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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

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↗

PubMed2026

Exploratory identification and cellular functional characterization of ppiabl as a candidate gene associated with growth traits in Paralichthys olivaceus.

The Japanese flounder (Paralichthys olivaceus) is an important mariculture species. However, the genetic mechanisms underlying its growth traits remain poorly understood. To explore the genetic basis of growth variation, whole-genome resequencing was performed in a cultured cohort of 60 individuals, followed by exploratory genome-wide association analysis and candidate-gene prioritization. The results revealed heritability estimates of 0.40 for body weight and 0.24 for body length, with substantial overlap in associated loci between the two traits. Exploratory association and variant-annotation analyses prioritized ppiabl, which carries a nonconservative missense variant, as a candidate gene for further investigation. Tissue expression analysis showed that ppiabl was highly expressed in muscle tissue. This gene encodes a protein belonging to the conserved peptidyl-prolyl cis-trans isomerase family. In Japanese flounder primary muscle cells, ppiabl knockdown was associated with altered expression of growth-related genes and an increased G1-phase fraction, whereas overexpression produced changes in the opposite direction. In line with this, fast-growing individuals were found to have significantly larger muscle fiber areas than slow-growing ones. These findings suggest that ppiabl may be involved in muscle-related cellular processes associated with growth variation in Japanese flounder, although its contribution to whole-animal growth requires further validation. Overall, this exploratory study prioritizes ppiabl as a candidate gene potentially associated with growth-related cellular processes in Japanese flounder, although validation in larger independent populations and in vivo models is required.

Animals↗

PubMed2026

Plasma proteomic profiling characterizes candidate biomarkers of perimesencephalic non-aneurysmal subarachnoid hemorrhage.

OBJECT: This study aims to explore the plasma proteomic profiles of angiographically confirmed pmSAH and aSAH, and to identify candidate protein biomarkers for discriminating these subtypes on a biological level. METHODS: The differentially abundant proteins of plasma samples from patients with pmSAH (n = 30) and aSAH (n = 30) were analyzed by data-independent acquisition proteomics, and candidate biomarkers were screened. RESULTS: 291 candidate biomarkers were obtained that could be used to distinguish pmSAH patients from aSAH patients, among which 76 were upregulated and 215 were downregulated in pmSAH. Subsequently, the 10 candidate biomarkers were validated by enzyme-linked immunosorbent assay in a validation cohort of 72 subjects. ORM1, ORM2, HP and NMNAT1 were specifically down-regulated in the pmSAH group, while ANP32A was specifically up-regulated in the pmSAH group. FGL2 was specifically up-regulated in the aSAH group. The combined model of ORM2, HP and ANP32A had the best discriminative power (AUC = 0.880). CONCLUSIONS: This study identified ORM2, HP, and ANP32A as candidate biomarkers reflecting biological differences between pmSAH and aSAH. SIGNIFICANCE: Although some proteomic studies have analyzed aneurysmal subarachnoid hemorrhage, to date, there have been no reports on the circulating proteomic analysis of pmSAH. Comparative analysis of the circulating proteomic differences between pmSAH and aSAH may not only help understand the causes of pmSAH, but also contribute to a deeper understanding of mechanisms showing how pmSAH differs from the formation and rupture mechanisms of intracranial aneurysms.

Humans↗

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

Transcriptomic responses of Porphyrophora sophorae larvae during licorice root colonization reveal coordinated remodeling of translation, mitochondrial energy metabolism and defense-related genes.

BACKGROUND: Porphyrophora sophorae is a subterranean piercing-sucking scale insect that damages licorice (Glycyrrhiza uralensis) roots, but the molecular responses associated with larval root colonization remain insufficiently defined. METHODS: We compared non-parasitic larvae (NP) and root-colonizing larvae (RC) using six RNA-seq libraries, de novo transcriptome assembly, DESeq2-based differential expression analysis, GO/KEGG enrichment, annotation-based candidate gene screening, and RT-qPCR validation of selected genes. RESULTS: Sequencing yielded 260.91 million clean reads, and de novo assembly produced 60,794 non-redundant transcripts. DESeq2 identified 703 FDR-significant DEGs, including 49 upregulated and 654 downregulated genes in RC larvae. Upregulated genes were mainly associated with translation- and ribosome-related processes, whereas downregulated genes were enriched in mitochondrial, oxidation-reduction, energy metabolism, and oxidative phosphorylation-related functions. Annotation-based screening identified 75 FDR-significant candidate genes associated with chemosensation, defense-related responses, and energy metabolism, with mitochondrial energy metabolism-related genes forming the largest module. RT-qPCR validation based on the raw Ct data showed concordant expression directions for ten selected transcript targets. CONCLUSIONS: Root colonization in P. sophorae larvae was associated with coordinated transcriptional remodeling involving selective activation of translation-related processes, adjustment of mitochondrial energy metabolism, and changes in defense-related gene expression. These results provide candidate molecular targets for future functional studies of host contact, feeding establishment, and physiological adjustment in this subterranean scale insect.

Animals↗

PubMed2026

Plasma proteomics: considerations for preanalytical variability; a systematic review with narrative synthesis.

BACKGROUND: The plasma proteome (PP) is a dynamic system subject to pathology-associated changes and a focus for novel disease biomarker discovery. Disease-related PP research assumes protein concentrations in test specimens accurately reflect the in vivo milieu. However, measures to maintain the physicochemical integrity of the proteome before assay are often rudimentary, poorly described, or lacking standardisation in published studies. Contrastingly, in laboratory medicine, there is an expectation that errors in the so-called "preanalytical phase" (PAP) that impact patient results are understood, monitored, and mitigated against, while also being well described in research publications. There is therefore scope for good practice from laboratory medicine to inform PP research workflows. This review considers factors in the PAP which may impact the validity of PP results. CONTENT: A systematic review was conducted per PRISMA guidelines, limited to English-language peer-reviewed studies (2014-2024). Candidate studies were imported, screened, and managed using Covidence systematic review software. SUMMARY: 15 eligible studies were reviewed, covering many relevant processes. 11 studies reported statistically significant differences in PP due to factors in the PAP. Temperature and time-to-processing were the most commonly reported factors affecting the PP, with significant effects reported in 8 studies. OUTLOOK: PAP variability can significantly affect results in PP studies. Careful consideration of the effect of each stage of the PAP is needed when working with the PP. In multicenter studies, pre-defined and research question-specific sample processing workflows are essential for reducing PAP variability, which helps ensure the validity of PP studies.

Humans↗

PubMed2026

Imaging techniques for assessing the hand in systemic sclerosis: a systematic review.

BACKGROUND: Systemic sclerosis (SSc) is a rare autoimmune connective tissue disease frequently associated with hand involvement, leading to significant functional impairment. Imaging techniques provide unique opportunities to visualize and quantify structural and functional abnormalities of the hand, supporting diagnosis, monitoring, and treatment evaluation. This systematic review summarizes the imaging techniques used in SSc. METHODS: A systematic search of PubMed and Embase was conducted. Eligible studies included original research articles in English that applied or evaluated imaging techniques of the hands in SSc, published after 2000. Ultrasound and nailfold capillaroscopy were excluded, given their established use. Screening was performed independently by two authors. Findings were synthesized by clinical manifestations, study quality was assessed using the QUADAS-2 tool. RESULTS: Sixty-one studies met the inclusion criteria. In total, 25 distinct imaging techniques were identified, enabling assessment of various hand structures, including vascular involvement, inflammation, fibrosis, calcifications, erosions, and bone marrow edema. Vascular imaging was most extensively studied, particularly in the context of Raynaud's phenomenon and digital ischemia, with multiple techniques demonstrating impaired perfusion and altered thermoregulatory responses. MRI consistently detected subclinical inflammatory and erosive changes of joints and soft tissues,. CT-based techniques provided detailed assessment of calcinosis cutis, while optical and photoacoustic methods showed promise for quantifying skin fibrosis. CONCLUSION: Imaging techniques provide valuable, complementary insights into hand involvement in SSc, often revealing subclinical disease. Despite promising results, limited standardization and longitudinal validation currently restrict clinical implementation. Future studies should focus on harmonizing protocols and validating against clinically meaningful outcomes.

Humans↗

PubMed2026

Comparative transcriptomic analysis of the gills and hepatopancreas of freshwater-cultured Litopenaeus vannamei under chronic nitrite stress.

To investigate the differences in molecular responses between the gills and hepatopancreas of freshwater-cultured Litopenaeus vannamei under chronic nitrite stress, a 30-day chronic stress experiment was conducted with a control group and a stress group. Transcriptomic analysis of the gills and hepatopancreas was performed using Illumina sequencing; differentially expressed genes (DEGs) were identified, and GO, KEGG, GSEA, PPI, and RT-qPCR validation were carried out. The results showed that 196 DEGs (161 up-regulated and 35 down-regulated) were identified in the gills, and 287 DEGs (199 up-regulated and 88 down-regulated) in the hepatopancreas, with only 18 DEGs shared between the two tissues. DEGs in the gills were enriched in oxidoreductase activity, glycerophospholipid metabolism, and tyrosine metabolism; DEGs in the hepatopancreas were enriched in lipid transporter activity, phagosome, ECM-receptor interaction, and riboflavin metabolism. GSEA revealed significant suppression of the mTOR pathway in the gills and the Polycomb complex pathway in the hepatopancreas. PPI network analysis identified hub genes P5CS and eEF2 in the gills, and PER, TUBB1, SHMT, and TUBB4B in the hepatopancreas. RT-qPCR validation was consistent with the RNA-seq results (R2 = 0.764). This study indicates that, under chronic nitrite stress, the gill response is centered on redox regulation and inhibition of growth metabolism, whereas the hepatopancreas response primarily involves lipid transport, cytoskeletal remodeling, and phagosome activation. The two tissues synergistically adapt through fundamental biosynthetic and motor protein pathways. This research provides molecular evidence for deciphering the nitrite tolerance mechanisms in freshwater-cultured shrimp.

Animals↗

PubMed2026

Metabolic and endocrine modulation of the gut-adipose tissue axis via pro-, pre-, and postbiotics in overweight dogs: A systematic review.

Canine obesity is a complex metabolic disorder driven by luminal dysbiosis, impaired gut barrier function, and metaflammation. Following PRISMA 2020 guidelines, this systematic review evaluated the efficacy of pro-, pre-, and postbiotics in modulating the gut-adipose tissue axis in overweight dogs (BCS ≥ 6/9) or diet-induced obesity models. Searches across PubMed and Dimensions (April 2026) identified seven eligible experimental trials. Results suggest that postbiotic Bifidobacterium animalis subsp. lactis CECT 8145 reduced postprandial glucose AUC by 6 % strictly during energy restriction. Pasteurized Akkermansia muciniphila postbiotics limited diet-induced weight gain, though glucoregulatory impacts were highly strain-specific (AKK2 reduced fasting glucose and insulin resistance indexes, whereas EB-AMDK19 exerted no significant effect). Specific probiotics (including Enterococcus faecium, Bifidobacterium lactis, Lactiplantibacillus plantarum and Bifidobacterium breve) attenuated fasting hyperinsulinemia and preserved circulating adiponectin, but lipid profile improvements (triglycerides and total cholesterol) were inconsistent across trials. In dogs, increased luminal short-chain fatty acids are not consistently mirrored by endocrine responses, so the coupling between microbial metabolites and incretin signaling remains incomplete. A critical lack of standardized reporting for species-validated insulin sensitivity metrics was identified. In conclusion, microbiome-targeted therapies, particularly inanimate postbiotics, may represent useful adjunctive strategies to mitigate metabolic dysregulation in obesogenic environments. However, clinical efficacy remains strictly strain-specific and dependent on host energy balance. Given the scarcity of high-certainty evidence, future trials must integrate dynamic physiological assessments with species-validated surrogate indexes alongside standardized dietary controls.

Animals↗

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↗

PubMed2026

Protein profiling and GC-MS product analysis provide insights into lignite solubilization and bioconversion by Lysinibacillus sphaericus strain SH19.

Lignite biosolubilization offers a mild route for valorizing low-rank coal, although the microbial processes that accompany solubilization remain incompletely defined. Here, an endogenous isolate designated Lysinibacillus sphaericus strain SH19 was evaluated using nitric-acid-pretreated Shengli lignite. Under the selected working conditions (4 M nitric-acid pretreatment, initial pH 8, 40°C, and 16 days), the apparent solubilization rate reached 66.81%. Changes in A450, residual solid mass, culture pH, and extracellular protein concentration showed that chemical pretreatment and bacterial culture were both associated with the release of soluble lignite-derived material. SDS-PAGE and two-dimensional electrophoresis revealed treatment-associated differences in extracellular and intracellular protein patterns. LC-MS/MS analysis of excised protein spots yielded 85 candidate protein assignments; the revised supplementary table reports PEAKS scores, sequence coverage, peak area, and unique-peptide counts and highlights the limited support for several entries. GC-MS analysis produced 33 tentative library assignments in the solubilized fraction, but siloxane- and silyl-related signals were treated as possible analytical background, and no pathway was inferred from these assignments alone. Together, the data identify strain SH19 as a promising lignite-biosolubilizing isolate and provide candidate proteins and product signals for future validation. The proposed process model remains exploratory because direct enzyme assays, inhibitor experiments, carbon-balance measurements, transcriptomic or genetic validation, complete GC-MS blank subtraction, and authentic-standard confirmation were not available.

Bacillaceae↗

PubMed2026

Comprehensive identification of carboxylic acids by using bromine isotope-based chemical isotope labelling and structure-guided molecular network.

Carboxylic acids (CAs) are important contributors to the flavor quality of sauce-flavor Chinese Baijiu, yet their comprehensive analysis remains challenging due to poor ionization efficiency, weak chromatographic retention, and limited annotation capability. Herein, we developed a workflow for the high-coverage discovery and annotation of CAs in Baijiu by coupling chemical isotope labeling-liquid chromatography-mass spectrometry with a structure-guided molecular network strategy (SGMNS). A bromine-containing derivatization reagent, 1-(3-aminopropyl)-3-bromoquinolin-1-ium bromide (APBQ), was designed and synthesized to exploit the natural isotope distribution of bromine and characteristic MS/MS fragmentation behavior. Following APBQ derivatization, the target CAs showed superior chromatographic retention and favorable analytical performance. Based on isotopic peak pairing in MS1 and diagnostic fragment validation in MS2, 372 potential CA derivatives were discovered from pooled Baijiu samples and 355 of them were validated by diagnostic fragments in MS2 spectra. To address the scarcity of derivatized spectral libraries, SGMNS was employed for annotation using a background network constructed from APBQ-labeled candidates derived from the Expanded Chinese Baijiu Compound Database. The developed method was further applied to profile Baijiu samples, revealing pronounced differences in CA composition across the seven fermentation rounds. Notably, rounds 3 to 5 exhibited the largest numbers of differential CAs. This study provided an effective analytical strategy for large-scale CA profiling, offering new insight into the chemical basis of flavor formation during multi-round fermentation of sauce-flavor Baijiu.

Isotope Labeling↗

PubMed2026

Smartphone Apps for Preventing Adolescent Health Problems Among Health Care Professionals: Systematic Search and Quality Assessment.

BACKGROUND: Health care professionals must consider multiple dimensions of prevention when consulting with adolescents. Identifying risky behaviors early in adolescence is crucial for reducing both morbidity and mortality. General practitioners are increasingly eager to incorporate digital tools for prevention into their consultations with adolescents; however, the relevance and clinical validity of these digital tools are not always established or well-known. Consequently, primary care professionals require guidance and support in selecting relevant mobile health (mHealth) tools. OBJECTIVE: The aim of this study is to identify relevant and useful digital apps to help primary care professionals detect at-risk adolescents across all recommended areas of prevention: orthopedics, mental health, substance abuse, risk behaviors, sexual health, vaccinations, social relationships, and nutrition. METHODS: A systematic review of smartphone apps, with an analysis of content quality, was carried out by 4 researchers using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) checklist. The App Store and Google Play Store platforms were surveyed. The inclusion criteria were as follows: free of charge, date of last update, availability in French or English, relevance of the preventive approach to adolescents, and scientific validation. Four health care professionals assessed the apps: 2 selected the apps relevant to health care professionals, then 3 analyzed these apps using the French version of the Mobile App Rating Scale (MARS-F). Intraclass correlation coefficient, model (2,1) (2-way random effects, absolute agreement, single measures); standard error of measurement; and mean absolute error were also calculated. RESULTS: A total of 976 apps were identified, 49 of which had disappeared from the platforms prior to analysis. Nine apps were retained. Seven (0.72%) were included after evaluation using the MARS-F: 2 on mental health and 5 on sexual health (including 3 on contraception only). The mean MARS-F interrater score ranged from 2.5/5 to 3.8/5. The global MARS-F score demonstrated a pooled SD of 0.60 and an intraclass correlation coefficient (2,1) of 0.0003, resulting in a calculated standard error of measurement of 0.60. The average discrepancy between raters was a mean absolute error of 0.53. CONCLUSIONS: No similar studies have been identified in the literature that specifically focus on mobile apps designed to support health care professionals in delivering preventive care to adolescents. Of the 8 areas of prevention identified as relevant for adolescents, only 3 are addressed by the apps validated through our methodology (5 focus on sexual health). Consequently, current apps are insufficient to support health care professionals in their overall preventive work with adolescents. Such a review should be conducted systematically prior to the development of any new tool to prevent duplication and channel creative efforts toward truly innovative digital solutions. Furthermore, a thorough analysis of relevant, recommended websites is essential, as these resources complement the use of mobile apps designed for health care professionals.

Humans↗

PubMed2026

Accurate quantification of canine mitochondrial DNA copy number from canine blood and brain samples.

Acute brain injury is difficult to evaluate in veterinary medicine and tools to investigate the potential involvement of mitochondrial involvement are limited. The brain is highly enriched in mitochondria and contains thousands of copies of mitochondrial DNA (mtDNA) per cell, but robust methods for quantifying mitochondrial DNA copy number (mtDNA-CN) in canine tissues are lacking. We describe the development of a quantitative real-time PCR assay for absolute measurement of mtDNA-CN which was validated in canine blood and brain tissue. To minimize amplification of nuclear mitochondrial insertion sequences (NumtS) and repetitive regions, species-specific oligonucleotide primers were designed following in silico genomic filtering. The assay was applied to a small pilot cohort comprising blood samples from dogs with and without acute brain injury (n = 4-6 per group) and cerebral cortex samples (n = 1 per group) to assess feasibility and biological plausibility. In non-brain injury dogs, blood mtDNA-CN ranged from 98 to 288 copies per nuclear genome (mean 193 ± 72), while values in brain-injured cases ranged from 163 to 228 copies per genome (mean 200 ± 33). Cerebral cortex samples exhibited higher mtDNA-CN than blood, consistent with known tissue-specific mitochondrial enrichment. In a single brain-injured case with serial sampling, mtDNA-CN increased over five days. This study presents a validated assay and pilot data for mtDNA-CN quantification in canine samples. While not powered for biomarker evaluation, this method may enable future studies of mitochondrial dynamics in canine brain injury and metabolic disease.

Animals↗

PubMed2026

Improved comprehensive profiling of fecal bile acids through chemical derivatization combined with HPLC-MS/MS analysis.

Bile acids (BAs) facilitate the digestion and absorption of fats and influence lipid and glucose homeostasis, making them potential therapeutic targets for obesity and related metabolic disorders. The liver and intestinal microbiota modify BAs structurally, generating diverse chemical forms and isomers. Comprehensive profiling of the BA pool is critical for understanding their key biological functions and as a therapeutic approach for related diseases. High-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) is usually chosen as the preferred method for BA detection due to the complex chemical structures, the wide range of actual concentrations and the complexity of fecal sample matrices. However, free BAs are difficult to ionize, resulting in low detection signals and a lack of characteristic structural fragments to assist in structural identification. In this method, the labeling reagent (2-aminoethyl) trimethylammonium (AETMA) is employed to label the carboxyl group of BAs. Compared with underivatized BAs, the detection sensitivity of unconjugated BAs was enhanced by 25-180 fold, while that of conjugated BAs increased by 6-160 fold. It also generates unique fragment ions and enhances MS response, facilitating the discovery of potential BAs. Methodological parameters were validated using 38 BAs as representatives. Through methodological validation, it was verified that the precision, recovery, matrix effect and stability parameters of the method met acceptable criteria. We also identified 61 confirmed BAs and 55 additional candidate BAs in human pooled fecal samples. It has been successfully applied to fecal BA analysis in obese populations, providing valuable insights into potential therapeutic strategies for obesity.

Tandem Mass Spectrometry↗

PubMed2026

Prevalence of Claudin 18.2 Expression in Gastric and Gastroesophageal Junction Adenocarcinoma: A Systematic Review and Meta-Analysis.

BACKGROUND: Claudin 18 isoform 2 (CLDN18.2) has emerged as a clinically validated therapeutic target in gastric and gastroesophageal junction (GEJ) adenocarcinoma following the regulatory approval of zolbetuximab in combination with first-line chemotherapy. Accurate prevalence data at the clinically validated immunohistochemical threshold are essential for patient selection, healthcare resource planning, and treatment strategy. Reported prevalence estimates vary widely across studies due to differences in populations, methodologies, and immunohistochemical protocols. This systematic review and meta-analysis aimed to generate a robust pooled prevalence estimate of CLDN18.2 expression at the threshold used in pivotal phase III trials. METHODS: PubMed, Embase, and the Cochrane Library were searched from database inception through March 12th, 2026. Studies reporting CLDN18.2 expression in gastric or gastroesophageal junction adenocarcinoma using the ≥ 75% moderate-to-strong membranous staining threshold were included. Prevalence proportions were pooled using a random-effects model with logit transformation and restricted maximum-likelihood estimation of between-study variance. Heterogeneity was assessed using the I² statistic and Cochran's Q test, and a 95% prediction interval was calculated. Pre-specified subgroup analyses assessed antibody clone and geographic region, with additional exploratory analyses according to disease setting and specimen type. Sensitivity analyses were performed to assess the robustness of the pooled estimate. RESULTS: Twenty-two predominantly retrospective cohort studies comprising 12,173 patients were included. The pooled prevalence of CLDN18.2 positivity using a random-effects model was 33.99% (95% CI: 30.13%-38.07%; 95% prediction interval: approximately 18%-55%), with high between-study heterogeneity (I² = 92.4%). Subgroup analysis by antibody clone showed no statistically significant difference between studies using the 43-14 A clone (32.79%, 95% CI: 28.86%-36.97%) and those using other reported antibody clones (41.74%, 95% CI: 26.76%-58.42%; p = 0.281). One study with an unreported antibody clone was excluded from this subgroup analysis. Geographic subgroup analysis excluding the multinational Shitara et al. cohort demonstrated a non-significant trend toward higher prevalence in non-Asian populations (37.85%, 95% CI: 31.59%-44.54%) compared with Asian populations (32.10%, 95% CI: 27.28%-37.34%; p = 0.169). All three sensitivity analyses confirmed robustness of the pooled estimate. No significant evidence of publication bias was detected (Egger's test p = 0.56). CONCLUSIONS: Approximately one-third of patients with gastric and GEJ adenocarcinoma express CLDN18.2 at the clinically validated ≥ 75% threshold. However, because the included studies encompassed heterogeneous disease settings and were predominantly HER2-unselected, the pooled estimate should not be interpreted directly as the proportion of patients eligible for zolbetuximab. The estimate was robust across sensitivity analyses and provides an evidence base for understanding CLDN18.2 prevalence and biomarker-testing requirements. Standardisation of immunohistochemical assessment methods is warranted to reduce between-study heterogeneity in future research.

Humans↗

PubMed2026

The future of pediatric vesicoureteral reflux management.

BACKGROUND AND OBJECTIVE: Vesicoureteral reflux (VUR) is a common condition in pediatric urology, yet important uncertainties persist regarding risk stratification, imaging strategies, and prevention of long-term renal damage. Emerging technologies may help address these challenges. This review provides a forward-looking overview of recent advances in artificial intelligence (AI) and immunomodulation that may influence future management of pediatric VUR. METHODS: A forward-looking literature review was performed using the PubMed database (January 2000-March 2025), focusing on studies addressing AI, immunomodulation, or vaccination in the context of VUR and urinary tract infections. Criteria of inclusion were the relevance to pediatric VUR, the novelty of the proposed concept, the potential clinical implications and, for the AI literature, the existence of a clinical evaluation of the algorithm on a dataset from patients. KEY FINDINGS AND LIMITATIONS: AI-based models show promising performance in supporting clinical decision-making, including prediction of the need for voiding cystourethrography, automated grading of VUR, estimation of recurrent urinary tract infection risk and prediction of chemoprophylaxis. These tools may facilitate more individualized diagnostic and therapeutic strategies, although current evidence is largely retrospective and requires prospective validation. Immunization and immunomodulatory approaches aim to reduce infection burden and modulate inflammatory pathways associated with renal scarring. While early experimental and adult clinical data are encouraging, pediatric-specific evidence remains limited, and clinical applicability in children with VUR is not yet established. CONCLUSION: Artificial intelligence and immunologically targeted strategies represent complementary, emerging approaches that may contribute to more personalized management of pediatric VUR. At present, both should be regarded as exploratory tools whose clinical impact will depend on further validation and appropriately designed pediatric studies.

Humans↗