Objective:To develop an artificial intelligence (AI)-based automatic scoring model for magnetic resonance imaging-detected extramural vascular invasion (AI-mrEMVI) and evaluate its performance and prognostic value in patients with rectal cancer.Methods:In this multicenter retrospective cohort study, a total of 2 501 rectal cancer patients from seven centers between November 2012 and December 2020 were included and divided into completely independent training ( n=1 830) and validation ( n=671) cohorts. A nnUNet-based AI-mrEMVI scoring model was constructed. Manual mrEMVI scores assigned by two radiologists served as the reference standard for accessing the accuracy of the AI-mrEMVI scoring. Kaplan-Meier survival analysis and Cox regression were used to evaluate the prognostic stratification ability of the AI-mrEMVI scores. The concordance index (C-index) was calculated to evaluate prognostic performance. Results:In the validation cohort, the manual mrEMVI scores were 0-2 in 425 patients (63.3%), 3 in 89 (13.4%), and 4 in 157 (23.4%). The AI-mrEMVI model identified 0-2 in 375 patients (55.9%), 3 in 95 (14.2%), and 4 in 201 (30.0%), with an overall accuracy of 81.1% (544/671, 95% CI 77.9%-84.0%). The 3-year disease-free survival (DFS) rates for patients with AI-mrEMVI scores of 0-2, 3, and 4 were 85.2%, 70.0%, and 58.2%, respectively, and the 5-year overall survival (OS) rates were 87.2%, 81.6%, and 62.6%, respectively (DFS: χ2=48.74, P<0.001; OS: χ2=30.04, P<0.001). Multivariable Cox regression showed that for DFS, AI-mrEMVI scores of 3 and 4 were associated with hazard ratios ( HR) of 1.75 (95% CI 1.11-2.77, P=0.016) and 2.65 (95% CI 1.86-3.78, P<0.001), respectively. For OS, an AI-mrEMVI score of 4 was associated with an HR of 2.56 (95% CI 1.62-4.03, P<0.001). The C-index values of the AI-mrEMVI scoring model for predicting DFS and OS were 0.647 (95% CI 0.608-0.686) and 0.650 (95% CI 0.598-0.702), respectively. Conclusion:The proposed AI-mrEMVI automatic scoring model demonstrated high diagnostic accuracy and performed favorably in predicting DFS and OS prognostic risk in patients with rectal cancer.

Objective:To develop an artificial intelligence (AI)-based automatic scoring model for magnetic resonance imaging-detected extramural vascular invasion (AI-mrEMVI) and evaluate its performance and prognostic value in patients with rectal cancer.Methods:In this multicenter retrospective cohort study, a total of 2 501 rectal cancer patients from seven centers between November 2012 and December 2020 were included and divided into completely independent training ( n=1 830) and validation ( n=671) cohorts. A nnUNet-based AI-mrEMVI scoring model was constructed. Manual mrEMVI scores assigned by two radiologists served as the reference standard for accessing the accuracy of the AI-mrEMVI scoring. Kaplan-Meier survival analysis and Cox regression were used to evaluate the prognostic stratification ability of the AI-mrEMVI scores. The concordance index (C-index) was calculated to evaluate prognostic performance. Results:In the validation cohort, the manual mrEMVI scores were 0-2 in 425 patients (63.3%), 3 in 89 (13.4%), and 4 in 157 (23.4%). The AI-mrEMVI model identified 0-2 in 375 patients (55.9%), 3 in 95 (14.2%), and 4 in 201 (30.0%), with an overall accuracy of 81.1% (544/671, 95% CI 77.9%-84.0%). The 3-year disease-free survival (DFS) rates for patients with AI-mrEMVI scores of 0-2, 3, and 4 were 85.2%, 70.0%, and 58.2%, respectively, and the 5-year overall survival (OS) rates were 87.2%, 81.6%, and 62.6%, respectively (DFS: χ2=48.74, P<0.001; OS: χ2=30.04, P<0.001). Multivariable Cox regression showed that for DFS, AI-mrEMVI scores of 3 and 4 were associated with hazard ratios ( HR) of 1.75 (95% CI 1.11-2.77, P=0.016) and 2.65 (95% CI 1.86-3.78, P<0.001), respectively. For OS, an AI-mrEMVI score of 4 was associated with an HR of 2.56 (95% CI 1.62-4.03, P<0.001). The C-index values of the AI-mrEMVI scoring model for predicting DFS and OS were 0.647 (95% CI 0.608-0.686) and 0.650 (95% CI 0.598-0.702), respectively. Conclusion:The proposed AI-mrEMVI automatic scoring model demonstrated high diagnostic accuracy and performed favorably in predicting DFS and OS prognostic risk in patients with rectal cancer.

Objective To observe the influence of functional ankle instability(FAI)on balance and lower limb explosive power. Methods A total of 26 male FAI participants,13 bilateral(bilateral group)and 13 left(left group),who regularly en-gaged in high-intensity exercise,were recruited at Harbin Sport University in May,2024.Meanwhile,13 unin-jured male participants who engaged in high-intensity exercise were recruited as control group.They were mea-sured the moving area of the left foot,right foot and body center of gravity standing on feet with the eyes opened and closed;as well as the sway angle,confidence ellipse diameter(maximum and minimum)to circle area ratio,sway ratio and confidence ellipse standing on single foot,with Gaitview plantar pressure analysis system.They were also tested with Y-balance test(YBT),and were measured flight time and center of gravity height during jumps single leg left/right drift,stiffness and counter movement jump using Opto-jump Optical Measurement of Motor Quality. Results There were significant differences among the groups in swing angle,confidence ellipse diameter(maximum and minimum)to circle area ratio,swing ratio and confidence ellipse as left-leg stance with eyes closed(F>3.300,P<0.05),which was the least in the control group(P<0.05).Swing angle,swing ratio and confidence ellipse were also different among the groups as right-leg stance with eyes closed(F>4.404,P<0.05),and they were less in the control group than in the bilateral group(P<0.05),and less in the left group than in the bilateral group(P<0.05),except swing angle.There was a significant difference in YBT results(F>3.649,P<0.05),which was the least in the bilateral group(P<0.05).There were significant differences in the flight time and center of gravity height during counter movement jump(F>7.458,P<0.01),which was the least in the bilateral group(P<0.05). Conclusion FAI may impair the static balance as single-leg stance with eyes closed,dynamic balance and lower limb ex-plosive power.

Objective:To study the patterns of tocilizumab (TCZ) use, its efficacy and safety in patients with rheumatoid arthritis (RA) in routine clinical practice.Methods:A total of 407 patients with RA were enrolled from 23 centers and treated with TCZ within 8 weeks prior to the enrollment visit, and were followed for 6-month. The patterns of TCZ treatment at 6 months, the effectiveness and safety outcomes were recorded. Statistical analysis was performed using SAS version 9.4.Results:A total of 396 patients were included for analysis, in which 330 (83.3%) patients received TCZ combined with conventional synthetic disease-modifying antirheumatic drugs (csDMARDs), and 16.7%(66/396) received TCZ monotherapy. At baseline, TCZ was initiated in 56.6%(224/396) and 9.6%(38/396) of patients after failure of DMARDs and other biological agents (bDMARDs) respectively. During the 6-month follow-up period, the mean frequency of TCZ administration was (3.7±1.6), the mean TCZ dosage was (7.4±1.2) mg/kg, and the mean interval between doses was (40±13) days. 120(25.8%) patients were on TCZ treatment at the end of the study. Improvements in disease activity, systemic symptoms and patient report outcomes were observed at the end of the study. 22.7%(90/396) patients experienced at least one treatment related adverse event, and 8 patients experienced at least one serious adverse event.Conclusion:This study demonstrates that TCZ treatment is effective in patients with RA when being treated for 6 months with an acceptable safety profile. The duration of TCZ treatment needs to be extended.

Objective:To investigate the application value of baseline MRI multi-parametric imaging radiomics in prediction of neoadjuvant chemoradiotherapy (NCR) efficacy of rectal mucinous adenocarcinoma (RMAC).Methods:Retrospective analysis was performed in the Sixth Affiliated Hospital of Sun Yat-sen University from August 2012 to October 2018. A total of 79 patients were included in this study, including 52 males and 27 females, aged 20-78 years (median age 52 years). According to the classification criteria of pathological regression, all patients were divided into NCR responsiveness group ( n=31) and nonresponsiveness group ( n=48). And 701 imaging features of T 2WI, diffusion weighted imaging (DWI) and enhanced T 1WI images of baseline MRI were extracted, and feature subsets were selected by repeatability analysis and feature dimensionality reduction to construct the radiomics prediction model. The tumor features from baseline MRI between the NCR responsiveness group and the nonresponsiveness group were compared, and the features of P<0.05 were combined with the radiomics to construct a model. Using pathology as the gold standard, the receiver operating characteristic (ROC) curve was used to evaluate the diagnostic efficiency of the prediction model, and the area under the curve (AUC), 95% confidence interval, sensitivity and specificity were calculated, and the DeLong test was used to compare the diagnostic efficacy of different prediction models. Results:By comparing the conventional tumor imaging characteristics of the NCR responsiveness group and the nonresponsiveness group, the differences in lymph node stage and mucinous nodule status between the two groups were statistically significant (χ2 =6.040, 5.870, P<0.05). The AUC of ROC curves based on T 2WI, DWI, and enhanced T 1WI radiomics were 0.816, 0.821, and 0.819, respectively, which were higher than those of conventional tumor characteristics (lymph node staging, mucinous nodule status) (AUC=0.607), and the differences were statistically significant ( Z=-2.391, -2.580 and -2.717, P<0.05). Among the joint prediction models of T 2WI, DWI and contrast-enhanced T 1WI radiomics and conventional tumor features, the DWI combined model had the largest AUC (0.843), and there was no statistically significant difference between the three combined models (all P>0.05). Conclusion:The baseline T 2WI, DWI, and contrast-enhanced T 1WI radiomics model can be used to predict the NCR efficacy of RMAC, which is better than the predictive efficacy of conventional features, and the combination with conventional features can further improve the predictive efficacy.

Mosaic variants resulting from postzygotic mutations are prevalent in the human genome and play important roles in human diseases. However, except for cancer-related variants, there is no collection of postzygotic mosaic variants in noncancer disease-related and healthy individuals. Here, we present MosaicBase, a comprehensive database that includes 6698 mosaic variants related to 266 noncancer diseases and 27,991 mosaic variants identified in 422 healthy individuals. Genomic and phenotypic information of each variant was manually extracted and curated from 383 publications. MosaicBase supports the query of variants with Online Mendelian Inheritance in Man (OMIM) entries, genomic coordinates, gene symbols, or Entrez IDs. We also provide an integrated genome browser for users to easily access mosaic variants and their related annotations for any genomic region. By analyzing the variants collected in MosaicBase, we find that mosaic variants that directlycontribute to disease phenotype show features distinct from those of variants in individuals with mild or no phenotypes, in terms of their genomic distribution, mutation signatures, and fraction of mutant cells. MosaicBase will not only assist clinicians in genetic counseling and diagnosis but also provide a useful resource to understand the genomic baseline of postzygotic mutations in the general human population. MosaicBase is publicly available at http://mosaicbase.com/ or http://49.4.21.8:8000.

The mammalian central nervous system (CNS) is considered an immune privileged system as it is separated from the periphery by the blood brain barrier (BBB). Yet, immune functions have been postulated to heavily influence the functional state of the CNS, especially after injury or during neurodegeneration. There is controversy regarding whether adaptive immune responses are beneficial or detrimental to CNS injury repair. In this study, we utilized immunocompromised SCID mice and subjected them to spinal cord injury (SCI). We analyzed motor function, electrophysiology, histochemistry, and performed unbiased RNA-sequencing. SCID mice displayed improved CNS functional recovery compared to WT mice after SCI. Weighted gene-coexpression network analysis (WGCNA) of spinal cord transcriptomes revealed that SCID mice had reduced expression of immune function-related genes and heightened expression of neural transmission-related genes after SCI, which was confirmed by immunohistochemical analysis and was consistent with better functional recovery. Transcriptomic analyses also indicated heightened expression of neurotransmission-related genes before injury in SCID mice, suggesting that a steady state of immune-deficiency potentially led to CNS hyper-connectivity. Consequently, SCID mice without injury demonstrated worse performance in Morris water maze test. Taken together, not only reduced inflammation after injury but also dampened steady-state immune function without injury heightened the neurotransmission program, resulting in better or worse behavioral outcomes respectively. This study revealed the intricate relationship between immune and nervous systems, raising the possibility for therapeutic manipulation of neural function via immune modulation.

To build a CT-based radiomics predictive mode to evaluate the differentiation degree of the esophageal squamous carcinoma.
 Methods: A total of 160 patients with surgical pathology, complete clinical data and chest CT scanning before operation were retrospectively collected from January 2008 to August 2016. All patients were assigned randomly to a primary data set and an independent validation. Texture analysis was performed on CT images, while the carcinomas were performed by manual segmentation to extract the radiomics features. Radiomics features were extracted and 9 radiomics signatures were finally selected after dimension reduction. Radiomics features were extracted and established via Matlab. Multivariable logistic regression analysis was performed to build the predictive model. A 10-fold cross-validation was used for selecting parameters in the least absolute shrinkage and selection operator (LASSO) model by minimum criteria. The receiver operating characteristic (ROC) curves and areas under ROC curve (AUC) were used to compare the model performance in the primary validation and the independent validation for evaluating the differentiation degree of esophageal squamous carcinoma.
 Results: Radiomics signature showed great effect in discriminating primary data set and independent validation. The predictive model had a good performance in primary data set. The AUC was 0.791, the sensitivity was 81.6%, and specificity was 72.3%. In the independent validation, the AUC was 0.757, the sensitivity was 70.0%, and the specificity was 73.0%.
 Conclusion: The predictive model can be used for evaluating the differentiation degree of esophageal squamous carcinoma efficiently, which can be helpful to clinicians in diagnosis and choice of treatment for esophageal squamous carcinoma.
Carcinoma, Squamous Cell ; Esophageal Neoplasms ; Humans ; ROC Curve ; Retrospective Studies ; Tomography, X-Ray Computed

Background:Diagnosis of liver cirrhosis in early stage with early intervention may stabilize disease progression, avoiding or delaying the occurrence of decompensation. Seeking non-invasive serum biomarkers is becoming an important topic in the diagnosis and assessment of liver cirrhosis. Aims:To study the value of serum miR-192 and miR-29a as non-invasive biomarkers for the diagnosis of liver cirrhosis. Methods:Differentially expressed serum miRNAs between patients with liver cirrhosis and healthy controls were screened through online literature retrieval and then confirmed by real-time PCR. Serum levels of two confirmed miRNAs,miR-192 and miR-29a were analyzed in 120 patients with liver cirrhosis and 76 healthy volunteers by real-time PCR. A mathematical model of combined detection of miR-192 and miR-29a for diagnosis of liver cirrhosis was established by binary logistic regression. The diagnostic performance of various non-invasive serum indicators was evaluated by ROC curve analysis. Results:Compared with healthy controls,expression level of serum miR-192 in cirrhotic patients was significantly increased and that of serum miR-29a was significantly reduced(P ﹤ 0. 001). The diagnostic performance of risk score obtained from mathematical model of combined detection of serum miR-192 and miR-29a was superior to that of single miRNA detection or other non-invasive serum indicators,such as APRI,FIB-4 and ARR,the areas under ROC curve of the above mentioned indicators were 0. 968,0. 887,0. 933,0. 796,0. 793,and 0. 571,respectively. Serum levels of miR-192,miR-29a and the risk score of their combined detection were significantly correlated with the stage of liver cirrhosis according to the Child-Pugh classification( P ﹤ 0. 05). Conclusions:Serum miR-192,miR-29a and the risk score of their combined detection might be novel non-invasive biomarkers for the diagnosis and assessment of liver cirrhosis.

Objective To investigate the effect of tube voltage and iodine concentration of contrast medium (CM) on abdominal dynamic enhanced CT image quality.Methods Six miniature pigs underwent repeated upper abdomen dynamic contrast-enhanced CT scans in 4 scanning protocols with different concentration of CM and tube voltage,namely,protocol 1,CM with iodine concentration of 270 milligrams iodine per milliliter (mg/ml) and 80 kV tube voltage;protocol 2,270 mg/ml and 120 kV;protocol 3,370 mg/ml and 80 kV and protocol 4,370 mg/ml and 120 kV.The same iodine dose (600 mg/ml) and iodine delivery rate (IDR) (920 mg/s) were used in all protocols.The CM with iodine concentration of 270 mg/ml were injected at a flow rate of 3.4 ml/s,and 370 mg/ml CM injected at 2.5 ml/s.Image reconstruction was performed with iterative reconstruction (iDose4) in protocol 1 and 3,filtered back projection (FBP) was used in protocol 2 and 4.A subjective scoring system for image quality,image noise and sharpness was conducted by 2 radiologists independently.The measured values (peak of enhanced CT values,image noise of aorta,inferior vena cava,portal vein,hepatic vein and liver parenchyma) as well as the calculated values [their time-to-peak,signal-to-noise (SNR) and contrast-to-noise (CNR) ratios] were compared between among 4 protocols.The CT volume dose index (CDTIvol) and dose length product (DLP) were recorded from the CT console after each scanning.Factorial designed ANOVA was used for comparison of enhanced CT values of vessels and liver parenchyma,noise,SNR and CNR.The Kruskal-Wallis test was used for comparison of values among the 4 protocols,including the time-to-peak enhancement of vessels and liver parenchyma,the subjective scores of image quality indices.Result There was no significant differences in subjective scores of the image quality,image noise and image sharpness (P＞0.05).The scored were more than 3,and the images with 4 scanning protocols were all acceptable for diagnosis.There was no significant differences between protocol 1 and 3,protocol 2 and 4 in the peak enhancement CT values of aorta [(729±46) HU vs.(707±59)HU,(515±84)HU vs.(513±53)HU],inferior vena cava [(366±95)HU vs.(368±92)HU,(282±39)HU vs.(262 ± 67)HU],portal vein [(213± 18)HU vs.(201 ±29)HU,(180±21)HU vs.(176±27)HU],hepatic vein [(207±18)HU vs.(193±10)HU,(179±24)HU vs.(170±14)HU] and liver parenchyma [(128±7) HU vs.(127±4) HU,(135±5)HU vs.(135±6)HU] (P＞0.05).But the CT values of vessels (aorta,inferior vena cava,portal vein and hepatic vein) in protocol 1 and 3 were significantly higher than those in protocol 2 and 4 (P＜0.05),the CT values of liver parenchyma in protocol 1 and 3 were significantly lower than values in protocol 2 and 4 (P＜0.05).The image noises of vessels were higher in protocol 1 and 3 than noises in other protocols (P＜0.05),but there was no significant difference in liver parenchyma noise among protocols (P＞0.05).No significant differences were observed on the peak times,SNR and CNR in aorta,inferior vena cava,portal vein,hepatic vein and liver parenchyma among 4 protocols (P＞0.05).The CDTIvol and DLP were 199.67 mGy,1 597.4 mGy· cm respectively in protocol 1 and 3,585.12 mGy and 4 680.9 mGy· cm in protocol 2 and 4 (scanning with 120 kV).Conclusions CM with different iodinated concentration could achieve the same enhancement in the abdominal vessels and liver parenchyma by using the proper scan protocols,which have the same IDR and iodine dose per kilogram body weight.Higher vessel enhanced peak values were achieved when using the protocols with 80 kV tube voltage than 120 kV.By using a low dose protocol of 80 kV tube voltage with the iterative reconstruction algorithm,the quality of image can be warranted.