Clinical learning environments across two different healthcare settings using the undergraduate clinical education environment measure

Data availability: The datasets used and/or analysed during the current study available from the corresponding author on reasonable request.Copyright © The Author(s) 2023. Background: The clinical placements of our medical students are almost equally distributed across private and public sectors. This study aims to assess medical students’ perceptions of their Clinical learning Environment (CLE) across these two different healthcare settings, using the Undergraduate Clinical Education Environment Measure (UCEEM). Methods: 76 undergraduate medical students (Year 5 and 6), were invited to participate. Data were collected using an online UCEEM with additional questions related to demographics and case load exposure. The UCEEM consists of two overarching domains of experiential learning and social participation, with four subdomains of learning opportunities, preparedness, workplace interaction, and inclusion. Results: 38 questionnaires were received. Of 225 responses to the individual UCEEM items, 51 (22.6%) scored a mean of ≥ 4 (range 4-4.5, representing strong areas), 31 (13.7%) scored a mean of ≤ 3 (range 2.1-3, needing attention) and 143 (63.6%) scored a mean of 3.1–3.9 (areas that could be improved). The majority (63%) of the case load exposure responses scored a mean of ≥ 4 (range 4-4.5). Compared to the private sittings, there is a significant reduction in total UCEEM (p = 0.008), preparedness for student entry (p = 0.003), and overarching dimension of social participation (p = 0.000) scores for the public sector. Similarly, both workplace interaction patterns and student inclusion and equal treatment scored significantly lower for the public sector (p = 0.000 and p = 0.011 respectively). Two out of three case load exposure items scored significantly higher for the public sector (p = 0.000). Discussion: The students’ CLE perceptions were generally positive. The lower UCEEM ratings in the public sector items were related to student entry preparedness, workplace interactions, student inclusiveness and workforce equity of treatment. In contrast the students were exposed to more variety and larger number of patients in the public sector. These differences indicated some significantly different learning environments between the two sectors.Not applicable

Generalisability of deep learning models in low-resource imaging settings: A fetal ultrasound study in 5 African countries

Most artificial intelligence (AI) research have concentrated in high-income countries, where imaging data, IT infrastructures and clinical expertise are plentiful. However, slower progress has been made in limited-resource environments where medical imaging is needed. For example, in Sub-Saharan Africa the rate of perinatal mortality is very high due to limited access to antenatal screening. In these countries, AI models could be implemented to help clinicians acquire fetal ultrasound planes for diagnosis of fetal abnormalities. So far, deep learning models have been proposed to identify standard fetal planes, but there is no evidence of their ability to generalise in centres with limited access to high-end ultrasound equipment and data. This work investigates different strategies to reduce the domain-shift effect for a fetal plane classification model trained on a high-resource clinical centre and transferred to a new low-resource centre. To that end, a classifier trained with 1,792 patients from Spain is first evaluated on a new centre in Denmark in optimal conditions with 1,008 patients and is later optimised to reach the same performance in five African centres (Egypt, Algeria, Uganda, Ghana and Malawi) with 25 patients each. The results show that a transfer learning approach can be a solution to integrate small-size African samples with existing large-scale databases in developed countries. In particular, the model can be re-aligned and optimised to boost the performance on African populations by increasing the recall to $0.92 \pm 0.04$ and at the same time maintaining a high precision across centres. This framework shows promise for building new AI models generalisable across clinical centres with limited data acquired in challenging and heterogeneous conditions and calls for further research to develop new solutions for usability of AI in countries with less resources

The Arab world's contribution to solid waste literature: a bibliometric analysis

BACKGROUND: Environmental and health-related effects of solid waste material are considered worldwide problems. The aim of this study was to assess the volume and impact of Arab scientific output published in journals indexed in the Science Citation Index (SCI) on solid waste. METHODS: We included all the documents within the SCI whose topic was solid waste from all previous years up to 31 December 2012. In this bibliometric analysis we sought to evaluate research that originated from Arab countries in the field of solid waste, as well as its relative growth rate, collaborative measures, productivity at the institutional level, and the most prolific journals. RESULTS: A total of 382 (2.35 % of the overall global research output in the field of solid waste) documents were retrieved from the Arab countries. The annual number of documents published in the past three decades (1982–2012) indicated that research productivity demonstrated a noticeable rise during the last decade. The highest number of articles associated with solid waste was that of Egypt (22.8 %), followed by Tunisia (19.6), and Jordan (13.4 %). the total number of citations over the analysed years at the date of data collection was 4,097, with an average of 10.7 citations per document. The h-index of the citing articles was 31. Environmental science was the most researched topic, represented by 175 (45.8 %) articles. Waste Management was the top active journal. The study recognized 139 (36.4 %) documents from collaborations with 25 non-Arab countries. Arab authors mainly collaborated with countries in Europe (22.5 %), especially France, followed by countries in the Americas (9.4 %), especially the USA. The most productive institution was the American University of Beirut, Lebanon, with 6.3 % of total publications. CONCLUSIONS: Despite the expected increase in solid waste production from Arab world, research activity about solid waste is still low. Governments must invest more in solid waste research to avoid future unexpected problems. Finally, since solid waste is a multidisciplinary science, research teams in engineering, health, toxicology, environment, geology and others must be formulated to produce research in solid waste from different scientific aspects

Blood transcriptomics of drug-na\uefve sporadic Parkinson's disease patients

BACKGROUND: Parkinson's disease (PD) is a chronic progressive neurodegenerative disorder that is clinically defined in terms of motor symptoms. These are preceded by prodromal non-motor manifestations that prove the systemic nature of the disease. Identifying genes and pathways altered in living patients provide new information on the diagnosis and pathogenesis of sporadic PD. METHODS: Changes in gene expression in the blood of 40 sporadic PD patients and 20 healthy controls ("Discovery set") were analyzed by taking advantage of the Affymetrix platform. Patients were at the onset of motor symptoms and before initiating any pharmacological treatment. Data analysis was performed by applying Ranking-Principal Component Analysis, PUMA and Significance Analysis of Microarrays. Functional annotations were assigned using GO, DAVID, GSEA to unveil significant enriched biological processes in the differentially expressed genes. The expressions of selected genes were validated using RT-qPCR and samples from an independent cohort of 12 patients and controls ("Validation set"). RESULTS: Gene expression profiling of blood samples discriminates PD patients from healthy controls and identifies differentially expressed genes in blood. The majority of these are also present in dopaminergic neurons of the Substantia Nigra, the key site of neurodegeneration. Together with neuronal apoptosis, lymphocyte activation and mitochondrial dysfunction, already found in previous analysis of PD blood and post-mortem brains, we unveiled transcriptome changes enriched in biological terms related to epigenetic modifications including chromatin remodeling and methylation. Candidate transcripts as CBX5, TCF3, MAN1C1 and DOCK10 were validated by RT-qPCR. CONCLUSIONS: Our data support the use of blood transcriptomics to study neurodegenerative diseases. It identifies changes in crucial components of chromatin remodeling and methylation machineries as early events in sporadic PD suggesting epigenetics as target for therapeutic intervention

Regional research priorities in brain and nervous system disorders

The characteristics of neurological, psychiatric, developmental and substance-use disorders in low-and middle-income countries are unique and the burden that they have will be different from country to country. Many of the differences are explained by the wide variation in population demographics and size, poverty, conflict, culture, land area and quality, and genetics. Neurological, psychiatric, developmental and substance-use disorders that result from, or are worsened by, a lack of adequate nutrition and infectious disease still afflict much of sub-Saharan Africa, although disorders related to increasing longevity, such as stroke, are on the rise. In the Middle East and North Africa, major depressive disorders and post-traumatic stress disorder are a primary concern because of the conflict-ridden environment. Consanguinity is a serious concern that leads to the high prevalence of recessive disorders in the Middle East and North Africa and possibly other regions. The burden of these disorders in Latin American and Asian countries largely surrounds stroke and vascular disease, dementia and lifestyle factors that are influenced by genetics. Although much knowledge has been gained over the past 10 years, the epidemiology of the conditions in low-and middle-income countries still needs more research. Prevention and treatments could be better informed with more longitudinal studies of risk factors. Challenges and opportunities for ameliorating nervous-system disorders can benefit from both local and regional research collaborations. The lack of resources and infrastructure for health-care and related research, both in terms of personnel and equipment, along with the stigma associated with the physical or behavioural manifestations of some disorders have hampered progress in understanding the disease burden and improving brain health. Individual countries, and regions within countries, have specific needs in terms of research priorities.Fil: Ravindranath, Vijayalakshmi. Indian Institute of Science; IndiaFil: Dang, Hoang Minh. Vietnam National University; VietnamFil: Goya, Rodolfo Gustavo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones Bioquímicas de La Plata ; ArgentinaFil: Mansour, Hader. University of Pittsburgh; Estados Unidos. Mansoura University; EgiptoFil: Nimgaonkar, Vishwajit L.. University of Pittsburgh; Estados UnidosFil: Russell, Vivienne Ann. University of Cape Town; SudáfricaFil: Xin, Yu. Peking University; Chin

Association of the PHACTR1/EDN1 genetic locus with spontaneous coronary artery dissection

Background: Spontaneous coronary artery dissection (SCAD) is an increasingly recognized cause of acute coronary syndromes (ACS) afflicting predominantly younger to middle-aged women. Observational studies have reported a high prevalence of extracoronary vascular anomalies, especially fibromuscular dysplasia (FMD) and a low prevalence of coincidental cases of atherosclerosis. PHACTR1/EDN1 is a genetic risk locus for several vascular diseases, including FMD and coronary artery disease, with the putative causal noncoding variant at the rs9349379 locus acting as a potential enhancer for the endothelin-1 (EDN1) gene. Objectives: This study sought to test the association between the rs9349379 genotype and SCAD. Methods: Results from case control studies from France, United Kingdom, United States, and Australia were analyzed to test the association with SCAD risk, including age at first event, pregnancy-associated SCAD (P-SCAD), and recurrent SCAD. Results: The previously reported risk allele for FMD (rs9349379-A) was associated with a higher risk of SCAD in all studies. In a meta-analysis of 1,055 SCAD patients and 7,190 controls, the odds ratio (OR) was 1.67 (95% confidence interval [CI]: 1.50 to 1.86) per copy of rs9349379-A. In a subset of 491 SCAD patients, the OR estimate was found to be higher for the association with SCAD in patients without FMD (OR: 1.89; 95% CI: 1.53 to 2.33) than in SCAD cases with FMD (OR: 1.60; 95% CI: 1.28 to 1.99). There was no effect of genotype on age at first event, P-SCAD, or recurrence. Conclusions: The first genetic risk factor for SCAD was identified in the largest study conducted to date for this condition. This genetic link may contribute to the clinical overlap between SCAD and FMD

Evidence-Based PET for Neurological Diseases

Over the past two decades, one of the major breakthroughs for the approach to neurological diseases both in the clinical and research settings has been represented by the validation of diagnostic biomarkers able to demonstrate the presence of pathological mechanisms, alteration in neurotransmission as well as to predict disease progression [1, 2]. The use of PET with different tracers as well as other imaging biomarkers support the etiological diagnosis of neurological disorders in vivo. This approach is particularly relevant in the field of neurodegenerative diseases. In fact, neurodegenerative diseases are characterized by the progressive degeneration and death of neurons. They represent a heterogeneous group of conditions characterized by different etiologies, different neuropathological and neurochemical alterations leading to different clinical pictures and courses [3]. Indeed, an early accurate diagnosis allows to tackle the disease with available or experimental intervention, lifestyle changes, or logistical arrangements, before disability has developed. Early intervention is expected to have greater clinical impact, extend independent and active life, improve its quality, and decrease the burden and costs of the disease [4]. However, the validation of PET tracers in neurological disease is still ongoing, and evidence on its comparative and combined diagnostic value with respect to other biomarkers is incomplete [4, 5]. As a matter of fact, the increasing pressure for cost-effectiveness requires systematic assessment and validation of all biomarker performance in the clinical settings. Similarly only an evidence-based approach to new PET tracers can allow to select the most promising tracers for PET imaging in the research field both for pathophysiological investigations and for upcoming diagnostic approaches