MiR-214 promotes renal fibrosis in diabetic nephropathy via targeting SOCS1

Purpose: To elucidate how miR-214 regulates the pathogenesis of diabetic nephropathy (DN). Methods: The extent of fibrosis in DN mice kidneys was examined using Masson’s staining. Quantitative polymerase chain reaction (qPCR) was used to determine the levels of miR-214. Dual luciferase reporter assay was used to identify the target of miR-214. The expression of fibrosis marker proteins of high glucose-stimulated NRK-52E cells transfected with miR-214 was determined using western blotting. Results: Fibrosis in renal tissue of DN mice was significantly increased and miR-214 was upregulated (p < 0.001). Suppressor of cytokine signaling 1 protein (SOCS1) was the target gene of miR-214, and overexpression of miR-214 promoted fibrosis (p < 0.05, p < 0.001). On the other hand, overexpression of SOCS1 inhibited this process, indicating that miR-214 promoted fibrosis via targeting SOCS1 (p < 0.001). Finally, inhibition of miR-214 c ameliorated renal fibrosis in DN mice (p < 0.01, p < 0.001). Conclusions: MiR-214 is upregulated in db/db DN mice kidney tissue; miR-214 regulates renal fibrosis in DN mice by targeting SOCS1

A General Theory of Correct, Incorrect, and Extrinsic Equivariance

Although equivariant machine learning has proven effective at many tasks, success depends heavily on the assumption that the ground truth function is symmetric over the entire domain matching the symmetry in an equivariant neural network. A missing piece in the equivariant learning literature is the analysis of equivariant networks when symmetry exists only partially in the domain. In this work, we present a general theory for such a situation. We propose pointwise definitions of correct, incorrect, and extrinsic equivariance, which allow us to quantify continuously the degree of each type of equivariance a function displays. We then study the impact of various degrees of incorrect or extrinsic symmetry on model error. We prove error lower bounds for invariant or equivariant networks in classification or regression settings with partially incorrect symmetry. We also analyze the potentially harmful effects of extrinsic equivariance. Experiments validate these results in three different environments.Comment: Published at NeurIPS 202

TRPA1 Activation-Induced Myelin Degradation Plays a Key Role in Motor Dysfunction After Intracerebral Hemorrhage

Intracerebral hemorrhage (ICH) is a devastating disease that is characterized by high morbidity and high mortality. ICH has an annual incidence of 10–30/100,000 people and accounts for approximately 10%–30% of all types of stroke. ICH mostly occurs at the basal ganglia, which is rich in nerve fibers; thus, hemiplegia is quite common in ICH patients with partial sensory disturbance and ectopic blindness. In the clinic, those symptoms are considered to originate from the white matter injury in the area, but the exact mechanisms are unknown, and currently, no effective drug treatments are available to improve the prognosis. Clarifying the mechanisms will contribute to the development of new treatment methods for patients. The transient receptor potential ankyrin 1 (TRPA1) channel is a non-selective cation channel that plays a role in inflammatory pain sensation and nociception and may be a potential regulator in emotion, cognition and social behavior. Here, we report that TRPA1 is involved in myelin damage and oxidative stress injury in a mouse ICH model. Intervention with the TRPA1 channel may be a new method to improve the motor function of patients in the early stage of ICH

An Attempt to Understand Kidney's Protein Handling Function by Comparing Plasma and Urine Proteomes

With the help of proteomics technology, the human plasma and urine proteomes, which closely represent the protein compositions of the input and output of the kidney, respectively, have been profiled in much greater detail by different research teams. Many datasets have been accumulated to form “reference profiles” of the plasma and urine proteomes. Comparing these two proteomes may help us understand the protein handling aspect of kidney function in a way, however, which has been unavailable until the recent advances in proteomics technology.After removing secreted proteins downstream of the kidney, 2611 proteins in plasma and 1522 in urine were identified with high confidence and compared based on available proteomic data to generate three subproteomes, the plasma-only subproteome, the plasma-and-urine subproteome, and the urine-only subproteome, and they correspond to three groups of proteins that are handled in three different ways by the kidney. The available experimental molecular weights of the proteins in the three subproteomes were collected and analyzed. Since the functions of the overrepresented proteins in the plasma-and-urine subproteome are probably the major functions that can be routinely regulated by excretion from the kidney in physiological conditions, Gene Ontology term enrichment in the plasma-and-urine subproteome versus the whole plasma proteome was analyzed. Protease activity, calcium and growth factor binding proteins, and coagulation and immune response-related proteins were found to be enriched.The comparison method described in this paper provides an illustration of a new approach for studying organ functions with a proteomics methodology. Because of its distinctive input (plasma) and output (urine), it is reasonable to predict that the kidney will be the first organ whose functions are further elucidated by proteomic methods in the near future. It can also be anticipated that there will be more applications for proteomics in organ function research

WT1-AS/IGF2BP2 Axis Is a Potential Diagnostic and Prognostic Biomarker for Lung Adenocarcinoma According to ceRNA Network Comprehensive Analysis Combined with Experiments

Lung adenocarcinoma (LUAD) is one of the most common malignancies, and there is still a lack of effective biomarkers for early detection and prognostic prediction. Here, we comprehensively analyze the characteristics of. an RNA sequencing data set of LUAD samples. In total, 395 long non-coding RNAs (lncRNAs), 89 microRNAs (miRNAs), and 872 mRNAs associated with c-Myc were identified, which were differentially expressed between tumor and normal tissues. The most relevant pathway was found to be WT1-AS–miR-200a-3p–IGF2BP2 according to the rules of competitive endogenous RNA (ceRNA) regulation. WT1-AS and IGF2BP2 expression were positively correlated and increased in LUAD samples, while miR-200a-3p had relatively low expression. The high expression of WT1-AS and IGF2BP2 was associated with poor prognosis in LUAD patients, while low expression of miR-200a-3p predicted reduced survival (p < 0.05). The analysis of the multi-gene regulation model indicated that the WT1-AS (downregulation)–miR-200a-3p (upregulation)–IGF2BP2 (downregulation) pattern significantly improved the survival of LUAD patients. Finally, reverse transcription-polymerase chain reaction (RT-PCR) and Western blotting were detected in LUAD cells, and the results are consistent with the bioinformatics analysis. In summary, the WT1-AS/IGF2BP2 axis is a potential prognostic biomarker in LUAD and is expected to become an effective target for diagnosis and treatment

BulletArm: An Open-Source Robotic Manipulation Benchmark and Learning Framework

We present BulletArm, a novel benchmark and learning-environment for robotic manipulation. BulletArm is designed around two key principles: reproducibility and extensibility. We aim to encourage more direct comparisons between robotic learning methods by providing a set of standardized benchmark tasks in simulation alongside a collection of baseline algorithms. The framework consists of 31 different manipulation tasks of varying difficulty, ranging from simple reaching and picking tasks to more realistic tasks such as bin packing and pallet stacking. In addition to the provided tasks, BulletArm has been built to facilitate easy expansion and provides a suite of tools to assist users when adding new tasks to the framework. Moreover, we introduce a set of five benchmarks and evaluate them using a series of state-of-the-art baseline algorithms. By including these algorithms as part of our framework, we hope to encourage users to benchmark their work on any new tasks against these baselines

On-Robot Learning With Equivariant Models

Recently, equivariant neural network models have been shown to improve sample efficiency for tasks in computer vision and reinforcement learning. This paper explores this idea in the context of on-robot policy learning in which a policy must be learned entirely on a physical robotic system without reference to a model, a simulator, or an offline dataset. We focus on applications of Equivariant SAC to robotic manipulation and explore a number of variations of the algorithm. Ultimately, we demonstrate the ability to learn several non-trivial manipulation tasks completely through on-robot experiences in less than an hour or two of wall clock time

Preparation and evaluation of poly(l-histidine) based pH-sensitive micelles for intracellular delivery of doxorubicin against MCF-7/ADR cells

In this study, a pH-sensitive micelle self-assembled from poly(l-histidine) based triblock copolymers of poly(ethylene glycol)–poly(d,l-lactide)–poly(l-histidine) (mPEG-PLA-PHis) was prepared and used as the intracellular doxorubicin (Dox) delivery for cancer chemotherapy. Dox was loaded into the micelles by thin-film hydration method and a Box–Behnken design for three factors at three levels was used to optimize the preparations. The optimized mPEG-PLA-Phis/Dox micelles exhibited good encapsulation efficiency of 91.12%, a mean diameter of 45 nm and narrow size distribution with polydispersity index of 0.256. In vitro drug release studies demonstrated that Dox was released from the micelles in a pH-dependent manner. Furthermore, the cellular evaluation of Dox loaded micelles displayed that the micelles possessed high antitumor activity in vitro with an IC50 of 35.30 µg/ml against MCF-7/ADR cells. The confocal microscopy and flow cytometry experiments indicated that mPEG-PLA-Phis micelles mediated efficient cytoplasmic delivery of Dox with the aid of poly(l-histidine) mediated endosomal escape. In addition, blank mPEG-PLA-Phis micelles were shown to be nontoxic to MCF-7/ADR cells even at a high concentration of 200 µg/ml. The pH-sensitive mPEG-PLA-PHis micelles have been demonstrated to be a promising nanosystem for the intracellular delivery of Dox for MDR reversal

Identification of EGFR-Related LINC00460/mir-338-3p/MCM4 Regulatory Axis as Diagnostic and Prognostic Biomarker of Lung Adenocarcinoma Based on Comprehensive Bioinformatics Analysis and Experimental Validation

Background: Lung adenocarcinoma (LUAD) is one of the most aggressive and lethal tumor types and requires effective diagnostic and therapeutic targets. Though the epidermal growth factor receptor (EGFR) is an important target for LUAD therapy, acquired resistance is still inevitable. In recent years, the regulation of the EGFR by competing endogenous RNAs (ceRNAs) has been extensively studied and significant progress has been made. Therefore, we aim to find new targets for the diagnosis and treatment of LUAD by analyzing the EGFR-related ceRNA network in LUAD and expect to address the problem of EGFR resistance. Methods: We identified differentially expressed lncRNAs, miRNAs and mRNAs closely associated with the EGFR by analyzing transcriptome data from LUAD samples. Comprehensive bioinformatics analysis strongly suggests that the LINC00460—mir-338-3p—MCM4 ceRNA network plays an important role in the diagnosis and prognosis of LUAD. The effects of different patterns of the LINC00460/MCM4 axis on the overall survival of patients with LUAD were analyzed by a polygene regulation model. We also verified the expression of these genes in LUAD cell lines and tumor tissues by RT-PCR and immunohistochemistry. The functional enrichment analysis and targeted drug prediction of the MCM4 gene were performed. Results: Survival analysis indicated that high expressions of LINC00460 and MCM4 predict a shorter survival period for patients. Univariate and multivariate regression analyses demonstrated that higher expressions of LINC00460 and MCM4 were significantly associated with tumor size, lymph node metastasis, distant metastasis and TNM stage. A multi-gene regulation model analysis revealed that the LINC00460 (downregulation)—mir-338-3p (upregulation)—MCM4 (downregulation) pattern significantly improved the overall survival of LUAD patients (p = 0.0093). RT-PCR and immunohistochemical experiments confirmed our analytical results. In addition, the functional enrichment analysis indicated that MCM4-related genes were mainly enriched in the cell cycle and cell division. A functional association network analysis showed that MCM4 was closely related to the EGFR. Finally, the possible targeted drugs of MCM4 were queried through the drug database platform, hoping to solve its drug resistance problem by targeting EGFR-related genes. Conclusions: In summary, the LINC00460/MCM4 axis can be used as a potential new perspective for targeting EGFR genes in precision medicine and is expected to serve as a diagnostic, prognostic and drug target for LUAD