Decrease of Klotho in the Kidney of Streptozotocin-Induced Diabetic Rats

The klotho gene is expressed in a limited number of tissues, most notably in distal convoluted tubules in the kidney and choroid plexus in the brain. A previous study suggested that Klotho increases resistance to oxidative stress. However, changes of Klotho expression in high glucose-induced oxidative stress remain unclear. In the present study, we used streptozotocin-induced diabetic rats (STZ rats) to examine the effects of insulin, phloridzin or antioxidant, tiron on diabetic nephropathy. Both insulin and phloridzin reversed the lower Klotho expression levels in kidneys of STZ rats by the correction of hyperglycemia. Also, renal functions were improved by these treatments. In addition to the improvement of renal functions, the decrease of Klotho expression in kidney of STZ rats was also reversed by tiron without changing blood glucose levels. The reduction of oxidative stress induced by high glucose can be considered for this action of tiron. This view was further confirmed in vitro using high glucose-exposed Madin-Darby canine kidney (MDCK) epithelial cells. Thus, we suggest that decrease of oxidative stress is not only responsible for the improvement of renal function but also for the recovery of Klotho expression in kidney of STZ rats

Exploring Trust in Online Ride-sharing Platform in China: A Perspective of Time and Location

Trust is a key issue to be considered deliberately in the online ride-sharing platform to reduce risk and ensure transactions. In this paper, trust-in-platform is explored from these two perspectives to fill the research gaps. A ride-sharing platform in China was investigated. Results show that trust-in-platform in economically developing districts is slightly higher than that in economically developed districts. At the same time, trust-in-platform level differs in time, trust-in-platform levels are obviously lower between 19’o clock and 23’o clock. Moreover, machine learning is employed to predict the relationships between time/location and trust-in-platform. The result is that recall is 78.3%, precision is 57.3%, and F1 is 66.2%. The result shows trust-in-platform has an obvious correlation with time and location, thus further consolidates the findings. This study contributes to the existing knowledge on trust in the ride-sharing platforms and has practical implications for platform operators

Portal Vein Gas in a Diabetic Patient with Gas-forming Pararenal Abscess

The incidence of portal vein gas (PVG), which used to be an ominous sign of intestinal sepsis, has increased with progressive improvements in imaging modalities. Therefore, the clinical significance of PVG has changed. Emphysematous pyelonephritis (EPN) is a rare, potentially life-threatening and gas-forming infection of the renal parenchyma and/or its surroundings. Gas-forming pararenal abscess presenting with PVG is even rarer. We hereby present the case of a diabetic female with poor glycemic control, who was diagnosed to have EPN and PVG concurrently by computed tomography. She underwent percutaneous catheter drainage (PCD) of the pyelonephritis. Both cultures of blood and pus grew Klebsiella pneumoniae. Her subsequent clinical course was uneventful. In summary, EPN is a rare but potentially fatal urinary tract infection in diabetic patients, and finding PVG on computed tomography can aid in diagnosis. Conservative treatment with intravenous antibiotics and PCD of pus may be adequate for the patient with EPN. However, nephrectomy may be necessary if the patient deteriorates and PCD fails to contain the infection

SFCNeXt: a simple fully convolutional network for effective brain age estimation with small sample size

Deep neural networks (DNN) have been designed to predict the chronological age of a healthy brain from T1-weighted magnetic resonance images (T1 MRIs), and the predicted brain age could serve as a valuable biomarker for the early detection of development-related or aging-related disorders. Recent DNN models for brain age estimations usually rely too much on large sample sizes and complex network structures for multi-stage feature refinement. However, in clinical application scenarios, researchers usually cannot obtain thousands or tens of thousands of MRIs in each data center for thorough training of these complex models. This paper proposes a simple fully convolutional network (SFCNeXt) for brain age estimation in small-sized cohorts with biased age distributions. The SFCNeXt consists of Single Pathway Encoded ConvNeXt (SPEC) and Hybrid Ranking Loss (HRL), aiming to estimate brain ages in a lightweight way with a sufficient exploration of MRI, age, and ranking features of each batch of subjects. Experimental results demonstrate the superiority and efficiency of our approach.Comment: This paper has been accepted by IEEE ISBI 202

Association between triglyceride glucose index and adverse clinical outcomes in patients with acute myocardial infarction and LDL-C≤1.8 mmol/L who underwent percutaneous coronary intervention: a prospective cohort study

BackgroundRecently, the triglyceride glucose (TyG) index has emerged as a reliable predictive indicator for adverse outcomes of cardiovascular disease. However, the roles of the TyG index in patients with acute myocardial infarction (AMI) and low-density lipoprotein cholesterol (LDL-C)≤1.8 mmol/L after percutaneous coronary intervention (PCI) remain unclear.MethodsA total of 599 patients diagnosed with AMI and LDL-C ≤ 1.8 mmol/L at the 1-month follow-up after PCI were consecutively enrolled between January 2017 and January 2020. The patients were subsequently divided into three groups based on tertiles of the TyG index. The parameters, including the TyG index, were compared to explore the risk factors associated with major adverse cardiovascular and cerebrovascular events (MACCEs) during the 1-year follow-up.ResultsSixty-nine patients (11.5%) with 90 MACCEs were recorded during the 1-year follow up, including 13 patients (8.6%) in the Tertile 1 group, 36 (12.0%) in the Tertile 2 group, and 20 (13.4%) in the Tertile 3 group. Patients with a higher TyG index had a significantly increased incidence of MACCEs compared to those with a lower TyG index (22.1% vs. 14.0% vs. 9.9%, p=0.010). Kaplan–Meier analysis demonstrated that patients with a higher TyG index had a significantly lower probability of survival without MACCEs. Furthermore, a binary logistic regression model indicated that the TyG index was the only independent predictor for MACCEs in these patients.ConclusionA higher TyG index was associated with a higher incidence of MACCEs in patients with AMI and well-controlled LDL-C levels after PCI. This suggests that the TyG index can serve as a predictive indicator for adverse cardiovascular outcomes in these patients