The drug resistance in the treatment of solid tumors is closely related to abnormalities in the tumor vascular microenvironment (TVM). The TVM is dynamically composed of multiple stromal, vascular, and immune cell populations together with extracellular matrix. Its structural disorder and functional imbalance can lead to abnormal angiogenesis, perfusion disorders, limited drug delivery, and insufficient immune cell infiltration, thereby creating a microenvironment conducive to tumor progression and treatment resistance. Therefore, the coordinated regulation of TVM through vascular normalization and immune remodeling has become an important research direction for improving the treatment effect of solid tumors. Tumor necrosis factor superfamily member 14 (TNFSF14), also known as LIGHT (homologous to lymphotoxin, inducible, competes with herpes simplex virus (HSV) glycoprotein D for herpesvirus entry mediator (HVEM), expressed by T lymphocyte), is an important molecule connecting tumor vascular remodeling and immune regulation. LIGHT can bind to the lymphotoxin β receptor (LTβR) to activate the NF-κB (nuclear factor kappa B)-related signaling pathway, regulate the functions of vascular endothelial cells and stromal cells, and induce the expression of adhesion molecules and chemokines such as VCAM-1(vascular cell adhesion molecule 1), ICAM-1(intercellular adhesion molecule 1), CCL19 (C-C motif chemokine ligand 19), CCL21 (C-C motif chemokine ligand 21), and CXCL13 (C-X-C motif chemokine ligand 13), promoting the formation of high endothelial venules (HEVs). HEVs can improve the vascular access of immune cells into tumor tissues and further promote the formation of tertiary lymphoid structures (TLS), providing a structural basis for the recruitment of effector T cells and sustained anti-tumor immune responses. At the same time, LIGHT interacts with HVEM to provide costimulatory signals to T cells, enhancing their activation, proliferation, and cytotoxic function. Thus, LIGHT can link tumor vascular normalization, immune cell recruitment, and T cell activation through the dual actions mediated by LTβR and HVEM, forming a coordinated regulation model of “vascular remodeling-immune infiltration-immune activation”, providing new molecular targets for the treatment of solid tumors. Despite LIGHT’s good anti-tumor potential, its therapeutic application is still limited by factors such as insufficient stability in vivo, short half-life, and potential off-target effects due to systemic exposure. In recent years, researchers have developed various strategies for the precise delivery of LIGHT, including fusion proteins, bacterial vectors, viral vectors, nanoparticles, chimeric antigen receptor T cells (CAR-T), and mesenchymal stem cells (MSCs), to enhance the enrichment, expression, or sustained release of LIGHT in tumor sites through different approaches, thereby improving its therapeutic efficacy and safety. This article systematically reviews the structural characteristics, biological functions, and molecular mechanisms mediating TVM remodeling by LIGHT, with a focus on the signal transduction mediated by LTβR and HVEM and their roles in tumor immune regulation. Subsequently, it systematically outlines the molecular mechanisms by which LIGHT regulates the tumor vascular microenvironment and its intrinsic connection with immune cell recruitment and activation, from the perspectives of TVM abnormalities, vascular normalization, HEV formation, and TLS induction. Furthermore, it categorizes and summarizes precise delivery strategies such as LIGHT fusion proteins, bacterial vectors, viral vectors, nanoparticles, CAR-T cells, and MSCs according to delivery vectors and modes of action, and compares their functional characteristics, antitumor effects, and potential advantages and limitations. On this basis, the article further discusses the key issues that LIGHT therapeutic strategies still face in terms of targeting, controllability,in vivo stability, safety, and clinical translation, and anticipates the potential value of its combination with immune checkpoint inhibitors, anti-angiogenic therapy, and other tumor treatment methods. This article aims to deepen the understanding of the antitumor mechanism of LIGHT from the perspective of synergistic regulation of tumor vascular microenvironment remodeling and immune activation, providing theoretical basis and new research ideas for the design of solid tumor treatment strategies based on precise regulation of TVM and the clinical translation of LIGHT-related treatment systems.

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.

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.

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.

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.

ObjectiveTo investigate the pathogenic spectrum and epidemiological characteristics of diarrheal disease in Fengxian District of Shanghai, and to provide scientific basis for the prevention and control of diarrheal diseases. MethodsBasic information of the initial adult cases visited diarrheal disease surveillance sentinel hospital in Fengxian District, Shanghai, was collected from August 2013 to 2023, and fecal samples were collected at 1∶5 sampling intervals to isolate and identify 5 kinds of diarrheagenic Escherichia coli (DEC), Salmonella (SAL), Vibrio parahaemolyticus, Campylobacter, Vibrio cholerae, Shigella and Yersinia enterocolitica (YE). Simultaneously, nucleic acid detection was performed for 3 kinds of rotavirus, 2 kinds of norovirus, intestinal adenovirus, astrovirus and sapovirus. ResultsA total of 1 861 cases of newly diagnosed diarrheal disease were reported, with the peak in July to August. Additionally, 704 surveillance samples were detected, with a total positive detection rate of 50.57%. The detection rates of bacterial, viral and mixed infection were 25.14%, 21.02% and 4.40%, respectively. Among the pathogens detected, DEC accounted for the highest (17.61%, 124/704), followed by norovirus (16.48%, 116/704), rotavirus (6.39%, 45/704), SAL (5.97%, 42/704) and Campylobacter (3.84%, 27/704). DEC detected were mainly enteroaggregative Escherichia coli and enterotoxigenic Escherichia coli, with no detection of Vibrio cholerae, Shigella and YE. The highest total pathogen detection rate was observed from June to September, and the detection peaks of norovirus were from March to June and from October to December, whereas that of DEC was from June to October. The detection rate of rotavirus peaked from January to February, but which was not detected between 2020‒2023. The SAL positive rate peak was in September, whereas that of Campylobacter was from July to September. ConclusionThe main pathogens detected in Fengxian District from 2013‒2019 are DEC, norovirus, rotavirus, SAL and Campylobacter. Different pathogens have different detection peaks, with bacteria predominating in summer and viruses in winter and spring. Prevention and control measures should be carried out according to the epidemiological characteristics of different seasons.

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.

OBJECTIVE: To detect the alleles of 12 blood group systems (Rh, MNS, Duffy, Kidd, Kell, Diego, Dombrock, Yt, Colton, Scianna, Lutheran and Lw) of Dongxiang ethnic group in Gansu province, and understand the characteristics of rare blood group alleles common in Dongxiang ethnic group, in order to provide a basis for safe blood transfusion and the establishment of blood group gene bank. METHODS: The alleles of 12 blood group systems were classified by polymerase chain reaction (PCR) in 100 people from Dongxiang ethnic group in Gansu province, and the differences of gene frequency compared to other areas in China were analyzed. RESULTS: The allele frequencies of Rh, MNS, and Dombrock blood group systems of Dongxiang ethnic group in Gansu province were similar to northern regions. The Duffy blood group system exhibited specificity, with frequencies lower than most southern regions as well as northern regions. There were no significant differences in Kidd, Kell and Diego blood group systems compared to other regions in China. The Lu^a gene frequency of Lutheran blood group system was higher than all regions in China, which might be associated with genetic variation or sample selection and size. Yt, Colton, Scianna and Lw blood group genes showed monomorphic distribution, and the genotypes were Yt^aYt^a, Co^aCo^a, Sc1Sc1 and Lw^aLw^a, respectively. CONCLUSION Rh, MNS, Duffy, Kidd, Kell, Diego, Dombrock and Lutheran blood group systems show polymorphic distribution, while Yt, Colton, Scianna and Lw blood group systems show monomorphic distribution. The distribution of blood group genes among Dongxiang ethnic group in Gansu province has its own specificity.
Humans ; China/ethnology* ; Polymorphism, Genetic ; Blood Group Antigens/genetics* ; Gene Frequency ; Alleles ; Asian People/genetics* ; Ethnicity/genetics* ; Genotype ; Female

Objective:To evaluate the cumulative live birth rate (CLBR) and cost-effectiveness of fixed versus adjusted follicle-stimulation hormone (FSH) dosages in infertile women with different ovarian responses during their first assisted reproductive technology (ART) cycle.Methods:A retrospective real-world cohort study was conducted on 5 419 infertile women who underwent their first ART treatment at the Department of Reproductive Medicine of the First Affiliated Hospital of Nanjing Medical University between January 2013 and December 2017. All patients received an individualized starting dosage of gonadotropin. Based on whether FSH dosages were adjusted during controlled ovarian stimulation (COS), patients were divided into fixed-dosage group ( n=2 061) and adjusted-dosage group ( n=3 358). Clinical outcomes and FSH cost-effectiveness were compared between the two groups across different ovarian response groups, with CLBR as the primary outcome. Propensity score matching (PSM) and multivariable logistic regression were used to adjust for potential confounders. Results:FSH dosage adjustments were found in 62.0% (3 358/5 419) of cycles during COS. After PSM, baseline characteristics were comparable between the two groups (all P>0.05). After adjusting for confounders using multivariable logistic regression, FSH dosage adjustment was not significantly associated with CLBR ( OR=1.06, 95% CI: 0.94-1.20, P=0.332). Compared with the adjusted-dosage group, the fixed-dosage group showed no significant differences in CLBR in poor-, normal-, and high-responder groups (all P>0.05). The incidence of ovarian hyperstimulation syndrome (OHSS) did not differ significantly between the two groups ( P>0.05). In poor-, normal-, and high-responder groups, the total FSH dosages in the fixed-dose group [1 350 (375, 1 825) U, 1 200 (375, 1 500) U and 525 (375, 1 128) U, respectively] were significantly lower than those in the adjusted-dose group [1 875 (1 425, 2 294) U, P=0.001; 1 425 (450, 1 875) U, P<0.001; 600 (375, 1 425) U, P=0.020]. Similarly, average FSH costs in different ovarian response groups in the fixed-dosage group [4 725.0 (1 312.5, 6 387.5) yuan, 4 200.0 (1 312.5, 5 250.0) yuan and 1 837.5 (1 312.5, 3 947.3) yuan, respectively] were significantly lower than those in the adjusted-dosage group [6 562.5 (4 987.5, 8 028.1) yuan, P=0.001; 4 987.5 (1 575.0, 6 562.5) yuan, P<0.001; 2 100.0 (1 312.5, 4 987.5) yuan, P=0.020]. For normal-responders, the FSH cost per high-quality embryo in the fixed-dosage group [1 365.0 (875.0, 2 537.5) yuan] was significantly lower than that in the adjusted-dosage group [2 056.3 (1 268.8, 3 412.5) yuan, P<0.001]. Conclusion:FSH dosage adjustment during COS is not associated with CLBR or the incidence of OHSS. However, the fixed-dose group exhibited lower total FSH dosages and costs across different ovarian response populations. In the context of ART being covered by medical insurance, fixed FSH dosage may represent a more cost-effective ovarian stimulation protocol.