1.Cryopreservation of small-volume red blood cells: evaluation of blood group antigen reactivity and its application value
Yaling ZHAO ; Yanxia WANG ; Ziye WANG ; Siyu MA ; Wei SHAO ; Yuanyuan ZHANG ; Xin JIANG ; Jia GAN
Chinese Journal of Blood Transfusion 2025;38(3):352-357
[Objective] To establish a cryopreservation protocol for small-volume (≤1 mL) red blood cells (RBCs) and to evaluate the reactivity and stability of blood group antigens after cryopreservation, so as to explore its potential application in immunohematology reference laboratories. [Methods] Small-volume RBCs were cryopreserved for 120 days, followed by thawing and deglycerolization to restore the RBC components. The quality of the RBCs was assessed. Serum antibodies were serially diluted and reacted with RBCs before and after cryopreservation, and agglutination scores were recorded to quantitatively evaluate the reactivity and stability of blood group antigens such as Rh, Duffy, Lewis, Kidd, M, and H. Flow cytometry was used to analyze the percentage and mean fluorescence intensity of ABO antigen expression on RBCs before and after cryopreservation to assess the usability of cryopreserved RBCs in flow immunophenotyping and blood group subtype studies. [Results] The hemolysis rate of thawed and deglycerolized RBCs was (0.27±0.10)%, with a supernatant free hemoglobin level of (0.52±0.14) g/L, and the RBC recovery rate was (69.12±7.91)%. The direct antiglobulin test (DAT) was negative for all thawed RBCs. There was no difference in the reactivity of blood group antigens before and after cryopreservation, and no difference in the percentage and mean fluorescence intensity of A and B antigen expression on RBCs before and after cryopreservation. [Conclusion] The small-volume RBC cryopreservation protocol can be applied to immunohematology analysis in reference laboratories and is expected to be widely used in blood group identification, antibody screening, identification, and blood group-related research.
2.Synthetic MRI Combined With Clinicopathological Characteristics for Pretreatment Prediction of Chemoradiotherapy Response in Advanced Nasopharyngeal Carcinoma
Siyu CHEN ; Jiankun DAI ; Jing ZHAO ; Shuang HAN ; Xiaojun ZHANG ; Jun CHANG ; Donghui JIANG ; Heng ZHANG ; Peng WANG ; Shudong HU
Korean Journal of Radiology 2025;26(2):135-145
Objective:
To explore the feasibility of synthetic magnetic resonance imaging (syMRI) combined with clinicopathological characteristics for the pre-treatment prediction of chemoradiotherapy (CRT) response in advanced nasopharyngeal carcinoma (ANPC).
Materials and Methods:
Patients with ANPC treated with CRT between September 2020 and June 2022 were retrospectively enrolled and categorized into response group (RG, n = 95) and non RGs (NRG, n = 32) based on the Response Evaluation Criteria in Solid Tumors (RECIST) 1.1. The quantitative parameters from pre-treatment syMRI (longitudinal [T1] and transverse [T2] relaxation times and proton density [PD]), diffusion-weighted imaging (apparent diffusion coefficient [ADC]), and clinicopathological characteristics were compared between RG and NRG. Logistic regression analysis was applied to identify parameters independently associated with CRT response and to construct a multivariable model. The areas under the receiveroperating characteristic curve (AUC) for various diagnostic approaches were compared using the DeLong test.
Results:
The T1, T2, and PD values in the NRG were significantly lower than those in the RG (all P < 0.05), whereas no significant difference was observed in the ADC values between these two groups. Clinicopathological characteristics (Epstein–Barr virus [EBV]-DNA level, lymph node extranodal extension, clinical stage, and Ki-67 expression) exhibited significant differences between the two groups. Logistic regression analysis showed that T1, PD, EBV-DNA level, clinical stage, and Ki-67 expression had significant independent relationships with CRT response (all P < 0.05). The multivariable model incorporating these five variables yielded AUC, sensitivity, and specificity values of 0.974, 93.8% (30/32), and 91.6% (87/95), respectively.
Conclusion
SyMRI may be used for the pretreatment prediction of CRT response in ANPC. The multivariable model incorporating syMRI quantitative parameters and clinicopathological characteristics, which were independently associated with CRT response, may be a new tool for the pretreatment prediction of CRT response.
3.Synthetic MRI Combined With Clinicopathological Characteristics for Pretreatment Prediction of Chemoradiotherapy Response in Advanced Nasopharyngeal Carcinoma
Siyu CHEN ; Jiankun DAI ; Jing ZHAO ; Shuang HAN ; Xiaojun ZHANG ; Jun CHANG ; Donghui JIANG ; Heng ZHANG ; Peng WANG ; Shudong HU
Korean Journal of Radiology 2025;26(2):135-145
Objective:
To explore the feasibility of synthetic magnetic resonance imaging (syMRI) combined with clinicopathological characteristics for the pre-treatment prediction of chemoradiotherapy (CRT) response in advanced nasopharyngeal carcinoma (ANPC).
Materials and Methods:
Patients with ANPC treated with CRT between September 2020 and June 2022 were retrospectively enrolled and categorized into response group (RG, n = 95) and non RGs (NRG, n = 32) based on the Response Evaluation Criteria in Solid Tumors (RECIST) 1.1. The quantitative parameters from pre-treatment syMRI (longitudinal [T1] and transverse [T2] relaxation times and proton density [PD]), diffusion-weighted imaging (apparent diffusion coefficient [ADC]), and clinicopathological characteristics were compared between RG and NRG. Logistic regression analysis was applied to identify parameters independently associated with CRT response and to construct a multivariable model. The areas under the receiveroperating characteristic curve (AUC) for various diagnostic approaches were compared using the DeLong test.
Results:
The T1, T2, and PD values in the NRG were significantly lower than those in the RG (all P < 0.05), whereas no significant difference was observed in the ADC values between these two groups. Clinicopathological characteristics (Epstein–Barr virus [EBV]-DNA level, lymph node extranodal extension, clinical stage, and Ki-67 expression) exhibited significant differences between the two groups. Logistic regression analysis showed that T1, PD, EBV-DNA level, clinical stage, and Ki-67 expression had significant independent relationships with CRT response (all P < 0.05). The multivariable model incorporating these five variables yielded AUC, sensitivity, and specificity values of 0.974, 93.8% (30/32), and 91.6% (87/95), respectively.
Conclusion
SyMRI may be used for the pretreatment prediction of CRT response in ANPC. The multivariable model incorporating syMRI quantitative parameters and clinicopathological characteristics, which were independently associated with CRT response, may be a new tool for the pretreatment prediction of CRT response.
4.Synthetic MRI Combined With Clinicopathological Characteristics for Pretreatment Prediction of Chemoradiotherapy Response in Advanced Nasopharyngeal Carcinoma
Siyu CHEN ; Jiankun DAI ; Jing ZHAO ; Shuang HAN ; Xiaojun ZHANG ; Jun CHANG ; Donghui JIANG ; Heng ZHANG ; Peng WANG ; Shudong HU
Korean Journal of Radiology 2025;26(2):135-145
Objective:
To explore the feasibility of synthetic magnetic resonance imaging (syMRI) combined with clinicopathological characteristics for the pre-treatment prediction of chemoradiotherapy (CRT) response in advanced nasopharyngeal carcinoma (ANPC).
Materials and Methods:
Patients with ANPC treated with CRT between September 2020 and June 2022 were retrospectively enrolled and categorized into response group (RG, n = 95) and non RGs (NRG, n = 32) based on the Response Evaluation Criteria in Solid Tumors (RECIST) 1.1. The quantitative parameters from pre-treatment syMRI (longitudinal [T1] and transverse [T2] relaxation times and proton density [PD]), diffusion-weighted imaging (apparent diffusion coefficient [ADC]), and clinicopathological characteristics were compared between RG and NRG. Logistic regression analysis was applied to identify parameters independently associated with CRT response and to construct a multivariable model. The areas under the receiveroperating characteristic curve (AUC) for various diagnostic approaches were compared using the DeLong test.
Results:
The T1, T2, and PD values in the NRG were significantly lower than those in the RG (all P < 0.05), whereas no significant difference was observed in the ADC values between these two groups. Clinicopathological characteristics (Epstein–Barr virus [EBV]-DNA level, lymph node extranodal extension, clinical stage, and Ki-67 expression) exhibited significant differences between the two groups. Logistic regression analysis showed that T1, PD, EBV-DNA level, clinical stage, and Ki-67 expression had significant independent relationships with CRT response (all P < 0.05). The multivariable model incorporating these five variables yielded AUC, sensitivity, and specificity values of 0.974, 93.8% (30/32), and 91.6% (87/95), respectively.
Conclusion
SyMRI may be used for the pretreatment prediction of CRT response in ANPC. The multivariable model incorporating syMRI quantitative parameters and clinicopathological characteristics, which were independently associated with CRT response, may be a new tool for the pretreatment prediction of CRT response.
5.Synthetic MRI Combined With Clinicopathological Characteristics for Pretreatment Prediction of Chemoradiotherapy Response in Advanced Nasopharyngeal Carcinoma
Siyu CHEN ; Jiankun DAI ; Jing ZHAO ; Shuang HAN ; Xiaojun ZHANG ; Jun CHANG ; Donghui JIANG ; Heng ZHANG ; Peng WANG ; Shudong HU
Korean Journal of Radiology 2025;26(2):135-145
Objective:
To explore the feasibility of synthetic magnetic resonance imaging (syMRI) combined with clinicopathological characteristics for the pre-treatment prediction of chemoradiotherapy (CRT) response in advanced nasopharyngeal carcinoma (ANPC).
Materials and Methods:
Patients with ANPC treated with CRT between September 2020 and June 2022 were retrospectively enrolled and categorized into response group (RG, n = 95) and non RGs (NRG, n = 32) based on the Response Evaluation Criteria in Solid Tumors (RECIST) 1.1. The quantitative parameters from pre-treatment syMRI (longitudinal [T1] and transverse [T2] relaxation times and proton density [PD]), diffusion-weighted imaging (apparent diffusion coefficient [ADC]), and clinicopathological characteristics were compared between RG and NRG. Logistic regression analysis was applied to identify parameters independently associated with CRT response and to construct a multivariable model. The areas under the receiveroperating characteristic curve (AUC) for various diagnostic approaches were compared using the DeLong test.
Results:
The T1, T2, and PD values in the NRG were significantly lower than those in the RG (all P < 0.05), whereas no significant difference was observed in the ADC values between these two groups. Clinicopathological characteristics (Epstein–Barr virus [EBV]-DNA level, lymph node extranodal extension, clinical stage, and Ki-67 expression) exhibited significant differences between the two groups. Logistic regression analysis showed that T1, PD, EBV-DNA level, clinical stage, and Ki-67 expression had significant independent relationships with CRT response (all P < 0.05). The multivariable model incorporating these five variables yielded AUC, sensitivity, and specificity values of 0.974, 93.8% (30/32), and 91.6% (87/95), respectively.
Conclusion
SyMRI may be used for the pretreatment prediction of CRT response in ANPC. The multivariable model incorporating syMRI quantitative parameters and clinicopathological characteristics, which were independently associated with CRT response, may be a new tool for the pretreatment prediction of CRT response.
6.Synthetic MRI Combined With Clinicopathological Characteristics for Pretreatment Prediction of Chemoradiotherapy Response in Advanced Nasopharyngeal Carcinoma
Siyu CHEN ; Jiankun DAI ; Jing ZHAO ; Shuang HAN ; Xiaojun ZHANG ; Jun CHANG ; Donghui JIANG ; Heng ZHANG ; Peng WANG ; Shudong HU
Korean Journal of Radiology 2025;26(2):135-145
Objective:
To explore the feasibility of synthetic magnetic resonance imaging (syMRI) combined with clinicopathological characteristics for the pre-treatment prediction of chemoradiotherapy (CRT) response in advanced nasopharyngeal carcinoma (ANPC).
Materials and Methods:
Patients with ANPC treated with CRT between September 2020 and June 2022 were retrospectively enrolled and categorized into response group (RG, n = 95) and non RGs (NRG, n = 32) based on the Response Evaluation Criteria in Solid Tumors (RECIST) 1.1. The quantitative parameters from pre-treatment syMRI (longitudinal [T1] and transverse [T2] relaxation times and proton density [PD]), diffusion-weighted imaging (apparent diffusion coefficient [ADC]), and clinicopathological characteristics were compared between RG and NRG. Logistic regression analysis was applied to identify parameters independently associated with CRT response and to construct a multivariable model. The areas under the receiveroperating characteristic curve (AUC) for various diagnostic approaches were compared using the DeLong test.
Results:
The T1, T2, and PD values in the NRG were significantly lower than those in the RG (all P < 0.05), whereas no significant difference was observed in the ADC values between these two groups. Clinicopathological characteristics (Epstein–Barr virus [EBV]-DNA level, lymph node extranodal extension, clinical stage, and Ki-67 expression) exhibited significant differences between the two groups. Logistic regression analysis showed that T1, PD, EBV-DNA level, clinical stage, and Ki-67 expression had significant independent relationships with CRT response (all P < 0.05). The multivariable model incorporating these five variables yielded AUC, sensitivity, and specificity values of 0.974, 93.8% (30/32), and 91.6% (87/95), respectively.
Conclusion
SyMRI may be used for the pretreatment prediction of CRT response in ANPC. The multivariable model incorporating syMRI quantitative parameters and clinicopathological characteristics, which were independently associated with CRT response, may be a new tool for the pretreatment prediction of CRT response.
7.Specification for postoperative care and treatment after transcatheter aortic valve replacement
Peide ZHANG ; Yuxin FAN ; Mian XU ; Siyu LIU ; Guangzhi ZHAO ; Shuo CHANG
Chinese Journal of Clinical Thoracic and Cardiovascular Surgery 2025;32(09):1203-1208
Since the first successful transcatheter aortic valve replacement (TAVR) was performed globally in 2002, the TAVR technology has become increasingly mature. With more than a decade of development in China, its application experience, device research and development, procedural improvements, evidence-based medicine, and guideline updates have continuously progressed, leading to a significant increase in the number of procedures conducted. Compared to traditional surgical operations, TAVR has different postoperative monitoring points and principles for the prevention and management of complications, necessitating the formulation of corresponding monitoring and treatment protocols that align with the technical characteristics of the procedure. This guideline is based on clinical practice and incorporates both domestic and international literature as well as the experiences of Fuwai Hospital. It distills and organizes routine postoperative monitoring practices, process optimization, and complication management for TAVR, establishing a set of practical guidelines for postoperative monitoring in China. These guidelines have strong practical value for optimizing postoperative management strategies and preventing and managing complications, which is beneficial for early functional recovery of patients, shortening hospital stays, and reducing complication rates. They provide guidance and reference for domestic peers and support the standardized development and quality improvement of postoperative management for TAVR in China.
8.A novel dual-targeting strategy of nanobody-driven protein corona modulation for glioma therapy.
Yupei ZHANG ; Shugang QIN ; Tingting SONG ; Zhiying HUANG ; Zekai LV ; Yang ZHAO ; Xiangyu JIAO ; Min SUN ; Yinghan ZHANG ; Guang XIE ; Yuting CHEN ; Xuli RUAN ; Ruyue LIU ; Haixing SHI ; Chunli YANG ; Siyu ZHAO ; Zhongshan HE ; Hai HUANG ; Xiangrong SONG
Acta Pharmaceutica Sinica B 2025;15(9):4917-4931
Glioma represents the most prevalent malignant tumor of the central nervous system, with chemotherapy serving as an essential adjunctive treatment. However, most chemotherapeutic agents exhibit limited ability to penetrate the blood-brain barrier (BBB). This study introduced a novel dual-targeting strategy for glioma therapy by modulating the formation of nanobody-driven protein coronas to enhance the brain and tumor-targeting efficiency of hydrophobic cisplatin prodrug-loaded lipid nanoparticles (C8Pt-Ls). Specifically, nanobodies (Nbs) with fibrinogen-binding capabilities were conjugated to the surface of C8Pt-Ls, resulting in the generation of Nb-C8Pt-Ls. Within the bloodstream, Nb-C8Pt-Ls could bound more fibrinogen, forming the protein corona that specifically interacted with LRP-1, a receptor highly expressed on the BBB. This interaction enabled a "Hitchhiking Effect" mechanism, facilitating efficient trans-BBB transport and promoting effective brain targeting. Additionally, the protein corona interacted with LRP-1, which is also overexpressed in glioma cells, achieving precise tumor targeting. Computational simulations and SPR detection clarified the molecular interaction mechanism of the Nb-fibrinogen-(LRP-1) complex, confirming its binding specificity and stability. Our results demonstrated that this strategy significantly enhanced C8Pt accumulation in brain tissues and tumors, induced apoptosis in glioma cells, and improved therapeutic efficacy. This study provides a novel framework for glioma therapy and underscores the potential of protein corona modulation-based dual-targeting strategies in advancing treatments for brain tumors.
9.The chordata olfactory receptor database.
Wei HAN ; Siyu BAO ; Jintao LIU ; Yiran WU ; Liting ZENG ; Tao ZHANG ; Ningmeng CHEN ; Kai YAO ; Shunguo FAN ; Aiping HUANG ; Yuanyuan FENG ; Guiquan ZHANG ; Ruiyi ZHANG ; Hongjin ZHU ; Tian HUA ; Zhijie LIU ; Lina CAO ; Xingxu HUANG ; Suwen ZHAO
Protein & Cell 2025;16(4):286-295

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