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PubMed2026

Comparison of the clinical efficacy, safety and EEG functional connectivity changes between 18-Hz rTMS and iTBS of accelerated dTMS treatment for major depressive disorder: a randomized controlled trial.

Although the antidepressant efficacy of 18-Hz deep transcranial magnetic stimulation (dTMS) has been validated, its prolonged treatment duration has considerable limitations for treatment capacity and patient adherence. Therefore, novel short-course protocols such as accelerated dTMS and intermittent theta burst stimulation (iTBS) present promising alternative options. Here we addressed the question of whether iTBS of accelerated dTMS achieves comparable therapeutic and electrophysiological effects to accelerated dTMS with the conventional 18-Hz rTMS protocol in patients with major depressive disorder (MDD). In a randomized controlled trial (n = 73), participants received either 18-Hz rTMS of accelerated dTMS (rTMS-dTMS group), iTBS of accelerated dTMS (iTBS-dTMS group), or pharmacotherapy alone (drug group). Both dTMS protocols were administered twice daily for 10 days targeting the left lateral prefrontal cortex including the dorsolateral region. Results showed that Hamilton Depression Rating Scale (HAMD) score of the iTBS-dTMS group decreased significantly from 22.5 ± 3.7 before treatment to 8.2 ± 4.1 after treatment (t = 15.900, p < 0.001). HAMD score of the rTMS-dTMS group decreased significantly from 21.3 ± 2.9 before treatment to 8.0 ± 3.8 after treatment (t = 17.232, p < 0.001). The drug group also exhibited significantly improved patients' mood symptoms, and the HAMD score decreased from 24.7 ± 6.8 to 14.0 ± 5.0 (t = 6.363, p < 0.001). The treatment response rate was 85.7% in the iTBS-dTMS group and 76.9% in the rTMS-dTMS group, which was much higher than that of the drug group (42.1%). The remission rate was 50.0% in the iTBS-dTMS group and 42.3% in the rTMS-dTMS group, which was significantly higher than 10.5% of the drug group. We demonstrate here that both accelerated dTMS protocols significantly reduced HAMD scores, improved the response rates, and remission rates, outperforming pharmacotherapy alone. Resting-state EEG analysis further revealed unique frequency-specific functional connectivity (FC) modulation effects: the rTMS-dTMS group primarily exhibited weakened alpha-band functional connectivity within the fronto-occipital, fronto-temporal and fronto-central networks after treatment, whereas the iTBS-dTMS group predominantly demonstrated reduced theta-band functional connectivity within the fronto-parietal, fronto-occipital and fronto-temporal pathways after treatment. These findings indicate that iTBS of accelerated dTMS demonstrates comparable efficacy and tolerability to 18-Hz rTMS of accelerated dTMS, whilst inducing treatment-specific network-level neurophysiological alterations. In the rTMS-dTMS group, relative changes in FC between the frontal and temporal/precentral regions showed significant negative correlation with HAMD score reduction rates, while relative changes in FC between the frontal lobe and parietal lobe showed a significant positive correlation with the rate of HAMD score reduction for the iTBS-dTMS group. This study revealed novel mechanisms by which accelerated dTMS protocols modulate brain networks, providing evidence for the clinical application of accelerated iTBS-dTMS as an efficient, evidence-based treatment for MDD.

Humans↗

PubMed2026

Efficacy of pharmacological and microbiota-based therapies in preclinical models of autism spectrum disorder: a systematic review.

BACKGROUND: Autism spectrum disorder (ASD) is a multifactorial neurodevelopmental condition in which pharmacological and microbiota-targeted interventions are emerging as promising therapeutic avenues. Animal models are the main tool to investigate etiology, molecular mechanisms and screening for pharmacological therapies. Methodological differences, outcome measure variability, incomplete reporting, biological confounders, and overgeneralization of the results made evaluating innovative pharmacological agents challenging. These limitations in the field highlight a need for systematic and standardized research to reliably assess and translate pharmacological interventions from ASD animal models to human clinical relevance. SUBJECTS: This systematic review synthesized efficacy evidence for pharmacological and microbiota-based therapies across established ASD animal models. RESULTS: We identified 52 recent (2010-2025) studies that reported key ASD behavioral outcomes after pharmacological or microbiota-focused treatments. Interventions were grouped into therapeutic classes - including oxytocinergic agents, E/I balance therapeutic targets, metabolic drugs, cannabinoids, purine-based interventions and emerging targets - alongside microbiota-directed strategies such as probiotics, prebiotics, and fecal microbiota transplantation. By integrating effect directions and robustness across models, we identified most potential drug candidates, evaluated the efficacy of novel strategies, and recognized critical translational gaps. The reviewed studies demonstrate that ASD-like behavioral deficits in preclinical models can be modulated through interventions targeting diverse biological systems, including neurotransmission, neuroinflammation, metabolism, and the gut-brain axis. CONCLUSIONS: These findings support the multifactorial nature of ASD pathophysiology which arises from a network of interacting systemic processes rather than a single molecular defect. It could explain the limited success of traditionally narrowly targeted interventions and suggest a paradigm shift into a more systemic approach.

Animals↗

PubMed2026

Retinal microstructural alterations as early phenotypes of depression in radiogenomics analysis.

BACKGROUND: With the increasing prevalence of depression, there is an urgent clinical need for early screening in depression. The retina offers a promising window for early screening in depression due to its rapid, non-invasive, objective, eye-brain correlated characteristics, but previous research has yielded conflicting alterations in retinal microstructure in depression. METHODS: We screened retinal optical coherence tomography and brain magnetic resonance imaging data in the UK Biobank to enroll 23,225 participants for retinal study of depression occurrence, and 1475 participants for the eye-brain association study. We also used genetic data (ID: ebi-a-GCST90014267 and ukb-d-20,448) from the Integrative Epidemiology Unit Open Genome-Wide Association Study for Mendelian randomization analysis. We used Cox regression to assess the association between retinal microstructure and depression risk, Mendelian randomization to infer causality, and mediation analysis to explore retina-brain pathway association. RESULTS: The Cox regression analysis showed that retinal ganglion cell-inner plexiform layer (GCIPL) thickness remained a significant predictor of depression. The Mendelian randomization analysis indicated a positive statistical association between GCIPL thickness and depression. Moreover, there was a significant positive correlation (all p < 0.001) between the volume of specific depression-related brain regions and the GCIPL thickness. Adjusting for age, sex, and head size, the mediation analysis provided preliminary evidence for a potential anatomical pathway linking retinal GCIPL thickness to depression-related brain regions through primary visual cortex and secondary visual cortex volumes. CONCLUSION: Thickened retinal GCIPL is a potential early phenotype of depression and has a potential association pathway with depression-related brain regions using a radiogenomics approach.

Humans↗

PubMed2026

Novel splice site variants in GBA1 are associated with Gaucher disease and genotype-phenotype correlations.

BACKGROUND: Variants in GBA1 are associated with neurodegenerative disease. This study aimed to explore pathogenic GBA1 variants. METHODS: Four patients with progressive myoclonic epilepsy (PME) and extremely low β-glucosidase levels were recruited. Whole-exome sequencing and long-range PCR were performed to identify GBA1 variants. Bioinformatic analyses were used to predict the impact of the identified variants. A literature review was performed to explore the genotype-phenotype correlations. GBA1 expression data across different brain regions and developmental stages were analyzed using the BrainSpan database. RT-PCR was performed to verify the splicing effects. RESULTS: Compound heterozygous GBA1 variants were identified in four patients. Five distinct variants were detected, including two novel splice site variants (c.308-2A>G and c.762-2A>C) and three previously reported variants. All identified variants were rare or absent in gnomAD. Splice site variants c.308-2A>G and c.762-2A>C were predicted to cause aberrant splicing. Minigene-based splicing assays coupled with RT-PCR and Sanger sequencing confirmed that both variants cause complete exon skipping (exon 4 and exon 7, respectively). All patients presented with PME onset in childhood/adolescence, intellectual regression, low β-glucosidase, and diffuse brain atrophy and were subsequently diagnosed with Gaucher disease type 3. GBA1 expression in the brain showed two distinct peaks: one in infancy and another after five years of age. The onset age of PME aligned with the second GBA1 expression peak (after five years of age). CONCLUSION: This study identified compound heterozygous GBA1 variants, including two novel candidate pathogenic splice site variants, in Gaucher disease type 3 patients, expanding the known mutational spectrum.

Humans↗

PubMed2026

Assessment of Surgical Salvage Outcomes for Exposed Cranial Neuromodulating Devices.

OBJECTIVES: Implanted neuromodulating devices (NMDs) such as cochlear implants (CIs) and deep brain stimulators (DBSs) are commonly used in modern medicine. Rarely, complications arise post-operatively, including hardware exposure. Traditional teaching suggests that these devices require removal if exposed; however, surgical salvage is a high risk, high reward alternative. We review our single institution experience managing NMD exposure with surgical salvage. METHODS: Retrospective chart review was performed on individuals who had a NMD implanted and underwent an attempt at surgical salvage for exposure during the study period (January 01, 2021 through December 31, 2023). Study outcome success was defined as maintaining a functional NMD 1 year after salvage was attempted. Surgical techniques associated with successful salvage were compared. RESULTS: Nine of 729 patients (1.2%) implanted with NMDs experienced hardware exposure during this 2-year study period. Nine subjects were referred for NMD salvage; however, only 6 of 9 subjects (66.7%, CI = 3; DBS = 3) underwent NMD salvage attempts. Four of the subjects had successful salvage demonstrated successful salvage with a functioning NMD and without wound healing concerns 1 year after their salvage procedure. CONCLUSIONS: Classic teaching states that exposed NMDs require explantation. However, this approach necessarily imposes time without benefit from the NMD between explantation and reimplantation. Our experience demonstrates that surgical salvage can be a successful alternative for the majority (66.7%) of individuals.

Humans↗

PubMed2026

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↗

PubMed2026

Functional neuroimaging subtypes of obsessive-compulsive disorder: A systematic review and meta-analysis.

Obsessive-compulsive disorder (OCD) exhibits substantial clinical heterogeneity that may reflect underlying neurobiological diversity. Neuroimaging-based subtyping may advance precision psychiatry by identifying biologically distinct subgroups with differential treatment responses. This study systematically synthesized evidence from functional neuroimaging subtyping studies in OCD to identify reproducible neurobiological subtypes, characterize their clinical profiles, and establish a consensus-based classification framework. We reviewed 40 original studies employing machine learning, clustering, normative modeling, or classification approaches, encompassing approximately 8,150 patients. Consensus clustering identified three reproducible neurobiological subtypes. The Limbic-Hyperactive subtype, comprising approximately 40% of patients, exhibited amygdala and insula hyperconnectivity, elevated anxiety levels, predominant contamination and washing symptoms, and favorable response to cognitive-behavioral therapy. The Fronto-Striatal-Hypoconnected subtype, comprising approximately 35% of patients, demonstrated reduced orbitofrontal-striatal connectivity, cognitive inflexibility, predominant checking and ordering symptoms, and a favorable response to selective serotonin reuptake inhibitors. The Global-Disrupted subtype, comprising approximately 25% of patients, exhibited widespread connectivity disruption, greater symptom severity, and poor treatment response. Support vector machine classification achieved 81.5% accuracy for subtype assignment, though classification of OCD versus healthy controls showed limited generalizability in multisite settings (AUC 0.567-0.673). These findings support a neuroimaging-based framework for personalized treatment selection but require prospective validation.

Humans↗

PubMed2026

Disentangling oscillatory and aperiodic neural activity in autism: A spectral parameterization analysis of neurofeedback intervention.

BACKGROUND: Autism Spectrum Disorder (ASD) is characterized by atypical neural oscillations and heterogeneous alterations in excitation/inhibition (E/I) balance, the directionality of which varies across individuals, neural circuits, and developmental stages. While Alpha-band neurofeedback (NFB) is a promising intervention, its underlying neurophysiological mechanisms remain unclear, partly due to the conflation of periodic and aperiodic signals in traditional EEG analysis. METHODS: This randomized controlled trial recruited 40 children with ASD, assigned to either an experimental group (Alpha-training NFB) or a no-feedback group. Resting-state EEG and behavioral assessments (SRS, ABC) were collected pre- and post-intervention. We employed spectral parameterization to decompose neural activity into aperiodic (1/f slope, offset) and periodic (periodic alpha power, center frequency) components. RESULTS: NFB training yielded significant behavioral improvements in social cognition and relating skills. Physiologically, the experimental group exhibited a significant steepening of the aperiodic slope (increased exponent), reflecting a reduction in neural noise and potential optimization of inhibitory modulation. Furthermore, we observed enhanced periodic alpha power and an acceleration of the alpha center frequency (ACF), indicative of improved neural efficiency and maturation. These physiological shifts in frontal and occipital regions were significantly correlated with improvements in behavioral scores. CONCLUSION: Alpha-training NFB was associated with improvements in caregiver-rated behavioral scores and modulated spectral features of resting-state EEG in children with ASD. These findings validate the utility of spectral parameterization markers in evaluating neuromodulatory interventions.

Humans↗

PubMed2026

Migration intentions among nigerian neurosurgeons: a national survey of workforce retention.

Physician emigration from low- and middle-income countries creates critical workforce shortages. This study explored factors influencing migration intentions among Nigerian neurosurgeons and trainees. We conducted an anonymized survey of consultant neurosurgeons, fellows, and residents practicing in Nigeria. Invitations were sent by email and professional messaging platforms, and snowball sampling was used to increase participation. The survey included quantitative and open-ended questions on demographics, income, migration plans, and retention factors. Seventy-nine respondents participated (61.5 % consultants; 93.7 % male; median age: 44 years). Nearly all practiced general neurosurgery (97.3 %), and many also performed trauma (65.3 %) and spine (61.3 %) neurosurgery. Most (85.7 %) reported that their earnings were insufficient to support their families. Nearly 40 % were considering emigration, most often citing financial pressures (88.5 %) and poor working conditions (63.5 %) as push factors. By contrast, personal or family ties (63.0 %) and relocation costs (45.2 %) were cited as reasons to stay. Respondents identified higher salaries (58.1 %) and greater investment in the health sector (51.4 %) as key measures to improve retention. In univariable analyses, younger age, income insufficiency, income dissatisfaction, and feeling undervalued at work were associated with migration intention. Financial insecurity emerged as the dominant driver of migration intentions among Nigerian neurosurgeons. In addition to salary increases, sustained investment in healthcare infrastructure and workforce support is essential to improve retention. International partnerships may complement these efforts by building neurosurgical capacity and mitigating brain drain.

Humans↗

PubMed2026

Co-Use of Some Substances Associated With Higher Doses in Adolescents: Findings From the Adolescent Brain Cognitive Development Study.

PURPOSE: Adolescence is a critical developmental period marked by heightened vulnerability to initiating substance use, with long-term implications for health and behavior. Nicotine, alcohol, and cannabis are the most commonly used substances among adolescents. Their use often co-occurs but few studies have described or quantified the patterns and doses of substance co-use in this vulnerable population. METHODS: We used data from six waves of the Adolescent Brain Cognitive Development study. Substance use was measured through a web-based timeline followback interview, and outcomes are operationalized into substance use quantity (in standard units), single use, and co-use (use of two substances on the same day) of alcohol, cannabis, and nicotine. Group differences of average dose in standard units between single use and co-use for each substance class were analyzed using linear mixed-effects modeling in years 4-6. RESULTS: The average dose of nicotine was significantly higher when co-used with alcohol (4.32; 95% confidence interval [CI]: 2.55-6.09; p < .001) or when co-used with cannabis (4.41; 95% CI: 2.76-6.05; p < .001) in year 6; nicotine trends were similar in years four and five. In year 6, the average dose of alcohol was higher when co-used with cannabis (1.87; 95% CI: 0.37-3.36; p = .004) or co-used with nicotine (1.64; 95% CI: 0.06-3.22; p = .03) compared to single use of alcohol. The average dose of cannabis was not significantly different when used singularly or co-used with either alcohol or nicotine in our study years. DISCUSSION: During adolescence, the co-use of substances (namely alcohol and nicotine) may lead to higher average doses compared to single-substance use.

Humans↗

PubMed2026

Transient acoustic stimulation induces time-dependent synaptic remodeling and enhancement of auditory nerve output after threshold recovery.

BACKGROUND: Acoustic stress can alter cochlear function even in the absence of permanent threshold elevation; however, synaptic consequences of transient acoustic stimulation remain incompletely understood. OBJECTIVE: This study aimed to investigate whether transient acoustic stimulation induces changes in the auditory nerve output and cochlear ribbon synapse morphology following hearing threshold recovery. METHODS: Young adult CBA/CaJ mice were exposed to band-limited acoustic stimulation (45-2,000 Hz, 95 dB SPL, 2 h). Auditory brainstem responses (ABRs), hair cell and spiral ganglion neuron survival, and synaptic morphology were evaluated before exposure and up to 2 weeks post-exposure. RESULTS: ABR thresholds were transiently elevated immediately after exposure but largely recovered by 1 day post-exposure. In contrast, ABR wave I amplitudes significantly increased after threshold recovery across multiple test frequencies. Ribbon-associated puncta in both inner and outer hair cell regions exhibited biphasic temporal changes, with an initial decrease immediately after exposure followed by an increase at 1 day post-exposure. The ribbon-associated punctal area also increased after exposure and remained elevated at later post-exposure time points. No significant loss of hair cells or spiral ganglion neurons was observed. Exploratory genomic analysis suggested enrichment of pathways related to metabolic defense and cellular stress responses. CONCLUSIONS: Transient acoustic stimulation induces time-dependent synaptic remodeling and enhancement of peripheral auditory nerve output without overt cellular degeneration. These findings support a model in which early cochlear responses to acoustic perturbation include adaptive synaptic plasticity and gain regulation, extending current concepts of noise-induced cochlear change beyond irreversible synaptic loss.

Animals↗

PubMed2026

Modelling the effects of biological intervention in a dynamical gene network.

Cellular response to environmental and internal signals can be modeled by dynamical gene regulatory networks (GRN). In the literature, three main classes of gene network models can be distinguished: (1) non-quantitative (or data-based) models which do not describe the probability distribution of gene expressions; (2) quantitative models which fully describe the probability distribution of all genes co-expression; and (3) mechanistic models which allow for a causal interpretation of gene interactions. We propose two rigorous frameworks to model gene alteration in a dynamical GRN, depending on whether the network model is quantitative or mechanistic. We explain how these models can be used for design of experiment, or, if additional alteration data are available, for validation purposes or to improve the parameter estimation of the original model. We apply these methods to the Gaussian graphical model, which is quantitative but non-mechanistic, and to mechanistic models of Bayesian networks and penalized linear regression.

Gene Regulatory Networks↗

PubMed2026

Cross-tissue multi-omics integration highlights BPHL and mitochondrial targets in Alzheimer's disease.

BACKGROUND: Mitochondrial dysfunction is a hallmark of Alzheimer's disease (AD), yet specific molecular targets remain to be fully characterized. METHODS: A summary-data-based Mendelian randomization (SMR) framework integrated AD genome-wide association study (GWAS) statistics (39,918 cases) with blood DNA methylation quantitative trait loci (mQTL), gene expression (eQTL), and protein (pQTL) data for 1136 mitochondria-related genes. Associations were assessed using Bayesian colocalization and HEIDI testing. Tissue relevance was evaluated in four brain regions (hippocampus, amygdala, cortex, frontal cortex) using GTEx and external transcriptomic datasets. RESULTS: Screening identified eight candidates supported across blood mQTL and eQTL layers. Stepwise central nervous system (CNS) evaluation singled out biphenyl hydrolase-like (BPHL) as the consistent candidate. Higher genetically predicted BPHL expression was associated with reduced AD risk across the hippocampus (OR=0.920, 95% CI 0.873-0.970), amygdala (OR=0.925, 95%CI 0.880-0.973), cortex (OR=0.943, 95% CI 0.908-0.978), and frontal cortex (OR=0.938, 95%CI 0.901-0.976). These findings aligned with protein-protein interactions connecting BPHL to respiratory complexes and lower BPHL expression in independent AD brains. Functional enrichment converged on oxidative phosphorylation pathways. CONCLUSIONS: By integrating multi-omics data with tissue-specific validation, this study nominates BPHL as a consistent protective candidate in the brain. These findings provide genetic support for mitochondrial molecular perturbations in AD, offering insights for future validation.

Alzheimer Disease↗

PubMed2026

PaNDA: Efficient Optimization of Phylogenetic Diversity in Networks.

Phylogenetic diversity (PD) plays an important role in biodiversity, conservation, and evolutionary studies by measuring the diversity of a set of taxa based on their phylogenetic relationships. In phylogenetic trees, a subset of k taxa with maximum PD can be found by a simple and efficient greedy algorithm. However, this algorithmic tractability is lost when considering phylogenetic networks, which incorporate reticulate evolutionary events such as hybridization and horizontal gene transfer. To address this challenge, we introduce PaNDA (Phylogenetic Network Diversity Algorithms), the first software package and interactive graphical user-interface for exploring, visualizing, and maximizing diversity in phylogenetic networks. PaNDA includes a novel algorithm to find a subset of k taxa with maximum diversity, running in polynomial time for networks of bounded scanwidth, a measure of tree-likeness of a network that grows slower than the well-known level measure. This algorithm considers the variant of PD on networks in which the branch lengths of all paths from the root to the selected taxa contribute towards their diversity. We demonstrate the scalability of this algorithm on simulated networks, successfully analyzing level-15 networks with up to 200 taxa in seconds. We also provide a proof-of-concept analysis using a phylogenetic network on Xiphophorus species, illustrating how the tool can support diversity studies based on real genomic data. The software is easily installable and freely available at https://github.com/nholtgrefe/panda. Additionally, we extend the definition of PD to semi-directed phylogenetic networks, which are mixed graphs increasingly used in phylogenetic analysis to model uncertainty of the root location. We prove that finding a subset of k taxa with maximum diversity remains NP-hard on semi-directed networks, but do present a polynomial-time algorithm for networks with bounded level.

network↗

PubMed2026

An automated geometric modeling framework in GATE for the design and optimization of high-sensitivity converging-beam SPECT collimators.

Objective.The trade-off between detection sensitivity and spatial resolution is a fundamental challenge in designing organ-dedicated Single-photon emission computed tomography (SPECT) collimators. While converging-hole geometries offer a solution, their optimization is often hindered by the lack of flexible computational tools capable of modeling large-scale, non-parallel hole arrays. This study aims to develop an automated geometric modeling framework to facilitate the design and evaluation of complex converging- and diverging-hole collimators within standard Monte Carlo environments.Approach.We developed a specialized modeling framework by implementing custom C++ classes and a vector-based alignment algorithm within GATE. This platform enables automated, orientation-consistent construction of large-scale converging arrays not natively supported by standard implementations. A high-sensitivity pure cone-beam collimator (CBC) was designed using this framework. The evaluation used hot-rod, disc, and Jaszczak phantoms for physical characterization, while XCAT and dedicated brain models were employed for clinical tasks, including cardiac, brain perfusion, and DaTscan SPECT simulations.Main results.The CBC achieved a nearly fourfold sensitivity increase compared to a conventional low-energy high-resolution parallel-hole collimator at a 20 cm radius of rotation, while maintaining comparable spatial resolution. Despite a 52.3% field of view reduction, the CBC yielded a 2.2-fold noise reduction (CV: 11.7% vs 25.9%) and mitigated partial volume effects via geometric magnification. XCAT and brain phantom simulations confirmed enhanced anatomical definition and contrast recovery in cardiac, perfusion, and DaTscan tasks.Significance.This work provides an efficient computational tool for rapid design space exploration of advanced collimator geometries. The results demonstrate that the proposed CBC design offers a significant sensitivity advantage, making it highly suitable for high-performance, small-volume clinical applications such as brain and cardiac molecular imaging.

Tomography, Emission-Computed, Single-Photon↗

PubMed2026

Awake Craniotomy for Eloquent Region Glioblastoma Classified by Tumor Location-A Retrospective and Prospective Cohort Study.

INTRODUCTION: The efficacy of awake craniotomy (AC) with intraoperative mapping for glioblastoma (GBM) in eloquent regions remains debated. This study aims to evaluate functional and survival outcomes of GBM patients undergoing AC stratified by tumor locations. METHODS: A combined retrospective (2015-2023, n = 114: 43 AC vs. 71 standard craniotomy) and prospective cohort (2023-2025, n = 28: 13 AC vs. 15 standard craniotomy) of GBM patients with motor/language-eloquent tumors was analyzed. Tumors were classified into motor subtypes (I: precentral gyrus; II: premotor/supplementary motor; III: internal capsule posterior limb; IV: other) and language subtypes (I: Broca's/precentral; II: postcentral/supramarginal gyrus; III: Wernicke's; IV: insular; V: other). Outcomes included extent of resection (EOR), postoperative motor/language recovery, overall survival (OS), and progression-free survival (PFS). RESULTS: The retrospective cohort demonstrated that AC has advantages in functional preservation across various motor/language subtypes. However, AC was associated with significantly deteriorated survival outcomes specifically in precentral gyrus GBMs. A prospective cohort study, enrolling only precentral gyrus GBMs for validation, yielded results consistent with the retrospective findings: worsened OS and PFS (OS: HR = 3.223, p = 0.0450; PFS: HR = 2.374, p = 0.0476); reduced EOR (AC: 74.3% ± 5.3%; standard craniotomy: 86.9% ± 12.3%, p = 0.0470); and better motor recovery. CONCLUSIONS: Functional preservation and survival outcomes of AC in GBM exhibited subtype-specific correlations with tumor locations. AC with intraoperative mapping effectively preserves neurological function in GBM patients. However, for tumors involving the precentral gyrus, the AC approach carries greater risks than benefits and should be considered with caution. TRIAL REGISTRATION: Strategic Intervention on Preserving Motor Function During Awake Craniotomy: NCT05143788. Strategic Intervention on Preserving Language Function During Awake Craniotomy: NCT05143775.

Adult↗

PubMed2026

Non-destructive prediction of lead content in oilseed rape leaves by fluorescence hyperspectral technology based on neural network.

Based on fluorescence hyperspectral imaging (FHSI), this study targeted rapid, non-destructive quantification of lead (Pb) content in oilseed rape leaves treated with varying silicon (Si) concentrations, acquiring fluorescence spectra over the 484.43-1001.61 nm wavelength range. To optimize spectral data quality, preprocessing methods (Savitzky-Golay smoothing, first derivative, detrending) were comprehensively compared. Characteristic wavelengths were then selected via interval variable iterative shrinkage, which effectively compressed data dimensionality and reduced computational load. A hybrid SE-CL1DA model, fusing a 1D convolutional neural network, a long short-term memory network and SE attention mechanism was constructed, with Bayesian optimization tuning hyperparameters to boost stability. The BO-SE-CL1DA outperformed both traditional machine learning and insufficiently optimized deep learning model (Rp2=0.9609, RMSE = 0.0377 mg/kg, RPD = 5.1736), thus enabling accurate Pb estimation, supporting Si-regulated heavy metal stress management and facilitating agricultural contamination monitoring.

Plant Leaves↗

PubMed2026

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 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↗