Application of machine learning for antibiotic resistance in water and wastewater: A systematic review.

Antibiotic resistance (AR) is considered one of the greatest global threats in the current century, which can only be overcome if all interconnected areas of humans, animals and the environment are taken into account as part of the One Health concept proposed by the World Health Organization (WHO). Water and wastewater are among the most important environmental media of AR sources, where the phenomena are generally non-linear. Therefore, the aim of this study was to investigate the application of machine learning-based methods (MLMs) to solve AR-induced problems in water and wastewater. For this purpose, most relevant databases were searched in the period between 1987 and 2023 to systematically analyze and categorize the applications. Accordingly, the results showed that out of 12 applications, 11 (91.6%) were for shallow learning and 1 (8.3%) for deep learning. In shallow learning category, n = 6, 50% of the applications were regression and n = 4, 33.3% were classification, mainly using artificial neural networks, decision trees and Bayesian methods for the following objectives: Predicting the survival of antibiotic-resistant bacteria (ARB), determining the order of influencing parameters on AR-based scores, and identifying the major sources of antibiotic resistance genes (ARGs). In addition, only one study (8.3%) was found for clustering and no study for association. Surprisingly, deep learning had been used in only one study (8.3%) to predict ARGs sequences. Therefore, working on the knowledge gaps of AR, especially using clustering, association and deep learning methods, would be a promising option to analyze more aspects of the related problems. However, there is still a long way to go to consider and apply MLMs as unique approaches to study different aspects of AR in water and wastewater.

Improving data adequacy of ultrasonography reports for non-alcoholic fatty liver disease (NAFLD) through a national structured template.

BACKGROUND: Non-alcoholic fatty liver disease (NAFLD) is a prevalent disorder that increases due to lifestyle, the rising rate of obesity, and population ages worldwide. Diagnostic ways, including sonography, do not have an explicit reporting structure. PURPOSE: To create a structure template for NAFLD reporting, investigate its completeness, and assess the specialist opinions of using it in clinical practice. MATERIAL AND METHODS: A structured reporting template (SRT) was designed and implemented in four stages. At first, important features were extracted from a comprehensive literature review and were evaluated by 10 radiologists and gastroenterologists using the Likert scale. Finally, the usefulness of the SRT in comparison with the conventional reporting template (CRT) was judged by 10 gastroenterologists completing the questionnaire. RESULTS: Demographic information and sonography of the liver, gallbladder, and spleen organs were the most critical features. The completeness scores of SRT reports were higher than CRT scores for almost all the factors studied. The difference in the scores was significant for most of the parameters. Moreover, the total completeness score increased from 42% in CRT to 92% in SRT. A comparison of the report adequacy of two reports was seen in all items. The SRT obtained more rates from specialists. CONCLUSION: Introduction of the SRT for NAFLD significantly enhanced the completeness of reporting to reduce variability in the interpretation of the related reports by clinicians. Nevertheless, more studies are needed to generalize the results in real scales for patients with NAFLD.

Practical Recommendations for the Preoperative Screening and Protective Protocols in Cancer Surgeries During COVID-19: A Systematic Review.

Introduction: The new coronavirus (COVID-19) has posed many new challenges to the health care and the timing of surgical care. At the beginning of the pandemic many guidelines recommended postponing elective surgical procedures to reallocate resources. As regards, delay in cancer treatment could be effective on cancer progression. The aim of this systematic review was to outline a guideline for preoperative screening before cancer surgeries and protecting health care workers during the pandemic. Materials and Methods: This study was conducted through a search in electronic databases up to August 2020. PubMed, EMBASE, Web of Science, Scopus, Science Direct, and Google Scholar databases were searched without time limitation. The keywords were a combination of preoperative, cancer surgery, COVID-19, and their synonyms. Results: The most commonly used ways to triage preoperatively were telephone pre-assessment for suspicious symptoms and history of contact or travel, 14-day self-isolation, in- hospital queries at admission, temperature monitoring, and isolation in a single room COVID-free ward or physical distancing. Reverse transcription-polymerase chain reaction (RT-PCR) test 24-72 h before operation was recommended commonly, except in inaccessible centers, but non-contrast chest-CT scan is not routinely advised for elective surgeries to salvage medical resources. Recommended personal protective equipment (PPE) for staffs were wearing N95 mask in addition to gown, gloves, eye protection in aerosol-generating procedures (AGPs), and wearing gloves, hats, and disposable surgical masks, practice distancing, and hand hygiene for all staffs. Meanwhile team separation of hospital staffs caring for COVID-19 patients, segregated areas for COVID-19 clean and contact, restriction of visitors and family members, and personal distancing are mostly recommended. Conclusion: We hope this review would be a guidance for triage, preoperative testing, and summarizing safety principles during COVID-19 pandemic alongside with surgical reintegration.

Socioeconomic determinants of global distribution of multiple sclerosis: an ecological investigation based on Global Burden of Disease data.

BACKGROUND: Socioeconomic factors may be involved in risk of multiple sclerosis (MS), either indirectly or as confounding factors. In this study two comprehensive indicators reflecting socioeconomic differences, including the Human Development Index (HDI) and Prosperity Index (PI), were used to assess the impact of these factors on the worldwide distribution of MS. METHODS: The data for this global ecological study were obtained from three comprehensive databases including the Global Burden of Disease (as the source of MS indices), United Nations Development Programme (source for HDI) and the Legatum Institute Database for PI. MS indices (including prevalence, incidence, mortality, and disability-adjusted life years) were all analyzed in the form of age- and sex-standardized. Correlation and regression analyses were used to investigate the relationship between HDI and PI and their subsets with MS indices. RESULTS: All MS indices were correlated with HDI and PI. It was also found that developed countries had significantly higher prevalence and incidence rates of MS than developing countries. Education and governance from the PI, and gross national income and expected years of schooling from the HDI were more associated with MS. Education was significantly related to MS indices (p < 0.01) in both developed and developing countries. CONCLUSION: In general, the difference in income and the socioeconomic development globally have created a landscape for MS that should be studied in more detail in future studies.

Association of the global distribution of multiple sclerosis with ultraviolet radiation and air pollution: an ecological study based on GBD data.

Given the growing global trend of multiple sclerosis (MS), this study was designed to evaluate environmental determinates of the worldwide distribution of MS in the presence of socioeconomic and geographic indices. MS data was obtained from the Institute for Health Metrics and Evaluation website. The air pollution parameters, including particles with aerodynamic diameter less than 2.5 µm (PM2.5), tropospheric ozone, and solid fuel use, were acquired from global burden of disease resources and the World Health Organization. Ultraviolet index (UVI) values were obtained from the Tropospheric Emission Monitoring Internet Service website. Correlation and linear regression analyses were used to investigate the relationship between air pollution and environmental parameters with MS variables. The average prevalence and incidence rates in countries with high UVI were 5.17 and 0.25 per 100,000, respectively, and in countries with low UVI were 101.37 and 0.78, respectively. The results showed negative associations between prevalence, incidence and mortality of MS with ozone concentrations (ß = - 1.04, - 0.04, and - 0.01 respectively; P < 0.01). Also, the fully adjusted model showed significant negative correlation of UVI with the MS variables in the presence of other variables (P < 0.01). Our findings demonstrated that UVI had the strongest significant inverse association with MS distribution. Consequently, vitamin D intake may be a major contributor to MS development. However, this study showed a slight influence of air pollution on the prevalence of MS in the presence of other parameters. Given the inconsistent results of previous studies, further studies may be required.

A new method of "student-centered formative assessment" and improving students' performance: An effort in the health promotion of community.

BACKGROUND: Improving the learning process in education will empower medical students, and also formative assessment helps improve the teaching-learning process by providing ongoing reflective information about learning gaps. OBJECTIVE: The aim of this study was to explore the effect of student-centered formative assessment by weekly reflective self-correction quizzes on medical laboratory students' performance on the final examination of hematology course in 2018. MATERIALS AND METHODS: A semi-experimental study was conducted on fifty students divided randomly into intervention (n = 25) and control groups (n = 25) using convenience sampling in 2018 from Torbat Heydariyeh University of Medical Sciences, Iran. Data analysis was performed using SPSS software version 16, two-sample t-test, Chi-square test, and analysis of covariance. RESULTS: The intervention had positive effects on students' mean test scores in hematology II so that the intervention and control groups managed to obtain 18.45 ± 1.46 and 14.57 ± 2.64, respectively (P < 0.01). CONCLUSIONS: The results suggested that weekly formative assessments along with reflective self-correction activity and active participation of students in the learning process by designing questions could improve student learning.

Colorectal Cancer Registration: Data Approach to Knowledge.

For ensuring the quality of data and facilitating data exchange between healthcare providers and professional organizations, it is necessary to define a standard data set. The main aim of this study was to define a national minimum data set for colorectal cancer in Iran. To develop this data set, a combination of literature review and two rounds of a modified Delphi technique were used. An initial checklist was proposed based on a literature review and comparative studies. Based on the literature review, main categories, including: demographic information, diagnostic information, treatment information, clinical status assessment information, and clinical trial information were proposed. In this study, the national minimum data set of colorectal cancer was collected. Developing this data set through standard contents can improve effective health information exchange for both healthcare providers and health information systems.