Iranian Journal of Public Health最新文献

Background: Gliomas are the most frequent and dangerous primary cerebral tumors. Therefore, there is a need to develop molecular targets for the diagnosis and treatment for glioma.

Methods: In September 2020, we retrieved the expression matrix of glioblastoma (GBM) sufferers and pertinent clinical data from the TCGA (The Cancer Genome Atlas) database. Prognostic differences between various families with sequence similarity 110 member C (FAM110C) expression groups were assessed by Kaplan-Meier with log-rank test. The R platform get used to assess the accuracy of FAM110C delivery in predicting the prognosis of PDAC using a time-dependent receptor operating characteristic (ROC) curve. The delivery level of FAM110C was determined by qRT-PCR and western blot. Gene set enrichment investigated possible mechanisms between different FAM110C expression groups in GBM (GSEA). The impact of FAM110C on glioma cell movement was discovered using migration test. The drug's gene-targeting impact was validated by the CCK8 test.

Results: A total of 173 GBM samples were obtained from the TCGA database, with 148 including information on IDH1 mutations and 151 containing information on overall survival. The mRNA expression level of FAM110C was greater in wild-type GBM, according to qRT-PCR data. The connection between FAM110C expression and Hallmark, GO, and KEGG pathway gene sets was investigated using GSEA software. We used migration test to assess the impact of FAM110C on glioma motility in order to confirm the findings of the GSEA analysis.

Conclusion: FAM110C might get used as a possible diagnostic and prognostic biomarker for wild-type GBM, and its inhibition could be used to prevention and treatment wild-type GBM.

Background: One of the negative effects of the COVID-19 illness, which has affected people all across the world, is Alzheimer's disease. Oblivion after COVID-19 has created a variety of issues for many people. Predicting this issue in COVID-19 patients can considerably lessen the severity of the problem.

Methods: Alzheimer's disease was predicted in Iranian persons with COVID-19 in using three algorithms: Nave Bayes, Random Forest, and KNN. Data collected by private questioner from hospitals of Tehran Province, Iran, during Oct 2020 to Sep 2021. For ML models, performance is quantified using measures such as Precision, Recall, Accuracy, and F1-score.

Results: The Nave Bayes, Random Forest algorithm has a prediction accuracy of higher than 80%. The predicted accuracy of the random forest algorithm was higher than the other two algorithms.

Conclusion: The Random Forest algorithm outperformed the other two algorithms in predicting Alzheimer's disease in persons using COVID-19. The findings of this study could help persons with COVID-19 avoid Alzheimer's problems.

Background: Globally, population growth and ageing are expected to increase the risk of vision impairment for more people. Eye disorders impose heavy social and economic burdens on communities through increased poverty, reduced quality of life, and decreased employment. We aimed to calculate the economic burden of eye diseases in Iran.

Methods: Prevalence-based and top-down cost estimation methods were used with a sociological approach. Data were collected from the Northeastern Ophthalmology Center Institute for Health Assessment, and Evaluation, besides the 2017 census. Eye diseases were classified according to the ICD10. Data were analyzed using Excel 2016 software.

Results: Survey data were collected from 19,113 patients with vision loss and eye disorders. The average cost of vision loss/eye disorders was estimated to be $250.3. The findings indicated that the economic burden of visual diseases was $2,844 million a year, with direct medical costs comprising 87% (66% of inpatient and 21% of outpatient) and direct non-medical and indirect costs estimated at 6% and 7%, respectively. Furthermore, 72.8% of direct medical costs was paid by insurance companies, 20.6% by patients, and 6.6% by the government.

Conclusion: Eye diseases and vision loss in Iran, as in other countries, are costly for the health system and society. Instituting effective policies and measures to address this rising burden should be a national priority. Another suggestion in this area would be to focus on preventive care and policies such as health education, highlighting the role of reorientation of health services and advocacy (for policies that promote eye health), where relevant.