Search

Possessing variable valence states, the element Arsenic (As) is intimidating the quality of the ecology and human health severely. In this study, eliminating As (III) from water-based solutions with great efficiency was done using Bagasse-Mn-Al, a sugarcane bagasse-derived biochar impregnated with Mn and Al. The Bagasse-Mn-Al composite yielded higher removal efficiency towards As (III) than the biochar itself. About 89.53 % of As (III) was removed within 65 min maintaining the very first concentration of As (III) at 400 μg/L, initial pH at 2–2.5, and adsorbent dosage at 0.625 g/L. The Bagasse-Mn-Al composite showed an adsorption potential maximum of 54.945 mg/g which is superior to most of the cheaply synthesized metal-impregnated biochar reported. Results from a variety of characterization techniques indicated that the •OH free radical in the Bagasse-Mn-Al composite mainly contributed to the removal of As (III) where oxidation and complexation were the major mechanisms. With high catalytic efficiency, this cost effectively produced metal-coated biochar showed easy and effective separation of As (III) from aqueous solution. Further, this study focuses on the high potential of Bagasse-Mn-Al adsorbent in the treatment of both ground and wastewater.

Highly bismuth-substituted iron garnet thin films are prepared on quartz substrates by using a radio frequency (RF) magnetron sputtering technique. We study the factors (process parameters associated with the RF magnetron sputter deposition technique) affecting the magneto-optical (MO) properties of ferrite garnet films of composition Bi2.1Dy0.9Fe3.9Ga1.1O12. All films show high MO response across the visible range of wavelengths after being annealed. In particular, the effects of substrate stage temperature and rotation rate on the various properties of films are studied. Experimental results reveal that the characteristics of garnet films of this type can be tuned and optimized for use in various magnetic field-driven nanophotonics and integrated optics devices, and that, at a substrate stage rotation rate near 16 revolutions per minute, the MO quality of the developed MO films is the best, in comparison with films deposited at other rotation rates. To the best of our knowledge, this is the first report on the effects of deposition parameters on the properties of garnet films of this stoichiometry.

The spectral properties of the transverse magneto-optical Kerr effect (TMOKE) in periodic metal–dielectric hybrid structures are studied, in particular with respect to the achievable magnitude. It is shown that the TMOKE is sensitive to the magneto-optical activity of the bismuth-substituted rare-earth iron garnet, which is used as a dielectric material in the investigated structures. For samples with larger Bi substitution level and, consequently, larger gyration constant, the magnitude of the TMOKE increases and reaches 13% in the case of a Bi _1.8 Lu _1.2 Fe _3.6 Al _1.4 O _12 magnetic film. Further, it is demonstrated that the TMOKE vanishes at the high-symmetry points of the Brillouin zone (at the Γ and X points). The main enhancement of the TMOKE takes place near the resonances of the surface plasmon polaritons (SPPs) at the metal/magnetic–dielectric interface. However, near the degenerate resonances of the SPPs at the air/metal and metal/magnetic–dielectric interfaces the TMOKE is increased by the air/metal SPPs as well. This phenomenon is explained in terms of a coupled oscillator model.

The microgrid (MG) faces significant security issues due to the two-way power and information flow. Integrating an Energy Management System (EMS) to balance energy supply and demand in Malaysian microgrids, this study designs a Fuzzy Logic Controller (FLC) that considers intermittent renewable sources and fluctuating demand patterns. FLC offers a flexible solution to energy scheduling effectively assessed by MATLAB/Simulink simulations. The microgrid consists of PV, battery, grid, and load. A Maximum Power Point Tracking (MPPT) controller helps to extract the maximum PV output and manages the power storage by providing or absorbing excess power. System analysis is performed by observing the State of Charge (SoC)of the battery and output power for each source. The grid supplies additional power if the battery and PV fail to meet the load demand. Total Harmonic Distortion (THD) analysis compares the performance of the Proportional-Integral Controller (PIC) and FLC. The results show that the PI controller design reduces the THD in the current signal, while FLC does not reduce the THD of the grid current when used in the EMS. However, FLC offers better control over the battery's SOC, effectively preventing overcharging and over-discharging. While PI reduces THD, FLC provides superior SOC control in a system comprising PV, battery, grid, and load. The findings demonstrate that the output current is zero when the SOC is higher than 80% or lower than 20%, signifying that no charging or discharging takes place to avoid overcharging and over-discharging. The third goal was accomplished by comparing and confirming that the grid current's THD for the EMS designed with both the PI Controller and the FLC is maintained below 5%, following the IEEE 519 harmonic standard, using the THD block in MATLAB Simulink. This analysis highlights FLC's potential to address demand-supply mismatches and renewable energy variability, which is crucial for optimizing microgrid performance., Competing Interests: Declarations. Competing interests: The authors declare no competing interests., (© 2025. The Author(s).)

Despite potential contamination, tap water remains the primary source of drinking in megacities. However, the sources of heavy metal(oid)s contamination and associated health hazards have not been thoroughly addressed in many developing cities, including Dhaka. Therefore, we made the first attempt to assess tap water quality in Dhaka City using indices, identify pollution sources with state-of-the-art techniques, and quantify associated health risks. Tap water samples from 35 locations were collected and analyzed for physicochemical properties and heavy metal(loid)s concentrations. While most parameters were within acceptable ranges, Hg (1.18 ± 0.15 µg/L) exceeded safety thresholds with concerns for Mn (51.08 ± 2.3 µg/L) and Fe (177.34 ± 5.6 µg/L). The calculated indices indicated that Dhaka City's tap water ranged from unfit (Heavy Metal Evaluation Index, HEI: 2.61), very poor (Heavy Metal Pollution Index, HPI: 95.67, Water Quality Index, WQI: 37.76), moderately affected (Metal Index, MI: 2.61, Synthetic Pollution Index, SPI: 0.96) to slightly polluted (Single-factor Index, Pij: 2.61, Nemerow Pollution Index, NPI: 1.41), healthy but not tasty (Taste Index, TI: 1.8, Health Index, HtI: 10.41), with Matuail, followed by Jurain, being the most contaminated. Non-carcinogenic health risk (NCR) values revealed that children were twice as susceptible to health risks from Pb, Co, and As. Alongside, Carcinogenic health hazards risk (CR) expressed potential cancer risks from Cr

Cardiovascular arrhythmia, characterized by irregular heart rhythms, poses significant health risks, including stroke and heart failure, making accurate and early detection critical for effective treatment. Traditional detection methods often struggle with challenges such as imbalanced datasets, limiting their ability to identify rare arrhythmia types. This study proposes a novel hybrid approach that integrates ConvNeXt-X deep learning models with advanced data balancing techniques to improve arrhythmia classification accuracy. Specifically, we evaluated three ConvNeXt variants-ConvNeXtTiny, ConvNeXtBase, and ConvNeXtSmall-combined with Random Oversampling (RO) and SMOTE-TomekLink (STL) on the MIT-BIH Arrhythmia Database. Experimental results demonstrate that the ConvNeXtTiny model paired with STL achieved the highest accuracy of 99.75%, followed by ConvNeXtTiny with RO at 99.72%. The STL technique consistently enhanced minority class detection and overall performance across models, with ConvNeXtBase and ConvNeXtSmall achieving accuracies of 99.69% and 99.72%, respectively. These findings highlight the efficacy of ConvNeXt-X models, when coupled with robust data balancing techniques, in achieving reliable and precise arrhythmia detection. This methodology holds significant potential for improving diagnostic accuracy and supporting clinical decision-making in healthcare., Competing Interests: Declarations. Competing interests: The authors have no conflicts of interest to declare that they are relevant to the content of this article., (© 2024. The Author(s).)

Given the increasing effectiveness of immune-based therapies, management of their associated toxicities is of utmost importance. Cytokine release syndrome (CRS), characterized by elevated levels of cytokine, poses a significant challenge following the administration of antibodies and CAR-T cell therapies. CRS also contributes to multiple organ dysfunction in severe viral infections, notably in COVID-19. Given the pivotal role of IL-6 cytokine in initiating CRS, it has been considered a most potential therapeutic target to mitigate hyperactivated immune responses. While monoclonal antibodies of IL-6 show promise in mitigating cytokine storm, concerns about immunotoxicity persist, and small molecule IL-6 antagonists remain unavailable. The present study employed sophisticated computational techniques to identify potential hit compounds as IL-6 inhibitors, with the aim of inhibiting IL-6/IL-6R protein-protein interactions. Through ligand-based pharmacophore mapping and shape similarity in combination with docking-based screening, we identified nine hit compounds with diverse chemical scaffolds as potential binders of IL-6. Further, the MD simulation of 300 ns of five virtual hits in a complex with IL-6 was employed to study the dynamic behavior. To provide a more precise prediction, binding free energy was also estimated. The identified compounds persistently interacted with the residues lining the binding site of the IL-6 protein. These compounds displayed low binding energy during MMPBSA calculations, substantiating their strong association with IL-6. This study suggests promising scaffolds as potential inhibitors of IL-6/IL-6R protein-protein interactions and provides direction for lead optimization., Competing Interests: Declarations. Competing interests: The authors report there are no competing interests to declare., (© 2024. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

The multifaceted impact of IL-1β has been proposed to have a central role in a spectrum of immunological responses spanning physiological reactions to aggressive inflammatory reactions and autoimmune disorders. Once IL-1β binds to its cognate receptor it initiates IL-1R1/TLR4 signaling cascade, leading to transcriptional modifications that sustain the inflammatory response. Extensive structural and functional investigations on IL-1β have yielded various inhibitors aimed at disrupting the formation of ligand receptor complex. Unfortunately, most have proven unsuccessful in clinical trials. Therefore, directing efforts towards IL-1β/IL-1R1 presents a unique opportunity to formulate an alternative therapy for the treatment of inflammatory disorders. In view of this, the present study aimed to identify small molecules obstructing protein-protein interactions (PPIs) to impede heterocomplex formation. In this context, a search query was formulated by integrating a ligand-based pharmacophore mapping alongside a multi-stage molecular docking to assess the potential of the predicted hits in terms of binding modes within the targeted cavity of the IL-1β and the associated binding affinities. Thus, via a stepwise screening process starting from an initial pool of 40,000 compounds, 8 potential hits were identified for detailed atomic studies employing molecular dynamic simulation encompassing a total time frame of 0.9 μs. The investigation in dynamic behavior was followed by the estimation of free energies using molecular mechanics Poisson-Boltzmann surface area (MM/PBSA) calculations. The stability matrices revealed that the chosen virtual hits possess a notable potential to hinder the complex formation between IL-1β/IL-1RI. The average backbone deviations recorded for the conformational ensembles of the ligand free IL-1β/IL-1RI exhibited significant dynamics, featuring the average value of 0.35 nm. Conversely, the identified hits particularly, inhouse-2603 and inhouse-1325 demonstrated a high degree of stability with mean values of 0.32 ± 0.05, 0.31 ± 0.03, respectively. The residue-wise fluctuations were maximum for Compound-1303, with the mean value of 0.31 nm and minimal for Compound-2691 with the mean value 0.21 nm. The MMPBSA revealed the highest binding energy of -89.50 ± 10.63, and -81.32 ± 14.9 kcal/mol, for the IL-1β/IL-1RI complex with compound-2603, and Compound-1325 respectively. The principal component analysis (PCA) in conjunction with free energy landscape (FEL) further shed light on the conformational space in terms of energetic stability. Considering the essential role of IL-1β in mediating several inflammatory cascades, it is proposed that the identified PPI inhibitors since demonstrated stable behavior and promising attributes in regard to inhibitory potential as outlined by mechanistic exploration, may serve as new chemotypes for the future exploration aimed at mitigation inflammatory disorders., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Inc. All rights reserved.)

A wealth of literature has highlighted the discovery of various immune modulators, frequently used in clinical practice, yet associated with numerous drawbacks. In light of this pharmacological deficiency, medical scientists are motivated to develop new immune modulators with minimized adverse effects yet retaining the improved therapeutic potential. T-cell differentiation and growth are central to human defense and are regulated by interleukin-2 (IL-2), an immune-modulatory cytokine. However, scientific investigation is hindered due to its flat binding site and widespread hotspot residues. In this regard, a prompt and logical investigation guided by integrated computational techniques was undertaken to unravel new and potential leads against IL-2. In particular, the combination of score-based and pharmacophore-based virtual screening approaches were employed, reducing the data from millions of small molecules to a manageable number. Subsequent docking and 3D-QSAR prediction via CoMFA further helped remove false positives from the data. The reliability of the model was assessed via standard metrics, which explain the model's fitness and the robustness of the model in predicting the activity of new compounds. The extensive virtual screening herein led to the identification of a total of 24 leads with potential anti-IL-2 activity. Furthermore, the theoretical findings were corroborated with in vitro testing, further endorsing the anti-inflammatory potential of the identified leads., Competing Interests: Declarations. Conflict of interest: All authors and co-authors agree with the statement that there is no conflict of interest among them., (© 2023. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

The use of nanosized particles is becoming more popular for the topical treatment of skin conditions. In this research work, we created and investigated the effects of solid lipid nanoparticles (SLN) containing hyaluronic acid and tretinoin. Solvent emulsification diffusion method was used to prepare the SLN formulation and characterized for their physicochemical properties. Fourier transform infrared spectroscopy was used to confirm that hyaluronic acid and tretinoin were incorporated in the SLN. Furthermore, X-ray diffractogram, thermal analysis including DSC and TGA and in vitro dissolution, permeation tests were also performed along with microbial assessment. Clinical studies in human were performed to evaluate the effect of the SLN on skin wrinkles. The SLN was 750 ± 31.29 nm in size, with a zeta potential of 13.07 ± 0.75 mV and a narrow polydispersity index of 0.24 ± 0.12. The entrapment efficiency of tretinoin was found to be 90.07 ± 4.79%. Clinical studies in healthy human volunteers demonstrated that 90% of the tested individuals had improved skin conditions (reduction in wrinkles), by at least one grade after 4 weeks of treatment. Regarding the development on SLN, it was found that the internal phase concentration did not considerably affect the physicochemical and microbiological properties. Therefore, Hyaluronic acid has potential for the development of SLN applicable to cosmetic formulations, especially for skin. These findings show that the developed SLN have potential for use as cosmetics in the future., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Mehmood, Shahid, Rizvi, Jamshaid, Arshad, Nur-e-Alam, Hussain and Kazi.)

The present study deals with the in-silico analyses of several flavonoid derivatives to explore COVID-19 through pharmacophore modelling, molecular docking, molecular dynamics, drug-likeness, and ADME properties. The initial literature study revealed that many flavonoids, including luteolin, quercetin, kaempferol, and baicalin may be useful against SARS β-coronaviruses, prompting the selection of their potential derivatives to investigate their abilities as inhibitors of COVID-19. The findings were streamlined using in silico molecular docking, which revealed promising energy-binding interactions between all flavonoid derivatives and the targeted protein. Notably, compounds 8, 9, 13, and 15 demonstrated higher potency against the coronavirus Mpro protein (PDB ID 6M2N). Compound 8 has a -7.2 Kcal/mol affinity for the protein and binds to it by hydrogen bonding with Gln192 and π-sulfur bonding with Met-165. Compound 9 exhibited a significant interaction with the main protease, demonstrating an affinity of -7.9 kcal/mol. Gln-192, Glu-189, Pro-168, and His-41 were the principle amino acid residues involved in this interaction. The docking score for compound 13 is -7.5 Kcal/mol, and it binds to the protease enzyme by making interactions with Leu-41, π-sigma, and Gln-189. These interactions include hydrogen bonding and π-sulfur. The major protease and compound 15 were found to bind with a favourable affinity of -6.8 Kcal/mol. This finding was further validated through molecular dynamic simulation for 1ns, analysing parameters such as RMSD, RMSF, and RoG profiles. The RoG values for all four of the compounds varied significantly (35.2-36.4). The results demonstrated the stability of the selected compounds during the simulation. After passing the stability testing, the compounds underwent screening for ADME and drug-likeness properties, fulfilling all the necessary criteria. The findings of the study may support further efforts for the discovery and development of safe drugs to treat COVID-19.

Despite the waning threat of the COVID-19 pandemic, its detrimental impact on global health persists. Regardless of natural immunity or immunity obtained through vaccination, emerging variants of the virus continue to undergo mutations and propagate globally. The persistent mutations in SARS-CoV-2, along with the subsequent formation of recombinant sub-variants has become a challenge for researchers and health professionals, raising concerns about the efficacy of current vaccines. Gaining a better understanding of the biochemical interactions between the Spike Protein (RBD) of SARS-CoV-2 variants and the human ACE2 receptor can prove to be beneficial in designing and developing antiviral therapeutics that are equally effective against all strains and emerging variants. Our objective in this study was to investigate the interfacial binding pattern of the SARS-CoV-2 RBD-ACE2 complex of the Wild Type (WT), Omicron, and the Omicron recombinant sub-variant XBB.1.16. We aimed to examine the atomic level factors and observe how mutations influence the interaction between the virus and its host using Molecular Dynamics simulation, MM/GBSA energy calculations, and Principal Component Analysis. Our findings reveal a higher degree of structural deviation and flexibility in XBB.1.16 compared to WT and Omicron. PCA indicated a wider cluster and significant flexibility in the movements of XBB.1.16 which can also be observed in free energy landscapes, while the normal mode analysis revealed converging motions within the RBD-ACE2 complexes which can facilitate the interaction between them. A pattern of decreased binding affinity was observed in case of XBB.1.16 when compared to the WT and Omicron. These observed deviations in XBB.1.16 when compared to its parent lineage Omicron, and WT can be attributed to the mutations specific to it. Collectively, these results enhance our understanding of the impact of mutations on the interaction between this strain and the host, taking us one step closer to designing effective antiviral therapeutics against the continually mutating strains., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Perovskite solar cells (PSCs) hold potential for low-cost, high-efficiency solar energy, but their sensitivity to moisture limits practical application. Current fabrication requires controlled environments, limiting mass production. Researchers aim to develop stable PSCs with longer lifetimes under ambient conditions. In this research work, we investigated the stability of perovskite films and solar cells fabricated and annealed in natural air using four different anti-solvents: toluene, ethyl acetate, diethyl ether, and chlorobenzene. Films (about 300 nm thick) were deposited via single-step spin-coating and subjected to ambient air-atmosphere for up to 30 days. We monitored changes in crystallinity, electrical properties, and optics over time. Results showed a gradual degradation in the films' crystallinity, morphology, and electro-optical properties. Notably, films made with ethyl acetate exhibited superior stability compared to other solvents. These findings contribute to advancing stable and high-performance PSCs manufactured under normal ambient conditions. In addition, we also discuss the possible machine learning (ML) approach to our future work direction to optimize the materials structures, and synthesis process parameters for future high-efficient perovskite solar cells fabrication., (© 2024. The Author(s).)

Phosphoinositide 3-kinase alpha (PI3Kα) is one of the most frequently dysregulated kinases known for their pivotal role in many oncogenic diseases. While the side effects linked to existing drugs against PI3Kα-induced cancers provide an avenue for further research, the significant structural conservation among PI3Ks makes it extremely difficult to develop new isoform-selective PI3Kα inhibitors. Embracing this challenge, we herein designed a hybrid protocol by integrating machine learning (ML) with in silico drug-designing strategies. A deep learning classification model was developed and trained on the physicochemical descriptors data of known PI3Kα inhibitors and used as a screening filter for a database of small molecules. This approach led us to the prediction of 662 compounds showcasing appropriate features to be considered as PI3Kα inhibitors. Subsequently, a multiphase molecular docking was applied to further characterize the predicted hits in terms of their binding affinities and binding modes in the targeted cavity of the PI3Kα. As a result, a total of 12 compounds were identified whereas the best poses highlighted the efficiency of these ligands in maintaining interactions with the crucial residues of the protein to be targeted for the inhibition of associated activity. Notably, potential activity of compound 12 in counteracting PI3Kα function was found in a previous in vitro study. Following the drug-likeness and pharmacokinetic characterizations, six compounds (compounds 1, 2, 3, 6, 7, and 11) with suitable ADME-T profiles and promising bioavailability were selected. The mechanistic studies in dynamic mode further endorsed the potential of identified hits in blocking the ATP-binding site of the receptor with higher binding affinities than the native inhibitor, alpelisib (BYL-719), particularly the compounds 1, 2, and 11. These outcomes support the reliability of the developed classification model and the devised computational strategy for identifying new isoform-selective drug candidates for PI3Kα inhibition., (© 2024. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Introduction: The Macrophage Migration Inhibitory Factor (MIF), a key pro-inflammatory mediator, is responsible for modulating immune responses. An array of inflammatory and autoimmune diseases has been linked to the dysregulated activity of MIF. The significance in physiological as well as pathophysiological phenomena underscores the potential of MIF as an attractive target with pharmacological relevance. Extensive research in past has uncovered a number of inhibitors, while the ISO-1, or (S, R)-3-(4-hydroxyphenyl)-4,5-dihydro-5-isoxazole acetic acid methyl ester being recognized as a benchmark standard so far. Recent work by Yang and coworkers identified five promising dietary flavonoids, with superior activity compared to the standard ISO-1. Nevertheless, the exact atomic-level inhibitory mechanism is still elusive. Methods: To improve the dynamic research, and rigorously characterize, and compare molecular signatures of MIF complexes with ISO-1 and flavonoids, principal component analysis (PCA) was linked with molecular dynamics (MD) simulations and binding free energy calculations. Results: The results suggest that by blocking the tautomerase site these small molecule inhibitors could modify the MIF activity by disrupting the intrinsic dynamics in particular functional areas. The stability matrices revealed the average deviation values ranging from 0.27-0.32 nm while the residue level fluctuations indicated that binding of the selected flavonoids confer enhanced stability relative to the ISO-1. Furthermore, the gyration values extracted from the simulated trajectories were found in the range of 1.80-1.83 nm. Discussion: Although all the tested flavonoids demonstrated remarkable results, the one obtained for the potent inhibitors, particularly Morin and Amentoflavone exhibited a good correlation with biological activity. The PCA results featured relatively less variance and constricted conformational landscape than others. The stable ensembles and reduced variation in turns might be the possible reasons for their outstanding performance documented previously. The results from the present exploration provide a comprehensive understanding of the molecular complexes formed by flavonoids and MIF, shedding light on their potential roles and impacts. Future studies on MIF inhibitors may benefit from the knowledge gathered from this investigation., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Siddiqui, Mushtaq, Sardar, Atta, Nur-e-Alam, Ahmad and Ul-Haq.)

Cyclin-dependent kinase 2 (CDK2) regulates cell cycle checkpoints in the synthesis and mitosis phases and plays a pivotal role in cancerous cell proliferation. The activation of CDK2, influenced by various protein signaling pathways, initiates the phosphorylation process. Due to its crucial role in carcinogenesis, CDK2 is a druggable hotspot target to suppress cancer cell proliferation. In this context, several studies have identified spirooxindoles as an effective class of CDK2 inhibitors. In the present study, three spirooxindoles (SOI1, SOI2, and SOI3) were studied to understand their inhibitory mechanism against CDK2 through a structure-based approach. Molecular docking and molecular dynamics (MD) simulations were performed to explore their interactions with CDK2 at the molecular level. The calculated binding free energy for the spirooxindole-based CDK2 inhibitors aligned well with experimental results regarding CDK2 inhibition. Energy decomposition (ED) analysis identified key binding residues, including I10, G11, T14, R36, F82, K89, L134, P155, T158, Y159, and T160, in the CDK2 active site and T-loop phosphorylation. Molecular mechanics (MM) energy was identified as the primary contributor to stabilizing inhibitor binding in the CDK2 protein structure. Furthermore, the analysis of binding affinity revealed that the inhibitor SOI1 binds more strongly to CDK2 compared to the other inhibitors under investigation. It demonstrated a robust interaction with the crucial residue T160 in the T-loop phosphorylation site, responsible for kinase activation. These insights into the inhibitory mechanism are anticipated to contribute to the development of potential CDK2 inhibitors using the spirooxindole scaffold.

Peroxisome proliferator-activated receptor gamma (PPAR-γ) serves as a nuclear receptor with a pivotal function in governing diverse facets of metabolic processes. In diabetes, the prime physiological role of PPAR-γ is to enhance insulin sensitivity and regulate glucose metabolism. Although PPAR-γ agonists such as Thiazolidinediones are effective in addressing diabetes complications, it is vital to be mindful that they are associated with substantial side effects that could potentially give rise to health challenges. The recent surge in the discovery of selective modulators of PPAR-γ inspired us to formulate an integrated computational strategy by leveraging the promising capabilities of both machine learning and in silico drug design approaches. In pursuit of our objectives, the initial stage of our work involved constructing an advanced machine learning classification model, which was trained utilizing chemical information and physicochemical descriptors obtained from known PPAR-γ modulators. The subsequent application of machine learning-based virtual screening, using a library of 31,750 compounds, allowed us to identify 68 compounds having suitable characteristics for further investigation. A total of four compounds were identified and the most favorable configurations were complemented with docking scores ranging from -8.0 to -9.1 kcal/mol. Additionally, the compounds engaged in hydrogen bond interactions with essential conserved residues including His323, Leu330, Phe363, His449 and Tyr473 that describe the ligand binding site. The stability indices investigated herein for instance root-mean-square fluctuations in the backbone atoms indicated higher mobility in the region of orthosteric site in the presence of agonist with the deviation peaks in the range of 0.07-0.69 nm, signifying moderate conformational changes. The deviations at global level revealed that the average values lie in the range of 0.25-0.32 nm. In conclusion, our identified hits particularly, CHEMBL-3185642 and CHEMBL-3554847 presented outstanding results and highlighted the stable conformation within the orthosteric site of PPAR-γ to positively modulate the activity., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Bangladesh is currently experiencing significant infrastructural development in road networking system through the construction or reconstruction of multiple roads and highways. Consequently, there is a rise in traffic intensity on roads and highways, along with a significant contamination of adjacent agricultural soils with heavy metals. The purpose of this study was to evaluate the ecological risk, health risk and the abundance of seven heavy metals (Cu, Mn, Pb, Cd, Cr, As, and Ni) in three distance gradients (0, 300, and 500 m) of agricultural soil along the Dhaka-Chattogram highway. The concentration of heavy metals was measured with an Atomic Absorption Spectrophotometer (AAS) on a total of 36 soil samples that were taken from 12 different sampling sites. Based on the findings, Cd had a high contamination factor for all distance gradients, whereas Cr had a moderate contamination factor in 67% of the study areas. According to the Pollution Load Index (PLI), Cd, Cr, and Pb were the predominant pollutants. Principal component analysis (PCA) result shows these metals mainly came from anthropogenic sources. The considerable positive correlations between Cu-Pb, Cu-Cd, Pb-Cd, and Cr-Ni all pointed to shared anthropogenic origins. As per Potential Ecological Risk Assessment (PERI) analysis, Pb, Cd, Cr, and Ni each contribute significantly and pose a moderate threat. The Target Hazard Quotient (THQ) values for all pathways of exposure to Pb and Cr in soils were more than 1, which would pose a significant risk to human health in the following order: THQ adult female  > THQ adult male  > THQ children . This study will help to evaluate the human health risk and develop a better understanding of the heavy metal abundance scenario in the agricultural fields adjacent to this highway., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Inc. All rights reserved.)

The intriguing optoelectronic properties, diverse applications, and facile fabrication techniques of perovskite materials have garnered substantial research interest worldwide. Their outstanding performance in solar cell applications and excellent efficiency at the lab scale have already been proven. However, owing to their low stability, the widespread manufacturing of perovskite solar cells (PSCs) for commercialization is still far off. Several instability factors of PSCs, including the intrinsic and extrinsic instability of perovskite materials, have already been identified, and a variety of approaches have been adopted to improve the material quality, stability, and efficiency of PSCs. In this review, we have comprehensively presented the significance of band gap tuning in achieving both high-performance and high-stability PSCs in the presence of various degradation factors. By investigating the mechanisms of band gap engineering, we have highlighted its pivotal role in optimizing PSCs for improved efficiency and resilience., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (This journal is © The Royal Society of Chemistry.)

Imidazoles and phenylthiazoles are an important class of heterocycles that demonstrate a wide range of biological activities against various types of cancers, diabetes mellitus and pathogenic microorganisms. The heterocyclic structure having oxothiazolidine moiety is an important scaffold present in various drugs, with potential for enzyme inhibition. In an effort to discover new heterocyclic compounds, we synthesized 26 new 4,5-diphenyl-1H-imidazole, phenylthiazole, and oxothiazolidine heterocyclic analogues that demonstrated potent α-glucosidase inhibition and anticancer activities. Majority of the compounds noncompetitively inhibited α-glucosidase except for two that exhibited competitive inhibition of the enzyme. Docking results suggested that the noncompetitive inhibitors bind to an apparent allosteric site on the enzyme located in the vicinity of the active site. Additionally, the analogues also exhibited significant activity against various types of cancers including non-small lung cancer. Since tubulin protein plays an important role in the pathogenesis of non-small lung cancer, molecular docking with one of the target compounds provided important clues to its binding mode. The current work on imidazoles and phenylthiazole derivatives bears importance for designing of new antidiabetic and anticancer drugs., (© 2024 Wiley-VHCA AG, Zurich, Switzerland.)

The purpose of this research work is to evaluate the degree of eight heavy metals (Fe, Mn, Cu, Zn, Cd, Pb, Cr, and Ni) contamination and health risks of three regularly consumed vegetables (papaya, bottle gourd, and esculent) near one of Bangladesh's busiest roadways, the Dhaka-Mymensingh highway. The heavy metal concentrations in 45 vegetable samples were analyzed using an atomic absorption spectrometer (AAS). These samples were collected from five different sampling sites based on various land use patterns adjacent to the highway. The average concentrations (mg/kg) of Cu, Fe, Mn, Zn, Cr, and Ni were found to be 9.86, 246.8, 16.9, 28.0, 9.02, and 2.02, respectively, for papaya; 14.9, 281.2, 387.6, 49.0, 10.1, and 2.92, respectively, for bottle gourd; and 17.6, 183.4, 107.2, 80.7, 7.98, and 2.34, respectively, for esculent. The mean concentrations of Cr, Zn, and Mn in papaya, bottle gourd, and esculent were higher than the acceptable limit. Correlation analysis revealed a significant positive correlation between Fe-Cu, Zn-Fe, Cu-Fe, and Fe-Zn in papaya; Cu-Zn, Fe-Cr, Zn-Ni, and Cr-Fe in bottle gourd; and Mn-Cr, Mn-Ni, Mn-Fe, and Cr-Ni in esculent, thereby indicating their common anthropogenic sources like agricultural activities, waste from the commercial area, filling station, and vehicular emissions. Health risk assessment through target hazard quotient (THQ) revealed the highest THQ of 9.52 for Cr in bottle gourd, which poses a high non-carcinogenic health risk to the localities upon the intake of these contaminated vegetables. Target cancer risk (TCR) was found to be highest for Cr in papaya (0.013) and bottle gourd (0.014). TCR trends were found for Cr in the following order: bottle gourd > esculent > papaya. This study contributed the greatest concern for both carcinogenic and non-carcinogenic health impacts through ingesting contaminated vegetables., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Free Fatty Acid Receptor 4 (FFAR4), a G-protein-coupled receptor, is responsible for triggering intracellular signaling pathways that regulate various physiological processes. FFAR4 agonists are associated with enhancing insulin release and mitigating the atherogenic, obesogenic, pro-carcinogenic, and pro-diabetogenic effects, normally associated with the free fatty acids bound to FFAR4. In this research, molecular structure-based machine-learning techniques were employed to evaluate compounds as potential agonists for FFAR4. Molecular structures were encoded into bit arrays, serving as molecular fingerprints, which were subsequently analyzed using the Bayesian network algorithm to identify patterns for screening the data. The shortlisted hits obtained via machine learning protocols were further validated by Molecular Docking and via ADME and Toxicity predictions. The shortlisted compounds were then subjected to MD Simulations of the membrane-bound FFAR4-ligand complexes for 100 ns each. Molecular analyses, encompassing binding interactions, RMSD, RMSF, RoG, PCA, and FEL, were conducted to scrutinize the protein-ligand complexes at the inter-atomic level. The analyses revealed significant interactions of the shortlisted compounds with the crucial residues of FFAR4 previously documented. FFAR4 as part of the complexes demonstrated consistent RMSDs, ranging from 3.57 to 3.64, with minimal residue fluctuations 5.27 to 6.03 nm, suggesting stable complexes. The gyration values fluctuated between 22.8 to 23.5 nm, indicating structural compactness and orderliness across the studied systems. Additionally, distinct conformational motions were observed in each complex, with energy contours shifting to broader energy basins throughout the simulation, suggesting thermodynamically stable protein-ligand complexes. The two compounds CHEMBL2012662 and CHEMBL64616 are presented as potential FFAR4 agonists, based on these insights and in-depth analyses. Collectively, these findings advance our comprehension of FFAR4's functions and mechanisms, highlighting these compounds as potential FFAR4 agonists worthy of further exploration as innovative treatments for metabolic and immune-related conditions., (© 2024. The Author(s).)

Perovskite materials have attracted significant attention as innovative and efficient X-ray detectors owing to their unique properties compared to traditional X-ray detectors. Herein, chronologically, we present an in-depth analysis of X-ray detection technologies employing organic-inorganic hybrids (OIHs), all-inorganic and lead-free perovskite material-based single crystals (SCs), thin/thick films and wafers. Particularly, this review systematically scrutinizes the advancement of the diverse synthesis methods, structural modifications, and device architectures exploited to enhance the radiation sensing performance. In addition, a critical analysis of the crucial factors affecting the performance of the devices is also provided. Our findings revealed that the improvement from single crystallization techniques dominated the film and wafer growth techniques. The probable reason for this is that SC-based devices display a lower trap density, higher resistivity, large carrier mobility and lifetime compared to film- and wafer-based devices. Ultimately, devices with SCs showed outstanding sensitivity and the lowest detectable dose rate (LDDR). These results are superior to some traditional X-ray detectors such as amorphous selenium and CZT. In addition, the limited performance of film-based devices is attributed to the defect formation in the bulk film, surfaces, and grain boundaries. However, wafer-based devices showed the worst performance because of the formation of voids, which impede the movement of charge carriers. We also observed that by performing structural modification, various research groups achieved high-performance devices together with stability. Finally, by fusing the findings from diverse research works, we provide a valuable resource for researchers in the field of X-ray detection, imaging and materials science. Ultimately, this review will serve as a roadmap for directing the difficulties associated with perovskite materials in X-ray detection and imaging, proposing insights into the recent status, challenges, and promising directions for future research., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (This journal is © The Royal Society of Chemistry.)