Clinical Characteristics and Outcomes of Type 2 Diabetes Patients Infected with COVID-19: A Retrospective Study

Diabetes and its related metabolic disorders have been reported as the leading comorbidities in patients with coronavirus disease 2019 (COVID-19). This clinical study aims to investigate the clinical features, radiographic and laboratory tests, complications, treatments, and clinical outcomes in COVID-19 patients with or without diabetes. This retrospective study included 208 hospitalized patients (≥ 45 years old) with laboratory-confirmed COVID-19 during the period between 12 January and 25 March 2020. Information from the medical record, including clinical features, radiographic and laboratory tests, complications, treatments, and clinical outcomes, were extracted for the analysis. 96 (46.2%) patients had comorbidity with type 2 diabetes. In COVID-19 patients with type 2 diabetes, the coexistence of hypertension (58.3% vs 31.2%), coronary heart disease (17.1% vs 8.0%), and chronic kidney diseases (6.2% vs 0%) was significantly higher than in COVID-19 patients without type 2 diabetes. The frequency and degree of abnormalities in computed tomography (CT) chest scans in COVID-19 patients with type 2 diabetes were markedly increased, including ground-glass opacity (85.6% vs 64.9%, P < 0.001) and bilateral patchy shadowing (76.7% vs 37.8%, P < 0.001). In addition, the levels of blood glucose (7.23 mmol·L⁻¹ (interquartile range (IQR): 5.80–9.29) vs 5.46 mmol·L⁻¹ (IQR: 5.00–6.46)), blood low-density lipoprotein cholesterol (LDL-C) (2.21 mmol·L⁻¹ (IQR: 1.67–2.76) vs 1.75 mmol·L⁻¹ (IQR: 1.27–2.01)), and systolic pressure (130 mmHg (IQR: 120–142) vs 122 mmHg (IQR: 110–137)) (1 mmHg = 133.3 Pa) in COVID-19 patients with diabetes were significantly higher than in patients without diabetes (P < 0.001). The coexistence of type 2 diabetes and other metabolic disorders is common in patients with COVID-19, which may potentiate the morbidity and aggravate COVID-19 progression. Optimal management of the metabolic hemostasis of glucose and lipids is the key to ensuring better clinical outcomes. Increased clinical vigilance is warranted for COVID-19 patients with diabetes and other metabolic diseases that are fundamental and chronic conditions.     

基于ASP．NET的糖尿病网站设计与实现

网站根据湘雅二医院内分泌研究所中南大学糖尿痛中心的需求．结合当代计算机数据库管理技术和ASP．NET编程技术设计开发糖尿病网站系统。该网站采用B／S架构模式．SQLServer2005作为数据库管理系统,对网站进行设计和实现。通过网站树立了糖尿病中心形象,提高了糖尿病中心的知名度,人们可以不受地域和时间限制了解糖尿病中心的医疗信息,从中获得服务,网站也加强了糖尿病中心对科研资料的有效利用和资源共享。     

Cloud based intelligent system for delivering health care as a service

The promising potential of cloud computing and its convergence with technologies such as mobile computing, wireless networks, sensor technologies allows for creation and delivery of newer type of cloud services. In this paper, we advocate the use of cloud computing for the creation and management of cloud based health care services. As a representative case study, we design a Cloud Based Intelligent Health Care Service (CBIHCS) that performs real time monitoring of user health data for diagnosis of chronic illness such as diabetes. Advance body sensor components are utilized to gather user specific health data and store in cloud based storage repositories for subsequent analysis and classification. In addition, infrastructure level mechanisms are proposed to provide dynamic resource elasticity for CBIHCS. Experimental results demonstrate that classification accuracy of 92.59% is achieved with our prototype system and the predicted patterns of CPU usage offer better opportunities for adaptive resource elasticity.     

Mass spectrometric immunoassay and MRM as targeted MS-based quantitative approaches in biomarker development: Potential applications to cardiovascular disease and diabetes

Type 2 diabetes mellitus (T2DM) is an important risk factor for cardiovascular disease (CVD)—the leading cause of death in the United States. Yet not all subjects with T2DM are at equal risk for CVD complications; the challenge lies in identifying those at greatest risk. Therapies directed toward treating conventional risk factors have failed to significantly reduce this residual risk in T2DM patients. Thus newer targets and markers are needed for the development and testing of novel therapies. Herein we review two complementary MS-based approaches—mass spectrometric immunoassay (MSIA) and MS/MS as MRM—for the analysis of plasma proteins and PTMs of relevance to T2DM and CVD. Together, these complementary approaches allow for high-throughput monitoring of many PTMs and the absolute quantification of proteins near the low picomolar range. In this review article, we discuss the clinical relevance of the high density lipoprotein (HDL) proteome and Apolipoprotein A-I PTMs to T2DM and CVD as well as provide illustrative MSIA and MRM data on HDL proteins from T2DM patients to provide examples of how these MS approaches can be applied to gain new insight regarding cardiovascular risk factors. Also discussed are the reproducibility, interpretation, and limitations of each technique with an emphasis on their capacities to facilitate the translation of new biomarkers into clinical practice.     

Glycated proteome: From reaction to intervention

Glycation, a nonenzymatic reaction between reducing sugars and proteins, is a proteome wide phenomenon, predominantly observed in diabetes due to hyperglycemia. Glycated proteome of plasma, kidney, lens, and brain are implicated in the pathogenesis of various diseases, including diabetic complications, neurodegenerative diseases, cancer, and aging. This review discusses the strategies to characterize protein glycation, its functional implications in different diseases, and intervention strategies to protect the deleterious effects of protein glycation.     

Evaluation of a type 1 diabetes serum cohort by SELDI-TOF MS protein profiling

Proteomics analysis of serum from patients with type 1 diabetes (T1D) may lead to novel biomarkers for prediction of disease and for patient monitoring. However, the serum proteome is highly sensitive to sample processing and before proteomics biomarker research serum cohorts should preferably be examined for potential bias between sample groups. SELDI‐TOF MS protein profiling was used for preliminary evaluation of a biological‐bank with 766 serum samples from 270 patients with T1D, collected at 18 different paediatric centers representing 15 countries in Europe and Japan over 2 years (2000–2002). Samples collected 1 (n = 270), 6 (n = 248), and 12 (n = 248) months after T1D diagnosis were grouped across centers and compared. The serum protein profiles varied with collection site and day of analysis; however, markers of sample processing were not systematically different between samples collected at different times after diagnosis. Three members of the apolipoprotein family increased with time in patient serum collected 1, 6, and 12 months after diagnosis (ANOVA, p<0.001). These results support the use of this serum cohort for further proteomic studies and illustrate the potential of high‐throughput MALDI/SELDI‐TOF MS protein profiling for evaluation of serum cohorts before proteomics biomarker research.     

Health information technologies for patients with diabetes

Patients with chronic illnesses, such as diabetes, need daily care and follow-up beyond occasional visits to healthcare providers. Research has shown that overcoming a multifaceted illness, such as diabetes, requires patients to be engaged in the monitoring and management of their own health. Health information technology (HIT) has been shown to empower chronically-ill patients to take charge of their healthcare, and alleviate their daily frustrations while they strive to lead a normal life. In this paper, we surveyed 31 patients with diabetes to identify the major frustrations they experience daily, examine the role of HIT in their current treatment, and identify gaps in their current care and education that, if addressed, could improve their quality of life. Themes identified in our survey results include a lack of interaction with healthcare providers, difficulties in scheduling appointments, a lack of timely communication with healthcare providers, and challenges in managing the complex care of diabetes. The contributions of this paper include a detailed set of recommendations on how HIT can be utilized to help chronically-ill patients live a better life despite their illnesses, with a particular emphasis on diabetes care and management.     

A MEMS affinity glucose sensor using a biocompatible glucose-responsive polymer

We present a MEMS affinity sensor that can potentially allow long-term continuous monitoring of glucose in subcutaneous tissue for diabetes management. The sensing principle is based on detection of viscosity changes due to affinity binding between glucose and poly(acrylamide-ran-3-acrylamidophenylboronic acid) (PAA-ran-PAAPBA), a biocompatible, glucose-specific polymer. The device uses a magnetically driven vibrating microcantilever as a sensing element, which is fabricated from Parylene and situated in a microchamber. A solution of PAA-ran-PAAPBA fills the microchamber, which is separated from the surroundings by a semi-permeable membrane. Glucose permeates through the membrane and binds reversibly to the phenylboronic acid moiety of the polymer. This results in a viscosity change of the sensing solution, which is obtained by measuring the damped cantilever vibration using an optical lever setup, allowing determination of the glucose concentration. Experimental results demonstrate that the device is capable of detecting glucose at physiologically relevant concentrations from 27 mg/dL to 324 mg/dL. The glucose response time constant of the sensor is approximately 3 min, which can be further improved with device design optimization. Excellent reversibility and stability are observed in sensor responses, as highly desired for long-term, stable continuous glucose monitoring.     

A new computer-assisted three-dimensional reconstruction method provides accurate measurement of glomerular mesangial volume

Many glomerulopathies are characterized by progressive mesangial (interstitial) expansion which can be quantitated by morphometric analysis. The purpose of this study was to analyze mesangial and glomerular volumes using a new computer-assisted reconstruction (CAR) method. CAR was compared to two standard planar methods, point-counting and linear integration, for accuracy and time efficiency. In Phase I of the study, a computer-based model of the mesangial space was created by placing spherical and ellipsoidal objects of known volume into an enclosing volume mimicking the glomerulus. The simulated mesangium occupied approximately 10 percent of the glomerular volume. The model glomerulus was sectioned serially into ten sections of equal thickness and the three morphometric methods applied to determine the mesangial/glomerular volume. The complexity of the mesangial model was varied by increasing the number of mesangial regions from one to ten to 100. The CAR method estimated the model mesangial volume more accurately (1–9 percent error) through each level of complexity compared to point-counting (3–17 percent error) and linear integration (3–18 percent error). The point-counting method consistently overestimated (P < 0.05) the fractional mesangial volume for the ten- and 100-region mesangium models. In Phase II of the study, a normal rat glomerulus was sectioned serially (215 sections) and a transmission electron micrograph (TEM) of every fifth section (n = 43) was obtained. Each TEM image (2% of glomerular surface) was digitized for analysis by CAR. Point-counting and linear integration were also performed on the whole glomerular TEMs (n = 10, randomly chosen). The estimated relative mesangial/glomerular volume was 6.6 ± 0.1 percent by CAR (x? ± SD), 9.7 ± 1.5 by linear integration, and 14.9 ± 3.4 by point-counting. The point-counting method was most efficient, requiring 40 ± 8 sec/section, followed by CAR at 85 ± 24 sec/section. Linear integration was least efficient (93 ± 23 sec/section). We conclude that CAR is the most accurate morphometric method of the three compared for estimating mesangial and glomerular methods, although it is more time consuming than the point-counting method and requires more complex instrumentation. CAR is the only method that will analyze the shape and three-dimensional complexity of glomerular structures using TEMs.     

Optimisation of immobilisation conditions for chick pea β-galactosidase (CpGAL) to alkylamine glass using response surface methodology and its applications in lactose hydrolysis

Response surface methodology was advantageously used to optimally immobilise a β-galactosidase from chick pea onto alkylamine glass using Box–Behnken experimental design, resulting in an overall 91% immobilisation efficiency. Analysis of variance was performed to determine the adequacy and significance of the quadratic model. Immobilised enzyme showed a shift in the optimum pH; however, optimum temperature remained unaffected. Thermal denaturation kinetics demonstrated significant improvement in thermal stability of the enzyme after immobilisation. Galactose competitively inhibits the enzyme in both soluble and immobilised conditions. Lactose in milk whey was hydrolysed at comparatively higher rate than that of milk. Immobilised enzyme showed excellent reusability with retention of more than 82% enzymatic activity after 15 uses. The immobilised enzyme was found to be fairly stable in both dry and wet conditions for three months with retention of more than 80% residual activity.