Approach-avoidance conflict(AAC)refers to the internal conflict that individuals experi-ence when faced with conflicting approach or avoidance thoughts.It reveals some characteristics of mental disorders,such as anxiety,depression,and addiction represented by excessive tendencies of approach or avoidance.The function of the cortico-limbic-striatal system influences behavioral choices at the neural level during the onset of AAC,and the development of related behavioral paradigms that can better represent AAC behaviors is critical to evaluating the efficacy of drugs and guiding the development of new drugs.This paper summarizes the neural mechanisms,behavioral paradigms,and applications in behavioral pharmacology related to AAC behaviors from the perspective of psychopharmacology with a view to providing new perspectives and methods for the diagnosis and treatment of related neuro-psychiatric disorders.

Objective:To explore the value of dual-layer detector spectral CT quantitative parameters in evaluating the treatment response of neoadjuvant chemoradiotherapy (nCRT) in patients with locally advanced rectal cancer (LARC).Methods:The study was a cross-sectional study. From May 2021 to March 2023, a total of 52 patients with LARC who received complete nCRT and were pathologically confirmed rectal adenocarcinoma at the Guangdong Province Hospital of Traditional Chinese Medicine were retrospectively enrolled. Each patient underwent spectral CT examination before and after nCRT, including plain scan, arterial phase (AP), and venous phase (VP) scans. According to the tumor regression grade, the patients were divided into the good response ( n=20) and the poor response group ( n=32). Measurements of the primary tumor′s spectral CT parameters, including effective atomic number (Z eff) at plain scan, iodine concentration (IC), CT values of 40 keV and 100 keV virtual monochromatic image (VMI) at dual-enhanced phases, were taken before and after nCRT. Additionally, the normalized iodine concentration (NIC), spectral curve slope (λHU), and the change rate of the above parameters before and after nCRT were calculated. The independent sample t-test or Mann-Whitney U test was used to compare the differences between the two groups. The receiver operating characteristic (ROC) curve was used to assess the efficacy of various metrics in evaluating the tumor treatment response of nCRT. A binary logistic regression analysis of combined parameter results was performed for the parameters with the areas under curve (AUC)>0.75, and the AUC of the combined parameter was evaluated. Results:There were significant differences in NIC AP and λHU VP before nCRT, NIC VP and λHU VP after nCRT, and the change rates of Z eff, NIC AP, NIC VP and λHU AP between the good response group and the poor response group ( P<0.05). The remaining parameters showed no statistically significant difference ( P>0.05). The ROC curve results showed that the AUCs of the above 8 parameters for evaluating tumor treatment response of nCRT were 0.702, 0.655, 0.695, 0.769, 0.738, 0.807, 0.791, and 0.677, respectively. The AUC of the combined model of the three parameters with AUC>0.75 (λHU VP after nCRT, the change rate of NIC AP and NIC VP) was 0.869, with 80.0% sensitivity and 84.4% specificity. Conclusion:The quantitative parameters derived from spectral CT may provide new markers for evaluating the response to nCRT treatment in patients with LARC. The multi-parameter combined model can improve diagnostic efficacy.

Objective To investigate the correlation between high-resolution computed tomograohy(HRCT)features and thera-peutic effect in patient with non-tuberculous mycobacteria pulmonary disease(NTM-PD).Methods A total of 225 NTM-PD patients were divided into curative group and non-curative group according to the efficacy criteria,and the clinical and HRCT features between the two groups were compared.Correlation analysis and logistic regression analysis were used to screen the risk factors for potential poor efficacy,and their predictive value was evaluated by the receiver operating characteristic(ROC)curve.Results The proportion of cavities,the number of nodules and bronchiectasis involving lung lobes in the non-curative group were significantly higher than those in the curative group,while the body mass index(BMI)was significantly lower than that in the curative group.The distribution of non-tuberculous mycobacteria(NTM)strains,cavities,the number of nodules involving lung lobes,and the number of bronchiecta-sis involving lung lobes were positively correlated with poor efficacy,while BMI was negatively correlated with poor efficacy(P＜0.05).The distribution of NTM strains,the number of nodules and bronchiectasis involving lung lobes were independent risk factors for poor efficacy(P＜0.05).Cavities,the number of nodules involving lung lobes,and the number of bronchiectasis involving lung lobes alone or in combination had high efficacy in predicting poor efficacy,with the highest prediction value of the three combined model[area under the curve(AUC)=0.819;95％confidence interval(CI)0.762-0.876].Conclusion The combined model based on cavities,the number of nodules involving lung lobes,and the number of bronchiectasis involving lung lobes has the highest effi-ciency in predicting poor efficacy in NTM-PD patients.

Objective:To evaluate the role of histogram analysis based on amide proton transfer weighted (APTw) and apparent diffusion coefficient (ADC) imaging in predicting alpha-thalassemia/mental retardation syndrome X-linked ( ATRX) mutation in isocitrate dehydrogenase ( IDH)-mutant WHO grading 2/3 gliomas. Methods:Seventy-eight patients with IDH-mutant WHO grading 2/3 gliomas, admitted to and confirmed by surgical pathology in Department of Functional Neurosurgery, Neurosurgery Center, Zhujiang Hospital, Southern Medical University from June 2017 to October 2023, including 52 with ATRX wild and 26 with ATRX mutant-type, were selected. Preoperative 3D-APTw and ADC imaging data were collected; after post-processing, the lesions were segmented using lesion outlining method based on inclusion of peri-tumor edema and lesion outlining method based on tumor entity, respectively; after that, the histogram features (the 10 th percentile, 90 th percentile, maximum, mean, median, minimum, skewness, kurtosis, entropy, range, uniformity, and variance) were extracted from 3D-APTw and ADC imaging, respectively. Univariate Logistic regression was used to compare the differences in histogram features between patients in the ATRX mutant group and ATRX wild-type group, and multivariate Logistic regression was used to screen the independent predictors for ATRX mutation (a Logistic regression prediction model was constructed). Predictive values of independent predictors and Logistic regression prediction models in ATRX mutation were evaluated by receiver operating characteristic (ROC) curve. Results:(1) With lesion outlining method based on inclusion of peri-tumor edema, univariate analysis indicated significant difference between ATRX mutant group and ATRX wild-type group in 9 histogram features: relative 3D-APTw minimum, 3D-APTw skewness, relative ADC 90 th percentile, relative ADC mean, relative ADC median, ADC kurtosis, ADC skewness, ADC uniformity, and ADC entropy ( P<0.05). With lesion outlining method based on tumor entity, univariate analysis indicated significant difference between ATRX mutant group and ATRX wild-type group in 9 histogram features: relative 3D-APTw 90 th percentile, 3D-APTw skewness, relative ADC 90 th percentile, relative ADC mean, relative ADC median, ADC kurtosis, ADC skewness, ADC uniformity and ADC entropy ( P<0.05). (2) With lesion outlining method based on inclusion of peri-tumor edema, multivariate Logistic regression showed that 3D-APTw skewness and ADC kurtosis were the independent predictor for ATRX mutation in IDH mutant WHO grading 2/3 glioma patients ( OR=0.168, 95% CI: 0.034-0.800, P=0.025; OR=0.508, 95% CI: 0.319-0.807, P=0.004). The constructed Logistic regression prediction model was P(Y=1|X)=1/1+e -(1.827-1.785×3D-APTw skewness-0.678×ADC kurtosis). With lesion outlining method based on tumor entity, multivariate Logistic regression showed that 3D-APTw skewness and ADC kurtosis were independent predictors for ATRX mutation in IDH mutant WHO grading 2/3 glioma patients ( OR=0.164, 95% CI: 0.034-0.791, P=0.024; OR=0.496, 95% CI: 0.312-0.788, P=0.003); the constructed Logistic regression prediction model was P(Y=1|X)=1/1+e -(1.585-1.810×3D-APTw skewness-0.702×ADC kurtosis). (3) ROC curve analysis showed that, with lesion outlining method based on inclusion of peri-tumor edema, area under ROC curve (AUC) of 3D-APTw skewness and ADC kurtosis was 0.725 (95% CI: 0.608-0.842, P=0.001) and 0.794 (95% CI: 0.685-0.904), respectively ( P<0.001); AUC of Logistic regression prediction model was 0.836 (95% CI: 0.729-0.942, P<0.001), and its sensitivity and specificity were 73.10% and 90.40% when the best threshold was 0.505. ROC curve showed that, with lesion outlining method based on tumor entity, AUC of 3D-APTw skewness and ADC kurtosis was 0.705 (95% CI: 0.587-0.823, P=0.003) and 0.808 (95% CI: 0.704-0.913), respectively ( P<0.001); AUC of Logistic regression prediction model was 0.844 (95% CI: 0.739-0.949, P<0.001), and its sensitivity and specificity were 84.60% and 80.80% when the best threshold was 0.399. Conclusion:Histogram analysis based on 3D-APTw and ADC imaging can predict ATRX mutation in IDH mutant WHO grading 2/3 gliomas to a certain extent.

Objective:To investigate the feasibility of a three-dimensional no new U-Net (3D nnU-Net) deep learning (DL) network for the automatic segmentation of colorectal cancer (CRC) based on abdominal CT images.Methods:This was a cross-sectional study. From January 2018 to May 2023, a total of 2180 primary CRC patients, confirmed by pathology at the Guangdong Provincial Hospital of Traditional Chinese Medicine (center 1, n=777), Nanfang Hospital, Southern Medical University (center 2, n=732), and Sun Yat-sen Memorial Hospital (center 3, n=671), were enrolled in this retrospective study. The baseline abdominal CT examination of each patient was conducted using CT equipment from 7 different models across 4 vendors, at the 3 centers, encompassing both the arterial phase (AP) and venous phase (VP). Two radiologists manually delineated the volume of interest to circumscribe the entire tumors in dual-enhanced phase CT images. The CT data of CRC patients from center 1 and center 3 were merged and divided into a training set ( n=1 159) and a validation set ( n=289) using a weighted random method with a ratio of 4∶1. The patients from center 2 were used as an independent external test set ( n=732). The 3D nnU-Net segmentation model was trained and tested. Using manually annotated label data as the benchmark, segmentation performance of the model was evaluated based on different phases and tumor locations. The segmentation coverage rate (SCR), Dice similarity coefficient (DSC), recall (REC), precision (PRE), F1-score, and 95% Hausdorff distance (HD 95) were calculated. The mean manual segmentation time and the mean automatic time were compared using independent samples t-test. Results:In the independent external test set, the performance of the 3D nnU-Net model based on the AP CT images was superior to that based on the VP CT images. On the AP images, the SCR, DSC, REC, PRE, F1-score, and HD 95 were 0.865, 0.714, 0.716, 0.736, 0.714, and 27.228, respectively; on the VP images, they were 0.834, 0.679, 0.710, 0.675, 0.679, and 29.358, respectively. The model achieved the best performance on right-sided colon cancer, with SCR, DSC, REC, PRE, F1-score, and HD95 on the AP CT images at 0.901, 0.775, 0.780, 0.787, 0.775, and 21.793, respectively. Next were left-sided colon cancer and rectal cancer, while the segmentation performance for transverse colon cancer was the worst (SCR, DSC, REC, PRE, F1-score, and HD 95 were 0.731, 0.631, 0.641, 0.630, 0.631 and 38.721, respectively). The automatic segmentation time on a single phase was (1.0±0.3) min, while the manual segmentation time was (17.5±6.0) min ( t=128.24, P<0.001). Conclusions:After training and validating on a dataset from multiple centers with various CT scanner vendors, the 3D nnU-Net DL model demonstrates the capability to automatically segment CRC based on abdominal CT images, while also showcasing commendable robustness and generalization ability.

Animal models are powerful tools for studying the mechanism of depressive disorders and screening antidepressants,but so far there is no model which can stimulate the clinical status of patients ideally.Here,we briefly introduced the research advances in classic animal models of depres-sive disorders,and focused on stress-related animal models,especially those induced by physical and social psychological stressors.The tests for evaluating animal depression behavior were reviewed.In this article,the strengths and weaknesses of each model were analyzed,and the precautions in its application were recommended.Finally,given the high heterogeneity of depressive disorders,this article elaborated on the research progress in models for subtypes of depressive disorders,such as treatment resistant depression,bipolar disorder,peripartum depression,and premenstrual syndrome.

OBJECTIVE: To develop a noninvasive method for prediction of 1p/19q codeletion in diffuse lower-grade glioma (DLGG) based on multimodal magnetic resonance imaging (MRI) radiomics. METHODS: We collected MRI data from 104 patients with pathologically confirmed DLGG between October, 2015 and September, 2022. A total of 535 radiomics features were extracted from T₂WI, T₁WI, FLAIR, CE-T₁WI and DWI, including 70 morphological features, 90 first order features, and 375 texture features. We constructed logistic regression (LR), logistic regression least absolute shrinkage and selection operator (LRlasso), support vector machine (SVM) and Linear Discriminant Analysis (LDA) radiomics models and compared their predictive performance after 10-fold cross validation. The MRI images were reviewed by two radiologists independently for predicting the 1p/19q status. Receiver operating characteristic curves were used to evaluate classification performance of the radiomics models and the radiologists. RESULTS: The 4 radiomics models (LR, LRlasso, SVM and LDA) achieved similar area under the curve (AUC) in the validation dataset (0.833, 0.819, 0.824 and 0.819, respectively; P>0.1), and their predictive performance was all superior to that of resident physicians of radiology (AUC=0.645, P=0.011, 0.022, 0.016, 0.030, respectively) and similar to that of attending physicians of radiology (AUC=0.838, P>0.05). CONCLUSION Multiparametric MRI radiomics models show good performance for noninvasive prediction of 1p/19q codeletion status in patients with in diffuse lower-grade glioma.
Humans ; Magnetic Resonance Imaging ; Chromosome Aberrations ; Area Under Curve ; Glioma/genetics* ; ROC Curve

Objective:To investigate the value of ultrasound in the diagnosis of intraneural perineurioma.Methods:From June 2015 to June 2022, 11 patients with intraneural perineurioma confirmed by surgery or biopsy in Provincial Hospital Affiliated to Shandong First Medical University were retrospectively collected, all of whom underwent high-frequency ultrasound examination. Clinical data and sonographic characteristics were collected. The maximum cross-sectional area of the affected nerve was recorded and compared with the corresponding site of the contralateral nerve.Results:All the 11 cases of intraneural perineurioma were single neuropathy. The sonogram showed that the affected nerve was spindle shaped and thickened. There was a statistical difference between the maximum cross-sectional area of the thickened intraneural perineurioma and the corresponding site of the contralateral nerve [(0.158±0.043)cm vs (0.044±0.012)cm, t=8.669, P<0.001]. The fascicles of the affected nerve were thickened with loss of normal fascicular definition, but there were still hyperechoic linear separation among the fascicles. Conclusions:High-frequency ultrasound may be a valuable technique for the diagnosis of intraneural perineurioma.

Objective:To explore the expressions of serum N-terminal osteocalcin (N-MID) and cytokeratin (CK) 5/6 in primary lung cancer patients with bone metastasis and their clinical significances.Methods:The clinical data of 96 patients with primary lung cancer admitted to Chengdu Second People's Hospital between February 2019 to February 2022 were retrospectively analyzed. All patients were divided into the bone metastasis group (38 cases) and the non-bone metastasis group (58 cases) according to whether bone metastasis occurred, and 45 healthy people who underwent physical examination during the same period were treated as the healthy control group. The expression levels of serum N-MID and CK5/6 in the bone metastasis group, the non-bone metastasis group and the healthy control group were compared. Logistic regression was used to analyze the factors affecting bone metastasis in patients with primary lung cancer; receiver operating characteristic (ROC) curve analysis was used to analyze the value of the expression levels of serum N-MID and CK5/6 in predicting bone metastasis in patients with primary lung cancer.Results:The composition ratio of patients with pathological stage Ⅲ-Ⅳ, serum bone-derived alkaline phosphatase and N-MID expression levels in the bone metastasis group were higher than those in the non-bone metastasis group (all P < 0.05). The expression level of serum N-MID in the bone metastasis group and non-bone metastasis group was higher than that in the healthy control group [(26.0±5.3) ng/ml, (15.3±3.1) ng/ml vs. (9.9±1.7) ng/ml, F = 224.27, P < 0.001], and there were statistically significant differences in the serum N-MID expression level of the pairwise comparison among the three groups (all P < 0.05). The expression level of serum CK5/6 in the bone metastasis group and the non-bone metastasis group was lower than that in the healthy control group [(3.6±0.7) ng/ml, (7.3±1.4) ng/ml vs. (10.6±2.4) ng/ml, F = 178.11, P < 0.001], and there were statistically significant differences in the serum CK5/6 expression level of the pairwise comparison among the three groups (all P < 0.05). Multivariate analysis showed that CK5/6, N-MID and bone-derived alkaline phosphatase were independent affecting factors for bone metastasis in patients with primary lung cancer ( OR = 4.088, 3.615, 2.892, all P < 0.05). ROC curve analysis showed that the optimal cut-off values of serum N-MID and CK5/6 expression levels for predicting bone metastasis in patients with primary lung cancer were 18.59 ng/ml and 4.71 ng/ml; the corresponding the area under the curve (AUC) was 0.881 and 0.862, respectively; and the specificity and AUC of the combination of serum N-MID and CK5/6 in predicting the bone metastasis in patients with primary lung cancer was 98.28% and 0.937 (95% CI 0.869-0.977), respectively; the AUC predicted by the combination of both was higher than that by serum N-MID or CK5/6 single (all P < 0.001). Conclusions:The expression levels of serum N-MID and CK5/6 in primary lung cancer patients with bone metastasis are abnormally changed. Clinical detection of serum N-MID and CK5/6 expression levels may be used as sensitive indicators for predicting the bone metastasis in patients with primary lung cancer.

In this paper, the domestic and international demand and development trend of clinical diagnostic radionuclides are analyzed, and the medium and high-energy cyclotrons, adequate and systematic facilities, and preparation techniques required for the production of medical radionuclides based on solid targets are introduced. This paper focuses on the research and development carried out by some important medical institutions and scientific research institutes in China over the years in the aspects of medium and high-energy cyclotrons, beam transmission lines, high-power irradiation target stations and new medical isotope production processes etc. It also looks forward to some new directions for the development of medical radionuclides in China during the 14th Five-Year Plan period.