Medical and Educational Indebtedness Among US Health Care Workers.

This cross-sectional study evaluates medical and educational debt among the US health care workforce and explores factors associated with higher debt burdens.

No evidence for metabolic adaptation during exercise-related energy compensation.

The constrained energy model posits that the increased total daily energy expenditure (TDEE) in response to exercise is often less than the energy cost of the exercise prescribed. The mechanisms behind this phenomenon, coined "exercise-related energy compensation" (ExEC), are poorly understood, and it is unknown if ExEC is coupled with metabolic adaptation. Using a randomized controlled 24-week exercise intervention, individuals who demonstrated ExEC were identified. Changes to all components of TDEE and metabolic adaptation were assessed using doubly labeled water over 14 days and room calorimetry over 24-h 48% of individuals exhibited ExEC (-308 ± 158 kcals/day). There were no statistically significant differences in sex, age, or BMI between ExEC and non-ExEC. ExEC was associated with baseline TDEE (r = -0.50, p = 0.006). There were no statistically significant differences in metabolic adaptations for 24 h, sleep, or resting expenditures. These findings reveal that ExEC occurs independent of metabolic adaptation in sedentary components of EE.

The Interplay of Acetylation and Ubiquitination Controls PRMT1 Homeostasis.

PRMT1 plays many important roles in both normal and disease biology, thus understanding it's regulation is crucial. Herein, we report the role of p300-mediated acetylation at K228 in triggering PRMT1 degradation through FBXL17-mediated ubiquitination. Utilizing mass-spectrometry, cellular biochemistry, and genetic code-expansion technologies, we elucidate a crucial mechanism independent of PRMT1 transcript levels. These results underscore the significance of acetylation in governing protein stability and expand our understanding of PRMT1 homeostasis. By detailing the molecular interplay between acetylation and ubiquitination involved in PRMT1 degradation, this work contributes to broader efforts in deciphering post-translational mechanisms that influence protein homeostasis.

Peptide Nucleic Acid-Mediated Regulation of CRISPR-Cas9 Specificity.

Although CRISPR-Cas9 gene therapies have proven to be a powerful tool across many applications, improvements are necessary to increase the specificity of this technology. Cas9 cutting in off-target sites remains an issue that limits CRISPR's application in human-based therapies. Treatment of autosomal dominant diseases also remains a challenge when mutant alleles differ from the wild-type sequence by only one base pair. Here, we utilize synthetic peptide nucleic acids (PNAs) that bind selected spacer sequences in the guide RNA (gRNA) to increase Cas9 specificity up to 10-fold. We interrogate variations in PNA length, binding position, and degree of homology with the gRNA. Our findings reveal that PNAs bound in the region distal to the protospacer adjacent motif (PAM) site effectively enhance specificity in both on-target/off-target and allele-specific scenarios. In addition, we demonstrate that introducing deliberate mismatches between PNAs bound in the PAM-proximal region of the gRNA can modulate Cas9 activity in an allele-specific manner. These advancements hold promise for addressing current limitations and expanding the therapeutic potential of CRISPR technology.

Antibodies to Influenza A Virus in Lesser (Aytha affinis) and Greater Scaup (Aytha marila) in the USA.

Scaup, including both Lesser and Greater (Aythya affinis and Aythya marila, respectively), are a grouping of populous and widespread North American diving ducks. Few influenza type A viruses (IAV) have been reported from these species despite a high prevalence of antibodies to IAV being reported. Existing virologic and serologic data indicate that IAV infection routinely occurs in scaup, yet it is unknown which IAV subtypes are linked to these infections. In this study, we aimed to gain a more complete picture of IAV natural history in Lesser and Greater Scaup from two coastal flyways in North America in 2015-18 (302 samples from California in the Pacific Flyway and 471 samples from Maryland in the Atlantic Flyway). Low prevalence of active IAV infection was detected by real-time reverse-transcription PCR in Lesser Scaup sampled in Maryland and California (2.8% and 8.1%, respectively). A single IAV (H1N1) was isolated in embryonated chicken eggs from a bird sampled in California. Similarly low levels were observed in Greater Scaup in California (3.3%). Antibodies to the nucleoprotein as detected with a commercial blocking ELISA were observed in all species and flyway combinations. Antibody seroprevalence estimates were higher in adult Lesser Scaup than in juveniles at both the ≤0.5 (P<0.001, z=-3.582) and ≤0.7 serum-sample-to-negative-control absorbance thresholds (P=0.003, z=-2.996). Neutralizing antibodies to H1-H12, H14, and H15 were detected using a microtiter virus neutralization assay, with the highest prevalence of antibodies against H1 (38%), H6 (36%), and H11 (35%). The high prevalence of antibodies to IAV and evidence of previous exposure to numerous subtypes are consistent with a high level of population immunity and a low prevalence of infection. These results must be interpreted in the context of season (winter sampling), as results may vary with the annual influx of naïve juvenile birds.

Implementation of a digital behavior change intervention (eCHANGE) for weight loss maintenance support: a service design and technology transfer approach.

Obesity is a chronic disease, and while weight loss is achievable, long-term weight loss maintenance is difficult and relapse common for people living with obesity. Aiming to meet the need for innovative approaches, digital behavior change interventions show promise in supporting health behavior change to maintain weight after initial weight loss. Implementation of such interventions should however be part of the design and development processes from project initiation to facilitate uptake and impact. Based on the development and implementation process of eCHANGE, an evidence-informed application-based self-management intervention for weight loss maintenance, this manuscript provides suggestions and guidance into; (1) How a service design approach can be used from initiation to implementation of digital interventions, and (2) How a technology transfer process can accelerate implementation of research-based innovation from idea to market.

Precise QCD predictions for W-boson production in association with a charm jet.

The production of a W-boson with a charm quark jet provides a highly sensitive probe of the strange quark distribution in the proton. Employing a novel flavour dressing procedure to define charm quark jets, we compute W+charm-jet production up to next-to-next-to-leading order (NNLO) in QCD. We study the perturbative stability of production cross sections with same-sign and opposite-sign charge combinations for the W boson and the charm jet. A detailed breakdown according to different partonic initial states allows us to identify particularly suitable observables for the study of the quark parton distributions of different flavours.

Visualizing the Heterogeneity in Homogeneous Supramolecular Polymers.

The dynamic properties of supramolecular polymers enable new functionality beyond the limitations of conventional polymers. The mechanism of the monomer exchange between different supramolecular polymers is proposed to be closely associated with local disordered domains within the supramolecular polymers. However, a direct detection of such heterogeneity has never been experimentally probed. Here, we present the direct visualization of the local disordered domains in the backbone of supramolecular polymers by a super-resolution microscopy technique: Nile Red-based spectrally resolved point accumulation for imaging in nanoscale topography (NR-sPAINT). We investigate the local disordered domains in trisamide-based supramolecular polymers comprising a (co)assembly of benzene-1,3,5-tricarboxamide (BTA) and a variant with one of the amide bonds inverted (iBTA). The NR-sPAINT allows us to simultaneously map the spatial distribution and polarity of the local disordered domains along the polymers with a spatial precision down to ∼20 nm. Quantitative autocorrelation and cross-correlation analysis show subtle differences in the spatial distribution of the disordered domains between polymers composed of different variants of BTA monomers. Further, statistical analysis unraveled high heterogeneity in monomer packing at both intra- and interpolymer levels. The results reported here demonstrate the necessity of investigating the structures in soft materials at nanoscale to fully understand their intricacy.

Prognosing post-treatment outcomes of head and neck cancer using structured data and machine learning: A systematic review.

BACKGROUND: This systematic review aimed to evaluate the performance of machine learning (ML) models in predicting post-treatment survival and disease progression outcomes, including recurrence and metastasis, in head and neck cancer (HNC) using clinicopathological structured data. METHODS: A systematic search was conducted across the Medline, Scopus, Embase, Web of Science, and Google Scholar databases. The methodological characteristics and performance metrics of studies that developed and validated ML models were assessed. The risk of bias was evaluated using the Prediction model Risk Of Bias ASsessment Tool (PROBAST). RESULTS: Out of 5,560 unique records, 34 articles were included. For survival outcome, the ML model outperformed the Cox proportional hazards model in time-to-event analyses for HNC, with a concordance index of 0.70-0.79 vs. 0.66-0.76, and for all sub-sites including oral cavity (0.73-0.89 vs. 0.69-0.77) and larynx (0.71-0.85 vs. 0.57-0.74). In binary classification analysis, the area under the receiver operating characteristics (AUROC) of ML models ranged from 0.75-0.97, with an F1-score of 0.65-0.89 for HNC; AUROC of 0.61-0.91 and F1-score of 0.58-0.86 for the oral cavity; and AUROC of 0.76-0.97 and F1-score of 0.63-0.92 for the larynx. Disease-specific survival outcomes showed higher performance than overall survival outcomes, but the performance of ML models did not differ between three- and five-year follow-up durations. For disease progression outcomes, no time-to-event metrics were reported for ML models. For binary classification of the oral cavity, the only evaluated subsite, the AUROC ranged from 0.67 to 0.97, with F1-scores between 0.53 and 0.89. CONCLUSIONS: ML models have demonstrated considerable potential in predicting post-treatment survival and disease progression, consistently outperforming traditional linear models and their derived nomograms. Future research should incorporate more comprehensive treatment features, emphasize disease progression outcomes, and establish model generalizability through external validations and the use of multicenter datasets.

Digoxin treatment does not reinduce radioiodine uptake in radioiodine refractory non-medullary thyroid carcinoma.

OBJECTIVES: Patients with non-medullary thyroid carcinoma (NMTC) that are refractory to radioactive iodine (RAI) have a poor prognosis. Strategies for restoring the ability to take up iodine, so called redifferentiation, are promising but not suitable for all patients. Preclinical studies have shown that the cardiac glycoside digoxin restored RAI uptake, both in human cell lines as in a murine model. This prospective single-center open-label study aimed to investigate whether treatment with digoxin could reinduce clinically relevant RAI uptake in patients with metastasized RAI refractory NMTC. METHODS: Eight patients with metastasized RAI refractory NMTC were included between November 2022 and June 2023. Before treatment a baseline [123I]NaI-scintigraphy was performed. Thereafter, patients were treated with digoxin for three weeks. Starting doses depended on age and weight. For safety reasons, the usual therapeutic range was aimed for. After one week, the digoxin plasma concentration as measured and digoxin dose was adjusted if necessary. After three weeks of digoxin treatment, a second [123I]NaI-scintigraphy was performed. RAI uptake was compared between the two scintigraphies. RESULTS: Seven patients completed the digoxin treatment and were evaluable. None of the seven patients showed clinically relevant RAI uptake after digoxin treatment. No digoxin-related serious adverse events occurred during this trial. CONCLUSION: Contrary to results from preclinical trials, in this trial, three weeks of digoxin treatment did not reinduce RAI uptake in patients with NMTC. This highlights essential challenges regarding the approach towards optimization of studies aimed to restore the RAI uptake and its therapeutic efficacy through drug repurposing.

From theory to practice in implementation science: qualitative insights from the implementation model developed by a commercial eMental Health provider.

BACKGROUND: Although eMental health interventions are a viable solution to address disparities in access to mental healthcare and increase its efficiency, they still face challenges of implementation. Literature highlights numerous barriers such as diffusion of responsibility and unclear expectations of what implementation entails might hinder this process. While research mostly focuses on analyzing these barriers, there is an urgent need to increase uptake in practice. In turn, commercial companies focus mostly on increasing uptake, while overlooking research outputs. To bridge the gap between research and practice, attention to how implementation occurs in practice is required. This study investigates "Make it Happen" (MiH), the implementation model developed by the eMental Health company Minddistrict, aiming to gain more insight into operationalizing implementation frameworks by 1) describing MiH and its conceptual underpinnings, and 2) gaining lessons learned from the development of MiH. Ultimately, this work aims at improving existing scientific frameworks by extending them with knowledge from practice. METHODS: First, individual interviews and focus groups with Minddistrict implementation managers were performed. Second, individual interviews with project leads in mental healthcare organizations that were involved in the implementation of Minddistrict were conducted. Within Minddistrict, 7 implementation managers and account managers were involved, in addition to 11 project leads from mental healthcare organizations. Data were elaborated with thematic analysis. RESULTS: A comprehensive description of MiH and its 5 main phases was achieved. During the 1) Onboarding phase, implementing organizations are guided by Minddistrict to build a team responsible for implementation, which then 2) designs patient and client journeys, 3) builds, tailors and configures their offer, 4) trains key-users and, 5) evaluates the success of implementation. All participants had extensive and aligned definitions and articulated expectations on implementation. Points of improvement for the model such as role ambiguity and excessive workload were identified. As strengths, internal motivation and good relationships with the provider were valued. CONCLUSION: The present study highlights the importance of clear role division and stakeholder engagement in implementation processes, and suggest that a strong collaboration between companies and academia could optimize implementation efforts and ensure a better fit between humans, context, and technologies.

A novel Slide-seq based image processing software to identify gene expression at the single cell level.

Analysis of gene expression at the single-cell level could help predict the effectiveness of therapies in the field of chronic inflammatory diseases such as arthritis. Here, we demonstrate an adopted approach for processing images from the Slide-seq method. Using a puck, which consists of about 50,000 DNA barcode beads, an RNA sequence of a cell is to be read. The pucks are repeatedly brought into contact with liquids and then recorded with a conventional epifluorescence microscope. The image analysis initially consists of stitching the partial images of a sequence recording, registering images from different sequences, and finally reading out the bases. The new method enables the use of an inexpensive epifluorescence microscope instead of a confocal microscope.

Including 'Work as a Treatment Goal' in the Care for Patients with Chronic Diseases : The Development of a Generic Care Model-A Descriptive Study.

BACKGROUND: The Netherlands faces 60% prevalence of chronic conditions by 2040, impacting societal participation and quality of life. Current clinical care inadequately addresses these consequences, and most hospitals do not integrate occupational health in their care. OBJECTIVES: To develop a generic person- and work-oriented medical care model (WMCM) based on real life experiences with work-oriented care and supporting the chronically ill in active societal participation. METHODS: A qualitative research project with a participative approach in one hospital (November 2019 until March 2020). In an expert meeting, a schematic representation of a work-oriented care model was developed. Subsequent discussion rounds, with professionals from different patient groups, iteratively refined the model to a WMCM. RESULTS: Consensus was reached after seven rounds of discussion, defining the model's core elements (1) a combination of biomedical and biopsychosocial approaches, (2) involvement of a clinical occupational physician in the treatment team, (3) a coordinating role for nursing specialists, and (4) incorporation of a work-oriented intervention plan (WoIP) into the treatment plan. Advocating early attention to societal participation, the model emphasises the WoIP and consensus on monitoring indicators. The final goal is a sustainable return to societal participation, considering both quality of life and work. CONCLUSION: It is feasible to develop a generic person- and work-oriented care model for patients with chronic illness within a hospital care setting. Collaboration between healthcare professionals and a specialised occupational physician, with a central role for nurses, is deemed crucial.

Appropriate trust in artificial intelligence for the optical diagnosis of colorectal polyps: The role of human/artificial intelligence interaction.

BACKGROUND AND AIMS: Computer-aided diagnosis (CADx) for optical diagnosis of colorectal polyps is thoroughly investigated. However, studies on human-artificial intelligence (AI) interaction are lacking. Aim was to investigate endoscopists' trust in CADx by evaluating whether communicating a calibrated algorithm confidence improved trust. METHODS: Endoscopists optically diagnosed 60 colorectal polyps. Initially, endoscopists diagnosed the polyps without CADx assistance (initial diagnosis). Immediately afterwards, the same polyp was again shown with CADx prediction; either only a prediction (benign or pre-malignant) or a prediction accompanied by a calibrated confidence score (0-100). A confidence score of 0 indicated a benign prediction, 100 a (pre-)malignant prediction. In half of the polyps CADx was mandatory, for the other half CADx was optional. After reviewing the CADx prediction, endoscopists made a final diagnosis. Histopathology was used as gold standard. Endoscopists' trust in CADx was measured as CADx prediction utilization; the willingness to follow CADx predictions when the endoscopists initially disagreed with the CADx prediction. RESULTS: Twenty-three endoscopists participated. Presenting CADx predictions increased the endoscopists' diagnostic accuracy (69.3% initial vs 76.6% final diagnosis, p<0.001). The CADx prediction was utilized in 36.5% (n=183/501) disagreements. Adding a confidence score led to a lower CADx prediction utilization, except when the confidence score surpassed 60. A mandatory CADx decreased CADx prediction utilization compared to an optional CADx. Appropriate trust, utilizing correct or disregarding incorrect CADx predictions was 48.7% (n=244/501). CONCLUSIONS: Appropriate trust was common and CADx prediction utilization was highest for the optional CADx without confidence scores. These results express the importance of a better understanding of human-AI interaction.

Uniportal versus multiportal video-assisted thoracoscopic surgery for spontaneous pneumothorax.

BACKGROUND: Multiportal video-assisted thoracic surgery (mVATS) is the standard approach for the surgical treatment of spontaneous pneumothorax. However, uniportal VATS (uVATS) has emerged as an alternative aiming to minimize surgical morbidity. This study aims to strengthen the evidence on the safety and efficiency of uVATS compared to mVATS. METHODS: From January 2004 to December 2020, records of patients who had undergone surgical treatment for primary or secondary spontaneous pneumothorax were evaluated for eligibility. Patients who had undergone pleurectomy combined with bullectomy or apical wedge resection via uVATS or mVATS were included. Surgical characteristics and postoperative data were compared between patients who had undergone surgery via uVATS or mVATS. Univariable and multivariable analyses were performed to determine whether the surgical approach was associated with any complication (primary outcome), major complications (i.e., Clavien-Dindo ≥ 3), recurrence, prolonged hospitalization or prolonged chest drainage duration (secondary outcomes). RESULTS: A total of 212 patients were enrolled. Patients treated via uVATS (n = 71) and mVATS (n = 141) were significantly different in pneumothorax type (secondary spontaneous; uVATS: 54 [76%], mVATS: 79 [56%]; p = 0.004). No significant differences were observed in (major) complications and recurrence rates between both groups. Multivariable analyses revealed that the surgical approach was no significant predictor for the primary or secondary outcomes. CONCLUSIONS: This study indicates that uVATS is non-inferior to mVATS in the surgical treatment of spontaneous pneumothorax regarding safety and efficiency, and thus the uVATS approach has the potential for further improvements in the perioperative surgical care for spontaneous pneumothorax.

Deep neural networks detect regional wall motion abnormalities and preclinical cardiovascular disease from 12-lead ECGs.

Background: Identifying regional wall motion abnormalities (RWMAs) is critical for diagnosing and risk stratifying patients with cardiovascular disease, particularly ischemic heart disease. We hypothesized that a deep neural network could accurately identify patients with regional wall motion abnormalities from a readily available standard 12-lead electrocardiogram (ECG). Methods: This observational, retrospective study included patients who were treated at Beth Israel Deaconess Medical Center and had an ECG and echocardiogram performed within 14 days of each other between 2008 and 2019. We trained a convolutional neural network to detect the presence of RWMAs, qualitative global right ventricular (RV) hypokinesis, and varying degrees of left ventricular dysfunction (left ventricular ejection fraction [LVEF] ≤50%, LVEF ≤40%, and LVEF ≤35%) identified by echocardiography, using ECG data alone. Patients were randomly split into development (80%) and test sets (20%). Model performance was assessed using area under the receiver operating characteristic curve (AUC). Cox proportional hazard models adjusted for age and sex were performed to estimate the risk of future acute coronary events. Results: The development set consisted of 19,837 patients (mean age 66.7±16.4; 46.7% female) and the test set comprised of 4,953 patients (mean age 67.5±15.8 years; 46.5% female). On the test dataset, the model accurately identified the presence of RWMA, RV hypokinesis, LVEF ≤50%, LVEF ≤40%, and LVEF ≤35% with AUCs of 0.87 (95% CI 0.858-0.882), 0.888 (95% CI 0.878-0.899), 0.923 (95% CI 0.914-0.933), 0.93 (95% CI 0.921-0.939), and 0.876 (95% CI 0.858-0.896), respectively. Among patients with normal biventricular function at the time of the index ECG, those classified as having RMWA by the model were 3 times the risk (age- and sex-adjusted hazard ratio, 2.8; 95% CI 1.9-3.9) for future acute coronary events compared to those classified as negative. Conclusions: We demonstrate that a deep neural network can help identify regional wall motion abnormalities and reduced LV function from a 12-lead ECG and could potentially be used as a screening tool for triaging patients who need either initial or repeat echocardiographic imaging.