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Artificial intelligence (AI) uses in stereotactic radiosurgery (SRS): diagnosis with brain metastasis (BM) - A systematic review.

BACKGROUND: Brain metastases (BM) are the most common intracranial tumors in adults, and stereotactic radiosurgery (SRS) has become a mainstay of management. However, several diagnostic challenges persist in the SRS pathway, particularly the differentiation of radiation necrosis (RN) from true tumor progression, which conventional MRI and even advanced imaging techniques often cannot reliably resolve. Recent advances in artificial intelligence (AI) offer the potential to address these diagnostic limitations. This systematic review synthesizes current literature on AI applications for MRI-based diagnostic decision support in BM patients undergoing SRS, with a focus on radiomics and deep learning tools for distinguishing RN from progression, classifying molecular and histologic subtypes, and predicting treatment response. METHODS: A systematic review was performed in accordance with PRISMA guidelines. PubMed, Web of Science, and Scopus were searched using a targeted query combining terms related to AI, brain metastasis, diagnosis or imaging, and SRS. After screening 483 records and applying strict inclusion and exclusion criteria, 18 studies published between 2015 and 2025 were included. Data were extracted on study design, cohort characteristics, imaging modality, AI methodology, validation strategy, and reported diagnostic performance. RESULTS: Among the 18 included studies, AI models demonstrated strong performance across diagnostic tasks in the BM-SRS pathway. The differentiation of RN from true tumor progression was the most extensively studied application, addressed by 14 of 18 studies, with reported AUCs ranging from 0.71 to 0.94. Support vector machines, random-forest ensembles, convolutional neural networks, and transformer-based multimodal architectures were widely used. The literature evolved from single-sequence radiomic classifiers in 2018 to multimodal deep learning frameworks fusing imaging with clinical and genomic data in 2025. Contrast-enhanced T1-weighted MRI was the dominant imaging input, and texture-based radiomic features (GLCM, GLSZM, GLDM, and wavelet-derived features) were the most consistently predictive. The highest-performing models reached AUCs of 0.85-0.91 through multimodal integration of imaging with clinical and genomic features, and consistently outperformed expert neuroradiologist read on matched cases. Remaining studies addressed longitudinal segmentation-based detection of local failure and adverse radiation effects, BRAF mutation status in melanoma BM, early Gamma Knife treatment response, and primary tumor histology classification, with more variable performance. CONCLUSION: AI models, particularly those integrating MRI-derived radiomic features with clinical and genomic data, show high accuracy in supporting diagnostic decisions for BM patients treated with SRS. The post-SRS differentiation of radiation necrosis from true tumor progression has reached the greatest level of maturity and is closest to clinical translation, with potential to reduce unnecessary biopsies, personalize surveillance intervals, and rationalize treatment-pathway decisions. Other diagnostic applications, including molecular subtyping and primary tumor histology classification, remain exploratory and require further multicenter validation. Integration of AI tools into multidisciplinary tumor-board workflows, combined with prospective validation and standardized reporting, will be essential to realize the full clinical benefits of AI in SRS for brain metastases.

Humans

Efferocytosis regulatory factors in atherosclerosis: A preclinical systematic review.

BACKGROUND: Impaired efferocytosis is a key driver of plaque instability during atherosclerosis progression. Efficient clearance of apoptotic cells through efferocytosis relies on the coordinated action of multiple regulatory factors. METHODS: PubMed, Web of Science, ScienceDirect, OVID MEDLINE, and Scopus were searched for studies published up to February 7, 2026. Eligible preclinical studies were systematically reviewed to identify endogenous factors that regulate efferocytosis in atherosclerosis. Clinical evidence was also incorporated to enable a preliminary translational assessment of these regulatory factors. RESULTS: Thirty-five endogenous regulatory factors were identified from 36 included studies, and their functional roles across distinct stages of efferocytosis were characterized. Notably, metabolic regulators such as PKM2, PFKFB3, GLS1, and Drp1 were involved in distinct efferocytosis stages. This suggests that metabolic reprogramming may provide the metabolic support require for efficient efferocytosis and inflammation resolution. Ten factors were supported by preliminary clinical evidence consistent with preclinical data. PKM2 was the only candidate biomarker with prospective observational data. However, its independent predictive value still requires validation in multicenter prospective studies. CONCLUSIONS: This review provides a systematic synthesis of 35 endogenous efferocytosis regulators and elucidates their regulatory network in atherosclerosis based on a functional stage framework. Metabolic reprogramming is identified as a central hub linking efferocytosis efficiency to inflammation resolution. This review offers a new theoretical basis for efferocytosis-targeted intervention strategies.

Animals

Comparative analysis of gut microbiota in yaks under different feeding management strategies during cold seasons.

Yaks (Bos grunniens) are crucial for the livelihoods of pastoral communities in cold regions, where feed scarcity during the cold season poses challenges to their health and productivity, underscoring the necessity of understanding how dietary management influences the gut microbiota. In this study, 24 yak steers matched for body weight and health status were randomly allocated to four groups: natural grazing or indoor feeding with roughage-to-concentrate ratios of 50:50, 70:30, or 90:10. Fecal samples were collected for 16S rDNA sequencing and subsequent functional prediction of the microbiota. The results showed that Firmicutes and Bacteroidetes were the dominant phyla across all groups, and UCG-005 and Rikenellaceae_RC9_gut_group were the predominant genera. Concentrate supplementation during the cold season significantly enhanced microbial richness and diversity, with the 70:30 ratio exerting the most pronounced beneficial effects on microbiota structure and key taxa enrichment. These findings highlight the critical role of dietary management in shaping the yak gut microbiota during cold seasons and suggest that the 70:30 ratio optimally improves microbial community structure, thereby promoting yak health and productivity under harsh climatic conditions. Future research should explore the long-term implications of such dietary strategies.

Animals

Identification of CD55 as a downstream factor of EP4 receptor signaling in colorectal cancer cells.

Prostaglandin E2 (PGE2) signaling through the E-type prostanoid 4 (EP4) receptor has been implicated in the pathophysiology of colorectal cancer (CRC). We herein identified decay-accelerating factor, also known as CD55, as a novel CRC-associated downstream factor of the EP4 receptor. The integration of transcriptomic profiling of PGE2-stimulated HCA-7 human colon cancer cells with analyses of cancer genomic databases predicted CD55 as a potential EP4 receptor-regulated target. Inhibitor-based experiments showed the induction of CD55 after a PGE2 stimulation required the EP4 receptor and Gi protein in HCA-7 cells, whereas protein kinase A signaling was dispensable. In combination with a toxicogenomic database analysis, p38 mitogen-activated protein kinase (MAPK) was identified as the predominant effector connecting the EP4 receptor to CD55 upregulation. A single-cell RNA-seq re-analysis of human CRC tissues revealed CD55 upregulation and p38 MAPK-related gene set enrichment in epithelial cells expressing the EP4 receptor, suggesting that this induction mechanism may operate in a subset of epithelial cells in clinical specimens. Collectively, these results delineate a PGE2/EP4 receptor/Gi protein/p38 MAPK signaling axis that induces CD55 expression in HCA-7 cells and epithelial tumor cells, provide new mechanistic clues for understanding the regulation of complement regulatory molecule CD55 expression by prostaglandin signaling.

Humans

Ecological momentary assessment studies on food craving among healthy adults: A systematic review.

Ecological Momentary Assessment (EMA) can capture the dynamic nature of food craving in free-living conditions, addressing limitations of laboratory and retrospective reporting methods. This systematic review synthesized findings from EMA studies to characterize 1) methodological features, 2) the temporal dynamics of food craving, and 3) the relationship between craving and eating behaviors. A systematic search of PubMed and PsycINFO databases was conducted following PRISMA guidelines. The review included 23 studies that utilized EMA designs to assess food craving repeatedly in daily life among healthy adults. Most studies employed EMA protocols that prompted participants to respond at pre-specified time points and utilized single-item craving measures. Most craving measures (71%) lacked specificity regarding the type of food craved. Results revealed a consistent positive within-person association between hunger and food craving. Conversely, associations between stress/negative affect and craving were inconsistent, varying by individual traits and context. Momentary food craving appeared to predict subsequent eating outcomes. Evidence suggested food craving may be a dynamic, transient state that co-fluctuates with hunger, functioning as a proximal antecedent to food intake. However, reliance on non-specific food craving measures and EMA protocols prompting at fixed schedules limits the granular understanding of craving mechanisms. Future research requires refining food craving measurement and incorporating randomized prompting within predefined windows, or participant-initiated sampling triggered by specific events (e.g., eating occasion), to better characterize food craving dynamics in relation to eating behaviors.

Humans

A combined stimulus of acute fasting and exercise modulates hippocampal mitochondrial quality control in healthy mice.

BACKGROUND AND AIMS: Exercise and fasting are recognized for their ability to improve brain health and mitigate neurodegeneration. However, little is known about how these interventions acutely impact mitochondrial quality control mechanisms including mitophagy. METHODS: We examined the effects of a single bout of fasting and exercise (FEx) on hippocampal mitochondrial function and proteomic remodeling in male and female mice. To assess in vivo autophagy dynamics, we combined proteomics with chloroquine (CQ) inhibition of autophagic flux. Mice were assigned to sedentary (Sed), fasting (F), exercise (Ex), or combined FEx groups and received unilateral intrahippocampal injections of CQ or PBS following treatments. Four hours later, hippocampi were collected for analysis. RESULTS: LC3-II levels significantly increased in the FEx group only following CQ treatment, indicating enhanced autophagic flux. Proteomic profiling showed sedentary males failed to mount a robust response to FEx however females exhibited upregulation of proteins involved in the TCA cycle, glutathione metabolism, and oxidative phosphorylation, suggesting greater mitochondrial adaptability. Functional assays supported these findings, females showed increased complex IV activity post-FEx. The mitochondrial DNA / nuclear DNA ratio increased after FEx regardless of sex, and upstream regulator analysis predicted activation of mitochondrial biogenesis. CONCLUSIONS: Together, these data reveal sex-specific mitochondrial remodeling in response to acute fasting and exercise. Defining these normative responses is critical for understanding how mitochondrial adaptability shapes resilience or vulnerability to neurological challenges.

Animals

Bioactive peptides for meat quality and preservation: Integrating peptidomics and computational screening.

Bioactive peptides generated from meat proteins, fermented meat products, and slaughter by-products have attracted increasing attention as functional molecules for improving meat quality and preservation. In meat systems, peptides can be produced through endogenous postmortem proteolysis, microbial fermentation, gastrointestinal digestion, or controlled enzymatic hydrolysis of underutilized animal by-products. These peptides are closely associated with key meat science endpoints, including postmortem tenderization, oxidative stability, color retention, flavor development, microbial inhibition, and the valorization of processing by-products. However, although high-resolution peptidomics has greatly expanded the identification of meat-derived peptide sequences, their translation into practical meat applications remains limited by matrix interactions, processing stability, sensory constraints, safety concerns, and insufficient validation in real meat systems. This review synthesizes recent advances in meat-related peptidomics and computational screening, including sequence-based prediction, machine learning, molecular docking, molecular dynamics, stability assessment, and safety-oriented filtering. Particular attention is given to how these approaches can prioritize peptides with antioxidant, antimicrobial, flavor-modulating, and preservation-related functions under meat-specific technological constraints. By integrating peptide generation pathways, mass spectrometry-based identification, in silico prioritization, and meat quality endpoints, this review proposes a stage-gated framework for translating meat-derived bioactive peptides from discovery to application. Future research should strengthen matrix-specific validation, standardized peptidomic reporting, and safety assessment to support the use of bioactive peptides in meat quality improvement, clean-label preservation, and circular utilization of meat industry by-products.

Animals

PPRC1 is a prognostic biomarker and key regulator of mitochondrial oxidative phosphorylation in multiple myeloma.

BACKGROUND: Multiple myeloma (MM) remains an incurable haematological malignancy, underscoring the need for novel prognostic biomarkers and therapeutic targets. This study aimed to investigate the clinical and biological significance of peroxisome proliferator-activated receptor gamma coactivator-related protein 1 (PPRC1) in MM. METHODS: Expression and clinical data were obtained from public databases and an independent local cohort. Kaplan-Meier and Cox regression analyses were performed to evaluate prognostic value. Differential expression analysis, pathway enrichment analysis and single-cell RNA-seq data analysis were used to explore biological functions. PPRC1 was silenced in MM cell lines using siRNA to assess its effects on cell survival and oxidative phosphorylation. RESULTS: PPRC1 was significantly upregulated in MM and was associated with advanced disease stage and poor overall survival. Multivariate Cox analysis identified PPRC1 as an independent prognostic factor. A nomogram incorporating PPRC1 and revised-ISS improved survival prediction. Functional analyses revealed that PPRC1 was positively correlated with oxidative phosphorylation and oncogenic signalling pathways. A potential connection between PPRC1 expression and immune cell infiltration was observed. PPRC1 knockdown inhibited cell proliferation, induced cell cycle arrest and apoptosis and impaired oxidative phosphorylation in MM. CONCLUSIONS: PPRC1 acts as a prognostic biomarker and metabolic regulator in MM by sustaining mitochondrial oxidative phosphorylation. These findings highlight PPRC1 as a potential therapeutic target in MM.

Humans

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

Genome-wide characterization of heat shock protein genes reveals thermal stress-responsive candidates in Litopenaeus vannamei.

Heat shock proteins (HSPs) are conserved molecular chaperones involved in protein folding, refolding, aggregation prevention, and degradation of damaged proteins. However, the genomic organization and thermal responsiveness of HSP genes in the Pacific white shrimp (Litopenaeus vannamei) remain incompletely understood. Here, we performed a genome-wide analysis of the HSP gene family and examined its phylogenetic relationships, structural features, duplication patterns, sequence variation, interaction networks, and transcriptional responses to acute heat stress. A total of 34 HSP genes were identified and classified into the HSP90, HSP70, HSP40/DNAJ, HSP60, and small HSP families. Phylogenetic, motif, gene structure, synteny, and subcellular localization analyses revealed evolutionary conservation and structural diversification among family members. Three duplicated gene pairs were identified, comprising two segmental duplications and one tandem duplication. All pairs exhibited Ka/Ks ratios below 1, consistent with purifying selection of varying strength. Sequence analysis identified 295 nonsynonymous single-nucleotide polymorphisms, of which 12 were consistently predicted to be deleterious by multiple algorithms. Protein-protein interaction analysis indicated enrichment of protein-folding and cellular stress-response functions. RT-qPCR analysis showed significant induction of HSPA4, HSP90AA1, TRAP1, BiP, and DNAJA1 after 6, 12, and 24 h of exposure to 34 °C, whereas DNAJC3 was significantly induced only at 12 h. All six genes reached their highest transcript abundance at 12 h. These findings may provide a genomic framework for HSP genes in L. vannamei and identify candidate genes and variants associated with thermal stress responses.

Animals

A systematic review of macaque brain stimulation: Trends and future directions.

Neurostimulation techniques can powerfully modulate neural circuit activity and provide causal insights into the relationship between brain function and behavior. Macaque monkeys have long been a key animal model for brain stimulation studies. While stimulating the macaque brain with one or a few electrodes has already taught us much about brain function and dysfunction, recent technological advances promise a future with more precise stimulation using many more electrodes. However, such possibilities also increase the number of choices an experimenter has when designing their study. We can learn from a rich past, but a comprehensive overview of which brain regions have been studied and with what stimulation parameters is lacking. Here, we present a PRISMA-compliant systematic review of 734 macaque brain stimulation studies using electrical and/or optogenetic stimulation. We find a striking bias in which brain areas have traditionally been stimulated: a mere 10 brain regions account for half of all studies, with the remainder of studies investigating approximately 150 other areas. Across studies, stimulation frequency robustly predicted direct behavioral effects independent of brain region, while amplitude did not. Future studies could more systematically explore less studied regions through lower stimulation frequencies (e.g., 20-50 Hz) alongside established ranges (∼200 Hz). Tools such as fMRI or optical imaging can capture neural circuit engagement evoked by these frequencies, even when behavioral effects are absent or remain subtle. Our synthesis offers a guide towards the next steps in high-channel-count, high-precision stimulation approaches.

Animals

The global potential of freshwater microbes for plastic degradation.

Plastic pollution is becoming increasingly severe on a global scale, and the potential for biodegradation as a treatment method that is environmentally friendly merits greater attention. A significant number of genes that associated the degradation of plastic (PDAGs) have been identified, however, the distribution of these genes among microorganisms in global inland waters remains to be elucidated. A global-scale meta-analysis was conducted, incorporating approximately 1000 metagenome datasets of inland waters across seven continents. A total of 13,109 metagenome-assembled genomes (MAGs) were obtained by means of metagenomics binning, and 22,621 PDAGs were identified from these. Among these recognized PDAGs, phenylacetaldehyde dehydrogenase (PAD) was the most dominant (n = 16,664), followed by catalase (n = 5931). The predominant hosts for PAD and catalase were identified as Gamma-proteobacteria and Bacteroidia, respectively. The largest number of both PAD and catalase was found in MAGs from North America, while the average gene number in single MAG was highest in MAGs from Oceania. In accordance with the prediction of traits, PDAG-carrying MAGs from Europe demonstrated the fastest growth rate and the lowest optimal growth rate. Furthermore, 25 styrene monooxygenase (StyA) enzymes were identified, which were found to cluster into two distinct groups hosted by Alpha-proteobacteria and Gamma-proteobacteria, respectively. Moreover, 11 MAGs were observed to possess the complete pathway of polystyrene degradation. These results explored the potential of inland water microorganisms as a biological resource for plastic degradation and provided valuable microbial reference information that can be used to develop biological treatment technologies for mitigating plastics.

Plastics

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

Integrated photoelectrocatalytic reduction and oxidation processes to achieve efficient degradation of fluoxetine in pharmaceutical wastewater.

Fluorinated organic compounds have been frequently detected in aquatic environments, with the widespread use of fluorinated drugs. The existing processes of urban sewage treatment plants are difficult to completely remove these pollutants containing the persistent C-F bonds. In this work, an integrated system of UV-activated sulfite and UV-assisted electrochemical oxidation was innovatively constructed for efficient degradation of fluoxetine. For the UV-activated sulfite unit system, when the sulfite dosage was 0.5 mmol/L and the initial pH was about 10, the defluorination efficiency of 5 mg/L fluoxetine wastewater under nitrogen atmosphere was about 98 %. Subsequently, the UV-assisted electrochemical oxidation unit system was employed to treat the reduced wastewater mentioned above. When the sodium chloride dosage was 25 mmol/L, the initial pH was about 5, and the current density was 30 mA/cm2, the total organic carbon (TOC) removal of the wastewater arrived at 65 %. Active species capture experiments and ESR tests confirmed that hydrated electrons, hydroxyl, and chlorine radicals were the main components for the efficient degradation of fluoxetine. According to the analysis of Fukui function and HPLC-MS, the degradation pathway of pollutants was proposed including defluorination and mineralization. Meanwhile, the toxicity of intermediates was predicted using the ECOSAR program. In addition, the verification test of actual wastewater treatment indicated that the defluorination and TOC removal efficiency of fluorouracil by the integrated system were similar to those for fluoxetine. This work provided a new approach for the efficient degradation of fluorinated organic pollutants in pharmaceutical wastewater.

Fluoxetine

Influence of soil types with different soil-forming process on the qualitative and quantitative detection of microplastics by near-infrared spectroscopy.

Microplastics (MPs) have become a pressing global environmental threat, with soils-acting as sinks for MPs from multiple sources-gaining increasing attention. Near-infrared (NIR) spectroscopy offers a promising tool for MPs detection due to its rapid, non-destructive, and field-applicable features. Although previous studies have focused on the effects of individual soil components on the NIR detection performance of MPs, there is still a lack of systematic research on how the complex background-formed by the coupling of multiple physicochemical properties in natural soils-affects detection performance. This study focuses on soil types with different soil-forming processes, selected five representative agricultural soils to systematically evaluate how the combinations of physicochemical properties they represented affect the performance of NIR-based qualitative and quantitative analysis of MPs in soils. The results demonstrated that soil type significantly affected both the spectral response and detection performance of MPs. Brown Pedocals and Brown Earth exhibited clearer characteristic absorption and stronger linear responses, achieving higher identification accuracy under low (<1.5 %) or zero MPs concentrations and the best quantitative performance (R2 &#x2265; 0.988, prediction set root mean square error (RMSEP) &#x2264; 0.110 %). In contrast, Phaeozem and Red Soil were more prone to misclassification at low concentrations, while Fluvo-aquic Soil showed the poorest quantitative performance. This study is the first to reveal, at a holistic level, the critical constraints posed by natural soil complexity on the NIR detection of MPs, offering targeted empirical evidence to support the application of NIR technology in real-world soil environments.

Soil

Genome-wide identification of the HSP70 superfamily in tropical sea cucumber Stichopus monotuberculatus and their expression analysis under low-salinity stress.

Heat shock proteins (HSPs) are a group of evolutionarily conserved molecular chaperones that serve as indispensable core regulators in preserving cellular homeostasis and orchestrating organismal stress responses. The tropical sea cucumber Stichopus monotuberculatus, a high-value aquaculture species, is sensitive to fluctuations in environmental salinity-a challenge that has emerged as a critical bottleneck limiting its large-scale commercial cultivation. However, no systematic investigation has been conducted to characterize the HSP70 superfamily in S. monotuberculatus and elucidate its functional roles in salinity adaptation. In the present study, we performed a comprehensive genome-wide scan and identified 19 HSP70 superfamily genes in the S. monotuberculatus genome, with the HSP70IV subfamily showing remarkable gene expansion, containing 8 distinct copies. Phylogenetic analysis, conserved motif identification, and gene structure characterization demonstrated high evolutionary conservation within each HSP subfamily. These genes were unevenly distributed across the chromosomes of S. monotuberculatus, and prediction of cis-acting elements revealed that their upstream regulatory regions were enriched with numerous functional elements associated with stress response and immune regulation. Salinity stress experiments revealed that under severe low-salinity conditions (18&#x2030;), the expression levels of SmHSPA14L and multiple HSP70IV subfamily members were significantly elevated, while SmHYOU1D was significantly downregulated; in contrast, only subtle changes were detected in the expression of most HSP70 genes under moderate low-salinity stress (24&#x2030;). These findings strongly suggest that HSP70 genes, particularly the expanded HSP70IV subfamily, may act as key modulators in the low-salinity stress response. This work provides valuable insight into the molecular mechanisms underlying salinity adaptation in tropical sea cucumbers.

Animals

Comparative transcriptome analysis reveals ncRNA-mediated regulatory networks associated with muscle crispiness in grass carp.

Non-coding RNAs (ncRNAs) have been demonstrated to be involved in muscle development and to function as key regulators. However, the molecular mechanism underlying muscle crispiness in grass carp (GC) remains poorly understood, and whether these ncRNAs are involved in its regulation is still unknown. In the current investigation, differentially expressed (DE) RNAs (including lncRNAs, circRNAs, miRNAs, and mRNAs) were identified; concomitantly, target genes prediction was conducted, and functional and signaling pathway enrichment analyses were performed. Pathways related to muscle crispiness were identified, and the competitive endogenous RNA (ceRNA) (lncRNA/circRNA-miRNA-mRNA) regulatory network was further constructed. The results showed that a total of 126 DE-lncRNAs, 17 DE-circRNAs, 329 DE-miRNAs, and 442 DE-mRNAs were identified in muscle tissues of both the GC and crisp grass carp (CGC). GO and KEGG enrichment analyses revealed that target genes of DE-ncRNAs were significantly enriched in signaling pathways, including structural constituents of muscle, apoptosis, oxidative phosphorylation, and regulation of actin cytoskeleton, suggesting that these pathways may be involved in muscle texture remodeling. Subsequently, DE-RNAs enriched in related pathways were identified, and a core ceRNA regulation network comprising 3 lncRNAs, 4 circRNAs, 3 miRNAs, and 17 mRNAs was constructed. Additionally, 10 DE-RNAs from randomly selected groups were validated by qRT-PCR. Our findings not only provide scientific evidence elucidating the molecular mechanisms underlying muscle crispiness in GC but also establish a foundation for studying changes in muscle textural qualities across other fish species.

Animals

Identification Matters: How Data Sharing Affects Pupil Honesty and Engagement in Universal School Well-Being Assessments.

PURPOSE: Universal well-being assessments in schools may support early identification of pupils needing mental health support. However, little is known about how privacy and confidentiality concerns influence pupils' acceptability of assessments and willingness to engage authentically. This study examined how hypothetical identification, where responses are linked to pupils and shared with key stakeholders, affects pupils' anticipated honesty and engagement, and whether known help-seeking barriers predict negative responses. METHODS: Cross-sectional data were collected from 12,377 primary (ages 8-10) and secondary pupils (ages 11-17) across 55 schools in England. Pupils reported whether their responses would change if identifiable and shared with school staff, parents/guardians, or external professionals. Responses indicating reduced honesty or likelihood of disengagement were coded as negative. Predictors were examined using mixed-effects logistic regression models, including demographics, school connectedness, and mental well-being. RESULTS: Identification and data sharing influenced pupils' anticipated engagement, particularly in secondary schools. Identification by school staff elicited the highest proportion of negative responses in both phases, whereas external professionals elicited the fewest. Most primary pupils reported they would respond authentically, while a larger proportion of secondary pupils indicated they would respond less honestly or disengage when responses were identifiable and shared. Across primary and secondary samples, low well-being, low school connectedness, and being female were associated with greater likelihood of negative response. DISCUSSION: Pupils' anticipated engagement with well-being assessments is shaped by who accesses their data, with marked developmental differences. Strengthening trust, privacy, and connectedness, and supporting pupils' autonomy, may improve the acceptability and response accuracy.

Humans