Updates of precision medicine in type 2 diabetes

Diabetes mellitus is prevalent worldwide and affects 1 in 10 adults. Despite the successful development of glucose-lowering drugs, such as glucagon-like peptide-1 (GLP-1) receptor agonists and sodium-glucose cotransporter-2 inhibitors recently, the proportion of patients achieving satisfactory glucose control has not risen as expected. The heterogeneity of diabetes determines that a one-size-fits-all strategy is not suitable for people with diabetes. Diabetes is undoubtedly more heterogeneous than the conventional subclassification, such as type 1, type 2, monogenic and gestational diabetes. The recent progress in genetics and epigenetics of diabetes has gradually unveiled the mechanisms underlying the heterogeneity of diabetes, and cluster analysis has shown promising results in the substratification of type 2 diabetes, which accounts for 95% of diabetic patients. More recently, the rapid development of sophisticated glucose monitoring and artificial intelligence technologies further enabled comprehensive consideration of the complex individual genetic and clinical information and might ultimately realize a precision diagnosis and treatment in diabetics.

Clinical characteristics of the host DNA-removed metagenomic next-generation sequencing technology for detecting SARS-CoV-2, revealing host local immune signaling and assisting genomic epidemiology

Background Metagenomic next-generation sequencing (mNGS) technology has been central in detecting infectious diseases and helping to simultaneously reveal the complex interplay between invaders and their hosts immune response characteristics. However, it needs to be rigorously assessed for clinical utility. The present study is the first to evaluate the clinical characteristics of the host DNA-removed mNGS technology for detecting SARS-CoV-2, revealing host local immune signaling and assisting genomic epidemiology. Methods 46 swab specimens collected from COVID-19 patients were assayed by two approved commercial RT-qPCR kits and mNGS. The evolutionary tree of SARS-CoV-2 was plotted using FigTree directly from one sample. The workflow of removing the host and retaining the host was compared to investigate the influence of host DNA removal on the performances of mNGS. Functional enrichment analysis of DEGs and xCell score were used to explore the characteristics of host local immune signaling. Results The detection rate of mNGS achieved 92.9% (26/28) for 28 samples with a Ct value ≤ 35 and 81.1% (30/37) for all 46 samples. The genome coverage of SARS-CoV-2 could reach up to 98.9% when the Ct value is about 20 in swab samples. Removing the host could enhance the sensitivity of mNGS for detecting SARS-CoV-2 from the swab sample but does not affect the species abundance of microbes RNA. Improving the sequencing depth did not show a positive effect on improving the detection sensitivity of SARS-CoV-2. Cell type enrichment scores found multiple immune cell types were differentially expressed between patients with high and low viral load. Conclusions The host DNA-removed mNGS has great potential utility and superior performance on comprehensive identification of SARS-CoV-2 and rapid traceability, revealing the microbiome’s transcriptional profiles and host immune responses.

Field measurements of indoor and community air quality in rural Beijing before, during, and after the COVID-19 lockdown.

The coronavirus (COVID-19) lockdown in China is thought to have reduced air pollution emissions due to reduced human mobility and economic activities. Few studies have assessed the impacts of COVID-19 on community and indoor air quality in environments with diverse socioeconomic and household energy use patterns. The main goal of this study was to evaluate whether indoor and community air pollution differed before, during, and after the COVID-19 lockdown in homes with different energy use patterns. Using calibrated real-time PM2.5 sensors, we measured indoor and community air quality in 147 homes from 30 villages in Beijing over 4 months including periods before, during, and after the COVID-19 lockdown. Community pollution was higher during the lockdown (61 ± 47 µg/m3 ) compared with before (45 ± 35 µg/m3 , p < 0.001) and after (47 ± 37 µg/m3 , p < 0.001) the lockdown. However, we did not observe significantly increased indoor PM2.5 during the COVID-19 lockdown. Indoor-generated PM2.5 in homes using clean energy for heating without smokers was the lowest compared with those using solid fuel with/without smokers, implying air pollutant emissions are reduced in homes using clean energy. Indoor air quality may not have been impacted by the COVID-19 lockdown in rural settings in China and appeared to be more impacted by the household energy choice and indoor smoking than the COVID-19 lockdown. As clean energy transitions occurred in rural households in northern China, our work highlights the importance of understanding multiple possible indoor sources to interpret the impacts of interventions, intended or otherwise.

Advances in application of single-cell RNA sequencing in cardiovascular research.

Single-cell RNA sequencing (scRNA-seq) provides high-resolution information on transcriptomic changes at the single-cell level, which is of great significance for distinguishing cell subtypes, identifying stem cell differentiation processes, and identifying targets for disease treatment. In recent years, emerging single-cell RNA sequencing technologies have been used to make breakthroughs regarding decoding developmental trajectories, phenotypic transitions, and cellular interactions in the cardiovascular system, providing new insights into cardiovascular disease. This paper reviews the technical processes of single-cell RNA sequencing and the latest progress based on single-cell RNA sequencing in the field of cardiovascular system research, compares single-cell RNA sequencing with other single-cell technologies, and summarizes the extended applications and advantages and disadvantages of single-cell RNA sequencing. Finally, the prospects for applying single-cell RNA sequencing in the field of cardiovascular research are discussed.

The Influencing Factors of Breastfeeding for Full-Term Singleton Within Six Months of Birth in Xi'an Before the Covid-19 Pandemic.

Objective: The study is designed to understand the situation of full-term infants breastfeeding within 6 months of birth in Xi'an before the Covid-19 pandemic and analyze the influencing factors of exclusive breastfeeding. Methods: Five hospitals in Xi'an province have been selected as research centers. Full-term infants who met the inclusion and exclusion criteria were recruited from these centers between January 1 and February 28, 2019. The feeding situation at 10 days, 42 days, 3 months, and 6 months after birth were investigated. A self-designed breastfeeding questionnaire was used for investigation and follow-up. SPSS 22.0 was applied for statistical analysis of the data. Results: The exclusive breastfeeding rate of full-term infants on days 10 and 42 and at months three and six after birth was 61.38%, 54.78%, 48.83%, and 38.78%, respectively, with a decreasing trend over time. During breastfeeding within 48 h after delivery, 1,653 cases (91.83%) of puerpera had different grades of pain, including 1,325 cases (80.16%) of mild discomfort, 321 cases (19.42%) of moderate pain, and seven cases (0.42%) of severe pain. Within 24-48 h postpartum, 1,607 (89.27%) mothers faced problems related to postpartum breastfeeding. Among them, 694 (43,19%) neonates could not be fed effectively; 665 (41.38%) mothers had wound pain and had inconvenience to turn over; 598 (37.21%) neonates were difficult to wake up; 439 (27.32%) mothers had incorrect feeding posture; 181 (11.26%) mothers experienced other problems. The Cox risk regression model showed that weight gain during pregnancy was higher than the recommended standard. Living in suburban counties was a risk factor of exclusive breastfeeding for full-term infants. Participation in breastfeeding courses during pregnancy, feeding more than eight times daily after delivery, were the protective factors of exclusive breastfeeding for full-term infants. Conclusion: The body weight gain of parturients should be controlled within a reasonable range during pregnancy. Parturients were encouraged by medical staff to participate in breastfeeding courses or watch the breastfeeding process during pregnancy to increase their self-confidence and improve the rate of exclusive breastfeeding for full-term infants. In addition, it is necessary to strengthen the publicity of breastfeeding in suburban areas to promote breastfeeding.

Serum Albumin Levels are a Predictor of COVID-19 Patient Prognosis: Evidence from a Single Cohort in Chongqing, China.

BACKGROUND: COVID-19 infections are still at pandemic levels globally and there are currently no specific drugs to treat these infections. Previous studies have demonstrated that serum albumin levels were abnormally low in COVID-19 patients and might be used as a prognosis biomarker. Supplemental albumin has been used as an experimental therapeutic method. However, dynamic evaluation of albumin in patients with COVID-19 was limited and whether serum albumin could predict the prognosis of these patients is unknown. METHODS: We enrolled 79 COVID-19 patients in the present study and reviewed electronic medical laboratory records. Data was processed using SPSS software (Version 20.0) and correlation analysis was performed between serum albumin and other clinical and laboratory findings. RESULTS: Serum albumin levels were gradually decreased both in severe and non-severe COVID-19 patients. Moreover, 17.7% of the patients presented with hypoalbuminemia at least one time during 3 consecutive weekly time points. The hypoalbuminemia group displayed more severe disease and comorbidity that included fever, fatigue, headache, and dizziness on admission. Moreover, serum albumin levels were positively correlated with lymphocyte and RBC numbers, Hb and prealbumin levels as well as with total T cell numbers and the presence of CD4+ and CD8+ T cells. In contrast, there was a negative correlation with C-reactive protein levels and this was an indicator of patient recovery. CONCLUSION: Our results demonstrated that hypoalbuminemia was common in COVID-19 patients and its levels were linked to disease severity. Patients with fever, fatigue and headache or dizziness on admission were more likely to experience hypoalbuminemia. Dynamic monitoring of serum albumin is therefore necessary and should be performed during COVID-19 patient treatments as a tool for evaluating the prognosis of COVID-19 infections.

Coagulopathy is a major extrapulmonary risk factor for mortality in hospitalized patients with COVID-19 with type 2 diabetes.

INTRODUCTION: To investigate the risk factors for the death in patients with COVID-19 with type 2 diabetes mellitus (T2DM). RESEARCH DESIGN AND METHODS: We retrospectively enrolled inpatients with COVID-19 from Wuhan Jinyintan Hospital (Wuhan, China) between December 25, 2019, and March 3, 2020. The epidemiological and clinical data were compared between non-T2DM and T2DM or between survivors and non-survivors. Univariable and multivariable Cox regression analyses were used to explore the effect of T2DM and complications on in-hospital death. RESULTS: A total of 1105 inpatients with COVID-19, 967 subjects with without T2DM (n=522 male, 54.0%) and 138 subjects with pre-existing T2DM (n=82 male, 59.4%) were included for baseline characteristics analyses. The complications were also markedly increased in patients with pre-existing T2DM, including acute respiratory distress syndrome (ARDS) (48.6% vs 32.3%, p<0.001), acute cardiac injury (ACI) (36.2% vs 16.7%, p<0.001), acute kidney injury (AKI) (24.8% vs 9.5%, p<0.001), coagulopathy (24.8% vs 11.1%, p<0.001), and hypoproteinemia (21.2% vs 9.4%, p<0.001). The in-hospital mortality was significantly higher in patients with pre-existing T2DM compared with those without T2DM (35.3% vs 17.4%, p<0.001). Moreover, in hospitalized patients with COVID-19 with T2DM, ARDS and coagulopathy were the main causes of mortality, with an HR of 7.96 (95% CI 2.25 to 28.24, p=0.001) for ARDS and an HR of 2.37 (95% CI 1.08 to 5.21, p=0.032) for coagulopathy. This was different from inpatients with COVID-19 without T2DM, in whom ARDS and cardiac injury were the main causes of mortality, with an HR of 12.18 (95% CI 5.74 to 25.89, p<0.001) for ARDS and an HR of 4.42 (95% CI 2.73 to 7.15, p<0.001) for cardiac injury. CONCLUSIONS: Coagulopathy was a major extrapulmonary risk factor for death in inpatients with COVID-19 with T2DM rather than ACI and AKI, which were well associated with mortality in inpatients with COVID-19 without T2DM.