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OBJECTIVE: This study aims to assess how enhancing upper limb function on the affected side of stroke influences the gait of the lower limb. METHODS: Forty eligible stroke patients were randomly assigned to either a control group or a treatment group, with 20 patients in each group. Both groups underwent dynamic evaluation using artificial intelligence and computer vision before treatment. This evaluation focused on analyzing the range of motion of the shoulder and elbow during the gait cycle, as well as various gait parameters (such as step length, step speed, and percentage of stance phase) on the affected side. Following evaluation, the control group received routine rehabilitation treatment. RESULTS: The results indicated that there was no significant difference between the two groups before treatment. However, following treatment, there was a notable improvement in the motion of the shoulder and elbow joints on the affected side among patients in the treatment group (p<0.05), whereas the control group showed only slight improvement, which was not statistically significant (p>0.05). CONCLUSION: The improvement in upper limb function on the affected side also appears to positively influence gait recovery. However, it's important to note that the observation period was relatively short. Further studies are needed to confirm whether this effect is sustained over the long term.

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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.

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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.

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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.

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^{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.

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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.

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We report results of a search for dark-matter-nucleon interactions via a dark mediator using optimized low-energy data from the PandaX-4T liquid xenon experiment. With the ionization-signal-only data and utilizing the Migdal effect, we set the most stringent limits on the cross section for dark matter masses ranging from 30 MeV/c^{2} to 2 GeV/c^{2}. Under the assumption that the dark mediator is a dark photon that decays into scalar dark matter pairs in the early Universe, we rule out significant parameter space of such thermal relic dark-matter model.

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This report introduces a young adult who has been in bed for more than ten years with end-stage hemophilic arthropathy. He didn't have access to factor VIII (FVIII) in the early stage of hemophilia due to the high costs of clotting replacement therapy. As a result, he is experiencing some difficulties, such as joint contracture, muscular atrophy, severe pain, and poor function of cardiopulmonary. He came to visit us for a comprehensive rehabilitation program, and, finally, he achieved the basic goal of self-care in daily life.

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BACKGROUND: Accumulating evidence has indicated a possible connection between post-stroke cognitive impairment (PSCI) and gut microbiota imbalance. To further investigate this association, the present work was designed to systematically assess the dissimilarity of gut microbiota between PSCI and healthy individuals or stroke patients. METHODS: A meta-analysis and systematic review was conducted by searching various databases including PubMed, Web of Science, Embase, VIP, CNKI, and Wangfang for relevant studies. The pooled outcomes were used to estimate the combined dissimilarity of gut microbiota composition between PSCI and healthy individuals or patients with stroke. RESULTS: Nine eligible studies were included in this meta-analysis. The results showed that there were no significant changes in observed richness indexes (Chao1 and ACE) and Shannon index. Notably, a significant decrease in Simpson index was observed in PSCI patients in comparison to the healthy individuals (-0.31, 95% CI: -0.62 to -0.01, P = 0.04). Moreover, the microbiota composition at the phylum level (increased abundance of Proteobacteria), family level (increased abundance of Bacteroidaceae, Lachnospiraceae, and Veillonellaceae; decreased abundance of Enterobacteriaceae), and genus level (increased abundance of Bacteroides, Clostridium XIVa, and Parabacteroides; decreased abundance of Prevotella and Ruminococcus) was found to be significantly different between PSCI and controls. CONCLUSION: This meta-analysis suggests a significant shift of observed species and microbiota composition in PSCI compared to healthy individuals or patients with stroke.

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OBJECTIVE: To identify key enhancer RNAs (eRNA) in esophageal cancer through a comprehensive analysis and explore its importance in esophageal cancer. STUDY DESIGN: An observational study. Place and Duration of the Study: Department of Thoracic Surgery, Hubei Cancer Hospital affiliated to Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei Province, China, from September to October 2022. METHODOLOGY: RNA-sequencing data, survival data, and clinical data for a total of 33 tumours were gathered from TCGA (The Cancer Genome Atlas) datasets. The survival-associated eRNAs were detected by means of Spearman's correlation and Kaplan-Meier survival analyses. Enhancer RNAs linked to survival rate and their target genes in esophageal cancer were screened, and a clinical correlation analysis of key eRNAs was carried out. A functional enrichment analysis was performed and the selected key eRNAs were confirmed in pan-cancer. RESULTS: The key eRNA was identified as SLC44A3-AS1, and patients with higher expression of SLC44A3-AS1 had worse prognosis than those with low expression. SLC44A3-AS1 expression was significantly associated with many clinical traits, namely tumour status, grade, pathological tumour, node, metastasis (TNM) stage, tumour type, etc. According to KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway enrichment results, SLC44A3 may affect the prognosis of esophageal cancer patients through the herpes simplex virus 1 (HSV1) infection pathway. According to pan-cancer validation results, SLC44A3-AS1 was related to the survival of eight tumours. Correlations were observed between SLC44A3-AS1 and SLC44A3 in 32 types of tumours. CONCLUSION: SLC44A3-AS1 plays a key role in esophageal cancer related to prognosis, which may be a new therapeutic target for clinical exploration. KEY WORDS: SLC44A3-AS1, Enhancer RNA, Esophageal cancer, Prognosis.

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We report a search for light dark matter produced through the cascading decay of η mesons, which are created as a result of inelastic collisions between cosmic rays and Earth's atmosphere. We introduce a new and general framework, publicly accessible, designed to address boosted dark matter specifically, with which a full and dedicated simulation including both elastic and quasielastic processes of Earth attenuation effect on the dark matter particles arriving at the detector is performed. In the PandaX-4T commissioning data of 0.63 tonne·year exposure, no significant excess over background is observed. The first constraints on the interaction between light dark matter generated in the atmosphere and nucleus through a light scalar mediator are obtained. The lowest excluded cross section is set at 5.9×10^{-37} cm^{2} for a dark matter mass of 0.1 MeV/c^{2} and mediator mass of 300 MeV/c^{2}. The lowest upper limit of η to the dark matter decay branching ratio is 1.6×10^{-7}.

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We report the search results of light dark matter through its interactions with shell electrons and nuclei, using the commissioning data from the PandaX-4T liquid xenon detector. Low energy events are selected to have an ionization-only signal between 60 to 200 photoelectrons, corresponding to a mean nuclear recoil energy from 0.77 to 2.54 keV and electronic recoil energy from 0.07 to 0.23 keV. With an effective exposure of 0.55 tonne·year, we set the most stringent limits within a mass range from 40 MeV/c^{2} to 10 GeV/c^{2} for pointlike dark matter-electron interaction, 100 MeV/c^{2} to 10 GeV/c^{2} for dark matter-electron interaction via a light mediator, and 3.2 to 4 GeV/c^{2} for dark matter-nucleon spin-independent interaction. For DM interaction with electrons, our limits are closing in on the parameter space predicted by the freeze-in and freeze-out mechanisms in the early Universe.

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Hydrochar has become a popular product for immobilizing heavy metals in water bodies. However, the relationships between the preparation conditions, hydrochar properties, adsorption conditions, heavy metal types, and the maximum adsorption capacity (Qm) of hydrochar are not adequately explored. Four artificial intelligence models were used in this study to predict the Qm of hydrochar and identify the key influencing factors. The gradient boosting decision tree (GBDT) showed excellent predictive capability for this study (R2 = 0.93, RMSE = 25.65). Hydrochar properties (37%) controlled heavy metal adsorption. Meanwhile, the optimal hydrochar properties were revealed, including the C, H, N, and O contents of 57.28-78.31%, 3.56-5.61%, 2.01-6.42%, and 20.78-25.37%. Higher hydrothermal temperatures (>220 °C) and longer hydrothermal time (>10 h) lead to the optimal type and density of surface functional groups for heavy metal adsorption, which increased the Qm values. This study has great potential for instructing industrial applications of hydrochar in treating heavy metal pollution.

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INTRODUCTION: As one of the most commonly used anesthetics, isoflurane has been demonstrated to possess a variety of protective effects. However, its' neurological impaired effect should be considered during clinical application. Roles of lncRNA BDNF-AS (BDNF-AS) and miR-214-3p in isoflurane-injured microglia and rats were investigated in this study, aiming to disclose the mechanism of isoflurane damage and to provide candidate therapeutic targets. MATERIAL AND METHODS: Isoflurane-induced microglia cells and rat models were established with 1.5% isoflurane. Inflammation and oxidative stress of microglia cells were evaluated with a level of pro-inflammation cytokines, malondialdehyde (MDA), superoxide dismutase (SOD), and nitrite. Cognitive and learning function of rats were assessed with Morris water maze task. Expressions of BDNF-AS and miR-214-3p and their function in the isoflurane-induced microglia cells and rats were estimated with PCR and corresponding transfection. RESULTS: Isoflurane induced significant neuro-inflammation and oxidative stress in the microglia cells. The increased BDNF-AS and the decreased miR-214-3p were noted, and BDNF-AS was found to negatively regulate miR-214-3p in the isoflurane-induced microglia cells. Isoflurane caused cognitive dysfunction in rats, and resulted in a significant inflammatory response. The knockdown of BDNF-AS significantly alleviated the neurological impairment induced by isoflurane, which was reversed by silencing miR-214-3p. CONCLUSIONS: In isoflurane-induced neuro-inflammation and cognitive dysfunction, BDNF-AS showed a significant protective effect on the neurological impairment induced by isoflurane through modulating miR-214-3p.

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A search for interactions from solar ^{8}B neutrinos elastically scattering off xenon nuclei using PandaX-4T commissioning data is reported. The energy threshold of this search is further lowered compared with the previous search for dark matter, with various techniques utilized to suppress the background that emerges from data with the lowered threshold. A blind analysis is performed on the data with an effective exposure of 0.48 tonne year, and no significant excess of events is observed. Among the results obtained using the neutrino-nucleus coherent scattering, our results give the best constraint on the solar ^{8}B neutrino flux. We further provide a more stringent limit on the cross section between dark matter and nucleon in the mass range from 3 to 9 GeV/c^{2}.

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Background: Proprioception is important for our everyday activity, as it indicates the position, movement, and force on the body. This is important not only for ambulation but also for patients who are diagnosed with stroke. Objective: This study aimed to evaluate the influence of proprioceptive training on lower limb function in patients after a stroke using an ankle-foot robot. Method: In total, 60 adult participants who met the criteria were randomly divided into a control group and an experimental group. The control group (RG) was given regular physical activity, and the sensory training group (SG) was given proprioceptive training based on an ankle-foot robot, the rest being the same as RG. Measurements for 10-meter walking time (10MWT), the Berg Balance Scale (BBS), the Fugl-Meyer assessment of lower extremity (FMA-LE), and active range of motion (AROM), passive range of motion (PROM), and ankle joint sensitivity before and after 6 weeks of treatment (30 sessions; five times per week) were assessed. Results: There was a significant decrease in both 10MWT and ankle joint sensitivity in both groups (p < 0.05), while there was a significant increase in BBS, FMA-LE, AROM, and PROM in both groups (p < 0.05). A significant relationship was identified between the two groups, the SG group had greater degrees of improvement compared to the RG group. Conclusion: The proprioceptive training based on an ankle-foot robot could improve proprioception and effectively improve the motor function and walking ability in patients after a stroke. Proprioceptive strength training is recommended to be emphasized in the regular rehabilitation of patients after a stroke.

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Compared with the signature of dark matter elastic scattering off nuclei, the absorption of fermionic dark matter by nuclei opens up a new searching channel for light dark matter with a characteristic monoenergetic signal. In this Letter, we explore the 95.0-day data from the PandaX-4T commissioning run and report the first dedicated searching results of the fermionic dark matter absorption signal through a neutral current process. No significant signal was found, and the lowest limit on the dark matter-nucleon interaction cross section is set to be 1.5×10^{-50} cm^{2} for a fermionic dark matter mass of 40 MeV/c^{2} with 90% confidence level.

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We report a search on sub-MeV fermionic dark matter absorbed by electrons with an outgoing active neutrino using the 0.63 tonne year exposure collected by the PandaX-4T liquid xenon experiment. No significant signals are observed over the expected background. The data are interpreted into limits to the effective couplings between such dark matter and the electron. For axial-vector or vector interactions, our sensitivity is competitive in comparison to existing astrophysical bounds on the decay of such a dark matter candidate into photon final states. In particular, we present the first direct detection limits for a vector (axial-vector) interaction which are the strongest in the mass range from 35 to 55 (25 to 45) keV/c^{2} in comparison to other astrophysical and cosmological constraints.

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Vitamin D3 supplementation has been previously reported to inhibit the occurrence and development of chronic obstructive pulmonary disease (COPD). However, the underlying mechanism remains unclear. Epithelial-mesenchymal transition (EMT) and fibrogenesis have been associated with the development of COPD. The aim of the present study was to investigate the potential effects and mechanism of vitamin D3 in an in vitro model of cigarette smoke (CS)-induced EMT and fibrosis, with specific focus on the role of club cell protein 16 (CC16). CS extract (CSE) at different concentrations (5, 10 and 20%) was used to treat 16-HBE cells to induce EMT and fibrogenesis following which they were treated with vitamin D3. Subsequently, the 20% CSE group was selected for further experiments, where 16-HBE cells were divided into the following five groups: The control group; the CSE group; the low-dose vitamin D3 group (250 nM); the medium-dose vitamin D3 group (500 nM); and the high-dose vitamin D3 group (1,000 nM). Western blot analysis was used to detect the protein expression levels of the EMT-related proteins E-cadherin, N-cadherin, Slug and α-SMA, fibrogenesis-related proteins collagen Ⅳ and fibronectin 1, proteins involved in the TGF-ß1/SMAD3 signaling pathway and CC16. Immunofluorescence was used to measure the protein expression levels of E-cadherin, N-cadherin and collagen Ⅳ. Specific CC16 knockdown was performed using short hairpin RNA transfection to investigate the role of CC16. The results of the present study found that vitamin D3 could increase the protein expression level of CC16 to inhibit the activation of the TGF-ß1/SMAD3 signaling pathway; thereby reducing the 20% increase in CSE-induced EMT- and fibrogenesis-related protein expression levels. Following CC16 knockdown, the inhibitory effects of vitamin D3 on EMT- and fibrogenesis-related protein expression were partially reversed. To conclude, these results suggest that vitamin D3 can inhibit the protein expression levels of EMT- and fibrogenesis-related proteins induced by CSE, at least partially through the function of CC16. These findings are expected to provide novel theoretical foundations and ideas for the pathogenesis and treatment of COPD.

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We report a novel search for the cosmic-ray boosted dark matter using the 100 tonne·day full dataset of the PandaX-II detector located at the China Jinping Underground Laboratory. With the extra energy gained from the cosmic rays, sub-GeV dark matter particles can produce visible recoil signals in the detector. The diurnal modulations in rate and energy spectrum are utilized to further enhance the signal sensitivity. Our result excludes the dark matter-nucleon elastic scattering cross section between 10^{-31} and 10^{-28} cm^{2} for dark matter masses from 0.1 MeV/c^{2} to 0.1 GeV/c^{2}, with a large parameter space previously unexplored by experimental collaborations.