DrugSK: A Stacked Ensemble Learning Framework for Predicting Drug Combinations of Multiple Diseases.

Combination therapy is an important direction of continuous exploration in the field of medicine, with the core goals of improving treatment efficacy, reducing adverse reactions, and optimizing clinical outcomes. Machine learning technology holds great promise in improving the prediction of drug synergy combinations. However, most studies focus on single disease-oriented collaborative predictive models or involve excessive feature categories, making it challenging to predict the majority of new drugs.

Knowledge mapping of graph neural networks for drug discovery: a bibliometric and visualized analysis.

Introduction: In recent years, graph neural network has been extensively applied to drug discovery research. Although researchers have made significant progress in this field, there is less research on bibliometrics. The purpose of this study is to conduct a comprehensive bibliometric analysis of graph neural network applications in drug discovery in order to identify current research hotspots and trends, as well as serve as a reference for future research.

Research focus and thematic trends of transient receptor potential vanilloid member 1 research: a bibliometric analysis of the global publications (1990-2023).

Recently, various studies have been devoted to the study of transient receptor potential vanilloid member 1 (TRPV1)-related diseases, potential drugs, and related mechanisms. The objective of this investigation was to examine the significant areas and cutting-edge developments in TRPV1 study within recent decades. Articles or reviews were obtained from the Web of Science Core Collection.

Butein, a potential drug for the treatment of bone cancer pain through bioinformatic and network pharmacology.

Bone cancer pain is a difficult-to-treat pathologic condition that impairs the patient's quality of life. The effective therapy options for BCP are restricted due to the unknown pathophysiology. Transcriptome data were obtained from the Gene Expression Omnibus database and differentially expressed gene extraction was performed.

Develop adult extrapolation to pediatrics and pediatric dose optimization based on the physiological pharmacokinetic model of azithromycin.

Physiologically-based pharmacokinetic (PBPK) models are more frequently used for supporting pediatric dose selection in small-molecule drugs. Through literature research, drug parameters of azithromycin and clinical data from different studies were obtained. Through parameter optimization of the absorption and dissolution process, the adult intravenous model was extended to the adult oral model.

Ensemble learning-based gene signature and risk model for predicting prognosis of triple-negative breast cancer.

Although medical science has been fully developed, due to the high heterogeneity of triple-negative breast cancer (TNBC), it is still difficult to use reasonable and precise treatment. In this study, based on local optimization-feature screening and genomics screening strategy, we screened 25 feature genes. In multiple machine learning algorithms, feature genes have excellent discriminative diagnostic performance among samples composed of multiple large datasets.

Ionizable drug delivery systems for efficient and selective gene therapy.

Gene therapy has shown great potential to treat various diseases by repairing the abnormal gene function. However, a great challenge in bringing the nucleic acid formulations to the market is the safe and effective delivery to the specific tissues and cells. To be excited, the development of ionizable drug delivery systems (IDDSs) has promoted a great breakthrough as evidenced by the approval of the BNT162b2 vaccine for prevention of coronavirus disease 2019 (COVID-19) in 2021.

A bibliometric and visualized analysis of liver fibrosis from 2002 to 2022.

Fibrosis of the liver is a degenerative alteration that occurs in the majority of chronic liver disorders. Further progression can lead to cirrhosis, liver failure, and hepatocellular carcinoma, which can seriously affect the health and lives of patients. The field of liver fibrosis research has flourished in the last 20 years, with approximately 9000 articles retrieved from the Web of Science Core Collection database alone.

Artificial intelligence-driven prediction of multiple drug interactions.

When a drug is administered to exert its efficacy, it will encounter multiple barriers and go through multiple interactions. Predicting the drug-related multiple interactions is critical for drug development and safety monitoring because it provides foundations for practical, safe compatibility and rational use of multiple drugs. With the progress of artificial intelligence (AI) technology, a variety of novel prediction methods for single interaction have emerged and shown great advantages compared to the traditional, expensive and time-consuming laboratory research.

An optimized herbal combination for the treatment of liver fibrosis: Hub genes, bioactive ingredients, and molecular mechanisms.

Ethnopharmacological Relevance: Liver fibrosis is a chronic liver disease that can lead to cirrhosis, liver failure, and hepatocellular carcinoma, and it is associated with long-term adverse outcomes and mortality. As a primary resource for complementary and alternative medicine, traditional Chinese medicine (TCM) has accumulated a large number of effective formulas for the treatment of liver fibrosis in clinical practice. However, studies on how to systematically optimize TCM formulas are still lacking.

Analysis of CFTR gene expression as an immunological and prognostic biomarker in pan-cancers.

Cystic fibrosis transmembrane conductance regulator (CFTR) is a cAMP-activated chloride channel that regulates fluid homeostasis via ATP binding and uses energy to transport relevant substrates across cytomembranes. It has been reported that CFTR plays a crucial role in the incidence and development of various types of cancers by regulating proliferation, metastasis, invasion and apoptosis. However, aberrant CFTR gene expression across different cancers makes it difficult to propose CFTR as a possible pan-cancer biomarker.

Systematic analysis of the mechanism of Xiaochaihu decoction in hepatitis B treatment via network pharmacology and molecular docking.

Hepatitis B (HB) is a globally prevalent infectious disease caused by the HB virus. Xiaochaihu decoction (XCHD) is a classic herbal formula with a long history of clinical application in treating HB. Although the anti-HB activity of XCHD has been reported, systematic research on the exact mechanism of action is lacking.

Incretin mimetics and sodium-glucose co-transporter 2 inhibitors as monotherapy or add-on to metformin for treatment of type 2 diabetes: a systematic review and network meta-analysis.

Purpose: Although there are many different methods of treating type 2 diabetes (T2D), it is still difficult to draw coincident conclusions concerning the efficacy and safety of different classes of new drugs, and the recommendation level of them has still kept uncertain as second anti-diabetic agents. Therefore, the aim of this study was to summarize evidence on the efficacy and safety of DPP-4is, GLP-1RAs and SGLT-2is as monotherapy or add-on to metformin (Met) for treatment of T2D.

Materials And Methods: We searched PubMed, Embase, Cochrane library and ClinicalTrials.

Research Progress of Coronavirus Based on Bibliometric Analysis.

Background: COVID-19 has become one of the most serious global epidemics in the 21st Century. This study aims to explore the distribution of research capabilities of countries, institutions, and researchers, and the hotspots and frontiers of coronavirus research in the past two decades. In it, references for funding support of urgent projects and international cooperation among research institutions are provided.

Genomic characterization of Inc: IncFII type plasmids p13294-KPC and pA1966-NR from .

To characterize two plasmids p13294-KPC and pA1966-NR from clinical strains. Plasmids p13294-KPC and pA1966-NR were fully sequenced and then detailed genomic analysis was performed in this work. The antimicrobial resistance phenotypes were determined.

N2 neutrophils may participate in spontaneous recovery after transient cerebral ischemia by inhibiting ischemic neuron injury in rats.

Neutrophils have been traditionally considered as the major mediators of harmful inflammatory responses in ischemic stroke, whereas accumulating evidence indicates that neutrophils can be polarized into an N2 phenotype. Similar to M2 microglia, N2 neutrophils contribute to resolution of inflammation and may participate in neuroprotection. However, it remains unclear whether N2 neutrophils protect ischemic neurons and whether they are associated with long-term outcomes after transient cerebral ischemia in rats.

Pseudoginsenoside-F11 Attenuates Lipopolysaccharide-Induced Acute Lung Injury by Suppressing Neutrophil Infiltration and Accelerating Neutrophil Clearance.

Pseudoginsenoside-F11 (PF11), an ocotillol-type saponin, has been reported to have anti-inflammatory properties, but the effects of PF11 on acute lung inflammation were unknown. The present study aimed to investigate the protective effects and potential mechanisms of PF11 on lipopolysaccharide (LPS)-induced acute lung injury (ALI) in male BALB/c mice. After being treated with PF11 (3, 10, and 30 mg/kg, intravenous) once a day for 3 consecutive days, the mice were challenged by intratracheal instillation of LPS, and then their lung tissues and bronchoalveolar lavage fluid (BALF) were collected for further analysis.

Comparative efficacy and safety of multiple antiplatelet therapies for secondary prevention of ischemic stroke or transient ischemic attack: A network meta-analysis.

Background: Antiplatelet therapies for secondary prevention of ischemic stroke or transient ischemic attack (TIA) is a highly active research topic with five critical drugs obtained by visual analysis. We aimed to compare and rank multiple antiplatelet therapies using a network meta-analysis.

Methods: Relevant medical databases were searched.

Efficacy and safety of sodium-glucose cotransporter-2 inhibitors versus dipeptidyl peptidase-4 inhibitors as monotherapy or add-on to metformin in patients with type 2 diabetes mellitus: A systematic review and meta-analysis.

Aims: To compare the efficacy and safety of dipeptidyl peptidase-4 inhibitors (DPP-4is) and sodium-glucose cotransporter-2 inhibitors (SGLT-2is) as monotherapy or add-on to metformin (Met) in patients with type 2 diabetes mellitus (T2DM).

Materials And Methods: PubMed, Embase and ClinicalTrials.gov sites were systematically searched for randomized controlled trials to assess the efficacy and safety of DPP-4is and SGLT-2is in patients with T2DM.

Preparation and investigation of controlled-release glipizide novel oral device with three-dimensional printing.

The purpose of this study was to explore the feasibility of combining fused deposition modeling (FDM) 3D printing technology with hot melt extrusion (HME) to fabricate a novel controlled-release drug delivery device. Glipizide used in the treatment of diabetes was selected as model drug, and was successfully loaded into commercial polyvinyl alcohol (PVA) filaments by HME method. The drug-loaded filaments were printed through a dual-nozzle 3D printer, and finally formed a double-chamber device composed by a tablet embedded within a larger tablet (DuoTablet), each chamber contains different contents of glipizide.

Development of self-nanoemulsifying drug delivery system for oral bioavailability enhancement of valsartan in beagle dogs.

Valsartan, an angiotensin II receptor antagonist, is widely used to treat high blood pressure in the clinical setting. However, its poor water solubility results in the low oral bioavailability. The aim of this study was to improve dissolution rate and oral bioavailability by developing a self-nanoemulsifying drug delivery system.

Efficacy and Safety of Vasopressin Receptor Antagonists for Euvolemic or Hypervolemic Hyponatremia: A Meta-Analysis.

Hyponatremia, defined as a nonartifactual serum sodium level <135 mmol/L, is the most common fluid and electrolyte abnormality in clinical practice. Traditional managements (fluid restriction, hypertonic saline and loop diuretics, etc.) are difficult to maintain or ineffective.

The role of the insular cortex in naloxone-induced conditioned place aversion in morphine-dependent mice.

A negative emotional state resulting from the withdrawal of drug addiction is thought to be an important factor that triggers and exacerbates relapse. Since the insular cortex is a key brain structure involved in the modulation of negative emotions, we investigated whether the integrity of the insular cortex was important for motivational aversion associated with morphine withdrawal as well as whether this kind of negative emotion induced neuroadaptation in the insular cortex. In this present study, a sensitive mouse conditioned place aversion (CPA) model measuring the motivational aversion of morphine withdrawal was first established.

Aggregated single-walled carbon nanotubes attenuate the behavioural and neurochemical effects of methamphetamine in mice.

Methamphetamine (METH) abuse is a serious social and health problem worldwide. At present, there are no effective medications to treat METH addiction. Here, we report that aggregated single-walled carbon nanotubes (aSWNTs) significantly inhibited METH self-administration, METH-induced conditioned place preference and METH- or cue-induced relapse to drug-seeking behaviour in mice.