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Information regarding the profile of reticulated platelets (RP) in ischemic cerebrovascular disease (CVD) patients is limited. Data from two prospective, observational, case-control studies were combined to compare the %RP using whole blood flow cytometry in patients ≤ 4 weeks of TIA/stroke onset (baseline, N = 210), and 14 ±7 days (14d, N = 182) and ≥ 90 days (90d, N = 145) after starting or changing antiplatelet therapy with healthy controls (N = 34). There were no differences in median %RP between the overall CVD patient population at baseline or 14d vs. controls (P ≥ 0.2). However, the median %RP was significantly higher in CVD patients overall at 90d (P = .036), and in the subgroup of patients with “lacunar” TIA/ischemic stroke at baseline (P = .04) and at 90d (P = .01), but not at 14d (P = .06) vs. controls. There were no significant differences in the median %RP between other TIA/stroke subgroups and controls (P ≥ 0.05). Elevated circulating reticulated platelets, as a marker of increased platelet production/turnover, may occur following an ischemic event in a well-phenotyped TIA/ischemic stroke population overall, but may precede symptom onset at least in the subgroup with small vessel occlusion. These data improve our understanding of the profile of reticulated platelets in CVD patients.

State-of-the-art atomic layer deposition (ALD) and photoemission characterisation are applied to grow and characterise cobalt nitride, a material that has applications in renewable energy and semiconductor technologies. The growth process is characterised using an in situ cycle-by-cycle methodology to identify the main factors which underpin optimal material growth. The role of co-reactant dosing and substrate temperature is analysed in detail to demonstrate the impact these parameters have on the overall composition of the film. The in situ approach, combined with high-energy synchrotron-based photoemission studies of the resulting films, enables understanding of the bulk chemical properties without need for physical removal of material by sputtering. The results provide an insight into optimising plasma assisted ALD processes for deposition of cobalt nitride, and strategies for minimizing carbon incorporation into the film from the precursor ligands.

Objective Treat‐to‐target (T2T) and shared decision‐making are valued features of current guidelines for rheumatoid arthritis (RA) management. Although T2T has demonstrated value for improving RA outcomes, implementation remains inconsistent and lacks standardization and procedures for including patient input. We sought to better understand the impact of shared decisions on T2T and how treatment goal discussions between patients and providers impact RA treatment improvement and satisfaction. Methods An anonymous, web‐based questionnaire was presented to United States residents aged 18 years or older with a self‐reported diagnosis of RA by a medical professional with 28 questions regarding socio‐demographics, RA disease activity (DA), diagnosis, treatments, outcomes, and goals. Analyses included descriptive statistics with χ2 and rank sum tests for comparisons. Results The questionnaire was completed by 907 people (mean age of 58 years; mean 11 years since diagnosis; 90% female). The majority (571; 63%) did not discuss RA treatment goals with providers. Patients engaging in treatment goal discussions with their providers were three times more likely to be satisfied with their treatment plans. Patients discussing treatment goals with their providers were more likely to have improved DA levels and 68% more likely to reach remission. Conclusion A majority of patients with RA report having no treatment goal discussion with their providers; however, these discussions are associated with greater DA improvement and treatment satisfaction. Further research should seek understanding of how shared treatment goal discussions relate to successful RA management and explore the development of practical tools to implement them in regular clinic practice as part of a T2T regimen.

The novel coronavirus disease 2019 is a global public health crisis that disproportionately affects those with preexisting conditions. Cardiovascular disease (CVD) is the leading cause of death worldwide and many key CVD risk factors are modifiable (e.g., physical inactivity, sedentary behaviour, obesity). To limit the spread of coronavirus 2019, most governments have implemented restrictions and recommended staying at home, reducing social contact to a select and exclusive few, and limiting large gatherings. Such public health constraints may have unintended, negative health consequences on 24-hour movement behaviours. The primary purpose of this review is to provide practical at-home recommendations for sedentary time, sleep, and physical activity in those living with CVD. Adults with CVD will benefit from practical recommendations to reduce sedentary time, increase purposeful exercise, and maintain optimal sleep patterns while being at home and adhering to public health restrictions. Our recommendations include the following: (i) self-monitoring sitting time; (ii) engaging in 2-3 days per week of purposeful exercise for those with low exercise capacity and > 3 days per week for those with moderate-to-high exercise capacity; (iii) self-monitoring exercise intensity through the use of scales or wearable devices; (iv) maintaining a regular sleep schedule; and (v) moving daily. Clinicians should be aware that clear communication of the importance of limiting prolonged sedentary time, engaging in regular physical activity and exercise, and ensuring optimal sleep in association with the provision of clear, comprehensible, and practical advice is fundamental to ensuring that those living with CVD respond optimally to the challenges posed by the pandemic. Résumé: La nouvelle maladie à coronavirus 2019 représente une crise de santé publique mondiale qui touche de manière disproportionnée les personnes présentant des pathologies préexistantes. Les maladies cardiovasculaires (MCV) constituent la principale cause de décès dans le monde et de nombreux facteurs de risque majeurs de MCV sont modifiables (par exemple, le manque d'activité physique, un comportement sédentaire, l'obésité). Pour limiter la propagation du coronavirus 2019, la plupart des gouvernements ont mis en place des restrictions et recommandé de rester à la maison, de réduire les contacts sociaux à un nombre de personnes restreint et exclusif, et de limiter les grands rassemblements. Ces contraintes de santé publique peuvent involontairement entraîner des conséquences sanitaires négatives sur les habitudes de déplacement sur 24 heures. L'objectif principal de cette étude est de fournir des recommandations pratiques, réalisables à domicile, en rapport avec le temps de sédentarité, le sommeil et l'activité physique chez les personnes atteintes de MCV. Les adultes atteints de MCV tireront avantage de recommandations pratiques dans le but de réduire le temps de sédentarité, augmenter l'activité physique volontaire et maintenir des habitudes de sommeil optimales, tout en restant à la maison et en respectant les restrictions sanitaires. Nos recommandations sont les suivantes: (i) autosurveillance du temps passé assis; (ii) pratique d'une activité physique volontaire 2 à 3 jours par semaine pour les personnes ayant une faible capacité d'exercice et > 3 jours par semaine pour les personnes ayant une capacité d'exercice modérée à élevée; (iii) autosurveillance de l'intensité de l'activité par l'utilisation de barème ou de dispositifs portatifs; (iv) maintien d'horaires de sommeil réguliers; et (v) action de bouger quotidiennement. Les cliniciens doivent être conscients qu'une communication claire quant à l'importance de limiter le temps de sédentarité prolongée, de pratiquer régulièrement de l'exercice ou une activité physique, et d'assurer un sommeil optimal, associée à la préconisation de conseils clairs, compréhensibles et pratiques, est fondamentale pour garantir une réponse optimale de la part des personnes vivant avec des MCV quant aux défis posés par la pandémie.

ABSTRACT Dietary phosphorus restriction and phosphorus binders are commonly prescribed for patients with chronic kidney disease (CKD). However, occurrences of non‐adherence to these interventions are common. As low‐phosphorus (LP) diets have been consistently experimentally shown in vitro to increase intestinal phosphorus absorption efficiency, a bout of non‐adherence to diet or binders may cause an unintended consequence of enhanced intestinal phosphorus absorption. Thus, we aimed to determine the effect of a single bout of high‐phosphorus (HP) intake after acclimation to a LP diet. Male Sprague Dawley rats with 5/6 nephrectomy (n = 36) or sham operation (n = 36) were block‐randomized to 1 of 3 diets: LP (0.1% P w/w), HP (1.2%), or LP followed by acute HP (LPHP 0.1% then 1.2%). Phosphorus absorption tests were conducted using 33P radioisotope administrated by oral gavage or intravenously (iv). Although the overall two‐way ANCOVA model for intestinal fractional phosphorus absorption was non‐significant, exploratory comparisons showed intestinal fractional phosphorus absorption efficiency tended to be higher in rats in the LP compared with HP or LPHP groups. Rats in the HP or LPHP groups had higher plasma phosphorus compared with rats in the LP group, but the LPHP group was not different from the HP group. Gene expression of the major intestinal phosphate transporter, NaPi‐2b, was lower in the jejunum of rats in the LPHP group compared with rats in the HP group but not different in the duodenum. These results demonstrate that an acute HP load after acclimation to a LP diet does not lead to enhanced intestinal fractional phosphorus absorption efficiency in 5/6 nephrectomized male rats. These data provide evidence against the notion that dietary phosphorus restriction or binder use adversely increases absorption efficiency after a single instance of dietary or binder non‐adherence. However, other adverse consequences of fluctuating dietary phosphorus intake cannot be ruled out. © 2022 The Authors. JBMR Plus published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research.

Abstract The spatial organization of T cell receptors (TCRs) correlates with membrane-associated signal amplification, dispersion, and regulation during T cell activation. Despite its potential clinical importance, quantitative analysis of the spatial arrangement of TCRs from standard fluorescence images remains difficult. Here, we report Statistical Classification Analyses of Membrane Protein Images or SCAMPI as a technique capable of analyzing the spatial arrangement of TCRs on the plasma membrane of T cells. We leveraged medical image analysis techniques that utilize pixel-based values. We transformed grayscale pixel values from fluorescence images of TCRs into estimated model parameters of partial differential equations. The estimated model parameters enabled an accurate classification using linear discrimination techniques, including Fisher Linear Discriminant (FLD) and Logistic Regression (LR). In a proof-of-principle study, we modeled and discriminated images of fluorescently tagged TCRs from Jurkat T cells on uncoated cover glass surfaces (Null) or coated cover glass surfaces with either positively charged poly-L-lysine (PLL) or TCR cross-linking anti-CD3 antibodies (OKT3). Using 80 training images and 20 test images per class, our statistical technique achieved 85% discrimination accuracy for both OKT3 versus PLL and OKT3 versus Null conditions. The run time of image data download, model construction, and image discrimination was 21.89 s on a laptop computer, comprised of 20.43 s for image data download, 1.30 s on the FLD-SCAMPI analysis, and 0.16 s on the LR-SCAMPI analysis. SCAMPI represents an alternative approach to morphology-based qualifications for discriminating complex patterns of membrane proteins conditioned on a small sample size and fast runtime. The technique paves pathways to characterize various physiological and pathological conditions using the spatial organization of TCRs from patient T cells.

Abstract Chronic kidney disease (CKD) leads to musculoskeletal impairments that are impacted by muscle metabolism. We tested the hypothesis that 10-weeks of voluntary wheel running can improve skeletal muscle mitochondria activity and function in a rat model of CKD. Groups included (n = 12–14/group): (1) normal littermates (NL); (2) CKD, and; (3) CKD-10 weeks of voluntary wheel running (CKD-W). At 35-weeks old the following assays were performed in the soleus and extensor digitorum longus (EDL): targeted metabolomics, mitochondrial respiration, and protein expression. Amino acid-related compounds were reduced in CKD muscle and not restored by physical activity. Mitochondrial respiration in the CKD soleus was increased compared to NL, but not impacted by physical activity. The EDL respiration was not different between NL and CKD, but increased in CKD-wheel rats compared to CKD and NL groups. Our results demonstrate that the soleus may be more susceptible to CKD-induced changes of mitochondrial complex content and respiration, while in the EDL, these alterations were in response the physiological load induced by mild physical activity. Future studies should focus on therapies to improve mitochondrial function in both types of muscle to determine if such treatments can improve the ability to adapt to physical activity in CKD.

Objectives: The aim of this study is to develop a scar detection method for routine computed tomography angiography (CTA) imaging using deep convolutional neural networks (CNN), which relies solely on anatomical information as input and is compatible with existing clinical workflows.Background: Identifying cardiac patients with scar tissue is important for assisting diagnosis and guiding interventions. Late gadolinium enhancement (LGE) magnetic resonance imaging (MRI) is the gold standard for scar imaging; however, there are common instances where it is contraindicated. CTA is an alternative imaging modality that has fewer contraindications and is faster than Cardiovascular magnetic resonance imaging but is unable to reliably image scar.Methods: A dataset of LGE MRI (200 patients, 83 with scar) was used to train and validate a CNN to detect ischemic scar slices using segmentation masks as input to the network. MRIs were segmented to produce 3D left ventricle meshes, which were sampled at points along the short axis to extract anatomical masks, with scar labels from LGE as ground truth. The trained CNN was tested with an independent CTA dataset (25 patients, with ground truth established with paired LGE MRI). Automated segmentation was performed to provide the same input format of anatomical masks for the network. The CNN was compared against manual reading of the CTA dataset by 3 experts.Results: Note that 84.7% cross-validated accuracy (AUC: 0.896) for detecting scar slices in the left ventricle on the MRI data was achieved. The trained network was tested against the CTA-derived data, with no further training, where it achieved an 88.3% accuracy (AUC: 0.901). The automated pipeline outperformed the manual reading by clinicians.Conclusion: Automatic ischemic scar detection can be performed from a routine cardiac CTA, without any scar-specific imaging or contrast agents. This requires only a single acquisition in the cardiac cycle. In a clinical setting, with near zero additional cost, scar presence could be detected to triage images, reduce reading times, and guide clinical decision-making.

Gastric aspiration severely injures donor lungs, frequently making them unacceptable for transplantation. Here the authors show that an interventional cross-circulation platform enables the regeneration of severely damaged lungs in a swine model of gastric aspiration injury.

Catheter ablation therapy for persistent atrial fibrillation (AF) typically includes pulmonary vein isolation (PVI) and may include additional ablation lesions that target patient-specific anatomical, electrical, or structural features. Clinical centers employ different ablation strategies, which use imaging data together with electroanatomic mapping data, depending on data availability. The aim of this study was to compare ablation techniques across a virtual cohort of AF patients. We constructed 20 paroxysmal and 30 persistent AF patient-specific left atrial (LA) bilayer models incorporating fibrotic remodeling from late-gadolinium enhancement (LGE) MRI scans. AF was simulated and post-processed using phase mapping to determine electrical driver locations over 15 s. Six different ablation approaches were tested: (i) PVI alone, modeled as wide-area encirclement of the pulmonary veins; PVI together with: (ii) roof and inferior lines to model posterior wall box isolation; (iii) isolating the largest fibrotic area (identified by LGE-MRI); (iv) isolating all fibrotic areas; (v) isolating the largest driver hotspot region [identified as high simulated phase singularity (PS) density]; and (vi) isolating all driver hotspot regions. Ablation efficacy was assessed to predict optimal ablation therapies for individual patients. We subsequently trained a random forest classifier to predict ablation response using (a) imaging metrics alone, (b) imaging and electrical metrics, or (c) imaging, electrical, and ablation lesion metrics. The optimal ablation approach resulting in termination, or if not possible atrial tachycardia (AT), varied among the virtual patient cohort: (i) 20% PVI alone, (ii) 6% box ablation, (iii) 2% largest fibrosis area, (iv) 4% all fibrosis areas, (v) 2% largest driver hotspot, and (vi) 46% all driver hotspots. Around 20% of cases remained in AF for all ablation strategies. The addition of patient-specific and ablation pattern specific lesion metrics to the trained random forest classifier improved predictive capability from an accuracy of 0.73 to 0.83. The trained classifier results demonstrate that the surface areas of pre-ablation driver regions and of fibrotic tissue not isolated by the proposed ablation strategy are both important for predicting ablation outcome. Overall, our study demonstrates the need to select the optimal ablation strategy for each patient. It suggests that both patient-specific fibrosis properties and driver locations are important for planning ablation approaches, and the distribution of lesions is important for predicting an acute response.

Medical residents in difficulty struggle to comply with educational requirements. They pose a liability to patient safety and they have problems to adapt to the professional role of a doctor. Consequently, being a resident in difficulty may cause identity crisis and have the potential to disrupt the resident's professional identity as a doctor. Only few studies explore the tipping point between becoming a resident in difficulty or not, and these studies rarely reflect the surrounding sociocultural aspects of the residents' difficulties such as organisational culture in the workplace. This article explores how medical residency training culture influence on residents' risk of ending in difficulty. Our study was based on six focus-group interviews with residents (n=28) and in-depth interviews with residents in difficulty (n=10). The interpretation of data employed sociologist Pierre Bourdieu's theoretical framework around dispositions. Across the data, we identified four themes: Conflicting games in the field of medical education, altruism, organisational hierarchy, and coping with stress. We found a (mis)match between legitimate rules in the field of medicine and the residents' dispositions to appreciate those rules. These results can inform clinical supervisors and consultants in their decisions for supporting residents in difficulty and increasing educational achievement among struggling residents.

The celebrated Abakaliki smallpox data have appeared numerous times in the epidemic modelling literature, but in almost all cases only a specific subset of the data is considered. The only previous analysis of the full data set relied on approximation methods to derive a likelihood and did not assess model adequacy. The data themselves continue to be of interest due to concerns about the possible re-emergence of smallpox as a bioterrorism weapon. We present the first full Bayesian statistical analysis using data-augmentation Markov chain Monte Carlo methods which avoid the need for likelihood approximations and which yield a wider range of results than previous analyses. We also carry out model assessment using simulation-based methods. Our findings suggest that the outbreak was largely driven by the interaction structure of the population, and that the introduction of control measures was not the sole reason for the end of the epidemic. We also obtain quantitative estimates of key quantities including reproduction numbers.

Background and Objective. Diabetic retinopathy (DR) is a major complication of diabetes and the leading cause of blindness among US working-age adults. Detection of subclinical DR is important for disease monitoring and prevention of damage to the retina before occurrence of vision loss. The purpose of this retrospective study is to describe an automated method for discrimination of subclinical DR using fine structure analysis of retinal images. Methods. Discrimination between nondiabetic control (NC; N = 16) and diabetic without clinical retinopathy (NDR; N = 17) subjects was performed using ordinary least squares regression and Fisher’s linear discriminant analysis. A human observer also performed the discrimination by visual inspection of the images. Results. The discrimination rate for subclinical DR was 88% using the automated method and higher than the rate obtained by a human observer which was 45%. Conclusions. The method provides sensitive and rapid analysis of retinal images and could be useful in detecting subclinical DR.