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Immune checkpoint inhibitors plus taxane-based chemotherapy for patients with advanced/metastatic NSCLC: a systematic review and meta-analysis across different PD-L1 expression levels.
Expert Rev Anticancer Ther
January 2025
Department of Microbiology, Pathology and Forensic Medicine, Faculty of Medicine, The Hashemite University, Zarqa, Jordan.
Background: Immune checkpoint inhibitors (ICIs) are currently the primary approach for managing NSCLC. However, numerous combination therapies are currently under investigation. Our goal is to investigate the overall efficacy and safety of ICIs and taxane-based chemotherapy.
View Article and Find Full Text PDFThe role of rodent behavioral models of schizophrenia in the ongoing search for novel antipsychotics.
Expert Opin Drug Discov
January 2025
Centro de Investigación en Reproducción Animal Universidad Autónoma de Tlaxcala - CINVESTAV Tlaxcala, Tlaxcala, México.
Introduction: Existing pharmacotherapies for schizophrenia have not progressed beyond targeting dopamine and serotonin neurotransmission. Rodent models of schizophrenia are a necessary tool for elucidating neuropathological processes and testing potential pharmacotherapies, but positive preclinical results in rodent models often do not translate to positive results in the clinic.
Areas Covered: The authors reviewed PubMed for studies that applied rodent behavioral models of schizophrenia to assess the antipsychotic potential of several novel pharmacotherapies currently under investigation.
Triethylamine-mediated protonation-deprotonation unlocks dual-drug self assembly to suppress breast cancer progression and metastasis.
Proc Natl Acad Sci U S A
February 2025
Key Laboratory of Drug-Targeting and Drug Delivery System of the Education Ministry and Sichuan Province, Sichuan Engineering Laboratory for Plant-Sourced Drug and Sichuan Research Center for Drug Precision Industrial Technology, West China School of Pharmacy, Sichuan University, Chengdu 610041, People's Republic of China.
Carrier-free nanomedicines exhibited significant potential in elevating drug efficacy and safety for tumor management, yet their self assembly typically relied on chemical modifications of drugs or the incorporation of surfactants, thereby compromising the drug's inherent pharmacological activity. To address this challenge, we proposed a triethylamine (TEA)-mediated protonation-deprotonation strategy that enabled the adjustable-proportion self assembly of dual drugs without chemical modification, achieving nearly 100% drug loading capacity. Molecular dynamic simulations, supported by experiment evidence, elucidated the underlying self-assembly mechanism.
View Article and Find Full Text PDFLeveraging Network Target Theory for Efficient Prediction of Drug-Disease Interactions: A Transfer Learning Approach.
Adv Sci (Weinh)
January 2025
Department of Molecular Pharmacology, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Tianjin's Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute & Hospital, Tianjin, 300060, China.
Efficient virtual screening methods can expedite drug discovery and facilitate the development of innovative therapeutics. This study presents a novel transfer learning model based on network target theory, integrating deep learning techniques with diverse biological molecular networks to predict drug-disease interactions. By incorporating network techniques that leverage vast existing knowledge, the approach enables the extraction of more precise and informative drug features, resulting in the identification of 88,161 drug-disease interactions involving 7,940 drugs and 2,986 diseases.
View Article and Find Full Text PDFIdentification of CD209 as an Intervention Target for Type 2 Diabetes after COVID-19 Infection: Insights from Proteome-wide Mendelian Randomization.
Diabetes
January 2025
School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, Guangdong, China.
Increasing evidence suggests that individuals infected with Coronavirus disease 2019 (COVID-19) are at a higher risk of developing type 2 diabetes (T2D) compared to those who are not infected. However, the mechanisms underlying this relationship remain poorly understood. In this study, we aimed to systematically evaluate the mediating roles of 3,283 plasma proteins in the link between COVID-19 susceptibility and T2D by conducting proteome-wide Mendelian randomization (MR) analyses.
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