Search

Abstract Objective Mobile-based educational software offers a wealth of resources that can foster the growth of learners and facilitate the creation of an interactive learning environment. This environment encourages both students and instructors to engage in exploration and the examination of various medical issues. The objective of this study is to design, implement, and evaluate an electronic educational program focused on common medical conditions, specifically tailored for medical students and accessible through mobile phones. Method The study was conducted following an action research approach, which comprised four key stages: needs assessment, application design, training, and evaluation. This research took place at the Kermanshah University of Medical Sciences’ Medical School. In the needs assessment phase, a formal survey was distributed to the teaching faculty members, requesting them to identify diseases and medical issues of high importance for medical interns’ education that were suitable for virtual teaching. Each faculty member was asked to prioritize a minimum of three and a maximum of seven cases. Subsequently, 10 faculty members from various departments completed the survey, leading to the identification of 47 common diseases after eliminating duplicates. These 47 cases were then presented to 30 medical interns, who were asked to select the 20 most significant cases. The 20 diseases with the highest statistical frequency were selected for further development due to resource constraints. The mobile application was developed for the Android platform using the Java programming language and the Android Studio development environment. To assess the application’s effectiveness from the students’ perspective, a questionnaire was designed, encompassing 25 questions across five domains: satisfaction, performance, learning, usability, and educational effectiveness. The questionnaire employed a Likert scale, with response options ranging from ‘completely disagree’ to ‘completely agree,’ scored from 1 to 5. One hundred medical interns and trainees were invited to participate in the evaluation, with 92 of them completing the questionnaires. Results The findings revealed a significant disparity in the average scores between students who underwent traditional teaching methods and those who engaged in mobile-based app-assisted education. This discrepancy was statistically significant across all three examined components. Conclusion Mobile-based learning represents a burgeoning educational approach with profound implications for healthcare education and the enhancement of patient care quality. The widespread integration of mobile phones into the educational framework offers a flexible teaching paradigm, fostering the potential for continuous lifelong learning.

Abstract Background Copy-number variations (CNVs) have been associated with rare and debilitating genomic disorders (GDs) but their impact on health later in life in the general population remains poorly described. Methods Assessing four modes of CNV action, we performed genome-wide association scans (GWASs) between the copy-number of CNV-proxy probes and 60 curated ICD-10 based clinical diagnoses in 331,522 unrelated white British UK Biobank (UKBB) participants with replication in the Estonian Biobank. Results We identified 73 signals involving 40 diseases, all of which indicating that CNVs increased disease risk and caused earlier onset. We estimated that 16% of these associations are indirect, acting by increasing body mass index (BMI). Signals mapped to 45 unique, non-overlapping regions, nine of which being linked to known GDs. Number and identity of genes affected by CNVs modulated their pathogenicity, with many associations being supported by colocalization with both common and rare single-nucleotide variant association signals. Dissection of association signals provided insights into the epidemiology of known gene-disease pairs (e.g., deletions in BRCA1 and LDLR increased risk for ovarian cancer and ischemic heart disease, respectively), clarified dosage mechanisms of action (e.g., both increased and decreased dosage of 17q12 impacted renal health), and identified putative causal genes (e.g., ABCC6 for kidney stones). Characterization of the pleiotropic pathological consequences of recurrent CNVs at 15q13, 16p13.11, 16p12.2, and 22q11.2 in adulthood indicated variable expressivity of these regions and the involvement of multiple genes. Finally, we show that while the total burden of rare CNVs—and especially deletions—strongly associated with disease risk, it only accounted for ~ 0.02% of the UKBB disease burden. These associations are mainly driven by CNVs at known GD CNV regions, whose pleiotropic effect on common diseases was broader than anticipated by our CNV-GWAS. Conclusions Our results shed light on the prominent role of rare CNVs in determining common disease susceptibility within the general population and provide actionable insights for anticipating later-onset comorbidities in carriers of recurrent CNVs.

Objective: Mobile-based educational software offers a wealth of resources that can foster the growth of learners and facilitate the creation of an interactive learning environment. This environment encourages both students and instructors to engage in exploration and the examination of various medical issues. The objective of this study is to design, implement, and evaluate an electronic educational program focused on common medical conditions, specifically tailored for medical students and accessible through mobile phones. Method: The study was conducted following an action research approach, which comprised four key stages: needs assessment, application design, training, and evaluation. This research took place at the Kermanshah University of Medical Sciences' Medical School. In the needs assessment phase, a formal survey was distributed to the teaching faculty members, requesting them to identify diseases and medical issues of high importance for medical interns' education that were suitable for virtual teaching. Each faculty member was asked to prioritize a minimum of three and a maximum of seven cases. Subsequently, 10 faculty members from various departments completed the survey, leading to the identification of 47 common diseases after eliminating duplicates. These 47 cases were then presented to 30 medical interns, who were asked to select the 20 most significant cases. The 20 diseases with the highest statistical frequency were selected for further development due to resource constraints. The mobile application was developed for the Android platform using the Java programming language and the Android Studio development environment. To assess the application's effectiveness from the students' perspective, a questionnaire was designed, encompassing 25 questions across five domains: satisfaction, performance, learning, usability, and educational effectiveness. The questionnaire employed a Likert scale, with response options ranging from 'completely disagree' to 'completely agree,' scored from 1 to 5. One hundred medical interns and trainees were invited to participate in the evaluation, with 92 of them completing the questionnaires. Results: The findings revealed a significant disparity in the average scores between students who underwent traditional teaching methods and those who engaged in mobile-based app-assisted education. This discrepancy was statistically significant across all three examined components. Conclusion: Mobile-based learning represents a burgeoning educational approach with profound implications for healthcare education and the enhancement of patient care quality. The widespread integration of mobile phones into the educational framework offers a flexible teaching paradigm, fostering the potential for continuous lifelong learning. [ABSTRACT FROM AUTHOR]

Background: Copy-number variations (CNVs) have been associated with rare and debilitating genomic disorders (GDs) but their impact on health later in life in the general population remains poorly described. Methods: Assessing four modes of CNV action, we performed genome-wide association scans (GWASs) between the copy-number of CNV-proxy probes and 60 curated ICD-10 based clinical diagnoses in 331,522 unrelated white British UK Biobank (UKBB) participants with replication in the Estonian Biobank. Results: We identified 73 signals involving 40 diseases, all of which indicating that CNVs increased disease risk and caused earlier onset. We estimated that 16% of these associations are indirect, acting by increasing body mass index (BMI). Signals mapped to 45 unique, non-overlapping regions, nine of which being linked to known GDs. Number and identity of genes affected by CNVs modulated their pathogenicity, with many associations being supported by colocalization with both common and rare single-nucleotide variant association signals. Dissection of association signals provided insights into the epidemiology of known gene-disease pairs (e.g., deletions in BRCA1 and LDLR increased risk for ovarian cancer and ischemic heart disease, respectively), clarified dosage mechanisms of action (e.g., both increased and decreased dosage of 17q12 impacted renal health), and identified putative causal genes (e.g., ABCC6 for kidney stones). Characterization of the pleiotropic pathological consequences of recurrent CNVs at 15q13, 16p13.11, 16p12.2, and 22q11.2 in adulthood indicated variable expressivity of these regions and the involvement of multiple genes. Finally, we show that while the total burden of rare CNVs—and especially deletions—strongly associated with disease risk, it only accounted for ~ 0.02% of the UKBB disease burden. These associations are mainly driven by CNVs at known GD CNV regions, whose pleiotropic effect on common diseases was broader than anticipated by our CNV-GWAS. Conclusions: Our results shed light on the prominent role of rare CNVs in determining common disease susceptibility within the general population and provide actionable insights for anticipating later-onset comorbidities in carriers of recurrent CNVs. [ABSTRACT FROM AUTHOR]

The current state of geriatric disease prevention and treatment in China has not yet been able to meet the urgent needs brought about by an aging population, and specific dietary patterns can significantly improve or exacerbate the risk of certain diseases. However, the relationship between geriatric diseases and the dietary patterns of the Chinese elderly population has not been fully explored. CLHLS 2018 were analyzed in the present study. Principal component analysis was employed to identify the main dietary patterns of the Chinese elderly, and binary logistic regression models were used to analyze the associations between these dietary patterns and the 16 common diseases. Four main dietary patterns were identified in the Chinese elderly population: Egg-Milk Pattern, Salt-preserved vegetable-Nut Pattern, Vegetable-Fruit Pattern, and Fish-Meat Pattern. Higher scores for the Egg-Milk Pattern were associated with a greater risk of heart disease, stroke or cardiovascular disease, respiratory disease, glaucoma, prostate tumor, and Parkinson's disease in older adults (p<0.05). Higher scores for Salt-preserved vegetable-Nut Pattern correlated with a greater risk of hypertension, heart disease, and uterine tumors and a lower risk of rheumatism or rheumatoid disease in older adults (P<0.05). The higher scores of the Vegetable-Fruit Pattern were associated with a lower risk of heart disease in older adults (p<0.05). Finally, higher scores of the Fish-Meat Pattern correlated with a lower risk of heart disease, stroke, and cardiovascular disease and a greater risk of rheumatic or rheumatoid disease in older adults (p<0.05). The same dietary pattern may have contrasting effects on different diseases. The correlations between dietary patterns and diseases derived from this study may provide a basis for the prevention and individualized management of diseases in the elderly. [ABSTRACT FROM AUTHOR]

Yichun Gu,1,&ast; Anqi Wang,2,&ast; Huan Tang,3 Haode Wang,4 Yuji Jiang,5 Chunlin Jin,1 Haiyin Wang1 1Shanghai Health Development Research Center, Shanghai, People’s Republic of China; 2School of Public Health, Weifang Medical University, Weifang, Shandong, People’s Republic of China; 3School of Public Health, Shanghai University of Traditional Chinese Medicine, Shanghai, People’s Republic of China; 4School of Health and Related Research, University of Sheffield, Sheffield, UK; 5Business School, Imperial College London, London, UK&ast;These authors contributed equally to this workCorrespondence: Chunlin Jin; Haiyin Wang, Shanghai Health Development Research Center, Shanghai, People’s Republic of China, Tel +8613162429202 ; +8618917769216, Email jinchunlin@shdrc.org; wanghaiyin@shdrc.orgBackground: In light of the limited availability of healthcare resources, providing universal access to healthcare is a challenging task. As a result, prioritizing healthcare services has emerged as a crucial issue. This study aims to explore the preferences of the public regarding healthcare prioritization for rare and common diseases. By examining public attitudes, this study seeks to inform government decisions concerning resource allocation and distribution within healthcare.Methods: “Social preference” and “rare disease” were searched as MeSH terms in the electronic databases of Ovid Medline, Web of Science, Embase, and Econlit for articles published since their establishment, and the information on the characteristics of the articles and the results of social preferences for rare diseases were analyzed and summarized.Results: The public held predominantly neutral views on the setting of healthcare priorities for rare and common diseases. The results of the included studies showed that with all else being equal, no social preference for rarity was found, but when the public considered the proportional advantage of rare diseases or when the respondents were young, a social preference for rarity existed. In addition, the public weighed attributes such as the health benefits of treatments, the effectiveness of treatment options, the safety of treatment, equity, unmet needs, and disease severity in the process of setting of treatment priorities for rare diseases. Furthermore, in consideration of equity, the public showed a willingness to pay for rare diseases in spite of the high medical costs.Conclusion: International studies on social preferences provide some evidence for the setting of healthcare priorities for rare diseases, and health policymakers should consider social preferences in an integrated manner in order to set healthcare priorities appropriately.Keywords: rare diseases, common diseases, healthcare, priority, social preference, social willingness to pay

Introduction: Sickle cell trait (SCT) is common in African descendants. Its association with several adverse pregnancy outcomes (APOs) has been reported but remains inconsistent. The objectives of this study are to test associations of SCT with APOs in non‐Hispanic Black women, including (1) validate the associations of SCT with previously reported APOs, (2) test novel associations of SCT with broad spectrum of APOs, and (3) estimate the attributable risk of SCT for implicated APOs. Material and methods: This is a retrospective analysis of a prospectively designed population‐based cohort. Women/participants were self‐reported non‐Hispanic Black women from the UK Biobank (UKB). SCT status was determined based on heterozygous Glu6Val in the HBB gene. Several APOs were studied, including four previously reported SCT‐associated APOs (preeclampsia, bacteriuria, pregnancy loss, and preterm delivery), and broad conditions related to pregnancy, childbirth, and the puerperium. APOs were curated by experts' peer review and consensus processes. Associations of SCT with APOs were tested by estimating its relative risk and 95% confidence interval (95% CI), adjusting for number of live births and age at first birth. Attributable risk proportion (ARP) and population attributable risk proportion (PARP) of SCT to APOs were estimated. Results: Among the 4057 self‐reported non‐Hispanic Black women with pregnancy records in the UKB, 581 (14.32%) were SCT carriers. For four previously reported SCT‐associated APOs, two were confirmed at a nominal P < 0.05; relative risk (RR) was 2.39 (95% CI 1.09–5.23) for preeclampsia, and 4.85 (95% CI 1.77–13.27) for bacteriuria. SCT contributed substantially to these two APOs among SCT carriers, with attributable risk proportion estimated at 61.00% and 68.96% for preeclampsia and bacteriuria, respectively. SCT also contributed substantially to these two APOs in the population (self‐reported Black UK women), with population attributable risk proportion estimated at 18.30% and 24.14% for preeclampsia and bacteriuria, respectively. In addition, novel associations were found for seven other APOs (nominal P < 0.05). Conclusions: SCT is significantly associated with APOs in this study and contributes substantially to APOs among self‐reported Black women in the UK. Confirmation of these findings in independent study populations is required. [ABSTRACT FROM AUTHOR]

Background In 2019, the National Health Commission issued the Capacity Standards for Community Health Service Center (2018 version), which proposed that the 56 common disease species should be offered diagnosis and treatment services by CHSC, but it did not specify the common disease species of children in the community, which to some extent affects the assessment and construction of CHSC capacity in the community. Objective To investigate and analyze the common childhood disease species and their characteristics in community health services, in order to provide a reference basis for further community child health service capacity building. Methods In April 2020, a convenience sampling method was adopted to select community health service agencies in 11 different level cities in China as the sample unit. A self-designed questionnaire was administered to cover the subject's basic condition, the common childhood disease conditions suitable for diagnosis and treatment in the community, and their sequencing. Filled out online voluntarily anonymously by child health service personnel at the sample institution, 3 090 cases were successfully investigated. Respondents ranked the common degree of children's related disorders from low to high, assigning 1 to 5 points to each of the top 5 common childhood disorders, which is, assigning 5 points to ranked 1, 1 point to ranked 5, and 0 points to unselected, calculating a total and sorting by total score. Results The top 5 disease categories for children in the community were acute upper respiratory infection, diarrhea, bronchitis, pneumonia, and eczema. Of the top 10 ranked community common childhood disorders, 3 were respiratory, 3 were facial and dermatologic, 2 were infectious, and 1 each was a digestive and growth and development related disorder. The top 5 common childhood diseases ranked by different regions, different levels of cities and different posts were consistent, but the ranking order was different, but there were differences in the 6th-10th disease species and order. Conclusion The current coverage of common childhood diseases in community health services is high. There is regional, urban, and post heterogeneity in common childhood disease species in communities. Construction of community child health service capacity should be oriented to improve the capacity of diagnosis and treatment service of common childhood diseases in the community, and fully consider the disease species variability in different regions, cities, and posts.

Quantifying an individual's risk for common diseases is an important goal of precision health. The polygenic risk score (PRS), which aggregates multiple risk alleles of candidate diseases, has emerged as a standard approach for identifying high-risk individuals. Although several studies have been performed to benchmark the PRS calculation tools and assess their potential to guide future clinical applications, some issues remain to be further investigated, such as lacking (i) various simulated data with different genetic effects; (ii) evaluation of machine learning models and (iii) evaluation on multiple ancestries studies. In this study, we systematically validated and compared 13 statistical methods, 5 machine learning models and 2 ensemble models using simulated data with additive and genetic interaction models, 22 common diseases with internal training sets, 4 common diseases with external summary statistics and 3 common diseases for trans -ancestry studies in UK Biobank. The statistical methods were better in simulated data from additive models and machine learning models have edges for data that include genetic interactions. Ensemble models are generally the best choice by integrating various statistical methods. LDpred2 outperformed the other standalone tools, whereas PRS-CS, lassosum and DBSLMM showed comparable performance. We also identified that disease heritability strongly affected the predictive performance of all methods. Both the number and effect sizes of risk SNPs are important; and sample size strongly influences the performance of all methods. For the trans -ancestry studies, we found that the performance of most methods became worse when training and testing sets were from different populations. [ABSTRACT FROM AUTHOR]

The present paper deals with the ethnomedicinal practices of the traditional fishing communities in the coastal areas of West Bengal. The traditional fishermen have used various medicinal plants for curing health-related problems and diseases for a long time. The ethnomedicinal system among them is quite diverse and old. In most cases, conventional knowledge has been applied in primary health care. Usually, the fishing community members have a better understanding of ethnomedicinal practices as it is available in the local areas instead of modern medical systems. The phenomenon is that they gradually left their old traditions and practices, rather accustomed to new emerging situations. In many cases, it happened due to the effects of infrastructural development, governmental influences, modernization, acculturation etc. The spread of education as well as the increasing level of consciousness also play a vital role. Here an attempt has been made to realize the conventional uses of various ethnomedicinal substances among the traditional fishing communities and successive changes come in the scenario. It is mainly a fieldwork-based study that is conducted in the traditional fishing communities' concentrated villages in the two coastal districts of West Bengal. To conduct the study, conventional anthropological field methods have been used with due importance. [ABSTRACT FROM AUTHOR]

This data article describes the dataset from a national cross-sectional questionnaire survey on Chinese internal migrants in 2017. The survey was part of the Chinese Migrants Dynamic Survey, which is an annually conducted large-scale national questionnaire survey on internal migrants. The respondents in the described dataset were migrants and registered local residents aged over 15 years old. A multistage stratified probability-proportionalto-size (PPS) sampling method based on the 2016 annual report data of China Migrant Population was adopted. The questionnaire was designed to collect demographic information of respondents and their family members, intention of migration or settlement, health status, health services accessibility, social integration, and epidemic influencing factors of common diseases, including hypertension, type 2 diabetes, diarrhea, fever, rash, icterus, conjunctival redness, cold, and other illnesses or injuries. The sample population in this survey include 13,998 internal migrants and 14,000 registered local residents from eight domestic cities / prefecture / districts across China. It is the most widely covering and highly representative dataset on common diseases and influencing factors of internal migrants in China. The dataset can be used to study common diseases and influencing factors among floating Chinese population. It provides data support for government to improve healthcare accessibility and the equity of public health services for internal migrants in China. [ABSTRACT FROM AUTHOR]

Middle East is a diverse and developing exotic animal market. Undergraduate, postgraduate, and continuing professional development (CPD) education are noticeably absent except in few countries. Avian species are the most commonly kept due to traditional falconry or aviculture. Small mammal and reptile pet numbers are increasing. Endangered wildlife is still illegally kept and trafficked. Common diseases are similar to other continents related heavily with poor diet and husbandry due to uneducated, financially restrained, and prejudiced owners. There is a significant lack of board-certified specialists, teaching facilities, or dedicated private practitioners who thirst for CPD. Clinical research is absent except falcons., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Background: Sickle cell trait is typically considered benign. Although evidence remains inconsistent, recent studies suggest that it is associated with several common diseases. We systematically assessed associations of sickle cell trait with reported diseases in a large population-based cohort.Methods: Study subjects were self-reported Blacks from the UK Biobank (UKB), a United Kingdom population-based cohort of subjects aged 40-69 years at recruitment in the United Kingdom. Sickle cell status was based on the International Classification of Diseases, Tenth Revision (ICD-10) or mutations in the HBB gene. Diagnoses of diseases were obtained from ICD-10 and self-reports. Associations of sickle cell trait and diseases were tested using logistic regression, adjusting for age at recruitment, sex, and genetic background (top 10 principal components).Results: Among the 8019 Blacks in the UKB, 699 (8.72%) were sickle cell trait carriers; the rate was significantly higher in females (9.74%) than males (7.48%), P = .0005. Sickle cell trait was under-diagnosed; most heterozygous hemoglobin subunit beta (HBB) gene Glu6Val carriers did not have a sickle cell trait ICD-10 record. Compared with non-sickle cell trait, sickle cell trait carriers had significantly increased risk for type 2 diabetes; odds ratio 1.38; 95% confidence interval, 1.12-1.68; P = .002. Sickle cell trait was also significantly associated with increased risk for renal diseases (rhabdomyolysis, end-stage renal disease, chronic kidney disease, renal papillary necrosis) and vascular diseases (hypertension, retinopathy, non-ischemic stroke), P < .05. While most of these diseases are complications/comorbidities of diabetes, their associations with sickle cell trait remained significant after adjusting for diabetes. Association with end-stage renal disease was stronger in subjects without diabetes, odds ratio 6.45; 95% confidence interval, 1.93-19.61; P = .001.Conclusions: Sickle cell trait is significantly associated with increased risk for diabetes and diabetes-related complications/comorbidities. [ABSTRACT FROM AUTHOR]

Delineation of underlying genomic and genetic factors in a specific disease may be valuable in establishing a definitive diagnosis and may guide patient management and counseling. In addition, genetic information may be useful in identification of at risk family members. Gene mapping and initial genome sequencing data enabled the development of microarrays to analyze genomic variants. The goal of this review is to consider different generations of sequencing techniques and their application to exome sequencing and whole genome sequencing and their clinical applications. In recent decades, exome sequencing has primarily been used in patient studies. Discussed in some detail, are important measures that have been developed to standardize variant calling and to assess pathogenicity of variants. Examples of cases where exome sequencing has facilitated diagnosis and led to improved medical management are presented. Whole genome sequencing and its clinical relevance are presented particularly in the context of analysis of nucleotide and structural genomic variants in large population studies and in certain patient cohorts. Applications involving analysis of cell free DNA in maternal blood for prenatal diagnosis of specific autosomal trisomies are reviewed. Applications of DNA sequencing to diagnosis and therapeutics of cancer are presented. Also discussed are important recent diagnostic applications of DNA sequencing in cancer, including analysis of tumor derived cell free DNA and exosomes that are present in body fluids. Insights gained into underlying pathogenetic mechanisms of certain complex common diseases, including schizophrenia, macular degeneration, neurodegenerative disease are presented. The relevance of different types of variants, rare, uncommon, and common to disease pathogenesis, and the continuum of causality, are addressed. Pharmogenetic variants detected by DNA sequence analysis are gaining in importance and are particularly relevant to personalized and precision medicine.

Important factors contribute to a gained momentum in candidate gene association studies (CGASs), including the generalized use of next-generation sequencing (NGS), growing opportunities for hospital-based research, and the availability of open-source databases and bioinformatics tools. This article summarizes the general principles and analytical methods as a guide to CGASs in today's favorable context. [ABSTRACT FROM AUTHOR]

Omega-3 polyunsaturated fatty acids (n-3 PUFAs), such as alpha-linolenic, eicosapentaenoic, and docosahexaenoic acids mostly exist in marine-derived foods, and have shown beneficial effects for hypertriglyceridemia, endothelial function, inflammation, and oxidative stress. Studies suggest that n-3 PUFAs can regulate the activity of NF-κB, Nrf2, SREBP-1c, and PPARa, which are linked to inflammations, ROS homeostasis, and lipid metabolism. Several epidemiological trials and physiological studies indicated protective effect of n-3 PUFAs against various common diseases such as cardiovascular diseases, diabetes mellitus, and non-alcoholic fatty liver disease. This review summarises the findings of many such studies highlighting the beneficial effects of n-3 PUFAs. [ABSTRACT FROM AUTHOR]

Abstract Background Providing adequate healthcare to newly arrived refugees is considered one of the significant challenges for the German healthcare system. These refugees can be classified mainly into two groups: asylum seekers (who have applied for asylum after arrival in Germany and are waiting for the refugee-status decision) and resettlement refugees (who have already been granted asylum status before arriving in Germany). Whereas earlier studies have explored the health status of asylum seekers especially in terms of mental and behavioural disorders and infectious diseases without distinguishing between these two groups, our study aims to evaluate possible relationships of asylum status and medical needs of these two groups with a special focus on mental and behavioural disorders and infectious diseases. Methods In this retrospective observational study, collected data on all asylum-seeker and resettlement-refugee patients (N = 2252) of a German reception centre (August 2017 to August 2018) is analysed by absolute and relative frequencies and medians. Patient data, collected by chart review, include age, gender, country of origin, asylum status, and diagnoses (ICD-10). To describe the relationship between sociodemographic factors (including asylum status) and diagnoses, we used tests of significance and bivariate correlations with Spearman correlation coefficients. All collected data are pseudonymised. Results Of all 2252 patients, 43% were resettlement refugees. In almost all ICD-10 categories, asylum seekers received significantly more diagnoses than resettlement refugees. According to our data, asylum seekers presented with mental and behavioural disorders nine times more often (9%) than resettlement refugees (1%). In the case of infectious diseases, the results are mixed: asylum seekers were twice as frequently (11%) diagnosed with certain infectious and parasitic diseases than resettlement refugees (5%), but resettlement refugees were treated twice as often (22% of the asylum seekers and 41% of the resettlement refugees) for diseases of the respiratory system, of which 84% were acute respiratory infections (in both groups). Conclusion This study indicates that patients with unregulated migration more frequently present symptoms of psychiatric diseases and somatoform symptoms than resettlement refugees. A health policy approach within migration policy should aim to enable persecuted persons to migrate under regulated and safe conditions. Trial registration German Clinical Trials Register: DRKS00013076, retrospectively registered on 29.09.2017.

Self-medication is the use of medicine by the patients for self-recognized symptoms without consulting with licensed clinicians. This practice is potentially associated with antibiotic resistance, morbidity and mortality due to toxic side-effects. To identify the prevalence of self-medication among the students of University of Dhaka, a questionnaire-based survey was conducted from August 08, 2017 to December 14, 2017 and analyzed statistically. A total of 805 students of different disciplines of both sex (Male; 638, 79.3%, Female; 167, 20.7%) were participated. According to the survey, common diseases were more prevalent among male students (79.3%) than in female (20.7%). Moreover, prevalence of common diseases among the students is significant (p<0.05) on the basis of sex but insignificant (p>0.05) in age group. On the other hand, higher degree holders (15.53%) practiced less self-medication than the bachelor degree holders (34.41%). The drug groups which were most commonly self-medicated were analgesics (39.5%), antibiotics (36.9%), and antihistamines (24.0%). Moreover, association between sex and side effects after self-medication were significant with p-value <0.05 where association between age group of the students and side effects after self-medication were not significant with p-value >0.05. Besides, results revealed that the principal reason behind self-medication is not to have enough time to consult with a doctor (47.82%) while others pointed out about the inability to manage appointment with physicians (16.4%). As the study showed that self-medication practice among the students of University of Dhaka is very alarming, so awareness should be raised among the students to overcome the scenario. [ABSTRACT FROM AUTHOR]

The "Mendelian code" hypothesis postulates a relationship between Mendelian (monogenic) and common pathologies. In this hypothesis, polymorphisms in the genes of Mendelian diseases may have a significant contribution to predisposition to common diseases in which the same biochemical pathways may be involved. In this review a group of genes encoding various proteins participating in the DNA repair, with a particular focus on the BRCA1-associated genome surveillance complex (BASC), is presented through the prism of the "Mendelian code" hypothesis. Here we discuss (1) their main functions in the repair of DNA double-strand breaks (ATM, MRE11, NBN, RAD50, BRCA1, and BLM) and mismatch repair (MSH2, MSH6, MLH1, PMS2, RF-C, and PCNA); (2) the mitochondrial involvement of these proteins; (3) the involvement of BASC proteins in the development of an adaptive immune response. For 13 out of 16 BASC protein encoding genes, mutations leading to monogenic diseases have already been described; for 11, there are associations with common diseases or individual biological processes. Patients with mutations in the genes of the BASC complex and patients with severe combined immunodeficiency share similar symptoms. Polymorphisms within DNA repair genes may play a role in the development of common diseases through the involvement of the immune response. The pleiotropic effects of these genes suggest their participation in the development of various conditions, both in health and pathology. [ABSTRACT FROM AUTHOR]

Copy number variations (CNVs) are major causative contributors both in the genesis of genetic diseases and human neoplasias. While “High-Throughput” sequencing technologies are increasingly becoming the primary choice for genomic screening analysis, their ability to efficiently detect CNVs is still heterogeneous and remains to be developed. The aim of this white paper is to provide a guiding framework for the future contributions of ELIXIR’s recently established h uman CNV Community, with implications beyond human disease diagnostics and population genomics. This white paper is the direct result of a strategy meeting that took place in September 2018 in Hinxton (UK) and involved representatives of 11 ELIXIR Nodes. The meeting led to the definition of priority objectives and tasks, to address a wide range of CNV-related challenges ranging from detection and interpretation to sharing and training. Here, we provide suggestions on how to align these tasks within the ELIXIR Platforms strategy, and on how to frame the activities of this new ELIXIR Community in the international context.

Copyright of Management Issues / Problemy Zarządzania is the property of Problemy Zarzadzania and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The burden of several common diseases including obesity, diabetes, hypertension, asthma, and depression is increasing in most world populations. However, the mechanisms underlying the numerous epidemiological and genetic correlations among these disorders remain largely unknown. We investigated whether common polymorphic inversions underlie the shared genetic influence of these disorders. We performed an inversion association analysis including 21 inversions and 25 obesity-related traits on a total of 408,898 Europeans and validated the results in 67,299 independent individuals. Seven inversions were associated with multiple diseases while inversions at 8p23.1, 16p11.2, and 11q13.2 were strongly associated with the co-occurrence of obesity with other common diseases. Transcriptome analysis across numerous tissues revealed strong candidate genes for obesity-related traits. Analyses in human pancreatic islets indicated the potential mechanism of inversions in the susceptibility of diabetes by disrupting the cis -regulatory effect of SNPs from their target genes. Our data underscore the role of inversions as major genetic contributors to the joint susceptibility to common complex diseases. [ABSTRACT FROM AUTHOR]

Abstract Background Large-scale genetic studies of common human diseases have focused almost exclusively on the independent main effects of single-nucleotide polymorphisms (SNPs) on disease susceptibility. These studies have had some success, but much of the genetic architecture of common disease remains unexplained. Attention is now turning to detecting SNPs that impact disease susceptibility in the context of other genetic factors and environmental exposures. These context-dependent genetic effects can manifest themselves as non-additive interactions, which are more challenging to model using parametric statistical approaches. The dimensionality that results from a multitude of genotype combinations, which results from considering many SNPs simultaneously, renders these approaches underpowered. We previously developed the multifactor dimensionality reduction (MDR) approach as a nonparametric and genetic model-free machine learning alternative. Approaches such as MDR can improve the power to detect gene-gene interactions but are limited in their ability to exhaustively consider SNP combinations in genome-wide association studies (GWAS), due to the combinatorial explosion of the search space. We introduce here a stochastic search algorithm called Crush for the application of MDR to modeling high-order gene-gene interactions in genome-wide data. The Crush-MDR approach uses expert knowledge to guide probabilistic searches within a framework that capitalizes on the use of biological knowledge to filter gene sets prior to analysis. Here we evaluated the ability of Crush-MDR to detect hierarchical sets of interacting SNPs using a biology-based simulation strategy that assumes non-additive interactions within genes and additivity in genetic effects between sets of genes within a biochemical pathway. Results We show that Crush-MDR is able to identify genetic effects at the gene or pathway level significantly better than a baseline random search with the same number of model evaluations. We then applied the same methodology to a GWAS for Alzheimer’s disease and showed base level validation that Crush-MDR was able to identify a set of interacting genes with biological ties to Alzheimer’s disease. Conclusions We discuss the role of stochastic search and cloud computing for detecting complex genetic effects in genome-wide data.

The exposome collectively refers to all exposures, beginning in utero and continuing throughout life, and comprises not only standard environmental exposures such as point source pollution and ozone levels but also exposures from diet, medication, lifestyle factors, stress, and occupation. The exposome interacts with individual genetic and epigenetic characteristics to affect human health and disease, but large-scale studies that characterize the exposome and its relationships with human disease are limited. To address this gap, we used extensive questionnaire data from the diverse North Carolina-based Personalized Environment and Genes Study (PEGS, n = 9, 429) to evaluate exposure associations in relation to common diseases. We performed an exposome-wide association study (ExWAS) to examine single exposure models and their associations with 11 common complex diseases, namely allergic rhinitis, asthma, bone loss, fibroids, high cholesterol, hypertension, iron-deficient anemia, ovarian cysts, lower GI polyps, migraines, and type 2 diabetes. Across diseases, we found associations with lifestyle factors and socioeconomic status as well as asbestos, various dust types, biohazardous material, and textile-related exposures. We also found disease-specific associations such as fishing with lead weights and migraines. To differentiate between a replicated result and a novel finding, we used an AI-based literature search and database tool that allowed us to examine the current literature. We found both replicated findings, especially for lifestyle factors such as sleep and smoking across diseases, and novel findings, especially for occupational exposures and multiple diseases., Competing Interests: None declared., (Published by Oxford University Press 2024.)

Diseases associated with mitochondrial DNA (mtDNA) mutations are highly variable in phenotype, in large part because of differences in the percentage of normal and mutant mtDNAs (heteroplasmy) present within the cell. For example, increasing heteroplasmy levels of the mtDNA tRNALeu(UUR) nucleotide (nt) 3243A > G mutation result successively in diabetes, neuromuscular degenerative disease, and perinatal lethality. These phenotypes are associated with differences in mitochondrial function and nuclear DNA (nDNA) gene expression, which are recapitulated in cybrid cell lines with different percentages of m.3243G mutant mtDNAs. Using metabolic tracing, histone mass spectrometry, and NADH fluorescence lifetime imaging microscopy in these cells, we now show that increasing levels of this single mtDNA mutation cause profound changes in the nuclear epigenome. At high heteroplasmy, mitochondrially derived acetyl-CoA levels decrease causing decreased histone H4 acetylation, with glutamine-derived acetyl-CoA compensating when glucose-derived acetyl-CoA is limiting. In contrast, α-ketoglutarate levels increase at midlevel heteroplasmy and are inversely correlated with histone H3 methylation. Inhibition of mitochondrial protein synthesis induces acetylation and methylation changes, and restoration of mitochondrial function reverses these effects. mtDNA heteroplasmy also affects mitochondrial NAD+/NADH ratio, which correlates with nuclear histone acetylation, whereas nuclear NAD+/NADH ratio correlates with changes in nDNA and mtDNA transcription. Thus, mutations in the mtDNA cause distinct metabolic and epigenomic changes at different heteroplasmy levels, potentially explaining transcriptional and phenotypic variability of mitochondrial disease. [ABSTRACT FROM AUTHOR]

Autozygosity is associated with rare Mendelian disorders and clinically relevant quantitative traits. We investigated associations between the fraction of the genome in runs of homozygosity (F ROH) and common diseases in Genes & Health (n = 23,978 British South Asians), UK Biobank (n = 397,184), and 23andMe. We show that restricting analysis to offspring of first cousins is an effective way of reducing confounding due to social/environmental correlates of F ROH. Within this group in G&H+UK Biobank, we found experiment-wide significant associations between F ROH and twelve common diseases. We replicated associations with type 2 diabetes (T2D) and post-traumatic stress disorder via within-sibling analysis in 23andMe (median n = 480,282). We estimated that autozygosity due to consanguinity accounts for 5%–18% of T2D cases among British Pakistanis. Our work highlights the possibility of widespread non-additive genetic effects on common diseases and has important implications for global populations with high rates of consanguinity. [Display omitted] • Robust method to reduce confounding in autozygosity-phenotype association studies • Higher autozygosity associated with increased risk for common diseases such as T2D • Replication of findings including a within-sibling analysis • Consanguinity explains ∼10% of T2D cases in British Pakistanis Autozygosity resulting from consanguinity is causally associated with several complex diseases, including type 2 diabetes. [ABSTRACT FROM AUTHOR]

Delineation of underlying genomic and genetic factors in a specific disease may be valuable in establishing a definitive diagnosis and may guide patient management and counseling. In addition, genetic information may be useful in identification of at risk family members. Gene mapping and initial genome sequencing data enabled the development of microarrays to analyze genomic variants. The goal of this review is to consider different generations of sequencing techniques and their application to exome sequencing and whole genome sequencing and their clinical applications. In recent decades, exome sequencing has primarily been used in patient studies. Discussed in some detail, are important measures that have been developed to standardize variant calling and to assess pathogenicity of variants. Examples of cases where exome sequencing has facilitated diagnosis and led to improved medical management are presented. Whole genome sequencing and its clinical relevance are presented particularly in the context of analysis of nucleotide and structural genomic variants in large population studies and in certain patient cohorts. Applications involving analysis of cell free DNA in maternal blood for prenatal diagnosis of specific autosomal trisomies are reviewed. Applications of DNA sequencing to diagnosis and therapeutics of cancer are presented. Also discussed are important recent diagnostic applications of DNA sequencing in cancer, including analysis of tumor derived cell free DNA and exosomes that are present in body fluids. Insights gained into underlying pathogenetic mechanisms of certain complex common diseases, including schizophrenia, macular degeneration, neurodegenerative disease are presented. The relevance of different types of variants, rare, uncommon, and common to disease pathogenesis, and the continuum of causality, are addressed. Pharmogenetic variants detected by DNA sequence analysis are gaining in importance and are particularly relevant to personalized and precision medicine.

Background: Large-scale genetic studies of common human diseases have focused almost exclusively on the independent main effects of single-nucleotide polymorphisms (SNPs) on disease susceptibility. These studies have had some success, but much of the genetic architecture of common disease remains unexplained. Attention is now turning to detecting SNPs that impact disease susceptibility in the context of other genetic factors and environmental exposures. These context-dependent genetic effects can manifest themselves as non-additive interactions, which are more challenging to model using parametric statistical approaches. The dimensionality that results from a multitude of genotype combinations, which results from considering many SNPs simultaneously, renders these approaches underpowered. We previously developed the multifactor dimensionality reduction (MDR) approach as a nonparametric and genetic model-free machine learning alternative. Approaches such as MDR can improve the power to detect gene-gene interactions but are limited in their ability to exhaustively consider SNP combinations in genome-wide association studies (GWAS), due to the combinatorial explosion of the search space. We introduce here a stochastic search algorithm called Crush for the application of MDR to modeling high-order gene-gene interactions in genomewide data. The Crush-MDR approach uses expert knowledge to guide probabilistic searches within a framework that capitalizes on the use of biological knowledge to filter gene sets prior to analysis. Here we evaluated the ability of Crush-MDR to detect hierarchical sets of interacting SNPs using a biology-based simulation strategy that assumes non-additive interactions within genes and additivity in genetic effects between sets of genes within a biochemical pathway. Results: We show that Crush-MDR is able to identify genetic effects at the gene or pathway level significantly better than a baseline random search with the same number of model evaluations. We then applied the same methodology to a GWAS for Alzheimer's disease and showed base level validation that Crush-MDR was able to identify a set of interacting genes with biological ties to Alzheimer's disease. Conclusions: We discuss the role of stochastic search and cloud computing for detecting complex genetic effects in genome-wide data. [ABSTRACT FROM AUTHOR]

Objectives: The purpose of this study was to explaine the association between the prevalence of common diseases and demographic, occupotional factors in elderly staff in IRIB (Tehran center) Regarding the increasing of elderly populationin the world, indluding IRAN, the prevalence of the physical disability in this age range is raised which leads to several unfavarable out comes such as: hospitalization, overuse of health care system and mortality rate. For achiving elderly health and preventing of chronic diseases and decreasing prevalence of elderly common diseases, the firsrt step is indentification of their health status. By which, we can recognise their health and medical needs and also prevent their occurrence. Considring relationship between demographic occupational factors and common disease in elderly staff in radio and television centers , unfortunately, I could not find any article. Methods & Materials: This study is a cross-sectional one wich was conducted on 152 enderly patient who were reffered to IRIB Clinic and studied for association between demographic and occupational factors with prevalenc of common diseases. In this reaserch a questionnaire contaning demographic information and history of diseases was used. They were complated with elderly paintent. then the phesition examined them. Data were analyzed with analysis of T-test chi-2 and pearson correlation in spss16. Results: The analysis of our data showed that osteoarthrities (46%), hypertension (36%), heart diseases (35.5%) and diabet (21%) were the most common diseases in elderly patient that were reffered to IRIB clinic during the year 1389. In this study a significant relactionship was observed between osteoarthrities, hypertension, heart disease and age (P=0.000), BMI (P=0.000), Incom level (P=0.000), education (P=0.000) and physical activity (P=0.01) while, ther was no singificany relationship between heart diseases and diabet whit gender (P=0.17), reffering times to the general practitioner and life satisfaction. (P=0.07) Conclusion: osteoarthrities, heart diseases, Hypertention and diabet are the most common diseases in the elderly staffs in IRIB. According to this study, there is a significant relation between prevalence of common diseases and health related variable. therfore through implementation of such programs like: changing life style, regular and periodic clinical examination ,changing diet habit, we can identification of these diseases in the primary stage and preventation of disability in the future will be possible.

Evolutionary medicine is a new discipline with novel approaches to diseases. It focuses on the ultimate causes of diseases rather than the proximal causes that have been the focus of traditional medicine. Whereas traditional medicine seeks answers to "what" and "how" questions on structure and mechanisms of diseases, evolutionary medicine seeks answers to "How" and "Why" questions on the origion and function. Evolutionary medicine applies the methods of evolutionary analysis such as molecular evolution, population genetics, and phylogenetics to study the origin and reasons of diseases. Evolutionary medicine aims to bring novel approaches to health problems that traditional medicine can not understand the mechanisms of and can not find cures for, in order to improve the overall health of human populations. [ABSTRACT FROM AUTHOR]

Susceptibility to common human diseases is influenced by both genetic and environmental factors. The explosive growth of genetic data, and the knowledge that it is generating, are transforming our biological understanding of these diseases. In this review, we describe the technological and analytical advances that have enabled genome-wide association studies to be successful in identifying a large number of genetic variants robustly associated with common disease. We examine the biological insights that these genetic associations are beginning to produce, from functional mechanisms involving individual genes to biological pathways linking associated genes, and the identification of functional annotations, some of which are cell-type-specific, enriched in disease associations. Although most efforts have focused on identifying and interpreting genetic variants that are irrefutably associated with disease, it is increasingly clear that-even at large sample sizes-these represent only the tip of the iceberg of genetic signal, motivating polygenic analyses that consider the effects of genetic variants throughout the genome, including modest effects that are not individually statistically significant. As data from an increasingly large number of diseases and traits are analysed, pleiotropic effects (defined as genetic loci affecting multiple phenotypes) can help integrate our biological understanding. Looking forward, the next generation of population-scale data resources, linking genomic information with health outcomes, will lead to another step-change in our ability to understand, and treat, common diseases. [ABSTRACT FROM AUTHOR]

Introduction. Investigating educational situations of interns in different departments is one of the objectives of educational planning in order to prevent a low quality education and provide some solution for that. This study was done to investigate the learning situation of male and female interns in Obstetrics and Gynecology Department at Zahedan University of Medical Sciences in order to compare the amount of their learning, and to provide some suggestions to improve the quality of learning and education. Methods. All inters (30 males and 40 females) in Zahedan Medical University have participated in this descriptive study during 2002. The data collection tool was a questionnaire which included questions regarding common emergencies and diseases of obstetrics and gynecology, and different learning criteria. The data analysis was done by SPSS software using mean, standard deviation, frequency of learning criteria and Chi-square. Results. The mean of frequency of learning indicators such as observation, discussion on bedside, managing under the supervision of residents and attending physicians, and personal management, in common emergencies and diseases of obstetrics and gynecology in male interns were lower than female interns. Furthermore, the mean of frequency of managing capabilities in common emergencies for male and female interns were 12% and 70.5%, respectively. These values for common diseases were 14.2% and 59.3%, in male and female interns, respectively. The Chi-square test showed a significant relationship between the learning criteria, and proper managing capabilities. Conclusion. Considering the low frequency of learning indicators such as observation, discussion on bedside, managing under supervision of attending physicians and residents, and personal managemen,t in male interns, and a need to their service in deprived areas, it is necessary to improve the learning quality in obstetrics and gynecology department, especially for male interns.