ACC/AHA/ESC guidelines for the management of patients with atrial fibrillation: executive summary: A Report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines and the European Society of Cardiology Committee for Practice Guidelines and Policy Conferences (Committee to Develop Guidelines for the Management of Patients With Atrial Fibrillation)

Atrial fibrillation (AF), the most common sustained cardiac rhythm disturbance, is increasing in prevalence as the population ages. Although it is often associated with heart disease, AF occurs in many patients with no detectable disease. Hemodynamic impairment and thromboembolic events result in significant morbidity, mortality, and cost. Accordingly, the American College of Cardiology (ACC), the American Heart Association (AHA), and the European Society of Cardiology (ESC) created a committee of experts to establish guidelines for management of this arrhythmia

ACC/AHA/ESC guidelines for the management of patients with atrial fibrillation: Executive summary. A report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines and the European Society of Cardiology Committee for Practice Guidelines and Policy Conferences (Committee to Develop Guidelines for the Management of Patients with Atrial Fibrillation)

Atrial fibrillation (AF), the most common sustained cardiac rhythm disturbance, is increasing in prevalence as the population ages. Although it is often associated with heart disease, AF occurs in many patients with no detectable disease. Hemodynamic impairment and thromboembolic events result in significant morbidity, mortality, and cost. Accordingly, the American College of Cardiology (ACC), the American Heart Association (AHA), and the European Society of Cardiology (ESC) created a committee of experts to establish guidelines for management of this arrhythmia

The NXDC-MEN-301 Study on 5-ALA for Meningiomas Surgery: An Innovative Study Design for the Assessing the Benefit of Intra-Operative Fluorescence Imaging

Background: 5-aminolevulinic acid (5-ALA; GleolanTM, NX Development Corps., Lexington, USA) is approved for fluorescence-guided resections of suspected malignant gliomas. Experience has demonstrated that meningiomas also show fluorescence, which may be a useful surgical adjunct. We present an innovative design for a multi-center, prospective study to determine the clinical safety and potential benefit of fluorescence-guided resection of meningiomas with utmost bias reduction. Methods: All patients with suspected meningioma (all grades) receive GleolanTM 20 mg/kg 2–4 h prior to surgery supported by fluorescence excitation from a blue light source (Blue400, Zeiss Meditech, Oberkochen, Germany; FL400, Leica Microsystems, Heerbrugg, Switzerland). Surgeons are asked whether a residual tumor can be observed to fluoresce under blue light (BL) after the tumor is no longer recognizable using conventional illumination at the end of surgery. In addition, when faced with tissues of uncertain tissue type (so-called “indeterminate” tissue), this study records how often surgeons make a correct decision based on fluorescence and how this influences surgical strategy. The primary endpoint is the percentage of patients in whom one of these two benefits are observed. Other endpoints include the diagnostic accuracy of fluorescence compared to white light (WL) versus correlative histology. For bias reduction, pertinent data are derived from surgical videos reviewed by independent reviewers blinded to surgeons’ assessments of tissue type and fluorescence status. Data will be included from approximately 100 study participants completing the study at approximately 15 centers in the United States, Germany, and Austria. Results: As of May 2022, 88 patients have completed the study. No adverse safety signal has been detected. Conclusions: Preliminary data confirm the feasibility of our study design. Accrual is targeted for completion in the third quarter of 2022

ACC/AHA/ESC guidelines for the management of patients with atrial fibrillation: A report of the American College of Cardiology/American Heart AssociationTask Force on Practice Guidelines and the European Society of Cardiology Committee for Practice Guidelines and Policy Conferences (Committee to develop guidelines for the management of patients with atrial fibrillation)

"Atrial fibrillation (AF) is the most common sustained rhythm disturbance. Its prevalence is increasing along with the age of the population. AF is often associated with structural heart disease, but a substantial proportion of patients with AF have no detectable heart disease. Haemodynamic impairment and thromboembolic events related to AF result in significant morbidity, mortality, and cost. Accordingly, the American College of Cardiology (ACC), the American Heart Association (AHA), and the European Society of Cardiology (ESC) created a committee to establish guidelines for better management of this frequent and complex arrhythmia.

Automated syndrome diagnosis by three-dimensional facial imaging.

PurposeDeep phenotyping is an emerging trend in precision medicine for genetic disease. The shape of the face is affected in 30-40% of known genetic syndromes. Here, we determine whether syndromes can be diagnosed from 3D images of human faces.MethodsWe analyzed variation in three-dimensional (3D) facial images of 7057 subjects: 3327 with 396 different syndromes, 727 of their relatives, and 3003 unrelated, unaffected subjects. We developed and tested machine learning and parametric approaches to automated syndrome diagnosis using 3D facial images.ResultsUnrelated, unaffected subjects were correctly classified with 96% accuracy. Considering both syndromic and unrelated, unaffected subjects together, balanced accuracy was 73% and mean sensitivity 49%. Excluding unrelated, unaffected subjects substantially improved both balanced accuracy (78.1%) and sensitivity (56.9%) of syndrome diagnosis. The best predictors of classification accuracy were phenotypic severity and facial distinctiveness of syndromes. Surprisingly, unaffected relatives of syndromic subjects were frequently classified as syndromic, often to the syndrome of their affected relative.ConclusionDeep phenotyping by quantitative 3D facial imaging has considerable potential to facilitate syndrome diagnosis. Furthermore, 3D facial imaging of "unaffected" relatives may identify unrecognized cases or may reveal novel examples of semidominant inheritance

Automated syndrome diagnosis by three-dimensional facial imaging.

PurposeDeep phenotyping is an emerging trend in precision medicine for genetic disease. The shape of the face is affected in 30-40% of known genetic syndromes. Here, we determine whether syndromes can be diagnosed from 3D images of human faces.MethodsWe analyzed variation in three-dimensional (3D) facial images of 7057 subjects: 3327 with 396 different syndromes, 727 of their relatives, and 3003 unrelated, unaffected subjects. We developed and tested machine learning and parametric approaches to automated syndrome diagnosis using 3D facial images.ResultsUnrelated, unaffected subjects were correctly classified with 96% accuracy. Considering both syndromic and unrelated, unaffected subjects together, balanced accuracy was 73% and mean sensitivity 49%. Excluding unrelated, unaffected subjects substantially improved both balanced accuracy (78.1%) and sensitivity (56.9%) of syndrome diagnosis. The best predictors of classification accuracy were phenotypic severity and facial distinctiveness of syndromes. Surprisingly, unaffected relatives of syndromic subjects were frequently classified as syndromic, often to the syndrome of their affected relative.ConclusionDeep phenotyping by quantitative 3D facial imaging has considerable potential to facilitate syndrome diagnosis. Furthermore, 3D facial imaging of "unaffected" relatives may identify unrecognized cases or may reveal novel examples of semidominant inheritance

Mapping the dynamic genetic regulatory architecture of HLA genes at single-cell resolution

The human leukocyte antigen (HLA) locus plays a critical role in complex traits spanning autoimmune and infectious diseases, transplantation and cancer. While coding variation in HLA genes has been extensively documented, regulatory genetic variation modulating HLA expression levels has not been comprehensively investigated. Here we mapped expression quantitative trait loci (eQTLs) for classical HLA genes across 1,073 individuals and 1,131,414 single cells from three tissues. To mitigate technical confounding, we developed scHLApers, a pipeline to accurately quantify single-cell HLA expression using personalized reference genomes. We identified cell-type-specific cis-eQTLs for every classical HLA gene. Modeling eQTLs at single-cell resolution revealed that many eQTL effects are dynamic across cell states even within a cell type. HLA-DQ genes exhibit particularly cell-state-dependent effects within myeloid, B and T cells. For example, a T cell HLA-DQA1 eQTL ( rs3104371 ) is strongest in cytotoxic cells. Dynamic HLA regulation may underlie important interindividual variability in immune responses.</p