Mechanism of Zhengsui Wan in the Treatment of Acute Lymphoblastic Leukemia Based on Network Pharmacology and Experimental Validation.

Background: Zhengsui Wan (ZSW) is a commonly used traditional Chinese medicine formula for treating Acute Lymphatic Leukemia (ALL) in our institution, and it has shown potential efficacy. However, its mechanism of action (MoA) remains unclear. In this study, we systematically explored the ZSW in ALL (in vitro and in vivo) using network pharmacology and molecular docking techniques.

Association of baseline plasma D-dimer and platelets with progression-free survival in patients with stage IV non-small cell lung cancer treated with anti-PD-1 antibody.

Background: In past studies, peripheral blood D-dimer and platelets have shown predictive value in the treatment of non-small cell lung cancer (NSCLC). However, it remains unclear whether pretreatment D-dimer and platelets can serve as biomarkers for predicting efficacy and prognosis in stage IV NSCLC patients without driver gene mutations receiving programmed cell death protein 1 (PD-1) antibody. Therefore, this study aims to investigate the correlation between baseline D-dimer and platelet levels and the efficacy and prognosis in the study population, aiding in determining the significance of baseline D-dimer and platelet levels as biomarkers.

Web-based prediction models for predicting overall survival and cancer specific survival in lung metastasis of patients with thyroid cancer: a study based on the SEER database and a Chinese cohort.

The current high incidence of thyroid cancer (TC) is usually accompanied by poor prognosis of patients who also develop lung metastasis. Therefore, the present study aimed to develop a survival prediction model to guide clinical decision-making. This study retrospectively analyzed 679 patients with TCLM from 2010 to 2015 using the Surveillance, Epidemiology, and End Results (SEER) database.

From pixels to patients: the evolution and future of deep learning in cancer diagnostics.

Deep learning has revolutionized cancer diagnostics, shifting from pixel-based image analysis to more comprehensive, patient-centric care. This opinion article explores recent advancements in neural network architectures, highlighting their evolution in biomedical research and their impact on medical imaging interpretation and multimodal data integration. We emphasize the need for domain-specific artificial intelligence (AI) systems capable of handling complex clinical tasks, advocating for the development of multimodal large language models that can integrate diverse data sources.

Investigating the impact of non-standard positioning on the accuracy of skull tracking algorithms using dual-panel imaging systems.

Objective: This study investigates the impact of non-standard positioning on the accuracy of 6D-skull tracking using dual-panel imaging systems. It explores whether positioning patients' heads at various angles during intracranial lesion treatment affects the accuracy of the CyberKnife 6D-skull tracking system.

Materials And Methods: A heterogeneous density skull phantom was used to simulate various patient skull positioning angles.

T. pallidum achieves immune evasion by blocking autophagic flux in microglia through hexokinase 2.

Increasing evidence suggests that immune cell clearance is closely linked to cellular metabolism. Neurosyphilis, a severe neurological disorder caused by Treponema pallidum (T. pallidum) infection, significantly impacts the brain.

PD-L1 expression and immune infiltration across molecular subtypes of endometrial cancer: An integrative-analysis of molecular classification and immune subtypes.

The immune subtypes of the tumor microenvironment in endometrial cancer (EC), associated with different molecular classifications, warrant further investigation to guide EC immunotherapy strategies. This study focused on programmed death-ligand 1 (PD-L1) expression (Clone SP263) and immune cell (IC) markers (CD3, CD8, CD68, CD20, CD21) in 110 EC cases. In this cohort, the molecular subtype distribution was: POLE mutation (POLEmut) 7.

Nanomaterials for the Diagnosis and Treatment of Triple-Negative Breast Cancer.

In recent years, the diagnosis and treatment at the early stages significantly raise the survival rate of breast cancer patients. Moreover, antibody drugs pave the way toward precision target therapy. However, the treatment and survival of triple-negative breast cancer (TNBC) patients is still worrying, which needs further understanding and study.

Multiomics reveals tumor microenvironment remodeling in locally advanced gastric and gastroesophageal junction cancer following neoadjuvant immunotherapy and chemotherapy.

Background: Perioperative chemotherapy is the standard of care for patients with locally advanced gastric and gastroesophageal junction cancer. Recent evidence demonstrated the addition of programmed cell death protein 1 (PD-1) inhibitors enhanced therapeutic efficacy. However, the mechanisms of response and resistance remain largely undefined.

Bone marrow stromal cells protect myeloma cells from ferroptosis through GPX4 deSUMOylation.

Bone marrow stromal cells (BMSCs) are vital for preventing chemotherapy induced apoptosis of multiple myeloma (MM), but roles and machinery in other forms of cell death have not been well elucidated. Here, using an in vitro BMSC-MM interacting model, we observed BMSCs protected MM cells from labile iron pool (LIP) and reactive oxygen species (ROS) triggered ferroptosis by elevating glutathione peroxidase 4 (GPX4). Mechanistically, direct interaction with BMSCs upregulated the expression of SUMO-specific protease 3 (SENP3) in MM cells through CD40/CD40L signaling pathway, and SENP3 de-conjugated SUMO2 at lysine 75 residue to stabilize GPX4 protein, thereby consuming ROS to obviate ferroptosis in MM cells from the Vk∗MYC mouse model, as well as in CD138B220 cells separated from the Cd40l;Prx1 mice (CD40-CKO) and Sumo2 knock out (SUMO2-KO) mice.

Osimertinib exacerbates immune checkpoint inhibitor-related severe adverse events by activating the IL-6/JAK/STAT3 pathway in macrophages.

Objective: The combination of epithelial growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs) and immune checkpoint inhibitors (ICIs) leads to an increased incidence of severe immune-related adverse events (irAEs). However, the mechanisms underlying macrophages in irAEs have not been elucidated.

Methods: An osimertinib and ICI-induced irAE mouse model was constructed.

Analysis of factors influencing the efficacy of NAC and prognosis between HER2-zero and HER2-low HR negative breast cancer.

The aim of this paper was to assess the differences in clinicopathological characteristics, efficacy and prognosis of neoadjuvant chemotherapy (NAC) in human epidermal growth factor receptor2(HER2)-zero and HER2-low hormone receptor (HR)-negative breast cancer (BC) patients, and the impact of HER2-evolution on prognosis before and after NAC. 319 triple negative breast cancer (TNBC) patients who completed NAC and surgery from August 2014 to August 2018 at Tianjin Medical University Cancer Institute and Hospital were included. Clinicopathological features, efficacy of NAC and assessment of prognosis were retrospectively analysed.

Efficacy and Safety of Polatuzumab Vedotin Plus Rituximab, Cyclophosphamide, Doxorubicin and Prednisone for Previously Untreated Diffuse Large B-Cell Lymphoma: A Real-World, Multi-Center, Retrospective Cohort Study.

Polatuzumab vedotin plus R-CHP (Pola-R-CHP) is approved as a new standard first-line therapy for diffuse large B-cell lymphoma (DLBCL) based on the POLARIX trial. However, real-world data on its efficacy and safety in unselected patients is lacking. We conducted a retrospective cohort study to evaluate Pola-R-CHP versus R-CHOP outcomes in routine clinical practice in China.

Interpretable multi-modal artificial intelligence model for predicting gastric cancer response to neoadjuvant chemotherapy.

Neoadjuvant chemotherapy assessment is imperative for prognostication and clinical management of locally advanced gastric cancer. We propose an incremental supervised contrastive learning model (iSCLM), an interpretable artificial intelligence framework integrating pretreatment CT scans and H&E-stained biopsy images, for improved decision-making regarding neoadjuvant chemotherapy. We have constructed and tested iSCLM using retrospective data from 2,387 patients across 10 medical centers and evaluated its discriminative ability in a prospective cohort (132 patients; ChiCTR2300068917).

[Progress in the Study of Mechanisms Clinically Relevant to Insulin Resistance and Lung Cancer].

At present, the incidence and mortality rates of lung cancer rank top among malignant tumors. The early diagnosis, treatment and drug resistance of lung cancer still remain as problems in the management of lung cancer. Researchers are dedicated to identifying reliable biomarkers as predictive indicators or effective therapeutic targets for lung cancer.

Comparison of MRI and Ultrasound for Evaluation of Axillary Lymph Node Status in Early Breast Cancer.

Introduction: This study aimed to compare the diagnostic accuracy of ultrasound (US) and magnetic resonance imaging (MRI) in evaluating axillary lymph nodes (ALNs) status in breast cancer patients.

Methods: We retrospectively analyzed 590 female breast cancer patients who had undergone both ultrasound and MRI to assess ALNs prior to any invasive procedures. Using pathological results as the standard, we compared the diagnostic performance of the two imaging modalities.

Prediction of Neoadjuvant Chemoradiotherapy Sensitivity in Patients With Esophageal Squamous Cell Carcinoma Using CT-Based Radiomics Combined With Clinical Features.

For patients with resectable locally advanced esophageal squamous cell carcinoma (ESCC), the current standard treatment is neoadjuvant chemoradiotherapy (nCRT) plus radical surgery. This study aimed to establish a predictive model, based on computed tomography (CT) radiomics features and clinical parameters, to predict sensitivity to nCRT in patients with ESCC pre-treatment. The goal was to provide risk stratification and decision-making recommendations for clinical treatments and offer more valuable information for developing personalized therapies.