Improved glucose detection limit based on phosphorescence from protected metalloporphyrin triplet state.

BACKGROUND: Non-invasive indirect blood glucose monitoring can be realized by detecting low concentrations of glucose (0.05-5 mM) in tears, but sensitive optical indicators are required. The intensity of the phosphorescence of a candidate optical indicator, palladium hematoporphyrin monomethyl ether (Pd-HMME), is increased by oxygen consumption under sealed conditions in the presence of glucose and glucose oxidase. However, the glucose detection limit based on this mechanism is high (800 µM) because the phosphorescence is completely quenched under ambient oxygen conditions and hence a large amount of glucose is required to reduce the oxygen levels such that the phosphorescence signal is detectable. RESULTS: To improve the glucose detection limit of Pd-HMME phosphorescence-based methods, the triplet protector imidazole was introduced, and strong phosphorescence was observed under ambient oxygen conditions. Detectable phosphorescence enhancement occurred at low glucose concentrations (<200 µM). Linear correlation between the phosphorescence intensity and glucose concentration was observed in the range of 30-727 µM (R2 = 99.9 %), and the detection limit was ∼10 µM. The glucose sensor has a fast response time (∼90 s) and excellent selectivity for glucose. SIGNIFICANCE AND NOVELTY: These results indicate the potential of the developed optical indicator for fast, selective, and reliable low-concentration glucose sensing.

Untargeted metabolomics reveals that declined PE and PC in obesity may be associated with prostate hyperplasia.

BACKGROUND: Recent studies have shown that obesity may contribute to the pathogenesis of benign prostatic hyperplasia (BPH). However, the mechanism of this pathogenesis is not fully understood. METHODS: A prospective case-control study was conducted with 30 obese and 30 nonobese patients with BPH. Prostate tissues were collected and analyzed using ultra performance liquid chromatography ion mobility coupled with quadrupole time-of-flight mass spectrometry (UPLC-IMS-Q-TOF). RESULTS: A total of 17 differential metabolites (3 upregulated and 14 downregulated) were identified between the obese and nonobese patients with BPH. Topological pathway analysis indicated that glycerophospholipid (GP) metabolism was the most important metabolic pathway involved in BPH pathogenesis. Seven metabolites were enriched in the GP metabolic pathway. lysoPC (P16:0/0:0), PE (20:0/20:0), PE (24:1(15Z)/18:0), PC (24:1(15Z)/14:0), PC (15:0/24:0), PE (24:0/18:0), and PC (16:0/18:3(9Z,12Z,15Z)) were all significantly downregulated in the obesity group, and the area under the curve (AUC) of LysoPC (P-16:0/0/0:0) was 0.9922. The inclusion of the seven differential metabolites in a joint prediction model had an AUC of 0.9956. Thus, both LysoPC (P-16:0/0/0:0) alone and the joint prediction model demonstrated good predictive ability for obesity-induced BPH mechanisms. CONCLUSIONS: In conclusion, obese patients with BPH had a unique metabolic profile, and alterations in PE and PC in these patients be associated with the development and progression of BPH.

Telomere maintenance-related genes are important for survival prediction and subtype identification in bladder cancer.

Background: Bladder cancer ranks among the top three in the urology field for both morbidity and mortality. Telomere maintenance-related genes are closely related to the development and progression of bladder cancer, and approximately 60%-80% of mutated telomere maintenance genes can usually be found in patients with bladder cancer. Methods: Telomere maintenance-related gene expression profiles were obtained through limma R packages. Of the 359 differential genes screened, 17 prognostically relevant ones were obtained by univariate independent prognostic analysis, and then analysed by LASSO regression. The best result was selected to output the model formula, and 11 model-related genes were obtained. The TCGA cohort was used as the internal group and the GEO dataset as the external group, to externally validate the model. Then, the HPA database was used to query the immunohistochemistry of the 11 model genes. Integrating model scoring with clinical information, we drew a nomogram. Concomitantly, we conducted an in-depth analysis of the immune profile and drug sensitivity of the bladder cancer. Referring to the matrix heatmap, delta area plot, consistency cumulative distribution function plot, and tracking plot, we further divided the sample into two subtypes and delved into both. Results: Using bioinformatics, we obtained a prognostic model of telomere maintenance-related genes. Through verification with the internal and the external groups, we believe that the model can steadily predict the survival of patients with bladder cancer. Through the HPA database, we found that three genes, namely ABCC9, AHNAK, and DIP2C, had low expression in patients with tumours, and eight other genes-PLOD1, SLC3A2, RUNX2, RAD9A, CHMP4C, DARS2, CLIC3, and POU5F1-were highly expressed in patients with tumours. The model had accurate predictive power for populations with different clinicopathological features. Through the nomogram, we could easily assess the survival rate of patients. Clinicians can formulate targeted diagnosis and treatment plans for patients based on the prediction results of patient survival, immunoassays, and drug susceptibility analysis. Different subtypes help to further subdivide patients for better treatment purposes. Conclusion: According to the results obtained by the nomogram in this study, combined with the results of patient immune-analysis and drug susceptibility analysis, clinicians can formulate diagnosis and personalized treatment plans for patients. Different subtypes can be used to further subdivide the patient for a more precise treatment plan.

What patients "see" doctors in online fever clinics during COVID-19 in Wuhan?

OBJECTIVE: In December 2019, coronavirus disease 2019 (COVID-19) occurred in Wuhan, China. Online fever clinics were developed by hospitals, largely relieving the hospital's burden. Online fever clinics could help people stay out of crowded hospitals and prevent the risk of cross infections. The objective of our study was to describe the patient characteristics of an online fever clinic and explore the most important concerns and question of online patients. MATERIALS AND METHODS: Our study extracted data from fever clinic records in medical information systems from January 24 to February 18, 2020 in a tertiary hospital in Wuhan. We described the characteristics of patients in fever clinic, then we extracted and classified questions of patient consultations through the online fever clinic dataset. RESULTS: For the 64 487 patients who attended the online fever clinic, the average age was 30.4 years, and 37 665 (58.4%) were female patients. The current state of patients from online were home without isolation (52 360 [81.2%]), home isolated (11 152 [17.29%]), and outpatient observation (975 [1.51%]). From the 594 patient questions analyzed, confirming diagnosis and seeking medical treatment account for 60.61% and 38.05%, respectively, followed by treating (25.59%), preventing (4.38%), and relieving anxiety (1.68%). DISCUSSION: Online fever clinics can effectively relieve patients' mood of panic, and doctors can guide patients with suspected of COVID-19 to isolate and protect themselves through online fever clinic. Online fever clinics can also help to reduce the pressure of hospital fever clinics and prevent cross infection. CONCLUSIONS: This study indicated the importance of online fever clinics during the COVID-19 outbreak for prevention and control.

Medical insurance and health equity in health service utilization among the middle-aged and older adults in China: a quantile regression approach.

BACKGROUND: China has achieved nearly universal coverage of the Social Basic Medical Insurance (SBMI), which aims to reduce the disease burden and improve the utilization of health services. We investigated the association between China's health insurance schemes and health service utilization of middle-aged and older adults at different quantiles, and then explored whether the SBMI could help reduce the underutilization of health services among the middle-aged and older adults in China. METHODS: Survey data of middle-aged and older adults were drawn from the China Health and Retirement Longitudinal Study (CHARLS). A linear quantile mixed regression model was utilized to provide a comprehensive understanding of the relationship between SBMI and health service utilization, which was measured by the total medical expenditure. We took the New Rural Cooperative Medical Scheme (NCMS) as the reference level and examined the associations of the Urban Employee Basic Medical Insurance (UEBMI) and the Urban Resident Basic Medical Insurance (URBMI) with health service utilization. RESULTS: The quantile regression analysis revealed a significant positive association between URBMI and health service utilization at the 0.75 (ß = 1.608, p < 0.01), 0.8 (ß = 1.578, p < 0.01), 0.85 (ß = 1.473, p < 0.01), 0.9 (ß = 1.403, p < 0.01) and 0.95 (ß = 1.152, p < 0.01) quantiles, and also a significant positive association between UEBMI and health service utilization at the 0.85 (ß = 1.196, p < 0.01), 0.9 (ß = 1.070, p < 0.01) and 0.95 (ß = 0.736, p < 0.01) quantiles. Results showed that URBMI was significantly associated with an improvement in inpatient health service utilization of the middle-aged and older adults, and a significant positive association between UEBMI and inpatient health service utilization was observed at 0.1 (ß = 0.559, p < 0.01), 0.25 (ß = 0.420, p < 0.05), 0.5 (ß = 0.352, p < 0.05), and 0.75 (ß = 0.306, p < 0.05) quantiles. CONCLUSIONS: Inequity in health service utilization exists among the middle-aged and older adults across urban and rural Chinese areas, and it can be explained by the different reimbursement benefits of SBMI types.