We propose the multi-level network Lasso, which aims to overcome the key limitations of existing personalized learning methods, such as ignoring sample homogeneity or heterogeneity, and over-parametrization. Multi-level network Lasso learns both sample-common model and sample-specific model, that are succinct and interpretable in the sense that model parameters are shared across neighboring samples based on only a subset of relevant features. To apply personalized learning in multi-task scenarios, we further extend the multi-level network Lasso for multi-task personalized learning by learning underlying task groups in the feature subspace. Additionally, we investigate a family of the multi-level network Lasso based on the $\ell_{p}$ quasi-norm ($0
The receptor for advanced glycation end products (RAGE) and thioredoxin (Trx) play opposing roles in diabetic myocardial ischemia-reperfusion (MI/R) injury. We recently demonstrated nitrative modification of Trx leads to its inactivation and loss of cardioprotection. The present study is to determine the relationship between augmented RAGE expression and diminished Trx activity pertaining to exacerbated MI/R injury in the diabetic heart. The diabetic state was induced in mice by multiple intraperitoneal low-dose streptozotocin injections. RAGE small-interfering RNA (siRNA) or soluble RAGE (sRAGE, a RAGE decoy) was via intramyocardial and intraperitoneal injection before MI/R, respectively. Mice were subjected to 30 min of myocardial infarction followed by 3 or 24 h of reperfusion. At 10 min before reperfusion, diabetic mice were randomized to receive EUK134 (peroxynitrite scavenger), recombinant hTrx-1, nitrated Trx-1, apocynin (a NADPH oxidase inhibitor), or 1400W [an inducible nitric oxide synthase (iNOS) inhibitor] administration. The diabetic heart manifested increased RAGE expression and N ε -(carboxymethyl)lysine (CML, major advanced glycation end product subtype) content, reduced Trx-1 activity, and increased Trx nitration after MI/R. RAGE siRNA or administration of sRAGE in diabetic mice decreased MI/R-induced iNOS and gp91 phox expression, reduced Trx nitration, preserved Trx activity, and decreased infarct size. Apocynin or 1400W significantly decreased nitrotyrosine production and restored Trx activity. Conversely, administration of either EUK134 or reduced hTrx, but not nitrated hTrx, attenuated MI/R-induced superoxide production, RAGE expression, and CML content and decreased cardiomyocyte apoptosis in diabetic mice. Collectively, we demonstrate that RAGE modulates the MI/R injury in a Trx nitrative inactivation fashion. Conversely, nitrative modification of Trx blocked its inhibitory effect upon RAGE expression in the diabetic heart. This is the first direct evidence demonstrating the alternative cross talk between RAGE overexpression and nitrative Trx inactivation, suggesting that interventions interfering with their interaction may be novel means of mitigating diabetic MI/R injury.
Background: Renal involvement resulting from hyperuricemia, known as hyperuricemia nephropathy (HN), is characterized by chronic tubulointerstitial inflammation caused by extensive urate crystal deposition. Managing this condition requires straightforward preventive or therapeutic interventions, primarily through dietary measures. Methods: In this study, the mouse model of HN was established using yeast extract combined with potassium oxonate. The effect and potential mechanism of β‐sitosterol in treating HN were investigated through biochemical indexes, pathological changes, untargeted metabolomics, and network pharmacology. Results: β‐Sitosterol reduced the levels of four biomarkers of HN: uric acid (UA), creatinine (CRE), blood urea nitrogen (BUN), and xanthine oxidase (XOD). It also mitigated inflammatory injury in renal tissues and reversed the abnormal expression of four key urate transporter proteins: glucose transporter protein 9 (GLUT9), organic anion transporter 1 (OAT1), ATP‐binding cassette transporter G2 (ABCG2), and urate transporter 1 (URAT1). To explore the mechanism of β‐sitosterol in treating HN, this study employed network pharmacology and metabolomics to analyze 27 intersecting gene targets and 14 differential metabolites. The findings indicated that glutathione (GSH) metabolism might be a crucial pathway. Treatment with β‐sitosterol increased the levels of reduced GSH as well as the activity and expression of 6‐phosphogluconate dehydrogenase (G6PDH) in mice, thereby effectively modulating GSH metabolism. This study proposes a novel strategy using β‐sitosterol for treating HN, providing a promising approach for addressing this condition.
With the rapid development of mobile edge computing (MEC) and wireless power transfer (WPT) technologies, the MEC-WPT system makes it possible to provide high-quality data processing services for end users. However, in a real-world WPT-MEC system, the channel gain decreases with the transmission distance, leading to “double near and far effect” in the joint transmission of wireless energy and data, which affects the quality of the data processing service for end users. Consequently, it is essential to design a reasonable system model to overcome the “double near and far effect” and make reasonable scheduling of multi-dimensional resources such as energy, communication and computing to guarantee high-quality data processing services. First, this paper designs a relay collaboration WPT-MEC resource scheduling model to improve wireless energy utilization efficiency. The optimization goal is to minimize the normalization of the total communication delay and total energy consumption while meeting multiple resource constraints. Second, this paper imports a BK-means algorithm to complete the end terminals cluster to guarantee effective energy reception and adapts the whale optimization algorithm with adaptive mechanism (AWOA) for mobile vehicle path-planning to reduce energy waste. Third, this paper proposes an immune differential enhanced deep deterministic policy gradient (IDDPG) algorithm to realize efficient resource scheduling of multiple resources and minimize the optimization goal. Finally, simulation experiments are carried out on different data, and the simulation results prove the validity of the designed scheduling model and proposed IDDPG.
Abstract Objectives The aim of this study was to use deep learning (DL) of intraoperative images of urinary stones to predict the composition of urinary stones. In this way, the laser frequency and intensity can be adjusted in real time to reduce operation time and surgical trauma. Materials and methods A total of 490 patients who underwent holmium laser surgery during the two-year period from March 2021 to March 2023 and had stone analysis results were collected by the stone laboratory. A total of 1658 intraoperative stone images were obtained. The eight stone categories with the highest number of stones were selected by sorting. Single component stones include calcium oxalate monohydrate (W1), calcium oxalate dihydrate (W2), magnesium ammonium phosphate hexahydrate, apatite carbonate (CH) and anhydrous uric acid (U). Mixed stones include W2 + U, W1 + W2 and W1 + CH. All stones have intraoperative videos. More than 20 intraoperative high-resolution images of the stones, including the surface and core of the stones, were available for each patient via FFmpeg command screenshots. The deep convolutional neural network (CNN) ResNet-101 (ResNet, Microsoft) was applied to each image as a multiclass classification model. Results The composition prediction rates for each component were as follows: calcium oxalate monohydrate 99% (n = 142), calcium oxalate dihydrate 100% (n = 29), apatite carbonate 100% (n = 131), anhydrous uric acid 98% (n = 57), W1 + W2 100% (n = 82), W1 + CH 100% ( n = 20) and W2 + U 100% (n = 24). The overall weighted recall of the cellular neural network component analysis for the entire cohort was 99%. Conclusion This preliminary study suggests that DL is a promising method for identifying urinary stone components from intraoperative endoscopic images. Compared to intraoperative identification of stone components by the human eye, DL can discriminate single and mixed stone components more accurately and quickly. At the same time, based on the training of stone images in vitro, it is closer to the clinical application of stone images in vivo. This technology can be used to identify the composition of stones in real time and to adjust the frequency and energy intensity of the holmium laser in time. The prediction of stone composition can significantly shorten the operation time, improve the efficiency of stone surgery and prevent the risk of postoperative infection.
Vascular insulin resistance contributes to elevated peripheral vascular resistance and subsequent hypertension. Clinical observation showed that lower plasma adiponectin concentration is significantly associated with hypertension. This study was aimed to determine whether hypoadiponectinemia induces vascular insulin resistance before systemic hypertension and the underlying mechanisms. Four-week-old young spontaneously hypertensive rats (ySHRs, normotensive) and adiponectin knockout (KO; APN(-/-)) mice were used to evaluate the role of hypoadiponectinemia in insulin-induced vasodilation of resistance vessels. ySHRs showed significant vascular insulin resistance as evidenced by the blunted vasorelaxation response to insulin in mesenteric arterioles compared with that of age-matched Wistar-Kyoto controls. Serum adiponectin and mesenteric arteriolar APPL1 (an adaptor protein that mediates adiponectin signaling) expression of ySHRs were significantly reduced. In addition, Akt and endothelial NO synthase phosphorylation and NO production in arterioles were markedly reduced, whereas extracellular signal-regulated protein kinases 1/2 (ERK1/2) phosphorylation and endothelin-1 secretion were augmented in ySHRs. APN(-/-) mice showed significantly decreased APPL1 expression and vasodilation evoked by insulin. More importantly, treatment of ySHRs in vivo with the globular domain of adiponectin for 1 week increased APPL1 expression and insulin-induced vasodilation, and restored the balance between insulin-stimulated endothelial vasodilator NO and vasoconstrictor endothelin-1. In cultured human umbilical vein endothelial cells, globular domain of adiponectin upregulated APPL1 expression. Suppression of APPL1 expression with small interfering RNA markedly blunted the globular domain of adiponectin-induced insulin sensitization as evidenced by reduced Akt/endothelial NO synthase and potentiated ERK1/2 phosphorylations. In conclusion, hypoadiponectinemia induces APPL1 downregulation in the resistance vessels, contributing to the development of vascular insulin resistance by differentially modulating the Akt/endothelial NO synthase/NO and ERK1/2/endothelin-1 pathways in vascular endothelium in normotensive ySHRs.
Abstract Objective This retrospective study aims to examine the correlation between calcium oxalate (CaOx) stones and common clinical tests, as well as urine ionic composition. Additionally, we aim to develop and implement a personalized column chart model to assess the accuracy and feasibility of using column charts to predict calcium oxalate stones in patients with urinary tract stones. Methods A retrospective analysis was conducted on data from 960 patients who underwent surgery for urinary stones at the First Affiliated Hospital of Soochow University from January 1, 2010, to December 31, 2022. Among these patients, 447 were selected for further analysis based on screening criteria. Multivariate logistic regression analysis was then performed to identify the best predictive features for calcium oxalate stones from the clinical data of the selected patients. A prediction model was developed using these features and presented in the form of a nomogram graph. The performance of the prediction model was assessed using the C-index, calibration curve, and decision curve, which evaluated its discriminative power, calibration, and clinical utility, respectively. Conclusion The nomogram diagram prediction model developed in this study is effective in predicting calcium oxalate stones, which is helpful in screening and early identification of high-risk patients with calcium oxalate urinary tract stones, and may be a guide for urologists in making clinical treatment decisions.
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