Search PubMedSearch

SEARCH · Search PubMed

Results for “growth curves”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

258 records · Page 12Linked to original sources

Analysis of end-stage renal disease mediated by cuproptosis-related genes.

OBJECTIVE: The complex pathophysiological mechanism of end-stage renal disease (ESRD) has not been fully understood. Cuproptosis is a newly discovered type of programmed cell death. Therefore, this study attempts to clarify the relationship between cuproptosis-related genes (CRGs) and the phenotype of ESRD. MATERIALS AND METHODS: The National Center for Biological Information Gene Expression Omnibus database was applied to obtain the GSE37171 dataset comprising whole-genome microarray analysis of peripheral blood samples. A 3 : 1 case-control design was employed with 75 ESRD patients and 20 healthy controls who were frequency-matched for age, sex, and ethnicity. Based on differentially expressed genes (DEGs) and genes related to cuproptosis, CRGs were identified. Thereafter, we explored two different subpopulations based on the cuproptosis gene and analyzed their expression and immune infiltration. Genes specific to the CRG cluster were identified through the weighted gene co-expression network analysis algorithm, and the best prediction model was determined and verified by four machine learning methods. RESULTS: The study identified 14 differentially expressed CRGs, among which ATP7B, SLC31A1, LIAS, LIPT1, DLD, MTF1, CDKN2A, DBT, and DLST had relatively high expression levels in the ESRD samples. Compared with the control group, expression levels of FDX1, DLAT, PDHA1, PDHB, and GLS were significantly lower in the ESRD group, and CRGs played a key role in the regulation of immune infiltration in ESRD. Two cuproptosis-related molecular clusters were identified in the ESRD samples. Cluster2 was more correlated with the immune infiltration of ESRD. By analyzing the intersection points between CRG cluster and key genes of ESRD, a total of 888 specific DEGs were identified. Functional differences related to specific DEGs were further explored using gene set variation analysis. Five significant genes (SMC5, USP47, USP53, AGA, and DMXL1) were identified by the support vector machine model as key predictors for ESRD disease risk, achieving an area under the curve (AUC) of 1.00 in internal validation. However, external validation in independent cohorts is required prior to clinical application. Individual gene analysis showed an AUC > 0.81 in discriminating ESRD patients from healthy controls, and the expression of all 5 genes in ESRD patients was significantly lower than in the control group. CONCLUSION: This study clarified the relationship between CRGs and the phenotype of ESRD, analyzed their specific roles in the immune microenvironment, and obtained a predictive model, providing new insights for the study of its potential therapeutic targets.

Humans

Electro-clinical efficacy and safety of midazolam in neonatal seizures: a systematic review with individual level exploratory analysis of gestational age-related treatment response.

UNLABELLED: Neonatal seizures are the most common neurological emergency during the neonatal period and are associated with increased mortality and adverse neurodevelopmental outcomes. Despite current recommendations supporting phenobarbital as first-line therapy, seizure control remains suboptimal in a large proportion of neonates, prompting the use of second-line antiseizure medications. Midazolam is increasingly administered in refractory neonatal seizures but evidence regarding its electro-clinical efficacy and safety remains limited and heterogeneous. To systematically review the available evidence on the electro-clinical efficacy and safety of midazolam in neonatal seizures and to perform an exploratory individual-level analysis investigating the association between gestational age and treatment response. A systematic review was conducted according to PRISMA 2020 guidelines. Studies including neonates with EEG- or aEEG-confirmed seizures treated with midazolam were included. Binary logistic regression was performed to assess the individual-level association between gestational age and treatment response. Eleven studies involving 146 neonates treated with midazolam were included. Electro-clinical response was observed in 101/146 neonates (69.2%), while seizure cessation was achieved in 61/146 neonates (41.8%). In an exploratory complete-case logistic regression analysis, higher gestational age appeared to be associated with a greater probability of electro-clinical response. The predicted probability curve crossed the 50% response probability at approximately 36.5 weeks of gestation. Hypotension was the most frequently reported adverse event, while respiratory depression, sedation-related effects, and transient EEG/aEEG suppression were reported less frequently. CONCLUSIONS: Midazolam may have a role as an add-on antiseizure medication in neonatal seizures, particularly in refractory cases. However, the evidence remains limited by heterogeneity in study design, EEG monitoring strategies, outcome definitions, and incomplete individual-level data. The observed association between gestational age and response is hypothesis-generating and requires prospective validation. WHAT IS KNOWN: • Phenobarbital often provides incomplete seizure control in neonates, making second-line antiseizure therapies necessary in refractory cases. • Evidence supporting midazolam for neonatal seizures remains limited and heterogeneous. WHAT IS NEW: • This systematic review summarizes the electro-clinical efficacy and safety of midazolam and includes an exploratory patient-level analysis suggesting that higher gestational age may be associated with improved treatment response. • These findings support further prospective studies on developmental determinants of response to GABAergic therapy.

Humans

Integrated assessment of biocontrol potential and genome analysis of endophytic Bacillus velezensis MGL-B1 against mango stem-end rot.

Mango stem-end rot is a globally significant postharvest disease that severely threatens the mango industry, primarily caused by Botryosphaeria dothidea. However, information on biocontrol agents targeting this pathogen in mango remains limited. In this study, we isolated and identified a strain of Bacillus velezensis MGL-B1 from mango leaf tissues for the first time, which exhibited broad-spectrum antifungal activity. Both in vitro and in vivo assays demonstrated that MGL-B1 effectively inhibited the growth of B. dothidea, with an in vivo biocontrol efficacy reaching 83.72 ± 5.10%, comparable to that of the commonly used chemical fungicide thiabendazole. Further mechanistic analysis revealed that MGL-B1 acts by directly disrupting the integrity of the pathogen's mycelial cell membrane. In addition, its released volatile organic compounds (VOCs) also displayed significant antifungal activity, with components such as 2-nonanone, 2-nonanol, and phenylethyl alcohol being confirmed to exert antifungal effects in in vitro fumigation assays. qPCR analysis showed that MGL-B1 treatment significantly upregulated the transcriptional levels of genes involved in plant-pathogen interaction, phenylpropanoid biosynthesis, and antioxidant defense pathways in mango fruits, with upregulation folds of 16.32, 37.19, and 75.93, respectively; meanwhile, the expression of browning-related genes such as polyphenol oxidase (PPO) was markedly suppressed. Whole-genome sequencing further revealed 14 biosynthetic gene clusters for antimicrobial compounds, including five unknown gene clusters. Collectively, B. velezensis MGL-B1 represents a promising biocandidate strain with multiple antifungal mechanisms and excellent control efficacy, providing a valuable resource for green and sustainable management of mango diseases.

Mangifera

Intraskeletal Variation in Cortical Bone Quantity in a Medieval Italian Sample: A Multivariate Exploratory Approach.

Bioarcheologists interpret skeletal health by examining variability within and between individuals. Studies of bone loss have generated contradictory and conflicting results regarding the onset and severity of age-related bone loss on a global and temporal scale, perhaps due to mismatched methodologies. Intraskeletal comparisons of bone tissue prove challenging precisely because of heterogeneous baselines in quantity and remodeling of cortical bone throughout the skeleton, as well as evolutionary histories and environmental impacts on growth and development. Here we analyze cortical bone indicators from the rib, metacarpal, and femoral cortical bone in a subset of individuals (n = 72) regions from the medieval Italian archaeological site of Pieve di Pava. To facilitate intraskeletal comparisons across elements with different biological baselines, we standardize cortical bone parameters using z-scores. Variation in relative intraskeletal cortical bone was assessed using accessible multivariate methods (principal component analysis and hierarchical cluster analysis). Results suggest an association between femoral and metacarpal cortical bone values, with stochastic trends in metacarpal and femoral relative bone quantity in relation to the rib bone quantity at the sample level. Our study demonstrates that while intraskeletal analyses are challenging, they are made more robust by synthesizing multivariate methods alongside exploratory data analysis (EDA) methods to tack between sample-level and individual-level scales and variability. Ultimately, we advocate for leveraging multivariate techniques not as a final step, but rather as a means of generating new hypotheses and challenging tendencies to a priori establish typological groups in the research process.

Skeleton

Adjuvant CDK4/6 inhibitors in early-stage breast cancer: Clinical evidence and considerations for risk stratification and treatment selection.

Hormone receptor-positive, human epidermal growth factor receptor 2-negative breast cancer is the most common biologic subtype and carries a persistent risk of recurrence, particularly in patients with high-risk, early-stage disease. Cyclin-dependent kinase 4 and 6 inhibitors, initially established as a standard component of first-line therapy in the metastatic setting based on improvements in progression-free and overall survival, have since been evaluated in the adjuvant setting. While adjuvant palbociclib did not improve invasive disease-free survival, the monarchE and NATALEE trials demonstrated that abemaciclib and ribociclib, respectively, reduce recurrence risk in patients with high-risk, early-stage disease, with emerging overall survival data further supporting their use. However, the absolute magnitude of benefit varies substantially with baseline risk, and treatment-related toxicity and adherence challenges must be considered, as approximately 20% to 25% of patients discontinue therapy before completion. The integration of these agents into clinical practice also intersects with ongoing efforts to deescalate axillary surgery, as treatment eligibility has been largely defined by anatomic staging, particularly nodal status. Available data suggest that the incremental impact of axillary surgery on identifying candidates for cyclin-dependent kinase 4 and 6 inhibition is modest, especially among the favorable-risk populations now eligible for surgical deescalation. As the field evolves, advances in molecular risk stratification, genomic profiling, and dynamic biomarkers are poised to shift treatment selection from anatomic staging toward biologically driven approaches. Multidisciplinary decision-making that integrates tumor biology, anticipated absolute benefit, toxicity, patient preferences, and surgical considerations will be essential to ensure individualized care.

Humans

Molecular characterization and biological characteristics of a highly pathogenic recombinant ALV-J strain (HUE2023) with cross-clade gp85 recombination.

Avian leukosis virus subgroup J (ALV-J) has undergone extensive diversification into phylogenetically distinct clades, yet whether recombination between these clades within the gp85 envelope glycoprotein generates variants with altered pathogenicity has received little direct investigation. A field strain (HUE2023) was recovered from breeding roosters displaying vascular tumors. The viral genome was sequenced and subjected to phylogenetic and recombination analyses. The three-dimensional structure of gp85 was predicted with AlphaFold3; electrostatic surface potentials and surface hydrophobicity were computed using the Adaptive Poisson-Boltzmann Solver and the Eisenberg hydrophobicity scale, respectively. Pathogenicity and immunosuppressive effects were assessed in Hy-Line Brown chickens. Recombination analysis revealed that HUE2023 is an inter-clade recombinant derived from Clade 1.1 (major parent: JS14NT01) and Clade 1.2 (minor parent: JS09GY3). A single-residue deletion at position 61 within receptor-binding domain 1 (RBD-1), unique to the recombinant, induced a localized conformational rearrangement that generated a concentrated electronegative surface patch and a contiguous hydrophobic pocket not observed in either parental gp85. Animal challenge showed that HUE2023 is highly pathogenic: female chickens in the high-dose group reached only 61% survival and displayed significant growth retardation (P&#x202f;<&#x202f;0.05) together with marked immunosuppression. The recombination in the RBD-1 led to local conformational rearrangement, resulting in a concentrated and negatively charged surface area as well as a continuous hydrophobic pocket, which were never present in any of the parental gp85 sequences. These results indicate that gp85 recombination across clades can yield variants with fundamentally altered receptor-binding surfaces and argue for integrating structural surveillance into ALV-J monitoring programmes.

Animals

From commensal to pathobiont: The emergence of virulence-enhanced Escherichia coli in China's food-animal systems - insights with future implications.

A fundamental shift in Escherichia coli epidemiology is being driven by convergence of virulence determinants and antimicrobial resistance within linked human-animal-environment systems. In China, the rapid growth of food-animal production, extensive antimicrobial use, and complex food networks are accelerating the emergence and dissemination of virulence-enhanced E. coli pathobionts. This review synthesizes recent epidemiological, genomics, and outbreak data to characterize China's evolving landscape of food-animal-associated E. coli. We highlight a significant shift from classical pathotypes to hybrid lineages that simultaneously carry virulence factors and last-resort antibiotic resistance determinants, including mcr-1, tet(X4), and blaNDM. These traits disseminate rapidly via plasmid-mediated horizontal gene transfer, facilitating rapid adaptation and enabling cross-sectoral One Health transmission. National surveillance, foodborne outbreak investigations, and whole-genome sequencing data show that food-animal reservoirs are active evolutionary niches that drive pathogen diversity and fitness, rather than serving merely as contamination sources. Whole-genome sequencing also pinpoints high-risk clones (e.g., ST394) and plasmid-mediated co-selection of virulence and AMR. The emergence of hybrid pathotypes (e.g., STEC/ETEC) and AMR-virulence co-selection challenges traditional classification and limits the effectiveness of conventional surveillance approaches. The 2017 colistin ban reduced mcr-1, yet ongoing resistance and emerging tet(X4) demand integrated surveillance. Collectively, these findings call for reconceptualizing E. coli as a dynamic genomic entity embedded within a unified ecological network. Addressing this threat requires an integrated One Health strategy including genomic surveillance, agricultural antimicrobial stewardship, and coordinated food-environment-clinical monitoring to prevent high-risk clone emergence and global spread.

Animals

Efficacy of smartphone- and bibliotherapy-delivered multicomponent lifestyle medicine interventions for probable depression: A three-arm randomized controlled trial.

BACKGROUND: This study examined the efficacy of smartphone- (AG) and bibliotherapy-delivered (BG) lifestyle medicine (LM) interventions compared with a waitlist control group (WLG) in reducing depressive symptoms. METHODS: A total of 122 adults with probable depression were randomized to AG (n&#xa0;=&#xa0;41), BG (n&#xa0;=&#xa0;40), or WLG (n&#xa0;=&#xa0;41). AG and BG received the same core 8-week multicomponent LM intervention via a smartphone application or booklets, respectively. The core content included lifestyle psychoeducation, physical activity, diet and nutrition, stress and sleep management, goal-setting, and motivational techniques. Outcomes were assessed at baseline and immediate post-intervention (Week 9) in all groups, with 1-month (Week 13) and 3-month (Week 21) follow-ups conducted in the intervention groups only. RESULTS: At Week 9, AG (d&#xa0;=&#xa0;0.89) and BG (d&#xa0;=&#xa0;0.64) showed significantly greater reductions in depressive symptoms than WLG, with within-group improvements maintained at 1- and 3-month follow-ups (ps&#xa0;<.001, d&#xa0;=&#xa0;0.77-0.96). Clinically significant improvement was achieved by 78% of AG and 55% of BG participants, both significantly higher than WLG (19.5%; ps&#xa0;<.001). Compared with WLG, both interventions yielded greater improvements in overall lifestyle and physical activity (d&#xa0;=&#xa0;0.59-0.91) at Week 9. The AG showed additional benefits for perceived stress, health responsibility, nutrition, spiritual growth, and stress management (d&#xa0;=&#xa0;0.58-0.73), whereas BG uniquely improved insomnia symptoms (d&#xa0;=&#xa0;0.83). CONCLUSION: Smartphone- and bibliotherapy-delivered LM interventions are efficacious for managing probable depression. Further RCTs comparing them with established treatments are warranted.

Humans

Toward real-time quantification of driving risks: a systematic review and research agenda of risk field theory.

In complex traffic systems, driving risk often evolves in a continuous and progressive manner prior to crash occurrence. How to effectively represent and analyze such latent risk states remains a central challenge in traffic safety research. In recent years, risk field-based approaches have introduced spatial and spatiotemporal continuous modeling paradigms, providing new perspectives for characterizing the distribution of traffic risk and its dynamic evolution. Motivated by the rapid growth of this research area and the lack of a systematic synthesis, this paper presents a comprehensive review of studies applying risk field theory to driving safety and traffic risk analysis. Following the PRISMA guidelines, relevant literature was collected through multi-database searches and analyzed using a combination of bibliometric analysis and qualitative review. The review systematically summarizes the theoretical foundations, modeling elements, data sources, analytical methods, and application domains of risk field-related research. Particular attention is given to studies that conceptualize traffic risk as a continuous field, complemented by a broader review of traffic risk factor literature to identify key elements and analytical dimensions involved in risk field modeling. On this basis, the paper synthesizes research progress in major application areas, including traffic safety state representation, driving behavior analysis, traffic conflict assessment, and autonomous driving and human-machine cooperative systems. Differences and commonalities among existing studies are compared in terms of modeling strategies, data support, and application scenarios. Through this systematic review, the paper clarifies the main research themes and methodological trends of risk field-based studies, providing a structured framework for understanding the evolution and application of this approach and offering methodological insights for risk perception modeling and safety-oriented decision support in intelligent transportation systems (ITS).

Humans

Exploring the dose-response relationship between prenatal exercise and postpartum depression: A systematic review and meta-analysis of randomized controlled trials.

IMPORTANCE: Postpartum depression (PPD) is a hidden and widespread global public health crisis affecting millions of mothers and infants annually. Prenatal exercise is a potentially accessible nonpharmacological strategy for PPD prevention, but its optimal dose remains uncertain. OBJECTIVE: To explore the dose-response relationship between prenatal exercise and the incidence of PPD through meta-analysis of randomized controlled trials (RCTs). DATA SOURCES: Systematic searches were conducted in PubMed, Embase, Web of Science, and Cochrane Library using MeSH terms and keywords related to "pregnant women," "prenatal exercise," and "postpartum depression," up to June 23, 2025. STUDY SELECTION: RCTs included examined prenatal exercise interventions in pregnant women without a history of depression, with PPD incidence reported using validated depression scales (such as EPDS, CES-D). Non-RCT studies, duplicate publications, and studies with insufficient data were excluded. DATA EXTRACTION AND SYNTHESIS: Two researchers independently extracted data according to the PRISMA guidelines. A random-effects model was used to pool odds ratios (OR) and their 95% confidence intervals (CI). Linear and nonlinear dose-response models were employed to analyze and evaluate the relationship between exercise dose (measured in METs-min/week) and the incidence of PPD. MAIN OUTCOME(S) AND MEASURE(S): The primary outcome is the incidence of PPD, analyzing its relationship with prenatal exercise dose. RESULTS: Eight RCTs involving 2231 pregnant women were included. The pooled analysis showed that prenatal exercise was associated with a potential reduction in PPD incidence, although the overall effect did not reach statistical significance (OR=0.58, 95% CI [0.33, 1.02]). In dose-stratified analysis, exercise doses &#x2265;500 METs-min/week were associated with significantly lower PPD incidence (OR=0.44, 95% CI [0.24, 0.78]). Subgroup analyses suggested trends toward greater benefits among women aged &#x2265;30 years and those initiating exercise between 14 and 28 weeks of gestation; however, subgroup differences did not reach statistical significance. The linear dose-response trend did not reach statistical significance (p = 0.0533), and neither the overall spline association (p = 0.1704) nor the test for nonlinearity (p = 0.6361) was statistically significant. CONCLUSIONS AND RELEVANCE: Prenatal exercise may be associated with a lower risk of PPD, but the overall pooled effect did not reach statistical significance. Findings concerning &#x2265;500 METs-min/week and the apparent flattening of the dose-response curve should be considered exploratory and require confirmation in larger trials.

Humans

Exploratory proteomic and metabolomic profiling of pleural effusions identifies histone H4 and alanine as promising complementary markers for pleural tuberculosis.

The diagnosis of pleural tuberculosis (Pl-TB) remains challenging. Histopathological analysis and pathogen detection in pleural biopsies are informative but limited. We investigated differentially expressed proteins and metabolites in pleural effusions from patients with Pl-TB, malignancies, and other pathologies. A proteomic analysis of pooled pleural effusions identified 45 proteins exclusively detected or upregulated in Pl-TB samples, many linked to infectious processes. Conversely, 18 proteins were uniquely found or upregulated in malignant pleural effusions, mainly associated with detoxification and hemostasis. To validate these findings, we employed targeted proteomics in individual samples. Eight proteins were validated: S100-A9, histone H4, insulin-like growth factor-binding protein 2, fibrinogen beta chain, ficolin-3, immunoglobulin heavy constant alpha 1, sulfhydryl oxidase 1, and histidine-rich glycoprotein. Additionally, NMR-based metabolomics identified 13 metabolites with differential abundance between Pl-TB and non-TB samples. Notably, N-acetyl-glycoprotein and the branched-chain amino acids, alanine and lysine differed between groups. Proteomic and metabolomic analyses revealed distinct molecular profiles between Pl-TB and non-TB patients, despite intra-group variability. To address this, we applied classification models. Histone H4 and alanine consistently emerged as discriminative features. Overall, this study provides novel insights into the molecular landscape of Pl-TB. The combined quantification of proteins and metabolites may improve differential diagnosis, although should be further validated in larger, independent cohorts before clinical application.

Humans

Predictive Models for Hypoglycemia Risk in Haemodialysis Patients With Diabetic Kidney Disease: Systematic Review and Meta-Analysis.

AIM: To provide evidence for selecting and developing reliable clinical assessment tools for hypoglycemia in diabetic kidney disease patients during haemodialysis. DESIGN: Review. METHODS: Systematic searches were performed in 9 Chinese and English databases to collect literature regarding the development of hypoglycemia risk prediction models in haemodialysis patients with diabetic kidney disease. Two reviewers independently performed literature screening, data extraction, risk-of-bias assessment, and applicability evaluation. The Prediction Model Risk of Bias Assessment Tool was used to assess the risk of bias and applicability of the included studies. Meta-analysis was conducted using R software. DATA SOURCES: CNKI, Wanfang, VIP, CBM, PubMed, Cochrane Library, EMbase, Web of Science, and CINAHL. The search period covered from the establishment date of each database to December 2025. RESULTS: Six studies, comprising six prediction models, were included. Two studies performed internal validation, and three conducted external validation. All models reported the area under the curve, ranging from 0.813 to 0.866, and calibration measures. Four studies were rated as having a high risk of bias, while all six demonstrated good overall applicability. The meta-analysis showed that the pooled AUC value of the six studies was 0.846 (95% CI: 0.823-0.867). CONCLUSION: Research on hypoglycemia risk prediction models in haemodialysis patients with diabetic kidney disease remains in the developmental stage. Although the included prediction models exhibited satisfactory apparent discriminatory ability and clinical applicability, most of the original studies suffered from a high risk of bias and lacked adequate validation. The true predictive performance and clinical application value of these models remain to be further verified. Accordingly, routine and unconditional clinical application is not recommended at this stage. Future studies should include more high-quality, multicenter external validation and develop models with high generalizability, favourable clinical applicability, and robust predictive performance to facilitate early identification of hypoglycemia risk in this population. IMPACT: This study systematically evaluated the hypoglycemia risk prediction models for diabetic kidney disease patients during haemodialysis, and the research on hypoglycemia risk prediction models for maintenance haemodialysis patients during dialysis is still in the development stage. This study provides a reference for clinical medical staff to select or develop hypoglycemia risk prediction and assessment tools for diabetic kidney disease patients during haemodialysis. REPORTING METHOD: This study was conducted in accordance with the relevant guidelines of the EQUATOR Network and followed the TRIPOD-SRMA Checklist. PATIENT OR PUBLIC CONTRIBUTION: No patient or public contribution. TRIAL REGISTRATION: PROSPERO: CRD420251243352.

Humans

ScRNA-seq analysis reveals the effects of nitrite stress on the endocrine system of the eyestalk in Litopenaeus vannamei.

Nitrite is a harmful substance generated in Litopenaeus vannamei farming systems, largely originating from the inadequate breakdown of surplus feed and shrimp feces. Its accumulation in the water can affect the growth and physiological functions of shrimp, damage the immune system, and even cause mass mortality, thus becoming a key environmental factor restricting the green development of the industry. Under nitrite stress, the eyestalk, as an important neuroendocrine regulatory center in crustaceans, participates in the stress adaptation of the organism and exerts a protective effect by regulating energy metabolism and immune function. However, the molecular regulatory mechanism of the eyestalk in response to nitrite stress remains unclear. In this study, single-cell RNA sequencing (scRNA-seq) technology was used to analyze the heterogeneity of eyestalk cells in L. vannamei under nitrite stress. A total of 18, 394 high-quality cells were obtained, and six major cell subpopulations, including Neurosecretory cell, Motor neuron, Sensory neuron, Interneuron, Neurogliocyte, and Support cell, were identified. Differential expression analysis identified 839 differentially expressed genes, and different cell types showed distinct specific responses to nitrite stress. Functional enrichment analysis indicated that pathways such as glycolysis, oxidative phosphorylation, ribosome function, and endoplasmic reticulum protein processing were significantly activated, while signal transduction and DNA repair-related pathways were inhibited. Further analysis revealed that nitrite stress could induce mitochondrial function changes and trigger oxidative stress, thereby affecting the neuroendocrine system function of the eyestalk. This study provided insights into transcriptomic responses of the eyestalk to nitrite stress at the single-cell level, laying a theoretical foundation for the management of aquaculture environments.

Animals

Diagnostic Performance of Machine Learning for Systemic Lupus Erythematosus: Systematic Review and Meta-Analysis.

BACKGROUND: Early and accurate diagnosis of systemic lupus erythematosus (SLE) and its organ involvement is essential. Previous reviews of machine learning (ML) in SLE combined heterogeneous tasks and validation strategies and may have overinterpreted model performance. OBJECTIVE: This study evaluated the diagnostic performance of ML and deep learning (DL) models for 3 clinically distinct SLE-related tasks: SLE classification or diagnosis, lupus nephritis (LN) diagnosis, and neuropsychiatric systemic lupus erythematosus (NPSLE) discrimination. We also assessed methodological quality and certainty of evidence. METHODS: PubMed, Embase, Cochrane Library, Web of Science, and IEEE Xplore were searched from January 2014 to April 2026. Eligible peer-reviewed diagnostic accuracy studies developed or validated ML or DL models for 1 of the 3 prespecified tasks, used an accepted reference standard, and provided data for a 2&#xd7;2 contingency table. Bivariate random-effects meta-analyses with the Hartung-Knapp-Sidik-Jonkman adjustment were used to pool sensitivity and specificity. We reported 95% prediction intervals (PIs), assessed risk of bias using the Quality Assessment of Diagnostic Accuracy Studies for Artificial Intelligence tool (QUADAS-AI; Viknesh Sounderajah [Imperial College London]), and evaluated certainty of evidence using the Grading of Recommendations Assessment, Development, and Evaluation framework for diagnostic test accuracy. RESULTS: Twenty-nine studies were included: 17 for SLE classification, 5 for LN diagnosis, and 7 for NPSLE discrimination. In the primary task-stratified analysis, pooled sensitivity was 0.91 (95% CI 0.86-0.94; 95% PI 0.56-0.99), and pooled specificity was 0.94 (95% CI 0.91-0.96; 95% PI 0.69-0.99), with low heterogeneity (I&#xb2;=23.9% and 22.9%, respectively). DL models showed a sensitivity of 0.93 and specificity of 0.95, compared with 0.88 and 0.94 for traditional ML models. Certainty of evidence was high for most analyses but low for LN diagnosis because of inconsistency and imprecision. All studies were retrospective, and only 9 of 29 (31%) performed independent external validation. Overall risk of bias was high or unclear in 22 of 29 (75.9%) studies. No study reported model calibration, decision-curve analysis, or net clinical benefit. CONCLUSIONS: ML models showed promising diagnostic accuracy across 3 distinct SLE-related tasks, but wide PIs, limited external validation, and pervasive risk of bias restrict conclusions about real-world generalizability. Prospective multicenter studies with standardized tasks and reference standards, independent external validation, and formal assessment of calibration and clinical utility are required before clinical implementation.

Humans

Genome-wide identification of CXE gene family in soybean and functional characterization of GmCXE31 in lipid biosynthesis and salt tolerance.

GmCXE31 negatively regulates salt tolerance and lipid synthesis in soybean, and the cxe31-edited lines improve soybean yield and seed quality. Carboxylesterases (CXEs), as essential lipid hydrolases of the &#x3b1;/&#x3b2;-hydrolase fold superfamily, are critical for plant stress responses, hormone signaling and secondary metabolism. The key candidate gene GmCXE31 was previously identified in our laboratory through a genome&#x2011;wide association study (GWAS) of soybean lipid&#x2011;related traits. In the present study, we further identified 60 GmCXE family genes in soybean. Phylogenetic analysis clustered them into 11 conserved subfamilies. Cis-acting element analysis showed their promoters are enriched with elements related to abiotic stress, growth and hormone signaling, suggesting potential roles in soybean development and stress adaptation. GmCXE31 is highly expressed in seedling roots and responsive to strigolactones (SLs) and salt stress. Functional assays revealed that GmCXE31 negatively regulates soybean salt tolerance: its overexpression reduced salt tolerance in Arabidopsis and soybean under 150&#x202f;mM NaCl stress, while its knockout enhanced this trait. Lipid profiling revealed GmCXE31-edited lines had higher seed oil content, elevated oleic/linoleic acid ratio and lower saturated fatty acid proportion, which was achieved by regulating lipid synthesis-related genes like GmNFYA. Agronomic trait analysis showed GmCXE31-edited lines had increased nodule number, plant height and single-plant yield at maturity, with opposite phenotypes in overexpression lines. In conclusion, this study elucidates the multifaceted roles of GmCXE31 in coordinating soybean salt tolerance, lipid metabolism and agronomic traits, providing theoretical and genetic resources for salt-tolerant and high-quality soybean molecular breeding.

Glycine max

Comparative Efficacy of Insulin and Alternative Therapies for Hypertriglyceridemia-Associated Acute Pancreatitis: A Systematic Review and Network Meta-Analysis.

BACKGROUND AND AIMS: Hypertriglyceridemia-induced acute pancreatitis is associated with high triglyceride levels and may lead to significant clinical complications. Rapid TG-lowering strategies, including insulin, therapeutic plasma exchange (TPE), heparin, hemofiltration, and conservative management, are used in clinical practice; however, their comparative efficacy and impact on clinical outcomes remain uncertain. METHODS: Following preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines and International Prospective Register of Systematic Reviews (PROSPERO) registration (CRD420251239674), we searched PubMed, Embase, Web of Science, Scopus, CINAHL, Google Scholar, and Cochrane. Primary outcomes included TG reduction, C-reactive protein (CRP), length of stay, mortality, and organ failure. Secondary outcomes included renal and respiratory failure. Random-effects network meta-analyses estimated mean differences or relative risks with 95% confidence intervals; treatments were ranked using the Surface Under the Cumulative Ranking curve (SUCRA). Predefined sensitivity analyses were conducted according to study design (RCTs) and risk of bias (ROB). RESULTS: Across predominantly observational evidence, no intervention demonstrated statistically significant superiority over insulin-based therapy for mortality, organ failure, or length of stay, and no consistent clinical benefit was observed despite differences in biochemical TG reduction. Although some interventions showed relatively favorable SUCRA rankings across selected outcomes, these findings were not consistently supported by statistically significant or high-certainty evidence. In RCT-restricted analyses, therapeutic plasma exchange (TPE) significantly reduced TG levels versus insulin (MD&#x2009;-&#x2009;620.0; p&#x2009;=&#x2009;0.03) and CRP versus conservative therapy (MD&#x2009;-&#x2009;0.80; p&#x2009;<&#x2009;0.01), while insulin plus heparin was associated with shorter hospital stay (MD&#x2009;-&#x2009;1.60&#xa0;days; p&#x2009;<&#x2009;0.01). However, faster triglyceride reduction did not consistently translate into improved mortality, organ failure, ICU-related outcomes, or length of stay. CONCLUSION: Despite improvements in biochemical markers, the clinical significance of rapid TG reduction in HTG-AP remains uncertain, as these effects were not consistently associated with improvements in mortality, organ failure, ICU-related outcomes, or hospital length of stay. Given that most available evidence was derived from nonrandomized studies and that the certainty of evidence was predominantly low or very low, adequately powered randomized controlled trials are needed to determine whether accelerated triglyceride lowering improves clinically meaningful patient outcomes.

Humans

Diagnostic performance of intraoperative in vivo hyperspectral imaging for meningioma grading and molecular alterations: results from a prospective feasibility study.

OBJECTIVE: Hyperspectral imaging (HSI) is an emerging intraoperative, noninvasive, contrast agent-free imaging modality that enables quantitative assessment of tissue composition. The present study aimed to investigate whether HSI-derived tissue parameters correlate with WHO grade and molecular markers of aggressiveness in cranial meningiomas. METHODS: In this prospective study, intraoperative in vivo HSI was performed using the TIVITA tissue system, capturing spectral signatures between 500 and 1000 nm. Quantitative tissue parameters included tissue oxygen saturation (StO2), near-infrared perfusion index, organ hemoglobin index (OHI), and tissue water index (TWI). HSI parameters were correlated with histopathological WHO grade and molecular alterations, including CDKN2A/B deletion, TERT promoter mutation, and 1p/22q loss. Group differences were analyzed using one-way ANOVA, and diagnostic performance was assessed using receiver operating characteristic (ROC) analysis. RESULTS: Forty-six meningiomas were included, comprising WHO grade 1 (n = 35) and WHO grade 2-3 (n = 11) tumors. TWI was significantly higher in WHO grade 2-3 meningiomas compared with WHO grade 1 tumors (mean 0.49 [SD 0.12] vs 0.38 [SD 0.17], p = 0.048). ROC analysis demonstrated an area under the ROC curve (AUC) of 0.71 (95% CI 0.56-0.86, p = 0.036) for TWI in discriminating higher-grade disease. A TWI cutoff &#x2265; 0.367 identified all WHO grade 2-3 meningiomas with 100% sensitivity and 100% negative predictive value. In a molecular subgroup (n = 15), OHI appeared higher in tumors with homozygous CDKN2A/B deletion than in nondeleted tumors (mean 0.77 [SD 0.04] vs 0.62 [SD 0.10]). However, only 3 CDKN2A/B-deleted cases were available, and these findings should be considered descriptive. ROC analysis yielded an AUC of 0.89 (95% CI 0.71-1.00). An OHI cutoff &#x2265; 0.712 identified all three CDKN2A/B-deleted tumors (100% sensitivity), with 83.3% specificity and 86.7% accuracy. CONCLUSIONS: The present investigation demonstrated that HSI-derived tissue water and hemoglobin metrics provide biologically meaningful information in meningiomas. Low tissue water content appeared to rule out higher-grade diseases in this first subset cohort, while elevated hemoglobin showed a potential association with CDKN2A/B deletion in a small exploratory subgroup. These findings support the potential of HSI as a real-time noninvasive tool for intraoperative risk stratification and should be evaluated in large-scale studies. German Clinical Trials Register no. DRKS00036771 (www.drks.de).

Humans

Complementary feeding patterns in preterm and term infants.

Complementary feeding is essential for infants' nutritional status and development, marking the transition to solid foods when breast milk or formula alone is insufficient. Despite its importance, clear recommendations on which foods to introduce when initiating complementary feeding in preterm infants are lacking. By using data from our previously published randomized controlled trial on the timing of complementary feeding in preterm infants, the current study explores the complementary feeding patterns of preterm infants and compares them with those of term-born infants, providing insights into parental decision-making and potential long-term health impacts. Complementary feeding practices differed significantly between preterm (n&#x202f;=&#x202f;255) and term (n&#x202f;=&#x202f;159) infants, with preterm infants more often receiving vegetables as their first solid food (85.4% versus 68.8%, difference 17.6% with 95% CI 12-35%). The group with early introduction of vegetables had a lower BMI-for-age z-scores (&#x3b2; -0.28 [95% CI -0.55 - 0.02]) and weight-for-height z-scores (&#x3b2; -0.27 [95% CI -0.53 to -0.01]) at two years of age. Additionally, preterm infants showed a greater variety in the numbers of different fruits and vegetables consumed by six months (corrected) age than term-born counterparts (8.29 (SD 3.65) versus 6.26 (SD 3.47), p&#x202f;<&#x202f;0.001). These results indicate that complementary feeding patterns in preterm infants differ from term-born infants, with potential positive implications on growth. These data contribute to the development of accurate feeding protocols for preterm infants. Given that feeding practices are culturally influenced, further multinational research is essential to refine complementary feeding guidelines for preterm infants and support caregivers in informed decision-making.

Humans