Objective To predict the lymph node metastasis status of patients with invasive pulmonary adenocarcinoma by constructing machine learning models based on primary tumor radiomics, peritumoral radiomics, and habitat radiomics, and to evaluate the predictive performance and generalization ability of different imaging features. Methods A retrospective analysis was performed on the clinical data of 1 263 patients with invasive pulmonary adenocarcinoma who underwent surgery at the Department of Thoracic Surgery, Jiangsu Province Hospital, from 2016 to 2019. Habitat regions were delineated by applying K-means clustering (average cluster number of 2) to the grayscale values of CT images. The peritumoral region was defined as a uniformly expanded area of 3 mm around the primary tumor. The primary tumor region was automatically segmented using V-net combined with manual correction and annotation. Subsequently, radiomics features were extracted based on these regions, and stacked machine learning models were constructed. Model performance was evaluated on the training, testing, and internal validation sets using the area under the receiver operating characteristic curve (AUC), F1 score, recall, and precision. Results After excluding patients who did not meet the screening criteria, a total of 651 patients were included. The training set consisted of 468 patients (181 males, 287 females) with an average age of (58.39±11.23) years, ranging from 29 to 78 years, the testing set included 140 patients (56 males, 84 females) with an average age of (58.81±10.70) years, ranging from 34 to 82 years, and the internal validation set comprised 43 patients (14 males, 29 females) with an average age of (60.16±10.68) years, ranging from 29 to 78 years. Although the habitat radiomics model did not show the optimal performance in the training set, it exhibited superior performance in the internal validation set, with an AUC of 0.952 [95%CI (0.87, 1.00)], an F1 score of 84.62%, and a precision-recall AUC of 0.892, outperforming the models based on the primary tumor and peritumoral regions. Conclusion The model constructed based on habitat radiomics demonstrated superior performance in the internal validation set, suggesting its potential for better generalization ability and clinical application in predicting lymph node metastasis status in pulmonary adenocarcinoma.

Sesquiterpenes are natural terpenoids with 15 carbon atoms in the basic skeleton, which mainly exist in plant volatile oil and have important physiological and medicinal value. Cytochrome P450 (CYP450) is a kind of monooxygenase encoded by supergene family, which is one of the largest gene families in plants. It is involved in the synthesis and metabolism of terpenoids, alkaloids and other secondary metabolites. In the process of terpene biosynthesis, CYP450 participates in the post-modification stage of terpenes by introducing functional groups such as hydroxyl, carboxyl and carbonyl, which plays an important role in enriching the diversity of terpenes. The CYP450 enzymes involved in sesquiterpene synthesis and their substrate catalytic specificity mechanisms have been partially investigated. In this paper, the biosynthetic pathway of plant sesquiterpenes, the structure and classification of CYP450 enzymes were briefly introduced, and the CYP450 enzymes involved in sesquiterpene biosynthesis were summarized, in order to provide a reference for intensive study of the role of CYP450 enzymes in the synthesis of sesquiterpenoids.

AIM To establish a GC-MS method for the simultaneous content determination of sixteen pesticide residues in Lycii Fructus and perform safety assessment.METHODS The analysis was performed on DB-5MS chromatographic column(30 m×0.25 mm,0.25 μm)subjected to the programmed heating,with splitless injection of 1.0 μL dissolved sample at a flowing rate of 1.0 mL/min.Other parameters were as follows:injection port temperature of 250℃,electron impact ionization(EI),electron energy of 70 eV;ion source temperature of 230℃,multi-reaction monitoring mode,and collision gas.of high-purity N2.Pesticide residues with relatively high dietary risk were analyzed and discussed with regard to residue levels,dietary intake risk,risk ranking and cumulative exposure assessment.RESULTS Sixteen pesticides showed good linear relationships within their own ranges(r≥0.994 4),whose average recoveries were 70%-114%,with the RSDs of less than 2%.The highest average cyfluthrin residue of 0.999 2 mg/kg in Lycii Fructus of production regions and the highest average cypermethrin residue of 0.088 4 mg/kg in Lycii Fructus commodities were both detected.In Lycii Fructus of production regions with chronic hazard index(HI)value of 0.012 9 and acute HI value of 0.065 5 and their commodities with chronic HI of 0.001 2 and acute HI of 0.005 4,the pesticide residue of cypermethrin was the leading cause of chronic and acute dietary risk,and additionally,pyridaben within maximum residue limit(MRL)was the only detectectable highly toxic pesticide among the other most concerning pestcides of deltamethrin,pyridaben,chlorpyrifos,dichlorvos and methidathion.CONCLUSION There exist pesticide residues within MRL values in some samples of Lycii Fructus and the use of cypermethrin should be well-controlled.

A high performance liquid chromatography (HPLC) method utilizing correction factors was established for the quantitative detection of related substances in flumazenil. Separation was achieved using an Agilent Pursuit XRs C18 column (250 mm × 4.6 mm, 5 μm) with an isocratic elution of dilute phosphoric acid, methanol, and tetrahydrofuran as the mobile phases. Correction factors calculated from a standard curve method were applied to determine the impurity content. The quantification of impurities in flumazenil was conducted using both external standard and correction factor methods, followed by validation and comparison of the two. For the identification of degradation products, a forced degradation approach was employed to prepare a flumazenil degradation solution, and the resulting impurities were confirmed by LC-MS analysis. The separation of flumazenil and its impurities was found to be efficient. The limits of quantification for impurities A, B, D, and E were established at 0.169 9, 0.314 7, 0.143 9, and 0.270 8 ng, respectively, with the limits of detection at 0.055 8, 0.096 9, 0.048 8, and 0.089 0 ng. These impurities demonstrated a strong linear relationship across the concentration ranges of 0.034 9-7.847 0, 0.038 7-8.710 7, 0.034 6-7.794 1, and 0.032 4-7.292 8 µg·mL^-1, respectively (n = 7). The method achieved average recoveries between 98.25% and 99.42%, with an RSD of less than 2.0% (n = 9), indicating high accuracy. The external standard and correction factor methods were used to determine the related substances in flumazenil, and the results of the two methods were consistent. The established HPLC method is characterized by its high accuracy, sensitivity, and repeatability, and is suitable for determining related substances in flumazenil.

Objective To describe and analyze the current situation of the four same type of departments in an hospital in order to provide a reference for the construction of"the most cost-effective medical care".Methods The CN-DRG were used to automatically group and compare the medical capacity and inpatient service efficiency of the hospital department groups,and in the refined analysis,one DRG disease group of in situ cancer and non-malignant disease loss uterine surgery and single species uterine fibroid was included,and the Kruskal-Wallis H test was used to further compare the differences in length of stay and various costs.Results It included a total of 22630 patients,whose weights varied from a maximum of 3948.62 in diagnostic group 1 to a minimum of 133.55 in diagnostic group 11.The cost consumption indexes ranged from a minimum of 0.89 in diagnostic group 5 to a maximum of 1.04 in diagnostic group 2,while the time consumption indexes ranged from a minimum of 0.48 in diagnostic group 11 to a maximum of 0.81 in diagnostic group 5.When comparing the diagnostic groups,there were statistically significant differences(P＜0.05)in hospitalization days,total cost,diagnostic cost,therapeutic cost,and cost of supplies.Specifically,when comparing the diagnostic and treatment groups within departments,the differences in hospitalization days and all costs were statistically significant(P＜0.05)in departments 1 and 2,the differences in diagnostic cost,therapeutic cost,and cost of supplies were statistically significant(P＜0.05)in department 3.Conclusion There exists a notable disparity in the extent to which each diagnostic and treatment group contributes to the hospital's service capacity and cost variability.Consequently,it is necessary to reasonably evaluate the length of hospital stay and medical cost of patients to achieve the highest cost-effective medical treatment.

Ankylosing spondylitis (AS) combined with lower cervical fracture is often categorized into unstable fracture, with a high incidence of neurological injury and a high rate of disability and morbidity. As factors such as shoulder occlusion may affect the accuracy of X-ray imaging diagnosis, it is often easily misdiagnosed at the primary diagnosis. Non-operative treatment has complications such as bone nonunion and the possibility of secondary neurological damage, while the timing, access and choice of surgical treatment are still controversial. Currently, there are no clinical practice guidelines for the treatment of AS combined with lower cervical fracture with or without dislocation. To this end, the Spinal Trauma Group of Orthopedics Branch of Chinese Medical Doctor Association organized experts to formulate Clinical guidelines for the treatment of ankylosing spondylitis combined with lower cervical fracture in adults ( version 2024) in accordance with the principles of evidence-based medicine, scientificity and practicality, in which 11 recommendations were put forward in terms of the diagnosis, imaging evaluation, typing and treatment, etc, to provide guidance for the diagnosis and treatment of AS combined with lower cervical fracture.

OBJECTIVE: To explore the mechanism of electroacupuncture (EA) in promoting recovery of the facial function with the involvement of autophagy, glial cell line-derived neurotrophic factor (GDNF), and phosphatidylinositol-3-kinase (PI3K)/mammalian target of rapamycin (mTOR) signaling pathway. METHODS: Seventy-two male Sprague-Dawley rats were randomly allocated into the control, sham-operated, facial nerve injury (FNI), EA, EA+3-methyladenine (3-MA), and EA+GDNF antagonist groups using a random number table, with 12 rats in each group. An FNI rat model was established with facial nerve crushing method. EA intervention was conducted at Dicang (ST 4), Jiache (ST 6), Yifeng (SJ 17), and Hegu (LI 4) acupoints for 2 weeks. The Simone's 10-Point Scale was utilized to monitor the recovery of facial function. The histopathological evaluation of facial nerves was performed using hematoxylin-eosin (HE) staining. The levels of Beclin-1, light chain 3 (LC3), and P62 were detected by immunohistochemistry (IHC), immunofluorescence, and reverse transcription-polymerase chain reaction, respectively. Additionally, IHC was also used to detect the levels of GDNF, Rai, PI3K, and mTOR. RESULTS: The facial functional scores were significantly increased in the EA group than the FNI group (P<0.05 or P<0.01). HE staining showed nerve axons and myelin sheaths, which were destroyed immediately after the injury, were recovered with EA treatment. The expressions of Beclin-1 and LC3 were significantly elevated and the expression of P62 was markedly reduced in FNI rats (P<0.01); however, EA treatment reversed these abnormal changes (P<0.01). Meanwhile, EA stimulation significantly increased the levels of GDNF, Rai, PI3K, and mTOR (P<0.01). After exogenous administration with autophagy inhibitor 3-MA or GDNF antagonist, the repair effect of EA on facial function was attenuated (P<0.05 or P<0.01). CONCLUSIONS EA could promote the recovery of facial function and repair the facial nerve damages in a rat model of FNI. EA may exert this neuroreparative effect through mediating the release of GDNF, activating the PI3K/mTOR signaling pathway, and further regulating the autophagy of facial nerves.
Rats ; Male ; Animals ; Rats, Sprague-Dawley ; Electroacupuncture ; Phosphatidylinositol 3-Kinase/metabolism* ; Facial Nerve Injuries/therapy* ; Phosphatidylinositol 3-Kinases/metabolism* ; Beclin-1 ; Glial Cell Line-Derived Neurotrophic Factor ; Signal Transduction ; TOR Serine-Threonine Kinases/metabolism* ; Autophagy ; Mammals/metabolism*

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]

Objective:To develop and validate a model to predict the risk of malnutrition in patients with nasopharyngeal carcinoma receiving concurrent chemoradiotherapy. Methods:From April 2022 to August 2023, 430 patients with nasopharyngeal carcinoma who were admitted to the department of radiotherapy of the first affiliated hospital of Guangxi medical university in Nanning were conveniently selected as the study subjects, and they were divided into the modelling group (300 cases) and the internal validation group (130 cases) in the internal validation group in the ratio of 7:3, and 61 patients with nasopharyngeal carcinoma admitted to the affiliated cancer hospital of Guangxi medical university in Nanning City were selected as the external validation group. Logistic regression was used to establish the risk prediction model and draw nomograms,Hosmer-Lemeshow, calibration curve and ROC were used to verify the goodness of fit and predictive power of the model, and clinical decision curve was used to assess the clinical utility. Results:Logistic regression analysis showed that skeletal muscle mass index, self-rated anxiety scale score, Pittsburgh sleep quality questionnaire score, Chinese diet pagoda score, regular exercise, and digestive symptom groups were the influencing factors for malnutrition in patients with nasopharyngeal carcinoma receiving concurrent chemoradiotherapy. In the modelling group, the area under the ROC curve was 0.853 (95％CI:0.81 ～ 0.89), the maximum Youden was 0.600, and the corresponding specificity was 0.764 and the sensitivity was 0.836. The Hosmer-Lemeshow test=4.040 and P=0.853 indicated that the model had good predictive ability. Calibration curve of the calibration showed that the predictive effect of the model matched actual probability well, with an average absolute error was 0.024. When the threshold probability of the clinical decision curve is 0.05 ～ 0.85, the clinical response rate is higher. The area under the operating curve of the subjects in the internal validation group was 0.891, the sensitivity was 77.36％, the specificity was 89.61％, and the practical application accuracy was 84.62％. The area under the operating curve of the subjects in the external validation group was 0.886, the sensitivity was 76.00％, the specificity was 83.33％, and the overall accuracy was 80.33％. Conclusion:The risk prediction model constructed in this study has a good effect, which can effectively predict the incidence of malnutrition in patients receiving concurrent radiotherapy and chemotherapy for nasopharyngeal carcinoma, and provide a reference for clinical staff to formulate and implement nutritional interventions.