Treatment of Knee Osteoarthritis Complicated with Femoral Condyle Fracture by Joint Replacement Combined with Internal Fracture Fixation.

Objective: To investigate the efficacy of artificial knee arthroplasty in conjunction with internal fracture fixation for treating knee osteoarthritis and a femoral condyle fracture. Methods: From January 2013 to June 2020, the researchers' department admitted 11 patients with femoral condyle fractures in combination with knee osteoarthritis. Three of the patients were males; 8 were females. They ranged in age from 62 to 76 years, with an average age of 69.2 years. Five patients were injured in traffic accidents, 6 were related to falls. Before the incidents, all patients had varying degrees of flexion inversion deformity and moderate to severe osteoarthritis in their knee joints. The fractures were of two types: 3 were epicondylar fractures, and 8 were medial femoral condyle fractures. To treat the combined condition of osteoarthritis and fractured femoral condyles, all patients underwent artificial knee joint replacement along with internal fixation with a single treatment. Knee radiographs and joint mobility assessments were performed during the follow-up period and were measured using the Hospital for Special Surgery (HSS) knee function score. Results: All patients were followed up from 18 to 105 months with a mean duration of (52.5±2.6) months. Significant differences in knee mobility and HSS ratings at 1 month and 1 year postoperatively compared favorably to the condition before surgery. HSS scores at the 1-year postoperative follow-up were excellent in 8 cases, good in 2, acceptable in 1, and poor in 0 cases. Conclusion: Artificial knee joint replacement combined with fracture internal fixation has good clinical efficacy in treating osteoarthritis of the knee joint combined with femoral condyle fracture. After surgery, patients resumed weight-bearing activities early, reducing the likelihood of complications and avoiding postoperative pain. This approach shortened the treatment period and enhanced the overall quality of life.

miR-149-5p mitigates tumor necrosis factor-α-induced chondrocyte apoptosis by inhibiting TRADD.

Introduction: Chondrocyte apoptosis as a prominent characteristic is usually accompanied by cartilage degeneration in osteoarthritis (OA). Herein, we aimed to determine the roles of miR-149-5p in tumor necrosis factor-α (TNF-α)-induced chondrocyte apoptosis. Material and methods: Human chondrocytes were cultured with TNF-α to establish an apoptosis cell model in vitro. After transfection with miR-149-5p mimics or co-expression with TRADD in chondrocytes, cell viability, apoptosis, inflammatory cytokines, mRNA and protein expression were measured using CCK8, Annexin V-FITC double staining, ELISA assays, RT-qPCR and western blotting, respectively. Results: TNF-α-induced chondrocyte apoptosis occurred in association with the inhibition of cell proliferation, the elevation of inflammatory cytokine levels and the activation of TRADD and caspase-3/8 signaling. The post-transcriptional regulatory mechanism suggested that TRADD was a direct target of miR-149-5p, and overexpression of miR-149-5p resulted in the down-regulation of TRADD protein expression in chondrocytes. In addition, miR-149-5p mimics had the ability to attenuate TNF-α-induced inflammation and apoptosis, while transfection with TRADD vector neutralized the protective effects of miR-149-5p on TNF-α-induced chondrocyte dysfunction. Conclusions: miR-149-5p inversely regulated TNF-α-mediated chondrocyte damage by inhibiting TRADD-modulated caspases signaling. The miR-149-5p/TRADD signaling pathway might be a promising therapeutic target for the treatment of OA.

Identification of CREB5 as a prognostic and immunotherapeutic biomarker in glioma through multi-omics pan-cancer analysis.

BACKGROUND: The functional relevance of cyclic adenosine monophosphate (cAMP)-response element-binding protein 5 (CREB5) in cancers remains elusive, despite its significance as a member of the CREB family. The current research aims to explore the role of CREB5 in multiple cancers. METHODS: Pan-cancer analysis was performed to explore the expression patterns, prognostic value, mutational landscape as well as single-cell omic, immunologic, and drug sensitivity profiles of CREB5. Furthermore, we incorporated five distinct machine learning algorithms and determined that the least absolute shrinkage and selection operator-COX (LASSO-COX) algorithm, which exhibited the highest C index, was the optimal selection. Subsequently, we constructed a prognostic model centered around CREB5-associated genes. To elucidate the biological function of CREB5 in glioma cells, several assays including cell counting kit-8 (CCK-8), wound healing, transwell, flow cytometric were performed. RESULTS: CREB5 was overexpressed in pan-cancer and was linked to unfavorable prognosis, particularly in glioma. Furthermore, genetic alterations were determined in various types of cancer, and modifications in the CREB5 gene were linked to the prognosis. The single-cell omics and enrichment analyses showed that CREB5 was predominantly expressed in malignant glioma cells and was critically involved in the regulation of various oncogenic processes. Elevated levels of CREB5 were strongly linked with the infiltration of cancer-associated fibroblasts and the Th1 subset of CD4+ T cells. The validated CREB5-associated prognostic model reliably predicted the prognosis and drug response of glioma patients. The in vitro experiments showed that CREB5 promoted glioma cell proliferation, invasion, migration, and gap phase 2/mitotic (G2/M) phase arrest and recruited M2 macrophages into glioma cells. CONCLUSION: CREB5 has the potential to act as an oncogene and a biological marker in multiple cancers, particularly glioma.

A Fusion Positioning Method for Indoor Geomagnetic/Light Intensity/Pedestrian Dead Reckoning Based on Dual-Layer Tent-Atom Search Optimization-Back Propagation.

Indoor positioning using smartphones has garnered significant research attention. Geomagnetic and sensor data offer convenient methods for achieving this goal. However, conventional geomagnetic indoor positioning encounters several limitations, including low spatial resolution, poor accuracy, and stability issues. To address these challenges, we propose a fusion positioning approach. This approach integrates geomagnetic data, light intensity measurements, and inertial navigation data, utilizing a hierarchical optimization strategy. We employ a Tent-ASO-BP model that enhances the traditional Back Propagation (BP) algorithm through the integration of chaos mapping and Atom Search Optimization (ASO). In the offline phase, we construct a dual-resolution fingerprint database using Radial Basis Function (RBF) interpolation. This database amalgamates geomagnetic and light intensity data. The fused positioning results are obtained via the first layer of the Tent-ASO-BP model. We add a second Tent-ASO-BP layer and use an improved Pedestrian Dead Reckoning (PDR) method to derive the walking trajectory from smartphone sensors. In PDR, we apply the Biased Kalman Filter-Wavelet Transform (BKF-WT) for optimal heading estimation and set a time threshold to mitigate the effects of false peaks and valleys. The second-layer model combines geomagnetic and light intensity fusion coordinates with PDR coordinates. The experimental results demonstrate that our proposed positioning method not only effectively reduces positioning errors but also improves robustness across different application scenarios.

Novel risk model based on angiogenesis-related lncRNAs for prognosis prediction of hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is a major cause of cancer-related death due to early metastasis or recurrence. Tumor angiogenesis plays an essential role in the tumorigenesis of HCC. Accumulated studies have validated the crucial role of lncRNAs in tumor angiogenesis. Here, we established an angiogenesis-related multi-lncRNAs risk model based on the machine learning for HCC prognosis prediction. Firstly, a total of 348 differential expression angiogenesis-related lncRNAs were identified by correlation analysis. Then, 20 of these lncRNAs were selected through univariate cox analysis and used for in-depth study of machine learning. After 1,000 random sampling cycles calculating by random forest algorithm, four lncRNAs were found to be highly associated with HCC prognosis, namely LUCAT1, AC010761.1, AC006504.7 and MIR210HG. Subsequently, the results from both the training and validation sets revealed that the four lncRNAs-based risk model was suitable for predicting HCC recurrence. Moreover, the infiltration of macrophages and CD8 T cells were shown to be closely associated with risk score and promotion of immune escape. The reliability of this model was validated by exploring the biological functions of lncRNA MIR210HG in HCC cells. The results showed that MIR210HG silence inhibited HCC growth and migration through upregulating PFKFB4 and SPAG4. Taken together, this angiogenesis-related risk model could serve as a reliable and promising tool to predict the prognosis of HCC.

The Extraction and Characterization of Pseudorange Multipath Based on BDS-3 Multi-Frequency Observations.

Global Navigation Satellite System (GNSS) observations are subject to various errors during their propagation process. A reasonable correction of these errors can improve the positioning, navigation, and timing (PNT) service capability. The impact of multipaths on pseudorange observations can reach a decimeters or even meters level. However, their mechanism is complex and there is currently no universally accepted high-precision correction model. The correlation between the pseudorange multipaths (MP) of BDS-2 satellites and satellite elevation has been confirmed, while there have been fewer analyses of the MP characteristics for different frequencies of BDS-3 satellites. The broadcasting of multi-frequency observations in BDS-3 should theoretically make the extracted MP more accurate compared to traditional methods. Based on this, in this contribution, a multi-frequency MP extraction algorithm based on the least squares principle is proposed, which can simultaneously eliminate the influence of higher-order ionospheric delay. The analytical expression for only eliminating first-order ionospheric delay is successfully derived. Subsequently, the characteristics of the MPs extracted from different frequency combinations and the impact of combination noise on the extraction accuracy are discussed. The influence of second-order ionospheric delay on the MPs for each frequency under different combination noises, as well as the periodic behavior exhibited in long-term observations of the BDS-3 medium earth orbit (MEO) and inclined geosynchronous orbit (IGSO) satellites, are also analyzed. Finally, the correlations between the MPs of each frequency of BDS satellite and elevation are quantitatively analyzed based on observations from 35 stations. Overall, this work has positive implications for the study of the MP characteristics of BDS-3 and subsequent modeling efforts.

A novel prognostic signature based on immunogenic cell death score predicts outcomes and response to transcatheter arterial chemoembolization and immunotherapy in hepatocellular carcinoma.

PURPOSE: The phenomenon of immunogenic cell death (ICD) is intricately linked to numerous antitumor treatments and exerts a profound regulatory function in the tumor immune microenvironment (TIME). We aimed to establish a prognostic signature from the ICD-related biomarkers to differentiate the TIME in hepatocellular carcinoma and predict diverse outcomes for patients with liver cancer. METHODS: ICD score-related genes (ICDSGs) were identified using the weighted gene co-expression network analysis (WGCNA). The ICD score-related signature (ICDSsig) was established by applying LASSO and Cox regression. Model precision was verified using the external datasets. We used independent prognostic variables in clinicopathologic factors to develop a nomogram. Further, clinical characteristics, immune and molecular landscapes, the responses of transcatheter arterial chemoembolization (TACE) and immunotherapy, and chemotherapy sensitivity were analyzed for high- and low-risk patients. RESULTS: ICD score-calculated using the single-sample gene set enrichment analysis (ssGSEA)-displayed strong associations with the TIME in HCC. We identified 34 ICDSGs after integrating the TCGA and GSE104580 datasets. Then, three novel ICDSGs (DNASE1L3, KLRB1, and LILRB1) were screened out to construct the ICDSsig; the prognostic signature performed well in the external databases. The high-risk patients had worse outcomes owing to their advanced pathological state, non-response of TACE, and immune-cold phenotype in the immune landscapes. The immune checkpoint genes, N6-methyladenosine-relevant genes, and microsatellite instability score were increased in the high-risk subgroup, thereby indicating a favorable sensitivity to immunotherapy. Common chemotherapy drugs were more effective in high-risk patients due to low half-maximal inhibitory concentration values. CONCLUSION: The ICDSsig can potentially predict outcomes and therapeutic responses for patients with liver cancer and may assist clinicians in designing individualized treatment strategies.

Empagliflozin, a sodium glucose cotransporter-2 inhibitor, ameliorates peritoneal fibrosis via suppressing TGF-ß/Smad signaling.

Sodium glucose cotransporter-2 (SGLT-2) inhibitor has been reported to exert a glucose-lowering effect in the peritoneum exposed to peritoneal dialysis solution. However, whether SGLT-2 inhibitors can regulate peritoneal fibrosis by suppressing TGF-ß/Smad signaling is unclear. We aimed to (i) examine the effect of the SGLT-2 inhibitor empagliflozin in reducing inflammatory reaction and preventing peritoneal dialysis solution-induced peritoneal fibrosis and (ii) elucidate the underlying mechanisms. High-glucose peritoneal dialysis solution or transforming growth factor ß1 (TGF-ß1) was used to induce peritoneal fibrosis in vivo, in a mouse peritoneal dialysis model (C57BL/6 mice) and in human peritoneal mesothelial cells in vitro, to stimulate extracellular matrix accumulation. The effects of empagliflozin and adeno-associated virus-RNAi, which is used to suppress SGLT-2 activity, on peritoneal fibrosis and extracellular matrix were evaluated. The mice that received chronic peritoneal dialysis solution infusions showed typical features of peritoneal fibrosis, including markedly increased peritoneal thickness, excessive matrix deposition, increased peritoneal permeability, and upregulated α-smooth muscle actin and collagen I expression. Empagliflozin treatment or downregulation of SGLT-2 expression significantly ameliorated these pathological changes. Inflammatory cytokines (TNF-α, IL-1ß, IL-6) and TGF-ß/Smad signaling-associated proteins, such as TGF-ß1 and phosphorylated Smad (p-Smad3), decreased in the empagliflozin-treated and SGLT-2 downregulated groups. In addition, empagliflozin treatment and downregulation of SGLT-2 expression reduced the levels of inflammatory cytokines (TNF-α, IL-1ß, IL-6), TGF-ß1, α-smooth muscle actin, collagen I, and p-Smad3 accumulation in human peritoneal mesothelial cells. Collectively, these results indicated that empagliflozin exerted a clear protective effect on high-glucose peritoneal dialysis-induced peritoneal fibrosis via suppressing TGF-ß/Smad signaling.

Coix lachryma-jobi extract ameliorates inflammation and oxidative stress in a complete Freund's adjuvant-induced rheumatoid arthritis model.

Context: Adlay seed [Job's tears, Coix lachryma-jobi L. var. ma-yuen Stapf (Poaceae)] is a Traditional Chinese Medicine, which has been investigated to treat inflammatory diseases and rheumatism.Objective: This study evaluates the ameliorative effects of adlay seed extract (ASE) in a complete Freund's adjuvant (CFA)-induced rheumatoid arthritis (RA) rats.Materials and methods: The RA Sprague-Dawley rat model was induced and randomly divided into six groups with or without ASE treatment (50, 100 or 200 mg/kg). After 28 d administration, the symptoms, biochemical parameters and molecular mechanisms were investigated.Results: The values of paw oedema, PGE2 and MMP-3 decreased from 1.46 ± 0.04 to 0.66 ± 0.07 cm3, from 126.2 ± 11.48 to 79.71 ± 6.8 pg/mL and from 142.7 ± 8.36 to 86.51 ± 5.95 ng/mL, respectively; the values of body weight increased from 177.25 ± 5.94 to 205 ± 6.52 g in HASE group. In addition, treatment of ASE reduced the levels of pro-inflammatory cytokines (IL-1ß, TNF-α, IL-6, MCP-1), and increased the activities of antioxidant enzyme (GSH-Px, SOD, and CAT). Furthermore, ASE could suppress the mRNA expression of COX-2 and CHI3L1 and improve the mRNA expression of CAT and GPx-1 in ankle tissues of RA rats.Discussion and conclusions: For the first time, our results indicated ASE exerts anti-RA effects via inhibiting pro-inflammatory factors and alleviating oxidative stress. Our finding sheds light on the research and development of anti-RA functional foods from adlay seed.

Comparison of high-performance liquid chromatography and ultraviolet-visible spectrophotometry to determine the best method to assess Levofloxacin released from mesoporous silica microspheres/nano-hydroxyapatite composite scaffolds.

An assessment of Levofloxacin by high-performance liquid chromatography (HPLC) or ultraviolet-visible spectrophotometry (UV-Vis) and its pharmacokinetics in serum or plasma was made in a previous study by the present authors. Levofloxacin-loaded mesoporous silica microspheres/nano-hydroxyapatite (n-HA) composite scaffolds comprise a novel synthetic composite scaffold that may be utilized as a drug-delivery system for clinical usage. However, few studies have been published concerning a comparison of HPLC with UV-Vis, which is the preferred method for determination of Levofloxacin. In the present study, an HPLC method was first established, and subsequently a comparison of HPLC with the UV-Vis method was performed. The standard curve was established, and recovery rate from simulated body fluid was calculated. The linear concentration range for Levofloxacin was 0.05-300 µg/ml. The regression equation for HPLC was y=0.033x+0.010, with R 2=0.9991, whereas that for UV-Vis was y=0.065x+0.017, with R 2=0.9999. The recovery rates of low, medium and high (5, 25 and 50 µg/ml) concentrations of Levofloxacin determined by HPLC were 96.37±0.50, 110.96±0.23 and 104.79±0.06%, respectively, whereas those for low, medium and high concentrations according to UV-Vis were 96.00±2.00, 99.50±0.00 and 98.67±0.06%, respectively. Taken together, these findings demonstrated that it is not accurate to measure the concentration of drugs loaded on the biodegradable composite composites by UV-Vis. HPLC is the preferred method to evaluate sustained release characteristics of Levofloxacin released from mesoporous silica microspheres/n-HA composite scaffolds. The present study also provides guidance on which methods should be selected for investigating the sustained release properties of drugs in tissue engineering. The accurate determination of drug concentration in the drug delivery system provides guidance for the treatment of infectious diseases.

Synergistic effect of graphene and silicon dioxide hybrids through hydrogen bonding self-assembly in elastomer composites.

A novel graphene-silicon dioxide hybrid (HGS) was prepared by plant polyphenol-tannic acid (TA) functionalized pristine graphene (G-TA) and primary amine-containing silane coupling agent modified SiO2 (Si-NH2). Through strong hydrogen-bonding interaction between the phenolic hydroxyl groups on G-TA and primary amine groups on Si-NH2, SiO2 was uniformly loaded to the surface of graphene. Due to the synergistic dispersion effect of graphene and SiO2, which prevents restacking and re-aggregating of both graphene and SiO2, HGS hybrids were distributed evenly in the natural rubber (NR) matrix (HGS@NR). Simultaneously, the surface roughness of graphene after loading SiO2 and the interfacial interaction between the HGS hybrid and NR matrix were substantially improved. Due to the good dispersion and strong interface, the overall properties of HGS@NR nanocomposites are drastically enhanced compared with those of GS@NR nanocomposites prepared by dispersing the blend of unmodified graphene and SiO2 (GS) in NR. The HGS@NR nanocomposites possess the highest tensile strength up to 27.8 MPa at 0.5 wt% and tear strength of 60.2 MPa at 0.5 wt%. Thermal conductivities of the HGS@NR nanocomposites were found to be 1.5-fold better than that of the GS@NR nanocomposites. Also, the HGS@NR nanocomposites exhibit excellent abrasive resistant capacity that is nearly 2-fold better than that of the GS@NR nanocomposites. These results suggest that HGS has great potential in high-performance nanocomposites and a new strategy of constructing the efficient graphene-SiO2 hybrid fillers has been established.

Lubrication and plasticization behavior of large-size micro-spherical structured SiO2 for natural rubber.

In many rubber dynamic applications such as tires and seals, imparting excellent flex fatigue properties and processing behavior are of prime importance. Research in this direction has been done based on a judicious choice of polymer type or a blend thereof and the compounding ingredients. In this study, the effect of micro-spherical SiO2 on the flex fatigue properties and processing behavior of natural rubber (NR) is studied. Two different particle sizes of spherical SiO2 (N90, average diameter: 200 nm and N98, average diameter: 120 nm) were used to optimize the flex fatigue properties and processing behavior, and the mechanism is investigated. In this blend, 5 phr loading of N90 was effective in imparting the best overall combination of properties. This work was aimed at providing some theoretical basis and application basis for the use of micro-spherical SiO2 in the rubber industry.