Qazvin University of Medical Sciences
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Plant/algal polysaccharides extracted by microwave: A review on hypoglycemic, hypolipidemic, prebiotic, and immune-stimulatory effect
Get PDFMicrowave-assisted extraction (MAE) is an emerging technology to obtain polysaccharides with an extensive
spectrum of biological characteristics. In this study, the hypoglycemic, hypolipidemic, prebiotic, and immunomodulatory (e.g., antiinflammatory, anticoagulant, and phagocytic) effects of algal- and plant-derived polysaccharides rich in glucose, galactose, and mannose using MAE were comprehensively discussed. The in vitro and
in vivo results showed that these bioactive macromolecules with the low digestibility rate could effectively
alleviate the fatty acid-induced lipotoxicity, acute hemolysis, and dyslipidemia status. The optimally extracted
glucomannan- and glucogalactan-containing polysaccharides revealed significant antidiabetic effects through
inhibiting α-amylase and α-glucosidase, improving dynamic insulin sensitivity and secretion, and promoting
pancreatic β-cell proliferation. These bioactive macromolecules as prebiotics not only improve the digestibility in
gastrointestinal tract but also reduce the survival rate of pathogens and tumor cells by activating macrophages
and producing pro-inflammatory biomarkers and cytokines. They can effectively prevent gastrointestinal disorders and microbial infections without any toxicity
بررسی ارتباط سرمایه اجتماعی با وضعیت روانشناختی و کیفیت زندگی مادران پرخطر مراجعه کننده به مراکز جامع سلامت در شهر قزوین
Get PDFبررسی ارتباط اضطراب ناشی از کوید19 و تاب آوری در پرستاران بخش های ویژه در بیمارستان های شهر قزوین در سال 1400
Get PDFPrediction of noise using artificial neural networks modeling and statistical methods in the woodworking industry
Get PDFIntroduction: Noise pollution is one of the most important pollutants in the work environment and is almost one of the harmful factors for workers' health. Sound prediction is one of the important aspects of sound control in industries. Forecasting is important in the carpentry industry, which is an important part of the woodworking industry and workers are exposed to excessive noise. There are many methods for predicting noise.
Materials and Methods: This research is a study Descriptive, analytical - cross-sectional that was carried out in 6 main phases, which include: 1- Identifying and collecting data 2- Determining the evaluation criteria of statistical models and artificial neural networks 3- Constructing multiple regression 4- Implementing artificial neural networks 5- Optimizing the weights of artificial neural networks It is model sensitivity analysis with genetic algorithm. In the first stage, data was collected from 375 carpentry workshops in Tehran province, Khavaran, Chahardangeh, Nematabad and Delavaran industrial towns. From the 10 main characteristics of acoustic, structural and carpentry processes that affect sound, in the next step, evaluation criteria were presented for comparison and accuracy of both statistical models and artificial neural networks. Then statistical analysis of multiple regressions was done. Then, artificial neural network modeling was implemented with the help of MATLAB software. In the next step, the weights of artificial neural networks were optimized using the genetic algorithm, then the sensitivity analysis of the model was performed using calculations.
Discussion: With the help of evaluation criteria, two models of artificial neural networks and statistical methods were compared. The results showed that artificial neural networks provide more accurate prediction than multiple regression. The best neural network can accurately predict the equivalent sound level, our results showed that the developed experimental methods can be a useful tool for the analysis of noise pollution and enable occupational health professionals to use these methods.
Conclusion: The artificial neural network model showed higher accuracy compared to linear and non-linear regression statistical models. In this study, the artificial neural network was trained 13,000 times by the gradient descent algorithm, which showed higher accuracy compared to similar studies where the repetition rate of the training algorithm was much lower, so this study showed that by increasing the repetition, the prediction accuracy can be increased. . Finally, a graphical user interface program was presented using factors affecting sound to predict noise in the woodworking industry.
Key word: Sound prediction, artificial neural networks, wood industry, sound exposur
Effect of music on the growth monitoring of low birth weight newborns
Get PDFBackground: Low Birth Weight (LBW) is a significant public health problem in many parts of the world and is associated with a range of adverse consequences. The aim of this study was to assess the effect of music on the growth monitoring of LBW newborns. Methods: In this clinical trial, 58 infants with birth weight between 2000 and 2500 g were assessed in the intervention (N: 35) and the control (N: 23) groups. The intervention group received daily classic music for 28 days about 15 to 20 min at home and the control group received only routine treatment. Both groups were followed by daily contact and visited by the pediatrician three times in a month. Primary and secondary outcomes were compared by Student's t-test, Mann Whitney test, chi-square test and repeated measurement ANOVA, being significant p < 0.05. Results: Height, weight, and head circumference were significantly different between two groups (P < 0.001). The time of breastfeeding (BMF), sleep and calming in the intervention were more than the control (P < 0.001). Formula Consumption in the control was more than the intervention (P < 0.001). Conclusion: The classic music can improve anthropometric index, feeding, sleeping time, and calm duration. IRCT registration number: IRCT2017061919077N3. © 2021 The Authors
Author keywords
Growth monitoring; Infant; Low birth weight; Musi
Mental health problems and the associated family and school factors in adolescents: A multilevel analysis
Get PDFObjective: Mental health is one of the most important issues in adolescents' life. Adolescents' health is highly important, because of their role in the future. This study was conducted using multilevel analysis to investigate the risk factors at student and school levels. Method: This was a cross sectional study for which 1740 students and 53 schools were selected between February and March 2018 in Qazvin, Iran. Multistage stratified cluster sampling was used for data collection. Mental health problems were measured by the Strengths and Difficulties Questionnaire (SDQ). Emotional symptom, conduct problem, hyperactivity, peer relationship problem, and prosocial behavior were the subscales. This study used multilevel analysis to determine the association between each of the questionnaire scales and students and schools variables. Results: The prevalence of the mental health problems was 16.2%. Conduct problem was more prevalent than others (21.1%). Overall, the score of mental health problems was significantly lower in boys' schools, in adolescents with physical activity, and in families with high socioeconomic status. Hyperactivity and emotional symptoms were significantly higher in girls' schools. While prosocial behavior and peer relationship problems were significantly higher in boys' schools. The association between variables and the scales of mental health problems was different. Conclusion: Results indicated desirable physical activity and socioeconomic status are effective components in the adolescents' mental health, and, mostly girls' schools were more vulnerable than boys' schools. Therefore, the educational authorities and health policymakers should consider this diversity to design interventional programs and pay more attention to the high-risk adolescents in different schools. Copyright © 2021 Tehran University of Medical Sciences.
Author keywords
Adolescents; Iran; Mental Health; Multilevel Analysis; SDQ; Student
Prevalence of G6PD deficiency in Iranian neonates with jaundice: a systematic review and meta-analysis
Get PDFObjectives: This systematic review and meta-analysis study aimed to estimate the overall prevalence of Glucose-6-phosphate dehydrogenase (G6PD) deficiency in neonates with jaundice who were admitted to hospitals in Iran. Materials and methods: In this systematic review and meta-analysis, we searched PubMed/Medline, Scopus, ISI Web of Sciences, and Iranian Local databases up to December 2019.We calculated Prevalence and 95% Confidence Interval (95% CI) of G6PD deficiency as summary measures. We conducted subgroup analysis based on the sex and quality of studies, while meta-regression were applied for investigating the effect of years of studies and years of publication on the pooled prevalence. We applied sensitivity analysis to investigate the effect of excluding each study on the pooled prevalence estimation. Results: The total sample size was 9799 people. The pooled prevalence of G6PD deficiency among neonates with jaundice in Iran was 7.0% (95% CI: 5.5–8.5%). The results of subgroup analysis showed that, pooled prevalence of G6PD deficiency among male neonate (12.1%, 95%CI: 7.6–16.7%) was more prevalent that female (3.00%, 95%CI: 1.1–4.9%). Based on the sensitivity analysis, lower and higher pooled prevalence of G6PD deficiency was observed 5.8% (95%CI: 4.7–6.9%) and 7.3% (95%CI: 5.7–8.8%) respectively by excluding each study. Conclusion: The overall prevalence of G6PD deficiency was 7% in Iranian neonates with Jaundice. Prevalence was high in male and early hours of life. We recommend screening test for G6PD deficiency in neonates to prevent its complications. © 2021 Informa UK Limited, trading as Taylor & Francis Group.
Author keywords
deficiency; Glucosephosphate dehydrogenase; jaundice; meta-analysis; neonata
Effect of occupational risk factors in cancer incidence in Iran: a Systematic Review
Get PDFBackground: Cancer is the main cause of death in developed countries and the second main cause of death in
developing countries. The aim of this study was to review the occupational risk factors and cancer incident in
Iran.
Materials and Methods: this present systematic review was done based on Preferred Reporting Items for
Systematic Reviews and Meta-Analyses (PRISMA) guidelines on Persian articles with no time limits in
publication and collected from January 2019 to April 2019 from Sid, Magiran and Google Scholar Databases.
Some search terms including “job” or “occupation” “occupational exposure” or “cancer” or “neoplasm were
used.
Results: A total number of 103 articles were detected. After applying the inclusion and exclusion criteria,
finally 18 studies remained in this systematic review with 13897 sample size and 7187 diagnosed patients. Most
included studies researched on non-melanoma skin as the most studied cancer and sunlight exposure as the most
carcinogenic reported occupational risk factor. Among included researches, only four studies were directly
related to occupational cancer with 1837 sample size and 604 diagnosed various cancers in workers that focused
on kidney, bladder and mesothelioma cancers (Pleural mesothelioma and Perivascular mesothelioma) .The
results showed that, the cancer was reported in some occupations more than others.
Conclusion: Most included researches reported skin cancer and exposure to sunlight as the most studied cancer
and occupational risk factor respectively. As regard to importance of effective risk factors on cancer incidence ,
identification and control of occupational risk factor in the work environment should be a main key element of
national cancer control program in countries specially developing countries. So it is recommended to develop
the researches in field of occupational cancer in Iran
Cyclic Mastalgia in Iranian Women: A Review
Get PDFDespite the high prevalence of cyclic mastalgia, there is much disagreement and uncertainties about its treatment methods. The present study aims to review studies conducted on cyclic mastalgia over the past two decades in Iran. In this regard, a search was conducted in Scopus, SID, PubMed, Google Scholar, ScienceDirect, and IranMedex databases on articles published in Persian and English from 1998 to 2018 using the following keywords: “Mastalgia”, “cyclic mastalgia”, “breast pain”, and “Mastodynia”. Initial search yielded 975 articles. Of these, 29 were selected for review based on inclusion criteria; 19 interventional and 10 non-interventional. Based on the results, most studies reported a mastalgia prevalence of about 30% in Iran. The most common age for cyclic mastalgia was 30 years. In most studies, a significant relationship between premenstrual syndrome and cyclic mastalgia was reported. The use of vitamins and herbal plants were the most common interventions for cyclic mastalgia, while counseling was the least common type. It seems that cyclic mastalgia affects the sleep quality and physical and sexual activities. Due to the high prevalence of cyclic mastalgia reported in various studies in Iran, and the lack a same treatment protocol, further study on cyclic mastalgia is recommended
Macro ergonomics and health workers during the COVID-19 pandemic
Get PDFThe COVID-19 pandemic is a disaster all over the
world. During this global calamity, the health and
safety of workers in the workplace should be considered.
Occupational exposure to pathogens is an
inherent risk factor of health care workplaces [1].
During the pandemic, the medical staff of hospitals
on the frontlines of medical services take the necessary
measures to identify patients, isolate them and
treat them [2]. The health and safety of these individuals
can be enhanced by ergonomics through the
redesign and re-evaluation of tasks, environments,
and systems. Ergonomics or human factors is “the scientific
discipline concerned with the understanding of
interactions among humans and other elements of a
system, and the profession that applies theory, principles, data and methods to design in order to optimize
human well-being and overall system performance”
(IEA Council, 2014)