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PubMed2026

Revealing potential biomarkers and metabolic mechanisms of ovarian aging in hens during late laying period based on machine learning and metabolomics.

Ovarian function decline during the late laying period represents a major bottleneck for the economic efficiency of the global poultry industry. However, the underlying metabolic mechanisms and reliable early-warning biomarkers for ovarian aging remain poorly understood. In this study, we performed the first untargeted LC-MS/MS metabolomics analysis of ovarian tissues from Taihe silky fowls at peak laying (30 weeks) and late laying (50 weeks) stages, and employed an ensemble machine learning strategy integrating LASSO, random forest, and support vector machine (SVM) algorithms to identify high-confidence core biomarkers of ovarian aging. Gene expression analysis was further conducted to validate the potential molecular mechanisms. Our results showed that the metabolic profiles of ovarian tissues differed significantly between the two groups. A total of 6 core biomarkers were identified, 4 of which were long-chain acylcarnitines. Mechanistic analysis revealed that downregulation of key genes in the carnitine shuttle system led to impaired mitochondrial fatty acid β-oxidation, which in turn triggered excessive oxidative stress and compromised ovarian endocrine function. In conclusion, this study identifies long-chain acylcarnitines as potential metabolic biomarkers for ovarian aging in Taihe silky fowls. These findings provide novel insights into the metabolic basis of poultry ovarian aging and lay a theoretical foundation for the precise regulation of reproductive performance in indigenous poultry breeds.

Animals↗

PubMed2026

Thrombus Metabolism-Based Molecular Subtyping for Prognostic Risk Stratification in Acute Ischemic Stroke: A Preliminary Study.

AIMS: To preliminarily characterize metabolic molecular subtypes of cerebral thromboemboli and evaluate their clinical significance in anterior circulation acute ischemic stroke due to large vessel occlusion (AIS-LVO). METHODS: Untargeted metabolomics was performed on thromboemboli retrieved from 36 patients with anterior circulation AIS-LVO using ultra-performance coupled liquid chromatography with quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS). Unsupervised hierarchical clustering was employed to identify distinct metabolic molecular subtypes, and their associations with stroke etiology, radiographic severity, and functional outcomes were analyzed. RESULTS: Two distinct thrombus metabolic molecular subtypes (C1 and C2) were identified based on 12 metabolites significantly associated with both short-term (7-day ∆NIHSS) and long-term (90-day mRS) functional outcomes. The C1 subtype, predominantly cardioembolic, exhibited enhanced lipid metabolism, whereas the C2 subtype, primarily atherothrombotic, demonstrated increased folate metabolism. Patients with C1 thromboemboli presented more severe admission ischemic lesions (as indicated by ASPECTS) and experienced poorer short-term and long-term outcomes. A six-metabolite signature derived from LASSO regression was identified for exploratory discrimination of thrombus metabolic subtypes, etiological subtypes, and 90-day outcomes. CONCLUSION: This preliminary exploratory study identifies two metabolically distinct thrombus molecular subtypes with clinical implications in anterior circulation AIS-LVO, providing a novel basis for risk stratification and personalized secondary prevention and warrants further investigation.

Humans↗

PubMed2026

Vortex-assisted liquid-liquid microextraction based on natural deep eutectic solvents for the determination of pyrethroid pesticides in urine.

A novel, facile, and environmentally friendly analytical method was developed based on vortex-assisted liquid-liquid microextraction and high-performance liquid chromatography with diode-array detection for detecting pyrethroid pesticides (PPs) in urine. Natural deep eutectic solvents (NADESs) were prepared using plant essential oil-derived monoterpenoids (thymol, carvacrol, and menthol) combined with aromatic primary alcohols (benzyl alcohol, phenethyl alcohol, and phenylpropyl alcohol) as hydrogen bond donors and acceptors. These solvents served as environmentally benign extraction media, thereby avoiding the use of conventional volatile, toxic organic solvents. NADESs are naturally derived, easy to prepare, biodegradable, and environmentally friendly solvents. Hydrophobic and π-π interactions between the NADESs and PPs may contribute to enhancing the affinity of PPs toward the NADESs phase. Vortex technology, accelerating mass transfer between the sample and extractant phases, enables fast extraction of PPs. Under optimized conditions, the method achieved a low detection limit (0.002 mg L-1), satisfactory precision with relative standard deviations (0.3%-2.4%), and acceptable recovery (80.7%-86.2%). The method demonstrated excellent performance in urine analysis and was feasible as a facile and green strategy for monitoring the content of PPs in biological matrices and assessing exposure risk.

Liquid Phase Microextraction↗

PubMed2026

Translating single-cell RNA sequencing into monocyte direct leukocyte subpopulation-transcript abundance assay ratio-based biomarkers (IFI27/PSAP or IFI27/CTSS) for clinical detection of viral infection.

A rapid method for triaging febrile patients by aetiology (e.g., viral or bacterial infection) using gene expression in peripheral blood (PB) is an intensively researched area. However, gene expression in blood represents a composite sum of gene expression of all the component cell types present in the sample. As a result, numerous genes are measured in most proposed signatures. Herein, we propose a simple ratio-based biomarker (RBB) called direct leukocyte subpopulation-transcript abundance assay (DIRECT LS-TA) that recapitulates gene expressions of a single cell type in PB (i.e., monocytes). Based on single-cell RNA sequencing (scRNAseq) data and bulk expression data, IFI27 and SIGLEC1 are found as interferon-stimulated genes (ISGs) predominantly expressed by monocytes. The DIRECT LS-TA method can use a simple ratio of two genes measured in PB as an RBB to represent the target gene expression in monocytes without the need for monocyte purification. Both scRNAseq and bulk RNA sequencing datasets were used to evaluate the correlation between ISG expression in monocytes and PB, with a particular focus on monocyte expression of IFI27. An iceberg plot of bulk transcriptome data was used to identify genes that were predominantly expressed by monocytes in PB. DIRECT LS-TA RBBs of the three genes (IFI27, IFI44L and SIGLEC1) were evaluated by group-wise comparison, receiver operating characteristic and meta-analysis. In addition, the conventional interferon (IFN) score was evaluated for comparison of diagnostic performance. In viral infection datasets, DIRECT LS-TA of IFI27 (IFI27/PSAP or IFI27/CTSS) was most intensely activated (p value by t test <1e-9) and had the best area under the curve (0.94) among the three potential monocyte ISGs analysed. DIRECT LS-TA SIGLEC1 was also another monocyte biomarker but showed a lower activation (p<9e-5). IFI27/PSAP showed better diagnostic performance than the conventional IFN score. On the other hand, IFI44L was not a predominant monocyte expression gene. DIRECT LS-TA of IFI27 (IFI27/PSAP or IFI27/CTSS) measured in PB was the best biomarker of viral infection and IFN activation among ISGs predominantly expressed by monocytes. It performed even better than the conventional IFN score which required quantification of eight genes. The results suggest that DIRECT LS-TA of IFI27 is a monocyte-informative biomarker which is easy to determine in PB without the need for cell sorting.

Humans↗

PubMed2026

CT-Derived pelvic morphometry for preoperative risk assessment of recurrent unilateral inguinal hernia.

BACKGROUND: Recurrent inguinal hernia remains a significant challenge in abdominal wall surgery despite advances in mesh-based repair techniques and minimally invasive approaches. Although pelvic skeletal morphology has been implicated in inguinal hernia development, its association with recurrent disease remains incompletely understood. This study aimed to evaluate computed tomography (CT)-derived pelvic morphometric parameters and investigate their potential value in preoperative recurrence risk assessment. METHODS: This retrospective study included 251 male patients with preoperative abdominal CT examinations and complete clinical records who underwent elective inguinal hernia repair at a tertiary referral center. After applying the predefined eligibility criteria, 188 patients with unilateral inguinal hernias constituted the primary study cohort, including 162 primary and 26 recurrent unilateral hernias. The Radoievitch angle and Ami's line were measured independently by two blinded radiology residents using a standardized CT-based pelvic morphometric measurement protocol, and the mean values were used for analysis. Multivariable logistic regression and receiver operating characteristic (ROC) curve analyses were performed to evaluate the association between pelvic morphometric parameters and recurrent inguinal hernia. RESULTS: Patients with recurrent unilateral inguinal hernias demonstrated significantly greater affected-side Ami's line measurements (8.27 ± 0.63 vs. 7.90 ± 0.71 cm, p = 0.014) and larger Radoievitch angles (40.68 ± 4.02° vs. 38.80 ± 3.68°, p = 0.018) than patients with primary unilateral hernias. Both the Radoievitch angle (OR 1.14, 95% CI 1.01-1.28, p = 0.033) and Ami's line (OR 2.26, 95% CI 1.14-4.49, p = 0.020) remained independently associated with recurrent inguinal hernia after adjustment for age and body mass index. ROC analysis demonstrated modest discriminatory performance (AUC 0.634 for the Radoievitch angle and 0.633 for Ami's line), while the multivariable model incorporating age, body mass index, and Ami's line showed slightly improved discrimination (AUC 0.655). CONCLUSION: CT-derived pelvic morphometric parameters were independently associated with recurrent unilateral inguinal hernia. Although their individual discriminatory performance was modest, standardized CT-based pelvimetry may serve as an objective adjunctive tool for individualized preoperative recurrence risk assessment in patients who already undergo CT imaging for unrelated clinical indications. Prospective multicenter studies are warranted to validate these findings and determine their clinical applicability.

Humans↗

PubMed2026

Prognostic value of the lactate-to-albumin ratio in adult sepsis: An updated systematic review of prognostic evidence.

BACKGROUND: The lactate-to-albumin ratio (LAR) has emerged as a potential prognostic biomarker in sepsis. This systematic review evaluated the prognostic value of LAR for mortality in adults with sepsis or septic shock. METHODS: PubMed/MEDLINE, Embase, Web of Science, Scopus, and the Cochrane Library were searched from inception through March 2026. Studies evaluating mortality-related prognostic performance of LAR in adults with sepsis or septic shock were included. Risk of bias was assessed using the Quality In Prognosis Studies (QUIPS) tool. Adjusted odds ratios (ORs) and hazard ratios (HRs) were evaluated separately because of methodological heterogeneity. Discrimination was assessed using study-specific area under the curve (AUC), sensitivity, specificity, and LAR thresholds. RESULTS: Fourteen primary studies were included. Higher LAR was consistently associated with increased mortality across emergency department and intensive care populations. AUC values generally ranged from approximately 0.65 to 0.87, although one smaller cohort reported an AUC of 0.976. Several multivariable analyses demonstrated associations between higher LAR and mortality after adjustment for clinical covariates. Adjusted ORs and HRs were not pooled because of differences in LAR scaling, thresholds, mortality endpoints, and adjustment strategies. Considerable variability was observed in reported cut-offs and diagnostic performance. CONCLUSIONS: Higher LAR is associated with mortality in adult sepsis and may provide complementary prognostic information. However, clinical and methodological heterogeneity precludes a universal cut-off or single pooled adjusted effect. Standardized prospective multicenter studies are required before routine clinical implementation.

Humans↗

PubMed2026

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

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

Neural Networks, Computer↗

PubMed2026

Artificial intelligence for dental caries detection: An umbrella review.

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

Dental Caries↗

PubMed2026

Artificial Intelligence for Diagnosis, Risk Stratification, and Prognosis of Neuroblastoma - A Systematic Review and Meta-Analysis.

PURPOSE: To synthesizes evidence on artificial intelligence (AI) performance in neuroblastoma (NB) diagnosis, risk stratification, prognosis, and genomic characterization. MATERIALS AND METHODS: A systematic review and meta-analysis was conducted following PRISMA 2020 guidelines (PROSPERO: CRD42024539475) across five databases. Meta-analyses used random-effects models with logit-transformed Area Under the Curve (AUCs) and cluster-robust standard errors. AI models were classified as Machine Learning Models (MLM) or Hybrid Nomograms (HN) based on their construction methodology. RESULTS: Of 3,742 articles identified, 53 were included. MLMs demonstrated higher point estimates than radiologists in differential diagnosis (AUC: 0.87 vs. 0.83), though this difference was not statistically significant and carried substantial uncertainty. HNs achieved stronger performance in risk stratification (AUC: 0.87). AI-derived nomograms (AUC: 0.9) and gene signatures (AUC: 0.8) outperformed conventional prognostic markers descriptively. Chemotherapy response prediction remained below clinical utility thresholds across all model types. Only 33.9% of models reported calibration and 24.5% underwent external validation. CONCLUSIONS: AI demonstrates proof-of-concept across multiple NB clinical domains. However, clinical adoption remains premature given persistent gaps in external validation, calibration, dataset size, and pediatric-specific model development. Future studies should test these models prospectively in multicenter pediatric cohorts, ideally through COG or SIOPEN, using shared definitions for diagnosis, risk group, treatment response, and survival outcomes.

Humans↗

PubMed2026

Penalized Cumulative Probability Model for a Continuous Outcome Subject to Detection Limits.

Mixed-type outcome data occur when the outcome variable's distribution is a mixture of both continuous and discrete ordinal variables. Such mixed-type outcomes are common in biomedical, psychological, and the health sciences, particularly for variables having either a detection or quantitation limit. When interest lies in identifying a combination of genomic features associated with a mixed-type outcome, any method used would require a variable selection strategy for high-dimensional data. Unfortunately, few variable selection methods exist for modeling a mixed-type outcome when the covariate space is high dimensional. This study develops a high-dimensional penalized cumulative probability model (CPM), to allow for the identification of genomic features associated with mixed-type outcome of interest. We demonstrated how such model may be estimated using the iterative penalization procedure-the generalized monotone incremental forward stagewise (GMIFS) algorithm. The Model-X knockoffs procedure was combined with the estimation algorithm to control the false discovery rates (FDR) when performing variable selection. Through extensive simulation studies, our penalized CPM was shown to outperform alternative methods in terms of controlled variable selection performance by achieving high statistical power with the FDR being controlled at the target level. We demonstrate the utility of our method by applying it to predict estimated glomeruli filtration rate (eGFR) in kidney transplant recipients at 24 months post-transplant using baseline gene expression data as predictors. Our CPM model identified five genes associated with this mixed-type outcome which have important links to renal disease, which may provide prognostic guidance for kidney transplantation recipients.

Models, Statistical↗

PubMed2026

Lower androgen sulfate metabolites in women with hypermobile Ehlers-Danlos syndrome may be associated with changed metabolism and disposition.

Hypermobile Ehlers-Danlos Syndrome (hEDS), characterized by joint hypermobility and multisystem involvement, is the most common type of EDS. Its comorbidities are wide-ranging, reflecting the involvement of connective tissue and its role in a multitude of processes. hEDS has been hypothesized to have hormonal aspects since the disorder is diagnosed more often in women and symptom changes closely correlate with hormonal shifts. To better understand the etiology and biochemical changes in hEDS and its comorbidities, a multiple-omics study was performed in women, controls (n = 45) and those with hEDS (n = 45), alongside the collection of questionnaires related to symptom severity. Metabolomic evaluation was performed on serum samples and RNA isolated from fibroblasts cultured from skin punches was analyzed for transcriptomics. Samples from hEDS patients had statistically significantly lower levels of multiple androgen sulfate metabolites, compared with controls, driven largely by participants aged 30-49. Changes to other classes of steroid hormones (corticosteroids, progestogens, and estrogens) were largely not significant between hEDS and control groups. Transcriptomics of skin fibroblasts from hEDS patients revealed downregulation of multiple enzymes involved in biosynthesis, metabolism, and disposition of androgens, compared with controls. Multiple steroid hormones correlated with symptoms surveyed in 18-29 year old participants with hEDS. Shifts in steroid hormone metabolites in hEDS compared with controls may be due to changes to metabolism and disposition, but more validation is necessary to be conclusive. This data provides insights into the unclear links between steroid hormones and hEDS and its comorbidities.

Humans↗

PubMed2026

Complete genome sequence of the Anaplasma phagocytophilum clinical isolate NCH-1.

Anaplasma phagocytophilum is an obligate intracellular gram-negative bacterium and etiologic agent of human granulocytic anaplasmosis. A. phagocytophilum genomic sequencing has historically been performed via short-read platforms. Our optimized bacterial isolation protocol combined with Nanopore sequencing produced a single, closed 1,481,805 bp circular A. phagocytophilum strain NCH-1 chromosome.

Anaplasma phagocytophilum↗

PubMed2026

Frequent readmissions after hospitalization for alcohol withdrawal: a systematic review and meta-analysis.

BACKGROUND: Alcohol use disorder and alcohol withdrawal syndrome impose substantial clinical and economic burdens, with repeated hospitalizations being common. We aimed to systematically review readmission rates following inpatient detoxification, assess variation across study designs and hospital settings, and identify key risk and protective factors. METHODS: We performed a literature search in Embase and Pubmed on 10/04/2026 focusing on studies assessing in hospital alcohol detoxification. Exclusion criteria included studies on substance use other than alcohol and outpatient or residential treatment. Main outcome was rehospitalization, and meta-analysis was performed to estimate pooled readmission proportions. Secondary outcomes were risk factors and protective factors influencing the rate of rehospitalization. RESULTS: Twenty-five studies were included. The pooled proportion of readmissions following alcohol detoxification was estimated at 17% (95% CI: 14%-21%; 13 studies, n = 287,896) within 1 month, increasing to 44% (95% CI: 36%-52%; 8 studies, n = 2,877) at 1 year. Substantial between-study heterogeneity was observed. Subgroup analyses found no significant differences by hospital setting or time period. Findings for study aim and study design were mixed and based on limited data A small number of studies suggested associations with housing stability, employment, and treatment engagement. CONCLUSIONS: This meta-analysis suggests that approximately one in six patients are readmitted within 1 month and nearly half within 1 year after inpatient alcohol detoxification. However, readmission rates varied considerably across settings and populations. Future research should evaluate targeted interventions to reduce readmissions among high-risk patient groups.

Humans↗

PubMed2026

Surgical management and outcomes of total colonic aganglionosis in children: A systematic review and meta-analysis.

AIM: Total colonic aganglionosis (TCA) is a rare form of Hirschsprung disease, and there is no consensus regarding its optimal surgical management. This systematic review and meta-analysis aimed to evaluate different surgical approaches and outcomes in children with TCA. METHODS: A systematic search of PubMed/MEDLINE and Embase was performed for studies published between January 2000 and December 2025. The review followed PRISMA guidelines and was prospectively registered in PROSPERO (CRD420251078401). Eligible studies included patients aged ≤18 years with TCA who underwent conventional pull-through procedures (CPT; Duhamel, Soave, Swenson, Rehbein, and Ikeda-Soper) or non-conventional techniques (NCPT; STATE procedure, J-pouch, right- or left-sided colonic patch pull-through, and ileocecal patch). A subgroup analysis comparing Duhamel and ileoanal pull-through procedures (IAPT) was also performed. Outcomes included fecal incontinence, Hirschsprung-associated enterocolitis (HAEC), requirement for additional interventions, postoperative intestinal obstruction, and mortality. Meta-analysis was performed using jamovi software, version 2.3.28, with p < 0.05 considered statistically significant. RESULTS: Seven studies including 134 patients compared CPT (n = 85) with NCPT (n = 49), and ten studies including 274 patients compared Duhamel (n = 143) with IAPT (n = 131). Across both comparisons, pooled odds ratios (ORs) showed no statistically significant differences in fecal incontinence, HAEC, requirement for additional interventions, postoperative intestinal obstruction (Duhamel vs IAPT only), or mortality. For CPT versus NCPT, the pooled ORs were 1.1 for fecal incontinence (95% CI, 0.44-2.73; p = 0.837), 1.1 for HAEC (95% CI, 0.49-2.71; p = 0.743), 4.3 for requirement for additional interventions (95% CI, 0.86-22.1; p = 0.074), and 3.4 for mortality (95% CI, 0.52-21.5; p = 0.198). For Duhamel versus IAPT, the pooled ORs were 1.4 for fecal incontinence (95% CI, 0.60-3.36; p = 0.423), 0.6 for HAEC (95% CI, 0.22-2.06; p = 0.503), 1.8 for requirement for additional interventions (95% CI, 0.62-5.50; p = 0.262), 1.1 for postoperative intestinal obstruction (95% CI, 0.21-6.01; p = 0.875), and 1.03 for mortality (95% CI, 0.25-4.20; p = 0.965). CONCLUSION: No statistically significant differences were identified between CPT and NCPT or between Duhamel and IAPT for the evaluated outcomes in children with TCA. However, the absence of statistically significant differences should not be interpreted as evidence of equivalence, particularly given the small sample sizes, wide confidence intervals, and clinical and methodological heterogeneity of the studies included. The choice of surgical approach should be individualized according to disease extent, patient-specific factors, institutional experience, and surgical expertise. TYPE OF STUDY: Meta-analysis. LEVEL OF EVIDENCE: III.

Humans↗

PubMed2026

Oxygen-controlled gamma-irradiation and annealing enable terminal processing of collagen-based biomaterials.

Gamma irradiation is a widely adopted method for terminal sterilization of medical devices; however, its application to collagen-based extracellular matrix (ECM) materials remains limited due to radiation-induced degradation of structural integrity and mechanical performance. Here, we present an engineered terminal-processing strategy that combines oxygen controlled gamma irradiation (25-30 kGy) with post-irradiation dry-heat annealing to preserve ECM functionality while achieving effective sterilization. By modulating oxygen availability during irradiation, this approach alters radical reaction pathways, suppresses oxygen-mediated oxidative degradation, and generates a metastable radical-containing intermediate, which is subsequently converted into a structurally stabilized collagen network through thermal annealing. As a result, the treated matrices preserved ECM integrity and recovered clinically relevant mechanical properties. Furthermore, the process achieved cumulative viral reductions exceeding 6 log10 across a representative panel including enveloped and non-enveloped DNA and RNA viruses, demonstrating compatibility with sterility assurance and viral safety requirements for biologically derived medical devices. Notably, preliminary observations indicate that mechanical integrity can be partially preserved even at elevated irradiation doses up to 50 kGy, suggesting potential applicability to sterilization validation frameworks requiring higher assurance levels. Overall, this work establishes a mechanistically grounded terminal-processing paradigm that enables control of radical fate, decouples sterilization efficacy from material degradation, and integrates sterilization, viral safety, and functional preservation into a unified and scalable framework for collagen-based biomaterials. This concept repositions gamma-irradiation from a purely degradative process to a controllable tool for tuning collagen structure and performance.

Gamma Rays↗

PubMed2026

Influence of Immediate Post-Bleaching Polishing on Enamel Color, Morphology, and Sensitivity: A Randomized Clinical Trial.

OBJECTIVE: This study evaluated the influence of polishing on enamel color change after in-office bleaching treatment on tooth morphology and sensitivity. MATERIALS AND METHODS: A total of 50 volunteers were randomized into two groups (n = 25): in-office bleaching with 35% hydrogen peroxide gel for 45 min without polishing (GSEM) or with polishing (GP). Color analysis was performed four times, at the beginning of the starting line and immediately after the first, second, and third bleaching sessions with a spectrophotometer. A qualitative analysis of enamel morphology was performed under a scanning electron microscope. Tooth sensitivity was assessed daily using the Visual Analog Scale (α = 0.05). RESULTS: There was no statistically significant difference (p > 0.05) in tooth color change when comparing ΔE, ΔE00, and ΔWID between the groups. The enamel surface showed larger areas of irregularities and depressions in the GP group than in the GSEM group. There was no difference in tooth sensitivity (p > 0.05) between the groups. CONCLUSIONS: Polishing after whitening in the office does not change the color and sensitivity of the tooth but promotes greater changes in the morphology of the enamel, such as increased surface roughness. CLINICAL RELEVANCE: Polishing immediately after teeth whitening causes greater changes in enamel surface morphology.

Humans↗

PubMed2026

Acute pre-exercise oral intake of cacao polyphenols attenuates central fatigue development during sustained low-intensity ankle dorsiflexion exercise in healthy young male adults.

This double-blind, randomized, crossover study investigated whether acute cacao polyphenol (CP) ingestion attenuates neuromuscular fatigue in 19 healthy young male adults. After consuming CP or placebo, participants performed sustained isometric ankle dorsiflexion at 25% of maximal voluntary isometric contraction (MVIC) torque until task failure. Neuromuscular function (MVIC torque, voluntary activation [VA%], doublet torque) and electromyographic activity were assessed before, immediately after, and during recovery (1 and 5 min). Salivary chromogranin A and α-amylase were measured at baseline and 1 min post-task. Only VA% and chromogranin A showed significant condition × time interactions (p = 0.027-0.039). VA% significantly decreased from before to immediately after the task and 1 min post-task in both conditions (p ≤ 0.002), with significantly higher values in the CP condition than in placebo immediately after and 1 min post-task (p ≤ 0.037). Chromogranin A significantly increased from baseline to 1 min post-task in the placebo condition (p < 0.001) but not in the CP condition (p = 0.083). These findings suggest that acute CP ingestion attenuates the decline in central motor drive and autonomic stress responses following strenuous exercise, without altering performance or peripheral recovery, supporting its potential as a nutritional strategy for modulating central fatigue.

Humans↗

PubMed2026

Integrated multi-omics profiling of amniotic fluid identifies predictive biomarkers for fetal growth restriction trajectories.

BACKGROUND: Fetal growth restriction (FGR) is a complex condition with highly heterogeneous clinical outcomes, making prenatal distinction between transient and persistent growth failure challenging. This study aims to identify amniotic fluid (AF) biomarkers capable of differentiating distinct FGR trajectories and characterizing persistent growth failure mechanisms. METHODS: Integrated proteomic and metabolomic profiling was performed on AF samples from transient FGR (n = 11), persistent FGR (n = 9), and healthy controls (n = 13). Diagnostic and prognostic models were developed using multivariate analysis. Selected protein candidates were validated via ELISA in an independent cohort (n = 69). RESULTS: Multi-omics analysis revealed distinct molecular signatures for FGR stratification. A two-protein diagnostic panel (PDGFA and phospho-STAT5A) achieved an AUC of 1.000 in the discovery stage and 0.780 in the external validation cohort. For prognostic assessment, a molecular signature including IREB2, HLA-C, and PLXNB2 accurately predicted persistent growth failure from transient recovery (AUC = 0.966). Cross-platform integration highlighted the mass spectrometry-derived WASHC2C as a central hub protein with a significant progressive increase across the control, transient, and persistent groups (p < 0.001). CONCLUSIONS: This study establishes a multi-omics framework for prenatal FGR stratification. Our findings identify distinct molecular signatures reflecting the intrauterine environment and provide high-performance molecular tools for predicting divergent fetal growth trajectories to guide personalized clinical decision-making.

Humans↗