Idiopathic pulmonary fibrosis （IPF） can be classified as pulmonary collateral disease，and its pathogenesis is mainly characterized by the loss of Qi meridian nourishment，the loss of Yin meridian nourishment，and the formation of blood stasis in the blood vessels. Qi Yin deficiency is the pathological basis that runs through IPF，and obstruction of meridians and collaterals is a key element in the development of the disease. The dysfunction of "spleen being in charge of the defensive function" is closely related to the formation of the pathological pattern of "lung deficiency and collateral stasis" in IPF. The term "spleen being in charge of the defensive function" originated from the Yellow Emperor's Inner Canon. If the spleen is healthy，the Qi will be filled with vitality. Positive energy is stored inside，evil cannot be dried up. Its concept is quite similar to the immune defense function in modern medicine. If the principle of "spleen being in charge of the defensive function" is lost，the key structure and function of the IPF alveolar epithelial barrier may be abnormal，and it can interact with various innate immune cells to promote inflammation and fibrosis processes. Therefore，this article explains the imbalance of immune homeostasis in IPF alveolar epithelium from two aspects：the barrier function of alveolar epithelial cells（AECs） and their interaction with innate immune cells. And based on the theory of "spleen being in charge of the defensive function"，using traditional Chinese medicine for strengthening the spleen and nourishing Qi to treat IPF from the perspective of the spleen. This not only strengthens the scientific connotation of "spleen being in charge of the defensive function" in the pathogenesis of IPF，but also provides new research directions and ideas for its future clinical prevention and treatment.

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.

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.

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 investigate a new noninvasive diagnostic model for nonalcoholic fatty liver disease (NAFLD) based on features of tongue images. METHODS: Healthy controls and volunteers confirmed to have NAFLD by liver ultrasound were recruited from China-Japan Friendship Hospital between September 2018 and May 2019, then the anthropometric indexes and sampled tongue images were measured. The tongue images were labeled by features, based on a brief protocol, without knowing any other clinical data, after a series of corrections and data cleaning. The algorithm was trained on images using labels and several anthropometric indexes for inputs, utilizing machine learning technology. Finally, a logistic regression algorithm and a decision tree model were constructed as 2 diagnostic models for NAFLD. RESULTS: A total of 720 subjects were enrolled in this study, including 432 patients with NAFLD and 288 healthy volunteers. Of them, 482 were randomly allocated into the training set and 238 into the validation set. The diagnostic model based on logistic regression exhibited excellent performance: in validation set, it achieved an accuracy of 86.98%, sensitivity of 91.43%, and specificity of 80.61%; with an area under the curve (AUC) of 0.93 [95% confidence interval (CI) 0.68-0.98]. The decision tree model achieved an accuracy of 81.09%, sensitivity of 91.43%, and specificity of 66.33%; with an AUC of 0.89 (95% CI 0.66-0.92) in validation set. CONCLUSIONS The features of tongue images were associated with NAFLD. Both the 2 diagnostic models, which would be convenient, noninvasive, lightweight, rapid, and inexpensive technical references for early screening, can accurately distinguish NAFLD and are worth further study.
Humans ; Non-alcoholic Fatty Liver Disease/diagnostic imaging* ; Ultrasonography ; Anthropometry ; Algorithms ; China

This study aimed to investigate halofuginone's inhibitory effect and mechanism on the activity of hepatocellular carcinoma cells. HepG2 cells were used to detect the effects of halofuginone. After treatment, cell activity, cell migration, cell cycle, and cell apoptosis were detected by CCK-8, transwell, and flow cytometry, respectively. The expression levels of growth and metabolism-related factors such as citrate synthase (CS), ketoglutarate dehydrogenase (OGDH), and isocitrate deoxygenase (IDH) were detected by real-time quantitative PCR and Western blot. Compared with the control group, the activity of HepG2 cells was significantly inhibited by halofuginone (P < 0.01), the migration rate of HepG2 cells was decreased (P < 0.01), the apoptosis of HepG2 cells was induced (P < 0.01), and the cell cycle was arrested in S phase (P < 0.01). The expression levels of tricarboxylic acid key enzymes CS, IDH3, and OGDH were up-regulated, the expression level of isocitrate dehydrogenase isoenzymes IDH1 and IDH2 were down-regulation. In conclusion, halofuginone can inhibit the proliferation and migration of HepG2 cells and promote apoptosis in a dose-dependent manner, which may be due to the promotion of the aerobic metabolism of cells.

Objective To investigate the predictive value of new simplified insulin resistance(IR)assessment indexes in identifying subclinical left ventricular systolic function impairment in patients with type 2 diabetes mellitus(T2DM).Methods A total of 150 T2DM patients with preserved left ventricular ejection fraction(LVEF≥50%)who were admitted to Department of Endocrinology of the First Affiliated Hospital of Air Force Medical University from June 2021 to December 2021 were retrospectively analyzed.All patients underwent two-dimensional speckle tracking echocardiography to measure left ventricular global longitudinal strain(GLS).According to GLS value,the subjects were divided into the normal group(GLS≥18%group,n=80)and the impaired group(GLS<18%group,n=70).Some new simplified IR assessment indicators were calculated and compared between the two groups,including body mass index(BMI),TG/HDL-C ratio,triglyceride-glucose(TyG)index,TyG-BMI index,TyG-WHR and metabolic score for IR(METS-IR).Correlation between the GLS and the new simplified IR assessment indexes was analyzed.The receiver operating characteristic(ROC)curve was used to analyze the diagnostic efficacy of different simplified IR assessment indexes,with the area under the curve(AUC)calculated.Furthermore,according to whether the subjects were complicated with hypertension,binary logistics regression analysis was performed to explore the independent correlation between the simplified IR assessment index and GLS<18%.Results Total 150 were included with aged(54.5±13.7)years with 96(64.0%)men and 54(36.0%)women.Compared with the GLS≥18%group,the TG/HDL-C ratio,TyG index,TyG-BMI,and METS-IR of subjects in the GLS<18%group were significantly increased(P<0.05).Pearson correlation analysis showed that TG/HDL-C ratio,TyG index,TyG-BMI,TyG-WHR,and METS-IR were negatively correlated with GLS(P<0.05).ROC analysis showed that TyG index had a certain predictive value for the evaluation of GLS<18%(AUC=0.678,95%CI 0.591-0.765,P<0.001).Stratification based on hypertension and further adjusting for confounding factors,TyG index remains significantly associated with GLS<18%(OR=3.249,95%CI 1.045-10.103,P=0.042).Conclusions The novel simplified insulin resistance evaluation indexes are closely associated with left ventricular subclinical systolic dysfunction in T2DM patients with preserved ejection fraction.TyG index is an effective index to identify left ventricular subclinical dysfunction in these populations.

Objective:To investigate the clinical value of abdominal adipose volume in predicting early tumor recurrence after resection of hepatocellular carcinoma (HCC).Methods:The retrospective case-control study was conducted. The clinicopathological data of 132 HCC patients with tumor diameter ≤5 cm who were admitted to The First Affiliated Hospital of Army Medical University from December 2017 to October 2019 were collected. There were 110 males and 22 females, aged (51±4)years. All patients underwent resection of HCC. Preoperative computer tomography scanning was performed and the visceral and subcutaneous fats of patients were quantified using the Mimics Research 21.0 software. Based on time to postoperative tumor recurrence patients were divided to two categories: early recurrence and non-early recurrence. Observation indicators: (1) consistency analy-sis; (2) analysis of factors influencing early tumor recurrence after resection of HCC and construction of prediction model. Measurement data with normal distribution were represented as Mean± SD, and comparison between groups was conducted using the t test. Measurement data with skewed distribu-tion were represented as M( Q1,Q3) or M(range), and comparison between groups was conducted using the Mann-Whitney U test. Count data were expressed as absolute numbers, and comparison between groups was conducted using the chi-square test or Fisher exact probability. Consistency analysis was conducted using the intragroup correlation coefficient (ICC) test. Multivariate analysis was performed using the binary Logistic regression model forward method. Independent risk factors influencing early tumor recurrence after resection of HCC were screened. The area under curve (AUC) of receiver operating characteristic (ROC) curve was applied to select the optimal cut-off value to classify high and low risks of recurrence. The Kaplan-Meier method was used to draw survival curve and calculate survival time. The Log-Rank test was used for survival analysis. Results:(1) Consistency analysis. The consistency ICC of abdominal fat parameters of visceral fat volume (VFV), subcutaneous fat volume, visceral fat area, and subcutaneous fat area measured by 2 radiologists were 0.84, 1.00, 0.86, and 0.94, respectively. (2) Analysis of factors influencing early tumor recurr-ence after resection of HCC and construction of prediction model. All 132 patients were followed up after surgery for 662(range, 292-1 111)days. During the follow-up, there were 52 patients with non-early recurrence and 80 patients with early recurrence. Results of multivariate analysis showed that VFV was an independent factor influencing early tumor recurrence after resection of HCC ( odds ratio=4.07, 95% confidence interval as 2.27-7.27, P<0.05). The AUC of ROC curve based on VFV was 0.78 (95% confidence interval as 0.70-0.85), and the sensitivity and specificity were 72.2 % and 77.4 %, respectively. The optimal cut-off value of VFV was 1.255 dm 3, and all 132 patients were divided into the high-risk early postoperative recurrence group of 69 cases with VFV >1.255 dm 3, and the low-risk early postoperative recurrence group of 63 cases with VFV ≤1.255 dm 3. The disease-free survival time of the high-risk early postoperative recurrence group and the low-risk early post-operative recurrence group were 414(193,702)days and 1 047(620,1 219)days, showing a significant difference between them ( χ2=31.17, P<0.05). Conclusions:VFV is an independent factor influen-cing early tumor recurrence of HCC after resection. As a quantitative indicator of abdominal fat, it can predict the prognosis of HCC patients.