Explore the vast range of titles available.

This paper proposes a single-step reliability-based optimization framework for the design of Visco-Frictional Multiple Tuned Mass Dampers (VFMTMDs), which integrate both viscous and frictional damping mechanisms within a single device, unlike traditional approaches that consider only one type of damping. The proposed methodology simultaneously optimizes the number, placement, and mechanical parameters of VFMTMDs to minimize the probability of structural failure under seismic loading, explicitly accounting for the inherent uncertainties of ground motion. The optimization process employs the Circle-Inspired Optimization Algorithm (CIOA), a state-of-the-art metaheuristic developed by the authors. A ten-story benchmark building under seven actual seismic accelerograms served as a case study. The results of three independent optimization runs produced identical solutions, confirming the robustness and repeatability of the proposed approach. The optimal configuration consisted of two VFMTMDs installed on the top two floors, each with a mass ratio of only 1.5%. The optimized design achieved a 96.85% reduction in the probability of structural failure and a more than 35% increase in the seismic acceleration associated with the average fragility, demonstrating a substantial improvement in seismic reliability. Overall, the findings validate the proposed methodology as a robust and efficient framework for the optimal design of VFMTMDs, significantly enhancing the seismic performance of buildings in earthquake-prone regions.

Osteoarthritis is a degenerative joint disease for which there is yet to be a disease-modifying drug available in clinics. New drug candidates often fail due to a combination of poor pharmacokinetics as well as an inability to address the complex, multifactorial nature of osteoarthritis. To address these issues, we developed a zwitterionic poly-carboxybetaine acrylamide-dexamethasone (pCBAA-DEX) conjugate showing good cartilage penetration as well as anti-inflammatory and lubricating properties in previous in vitro studies. Here, we investigate the therapeutic potential of pCBAA-DEX in the collagenase-induced osteoarthritis (CIOA) model in rats. Upon induction of the model, animals received one-time, unilateral injections of either saline, DEX or pCBAA-DEX on day 4 ( N  = 8). On day 70, joint tissues were harvested and analyzed. While pCBAA-DEX achieved ~ 50% cartilage retention at the terminal timepoint, it did not prevent cartilage degeneration, synovial inflammation and synovial fibrosis, nor did DEX alone. Nevertheless, DEX and pCBAA-DEX slightly decreased the fibrosis levels in the synovium with DEX also decreasing the number of synovial lining layers. For the cartilage, DEX did not cause any notable differences, instead we observed an increase in cartilage degeneration in the pCBAA-DEX group. These findings challenge the previous in vitro results and motivate a substantial redesign of these conjugates and associated in vitro methods to reconsider them for the treatment of osteoarthritis.

Background The aim of this study was to provide an in-depth longitudinal locomotor and structural characterisation of the collagenase-induced osteoarthritis (CIOA) mouse model, using the most relevant and up-to-date non-invasive locomotor phenotyping and imaging methods. The ultimate goal of this study was to predict histological scores, the gold standard parameter in osteoarthritis (OA), based on locomotor or structural deficits. Methods The CIOA model was induced in C57BL/6 male mice, which were then maintained in their home cage with or without a running wheel for 6 weeks. Both global and fine locomotor effects were measured using the open field and Catwalk™ tests. Imaging of bone and cartilage was performed using either µCT, contrast-enhanced µCT or confocal laser scanning microscopy (CLSM) at different time points. Correlations between functional or structural changes and histological scores were sought in order to provide tools for predicting histological degradation. Results Locomotor deficits were observed at early time points (days 3 to 9) but did not persist to the end of the experiment. Signs of inflammation appeared as early as day 9. They worsened on day 28 as the disease progressed and meniscal calcifications were observed by µCT. The early functional and structural changes correlated with the histological scores measured post mortem and some specific locomotor or structural parameters were identified as predictors of histological changes. Free exercise (voluntary running wheel activity) did not seem to influence the severity of the observed changes. Conclusions Open-field quantification of kinetic parameters is a simple and timely relevant test to detect early locomotor changes and predict histological changes. Meniscal calcifications and osteophyte formation, which can be observed by µCT at early time points, are also highly predictive of OA severity. These two non-invasive techniques are very useful for longitudinal monitoring of mice and OA score prediction.

Predicting stock market behavior using sentiment analysis has become increasingly popular, as customer responses on platforms like Twitter can influence market trends. However, most existing sentiment-based models struggle with two major issues: inaccuracy and high complexity. These problems lead to frequent prediction errors and make the models difficult to implement in real-time trading systems. To address these challenges, this paper proposes a new method called Siagra-ConSA-HSOA (Siamese Graph Convolutional Split-Attention Network with NLP-based Social Sentiment Data). Two data sources feed the model: specifically, NIFTY-50 Stock Market and real-time Twitter sentiment. Through Natural Language Processing (NLP), the raw data is pre-processed and key features are extracted before they are fused into a unified dataset using a cross-domain transformer, namely CDSFT, and then Circle-Inspired Optimization Algorithm (CIOA) selects the most important features from this dataset. This decreases the complexity of the model without losing essential information. Finally, a Graph Convolutional Split-Attention Network (SGCSAN) for promisingly predicting whether the stock prices are going to hit the ground and fly high again or is going to nosedive with Humboldt Squid Optimization Algorithm (HSOA) is introduced to further improve accuracy with lesser error generation. The proposed model Siagra-ConSA-HSOA achieved 99.9% accuracy and 99.8% recall in the testing stage, meaning that such a model performs better than the current approaches both in prediction accuracy and efficiency. Thus, this is a glimmer that the model shall be able to overcome some of the main problems with the current techniques used in predicting the behavior of the stock market.GitHub Repository: https://github.com/jramans2/Siamese-GCN-SplitAttention-Stock-Prediction.git

An adnexal mass, also known as a pelvic mass, is a growth that develops in or near the uterus, ovaries, fallopian tubes, and supporting tissues. For women suspected of having ovarian cancer, timely and accurate detection of a malignant pelvic mass is crucial for effective triage, referral, and follow-up therapy. While various deep learning techniques have been proposed for identifying pelvic masses, current methods are often not accurate enough and can be computationally intensive. To address these issues, this manuscript introduces an optimized Siamese circle-inspired neural network with deep linear graph attention (SCINN-DLGN) model designed for pelvic mass classification. The SCINN-DLGN model is intended to classify pelvic masses into three categories: benign, malignant, and healthy. Initially, real-time MRI pelvic mass images undergo pre-processing using semantic-aware structure-preserving median morpho-filtering to enhance image quality. Following this, the region of interest (ROI) within the pelvic mass images is segmented using an EfficientNet-based U-Net framework, which reduces noise and improves the accuracy of segmentation. The segmented images are then analysed using the SCINN-DLGN model, which extracts geometric features from the ROI. These features are classified into benign, malignant, or healthy categories using a deep clustering algorithm integrated into the linear graph attention model. The proposed system is implemented on a Python platform, and its performance is evaluated using real-time MRI pelvic mass datasets. The SCINN-DLGN model achieves an impressive 99.9% accuracy and 99.8% recall, demonstrating superior efficiency compared to existing methods and highlighting its potential for further advancement in the field.

Evidence suggests that subchondral bone and whole joint structure features can be used as morphological markers associated with early-stage osteoarthritis (OA). A three-dimensional quantitative morphometric analysis (3D QMA) was previously established and demonstrated to reproducibly quantify subchondral bone and whole joint structure in small animal models. This work evaluates the reproducibility of this previously defined 3D QMA in a mouse model of OA and characterizes the osteoarthritic changes to subchondral bone and whole joint structure. Thirty-five male C57BL/10 mice aged 9 wk were recruited and divided evenly into 5 cross-sectional groups. Of these, 14 10-wk-old mice were assigned to disease groups and underwent intraarticular injection of collagenase (CIOA) on the right knee joint to induce OA in the right tibiofemoral joint, and isotonic saline injected into the left contralateral knee joint. Animals were sacrificed at 3 time points (0, 4, and 8 wk) and scanned ex vivo repeatedly for five times with micro-CT (microCT). 3D QMA was performed, including subchondral cortical and epiphyseal bone measures, osteophyte detection and tibiofemoral joint metrics. The scan–rescan reproducibility of 3D QMA was tested on repeated microCT scans. Excellent reproducibility was obtained for all 3D QMA parameters, with ICC ranging from 0.771 to 0.999. Pathological changes caused by CIOA were characterized by measures of bone morphometry, osteophyte presence, as well as whole joint structure. Mechanical malalignment of tibiofemoral joint was observed in osteoarthritic joints, along with larger joint space width, reduced bone volume fraction, trabecular thinning predominantly in the lateral compartment, and osteophyte formation on medial joint margins.

Injection of adipose-derived mesenchymal stromal cells (ASCs) into murine knee joints after induction of inflammatory collagenase-induced osteoarthritis (CiOA) reduces development of joint pathology. This protection is only achieved when ASCs are applied in early CiOA, which is characterized by synovitis and high S100A8/A9 and IL-1β levels, suggesting that inflammation is a prerequisite for the protective effect of ASCs. Our objective was to gain more insight into the interplay between synovitis and ASC-mediated amelioration of CiOA pathology. CiOA was induced by intra-articular collagenase injection. Knee joint sections were stained with hematoxylin/eosin and immunolocalization of polymorphonuclear cells (PMNs) and ASCs was performed using antibodies for NIMP-R14 and CD271, respectively. Chemokine expression induced by IL-1β or S100A8/A9 was assessed with qPCR and Luminex. ASC-PMN co-cultures were analyzed microscopically and with Luminex for inflammatory mediators. Migration of PMNs through transwell membranes toward conditioned medium of non-stimulated ASCs (ASC -CM) or IL-1β-stimulated ASCs (ASC -CM) was examined using flow cytometry. Phagocytic capacity of PMNs was measured with labeled zymosan particles. Intra-articular saline injection on day 7 of CiOA increased synovitis after 6 h, characterized by PMNs scattered throughout the joint cavity and the synovium. ASC injection resulted in comparable numbers of PMNs which clustered around ASCs in close interaction with the synovial lining. IL-1β-stimulation of ASCs strongly increased expression of PMN-attracting chemokines CXCL5, CXCL7, and KC, whereas S100A8/A9-stimulation did not. In agreement, the number of clustered PMNs per ASC was significantly increased after 6 h of co-culturing with IL-1β-stimulated ASCs. Also migration of PMNs toward ASC -CM was significantly enhanced (287%) when compared to ASC -CM. Interestingly, association of PMNs with ASCs significantly diminished KC protein release by ASCs (69% lower after 24 h), accompanied by reduced release of S100A8/A9 protein by the PMNs. Moreover, phagocytic capacity of PMNs was strongly enhanced after priming with ASC -CM. Local application of ASCs in inflamed CiOA knee joints results in clustering of attracted PMNs with ASCs in the synovium, which is likely mediated by IL-1β-induced up-regulation of chemokine release by ASCs. This results in enhanced phagocytic capacity of PMNs, enabling the clearance of debris to attenuate synovitis.

Tyrphostin AG490 is a Janus kinase (JAK) 2 inhibitor that is clinically used as an anticancer agent and is also effective in various models of inflammatory and autoimmune diseases. In this study, we examined the effects of tyrphostin AG490 on the development of collagenase-induced osteoarthritis (CIOA). Our results showed that tyrphostin-ameliorated cartilage and bone destructions. This effect was associated with decreased expression of signal transducers and activators of transcription 3 (STAT3), phosphorylated JAK2, Dickkopf homolog 1, and receptor activator of nuclear factor κB ligand (RANKL) in the joints of arthritic mice. Tyrphostin AG490 suppressed STAT3 phosphorylation and the expression of tumor necrosis factor-related apoptosis-inducing ligand and RANKL by synovial fluid cells. The drug inhibited RANKL-induced osteoclast differentiation in vitro . Molecules, such as tyrphostin AG490 that limit bone erosion and influence osteoclast generation, might have therapeutic utility in joint degenerative disorders.

The janus kinase (JAK)-signal transducer and activator of transcription (STAT) cascade plays a principal role in the signaling of a vast array of cytokines and growth factors which stimulates diverse cellular functions and immune responses. Osteoarthritis (OA) is the most common joint disease in the adult population. The present study was designed to evaluate the effects of tyrosine kinase inhibitor, tyrphostin AG490 in a mouse model of collagenase-induced osteoarthritis (CIOA). CIOA was provoked by two intraarticular (i.a.) injections of collagenase in mice and intraperitoneally (i.p.) treated with AG490 at a dose of 5 mg/kg at days 0, 5 and 10 and at a dose of 8 mg/kg at day 18. The administration of AG490 in CIOA mice inhibited osteoclast generation in bone and the loss of glycosaminoglycans and proteoglycans in cartilage. Tyrphostin decreased the levels of IFN-γ, IL1, IL-6 and IL-17 in the synovial fluid (SF) dependant on the time post AG490 administration. Limited numbers of CD11b positive Ly6G neutrophils in blood and SF along with a decrease of F4/80 positive cells in synovial fluid (SF) were observed in tyrphostin AG490-treated arthritic mice. AG490 inhibited M-CSF+RANKL-induced cytokine production by bone marrow (BM) cells and the differentiation of BM cells in vitro. Because of the findings presented, we argue that tyrphostin AG490 may hold promising therapeutic potential against important clinical conditions such as osteoarthritis (OA).

Osteoarthritis (OA) is a multifactorial disease affecting both the cartilage and the subchondral bone. However, animal models of OA cannot represent both of the changes and show variations depending on induction methods and animal species/strains. This study first investigated subchondral bone changes and its correlation with cartilage degeneration in two different OA models in C57Bl/6 mice. Experimental OA was produced by type II collagenase-induced osteoarthritis (CIOA) and destabilization of the medial meniscus (DMM). The subchondral plate and trabecular bone of the tibia were analyzed by micro-computed tomography and cartilage degeneration was analyzed histologically after safranin-O staining at 2, 4, 6 and 8 weeks. In the DMM model, cartilage degeneration was induced reproducibly and progressively with time. Progressive increase in subchondral bone volume, but not in bone thickness, was also observed in both subchondral bone plate and subchondral trabecular bone in the medial tibial area. The changes in subchondral bone volume correlated well with the histological cartilage degeneration (R2=0.7870). In contrast, in the CIOA model, cartilage degeneration was relatively unstable, increasing only until 4 weeks and decreasing thereafter. No significant changes in subchondral bone were observed in all areas at all time points. These results suggest that the DMM OA mouse model is more reliable and useful than the CIOA model by virtue of its better representation of cartilage degeneration and subchondral bone change with high correlation coefficient.