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From host response to genomic targets: electrochemical biosensing of tuberculosis biomarkers.

Tuberculosis (TB) remains one of the leading causes of death from a single infectious agent worldwide, with timely diagnosis continuing to be a major challenge, particularly in resource-limited settings. Conventional TB diagnostic methods are limited by low sensitivity, long turnaround times, and an inability to reliably differentiate latent from active disease. Biomarker-based diagnostic strategies have therefore gained increasing attention as they offer the potential to improve early detection, disease differentiation, and treatment monitoring. Herein, we examine electrochemical biosensing strategies for TB diagnostics using a biomarker-class-driven framework, covering host-response biomarkers (IFN-γ and TNF-α), pathogen-derived antigens (ESAT6, CFP10, CFP10-ESAT6, MPT64, Ag85, HspX and LpqH), cell-wall signatures and whole-cell markers (LAM and whole cell Mtb), and genomic markers (Mtb DNA and IS6110). Through structured comparison of recognition elements, biointerface designs, signal amplification strategies, electrochemical techniques, matrices, and validation levels, this review identifies the most promising technical approaches for different TB biomarker classes. It further highlights key translational bottlenecks, including limited clinical validation, buffer-based testing, complex multistep amplification, redox-probe dependence, matrix fouling, and insufficient evidence of manufacturability. This review therefore provides practical guidance for developing electrochemical TB biosensors that are analytically sensitive, clinically relevant, and suitable for decentralized diagnostic applications.

Biosensing Techniques

Genetic Screening of Colombian Patients With Early-Onset Parkinson Disease.

BACKGROUND AND OBJECTIVES: Early-onset Parkinson disease (EOPD), defined as symptom onset before 50 years of age, accounts for approximately 10% of patients and is suggested to have a greater genetic component than typical late-onset forms of the disease. Recessive variants in PRKN, PINK1, and DJ-1, are the most common genetic cause of EOPD, however, most studies are in patients of white ancestry. This study aims to analyze genetic variants in PRKN, PINK1, and DJ-1 in Colombian patients to help address the gap in EOPD genetic research of South American populations. METHODS: We analyzed 43 unrelated patients with EOPD using Sanger sequencing for the PRKN, PINK1, and DJ-1 genes and employed multiplex ligation-dependent probe amplification to detect copy number variants. Additionally, long-read whole-genome sequencing was conducted on 3 unresolved patients with age at onset before 30 years of age (long-read sequencing [LRS] patient A-C). RESULTS: We identified known pathogenic single-nucleotide variants and copy number variants in the PRKN gene accounting for 2 patients' disease (4.6% of patients). We observed 2 pathogenic variants in PRKN (c.155delA; p.N52Mfs*29 and c.1083+1G>A) in patient 1, who reported an age at onset of 16 years. We further detected a homozygous duplication of PRKN exons 5-6 in an additional patient, age at onset of 18 years. DISCUSSION: Our study helps characterize genetic contributors to EOPD in Colombian patients, demonstrating genetic forms (PRKN, PINK1, and DJ-1) are rare. Our results highlight a need to include diverse populations in research to improve genetic understanding of disease.

Journal Article

Variants in the interferon regulatory factor 5 gene confer genetic risk for systemic lupus erythematosus in a Han Chinese population.

BACKGROUND: Interferon regulatory factor 5 (IRF5), integral to interferon signaling pathways, has been identified as a susceptibility locus for systemic lupus erythematosus (SLE). Nevertheless, the relationship between IRF5 variants and SLE risk within the Han Chinese demographic remains inadequately characterized. MATERIALS AND METHODS: Genotyping of two functional single nucleotide variants (SNVs) in IRF5 was conducted in 167 individuals with SLE and 246 healthy controls utilizing sequence-specific primer polymerase chain reaction (PCR-SSP). Chi-square and Fisher's exact tests were employed to assess associations. RESULTS: The rs10954213 variant demonstrated a significant association with SLE susceptibility under the recessive model (GG vs. AG+AA, OR = 2.20, 95% CI: 1.30-3.75, p&#x2009;=&#x2009;0.003, adjusted p [pc]&#x2009;=&#x2009;0.030) and homozygous model (GG vs. AA, OR = 2.43, 95% CI: 1.36-4.42, p&#x2009;=&#x2009;0.003, pc = 0.032). Similarly, the rs2004640 variant was associated with an increased risk of SLE across allelic (T vs. G, OR = 1.66, 95% CI: 1.22-2.26, p&#x2009;=&#x2009;0.001, pc = 0.011), dominant (TG+TT vs. GG, OR = 1.77, 95% CI: 1.19-2.63, p&#x2009;=&#x2009;0.005, pc = 0.047), and homozygous models (TT vs. GG, OR = 3.72, 95% CI: 1.58-8.78, p&#x2009;=&#x2009;0.002, pc = 0.016). Haplotype analysis identified protective haplotype HT1 (A/G, OR = 0.54, 95% CI: 0.41-0.73, p&#x2009;<&#x2009;0.001) and risk haplotype HT4 (G/T, OR = 2.51, 95% CI: 1.42-4.42, p&#x2009;=&#x2009;0.001). CONCLUSIONS: These findings indicate that IRF5 gene variants substantially modulate susceptibility to SLE in the Han Chinese population. They hold potential as biomarkers for evaluating SLE risk and offer valuable perspectives into disease pathogenesis.

Adult

The Case for Master Protocols for Rare Neurological Diseases.

Master protocol trials allow for simultaneous multiple hypothesis testing within a common framework and might be applicable for rare diseases. In May 2025, the Network for Excellence in Neuroscience Clinical Trials convened a multistakeholder conference to discuss master protocol trials in rare neurological disorders. In this paper, we explore how master protocol trial designs may apply to rare neurological disorders, using the neuronal ceroid lipofuscinoses as an example. Through shared protocol elements and trial infrastructure, master protocols may decrease cost and improve efficiency in testing potential therapeutics in rare disease, accelerating the delivery of urgently needed therapies to patients. ANN NEUROL 2026;100:477-486.

Humans

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

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

Humans

Technology choice, glycemic control and patient-reported outcome measures in adults with type 1 diabetes: A randomized crossover trial comparing a smart insulin pen with an automated insulin delivery system (EBIACE-1).

AIMS: To compare glycemic outcomes and patient-reported outcome measures (PROMs) between smart insulin pens (SIP) and an automated insulin delivery (AID) system in adults with type 1 diabetes (T1D), and to identify individuals able to maintain near-optimal glycemic control using SIP. METHODS: EBIACE-1 was a randomized, open-label, crossover trial including 31 adults with T1D. Participants received SIP (InPen&#x2122;) and AID (MiniMed&#x2122; 780G) for 6&#xa0;months each. Co-primary outcomes were time in range (TIR 70-180 mg/dL) and HbA1c. Treatment effects were assessed using longitudinal models in intention-to-treat (ITT) and per-protocol (PP) analyses. Predictors of near-optimal glycemic control with SIP were evaluated using multivariable logistic regression. RESULTS: AID improved glycemic control versus SIP, with higher TIR (81&#xa0;% vs 66&#xa0;%; +15&#xa0;%, 95&#xa0;% CI 10-19; P&#xa0;<&#xa0;0.001) and lower HbA1c (6.9&#xa0;% [52&#xa0;mmol/mol] vs 7.3&#xa0;% [56&#xa0;mmol/mol]; -0.4&#xa0;%, 95&#xa0;% CI&#xa0;-&#xa0;0.6 to&#xa0;-&#xa0;0.3; P&#xa0;<&#xa0;0.001). Near-optimal glycemic control with SIP was achieved by 12 of 26 participants (46&#xa0;%). In exploratory analyses, higher baseline diabetes-related life interference was associated with a lower probability of achieving this outcome. CONCLUSIONS: AID provides superior glycemic control, although nearly half of participants achieved near-optimal control with SIP, supporting a personalized approach to technology selection.

Adult

Systematic meta-analysis of the toxicities and side effects of the targeted drug lenvatinib.

BACKGROUND: Lenvatinib, an effective targeted drug for various cancers, has clinical medication safety concerns due to its toxicities and side effects. OBJECTIVE: This study evaluated lenvatinib-induced any adverse events (any AEs) and nine aspects: vascular toxicities related to the circulatory system (vascular toxicities, blood system, and heart), toxicities of the skin and its appendages (skin/subcutaneous tissue and taste system), toxicities of the respiratory system (respiratory, thoracic, and mediastinal and respiratory tract), toxicities of the nervous system (nervous system and general), toxicities of the digestive system (gastrointestinal and liver), toxicities of the urinary system, toxicities of the endocrine and metabolic system (endocrine and metabolism/nutrition), toxicities of the musculoskeletal system, and other severe toxicities. Toxicities and side effects were stratified by severity into any and &#x2265;3 grades for analysis. PATIENTS/MATERIALS AND METHODS: Multiple databases were searched for lenvatinib cancer clinical studies (cohort studies and randomized controlled trials) from inception to December 31, 2024; toxicity and side effect data were extracted and analyzed. RESULTS: Nine high-quality studies were included, showing that lenvatinib is effective in cancers but has notable toxicities. Taking hypertension as an example, for any grade, the risk ratio (RR) was 2.34 with a 95% confidence interval (CI) of [2.09, 2.62], a Z-value of 14.74, and a P-value <0.00001; for grade &#x2265;3, the RR was 2.60 with a 95% CI of [2.21, 3.06], a Z-value of 11.44, and a P-value <0.00001. CONCLUSION: Lenvatinib is effective for cancer but toxic, and this study supports its rational clinical use.

Humans

Development of a cell-based nanoluciferase reporter system for high-throughput screening of HBV cccDNA inhibitors.

Hepatitis B virus (HBV) persistence is sustained by the viral covalently closed circular DNA (cccDNA) minichromosome, which remains a major barrier to curative antiviral therapies. The lack of reliable quantitative cccDNA detection methods and surrogate markers has hindered efforts to target cccDNA in antiviral high-throughput screening (HTS). Here, we established a novel inducible cccDNA-dependent nanoluciferase (NLuc) reporter cell line, designated HepBLE12, by inserting an in-frame 11-amino acid split-NLuc HiBiT tag into the precore (pC) coding region of an HBV transgene. The resulting 1.3-kDa HiBiT tag on pC serves as the detection module of the split NLuc system, generating quantitative luminescence upon high-affinity complementation with the cognate 18-kDa LgBiT subunit in cell lysates. Notably, the HiBiT assay enables direct detection of intracellular HiBiT-pC protein rather than secreted HBeAg, providing a reporter signal more closely linked to cccDNA activity. HepBLE12&#x202f;cells exhibited inducible and robust viral DNA replication, and the cccDNA-dependent HiBiT signal was validated under diverse experimental conditions that modulate cccDNA formation or transcription. We further miniaturized the assay to a 384-well format and optimized key parameters following standard HTS assay development practices. The assay was successfully automated and demonstrated excellent performance in a multi-day variability study and a pilot screen, with signal-to-background (S/B)&#x202f;&#x2248;&#x202f;9, coefficient of variance (CV)&#x202f;<&#x202f;10%, and average Z-factor value of 0.74, exceeding canonical HTS quality benchmarks. Together, the HepBLE12 cell-based HTS platform provides a robust and practical tool for identifying inhibitors targeting HBV cccDNA.

Hepatitis B virus

A system-level metastable model of cancer evolution: integrating replication stress, cell cycle deregulation and chromosomal instability.

INTRODUCTION: Cancer cell proliferation occurs within the context of persistent genomic instability. In this review, we propose the RS-CCD-CIN axis as a systems-level framework in which replication stress (RS), cell cycle deregulation (CCD) and chromosomal instability (CIN) form an interdependent triad that shapes tumour evolution. This axis represents a constrained metastable state in which genomic instability is tolerated and buffered. The objective of this review is to synthesize the current understanding of how the RS-CCD-CIN axis contributes to tumour heterogeneity, adaptability and therapy response. DISCUSSION: Evidence indicates that RS, CCD and CIN operate as a dynamic, interconnected network rather than as independent processes. Replication stress induces DNA damage and mutagenesis, while partial checkpoint disruption permits cells with unresolved lesions to proliferate. Chromosomal instability generates both structural and numerical alterations, contributing to intratumoural heterogeneity. Together, these processes facilitate adaptation to environmental and therapeutic pressures. Extrachromosomal DNA, micronuclei formation and cytosolic DNA signalling, including the cGAS-STING pathway, connect genomic instability to adaptive responses and immune modulation. Single-cell and spatial profiling reveal temporal and spatial variability in RS, CCD and CIN states, highlighting the limitations of static biomarkers. Therapeutically, targeting individual components often yields limited durability, whereas approaches that simultaneously perturb multiple aspects of the RS-CCD-CIN axis may improve clinical outcomes. CONCLUSIONS: This review highlights the RS-CCD-CIN axis as a fragile and metastable architecture that supports cancer evolution, while also being susceptible to collapse. A deeper understanding of this interconnected framework may inform the development of therapeutic strategies and enhance the management of resistance.

Humans

Screening of Estrogenic and Antiestrogenic Effects of Estradiol, Bisphenol A, and Fulvestrant Using 2D and 3D Breast Cancer Cell Systems With a Luciferase Reporter Gene Assay.

Endocrine-disrupting chemicals (EDCs) like bisphenol A (BPA) pose health risks by interfering with hormones. This study develops and utilizes in&#xa0;vitro 2D and 3D cell models to evaluate the estrogenic and antiestrogenic properties of compounds. Human breast cancer cell lines T47D and MCF7, stably transfected with a luciferase reporter gene (ERE-LUC), were first compared in 2D. Due to the significantly higher sensitivity and responsiveness observed in the T47D line during preliminary 2D screenings, this cell line was exclusively selected for the development of the 3D spheroid model. Cells were treated with 17&#x3b2;-estradiol (E2), BPA, and Fulvestrant (FUL) to assess cell viability and luciferase activity. In 2D models, T47D ERE-LUC cells showed higher responsiveness than MCF7 ERE-LUC, which failed to show significant luciferase induction with E2. In the 3D T47D model, cells exhibited significant and robust changes in luciferase activity in response to E2 and BPA, highlighting the enhanced fidelity of 3D cultures in replicating tissue conditions compared to their 2D counterparts. The study highlights the effectiveness of 3D models over 2D in evaluating estrogenic activity. Specifically, the 3D T47D ERE-LUC system serves as a superior, sensitive, and reliable platform for screening EDCs, offering benefits in cost, data speed, and reduced in&#xa0;vivo reliance.

Humans

Diversification of yeast proteins as an approach for the development of sustainable food systems.

Despite growing trend in sustainable protein sources, yeast proteins have mainly been explored as a source of bioactive peptides using a monospecies and general protein approach. The contribution of highly abundant protein fractions in the yeast proteome to peptide formation remains insufficiently investigated, limiting a comprehensive understanding of yeast proteins as optimized peptide sources. The current review presents a systematic analysis of yeast proteins as emerging protein sources and evaluates the suitability of high-abundance proteins as bioactive peptide precursors by in silico techniques. Moreover, brewery by-product and single-cell yeast protein approaches are compared in terms of composition and techno-functionality whereas peptide formation mechanisms (in situ and ex situ) and regulatory aspects for food applications are also addressed. Cytoplasmic metabolic proteins, particularly glycolytic enzymes (GAPDH), are identified as highly abundant fractions of the yeast proteome. Proteins associated with cell and organelle membranes also contribute substantially based on cellular localization. These findings imply that such proteins may act as key precursors of yeast-derived bioactive peptides. In silico hydrolysis with Alcalase suggests a tendency toward the generation of short-chain peptides (3-11/14 aa), which may support biological activity. Moreover, peptide profiles appear to vary across yeast species, highlighting the role of species diversity in peptide generation. While single-cell yeast protein allows more controlled production than brewery by-products, nucleic acid content in both may limit applications. Overall, yeast proteins appear to be metabolically adaptable and species-diverse sources for various biological peptides.

Saccharomyces cerevisiae

Determinants of Meal Satisfaction and Their Association With Childhood Obesity: A Systematic Review.

Meal satisfaction is considered a multidimensional concept that includes sensory enjoyment, cognitive, emotional, and physiological components and relates to contentment with the meal experience as a whole. However, its relevance to eating behavior and body weight remains unclear, especially in children. The present review investigated the potential relationship between meal satisfaction-related constructs and childhood obesity, and whether this relation is shaped by individual factors and the external environment. Seventeen eligible studies from 350 records published between 2008 and 2024 were included. No study directly assessed meal satisfaction; instead, proxy measures were used. Food enjoyment emerged as the proxy most consistently associated with BMI, often clustering with higher food responsiveness, lower satiety responsiveness, and emotional overeating. Parental feeding practices, especially pressure to eat, significantly contributed to variation in children's eating behavior and were associated with lower food enjoyment. Overall, meal satisfaction could be a key aspect to consider in childhood obesity prevention programs. However, to date, the available evidence is heterogeneous and predominantly observational. Future longitudinal and intervention studies are needed, alongside child-appropriate instruments to objectively quantify food satisfaction in children. Research that helps understand the role of contextual eating factors on children's meal satisfaction and eating behavior is also warranted.

Humans

Comparison of the predictive performance of systemic immune-inflammation index and neutrophil-to-lymphocyte ratio for three-month poor functional outcome in ischemic stroke: a systematic review and meta-analysis.

INTRODUCTION: Ischemic stroke (IS) is a leading cause of global mortality and disability. Early and accurate prognosis is crucial for patient management. The neutrophil-to-lymphocyte ratio (NLR) and systemic immune-inflammation index (SII) are emerging inflammatory biomarkers; however, their relative predictive value for three-month poor functional outcome (modified Rankin Scale [mRS]&#x2009;>&#x2009;2) remains uncertain. METHODS: We systematically searched PubMed, Embase, Web of Science, and the Cochrane Library up to 20 July 2025, adhering to PRISMA guidelines. Observational studies reporting the association of SII or NLR with three-month poor outcome were included. Study quality was evaluated using the Newcastle-Ottawa Scale. Area under the curve (AUC), odds ratios (OR), and standardized mean differences (SMD) were pooled using random-effects models in Stata 16.0. RESULTS: Twenty-one studies involving 7520 IS patients were analysed. NLR demonstrated marginally superior discriminative ability compared to SII (AUC 0.71, 95% CI: 0.67-0.76 vs. 0.68, 95% CI: 0.64-0.71), though this difference was not statistically significant. Elevated NLR was significantly associated with poor outcome (OR = 1.26, 95% CI: 1.17-1.37, p&#x2009;<&#x2009;.001), whereas SII was not (OR = 1.00, 95% CI: 1.00-1.00, p&#x2009;=&#x2009;.384). Both markers showed moderate effect sizes (SMD: NLR = 0.69, SII = 0.72; p&#x2009;<&#x2009;.001). NLR performed better in non-intervention and Chinese subgroups, while SII exhibited consistent AUC values across treatment and ethnic subgroups. CONCLUSION: NLR and SII are accessible prognostic markers in IS. NLR demonstrates superior accuracy and a significant association with poor outcome, while SII shows greater stability across patient subgroups. Both may assist in risk stratification, in resource-limited settings.

Humans

Privacy, security, and reliability risks of artificial intelligence in healthcare: a systematic review of empirical evidence.

BACKGROUND: Artificial intelligence (AI) is increasingly integrated into healthcare information systems, supporting clinical decision-making, imaging analysis, and predictive modeling. While these applications offer operational and clinical benefits, they also introduce emerging risks to patient privacy, data security, and system reliability. OBJECTIVE: To systematically review empirical evidence on privacy breaches, security vulnerabilities, and misuse associated with AI applications in healthcare settings. METHODS: PubMed, Embase, Web of Science, Scopus, IEEE Xplore, and ACM Digital Library were searched for empirical studies published between January 2015 and November 2025 that evaluated AI use or misuse in clinical diagnosis, treatment, or decision-making. Two reviewers independently screened studies and extracted data using a standardized form. Findings were synthesized narratively due to heterogeneity in study designs, AI methods, and reported outcomes. RESULTS: Of 7,285 records identified through database searches and 205 through citation screening, 22 empirical studies met the inclusion criteria, spanning multiple clinical domains and data modalities, predominantly medical imaging applications. Five recurring threat categories were identified: patient re-identification, membership inference, unauthorized access and adversarial exploitation, input manipulation, and misuse or overinterpretation of AI outputs. Across studies, AI models were shown to encode latent biometric signals across diverse data types, limiting the effectiveness of traditional anonymization and synthetic data approaches. Adversarial attacks and input manipulation were also shown to compromise diagnostic performance and system integrity. CONCLUSION: This systematic review provides empirical evidence suggesting that contemporary AI systems in healthcare introduce privacy and security risks that may challenge traditional assumptions about data protection. These findings underscore the need for privacy- and security-by-design approaches and governance frameworks that address risks across the AI lifecycle.

Humans

Dosimetric Parameters of the Heart and Its Substructures in Predicting Cardiac Events or Survival in Patients With Lung Cancer After Radiation Therapy: A Systematic Review and Meta-analysis.

The predictive value of radiation dose to the whole heart (WH) and cardiac substructures (CS) for cardiac events (CEs) and survival in patients with lung cancer remains uncertain. The goal of this study was to conduct a systematic review and meta-analysis to provide an evidence-based estimate of the relationship between these associations. A systematic meta-analysis was performed following PRISMA guidelines. Risk of bias was assessed using the JBI Critical Appraisal Checklist for Case Series. Outcomes were classified into major adverse cardiac events (MACE), arrhythmias, pericardial effusion, and survival. Depending on heterogeneity, random- or fixed-effects models were applied to calculate pooled hazard ratios (HRs) for univariable and multivariable analyses. A total of 80 studies, including 21,645 patients, were analyzed. Of these, 25 studies reported CEs, and 69 reported survival outcomes. Among 91 WH and 215 CS parameters evaluated, several showed significant associations. Key findings from our meta-analysis include: (1) left anterior descending (LAD) V15 was significantly associated with MACE. The mean heart dose (MHD), as well as ventricle and LAD doses, were significantly associated with ischemic events. (2) Multiple CS parameters were associated with different arrhythmia subtypes. (3) MHD, heart V5/V35/V55 and pericardial doses were significantly associated with pericardial effusion. (4) MHD was significantly associated with survival; CS parameters also showed predictive value, and especially, heart base dose being the most significant. (5) We also identified several thresholds with potential predictive values, such as LAD V15 <10% for MACE, left pulmonary vein (LPV) V55 <2%, and right pulmonary vein (RPV) V10 <54% for atrial fibrillation (AF), right atrium (RA) V60 <0.03 cc for non-AF supraventricular tachyarrhythmia, and left main artery (LMA) V10 &#x2265;1 cc for bradyarrhythmia. This study identified 130 WH and CS dosimetric parameters associated with CEs and 131 with survival outcomes. These findings enhance our understanding of radiation-induced heart injury mechanisms and provide guidance for potential protective and intervention strategies.

Humans

Extent of resection as an independent predictor of survival for patients with glioblastoma as defined by the new WHO 2021 classification.

OBJECTIVE: Extent of resection (EOR) has previously been demonstrated to have an impact on survival in patients with glioblastoma (GBM). However, with the World Health Organization (WHO) 2021 reclassification of GBMs based on IDH-mutation status, patients with "IDH-mutant GBMs," who typically survive long term, were reclassified as WHO grade 4 IDH-mutant astrocytomas and removed from the GBM taxonomy. Therefore, it is unknown whether the previously reported impact of resection on survival was a false-positive result due to the inclusion of the less aggressive IDH-mutant tumors in previous datasets. This study aimed to determine the extent to which EOR remains an independent predictor of survival in patients with WHO 2021 GBM after the reclassification of IDH-mutant grade 4 astrocytomas. METHODS: All cases of GBM tumors (based on the pre-2021 GBM classification) that were newly diagnosed between 2005 and 2021 were identified in our institutional database and subsequently reclassified based on the updated WHO 2021 criteria using IDH status. Multivariable statistical analyses of demographic information, survival time, and EOR based on volumetric MRI were performed to determine the independent predictors of survival for the whole group of patients and for IDH-wildtype GBM patients exclusively. Additional analyses were performed to identify an EOR threshold for improvement in survival. RESULTS: Of the 523 tumors classified as GBM based on the pre-2021 taxonomy, 52 (9.9%) cases were reclassified as WHO grade 4 IDH-mutant astrocytomas, and the median survival of patients in this group was 7.9 years, whereas median survival of the IDH-wildtype GBM patients was 1.4 years. Multivariate analyses of the whole group demonstrated that IDH-mutant astrocytomas were associated with reduced hazard of death. In both the whole group (n = 523) and in IDH-wildtype GBMs (n = 471), higher EOR of the contrast-enhancing (CE) tumor was associated with reduced hazard of death, whereas older age or male sex was associated with increased hazard of death. Because most patients (90%) had high EOR values (> 81%), a statistically meaningful EOR threshold could not be established. CONCLUSIONS: These analyses demonstrated that EOR of the CE tumor is an independent predictor of survival and that greater EOR is associated with improved survival in WHO 2021 IDH-wildtype GBMs even after excluding grade 4 IDH-mutant astrocytomas. However, an absolute EOR threshold below which resection did not improve survival could not be established, raising concerns about prior cutoff assessments.

Humans

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

Mitochondrial DNA diversity in Ecuadorian populations: Recurrence of variant 16136 within haplogroup B2.

The identification of lineage-defining variants, frequently found in the coding region of mitochondrial DNA (mtDNA), is essential for refining haplogroup classification. Most mtDNA studies in South American populations have focused on the control region (CR), which has provided important insights into population structure and maternal lineage origins, although information needed for more robust phylogenetic resolution has been neglected. This study investigates the maternal genetic structure of Ecuadorian populations by combining CR and whole mitogenome analyses. Sequences from the mtDNA CR were obtained from 461 individuals (253 Mestizos and 208 Native Americans), while complete mitogenomes were sequenced for 127 individuals to improve phylogenetic resolution by identifying lineage-defining variants present in coding region. Most mtDNA haplogroups in the two population groups analyzed were of Native American origin (A2, B2, B4, C1, D1, D4), with significant differences in the distribution of specific lineages between them. Among Mestizos, African haplogroups (all within the L branches) and Eurasian haplogroups (H, K, R, U) were detected at low frequencies, whereas no African lineages were observed among Native Americans. The results obtained highlighted a heterogeneity within Ecuadorian populations that must be considered when developing mtDNA haplotype databases for forensic purposes. Whole mitogenome sequences enabled the identification of variants that refined haplogroup classifications, provided a more accurate reconstruction of the maternal genetic diversity, and improve the discrimination between Native American and Asian maternal lineages within haplogroup B4b.

Humans