Activity-dependent neurorehabilitation beyond physical trainings: "mental exercise" through mirror neuron activation

The activity dependent brain repair mechanism has been widely adopted in many types of neurorehabilitation. The activity leads to target specific and non-specific beneficial effects in different brain regions, such as the releasing of neurotrophic factors, modulation of the cytokines and generation of new neurons in adult hood. However physical exercise program clinically are limited to some of the patients with preserved motor functions; while many patients suffered from paralysis cannot make such efforts. Here the authors proposed the employment of mirror neurons system in promoting brain rehabilitation by "observation based stimulation". Mirror neuron system has been considered as an important basis for action understanding and learning by mimicking others. During the action observation, mirror neuron system mediated the direct activation of the same group of motor neurons that are responsible for the observed action. The effect is clear, direct, specific and evolutionarily conserved. Moreover, recent evidences hinted for the beneficial effects on stroke patients after mirror neuron system activation therapy. Finally some music-relevant therapies were proposed to be related with mirror neuron system

Phase-resolved spectral analysis of 4U 1901+03 during its outburst

The high mass X-ray binary 4U 1901+03 was reported to have the pulse profile evolving with the X-ray luminosity and energy during its outburst in February-July 2003: the pulse peak changed from double to single along with the decreasing luminosity. We have carried out a detailed analysis on the contemporary phase-resolved energy spectrum of 4U 1901+03 as observed by Rossi X-ray Timing Explorer (RXTE). We find that, both the continuum and the pulse spectra are phase dependent. The optical depth derived from the pulse spectrum is in general larger than that from the continuum. Fe Ka emission line is only detected in the spectrum of the continuum and is missing in the pulse spectrum. This suggests an origin of Fe emission from the accretion disk but not the surface of the neutron star.Comment: 18 pages, 8 figures, accepted by Ap

Timeframe for return to driving for patients with minimally invasive knee arthroplasty is associated with knee performance on functional tests

BACKGROUND: This study hopes to establish the timeframe for a safe return to driving under different speed conditions for patients after minimally invasive total knee arthroplasty and further explores how well various kinds of functional tests on knee performance can predict the patients’ braking ability. METHODS: 14 patients with right knee osteoarthritis were included in the present study and instructed to perform three simulated driving tasks at preoperative, 2 weeks postoperative and 4 weeks postoperative. RESULTS: The results showed that the total braking time at 4 week postoperative has attained the preoperative level at the driving speed 50 and 70 km/hr but not at the driving speed 90 km/hr. It had significantly improving in knee reaction time and maximum isometric force at 4 weeks postoperative. Besides, there was a moderate to high correlation between the scores of the step counts and the total braking time. CONCLUSIONS: Summary, it is recommended that driving may be resumed 4 weeks after a right knee replacement but had to drive at low or moderate speed and the best predictor of safety driving is step counts

KCNN2 polymorphisms and cardiac tachyarrhythmias

Potassium calcium-activated channel subfamily N member 2 (KCNN2) encodes an integral membrane protein that forms small-conductance calcium-activated potassium (SK) channels. Recent studies in animal models show that SK channels are important in atrial and ventricular repolarization and arrhythmogenesis. However, the importance of SK channels in human arrhythmia remains unclear. The purpose of the present study was to test the association between genetic polymorphism of the SK2 channel and the occurrence of cardiac tachyarrhythmias in humans. We enrolled 327 Han Chinese, including 72 with clinically significant ventricular tachyarrhythmias (VTa) who had a history of aborted sudden cardiac death (SCD) or unexplained syncope, 98 with a history of atrial fibrillation (AF), and 144 normal controls. We genotyped 12 representative tag single nucleotide polymorphisms (SNPs) across a 141-kb genetic region containing the KCNN2 gene; these captured the full haplotype information. The rs13184658 and rs10076582 variants of KCNN2 were associated with VTa in both the additive and dominant models (odds ratio [OR] 2.89, 95% confidence interval [CI] = 1.505-5.545, P = 0.001; and OR 2.55, 95% CI = 1.428-4.566, P = 0.002, respectively). After adjustment for potential risk factors, the association remained significant. The population attributable risks of these 2 variants of VTa were 17.3% and 10.6%, respectively. One variant (rs13184658) showed weak but significant association with AF in a dominant model (OR 1.91, CI = 1.025-3.570], P = 0.042). There was a significant association between the KCNN2 variants and clinically significant VTa. These findings suggest an association between KCNN2 and VTa; it also appears that KCNN2 variants may be adjunctive markers for risk stratification in patients susceptible to SCD

Accelerating and Improving AlphaZero Using Population Based Training

AlphaZero has been very successful in many games. Unfortunately, it still consumes a huge amount of computing resources, the majority of which is spent in self-play. Hyperparameter tuning exacerbates the training cost since each hyperparameter configuration requires its own time to train one run, during which it will generate its own self-play records. As a result, multiple runs are usually needed for different hyperparameter configurations. This paper proposes using population based training (PBT) to help tune hyperparameters dynamically and improve strength during training time. Another significant advantage is that this method requires a single run only, while incurring a small additional time cost, since the time for generating self-play records remains unchanged though the time for optimization is increased following the AlphaZero training algorithm. In our experiments for 9x9 Go, the PBT method is able to achieve a higher win rate for 9x9 Go than the baselines, each with its own hyperparameter configuration and trained individually. For 19x19 Go, with PBT, we are able to obtain improvements in playing strength. Specifically, the PBT agent can obtain up to 74% win rate against ELF OpenGo, an open-source state-of-the-art AlphaZero program using a neural network of a comparable capacity. This is compared to a saturated non-PBT agent, which achieves a win rate of 47% against ELF OpenGo under the same circumstances.Comment: accepted by AAAI2020 as oral presentation. In this version, supplementary materials are adde

THE EFFECTS OF EXTERNAL LOAD ON LOWER EXTREMiTY ELECTROMYOGRAPHY AMPLITUDE DURING COUNTERMOVEMENT JUMP

The purpose of this study was to investigate the effects of different loads on the mean electromyography (EMG) amplitude of the gluteus maximus, biceps fernoris, vastus medialis, gastrocnemius, soleus, and tibialis anterior during the deceleration phase and the acceleration phase of the countermovement jumps (CMJ). Ten male physical education students performed different CMJs with and without an external load (0,2.5,5.0, 7.5, or 10.0 kg hold in arms). The results s h o w the amplitude of the gluteus maximus with load of 7.5 kg was higher than with load of 2.5 kg during the deceleration phase (p < .05), and the amplitude of the soleus with load of 10.0 kg was higher than with load of 2.5 kg during the acceleration phase (p < .05). It indicated that the activities of lower limb muscles were not influenced by the relative lower of external loading during CMJ

A Local-Pattern Related Look-Up Table

This paper describes a Relevance-Zone pattern table (RZT) that can be used to replace a traditional transposition table. An RZT stores exact game values for patterns that are discovered during a Relevance-Zone-Based Search (RZS), which is the current state-of-the-art in solving L&D problems in Go. Positions that share the same pattern can reuse the same exact game value in the RZT. The pattern matching scheme for RZTs is implemented using a radix tree, taking into consideration patterns with different shapes. To improve the efficiency of table lookups, we designed a heuristic that prevents redundant lookups. The heuristic can safely skip previously queried patterns for a given position, reducing the overhead to 10% of the original cost. We also analyze the time complexity of the RZT both theoretically and empirically. Experiments show the overhead of traversing the radix tree in practice during lookup remain flat logarithmically in relation to the number of entries stored in the table. Experiments also show that the use of an RZT instead of a traditional transposition table significantly reduces the number of searched nodes on two data sets of 7x7 and 19x19 L&D Go problems.Comment: Submitted to IEEE Transactions on Games (under review

The feasibility and cost-effectiveness of implementing mobile low-dose computed tomography with an AI-based diagnostic system in underserved populations

Low-dose computed tomography (LDCT) significantly increases early detection rates of lung cancer and reduces lung cancer-related mortality by 20%. However, many significant screening barriers remain. This study conduct an initial feasibility and cost-effectiveness analysis of a community-based program that used a mobile low-dose computed tomography (LDCT) scan unit and discuss the operational challenges faced during its implementation. This study was conducted in rural areas in Fujian Province, China from July 2022 to August 2022. Individuals aged 40 years and above who had not previously undergone LDCT and who were socioeconomically marginalized were included. Participants received a LDCT program from a multidisciplinary research team. Physicians analyzed the images with the assistance of artificial intelligence "InferRead CT Lung Research" and completed structured reports on their impressions. The primary evaluation indicators for mobile LDCT screening effectiveness were the lung cancer detection rate and diagnosis rate, while the main evaluation indicators for cost-effective analysis were the cost-effective ratio and early detection cost index. A total of 10,159 individuals participated in this study. The detection rates of suspected lung cancer cases and confirmed cases were 1.06% (n = 108) and 0.7% (n = 71), respectively. The cost of lung cancer screening (LCS) was ¥1,203,504 (US$188,847.71), the average cost per screening was ¥118.47 (US$18.65), and the cost effective ratios for the detection of suspected lung cancer and confirmed lung cancer were ¥11,143.56 (US$1,753.29) and ¥16,950.76 (US$2,669.94), respectively. The early detection cost indices for suspected lung cancer were 0.09 and 0.13 for confirmed lung cancer, respectively. This LDCT with artificial intelligence model for LCS holds economic promise for reducing health disparities in underserved areas and promote larger populations in similar low-income country

Evaluating digital nudge interventions for the promotion of cancer screening behavior: a systematic review and meta-analysis.

BACKGROUND: Public adherence to cancer screening remains low and is influenced by both rational and non-rational factors, including decision biases that underestimate screening benefits. Digital nudge interventions have shown promise in promoting screening behaviors among at-risk populations, but systematic evidence is still lacking. This study aims to synthesize the effects of digital nudge interventions on promoting cancer screening behaviors in high-risk individuals. METHODS: A systematic search of 10 electronic databases was conducted, and studies published before April 1, 2024, were included. Eligible studies were randomized controlled trials (RCTs) that compared the effects of digital nudge interventions on cancer screening behavior with those of a control group and reported at least one outcome. The risk of bias was evaluated using the Cochrane Risk of Bias tool. Data on cancer screening uptake rates were pooled using a random-effects model. Subgroup analyses were performed for cancer types, intervention media, delivery conditions, and sensitivity. The study identified digital nudge strategies via the MINDSPACE framework and explored their influence on screening behavior through the HSM. RESULTS: Of the 14 randomized controlled trials included, 10 reported statistically significant results. The types of interventions in these studies were heterogeneous and available across multiple delivery channels based on the web, computer programmes, DVDs, telephones, patient navigation, or apps that tailored or served interactive information to participants to better understand screening risks and options. A random-effects model showed that digital nudge intervention strategies significantly improved adherence to cancer screening behavior (OR = 1.81, 95% CI = 1.35-2.44, p &lt; 0.001). Differences between cancer types, intervention media, and delivery conditions were noted. Based on the MINDSPACE framework and HSM, eight nudge strategies were designed to promote screening behaviors, with the most common being the default strategy (n = 9). Most nudge tools were designed to leverage unconscious System 1 thinking, aiming to influence behavior in a more spontaneous and subtle way. CONCLUSIONS: While digital nudge interventions have demonstrated significant positive effects in promoting early cancer screening participation among high-risk individuals, their impact varies. More robust research is needed to address methodological limitations and facilitate broader adoption and application of these interventions