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.

Traditional Chinese medicine(TCM) decoction pieces are a core carrier for the inheritance and innovation of TCM, and their quality and safety are critical to public health and the sustainable development of the industry. Conventional quality control models, while having established a well-developed system through long-term practice, still face challenges such as relatively long inspection cycles, insufficient objectivity in characterizing complex traits, and urgent needs for improving the efficiency of integrating multidimensional quality information when confronted with the dual demands of large-scale production and precision quality control. With the rapid development of artificial intelligence, machine learning can deeply analyze multidimensional data of the morphology, spectroscopy, and chemical fingerprints of decoction pieces by constructing high-dimensional feature space analysis models, significantly improving the standardization level and decision-making efficiency of quality evaluation. This article reviews the research progress in the application of machine learning in the processing, production, and rapid quality evaluation of TCM decoction pieces. It further analyzes current challenges in technological implementation and proposes potential solutions, offering theoretical and technical references to advance the digital and intelligent transformation of the industry.
Machine Learning ; Drugs, Chinese Herbal/standards* ; Quality Control ; Medicine, Chinese Traditional/standards* ; Humans

OBJECTIVE: Investigating the clinical efficacy of treating dorsally displaced distal radial double-column Die-punch fractures using a dorsal approach external fixator combined with Kirschner wires. METHODS: Retrospectively analyzed the clinical data of 15 patients with distal radial double-column Die-punch fractures treated with an external fixator combined with Kirschner wire between July 2020 and January 2023. There were 10 males and 5 females;6 cases on the left side and 9 on the right;age ranged from 22 to 76 years old. Recorded the preoperative and the final follow-up Cooney wrist function scores for the patients. The fracture healing time, and occurrence of complications were recorded. RESULTS: All 15 patients were followed up ranged from 12 to 16 months post-operation. All fractures achieved bony union, healing time ranging form 8 to 16 weeks. Not a single patient exhibited complications such as surgical site infection, fracture redislocation, or tendon injury. All individuals had their Kirschner wires and external fixation devices removed six weeks post-operatively and commenced rehabilitative therapy for wrist articulation. The Cooney wrist function scores at preoperative and ranged from 5 to 45 scores, at the latest follow-up ranged from 65 to 100 scores. At the final follow-up, the results were assessed as excellent in 10 patients, good in 4 patients, and fair in 1 patient. CONCLUSION The clinical efficacy of treating distal radial double-column Die-punch fractures using a dorsal approach external fixator combined with Kirschner wires is satisfactory.
Humans ; Male ; Female ; Middle Aged ; Adult ; External Fixators ; Bone Wires ; Aged ; Retrospective Studies ; Radius Fractures/physiopathology* ; Young Adult ; Fracture Fixation/methods*

BACKGROUND: Non-invasive computed tomography angiography (CTA)-based fractional flow reserve (CT-FFR) could become a gatekeeper to invasive coronary angiography. Deep learning (DL)-based CT-FFR has shown promise when compared to invasive FFR. To evaluate the performance of a DL-based CT-FFR technique, DeepVessel FFR (DVFFR). METHODS: This retrospective study was designed for iScheMia Assessment based on a Retrospective, single-center Trial of CT-FFR (SMART). Patients suspected of stable coronary artery disease (CAD) and undergoing both CTA and invasive FFR examinations were consecutively selected from the Beijing Anzhen Hospital between January 1, 2016 to December 30, 2018. FFR obtained during invasive coronary angiography was used as the reference standard. DVFFR was calculated blindly using a DL-based CT-FFR approach that utilized the complete tree structure of the coronary arteries. RESULTS: Three hundred and thirty nine patients (60.5 ±10.0 years and 209 men) and 414 vessels with direct invasive FFR were included in the analysis. At per-vessel level, sensitivity, specificity, accuracy, positive predictive value (PPV) and negative predictive value (NPV) of DVFFR were 94.7%, 88.6%, 90.8%, 82.7%, and 96.7%, respectively. The area under the receiver operating characteristics curve (AUC) was 0.95 for DVFFR and 0.56 for CTA-based assessment with a significant difference (P < 0.0001). At patient level, sensitivity, specificity, accuracy, PPV and NPV of DVFFR were 93.8%, 88.0%, 90.3%, 83.0%, and 95.8%, respectively. The computation for DVFFR was fast with the average time of 22.5 ± 1.9 s. CONCLUSIONS The results demonstrate that DVFFR was able to evaluate lesion hemodynamic significance accurately and effectively with improved diagnostic performance over CTA alone. Coronary artery disease (CAD) is a critical disease in which coronary artery luminal narrowing may result in myocardial ischemia. Early and effective assessment of myocardial ischemia is essential for optimal treatment planning so as to improve the quality of life and reduce medical costs.

Objective To analyze the clinical characteristics of high energy metabolism in lung cancer patients and its correlation with body composition,nutritional status,and quality of life,and to develop a corresponding risk prediction model.Methods Retrospectively analyzed 132 primary lung cancer patients admitted to the First Hospital of Shanxi Medical University from January 2022 to May 2023,and categorized into high(n=94)and low energy metabolism group(n=38)based on their metabolic status.Differences in clinical data,body composition,Patient Generated Subjective Global Assessment(PG-SGA)scores,and European Organization for Research and treatment of Cancer(EORTC)Quality of Life Questionnaire-Core 30(QLQ-C30)scores were compared between the two groups.Logistic regression was used to identify the risk factors for high energy metabolism in lung cancer patients,and a risk prediction model was established accordingly;the Hosmer-Lemeshow test was used to assess the model fit,and the ROC curve was used to test the predictive efficacy of the model.Results Of the 132 patients with primary lung cancer,94(71.2%)exhibited high energy metabolism.Compared with low energy metabolism group,patients in high-energy metabolism group had a smoking index of 400 or higher,advanced disease staging of stage Ⅲ or Ⅳ,and higher levels of IL-6 level,low adiposity index,low skeletal muscle index,and malnutrition(P<0.05),and lower levels of total protein,albumin,hemoglobin level,and prognostic nutritional index(PNI)(P<0.05).There was no significant difference in age,gender,height,weight,BMI and disease type between the two groups(P>0.05).Logistic regression analysis showed that smoking index≥400,advanced disease stage,IL-6≥3.775 ng/L,and PNI<46.43 were independent risk factors for high energy metabolism in lung cancer patients.The AUC of the ROC curve for the established prediction model of high energy metabolism in lung cancer patients was 0.834(95%CI 0.763-0.904).Conclusion The high energy metabolic risk prediction model of lung cancer patients established in this study has good fit and prediction efficiency.

Objective To develop an automatic urine volume detection and collection device to solve the problems of routine urine test.Methods An automatic urine volume detection and collection device was developed with the components of a main control system,a detection system,a prompting system and a grasping and moving system.The main control system consisted of two STM32 microcontrollers and a reset switch;the detection system was made up of a weighing module,an infrared module and indicator lights,which had its urine volume automatic detection algorithm developed based on the Keil5 platform;the prompting system realized voice broadcasting through the voice module fixed on the back panel of the box;the grasping and moving system was composed of a rail drive motor(86CM stepper motor),a photoelectric switch and a motorized gripper.Results The device developed tested urine samples with an accuracy of 99.44％,and could collect qualified samples automatically and quickly.Conclusion The device developed detects urine volume and collects samples automatically,and enhances the accuracy and efficiency of urine examination.[Chinese Medical Equipment Journal,2024,45(4):66-69]

Tyrosine kinase inhibitors(TKIs)have emerged as the first-line small molecule drugs in many cancer therapies,exerting their effects by impeding aberrant cell growth and proliferation through the mod-ulation of tyrosine kinase-mediated signaling pathways.However,there exists a substantial inter-individual variability in the concentrations of certain TKIs and their metabolites,which may render patients with compromised immune function susceptible to diverse infections despite receiving theo-retically efficacious anticancer treatments,alongside other potential side effects or adverse reactions.Therefore,an urgent need exists for an up-to-date review concerning the biological matrices relevant to bioanalysis and the sampling methods,clinical pharmacokinetics,and therapeutic drug monitoring of different TKIs.This paper provides a comprehensive overview of the advancements in pretreatment methods,such as protein precipitation(PPT),liquid-liquid extraction(LLE),solid-phase extraction(SPE),micro-SPE(p-SPE),magnetic SPE(MSPE),and vortex-assisted dispersive SPE(VA-DSPE)achieved since 2017.It also highlights the latest analysis techniques such as newly developed high performance liquid chromatography(HPLC)and high-resolution mass spectrometry(HRMS)methods,capillary electro-phoresis(CE),gas chromatography(GC),supercritical fluid chromatography(SFC)procedures,surface plasmon resonance(SPR)assays as well as novel nanoprobes-based biosensing techniques.In addition,a comparison is made between the advantages and disadvantages of different approaches while pre-senting critical challenges and prospects in pharmacokinetic studies and therapeutic drug monitoring.

Objective To investigate the nutritional status of children with Crohn's Disease (CD) at diagnosis and its association with clinical characteristics. Methods A retrospective analysis was performed for the clinical data and nutritional status of 118 children with CD who were admitted to Beijing Children's Hospital,Capital Medical University,from January 2016 to January 2024. A multivariate logistic regression analysis was used to investigate the risk factors for malnutrition. Results A total of 118 children with CD were included,among whom there were 68 boys (57.6％) and 50 girls (42.4％),with a mean age of (11±4) years. Clinical symptoms mainly included recurrent abdominal pain (73.7％,87/118),diarrhea (37.3％,44/118),and hematochezia (32.2％,38/118),and 63.6％ (75/118) of the children had weight loss at diagnosis. The incidence rate of malnutrition was 63.6％ (75/118),and the children with moderate or severe malnutrition accounted for 67％ (50/75). There were 50 children (42.4％) with emaciation,8 (6.8％) with growth retardation,and 9 (7.6％) with overweight or obesity. Measurement of nutritional indices showed a reduction in serum albumin in 83 children (70.3％),anemia in 74 children (62.7％),and a reduction in 25 hydroxyvitamin D in 15 children (60％,15/25). The children with malnutrition had significantly higher disease activity,proportion of children with intestinal stenosis,and erythrocyte sedimentation rate and a significant reduction in serum albumin (P<0.05). The multivariate logistic regression analysis showed that intestinal stenosis was an independent risk factor for malnutrition in children with CD (OR=4.416,P<0.05). Conclusions There is a high incidence rate of malnutrition in children with CD at diagnosis,which is associated with disease activity and disease behavior. The nutritional status of children with CD should be closely monitored.

The current production of Chinese herbal decoction pieces faces several issues including strong subjectivity,unstable quality,low production efficiency,and a lack of intelligent systems.In order to expedite the intelligent transformation and upgrading of Chinese medicine processing,this paper delves deeply into the problems and challenges encountered in establishing a digital and intel-ligent production model for Chinese herbal pieces.Addressing the slow progress in fundamental research on traditional Chinese medi-cine processing mechanisms,the absence of online digital quality characterization techniques,the low level of production equipment in-telligence,and the lack of evaluation standards for high-quality decoction pieces,this paper proposes a"New Quality Productive Forces"formation approach driven by technological innovation.Through interdisciplinary integration methods,the paper explores the mechanisms of Chinese medicine processing in depth,clarifies the correlation between the processing procedures and the"medicinal properties-quality"relationship,and employs bionic sensing and artificial intelligence to achieve a holistic quality characterization of decoction pieces.Additionally,the use of cloud-edge collaborative big data systems is proposed to enhance intelligent upgrades of the production lines.The paper also aims to establish a high-quality decoction piece evaluation system integrating"physical-chemical-bio-logical"multimodal data fusion.This approach aims to steer the Chinese medicine processing towards becoming more efficient,precise,and sustainable,thereby promoting high-quality sustainable development of the Chinese herbal decoction industry and providing both theoretical and practical support for the modernization of traditional Chinese medicine.

Objective To establish a method for the simultaneous determination of aconitine,neoaconitine,hypaconitine,benzoyl aconitine,benzoyl mesaconine and benzoylhypacoitine in Xiaozhong ointment by UPLC-TQD-MS.Methods ACQUITY UPLC BEH C18 column(50 mm ×2.1 mm,1.7 μm),mobile phase 0.1％formic acid water(A)-acetonitrile(B),gradient elution,column temperature 40 ℃,flow rate 0.3 mL·min-1,injection volume 5 μL;electrospray ionization source(ESI+)and multiple reaction monitoring(MRM)were used for mass spectrometry analysis.Results The concentration of aconitine,new aconitine,hypaconitine,benzoyl aconitine,benzoyl new aconitine and benzoyl hypaconitine were 1.0-100.0 ng·mL-1,respectively,the average recovery were 98.62％-101.24％.The mass fractions of the six components were 0.18,0.33,0.38,0.43,0.28,0.06μg·g-1.Conclusion The method can be used to determine the content of 6 aconitine-type alkaloids in Xiaozhong ointment,and provide reference for the quality evaluation and clinical safe use of Xiaozhong ointment.