Phase-locked transcranial electrical brain stimulation for tremor suppression in dystonic tremor syndromes

Background: Tremor is a common and burdensome symptom in patients with dystonia, which is clinically heterogeneous and often resistant to treatment. The pathophysiology is suggested to involve abnormal activity in the cerebellum and motor cortex, but the causal role of these brain regions remains to be established. Transcranial alternating current stimulaton (TACS) can suppress rhytmic cerebral activity in other tremor disorders when phase-locked to the ongoing arm tremor, but the effect on dystonic tremor syndromes is unknown. Objective/Hypothesis: We aimed to establish the causal role of the cerebellum and motor cortex in dystonic tremor syndromes, and explore the therapeutic efficacy of phase-locked TACS. Methods: We applied phase-locked TACS over the ipsilateral cerebellum (N=14) and contralateral motor cortex (N=17) in dystonic tremor syndrome patients, while patients assumed a tremor-evoking posture. We measured tremor power using accelerometery during 30s stimulation periods at 10 different phase-lags (36-degrees increments) between tremor and TACS for each target. Post-hoc, TACS-effects were related to a key clinical feature: the jerkiness (regularity) of tremor. Results: Cerebellar TACS modulated tremor amplitude in a phase-dependent manner, such that tremor amplitude was suppressed or enhanced at opposite sides of the phase-cycle. This effect was specific for patients with non-jerky (sinusoidal) tremor (n=10), but absent in patients with jerky (irregular) tremor (n=4). Phase-locked stimulation over the motor cortex did not modulate tremor amplitude. Conclusions: This study indicates that the cerebellum plays a causal role in the generation of (non-jerky) dystonic tremor syndrome. Our findings suggest pathophysiologic heterogeneity between patients with dystonic tremor syndrome, which mirrors clinical variability.

Improvement of Mathematical Communication Skills for Students DIII Mechanical Engineering with Think Pair Share Method: A Case of Indonesia

Think Pair Share (TPS) based on Mathematical Good communication is a good thing expected related to the solutions students in college to improve the attractiveness and troubleshooting ability for mechanical engineering students in Indonesia. Research on this occasion is CAR (Class Action Research) . Results of the study are: (1) student interest before and after learning undergoes a change in the first cycle that 53% experienced an increase in 97% at cycle stage II, (2) there is an increase in in a student learning process activity that can be viewed from percentage level to student activities in the first phase cycle 83% which have a fairly active conclusion, and in the next cycle with 100%, (3) in this study there was an increase in the value of student achievement from has an average score of achieved from students in this early cycle 68 with the completeness of student learning in this study by 53% and in the second cycle 94 with 97% student learning completeness.

Qualitative analysis of the response regimes and triggering mechanism of bistable NES

The main focus of this study is the development of an adapted complex variable method in the vicinity of equilibrium in bistable NES. A simplified chaos trigger model is established to describe the distance between the stable phase cycle and the pseudo-separatrix. An analytical expression can predict the excitation threshold for chaos occurrence. The relative positions between the chaos trigger threshold line and the Slow Invariant Manifold (SIM) structure can express the distribution of response regimes under growing harmonic excitation. This topological structure implies the alternation of the response regime and helps to classify the bistable NES. The experiment compares the analytical result of intra-well oscillation with the numerical result in the frequency domain. The experimental response regimes under different input energy levels and frequency domains have been observed and give ideas to guide the optimal design of a bistable NES. It is shown that the modest bistable NES possesses strong robustness to frequency perturbation.

Licorice extract inhibits growth of non-small cell lung cancer by down-regulating CDK4-Cyclin D1 complex and increasing CD8+ T cell infiltration

Background Targeting tumor microenvironment (TME) may provide therapeutic activity and selectivity in treating cancers. Therefore, an improved understanding of the mechanism by which drug targeting TME would enable more informed and effective treatment measures. Glycyrrhiza uralensis Fisch (GUF, licorice), a widely used herb medicine, has shown promising immunomodulatory activity and anti-tumor activity. However, the molecular mechanism of this biological activity has not been fully elaborated. Methods Here, potential active compounds and specific targets of licorice that trigger the antitumor immunity were predicted with a systems pharmacology strategy. Flow cytometry technique was used to detect cell cycle profile and CD8+ T cell infiltration of licorice treatment. And anti-tumor activity of licorice was evaluated in the C57BL/6 mice. Results We reported the G0/G1 growth phase cycle arrest of tumor cells induced by licorice is related to the down-regulation of CDK4-Cyclin D1 complex, which subsequently led to an increased protein abundance of PD-L1. Further, in vivo studies demonstrated that mitigating the outgrowth of NSCLC tumor induced by licorice was reliant on increased antigen presentation and improved CD8+ T cell infiltration. Conclusions Briefly, our findings improved the understanding of the anti-tumor effects of licorice with the systems pharmacology strategy, thereby promoting the development of natural products in prevention or treatment of cancers.

Could Kallikrein-Related Serine Peptidase 3 Be an Early Biomarker of Environmental Exposure in Young Women?

Bisphenols and phthalates affect androgen receptor-mediated signaling that directly regulates Kallikrein-Related serine Peptidase 3 (KLK3) secretion, indicating that environmental factors may play a role in KLK3 secretion. With the aim of obtaining preliminary data on whether KLK3 could serve as an early marker of environmental pollution effects, in 61 and 58 healthy women living in a high environmental impact (HEI) and low environmental impact (LEI) area, respectively, serum KLK3 levels at different phases of menstrual cycle were measured. KLK3 values resulted in always being higher in the HEI group with respect to the LEI group. These differences were particularly relevant in the ovulatory phase (cycle day 12°–13°) of the menstrual cycle. The differences in KLK3 values during the three phases of the menstrual cycle were significant in the LEI group differently from the HEI group. In addition, higher progesterone levels were observed in the LEI group with respect to the HEI group in the luteal phase, indicating an opposite trend of KLK3 and progesterone in this phase of the menstrual cycle. Although changes in KLK3 could also depend on other factors, these preliminary data could be an early indication of an expanding study of the role of biomarkers in assessing early environmental effects for female reproductive health.

Enrichment of leukocytes in peripheral blood using 3D printed tubes

Leukocytes have an essential role in patient clinical trajectories and progression. Traditional methods of leukocyte enrichment have many significant limitations for current applications. It is demonstrated a novel 3D printing leukocyte sorting accumulator that combines with centrifugation to ensure label-free initial leukocyte enrichment based on cell density and size. The internal structure of leukocyte sorting accumulator (revealed here in a new design, leukocyte sorting accumulator-3, upgraded from earlier models), optimizes localization of the buffy coat fraction and the length of the period allocated for a second centrifugation step to deliver a higher recovery of buffy coats than earlier models. Established methodological parameters were evaluated for reliability by calculating leukocyte recovery rates and erythrocyte depletion rates by both pushing and pulling methods of cell displacement. Results indicate that leukocyte sorting accumulator-3 achieves a mean leukocytes recovery fraction of 96.2 ± 2.38% by the pushing method of layer displacement. By the pulling method, the leukocyte sorting accumulator-3 yield a mean leukocytes recovery fraction of 94.4 ± 0.8%. New procedures for preliminary enrichment of leukocytes from peripheral blood that avoid cellular damage, as well as avert metabolic and phase cycle intervention, are required as the first step in many modern clinical and basic research assays.

A novel two-phase cycle algorithm for effective cyber intrusion detection in edge computing

Edge computing extends traditional cloud services to the edge of the network, closer to users, and is suitable for network services with low latency requirements. With the rise of edge computing, its security issues have also received increasing attention. In this paper, a novel two-phase cycle algorithm is proposed for effective cyber intrusion detection in edge computing based on a multi-objective genetic algorithm (MOGA) and modified back-propagation neural network (MBPNN), namely TPC-MOGA-MBPNN. In the first phase, the MOGA is employed to build a multi-objective optimization model that tries to find the Pareto optimal parameter set for MBPNN. The Pareto optimal parameter set is applied for simultaneous minimization of the average false positive rate (Avg FPR), mean squared error (MSE) and negative average true positive rate (Avg TPR) in the dataset. In the second phase, some MBPNNs are created based on the parameter set obtained by MOGA and are trained to search for a more optimal parameter set locally. The parameter set obtained in the second phase is used as the input of the first phase, and the training process is repeated until the termination criteria are reached. A benchmark dataset, KDD cup 1999, is used to demonstrate and validate the performance of the proposed approach for intrusion detection. The proposed approach can discover a pool of MBPNN-based solutions. Combining these MBPNN solutions can significantly improve detection performance, and a GA is used to find the optimal MBPNN combination. The results show that the proposed approach achieves an accuracy of 98.81% and a detection rate of 98.23% and outperform most systems of previous works found in the literature. In addition, the proposed approach is a generalized classification approach that is applicable to the problem of any field having multiple conflicting objectives.

A Multipath Processing Technology Based on Multiparameter-Combined Observation in GNSS

In the Global Navigation Satellite System (GNSS), the multipath error affected by many aspects is the main error source that affects satellite navigation, and it is difficult to establish a much more accurate model to analyze it. Based on the ground multipath reflection model, it firstly deeply studies the influence of GNSS satellite orbit parameters on multipath fading frequency and establishes a multipath signal model related to satellite orbit parameters. Secondly, the influence of carrier phase cycle slip, receiver clock adjustment, and GNSS satellite orbit on multiparameter- (MP-) combined observations is analyzed in detail based on the measured data. Finally, aiming at the common phenomenon of code-carrier divergence in the Beidou system, the elevation-based pseudorange correction model and a sidereal filtering are built to correct the MP errors; experiments with measured data show that there is a fluctuation range reduction of 35.7% after sidereal filtering when the receiver reaches a steady state.