Revisiting Supersaturation of a Biopharmaceutical Classification System IIB Drug: Evaluation via a Multi-Cup Dissolution Approach and Molecular Dynamic Simulation.

As a subclass of the biopharmaceutical classification system (BCS) class II, basic drugs (BCS IIB) exhibit pH-dependent solubility and tend to generate supersaturation in the gastrointestinal tract, leading to less qualified in vitro-in vivo correlation (IVIVC). This study aims to develop a physiologically based multi-cup dissolution approach to improve the evaluation of the supersaturation for a higher quality of IVIVC and preliminarily explores the molecular mechanism of supersaturation and precipitation of ketoconazole affected by Polyvinylpyrrolidone-vinyl acetate copolymer (PVPVA) and hydroxypropyl methyl-cellulose (HPMC). The concentration of ketoconazole in each cup of the dynamic gastrointestinal model (DGIM) was measured using fiber optical probes.

Network module analysis and molecular docking-based study on the mechanism of astragali radix against non-small cell lung cancer.

Background: Most lung cancer patients worldwide (stage IV non-small cell lung cancer, NSCLC) have a poor survival: 25%-30% patients die < 3 months. Yet, of those surviving > 3 months, 10%-15% patients survive (very) long. Astragali radix (AR) is an effective traditional Chinese medicine widely used for non-small cell lung cancer (NSCLC).

HSPA5, as a ferroptosis regulator, may serve as a potential therapeutic for head and neck squamous cell carcinoma.

Background: Head and neck squamous cell carcinoma (HNSCC) is a ferroptosis sensitive tumor type with high mortality rate. However, it remains largely unknown whether ferroptosis influences the tumor cell in HNSCC.

Materials And Methods: To investigate how ferroptosis regulators were differentially expressed between normal and tumor tissue, data related to HNSCC was downloaded from The Cancer Genome Atlas.

Objectification of Tongue Diagnosis in Traditional Medicine, Data Analysis, and Study Application.

Tongue diagnosis is an essential technique of traditional Chinese medicine (TCM) diagnosis, and the need for objectifying tongue images through image processing technology is growing. The present study provides an overview of the progress made in tongue objectification over the past decade and compares segmentation models. Various deep learning models are constructed to verify and compare algorithms using real tongue image sets.

Research and application of tongue and face diagnosis based on deep learning.

Objective: To explore the technical research and application characteristics of deep learning in tongue-facial diagnosis.

Methods: Through summarizing the merits and demerits of current image processing techniques used in the traditional medical tongue and face diagnosis, the research status of deep learning in tongue image preprocessing, segmentation, and classification was analyzed and reviewed, and the algorithm was compared and verified with the real tongue and face image. Images of the face and tongue used for diagnosis in conventional medicine were systematically reviewed, from acquisition and pre-processing to segmentation, classification, algorithm comparison, result from analysis, and application.

Herceptin-Conjugated DOX-FeO/P(NIPAM-AA-MAPEG) Nanogel System for HER2-Targeted Breast Cancer Treatment and Magnetic Resonance Imaging.

It is essential to synthesize a "diagnosis and therapy" integration nanocarrier for magnetic resonance imaging-guided breast cancer-targeted chemotherapy. Here, we report FeO/P(NIPAM-AA-MAPEG) nanogels (MNLs) based on in situ loading of doxorubicin (DOX) by miniemulsion polymerization. Especially, propyl acrylic acid (AA) moieties were introduced to absorb DOX by electrostatic interactions and conjugated with the antibody herceptin (HER) through the amino-carboxyl coupling reaction.

Different Data Mining Approaches Based Medical Text Data.

The amount of medical text data is increasing dramatically. Medical text data record the progress of medicine and imply a large amount of medical knowledge. As a natural language, they are characterized by semistructured, high-dimensional, high data volume semantics and cannot participate in arithmetic operations.

Network pharmacology analysis of the therapeutic mechanisms of the traditional Chinese herbal formula Lian Hua Qing Wen in Corona virus disease 2019 (COVID-19), gives fundamental support to the clinical use of LHQW.

Background: The traditional Chinese Medicine (TCM) herbal formula Lian Hua Qing Wen (LHQW) improves the results of COVID-19 treatment. Three very recent studies analyzed with network pharmacology some working mechanisms of LHQW. However, we used more techniques and also included Angiotensin converting enzyme 2 (ACE2) (a SARS-CoV receptor, possibly the viral entry point in alveolar lung cells) and the immune system, as cytokine storm is essential in the late phase.