Chronic obstructive pulmonary disease （COPD） is a common clinical chronic airway disease with high morbidity， high mortality， a heavy disease burden， and complex mechanisms that have not been fully elucidated. Clinical problems promote the continuous progress of basic research. The establishment and evaluation of animal models is an important way to delve into the pathogenesis and treatment strategies of COPD. On the basis of the etiology， pathogenesis， diagnostic criteria， and syndrome differentiation of COPD in traditional Chinese medicine （TCM） and Western medicine， this paper summarizes the establishment methods and characteristics of existing animal models of COPD and analyzes the fitting degree of the models with the disease characteristics in Western medicine and syndrome characteristics in TCM. The results showed that the animal models of COPD in Western medicine were mainly induced by single factors and compound factors， and the model with the highest fitting degree was established by cigarette smoke combined with lipopolysaccharide and hormone. The model showed a fitting degree of 84% with the disease characteristics in Western medicine and 70% with the syndrome characteristics in TCM， being consistent with the clinical characteristics of COPD induced by multiple factors. Most of the animal models of COPD in TCM were established on the basis of disease models and combined with TCM etiology and pathogenesis characteristics， and prepared by syndrome differentiation. Among them， the model of accumulation of cold and water retention in lung had the highest fitting degree of 92% with the TCM diagnostic criteria. The models of phlegm-heat obstructing lung and phlegm-stasis obstructing lung had the fitting degree of 94% with clinical manifestations in Western medicine and the highest fitting degree with the diagnostic criteria in Western medicine. Different animal models of COPD have their own advantages and disadvantages， and most of them simply replicate the manifestations of COPD at a certain stage， failing to reflect the multiple causes and the dynamic changes of TCM etiology and pathogenesis. Moreover， the syndromes of these models fail to match the clinical syndromes in TCM. Therefore， establishing the animal models reflecting clinical characteristics of COPD in TCM and Western medicine and improving the model evaluation criteria are important contents to promote the overall development of integrated traditional Chinese and western medicine for COPD.

Objective:To investigate the value of biparametric-MRI (bpMRI) based peritumoral radiomics for preoperative prediction of extraprostatic extension (EPE) in prostate cancer (PCa).Methods:In this cross-sectional study, consecutive bpMRI of patients undergoing prostatectomy for PCa were retrospectively collected from the First Medical Center (center 1) and the Third Medical Center (center 2) of Chinese PLA General Hospital. A total of 274 patients were finally enrolled. Patients at center 1 from January 2020 to December 2022 were randomly divided into a training set (149 cases) and an internal validation set (63 cases) by stratified random sampling. Patients at center 2 from January 2023 to March 2024 were assigned to the external test set (62 cases). Patients were categorized into EPE-positive group and EPE-negative group according to pathological assessment postoperatively. In the training set, there were 49 cases in EPE-positive group and 100 cases in EPE-negative group. In the internal validation set, there were 26 cases in EPE-positive group and 37 cases in EPE-negative group. In the external test set, there were 22 cases in EPE-positive group and 40 cases in EPE-negative group. Axial T 2WI and apparent diffusion coefficient (ADC) images were manually annotated to obtain index lesion regions of interest (ROIs), with the peritumoral ROIs subsequently delineated by semi-automatic segmentation technique. Radiomics features were extracted from intra-tumoral, peri-tumoral, and intra-tumoral plus peri-tumoral ROIs. The training set data was employed to select and optimize features to build the radiomics models. The logistic regression analysis was used to develop radiomics, clinical, and integrated models. The predictive performance was assessed by the area under the receiver operating characteristic curve (AUC) in the external test set, and compared by the DeLong test. The sensitivity and specificity were compared by the exact McNemar test. Results:In the external test set, the peri-tumoral radiomics model based on bpMRI showed the highest performance in evaluating EPE, with an AUC of 0.739 (95% CI 0.611-0.842), which was identified as the optimal radiomics model. EPE grade ( OR=6.151, 95% CI 3.371-11.226, P<0.001) was incorporated into the clinical model, with an AUC of 0.780 (95% CI 0.657-0.875) in the external test set. The integrated model had an AUC of 0.817 (95% CI 0.698-0.904) in the external test set. There was no statistically significant difference in comparisons of AUCs among the three models (all P>0.05). The sensitivity of the integrated model (68.2%) showed no significant difference from those of the clinical model and the optimal radiomics model (77.3% and 86.4%, respectively; P=0.500 and P=0.289). However, the specificity of the integrated model (85.0%) was significantly higher than those of the clinical model (67.5%, P=0.016) and the optimal radiomics model (50.0%, P<0.001). Conclusion:A bpMRI-based peritumoral radiomics integrating clinical model demonstrates high performance for preoperative prediction of EPE in PCa.

Objective:To investigate the value of biparametric-MRI (bpMRI) based peritumoral radiomics for preoperative prediction of extraprostatic extension (EPE) in prostate cancer (PCa).Methods:In this cross-sectional study, consecutive bpMRI of patients undergoing prostatectomy for PCa were retrospectively collected from the First Medical Center (center 1) and the Third Medical Center (center 2) of Chinese PLA General Hospital. A total of 274 patients were finally enrolled. Patients at center 1 from January 2020 to December 2022 were randomly divided into a training set (149 cases) and an internal validation set (63 cases) by stratified random sampling. Patients at center 2 from January 2023 to March 2024 were assigned to the external test set (62 cases). Patients were categorized into EPE-positive group and EPE-negative group according to pathological assessment postoperatively. In the training set, there were 49 cases in EPE-positive group and 100 cases in EPE-negative group. In the internal validation set, there were 26 cases in EPE-positive group and 37 cases in EPE-negative group. In the external test set, there were 22 cases in EPE-positive group and 40 cases in EPE-negative group. Axial T 2WI and apparent diffusion coefficient (ADC) images were manually annotated to obtain index lesion regions of interest (ROIs), with the peritumoral ROIs subsequently delineated by semi-automatic segmentation technique. Radiomics features were extracted from intra-tumoral, peri-tumoral, and intra-tumoral plus peri-tumoral ROIs. The training set data was employed to select and optimize features to build the radiomics models. The logistic regression analysis was used to develop radiomics, clinical, and integrated models. The predictive performance was assessed by the area under the receiver operating characteristic curve (AUC) in the external test set, and compared by the DeLong test. The sensitivity and specificity were compared by the exact McNemar test. Results:In the external test set, the peri-tumoral radiomics model based on bpMRI showed the highest performance in evaluating EPE, with an AUC of 0.739 (95% CI 0.611-0.842), which was identified as the optimal radiomics model. EPE grade ( OR=6.151, 95% CI 3.371-11.226, P<0.001) was incorporated into the clinical model, with an AUC of 0.780 (95% CI 0.657-0.875) in the external test set. The integrated model had an AUC of 0.817 (95% CI 0.698-0.904) in the external test set. There was no statistically significant difference in comparisons of AUCs among the three models (all P>0.05). The sensitivity of the integrated model (68.2%) showed no significant difference from those of the clinical model and the optimal radiomics model (77.3% and 86.4%, respectively; P=0.500 and P=0.289). However, the specificity of the integrated model (85.0%) was significantly higher than those of the clinical model (67.5%, P=0.016) and the optimal radiomics model (50.0%, P<0.001). Conclusion:A bpMRI-based peritumoral radiomics integrating clinical model demonstrates high performance for preoperative prediction of EPE in PCa.

Objective:To investigate the impact of the interval period between biopsy and MR examination on tumor detection and extraprostatic extension (EPE) assessment for prostate cancer (PCa) using multi-parametric MRI (mpMRI).Methods:The study was cross-sectional and retrospectively included 130 patients with PCa who underwent RP and preoperative systematic biopsies followed by mpMRI between January 2021 and December 2022 in the First Medical Center of Chinese PLA General Hospital. Patients were divided into 3 groups according to interval following biopsy (group A,<3 weeks, 31 cases; group B, 3-6 weeks, 67 cases; group C,>6 weeks, 32 cases). The percentages of hemorrhage volume in the total prostate were drawn on T 1WI and calculated. The junior, senior and expert radiologists independently localized the index lesions and calculated the accuracy for tumor detection, in addition to assessing the probabilities of EPE according to EPE grade. The correlation between the hemorrhage extent and interval was analyzed using the Spearman correlation coefficient. The accuracy for tumor detection was compared using χ2 test among groups. The diagnostic performance of the radiologists for EPE prediction was assessed using the receiver operating characteristic curve, and the differences between the corresponding area under the curve (AUC) were compared using the DeLong test. Results:The percentage of hemorrhage was correlated with the interval between biopsy and MR examination ( r=-0.325, P<0.001). The detection accuracy of junior radiologist was 83.9% (26/31), 76.1% (51/67), and 78.1% (25/32) in group A, B and C, respectively; no differences were observed in the detection accuracy among three groups ( χ2=0.76, P=0.685). The detection accuracy of senior radiologist was 83.9% (26/31), 80.6% (54/67), and 71.9% (23/32) in 3 groups with no differences ( χ2=1.53, P=0.464). The detection accuracy of expert radiologist was 80.6% (25/31), 77.6% (52/67), and 93.8% (30/32) with no differences ( χ2=3.95, P=0.139). The AUC (95% CI) for predicting EPE were 0.830 (0.652-0.940), 0.704 (0.580-0.809), 0.800 (0.621-0.920) in the group A, B and C for junior radiologist; 0.876 (0.708-0.966), 0.768 (0.659-0.863), 0.896 (0.736-0.975) for senior radiologist; and 0.866 (0.695-0.961), 0.813 (0.699-0.895), 0.852 (0.682-0.952) for expert radiologist, respectively. No differences were observed among the subgroups in each radiologist ( P>0.05). Conclusion:The interval period does not significantly affect the detection accuracy and EPE assessment of PCa using mpMRI. There is probably no necessity for prolonged intervals following systematic biopsy to preserve the clarity of MRI interpretation for PCa.

Objective·To systematically review the effectiveness of actigraphy on the evaluation of circadian rhythm characteristics in patients with depression.Methods·A systematic literature search was conducted in PubMed,Embase,Web of Science,Cochrane Library,PsycINFO,CNKI,WanFang Data,and Chinese biomedical literature database(CBM),from the inception of each database to May 5th,2023.Case control studies that used actigraphy to evaluate circadian rhythms in patients with depression and compared them with healthy controls were collected.Literature was screened according to the inclusion and exclusion criteria,and the quality of the included literature was evaluated by using the Newcastle-Ottawa Scale.The meta-analysis was performed by using RevMan 5.4 software.Results·A total of 9 articles were included,including 390 patients with depression and 288 healthy controls.The meta-analysis showed that the MESOR(midline statistic of rhythm)(SMD=-0.29,95%CI-0.51 ?-0.07,P=0.009)of the circadian cosine function in patients with depression was lower than that in healthy controls;sleep onset(MD=33.06,95%CI 14.90 ? 51.23,P=0.000)and sleep offset(MD=53.80,95%CI 22.38 ? 85.23,P=0.000)were later in patients with depression than those in healthy controls;no statistical difference was found in the activity level of the most active 10 hours(SMD=-0.26,95%CI-0.52 ? 0.01,P=0.060)between patients with depression and healthy controls,although there was a trend for lower activity in patients with depression;no statistical difference was found in the acrophase(MD=25.33,95%CI-12.41 ? 63.06,P=0.190)of the circadian cosine function between patients with depression and healthy controls;no clear statistical significance of the difference was found in the amplitude(SMD=-0.14,95%CI-0.42 ? 0.14,P=0.340)and the activity level of the least active 5 hours(SMD=0.31,95%CI-0.10 ? 0.71,P=0.140)between patients with depression and healthy controls.Conclusion·Actigraphy can reflect circadian rhythm disruption in patients with depression to some extent,but the limited number of included studies and inconsistencies in the study populations and methodologies have affected the quality and results of the analyses.More high-quality clinical trials are needed to provide evidence.

Purpose To explore the diagnostic value of prostate imaging report and data system 2.1(PI-RADS v2.1)combined with prostate-specific antigen density(PSAD)for clinically significant prostate cancer(csPCa)in prostate-specific antigen(PSA)gray area(4-10 ng/ml)based on two-center data.Materials and Methods The clinical and imaging data of patients with PSA gray zone prostate disease who underwent multi-parametric magnetic resonance imaging and all pathological data in the First Medical Center(center 1)and the Sixth Medical Center(center 2)of the Chinese PLA General Hospital from January 2017 to May 2022 were retrospectively selected and analyzed.The patients from center 1 were used as the training group(220 cases),and the patients from center 2 were used as the test group(50 cases).Logistic regression was used to determine the independent predictors of csPCa in the training group,and the diagnostic efficacy of multi-parameter combination for csPCa was analyzed,which was further verified in the test group.Results There were significant differences in prostate volume,PSAD and PI-RADS v2.1 scores between the csPCa and non-csPCa groups in the training group(Z=-6.468,6.589,75.676,all P＜0.001).Logistic regression analysis showed that PI-RADS v2.1 score and PSAD were the independent risk factors for csPCa(both P＜0.001).The area under the curve of the Logistic regression model composed of PI-RADS v2.1 and PSAD for predicting csPCa in the PSA gray zone was 0.860(95％CI 0.808-0.903)in the training group and 0.906(95％CI 0.790-0.970)in the test group,respectively.The area under the curve of Logistic regression model was significantly higher than that of PI-RADS v2.1 and PSAD,respectively,with statistically significant difference(both P＜0.05).When the PI-RADS v2.1 score was low or moderate risk and PSAD＜0.15 ng/ml2,csPCa in the training group and the test group was with low detection rate.Conclusion PI-RADS v2.1 score and PSAD may be the independent risk factors for predicting csPCa in the PSA gray zone.The combined application of the two methods is better than the single method in the diagnosis of csPCa in the PSA gray zone,with benefits for clinical biopsy decision-making.

Purpose To explore the additional value of apparent diffusion coefficient(ADC)histogram in predicting extraprostatic extension(EPE)of prostate cancer.Materials and Methods Consecutive patients undergoing multi-parameter MRI and subsequent radical prostatectomy from January 2021 to December 2022 were retrospectively included in this study.Two radiologists independently estimated EPE by using national cancer institute grading system for extraprostatic extension(EPE grade system),with disagreement resolved by discussion.Histogram metrics were derived from three-dimensional volumes of interest encompassing the entire lesion on ADC maps using FireVoxel,obtaining mean ADC,1st,5th,10th,25th,50th,75th,90th,95th and 99th ADC values.The ADC histograms between the groups with and without EPE were compared.Multivariable Logistic regression analysis was used to identify the independent predictive factors of EPE,and a combined model was developed.Receiver operator characteristic curve was used to evaluate the diagnostic performance,and the area under the curve was calculated and compared.Results Thirty-four patients(34％)had pathologic confirmed EPE after radical prostatectomy.ADC histogram parameters showed significant differences between patients with and without EPE(P＜0.05).Multivariate Logistic regression analysis revealed 99th ADC(OR=0.609,P=0.008)and EPE grade system(OR=4.158,P＜0.001)were independent predictors of EPE.For predicting EPE,the area under the curve of 99th ADC,EPE grade system and the combined model were 0.756,0.805 and 0.856,respectively.The area under the curve of 99th ADC and the EPE grade system in identifying EPE showed no significant difference.The diagnostic efficacy of combined model was significantly superior to that of 99th ADC or EPE grading system(Z=2.223,2.208,both P＜0.05).Conclusion The ADC histogram parameters demonstrate additional value for preoperative prediction of EPE.Combining the 99th ADC histogram parameter with the EPE grade system may improve the diagnostic efficacy of EPE.

Adolescent depression has a high prevalence, atypical symptoms, and poor prognosis. Cytokines, as related to the inflammation hypothesis, which is one of the potential pathogenesis of depressive disorder and thus crucial in adolescent patients who are in the early stage of the disease, have received widespread attention. Based on the current research status, this commentary briefly discusses the research on cytokines related to adolescent depression to elucidate the value of cytokines in the clinical practice of adolescent depression.

Objective:This study aimed to explore whether there are abnormalities in the kynurenine pathway in patients with depression and suicidal ideation, and their dynamic relationship with clinical symptoms.Methods:According to the DSM-5 diagnostic criteria, a total of 68 patients with depression were prospectively enrolled, including 28 males and 40 females, aged( M ( Q1, Q3)) 22.0 (17.3, 47.8) years, who were the inpatients in the Division of Mood Disorders of Shanghai Mental Health Center from July 2019 to July 2022. The depressed patients were divided into groups with ( n=41) or without suicidal ideation ( n=27) based on whether they chose "weak" or "moderate to strong" suicidal ideation in questions 4 and 5 of the Beck Scale for Suicide Ideation (BSI). And 72 gender-matched healthy controls were also enrolled, including 29 males and 43 females, aged 25.5 (24.0, 36.8) years. Hamilton Depression Rating Scale-24 (HAMD 24), Hamilton Anxiety Rating Scale (HAMA), and BSI were used to evaluate the depression symptoms, anxiety symptoms, and suicidal ideation of depressed patients. All the participants received fasting venous blood collection to measure the levels of kynurenine metabolites in plasma. Among them, depressed patients with suicidal ideation were followed up, and the assessment s of depression symptoms, anxiety symptoms, and suicidal ideation, as well as kynurenine metabolites measurements, were repeated at the end of the 2nd and 4th weeks. Ultra-high performance liquid chromatography-triple quadrupole mass spectrometry was used to measure the levels of kynurenine metabolites in plasma. The hematological indicators were log-transformed, Z-score standardized, and false discovery rate correction was used for multiple comparisons of different metabolites. The relationship between baseline kynurenine metabolites and scale scores was analyzed. The relationship between kynurenine metabolites and scale scores during the follow-up process was analyzed by a linear mixed-effects model. Results:The peripheral picolinic acid (0.39±0.87 vs -0.23±1.09, t=3.89), 3-hydroxykynurenine/kynurenine (3-HK/KYN) (0.38±0.85 vs -0.09±1.01, t=2.98) and 3-HK (0.31±0.81 vs 0.14±1.04, t=2.78) of patients with depression were lower than those of healthy controls (both P<0.05). No statistically significant difference was found between patients with depression with or without suicidal ideation in kynurenine metabolites. In patients with depression and suicidal ideation, baseline HAMD 24 and HAMA scores were positively correlated with plasma 3-HK (HAMD 24: r=0.38; HAMA: r=0.39) and 3-HK/KYN (HAMD 24: r=0.34; HAMA: r=0.37) levels (all P<0.05). After adjusting for age and gender factors, a linear mixed-effects model was established for the follow-up scale scores, and kynurenine metabolite levels of this group of patients, and the results showed that the positive effect of HAMA score on 3-HK/KYN during follow-up was statistically significant ( B=0.04, t=2.46, P<0.05). Conclusion:There are abnormalities in the kynurenine pathway of tryptophan metabolism in patients with depression. 3-HK and 3-HK/KYN are related to the severity of depression and anxiety in patients with depression and suicidal ideation, among which 3-HK/KYN, representing the activity of kynurenine-3-monooxygenase, is dynamically associated with anxiety level.

Adolescent depression has a high prevalence, atypical symptoms, and poor prognosis. Cytokines, as related to the inflammation hypothesis, which is one of the potential pathogenesis of depressive disorder and thus crucial in adolescent patients who are in the early stage of the disease, have received widespread attention. Based on the current research status, this commentary briefly discusses the research on cytokines related to adolescent depression to elucidate the value of cytokines in the clinical practice of adolescent depression.