Pleural effusion guidelines from ICS and NCCP Section 1: Basic principles, laboratory tests and pleural procedures.

Pleural effusion is a common problem in our country, and most of these patients need invasive tests as they can't be evaluated by blood tests alone. The simplest of them is diagnostic pleural aspiration, and diagnostic techniques such as medical thoracoscopy are being performed more frequently than ever before. However, most physicians in India treat pleural effusion empirically, leading to delays in diagnosis, misdiagnosis and complications from wrong treatments. This situation must change, and the adoption of evidence-based protocols is urgently needed. Furthermore, the spectrum of pleural disease in India is different from that in the West, and yet Western guidelines and algorithms are used by Indian physicians. Therefore, India-specific consensus guidelines are needed. To fulfil this need, the Indian Chest Society and the National College of Chest Physicians; the premier societies for pulmonary physicians came together to create this National guideline. This document aims to provide evidence based recommendations on basic principles, initial assessment, diagnostic modalities and management of pleural effusions.

Mapping hippocampal and thalamic atrophy in epilepsy: A 7-T magnetic resonance imaging study.

OBJECTIVE: Epilepsy patients are often grouped together by clinical variables. Quantitative neuroimaging metrics can provide a data-driven alternative for grouping of patients. In this work, we leverage ultra-high-field 7-T structural magnetic resonance imaging (MRI) to characterize volumetric atrophy patterns across hippocampal subfields and thalamic nuclei in drug-resistant focal epilepsy. METHODS: Forty-two drug-resistant epilepsy patients and 13 controls with 7-T structural neuroimaging were included in this study. We measured hippocampal subfield and thalamic nuclei volumetry, and applied an unsupervised machine learning algorithm, Latent Dirichlet Allocation (LDA), to estimate atrophy patterns across the hippocampal subfields and thalamic nuclei of patients. We studied the association between predefined clinical groups and the estimated atrophy patterns. Additionally, we used hierarchical clustering on the LDA factors to group patients in a data-driven approach. RESULTS: In patients with mesial temporal sclerosis (MTS), we found a significant decrease in volume across all ipsilateral hippocampal subfields (false discovery rate-corrected p [pFDR] < .01) as well as in some ipsilateral (pFDR < .05) and contralateral (pFDR < .01) thalamic nuclei. In left temporal lobe epilepsy (L-TLE) we saw ipsilateral hippocampal and some bilateral thalamic atrophy (pFDR < .05), whereas in right temporal lobe epilepsy (R-TLE) extensive bilateral hippocampal and thalamic atrophy was observed (pFDR < .05). Atrophy factors demonstrated that our MTS cohort had two atrophy phenotypes: one that affected the ipsilateral hippocampus and one that affected the ipsilateral hippocampus and bilateral anterior thalamus. Atrophy factors demonstrated posterior thalamic atrophy in R-TLE, whereas an anterior thalamic atrophy pattern was more common in L-TLE. Finally, hierarchical clustering of atrophy patterns recapitulated clusters with homogeneous clinical properties. SIGNIFICANCE: Leveraging 7-T MRI, we demonstrate widespread hippocampal and thalamic atrophy in epilepsy. Through unsupervised machine learning, we demonstrate patterns of volumetric atrophy that vary depending on disease subtype. Incorporating these atrophy patterns into clinical practice could help better stratify patients to surgical treatments and specific device implantation strategies.

Tissue-targeted and localized AAV5-DCN and AAV5-PEDF combination gene therapy abrogates corneal fibrosis and concurrent neovascularization in rabbit eyes in vivo.

PURPOSE: Corneal fibrosis and neovascularization (CNV) after ocular trauma impairs vision. This study tested therapeutic potential of tissue-targeted adeno-associated virus5 (AAV5) mediated decorin (DCN) and pigment epithelium-derived factor (PEDF) combination genes in vivo. METHODS: Corneal fibrosis and CNV were induced in New Zealand White rabbits via chemical trauma. Gene therapy in stroma was delivered 30-min after chemical-trauma via topical AAV5-DCN and AAV5-PEDF application using a cloning cylinder. Clinical eye examinations and multimodal imaging in live rabbits were performed periodically and corneal tissues were collected 9-day and 15-day post euthanasia. Histological, cellular, and molecular and apoptosis assays were used for efficacy, tolerability, and mechanistic studies. RESULTS: The AAV5-DCN and AAV5-PEDF combination gene therapy significantly reduced corneal fibrosis (p < 0.01 or p < 0.001) and CNV (p < 0.001) in therapy-given (chemical-trauma and AAV5-DCN + AAV5-PEDF) rabbit eyes compared to the no-therapy given eyes (chemical-trauma and AAV5-naked vector). Histopathological analyses demonstrated significantly reduced fibrotic α-smooth muscle actin and endothelial lectin expression in therapy-given corneas compared to no-therapy corneas on day-9 (p < 0.001) and day-15 (p < 0.001). Further, therapy-given corneas showed significantly increased Fas-ligand mRNA levels (p < 0.001) and apoptotic cell death in neovessels (p < 0.001) compared to no-therapy corneas. AAV5 delivered 2.69 × 107 copies of DCN and 2.31 × 107 copies of PEDF genes per µg of DNA. AAV5 vector and delivered DCN and PEDF genes found tolerable to the rabbit eyes and caused no significant toxicity to the cornea. CONCLUSION: The combination AAV5-DCN and AAV5-PEDF topical gene therapy effectively reduces corneal fibrosis and CNV with high tolerability in vivo in rabbits. Additional studies are warranted.

iEEG-recon: A fast and scalable pipeline for accurate reconstruction of intracranial electrodes and implantable devices.

OBJECTIVE: Clinicians use intracranial electroencephalography (iEEG) in conjunction with noninvasive brain imaging to identify epileptic networks and target therapy for drug-resistant epilepsy cases. Our goal was to promote ongoing and future collaboration by automating the process of "electrode reconstruction," which involves the labeling, registration, and assignment of iEEG electrode coordinates on neuroimaging. We developed a standalone, modular pipeline that performs electrode reconstruction. We demonstrate our tool's compatibility with clinical and research workflows and its scalability on cloud platforms. METHODS: We created iEEG-recon, a scalable electrode reconstruction pipeline for semiautomatic iEEG annotation, rapid image registration, and electrode assignment on brain magnetic resonance imaging (MRI). Its modular architecture includes a clinical module for electrode labeling and localization, and a research module for automated data processing and electrode contact assignment. To ensure accessibility for users with limited programming and imaging expertise, we packaged iEEG-recon in a containerized format that allows integration into clinical workflows. We propose a cloud-based implementation of iEEG-recon and test our pipeline on data from 132 patients at two epilepsy centers using retrospective and prospective cohorts. RESULTS: We used iEEG-recon to accurately reconstruct electrodes in both electrocorticography and stereoelectroencephalography cases with a 30-min running time per case (including semiautomatic electrode labeling and reconstruction). iEEG-recon generates quality assurance reports and visualizations to support epilepsy surgery discussions. Reconstruction outputs from the clinical module were radiologically validated through pre- and postimplant T1-MRI visual inspections. We also found that our use of ANTsPyNet deep learning-based brain segmentation for electrode classification was consistent with the widely used FreeSurfer segmentations. SIGNIFICANCE: iEEG-recon is a robust pipeline for automating reconstruction of iEEG electrodes and implantable devices on brain MRI, promoting fast data analysis and integration into clinical workflows. iEEG-recon's accuracy, speed, and compatibility with cloud platforms make it a useful resource for epilepsy centers worldwide.

Differential gene expression and protein-protein interaction network profiling of sulfur mustard-exposed rabbit corneas employing RNA-seq data and bioinformatics tools.

Sulfur mustard (SM) ocular exposure severely damages the cornea and causes vision impairment. At present, no specific therapy exists to mitigate SM-induced corneal injury and vision loss. This study performed transcriptome profiling of naïve, SM-damaged, and SM-undamaged rabbit corneas using RNA-seq analysis and bioinformatic tools to gain a better mechanistic understanding and develop SM-specific medical countermeasures. The mRNA profiles of rabbit corneas 4 weeks post SM vapor exposure were generated using Illumina-NextSeq deep sequencing (Gene Expression Omnibus accession # GSE127708). The RNA sequences of naïve (n = 4), SM-damaged (n = 5), and SM-undamaged (n = 5) corneas were subjected to differential expression (DE) analysis after quality control profiling with FastQC. DE analysis was performed using HISAT2, StringTie, and DESeq2. The log2(FC)±2 and adjusted p˂0.05 were chosen to identify the most relevant genes. A total of 5930 differentially expressed genes (DEGs) (upregulated: 3196, downregulated: 2734) were found in SM-damaged corneas compared to naïve corneas, whereas SM-undamaged corneas showed 1884 DEGs (upregulated: 1029, downregulated: 855) compared to naïve corneas. DE profiling of SM-damaged corneas to SM-undamaged corneas revealed 985 genes (upregulated: 308, downregulated: 677). The DE profiles were subsequently subjected to signaling pathway enrichment, and protein‒protein interactions (PPIs) were analyzed. Pathway enrichment was performed for the genes associated with cellular apoptosis, death, adhesion, migration, differentiation, proliferation, extracellular matrix, and tumor necrosis factor production. To identify novel targets, we narrowed the pathway analysis to upregulated and downregulated genes associated with cell proliferation and differentiation, and PPI networks were developed. Furthermore, protein targets associated with cell differentiation and proliferation that may play vital roles in corneal fibrosis and wound healing post SM injury were identified.

Quantifying interictal intracranial EEG to predict focal epilepsy.

Introduction: Intracranial EEG (IEEG) is used for 2 main purposes, to determine: (1) if epileptic networks are amenable to focal treatment and (2) where to intervene. Currently these questions are answered qualitatively and sometimes differently across centers. There is a need for objective, standardized methods to guide surgical decision making and to enable large scale data analysis across centers and prospective clinical trials. Methods: We analyzed interictal data from 101 patients with drug resistant epilepsy who underwent presurgical evaluation with IEEG. We chose interictal data because of its potential to reduce the morbidity and cost associated with ictal recording. 65 patients had unifocal seizure onset on IEEG, and 36 were non-focal or multi-focal. We quantified the spatial dispersion of implanted electrodes and interictal IEEG abnormalities for each patient. We compared these measures against the "5 Sense Score (5SS)," a pre-implant estimate of the likelihood of focal seizure onset, and assessed their ability to predict the clinicians' choice of therapeutic intervention and the patient outcome. Results: The spatial dispersion of IEEG electrodes predicted network focality with precision similar to the 5SS (AUC = 0.67), indicating that electrode placement accurately reflected pre-implant information. A cross-validated model combining the 5SS and the spatial dispersion of interictal IEEG abnormalities significantly improved this prediction (AUC = 0.79; p<0.05). The combined model predicted ultimate treatment strategy (surgery vs. device) with an AUC of 0.81 and post-surgical outcome at 2 years with an AUC of 0.70. The 5SS, interictal IEEG, and electrode placement were not correlated and provided complementary information. Conclusions: Quantitative, interictal IEEG significantly improved upon pre-implant estimates of network focality and predicted treatment with precision approaching that of clinical experts. We present this study as an important step in building standardized, quantitative tools to guide epilepsy surgery.

The seizure severity score: a quantitative tool for comparing seizures and their response to therapy.

Objective.Epilepsy is a neurological disorder characterized by recurrent seizures which vary widely in severity, from clinically silent to prolonged convulsions. Measuring severity is crucial for guiding therapy, particularly when complete control is not possible. Seizure diaries, the current standard for guiding therapy, are insensitive to the duration of events or the propagation of seizure activity across the brain. We present a quantitative seizure severity score that incorporates electroencephalography (EEG) and clinical data and demonstrate how it can guide epilepsy therapies.Approach.We collected intracranial EEG and clinical semiology data from 54 epilepsy patients who had 256 seizures during invasive, in-hospital presurgical evaluation. We applied an absolute slope algorithm to EEG recordings to identify seizing channels. From this data, we developed a seizure severity score that combines seizure duration, spread, and semiology using non-negative matrix factorization. For validation, we assessed its correlation with independent measures of epilepsy burden: seizure types, epilepsy duration, a pharmacokinetic model of medication load, and response to epilepsy surgery. We investigated the association between the seizure severity score and preictal network features.Main results.The seizure severity score augmented clinical classification by objectively delineating seizure duration and spread from recordings in available electrodes. Lower preictal medication loads were associated with higher seizure severity scores (p= 0.018, 97.5% confidence interval = [-1.242, -0.116]) and lower pre-surgical severity was associated with better surgical outcome (p= 0.042). In 85% of patients with multiple seizure types, greater preictal change from baseline was associated with higher severity.Significance.We present a quantitative measure of seizure severity that includes EEG and clinical features, validated on gold standard in-patient recordings. We provide a framework for extending our tool's utility to ambulatory EEG devices, for linking it to seizure semiology measured by wearable sensors, and as a tool to advance data-driven epilepsy care.

Intracranial EEG Structure-Function Coupling and Seizure Outcomes After Epilepsy Surgery.

BACKGROUND AND OBJECTIVES: Surgery is an effective treatment for drug-resistant epilepsy, which modifies the brain's structure and networks to regulate seizure activity. Our objective was to examine the relationship between brain structure and function to determine the extent to which this relationship affects the success of the surgery in controlling seizures. We hypothesized that a stronger association between brain structure and function would lead to improved seizure control after surgery. METHODS: We constructed functional and structural brain networks in patients with drug-resistant focal epilepsy by using presurgery functional data from intracranial EEG (iEEG) recordings, presurgery and postsurgery structural data from T1-weighted MRI, and presurgery diffusion-weighted MRI. We quantified the relationship (coupling) between structural and functional connectivity by using the Spearman rank correlation and analyzed this structure-function coupling at 2 spatial scales: (1) global iEEG network level and (2) individual iEEG electrode contacts using virtual surgeries. We retrospectively predicted postoperative seizure freedom by incorporating the structure-function connectivity coupling metrics and routine clinical variables into a cross-validated predictive model. RESULTS: We conducted a retrospective analysis on data from 39 patients who met our inclusion criteria. Brain areas implanted with iEEG electrodes had stronger structure-function coupling in seizure-free patients compared with those with seizure recurrence (p = 0.002, d = 0.76, area under the receiver operating characteristic curve [AUC] = 0.78 [95% CI 0.62-0.93]). Virtual surgeries on brain areas that resulted in stronger structure-function coupling of the remaining network were associated with seizure-free outcomes (p = 0.007, d = 0.96, AUC = 0.73 [95% CI 0.58-0.89]). The combination of global and local structure-function coupling measures accurately predicted seizure outcomes with a cross-validated AUC of 0.81 (95% CI 0.67-0.94). These measures were complementary to other clinical variables and, when included for prediction, resulted in a cross-validated AUC of 0.91 (95% CI 0.82-1.0), accuracy of 92%, sensitivity of 93%, and specificity of 91%. DISCUSSION: Our study showed that the strength of structure-function connectivity coupling may play a crucial role in determining the success of epilepsy surgery. By quantitatively incorporating structure-function coupling measures and standard-of-care clinical variables into presurgical evaluations, we may be able to better localize epileptogenic tissue and select patients for epilepsy surgery. CLASSIFICATION OF EVIDENCE: This is a Class IV retrospective case series showing that structure-function mapping may help determine the outcome from surgical resection for treatment-resistant focal epilepsy.

iEEG-recon: A Fast and Scalable Pipeline for Accurate Reconstruction of Intracranial Electrodes and Implantable Devices.

Background: Collaboration between epilepsy centers is essential to integrate multimodal data for epilepsy research. Scalable tools for rapid and reproducible data analysis facilitate multicenter data integration and harmonization. Clinicians use intracranial EEG (iEEG) in conjunction with non-invasive brain imaging to identify epileptic networks and target therapy for drug-resistant epilepsy cases. Our goal was to promote ongoing and future collaboration by automating the process of "electrode reconstruction," which involves the labeling, registration, and assignment of iEEG electrode coordinates on neuroimaging. These tasks are still performed manually in many epilepsy centers. We developed a standalone, modular pipeline that performs electrode reconstruction. We demonstrate our tool's compatibility with clinical and research workflows and its scalability on cloud platforms. Methods: We created iEEG-recon, a scalable electrode reconstruction pipeline for semi-automatic iEEG annotation, rapid image registration, and electrode assignment on brain MRIs. Its modular architecture includes three modules: a clinical module for electrode labeling and localization, and a research module for automated data processing and electrode contact assignment. To ensure accessibility for users with limited programming and imaging expertise, we packaged iEEG-recon in a containerized format that allows integration into clinical workflows. We propose a cloud-based implementation of iEEG-recon, and test our pipeline on data from 132 patients at two epilepsy centers using retrospective and prospective cohorts. Results: We used iEEG-recon to accurately reconstruct electrodes in both electrocorticography (ECoG) and stereoelectroencephalography (SEEG) cases with a 10 minute running time per case, and ~20 min for semi-automatic electrode labeling. iEEG-recon generates quality assurance reports and visualizations to support epilepsy surgery discussions. Reconstruction outputs from the clinical module were radiologically validated through pre- and post-implant T1-MRI visual inspections. Our use of ANTsPyNet deep learning approach for brain segmentation and electrode classification was consistent with the widely used Freesurfer segmentation. Discussion: iEEG-recon is a valuable tool for automating reconstruction of iEEG electrodes and implantable devices on brain MRI, promoting efficient data analysis, and integration into clinical workflows. The tool's accuracy, speed, and compatibility with cloud platforms make it a useful resource for epilepsy centers worldwide. Comprehensive documentation is available at https://ieeg-recon.readthedocs.io/en/latest/.

Dynamics of soil organic carbon of jhum agriculture land-use system in the heterogeneous hill of Arunachal Pradesh, India.

Land-use conversion affects soil organic carbon (SOC) dynamics. Therefore, an in-depth study of change in SOC, SOC pool, fractions of SOC and enzymatic activities of soil microbial biomass carbon (SMBC) and dehydrogenase (DHA) with the conversion of forest land to jhum, fallow jhum and settle cultivation use has been undertaken on the hills of Arunachal Pradesh of India. Geo-referenced soil samples from eight different locations, each from different land uses were collected at three depth. One part of the soil sample had been used for the analysis of SOC and its carbon fraction. The second portion was kept in a deep freezer for determining SMBC and DHA. The third part was used for the analysis of bulk density. The result revealed that the highest loss of SOC pool was recorded in jhum land (41.8 to 13.4%), and the labile carbon was also found to decrease in jhum land. The highest SMBC was observed on the surface soil of the natural forest; the highest DHA was found in the natural forest; and the lowest DHA was recorded in jhum land. This study found that the converting natural forest to jhum reduces SOC storage, enzymatic activities and C fractions significantly whereas fallow jhum shows sign of recovery because all of these parameters improved when compared to the jhum land-use system. This study also confirms that the fallow period helps restore the initial situation.

Toxicological effects of ocular acrolein exposure to eyelids in rabbits in vivo.

Acrolein is a highly reactive volatile toxic chemical that injures the eyes and many organs. It has been used in wars and terrorism for wounding masses on multiple occasions and is readily accessible commercially. Our earlier studies revealed acrolein's toxicity to the cornea and witnessed damage to other ocular tissues. Eyelids play a vital role in keeping eyes mobile, moist, lubricated, and functional utilizing a range of diverse lipids produced by the Meibomian glands located in the upper and lower eyelids. This study sought to investigate acrolein's toxicity to eyelid tissues by studying the expression of inflammatory and lipid markers in rabbit eyes in vivo utilizing our reported vapor-cap model. The study was approved by the institutional animal care and use committees and followed ARVO guidelines. Twelve New Zealand White Rabbits were divided into 3 groups: Naïve (group 1), 1-min acrolein exposure (group 2), or 3-min acrolein exposure (group 3). The toxicological effects of acrolein on ocular health in live animals were monitored with regular clinical eye exams and intraocular pressure measurements and eyelid tissues post-euthanasia were subjected to H&E and Masson's trichrome histology and qRT-PCR analysis. Clinical eye examinations witnessed severely swollen eyelids, abnormal ocular discharge, chemosis, and elevated intraocular pressure (p < 0.001) in acrolein-exposed eyes. Histological studies supported clinical findings and exhibited noticeable changes in eyelid tissue morphology. Gene expression studies exhibited significantly increased expression of inflammatory and lipid mediators (LOX, PAF, Cox-2, and LTB4; p < 0.001) in acrolein-exposed eyelid tissues compared to naïve eyelid tissues. The results suggest that acrolein exposure to the eyes causes acute damage to eyelids by altering inflammatory and lipid mediators in vivo.

Improved Seizure Onset-Zone Lateralization in Temporal Lobe Epilepsy using 7T Resting-State fMRI: A Direct Comparison with 3T.

Objective: Resting-state functional magnetic resonance imaging (rs-fMRI) at ultra high-field strengths (≥7T) is known to provide superior signal-to-noise and statistical power than comparable acquisitions at lower field strengths. In this study, we aim to provide a direct comparison of the seizure onset-zone (SOZ) lateralizing ability of 7T rs-fMRI and 3T rs-fMRI. Methods: We investigated a cohort of 70 temporal lobe epilepsy (TLE) patients. A paired cohort of 19 patients had 3T and 7T rs-fMRI acquisitions for direct comparison between the two field strengths. Forty-three patients had only 3T, and 8 patients had only 7T rs-fMRI acquisitions. We quantified the functional connectivity between the hippocampus and other nodes within the default mode network (DMN) using seed-to-voxel connectivity, and measured how hippocampo-DMN connectivity could inform SOZ lateralization at 7T and 3T field strengths. Results: Differences between hippocampo-DMN connectivity ipsilateral and contralateral to the SOZ were significantly higher at 7T (pFDR=0.008) than at 3T (pFDR=0.80) when measured in the same subjects. We found that our ability to lateralize the SOZ, by distinguishing subjects with left TLE from subjects with right TLE, was superior at 7T (AUC = 0.97) than 3T (AUC = 0.68). Our findings were reproduced in extended cohorts of subjects scanned at either 3T or 7T. Our rs-fMRI findings at 7T, but not 3T, are consistent and highly correlated (Spearman Rho=0.65) with clinical FDG-PET lateralizing hypometabolism. Significance: We show superior SOZ lateralization in TLE patients when using 7T relative to 3T rs-fMRI, supporting the adoption of high-field strength functional imaging in the epilepsy presurgical evaluation.

Mustard Gas Exposure Actuates SMAD2/3 Signaling to Promote Myofibroblast Generation in the Cornea.

Sulfur mustard gas (SM) is a vesicating and alkylating agent used as a chemical weapon in many mass-casualty incidents since World War I. Ocular injuries were reported in >90% of exposed victims. The mechanisms underlying SM-induced blindness remain elusive. This study tested the hypothesis that SM-induced corneal fibrosis occurs due to the generation of myofibroblasts from resident fibroblasts via the SMAD2/3 signaling pathway in rabbit eyes in vivo and primary human corneal fibroblasts (hCSFs) isolated from donor corneas in vitro. Fifty-four New Zealand White Rabbits were divided into three groups (Naïve, Vehicle, SM-Vapor treated). The SM-Vapor group was exposed to SM at 200 mg-min/m3 for 8 min at the MRI Global facility. Rabbit corneas were collected on day 3, day 7, and day 14 for immunohistochemistry, RNA, and protein lysates. SM caused a significant increase in SMAD2/3, pSMAD, and ɑSMA expression on day 3, day 7, and day 14 in rabbit corneas. For mechanistic studies, hCSFs were treated with nitrogen mustard (NM) or NM + SIS3 (SMAD3-specific inhibitor) and collected at 30 m, 8 h, 24 h, 48 h, and 72 h. NM significantly increased TGFß, pSMAD3, and SMAD2/3 levels. On the contrary, inhibition of SMAD2/3 signaling by SIS3 treatment significantly reduced SMAD2/3, pSMAD3, and ɑSMA expression in hCSFs. We conclude that SMAD2/3 signaling appears to play a vital role in myofibroblast formation in the cornea following mustard gas exposure.

Subcortical functional connectivity gradients in temporal lobe epilepsy.

BACKGROUND AND MOTIVATION: Functional gradients have been used to study differences in connectivity between healthy and diseased brain states, however this work has largely focused on the cortex. Because the subcortex plays a key role in seizure initiation in temporal lobe epilepsy (TLE), subcortical functional-connectivity gradients may help further elucidate differences between healthy brains and TLE, as well as differences between left (L)-TLE and right (R)-TLE. METHODS: In this work, we calculated subcortical functional-connectivity gradients (SFGs) from resting-state functional MRI (rs-fMRI) by measuring the similarity in connectivity profiles of subcortical voxels to cortical gray matter voxels. We performed this analysis in 24 R-TLE patients and 31 L-TLE patients (who were otherwise matched for age, gender, disease specific characteristics, and other clinical variables), and 16 controls. To measure differences in SFGs between L-TLE and R-TLE, we quantified deviations in the average functional gradient distributions, as well as their variance, across subcortical structures. RESULTS: We found an expansion, measured by increased variance, in the principal SFG of TLE relative to controls. When comparing the gradient across subcortical structures between L-TLE and R-TLE, we found that abnormalities in the ipsilateral hippocampal gradient distributions were significantly different between L-TLE and R-TLE. CONCLUSION: Our results suggest that expansion of the SFG is characteristic of TLE. Subcortical functional gradient differences exist between left and right TLE and are driven by connectivity changes in the hippocampus ipsilateral to the seizure onset zone.

Corneal gene therapy: Structural and mechanistic understanding.

Cornea, a dome-shaped and transparent front part of the eye, affords 2/3rd refraction and barrier functions. Globally, corneal diseases are the leading cause of vision impairment. Loss of corneal function including opacification involve the complex crosstalk and perturbation between a variety of cytokines, chemokines and growth factors generated by corneal keratocytes, epithelial cells, lacrimal tissues, nerves, and immune cells. Conventional small-molecule drugs can treat mild-to-moderate traumatic corneal pathology but requires frequent application and often fails to treat severe pathologies. The corneal transplant surgery is a standard of care to restore vision in patients. However, declining availability and rising demand of donor corneas are major concerns to maintain ophthalmic care. Thus, the development of efficient and safe nonsurgical methods to cure corneal disorders and restore vision in vivo is highly desired. Gene-based therapy has huge potential to cure corneal blindness. To achieve a nonimmunogenic, safe and sustained therapeutic response, the selection of a relevant genes, gene editing methods and suitable delivery vectors are vital. This article describes corneal structural and functional features, mechanistic understanding of gene therapy vectors, gene editing methods, gene delivery tools, and status of gene therapy for treating corneal disorders, diseases, and genetic dystrophies.

Mustard gas exposure instigates retinal Müller cell gliosis.

Sulfur mustard (SM) is a chemical warfare agent (CWA) that causes severe eye pain, photophobia, excessive lacrimation, corneal and ocular surface defects, and blindness. However, SM's effects on retinal cells are relatively meager. This study investigated the role of SM toxicity on Müller glial cells responsible for cellular architecture, inner blood-retinal barrier maintenance, neurotransmitter recycling, neuronal survival, and retinal homeostasis. Müller glial cells (MIO-M1) were exposed to SM analog, nitrogen mustard (NM), at varying concentrations (50-500 µM) for 3 h, 24 h, and 72 h. Müller cell gliosis was evaluated using morphological, cellular, and biochemical methods. Real-time cellular integrity and morphological evaluation were performed using the xCELLigence real-time monitoring system. Cellular viability and toxicity were measured using TUNEL and PrestoBlue assays. Müller glia hyperactivity was calculated based on glial fibrillary acidic protein (GFAP) and vimentin immunostaining. Intracellular oxidative stress was measured using DCFDA and DHE cell-based assays. Inflammatory markers and antioxidant enzyme levels were determined by quantitative real-time PCR (qRT-PCR). AO/Br and DAPI staining further evaluated DNA damage, apoptosis, necrosis, and cell death. Inflammasome-associated Caspase-1, ASC, and NLRP3 were studied to identify mechanistic insights into NM toxicity in Müller glial cells. The cellular and morphological evaluation revealed the Müller glia hyperactivity after NM exposure in a dose- and time-dependent manner. NM exposure caused significant oxidative stress and enhanced cell death at 72 h. A significant increase in antioxidant indices was observed at the lower concentrations of NM. Mechanistically, we found that NM-treated MIO-M1 cells increased caspase-1 levels that activated NLRP3 inflammasome-induced production of IL-1ß and IL-18, and elevated Gasdermin D (GSDMD) expression, a crucial component actuating pyroptosis. In conclusion, NM-induced Müller cell gliosis via increased oxidative stress results in caspase-1-dependent activation of the NLRP3 inflammasome and cell death driven primarily by pyroptosis.

Structural brain network deviations predict recovery after traumatic brain injury.

OBJECTIVE: Traumatic brain injury results in diffuse axonal injury and the ensuing maladaptive alterations in network function are associated with incomplete recovery and persistent disability. Despite the importance of axonal injury as an endophenotype in TBI, there is no biomarker that can measure the aggregate and region-specific burden of axonal injury. Normative modeling is an emerging quantitative case-control technique that can capture region-specific and aggregate deviations in brain networks at the individual patient level. Our objective was to apply normative modeling in TBI to study deviations in brain networks after primarily complicated mild TBI and study its relationship with other validated measures of injury severity, burden of post-TBI symptoms, and functional impairment. METHOD: We analyzed 70 T1-weighted and diffusion-weighted MRIs longitudinally collected from 35 individuals with primarily complicated mild TBI during the subacute and chronic post-injury periods. Each individual underwent longitudinal blood sampling to characterize blood protein biomarkers of axonal and glial injury and assessment of post-injury recovery in the subacute and chronic periods. By comparing the MRI data of individual TBI participants with 35 uninjured controls, we estimated the longitudinal change in structural brain network deviations. We compared network deviation with independent measures of acute intracranial injury estimated from head CT and blood protein biomarkers. Using elastic net regression models, we identified brain regions in which deviations present in the subacute period predict chronic post-TBI symptoms and functional status. RESULTS: Post-injury structural network deviation was significantly higher than controls in both subacute and chronic periods, associated with an acute CT lesion and subacute blood levels of glial fibrillary acid protein (r = 0.5, p = 0.008) and neurofilament light (r = 0.41, p = 0.02). Longitudinal change in network deviation associated with change in functional outcome status (r = -0.51, p = 0.003) and post-concussive symptoms (BSI: r = 0.46, p = 0.03; RPQ: r = 0.46, p = 0.02). The brain regions where the node deviation index measured in the subacute period predicted chronic TBI symptoms and functional status corresponded to areas known to be susceptible to neurotrauma. CONCLUSION: Normative modeling can capture structural network deviations, which may be useful in estimating the aggregate and region-specific burden of network changes induced by TAI. If validated in larger studies, structural network deviation scores could be useful for enrichment of clinical trials of targeted TAI-directed therapies.

Resting state functional connectivity demonstrates increased segregation in bilateral temporal lobe epilepsy.

OBJECTIVE: Temporal lobe epilepsy (TLE) is the most common type of focal epilepsy. An increasingly identified subset of patients with TLE consists of those who show bilaterally independent temporal lobe seizures. The purpose of this study was to leverage network neuroscience to better understand the interictal whole brain network of bilateral TLE (BiTLE). METHODS: In this study, using a multicenter resting state functional magnetic resonance imaging (rs-fMRI) data set, we constructed whole-brain functional networks of 19 patients with BiTLE, and compared them to those of 75 patients with unilateral TLE (UTLE). We quantified resting-state, whole-brain topological properties using metrics derived from network theory, including clustering coefficient, global efficiency, participation coefficient, and modularity. For each metric, we computed an average across all brain regions, and iterated this process across network densities. Curves of network density vs each network metric were compared between groups. Finally, we derived a combined metric, which we term the "integration-segregation axis," by combining whole-brain average clustering coefficient and global efficiency curves, and applying principal component analysis (PCA)-based dimensionality reduction. RESULTS: Compared to UTLE, BiTLE had decreased global efficiency (p = .031), and decreased whole brain average participation coefficient across a range of network densities (p = .019). Modularity maximization yielded a larger number of smaller communities in BiTLE than in UTLE (p = .020). Differences in network properties separate BiTLE and UTLE along the integration-segregation axis, with regions within the axis having a specificity of up to 0.87 for BiTLE. Along the integration-segregation axis, UTLE patients with poor surgical outcomes were distributed in the same regions as BiTLE, and network metrics confirmed similar patterns of increased segregation in both BiTLE and poor outcome UTLE. SIGNIFICANCE: Increased interictal whole-brain network segregation, as measured by rs-fMRI, is specific to BiTLE, as well as poor surgical outcome UTLE, and may assist in non-invasively identifying this patient population prior to intracranial electroencephalography or device implantation.

Novel Therapies for the Prevention of Fibrosis in Glaucoma Filtration Surgery.

Conjunctival fibrosis remains the major impediment to the success of glaucoma filtration surgery. Anti-metabolites remain the gold standard for mitigating post-surgical fibrosis, but they are associated with high complication rates and surgical failure rates. Establishing a more targeted approach to attenuate conjunctival fibrosis may revolutionize the surgical approach to glaucoma. A new strategy is needed to prevent progressive tissue remodeling and formation of a fibrotic scar, subsequently increasing surgical success and reducing the prevalence of glaucoma-related vision loss. Advancements in our understanding of molecular signaling and biomechanical cues in the conjunctival tissue architecture are broadening the horizon for new therapies and biomaterials for the mitigation of fibrosis. This review aims to highlight the strategies and current state of promising future approaches for targeting fibrosis in glaucoma filtration surgery.