A novel distributed meta-module motion design for modular robotic systems based on grid partition method.

This article studies a meta-module motion design approach for homogenous modular robotic systems in self-configuration. By utilizing configuration diversity, scalability and unit-substitutability, homogenous modular robotic systems can be a promising approach to life detection and space exploration in the future. Based on the requirements of the potential applications, self-configuration can be considered as the precondition. As similar to swarm robotic systems, the distributed control strategy in which the modular robots are operated in a sequence of motion circles consist of 'detection'- 'decision'- 'execution' is of great significance. However, there is a limitation to the applicability of previously proposed work on the self-configuration topic, due to the fact that the self-configuration strategy execution suffers from the motion constraints of modular robots. In order to solve the problem, we propose a grid partition method that removes the gap between the locomotion of a single modular robot and the reconfiguration of the whole system. Under the analysis of the grid partition, the meta-module motion design is proposed to realize the distributed self-configuration strategy. We simulated the self-configuration in M-Lattice, a two-dimensional homogenous modular robotic system.

Adaptive Skid-Steering Control Approach for Robots on Uncertain Inclined Planes with Redundant Load-Bearing Mobility.

Climbing manufacturing robots can create a revolutionary manufacturing paradigm for large and complex components, while the motion control of climbing manipulation-oriented robots (CMo-Rs) is still challenging considering anti-slippage problems. In this study, a CMo-R with full-scenery climbing capability and redundant load-bearing mobility is designed based on magnetic adsorption. A four-wheel kinematic model considering the slipping phenomenon is established. An adaptive kinematic control algorithm based on slip estimation using Lyapunov theory is designed for uncertain inclined planes. For comparison, the traditional PID-based algorithm without slip consideration is implemented as well. Numeric simulations are conducted to tackle the trajectory tracking problems for both circular and linear trajectories on the horizontal plane (HP), 50° inclined plane (50° IP), 60° inclined plane (60° IP), and vertical plane (VP). The results prove that our approach achieves better tracking accuracy. It demonstrated applicability in various climbing scenarios with uncertain inclined planes. The results of experiments also validate the feasibility, applicability, and stability of the proposed approach.

Online Muscle Activation Onset Detection Using Likelihood of Conditional Heteroskedasticity of Electromyography Signals.

Surface electromyography (sEMG) signals are crucial in developing human-machine interfaces, as they contain rich information about human neuromuscular activities. OBJECTIVE: The real-time, accurate detection of muscle activation onset (MAO) is significant for EMG-triggered control strategies in embedded applications like prostheses and exoskeletons. METHODS: This paper investigates sEMG signals using the generalized autoregressive conditional heteroskedasticity (GARCH) model, focusing on variance. A novel feature, the likelihood of conditional heteroskedasticity (LCH) extracted from the maximum likelihood estimation of GARCH parameters, is proposed. This feature effectively distinguishes signal from noise based on heteroskedasticity, allowing for the detection of MAO through the LCH feature and a basic threshold classifier. For online calculation, the model parameter estimation is simplified, enabling direct calculation of the LCH value using fixed parameters. RESULTS: The proposed method was validated on two open-source datasets and demonstrated superior performance over existing methods. The mean absolute error of onset detection, compared with visual detection results, is approximately 65 ms under online conditions, showcasing high accuracy, universality, and noise insensitivity. CONCLUSION: The results indicate that the proposed method using the LCH feature from the GARCH model is highly effective for real-time detection of muscle activation onset in sEMG signals. SIGNIFICANCE: This novel approach shows great potential and possibility for real-world applications, reflecting its superior performance in accuracy, universality, and insensitivity to noise.

Atractylenolide III Enhances the Anti-Neoplastic Efficacy of Docetaxel in Gastric Cancer Cell by Inhibiting Fibroblast Growth Factor Receptors 1, -2, and -4 Expression.

BACKGROUND: Natural active components have been reported to serve as adjuvant medications in the clinical practice of cancer therapeutics. However, the antineoplastic roles of atractylenolide III (ATL) are rarely reported. In the present study, we assessed the functions of ATL combined with docetaxel in gastric cancer cells. METHODS: Cell viability and cytotoxic activity were evaluated using CCK-8 and LDH-based cytotoxicity assays, respectively. Protein expression levels were measured by western blotting analysis. Annexin V-FITC/PI staining was used to evaluate cell apoptosis using flow cytometry. RESULTS: AGS and SGC-7901 cell viability was significantly inhibited in ATL combined with docetaxel group compared with docetaxel treatment alone. The levels of LDH, apoptosis rate, and the ratio of BAX to Bcl-2 were significantly elevated in combination treatment group compared to docetaxel treatment alone. Intriguingly, docetaxel combined with ATL resulted in a significant decrease in FGFR1, FGFR2, and FGFR4 protein expression compared with docetaxel treatment alone. Knockout of FGFR1, -2, and -4 exhibited a similar role of medications to inhibit growth and induce apoptosis in AGS and SGC-7901 cells. CONCLUSIONS: ATL and docetaxel treatment performed the synergistic effects on the inhibition of growth and induction of apoptosis in gastric cancer cells, and the underlying mechanism was mediated, at least partially, through the inhibition of FGFR1, -2, and -4.

Effect of mechanical error on dual-wedge laser scanning system and error correction.

Compared with the traditional mechanical beam deflector in a beam-scanning system, the dual-wedge scanning system has several advantages, for example, compact structure, fast scanning speed, and low power consumption. High accuracy is the most important factor in dual-wedge scanning, but mechanical errors caused by machining or assembly errors adversely affect this scanning accuracy. Horizontal and angular mechanical errors appear between the incident light and the dual-wedge central optical axes. By building a mathematical model of an ideal dual-wedge scanning trajectory and a trajectory affected by mechanical errors, this paper analyzes the types and degree of influence on the scanning process, as well as the sensitivity of scanned images to different errors. Results show that the angular error has the most significant influence on the scanning image accuracy, in terms of trajectory shape and coverage. To correct the angular error, the two degrees-of-freedom flexible fine-tuning mechanism is customized based on the principle of the cantilever beam type. After finite element analysis and experimental validations, the fine-tuning mechanism can guarantee that the angular error in the dual-wedge central optical axes will be lower than 0.05 deg, thus ensuring scanning trajectory accuracy.

Resveratrol protects hippocampal neurons against cerebral ischemia-reperfusion injury via modulating JAK/ERK/STAT signaling pathway in rats.

Cerebral ischemia/reperfusion injury (I/R injury) can cause neuronal deficits even death. Recent studies demonstrated that resveratrol (RSV) exerts neuroprotective effects in ischemia and several signaling pathways were involved in the process. However, it is still possible that other signaling pathway participates in the neuronal protective process. Our study examines the possible mechanism underlying RSV treatment. We randomly divided rats into four groups: the sham group, I/R group, I/R group, I/R+RSV group, I/R+vehicle group. Locomotive and cognitive behavior were utilized by open-field and closed-field test and Morris water maze test. Neuronal cell loss was measured by hematoxylin-eosin (HE) staining for hippocampus. Western blot was applied to measure the level of p-JAK, p-ERK, p-STAT and p-JNK. The results indicated that RSV could alleviate cognitive impairment, reduce neuronal loss, downregulate p-JAK, p-ERK, p-STAT and p-JNK expression and inflammatory cytokines. In summary, resveratrol protects hippocampal neurons against cerebral ischemia-reperfusion injury via modulating JAK/ERK/STAT signaling pathway in rats.

Relationship between serotonin transporter gene polymorphism and constipation in cancer patients.

INTRODUCTION: To assess the potential association between serotonin transporter gene insertion/deletion polymorphism and the cancer-related constipation phenotype. MATERIAL AND METHODS: A total of 120 patients diagnosed with malignant solid tumors were subjected to genotyping. For the two groups - patients with constipation and constipation-free patients with non-gastrointestinal cancer, 60 cases in each group - we collected the peripheral venous blood. We extracted genomic DNA, and used polymerase chain reaction (PCR) to analyze the serotonin transporter (5-HT) link polymorphic region (5-HTTLPR) polymorphism of the serotonin transporter gene. RESULTS: The frequency of S/S genotype in cancer patients with constipation was 66.67% (40/60), and the frequency of the S allele was 79.17% (95/120); the frequency of S/S genotype in cancer patients without constipation was 48.33% (29/60), and the frequency of the S allele was 65.83% (79/120). There was a significant difference between the two groups (p < 0.05). CONCLUSIONS: The presence of 5-HTTLPRS/S genotype and the S allele in patients with cancers probably carry an increased risk of constipation. However, its role as a cause of cancer-related constipation needs to be further investigated.

NF-κB-modulated miR-130a targets TNF-α in cervical cancer cells.

BACKGROUND: Nuclear factor-κB (NF-κB) induces a variety of biological processes through transcriptional gene control whose products are components in various signaling pathways. MicroRNAs are a small endogenous non-coding RNAs that regulate gene expression and are involved in tumorigenesis. Using human cervical cancer cell lines, this study aimed to investigate whether NF-κB could regulate miR-130a expression and the functions and targets of miR-130a. METHODS: We used the HeLa and C33A cervical cancer cell lines that were transfected with NF-κB or miR-130a overexpression plasmids to evaluate their effects on cell growth. We utilized bioinformatics, a fluorescent reporter assay, qRT-PCR and Western blotting to identify downstream target genes. RESULTS: In HeLa and C33A cells, NF-κB and miR-130a overexpression promoted cell growth, but genetic knockdowns suppressed growth. TNF-α was identified as a target of miR-130a by binding in a 3'-untranslated region (3'UTR) EGFP reporter assay and by Western blot analysis. Furthermore, low TNF-α concentrations stimulated NF-κB activity and then induced miR-130a expression, and TNF-α overexpression rescued the effects of miR-130a on cervical cancer cells. CONCLUSIONS: Our findings indicate that TNF-α can activate NF-κB activity, which can reduce miR-130a expression, and that miR-130a targets and downregulates TNF-α expression. Hence, we shed light on the negative feedback regulation of NF-κB/miR-130a/TNF-α/NF-κB in cervical cancer and may provide insight into the carcinogenesis of cervical cancer.

[Analysis of prognostic factors in 68 patients with cancer of unknown primary site].

OBJECTIVE: The aim of this study was to analyze the clinical characteristics and prognostic factors in patients with cancer of unknown primary site (CUP). METHODS: The clinical and follow-up data of 68 CUP patients (46 adenocarcinoma patients, 22 squamous cell carcinoma patients), were retrospectively analyzed. Univariate and multivariate analysis were conducted to determine the correlation of survival with clinical features, tumor markers, blood test, liver function and so on. RESULTS: The median survival time of the 68 CUP patients was 123 days. The results from univariate Cox regression analysis showed that the prognostic factors were related to a performance status, presence or absence of liver metastases, the number of metastatic sites, carcinoembryonic antigen (CEA), lactate dehydrogenase (LDH), hypoalbuminemia, hypohemoglobinemia and lymphocyte count. Multivariate Cox regression analysis of the clinical factors identified that a performance status (PS) ≥ 2, liver metastasis, elevated serum carcinoembryonic antigen (CEA) and lactate dehydrogenase (LDH) levels, hypoalbuminemia (< 35 g/L) and lymphopenia (≤ 0.7 × 10(9)/L) were significant independent unfavorable predictive factors. Based on the number of the unfavorable predictive factors, we divided all the patients into three subgroups: subgroup involving 0-1 unfavorable factor, subgroup involving 2 - 3 unfavorable factors and subgroup involving 4 - 6 unfavorable factors. The median survival time was 390 days, 138 days and 77 days, respectively, in the 3 subgroups. Compared with the other two groups, the survival of the subgroup involving 0 - 1 unfavorable factor was significantly longer (P < 0.05), the survival between the subgroup involving 2 - 3 unfavorable factors and subgroup involving 4 - 6 unfavorable factors was not significantly different (P > 0.05). CONCLUSIONS: A performance status ≥ 2, liver metastasis, elevated serum carcinoembryonic antigen and lactate dehydrogenase levels, hypoalbuminemia and lymphopenia are independent unfavorable prognostic factors in patients with cancer of unknown primary site. The patients who had more than 2 unfavorable prognostic factors have a worse prognosis.