MATERIALS AND METHODS: The GIS software package "Epidemiological Atlas of Russia" was designed for data monitoring, epidemiological analysis, and cartographic visualization and was implemented as a web resource consisting of a web application, a package administration module, and a database management system. The following development tools were used to create the package: JavaScript, PHP, additional mapping libraries (Leaflet, OpenStreetMap), MySQL database management systems, Visual Basic .NET. The primary information for the database was taken from official federal statistical observation forms No.1 and No.2 "Information on infectious and parasitic diseases".
RESULTS: Analytical methods and GIS technologies used in epidemiological practice were evaluated, optimal technical solutions based on the experience of developing the "Epidemiological Atlas of the Volga Federal District" were selected. A versatile database structure was designed and developed to create an array of input and output statistical values of an epidemiological nature. Original algorithms were created to obtain and evaluate epidemiological indicators. Web application "Epidemiological Atlas of Russia" was developed to present, analyze, and visualize information on infectious and parasitic diseases in the subjects of a district, federal districts, and the Russian Federation as a whole. It allows to work with report forms of the Ministry of Health to organize federal statistical monitoring in the field of health protection and with laboratory studies results to create thematic modules providing detailed information on individual nosologies. Initial data were temporally broken down by months, and spatially, by Russian Federation subjects. All visualization results were dynamically updated and generated based on user's interactive request.
CONCLUSION: GIS software package "Epidemiological Atlas of Russia" was developed as an open and publicly accessible information resource and is designed to improve the quality of epidemiological monitoring, operational and retrospective epidemiological analysis of the incidence of current infectious and parasitic diseases in the Russian Federation. The package is intended for use in federal executive authorities, in supervisory authorities and institutions of Rospotrebnadzor, in medical organizations of the Ministry of Health of the Russian Federation and is in line with the state policy aimed to introduce modern technologies into practice.
MATERIALS AND METHODS: We have analyzed 17 immunological parameters in 63 schizophrenia patients and 36 healthy volunteers. The parameters of humoral immunity, systemic level of the key cytokines of adaptive immunity, anti-inflammatory and pro-inflammatory cytokines, and other inflammatory markers were determined by enzyme immunoassay. Applied methods of machine learning covered the main group of approaches to supervised learning such as linear models (logistic regression), quadratic discriminant analysis (QDA), support vector machine (linear SVM, RBF SVM), k-nearest neighbors algorithm, Gaussian processes, naive Bayes classifier, decision trees, and ensemble models (AdaBoost, random forest, XGBoost). The importance of features for prediction from the best fold has been analyzed for the machine learning methods, which demonstrated the best quality. The most significant features were selected using 70% quantile threshold.
RESULTS: The AdaBoost ensemble model with ROC AUC of 0.71±0.15 and average accuracy (ACC) of 0.78±0.11 has demonstrated the best quality on a 10-fold cross validation test sample. Within the frameworks of the present investigation, the AdaBoost model has shown a good quality of classification between the patients with schizophrenia and healthy volunteers (ROC AUC over 0.70) at a high stability of the results (σ less than 0.2). The most important immunological parameters have been established for differentiation between the patients and healthy volunteers: the level of some systemic inflammatory markers, activation of humoral immunity, pro-inflammatory cytokines, immunoregulatory cytokines and proteins, Th1 and Th2 immunity cytokines. It was for the first time that the possibility of differentiating schizophrenia patients from healthy volunteers was shown with the accuracy of more than 70% with the help of machine learning using only immune parameters.The results of this investigation confirm a high importance of the immune system in the pathogenesis of schizophrenia.
OBJECTIVE: This scoping review seeks to find and map research publications that investigate the effect of MF on SSMP in team sports.
METHODS: Web of Science, Scopus, and PubMed were searched as the main databases, and CENTRAL, Psychology, and Behavioral Sciences Collection, SPORTDicus obtained from EBSCOhost, as well as gray literature was searched for relevant literature and Google Scholar. Cognitive tasks before the SSMP exam are the focus of the selected literature on mental exhaustion. Only experiments testing mental and non-mental exhaustion were chosen.
RESULTS: Twelve studies fulfill the requirement of selection criteria. SSMP in team sports, including soccer, basketball, cricket, and Australian football mainly is examined as physical and technical performance. More specifically, MF significantly influenced physical performance measured as intermittent endurance and total distance (P < 0.05), while data was inclusive when assess in an ecological setting (e.g., small-sided game) (P > 0.05). Technical performance was mainly measured as ball loss, errors in passing and shooting, interception, and successful tackle and showed a dramatic impairment (P < 0.05). The decline of physical activity is relevant with higher level PRE, while decreased technical performance is related to impaired attention resources shown as visual perceptual.
CONCLUSION: MF adversely influences SSMP in team sports. The most relevant theory for future study to examine the impacts of MF on team-sport athletes could be the psychological model of exercise and its potential extension on attention resources, rather than the traditional "catastrophe" theory.
OBJECTIVE: To analyze the role of dentists in identifying Monkeypox cases and limiting its spread.
METHODS: We conducted a scoping review on monkeypox and its oral manifestation. PRISMA protocols were observed in data collection. The relevant literature search was conducted in relevant databases like PubMed, Scopus, Web of Science, Embase, CINAHL, and Google Scholar. Relevant articles related to Monkeypox, and Dentistry were included in the final review. Articles published from March 2022- September 2022 were included in the review. Keywords and Mesh words related to monkeypox, and dentistry were used as part of the search strategy.
RESULTS: A total of 1881 articles were reviewed, among which 7 articles were included. Dentists were strongly advised to be on high alert for Monkeypox symptoms due to their close contact with patients. Around 70% of Monkeypox cases reported oral lesions at early stages, which requires a differential diagnosis from other oral lesions. Considering this, dentists should be well-versed in this new and emerging threat.
CONCLUSION: Although dentists have been shown to play an important role in the treatment of monkeypox, there is insufficient data available. More research on dentistry and monkeypox will be needed in the near future.
METHODS: Therefore, this study translates and culturally adapts the M-CHAT-R/F into Malay and verifies its psychometric properties among the Malaysian population. 500 Malaysian toddlers aged between 18 and 48 months were recruited from different settings. The parents of the toddlers were asked to complete the Malaysian M-CHAT-R/F. The reliability of the screening tool was verified using Cronbach's alpha.
RESULTS: By comparing the screening outcomes of the Malaysian M-CHAT-R/F and clinical evaluation results, the prevalence of ASD was determined as 6.6% in the sample. High values of sensitivity (96.6%) and specificity (93.2%) and a satisfactory positive predictive value (47.5%) supported the validity of the Malaysian M-CHAT-R/F. Furthermore, the receiver operating characteristic analysis yielded three as the optimal cut-off score of the Malaysian M-CHAT-R/F.
DISCUSSION: These results suggest that the Malaysian M-CHAT-R/F is an effective screening tool reliable for use in clinical practice. Further investigation using a representative sample of the whole country is recommended given the high prevalence rate obtained in the current sample.
METHODS: A cross-sectional study used to collect the data via an online cross using a form created from a google questionnaire forms. A total of 1,802 respondents were gathered at a single point in time. The authors used the Health Belief Model (HBM) approach to measure and create a model for the prevention of local transmission of COVID-19.
RESULTS: This study found that more than half of the respondents still had low perceived susceptibility (16%) and severity (43%). There were only 3% respondents with perceived barriers and 19% with strong self-efficacy. The findings showed that self-efficacy and perceived barriers had statistically significant relationships with preventive behavior (p-value <0.05). The goodness of fit index showed that the proposed model was not fit for the data (RMSE<0.080, GFI>0.950, AGFI>0.950, SRMR<0.100), which means that it was not fit to describe the empirical phenomenon under study.
CONCLUSIONS: This study found that more than half of the respondents still had low perceived susceptibility (84%) and severity (67%), but more than half had high perceived benefits (54%). Only a few respondents had significant barriers to implementing COVID-19 transmission prevention behaviours (3%). Still, most respondents had low perceived self-efficacy (81%), and only 60% had good behaviours related to COVID-19 prevention. In the context of COVID-19 preventive behaviour, we recommended to improve perceived susceptibility and severity by providing the correct information (which contain information about how people susceptible to the virus and the impact of infected by the virus) with the local cultural context.
METHODS: A cross-sectional study involving 7585 adults was performed covering the rural and urban areas. Respondents with systolic blood pressure (SBP) of 120-139 mmHg and/or diastolic blood pressure (DBP) of 80-89 mmHg were categorized as prehypertensive, and hypertensive categorization was used for respondents with an SBP of ≥140 mmHg and/or DBP of ≥90 mmHg.
RESULTS: Respondents reported to have prehypertension and hypertension were 40.7% and 38.0%, respectively. Those residing in a rural area, older age, male, family history of hypertension, and overweight or obese were associated with higher odds of prehypertension and hypertension. Unique to hypertension, the factors included low educational level (AOR: 1.349; 95% CI: 1.146, 1.588), unemployment (1.350; 1.16, 1.572), comorbidity of diabetes (1.474; 1.178, 1.844), and inadequate fruit consumption (1.253; 1.094, 1.436).
CONCLUSIONS: As the prehypertensive state may affect the prevalence of hypertension, proactive strategies are needed to increase early detection of the disease among specific group of those residing in a rural area, older age, male, family history of hypertension, and overweight or obese.