OBJECTIVE: To study the clinical effects of ibrutinib in the treatment of relapsed/refractory diffuse large B-cell lymphoma (RRDLBCL). METHODS: A total of 101 patients with RRDLBCL in Daqing People's Hospital from September 2019 to September 2022 were selected. 45 patients were received ibrutinib monotherapy, 36 patients were received a combination therapy of ibrutinib, rituximab, and lenalidomide, and 20 patients were received a combination therapy of ibrutinib and lenalidomide. The clinical effects were observed. RESULTS: The median duration of treatment for all patients was 4 (2-9) months. The disease control rates(DCR) and objective response rates(ORR) in the ibrutinib monotherapy group were 46.67% and 26.67%, respectively. In the combination therapy group of ibrutinib, rituximab, and lenalidomide, the DCR and ORR were 69.44% and 44.44%, respectively. In the combination therapy group of ibrutinib and lenalidomide, the DCR and ORR were 60.00% and 35.00%, respectively. The DCR and ORR in the combination therapy group of ibrutinib, rituximab, and lenalidomide were significantly higher than those in the ibrutinib monotherapy group (P < 0.05). There were no significant differences in DCR and ORR between the combination therapy group of ibrutinib and lenalidomide and the ibrutinib monotherapy group (P >0.05). The median follow-up time of all patients was 15 (5-35) months, with a median overall survival(OS) of 21.0 (15.8-26.2) months and a median progression-free survival(PFS) of 14.0 (12.1-15.9) months. In the ibrutinib monotherapy group, the median OS and PFS were 15.0 (12.1-17.9) months and 12.0 (11.0-13.0) months, respectively. In the combination therapy group of ibrutinib and lenalidomide, the median OS and PFS were 22.0 (13.3-30.7) months and 16.0 (14.1-19.7) months, respectively. In the combination therapy group of ibrutinib, rituximab, and lenalidomide, the median OS and PFS were 23.0 (19.7-26.3) months and 17.0 (14.8-19.1) months, respectively. The median OS and PFS in the combination therapy group of ibrutinib, rituximab, and lenalidomide were significantly higher than those in the ibrutinib monotherapy group (P < 0.05). There were no significant differences in median OS and PFS between the combination therapy group of ibrutinib and lenalidomide and the combination therapy group of ibrutinib, rituximab, and lenalidomide (P >0.05). Hematological adverse reactions included neutropenia in 14 cases (13.86%), thrombocytopenia in 16 cases (15.84%), and leukopenia in 13 cases (12.87%). Non-hematological adverse reactions mainly included nausea and vomiting in 33 cases (32.67%) and fatigue in 44 cases (43.56%). CONCLUSION Ibrutinib has certain clinical effects and good safety in the treatment of RRDLBCL.
Humans ; Piperidines/therapeutic use* ; Lymphoma, Large B-Cell, Diffuse/drug therapy* ; Adenine/therapeutic use* ; Rituximab/therapeutic use* ; Lenalidomide/therapeutic use* ; Male ; Female ; Middle Aged ; Antineoplastic Combined Chemotherapy Protocols/therapeutic use* ; Adult ; Aged ; Pyrimidines/therapeutic use* ; Pyrazoles/therapeutic use* ; Treatment Outcome

Allergen-specific immunotherapy（AIT） remains the only therapeutic approach with the potential to modify the natural course of allergic rhinitis（AR）. Nevertheless, considerable inter-individual variability exists in patients'responses to AIT. To facilitate more reliable assessment of treatment efficacy, the China Rhinopathy Research Cooperation Group（CRRCG） convened young and middle-aged nasal experts in China to formulate the present consensus. The recommended subjective outcome measures for AIT comprise symptom scores, medication scores, combined symptom and medication scores, quality-of-life assessments, evaluation of disease control, and assessment of comorbidities. Objective indicators may supplement these measures. Currently available objective approaches include skin prick testing, nasal provocation testing, and allergen exposure chambers. However, these methods remain constrained by practical limitations and are not yet appropriate for routine implementation in clinical efficacy evaluation. In addition, several biomarkers, including sIgE and the sIgE/tIgE ratio, sIgG4, serum IgE-blocking activity, IgA, cytokines and chemokines, as well as immune cell surface molecules and their functional activity, have been shown to have associations with AIT outcomes. While these biomarkers may complement subjective assessments, they are subject to significant limitations. Consequently, large-scale multicenter trials and real-world evidence are required to strengthen the evidence base. The present consensus underscores the necessity of integrating patients'subjective experiences with objective testing throughout the treatment process, thereby providing a more comprehensive and accurate framework for efficacy evaluation. Looking forward, future investigations should prioritize the incorporation of multi-omics data and artificial intelligence methodologies, which hold promise for overcoming current limitations in assessment strategies and for advancing both the standardization and personalization of AIT.
Humans ; Allergens/immunology* ; China ; Consensus ; Desensitization, Immunologic ; Immunoglobulin E ; Quality of Life ; Rhinitis, Allergic/therapy* ; Treatment Outcome ; East Asian People

The elevated polyamines, amine-rich molecules with diverse functions in pathophysiology processes, are implicated in contributing to tumorigenesis and progression. Whether and how they affect the efficacy of chemotherapy is incompletely understood. Our screening assays reveal that the supplement with a low dose of spermidine (Spd), one of the polyamines, enhances ferroptosis in prostate cancer cells as evidenced by increased lipid peroxidation and intracellular Fe²⁺ levels in vitro. Combination treatment with Spd and a low dose of ferroptosis inducer erastin synergistically augments anti-tumor efficacy with undetectable toxicity in mice. Analysis of RNA-seq data indicates that heme oxygenase 1 (HMOX1), an enzyme that catalyzes the cleavage of heme to release Fe²⁺, is significantly upregulated in response to Spd and erastin cotreatment. Spd mediated the hypusine modification of the eukaryotic initiation factor 5A (EIF5A) promotes the translation of the nuclear factor erythroid 2-related factor 2 (NRF2), subsequently leading to elevation of HMOX1. Moreover, Spd and erastin significantly inhibit proteasome activity which results in a decrease in proteasomal degradation of NRF2, although many proteasome-related genes are induced either by Spd or Spd plus erastin. Thus, in addition to its pro-oncogenic activity, the supplement of Spd improves antitumor activity in combination with ferroptosis inducers and offers an optional approach to cancer treatment.

Background Occupational stress has emerged as a critical public health concern affecting the physical and mental well-being of workers in the manufacturing sector. However, researchers typically evaluate its core driver—cumulative fatigue—using a crude binary “present/absent” variable, thereby overlooking the high-dimensional complexity and heterogeneity inherent in fatigue characteristics. This oversimplification constrains both the precision and predictive performance of occupational stress risk assessment model. Objective Leveraging a data-driven approach, to survey data on cumulative fatigue among manufacturing employees, and then use this new classification to develop and validate an occupational stress prediction model, with an ultimate aim of enhancing the accuracy and effectiveness of occupational stress assessment. Methods A set of cross-sectional survey data on 3871 manufacturing employees in 2021 were derived from the “Long working hours exposure and its adverse health effect risk assessment” program of the National Institute for Occupational Health and Poison Control, Chinese Center for Disease Control and Prevention. Occupational stress was assessed using the Core Occupational Stress Measurement Scale, while cumulative fatigue was evaluated via the Worker’s Self-Diagnostic Questionnaire for Fatigue Accumulation. Boruta method was applied to screen core variables from 20 occupational stress influencing factors. Dimensionality reduction of cumulative fatigue features was performed using a Bayesian sparse autoencoder (BASE), followed by comparison and application of clustering methods to achieve multi-class classification of the reduced features. Six machine learning classification models were then selected including logistic regression, support vector machine, decision tree, random forest, adaptive boosting, and lightweight gradient boosting machine (LightGBM) to construct and compare two occupational stress prediction models involving cumulative fatigue combined with ten other core variables: one utilizing the original binary cumulative fatigue label as a core variable, and another employing the novel fatigue classification proposed herein as a core variable. Results The positive rate of occupational stress among the manufacturing employees was 38.9%. The Boruta method identified 11 core variables of occupational stress: depressive symptoms, cumulative fatigue, age, length of service, tenure in current position, average weekly working hours, average daily overtime hours, average monthly income, low levels of exercise, life satisfaction, and sleep quality. The BSAE reduced the original cumulative fatigue factors to 12 dimensions, while the K-means clustering grouped the reduced fatigue features into three categories: no fatigue, moderate fatigue, and sever fatigue. Six occupational stress prediction models were constructed using the three-category labels of cumulative fatigue and ten additional factors. The results indicated that the LightGBM model performed best, achieving an area under the curve (AUC) of 0.78, an accuracy of 0.77, and an F1 score of 0.72. Compared with the model incorporating the traditional binary labels for cumulative fatigue, the best prediction AUC (0.72), accuracy (0.66), and F1 score (0.65) improved by 6%, 11%, and 7%, respectively. Conclusion Cumulative fatigue is a significant predictor of occupational stress among manufacturing employees. Applying data dimensionality reduction combined with three-class cluster analysis to characterize cumulative fatigue improves the performance of occupational stress prediction models. From a data-driven perspective, machine learning methods demonstrate strengths in processing complex datasets, capturing nonlinear relationships, and generating predictions based on key variables. This study therefore confirms that refined processing of core factors substantially enhances the predictive capability of machine learning models in assessing occupational stress risk in the manufacturing workforce.

PI3K/AKT/mTOR signaling pathway plays a crucial role in cell proliferation, survival, differentiation, motility and intracellular transport. PI3Kδ, an isoform of PI3K, is highly expressed in B lymphocytes and is involved in the malignant progression of B-cell lymphoma. Thus, PI3Kδ has emerged as an attractive target for the development of anti-B-cell lymphoma drugs. Currently, there are several PI3Kδ inhibitors approved by the FDA for the treatment of B-cell lymphoma, each with its own characteristics, but also with varying degrees of adverse effects in clinical practice. Due to the complexity and diversity of the pathogenesis of B-cell lymphoma, single-target PI3Kδ inhibitors often have limited efficacy and are prone to drug resistance, and need to be combined with chemotherapy or other targeted drugs to enhance their efficacy. The future trend is to design novel inhibitors with higher efficacy and lower toxicity or to develop novel combination regimens with other chemotherapy, radiotherapy, and target drugs to acquire better anti-tumor effects with reduced adverse effects. This review summarizes the PI3Kδ inhibitors that have been approved for the treatment of B-cell lymphoma or are still in clinical trials, mainly focusing on their characteristics, adverse effects and combination regimens.

To investigate the expression and significance of cell surface receptor signaling lymphocyte activation molecule family member 7 (SLAMF7) in normal intestinal tissues and intestinal inflammatory tissues of mice.

Cancer immunotherapy has great potential and is expected to become the mainstream method of cancer treatment.In the current application of cancer immunotherapy,immune checkpoint inhibitors(ICIs)have achieved remarkable results.The cur-rently widely used ICIs in clinical practice include inhibitors targeting cytotoxic T lymphocyte-associated antigen-4(CTLA-4),pro-grammed death-1(PD-1)and programmed death-ligand 1(PD-L1).In addition,new immunotherapies such as oncolytic viruses and chimeric antigen receptor T cells are gradually entering the clinical practice,and combination therapy related to ICIs has shown unique advantages.This article will focus on the current application status of ICIs,oncolytic viruses,and chimeric antigen receptor T cell ther-apies in solid tumors either their individual or combined forms.

Objective To construct a prognostic model for liver hepatocellular carcinoma(LIHC)based on immune-related genes.Methods LIHC and normal tissue samples were downloaded from the UCSC Xena database and The Cancer Genome Atlas(TCGA)database.Differential analysis was performed on the gene data of LIHC samples and adjacent/normal samples.Enrichment analysis was conducted on differentially expressed genes.Kaplan-Meier survival analysis was performed on liver cancer samples from the TCGA cohort to obtain survival-and immune-related differentially expressed genes.LASSO Cox and multivariate Cox regression analysis were used to identify hub genes and construct a gene risk prognostic model.Data from a high-throughput gene expression(GEO)database was obtained for external validation.The sensitivity of hub genes to common anticancer drugs was investigated using the CellMiner database.Results Enrichment analysis result indicated that differentially expressed genes were mainly associated with metabolic pathways.Through differential analysis and Kaplan-Meier survival analysis,25 survival-and immune-related differentially expressed genes were obtained.Based on the result of LASSO Cox and multivariate Cox regression analysis,five hub genes(FYN,CSF3R,HLA-G,FOS,BIRC5)were identified and a nomogram was constructed.The concordance index(C-index)value for the training cohort and validation cohort were 0.739 and 0.625,respectively.Based on the sensitivity of hub genes to anticancer drugs,12 types of anticancer drugs were selected for subsequent experiments.Conclusion This model can effectively predict the prognosis of LIHC patients and provide a new insights for immune therapy in LIHC.

Host cell residue DNA is one of the most common impurity which can affect the safety of biological products,therefore,domestic and international regulatory agencies have required the limit for host cell residue DNA in different biological products,either at the final product qualification or the appropriate intermediate control stage.The removal effect is verified by monitoring the residue DNA of products in different production stages,which is beneficial for assuring the scientificity and stability of the production process.In order to strengthen the understanding of control strategy about host cell residual DNA,the paper reviews progress in host cell residual DNA in biological products by authors'work experience and other's research,which provides reference for future work.

Objective:To explore the relationship between ultrasound characteristics and invasiveness in the follicular variant of papillary thyroid carcinoma (FVPTC), and to integrate multiple ultrasound parameters for visual assessment of predictive outcomes by using Nomogram.Methods:A total of 312 FVPTC patients who were pathologically confirmed through surgery in Zhejiang Cancer Hospital and Zhejiang Provincial People′s Hospital from January 2013 to December 2023 were retrospectively collected.Based on defined criteria, FVPTC patients were categorized into high-invasion and low-invasion groups. The dataset was divided into a training set and a validation set in a ratio of 7 to 3. Clinical information and ultrasound feature parameters were collected. Univariate and multivariate Logistic regression analyses were performed on the training set. A predictive model for FVPTC invasiveness was constructed based on ultrasound features. The model′s discriminative ability and calibration were evaluated in the validation set, and a nomogram was generated.Results:The training set included a total of 218 patients with FVPTC, among which 131 were classified as high invasive.The validation set consisted of 94 patients, with 53 cases of high invasive FVPTC patients. Multivariate logistic regression analysis on the training set revealed that tumor multifocality ( OR=6.505, P=0.016), hypoechoic ( OR=3.235, P=0.103), shape ( OR=0.521, P=0.049), and microcalcifications ( OR=2.479, P=0.004) were independent influencing factors for predicting invasiveness in FVPTC. In the training set, the area under the curve (AUC) of the ultrasound predictive model was 0.704 (95% CI=0.634-0.771), and in the validation set, the AUC was 0.650 (95% CI=0.531-0.770), indicated good discriminative ability.The calibration curve showed good alignment with the ideal curve, demonstrating favorable calibration performance. Conclusions:Ultrasound features provide valuable information for assessing the invasiveness of FVPTC, and the model constructed by combining ultrasound features demonstrates good predictive efficacy for the invasiveness of FVPTC.