Developmental Neurobiology最新文献

{"title":"Silent Synapses in Multiple Sclerosis: From Synaptic Dysfunction to Reactivation-Based Therapies—A Narrative Review of Cognitive and Neuroplasticity Outcomes","authors":"Zinab Alatawi","doi":"10.1002/dneu.23014","DOIUrl":"10.1002/dneu.23014","url":null,"abstract":"<div>\u0000 \u0000 <p>Silent synapses in multiple sclerosis (MS) represent a key yet underexplored concept in the pathology of this disease, playing a crucial role in cognitive impairments and reduced neuroplasticity. These synapses, due to the inactivity of AMPA receptors under pathological conditions, are unable to efficiently transmit neural signals, leading to disrupted neural communication. This dysfunction is particularly influenced by chronic inflammation, alterations in neurotransmitter dynamics, and a reduction in neurotrophic factors in MS patients. One of the key aspects of understanding silent synapses is that they not only have the potential for reactivation, but they can also contribute to the restoration of neural networks by re-establishing neuroplasticity. Recent research has shown that targeted treatments, including activating NMDA receptors, increasing brain-derived neurotrophic factor (BDNF), and using drugs like ketamine, help restore patients’ cognitive function. Apart from pharmacological therapies, non-pharmacological strategies also include cognitive rehabilitation, physical activity, and noninvasive brain stimulation, which might promote synaptic plasticity and consequently quality of life. Therefore, reactivating latent synapses as a novel and interesting therapy strategy could not only improve cognitive performance in MS patients but also open the road for fresh methods to mend the nervous system and increase their quality of life. Though its specific form has not yet been thoroughly investigated, this approach offers great promise to become a viable MS treatment.</p>\u0000 </div>","PeriodicalId":11300,"journal":{"name":"Developmental Neurobiology","volume":"85 4","pages":""},"PeriodicalIF":2.3,"publicationDate":"2025-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145354149","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Administering MSC-Derived Exosomes After Hypoxia-Induced Seizures in Neonatal Rats Improved Cognitive Function and Delayed the Onset of Epilepsy in Adulthood, Likely by Reducing Inflammation and Oxidative Stress","authors":"Parisa Arvin,&nbsp;Maryam Khombi Shooshtari,&nbsp;Ali Asadirad,&nbsp;Kowsar Bavarsad,&nbsp;Azam Asgarihafshejani,&nbsp;Yaghoob Farbood,&nbsp;Alireza Sarkaki,&nbsp;Samireh Ghafouri","doi":"10.1002/dneu.23010","DOIUrl":"10.1002/dneu.23010","url":null,"abstract":"<div>\u0000 \u0000 <p>Hypoxia-induced neonatal seizures (HINSs) are a major cause of long-term cognitive deficits and heightened epilepsy risk in adulthood. Early inflammatory responses following HINS contribute to these pathological outcomes. This study examined the sustained neuroprotective benefits of exosomes derived from mesenchymal stem cells (MSC-exosomes) in a rat model of HINS, leveraging their anti-inflammatory and neuroregenerative properties. Forty-nine male and female Wistar rats were divided into four groups: (1) control + saline, (2) control + exosome, (3) hypoxia + saline, and (4) hypoxia + exosome. Neonatal rats (postnatal day 10) were subjected to hypoxia (5% O₂ for 15 min). Sixty minutes after the onset of hypoxia induction, pups received either MSC-exosomes (30 µg/100 µL) or saline for 12 consecutive days (lactation period). Behavioral tests, hippocampal tissue analysis (for RT-PCR and oxidative stress markers), and pentylenetetrazole (PTZ) kindling were performed at P60–P61.</p>\u0000 <p>The study revealed that treatment with exosomes improved memory performance and reduced anxiety-like behaviors in the hypoxia-exposed group, as evidenced by the novel object recognition and elevated plus maze tests. These benefits were linked to decreased oxidative stress (lower malondialdehyde/MDA levels), reduced pro-inflammatory markers (interleukin-6 [IL-6] and tumor necrosis factor-α [TNF-α]), and increased anti-inflammatory signaling (higher IL-10) in the hippocampus. Although exosome therapy delayed the onset of epileptogenesis, it did not lessen the intensity of seizures. The results indicate that administering MSC-derived exosomes after HINS can reduce susceptibility to PTZ-induced kindling, alleviate neuroinflammation, regulate oxidative stress, and protect against long-term cognitive impairments. Together, these findings highlight the potential of exosome-based interventions in mitigating the delayed neurological effects of HINS during adolescence.</p>\u0000 </div>","PeriodicalId":11300,"journal":{"name":"Developmental Neurobiology","volume":"85 4","pages":""},"PeriodicalIF":2.3,"publicationDate":"2025-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145336654","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Declines in Oxytocin Receptor Density and Social Behavior Across a Dispersal-Like Transition in Solitary Hamsters","authors":"Annaliese K. Beery,&nbsp;Nicole S. Lee,&nbsp;Emma M. Cooke","doi":"10.1002/dneu.23005","DOIUrl":"10.1002/dneu.23005","url":null,"abstract":"<div>\u0000 \u0000 <p>Mammals are born into social groups: even species that become solitary begin life seeking social contact with family members. For solitary mammals, dispersal thus marks a major geographic and social transition from their natal group. This transition may be promoted by reduced social tolerance for and reduced interest in family members, and/or by unrelated factors such as increased exploration and activity. Dispersal may also coincide with other developmental events such as weaning or puberty. We investigated developmental changes in oxytocin receptor density in two solitary hamster species (Syrian hamsters: <i>Mesocricetus auratus</i> and Siberian hamsters: <i>Phodopus sungorus</i>) that disperse to individual burrows in the wild. We quantified oxytocin receptor density prior to and after separation from the natal group to determine whether and how neurobiological changes coincide with changes in social behavior. We also quantified transitions in social behavior across development in Syrian hamsters at 2.5, 4, and 8 weeks. Oxytocin receptor densities and distributions reorganized substantially from pre- to post-dispersal ages in both species. Binding decreased across brain regions, with declines in binding in the endopiriform nucleus of both species, and the greatest reduction in hippocampal CA2 of Syrian hamsters. All metrics of social interest and interaction declined across the 2.5–8 week interval—consistent with transition to a solitary lifestyle—except play behavior which peaked in the characteristic juvenile range. Developmental decline in oxytocin receptor density and oxytocin signaling may support transitions in social behavior in solitary mammals.</p>\u0000 </div>","PeriodicalId":11300,"journal":{"name":"Developmental Neurobiology","volume":"85 4","pages":""},"PeriodicalIF":2.3,"publicationDate":"2025-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145336710","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Real-Time Classification for EEG Data in Children With ASD Using Deep Learning Techniques","authors":"Lekshmylal P. L.,&nbsp;Suresh Kumar E.,&nbsp;Ashalatha Radhakrishnan,&nbsp;Shiny G.","doi":"10.1002/dneu.23009","DOIUrl":"10.1002/dneu.23009","url":null,"abstract":"<div>\u0000 \u0000 <p>Autism spectrum disorder (ASD) presents unique challenges in diagnosis and treatment, necessitating innovative approaches to understanding its underlying neurophysiological mechanisms. Real-time classification of electroencephalography (EEG) data in children with ASD faces significant challenges due to variability in EEG signals caused by individual differences in brain activity, age, and behavioral states, complicating robust algorithm development. This study develops and validates a deep learning–based framework for real-time EEG classification in children with ASD, aiming to enhance diagnostic accuracy and enable timely interventions. The dataset includes EEG recordings from 60 children (30 with ASD and 30 typically developing), representing diverse age groups and behavioral profiles to improve generalizability. Pre-processing removes noise and artifacts through segmentation, short-time Fourier transform (STFT), and independent component analysis (ICA). Grid search optimization (GSO) enhances model performance by systematically searching hyperparameter combinations to find the optimal configuration. A hybrid convolutional neural network (CNN)–long short-term memory (LSTM) framework is proposed, combining convolutional layers for spatial feature extraction with LSTM layers for temporal sequence modeling. This hybrid model is the primary proposed solution for real-time EEG classification due to its ability to capture both spatial and temporal features critical for interpreting sequential EEG data in children with ASD. The model achieves an accuracy of 87.5%, a precision of 85.0%, a recall of 90.0%, and an <i>F</i>1 score of 87.5% implemented using MATLAB software. In comparison, ResNet, a baseline deep CNN model, achieves slightly higher accuracy (89.1%) but lacks temporal modeling capabilities essential for sequential EEG interpretation. Despite ResNet's marginally higher accuracy, the hybrid CNN–LSTM is favored as the final model for its superior temporal modeling, critical in EEG analysis. Future work may include real-time feedback mechanisms, mobile application development, and longitudinal data expansion.</p>\u0000 </div>","PeriodicalId":11300,"journal":{"name":"Developmental Neurobiology","volume":"85 4","pages":""},"PeriodicalIF":2.3,"publicationDate":"2025-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145336671","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Neurodevelopmental Impact of Prenatal Stress: A Proteomic Analysis of Myelination Disruptions in the Avian Embryo","authors":"Bela Gaertner,&nbsp;Gabriela Morosan-Puopolo,&nbsp;Beate Brand-Saberi,&nbsp;Charmaine Schücke,&nbsp;Darius Saberi,&nbsp;Katharina Klöster,&nbsp;Simon Faissner,&nbsp;Katrin Marcus,&nbsp;Morris Gellisch,&nbsp;Britta Eggers","doi":"10.1002/dneu.23003","DOIUrl":"10.1002/dneu.23003","url":null,"abstract":"<p>Prenatal stress, mediated by elevated glucocorticoid (GC) levels, is a relevant modulator of fetal brain development and a known risk factor for neurodevelopmental disorders. Using the avian embryo as a vertebrate model, we injected corticosterone into the yolk on embryonic day 6 (E6) and assessed neurodevelopmental outcomes at day 14 (E14). Through deep proteomic profiling — quantifying over 6500 proteins — we uncovered a robust molecular signature of stress-induced disruption. Key myelin-associated proteins (myelin basic protein [MBP], PLP1, 2′,3′-cyclic-nucleotide 3′-phosphodiesterase [CNP]) were markedly downregulated, indicating impaired oligodendrocyte maturation. These proteomic shifts were corroborated by immunohistochemistry and qPCR. Pathway-level analysis pointed to altered MAPK and AKT signaling as putative mediators of the observed phenotype. Our findings mirror previous mammalian data while highlighting the avian model's unique suitability for mechanistic dissection of prenatal stress effects. This study offers new insight into how early GC exposure impairs glial development, with broader implications for understanding the molecular origins of stress-linked brain vulnerability.</p>","PeriodicalId":11300,"journal":{"name":"Developmental Neurobiology","volume":"85 4","pages":""},"PeriodicalIF":2.3,"publicationDate":"2025-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12521880/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145291417","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cuminaldehyde, a Hopeful Agent, Mitigates Autistic-Like Behaviors, Combating Hippocampal Neuroinflammation in Maternal Separation Stress Model in Male Mice","authors":"Alireza Gholipour Shahraki,&nbsp;Fariba Houshmand,&nbsp;Elham Saghaei,&nbsp;Hossein Amini-Khoei","doi":"10.1002/dneu.23008","DOIUrl":"10.1002/dneu.23008","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background and aim</h3>\u0000 \u0000 <p>Autism spectrum disorder (ASD) is a neurodevelopmental disorder that appears in the earliest ages of the lifespan. The causes of ASD remain anonymous, although immunological, genetic, biological, and psychosocial theories have been proposed. Stresses during early life, such as maternal separation (MS), are one of the psychosocial causes of ASD. The neuroimmune response is complicated in the pathophysiology of ASD. Cuminaldehyde (CA) has different pharmacological effects, such as anti-inflammatory properties. This study aimed to explore effects of CA on autistic-like behaviors in maternally separated mice with respect to its probable anti-neuroinflammatory effects.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Forty male mice were randomly allocated to five groups, including control mice administered with normal saline, and MS groups received normal saline and CA with doses of 5, 25, 50 mg/kg intraperitoneally for 14 continuous days. The three-chamber sociability, the resident–intruder, and shuttle box tests were performed. Subsequently, mice were euthanized, and the expression of the <i>NLRP3</i>, <i>TLR4</i>, <i>HMGB1</i>, and <i>IL-1β</i> genes in the hippocampus was investigated using real-time PCR.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>MS mice showed diminished sociability preference, damaged passive avoidance memory, as well as aggressive behaviors. Behaviors related to autism in MS mice are associated with a rise in the expression of inflammatory markers in the hippocampus. CA reversed the deleterious effects of MS on behaviors, in addition to a decrease in the expression of inflammatory genes in the hippocampus.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>CA, via attenuation of neuroimmune reaction in the hippocampus, partially mitigated autistic-like behaviors in the MS mouse model.</p>\u0000 </section>\u0000 </div>","PeriodicalId":11300,"journal":{"name":"Developmental Neurobiology","volume":"85 4","pages":""},"PeriodicalIF":2.3,"publicationDate":"2025-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145291428","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Early Prediction and Risk Analysis Using Hybrid Deep Learning Techniques in Multimodal Biomedical Image","authors":"Anoop Vylala,&nbsp;Bipin Plakkottu Radhakrishnan,&nbsp;Anoop Balakrishnan Kadan","doi":"10.1002/dneu.23001","DOIUrl":"10.1002/dneu.23001","url":null,"abstract":"<div>\u0000 \u0000 <p>Medical imaging plays a pivotal role in diagnosing and treating various health conditions, especially in early-stage cancer detection. Despite advancements in imaging techniques, the complexity and variability of multimodal medical images, such as MRI and CT scans, pose challenges for accurate diagnosis. Traditional methods often struggle with combining these heterogeneous data sources effectively, limiting the ability to provide timely and precise predictions for early cancer detection. This study proposes a hybrid deep learning framework that integrates multimodal image fusion techniques to improve early cancer prediction. The primary objective of this work is to develop an efficient model that can process diverse medical images, extract meaningful features, and provide accurate classifications for identifying cancerous regions. The techniques employed include Gaussian smoothing for image pre-processing, feature extraction using ORB (Oriented FAST and Rotated BRIEF) for handcrafted features, and the InceptionV4 network for deep learning-based feature extraction. The final stage involves classification using Sparse Logistic Regression and the MS-GWNN classifier, designed to predict the malignancy stage of tumors. The experimental results demonstrate that the proposed approach significantly outperforms traditional methods, achieving a classification accuracy of 93.4%, sensitivity of 91.8%, and specificity of 92.5%. These metrics show superior performance in early detection and risk assessment, especially for high-risk cancer cases. The model is validated using TCIA dataset and displays robust fusion capabilities, leading to high-quality and reliable predictions. Future work will explore the integration of additional imaging modalities, real-time applications for clinical settings, and optimization of fusion strategies. Furthermore, incorporating explainable AI (XAI) can improve the interpretability of the model, enhancing its usability in clinical practice.</p>\u0000 </div>","PeriodicalId":11300,"journal":{"name":"Developmental Neurobiology","volume":"85 4","pages":""},"PeriodicalIF":2.3,"publicationDate":"2025-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145181847","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Neuronal Plasticity in the Mushroom Bodies of Winter Bees Is Retained Despite Substantially Advanced Age","authors":"Nadine Kraft,&nbsp;Wolfgang Rössler,&nbsp;Claudia Groh","doi":"10.1002/dneu.23006","DOIUrl":"10.1002/dneu.23006","url":null,"abstract":"<p>Honeybee (<i>Apis mellifera</i>) workers exhibit remarkable behavioral plasticity throughout adult life. In spring and summer, they transition through diverse tasks over a short lifespan of 4–6 weeks. This involves dramatic changes in sensory environment and cognitive demands associated with pronounced structural neuronal plasticity in the mushroom bodies (MBs), high-order brain centers for sensory integration, learning, and memory. This plasticity manifests as age- and experience-related volume increase in sensory input regions of the MB calyces, accompanied by pruning of projection neuron (PN) boutons in synaptic microcircuits within visual and olfactory compartments. As winter approaches, honeybees suspend brood rearing and foraging activities to survive the cold months by forming a tight, thermoregulated cluster. Unique physiological adaptations enable winter bees to live up to 8 months until a new generation emerges in spring. This extended lifespan occurs during a period of reduced sensory input and high metabolic costs raising the question of how such conditions affect structural neuronal plasticity. Using synapsin immunolabeling and 3D confocal-microscopy image analyses of MB synaptic neuropils in whole-mount brains of age-controlled worker bees, we found that winter bees retain a high degree of neuronal plasticity throughout their lifespan. MB calyces exhibit an initial volume increase followed by a period of stagnation to then undergo another expansion at the onset of spring foraging. While olfactory PN boutons exhibit continuous pruning, visual bouton numbers remain stable during winter. We conclude that winter bees retain comparable neuronal capacities to summer bees, despite strong differences in lifespan, physiological, and environmental conditions.</p>","PeriodicalId":11300,"journal":{"name":"Developmental Neurobiology","volume":"85 4","pages":""},"PeriodicalIF":2.3,"publicationDate":"2025-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12476488/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145181864","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"E2E-TM: Dual-Way Feature Extraction and End-to-End Transformer Based Parkinson's Disease Diagnosis Using Integrated MR Imaging and Electroencephalogram Signals","authors":"Sundaram Mohanapriya,&nbsp;Kamalraj Subramaniam","doi":"10.1002/dneu.23002","DOIUrl":"10.1002/dneu.23002","url":null,"abstract":"<div>\u0000 \u0000 <p>Parkinson's disease (PD) is a liberal neurological disorder categorized by tremors, stiffness, and decreased motor function, resulting from the degeneration of dopamine-producing nerve cells in the brain. The limitations of early diagnosis of PD using ML and deep learning (DL) include potential challenges in accessing diverse and representative datasets, as well as the risk of overfitting models to specific populations, hindering the generalizability of diagnostic tools transversely diverse patient groups and demographics. To alleviate these issues, we introduced an end-to-end transformer module, E2E-TM, for precise PD diagnosis. Initially, we acquired both magnetic resonance imaging (MRI) and electroencephalography (EEG) data, underwent noise reduction using the bilateral filter and wavelet decomposition, and performed segmentation and reconstruction on MRI images using Super U-Net to reduce data complexity. Subsequently, false peaks in EEG signals were eliminated on the basis of multiple features, and both datasets were input into the proposed E2E-TM model. The transformer encoder module (TEM) included a multi-scale trunk convolution (Multi-TC) module with a penalty and reward strategy, designed in a parallel manner for feature extraction via trunk convolution. Feature maps were then mapped to their feature points using the dual-way trunk convolutional (DW-TC) module, and dual-parallel attention network (DPANet) was employed to minimize feature dimensionality. Finally, the transformer decoder module (TDM) was developed to entangle and decode the feature maps of both datasets for the classification of the diagnosed outcome. Our proposed E2E-TM model's efficiency is evaluated for proving its efficacy. As a result, our E2E-TM model attained superior diagnosis performance compared to other baseline approaches.</p>\u0000 </div>","PeriodicalId":11300,"journal":{"name":"Developmental Neurobiology","volume":"85 4","pages":""},"PeriodicalIF":2.3,"publicationDate":"2025-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145181880","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Altered Serum IL-6 and TGF-β1 Levels Are Associated With Generalized Anxiety Disorder: A Case–Control Study","authors":"Md. Ashrafuzzaman Alfi,&nbsp;Jannatul Naim,&nbsp;Iftekhar Ahmed,&nbsp;Mohammad Fahim Kadir,&nbsp;Sarder Mohammad Ashraful Islam,&nbsp;Mohiuddin Ahmed Bhuiyan,&nbsp;Md. Rabiul Islam","doi":"10.1002/dneu.23004","DOIUrl":"10.1002/dneu.23004","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Generalized anxiety disorder (GAD) is a chronic psychiatric disease characterized by excessive and uncontrollable worry about common life events. Neurological, neurochemical, genomic, environmental, psychogenic, and immunological factors are thought to be involved in GAD. However, studies conducted to establish any suitable biomarkers for the assessment of anxiety disorder is limited. Hence, we aim to investigate the serum levels of interleukin-6 (IL-6) and transforming growth factor-beta 1 (TGF-β1) in GAD patients.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Method</h3>\u0000 \u0000 <p>The present study enrolled 44 GAD patients and 44 healthy controls (HCs) from a tertiary care teaching hospital in Dhaka, Bangladesh. A qualified psychiatrist assessed the study population based on the criteria mentioned in the DSM-5. We measured the serum levels of IL-6 and TGF-β1 using the commercially available enzyme-linked immunosorbent assay (ELISA) kits.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>We noted a significant reduction in serum IL-6 and TGF-β1 levels in GAD patients compared to HCs (IL-6: 7.72 ± 2.14 vs. 9.39 ± 1.22 pg/mL; <i>p</i> = 0.003, and TGF-β1: 386.77 ± 157.91 vs. 774.51 ± 327.73 pg/mL; <i>p</i> = 0.001). Moreover, a significant negative association was found between the levels of IL-6 and GAD-7 scores among the GAD patients (<i>r</i> = −0.395, <i>p</i> &lt; 0.001). Lastly, the ROC analysis demonstrated a strong predictive accuracy with a moderately higher area under the curve (AUC) value (IL-6: 0.888 and TGF-β1: 0.891), relatively higher sensitivity (IL-6: 85.3% and TGF-β1: 85.6%), and higher specificity (IL-6: 86.7% and TGF-β1: 82.4%).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>Our study findings underscore that lowered IL-6 and TGF-β1 levels might have a role in the pathophysiology and development of GAD. Therefore, the alterations of cytokines have a crucial role in evaluating the GAD patients. We suggest further interventional studies to determine the actual predictive performance of IL-6 and TGF-β1 in GAD.</p>\u0000 </section>\u0000 </div>","PeriodicalId":11300,"journal":{"name":"Developmental Neurobiology","volume":"85 4","pages":""},"PeriodicalIF":2.3,"publicationDate":"2025-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145130366","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}