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Global molecular and serological evidence of dengue and chikungunya infection: a systematic review and meta-analysis of 158,608 tested participants.

INTRODUCTION: Dengue virus (DENV) and chikungunya virus (CHIKV) are Aedes-borne arboviruses with overlapping clinical manifestations, shared vectors, and substantial diagnostic challenges in co-endemic settings. This systematic review and meta-analysis synthesized published evidence on molecular detection, serological positivity, and DENV-CHIKV dual positivity/co-infection in human clinical, surveillance, and community-based study populations. CONTENT: Following PRISMA 2020 guidance, five bibliographic databases (PubMed/MEDLINE, Scopus, Web of Science, ScienceDirect, and Google Scholar) and supplementary grey-literature/preprint sources were searched for English-language studies published from 1 January 1980 to 31 December 2024. No prospective PROSPERO or OSF protocol registration was available. Eligible records reported extractable numerators and denominators for DENV and/or CHIKV in humans using recognized molecular or serological assays. A total of 196 studies comprising 158,608 tested or suspected participants were included in the extraction table. The pooled CHIKV estimate was 14.0 % (95 % CI: 12.0-16.4; I2=97.5 %), with molecular and serological estimates of 9.8 and 15.7 %, respectively. The pooled DENV estimate was 13.8 % (95 % CI: 10.9-17.3; I2=99.0 %), with molecular and serological estimates of 13.1 % (95 % CI: 7.9-21.0) and 14.3 % (95 % CI: 10.2-19.8), respectively. DENV-CHIKV dual positivity/co-infection was 52.9 % (95 % CI: 48.7-57.1) among studies that tested and reported both outcomes. Country-level estimates varied widely and should be interpreted as summaries of available studies rather than nationally representative burden estimates. Funnel-plot asymmetry was statistically significant in DENV analyses but not in the overall CHIKV analysis. SUMMARY: Available evidence indicates extensive but highly heterogeneous DENV and CHIKV positivity across selected clinical and surveillance populations. The pooled estimates should be interpreted cautiously because of substantial between-study heterogeneity, diagnostic variability, outbreak-period sampling, and uneven geographic representation. OUTLOOK: The findings support integrated arboviral surveillance, multiplex diagnostics, and vector-control preparedness in co-endemic regions.

Humans

The circadian clock proteins PRR modulate root hair development via the RHD6/RSL module in Arabidopsis.

Root hairs, derived from trichoblasts, are critical for plant growth and environmental adaptation. Although environmental cues are known to influence root hair development, how endogenous timing systems such as the circadian clock integrate into the core transcriptional network governing root hair formation remains unclear. Here, we show that the circadian clock-associated protein PSEUDO-RESPONSE REGULATOR5 (PRR5) physically interacts with ROOT HAIR DEFECTIVE6 (RHD6) and RHD6 LIKE1 (RSL1), two basic helix-loop-helix transcription factors essential for root hair initiation. Genetic analyses suggest that PRR proteins contribute to root hair development under long-day conditions in Arabidopsis thaliana. Simultaneous disruption of PRR5, PRR7, and PRR9 results in defective root hairs, whereas PRR5 overexpression markedly increases root hair density and length. Transcriptomic and RT-qPCR analyses reveal that PRRs enhance the expression of RHD6, RSL1, and multiple downstream root hair-responsive genes, while modulating their temporal expression patterns. Furthermore, PRR5-mediated root hair promotion requires RHD6/RSL1, and PRR proteins enhance RHD6-dependent activation of the RSL4 promoter. PRRs also contribute to root hair development under phosphate-deficient and salt-stress conditions. Together, these findings establish a molecular framework in which PRR proteins regulate the RHD6/RSL network to coordinate root hair development and environmental responses.

Arabidopsis

Exploring perceptions and willingness to recycle wastes among small businesses in selected townships of the Gauteng province in South Africa.

Although small businesses play an important role in generating employment opportunities and local economic development, their involvement in recycling programs has not been characterized in greater detail. This study explored the perceptions and willingness of selected small businesses in Gauteng province townships to reuse or recycle some of their waste materials. This study used a quantitative research approach to explore the perceptions and willingness of selected small businesses to reuse or recycle some of the waste they generate. The results showed that the perceptions about the contribution of recycling to environmental pollution reduction among small businesses in the study differed significantly across the townships (χ2 = 6.892, p = 0.003). On the other hand, most formal businesses significantly agreed with the potential benefits of waste recycling on environmental pollution reduction (χ2 = 16.118, p = 0.003), saving landfill space (χ2 = 11.610, p = 0.003), improving environmental quality (χ2 = 10.443, p = 0.005), and providing job opportunities (χ2 = 10.263, p = 0.036). However, regardless of their formality (χ2 = 2.957, p = 0.228) or location (χ2 = 9.463, p = 0.051), there was no statistically significant variation in the recycling practices of the small businesses in this study. Moreover, businesses' willingness to use recycling facilities if they were located nearby differed across townships (0.05 > p = 0.010) but was similar despite the formality of the enterprises. In conclusion, recycling perceptions and willingness of small businesses can vary significantly depending on whether they are formal or informal and across townships. As a result, relevant educational interventions should be uniquely developed to raise awareness about the need for waste minimization through recovery, re-use, and recycling among small businesses in the Gauteng province.Implications: Small, Medium, and Micro enterprises (SMMEs) play a crucial role in local economic development in South Africa. However, research on their environmental sustainability is scarce, despite their significant impacts on natural resources and contributions to pollution. Most waste management studies have focused on households and municipalities, leaving a gap in understanding SMMEs' waste management behaviors, particularly in townships.

South Africa

Moderate expression and activity of flocculins underlie the characteristic flocculation phenotype of Saccharomyces pastorianus.

Flocculation is a key technological trait in lager brewing, governing fermentation performance, yeast recovery, and beer quality. In the allo-aneuploid hybrid yeast Saccharomyces pastorianus, the genetic basis of flocculation remains poorly resolved due to its complex dual sub-genome architecture. Here, we systematically re-annotated and functionally characterized the complete FLO gene repertoire of the Group II strain CBS 1483. Thirteen FLO genes were identified, including allelic variants and a previously uncharacterized adhesin, Flo12, containing a Hyphal_reg_CWP domain instead of the canonical PA14 lectin-binding domain. Structural modeling revealed strong conservation of Ca²+-binding residues in PA14 domains, alongside repeat-region diversification likely contributing to functional variability. Using optogenetic expression in a FLO-null background, we demonstrated that SpcI-FLO9-1 and SpcI-FLO9-2_1 are the strongest drivers of flocculation, exhibiting NewFlo-like sugar sensitivity. Transcriptomic analysis during 17°P wort fermentation showed dynamic induction of these genes coinciding with flocculation onset. Surprisingly, deletion of both loci in CBS 1483 did not abolish but only delayed sedimentation in wort, accompanied by improved maltose utilization and attenuation. These findings reveal functional redundancy and compensatory mechanisms within the FLO network of lager yeast, highlighting the genetic complexity underlying flocculation, and providing a molecular framework to inform yeast selection, strain development, and optimization of the lager fermentation processes.IMPORTANCEFlocculation, the process by which yeast cells aggregate and settle, is essential for producing clear, high-quality lager beer, and for efficient yeast recovery during brewing. However, the genetic basis of this trait in lager yeast has remained poorly understood because these strains possess unusually complex hybrid genomes. In this study, we systematically identified and characterized the complete set of flocculation genes in the industrial lager yeast Saccharomyces pastorianus CBS 1483. We demonstrated that lager yeast flocculation is not controlled by a single dominant gene, but instead emerges from the combined action of several moderately active adhesion proteins that are expressed at low levels during fermentation. Surprisingly, deleting the two strongest candidate genes only delayed, rather than eliminated, sedimentation, revealing a robust compensatory network that preserves brewing performance. These findings refine the current understanding of yeast flocculation and provide a molecular framework for developing brewing strains with improved fermentation efficiency, product consistency, and flavor quality.

Saccharomyces pastorianus

Peptide molecular lock-engineered nanobodies enable an oriented dual-modal immunoassay for reliable detection of Cronobacter sakazakii.

Conventional nanobody ELISAs for trace Cronobacter sakazakii in powdered infant formula suffer from random orientation and low signal output. We developed an oriented dual-modal immunoassay that combines site-specific biotinylation via a C-terminal AviTag and a peptide molecular lock, enabling controlled surface orientation while preserving nanobody structural integrity. This strategy was further integrated with phage-displayed nanobodies for multivalent amplification and both fluorescent and colorimetric readouts. The assay exhibited a broad linear range of 103-106 CFU/mL, with limits of detection (LODs) of 6.70 × 102 CFU/mL for fluorescence and 1.55 × 103 CFU/mL for colorimetry, showing improved sensitivity compared with the conventional passive adsorption-based Nb-ELISA evaluated in this study. XGBoost-based multimodal fusion improved quantitative accuracy, and SHAP analysis elucidated modality contributions. In spiked powdered infant formula samples, recoveries ranged from 92.1% to 118% with coefficients of variation below 5.98%, confirming acceptable matrix tolerance and analytical reliability.

Cronobacter sakazakii

Functional and Nutritional Potential of Chickpea Protein Hydrolysates: A Systematic Review and Plant-protein Network Analysis.

Chickpea is a protein-rich legume increasingly explored as a substrate for functional plant-based ingredients. Chickpea protein hydrolysates (CPHs) and chickpea-derived peptides (CPs), obtained through enzymatic hydrolysis or simulated gastrointestinal digestion, may provide technological and biological properties while supporting the valorization of chickpea fractions and by-products. This review integrates a network analysis of title-abstract terms from 5,728 unique Scopus and PubMed records on plant protein hydrolysates with a systematic review of 72 studies focused on CPH production, peptide characterization, bioactivity, and translational gaps. The evidence indicates that CPHs and CPs show promising antioxidant, antihypertensive, antidiabetic, anti-inflammatory, lipid-lowering, immunomodulatory, antimicrobial, and anticancer-related activities, mainly supported by biochemical assays, cell models, and animal studies. However, heterogeneous hydrolysis protocols, incomplete peptide characterization, inconsistent bioactivity methods, limited scale-up evidence, and the absence of human intervention trials restrict translation. Future studies should prioritize standardized protocols, mechanistic validation, bioavailability, sensory and regulatory assessment, food-matrix validation, and clinical trials.

Cicer

Recent advances in electrode materials for electrochemical detection of zearalenone.

Zearalenone (ZEN) is an estrogenic mycotoxin commonly found in cereals, animal feed, and processed foods, making it an important concern for food safety and public health. Conventional chromatographic and immunological methods can detect ZEN; however, they often require expensive instruments, lengthy sample preparation, and skilled personnel, which restrict their use for rapid and on-site testing. Electrochemical sensors have attracted enormous interest of the scientific community because of their high sensitivity, rapid response, low cost, miniaturization potential, and compatibility with portable systems. The analytical performance of the electrochemical sensors is strongly influenced by electrode materials, morphology, conductivity, porosity, surface functionality, and the efficiency of bioreceptor immobilization. Despite several reviews on mycotoxin detection, a systematic assessment connecting electrode-material design, modification strategies, sensing mechanisms, and electroanalytical performance specifically for ZEN sensing remain limited. This review critically evaluates recent advances in metal oxides, carbon-based materials, metal-organic- and covalent organic frameworks, MXenes, polymers, and hybrid composites for electrochemical ZEN detection. Particular attention has been given to their roles in electron transfer, analyte enrichment, selectivity, and real-sample analysis. The review also compares the major limitations of current sensing systems, including complex fabrication, matrix interference, insufficient long-term stability, poor inter-electrode reproducibility, and limited scalability. Finally, future directions for developing robust, cost-effective, portable, and commercially viable ZEN sensors are discussed.

Journal Article

From host response to genomic targets: electrochemical biosensing of tuberculosis biomarkers.

Tuberculosis (TB) remains one of the leading causes of death from a single infectious agent worldwide, with timely diagnosis continuing to be a major challenge, particularly in resource-limited settings. Conventional TB diagnostic methods are limited by low sensitivity, long turnaround times, and an inability to reliably differentiate latent from active disease. Biomarker-based diagnostic strategies have therefore gained increasing attention as they offer the potential to improve early detection, disease differentiation, and treatment monitoring. Herein, we examine electrochemical biosensing strategies for TB diagnostics using a biomarker-class-driven framework, covering host-response biomarkers (IFN-γ and TNF-α), pathogen-derived antigens (ESAT6, CFP10, CFP10-ESAT6, MPT64, Ag85, HspX and LpqH), cell-wall signatures and whole-cell markers (LAM and whole cell Mtb), and genomic markers (Mtb DNA and IS6110). Through structured comparison of recognition elements, biointerface designs, signal amplification strategies, electrochemical techniques, matrices, and validation levels, this review identifies the most promising technical approaches for different TB biomarker classes. It further highlights key translational bottlenecks, including limited clinical validation, buffer-based testing, complex multistep amplification, redox-probe dependence, matrix fouling, and insufficient evidence of manufacturability. This review therefore provides practical guidance for developing electrochemical TB biosensors that are analytically sensitive, clinically relevant, and suitable for decentralized diagnostic applications.

Biosensing Techniques

Comparison of black carbon measurements using filter-specific reference transmittance to those using lab blanks or an average of unloaded filters.

Filter-based optical techniques compare light transmission intensities between loaded (I) and unloaded (I0) filters as a measure of light-absorbing mass for subsequent estimations of equivalent black carbon (eBC). We analyzed 5,379 15 mm Teflon filters from the Household Air Pollution Intervention Network (HAPIN) trial to assess the influence that different methods of I0 estimations have on eBC measures. We compared eBC measurements using filter-specific I0 values (Method 1) to those using three other methods of I0 estimation: the lab blank scan from a given session (Method 2), the average of all pre-sample filter scans (Method 3), and the average of all lab blank filter scans (Method 4). We assessed the agreement between Method 1 and the alternative methods using Bland-Altman analysis. We also assessed the relationship between Method 1 and the alternative methods across the complete measurement range and after stratifying exposure data into quartiles according to Method 1 eBC exposures. The mean (SD) personal eBC exposure for Method 1 was 7.8 μg/m3 (5.9), and exposures ranged from 1.3 to 46.8 μg/m3. Compared to Method 1, eBC using Methods 2, 3, and 4 were higher by 0.7 μg/m3, 0.1 μg/m3, and 0.7 μg/m3, respectively. The performances of linear regression models between Method 1 and all other methods were moderate to strong (R2 range: 0.42-0.93) in the second, third, and fourth quartiles; however, the models in the first quartile (eBC range: 1.3-2.9 μg/m3) performed poorly (R2 = 0.25-0.26), with error approximately 25% of the mean. Our findings suggest that, in most instances, conventional methods for obtaining I0 values can be used to sufficiently characterize eBC; however, analyzing filters before sampling adds appreciably to the accuracy of eBC estimations in lower concentration settings.Implications: Filter-based optical techniques compare light transmission intensities between loaded (I) and unloaded (I0) filters as a measure of light-absorbing mass for subsequent estimations of equivalent black carbon (eBC). To assess the influence that different methods of I0 estimations have on eBC measures, we analyzed 5,379 15 mm Teflon filters from the Household Air Pollution Intervention Network (HAPIN) trial. Our findings suggest that, in most instances, conventional methods for obtaining I0 values can be used to sufficiently characterize eBC; however, analyzing filters before sampling adds appreciably to the accuracy of eBC estimations in lower concentration settings.

Soot

A Multi-omics Regulated Cell Death Framework Defines Immune Phenotypes and Guides Precision Therapy in Colorectal Cancer.

Colorectal cancer (CRC) is molecularly and immunologically heterogeneous, contributing to variable treatment response. Because regulated cell death (RCD) intersects with tumor metabolism, immune regulation, and therapeutic susceptibility, we built an RCD-centered framework for CRC stratification. Multi-cohort transcriptomic data were used to infer RCD subtypes with non-negative matrix factorization (NMF) and non-negative least squares (NNLS). Genomic, bulk RNA-seq, single-cell RNA-seq, and spatial transcriptomic datasets were integrated to characterize subtype-associated biology. Machine-learning models were developed for immunotherapy response and survival-risk estimation. Candidate compounds were screened by GDSC2-based drug-sensitivity modeling and molecular docking, and FSTL3 was functionally assessed in vitro. The framework separated CRC samples into two RCD-related phenotypes resembling immune-hot and immune-cold states. RCD1 showed immune activation and higher mutational burden, whereas RCD2 showed immune-suppressed features, intratumoral heterogeneity, and aggressive biology. RCD-associated signatures showed potential for predicting immunotherapy response and survival risk. Dasatinib was prioritized for immune-cold, high-risk tumors, with preliminary evidence supporting its activity in CRC cells, while functional assays suggested a role for FSTL3 in growth, invasion, epithelial-mesenchymal transition, and apoptosis regulation. These findings suggest that RCD-based multi-omics analysis may refine CRC stratification and help generate therapeutic hypotheses.

Colorectal cancer

TWIST2-dependent transcriptional activation of TPI1 mediates TGF-β1-driven fibroblast activation in pulmonary fibrosis.

Idiopathic pulmonary fibrosis (IPF) is a progressive and fatal interstitial lung disease characterized by aberrant profibrotic signaling and excessive extracellular matrix deposition, accompanied by fibroblast-to-myofibroblast transition. Despite extensive investigation, the molecular mechanisms underlying IPF pathogenesis remain incompletely understood. Here, we investigated the role of triosephosphate isomerase 1 (TPI1) in IPF progression and its regulation by transforming growth factor-β (TGF-β) signaling. Loss-of-function analyses identified TPI1 as a downstream effector of TGF-β1, as its knockdown markedly suppressed fibrotic marker expression, fibroblast proliferation, and migration. Mechanistically, TWIST2 was shown to function as a direct transcriptional regulator of TPI1, binding to its promoter and promoting transcriptional activation. Rescue experiments further confirmed that the TWIST2-TPI1 axis is central to the progression of pulmonary fibrosis. Notably, knockdown of either TPI1 or TWIST2 effectively attenuated TGF-β1-induced fibrotic phenotypes. Collectively, these findings define the TGF-β1/TWIST2/TPI1 signaling axis as an important regulator of pathogenic fibroblast behavior and pro-fibrotic responses through transcriptional control of TPI1, highlighting its potential as a therapeutic target for IPF.

Twist-Related Protein 1

A Letter Matters: ADRB2 rs1042713 c.46A Modulates Anti-osteogenic Effect of Epinephrine in Human Mesenchymal Stem Cells.

Osteoporosis (OP) is a systemic bone disease affecting millions worldwide, characterized by long-term asymptomatic development that manifests in low-energy fractures. Due to their high stability, genetic markers represent a promising strategy for early diagnostics. The ADRB2 rs1042713 polymorphism is one such marker, considered as a potential predictor for OP. Although the anti-osteogenic role of the β2-adrenergic receptor is well-established, debate continues on which allele (G or A) of this polymorphism drives bone deterioration. In this study, we examined the influence of the ADRB2 rs1042713 G/G and A/A variants on osteogenic differentiation in patient-derived mesenchymal stem cells (MSCs) under treatment with the endogenous agonist epinephrine. We show that epinephrine (whose levels are often elevated in comorbid conditions) drastically impairs osteogenic differentiation, specifically at the matrix mineralization stage in MSCs A/A. Epinephrine fails to activate the canonical β2-adrenergic receptor pathway and promotes receptor perinuclear and nuclear localization in MSCs A/A. Crucially, metformin, a common anti-diabetic drug, rescues this anti-osteogenic effect. These results open new perspectives for early diagnostics by identifying epinephrine sensitivity as a critical factor, while also suggesting a potential therapeutic strategy to counteract epinephrine detrimental effect in individuals carrying the ADRB2 rs1042713 A-allele.

Humans

Genome-wide scans reveal candidate genes associated with wing morph differentiation in Tetrix japonica.

Wing dimorphism is an important dispersal-related trait in insects, but its genomic basis remains poorly understood in pygmy grasshoppers. Here, we integrated genome-wide single-nucleotide polymorphism (SNP) analyses, population structure inference, selection scans, and functional annotation to investigate genomic differentiation between long- and short-winged Tetrix japonica. Principal component analysis (PCA), ADMIXTURE, and phylogenetic analyses revealed weak genome-wide separation between morphs, indicating differentiation on a largely shared genetic background. Genome-wide scans based on the fixation index (FST), nucleotide diversity ratios, and Tajima's D, using 50-kb non-overlapping windows and empirical top-5% outlier thresholds, identified multiple candidate regions across seven chromosomes. The broader long- and short-winged candidate sets spanned 9.35 Mb and 9.37 Mb and directly overlapped 82 and 77 genes, respectively. Candidate genes were associated with signaling/hormone regulation, membrane transport, metabolism, cytoskeletal organization, extracellular matrix structure, and development. Short-winged candidate genes were significantly enriched for ABC-type transporter activity and ATP hydrolysis activity. Because all individuals originated from a single laboratory-maintained population with weak genome-wide structure, these regions should be regarded as candidate loci from a screening-stage analysis that require validation in independent populations and by functional assays, rather than as confirmed targets of selection.

Animals

Development and validation of a novel LC-MS/MS method for simultaneous quantification of fidaxomicin and metabolite (OP-1118) from feces for gut pharmacobiome studies.

Fidaxomicin is a first-line antibiotic for treating Clostridioides difficile infection. While it has low systemic absorption and reaches high colonic concentrations, it is hydrolyzed to a less active metabolite, OP-1118. Few studies have completely described critical experimental details of liquid chromatography-tandem mass spectrometry (LC-MS/MS) for quantifying fecal fidaxomicin and OP-1118. This study developed and validated a simple, fast, and sensitive LC-MS/MS method to quantify fidaxomicin and OP-1118 in human and mouse feces. This method simplified fecal sample preparation without the use of solid phase extraction and optimized LC-MS/MS parameters. A broad working range (0.3-1000 ng/ml) in both diluted human and murine fecal matrices was achieved with good intra- and inter-day accuracy (93-107%), precision (1-7%), and recovery (70-105%) as well as little IS-normalized matrix effects. This method was utilized to quantify fidaxomicin and OP-1118 in human and murine fecal samples. This novel method was simple, fast, sensitive, and accurate in analyzing fecal fidaxomicin and OP-1118 and could be deployed to facilitate gut pharmacobiome research.

Feces

Experimental evolution reveals contrasting adaptive landscapes in lab and field environments.

Experimental evolution is widely used to infer microbial responses to environmental change, yet most laboratory studies impose constant, well-mixed conditions that differ fundamentally from fluctuating, spatially structured field environments. We compared genomic evolution in the leaf litter-associated bacterium Curtobacterium strain MMLR14_002 under control and warming treatments in laboratory culture and in a complementary field experiment. Laboratory-derived isolates accumulated more mutations per genome and exhibited stronger locus-level parallelism, with mutations recurring in a small number of coding loci. Field-derived isolates accumulated fewer mutations per genome, and these mutations rarely occurred in the same coding loci across replicate populations. Instead, field isolates exhibited a higher proportion of intergenic mutations, with mutations recurring in the same intergenic regions across independent field deployments. When coding mutations were detected in the field, they were distributed across functionally diffuse targets and more often involved metabolic pathways than the core cellular processes repeatedly targeted during laboratory evolution. Warming itself did not consistently influence mutation accumulation or the genomic distribution of mutations; instead, laboratory and field contexts primarily shaped the accumulation, targets, and repeatability of genomic change. These results suggest that laboratory thermal evolution identifies adaptive routes favored under sustained selection but may overestimate coding-level parallelism under heterogeneous field conditions. Bridging laboratory and field evolution will likely require experimental designs that incorporate temporal variability and spatial heterogeneity characteristic of natural systems.IMPORTANCEA central goal of experimental evolution is to infer how microbes evolve in nature from laboratory studies. Here, we evaluate this assumption by comparing genomic evolution of a leaf litter-associated Curtobacterium strain in laboratory and field warming experiments to identify broad patterns rather than isolate the contribution of any single environmental factor. We find that the strong parallelism at coding loci observed under laboratory conditions is reduced in the field, while mutations recurring in the same intergenic regions across field deployments suggest that parallel evolution in nature may more often involve regulatory noncoding regions rather than coding targets. These results show that environmental context reshapes adaptive landscapes and may limit the parallelism of coding-level genomic responses inferred from homogeneous laboratory conditions.

experimental evolution

Molecular mechanisms of neuroendocrine regulation of molting in the Chinese mitten crab (Eriocheir sinensis): A transcriptomic analysis based on eyestalk ablation model.

Molting disability severely restricts the sustainable aquaculture of the Chinese mitten crab, yet the neuroendocrine mechanisms coordinating physiological responses remain poorly understood. Using unilateral eyestalk ablation to remove the primary source of molt-inhibiting hormone (MIH), we performed time-resolved transcriptomic profiling of the thoracic ganglion at 24 h (early premolt) and 48 h (ecdysis) post-ablation. We identified 2825 differentially expressed genes and uncovered a biphasic molecular response. At 24 h, the thoracic ganglion activates pathways associated with neuromuscular adaptation, oxidative stress, and cardiac muscle contraction. Notably, the arachidonic acid metabolism pathway is selectively rewired: cytochrome P450 ω-hydroxylases (CYP2J2, CYP4V2) are upregulated, while competing branches (epoxide hydrolase, cyclooxygenase) are suppressed, promoting local synthesis of the potent vasoconstrictor 20-HETE within the thoracic ganglion. This enzymatic switch provides a mechanistic link between MIH withdrawal and the local generation of elevated hemolymph pressure required for molting. By 48 h, the transcriptional program shifts toward chitin-based extracellular matrix remodeling, glycosphingolipid biosynthesis, and synaptic reorganization. Collectively, our findings redefine the thoracic ganglion as an active neuroendocrine integrator that translates reduced MIH signaling into phased physiological outputs, revealing a "neuro-endocrine-hemolymph pressure" regulatory axis. This study provides novel molecular targets (e.g., CYP2J2, CHS1, UGCG) for mitigating molting disability in E. sinensis aquaculture.

Animals

Electrospun Nanofiber Dressings for Diabetic Wounds: From Single-Layer to Intelligent Composite Systems.

Diabetic chronic wounds have become a major challenge for clinical treatment due to their complex pathological microenvironment, including persistent inflammatory response, angiogenesis disorder, excessive oxidative stress, and susceptible infection. Traditional dressings as a passive barrier have difficulty meeting the above multiple treatment needs. Electrospinning technology, with its ability to mimic the fibrous network structure of the natural extracellular matrix (ECM), offers a high specific surface area, controllable porosity, and excellent drug-loading capacity, making it an ideal platform for developing a new generation of multifunctional wound dressings. This article provides a systematic review of the research progress on electrospun nanofiber dressings in the treatment of diabetic wounds, focusing on the design evolution from basic single-layer structures to advanced complex structures and elucidating the mechanisms of action and quantifiable effects of each structural type in addressing specific pathological challenges. We also compared the current status of clinical translation for electrospun dressings with that of other advanced wound care platforms and proposed a standardized preclinical evaluation framework. A large number of research data show that these advanced designs can effectively improve the quality of healing. Finally, this paper points out the challenges faced by this field, such as scalable fabrication, in vivo reliability of smart systems, and long-term biosafety, and provides theoretical basis and technical reference for the design of efficient and intelligent electrostatic spinning diabetic wound dressings.

Nanofibers

Predictive evolutionary genomics: principles, validation, and practice.

Climate change and habitat loss are driving rapid evolutionary responses in populations world-wide, which creates an urgent need for evolutionary forecasting in conservation and agriculture. Such forecasting can be categorized into three time scales: trait-based models that use multivariate quantitative genetic equations to project correlated phenotypic responses up to c. 20 generations, allele-based analyses that model allele frequency dynamics up to 100 generations, and composite adaptation scores that aggregate many small effects to yield predictions across longer horizons. However, these approaches have remained largely disconnected. Here, we present a Bayesian framework that integrates these three complementary approaches for evolutionary prediction. Our framework combines genomic, phenotypic, and environmental data to yield probabilistic predictions with explicit uncertainty. We show how predictive evolutionary forecasts can be validated with experimental evolution, field experimentation, historical specimens, and reciprocal transplants. These validated forecasts can help advance conservation and agricultural programmes by helping predict which populations are at risk of future extinction, optimizing breeding programmes for future climates, and planning ecosystem management under environmental change. By supporting a shift towards more predictive approaches in evolutionary biology, this framework may help improve our ability to manage biodiversity and food security in a changing world.

Genomics