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PubMed2026

Temporal redistribution of control reveals age-related differences in task switching at the level of preparation.

Task-switching studies often report minimal age-related differences in switch costs, leading to the conclusion that switching-related control processes are relatively preserved in aging. However, this conclusion is based on paradigms that confound preparatory and execution processes. This study examined whether age-related differences in semantic task-set reconfiguration may be underestimated due to this confound. In Experiment 1 (36 young and 30 older adults), participants performed an externally paced task-switching paradigm without control over preparation. In Experiment 2 (28 young and 28 older adults), a self-paced paradigm allowed participants to initiate stimulus onset, enabling measurement of preparation time. Across both experiments, reaction time (RT) and error rate (ER) showed reliable age effects but no interactions between age and condition, whereas switching-related condition effects varied across measures and experiments. The expression of switching-related costs differed across measures and task structures. Local switch costs were expressed in ER in Experiment 1 but in RT in Experiment 2. Global switch costs (all-switch vs. all-repeat) were observed in execution measures only in Experiment 1. In Experiment 2, preparation time showed reliable mixing, local, and global switching effects, with age-related amplification emerging specifically for global switching. These findings indicate that switching-related costs are redistributed across processing stages and behavioral measures. The results suggest that age-related modulation of semantic task-set reconfiguration may emerge more clearly during preparation than task execution, particularly under continuous switching demands. Preparation time is interpreted cautiously as reflecting participant-regulated preparatory processes rather than a pure measure of preparation efficiency.

Humans↗
PubMed2026

Fructophilic lactic acid bacteria as a window into multi-scale convergent evolution.

Fructophilic lactic acid bacteria (FLAB) are a group of lactic acid bacteria with unique growth characteristics, that is, poor growth on glucose. Their growth is enhanced in the presence of fructose or external electron acceptors. These organisms inhabit fructose-rich environments such as flowers, fruits, and pollinating insects, particularly honey bees. Apilactobacillus spp. and Fructobacillus spp. are representatives of FLAB, although they belong to phylogenetically distant clades. These organisms commonly possess markedly small genomes with a low number of coding DNA sequences. Furthermore, their genomes are characterized by a markedly reduced number of genes involved in carbohydrate transport and metabolism. Genome reduction in FLAB reflects convergent adaptation to fructose-rich environments rather than general genome streamlining. The two distinct FLAB genera, Fructobacillus and Apilactobacillus, independently lost more than 100 genes in statistically similar orders. In contrast, genes involved in carbohydrate and amino acid metabolism exhibited reversed orders of loss between the two genera. Furthermore, FLAB genomes lack an intact bifunctional alcohol/aldehyde dehydrogenase gene (adhE), which causes their poor growth on glucose. A comparative genomic study suggested the evolutionary process underlying adhE gene decay during adaptation to the fructose-rich environments, including pollinating insects. In conclusion, FLAB represent a unique example of habitat-driven convergent reductive evolution that can be investigated across multiple biological scales - from individual genes to whole genomes - in the diverse LAB group with a wide range of habitats, and partially share the fructophilic evolution with eukaryotic yeasts found in fructose-rich habitats.

Fructose↗
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

A status update on the unkept promise of high-frequency spinal cord stimulation for treatment-refractory chronic migraine.

INTRODUCTION: Chronic migraine (CM) refractory to conventional pharmacotherapy (r-CM) remains a debilitating neurological condition with limited therapeutic options. High-frequency spinal cord stimulation at 10 kilohertz (HF-SCS) has recently emerged as a distinct neuromodulatory paradigm for this patient population. Unlike traditional spinal cord stimulation, HF-SCS operates above the frequency range that generates paresthesia, thereby eliminating stimulation-induced sensation while potentially engaging unique analgesic mechanisms. AREAS COVERED: This focused narrative review synthesizes the available clinical evidence, technical considerations, and mechanistic hypotheses specifically pertaining to cervical HF-SCS for refractory chronic migraine (r-CM). The authors further provide their expert perspectives on the future of this technology as a treatment option for refractory chronic migraine. EXPERT OPINION: Current data from prospective open-label studies and retrospective case series suggest that cervical HF-SCS may reduce monthly migraine days, facilitate conversion from chronic to episodic migraine patterns in some implanted patients, and may improve headache-related disability and quality of life over at least 52 weeks of follow-up. The paresthesia-free nature of HF-SCS confers a distinct advantage for both patient tolerability and future trial design, as it permits sham-controlled methodologies that have historically been impossible with conventional neurostimulation. However, these findings remain preliminary and should be considered hypothesis-generating pending confirmation in adequately powered randomized sham-controlled trials.

Humans↗
PubMed2026

A framework for delivering real-time, instrument-relative navigation in transoral robotic surgery.

Transoral robotic surgery (TORS) is a minimally invasive, inside-out technique that, compared with traditional open approaches, provides fewer post-operative complications, shorter hospital stays, and improved survival for early-stage head and neck cancer. However, TORS is limited by its steep learning curve and poor visualization of deep tumor margins. This randomized crossover study evaluated a surgical navigation system's potential to enhance accuracy and user experience with real-time, instrument-relative feedback. Seven Teflon beads (d = 2.381 mm) were embedded at the tongue base of a porcine pharynx-and-larynx model. Tongue blade compression and retraction were applied to the model to mimic intraoperative tissue deformation, reproducing the anatomical shifts that occur relative to preoperative imaging. Eight participants used the da Vinci Surgical system to localize the beads by placing pins under two conditions: (a) preoperative computed tomography with no navigation; (b) model-based visual navigation with quantitative instrument-to-target metrics. Surgical accuracy was determined by calculating the target localization error (TLE, pin-to-bead Euclidean distance) and the angular error (AE, pin axis trajectory to bead). Accounting for training level and bead depth, surgical navigation reduced TLE by 5.44 mm (95% CI, 4.02-6.86 mm; p = 2.00e-11) and AE by 8.47 degrees (95% CI, 6.21-10.72 degrees; p = 5.17e-11). Impressions of the system were generally favorable using a 5-point Likert survey and task duration (p = 0.26) or cognitive workload via the NASA-Task Load Index (p = 0.22) were not significantly affected. The navigation system demonstrated translational promise, offering improved target localization accuracy and more consistent performance across experience levels, two critical determinants of surgical quality in TORS.

Robotic Surgical Procedures↗
PubMed2026

Artificial intelligence in treatment prediction for skeletal Class III malocclusion: A systematic review.

In skeletal Class III patients, treatment options range from orthodontics to orthognathic surgery. Choosing the optimal approach requires a comprehensive clinical evaluation, which may be supported by AI tools. The aim of this study was to assess the performance of AI models in predicting the need for orthognathic surgery and in identifying predictors influencing treatment decisions. A PRISMA-guided electronic database search (PubMed, Web of Science; 2009-2024; English/French) was performed to identify studies using machine learning (ML) or deep learning (DL) on cephalometric and clinical data. After screening and assessment for eligibility, 15 studies were critically appraised. Model performance was summarized using accuracy, sensitivity, specificity, and the area under the curve (AUC). ML algorithms (particularly Random Forest and XGBoost) and DL models (ResNet-based convolutional neural networks (CNNs)) achieved high accuracy for predicting surgical need. Frequently selected predictors included Wits appraisal, ANB angle, the maxillomandibular ratio (Mx/Md), overjet, and the divergence of the lower gonial angle. AI methods show promise for assisting treatment decisions in Class III malocclusion, with Random Forest and XGBoost performing well on tabular cephalometric data and CNNs on imaging. Larger, multicentre datasets and external validation are needed to improve reliability, address bias, and support clinical implementation.

Humans↗
PubMed2026

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

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

Humans↗
PubMed2026

Effects of anodal transcranial direct current stimulation over the right primary motor cortex on a sequential motor finger tapping task in developmental stuttering.

INTRODUCTION: This study investigates the impact of anodal transcranial direct current stimulation (tDCS) on non-speech sequential motor practice in adults who stutter (AWS), compared to non-stuttering controls (ANS). Recent research has explored the effects of tDCS on speech fluency in stuttering. However, its effect on non-speech motor tasks has not yet been studied. METHODS: 20 AWS and 30 ANS right-handed participants were randomly assigned to anodal or sham tDCS conditions, performing a sequential finger tapping task. We targeted over the right primary motor cortex, stimulating at 2 mA for 20 min. Sequence duration and reaction time were analyzed. RESULTS: AWS analysis revealed that the anodal condition had significantly slower reaction times in the second half of the task compared to sham. For sequence durations, AWS in the anodal condition had slower overall sequence durations than the sham condition. However, there were no block-by-block differences in sequence duration. When comparing AWS and ANS, no significant differences were observed for sequence duration. However, there were significant differences in reaction time between AWS and ANS, specifically in earlier blocks. Additionally, there was no significant Group × Condition interaction. DISCUSSION: The findings suggest that anodal stimulation impeded finger sequencing in AWS, showing overall slower sequence durations and a diminishing effect on reaction times in the second half of the experiment, suggesting anodal tDCS may interact uniquely with the neural mechanisms in stuttering. Future studies should explore the effects of anodal tDCS on non-speech motor tasks to gain a broader understanding of its impact on motor control and motor learning.

Humans↗
PubMed2026

Timing of carbetocin administration in vaginal deliveries: a double-blind, randomized controlled trial.

OBJECTIVES: This study aimed to compare the efficacy of administering carbetocin before vs. after placental delivery in preventing postpartum hemorrhage (PPH) in low-risk vaginal deliveries. METHODS: The randomized controlled trial was conducted at Kartal City Hospital, Istanbul, Turkey. A total of 160 primiparous women with uncomplicated pregnancies who underwent vaginal delivery were enrolled. Participants were randomly assigned to receive 100&#x202f;&#x3bc;g of carbetocin either before or after placental delivery. The primary outcome was the incidence of PPH. Secondary outcomes included the need for additional uterotonics, manual removal of the placenta with consequent antibiotic administration, blood transfusions, maternal adverse events, and changes in hemoglobin levels at baseline and 24&#x202f;h postpartum. RESULTS: The incidence of PPH was significantly lower in the carbetocin-before group than in the carbetocin-after group (p=0.015). The carbetocin-before group had a significantly lower mean hemoglobin drop compared to the carbetocin-after group (p<0.001). The need for additional uterotonics was significantly higher in the carbetocin-after group (p<0.001). Manual placenta removal and the need for antibiotics were more frequent in the carbetocin-before group (p=0.017). No significant differences in adverse maternal events were observed between the groups. CONCLUSIONS: Administering carbetocin before placental delivery significantly reduces the incidence of PPH, blood loss, and the need for additional uterotonics. However, the increased rate of manual placenta removal necessitates individualized risk-benefit assessment; pre-placental administration may be most advantageous in women at elevated risk for PPH, in whom the hemorrhagic benefit outweighs the risks associated with manual extraction.

Humans↗
PubMed2026

Extreme Temperature and Incident Diabetes Risk Among Middle-Aged and Older Adults in China: A National Longitudinal Cohort Study.

BACKGROUND AND AIMS: The metabolic consequences of extreme temperature exposure in nondiabetic populations remain poorly understood. This study aimed to examine associations between heatwave and coldwave exposure and incident diabetes mellitus (DM) and impaired glucose tolerance (IGT) in middle-aged and older Chinese adults. METHODS: A total of 1803 China Health and Retirement Longitudinal Study participants aged &#x2265;45 years with normoglycemia at baseline were followed from Wave 1 (2011) to Wave 3 (2015). Eighteen extreme-temperature indicators were derived from city-level fifth-generation European Centre for Medium-Range Weather Forecasts atmospheric reanalysis data. Outcomes were classified according to American Diabetes Association criteria. Generalized linear mixed-effects models (GLMMs) were pooled across five imputed datasets, with Bonferroni correction for multiple comparisons (&#x3b1; = 0.0028) and sensitivity analysis adjusting for individual follow-up duration. RESULTS: All nine heatwave indicators showed odds ratios (ORs) < 1.0 for DM and IGT. HT9 (&#x2265;97.5th percentile, &#x2265;4 consecutive days) was the sole Bonferroni-significant result: OR = 0.845 (95% confidence interval [CI]: 0.802-0.890). Coldwave indicators showed no consistent associations. Age significantly modified the HT9 effect (P-interaction = 0.004): adults aged 65-84 showed a stronger inverse association (OR = 0.616) than those aged < 65 (OR = 0.921). CONCLUSION: Prolonged heatwave exposure was consistently associated with reduced diabetes risk, with pronounced age heterogeneity. Replication in larger prospective studies is warranted.

Humans↗
PubMed2026

Venomous Lepidoptera: defensive toxin systems, venom composition, and clinical significance.

Venomous Lepidoptera constitute an underrecognized yet medically significant group of toxin-producing arthropods that employ contact-mediated defensive envenomation through specialized integumentary structures such as setae, spines, and scoli. Unlike actively stinging arthropods, these insects deliver venom passively upon contact, eliciting a diverse spectrum of clinical manifestations collectively termed lepidopterism. Clinical outcomes range from localized pain and dermatitis to severe systemic effects, including hemorrhagic syndromes, complement activation, and chronic inflammatory disorders. Recent advances in proteomic and transcriptomic technologies have transformed our understanding of lepidopteran venoms, revealing unexpectedly complex toxin repertoires comprising serine proteases, phospholipases, pore-forming proteins, disulfide-rich peptides, neuroactive RF-amide peptides, and immune-modulating components. These findings have provided new insights into the molecular basis of toxicity, host-pathogen interactions, and the evolutionary diversification of venom systems within Lepidoptera. This review synthesizes current knowledge on the morphology of venom-delivery structures, venom composition, mechanisms of action, and associated clinical manifestations, while highlighting medically important taxa, particularly species of the genus Lonomia. The successful development of antivenom against Lonomia envenomation underscores the translational relevance of lepidopteran toxin research and its potential for therapeutic innovation. By integrating molecular, clinical, and evolutionary perspectives, this review repositions venomous Lepidoptera as a legitimate and important component of arthropod toxinology. Furthermore, it identifies critical methodological limitations and key knowledge gaps, providing a framework for future investigations aimed at advancing our understanding of toxin biology, immunopathology, and the development of novel biomedical applications.

Animals↗
PubMed2026

Association of time-averaged systemic immune-inflammation indices with in-hospital mortality after intracerebral hemorrhage: a retrospective study.

BACKGROUND: Systemic inflammation plays a central role in secondary brain injury following intracerebral hemorrhage (ICH). Although inflammatory indices such as the neutrophil-to-lymphocyte ratio (NLR), systemic immune-inflammation index (SII), and systemic inflammation response index (SIRI) are linked to poor outcomes, their associations with mortality are commonly assumed to be linear, potentially overlooking nonlinear patterns where mortality risk rises steeply at higher levels. METHODS: We conducted a retrospective study using the MIMIC-IV database, including 440 patients with non-traumatic ICH who were alive and remained in the ICU for at least 72&#xa0;h after admission. Mean NLR, SII, and SIRI were calculated from measurements obtained during this period. Multivariable logistic regression and restricted cubic spline (RCS) analyses were applied to assess their independent and nonlinear associations with in-hospital mortality. Model discrimination and calibration were internally validated using 1,000 bootstrap resamples. RESULTS: The in-hospital mortality rate was 26.1%. After multivariable adjustment, NLR and SIRI remained independently associated with mortality. Patients in the highest SIRI quartile had the highest risk of death (aOR&#xa0;=&#xa0;5.12; 95% CI: 2.57-12.24; p&#xa0;<&#xa0;0.001). RCS analysis revealed a significant nonlinear association between SIRI and mortality (p-nonlinearity&#xa0;<&#xa0;0.05), showing a steep risk increase at higher SIRI levels. Adding SIRI to the base model provided a modest improvement in discrimination (AUC 0.762 to 0.785, p&#xa0;=&#xa0;0.045) and significantly improved risk reclassification (cNRI&#xa0;=&#xa0;0.4778, p&#xa0;<&#xa0;0.001; IDI&#xa0;=&#xa0;0.0240, p&#xa0;=&#xa0;0.0151). CONCLUSIONS: Among patients with ICH who met the 72-hour eligibility criterion, higher 72-hour average SIRI was independently associated with in-hospital mortality. As a time-averaged measure, SIRI should be interpreted as a dynamic marker integrating the initial inflammatory state and the early clinical course rather than as a purely baseline prognostic factor. Although adding SIRI to the base model modestly improved discrimination and risk reclassification, it should be considered a candidate prognostic marker requiring external validation before clinical application.

Humans↗
PubMed2026

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

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

Humans↗
PubMed2026

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

Salmonella Typhimurium (S. typhimurium) is a major foodborne pathogen that poses a serious threat to public health. In this study, a colorimetric/electrochemical dual-mode biosensor assisted by artificial neural network (ANN) was developed for the sensitive detection of S. typhimurium. Fe3O4@PdIr nanocomposites with enhanced peroxidase-like activity and electrochemical performance were prepared and conjugated with an aptamer specific to S. typhimurium to obtain Fe3O4@PdIr-Apt. Through the sandwich binding of Fe3O4@PdIr-Apt and Apt to the target, the nanocomposites were attached to microplates or Au electrodes, thereby generating colorimetric and electrochemical signals. The ANN model deeply resolved the complex nonlinear relationship between the dual signals, enabling mutual correction and ultimately performing data fusion to output a single detection result, which significantly reduced the mean square error while improving detection sensitivity and reliability. This sensor exhibited a wide linear range of 2.7-2.7&#xa0;&#xd7;&#xa0;108&#xa0;CFU/mL and a low detection limit of 1.66&#xa0;CFU/mL. Additionally, this method was successfully applied to the detection of S. typhimurium in pork and milk, with a recovery rate of 95.19%&#xa0;&#x223c;&#xa0;104.07%. It indicated that the constructed sensor holds great practical potential for S. typhimurium detection.

Neural Networks, Computer↗
PubMed2026

Artificial intelligence for dental caries detection: An umbrella review.

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

Dental Caries↗
PubMed2026

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

Genomic identification and functional characterization of the nuclear receptor gene family in relation to sex determination and gonad development in the Pacific oyster (Crassostrea gigas).

Nuclear receptors (NRs) are a large superfamily of transcription factors that control a wide range of physiological processes by modulating the expression of downstream target genes. Numerous studies have confirmed that NR family members play critical and conserved roles in sex determination and gonadal development across metazoans. However, in mollusks, systematic characterization of NRs and their potential functions in gonadal regulation remain largely unexplored. In this study, 46 NR gene family members in the Pacific oyster (Crassostrea gigas) were identified and assigned to eight subfamilies. All NR family members contain at least one of the two core domains (DNA-binding domain, DBD; ligand-binding domain, LBD), and conserved exon-intron structures were observed within the same subgroup, indicating their evolutionary conservation. Furthermore, expression profiling revealed high expression of CgNR2F, CgNR5A1-1, and CgNR0B1 in undifferentiated gonads, suggesting their potential involvement in sex determination. CgNR1A and CgNR2E5 were specifically expressed in female gonads and exhibited female-biased expression patterns, indicating a putative role in ovarian development. Moreover, CgNR3A and CgNR3B showed high expression levels during the undifferentiated stage and early male development stage, implying their possible participation in male gonadal development and gametogenesis. These results expand the understanding of the NR gene family in C. gigas and help elucidate the potential functions of NR genes in sex determination and gonadal development.

Animals↗