Ensemble Algorithm for Risk Prediction of Clinical Failure After Anterior Cruciate Ligament Reconstruction.

Background: Patient-specific risk profiles of clinical failure after anterior cruciate ligament reconstruction (ACLR) are meaningful for preoperative surgical planning and postoperative rehabilitation guidance. Purpose: To create an ensemble algorithm machine learning (ML) model and ML-based web-based tool that can predict the patient-specific risk of clinical failure after ACLR. Study Design: Cohort study; Level of evidence, 3. Methods: Included were 432 patients (mean age, 26.8 ± 8.4 years; 74.1% male) who underwent anatomic double-bundle ACLR with hamstring tendon autograft between January 2010 and February 2019. The primary outcome was the probability of clinical failure at a minimum 2-year follow-up. The authors included 24 independent variables for feature selection and model development. The data set was split randomly into training sets (75%) and test sets (25%). Models were built using 4 ML algorithms: extreme gradient boosting, random forest, light gradient boosting machine, and adaptive boosting. In addition, a weighted-average voting (WAV) ensemble model was constructed using the ensemble-voting technique to predict clinical failure after ACLR. Concordance (area under the receiver operating characteristic curve [AUC]), calibration, and decision curve analysis were used to evaluate predictive performances of the 5 models. Results: Clinical failure occurred in 73 of the 432 patients (16.9%). The 8 most important predictors for clinical failure were follow-up period, high-grade preoperative knee laxity, time from injury to ACLR, participation in competitive sports, posterior tibial slope, graft diameter, age at surgery, and medial meniscus resection. The WAV ensemble algorithm achieved the best predictive performance based on concordance (AUC, 0.9139), calibration (calibration intercept, -0.1806; calibration slope, 1.2794; Brier score, 0.0888), and decision curve analysis (greatest net benefits) and was used to develop an web-based application to predict a patient's clinical failure risk of ACLR. Conclusion: The WAV ensemble algorithm was able to accurately predict patient-specific risk of clinical failure after ACLR. Clinicians and patients can use the web-based application during preoperative consultation to understand individual prediction outcomes.

Host genetic variation and specialized metabolites from wheat leaves enriches for phyllosphere Pseudomonas spp. with enriched antibiotic resistomes.

Antibiotic resistance in plant-associated microbiomes poses significant risks for agricultural ecosystems and human health. Although accumulating evidence suggests a role for plant genotypes in shaping their microbiome, almost nothing is known about how the changes of plant genetic information affect the co-evolved plant microbiome carrying antibiotic resistance genes (ARGs). Here, we selected 16 wheat cultivars and experimentally explored the impact of host genetic variation on phyllosphere microbiome, ARGs, and metabolites. Our results demonstrated that host genetic variation significantly influenced the phyllosphere resistomes. Wheat genotypes exhibiting high phyllosphere ARGs were linked to elevated Pseudomonas populations, along with increased abundances of Pseudomonas aeruginosa biofilm formation genes. Further analysis of 350 Pseudomonas spp. genomes from diverse habitats at a global scale revealed that nearly all strains possess multiple ARGs, virulence factor genes (VFGs), and mobile genetic elements (MGEs) on their genomes, albeit with lower nucleotide diversity compared to other species. These findings suggested that the proliferation of Pseudomonas spp. in the phyllosphere significantly contributed to antibiotic resistance. We further observed direct links between the upregulated leaf metabolite DIMBOA-Glc, Pseudomonas spp., and enrichment of phyllosphere ARGs, which were corroborated by microcosm experiments demonstrating that DIMBOA-Glc significantly enhanced the relative abundance of Pseudomonas spp. Overall, alterations in leaf metabolites resulting from genetic variation throughout plant evolution may drive the development of highly specialized microbial communities capable of enriching phyllosphere ARGs. This study enhances our understanding of how plants actively shape microbial communities and clarifies the impact of host genetic variation on the plant resistomes.

Effects of heavy metal and disinfectant on antibiotic resistance genes and virulence factor genes in the plastisphere from diverse soil ecosystems.

Antibiotic-resistance genes (ARGs) are world-wide contaminants posing potential health risks. Quaternary ammonium compounds (QACs) and heavy metals can apply selective pressure on antibiotic resistance. However, there is a lack of evidence regarding their coupled effect on changes in ARGs and virulence factor genes (VFGs) in various soil types and their plastispheres. Herein, we conducted a microcosm experiment to explore the abundances and profiles of ARGs and VFGs in soil plastispheres from three distinct types of soils amended with Cu and disinfectants. The plastispheres enriched the ARGs' abundance compared to soils and stimulated the coupling effect of combined pollutants on promoting the abundances of ARGs and VFGs. Horizontal gene transfer inevitably accelerates the propagation of ARGs and VFGs in plastispheres under pollutant stress. In plastispheres, combined exposure to disinfectants and Cu increased some potential pathogens' relative abundances. Moreover, the combined effect of disinfectants and Cu on ARGs and VFGs changed with soil type in plastispheres, emphasising the necessity to incorporate soil type considerations into health risk assessments for ARGs and VFGs. Overall, this study highlights the high health risks of ARGs under the selective pressure of combined pollutants in plastispheres and provides valuable insights for future risk assessments related to antibiotic resistance.

Selective enrichment of virulence factor genes in the plastisphere under antibiotic and heavy metal pressures.

The growing accumulation of plastic waste in the environment has created novel habitats known as the "plastisphere", where microorganisms can thrive. Concerns are rising about the potential for pathogenic microorganisms to proliferate in the plastisphere, posing risks to human health. However, our knowledge regarding the virulence and pathogenic potential of these microorganisms in the plastisphere remains limited. This study quantified the abundance of virulence factor genes (VFGs) in the plastisphere and its surrounding environments (water and soil) to better assess pathogenic risks. Our findings revealed a selective enrichment of VFGs in the plastisphere, which were attributed to the specific microbial community assembled. The presence of arsenic and ciprofloxacin in the plastisphere exerted additional co-selective pressures, intensifying the enrichment of VFGs. Notably, VFGs that encoded multiple functions or enhanced the survival of host microorganisms (e.g., encoding adherence functions) tended to accumulate in the plastisphere. These versatile and environmentally adaptable VFGs are more likely to be favored by bacteria in the environment, warranting increased attention in future investigations due to their potential for widespread dissemination. In terms of virulence and pathogenicity, this research offers new insights into evaluating pathogen-related risks in the plastisphere.

The pH-specific response of soil resistome to triclocarban and arsenic co-contamination.

Heavy metals as well as disinfectants affect the spread of antibiotic resistance genes (ARGs) in soil microbes, however, their cumulative impacts on the proliferation of ARGs are not well studied. In addition, both the chemical stability/availability and ARG profiles are affected by the soil pH, but it has never been considered in the systematic evaluation of soil resistome. In the present study, a microcosm experiment was conducted to study the combined effects of arsenic and triclocarban on the resistome in soil samples with variable pH (pH 4-7). The simultaneous additions of arsenic and triclocarban increase the ARG abundance at pH > 6, because of the intensive co-selective pressures triggered by the increase in concentrations of available arsenic and triclocarban. The occurrence of multidrug ARGs increases with the addition of arsenic and triclocarban, due to the preferred selection of their functional flexibility. The presence of arsenic and triclocarban is strongly related to the spread of MGEs affecting the soil resistome. Furthermore, pH alters the patterns of microbial inhabitants, increasing the relative abundance of Bacteroidota and Proteobacteria and contributing to the prevalence of tetracycline and sulfonamide ARGs at neutral pH. These findings have insight that the effects of arsenic and triclocarban co-contamination on the soil antibiotic resistome is pH dependent.

Exosomes Derived From Kartogenin-Preconditioned Mesenchymal Stem Cells Promote Cartilage Formation and Collagen Maturation for Enthesis Regeneration in a Rat Model of Chronic Rotator Cuff Tear.

BACKGROUND: Poor tendon-to-bone healing in chronic rotator cuff tears (RCTs) is related to unsatisfactory outcomes. Exosomes derived from mesenchymal stem cells reportedly enhance rotator cuff healing. However, the difficulty in producing exosomes with a stronger effect on enthesis regeneration must be resolved. PURPOSE: To study the effect of exosomes derived from kartogenin (KGN)-preconditioned human bone marrow mesenchymal stem cells (KGN-Exos) on tendon-to-bone healing in a rat model of chronic RCT. STUDY DESIGN: Controlled laboratory study. METHODS: Exosome-loaded sodium alginate hydrogel (SAH) was prepared. Moreover, exosomes were labeled with 1,1'-dioctadecyl-3,3,3',3'-tetramethylindotricarbocyanine iodide (DiR) or 1,1'-dioctadecyl-3,3,3'3'-tetramethylindocarbocyanine perchlorate (Dil) for in vivo tracking. Bilateral rotator cuff repair (RCR) was conducted in an established chronic RCT rat model. A total of 66 rats were randomized to control, untreated exosome (un-Exos), and KGN-Exos groups to receive local injections of pure SAH, un-Exos, or KGN-Exos SAH at the repaired site. The presence of DiR/Dil-labeled exosomes was assessed at 1 day and 1 week, and tendon-to-bone healing was evaluated histologically, immunohistochemically, and biomechanically at 4 and 8 weeks. RESULTS: Both un-Exos and KGN-Exos exhibited sustained release from SAH for up to 96 hours. In vivo study revealed that un-Exos and KGN-Exos were localized to the repaired site at 1 week. Moreover, the KGN-Exos group showed a higher histological score and increased glycosaminoglycan and collagen II expression at 4 and 8 weeks. In addition, more mature and better-organized collagen fibers with higher ratios of collagen I to collagen III were observed at 8 weeks in the tendon-to-bone interface compared with those in the control and un-Exos groups. Biomechanically, the KGN-Exos group had the highest failure load (28.12 ± 2.40 N) and stiffness (28.57 ± 2.49 N/mm) among the 3 groups at 8 weeks. CONCLUSION: Local injection of SAH with sustained KGN-Exos release could effectively promote cartilage formation as well as collagen maturation and organization for enthesis regeneration, contributing to enhanced biomechanical properties after RCR. CLINICAL RELEVANCE: KGN-Exos injection may be used as a cell-free therapeutic option to accelerate tendon-to-bone healing in chronic RCT.

Constructing high-strength nano-micro fibrous woven scaffolds with native-like anisotropic structure and immunoregulatory function for tendon repair and regeneration.

Tendon injuries are common debilitating musculoskeletal diseases with high treatment expenditure in sports medicine. The development of tendon-biomimetic scaffolds may be promising for improving the unsatisfactory clinical outcomes of traditional therapies. In this study, we combined an advanced electrospun nanofiber yarn-generating technique with a traditional textile manufacturing strategy to fabricate innovative nano-micro fibrous woven scaffolds with tendon-like anisotropic structure and high-strength mechanical properties for the treatment of large-size tendon injury. Electrospun nanofiber yarns made from pure poly L-lactic acid (PLLA) or silk fibroin (SF)/PLLA blend were fabricated, and their mechanical properties matched and even exceeded those of commercial PLLA microfiber yarns. The PLLA or SF/PLLA nanofiber yarns were then employed as weft yarns interlaced with commercial PLLA microfiber yarns as warp yarns to generate two new types of nanofibrous scaffolds (nmPLLA and nmSF/PLLA) with a plain-weaving structure. Woven scaffolds made from pure PLLA microfiber yarns (both weft and warp directions) (mmPLLA) were used as controls.In vitroexperiments showed that the nmSF/PLLA woven scaffold with aligned fibrous topography significantly promoted cell adhesion, elongation, proliferation, and phenotypic maintenance of tenocytes compared with mmPLLA and nmPLLA woven scaffolds. Moreover, the nmSF/PLLA woven scaffold exhibited the strongest immunoregulatory functions and effectively modulated macrophages towards the M2 phenotype.In vivoexperiments revealed that the nmSF/PLLA woven scaffold notably facilitated Achilles tendon regeneration with improved structure by macroscopic, histological, and ultrastructural observations six months after surgery, compared with the other two groups. More importantly, the regenerated tissue in the nmSF/PLLA group had excellent biomechanical properties comparable to those of the native tendon. Overall, our study provides an innovative biological-free strategy with ready-to-use features, which presents great potential for clinical translation for damaged tendon repair.

Predicting the Objective and Subjective Clinical Outcomes of Anterior Cruciate Ligament Reconstruction: A Machine Learning Analysis of 432 Patients.

BACKGROUND: Sports levels, baseline patient-reported outcome measures (PROMs), and surgical procedures are correlated with the outcomes of anterior cruciate ligament reconstruction (ACLR). Machine learning may be superior to conventional statistical methods in making repeatable and accurate predictions. PURPOSE: To identify the best-performing machine learning models for predicting the objective and subjective clinical outcomes of ACLR and to determine the most important predictors. STUDY DESIGN: Case-control study; Level of evidence, 3. METHODS: A total of 432 patients who underwent anatomic double-bundle ACLR with hamstring tendon autograft between January 2010 and February 2019 were included in the machine learning analysis. A total of 15 predictive variables and 6 outcome variables were selected to validate the logistic regression, Gaussian naïve Bayes machine, random forest, Extreme Gradient Boosting (XGBoost), isotonically calibrated XGBoost, and sigmoid calibrated XGBoost models. For each clinical outcome, the best-performing model was determined using the area under the receiver operating characteristic curve (AUC), whereas the importance and direction of each predictive variable were demonstrated in a Shapley Additive Explanations summary plot. RESULTS: The AUC and accuracy of the best-performing model, respectively, were 0.944 (excellent) and 98.6% for graft failure; 0.920 (excellent) and 91.4% for residual laxity; 0.930 (excellent) and 91.0% for failure to achieve the minimal clinically important difference (MCID) of the Lysholm score; 0.942 (excellent) and 95.1% for failure to achieve the MCID of the International Knee Documentation Committee (IKDC) score; 0.773 (fair) and 70.5% for return to preinjury sports; and 0.777 (fair) and 69.2% for return to pivoting sports. Medial meniscal resection, participation in competitive sports, and steep posterior tibial slope were top predictors of graft failure, whereas high-grade preoperative knee laxity, long follow-up period, and participation in competitive sports were top predictors of residual laxity. High preoperative Lysholm and IKDC scores were highly predictive of not achieving the MCIDs of PROMs. Young age, male sex, high preoperative IKDC score, and large graft diameter were important predictors of return to preinjury or pivoting sports. CONCLUSION: Machine learning analysis can provide reliable predictions for the objective and subjective clinical outcomes (graft failure, residual laxity, PROMs, and return to sports) of ACLR. Patient-specific evaluation and decision making are recommended before and after surgery.

Biomechanical and Histological Results of Dual-Suspensory Reconstruction Using Banded Tendon Graft to Bridge Massive Rotator Cuff Tears in a Chronic Rabbit Model.

BACKGROUND: Bridging rotator cuff tendon defects with a patch is a reasonable treatment for massive rotator cuff tears (MRCTs). However, the poor outcomes associated with routine patch repair have prompted exploration into superior bridging techniques and graft structures. PURPOSE: To detect whether dual-suspensory reconstruction using a banded graft would be superior to routine bridging using a patch graft to treat MRCTs and to detect the comparative effectiveness of patellar tendon (PT) and fascia lata (FL) grafts in dual-suspensory reconstruction. STUDY DESIGN: Controlled laboratory study. METHODS: Unilateral chronic MRCTs were created in 72 mature male New Zealand White rabbits, which were randomly divided into 3 groups: (1) patch bridging repair using rectangular FL autograft (PR-FL), (2) dual-suspensory bridging reconstruction using banded FL autograft (DSR-FL), and (3) dual-suspensory bridging reconstruction using banded PT autograft (DSR-PT). In each group, the mean failure load and stiffness of the cuff-graft-humerus (C-G-H) complexes of 6-week and 12-week specimens were recorded, with the failure modes and sites noted. Moreover, cuff-to-graft and graft-to-bone interface healing and graft substance remodeling of the complexes were histologically evaluated (via hematoxylin and eosin, Picrosirius red, Masson trichrome, and Safranin O/fast green staining) at 6 and 12 weeks to assess integrations between the bridging constructs and the native bone or rotator cuff tendons. RESULTS: The DSR-PT group had the greatest mean failure loads and stiffness of the C-G-H complexes at 6 and 12 weeks (41.81 ± 7.00 N, 10.34 ± 2.68 N/mm; 87.62 ± 9.20 N, 17.98 ± 1.57 N/mm, respectively), followed by the DSR-FL group (32.04 ± 5.49 N, 8.20 ± 2.27 N/mm; 75.30 ± 7.31 N, 14.39 ± 3.29 N/mm, respectively). In the DSR-PT and DSR-FL groups, fewer specimens failed at the graft-to-bone junction and more failed at the cuff-to-graft junction, but both groups had higher median failure loads at 6 and 12 weeks (DSR-PT: cuff-to-graft junction, 37.80 and 83.76 N; graft-to-bone junction, 45.46 and 95.86 N) (DSR-FL: cuff-to-graft junction, 28.52 and 67.68 N; graft-to-bone junction, 37.92 and 82.18 N) compared with PR-FL (cuff-to-graft junction, 27.17 and 60.04 N; graft-to-bone junction, 30.12 and 55.95 N). At 12 weeks, the DSR-FL group had higher median failure loads at graft substance (72.26 N) than the PR-FL group (61.27 N). Moreover, the PR-FL group showed more inflammatory responses at the 2 healing interfaces and the graft substance in the 6-week specimens and subsequently displayed poorer interface healing (assessed via collagen organization, collagen maturity, and fibrocartilage regeneration) and graft substance remodeling (assessed via collagen organization and maturity) in 12-week specimens compared with the DSR-PT and DSR-FL groups. Superior interface healing and substance remodeling processes were observed in the DSR-PT group compared with the DSR-FL group. CONCLUSION: When compared with routine patch repair, the dual-suspensory reconstructions optimized biomechanical properties and improved interface healing and graft substance remodeling for bridging MRCTs. Furthermore, the dual-suspensory technique using the PT graft presented superior histological and biomechanical characteristics than that using FL. CLINICAL RELEVANCE: The dual-suspensory reconstruction technique using banded tendon grafts may enhance bridging constructs for MRCTs in humans, warranting further investigations of clinical outcomes.

Infrapatellar Fat Pad Mesenchymal Stromal Cell-Derived Exosomes Accelerate Tendon-Bone Healing and Intra-articular Graft Remodeling After Anterior Cruciate Ligament Reconstruction.

BACKGROUND: Exosomes derived from mesenchymal stromal cells (MSCs) reportedly enhance the healing process. However, no studies have investigated the effect of exosomes from infrapatellar fat pad (IPFP) MSCs on tendon-bone healing and intra-articular graft remodeling after anterior cruciate ligament reconstruction (ACLR). PURPOSE: To evaluate the in vivo effect of exosomes from IPFP MSCs on tendon-bone healing and intra-articular graft remodeling in a rat model of ACLR. STUDY DESIGN: Controlled laboratory study. METHODS: A total of 90 skeletally mature male Sprague Dawley rats underwent unilateral ACLR using an autograft. All rats were randomly divided into 3 groups: sham injection (SI) group (n = 30), control injection (CI) group (n = 30), and IPFP MSC-derived exosome injection (IMEI) group (n = 30). At 2, 4, and 8 weeks postoperatively, tendon-bone healing and intra-articular graft remodeling were evaluated via biomechanical testing, micro-computed tomography, and histological analysis; macrophage polarization was evaluated using immunohistochemical staining. RESULTS: Biomechanical testing demonstrated a significantly higher failure load and stiffness in the IMEI group than in the SI and CI groups at 4 and 8 weeks postoperatively. Moreover, a thinner graft-to-bone healing interface with more fibrocartilage was observed in the IMEI group at both time points. Micro-computed tomography revealed greater new bone ingrowth in the IMEI group than in the other groups, as demonstrated by smaller mean bone tunnel areas and a larger bone volume/total volume ratio. Additionally, more cellular infiltration was observed in the intra-articular graft in the IMEI group than in the other groups at 4 weeks, followed by more regularly organized fibers with mature collagen at 8 weeks. Notably, similar trends of macrophage polarization were found at both the graft-to-bone interface and the intra-articular graft in the IMEI group, with significantly fewer proinflammatory M1 macrophages and larger numbers of reparative M2 macrophages than in the SI and CI groups. CONCLUSION: IPFP MSC-derived exosomes accelerated tendon-bone healing and intra-articular graft remodeling after ACLR, which may have resulted from the immunomodulation of macrophage polarization. CLINICAL RELEVANCE: The IPFP can be easily harvested by most orthopaedic surgeons. Exosomes from IPFP MSCs, constituting a newly emerging cell-free approach, may represent a treatment option for improving tendon-bone healing and intra-articular graft remodeling after ACLR.

Fine-grained classification based on multi-scale pyramid convolution networks.

The large intra-class variance and small inter-class variance are the key factor affecting fine-grained image classification. Recently, some algorithms have been more accurate and efficient. However, these methods ignore the multi-scale information of the network, resulting in insufficient ability to capture subtle changes. To solve this problem, a weakly supervised fine-grained classification network based on multi-scale pyramid is proposed in this paper. It uses pyramid convolution kernel to replace ordinary convolution kernel in residual network, which can expand the receptive field of the convolution kernel and use complementary information of different scales. Meanwhile, the weakly supervised data augmentation network (WS-DAN) is used to prevent over fitting and improve the performance of the model. In addition, a new attention module, which includes spatial attention and channel attention, is introduced to pay more attention to the object part in the image. The comprehensive experiments are carried out on three public benchmarks. It shows that the proposed method can extract subtle feature and achieve classification effectively.

HOTAIR Promotes Cisplatin Resistance of Osteosarcoma Cells by Regulating Cell Proliferation, Invasion, and Apoptosis via miR-106a-5p/STAT3 Axis.

Osteosarcoma (OS) is a common primary malignant bone tumor among adolescences, and the emergence of multidrug resistance poses a huge challenge for clinical treatment of OS. LncRNA HOTAIR (HOX antisense intergenic RNA) has been reported to be associated with many malignancies, including OS. However, the underlying mechanisms of HOTAIR involved in drug resistance in OS are obscure. Our study showed that HOTAIR was upregulated in cisplatin (DDP)-resistant OS tissues and cells. HOTAIR knockdown decreased the DDP resistance, drug resistance-related gene expression, cell proliferation, and invasion and promoted apoptosis of Saos2/DDP, MG-63/DDP, and U2OS/DDP cells. Mechanism researches displayed that miR-106a-5p was downregulated in DDP-resistant OS tissues and cells. MiR-106a-5p directly bound with HOTAIR and was regulated by HOTAIR. Moreover, STAT3 was inhibited by miR-106a-5p at a post-transcriptional level, and the transfection of miR-106a-5p reversed the upregulation of STAT3 caused by HOTAIR overexpression. The increase or decrease of miR-106a-5p suppressed the effect of HOTAIR upregulation or downregulation on DDP resistance, cell proliferation, invasion, and apoptosis of Saos2/DDP, MG-63/DDP, and U2OS/DDP cells. What's more, the transfection of STAT3 siRNA reversed the decrease of DDP resistance, cell proliferation, and invasion and rescued the increase of apoptosis induced by miR-106a-5p inhibition. These data suggested that HOTAIR enhanced DDP resistance of Saos2/DDP, MG-63/DDP, and U2OS/DDP cells by affecting cell proliferation, invasion, and apoptosis via miR-106a-5p/STAT3 axis.

Evolutionary extreme learning machine with sparse cost matrix for imbalanced learning.

Extreme learning machine is a popular machine learning technique for single hidden layer feed-forward neural network. However, due to the assumption of equal misclassification cost, the conventional extreme learning machine fails to properly learn the characteristics of the data with skewed category distribution. In this paper, to enhance the representation of few-shot cases, we break down that assumption by assigning penalty factors to different classes, and minimizing the cumulative classification cost. To this end, a case-weighting extreme learning machine is developed on a sparse cost matrix with a diagonal form. To be more actionable, we formulate a multi-objective optimization with respect to penalty factors, and optimize this problem using an evolutionary algorithm combined with an error bound model. By doing so, this proposed method is developed into an adaptive cost-sensitive learning, which is guided by the relation between the generalization ability and the case-weighting factors. In a broad experimental study, our method achieves competitive results on benchmark and real-world datasets for software bug reports identification.

Knockdown of HOXB8 inhibits tumor growth and metastasis by the inactivation of Wnt/ß-catenin signaling pathway in osteosarcoma.

Homeobox B8 (HOXB8) is a member of HOX family and was reported to be dysregulated in human cancers. However, its expression pattern and function in human osteosarcoma (OS) remain unknown. The aim of the current study is to examine its expression and biological roles in human OS cells. Our results showed that HOXB8 was highly expressed in human OS tissues and cell lines. Knockdown of HOXB8 significantly suppressed the proliferation of OS cells in vitro and attenuated the tumor growth in a tumor xenograft model. In addition, knockdown of HOXB8 dramatically repressed the migration and invasion of OS cells. Furthermore, knockdown of HOXB8 efficiently prevented the activation of Wnt/ß-catenin signaling pathway in OS cells. In conclusion, the findings of the present study demonstrated that knockdown of HOXB8 could suppress tumorigenesis and metastasis in OS through regulation of the Wnt/ß-catenin signaling pathway. Thus, HOXB8 may represent a novel therapeutic target for the treatment of OS.

Effects of TLR-2/NF-κB signaling pathway on the occurrence of degenerative knee osteoarthritis: an in vivo and in vitro study.

The study aims to explore the effects of TLR-2/NF-κB signaling pathway on the occurrence of degenerative knee osteoarthritis (OA). Degenerative knee OA and normal cartilage samples were collected from patients with degenerative knee OA receiving total knee arthroplasty and amputation. Expressions of TLR-2, NF-κB and MMP-13 were determined by qRT-PCR and immunochemistry. The chondrocytes were divided into control, IL-1ß, IL-1ß + anti-TLR-2 and IL-1ß + PDTC groups. MTT assay and flow cytometry were performed to determine proliferation and apoptosis of the chondrocytes. Expressions of TLR-2, NF-κB and MMP-13 were measured by Western blotting. ELISA was conducted to detect the expressions of related inflammatory factors. The positive expressions of TLR, NF-κB and MMP13 were associated with body mass index (BMI), family history, exercise, and WOMAC scores of OA patients. Logistic regression analysis showed that OA influencing factors were TLR, NF-κB, MMP13, BMI, family history and exercise. Compared with normal chondrocytes, the expressions of TLR-2, NF-κB, MMP-13 and related inflammatory factors increased in degenerative knee OA. The chondrocytes in the IL-1ß + anti-TLR-2 and IL-1ß + PDTC groups showed lower apoptosis rates than those in the IL-1ß group. Compared with the control group, increased expressions of TLR-2, NF-κB, phosphorylated-NF-κB (p-NF-κB), MMP-13, IL-1, IL-6 and TNF-α were found in the IL-1ß group. In the IL-1ß + anti-TLR-2 and IL-1ß + PDTC groups, decreased expressions of NF-κB, p-NF-κB, MMP-13, IL-1, IL-6 and TNF-α were found compared with those in the IL-1ß group. TLR-2/NF-κB signaling pathway contributes to the occurrence of degenerative knee OA.