The concept of "qi deficiency with stagnation" refers to a pathological state characterized by the depletion of primordial qi， impaired qi transformation， and the development of internal stagnation. Under the cyclic chemotherapy regimen in oncology， chemotherapy-induced myelosuppression follows a progressive pathological course from qi deficiency to increasing stagnation. This sequential evolution from mild to severe myelosuppression closely aligns with the dynamic syndrome differentiation and treatment framework of "qi deficiency with stagnation". "Qi deficiency" reflects the gradual depletion of qi， blood， and essence， while "stagnation" refers to the accumulation of phlegm， turbid dampness， and blood stasis. These two components interact reciprocally， forming a vicious cycle where deficiency leads to stagnation， and stagnation further damages the healthy qi. In the early stage of mild myelosuppression， chemotoxicity begins to accumulate in the bone marrow， leading to qi consumption， blood deficiency， yin injury， and the gradual formation of turbid phlegm and damp stagnation. In the advanced stage of severe myelosuppression， the accumulation of toxicity causes qi sinking， exhaustion of essence， and marrow depletion， along with blood stasis obstructing the collaterals. Treatment strategies should be based on syndrome differentiation， with an emphasis on assessing the severity of the condition， balancing deficiency and excess， and achieving both symptomatic relief and root cause resolution.

Neutrophil extracellular traps (NETs), intricate reticular structures released by activated neutrophils, play a pivotal regulatory role in the pathogenesis of malignant tumors. Lung cancer is one of the most prevalent malignancies globally, with persistently high incidence and mortality rates. Recent studies have revealed that NETs dynamically modulate the tumor microenvironment through unique pathological mechanisms, exhibiting complex immunoregulatory characteristics during the progression of lung cancer, and this discovery has increasingly become a focal point in tumor immunology research. This paper provides a comprehensive review of the latest advancements in NETs research related to lung cancer, offering an in-depth analysis of their impact on lung cancer progression, their potential diagnostic value, and the current state of research on targeting NETs for lung cancer prevention and treatment. The aim is to propose novel strategies to enhance therapeutic outcomes and improve the prognosis for lung cancer patients.
.
Extracellular Traps/immunology* ; Humans ; Lung Neoplasms/metabolism* ; Neutrophils/metabolism* ; Animals ; Tumor Microenvironment

BACKGROUND: Biomarkers-based prediction of long-term risk of acute coronary syndrome (ACS) is scarce. We aim to develop a risk score integrating clinical routine information (C) and plasma biomarkers (B) for predicting long-term risk of ACS patients. METHODS: We included 2729 ACS patients from the OCEA (Observation of cardiovascular events in ACS patients). The earlier admitted 1910 patients were enrolled as development cohort; and the subsequently admitted 819 subjects were treated as validation cohort. We investigated 10-year risk of cardiovascular (CV) death, myocardial infarction (MI) and all cause death in these patients. Potential variables contributing to risk of clinical events were assessed using Cox regression models and a score was derived using main part of these variables. RESULTS: During 16,110 person-years of follow-up, there were 238 CV death/MI in the development cohort. The 7 most important predictors including in the final model were NT-proBNP, D-dimer, GDF-15, peripheral artery disease (PAD), Fibrinogen, ST-segment elevated MI (STEMI), left ventricular ejection fraction (LVEF), termed as CB-ACS score. C-index of the score for predication of cardiovascular events was 0.79 (95% CI: 0.76-0.82) in development cohort and 0.77 (95% CI: 0.76-0.78) in the validation cohort (5832 person-years of follow-up), which outperformed GRACE 2.0 and ABC-ACS risk score. The CB-ACS score was also well calibrated in development and validation cohort (Greenwood-Nam-D'Agostino: P = 0.70 and P = 0.07, respectively). CONCLUSIONS CB-ACS risk score provides a useful tool for long-term prediction of CV events in patients with ACS. This model outperforms GRACE 2.0 and ABC-ACS ischemic risk score.

OBJECTIVE: To investigate the effectiveness of Xuanshen Yishen Decoction (XYD) in the treatment of hypertension. METHODS: Hospital electronic medical records from 2019-2023 were utilized to emulate a randomized pragmatic clinical trial. Hypertensive participants were eligible if they were aged ⩾40 years with baseline systolic blood pressure (BP) ⩾140 mm Hg. Patients treated with XYD plus antihypertensive regimen were assigned to the treatment group, whereas those who followed only antihypertensive regimen were assigned to the control group. The primary outcome assessed was the attainment rate of intensive BP control at discharge, with the secondary outcome focusing on the 6-month all-cause readmission rate. RESULTS: The study included 3,302 patients, comprising 2,943 individuals in the control group and 359 in the treatment group. Compared with the control group, a higher proportion in the treatment group achieved the target BP for intensive BP control [8.09% vs. 17.5%; odds ratio (OR)=2.29, 95% confidence interval (CI)=1.68 to 3.13; P<0.001], particularly in individuals with high homocysteine levels (OR=3.13; 95% CI=1.72 to 5.71; P<0.001; P for interaction=0.041). Furthermore, the 6-month all-cause readmission rate in the treatment group was lower than in the control group (hazard ratio=0.58; 95% CI=0.36 to 0.91; P=0.019), and the robustness of the results was confirmed by sensitivity analyse. CONCLUSIONS XYD could be a complementary therapy for intensive BP control. Our study offers real-world evidence and guides the choice of complementary and alternative therapies. (Registration No. ChiCTR2400086589).
Adult ; Aged ; Female ; Humans ; Male ; Middle Aged ; Antihypertensive Agents/pharmacology* ; Blood Pressure/drug effects* ; Drugs, Chinese Herbal/pharmacology* ; Hypertension/physiopathology* ; Patient Readmission ; Treatment Outcome

This study explores the effect and mechanism of Banxia Xiexin Decoction(BXD) in inhibiting colon cancer progression by reshaping tryptophan metabolism. Balb/c mice were assigned into control, model, low-dose BXD(BXD-L), and high-dose BXD(BXD-H) groups. Except the control group, the other groups were subcutaneously injected with CT26-Luc cells for the modeling of colon cancer, which was followed by the intervention with BXD. Small animal live imaging was employed to monitor tumor growth, and the tumor volume and weight were measured. Hematoxylin-eosin(HE) staining was used to observe the pathological changes in mouse tumors. Immunohistochemistry was used to detect Ki67 expression in tumors. Immunofluorescence and flow cytometry were used to detect the infiltration and number changes of CD3~+/CD8~+ T cells in the tumor tissue. Enzyme-linked immunosorbent assay(ELISA) was employed to measure the levels of interferon-gamma(IFN-γ) and interleukin-2(IL-2) in tumors. Targeted metabolomics was employed to measure the level of tryptophan(Trp) in the serum, and the Trp content in the tumor tissue was measured. Western blot and RT-qPCR were employed to determine the protein and mRNA levels, respectively, of indoleamine 2,3-dioxygenase 1(IDO1), MYC proto-oncogene, and solute carrier family 7 member 5(SLC7A5) in the tumor tissue. Additionally, a co-culture model with CT26 cells and CD8~+ T cells was established in vitro and treated with the BXD-containing serum. The cell counting kit-8(CCK-8) assay was used to examine the viability of CT26 cells. The content of Trp in CT26 cells and CD8~+ T cells, as well as the secretion of IFN-γ and IL-2 by CD8~+ T cells, was measured. RT-qPCR was used to determine the mRNA levels of MYC and SLC7A5 in CT26 cells. The results showed that BXD significantly inhibited the tumor growth, reduced the tumor weight, and decreased the tumor volume in the model mice. In addition, the model mice showed sparse arrangement of tumor cells, varying degrees of patchy necrosis, and downregulated expression of Ki67 in the tumor tissue. BXD elevated the levels of IFN-γ and IL-2 in the tumor tissue, while upregulating the ratio of CD3~+/CD8~+ T cells and lowering the levels of Trp, IDO1, MYC, and SLC7A5. The co-culture experiment showed that BXD-containing serum reduced Trp uptake by CT26 cells, increased Trp content in CD8~+T cells, enhanced IL-2 and IFN-γ secretion of CD8~+T cells, and down-regulated the mRNA levels of MYC and SLC7A5 in CT26 cells. In summary, BXD can inhibit the MYC/SLC7A5 pathway to reshape Trp metabolism and adjust Trp uptake by CD8~+ T cells to enhance the cytotoxicity, thereby inhibiting the development of colon cancer.
Animals ; Tryptophan/metabolism* ; Colonic Neoplasms/pathology* ; Mice ; Drugs, Chinese Herbal/administration & dosage* ; Mice, Inbred BALB C ; Humans ; Cell Line, Tumor ; Indoleamine-Pyrrole 2,3,-Dioxygenase/metabolism* ; Female ; Disease Progression ; Cell Proliferation/drug effects* ; Proto-Oncogene Mas ; Male

Transformer models have emerged as pivotal tools within the realm of drug discovery,distinguished by their unique architectural features and exceptional performance in managing intricate data landscapes.Leveraging the innate capabilities of transformer architectures to comprehend intricate hierarchical dependencies inherent in sequential data,these models showcase remarkable efficacy across various tasks,including new drug design and drug target identification.The adaptability of pre-trained trans-former-based models renders them indispensable assets for driving data-centric advancements in drug discovery,chemistry,and biology,furnishing a robust framework that expedites innovation and dis-covery within these domains.Beyond their technical prowess,the success of transformer-based models in drug discovery,chemistry,and biology extends to their interdisciplinary potential,seamlessly combining biological,physical,chemical,and pharmacological insights to bridge gaps across diverse disciplines.This integrative approach not only enhances the depth and breadth of research endeavors but also fosters synergistic collaborations and exchange of ideas among disparate fields.In our review,we elucidate the myriad applications of transformers in drug discovery,as well as chemistry and biology,spanning from protein design and protein engineering,to molecular dynamics(MD),drug target iden-tification,transformer-enabled drug virtual screening(VS),drug lead optimization,drug addiction,small data set challenges,chemical and biological image analysis,chemical language understanding,and single cell data.Finally,we conclude the survey by deliberating on promising trends in transformer models within the context of drug discovery and other sciences.

Glioma, the most prevalent primary tumor of the central nervous system (CNS), is also the most lethal primary malignant tumor. Currently, there are limited chemotherapeutics available for glioma treatment, necessitating further research to identify and develop new chemotherapeutic agents. A significant approach to discovering anti-glioma drugs involves isolating antitumor active ingredients from natural products (NPs) and optimizing their structures. Additionally, targeted drug delivery systems (TDDSs) are employed to enhance drug solubility and stability and overcome the blood-brain barrier (BBB). TDDSs can penetrate deep into the brain, increase drug concentration and retention time in the CNS, and improve the targeting efficiency of NPs, thereby reducing adverse effects and enhancing anti-glioma efficacy. This paper reviews the research progress of anti-glioma activities of NPs, including alkaloids, polyphenols, flavonoids, terpenoids, saponins, quinones, and their synthetic derivatives over the past decade. The review also summarizes anti-glioma mechanisms, such as suppression of related protein expression, regulation of reactive oxygen species (ROS) levels, control of apoptosis signaling pathways, reduction of matrix metalloproteinases (MMPs) expression, blocking of vascular endothelial growth factor (VEGF), and reversal of immunosuppression. Furthermore, the functions and advantages of NP-based TDDSs in anti-glioma therapy are examined. The key information presented in this review will be valuable for the research and development of NP-based anti-glioma drugs and related TDDSs.
Humans ; Glioma/metabolism* ; Biological Products/therapeutic use* ; Animals ; Brain Neoplasms/genetics* ; Drug Delivery Systems ; Antineoplastic Agents/therapeutic use* ; Blood-Brain Barrier/metabolism* ; Apoptosis/drug effects*

Transformer models have emerged as pivotal tools within the realm of drug discovery, distinguished by their unique architectural features and exceptional performance in managing intricate data landscapes. Leveraging the innate capabilities of transformer architectures to comprehend intricate hierarchical dependencies inherent in sequential data, these models showcase remarkable efficacy across various tasks, including new drug design and drug target identification. The adaptability of pre-trained transformer-based models renders them indispensable assets for driving data-centric advancements in drug discovery, chemistry, and biology, furnishing a robust framework that expedites innovation and discovery within these domains. Beyond their technical prowess, the success of transformer-based models in drug discovery, chemistry, and biology extends to their interdisciplinary potential, seamlessly combining biological, physical, chemical, and pharmacological insights to bridge gaps across diverse disciplines. This integrative approach not only enhances the depth and breadth of research endeavors but also fosters synergistic collaborations and exchange of ideas among disparate fields. In our review, we elucidate the myriad applications of transformers in drug discovery, as well as chemistry and biology, spanning from protein design and protein engineering, to molecular dynamics (MD), drug target identification, transformer-enabled drug virtual screening (VS), drug lead optimization, drug addiction, small data set challenges, chemical and biological image analysis, chemical language understanding, and single cell data. Finally, we conclude the survey by deliberating on promising trends in transformer models within the context of drug discovery and other sciences.

The prevention and control of emerging and reemerging infectious diseases are crucial for national biosecurity, and surveillance and reporting of pneumonia of unknown etiology are main ways for the early detection of these diseases and mitigation of their severity. This paper summaries the surveillance methods for pneumonia of unknown etiology and emerging and reemerging infectious diseases globally, indicating that such surveillance is mainly conducted based on hospital. Western countries primarily combine active and passive surveillance while utilizing artificial intelligence technology to rapidly identify cases. China mainly use passive surveillance based on the surveillance system for pneumonia of unknown etiology, with the function of early warning in the identification of emerging infectious diseases, such as avian influenza. However, with the improvement in the surveillance system operation, the overlap with other surveillance disease systems, such as influenza, has occurred, and the improvements in case definition and operational protocol are needed. It is recommended to improve the specificity of the case definition, strenthen training in hospital staff, inclduing clinical workers and office workers, and formulate incentive mechanisms. It is necessary to emphasize the responsibility of clinicians as the main force for the detection and reporting of pneumonia of unknown etiology and emerging infectious diseases, improve the appilication of artifical intelligent technique and conduct multi-source surveillance, such as third-party testing.