BackgroundAssessment and treatment monitoring in alcohol dependence syndrome often rely on subjective measures, particularly in resource-limited settings. Quantitative electroencephalogram (qEEG) provides an objective alternative, though its role in alcohol use and abstinence remains underexplored in the Indian context.AimTo study changes in the quantitative electroencephalogram in persons with alcohol dependence syndrome undergoing treatment.MethodsPatients diagnosed with alcohol dependence syndrome as per ICD-11 were recruited. At baseline, the Severity of Alcohol Dependence Questionnaire (SADQ) (mean 22.60 ± 4.81) and Clinical Institute Withdrawal Assessment for Alcohol-Revised (CIWA-Ar) (mean 10.98 ± 2.45) were administered to assess the severity of dependence and withdrawal symptoms. qEEG was recorded at baseline, following detoxification and at 12 weeks. Detoxification was done using benzodiazepines via a symptom-triggered regimen. Baclofen was offered post-detoxification with regular follow-ups. EEG signals were analysed for changes across standard frequency bands in various scalp regions and in terms of absolute powers.ResultsSixty patients completed the 12-week follow-up. The sample consisted of all males, with a mean age of 40.85 ± 8.30 years. Alpha and gamma powers showed increasing trends, while beta, theta, and delta powers declined across most scalp regions. Absolute power trends were similar, with a statistically significant reduction noted in the delta wave (p-value=.024). No significant correlation was found between severity of dependence and wave powers, except for gamma in the fronto-parietal region (p-value=.01) and beta in the central region (p-value=.021).ConclusionqEEG changes with detoxification and abstinence may serve as an objective indicator for assessing treatment efficacy and abstinence status in alcohol dependence.

Major Depressive Disorder(MDD) affects over 280 million people globally, with traditional diagnosis replying on subjective clinical assessments.This study introduces an AI driven Human-Computer Interaction (HCI) framework utilizing multimodal EEG data and psychometric metadata for objective MDD detection. Using MODMA dataset, three modalities- 128-channel resting-state EEG, 128-channel ERP, and 3-channel EEG-alongside clinical scores are analyzed.Features from time, frequency, non-linear, and ERP domains were extracted post-preprocessing. Traditional ML models (Random Forest, XGBoost, SVM, Logistic Regression), deep learning (CNN, MLP),and ensemble methods are evaluated. Random Forest on 3-channel EEG achieved 100% accuracy, Random Forest and MLP on 128-channel resting-state EEG reached 98%, outperforming prior studies. The results validate the proposed system’s robustness and suitability for scalable, intelligent MDD screening. This work is novel in it’s simultaneous analysis of both high-resolution data and practical low-channel setups, with an architecture designed to be adaptable to future HCI-based diagnostic tools for scalable, real-world mental health screening.

Opioid use disorder (OUD) has been linked to alterations in brain white matter microstructure, but evidence comparing pre-treatment and six-month buprenorphine-naloxone (BNX) treatment remains limited. This study examined changes in brain diffusion tensor imaging (DTI) metrics before and after six months of BNX treatment in individuals with OUD and assessed the influence of concurrent cannabis and tobacco use. This pre-post study included 25 individuals with OUD initiating BNX treatment and 25 healthy controls. All participants underwent 3-Tesla brain DTI scans at baseline and at six-month follow-up. Fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) were quantified across 48 regions of interests defined by JHU White Matter Atlas. Linear mixed-effects models were applied to examine group and time effects. At follow-up, the OUD group demonstrated widespread increases in MD, AD, RD compared with baseline and healthy controls, involving commissural, projection, and association tracts. Compared with healthy controls, the OUD group at baseline showed lower FA in key commissural and projection pathways. White matter changes after 6-month BNX treatment are modest overall but might be influenced by continued cannabis and tobacco use. Addressing concurrent substance use may be important for optimizing neurobiological recovery during buprenorphine treatment.

Background:Opioid use disorder (OUD) is associated with structural brain alterations. Buprenorphine maintenance treatment (BMT)'s impact on brain morphology remains underexplored. We examined the effect of BMT on surface-based morphometry (SBM) metrics- cortical thickness, sulcal depth, gyrification, and fractal dimension, in a longitudinal controlled design. Methods:Twenty-five men with OUD and age- and education-matched participants in the control group were recruited. Participants underwent T1-weighted MRI scans immediately after starting BMT and after six months of treatment. SBM metrics were analyzed using the Computational Anatomy Toolbox 12 (CAT12), employing threshold-free cluster enhancement (TFCE) and family-wise error correction. Results:At baseline, individuals with OUD had greater cortical thickness in superior parietal and occipital regions and reduced thickness in the inferior temporal gyrus versus participants in the control group. After six months, significant cortical thickness reductions were observed in the occipital pole, cuneus, and occipito-temporal gyri, and calcarine sulcus in both hemispheres; sulcal depth, gyrification, and fractal dimension remained unchanged. We observed negative correlations between buprenorphine dosage and change in cortical depth in the parahippocampal region (r = -0.53, p = .007) and temporal pole (r = -0.55, p = .005), and positive correlations with fractal dimension in the medial orbitofrontal cortex (r = 0.53, p = .006) and gyrification in the lateral orbital region (r = 0.56, p = .004). Conclusion:BMT is associated with a generalized cortical thinning in sensory regions, while dose-dependent changes are observed in memory, emotional regulation, and cognitive control regions, highlighting neuroadaptive processes in overall treatment and medication-specific effects.

Autism Spectrum Disorder (ASD) is a complex neurodevelopmental condition where scalable biomarkers remain limited. Electroencephalography (EEG), with its high temporal resolution and portability, offers a promising foundation for computational analysis. This work benchmarks deep and handcrafted EEG pipelines on paediatric data from 34 children, using strict leave-one-subject-out (LOSO) validation to prevent data leakage. While many models achieved inflated epoch- level accuracies of 80-90%, subject-level performance dropped sharply, often nearing chance. Supervised Transformers reached 60-78% accuracy across sites but underperformed Random Forests, which paired with spectral and entropy features achieved the most consistent subject-level accuracy 71%. Self-supervised pretraining partially closed the transformer gap, improving calibration but not surpassing RF. These findings highlight the importance of rigorous validation and suggest that physiologically informed, interpretable features may currently offer more robust support for ASD assessment than purely deep models, while also clarifying both the potential and current limitations of EEG- based pipelines.

BackgroundSchizophrenia affects millions globally, with up to 30% showing resistance to standard antipsychotics. Clozapine is effective for treatment resistant schizophrenia (TRS), but its use is often delayed. This study explores Quantitative electroencephalogram (QEEG) as a tool to predict clozapine response in Indian TRS patients, aiming to support early, personalized treatment.AimThis study aims to predict treatment response to clozapine in TRS patients using quantitative electroencephalogram (QEEG) by assessing and comparing baseline and 6 weeks QEEG patterns and their changes in responders versus non-responders.Methods39 clozapine-naïve TRS patients were recruited at tertiary care hospital in North India and assessed using BPRS, GASS-C and EEG at baseline, 3 weeks and 6 weeks. EEG data were processed and analyzed for frequency band power to compare responders (≥20% BPRS improvement) and non-responders.ResultsOf the 39 patients included, 36 completed the study, with 67% classified as responders and 33% as non-responders. Responders showed significantly higher right temporal delta power at 3 and 6 weeks, with ROC analysis at 6 weeks yielding an Area under curve of 0.757 (P = .014). Statistically significant increases in delta and theta power were observed in responders.ConclusionsIncreased right temporal delta power was seen in responders, but changes were insufficient to reliably predict outcomes.

Objective: The COVID-19 pandemic has affected the availability of and access to medications for opioid dependence (OD). We examined the monthly trends in new buprenorphine/naloxone (BNX) treatment episodes, number of clinical visits for BNX, BNX dispensed per person, and BNX prescription over 56 months, which included the pre-pandemic period and the early and later parts of the pandemic (January 2017 to August 2022). Method: Research data were collected from the pharmacy database of a large publicly funded treatment center in India. A flexible, low-threshold service was adopted in April 2020 in response to the lockdown implemented on March 25, 2020. Change point analyses were performed to examine monthly trends visually and statistically. We used autoregressive integrated moving averages to forecast trends from April to August 2020 and March to August 2022, using January 2017 to March 2020 and March 2020 to February 2022 as training data sets. Results: A total of 993 patients were started on BNX treatment; 40,452 BNX clinic attendances were made; 1,401,393 BNX tablets were dispensed; and 6,795 new patients with OD were registered. The observed data for clinic attendance for BNX was significantly lower than the projected estimates in April to August 2020; however, observed new treatment episodes and monthly BNX prescriptions were within the 95% projected estimates; BNX dispensed per person was significantly more than the projected estimate. In contrast, observed BNX prescription trends surpassed the upper limit of the 95% confidence interval in March to August 2022. Conclusions: A low-threshold and flexible-treatment service could mitigate the unintended consequences of pandemic- induced restrictions. (J. Stud. Alcohol Drugs, 86, 48-57, 2025)

Chemotherapy-induced cognitive impairment (CICI), also known as “chemobrain,” is a common side effect of breast cancer therapy which causes oxidative stress and generation of reactive oxygen species (ROS). Ferulic acid (FA), a natural polyphenol, belongs to BCS class II is confirmed to have nootropic, neuroprotective and antioxidant effects. Here, we have developed FA solid dispersion (SD) in order to enhance its therapeutic potential against chemobrain. An amorphous ferulic acid loaded leucin solid dispersion (FA-Leu SD) was prepared by utilizing amino acid through spray-drying technique. The solid-state characterization was carried out via Fourier-transform infrared spectroscopy (FT-IR), differential scanning calorimetry (DSC), X-ray diffraction (XRD), and field emission scanning electron microscopy (FE-SEM). Additionally, in-vitro release studies and antioxidant assay were also performed along with in-vivo locomotor, biochemical and histopathological analysis. The physical properties showed that FA-Leu SD so formed exhibited spherical, irregular surface hollow cavity of along with broad melting endotherm as observed from FE-SEM and DSC results. The XRD spectra demonstrated absence of sharp and intense peaks in FA-Leu SD which evidenced for complete encapsulation of drug into carrier. Moreover, in-vitro drug release studies over a period of 5 h in PBS (pH 7.4) displayed a significant enhanced release in the first hr (68. 49 ± 5.39

Background: Predicting treatment response with antidepressant is a challenging task for clinicians and researchers. An important limitation of an antidepressant trial is the increased time spent before an adequacy of trial can be decided. Quantitative Electroencephalography has shown some evidence in identifying early changes seen with antidepressants. No data has been reported from Indian population on its predictive capabilities. Aim: To examine whether early changes in frontal and prefrontal theta value in QEEG could predict antidepressant treatment response. Methods: Structured clinical assessments were conducted at baseline and after one week in a sample of treatment-seeking adults with major depressive disorder (n = 50). Patients were started on SSRI (Escitalopram, fluoxetine, paroxetine or sertraline) and followed for 8 weeks. QEEG recordings were carried out at baseline and week 1 and its parameters (relative theta power and cordance) were assessed to identify its predictive value for treatment response. Treatment response was assessed using Hamilton depression rating scale with 50% reduction after 8 weeks being considered as response. Results: Mean age of the sample was 39 ± 10 years and majority of them were females (64%). A significant reduction was found in relative frontal theta value (p = 0.021) from baseline to one week in responders. However, linear regression revealed that this change could not predict the treatment response (p = 0.37). Conclusions: QEEG changes are observed in initial phase of antidepressant treatment but these changes can't predict the treatment response.

Background: Cortical differences in thickness, folding, and complexity may reflect synaptic pruning and myelination alterations. Individuals with opioid use disorder (OUD) may demonstrate differences in these cortical metrics due to neurodevelopmental aberrations or early opioid exposure.Objectives: We compared the cortical metrics between individuals with OUD and controls. The influence of age and duration of opioid exposure were considered indirect evidence for preexisting or opioid-exposure-based structural aberrations.Methods: Sixty-nine treatment-naïve men with OUD (52 heroin, 17 non-heroin) and 25 age and education-matched non-drug-using male controls were recruited from a treatment center and community, respectively. 3-Tesla Siemens Magnetom Verio scanner and Computational Anatomy Toolbox 12 were used for image acquisition and processing. Cortical parcellation was performed using Destrieux atlas. Surface-based morphometry (SBM) metrics were cortical thickness, sulcal depth, fractal dimension, and gyrification index.Results: Only two cortical areas survived corrections for multiple comparisons: persons with OUD had greater sulcal depth in the right lateral orbital sulcus (p = .0003, Glass's delta = 0.98) and lower gyrification index in the left frontal middle gyrus (p = .0005, Glass's delta = 0.67) than controls. The group-by-age interaction effect on the cortical thickness was non-significant. Lower age of initiation of opioid use was associated with larger cortical thickness in the inferior frontal (r = -0.36, p = .002) and anterior cingulate (r = -0.35, p = .003) regions. Duration of OUD negatively correlated with cortical thickness in frontal and occipital areas (r > -.30, p = .004-.007).Conclusion: Cortical abnormalities may stem from altered synaptic pruning and myelination, possibly due to neurodevelopmental aberrations or early opioid exposure.

Background & aim: Obesity is a worldwide epidemic leading to decreased quality of life, higher medical expenses and significant morbidity. Enhancing energy expenditure and substrate utilization in adipose tissues through dietary constituents and polypharmacological approaches is gaining importance for the prevention and therapeutics of obesity. An important factor in this regard is Transient Receptor Potential (TRP) channel modulation and resultant activation of "brite" phenotype. Various dietary TRP channel agonists like capsaicin (TRPV1), cinnamaldehyde (TRPA1), and menthol (TRPM8) have shown anti-obesity effects, individually and in combination. We aimed to determine the therapeutic potential of such combination of sub-effective doses of these agents against diet-induced obesity, and explore the involved cellular processes. Key findings: The combination of sub-effective doses of capsaicin, cinnamaldehyde and menthol induced "brite" phenotype in differentiating 3T3-L1 cells and subcutaneous white adipose tissue of HFD-fed obese mice. The intervention prevented adipose tissue hypertrophy and weight gain, enhanced the thermogenic potential, mitochondrial biogenesis and overall activation of brown adipose tissue. These changes observed in vitro as well as in vivo, were linked to increased phosphorylation of kinases, AMPK and ERK. In the liver, the combination treatment enhanced insulin sensitivity, improved gluconeogenic potential and lipolysis, prevented fatty acid accumulation and enhanced glucose utilization. Significance: We report on the discovery of therapeutic potential of TRP-based dietary triagonist combination against HFD-induced abnormalities in metabolic tissues. Our findings indicate that a common central mechanism may affect multiple peripheral tissues. This study opens up avenues of development of therapeutic functional foods for obesity.

INTRODUCTION:Treatment completion is associated with a better outcome in substance use disorders. We examined the rates of treatment completion and its predictors in patients admitted to specialized addiction treatment settings over a 13-year period.METHODS:Ours was a retrospective cohort study. We included consecutive 2850 patients admitted to the inpatient treatment between January 2007 and December 2019. We divided the patients into 2 groups: completed versus premature discontinuation of treatment. The predictor variables were based on previous research, clinical experience, and availability of the digital record.RESULTS:The number of patients who completed and discontinued treatments was 1873 (72.6%) and 707 (27.4%), respectively. The inpatient treatment discontinuation rate varied widely during the study period (18% in 2007 and 41% in 2012). The average rate of treatment discontinuation was 27%. The change-point analysis showed 5 statistically significant change points in the years 2008, 2010, 2012, 2014, and 2016. Patients who were prescribed medications for alcohol and opioid dependence and those who were on opioid agonist treatment had 4.7 and 6.3 higher odds of completing inpatient treatment than those who were not on medication. Patients with physical and psychiatric comorbidities had higher odds of treatment completion. Patients with a primary diagnosis of opioid dependence had lower odds of treatment completion than those with alcohol dependence.CONCLUSIONS:The rates of discontinuation may vary with concurrent changes in the treatment policies. Awareness of the risk factors and policy measures that may improve treatment completion must aid in informed decision making.

Autophagy is a self-destructive cellular process that removes essential metabolites and waste from inside the cell to maintain cellular health. Mitophagy is the process by which autophagy causes disruption inside mitochondria and the total removal of damaged or stressed mitochondria, hence enhancing cellular health. The mitochondria are the powerhouses of the cell, performing essential functions such as ATP (adenosine triphosphate) generation, metabolism, Ca2+ buffering, and signal transduction. Many different mechanisms, including endosomal and autophagosomal transport, bring these substrates to lysosomes for processing. Autophagy and endocytic processes each have distinct compartments, and they interact dynamically with one another to complete digestion. Since mitophagy is essential for maintaining cellular health and using genetics, cell biology, and proteomics techniques, it is necessary to understand its beginning, particularly in ubiquitin and receptor-dependent signalling in injured mitochondria. Despite their similar symptoms and emerging genetic foundations, Alzheimer's disease (AD), Parkinson's disease (PD), Huntington's disease (HD), and amyotrophic lateral sclerosis (ALS) have all been linked to abnormalities in autophagy and endolysosomal pathways associated with neuronal dysfunction. Mitophagy is responsible for normal mitochondrial turnover and, under certain physiological or pathological situations, may drive the elimination of faulty mitochondria. Due to their high energy requirements and post-mitotic origin, neurons are especially susceptible to autophagic and mitochondrial malfunction. This article focused on the importance of autophagy and mitophagy in neurodegenerative illnesses and how they might be used to create novel therapeutic approaches for treating a wide range of neurological disorders.

Background: Google Trends provides an easily accessible and cost-effective method of providing real-time insight into user interest.Objective: to address the gap in UK prevalence data for e-cigarettes by analyzing Google Trends to identify correlations with official data from Action on Smoking and Health. The study further evaluates Google Trend’s sensitivity to real-time events and the ability for predictive models to forecast future data based on Google Trends.Methods: UK Google Trends data from 2012 to 2021 was analyzed to assess (a) the most popular electronic nicotine device terminology; (b) statistically significant points in time; (c) correlations between Relative Search Volumes and official reports on electronic cigarette use and (d) whether Google Trends could predict future patterns in data. These were achieved using Locally Weighted Scatterplot Smoothing regression, Pruned Exact Linear Time Method, cross correlation, and Autoregressive Integrated Moving Average algorithms respectively.Results: “Vape” was revealed to be the most popular electronic nicotine device terminology with a correlation coefficient greater than +0.9 when compared to official electronic cigarette consumption data within a one-year timescale (lag 0). Results from ARIMA modeling were varied with the algorithms forecasted trends line occasionally lying outside of a 95% prediction interval.Conclusion: Google Trends may correspond to population-based prevalence of electronic cigarette use. The changing trends coincide with changing policy decisions. Google Trends based prediction for online interest in electronic cigarettes requires further validation so should currently be used in conjunction with other traditional methods of data collections.

Huntington's disease (HD) is an inherited fatal neurodegenerative disorder associated with striatal-specific GABAergic medium-spiny neurons (MSNs) characterized by choreiform movements, psychiatric, cognitive, and motor dysfunctions. The average HD prevalence is 5 in 100,000 people in the western world; small frequencies are known in Africa, Japan, China, and Finland. HD is caused by the CAG (cytosine, adenine, guanine) repeated expansion in exon-1 of the Huntington (Htt) gene. CAG triplet repeats in exon-1 are responsible for the increase in the polyglutamine (poly Q) on Htt in HD patients. Normal Htt has 35 CAG repeats, whereas mutant Huntington (mHtt) > 40 CAGs, patients with 36-39 CAG repeat extensions are at risk of HD. The exact mechanism of HD is still unknown; however, neuroinflammation, mitochon-drial

Textile substrates and paper-based substrates are generally used to design the flexible antennas. However, these substrates have the issue of moisture absorbance which effect the antenna working. In the present work, a compact flexible crown rectangular fractal antenna has been fabricated and tested using copper tape (conducting material) and PET sheet (substrate). The proposed antenna is simulated and fabricated and the results are found in good agreement. Further, the results for prototype antenna are obtained in bent form. Also, the proposed antenna is compared with similar shaped antenna fabricated on RT-Duroid. The proposed PET substrate based antenna shows 53.17 % miniaturization capability with an advantage of flexibility compared to the earlier published antenna.

Anthocyanins act as antioxidants and prebiotics and colored wheat has additional health benefits due to the presence of anthocyanins. The current study was designed to study the gut microbiota modulating effects of colored wheat in mice. Male swiss albino mice were subjected to different isocaloric diet interventions for 11 weeks. Black wheat flour had the lowest in vitro glycemic index (GI) and highest fructan content followed by purple and white wheat. The chapatti of colored wheat exhibited even lesser GI than their respective flours. Colored wheat interventions in mice resulted in lower oral glucose tolerance test (OGTT) value and higher short-chain fatty acids content compared to white wheat intervention. Additionally, the hepatic antioxidants profile of the colored wheat intervention groups showed a higher concentration of antioxidant enzyme compared to white wheat intervention. Gut diversity analysis revealed that the colored wheat varieties both as flours and chapattis augmented the abundance of beneficial phyla and improved the ratio of Bac/Fir compared to white wheat. Bacteria potentially related to diseased conditions (Rikenellacea, Ruminococcus, and Clostridia) decreased. Colored wheat especially black wheat in raw as well as the cooked form, has the potential to positively modulate the gut microbiome and exert a prebiotic-like effect.