Search Results (383)

Penile cancer is a rare malignancy, with approximately 2100 cases diagnosed annually in the United States. The 5-year overall survival rate varies significantly depending on the node involvement status, at 79% in node-negative disease versus 51% for patients with inguinal metastasis. Inguinal lymph nodes are involved in micrometastatic disease in up to one out of four patients. Early inguinal lymph node dissection (ILND) has been shown to provide a survival advantage, which is why many patients undergo inguinal lymph node dissection for diagnostic and therapeutic purposes. Unfortunately, ILND is associated with high morbidity rates, which have led to potential overtreatment and decreased quality of life in the penile cancer population. Several advancements have been made to mitigate these challenges, such as dynamic sentinel node dissection, modifications to the technique or surgical templates, the introduction of minimally invasive procedures, and changes to the postoperative pathway. This manuscript examines the evolution in managing the inguinal lymph nodes in penile cancer, its associated complications, and effective strategies for their prevention and management. Full article

Industrial effluents pose a significant concern because they contain a variety of metals and metalloids that have detrimental effects on the environment. Conventional techniques are widely used in effluent treatment plants (ETPs) to remove metallic pollutants; however, they are less effective, are costly, and generate secondary toxic waste. Mycosorbent would be a sustainable and economical alternative to conventional techniques, as it offers numerous advantages. In this study, we shed light on the development of mycosorbent, which could be potentially applicable in the treatment of industrial effluent. In a competitive (i.e., multimetal system) optimisation study, mycosorbent AD2 exhibited a maximum biosorption capacity of 3.7 to 6.20 mg/g at pH 6.0, with an initial metal ion concentration of 25 mg/L, a contact time of 2 h, at 50 ± 2 °C, and a pH_PZC of 5.3. The metal-removal capacity increased up to 1.23-fold after optimisation. The thermodynamic parameters confirmed that the AD2 mycosorbent facilitated an endothermic, feasible, and spontaneous biosorption process. The FT-IR and SEM characterisation analysis confirmed the adsorption of metals on the surface of the mycosorbent from the aqueous system. This study demonstrated that mycosorbent could be an effective tool for combating metallic pollutants in various industrial effluents. Full article

The extensive environmental pollution caused by petroleum-based plastics highlights the urgent need for sustainable, economically viable alternatives. The practical challenge of enhancing polyhydroxybutyrate (PHB) production with cost-effective agro-industrial residues—rice-bran and corn-flour hydrolysates—has been demonstrated. Bacillus bingmayongensis GS2 was isolated from soil samples collected at the Pirana municipal landfill in Ahmedabad, India, and identified through VITEK-2 biochemical profiling and 16S rDNA sequencing (GenBank accession OQ749793). Initial screening for PHB accumulation was performed using Sudan Black B staining. Optimization via a sequential one-variable-at-a-time (OVAT) approach identified optimal cultivation conditions (36 h inoculum age, 37 °C, pH 7.0, 100 rpm agitation), resulting in a PHB yield of 2.77 g L⁻¹ (66% DCW). Further refinement using a central composite response surface methodology (RSM)—varying rice-bran hydrolysate, corn-flour hydrolysate, peptone concentration, and initial pH—significantly improved the PHB yield to 3.18 g L⁻¹(74% DCW), representing more than a threefold enhancement over unoptimized conditions. Structural validation using Fourier Transform Infrared spectroscopy (FTIR) and Proton Nuclear Magnetic Resonance spectroscopy (¹H-NMR) confirmed the molecular integrity of the produced PHB. That Bacillus bingmayongensis GS2 effectively converts low-cost agro-industrial residues into high-value bioplastics has been demonstrated, indicating substantial industrial potential. Future work will focus on bioreactor scale-up, targeted metabolic-engineering strategies, and comprehensive sustainability evaluations, including life-cycle assessment. Full article

In 2023, the VAS international working group on Buerger’s Disease (BD) recommended two diagnostic criteria based on a prior Delphi study: “definitive” and “suspected”. The “definitive” criteria are history of smoking, typical angiography, and typical histopathological features. All three features are mandatory to confirm a “definitive” diagnosis of BD. The conundrum is—what features should be considered typical of BD angiography? According to this review, segmental occlusion of infrapopliteal arteries, corkscrew collaterals that appear to continue the occluded arterial segment (Martorell’s sign) or bypass the segmental occlusion, absence of atherosclerotic plaque or aneurysm could differentiate BD from ASO. Hence, for “typical” BD angiography, these manifestations should certainly be considered. However, data for differentiating angiography patterns of BD from the small- and medium-sized vasculitis including Behcet’s disease, scleroderma, hepatitis associated vasculitis, and anti-phospholipid syndrome are limited. Further studies for investigating the angiography pattern in BD patients in early and late presentation of BD, particularly in the patients with long-term follow up, are highly recommended. Full article

Glaucoma is a leading cause of irreversible blindness globally, with early diagnosis being crucial to preventing vision loss. Traditional diagnostic methods, including fundus photography, OCT imaging, and perimetry, often fall short in sensitivity and fail to integrate structural and functional data. This study proposes a novel multi-modal diagnostic framework that combines convolutional neural networks (CNNs), vision transformers (ViTs), and quantum-enhanced layers to improve glaucoma detection accuracy and efficiency. The framework integrates fundus images, OCT scans, and clinical biomarkers, leveraging their complementary strengths through a weighted fusion mechanism. Datasets, including the GRAPE and other public and clinical sources, were used, ensuring diverse demographic representation and supporting generalizability. The model was trained and validated using cross-entropy loss, L2 regularization, and adaptive learning strategies, achieving an accuracy of 96%, sensitivity of 94%, and an AUC of 0.97—outperforming CNN-only and ViT-only approaches. Additionally, the quantum-enhanced architecture reduced computational complexity from O(n²) to O (log n), enabling real-time deployment with a 40% reduction in FLOPs. The proposed system addresses key limitations of previous methods in terms of computational cost, data integration, and interpretability. The proposed system addresses key limitations of previous methods in terms of computational cost, data integration, and interpretability. This framework offers a scalable and clinically viable tool for early glaucoma detection, supporting personalized care and improving diagnostic workflows in ophthalmology. Full article

Coronary artery disease (CAD) remains a leading cause of global morbidity and mortality despite advances in medical and interventional therapies. Mesenchymal stem cell (MSC) therapy has emerged as a promising regenerative approach for patients with refractory or non-revascularizable CAD. MSCs exhibit unique immunomodulatory, pro-angiogenic, and anti-fibrotic properties, primarily through paracrine mechanisms involving the secretion of cytokines, growth factors, and exosomal microRNAs. Clinical and preclinical studies have demonstrated improvements in myocardial perfusion, left ventricular ejection fraction (LVEF), and functional capacity following MSC-based interventions, particularly in patients with low baseline LVEF and heightened inflammation. Various MSC sources—including bone marrow, adipose tissue, and umbilical cord—offer distinct advantages, while delivery strategies such as intracoronary, intramyocardial, intravenous, and subcutaneous administration impact cell retention and efficacy. Advances in genetic modification, hypoxic preconditioning, and exosome-based therapies aim to enhance MSC survival and therapeutic potency. However, challenges persist regarding cell engraftment, cryopreservation effects, and inter-patient variability. Moving toward precision cell therapy, future approaches may involve stratifying patients by inflammatory status, ischemic burden, and comorbidities to optimize treatment outcomes. MSCs may not yet replace conventional therapies but are increasingly positioned to complement them within a personalized, regenerative framework for CAD management. Full article

A classical molecular dynamics simulation of cation diffusion in isolated crystals (U_xPu_yTh_1−x−y)O₂ bounded by a free surface was performed. It was shown that in the bulk of the same model crystallite, the diffusion coefficients of cations of all types were practically identical. At the same time, the cation diffusion coefficients changed with the melting temperature of nanocrystals, which increased with increasing thorium content. At a given temperature, the diffusion coefficients were the higher, the lower were the melting points of the (U_xPu_yTh_1−x−y)O₂ crystallites. The temperature dependences of the diffusion coefficients in crystallites of different compositions converged when using coordinates normalized to the melting points. Full article

Artificial intelligence (AI) has rapidly emerged as a transformative force in musculoskeletal imaging and interventional radiology. This article explores how AI-based methods—including machine learning (ML) and deep learning (DL)—streamline diagnostic processes, guide interventions, and improve patient outcomes. Key applications discussed include ultrasound-guided procedures for joints, nerves, and tumor-targeted interventions, along with CT-guided biopsies and ablations, and fluoroscopy-guided facet joint and nerve block injections. AI-powered segmentation algorithms, real-time feedback systems, and dose-optimization protocols collectively enable greater precision, operator consistency, and patient safety. In rehabilitation, AI-driven wearables and predictive models facilitate personalized exercise programs that can accelerate recovery and enhance long-term function. While challenges persist—such as data standardization, regulatory hurdles, and clinical adoption—ongoing interdisciplinary collaboration, federated learning models, and the integration of genomic and environmental data hold promise for expanding AI’s capabilities. As personalized medicine continues to advance, AI is poised to refine risk stratification, reduce radiation exposure, and support minimally invasive, patient-specific interventions, ultimately reshaping musculoskeletal care from early detection and diagnosis to individualized treatment and rehabilitation. Full article

Background: Desmocollin3, a transmembrane protein, is expressed in the basal/suprabasal layer of normal stratified epithelium. DSC3 gene expression is described in muscle-invasive bladder cancer (MIBC). DSC3-protein-expressing recurrent non-muscle-invasive bladder cancer (NMIBC) had a durable response to CADI-03, a DSC3-specific active immunotherapy. Methods: We evaluated DSC3 protein expression and its correlation with tumor-infiltrating immune cells in bladder cancer. DSC3 gene expression and its correlation with 208 immune encoding genes, treatment outcome, and survival were evaluated using the “ARRAYEXPRESS” and “TCGA” datasets. Immune genes were grouped as tumor-controlling immune genes (TCIGs) and tumor-promoting immune genes (TPIGs) as per their functions. Results & conclusions: NMIBC had higher DSC3 expression compared to MIBC. More immune genes were correlated with DSC3 in MIBC (21) compared to NMIBC (11). Amongst the TCIGs, six in NMIBC and one in MIBC had a negative correlation while two in NMIBC and nine in MIBC had a positive correlation with DSC3. Amongst the TPIGs, nine in NMIBC and five in MIBC had a negative correlation. Seven TPIGs had a positive correlation with DSC3 in MIBC and none in NMIBC. Of the T cell exhaustion markers, none were correlated with DSC3 in MIBC. Among NMIBC, CTLA4 and TIGIT were the only markers of exhaustion that demonstrated a negative correlation with DSC3. DSC3 expression was also higher in p53 mutant compared to wild p53, non-papillary MIBC compared to papillary MIBC, and in basal, squamous molecular subtype compared to luminal MIBC. MIBC with lower DSC3 expression had better outcomes (response, survival) compared to those with higher DSC3 expression. Full article

Passenger flow forecasting is crucial for optimizing urban transit operations, especially in developing countries such as India, where congestion, infrastructure constraints, and diverse commuter behaviors pose significant challenges. Despite its importance, limited research explored forecasting models for Indian urban transit systems, particularly incorporating the effects of holidays and disruptions caused by the COVID-19 pandemic. To address this gap, we propose TBATS Boosting, a novel hybrid forecasting model that integrates the statistical strengths of trigonometric, Box–Cox, ARMA, trend, and seasonal (TBATS) with the predictive power of LightGBM. The model is trained on a five-year real-world dataset from e-ticketing machines (ETM) in Thane Municipal Transport (TMT), incorporating holiday and pandemic-related variations. While Route 12 serves as a primary evaluation route, different station pairs are analyzed to validate their scalability across varying passenger demand levels. To comprehensively evaluate the proposed framework, a rigorous performance assessment was conducted using MAE, RMSE, MAPE, and WMAPE across station pairs characterized by heterogeneous passenger flow patterns. Empirical results demonstrate that the TBATS Boosting approach consistently outperforms benchmark models, including standalone SARIMA, TBATS, XGBoost, and LightGBM. By effectively capturing complex temporal dependencies, multiple seasonalities, and nonlinear relationships, the proposed framework significantly enhances forecasting accuracy. These advancements provide transit authorities with a robust tool for optimizing resource allocation, improving service reliability, and enabling data-driven decision making across varied and dynamic urban transit environments. Full article

Background: Dopaminergic therapy (DT) is the gold standard pharmacological treatment for Parkinson’s disease (PD). Currently, understanding the neuromodulation effect in the brain of PD after DT is important for doctors to optimize doses and identify the adverse effects of medication. The objective of this study is to investigate the brain connectivity alteration with and without DT in PD using resting-state EEG. Methods: Graph theory (GT) is an efficient technique for analyzing brain connectivity alteration in healthy and patient groups. We applied GT analyses on three groups, namely healthy control (HC), Parkinson with medication OFF (PD-OFF), and Parkinson with medication ON (PD-ON). Results: Using the clustering coefficient (CC), participation coefficient (PC), and small-worldness (SW) properties of GT, we showed that PD-ON patients’ brain connectivity normalized towards healthy group brain connectivity due to DT. This normalization effect appeared in the brain connectivity of all EEG frequency bands, such as theta, alpha, beta-1, beta-2, and gamma except the delta band. We also analyzed region-wise brain connectivity between 10 regions of interest (ROIs) (right and left frontal, right and left temporal, right and left parietal, right and left occipital, upper and lower midline regions) at the scalp level and compared across conditions. During PD-ON, we observed a significant decrease in alpha band connectivity between right frontal and left parietal (p-value 0.0432) and right frontal and left occipital (p-value 0.008) as well as right frontal and right temporal (p-value 0.041). Conclusion: These findings offer new insights into how dopaminergic therapy modulates brain connectivity across frequency bands and highlight the continuous elevation of both the segregation and small-worldness of the delta band even after medication as a potential biomarker for adverse effects due to medication. Additionally, reduced frontal alpha band connectivity is associated with cognitive impairment and levodopa-induced dyskinesia, highlighting its potential role in Parkinson’s disease progression. This study underscores the need for personalized treatments that address both motor and non-motor symptoms in PD patients. Full article

The aim of this study was to enhance and maintain bioelectricity generation from distillery spent wash using a microbial fuel cell (MFC). Electrode materials play a critical role in the generation of bioelectricity in MFCs. Utilizing double oxidant-treated carbon felts in MFC applications increased current density to 749.56 mA/m² and increased peak power density to 125.23 mW/m². Electrochemical impedance spectroscopy (EIS) analysis further verified the improved electrocatalytic activity observed in the oxidized carbon felt, consistent with the findings from cyclic voltammetry (CV) and polarization curves, thereby confirming the enhanced performance of the oxidized carbon felt electrode. Overall, the study highlights the significance of electrode morphology and surface modifications in influencing microbial adhesion, electron transport, and the overall efficiency of fuel cells using distillery spent wash as a substrate. Full article

This study explores a unique Finsler space with a Rander’s-type exponential metric, $\mathcal{G}(\alpha ,\beta )=(\alpha +\beta )e^{{\displaystyle \frac{\beta }{(\alpha +\beta )}}}$, where $\alpha$ is a Riemannian metric and $\beta$ is a 1-form. We analyze the conditions under which its hypersurfaces behave like hyperplanes of the first, second, and third kinds. Additionally, we examine the reducibility of the Cartan tensor $\mathcal{C}$ for these hypersurfaces, providing insights into their geometric structure. Full article

The hydrological dynamics of Raipur are profoundly influenced by the intricate interplay between surface and groundwater systems, driven by changes in land use, climatic conditions, and human activities such as agriculture and industry. This research investigated the interdependencies between the Kharun River and groundwater systems, essential for understanding water security in the face of escalating demands and rapid urbanization. Through meticulous monitoring and analysis of approximately 70 bore wells, nine river sampling sites, and 13 groundwater samples from dug wells, alongside rigorous adherence to established sampling protocols, this study delved into the seasonal variations and influences on water quantity and quality. Statistical methodologies, stable isotope analyses, and Gibbs diagrams were employed to unravel the complexities governing water resource dynamics and interactions. Notably, correlation analysis revealed significant associations between various water quality parameters, indicating anthropogenic influences on groundwater chemistry. Cluster analysis aided in understanding hydro-chemical processes, while stable isotope examinations further elucidated the sources and interactions of groundwater and surface water. Results indicate the urgent need for sustainable water management strategies tailored to the region’s evolving socio-environmental landscape, considering escalating urbanization and agricultural activities. This integrated approach, combining analytical methods and statistical techniques, offers a holistic understanding of water resource dynamics essential for effective governance and sustainable development. Full article

The cosmetic market is constantly evolving and ever-changing, particularly with the introduction and incorporation of nanotechnology-based processes into cosmetics for the production of unique formulations with both aesthetic and therapeutic benefits. There is no doubt that nanotechnology is an emerging technology for cosmetic formulations. Among the numerous cosmetic items, incorporating nanomaterials has provided a greater scope and is commonly utilized in facial masks, hair products, antiaging creams, sunscreen creams, and lipsticks. In cosmetics, nanosized materials, including lipid crystals, liposomes, lipid NPs, inorganic nanocarriers, polymer nanocarriers, solid lipid nanocarriers (SLNs), nanostructured lipid carriers (NLCs), nanofibers, nanocrystals, and nanoemulsions, have become common ingredients. The implementation of nanotechnology in the formulation of face masks will improve its efficacy. Nanotechnology enhances the penetration of active ingredients used in the preparation of face masks, such as peel-off masks and sheet masks, which results in better effects. The emphasis of this review is mainly on the formulation of cosmetic face masks, in which the impact of nanotechnology has been demonstrated to improve the product performance on the skin. Full article