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Background/Objectives: Benign prostatic hyperplasia (BPH) is a prevalent urological disorder in aging men, characterized by the enlargement of prostate epithelial and stromal cells, which leads to lower urinary tract symptoms. Paeonol, a bioactive compound derived from Moutan Cortex (Paeonia suffruticosa), exhibits multiple pharmacological properties; however, its therapeutic potential in BPH remains unclear. This study aimed to elucidate the mechanisms of paeonol in BPH treatment using network pharmacology and in vivo experiments. Methods: Network pharmacology and molecular docking were conducted to identify potential targets of paeonol against BPH. For the in vivo study, testosterone-induced BPH rat models were employed, and efficacy was evaluated through prostate weight assessment, histological examination, and the quantitative real-time polymerase chain reaction (qRT-PCR) analysis of prostate tissues. Results: In silico analysis revealed key signaling pathways involved in apoptosis, proliferation, phosphatidylinositol 3-kinase (PI3K)–protein kinase B (Akt), and inflammation. Paeonol administration significantly reduced prostate weight, volume, and histological hyperplasia in BPH rats. qRT-PCR analysis demonstrated that paeonol may suppress dihydrotestosterone production by inhibiting 5α-reductase 2 (5AR2) and the androgen receptor (AR), while also downregulating local growth factors, alpha serine/threonine-protein kinase (Akt1), nuclear factor-κB (NF-κB), and glutathione reductase (GR) expression. Conclusions: These findings provide novel insights into the multitargeted therapeutic potential of paeonol in BPH by inhibiting 5AR and AR and suppressing proliferation via NF-κB and Akt pathway modulation.

The purpose of this study was to evaluate the performance of the deep convolutional neural network (DCNN) in differentiating between tuberculous and pyogenic spondylitis on magnetic resonance (MR) imaging, compared to the performance of three skilled radiologists. This clinical retrospective study used spine MR images of 80 patients with tuberculous spondylitis and 81 patients with pyogenic spondylitis that was bacteriologically and/or histologically confirmed from January 2007 to December 2016. Supervised training and validation of the DCNN classifier was performed with four-fold cross validation on a patient-level independent split. The object detection and classification model was implemented as a DCNN and was designed to calculate the deep-learning scores of individual patients to reach a conclusion. Three musculoskeletal radiologists blindly interpreted the images. The diagnostic performances of the DCNN classifier and of the three radiologists were expressed as receiver operating characteristic (ROC) curves, and the areas under the ROC curves (AUCs) were compared using a bootstrap resampling procedure. When comparing the AUC value of the DCNN classifier (0.802) with the pooled AUC value of the three readers (0.729), there was no significant difference ( P  = 0.079). In differentiating between tuberculous and pyogenic spondylitis using MR images, the performance of the DCNN classifier was comparable to that of three skilled radiologists.

Obesity-induced insulin resistance is the fundamental cause of metabolic syndrome. Accordingly, we evaluated the effect of mangiferin (MGF) on obesity and glucose metabolism focusing on inflammatory response and autophagy. First, an in silico study was conducted to analyze the mechanism of MGF in insulin resistance. Second, an in vivo experiment was conducted by administering MGF to C57BL/6 mice with high-fat-diet (HFD)-induced metabolic disorders. The in silico analysis revealed that MGF showed a high binding affinity with macrophage-related inflammatory cytokines and autophagy proteins. In the in vivo study, mice were divided into three groups: normal chow, HFD, and HFD + MGF 150 mg/kg. MGF administration to obese mice significantly improved the body weight, insulin-sensitive organs weights, glucose and lipid metabolism, fat accumulation in the liver, and adipocyte size compared to HFD alone. MGF significantly reduced the macrophages in adipose tissue and Kupffer cells, inhibited the gene expression ratio of tumor necrosis factor-α and F4/80 in adipose tissue, reduced the necrosis factor kappa B gene, and elevated autophagy-related gene 7 and fibroblast growth factor 21 gene expressions in the liver. Thus, MGF exerted a therapeutic effect on metabolic diseases by improving glucose and lipid metabolism through inhibition of the macrophage-mediated inflammatory responses and activation of autophagy.

This study investigates the effect of a change in the sliding speed on the wear behavior of mild steel and, in particular, the influence of the original speed on the wear behavior at subsequent speeds, in order to utilize it for the tribosystems design. The sliding wear tests were conducted by using a combination of changing conditions between two of three different sliding speeds in a pin-on-disc type wear testing machine: two sliding speeds with mild wear behavior and a sliding speed with severe wear behavior. It was obvious that the wear behavior after the speed change was highly dependent on the formation of oxides on the worn surface at each speed. When the speed changed between two speeds at which a mild wear behavior is exhibited, there was no significant difference in the sliding wear behavior before and after the speed change. When the speed changed from 0.3 and 3 m/s with a mild wear behavior to 1 m/s with a severe wear behavior, there was no significant increase in the wear rate. In contrast, the wear rate rapidly decreased at a subsequent speed change to 0.3 and 3 m/s. The time required until the steady-state wear condition was attained at the sliding speed of 0.3 m/s was significantly longer than that at 3 m/s.Graphic Abstract

Background/Objectives: Dyslipidemia is a significant risk factor for atherosclerotic cardiovascular disease (ASCVD), a leading cause of death worldwide. Salvia miltiorrhiza Burge is widely used in East Asia for cardiovascular health, showing potential benefits in lowering cholesterol and reducing inflammation. Methods: This study systematically reviewed and conducted a meta-analysis of randomized controlled trials (RCTs) to assess the clinical effectiveness of Salvia miltiorrhiza in treating dyslipidemia. Moreover, network pharmacology and molecular docking analyses were performed to explore the mechanisms underlying the effects of Salvia miltiorrhiza. Results: The meta-analysis revealed that when Salvia miltiorrhiza is combined with statin therapy, it significantly enhances lipid profiles, including reductions in total cholesterol, low-density lipoprotein cholesterol (LDL-C), and triglycerides and improvements in high-density lipoprotein cholesterol (HDL-C), compared to statin therapy alone. The in silico analyses indicated that Salvia miltiorrhiza may influence key biological pathways, such as the PI3K/Akt, JAK/STAT, and HMGCR pathways, which are involved in inflammation, lipid metabolism, and the development of atherosclerosis. Conclusions: Salvia miltiorrhiza shows potential as a complementary therapy for dyslipidemia, offering additional lipid-lowering and anti-inflammatory benefits.

Purpose (1) To analyse popliteal artery (PA) movement in a three-dimensional (3D) coordinate system in relation to knee flexion and high tibial osteotomy (HTO) techniques (lateral closed wedge HTO [LCHTO], uniplane medial open wedge HTO [UP-MOHTO], biplane medial open wedge HTO [BP-MOHTO]) and (2) to identify safe zones of the PA in each osteotomy plane. Methods Sixteen knees of patients who underwent magnetic resonance imaging with extension and 90° flexion were used to develop subject-specific 3D knee flexion models. Displacement of the PA during knee flexion was measured along the X - and Y -axis, as was the distance between the posterior tibial cortex and PA parallel to the Y -axis (d-PCA). Frontal plane safety index (FPSI) and maximal axial safe angles (MASA) of osteotomy, which represented safe zones for the osteotomy from the PA injury, were analysed. All measurements were performed along virtual osteotomy planes. Differences among the three osteotomy methods were analysed for each flexion angle using a linear mixed model. Results The average increments in d-PCA during knee flexion were 1.3 ± 2.3 mm in LCHTO (n.s.), 1.4 ± 1.2 mm in UP-MOHTO ( P  < 0.0001), and 1.7 ± 2.0 mm in BP-MOHTO ( P  = 0.015). The mean FPSIs in knee extension were 37.6 ± 5.9%, 46.4 ± 5.8%, and 45.1 ± 8.1% for LCHTO, UP-MOHTO, and BP-MOHTO, respectively. The mean MASA values in knee extension were 45.8° ± 4.4°, 37.3° ± 6.1°, and 38.9° ± 6.5° for LCHTO, UP-MOHTO, and BP-MOHTO, respectively. Conclusion Although the PA moved posteriorly during knee flexion, the small (1.7 mm) increment thereof and inconsistent movements in subjects would not be of clinical relevance to PA safety during HTO. Level of evidence Diagnostic study, Level II.

To evaluate the performance of a deep convolutional neural network (DCNN) in detecting local tumor progression (LTP) after tumor ablation for hepatocellular carcinoma (HCC) on follow-up arterial phase CT images. The DCNN model utilizes three-dimensional (3D) patches extracted from three-channel CT imaging to detect LTP. We built a pipeline to automatically produce a bounding box localization of pathological regions using a 3D-CNN trained for classification. The performance metrics of the 3D-CNN prediction were analyzed in terms of accuracy, sensitivity, specificity, positive predictive value (PPV), area under the receiver operating characteristic curve (AUC), and average precision. We included 34 patients with 49 LTP lesions and randomly selected 40 patients without LTP. A total of 74 patients were randomly divided into three sets: training (n = 48; LTP: no LTP = 21:27), validation (n = 10; 5:5), and test (n = 16; 8:8). When used with the test set (160 LTP positive patches, 640 LTP negative patches), our proposed 3D-CNN classifier demonstrated an accuracy of 97.59%, sensitivity of 96.88%, specificity of 97.65%, and PPV of 91.18%. The AUC and precision–recall curves showed high average precision values of 0.992 and 0.96, respectively. LTP detection on follow-up CT images after tumor ablation for HCC using a DCNN demonstrated high accuracy and incorporated multichannel registration.

Soil microorganisms play an essential role in soil ecosystem processes such as organic matter decomposition, nutrient cycling, and plant nutrient availability. The land use for greenhouse cultivation has been increasing continuously, which involves an intensive input of agricultural materials to enhance productivity; however, relatively little is known about bacterial communities in greenhouse soils. To assess the effects of environmental factors on the soil bacterial diversity and community composition, a total of 187 greenhouse soil samples collected across Korea were subjected to bacterial 16S rRNA gene pyrosequencing analysis. A total of 11,865 operational taxonomic units at a 97% similarity cutoff level were detected from 847,560 sequences. Among nine soil factors evaluated; pH, electrical conductivity (EC), exchangeable cations (Ca 2+ , Mg 2+ , Na + , and K + ), available P 2 O 5 , organic matter, and NO 3 -N, soil pH was most strongly correlated with bacterial richness (polynomial regression, pH: R 2 = 0.1683, P < 0.001) and diversity (pH: R 2 = 0.1765, P < 0.001). Community dissimilarities (Bray-Curtis distance) were positively correlated with Euclidean distance for pH and EC (Mantel test, pH: r = 0.2672, P < 0.001; EC: r = 0.1473, P < 0.001). Among dominant phyla (> 1%), the relative abundances of Proteobacteria , Gemmatimonadetes , Acidobacteria , Bacteroidetes , Chloroflexi , and Planctomycetes were also more strongly correlated with pH and EC values, compared with other soil cation contents, such as Ca 2+ , Mg 2+ , Na + , and K + . Our results suggest that, despite the heterogeneity of various environmental variables, the bacterial communities of the intensively cultivated greenhouse soils were particularly influenced by soil pH and EC. These findings therefore shed light on the soil microbial ecology of greenhouse cultivation, which should be helpful for devising effective management strategies to enhance soil microbial diversity and improving crop productivity.

ObjectivesTo investigate the agreement between double-inversion recovery (DIR) with synthetic magnetic resonance imaging (MRI) and T1-weighted contrast-enhanced (CE)-MRI for the assessment of knee synovitis.MethodsT1-weighted CE-MRI and synthetic MRI of 30 patients were compared. Synthetic DIR image reconstruction was performed with two inversion times (280–330 ms and 2800–2900 ms). Subjective image quality, visibility of synovium, detection of synovitis, and total synovitis score in the knee joint were evaluated on both MR images. The relative signal intensity (SI) and relative contrast of synovium, joint effusion, and bone marrow for two imaging were assessed. Differences in data between two imaging were assessed by using Wilcoxon’s signed-rank test and chi-square test/Fisher’s exact test. Interobserver agreement was expressed as weighted kappa value. Accuracy of synthetic DIR image was calculated by using CE-MRI as reference standard.ResultsT1-weighted CE-MRI yielded better image quality than synthetic DIR imaging (p < 0.001). Interobserver agreements for detecting synovitis diagnosis/sum of the synovitis score were moderate to almost perfect (κ = 0.58/0.44, synthetic DIR; κ = 0.83/0.65, T1-weighted CE-MRI). There were no statistical differences in visibility of synovium (p = 0.058–0.190), detection of synovitis (p < 0.001), and relative SI of structures between two imaging (p = 0.086–0.360). Synovium-to-effusion contrast was higher in synthetic DIR (p = 0.003) and synovium-to-bone marrow contrast was higher in CE-MRI (p < 0.001).ConclusionSynthetic DIR imaging showed a moderate degree of interobserver agreement and good accuracy for detecting synovitis. Though it has limitations, it may play a role in imaging of degenerative joint disease or larger cohort scientific studies where gadolinium application is not feasible.Key Points• Synthetic double-inversion recovery (DIR) imaging avoids the use of contrast agent.• There was no significant difference between T1-weighted CE-MRI and synthetic DIR imaging in evaluating presence of synovitis in knee joint.• Synthetic DIR imaging showed moderate degree of interobserver agreement and good accuracy for detecting synovitis compared to CE-MRI, and it may facilitate evaluation of some regions of peripatellar synovitis.

A carbon matrix for high-capacity Li/Na/K-alloy-based anode materials is required because it can effectively accommodate the variation in the volume of Li/Na/K-alloy-based anode materials during cycling. Herein, a nanostructured porous polyhedral carbon (PPC) was synthesized via a simple two-step method consisting of carbonization and selective acid etching, and their electrochemical Li/Na/K-ion storage performance was investigated. The highly uniform PPC, with an average particle size of 800 nm, possesses a porous structure and large specific surface area of 258.82 cm 2  g –1 . As anodes for Li/Na/K-ion batteries (LIBs/NIBs/KIBs), the PPC matrix exhibited large initial reversible capacity, fast rate capability (LIB: ~ 320 mAh g –1 at 3C; NIB: ~ 140 mAh g –1 at 2C; KIB: ~ 110 mAh g –1 at 2C), better cyclic performance (LIB: ~ 550 mAh g –1 ; NIB: ~ 210 mAh g –1 ; KIB: ~ 190 mAh g –1 at 0.2C over 100 cycles), high ionic diffusivity, and excellent structural robustness upon cycling, which demonstrates that the PPC matrix can be highly used as a carbon matrix for high-capacity alloy-based anode materials for LIBs/NIBs/KIBs. Graphical abstract