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Evolutionary characterization and expression profiling of ACC and FASN genes in Chinese mitten crab Eriocheir sinensis.

Acetyl-CoA carboxylase (ACC) and fatty acid synthase (FASN) are rate-limiting enzymes in the fatty acid biosynthetic pathway, yet their evolutionary relationships, sequence features, and expression profiles remain poorly understood in crustaceans, particularly in the economically important Chinese mitten crab (Eriocheir sinensis). Here, we identified and systematically analyzed ACC and FASN genes in E. sinensis using comparative genomic analyses across 43 species. ACC was highly conserved as a single-copy gene in invertebrates, in contrast to the multiple paralogs observed in vertebrates. Similarly, FASN was generally maintained as a single-copy gene across most taxa but exhibited lineage-specific expansion in certain insect groups. Phylogenetic and structural analysis revealed strong conservation of both genes within crustaceans, supported by multiple conserved motifs and canonical functional domains. Expression profiling showed predominant expression in the hepatopancreas and midgut, suggesting their potential involvement in crustacean lipid metabolism. During the molting cycle, ACC and FASN exhibited higher expression levels during stages C and D, suggesting an increased capacity for fatty acid biosynthesis before molting. In addition, dietary lipid levels experiment revealed that ACC and FASN expression responded dynamically to dietary lipid availability, with increased expression at moderate lipid levels but reduced expression under excessive lipid supplementation, indicating a possible adaptive transcriptional response to lipid status. Collectively, this study provides insights into the evolutionary conservation and expression dynamics of ACC and FASN and improves our understanding of lipid metabolic adaptation in crustaceans.

Animals

Modelling the effects of biological intervention in a dynamical gene network.

Cellular response to environmental and internal signals can be modeled by dynamical gene regulatory networks (GRN). In the literature, three main classes of gene network models can be distinguished: (1) non-quantitative (or data-based) models which do not describe the probability distribution of gene expressions; (2) quantitative models which fully describe the probability distribution of all genes co-expression; and (3) mechanistic models which allow for a causal interpretation of gene interactions. We propose two rigorous frameworks to model gene alteration in a dynamical GRN, depending on whether the network model is quantitative or mechanistic. We explain how these models can be used for design of experiment, or, if additional alteration data are available, for validation purposes or to improve the parameter estimation of the original model. We apply these methods to the Gaussian graphical model, which is quantitative but non-mechanistic, and to mechanistic models of Bayesian networks and penalized linear regression.

Gene Regulatory Networks

A Phase I Study Assessing the Safety, Tolerability, and Pharmacokinetics of Yinfenidone: A Novel, Potent Drug for Idiopathic Pulmonary Fibrosis Treatment in Healthy Chinese Subjects.

PURPOSE: Idiopathic pulmonary fibrosis (IPF) is a fatal interstitial lung disease with a median survival of only 2-3 years after diagnosis. Yinfenidone (HEC585) possesses the potential to inhibit the proliferation of pulmonary fibroblasts, making it a promising candidate for the treatment of IPF. This study assessed the safety, tolerability, pharmacokinetics, and metabolic profile of Yinfenidone hydrochloride capsule in healthy Chinese subjects. METHODS: This single-center, randomized, double-blind, placebo-controlled, single ascending-dose trial included seven dose groups(20, 50, 100, 200, 400, 600, and 800 mg). Each group enrolled8 healthy subjects: 6 received Yinfenidone hydrochloride capsules and 2 received matching placebo under fasting conditions. Serial pharmacokinetic (PK) blood samples were collected pre-dose and post-dose, liquid chromatography-tandem mass spectrometry was used to analyze the plasma concentrations of Yinfenidone. Additionally, metabolic biotransformation of Yinfenidone in plasma were conducted in the 100 mg dose group. Safety and tolerability endpoints were monitored via physical examinations, vital signs measurements, clinical laboratory tests, 12-lead electrocardiography (ECG), and adverse events (AEs) documentation throughout the trial. FINDINGS: Yinfenidone was rapidly absorbed, with a median maximum plasma concentration (Tmax) of 1.8-3.0 hours, and had a mean half-life (t1/2) ranging from 31.9 to 62.0 hours. Within the 20-100 mg dose range, systemic drug exposure generally increased with ascending dose, above 100 mg, exposure increased less than proportionally to dose. Metabolite profiling in the 100 mg group revealed that the parentcompound predominated in plasma, with metabolic pathways including mono-oxygenation and N-dealkylation. All reported AEswere mild, classified as Common Terminology Criteria for Adverse Events (CTCAE) version 4.03 grade 1. No serious AEs observed; no subject discontinued the trial due to AEs. Single oral doses of 20-800 mg Yinfenidone hydrochloride capsules administered under fasting conditions demonstrated favorable safety and tolerability profiles in healthy Chinese subjects. IMPLICATIONS: Yinfenidone exhibited rapid absorption (median Tmax, 1.8-3.0 hours) and a long terminal t1/2 ranging from 31.9 to 62.0 hours in this single ascending-dose study, indicating that Yinfenidone can be taken once a day in subsequent clinical studies. Yinfenidone mainly exists in human plasma as the original drug and is metabolized through a variety of metabolic pathways. The AEs observed with Yinfenidone in this study, such as diarrhea, nausea, and dizziness, were similar to those reported with pirfenidone. Overall, Yinfenidone demonstrated a favorable safety and tolerability profile in this cohort of healthy subjects.

Adult

PaNDA: Efficient Optimization of Phylogenetic Diversity in Networks.

Phylogenetic diversity (PD) plays an important role in biodiversity, conservation, and evolutionary studies by measuring the diversity of a set of taxa based on their phylogenetic relationships. In phylogenetic trees, a subset of k taxa with maximum PD can be found by a simple and efficient greedy algorithm. However, this algorithmic tractability is lost when considering phylogenetic networks, which incorporate reticulate evolutionary events such as hybridization and horizontal gene transfer. To address this challenge, we introduce PaNDA (Phylogenetic Network Diversity Algorithms), the first software package and interactive graphical user-interface for exploring, visualizing, and maximizing diversity in phylogenetic networks. PaNDA includes a novel algorithm to find a subset of k taxa with maximum diversity, running in polynomial time for networks of bounded scanwidth, a measure of tree-likeness of a network that grows slower than the well-known level measure. This algorithm considers the variant of PD on networks in which the branch lengths of all paths from the root to the selected taxa contribute towards their diversity. We demonstrate the scalability of this algorithm on simulated networks, successfully analyzing level-15 networks with up to 200 taxa in seconds. We also provide a proof-of-concept analysis using a phylogenetic network on Xiphophorus species, illustrating how the tool can support diversity studies based on real genomic data. The software is easily installable and freely available at https://github.com/nholtgrefe/panda. Additionally, we extend the definition of PD to semi-directed phylogenetic networks, which are mixed graphs increasingly used in phylogenetic analysis to model uncertainty of the root location. We prove that finding a subset of k taxa with maximum diversity remains NP-hard on semi-directed networks, but do present a polynomial-time algorithm for networks with bounded level.

network

Cooperative anaerobic catabolism of chlorinated organic compounds: implications for sustainable bioremediation.

Biodegradation research historically followed a reductionist approach focused on axenic (pure) cultures capable of catabolizing the specific contaminant(s) of interest. While this approach has substantially advanced our understanding of the microbiology, physiology, biochemistry, and genetics of contaminant degradation under laboratory conditions, it does not capture the complexity of natural and engineered environments. During in situ bioremediation, microbiomes are exposed to mixtures of contaminants, and microbial interactions profoundly influence contaminant transformation and fate. In anoxic environments, degradation of chlorinated compounds is often sustained by metabolic cooperation among taxonomically and physiologically distinct microorganisms. Through the exchange of metabolites such as hydrogen, formate, acetate, and other nutrients, microbial populations establish interdependent networks that overcome thermodynamic and physiological constraints, enabling self-sustaining systems of contaminant transformations that would be inefficient or impossible with individual organisms. We highlight examples of microbial interactions that underpin anaerobic catabolism of chlorinated contaminants, including systems resulting in self-sustained anaerobic bioremediation.

Biodegradation, Environmental

Ecr positively regulates activity of the PhoQ/PhoP signalling system in Klebsiella pneumoniae.

BACKGROUND: The rising prevalence of polymyxin resistance in multidrug-resistant Klebsiella pneumoniae presents a critical situation with limited therapeutic options. METHODS: Methods Genomic sequencing of 15 clinical polymyxin-resistant K. pneumoniae strains with multidrug resistance revealed that MgrB inactivation, predominantly disrupted by insertion sequences (ISs) in the IS1, IS4, and IS5 families, was the leading cause of polymyxin resistance. Comparative transcriptomics of wild-type, ΔmgrB, and ΔmgrBΔphoP were performed to elucidate the MgrB-PhoPQ regulatory network. RESULTS: This study conducted a system-wide analysis of the regulatory network and identified a species-specific PhoPQ regulon in K. pneumoniae.Beyond the classical MgrB-PhoPQ-ArnBCADTEF pathway, we identified a previously unannotated PhoPQ-regulated gene, 144 bp LN739_RS09850, encoding an Ecr homologue from Enterobacter cloacae. This protein has been reported to confer colistin heteroresistance, with the underlying mechanism not yet functionally validated. This study revealed that overexpression of Ecr homologues decreased colistin susceptibility in both K. pneumoniae and E. cloacae, but this phenotype was abolished upon phoP deletion, confirming PhoP's essential role. Consistent with this dependency, comparative transcriptomics of Ecr-overexpressing K. pneumoniae vs. control revealed significant upregulation of mgrB, phoPQ, arnBCADTE, and pmrD. Two-hybrid bacterial assays further demonstrated direct Ecr-PhoQ interaction. Electrophoretic mobility shift assay confirmed that PhoP directly binds to the ecr promoter in vitro, and a β-galactosidase reporter assay demonstrated that PhoP enhanced ecr promoter activity, indicating that PhoP regulates ecr expression by directly controlling its transcription. CONCLUSION: Collectively, these findings suggest that PhoP may directly activate the transcription of Ecr, with Ecr feedback activating the PhoPQ system via interaction with PhoQ, leading to induction of the arn operon and consequent polymyxin resistance.

Klebsiella pneumoniae

Low Carbohydrate Availability in Energy Balance Alters Bone Turnover and Muscle Proteomic Response With Limited Endocrine Disruption.

Training with low carbohydrate availability (LCA) has been proposed as an independent determinant of physiological perturbations commonly attributed to low energy availability (LEA) and to increase skeletal muscle oxidative machinery, yet the effects of LCA in isolation from LEA remain unclear. We examined whether short-term carbohydrate restriction under energy balance alters endocrine and metabolic markers associated with LEA and skeletal muscle proteomic response. In a randomized crossover design, eight trained males completed 4 days of either a low-carbohydrate high-fat diet (LOW; 12% carbohydrate, 69% fat, 19% protein) or a normal-carbohydrate diet (NORM; 62% carbohydrate, 19% fat, 19% protein), while undertaking daily cycloergometer exercise (15 kcal kg FFM-1 day-1) and maintaining energy availability at 45 kcal kg FFM-1 day-1. LOW induced a clear metabolic shift consistent with LCA, evidenced by elevated circulating free fatty acids, glycerol and β-hydroxybutyrate, in fasting conditions and fat oxidation at rest and during exercise, alongside reduced exercise glucose concentrations. Despite these responses, LOW did not alter insulin, testosterone, triiodothyronine, leptin, hepcidin, or P1NP. In contrast, β-CTX increased and IGF-1 decreased relative to NORM. Muscle glycogen concentration decreased only in LOW (40% ± 14%). Proteomic analysis identified 671 proteins; 57 differentially expressed in LOW relative to NORM were limited to fatty acid metabolism pathways and suppression of ribosomal, sarcomeric, and extracellular matrix proteins. These findings indicate that isolated LCA exerts limited endocrine disruption but may selectively compromise bone turnover and muscle anabolic response, suggesting that without acute LEA, LCA has limited influence on muscle oxidative phenotype.

Male

Non-destructive prediction of lead content in oilseed rape leaves by fluorescence hyperspectral technology based on neural network.

Based on fluorescence hyperspectral imaging (FHSI), this study targeted rapid, non-destructive quantification of lead (Pb) content in oilseed rape leaves treated with varying silicon (Si) concentrations, acquiring fluorescence spectra over the 484.43-1001.61 nm wavelength range. To optimize spectral data quality, preprocessing methods (Savitzky-Golay smoothing, first derivative, detrending) were comprehensively compared. Characteristic wavelengths were then selected via interval variable iterative shrinkage, which effectively compressed data dimensionality and reduced computational load. A hybrid SE-CL1DA model, fusing a 1D convolutional neural network, a long short-term memory network and SE attention mechanism was constructed, with Bayesian optimization tuning hyperparameters to boost stability. The BO-SE-CL1DA outperformed both traditional machine learning and insufficiently optimized deep learning model (Rp2=0.9609, RMSE = 0.0377 mg/kg, RPD = 5.1736), thus enabling accurate Pb estimation, supporting Si-regulated heavy metal stress management and facilitating agricultural contamination monitoring.

Plant Leaves

Integrated metabolomic, transcriptomic, and proteomic analyses reveal changes in the non-volatile metabolite profile of LED light-withered oolong tea.

LED light withering is a crucial method for overcoming weather limitations and enhancing the quality of oolong tea. To elucidate the underlying molecular mechanisms, this study simulated solar spectra using multiwavelength LED light and compared the resulting metabolic, transcriptomic, and proteomic profiles during the enzymatic-catalysis process (ECP) in oolong tea processing. Results indicated that LED light withering altered gene expression and protein regulation of secondary metabolism, particularly in the flavonoid biosynthesis pathway. These shifts encompassed key quality-related compounds, including flavonoids (quercetin-3-O-rhamnoside, dihydroquercetin), amino acids (L-asparagine, L-histidine), guanosine 5'-monophosphate (GMP), and carbohydrates. Furthermore, LED light withering accelerated tea leaf water loss, influenced gene expression involved in photosynthetic cellular components (chloroplasts, thylakoids), increased ascorbate peroxidase regulation under stress, and subsequently modulated energy metabolism and signal transduction in tea leaves. This study offers molecular theoretical framework for the controlled light-withering of oolong tea under bad weather and the associated improvements in its quality.

Camellia sinensis

Decoding tumor immune microenvironment heterogeneity by single-cell and spatial multi-omics: From immunotherapy resistance to translational biomarkers.

Immune checkpoint blockade has transformed cancer therapy, yet primary and acquired resistance remain major clinical challenges. Increasing evidence indicates that immunotherapy resistance cannot be fully explained by tumor-intrinsic alterations or conventional biomarkers such as PD-L1 expression, tumor mutational burden, or microsatellite instability. Instead, therapeutic response is shaped by the tumor immune microenvironment (TIME) as a heterogeneous, spatially organized, and dynamically evolving ecosystem. Single-cell omics has revealed diverse immune and stromal cell states, including progenitor and terminally exhausted T cells, suppressive myeloid programs, B-cell/TLS-associated immune-reactive states, and CAF-mediated exclusion phenotypes. Spatial transcriptomics, spatial proteomics, and imaging-based approaches further demonstrate that these cell states assemble into distinct immune niches, including immune-inflamed, T-cell-excluded, myeloid-suppressive, metabolic/hypoxic, and TLS-associated niches. These spatial ecosystems determine whether antitumor immune cells can access malignant cells, receive antigen-presenting support, or become restrained by stromal, vascular, metabolic, and myeloid barriers. In this review, we summarize how single-cell and spatial multi-omics redefine TIME heterogeneity in immunotherapy resistance, highlight ligand-receptor communication networks linking cell states to spatial immune dysfunction, and discuss emerging translational biomarkers for patient stratification. We further propose that future immunotherapy biomarkers should evolve from static single-marker assays toward longitudinal, spatially resolved, and interpretable multi-omics models that guide precision combination immunotherapy.

Humans

Transcriptomic responses of gill and intestinal tissues in Nile tilapia (Oreochromis niloticus) to bacterial infection following sequential nanoimmersion and hydrogel-based multivalent vaccination.

Bacterial pathogens, including Flavobacterium oreochromis, Aeromonas veronii, Streptococcus agalactiae, and Edwardsiella tarda, represent major infectious threats to Nile tilapia (Oreochromis niloticus). A multivalent vaccination strategy integrating cationic nanoemulsion immersion with oral hydrogel boosters was developed to investigate tissue-specific immune responses at the transcriptomic level. Gill tissues were collected following immersion challenge and intestinal tissues following intraperitoneal injection challenge, reflecting the physiologically relevant infection biology of each pathogen and the mechanistic rationale of each delivery platform. RNA sequencing (RNA-seq) generated high-quality datasets (mapping rate > 81.64%) with strong concordance to quantitative real-time PCR (qRT-PCR) validation (r = 0.83). Comparative transcriptomic analysis revealed distinct yet complementary immune signatures between tissues. Gill transcriptomes were enriched in phagosome, focal adhesion, extracellular matrix-receptor interaction (ECM-receptor interaction), and cytokine-cytokine receptor interaction pathways, accompanied by increased expression of major histocompatibility complex class I/II (MHC class I/II), mannose receptor, αVβ3 integrin, and calnexin, indicating innate activation, enhanced phagocytic capacity, epithelial barrier reinforcement, and adaptive immune coordination. Intestinal transcriptomes showed predominant enrichment of adaptive immune pathways, including the intestinal immune network for immunoglobulin (Ig) production, Forkhead box O (FoxO) signaling, and mitogen-activated protein kinase (MAPK) signaling, with increased expression of T-cell receptor (TCR), inducible T-cell co-stimulator ligand (ICOS-L), C-X-C chemokine receptor type 4 (CXCR4), and polymeric immunoglobulin receptor (pIgR), reflecting T and B cell coordination, lymphocyte trafficking, and mucosal immunoglobulin transport, alongside innate engagement through phagosome pathway enrichment. Shared upregulation of MHC class II, B-cell receptor (BCR) signaling, integrin alpha M (ITGAM), and immunoglobulin-associated components across both tissues suggests coordinated mucosal immune activation through a conserved immune module, warranting direct experimental validation. Collectively, these findings provide transcriptomic evidence that this vaccination strategy elicits an integrated, tissue-specialized immune response, advancing mechanistic understanding of gill and intestinal immunity in vaccine-induced protection of teleost fish.

Animals

Redox Rewiring in Nicotine-Driven Gastric Carcinogenesis: Uncovering ROS-Dependent Oncogenic Circuits.

SIGNIFICANCE: Nicotine from tobacco products, secondhand smoke, and emerging delivery systems remains a major but underappreciated driver of gastric carcinogenesis (GC). Although reactive oxygen species (ROS) have long been implicated in tumor biology, current models incompletely explain how chronic nicotine selectively reprograms gastric epithelial signaling. This review advances the concept of redox rewiring, whereby nicotine establishes a persistent oxidative state that orchestrates multiple oncogenic programs via spatially compartmentalized NOX signaling. RECENT ADVANCES: We synthesize evidence for a unified model wherein nicotine activates nAChR/β-AR signaling, Ca2+ influx, PKC, and compartmentalized NOX-derived ROS to generate distinct oncogenic outputs. Beyond the established NOX/ROS/NF-κB/MAPK-driven IL-8 and MMP-9 axes, we integrate emerging evidence into three interconnected modules governing EMT/metastasis (ABL1/STAT3/COX-2/periostin), survival/chemoresistance (ERK/GLI1/Bcl-2), and invasion/immune evasion (miR-21/PDCD4). Collectively, these circuits suggest that ROS function not merely as damaging byproducts but as spatially organized signaling mediators dictating tumor behavior. CRITICAL ISSUES: A major challenge is distinguishing established mechanisms from incompletely validated models. The three proposed axes are testable hypotheses requiring experimental validation. Most data derive from in vitro studies with nonphysiologic nicotine concentrations, and artifacts from nonspecific ROS probes are common. Compensatory pathway activation and multi-target effects of natural products remain underexplored. FUTURE DIRECTIONS: We outline a precision-redox oncology roadmap linking pathway-specific biomarkers, mechanistically matched natural products, and biomarker-enriched trials. Priorities include genetic validation of the three axes, time-resolved ROS imaging, and pulsed natural product regimens. By reframing nicotine-driven GC as adaptive redox network remodeling, this review provides a framework for prevention, stratification, and next-generation therapy. Antioxid. Redox Signal. 00, 000-000.

gastric cancer

Brain network alterations underlying cue reactivity and craving in abstinent methamphetamine users: a systematic review of functional MRI findings.

BACKGROUND: Methamphetamine use disorder (MUD) is marked by intense craving and high relapse risk, often triggered by drug-related cues. Functional magnetic resonance imaging (fMRI) provides key insight into the neural basis of this cue reactivity, implicating large-scale brain networks for reward, motivation, and control. Yet, findings remain inconsistent across studies due to differences in task design, abstinence duration, and participant characteristics. OBJECTIVE: This systematic review synthesises evidence on how abstinence influences brain network alterations underlying cue reactivity and craving in methamphetamine users, integrating task-based and resting-state fMRI findings within leading neurobiological models of addiction. METHODS: A systematic search of PubMed, Scopus, Web of Science, and Ovid was conducted up to August 10, 2025, following PRISMA 2020 guidelines. Eligible fMRI studies examined cue reactivity or craving in abstinent methamphetamine users. Data were extracted on activation, connectivity, and brain-behaviour associations, and synthesised narratively. RESULTS: Task-based studies revealed heightened activation across reward, salience, and control networks during cue exposure, which diminished as parietal and executive control systems re-engaged with longer abstinence. Resting-state findings showed disrupted intrinsic connectivity among default mode, salience, and frontoparietal networks, reflecting persistent imbalances linked to craving and use severity. CONCLUSION: fMRI evidence shows that MUD is marked by network-level disruption linking reward, salience, and control systems. Task-based findings reveal strong cue reactivity in reward circuits, while resting-state data show persistent imbalance among default mode and control networks. With abstinence, partial restoration of network integrity emerges, highlighting both vulnerability and opportunities for targeted, recovery-based interventions.

Humans

Artificial neural network data fusion-mediated dual-mode sensor based on Fe3O4@PdIr for Salmonellatyphimurium detection in food.

Salmonella Typhimurium (S. typhimurium) is a major foodborne pathogen that poses a serious threat to public health. In this study, a colorimetric/electrochemical dual-mode biosensor assisted by artificial neural network (ANN) was developed for the sensitive detection of S. typhimurium. Fe3O4@PdIr nanocomposites with enhanced peroxidase-like activity and electrochemical performance were prepared and conjugated with an aptamer specific to S. typhimurium to obtain Fe3O4@PdIr-Apt. Through the sandwich binding of Fe3O4@PdIr-Apt and Apt to the target, the nanocomposites were attached to microplates or Au electrodes, thereby generating colorimetric and electrochemical signals. The ANN model deeply resolved the complex nonlinear relationship between the dual signals, enabling mutual correction and ultimately performing data fusion to output a single detection result, which significantly reduced the mean square error while improving detection sensitivity and reliability. This sensor exhibited a wide linear range of 2.7-2.7 × 108 CFU/mL and a low detection limit of 1.66 CFU/mL. Additionally, this method was successfully applied to the detection of S. typhimurium in pork and milk, with a recovery rate of 95.19% ∼ 104.07%. It indicated that the constructed sensor holds great practical potential for S. typhimurium detection.

Neural Networks, Computer

Desert-derived Ensifer sp. SA403 enhances potato salt tolerance by reshaping rhizosphere microbiome functions and host responses.

Soil salinization increasingly threatens global food security, and potato (Solanum tuberosum L.), a moderately salt-sensitive crop, is particularly vulnerable to saline soils. Plant growth-promoting rhizobacteria (PGPR) offer a promising strategy to improve crop performance, yet how PGPR interact with native microorganisms to enhance potato salt tolerance remains poorly understood. In this study, we identified a desert-derived PGPR strain, Ensifer sp. SA403, which substantially enhanced potato performance under high salinity across sterile, non-sterile and field conditions. Physiologically, inoculation with SA403 reduced shoot Na⁺ accumulation and increased the K⁺/Na⁺ ratio; notably, these effects were markedly stronger in non-sterile substrates than under sterile conditions, indicating that SA403-mediated ion homeostasis relies on cooperation with the resident microbiota rather than on the strain acting alone. Metagenomic profiling indicated that SA403 strain reshaped rhizosphere communities, significantly enriching beneficial taxa such as Priestia and Bradyrhizobium, and upregulated functional pathways involved in glutathione and sulfur metabolism. Furthermore, host transcriptomic analyses showed that SA403 modulated plant responses to salt stress, with differentially expressed genes enriched in jasmonic acid signaling, ethanolamine metabolism and amino-acid biosynthesis pathways. Field trials on saline soils confirmed that SA403 significantly increased seedling emergence and tuber weight. Together, our results demonstrate that SA403 functions as a biological mediator that optimizes rhizosphere microecology and coordinates ion balance and host signaling to enhance potato salt tolerance. These findings support the potential of SA403 as a robust PGPR-based tool for sustainable potato production on saline soils.

Rhizosphere

Efficacy of pharmacological and microbiota-based therapies in preclinical models of autism spectrum disorder: a systematic review.

BACKGROUND: Autism spectrum disorder (ASD) is a multifactorial neurodevelopmental condition in which pharmacological and microbiota-targeted interventions are emerging as promising therapeutic avenues. Animal models are the main tool to investigate etiology, molecular mechanisms and screening for pharmacological therapies. Methodological differences, outcome measure variability, incomplete reporting, biological confounders, and overgeneralization of the results made evaluating innovative pharmacological agents challenging. These limitations in the field highlight a need for systematic and standardized research to reliably assess and translate pharmacological interventions from ASD animal models to human clinical relevance. SUBJECTS: This systematic review synthesized efficacy evidence for pharmacological and microbiota-based therapies across established ASD animal models. RESULTS: We identified 52 recent (2010-2025) studies that reported key ASD behavioral outcomes after pharmacological or microbiota-focused treatments. Interventions were grouped into therapeutic classes - including oxytocinergic agents, E/I balance therapeutic targets, metabolic drugs, cannabinoids, purine-based interventions and emerging targets - alongside microbiota-directed strategies such as probiotics, prebiotics, and fecal microbiota transplantation. By integrating effect directions and robustness across models, we identified most potential drug candidates, evaluated the efficacy of novel strategies, and recognized critical translational gaps. The reviewed studies demonstrate that ASD-like behavioral deficits in preclinical models can be modulated through interventions targeting diverse biological systems, including neurotransmission, neuroinflammation, metabolism, and the gut-brain axis. CONCLUSIONS: These findings support the multifactorial nature of ASD pathophysiology which arises from a network of interacting systemic processes rather than a single molecular defect. It could explain the limited success of traditionally narrowly targeted interventions and suggest a paradigm shift into a more systemic approach.

Animals

Suction-assisted ureteroscopy compared with traditional ureteroscopy for renal stones ≤ 2 cm: a systematic review, Bayesian network meta-analysis and meta-regression.

INTRODUCTION AND OBJECTIVE: Suction-enhanced flexible ureteroscopy (URS) aims to improve stone clearance and reduce complications. We performed a Bayesian network meta-analysis to compare the efficacy and safety of flexible aspiration navigable sheaths (FANS) and direct in-scope suction (DISS) for renal calculi ≤ 2 cm. METHODS: A systematic search of PubMed, MEDLINE, Scopus, Web of Science, and Google Scholar was conducted through June 2026. Comparative studies of FANS, DISS, or conventional access sheaths for renal stones ≤ 2 cm were included. The primary outcome was 30-day stone-free rate (SFR). Secondary outcomes included operative time, fever, sepsis, and complications. A Bayesian random-effects network meta-analysis synthesized direct and indirect evidence. RESULTS: Seventeen studies including 3,657 patients (1,677 FANS, 56 DISS, 1,924 control) were included. FANS showed higher SFR (OR 2.5, 95% CrI 2.0-3.1), while grouped DISS had a similar but less precise effect (OR 3.1, 95% CrI 1.0-8.8). Calyxo V2 had the highest SFR (OR 5.4, 95% CrI 1.0-29.0), whereas PUSEN showed no significant difference (OR 1.6, 95% CrI 0.41-6.3). FANS reduced postoperative fever and complications. FANS also showed lower odds of postoperative sepsis (OR 0.40, 95% CrI 0.12-0.97). CONCLUSIONS: Suction-assisted ureteroscopy improves SFR for renal calculi ≤ 2 cm. FANS was associated with shorter operative time, fever, and complications. DISS systems show promising but limited results, with performance differing by technology configuration. Larger prospective trials are needed.

Humans