Antibody-drug conjugates (ADCs) represent a promising class of targeted cancer therapeutics that combine the specificity of monoclonal antibodies with the potency of cytotoxic payloads. Despite their therapeutic potential, the use of ADCs faces significant challenges, including off/on-target toxicity and resistance development. This review examines the current landscape of ADC development, focusing on the critical aspects of target selection and antibody engineering. We discuss strategies to increase ADC efficacy and safety, including multitarget approaches, pH-dependent antibodies, and masked peptide technologies. The importance of comprehensive antigen expression profiling in both tumor and normal tissues is emphasized, highlighting the role of advanced technologies, such as single-cell sequencing and artificial intelligence, in optimizing target selection. Furthermore, we explore combination therapies and innovations in linker‒payload chemistry, which may provide approaches for expanding the therapeutic window of ADCs. These advances pave the way for the development of more precise and effective cancer treatments, potentially extending ADC applications beyond oncology.
Humans ; Immunoconjugates/adverse effects* ; Neoplasms/immunology* ; Animals ; Antibodies, Monoclonal/therapeutic use* ; Antineoplastic Agents/therapeutic use*

Objective:To prepare decellularized extracellular matrix (dECM)-gelatin methacryloyl (GelMA) composite hydrogels and to study their effects on hepatocyte proliferation.Methods:Hepatic dECM was prepared by elution, and GelMA hydrogel and 10%, 30% and 50% dECM-GelMA composite hydrogels were prepared by pepsin solubilization. The morphology of normal liver and dECM liver was observed by eyes and scanning electron microscopy using hematoxylin-eosin, Sirius red and periodate-Schiff staining, respectively. The internal structure of the dECM-GelMA composite hydrogels was observed by scanning electron microscopy, and the pore diameter was measured. Liver HL-7702 cells were co-cultured with GelMA hydrogel and 10%, 30% and 50% dECM-GelMA composite hydrogels, and the cell proliferation viability was determined by cell counting kit-8. The expression of proliferating cell nuclear antigen (PCNA), Wnt family protein 5a (Wnt5a), β-catenin, extracellular-regulated protein kinase 1/2 (ERK1/2) and phosphorylated ERK1/2 (p-ERK1/2) were detected by Western blotting. Comparisons were made using independent sample t-test or one-factor analysis of variance. Results:After decellularization, the hepatocyte morphology showed rounded depressions, and the extracellular matrix structure was intact. The GelMA hydrogel and 10%, 30% and 50% dECM-GelMA composite hydrogels showed inernally porous structures. The pore diameter increased from (3.06±1.35) μm in the GelMA hydrogel to (16.01±4.02) μm in the 50% dECM-GelMA composite hydrogel. On the 3rd, 5th and 7th day, the relative cell proliferation was higher in the 50% dECM-GelMA composite hydrogel group than that in the GelMA hydrogel group (1.89±0.04 vs 1.53±0.01, 9.36±0.04 vs 3.89±0.09, 7.15±0.27 vs 4.89±0.15, all P<0.05). The relative expression levels of PCNA, Wnt5a, β-catenin, and p-ERK1/2/ERK1/2 proteins in the 50% dECM-GelMA composite hydrogel group were higher than those in the GelMA hydrogel group (2.14±0.04 vs 1.00±0.03, 2.36±0.09 vs 1.00±0.08, 1.45±0.03 vs 1.00±0.04, 1.43±0.04 vs 1.00±0.01, all P<0.05). Conclusions:A dECM-GelMA composite hydrogel can be prepared, which may promote hepatocyte proliferation by upregulating the phosphorylation of ERK1/2 and activating Wnt/β-catenin signaling pathway.

Objective To construct a discharge preparation program for patients after total laryn-gectomy led by specialist nurses and explore its application effects.Methods A multidisciplinary team was established to construct a discharge preparation program for patients after total laryngectomy led by specialist nurses based on Meleis's transition theory.A total of 120 patients who underwent to-tal laryngectomy from April 2023 to October 2024 were selected as the study subjects.A total of 60 patients admitted from April to December 2023 were set as control group,and 60 patients admitted from January to October 2024 were set as intervention group.The intervention group implemented the discharge preparation program for patients after total laryngectomy led by specialist nurses,while the control group received conventional perioperative management after total laryngectomy.The discharge readiness,quality of discharge instruction,and incidence of complications during hospitalization on the day of discharge were compared between the two groups.Additionally,the scores of home health care experience at 1 and 3 months after discharge were compared between the two groups.Results On the day of discharge,the scores of each dimension and the total score of the discharge readinessscale in the intervention group were higher than those in the control group.The scores of the dimensions("Actually received content"and"Discharge instruction skills and effects")and the total score of the Quality of Discharge Instruction Scale in the intervention group were higher than those in the control group,with statistically significant differences(P＜0.05).The total incidence of complications during hospitalization in the intervention group was lower than that in the control group,with a sta-tistically significant difference(P＜0.05).At 1 and 3 months after discharge,the scores of the home health care experience scale in the intervention group were higher than those in the control group,with statistically significant differences(P＜0.05).Conclusion The construction of a dis-charge preparation service program for patients after total laryngectomy led by specialist nurses based on Meleis's transition theory can effectively improve the discharge readiness and quality of discharge instruction of patients undergoing total laryngectomy,reduce the incidence of complications,and im-prove the prognosis and early home health care level.

The traditional Chinese medicine(TCM) industry is a crucial part of China's pharmaceutical sector and plays a strategic role in ensuring public health and promoting economic and social development. In response to the practical demand for high-quality development of the TCM industry, this paper focused on the bottlenecks encountered during the digital and intelligent transformation of TCM production systems. Specifically, it explored technical strategies and methodologies for constructing the best TCM production mode. An innovative artificial intelligence(AI)-centered technical architecture for TCM production was proposed, focusing on key aspects of production management including process modeling, state evaluation, and decision optimization. Furthermore, a series of critical technologies were developed to realize the best TCM production mode. Finally, a novel AI-driven TCM production mode characterized by a closed-loop system of "measurement-modeling-decision-execution" was presented through engineering case studies. This study is expected to provide a technological pathway for developing new quality productive forces within the TCM industry.
Artificial Intelligence ; Drugs, Chinese Herbal ; Medicine, Chinese Traditional/methods* ; Humans

OBJECTIVE: To investigate the expression levels of EZH2 and KMT2D in patients with diffuse large B-cell lymphoma (DLBCL) and their relationship with pathological features. METHODS: 84 patients with DLBCL treated in our hospital from January 2021 to June 2022 were selected as the study subjects, and clinical characteristics such as sex, age and pathological classification of the patients were collected. Immunohistochemistry was used to detecet the expression of KMT2D and EZH2 proteins in tumor tissue cells of the DLBCL patients. The differential expression of KMT2D and EZH2 in subgroups of different sexes, ages, primary sites, clinical stages, Hans subtypes, etc. were compared. The correlation between the expression of KMT2D and EZH2 protein and BCL-6, CD79A was analyzed and validated through the interaction of protein molecular structures. We followed up and recorded the survival status of the patients for 12 months, and analyzed the factors that affect the mortality of DLBCL patients. RESULTS: The positive rate of KMT2D and EZH2 was high (over 95%) in DLBCL patients. There was no significant difference in the expression of EZH2 and KMT2D among subgroups of different sexes, ages and stages (P >0.05). However, patients with different levels of BCL-6 and CD79A expression showed differences in EZH2 and KMT2D expression (P < 0.05). EZH2 and KMT2D were positively correlated with BCL-6 (r =0.391, r =0.332) and CD79A (r =0.309, r =0.258), respectively, and there were interactions in the protein molecular structures. The risk factors for mortality in DLBCL patients include male sex (OR =1.106, 95%CI : 1.082-1.130, P < 0.001), stage II (OR =1.778, 95%CI : 1.567-2.016, P < 0.001), stage IV (OR =2.233, 95%CI : 2.021-2.467, P < 0.001), EZH2 positive (OR =2.762, 95%CI : 1.304-5.850, P =0.008), BCL-6 positive (OR =7.309, 95%CI : 1.340-39.859, P =0.022), age≥74 years (OR =3.080, 95%CI : 1.658-5.723, P < 0.001), and 63-73 years old (OR =2.400, 95%CI : 1.564-3.682, P < 0.001), while KMT2D positive (OR =0.180, 95%CI : 0.054-0.608, P =0.006) and 41-51 years old (OR =0.406, 95%CI : 0.274-0.603, P < 0.001) were factors which could reduce the risk of mortality. CONCLUSION EZH2 and KMT2D are highly expressed in patients with DLBCL, and they are positively correlated with BCL-6 and CD79A, and affect the prognosis of DLBCL patients.
Humans ; Enhancer of Zeste Homolog 2 Protein/metabolism* ; Lymphoma, Large B-Cell, Diffuse/metabolism* ; DNA-Binding Proteins/metabolism* ; Female ; Male ; Middle Aged ; Adult ; Neoplasm Proteins/metabolism* ; Aged ; Immunohistochemistry ; Proto-Oncogene Proteins c-bcl-6/metabolism* ; Prognosis

The development of bone in human body and the maintenance of bone mass in adulthood are regulated by a variety of biological factors. Myocyte enhancer factor 2C (MEF2C), as one of the many factors regulating bone tissue development and balance, has been shown to play a key role in bone development and metabolism. However, there is limited systematic analysis on the effects of MEF2C on bone tissue. This article reviews the role of MEF2C in bone development and metabolism. During bone development, MEF2C promotes the development of neural crest cells (NC) into craniofacial cartilage and directly promotes cartilage hypertrophy. In terms of bone metabolism, MEF2C exhibits a differentiated regulatory model across different types of osteocytes, demonstrating both promoting and other potential regulatory effects on bone formation, with its stimulating effect on osteoclasts being determined. In view of the complex roles of MEF2C in bone tissue, this paper also discusses its effects on some bone diseases, providing valuable insights for the physiological study of bone tissue and strategies for the prevention of bone diseases.
Humans ; MEF2 Transcription Factors/physiology* ; Bone and Bones/metabolism* ; Animals ; Bone Development/physiology* ; Osteogenesis/physiology* ; Myogenic Regulatory Factors/physiology*

Objective:To establish a prognostic model based on endoplasmic reticulum stress-related genes for evaluating the prognosis of patients with renal cell carcinoma.Methods:This study utilized Non-negative Matrix Factorization to identify molecular subgroups based on endoplasmic reticulum stress-related genes and employed Weighted Correlation Network Analysis to determine co-expressed genes associ-ated with these subgroups.A risk prognostic model was constructed using univariate Cox regression analysis and Lasso regression analysis.Preliminary experimental validations were conducted to elucidate the biological functions of model genes in renal cell carcinoma.Results:Two molecular subgroups with distinct survival prognoses were identified,and an intersection of related genes was used to construct a nov-el endoplasmic reticulum stress-related prognostic model.Patients in the high-risk group exhibited significantly poorer overall survival in both the training and validation cohorts.In vivo experiments demonstrated that PCK1,a model gene,could inhibit the proliferation,migra-tion,and invasion of renal cell carcinoma cells.Conclusions:The risk scoring model developed in this study effectively predicts the survival probability of renal cell carcinoma patients and can serve as an independent prognostic indicator.This model offers a new direction for per-sonalized treatment strategies in renal cell carcinoma patients.

Inflammatory response,immunosuppression,and drug sensitivity have been reported to have a significant correlation with the disulfidptosis levels in cancer patients.However,the value of disulfidpto-sis in colorectal cancer therapy remains unclear.Therefore,we classified the CRC cells into different cell types using single-cell sequencing data and cell-specific markers and analyzed their relationship with the cell disulfidptosis level.We found that the high disulfidptosis regions were concentrated in epithelial-like CRC cells.Further exploration using the disulfidptosis and programmed cell death 1 inhibitor therapy treated differential expression genes indicated that CRC patients with high disulfidptosis levels exhibited a lower risk profile and increased sensitivity to immunotherapy.By using the spatial transcriptomic analy-sis,we found that ubiquinol-cytochrome c reductase core protein 1(UQCRC1),a disulfidptosis-related gene,is highly expressed in epithelial-like CRC cells and co-localized with immune-infiltrated tumor re-gions.Additional bioinformatic analyses and experimental validation further confirmed that UQCRC1 was downregulated in CRC tissues.Overexpression of UQCRC1 suppressed CRC cell proliferation and migra-tion.These findings indicate that UQCRC1 is a potential target for CRC diagnosis and treatment.

AIM To study the chemical constituents from Periploca forrestii Schltr and their antitumor activity in vitro.METHODS Silica gel and Sephadex LH-20 were used for isolation and purification,then the structures of obtained compounds were identified by physicochemical properties and spectral data.The in vitro antitumor activity was evaluated by MTT mothod.RESULTS Twenty-four compounds were isolated and identified as lysidicichin(1),fraxidin(2),methoxylatifolone(3),corilagin(4),ligballinol(5),6-dehydroprogesterone(6),anomallenodiol(7),mustakone(8),eupatoricacid(9),honokiol(10),methyl 4-hydroxybenzoate(11),5,6,7,8-tetramethoxycoumarin(12),6,7-dimethoxycoumarin(13),5,6,7,4'-tetramethoxyflavone(14),2,3,2",3"-tetrahydrospirotaxone(15),sequoiavone(16),isocubebin(17),isoquercitrin(18),mellein(19),pistaciamide(20),suberoyltrigone(21)、daucosterol(22)、berchemol(23)、confluentin(24).The IC50 value of compound 18 for lung cancer cell NCI-H596 was(27.41±3.36)μmol/L.CONCLUSION Compounds 1-24 are isolated from P.forrestii for the first time.Compound 18 has good antitumor activity in vitro.

Objective:To identify the risk factors for ascending aortic dilatation and develop a prediction model using LASSO-Logistic regression in patients with normally functioning bicuspid aortic valves（BAV）.Methods:Eight-four adult patients with BAV diagnosed as having normal valve function by transthoracic echocardiography who attended to the General Hospital of Ningxia Medical University between June 2024 and April 2025 were prospectively selected，there were 42 patients with ascending aortic dilatation and 42 patients without dilatation.The patients were divided into a training set（60 cases）and a test set（24 cases）using stratified random sampling at a ratio of 7 to 3 via the R caret package. All subjects underwent transthoracic echocardiography，lipid and plasma matrix metalloproteinases（MMP）and tissue inhibitors（TIMP）levels detection. The inverse probability of treatment weighting（IPTW）method was employed to control for potential confounding factors. LASSO and multifactorial binary Logistic regression was applied to screen the independent risk factors for ascending aortic dilatation of BAV and development a nomogram prediction model. The accuracy，consistency and clinical applicability of the prediction model were evaluated by applying the ROC curve，calibration curve，and decision curve analysis（DCA），respectively.Results:①After adjustment for IPTW，LASSO-Logistic regression analysis identified left ventricular global longitudinal strain（LVGLS）and plasma MMP-2 levels as independent risk factors for ascending aortic dilatation in BAV patients with normal valve function.②The nomogram prediction model constructed based on the above screening features，and the area under the curve（AUC）of ROC for the training set and test set were 0.917 and 0.903，with specificities of 0.867 and 0.917，and sensitivities of 0.933 and 0.916，respectively. ③Calibration curves demonstrated satisfactory alignment，with C-indices of 0.908（95% CI=0.879～0.937）for the training set and 0.903（95% CI=0.874 - 0.932）for the test set. Hosmer-Lemeshow goodness-of-fit tests indicated strong consistency between predicted and observed outcomes，with P-values of 0.138 and 0.750 for the training and test sets，respectively.The DCA curve demonstrated that within a threshold probability range of 0.04 - 0.90 in the test set，the clinical decision-making model provided a higher net benefit rate for patients with BAV. Conclusions:LVGLS absolute value reduction and elevated plasma MMP-2 levels are independent risk factors for predicting ascending aortic dilatation in BAV patients with normal valve function. The prediction model based on LASSO-Logistic regression has good predictive value，providing a scientific basis for clinical decision-making in patients with BAV and aortic diseases.