The barriers and facilitators to the design and delivery of sustainable healthcare across NHS Scotland: A forcefield analysis.

Healthcare systems around the world have set ambitious targets to design and deliver more environmentally sustainable healthcare. To achieve these targets, individuals, teams, organisations, and whole systems will have to change current attitudes, practices and processes. Change management theory advocates for early identification of the influencing forces to change, so that actions can be taken to overcome the barriers and strengthen the facilitators to increase the likelihood of success. This project undertook a forcefield analysis exercise to identify the barriers and facilitators to the design and delivery of sustainable healthcare in Scotland. The exercise identified 12 facilitators and 12 barriers to sustainable change and formulated ten recommendations to strengthen the former and overcome the latter. It is hoped that the results will raise awareness of the factors that influence the design and delivery of sustainable healthcare and will inform what actions can be taken to increase the likelihood of success.

Comparable safety and non-inferior immunogenicity of the SARS-CoV-2 mRNA vaccine candidate PTX-COVID19-B and BNT162b2 in a phase 2 randomized, observer-blinded study.

In the aftermath of the COVID-19 pandemic, the evolution of the SARS-CoV-2 into a seasonal pathogen along with the emergence of new variants, underscores the need for dynamic and adaptable responses, emphasizing the importance of sustained vaccination strategies. This observer-blind, double-dummy, randomized immunobridging phase 2 study (NCT05175742) aimed to compare the immunogenicity induced by two doses of 40 µg PTX-COVID19-B vaccine candidate administered 28 days apart, with the response induced by two doses of 30 µg Pfizer-BioNTech COVID-19 vaccine (BNT162b2), administered 21 days apart, in Nucleocapsid-protein seronegative adults 18-64 years of age. Both vaccines were administrated via intramuscular injection in the deltoid muscle. Two weeks after the second dose, the neutralizing antibody (NAb) geometric mean titer ratio and seroconversion rate met the non-inferiority criteria, successfully achieving the primary immunogenicity endpoints of the study. PTX-COVID19-B demonstrated similar safety and tolerability profile to BNT162b2 vaccine. The lowest NAb response was observed in subjects with low-to-undetectable NAb at baseline or no reported breakthrough infection. Conversely, participants who experienced breakthrough infections during the study exhibited higher NAb titers. This study also shows induction of cell-mediated immune (CMI) responses by PTX-COVID19-B. In conclusion, the vaccine candidate PTX-COVID19-B demonstrated favourable safety profile along with immunogenicity similar to the active comparator BNT162b2 vaccine.

The Association Between Well-Being and Empathy in Medical Residents: A Cross-Sectional Survey.

Objective: To evaluate the extent to which personal well-being may be associated with empathy, while controlling for potential confounders. Settings/Location: Residency programs throughout the United States. Subjects: A total of 407 medical residents from residencies including general medicine, surgery, specialized and diagnostic medicine participated in this study. Outcome Measures: Well-being was measured using the modified existential well-being subscale of the spiritual well-being scale. Empathy was measured using the Jefferson Scale of Empathy. Results: Well-being was found to be positively correlated with empathy when adjusted for possible confounders (p < 0.001). In addition to well-being, other factors noted to be statistically significant contributors to higher empathy scores while controlling for the others included age, gender, year in residency, specialty, and work-hours (p < 0.05 for each). After controlling for these factors, a resident's year in residency was not found to be a statistically significant contributor to empathy score. Conclusions: In this study, well-being was associated with empathy in medical and surgical residents. Empathy is a fundamental component of physician competency, and its development is an essential aspect of medical training. These findings suggest that efforts to increase well-being may promote empathy among medical residents.

Clinical correlates of CT imaging-derived phenotypes among lean and overweight patients with hepatic steatosis.

The objective of this study is to define CT imaging derived phenotypes for patients with hepatic steatosis, a common metabolic liver condition, and determine its association with patient data from a medical biobank. There is a need to further characterize hepatic steatosis in lean patients, as its epidemiology may differ from that in overweight patients. A deep learning method determined the spleen-hepatic attenuation difference (SHAD) in Hounsfield Units (HU) on abdominal CT scans as a quantitative measure of hepatic steatosis. The patient cohort was stratified by BMI with a threshold of 25 kg/m2 and hepatic steatosis with threshold SHAD ≥ - 1 HU or liver mean attenuation ≤ 40 HU. Patient characteristics, diagnoses, and laboratory results representing metabolism and liver function were investigated. A phenome-wide association study (PheWAS) was performed for the statistical interaction between SHAD and the binary characteristic LEAN. The cohort contained 8914 patients-lean patients with (N = 278, 3.1%) and without (N = 1867, 20.9%) steatosis, and overweight patients with (N = 1863, 20.9%) and without (N = 4906, 55.0%) steatosis. Among all lean patients, those with steatosis had increased rates of cardiovascular disease (41.7 vs 27.8%), hypertension (86.7 vs 49.8%), and type 2 diabetes mellitus (29.1 vs 15.7%) (all p < 0.0001). Ten phenotypes were significant in the PheWAS, including chronic kidney disease, renal failure, and cardiovascular disease. Hepatic steatosis was found to be associated with cardiovascular, kidney, and metabolic conditions, separate from overweight BMI.

Text mining-based identification of promising miRNA biomarkers for diabetes mellitus.

Introduction: MicroRNAs (miRNAs) are small, non-coding RNAs that play a critical role in diabetes development. While individual studies investigating the mechanisms of miRNA in diabetes provide valuable insights, their narrow focus limits their ability to provide a comprehensive understanding of miRNAs' role in diabetes pathogenesis and complications. Methods: To reduce potential bias from individual studies, we employed a text mining-based approach to identify the role of miRNAs in diabetes and their potential as biomarker candidates. Abstracts of publications were tokenized, and biomedical terms were extracted for topic modeling. Four machine learning algorithms, including Naïve Bayes, Decision Tree, Random Forest, and Support Vector Machines (SVM), were employed for diabetes classification. Feature importance was assessed to construct miRNA-diabetes networks. Results: Our analysis identified 13 distinct topics of miRNA studies in the context of diabetes, and miRNAs exhibited a topic-specific pattern. SVM achieved a promising prediction for diabetes with an accuracy score greater than 60%. Notably, miR-146 emerged as one of the critical biomarkers for diabetes prediction, targeting multiple genes and signal pathways implicated in diabetic inflammation and neuropathy. Conclusion: This comprehensive approach yields generalizable insights into the network miRNAs-diabetes network and supports miRNAs' potential as a biomarker for diabetes.

Identifying miRNA biomarkers for breast cancer and ovarian cancer: a text mining perspective.

BACKGROUND: microRNA (miRNAs) are small, non-coding RNAs that mediate post-transcriptional gene silencing. Numerous studies have demonstrated the critical role of miRNAs in the development of breast cancer and ovarian cancer. To reduce potential bias from individual studies, a more comprehensive approach of exploring miRNAs in cancer research is essential. This study aims to explore the role of miRNAs in the development of breast cancer and ovarian cancer. METHODS: Abstracts of the publications were tokenized and the biomedical terms (miRNA, gene, disease, species) were identified and extracted for vectorization. Predictive analyses were conducted with four machine learning models: K-Nearest Neighbors (KNN), Support Vector Machines (SVM), Random Forest (RF), and Naïve Bayes. Both holdout validation and cross-validation were utilized. Feature importance will be identified for miRNA-cancer networks construction. RESULTS: We found that miR-182 is highly specific to female cancers. miR-182 targets different genes in regulating breast cancer and ovarian cancer. Naïve Bayes provided a promising prediction model for breast cancer and ovarian cancer with miRNAs and genes combination, with an accuracy score greater than 60%. Feature importance identified miR-155 and miR-199 are critical for breast cancer and ovarian cancer prediction, with miR-155 being highly related to breast cancer, whereas miR-199 being more associated with ovarian cancer. CONCLUSION: Our approach effectively identified potential miRNA biomarkers associated with breast cancer and ovarian cancer, providing a solid foundation for generating novel research hypotheses and guiding future experimental studies.

Longitudinal Cadaver-Based Training Curriculum for Musculoskeletal Ultrasound-Guided Procedures Among Physical Medicine and Rehabilitation Residents.

ABSTRACT: Musculoskeletal ultrasound has become a fundamental diagnostic and treatment tool in the field of physical medicine and rehabilitation. However, there is no standardized curriculum for teaching and practicing musculoskeletal ultrasound during physical medicine and rehabilitation residency. The objective of this study was to describe a longitudinal curriculum using unembalmed fresh frozen cadavers to teach physical medicine and rehabilitation residents ultrasound-guided procedures. This protocol can help guide residents to begin learning how to independently identify important musculoskeletal structures and perform some of the most common musculoskeletal procedures relevant to clinical practice. Residents performed a procedure on average 6.99 times per block, and residents' self-reported confidence in various aspects of ultrasound practice significantly improved after this curriculum ( P < 0.005). Hence, a cadaver-based training curriculum may be a worthwhile tool for preparing physical medicine and rehabilitation residents to perform musculoskeletal ultrasound-guided procedures in the clinical setting.

A comprehensive review of computational and image analysis techniques for quantitative evaluation of striated muscle tissue architecture.

Unbiased evaluation of morphology is crucial to understanding development, mechanics, and pathology of striated muscle tissues. Indeed, the ability of striated muscles to contract and the strength of their contraction is dependent on their tissue-, cellular-, and cytoskeletal-level organization. Accordingly, the study of striated muscles often requires imaging and assessing aspects of their architecture at multiple different spatial scales. While an expert may be able to qualitatively appraise tissues, it is imperative to have robust, repeatable tools to quantify striated myocyte morphology and behavior that can be used to compare across different labs and experiments. There has been a recent effort to define the criteria used by experts to evaluate striated myocyte architecture. In this review, we will describe metrics that have been developed to summarize distinct aspects of striated muscle architecture in multiple different tissues, imaged with various modalities. Additionally, we will provide an overview of metrics and image processing software that needs to be developed. Importantly to any lab working on striated muscle platforms, characterization of striated myocyte morphology using the image processing pipelines discussed in this review can be used to quantitatively evaluate striated muscle tissues and contribute to a robust understanding of the development and mechanics of striated muscles.

Interventions to prevent HIV and Hepatitis C among people who inject drugs: Latest evidence of effectiveness from a systematic review (2011 to 2020).

BACKGROUND: Hepatitis C virus (HCV) and HIV remain prevalent among people who inject drugs (PWID) and transmission is usually associated with injecting risk behaviour (IRB). We update a 2011 review of reviews (RoR) to assess the latest evidence on the effectiveness of harm reduction interventions - drug treatment (including opioid agonist therapy [OAT]), needle and syringe programmes (NSP) and other interventions - in the prevention of HCV and HIV transmission, and related measures of infection risk (IRB and injecting frequency [IF]), among PWID. METHODS: We undertook an initial search for systematic reviews (i.e. an Overview of Reviews [OoR]) and subsequent systematic searches for primary studies where required. Where there was sufficient evidence based on synthesis of multiple robust studies for an intervention effect in the 2011 RoR, new evidence was not sought. Medline, CINAHL, The Cochrane Library, EMBASE, PsycINFO and Web of Science were searched (2011-2020). Two reviewers screened papers, extracted data, and graded reviews/studies. We classified evidence as 'sufficient', 'tentative', 'insufficient', or 'no evidence'. RESULTS: We screened 8513 reviews and 7133 studies, with 27 and 61 identified as relevant, respectively. The level of evidence increased since the 2011 RoR and is now 'sufficient' for OAT (regarding all outcomes), NSP (for reducing HIV transmission and IRB), and combination OAT/NSP (for reducing HCV transmission). There is also now sufficient evidence for in-prison OAT, psychosocial interventions, pharmacy-based NSP and provision of sterile drug preparation equipment for reducing IRB. CONCLUSION: There is now a strong body of empirical evidence for the effectiveness of OAT and NSP, alone and in combination, in reducing IRB, and HCV and HIV transmission. However, there is still a relative lack of evidence for other interventions, including heroin-assisted treatment, pharmacological treatment for stimulant dependence, contingency management, technology-based interventions, low dead space syringes and drug consumption rooms on HCV or HIV risk.

Screening of bimetallic electrocatalysts for water purification with machine learning.

Electrocatalysis provides a potential solution to NO3 - pollution in wastewater by converting it to innocuous N2 gas. However, materials with excellent catalytic activity are typically limited to expensive precious metals, hindering their commercial viability. In response to this challenge, we have conducted the most extensive computational search to date for electrocatalysts that can facilitate NO3 - reduction reaction, starting with 59 390 candidate bimetallic alloys from the Materials Project and Automatic-Flow databases. Using a joint machine learning- and computation-based screening strategy, we evaluated our candidates based on corrosion resistance, catalytic activity, N2 selectivity, cost, and the ability to synthesize. We found that only 20 materials will satisfy all criteria in our screening strategy, all of which contain varying amounts of Cu. Our proposed list of candidates is consistent with previous materials investigated in the literature, with the exception of Cu-Co and Cu-Ag based compounds that merit further investigation.

Development of Biodegradable Osteopromotive Citrate-Based Bone Putty.

The burden of bone fractures demands development of effective biomaterial solutions, while additional acute events such as noncompressible bleeding further motivate the search for multi-functional implants to avoid complications including osseous hemorrhage, infection, and nonunion. Bone wax has been widely used in orthopedic bleeding control due to its simplicity of use and conformation to irregular defects; however, its nondegradability results in impaired bone healing, risk of infection, and significant inflammatory responses. Herein, a class of intrinsically fluorescent, osteopromotive citrate-based polymer/hydroxyapatite (HA) composites (BPLP-Ser/HA) as a highly malleable press-fit putty is designed. BPLP-Ser/HA putty displays mechanics replicating early nonmineralized bone (initial moduli from ≈2-500 kPa), hydration induced mechanical strengthening in physiological conditions, tunable degradation rates (over 2 months), low swelling ratios (<10%), clotting and hemostatic sealing potential (resistant to blood pressure for >24 h) and significant adhesion to bone (≈350-550 kPa). Simultaneously, citrate's bioactive properties result in antimicrobial (≈100% and 55% inhibition of S. aureus and E. coli) and osteopromotive effects. Finally, BPLP-Ser/HA putty demonstrates in vivo regeneration in a critical-sized rat calvaria model equivalent to gold standard autograft. BPLP-Ser/HA putty represents a simple, off-the-shelf solution to the combined challenges of acute wound management and subsequent bone regeneration.

Social Determinants of Disparities in Mortality Outcomes in Congenital Heart Disease: A Systematic Review and Meta-Analysis.

Background: Social determinants of health (SDoH) affect congenital heart disease (CHD) mortality across all forms and age groups. We sought to evaluate risk of mortality from specific SDoH stratified across CHD to guide interventions to alleviate this risk. Methods: We searched electronic databases between January 1980 and June 2019 and included studies that evaluated occurrence of CHD deaths and SDoH in English articles. Meta-analysis was performed if SDoH data were available in >3 studies. We included race/ethnicity, deprivation, insurance status, maternal age, maternal education, single/multiple pregnancy, hospital volume, and geographic location of patients as SDoH. Data were pooled using random-effects model and outcome was reported as odds ratio (OR) with 95% confidence interval (CI). Results: Of 17,716 citations reviewed, 65 met inclusion criteria. Sixty-three were observational retrospective studies and two prospective. Of 546,981 patients, 34,080 died. Black patients with non-critical CHD in the first year of life (Odds Ratio 1.62 [95% confidence interval 1.47-1.79], I2 = 7.1%), with critical CHD as neonates (OR 1.27 [CI 1.05-1.55], I2 = 0%) and in the first year (OR 1.68, [1.45-1.95], I2 = 0.3%) had increased mortality. Deprived patients, multiple pregnancies, patients born to mothers <18 years and with education <12 years, and patients on public insurance with critical CHD have greater likelihood of death after the neonatal period. Conclusion: This systematic review and meta-analysis found that Black patients with CHD are particularly vulnerable for mortality. Numerous SDoH that affect mortality were identified for specific time points in CHD course that may guide interventions, future research and policy. Systematic Review Registration: [https://www.crd.york.ac.uk/PROSPERO/display_record.php?ID=CRD42019139466&ID=CRD42019139466], identifier [CRD42019139466].

A functional genomic approach to actionable gene fusions for precision oncology.

Fusion genes represent a class of attractive therapeutic targets. Thousands of fusion genes have been identified in patients with cancer, but the functional consequences and therapeutic implications of most of these remain largely unknown. Here, we develop a functional genomic approach that consists of efficient fusion reconstruction and sensitive cell viability and drug response assays. Applying this approach, we characterize ~100 fusion genes detected in patient samples of The Cancer Genome Atlas, revealing a notable fraction of low-frequency fusions with activating effects on tumor growth. Focusing on those in the RTK-RAS pathway, we identify a number of activating fusions that can markedly affect sensitivity to relevant drugs. Last, we propose an integrated, level-of-evidence classification system to prioritize gene fusions systematically. Our study reiterates the urgent clinical need to incorporate similar functional genomic approaches to characterize gene fusions, thereby maximizing the utility of gene fusions for precision oncology.