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Computational screening of natural compounds from traditional Persian medicinal plant for the finding of potential antidepressant

Medication error reporting in Ghana: A multicenter assessment of healthcare professionals’ knowledge, attitudes and practices

Background Medication errors (MEs) remain a leading cause of preventable patient harm globally, with significant implications in low- and middle-income countries (LMICs) where reporting systems are not standardized. Understanding healthcare professionals’ knowledge, attitudes and practices is critical to designing interventions that strengthen patient safety. Methods A cross-sectional, multicenter study was conducted among healthcare professionals, including nurses, doctors, and pharmacists. A structured questionnaire assessed sociodemographic characteristics, knowledge of categories and sources of MEs, medication administration practices, and awareness and use of error reporting systems. Data were analyzed using descriptive statistics and Poisson regression with robust standard errors to identify factors associated with reporting system awareness. Results A total of 2078 healthcare professionals including nurses, doctors, and pharmacists were surveyed. Knowledge levels varied across different medication error categories, with highest recognition for wrong dose (85.5%) and wrong patient errors (81.5%), while shortage of drugs showed lower recognition (44.0%). While adherence to some safety practices was strong (86.6% always checked patient identity), unsafe behaviors such as preparing medications for more than one patient at a time (37.4%) and failure to double-check insulin doses (only 33.9% compliance) were reported. Although 62.6% were aware of institutional error reporting systems, only 23.6% consistently reported errors, and over 53% were uncertain about the process of submitting incident forms. Conclusion Healthcare professionals in Ghana demonstrate strong knowledge of medication error categories and sources but notable gaps persist in safe medication practices and reporting behaviors. Despite moderate awareness of reporting systems, utilization remains poor, reflecting systemic and cultural barriers. These findings highlight the need for targeted educational interventions and system improvements to enhance medication safety culture and error reporting practices across different healthcare specialties and experience levels.

N6-methyladenosine reader IGF2BP2 in T-cell lymphoma

Peripheral T-cell lymphoma (PTCL) represents a highly heterogeneous and aggressive lymphoid neoplasm, lacking pathogenic biomarkers of RNA modification with therapeutic potential. IGF2BP2 is recognized as an N6-methyladenosine (m6A) reader, critically involved in oncogenesis. In this study, we observed consistently high expression of IGF2BP2 across common nodal PTCL subtypes in three independent external cohorts, which was further confirmed in our RNA sequencing (RNA-seq) dataset of 196 patients with newly diagnosed PTCL. Both in vitro and in vivo, IGF2BP2 promoted tumor cell growth and inhibited CD8+ T cell infiltration within the tumor microenvironment. Mechanistically, IGF2BP2 bound to endosome-related genes (RAB4, VPS35, RAB9, and STAM) to maintain their stability, resulting in enhanced endocytic activity and increased internalization of membrane proteins, and ultimately induced tumor cell proliferation and inhibition of CD8+ T cell-mediated tumor cytotoxicity. The relationship between IGF2BP2 and endocytosis-associated genes was confirmed by RNA-seq data of PTCL patients. IGF2BP2 as an upstream regulator of both tumor growth and immune suppression was further demonstrated by patient-derived xenograft models and co-culture system established by tumor samples of PTCL patients and peripheral blood mononuclear cells. Of note, therapeutic targeting of IGF2BP2 with CWI1-2 suppressed endocytosis and impeded tumor growth in both cell lines and patient-derived xenograft models. Collectively, our findings highlight IGF2BP2 as a clinically relevant oncogenic driver in PTCL that integrates tumor-intrinsic growth signals with immune evasion through endocytosis-centered regulation, providing a novel therapeutic rationale for RNA modification-based strategies that concurrently target tumor cells and tumor microenvironment.

Postbiotic derived from Lacticaseibacillus paracasei CNCM I-5220 as a novel approach to improve ageing-induced skin damage

A systematic review and narrative synthesis of the psychometric properties and biopsychosocial correlates of the English version of the Intuitive Eating Scale-2

Intuitive eating is an adaptive eating approach characterised by having unconditional permission to eat when you are hungry, eating for physical rather than emotional reasons, relying on internal hunger and satiety cues, and honouring your health and practising gentle nutrition. The Intuitive Eating Scale-2 (IES-2) is currently the most commonly-used intuitive eating measure but, to date, there has not been a systematic review of how it performs psychometrically outside of the student sample in which it was developed. This systematic review aimed to assess the psychometric properties of the IES-2, including its associations with other variables, across all studies that used it as a measure of intuitive eating and reported psychometric data. MEDLINE, PsycINFO, Scopus and Web of Science were searched in April 2022, May 2024 and June 2025, identifying 90 papers from diverse populations including college students, people from the general population/community, and people seeking treatment for eating disorders or weight management. Results were presented and synthesised narratively, and risk of bias was assessed using two domains from the COSMIN Risk of Bias checklist. Findings suggest that the IES-2 has good construct validity but underperforms psychometrically in other areas such as response distribution, subscale inter-correlations and dimensionality, particularly in relation to the ‘Unconditional permission to eat’ subscale. Alternative factor structures were reported on and a three-factor solution excluding the ‘Unconditional permission to eat’ subscale was found to have promising results. The review contributes a comprehensive account of the biopsychosocial correlates of the IES-2, as well as identifying that studies relating to weight or eating disorders often report mean scores that tend towards the extremes of the scale. Limitations include the exclusion of non-English translations of the IES-2, and future reviews would benefit from being conducted in other languages. PROSPERO registration: CRD42022299436. Funder: ESRC (ES/P000711/1).

Shanmuganathan N, Yeung DT, Wadham C, et al. Impact of <i>ASXL1</i> at diagnosis in patients with CML receiving frontline potent TKIs: high risk of kinase domain mutations. <i>Blood</i> . 2025;146(23):2821-2832.

Beyond GDP: 31 alternatives to the world’s favourite measure of economic health

Learning-driven multi-timescale operation simulation and hierarchical boundary optimization for renewable-dominated energy systems under temporal and scenario uncertainties

Prediction of cognitive impairment through speech data analysis: A comparative evaluation of deep learning models

Background The early detection of cognitive impairments, such as mild cognitive impairment (MCI) and Alzheimer’s disease (AD), is essential for timely intervention and management. This study evaluates the performance of various deep-learning models in classifying speech recordings from individuals with normal cognition (NC), MCI, and AD, to identify the most effective approach for audio-based cognitive impairment diagnosis. Methods Speech data were obtained from the AI Hub “Cognitive Impairment Diagnosis Voice/Conversation” dataset. The study analyzed voice recordings from 320 female participants (105 with Alzheimer’s disease, 92 with mild cognitive impairment, and 123 cognitively normal controls). Three deep-learning architectures were compared: a one-dimensional convolutional neural network (1D CNN), an audio spectrogram transformer (AST), and a speech recognition model (Wav2Vec 2.0). The models were trained using features such as spectrograms, mel-spectrograms, and mel-frequency cepstral coefficients (MFCCs). Model performance was assessed using accuracy, recall, precision, and F1-score, with a five-fold cross-validation strategy to ensure robust and unbiased evaluation. Statistical significance was assessed using pairwise proportion z-tests with Holm-Bonferroni correction, and Wilson score 95% confidence intervals were computed for each model’s accuracy. Results Wav2Vec 2.0 outperformed the other models, achieving the highest accuracy and F1-scores for NC vs. MCI (accuracy: 0.74, F1: 0.72) and NC vs. AD (accuracy: 0.83, F1: 0.83). Pairwise proportion z-tests with Holm-Bonferroni correction confirmed that Wav2Vec 2.0 significantly outperformed 7 of 10 competing models (corrected p &lt; 0.05) in both classification tasks. Performance varied by model and classification task, with Wav2Vec 2.0 consistently demonstrating superior accuracy across labels. Conclusion This study emphasizes the importance of selecting appropriate models and features for task-specific optimization and provides a foundation for developing non-invasive, speech-based diagnostic tools for cognitive disorders.

Regulatory-like FOXP3+Helios+CD4+ T conventional cells correlate with T-cell activation after Orca-T immunotherapy

Abstract Allogeneic hematopoietic stem cell transplantation (allo-HSCT) is a curative therapy for hematologic malignancies. The primary nonrelapse complication after allo-HSCT is graft-versus-host disease (GVHD). The use of regulatory T cells to prevent GVHD has emerged as a promising allogeneic T-cell immunotherapy in the form of Orca-T. However, the precise differences in immune activation, which may influence infection, GVHD, and relapse after Orca-T compared with unmanipulated peripheral blood stem cell (PBSC) grafts, remain unexplored. Using peripheral blood specimens longitudinally collected between 3 weeks and 1 year after leukemia treatment, we report single-cell RNA sequencing (scRNA-seq) and flow cytometric analysis of 51 HLA-matched patients receiving either Orca-T or unmanipulated PBSC grafts. Orca-T recipients exhibited increased frequencies of effector memory CD4+ T cells 3 weeks after transplantation, and this difference persisted through 6 months after treatment. scRNA-seq analysis 3 weeks after transplantation identified increased expression of FOXP3 and Helios among CD4+CD25− T conventional cells (Tcon) in Orca-T–treated patients. Using flow cytometry, we then confirmed the increased frequency of this novel population of CD4+CD25−FOXP3+Helios+ Tcon 3 weeks after treatment in patients receiving Orca-T. Furthermore, we discovered that this T-cell subset possessed a regulatory-like phenotype and correlated significantly with the frequencies of activated CD4+ and CD8+ T-cell populations 3 months after treatment, regardless of which therapy patients received. Overall, this study identifies a novel T-cell subset that is enriched very early after cellular therapy for leukemia and may be predictive of long-term immune activation after Orca-T and PBSC-derived T-cell infusion.

Maximizing pancreatic carcinoma classification performance using parrot optimized vision transformer

Abstract Pancreatic cancer is a rare kind of cancer that is detected during the final stages. This is because the symptoms are very common and also do not show up in the starting phase. Hence an automated system for identification and classification of pancreatic cancer becomes essential. This becomes possible with the help of artificial intelligence and machine learning. The aim of this research is to develop a model that classifies pancreatic cancer using Pancreatic CT image dataset involving 1411 images from Kaggle website. The input images are augmented for increasing the dataset quality and preprocessed using Gabor filter. Segmentation is performed using UNet and features are extracted using YOLOv11 model. Pancreatic carcinoma classification is achieved using a modern deep learning-based classifier called the Vision Transformer. The classified results are optimized with the help of Parrot metaheuristic optimization algorithm. The proposed model produced an accuracy of 99%, precision of 98.5%, recall value of 97.7%, F1-Score of 96.4% and Matthew’s correlation coefficient value of 97.3% in addition to true positive and false positive rates of 96.1% and 0.07%. These results are considered phenomenal and superior when compared to existing models of Random Forest, Convolutional Neural Network, Deep belief networks, and Support Vector Machine.

Views of the Swiss public towards gene editing

There is little country-specific data about how the general public views gene editing therapies. In Autumn 2023 we randomly surveyed the Swiss public, using the Federal Register and stratifying by language region (German, French, Italian), gender and age. We present a representative sample of 3855 responses, including &gt;4000 open-ended comments. When presented with 7 therapeutic options for somatic gene editing, 7% disagreed with all therapeutic options, and 35% supported them all. Most agreed with using somatic gene editing to cure life-threatening (76%) and debilitating diseases (70%); support declined as severity decreased or with later onset. Few supported somatic gene editing to enhance physical (6%) or cognitive (9%) abilities. In all scenarios, people were less likely to agree with gene editing of embryos. Notably, all therapeutic gene editing attitudes clustered, regardless of somatic vs. germline differentiations. Factor analysis also demonstrated two clusters for “support” and “caution” towards gene editing, and multivariate analysis demonstrated relationships with age, gender, religion and knowledge. When asked what influenced their views, the most endorsed reasons for feeling positively were ‘views towards what it means to have a good life’ (59.8%) and ‘views about illness and suffering’ (58.5%). Most selected “neutral” to describe religion’s influence (68.9%) despite findings that those who endorsed high religiosity were less supportive and more cautious towards gene editing. Conclusions: Uncovering systematic differences in the attitudes towards specific therapies and the values shaping them underscores the importance of including peoples’ voices in policy decisions in a country-specific manner.

Revisiting clinical response and refractoriness in immune thrombotic thrombocytopenic purpura

Abstract Immune thrombotic thrombocytopenic purpura (iTTP) is a rare, life-threatening condition. Caplacizumab substantially shortens the time to clinical response, yet delayed platelet count recovery is occasionally observed, raising concerns about iTTP refractoriness. This retrospective multicenter study analyzed 204 acute iTTP episodes reported to the German REACT (Retrospective Evaluation of Acquired Thrombotic Thrombocytopenic Purpura in Caplacizumab-Treated Patients) 2020 and ATMAR (Austrian Thrombotic Microangiopathy Registry) registries, all treated with caplacizumab. Refractoriness was assessed using the 2017 International Working Group criteria and the more stringent definition by the French Reference Center for Thrombotic Microangiopathies. We evaluated time to platelet recovery and presence of confounding clinical conditions, potentially accounting for persistent thrombocytopenia, in all episodes. By day 5 after caplacizumab initiation, 171 of 204 patients (83.8%) achieved a clinical response, and the remaining 33 of 204 (16.2%) showed at least a doubling of the platelet count. Only 3 patients (1.5%) met laboratory criteria for refractoriness. In all cases, plausible alternative causes were present (eg, missed doses, infection). No patient was refractory without a confounding factor. In 8 of 204 patients (3.9%) we observed a markedly prolonged thrombocytopenia (≥10 days) and identified confounding conditions in all cases. In the stratified Cox model, the presence of alternative causes of thrombocytopenia was the only independent determinant of delayed platelet count normalization (hazard ratio, 0.16; 95% confidence interval, 0.09-0.28; P&amp;lt; .001). In the context of caplacizumab-based therapy, true refractoriness is rare. Delayed platelet count recovery is predominantly attributable to concomitant clinical conditions. Careful clinical assessment and context-sensitive interpretation of treatment response before escalating iTTP-specific therapy may avoid unnecessary treatment intensification and associated risks.

World-leading climate centre takes Trump administration to court

Biocontrol potential of endophytic Sphingobium xenophagum J-1 against Fusarium oxysporum causing root rot in Paris polyphylla var. yunnanensis

Editorial Note: Home bias and employee social responsibility: Identification vs. benefit exchange

Orca-T as a force multiplier for HCT immune tolerance

Large language models for zero-shot procedure extraction in orthopedic surgery: a comparative evaluation

Incidence of frailty-related fracture among Medicaid beneficiaries living with HIV and cancer: A cohort study

Background People living with HIV (PLWH) are at increased risk for frailty-related fracture. Limited evidence suggests recent diagnosis of non-AIDS defining cancer (NADC) is a risk factor for fracture among PLWH. We evaluated frailty-related fracture by HIV and cancer status to inform the burden of fracture among PLWH. Methods We included 14,554,711 beneficiaries without HIV and 159,188 beneficiaries with HIV who were 30–64 years old enrolled in Medicaid between 2001–2015 in 14 states. HIV, NADC, and fracture diagnoses were identified from inpatient and other non-prescription claims. We calculated age-specific fracture incidence per 100 person-years and 95% confidence intervals for beneficiaries with no NADC or HIV, NADC only, HIV only, or both. We estimated the cumulative incidence of frailty-related fracture with death as a competing event for each group. Results Fracture incidence increased with age in all groups. Compared to beneficiaries without NADC or HIV, all groups had significantly higher age-specific incidence of fracture. Beneficiaries with HIV and NADC had higher incidence of frailty-related fracture than those with HIV only at all ages (Incidence per 100 person-years for ages 30–44 Both: 1.24 95%CI:0.96,1.59; HIV: 0.74 95%CI:0.71,0.77; for ages 60–64 Both: 2.11 95%CI:1.64,2.67; HIV: 1.47 95%CI:1.37,1.58). Conversely, cumulative incidence was lowest for both HIV and NADC, likely due to in part to the very high incidence of death. Conclusion Beneficiaries with HIV and NADC had higher age-specific frailty-related fracture and death than beneficiaries with HIV alone. Future work should investigate fracture risk among PLWH with cancer to inform interventions for fracture prevention.

A metabolism-specific drug-repurposing screen reveals itraconazole as a potent OXPHOS inhibitor in acute myeloid leukemia

Abstract Targeting mitochondrial oxidative phosphorylation (OXPHOS) enhances the effects of standard chemotherapy and overcomes treatment resistance in preclinical models of acute myeloid leukemia (AML). So far, the few clinically available OXPHOS inhibitors have shown adverse effects or limited potency in clinical trials; therefore, the identification of safe and effective drugs that target mitochondrial metabolism in AML is critical. Here, we performed a high-throughput drug-repurposing screen designed to identify clinically applicable OXPHOS-specific inhibitors through nutrient sensing. We uncover itraconazole, a US Food and Drug Administration–approved antifungal compound, as a potent OXPHOS inhibitor in AML cells. Mechanistically, through stable isotope-assisted metabolomics and functional studies, we reveal that cytochrome P450 family 51 subfamily A member 1 (CYP51A1), which is part of the cytochrome P450 family and the prime target of azole antifungals, is involved in mitochondrial respiration and electron transport chain (ETC) complex I activity in AML cells. Critically, we demonstrate that itraconazole and related azole antifungals interfere with tricarboxylic acid cycle activity and inhibit OXPHOS through the inhibition of ETC complex I activity. Overexpression of yeast nicotinamide adenine dinucleotide (NADH) dehydrogenase-1 (NDI1) restored mitochondrial NADH oxidation and complex I activity following itraconazole treatment. Using patient-derived cells and preclinical xenograft models, we demonstrate that itraconazole targets therapy-resistant leukemic stem cells (LSCs) when used in combination with cytarabine, highlighting the repurposing potential for itraconazole as a clinically safe and effective therapeutic option for AML LSC eradication.