Effect of diabetes on mortality and length of hospital stay in patients with renal or perinephric abscess

OBJECTIVES: We compared the risk of in-hospital mortality and the length of hospital stay between diabetic and non-diabetic patients hospitalized for renal or perinephric abscess. METHOD: The data analyzed in this study were retrieved from Taiwan's National Health Insurance claims. The risk of in-hospital mortality and the length of hospital stay were compared between 1,715 diabetic patients, hospitalized because of renal or perinephric abscess in Taiwan between 1997 and 2007, and a random sample of 477 non-diabetes patients with renal or perinephric abscess. RESULTS: The in-hospital mortality rates from renal or perinephric abscess for the diabetic patients and the non-diabetic patients were not different, at 2.3% and 3.4%, respectively. However, diabetes was significantly associated with a longer length of hospital stay among patients with renal abscess, by 3.38 days (95% confidence interval [CI]: 1.59-5.17). CONCLUSIONS: Diabetes does not increase the risk of in-hospital mortality from renal or perinephric abscess. Nevertheless, appropriate management of patients with diabetes and concurrent renal or perinephric abscess is essential to reduce the length of hospital stay

Clinical significance, challenges and limitations in using artificial intelligence for electrocardiography-based diagnosis

Cardiovascular diseases are one of the leading global causes of mortality. Currently, clinicians rely on their own analyses or automated analyses of the electrocardiogram (ECG) to obtain a diagnosis. However, both approaches can only include a finite number of predictors and are unable to execute complex analyses. Artificial intelligence (AI) has enabled the introduction of machine and deep learning algorithms to compensate for the existing limitations of current ECG analysis methods, with promising results. However, it should be prudent to recognize that these algorithms also associated with their own unique set of challenges and limitations, such as professional liability, systematic bias, surveillance, cybersecurity, as well as technical and logistical challenges. This review aims to increase familiarity with and awareness of AI algorithms used in ECG diagnosis, and to ultimately inform the interested stakeholders on their potential utility in addressing present clinical challenges

Use of Multi-Functional Flexible Micro-Sensors for in situ Measurement of Temperature, Voltage and Fuel Flow in a Proton Exchange Membrane Fuel Cell

Temperature, voltage and fuel flow distribution all contribute considerably to fuel cell performance. Conventional methods cannot accurately determine parameter changes inside a fuel cell. This investigation developed flexible and multi-functional micro sensors on a 40 μm-thick stainless steel foil substrate by using micro-electro-mechanical systems (MEMS) and embedded them in a proton exchange membrane fuel cell (PEMFC) to measure the temperature, voltage and flow. Users can monitor and control in situ the temperature, voltage and fuel flow distribution in the cell. Thereby, both fuel cell performance and lifetime can be increased

The Geomorphometry of Rainfall-Induced Landslides in Taiwan Obtained by Airborne Lidar and Digital Photography

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Anti-Cancer Effects of Protein Extracts from Calvatia lilacina, Pleurotus ostreatus and Volvariella volvacea

Calvatia lilacina (CL), Pleurotus ostreatus (PO) and Volvariella volvacea (VV) are widely distributed worldwide and commonly eaten as mushrooms. In this study, cell viabilities were evaluated for a human colorectal adenocarcinoma cell line (SW480 cells) and a human monocytic leukemia cell line (THP-1 cells). Apoptotic mechanisms induced by the protein extracts of PO and VV were evaluated for SW480 cells. The viabilities of THP-1 and SW480 cells decreased in a concentration-dependent manner after 24 h of treatment with the protein extracts of CL, PO or VV. Apoptosis analysis revealed that the percentage of SW480 cells in the SubG1 phase (a marker of apoptosis) was increased upon PO and VV protein-extract treatments, indicating that oligonucleosomal DNA fragmentation existed concomitantly with cellular death. The PO and VV protein extracts induced reactive oxygen species (ROS) production, glutathione (GSH) depletion and mitochondrial transmembrane potential (ΔΨm) loss in SW480 cells. Pretreatment with N-acetylcysteine, GSH or cyclosporine A partially prevented the apoptosis induced by PO protein extracts, but not that induced by VV extracts, in SW480 cells. The protein extracts of CL, PO and VV exhibited therapeutic efficacy against human colorectal adenocarcinoma cells and human monocytic leukemia cells. The PO protein extracts induced apoptosis in SW480 cells partially through ROS production, GSH depletion and mitochondrial dysfunction. Therefore, the protein extracts of these mushrooms could be considered an important source of new anti-cancer drugs

Nanoparticles prepared from the water extract of Gusuibu (Drynaria fortunei J. Sm.) protects osteoblasts against insults and promotes cell maturation

Our previous study showed that Gusuibu (Drynaria fortunei J. Sm.) can stimulate osteoblast maturation. This study was further designed to evaluate the effects of nanoparticles prepared from the water extract of Gusuibu (WEG) on osteoblast survival and maturation. Primary osteoblasts were exposed to 1, 10, 100, and 1000 μg/mL nanoparticles of WEG (nWEG) for 24, 48, and 72 hours did not affect morphologies, viability, or apoptosis of osteoblasts. In comparison, treatment of osteoblasts with 1000 μg/mL WEG for 72 hours decreased cell viability and induced DNA fragmentation and cell apoptosis. nWEG had better antioxidant bioactivity in protecting osteoblasts from oxidative and nitrosative stress-induced apoptosis than WEG. In addition, nWEG stimulated greater osteoblast maturation than did WEG. Therefore, this study shows that WEG nanoparticles are safer to primary osteoblasts than are normal-sized products, and may promote better bone healing by protecting osteoblasts from apoptotic insults, and by promoting osteogenic maturation

A cross-cultural examination of the impact of social, organisational and individual factors on educational technology acceptance between British and Lebanese university students

This paper examines the social, organisational and individual factors that may affect students' acceptance of e-learning systems in higher education in a cross-cultural context. A questionnaire was developed based on an extended technology acceptance model (TAM). A total sample of 1173 university students from two private universities in Lebanon and one university in England participated in this study. After performing the satisfactory reliability and validity checks, the hypothesised model was estimated using structural equation modeling. The findings of this study revealed that perceived usefulness (PU), perceived ease of use (PEOU), social norms (SNs), perceived quality of work life (QWL), computer self-efficacy (SE) and facilitating conditions (FC) are significant determinants of behavioural intentions (BIs) and usage of e-learning system for the Lebanese and British students. QWL, the newly added variable, was found the most important construct in explaining the causal process in the model for both samples. Differences were found between Lebanese and British students with regard to PEOU, SN, QWL, FC, SE and actual usage; however, no differences were detected in terms of PU and BI. Overall, the proposed model achieves acceptable fit and explains for 69% of the British sample and 57% of the Lebanese sample of its variance which is higher than that of the original TAM. Our findings suggest that individual, social and organisational factors are important to consider in explaining students' BI and usage of e-learning environments

The New Extended Left-Right Symmetric Grand Unified Model with SO(3) Family Symmetry

We suggest a new left-right symmetric grand unified model by extending Pati-Salam group to contain an isospin SU(2) and a flavor SO(3) subgroup, where the superheavy fermions are introduced as a mirror to the low-energy standard model fermions. The model undergoes three steps to break to the SM by means of the specified Higgs multiplets. The model few parameters can elegantly accommodate whole mass spectra for all the particles at the electroweak scale, especially, two different flavor mixing for the quark and lepton sectors are reproduced in agreement with the current experimental data very well. The strong CP violation is excellently explained. The matter-antimatter asymmetry in the universe is successfully implemented through the B-L violating decays of the superheavy gauge bosons. The model also predicts that the lightest right-handed Majorana neutrino, whose mass is about several hundred GeVs and energy is about $10^{16}$ GeV, is possibly a candidate for the dark matter.Comment: 24 pages, 4 figures; to revise the old manuscript and add some new content

Comparison of sodium-glucose cotransporter-2 inhibitor and dipeptidyl peptidase-4 inhibitor on the risks of new-onset atrial fibrillation, stroke and mortality in diabetic patients: A propensitysScore-matched study in Hong Kong

Objective To compare the effects of sodium-glucose cotransporter 2 inhibitors (SGLT2Is) and dipeptidyl peptidase-4 inhibitors (DPP4Is) on adverse outcomes in diabetic patients in Hong Kong. Methods This was a retrospective population-based cohort study of type 2 diabetes mellitus patients (n = 72,746) treated with SGLT2I or DPP4I between January 1, 2015, and December 31, 2020, in Hong Kong. Patients with exposure to both DPP4I and SGLT2I therapy, without complete demographics or mortality data, or who had prior atrial fibrillation (AF) were excluded. The study outcomes were new-onset AF, stroke/transient ischemic attack, cardiovascular mortality and all-cause mortality. Propensity score matching (1:1 ratio) between SGLT2I and DPP4I users was performed. Results The unmatched study cohort included 21,713 SGLT2I users and 39,510 DPP4I users (total: n = 61,233 patients; 55.37% males, median age: 62.7 years [interquartile range (IQR): 54.6–71.9 years]). Over a median follow-up of 2030 (IQR: 1912–2117) days, 2496 patients (incidence rate [IR]: 4.07%) developed new-onset AF, 2179 patients (IR: 3.55%) developed stroke/transient ischemic attack, 1963 (IR: 3.20%) died from cardiovascular causes and 6607 patients (IR: 10.79%) suffered from all-cause mortality. After propensity score matching (SGLT2I: n = 21,713; DPP4I: n = 21,713), SGLT2I users showed lower incidence of new-onset AF (1.96% vs. 2.78%, standardized mean difference [SMD] = 0.05), stroke (1.80% vs. 3.52%, SMD = 0.11), cardiovascular mortality (0.47% vs. 1.56%, SMD = 0.11) and all-cause mortality (2.59% vs. 7.47%, SMD = 0.22) compared to DPP4I users. Cox regression found that SGLT2I users showed lower risk of new-onset AF (hazard ratio [HR]: 0.68, 95% confidence interval [CI]: [0.56, 0.83], P = 0.0001), stroke (HR: 0.64, 95% CI: [0.53, 0.79], P < 0.0001), cardiovascular mortality (HR: 0.39, 95% CI: [0.27, 0.56], P < 0.0001) and all-cause mortality (HR: 0.44, 95% CI: [0.37, 0.51], P < 0.0001) after adjusting for significant demographics, past comorbidities, medications and laboratory tests. Conclusions Based on real-world data of type 2 diabetic patients in Hong Kong, SGLT2I use was associated with lower risk of incident AF, stroke/transient ischemic attack, and cardiovascular and all-cause mortality outcomes compared to DPP4I use