Browse Articles

A qualitative study to identify the determinants and strategies for the prevention of dengue fever in Iran

Abstract In June 2024, Iran reported a dengue fever outbreak beginning in Hormozgan province and spreading to several other provinces, raising significant public health concerns. To mitigate the disease’s impact, multiple meetings were held to explore control strategies, emphasizing community participation through focus groups. This study aimed to identify the determinants, priorities, and control strategies for combating dengue fever and breeding sites of Aedes mosquitoes in Hormozgan province, Iran. This qualitative study employed purposive sampling with maximum variation to conduct 13 focus group discussions (FGDs) with 163 participants (8–13 per group) in Hormozgan Province during June-July 2024. Participants included health department officials, municipal managers, port authorities, and community leaders. Data were analyzed using thematic analysis following Braun and Clarke’s six-phase approach, with trustworthiness ensured through member checking and peer debriefing. These FGDs included health department officials, governors, municipal managers, medical university representatives, Shipping offices, and influential community leaders involved in dengue prevention education. Through these discussions, seven key determinants for dengue fever control in Iran were identified. The primary factors were: (a) Environmental (b) Therapeutic and health care (c) interdisciplinary cooperation (d) Administrative, legal, and regulatory determinants (e) Financial and budgetary (f) Educational determinants and (g) Social determinants. Effective community empowerment and health program decision-making require cooperation across various organizations, enhancement of high-risk environments, and fostering a sense of responsibility and participation among community members. Given the rise of re-emerging diseases globally, identifying their determinants is crucial for quick disease control in the region and for preventing global pandemics.

Mitochondrial-dependent apoptosis and STAT3 activation induced by oxidative stress in pemphigus vulgaris

Predicting cortical bone resorption in the mouse tibia under disuse conditions caused by transient muscle paralysis

Large language model driven transferable key information extraction mechanism for nonstandardized tables

Comparative evaluation of adaptation and fracture resistance of CAD-CAM fabricated zirconia posts in endodontically treated teeth

Prevalence and determinants of antidepressant non-adherence among patients with major depressive disorder in Ethiopia: a multi-center cross sectional study

Abstract   Non-adherence to antidepressant medication is a well-established factor contributing to treatment failure among patients with major depressive disorder. Addressing this issue is crucial not only for enhancing individual patient outcomes but also for alleviating the broader public health burden. The study aimed to assess antidepressant medication non-adherence and its determinants among patients with major depressive disorder at public hospital psychiatric clinics in Ethiopia. Between June 12, 2024, and November 13, 2024, a multicenter cross-sectional study was conducted at public hospital psychiatric clinics in Ethiopia. Antidepressant non-adherence was assessed using a self-reported tablet count tool with pharmacy refill records available in patients’ charts at the time of the interview. The severity of adverse drug reactions (ADRs) was evaluated using the Antidepressant Side-Effect Checklist (ASEC), while the Naranjo ADR Probability Scale was employed to determine the likelihood of ADRs. Data analysis was performed using SPSS version 26.0. Frequencies and percentages, were used to describe the characteristics of study participants. For factors associated with antidepressant non-adherence, multivariate logistic regression was conducted. The association between explanatory variable and non-adherence was assessed using odds ratios (ORs) with 95% CIs. The prevalence of antidepressant medication non-adherence was 139 (32.9%). Female gender [AOR = 3.29, 95% CI (2.04, 5.31)], illiteracy [AOR = 2.17, 95% CI (1.35, 3.50)], unemployment [AOR = 3.40, 95% CI (2.15, 5.38)], treatment duration greater than 25 months [AOR = 1.89, 95% CI (1.05, 3.41)], and severe ADRs [AOR = 3.94, 95% CI (1.68, 9.23)] were significantly associated with Antidepressant medication non-adherence. Being female, illiterate, unemployed, having a treatment duration of more than 25 months, and experiencing severe adverse drug reactions were significantly associated with non-adherence. These findings highlight the need for targeted interventions to improve adherence among these high-risk groups.

Revisiting model scaling with a U-net benchmark for 3D medical image segmentation

Spatiotemporal variability and trends in extreme rainfall and temperature indices in Southeastern Oromia, Ethiopia

Advanced machine learning framework for thyroid cancer epidemiology in Iran through integration of environmental socioeconomic and health system predictors

HPV vaccination improves immune response in children with respiratory papillomatosis

One-third of Sun-like stars are born with misaligned planet-forming disks

Development and validation of a predictive model for 90-day mortality risk after discharge in patients with cirrhosis and esophagogastric variceal bleeding

Identification of medication–microbiome interactions that affect gut infection

Decoding 4-vinylanisole biosynthesis and pivotal enzymes in locusts

Extensive digital health technology assessment detects subtle motor impairment in mild and asymptomatic Pompe disease

Nuclear-weapons risks are back — and we need to act like it

Quantum granular-ball generation methods and their application in KNN classification

Mystery of billions of sea-star deaths solved at last

Tiny motor uses heat to perform molecular magic

Molecular gradients shape synaptic specificity of a visuomotor transformation

Abstract How does the brain convert visual input into specific motor actions1,2? In Drosophila, visual projection neurons (VPNs)3,4 perform this visuomotor transformation by converting retinal positional information into synapse number in the brain5. The molecular basis of this phenomenon remains unknown. We addressed this issue in LPLC2 (ref. 6), a VPN type that detects looming motion and preferentially drives escape behaviour to stimuli approaching from the dorsal visual field with progressively weaker responses ventrally. This correlates with a dorsoventral gradient of synaptic inputs into and outputs from LPLC2. Here we report that LPLC2 neurons sampling different regions of visual space exhibit graded expression of cell recognition molecules matching these synaptic gradients. Dpr13 shapes LPLC2 outputs by binding DIP-ε in premotor descending neurons mediating escape. Beat-VI shapes LPLC2 inputs by binding Side-II in upstream motion-detecting neurons. Gain-of-function and loss-of-function experiments show that these molecular gradients act instructively to determine synapse number. These patterns, in turn, fine-tune the perception of the stimulus and drive the behavioural response. Similar transcriptomic variation within neuronal types is observed in the vertebrate brain7 and may shape synapse number via gradients of cell recognition molecules acting through both genetically hard-wired programs and experience.