Searching for Two-Neutrino and Neutrinoless Double Beta Decay of

^{134}Xe is a candidate isotope for neutrinoless double beta decay (0νßß) search. In addition, the two-neutrino case (2νßß) allowed by the standard model of particle physics has not yet been observed. With the 656-kg natural xenon in the fiducial volume of the PandaX-4T detector, which contains 10.4% of ^{134}Xe, and its initial 94.9-day exposure, we have established the most stringent constraints on 2νßß and 0νßß of ^{134}Xe half-lives, with limits of 2.8×10^{22} yr and 3.0×10^{23} yr at 90% confidence level, respectively. The 2νßß (0νßß) limit surpasses the previously reported best result by a factor of 32 (2.7), highlighting the potential of large monolithic natural xenon detectors for double beta decay searches.

Effects of gait adaptation training on augmented reality treadmill for patients with stroke in community ambulation.

Gait adaptability is essential for stroke survivors to achieve efficient and safe community ambulation. However, conventional treadmill rehabilitation is only a repetitive practice of leg movement. This study compared the effects of augmented reality treadmill-based gait adaptation training with regular treadmill programs for patients with stroke. Forty patients with stroke (n = 40) were randomly assigned to the gait adaptation training {n = 20, age: 49.85 [standard deviation (SD) 8.44] years; onset of stroke: 107.80 (SD 48.31) days} and regular training [n = 20, age: 50.75 (SD 8.05) years, onset of stroke: 111.60 (SD 49.62) days] groups. Both groups completed three sessions of training per week for 5 weeks (15 sessions). The primary outcomes were the 10-m walk test and success rate of obstacle avoidance, while secondary outcomes included the Berg balance scale, component timed-up-and-go, and fall rate in a 6-month follow-up period. Assessments were performed before and after the intervention. The paired t-test was applied to compare the differences within groups and independent sample t-test was performed to compare the differences between groups. The 10-m walk test, success rate of obstacle avoidance, Berg balance scale, and component timed-up-and-go all significantly improved in the both groups (P < .001). The success rate of obstacle avoidance [P = .02, 95% confidence interval (CI): -21.07, -1.64], Berg Balance Scale (P = .02, 95% CI: -8.03, -0.67), 'turning around time' (P = .04, 95% CI: 0.08, 2.81), 'stand-to-sit' (P = .03, 95% CI: 0.16, 2.41) and 'total time' (P = .048, 95% CI: 0.04, 10.32) improved significantly in gait adaptation training group after intervention, while the 10-m walk test (P = .09, 95% CI: -0.17, 0.01), timed 'sit-to-stand' (P = .09, 95% CI: -0.14, 2.04), and 'linear walking' (P = .09, 95% CI: -0.27, 3.25) in gait adaptation training group did not show statistical difference compared to the regular training group. Total fall rate during the follow-up period was statistically decreased in the gait adaptation training group (P = .045). Both interventions improved mobility outcomes, with augmented reality treadmill-based gait adaptation indicating greater improvement in obstacle avoidance, balance, turning, and stand-to-sit. Augmented reality treadmill-based gait adaptation training emerges as an effective and promising intervention for patients with stroke in early rehabilitation.

Spinal cord electrical stimulation for severe disturbance of consciousness after traumatic brain injury: A case report.

Background: Currently, the use of spinal cord electrical stimulations for patients with severe disorders of consciousness after traumatic brain injury remains limited, and long-term follow-up studies are even scarcer. To date, there have been few reports using near-infrared spectroscopy to evaluate the clinical effects and optimal parameters of spinal cord electrical stimulation for severe consciousness disorders. This report describes a case of a patient with severe disturbance of consciousness after traumatic brain injury who underwent spinal cord electrical stimulation implantation. Advanced near-infrared spectroscopy was employed to monitor and evaluate postoperative efficacy. The findings of this case report will provide a reference for the clinical treatment of severe consciousness disturbances. Methods: A patient diagnosed with a severe disturbance of consciousness following traumatic brain injury presented symptoms of coma and lack of voluntary activity. The treatment regimen included conventional approaches (medication combined with rehabilitation training) and adjustments to the spinal cord electrical stimulation parameters. Advanced functional near-infrared spectroscopy (fNIRS) was used to explore changes in brain functional connectivity strength and assess clinical efficacy. Results: The integration of conventional treatment and continuous modification of spinal cord electrical stimulation parameters, combined with fNIRS monitoring, demonstrated that conventional treatment and spinal cord electrical stimulation displayed a positive effect on increasing brain functional strength connection. The Glasgow Coma Scale(GCS) score significantly improved from the baseline. Optimal results were observed with spinal cord stimulation settings at 4.5 V amplitude, 210 µs pulse width, and 70 Hz frequency, operating from 8:00-20:00 in a cycling mode of 15 min on and 15 min off, where improvements in consciousness were markedly evident. Conclusions: Patients with severe disturbances of consciousness after traumatic brain injury recover slowly. Conventional treatment combined with spinal cord electrical stimulation can improve the degree of disturbance of consciousness and promote recovery from the condition.

Non-linear relationship of serum albumin-to-globulin ratio and cognitive function in American older people: a cross-sectional national health and nutrition examination survey 2011-2014 (NHANES) study.

Background: Inflammation and liver function are associated with cognitive decline and dementia. Little is known about the serum albumin-to-globulin ratio on cognitive function. Objective: The objective of this study was to investigate the association between albumin-to-globulin ratio and cognitive function among the American older people. Methods: The public data available on the US National Health and Nutrition Examination Survey (NHANES) from 2011 to 2014 was used for this cross-sectional study. Participants aged ≥60 years completed the cognitive function assessments, including word learning and recall modules from the Consortium to Establish a Registry for Alzheimer's Disease (CERAD), the animal fluency (AF) test, and the digit symbol substitution test (DSST). A composite cognition score was calculated to evaluate global cognition. The univariate and multivariate linear regression analysis, curve fitting, a threshold effect, along with a subgroup analysis and interaction tests were conducted. Results: Serum albumin-to-globulin ratio (per 0.1 unit) was positively associated DSST score (ß = 0.36, 95% CI: 0.21, 0.51), AF score (ß = 0.1, 95% CI: 0.04, 0.16) and global cognition score (ß = 0.05, 95% CI: 0.02, 0.07), after being fully adjusted, while albumin-to-globulin ratio was not related to CERAD score (ß = 0.05, 95% CI: -0.02, 0.12). A non-linear was observed in the dose-response relationship between albumin-to-globulin ratio and global cognition (P for non-linearity < 0.001). The subgroup analysis was overall stable, yet the interaction test was significant for age on global cognition (P for interaction = 0.036). Conclusion: The findings of this cross-sectional study suggested a positive and non-linear association between albumin-to-globulin ratio and cognitive function in the American older people. Maintaining albumin-to-globulin ratio with an appropriate range may be one of the therapeutic strategies to limit the progression of cognitive decline for the older people.

Machine learning-based gait adaptation dysfunction identification using CMill-based gait data.

Background: Combining machine learning (ML) with gait analysis is widely applicable for diagnosing abnormal gait patterns. Objective: To analyze gait adaptability characteristics in stroke patients, develop ML models to identify individuals with GAD, and select optimal diagnostic models and key classification features. Methods: This study was investigated with 30 stroke patients (mean age 42.69 years, 60% male) and 50 healthy adults (mean age 41.34 years, 58% male). Gait adaptability was assessed using a CMill treadmill on gait adaptation tasks: target stepping, slalom walking, obstacle avoidance, and speed adaptation. The preliminary analysis of variables in both groups was conducted using t-tests and Pearson correlation. Features were extracted from demographics, gait kinematics, and gait adaptability datasets. ML models based on Support Vector Machine, Decision Tree, Multi-layer Perceptron, K-Nearest Neighbors, and AdaCost algorithm were trained to classify individuals with and without GAD. Model performance was evaluated using accuracy (ACC), sensitivity (SEN), F1-score and the area under the receiver operating characteristic (ROC) curve (AUC). Results: The stroke group showed a significantly decreased gait speed (p = 0.000) and step length (SL) (p = 0.000), while the asymmetry of SL (p = 0.000) and ST (p = 0.000) was higher compared to the healthy group. The gait adaptation tasks significantly decreased in slalom walking (p = 0.000), obstacle avoidance (p = 0.000), and speed adaptation (p = 0.000). Gait speed (p = 0.000) and obstacle avoidance (p = 0.000) were significantly correlated with global F-A score in stroke patients. The AdaCost demonstrated better classification performance with an ACC of 0.85, SEN of 0.80, F1-score of 0.77, and ROC-AUC of 0.75. Obstacle avoidance and gait speed were identified as critical features in this model. Conclusion: Stroke patients walk slower with shorter SL and more asymmetry of SL and ST. Their gait adaptability was decreased, particularly in obstacle avoidance and speed adaptation. The faster gait speed and better obstacle avoidance were correlated with better functional mobility. The AdaCost identifies individuals with GAD and facilitates clinical decision-making. This advances the future development of user-friendly interfaces and computer-aided diagnosis systems.

Determination of Double Beta Decay Half-Life of 136Xe with the PandaX-4T Natural Xenon Detector.

Precise measurement of two-neutrino double beta decay (DBD) half-life is an important step for the searches of Majorana neutrinos with neutrinoless double beta decay. We report the measurement of DBD half-life of 136Xe using the PandaX-4T dual-phase Time Projection Chamber (TPC) with 3.7-tonne natural xenon and the first 94.9-day physics data release. The background model in the fiducial volume is well constrained in situ by events in the outer active region. With a 136Xe exposure of 15.5 kg-year, we establish the half-life as 2.27 ± 0.03(stat.) ± 0.10(syst.) × 1021 years. This is the first DBD half-life measurement with natural xenon and demonstrates the physics capability of a large-scale liquid xenon TPC in the field of rare event searches.