Basic & Clinical Pharmacology & Toxicology最新文献

RETRACTION: P. Manna, M. Sinha, and P. C. Sil, “Protection of Arsenic-Induced Hepatic Disorder by Arjunolic Acid,” Basic & Clinical Pharmacology & Toxicology 101, no. 5 (2007): 333–338, https://doi.org/10.1111/j.1742-7843.2007.00132.x.

The above article, published online on 3 September 2007 in Wiley Online Library (wileyonlinelibrary.com), has been retracted by agreement between the journal Editors-in-Chief, Jens Lykkesfeldt and Ulf Simonsen; the Nordic Association for the Publication of BCPT; and John Wiley & Sons Ltd.

The retraction has been agreed following an investigation based on allegations raised by a third party. Figures 4A and 4C were found to be duplicates, and the authors were unable to provide the original data due to the age of the paper. Additionally, the article contains multiple scientific inaccuracies, conceptual flaws and methodological omissions. Thus, the editors consider the conclusions of this article to be invalid.

The authors disagree with the retraction.

This scoping review investigates the association between ABCB1 polymorphisms and antidepressant efficacy in humans. A systematic search identified 630 records, of which 58 met the inclusion criteria, resulting in 42 unique studies (five randomised controlled trials (RCTs), two randomised studies (non-RCTs), 30 prospective cohort studies, three case–control studies, one cross-sectional clinical study and one phase I clinical trial). These studies examined single nucleotide polymorphisms (SNPs) in or near the ABCB1 gene and their association with antidepressant treatment response. Of the 42 studies, 30 focused on rs1045642, the most extensively studied SNP. Among these, only 20% reported statistically significant associations. Beyond rs1045642, rs2032582 and rs1128503 were also frequently studied, but statistically significant associations were reported in only a minority of cases (28% and 13%, respectively), often with conflicting directions. Haplotype analyses involving all three SNPs (the TTT haplotype) showed mixed results. Results were variable across antidepressants, likely due to overlapping pharmacokinetic pathways. Methodological differences, including study design, sample sizes and definitions of remission, likely contribute to these inconsistencies. This review highlights the complexity of linking ABCB1 polymorphisms to antidepressant treatment response and suggests the need for standardised methodologies and larger, diverse populations in future studies. Haplotype analyses could provide deeper insights and enhance personalised treatment strategies.

Cytochrome P450 3A4 (CYP3A4) is one of the most important members of the cytochrome P450 subfamily, which is involved in the catalytic process of many drug activation or deactivation. Meanwhile, it is also a risk factor for drug-induced toxic reactions. Our research investigates the impact of drugs on CYP3A4 enzyme activity and protein expression, and that CYP3A4 inhibition induced by drugs may exacerbate under hypoxia. Molecular docking has found that the drug has binding sites with amino acid residues in the active region of CYP3A4, which may affect the ability of the CYP3A4 enzyme to metabolize drugs. Twenty male Sprague Dawley rats were divided into two groups: control (FiO₂: 21%), hypoxia (FiO₂: 10%) for 14 days. Liver microsomes from hypoxic and normoxic rats were used for in vitro experiments by high-performance liquid chromatography. Drug concentration in blood in vivo was measured by LC–MS/MS. Further studies have revealed that drugs mediate the degradation of CYP3A4 ubiquitination-proteasome pathway through E3 ubiquitin ligase gp78 by immunoprecipitation, which may exacerbate the CYP3A4 inhibition under hypoxic conditions. These elucidated that the inhibition of CYP3A4 may worsen under pathological conditions (such as hypoxia), providing a basis for rational clinical medication to reduce or avoid drug interactions and toxic reactions.

Psychotropic use for challenging behaviours in people with intellectual disability persists despite initiatives and prescribing guidelines encouraging judicious use. The use of some medications, such as psychiatric medications, can be stigmatised or linked to certain social and cultural beliefs. Rodgers' (1989) evolutionary framework of concept analysis was employed, alongside qualitative data collection, to examine the extent to which people with intellectual disability, their family members and health professionals have similar beliefs about appropriate psychotropic use and shared decision making processes. This study found that the justification for psychotropic use ranges from maintaining mood and safety according to service users and service providers; however, only service providers spoke about the use of medication as a last resort or legacy use. We identified organisational and health system factors, as well as professional, cultural, and relational factors stemming from diverging perceptions of psychotropic risk and power imbalances that influence psychotropic use. This suggests that there are gaps in understanding how to support decision making among people with intellectual disability about their medications. The results clarify the need for further research on effective interventions to enhance the shared decision making process around medications.

While deprescribing benzodiazepines and related drugs (BZRDs) is crucial for preventing prolonged use and their associated adverse effects, it presents challenges from a healthcare perspective, because of limited resources and time. Recently, a pharmacist-led deprescribing of BZRDs in the treatment of insomnia was introduced in Helsinki's primary care health centres. To explore pharmacists' and physicians' insights, qualitative semi-structured interviews were conducted via Microsoft Teams with physicians and pharmacists involved in a pharmacist-led deprescribing. The interviews were recorded, transcribed verbatim and analysed abductively. A total of four pharmacists and four physicians from four health centres participated in this study. Pharmacist-led deprescribing was perceived as having positive outcomes and as being efficient, particularly in saving physicians' time and resources. Various patient-related facilitators and barriers were identified, with patient motivation and willingness being the most cited. Suggestions for improvement included establishing clear criteria for deprescribing, clarifying the roles in the process flow, providing enhanced deprescribing guidance and educational materials and enhancing the patient-centred approach by actively involving patients in the decision-making process and considering the patient's overall situation. Overall, the pharmacist-led model was seen as a promising and resource-efficient approach to deprescribing BZRDs in primary care health centres.

Pleural effusions (PLEF) in pulmonary arterial hypertension (PAH), particularly in patients with isolated right heart failure, are associated with poor prognosis and increased mortality. This study investigates changes in alveolar fluid clearance (AFC) transporter expression in relation to lung fluid accumulation and PLEF formation during PAH progression, as well as the effects of terbutaline (TER) and riociguat (RIO) treatment. Using a monocrotaline (MCT)-induced pulmonary hypertension (PH) rat model, we performed a detailed molecular analysis of AFC transporter expression at different disease stages, both before and after PH development. Although only minor changes were observed in the early stages prior to PH onset, a downregulation of key transporters, γ-ENaC and Na⁺/K⁺-ATPase subunits Atp1a2 and Atp1b1, was evident in the later stages. This reduction may have contributed to pulmonary oedema, as indicated by histological analysis. TER treatment modestly increased Atp1a2 expression, aligning with the stimulatory effects of β₂-agonist on oedema clearance. Conversely, RIO showed trends towards fluid accumulation, indicated by perivascular oedema in control animals and reduced oxygen saturation in MCT-treated rats. These findings support a potential role of impaired AFC in the pathogenesis of PLEF in PAH and suggest that pharmacological interventions may differentially affect lung fluid homeostasis in this setting.

Neurodegenerative disorders such as Alzheimer's disease, Parkinson's disease, Huntington's disease, amyotrophic lateral sclerosis and frontotemporal dementia represent a significant global health burden with limited therapeutic options. Current treatments are primarily symptomatic and fail to modify disease progression, emphasizing the urgent need for novel, mechanism-based interventions. Recent advances in molecular neuroscience have identified several non-classical pathogenic pathways, including neuroinflammation, mitochondrial dysfunction, impaired autophagy and proteostasis, synaptic degeneration and non-coding RNA dysregulation. In this focused review, we highlight emerging molecular targets such as TREM2, NLRP3, mTOR, TFEB, PINK1 and SIRT3, which offer promising avenues for therapeutic intervention. We also address challenges in target validation and translational drug development, while proposing future research directions that may facilitate the design of more effective treatments. A deeper understanding of these molecular mechanisms is essential for developing disease-modifying strategies to combat neurodegeneration.

Early detection of diseases is a critical pillar in advancing modern healthcare, offering timely interventions and better patient outcomes. This overview highlights a range of machine learning (ML) approaches that are transforming early disease diagnosis. We discuss how traditional supervised and unsupervised methods, alongside advanced deep learning and reinforcement learning techniques, are utilized to detect early disease markers, often before clinical symptoms appear. The paper begins with a discussion of ML fundamentals within healthcare, along with standard evaluation metrics such as accuracy, precision, recall, F1-score and AUC-ROC. It then explores various ML models, including supervised algorithms (support vector machines, decision trees and random forests), unsupervised methods (K-means, hierarchical clustering and principal component analysis) and deep learning architectures (convolutional neural networks, recurrent neural networks and transformers). Reinforcement learning's emerging role in healthcare is also examined. Practical applications across disease areas such as cancer, cardiovascular diseases, neurological disorders and infectious diseases are reviewed. We emphasize the importance of high-quality datasets, balanced data distribution and clinical relevance. Key challenges such as data scarcity, model interpretability, privacy, the risk of overdiagnosis and clinical integration are critically discussed. It underscores that the successful translation of these technologies from code to clinic hinges on a deep, bidirectional collaboration between data scientists and clinical experts to ensure that newly developed tools address real-world patient needs. The overview concludes with future directions, including explainable AI, federated learning, multimodal data fusion, real-time applications and quantum ML, charting the evolving path of early disease detection.

This scoping review provides an overview of tools used to assess potentially inappropriate prescribing among older adults and discusses their suitability for register-based research. We performed a systematic search using PubMed (March 2024), retrieving 5493 records. Studies were included if they evaluated potentially inappropriate medication use among older adults with a mean or median age of ≥ 65 years. Identified tools were described by characteristics, usage frequency, and applicability to register-based research by identifying required data types. A total of 419 studies were included, using 44 different tools, including multiple versions. Beers criteria and the Screening Tool of Older People's Prescriptions were most often used (50% and 19%, respectively). Ten tools were used in five or more studies, each differing in structure, particularly regarding the clinical information required. The European list of potentially inappropriate medications, the PRISCUS list, the Zhan criteria, and the Norwegian General Practice criteria do not require clinical data on medical history, symptoms, laboratory tests or other parameters, making them particularly useful for register-based research. Specific segments of other tools can also be applied effectively. To generate valid and meaningful results, the availability of required data is a crucial consideration for researchers when selecting the most appropriate tool.