Glycosyl Radical-Based Synthesis of -Alkyl Glycosides Bearing a Cyclopropane via a Deoxygenative Giese Addition-Reduction-Cyclization Cascade.

We have developed a glycosyl radical-based synthesis of -alkyl glycosides through a deoxygenative Giese addition-reduction-cyclization cascade, in which readily available 1-hydroxy carbohydrates serve as precursors for glycosyl radicals and aryl alkenes function as radical acceptors. This reaction not only provides an effective method for accessing a previously underexplored class of functionalized cyclopropanes but also enhances the application of Giese addition in the synthesis of -alkyl glycosides by derivatizing the radical intermediate generated through polar cyclization to yield a cyclopropane.

Targeted Drug Screening Leveraging Senescence-Induced T-Cell Exhaustion Signatures in Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) is the sixth most prevalent cancer and a leading cause of cancer-related mortality globally, with most patients diagnosed at advanced stages and facing limited early treatment options. This study aimed to identify characteristic genes associated with T-cell exhaustion due to senescence in hepatocellular carcinoma patients, elucidating the interplay between senescence and T-cell exhaustion. We constructed prognostic models based on five signature genes (ENO1, STMN1, PRDX1, RAN, and RANBP1) linked to T-cell exhaustion, utilizing elastic net regression.

Study on chemical constituents and antioxidant activities of L.

Objective: is a plant that holds high value in terms of its edibility, medicinal properties, and ornamental appeal. Creating no sense he aim of this study was to evaluate the antioxidant and antitumor properties of extracts derived from various parts of the carnation plant. Metabolomics technology was employed to identify the primary chemical constituents.

Development and Evaluation of a Retrieval-Augmented Large Language Model Framework for Ophthalmology.

Importance: Although augmenting large language models (LLMs) with knowledge bases may improve medical domain-specific performance, practical methods are needed for local implementation of LLMs that address privacy concerns and enhance accessibility for health care professionals.

Objective: To develop an accurate, cost-effective local implementation of an LLM to mitigate privacy concerns and support their practical deployment in health care settings.

Design, Setting, And Participants: ChatZOC (Sun Yat-Sen University Zhongshan Ophthalmology Center), a retrieval-augmented LLM framework, was developed by enhancing a baseline LLM with a comprehensive ophthalmic dataset and evaluation framework (CODE), which includes over 30 000 pieces of ophthalmic knowledge.

Cervical cancer subtype identification and model building based on lipid metabolism and post-infection microenvironment immune landscape.

Background: As the second most common gynecological cancer, cervical cancer (CC) seriously threatens women's health. The poor prognosis of CC is closely related to the post-infection microenvironment (PIM). This study investigated how lipid metabolism-related genes (LMRGs) affect CC PIM and their role in diagnosing CC.

Identification of potential drug targets for allergic diseases from a genetic perspective: A mendelian randomization study.

Background: Allergic diseases typically refer to a heterogeneous group of conditions primarily caused by the activation of mast cells or eosinophils, including atopic dermatitis (AD), allergic rhinitis (AR), and asthma. Asthma, AR, and AD collectively affect approximately one-fifth of the global population, imposing a significant economic burden on society. Despite the availability of drugs to treat allergic diseases, they have been shown to be insufficient in controlling relapses and halting disease progression.

Single-cell and bulk RNA-sequencing analysis to predict the role and clinical value of CD36 in lung squamous cell carcinoma.

The majority of patients with lung squamous cell carcinoma are diagnosed at an advanced stage, which poses a challenge to the efficacy of chemotherapy. Therefore, the search for an early biomarker needs to be addressed. CD36 is a scavenger receptor expressed in various cell types.

Stemness signature and targeted therapeutic drugs identification for Triple Negative Breast Cancer.

Triple-negative breast cancer (TNBC) is the most aggressive subtype of breast cancer and carries the worst prognosis, characterized by the lack of progesterone, estrogen, and HER2 gene expression. This study aimed to analyze cancer stemness-related gene signature to determine patients' risk stratification and prognosis feature with TNBC. Here one-class logistic regression (OCLR) algorithm was applied to compute the stemness index of TNBC patients.

Application of Novel Transcription Factor Machine Learning Model and Targeted Drug Combination Therapy Strategy in Triple Negative Breast Cancer.

Transcription factors (TFs) have been shown to play a key role in the occurrence and development of tumors, including triple-negative breast cancer (TNBC), with a worse prognosis. Machine learning is widely used for establishing prediction models and screening key tumor drivers. Current studies lack TF integration in TNBC, so targeted research on TF prognostic models and targeted drugs is beneficial to improve clinical translational application.

DeepFundus: A flow-cytometry-like image quality classifier for boosting the whole life cycle of medical artificial intelligence.

Medical artificial intelligence (AI) has been moving from the research phase to clinical implementation. However, most AI-based models are mainly built using high-quality images preprocessed in the laboratory, which is not representative of real-world settings. This dataset bias proves a major driver of AI system dysfunction.

Application of Artificial Intelligence in Precision Medicine for Diabetic Macular Edema.

Diabetic macular edema (DME) is the primary cause of central vision impairment in patients with diabetes and the leading cause of preventable blindness in working-age people. With the advent of optical coherence tomography and antivascular endothelial growth factor (anti-VEGF) therapy, the diagnosis, evaluation, and treatment of DME were greatly revolutionized in the last decade. However, there is tremendous heterogeneity among DME patients, and 30%-50% of DME patients do not respond well to anti-VEGF agents.

Integrating Single-cell RNA-seq to construct a Neutrophil prognostic model for predicting immune responses in non-small cell lung cancer.

Non-small cell lung cancer (NSCLC) is the most widely distributed tumor in the world, and its immunotherapy is not practical. Neutrophil is one of a tumor's most abundant immune cell groups. This research aimed to investigate the complex communication network in the immune microenvironment (TIME) of NSCLC tumors to clarify the interaction between immune cells and tumors and establish a prognostic risk model that can predict immune response and prognosis of patients by analyzing the characteristics of Neutrophil differentiation.

Bioinformatics Analysis and Structure of Gastric Cancer Prognosis Model Based on Lipid Metabolism and Immune Microenvironment.

Objectives: The reprogramming of lipid metabolism is a new trait of cancers. However, the role of lipid metabolism in the tumor immune microenvironment (TIME) and the prognosis of gastric cancer remains unclear.

Methods: Consensus clustering was applied to identify novel subgroups.

The Value of the Stemness Index in Ovarian Cancer Prognosis.

Ovarian cancer (OC) is one of the most common gynecological malignancies. It is associated with a difficult diagnosis and poor prognosis. Our study aimed to analyze tumor stemness to determine the prognosis feature of patients with OC.

Copper-Catalyzed Reductive Ring-Cleavage of Isoxazoles: Synthesis of Fluoroalkylated Enaminones and Application for the Preparation of Celecoxib, Deracoxib, and Mavacoxib.

We have identified a new reactivity of copper/diamine catalysis for the reductive ring-cleavage of isoxazoles to yield fluoroalkylated enaminones. This protocol has the advantage of using commercially available reagents, ease of setting up, broad tolerance of functionality, and is regiospecific and free of defluorination and reduction of reducible functional groups. The utility was demonstrated by a one-step, regioselective synthesis of fluoroalkylated pyrazole-based drugs such as celecoxib, deracoxib, and mavacoxib.