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The abuse of stimulants, such as methamphetamine (METH), is associated with treatment non-compliance, a greater risk of viral transmission, and the more rapid clinical progression of immunological and central nervous system human immunodeficiency virus (HIV) disease. The behavioral effects of METH in the setting of HIV remain largely uncharacterized. We used a state-of-the-art paradigm of the escalation of voluntary intravenous drug self-administration in HIV transgenic (Tg) and wildtype rats. The rats were first allowed to self-administer METH under short-access (ShA) conditions, which is characterized by a nondependent and more "recreational" pattern of METH use, and then allowed to self-administer METH under long-access (LgA) conditions, which leads to compulsive (dependent) METH intake. HIV Tg and wildtype rats self-administered equal amounts of METH under ShA conditions. HIV Tg rats self-administered METH under LgA conditions following a 4-week enforced abstinence period to model the intermittent pattern of stimulant abuse in humans. These HIV Tg rats developed greater motivation to self-administer METH and self-administered larger amounts of METH. Impairments in function of the medial prefrontal cortex (mPFC) contribute to compulsive drug and alcohol intake. Gene expression profiling of the mPFC in HIV Tg rats with a history of escalated METH self-administration under LgA conditions showed transcriptional evidence of increased inflammation, greater neural injury, and impaired aerobic glucose metabolism than wildtype rats that self-administered METH under LgA conditions. The detrimental effects of the interaction between neuroHIV and escalated METH intake on the mPFC are likely key factors in the greater vulnerability to excessive drug intake in the setting of HIV.

The article focuses on the 2007 preface to "The Pattern of the Chinese Past" book, its reflective discussion of the book's methodology and key research questions, and its ongoing relevance in understanding China's historical trajectory.

To investigate changes in cardiometabolic risk factors after completion of cardiac rehabilitation (CR) for coronary heart disease (CHD) and ascertain whether the magnitude of improvement in cardiometabolic health differs between those with and without metabolic syndrome (MetS). Methods: In this observational cohort study, data were analyzed from 1984 patients enrolled in CR at the University of Michigan between 2011-01-01 and 2020-02-29 for the indication of CHD. Patient characteristics were collected from standardized health questionnaires and during CR intake evaluations. Cardiometabolic biomarkers were recorded from baseline laboratory data and re-examined upon completion of CR. Differences in baseline patient characteristics by MetS status were compared using chi-square tests. Wilcoxon rank-sum tests were used to compare baseline differences, and signed-rank tests were used to evaluate the change in variables between baseline and completion of CR. The difference of change by MetS status was assessed using difference-in-differences regression models. Results: Of the 1984 patients, 1070 (53.9%) met the criteria for MetS at baseline, of which 770 were male (72.0%). Those with MetS lost 1.43 pounds more (95% CI: 0.56, 2.31, P = 0.001), experienced a 0.21 larger drop in body mass index (95% CI: 0.03, 0.37, P = 0.02), and had a 0.31 greater reduction in waist circumference (95% CI: 0.08, 0.54, P = 0.008). Difference-in-differences regression models revealed those with MetS experienced a greater reduction in triglycerides and fasting glucose, with a difference of change of − 8.70 for triglycerides (95% CI: − 15.04, − 2.37, P = 0.007) and − 5.48 for glucose (95% CI: − 10.44, − 0.53, P = 0.03). There was no significant difference in the change in HDL-C or LDL-C for MetS status. Conclusion: Compared to those without MetS, patients with MetS experienced a comparable or greater benefit from CR, particularly with respect to improvements in MetS components. [ABSTRACT FROM AUTHOR]

Abstract Background Intensive Care Resources are heavily utilized during the COVID-19 pandemic. However, risk stratification and prediction of SARS-CoV-2 patient clinical outcomes upon ICU admission remain inadequate. This study aimed to develop a machine learning model, based on retrospective & prospective clinical data, to stratify patient risk and predict ICU survival and outcomes. Methods A Germany-wide electronic registry was established to pseudonymously collect admission, therapeutic and discharge information of SARS-CoV-2 ICU patients retrospectively and prospectively. Machine learning approaches were evaluated for the accuracy and interpretability of predictions. The Explainable Boosting Machine approach was selected as the most suitable method. Individual, non-linear shape functions for predictive parameters and parameter interactions are reported. Results 1039 patients were included in the Explainable Boosting Machine model, 596 patients retrospectively collected, and 443 patients prospectively collected. The model for prediction of general ICU outcome was shown to be more reliable to predict “survival”. Age, inflammatory and thrombotic activity, and severity of ARDS at ICU admission were shown to be predictive of ICU survival. Patients’ age, pulmonary dysfunction and transfer from an external institution were predictors for ECMO therapy. The interaction of patient age with D-dimer levels on admission and creatinine levels with SOFA score without GCS were predictors for renal replacement therapy. Conclusions Using Explainable Boosting Machine analysis, we confirmed and weighed previously reported and identified novel predictors for outcome in critically ill COVID-19 patients. Using this strategy, predictive modeling of COVID-19 ICU patient outcomes can be performed overcoming the limitations of linear regression models. Trial registration “ClinicalTrials” (clinicaltrials.gov) under NCT04455451.

Although highly active antiretroviral therapy (HAART) has changed infection with human immunodeficiency virus (HIV) from a diagnosis with imminent mortality to a chronic illness, HIV positive patients who do not develop acquired immunodeficiency syndrome (AIDs) still suffer from a high rate of cardiac dysfunction and fibrosis. Regardless of viral load and CD count, HIVassociated cardiomyopathy (HIVAC) still causes a high rate of mortality and morbidity amongst HIV patients. While this is a well characterized clinical phenomena, the molecular mechanism of HIVAC is not well understood. In this review, we consolidate, analyze, and discuss current research on the intersection between autophagy and HIVAC. Multiple studies have linked dysregulation in various regulators and functional components of autophagy to HIV infection regardless of mode of viral entry, i.e., coronary, cardiac chamber, or pericardial space. HIV proteins, including negative regulatory factor (Nef), glycoprotein 120 (gp120), and transactivator (Tat), have been shown to interact with type II microtubule-associated protein-1 β light chain (LC3-II), Rubiquitin, SQSTM1/p62, Rab7, autophagy-specific gene 7 (ATG7), and lysosomal-associated membrane protein 1 (LAMP1), all molecules critical to normal autophagy. HIV infection can also induce dysregulation of mitochondrial bioenergetics by altering production and equilibrium of adenosine triphosphate (ATP), mitochondrial reactive oxygen species (ROS), and calcium. These changes alter mitochondrial mass and morphology, which normally trigger autophagy to clear away dysfunctional organelles. However, with HIV infection also triggering autophagy dysfunction, these abnormal mitochondria accumulate and contribute to myocardial dysfunction. Likewise, use of HAART, azidothymidine and Abacavir, have been shown to induce cardiac dysfunction and fibrosis by inducing abnormal autophagy during antiretroviral therapy. Conversely, studies have shown that increasing autophagy can reduce the accumulation of dysfunctional mitochondria and restore cardiomyocyte function. Interestingly, Rapamycin, a mammalian target of rapamycin (mTOR) inhibitor, has also been shown to reduce HIV-induced cytotoxicity by regulating autophagy-related proteins, making it a non-antiviral agent with the potential to treat HIVAC. In this review, we synthesize these findings to provide a better understanding of the role autophagy plays in HIVAC and discuss the potential pharmacologic targets unveiled by this research. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic is expected to have serious negative consequences on mental and physical health, which may disproportionally affect young adults. The aim of this study was to understand short-term impacts on a population of students at a college that held in-person classes during the pandemic. This study was conducted at a moderately-sized private university in the southeastern United States where approximately 75% of students were enrolled in undergraduate degree programs and 25% in graduate degree programs. A survey was created to assess anxiety and depression symptoms, psychotherapeutic medication use, healthy living, and coping skills. Links to the electronic form were distributed to students via email in Spring 2020 and Fall 2020. Participation was completely voluntary and responses were collected anonymously. The rate of anxiety symptoms in the study cohort was higher than the national average (31%) and increased between Spring 2020 (39%) and Fall 2020 (50%). Rates of psychotherapeutic medication use also rose, with benzodiazepine use increasing from 6% to 11% and antidepressant use increasing from 16% to 20%. Compared to the national average, fewer students in the study cohort rated their overall health as "good" or better (72-76% vs. 82%). Physical exercise, nutrition, and alcohol use worsened between Spring and Fall 2020. Problem-focused engagement was associated with significantly fewer anxiety and depression symptoms. Demographic factors such as gender, race, and sexual orientation interacted with several outcomes studied. Students at a private university that held in-person classes during the COVID-19 pandemic reported high rates of anxiety that increased between Spring and Fall 2020. Self-reported physical health was below average in Spring 2020 but improved in Fall 2020. Appropriate identification and management of the effects of pandemic-related stressors is critical during this uncertain time. Supplemental data for this article can be accessed online at https://doi.org/10.1080/07448481.2022.2052074. [ABSTRACT FROM AUTHOR]