ObjectiveThis study aimed to investigate the current status of biosafety management in laboratory animal institutions in Hunan Province, identify management shortcomings, and provide targeted recommendations for improvement. MethodsA questionnaire survey was conducted in July 2023 among 40 laboratory animal institutions in Hunan Province, covering topics such as the establishment of laboratory management system and its overall operation status, emergency management for incidents, medical waste disposal, animal transportation, personnel practitioner management, environmental disinfection, and equipment maintenance. The awareness of biosafety, animal bite incidents, and vaccination history was surveyed from at least one animal feeder or experimental operation practitioner from each institution, totaling 50 practitioners. Through literature review and comparative analysis, this paper analyzed the current status of biosafety management in production, transportation, and use of laboratory animals in Hunan Province from aspects such as biosafety management systems, personnel training, disinfection of environmental facilities and waste disposal, and provided recommendations. ResultsAmong the 40 laboratory animal institutions in Hunan Province,39 institutions (97.5%) had established laboratory management systems, 37 (92.5%) had emergency response plans for incidents of to transport laboratory animals, 15 (37.5%) had complete records of emergency drills for laboratory animal biosafety, and 39 (97.5%) had established protocols for carcass and waste management. Moreover, 26 institutions (65.0%) had laboratory biosafety risk assessment reports. 4 out of 8 (50.0%) production units had emergency plans for animal transportation, with 7 (87.5%) using special vehicles to transport laboratory animals. 2 (4.0%) of the 50 practitioners were unaware of emergency response plans, 6 participants (12.0%) did not consistently wear personal protective equipment, and 38 participants (76.0%) had been bitten or scratched by laboratory animals. The results of the survey showed that emergency management, transportation management and personnel management of laboratory animal incidents still need improvement in Hunan Province. Relevant functional departments should strengthen supervision and management efforts, establish local regulations for the transportation management of laboratory animals, ensure strict compliance with relevant documents, conduct emergency drills in all units, and strengthen training for practitioners. ConclusionWhile daily management practices in the 40 laboratory animal institutions in Hunan Province are generally satisfactory, there remains a need for further improvement in emergency management, transportation management, personnel management, etc. Gradually enhancing the level of laboratory animal safety management is essential to collectively safeguard public health safety.

The emergency management of biosafety for laboratory animals in Hunan Province is an essential component of the province's implementation of the national biosafety strategy.To strengthen the prevention and control of biosafety risks in laboratory animals and to ensure a quick and effective response to laboratory animal biosafety emergencies,Hunan Province has formulated the"Emergency Response Plan for Laboratory Animal Biosafety Emergencies in Hunan Province".This plan aims to minimize damages caused to practitioners,public health,and laboratory animal industry,protect lives and property,and safeguard public safety and social stability.This paper analyzes the necessity,guiding ideology,principles,and basis for formulating the plan.It details the main contents of the plan,which includes scope of application,incident classification,organizational structure and responsibilities,monitoring and early warning mechanisms,emergency reporting and response,post-incident assessment,and safeguard measures.Moreover,this paper provides a summary and outlook on the emergency management of biosafety laboratory animals in Hunan Province in recent years.

Due to the low contrast of CT images,irregular shape of the liver,and blurred boundaries with adjacent organs,the existing methods based on convolutional neural network underperform in liver segmentation tasks,especially for boundary recognition and small object detection.A novel liver segmentation method is proposed based on multi-scale feature fusion and attention,namely MFFA UNet.Multi-scale feature fusion is firstly employed to acquire abundant segmentation details,while spatial and channel attention mechanisms are utilized to capture global spatial and inter-channel relationships.Additionally,a deep supervision module fully leverages the output of intermediate hidden layers,enhancing the learning capability of the network,which in turn accelerates the network's convergence speed.Moreover,a hybrid loss function is adopted to address the issue of class imbalance,further boosting the model's segmentation efficacy.Experimental results demonstrate that the proposed MFFA UNet outperforms the prevailing segmentation networks on the public LITS dataset,producing results that are closer to the ground truth.

Primary central nervous system lymphoma (PCNSL) is a rare and aggressive non-Hodgkin’s lymphoma that affects the brain, eyes, cerebrospinal fluid, or spinal cord without systemic involvement. The outcome of patients with PCNSL is worse compared to patients with systemic diffuse large B-cell lymphoma. Given potential mortality associated with severe immune effector cell-associated neurotoxicity syndrome (ICANS), patients with PCNSL have been excluded from most clinical trials involving chimeric antigen receptor T-cell (CAR-T) therapy initially. Here, we report for the first time to apply decitabine-primed tandem CD19/CD22 dual-targeted CAR-T therapy with programmed cell death-1 (PD-1) and Bruton’s tyrosine kinase (BTK) inhibitors maintenance in one patient with multiline-resistant refractory PCNSL and the patient has maintained complete remission (CR) for a 35-month follow-up period. This case represents the first successful treatment of multiline resistant refractory PCNSL with long-term CR and without inducing ICANS under tandem CD19/CD22 bispecific CAR-T therapy followed by maintenance therapy with PD-1 and BTK inhibitors. This study shows tremendous potential in the treatment of PCNSL and offers a look toward ongoing clinical studies.

Objective:To explore the predictive value of ultrasound-based radiomics for liver metastasis in pancreatic neuroendocrine tumors (pNEN).Methods:A retrospective analysis was conducted on clinical, pathological, and ultrasound data of 269 pNEN patients confirmed by pathology at Tianjin Medical University Cancer Institute and Hospital from January 2012 to June 2022, including 94 patients with liver metastasis and 175 without liver metastasis. The regions of interest (ROI) were delineated on the maximum diameter section of the tumor using ITKSNAP software, and radiomics features were extracted using Pyradiomics. Radiomics features with an intra-group correlation coefficient greater than 0.90 were retained, and the optimal features were selected using the maximum relevance minimum redundancy (MRMR) algorithm. The dataset was randomly divided into a training set and a validation set in a ratio of 7∶3, and the random forest algorithm (Rfs) was used to predict pNEN liver metastasis. Three models were constructed, including the clinical ultrasound model, the radiomics model, and the comprehensive model that combined clinical ultrasound and radiomics features. The predictive performance of different models for pNEN liver metastasis was analyzed using the ROC curve, and the predictive performance of different models was compared using the Delong test.Results:A total of 874 features were extracted from the ROI, and 12 highly robust radiomics features were retained for model construction based on inter- and intra-observer correlation grading and feature selection. The area under curve(AUC), sensitivity, specificity, and accuracy of the radiomics model, the clinical ultrasound model, and the comprehensive model for predicting liver metastasis in pNEN patients were 0.800, 0.574, 0.789, 0.714; 0.780, 0.596, 0.874, 0.777; and 0.890, 0.694, 0.874, 0.810, respectively. The Delong test showed that the comprehensive model had the best predictive performance, with an AUC superior to that of radiomics model ( Z=3.845, P=0.000 12) and clinical ultrasound model ( Z=3.506, P=0.000 45). Conclusions:The radiomics model based on ultrasound has good performance in predicting liver metastasis in pNEN, and the comprehensive model that combines clinical ultrasound and radiomics features can further improve the predictive performance of the model.

Objective:To predict the clinical value of World Health Organization/International Society of Urological Pathology (WHO/ISUP) grading of clear cell renal cell carcinoma (ccRCC) pre-scholarly based on ultrasound imaging group.Methods:Clinical and ultrasound imaging data of patients with surgically pathologically confirmed ccRCC at Tianjin Medical University Cancer Institue and Hospital from January 2021 to October 2022 were retrospectively collected and divided into a low grade group (grade Ⅰ and Ⅱ, 105 cases) and a high grade group (grade Ⅲ and Ⅳ, 70 cases) using WHO/ISUP pathological grading criteria. The clear image of the largest diameter of the tumor was selected and imported into ITK-SNAP software for manual segmentation of the image and extraction of ultrasonographic radiomics features. The patients were randomly divided into a training group and a test group in the ratio of 7∶3, with 122 cases in the training group and 53 cases in the test group. Stable radiomics features were obtained by dimensionality reduction. The support vector machines (SVM) algorithm was applied to predict the pathological grading of ccRCC. Finally, a clinical-ultrasound imaging model, an ultrasonographic radiomics model and a comprehensive model combining the two were constructed. The predictive effects of the three models were analyzed by the area under the ROC curve (AUC). The performance of each model was evaluated by applying the calibration curve. The net benefit of patients was obtained by applying the decision curve.Results:A total of 873 radiomics features were extracted, and 10 features were finally obtained for model construction after dimensionality reduction. Final test results showed that the AUC, sensitivity, specificity and accuracy of the clinical-ultrasound imaging model were 0.68, 0.47, 0.78, 0.66. The AUC, sensitivity, specificity and accuracy of the ultrasonographic radiomics model were 0.74, 0.53, 0.88, 0.74. The AUC, sensitivity, specificity and accuracy of the comprehensive model were 0.84, 0.63, 0.86, 0.77. The AUC of the comprehensive model being larger than that of the clinical-ultrasound imaging model ( Z=-3.224, P=0.001) and ultrasonographic radiomics model ( Z=-2.594, P=0.009). The calibration curves showed that the comprehensive model was more stable than the other two models. The decision curve showed a higher net clinical benefit for the comprehensive model than for the other two models within a threshold of 0.1-1.0. Conclusions:The preoperative prediction of ccRCC pathological grading by the radiomics model based on ultrasound images is effective. The comprehensive model constructed by combining relevant clinical and ultrasound parameters has better performance, which can help predict ccRCC pathological grading preoperatively to a certain extent. It is crucial to help physicians choose the best management plan in the era of personalized medicine.

Objective:To investigate the prediction of National Institute of Healthy (NIH) risk stratification of gastrointestinal stromal tumor(GIST) based on clinical ultrasound model, ultrasonographic radiomics model and combined model by oral contrast enhanced ultrasonography.Methods:The clinical and ultrasound imaging data of 204 gastric GIST patients attending Tianjin Medical University Cancer Institute and Hospital from June 2021 to June 2022 were retrospectively analyzed, among whom a total of 101 patients with high and moderate NIH risk stratification GIST confirmed by postoperative pathology were included in the high risk group, and a total of 103 patients with low and extremely low NIH risk stratification GIST were in the low risk group. The ultrasound images of the largest diameter of the GIST were manually segmented by ITK-SNAP software, and Pyradiomics (v3.0.1) module in Python 3.8.7 was applied to extract ultrasonographic radiomics features from the ROI segmented images. The patients were randomly divided into training and validation sets in the ratio of 7∶3. The XGBoost of Sklearn module was applied to construct the clinical ultrasound imaging model, ultrasonographic radiomics model, and combined model. Then the area under ROC curve (AUC), sensitivity, specificity, and accuracy were evaluated; the predictive ability of the three models was compared by Delong test. Calibration Curve was applied to evaluate the model performance, and the clinical Decision Curve Analysis was applied to determine the net benefit to patients.Results:A total of 578 ultrasonographic radiomics features were extracted from ROI, and 8 ultrasonographic radiomics features were finally retained for modeling after regression and dimensionality reduction. Finally, test results showed that AUC, sensitivity, specificity and accuracy of clinical ultrasound imaging model, ultrasonographic radiomics model and combined model were 0.75, 69.3%, 68.9%, 69.1%; 0.87, 79.2%, 81.6%, 80.4%; 0.91, 80.2%, 83.5%, 81.9%, respectively. Delong test showed that the difference of AUC between ultrasonographic radiomics model and clinical ultrasound imaging model was statistically significant ( Z=2.698, P<0.001), and the combined model was significantly better than clinical ultrasound imaging model ( Z=4.062, P<0.001) and ultrasonographic radiomics model ( Z=2.225, P=0.026). Calibration Curve showed the high performance of combined model, and Decision Curve Analysis showed the superior clinical usefulness of combined model. Conclusions:It is feasible to construct an ultrasonographic radiomics model for GIST NIH risk stratification based on oral contrast enhanced ultrasonography images, and the combined model has more advantageous diagnostic performance, which can identify high risk NIH GIST objectively and stably for clinical purposes.

Objective: To investigate the effect of chrysotile exposure on ribosomal DNA (rDNA) copy number and DNA damage response, so as to provide insights into the mechanism of asbestos-induced carcinogenesis. Methods: Human pleural mesothelial MeT-5A cells were treated with chrysotile suspensions at doses of 1.25, 2.5 and 5 μg/cm2 (low-, medium-, high-dose group), while PBS served as controls. MeT-5A cells were harvested 6, 24, 48 and 72 h post-treatment, and the rDNA copy numbers and the BIRC5, HRAS, GINS4 and RRM2 mRNA expression were determined using a quantitative real-time PCR (qPCR) assay. The apoptosis of MeT-5A cells and DNA damage were detected using Muse cell analyzer. The rDNA copy numbers, DNA damage responses and BIRC5, HRAS, GINS4 and RRM2 mRNA expression were compared in MeT-5A cells treated with different doses of chrysotile suspensions. Results: There were significant differences in 45S rDNA copy numbers among low-, medium-, high-dose groups and the control groups 6, 48 and 72 h post-treatment with chrysotile suspensions, and significantly lower 45S rDNA copy numbers were measured in low-, medium- and high-dose groups than in the control group 6 h post-treatment, while significantly higher 45S rDNA copy numbers were found in the high-dose group than in low- and medium-dose groups 48 and 72 h post-treatment (all P<0.05). There were significant differences in 5S rDNA copy numbers among low-, medium-, high-dose groups and the control groups 24, 48 and 72 h post-treatment with chrysotile suspensions, and significantly lower 5S rDNA copy numbers were measured in medium- and high-dose groups than in the control group 24 and 48 h post-treatment, while significantly lower 5S rDNA copy numbers were found in medium- and high-dose groups than in the low-dose group 24, 72 h post-treatment (all P<0.05). There were significant differences in the overall apoptotic rate of MeT-5A cells among groups at different time points, and the overall apoptotic rate of MeT-5A cells were significantly higher in medium- and high-dose groups than in the control group (all P<0.05), with late-stage apoptosis predominantly detected. There were significant differences in the rates of ATM activation and DNA double-strand break in MeT-5A cells among groups 72 h post-treatment, and higher rates of ATM activation and DNA double-strand break were measured in medium- and high-dose groups than in the control group (all P<0.05). In addition, there were significant differences in the relative mRNA expression of BIRC5, HRAS, GINS4 and RRM2 genes among groups 24 and 48 h post-treatment, and significantly lower BIRC5, HRAS, GINS4 and RRM2 mRNA expression was quantified in medium- and high-dose groups than in the control group (all P<0.05). Conclusion Exposure to chrysotile may induce rDNA copy number variations and altered expression of nucleolar proteins in human pleural mesothelial cells, which may be involved in the regulation of DNA damage responses.

Objective:This study aims to explore the clinical characteristics of T-cell large granular lymphocyte leukemia (T-LGLL) patients with STAT3 mutation status and provide a reference for clinical management of such patients.Methods:The clinical data of T-LGLL patients between 2009 and 2019 in Jiangsu Province Hospital were retrospectively analyzed. Differences in baseline clinical data, treatment responses, and survival outcomes in patients with STAT3 mutations or with no mutations were compared.Results:A total of 80 patients were included, including 66 patients without STAT3 mutation and 14 patients (17.5%) with STAT3 mutation. The frequency of Y640F mutation was the highest (42.9%) . Compared with non STAT3 mutation group, STAT3 mutation group had lower HGB (67.5 g/L vs 82.5 g/L, P=0.018) , lower neutrophil count (0.665×10 9/L vs 1.465×10 9/L, P<0.001) , higher LDH (229 U/L vs 198 U/L, P=0.041) , higher ferritin (402.5 g/L vs 236.0 g/L, P=0.029) , higher expression rate of TCR Vβ subfamily (89.2% vs 65.4%, P=0.014) and higher proportion of patients with treatment indications (100% vs 74%, P=0.033) . The complete remission rates of STAT3 mutation group and non mutation group were 38.5% and 32.7%, respectively, with no significant difference ( P=0.748) . The overall response rate of first-line immunosuppressive therapy in STAT3 mutation group and non mutation group were 69.2% and 69.4%, respectively, with no significant difference ( P=1.000) . The median follow-up time was 63 (2-121) months. There was no significant difference in the overall survival time between the two groups ( P=0.170) . Conclusions:T-LGLL patients with STAT3 mutations seems to be correlated with an increased tumor burden and high treatment demand, and had a good response to first-line immunotherapies. The prognostic significance of STAT3 mutation in T-LGLL patients requires further validation.

Objectives To determine the contents of heavy metals lead, cadmium, mercury, arsenic, and chromium in water and sediment samples from Luoyang River in Quanzhou City, Fujian Province, and to understand the temporal and spatial distribution of heavy metal pollutants. Methods In 2018, 231 water and sediment samples were collected from 43 sampling points in 6 representative areas in Luoyang River during normal, rainy and dry seasons. The presence of heavy metals in the samples was then determined. Results Pb, Cd, Hg, As and Cr⁶⁺ were not detected in the water samples. Pb, Cd, Hg, As and Cr were detected in the sediments were 10.33,0.33,0.029,5.18 and 23.3 mg/kg , but the contents were low. Conclusion The water and sediments of Luoyang River in 2018 had good quality, both of which met Class I standards according to the environmental quality standards for surface water and for marine sediment quality, respectively.