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Abstract Early insulin therapy is capable to achieve glycemic control and restore β-cell function in newly diagnosed type 2 diabetes (T2D), but its effect on cardiovascular outcomes in these patients remains unclear. In this nationwide real-world study, we analyzed electronic health record data from 19 medical centers across China between 1 January 2000, and 26 May 2022. We included 5424 eligible patients (mean age 56 years, 2176 women/3248 men) who were diagnosed T2D within six months and did not have prior cardiovascular disease. Multivariable Cox regression models were used to estimate the associations of early insulin therapy (defined as the first-line therapy for at least two weeks in newly diagnosed T2D patients) with the incidence of major cardiovascular events including coronary heart disease (CHD), stroke, and hospitalization for heart failure (HF). During 17,158 persons years of observation, we documented 834 incident CHD cases, 719 stroke cases, and 230 hospitalized cases for HF. Newly diagnosed T2D patients who received early insulin therapy, compared with those who did not receive such treatment, had 31% lower risk of incident stroke, and 28% lower risk of hospitalization for HF. No significant difference in the risk of CHD was observed. We found similar results when repeating the aforesaid analysis in a propensity-score matched population of 4578 patients and with inverse probability of treatment weighting models. These findings suggest that early insulin therapy in newly diagnosed T2D may have cardiovascular benefits by reducing the risk of incident stroke and hospitalization for HF.

Key Clinical Message Prompt and precise diagnosis of pituitary hyperplasia secondary to primary hypothyroidism (PHPH) is crucial to avoid unwarranted pituitary surgery and potential permanent impairment. Although PHPH may present similarly to pituitary adenoma, it is responsive to thyroxine therapy, underscoring the critical role of differential diagnosis in the treatment of adolescent patients.

Abstract Background The composition and function of gut microbiota, lipids, and metabolites in patients with type 1 diabetes (T1D) or its association with glycemic control remains unknown. We aimed to use multi‐omics sequencing technology and machine learning (ML) approaches to investigate potential function and relationships among the gut microbiota, lipids, and metabolites in T1D patients at varied glycemic levels. Methods We conducted a multi‐omics analysis of the gut microbiome from fecal samples, metabolites, and lipids obtained from serum samples, collected from a cohort of 72 T1D patients. The patients were divided into two groups based on their hemoglobin A1c (HbA1c) levels. 16S rRNA sequencing, and metabolomics methods were applied to analyze changes in composition and function of gut microbiota, metabolites, and lipids. Results The linear discriminant analysis, Shapley additive explanations (SHAP) algorithm, and ML algorithms revealed the enrichment of Bacteroides_nordii, Bacteroides_cellulosilyticus in the glycemic control (GC) group, while Bacteroides_coprocola and Sutterella_wadsworthensis were enriched in the poor glycemic control (PGC) group. Several metabolic enrichment sets like fatty acid biosynthesis and glycerol phosphate shuttle metabolism were different between two groups. Bacteroides_nordii exhibited a negative association with D‐fructose, a component involved in the starch and sucrose metabolism pathway, as well as with monoglycerides (16:0) involved in the glycerolipid metabolism pathway. Conclusions We identified distinct characteristics of gut microbiota, metabolites, and lipids in T1D patients exhibiting different levels of glycemic control. Through comprehensive analysis, microbiota (Bacteroides_nordii, Bacteroides_coprocola), metabolites (D‐fructose), and lipids (Monoglycerides) may serve as potential mediators that communicated the interaction between the gut, circulatory systems, and glucose fluctuations in T1D patients.

Introduction Non-ST-elevation acute coronary syndrome (NSTE-ACS) remains a significant clinical concern, accounting for over 70% of acute coronary syndrome cases. One well-established risk factor for NSTE-ACS is abnormal glucose metabolism, which is associated with a poor prognosis postpercutaneous coronary intervention. Effective monitoring of blood glucose is crucial in diabetes care, as it helps identify glucose metabolic imbalances, thereby guiding therapeutic strategies and assessing treatment efficacy. Continuous glucose monitoring (CGM) provides comprehensive glucose profiles. Therefore, the study aims to use CGM to track perioperative glucose variations in NSTE-ACS patients and to determine its prognostic implications.Methods and analysis This is a multicentre, prospective observational study in a sample of patients (aged >18 years) with NSTE-ACS. A total of 1200 eligible patients will be recruited within 1 year at 6 sites in China. The primary composite endpoint will be determined as major adverse cardiovascular events (MACE) at 3 years. MACE includes all-cause mortality, non-fatal myocardial infarction, non-fatal stroke and target vessel revascularisation. Employing the CGM system, glucose levels will be continuously monitored throughout the perioperative phase. Prespecified cardiovascular analyses included analyses of the components of this composite and outcomes according to CGM-derived glucometrics at baseline.Ethics and dissemination This study has received approval from the Medical Research Ethics Committee of The First Affiliated Hospital of the University of Science and Technology of China (No. 2022KY357) and will adhere to the moral, ethical and scientific principles outlined in the Declaration of Helsinki. All participants will provide written informed consent prior to any study-related procedures. Findings from the study will be shared at conferences and published in peer-reviewed scientific journals.Trial registration number ChiCT2300069663.

Abstract Introduction The study aimed to compare glycemic control and pregnancy outcomes in women with type 1 diabetes mellitus (T1DM) using multiple daily injection therapy (MDI) and continuous subcutaneous insulin infusion (CSII) and to compare outcomes of women treated with long‐acting insulin or neutral protamine Hagedorn (NPH). Methods This multicenter prospective cohort study involved women with pregestational T1DM treated with MDI and CSII. Primary outcome was glycated hemoglobin (HbA1c) before and during pregnancy. Secondary outcomes included maternal and neonatal outcomes and quality of life. Results Of the 121 studied women, the average age was 28.48 years, and the average body mass index was 21.29 kg/m2 at conception and 26.32 kg/m2 at delivery. Of the studied women, 78.51% had planned pregnancy. Women treated with MDI and CSII had comparable HbA1c before pregnancy or in the first and second trimesters. In the third trimester, women on CSII therapy had significantly lower HbA1c (6.07 ± 0.62 vs 6.20 ± 0.88%, p = .017), higher HbA1c on‐target rate (71.43% vs 64.62%, p = .030), and greater decline of HbA1c from preconception to the third trimester (−0.65 vs −0.30%, p = .047). Fewer daily insulin requirements were observed in those used CSII compared with MDI‐treated women (0.60 ± 0.22 vs 0.73 ± 0.25 U/kg/day, p = .004). Newborns born of mothers treated with the CSII method were more likely to have neonatal jaundice (adjusted odds ratio [OR] 2.76, 95% confidence interval [CI] 1.16–6.57) and neonatal intensive care unit (adjusted OR 3.73, 95%CI 1.24–11.16), and women on CSII had lower scores in patient‐reported quality of life (p = .045). In the MDI group, those receiving long‐acting insulin had nonsignificant lower HbA1c and higher HbA1c on‐target rate in the second and third trimesters, compared with those treated with NPH. Conclusions Insulin pump users may achieve better glycemic control than multiple daily insulin injections, which did not substantially improve pregnancy outcome.

Abstract Background Depression is the most common psychological disorder in patients with type 1 diabetes (T1D). However, the characteristics of microbiota and metabolites in these patients remain unclear. This study aimed to investigate microbial and metabolomic profiles and identify novel biomarkers for T1D with depression. Methods A case–control study was conducted in a total of 37 T1D patients with depression (TD+), 35 T1D patients without depression (TD−), and 29 healthy controls (HCs). 16S rRNA gene sequencing and liquid chromatography–mass spectrometry (LC–MS) metabolomics analysis were conducted to investigate the characteristics of microbiota and metabolites. The association between altered microbiota and metabolites was explored by Spearman's rank correlation and visualized by a heatmap. The microbial signatures to discriminate TD+ from TD− were identified by a random forest (RF) classifying model. Results In microbiota, 15 genera enriched in TD− and 2 genera enriched in TD+, and in metabolites, 14 differential metabolites (11 upregulated and 3 downregulated) in TD+ versus TD− were identified. Additionally, 5 genera (including Phascolarctobacterium, Butyricimonas, and Alistipes from altered microbiota) demonstrated good diagnostic power (area under the curve [AUC] = 0.73; 95% CI, 0.58–0.87). In the correlation analysis, Butyricimonas was negatively correlated with glutaric acid (r = −0.28, p = 0.015) and malondialdehyde (r = −0.30, p = 0.012). Both Phascolarctobacterium (r = 0.27, p = 0.022) and Alistipes (r = 0.31, p = 0.009) were positively correlated with allopregnanolone. Conclusions T1D patients with depression were characterized by unique profiles of gut microbiota and serum metabolites. Phascolarctobacterium, Butyricimonas, and Alistipes could predict the risk of T1D with depression. These findings provide further evidence that the microbiota–gut–brain axis is involved in T1D with depression.

Owing to their high volumetric capacity, low cost and high safety, rechargeable aluminum batteries have become promising candidates for energy applications. However, the high charge density of Al3+ leads to strong coulombic interactions between anions and the cathode, resulting in sluggish diffusion kinetics and irreversible collapse of the cathode structure. Furthermore, AlCl3-based ionic liquids, which are commonly used as electrolytes in such batteries, corrode battery components and are prone to side reactions. The above problems lead to low capacity and poor cycling stability. Herein, we propose a reduced graphene oxide (rGO) cathode with a three-dimensional porous structure prepared using a simple and scalable method. The lamellar edges and oxygen-containing group defects of rGO synergistically provide abundant ion storage sites and enhance ion transfer kinetics. We matched the prepared rGO cathode with noncorrosive electrolyte 0.5 mol·L−1 Al(OTF)3/[BMIM]OTF and Al metal to construct a high-performance battery, Al||rGO-150, with good cycling stability for 2700 cycles. Quasi-in-situ physicochemical characterization results show that the ion storage mechanism is codominated by diffusion and capacitance. The capacity consists of the insertion of Al-based species cations as well as synergistic adsorption of Al(OTF)x(3−x)+ (x < 3) and [BMIM]+. The present study promotes the fundamental and applied research on rechargeable aluminum batteries.

Abstract Aim Evidence for contribution of basal and postprandial glucose increment, and glycemic variability to glycated hemoglobin (HbA1c) among adults with type 1 diabetes (T1D) is limited. This study aimed to capture glycemic fluctuation patterns and quantify contributions of these factors to HbA1c levels among adults with T1D. Methods HbA1c, continuous glucose monitoring (CGM), and diet diaries were collected and pooled from two clinical trials. Available data sets were divided into HbA1c quartiles: group 1 (≤6.7%), group 2 (6.7%–7.3%), group 3 (7.3%–7.8%), and group 4 (≥7.8%). Area under curve above 110 mg/dL (AUC>110mg/dL) in 24‐h profile was defined as overall hyperglycemia and stratified with postprandial hyperglycemia (PHG, AUC>110mg/dL in 3‐h period after meals) and basal hyperglycemia (BHG, AUC>110mg/dL in remaining period). Linear regression analysis was used to estimate the proportion of variance in HbA1c explained by BHG, preprandial glucose, PHG, glycemic variability, and non‐glycemic factors (age, body mass index, hemoglobin, and duration). Results A total of 169 550 glucose data in 2409 meals recorded from 102 patients (male/female, 34/68) were included. Age and duration were 35.2 ± 12.6 and 8.9 (2.9, 13.0) years, with 51.0% using pumps. Overall, BHG was four times higher than PHG (p all .05). Factors included in analysis explained a total of 74% of the variance in HbA1c, in which BHG accounted for 32.1% of variance whereas PHG accounted for 24.4%. In group with HbA1c >7.3%, BHG accounted for a higher percentage with 33.8% of the variance in HbA1c. Conclusions In our study, basal hyperglycemia better predicts overall glycemic control than postprandial hyperglycemia among adults with T1D. The relative contribution of basal hyperglycemia increased gradually with HbA1c increasing and predominant strategy for insulin titration among T1D is different among different levels of glycemic control.

Introduction ST-segment elevation myocardial infarction (STEMI) presents a serious cardiovascular condition requiring prompt intervention. Dysglycaemia has been identified as a significant risk factor impacting STEMI prognosis. However, limited research has focused on comprehensively examining the association between glucose dynamics during the perioperative period and patient outcomes. This study aims to address this gap by leveraging continuous glucose monitoring (CGM) technology to gain real-time insights into glucose fluctuations and their potential impact on STEMI prognosis.Methods and analysis This is a multicentre, prospective, 3-year follow-up cohort study. Between May 2023 and May 2024, 550 eligible STEM patients who underwent percutaneous coronary intervention are expected to be recruited. Using the CGM system, continuous glucose levels will be collected throughout the perioperative phase. Key clinical parameters, including cardiac biomarkers, angiographic findings and major adverse cardiovascular events, will be assessed in relation to glucose profile.Ethics and dissemination The study was approved by the Medical Research Ethics Committee of The First Affiliated Hospital of University of Science and Technology of China and will be conducted in accordance with the moral, ethical and scientific principles of the Declaration of Helsinki. Written informed consent will be obtained from all participants before any study-related procedures are implemented. Study results will be disseminated through conferences and peer-reviewed scientific journals.Trial registration number ChiCTR2300069662.

There are two contradictory views of the eROSITA bubbles: either a 10 ^4 pc scale pair of giant bubbles blown by the Galactic center (GC), or a 10 ^2 pc scale local structure coincidentally located in the direction of GC. A key element of this controversy is the distance to the bubbles. Based on the 3D dust distribution in the Galactic plane, we found three isolated, distant (500–800 pc) clouds at intermediate Galactic latitudes. Their projected morphologies perfectly match the X-ray shadows on the defining features of the north eROSITA bubble, i.e., the North Polar Spur (NPS) and the Lotus Petal Cloud (LPC), indicating that both the NPS and LPC are distant, with a distance lower limit of nearly 1 kpc. In the X-ray-dark region between the NPS and LPC, we found a few polarized radio arcs and attributed them to the bubble’s shock front. These arcs match up perfectly with the outer border of the NPS and LPC and provide a way to define the bubble’s border. The border defined in this way can be well described by the line-of-sight tangent of a 3D skewed cup model rooted in the GC. We conclude that, instead of being two independent, distant features, the NPS and LPC compose a single, giant bubble, which therefore is most plausibly a 10 kpc scale bubble rooted at the GC.

Wang, Liang, Huang et al. evaluate associations between mitochondrial DNA copy number (mtDNA-CN) and HbA1c and weight loss in patients with type 2 diabetes treated with metformin or acarbose, as part of the MARCH study. They find that patients with higher mtDNA-CN lost more weight on metformin, but did not see the same with acarbose.

Abstract. Background:. Data on the glycemic profile of pregnant women with gestational diabetes mellitus (GDM) during the perinatal period are sparse. This study described the intrapartum and early postpartum glucose profiles among pregnant women with GDM, and analyzed factors potentially affecting glycemic parameters during the period. Methods:. This was a prospective observational study conducted from March 2020 to November 2021. Pregnant women with GDM receiving lifestyle interventions alone during pregnancy and matched women with non-diabetic pregnancies (NDPs) were enrolled from among patients admitted to the obstetrics department for childbirth. Glucose monitoring was performed via a flash glucose monitoring (FGM) system on admission, and glucose readings during labor and early postpartum were analyzed. The clinical characteristics and FGM-based parameters of participants in the two groups were compared. Results:. A total of 124 participants (mean age: 29.5 ± 3.5 years, 92 [74.2%] primipara) were included in the final analysis. A total of 17,571 glucose readings were retrieved. There were no significant differences in clinical characteristics between the GDM (n = 60) and NDP (n = 64) groups. The average glucose level was 92.2 mg/dL, and the level was higher in the GDM group (95.5 ± 12.1 mg/dL vs. 89.1 ± 13.4 mg/dL, P = 0.008) during the intrapartum and early postpartum periods. The data were split into the intrapartum period (from the start of labor to delivery of the placenta) and the early postpartum period (within 24 h after placental delivery) for analysis. During intrapartum, women with GDM exhibited glycemic profiles and fluctuations similar to those in the NDP group. However, women with GDM had higher postpartum glucose levels (97.7 ± 13.4 mg/dL vs. 90.8 ± 15.3 mg/dL, P = 0.009), a longer time spent >140 mg/dL (8.7 ± 9.3% vs. 5.9 ± 10.3%, P = 0.011), and greater glycemic fluctuations than those with NDP. Postpartum hyperglycemia in GDM might be associated with high parity and postprandial glucose abnormalities in GDM screening tests. Conclusion:. Compared to those with normoglycemia, pregnant women with GDM receiving lifestyle interventions alone had similar intrapartum glucose profiles but higher early postpartum glucose levels and greater glucose variability, providing evidence for modification of the current perinatal glucose monitoring strategy for GDM. Trial Registration:. ChiCTR.org.cn, ChiCTR2000030972

Abstract Aims/Introduction Peer support for diabetes has become convenient and interactive after the emergence of mobile health (mHealth). We aimed to evaluate the association between engagement in peer support through the mHealth app and glycemic control in type 1 diabetes patients. Materials and Methods This retrospective study included adults with type 1 diabetes who had joined the mobile community “TangTangQuan” since May 2018 for at least 1 year. “Like”, “comment” and “share” were the major interaction indicators of the mobile community and were used to assess engagement in peer support. The patients were divided into four engagement groups by quartile. The primary outcome was the change in glycosylated hemoglobin (HbA1c), mean fasting blood glucose (FBG) and postprandial blood glucose (PBG) from baseline to the 12th month. Other outcomes included the change of self‐monitoring of blood glucose frequency, hypoglycemia frequency and the proportion of reaching optimal glycemic control. Results Among the 693 individuals, the HbA1c, mean FBG and PBG improved in the 12th month. Multiple regression analysis showed that higher engagement in peer support was associated with a greater reduction of HbA1c (β = −0.45, P

Checkpoint inhibitors are designed to rejuvenate depleted or suppressed T cells in the tumor microenvironment, relying on the immune system to control and kill tumors. However, accumulating evidence indicates that tumor-infiltrating neutrophils impede the proliferation and activation of T cells and determine the resistance to checkpoint blockade and chemotherapy. In this study, sialic acid ligand-modified colchicine derivative phospholipid complexes specifically targeted tumor-associated neutrophils in the peripheral blood, blocked neutrophil accumulation in tumors, and attenuated the inhibitory effect of infiltrating neutrophils on T cells. Neutrophil blocking therapy enhanced the immunotherapy effect of the PD-L1 antibody in S180 advanced tumors and 4T1 breast cancer. Our study found that PD-L1 antibody monotherapy increased the tumor infiltration of immunosuppressive neutrophils. Combination therapy with neutrophil blocking can greatly reduce tumor-infiltrating neutrophils and increase the proliferation of cytotoxic CD8+ T lymphocytes in the tumor. The combination therapy significantly improved the survival rate of mice with advanced S180 tumors and increased the sensitivity of immune checkpoint inhibitors to 4T1 cold tumors.

BackgroundUnderstanding the compliance of infected individuals and the psychological process underlying compliance during pandemics is important for preventing and controlling the spread of pathogens. Our study investigated whether fundamental social motives mediate the relationship between having infectious disease and compliance.MethodsAn online survey was conducted in March 2020, during the severe phase of the COVID-19 outbreak in China to collect data from 15,758 participants. The survey comprised self-report questionnaires with items pertaining to current symptoms (COVID-19 symptoms, other symptoms or no symptoms), the Fundamental Social Motive Inventory, and measures of compliance. Correlation analysis, linear regression analysis, and structural equation model were used for data analysis.ResultsThe participants with COVID-19 symptoms had lower levels of compliance than those without symptoms, and their lower compliance was caused by a decrease in disease avoidance (indirect effect = −0.058, 95% CI = [−0.061, −0.056]) and familial motives (indirect effect = −0.113, 95% CI = [−0.116, −0.062]). Whereas exclusion concern (indirect effect = 0.014, 95% CI = [0.011, 0.017]) suppressed the effects of COVID-19 symptoms on compliance, the effect disappeared in the multiple mediation model, while those of disease avoidance and familial motives remained.ConclusionOur findings emphasize the critical role of disease avoidance and familial motives in promoting compliance with public health norms during pandemics and suggest that enhancing these motives may serve as an effective intervention strategy to mitigate noncompliance among potentially infected individuals.

Abstract Background We aimed to report pregnancy outcomes of women with type 1 diabetes (T1D) in China, on which data were sparse. Methods This is a nationwide retrospective study conducted in 11 general medical centers in 8 cities across China. We investigated the clinical data of all women who attended these centers with a singleton pregnancy and whose pregnancy ended between 1 January 2004 and 31 December 2014. Pregnancies of women with pregestational T1D were ascertained and compared with those of women without T1D. Results From over 300 000 pregnancies over the 11‐year study period, we identified 265 singleton pregnancies of women with T1D. One maternal death was documented among 265 (0.37%) women with T1D and 83 among 318 486 (0.03%) women without T1D. Women with T1D suffered from higher rates of pregnancy loss (13.21% vs 2.92%, crude risk ratio [cRR] 5.08 [95% CI, 3.56‐7.26]) and preeclampsia (17.74% vs 4.20%, cRR 4.94 [95% CI, 3.60‐6.77]) compared with those without T1D. Infants of these women with T1D had elevated rates of neonatal death (5.65% vs 0.16%, cRR 37.36 [95% CI, 21.21‐65.82]) and congenital malformation(s) (8.26% vs 3.53%, cRR 2.46 [95% CI, 1.54‐3.93]) compared with those of women without T1D. No significant improvement in pregnancy outcomes in women with T1D was observed over the period 2004 to 2014. Conclusions Pregnancy outcomes were persistently poor in women with T1D during 2004 to 2014 in China. Pregnancy care needs to be improved to reduce adverse pregnancy outcomes among Chinese women with T1D.

Background Both type 1 diabetes mellitus (T1DM) and metabolic syndrome (MetS) are associated with an elevated risk of morbidity and mortality yet with increasing heterogeneity. This study primarily aimed to evaluate the prevalence of MetS among adult patients with T1DM in China and investigate its associated risk factors, and relationship with microvascular complications. Methods We included adult patients who had been enrolled in the Guangdong T1DM Translational Medicine Study conducted from June 2010 to June 2015. MetS was defined according to the updated National Cholesterol Education Program criterion. Logistic regression models were used to estimate the odds ratio (OR) for the association between MetS and the risk of diabetic kidney disease (DKD) and diabetic retinopathy (DR). Results Among the 569 eligible patients enrolled, the prevalence of MetS was 15.1%. While female gender, longer diabetes duration, higher body mass index, and glycosylated hemoglobin A1c (HbA1c) were risk factors associated with MetS (OR, 2.86, 1.04, 1.14, and 1.23, respectively), received nutrition therapy education was a protective factor (OR, 0.46). After adjustment for gender, age, diabetes duration, HbA1c, socioeconomic and lifestyle variables, MetS status was associated with an increased risk of DKD and DR (OR, 2.14 and 3.72, respectively; both P

Background: Myasthenia gravis (MG) is an autoimmune disease characterized by muscle weakness and fatigability. The fluctuating nature of the disease course impedes the clinical management. Objective: The purpose of the study was to establish and validate a machine learning (ML)–based model for predicting the short-term clinical outcome in MG patients with different antibody types. Methods: We studied 890 MG patients who had regular follow-ups at 11 tertiary centers in China from 1 January 2015 to 31 July 2021 (653 patients for derivation and 237 for validation). The short-term outcome was the modified post-intervention status (PIS) at a 6-month visit. A two-step variable screening was used to determine the factors for model construction and 14 ML algorithms were used for model optimisation. Results: The derivation cohort included 653 patients from Huashan hospital [age 44.24 (17.22) years, female 57.6%, generalized MG 73.5%], and the validation cohort included 237 patients from 10 independent centers [age 44.24 (17.22) years, female 55.0%, generalized MG 81.2%]. The ML model identified patients who were improved with an area under the receiver operating characteristic curve (AUC) of 0.91 [0.89–0.93], ‘Unchanged’ 0.89 [0.87–0.91], and ‘Worse’ 0.89 [0.85–0.92] in the derivation cohort, whereas identified patients who were improved with an AUC of 0.84 [0.79–0.89], ‘Unchanged’ 0.74 [0.67–0.82], and ‘Worse’ 0.79 [0.70–0.88] in the validation cohort. Both datasets presented a good calibration ability by fitting the expectation slopes. The model is finally explained by 25 simple predictors and transferred to a feasible web tool for an initial assessment. Conclusion: The explainable, ML-based predictive model can aid in forecasting the short-term outcome for MG with good accuracy in clinical practice.

Diabetic retinopathy is one of the most common complications of diabetes mellitus and the leading cause of low vision and blindness worldwide. Mounting evidence demonstrates that inflammation is a key mechanism driving diabetes-associated retinal disturbance, yet the pathophysiological process and molecular mechanisms of inflammation underlying diabetic retinopathy are not fully understood. Cytokines, chemokines, and adhesion molecules interact with each other to form a complex molecular network that propagates the inflammatory and pathological cascade of diabetic retinopathy. Therefore, it is important to understand and elucidate inflammation-related mechanisms behind diabetic retinopathy progression. Here, we review the current understanding of the pathology and pathogenesis of inflammation in diabetic retinopathy. In addition, we also summarize the relevant clinical trials to further suggest inflammation-targeted therapeutics for prevention and management of diabetic retinopathy.

BackgroundThe profile of gut microbiota, serum metabolites, and lipids of type 1 diabetes (T1D) patients with different human leukocyte antigen (HLA) genotypes remains unknown. We aimed to explore gut microbiota, serum metabolites, and lipids signatures in individuals with T1D typed by HLA genotypes.MethodsWe did a cross-sectional study that included 73 T1D adult patients. Patients were categorized into two groups according to the HLA haplotypes they carried: those with any two of three susceptibility haplotypes (DR3, DR4, DR9) and without any of the protective haplotypes (DR8, DR11, DR12, DR15, DR16) were defined as high-risk HLA genotypes group (HR, n=30); those with just one or without susceptibility haplotypes as the non-high-risk HLA genotypes group (NHR, n=43). We characterized the gut microbiome profile with 16S rRNA gene amplicon sequencing and analyzed serum metabolites with liquid chromatography-mass spectrometry.ResultsStudy individuals were 32.5 (8.18) years old, and 60.3% were female. Compared to NHR, the gut microbiota of HR patients were characterized by elevated abundances of Prevotella copri and lowered abundances of Parabacteroides distasonis. Differential serum metabolites (hypoxanthine, inosine, and guanine) which increased in HR were involved in purine metabolism. Different lipids, phosphatidylcholines and phosphatidylethanolamines, decreased in HR group. Notably, Parabacteroides distasonis was negatively associated (p ≤ 0.01) with hypoxanthine involved in purine metabolic pathways.ConclusionsThe present findings enabled a better understanding of the changes in gut microbiome and serum metabolome in T1D patients with HLA risk genotypes. Alterations of the gut microbiota and serum metabolites may provide some information for distinguishing T1D patients with different HLA risk genotypes.

BackgroundTo investigate the effect of school life by comparing the glycemic control between holidays and schooldays in children and adolescents with type 1 diabetes (T1D).MethodsThis observational study enrolled school-aged students with T1D (aged 6–19) from September 2019 to July 2021. Continuous glucose monitoring (CGM) records were processed and divided into holidays and schooldays. Other information was collected via questionnaires. We compared the results using paired T-test, Wilcoxon paired test and logistic regression analysis.Results78 paticipants were included (40 boys, mean age 9.95 years). A total of 142,945 h of CGM data were analyzed. Overall, TIR (3.9–7.8 mmol/L) during holidays was better than schooldays [56.97 (SD 15.03) vs. 55.87 (15.06), %, p = 0.039]. On nocturnal (0–6 am) glycemic fluctuation, TIR was longer in children aged 6–10 [60.54 (17.40) vs. 56.98 (SD 16.32), %, p = 0.012] during holiday and TAR (7.8 mmol/L) was shorter [31.54 (17.54) vs. 35.54 (16.95), %, p = 0.013], compared with schooldays. In adolescents aged 10–19 years, TAR was also significantly shorter during holidays. Stratified analysis showed that girls, patients with longer duration, and insulin pump users had more pronounced worsening of nighttime glycemia on schooldays. Logistic regression analysis showed that girls had higher risk of worse nocturnal glycemic control [3.26, 95% CI: (1.17, 9.72), p = 0.027] and nocturnal hyperglycemia [OR = 2.95, 95% CI: (1.08, 8.56), p = 0.039], compared to boys.ConclusionsChildren and adolescents with T1D were found to have worse glycemic control in nighttime during schooldays.

Abstract Aims/Introduction The coronavirus disease 2019 (COVID‐19) pandemic urged authorities to impose rigorous quarantines and brought considerable changes to people’s lifestyles. The impact of these changes on glycemic control has remained unclear, especially the long‐term effect. We aimed to investigate the impact of COVID‐19 lockdown on glycemic control in children and adolescents with type 1 diabetes. Materials and Methods This observational study enrolled children with type 1 diabetes using continuous glucose monitoring. Continuous glucose monitoring data were extracted from the cloud‐based platform before, during and after lockdown. Demographics and lifestyle change‐related information were collected from the database or questionnaires. We compared these data before, during and after lockdown. Results A total of 43 children with type 1 diabetes were recruited (20 girls; mean age 7.45 years; median diabetes duration 1.05 years). We collected 41,784 h of continuous glucose monitoring data. Although time in range (3.9–10.0 mmol/L) was similar before, during and after lockdown, the median time below range

Objective Data are sparse on healthcare needs related to pregnancy among Chinese women with type 1 diabetes (T1D) or the gap between the needs and healthcare provision in China. We aimed to identify their needs and the gaps in pregnancy care provision.Design This is a qualitative, face-to-face, one-to-one in-depth interview study. We recruited our participants using a purposive sampling strategy. Semistructural outlines were used to guide the interviews. The interviews were digitally recorded, transcribed and analysed using a thematic framework method with NVivo V.10.0.Setting Guangdong Province in China.Participants This study involved three key stakeholders of pregnancy care for women with T1D: 29 women with T1D of childbearing age (aged 18–50 years), 16 family members (husbands, parents and parents-in-law of women with T1D) and 35 relevant healthcare providers (HCPs).Results We found that women with T1D and the family members had a more pessimistic attitude towards pregnancy outcomes, which was different from the more positive view of HCPs. However, all three stakeholders shared the following perspectives regarding pregnancy-related care for women with T1D: (1) lack of knowledge and access to education, (2) lack of multidisciplinary cooperation, (3) education should be started earlier in adulthood, (3) positive role of peer support, and (4) hope for future training of HCPs for relevant knowledge and skills specified for T1D and pregnancy with T1D.Conclusions An immense gap was identified between the needs of women with T1D regarding pregnancy-related care and current care provision in China. These findings suggest that education be provided to patients and HCPs, and the role of professional and multidisciplinary support should be enhanced to optimise pregnancy care for women with T1D in China.

ObjectiveType 1 diabetes (T1D) progression is affected by circulating glutamic acid decarboxylase antibody (GADA) that persist for many years. This study aimed at investigating whether and how the gut microbiome and its correlated metabolites change in T1D with the presence of GADA.MethodsWe used a radiobinding assay to measure GADA titers and identify the 49 T1D patients with GADA+ and 52 T1D patients with GADA-. The fresh feces and serum were analyzed using 16S rRNA gene sequencing and GC/MS. Then gut microbiome and serum metabolites were compared between the GADA+ patients and the GADA- patients. The association between gut microbial community and metabolites was assessed using the Spearman’s rank correlation.ResultsThe gut microbiome in diversity, composition, and function differed between these two groups. The abundance of genus Alistipes, Ruminococcus significantly increased in patients with GADA+ compared to that observed in the samples of GADA-. There were 54 significantly altered serum metabolites associated with tryptophan metabolism, phenylalanine, and tyrosine biosynthesis in individuals with GADA+ compared with those of GADA-For the serum metabolites, compared with those of GADA-, there were 54 significantly different metabolites with tryptophan metabolism, phenylalanine, and tyrosine and tryptophan biosynthesis decreased in individuals with GADA+. The abundance of Alistipes was positively correlated with altered metabolites involved in tryptophan metabolism.ConclusionWe demonstrate that T1D patients with GADA+ are characterised by aberrant profiles of gut microbiota and serum metabolites. The abundance of Alistipes disturbances may participate in the development of T1D patients with GADA by modulating the host’s tryptophan metabolism. These findings extend our insights into the association between the gut microbiota and tryptophan metabolism and GADA and might be targeted for preventing the development of T1D.

Abstract Coronavirus disease 2019 (COVID-19) is regarded as an endothelial disease (endothelialitis) with its patho-mechanism being incompletely understood. Emerging evidence has demonstrated that endothelial dysfunction precipitates COVID-19 and its accompanying multi-organ injuries. Thus, pharmacotherapies targeting endothelial dysfunction have potential to ameliorate COVID-19 and its cardiovascular complications. The objective of the present study is to evaluate whether kruppel-like factor 2 (KLF2), a master regulator of vascular homeostasis, represents a therapeutic target for COVID-19-induced endothelial dysfunction. Here, we demonstrate that the expression of KLF2 was reduced and monocyte adhesion was increased in endothelial cells treated with COVID-19 patient serum due to elevated levels of pro-adhesive molecules, ICAM1 and VCAM1. IL-1β and TNF-α, two cytokines elevated in cytokine release syndrome in COVID-19 patients, decreased KLF2 gene expression. Pharmacologic (atorvastatin and tannic acid) and genetic (adenoviral overexpression) approaches to augment KLF2 levels attenuated COVID-19-serum-induced increase in endothelial inflammation and monocyte adhesion. Next-generation RNA-sequencing data showed that atorvastatin treatment leads to a cardiovascular protective transcriptome associated with improved endothelial function (vasodilation, anti-inflammation, antioxidant status, anti-thrombosis/-coagulation, anti-fibrosis, and reduced angiogenesis). Finally, knockdown of KLF2 partially reversed the ameliorative effect of atorvastatin on COVID-19-serum-induced endothelial inflammation and monocyte adhesion. Collectively, the present study implicates loss of KLF2 as an important molecular event in the development of COVID-19-induced vascular disease and suggests that efforts to augment KLF2 levels may be therapeutically beneficial.

Background and objectivesMyasthenia gravis (MG) is a T cell-driven, autoantibody-mediated disorder affecting transmission in neuromuscular junctions. The associations between the peripheral T cells and MG have been extensively studied. However, they are mainly of observational nature, thus limiting our understanding of the effect of inflammatory biomarkers on MG risk. With large data sets now available, we used Mendelian randomization (MR) analysis to investigate whether the biomarkers on T cells are causally associated with MG and further validate the relationships.MethodsWe performed a two-sample MR analysis using genetic data from one genome-wide association study (GWAS) for 210 extensive T-cell traits in 3,757 general population individuals and the largest GWAS for MG currently available (1,873 patients versus 36,370 age/gender-matched controls) from US and Italy. Then the biomarkers of interest were validated separately in two GWASs for MG in FIN biobank (232 patients versus 217,056 controls) and UK biobank (152 patients versus 386,631 controls).ResultsIn the first analysis, three T-cell traits were identified to be causally protective for MG risk: 1) CD8 on terminally differentiated CD8+ T cells (OR [95% CI] = 0.71 [0.59, 0.86], P = 5.62e-04, adjusted P =2.81e-02); 2) CD4+ regulatory T proportion in T cells (OR [95% CI] = 0.44 [0.26, 0.72], P = 1.30e-03, adjusted P =2.81e-02); 3) HVEM expression on total T cells (OR [95% CI] = 0.67 [0.52, 0.86], P = 1.61e-03, adjusted P =2.81e-02) and other eight T-cell subtypes (e.g., naïve CD4+ T cells). In particular, HVEM is a novel immune checkpoint on T cells that has never been linked to MG before. The SNPs on the TNFRSF14 per se further support a more direct link between the HVEM and MG. The validation analysis replicated these results in both FIN and UK biobanks. Both datasets showed a concordant protective trend supporting the findings, albeit not significant.ConclusionThis study highlighted the role of HVEM on T cells as a novel molecular-modified factor for MG risk and validated the causality between T cells and MG. These findings may advance our understanding of MG’s immunopathology and facilitate the future development of predictive disease-relevant biomarkers.

Abstract Aims/Introduction Given that mutations related to maturity‐onset diabetes of the young (MODY) are rarely found in Chinese populations, we aim to characterize the mutation spectrum of MODY pedigrees. Materials and Methods Maturity‐onset diabetes of the young candidate gene‐ or exome‐targeted capture sequencing was carried out in 76 probands from unrelated families fulfilling the clinical diagnostic criteria for MODY. MAF

Abstract Objective Myasthenia gravis (MG) is an autoimmune disease caused by autoantibodies against neuromuscular junctions. Myasthenic crisis (MC) represents the most severe state of MG with high in‐hospital mortality. We aimed to identify immune signatures using in‐depth profiling in MC, and to assess the correlations between immune biomarkers with clinical severity longitudinally. Methods We studied 181 participants including 57 healthy controls, 96 patients with MG who never experienced crisis and 28 MC patients from December 2018 through June 2020. Follow‐up visits occurred prospectively from crisis to 6 months off‐mechanical ventilation. The frequencies of 20 CD4+ T subpopulations and 18 serum cytokines were associated with clinical scores using correlations and principal component analysis. Results Patients in crisis exhibited a proinflammatory CD4+T response with elevated Th1 (P = 0.026), and Th17 cells (P = 0.032); decreased T follicular helper 2 (Tfh2) cells (P

Abstract Background A pandemic is a very stressful event, especially for highly vulnerable people (e.g., older adults). The purpose of the current study was to investigate the main and interactive relationships of social support and resilience on individual mental health during the COVID-19 pandemic across three age groups: emerging adults, adults, and older adults. Methods A survey was conducted with 23,192 participants aged 18–85. Respondents completed a questionnaire, including items on the COVID-19-related support they perceived from different sources, the abbreviated version of the Connor-Davidson Resilience Scale, and the Mental Health Inventory. Results Latent profile analysis identified five profiles of social support, and the patterns of potential profiles were similar in all groups. However, category distribution in the five profiles was significantly different among the age groups. Furthermore, analysis using the BCH command showed significant differences in mental health among these profiles. Lastly, interactive analyses indicated resilience had a positive relationship with mental health, and social support served as a buffer against the negative impact of low resilience on mental health. Conclusions This study provides quantitative evidence for socioemotional selectivity theory (SST) and enables several practical implications for helping different age groups protecting mental health during pandemic.

PurposeThis study aimed to characterize the clinical features of early-stage ovarian cancer (OC) survivors with second primary malignancies (SPMs) and provided a prediction tool for individualized risk of developing SPMs.MethodsData were obtained from the Surveillance, Epidemiology and End Results (SEER) database during 1998–2013. Considering non-SPM death as a competing event, the Fine and Gray model and the corresponding nomogram were used to identify the risk factors for SPMs and predict the SPM probabilities after the initial OC diagnosis. The decision curve analysis (DCA) was performed to evaluate the clinical utility of our proposed model.ResultsA total of 14,314 qualified patients were enrolled. The diagnosis rate and the cumulative incidence of SPMs were 7.9% and 13.6% [95% confidence interval (CI) = 13.5% to 13.6%], respectively, during the median follow-up of 8.6 years. The multivariable competing risk analysis suggested that older age at initial cancer diagnosis, white race, epithelial histologic subtypes of OC (serous, endometrioid, mucinous, and Brenner tumor), number of lymph nodes examined (

Objectives The study objectives were to examine: (1) adolescents’ media viewing habits, (2) associations with media viewing and self-reported exposure to unhealthy food and beverage advertising and (3) differences in trends among younger and older adolescents in six high and upper middle-income countries.Design Repeat cross-sectional online survey.Setting Australia, Canada, Chile, Mexico, the United Kingdom (UK) and the United States of America (USA).Participants Respondents to the International Food Policy Study who provided information on all variables of interest in November–December 2019 aged 10–17 years (n=9171).Outcome measures Self-reported exposure to screen-based media (screen time by media channel), use of social media platforms and self-reported location and frequency of exposure to unhealthy food and beverage advertising.Results The average amount of time spent in front of various screens ranged from 7.6 hours to 10.2 hours across countries per week day, which may include possible viewing of multiple media channels simultaneously. Overall, Instagram was the most popular social media platform (52%–68% by country), followed by Facebook (42%–79%) and Snapchat (28%–52%). The percentage of respondents who self-reported having seen unhealthy food advertisements in the past 30 days was highest on television (43%–69%), followed by digital media (27%–60%) and gaming applications (10%–17%). Self-reported daily exposure to advertising varied between countries for sugary drinks (10%–43%) and fast food (19%–44%) and was positively associated with self-reported screen time. Self-reported exposure to screen-based media and social media platforms differed by sociodemographic characteristics and was higher among older adolescents than younger adolescents.Conclusions The important amount of time spent on screen-based media reported by adolescents and large percentage of adolescents reporting social media usage, coupled with high rates of self-reported advertising exposure, support the need for policies to restrict marketing of unhealthy food and beverages appealing to adolescents on screen-based media.

Sodium metal anodes (SMAs) suffer from extremely low reversibility (95% with conventional NaPF6 salt at a regular concentration (1.0 M). The peculiar role of FEC is firstly unraveled via its involvement into the solvation structure, where a threshold FEC concentration with a coordination number>1.2 is needed in guaranteeing high Na reversibility over the long-term. Specifically, by incorporating an average number of 1.2 FEC molecules into the primary Na+ solvation sheath, lowest unoccupied molecular orbital (LUMO) levels of such Na+-FEC solvates undergo further decrease, with spin electrons residing either on the O=CO(O) moiety of FEC or sharing between Na+ and its C=O bond, which ensures a prior FEC decomposition in passivating the Na surface against other carbonate molecules. Further, by adopting cryogenic transmission electron microscopy (cryo-TEM), we found that the Na filaments grow into substantially larger diameter from ~400 nm to >1 μm with addition of FEC upon the threshold value. A highly crystalline and much thinner (~40 nm) solid-electrolyte interphase (SEI) is consequently observed to uniformly wrap the Na surface, in contrast to the severely corroded Na as retrieved from the blank electrolyte. The potence of FEC is further demonstrated in a series of “corrosive solvents” such as ethyl acetate (EA), trimethyl phosphate (TMP), and acetonitrile (AN), enabling highly reversible SMAs in the otherwise unusable solvent systems.

BackgroundLung adenocarcinoma (LUAD) is the most common pathological type of lung cancer, with high incidence and mortality. To improve the curative effect and prolong the survival of patients, it is necessary to find new biomarkers to accurately predict the prognosis of patients and explore new strategy to treat high-risk LUAD.MethodsA comprehensive genome-wide profiling analysis was conducted using a retrospective pool of LUAD patient data from the previous datasets of Gene Expression Omnibus (GEO) including GSE18842, GSE19188, GSE40791 and GSE50081 and The Cancer Genome Atlas (TCGA). Differential gene analysis and Cox proportional hazard model were used to identify differentially expressed genes with survival significance as candidate prognostic genes. The Kaplan–Meier with log-rank test was used to assess survival difference. A risk score model was developed and validated using TCGA-LUAD and GSE50081. Additionally, The Connectivity Map (CMAP) was used to predict drugs for the treatment of LUAD. The anti-cancer effect and mechanism of its candidate drugs were studied in LUAD cell lines.ResultsWe identified a 5-gene signature (KIF20A, KLF4, KRT6A, LIFR and RGS13). Risk Score (RS) based on 5-gene signature was significantly associated with overall survival (OS). Nomogram combining RS with clinical pathology parameters could potently predict the prognosis of patients with LUAD. Moreover, gliclazide was identified as a candidate drug for the treatment of high-RS LUAD. Finally, gliclazide was shown to induce cell cycle arrest and apoptosis in LUAD cells possibly by targeting CCNB1, CCNB2, CDK1 and AURKA.ConclusionThis study identified a 5-gene signature that can predict the prognosis of patients with LUAD, and Gliclazide as a potential therapeutic drug for LUAD. It provides a new direction for the prognosis and treatment of patients with LUAD.

Spinel LiNi0.5Mn1.5O4 (LNMO) cathode material doped with Ti and La co-doping were synthesized through a solid-state method. The bi-functions of the Ti and La co-doping is realized. On the one hand, the stability of the LiNi0.5Mn1.5O4 crystal structure is enhanced and the Mn3+ interference inside the material is reduced by the Ti doping. On the other hand, the co-doped La contributes to the formation of Li0.5La0.5TiO3 (LLTO) superionic conductor incorporated in the bulk LiNi0.5Mn1.5O4 phase, thereby enhancing the Li diffusion. With the help of XRD, FTIR, SEM and STEM techniques, La and Ti in the crystallographic structure and the dispersion of the LLTO superionic conductor in the bulk LNMO spinel are discussed. At the optimized molar ratio of 20:1 between LNMO and LLTO, the composite exhibits the best electrochemical performances in terms of the reversible capacity, rate capability and cycling stability. The lithium ion diffusion coefficient in the bulk LNMO phase is tripled by the LLTO superionic conductor incorporation. Keywords: Lithium ion batteries, Spinel LiNi0.5Mn1.5O4, Li0.5La0.5TiO3, Co-doping, Superionic-conductor

State-of-health (SOH) prediction for lithium-ion batteries is a challenging and important topic in the modern industry. With the advent of cloud-connected devices, there are huge amounts of the battery degradation trend data available. How to make full use of these existing degradation data for the SOH prediction is a valuable problem deserving deep research. Aiming at this problem, a multiple Gaussian process regression (MGPR) method is proposed for the SOH prediction of lithium-ion batteries. In this work, the health indicators (HIs) are firstly extracted from the charging process curves of the batteries, and the mutual information analysis is used to select the important HIs which are strongly correlated to the SOH. These selected HIs are applied as the regression model input for describing the aging procedure of the battery effectively. Then, Gaussian process regression modeling is performed on the different batteries to bring multiple GPR models. Lastly, a weighting strategy based on the prediction uncertainty is designed to integrate the predictions from the multiple GPR models. The method validations are executed on the battery datasets from NASA, and the results show that the proposed MGPR method has higher prediction accuracy than the basic GPR method.

Aims: A novel coronavirus SARS-CoV-2 has resulted in an ongoing global pandemic of Coronavirus disease 2019 (COVID-19). However, the outcomes of recovered patients have not been well defined. Methods: This is a prospective observational follow-up study of survivors with COVID-19 from a designated tertiary center in Hefei, China. We examined chest computed tomography (CT) scanning, pulmonary function, 6-min walk distance (6MWD), and 36 item Short Form General Health Survey (SF-36). Results: Among 81 enrolled patients, 62 (77%) patients and 61 (75%) patients, respectively, completed 1-month and 3-month follow-ups. Abnormal CT findings were still present in 73% of patients at 1 month and 54% at 3 months, whereas chest CT scan scores improved progressively at 1-month (5.0 ± 5.1) and 3-month follow up (3.0 ± 4.5) compared with that during hospitalization (11 ± 6.8). Mild restrictive pulmonary impairment was detected in 11% and 10% of patients at 1-month and 3-month follow up, respectively. The 6MWD was 523 ± 77 m in male patients and 484 ± 58 m in female patients, which was significantly lower than in healthy controls (606 ± 68 m, 568 ± 78 m, p

Background: The timing of administration of agents and use of combination treatments in COVID-19 remain unclear. We assessed the effectiveness of therapeutics in cohorts in Hong Kong SAR and Anhui, China. Methods: We conducted propensity-score analysis of 4771 symptomatic patients from Hong Kong between 21st January and 6th December 2020, and 648 symptomatic patients from Anhui between 1st January and 27th February 2020. We censored all observations as at 13st December 2020. Time from hospital admission to discharge, and composite outcome of death, invasive mechanical ventilation or intensive care unit admission across 1) all therapeutic options including lopinavir-ritonavir, ribavirin, umifenovir, interferon-alpha-2b, interferon-beta-1b, corticosteroids, antibiotics, and Chinese medicines, and 2) four interferon-beta-1b combination treatment groups were investigated. Findings: Interferon-beta-1b was associated with an improved composite outcome (OR=0.55, 95%CI 0.38, 0.80) and earlier discharge (−8.8 days, 95%CI −9.7, −7.9) compared to those not administered interferon-beta-1b. Oral ribavirin initiated within 7 days from onset was associated with lower risk of the composite outcome in Hong Kong (OR=0.51, 95%CI 0.29, 0.90). Lopinavir-ritonavir, intravenous ribavirin, umifenovir, corticosteroids, interferon-alpha-2b, antibiotics or Chinese medicines failed to show consistent clinical benefit. Interferon-beta-1b co-administered with ribavirin was associated with improved composite outcome (OR=0.50, 95%CI 0.32, 0.78) and earlier discharge (−2.35 days, 95%CI −3.65, −1.06) compared to interferon-beta-1b monotherapy. Interpretation: Our findings support the early administration of interferon-beta-1b alone or in combination with oral ribavirin for COVID-19 patients. Funding: Hong Kong Health and Medical Research Fund; Hong Kong Innovation and Technology Commission; Chinese Fundamental Research Funds for the Central Universities.

Background: Previous studies show that the use of do-it-yourself artificial pancreas system (DIYAPS) may be associated with better glycemic control characterized by improved estimated hemoglobin A1c (eHbA1c) and time in range among adults with type 1 diabetes (T1D). However, few studies have demonstrated the changes in laboratory-measured HbA1c, which is a more accepted index for glycemic control, after using a DIYAPS. Methods: This is a retrospective before-after study approaching patients who reported self-use of AndroidAPS. The main inclusion criteria included: T1D; aged ⩾18 years; having complete record of ⩾3 months of continuous AndroidAPS use; with laboratory-measured HbA1c and quality of life scale data before and after 3 months of AndroidAPS use; and not pregnant. The primary outcome was the change in HbA1c between baseline and 3 months after initiation of AndroidAPS use. Results: Overall, 15 patients (10 females) were included; the median age was 32.2 years (range: 19.2–69.4), median diabetes duration was 9.7 years (range: 1.8–23.7) and median baseline HbA1c was 7.3% (range: 6.4–10.1). The 3 months of AndroidAPS use was associated with substantial reductions in HbA1c [6.79% (SD: 1.29) versus 7.63% (SD: 1.06), p = 0.002] and glycemic variability when compared with sensor-augmented pump therapy. A lower level of fear of hypoglycemia [22.13 points (SD: 6.87) versus 26.27 points (SD: 5.82), p = 0.010] was also observed after using AndroidAPS. Conclusions: The 3 months of AndroidAPS use was associated with significant improvements in glucose management and quality of life among adults with T1D.

Aims: Our aim was to investigate the impact of glycemic variability (GV) on the relationship between glucose management indicator (GMI) and laboratory glycated hemoglobin A1c (HbA1c). Methods: Adult patients with type 1 diabetes mellitus (T1D) were enrolled from five hospitals in China. All subjects wore the iPro ™ 2 system for 14 days before HbA1c was measured at baseline, 3 months and 6 months. Data derived from iPro ™ 2 sensor was used to calculate GMI and GV parameters [standard deviation (SD), glucose coefficient of variation (CV), and mean amplitude of glycemic excursions (MAGE)]. Differences between GMI and laboratory HbA1c were assessed by the absolute value of the hemoglobin glycation index (HGI). Results: A total of 91 sensor data and corresponding laboratory HbA1c, as well as demographic and clinical characteristics were analyzed. GMI and HbA1c were 7.20 ± 0.67% and 7.52 ± 0.73%, respectively. The percentage of subjects with absolute HGI 0 to lower than 0.1% was 21%. GMI was significantly associated with laboratory HbA1c after basic adjustment (standardized β = 0.83, p

Background. Fulminant type l diabetes mellitus (FT1DM) is a subtype of type 1 diabetes mellitus (T1DM) with abrupt onset, but data on its progression was limited. This study was aimed at exploring the clinical features through one-year follow-up. Methods and Materials. Patients with T1DM finishing at least one-year follow-up from June 2011 to July 2018 were enrolled from Guangdong Type 1 Diabetes Translational Medicine Study. Patients who fulfilled the respective criteria were categorized as an FT1DM group and a typical T1DM group (TT1DM). The 1 : 4 propensity score matching based on onset age, duration, and gender was performed between the FT1DM and TT1DM groups. Characteristics at the onset and after one-year follow-up were compared between the two groups. Results. A total of 53 patients with FT1DM and 212 matched patients with TT1DM were included. At the onset, there was a shorter duration of symptomatic period before diagnosis observed in the FT1DM group than in the TT1DM group (2 [1, 7] vs. 30 [10, 60] days, P

Background. To comprehensively assess the effects of metformin added to insulin on metabolic control, insulin sensitivity, and cardiovascular autonomic function in adolescents with type 1 diabetes. Materials and Methods. This was an exploratory, crossover, randomized trial conducted in adolescents with type 1 diabetes aged 12-18 years old. Participants were randomly received metformin (≤1000 mg/d) added to insulin for 24 weeks followed by insulin monotherapy for a subsequent 24 weeks or vice versa. Blood pressure, body mass index, insulin dose, estimated insulin sensitivity, glycated hemoglobin A1c (HbA1c), and lipid profiles were measured, with a 72-hour continuous glucose monitoring and 24-hour Holter monitoring performed at baseline, 24, and 50 weeks for the assessments of glucose variability and heart rate variability. Results. Seventeen patients with mean±SD age 14.4±2.3 years, body mass index 18.17±1.81 kg/m2, median (IQR) diabetes duration 4.50 (3.58, 6.92) years, and HbA1c 9.0% (8.5%, 9.4%) were enrolled. The between-group difference in HbA1c of 0.28% (95% CI -0.39 to 0.95%) was not significant (P=0.40). Changes in body mass index, insulin dose, blood pressure, lipid profiles, and estimated insulin sensitivity were similar for metformin add-on vs. insulin monotherapy. Glucose variability also did not differ. Compared with insulin monotherapy, metformin add-on significantly increased multiple heart rate variability parameters. Conclusions. Metformin added to insulin did not improve metabolic control or glucose variability in lean/normal-weight adolescents with type 1 diabetes. However, metformin added to insulin significantly increased heart rate variability, suggesting that metformin might improve cardiovascular autonomic function in this population.

Abstract Germanium is considered as a potential anode material for sodium-ion batteries due to its fascinating theoretical specific capacity. However, its poor cyclability resulted from the sluggish kinetics and large volume change during repeated charge/discharge poses major threats for its further development. One solution is using its ternary compound as an alternative to improve the cycling stability. Here, high-purity CuGeO3 nanowires were prepared via a facile hydrothermal method, and their sodium storage performances were firstly explored. The as-obtained CuGeO3 delivered an initial charge capacity of 306.7 mAh g−1 along with favorable cycling performance, displaying great promise as a potential anode material for sodium ion batteries.

Abstract Background Unlike influenza viruses, little is known about the prevalence and seasonality of other respiratory viruses because laboratory surveillance for non-influenza respiratory viruses is not well developed or supported in China and other resource-limited countries. We studied the interference between seasonal epidemics of influenza viruses and five other common viruses that cause respiratory illnesses in Hong Kong from 2014 to 2017. Methods The weekly laboratory-confirmed positive rates of each virus were analyzed from 2014 to 2017 in Hong Kong to describe the epidemiological trends and interference between influenza viruses, respiratory syncytial virus (RSV), parainfluenza virus (PIV), adenovirus, enterovirus and rhinovirus. A sinusoidal model was established to estimate the peak timing of each virus by phase angle parameters. Results Seasonal features of the influenza viruses, PIV, enterovirus and adenovirus were obvious, whereas annual peaks of RSV and rhinovirus were not observed. The incidence of the influenza viruses usually peaked in February and July, and the summer peaks in July were generally caused by the H3 subtype of influenza A alone. When influenza viruses were active, other viruses tended to have a low level of activity. The peaks of the influenza viruses were not synchronized. An epidemic of rhinovirus tended to shift the subsequent epidemics of the other viruses. Conclusion The evidence from recent surveillance data in Hong Kong suggests that viral interference during the epidemics of influenza viruses and other common respiratory viruses might affect the timing and duration of subsequent epidemics of a certain or several viruses.

Abstract Background According to the current official guidelines, at least 12 lymph nodes (LNs) are qualified as an adequate sampling for colon cancer patients. However, patients evaluated with less nodes were still common in the United States, and the prevalence of positive nodal disease may be under-estimated because of the false-negative assessment. In this study, we present a statistical model that allows preoperative determination of the minimum number of lymph nodes needed to confirm a node-negative disease with certain confidence. Methods Adenocarcinoma colon cancer patients with stage T1-T3, diagnosed between 2004 and 2013, who did not receive neoadjuvant therapies and had at least one lymph node pathologically examined, were extracted from the Surveillance, Epidemiology and End Results (SEER) database. A beta binomial distribution was used to estimate the probability of an occult nodal disease is truly node-negative as a function of total number of LNs examined and T stage. Results A total of 125,306 patients met study criteria; and 47,788 of those were node-positive. The probability of falsely identifying a patient as node-negative decreased with an increasing number of nodes examined for each stage, and was estimated to be 72% for T1 and T2 patients with a single node examined and 57% for T3 patients with a single node examined. To confirm an occult nodal disease with 90% confidence, 3, 8, and 24 nodes need to be examined for patients from stage T1, T2, and T3, respectively. Conclusions The false-negative rate of diagnosed node negative, together with the minimum number of examined nodes for adequate staging, depend preoperatively on the clinical T stage. Predictive tools can recommend a threshold on the minimum number of examined nodes regarding to the favored level of confidence for each T stage.

Gastric cancer (GC), with high heterogeneity, can be mainly classified into intestinal type and diffuse type according to the Lauren classification system. Although a number of differences were reported between these two types, no study on the Lauren subtype-specific multi-gene signature for evaluation of GC prognosis has been conducted, and the molecular mechanism underlying its poor prognosis has still remained elusive. Therefore, this study aimed to explore subtype-specific multi-gene signature for prognostic prediction in different subtypes of Lauren classification. With combination of the least absolute shrinkage and selection operator (LASSO) algorithm and the Akaike information criterion (AIC), the 3-gene subtype-specific prognostic signature was successfully established in diffuse type GC using GSE62254 dataset. Following the calculation of risk score (RS) based on 3-gene signature, the nomogram models were established to predict 1-, 3-, and 5-year overall survival in diffuse type GC. Moreover, the prognostic predictive nomogram model of diffuse type GC was also proved to be effective for validation of GSE1549 dataset and by a Gene Expression Omnibus (GEO)-based meta-analysis. In the analysis of the correlation between RS and clinical-pathological characteristics, RS and two genes of the 3-gene signature (EMCN and COL4A5) were found to be positively correlated with peritoneal metastasis. Furthermore, EMCN and COL4A5, rather than CCL11, were proved to be able to enhance the adhesion ability of MKN45 and NUGC4 cells to peritoneal mesothelial cell line HMR-SV5. Eventually, it was proved that COL4A5 promoted peritoneal metastasis by activating Wnt signaling pathway, whereas the upregulation of integrin family genes mediated by FAK-AKT/ERK/STAT3 signaling pathway activation is involved in peritoneal metastasis promotion function of EMCN. Taken together, our study identified the subtype-specific 3-gene signature in diffuse type GC, which could effectively predict the patients' OS and might explain the molecular mechanisms in presence of its poor prognosis.

Influenza is active during the winter and spring in the city of Beijing, which has a typical temperate climate with four clear distinct seasons. The clinical and laboratory surveillance data for influenza have been used to construct critical indicators for influenza activities in the community, and previous studies have reported varying degrees of association between laboratory-confirmed influenza specimens and outpatient consultation rates of influenza-like illness in subtropical cities. However, few studies have reported on this issue for cities in temperate regions, especially in developing countries. Furthermore, the mechanism behind age-specific seasonal epidemics remains unresolved, although it has been widely discussed. We utilized a wavelet analysis method to monitor the coherence of weekly percentage of laboratory-confirmed influenza specimens with the weekly outpatient consultation rates of influenza-like illness in Beijing, China. We first examined the seasonal pattern of laboratory-confirmed cases of influenza A (subtyped into seasonal A(H1N1) and A(H3N2) and pandemic virus A(H1N1) pdm09) and influenza B separately within the period from 2008-2015; then, we detected the coherence of clinical and laboratory surveillance data in this district, specially examining weekly time series of age-specific epidemics of influenza-like illnesses in the whole study period for three age categories (age 0-5, 5-15 and 25-60). We found that influenza A and B were both active in winter but were not always seasonally synchronous in Beijing. Synchronization between age ranges was found in most epidemic peaks from 2008-2015. Our findings suggested that peaks of influenza-like illness in individuals aged 0-5 and 5-15 years consistently appeared ahead of those of adults, implying the possibility that schoolchildren may lead epidemic fluctuations.