How early clinical experiences in rural communities influence student learning about rural generalism considered through the lens of educational theory.

Introduction: Rural communities have poorer health compared to urban populations due partly to having lesser healthcare access. Rural placements during medical education can equip students with the knowledge and skills to work in rural communities, and, it is hoped, increase the supply of rural physicians. It is unclear how students gain knowledge of rural generalism during placements, and how this can be understood in terms of place-based and/or sociocultural educational theories. To gain insight into these questions we considered the experiences of pre-clerkship medical students who completed two mandatory four-week rural placements during their second year of medical school. Methods: Data was collected using semi-structured interviews or focus groups, followed by thematic analysis of the interview transcripts. Results: Rural placements allowed students to learn about rural generalism such as breadth of practice, and boundary issues. This occurred mainly by students interacting with rural physician faculty, with the effectiveness of precepting being key to students acquiring knowledge and skills and reporting a positive regard for the placement experience. Discussion: Our data show the central role of generalist physician preceptors in how and what students learn while participating in rural placements. Sociocultural learning theory best explains student learning, while place-based education theory helps inform the curriculum. Effective training and preparation of preceptors is likely key to positive student placement experiences.

Introduction: Les communautés rurales sont en moins bonne santé que les populations urbaines, en partie parce qu'elles ont moins accès aux soins de santé. Les stages de médecine en milieu rural peuvent permettre aux étudiants d'acquérir les connaissances et les compétences nécessaires pour travailler dans les communautés rurales et, on l'espère, augmenter le nombre de médecins y travaillent. On ne sait pas clairement comment les étudiants acquièrent des connaissances sur le généralisme rural au cours de leurs stages, et comment cela peut être compris en termes de théories éducatives socioculturelles et/ou basées sur le lieu de travail. Pour répondre à ces questions, nous avons étudié les expériences d'étudiants en médecine au pré-clinique qui ont effectué deux stages obligatoires de quatre semaines en milieu rural au cours de leur deuxième année d'études de médecine. Méthodes: Les données ont été recueillies au moyen d'entrevues semi-structurées ou de groupes de discussion, suivis d'une analyse thématique des transcriptions des entrevues. Résultats: Les stages en milieu rural ont permis aux étudiants de se familiariser avec le généralisme rural, notamment l'étendue de la pratique et les questions de limites. L'efficacité du préceptorat est essentielle pour que les étudiants acquièrent des connaissances et des compétences et qu'ils aient une expérience de stage positive. Discussion: Nos données témoignent du rôle central que jouent les médecins généralistes précepteurs quant au contenu et modes d'apprentissage des étudiants lorsqu'ils participent à des stages en milieu rural. La théorie de l'apprentissage socioculturel est celle qui explique le mieux l'apprentissage des étudiants, tandis que la théorie de la formation fondée sur le lieu contribue à orienter le programme d'études. Une formation et préparation efficace des précepteurs est probablement la clé d'une expérience de stage positive pour les étudiants.

Local Assessment and Small Bowel Crohn's Disease Severity Scoring using AI.

RATIONALE AND OBJECTIVES: We present a machine learning and computer vision approach for a localized, automated, and standardized scoring of Crohn's disease (CD) severity in the small bowel, overcoming the current limitations of manual measurements CT enterography (CTE) imaging and qualitative assessments, while also considering the complex anatomy and distribution of the disease. MATERIALS AND METHODS: Two radiologists introduced a severity score and evaluated disease severity at 7.5 mm intervals along the curved planar reconstruction of the distal and terminal ileum using 236 CTE scans. A hybrid model, combining deep-learning, 3-D CNN, and Random Forest model, was developed to classify disease severity at each mini-segment. Precision, sensitivity, weighted Cohen's score, and accuracy were evaluated on a 20% hold-out test set. RESULTS: The hybrid model achieved precision and sensitivity ranging from 42.4% to 84.1% for various severity categories (normal, mild, moderate, and severe) on the test set. The model's Cohen's score (κ = 0.83) and accuracy (70.7%) were comparable to the inter-observer agreement between experienced radiologists (κ = 0.87, accuracy = 76.3%). The model accurately predicted disease length, correlated with radiologist-reported disease length (r = 0.83), and accurately identified the portion of total ileum containing moderate-to-severe disease with an accuracy of 91.51%. CONCLUSION: The proposed automated hybrid model offers a standardized, reproducible, and quantitative local assessment of small bowel CD severity and demonstrates its value in CD severity assessment.

Allergen-Encapsulating Nanoparticles Reprogram Pathogenic Allergen-Specific Th2 Cells to Suppress Food Allergy.

Food allergy is a prevalent, potentially deadly disease caused by inadvertent sensitization to benign food antigens. Pathogenic Th2 cells are a major driver for disease, and allergen-specific immunotherapies (AIT) aim to increase the allergen threshold required to elicit severe allergic symptoms. However, the majority of AIT approaches require lengthy treatments and convey transient disease suppression, likely due to insufficient targeting of pathogenic Th2 responses. Here, the ability of allergen-encapsulating nanoparticles to directly suppress pathogenic Th2 responses and reactivity is investigated in a mouse model of food allergy. NPs associate with pro-tolerogenic antigen presenting cells, provoking accumulation of antigen-specific, functionally suppressive regulatory T cells in the small intestine lamina propria. Two intravenous doses of allergen encapsulated in poly(lactide-co-glycolide) nanoparticles (NPs) significantly reduces oral food challenge (OFC)-induced anaphylaxis. Importantly, NP treatment alters the fates of pathogenic allergen-specific Th2 cells, reprogramming these cells toward CD25+FoxP3+ regulatory and CD73+FR4+ anergic phenotypes. NP-mediated reductions in the frequency of effector cells in the gut and mast cell degranulation following OFC are also demonstrated. These studies reveal mechanisms by which an allergen-encapsulating NP therapy and, more broadly, allergen-specific immunotherapies, can rapidly attenuate allergic responses by targeting pathogenic Th2 cells.

Artificial Intelligence for Quantifying Cumulative Small Bowel Disease Severity on CT-Enterography in Crohn's Disease.

INTRODUCTION: Assessing the cumulative degree of bowel injury in ileal Crohn's disease (CD) is difficult. We aimed to develop machine learning (ML) methodologies for automated estimation of cumulative ileal injury on computed tomography-enterography (CTE) to help predict future bowel surgery. METHODS: Adults with ileal CD using biologic therapy at a tertiary care center underwent ML analysis of CTE scans. Two fellowship-trained radiologists graded bowel injury severity at granular spatial increments along the ileum (1 cm), called mini-segments. ML segmentation methods were trained on radiologist grading with predicted severity and then spatially mapped to the ileum. Cumulative injury was calculated as the sum (S-CIDSS) and mean of severity grades along the ileum. Multivariate models of future small bowel resection were compared with cumulative ileum injury metrics and traditional bowel measures, adjusting for laboratory values, medications, and prior surgery at the time of CTE. RESULTS: In 229 CTE scans, 8,424 mini-segments underwent analysis. Agreement between ML and radiologists injury grading was strong (κ = 0.80, 95% confidence interval 0.79-0.81) and similar to inter-radiologist agreement (κ = 0.87, 95% confidence interval 0.85-0.88). S-CIDSS (46.6 vs 30.4, P = 0.0007) and mean cumulative injury grade scores (1.80 vs 1.42, P < 0.0001) were greater in CD biologic users that went to future surgery. Models using cumulative spatial metrics (area under the curve = 0.76) outperformed models using conventional bowel measures, laboratory values, and medical history (area under the curve = 0.62) for predicting future surgery in biologic users. DISCUSSION: Automated cumulative ileal injury scores show promise for improving prediction of outcomes in small bowel CD. Beyond replicating expert judgment, spatial enterography analysis can augment the personalization of bowel assessment in CD.

Quantitative MRI reveals heterogeneous impacts of treatment on diseased bone marrow in a mouse model of myelofibrosis.

PURPOSE: Analyzing bone marrow in the hematologic cancer myelofibrosis requires endpoint histology in mouse models and bone marrow biopsies in patients. These methods hinder the ability to monitor therapy over time. Preclinical studies typically begin treatment before mice develop myelofibrosis, unlike patients who begin therapy only after onset of disease. Using clinically relevant, quantitative MRI metrics allowed us to evaluate treatment in mice with established myelofibrosis. METHODS: We used chemical shift-encoded fat imaging, DWI, and magnetization transfer sequences to quantify bone marrow fat, cellularity, and macromolecular components in a mouse model of myelofibrosis. We monitored spleen volume, the established imaging marker for treatment, with anatomic MRI. After confirming bone marrow disease by MRI, we randomized mice to treatment with an approved drug (ruxolitinib or fedratinib) or an investigational agent, navitoclax, for 33 days. We measured the effects of therapy over time with bone marrow and spleen MRI. RESULTS: All treatments produced heterogeneous responses with improvements in bone marrow evident in subsets of individual mice in all treatment groups. Reductions in spleen volume commonly occurred without corresponding improvement in bone marrow. MRI revealed patterns associated with effective and ineffective responses to treatment in bone marrow and identified regional variations in efficacy within a bone. CONCLUSIONS: Quantitative MRI revealed modest, heterogeneous improvements in bone marrow disease when treating mice with established myelofibrosis. These results emphasize the value of bone marrow MRI to assess treatment in preclinical models and the potential to advance clinical trials for patients.

An engineered niche delineates metastatic potential of breast cancer.

Metastatic breast cancer is often not diagnosed until secondary tumors have become macroscopically visible and millions of tumor cells have invaded distant tissues. Yet, metastasis is initiated by a cascade of events leading to formation of the pre-metastatic niche, which can precede tumor formation by a matter of years. We aimed to distinguish the potential for metastatic disease from nonmetastatic disease at early times in triple-negative breast cancer using sister cell lines 4T1 (metastatic), 4T07 (invasive, nonmetastatic), and 67NR (nonmetastatic). We used a porous, polycaprolactone scaffold, that serves as an engineered metastatic niche, to identify metastatic disease through the characteristics of the microenvironment. Analysis of the immune cell composition at the scaffold was able to distinguish noninvasive 67NR tumor-bearing mice from 4T07 and 4T1 tumor-bearing mice but could not delineate metastatic potential between the two invasive cell lines. Gene expression in the scaffolds correlated with the up-regulation of cancer hallmarks (e.g., angiogenesis, hypoxia) in the 4T1 mice relative to 4T07 mice. We developed a 9-gene signature (Dhx9, Dusp12, Fth1, Ifitm1, Ndufs1, Pja2, Slc1a3, Soga1, Spon2) that successfully distinguished 4T1 disease from 67NR or 4T07 disease throughout metastatic progression. Furthermore, this signature proved highly effective at distinguishing diseased lungs in publicly available datasets of mouse models of metastatic breast cancer and in human models of lung cancer. The early and accurate detection of metastatic disease that could lead to early treatment has the potential to improve patient outcomes and quality of life.

Morphomics-informed population pharmacokinetic and physiologically-based pharmacokinetic modeling to optimize cefazolin surgical prophylaxis.

INTRODUCTION: Cefazolin is the leading antibiotic used to prevent surgical site infections worldwide. Consensus guidelines recommend adjustment of the cefazolin dose above and below 120 kg without regard to body composition. Algorithms exist to repurpose radiologic data into body composition (morphomics) and inform dosing decisions in obesity. OBJECTIVES: To compare the current standard of body weight to morphomic measurements as covariates of cefazolin pharmacokinetics and aid dose stratification of cefazolin in patients with obesity undergoing colorectal surgery. METHODS: This prospective study measured cefazolin plasma, fat, and colon tissue concentrations in colorectal surgery patients in order to develop a morphomics-informed population pharmacokinetic (PopPK) model to guide dose adjustments. A physiologically-based pharmacokinetic (PBPK) model was also constructed to inform tissue partitioning in morbidly obese patients (n = 21, body mass index ≥35 kg/m2 with one or more co-morbid conditions). RESULTS: Morphomics and pharmacokinetic data were available in 58 patients with a median [min, max] weight and age of 95.9 [68.5, 148.8] kg and 55 [25, 79] years, respectively. The plasma-to-subcutaneous fat partition coefficient was predicted to be 0.072 and 0.060 by the PopPK and PBPK models, respectively. The estimated creatinine clearance (eCLcr ) and body depth at the third lumbar vertebra (body depth_L3) were identified as covariates of cefazolin exposure. The probability of maintaining subcutaneous fat concentrations above 2 µg/mL for 100% of a 4-h surgical period was below 90% when eCLcr ≥105 mL/min and body depth_L3 ≥ 300 mm and less sensitive to the rate of infusion between 5 and 60 min. CONCLUSIONS: Kidney function and morphomics were more informative than body weight as covariates of cefazolin target site exposure. Data from more diverse populations, consensus on target cefazolin exposure, and comparative studies are needed before a change in practice can be implemented.

Building-Block Size Mediates Microporous Annealed Particle Hydrogel Tube Microenvironment Following Spinal Cord Injury.

Spinal cord injury (SCI) is a life-altering event, which often results in loss of sensory and motor function below the level of trauma. Biomaterial therapies have been widely investigated in SCI to promote directional regeneration but are often limited by their pre-constructed size and shape. Herein, the design parameters of microporous annealed particles (MAPs) are investigated with tubular geometries that conform to the injury and direct axons across the defect to support functional recovery. MAP tubes prepared from 20-, 40-, and 60-micron polyethylene glycol (PEG) beads are generated and implanted in a T9-10 murine hemisection model of SCI. Tubes attenuate glial and fibrotic scarring, increase innate immune cell density, and reduce inflammatory phenotypes in a bead size-dependent manner. Tubes composed of 60-micron beads increase the cell density of the chronic macrophage response, while neutrophil infiltration and phenotypes do not deviate from those seen in controls. At 8 weeks postinjury, implantation of tubes composed of 60-micron beads results in enhanced locomotor function, robust axonal ingrowth, and remyelination through both lumens and the inter-tube space. Collectively, these studies demonstrate the importance of bead size in MAP construction and highlight PEG tubes as a biomaterial therapy to promote regeneration and functional recovery in SCI.

Co-Clinical Imaging Metadata Information (CIMI) for Cancer Research to Promote Open Science, Standardization, and Reproducibility in Preclinical Imaging.

Preclinical imaging is a critical component in translational research with significant complexities in workflow and site differences in deployment. Importantly, the National Cancer Institute's (NCI) precision medicine initiative emphasizes the use of translational co-clinical oncology models to address the biological and molecular bases of cancer prevention and treatment. The use of oncology models, such as patient-derived tumor xenografts (PDX) and genetically engineered mouse models (GEMMs), has ushered in an era of co-clinical trials by which preclinical studies can inform clinical trials and protocols, thus bridging the translational divide in cancer research. Similarly, preclinical imaging fills a translational gap as an enabling technology for translational imaging research. Unlike clinical imaging, where equipment manufacturers strive to meet standards in practice at clinical sites, standards are neither fully developed nor implemented in preclinical imaging. This fundamentally limits the collection and reporting of metadata to qualify preclinical imaging studies, thereby hindering open science and impacting the reproducibility of co-clinical imaging research. To begin to address these issues, the NCI co-clinical imaging research program (CIRP) conducted a survey to identify metadata requirements for reproducible quantitative co-clinical imaging. The enclosed consensus-based report summarizes co-clinical imaging metadata information (CIMI) to support quantitative co-clinical imaging research with broad implications for capturing co-clinical data, enabling interoperability and data sharing, as well as potentially leading to updates to the preclinical Digital Imaging and Communications in Medicine (DICOM) standard.

Repeatability of Quantitative Magnetic Resonance Imaging Biomarkers in the Tibia Bone Marrow of a Murine Myelofibrosis Model.

Quantitative MRI biomarkers are sought to replace painful and invasive sequential bone-marrow biopsies routinely used for myelofibrosis (MF) cancer monitoring and treatment assessment. Repeatability of MRI-based quantitative imaging biomarker (QIB) measurements was investigated for apparent diffusion coefficient (ADC), proton density fat fraction (PDFF), and magnetization transfer ratio (MTR) in a JAK2 V617F hematopoietic transplant model of MF. Repeatability coefficients (RCs) were determined for three defined tibia bone-marrow sections (2-9 mm; 10-12 mm; and 12.5-13.5 mm from the knee joint) across 15 diseased mice from 20-37 test-retest pairs. Scans were performed on consecutive days every two weeks for a period of 10 weeks starting 3-4 weeks after transplant. The mean RC with (95% confidence interval (CI)) for these sections, respectively, were for ADC: 0.037 (0.031, 0.050), 0.087 (0.069, 0.116), and 0.030 (0.022, 0.044) µm2/ms; for PDFF: 1.6 (1.3, 2.0), 15.5 (12.5, 20.2), and 25.5 (12.0, 33.0)%; and for MTR: 0.16 (0.14, 0.19), 0.11 (0.09, 0.15), and 0.09 (0.08, 0.15). Change-trend analysis of these QIBs identified a dynamic section within the mid-tibial bone marrow in which confident changes (exceeding RC) could be observed after a four-week interval between scans across all measured MRI-based QIBs. Our results demonstrate the capability to derive quantitative imaging metrics from mouse tibia bone marrow for monitoring significant longitudinal MF changes.

Improved Repeatability of Mouse Tibia Volume Segmentation in Murine Myelofibrosis Model Using Deep Learning.

A murine model of myelofibrosis in tibia was used in a co-clinical trial to evaluate segmentation methods for application of image-based biomarkers to assess disease status. The dataset (32 mice with 157 3D MRI scans including 49 test-retest pairs scanned on consecutive days) was split into approximately 70% training, 10% validation, and 20% test subsets. Two expert annotators (EA1 and EA2) performed manual segmentations of the mouse tibia (EA1: all data; EA2: test and validation). Attention U-net (A-U-net) model performance was assessed for accuracy with respect to EA1 reference using the average Jaccard index (AJI), volume intersection ratio (AVI), volume error (AVE), and Hausdorff distance (AHD) for four training scenarios: full training, two half-splits, and a single-mouse subsets. The repeatability of computer versus expert segmentations for tibia volume of test-retest pairs was assessed by within-subject coefficient of variance (%wCV). A-U-net models trained on full and half-split training sets achieved similar average accuracy (with respect to EA1 annotations) for test set: AJI = 83-84%, AVI = 89-90%, AVE = 2-3%, and AHD = 0.5 mm-0.7 mm, exceeding EA2 accuracy: AJ = 81%, AVI = 83%, AVE = 14%, and AHD = 0.3 mm. The A-U-net model repeatability wCV [95% CI]: 3 [2, 5]% was notably better than that of expert annotators EA1: 5 [4, 9]% and EA2: 8 [6, 13]%. The developed deep learning model effectively automates murine bone marrow segmentation with accuracy comparable to human annotators and substantially improved repeatability.

Animal Models and Their Role in Imaging-Assisted Co-Clinical Trials.

The availability of high-fidelity animal models for oncology research has grown enormously in recent years, enabling preclinical studies relevant to prevention, diagnosis, and treatment of cancer to be undertaken. This has led to increased opportunities to conduct co-clinical trials, which are studies on patients that are carried out parallel to or sequentially with animal models of cancer that mirror the biology of the patients' tumors. Patient-derived xenografts (PDX) and genetically engineered mouse models (GEMM) are considered to be the models that best represent human disease and have high translational value. Notably, one element of co-clinical trials that still needs significant optimization is quantitative imaging. The National Cancer Institute has organized a Co-Clinical Imaging Resource Program (CIRP) network to establish best practices for co-clinical imaging and to optimize translational quantitative imaging methodologies. This overview describes the ten co-clinical trials of investigators from eleven institutions who are currently supported by the CIRP initiative and are members of the Animal Models and Co-clinical Trials (AMCT) Working Group. Each team describes their corresponding clinical trial, type of cancer targeted, rationale for choice of animal models, therapy, and imaging modalities. The strengths and weaknesses of the co-clinical trial design and the challenges encountered are considered. The rich research resources generated by the members of the AMCT Working Group will benefit the broad research community and improve the quality and translational impact of imaging in co-clinical trials.

Teaching compassion for social accountability: A parallaxic investigation.

BACKGROUND: In an arts integrated interdisciplinary study set to investigate ways to improve social accountability (SA) in medical education, our research team has established a renewed understanding of compassion in the current SA movement. AIM: This paper explores the co-evolution of compassion and SA. METHODS: The study used an arts integrated approach to investigate people's perceptions of SA in four medical schools across Australia, Canada, and the USA. Each school engaged approximately 25 participants who partook in workshops and in-depth interviews. RESULTS: We began with a study of SA and the topic of compassion emerged out of our qualitative data and biweekly meetings within the research team. Content analysis of the data and pedagogical discussion brought us to realize the importance of compassion in the practice of SA. CONCLUSIONS: The cultivation of compassion needs to play a significant role in a socially accountable medical educational system. Medical schools as educational institutions may operate themselves with compassion as a driving force in engaging partnership with students and communities. Social accountability without compassion is not SA; compassion humanizes institutional policy by engaging sympathy and care.

A geographic-location-based medical school admissions process does not influence pre-clerkship and licensing examination academic performance.

Background: Students are selected for admission to the Northern Ontario School of Medicine University (NOSM U) MD degree program using criteria aiming to maximize access of persons thought most likely to practice in the region, including use of a geographic context score (GCS) which ranks those with lived experience in northern Ontario and/or rurality most highly. This study investigates the effect of this admissions process upon medical school academic performance. Methods: We used a retrospective cohort design combined with multiple linear regression analysis to investigate the relationship between admission scores and performance on pre-clerkship courses, and the Medical Council of Canada Qualifying Exam Part 1 (MCCQE1).The GCS did not significantly explain performance variance on any pre-clerkship course, nor on the MCCQE1, while the undergraduate Grade Point Average correlated with most assessment scores. The number of prior undergraduate biomedical courses predicted science and clinical skills performance, particularly in Year 1, but not with MCCQE1 scores. Performance on Year 2 courses, particularly foundational sciences and clinical skills, significantly predicted MCCQE1 scores. Results: Our data suggest that admission geographic context scoring is unrelated to future academic performance. Further, students with fewer prior undergraduate biomedical courses may benefit from increased support and/or a modified program during the early years.

Contexte: La sélection étudiants à l'École de médecine du Nord de l'Ontario est fondée sur des critères visant à faciliter l'admission de candidats qu'on estime susceptibles de pratiquer dans la région. Un de ces critères est le score de contexte géographique (SCG) qui classe au premier rang les personnes ayant déjà vécu dans le Nord de l'Ontario ou en milieu rural. Cette étude examine l'effet de ce processus d'admission sur les résultats académiques des étudiants en médecine. Méthodes: Nous avons utilisé un modèle de cohorte rétrospective et une analyse par régression linéaire multiple pour étudier la relation entre les scores d'admission et les résultats obtenus aux cours avant l'externat et à l'examen d'aptitude du Conseil médical du Canada (EACMC), partie 1.Le SCG n'explique pas de manière significative la variance des résultats dans les cours pré-cliniques, ni à l'EACMC1, tandis que la moyenne pondérée cumulative au premier cycle est en corrélation avec la plupart des scores d'évaluation. Le nombre de cours en sciences biomédicales suivis dans un programme de premier cycle ont permis de prédire les résultats en sciences et en compétences cliniques, en particulier en première année, mais pas les résultats à l'EACMC1. Les résultats aux cours de deuxième année, en particulier de sciences fondamentales et de compétences cliniques, ont permis de prédire de manière significative les résultats à l'EACMC1. Résultats: Nos données portent à croire que le score de contexte géographique au moment de l'admission est sans lien avec les résultats académiques subséquents. En outre, les étudiants ayant suivi moins de cours en sciences biomédicales au premier cycle pourraient bénéficier d'un soutien plus important ou d'un programme adapté au cours des premières années.

Variation in aorta attenuation in contrast-enhanced CT and its implications for calcification thresholds.

BACKGROUND: CT contrast media improves vessel visualization but can also confound calcification measurements. We evaluated variance in aorta attenuation from varied contrast-enhancement scans, and quantified expected plaque detection errors when thresholding for calcification. METHODS: We measured aorta attenuation (AoHU) in central vessel regions from 10K abdominal CT scans and report AoHU relationships to contrast phase (non-contrast, arterial, venous, delayed), demographic variables (age, sex, weight), body location, and scan slice thickness. We also report expected plaque segmentation false-negative errors (plaque pixels misidentified as non-plaque pixels) and false-positive errors (vessel pixels falsely identified as plaque), comparing a uniform thresholding approach and a dynamic approach based on local mean/SD aorta attenuation. RESULTS: Females had higher AoHU than males in contrast-enhanced scans by 65/22/20 HU for arterial/venous/delayed phases (p < 0.001) but not in non-contrast scans (p > 0.05). Weight was negatively correlated with AoHU by 2.3HU/10kg but other predictors explained only small portions of intra-cohort variance (R2 < 0.1 in contrast-enhanced scans). Average AoHU differed by contrast phase, but considerable overlap was seen between distributions. Increasing uniform plaque thresholds from 130HU to 200HU/300HU/400HU produces respective false-negative plaque content losses of 35%/60%/75% from all scans with corresponding false-positive errors in arterial-phase scans of 95%/60%/15%. Dynamic segmentation at 3SD above mean AoHU reduces false-positive errors to 0.13% and false-negative errors to 8%, 25%, and 70% in delayed, venous, and arterial scans, respectively. CONCLUSION: CT contrast produces heterogeneous aortic enhancements not readily determined by demographic or scan protocol factors. Uniform CT thresholds for calcified plaques incur high rates of pixel classification errors in contrast-enhanced scans which can be minimized using dynamic thresholds based on local aorta attenuation. Care should be taken to address these errors and sex-based biases in baseline attenuation when designing automatic calcification detection algorithms intended for broad use in contrast-enhanced CTs.

Comparing and using prominent social accountability frameworks in medical education: moving from theory to implementation in Northern Ontario, Canada.

Background: Social accountability in medical education is conceptualized as a responsibility to respond to the needs of local populations and demonstrate impact of these activities. The objective of this study was to rigorously examine and compare social accountability theories, models, and frameworks to identify a theory-informed structure to understand and evaluate the impacts of medical education in Northern Ontario. Methods: Using a narrative review methodology, prominent social accountability theories, models, and frameworks were identified. The research team extracted important constructs and relationships from the selected frameworks. The Theory Comparison and Selection Tool was used to compare the frameworks for fit and relevance. Results: Eleven theories, models, and frameworks were identified for in-depth analysis and comparison. Two realist frameworks that considered community relationships in medical education and social accountability in health services received the highest scores. Frameworks focused on learning health systems, evaluating institutional social accountability, and implementing evidence-based practices also scored highly. Conclusion: We used a systematic theory selection process to describe and compare social accountability constructs and frameworks to inform the development of a social accountability impact framework for the Northern Ontario School of Medicine. The research team examined important constructs, relationships, and outcomes, to select a framework that fits the aims of a specific project. Additional engagement will help determine how to combine, adapt, and implement framework components to use in a Northern Ontario framework.

Contexte: La responsabilité sociale dans l'éducation médicale est conceptualisée comme étant la responsabilité de répondre aux besoins des populations locales et de démontrer l'impact de ces activités. L'objectif de cette étude était d'examiner rigoureusement et de comparer les théories, les modèles et les cadres de la responsabilité sociale afin d'élaborer un dispositif ayant des fondements théoriques qui servirait à cerner et à évaluer les retombées de l'éducation médicale dans le Nord de l'Ontario. Méthodes: Suivant une méthodologie de revue narrative, les théories, modèles et cadres principaux de la responsabilité sociale ont été recensés. L'équipe de recherche a extrait les concepts et les relations importants des cadres sélectionnés. Les cadres ont ensuite été comparés sur le plan de l'adéquation et de la pertinence à l'aide d'un outil de comparaison et de sélection des théories (le Theory Comparison and Selection Tool). Résultats: Onze théories, modèles et cadres ont été retenus pour une analyse et une comparaison approfondies. Deux cadres réalistes prenant en considération les relations communautaires dans l'éducation médicale et la responsabilité sociale dans les services de soins de santé ont reçu les scores les plus élevés. Les cadres axés sur l'apprentissage des systèmes de santé e, sur l'évaluation de la responsabilité sociale des institutions et sur la mise en œuvre de pratiques fondées sur les données probantes ont également obtenu des scores élevés. Conclusion: Nous avons utilisé un processus systématique de sélection des théories pour décrire et comparer les construits et les cadres de responsabilité sociale afin d'éclairer le développement d'un cadre de référence sur les retombées de la responsabilité sociale pour l'École de médecine du Nord de l'Ontario. L'équipe de recherche a examiné les construits importants, les liens entre ces derniers et les retombées afin de choisir un cadre pouvant répondre aux objectifs d'un projet spécifique. Des travaux ultérieurs permettront de déterminer de quelle manière il sera possible de combiner, d'adapter et de mettre en œuvre les composantes de ce cadre qui sera utilisé dans le Nord de l'Ontario.

A lymphatic-absorbed multi-targeted kinase inhibitor for myelofibrosis therapy.

Activation of compensatory signaling nodes in cancer often requires combination therapies that are frequently plagued by dose-limiting toxicities. Intestinal lymphatic drug absorption is seldom explored, although reduced toxicity and sustained drug levels would be anticipated to improve systemic bioavailability. A potent orally bioavailable multi-functional kinase inhibitor (LP-182) is described with intrinsic lymphatic partitioning for the combined targeting of phosphoinositide 3-kinase (PI3K) and mitogen-activated protein kinase (MAPK) signaling pathways without observable toxicity. We demonstrate selectivity and therapeutic efficacy through reduction of downstream kinase activation, amelioration of disease phenotypes, and improved survival in animal models of myelofibrosis. Our further characterization of synthetic and physiochemical properties for small molecule lymphatic uptake will support continued advancements in lymphatropic therapy for altering disease trajectories of a myriad of human disease indications.

A conceptual framework to describe and evaluate a socially accountable learning health system: Development and application in a northern, rural, and remote setting.

Health care and academic institutions are increasingly committing to social accountability, a strategic shift that requires priorities, activities, and evaluations to be co-determined with all relevant partners. Consequently, governments, accreditors, funders, and communities are calling for these institutions to communicate their progress towards social accountability. The purpose of this study was to develop a conceptual framework around a socially accountable learning health system. This article presents an integrated analysis of two studies: (i) a narrative review of 11 prominent social accountability and health services conceptual frameworks and (ii) a reflexive thematic analysis of 18 key informant interviews. Using a systematic conceptual framework development and integrated theory of change/realist evaluation methodologies, we describe a synthesis of these findings to develop a conceptual framework for describing and evaluating socially accountable health professional education. The resulting framework describes assessment phases of social accountability, transitions between phases, learning cycles, and the actors and systems that collectively mobilise social accountability at multiple levels in health and education systems. The framework can be used to evaluate interventions or characterise progress towards social accountability in different settings, as illustrated in the example at the end of the paper. The framework emphasises the significance of designing, mobilising, and evaluating social accountability as part of a contextualised learning health system.

Multiparametric MRI to quantify disease and treatment response in mice with myeloproliferative neoplasms.

Histopathology, the standard method to assess BM in hematologic malignancies such as myeloproliferative neoplasms (MPNs), suffers from notable limitations in both research and clinical settings. BM biopsies in patients fail to detect disease heterogeneity, may yield a nondiagnostic sample, and cannot be repeated frequently in clinical oncology. Endpoint histopathology precludes monitoring disease progression and response to therapy in the same mouse over time, missing likely variations among mice. To overcome these shortcomings, we used MRI to measure changes in cellularity, macromolecular constituents, and fat versus hematopoietic cells in BM using diffusion-weighted imaging (DWI), magnetization transfer, and chemical shift-encoded fat imaging. Combining metrics from these imaging parameters revealed dynamic alterations in BM following myeloablative radiation and transplantation. In a mouse MPLW515L BM transplant model of MPN, MRI detected effects of a JAK2 inhibitor, ruxolitinib, within 5 days of initiating treatment and identified differing kinetics of treatment responses in subregions of the tibia. Histopathology validated the MRI results for BM composition and heterogeneity. Anatomic MRI scans also showed reductions in spleen volume during treatment. These findings establish an innovative, clinically translatable MRI approach to quantify spatial and temporal changes in BM in MPN.

Uniform binding and negative catalysis at the origin of enzymes.

Enzymes are well known for their catalytic abilities, some even reaching "catalytic perfection" in the sense that the reaction they catalyze has reached the physical bound of the diffusion rate. However, our growing understanding of enzyme superfamilies has revealed that only some share a catalytic chemistry while others share a substrate-handle binding motif, for example, for a particular phosphate group. This suggests that some families emerged through a "substrate-handle-binding-first" mechanism ("binding-first" for brevity) instead of "chemistry-first" and we are, therefore, left to wonder what the role of non-catalytic binders might have been during enzyme evolution. In the last of their eight seminal, back-to-back articles from 1976, John Albery and Jeremy Knowles addressed the question of enzyme evolution by arguing that the simplest mode of enzyme evolution is what they defined as "uniform binding" (parallel stabilization of all enzyme-bound states to the same degree). Indeed, we show that a uniform-binding proto-catalyst can accelerate a reaction, but only when catalysis is already present, that is, when the transition state is already stabilized to some degree. Thus, we sought an alternative explanation for the cases where substrate-handle-binding preceded any involvement of a catalyst. We find that evolutionary starting points that exhibit negative catalysis can redirect the reaction's course to a preferred product without need for rate acceleration or product release; that is, if they do not stabilize, or even destabilize, the transition state corresponding to an undesired product. Such a mechanism might explain the emergence of "binding-first" enzyme families like the aldolase superfamily.