Underwater Intention Recognition using Head Motion and Throat Vibration for Supernumerary Robotic Assistance

This study presents a multi-modal mechanism for recognizing human intentions while diving underwater, aiming to achieve natural human-robot interactions through an underwater superlimb for diving assistance. The underwater environment severely limits the divers' capabilities in intention expression, which becomes more challenging when they intend to operate tools while keeping control of body postures in 3D with the various diving suits and gears. The current literature is limited in underwater intention recognition, impeding the development of intelligent wearable systems for human-robot interactions underwater. Here, we present a novel solution to simultaneously detect head motion and throat vibrations under the water in a compact, wearable design. Experiment results show that using machine learning algorithms, we achieved high performance in integrating these two modalities to translate human intentions to robot control commands for an underwater superlimb system. This study's results paved the way for future development in underwater intention recognition and underwater human-robot interactions with supernumerary support.Comment: 6 pages, 9 figures, 3 tables, accepted to IEEE CASE 202

Heat Shock Protein 90 Family Isoforms as Prognostic Biomarkers and Their Correlations with Immune Infiltration in Breast Cancer

Background. The heat shock protein 90 (HSP90s) family is composed of molecular chaperones composed of four isoforms in humans, which has been widely reported as unregulated in various kinds of cancers. Nevertheless, the role of each HSP90s isoform in prognosis and immune infiltration in distinct subtypes of breast cancer (BRAC) remains unclear. Methods. Public online databases including the Oncomine, UALCAN, Kaplan-Meier Plotter, Tumor IMmune Estimation Resource (TIMER), Gene Expression Profiling Interactive Analysis (GEPIA), GeneMANIA, and Database for Annotation, Visualization, and Integrated Discovery (DAVID) were integrated to perform bioinformatic analyses and to explore the possible associations among HSP90s gene expression, prognosis, and immune infiltration in BRAC. Results. The mRNA expression of all HSP90s members was elevated in distinct clinical stages and subtypes of BRAC, compared with the normal breast tissue (P<0.05). Overexpressed HSP90AA1 was associated with poor prognosis, particularly, both short overall survival (OS) and release-free survival (RFS) in Basal-like BRAC patients; overexpressed HSP90AB1 and HSP90B1 were both associated with poor RFS in Luminal A BRAC patients, while overexpressed TRAP1 was associated with favorable RFS in Luminal A BRAC patients. Moreover, HSP90s gene expression in BRAC showed correlations with the infiltration of CD8+ T cells, neutrophils, macrophages, and dendritic cells (DCs), as well as the activation of tumor-associated macrophages (TAMs), DCs, and CD4+ helper T (Th) cells. The underlying mechanisms of HSP90s modulating tumor-infiltrating immune cells (TIICs) might be related with their functions in antigen processing and presentation, major histocompatibility complex (MHC) binding, and assisting client proteins. Conclusion. This study demonstrated that HSP90s family genes were overexpressed and might be serve as prognostic biomarkers in subtypes of BRAC. It might be a novel breakthrough point of BRAC treatment to regulate immune infiltration in BRAC microenvironment for more effective anticancer immunity through pharmacological intervention of HSP90s

NMR-Based Metabonomic Study Reveals Intervention Effects of Polydatin on Potassium Oxonate-Induced Hyperuricemia in Rats

Previous studies have disclosed the antihyperuricemic effect of polydatin, a natural precursor of resveratrol; however, the mechanisms of action still remain elusive. The present study was undertaken to evaluate the therapeutic effects and the underlying mechanisms of polydatin on potassium oxonate-induced hyperuricemia in rats through metabonomic technology from a holistic view. Nuclear magnetic resonance (NMR) spectroscopy was applied to capture the metabolic changes in sera and urine collected from rats induced by hyperuricemia and polydatin treatment. With multivariate data analysis, significant metabolic perturbations were observed in hyperuricemic rats compared with the healthy controls. A total of eleven and six metabolites were identified as differential metabolites related to hyperuricemia in serum and urine of rats, respectively. The proposed pathways primarily included branched-chain amino acid (BCAA) metabolism, glycolysis, the tricarboxylic acid cycle, synthesis and degradation of ketone bodies, purine metabolism, and intestinal microflora metabolism. Additionally, some metabolites indicated the risk of renal injury induced by hyperuricemia. Polydatin significantly lowered the levels of serum uric acid, creatinine, and blood urea nitrogen and alleviated the abnormal metabolic status in hyperuricemic rats by partially restoring the balance of the perturbed metabolic pathways. Our findings shed light on the understanding of the pathophysiological process of hyperuricemia and provided a reference for revealing the metabolic mechanism produced by polydatin in the treatment of hyperuricemia

Malposition is main cause of failure of Oxford mobile-bearing medial unicompartmental knee arthroplasty: a retrospective study with minimum five-year follow-up

Aims: Unicompartmental knee arthroplasty (UKA) is the preferred treatment for anterior medial knee osteoarthritis (OA) owing to the rapid postoperative recovery. However, the risk factors for UKA failure remain controversial. Methods: The clinical data of Oxford mobile-bearing UKAs performed between 2011 and 2017 with a minimum follow-up of five years were retrospectively analyzed. Demographic, surgical, and follow-up data were collected. The Cox proportional hazards model was used to identify the risk factors that contribute to UKA failure. Kaplan-Meier survival was used to compare the effect of the prosthesis position on UKA survival. Results: A total of 407 patients who underwent UKA were included in the study. The mean age of patients was 61.8 years, and the mean follow-up period of the patients was 91.7 months. The mean Knee Society Score (KSS) preoperatively and at the last follow-up were 64.2 and 89.7, respectively (p = 0.001). Overall, 28 patients (6.9%) with UKA underwent revision due to prosthesis loosening (16 patients), dislocation (eight patients), and persistent pain (four patients). Cox proportional hazards model analysis identified malposition of the prostheses as a high-risk factor for UKA failure (p = 0.007). Kaplan-Meier analysis revealed that the five-year survival rate of the group with malposition was 85.1%, which was significantly lower than that of the group with normal position (96.2%; p < 0.001). Conclusion: UKA constitutes an effective method for treating anteromedial knee OA, with an excellent five-year survival rate. Aseptic loosening caused by prosthesis malposition was identified as the main cause of UKA failure. Surgeons should pay close attention to prevent the potential occurrence of this problem. Cite this article: Bone Jt Open 2023;4(12):914–922

Predicting neighborhood-level residential carbon emissions from Street View images using computer vision and machine learning

Predicting urban-scale carbon emissions (CEs) is crucial in drawing implications for various urgent environmental issues, including global warming. However, prior studies have overlooked the impact of the micro-level street environment, which might lead to biased prediction. To fill this gap, we developed an effective machine learning (ML) framework to predict neighborhood-level residential CEs based on a single data source, street view images (SVIs), which are publicly available worldwide. Specifically, more than 30 streetscape elements were classified from SVIs using semantic segmentation to describe the micro-level street environment, whose visual features can indicate major socioeconomic activities that significantly affect residential CEs. A ten-fold cross-validation was deployed to train ML models to predict the residential CEs at the 1 km grid level. We found, first, that random forest (R2 = 0.8) outperforms many traditional models, confirming that visual features are non-negligible in explaining CEs. Second, more building, wall, and fence views indicate higher CEs. Third, the presence of trees and grass is inversely related to CEs. Our findings justify the feasibility of using SVIs as a single data source to effectively predict neighborhood-level residential CEs. The framework is applicable to large regions across diverse urban forms, informing urban planners of sustainable urban form strategies to achieve carbon-neutral goals, especially for the development of new towns

Responses of Digestive, Antioxidant, Immunological and Metabolic Enzymes in the Intestines and Liver of Largemouth Bass (<i>Micropterus salmoides</i>) under the Biofloc Model

To investigate the activities of intestinal digestive enzymes, liver antioxidant enzymes, immunological enzymes, and glucometabolic enzymes in largemouth bass (Micropterus salmoides) under the biofloc model, an experiment was conducted in 300-liter glass tanks. The experiment comprised a control group, which was fed a basal diet, and a biofloc group, where glucose was added to maintain a C/N ratio of 15. Each group had three parallel setups, with a stocking density of 20 fish per tank. The experiment ran for 60 days, employing a zero-water exchange aquaculture model. The results showed that at the end of the culture period, there were no significant differences between the initial weight, final weight, WGR, SGR, and SR of the biofloc group and the control group of largemouth bass (p > 0.05), whereas the lower FCR and the higher PER in the biofloc group were significant (p p p p p p < 0.05). The study showed that the biofloc model of culturing largemouth bass can not only enhance digestive enzyme activities, antioxidant capacity, and immune response but can also promote the process of glucose metabolism and reduce feeding costs. This study provides data support for healthy culturing of largemouth bass in future production, provides a theoretical reference for optimizing the biofloc technology culture model, and is crucial for promoting the healthy and green development of aquaculture

Synergistic effects of immunoregulation and osteoinduction of ds-block elements on titanium surface

Ds-block elements have been gaining increasing attention in the field of biomaterials modification, owing to their excellent biological properties, such as antibiosis, osteogenesis, etc. However, their function mechanisms are not well understood and conflicting conclusions were drawn by previous studies on this issue, which are mainly resulted from the inconsistent experimental conditions. In this work, three most widely used ds-block elements, copper, zinc, and silver were introduced on titanium substrate by plasma immersion ion implantation method to investigate the rule of ds-block elements in the immune responses. Results showed that the implanted samples could decrease the inflammatory responses compared with Ti sample. The trend of anti-inflammatory effects of macrophages on samples was in correlation with cellular ROS levels, which was induced by the implanted biomaterials and positively correlated with the number of valence electrons of ds-block elements. The co-culture experiments of macrophages and bone marrow mesenchymal stem cells showed that these two kinds of cells could enhance the anti-inflammation and osteogenesis of samples by the paracrine manner of PGE2. In general, in their steady states on titanium substrate (Cu2+, Zn2+, Ag), the ds-block elements with more valence electrons exhibit better anti-inflammatory and osteogenic effects. Moreover, molecular biology experiments indicate that the PGE2-related signaling pathway may contribute to the desired immunoregulation and osteoinduction capability of ds-block elements. These findings suggest a correlation between the number of valence electrons of ds-block elements and the relevant biological responses, which provides new insight into the selection of implanted ions and surface design of biomaterials