Biomineralization of Polyelectrolyte-Functionalized Electrospun Fibers: Optimization and In Vitro Validation for Bone Applications.

In recent years, polyelectrolytes have been successfully used as an alternative to non-collagenous proteins to promote interfibrillar biomineralization, to reproduce the spatial intercalation of mineral phases among collagen fibrils, and to design bioinspired scaffolds for hard tissue regeneration. Herein, hybrid nanofibers were fabricated via electrospinning, by using a mixture of Poly ɛ-caprolactone (PCL) and cationic cellulose derivatives, i.e., cellulose-bearing imidazolium tosylate (CIMD). The obtained fibers were self-assembled with Sodium Alginate (SA) by polyelectrolyte interactions with CIMD onto the fiber surface and, then, treated with simulated body fluid (SBF) to promote the precipitation of calcium phosphate (CaP) deposits. FTIR analysis confirmed the presence of SA and CaP, while SEM equipped with EDX analysis mapped the calcium phosphate constituent elements, estimating an average Ca/P ratio of about 1.33-falling in the range of biological apatites. Moreover, in vitro studies have confirmed the good response of mesenchymal cells (hMSCs) on biomineralized samples, since day 3, with a significant improvement in the presence of SA, due to the interaction of SA with CaP deposits. More interestingly, after a decay of metabolic activity on day 7, a relevant increase in cell proliferation can be recognized, in agreement with the beginning of the differentiation phase, confirmed by ALP results. Antibacterial tests performed by using different bacteria populations confirmed that nanofibers with an SA-CIMD complex show an optimal inhibitory response against S. mutans, S. aureus, and E. coli, with no significant decay due to the effect of CaP, in comparison with non-biomineralized controls. All these data suggest a promising use of these biomineralized fibers as bioinspired membranes with efficient antimicrobial and osteoconductive cues suitable to support bone healing/regeneration.

Artificial Intelligence in Cardiovascular Care - Part 2: Applications: JACC Review Topic of the Week.

Recent Artificial Intelligence (AI) advancements in cardiovascular care offer potential enhancements in effective diagnosis, treatment, and outcomes. Over 600 Food and Drug Administration (FDA)-approved clinical AI algorithms now exist, with 10% focusing on cardiovascular applications, highlighting the growing opportunities for AI to augment care. This review discusses the latest advancements in the field of AI, with a particular focus on the utilization of multimodal inputs and the field of generative AI. Further discussions in this review involve an approach to understanding the larger context in which AI-augmented care may exist, and include a discussion of the need for rigorous evaluation, appropriate infrastructure for deployment, ethics and equity assessments, regulatory oversight, and viable business cases for deployment. Embracing this rapidly evolving technology while setting an appropriately high evaluation benchmark with careful and patient-centered implementation will be crucial for cardiology to leverage AI to enhance patient care and the provider experience.

Artificial Intelligence for Cardiovascular Care - Part 1: Advances: JACC Review Topic of the Week.

Recent AI advancements in cardiovascular care offer potential enhancements in diagnosis, treatment, and outcomes. Innovations to date focus on automating measurements, enhancing image quality, and detecting diseases using novel methods. Applications span wearables, electrocardiograms, echocardiography, angiography, genetics, and more. AI models detect diseases from electrocardiograms at accuracy not previously achieved by technology or human experts, including reduced ejection fraction, valvular heart disease, and other cardiomyopathies. However, AI's unique characteristics necessitates rigorous validation by addressing training methods, real-world efficacy, equity concerns, and long-term reliability. Despite an exponentially growing number of studies in cardiovascular AI, trials showing improvement in outcomes remain lacking. A number are currently underway. Embracing this rapidly evolving technology while setting a high evaluation benchmark will be crucial for cardiology to leverage AI to enhance patient care and the provider experience.

Physical and structural characterization of bis-acryl composite resin.

During the preparation of fixed prosthesis (including individual bridges and crowns) it is important to select the materials that have the best features and properties to predict a successful clinical treatment. The objective of this study was to determine if the chemical and structural characteristics could cause to increase the fracture resistance, we used four bis-acryl resins Luxatemp, Protemp, Structur and Telio. Three-points bending by Flexural test were performed in ten bars and they were carried out to compare with Anova test. In addition, the bis-acryl resins were analyzed by scanning electron microscopy, to analyze microstructure and morphology and the molecular structure were performed by Infrared Spectroscopy through Attenuated Total Reflectance. A higher flexural strength was found in Luxatemp and Structur with, no significant differences between this study groups. Regarding Protemp and Telio, these study groups showed a lower flexural strength when were compared with Luxatemp and Structur. These results corroborate SEM and ATR analysis because Luxatemp sample showed a regular size particle on the surface and chemically presents a long cross-linkage polymer chain. The presence of CO3, SiO2 and N-H groups as a fillers particle interacting with OH groups cause a higher flexural strength compared with another groups.

Characteristics of contemporary atrial fibrillation clinical trials and their association with industry sponsorship.

BACKGROUND: Industry sponsorship is an important source of funding for atrial fibrillation (AF) clinical trials, the implications of which have not been analyzed. OBJECTIVE: The purpose of this study was to determine the characteristics of contemporary AF clinical trials and to evaluate their association with funding source. METHODS: We systematically assessed all completed AF trials registered in the ClinicalTrials.gov database between conception to October 31, 2023, and extracted publicly available information including funding source, trial size, demographic distribution, intervention, location, and publication status. Trial characteristics were compared using the Wilcoxon rank-sum test and Fisher exact test for continuous and categorical variables, respectively. RESULTS: Of the 253 clinical trials assessed, 171 (68%) reported industry funding. Industry funding was associated with a greater median number of patients enrolled (172 vs 80; P <.001), publication rate (56.7% vs 42.7%; P = .04), probability of being product-focused (48.0% vs 24.4%; P <.001), and multicontinental recruitment location (25.2% vs 2.4%; P <.001) when compared to nonindustry-funded trials. However, industry funding was not associated with a significant difference in median impact factor (7.7 vs 7.7; P = .723). The overall proportion of industry-funded trials did not change over time (P = 1). CONCLUSION: Industry-funded clinical trials in AF often are larger, more frequently published, multicontinental, and product-focused. Industry funding was found to be associated with significant differences in study enrollment and publication metrics.

Prevalence of frequent premature ventricular contractions and nonsustained ventricular tachycardia in older women screened for atrial fibrillation in the Women's Health Initiative.

BACKGROUND: Frequent premature ventricular contractions (PVCs) and nonsustained ventricular tachycardia (NSVT) have been associated with cardiovascular disease and mortality. Their prevalence, especially in ambulatory populations, is understudied and limited by few female participants and the use of short-duration (24- to 48-hour) monitoring. OBJECTIVE: The objective of this study was to report the prevalence of frequent PVCs and NSVT in a community-based population of women likely to undergo electrocardiogram (ECG) screening by sequential patch monitoring. METHODS: Participants from the Women's Health Initiative Strong and Healthy (WHISH) trial with no history of atrial fibrillation (AF) but 5-year predicted risk of incident AF ≥5% by CHARGE-AF score were randomly selected to undergo screening with 7-day ECG patch monitors at baseline, 6 months, and 12 months. Recordings were reviewed for PVCs and NSVT (>5 beats); data were analyzed with multivariate regression models. RESULTS: There were 1067 participants who underwent ECG screening at baseline, 866 at 6 months, and 777 at 12 months. Frequent PVCs were found on at least 1 patch from 4.3% of participants, and 1 or more episodes of NSVT were found in 12 (1.1%) women. PVC frequency directly correlated with CHARGE-AF score and NSVT on any patch. Detection of frequent PVCs increased with sequential monitoring. CONCLUSION: In postmenopausal women at high risk for AF, frequent PVCs were relatively common (4.3%) and correlated with higher CHARGE-AF score. As strategies for AF screening continue to evolve, particularly in those individuals at high risk of AF, the prevalence of incidental ventricular arrhythmias is an important benchmark to guide clinical decision-making.

Expedited loading with intravenous sotalol is safe and feasible-primary results of the Prospective Evaluation Analysis and Kinetics of IV Sotalol (PEAKS) Registry.

BACKGROUND: Loading of oral sotalol for atrial fibrillation requires 3 days, frequently in the hospital, to achieve steady state. The Food and Drug Administration approved loading with intravenous (IV) sotalol through model-informed development, without patient data. OBJECTIVE: We present results of the first multicenter evaluation of this recent labeling for IV sotalol. METHODS: The Prospective Evaluation Analysis and Kinetics of IV Sotalol (PEAKS) Registry was a multicenter observational registry of patients undergoing elective IV sotalol load for atrial arrhythmias. Outcomes, measured from hospital admission until first outpatient follow-up, included adverse arrhythmia events, efficacy, and length of stay. RESULTS: Of 167 consecutively enrolled patients, 23% were female; the median age was 68 (interquartile range, 61-74) years, and the median CHA2DS2-VASc score was 3 (interquartile range, 2-4). Overall, 99% were admitted for sotalol initiation (1% for dose escalation), with a target oral sotalol dose of either 80 mg twice daily (85 [51%]) or 120 mg twice daily (78 [47%]); 62 patients (37%) had an estimated creatinine clearance ≤90 mL/min. On presentation, 40% of patients were in sinus rhythm, whereas 26% underwent cardioversion before sotalol infusion. In 2 patients, sotalol infusion was stopped for bradycardia or hypotension. In 6 patients, sotalol was discontinued before discharge because of QTc prolongation (3), bradycardia (1), or recurrent atrial arrhythmia (2). The mean length of stay was 1.1 days, and 95% (n = 159) were discharged within 1 night. CONCLUSION: IV sotalol loading is safe and feasible for atrial arrhythmias, with low rates of adverse events, and yields shorter hospitalizations. More data are needed on the minimal duration required for monitoring in the hospital.

2023 ACC/AHA/ACCP/HRS Guideline for the Diagnosis and Management of Atrial Fibrillation: A Report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines.

AIM: The "2023 ACC/AHA/ACCP/HRS Guideline for the Diagnosis and Management of Patients With Atrial Fibrillation" provides recommendations to guide clinicians in the treatment of patients with atrial fibrillation. METHODS: A comprehensive literature search was conducted from May 12, 2022, to November 3, 2022, encompassing studies, reviews, and other evidence conducted on human subjects that were published in English from PubMed, EMBASE, the Cochrane Library, the Agency for Healthcare Research and Quality, and other selected databases relevant to this guideline. Additional relevant studies, published through November 2022, during the guideline writing process, were also considered by the writing committee and added to the evidence tables, where appropriate. STRUCTURE: Atrial fibrillation is the most sustained common arrhythmia, and its incidence and prevalence are increasing in the United States and globally. Recommendations from the "2014 AHA/ACC/HRS Guideline for the Management of Patients With Atrial Fibrillation" and the "2019 AHA/ACC/HRS Focused Update of the 2014 AHA/ACC/HRS Guideline for the Management of Patients With Atrial Fibrillation" have been updated with new evidence to guide clinicians. In addition, new recommendations addressing atrial fibrillation and thromboembolic risk assessment, anticoagulation, left atrial appendage occlusion, atrial fibrillation catheter or surgical ablation, and risk factor modification and atrial fibrillation prevention have been developed.

Electrocardiographic deep learning for predicting post-procedural mortality: a model development and validation study.

BACKGROUND: Preoperative risk assessments used in clinical practice are insufficient in their ability to identify risk for postoperative mortality. Deep-learning analysis of electrocardiography can identify hidden risk markers that can help to prognosticate postoperative mortality. We aimed to develop a prognostic model that accurately predicts postoperative mortality in patients undergoing medical procedures and who had received preoperative electrocardiographic diagnostic testing. METHODS: In a derivation cohort of preoperative patients with available electrocardiograms (ECGs) from Cedars-Sinai Medical Center (Los Angeles, CA, USA) between Jan 1, 2015 and Dec 31, 2019, a deep-learning algorithm was developed to leverage waveform signals to discriminate postoperative mortality. We randomly split patients (8:1:1) into subsets for training, internal validation, and final algorithm test analyses. Model performance was assessed using area under the receiver operating characteristic curve (AUC) values in the hold-out test dataset and in two external hospital cohorts and compared with the established Revised Cardiac Risk Index (RCRI) score. The primary outcome was post-procedural mortality across three health-care systems. FINDINGS: 45 969 patients had a complete ECG waveform image available for at least one 12-lead ECG performed within the 30 days before the procedure date (59 975 inpatient procedures and 112 794 ECGs): 36 839 patients in the training dataset, 4549 in the internal validation dataset, and 4581 in the internal test dataset. In the held-out internal test cohort, the algorithm discriminates mortality with an AUC value of 0·83 (95% CI 0·79-0·87), surpassing the discrimination of the RCRI score with an AUC of 0·67 (0·61-0·72). The algorithm similarly discriminated risk for mortality in two independent US health-care systems, with AUCs of 0·79 (0·75-0·83) and 0·75 (0·74-0·76), respectively. Patients determined to be high risk by the deep-learning model had an unadjusted odds ratio (OR) of 8·83 (5·57-13·20) for postoperative mortality compared with an unadjusted OR of 2·08 (0·77-3·50) for postoperative mortality for RCRI scores of more than 2. The deep-learning algorithm performed similarly for patients undergoing cardiac surgery (AUC 0·85 [0·77-0·92]), non-cardiac surgery (AUC 0·83 [0·79-0·88]), and catheterisation or endoscopy suite procedures (AUC 0·76 [0·72-0·81]). INTERPRETATION: A deep-learning algorithm interpreting preoperative ECGs can improve discrimination of postoperative mortality. The deep-learning algorithm worked equally well for risk stratification of cardiac surgeries, non-cardiac surgeries, and catheterisation laboratory procedures, and was validated in three independent health-care systems. This algorithm can provide additional information to clinicians making the decision to perform medical procedures and stratify the risk of future complications. FUNDING: National Heart, Lung, and Blood Institute.

2023 ACC/AHA/ACCP/HRS Guideline for the Diagnosis and Management of Atrial Fibrillation: A Report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines.

AIM: The "2023 ACC/AHA/ACCP/HRS Guideline for the Diagnosis and Management of Atrial Fibrillation" provides recommendations to guide clinicians in the treatment of patients with atrial fibrillation. METHODS: A comprehensive literature search was conducted from May 12, 2022, to November 3, 2022, encompassing studies, reviews, and other evidence conducted on human subjects that were published in English from PubMed, EMBASE, the Cochrane Library, the Agency for Healthcare Research and Quality, and other selected databases relevant to this guideline. Additional relevant studies, published through November 2022, during the guideline writing process, were also considered by the writing committee and added to the evidence tables, where appropriate. STRUCTURE: Atrial fibrillation is the most sustained common arrhythmia, and its incidence and prevalence are increasing in the United States and globally. Recommendations from the "2014 AHA/ACC/HRS Guideline for the Management of Patients With Atrial Fibrillation" and the "2019 AHA/ACC/HRS Focused Update of the 2014 AHA/ACC/HRS Guideline for the Management of Patients With Atrial Fibrillation" have been updated with new evidence to guide clinicians. In addition, new recommendations addressing atrial fibrillation and thromboembolic risk assessment, anticoagulation, left atrial appendage occlusion, atrial fibrillation catheter or surgical ablation, and risk factor modification and atrial fibrillation prevention have been developed.

Clinical Management of Brugada Syndrome: Commentary From the Experts.

Although there is consensus on the management of patients with Brugada Syndrome with high risk for sudden cardiac arrest, asymptomatic or intermediate-risk patients present clinical management challenges. This document explores the management opinions of experts throughout the world for patients with Brugada Syndrome who do not fit guideline recommendations. Four real-world clinical scenarios were presented with commentary from small expert groups for each case. All authors voted on case-specific questions to evaluate the level of consensus among the entire group in nuanced diagnostic and management decisions relevant to each case. Points of agreement, points of controversy, and gaps in knowledge are highlighted.

Race, Sex, and Age Disparities in the Performance of ECG Deep Learning Models Predicting Heart Failure.

BACKGROUND: Deep learning models may combat widening racial disparities in heart failure outcomes through early identification of individuals at high risk. However, demographic biases in the performance of these models have not been well-studied. METHODS: This retrospective analysis used 12-lead ECGs taken between 2008 and 2018 from 326 518 patient encounters referred for standard clinical indications to Stanford Hospital. The primary model was a convolutional neural network model trained to predict incident heart failure within 5 years. Biases were evaluated on the testing set (160 312 ECGs) using the area under the receiver operating characteristic curve, stratified across the protected attributes of race, ethnicity, age, and sex. RESULTS: There were 59 817 cases of incident heart failure observed within 5 years of ECG collection. The performance of the primary model declined with age. There were no significant differences observed between racial groups overall. However, the primary model performed significantly worse in Black patients aged 0 to 40 years compared with all other racial groups in this age group, with differences most pronounced among young Black women. Disparities in model performance did not improve with the integration of race, ethnicity, sex, and age into model architecture, by training separate models for each racial group, or by providing the model with a data set of equal racial representation. Using probability thresholds individualized for race, age, and sex offered substantial improvements in F1 scores. CONCLUSIONS: The biases found in this study warrant caution against perpetuating disparities through the development of machine learning tools for the prognosis and management of heart failure. Customizing the application of these models by using probability thresholds individualized by race, ethnicity, age, and sex may offer an avenue to mitigate existing algorithmic disparities.

Utility of smart watches for identifying arrhythmias in children.

BACKGROUND: Arrhythmia symptoms are frequent complaints in children and often require a pediatric cardiology evaluation. Data regarding the clinical utility of wearable technologies are limited in children. We hypothesize that an Apple Watch can capture arrhythmias in children. METHODS: We present an analysis of patients ≤18 years-of-age who had signs of an arrhythmia documented by an Apple Watch. We include patients evaluated at our center over a 4-year-period and highlight those receiving a formal arrhythmia diagnosis. We evaluate the role of the Apple Watch in arrhythmia diagnosis, the results of other ambulatory cardiac monitoring studies, and findings of any EP studies. RESULTS: We identify 145 electronic-medical-record identifications of Apple Watch, and find arrhythmias confirmed in 41 patients (28%) [mean age 13.8 ± 3.2 years]. The arrythmias include: 36 SVT (88%), 3 VT (7%), 1 heart block (2.5%) and wide 1 complex tachycardia (2.5%). We show that invasive EP study confirmed diagnosis in 34 of the 36 patients (94%) with SVT (2 non-inducible). We find that the Apple Watch helped prompt a workup resulting in a new arrhythmia diagnosis for 29 patients (71%). We note traditional ambulatory cardiac monitors were worn by 35 patients (85%), which did not detect arrhythmias in 10 patients (29%). In 73 patients who used an Apple Watch for recreational or self-directed heart rate monitoring, 18 (25%) sought care due to device findings without any arrhythmias identified. CONCLUSION: We demonstrate that the Apple Watch can record arrhythmia events in children, including events not identified on traditionally used ambulatory monitors.

Wearable devices, such as smart watches, have become popular for the monitoring of health, particularly for people with heart conditions. Wearable devices have been well-studied in adults, however there is less information available on their effectiveness in monitoring children's health. We reviewed the heart electrical recordings of a group of children who submitted recordings obtained from their Apple Watches during moments when they felt as though their heart's rhythm was abnormal. The Apple Watches captured rhythm abnormalities that matched the diagnoses obtained using heart monitors used clinically. This study shows that use of Apple Watches can enable clinicians to identify abnormalities that many traditional at-home monitoring devices do not detect. Thus, wearable devices, such as the Apple Watch, could be used to help identify heart rhythm disorders in children.

Mineralized Microgels via Electrohydrodynamic Atomization: Optimization and In Vitro Model for Dentin-Pulp Complex.

There is growing interest in the use of micro-sized hydrogels, including bioactive signals, as efficient platforms for tissue regeneration because they are able to mimic cell niche structure and selected functionalities. Herein, it is proposed to optimize bioactive composite microgels via electrohydrodynamic atomization (EHDA) to regenerate the dentin-pulp complex. The addition of disodium phosphate (Na2HPO4) salts as mineral precursors triggered an in situ reaction with divalent ions in solution, thus promoting the encapsulation of different amounts of apatite-like phases. Morphological analysis via image analysis of optical images confirmed a narrow distribution of perfectly rounded particles, with an average diameter ranging from 223 ± 18 µm to 502 ± 64 µm as a function of mineral content and process parameters used. FTIR, TEM, and EDAX analyses confirmed the formation of calcium phosphates with a characteristic Ca/P ratio close to 1.67 and a needle-like crystal shape. In vitro studies-using dental pulp stem cells (DPSCs) in crown sections of natural teeth slices-showed an increase in cell viability until 14 days, recording a decay of proliferation at 21 days, independent on the mineral amount, suggesting that differentiation is started, as confirmed by the increase of ALP activity at 14 days. In this view, mineralized microgels could be successfully used to support in vitro osteogenesis, working as an interesting model to study dental tissue regeneration.

Improved Cardiac Performance and Decreased Arrhythmia in Hypertrophic Cardiomyopathy With Non-ß-Blocking R-Enantiomer Carvedilol.

BACKGROUND: Hypercontractility and arrhythmia are key pathophysiologic features of hypertrophic cardiomyopathy (HCM), the most common inherited heart disease. ß-Adrenergic receptor antagonists (ß-blockers) are the first-line therapy for HCM. However, ß-blockers commonly selected for this disease are often poorly tolerated in patients, where heart-rate reduction and noncardiac effects can lead to reduced cardiac output and fatigue. Mavacamten, myosin ATPase inhibitor recently approved by the US Food and Drug Administration, has demonstrated the ability to ameliorate hypercontractility without lowering heart rate, but its benefits are so far limited to patients with left ventricular (LV) outflow tract obstruction, and its effect on arrhythmia is unknown. METHODS: We screened 21 ß-blockers for their impact on myocyte contractility and evaluated the antiarrhythmic properties of the most promising drug in a ventricular myocyte arrhythmia model. We then examined its in vivo effect on LV function by hemodynamic pressure-volume loop analysis. The efficacy of the drug was tested in vitro and in vivo compared with current therapeutic options (metoprolol, verapamil, and mavacamten) for HCM in an established mouse model of HCM (Myh6R403Q/+ and induced pluripotent stem cell (iPSC)-derived cardiomyocytes from patients with HCM (MYH7R403Q/+). RESULTS: We identified that carvedilol, a ß-blocker not commonly used in HCM, suppresses contractile function and arrhythmia by inhibiting RyR2 (ryanodine receptor type 2). Unlike metoprolol (a ß1-blocker), carvedilol markedly reduced LV contractility through RyR2 inhibition, while maintaining stroke volume through α1-adrenergic receptor inhibition in vivo. Clinically available carvedilol is a racemic mixture, and the R-enantiomer, devoid of ß-blocking effect, retains the ability to inhibit both α1-receptor and RyR2, thereby suppressing contractile function and arrhythmias without lowering heart rate and cardiac output. In Myh6R403Q/+ mice, R-carvedilol normalized hyperdynamic contraction, suppressed arrhythmia, and increased cardiac output better than metoprolol, verapamil, and mavacamten. The ability of R-carvedilol to suppress contractile function was well retained in MYH7R403Q/+ iPSC-derived cardiomyocytes. CONCLUSIONS: R-enantiomer carvedilol attenuates hyperdynamic contraction, suppresses arrhythmia, and at the same time, improves cardiac output without lowering heart rate by dual blockade of α1-adrenergic receptor and RyR2 in mouse and human models of HCM. This combination of therapeutic effects is unique among current therapeutic options for HCM and may particularly benefit patients without LV outflow tract obstruction.

Phase II trial of CDK4/6 inhibitor palbociclib in advanced sarcoma based on mRNA expression of CDK4/ CDKN2A.

Cyclin-dependent kinases 4 and 6 (CDK4/6) inhibitors demonstrated activity in terms of progression-free survival (PFS) in advanced dedifferentiated liposarcoma (DD-LPS), a sarcoma with CDK4 amplification. CDK4 overexpression is by far more common than amplification in sarcomas and it might be a rational target for CDK inhibitors. Preclinical investigators of this study found that CDK4 overexpression, while not of CDKN2A, was the most consistent predictive factor for palbociclib efficacy in sarcomas. Advanced adult-type soft-tissue sarcoma, excluding DD-LPS, or bone sarcoma patients, progressing after at least one systemic line, whose tumors overexpressed CDK4, but not CDKN2A at baseline biopsy, were accrued in this single-arm phase II trial (EudraCT number: 2016-004039-19). With the main endpoint of a 6-month PFS rate, 40% was considered promising in this population. Palbociclib was administered orally at 125 mg/day for 21 days in 28-day cycles. A total of 214 patients with 236 CDK4/CDKN2A determinations were assessed for prescreening, archival material (141), and screening, baseline biopsy (95). There were 28 (29%) with favorable mRNA profiles from 95 screened patients at baseline. From 23 enrolled patients, 21 evaluable, the 6-month PFS rate was 29% (95% CI 9-48), and there were 6 patients out of 21 with a PFS longer than 6 months. The median PFS and overall survival were 4.2 (95% CI 3.6-4.8) and 12 (95% CI 8.7-15.4) months, respectively. Translational research showed a significant correlation between CDK4 mRNA and protein expression. Palbociclib was active in a variety of sarcoma subtypes, selected by CDK4/CDKN2A, and deserves further investigation in the sarcoma context.

Primary explants of the postnatal thymus allow the expansion of clonogenic thymic epithelial cells that constitute thymospheres.

BACKGROUND: Thymic epithelial cells (TECs) are responsible for shaping the repertoires of T cells, where their postnatal regeneration depends on a subset of clonogenic TECs. Despite the implications for regenerative medicine, their cultivation and expansion remain challenging. Primary explant cell culture is a technique that allows the seeding and expansion of difficult-to-culture cells. Here, we report a reliable and simple culture system to obtain functional TECs and thymic interstitial cells (TICs). METHODS: To establish primary thymic explants, we harvested 1 mm cleaned fragments of thymus from 5-week-old C57/BL6 mice. Tissue fragments of a complete thymic lobe were placed in the center of a Petri dish with 1 mL of DMEM/F-12 medium supplemented with 20% fetal bovine serum (FBS) and 1% penicillin‒streptomycin. To compare, thymic explants were also cultivated by using serum-free DMEM/F-12 medium supplemented with 10% KnockOut™. RESULTS: We obtained high numbers of functional clonogenic TECs and TICs from primary thymic explants cultivated with DMEM/F-12 with 20% FBS. These cells exhibited a highly proliferative and migration profile and were able to constitute thymospheres. Furthermore, all the subtypes of medullary TECs were identified in this system. They express functional markers to shape T-cell and type 2 innate lymphoid cells repertoires, such as Aire, IL25, CCL21 and CD80. Finally, we also found that ≥ 70% of lineage negative TICs expressed high amounts of Aire and IL25. CONCLUSION: Thymic explants are an efficient method to obtain functional clonogenic TECs, all mTEC subsets and different TICs Aire+IL25+ with high regenerative capacity.

The evolving role of data & safety monitoring boards for real-world clinical trials.

Introduction: Clinical trials provide the "gold standard" evidence for advancing the practice of medicine, even as they evolve to integrate real-world data sources. Modern clinical trials are increasingly incorporating real-world data sources - data not intended for research and often collected in free-living contexts. We refer to trials that incorporate real-world data sources as real-world trials. Such trials may have the potential to enhance the generalizability of findings, facilitate pragmatic study designs, and evaluate real-world effectiveness. However, key differences in the design, conduct, and implementation of real-world vs traditional trials have ramifications in data management that can threaten their desired rigor. Methods: Three examples of real-world trials that leverage different types of data sources - wearables, medical devices, and electronic health records are described. Key insights applicable to all three trials in their relationship to Data and Safety Monitoring Boards (DSMBs) are derived. Results: Insight and recommendations are given on four topic areas: A. Charge of the DSMB; B. Composition of the DSMB; C. Pre-launch Activities; and D. Post-launch Activities. We recommend stronger and additional focus on data integrity. Conclusions: Clinical trials can benefit from incorporating real-world data sources, potentially increasing the generalizability of findings and overall trial scale and efficiency. The data, however, present a level of informatic complexity that relies heavily on a robust data science infrastructure. The nature of monitoring the data and safety must evolve to adapt to new trial scenarios to protect the rigor of clinical trials.