1.Molecular biological research and molecular homologous modeling of Bw.03 subgroup
Li WANG ; Yongkui KONG ; Huifang JIN ; Xin LIU ; Ying XIE ; Xue LIU ; Yanli CHANG ; Yafang WANG ; Shumiao YANG ; Di ZHU ; Qiankun YANG
Chinese Journal of Blood Transfusion 2025;38(1):112-115
[Objective] To study the molecular biological mechanism for a case of ABO blood group B subtype, and perform three-dimensional modeling of the mutant enzyme. [Methods] The ABO phenotype was identified by the tube method and microcolumn gel method; the ABO gene of the proband was detected by sequence-specific primer polymerase chain reaction (PCR-SSP), and the exon 6 and 7 of the ABO gene were sequenced and analyzed. Homologous modeling of Bw.03 glycosyltransferase (GT) was carried out by Modeller and analyzed by PyMOL2.5.0 software. [Results] The weakening B antigen was detected in the proband sample by forward typing, and anti-B antibody was detected by reverse typing. PCR-SSP detection showed B, O gene, and the sequencing results showed c.721 C>T mutation in exon 7 of the B gene, resulting in p. Arg 241 Trp. Compared with the wild type, the structure of Bw.03GT was partially changed, and the intermolecular force analysis showed that the original three hydrogen bonds at 241 position disappeared. [Conclusion] Blood group molecular biology examination is helpful for the accurate identification of ambiguous blood group. Homologous modeling more intuitively shows the key site for the weakening of Bw.03 GT activity. The intermolecular force analysis can explain the root cause of enzyme activity weakening.
2.Analyzing Differences in Volatile Components of Citri Reticulatae Pericarpium Before and After Being Stir-fried with Halloysitum Rubrum Based on HS-GC-MS and Intelligent Sensory Technology
Li XIN ; Jiawen WEN ; Wenhui GONG ; Beibei ZHAO ; Shihao YAN ; Huashi CHEN ; Haiping LE ; Jinlian ZHANG ; Yanhua XUE
Chinese Journal of Experimental Traditional Medical Formulae 2025;31(7):157-162
ObjectiveTo analyze the differences in color, odor and volatile components of Citri Reticulatae Pericarpium(CRP) before and after being stir-fried with Halloysitum Rubrum, and to explore the material basis of enhancing the effect of strengthening spleen after processing and the scientific connotation of decoction pieces processed with Halloysitum Rubrum as the auxiliary material. MethodsThe volatile components of the samples before and after processing were identified and relatively quantified by headspace gas chromatography-mass spectrometry(HS-GC-MS), and the volatile components were analyzed by principal component analysis(PCA) and orthogonal partial least squares-discriminant analysis(OPLS-DA). According to the principle of variable importance in the projection(VIP) value>1.5, volatile differential components before and after processing were screened. And combined with intelligent sensory technologies such as colorimeter and electronic nose, the chroma and odor information of CRP before and after being stir-fried with Halloysitum Rubrum were identified. Pearson correlation analysis was used to explore the correlation between volatile differential components and chroma values. ResultsA total of 112 volatile components were identified from CRP and CRP stir-fried with Halloysitum Rubrum, of which 84 were from CRP and 97 were from CRP stir-fried with Halloysitum Rubrum. And 7 differential components were selected, including α-pinene, β-myrcene, linalool, sabinene, ocimene isomer mixture, A-ocimene, and δ-elemene. After being processed with Halloysitum Rubrum, the brightness value(L*), yellow-blue value(b*) and total chromatic value(E*ab) of CRP were decreased(P<0.01), and red-green value(a*) was increased(P<0.01), the response values of S4, S5, S10 and S13 sensors were significantly increased(P<0.05), and the response values of S3 and S8 sensors were significantly decreased(P<0.05). Correlation analysis showed that α-pinene and β-myrcene were negatively correlated with L* and E*ab, but positively correlated with a*. Sabinene was positively correlated with L* and E*ab. Linalool was positively correlated with L* and E*ab, and negatively correlated with a*. The ocimene isomer mixture was positively correlated with the L*. ConclusionAfter being processed with Halloysitum Rubrum, the appearance color, odor and volatile components of CRP change significantly, and α-pinene, β-myrcene, sabinene, linalool and A-ocimene are the characteristic volatile components before and after processing, which can provide references for the quality evaluation and clinical application of CRP and its processed products.
3.Analyzing Differences in Volatile Components of Citri Reticulatae Pericarpium Before and After Being Stir-fried with Halloysitum Rubrum Based on HS-GC-MS and Intelligent Sensory Technology
Li XIN ; Jiawen WEN ; Wenhui GONG ; Beibei ZHAO ; Shihao YAN ; Huashi CHEN ; Haiping LE ; Jinlian ZHANG ; Yanhua XUE
Chinese Journal of Experimental Traditional Medical Formulae 2025;31(7):157-162
ObjectiveTo analyze the differences in color, odor and volatile components of Citri Reticulatae Pericarpium(CRP) before and after being stir-fried with Halloysitum Rubrum, and to explore the material basis of enhancing the effect of strengthening spleen after processing and the scientific connotation of decoction pieces processed with Halloysitum Rubrum as the auxiliary material. MethodsThe volatile components of the samples before and after processing were identified and relatively quantified by headspace gas chromatography-mass spectrometry(HS-GC-MS), and the volatile components were analyzed by principal component analysis(PCA) and orthogonal partial least squares-discriminant analysis(OPLS-DA). According to the principle of variable importance in the projection(VIP) value>1.5, volatile differential components before and after processing were screened. And combined with intelligent sensory technologies such as colorimeter and electronic nose, the chroma and odor information of CRP before and after being stir-fried with Halloysitum Rubrum were identified. Pearson correlation analysis was used to explore the correlation between volatile differential components and chroma values. ResultsA total of 112 volatile components were identified from CRP and CRP stir-fried with Halloysitum Rubrum, of which 84 were from CRP and 97 were from CRP stir-fried with Halloysitum Rubrum. And 7 differential components were selected, including α-pinene, β-myrcene, linalool, sabinene, ocimene isomer mixture, A-ocimene, and δ-elemene. After being processed with Halloysitum Rubrum, the brightness value(L*), yellow-blue value(b*) and total chromatic value(E*ab) of CRP were decreased(P<0.01), and red-green value(a*) was increased(P<0.01), the response values of S4, S5, S10 and S13 sensors were significantly increased(P<0.05), and the response values of S3 and S8 sensors were significantly decreased(P<0.05). Correlation analysis showed that α-pinene and β-myrcene were negatively correlated with L* and E*ab, but positively correlated with a*. Sabinene was positively correlated with L* and E*ab. Linalool was positively correlated with L* and E*ab, and negatively correlated with a*. The ocimene isomer mixture was positively correlated with the L*. ConclusionAfter being processed with Halloysitum Rubrum, the appearance color, odor and volatile components of CRP change significantly, and α-pinene, β-myrcene, sabinene, linalool and A-ocimene are the characteristic volatile components before and after processing, which can provide references for the quality evaluation and clinical application of CRP and its processed products.
4.Alanine transferase test results and exploration of threshold adjustment strategies for blood donors in Shenzhen, China
Xin ZHENG ; Yuanye XUE ; Haobiao WANG ; Litiao WU ; Ran LI ; Yingnan DANG ; Tingting CHEN ; Xiaoxuan XU ; Xuezhen ZENG ; Jinfeng ZENG
Chinese Journal of Blood Transfusion 2025;38(4):488-494
[Objective] To conduct a retrospective statistical comparison of alanine aminotransferase (ALT) test values in blood donors prior to blood collection, aiming to analyze the objective characteristics of the population with elevated ALT levels (ALT>50 U/L) and provide reference data for adjusting the screening eligibility threshold for ALT. [Methods] The preliminary ALT screening data of 30 341 blood donor samples collected prior to blood donation from three smart blood donation sites at the Shenzhen Blood Center between 2022 and 2023 were extracted and compared with data from a health examination department of a tertiary hospital in Shenzhen (representing the general population, n=24 906). Both datasets were categorized and statistically described. A retrospective analysis was conducted to examine the associations between ALT test results and factors such as donors' gender, age, ethnicity, donation site, donation season, and frequency of blood donation. [Results] The ALT levels in both blood donors and the general population were non-normally distributed. The 95th percentile of ALT values was calculated as 61.4 U/L (male: 67.8 U/L, female: 39.3 U/L) for blood donors and 58.1 U/L (male: 63.7 U/L, female: 51.2 U/L) for the general population. The non-compliance rates (ALT>50 U/L) were 7.65% (2 321/30 341) in blood donors and 7.08% (1 763/24 906) in the general population. There were significant differences (P<0.05) in the ALT failure rate among blood donors based on gender, age, and donation site, but no significant differences (P>0.05) during the blood donation season. There was no statistically significant difference (P>0.05) in the positive rates of four serological markers (HBsAg, anti HCV, HIV Ag/Ab, anti TP) for blood screening pathogens between ALT unqualified and qualified individuals (2.05% vs 1.5%). If the ALT qualification threshold was raised from 50 U/L to 90 U/L, the non qualification rates of male and female blood donors would decrease from 9.82% (2 074/21 125) to 2.23% (471/21 125) and from 2.70% (249/9 216) to 0.75% (69/9 216), respectively. Among the 154 blood donors who donated blood more than 3 times, 88.31% of the 248 ALT test results were in the range of 50-90 U/L. Among them, 9 cases had ALT>130 U/L, and ALT was converted to qualified in subsequent blood donations. [Conclusion] There are differences in the ALT failure rate among blood donors of different genders and ages, and different blood donation sites and operators can also affect the ALT detection values of blood donors. The vast majority of blood donors with ALT failure are caused by transient and non pathological factors. With the widespread use of blood virus nucleic acid testing, appropriately increasing the ALT qualification threshold for blood donors can expand the qualified population and alleviate the shortage of blood sources, and the risk of blood safety will not increase.
5.PDGF-C: an Emerging Target in The Treatment of Organ Fibrosis
Chao YANG ; Zi-Yi SONG ; Chang-Xin WANG ; Yuan-Yuan KUANG ; Yi-Jing CHENG ; Ke-Xin REN ; Xue LI ; Yan LIN
Progress in Biochemistry and Biophysics 2025;52(5):1059-1069
Fibrosis, the pathological scarring of vital organs, is a severe and often irreversible condition that leads to progressive organ dysfunction. It is particularly pronounced in organs like the liver, kidneys, lungs, and heart. Despite its clinical significance, the full understanding of its etiology and complex pathogenesis remains incomplete, posing substantial challenges to diagnosing, treating, and preventing the progression of fibrosis. Among the various molecular players involved, platelet-derived growth factor-C (PDGF-C) has emerged as a crucial factor in fibrotic diseases, contributing to the pathological transformation of tissues in several key organs. PDGF-C is a member of the PDGFs family of growth factors and is synthesized and secreted by various cell types, including fibroblasts, smooth muscle cells, and endothelial cells. It acts through both autocrine and paracrine mechanisms, exerting its biological effects by binding to and activating the PDGF receptors (PDGFRs), specifically PDGFRα and PDGFRβ. This binding triggers multiple intracellular signaling pathways, such as JAK/STAT, PI3K/AKT and Ras-MAPK pathways. which are integral to the regulation of cell proliferation, survival, migration, and fibrosis. Notably, PDGF-C has been shown to promote the proliferation and migration of fibroblasts, key effector cells in the fibrotic process, thus accelerating the accumulation of extracellular matrix components and the formation of fibrotic tissue. Numerous studies have documented an upregulation of PDGF-C expression in various fibrotic diseases, suggesting its significant role in the initiation and progression of fibrosis. For instance, in liver fibrosis, PDGF-C stimulates hepatic stellate cell activation, contributing to the excessive deposition of collagen and other extracellular matrix proteins. Similarly, in pulmonary fibrosis, PDGF-C enhances the migration of fibroblasts into the damaged areas of lungs, thereby worsening the pathological process. Such findings highlight the pivotal role of PDGF-C in fibrotic diseases and underscore its potential as a therapeutic target for these conditions. Given its central role in the pathogenesis of fibrosis, PDGF-C has become an attractive target for therapeutic intervention. Several studies have focused on developing inhibitors that block the PDGF-C/PDGFR signaling pathway. These inhibitors aim to reduce fibroblast activation, prevent the excessive accumulation of extracellular matrix components, and halt the progression of fibrosis. Preclinical studies have demonstrated the efficacy of such inhibitors in animal models of liver, kidney, and lung fibrosis, with promising results in reducing fibrotic lesions and improving organ function. Furthermore, several clinical inhibitors, such as Olaratumab and Seralutinib, are ongoing to assess the safety and efficacy of these inhibitors in human patients, offering hope for novel therapeutic options in the treatment of fibrotic diseases. In conclusion, PDGF-C plays a critical role in the development and progression of fibrosis in vital organs. Its ability to regulate fibroblast activity and influence key signaling pathways makes it a promising target for therapeutic strategies aiming at combating fibrosis. Ongoing research into the regulation of PDGF-C expression and the development of PDGF-C/PDGFR inhibitors holds the potential to offer new insights and approaches for the diagnosis, treatment, and prevention of fibrotic diseases. Ultimately, these efforts may lead to the development of more effective and targeted therapies that can mitigate the impact of fibrosis and improve patient outcomes.
6.Discriminating Tumor Deposits From Metastatic Lymph Nodes in Rectal Cancer: A Pilot Study Utilizing Dynamic Contrast-Enhanced MRI
Xue-han WU ; Yu-tao QUE ; Xin-yue YANG ; Zi-qiang WEN ; Yu-ru MA ; Zhi-wen ZHANG ; Quan-meng LIU ; Wen-jie FAN ; Li DING ; Yue-jiao LANG ; Yun-zhu WU ; Jian-peng YUAN ; Shen-ping YU ; Yi-yan LIU ; Yan CHEN
Korean Journal of Radiology 2025;26(5):400-410
Objective:
To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer.
Materials and Methods:
A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs.
Results:
All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027).
Conclusion
The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.
7.Discriminating Tumor Deposits From Metastatic Lymph Nodes in Rectal Cancer: A Pilot Study Utilizing Dynamic Contrast-Enhanced MRI
Xue-han WU ; Yu-tao QUE ; Xin-yue YANG ; Zi-qiang WEN ; Yu-ru MA ; Zhi-wen ZHANG ; Quan-meng LIU ; Wen-jie FAN ; Li DING ; Yue-jiao LANG ; Yun-zhu WU ; Jian-peng YUAN ; Shen-ping YU ; Yi-yan LIU ; Yan CHEN
Korean Journal of Radiology 2025;26(5):400-410
Objective:
To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer.
Materials and Methods:
A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs.
Results:
All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027).
Conclusion
The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.
8.Discriminating Tumor Deposits From Metastatic Lymph Nodes in Rectal Cancer: A Pilot Study Utilizing Dynamic Contrast-Enhanced MRI
Xue-han WU ; Yu-tao QUE ; Xin-yue YANG ; Zi-qiang WEN ; Yu-ru MA ; Zhi-wen ZHANG ; Quan-meng LIU ; Wen-jie FAN ; Li DING ; Yue-jiao LANG ; Yun-zhu WU ; Jian-peng YUAN ; Shen-ping YU ; Yi-yan LIU ; Yan CHEN
Korean Journal of Radiology 2025;26(5):400-410
Objective:
To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer.
Materials and Methods:
A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs.
Results:
All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027).
Conclusion
The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.
9.Discriminating Tumor Deposits From Metastatic Lymph Nodes in Rectal Cancer: A Pilot Study Utilizing Dynamic Contrast-Enhanced MRI
Xue-han WU ; Yu-tao QUE ; Xin-yue YANG ; Zi-qiang WEN ; Yu-ru MA ; Zhi-wen ZHANG ; Quan-meng LIU ; Wen-jie FAN ; Li DING ; Yue-jiao LANG ; Yun-zhu WU ; Jian-peng YUAN ; Shen-ping YU ; Yi-yan LIU ; Yan CHEN
Korean Journal of Radiology 2025;26(5):400-410
Objective:
To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer.
Materials and Methods:
A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs.
Results:
All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027).
Conclusion
The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.
10.Discriminating Tumor Deposits From Metastatic Lymph Nodes in Rectal Cancer: A Pilot Study Utilizing Dynamic Contrast-Enhanced MRI
Xue-han WU ; Yu-tao QUE ; Xin-yue YANG ; Zi-qiang WEN ; Yu-ru MA ; Zhi-wen ZHANG ; Quan-meng LIU ; Wen-jie FAN ; Li DING ; Yue-jiao LANG ; Yun-zhu WU ; Jian-peng YUAN ; Shen-ping YU ; Yi-yan LIU ; Yan CHEN
Korean Journal of Radiology 2025;26(5):400-410
Objective:
To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer.
Materials and Methods:
A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs.
Results:
All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027).
Conclusion
The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

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