GNNGL-PPI: multi-category prediction of protein-protein interactions using graph neural networks based on global graphs and local subgraphs.

Most proteins exert their functions by interacting with other proteins, making the identification of protein-protein interactions (PPI) crucial for understanding biological activities, pathological mechanisms, and clinical therapies. Developing effective and reliable computational methods for predicting PPI can significantly reduce the time-consuming and labor-intensive associated traditional biological experiments. However, accurately identifying the specific categories of protein-protein interactions and improving the prediction accuracy of the computational methods remain dual challenges. To tackle these challenges, we proposed a novel graph neural network method called GNNGL-PPI for multi-category prediction of PPI based on global graphs and local subgraphs. GNNGL-PPI consisted of two main components: using Graph Isomorphism Network (GIN) to extract global graph features from PPI network graph, and employing GIN As Kernel (GIN-AK) to extract local subgraph features from the subgraphs of protein vertices. Additionally, considering the imbalanced distribution of samples in each category within the benchmark datasets, we introduced an Asymmetric Loss (ASL) function to further enhance the predictive performance of the method. Through evaluations on six benchmark test sets formed by three different dataset partitioning algorithms (Random, BFS, DFS), GNNGL-PPI outperformed the state-of-the-art multi-category prediction methods of PPI, as measured by the comprehensive performance evaluation metric F1-measure. Furthermore, interpretability analysis confirmed the effectiveness of GNNGL-PPI as a reliable multi-category prediction method for predicting protein-protein interactions.

Peer Ambassador Perspectives in a Culturally Tailored Self-Management Intervention for African Americans with Type 2 Diabetes: A Qualitative Study.

OBJECTIVE: Diabetes disproportionately affects African Americans, leading to higher morbidity and mortality. This study explores the experiences of African American adults who successfully self-manage their type 2 diabetes (called Peer Ambassadors) and provided phone-based peer support in a 6-month culturally tailored diabetes self-management program for African Americans guided by the information-motivation-behavioral skills model. DESIGN: A group discussion using a semi-structured discussion guide was conducted. Qualitative content analysis was used to identify the facilitators and barriers to completing the role of a Peer Ambassador and to develop strategies for overcoming possible challenges in the future. SETTING: Key informant discussions were conducted in a community location to gain insights into Ambassadors' motivations and challenges in delivering peer support. PARTICIPANTS: Three Peer Ambassadors completed ethics training and peer mentor training and received a phone call guide before providing support to their peers. RESULTS: There were four core themes related to Peer Ambassador experiences: (1) Motivation to be a Peer Ambassador, (2) program elements that supported Peer Ambassador role, (3) key elements of achieving engagement, and (4) challenges related to being a Peer Ambassador. CONCLUSIONS: This study showed Peer Ambassadors in a culturally tailored peer supported self-management program found fulfillment in sharing experiences and supporting peers. They highly valued educational group sessions for knowledge updates and sustaining their health-related goals, suggesting the potential benefits of recognizing milestones or providing advanced training for future program sustainability. Findings suggest the importance of recruiting motivated patients and providing effective facilitation for peer support roles, including addressing barriers such as time commitment and lack of socialization opportunities.

Advancements and Practical Considerations for Biophysical Research: Navigating the Challenges and Future of Super-resolution Microscopy.

The introduction of super-resolution microscopy (SRM) has significantly advanced our understanding of cellular and molecular dynamics, offering a detailed view previously beyond our reach. Implementing SRM in biophysical research, however, presents numerous challenges. This review addresses the crucial aspects of utilizing SRM effectively, from selecting appropriate fluorophores and preparing samples to analyzing complex data sets. We explore recent technological advancements and methodological improvements that enhance the capabilities of SRM. Emphasizing the integration of SRM with other analytical methods, we aim to overcome inherent limitations and expand the scope of biological insights achievable. By providing a comprehensive guide for choosing the most suitable SRM methods based on specific research objectives, we aim to empower researchers to explore complex biological processes with enhanced precision and clarity, thereby advancing the frontiers of biophysical research.

Numerical Optimization Study of Combustion and Heat Transfer Characteristics in Municipal Solid Waste Incinerators.

The efficient and clean utilization of urban waste can substitute for partial fossil fuels and reduce total carbon emissions. Fuel combustion is divided into three stages. Before the fire, the fuel is put into the furnace to reach the preparation stage of the fire temperature, the combustion stage takes place after the ignition temperature is reached, and finally, the combustion is completed. This article employs numerical simulation methods to comprehensively study the effects of various factors on the combustion characteristics of waste in a mechanical grate incinerator, including the inclination angle of the front arch, fuel properties, height of the front and rear arches, air distribution methods, and speed of the grate chain rotation. The results indicate that when the rear arch angle is set at 25°, the airflow distribution within the furnace is uniform and the high-temperature flue gas exhibits an ideal "L" shaped flow, achieving favorable characteristics of airflow distribution inside the furnace. With this structure, the airflow from the rear arch can adequately penetrate deep into the front arch area, thereby forming an efficient T-shaped combustion flame.

Drug-Online: an online platform for drug-target interaction, affinity, and binding sites identification using deep learning.

BACKGROUND: Accurately identifying drug-target interaction (DTI), affinity (DTA), and binding sites (DTS) is crucial for drug screening, repositioning, and design, as well as for understanding the functions of target. Although there are a few online platforms based on deep learning for drug-target interaction, affinity, and binding sites identification, there is currently no integrated online platforms for all three aspects. RESULTS: Our solution, the novel integrated online platform Drug-Online, has been developed to facilitate drug screening, target identification, and understanding the functions of target in a progressive manner of "interaction-affinity-binding sites". Drug-Online platform consists of three parts: the first part uses the drug-target interaction identification method MGraphDTA, based on graph neural networks (GNN) and convolutional neural networks (CNN), to identify whether there is a drug-target interaction. If an interaction is identified, the second part employs the drug-target affinity identification method MMDTA, also based on GNN and CNN, to calculate the strength of drug-target interaction, i.e., affinity. Finally, the third part identifies drug-target binding sites, i.e., pockets. The method pt-lm-gnn used in this part is also based on GNN. CONCLUSIONS: Drug-Online is a reliable online platform that integrates drug-target interaction, affinity, and binding sites identification. It is freely available via the Internet at http://39.106.7.26:8000/Drug-Online/ .

A comprehensive review of the recent advances on predicting drug-target affinity based on deep learning.

Accurate calculation of drug-target affinity (DTA) is crucial for various applications in the pharmaceutical industry, including drug screening, design, and repurposing. However, traditional machine learning methods for calculating DTA often lack accuracy, posing a significant challenge in accurately predicting DTA. Fortunately, deep learning has emerged as a promising approach in computational biology, leading to the development of various deep learning-based methods for DTA prediction. To support researchers in developing novel and highly precision methods, we have provided a comprehensive review of recent advances in predicting DTA using deep learning. We firstly conducted a statistical analysis of commonly used public datasets, providing essential information and introducing the used fields of these datasets. We further explored the common representations of sequences and structures of drugs and targets. These analyses served as the foundation for constructing DTA prediction methods based on deep learning. Next, we focused on explaining how deep learning models, such as Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Transformer, and Graph Neural Networks (GNNs), were effectively employed in specific DTA prediction methods. We highlighted the unique advantages and applications of these models in the context of DTA prediction. Finally, we conducted a performance analysis of multiple state-of-the-art methods for predicting DTA based on deep learning. The comprehensive review aimed to help researchers understand the shortcomings and advantages of existing methods, and further develop high-precision DTA prediction tool to promote the development of drug discovery.

NAD+ precursors promote the restoration of spermatogenesis in busulfan-treated mice through inhibiting Sirt2-regulated ferroptosis.

Rationale: In recent years, nicotinamide adenine dinucleotide (NAD+) precursors (Npre) have been widely employed to ameliorate female reproductive problems in both humans and animal models. However, whether and how Npre plays a role in the male reproductive disorder has not been fully clarified. Methods: In the present study, a busulfan-induced non-obstructive azoospermic mouse model was used, and Npre was administered for five weeks following the drug injection, with the objective of reinstating spermatogenesis and fertility. Initially, we assessed the NAD+ level, germ cell types, semen parameters and sperm fertilization capability. Subsequently, testis tissues were examined through RNA sequencing analysis, ELISA, H&E, immunofluorescence, quantitative real-time PCR, and Western blotting techniques. Results: The results indicated that Npre restored normal level of NAD+ in blood and significantly alleviated the deleterious effects of busulfan (BU) on spermatogenesis, thereby partially reestablishing fertilization capacity. Transcriptome analysis, along with recovery of testicular Fe2+, GSH, NADPH, and MDA levels, impaired by BU, and the fact that Fer-1, an inhibitor of ferroptosis, restored spermatogenesis and semen parameters close to CTRL values, supported such possibility. Interestingly, the reduction in SIRT2 protein level by the specific inhibitor AGK2 attenuated the beneficial effects of Npre on spermatogenesis and ferroptosis by affecting PGC-1α and ACLY protein levels, thus suggesting how these compounds might confer spermatogenesis protection. Conclusion: Collectively, these findings indicate that NAD+ protects spermatogenesis against ferroptosis, probably through SIRT2 dependent mechanisms. This underscores the considerable potential of Npre supplementation as a feasible strategy for preserving or restoring spermatogenesis in specific conditions of male infertility and as adjuvant therapy to preserve male fertility in cancer patients receiving sterilizing treatments.

Circ-Bptf Ameliorates Learning and Memory Impairments via the miR-138-5p/p62 Axis in APP/PS1 Mice.

Alzheimer's disease (AD) is a common age-associated progressive neurodegenerative disorder that is implicated in the aberrant regulation of numerous circular RNAs (circRNAs). Here, we reported that circ-Bptf, a conserved circRNA derived from the Bptf gene, showed an age-dependent decrease in the hippocampus of APP/PS1 mice. Overexpression of circ-Bptf significantly reversed dendritic spine loss and learning and memory impairment in APP/PS1 mice. Moreover, we found that circ-Bptf was predominantly localized to the cytoplasm and upregulated p62 expression by binding to miR-138-5p. Furthermore, the miR-138-5p mimics reversed the decreased expression of p62 induced by the silencing of circ-Bptf. Together, our findings suggested that circ-Bptf ameliorated learning and memory impairments via the miR-138-5p/p62 axis in APP/PS1 mice. It may act as a potential player in AD pathogenesis and therapy.

Exploring the diversity, bioactivity of endophytes, and metabolome in Synsepalum dulcificum.

Synsepalum dulcificum exhibits high edible and medicinal value; however, there have been no reports on the exploration of its endophyte resources. Here, we conducted analyses encompassing plant metabolomics, microbial diversity, and the biological activities of endophytic metabolites in S. dulcificum. High-throughput sequencing identified 4,913 endophytic fungal amplicon sequence variants (ASVs) and 1,703 endophytic bacterial ASVs from the roots, stems, leaves, flowers, and fruits of S. dulcificum. Fungi were classified into 5 phyla, 24 classes, 75 orders, 170 families, and 313 genera, while bacteria belonged to 21 phyla, 47 classes, 93 orders, 145 families, and 232 genera. Furthermore, there were significant differences in the composition and content of metabolites in different tissues of S. dulcificum. Spearman's correlation analysis of the differential metabolites and endophytes revealed that the community composition of the endophytes correlated with plant-rich metabolites. The internal transcribed spacer sequences of 105 isolates were determined, and phylogenetic analyses revealed that these fungi were distributed into three phyla (Ascomycota, Basidiomycota, and Mucoromycota) and 20 genera. Moreover, 16S rDNA sequencing of 46 bacteria revealed they were distributed in 16 genera in three phyla: Actinobacteria, Proteobacteria, and Firmicutes. The antimicrobial activities (filter paper method) and antioxidant activity (DPPH and ABTS assays) of crude extracts obtained from 68 fungal and 20 bacterial strains cultured in different media were evaluated. Additionally, the α-glucosidase inhibitory activity of the fungal extracts was examined. The results showed that 88.6% of the strains exhibited antimicrobial activity, 55.7% exhibited antioxidant activity, and 85% of the fungi exhibited α-glucosidase inhibitory activity. The research suggested that the endophytes of S. dulcificum are highly diverse and have the potential to produce bioactive metabolites, providing abundant species resources for developing antibiotics, antioxidants and hypoglycemic drugs.

MMDTA: A Multimodal Deep Model for Drug-Target Affinity with a Hybrid Fusion Strategy.

The prediction of the drug-target affinity (DTA) plays an important role in evaluating molecular druggability. Although deep learning-based models for DTA prediction have been extensively attempted, there are rare reports on multimodal models that leverage various fusion strategies to exploit heterogeneous information from multiple different modalities of drugs and targets. In this study, we proposed a multimodal deep model named MMDTA, which integrated the heterogeneous information from various modalities of drugs and targets using a hybrid fusion strategy to enhance DTA prediction. To achieve this, MMDTA first employed convolutional neural networks (CNNs) and graph convolutional networks (GCNs) to extract diverse heterogeneous information from the sequences and structures of drugs and targets. It then utilized a hybrid fusion strategy to combine and complement the extracted heterogeneous information, resulting in the fused modal information for predicting drug-target affinity through the fully connected (FC) layers. Experimental results demonstrated that MMDTA outperformed the competitive state-of-the-art deep learning models on the widely used benchmark data sets, particularly with a significantly improved key evaluation metric, Root Mean Square Error (RMSE). Furthermore, MMDTA exhibited excellent generalization and practical application performance on multiple different data sets. These findings highlighted MMDTA's accuracy and reliability in predicting the drug-target binding affinity. For researchers interested in the source data and code, they are accessible at http://github.com/dldxzx/MMDTA.

Implementation and evaluation of a pharmacy family program to foster community and inclusion.

BACKGROUND AND PURPOSE: Learning communities in the form of student-faculty families in pharmacy education provide a structure to foster community and inclusion. The purpose of this work is to describe how a new Pharmacy Family (PF) program was implemented and to evaluate the impact on students. EDUCATIONAL ACTIVITY AND SETTING: Our PF program was developed with the goals of building community, promoting a sense of belonging, providing students with opportunities to share and receive advice, and providing a venue for surveillance of student concerns. Each family was comprised of one to two faculty/instructor leaders and three to four doctor of pharmacy students from each cohort and met longitudinally over the course of the academic year. Quantitative and qualitative survey data were collected to assess student perceptions and program satisfaction. FINDINGS: A total of 233 students (66.2%) completed the survey and the majority (66%) were satisfied with the program. Thematic analysis of open-ended questions revealed four themes that contributed to students' satisfaction ratings: meeting content, relationships, atmosphere, and timing. Students with high satisfaction frequently noted that the program fostered connections, mentoring opportunities, and a safe space to share concerns. Students that were neutral or dissatisfied frequently commented on the timing of meetings and inability to form deeper connections. SUMMARY: Student-faculty families can be implemented to improve community and engagement within pharmacy education. Our program was most successful in providing a venue for students to share concerns. Addressing meeting times and adjusting the structure to promote community building is warranted to achieve program goals.

Understanding the medication experience of patients with advanced non-small cell lung cancer taking epidermal growth factor receptor-tyrosine kinase inhibitors: A phenomenological study.

BACKGROUND AND OBJECTIVE: Patients with cancer taking oral antineoplastic medications may encounter problems including suboptimal adherence as well as physical and psychological disease burden. Despite increase in the use of oncology pharmacy services, there are wide variations between healthcare professionals and patient perceptions of patients' medication experiences. The objective of the study was to explore the medication experience of taking oral targeted therapy in patients with advanced non-small cell lung cancer (NSCLC). METHOD: We purposively sampled advanced stage (stage III or IV) NSCLC patients taking epidermal growth factor receptor-tyrosine kinase inhibitors (EGFR-TKIs) in a medical center in Taiwan. Face-to-face interviews using semi-structured interview guides were conducted. Interviews were transcribed verbatim and thematic analysis was applied. A phenomenological methodology was adopted to explore the underlying meaning of patients' lived experience. RESULTS: A total of 19 participants with a mean age of 68.2 years were interviewed. The duration of EGFR-TKIs use ranged from 2 weeks to 5 years. When first learned about the unexpected yet 'treatable' cancer, participants expressed strong emotional responses based on their intrinsic beliefs of the terminal disease and therapy. They walked along an unfamiliar trail while confronting physical and psychological challenges and made compromises to treatment. Gaining experiences from cancer journey, patients with cancer continuously seek the ultimate goals-'return to normal'. CONCLUSIONS: This study also revealed medication experiences of participants' journey from seeking information in the initial phase and living with cancer, to taking back control of their own lives. Healthcare professionals could better empathize with patients' loss of control and understand their perspectives when making clinical decisions. These findings can guide interdisciplinary teams to integrate patients' beliefs and conduct pre-screening assessments of health literacy levels to tailor communication. Subsequent interventions should be developed to identify barriers to medication self-management and empower patients by building social networks.

Exogenous myo-inositol increases salt tolerance and accelerates CAM induction in the early juvenile stage of the facultative halophyte Mesembryanthemum crystallinum but not in the late juvenile stage.

Mesembryanthemum crystallinum L. (ice plant) develops salt tolerance during the transition from the juvenile to the adult stage through progressive morphological, physiological, biochemical, and molecular changes. Myo -inositol is the precursor for the synthesis of compatible solute D-pinitol and promotes Na+ transport in ice plants. We previously showed that supplying myo -inositol to 9-day-old seedlings alleviates salt damage by coordinating the expression of genes involved in inositol synthesis and transport, affecting osmotic adjustment and the Na/K balance. In this study, we examined the effects of myo -inositol on physiological parameters and inositol-related gene expression in early- and late-stage juvenile plants. The addition of myo -inositol to salt-treated, hydroponically grown late juvenile plants had no significant effects on growth or photosynthesis. In contrast, supplying exogenous myo -inositol to salt-treated early juvenile plants increased leaf biomass, relative water content, and chlorophyll content and improved PSII activity and CO2 assimilation. The treatment combining high salt and myo -inositol synergistically induced the expression of myo -inositol phosphate synthase (INPS ), myo -inositol O -methyltransferase (IMT ), and inositol transporters (INTs ), which modulated root-to-shoot Na/K ratio and increased leaf D-pinitol content. The results indicate that sufficient myo -inositol is a prerequisite for high salt tolerance in ice plant.

Risk Factors for Level-VII Lymph Node Metastases of Thyroid Neoplasms: A Meta-Analysis.

OBJECTIVE: The present study conducted a meta-analysis to forecast the risk factors associated with level-VII lymph node metastases in case of thyroid neoplasms, intending to assist in determining the requirement for level-VII lymph node lymphadenectomy during the surgery. METHODS: Electronic databases, PubMed, Embase, the Cochrane Library, CNKI, Wanfang Data, VIP, and CBM electronic databases were searched for studies focused on level-VII lymph node metastases in thyroid neoplasms, published up to April 2021. Stata 13.1 software was used for analyses. RESULTS: The literature search identified a total of 997 studies. Among these, 8 studies, involving 1813 patients, were included in the present case. All these studies were case-control studies. Results for meta-analysis showed that male (OR = 1.340, 95% CI: 1.018-1.764, P = .037), age < 45 years (OR = 4.178, 95% CI: 1.601-10.908, P = .003), tumor size ≥ 2.0 cm (OR = 1.960, 95% CI: 1.079-3.562, P = .027), extrathyroidal extension (OR = 2.037, 95% CI: 1.578-2.630, P < .001), distant metastasis (OR = 2.775, 95% CI: 2.005-3.840, P < .001), central lymph node metastasis (OR = 3.500, 95% CI: 1.127-10.874, P = .03), contralateral cervicolateral metastasis (OR = 2.119, 95% CI: 1.514-2.965, P < .001), and bilateral nodal metastasis (OR = 4.651, 95% CI: 2.697-8.020, P < .001) acted as risk factors for level-VII lymph node metastases. In addition to this, sensitivity analyses and bias test showed that the results of meta-analysis were reliable and stable and involved no publication bias. CONCLUSION: In the present study, male gender, age < 45 years, tumor size ≥ 2.0 cm, extrathyroidal extension, distant metastasis, central lymph node metastasis, contralateral cervicolateral metastasis, and bilateral nodal metastasis were identified as risk factors for level-VII lymph node metastases in case of thyroid neoplasms.

Estimation of the population, death, and quality of life in Shaanxi Province, western China: a cross-sectional study / 中华医学杂志(英文版)

BACKGROUND@#Measuring the health of the population is of great significance to the development of a region. We aimed to estimate the population, probability of death, and quality of life in western China.@*METHODS@#We calculated the age-specific mortality rate and prevalence rate of diseases and injuries using the Full Population Database and the Home Page of Inpatient Medical Record. We used multiple interpolation methods to insert missing information from the death data and the model of Kannisto to adjust the mortality rate for elderly individuals. The age-specific prevalence rate of diseases and injuries was adjusted according to the standard ratio of age and methods of equal proportional allocation. Life expectancy was calculated by a life table, and the quality of life was estimated using the Sullivan method.@*RESULTS@#The total population continued to increase in 2015 to 2019 in the Shaanxi Province, China. The mortality rate of children under five has improved, and the mortality rate of people over 65 is decreasing year by year. Life expectancy increased from 74.66 years in 2015 to 77.19 years in 2019. Even with the total risk of disease and injury, the health-adjusted life expectancy increased by 1.90 years within 5 years, and the number of unhealthy years significantly improved. Health-adjusted life expectancy increased by 1.75 years when only considered the ten major disease systems (tumors; endocrinology, nutrition and metabolism; mental and behavioral disorders; nervous system; sensory diseases; circulatory system; respiratory system; digestive system; genitourinary system; musculoskeletal system and connective tissue), and the number of unhealthy years increased slightly.@*CONCLUSIONS@#In the past five years, Shaanxi Province has made progress in improving life expectancy and controlling the development of chronic diseases. It is necessary to take specific preventive measures and improve the quality of basic public health services.

Effect of Home Blood Pressure Telemonitoring Plus Additional Support on Blood Pressure Control: A Randomized Clinical Trial / 生物医学与环境科学（英文）

OBJECTIVE@#Current clinical evidence on the effects of home blood pressure telemonitoring (HBPT) on improving blood pressure control comes entirely from developed countries. Thus, we performed this randomized controlled trial to evaluate whether HBPT plus support (patient education and clinician remote hypertension management) improves blood pressure control more than usual care (UC) in the Chinese population.@*METHODS@#This single-center, randomized controlled study was conducted in Beijing, China. Patients aged 30-75 years were eligible for enrolment if they had blood pressure [systolic (SBP) ≥ 140 mmHg and/or diastolic (DBP) ≥ 90 mmHg; or SBP ≥ 130 mmHg and/or DBP ≥ 80 mmHg with diabetes]. We recruited 190 patients randomized to either the HBPT or the UC groups for 12 weeks. The primary endpoints were blood pressure reduction and the proportion of patients achieving the target blood pressure.@*RESULTS@#Totally, 172 patients completed the study, the HBPT plus support group ( n = 84), and the UC group ( n = 88). Patients in the plus support group showed a greater reduction in mean ambulatory blood pressure than those in the UC group. The plus support group had a significantly higher proportion of patients who achieved the target blood pressure and maintained a dipper blood pressure pattern at the 12th week of follow-up. Additionally, the patients in the plus support group showed lower blood pressure variability and higher drug adherence than those in the UC group.@*CONCLUSION@#HBPT plus additional support results in greater blood pressure reduction, better blood pressure control, a higher proportion of dipper blood pressure patterns, lower blood pressure variability, and higher drug adherence than UC. The development of telemedicine may be the cornerstone of hypertension management in primary care.

Subcellular redox responses reveal different Cu-dependent antioxidant defenses between mitochondria and cytosol.

Excess intracellular Cu perturbs cellular redox balance and thus causes diseases. However, the relationship between cellular redox status and Cu homeostasis and how such an interplay is coordinated within cellular compartments has not yet been well established. Using combined approaches of organelle-specific redox sensor Grx1-roGFP2 and non-targeted proteomics, we investigate the real-time Cu-dependent antioxidant defenses of mitochondria and cytosol in live HEK293 cells. The Cu-dependent real-time imaging experiments show that CuCl2 treatment results in increased oxidative stress in both cytosol and mitochondria. In contrast, subsequent excess Cu removal by bathocuproine sulfonate, a Cu chelating reagent, lowers oxidative stress in mitochondria but causes even higher oxidative stress in the cytosol. The proteomic data reveal that several mitochondrial proteins, but not cytosolic ones, undergo significant abundance change under Cu treatments. The proteomic analysis also shows that proteins with significant changes are related to mitochondrial oxidative phosphorylation and glutathione synthesis. The differences in redox behaviors and protein profiles in different cellular compartments reveal distinct mitochondrial and cytosolic response mechanisms upon Cu-induced oxidative stress. These findings provide insights into how redox and Cu homeostasis interplay by modulating specific protein expressions at the subcellular levels, shedding light on understanding the effects of Cu-induced redox misregulation on the diseases.

A Culturally Tailored Diabetes Self-Management Intervention Incorporating Race-Congruent Peer Support to Address Beliefs, Medication Adherence and Diabetes Control in African Americans: A Pilot Feasibility Study.

Introduction: Current diabetes self-management programs are often insufficient to improve outcomes for African Americans because of a limited focus on medication adherence and addressing culturally influenced beliefs about diabetes and medicines. This study evaluated the feasibility and acceptability of a novel culturally tailored diabetes self-management intervention that addressed key psychosocial and sociocultural barriers to medication adherence for African Americans. Methods: The intervention consisted of group education and race-congruent peer-based phone support. Three African Americans who were engaged in taking their diabetes medicines (ambassadors), were matched with 8 African Americans who were not engaged in taking medicines (buddies). We conducted a single group, pre/post study design with African Americans with type 2 diabetes. Wilcoxon signed rank tests assessed mean score differences in outcomes at baseline compared with 6-months follow-up. Semi-structured interviews explored buddies' acceptability of the intervention. Results: Buddies and ambassadors were similar in age and mostly female. Recruitment rates were 80% for buddies and 100% for ambassadors. Retention rate for primary outcomes was 75%. Buddies had a mean completion of 13.4/17 of sessions and phone calls. Ambassadors completed 84% of intervention calls with buddies. Although there were no statistically significant differences in mean A1C and medication adherence, we found a clinically meaningful decrease (-0.7) in mean A1C at the 6-month follow up compared to baseline. Secondary outcomes showed signal of changes. Themes showed buddies perceived an improvement in provider communication, learned goal setting strategies, and developed motivation, and confidence for self-management. Buddies perceived the program as acceptable and culturally appropriate. Conclusion: This culturally tailored diabetes self-management intervention that addresses diabetes self-management, psychosocial and behavioral barriers to medication adherence, and incorporates race-congruent peer support from African Americans engaged in taking medicines seemed feasible and acceptable. The results provide support for a fully powered randomized trial to test the intervention's efficacy. Trial Registration: https://clinicaltrials.gov/ct2/show/NCT04857411. Date of Registration: April 23, 2021.

Perspectives on a Novel Culturally Tailored Diabetes Self-Management Program for African Americans: A Qualitative Study of Healthcare Professionals and Organizational Leaders.

BACKGROUND: There is an urgent need for culturally tailored diabetes self-management education to improve health outcomes in African Americans, especially given the disproportionate prevalence of diabetes and medication non-adherence. Stakeholder engagement can guide and enrich the development of these interventions by integrating content directly addressing barriers to African Americans' adherence with existing community-based diabetes self-management education programs. The aim of this study is to explore stakeholder perspectives on a novel culturally tailored diabetes self-management program for African Americans. METHODS: Thirteen semi-structured individual interviews were conducted in a large Midwestern U.S. city with healthcare professionals and organizational leaders serving African American communities and/or providing diabetes education. Transcripts were analyzed using directed content analysis with the Consolidated Framework for Implementation Research and inductive content analysis. RESULTS: Five overarching themes were identified: (1) fulfill needs among stakeholders, (2) creating a supportive and trusting environment to address distrust, (3) building relationships and empowering peers, (4) logistical organization barriers to program implementation and (5) challenges to program acceptance by participants. CONCLUSION: Stakeholders delineated how the new culturally tailored diabetes self-management program aligned with the needs of African American patients. Perceived challenges and corresponding strategies to address barriers to participation were identified to inform program implementation and sustainability.

Annexin V- and tissue factor+ microparticles as biomarkers for predicting deep vein thrombosis in patients after joint arthroplasty.

OBJECTIVE: Venous thromboembolism (VTE) is a common and severe complication of joint arthroplasty. Microparticles (MPs) containing phosphatidylserine (PS) and tissue factor (TF) can trigger coagulation in VTE. This study aims to measure and compare MP levels in joint arthroplasty patients with and without VTE. METHODS: This prospective cohort study enrolled 181 patients who underwent joint arthroplasty. Ultrasound examination was used to diagnose VTE on preoperative day 0 and postoperative day 6. MPs were analysed using transmission electron microscopy (TEM), nanoparticle tracking analysis (NTA), and flow cytometry. The levels of platelet-derived microparticles (PMPs), endothelial cell-derived microparticles (EMPs), granulocyte-derived microparticles (GMPs), red cell-derived microparticles (RMPs), monocyte-derived microparticles (MMPs), Annexin V+ MPs (AV+ MPs), and tissue factor+ MPs (TF+ MPs) derived from five kinds of MPs were measured on day 0 (before surgery), 1, 2, 3, 4, 5, and 6 after surgery. RESULTS: The levels of AV-TF+ EMPs and AV-TF+ MMPs were significantly increased in patients with VTE on postoperative day 5 compared to those without VTE (P = 0.031 and P = 0.031, respectively). CONCLUSION: AV-TF+ MPs may indicate the development of VTE and serve as predictive markers in joint arthroplasty patients.