Personalized drug response prediction from molecular data is an important challenge in precision medicine for treating cancer. Computational methods have been widely explored and have become increasingly accurate in recent years. However, the clinical application of prediction methods is still in its infancy due to large discrepancies between preclinial models and patients. We present a novel disentangled synthesis transfer network (DiSyn) for drug response prediction specifically designed for transfer learning from preclinical models to clinical patients. DiSyn uses a domain separation network (DSN) to disentangle drug response related features, employs data synthesis technology to increase the sample size and iteratively trains for better feature disentanglement. DiSyn is pretrained on large-scale unlabeled cancer samples and validated by three datasets, The Cancer Genome Atlas (TCGA), Investigation of Serial Studies to Predict Your Therapeutic Response With Imaging And moLecular Analysis 2 (I-SPY2) and Novartis Institutes for Biomedical Research Patient-Derived Xenograft Encyclopedia (NIBR PDXE), achieving competitive performance with the state-of-the-art methods on cancer patients and mice. Furthermore, the application of DiSyn to thousands of breast cancer patients show the heterogeneity in drug responses and demonstrate its potential value in biomarker discovery and drug combination prediction.

Ocular accommodation refers to the process by which the ciliary muscle creates a clear image of the object in the retina by changing the refractive power of the lens. When the accommodation ability of the eye is insufficient, the imaging focus falls on the region behind the retina and hyperopic defocus is easily formed, resulting in axial growth and leading to the development of myopia, and it is found that most myopic patients usually have some accommodation dysfunction. Myopia has become a public health problem in China, and the prevalence of adolescents has increased dramatically. How to prevent and stop the occurrence and development of myopia is a major challenge. Previous studies have found that ocular accommodation dysfunction is associated with the occurrence and development of myopia, and the measurement of parameters related to accommodation function has certain guiding significance for the prevention and control of myopia. The purpose of this paper is to review the correlation between myopia and ocular accommodation function, with a view to providing new ideas for the prevention, control and treatment of myopia.

Objective:To investigate the value of CT radiomic model based on analysis of primary gastric cancer and the adipose tissue outside the gastric wall beside cancer in differentiating stage T1-2 from stage T3-4 gastric cancer.Methods:This study was a case-control study. Totally 465 patients with gastric cancer treated in Affiliated People′s Hospital of Jiangsu University from December 2011 to December 2019 were retrospectively collected. According to postoperative pathology, they were divided into 2 groups, one with 150 cases of T1-2 tumors and another with 315 cases of T3-4 tumors. The cases were divided into a training set (326 cases) and a test set (139 cases) by stratified sampling method at 7∶3. There were 104 cases of T1-2 stage and 222 cases of T3-4 stage in the training set, 46 cases of T1-2 stage and 93 cases of T3-4 stage in the test set. The axial CT images in the venous phase during one week before surgery were selected to delineate the region of interest (ROI) at the primary lesion and the extramural gastric adipose tissue adjacent to the cancer areas. The radiomic features of the ROIs were extracted by Pyradiomics software. The least absolute shrinkage and selection operator was used to screen features related to T stage to establish the radiomic models of primary gastric cancer and the adipose tissue outside the gastric wall beside cancer. Independent sample t test or χ2 test were used to compare the differences in clinical features between T1-2 and T3-4 patients in the training set, and the features with statistical significance were combined to establish a clinical model. Two radiomic signatures and clinical features were combined to construct a clinical-radiomics model and generate a nomogram. The area under the receiver operating characteristic curve (AUC) was used to evaluate the efficacy of each model in differentiating stage T1-2 from stage T3-4 gastric cancer. The calibration curve was used to evaluate the consistency between the T stage predicted by the nomogram and the actual T stage of gastric cancer. And the decision curve analysis was used to evaluate the clinical net benefit of treatment guided by the nomogram and by the clinical model. Results:There were significant differences in CT-T stage and CT-N stage between T1-2 and T3-4 patients in the training set ( χ2=10.59, 15.92, P=0.014, 0.001) and the clinical model was established. After screening and dimensionality reduction, the 5 features from primary gastric cancer and the 6 features from the adipose tissue outside the gastric wall beside cancer established the radiomic models respectively. In the training set and the test set, the AUC values of the primary gastric cancer radiomic model were 0.864 (95% CI 0.820-0.908) and 0.836 (95% CI 0.762-0.910), and the adipose tissue outside the gastric wall beside cancer radiomic model were 0.782 (95% CI 0.731-0.833) and 0.784 (95% CI 0.702-0.866). The AUC values of the clinical model were 0.761 (95% CI 0.705-0.817) and 0.758 (95% CI 0.671-0.845), and the nomogram were 0.876 (95% CI 0.835-0.917) and 0.851 (95% CI 0.781-0.921). The calibration curve reflected that there was a high consistency between the T stage predicted by the nomogram and the actual T stage in the training set ( χ2=1.70, P=0.989). And the decision curve showed that at the risk threshold 0.01-0.74, a higher clinical net benefit could be obtained by using a nomogram to guide treatment. Conclusions:The CT radiomics features of primary gastric cancer lesions and the adipose tissue outside the gastric wall beside cancer can effectively distinguish T1-2 from T3-4 gastric cancer, and the combination of CT radiomic features and clinical features can further improve the prediction accuracy.

Objective:This study aims to explore the predictive value of T2-weighted imaging (T2WI), apparent diffusion coefficient (ADC), and early-delayed phases enhanced magnetic resonance imaging (DCE-MRI) radiomics prediction model in determining human epidermal growth factor receptor 2 status in breast cancer.Methods:A retrospective study was conducted, involving 187 patients with confirmed breast cancer by postsurgical pathology at Zhenjiang First People's Hospital during January 2021 and May 2023. Immunohistochemistry or fluorescence in situ hybridization was used to determine the HER-2 status of these patients, with 48 cases classified as HER-2 positive and 139 cases as HER-2 negative. The training set was used to construct the prediction models and the validation set was used to verify the prediction models. Layers of T2WI, ADC, and early-delayed phase DCE-MRI images were used to delineate the volumeof interest and 960 radiomic features were extracted from each case using Pyradiomic. After screening and dimensionality reduction by intraclass correlation coefficient, Pearson correlation analysis, least absolute shrinkage, and selection operator, the radiomics labels were established. Logistic regression analysis was used to construct the T2WI radiomics model, ADC radiomics model, DCE-2 radiomics model, DCE-6 radiomics model, and the joint sequence radiomics model to predict the HER-2 expression status of breast cancer, respectively. Based on the clinical, pathological, and MRI image characteristics of patients, univariate and multivariate logistic regression analysis wasused to construct a clinicopathological MRI feature model. The radscore of every patient and the clinicopathological MRI features which were statistically significant after screening were used to construct a nomogram model. The receiver operating characteristic (ROC) curve was used to evaluate the predictive performance of each model and the decision curve analysis wasused to evaluate the clinical usefulness.Results:The T2WI, ADC, DCE-2, DCE-6, and joint sequence radiomics models, the clinicopathological MRI feature model, and the nomogram model were successfully constructed to predict the expression status of HER-2 in breast cancer. ROC analysis showed that in the training set and validation set, the areas under the curve (AUC) of the T2WI radiomics model were 0.797 and 0.760, of the ADC radiomics model were 0.776 and 0.634, of the DCE-2 radiomics model were 0.804 and 0.759, of the DCE-6 radiomics model were 0.869 and 0.798, of the combined sequence radiomics model were 0.908 and 0.847, of the clinicopathological MRI feature model were 0.703 and 0.693, and of the nomogram model were 0.938 and 0.859, respectively. In the training set, the combined sequence radiomics model outperformed the clinicopathological features model ( P＜0.001). In the training and validation sets, the nomogram outperformed the clinicopathological features model ( P＜0.05). In addition, the diagnostic performance of the nomogram was better than that of the four single-modality radiomics models in the training cohort ( P＜0.05) and was better than that of DCE-2 and ADC models in the validation cohort ( P＜0.05). Decision curve analysis indicated that the value of individualized prediction models was higher than clinical and pathological prediction models in clinical practice. The calibration curve showed that the multimodal radiomics model had a high consistency with the actual results in predicting HER-2 expression. Conclusions:T2WI, ADC and early-delayed phase DCE-MRI imaging histology models for HER-2 expression status in breast cancer are expected to provide a non-invasive virtual pathological basis for decision-making on preoperative neoadjuvant regimens in breast cancer.

Objective To study the effect of squatting toilet behavior on gastric transport time(GTT)and complete examination rate of small bowel(CER)during capsule endoscopy.Methods A total of 122 patients who underwent capsule endoscopy at the Second Affiliated Hospital of Chongqing Medical University from January to December 2019 were recruited and randomly divided into test group(n=63)and control group(n=59).The patients of the test group were asked to take squatting posture for toileting after swallowing the capsule,while those of the control group were asked to take sitting in defecation if needed.GTT,small bowel transit time(SBTT),CER and diagnostic yield(DY)were compared between the 2 groups.Results There were no significant differences in gender,age and conditions during hospitalization between the test group and the control group.The test group obtained obviously higher CER(92.06％vs 79.66％,P=0.048)and shorter GTT(26.7 vs 45.6 min,P=0.027)when compared with the control group.No statistical differences were seen in SBTT and DY between the 2 groups.Conclusion Squatting posture for toileting of patients accepted capsule endoscopy can reduce the transit time of capsules in the stomach and increase the CER.

Objective:This study aims to explore the predictive value of T2-weighted imaging (T2WI), apparent diffusion coefficient (ADC), and early-delayed phases enhanced magnetic resonance imaging (DCE-MRI) radiomics prediction model in determining human epidermal growth factor receptor 2 status in breast cancer.Methods:A retrospective study was conducted, involving 187 patients with confirmed breast cancer by postsurgical pathology at Zhenjiang First People's Hospital during January 2021 and May 2023. Immunohistochemistry or fluorescence in situ hybridization was used to determine the HER-2 status of these patients, with 48 cases classified as HER-2 positive and 139 cases as HER-2 negative. The training set was used to construct the prediction models and the validation set was used to verify the prediction models. Layers of T2WI, ADC, and early-delayed phase DCE-MRI images were used to delineate the volumeof interest and 960 radiomic features were extracted from each case using Pyradiomic. After screening and dimensionality reduction by intraclass correlation coefficient, Pearson correlation analysis, least absolute shrinkage, and selection operator, the radiomics labels were established. Logistic regression analysis was used to construct the T2WI radiomics model, ADC radiomics model, DCE-2 radiomics model, DCE-6 radiomics model, and the joint sequence radiomics model to predict the HER-2 expression status of breast cancer, respectively. Based on the clinical, pathological, and MRI image characteristics of patients, univariate and multivariate logistic regression analysis wasused to construct a clinicopathological MRI feature model. The radscore of every patient and the clinicopathological MRI features which were statistically significant after screening were used to construct a nomogram model. The receiver operating characteristic (ROC) curve was used to evaluate the predictive performance of each model and the decision curve analysis wasused to evaluate the clinical usefulness.Results:The T2WI, ADC, DCE-2, DCE-6, and joint sequence radiomics models, the clinicopathological MRI feature model, and the nomogram model were successfully constructed to predict the expression status of HER-2 in breast cancer. ROC analysis showed that in the training set and validation set, the areas under the curve (AUC) of the T2WI radiomics model were 0.797 and 0.760, of the ADC radiomics model were 0.776 and 0.634, of the DCE-2 radiomics model were 0.804 and 0.759, of the DCE-6 radiomics model were 0.869 and 0.798, of the combined sequence radiomics model were 0.908 and 0.847, of the clinicopathological MRI feature model were 0.703 and 0.693, and of the nomogram model were 0.938 and 0.859, respectively. In the training set, the combined sequence radiomics model outperformed the clinicopathological features model ( P＜0.001). In the training and validation sets, the nomogram outperformed the clinicopathological features model ( P＜0.05). In addition, the diagnostic performance of the nomogram was better than that of the four single-modality radiomics models in the training cohort ( P＜0.05) and was better than that of DCE-2 and ADC models in the validation cohort ( P＜0.05). Decision curve analysis indicated that the value of individualized prediction models was higher than clinical and pathological prediction models in clinical practice. The calibration curve showed that the multimodal radiomics model had a high consistency with the actual results in predicting HER-2 expression. Conclusions:T2WI, ADC and early-delayed phase DCE-MRI imaging histology models for HER-2 expression status in breast cancer are expected to provide a non-invasive virtual pathological basis for decision-making on preoperative neoadjuvant regimens in breast cancer.

Objective:To assess the ultrasonographic features and potential diseases of fetal abnormal sylvian fissure(SF), and to explore the value of whole-genome sequencing (WGS) in prenatal detection.Methods:A total of 28 fetuses with a sonographic diagnosis of abnormal SF in Shenzhen Maternal and Child Health Hospital Affiliated to Southern Medical University between October 2018 and October 2020 were prospectively included. The fetal brain was evaluated by neuroultrasound and intrauterine MRI in detail. Amniotic fluid/cord blood obtained by amniocentesis or tissue samples from umbilical cord after birth were collected for WGS. Pregnancy outcomes and postnatal MRI were recorded, and neurodevelopment of live-born infants was followed up for more than 24 months after delivery.Results:During the study period, 28 fetuses with abnormal SF were identified, with a gestational age of 21.3-30.0 (24.8±2.0) weeks. Abnormal SF presented in MCD ( n=15, 53.6%), chromosomal anomalies ( n=3, 10.7%) or single-gene genetic syndromes ( n=3, 10.7%) with the affected fetuses showing developmental delay, hydrocephalus or leukomalacia ( n=4, 14.2%), corpus callosal agenesis with large interhemispheric cysts ( n=1, 3.6%), benign subarachnoid space enlargement with arachnoid cysts ( n=1, 3.6%), and multiple malformations ( n=1, 3.6%). Among the 15 cases with MCD, the most common pathology was lissencephaly/pachygyria, followed by schizencephaly, severe microcephaly, hemimegalencephaly with paraventricular heterotopia, and polymicrogyria. Abnormal SF presented bilaterally in 23 fetuses and unilaterally in 5. All cases were categorized into six types depending on SF morphology in the transthalamic section: no plateau-like or a small insula, linear type, irregular corrugated SF, Z-shaped, and cyst occupying type. In addition to abnormal SF, associated anomalies or mild variations were identified in all fetuses. There were 17 cases underwent intrauterine MRI, and 13 cases underwent postnatal MRI examination.And 25 pregnancies were terminated; 3 were born alive, and 2 had typical syndromic changes with poor neurodevelopmental prognosis. A related pathogenic genetic variant was detected in 57.1% (16/28) fetus, and the incidence of single nucleotide variants(SNVs) was 42.9% (12/28), among which de novo SNVs accounted for 91.7% (11/12). Conclusions:Fetal abnormal SF could be classified based on the ultrasonographic features of transthalamic section. Fetal abnormal SF may indicate MCD, some chromosomal abnormalities or single-gene genetic syndromes that may lead to poor neurodevelopmental outcomes, and may be affected by extra-cortical factors. It is suggested to carry out targeted prenatal genetic diagnosis for fetuses with abnormal SF.

OBJECTIVE To investigate the improvement effects and mechanism of scutellarin （Scu） on neuroinflammation in rats with traumatic brain injury （TBI）. METHODS The modified Feeney method was applied to construct TBI rat model. The rats were randomly grouped into TBI group，Scu low-dose group （40 mg/kg），Scu high-dose group （80 mg/kg），cyclic guanylate- adenylate synthase （cGAS） inhibitor group （cGAS inhibitor RU.521，450 μg/kg），with 24 rats in each group. Other 24 rats were included in the sham operation group. The modified neurological deficit score （mNSS） method was applied to assess the neurological function of rats； the brain water content of rats was measured by dry/wet specific gravity method； hematoxylin-eosin and TdT-mediated dUTP nick-end labeling staining were applied to observe the pathological changes and apoptosis of brain tissue in rats； the levels of interferon-β （IFN-β），CXC chemokine ligand-10 （CXCL10），tumor necrosis factor-α （TNF-α） and interleukin-6 （IL-6） in rat brain tissue were detected by enzyme-linked immunosorbent assay； Western blot method was applied to detect the expression of cGAS/interferon gene stimulating protein （STING） signal pathway-related proteins in brain tissue of rats. RESULTS Compared with the sham operation group，the mNSS，brain water content，apoptosis rate，the contents of IFN-β，CXCL10，TNF-α and IL-6，and the relative expressions of cGAS and STING proteins in TBI group increased significantly （P＜0.05）； there were edema，bleeding and pathological damage to neurons in the brain tissue. Compared with TBI group，the above indicators and pathological changes of rats in administration groups were improved significantly （P＜0.05），and the effect of Scu was in a dose- dependent manner （P＜0.05）； however，there was no statistically obvious difference in the above indicators between the Scu high- dose group and the cGAS inhibitor group （P＞0.05）. CONCLUSIONS Scu may alleviate neuroinflammation，reduce brain tissue damage and apoptosis，and promote the recovery of neural function in TBI rats by inhibiting the activation of cGAS/STING signaling pathway.

Aristolochic acids (AAs) have long been considered as a potent carcinogen due to its nephrotoxicity. Aristolochic acid I (AAI) reacts with DNA to form covalent aristolactam (AL)-DNA adducts, leading to subsequent A to T transversion mutation, commonly referred as AA mutational signature. Previous research inferred that AAs were widely implicated in liver cancer throughout Asia. In this study, we explored whether AAs exposure was the main cause of liver cancer in the context of HBV infection in mainland China. Totally 1256 liver cancer samples were randomly retrieved from 3 medical centers and a refined bioanalytical method was used to detect AAI-DNA adducts. 5.10% of these samples could be identified as AAI positive exposure. Whole genome sequencing suggested 8.41% of 107 liver cancer patients exhibited the dominant AA mutational signature, indicating a relatively low overall AAI exposure rate. In animal models, long-term administration of AAI barely increased liver tumorigenesis in adult mice, opposite from its tumor-inducing role when subjected to infant mice. Furthermore, AAI induced dose-dependent accumulation of AA-DNA adduct in target organs in adult mice, with the most detected in kidney instead of liver. Taken together, our data indicate that AA exposure was not the major threat of liver cancer in adulthood.

Objective:To clarity the clinical features of juvenile dermatomyositis (JDM) with positive anti-melanoma differentiation associated gene 5 (MDA5) antibody.Methods:Retrospective study.Clinical data of 11 anti-MDA5 autoantibody-positive JDM patients in the Department of Rheumatology and Immunology, Children′s Hospital Affiliated to Capital Institute of Pediatrics from January 2016 to January 2019 were retrospectively recruited for analyzing their clinical characteristics, pulmonary imaging and pulmonary function, thus summarizing treatment experiences.Results:A total of 11 children with anti-MDA5 autoantibody-positive JDM were recruited, involving 2 males and 9 females, with the average onset age of 1-13 (5.8±4.2) years.Clinical manifestations included rash in 11 cases (100.0%), arthritis in 5 cases (45.5%), and myasthenia in 4 cases (36.4%). Muscle enzyme elevated in 10 cases (90.9%) and serum ferritin (SF) elevated in 9 patients (81.8%). Ten cases (90.9%) showed interstitial lung disease (ILD), manifesting as ground glass opacity at subpleural area on CT scans, restrictive ventilation and decreased diffusion function on lung function test, while respiratory symptoms were absent.All patients were treated with glucocorticoid combined with immunosuppressor.Case 2 developed into rapid progressive pulmonary interstitial disease (RPILD), and died of respiratory failure 2 months later.The remaining was followed up for 1-2 years, and the ILD was relieved.Conclusions:All recruited children with anti-MDA5 autoantibody-positive JDM presented typical rash, and mild muscle weakness with a greater tendency to arthritis.Chinese pediatric patients are prone to complicate with ILD with no respiratory symptoms, but ground glass opacity at subpleural area on CT, and restrictive ventilation and decreased diffusion function on lung function test can be detected.Elevated SF is associated with the development of ILD.Glucocorticoid combined with immunosuppressive therapy is effective to JDM with ILD, but ineffective for RPILD.The mortality of anti-MDA5 autoantibody-positive JDM is high without an effective treatment.