Search

Abstract Background Dengue and leptospirosis are prominent vector-borne diseases in tropical and subtropical regions, sharing overlapping geographic distribution and clinical presentations, which complicates diagnosis and management. Co-infection of these pathogens places additional strain on healthcare resources in endemic areas. This study aims to systematically estimate the prevalence and mortality rates of dengue and leptospirosis co-infections and assess their clinical implications. Methods Adhering the PRISMA 2020 guidelines and registered in the PROSPERO database, we conducted a systematic review and meta-analysis using the PubMed, Embase, and Web of Science databases up to October 2024. Nested Knowledge was used for screening and data extraction. Studies reporting quantitative data on the prevalence or mortality of dengue and leptospirosis co-infections were included. Data extraction and quality assessment were performed independently by two reviewers using the Modified Newcastle-Ottawa Scale. Statistical analyses, including prevalence and mortality estimation, sensitivity analysis were conducted using R, with heterogeneity evaluated by the I² statistic. Results Out of 3,982 records, 14 studies met the eligibility criteria, yielding a pooled prevalence of dengue and leptospirosis co-infection at 2.33% (95% CI: 1.41–3.46%) across 16,638 participants, with significant heterogeneity (I² = 90%). The prediction interval for co-infection ranged from 0.05 to 7.27%. The pooled mortality rate among co-infected patients was 9.96% (95% CI: 0–53.49%), with moderate heterogeneity (I² = 71%). The prediction interval for mortality ranged from 0.00 to 100%. Publication bias was indicated by an LFK index of 2.52. Conclusion This meta-analysis revealed a moderate prevalence and a notable mortality rate for dengue and leptospirosis co-infections, with significant variability observed across different studies. Further research into the immunopathology and the implementation of integrated surveillance systems could enhance the effectiveness of diagnosis and treatment strategies in regions where these diseases are endemic.

Abstract In this work, a triple-junction tandem solar cell (TSC) has been designed in order to increase the photovoltaic (PV) performance through utilizing maximum light photons. To create three junctions in this work three subcells have been designed and optimized at its best PV performance. The optimization of all the three subcells have been done through the various variations in the absorber layer like thickness and bulk defect density (BDD). It has been seen that best PV parameters in the top middle and bottom cell are maximum at high thickness and low BDD. For the designing of triple junction tandem configuration, two filtered spectrums (FS1 and FS2) have been calculated for the proper current matching in the three subcells. The optimized triple-junction TSC demonstrates significantly enhanced PV parameters, including high open-circuit voltage (VOC- 2.750), short-circuit current density (JSC- 16.45 mA/cm2), fill factor (FF- 83.40%), and power conversion efficiency (PCE- 37.74%). The strategy of using filtered spectrums and exact design optimization provides a potential road to the next generation of high-efficiency tandem solar cells, furthering the field of renewable energy solutions.

The current study aims at modeling the solubility of anti-cancer agents in supercritical carbon dioxide (SC-CO2). An extensive databank, including 893 measured samples for 33 anti-cancer agents were collected from the literature, covering extensive ranges of operating conditions. Eight density-based empirical models were firstly employed to correlate the collected data. After adjusting their constant coefficients, four of them provided satisfactory estimations, with total average absolute relative errors (AAREs) below 10 %. A novel six-parameter empirical correlation was also proposed, with input factors optimized based on the Pearson coefficient analysis. This correlation produced satisfactory results for the analyzed drugs, achieving a total AARE of 7.71 %. Afterward, a generalized and unified model was built using the intelligent method of gaussian process regression (GPR). For the testing data, this model showed excellent results with AARE and R2 values of 2.90 % and 99.87 %, respectively. Furthermore, its estimations for all anti-cancer agents outperformed the empirical correlations significantly. Both empirical and intelligent models accurately described the physical behavior of anti-cancer agents’ solubility in SC-CO2 under various conditions. Subsequently, the most effective factors on the performances of the models were recognized through a sensitivity analysis.

The 1,2,4-oxadiazole motif is highly significant in biological studies. An efficient Suzuki-Miyaura coupling methodology has been developed, catalyzed by RuPhos Pd G4, for 1,2,4-oxadiazole substrates This method achieves high yields and clean reactions, featuring a broad substrate scope and straightforward gram-scale synthesis. The pathway offers new biologically useful moieties that can be further explored for their potential applications.

Background: Dengue and leptospirosis are prominent vector-borne diseases in tropical and subtropical regions, sharing overlapping geographic distribution and clinical presentations, which complicates diagnosis and management. Co-infection of these pathogens places additional strain on healthcare resources in endemic areas. This study aims to systematically estimate the prevalence and mortality rates of dengue and leptospirosis co-infections and assess their clinical implications. Methods: Adhering the PRISMA 2020 guidelines and registered in the PROSPERO database, we conducted a systematic review and meta-analysis using the PubMed, Embase, and Web of Science databases up to October 2024. Nested Knowledge was used for screening and data extraction. Studies reporting quantitative data on the prevalence or mortality of dengue and leptospirosis co-infections were included. Data extraction and quality assessment were performed independently by two reviewers using the Modified Newcastle-Ottawa Scale. Statistical analyses, including prevalence and mortality estimation, sensitivity analysis were conducted using R, with heterogeneity evaluated by the I² statistic. Results: Out of 3,982 records, 14 studies met the eligibility criteria, yielding a pooled prevalence of dengue and leptospirosis co-infection at 2.33% (95% CI: 1.41–3.46%) across 16,638 participants, with significant heterogeneity (I² = 90%). The prediction interval for co-infection ranged from 0.05 to 7.27%. The pooled mortality rate among co-infected patients was 9.96% (95% CI: 0–53.49%), with moderate heterogeneity (I² = 71%). The prediction interval for mortality ranged from 0.00 to 100%. Publication bias was indicated by an LFK index of 2.52. Conclusion: This meta-analysis revealed a moderate prevalence and a notable mortality rate for dengue and leptospirosis co-infections, with significant variability observed across different studies. Further research into the immunopathology and the implementation of integrated surveillance systems could enhance the effectiveness of diagnosis and treatment strategies in regions where these diseases are endemic. [ABSTRACT FROM AUTHOR]

The current study aims at modeling the solubility of anti-cancer agents in supercritical carbon dioxide (SC-CO 2). An extensive databank, including 893 measured samples for 33 anti-cancer agents were collected from the literature, covering extensive ranges of operating conditions. Eight density-based empirical models were firstly employed to correlate the collected data. After adjusting their constant coefficients, four of them provided satisfactory estimations, with total average absolute relative errors (AAREs) below 10 %. A novel six-parameter empirical correlation was also proposed, with input factors optimized based on the Pearson coefficient analysis. This correlation produced satisfactory results for the analyzed drugs, achieving a total AARE of 7.71 %. Afterward, a generalized and unified model was built using the intelligent method of gaussian process regression (GPR). For the testing data, this model showed excellent results with AARE and R2 values of 2.90 % and 99.87 %, respectively. Furthermore, its estimations for all anti-cancer agents outperformed the empirical correlations significantly. Both empirical and intelligent models accurately described the physical behavior of anti-cancer agents' solubility in SC-CO 2 under various conditions. Subsequently, the most effective factors on the performances of the models were recognized through a sensitivity analysis. • 893 experimental data for solubility of 33 anti-cancer agents in SC-CO 2 were analyzed. • Eight density-based empirical models were assayed to predict the solubility. • A novel six-parameter correlation was proposed by optimizing the input factors. • A generalized machine learning model was designed based on the GPR method. • The most effective factors on solubility were identified by a sensitivity analysis. [ABSTRACT FROM AUTHOR]

Cyclooxygenase-2 (COX-2), a key enzyme in the inflammatory pathway, is the target for various nonsteroidal anti-inflammatory drugs (NSAIDs) and selective inhibitors known as coxibs. This study focuses on the development of novel imidazole derivatives as COX-2 inhibitors, utilizing a Structure-Activity Relationship (SAR) approach to enhance binding affinity and selectivity. Molecular docking was performed using Autodock Vina, revealing binding energies of -6.928, -7.187, and -7.244 kJ/mol for compounds 5b, 5d, and 5e, respectively. Molecular dynamics simulations using GROMACS provided insights into the stability and conformational changes of the protein-ligand complexes. Key metrics such as RMSD, RMSF, Rg, SASA, and hydrogen bond analysis were employed to assess the interactions. The binding free energy of the inhibitors was estimated using the MMPBSA method, highlighting compound 5b (N-[(3-benzyl-2-methylsulfonylimidazol-4-yl)methyl]-4-methoxyaniline) with the lowest binding energy of -162.014 kcal/mol. ADMET analysis revealed that compound 5b exhibited the most favorable pharmacokinetic properties and safety profile. Overall, this investigation underscores the potential of these novel imidazole derivatives as effective COX-2 inhibitors, with compound 5b emerging as the most promising candidate for further development., 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 © 2025. Published by Elsevier Ltd.)