Objective To explore the risk factors associated with the occurrence of dampness syndrome based on peripheral blood multiple laboratory indicators,construct predictive model and validate it.Methods A retrospective analysis was conducted on 180 patients who visited the Preventive Treatment Center of Guangdong Provincial Hospital of Chinese Medicine from May 2022 to December 2023.They were divided into two groups according to the diagnostic criteria:the damp syndrome of TCM group(n=118)and the balanced yin-yang constitution group(n=62),with the latter serving as the"non-syndrome"control group for dampness syndrome.Serum biochemical indicators were detected by electrochemiluminescence(ECL),immune cell subsets were analyzed through flow cytometer,and routine blood parameters were assessed using an automatic hematology analyzed.Logistic regression analysis was employed to screen risk factors and develop a predictive model.The Bootstrap method was used for data resampling to draw the receiver operating characteristic(ROC)curve,calibration curve,and clinical decision curve analysis(DCA)to evaluate the predictive value,consistency,and clinical efficacy of the model.Results Compared with the balanced yin-yang constitution group,the damp syndrome of TCM group showed increased levels of insulin(INS),non-high-density lipoprotein cholesterol(non HDL-C),red blood cells(RBC)and the proportion of CD4+T cells,the proportion of triglyceride(TG)>1.70 mmol/L,total cholesterol(TC)>5.20 mmol/L,low-density lipoprotein cholesterol(LDL-C)>3.37 mmol/L,and high-density lipoprotein cholesterol(HDL-C)≤1.15 mmol/L were also significantly higher,with statistical significance(U/t/χ2=-2.900～4 626,all P＜0.05).Logistic regression analysis showed that INS,TC>5.20 mmol/L,HDL-C≤1.15 mmol/L,and the proportion of CD4+T cells were independent risk factors for the occurrence of damp syndrome of TCM(all P＜0.05).Based on the screened risk factors,a forecasting model was established and a nomogram was plotted.The model had an area under the ROC curve area under curve(AUC)of 0.747(95%CI=0.672～0.822),a Brier score of 0.184 for the calibration curve,and demonstrated clinical net benefit at threshold probabilities ranging from 0.30 to 1.00.Conclusion The forecasting model constructed based on INS,TC>5.20 mmol/L,HDL-C≤1.15 mmol/L,and CD4+T cells ratio has a high predictive value for damp syndrome of TCM.

Objective:To develop a clinical predictive model for dampness constitution based on laboratory testing indicators.Methods:A retrospective cohort study was conducted on 1 355 healthy individuals who underwent physical examinations at the Health Examination Center of Guangdong Provincial Hospital of Traditional Chinese Medicine from October 1 st, 2022 to October 31 st, 2023. Basic information and blood routine, blood glucose, liver function, lipid metabolism, and kidney function test results of 1 355 apparently healthy individuals were collected. According to the diagnostic criteria for dampness constitution in traditional Chinese medicine, they were divided into a dampness constitution group (683 cases, including 394 with phlegm-dampness constitution and 289 with damp-heat constitution) and a non-dampness constitution group (672 cases). Among them, there were 547 males and 136 females in the dampness constitution group, with an age of 38.0 (32.0, 45.0) years; and there were 355 males and 317 females in the non-dampness constitution group, with an age of 33.0 (27.0, 41.0) years. A total of 1 355 apparently healthy individuals were randomly divided into a training set ( n=948) and a validation set ( n=407) using computer-generated random numbers in a 7∶3 ratio. Logistic regression analysis was employed to identify risk factors associated with dampness constitution. Utilizing these identified risk factors, a predictive model was constructed and subsequently visualized. The model′s predictive accuracy, consistency, and clinical utility were assessed using the receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA), respectively. Results:Among 1 355 subjects, there were statistically significant differences ( P<0.05) in gender, age, body mass index (BMI), blood glucose, some indicators of renal function, some indicators of blood routine, liver function, and four indicators of lipid metabolism between the dampness constitution group and the non-dampness constitution group. Gender ( OR=0.434,95 %CI 0.253-0.738), Cr ( OR=0.981,95 %CI 0.967-0.996), BMI ( OR=1.366,95 %CI 1.290-1.450), and LDL-C ( OR=1.388,95 %CI 1.014-1.897) were independent risk factors for dampness constitution ( P<0.05). A nomogram was subsequently developed based on these identified risk factors. The areas under the ROC curves (AUC) of the training set and validation set were 0.810 (95 %CI 0.783-0.837) and 0.804 (95 %CI 0.762-0.846), respectively. Conclusion:Gender,BMI,Cr and LDL-C were risk factors for the development of dampness constitution, and the clinical predictive model has clinical application value in predicting the risk of dampness constitution.

Objective:To develop a clinical predictive model for dampness constitution based on laboratory testing indicators.Methods:A retrospective cohort study was conducted on 1 355 healthy individuals who underwent physical examinations at the Health Examination Center of Guangdong Provincial Hospital of Traditional Chinese Medicine from October 1 st, 2022 to October 31 st, 2023. Basic information and blood routine, blood glucose, liver function, lipid metabolism, and kidney function test results of 1 355 apparently healthy individuals were collected. According to the diagnostic criteria for dampness constitution in traditional Chinese medicine, they were divided into a dampness constitution group (683 cases, including 394 with phlegm-dampness constitution and 289 with damp-heat constitution) and a non-dampness constitution group (672 cases). Among them, there were 547 males and 136 females in the dampness constitution group, with an age of 38.0 (32.0, 45.0) years; and there were 355 males and 317 females in the non-dampness constitution group, with an age of 33.0 (27.0, 41.0) years. A total of 1 355 apparently healthy individuals were randomly divided into a training set ( n=948) and a validation set ( n=407) using computer-generated random numbers in a 7∶3 ratio. Logistic regression analysis was employed to identify risk factors associated with dampness constitution. Utilizing these identified risk factors, a predictive model was constructed and subsequently visualized. The model′s predictive accuracy, consistency, and clinical utility were assessed using the receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA), respectively. Results:Among 1 355 subjects, there were statistically significant differences ( P<0.05) in gender, age, body mass index (BMI), blood glucose, some indicators of renal function, some indicators of blood routine, liver function, and four indicators of lipid metabolism between the dampness constitution group and the non-dampness constitution group. Gender ( OR=0.434,95 %CI 0.253-0.738), Cr ( OR=0.981,95 %CI 0.967-0.996), BMI ( OR=1.366,95 %CI 1.290-1.450), and LDL-C ( OR=1.388,95 %CI 1.014-1.897) were independent risk factors for dampness constitution ( P<0.05). A nomogram was subsequently developed based on these identified risk factors. The areas under the ROC curves (AUC) of the training set and validation set were 0.810 (95 %CI 0.783-0.837) and 0.804 (95 %CI 0.762-0.846), respectively. Conclusion:Gender,BMI,Cr and LDL-C were risk factors for the development of dampness constitution, and the clinical predictive model has clinical application value in predicting the risk of dampness constitution.

Objective To explore the risk factors associated with the occurrence of dampness syndrome based on peripheral blood multiple laboratory indicators,construct predictive model and validate it.Methods A retrospective analysis was conducted on 180 patients who visited the Preventive Treatment Center of Guangdong Provincial Hospital of Chinese Medicine from May 2022 to December 2023.They were divided into two groups according to the diagnostic criteria:the damp syndrome of TCM group(n=118)and the balanced yin-yang constitution group(n=62),with the latter serving as the"non-syndrome"control group for dampness syndrome.Serum biochemical indicators were detected by electrochemiluminescence(ECL),immune cell subsets were analyzed through flow cytometer,and routine blood parameters were assessed using an automatic hematology analyzed.Logistic regression analysis was employed to screen risk factors and develop a predictive model.The Bootstrap method was used for data resampling to draw the receiver operating characteristic(ROC)curve,calibration curve,and clinical decision curve analysis(DCA)to evaluate the predictive value,consistency,and clinical efficacy of the model.Results Compared with the balanced yin-yang constitution group,the damp syndrome of TCM group showed increased levels of insulin(INS),non-high-density lipoprotein cholesterol(non HDL-C),red blood cells(RBC)and the proportion of CD4+T cells,the proportion of triglyceride(TG)>1.70 mmol/L,total cholesterol(TC)>5.20 mmol/L,low-density lipoprotein cholesterol(LDL-C)>3.37 mmol/L,and high-density lipoprotein cholesterol(HDL-C)≤1.15 mmol/L were also significantly higher,with statistical significance(U/t/χ2=-2.900～4 626,all P＜0.05).Logistic regression analysis showed that INS,TC>5.20 mmol/L,HDL-C≤1.15 mmol/L,and the proportion of CD4+T cells were independent risk factors for the occurrence of damp syndrome of TCM(all P＜0.05).Based on the screened risk factors,a forecasting model was established and a nomogram was plotted.The model had an area under the ROC curve area under curve(AUC)of 0.747(95%CI=0.672～0.822),a Brier score of 0.184 for the calibration curve,and demonstrated clinical net benefit at threshold probabilities ranging from 0.30 to 1.00.Conclusion The forecasting model constructed based on INS,TC>5.20 mmol/L,HDL-C≤1.15 mmol/L,and CD4+T cells ratio has a high predictive value for damp syndrome of TCM.

Objective To acquire the external contour changes and positioning errors during fractionated intensity-modulated radiotherapy for nasopharyngeal carcinoma using kilovoltage cone-beam computed tomography(CBCT),and to analyze their effects on the dose distributions in target areas and organs-at-risk.Methods Twenty-one patients with nasopharyngeal carcinoma were enrolled in the study,and the positioning errors in the left-right,superior-inferior and anterior-posterior directions were obtained by matching 137 CBCT images with the positioning CT images.The transverse width of the external contour was measured at 3 different layers of the neck,and its effects on positioning errors were analyzed using Pearson's coefficient and independent sample t-tests.Additionally,simulation plans based on CBCT images were created to analyze the effects of positioning errors and external contour changes on radiotherapy dose,with Mann-Whitney U tests applied for significance analysis.Results The positioning errors in the left-right,superior-inferior and anterior-posterior directions were(1.04±0.73),(1.13±0.87)and(1.38±0.95)mm,respectively.The rates of external contour changes at the A,B and C layers of the head and neck were 15.36%,14.94%and 14.99%,respectively.Compared with executed plans,simulation plans had lower GTV D98,CTV1 D95 and CTV2 D95(P<0.05),and higher Dmax for the brainstem and spinal cord(P<0.05).Conclusion The simulation plans indicate that the presence of uncertainties such as positioning errors and external contour changes will significantly affect dose distributions in target areas,with the largest decrease observed in GTV D98(11.49%)and the maximum change rates in CTV1 D95 and CTV2 D95 being 12.88%and 21.64%,respectively.Except for the left and right lenses and left parotid gland,significant differences are observed in the doses for the other organs-at-risk and target areas,suggesting that positioning errors and external contour changes in actual radiotherapy will exert significant effects on dose distributions.

Objective:To evaluate the feasibility and clinical value of pre-treatment non-enhanced chest CT radiomics features and machine learning algorithm to predict the mutation status and subtype (19Del/21L858R) of epidermal growth factor receptor (EGFR) for patients with non-small cell lung cancer (NSCLC).Methods:This retrospective study enrolled 280 NSCLC patients from first and second affiliated hospital of University of South China who were confirmed by biopsy pathology, gene examination, and have pre-treatment non-enhanced CT scans. There are 136 patients were confirmed EGFR mutation. Primary lung gross tumor volume was contoured by two experienced radiologists and oncologists, and 851 radiomics features were subsequently extracted. Then, spearman correlation analysis and RELIEFF algorithm were used to screen predictive features. The two hospitals were training and validation cohort, respectively. Clinical-radiomics model was constructed using selected radiomics and clinical features, and compared with models built by radiomics features or clinical features respectively. In this study, machine learning models were established using support vector machine (SVM) and a sequential modeling procedure to predict the mutation status and subtype of EGFR. The area under receiver operating curve (AUC-ROC) was employed to evaluate the performances of established models.Results:After feature selection, 21 radiomics features were found to be efffective in predicting EGFR mutation status and subtype and were used to establish radiomics models. Three types models were established, including clinical model, radiomics model, and clinical-radiomics model. The clinical-radiomics model showed the best predictive efficacy, AUCs of predicting EGFR mutation status for training dataset and validation dataset were 0.956 (95% CI: 0.952-1.000) and 0.961 (95% CI: 0.924-0.998), respectively. The AUCs of predicting 19Del/L858R mutation subtype for training dataset and validation dataset were 0.926 (95% CI: 0.893-0.959), 0.938 (95% CI: 0.876-1.000), respectively. Conclusions:The constructed sequential models based on integration of CT radiomics, clinical features and machine learning can accurately predict the mutation status and subtype of EGFR.

The relationship between chronic psychological stress and tumorigenesis has been well defined in epidemiological studies; however, the underlying mechanism remains underexplored. In this study, we discovered that impaired macrophage phagocytosis contributed to the psychological stress-evoked tumor susceptibility, and the stress hormone glucocorticoid (GC) was identified as a principal detrimental factor. Mechanistically, GC disturbed the balance of the "eat me" signal receptor (low-density lipoprotein receptor-related protein-1, LRP1) and the "don't eat me" signal receptor (signal regulatory protein alpha, SIRPα). Further analysis revealed that GC led to a direct, glucocorticoid receptor (GR)-dependent trans-repression of LRP1 expression, and the repressed LRP1, in turn, resulted in the elevated gene level of SIRPα by down-regulating miRNA-4695-3p. These data collectively demonstrate that stress induces the imbalance of the LRP1/SIRPα axis and entails the disturbance of tumor cell clearance by macrophages. Our findings provide the mechanistic insight into psychological stress-evoked tumor susceptibility and indicate that the balance of LRP1/SIRPα axis may serve as a potential therapeutic strategy for tumor treatment.

Rabdosia serra(R.serra),an important component of Chinese herbal tea,has traditionally been used to treat hepatitis,jaundice,cholecystitis,and colitis.However,the chemical composition of R.serra and its effect against colitis remain unclear.In this study,the chemical composition of the water extract of R.serra was analyzed using ultra performance liquid chromatography coupled with a hybrid linear ion trap quadrupole-orbitrap mass spectrometer(UPLC-LTQ-Orbitrap-MS).A total of 46 compounds,comprising ent-kaurane diterpenoids,flavonoids,phenolic acids,and steroids,were identified in the water extract of R.serra,and the extract could significantly alleviate dextran sulfate sodium salt-induced colitis by improving colon length,upregulating anti-inflammatory factors,downregulating proinflammatory fac-tors,and restoring the balance of T helper 17/T regulatory cells.R.serra also preserved intestinal barrier function by increasing the level of tight junction proteins(zonula occludens 1 and occludin)in mouse colonic tissue.In addition,R.serra modulated the gut microbiota composition by increasing bacterial richness and diversity,increasing the abundance of beneficial bacteria(Muribaculaceae,Bacteroides,Lactobacillus,and Prevotellaceae_UCG-O01),and decreasing the abundance of pathogenic bacteria(Turi-cibacter,Eubacterium_fissicatena_group,and Eubacterium_xylanophilum_group).Gut microbiota depletion by antibiotics further confirmed that R.serra alleviated colitis in a microbiota-dependent manner.Overall,our findings provide chemical and biological evidence for the potential application of R.serra in the management of colitis.

Objective To express adenosine deaminase protein by molecular cloning technique.MethodsTotal RNA was extracted from human leukocytes and the cDNA was obtained by reverse transcription.Whereupon the cDNA was used as a template to amplify adenosine deaminase gene by polymerase chain reaction (PCR) and then integrated it into three prokaryotic plasmids pET-28 b, pET-32 a (+) and pHSIE.The plasmid with the correct sequencing was transformed into E.coli BL21 (DE3) by CaCl2 method for the protein expression.The expression activity of these fusion proteins were detected by Western-blot and SDS-PAGE, with the optimized expression conditions.Results Complete fusion of target gene and three prokaryotic plasmids was observed through sequencing.The expressed and accurate ADA protein was identified by Westernblot and SDS-PAGE.The optimal expression conditions were observed:the protein expression would be induced with 0.4 mmol/L IPTG and incubated at 16℃for 24 hours.Conclusion The prokaryotic vectors of adenosine deaminase (BL21+pET-28 b+ADA, BL21+pET-32 a+ADA, BL21+pHSIE+ADA) were successfully constructed and efficiently expressed.

Objective Clinical study on the treatment of bilateral lumbar spinal stenosis with percutane-ous fixation combined with unilateral open-ended spinal canal decompression. Methods 126 patients with bilater-al lumbar spinal stenosis admitted to our hospital were randomly divided into two groups.The observation group was treated by percutaneous nail combined with unilateral laminar fenestration,and the control group was treated by open reduction combined with bilateral hemi laminectomy and spinal canal decompression.The two groups of pa-tients with general surgical complications after treatment,index,lumbago and leg pain VAS score and ODI score were compared.Results The operation time of the observation group,the amount of bleeding,the time of hospital-ization and the cost of hospitalization were less than those of the control group.There were no complications such as incision infection after operation in the two groups.The two groups were statistically significant postoperative pain and leg pain VAS score and ODI score compared with preoperative difference.The two groups had statistical signifi-cance between low back and leg pain VAS score and ODI score after 6 and 12 months and last follow-up phase dif-ference.But the two groups after 3 months of lumbago and leg pain VAS score and ODI score had no significant dif-ference.Conclusions Percutaneous minimally invasive nail combined with unilateral laminar fenestration and de-compression for bilateral lumbar spinal stenosis has the advantages of less trauma,less bleeding,shorter hospitaliza-tion time and quicker recovery.It is worthy of clinical promotion.