ObjectiveBy comparing the composition and content of volatile components in raw products， wine-washed products and wine-fried products of Ligusticum sinense cv. Chaxiong rhizome（LSCR）， to investigate the influence of wine processing on the volatile components of LSCR， in order to provide a basis for the development of quality standards for LSCR and its processed products. MethodsElectronic nose was used to identify the odors of LSCR， wine-washed and wine-fried LSCR， and their volatile components were detected by headspace gas chromatography-mass spectrometry（HS-GC-MS）， and the relative mass fractions of these components were determined by peak area normalization method. Principal component analysis（PCA） and orthogonal partial least squares-discriminant analysis（OPLS-DA） were performed on the obtained sample data by SIMCA 14.1 software， and the differential components of LSCR， wine-washed and wine-fried LSCR were screened according to the variable importance in the projection（VIP） value>1. Pearson correlation analysis was used to explore the relationship between volatile differential flavor components and electronic nose sensors. ResultsElectronic nose detection results showed that there were significant differences in the odors of LSCR， wine-washed and wine-fried LSCR， mainly reflected in the sensors S2， S4， S5， S6， S11， S12， S13. And a total of 62 compounds were identified from LSCR and its wine-processed products， among which 46， 50 and 51 compounds were identified from LSCR， wine-fried and wine-washed LSCR， respectively. There were 21 differential components between the raw products and wine-fried products， of which 10 components were increased and 11 were decreased after processing. There were 20 differential components between the raw products and wine-washed products， of which 11 constituents increased and 9 decreased after processing. There were 17 differential components between the wine-wash products and wine-fried products. Compared with the wine-washed products， the contents of 13 components in the wine-fried products increased， and the contents of 4 components decreased. The increasing trend of the content of phthalides in the wine-washed products was more obvious than that in the wine-fried products， but the content of total volatile components was higher in the wine-fried products than the wine-washed products. Correlation analysis showed that there were different degrees of correlation between the 7 differential sensors of electronic nose and 24 differential volatile components， mainly phthalides and olefins. ConclusionThe odor and the content of volatile components in LSCR changed obviously after wine processing， and n-butylphthalide， Z-butylidenephthalide and E-ligustilide can be used as the candidate differential markers of volatile components in LSCR before and after wine processing.

ObjectiveTo investigate the influence of entecavir （ETV） versus tenofovir alafenamide fumarate （TAF） on renal function in previously untreated patients with chronic hepatitis B （CHB）. MethodsA retrospective analysis was performed for the clinical data of 167 previously untreated CHB patients who received ETV or TAF treatment for at least 48 weeks at the outpatient service of Department of Infectious Diseases in The First Affiliated Hospital of Nanchang University from September 2019 to November 2023， and according to the antiviral drug used， they were divided into ETV group with 117 patients and TAF group with 50 patients. In order to balance baseline clinical data， propensity score matching （PSM） was used for matching and analysis at a ratio of 2∶1， and the two groups were compared in terms of estimated glomerular filtration rate （eGFR） and the incidence rate of abnormal renal function at week 48. According to eGFR at week 48， the patients were divided into normal renal function group and abnormal renal function group. The independent-samples t test or the Mann-Whitney U test was used for comparison of continuous data between two groups， and the chi-square test or the Fisher’s exact test was used for comparison of categorical data between two groups. The multivariate Logistic regression analysis was used to investigate the influencing factors for abnormal renal function， and the receiver operating characteristic （ROC） curve was used to assess the performance of each indicator in predicting abnormal renal function. The Kaplan-Meier method was used to analyze the cumulative incidence rate of abnormal renal function， and the log-rank test was used for comparison. The analysis of variance with repeated measures was used to compare the dynamic changes of eGFR during antiviral therapy in CHB patients. ResultsAfter PSM matching， there were 100 patients in the ETV group and 50 patients in the TAF group. There were no significant differences in baseline clinical data between the ETV group and the TAF group （all P>0.05）， with an eGFR level of 112.29±9.92 mL/min/1.73 m² in the ETV group and 114.72±12.15 mL/min/1.73 m² in the TAF group. There was a reduction in eGFR from baseline to week 48 in both groups， and compared with the TAF group at week 48， the ETV group had a significantly lower eGFR （106.42±14.12 mL/min/1.73 m² vs 112.25±13.44 mL/min/1.73 m²， t=-2.422， P=0.017） and a significantly higher incidence rate of abnormal renal function （17.00% vs 4.00%， χ²=5.092， P=0.024）. After the patients were divided into normal renal function group with 131 patients and abnormal renal function group with 19 patients， the univariate analysis showed that there were significant differences between the two groups in age （Z=-2.039， P=0.041）， treatment drug （ETV/TAF） （χ²=5.092， P=0.024）， and baseline eGFR level （t=4.023， P<0.001）， and the multivariate Logistic regression analysis showed that baseline eGFR （odds ratio ［OR］=0.896， 95% confidence interval ［CI］： 0.841 — 0.955， P<0.001） and treatment drug （OR=5.589， 95%CI： 1.136 — 27.492， P=0.034） were independent influencing factors for abnormal renal function. Baseline eGFR had an area under the ROC curve of 0.781 in predicting abnormal renal function in CHB patients， with a cut-off value of 105.24 mL/min/1.73 m²， a sensitivity of 73.68%， and a specificity of 82.44%. The Kaplan-Meier curve analysis showed that the patients with baseline eGFR≤105.24 mL/min/1.73 m² had a significantly higher cumulative incidence rate of abnormal renal function than those with baseline eGFR>105.24 mL/min/1.73 m² （χ²=22.330， P<0.001）， and the ETV group had a significantly higher cumulative incidence rate of abnormal renal function than the TAF group （χ²=4.961， P=0.026）. With the initiation of antiviral therapy， both the ETV group and the TAF group had a significant reduction in eGFR （F=5.259， P<0.001）， but the ETV group only had a significant lower level of eGFR than the TAF group at week 48 （t=-2.422， P=0.017）； both the baseline eGFR≤105.24 mL/min/1.73 m² group and the baseline eGFR>105.24 mL/min/1.73 m² group had a significant reduction in eGFR （F=5.712， P<0.001）， and there was a significant difference in eGFR between the two groups at baseline and weeks 12， 24， 36， and 48 （t=-13.927， -9.780， -8.835， -9.489， and -8.953， all P<0.001）. ConclusionFor CHB patients initially treated with ETV or TAF， ETV antiviral therapy has a higher risk of renal injury than TAF therapy at week 48.

GPR126, also known as ADGRG6, is one of the most deeply studied aGPCRs. Initially, GPR126 was thought to be a receptor associated with muscle development and was primarily expressed in the muscular and skeletal systems. With the deepening of research, it was found that GPR126 is expressed in multiple mammalian tissues and organs, and is involved in many biological processes such as embryonic development, nervous system development, and extracellular matrix interactions. Compared with other aGPCRs proteins, GPR126 has a longer N-terminal domain, which can bind to ligands one-to-one and one-to-many. Its N-terminus contains five domains, a CUB (complement C1r/C1s, Uegf, Bmp1) domain, a PTX (Pentraxin) domain, a SEA (Sperm protein, Enterokinase, and Agrin) domain, a hormone binding (HormR) domain, and a conserved GAIN domain. The GAIN domain has a self-shearing function, which is essential for the maturation, stability, transport and function of aGPCRs. Different SEA domains constitute different GPR126 isomers, which can regulate the activation and closure of downstream signaling pathways through conformational changes. GPR126 has a typical aGPCRs seven-transmembrane helical structure, which can be coupled to Gs and Gi, causing cAMP to up- or down-regulation, mediating transmembrane signaling and participating in the regulation of cell proliferation, differentiation and migration. GPR126 is activated in a tethered-stalk peptide agonism or orthosteric agonism, which is mainly manifested by self-proteolysis or conformational changes in the GAIN domain, which mediates the rapid activation or closure of downstream pathways by tethered agonists. In addition to the tethered short stem peptide activation mode, GPR126 also has another allosteric agonism or tunable agonism mode, which is specifically expressed as the GAIN domain does not have self-shearing function in the physiological state, NTF and CTF always maintain the binding state, and the NTF binds to the ligand to cause conformational changes of the receptor, which somehow transmits signals to the GAIN domain in a spatial structure. The GAIN domain can cause the 7TM domain to produce an activated or inhibited signal for signal transduction, For example, type IV collagen interacts with the CUB and PTX domains of GPR126 to activate GPR126 downstream signal transduction. GPR126 has homology of 51.6%-86.9% among different species, with 10 conserved regions between different species, which can be traced back to the oldest metazoans as well as unicellular animals.In terms of diseases, GPR126 dysfunction involves the pathological process of bone, myelin, embryo and other related diseases, and is also closely related to the occurrence and development of malignant tumors such as breast cancer and colon cancer. However, the biological function of GPR126 in various diseases and its potential as a therapeutic target still needs further research. This paper focuses on the structure, interspecies differences and conservatism, signal transduction and biological functions of GPR126, which provides ideas and references for future research on GPR126.

ObjectiveTo elucidate the critical role of rehabilitation medical records (including electronic records) in rehabilitation medicine's clinical practice and management, comprehensively analyzed the structure, core content and data standards of rehabilitation medical records, to develop a standardized medical record data architecture and core dataset suitable for rehabilitation medicine and to explore the application of rehabilitation data in performance evaluation and payment. MethodsBased on the regulatory documents Basic Specifications for Medical Record Writing and Basic Specifications for Electronic Medical Records (Trial) issued by National Health Commission of China, and referencing the World Health Organization (WHO) Family of International Classifications (WHO-FICs) classifications, International Classification of Diseases (ICD-10/ICD-11), International Classification of Functioning, Disability and Health (ICF), and International Classification of Health Interventions (ICHI Beta-3), this study constructed the data architecture, core content and data standards for rehabilitation medical records. Furthermore, it explored the application of rehabilitation record summary sheets (home page) data in rehabilitation medical statistics and payment methods, including Diagnosis-related Groups (DRG), Diagnosis-Intervention Packet (DIP) and Case Mix Index. ResultsThis study proposed a systematic standard framework for rehabilitation medical records, covering key components such as patient demographics, rehabilitation diagnosis, functional assessment, rehabilitation treatment prescriptions, progress evaluations and discharge summaries. The research analyzed the systematic application methods and data standards of ICD-10/ICD-11, ICF and ICHI Beta-3 in the fields of medical record terminology, coding and assessment. Constructing a standardized data structure and data standards for rehabilitation medical records can significantly improve the quality of data reporting based on the medical record summary sheet, thereby enhancing the quality control of rehabilitation services, effectively supporting the optimization of rehabilitation medical insurance payment mechanisms, and contributing to the establishment of rehabilitation medical performance evaluation and payment based on DRG and DIP. ConclusionStructured rehabilitation records and data standardization are crucial tools for quality control in rehabilitation. Systematically applying the three reference classifications of the WHO-FICs, and aligning with national medical record and electronic health record specifications, facilitate the development of a standardized rehabilitation record architecture and core dataset. Standardizing rehabilitation care pathways based on the ICF methodology, and developing ICF- and ICD-11-based rehabilitation assessment tools, auxiliary diagnostic and therapeutic systems, and supporting terminology and coding systems, can effectively enhance the quality of rehabilitation records and enable interoperability and sharing of rehabilitation data with other medical data, ultimately improving the quality and safety of rehabilitation services.

Objective: To explore the relationship of physical exercise behavior with mobile phone addiction and mental health of college students, so as to provide evidence for interventions to improve mobile phone addiction and mental health of college students. Methods: From October 8 to December 20 in 2024, 896 college students from 4 colleges in Beijing were selected using a combination of convenience sampling and stratified random cluster sampling method. Physical Activity Rating Scale (PARS-3), Mobile Phone Addiction Tendency Scale (MPATS), Adolescence Mental Health Diathesis Questionnaire (AMHDQ) and Symptom Checklist 90 (SCL-90) were used. The correlation of mobile phone addiction and mental health on physical exercise behavior of college students were analyzed by multivariable Logistic regression and linear regression. Results: Among the surveyed college students, 504 (56.25%) students had low exercise, 262 (29.24%) had moderate exercise, 130 (14.51%) had high exercise, and 392 (43.75%) had sufficient exercise. The total score of PARS-3 was 18.00 ( 15.00 , 33.00) points. Logistic regression analysis showed that the total score of MPATS ( OR=1.022, 95%CI =1.008-1.036), the total score of SCL-90 ( OR=1.010, 95%CI = 1.005 -1.015), the total AMHDQ score ( OR=0.995, 95%CI =0.992-0.998) were significantly associated with insufficient exercise among college students ( P <0.05). Linear regression analysis showed that the scores of MPATS, AMHDQS and SCL-90 were significantly correlated with physical exercise behavior ( B=-0.20, 0.04, -0.07, P <0.05). Conclusion The physical exercise behavior of college students is related to mobile phone addiction and mental health.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Abstract The construction of autism spectrum disorders (ASD) specialty cohorts in China is still in its infancy, and the cost effectiveness is insufficient when relying on diagnostic and treatment processes of child health care to collect ample and high quality data. After 2000, the United States Simons Foundation s ASD Research Initiative, the Early ASD Risk Longitudinal Investigation (EARLI), and the British ASD Study of Infant Siblings (BASIS), which have been built based on Internet recruitment, have provided new insight for the construction of large sample ASD specialty cohorts in China. Future research can further explore and optimize the methods of Internet recruitment, and establish a more comprehensive and accurate ASD specialty cohorts.