BACKGROUND: T-cell lymphoblastic lymphoma/acute lymphoblastic leukemia (T-LBL/ALL) is an aggressive form of hematological malignancy associated with poor prognosis in adult patients. Histone deacetylases (HDACs) are aberrantly expressed in T-LBL/ALL and are considered potential therapeutic targets. Here, we investigated the antitumor effect of a novel HDAC inhibitor, chidamide, on T-LBL/ALL. METHODS: HDAC1, HDAC2 and HDAC3 levels in T-LBL/ALL cell lines and patient samples were compared with those in normal controls. Flow cytometry, transmission electron microscopy, and lactate dehydrogenase release assays were conducted in Jurkat and MOLT-4 cells to assess apoptosis and pyroptosis. A specific forkhead box O1 (FOXO1) inhibitor was used to rescue pyroptosis and upregulated gasdermin E (GSDME) expression caused by chidamide treatment. The role of the FOXO1 transcription factor was evaluated by dual-luciferase reporter and chromatin immunoprecipitation assays. The efficacy of chidamide in vivo was evaluated in a xenograft mouse. RESULTS: The expression of HDAC1, HDAC2 and HDAC3 was significantly upregulated in T-LBL/ALL. Cell viability was obviously inhibited after chidamide treatment. Pyroptosis, characterized by cell swelling, pore formation on the plasma membrane and lactate dehydrogenase leakage, was identified as a new mechanism of chidamide treatment. Chidamide triggered pyroptosis through caspase 3 activation and GSDME transcriptional upregulation. Chromatin immunoprecipitation assays confirmed that chidamide led to the increased transcription of GSDME through a more relaxed chromatin structure at the promoter and the upregulation of FOXO1 expression. Moreover, we identified the therapeutic effect of chidamide in vivo . CONCLUSIONS This study suggested that chidamide exerts an antitumor effect on T-LBL/ALL and promotes a more inflammatory form of cell death via the FOXO1/GSDME axis, which provides a novel choice of targeted therapy for patients with T-LBL/ALL.
Humans ; Pyroptosis/drug effects* ; Forkhead Box Protein O1/genetics* ; Aminopyridines/pharmacology* ; Animals ; Mice ; Benzamides/pharmacology* ; Cell Line, Tumor ; Precursor T-Cell Lymphoblastic Leukemia-Lymphoma/drug therapy* ; Phosphate-Binding Proteins/metabolism* ; Histone Deacetylase Inhibitors/pharmacology* ; Jurkat Cells ; Histone Deacetylases/metabolism* ; Apoptosis/drug effects* ; Gasdermins

OBJECTIVE: To investigate whether auraptene (AUR) exerts a protective effect on acute diquat (DQ)-induced liver injury in mice and explore its underlying mechanisms. METHODS: Forty SPF-grade healthy male C57BL/6 mice were randomly divided into normal control group (Control group), DQ poisoning model group (DQ group), AUR treatment group (DQ+AUR group), and AUR control group (AUR group), with 10 mice in each group. The DQ poisoning model was established via a single intraperitoneal injection of 40 mg/kg DQ aqueous solution (0.5 mL); Control group and AUR group received an equal volume of pure water intraperitoneally. Four hours post-modeling, DQ+AUR group and AUR group were administered 0.5 mg/kg AUR aqueous solution (0.2 mL) by gavage once daily for 7 consecutive days, while Control group and DQ group received pure water. Blood and liver tissues were collected after anesthesia on day 7. Liver ultrastructure was observed by transmission electron microscopy. Serum alanine aminotransferase (ALT) and aspartate aminotransferase (AST) levels were measured via enzyme-linked immunosorbent assay (ELISA). Hepatic glutathione (GSH), superoxide dismutase (SOD), and malondialdehyde (MDA) levels were detected using WST-1, thiobarbituric acid (TBA), and enzymatic reaction methods, respectively. Protein expression of nuclear factor-erythroid 2-related factor 2 (Nrf2), heme oxygenase-1 (HO-1), Kelch-like ECH-associated protein 1 (Keap1), and activated caspase-9 in liver tissues was analyzed by Western blotting. RESULTS: Transmission electron microscopy revealed that mitochondria in the Control group exhibited mild swelling, uneven distribution of matrix, and a small number of cristae fractures. In the AUR group, mitochondria showed mild swelling, with no obvious disruption of cristae structure. In the DQ group, mitochondria demonstrated marked swelling and increased volume, matrix dissolution, loss and fragmentation of cristae, and extensive vacuolization. In contrast, the DQ+AUR group showed significantly reduced mitochondrial swelling, volume increase, matrix dissolution, cristae loss and fragmentation, and vacuolization compared to the DQ group. Compared with the DQ group, the DQ+AUR group exhibited significantly lower serum AST levels (U/L: 173.45±23.60 vs. 255.33±41.51), ALT levels (U/L: 51.77±21.63 vs. 100.70±32.35), and hepatic MDA levels (μmol/g: 12.40±2.76 vs. 19.74±4.10), along with higher hepatic GSH levels (mmol/g: 37.65±14.95 vs. 20.58±8.52) and SOD levels (kU/g: 124.10±33.77 vs. 82.81±22.00), the differences were statistically significant (all P < 0.05). Western blotting showed upregulated Nrf2 expression (Nrf2/β-actin: 0.87±0.37 vs. 0.53±0.22) and HO-1 expression (HO-1/β-actin: 1.06±0.22 vs. 0.49±0.08), and downregulated Keap1 expression (Keap1/β-actin: 0.82±0.12 vs. 1.52±0.76) and activated caspase-9 expression (activated caspase-9/β-actin: 1.16±0.28 vs. 1.71±0.30) in the DQ+AUR group compared to the DQ group (all P < 0.05). CONCLUSION AUR attenuates DQ-induced acute liver injury in mice by activating the Keap1/Nrf2 signaling pathway.
Animals ; Male ; Mice ; Mice, Inbred C57BL ; Liver/pathology* ; Chemical and Drug Induced Liver Injury/drug therapy* ; Diquat/poisoning* ; NF-E2-Related Factor 2/metabolism* ; Oxidative Stress ; Apoptosis ; Coumarins

Animal models of cardiac arrhythmia are important tools for analyses of antiarrhythmic drug mechanisms and medical laboratory teaching.In this study,two major models,namely,barium chloride-induced arrhythmia in rabbits and ouabain-induced arrhythmia in guinea pigs,were systematically compared in terms of technical principles,modeling method,and indexes.By optimizing electrocardiographic parameters,standardizing arrhythmia grading criteria,and introducing quantitative analysis method,we revealed differences between the two models in terms of ion channel mechanisms,drug targets,and applicability to teaching.The barium chloride model was characterized by rapidly induced ventricular arrhythmia,which is suitable for the observation of acute drug efficacy.The ouabain model simulated the development of progressive arrhythmia,which is suitable for the study of the preventive effects of anti-arrhythmic drugs.This study provides a technical reference for the selection of arrhythmia models,optimization process,and mechanistic analyses in medical experimental teaching and is of great significance for improving the electrophysiology experimental skills of medical students.

Histological staining is the basis of pathological analysis,but the traditional staining method relies on chemical reagents,which not only consumes a lot of resources,but also causes harm to the environment and human health.In recent years,with the rapid development of deep learning technology,virtual staining technology,as a new method,is expected to effectively replace and supplement the traditional histological staining methods.It uses neural networks to analyze unstained tissue images,generate digital images that are highly similar to chemical staining effects,and even realize the mutual conversion between different staining modes,reducing the laboratory's dependence on chemical reagents and providing sustainable research programs.In this paper,the basic principles of virtual staining and its potential applications in histopathology are introduced in detail,and the current challenges and future research directions are discussed.

Objective:To explore the acupoint selection law of acupuncture and moxibustion in the treatment of broca aphasia after stroke.Methods:RCT articles about acupuncture and moxibustion treatment for broca aphasia after stroke were retrieved from CNKI, VIP, Wanfang Data, China Medical Journal Full-text Database, SinoMed, PubMed, Web of Science and Embase database from the establishment of the databases to May 31, 2024. Excel 2021, SPSS Statistics 27.0, SPSS Modeler 18.0 and Cytoscape 3.9.1 software were used to analyze the frequency of acupoint, clustering, association rules and core co-occurrence network.Results:A total of 87 articles were included, involving 100 acupuncture and moxibustion prescriptions and 101 acupoints/acupoint area, involving 6 types, including Lianquan (CV 23) (35 times), Jinjin (EX-HN12) (35 times) and Yuye (EX-HN13) (34 times). The selected acupoints were mainly distributed in the head, face, neck and lower limbs, and the meridians were mainly Governor Vessel and Conception Vessel; the specific acupoints were mainly original acupoints, followed by collaterals acupoints, and scalp acupuncture was used most frequently in special acupuncture (88 times). According to the clustering analysis of high-frequency acupoints/acupoint area, there were five effective groups, such as "Jinjin (EX-HN12)-Yuye (EX-HN13)-Lianquan (CV 23)-Baihui (GV 20)-Yamen (GV 15)". The core co-occurrence network analysis showed that the acupoints used most frequently were Lianquan (CV 23) and Jinjin (EX-HN12), and the highest correlation between the two acupoints was Jinjin (EX-HN12)-Yuye (EX-HN13).Conclusions:Acupuncture and moxibustion for the treatment of broca aphasia after stroke is often based on "awakening the brain as the outline, benefiting the marrow as the foundation, and resuscitation". Under the guidance of the theory of Zang-fu meridians and collaterals, through dredging the meridians and collaterals, tonifying the brain and opening and closing the sound, the recovery of language function can be achieved.

In recent years, with the rapid development of artificial intelligence technology, the application of deep learning in the field of pathology has been continuously expanding. Particularly, the rise of multimodal data fusion methods has opened up new technical paths for the precise diagnosis, prognosis assessment, and individualized treatment of tumors. By integrating multi-level and multi-source data such as clinical information, pathological omics, molecular omics, and imaging omics, deep learning models can identify potential associated features and key biological mechanisms that are difficult to reveal by a single modality, thereby significantly improving the accuracy of disease classification and the scientific nature of risk stratification. This article systematically reviews the research progress of multimodal data fusion methods based on deep learning in the field of pathology in recent years, focuses on sorting out different types of fusion strategies, evaluates their advantages and challenges in practical clinical applications, and looks forward to future development trends.

Animal models of cardiac arrhythmia are important tools for analyses of antiarrhythmic drug mechanisms and medical laboratory teaching.In this study,two major models,namely,barium chloride-induced arrhythmia in rabbits and ouabain-induced arrhythmia in guinea pigs,were systematically compared in terms of technical principles,modeling method,and indexes.By optimizing electrocardiographic parameters,standardizing arrhythmia grading criteria,and introducing quantitative analysis method,we revealed differences between the two models in terms of ion channel mechanisms,drug targets,and applicability to teaching.The barium chloride model was characterized by rapidly induced ventricular arrhythmia,which is suitable for the observation of acute drug efficacy.The ouabain model simulated the development of progressive arrhythmia,which is suitable for the study of the preventive effects of anti-arrhythmic drugs.This study provides a technical reference for the selection of arrhythmia models,optimization process,and mechanistic analyses in medical experimental teaching and is of great significance for improving the electrophysiology experimental skills of medical students.

Histological staining is the basis of pathological analysis,but the traditional staining method relies on chemical reagents,which not only consumes a lot of resources,but also causes harm to the environment and human health.In recent years,with the rapid development of deep learning technology,virtual staining technology,as a new method,is expected to effectively replace and supplement the traditional histological staining methods.It uses neural networks to analyze unstained tissue images,generate digital images that are highly similar to chemical staining effects,and even realize the mutual conversion between different staining modes,reducing the laboratory's dependence on chemical reagents and providing sustainable research programs.In this paper,the basic principles of virtual staining and its potential applications in histopathology are introduced in detail,and the current challenges and future research directions are discussed.

In recent years, with the rapid development of artificial intelligence technology, the application of deep learning in the field of pathology has been continuously expanding. Particularly, the rise of multimodal data fusion methods has opened up new technical paths for the precise diagnosis, prognosis assessment, and individualized treatment of tumors. By integrating multi-level and multi-source data such as clinical information, pathological omics, molecular omics, and imaging omics, deep learning models can identify potential associated features and key biological mechanisms that are difficult to reveal by a single modality, thereby significantly improving the accuracy of disease classification and the scientific nature of risk stratification. This article systematically reviews the research progress of multimodal data fusion methods based on deep learning in the field of pathology in recent years, focuses on sorting out different types of fusion strategies, evaluates their advantages and challenges in practical clinical applications, and looks forward to future development trends.

Innovation is an important way to promote economic development and social progress. Recent years have seen rapid development of biological sciences. In response to social demands and the needs for developing an innovative country, fostering innovative talents in the field of biosciences has become a significant initiative supported by national policies and the needs from talent market. Taking the innovative talent training mode implemented by Zhejiang Normal University in the field of biological sciences as an example, this paper comprehensively introduces several key aspects of the mode. This includes establishing a mentorship system as the foundation, carrying out curriculum reform through project competitions and practical platforms, and promoting synergy among industry, academia, and research in talent training. This training mode has achieved positive results in practice, promoting the training of outstanding innovative talents in biological science majors, and may facilitate the reform of talent training in similar majors.
Humans ; Biological Science Disciplines ; Industry ; Policy ; Universities