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The adherence to public health recommendations to control COVID-19 spread is influenced by public knowledge, attitudes and practices (KAP). We performed this cross-sectional study to assess the levels and determinants of public KAP towards COVID-19 in a large, multinational sample. Cross-sectional study (survey). The questionnaire was distributed to potential respondents via online platforms. 71 890 individuals from 22 countries. We formulated a four-section questionnaire in English, followed by validation and translation into seven languages. The questionnaire was distributed (May to June 2020) and each participant received a score for each KAP section. Overall, the participants had fair knowledge (mean score: 19.24±3.59) and attitudes (3.72±2.31) and good practices (12.12±1.83) regarding COVID-19. About 92% reported moderate to high compliance with national lockdown. However, significant gaps were observed: only 68.2% knew that infected individuals may be asymptomatic; 45.4% believed that antibiotics are an effective treatment; and 55.4% stated that a vaccine has been developed (at the time of data collection). 71.9% believed or were uncertain that COVID-19 is a global conspiracy; 36.8% and 51% were afraid of contacting doctors and Chinese people, respectively. Further, 66.4% reported the pandemic had moderate to high negative effects on their mental health. Female gender, higher education and urban residents had significantly (p≤0.001) higher knowledge and practice scores. Further, we observed significant correlations between all KAP scores. Although the public have fair/good knowledge and practices regarding COVID-19, significant gaps should be addressed. Future awareness efforts should target less advantaged groups and future studies should develop new strategies to tackle COVID-19 negative mental health effects.

ObjectiveThe adherence to public health recommendations to control COVID-19 spread is influenced by public knowledge, attitudes and practices (KAP). We performed this cross-sectional study to assess the levels and determinants of public KAP towards COVID-19 in a large, multinational sample.DesignCross-sectional study (survey).SettingThe questionnaire was distributed to potential respondents via online platforms.Participants71 890 individuals from 22 countries.MethodsWe formulated a four-section questionnaire in English, followed by validation and translation into seven languages. The questionnaire was distributed (May to June 2020) and each participant received a score for each KAP section.ResultsOverall, the participants had fair knowledge (mean score: 19.24±3.59) and attitudes (3.72±2.31) and good practices (12.12±1.83) regarding COVID-19. About 92% reported moderate to high compliance with national lockdown. However, significant gaps were observed: only 68.2% knew that infected individuals may be asymptomatic; 45.4% believed that antibiotics are an effective treatment; and 55.4% stated that a vaccine has been developed (at the time of data collection). 71.9% believed or were uncertain that COVID-19 is a global conspiracy; 36.8% and 51% were afraid of contacting doctors and Chinese people, respectively. Further, 66.4% reported the pandemic had moderate to high negative effects on their mental health. Female gender, higher education and urban residents had significantly (p≤0.001) higher knowledge and practice scores. Further, we observed significant correlations between all KAP scores.ConclusionsAlthough the public have fair/good knowledge and practices regarding COVID-19, significant gaps should be addressed. Future awareness efforts should target less advantaged groups and future studies should develop new strategies to tackle COVID-19 negative mental health effects.

Mycobacterium tuberculosis is a lethal human pathogen, with the key flavoenzyme for catalyzing bacterial cell-wall biosynthesis, decaprenylphosphoryl-D-ribose oxidase (DprE1), considered an Achilles heal for tuberculosis (TB) progression. Inhibition of DprE1 blocks cell wall biosynthesis and is a highly promising antitubercular target. Macozinone (PBTZ169, a benzothiazinone (BTZ) derivative) is an irreversible DprE1 inhibitor that has attracted considerable attention because it exhibits an additive activity when combined with other anti-TB drugs. Herein, 754 BTZ analogs were assembled in a virtual library and evaluated against the DprE1 target using a covalent docking approach. After validation of the employed covalent docking approach, BTZ analogs were screened. Analogs with a docking score less than –9.0 kcal/mol were advanced for molecular dynamics (MD) simulations, followed by binding energy evaluations utilizing the MM-GBSA approach. Three BTZ analogs–namely, PubChem-155-924-621, PubChem-127-032-794, and PubChem-155-923-972– exhibited higher binding affinities against DprE1 compared to PBTZ169 with Δ G binding values of –77.2, –74.3, and –65.4 kcal/mol, versus –49.8 kcal/mol, respectively. Structural and energetical analyses were performed for the identified analogs against DprE1 throughout the 100 ns MD simulations, and the results demonstrated the great stability of the identified BTZ analogs. Physicochemical and ADMET characteristics indicated the oral bioavailability of the identified BTZ analogs. The obtained in-silico results provide promising anti-TB inhibitors that are worth being subjected to in-vitro and in-vivo investigations.

Background Candida species have emerged as a significant cause of opportunistic infections. Alongside the expression of various virulence factors, the rise of antifungal resistance among Candida species presents a considerable clinical challenge. Aim This study aimed to identify different Candida species isolated from clinical specimens, evaluate their antifungal sensitivity patterns, identify key genes regulating virulence mechanisms using multiplex PCR and to assess any correlation between their virulence profiles and antifungal resistance patterns. Method A total of 100 Candida spp. was isolated from 630 different clinical specimens and identified to the species level. Their antifungal susceptibility was phenotypically evaluated in accordance with CLSI guidelines using the Vitek-2 Compact System. Virulence markers, including biofilm formation capacity, protease production, melanin production, coagulase production and hemolysin production, were also phenotypically detected. The genetic determinants for biofilm formation and extracellular hydrolytic enzymes were assessed using a multiplex PCR assay. Results The prevalence of Candida spp. was 15.9%, with C. albicans (48%) and C. glabrata (16%) being the most common. C. albicans showed the highest virulence, with strong biofilm formation, and high proteinase and melanin production. Multiplex PCR revealed Hlp in 22.0%, Hwp in 80.0%, Als in 56.0%, and Sap genes in 56.0% of isolates. Virulence genes were more common in C. albicans than in non-albicans Candida (NAC). Resistance patterns significantly correlated with virulence profiles, with notable associations between flucytosine resistance and the presence of Hlp and Hwp genes. Conclusion The significant correlation between virulent markers such as germination, coagulase, hemolysin production and resistance patterns among different Candida isolates is crucial for predicting the severity and outcomes of Candida infections. This understanding aids in guiding tailored treatment strategies.

Tuberculosis (TB) is one of the most fatal infectious diseases. Decaprenylphosphoryl‐D‐ribose oxidase (DprE1), one of the key enzymes in the synthesis of arabinogalactan and lipoarabinomannan, has become a focal point for anti‐TB drug discovery. An investigation of the StreptomeDB database, an extensive collection of natural products from Streptomyces species, yielded 63 nitro‐containing compounds with strong potential as masked electrophiles for covalent inhibitors. The compounds are prepared and screened against DprE1. The reliability of AutoDock 4.2.6 software in predicting the covalent docking scores and poses of the DprE1 inhibitors is evaluated. StreptomeDB compounds exhibiting covalent docking scores lower than PBTZ169, the reference inhibitor, against DprE1 (calc. –7.8 kcal mol−1) are recognized and underwent molecular dynamics simulations, succeeded by estimations of MM‐GBSA binding energies. According to the MM‐GBSA results obtained after 300 ns MDS, hydroxythaxtomin A and lajollamycin B exhibited better binding affinities against DprE1 with ΔGbinding $\\Delta G_{\\text{binding}}$values of –51.2 and –50.5 kcal mol−1, respectively, compared to PBTZ169 (calc. –49.3 kcal mol−1). Post‐MD analyses are conducted to examine the stability and affinity of the identified StreptomeDB compounds with DprE1. Robust bioavailability and drug‐likeness characteristics are expected for the investigated StreptomeDB compounds. These findings unveiled promising inhibitory activity for hydroxythaxtomin A and lajollamycin B against DprE1. StreptomeDB‐derived nitro compounds are screened against Mycobacterium tuberculosis decaprenylphosphoryl‐D‐riboseoxidase (DprE1) . Covalent docking, molecular dynamics simulations, and molecularmechanics/generalized Born surface area analyses identify hydroxythaxtomin and lajollamycin B as potent DprE1 inhibitors, surpassing the reference PBTZ169 in binding affinity. Drug‐likeness and bioavailability profiles support their potential as antituberculosis candidates.

The aim of this study is to evaluate the anti-diabetic nephropathy effect of Caffeic acid and to prove our hypothesis for its mechanism of action that it may occur by reactivation of autophagy pathway via suppression of autophagy regulatory miRNAs. In vivo, high-fat diet and streptozotocin-induced (HFD-STZ) diabetic rats were treated with Caffeic acid once per day for 12 weeks before and after development of diabetic nephropathy. Blood and urine biochemical parameters, autophagy transcripts and their epigenetic regulators together with renal tissue morphology were investigated. In diabetic rats, Caffeic acid intake, caused improvement in albumin excretion,blood glucose, reduced renal mesangial matrix extension with increased vacuolation and reappearance of autophagosomes. Meanwhile, it resulted in autophagy genes up-regulation [RB 1-inducible coiled coil protein (RB1CC1), Microtubule-associated proteins 1A/1B light chain 3(MAP1LC3B), Autophagy related gene (ATG-12),] with simultaneous reduction in their epigenetic regulators; miRNA-133b, −342 and 30a, respectively. These above mentioned effects were more significant in the diabetic nephropathy Caffeic treated rats than in the prophylactic group. Based on our results we postulated that caffeic acid modulates autophagy pathway through inhibition of autophagy regulatory miRNAs, that could explain its curative properties against diabetic kidney disease.

Green hydrogen production is emerging as a crucial component in global decarbonization efforts. This review focuses on the role of computational approaches and artificial intelligence (AI) in optimizing green hydrogen technologies. Key approaches to improving electrolyzer efficiency and scalability include computational fluid dynamics (CFD), thermodynamic modeling, and machine learning (ML). As an instance, CFD has achieved over 95% accuracy in estimating flow distribution and polarization curves, but AI-driven optimization can lower operational expenses by up to 24%. Proton exchange membrane electrolyzers achieve efficiencies of 65–82% at 70–90 °C, but solid oxide electrolyzers reach up to 90% efficiency at temperatures ranging from 650 to 1000 °C. According to studies, combining renewable energy with hydrogen production reduces emissions and improves grid reliability, with curtailment rates of less than 1% for biomass-driven systems. This integration of computational approaches and renewable energy ensures a long-term transition to green hydrogen while also addressing energy security and environmental concerns.