Critical Global Health Research Articles

Clearing the Air to Address Pollution's Cardiovascular Health Crisis.

Air pollution is a critical global health issue that significantly impacts cardiovascular health. The air pollutant PM2.5 (particulate matter with a diameter of 2.5 micrometres or less) has been positioned as a leading environmental risk factor for morbidity and mortality, especially from cardiovascular diseases (CVDs). Using data from the World Health Organization (WHO), Global Health Observatory, and the United Nations Environment Programme, we explored global trends in air pollution, with a focus on PM2.5 levels, the implications for cardiovascular health, and the policy measures aimed at reducing their impact. Despite progress in reducing pollution levels in high-income countries, global trends show a limited annual reduction in PM2.5 concentration. The analysis highlights disparities between regions, with low- and middle-income countries bearing the brunt of air pollution-related CVDs. In 2019 alone, ambient air pollution was responsible for approximately 4.2 million deaths worldwide. Of these, 70% were caused by CVDs, with approximately 1.9 million deaths from ischemic heart disease and 900,000 deaths from stroke. Policy gaps remain a challenge, with many countries lacking adequate legally binding air quality standards. We recommend the adoption of WHO air quality guidelines, enhanced monitoring of air pollution levels, and increased investment in interdisciplinary research to understand the full scope of air pollution's effects on cardiovascular health. Addressing the global cardiovascular crisis linked to air pollution will require coordinated efforts from policymakers, healthcare systems, and global health organisations.

Ethics in social listening in infodemic management in health emergencies

Abstract Issue During the COVID-19 pandemic and subsequent outbreaks, health organizations have increased the use of social listening to inform infodemic management and outbreak response activities. This demonstrated the need to provide ethical guidance to organizations, and individuals engaging in social listening practices before, during and after public health emergencies, whilst protecting human rights. Description of the problem Social listening as a public health activity draws on analysis of conversations in social media, internet platforms, and feedback from geographically localized communities. Infodemic insights are generated rapidly, to support agile action by health organizations that improves outbreak response, health information delivery, community engagement, or reduction of unintended harm experiences by communities. Social listening involves use of social media and internet trace data, which were traditionally not used in public health for understanding community expressions, WHO convened a panel of experts to develop a framework on ethical considerations for social listening in infodemic management to provide recommendations for health authorities and researchers on practical tools that support setting up new data analysis and use of insights hereto not used in routine. Results The guidance framework has been structured into segments that vary from ethical principles and challenges in social listening and generation of infodemic insights, alignment with human rights, substantive principles, procedural principles, and practical guidance for translating these principles into real-world practice. Lessons This guidance aims to illuminate the intricate ethical dimensions of social listening and stress the urgent need for ethical guidance in this realm. The framework is a comprehensive inquiry of the ethical scope in social listening, providing valuable insights, practical guidance, and case studies to enhance understanding of this critical global health issue. Key messages • While essential, social listening and infodemic insights come with ethical risks, including potential harm to populations in vulnerable situations, erosion of trust, and misuse of data. • This ethical framework will govern social listening practices and ensure responsible and ethical social listening.

The Interaction Effect of Age, Initial Rhythm, and Location on Outcomes After Out-of-Hospital Cardiac Arrest: A Retrospective Cohort Study

Background: Out-of-hospital cardiac arrest (OHCA) is a critical global health challenge and a leading cause of mortality. This study investigates the combined effect of initial cardiac arrest rhythm, patient age, and location on the return of spontaneous circulation (ROSC) in OHCA patients. Methods: This retrospective study analyzed medical records from the National Emergency Medical Service (EMS) in Poland between January 2021 and June 2022. Data from 33,636 patients with OHCA who received cardiopulmonary resuscitation (CPR) at the scene were included. Results: Public incidents were associated with higher ROSC rates (54.10% vs. 31.53%, p < 0.001). Initial shockable rhythms (VF/pVT) significantly increased the odds of ROSC (OR = 3.74, 95% CI 3.39–4.13, p < 0.001). Obesity decreased the odds of ROSC in at-home cases (OR = 0.85, 95% CI 0.73–0.99, p = 0.036) but had no significant effect in public cases. The effect of age on ROSC outcomes varied significantly depending on the location. In patients younger than 60 years, better ROSC outcomes were observed in at-home cases, while for those older than 60 years, the odds of ROSC were higher in public locations. Each additional year of age decreased the odds of ROSC by 1.62% in at-home incidents (p < 0.001) and by 0.40% in public incidents (p = 0.009). Sex differences were significant in public locations, with women having higher odds of ROSC compared to men (OR = 0.57, 95% CI 0.37–0.87, p = 0.009 for VF/pVT). Conclusions: The interaction between the location of OHCA, initial cardiac rhythm, and patient age significantly impacts ROSC outcomes. Public locations show higher ROSC rates, especially in cases with shockable rhythms (VF/pVT). Age modifies ROSC outcomes, with younger patients benefiting more at home, and older patients showing better outcomes in public places.

Dysregulation of the 3β-hydroxysteroid dehydrogenase type 2 enzyme and steroid hormone biosynthesis in chronic kidney disease

IntroductionChronic kidney disease (CKD) presents a critical global health challenge, marked by the progressive decline of renal function. This study explores the role of the 3β-hydroxysteroid dehydrogenase type 2 enzyme (HSD3B2) and the steroid hormone biosynthesis pathway in CKD pathogenesis and progression.MethodsUsing an adenine-induced CKD mouse model, we conducted an untargeted metabolomic analysis of plasma samples to identify key metabolite alterations associated with CKD. Immunohistochemistry, Western blotting, and qPCR analyses were performed to confirm HSD3B2 expression in both human and mouse tissues. Additionally, Nephroseq and Human Protein Atlas data were utilized to assess the correlation between HSD3B2 and kidney function. Functional studies were conducted on HK2 cells with HSD3B2 knockdown to evaluate the impact on cell proliferation and apoptosis.ResultsMetabolic characteristics revealed significant shifts in CKD, with 61 metabolites increased and 65 metabolites decreased, highlighting the disruption in steroid hormone biosynthesis pathways influenced by HSD3B2. A detailed examination of seven key metabolites underscored the enzyme's central role. HSD3B2 exhibited a strong correlation with kidney function, supported by data from Nephroseq and the Human Protein Atlas. Immunohistochemistry, Western blotting, and qPCR analyses confirmed a drastic reduction in HSD3B2 expression in CKD-affected kidneys. Suppressed proliferation and increased apoptosis rates in HSD3B2 knocked down HK2 cells further demonstrated the enzyme's significance in regulating renal pathophysiology.DiscussionThese findings underscore the potential of HSD3B2 as a clinical diagnostic and therapeutic target in CKD. While further studies are warranted to fully elucidate the mechanisms, our results provide valuable insights into the intricate interplay between steroid hormone biosynthesis and CKD. This offers a promising avenue for precision medicine approaches and personalized treatment strategies.

Exploring the Antidiabetic and Antihypertensive Potential of Peptides Derived from Bitter Melon Seed Hydrolysate

Background/Objectives: Type 2 diabetes (T2D) has become a critical global health issue, with an increasing prevalence that contributes to significant morbidity and mortality. Inhibiting dipeptidyl peptidase-IV (DPP4) is a promising strategy for managing T2D. This study aimed to explore the DPP4 inhibitory peptide derived from bitter melon seed protein (BMSP) hydrolysate. Methods: Reversed-phase high-performance liquid chromatography (RP-HPLC) was utilized to fractionate the hydrolysate. Peptide in the highest activity fraction was analyzed using liquid chromatography-mass spectrometry (LC-MS/MS). Peptide synthetic was used for further characterizations, such as bioactivity exploration, inhibition mechanism, molecular docking, and peptide stability against in vitro simulated gastrointestinal (SGI) digestion. Results: The BMSP hydrolysate was digested with gastrointestinal proteases (GP) and assessed for DPP4 inhibitory activity, yielding an IC50 of 1448 ± 105 μg/mL. Following RP-HPLC fractionation, MPHW (MW4) and VPSGAPF (VF7) were identified from fraction F8 with DPP4 IC50 values of 128.0 ± 1.3 µM and 150.6 ± 3.4 µM, respectively. Additionally, MW4 exhibited potential antihypertensive effects through ACE inhibition with an IC50 of 172.2 ± 10.6 µM. The inhibitory kinetics and molecular docking simulations indicated that both MW4 and VF7 were competitive inhibitors of DPP4, while MW4 was also a competitive inhibitor of ACE. Importantly, both peptides remained stable during simulated gastrointestinal digestion, suggesting their resistance to human digestive processes and their capacity to maintain biological activity. Conclusions: The findings suggest that BMSP-GP hydrolysate may have potential in terms of the development of health foods or therapeutic agents. However, in vivo studies are also essential for further confirmation of efficacy.

Profiling of Potential Anti-Diabetic Active Compounds in White Tea: An Integrated Study of Polyphenol-Targeted Metabolomics, Network Pharmacology, and Computer Simulation

Diabetes remains a critical global public health challenge, posing a growing threat to human health and well-being. White tea is a lightly fermented tea and one of the six traditional tea categories in China. Owing to its rich content of bioactive compounds such as catechins and alkaloids, it has demonstrated potential anti-diabetic properties. However, its precise bioactive components, mechanisms of action, and relevant molecular targets require further investigation. In this study, an integrated approach combining polyphenol-targeted metabolomics, in vitro antioxidant assays, α-glucosidase inhibition tests, network pharmacology analysis, GEO database exploration, molecular docking, and molecular dynamics simulations was employed to identify the potential anti-diabetic compounds, targets, and mechanisms of white tea. The findings revealed that white tea is particularly abundant in 10 bioactive compounds, including epigallocatechin gallate, epicatechin gallate, and catechin, all of which exhibit significant anti-diabetic potential. These compounds were found to exert their effects by interacting with core molecular targets, namely cathepsin V (CTSV) and nucleotide-binding oligomerization domain-containing protein 1 (NOD1), and engaging in pathways related to signal transduction, apoptosis, and immune responses. This study establishes a strong theoretical basis for advancing white tea research and underscores new opportunities for applying natural products in diabetes therapy.

Non-Conventional Data for Farming-Related Air Pollution: Contributions to Modelling and Risk Assessment in the Lombardy Region, Italy

Air pollution is one of the most critical global health concerns today. While emissions from industrial activities and combustion processes are the primary threats to air quality, intensive farming activities also contribute significantly, especially through ammonia emissions that promote the formation of secondary pollutants, such as particulate matter. Advancements in air quality research have been achieved by enhancements in emissions characterisation, modelling techniques, and sensor technology, expanding the availability of air pollution data beyond traditional ground sensor observations, which are often lacking in rural agricultural areas. Accordingly, this paper demonstrates the advantages of integrating traditional and non-conventional data to investigate farming-related air pollution through a case study in the Lombardy Region, Northern Italy. The study incorporates an array of data sources, including ground sensors and atmospheric composition model estimates. The concurrent utilisation of these diverse datasets is explored through machine learning modelling, focusing on assessing the influence of agricultural activities on particulate matter distribution patterns. Finally, the reliability of non-conventional air pollution data for health risk assessment applications is also investigated. The paper critically discusses the main findings based on empirical results, highlighting the significance of integrating multiple data sources to complement traditional air quality monitoring while outlining the main limitations in terms of the accuracy and usability of such non-conventional data.

Kynurenine-AhR reduces T-cell infiltration and induces a delayed T-cell immune response by suppressing the STAT1-CXCL9/CXCL10 axis in tuberculosis.

Tuberculosis, caused by Mycobacterium tuberculosis (Mtb), is a critical global health issue that is complicated by the ability of the pathogen to delay the host's T-cell immune response. This delay in T-cell recruitment to the site of infection is a pivotal survival strategy for Mtb, allowing it to establish a persistent chronic infection. To investigate the underlying mechanisms, this study focused on Mtb's exploitation of host tryptophan metabolism. Mtb upregulates indoleamine 2,3-dioxygenase 1 (IDO1) in inflammatory macrophages, thereby increasing kynurenine (Kyn) production. Kyn then activates the aryl hydrocarbon receptor (AhR), leading to the upregulation of suppressor of cytokine signaling 3 and subsequent inhibition of the JAK-STAT1 signaling pathway. This results in reduced secretion of the chemokines CXCL9 and CXCL10, which are crucial for T-cell recruitment to the lungs. Supported by in vivo mouse models, our findings reveal that disrupting this pathway through AhR knockout significantly enhances T-cell infiltration and activity, thereby undermining Mtb-induced immunosuppression. In contrast, additional Kyn injection obviously inhibited T-cell infiltration and activity. These results highlight potential therapeutic targets of AhR and IDO1, offering new avenues for enhancing the host immune response against tuberculosis and guiding future vaccine development efforts.

Deep learning in disease vector image identification.

Vector-borne diseases (VBDs) represent a critical global public health concern, with approximately 80% of the world's population at risk of one or more VBD. Manual disease vector identification is time-consuming and expert-dependent, hindering disease control efforts. Deep learning (DL), widely used in image, text, and audio tasks, offers automation potential for disease vector identification. This paper explores the substantial potential of combining DL with disease vector identification. Our aim is to comprehensively summarize the current status of DL in disease vector identification, covering data collection, data preprocessing, model construction, evaluation methods, and applications in identification spanning from species classification to object detection and breeding site identification. We also discuss the challenges and possible prospects for DL in disease vector identification for further research. © 2024 Society of Chemical Industry.

Elucidation of significant regulatory proteins in the JNK pathway modulated by truncated pardaxin, PC6 through molecular dynamic simulation

ABSTRACT Cancer remains a critical global health issue, with current treatments often causing significant side effects. This has spurred the search for alternative therapies, such as bioactive peptides, which offer advantages such as higher selectivity against cancer cells and ease of modification. Pardaxin, a bioactive peptide, has shown anticancer effects on various cell lines via the JNK pathway. A truncated form of pardaxin, PC6, has demonstrated anticancer properties with reduced haemolytic effects though its cell death mechanism is unclear. This study aimed to investigate PC6-induced cell death, focusing on the JNK cascade compared to parental pardaxin (PAR). JNK cascade genes were sourced from the Gene Ontology database, followed by docking screening and protein-peptide network analysis. The network identified 65 genes involved in the JNK pathway, which were verified through gene enrichment analysis. Molecular dynamic simulation and binding affinity analysis showed that PC6 had a higher affinity (−88.69, −82.17, −54.93 kcal/mol) for MAPK8, MAPK9 and HRAS proteins than PAR (−68.88, −76.64, −38.63 kcal/mol). These findings suggest that PC6 specifically interacts with these proteins to induce apoptosis via the JNK cascade, highlighting its potential as an effective anticancer agent.

CSA-Net: Channel and Spatial Attention-Based Network for Mammogram and Ultrasound Image Classification.

Breast cancer persists as a critical global health concern, emphasizing the advancement of reliable diagnostic strategies to improve patient survival rates. To address this challenge, a computer-aided diagnostic methodology for breast cancer classification is proposed. An architecture that incorporates a pre-trained EfficientNet-B0 model along with channel and spatial attention mechanisms is employed. The efficiency of leveraging attention mechanisms for breast cancer classification is investigated here. The proposed model demonstrates commendable performance in classification tasks, particularly showing significant improvements upon integrating attention mechanisms. Furthermore, this model demonstrates versatility across various imaging modalities, as demonstrated by its robust performance in classifying breast lesions, not only in mammograms but also in ultrasound images during cross-modality evaluation. It has achieved accuracy of 99.9% for binary classification using the mammogram dataset and 92.3% accuracy on the cross-modality multi-class dataset. The experimental results emphasize the superiority of our proposed method over the current state-of-the-art approaches for breast cancer classification.

Implementation of the WHO surgical safety checklist in resource-limited Somalia: a new standard in surgical safety

BackgroundSurgical safety remains a critical global health concern, with complications from surgical procedures resulting in significant morbidity and mortality, particularly in low- and middle-income countries. The World Health Organization (WHO) Surgical Safety Checklist (SSC) has been shown to reduce surgical complications and mortality rates. However, its implementation and impact in resource-limited settings like Somalia remain understudied. This study aimed to evaluate the implementation of the WHO SSC in selected hospitals in Mogadishu, Somalia, and assess its impact on surgical safety practices.MethodsA pre- and post-intervention study was conducted in 15 randomly selected hospitals in Mogadishu, Somalia. The intervention involved a comprehensive training program on the WHO SSC for surgical teams. Data on hospital characteristics, surgical details, and adherence to the SSC were collected over two periods: pre-intervention (April 12th to May 4th, 2024) and post-intervention (May 12th to June 3rd, 2024). The primary outcome was the adherence to the SSC, categorized as good (> 60%) or poor (≤ 60%). Descriptive statistics, McNemar’s test, and binary logistic regression were used for data analysis.ResultsAdherence to the WHO SSC significantly improved post-intervention, with 98.8% of surgical cases demonstrating good adherence compared to 37% pre-intervention (p < 0.001). The mean adherence score increased from 51.6% (SD = 29.6) to 94.1% (SD = 8.2). Significant improvements were observed for most individual checklist items, including patient identity confirmation, surgical site marking, anesthesia machine checks, and pulse oximeter use (p < 0.001). Team dynamics and communication also improved significantly post-intervention. Hospital type, size, years of service, funding source, surgical department, surgery type, urgency, and staff numbers were associated with checklist adherence pre-intervention.ConclusionThe implementation of a comprehensive training intervention significantly improved adherence to the WHO Surgical Safety Checklist in resource-limited hospitals in Mogadishu, Somalia. The findings highlight the feasibility and effectiveness of the SSC in enhancing surgical safety practices, team communication, and patient outcomes in challenging healthcare environments. Tailored implementation strategies, ongoing training, and cultural adaptation are crucial for the successful adoption of the SSC in resource-constrained settings.

Epidemiological profile of imported malaria cases in Colombia

Despite the significant progress made in reducing morbidity and mortality in recent years, malaria remains a critical global health challenge. In Colombia, we are working towards eliminating malaria to achieve zero indigenous cases of human malaria. In this effort, it is also essential to understand the epidemiological profile of imported cases. This study aimed to determine the epidemiological situation of imported malaria cases in Colombia from 2007 to 2020. An observational, descriptive, and retrospective study used secondary sources for data analysis. A total of 7,583 imported malaria cases (0.8% of total burden) were recorded. 85% (6,507/7,583) were caused by Plasmodium vivax, and 89% (6,772/7,583) were imported from Venezuela. Imported malaria trend varied, contributing minimally to the national burden. Venezuela was identified as the main source of imported cases. These findings will contribute to improving disease surveillance and preventing the reintroduction of malaria in areas undergoing elimination.

Application of a new highly multiplexed amplicon sequencing tool to evaluate Plasmodium falciparum antimalarial resistance and relatedness in individual and pooled samples from Dschang, Cameroon.

Resistance to antimalarial drugs remains a major obstacle to malaria elimination. Multiplexed, targeted amplicon sequencing is being adopted for surveilling resistance and dissecting the genetics of complex malaria infections. Moreover, genotyping of parasites and detection of molecular markers drug resistance in resource-limited regions requires open-source protocols for processing samples, using accessible reagents, and rapid methods for processing numerous samples including pooled sequencing. P lasmodium falciparum S treamlined M ultiplex A ntimalarial R esistance and R elatedness T esting ( Pf -SMARRT) is a PCR-based amplicon panel consisting of 15 amplicons targeting antimalarial resistance mutations and 9 amplicons targeting hypervariable regions. This assay uses oligonucleotide primers in two pools and a non-proprietary library and barcoding approach. We evaluated Pf -SMARRT using control mocked dried blood spots (DBS) at varying levels of parasitemia and a mixture of 3D7 and Dd2 strains at known frequencies, showing the ability to genotype at low parasite density and recall within-sample allele frequencies. We then piloted Pf -SMARRT to genotype 100 parasite isolates collected from uncomplicated malaria cases at three health facilities in Dschang, Western Cameroon. Antimalarial resistance genotyping showed high levels of sulfadoxine-pyrimethamine resistance mutations, including 31% prevalence of the DHPS A613S mutation. No K13 candidate or validated artemisinin partial resistance mutations were detected, but one low-level non-synonymous change was observed. Pf -SMARRT's hypervariable targets, used to assess complexity of infections and parasite diversity and relatedness, showed similar levels and patterns compared to molecular inversion probe (MIP) sequencing. While there was strong concordance of antimalarial resistance mutations between individual samples and pools, low-frequency variants in the pooled samples were often missed. Overall, Pf -SMARRT is a robust tool for assessing parasite relatedness and antimalarial drug resistance markers from both individual and pooled samples. Control samples support that accurate genotyping as low as 1 parasite per microliter is routinely possible. Malaria remains a critical global public health problem. Antimalarial drug resistance has repeatedly undermined control and the emergence of artemisinin partial resistance in Africa is the latest major challenge. Malaria molecular surveillance (MMS) has emerged as a powerful tool to monitor molecular markers of resistance and changes in the parasite population. Streamlined methods are needed that can be readily adopted in endemic countries. We developed P lasmodium falciparum S treamlined M ultiplex A ntimalarial R esistance and R elatedness T esting ( Pf -SMARRT), a multiplex amplicon deep sequencing approach that uses easily accessible products without proprietary steps and can be sequenced on any Illumina sequencer. We validated this tool using controls, including mocked dried blood spots, and then implemented it to evaluate resistance and parasite relatedness among 100 samples from Cameroon. The assay was able to reliably assess the within-sample allele frequency of antimalarial resistance markers and discriminate strains within and between individuals. We also evaluated a more cost-effective surveillance approach for antimalarial resistance polymorphisms using pooled samples. While within-pool frequencies of mutations were accurate in pools with higher numbers of samples, this resulted in the loss of the ability to detect variants uncommon in the pool. Overall Pf- SMARRT provides a new protocol for conducting MMS that is easily implementable in Africa.

New LsrK Ligands as AI-2 Quorum Sensing Interfering Compounds against Biofilm Formation.

Antimicrobial resistance (AMR) represents a critical global health crisis. An innovative strategy to deal with AMR is to interfere with biofilm formation and bacterial quorum sensing (QS). In this study, newly designed autoinducer-2 (AI-2)-inspired compounds in targeting biofilm-associated infections were evaluated for their ability to inhibit biofilm formation in Staphylococcus aureus and Pseudomonas aeruginosa. The most effective compounds, 5d, 5e, and 7b, exhibited potent antibiofilm activity with minimal inhibitory concentrations in the low microgram per mL range. Detailed biological assays confirmed that the antibiofilm activity was primarily driven through AI-2 QS inhibition rather than direct antimicrobial effects. The combination of different spectroscopic techniques, such as differential scanning fluorimetry, intrinsic tryptophan fluorescence, circular dichroism, and nuclear magnetic resonance, elucidated the binding between the compounds and the LsrK enzyme, a key player in AI-2 mediated QS. Our findings highlight the potential of these novel QS inhibitors as promising therapeutic agents against biofilm-associated infections.

Exploring the association between consultation themes and suicidal ideation: a gender-stratified analysis of Hangzhou Mental Health Hotline (2014-2023)

BackgroundSuicide is a critical global public health issue that demands a better understanding of its complex causes and effective interventions. This study examines data from the Hangzhou Mental Health Hotline (2014-2023) to explore the relationship between consultation themes and suicidal ideation, with an emphasis on gender differences and how these associations changed during different phases of the COVID-19 pandemic.MethodsThis retrospective analysis covers 128,245 calls to the hotline over a decade. Chi-square tests identified differences in suicidal ideation across consultation themes and demographics. Multivariate logistic regression models were used to examine the relationship between specific themes and suicidal ideation, adjusting for confounders. The analysis was stratified by gender and pandemic phases to assess the interaction between gender and pandemic-related changes.ResultsThe incidence of suicidal ideation was highest during the mid-pandemic phase (11.95%), compared to the pre-pandemic (7.68%) and post-pandemic phases (10.66%). Additionally, the rate was slightly higher among female callers (9.8%) than male callers (9.4%). Physical illness (OR = 4.70, 95% CI: 3.71-5.91) had the strongest association with suicidal ideation, followed by mental health issues (OR = 3.35, 95% CI: 3.03-3.70). Compared to male callers, female callers were more significantly affected by physical illness (OR = 6.86 vs. OR = 3.71, p < 0.001) and mental health issues (OR = 6.81 vs. OR = 2.11, p < 0.001). In the context of romantic relationship problems, female callers had a higher likelihood of suicidal ideation (OR = 4.13 vs. OR = 1.88, p < 0.001). Similarly, marital and family issues were more strongly associated with suicidal ideation in female callers (OR = 4.58 vs. OR = 1.21, p < 0.001). During the global COVID-19 pandemic, the association between suicidal ideation and consultation themes among male callers showed a sharp upward trend, which eased after the pandemic. In contrast, the association among female callers gradually accumulated and continued to worsen in the later stages of the pandemic.ConclusionThis study highlights the necessity of implementing gender-sensitive mental health interventions tailored to different gender groups during and after global crises such as the COVID-19 pandemic, to safeguard public mental health effectively.

Development of Tetracycline by AgO Nanoparticles and Studying its Activity on Antibiotic-Resistant Bacteria

General background: Antibiotic resistance in bacteria has become a critical global health issue, necessitating the development of new strategies to enhance antibiotic efficacy. Specific background: Nanoparticles, particularly silver nanoparticles (AgNPs), have emerged as potential enhancers of antibiotics due to their unique properties and interactions with bacterial cells. Knowledge gap: However, the combination of nanoparticles with existing antibiotics, such as tetracycline, and their impact on bacterial inhibition and safety has not been fully explored. Aims: This study aims to investigate the antibacterial activity of silver oxide nanoparticles (AgO NPs) combined with tetracycline (TCS) and evaluate their effectiveness against resistant bacterial strains. Results: AgO NPs were synthesized using a photodeposition method, yielding nanoparticles with an average diameter of 2.24 nm. The AgO NPs + TCS combination demonstrated superior antibacterial activity, with a minimum inhibitory concentration (MIC) of 16 μg/mL against Staphylococci and 32 μg/mL against Pseudomonas aeruginosa, significantly outperforming standard tetracycline. Hemolysis assays confirmed the safety of the synthesized compound at all concentrations. Novelty: Silver oxide nanoparticles and tetracycline exhibit a unique synergistic interaction, enhancing antimicrobial effects by increasing bacterial membrane permeability, facilitating greater antibiotic infiltration. Implications: These findings suggest that AgO NPs combined with tetracycline offer a promising solution to overcome bacterial resistance, providing a potent and safe alternative to conventional antibiotic treatments. Highlights: AgO NPs and tetracycline show enhanced antibacterial effects. More effective than standard tetracycline against resistant bacteria. Safe with no toxicity observed in hemolysis tests. Keywords: Antibiotic resistance, silver nanoparticles, tetracycline, photodeposition, antibacterial activity

Investigation on the mosquitocidal property of cis-13-Octadecenoic acid isolated from Andrographis paniculata against Aedes aegypti and Culex quinquefasciatus (Diptera: Culicidae)

Mosquitoes are a critical global public health concern, causing millions of deaths each year due to the viral infections and diseases they spread. In recent decades, synthetic insecticides and repellents have been used to control mosquito populations and virus transmission, but they often harm the environment and non-target organisms, including humans. This research investigates the isolation, characterization, and structural elucidation of cis-13-Octadecenoic acid derived from Andrographis paniculata, and its effectiveness against the immature stages of Aedes aegypti and Culex quinquefasciatus. The extracts from A. paniculata underwent fractionation, with the most bioactive fractions being further purified and analyzed. Spectroscopic techniques were employed to confirm the structure of cis-13-Octadecenoic acid. Biological assays were then performed to evaluate its ovicidal, larvicidal, and pupicidal activities. cis-13-Octadecenoic acid exhibited notable ovicidal activity, causing 25 % mortality in Ae. aegypti eggs and 29 % mortality in Cx. quinquefasciatus eggs at a concentration of 2 ppm. Additionally, it showed strong larvicidal and pupicidal activities, with LC50 values of 2.67 ppm and 3.39 ppm for Ae. aegypti larvae and pupae, and 3.10 ppm and 2.93 ppm for Cx. quinquefasciatus larvae and pupae, respectively. These findings demonstrate the potential of cis-13-Octadecenoic acid as an effective natural compound for mosquito control, highlighting the broader importance of natural products as alternatives to synthetic insecticides in the management of vector-borne diseases.

Exploring the decision-making experience of elderly diabetes patients regarding their health-seeking behaviour: a descriptive qualitative study

BackgroundDiabetes has emerged as a critical global public health issue. The burden of diabetes is escalating in developing countries, including China. For individuals with diabetes, making informed and rational decisions...

Analyzing stroke burden and risk factors in India using data from the Global Burden of Disease Study.

Stroke remains a critical global health issue, significantly impacting India with substantial contributions to mortality and disability. This study comprehensively analyses stroke incidence, mortality, and disability-adjusted life years (DALYs) across India from 1990 to 2021, using the latest Global Burden of Disease (GBD) 2021 data. We evaluate how Universal Health Coverage (UHC), health expenditure, human development index (HDI), and gross national income (GNI) influence stroke outcomes. Our findings reveal significant regional disparities, with higher stroke rates in urban areas and states like Goa and Kerala. Higher health expenditure and HDI are linked to lower stroke rates, while higher GNI per capita correlates with increased stroke incidence, likely due to lifestyle changes. Risk factors include air pollution, tobacco use, dietary risks, and high blood pressure. Air pollution notably impacts stroke mortality in Bihar and Jharkhand, while tobacco use is a major risk factor in Mizoram and Manipur. Dietary risks and hypertension are prevalent in Maharashtra and Jammu & Kashmir. The study highlights the need for targeted public health strategies addressing regional disparities and socioeconomic factors. Policymakers should focus on lifestyle modification programs, public awareness campaigns, and enhanced access to quality stroke care to reduce stroke-related morbidity and mortality effectively.