Technology engagement is associated with higher perceived physical well-being in stroke patients prescribed smartwatches for atrial fibrillation detection

BackgroundIncreasing ownership of smartphones among Americans provides an opportunity to use these technologies to manage medical conditions. We examine the influence of baseline smartwatch ownership on changes in self-reported anxiety, patient engagement, and health-related quality of life when prescribed smartwatch for AF detection.MethodWe performed a post-hoc secondary analysis of the Pulsewatch study (NCT03761394), a clinical trial in which 120 participants were randomized to receive a smartwatch-smartphone app dyad and ECG patch monitor compared to an ECG patch monitor alone to establish the accuracy of the smartwatch-smartphone app dyad for detection of AF. At baseline, 14 days, and 44 days, participants completed the Generalized Anxiety Disorder-7 survey, the Health Survey SF-12, and the Consumer Health Activation Index. Mixed-effects linear regression models using repeated measures with anxiety, patient activation, physical and mental health status as outcomes were used to examine their association with smartwatch ownership at baseline.ResultsNinety-six participants, primarily White with high income and tertiary education, were randomized to receive a study smartwatch-smartphone dyad. Twenty-four (25%) participants previously owned a smartwatch. Compared to those who did not previously own a smartwatch, smartwatch owners reported significant greater increase in their self-reported physical health (β = 5.07, P < 0.05), no differences in anxiety (β = 0.92, P = 0.33), mental health (β = −2.42, P = 0.16), or patient activation (β = 1.86, P = 0.54).ConclusionsParticipants who own a smartwatch at baseline reported a greater positive change in self-reported physical health, but not in anxiety, patient activation, or self-reported mental health over the study period

A Highly Hydrophilic and Biodegradable Novel Poly(amide-imide) for Biomedical Applications

A novel biodegradable poly(amide-imide) (PAI) with good hydrophilicity was synthesized by incorporation of l-glycine into the polymer chain. For comparison purposes, a pure PAI containing no l-glycine was also synthesized with a three-step method. In this study, we evaluated the novel PAI’s thermal stability, hydrophilicity, solubility, biodegradability and ability to support bone marrow mesenchymal stem cell (BMSC) adhesion and growth by comparing with the pure PAI. The hydrophilic tests demonstrated that the novel PAI has possible hydrophilicity at a 38° water contact angle on the molecule surface and is about two times more hydrophilic than the pure PAI. Due to an extra unit of l-glycine in the novel PAI, the average degradation rate was about 2.4 times greater than that of the pure PAI. The preliminary biocompatibility studies revealed that all the PAIs are cell compatible, but the pure PAI exhibited much lower cell adhesion than the l-glycine-incorporated novel PAI. The hydrophilic surface of the novel PAI was more suitable for cell adhesion, suggesting that the surface hydrophilicity plays an important role in enhancing cell adhesion and growth

The Protective Effect of Different Polar Solvent Extracts of Er Miao San on Rats with Adjuvant Arthritis

Objective. The aim of this study was to evaluate the antiarthritic effects of different polar solvent extracts of Er Miao San (EMS) on model rats with adjuvant arthritis (AA) and screen the effective pats of EMS in the treatment of arthritis. Methods. Four different polar solvent extracts of EMS such as petroleum ether (PE), methylene chloride (CH2Cl2), ethyl acetate (EtOAc), and n-butanol (n-BuOH) were extracted and separated by different solvent polar extraction. Different polar parts of the aqueous extract of EMS were orally administered for 14 days to AA rats. Progression of clinical signs such as edema of paws and polyarthritis index was measured. The ankle joint changes were observed by pathological sections. ELISA was used to measure cytokines in the serum according to the manufacturer’s instructions. UHPLC measured the effective parts of EMS. Results. Administration of EtOAc and CH2Cl2 parts remarkably inhibited the paw swelling, decreased the index of arthritis, decreased the body weight loss, and improved the changes of histopathology. Furthermore, the concentrations of proinflammatory cytokines (TNF-α, IL-1β, and IL-6) were significantly lower, while the anti-inflammatory cytokine (IL-10) was remarkably higher compared with that in the model group. And the result of UHPLC analysis indicated that the effective parts of EMS contain berberine and atractylodin. Conclusions. EtOAc and CH2Cl2 are the effective parts of EMS that can improve arthritis. In particular, berberine and atractylodin may be responsible for the antiarthritic activity of EMS. This research provided pharmacological and chemical foundation for the application of EMS in treating rheumatoid arthritis (RA)

Machine learning predicting mortality in sarcoidosis patients admitted for acute heart failure

Background: Sarcoidosis with cardiac involvement, although rare, has a worse prognosis than sarcoidosis involving other organ systems. Objective: We used a large dataset to train machine learning models to predict in-hospital mortality among sarcoidosis patients admitted with heart failure (HF). Method: Utilizing the National Inpatient Sample, we identified 4659 patients hospitalized with a primary diagnosis of HF. In this cohort, we identified patients with a secondary diagnosis of sarcoidosis using International Statistical Classification of Disease, Tenth Revision (ICD-10) codes. Patients were separated into a training group and a testing group in a 7:3 ratio. Least absolute shrinkage and selection operator regression was used to select variables to prevent model overfitting or underfitting. For machine learning models, logistic regression, random forest, and XGBoosting were applied in the training group. Parameters in each of the models were tuned using the GridSearchCV function. After training, all models were further validated in the testing group. Models were then evaluated using the area under curve (AUC) score, sensitivity, and specificity. Results: A total of 2.3% of sarcoidosis patients died in HF admission. Our machine learning model analysis found the RF model to have the highest AUC score and sensitivity. Feature analysis found that comorbid arrhythmias and fluid electrolyte disorders were the strongest factors in predicting in-hospital mortality. Conclusion: Machine learning methods can be useful in identifying predictors of in-hospital mortality in a given dataset

Serum-Derived Extracellular Vesicles Protect Against Acute Myocardial Infarction by Regulating miR-21/PDCD4 Signaling Pathway

Acute myocardial infarction (AMI) represents a leading cause of morbidity and mortality worldwide. Extracellular vesicles (EVs) are being recognized as a promising therapeutic approach in protecting against MI. Serum is a rich source of EVs, which transports various microRNAs (miRNAs, miRs). EVs from serum have been shown beneficial for protecting against ischemia-reperfusion injury; however, their roles in AMI are unclear. In addition, whether a miRNA might be responsible for the effects of serum EVs on protecting against AMI is undetermined. Here, we demonstrated that serum EVs significantly reduced cardiomyocytes apoptosis in both cellular and mouse models of AMI, and dramatically attenuated the infarct size in mouse hearts after AMI. Inhibition of miR-21 was shown to reduce the protective effects of serum EVs in inhibiting cardiomyocytes apoptosis. miR-21 was decreased in mouse hearts after AMI, while serum EVs increased that. In addition, the programmed cell death 4 (PDCD4) expression was identified as a target gene of miR-21. Therefore, our study showed the protective effects of serum EVs on AMI, and provided a novel strategy for AMI therapy

Expression Regulation of Starch and Storage Protein Synthesis Related Genes in Rice Grains

Starch and the storage proteins are the main nutritious substances in crop grains, and their composition and content in grains play a decisive role in the grain quality of rice and other staple food crops. This review has mainly summarized the new advances in the expression regulation of starch and storage protein synthesis related genes in rice grains. Moreover, the challenges of the starch and storage protein synthesis substances in rice genetic improvement were also discussed. This review will provide important information for genetic improvement of grain quality in rice and, potentially, other staple cereals