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

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

Animals

Analysis of the Relationship between Early Clinical Factors and Glasgow Outcome Scale in Patients With Traumatic Brain Injury.

OBJECTIVE: This study aimed to evaluate the association between early clinical factors and the Glasgow outcome scale (GOS) in patients with traumatic brain injury (TBI). METHODS: We conducted a retrospective analysis of 98 TBI patients who underwent emergency surgery between January 2021 and January 2024. Based on GOS scores at 6 months post-surgery, patients were classified into a favorable outcome group (GOS&#xa0;&#x2265;&#xa0;4, defined as moderate disability or good recovery,&#xa0;n = 58) and an unfavorable outcome group (GOS < 4, i.e., death, persistent vegetative state, or severe disability,&#xa0;n = 40). Baseline and early clinical parameters were compared between groups. Statistically significant variables from univariate analysis were entered into a multivariate logistic regression model to identify independent prognostic factors. RESULTS: Significant intergroup differences were observed in age, time from injury to surgery, bleeding site, midline shift, Glasgow coma scale (GCS) score at admission, blood glucose level, and D-dimer level (all p < 0.05). Multivariate analysis confirmed that age, time from injury to surgery, GCS score, blood glucose, and D-dimer level were independent predictors of GOS (all p < 0.05). CONCLUSION: Early clinical factors, including age, time to surgery, GCS score, blood glucose, and D-dimer level, independently influence GOS in TBI patients. Time from injury to surgery&#xa0;emerged as a potentially modifiable factor in this cohort, suggesting that minimizing delays may improve outcomes.

Humans

Human iPSC-EV-loaded nanofiber stent coatings accelerate vascular repair by enhancing EGFR/HIF-1&#x3b1; signaling and suppressing ROCK1-mediated remodeling.

Arterial disease management is shifting from antiproliferative drug-eluting stents toward approaches that restore endothelial function and modulate smooth muscle cell (SMC) behavior. Stem cell-derived extracellular vesicles (EVs) carry miRNAs that promote endothelial proliferation and migration while restraining aberrant SMC growth and inflammation. Here, human induced pluripotent stem cell (iPSC)-derived EVs were collected by ultracentrifugation and incorporated into 50:50 poly (lactic-co-glycolic acid) (PLGA 503) core-shell nanofibrous membranes, which were fabricated as stent coatings for sustained release to overcome rapid clearance and poor tissue retention. EVs derived from three independent iPSC lines all enhanced tube formation in human umbilical vein endothelial cells (HUVECs) under hypoxic and serum-starved conditions and revealed a trend toward reduced platelet-derived growth factor-BB (PDGF-BB)-induced smooth muscle cell (SMC) migration. The fabricated core-shell nanofibers enabled sustained EV release, maintaining therapeutic efficacy for 28 days. Small RNA sequencing (NGS) analysis demonstrated that EVs from these independent iPSC lines shared miR-148a-3p and members of the miR-92 family, which collectively accounted for more than 75% of the reads within the 25 top-expressed miRNA set. In vitro, iPSC-EVs enhanced HUVEC proliferation and survival signaling by downregulating the negative regulators ERRFI1 and VHL, which are specific targets of miR-148a-3p and the miR-92 family, thereby activating the EGFR and HIF-1&#x3b1; axes and driving downstream ERK1/2 and VEGF expression under hypoxic and serum starvation stress conditions. Concurrently, iPSC-EVs prevented PDGF-BB-induced SMC phenotypic switching by downregulating ROCK1, a target of miR-148a-3p, thereby inhibiting downstream AKT and ERK signaling and preserving contractile markers while suppressing the synthetic phenotype. In vivo, the iPSC-EV-functionalized scaffolds significantly accelerated re-endothelialization and inhibited neointimal hyperplasia, evidenced by the upregulation of angiogenic factors (VEGF, CD31) and the concurrent suppression of pathological remodeling markers (&#x3b1;-SMA, MMPs) and inflammatory cytokines (IL-6, TGF-&#x3b2;1). Therefore, iPSC-EVs enriched with specific miRNAs and delivered via PLGA 503 core-shell nanofibers promote endothelial repair while suppressing SMC overgrowth, providing a promising strategy for vascular healing.

Core-shell nanofibers

The role of artificial intelligence in the diagnosis and prognosis of traumatic brain injury based on brain CT scans: a systematic review.

Traumatic brain injury (TBI) is a leading cause of emergency department visits and a major contributor to injury-related mortality and long-term neurological disability. Non-contrast computed tomography (CT) is the gold-standard imaging modality for the rapid diagnosis of TBI. Clinical outcomes depend strongly on early detection and prompt acute management. Artificial intelligence (AI)-based models may support faster automated identification of traumatic findings and early prediction of patient prognosis.&#xa0;A systematic literature search was conducted in PubMed/MEDLINE, Scopus, IEEE Xplore, ACM Digital Library, and the Cochrane Library in accordance with PRISMA 2020 guidelines to evaluate AI-based models for automated detection of TBI-related findings on CT and for prediction of clinical outcomes. Risk of bias and applicability were assessed using QUADAS-2 for diagnostic accuracy studies and PROBAST&#x2009;+&#x2009;AI for prediction model studies.&#xa0;Twenty-two studies were included. Sixteen studies evaluated diagnostic tasks and 10 evaluated prognostic outcomes, with four studies contributing to both categories. Diagnostic performance was generally high, with many studies reporting AUC values approaching or exceeding 0.90, particularly for larger lesion volumes.Prognostic performance was more variable, with moderate to high discrimination and substantial heterogeneity. Only 9 studies incorporated independent external validation, and performance was frequently lower in external cohorts. All prognostic model studies were judged to be at high overall risk of bias using PROBAST&#x2009;+&#x2009;AI, and most diagnostic accuracy studies also demonstrated high or unclear risk of bias in at least one QUADAS-2 domain, most frequently in patient selection.&#xa0;AI-based models applied to brain CT demonstrate strong technical performance for both diagnostic and prognostic tasks in TBI. However, most studies relied on retrospective designs and lacked independent external validation which limits models generalizability and raises concern for potential overfitting. Prospective, multicenter studies with standardized methodologies and rigorous external validation are required before widespread clinical implementation.

Humans

Effects of strength and balance training on the structure of the aging brain.

BACKGROUND: While it is established that motor training induces structural changes in the brains of young adults, structural adaptations in aging brains are less studied. METHODS: This randomized controlled study investigated the impact of long-term strength and balance training on the structural plasticity in 60 elderly adults (64 - 82 years old, 70.6 &#xb1; 4.7) using multi-modal neuroimaging. We compared the effects of three months of strength training to balance training of the same duration and to a passive control group. Voxel-based morphometry (VBM) and tract-based spatial statistics (TBSS) were used to assess grey matter (GM) and white matter (WM) plasticity. White matter tract integrity (WMTI) modelling was employed to explore the microstructural underpinnings of white matter alterations. RESULTS: We found that strength training was associated with changes in diffusion metrics consistent with white matter microstructural remodeling, specifically increased extra-axonal axial diffusivity in the bilateral inferior fronto-occipital and longitudinal fasciculi. Additionally, both balance and strength training mitigated reductions in axonal water fraction in the splenium of the corpus callosum and the right posterior corona radiata observed in the control group. CONCLUSION: These results underscore the potential relevance of strength and balance training to induce beneficial neural plasticity by counteracting aging-related demyelination in the corpus callosum and highlight the specific role of strength training in facilitating white matter reorganization in key transmission fiber pathways.

Humans

Applications of quantum AI in brain disorder diagnosis: A systematic review.

BACKGROUND AND OBJECTIVE: Brain disorder diagnosis and prediction remain challenging because neuroimaging, electrophysiological, behavioral, and multimodal data are high-dimensional, noisy, heterogeneous, and limited by small clinical cohorts. This systematic review synthesised applications of quantum artificial intelligence (QAI) for brain disorder diagnosis, prediction, detection, and monitoring. METHODS: Following PRISMA guidelines, studies published from 2016 to 13 January 2026 were retrieved from Scopus, Web of Science, and IEEE Xplore. After screening, 36 studies met the eligibility criteria and were qualitatively analysed according to disorder category, data modality, QAI method, implementation setting, validation strategy, and performance. RESULTS: At the broader disease-group level, neurodegenerative disorders were the most frequently investigated, followed by mental health and psychiatric disorders. At the individual level, Parkinson's disease and schizophrenia were the leading applications, followed by depression, anxiety, Alzheimer's disease, and stress-related tasks. MRI-based modalities were the most frequently used data source, followed by multimodal data and EEG. Methodologically, primary QAI approaches were dominated by quantum neural and QDL architectures, followed by quantum-inspired optimization or feature-selection methods and quantum-kernel/conventional QML classifiers. Qiskit/IBM Quantum and PennyLane were the most frequently reported quantum software frameworks. However, most studies relied on simulators, classical quantum-inspired implementations, or unclear implementation settings, with limited real-hardware evaluation. CONCLUSIONS: QAI shows emerging potential for brain disorder analysis, particularly through hybrid quantum-classical learning, quantum neural architectures, quantum-kernel methods, and quantum-inspired optimization. Nevertheless, current evidence remains preliminary and requires larger datasets, subject-level and external validation, fair classical benchmarking, noise-resilient circuits, real quantum hardware evaluation, explainability, and clinical validation.

Humans

Artificial intelligence (AI) uses in stereotactic radiosurgery (SRS): diagnosis with brain metastasis (BM) - A systematic review.

BACKGROUND: Brain metastases (BM) are the most common intracranial tumors in adults, and stereotactic radiosurgery (SRS) has become a mainstay of management. However, several diagnostic challenges persist in the SRS pathway, particularly the differentiation of radiation necrosis (RN) from true tumor progression, which conventional MRI and even advanced imaging techniques often cannot reliably resolve. Recent advances in artificial intelligence (AI) offer the potential to address these diagnostic limitations. This systematic review synthesizes current literature on AI applications for MRI-based diagnostic decision support in BM patients undergoing SRS, with a focus on radiomics and deep learning tools for distinguishing RN from progression, classifying molecular and histologic subtypes, and predicting treatment response. METHODS: A systematic review was performed in accordance with PRISMA guidelines. PubMed, Web of Science, and Scopus were searched using a targeted query combining terms related to AI, brain metastasis, diagnosis or imaging, and SRS. After screening 483 records and applying strict inclusion and exclusion criteria, 18 studies published between 2015 and 2025 were included. Data were extracted on study design, cohort characteristics, imaging modality, AI methodology, validation strategy, and reported diagnostic performance. RESULTS: Among the 18 included studies, AI models demonstrated strong performance across diagnostic tasks in the BM-SRS pathway. The differentiation of RN from true tumor progression was the most extensively studied application, addressed by 14 of 18 studies, with reported AUCs ranging from 0.71 to 0.94. Support vector machines, random-forest ensembles, convolutional neural networks, and transformer-based multimodal architectures were widely used. The literature evolved from single-sequence radiomic classifiers in 2018 to multimodal deep learning frameworks fusing imaging with clinical and genomic data in 2025. Contrast-enhanced T1-weighted MRI was the dominant imaging input, and texture-based radiomic features (GLCM, GLSZM, GLDM, and wavelet-derived features) were the most consistently predictive. The highest-performing models reached AUCs of 0.85-0.91 through multimodal integration of imaging with clinical and genomic features, and consistently outperformed expert neuroradiologist read on matched cases. Remaining studies addressed longitudinal segmentation-based detection of local failure and adverse radiation effects, BRAF mutation status in melanoma BM, early Gamma Knife treatment response, and primary tumor histology classification, with more variable performance. CONCLUSION: AI models, particularly those integrating MRI-derived radiomic features with clinical and genomic data, show high accuracy in supporting diagnostic decisions for BM patients treated with SRS. The post-SRS differentiation of radiation necrosis from true tumor progression has reached the greatest level of maturity and is closest to clinical translation, with potential to reduce unnecessary biopsies, personalize surveillance intervals, and rationalize treatment-pathway decisions. Other diagnostic applications, including molecular subtyping and primary tumor histology classification, remain exploratory and require further multicenter validation. Integration of AI tools into multidisciplinary tumor-board workflows, combined with prospective validation and standardized reporting, will be essential to realize the full clinical benefits of AI in SRS for brain metastases.

Humans

Individual differences in brain dynamics across a social cognition network induced by cortico-cerebellar tDCS in adults with autism spectrum disorder (ASD).

Autism spectrum disorder (ASD) is a neurodevelopmental condition with core diagnostic domains of social communication impairments, restricted interests and repetitive behaviors. Idiosyncratic brain organization is a potential hallmark of ASD. Previous transcranial direct current stimulation (tDCS) studies often targeted dorsolateral prefrontal cortex, with changes oin brain dynamics averaged across the cohort. We utilized a magnetoencephalographic (MEG) array to characterize individual differences in brain dynamics induced by cortico-cerebellar tDCS across nodes of a social cognition network. A randomized, sham-controlled, double-blind, within-subject clinical trial was conducted in a cohort of 24 young adults with ASD or high autistic traits. Two separate sessions of computerized social learning activities were combined with verum/sham tDCS, with anodal electrode over right temporoparietal junction (TPJ) and cathode on right deltoid. Following stimulation, theta- and alpha-band activity were evaluated within nodes of a social cognition network: bilateral TPJ, fusiform, medial prefrontal cortex and Crus I/II of cerebellum. Idiosyncratic participant-specific up- and down-regulation of theta- and alpha-band activity occurred across the network. Activity in right Crus I/II, a region inundated by the stimulation current, strongly correlated with the change of activity summed across all cerebral cortical nodes in theta- but not alpha-band. Intrinsic theta-band activity is believed to mediate input/output relationships in cerebellar cortex and to drive synaptic plasticity. These results suggest that theta-band stimulation of cerebellar cortex might be an effective therapy for individuals on the autism spectrum who present with cerebellar hyperactivity.

Humans

Effectiveness of hyperbaric oxygen in traumatic brain injury patients: A systematic review and meta-analysis.

BACKGROUND: Traumatic brain injury (TBI) is the most common neurological disorder and a leading cause of global mortality and disability. Although growing evidence suggests potential benefits of Hyperbaric Oxygen Therapy (HBOT) for TBI, its efficacy remains controversial. METHODS: We systematically searched PubMed, Embase, Cochrane Library, and Web of Science from inception to March 2026. Randomized controlled trials (RCTs) evaluating HBOT versus any comparator including sham, standard care and no treatment in adults with TBI were included. Two independent reviewers screened records, extracted data, and assessed risk of bias using the Cochrane Risk of Bias tool. Heterogeneity was assessed using the I&#xb2; statistic. Effect sizes were pooled using random/fixed-effects models per heterogeneity results. RESULTS: 8 studies involving 570 participants were included. HBOT significantly improved computerized cognitive performance (SMD = 0.23, 95% CI: 0.07-0.40, p&#x202f;=&#x202f;0.004, I&#xb2; = 0%), executive function and processing speed (SMD = -0.59, 95% CI: -0.93 to -0.26, p&#x202f;=&#x202f;0.0005, I&#xb2; = 30%), memory function (SMD = 0.33, 95% CI: 0.03-0.63, p&#x202f;=&#x202f;0.03, I&#xb2; = 0%), and sleep quality (MD = 1.98, 95% CI: 0.07-3.88, p&#x202f;=&#x202f;0.04, I&#xb2; = 65%). No significant benefits were observed for Glasgow Outcome Scale (RR = 1.57, 95% CI: 0.55-4.44, I&#xb2; = 87%), PTSD symptoms (MD = -3.05, 95% CI: -7.05-0.95, I&#xb2; = 67%), neurobehavioral symptoms (MD = -9.06, 95% CI: -32.13-14.00, I&#xb2; = 97%), and emotional distress (SMD = 0.25, 95% CI: -0.32-0.81, I&#xb2; = 85%). Most adverse events were mild and transient. CONCLUSION: HBOT demonstrates domain&#x2011;specific benefits for cognitive function and sleep quality in TBI patients, predominantly those with mild TBI. However, evidence for PTSD, neurobehavioral symptoms, and emotional distress remains uncertain. Furthermore, the applicability of current evidence to moderate-to-severe TBI populations is restricted.

Humans

Reducing state anxiety with alpha-frequency transcranial alternating current stimulation.

BACKGROUND: Anxiety reactivity to acute stress is a transdiagnostic vulnerability factor. We tested whether a single session of alpha-frequency transcranial alternating current stimulation (tACS) targeting the frontoparietal control network reduces stress-evoked state anxiety in healthy adults. METHODS: In a randomized, blinded, sham-controlled study, 42 participants (mean age 58.9&#xa0;years) completed an acute stress task before and after stimulation. The task was an adapted moving-circles paradigm in which circle collisions triggered a brief aversive event (mild electric shock plus unpleasant noise and a white flash). Active stimulation consisted of 20&#xa0;min of 10-Hz tACS (2.0&#xa0;mA/channel; 30-s ramp up/down) delivered via electrodes at F3, P3, Cz, and T7 (0&#xb0; phase at F3/P3; 180&#xb0; at Cz/T7). Sham stimulation used the same montage and ramp periods but no sustained current. RESULTS: State anxiety showed a significant Time &#xd7; Protocol interaction (F(1,35)&#xa0;=&#xa0;4.22, p&#xa0;=&#xa0;.047): STAI-S decreased after active tACS (&#x394;&#xa0;=&#xa0;-3.16) but increased slightly after sham (&#x394;&#xa0;=&#xa0;+1.17). Perceived stress appraisal (SAAS) did not change. Resting-state alpha power at F3/P3 showed no reliable pre-post effects. During the task, left-frontal relative alpha differed by protocol and showed a trend toward larger increases following active tACS. Electrodermal and pupil indices changed across sessions in both groups, with no differential stimulation effects. CONCLUSIONS: A single alpha-tACS session produced a modest, selective reduction in stress-evoked state anxiety, supporting oscillatory neuromodulation as a scalable approach to dampen anxiety reactivity.

Humans

Cognitive-metabolic relationship in temporal lobe epilepsy: A systematic review.

OBJECTIVE: To summarize the current literature on neurometabolic dysfunction identified through brain imaging and its cognitive correlates in temporal lobe epilepsy (TLE). BACKGROUND: Cognitive decline contributes to chronic disability in TLE. The pathophysiology of cognitive decline in TLE is poorly understood, limiting therapeutic advances. Characterizing metabolic changes in patients with TLE and cognitive impairment may identify biomarkers and inform new treatment strategies. DESIGN/METHODS: We conducted a systematic review of five major databases, gathering studies published through December 2024, in accordance with PRISMA guidelines. We included all observational studies describing associations between metabolic imaging findings and cognitive measures in TLE. RESULTS: Of 1449 reports, 38 met the inclusion criteria, encompassing 1161 patients with TLE aged 5-66&#xa0;years. Twenty-two studies applied fluorodeoxyglucose (18F-FDG) positron emission tomography (PET) to assess interictal brain glucose metabolism. Two studies utilized PET with other tracers to assess more specific metabolic aspects. Fourteen studies used proton magnetic resonance spectroscopy (1H-MRS) to quantify local concentrations of brain metabolites. Impairment of verbal memory was consistently associated with left temporal lobe metabolite changes. Non-memory cognitive impairments correlated with changes in glucose metabolism, N-acetylaspartate, and gamma-aminobutyrate in both temporal and extratemporal areas. CONCLUSION: 18F-FDG PET remains the most widely used imaging modality to assess cognitive-metabolic correlates in TLE, while other PET tracers and 1H-MRS are potentially underexplored. Verbal memory impairment correlates robustly with left temporal dysmetabolism. Cognitive impairment in TLE is multifaceted and correlates with measurable changes in metabolism in both temporal and extratemporal regions. While our synthesis was restricted by some methodological limitations, these neurometabolic signatures may hold promise as potential biomarkers for identifying risk of cognitive decline and highlight avenues for future research.

Humans

Ultra-high-field 7T MRI reveals neural abnormalities of attention networks in relation to cognitive impairment in hypertension.

Hypertension is a significant risk factor for cognitive impairment (CI), yet the corresponding neural network abnormalities remain underexplored. In this study, we examined the associations among global and domain-specific cognitive dysfunction, neuroimaging measures, and blood pressure in a subgroup of hypertensive patients with CI (N&#xa0;=&#xa0;41) from a randomized controlled trial who underwent ultra-high-field 7&#xa0;T MRI. Structural atrophy related to CI was localized to regions overlapping the attention networks. Both whole-brain and within-network dysfunction of the attention networks were associated with worse global cognitive performance. Notably, hyperconnectivity within key attention network hubs, including the right anterior insula and posterior intraparietal sulcus, was associated with declined processing speed in hypertensive patients, mediating the association between pulse pressure and processing speed. These findings provide new insights into the neural pathophysiology of hypertension-related CI and suggest potential network-based targets for intervention.

Magnetic Resonance Imaging

Comparison of posterior cellular bonegraft options for single-level lumbar spinal fusion: a randomized trial.

BACKGROUND: Iliac bone autograft (IBG) is osteoinductive/osteogenic/osteoconductive but requires an additional harvesting procedure with known morbidities. Bone morphogenic protein (BMP) is osteoinductive and effective in obtaining fusion but is used off label for posterior fusion, has multiple side effects, and is expensive. Stem cell bone products, both auto- and allograft are attractive osteoinductive alternatives that avoid morbidity related to the graft donor site and may have a better safety profile than BMP. Morcelized allograft bone is osteoconductive but not osteoinductive or osteogenic. PURPOSE: Evaluate and compare the effectiveness of 6 types of viable or osteoinductive bone graft material in obtaining a solid posterior spinal fusion (PSF) for single level anterior/posterior lumbar spinal fusion. The bone grafts were IBG, BMP, autogenous stem cells (MSC) from concentrated bone marrow aspirate (BMA), allograft MSC from bone marrow, adipose tissue, or amniotic fluid, combined with inert cancellous allograft (Allo). STUDY DESIGN/SETTING: Prospective, single-blinded randomized study of 6 cohorts and inert historical control. PATIENT SAMPLE: Elective anterior-posterior lumbar spinal fusion of 175 patients. OUTCOME MEASURES: Assessments included pre and postoperative back and leg pain (VAS) scores, pain drawing, disability (ODI) scores, pain medication usage, and 1-year postoperative thin-cut CT scans (read by blinded radiologists). METHODS: Patients who were surgical candidates for a 1-level anterior/posterior lumbar fusion were randomized to 1 of 6 types of posterior bone graft alternatives: IBG, BMP, BMA, allograft MSC derived from bone marrow combined with morcelized Allo (cAlloBone), adipose derived MSC combined with morcelized Allo (cAlloFat), or amnion derived MSC combined with morcelized Allo (cAlloAm). Historical Allo patients served as a negative control group. Each group (n 27) had prospective outcomes and were followed for a minimum of 2 years. Fusion rate and outcomes were compared and referenced to Allo group. RESULTS: All but 5 patients had a solid ASF. The posterior fusion rates were 98% for IBG, 94% for BMP, 85% for BMA, 67% for cAlloBone, 64% for cAlloFat, 62% for cAlloAm, and 50% for Allo. Outcomes were significantly improved for all measures for all groups and there was no difference between groups except cAlloFat had slightly greater improvement in back pain in the 7-12 month follow-up period. BMP was the most expensive graft material; cellular allografts had a high-cost relative to fusion rate. CONCLUSIONS: For single level ASF/PSF, the PSF fusion rate was significantly greater for IBG and BMP followed by BMA. Various allograft MSC bone graft options resulted in lower fusion rates but may be greater than Allo. Outcomes were uniformly improved regardless of the type of graft used or the fusion status of the posterior fusion as long as the interbody fusion was solid. If bone graft cost savings is a consideration for PSF, then IBG has the greatest radiographic value, and Allo the greatest clinical value as long as the anterior interbody fusion is solid.

Humans

Diagnostic and Predictive Value of Circulating and Exosomal microRNAs in Ferroptosis-Associated Neurological Conditions: A Systematic Review and Meta-analysis.

Circulating microRNAs (miRNAs) have emerged as potential non-invasive markers for intracranial pathology, yet their diagnostic accuracy and relationship with ferroptosis-mediated neuronal damage remain poorly defined. The primary objective of this study was to evaluate the diagnostic and predictive potential of circulating and exosomal miRNAs across ferroptosis-associated neurological conditions and to explore their associations with ferroptosis-related pathways. Following PRISMA-DTA guidelines, a systematic literature search was conducted across PubMed, Scopus, Cochrane, and ScienceDirect, identifying 205 records. After screening for human clinical cohort validation, 7 studies were included in the qualitative synthesis and 5 in the quantitative meta-analysis. Pooled Area-under-the-Curve (AUC) was calculated using a random-effects inverse-variance model, while prognostic correlation coefficients (r) were synthesized using Fisher's Z-transformation. Methodological quality was assessed via QUADAS-2. Analysis of 7 clinical cohorts provided heterogeneous evidence on the diagnostic and prognostic potential of miRNAs. Random-effects pooling of the two eligible diagnostic AUC estimates yielded an exploratory pooled AUC of 0.87 (95% CI, 0.79-0.94; I2&#x2009;.90%). Prognostic synthesis of Group 2 identified an exploratory association between miRNA levels and clinical severity scales (exploratory pooled correlation coefficient of 0.67 (95% CI: 0.56-0.76; I2&#x2009;.714.4%). Selected miRNAs were mapped to ferroptosis-associated regulators, including SLC7A11, ABCB8, and SLC40A1. Exosomal miRNAs hold potential to indicate disease-associated molecular information, although comparative clinical evidence remains yet to be explored. Circulating and exosomal miRNAs show promising diagnostic and prognostic potential across selected neurological conditions. These findings highlight a potential mechanistic association between miRNA expression and ferroptosis-mediated neuronal injury.

Humans

Neurocorrelates of nocturnal enuresis in pre-adolescent children.

INTRODUCTION: Nocturnal enuresis (NE) is a common neurodevelopmental condition, yet its underlying neural mechanisms remain unclear. This study leverages the large-scale Adolescent Brain Cognitive Development (ABCD) dataset to identify structural and functional brain correlates associated with active symptoms and the resolution of bedwetting. METHODS: Using cross-sectional data from 3472 participants aged 9-10 years, children were categorized into three groups: active nocturnal enuresis (ANE, n = 225), history of nocturnal enuresis (HNE, n = 1171), and healthy control groups (CG, n = 2076). Multimodal neuroimaging protocol evaluated macrostructural properties via structural MRI (sMRI), microstructural white matter integrity via diffusion MRI (dMRI), and functional connectivity via resting-state fMRI (fMRI). Group differences were evaluated using linear models within an ANCOVA framework, adjusting for intracranial volume and handedness with False Discovery Rate (FDR) correction. RESULTS: Compared to controls, the ANE group exhibited a significant volume deficit in the right caudate, decreased sulcal depth in the left insula, and lower internal correlation within the Cingulo-Opercular Network (CON). Conversely, the dry HNE group demonstrated significant structural adaptations, including bilaterally larger putamen volumes and increased right caudate volume compared to the ANE group. The HNE group also showed increased microstructural density (decreased mean diffusivity) in the bilateral hippocampus and an increased cortical surface area in the left insula. Both NE groups demonstrated persistently reduced functional coupling within the CON. CONCLUSIONS: Nocturnal enuresis appears to be associated with a potential complex central signaling deficits. Reduced internal correlation within the CON across both active and former bedwetters indicates a potential for impairment in processing internal homeostatic bladder signals during sleep.

Humans

Prognostic significance of NLRP-3 expression in solid cancers: a systematic review and meta-analysis.

BACKGROUND: The inflammasome is a critical immunological sensor comprised of NLRP-3, ASC, and CASPASE-1. Mutations in NLRP-3 are prevalent in inflammatory diseases. However, the role of NLRP-3 in cancer is controversial. This study investigates whether NLRP-3 expression is associated with clinical outcomes in patients with solid cancers. METHODS: PubMed (MEDLINE), Embase, Cochrane, and Google Scholar were searched for articles reporting NLRP-3 expression and disease outcome data in cancer patients. RevMan Review Manager was used to calculate pooled hazard ratios and Mantel-Haenszel pooled odds ratios. RNA sequencing datasets from the TCGA Pan-Cancer (PANCAN) were used for external validation. RESULTS: Patients with higher NLRP-3 expression showed a significant association with larger tumor size, advanced tumor grade, TNM stage, and presence of metastasis. High NLRP-3 expression has a significant association with poor OS (HR:2.12, 95% CI = 1.49-3.03), p&#x2009;<&#x2009;0.0001) and DFS (HR:1.86, 95% CI = 1.30- 2.65, p&#x2009;=&#x2009;0.0007). Subgroup analysis showed that higher NLRP-3 expression is associated with worse OS in head and neck cancer (HR: 2.77, 95% CI = 1.88-4.09, p&#x2009;<&#x2009;0.00001), colorectal cancers (HR:2.14, 95% CI= 1.59- 2.87, p&#x2009;<&#x2009;0.00001), and pancreatic cancer patients (HR: 3.19, 95% CI = 1.73-5.91, p&#x2009;=&#x2009;0.0002). CONCLUSION: High NLRP-3 expression is associated with advanced disease and poor outcomes in many solid tumours.

Humans

A multicenter randomized phase II/III trial of salvage treatment for refractory primary central nervous system lymphoma using tirabrutinib: JCOG2314 (ReSTART).

Primary central nervous system lymphoma (PCNSL) is an aggressive malignancy. Patients refractory to high-dose methotrexate-based induction therapy have an extremely poor prognosis. Although whole-brain radiotherapy (WBRT) is the standard salvage treatment and provides potent tumor control, early functional deterioration and late neurocognitive toxicity remain major concerns. A phase I/II trial on relapsed or refractory PCNSL demonstrated favorable efficacy and tolerability of tirabrutinib, a second-generation selective Bruton's tyrosine kinase inhibitor. Tirabrutinib's oral administration has enabled outpatient management. However, its clinical value for induction-refractory PCNSL remains uncertain. We designed a multicenter, randomized phase II/III trial (JCOG2314) to assess the non-inferiority of tirabrutinib to WBRT in overall survival and its potential to reduce functional deterioration and cognitive impairment. A total of 94 patients from 49 institutions will be enrolled over 4 years. The trial has been registered in the Japan Registry of Clinical Trials (study number: jRCT1031250645).

Humans

Factors Associated With Accelerated Fracture Healing in Patients With Traumatic Brain Injury and Extremity Comminuted Fractures: A Retrospective Case-Control Study.

OBJECTIVE: Although traumatic brain injury (TBI) has been clinically associated with accelerated bone healing, the factors that determine which patients experience this phenomenon remain poorly defined, and previous findings are conflicting. This study aimed to investigate the clinical factors associated with accelerated fracture healing in patients with TBI combined with comminuted fractures of the limbs, so as to provide an evidence-based foundation for elucidating the clinical phenomenon of TBI-promoted fracture healing. METHODS: A retrospective case-control study design was employed. Patients between January 2020 and April 2024 with concurrent diagnoses of TBI and comminuted fractures were included. Based on radiographic findings and RUST/mRUST scores, patients were divided into an accelerated healing group (AHG) and a normal/delayed healing group (NDHG). Clinical data including demographics (age, sex, BMI), TBI characteristics (injury site, GCS score), admission laboratory indices (blood count, coagulation function, inflammatory markers), and fracture site/local soft tissue conditions, as well as functional outcomes assessed by the Short Musculoskeletal Function Assessment (SMFA) questionnaire at final follow-up were collected. Univariate analysis and multivariate logistic regression analysis were used to identify independent factors influencing accelerated fracture healing. Receiver operating characteristic (ROC) curves were plotted to evaluate their predictive value. RESULTS: A total of 119 patients were included, with 69 in the AHG and 50 in the NDHG. Significant differences were observed between the two groups in terms of age, BMI, GCS score, and platelet count (p&#x2009;<&#x2009;0.05). Univariate analysis showed that age, BMI, GCS score, red blood cell count, and platelet count were associated with accelerated fracture healing (p&#x2009;<&#x2009;0.20). Multivariate logistic regression analysis indicated that younger age (OR&#x2009;=&#x2009;0.875, 95% CI: 0.821-0.934) and lower GCS score (indicating more severe TBI; OR&#x2009;=&#x2009;0.490, 95% CI: 0.339-0.707) were independent predictors of accelerated fracture healing. ROC curve analysis showed that the area under the curve (AUC) for age and GCS score in predicting accelerated healing were 0.893 and 0.851, respectively. CONCLUSIONS: In patients with TBI combined with comminuted fractures, younger age and greater TBI severity (lower GCS score) are independent predictors of accelerated fracture healing. These findings assist clinicians in the early identification of patients with high healing potential to optimize treatment strategies, facilitate the early identification of high-risk patients, and provide clinical clues for further exploration of the molecular mechanisms underlying neurohumoral regulation of bone regeneration.

Humans