Attitude towards seeking professional help for mental health among medical students In Karachi, Pakistan.

Aim: In Pakistan, seeking help for mental health is considered a social stigma and a large number of medical students are suffering from mental health. This study aimed to investigate the attitude toward seeking professional care for mental health issues among medical students. Methodology: A cross-sectional study was conducted with a total of 316 students selected through multistage stratified cluster sampling. With each academic year 500 students were enrolled. Linear regression analysis was used to find the association of outcome and independent variables. Results: Around 56% of students had a negative attitude toward seeking professional help. Common predictors associated with a negative attitude were age (p < 0.001), academic year (p < 0.001) and with self-harm behavior (p < 0.001). Conclusion: University students generally had moderate intentions to seek counseling regarding mental health.

Mental health disorders are considered common in society. In particular, medical students commonly suffer from depression and anxiety. This study found that there are different factors that contribute to a negative attitude towards seeking mental health counseling. For example, a younger age and a history of self-harm contributed the most to a negative attitude towards mental health help, and not sharing any health problems with parents and doctors. There is a need to increase awareness among students regarding mental disorders and seeking help to overcome problems.

Efficacy of Hydrocortisone, Povidone-Iodine, and Normal Saline as an Irrigating Solution During Surgical Removal of Impacted Mandibular Third Molars: A Randomized Controlled Trial.

Background The surgical removal of mandibular third molars is one of the most common procedures in dentistry. Researchers have extensively studied the treatment of postoperative sequelae such as pain, edema, trismus, and alveolar osteitis throughout the past six decades. Many approaches have been used to address clinical difficulties after third molar surgery, including various flap designs and irrigating solutions. The aim of this study was to compare the effects of three irrigating solutions, hydrocortisone, povidone-iodine, and normal saline, on pain, trismus, and edema following surgical removal of the impacted mandibular third molar. Methodology The study involved 105 participants who required surgical extraction of mandibular third molars. The patients' ages ranged from 18 to 40 years, and they fulfilled the inclusion criteria. Using a simple random sampling technique, they were divided into three groups (group 1: hydrocortisone, group 2: povidone-iodine, group 3: normal saline). The parameters evaluated were edema, pain, and trismus on the second and seventh postoperative days. All data were input into Microsoft Excel (Microsoft® Corp., Redmond, USA) worksheets and analyzed using Stata 17.0 (StataCorp LLC, College Station, USA). The visual analog scale (VAS) score was used to measure postoperative pain, and postoperative swelling was measured using linear measurements from four fixed anatomical points and compared to preoperative values. To assess trismus, the inter-incisal distance was measured in millimeters with a caliper. A p-value of <0.01 was considered statistically significant. Results The mean VAS score for pain in group 1 was lower than the other two groups. The effect of group 1 was significant on the second postoperative day but insignificant on the seventh postoperative day for swelling. The effect of all three groups on trismus was significant on the second and seventh days. Conclusions Hydrocortisone as an irrigating solution showed promising results in managing postoperative swelling in the first 48 hours, but its effect gradually declined by the seventh postoperative day. Additionally, it was effective in controlling postoperative pain and trismus. This suggests that utilizing hydrocortisone as an irrigating solution, compared to povidone-iodine, has been proven to be a significantly effective option in reducing postoperative pain, edema, and trismus resulting from the surgical removal of impacted teeth.

Integrating Transcriptomic and Structural Insights: Revealing Drug Repurposing Opportunities for Sporadic ALS.

Amyotrophic lateral sclerosis (ALS) is a progressive and devastating neurodegenerative disorder characterized by the loss of upper and lower motor neurons, resulting in debilitating muscle weakness and atrophy. Currently, there are no effective treatments available for ALS, posing significant challenges in managing the disease that affects approximately two individuals per 100,000 people annually. To address the urgent need for effective ALS treatments, we conducted a drug repurposing study using a combination of bioinformatics tools and molecular docking techniques. We analyzed sporadic ALS-related genes from the GEO database and identified key signaling pathways involved in sporadic ALS pathogenesis through pathway analysis using DAVID. Subsequently, we utilized the Clue Connectivity Map to identify potential drug candidates and performed molecular docking using AutoDock Vina to evaluate the binding affinity of short-listed drugs to key sporadic ALS-related genes. Our study identified Cefaclor, Diphenidol, Flubendazole, Fluticasone, Lestaurtinib, Nadolol, Phenamil, Temozolomide, and Tolterodine as potential drug candidates for repurposing in sporadic ALS treatment. Notably, Lestaurtinib demonstrated high binding affinity toward multiple proteins, suggesting its potential as a broad-spectrum therapeutic agent for sporadic ALS. Additionally, docking analysis revealed NOS3 as the gene that interacts with all the short-listed drugs, suggesting its possible involvement in the mechanisms underlying the therapeutic potential of these drugs in sporadic ALS. Overall, our study provides a systematic framework for identifying potential drug candidates for sporadic ALS therapy and highlights the potential of drug repurposing as a promising strategy for discovering new therapies for neurodegenerative diseases.

Network-based drug repurposing identifies small molecule drugs as immune checkpoint inhibitors for endometrial cancer.

Endometrial cancer (EC) is the 6th most common cancer in women around the world. Alone in the United States (US), 66,200 new cases and 13,030 deaths are expected to occur in 2023 which needs the rapid development of potential therapies against EC. Here, a network-based drug-repurposing strategy is developed which led to the identification of 16 FDA-approved drugs potentially repurposable for EC as potential immune checkpoint inhibitors (ICIs). A network of EC-associated immune checkpoint proteins (ICPs)-induced protein interactions (P-ICP) was constructed. As a result of network analysis of P-ICP, top key target genes closely interacting with ICPs were shortlisted followed by network proximity analysis in drug-target interaction (DTI) network and pathway cross-examination which identified 115 distinct pathways of approved drugs as potential immune checkpoint inhibitors. The presented approach predicted 16 drugs to target EC-associated ICPs-induced pathways, three of which have already been used for EC and six of them possess immunomodulatory properties providing evidence of the validity of the strategy. Classification of the predicted pathways indicated that 15 drugs can be divided into two distinct pathway groups, containing 17 immune pathways and 98 metabolic pathways. In addition, drug-drug correlation analysis provided insight into finding useful drug combinations. This fair and verified analysis creates new opportunities for the quick repurposing of FDA-approved medications in clinical trials.

Potential of Capparis decidua plant and eggshell composite adsorbent for effective removal of anionic dyes from aqueous medium.

The presence of hazardous dyes in wastewater poses significant threats to both ecosystems and the natural environment. Conventional methods for treating dye-contaminated water have several limitations, including high costs and complex operational processes. This study investigated a sustainable bio-sorbent composite derived from the Capparis decidua plant and eggshells, and evaluated its effectiveness in removing anionic dyes namely tartrazine (E-102), methyl orange (MO), and their mixed system. The research examines the influence of initial concentration, contact time, pH, adsorbent dosage, and temperature on the adsorption properties of anionic dyes. Optimal removal of tartrazine (E-102), methyl orange (MO), and their mixed system was achieved at a pH of 3. The equilibrium was achieved at 80 min for MO and mixed systems, and 100 min for E-102. The adsorption process showed an exothermic nature, indicating reduced capacity with increasing temperature, consistent with heat release during adsorption. Positive entropy values indicated increased disorder at the solid-liquid interface, attributed to molecular rearrangements and interactions between dye molecules and the adsorbent. Isotherm analysis using Langmuir, Freundlich, Temkin, and Redlich-Peterson models revealed that the Langmuir model best fit the experimental data. The maximum adsorption capacities of 50.97 mg/g, 52.24 mg/g, and 56.23 mg/g were achieved for E-102, MO, and the mixed system under optimized conditions, respectively. The pseudo-second-order kinetic model demonstrated the best fit, indicating that adsorption occurs through physical and chemical interactions such as electrostatic attraction, pore filling, and hydrogen bonding. Hence, the developed bio-sorbent could be a sustainable and cost-effective solution for the treatment of anionic dyes from industrial effluents.

Synergism of Holmium Orthovanadate/Phosphorus-Doped Carbon Nitride Nanocomposite: Nonenzymatic Electrochemical Detection of Hydrogen Peroxide.

Developing efficient and robust electrode materials for electrochemical sensors is critical for real-time analysis. In this paper, a hierarchical holmium vanadate/phosphorus-doped graphitic carbon nitride (HoVO4/P-CN) nanocomposite is synthesized and used as an electrode material for electrochemical detection of hydrogen peroxide (H2O2). The HoVO4/P-CN nanocomposite exhibits superior electrocatalytic activity at a peak potential of -0.412 V toward H2O2 reduction in alkaline electrolytes while compared with other reported electrocatalysts. The HoVO4/P-CN electrochemical platform operated under the optimized conditions shows excellent analytical performance for H2O2 detection with a linear concentration range of 0.009-77.4 µM, a high sensitivity of 0.72 µA µM-1 cm-2, and a low detection limit of 3.0 nΜ. Furthermore, the HoVO4/P-CN-modified electrode exhibits high selectivity, remarkable stability, good repeatability, and satisfactory reproducibility in detecting H2O2. Its superior performance can be attributed to a large specific surface area, high conductivity, more active surface sites, unique structure, and synergistic action of HoVO4 and P-CN to benefit enhanced electrochemical activity. The proposed HoVO4/P-CN electrochemical platform is effectively applied to ascertain the quantity of H2O2 in food and biological samples. This work outlines a promising and effectual strategy for the sensitive electrochemical detection of H2O2 in real-world samples.

Unveiling the potential of PANI@MnO2@rGO ternary nanocomposite in energy storage and gas sensing.

The development of advanced materials for energy storage and gas sensing applications has gained significant attention in recent years. In this study, we synthesized and characterized PANI@MnO2@rGO ternary nanocomposites (NCs) to explore their potential in supercapacitors and gas sensing devices. The ternary NCs were synthesized through a multi-step process involving the hydrothermal synthesis of MnO2 nanoparticles, preparation of PANI@rGO composites and the assembly to the ternary PANI@MnO2@rGO ternary NCs. The structural, morphological, and compositional characteristics of the materials were thoroughly analyzed using techniques such as XRD, FESEM, TEM, FTIR, and Raman spectroscopy. In the realm of gas sensing, the ternary NCs exhibited excellent performance as NH3 gas sensors. The optimized operating temperature of 100 °C yielded a peak response of 15.56 towards 50 ppm NH3. The nanocomposites demonstrated fast response and recovery times of 6 s and 10 s, respectively, and displayed remarkable selectivity for NH3 gas over other tested gases. For supercapacitor applications, the electrochemical performance of the ternary NCs was evaluated using cyclic voltammetry and galvanostatic charge-discharge techniques. The composites exhibited pseudocapacitive behavior, with the capacitance reaching up to 185 F/g at 1 A/g and excellent capacitance retention of approximately 88.54% over 4000 charge-discharge cycles. The unique combination of rGO, PANI, and MnO2 nanoparticles in these ternary NCs offer synergistic advantages, showcasing their potential to address challenges in energy storage and gas sensing technologies.

Post-operative Scar Comparison With Supraorbital Eyebrow and Upper Blepharoplasty Approach in the Management of Zygomaticomaxillary Complex Fractures.

Study Design: A prospective randomized comparative study was conducted to evaluate the postsurgical scar with Supraorbital Eyebrow (SE) Approach and Upper Blepharoplasty (UB) Approach used for open reduction and internal fixation (ORIF) of zygomaticomaxillary complex (ZMC) fractures. Objective: To evaluate and compare the post-operative scar using Vancouver Scar Scale (VSS) following ORIF of ZMC fractures with SE and UB approaches. Methods: In this study, 88 patients with ZMC fractures requiring ORIF and meeting the inclusion criteria were recruited between 2019 and 2020. Patients were randomly divided into SE and UB group, 44 patients in each. Clinical and radiological assessment was done preoperatively and post-operative scar evaluation was carried out at different intervals over a period of 6 months using VSS. A blinded observer rated the scar. Results: The results showed that after 6 months of surgery, all the 44 (100%) patients in UB group had a mild scar (VSS score 1-5), while in the SE group 34 (77.3%) patients had a mild scar (VSS score 1-5) and 10 (22.7%) had a moderate scar (VSS score 6-10). The difference between the 2 groups was statistically significant (P-value = .001). Conclusions: The UB approach has been established to be superior to SE approach in terms of post-operative scar as the results were statistically significant. This study can be used to advocate more frequent use of UB approach as compared to the previously popular SE approach for the management of ZMC fractures.

Network-based drug repurposing for HPV-associated cervical cancer.

In women, cervical cancer (CC) is the fourth most common cancer around the world with average cases of 604,000 and 342,000 deaths per year. Approximately 50% of high-grade CC are attributed to human papillomavirus (HPV) types 16 and 18. Chances of CC in HPV-positive patients are 6 times more than HPV-negative patients which demands timely and effective treatment. Repurposing of drugs is considered a viable approach to drug discovery which makes use of existing drugs, thus potentially reducing the time and costs associated with de-novo drug discovery. In this study, we present an integrative drug repurposing framework based on a systems biology-enabled network medicine platform. First, we built an HPV-induced CC protein interaction network named HPV2C following the CC signatures defined by the omics dataset, obtained from GEO database. Second, the drug target interaction (DTI) data obtained from DrugBank, and related databases was used to model the DTI network followed by drug target network proximity analysis of HPV-host associated key targets and DTIs in the human protein interactome. This analysis identified 142 potential anti-HPV repurposable drugs to target HPV induced CC pathways. Third, as per the literature survey 51 of the predicted drugs are already used for CC and 33 of the remaining drugs have anti-viral activity. Gene set enrichment analysis of potential drugs in drug-gene signatures and in HPV-induced CC-specific transcriptomic data in human cell lines additionally validated the predictions. Finally, 13 drug combinations were found using a network based on overlapping exposure. To summarize, the study provides effective network-based technique to quickly identify suitable repurposable drugs and drug combinations that target HPV-associated CC.

Influence of Fe Doping on the Electrochemical Performance of a ZnO-Nanostructure-Based Electrode for Supercapacitors.

ZnO is a potential candidate for providing an economic and environmentally friendly substitute for energy storage materials. Therefore, in this work, Fe-doped ZnO nanostructures prepared using the microwave irradiation procedure were investigated for structural, morphological, magnetic, electronic structural, specific surface area and electrochemical properties to be used as electrodes for supercapacitors. The X-ray diffraction, high-resolution transmission electron microscopy images, and selective-area electron diffraction pattern indicated that the nanocrystalline structures of Fe-doped ZnO were found to possess a hexagonal wurtzite structure. The effect of Fe doping in the ZnO matrix was observed on the lattice parameters, which were found to increase with the dopant concentration. Rods and a nanosheet-like morphology were observed via FESEM images. The ferromagnetic nature of samples is associated with the presence of bound magnetic polarons. The enhancement of saturation magnetization was observed due to Fe doping up to 3% in correspondence with the increase in the number of bound magnetic polarons with an Fe content of up to 3%. This behavior is observed as a result of the change in the oxidation state from +2 to +3, which was a consequence of Fe doping ranging from 3% to 5%. The electrode performance of Fe-doped ZnO nanostructures was studied using electrochemical measurements. The cyclic voltammetry (CV) results inferred that the specific capacitance increased with Fe doping and displayed a high specific capacitance of 286 F·g-1 at 10 mV/s for 3% Fe-doped ZnO nanostructures and decreased beyond that. Furthermore, the stability of the Zn0.97Fe0.03O electrode, which was examined by performing 2000 cycles, showed excellent cyclic stability (85.0% of value retained up to 2000 cycles) with the highest specific capacitance of 276.4 F·g-1, signifying its appropriateness as an electrode for energy storage applications.

Artificial intelligence-assisted repurposing of lubiprostone alleviates tubulointerstitial fibrosis.

Tubulointerstitial fibrosis (TIF) is the most prominent cause which leads to chronic kidney disease (CKD) and end-stage renal failure. Despite extensive research, there have been many clinical trial failures, and there is currently no effective treatment to cure renal fibrosis. This demonstrates the necessity of more effective therapies and better preclinical models to screen potential drugs for TIF. In this study, we investigated the antifibrotic effect of the machine learning-based repurposed drug, lubiprostone, validated through an advanced proximal tubule on a chip system and in vivo UUO mice model. Lubiprostone significantly downregulated TIF biomarkers including connective tissue growth factor (CTGF), extracellular matrix deposition (Fibronectin and collagen), transforming growth factor (TGF-ß) downstream signaling markers especially, Smad-2/3, matrix metalloproteinase (MMP2/9), plasminogen activator inhibitor-1 (PAI-1), EMT and JAK/STAT-3 pathway expression in the proximal tubule on a chip model and UUO model compared to the conventional 2D culture. These findings suggest that the proximal tubule on a chip model is a more physiologically relevant model for studying and identifying potential biomarkers for fibrosis compared to conventional in vitro 2D culture and alternative of an animal model. In conclusion, the high throughput Proximal tubule-on-chip system shows improved in vivo-like function and indicates the potential utility for renal fibrosis drug screening. Additionally, repurposed Lubiprostone shows an effective potency to treat TIF via inhibiting 3 major profibrotic signaling pathways such as TGFß/Smad, JAK/STAT, and epithelial-mesenchymal transition (EMT), and restores kidney function.

Improvement of Supercapacitor Performance of In Situ Doped Laser-Induced Multilayer Graphene via NiO.

Herein, we have reported a novel strategy for improving the electrochemical performance of laser-induced graphene (LIG) supercapacitors (SCs). The LIG was prepared using a CO2 laser system. The polyimide polymer was the source material for the fabrication of the LIG. The doping process was performed in situ using the CO2 laser, which works as a rapid thermal treatment to combine graphene and NiO particles. NiO was used to improve the capacitance of graphene by combining an electric double-layer capacitor (EDLC) with the pseudo-capacitance effect. The high-resolution transmission electron microscopy, energy-dispersive X-ray spectroscopy, and Raman spectroscopy showed that the structure of the LIG is multilayered and waved. The HRTEM image proves the distribution of NiO fine particles with sizes of 5-10 nm into the graphene layers. The electrochemical performance of the as-prepared LIG was tested. The effect of the combination of the two materials (oxide and carbon) was investigated at different concentrations. The LIG showed a specific capacitance of 69 Fg-1, which increased up to 174 Fg-1 for the NiO-doped LIG. The stability investigations showed that the electrodes were very stable for more than 1000 cycles. This current study establishes an innovative method to improve the electrochemical properties of LIG.

Simultaneous adsorption of methylene blue and amoxicillin by starch-impregnated MgAl layered double hydroxide: Parametric optimization, isothermal studies and thermo-kinetic analysis.

Textile and pharmaceutical effluents contain significant amounts of dyes and antibiotics, which pose a serious threat to the ecosystem when discharged directly. Therefore, they should be treated by facile treatment techniques using low-cost materials. Layered double hydroxide (LDH) and its hybrids have emerged as robust and economic adsorbents for water treatment. Herein, magnesium/aluminum LDH and its starch-based composite were synthesized by a co-precipitation technique. The physicochemical features of the developed adsorbents were thoroughly characterized using various analytical tools. The developed materials were tested for the eradication of methylene blue (MB) and amoxicillin (AMX) in batch mode adsorption by varying operating conditions. Adsorption performance depends on the solution's pH. Under optimum adsorption conditions of pH 11, adsorbent dosage of 50 mg/L, and treatment time of 120 min, starch-impregnated MgAl-LDH exhibited maximum MB and AMX adsorption capacities of 114.94 and 48.08 mg/g, respectively. The adsorption mechanism states that hydrogen bonds and weak van der Waals forces are responsible for the removal of pollutants by the developed materials. Moreover, equilibrium and kinetic studies revealed that the removal of dye and antibiotic followed the Freundlich and Langmuir models with the pseudo-second-order reaction kinetics, respectively. The spent adsorbents were regenerated using 0.1 M HCl (for MB) and methanol (for AMX) eluent, and reusability studies ensured that the developed adsorbents retained their performance for up to four consecutive adsorption/desorption cycles. MgAl-LDH and its starch-based hybrid could thus be used to effectively remove organic contaminants from wastewater streams on a commercial scale.

Combining second harmonic generation and multiphoton excited photo-luminescence to investigate TiO2 nanoparticle powders.

Disentangling Second Harmonic Generation (SHG) and Multiphoton Excited Photoluminescence (MEPL) signals in microscopy experiments is not an easy task. Two methods have been so far proposed based either on a time domain or a spectral domain analysis of the collected signals. In this report, a new method based on polarization discrimination is proposed to separate these SHG and MEPL contributions. In order to demonstrate this operation, intensity depth profiles are recorded for an anatase titanium dioxide powder consisting of 22 nm diameter nanoparticles using ultrafast femtosecond laser excitation. Polarization analysis of these intensity depth profiles is therefore performed and demonstrates a polarization angle shift for the SHG intensity contribution as compared to the MEPL one, allowing for the discrimination of the two SHG and MEPL contributions. The fundamental beam is set at two different wavelengths in order to provide a SHG photon energy above and below the anatase TiO2 band-gap of 3.2 eV, leading to a change in the relative intensity weight and a spectral shift between the SHG and MEPL contributions. This operation further demonstrates the potential of the method when the spectral domain disentangling cannot be performed. SHG profiles are by far narrower than those of MEPL. This study where both SHG and MEPL contributions are observed offers perspectives in photonics of powder materials as the different origin and properties of the two processes can be separated.

Investigations of Structural, Magnetic, and Electrochemical Properties of NiFe2O4 Nanoparticles as Electrode Materials for Supercapacitor Applications.

Magnetic nanoparticles of NiFe2O4 were successfully prepared by utilizing the sol-gel techniques. The prepared samples were investigated through various techniques such as X-ray diffraction (XRD), transmission electron microscopy (TEM), dielectric spectroscopy, DC magnetization and electrochemical measurements. XRD data analysed using Rietveld refinement procedure inferred that NiFe2O4 nanoparticles displayed a single-phase nature with face-centred cubic crystallinity with space group Fd-3m. Average crystallite size estimated using the XRD patterns was observed to be ~10 nm. The ring pattern observed in the selected area electron diffraction pattern (SAED) also confirmed the single-phase formation in NiFe2O4 nanoparticles. TEM micrographs confirmed the uniformly distributed nanoparticles with spherical shape and an average particle size of 9.7 nm. Raman spectroscopy showed characteristic bands corresponding to NiFe2O4 with a shift of the A1g mode, which may be due to possible development of oxygen vacancies. Dielectric constant, measured at different temperatures, increased with temperature and decreased with increase in frequency at all temperatures. The Havrilliak-Negami model used to study the dielectric spectroscopy indicated that a NiFe2O4 nanoparticles display non-Debye type relaxation. Jonscher's power law was utilized for the calculation of the exponent and DC conductivity. The exponent values clearly demonstrated the non-ohmic behaviour of NiFe2O4 nanoparticles. The dielectric constant of the nanoparticles was found to be >300, showing a normal dispersive behaviour. AC conductivity showed an increase with the rise in temperature with the highest value of 3.4 × 10-9 S/cm at 323 K. The M-H curves revealed the ferromagnetic behaviour of a NiFe2O4 nanoparticle. The ZFC and FC studies suggested a blocking temperature of ~64 K. The saturation of magnetization determined using the law of approach to saturation was ~61.4 emu/g at 10 K, corresponding to the magnetic anisotropy ~2.9 × 104 erg/cm3. Electrochemical studies showed that a specific capacitance of ~600 F g-1 was observed from the cyclic voltammetry and galvanostatic charge-discharge, which suggested its utilization as a potential electrode for supercapacitor applications.

Fabrication of High-Performance Asymmetric Supercapacitors Using Rice Husk-Activated Carbon and MnFe2O4 Nanostructures.

To meet the growing demand for efficient and sustainable power sources, it is crucial to develop high-performance energy storage systems. Additionally, they should be cost-effective and able to operate without any detrimental environmental side effects. In this study, rice husk-activated carbon (RHAC), which is known for its abundance, low cost, and excellent electrochemical performance, was combined with MnFe2O4 nanostructures to improve the overall capacitance of asymmetric supercapacitors (ASCs) and their energy density. A series of activation and carbonization steps are involved in the fabrication process for RHAC from rice husk. Furthermore, the BET surface area for RHAC was determined to be 980 m2 g-1 and superior porosities (average pore diameter of 7.2 nm) provide abundant active sites for charge storage. Additionally, MnFe2O4 nanostructures were effective pseudocapacitive electrode materials due to their combined Faradic and non-Faradic capacitances. In order to assess the electrochemical performance of ASCs extensively, several characterization techniques were employed, including galvanostatic charge -discharge, cyclic voltammetry, and electrochemical impedance spectroscopy. Comparatively, the ASC demonstrated a maximum specific capacitance of ~420 F/g at a current density of 0.5 A/g. The as-fabricated ASC possesses remarkable electrochemical characteristics, including high specific capacitance, superior rate capability, and long-term cycle stability. The developed asymmetric configuration retained 98% of its capacitance even after 12,000 cycles performed at a current density of 6A/g, demonstrating its stability and reliability for supercapacitors. The present study demonstrates the potential of synergistic combinations of RHAC and MnFe2O4 nanostructures in improving supercapacitor performance, as well as providing a sustainable method of using agricultural waste for energy storage.

Metal-based nanomaterials and nanocomposites as promising frontier in cancer chemotherapy.

Cancer is a disease associated with complex pathology and one of the most prevalent and leading reasons for mortality in the world. Current chemotherapy has challenges with cytotoxicity, selectivity, multidrug resistance, and the formation of stemlike cells. Nanomaterials (NMs) have unique properties that make them useful for various diagnostic and therapeutic purposes in cancer research. NMs can be engineered to target cancer cells for early detection and can deliver drugs directly to cancer cells, reducing side effects and improving treatment efficacy. Several of NMs can also be used for photothermal therapy to destroy cancer cells or enhance immune response to cancer by delivering immune-stimulating molecules to immune cells or modulating the tumor microenvironment. NMs are being modified to overcome issues, such as toxicity, lack of selectivity, increase drug capacity, and bioavailability, for a wide spectrum of cancer therapies. To improve targeted drug delivery using nano-carriers, noteworthy research is required. Several metal-based NMs have been studied with the expectation of finding a cure for cancer treatment. In this review, the current development and the potential of plant and metal-based NMs with their effects on size and shape have been discussed along with their more effective usage in cancer diagnosis and treatment.

A systematic review of computational approaches to understand cancer biology for informed drug repurposing.

Cancer is the second leading cause of death globally, trailing only heart disease. In the United States alone, 1.9 million new cancer cases and 609,360 deaths were recorded for 2022. Unfortunately, the success rate for new cancer drug development remains less than 10%, making the disease particularly challenging. This low success rate is largely attributed to the complex and poorly understood nature of cancer etiology. Therefore, it is critical to find alternative approaches to understanding cancer biology and developing effective treatments. One such approach is drug repurposing, which offers a shorter drug development timeline and lower costs while increasing the likelihood of success. In this review, we provide a comprehensive analysis of computational approaches for understanding cancer biology, including systems biology, multi-omics, and pathway analysis. Additionally, we examine the use of these methods for drug repurposing in cancer, including the databases and tools that are used for cancer research. Finally, we present case studies of drug repurposing, discussing their limitations and offering recommendations for future research in this area.

A mixed method study to assess notification of tuberculosis patients by private practitioners in New Delhi, India.

Background: A staggering one million tuberculosis (TB) cases are missing from notification, most of them being diagnosed and treated in the private sector. To curb this issue, the Government of India declared TB as a notifiable disease and NIKSHAY was launched in 2012. However, even after years of implementation, as per the report published by TB India 2020, the proportion of private case notification of total TB cases is very low. Objectives: The objectives of the study were to assess the current practices related to TB Notification being followed by private practitioners of Delhi and to explore the enablers and barriers to TB notification among private-sector treatment providers. Methods: This cross-sectional study was done from January 2019 to January 2020. Six hundred doctors were line listed under the chosen TB unit, 375 gave consent and in depth interview was conducted among them. Data were collected on the reporting status and facilitators and barrier toward NIKSHAY reporting were assessed. For the qualitative component, focused group discussions were done. Results: Out of 375 private practitioners, over two-third (68%) practitioners reported that they were not treating TB patients. Out of 108 doctors treating patients only 50% were reporting the cases. Major reason cited for not reporting was "don't know how to" and major barrier considered was "lack of training." Conclusion: Strategies such as training and retraining, and one-to-one sensitization of private practitioners to address barriers may enhance TB notification.

Drug repurposing for viral cancers: A paradigm of machine learning, deep learning, and virtual screening-based approaches.

Cancer management is major concern of health organizations and viral cancers account for approximately 15.4% of all known human cancers. Due to large number of patients, efficient treatments for viral cancers are needed. De novo drug discovery is time consuming and expensive process with high failure rate in clinical stages. To address this problem and provide treatments to patients suffering from viral cancers faster, drug repurposing emerges as an effective alternative which aims to find the other indications of the Food and Drug Administration approved drugs. Applied to viral cancers, drug repurposing studies following the niche have tried to find if already existing drugs could be used to treat viral cancers. Multiple drug repurposing approaches till date have been introduced with successful results in viral cancers and many drugs have been successfully repurposed various viral cancers. Here in this study, a critical review of viral cancer related databases, tools, and different machine learning, deep learning and virtual screening-based drug repurposing studies focusing on viral cancers is provided. Additionally, the mechanism of viral cancers is presented along with drug repurposing case study specific to each viral cancer. Finally, the limitations and challenges of various approaches along with possible solutions are provided.