Medical Research Research Articles

Delineation of chicken immune markers in the era of omics and multicolor flow cytometry

Multiparameter flow cytometry is a routine method in immunological studies incorporated in biomedical, veterinary, agricultural, and wildlife research and routinely used in veterinary clinical laboratories. Its use in the diagnostics of poultry diseases is still limited, but due to the continuous expansion of reagents and cost reductions, this may change in the near future. Although the structure and function of the avian immune system show commonalities with mammals, at the molecular level, there is often low homology across species. The cross-reactivity of mammalian immunological reagents is therefore low, but nevertheless, the list of reagents to study chicken immune cells is increasing. Recent improvement in multicolor antibody panels for chicken cells has resulted in more detailed analysis by flow cytometry and has allowed the discovery of novel leukocyte cell subpopulations. In this article, we present an overview of the reagents and guidance needed to perform multicolor flow cytometry using chicken samples and common pitfalls to avoid.

Bright Innovations: Review of Next-Generation Advances in Scintillator Engineering.

This review focuses on modern scintillators, the heart of ionizing radiation detection with applications in medical diagnostics, homeland security, research, and other areas. The conventional method to improve their characteristics, such as light output and timing properties, consists of improving in material composition and doping, etc., which are intrinsic to the material. On the contrary, we review recent advancements in cutting-edge approaches to shape scintillator characteristics via photonic and metamaterial engineering, which are extrinsic and introduce controlled inhomogeneity in the scintillator's surface or volume. The methods to be discussed include improved light out-coupling using photonic crystal (PhC) coating, dielectric architecture modification producing the Purcell effect, and meta-materials engineering based on energy sharing. These approaches help to break traditional bulk scintillators' limitations, e.g., to deal with poor light extraction efficiency from the material due to a typically large refractive index mismatch or improve timing performance compared to bulk materials. In the Outlook section, modern physical phenomena are discussed and suggested as the basis for the next generations of scintillation-based detectors and technology, followed by a brief discussion on cost-effective fabrication techniques that could be scalable.

A Study to Evaluate the Efficacy of Preoperative Low-dose Nebulised Dexamethasone in Decreasing the Incidence of Postoperative Sore Throat in Patients Undergoing Surgery Under General Anaesthesia

Background and Aims: Postoperative sore throat (POST) is a stereotypical postoperative complication that usually occurs in approximately 21%–65% of patients who are under general anaesthesia and is ranked around eighth among the most undesirable subjective and unpleasant complaints by the society of American anaesthesiologist after general anaesthesia. As airway management is a crucial factor in the causation of POST, various methods, especially non-pharmacological, are used to reduce the incidence of postoperative sore throat with the use of a small-sized endotracheal tube with low intracuff pressures. The tracheal tube is applied with other agents that may help in reducing the symptoms such as steroids, lozenges, lignocaine, ketamine gargles, inhalation of steroids (also included in pharmacological methods used for reducing the incidence of postoperative sore throat). Aim and Objective: The aim of this study was to evaluate the efficacy of prophylactic low-dose nebulised dexamethasone for decreasing the incidence of post-extubation sore throat and to evaluate the complications of low-dose dexamethasone nebulisation in patients undergoing surgery under general anaesthesia. Patients and Methods: The study was done in the Anaesthesiology Department of Maharishi Markandeshwar Institute of Medical Sciences and Research (MMIMSR) Mullana, Ambala, after institutional ethical committee approval and written, informed consent was obtained from the patients from March 2021 to March 2022 with a group size of Group S – 25 patients and Group D – 25 patients. Observation and Results: The results showed that patients in the dexamethasone group had a lower POST rate compared to the control group. Conclusion: We concluded that a low dose of 4 mg dexamethasone was effective in reducing the incidence and severity of POST in patients after anaesthesia, and no side effects compared to 4 mg normal saline.

CoRTEx: contrastive learning for representing terms via explanations with applications on constructing biomedical knowledge graphs.

Biomedical Knowledge Graphs play a pivotal role in various biomedical research domains. Concurrently, term clustering emerges as a crucial step in constructing these knowledge graphs, aiming to identify synonymous terms. Due to a lack of knowledge, previous contrastive learning models trained with Unified Medical Language System (UMLS) synonyms struggle at clustering difficult terms and do not generalize well beyond UMLS terms. In this work, we leverage the world knowledge from large language models (LLMs) and propose Contrastive Learning for Representing Terms via Explanations (CoRTEx) to enhance term representation and significantly improves term clustering. The model training involves generating explanations for a cleaned subset of UMLS terms using ChatGPT. We employ contrastive learning, considering term and explanation embeddings simultaneously, and progressively introduce hard negative samples. Additionally, a ChatGPT-assisted BIRCH algorithm is designed for efficient clustering of a new ontology. We established a clustering test set and a hard negative test set, where our model consistently achieves the highest F1 score. With CoRTEx embeddings and the modified BIRCH algorithm, we grouped 35 580 932 terms from the Biomedical Informatics Ontology System (BIOS) into 22 104 559 clusters with O(N) queries to ChatGPT. Case studies highlight the model's efficacy in handling challenging samples, aided by information from explanations. By aligning terms to their explanations, CoRTEx demonstrates superior accuracy over benchmark models and robustness beyond its training set, and it is suitable for clustering terms for large-scale biomedical ontologies.

Dependency-aware deep generative models for multitasking analysis of spatial omics data.

Spatially resolved transcriptomics (SRT) technologies have significantly advanced biomedical research, but their data analysis remains challenging due to the discrete nature of the data and the high levels of noise, compounded by complex spatial dependencies. Here, we propose spaVAE, a dependency-aware, deep generative spatial variational autoencoder model that probabilistically characterizes count data while capturing spatial correlations. spaVAE introduces a hybrid embedding combining a Gaussian process prior with a Gaussian prior to explicitly capture spatial correlations among spots. It then optimizes the parameters of deep neural networks to approximate the distributions underlying the SRT data. With the approximated distributions, spaVAE can contribute to several analytical tasks that are essential for SRT data analysis, including dimensionality reduction, visualization, clustering, batch integration, denoising, differential expression, spatial interpolation, resolution enhancement and identification of spatially variable genes. Moreover, we have extended spaVAE to spaPeakVAE and spaMultiVAE to characterize spatial ATAC-seq (assay for transposase-accessible chromatin using sequencing) data and spatial multi-omics data, respectively.

Effect of 4-Week Pulmonary Rehabilitation on Dyspnea, Fatigue, Quality of Life and Radiological Findings in a Patient with Pulmonary Renal Syndrome Suffering from Pneumonia - A Case Study

Background: Pulmonary renal syndrome (PRS) is a rare, autoimmune disease, defined as combination of pulmonary symptoms (cough, chest pain and dyspnea- at acute stage) and rapidly progressive glomerulonephritis. Pneumonia is an inflammatory condition caused by infectious agents leading to fever, cough and shortness of breath. We report a case of a 42 years old female suffering from PRS and recently diagnosed with bacterial pneumonia. Medically she was managed through antibacterial and oral corticosteroids. At initial encounter of pneumonia, she was in intensive care unit and had cough, dyspnea, pyrexia and fatigue with oxygen saturation (SpO2) of 94% on 15 liters of oxygen via non rebreathable mask. Her chest x-ray demonstrated lobar pneumonia involving right upper lobe. Even after the resolution of pneumonia, she had fatigue, dyspnea and baseline SpO2 of 90-92% on room air. Thus, all the above traits were treated by pulmonary rehabilitation. Purpose: To study the effect of tailor-made pulmonary rehabilitation in pneumonia along with PRS. Method: Physiotherapy was divided into 2 phases: (1) Acute phase: chest physiotherapy (breathing exercises, nebulization, bronchial hygiene, percussion and vibration) (2) Subacute and Late phase: dyspnea management, energy conservation techniques, early mobilization, exercise training (aerobic and strength) Result: 4 weeks of pulmonary rehabilitation resulted in significant improvement in radiological finding, St. George’s respiratory questionnaire (85.39 to 15.53), SpO2 at room air (90% to 99%), Modified Medical Research council score (4 to 1), fatigue severity scale (43 to 21) with an improved inspiratory capacity measured by incentive spirometer. Conclusion: Pulmonary rehabilitation is a structured and multifaceted approach which improves respiratory function, enhance physical fitness, reduces fatigue and the length of hospital stay, prevent recurrence and optimize overall quality of life. Our findings underscore the pivotal role of pulmonary rehabilitation in the treatment of pneumonia alongside Pulmonary Renal Syndrome. Keywords: pulmonary rehabilitation, pneumonia, pulmonary renal syndrome

#1534 Risk of CKD progression taken into account of metabolic changes

Abstract Background and Aims The purpose of this study was to study the relationship between metabolic syndrome and the risk of progression of CKD in a representative sample of patients who were hospitalized in the nephrology department of the 3rd clinic of the Tashkent Medical Academy and in the department of cardiology and interventional cardiology of the Russian National Medical Research and Medical Center. Method In the retrospective part of the study, 1000 case histories of patients with CKD who were inpatient treatment from 2013 to 2019 in the nephrology department of the 3rd clinic of the Tashkent Medical Academy and in the department of cardiology and interventional cardiology of the Russian National Medical Research Center for Medical Sciences were studied. In the prospective part of the study, information on demographic characteristics, including age, gender, education, and profession, was collected during medical visits using a standard questionnaire. Metabolic syndrome was defined according to international guidelines as the presence of three or more of the following risk factors: waist circumference >102 cm in men or >88 cm in women; serum triglyceride level ≥1.70 mmol/L; HDL cholesterol < 1.04 mmol/L in men or < 1.30 mmol/L in women; Blood pressure ≥ 130/85 mm Hg, including achieved; serum glucose level ≥6.11 mmol/L. Metabolic syndrome definition criteria used Results The demographic characteristics of the patients are presented in the table. Mean serum creatinine was similar, but GFR was estimated to be lower among those with metabolic syndrome compared with those without. The percentage of individuals with CKD and elevated serum creatinine was statistically significantly higher among individuals with metabolic syndrome. Low HDL cholesterol, elevated plasma glucose, and abdominal obesity were found to be statistically significantly associated with the risk of developing C5 CKD and elevated serum creatinine. In addition, a significant relationship was observed between the number of metabolic syndrome components and the percentage of CKD C5 or elevated serum creatinine (P < 0.015 and P = 0.02, respectively). In the multivariate model, patients with 1, 2, 3 and 4 or 5 components of the metabolic syndrome had 1.51; 1.50; 2.13 and 2.72 times higher odds of CKD C5 CKD, respectively, compared with individuals without metabolic syndrome components. Overall, patients with metabolic syndrome had a 64% increased odds of CKD compared with a comparison group without metabolic syndrome. Conclusion The present study revealed a positive and significant association between metabolic syndrome and the risk of CKD C5 in those examined. The risk of CKD increased progressively with increasing number of metabolic syndrome components.

Ultrasound description of the coelomic cavity of the axolotl (Ambystoma mexicanum) in a clinically healthy population: a pilot study

Axolotls (Ambystoma mexicanum) are extensively studied for their relevance in human medical research. Despite being critically endangered in the wild, they have gained popularity as household pets. Although they have been kept in captivity for over a century, detailed descriptions of their coelomic organ anatomy remain limited. Also, this species exhibits significant variations compared to other amphibians. Ultrasound is a non-invasive and painless medical imaging technique, ideally suited for investigating internal organs or structures. This study focused on describing the ultrasound appearance of the axolotl coelomic cavity. It details the identification, localization and parenchymal description of major organs in 28 neotenic axolotls using ultrasound frequencies ranging from 7 to 15 MHz. The accuracy of the results was validated by comparing ultrasound findings with necropsy results from one male and one female axolotl. The heart, lung surface, liver and reproductive tracts were visualized. Measurements, along with confidence intervals, were calculated for the spleen, kidneys, testicles, gastric wall, gallbladder, and pylorus. Occasional detection of hyperechoic millimetric particles in the gallbladder or ascites was noted. However, visualization of the pancreas and bladder was not possible. This research outcomes involve the development of a comprehensive atlas comprising images obtained throughout the study. Additionally, the experiment established a reproducible and readily accessible protocol for conducting anatomy-morphological assessments in axolotl medicine. This protocol stands as a crucial preliminary stage before advancing to lesion identification.

Development of a Method for Automatic Matching of Unstructured Medical Data to ICD-10 Codes.

Inconsistent disease coding standards in medicine create hurdles in data exchange and analysis. This paper proposes a machine learning system to address this challenge. The system automatically matches unstructured medical text (doctor notes, complaints) to ICD-10 codes. It leverages a unique architecture featuring a training layer for model development and a knowledge base that captures relationships between symptoms and diseases. Experiments using data from a large medical research center demonstrated the system's effectiveness in disease classification prediction. Logistic regression emerged as the optimal model due to its superior processing speed, achieving an accuracy of 81.07% with acceptable error rates during high-load testing. This approach offers a promising solution to improve healthcare informatics by overcoming coding standard incompatibility and automating code prediction from unstructured medical text.

“Pre-Discharge Syndrome” in Gerontopsychiatric Practice: Clinical Manifestations and Risk Factors

Background: hospitalization of elderly patients is associated with social and psychological maladaptation, reduced levels of daily functioning, and development of hospitalism. Patients whose status suddenly worsened immediately prior to discharge from psychiatric hospital make up a group that is difficult for diagnostics and treatment and not sufficiently studied. The aim of the study was to analyze changes in patients’ status before planned discharge from hospital to identify clinical patterns of deterioration and factors associated with this adverse event. Patients and methods: study participants were selected from 181 consecutive patients of the Geriatric Psychiatry Department of V.M. Bekhterev National Medical Research Center for Psychiatry and Neurology. The main study methods were history-taking and psychological assessment. Results: predischarge deterioration was observed in 81 patients (44.8%) and was represented by exacerbation of mental disorder in 60 cases (33.2%), development of new symptoms in 12 patients (6.6%), or decompensation of somatic disease in 9 cases (5.0%). The history of patients with predischarge worsening was characterized by longer prior hospitalizations. These patients were more heavily pretreated, and had higher rates of hospitalism and non-compliance. For patients with worsening or development of new symptoms of mental disorder median duration of mental disease was respectively 84 and 204 months. They were more prone to violation of compliance, of the prescribed treatment regime and doses. Somatic decompensation occurred in patients with median duration of mental disorder 36 months and was associated with latent refusal to take medicines. Conclusions: an increased risk of predischarge deterioration in geropsychiatric patients with a history of prolonged hospitalizations needs earlier rehabilitation, psychotherapy, and psychological support when planning hospital discharge.

The Biomedicine Project Course: Promoting Young Scientists at School and University

This article presents a cooperation project between science and schools, which aims to provide high-achieving students with initial research experience at university and at the same time to encourage these students to take up medical or scientific courses of study. This is linked to the university's perspective of being able to attract potentially outstanding young scientists, especially in biomedical research. Thus, the project offers a win-win effect for all parties involved from school and university (Irmer, 2012). Feedback from an online survey of participating project students illustrates that even high demands can be motivating for students if the offer meets the students' interest and leads to experiences of self-efficacy. This article is intended to encourage the search for such opportunities for cooperation between schools and universities and to focus more strongly on their importance in generating young scientists.

Ufosomes as Topical/Transdermal Drug Delivery System: Structural Components, Preparation Techniques and Therapeutic Application.

Fatty acid vesicles, or ufasomes, are spherical structures that encapsulate and deliver bioactive molecules to the skin or other tissues. They are formed from both saturated and unsaturated fatty acids and offer advantages over liposomes, including greater stability and a wider range of pH compatibility. They are composed of two layers of fatty acid molecules with their hydrocarbon tails facing inwards and their carboxylic groups facing outwards. The space between the two layers is filled with surfactants. There are various methods for characterizing and evaluating the properties of vesicles and drug-loaded vesicles, such as differential scanning calorimetry (DSC), Electron microscopy, UV-visible spectrophotometry, Dialysis, Franz diffusion cell, and stability testing. Each method provides specific information about the vesicles, such as their size, zeta potential, morphology, drug content, entrapment efficiency, drug release, permeability, and stability. Ufasomes have potential applications in topical/transdermal drug delivery as food additives, cosmetics, vaccines, gene therapy vectors, and diagnostic tools. Their ability to encapsulate and deliver bioactive molecules makes them valuable in various fields, including drug delivery and biomedical research. In summary, fatty acid vesicles represent a versatile drug delivery system with potential applications in various fields.

Patients and Stakeholders' Perspectives Regarding the Privacy, Security, and Confidentiality of Data Collected via Mobile Health Apps in Saudi Arabia: Protocol for a Mixed Method Study.

There is data paucity regarding users' awareness of privacy concerns and the resulting impact on the acceptance of mobile health (mHealth) apps, especially in the Saudi context. Such information is pertinent in addressing users' needs in the Kingdom of Saudi Arabia (KSA). This article presents a study protocol for a mixed method study to assess the perspectives of patients and stakeholders regarding the privacy, security, and confidentiality of data collected via mHealth apps in the KSA and the factors affecting the adoption of mHealth apps. A mixed method study design will be used. In the quantitative phase, patients and end users of mHealth apps will be randomly recruited from various provinces in Saudi Arabia with a high population of mHealth users. The research instrument will be developed based on the emerging themes and findings from the interview conducted among stakeholders, app developers, health care professionals, and users of mHealth apps (n=25). The survey will focus on (1) how to improve patients' awareness of data security, privacy, and confidentiality; (2) feedback on the current mHealth apps in terms of data security, privacy, and confidentiality; and (3) the features that might improve data security, privacy, and confidentiality of mHealth apps. Meanwhile, specific sections of the questionnaire will focus on patients' awareness, privacy concerns, confidentiality concerns, security concerns, perceived usefulness, perceived ease of use, and behavioral intention. Qualitative data will be analyzed thematically using NVivo version 12. Descriptive statistics, regression analysis, and structural equation modeling will be performed using SPSS and partial least squares structural equation modeling. The ethical approval for this research has been obtained from the Biomedical and Scientific Research Ethics Committee, University of Warwick, and the Medical Research and Ethics Committee Ministry of Health in the KSA. The qualitative phase is ongoing and 15 participants have been interviewed. The interviews for the remaining 10 participants will be completed by November 25, 2023. Preliminary thematic analysis is still ongoing. Meanwhile, the quantitative phase will commence by December 10, 2023, with 150 participants providing signed and informed consent to participate in the study. The mixed methods study will elucidate the antecedents of patients' awareness and concerns regarding the privacy, security, and confidentiality of data collected via mHealth apps in the KSA. Furthermore, pertinent findings on the perspectives of stakeholders and health care professionals toward the aforementioned issues will be gleaned. The results will assist policy makers in developing strategies to improve Saudi users'/patients' adoption of mHealth apps and addressing the concerns raised to benefit significantly from these advanced health care modalities. DERR1-10.2196/54933.

Improving transparency of longitudinal health research: glossary, infographic and accessible study summaries

BackgroundLongitudinal studies collect information repeatedly about the same group of people, allowing for analyses of changes over time. They are vital in mental health research, as elsewhere. As longitudinal studies rely on the participation of patients and the public, their methods, purposes and results must be transparent and accessible. IntroductionMany UK longitudinal research studies with mental health data are indexed via the Catalogue of Mental Health Measures (‘Catalogue’), and organisations including DATAMIND provide broader information about mental health data research. However, the information on such platforms is primarily researcher-oriented, creating a barrier to its transparency and accessibility. Barriers can be alleviated by providing clear definitions of specialist terms, a transparent overview of longitudinal mental health research, and ‘bite-sized’ summaries of the Catalogue studies. MethodsThis project was co-designed and co-created by patient/public representatives from the DATAMIND Super Research Advisory Group (SRAG) and researchers. UK Health Data Research Alliance transparency standards were followed across the delivery of three outputs. (1) To provide clear definitions of specialist terms, SRAG members and researchers collected terms commonly used longitudinal research and researchers clarified definitions. Definitions were revised by SRAG members and terms were added to an existing data science glossary. (2) To create a transparent overview of longitudinal mental health research, the patient/public involvement (PPI) lead and SRAG co-applicant proposed content for an infographic about longitudinal research. The design was discussed with a graphic designer who created the infographic, and involved the PPI lead for the UK Longitudinal Linkage Collaboration. This was then revised iteratively for clarity, accessibility and diversity. (3) To generate accessible summaries of the Catalogue studies, psychology undergraduate students drafted summaries for an initial six studies, which were reviewed via a workshop led by the SRAG. Following revisions to the content and style, summaries were created for all 55+ studies on the Catalogue. Unfamiliar terms encountered during the process were also added to the glossary. ResultsThree new resources were created. (1) We developed a glossary of terms commonly used in longitudinal studies and research, to be incorporated into the DATAMIND glossary (https://datamind.org.uk/glossary/). (2) We created an infographic ‘storyboard’ to show how researchers, patients and the public can work together in the creation and curation of longitudinal research. The infographic illustrates the intertwined relationships between patients and the public, providing a transparent representation of challenges such as sharing studies, data access, patient benefit, and the importance and impact of public involvement. It illustrates many ways to find out about longitudinal research. (3) Accessible and transparent short summaries were created for all longitudinal studies in the Catalogue (https://www.cataloguementalhealth.ac.uk/). These provide clear and concise overviews, enough to capture the essence of each study and inform researchers and the public quickly and easily. ConclusionsCo-production supports the transparency of longitudinal research, and ensures resources designed and produced for the public have public input. Two generic information resources and one specific resource are presented. AcknowledgementsProject funded by HDR UK (HDRUK2023.0465). DATAMIND is funded by the Medical Research Council (MR/W014386/1). All research at the Department of Psychiatry in the University of Cambridge is supported by the NIHR Cambridge Biomedical Research Centre (NIHR203312) and the NIHR Applied Research Collaboration East of England; the views expressed are those of the author(s) and not necessarily those of the NIHR or the Department of Health and Social Care.

Click Chemistry: Reaction Rates and Their Suitability for Biomedical Applications.

Click chemistry has become a commonly used synthetic method due to the simplicity, efficiency, and high selectivity of this class of chemical reactions. Since their initial discovery, further click chemistry methods have been identified and added to the toolbox of click chemistry reactions for biomedical applications. However, selecting the most suitable reaction for a specific application is often challenging, as multiple factors must be considered, including selectivity, reactivity, biocompatibility, and stability. Thus, this review provides an overview of the benefits and limitations of well-established click chemistry reactions with a particular focus on the importance of considering reaction rates, an often overlooked criterion with little available guidance. The importance of understanding each click chemistry reaction beyond simply the reaction speed is discussed comprehensively with reference to recent biomedical research which utilized click chemistry. This review aims to provide a practical resource for researchers to guide the selection of click chemistry classes for different biomedical applications.

Upper limb muscle strength and exercise endurance as predictors of successful extubation in mechanically ventilated patients

BackgroundFailed extubation increases the intensive care unit (ICU) length of stay, hospital length of stay, and financial costs and it reduces the patient’s functional ability. Avoiding failed extubation is of utmost importance, therefore predictors for successful extubation are paramount.ObjectiveTo determine if successful extubation in mechanically ventilated patients can be predicted by physiotherapists using upper limb muscle strength and exercise endurance.MethodsFifty-seven patients from the medical and trauma ICUs of a large academic hospital were eligible for testing. Muscle strength was evaluated using the Oxford grading scale, Medical Research Council score (MRC score), handgrip dynamometer, and maximum inspiratory pressure (MIP). Exercise endurance was tested while the patient was actively riding the MOTOmed® letto2 cycle ergometer for six minutes with the upper limbs.ResultsExercise endurance (time the patient rode actively) (P = 0.005), MRC-score (P = 0.007), and number of days ventilated (P = 0.005) were associated with successful extubation. The handgrip strength (P = 0.061), MIP (P = 0.095), and muscle strength of the sternocleidomastoid (P = 0.053) and trapezius muscles (P = 0.075) were marginally associated with successful extubation. Due to multicollinearity when developing the prediction equation, the final multivariable logistic regression prediction model included only exercise endurance and the number of days ventilated. The newly developed prediction equation conferred a sensitivity of 81.82% and a specificity of 77.14% to predict successful extubation.ConclusionSuccessful extubation of mechanically ventilated patients can be predicted by physiotherapists using the newly developed prediction equation consisting of exercise endurance and number of days ventilated.

Skylark Wiki: Accessing research data of the MRC National Survey of Health and Development

Background & IntroductionThe Medical Research Council National Survey of Health and Development (NSHD) is the oldest and longest-running of the British birth cohort studies. In 2018 we launched the Skylark Wiki, a central metadata repository and the first port of call for any data sharing queries. In 2023 we utilised the HDRUK funding initiative to work with our advisory group and research community to improve the transparency of our data access process and make the content more accessible. MethodsWe conducted a focus group session with the NSHD Participant Advisory Panel to understand their views on the data sharing process and whether the information we provided them, sufficiently explained how their data are shared. We also sent out a questionnaire to all Skylark Users to identify areas of improvement. Lastly, we undertook an audit of the website’s content and used Google Analytics to see how Users navigated across the site. Combining all this information we identified areas requiring improvements, from the point of view of our stakeholders, and comparing these to the requirements indicated in the HDRUK Transparency Standards we mapped out updates to the Skylark Wiki. The work was carried out by an external agency (Aubergine262 Ltd). ResultsTo increase transparency and searchability, we improved the flow diagram of the data sharing process to include links to the relevant web pages. We also created guidance to explain why the information in the data request application form is being asked. As feedback from Skylark Users suggested difficulties in finding the required information, the navigation has been updated. We have also changed the layout of the front page to include navigation boxes that takes users straight to the content. The NSHD Advisory Panel reinforced the notion of trust that study participants place in the study and its approach to data sharing. They confirmed the information provided on data sharing was adequate and appreciated that this information was placed on the main study website (https://nshd.mrc.ac.uk/) for their benefit. Initial feedback from Users indicates that it is easier to find information on the website. We will keep monitoring access to the website, the number of queries, and data access requests to evaluate long-term benefits. We have changed the sitemap and added in large link boxes, to make it easier to find the different sections. We hope this will improve the searchability of the site so users can find information they required. We hope this will therefore lead to fewer emails and correspondence between the data sharing team and users. We have also updated the flow diagram of the data sharing process to include links to the web pages which are related to that section. We hope this will help the users find the information they require. ConclusionsThe new Skylark data-sharing website supports easier navigation providing a better User experience. In return, this should lead to fewer queries from Users. The website will be easier to maintain having changed the content management system from a Wiki to WordPress. WordPress requires less technical knowledge, allowing more staff to contribute to regular maintenance. References Skylark data-sharing website: https://skylark.ucl.ac.uk/NSHD/ Aubergine: https://www.aubergine262.com/

The advancement of artificial intelligence in biomedical research and health innovation: challenges and opportunities in emerging economies

The advancement of artificial intelligence (AI), algorithm optimization and high-throughput experiments has enabled scientists to accelerate the discovery of new chemicals and materials with unprecedented efficiency, resilience and precision. Over the recent years, the so-called autonomous experimentation (AE) systems are featured as key AI innovation to enhance and accelerate research and development (R&D). Also known as self-driving laboratories or materials acceleration platforms, AE systems are digital platforms capable of running a large number of experiments autonomously. Those systems are rapidly impacting biomedical research and clinical innovation, in areas such as drug discovery, nanomedicine, precision oncology, and others. As it is expected that AE will impact healthcare innovation from local to global levels, its implications for science and technology in emerging economies should be examined. By examining the increasing relevance of AE in contemporary R&D activities, this article aims to explore the advancement of artificial intelligence in biomedical research and health innovation, highlighting its implications, challenges and opportunities in emerging economies. AE presents an opportunity for stakeholders from emerging economies to co-produce the global knowledge landscape of AI in health. However, asymmetries in R&D capabilities should be acknowledged since emerging economies suffers from inadequacies and discontinuities in resources and funding. The establishment of decentralized AE infrastructures could support stakeholders to overcome local restrictions and opens venues for more culturally diverse, equitable, and trustworthy development of AI in health-related R&D through meaningful partnerships and engagement. Collaborations with innovators from emerging economies could facilitate anticipation of fiscal pressures in science and technology policies, obsolescence of knowledge infrastructures, ethical and regulatory policy lag, and other issues present in the Global South. Also, improving cultural and geographical representativeness of AE contributes to foster the diffusion and acceptance of AI in health-related R&D worldwide. Institutional preparedness is critical and could enable stakeholders to navigate opportunities of AI in biomedical research and health innovation in the coming years.

Plasma-derived extracellular matrix for xenofree and cost-effective organoid modeling for hepatocellular carcinoma

BackgroundHepatocellular carcinoma (HCC) causes significant cancer mortality worldwide. Cancer organoids can serve as useful disease models by high costs, complexity, and contamination risks from animal-derived products and extracellular matrix (ECM) that limit its applications. On the other hand, synthetic ECM alternatives also have limitations in mimicking native biocomplexity. This study explores the development of a physiologically relevant HCC organoid model using plasma-derived extracellular matrix as a scaffold and nutritive biomatrix with different cellularity components to better mimic the heterogenous HCC microenvironment. Plasma-rich platelet is recognized for its elevated levels of growth factors, which can promote cell proliferation. By employing it as a biomatrix for organoid culture there is a potential to enhance the quality and functionality of organoid models for diverse applications in biomedical research and regenerative medicine and to better replicate the heterogeneous microenvironment of HCC.MethodTo generate the liver cancer organoids, HUH-7 hepatoma cells were cultured alone (homogenous model) or with human bone marrow-derived mesenchymal stromal cells and human umbilical vein endothelial cells (heterogeneous model) in plasma-rich platelet extracellular matrix (ECM). The organoids were grown for 14 days and analyzed for cancer properties including cell viability, invasion, stemness, and drug resistance.ResultsHCC organoids were developed comprising HUH-7 hepatoma cells with or without human mesenchymal stromal and endothelial cells in plasma ECM scaffolds. Both homogeneous (HUH-7 only) and heterogeneous (mixed cellularity) organoids displayed viability, cancer hallmarks, and chemoresistance. The heterogeneous organoids showed enhanced invasion potential, cancer stem cell populations, and late-stage HCC genetic signatures versus homogeneous counterparts.ConclusionThe engineered HCC organoids system offers a clinically relevant and cost-effective model to study liver cancer pathogenesis, stromal interactions, and drug resistance. The plasma ECM-based culture technique could enable standardized and reproducible HCC modeling. It could also provide a promising option for organoid culture and scaling up.

Zigzag boron nitride nanotube functionalization as a sensor for the recognition of group IIA (Mg2+, Ca2+) metal ions, quasi-metal (Si2+, Ge2+) ions, and transition metal (Cu2+, Zn2+) ions: a computational study.

Boron nitride nanotubes (BNNTs) provide an exceptional and sophisticated platform for detecting metal ions with high surface area and remarkable chemical stability. Metal cations tend to bind to the surface of BNNTs, which leads to significant changes in the electrical properties of nanotubes. BNNT-based metal ion sensors have shown promising results in various applications, including water quality monitoring, biomedical research, industrial quality control, and environmental monitoring. In the present study, we have explored the electronic sensitivity of the BNNT to metal ions (Si2+, Ge2+, Cu2+, Zn2+, Mg2+, and Ca2+). The interaction between the ions with the pristine BNNT is performed in the solution phase. The results show that ion adsorption on the nanotube surface is exothermic and favorable. The density of states calculation is presented to investigate the electronic properties of the nanotube during the adsorption process. The results display that an increase in the electrical conductivity of the complexes accompanies the reduction in the energy gap. Based on the obtained data, the Si2+ and Ge2+ cations adsorbed on the BNNT with satisfactory Eg changes (%ΔE) can be promising candidates for better sensing ability. All calculations are conducted within the density functional theory (DFT) using the ωB97XD functional and 6-31G(d,p) basis set. The present approach incorporates the utilization of empirical atom-atom dispersion in conjunction with long-range correction. The calculations are performed using the quantum chemistry package GAMESS, and the obtained results are visualized by employing the GaussView 6.0.16 program.