Neuroinflammation is a key pathologic hallmark of numerous neurologic diseases, however, its exact role in vivo is yet to be fully understood. PET imaging enables investigation, quantification, and tracking of different neuroinflammation biomarkers in living subjects longitudinally. One such biomarker that has been imaged extensively using PET is translocator protein 18 kDa (TSPO). Although imaging TSPO has yielded valuable clinical data linking neuroinflammation to various neurodegenerative diseases, considerable limitations of TSPO PET have prompted identification of other more cell-specific and functionally relevant biomarkers. This review analyzes the clinical potential of available and emerging PET biomarkers of innate and adaptive immune responses, with mention of exciting future directions for the field.

Background Social media provides a potential avenue for genetic counselors to address gaps in access to reliable genetics information for rare disease communities. However, only limited research has examined patient and family attitudes toward engaging with genetic counselors through social media. Objective Our study assessed the attitudes of members of rare disease social media groups toward engaging with genetic counselors through social media, characteristics associated with greater interest, and the benefits and potential pitfalls of various approaches to such engagement. Methods We conducted a mixed methods survey of patients and family members recruited from a systematic sample of rare disease Facebook groups. Patient characteristics and their associations with interest in engagement with genetic counselors were evaluated using univariate and bivariate statistics. Responses to open-ended questions were analyzed using thematic content analysis. Results In total, 1053 individuals from 103 rare disease groups participated. The median overall interest in engaging with genetic counselors on social media was moderately high at 7.0 (IQR 4.0-9.0, range 0-10). No past experience with a genetic counselor was associated with greater interest in engaging with one through social media (µ=6.5 vs 6.0, P=.04). Participants expressed greatest interest (median 9.0, IQR 5.0-10.0) in engagement models allowing direct communication with genetic counselors, which was corroborated by the majority (n=399, 61.3%) of individuals who responded to open-ended questions explicitly stating their interest in 1-on-1 interactions. When asked what forms of support they would request from genetic counselors through social media, participants desired individualized support and information about how to access services. However, participants also expressed concerns regarding privacy and confidentiality. Conclusions Patients and family members in rare disease social media groups appear interested in engaging with genetic counselors through social media, particularly for individualized support. This form of engagement on social media is not meant to replace the current structure and content of genetic counseling (GC) services, but genetic counselors could more actively use social media as a communication tool to address gaps in knowledge and awareness about genetics services and gaps in accessible patient information. Although encouraging, concerns regarding privacy and feasibility require further consideration, pointing to the need for professional guidelines in this area.

ImportanceThe expansion of genetic and genomic testing in health care has led to recognition that these tests provide personal as well as clinical utility to patients and families. However, available systematic reviews on this topic have not reported the demographic backgrounds of participants in studies of personal utility, leaving generalizability unclear.ObjectiveTo determine the demographic characteristics of participants in studies examining the personal utility of genetic and genomic testing in health care.Evidence ReviewFor this systematic review, we utilized and updated the results of a highly cited 2017 systematic review on the personal utility of genetics and genomics, which identified relevant articles published between January 1, 2003, and August 4, 2016. We also used the original methods to update this bibliography with literature published subsequently up to January 1, 2022. Studies were screened for eligibility by 2 independent reviewers. Eligible studies reported empirical data on the perspectives of patients, family members, and/or the general public in the US on the personal utility of any type of health-related genetic or genomic test. We utilized a standardized codebook to extract study and participant characteristics. We summarized demographic characteristics descriptively across all studies and by subgroup based on study and participant characteristics.FindingsWe included 52 studies with 13 251 eligible participants. Sex or gender was the most frequently reported demographic characteristic (48 studies [92.3%]), followed by race and ethnicity (40 studies [76.9%]), education (38 studies [73.1%]), and income (26 studies [50.0%]). Across studies, participants disproportionately were women or female (mean [SD], 70.8% [20.5%]), were White (mean [SD], 76.1% [22.0%]), had a college degree or higher (mean [SD], 64.5% [19.9%]), and reported income above the US median (mean [SD], 67.4% [19.2%]). Examination of subgroups of results by study and participant characteristics evidenced only small shifts in demographic characteristics.Conclusions and RelevanceThis systematic review examined the demographic characteristics of individual participants in studies of the personal utility of health-related genetic and genomic testing in the US. The results suggest that participants in these studies were disproportionately White, college-educated women with above-average income. Understanding the perspectives of more diverse individuals regarding the personal utility of genetic and genomic testing may inform barriers to research recruitment and uptake of clinical testing in currently underrepresented populations.

E-adoption of emerging technology plays an important role during the pandemic. The COVID-19 pandemic taught us that everyone must make himself healthy and immune to viral disease. Diabetes is the most common disease in the Indian population found in people of every age. The objective of this research work is to use the emerging technologies such as machine learning to implement e-adoption in the healthcare system. The proposed methodology can predict the diabetes disease by using vital parameters like age, glucose level, blood pressure, etc. This proposed model is implemented into Python programming language and various machine learning classifiers such as random forest, decision tree, logistic regression, and XGBoost are used on PIMA database. Thereafter, comparative analysis is performed to test which technique is better for predicting and diagnosing diabetes disease. The method founds XGBoost classifier gives the highest accuracy (i.e., 84%) among all classifiers with single database and single classifier.

Importance: Expansion in the clinical use of genetic and genomic testing has led to a recognition that these tests provide personal as well as clinical utility to patients and families. It is essential to ensure that members of diverse sociodemographic backgrounds are included in defining and measuring personal utility. Objective: To determine the demographics of participants contributing to the development of a definition of personal utility for genetic and genomic testing. Evidence Review: We searched PubMed, Scopus, Web of Science, and Embase for peer-reviewed literature published between 2003 and January 2022 on the personal utility of genetic or genomic sequencing. Our review included both qualitative and quantitative studies with samples that included patients, their family members, or the general public. Eligible studies could examine any clinical genetic or genomic test and required the use of the term "utility." Authors extracted and reviewed study and participant characteristics including number of participants, study location (U.S. or international), primary methodology (qualitative or quantitative), race and ethnicity, gender, income and education data. Findings: Our final review included 53 studies and 13,315 total participants. Gender was provided for 95.6% of participants (n=12,724), of whom 61.5% were female (n=7,823). Race and/or ethnicity was provided for 83.0% of participants (n=11,048), of whom 82.2% (n=9,083) were White. The remaining participants were identified as Hispanic/Latinx (5.5%, n=607), Asian American and Pacific Islander (3.8%, n=421), Black (3.5%, n=387), multiracial (0.2%, n=27), and various other racial or ethnic categories (3.7%, n=412). Educational attainment was reported for 82.6% of participants. Among these participants, 71.2% (n=7,830) had a bachelor's degree or higher. Income was reported for 66.5% of participants (n=8,857), and 66% of these participants (n=5,831) reported income above the U.S. median. Conclusions and Relevance: Our results suggest that the concept of personal utility in genetic and genomic testing in the U.S. is disproportionately defined by the perspectives a narrow subset of the population - specifically non-Hispanic White, well-educated women with above-average household incomes. If we are to provide equitable care in the areas of genomics and genetics, we will need to expand research to include more diverse and representative samples.