seq analysis of hepatopancreatic tissues collected at 48 h post-infection, the peak mortality time point, with PBS-injected individuals used as controls. Infection with V. alginolyticus caused severe histopathological damage in the hepatopancreas and resulted in a cumulative mortality of 53.3% over 14 d, compared with 3.3% in the control group. Transcriptomic analysis identified 2623 differentially expressed genes (DEGs), including 1585 significantly up-regulated genes and 1038 down-regulated genes. KEGG enrichment analysis demonstrated that DEGs were significantly enriched in immune related and metabolism pathways, including the JAK-STAT signaling pathway, RIG-I-like receptor (RLR) signaling pathway, and cytochrome P450 (CYP450) signaling pathway. Collectively, these findings revealed candidate immune related genes (tlr3, tlr5, myd88, nfkb1, il-17d, and ifi44l), a putative TLR-MyD88-NF-κB signaling axis, and KEGG signaling pathways, including JAK-STAT, RLR and CYP450, that may be involved in the innate immune response of M. veneriformis to V. alginolyticus infection. These results provide a transcriptomic basis for understanding host-pathogen interactions in this species and highlight candidate genes and pathways for future functional validation and potential application in disease-resistance breeding.

Animals↗

PubMed2026

Mechanisms linking the gut microbiota to colorectal cancer development and progression.

Colorectal cancer remains a leading cause of global cancer mortality, with a concerning rise in early-onset cases driven by complex interactions between environmental exposures, lifestyle factors, and host genetics. Mounting evidence indicates that gut microbiota dysbiosis critically modulates this oncogenic process, acting as an active participant rather than a passive bystander. This review systematically synthesizes the dichotomous roles of the intestinal microbiome in colorectal tumorigenesis through the conceptual framework of the driver-passenger model. We discuss how early initiating driver bacteria, such as Polyketide synthase-positive Escherichia coli and enterotoxigenic Bacteroides fragilis, compromise mucosal barriers, induce chronic mucosal inflammation, and inflict direct genomic instability. As the local tumor microenvironment undergoes profound metabolic remodeling, opportunistic passenger pathogens, notably Fusobacterium nucleatum, become enriched, further promoting cellular proliferation and facilitating tumor immune evasion. Conversely, protective commensals, exemplified by Clostridium butyricum and Streptococcus thermophilus, exert robust tumor-suppressive effects through multifaceted mechanisms. These beneficial microbes actively antagonize malignant progression by redirecting tumor metabolic fluxes toward oxidative stress, orchestrating deep epigenetic reprogramming, and degrading core oncoproteins to reverse chemoresistance. Transitioning from fundamental mechanisms to clinical application, we evaluate a comprehensive spectrum of microbiota-targeted interventions, encompassing non-invasive diagnostic biomarkers, fecal microbiota transplantation, engineered bacteria, phage therapy, and postbiotics. Finally, we critically address the formidable translational challenges associated with microbial heterogeneity, long-term safety, and regulatory standardization, aiming to provide a balanced perspective on integrating microbiome-based strategies into next-generation precision oncology for colorectal cancer.

Humans↗

PubMed2026

Artificial intelligence for dental caries detection: An umbrella review.

Artificial intelligence (AI) has been proposed as a tool to improve dental caries detection across imaging modalities; however, its clinical value remains uncertain. This umbrella review aimed to synthesize and critically appraise systematic reviews evaluating AI for caries detection and diagnosis. An umbrella review was conducted following PRIOR guidance (PROSPERO CRD420261340728). Searches were performed in MEDLINE, Embase, Scopus, Web of Science, and Google Scholar up to 15 March 2026. Methodological quality was assessed using AMSTAR 2, and overlap of primary studies was quantified using the corrected covered area (CCA). Seventeen systematic reviews were included, of which five reported diagnostic test accuracy meta-analyses using bivariate or HSROC models. Across these meta-analyses, pooled sensitivity ranged from 0.76 to 0.94 and specificity from 0.85 to 0.91. Most systems were based on deep learning models applied to bitewing radiographs and intraoral photographs. However, substantial heterogeneity was observed in imaging modalities, lesion thresholds, analytical tasks, and evaluation metrics. In addition, a high degree of overlap across reviews and recurrent methodological limitations, including reliance on retrospective datasets, limited external validation, and inconsistent reporting, substantially weaken the reliability of the evidence. Although AI models demonstrate high diagnostic performance under experimental conditions, current evidence does not support their use as stand-alone diagnostic tools. Their clinical applicability remains limited, and implementation should be restricted to decision-support contexts until robust prospective validation demonstrates meaningful impact on clinical decision-making and patient outcomes.

Dental Caries↗

PubMed2026

Infra-low-frequency neurofeedback alters EEG network efficiency: exploratory evidence from healthy volunteers.

Infra-Low-Frequency Neurofeedback (ILF-NFB) combines classic frequency-band (FB) and infra-low-frequency (ILF) EEG components in implicit training protocols and is increasingly applied in clinical contexts. Yet, the neurophysiological mechanisms underlying ILF-NFB remain to be further elucidated. In this randomized, sham-controlled and double-blind study, we explored the online impact of a one-session ILF-NFB application on EEG correlates in healthy participants (39 analyzed datasets). Continuous 31-channel EEG was recorded during verum and sham feedback in a double-blind, randomized crossover design. In this exploratory analysis approach, functional connectivity was estimated using the debiased weighted phase-lag index (dwPLI) and analyzed with graph-theoretical measures. The results revealed higher global efficiency during verum compared to sham in the Beta1 band (12-15 Hz), reaching significance in the primary comparison but not surviving Bonferroni correction across the five tested bands; block-wise follow-ups showed a significant verum-sham difference in the first half of the neurofeedback session and a directionally consistent pattern in the second half. The Condition × Block interaction was not significant. No consistent differences were observed in other frequency bands, nor for betweenness centrality. While preliminary, these exploratory results point to possible network-level effects during ILF-NFB and motivate further confirmatory work in extended training protocols and clinical populations.

Humans↗

PubMed2026

Mitigating pH-induced instability in deruxtecan-based ADCs: an onboard-mixing icIEF approach for robust charge heterogeneity characterization.

Accurate charge variant analysis of antibody-drug conjugates (ADCs) is essential for understanding product heterogeneity and ensuring quality control. However, Deruxtecan (DXd)-based ADCs present a unique analytical challenge due to the intrinsic instability of the payload, where the lactone ring readily undergoes hydrolysis under alkaline conditions, resulting in time-dependent shifts in charge distribution during imaged capillary isoelectric focusing (icIEF). In this study, we describe the development of an onboard-mixing icIEF method designed to minimize pH-induced degradation during sample preparation. By separating ADC samples from carrier ampholytes (CAs) prior to injection and enabling real-time mixing within the instrument, this approach effectively suppresses premature lactone ring opening and stabilizes charge variant profiles. Comparative studies between conventional premixing and onboard-mixing approach demonstrated that the latter significantly enhances reproducibility, particularly for acidic variants that are highly sensitive to structural conversion. Comprehensive method validation confirmed excellent precision, linearity, and sensitivity, with consistent performance across run-to-run and intra-day analyses. The results underscore the importance of controlling microenvironmental pH exposure in the analysis of chemically instable ADCs. The proposed onboard-mixing strategy provides a robust and efficient solution for icIEF-based characterization, reducing analytical artifacts while simplifying method development. This approach is broadly applicable to ADCs and other biotherapeutics containing pH-sensitive functional groups.

Hydrogen-Ion Concentration↗

PubMed2026

Genome-wide identification and expression profiling of CSP and OBP genes in Stictocephala bisonia reveals candidate genes potentially associated with insecticide response.

Stictocephala bisonia is an important invasive agricultural pest. Due to the frequent application of insecticides in its habitat, this species is under intense selection pressure. Chemosensory proteins (CSPs) and odorant-binding proteins (OBPs) are known to play key roles in insecticide resistance, but their specific functions in S. bisonia remain unclear. In this study, we identified a total of 22 SbisCSPs and 16 SbisOBPs based on the S. bisonia genome. To screen for candidate genes potentially linked to insecticide resistance, we adopted a multi-criteria screening strategy that integrated phylogenetic analysis, molecular docking with three insecticides, and tissue-specific expression profiling. Phylogenetic analysis identified several SbisCSPs and SbisOBPs clustering with genes known to be involved in insecticide resistance, serving as an initial evolutionary filter. Molecular docking results indicated that λ-Cyhalothrin exhibited the strong predicted binding affinity with most of SbisCSPs and SbisOBPs. Subsequent qPCR validation of seven prioritized candidates revealed distinct expression patterns: SbisCSP22 was highly expressed in adults and demonstrated strong binding affinity to all three insecticides tested, suggesting a potential role in mediating multi-insecticide response. Conversely, SbisCSP17 was significantly upregulated in larvae, clustered with genes known to mediate imidacloprid resistance, and exhibited strong binding affinity to imidacloprid. Given its larval-specific expression and the soil-dwelling behavior of larvae, we hypothesize that SbisCSP17 is a key candidate gene for larvae coping with soil-treated insecticides.

Animals↗

PubMed2026

Enrichment of Lysobacter in a long-term organically managed agricultural field with low soilborne disease incidence.

Disease-suppressive soils, in which soilborne pathogens are naturally suppressed, offer a promising model for sustainable crop protection, particularly in organic farming systems where chemical disease control options are limited. Although disease suppression in these soils is considered to rely on biological control, the underlying mechanisms remain poorly understood. In this study, we investigated soil from a long-term organically managed field in Shiga Prefecture, Japan, where soilborne disease incidence has remained consistently low, to identify bacterial community features potentially associated with this field. The 16S rRNA gene amplicon sequencing indicated that this soil harbored a bacterial community distinct from those of nearby agricultural soils. Following the application of organic compounds, the genus Lysobacter, a taxon with known antagonistic activity against plant pathogens, was markedly enriched in response to proteinaceous organic inputs. This enrichment was consistent across sampling times and specific to certain proteinaceous organic inputs, whereas minimal effects were observed on chitin, N-acetyl-d-glucosamine, or cysteine. Broader soil surveys indicated that Lysobacter enrichment was not strictly associated with whether soils had been managed under organic or conventional farming practices. Stepwise multiple regression analysis identified 10 co-occurring bacterial genera that were strongly associated with Lysobacter abundance. These findings highlight condition-dependent Lysobacter enrichment as a characteristic microbial response to proteinaceous organic amendments in this low-disease-incidence field and provide microbial insights that may inform microbiome-based strategies for sustainable soil management.

Lysobacter↗

PubMed2026

Protein isolation markedly enhances in vitro digestibility, nutritional quality, and bioactivity of fungal mycelial proteins.

Fungal mycelial proteins are promising sustainable protein sources, yet their nutritional utilization is often limited by structural constraints. This study systematically evaluated the effects of protein isolation on the proteomic composition, gastrointestinal digestion behavior, amino acid utilization, and bioactivity of Pleurotus citrinopileatus mycelial proteins. Quantitative proteomics identified 3591 proteins, of which 3374 were shared between mycelial flour (PCMF) and protein isolate (PCMPI), indicating that PCMPI primarily represents the soluble proteome fraction. In vitro digestion revealed that PCMPI exhibited significantly higher digestibility (93.98%) than PCMF (42.98%) (p < 0.05), reaching levels comparable to whey protein isolate. Enhanced enzymatic accessibility in PCMPI promoted rapid peptide generation during the gastric phase and efficient amino acid release during the intestinal phase, resulting in higher peptide (634.76 mg/g) and free amino acid levels (341.69 mg/g) at the digestion endpoint. Consequently, PCMPI achieved a balanced amino acid profile with a PDCAAS of 1.0. Moreover, its digestion products exhibited stronger antioxidant activity (IC₅₀ = 8.36 mg/mL) and ACE inhibitory activity (IC₅₀ = 15.65 mg/mL) compared with PCMF. Mechanistically, protein isolation disrupted the cell wall matrix, shifting digestion from a structure-limited to an accessibility-driven regime. Collectively, these findings demonstrate that protein isolation markedly enhances the digestibility, nutritional quality, and functional potential of mycelial proteins, supporting their application as high-value sustainable protein ingredients.

Digestion↗

PubMed2026

Efficacy of current approaches to non-invasive diagnosis of skin cancer and the potential impact of artificial intelligence: A systematic review and meta-analysis.

BACKGROUND: Skin cancer is one of the most prevalent malignancies worldwide, particularly within Caucasian populations. This systematic review and meta-analysis aimed to quantitatively review the current literature on non-invasive diagnosis of skin cancer and evaluate the current evidence to support the use of tools in addition to, or in replacement of clinician face-to-face assessment. METHODS: A literature search was conducted for publications in PubMed, Medline and Embase databases. Articles describing accuracy, sensitivity, specificity and outcomes of their mode of assessment were included. A total of 208 articles met the inclusion criteria. RESULTS AND CONCLUSION: This systematic review and meta-analysis showed that the diagnostic performance of artificial intelligence (AI) in the interpretation of dermatoscopic images was high for melanoma diagnosis, basal cell carcinoma or malignancy, in comparison to dermatoscopic assessment alone by clinicians and experts. Although AI interpretation of images demonstrated higher sensitivity for melanoma diagnosis in comparison to clinical assessment combined with dermatoscopic assessment, it is unclear if this is also the case for basal cell carcinoma and squamous cell carcinoma diagnosis. Reflectance confocal microscopy, a non-invasive high resolution imaging technique, is known to have a high sensitivity for diagnosing cutaneous malignancy, and this may have applications within secondary care. Therefore, AI could help reduce resource burden and aid in clinical assessment, particularly within primary care settings.

Humans↗

PubMed2026

Bioprospecting microbial genomes to expand the biocatalytic toolbox of rubber oxygenases.

A set of rubber oxygenases was discovered through phylogenetic analysis and AI-based structural modeling of complexes of the putative enzymes with a substrate mimicking cis-1,4-polyisoprene. Sixteen candidate proteins were selected from thermophilic microorganisms, all sequence-related to the Latex clearing protein from Streptomyces sp. K30 (LcpK30). Sequence truncation and solubility tags were then evaluated to enhance protein expression, with the SUMO tag proving to be the most effective. Including LcpK30, nine heme-containing oxygenases were successfully expressed in E. coli NEB 10-beta cells, purified (35-157 mg L-1 yield) and characterized. Steady-state kinetics revealed significant rubber latex-degrading properties for six of them, with the truncated SUMO-fused LcpK30 (SUMO-LcpK30T) showing activity in agreement with literature. Notably, the catalytic efficiencies of all the expressed homologs lay within one order of magnitude and the oxygenase from Thermomonospora echinospora was found to be particularly promising in terms of activity, especially at high latex concentrations (more than 1% w/v). The analysis of reaction mixtures by both HPLC and HPLC-MS confirmed the oxidation of cis-1,4-polyisoprene to form the expected isoprenoid oligomers (n = 2-12), whose distribution was consistent with the usual endo-type cleavage pattern in all but one case. This bioprospecting effort afforded a platform of new rubber-degrading enzymes with diverse efficiencies and product profiles, capable of adapting to targeted applications.

Oxygenases↗

PubMed2026

Seed-derived mucilage polysaccharides as biomaterials for in vivo tissue regeneration: A systematic review.

Chronic wounds, bone defects, and cartilage injuries represent persistent clinical challenges requiring biomaterial platforms that actively regulate inflammation, oxidative stress, angiogenesis, and extracellular matrix remodeling. Conventional synthetic dressings often provide limited biological activity in these contexts. Seed-derived mucilages - polysaccharide-rich hydrocolloids obtained from chia (Salvia hispanica), flaxseed (Linum usitatissimum), fenugreek (Trigonella foenum-graecum), psyllium (Plantago ovata), guar (Cyamopsis tetragonoloba), quince (Cydonia oblonga) etc. - have emerged as biocompatible, biodegradable, and chemically versatile platforms for tissue engineering. This systematic review, conducted according to PRISMA 2020 guidelines, synthesized in vivo evidence on seed-derived mucilage-based biomaterials across wound healing, bone repair, cartilage regeneration, and related applications. PubMed, Scopus, and Web of Science Core Collection were searched for original in vivo experimental studies published in English between 2020 and 2026. Eligible studies reported at least one measurable regenerative outcome. Data were extracted independently by two reviewers, and methodological quality was assessed using the SYRCLE Risk of Bias tool. Forty-three studies were included. Hydrogels were the dominant biomaterial format, followed by films, scaffolds, sponges, nanoparticle systems, and bilayer or Janus composites. Included systems generally improved wound closure, re-epithelialization, collagen deposition, angiogenesis, antioxidant defense, and inflammatory regulation. However, most studies used small animals with short follow-up periods, and many incorporated nanoparticles or bioactive agents, limiting attribution of efficacy to the mucilage matrix alone. Risk of bias was predominantly unclear due to insufficient reporting of randomization and blinding. Blank mucilage controls, standardized characterization, long-term biosafety data, and clinically relevant models are essential prerequisites for translational progress.

Humans↗

PubMed2026

Systematic modular engineering of genome-integrated Escherichia coli MG1655 for high-level 2'-fucosyllactose production.

2'-Fucosyllactose (2'-FL), the most abundant human milk oligosaccharide (HMO), has attracted considerable interest for its prebiotic and immunomodulatory functions, with broad applications in infant nutrition. In this study, we report the development of a high-yield, genome-integrated 2'-FL-producing strain based on Escherichia coli MG1655 through systematic modular optimization. Starting from a single-copy BKHT strain (MGC06), we first optimized the copy number of the α-1,2-fucosyltransferase (α-1,2-FT) gene BKHT. Subsequently, the GDP-L-fucose supply was enhanced through coordinated genomic integration of the gene clusters cpsG-cpsB and gmd-fcl, while the multidrug efflux transporter gene mdfA was integrated to improve product export and strain robustness. BKHT copy number was then re-evaluated in the optimized background, with four copies yielding the highest production. The final engineered strain, harboring all genetic modifications stably integrated into the chromosome, produced 17.18 g/L 2'-FL in shake-flask culture. In fed-batch fermentation using a 5-L bioreactor, this strain achieved a titer of 154.12 g/L after 60 h, with a productivity of 2.57 g/L/h. Notably, throughout the entire fermentation process, no antibiotics or inducers were supplemented, underscoring the genetic stability and regulatory compliance of this plasmid-free system. To our knowledge, this represents the highest 2'-FL titer reported to date, positioning our engineered strain as a promising candidate for commercial 2'-FL production.

Escherichia coli↗

PubMed2026

Comparative transcriptome analysis provides insights into dorso-ventral color pattern formation of Holothuria edulis.

Animal body color patterns are highly diverse and play critical roles in camouflage, intraspecific communication, and environmental adaptation. Holothuria edulis, an important echinoderm inhabiting tropical waters, exhibits a typical dorsoventral dichromatism. This unique body color difference represents a key phenotypic trait for its habitat adaptation; however, the core differential genes regulating this trait remain to be elucidated. In this study, comparative transcriptome sequencing was performed on the dorsal and ventral body wall tissues of H. edulis, leading to the identification of a number of differentially expressed genes (DEGs), followed by GO functional annotation and KEGG pathway enrichment analysis. GO enrichment analysis indicated that the DEGs were significantly enriched in functional categories such as extracellular region, peptidase inhibitor activity, and tetrapyrrole binding. KEGG pathway analysis further revealed significant enrichment of protein digestion and absorption, the TNF signaling pathway, and cholesterol metabolism. Notably, the pigmentation-related gene FMO2 was highly expressed in the dorsal body wall tissue, whereas cyp1a1, ZIC1, Slc7a11, WNT-1, and ADAMTS20 were highly expressed in the ventral body wall tissue. This study identified DEGs and enriched pathways associated with dorsoventral body color differences in H. edulis, providing new insights into the molecular regulatory mechanisms underlying body color pattern formation. From the perspective of aquaculture applications, body color is one of the important traits affecting the quality and market value of sea cucumber products. Elucidating the molecular mechanisms of body color variation can provide a scientific basis for molecular marker-assisted breeding of superior sea cucumber variety.

Animals↗

PubMed2026

Comprehensive source-risk assessment of organophosphate esters in surface water of the Dianchi Lake Basin, Yunnan, China.

Organophosphate esters (OPEs), widely used as flame retardants and plasticizers, have been increasingly detected in aquatic environments. However, investigations of their distribution in high-altitude plateau lakes remain scarce. Identifying and quantifying the sources and associated risks of OPEs are crucial for subsequent water environment management. In this study, an integrated source-risk analysis approach was employed by combining the Positive Matrix Factorization (PMF) model, the Geodetector (GD) model, and risk quotient (RQ). Analysis of 14 OPEs in surface waters of the Dianchi Lake Basin (DLB) revealed 12 detectable compounds, with total OPEs concentrations (ΣOPEs) ranging from not detected (ND)-64.6 ng/L during the wet season and ND-35.8 ng/L during the dry season. Elevated ΣOPEs were primarily observed at inflow sites in the northern part of the lake and in urban rivers. Source apportionment indicated four major contributing sources: agricultural films containing flame-retardant and plasticizer additives, traffic-related particulate emissions, releases from household and personal care products, and industrial production and applications of flame retardants in plastics, electronics, and related products (the predominant source). The ecological impact caused by OPEs ranges from no risk to low risk, with tris(2-chloroethyl) phosphate emitted from industrial source being the primary driver of potential environmental risk. These findings highlight the necessity of prioritizing industrial sources in future management strategies. Overall, this study provides a methodological framework for source apportionment and risk assessment of OPEs and offers scientific evidence to support environmental management of OPEs in the DLB.

Environmental Monitoring↗

PubMed2026

Decoding the spatiotemporal patterns of food spoilage microbial communities: Integrating multi-omics and artificial intelligence to enable precision preservation.

In the global food supply chain, food wastage caused by spoilage has resulted in significant economic losses, food shortages, and environmental pressure. This process is fundamentally driven by the spatiotemporal dynamics of microbial communities. However, traditional research methods struggle to elucidate the complex mechanisms of spatial heterogeneity, interspecies interactions, and functional succession. This limits the development of effective preservation strategies. This review systematically reviews the cutting-edge progress of integrating multi-omics technologies and artificial intelligence (AI) to study food spoilage microbial communities, breaking through this bottleneck. We propose an intelligent theoretical framework that could potentially analyze microbial metabolic activities and predict dynamic shelf life if implemented. The conceptual framework integrates multidimensional data, including spatial metabolomics, temporal metatranscriptomics, single-cell transcriptomics, and longitudinal metagenomics. It can also be combined with AI models, such as graph neural networks. The article elaborates on the principles and applications of spatio-temporal monitoring technologies, such as nano secondary ion mass spectrometry, hyperspectral imaging, and the Internet of Things sensing. Through illustrative cases of typical perishable foods, it also explores how such a multi-omics - AI system might be applied to spoilage warning and precise intervention. Additionally, the article addresses the current challenges in data coverage, model generalization, and federated learning implementation. Then the research further explores emerging areas such as engineered probiotics, edge AI, and microfluidic sensing. These areas are targeted at transforming food preservation from an empirical control approach to a data-driven, precise regulatory framework. This transformation provides theoretical support and technical approaches for developing a smart, sustainable food preservation system.

Multiomics↗

PubMed2026

Nimodipine in animal models of demyelination relevant to multiple sclerosis: a systematic review.

BACKGROUND: Multiple sclerosis (MS) is the most common inflammatory neurodegenerative disease in which axonal injury, neuronal death, and demyelination occur. Treatment for MS relapses remains limited, which alleviates acute loss of function but has no impact on long-term disability. This study aimed to perform a systematic review of the effects of nimodipine on experimental demyelination models, including experimental autoimmune encephalomyelitis (EAE) and Cuprizone models in rodents. METHODS: This study was conducted following the PRISMA statement. A systematic search was performed in PubMed, Scopus, the Cochrane Library, and Google Scholar. The primary outcome was EAE clinical disease severity (peak clinical score and/or cumulative disease burden). Secondary outcomes included relapse activity (when reported), histological myelin outcomes, oligodendrocyte lineage markers, neuroaxonal injury markers, and inflammatory readouts. Risk of bias was assessed using the SYRCLE tool. RESULTS: Out of 4660 results, 5 studies were included in the systematic review (four EAE studies and one cuprizone model). Nimodipine was administered using heterogeneous regimens (oral, intravenous, intraperitoneal, subcutaneous, or osmotic pump delivery; 1-30 mg/kg/day). The included studies reported the variable effects of nimodipine on relapse-related outcomes, myelination, inflammatory processes, and neuroprotection in the EAE model of MS. Across EAE studies, nimodipine generally reduced clinical disease severity or cumulative burden, although relapse-related outcomes were inconsistent. CONCLUSIONS: Preclinical evidence suggests that nimodipine may attenuate disease severity and demyelination and may promote repair-related processes in rodent models relevant to MS. However, to evaluate the clinical applicability of nimodipine in MS patients, well-powered, transparently reported preclinical replication and early-phase clinical studies are required before clinical translation.

Animals↗

PubMed2025

UV-based homogeneous disinfection process for removal of antibiotic resistance genes: Efficiency, mechanisms and influencing factors.

The proliferation and dissemination of antibiotic resistance genes (ARGs) in aquatic environments pose a serious threat to global public health. Ultraviolet-driven homogeneous advanced oxidation processes (UV-AOPs) represent a prospective suite of technologies for the efficient removal of ARGs. This review critically assesses recent advances in the application of UV-AOPs, specifically UV/hydrogen peroxide (UV/H2O2), UV/peracetic acid (UV/PAA), UV/persulfate (UV/PS), and UV/chlorine (UV/Cl), for the elimination of extracellular ARGs and intracellular ARGs. The underlying mechanisms involve direct ultraviolet-induced DNA damage, including pyrimidine dimer formation and strand breakage, as well as oxidation mediated by radicals such as hydroxyl radicals, sulfate radicals, carbon-centered radicals, and reactive chlorine species. The relative contribution of radical and non-radical pathways is strongly influenced by water chemistry and process conditions. We further expound on the critical operational and environmental factors governing ARG removal kinetics, including UV wavelength and fluence, oxidant type and dosage, ARG sequence characteristics, pH, ubiquitous anions, and dissolved organic matter, which collectively affect radical generation, quenching, and reaction microenvironments. Notably, for i-ARGs, UV-AOPs facilitate degradation not only through direct radical attack but also by disrupting cellular integrity and permeabilizing membranes, thereby enhancing the exposure of genetic materials to oxidative and photolytic damage. This review synthesizes current understanding to provide a mechanistic basis for the design and optimization of UV-AOP systems, highlighting their potential as effective barriers against the dissemination of antibiotic resistance in water reuse and purification scenarios.

Disinfection↗