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Objectives Type 2 diabetes mellitus (T2DM) imposes a great burden on healthcare systems, and these patients experience higher long-term risks for developing end-stage renal disease (ESRD). Managing diabetic nephropathy becomes more challenging when kidney function starts declining. Therefore, developing predictive models for the risk of developing ESRD in newly diagnosed T2DM patients may be helpful in clinical settings. Methods We established machine learning models constructed from a subset of clinical features collected from 53,477 newly diagnosed T2DM patients from January 2008 to December 2018 and then selected the best model. The cohort was divided, with 70% and 30% of patients randomly assigned to the training and testing sets, respectively. Results The discriminative ability of our machine learning models, including logistic regression, extra tree classifier, random forest, gradient boosting decision tree (GBDT), extreme gradient boosting (XGBoost), and light gradient boosting machine were evaluated across the cohort. XGBoost yielded the highest area under the receiver operating characteristic curve (AUC) of 0.953, followed by extra tree and GBDT, with AUC values of 0.952 and 0.938 on the testing dataset. The SHapley Additive explanation summary plot in the XGBoost model illustrated that the top five important features included baseline serum creatinine, mean serum creatine within 1 year before the diagnosis of T2DM, high-sensitivity C-reactive protein, spot urine protein-to-creatinine ratio and female gender. Conclusions Because our machine learning prediction models were based on routinely collected clinical features, they can be used as risk assessment tools for developing ESRD. By identifying high-risk patients, intervention strategies may be provided at an early stage.

Background Life-long peritoneal dialysis (PD) as a renal replacement therapy is limited by peritoneal fibrosis. Previous studies showed immunomodulatory and antifibrotic effects of adipose-derived mesenchymal stem cells (ADSCs) on peritoneal fibrosis. However, the role of the peritoneal macrophage in this process remains uninvestigated. Methods We examined the therapeutic effects of ADSC and bone marrow-derived mesenchymal stem cells (BM-MSC) in the rat model of dialysis-induced peritoneal fibrosis using methylglyoxal. In addition, treatment of macrophages with the conditioned medium of ADSC and BM-MSC was performed individually to identify the beneficial component of the stem cell secretome. Results In the in vivo experiments, we found dialysis-induced rat peritoneal fibrosis was attenuated by both ADSC and BM-MSC. Interestingly, ADSC possessed a more prominent therapeutic effect than BM-MSC in ameliorating peritoneal membrane thickening while also upregulating epithelial cell markers in rat peritoneal tissues. The therapeutic effects of ADSC were positively associated with M2 macrophage polarization. In the in vitro experiments, we confirmed that interleukin-6 (IL-6) secreted by MSCs upon transforming growth factor-β1 stimulation promotes M2 macrophage polarization. Conclusions In dialysis-induced peritoneal fibrosis, MSCs are situated in an inflammatory environment of TGF-β1 and secrete IL-6 to polarize macrophages into the M2 phenotype. Our findings reveal a previously unidentified role of tissue macrophage in this antifibrotic process. ADSC has the advantage of abundance and accessibility, making the application values extremely promising. Graphical abstract In dialysis-induced peritoneal fibrosis, peritoneal mesothelial cells secrete transforming growth factor-β1 (TGF-β1) when exposed to methylglyoxal (MGO)-containing peritoneal dialysate. When situated in TGF-β1, the inflammatory environment induces mesenchymal stem cells to secrete interleukin-6 (IL-6), IL-6 polarizes macrophages into the M2 phenotype. The dominant peritoneal tissue M2 macrophages, marked by upregulated Arg-1 expression, account for the attenuation of MGO-induced dedifferentiation of peritoneal mesothelial cells to maintain epithelial integrity.

A new theoretical developments of measuring blood flow volume at arteriovenous fistula (AVF) using a photoplethysmography (PPG) sensor is presented in this work. The mathematical equation is derived under the practical perspective, aiming at applying to small-size, portable, inexpensive and easy-to-use PPG sensor, in order to replace bulky, expensive Doppler machines which is the commonly used instruments for accessing AVF noninvasively nowadays. Furthermore, a new, portable and wireless PPG sensor with ambient light compensation and motion artifact detection, is designed for performing clinical validation of the proposed equation. After neural network calibration with the gold standard, dilution concentration sensor, the experiment result reveals that the PPG sensors implementing the proposed equation successfully achieve much higher correlation (R2 = 0.8064) and much lower error (RMSE = 171.68 ml/min, MAPE = 15.84%) compared to the commercial Doppler machine and other previous works.

We report a 71-year-old woman who presented with unilateral flank pain and sepsis. A computed tomographic (CT) scan demonstrated left-sided hydronephrosis. Subsequent percutaneous nephrotomy drainage showed pus-like material, confirming the diagnosis of pyonephrosis. The ureteral stricture was caused by previous radiation injury for cervical cancer in this ESRD patient who was on chronic dialysis for years. In our case, the grade IVB hydronephrosis is a result of an extremely atrophic kidney, pyonephrosis, and ureteral stricture. The CT section of pyonephrosis in an extremely atrophic kidney resembles a sagittal section of a Nautilus shell, as the shell corresponds to the diffusely thinned renal cortex.

Because of the increasing usage of lanthanum carbonate in dialysis patients, clinicians should be aware of its typical radiographic appearance. A dialysis patient received a plain film and a computed tomography, both showing a “starry-sky” appearance in the nearly whole colon, and the radiological report mistakenly denoted it as barium. The patient denied any exposure to barium or radiocontrast medium. Tracing back her medication history, lanthanum carbonate, 500 mg twice a day, has been prescribed for her hyperphosphatemia in recent 5 months. Clinicians should be aware of typical radiographic appearance of lanthanum carbonate to avoid unnecessary management and may also take its radiopaque characteristic as an advantage to assess the patient's drug adherence.

Retinal electrostimulation is promising a successful therapy to restore functional vision. However, a narrow stimulating current range exists between retinal neuron excitation and inhibition which may lead to misperformance of visual prostheses. As the conveyance of representation of complex visual scenes may require neighbouring electrodes to be activated simultaneously, electric field summation may contribute to reach this inhibitory threshold. This study used three approaches to assess the implications of relatively high stimulating conditions in visual prostheses: (1) in vivo, using a suprachoroidal prosthesis implanted in a feline model, (2) in vitro through electrostimulation of murine retinal preparations, and (3) in silico by computing the response of a population of retinal ganglion cells. Inhibitory stimulating conditions led to diminished cortical activity in the cat. Stimulus-response relationships showed non-monotonic profiles to increasing stimulating current. This was observed in vitro and in silico as the combined response of groups of neurons (close to the stimulating electrode) being inhibited at certain stimulating amplitudes, whilst other groups (far from the stimulating electrode) being recruited. These findings may explain the halo-like phosphene shapes reported in clinical trials and suggest that simultaneous stimulation in retinal prostheses is limited by the inhibitory threshold of the retinal ganglion cells.

The evidence suggests that a surprisingly large number of firms comply with pollution standards even though expected penalties for non-compliance are quite low. This paper establishes an environmental social norm model that embodies collective environmental actions among firms. It provides a plausible explanation for these puzzling empirical findings. In this social norm framework, we also explore how the extrinsic pricing incentive affects the intrinsic environmental morale among firms. By taking into account the crowding-out effect of pricing incentives, we show that pollution taxes may not be an effective tool in fighting pollution.