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AbstractFood dyes with a diverse set of colorants stimulate appetite and enhance aesthetic charm of food on table but at the same time these dyes contaminate the aquatic and biological ecosystems due to their cytotoxic and carcinogenic potentials. Herein, we report magnetite catalyzed removal of sunset yellow dye from water through catalytic degradation and ozonation. The magnetite catalyst revealed about 83% catalytic degradation and 92% catalytic ozonation performance toward sunset yellow dye at 100 and 25 min, respectively. Furthermore, the persulphate/magnetite/O3 hybrid system revealed superior performance compared to the persulphate/magnetite under identical conditions. Kinetic studies revealed that the dye degradation data followed second-order kinetics, suggesting that the dye removal process is physicochemical in nature. This study further demonstrates that the persulfate/magnetite/O3 hybrid system can efficiently decompose sunset yellow dye in aqueous solution compared to the Fenton’s reagent and simple catalytic decomposition processes which is attributed to its unique structural features.

AbstractElectrochromic (EC) thin films have received considerable attention due to their potential applications in various fields such as smart windows, electrochromic displays, and energy storage devices. This review highlights various methods used for the fabrication and functionalization of EC films for various applications. Various techniques for EC thin film deposition ranging from solution-processable, low-temperature approaches such as sol-gel, spin coating, dip coating, and spray pyrolysis, to advanced techniques for deposition such as physical vapor deposition, chemical vapor deposition, and sputtering are summarized in this review. In addition, various applications of EC thin films and the outcome of different deposition approaches on the opto-electrochromic properties of EC thin films have been discussed elaborately. This review has the potential to spark the interest of researchers from a broad range of disciplines, including photocatalysis, electrocatalysis, nanotechnology and materials science.

Anemia and malnutrition are global health problem among all nutritional disorder with high morbidity and mortality in school aged children. Therefore the aims of the study assist the prevalence and risk factors of anemia, and malnutrition among school-going children of District Swabi Pakistan. A total of 600 school aged children of aged 4-15 years were included in the study in 2023. Hematocrit level was obtained using a centrifuge microhematocrit, and converted to hemoglobin using standard conversion. Nutritional status was determined by the anthropometric measurements, and demographic characteristics were obtained by questionnaire. Anemia and malnutrition were defined according to the World Health Organization standards. In current research work 600 children were selected for the assessment of nutritional status in which 105(17.5%) were found malnutrated. Moderate frequency of assessment were found among anemia 25(23.80%), stunting 22(21%) and underweight 18(17%) respectively. High frequency was found in malnutrition 40(38%) while very low frequency was seen in wasting 2(1.90%). Gender wise assessment of the students shows that the nutritional deficiencies were slightly high in male as compare to female students in comparison of Anemia, Malnutrition, Stunting, and Underweight and in wasting respectively. Aged group wised assessment of the students shows that the nutritional deficiencies were slightly high in low aged student (4-7 years) as compare to 8-11 years and 12-15 years in both gender. Among them Malnutrition were very high leading by Anemia while Underweight and wasting of very low frequency respectively.

In recent years, green nanomaterials are increasingly being utilized in horticulture and agriculture due to their potential to transform plant development, improve crop yield, combat diseases, and pest management, among other applications. Significantly, green nanomaterials enhance nutrient delivery by improving stability, uptake, and solubility efficiency. Utilizing non-toxic precursors, waste reduction strategies, renewable resources, and energy-efficient processes, they offer sustainable technology advancement. Moreover, tomatoes, the largest domestic and industrial crop, yield around 200 million tons globally. They are beneficial for blood cleansing, gastrointestinal secretion, and nutrient reduction. However, they are susceptible to diseases like early blight, septoria leaf spot, late blight, and buckeye rot. In this regard, green nanomaterials have the potential to revolutionize agriculture by improving disease management, detecting diseases quickly, enhancing nutrient uptake, safely delivering agrochemicals, and reducing pesticide dosage. So, impressed by this, in this current review paper, we explored the use of green nanomaterials for tomato growth, and development and investigated their unique features, utilization, challenges, and future prospects. Ultimately, this review will open a new research gateway for plant-based nanomaterial and their utilization in various disciplines particularly for crop protection, growth, and soil health.

Abstract Aortic aneurysm (AA) is an aortic disease with a high mortality rate, and other than surgery no effective preventive or therapeutic treatment have been developed. The renin–angiotensin system (RAS) is an important endocrine system that regulates vascular health. The ACE2/Ang‐(1–7)/MasR axis can antagonize the adverse effects of the activation of the ACE/Ang II/AT1R axis on vascular dysfunction, atherosclerosis, and the development of aneurysms, thus providing an important therapeutic target for the prevention and treatment of AA. However, products targeting the Ang‐(1–7)/MasR pathway still lack clinical validation. This review will outline the epidemiology of AA, including thoracic, abdominal, and thoracoabdominal AA, as well as current diagnostic and treatment strategies. Due to the highest incidence and most extensive research on abdominal AA (AAA), we will focus on AAA to explain the role of the RAS in its development, the protective function of Ang‐(1–7)/MasR, and the mechanisms involved. We will also describe the roles of agonists and antagonists, suggest improvements in engineering and drug delivery, and provide evidence for Ang‐(1–7)/MasR's clinical potential, discussing risks and solutions for clinical use. This study will enhance our understanding of AA and offer new possibilities and promising targets for therapeutic intervention.

Abstract The COVID-19 pandemic, caused by the SARS-CoV-2 virus, has led to over six million deaths worldwide. In human immune system, the type 1 interferon (IFN) pathway plays a crucial role in fighting viral infections. However, the ORF8 protein of the virus evade the immune system by interacting with IRF3, hindering its nuclear translocation and consequently downregulate the type I IFN signaling pathway. To block the binding of ORF8–IRF3 and inhibit viral pathogenesis a quick discovery of an inhibitor molecule is needed. Therefore, in the present study, the interface between the ORF8 and IRF3 was targeted on a high-affinity carbon nanotube by using computational tools. After analysis of 62 carbon nanotubes by multiple docking with the induced fit model, the top five compounds with high docking scores of − 7.94 kcal/mol, − 7.92 kcal/mol, − 7.28 kcal/mol, − 7.19 kcal/mol and − 7.09 kcal/mol (top hit1-5) were found to have inhibitory activity against the ORF8–IRF3 complex. Molecular dynamics analysis of the complexes revealed the high compactness of residues, stable binding, and strong hydrogen binding network among the ORF8-nanotubes complexes. Moreover, the total binding free energy for top hit1-5 was calculated to be − 43.21 ± 0.90 kcal/mol, − 41.17 ± 0.99 kcal/mol, − 48.85 ± 0.62 kcal/mol, − 43.49 ± 0.77 kcal/mol, and − 31.18 ± 0.78 kcal/mol respectively. These results strongly suggest that the identified top five nanotubes (hit1-5) possess significant potential for advancing and exploring innovative drug therapies. This underscores their suitability for subsequent in vivo and in vitro experiments, marking them as promising candidates worthy of further investigation.

Abstract Over the course of the COVID-19 pandemic, several SARS-CoV-2 variants have emerged that may exhibit different etiological effects such as enhanced transmissibility and infectivity. However, genetic variations that reduce virulence and deteriorate viral fitness have not yet been thoroughly investigated. The present study sought to evaluate the effects of viral genetic makeup on COVID-19 epidemiology in Pakistan, where the infectivity and mortality rate was comparatively lower than other countries during the first pandemic wave. For this purpose, we focused on the comparative analyses of 7096 amino-acid long polyprotein pp1ab. Comparative sequence analysis of 203 SARS-CoV-2 genomes, sampled from Pakistan during the first wave of the pandemic revealed 179 amino acid substitutions in pp1ab. Within this set, 38 substitutions were identified within the Nsp3 region of the pp1ab polyprotein. Structural and biophysical analysis of proteins revealed that amino acid variations within Nsp3’s macrodomains induced conformational changes and modified protein-ligand interactions, consequently diminishing the virulence and fitness of SARS-CoV-2. Additionally, the epistatic effects resulting from evolutionary substitutions in SARS-CoV-2 proteins may have unnoticed implications for reducing disease burden. In light of these findings, further characterization of such deleterious SARS-CoV-2 mutations will not only aid in identifying potential therapeutic targets but will also provide a roadmap for maintaining vigilance against the genetic variability of diverse SARS-CoV-2 strains circulating globally. Furthermore, these insights empower us to more effectively manage and respond to potential viral-based pandemic outbreaks of a similar nature in the future.

Biochar is a porous, high-surface-area, black carbon-rich product that offers a cost-effective and environmentally friendly option to replace conventional charcoal. However, its specific structure and limited biodegradability pose challenges for its widespread applications. Photocatalysis is suggested as an alternative approach to harness solar energy and transform it into solar fuels. Interestingly, nanomaterials-based photocatalysts with tailored energy band properties and non-toxic characteristics, high surface areas, enhanced stability, and tunable pore sizes, have gained attention for their potential in diverse applications. Therefore, existing research on biochar-based photocatalysis systems (BBPs) aims to address different environmental issues. Interestingly, BBPs offer benefits such as excellent electrical conductivity, versatile functional groups, large surface area, and multiple surface-active sites, promoting high charge mobility, electron reservoir, superior charge separation, and small bandgap. This review provides a comprehensive overview of BBPs developments, including synthesis methods and properties. The fusion of BBPs is used in CO2 conversion, photocatalytic H2 generation, CO2 reduction, pollutants, dyes, and pharmaceutical degradation. Although the intermarriage of BBPs has potential benefits, their effectiveness may be compromised when modified photocatalysts are incorporated, which may negatively influence carrier generation efficiency and overall performance. Therefore, there is empty room for further research on their physical properties, effectiveness, long-term stability, and reusability of BBPs.

Effective wastewater treatment is essential due to the dye environmental threats. Photocatalysis offers an eco-friendly dye degradation solution. Herein, we report a double Z-scheme photocatalyst, i.e. LaFeO3/Boron-doped g-C3N4/Fe2O3 (LFO/B-CN/FO), fabricated via a hydrothermal method. The formation of this ternary system is supported by structural, surface, and morphological analyses. Differential scanning calorimetry and thermal gravimetric analysis demonstrated the crystallization behavior of the composite. Because of synergetic effects in the ternary composite and boron doping, the optical band gap energy is reduced to 1.6 eV. Under visible light irradiation, the LFO/B-CN/FO nanocomposite degraded navy-blue dye by 98% in 130 min at neutral pH, surpassing CN, B-CN, and binary composites of B-CN with LFO and FO. The degradation process was rationalized using pseudo-first- and pseudo-second-order kinetic models, which confirmed high catalytic efficiency. The double Z-scheme heterojunction enhanced light absorption, charge separation, and carrier lifetime, hence improving the photocatalytic activity. Overall, the as-fabricated LFO/B-CN/FO ternary composite outperformed reference catalysts in terms of chemical reactivity, optical characteristics, and electrical performance. This work opens up a new route for the design and fabrication of double Z-scheme ternary composite photocatalysts for potential wastewater treatment and renewable energy applications.

ABSTRACTThe growing demand for renewable energy sources has driven research efforts towards highly efficient electrochemical processes, especially the Hydrogen Evolution Reaction (HER) which is an essential component in renewable hydrogen production. Single Atom Catalysts (SACs) have been recognised as promising catalysts for exceptional HER activities owing to their unique electronic and geometrical features. This comprehensive review highlights the effective correlation between computational modelling and experimental research in fabricating new SACs and better understanding their catalytic mechanisms in the HER. Furthermore, the review briefly describes the choice of metals and tailoring the electronic structure, as well as exploring the influence of the reaction parameters on the catalytic activity of SACs for HER. Concluding remarks alongside future perspectives on the improvement of SACs for HER are emphasised. It is hoped that this review will pave the way for rational design of highly effective, low-cost and stable SACs for sustainable hydrogen production.

ABSTRACTThe quality of water significantly affects the health and walefare of all orginisms, highlighting the importance to develop low-cost and efficient wastewater treatment methods. Herein, we report the fabrication, characterization, and utilization of a polymer-based ternary nanocomposite (CuO–SiO2/PVA) for the removal of Nile Blue (NB) and Methylene Blue (MB) contaminants from wastewater, along with exploring its potential biological activities. We have successfully employed the cost-effective sol–gel and in-situ polymerization approaches to fabricate the CuO–SiO2/PVA based ternary composite, utilizing Cu(NO3)2·3H2O:Glycerol:TEOS:PVA in a ratio of 8:2:3:4. The desired fabrication of nanocomposite was confirmed through UV-Visible spectroscopy, SEM (scanning electron microscope), TEM (transmission electron microscope), EDX (energy dispersive X-ray diffraction), FTIR (Fourier transform infrared), DSC (differential scanning calorimetry), and TGA (thermogravimetric analysis). In addition to its biological potentialthe performance of the nanocomposite in catalytic / photocatalytic removal of NB and MB dyes is investigated and compared. The higher photodegradation performance of the composite for NB (85%) dye than for MB (76%) dye indicates that variables such as chemical structure, charge, molecular mass, and pH sensitivity of the dyes can influence the catalyst's removal potential. This composite is considered to have a higher capability for removing pollutants and microorganisms from wastewater.

Myocarditis is a cardiovascular disease characterised by inflammation of the heart muscle which can lead to heart failure. There is heterogeneity in the mode of presentation, underlying aetiologies, and clinical outcome with impact on a wide range of age groups which lead to diagnostic challenges. Cardiovascular magnetic resonance (CMR) is the preferred imaging modality in the diagnostic work-up of those with acute myocarditis. There is a need for systematic analytical approaches to improve diagnosis. Artificial intelligence (AI) and machine learning (ML) are increasingly used in CMR and has been shown to match human diagnostic performance in multiple disease categories. In this review article, we will describe the role of CMR in the diagnosis of acute myocarditis followed by a literature review on the applications of AI and ML to diagnose acute myocarditis. Only a few papers were identified with limitations in cases and control size and a lack of detail regarding cohort characteristics in addition to the absence of relevant cardiovascular disease controls. Furthermore, often CMR datasets did not include contemporary tissue characterisation parameters such as T1 and T2 mapping techniques, which are central to the diagnosis of acute myocarditis. Future work may include the use of explainability tools to enhance our confidence and understanding of the machine learning models with large, better characterised cohorts and clinical context improving the diagnosis of acute myocarditis.

This review underscores the fundamentals of MIP-CMs and systematically summarizes their synthetic strategies and applications, and potential developments. MIP-CMs are widely acclaimed for their versatility, finding applications in separation, filtration, detection, and trace analysis, as well as serving as scaffolds in a range of analytical, biomedical and industrial contexts. Also characterized by extraordinary selectivity, remarkable sensitivity, and outstanding capability to bind molecules, those membranes are also cost-effective, highly stable, and configurable in terms of recognition and, therefore, inalienable in various application fields. Issues relating to the potential future for the paper are discussed in the last section with the focus on the improvement of resource practical application across different areas. Hence, this review can be seen as a kind of cookbook for the design and fabrication of MIP-CMs with an intention to expand the scope of their application.

Background: Influenza A virus causes severe respiratory illnesses, especially in developing nations where most child deaths under 5 occur due to lower respiratory tract infections. The RIG-I protein acts as a sensor for viral dsRNA, triggering interferon production through K63-linked poly-ubiquitin chains synthesized by TRIM25. However, the influenza A virus's NS1 protein hinders this process by binding to TRIM25, disrupting its association with RIG-I and preventing downstream interferon signalling, contributing to the virus's evasion of the immune response. Methods: In our study we used structural-based drug designing, molecular simulation, and binding free energy approaches to identify the potent phytocompounds from various natural product databases (>100,000 compounds) able to inhibit the binding of NS1 with the TRIM25. Results: The molecular screening identified EA-8411902 and EA-19951545 from East African Natural Products Database, NA-390261 and NA-71 from North African Natural Products Database, SA-65230 and SA- 4477104 from South African Natural Compounds Database, NEA- 361 and NEA- 4524784 from North-East African Natural Products Database, TCM-4444713 and TCM-6056 from Traditional Chinese Medicines Database as top hits. The molecular docking and binding free energies results revealed that these compounds have high affinity with the specific active site residues (Leu95, Ser99, and Tyr89) involved in the interaction with TRIM25. Additionally, analysis of structural dynamics, binding free energy, and dissociation constants demonstrates a notably stronger binding affinity of these compounds with the NS1 protein. Moreover, all selected compounds exhibit exceptional ADMET properties, including high water solubility, gastrointestinal absorption, and an absence of hepatotoxicity, while adhering to Lipinski’s rule. Conclusion: Our molecular simulation findings highlight that the identified compounds demonstrate high affinity for specific active site residues involved in the NS1-TRIM25 interaction, exhibit exceptional ADMET properties, and adhere to drug-likeness criteria, thus presenting promising candidates for further development as antiviral agents against influenza A virus infections.

The pyrolysis process of coconut residue and the activated carbon was investigated using thermogravimetric analysis in the range of 25 to 900 °C, with three altered heating rates: 3, 5, and 10 °C/min. The results of the thermal decomposition showed that it occurred in three distinct phases: dehydration, active pyrolysis, and passive pyrolysis. The derivative thermogravimetric analysis indicated that increasing the heating rate led to a shift in the maximum weight loss rate towards higher temperatures. To better understand the kinetics constraints, the Coats–Redfern method was applied to determine the activation energy (Ea) and the frequency factor (A). The activation energies for the pyrolysis process varied between 159.57 and 177.45 kJ/mol for RCR and from 132.62 to 147.1 kJ/mol for ACCR at different heating rates. Additionally, the physical properties of the samples were investigated using techniques like scanning electron microscopy and the Brunauer–Emmett–Teller surface analysis. The findings of the study demonstrated that the activation energies of the activated carbon were lower than those of the original biomass. Furthermore, the activation energy values achieved from the D1–D4 models were considered reliable, indicating that the D model was more suitable compared to other models for describing the pyrolysis process and predicting its kinetics.

In this study, ZrCuO2 nanoparticles were made using the hydrothermal method and potassium hydroxide as the precipitant. The material was irradiated with 500 keV carbon (C++) ions at doses of 1 × 1014, 1 × 1016, and 1 × 1018 ions/cm2. The ZrCuO2 nanoparticles exhibited cubic crystal structures with clear peaks on different orientation planes, both before and after being irradiated with carbon ions (C++). By incorporating carbon ions, the peak intensity and crystallinity of CuO nanostructures were enhanced. The non-irradiated micrographs display groups of tiny pebbles, whereas the carbon ion irradiated ZrCuO2 nanoparticles show flake-like structures. The material became denser because of carbon ion irradiation, which increased the carrier concentration. The absorption rate increase of the material reveals the impact of a carbon ion on irradiated ZrCuO2 nanoparticles. The absorbance of ZrCuO2 nanoparticles is enhanced through carbon ion implantation. The material has a bandgap energy of 1.95 eV without irradiation. The bandgap energy range of the irradiated material is 1.55–1.82 eV. The energy bandgap of the synthesized material was reduced because of carbon ion irradiation. The ZrCuO2 nanoparticle electrode with a specific capacitance value of 225 F/g. The electrodes prepared at 500 keV carbon (C++) ions with dosages of 1 × 1014, 1 × 1016, and 1 × 1018 ions/cm2 yielded specific capacitance values of 275 F/g, 300 F/g, and 312.5 F/g, respectively.

Modern industries rapid expansion has heightened energy needs and accelerated fossil fuel depletion, contributing to global warming. Additionally, organic pollutants present substantial risks to aquatic ecosystems due to their stability, insolubility, and non-biodegradability. Scientists are currently researching high-performance materials to address these issues. LaFeO3 nanosheets (LFO-NS) were synthesized in this study using a solvothermal method with polyvinylpyrrolidone (PVP) as a soft template. The LFO-NS demonstrate superior performance, large surface area and charge separation than that of LaFeO3 nanoparticles (LFO-NP). The LFO-NS performance is further upgraded by incorporating ZIF-67. Our results confirmed the ZIF-67/LFO-NS nanocomposite have superior performances than pure LFO-NP and ZIF-67. The integration of ZIF-67 has enhanced the charge separation and promote the surface area of LFO-NSwhich was confirmed by various characterization techniques including TEM, HRTEM, DRS, EDX, XRD, FS, XPS, FT-IR, BET, PL, and RAMAN. The 5ZIF-67/LFO-NS sample showed significant activities for CO2 conversion, malachite green degradation, and antibiotics (cefazolin, oxacillin, and vancomycin) degradation. Furthermore, stability tests have confirmed that our optimal sample very active and stable. Furthermore, based on scavenger experiments and the photocatalytic degradation pathways, it has been established that H+ and •O2− are vital in the decomposition of MG and antibiotics. Our research work will open new gateways to prepare MOFs-Perovskites nanocatalysts for exceptional CO2 conversion, organic pollutants and antibiotics degradation.

IntroductionDiabetes mellitus (DM) is recognized as one of the oldest chronic diseases and has become a significant public health issue, necessitating innovative therapeutic strategies to enhance patient outcomes. Traditional treatments have provided limited success, highlighting the need for novel approaches in managing this complex disease.MethodsIn our study, we employed graph signature-based methodologies in conjunction with molecular simulation and free energy calculations. The objective was to engineer the CA33 monoclonal antibody for effective targeting of the aP2 antigen, aiming to elicit a potent immune response. This approach involved screening a mutational landscape comprising 57 mutants to identify modifications that yield significant enhancements in binding efficacy and stability.ResultsAnalysis of the mutational landscape revealed that only five substitutions resulted in noteworthy improvements. Among these, mutations T94M, A96E, A96Q, and T94W were identified through molecular docking experiments to exhibit higher docking scores compared to the wild-type. Further validation was provided by calculating the dissociation constant (KD), which showed a similar trend in favor of these mutations. Molecular simulation analyses highlighted T94M as the most stable complex, with reduced internal fluctuations upon binding. Principal components analysis (PCA) indicated that both the wild-type and T94M mutant displayed similar patterns of constrained and restricted motion across principal components. The free energy landscape analysis underscored a single metastable state for all complexes, indicating limited structural variability and potential for high therapeutic efficacy against aP2. Total binding free energy (TBE) calculations further supported the superior performance of the T94M mutation, with TBE values demonstrating the enhanced binding affinity of selected mutants over the wild-type.DiscussionOur findings suggest that the T94M substitution, along with other identified mutations, significantly enhances the therapeutic potential of the CA33 antibody against DM by improving its binding affinity and stability. These results not only contribute to a deeper understanding of antibody-antigen interactions in the context of DM but also provide a valuable framework for the rational design of antibodies aimed at targeting this disease more effectively.

With the use of facile single-step calcination of Zinc glutamate MOF and melamine, highly efficient ZnO/g-C3N4 nanocomposite was prepared and utilized in photocatalytic degradation of Rhodamine B (RhB), an organic pollutant. The composite's morphology, crystallinity, optical properties, and composition were determined using several analytical techniques, which include scanning electron microscopy (SEM), transmission electron microscopy (TEM), Fourier-transform infrared (FTIR) spectroscopy, X-ray powder diffraction (XRD), diffuse reflectance spectroscopy. The degradation of RhB over the optimized 1.0%ZnO/g-C3N4 composite is ∼1.77 fold higher compared to the pure g-C3N4 under identical conditions. The synergistic interfacial interaction between g-C3N4 and MOF derived ZnO remarkably improved the electron-hole pairs separation, which led to the exceptionally high photocatalytic activity of the composite photocatalysts. Based on the radical scavenger tests and ESR analysis, it is confirmed that •O2− as the dominant active specie facilitated the degradation of RhB over the as-prepared ZnO/g-C3N4 composites. This work will open up new insights for further research on g-C3N4 based composite materials.

Abstract Background Doxorubicin (DOX)-induced cardiotoxicity (DIC) is a major impediment to its clinical application. It is indispensable to explore alternative treatment molecules or drugs for mitigating DIC. WGX50, an organic extract derived from Zanthoxylum bungeanum Maxim, has anti-inflammatory and antioxidant biological activity, however, its function and mechanism in DIC remain unclear. Methods We established DOX-induced cardiotoxicity models both in vitro and in vivo. Echocardiography and histological analyses were used to determine the severity of cardiac injury in mice. The myocardial damage markers cTnT, CK-MB, ANP, BNP, and ferroptosis associated indicators Fe2+, MDA, and GPX4 were measured using ELISA, RT-qPCR, and western blot assays. The morphology of mitochondria was investigated with a transmission electron microscope. The levels of mitochondrial membrane potential, mitochondrial ROS, and lipid ROS were detected using JC-1, MitoSOX™, and C11-BODIPY 581/591 probes. Results Our findings demonstrate that WGX50 protects DOX-induced cardiotoxicity via restraining mitochondrial ROS and ferroptosis. In vivo, WGX50 effectively relieves doxorubicin-induced cardiac dysfunction, cardiac injury, fibrosis, mitochondrial damage, and redox imbalance. In vitro, WGX50 preserves mitochondrial function by reducing the level of mitochondrial membrane potential and increasing mitochondrial ATP production. Furthermore, WGX50 reduces iron accumulation and mitochondrial ROS, increases GPX4 expression, and regulates lipid metabolism to inhibit DOX-induced ferroptosis. Conclusion Taken together, WGX50 protects DOX-induced cardiotoxicity via mitochondrial ROS and the ferroptosis pathway, which provides novel insights for WGX50 as a promising drug candidate for cardioprotection. Graphic abstract

Background: MMTV causes mammary tumors in mice, and it is associated with invasive and aggressive forms of breast cancer in humans. However, the underlying mechanisms are yet unknown. We aimed to determine the MMTV-like virus (MMTV-LV) association with histological types of breast cancer, nodal involvement, and metastasis. Methods: First, 105 breast cancer biopsies and 15 disease-free biopsies were collected. Details of clinicopathological characteristics were retrieved from patients’ records. The status of MMTV-LV was already known for these biopsy samples. Associations of MMTV-LV prevalence with LNM status and metastatic history were determined. Next, quantitative PCR (qPCR) was used to quantify env gene mRNA in biopsies positive for MMTV-LV. Expression of the env gene was compared against different histopathological types of mammary tumor, LNM status, and metastasis by performing Ordinary One Way ANOVA followed by Tukey’s multiple comparisons test. Results: MMTV-LV prevalence was found to have no significant association with LNM or metastatic history. As compared to normal control, expression of the env gene was significantly higher (>2.8 folds) in invasive samples (P-value: < 0.01). Expression was also higher (3.28 and 2.89 folds) in patient samples with LNM (P-value: 0.0006) or metastatic history (P-value: < 0.0001), respectively. Conclusion: We conclude that MMTV-LV prevalence is not associated with LNM status or breast cancer metastasis; samples with invasive phenotypes, nodal involvement, and metastasis exhibit significantly higher expression of the MMTV-like env gene.

The authors would like to make the following correction to this published paper [...]

In the current study, Neosetophomone B (NSP–B) was investigated for its anti-cancerous potential using network pharmacology, quantum polarized ligand docking, molecular simulation, and binding free energy calculation. Using SwissTarget prediction, and Superpred, the molecular targets for NSP-B were predicted while cancer-associated genes were obtained from DisGeNet. Among the total predicted proteins, only 25 were reported to overlap with the disease-associated genes. A protein-protein interaction network was constructed by using Cytoscape and STRING databases. MCODE was used to detect the densely connected subnetworks which revealed three sub-clusters. Cytohubba predicted four targets, i.e., fibroblast growth factor , FGF20, FGF22, and FGF23 as hub genes. Molecular docking of NSP-B based on a quantum-polarized docking approach with FGF6, FGF20, FGF22, and FGF23 revealed stronger interactions with the key hotspot residues. Moreover, molecular simulation revealed a stable dynamic behavior, good structural packing, and residues’ flexibility of each complex. Hydrogen bonding in each complex was also observed to be above the minimum. In addition, the binding free energy was calculated using the MM/GBSA (Molecular Mechanics/Generalized Born Surface Area) and MM/PBSA (Molecular Mechanics/Poisson-Boltzmann Surface Area) approaches. The total binding free energy calculated using the MM/GBSA approach revealed values of −36.85 kcal/mol for the FGF6-NSP-B complex, −43.87 kcal/mol for the FGF20-NSP-B complex, and −37.42 kcal/mol for the FGF22-NSP-B complex, and −41.91 kcal/mol for the FGF23-NSP-B complex. The total binding free energy calculated using the MM/PBSA approach showed values of −30.05 kcal/mol for the FGF6-NSP-B complex, −39.62 kcal/mol for the FGF20-NSP-B complex, −34.89 kcal/mol for the FGF22-NSP-B complex, and −37.18 kcal/mol for the FGF23-NSP-B complex. These findings underscore the promising potential of NSP-B against FGF6, FGF20, FGF22, and FGF23, which are reported to be essential for cancer signaling. These results significantly bolster the potential of NSP-B as a promising candidate for cancer therapy.

The design and fabrication of a low-speed wind tunnel (LSWT), which is a critical component for testing and comprehending aircraft aerodynamics, is presented in this study. Despite the increasing prominence of computational fluid dynamics (CFDs) in manufacturing engineering, wind tunnels remain essential for the intricate development of aircraft and automobile designs with complex flow interactions. Using SolidWorks, we focused on controlling flow turbulence approaching the test section, emphasizing performance and quality parameters. The construction of the wind tunnel used plywood with an axial fan regulating the airspeed, and Arduino facilitated data acquisition. The drag and lift on the Y Clerk Airfoil were quantified by two load cells along the XY-axis, complemented by a Pitot Static Tube and a multitube inclined plane manometer for pressure and velocity calculation. Fusion 360 simulation software was used to analyze pressure and velocity profiles at speeds ranging from 10 to 20 m/s, providing a comprehensive quantitative evaluation of the wind tunnel’s capabilities. By emphasizing both design innovation and quantitative performance metrics, this study underscores the continuing significance of wind tunnels in engineering.

Nanomaterials (NMs) have garnered significant attention in recent decades due to their versatile applications in a wide range of fields. Thanks to their tiny size, enhanced surface modifications, impressive volume-to-surface area ratio, magnetic properties, and customized optical dispersion. NMs experienced an incredible upsurge in biomedical applications including diagnostics, therapeutics, and drug delivery. This minireview will focus on notable examples of NMs that tackle important issues, demonstrating various aspects such as their design, synthesis, morphology, classification, and use in cutting-edge applications. Furthermore, we have classified and outlined the distinctive characteristics of the advanced NMs as nanoscale particles and hybrid NMs. Meanwhile, we emphasize the incredible potential of metal-organic frameworks (MOFs), a highly versatile group of NMs. These MOFs have gained recognition as promising candidates for a wide range of bio-applications, including bioimaging, biosensing, antiviral therapy, anticancer therapy, nanomedicines, theranostics, immunotherapy, photodynamic therapy, photothermal therapy, gene therapy, and drug delivery. Although advanced NMs have shown great potential in the biomedical field, their use in clinical applications is still limited by issues such as stability, cytotoxicity, biocompatibility, and health concerns. This review article provides a thorough analysis offering valuable insights for researchers investigating to explore new design, development, and expansion opportunities. Remarkably, we ponder the prospects of NMs and nanocomposites in conjunction with current technology.

Amid the ongoing monkeypox outbreak, there is an urgent need for the rapid development of effective therapeutic interventions capable of countering the immune evasion mechanisms employed by the monkeypox virus (MPXV). The evasion strategy involves the binding of the F3L protein to dsRNA, resulting in diminished interferon (IFN) production. Consequently, our current research focuses on utilizing virtual drug screening techniques to target the RNA binding domain of the F3L protein. Out of the 954 compounds within the South African natural compound database, only four demonstrated notable docking scores: −6.55, −6.47, −6.37, and −6.35 kcal/mol. The dissociation constant (KD) analysis revealed a stronger binding affinity of the top hits 1-4 (−5.34, −5.32, −5.29, and −5.36 kcal/mol) with the F3L in the MPXV. All-atom simulations of the top-ranked hits 1 to 4 consistently exhibited stable dynamics, suggesting their potential to interact effectively with interface residues. This was further substantiated through analyses of parameters such as radius of gyration (Rg), Root Mean Square Fluctuation, and hydrogen bonding. Cumulative assessments of binding free energy confirmed the top-performing candidates among all the compounds, with values of −35.90, −52.74, −28.17, and −32.11 kcal/mol for top hits 1-4, respectively. These results indicate that compounds top hit 1-4 could hold significant promise for advancing innovative drug therapies, suggesting their suitability for both in vivo and in vitro experiments.

It is highly desirable and of utmost importance to find eco-friendly and green approaches for a sustainable environment. Nowadays researchers from different communities have determined that it is economical and highly demanding to synthesize green nanomaterials by utilizing plants, fruits, yeast, algae, fungi, and other green techniques as stabilizers and mediators. Compared to the chemical synthesis techniques, the plant-mediated approach is considered an eco-friendly, efficient, easy, stable, and cost-effective means for the synthesis of nanomaterials. Among various nano-size materials, Graphitic carbon nitride, g-C3N4, (CN) belongs to a new class of multifunctional metal-free n-type semiconductors. It has a polymeric structure with many potential applications in agriculture and energy sectors and other fields. So, it is highly demanding to explore the green synthesis approaches and their utilization for nanomaterials, especially g-C3N4. In this review, we comprehensively explored the green g-C3N4 based nanomaterials, their preparation, properties, applications, and opportunities. Adding more, this study aims to explore all feasible green synthesis approaches, applications, characterization techniques, and modification methods. Apart from this, the current statutes and future prospectus of the green g-C3N4 based nanomaterials are also explored. Finally, this work will open a new gateway for the synthesis of green g-C3N4 based nanomaterials and their utilization for a sustainable environment.

One of the most widespread metabolic diseases, Type-2 Diabetes Mellitus (T2DM) is defined by high blood sugar levels brought on by decreased insulin secretion, reduced insulin action, or both. Due to its cost-effectiveness and eco-friendliness, plant-mediated green synthesis of nanomaterials has become more and more popular. The aim of the study is to synthesize AgNPs, their characterizations and further in-vitro and in-vivo studies. Several methods were used to morphologically characterise the AgNPs. The AgNPs were crystalline, spherical, and clustered, with sizes ranging from 20 to 50 nm. AgNPs were found to contain various functional groups using Fourier transform infrared spectroscopy. This study focuses on the green-synthesis of AgNPs from Fagonia cretica (F. cretica) leaves extract to evaluate their synthesized AgNPs for in-vitro and in-vivo anti-diabetic function. For the in-vivo tests, 20 male Balb/C albino-mice were split up into four different groups. Anti-diabetic in-vivo studies showed significant weight gain and a decrease in all biochemical markers (pancreas panel, liver function panel, renal function panel, and lipid profile) in Streptozotocin (STZ)-induced diabetic mice. In vitro anti-diabetic investigations were also conducted on AgNPs, comprising α-amylase, α-glucosidase inhibitions, and antioxidant assays. AgNPs showed antioxidant activity in both the DPPH and ABTS assays. The research showed that the isolated nanoparticles have powerful antioxidant and enzyme inhibitory properties, especially against the main enzymes involved in T2DM.

The growing concerns and cases of COVID-19 with the appearance of novel variants i.e., BA.2.75. BA.5 and XBB have prompted demand for more effective treatment options that could overcome the risk of immune evasion. For this purpose, discovering novel small molecules to inhibit druggable proteins such as PLpro required for viral pathogenesis, replication, survival, and spread is the best choice. Compounds from the Dark chemical matter (DCM) database is consistently active in various screening tests and offer intriguing possibilities for finding drugs that are extremely selective or active against uncommon targets. Considering the essential role of PLpro, the current study uses DCMdatabase for the identification of potential hits using in silico virtual molecular screening and simulation approaches to inhibit the current and emerging variants of SARS-CoV-2. Our results revealed the 10 best compounds with docking scores between −7.99 to −7.03 kcal/mol better than the control drug (GRL0617) among which DC 5977–0726, DC 6623–2024, DC C879-0379 and DC D135-0154 were observed as the best hits. Structural-dynamics properties such as dynamic stability, protein packing, and residue flexibility demonstrated the pharmacologically favorable properties of these top hits in contrast to GRL0617. The hydrogen bonding half-life revealed that Asp164, Arg166, Tyr264, and Tyr268 have major contributions to the hydrogen bonding during the simulation. However, some of the important hydrogen bonds were missing in the control drug (GRL0617). Finally, the total binding free energy was reported to be −34.41 kcal/mol for GRL0617 (control), −41.03 kcal/mol for the DC5977-0726-PLpro, for the DC6623-2024-Plpro complex the TBE was −48.87 kcal/mol, for the for DCC879-0379-Plpro complex the TBE was −45.66 kcal/mol while for the DCD135-0154-PLpro complex the TBE was calculated to be −40.09 kcal/mol respectively, which shows the stronger potency of these compounds against PLpro and further in in vivo and in vitro test are required for the possible usage as potential drug against SARS-CoV-2.

Abstract The increasing trend in the incidence of adverse perinatal outcomes is a public health concern globally as well as in China. However, the causes of the increasing trend are not well understood. The present tertiary-hospital-based retrospective study (2011–2019) aims to determine the secular trends and age-period-cohort effect on adverse perinatal outcomes in Hubei, China. The age-standardized incidence rates of adverse perinatal outcomes significantly decreased such as preterm births by 22% [AAPC − 3.4% (95% CI − 7.8, − 1.2)], low birth weight (LBW) by 28.5% [AAPC − 4.7% (95% CI − 6.0, − 3.3)], and fetal distress by 64.2% [AAPC − 14.0% (95% CI − 17.8, − 10.0)] during 2011–2019. Both extremes of maternal age groups (18–20 years and 42–44 years) had a higher risk ratio for adverse perinatal outcomes including preterm birth, perinatal mortality, LBW, low ponderal index (LPI), low Apgar score, and congenital defect compared to the reference age group (30–32 years). A higher risk ratio for perinatal mortality, intrauterine growth restriction (IUGR), and fetal distress and a lower risk ratio for preterm births and LBW were observed in the period 2017–2019. Both the young cohort (1997–1999) and the old cohort (1976–1969) had a higher risk ratio for preterm birth, perinatal mortality, macrosomia, and congenital defect compared to the reference cohort (1982–1984). In conclusion, some of the adverse perinatal outcomes incidence significantly decreased in the last 9 years in Hubei. However, extremes of maternal age groups and both young and old cohorts were associated with a higher risk of preterm birth, perinatal mortality, and congenital defect.

Introduction: Hypoxia-inducible factor (HIF) prolyl hydroxylase domain (PHD) enzymes are major therapeutic targets of anemia and ischemic/hypoxia diseases. To overcome safety issues, liver failure, and problems associated with on-/off-targets, natural products due to their novel and unique structures offer promising alternatives as drug targets.Methods: In the current study, the Marine Natural Products, North African, South African, East African, and North-East African chemical space was explored for HIF-PHD inhibitors discovery through molecular search, and the final hits were validated using molecular simulation and free energy calculation approaches.Results: Our results revealed that CMNPD13808 with a docking score of −8.690 kcal/mol, CID15081178 with a docking score of −8.027 kcal/mol, CID71496944 with a docking score of −8.48 kcal/mol and CID11821407 with a docking score of −7.78 kcal/mol possess stronger activity than the control N-[(4-hydroxy-8-iodoisoquinolin-3-yl)carbonyl]glycine, 4HG (−6.87 kcal/mol). Interaction analysis revealed that the target compounds interact with Gln239, Tyr310, Tyr329, Arg383 and Trp389 residues, and chelate the active site iron in a bidentate manner in PHD2. Molecular simulation revealed that these target hits robustly block the PHD2 active site by demonstrating stable dynamics. Furthermore, the half-life of the Arg383 hydrogen bond with the target ligands, which is an important factor for PHD2 inhibition, remained almost constant in all the complexes during the simulation. Finally, the total binding free energy of each complex was calculated as CMNPD13808-PHD2 −72.91 kcal/mol, CID15081178-PHD2 −65.55 kcal/mol, CID71496944-PHD2 −68.47 kcal/mol, and CID11821407-PHD2 −62.06 kcal/mol, respectively.Conclusion: The results show the compounds possess good activity in contrast to the control drug (4HG) and need further in vitro and in vivo validation for possible usage as potential drugs against HIF-PHD2-associated diseases.

Therapeutic moieties derived from medicinal plants as well as plants-based ecofriendly processes for producing selenium nanoparticles have shown great promise in the management of type 2 diabetes mellitus (T2DM). The current study was aimed to assess the anti-diabetic potentials of Fagonia cretica mediated biogenic selenium nanoparticles (FcSeNPs) using in-vitro and in-vivo approaches. The bio-synthesized FcSeNPs were characterized using various techniques including UV–VIS spectrophotometry and FTIR analysis. The in-vitro efficacy of FcSeNPs were assessed against α-glucosidase, α-amylase enzymes as well as the anti-radical studies were performed using DPPH and ABTS free radicals scavenging assays. For in-vivo studies, 20 Male Balb/C albino-mice were randomly divided into 4 groups (n = 5) including normal group, disease group (Diabetic group with no treatment), control group and treatment group (Diabetic group treated with FcSeNPs). Further, biochemistry markers including pancreas, liver, kidney and lipid profile were assessed for all treatment groups. The FcSeNPs exhibited a dose-dependent inhibition against α-amylase and α-glucosidase at 62–1000 µg mL−1 concentration with IC50 values of 92 and 100 µg mL−1 respectively. In antioxidant experiments, the FcSeNPs demonstrated significant radicals scavenging effect against DPPH and ABTS radicals. In STZ-induced diabetic mice, a considerable decline in blood glucose level was observed after treatment with FcSeNPs. Anti-hyperglycemic effect of FcSeNPs treated animals were high (105 ± 3.22**) as compared to standard drug (128.6 ± 2.73** mg dL−1). Biochemical investigations revealed that all biochemical parameters for pancreas, liver function, renal function panel and lipid profile were significantly lowered in FcSeNPs treated animals. Our findings indicate a preliminary multi-target efficacy for FcSeNPs against type-2 diabetes and thus warrant further detailed studies.

Abstract Water constitutes ≈70–90% of the organism's body by mass and is highly important for its survival. Water contains a variety of chemical contaminants introduced by various sectors, resulting in contamination that has a direct impact on the ecosystem. Various approaches are in practice to tackle these issues. Among these, semiconductor photocatalysis appears to be the cutting‐edge technology for the degradation of wastewater contaminants. Herein, the fabrication of Fe3O4−SiO2 nanocomposite via facile co‐precipitation and Stober methods are reported. Various characterization techniques are employed for the structural elucidation, morphology, crystallinity, and stability of the as‐prepared composite. The nanocomposite is employed in catalytic and photocatalytic applications toward the removal of methylene blue (MB) and methyl orange (MO) dyes from a comparative perspective. It is observed that the composite can remove about 93% of MB and 51% of MO within 7 and 6 h, respectively. These findings indicate that the nanocomposite has a higher MB removal effectiveness than the MO. This trend can be accredited to the difference in the chemical structure of both dyes. The nanocomposite is also evaluated for antioxidant and antileishmanial activity, and it is shown to be quite effective even at very low concentrations.

Introduction: The current XBB variant of SARS-CoV-2 with the strongest immune escaping properties is currently the most dominant variant circulating around the world. With the emergence of XBB global morbidities and mortalities have raised again. In the current scenario, it was highly required to delineate the binding capabilities of NTD of XBB subvariant towards human neutralizing antibodies and to dig out the binding affinity of RBD of XBB subvariant with ACE2 receptor.Materials and Methods: The current study uses molecular interaction and simulation-based approaches to decipher the binding mechanism of RBD with ACE2 and mAb interaction with NTD of the spike protein.Results: Molecular docking of the Wild type NTD with mAb revealed a docking score of −113.2 ± 0.7 kcal/mol while XBB NTD docking with mAb reported −76.2 ± 2.3 kcal/mol. On the other hand, wild-type RBD and XBB RBD with ACE2 receptor demonstrated docking scores of −115.0 ± 1.5 kcal/mol and −120.8 ± 3.4 kcal/mol respectively. Moreover, the interaction network analysis also revealed significant variations in the number of hydrogen bonds, salt-bridges, and non-bonded contacts. These findings were further validated by computing the dissociation constant (KD). Molecular simulation analysis such as RMSD, RMSF, Rg and hydrogen bonding analysis revealed variation in the dynamics features of the RBD and NTD complexes due to the acquired mutations. Furthermore, the total binding energy for the wild-type RBD in complex with ACE2 reported −50.10 kcal/mol while XBB-RBD coupled with ACE2 reported −52.66 kcal/mol respectively. This shows though the binding of XBB is slightly increased but due to the variation in the bonding network and other factors makes the XBB variant to enter into the host cell efficiently than the wild type. On the other hand, the total binding free energy for the wildtype NTD-mAb was calculated to be −65.94 kcal/mol while for XBB NTD-mAb was reported to be −35.06 kcal/mol respectively. The significant difference in the total binding energy factors explains that the XBB variant possess stronger immune evasion properties than the others variants and wild type.Conclusions: The current study provides structural features for the XBB variant binding and immune evasion which can be used to design novel therapeutics.

Streptococcus gordonii is an oral bacterium colonizing the dental cavity and leading to plaque formation. This pervasive colonizer is also the etiologic agent of bacterial endocarditis and has a major role in infective endocarditis. The bacteria reach the heart through oral bleeding, leading to inflammation of cardiovascular valves. Over the past 50 years, it has shown a significant pathogenic role in immunocompromised and neutropenic patients. Since antibiotic resistance has created prophylaxis failure towards infective endocarditis, a potent therapeutic candidate is needed. Therefore, multi-epitopes vaccine offers advantages over the other approaches. Thus, herein, numerous molecular-omics tools were exploited to mine immunogenic peptides, i.e., T-cell and B-cell epitopes, and construct a vaccine sequence. Our findings revealed a total of 24 epitopes, including CTL, HTL, and B-cell are responsible for imparting immune responses, which were combined with the help of different linkers, and MEVC was constructed. Multifactorial validation of the candidate vaccine was performed to minimize the risk factors. The final sequence was docked with TLR2 to validate its conformation compatibility with receptor and long-term interactions stability. Our analysis revealed that the vaccine construct is immunogenic and non-allergenic. The construct also established various contacts with the immune receptor. Finally, the vaccine sequence was reverse-translated, optimized for codon usage, and analyzed for expression in the Escherichia coli K12 strain. Maximum expression was noted with a CAI score of 0.95. In silico immune simulation revealed that the antigen was neutralized on the 3rd day after injection. In conclusion, the current study warrants validation of the vaccine construct both in in vitro and in vivo models for accurate therapeutic intervention.

The SARS COV-2 and its variants are spreading around the world at an alarming speed, due to its higher transmissibility and the conformational changes caused by mutations. The resulting COVID-19 pandemic has imposed severe health consequences on human health. Several countries of the world including Pakistan have studied its genome extensively and provided productive findings. In the current study, the mCSM, DynaMut2, and I-Mutant servers were used to analyze the effect of identified mutations on the structural stability of spike protein however, the molecular docking and simulations approaches were used to evaluate the dynamics of the bonding network between the wild-type and mutant spike proteins with furin. We addressed the mutational modifications that have occurred in the spike protein of SARS-COV-2 that were found in 215 Pakistani's isolates of COVID-19 patients to study the influence of mutations on the stability of the protein and its interaction with the host cell. We found 7 single amino acid substitute mutations in various domains that reside in spike protein. The H49Y, N74K, G181V, and G446V were found in the S1 domain while the D614A, V622F, and Q677H mutations were found in the central helices of the spike protein. Based on the observation, G181V, G446V, D614A, and V622F mutants were found highly destabilizing and responsible for structural perturbation. Protein-protein docking and molecular simulation analysis with that of furin have predicted that all the mutants enhanced the binding efficiency however, the V622F mutant has greatly altered the binding capacity which is further verified by the KD value (7.1 E−14) and therefore may enhance the spike protein cleavage by Furin and increase the rate of infectivity by SARS-CoV-2. On the other hand, the total binding energy for each complex was calculated which revealed −50.57 kcal/mol for the wild type, for G181V −52.69 kcal/mol, for G446V −56.44 kcal/mol, for D614A −59.78 kcal/mol while for V622F the TBE was calculated to be −85.84 kcal/mol. Overall, the current finding shows that these mutations have increased the binding of Furin for spike protein and shows that D614A and V622F have significant effects on the binding and infectivity.

Electrical Power quality in distribution systems is crucial to both utility and consumers simultaneously. The main issue that affects the quality factor of electrical distribution systems is phase load imbalance. Phase imbalance is a major issue in distribution networks in Pakistan, India, the United States, China, and other nations and regions. The distribution system in Pakistan is normally a three-phase, four-wire system, whereas our residential and commercial loads are often single-phase, resulting in an unbalanced system. These unbalanced circumstances in the system result in single-phasing, overloading, and overheating situations, and the return of current to neutral, as well as increased power system investment and operational expenses. In this paper, several methodologies for phase balance are being studied. After researching several techniques of phase balancing and building on that methodology, a simulation prototype is developed, and different unbalanced situations are studied. To analyze unbalanced conditions in practical mode, a hardware prototype is developed on the basis of simulation. Examined some unbalanced loads on the simulation prototype and then on the hardware prototype and achieved the best possible load balancing on phases.

Among the different drug targets of SARS-CoV-2, a multi-domain protein known as NSP3 is a critical element of the translational and replication machinery. The macrodomain-I, in particular, has been reported to have an essential role in the viral attack on the innate immune response. In this study, we explore natural medicinal compounds and identify potential inhibitors to target the SARS-CoV-2–NSP3 macrodomain-I. Computational modeling and simulation tools were utilized to investigate the structural-dynamic properties using triplicates of 100 ns MD simulations. In addition, the MM/GBSA method was used to calculate the total binding free energy of each inhibitor bound to macrodomain-I. Two significant hits were identified: 3,5,7,4′-tetrahydroxyflavanone 3′-(4-hydroxybenzoic acid) and 2-hydroxy-3-O-beta-glucopyranosyl-benzoic acid. The structural-dynamic investigation of both compounds with macrodomain-I revealed stable dynamics and compact behavior. In addition, the total binding free energy for each complex demonstrated a robust binding affinity, of ΔG −61.98 ± 0.9 kcal/mol for Compound A, while for Compound B, the ΔG was −45.125 ± 2.8 kcal/mol, indicating the inhibitory potential of these compounds. In silico bioactivity and dissociation constant (KD) determination for both complexes further validated the inhibitory potency of each compound. In conclusion, the aforementioned natural products have the potential to inhibit NSP3, to directly rescue the host immune response. The current study provides the basis for novel drug development against SARS-CoV-2 and its variants.

Introduction: Coronavirus disease 2019 (COVID-19), caused by SARS-CoV-2, has had a disastrous effect worldwide during the previous three years due to widespread infections with SARS-CoV-2 and its emerging variations. More than 674 million confirmed cases and over 6.7 million deaths have been attributed to successive waves of SARS-CoV-2 infections as of 29th January 2023. Similar to other RNA viruses, SARS-CoV-2 is more susceptible to genetic evolution and spontaneous mutations over time, resulting in the continual emergence of variants with distinct characteristics. Spontaneous mutations of SARS-CoV-2 variants increase its transmissibility, virulence, and disease severity and diminish the efficacy of therapeutics and vaccines, resulting in vaccine-breakthrough infections and re-infection, leading to high mortality and morbidity rates.Materials and methods: In this study, we evaluated 10,531 whole genome sequences of all reported variants globally through a computational approach to assess the spread and emergence of the mutations in the SARS-CoV-2 genome. The available data sources of NextCladeCLI 2.3.0 (https://clades.nextstrain.org/) and NextStrain (https://nextstrain.org/) were searched for tracking SARS-CoV-2 mutations, analysed using the PROVEAN, Polyphen-2, and Predict SNP mutational analysis tools and validated by Machine Learning models.Result: Compared to the Wuhan-Hu-1 reference strain NC 045512.2, genome-wide annotations showed 16,954 mutations in the SARS-CoV-2 genome. We determined that the Omicron variant had 6,307 mutations (retrieved sequence:1947), including 67.8% unique mutations, more than any other variant evaluated in this study. The spike protein of the Omicron variant harboured 876 mutations, including 443 deleterious mutations. Among these deleterious mutations, 187 were common and 256 were unique non-synonymous mutations. In contrast, after analysing 1,884 sequences of the Delta variant, we discovered 4,468 mutations, of which 66% were unique, and not previously reported in other variants. Mutations affecting spike proteins are mostly found in RBD regions for Omicron, whereas most of the Delta variant mutations drawn to focus on amino acid regions ranging from 911 to 924 in the context of epitope prediction (B cell & T cell) and mutational stability impact analysis protruding that Omicron is more transmissible.Discussion: The pathogenesis of the Omicron variant could be prevented if the deleterious and persistent unique immunosuppressive mutations can be targeted for vaccination or small-molecule inhibitor designing. Thus, our findings will help researchers monitor and track the continuously evolving nature of SARS-CoV-2 strains, the associated genetic variants, and their implications for developing effective control and prophylaxis strategies.

Introduction: The perpetual appearance of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-COV-2), and its new variants devastated the public health and social fabric around the world. Understanding the genomic patterns and connecting them to phenotypic attributes is of great interest to devise a treatment strategy to control this pandemic.Materials and Methods: In this regard, computational methods to understand the evolution, dynamics and mutational spectrum of SARS-CoV-2 and its new variants are significantly important. Thus, herein, we used computational methods to screen the genomes of SARS-CoV-2 isolated from Pakistan and connect them to the phenotypic attributes of spike protein; we used stability-function correlation methods, protein-protein docking, and molecular dynamics simulation.Results: Using the Global initiative on sharing all influenza data (GISAID) a total of 21 unique mutations were identified, among which five were reported as stabilizing while 16 were destabilizing revealed through mCSM, DynaMut 2.0, and I-Mutant servers. Protein-protein docking with Angiotensin-converting enzyme 2 (ACE2) and monoclonal antibody (4A8) revealed that mutation G446V in the receptor-binding domain; R102S and G181V in the N-terminal domain (NTD) significantly affected the binding and thus increased the infectivity. The interaction pattern also revealed significant variations in the hydrogen bonding, salt bridges and non-bonded contact networks. The structural-dynamic features of these mutations revealed the global dynamic trend and the finding energy calculation further established that the G446V mutation increases the binding affinity towards ACE2 while R102S and G181V help in evading the host immune response. The other mutations reported supplement these processes indirectly. The binding free energy results revealed that wild type-RBD has a TBE of −60.55 kcal/mol while G446V-RBD reported a TBE of −73.49 kcal/mol. On the other hand, wild type-NTD reported −67.77 kcal/mol of TBE, R102S-NTD reported −51.25 kcal/mol of TBE while G181V-NTD reported a TBE of −63.68 kcal/mol.Conclusions: In conclusion, the current findings revealed basis for higher infectivity and immune evasion associated with the aforementioned mutations and structure-based drug discovery against such variants.

In the past few years, various somatic point mutations of isocitrate dehydrogenase (IDH) encoding genes (IDH1 and IDH2) have been identified in a broad range of cancers, including glioma. Despite the important function of IDH1 in tumorigenesis and its very polymorphic nature, it is not yet clear how different nsSNPs affect the structure and function of IDH1. In the present study, we employed different machine learning algorithms to screen nsSNPs in the IDH1 gene that are highly deleterious. From a total of 207 SNPs, all of the servers classified 80 mutations as deleterious. Among the 80 deleterious mutations, 14 were reported to be highly destabilizing using structure-based prediction methods. Three highly destabilizing mutations G15E, W92G, and I333S were further subjected to molecular docking and simulation validation. The docking results and molecular simulation analysis further displayed variation in dynamics features. The results from molecular docking and binding free energy demonstrated reduced binding of the drug in contrast to the wild type. This, consequently, shows the impact of these deleterious substitutions on the binding of the small molecule. PCA (principal component analysis) and FEL (free energy landscape) analysis revealed that these mutations had caused different arrangements to bind small molecules than the wild type where the total internal motion is decreased, thus consequently producing minimal binding effects. This study is the first extensive in silico analysis of the IDH1 gene that can narrow down the candidate mutations for further validation and targeting for therapeutic purposes.

Non-obstructive azoospermia (NOA) is a severe factor of male infertility; it affects approximately 1% of the global male population and accounts for 40% of male infertility cases. However, the majority of NOA cases remain idiopathic. This is the first study using whole-exome sequencing (WES) to identify a novel missense mutation in the DND1 gene (c.212A>C, p. E71A) from a Pakistani family, that includes three males with NOA. This mutation is predicted to cause DND1 protein misfolding and weaken the DND1 interaction with NANOS2, a significant regulator in primordial germ cell development. Our study identified a DND1 pathogenic mutation in NOA patients and highlighted its critical role in male fertility in humans.

Cyclin-dependent kinase 2 (CDK2) is a promising target for cancer treatment, developing new effective CDK2 inhibitors is of great significance in anticancer therapy. The involvement of CDK2 in tumorigenesis has been debated, but recent evidence suggests that specifically inhibiting CDK2 could be beneficial in treating certain tumors. This approach remains attractive in the development of anticancer drugs. Several small-molecule inhibitors targeting CDK2 have reached clinical trials, but a selective inhibitor for CDK2 is yet to be discovered. In this study, we conducted machine learning-based drug designing to search for a drug candidate for CDK2. Machine learning models, including k-NN, SVM, RF, and GNB, were created to detect active and inactive inhibitors for a CDK2 drug target. The models were assessed using 10-fold cross-validation to ensure their accuracy and reliability. These methods are highly suitable for classifying compounds as either active or inactive through the virtual screening of extensive compound libraries. Subsequently, machine learning techniques were employed to analyze the test dataset obtained from the zinc database. A total of 25 compounds with 98% accuracy were predicted as active against CDK2. These compounds were docked into CDK2’s active site. Finally, three compounds were selected based on good docking score, and, along with a reference compound, underwent MD simulation. The Gaussian naïve Bayes model yielded superior results compared to other models. The top three hits exhibited enhanced stability and compactness compared to the reference compound. In conclusion, our study provides valuable insights for identifying and refining lead compounds as CDK2 inhibitors.

Groundwater heavy metal pollution is a major concern all around the world. For the assessment of heavy metals and physico-chemical characteristics, groundwater samples were collected from different locations of the Karak District, Pakistan. With the help of the global information system device (GIS), groundwater samples were collected and studied from 47 locations. The present study focused on the water table (WT), water source depth (WSD), pH, electrical conductivity (EC), dissolved oxygen (DO), total dissolved solids (TDS), lead (Pb(II)), silver (Ag(I)), iron (Fe(II)) and chromium (Cr(VI)) parameters. Heavy metals were analyzed by the Atomic Absorption Spectrophotometer (AAS). The Pearsonâs matrix of correlation showed relationships between several parameters, such as the EC and the TDS which had close interactions between all the three different groundwater samples (collected by hand pump (HP), bore holes (BH) and tube wells (TW)). The strong correlation was detected in all the sources of water between the TDS and the EC, the regression coefficient (r) of which was 1. In the hierarchical clustering (by dendrograms) the HP samples show two clusters: Cluster 1 contains seven parameters and Cluster 2 has four parameters. The BH samples have two clusters: Cluster 1 contains three parameters and Cluster 2 has eight parameters. The TW dendrogram also shows two clusters: Cluster 1 contains six parameters while Cluster 2 has five parameters.