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The traditional two-wheeled self-balancing robot can travel quickly in a flat road environment, and it is easy to destabilize and capsize when passing through a bumpy road. To improve the passing ability of a two-wheeled robot, a new wheel-legged two-wheeled robot is developed. A seven-link leg structure is proposed through the comprehensive design of mechanism configuration, which decouples the balanced motion and leg motion of the robot. Based on the Euler–Lagrange method, the dynamic model of the system is obtained by applying the nonholonomic dynamic Routh equation in the generalized coordinate system. The robot's state space is divided according to the robot's height, and the Riccati equation is solved in real-time by the linear quadratic regulator (LQR) method to complete the balance and motion control of the robot. The robot leg motion control is achieved based on the active disturbance rejection control (ADRC) way. A robot simulation model is built on Recurdyn to verify the algorithm's feasibility, and then an experimental prototype is built to demonstrate the algorithm's effectiveness. The experimental results show that the control method based on LQR and ADRC can make the robot pass through the bumpy road. [ABSTRACT FROM AUTHOR]

The traditional two-wheeled self-balancing robot can travel quickly in a flat road environment, and it is easy to destabilize and capsize when passing through a bumpy road. To improve the passing ability of a two-wheeled robot, a new wheel-legged two-wheeled robot is developed. A seven-link leg structure is proposed through the comprehensive design of mechanism configuration, which decouples the balanced motion and leg motion of the robot. Based on the Euler–Lagrange method, the dynamic model of the system is obtained by applying the nonholonomic dynamic Routh equation in the generalized coordinate system. The robot's state space is divided according to the robot's height, and the Riccati equation is solved in real-time by the linear quadratic regulator (LQR) method to complete the balance and motion control of the robot. The robot leg motion control is achieved based on the active disturbance rejection control (ADRC) way. A robot simulation model is built on Recurdyn to verify the algorithm's feasibility, and then an experimental prototype is built to demonstrate the algorithm's effectiveness. The experimental results show that the control method based on LQR and ADRC can make the robot pass through the bumpy road. [ABSTRACT FROM AUTHOR]

The aim of this study was to develop a model for early prediction of adverse events and treatment effectiveness in patients with hyperkalemia. We collected clinical data from patients with hyperkalemia in the First Hospital of Zhejiang University School of Medicine between 2015 and 2021. The least absolute shrinkage and selection operator (LASSO) and multivariate logistic regression were used to analyze the predictors on the full dataset. We randomly divided the data into a training group and a validation group, and used LASSO to filter variables in the training set. Six machine learning methods were used to develop the models. The best model was selected based on the area under the curve (AUC). Shapley additive exPlanations (SHAP) values were used to explain the best model. A total of 1074 patients with hyperkalemia were finally enrolled. Diastolic blood pressure (DBP), breathing, oxygen saturation (SPO2), Glasgow coma score (GCS), liver disease, oliguria, blood sodium, international standardized ratio (ISR), and initial blood potassium were the predictors of the occurrence of adverse events; peripheral edema, estimated glomerular filtration rate (eGFR), blood sodium, actual base residual, and initial blood potassium were the predictors of therapeutic effect. Extreme gradient boosting (XGBoost) model achieved the best performance (adverse events: AUC = 0.87; therapeutic effect: AUC = 0.75). A model based on clinical characteristics was developed and validated with good performance. [ABSTRACT FROM AUTHOR]

The aim of this study was to develop a model for early prediction of adverse events and treatment effectiveness in patients with hyperkalemia. We collected clinical data from patients with hyperkalemia in the First Hospital of Zhejiang University School of Medicine between 2015 and 2021. The least absolute shrinkage and selection operator (LASSO) and multivariate logistic regression were used to analyze the predictors on the full dataset. We randomly divided the data into a training group and a validation group, and used LASSO to filter variables in the training set. Six machine learning methods were used to develop the models. The best model was selected based on the area under the curve (AUC). Shapley additive exPlanations (SHAP) values were used to explain the best model. A total of 1074 patients with hyperkalemia were finally enrolled. Diastolic blood pressure (DBP), breathing, oxygen saturation (SPO2), Glasgow coma score (GCS), liver disease, oliguria, blood sodium, international standardized ratio (ISR), and initial blood potassium were the predictors of the occurrence of adverse events; peripheral edema, estimated glomerular filtration rate (eGFR), blood sodium, actual base residual, and initial blood potassium were the predictors of therapeutic effect. Extreme gradient boosting (XGBoost) model achieved the best performance (adverse events: AUC = 0.87; therapeutic effect: AUC = 0.75). A model based on clinical characteristics was developed and validated with good performance. [ABSTRACT FROM AUTHOR]

Numerous researches have evaluated the prevalence and clinical outcome of vitamin D deficiency in patients with chronic kidney disease (CKD) and end-stage renal disease (ESRD). But the quantitative vitamin D status in acute kidney injury (AKI) patients and its relationship with prognosis remains controversial. We conducted this systemic review and meta-analysis to assess the quantitative difference of vitamin D status, including serum 25(OH) D and 1,25(OH)2D levels, between AKI patients and non-AKI controls, and further explore whether vitamin D status can be clearly correlated with the mortality of AKI. Major databases, including PubMed, Web of Science and EBSCO, were searched until 1st September 2021. All published observational studies related to vitamin D and AKI According to predefined inclusion and exclusion criteria were extracted. Meta-analyses were performed using Review Manager 5.3.5. Four studies including five cohorts were included with a total of 413 patients. The serum 25(OH)D levels showed no statistically significant difference in AKI patients and non-AKI controls. On the other hand, the serum 1,25(OH)2D levels were significant lower in AKI patients than in non-AKI controls (MD = − 17.79, 95% CI = − 32.73 to − 2.85, P = 0.02). As for the relationship between serum vitamin D status and AKI patients' mortality, we were unable to give a consistent conclusion based on current limited and conflict study results. Our meta-analysis suggested that serum 1,25(OH)2D levels, rather than 25(OH)D, is significantly lower in AKI patients. The relationship between vitamin D status and clinical outcome of AKI remains controversial based on current evidence. Future comprehensive studies are required to confirm these relations and to elucidate potential mechanisms. [ABSTRACT FROM AUTHOR]

The coronavirus disease 2019 (COVID-19) has been spreading worldwide. Severe cases quickly progressed with unfavorable outcomes. We aim to investigate the clinical features of COVID-19 and identify the risk factors associated with its progression. Data of confirmed SARS-CoV-2-infected patients and healthy participants were collected. Thirty-seven healthy people and 79 confirmed patients, which include 48 severe patients and 31 mild patients, were recruited. COVID-19 patients presented with dysregulated immune response (decreased T, B, and NK cells and increased inflammatory cytokines). Also, they were found to have increased levels of white blood cell, neutrophil count, and D-dimer in severe cases. Moreover, lymphocyte, CD4+ T cell, CD8+ T cell, NK cell, and B cell counts were lower in the severe group. Multivariate logistic regression analysis showed that CD4+ cell count, neutrophil-to-lymphocyte ratio (NLR) and D-dimer were risk factors for severe cases. Both CT score and clinical pulmonary infection score (CPIS) were associated with disease severity. The receiver operating characteristic (ROC) curve analysis has shown that all these parameters and scores had quite a high predictive value. Immune dysfunction plays critical roles in disease progression. Early and constant surveillance of complete blood cell count, T lymphocyte subsets, coagulation function, CT scan and CPIS was recommended for early screening of severe cases. [ABSTRACT FROM AUTHOR]

This retrospective and a single-center study evaluated the prognostic value of the maximum serum creatinine value (maxCr) and the maximum serum creatinine growth rate (Vmax) after paraquat (PQ) ingestion. One hundred and seventy-one patients with PQ poisoning were treated with a uniform protocol. Demographic variables, clinical manifestations, relevant laboratory data, maxCr and Vmax of all patients were recorded and calculated. The time after PQ ingestion of maxCr and Vmax were also recorded. Vmax and MaxCr exhibited statistically significant differences between the survivor (n = 53) and death (n = 118) groups. Vmax appeared earlier in the death group than the survivor group. Regard to the receiver operating characteristic (ROC) curve analysis, Vmax had an AUC of 0.861 (95% CI, 0.801-0.921) and the optimal cut-off value of 6.21 μmol/(L·h) (sensitivity, 76.3%; specificity, 81.1%). MaxCr had an area under the curve (AUC) of 0.821 (95% CI, 0.752-0.889) and the optimal cut-off value of 225.5 µmol/L (sensitivity, 82.2%; specificity, 67.9%). The comparison of the AUC in the two parameters showed no significant difference, but Vmax appeared earlier than maxCr. Based on binary logistic regression analysis, MaxCr and Vmax both showed strong predictive powers for evaluating the prognosis of acute PQ poisoning patients. [ABSTRACT FROM AUTHOR]

Evidence from behavioral, electrophysiological and diffusion-weighted imaging studies suggest that schizophrenia patients suffer from deficiencies in bilateral brain communication, and this disruption may be related to the occurrence of auditory verbal hallucinations (AVH). To increase our understanding of aberrant inter-hemispheric communication in relation to AVH, we recruited two groups of first-episode schizophrenia patients: one group with AVH (N = 18 AVH patients) and one without hallucinations (N = 18 Non-AVH patients), and 20 healthy controls. All participants received T1 structural imaging and resting-state fMRI scanning. We adopted a newly developed index, voxel-mirrored homotopic connectivity (VMHC), to quantitatively describe bilateral functional connectivity. The whole-brain VMHC measure was compared among the three groups and correlation analyses were conducted between symptomology scores and neurological measures. Our findings suggest all patients shared abnormalities in parahippocampus and striatum. Aberrant bilateral connectivity of default mode network (DMN), inferior frontal gyrus and cerebellum only showed in AVH patients, whereas aberrances in superior temporal gyrus and precentral gyrus were specific to Non-AVH patients. Meanwhile, inter-hemispheric connectivity of DMN correlated with patients' symptomatology scores. This study corroborates that schizophrenia is characterized by inter-hemispheric dysconnectivity, and suggests the localization of such abnormalities may be crucial to whether auditory verbal hallucinations develop. [ABSTRACT FROM AUTHOR]