Background and purpose:16α-[18F]lfuoroestradiol (18F-FES) is an in vivo speciifc imaging agent for estrogen receptor (ER). We investigated the concordance between tumor ER status as determined by FES-PET and in vitro immunohistochemical assays. Methods: 18F-FES was prepared by ourselves. Twenty-six patients were enrolled (17 primary and 9 metastatic/recurrent). Patients underwent both 18F-FES and 18F-FDG PET/CT. Results:We found good overall agreement (96.15%) between in vitro ER assays and FES-PET. The ER status diagnosis sensitivity of 18F-FES was 93.33%and the speciifcity was 100%when using cut-off value of SUVmax≥1.5. There was a positive correlation between in vitro ER, PR assays and the SUVmax of 18F-FES while in vitro HER-2/neu assays correlatived negatively with 18F-FES SUVmax. Conclusion:These results suggested 18F-FES may be useful for studying the ER expression of all malignant lesions in patients with breast cancer and guiding individual therapy.

Arsenic is a widely occurring metalloid element in the natural environment and is one of the primary carcinogens identified by the World Health Organization (WHO), but the specific carcinogenic mechanism is currently unclear. In recent years, through toxicological studies on arsenic, it has been found that exposure to arsenic can affect cellular metabolism in the body, which may be closely related to the carcinogenic mechanism of arsenic. Therefore, the authors review the research progress on arsenic exposure-induced effects on glucose metabolism, lipid metabolism, and amino acid metabolism, with a view to providing a theoretical basis for the study of the mechanism of arsenic carcinogenesis.

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 study the hospital exemption clause of advanced therapy medicinal products in the EU， and to provide policy recommendations for improving the regulatory system of cell and gene therapy （CGT） products in China. METHODS Through literature review and investigation of the official websites of EU member states， this study compared the differences in the application and implementation of the hospital exemption clause among member states from the perspectives of “non-conventional” definition， manufacturing standards， and pharmacovigilance requirements； the potential issues of hospital exemption clauses in practice were analyzed to propose policy recommendations based on the regulatory status of CGT in China. RESULTS & CONCLUSIONS EU has provided patients with rare diseases， who lack effective treatment or better therapy plans， with the opportunity to obtain new treatments through the hospital exemption clause， which has effectively improved the accessibility of medicines for patients. However， there still are certain disparities in the provisions of hospital exemption clause among EU member states. For instance， some member states have not explicitly defined “unconventional” circumstances； each member state has different requirements regarding production quality standards and pharmacovigilance requirement. Additionally， in the practical implementation of hospital exemption clause， issues such as poor transparency of information and a lack of certain restrictive conditions persist. Therefore， considering the current landscape and regulation of China’s CGT， it is recommended that China explore the clinical translational application of low-risk CGT in “unconventional” situations， strengthen the management of clinical translational application in terms of production quality standards and pharmacovigilance requirement. At the same time， it is necessary to further standardize the investigator initiated trials， and pay attention to the balance between clinical application and drug registration and marketing， thereby guiding the sustained and healthy development of China’s CGT.

OBJECTIVE To study the hospital exemption clause of advanced therapy medicinal products in the EU， and to provide policy recommendations for improving the regulatory system of cell and gene therapy （CGT） products in China. METHODS Through literature review and investigation of the official websites of EU member states， this study compared the differences in the application and implementation of the hospital exemption clause among member states from the perspectives of “non-conventional” definition， manufacturing standards， and pharmacovigilance requirements； the potential issues of hospital exemption clauses in practice were analyzed to propose policy recommendations based on the regulatory status of CGT in China. RESULTS & CONCLUSIONS EU has provided patients with rare diseases， who lack effective treatment or better therapy plans， with the opportunity to obtain new treatments through the hospital exemption clause， which has effectively improved the accessibility of medicines for patients. However， there still are certain disparities in the provisions of hospital exemption clause among EU member states. For instance， some member states have not explicitly defined “unconventional” circumstances； each member state has different requirements regarding production quality standards and pharmacovigilance requirement. Additionally， in the practical implementation of hospital exemption clause， issues such as poor transparency of information and a lack of certain restrictive conditions persist. Therefore， considering the current landscape and regulation of China’s CGT， it is recommended that China explore the clinical translational application of low-risk CGT in “unconventional” situations， strengthen the management of clinical translational application in terms of production quality standards and pharmacovigilance requirement. At the same time， it is necessary to further standardize the investigator initiated trials， and pay attention to the balance between clinical application and drug registration and marketing， thereby guiding the sustained and healthy development of China’s CGT.

During coronavirus disease 2019 epidemic, the treatment of severe trauma has been impacted. The Consensus on emergency surgery and infection prevention and control for severe trauma patients with 2019 novel corona virus pneumonia was published online on February 12, 2020, providing a strong guidance for the emergency treatment of severe trauma and the self-protection of medical staffs in the early stage of the epidemic. With the Joint Prevention and Control Mechanism of the State Council renaming "novel coronavirus pneumonia" to "novel coronavirus infection" and the infection being managed with measures against class B infectious diseases since January 8, 2023, the consensus published in 2020 is no longer applicable to the emergency treatment of severe trauma in the new stage of epidemic prevention and control. In this context, led by the Chinese Traumatology Association, Chinese Trauma Surgeon Association, Trauma Medicine Branch of Chinese International Exchange and Promotive Association for Medical and Health Care, and Editorial Board of Chinese Journal of Traumatology, the Chinese expert consensus on emergency surgery for severe trauma and infection prevention during coronavirus disease 2019 epidemic ( version 2023) is formulated to ensure the effectiveness and safety in the treatment of severe trauma in the new stage. Based on the policy of the Joint Prevention and Control Mechanism of the State Council and by using evidence-based medical evidence as well as Delphi expert consultation and voting, 16 recommendations are put forward from the four aspects of the related definitions, infection prevention, preoperative assessment and preparation, emergency operation and postoperative management, hoping to provide a reference for severe trauma care in the new stage of the epidemic prevention and control.