Termansennoer1411

The (pro)renin receptor is a multifunctional protein with roles in angiotensin-II-dependent and -independent intracellular cell signaling and roles as an intracellular accessory protein for the vacuolar H+-ATPase, including hormone secretion. While (pro)renin receptor mRNA is widely expressed in various human tissues, localization of (pro)renin receptor protein expression has not yet been systemically determined. Therefore, this study localized (pro)renin receptor protein expression in human organs. Systemic immunohistochemical examination of (pro)renin receptor expression was performed in whole body organs of autopsy cases. (Pro)renin receptor immunostaining was observed in the cytoplasm of cells in almost all human organs. It was observed in thyroid follicular epithelial cells, hepatic cells, pancreatic duct epithelial cells, zona glomerulosa and zona reticularis of the cortex and medulla of the adrenal gland, proximal and distal tubules and collecting ducts of the kidney, cardiomyocytes, and skeletal muscle cells. In the brain, (pro)renin receptor staining was detected in neurons throughout all areas, especially in the medulla oblongata, paraventricular nucleus and supraoptic nucleus of the hypothalamus, cerebrum, granular layer of the hippocampus, Purkinje cell layer of the cerebellum, and the pituitary anterior and posterior lobes. In the anterior lobe of the pituitary gland, all types of anterior pituitary hormone-positive cells showed double staining with (pro)renin receptor. These data showed that (pro)renin receptor protein was expressed in almost all organs of the human body. Its expression pattern was not uniform, and cell-specific expression pattern was observed, supporting the notion that (pro)renin receptor plays numerous physiological roles in each human organ.

In chronic inflammatory diseases, proinflammatory cytokines such as TNF-

are present in high amounts in the circulation and are associated with anemia in most cases. Experimental studies have shown that TNF-

inhibits the synthesis of erythropoietin (Epo), the main stimulant of hematopoiesis. Our aim was to figure out which microRNAs are involved in the Epo repression by TNF-

.

First, we determined the dose of TNF-

in HepG2 cells that has no cytotoxic effect by using MTT assays and that inhibits Epo synthesis by qRT-PCR and ELISA. Then, we performed the microRNA array study with TNF-

(20 ng/ml)-treated cells, and the array results were confirmed by qRT-PCR. We transfected the miR663 group with the mimic-miR663 (30 pmol) for 24 hrs; other groups were treated with a transfection reagent followed by treatment of TNF-

for 24 hrs; miR663 groups were treated with TNF-

for 24 hrs; and the control group was incubated with normal medium. We analyzed Epo mRNA levels by qRT-PCR. If mimic-miR663 prevents the Epo repression by TNF-

, more Epo-dependent UT-7 cells would survive. Therefore, we cocultured HepG2 cells with UT-7 cells. The percentage of apoptotic UT-7 cells was determined by TUNEL assays.

According to our array study, TNF-

significantly decreases miR663 expression. After transfection of miR663 mimics into HepG2 cells, TNF-alpha was unable to decrease Epo mRNA amounts. Furthermore, mimic-miR663 transfection resulted in a lower apoptosis rate of UT-7 cells in coculture experiments.

miR663 is involved in Epo mRNA production and that is able to prevent or reverse the inhibitory effect of TNF-

. In our coculture study, transfecting HepG2 cells with miR663 mimics decreased the apoptosis of UT-7 cells.

miR663 is involved in Epo mRNA production and that is able to prevent or reverse the inhibitory effect of TNF-α. In our coculture study, transfecting HepG2 cells with miR663 mimics decreased the apoptosis of UT-7 cells.

Neoadjuvant chemotherapy (NAC) with subsequent radical surgery has become a popular treatment modality for advanced gastric cancer (AGC) worldwide. However, the survival benefit is still controversial, and prognostic factors remain undetermined.

To identify clinical parameters that are associated with the survival of AGC patients after NAC and radical surgery and to establish a nomogram integrating multiple factors to predict survival.

We reviewed the medical profiles of 215 AGC patients who received NAC and radical resection, and clinical parameters concerning NAC, surgery, pathological findings, and adjuvant chemotherapy were analyzed using a Cox regression model to determine their impact on survival. Based on these factors, a nomogram was developed and validated.

The overall 1-year and 3-year survival rates were 85.8% and 55.6%, respectively. Younger age (<60 years old), increased examined lymph nodes (exLNs), successful R0 resection, the achievement of pathological complete response (pCR), and acceptance of adjuvant chemotherapy were positive predictors of survival. The C-index of the established nomogram was 0.785. The area under receiver operating curve (ROC) at 1/3 years of prediction was 0.694/0.736, respectively. The model showed an ideal calibration following internal bootstrap validation.

A nomogram predicting survival after NAC and surgery was established. Since this nomogram exhibited satisfactory and stable predictive power, it can be inferred that this is a practical tool for predicting AGC patient survival after NAC and radical surgery.

A nomogram predicting survival after NAC and surgery was established. Since this nomogram exhibited satisfactory and stable predictive power, it can be inferred that this is a practical tool for predicting AGC patient survival after NAC and radical surgery.

KLF4 and KLF5 are members of the KLF transcription factor family, which play an important role in many gastrointestinal tumors. To gain a deeper insight into its function and role, bioinformatics was used to analyze the function and role of KLF4 and KLF5 in gastrointestinal tumors.

Data were collected from several online databases. Gene Expression Profiling Interactive Analysis (GEPIA), UALCAN database analysis, Kaplan-Meier Plotter analysis, LOGpc system, the Pathology Atlas, and the STRING website were used to analyze the data. We download relevant data from TCGA and then perform GO enrichment and KEGG enrichment analysis. The effects of KLF5 on gastric cancer cell proliferation were measured by CCK-8 assay. The effect of KLF5 on the expression of CyclinD1 and MMP9 was detected by Western blot.

KLF4 and KLF5 were differentially expressed in normal and tumor tissues of the gastrointestinal tract, and their differential expression is related to several genes or pathways. KEGG analysis showed that KLF5 was coexpressed with endocytosis-related genes. KLF5 promotes the proliferation of gastric cancer cells and the expression of metastasis-related molecules.

KLF4 and KLF5 are of great significance for developing gastrointestinal tumors and can be used as therapeutic targets.

KLF4 and KLF5 are of great significance for developing gastrointestinal tumors and can be used as therapeutic targets.

This study is aimed at exploring the effects of virtual reality (VR) training on postural control, measured by anticipatory and compensatory postural adjustments (APAs and CPAs, respectively), in patients with chronic nonspecific low back pain (CNLBP) and the potential neuromuscular mechanism of VR training.

Thirty-four patients were recruited and randomly assigned to the VR group (

= 11), the motor control exercise group (MCE,

= 12) and the control group (CG,

= 11). The VR group received VR training using Kinect Xbox 360 systems and magnetic therapy. Besides magnetic therapy, the participants in the MCE group performed real-time ultrasound-guided abdominal drawing-in maneuver (ADIM) and four-point kneeling exercise. The CG only received magnetic therapy. Surface muscle electromyography (sEMG) was used to record the muscle activities of transverse abdominis (TrA), multifidus (MF), lateral gastrocnemius (LG), and tibialis anterior (TA) during ball-hitting tasks. TGFbeta inhibitor The muscle activation time and integhowed reciprocal muscle activation patterns of the TrA and MF muscles after VR training. VR training may be a potential intervention for enhancing the APAs of the patients with CNLBP.

Parkinson's disease (PD) is a common neurological degenerative disease that cannot be completely cured, although drugs can improve or alleviate its symptoms. Optogenetic technology, which stimulates or inhibits neurons with excellent spatial and temporal resolution, provides a new idea and approach for the precise treatment of Parkinson's disease. However, the neural mechanism of photogenetic regulation remains unclear.

In this paper, we want to study the nonlinear features of EEG signals in the striatum and globus pallidus through optogenetic stimulation of the substantia nigra compact part.

Rotenone was injected stereotactically into the substantia nigra compact area and ventral tegmental area of SD rats to construct rotenone-treated rats. Then, for the optogenetic manipulation, we injected adeno-associated virus expressing channelrhodopsin to stimulate the globus pallidus and the striatum with a 1 mW blue light and collected LFP signals before, during, and after light stimulation. Finally, the collecdy LFP changes in rotenone-treated rats.At present, machine learning artificial neural network technology, as one of the core technologies of enterprises, has received unprecedented attention. This technology is widely used in automatic driving, pattern recognition, teaching aid, product modeling, and other fields. According to the development of product design, this paper analyzes the factors that affect the decision-making of product design. The neural network optimized by genetic algorithm is studied, and the technical analysis of neural network algorithm before and after optimization is mainly carried out. The basic process of product modeling design model based on image processing under the background of big data is introduced. The multidirectional group decision-making model of product modeling design scheme in big data cloud environment is constructed. The final decision model can improve the overall design efficiency, shorten the manufacturing period, and provide a new idea for product modeling design.Accurate segmentation of the tongue body is an important prerequisite for computer-aided tongue diagnosis. In general, the size and shape of the tongue are very different, the color of the tongue is similar to the surrounding tissue, the edge of the tongue is fuzzy, and some of the tongue is interfered by pathological details. The existing segmentation methods are often not ideal for tongue image processing. To solve these problems, this paper proposes a symmetry and edge-constrained level set model combined with the geometric features of the tongue for tongue segmentation. Based on the symmetry geometry of the tongue, a novel level set initialization method is proposed to improve the accuracy of subsequent model evolution. In order to increase the evolution force of the energy function, symmetry detection constraints are added to the evolution model. Combined with the latest convolution neural network, the edge probability input of the tongue image is obtained to guide the evolution of the edge stop function, so as to achieve accurate and automatic tongue segmentation.