Objective:To analyze relevant factors influencing severe acute radiation enteritis (SARE) during total neoadjuvant therapy (TNT) for locally advanced rectal cancer (LARC). To identify specific prediction indicators of the occurrence and progression of radiation enteritis by investigating the effect relationships between radiation enteritis and multidimensional factors.Methods:A total of 92 patients with rectal adenocarcinoma who received total neoadjuvant therapy at the First Affiliated Hospital of Soochow University from January 2020 to September 2023 were enrolled in this study. Their relevant information was collected, encompassing clinical nutritional indicators, dynamic changes in hematological parameters, systemic inflammatory indicators, and the occurrence of adverse reactions. Then, risk factors associated with radiation enteritis were determined using logistic regression analysis. Based on independent risk factors, a nomogram model for risk prediction was constructed.Results:Univariate analysis revealed significant correlations of the SARE occurrence with certain nutritional indicators, local tumor measurement data, and laboratory parameters. Multivariate regression analysis further identified the independent risk factors for SARE occurrence, including albumin reduction >26.5% before vs. after treatment ( OR = 5.010, 95% CI: 1.766-14.154, P = 0.010), rectual tenesmus rating of Grade 1-3 ( OR = 3.639, 95% CI: 1.425-9.300, P = 0.024), and elevated disease activity index (DAI) score ( OR ≈ 7.683 per 1-point increase, 95% CI: 1.105-53.410, P = 0.039). The prediction model constructed based on these factors demonstrated high prediction efficiency (AUC = 0.841; 95% CI: 0.749-0.934). Conclusions:The nomogram model constructed using albumin reduction, rectal tenesmus rating, and DAI score can provide accurate, simple, and low-cost risk prediction of radiation enteritis during TNT for LARC patients. This model facilitates the early clinical identification of high-risk patients, providing a basis for implementing personalized adjustments to radiotherapy regimens and enhancing nutritional interventions.

Objective:To identify the relevant factors for the first-course remission of acute myeloid leukemia (AML) and to develop a predictive model as well as assess its predictive capability.Methods:Clinical data of 749 patients newly diagnosed with AML admitted to the Department of Hematology, the First Affiliated Hospital, Zhejiang University, School of Medicine from January 1, 2019, to April 30, 2023, were collected and randomly divided into training and validation sets. Multivariate logistic regression analysis was conducted to determine variables associated with complete remission in the first course of induction therapy, and a predictive model was established based on these variables. The receiver operating characteristic (ROC) curve of the predictive model was plotted, and the area under the curve (AUC) was calculated.Results:The indicators predicting the first remission course included peripheral blood white blood cell count during onset, CBF::MYH11 fusion gene, CEBPA bZIP region mutation, myelodysplastic syndrome-related gene mutation, and induction chemotherapy regimen selection as independent factors for the first remission course. The model’s area under the training and validation curves was 0.738 (95% CI: 0.696-0.780) and 0.726 (95% CI: 0.650-0.801), respectively. The Hosmer-Lemeshow test results yielded P-values of 0.993 and 0.335, respectively. Conclusion:In this study, the developed model demonstrates a strong predictive capability for the efficacy of the first course of patients with AML, providing valuable guidance to clinicians in assessing patient prognosis and selecting appropriate treatment strategies.

ObjectiveTo explore the mechanisms associated with Mahoniae Caulis alkaloids （MA） in ameliorating depression by network pharmacology， molecular docking， and animal experiments. MethodsThe component targets of MA were obtained through Swiss Target Prediction and TCMIP database. The depression targets were collected through TCMIP， Genecards， HPO， DrugBank and OMIM database. The depression targets were collected through TCMIP， Genecards， HPO， DrugBank and OMIM database. Protein-protein interaction （PPI） network was constructed by protein interaction analysis （STRING） database. Gene ontology （GO） and Kyoto Encyclopedia of Genes and Genomes （KEGG） analyses were performed through Bioinformatics （DAVID） database. The docking of components and targets was performed by AGFR. The mouse model of depression was established by intraperitoneal injection of corticosterone （CORT） once a day for 35 consecutive days. Sixty mice were randomly allocated into control （0.9% normal saline）， model （CORT， 20 mg·kg^-1）， positive control （fluoxetine hydrochloride， 3.6 mg·kg^-1）， and MA （10， 5， and 2.5 mg·kg^-1） groups. Each group was administrated with corresponding medicine or normal saline once a day for 28 consecutive days. The depression-like behavior of mice was observed. The pathological changes of prefrontal cortex in mice were observed by hematoxylin-eosin staining. Terminal deoxynucleotidyl dUTP transferase nick end labeling （TUNEL） was employed to observe the apoptosis of neurons in the prefrontal cortex. Enzyme-linked immunosorbent assay was employed to assess the serum levels of brain-derived neurotrophic factor （BDNF）， dopamine （DA）， 5-hydroxytryptamine （5-HT）， and norepinephrine （NE） in mice. The mRNA levels of cyclic adenosine monophosphate （cAMP） pathway-related factors and inflammatory factors were determined by Real-time PCR. Western blot was employed to determine the expression of cAMP pathway-related factors and connexin 43 （Cx43）. ResultsA total of 434 component targets and 545 depression targets were obtained， including 84 common targets， among which 10 core targets were screened out. GO analysis predicted 34 biological processes， 15 cell components， and 11 molecular functions. The KEGG pathways were mainly related to gap junction and cAMP signaling pathway. The core components had good binding affinity with the core targets. The results of animal experiments showed that compared with the control group， CORT prolonged the immobility time of mice in forced swimming and tail suspension tests （P<0.01）， lowered the serum levels of NE， BDNF， and 5-HT （P<0.05）， up-regulated the mRNA levels of nuclear factor-κB （NF-κB） and interleukin-6 （IL-6） in the brain tissue （P<0.05）， and down-regulated the mRNA levels of cyclic adenosine monophosphate effector binding protein （CREB） and BDNF （P<0.05） and the protein levels of protein kinase （PRKACA）， phosphorylation （p）-CREB/CREB， BDNF， and Cx43 （P<0.05） in the brain tissue. Compared with the model group， high-dose MA reduced the immobility time of mice in forced swimming （P<0.05） and tail suspension （P<0.01） tests， raised the serum levels of NE， BDNF， and 5-HT （P<0.01）， down-regulated the mRNA level of NF-κB （P<0.01）， and up-regulated the mRNA level of BDNF （P<0.01） and protein levels of PRKACA， p-CREB/CREB， BDNF， and Cx43 （P<0.05）. ConclusionMA alleviates the CORT-induced depressive behavior of mice. It may play an antidepressant role by regulating cAMP signaling pathway and gap junction pathway， improving synaptic plasticity and gap junction function， and reducing neuroinflammation.

ObjectiveTo explore the mechanisms associated with Mahoniae Caulis alkaloids （MA） in ameliorating depression by network pharmacology， molecular docking， and animal experiments. MethodsThe component targets of MA were obtained through Swiss Target Prediction and TCMIP database. The depression targets were collected through TCMIP， Genecards， HPO， DrugBank and OMIM database. The depression targets were collected through TCMIP， Genecards， HPO， DrugBank and OMIM database. Protein-protein interaction （PPI） network was constructed by protein interaction analysis （STRING） database. Gene ontology （GO） and Kyoto Encyclopedia of Genes and Genomes （KEGG） analyses were performed through Bioinformatics （DAVID） database. The docking of components and targets was performed by AGFR. The mouse model of depression was established by intraperitoneal injection of corticosterone （CORT） once a day for 35 consecutive days. Sixty mice were randomly allocated into control （0.9% normal saline）， model （CORT， 20 mg·kg^-1）， positive control （fluoxetine hydrochloride， 3.6 mg·kg^-1）， and MA （10， 5， and 2.5 mg·kg^-1） groups. Each group was administrated with corresponding medicine or normal saline once a day for 28 consecutive days. The depression-like behavior of mice was observed. The pathological changes of prefrontal cortex in mice were observed by hematoxylin-eosin staining. Terminal deoxynucleotidyl dUTP transferase nick end labeling （TUNEL） was employed to observe the apoptosis of neurons in the prefrontal cortex. Enzyme-linked immunosorbent assay was employed to assess the serum levels of brain-derived neurotrophic factor （BDNF）， dopamine （DA）， 5-hydroxytryptamine （5-HT）， and norepinephrine （NE） in mice. The mRNA levels of cyclic adenosine monophosphate （cAMP） pathway-related factors and inflammatory factors were determined by Real-time PCR. Western blot was employed to determine the expression of cAMP pathway-related factors and connexin 43 （Cx43）. ResultsA total of 434 component targets and 545 depression targets were obtained， including 84 common targets， among which 10 core targets were screened out. GO analysis predicted 34 biological processes， 15 cell components， and 11 molecular functions. The KEGG pathways were mainly related to gap junction and cAMP signaling pathway. The core components had good binding affinity with the core targets. The results of animal experiments showed that compared with the control group， CORT prolonged the immobility time of mice in forced swimming and tail suspension tests （P<0.01）， lowered the serum levels of NE， BDNF， and 5-HT （P<0.05）， up-regulated the mRNA levels of nuclear factor-κB （NF-κB） and interleukin-6 （IL-6） in the brain tissue （P<0.05）， and down-regulated the mRNA levels of cyclic adenosine monophosphate effector binding protein （CREB） and BDNF （P<0.05） and the protein levels of protein kinase （PRKACA）， phosphorylation （p）-CREB/CREB， BDNF， and Cx43 （P<0.05） in the brain tissue. Compared with the model group， high-dose MA reduced the immobility time of mice in forced swimming （P<0.05） and tail suspension （P<0.01） tests， raised the serum levels of NE， BDNF， and 5-HT （P<0.01）， down-regulated the mRNA level of NF-κB （P<0.01）， and up-regulated the mRNA level of BDNF （P<0.01） and protein levels of PRKACA， p-CREB/CREB， BDNF， and Cx43 （P<0.05）. ConclusionMA alleviates the CORT-induced depressive behavior of mice. It may play an antidepressant role by regulating cAMP signaling pathway and gap junction pathway， improving synaptic plasticity and gap junction function， and reducing neuroinflammation.

Most patients with pancreatic cancer are already in the locally advanced or metastatic stage at initial diagnosis. While systemic chemotherapy provides clinical benefits for those with mid-to-late-stage pancreatic cancer, its efficacy is often limited by patient tolerance. In response to the dual clinical demands of robust antitumor activity and high targeting specificity, antibody-drug conjugate (ADC) has emerged as a promising solution. By conjugating highly selective monoclonal antibodies with potent cytotoxic small-molecule drugs, ADC achieves precise tumor-targeting while minimizing damage to healthy tissues, which thereby improves treatment tolerance. However, due to the complex pathological features of pancreatic cancer, no ADC has yet been approved for clinical use for this disease. A comprehensive evaluation of factors including ADC-specific targets, payload selection, antibody-drug linkage strategies, drug delivery mechanisms, tissue distribution variability, and tumor heterogeneity will be crucial to advancing the clinical translation of ADC for pancreatic cancer treatment.

Radiotherapy plays a pivotal role in the treatment of malignant tumors. The emergence of radiation resistance in malignant tumors, contributing to tumor recurrence, progression, or distant metastasis, remains a significant treatment challenge. Exploring the mechanisms underlying radiation resistance and overcoming the radio-resistance of tumors have become urgent problems in oncological practice. Cuproptosis, a copper-dependent form of regulated cell death, is driven by the aggregation of lipoylated proteins and the reduction of Fe-S cluster proteins, etc. Copper and cuproptosis are not only intricately related to the incidence and development of tumors, but also participate in radiation resistance of tumor cells. Strategic interventions targeting copper and inducing cuproptosis will present promising avenues for overcoming radiation resistance and further improving the prognosis of tumor patients. This review comprehensively delineates established and potential mechanisms governing the intricate crosstalk between radiation resistance and cuproptosis, aiming to provide reference for overcoming radiation resistance in malignant tumor cells.

Objective:To analyze relevant factors influencing severe acute radiation enteritis (SARE) during total neoadjuvant therapy (TNT) for locally advanced rectal cancer (LARC). To identify specific prediction indicators of the occurrence and progression of radiation enteritis by investigating the effect relationships between radiation enteritis and multidimensional factors.Methods:A total of 92 patients with rectal adenocarcinoma who received total neoadjuvant therapy at the First Affiliated Hospital of Soochow University from January 2020 to September 2023 were enrolled in this study. Their relevant information was collected, encompassing clinical nutritional indicators, dynamic changes in hematological parameters, systemic inflammatory indicators, and the occurrence of adverse reactions. Then, risk factors associated with radiation enteritis were determined using logistic regression analysis. Based on independent risk factors, a nomogram model for risk prediction was constructed.Results:Univariate analysis revealed significant correlations of the SARE occurrence with certain nutritional indicators, local tumor measurement data, and laboratory parameters. Multivariate regression analysis further identified the independent risk factors for SARE occurrence, including albumin reduction >26.5% before vs. after treatment ( OR = 5.010, 95% CI: 1.766-14.154, P = 0.010), rectual tenesmus rating of Grade 1-3 ( OR = 3.639, 95% CI: 1.425-9.300, P = 0.024), and elevated disease activity index (DAI) score ( OR ≈ 7.683 per 1-point increase, 95% CI: 1.105-53.410, P = 0.039). The prediction model constructed based on these factors demonstrated high prediction efficiency (AUC = 0.841; 95% CI: 0.749-0.934). Conclusions:The nomogram model constructed using albumin reduction, rectal tenesmus rating, and DAI score can provide accurate, simple, and low-cost risk prediction of radiation enteritis during TNT for LARC patients. This model facilitates the early clinical identification of high-risk patients, providing a basis for implementing personalized adjustments to radiotherapy regimens and enhancing nutritional interventions.

Objective:To identify the relevant factors for the first-course remission of acute myeloid leukemia (AML) and to develop a predictive model as well as assess its predictive capability.Methods:Clinical data of 749 patients newly diagnosed with AML admitted to the Department of Hematology, the First Affiliated Hospital, Zhejiang University, School of Medicine from January 1, 2019, to April 30, 2023, were collected and randomly divided into training and validation sets. Multivariate logistic regression analysis was conducted to determine variables associated with complete remission in the first course of induction therapy, and a predictive model was established based on these variables. The receiver operating characteristic (ROC) curve of the predictive model was plotted, and the area under the curve (AUC) was calculated.Results:The indicators predicting the first remission course included peripheral blood white blood cell count during onset, CBF::MYH11 fusion gene, CEBPA bZIP region mutation, myelodysplastic syndrome-related gene mutation, and induction chemotherapy regimen selection as independent factors for the first remission course. The model’s area under the training and validation curves was 0.738 (95% CI: 0.696-0.780) and 0.726 (95% CI: 0.650-0.801), respectively. The Hosmer-Lemeshow test results yielded P-values of 0.993 and 0.335, respectively. Conclusion:In this study, the developed model demonstrates a strong predictive capability for the efficacy of the first course of patients with AML, providing valuable guidance to clinicians in assessing patient prognosis and selecting appropriate treatment strategies.

Radiotherapy plays a pivotal role in the treatment of malignant tumors. The emergence of radiation resistance in malignant tumors, contributing to tumor recurrence, progression, or distant metastasis, remains a significant treatment challenge. Exploring the mechanisms underlying radiation resistance and overcoming the radio-resistance of tumors have become urgent problems in oncological practice. Cuproptosis, a copper-dependent form of regulated cell death, is driven by the aggregation of lipoylated proteins and the reduction of Fe-S cluster proteins, etc. Copper and cuproptosis are not only intricately related to the incidence and development of tumors, but also participate in radiation resistance of tumor cells. Strategic interventions targeting copper and inducing cuproptosis will present promising avenues for overcoming radiation resistance and further improving the prognosis of tumor patients. This review comprehensively delineates established and potential mechanisms governing the intricate crosstalk between radiation resistance and cuproptosis, aiming to provide reference for overcoming radiation resistance in malignant tumor cells.

Nowadays, the research on traditional radiomics has gradually matured. However, it usually regards the tumor as a whole, and high-throughput data are often generated in the entire tumor region, which cannot express clear spatial heterogeneity. In order to explore the potential biological information within tumors and realize individualized precise diagnosis and treatment, habitat analysis technology emerges at the historic moment, which provides a new way of thinking to identify tumor microenvironment. On the basis of traditional radiomics, the tumor cell population with similar characteristics is clustered, and the tumor is segmented into multiple sub-regions. Therefore, the study of tumor is no longer limited by the subjective differences of observers in the description of imaging features, and the information of tumor spatial heterogeneity is ideally obtained.