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PubMed2026

Candidate biomarkers for early Giardia duodenalis infection revealed by time-resolved secretome proteomics.

Giardia duodenalis is a zoonotic protozoan parasite that causes giardiasis in humans and other mammals. Early diagnosis remains challenging because current diagnostic methods, including microscopy and enzyme-linked immunosorbent assays (ELISAs), primarily detect established infections. Consequently, a critical diagnostic gap exists during the early stage of infection within the first 2-48 h following exposure. To address this limitation, we characterized the proteins released by in vitro-cultured G. duodenalis trophozoites under serum-free conditions and evaluated their potential as early diagnostic biomarkers. Proteomic analysis of culture supernatants collected during early trophozoite incubation identified 31,773 peptides corresponding to 2504 quantifiable proteins. Temporal profiling showed distinct secretion patterns, including proteins that peaked during the early stage, progressively accumulated over time, or remained persistently abundant throughout the incubation period. Based on their secretion characteristics and predicted immunogenic properties, five candidate biomarkers were selected for further evaluation. Polyclonal antibodies raised against selected candidates successfully detected the corresponding proteins in serum-free culture supernatants, providing preliminary evidence for their potential utility as early-stage diagnostic targets. These findings identify stage-associated candidate proteins that may serve as a resource for future early giardiasis diagnostic development, provide a valuable resource for investigating host-parasite interactions, and establish a foundation for future diagnostic assay development. However, further validation in clinical and biological samples is required to confirm their diagnostic applicability. SIGNIFICANCE: Giardiasis, caused by Giardia duodenalis, is a major diarrheal disease worldwide. Although enzyme-linked immunosorbent assays (ELISAs) provide rapid detection, their diagnostic utility is limited by the lack of biomarkers capable of identifying infection during its earliest stages, creating a critical gap in the detection of active infection within 2-48 h following exposure. Using data-independent acquisition proteomics, this study provides a time-resolved characterization of proteins released by G. duodenalis trophozoites into serum-free culture supernatants. Our findings reveal temporal secretion dynamics of protein secretion and identify candidate biomarkers with potential utility for the development of early-stage diagnostic assays pending rigorous biological and clinical validation. In addition, this proteomic resource provides a foundation for investigating host-parasite interactions and may facilitate the development of future point-of-care diagnostic strategies.

Giardiasis↗

PubMed2026

An Update on Inborn Errors of V(D)J Recombination.

V(D)J recombination is the fundamental process by which developing T and B lymphocytes generate diverse antigen receptors, enabling adaptive immunity. This tightly regulated program operates exclusively in lymphoid precursors during G1 phase and depends on the lymphocyte-specific RAG1-RAG2 recombinase to introduce programmed DNA double-strand breaks at recombination signal sequences, followed by repair through the classical nonhomologous end joining (c-NHEJ) pathway. Disruption of any step in this molecular choreography compromises antigen receptor diversity and underlies a spectrum of inborn errors of immunity (IEIs), ranging from severe combined immunodeficiency (SCID) to immune dysregulation with autoimmunity and granulomatous disease. In this review, we place disorders of V(D)J recombination within the broader framework of T-cell development, detailing the temporal waves of recombinase activity, chromatin accessibility, and DNA damage responses that guide thymocyte differentiation. We discuss pathogenic variants affecting the cleavage phase [RAG1, RAG2, and the recently identified RAG cochaperone NudC domain-containing 3 (NUDCD3)], end processing (ARTEMIS), ligation and repair (LIG4, XLF, XRCC4, PRKDC), and genome surveillance pathways (ATM, MRN complex, RNF168), highlighting genotype-phenotype correlations and mechanisms driving immune deficiency and dysregulation. We briefly review recent diagnostic advances, including newborn screening using T-cell receptor excision circles, repertoire sequencing, and functional assays, alongside current therapeutic strategies. Finally, we outline key unanswered questions and argue that continued integration of clinical observation with molecular discovery is essential to improve outcomes and deepen understanding of adaptive immune development.

Humans↗

PubMed2026

Practical Saudi Guidelines on management of moderate-to-severe psoriasis: 2026 update.

BACKGROUND: Psoriasis is a chronic, immune-mediated inflammatory skin disease that affects approximately 5.3% of the population in the Kingdom of Saudi Arabia (KSA). Thus, we aim to develop updated evidence-based clinical practice guidelines for the management of adults and pediatric patients with moderate-to-severe plaque psoriasis in the KSA. METHODS: These guidelines followed the "Grading of Recommendations, Assessment, Development, and Evaluation" (GRADE) methodology. We conducted a systematic literature review of PubMed, EMBASE, and the Cochrane Library for high-quality evidence published between 2020 and 2026. The panel developed 31 PICO questions that address key treatment considerations for moderate-to-severe psoriasis. RESULTS: We established 27 evidence-based recommendations and 4 good-practice statements addressing key aspects of moderate-to-severe psoriasis management. These guidelines strongly recommend adopting the Psoriasis Area and Severity Index (PASI) 90 as the primary treatment goal over PASI 75. For adult patients, the guidelines recommend biologic therapies, including interleukin (IL)-17 inhibitors, IL-23 inhibitors, IL-12/23 inhibitors, and tumor necrosis factor (TNF)-α inhibitors, for better disease control. For pediatric patients, the guidelines recommend early initiation of biologic therapy, with etanercept, secukinumab, ixekizumab, and adalimumab as preferred options. CONCLUSION: These Saudi national guidelines offer a comprehensive, evidence-based framework for managing moderate-to-severe psoriasis in adults and pediatric patients.

Humans↗

PubMed2026

Premenarche risk factors for future dysmenorrhoea: a prospective cohort study.

BACKGROUND: Dysmenorrhoea, or pain during menstruation, is common in adolescence and is often dismissed or left untreated. Dysmenorrhoea can interfere with daily functioning and can lead to other chronic pain conditions; however, little is known about the risk factors for dysmenorrhoea. We aimed to characterise premenarche risk factors for the presence and severity of future dysmenorrhoea. METHODS: In this prospective cohort study, we obtained data for female adolescents from the population-based Adolescent Brain Cognitive Development Study (USA) who were premenarchal at baseline (age 9-10 years) and had both reached menarche and completed the Menstrual Cycle Survey at 3-year follow-up (age 12-13 years). Parents or guardians provided sociodemographic information and completed the Child Behavior Checklist, the Sleep Disturbance Scale for Children, and the Pubertal Development Scale, which captured data on non-painful somatic symptoms, attention problems, anxiety, depression, sleep disturbances, and pubertal development at baseline. Our primary objective was to analyse associations between dysmenorrhoea at 3-year follow-up (status and severity) with select symptom domains (sleep problems, attention problems, somatic symptoms, anxious or depressive symptoms, and baseline pain status) at baseline. We also investigated associations between dysmenorrhoea and participant characteristics (pubertal status, race or ethnicity, and income-to-needs ratio) that underlie social determinants of health. Differences by race were tested using Fisher exact tests. Differences by ethnicity and baseline pain status were tested using χ2 tests. Differences in continuous variables were assessed using ANOVA. Wilcoxon-Rank Sum tests were used in analyses of sleep problems, attention problems, and somatic symptoms, and ANOVA was used for pubertal status and income-to-needs ratio. Multinomial logistic regression was used to test associations with dysmenorrhoea severity, and linear regression was used to test associations with dysmenorrhoea status and menstrual pain interference. FINDINGS: 2254 female adolescents were included in this study. 1299 (57·6%) participants developed dysmenorrhoea at age 12-13 years, and 247 (19·0% of those with dysmenorrhoea) reported severe dysmenorrhoea. Non-painful somatic symptoms were prospectively associated with future dysmenorrhoea (odds ratio [OR] 1·17 [95% CI 1·04-1·32]; p=0·0070), whereas anxiety or depression, sleep disturbances, and attention problems were not. Sleep disturbances were prospectively associated with menstrual pain interference (β coefficient 0·16 [95% CI 0·01-0·31]). Advanced pubertal status at ages 9-10 years was prospectively associated with risk of dysmenorrhoea 3 years later (OR 1·79 [95% CI 1·47-2·17]; p<0·0001), as was lower income-to-needs ratio (0·96 [0·93-1·00]; p=0·031). Black (1·38 [1·05-1·83]; p=0·024) and Hispanic (1·34 [1·03-1·68]; p=0·010) young females were at a significantly greater risk of experiencing dysmenorrhoea than were White and non-Hispanic young females, respectively. INTERPRETATION: Sociodemographic characteristics and clinical symptoms present before menarche might help to identify at-risk individuals for dysmenorrhoea before pain becomes a lifelong issue. FUNDING: The National Institute of Nursing Research, the National Institute of Diabetes and Digestive and Kidney Diseases, and the Eunice Kennedy Shriver National Institute for Child Health and Human Development.

Humans↗

PubMed2026

AI Health message intervention: The role of message customization and message source in breast cancer screening among women of color.

OBJECTIVES: To examine the effectiveness of breast cancer screening messages with varying levels of customization (generic, targeted, and tailored) and to compare AI-generated versus human-generated messages. METHODS: A between-subjects experimental design with a control condition was employed. Message content followed a standardized structure and varied by level of customization: generic, targeted (demographic-based), and tailored (perceived susceptibility- and barrier-based). Messages were developed by either the authors or GenAI (ChatGPT-4o). A total of 391 participants recruited via Prolific were randomly assigned to five groups (generic, targeted-human, targeted-AI, tailored-human, and tailored-AI). Self-efficacy, behavioral intentions, attitudes, and message believability were measured using different scales. RESULTS: Customized (tailoring and targeting) health messages performed comparably to generic messages in shaping positive health outcomes. GenAI-generated messages also produced outcomes comparable to those of human-generated messages under standardized conditions. Significant negative indirect effects through message believability for the human-tailored condition was found relative to the generic condition. CONCLUSIONS: GenAI may be a useful tool for developing and customizing scalable health messages. Its effectiveness depends not only on customization but also on maintaining message quality, including readability, clarity, coherence, naturalness, and credibility. PRACTICAL IMPLICATIONS: GenAI may support health practitioners in developing customized and scalable breast cancer messages. However, professional review remains necessary to ensure that the message is culturally appropriate, responsive to patient concerns, and suitable for use alongside patient-provider communication.

Humans↗

PubMed2026

Cis-regulatory variation in the MdCKX6 promoter is associated with allele-specific expression and fruit size in apple.

Fruit size is a key determinant of apple fruit quality and market value and is strongly influenced by phytohormone-regulated cell proliferation and expansion during early fruit development. Cytokinin oxidase/dehydrogenase (CKX) enzymes regulate cytokinin homeostasis by irreversibly degrading active cytokinins, but the contribution of natural variation in CKX genes to fruit size remains poorly understood. Here, we identified MdCKX6 as a candidate regulator of fruit growth in apple (Malus domestica). MdCKX6 exhibited pronounced allele-specific expression during fruit development in the cultivar 'Royal Gala'. Sequence analysis identified a promoter SNP associated with differential promoter activity and allele-specific expression. Genotyping of diverse apple cultivars and wild Malus accessions revealed a significant association between MdCKX6 promoter genotype and fruit size. Cultivars carrying low-expression alleles produced larger fruits, whereas high-expression alleles were associated with smaller fruits. To investigate gene function, MdCKX6 was overexpressed in tomato, resulting in reduced fruit size. Histological analyses of the transgenic tomato fruit revealed smaller pericarp cells. Transcriptome analysis of transgenic fruits revealed widespread changes in genes associated with cell-cycle regulation, cell wall modification, hormone-related processes, and transcriptional regulation. Together, these results identify MdCKX6 as a potential negative regulator of apple fruit growth and reveal an association between cis-regulatory variants, gene expression, and fruit size. This study provides new insights into the role of cytokinin metabolism in fruit development and highlights regulatory variation in MdCKX6 as a potential target for apple breeding.

Malus↗

PubMed2026

Simultaneous determination of imiquimod and terbinafine in skin permeation studies: Validation of a liquid chromatography method with fluorescence detection.

Chromoblastomycosis is a chronic, neglected subcutaneous mycosis posing significant therapeutic challenges. A topical strategy combining terbinafine (TBF), an antifungal, with imiquimod (IMQ), a TLR-7/8 agonist immunomodulator, has emerged a promising alternative. However, no validated analytical method is currently available to simultaneously quantify both drugs in skin, which is crucial for novel formulation development. This study reports the development and validation of a simple HPLC method with fluorescence detection (excitation 236 nm, emission 340 nm) for the simultaneous determination of TBF and IMQ extracted from porcine skin. Separation was achieved on a C8 reversed-phase column (125 × 4.0 mm, 5 μm) using a mobile phase of methanol and water (60,40, v/v), both containing 0.1% formic acid at a flow rate of 0.8 mL/min. The method showed excellent linearity (r > 0.999) over 0.01-1.0 μg/mL for IMQ and 0.1-2.0 μg/mL for TBF. Intra- and inter-day precision demonstrated coefficients of variation below 5%, and recovery rates from skin (79-105%) confirmed accuracy. Limits of detection were 0.001 μg/mL for IMQ and 0.004 μg/mL for TBF, with quantification limits of 0.02 μg/mL and 0.16 μg/mL, respectively. This selective, sensitive, and reproducible method represents a valuable analytical tool for supporting the development and quality control of topical formulations for chromoblastomycosis and other fungal skin diseases.

Animals↗

PubMed2026

Analysis of deep learning techniques in computer-aided diagnosis for meniscus injuries: a systematic literature review.

Meniscus informatics is a growing subject of study in the healthcare industry. One of the major hindrances to the healthcare system's transformation is obtaining knowledge and meaningful information from complicated, high-dimensional and diverse sources. Modern biomedical research, for instance, has seen an increase in the use of complex, dissimilar, poorly documented, and generally unstructured electronic health records, imaging, sensor data and text, even after many current techniques have been used to extract more robust and useful elements from the data for analysis. New efficient standards for building end-to-end learning models from complex data are therefore needed. Therefore, the current study aims to examine the most recent research on the use of deep learning techniques for diagnosing meniscus tears and recommend creating comprehensive and meaningful interpretable structures that might benefit the healthcare industry. We also draw attention to shortcomings and the need for better technique development, and we provide new perspectives about this exciting new development in the field.

Humans↗

PubMed2026

Final-year nursing students' clinical practice experiences: a reflection study.

OBJECTIVES: This study aimed to explore the most impactful clinical practice experiences of final-year nursing students and the future-oriented actions developed in response to these experiences. METHODS: A retrospective descriptive qualitative design was used. Following reflection training in the internship practice course, 134 final-year nursing students were asked to describe the experience that affected them most during clinical practice. A total of 123 written reflections were analyzed using content analysis. RESULTS: Three themes emerged: near-miss events, incivility behaviors, and positive preceptoring roles. Negative experiences were mainly related to patients, relatives, and nurses and often led students to feel fear and inadequacy. Students reported action plans focused on effective communication, safe patient care, and becoming positive role models. CONCLUSIONS: These findings highlight the importance of supportive clinical learning environments and positive professional socialization during the transition from student to nurse. IMPLICATIONS FOR INTERNATIONAL AUDIENCE: Nursing students worldwide may encounter incivility and near-miss events during clinical practice, potentially adversely affecting their learning experiences and professional development.

Humans↗

PubMed2026

A Dynamic Nomogram to Predict Metabolic Dysfunction-Associated Fatty Liver Disease in Patients with Metabolic Syndrome.

BACKGROUND: Metabolic syndrome (MetS) involves multiple metabolic disorders. This study aimed to identify high-risk populations for metabolic dysfunction-associated fatty liver disease (MAFLD) in patients with MetS and to establish a dynamic predictive nomogram. METHODS: A total of 627 patients with MetS from six regions in Zhejiang Province were enrolled and categorized into MAFLD and non-MAFLD groups, then randomly assigned to training and validation sets at a ratio of 7:3. Independent predictors of MAFLD were identified using least absolute shrinkage and selection operator regression and multivariable logistic regression analyses. These predictors were then used to construct a dynamic nomogram. RESULTS: A total of 627 patients with MetS were included in the final analysis, of whom 77.0% (483/627) were diagnosed with MAFLD. Multivariable logistic regression analysis identified body mass index (BMI), waist circumference (WC), total cholesterol (TC), alanine aminotransferase (ALT), MetS-defined dysglycemia, and education level as independent risk factors for MAFLD. MetS-defined dysglycemia showed the highest odds ratio (OR) for MAFLD development [OR = 1.87, 95% confidence interval (CI): 1.07-3.29]. Although the number of MetS components and the metabolic syndrome score were significantly associated with MAFLD in univariate analysis, they were not independently associated with MAFLD in the multivariate model. A dynamic nomogram for predicting MAFLD risk in patients with MetS was developed and internally validated. The area under the receiver operating characteristic curve was 0.834 (95% CI: 0.787-0.880) in the training set and 0.839 (95% CI: 0.771-0.899) in the validation set, indicating strong predictive performance. Bootstrap internal validation demonstrated good agreement between predicted and observed outcomes in calibration curves. Decision curve analysis further indicated favorable clinical applicability of the nomogram. CONCLUSION: BMI, WC, TC, ALT, MetS-defined dysglycemia, and education level are independent risk factors for MAFLD. A dynamic nomogram for predicting MAFLD risk in patients with MetS was successfully developed and validated.

Humans↗

PubMed2026

Molecular adaptation of caspase genes to salinity stress in the tropical sea cucumber Stichopus monotuberculatus: A comparative analysis across echinoderms.

Apoptosis is an essential physiological process that plays a critical role in development and tissue homeostasis. Caspases, as central regulators of apoptosis, are crucial in controlling inflammation and cell death. In this study, we investigated the caspase gene family in Stichopus monotuberculatus to explore their potential roles in salinity stress adaptation. Five caspase genes were identified from the genome of S. monotuberculatus, including Smcaspase3, Smcaspase6, Smcaspase8a, Smcaspase8b, and Smcaspase8c. Phylogenetic analysis revealed that these Smcaspase genes clustered into distinct caspase subfamilies and showed high conservation with homologs from other echinoderms and representative vertebrates. Conserved motif and gene structure analyses showed relatively similar structural patterns within each clade, whereas divergence was observed among different subfamilies. Promoter analysis identified numerous cis-acting elements related to gene regulation, immune response, and growth and development. Expression profiling under salinity stress showed that Smcaspase8a was significantly upregulated, particularly under prolonged stress, whereas the other genes exhibited limited transcriptional responses. Our findings highlight caspase function in salinity stress and provide the foundation of molecular salinity adaptation mechanisms in S. monotuberculatus.

Animals↗

PubMed2026

Machine learning-ready genomic biomarkers: ATF3 polymorphisms predict postoperative analgesic demand through AI-compatible phenotyping.

PURPOSE: To determine whether ATF3 polymorphisms can serve as genetic biomarkers for machine learning-based precision analgesia by establishing a genotype-phenotype association suitable for predictive modeling of postoperative opioid requirements. METHODS: In a prospective cohort of 167 adults undergoing abdominal surgery, ATF3 SNPs rs3122721 and rs3125293 were genotyped. A structured dataset architecture was developed to represent genetic profiles as input features for supervised learning models, enabling translational analysis of genotype‑dependent opioid consumption over 72 h. RESULTS: Patients with homozygous genotypes of the ATF3 SNPs had significantly higher opioid requirements than non‑carriers, despite reporting similar subjective pain scores. This consistent genotype‑dependent pattern provided a clinically relevant phenotype suitable for integration into predictive algorithms. CONCLUSION: ATF3 genotyping offers a promising biomarker for computationally informed precision analgesia. By linking genomic variability to clinically meaningful outcomes within a structured clinical and genomic framework, this approach supports the future development of risk-stratified clinical decision-support systems to optimize postoperative pain management.Trial registration ChiCTR1900021991, registered 30 April 2019. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at https://doi.org/10.1007/s13755-026-00480-9.

ATF3↗

PubMed2026

Emerging techniques of CRISPR/Cas system in antiviral therapy and diagnostics: Applications, limitations, and translational perspectives.

The CRISPR/Cas (clustered regularly interspaced short palindromic repeats) system is a versatile technology for developing antiviral medicines and editing viral genomes in both diagnostics and vaccine synthesis. Emerging insights into class 2 effectors, such as Cas9, Cas12, and Cas13, which target viral DNA and RNA, have revolutionized vaccines against viruses such as HIV, HPV, HBV, and EBV. Innovative diagnostic techniques such as SHERLOCK, DETECTR, and FELUDA have demonstrated system's diversity and accuracy in detecting the virus markers, supporting clinical decision-making, indicating adaptability and precision of CRISPR. This review critically evaluates CRISPR's role in RNA editing, emphasizing its importance for functional genomics and development of recombinant vaccines. Translational challenges are critically discussed, including off-target effects, delivery limitations, and ethical issues, for which unique approaches such as high-fidelity Cas variants, non-viral delivery systems, and bioethical frameworks are evaluated to address these limitations. This review also covers other social implications, such as accessibility and biosecurity risks, associated with CRISPR technologies Collectively, these advances underscore the transformative potential of CRISPR technologies in shaping next-generation antiviral diagnostics and therapeutics.

CRISPR-Cas Systems↗

PubMed2026

Leveraging environmental applications and risks of coal gangue: A critical review on authigenic inorganic heavy metals, organic contaminants, and the removal of exogenetic contaminants.

Coal gangue (CG) as bulk solid waste has seriously threatened the ecosystem. Therefore, identifying the key risk drivers and exploring feasible disposal methods for CG are essential for developing a sustainable strategy. However, there is currently a lack of comprehensive information that balances the contamination risks with the valuable constituents present in CG, which hinders its full potential for sustainable use without negative environmental impacts. Given the complex composition and associated risks, we propose that addressing the critical properties related to contamination is crucial for the efficient utilization of CG. On this premise, we summarized several practical resource pathways (ecological multifunctional materials, extraction of rare elements, and soil additives) that are more favorable for sustainable development relative to conventional disposals. Meanwhile, we also propose that coupling disposals could intensely reduce CG's environmental footprints and capital costs. Consequently, regardless of the number of challenges to be solved, we believe the CG has broad application prospects, and we hope this review will promote the conversion of CG into an asset with lower ecological and social impacts.

Metals, Heavy↗

PubMed2026

Machine learning-based prediction of unplanned readmission and construction of an online calculator for elderly patients with mild ischemic stroke.

OBJECTIVE: To screen for independent risk factors for unplanned readmission in elderly patients with mild ischemic stroke, and to construct and validate an online risk prediction calculator based on an interpretable machine learning model, thereby providing a promising practical tool for accurate clinical assessment of 30‑day all‑cause unplanned readmission risk in this population. METHODS: A prospective cohort study was conducted, including 1050 patients aged ≥ 60 years with mild ischemic stroke admitted between August 2023 and September 2024. Participants were randomly divided into a training set (840 cases) and a test set (210 cases) at a ratio of 8:2. Risk factors were screened by univariate analysis and multivariable Logistic regression. Four machine learning models, namely LightGBM, XGBoost, Random Forest, and K‑Nearest Neighbors (KNN), were developed and their performance was evaluated using AUC, accuracy, sensitivity, and specificity as metrics. The SHAP framework was used for interpretability analysis, and an online calculator was subsequently developed based on the optimal model. RESULTS: Univariate analysis showed significant differences (P < 0.05) in 13 factors including age, smoking, AIP, TyG index, HALP score, etc. Multivariable Logistic regression identified age (OR = 9.752), smoking (OR = 5.171), AIP (OR = 6.691), TyG index (OR = 4.393), HALP score (OR = 2.831), and ≥ 2 comorbidities (OR = 3.664) as independent risk factors. All four machine learning models demonstrated good predictive performance. Based on a comprehensive evaluation of multiple metrics and computational efficiency, the LightGBM model exhibited the best predictive performance (AUC = 0.884, accuracy = 0.829, sensitivity = 0.812, specificity = 0.875). SHAP analysis showed that age, AIP, TyG index, smoking, and HALP score were key predictors. An online calculator developed based on this model enables individualized risk predictions. CONCLUSION: Key risk factors associated with 30‑day unplanned readmission in elderly patients with mild ischemic stroke were identified. The LightGBM model demonstrated high predictive accuracy, and together with the interpretability analysis and online calculator, offers a practical tool to support clinical risk assessment. However, this tool requires future external validation.

Humans↗

PubMed2026

Assessment of the Potential of Different Anthropometric Indices in Predicting the Risk of Diabetes and Associated Co-morbidities.

Diabetes, a chronic disorder, is showing a rapidly increasing trend globally. India holds the second position in the global diabetes epidemic. The present investigation is an assessment of different anthropometric measurements and their association with type 2 diabetes to determine their diagnostic potential for diabetes as well as its co-morbidities. In this cross-sectional study, we have measured anthropometric parameters and blood biomarkers in subjects with diabetes. We have presented the comparisons of cost- and time-effective anthropometric variable with costly and time-dependent biochemical variables in control and diabetic groups (n = 233/group). Correlations between anthropometric variables and biochemical measurements, as well as the diagnostic utility of anthropometric variables for diabetes, were evaluated. The diagnostic utility of anthropometric variables for diabetes was assessed through receiver operating characteristic (ROC) curves. Neck circumference, sagittal abdominal diameter (SAD), skinfold thickness, and body roundness index (BRI) displayed high specificity and diagnostic utility for diabetes, emphasizing their potential in predicting diabetes and the further development of metabolic syndrome. The study highlights the importance of cost- and time-effective anthropometric assessments in diabetes risk evaluation and calls for further research to elucidate this intricate relationship and develop personalized management strategies.

Humans↗

PubMed2026

The mighty microproteins: from versatile cellular regulators to precision medicine therapeutics.

Microproteins, are tiny proteins encoded by small open reading frame (sORF), translation of these non-canonical open reading frames (ncORFs) has been implicated in diverse biological processes and diseases. This review summarizes recent developments in the discovery, biogenesis, and functional characterization of microproteins, and their involvement in various disease, with special focus on their roles in cancer, cardiovascular, metabolic, neurodegenerative and immune-related disorders. We emphasize the regulation of key cellular pathways by microproteins, including mitochondrial homeostasis, apoptosis, metabolic reprogramming, and immune signaling, all of which affect disease initiation and progression. Emerging evidence also supports their potential as disease biomarkers and therapeutic candidates for precision medicine. Finally, the review critically discusses the current challenges including discrepancies in microprotein annotation, the limitations of ribosome profiling and proteogenomic approaches, the gap between computationally predicted and experimentally validated microproteins, and the need for rigorous orthogonal validation by means of CRISPR-based genome editing, ribosome release assays, mutational analysis, high-resolution mass spectrometry, and functional studies. Finally, we review recent development of AI-assisted ORF prediction, single-cell translatomics, spatial proteomics, and integrated multi-omics as emerging technologies reshaping. Microprotein discovery and functional annotation. Finally, we discuss the translational potential of microproteins and highlight the remaining challenges to clinical application, including peptide stability, pharmacokinetics, tissue-specific delivery, immunogenicity, and the need for rigorous preclinical and clinical validation. Together, this review provides an updated and critical overview of the rapidly evolving microprotein field and highlights future research priorities for translating these molecules into clinically useful biomarkers and precision therapeutics.

Microproteins↗

PubMed2025

The molecular mechanism of cuproptosis and research progress in pancreatic diseases.

PURPOSE: Cuproptosis has been proven to be a novel mode of cell death, distinct from other types of cell death such as necrosis, ferroptosis, pyroptosis, and apoptosis. This study aims to systematically review the molecular mechanisms of cuproptosis in recent years and its research progress in pancreatic diseases. METHODS: By searching PubMed and Web of Science databases, 113 key literatures were included for thematic analysis, covering the molecular mechanism of cuproptosis and its role in the occurrence and development of pancreatic cancer, acute and chronic pancreatitis, diabetes, pancreatic cyst, pancreatic injury and pancreatic neuroendocrine tumor. RESULTS: Cuproptosis refers to the accumulation of copper ions in cells, which leads to instability of ferritin and aggregation of acylated proteins, resulting in oxidative stress-related cell death. Recent studies have shown that cuproptosis plays an important role in the occurrence and development of various pancreatic diseases, such as pancreatic cancer, acute and chronic pancreatitis, diabetes, pancreatic cysts, pancreatic injuries and pancreatic neuroendocrine tumor. The inducers of cuproptosis, such as disulfiram, chloroquinolones, and perilla phenols, alleviate pancreatic cancer by promoting cell cuproptosis. Copper chelators such as tetraethylenepentamine and tetrathiomolybdate promote the recovery of pancreatic injury by inhibiting cell cuproptosis. CONCLUSIONS: Cuproptosis plays a crucial role in the pathogenesis of pancreatic diseases. Further research on the cuproptosis pathway may become a potential target for the treatment of pancreatic diseases.

Animals↗