7973 research outputs found
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Investigating how dengue virus-induced metabolic changes affect the host immune response and how to develop Immunomodulatory strategies
No full textDengue virus (DENV) infection imposes a significant global health burden, driven by its ability to manipulate host cellular processes to facilitate replication and evade immune defenses. This review explores the complex interplay between DENV, host immunometabolism, and signaling pathways. DENV induces metabolic reprogramming, including glycolytic upregulation, lipid droplet utilization through lipophagy, and alterations in amino acid metabolism, to fulfill its energy and biosynthetic needs. The virus also disrupts mitochondrial dynamics, leading to increased reactive oxygen species (ROS) production, which modulates immune responses but may also contribute to oxidative stress and severe pathology. Concurrently, DENV hijacks host signaling pathways, including PI3K/Akt, NF-κB, and JAK/STAT, to suppress apoptosis, evade type I interferon responses, and drive pro-inflammatory cytokine production. The interplay between these signaling and metabolic pathways highlights a dual role of host processes: enabling viral replication while activating antiviral immune responses. The review also examines potential therapeutic strategies targeting metabolic and signaling pathways to combat DENV infection, including glycolysis inhibitors, lipid metabolism modulators, and host-directed therapies. While significant progress has been made in understanding DENV-induced immunometabolism, further research is needed to elucidate the precise molecular mechanisms and translate these findings into clinical applications. This study underscores the importance of integrating metabolic and signaling insights to identify novel therapeutic targets against DENV and related flaviviruses, addressing the critical need for effective antiviral interventions
Nanocarriers for cutting-edge cancer immunotherapies
No full textCancer immunotherapy aims to harness the body's own immune system for effective and long-lasting elimination of malignant neoplastic tissues. Owing to the advance in understanding of cancer pathology and immunology, many novel strategies for enhancing immunological responses against various cancers have been successfully developed, and some have translated into excellent clinical outcomes. As one promising strategy for the next generation of immunotherapies, activating the multi-cellular network (MCN) within the tumor microenvironment (TME) to deploy multiple mechanisms of action (MOAs) has attracted significant attention. To achieve this effectively and safely, delivering multiple or pleiotropic therapeutic cargoes to the targeted sites of cancerous tissues, cells, and intracellular organelles is critical, for which numerous nanocarriers have been developed and leveraged. In this review, we first introduce therapeutic payloads categorized according to their predicted functions in cancer immunotherapy and their physicochemical structures and forms. Then, various nanocarriers, along with their unique characteristics, properties, advantages, and limitations, are introduced with notable recent applications in cancer immunotherapy. Following discussions on targeting strategies, a summary of each nanocarrier matching with suitable therapeutic cargoes is provided with comprehensive background information for designing cancer immunotherapy regimen
3D-printing of shear-thinning and self-healing gelatin/starch/halloysite-nanotube hydrogels for soft tissue engineering: An in vitro and in vivo assessment
No full textShear-thinning and self-healing hydrogels are essential for various biomedical applications, specially 3D-printing. This study developed a novel shear-thinning and self-healing hydrogel based on gelatin, starch, and Halloysite-nanotubes (G–S–H) for 3D-printing soft tissues. Different G–S–H ratios and cross-linking reagents (i.e. EDC–NHS and glutaraldehyde) were employed to enhance mechanical properties and degradation rates. Characterization encompassed compression and rheological tests, degradation rates, zeta potential and Dynamic light scattering measurement, morphological analysis, and cytotoxicity assessment. The hydrogels demonstrated suitable stiffness resembling soft tissues and exhibited non-Newtonian behavior with distinct shear-thinning and self-healing properties. In vivo assessments of implanted scaffolds in rats revealed rapid degradation of the non-cross-linked scaffold subcutaneously, while the EDC–NHS scaffold showed prolonged degradation over 60 days, supporting tissue ingrowth into inter-filament spaces and filament pores. Histological analysis indicated initial acute inflammatory responses followed by transition to mild immune responses by day 60. The EDC–NHS-cross-linked scaffold supported higher vascularization and collagen deposition compared to the glutaraldehyde-cross-linked scaffold. Overall, the G–S–H hydrogels showed promise for 3D-printing applications in soft tissue engineering, offering optimal mechanical properties, degradation rate and biocompatibility for long-term tissue support. This study underscores the importance of scaffold composition in governing degradation rates, tissue integration, and biocompatibility in tissue engineering applications
Intelligent Grading of Green Cardamom Using Data Fusion of Electronic Nose and Computer Vision Methods
No full textIn this research, the intelligent quality grading of green cardamom was carried out using electronic nose (e-nose) and computer vision (CV) methods along with machine learning (ML) approaches. Cardamom samples were analyzed in three grades including Grade 1 (healthy and green), Grade 2 (healthy with yellow color), and Grade 3 (immature and shriveled) for capsules and Grade 1 (Black), Grade 2 (Brown), and Grade 3 (Yellow and red) for seeds. Three ML algorithms including Decision Tree (DT), Bayesian Network (BN), and Support Vector Machine (SVM) were used to classify the quality grades. Results showed that the correlation-based feature selection (CFS) algorithm decreased the number of input features and increased the classification performance. For classifying cardamom capsule samples based on the visual features, the CFS-BN model was the best classifier, with the root mean squared error (RMSE) and accuracy of 0.1408 and 96.67%, respectively. The RMSE and accuracy of this model for classifying cardamom seeds based on image features were 0.1220 and 96.67%, respectively. In classifying cardamom seeds using e-nose data, the CFS-DT model was the best classifier with RMSE and accuracy of 0.2093 and 93.33%, respectively. The CFS-BN model was the best for classifying cardamom capsules with an RMSE of 0.1126 and an accuracy of 96.67%. The fusion of e-nose and CV data increased the model performance compared to the separate use of e-nose and CV datasets. The accuracy of the CFS-BN model using the combination of CV and e-nose data was 100% during both the calibration and evaluation stages. It can be concluded that data fusion of e-nose and CV methods can be effectively used to develop an intelligent, accurate, reliable, fast, and non-destructive system for quality grading of cardamom capsules and seeds
Development of the equivalent air temperature index (EATI) among male workers under hot and dry and hot and humid climatic conditions
No full textIdentifying knowledge gaps in social determinants of health and related challenges in Iran; 2023
No full textBackground: Socioeconomic determinants of health (SDH) account for about 40% of modifiable determinants of health, followed by health behaviours (30%), clinical care (20%) and physical environmental factors (10%). The “10/90 gap” is the idea that only 10% of global health research is devoted to conditions that account for 90% of the global disease burden. For over a decade, SDH research centres have been established in Iran to generate evidence and address SDH. Objective: The purpose of this study was to evaluate the activities and challenges faced by SDH research centres and identify knowledge gaps. Methods: We systematically categorized 759 approved projects (2012–2022) from 29 SDH centres using predefined themes (e.g. mental health, COVID-19, social inequalities). Interrater reliability was ensured through dual independent coding, with discrepancies resolved by consensus. In addition, a bibliometric analysis of 5892 PubMed-indexed articles was conducted using VOSviewer, a validated tool for mapping research trends and collaborations. This phase provided objective insights into publication patterns, keyword clusters and interdisciplinary networks. Finally, semi-structured surveys were conducted with SDH researchers to identify knowledge gaps and prioritize research areas. Prioritization criteria (e.g. disease burden, equity impact) were scored using a five-point Likert scale, and the results were validated through an expert panel to ensure alignment with real-world challenges. Results: Out of the 759 approved research projects gathered from 29 reviewed centres, 79 projects were related to mental health, and 53 were related to coronavirus disease 2019 (COVID-19). A total of 5892 articles from 35 research centres obtained by searching PubMed were reviewed and analysed with VOS viewer software. The most frequently used keywords in the centres’ published works are COVID-19, meta-analysis, systematic review, depression, anxiety, and quality of life. In 11 clusters, the 35 research centres under investigation collaborate with 82 additional research centres. Measuring different SDHs at the population level and carrying out related interventions cost far more than the centres’ annual budget. Because of this and other factors stated in the results section, the research centres have shifted their focus to smaller research and more accessible and limited groups and subjects. Conclusions: There is a mismatch between the subjects that the research centres’ researchers believe should be studied and the approved projects of the centres, as is evident from a review of the centres’ projects and their opinions. Numerous issues may be the root of these discrepancies, such as methods for ranking research subjects, methods for selecting study target groups, how to assess research centres and the different criteria set by colleges and universities
Mediterranean diet and prime diet quality score are associated with reduced risk of premature coronary artery disease in Iran: a multi-centric case-control study
No full textThe Mediterranean diet (Med-Diet) is widely recognized for its protective effect in cardiovascular diseases (CVDs), less is known about the associations between health and adherence to the Prime Diet Quality Score (PDQS). This study investigates the relationship between adherence to the Med-Diet and PDQS with the risk of premature coronary artery disease (PCAD) in an Iranian population. A total of 3287 participants were included in this multicenter case-control study across various ethnic groups in Iran, categorized into PCAD cases (n = 2106) and controls (n = 1181). PCAD cases were defined as individuals with at least one coronary artery exhibiting ≥ 75% stenosis or a left main coronary artery with ≥ 50% stenosis, while controls had normal coronary arteries. Dietary intake was assessed using a semi-quantitative food frequency questionnaire (FFQ), previously validated for accuracy in the Iranian population Adherence to the Med-Diet was assessed using a standardized scoring system, awarding one point for higher consumption of beneficial food groups (such as vegetables, whole grains, legumes, fish, nuts, and a high monounsaturated-to-saturated fat ratio) and one point for lower consumption of less favorable foods (such as red and processed meats). The total score ranged from 0 to 9, with higher scores indicating greater adherence to the Med-Diet. The PDQS, a dietary quality index, evaluated adherence across 14 healthy and 7 unhealthy food groups, with higher scores reflecting better diet quality. Logistic regression models were employed to examine the association between dietary scores and PCAD risk. Participants with higher adherence to both the Med-Diet and PDQS had significantly lower odds of PCAD (OR = 0.30, 95% CI: 0.22, 0.40; P for trend < 0.001 for PDQS), with a stronger association observed for the Med-Diet (OR = 0.08, 95% CI: 0.06, 0.10; P for trend < 0.001). Additionally, higher adherence to the Med-Diet (OR = 0.04, 95% CI 0.03, 0.05) and PDQS (OR = 0.21, 95% CI: 0.17, 0.26) was inversely associated with PCAD severity in the fully adjusted model. This study showed a protective association of the Med-Diet and PDQS with reduced risk of PCAD in the Iranian population
CD73 Molecule Inhibitor Upregulates miR16 Expression in Experimental Glioblastoma and Inhibits Angiogenesis by Targeting VEGF
No full textThe function of CD73 (Cluster of Differentiation 73), an enzyme involved in the formation of adenosine (ADO), in the development of glioblastomas has been demonstrated. Indeed, ADO helps tumor angiogenesis by stimulating endothelial cell migration, proliferation, and tube formation. However, the details of the molecular mechanisms are not yet fully understood. Given the importance of angiogenesis in cancer progression, invasion, and metastasis, this study aimed to investigate how the inhibition of CD73 by adenosine-5′-(α, β-methylene) diphosphate (APCP) affects the angiogenesis process of experimental orthotopic glioblastoma at mRNAs, microRNAs, and protein levels. According to the real-time-polymerase chain reaction (RT-PCR) results, inhibition of CD73 decreased the angiogenesis of glioblastoma by reducing the expression of vascular endothelial growth factor (VEGF) and hypoxia-inducible factor 1-alpha (HIF-1α) by ****P < 0.0001 and **P < 0.01, respectively. Furthermore, immunohistochemical staining showed that this treatment protocol attenuated the expression of VEGF and CD31. Moreover, APCP treatment significantly increased miR-16 expression in glioblastoma model rats by P < 0.001, but no significant change in miR-29A expression was observed. The results showed that the treatment did not lead to systemic damage or significant weight loss. Our results suggest that inhibition of CD73 may reduce the formation of new tumor vessels by inhibiting the VEGF, HIF-1α, and CD31 in this process. Therefore, CD73 may be a practical target and provide new opportunities to improve the treatment of malignant brain tumors
Dementia in People With Multiple Sclerosis: A Systematic Review and Meta‐Analysis
No full textIntroduction: Multiple sclerosis (MS), as an autoimmune demyelinating disorder, is associated with cognitive dysfunction. Dementia can result from severe cognitive dysfunction or other pathways in MS, but the exact mechanisms and prevalence are unknown. Objective: This review aimed to determine the pooled prevalence and risk of dementia in people with MS (PwMS). Design: This meta-analysis was performed in accordance with the guidelines established by the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA). Methods: Embase, PubMed, Web of Science, and Scopus were comprehensively searched up to August 29, 2024, to identify observational studies that examined the prevalence or hazard ratio (HR) of dementia among PwMS. This meta-analysis used a random-effects model to calculate the pooled prevalence and risk of dementia among PwMS, where the prevalence rate and HR were the main metrics for effect size. Results: Ten studies, including a total of 37,831 PwMS, estimated the prevalence of dementia in PwMS to be 5.31% (I2 = 99.2%, 95% CI: 2.25%–11.98%). In addition, a meta-analysis of four studies assessed the HR of dementia among PwMS, revealing a pooled HR of 1.67 (p < 0.01, I2 = 73.5%, 95% CI: 1.31–2.13). Conclusion: While dementia is not a common feature of MS, PwMS still have a significantly higher risk of developing it, compared to healthy indiviuals. However, the considerable variability across studies indicates that these estimates should be interpreted with caution, as inconsistencies in research approaches may have influenced the results. These findings warrant further validation
The effect of an educative-supportive program based on the continuous care model on daily living activities and sleep quality in peoples with epilepsy
No full textThe impairment of sleep quality and the occurrence of frequent nocturnal awakenings significantly contribute to the reduction of effective sleep duration in individuals diagnosed with epilepsy. This deterioration not only compromises overall life satisfaction but also adversely affects cognitive functioning and concentration on daily living activities. Therefore, the imperative for enhanced management strategies for this disorder among individuals with epilepsy is critically important. This study is designed to systematically assess the impact of an educational-support program grounded in the Continuous Care Model on the daily living activities and sleep quality of individuals with epilepsy. Methods: This clinical trial was conducted in 2023, involving 70 patients diagnosed with epilepsy, who were selected through purposive sampling and subsequently randomized into intervention and control groups. The intervention group participated in a 12-week program formulated according to the principles of the Continuous Care Model. Data collection was executed utilizing a demographic questionnaire, the Barthel Activities of Daily Living Scale, and the Pittsburgh Sleep Quality Index (PSQI). Statistical analyses were performed using SPSS software version 22 to evaluate the data. Findings: The study population consisted of 42.9 % females and 57.1 % males, with a mean age of 37.8 ± 16.6 years. The mean age for the intervention group was 34.9 ± 12.9 years, while the control group had a mean age of 40.7 ± 19.4 years. Prior to the intervention, no statistically significant differences were identified between the intervention and control groups concerning the mean scores for daily living activities (P = 0.24) and sleep quality (P = 0.377). However, immediately following the intervention and at the two-month follow-up, statistically significant differences were observed between the two groups in the mean scores for daily living activities (P < 0.001) and sleep quality (P < 0.001). Conclusion: The implementation of a structured care program based on the Continuous Care Model has demonstrated beneficial effects on both daily living activities and sleep quality in individuals with epilepsy. Given its safety profile, cost-effectiveness, and proven efficacy, the integration of this model into standard care practices is strongly advocated to enhance the functional capabilities and sleep quality of individuals living with epilepsy