Mechanical design and trajectory planning of a lower limb rehabilitation robot with a variable workspace

The early phase of extremity rehabilitation training has high potential impact for stroke patients. However, most of the lower limb rehabilitation robots in hospitals are proposed just suitable for patients at the middle or later recovery stage. This article investigates a new sitting/lying multi-joint lower limb rehabilitation robot. It can be used at all recovery stages, including the initial stage. Based on man–machine engineering and the innovative design for mechanism, the leg length of the lower limb rehabilitation robot is automatically adjusted to fit patients with different heights. The lower limb rehabilitation robot is a typical human–machine system, and the limb safety of the patient is the most important principle to be considered in its design. The hip joint rotation ranges are different in people’s sitting and lying postures. Different training postures cannot make the training workspace unique. Besides the leg lengths and joint rotation angles varied with different patients, the idea of variable workspace of the lower limb rehabilitation robot is first proposed. Based on the variable workspace, three trajectory planning methods are developed. In order to verify the trajectory planning methods, an experimental study has been conducted. Theoretical and actual curves of the hip rotation, knee rotation, and leg mechanism end point motion trajectories are obtained for three unimpaired subjects. Most importantly, a clinical trial demonstrated the safety and feasibility of the proposed lower limb rehabilitation robot

Bioinformatic and systems biology approach revealing the shared genes and molecular mechanisms between COVID-19 and non-alcoholic hepatitis

Introduction: Coronavirus disease 2019 (COVID-19) has become a global pandemic and poses a serious threat to human health. Many studies have shown that pre-existing nonalcoholic steatohepatitis (NASH) can worsen the clinical symptoms in patients suffering from COVID-19. However, the potential molecular mechanisms between NASH and COVID-19 remain unclear. To this end, key molecules and pathways between COVID-19 and NASH were herein explored by bioinformatic analysis.Methods: The common differentially expressed genes (DEGs) between NASH and COVID-19 were obtained by differential gene analysis. Enrichment analysis and protein-protein interaction (PPI) network analysis were carried out using the obtained common DEGs. The key modules and hub genes in PPI network were obtained by using the plug-in of Cytoscape software. Subsequently, the hub genes were verified using datasets of NASH (GSE180882) and COVID-19 (GSE150316), and further evaluated by principal component analysis (PCA) and receiver operating characteristic (ROC). Finally, the verified hub genes were analyzed by single-sample gene set enrichment analysis (ssGSEA) and NetworkAnalyst was used for the analysis of transcription factor (TF)-gene interactions, TF-microRNAs (miRNA) coregulatory network, and Protein-chemical Interactions.Results: A total of 120 DEGs between NASH and COVID-19 datasets were obtained, and the PPI network was constructed. Two key modules were obtained via the PPI network, and enrichment analysis of the key modules revealed the common association between NASH and COVID-19. In total, 16 hub genes were obtained by five algorithms, and six of them, namely, Kruppel-like factor 6 (KLF6), early growth response 1 (EGR1), growth arrest and DNA-damage-inducible 45 beta (GADD45B), JUNB, FOS, and FOS-like antigen 1 (FOSL1) were confirmed to be closely related to NASH and COVID-19. Finally, the relationship between hub genes and related pathways was analyzed, and the interaction network of six hub genes was constructed with TFs, miRNAs, and compounds.Conclusion: This study identified six hub genes related to COVID-19 and NASH, providing a new perspective for disease diagnosis and drug development

Evaluation of the Observational Associations and Shared Genetics Between Glaucoma With Depression and Anxiety

PURPOSE: Glaucoma, a leading cause of blindness worldwide, is suspected to exhibit a notable association with psychological disturbances. This study aimed to investigate epidemiological associations and explore shared genetic architecture between glaucoma and mental traits, including depression and anxiety.METHODS: Multivariable logistic regression and Cox proportional hazards regression models were employed to investigate longitudinal associations based on UK Biobank. A stepwise approach was used to explore the shared genetic architecture. First, linkage disequilibrium score regression inferred global genetic correlations. Second, MiXeR analysis quantified the number of shared causal variants. Third, specific shared loci were detected through conditional/conjunctional false discovery rate (condFDR/conjFDR) analysis and characterized for biological insights. Finally, two-sample Mendelian randomization (MR) was conducted to investigate bidirectional causal associations.RESULTS: Glaucoma was significantly associated with elevated risks of hospitalized depression (hazard ratio [HR] = 1.54; 95% confidence interval [CI], 1.01-2.34) and anxiety (HR = 2.61; 95% CI, 1.70-4.01) compared to healthy controls. Despite the absence of global genetic correlations, MiXeR analysis revealed 300 variants shared between glaucoma and depression, and 500 variants shared between glaucoma and anxiety. Subsequent condFDR/conjFDR analysis discovered 906 single-nucleotide polymorphisms (SNPs) jointly associated with glaucoma and depression and two associated with glaucoma and anxiety. The MR analysis did not support robust causal associations but indicated the existence of pleiotropic genetic variants influencing both glaucoma and depression.CONCLUSIONS: Our study enhances the existing epidemiological evidence and underscores the polygenic overlap between glaucoma and mental traits. This observation suggests a correlation shaped by pleiotropic genetic variants rather than being indicative of direct causal relationships.</p

Evaluation of the Observational Associations and Shared Genetics Between Glaucoma With Depression and Anxiety

PURPOSE: Glaucoma, a leading cause of blindness worldwide, is suspected to exhibit a notable association with psychological disturbances. This study aimed to investigate epidemiological associations and explore shared genetic architecture between glaucoma and mental traits, including depression and anxiety.METHODS: Multivariable logistic regression and Cox proportional hazards regression models were employed to investigate longitudinal associations based on UK Biobank. A stepwise approach was used to explore the shared genetic architecture. First, linkage disequilibrium score regression inferred global genetic correlations. Second, MiXeR analysis quantified the number of shared causal variants. Third, specific shared loci were detected through conditional/conjunctional false discovery rate (condFDR/conjFDR) analysis and characterized for biological insights. Finally, two-sample Mendelian randomization (MR) was conducted to investigate bidirectional causal associations.RESULTS: Glaucoma was significantly associated with elevated risks of hospitalized depression (hazard ratio [HR] = 1.54; 95% confidence interval [CI], 1.01-2.34) and anxiety (HR = 2.61; 95% CI, 1.70-4.01) compared to healthy controls. Despite the absence of global genetic correlations, MiXeR analysis revealed 300 variants shared between glaucoma and depression, and 500 variants shared between glaucoma and anxiety. Subsequent condFDR/conjFDR analysis discovered 906 single-nucleotide polymorphisms (SNPs) jointly associated with glaucoma and depression and two associated with glaucoma and anxiety. The MR analysis did not support robust causal associations but indicated the existence of pleiotropic genetic variants influencing both glaucoma and depression.CONCLUSIONS: Our study enhances the existing epidemiological evidence and underscores the polygenic overlap between glaucoma and mental traits. This observation suggests a correlation shaped by pleiotropic genetic variants rather than being indicative of direct causal relationships.</p

Pharmacokinetics/pharmacodynamics of polymyxin B in patients with bloodstream infection caused by carbapenem-resistant Klebsiella pneumoniae

Introduction: Polymyxin B is a last-line therapy for carbapenem-resistant microorganisms. However, a lack of clinical pharmacokinetic/pharmacodynamic (PK/PD) data has substantially hindered dose optimization and breakpoint setting.Methods: A prospective, multi-center clinical trial was undertaken with polymyxin B [2.5 mg/kg loading dose (3-h infusion), 1.25 mg/kg/12 h maintenance dose (2-h infusion)] for treatment of carbapenem-resistant K. pneumoniae (CRKP) bloodstream infections (BSI). Safety, clinical and microbiological efficacy were evaluated. A validated liquid chromatography-tandem mass spectrometry (LC-MS/MS) method was applied to determine the concentrations of polymyxin B in blood samples. Population pharmacokinetic (PK) modeling and Monte Carlo simulations were conducted to examine the susceptibility breakpoint for polymyxin B against BSI caused by CRKP.Results: Nine patients were enrolled and evaluated for safety. Neurotoxicity (5/9), nephrotoxicity (5/9), and hyperpigmentation (1/9) were recorded. Blood cultures were negative within 3 days of commencing therapy in all 8 patients evaluated for microbiological efficacy, and clinical cure or improvement occurred in 6 of 8 patients. Cmax and Cmin following the loading dose were 5.53 ± 1.80 and 1.62 ± 0.41 mg/L, respectively. With maintenance dosing, AUCss,24 h was 79.6 ± 25.0 mg h/L and Css,avg 3.35 ± 1.06 mg/L. Monte Carlo simulations indicated that a 1 mg/kg/12-hourly maintenance dose could achieve &gt;90% probability of target attainment (PTA) for isolates with minimum inhibitory concentration (MIC) ≤1 mg/L. PTA dropped substantially for MICs ≥2 mg/L, even with a maximally recommended daily dose of 1.5 mg/kg/12-hourly.Conclusion: This is the first clinical PK/PD study evaluating polymyxin B for BSI. These results will assist to optimize polymyxin B therapy and establish its breakpoints for CRKP BSI

COPA - a painting project for color-blind people

"We are not ‘colorblind’, we just see color in different ways." COPA is a painting related brand which helps people with color vision deficiency to know more about colors. Around 9% of people have some sort of color-blindness in this world. Most of them don't want to face it. People with normal color vision don't really understand color-blindness. COPA aims to encourage people with color-blindness to face it positively through helping them to learn how to paint with proper colors through practical color theory. COPA helps them enjoy colors through painting as well.Bachelor of Fine Art

Non-Starch Polysaccharides in Wheat Beers and Barley Malt beers: A Comparative Study

Non-starch polysaccharides (NSPs) in beers attract extensive attention due to their health benefits. The aim of this work was to investigate and compare NSPs including arabinoxylan, arabinogalactan, &beta;&ndash;glucans, and mannose polymers in wheat and barley malt beers as well as the influence on its quality. NSPs in wheat beers (1953&ndash;2923 mg/L) were higher than that in barley malt beers (1442&ndash;1756 mg/L). Arabinoxylan was the most abundant followed by arabinogalactan. In contrast to barley malt beers, wheat beers contained more mannose polymers (130&ndash;182 mg/L) than &beta;-glucan (26&ndash;99 mg/L), indicating that more arabinoxylan, arabinogalactan, and mannose polymers came from wheat malt. The substitution degree of arabinoxylan in wheat beers (0.57&ndash;0.66) was lower than that in barley malt beers (0.68&ndash;0.72), while the degree of polymerization (38&ndash;83) was higher (p &lt; 0.05) than that in barley malt beers (38&ndash;48), indicating different structures of arabinoxylan derived from barley malt and wheat malt. NSPs, especially arabinoxylan content, positively correlated (p &lt; 0.01) with real extract and viscosity of beers. Furthermore, wheat and barley malt beers were well separated in groups by principal component analysis

Efficacy of adalimumab in pediatric generalized pustular psoriasis: case series and literature review

Background Generalized pustular psoriasis (GPP) is a rare, severe, and sometimes fatal form of childhood psoriasis. The first line therapies include acitretin, cyclosporin A, and methotrexate which take effect slowly and have varying long-term side effects for children. Recently, the anti-tumor necrosis factor-alpha (TNF-α), adalimumab has shown efficacy in adult patients with pustular psoriasis; however, there is lack of evidence of its usage in the pediatric population. Methods Data on efficacy of adalimumab in treating pediatric GPP along with a literature review are presented. Results A total of seven patients had marked clearance and reduction in PGA and systemic/laboratory score within the first week of first injection and achieved almost complete clearance of skin lesions by 1-month follow up. In literature, adalimumab treating pustular psoriasis in pediatric has been described in six children who failed in prior treatment. All six patients showed a satisfactory therapeutic effect. Conclusions Subcutaneous injection of adalimumab every other week in the treatment of children with GPP has significant clinical efficacy with rapid clearance of skin lesions, providing a novel alternative for children with pustular psoriasis who responded poorly to traditional treatment or are not suitable for traditional treatment

Design and Isokinetic Training Control Method of Leg Press Training Device

Lower-limb function in elderly people gradually degenerates with age, and poor rehabilitation conditions preventing the elderly from receiving scientific rehabilitation training result in the decline of social labor force and the increased economic burden of the elderly. Aiming at the characteristics of the single function and the complex structure of an existing telescopic leg trainer combined with the needs of the application group, a new type of leg-stretching training device with multiple training modes for lower extremity extension and flexion of the elderly is proposed. A new mechanical structure and electrical system is designed. At the same time, the anti-resistance training man&ndash;machine model is analyzed, aiming at the isokinetic resistance training mode, and a training controller strategy based on a fuzzy synovial algorithm is proposed. Finally, the feasibility of the designed controller strategy and the proposed leg training device are verified by prototype experiments, which will guide further research

Radar-based human activity recognition using denoising techniques to enhance classification accuracy

Radar-based human activity recognition is considered as a competitive solution for the elderly care health monitoring problem, compared to alternative techniques such as cameras and wearable devices. However, raw radar signals are often contaminated with noise, clutter, and other artifacts that significantly impact recognition performance, which highlights the importance of prepossessing techniques that enhance radar data quality and improve classification model accuracy. In this study, two different human activity classification models incorporated with pre-processing techniques have been proposed. The authors introduce wavelet denoising methods into a cyclostationarity-based classification model, resulting in a substantial improvement in classification accuracy. To address the limitations of conventional pre-processing techniques, a deep neural network model called Double Phase Cascaded Denoising and Classification Network (DPDCNet) is proposed, which performs end-to-end signal-level classification and achieves state-of-the-art accuracy. The proposed models significantly reduce false detections and would enable robust activity monitoring for older individuals with radar signals, thereby bringing the system closer to a practical implementation for deployment.Radar-based Human activity recognition using denoising techniques is used to enhance classification accuracy. Two methods are evaluated; cyclostationarity-based with wavelet-based denoising and a deep neural network model called Double Phase Cascaded Denoising and Classifi-cation Network (DPDCNet). The proposed models significantly reduce false detections and would enable robust activity monitoring for older individuals with radar signals, thereby bringing the system closer to a practical implementation for deployment.imag