In order to observe the effect of the immune and weight of chickens after use the attenuated vaccine with low dose of chicken infectious anemia virus (CIAV). In this study, the effects of low dose of CIAV on the weight of SPF chickens and NDV antibody production were observed by simulated experiments. The results showed that 10 EID50 and 5 EID50 CIAV per plume attenuated NDV vaccines were used to cause the weight loss of SPF chickens. Compared with the use of the non contaminated vaccine group, it has significant difference. And NDV antibody levels compared with the use of the non contaminated groups also decreased after use the vaccine with two doses of CIAV contaminated. It has significant difference. A certain proportion of CIAV antibody positive was detected at the beginning of the second week after use the NDV vaccine with two doses of CIAV contaminated. The detection of a high proportion of CIAV nucleic acid was detected in the first week after the use of a contaminated vaccine. The results of the study demonstrate the effects of CIAV pollution on the production and immune function of SPF chickens, and it is suggested that increasing the detection of viral nucleic acid can help save time and improve the detection rate in the detection of exogenous virus contamination by SPF chicken test method.
Animals ; Antibodies, Viral ; immunology ; Chicken anemia virus ; genetics ; immunology ; physiology ; Chickens ; Circoviridae Infections ; immunology ; veterinary ; virology ; Poultry Diseases ; immunology ; virology ; Specific Pathogen-Free Organisms ; Vaccines, Attenuated ; administration & dosage ; genetics ; immunology

Objective:To analyze the clinical characteristics of patients with de-novo non-alcoholic fatty liver disease (de-novo NAFLD) and patients with de-novo NAFLD combined with metabolic syndrome (MS) after liver transplantation (LT) , and to determine the related risk factors.Methods:Patients who underwent LT at the Organ Transplantation Center, the Affiliated Hospital of Qingdao University, from Jan. 2016 to Oc. 2020 and were monitored until Oct. 2021 were gathered. The recipients were divided into the group with/without de-novo NAFLD, and LT recipients with de-novo NAFLD were divided into the group with/without combined MS. Clinical characteristics of the LT recipients with de-novo NAFLD combined with MS were analyzed. Logistic regression analyses were performed to identify the risk factors for LT recipients with de-novo NAFLD and those with combined MS.Results:A total of 324 LT recipients with a median follow-up of 2.9 years (range: 2.0-4.3 years) were included in the study. De-novo NAFLD was diagnosed in 21.0% (68/324) of the LT recipients, and MS was diagnosed in 44.1% (30/68) of these patients. Compared with LT recipients without de-novo NAFLD, those with de-novo NAFLD had higher preoperative body mass index (BMI) , blood glucose, glycated hemoglobin levels and lower platelet levels, and longer postoperative follow-up, higher BMI, waist circumference, albumin, triglycerides (TG) , low-density lipoprotein (LDL) , blood glucose, glycated hemoglobin levels, and the incidence of MS (all P<0.05) . Preoperative platelets, glucose, postoperative albumin, LDL and BMI were independent risk factors for predicting de-novo NAFLD after LT (all P<0.05) . Preoperative glucose performed well in predicting the occurrence of de-novo NAFLD (threshold: 5.5mmol/L, P<0.001, AUC=0.678) . The differences in Pre-LT blood glucose, post-LT BMI, waist circumference, prevalence of prediabetes or diabetes, fatty liver index (FLI) , and NAFLD fibrosis score (NFS) between de-novo NAFLD LT recipients with and without combined MS were significantly different (all P<0.05) . Conclusions:The incidence of de-novo NAFLD after LT is noteworthy, and LT recipients with de-novo NAFLD are more likely to have a combination with MS. In preoperative treatment, keeping blood glucose to 5.5 mmol/L or below trends helps to lower the risk of de-novo NAFLD following LT. LT recipients’ nutritional state and lipid levels require prompt care. High albumin levels might not be a desirable thing. De-novo NAFLD LT recipients with concomitant prediabetes or diabetes may imply an increased risk of developing comorbid MS during the post-LT follow-up. Controlling FLI levels in LT recipients with de-novo NAFLD may reduce the risk of developing comorbid MS.

Objective To investigate the correlation between the expression of Hsa_circ_0026352 and the clinical characteristics of breast cancer(BC) patients, to evaluate the value of Hsa_circ_0026352 as a diagnostic marker of breast cancer. Methods Human circRNA microarray was used to screen the different expression of circRNAs in BC tissues. qRT-PCR was used to verify the expression of Hsa_circ_0026352 in BC tissue and peripheral blood. CircRNA structure were performed by circPrimer1.2 software. T-test, ANOVA analysis, curve regression analysis and ROC curve analysis were performed to determine the diagnostic values of Hsa_circ_0026352. Results Hsa_circ_0026352 was significantly down-regulated in both breast cancer tissues and peripheral blood (P < 0.01). The AUC of Hsa_circ_0026352 were 0.881 in tissues and 0.826 in peripheral blood (both P < 0.01). The relative expression of Hsa_circ_0026352 in peripheral blood of BC cancer patients was negatively correlated with CA153 level (P < 0.05). The AUC of Hsa_circ_0026352 in peripheral blood of patients with ER positive, early stage breast cancer and breast neoplasm metastasis were 0.710, 0.771 and 0.722 (all P < 0.01), respectively. Conclusion Hsa_circ_0026352 could be a novel predictive biomarker for diagnosis of BC.

Objective:To develop and validate the models based on mixed enhanced computed tomography (CT) radiomics and deep learning features, and evaluate the efficacy for differentiating pancreatic adenosquamous carcinoma (PASC) from pancreatic ductal adenocarcinoma (PDAC) before surgery.Methods:The clinical data of 201 patients with surgically resected and histopathologically confirmed PASC (PASC group) and 332 patients with surgically resected histopathologically confirmed PDAC (PDAC group) who underwent enhanced CT within 1 month before surgery in the First Affiliated Hospital of Naval Medical University from January 2011 to December 2020 were retrospectively collected. The patients were chronologically divided into a training set (treated between January 2011 and January 2018, 156 patients with PASC and 241 patients with PDAC) and a validation set (treated between February 2018 and December 2020, 45 patients with PASC and 91 patients with PDAC) according to the international consensus on the predictive model. The nnU-Net model was used for pancreatic tumor automatic segmentation, the clinical and CT images were evaluated, and radiomics features and deep learning features during portal vein phase were extracted; then the features were dimensionally reduced and screened. Binary logistic analysis was performed to develop the clinical, radiomics and deep learning models in the training set. The models' performances were determined by area under the ROC curve (AUC), sensitivity, specificity, accuracy, and decision curve analysis (DCA).Results:Significant differences were observed in tumor size, ring-enhancement, upstream pancreatic parenchymal atrophy and cystic degeneration of tumor both in PASC and PDAC group in the training and validation set (all P value <0.05). The multivariable logistic regression analysis showed the tumor size, ring-enhancement, dilation of the common bile duct and upstream pancreatic parenchymal atrophy were associated with PASC significantly in the clinical model. The ring-enhancement, dilation of the common bile duct, upstream pancreatic parenchymal atrophy and radiomics score were associated with PASC significantly in the radiomics model. The ring-enhancement, upstream pancreatic parenchymal atrophy and deep learning score were associated with PASC significantly in the deep learning model. The diagnostic efficacy of the deep learning model was highest, and the AUC, sensitivity, specificity, and accuracy of the deep learning model was 0.86 (95% CI 0.82-0.90), 75.00%, 84.23%, and 80.60% and those of clinical and radiomics models were 0.81 (95% CI 0.76-0.85), 62.18%, 85.89%, 76.57% and 0.84 (95% CI 0.80-0.88), 73.08%, 82.16%, 78.59% in the training set. In the validation set, the area AUC, sensitivity, specificity, and accuracy of deep learning model were 0.78 (95% CI 0.67-0.84), 68.89%, 78.02% and 75.00%, those of clinical and radiomics were 0.72 (95% CI 0.63-0.81), 77.78%, 59.34%, 65.44% and 0.75 (95% CI 0.66-0.84), 86.67%, 56.04%, 66.18%. The DCA in the training and validation sets showed that if the threshold probabilities were >0.05 and >0.1, respectively, using the deep learning model to distinguish PASC from PDAC was more beneficial for the patients than the treat-all-patients as having PDAC scheme or the treat-all-patients as having PASC scheme. Conclusions:The deep learning model based on CT automatic image segmentation of pancreatic neoplasm could effectively differentiate PASC from PDAC, and provide a new non-invasive method for confirming PASC before surgery.

OBJECTIVE：To provid e reference for pharmaceutical workers to better understand Novel Coronavirus Infection ： Expert Consensus on Guidance and Prevention Strategies for Hospital Pharmacists and the Pharmacy Workforce （hereinafter referred to as “expert consensus ”），and to apply and practice in specific work ，so as to give full play to the role of pharmacists to help fight the epidemic.METHODS ：The background of the formulation and revision of the expert consensus were introduced ，and its main contents and viewpoints were interpreted. RESULTS & CONCLUSIONS ：The text of expert consensus is divided into 8 parts，mainly including disease diagnosis and treatment [SARS-CoV- 2 infection related background ，clinical manifestations and diagnosis， treatment]，hospital pharmacy （prevention and control strategy ，work guidance ），drug and facility support management（key drug/facility/equipment support ，management and use of the drug in special circumstances ），information sources and related resources ，etc.，which comprehensively and detailedly provide information ，guidance and strategies for coronavirus SARS-CoV-2 infection prevention and control to play the role of pharmacists in hospital pharmacy well ，do well in the protection of staff in different pharmaceutical posts ，drug security work in response to epidemic situation ，and develop pharmaceutical care. So far，the understanding of SARS-CoV- 2 in the pharmaceutical industry is relatively limited. Based on the accumulated experience and progress in epidemic prevention and control ，the expert consensus will be updated and improved continuously ，so as to provide guidance and help for hospital pharmaceutical personnel.