Racial Discrimination and Trajectories of Problematic Alcohol Use Among African American Emerging Adults: The Role of Organizational Religious Involvement

Racial discrimination jeopardizes a wide range of health behaviors for African Americans. Numerous studies demonstrate significant negative associations between racial discrimination and problematic alcohol use among African Americans. Culturally specific contexts (e.g., organized religious involvement) often function protectively against racial discrimination’s adverse effects for many African Americans. Yet organized religious involvement may affect the degree to which racial discrimination increases problematic alcohol use resulting in various alcohol use trajectories. These links remain understudied in emerging adulthood marked by when individuals transition from adolescence to early adult roles and responsibilities. We use data from 496 African American emerging adults from the Flint Adolescent Study (FAS) to (a) identify multiple and distinct alcohol use trajectories and (b) examine organizational religious involvement’s protective role. Three trajectory classes were identified: the high/stable, (20.76% of sample; n = 103); moderate/stable, (39.52% of sample; n = 196); and low/rising, (39.72% of the sample; n = 197). After controlling for sex, educational attainment, and general stress, the interaction between racial discrimination and organized religious involvement did not influence the likelihood of classifying into the moderate/stable class or the low/rising class, compared with the high/stable class. These results suggest organized religious involvement counteracts, but does not buffer racial discrimination’s effects on problematic alcohol use. Findings emphasize the critical need for culturally sensitive prevention efforts incorporating organized religious involvement for African American emerging adults exposed to racial discrimination. These prevention efforts may lessen the role of racial discrimination on health disparities related to alcohol use.

Trajectory Analysis of Orthostatic Hypotension in Parkinson’s Disease: Results From Parkinson’s Progression Markers Initiative Cohort

Background: Orthostatic hypotension (OH) in Parkinson’s disease (PD) can lead to falls, impair quality of life, and increase mortality. A trajectory analysis of OH could be useful to predict and prevent the hypotension incidence early.Methods: The longitudinal data of 660 patients with PD with disease duration up to 12 years were extracted from an integrated PD database. We used latent class mixed modeling (LCMM) to identify patient subgroups, demonstrating trajectories of changes in orthostatic blood pressure (BP) over time. The optimal number of subgroups was selected by several criteria including the Bayesian Information Criterion. Baseline information comparison between groups and backward stepwise logistic regression were conducted to define the distinguishing characteristics of these subgroups and to investigate the predictors for BP trajectory.Results: We identified three trajectories for each orthostatic change of systolic blood pressure (ΔSBP), namely, Class 1 (i.e., the increasing class) consisted of 18 participants with low ΔSBP that increased continuously during the follow-up; Class 2 (i.e., the low-stable class) consisted of 610 participants with low ΔSBP that remained low throughout the follow-up; and Class 3 (i.e., the high-stable class) consisted of 32 participants with high ΔSBP at baseline that was relatively stable throughout the follow-up. Several parameters differed among subgroups, but only male sex [odds ratio (OR) = 4.687, 95% confidence interval (CI) = 1.024–21.459], lower supine diastolic blood pressure (DBP) (OR = 0.934, 95% CI = 0.876–0.996), and lower level of total protein at baseline (OR = 0.812, 95% CI = 0.700–0.941) were significant predictors of an increasing ΔSBP trajectory.Conclusion: This study provides new information on the longitudinal development of ΔSBP in patients with PD with distinct trajectories of rapidly increasing, low-stable, and high-stable class. The parameters such as male sex, lower supine DBP, and lower total proteins help to identify the rapidly increasing class.

Trajectories of mid-life to elderly adulthood BMI and incident hypertension: the China Health and Nutrition Survey

ObjectivesThis study is designed to identify different body mass index (BMI) trajectories of individuals aged 40–70 years and test the effect of distinct BMI trajectories on incident hypertension.DesignThe accelerated longitudinal design was used for this study.MethodsThe study drew data from the third to ninth China Health and Nutrition Surveys (CHNS), and 4697 participants were included between 1991 and 2015. As analysed, three distinct individual BMI trajectories were identified by the latent class growth mixed model (LCGMM). Then, BMI values and BMI slopes were worked out through calculation with LCGMM trajectory parameters and their primary derivatives, respectively. Later, Cox proportional hazard models were applied to examine BMI values and slopes, and find out the relationship between the said predicted data and incident hypertension for different classes.ResultsThree different trajectory classes were identified, that is, low-stable class (n=3711), sharp-increasing class (n=282) and high-stable class (n=704). Compared with the low-stable class, the adjusted HRs (95% CI) were 1.321 (1.119 to 1.559) and 1.504 (1.322 to 1.711) for the sharp-increasing class and the high-stable class, respectively. The HR (95% CI) for BMI values rose from 1.081 (1.030 to 1.135) to 1.221 (1.171 to 1.273) while the HR (95% CI) for BMI slopes dropped from 1.154 (1.100 to 1.211) to 0.983 (0.943 to 1.025). That is, the HR for BMI slopes were higher than that for BMI values for the class aged 40–47 years.ConclusionThese findings suggest that the calibrated BMI trajectories for the period from mid-life to elderly adulthood have a significant effect on the risk of incident hypertension. The period from age 40 to 47 years is critical and has positive implications for the early prevention of hypertension.

Al-Maʿarrī’s Anxious Menagerie: The Epistle of the Horse and the Mule

Around the year 411/1021, blind author and controversial freethinker Abū l-ʿAlāʾ al-Maʿarrī (449/1057) wrote Risālat al-ṣāhil wa-l-shāḥij (The Epistle of the Horse and the Mule), a meandering prose work populated by animal characters who talk about Syrian society on the eve of the crusades. The story exudes a brand of fictionality, namely creative literary exaggeration designed to call forth mental pictures, that sets it apart from other animal texts due to the overwhelming ambiguity it creates. The animal characters suffer existential anxiety when, for instance, they realize that concepts like genus (jins) and species (nawʿ) turn out to be fuzzier than they thought, thereby calling into question whether any species—be it biological or linguistic—is a stable class. Animal ontology gets further confused by just-so stories about hybrids and crossbreeds, and by terms for philosophical contingency that question whether talking animals even exist—this is not just a story that did not happen, but a story that cannot happen except in the imagination. On the other hand, those same philosophical terms may yet affirm that speaking animals could exist, and that they have value in themselves, by hinting at their place in a cosmic order that radiates the goodness of its Source.

Random and Synthetic Over-Sampling Approach to Resolve Data Imbalance in Classification

High accuracy value is one of the parameters of the success of classification in predicting classes. The higher the value, the more correct the class prediction. One way to improve accuracy is dataset has a balanced class composition. It is complicated to ensure the dataset has a stable class, especially in rare cases. This study used a blood donor dataset; the classification process predicts donors are feasible and not feasible; in this case, the reward ratio is quite high. This work aims to increase the number of minority class data randomly and synthetically so that the amount of data in both classes is balanced. The application of SOS and ROS succeeded in increasing the accuracy of inappropriate class recognition from 12% to 100% in the KNN algorithm. In contrast, the naïve Bayes algorithm did not experience an increase before and after the balancing process, which was 89%.

Dynamic stability of complex networks

Will a large complex system be stable? This question, first posed by May in 1972, captures a long standing challenge, fueled by a seeming contradiction between theory and practice. While empirical reality answers with an astounding yes, the mathematical analysis, based on linear stability theory, seems to suggest the contrary - hence, the diversity-stability paradox. Here we settle this dichotomy, by considering the interplay between topology and dynamics. We show that this interplay leads to the emergence of non-random patterns in the system's stability matrix, leading us to relinquish the prevailing random matrix-based paradigm. Instead, we offer a new matrix ensemble, which captures the dynamic stability of real-world systems. This ensemble helps us analytically identify the relevant control parameters that predict a system's stability, exposing three broad dynamic classes: In the asymptotically unstable class, diversity, indeed, leads to instability a la May's paradox. However, we also expose an asymptotically stable class, the class in which most real systems reside, in which diversity not only does not prohibit, but, in fact, enhances dynamic stability. Finally, in the sensitively stable class diversity plays no role, and hence stability is driven by the system's microscopic parameters. Together, our theory uncovers the naturally emerging rules of complex system stability, helping us reconcile the paradox that has eluded us for decades.

Predicting differentiated developmental trajectories of prosocial behavior: A 12-year longitudinal study of children facing early risks and vulnerabilities

The current study examined the heterogeneity in the development of school-based prosocial behavior from Grades 1 to 12 and the role of multiple early childhood antecedents in predicting heterogeneous developmental trajectories of prosocial behavior in a sample of 784 children facing early risks and vulnerabilities (predominantly from low-income families and academically at risk; 52.6% male). In alignment with the risk and resilience framework, antecedents consisted of risk and protective factors from both individual (i.e., ego-resilient personality, behavior problems, intelligence, academic performance, gender, and ethnicity) and contextual domains (i.e., maternal support and responsiveness, family socioeconomic adversity, teacher–child warmth and conflict, and peer acceptance and rejection). We identified four distinct prosocial trajectories including a high-stable (52.5%), high-desisting (15%), moderate-increasing (20.6%), and low-stable class (11.9%). Results revealed that the low-stable, high-desisting, and moderate-increasing classes were associated with lower ego resiliency, higher behavior problems, lower teacher–child warmth, higher teacher–child conflict, and peer rejection in early childhood, compared to the high-stable group. Boys and African Americans were more likely to be in the low-stable, high-desisting, and moderate-increasing classes. Individual characteristics such as ego-resilient personality and contextual influences such as teacher–child warmth served as common protective antecedents. Interestingly, teacher–child conflict served as a unique predictor for the high-desisting class, and behavior problems and peer rejection served as unique predictors for the low-stable class.

Keratins and Plakin family cytolinker proteins control the length of epithelial microridge protrusions

ABSTRACTActin filaments and microtubules create diverse cellular protrusions, but intermediate filaments, the strongest and most stable class of cytoskeletal elements, are not known to directly participate in the formation of protrusions. Here we show that Keratin intermediate filaments directly regulate the morphogenesis of microridges, elongated protrusions from mucosal epithelial cells arranged in elaborate fingerprint-like patterns. Developing microridges on zebrafish skin cells contained both Actin and Keratin filaments. Keratin filaments maintained microridges upon F-actin disruption, and overexpressing Keratins lengthened microridges. Envoplakin and Periplakin, Plakin family cytolinkers that bind to F-actin and Keratins, localized to microridges and were required for their morphogenesis. Strikingly, Plakin protein levels directly determined microridge length. An actin-binding domain of Periplakin was required to initiate microridge morphogenesis, whereas Periplakin-Keratin binding was required to stabilize and elongate microridges. Our results thus separate microridge morphogenesis into two steps with differential requirements for cytoskeletal elements, expand our understanding of intermediate filament functions, and identify microridges as cellular protrusions that integrate actin and intermediate filaments.