Primary liver cancer is the second most common cause of cancer-related mortality, and exploring effective cure methods for liver cancer has become a major challenge. Ferroptosis is an iron-dependent pattern of cell death caused by the accumulation of lipid peroxides. The main mechanisms of ferroptosis include iron metabolism disorders, imbalance of the antioxidant system, and accumulation of lipid peroxides. Inducing ferroptosis of hepatoma cells is regarded as a potential therapeutic strategy for liver cancer. This article aims to outline the key regulatory signaling pathways of ferroptosis in the occurrence and development of liver cancer, and to deeply analyze the potential application prospects of the ferroptosis mechanism in the field of liver cancer treatment.

Objective:To identify the clinical characteristics and prognosis of patients with hematological disease and neutropenic sepsis in the hematological intensive care unit (HCU).Methods:A retrospective analysis was conducted on patients with hematological disease and sepsis who admitted to HCU, the First Affiliated Hospital of Harbin Medical University from October 2017 to October 2024, to examine the primary therapeutic options, prognosis, cause of death, and infectious features of sepsis.Results:A total of 245 septic patients were included in the study, comprising 88 cases in the neutropenic sepsis group (neutropenic group) and 157 cases in the non-neutropenic sepsis group (non-neutropenic group). Acute leukemia was more prevalent in the neutropenic group [55.68% (49/88) ]. At the time of admission to the HCU, the neutropenic group exhibited unstable vital signs, lower blood cell counts, higher inflammatory markers, elevated Sequential Organ Failure Assessment (SOFA) scores, increased creatinine levels (120.00 μmol/L vs 77.10 μmol/L, P<0.01), higher total bilirubin levels (24.70 μmol/L vs 17.90 μmol/L, P<0.01), and significantly elevated B-type natriuretic peptide levels (567.90 ng/L vs 134.50 ng/L, P<0.01) compared with the non-neutropenic group. Furthermore, septic shock was more common in the neutropenic group [53.40% (47/88) vs 36.94% (58/157), P<0.05]. The mortality rate was also higher in the neutropenic group [46.59% (41/88) ] compared with the non-neutropenic group [32.48% (51/157) ] ( P<0.05), with septic shock accounting for the majority of deaths [70.73% (29/41) ]. Infections caused by gram-negative bacteria [55.68% (49/88) vs 36.30% (57/157), P<0.01] and fungi [14.77% (13/88) vs 6.36% (10/157), P<0.05] were more common in the neutropenic group. However, lung infections were significantly less frequent in the neutropenic group ( P<0.01). Kaplan-Meier survival analysis revealed a substantially worse 28-day overall survival rate for the neutropenic group compared with the non-neutropenic group ( P<0.05) . Conclusion:Patients with hematological diseases and neutropenic sepsis presented with more severe clinical conditions, a higher likelihood of organ failure and septic shock, and significantly increased mortality compared with patients with non-neutropenic sepsis.

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.

Objective:To investigate the correlation between peri-coronary fat attenuation index (FAI) and plaque formation in patients with myocardial bridge (MB) of the left anterior descending artery (LAD) using coronary computed tomography angiography (CCTA) and to develop an optimal predictive model to explore the potential application of FAI in the primary prevention of MB related atherosclerosis.Methods:In this retrospective study, prediction models associated with perivascular fat inflammation were developed and validated using both logistic regression and machine learning (ML) algorithm. A training dataset was collected from 253 patients who underwent ≥2 coronary computed tomography angiography (CCTA) with ≥3 months intervals from one tertiary hospital from January 2007 to April 2021 and had baseline CCTA showing no plaques in LAD MB. The median follow-up time was 3.2 years. According to the same criteria, a total of 75 LAD MB patients from four other hospitals were included to form an independent external validation dataset, with a median follow-up time of 1.8 years. Receiver operating characteristic (ROC) curve analysis with integrated discrimination improvement (IDI) and category net reclassification index (NRI) were used to compare the performance of the predictive models.Results:62 patients (24.5%) in the training dataset had proximal plaque formation in LAD MB, while 22 patients (29.3%) in the external validation dataset had plaque formation during the follow-up period. Baseline FAI within the longitudinal distance equal to 30 mm proximal to the MB entrance was an independent predictor ( OR=1.068, P=0.046). According to the model results, ROC curves were plotted. The AUC of Model 1 was 0.822, and the AUCs of Model 2 and 1 were 0.821 and 0.591 in the training dataset. After the DeLong test, the AUC of Model 1 was superior to that of Model 2 ( Z=2.839, P=0.005) and Model 1 ( Z=6.124, P<0.001). These findings were further validated in the external validation dataset, where ML-model 3 yielded the best predictive performance, outperforming the logistic regression-based Model 2 (categorical NRI=0.359, P=0.048; IDI=0.108, P=0.046). Conclusion:FAI measured within the 30 mm proximal to the entrance of MBs due to its prone to plaque development is an independent predictor for atherosclerotic plaque formation. The ML-prediction model based on a decision tree algorithm combines FAI, MB anatomical features, and patient risk factors, which is beneficial for patients undergoing routine CCTA examination to identify inflamed coronary arteries in advance and guide the clinical adoption of more targeted preventive treatment, including anti-inflammatory treatment.

Purpose To explore the role and mechanism by which the forkhead box C1(FOXC1)promoter up-stream transcript(FOXCUT)regulates proliferation and invasion of non-small cell lung carcinoma(NSCLC)cells.Methods Bioinformatic analysis and RT-qPCR were used to quantify FOXCUT expression in NSCLC tissues.After FOXCUT knockdown in NSCLC cell lines,cell proliferation was examined using CCK-8 and EdU assays,and invasion was evaluated by Transwell assay.The expression of E-cadherin,vimentin,N-cadherin,and FOXC1 was detected by Western blot.FOXCUT-silenced H460 cells were constructed using lentiviruses and subcutaneously injected into nude mice to observe tumor growth.To rescue FOXC1 expression,an FOXC1 expression plasmid was transfected into FOX-CUT-knockdown cells.LncBook 2.0,ENCORI,and TargetScan databases were queried to predict miRNAs that inter-act with FOXCUT and FOXC1.Results FOXCUT expression was significantly higher in NSCLC tissues than in normal lung tissues(normal:0.24±0.22 vs NSCLC:0.68±0.76,t=5.94,P＜0.001),and patients with high FOXCUT expression had a poorer prognosis(P＜0.01).FOXCUT interference markedly repressed NSCLC cells' proliferation and invasion(P＜0.01).FOXCUT knockdown significantly upregulated E-cadherin and downregulated vimentin and N-cadherin(P＜0.01).In vivo,FOXCUT-silenced cells formed significantly smaller tumors in nude mice(P＜0.01).FOXCUT knockdown markedly reduced FOXC1 expression(P＜0.01).Overexpression of FOXC1 in FOX-CUT-depleted cells rescued cell proliferation(P＜0.01).Bioinformatic analysis identified 8 miRNAs potentially co-regulated by FOXCUT and FOXC1.Conclusion Knockdown of FOXCUT restrains NSCLC cell proliferation and inva-sion,possibly through suppression of FOXC1 expression.

Pancreatic cancer(PC)is a highly malignant digestive system tumor with extremely high mortality and recurrence rates.While traditional surgical resection and chemotherapy remain the main treatment options,challenges such as high postoperative recurrence and poor prognosis persist.Therefore,exploring more effective comprehensive treatment strategies is crucial for improving patient survival and prognosis.This review systematically summarizes recent advances in systemic therapy for PC,with a focus on the application and efficacy of chemotherapy,targeted therapy,and immunotherapy.Additionally,it discusses the potential of neoadjuvant therapy,integrated traditional Chinese and Western medicine approaches,and conversion therapy in enhancing the effects of conventional chemotherapy.Studies have shown that targeted therapy can enhance antigen presentation and reduce side effects,while immune checkpoint inhibitors,cancer vaccines,and adoptive cell immunotherapy help mitigate tumor immune evasion and improve the tumor microenvironment.Despite continuous innovation in treatment approaches,clinical management of PC,particularly for advanced-stage patients,still faces significant challenges.Future research should focus on early diagnosis,precision medicine,and personalized treatment strategies to further improve cure rates and patient survival quality,providing more effective therapeutic options for clinical practice.

Objective:To investigate the correlation between peri-coronary fat attenuation index (FAI) and plaque formation in patients with myocardial bridge (MB) of the left anterior descending artery (LAD) using coronary computed tomography angiography (CCTA) and to develop an optimal predictive model to explore the potential application of FAI in the primary prevention of MB related atherosclerosis.Methods:In this retrospective study, prediction models associated with perivascular fat inflammation were developed and validated using both logistic regression and machine learning (ML) algorithm. A training dataset was collected from 253 patients who underwent ≥2 coronary computed tomography angiography (CCTA) with ≥3 months intervals from one tertiary hospital from January 2007 to April 2021 and had baseline CCTA showing no plaques in LAD MB. The median follow-up time was 3.2 years. According to the same criteria, a total of 75 LAD MB patients from four other hospitals were included to form an independent external validation dataset, with a median follow-up time of 1.8 years. Receiver operating characteristic (ROC) curve analysis with integrated discrimination improvement (IDI) and category net reclassification index (NRI) were used to compare the performance of the predictive models.Results:62 patients (24.5%) in the training dataset had proximal plaque formation in LAD MB, while 22 patients (29.3%) in the external validation dataset had plaque formation during the follow-up period. Baseline FAI within the longitudinal distance equal to 30 mm proximal to the MB entrance was an independent predictor ( OR=1.068, P=0.046). According to the model results, ROC curves were plotted. The AUC of Model 1 was 0.822, and the AUCs of Model 2 and 1 were 0.821 and 0.591 in the training dataset. After the DeLong test, the AUC of Model 1 was superior to that of Model 2 ( Z=2.839, P=0.005) and Model 1 ( Z=6.124, P<0.001). These findings were further validated in the external validation dataset, where ML-model 3 yielded the best predictive performance, outperforming the logistic regression-based Model 2 (categorical NRI=0.359, P=0.048; IDI=0.108, P=0.046). Conclusion:FAI measured within the 30 mm proximal to the entrance of MBs due to its prone to plaque development is an independent predictor for atherosclerotic plaque formation. The ML-prediction model based on a decision tree algorithm combines FAI, MB anatomical features, and patient risk factors, which is beneficial for patients undergoing routine CCTA examination to identify inflamed coronary arteries in advance and guide the clinical adoption of more targeted preventive treatment, including anti-inflammatory treatment.

Pancreatic cancer(PC)is a highly malignant digestive system tumor with extremely high mortality and recurrence rates.While traditional surgical resection and chemotherapy remain the main treatment options,challenges such as high postoperative recurrence and poor prognosis persist.Therefore,exploring more effective comprehensive treatment strategies is crucial for improving patient survival and prognosis.This review systematically summarizes recent advances in systemic therapy for PC,with a focus on the application and efficacy of chemotherapy,targeted therapy,and immunotherapy.Additionally,it discusses the potential of neoadjuvant therapy,integrated traditional Chinese and Western medicine approaches,and conversion therapy in enhancing the effects of conventional chemotherapy.Studies have shown that targeted therapy can enhance antigen presentation and reduce side effects,while immune checkpoint inhibitors,cancer vaccines,and adoptive cell immunotherapy help mitigate tumor immune evasion and improve the tumor microenvironment.Despite continuous innovation in treatment approaches,clinical management of PC,particularly for advanced-stage patients,still faces significant challenges.Future research should focus on early diagnosis,precision medicine,and personalized treatment strategies to further improve cure rates and patient survival quality,providing more effective therapeutic options for clinical practice.

Purpose To explore the role and mechanism by which the forkhead box C1(FOXC1)promoter up-stream transcript(FOXCUT)regulates proliferation and invasion of non-small cell lung carcinoma(NSCLC)cells.Methods Bioinformatic analysis and RT-qPCR were used to quantify FOXCUT expression in NSCLC tissues.After FOXCUT knockdown in NSCLC cell lines,cell proliferation was examined using CCK-8 and EdU assays,and invasion was evaluated by Transwell assay.The expression of E-cadherin,vimentin,N-cadherin,and FOXC1 was detected by Western blot.FOXCUT-silenced H460 cells were constructed using lentiviruses and subcutaneously injected into nude mice to observe tumor growth.To rescue FOXC1 expression,an FOXC1 expression plasmid was transfected into FOX-CUT-knockdown cells.LncBook 2.0,ENCORI,and TargetScan databases were queried to predict miRNAs that inter-act with FOXCUT and FOXC1.Results FOXCUT expression was significantly higher in NSCLC tissues than in normal lung tissues(normal:0.24±0.22 vs NSCLC:0.68±0.76,t=5.94,P＜0.001),and patients with high FOXCUT expression had a poorer prognosis(P＜0.01).FOXCUT interference markedly repressed NSCLC cells' proliferation and invasion(P＜0.01).FOXCUT knockdown significantly upregulated E-cadherin and downregulated vimentin and N-cadherin(P＜0.01).In vivo,FOXCUT-silenced cells formed significantly smaller tumors in nude mice(P＜0.01).FOXCUT knockdown markedly reduced FOXC1 expression(P＜0.01).Overexpression of FOXC1 in FOX-CUT-depleted cells rescued cell proliferation(P＜0.01).Bioinformatic analysis identified 8 miRNAs potentially co-regulated by FOXCUT and FOXC1.Conclusion Knockdown of FOXCUT restrains NSCLC cell proliferation and inva-sion,possibly through suppression of FOXC1 expression.

Primary liver cancer is the second most common cause of cancer-related mortality, and exploring effective cure methods for liver cancer has become a major challenge. Ferroptosis is an iron-dependent pattern of cell death caused by the accumulation of lipid peroxides. The main mechanisms of ferroptosis include iron metabolism disorders, imbalance of the antioxidant system, and accumulation of lipid peroxides. Inducing ferroptosis of hepatoma cells is regarded as a potential therapeutic strategy for liver cancer. This article aims to outline the key regulatory signaling pathways of ferroptosis in the occurrence and development of liver cancer, and to deeply analyze the potential application prospects of the ferroptosis mechanism in the field of liver cancer treatment.