This paper comprehensively discusses on the potential neurobiological mechanisms of acupuncture in the treatment of tobacco dependence， focusing on three important aspects， including acupuncture's regulation of tobacco dependence behavior， effects of acupuncture on withdrawal syndrome， and the role of acupuncture in preventing relapse. It is found that acupuncture can inhibit drug-seeking behavior by regulating the reward pathway and related neurons， such as dopamine， thus modulating tobacco dependence behavior. It also alleviates withdrawal symptoms by improving the oral environment of smokers and reducing negative emotions after quitting. Furthermore， acupuncture can prevent relapse by decreasing brain network activity related to smoking cravings and improving cognitive brain functions like addiction memory. Currently， research on the specific neurobiological mechanism of acupuncture in treating tobacco dependence and the involved neural circuits is limited. Future research directions are proposed， including the evaluation of clinical effects， exploration of specific therapeutic mechanisms， investigation of brain pathology， and strengthening the exploration of brain functions. Additionally， combining modern technologies to clarify the neural circuits involved in acupuncture intervention will provide a basis for acupuncture treatment of tobacco addiction.

ObjectiveTo compare the differences in color， odor， coumarin content and microbial community composition of Angelicae Dahuricae Radix（ADR） during different drying processes， and to explore the correlation between changes in microbial community composition and changes in quality indexes of ADR. MethodsThe fresh ADR was processed at three drying temperatures（50， 70， 100 ℃） by drying and steaming cutting， semi-fresh cutting and drying， fresh cutting and drying， and sulfur fumigation methods. The color values of samples were extracted by Adobe Photoshop 2022 software and subjected to principal component analysis（PCA）， electronic nose was used to identify the odor information of medicinal powders and subjected to loadings analysis， PCA， and linear discriminant analysis（LDA）， and high performance liquid chromatography（HPLC） was used to determine the contents of five coumarins（bergapten， oxypeucedanin， imperatorin， phellopterin， isoimperatorin）. The samples for microbial detection were taken from fresh dried samples， 50 ℃（dried and steamed cut， sulfur fumigated） samples， and 100 ℃（dried and steamed cut） samples when the water content was 50% and 14%， respectively. And the changes of microbial community composition during processing were determined by high-throughput sequencing method. The relationship between the changes of microbial community composition and the changes of odor， color and active component content of ADR during drying process was analyzed by Pearson correlation analysis. ResultsThe color quantification results showed that an increase in drying temperature led to the decrease of brightness value（L）， and the increases of red-green value（a） and yellow-blue value（b）， and the change of processing method had no obvious effect on the color of medicinal materials. The results of odor quantification showed that W1S， W2S， W5S， W2W and W1W sensor were sensitive to the odor changes of ADR and could be used to distinguish ADR decoction pieces from different processing methods. The results of HPLC showed that the coumarin content of ADR decreased with the increase of drying temperature and the delay of processing time， the optimal processing method was drying and steaming cutting method， and the optimal temperature was 50 ℃. High-throughput sequencing results showed that the dominant bacteria in ADR during processing were Achromobacter， Agrobacterium， Nocardioides， Mycobacterium and Enterobacter， the dominant fungi were Coprinopsis， Meyerozyma and Apiotrichum. The results of correlation analysis showed that the quality indexes of ADR were positively correlated with Agrobacterium， Mycobacterium in bacteria， Candida in fungi， and negatively correlated with Bacillus in bacteria. ConclusionThere are significant differences in the color， odor， coumarin content and microbial community composition of ADR in different drying processes， and the best drying method is drying and steaming cutting at 50 ℃. The relative abundance changes of 9 bacterial genera and 4 fungal genera are closely related to the quality formation of ADR during the drying process.

[Objective] To study the molecular biological mechanism for a case of ABO blood group B subtype, and perform three-dimensional modeling of the mutant enzyme. [Methods] The ABO phenotype was identified by the tube method and microcolumn gel method; the ABO gene of the proband was detected by sequence-specific primer polymerase chain reaction (PCR-SSP), and the exon 6 and 7 of the ABO gene were sequenced and analyzed. Homologous modeling of Bw.03 glycosyltransferase (GT) was carried out by Modeller and analyzed by PyMOL2.5.0 software. [Results] The weakening B antigen was detected in the proband sample by forward typing, and anti-B antibody was detected by reverse typing. PCR-SSP detection showed B, O gene, and the sequencing results showed c.721 C>T mutation in exon 7 of the B gene, resulting in p. Arg 241 Trp. Compared with the wild type, the structure of Bw.03GT was partially changed, and the intermolecular force analysis showed that the original three hydrogen bonds at 241 position disappeared. [Conclusion] Blood group molecular biology examination is helpful for the accurate identification of ambiguous blood group. Homologous modeling more intuitively shows the key site for the weakening of Bw.03 GT activity. The intermolecular force analysis can explain the root cause of enzyme activity weakening.

To evaluate long-term survival and clinical outcomes of patients with knee osteo-arthritis undergoing total knee arthroplasty (TKA) through long-term follow-up.

BACKGROUND:Several observational studies have found a close relationship between thyroid function levels and sarcopenia,but the causal relationship between thyroid function levels and the onset of sarcopenia is not yet clear. OBJECTIVE:To investigate the causal relationship between thyroid function levels and sarcopenia using a two sample Mendelian randomization method. METHODS:A two sample Mendelian randomization analysis was conducted using genome-wide association study data on thyrotropin,free triiodothyronine,free tetraiodothyronine,subclinical hyperthyroidism,subclinical hypothyroidism,and four related phenotypes of sarcopenia-lefthand grip strength,right hand grip strength,limb lean mass,and gait speed.The inverse-variance weighted method,weighted median method,simple mode method,weighted median estimator method,and MR Egger regression method were used as analysis methods,while heterogeneity test,pleiotropy test,MR-PRESSO,leave-one-out method,funnel plot and other methods were used for sensitivity analysis. RESULTS AND CONCLUSION:Elevated levels of thyroid-stimulating hormone increased left-(β=0.02,SE=0.01,P=0.01)and right-handed grip strength(β=0.02,SE=0.01,P=0.01),an increase in free triiodothyronine decreased left-(β=-0.06,SE=0.02,P=9.5×10-5)and right-handed grip strength(β=-0.07,SE=0.02,P=9.3×10-5),and subclinical hyperthyroidism decreased gait speed(β=-4.4×10-3,SE=1.7×10-3,P=0.01).The sensitivity analysis results were basically consistent with the main analysis results.To conclude,an increase in thyroid-stimulating hormone is a protective factor for sarcopenia,and elevation of free triiodothyronine and subclinical hyperthyroidism may increase the risk of sarcopenia.

Since its establishment in 2016, the National Rare Diseases Registry System of China (NRDRS) has accumulated valuable case data and bio-specimen for basic and clinical research on rare diseases in China. However, the emerging challenges in clinical diagnosis and treatment of rare diseases make it unable for data and resource platform to fully meet the diversified needs. Under this backdrop, we have developed a protocol to optimize and upgrade the system based on the core functions of the NRDRS platform. The goal is to leverage intelligent digital technologies to transform NRDRS into a new platform integrating multimodal data and auxiliary diagnostic and treatment functions. It is specified as the development and construction of "one platform and four intelligent tools." Currently, we have upgraded and developed NRDRS platform, intelligent tool for genotype-phenotype analysis of rare diseases, AI-assisted diagnostic tool for rare diseases, remote multidisciplinary diagnosis and teaching tool for rare diseases, drug screening and validation tool for rare diseases. The next step will focus on the promotion of the application of these tools in clinical settings in order to address the issue of severe imbalance in the allocation of resources for the diagnosis and treatment of rare diseases. This article provides an overview of the digital and intelligent upgrades of the NRDRS, the trials in applications in clinical settings, and direction in the future.

The shaoyang meridian is an important pivot between the internal organs and meridians system， with the functions of regulating qi and blood， balancing yin and yang， and coordinating the ascending and descending movement of qi. Dysfunction of the shaoyang pivot can lead to spleen and kidney deficiency， impaired liver and gallbladder qi regulation， and stagnation of qi and blood. It is believed that the onset and progression of Crohn's disease are closely related to shaoyang pivot dysfunction， with the core pathogenesis characterized by shaoyang disharmony， spleen deficiency， dampness retention， and blood stasis. Based on this understanding， the treatment principle centers on harmonizing the shaoyang pivot， supplemented by methods such as warming and nourishing the spleen and stomach， tonifying shaoyang， and soothing the liver and benefiting the gallbladder. Acupuncture is employed to target key acupoints along the shaoyang meridian to restore its regulatory functions， improve spleen and stomach transformation and transportation， facilitate liver and gallbladder qi flow， and promote the circulation of qi and blood. This provides a practical therapeutic approach for acupuncture-based treatment of Crohn's disease.

Background: The association of changes in metabolic syndrome (MetS) with cognitive function remains unclear. We explored this association using prospective and Mendelian randomization (MR) studies. Methods: MetS components including high-density lipoprotein cholesterol (HDL-C), systolic blood pressure (SBP), waist circumference (WC), fasting plasma glucose (FPG), and triglycerides were measured at baseline and two follow-ups, constructing a MetS index. Immediate, delayed memory recall, and cognitive function along with its dimensions were assessed by immediate 10- word recall test (IWRT) and delayed 10-word recall test (DWRT), and mini-mental state examination (MMSE), respectively, at baseline and follow-ups. Linear mixed-effect model was used. Additionally, the genome-wide association study (GWAS) of MetS was conducted and one-sample MR was performed to assess the causality between MetS and cognitive function. Results: Elevated MetS index was associated with decreasing annual change rates (decrease) in DWRT and MMSE scores, and with decreases in attention, calculation and recall dimensions. HDL-C was positively associated with an increase in DWRT scores, while SBP and FPG were negatively associated. HDL-C showed a positive association, whereas WC was negatively associated with increases in MMSE scores, including attention, calculation and recall dimensions. Interaction analysis indicated that the association of MetS index on cognitive decline was predominantly observed in low family income group. The GWAS of MetS identified some genetic variants. MR results showed a non-significant causality between MetS and decrease in DWRT, IWRT, nor MMSE scores. Conclusion Our study indicated a significant association of MetS and its components with declines in memory and cognitive function, especially in delayed memory recall.

The etiology of tumors is complex and influenced by multiple factors, including the host and environmental conditions. Allergy is primarily driven by the immune response of helper T cell 2 (Th2). Research has shown that the Th2 immune response is closely related to tumors, which is specifically manifested through Th2 antibodies, allergy-related effector cells and mediators within the tumors, as well as tumor immune-related functions. This internal interaction mechanism will increase the complexity and challenges associated with the clinical diagnosis and treatment of tumors and allergy. The formation of allergic constitution is shaped by both congenital and acquired factors, and its physical state is closely linked to the occurrence and progression of allergic diseases. Therefore, this paper aims to explore the relationship between tumors and allergic reactions from the perspective of traditional Chinese medicine (TCM) constitution theory. Based on the four basic principles of the TCM constitution, including endowment inheritance theory, environment constraint theory, body-spirit composition theory, and life process theory, this exploration will focus on four aspects: genetic factors and internal disease causes, inflammatory environments and functional regulation, psychological disorders and emotional pathogenesis, as well as age structure and disease risk. Furthermore, from the perspective of constitution-disease relation of chronic disease prevention, this paper will discuss the significant importance of adjusting allergic constitution to improve both subjective symptoms and objective indicators of allergic reactions in tumor patients.

OBJECTIVE To provide medication reference for duloxetine use in clinical settings， particularly for patients with depression in primary medical institutions in Xinjiang that lack therapeutic drug monitoring conditions. METHODS The medical records of 281 depression inpatients taking duloxetine in the First Affiliated Hospital of Xinjiang Medical University from January 2022 to December 2023 were retrospectively collected. They were divided into training set （196 cases） and test set （85 cases） in the ratio of 7∶3. Feature selection was performed by encapsulating random forests （RF） with recursive feature elimination. Four machine learning algorithms， namely support vector machine， RF， extreme gradient boosting （XGBoost） and artificial neural network， were used to construct duloxetine blood concentration prediction model. The prediction performance of the models was evaluated and compared by coefficient of determination （R2）， mean absolute error （MAE） and root mean squared error （RMSE）. The feature of the selected optimal model was explained by Shapley additive explanation method， and the importance ranking of the features and the influence on the prediction results of duloxetine blood concentration were determined. RESULTS A total of 29 characteristic variables were selected， including age， ethnicity， body mass index（BMI）， etc. XGBoost showed the highest R2 （0.808）， and the lowest MAE （7.644） and RMSE （10.808）. The ranking of feature importance for predicting the blood concentration of duloxetine was as follows： BMI＞age＞other 20 feature sets （including liver and kidney function and biochemical indicators）＞daily dosage＞comorbidities＞combination therapy＞ethnicity＞white blood cell count＞hemoglobin＞height. CONCLUSIONS XGBoost model possesses the best prediction performance of duloxetine blood concentration； BMI and age have a greater impact on the prediction of duloxetine blood concentration.