Explore the vast range of titles available.

Objective. To quantify the presence of health behavior theory constructs in iPhone apps targeting physical activity. Methods. This study used a content analysis of 127 apps from Apple's (App Store) Health & Fitness category. Coders downloaded the apps and then used an established theory-based instrument to rate each app's inclusion of theoretical constructs from prominent behavior change theories. Five common items were used to measure 20 theoretical constructs, for a total of 100 items. A theory score was calculated for each app. Multiple regression analysis was used to identify factors associated with higher theory scores. Results. Apps were generally observed to be lacking in theoretical content. Theory scores ranged from I to 28 on a 100-point scale. The health belief model was the most prevalent theory, accounting for 32% of all constructs. Regression analyses indicated that higher priced apps and apps that addressed a broader activity spectrum were associated with higher total theory scores. Conclusion. It is not unexpected that apps contained only minimal theoretical content, given that app developers come from a variety of backgrounds and many are not trained in the application of health behavior theory. The relationship between price and theory score corroborates research indicating that higher quality apps are more expensive. There is an opportunity for health and behavior change experts to partner with app developers to incorporate behavior change theories into the development of apps. These future collaborations between health behavior change experts and app developers could foster apps superior in both theory and programming possibly resulting in better health outcomes.

Background Immunology research, particularly next generation sequencing (NGS) of the immune T-cell receptor β (TCRβ) repertoire, has advanced progression in several fields, including treatment of various cancers and autoimmune diseases. This study aimed to identify the TCR repertoires from dry blood spots (DBS), a method that will help collecting real-world data for biomarker applications. Methods Finger-prick blood was collected onto a Whatman filter card. RNA was extracted from DBS of the filter card, and fully automated multiplex PCR was performed to generate a TCRβ chain library for next generation sequencing (NGS) analysis of unique CDR3s (uCDR3). Results We demonstrated that the dominant clonotypes from the DBS results recapitulated those found in whole blood. According to the statistical analysis and laboratory confirmation, 40 of 2-mm punch disks from the filter cards were enough to detect the shared top clones and have strong correlation in the uCDR3 discovery with whole blood. uCDR3 discovery was neither affected by storage temperatures (room temperature versus − 20 °C) nor storage durations (1, 14, and 28 days) when compared to whole blood. About 74–90% of top 50 uCDR3 clones of whole blood could also be detected from DBS. A low rate of clonotype sharing, 0.03–1.5%, was found among different individuals. Conclusions The DBS-based TCR repertoire profiling method is minimally invasive, provides convenient sampling, and incorporates fully automated library preparation. The system is sensitive to low RNA input, and the results are highly correlated with whole blood uCDR3 discovery allowing study scale-up to better understand the relationship and mutual influences between the immune and diseases.

Social work has historically operated as an extension of the carceral state, embedding policing, surveillance, and punishment into youth-serving institutions under the guise of care. This paper examines carceral seepage—the infiltration of punitive logics into social work practice—across child welfare, education, and juvenile legal, revealing how these systems function as interconnected circuits of criminalization rather than support. Using abolitionist frameworks, we critique social work’s complicity in punitive interventions and address common concerns about safety, scalability, and sustainability. Instead of reforming oppressive institutions, we argue for a fundamental transformation of social work, advocating for non-carceral models such as community-led crisis response, restorative justice, and mutual aid. By divesting from punishment and investing in collective care, abolitionist social work can move beyond harm reduction and toward genuine liberation.

This study measured the likelihood of adult patients with diabetes being referred to diabetes self-management education (DSME) when \"in need\" according to clinical guidelines and identified which types of clinical need predict a greater likelihood of provider referral to DSME. This repeated cross-sectional analysis utilized patient electronic health records (EHRs) and a statewide health information exchange database to examine a 7-year panel (2010-2016) of adult patients with diabetes. Our analytic sample included 8782 adult patients with diabetes with a total of 356,631 encounters. Fixed-effects linear probability models with clustered robust standard errors estimated the association between patients' need for DSME and likelihood of being referred to the service. Models controlled for patients' health status, prior utilization, encounter setting, comorbidity risk scores, the state's expansion of Medicaid, and the count of accredited DSME program sites in the community. Most patient encounters indicated at least 1 type of need for DSME, but less than 7% of those encounters with a documented need resulted in a provider referral. In regression analysis, clinical indicators of need increased the likelihood that patients would be referred to DSME. Patients exhibiting multiple types of need were most likely to be referred to DSME. Although findings indicate that patient need for DSME does improve the likelihood of being referred, provider referral rates were significantly lower than anticipated. Future research should explore barriers to clinical guideline adherence and whether clinical decision support in EHR systems can facilitate provider referrals.

Migraine is a common neurological disorder characterized by repeated headaches of varying intensity. The prevalence and severity of migraine headaches disproportionally affects women, particularly during the postpartum period. Moreover, migraines during pregnancy have been associated with adverse maternal outcomes, including preeclampsia and postpartum stroke. However, due to the lack of a validated instrument for uniform case ascertainment on postpartum migraine headache, there is uncertainty in the reported prevalence in the literature. The aim of this study was to evaluate the completeness and accuracy of reporting postpartum migraine headache coding in a large integrated health care system's electronic health records (EHRs) and to compare the coding quality before and after the implementation of the International Classification of Diseases, 10th revision, Clinical Modification (ICD-10-CM) codes and pharmacy records in EHRs. Medical records of 200 deliveries in all 15 Kaiser Permanente Southern California hospitals during 2 time periods, that is, January 1, 2012 through December 31, 2014 (International Classification of Diseases, 9th revision, Clinical Modification [ICD-9-CM] coding period) and January 1, 2017 through December 31, 2019 (ICD-10-CM coding period), were randomly selected from EHRs for chart review. Two trained research associates reviewed the EHRs for all 200 women for postpartum migraine headache cases documented within 1 year after delivery. Women were considered to have postpartum migraine headache if either a mention of migraine headache (yes for diagnosis) or a prescription for treatment of migraine headache (yes for pharmacy records) was noted in the electronic chart. Results from the chart abstraction served as the gold standard and were compared with corresponding diagnosis and pharmacy prescription utilization records for both ICD-9-CM and ICD-10-CM coding periods through comparisons of sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), as well as the summary statistics of F-score and Youden J statistic (J). The kappa statistic (κ) for interrater reliability was calculated. The overall agreement between the identification of migraine headache using diagnosis codes and pharmacy records compared to the medical record review was strong. Diagnosis coding (F-score=87.8%; J=82.5%) did better than pharmacy records (F-score=72.7%; J=57.5%) when identifying cases, but combining both of these sources of data produced much greater accuracy in the identification of postpartum migraine cases (F-score=96.9%; J=99.7%) with sensitivity, specificity, PPV, and NPV of 100%, 99.7%, 93.9%, and 100%, respectively. Results were similar across the ICD-9-CM (F-score=98.7%, J=99.9%) and ICD-10-CM coding periods (F-score=94.9%; J=99.6%). The interrater reliability between the 2 research associates for postpartum migraine headache was 100%. Neither diagnostic codes nor pharmacy records alone are sufficient for identifying postpartum migraine cases reliably, but when used together, they are quite reliable. The completeness of the data remained similar after the implementation of the ICD-10-CM coding in the EHR system.

The metabolic activity of uncultivated microorganisms contributes to numerous ecosystem processes, ranging from nutrient cycling in the environment to influencing human health and disease. Advances in sequencing technology have enabled the assembly of genomes for these microorganisms, but our ability to generate reference genomes far outstrips our ability to analyze them. Common approaches to analyzing microbial metabolism require reconstructing the entirety of an organism’s metabolic pathways or performing targeted searches for genes involved in a specific process. This paper presents a third approach, in which draft metabolic reconstructions are used to identify compounds through which an organism may interact with its environment. These compounds can then guide more-intensive metabolic reconstruction efforts and can also provide new hypotheses about the specific contributions that microbes make to ecosystem-scale metabolic processes. An explosion in the number of available genome sequences obtained through metagenomics and single-cell genomics has enabled a new view of the diversity of microbial life, yet we know surprisingly little about how microbes interact with each other or their environment. In fact, the majority of microbial species remain uncultivated, while our perception of their ecological niches is based on reconstruction of their metabolic potential. In this work, we demonstrate how the “seed set framework,” which computes the set of compounds that an organism must acquire from its environment (E. Borenstein, M. Kupiec, M. W. Feldman, and E. Ruppin, Proc Natl Acad Sci U S A 105:14482–14487, 2008, https://doi.org/10.1073/pnas.0806162105 ), enables computational analysis of metabolic reconstructions while providing new insights into a microbe’s metabolic capabilities, such as nutrient use and auxotrophies. We apply this framework to members of the ubiquitous freshwater actinobacterial lineage acI, confirming and extending previous experimental and genomic observations implying that acI bacteria are heterotrophs reliant on peptides and saccharides. We also present the first metatranscriptomic study of the acI lineage, revealing high expression of transport proteins and the light-harvesting protein actinorhodopsin. Putative transport proteins complement predictions of nutrients and essential metabolites while providing additional support of the hypothesis that members of the acI are photoheterotrophs. IMPORTANCE The metabolic activity of uncultivated microorganisms contributes to numerous ecosystem processes, ranging from nutrient cycling in the environment to influencing human health and disease. Advances in sequencing technology have enabled the assembly of genomes for these microorganisms, but our ability to generate reference genomes far outstrips our ability to analyze them. Common approaches to analyzing microbial metabolism require reconstructing the entirety of an organism’s metabolic pathways or performing targeted searches for genes involved in a specific process. This paper presents a third approach, in which draft metabolic reconstructions are used to identify compounds through which an organism may interact with its environment. These compounds can then guide more-intensive metabolic reconstruction efforts and can also provide new hypotheses about the specific contributions that microbes make to ecosystem-scale metabolic processes.

Cardiovascular disease (CVD) is a leading cause of mortality among U.S. adults, especially low-income and uninsured adults. Non-Hispanic Black adults, who are overrepresented among low-income and uninsured populations, are disproportionately burdened by CVD mortality compared with non-Hispanic White adults. Medicaid expansion is associated with improved insurance coverage and access to care among low-income adults as well as reduced CVD mortality. It is unclear whether Medicaid expansion has reduced the Black-White disparity in CVD mortality. This study estimated a difference-in-differences model to compare changes in county-level CVD mortality ratios between expansion and non-expansion states. Findings indicate that Medicaid expansion is not associated with a statistically significant reduction in Black-White disparities in CVD mortality (β = -.039; p =.30). In conclusion, Medicaid expansion may be associated with improved health outcomes and access to care overall; however, it is insufficient to overcome other (i.e., social and economic) drivers of racial/ethnic disparities in CVD mortality.

Background Cardiac hypertrophy is central to the etiology of heart failure. Understanding the molecular pathways promoting cardiac hypertrophy may identify new targets for therapeutic intervention. Sodium-proton exchanger (NHE1) activity and expression levels in the heart are elevated in many models of hypertrophy through protein kinase C (PKC)/MAPK/ERK/p90 RSK pathway stimulation. Sustained NHE1 activity, however, requires an acid-loading pathway. Evidence suggests that the Cl − /HCO 3 − exchanger, AE3, provides this acid load. Here we explored the role of AE3 in the hypertrophic growth cascade of cardiomyocytes. Methods AE3-deficient ( ae3 −/− ) mice were compared to wildtype (WT) littermates to examine the role of AE3 protein in the development of cardiomyocyte hypertrophy. Mouse hearts were assessed by echocardiography. As well, responses of cultured cardiomyocytes to hypertrophic stimuli were measured. pH regulation capacity of ae3 −/− and WT cardiomyocytes was assessed in cultured cells loaded with the pH-sensitive dye, BCECF-AM. Results ae3 −/− mice were indistinguishable from wild type (WT) mice in terms of cardiovascular performance. Stimulation of ae3 −/− cardiomyocytes with hypertrophic agonists did not increase cardiac growth or reactivate the fetal gene program. ae3 −/− mice are thus protected from pro-hypertrophic stimulation. Steady state intracellular pH (pH i ) in ae3 −/− cardiomyocytes was not significantly different from WT, but the rate of recovery of pH i from imposed alkalosis was significantly slower in ae3 −/− cardiomyocytes. Conclusions These data reveal the importance of AE3-mediated Cl − /HCO 3 − exchange in cardiovascular pH regulation and the development of cardiomyocyte hypertrophy. Pharmacological antagonism of AE3 is an attractive approach in the treatment of cardiac hypertrophy.

Objectives. To examine postgraduation employment trends among graduates of doctoral programs in public health from 2003 to 2015. Methods. We analyzed pooled cross-sectional data from a census of graduates receiving a research doctorate from US accredited institutions. The outcome of interest was employment status. Covariates included public health discipline, sociodemographic characteristics, and institutional attributes. Results. Of 11 771 graduates, nearly two thirds secured employment in either academic (34.8%) or nonacademic (31.4%) settings at the time of graduation. The proportion of those still seeking employment increased over time. Individuals who were White, younger, trained in either biostatistics or epidemiology, or from an institution with the highest level of research intensity were significantly more likely to secure employment. Academic employment was the most common setting for all 5 public health disciplines, but we observed differences in employment patterns (e.g., government, nonprofit, for-profit) across disciplines. Conclusions. Certain characteristics among public health doctoral recipients are correlated with postgraduation employment. More research is needed, but the observed increase in individuals still seeking employment may be attributable to increases in general public health graduates from for-profit institutions.

Objectives: Given public health’s emphasis on health disparities in underrepresented racial/ethnic minority communities, having a racially and ethnically diverse faculty is important to ensure adequate public health training. We examined trends in the number of underrepresented racial/ethnic minority (ie, non-Hispanic black, Hispanic, American Indian/Alaska Native, Native Hawaiian, and Pacific Islander) doctoral graduates from public health fields and determined the proportion of persons from underrepresented racial/ethnic minority groups who entered academia. Methods: We analyzed repeated cross-sectional data from restricted files collected by the National Science Foundation on doctoral graduates from US institutions during 2003-2015. Our dependent variables were the number of all underrepresented racial/ethnic minority public health doctoral recipients and underrepresented racial/ethnic minority graduates who had accepted academic positions. Using logistic regression models and adjusted odds ratios (aORs), we examined correlates of these variables over time, controlling for all independent variables (eg, gender, age, relationship status, number of dependents). Results: The percentage of underrepresented racial/ethnic minority doctoral graduates increased from 15.4% (91 of 592) in 2003 to 23.4% (296 of 1264) in 2015, with the largest increase occurring among black graduates (from 6.6% in 2003 to 14.1% in 2015). Black graduates (310 of 1241, 25.0%) were significantly less likely than white graduates (2258 of 5913, 38.2%) and, frequently, less likely than graduates from other underrepresented racial/ethnic minority groups to indicate having accepted an academic position (all P < .001). Conclusions: Stakeholders should consider targeted programs to increase the number of racial/ethnic minority faculty members in academic public health fields.