Assessment of Digital Pathology Imaging Biomarkers Associated with Breast Cancer Histologic Grade

Background: Evaluating histologic grade for breast cancer diagnosis is standard and associated with prognostic outcomes. Current challenges include the time required for manual microscopic evaluation and interobserver variability. This study proposes a computer-aided diagnostic (CAD) pipeline for grading tumors using artificial intelligence. Methods: There were 138 patients included in this retrospective study. Breast core biopsy slides were prepared using standard laboratory techniques, digitized, and pre-processed for analysis. Deep convolutional neural networks (CNNs) were developed to identify the regions of interest containing malignant cells and to segment tumor nuclei. Imaging-based features associated with spatial parameters were extracted from the segmented regions of interest (ROIs). Clinical datasets and pathologic biomarkers (estrogen receptor, progesterone receptor, and human epidermal growth factor 2) were collected from all study subjects. Pathologic, clinical, and imaging-based features were input into machine learning (ML) models to classify histologic grade, and model performances were tested against ground-truth labels at the patient-level. Classification performances were evaluated using receiver-operating characteristic (ROC) analysis. Results: Multiparametric feature sets, containing both clinical and imaging-based features, demonstrated high classification performance. Using imaging-derived markers alone, the classification performance demonstrated an area under the curve (AUC) of 0.745, while modeling these features with other pathologic biomarkers yielded an AUC of 0.836. Conclusion: These results demonstrate an association between tumor nuclear spatial features and tumor grade. If further validated, these systems may be implemented into pathology CADs and can assist pathologists to expeditiously grade tumors at the time of diagnosis and to help guide clinical decisions

Predicting Patterns of Distant Metastasis in Breast Cancer Patients following Local Regional Therapy Using Machine Learning

Up to 30% of breast cancer (BC) patients will develop distant metastases (DM), for which there is no cure. Here, statistical and machine learning (ML) models were developed to estimate the risk of site-specific DM following local-regional therapy. This retrospective study cohort included 175 patients diagnosed with invasive BC who later developed DM. Clinicopathological information was collected for analysis. Outcome variables were the first site of metastasis (brain, bone or visceral) and the time interval (months) to developing DM. Multivariate statistical analysis and ML-based multivariable gradient boosting machines identified factors associated with these outcomes. Machine learning models predicted the site of DM, demonstrating an area under the curve of 0.74, 0.75, and 0.73 for brain, bone and visceral sites, respectively. Overall, most patients (57%) developed bone metastases, with increased odds associated with estrogen receptor (ER) positivity. Human epidermal growth factor receptor-2 (HER2) positivity and non-anthracycline chemotherapy regimens were associated with a decreased risk of bone DM, while brain metastasis was associated with ER-negativity. Furthermore, non-anthracycline chemotherapy alone was a significant predictor of visceral metastasis. Here, clinicopathologic and treatment variables used in ML prediction models predict the first site of metastasis in BC. Further validation may guide focused patient-specific surveillance practices.</jats:p

Understanding open access: when, why, and how to make your work openly accessible

This book provides the most up-to-date information about when, why, and how to make your work openly accessible.Its goal is to encourage authors to consider open access publishing by addressing common questions and concerns and by providing real-life strategies and tools that authors can use to work with publishers, institutions, and funders to make their works more widely accessible to all.&nbsp;The advent of global digital networks now provides authors who write to be read with exciting new options for communicating their ideas broadly. One of these options is open access. The basic idea of open access is that it makes copyrightable works available without all of the access barriers associated with the “all rights reserved” model. These can take the form of price barriers and permission barriers.&nbsp;Open access typically comes in two forms. What has come to be known as gratis open access is the practice of making a work available online &nbsp;free of charge (also called public access). The term libre open access (also called full open access) refers to the practice of making a work available online free of charge and with some additional reuse rights, typically granted through a Creative Commons license. Gratis open access removes price barriers, whereas libre open access additionally removes at least some permission barriers, allowing users to copy, redistribute, and/or adapt a work. Open access contrasts with more traditional models of restricted-access publishing in which copies of works are made directly available only to paying customers. Authors who are interested in increasing access to their works may want to understand whether eliminating cost and permissions barriers is a good option for them and, if so, how they might release their works under open access terms. Other authors may be required by their employer or funding agency to comply with an open access policy. Still other authors may be skeptical about whether open access is compatible with their publication goals—including rigorous peer review, prestige, or monetary compensation—and want to learn more

Brief Report: Impact of COVID-19 on Individuals with ASD and Their Caregivers: A Perspective from the SPARK Cohort

The impact of the 2019 coronavirus pandemic (COVID-19) in the United States is unprecedented, with unknown implications for the autism community. We surveyed 3502 parents/caregivers of individuals with an autism spectrum disorder (ASD) enrolled in Simons Powering Autism Research for Knowledge (SPARK) and found that most individuals with ASD experienced significant, ongoing disruptions to therapies. While some services were adapted to telehealth format, most participants were not receiving such services at follow-up, and those who were reported minimal benefit. Children under age five had the most severely disrupted services and lowest reported benefit of telehealth adaptation. Caregivers also reported worsening ASD symptoms and moderate family distress. Strategies to support the ASD community should be immediately developed and implemented

Brief Report: Impact of COVID-19 on Individuals with ASD and Their Caregivers: A Perspective from the SPARK Cohort

The impact of the 2019 coronavirus pandemic (COVID-19) in the United States is unprecedented, with unknown implications for the autism community. We surveyed 3502 parents/caregivers of individuals with an autism spectrum disorder (ASD) enrolled in Simons Powering Autism Research for Knowledge (SPARK) and found that most individuals with ASD experienced significant, ongoing disruptions to therapies. While some services were adapted to telehealth format, most participants were not receiving such services at follow-up, and those who were reported minimal benefit. Children under age five had the most severely disrupted services and lowest reported benefit of telehealth adaptation. Caregivers also reported worsening ASD symptoms and moderate family distress. Strategies to support the ASD community should be immediately developed and implemented

Maximizing success in single-session EUS-directed transgastric ERCP: a retrospective cohort study to identify predictive factors of stent migration

BACKGROUND AND AIMS: EUS-directed transgastric ERCP (the EDGE procedure) is a simplified method of performing ERCP in Roux-en-Y gastric bypass patients. The EDGE procedure involves placement of a lumen-apposing metal stent (LAMS) into the excluded stomach to serve as a conduit for passage of the duodenoscope for pancreatobiliary intervention. Originally a multistep process, urgent indications for ERCP have led to the development of single-session EDGE (SS-EDGE) with LAMS placement and ERCP performed in the same session. The goal of this study was to identify predictive factors of intraprocedural LAMS migration in SS-EDGE. METHODS: We conducted a multicenter retrospective review that included 9 tertiary medical centers across the United States. Data were collected and analyzed from 128 SS-EDGE procedures. The primary outcome was intraprocedural LAMS migration. Secondary outcomes were other procedural adverse events such as bleeding and perforation. RESULTS: Eleven LAMS migrations were observed in 128 procedures (8.6%). Univariate analysis of clinically relevant variables was performed, as was a binary logistic regression analysis of stent diameter and stent dilation. This revealed that use of a smaller (15 mm) diameter LAMS was an independent predictor of intraprocedural stent migration (odds ratio, 5.36; 95% confidence interval, 1.29-22.24; P = .021). Adverse events included 3 patients who required surgery and 2 who experienced intraprocedural bleeding. CONCLUSIONS: Use of a larger-diameter LAMS is a predictive factor for a nonmigrated stent and improved procedural success in SS-EDGE. Although larger patient cohorts are needed to adequately assess these findings, performance of LAMS dilation and fixation may also decrease risk of intraprocedural LAMS migration and improve procedural success

SPARK: A US Cohort of 50,000 Families to Accelerate Autism Research

The Simons Foundation Autism Research Initiative (SFARI) has launched SPARKForAutism. org, a dynamic platform that is engaging thousands of individuals with autism spectrum disorder (ASD) and connecting them to researchers. By making all data accessible, SPARK seeks to increase our understanding of ASD and accelerate new supports and treatments for ASD

The First Habitable-zone Earth-sized Planet from TESS. I. Validation of the TOI-700 System

We present the discovery and validation of a three-planet system orbiting the nearby (31.1 pc) M2 dwarf star TOI-700 (TIC 150428135). TOI-700 lies in the TESS continuous viewing zone in the Southern Ecliptic Hemisphere; observations spanning 11 sectors reveal three planets with radii ranging from 1 R⊕ to 2.6 R⊕ and orbital periods ranging from 9.98 to 37.43 days. Ground-based follow-up combined with diagnostic vetting and validation tests enables us to rule out common astrophysical false-positive scenarios and validate the system of planets. The outermost planet, TOI-700 d, has a radius of 1.19 ± 0.11 R⊕ and resides within a conservative estimate of the host star's habitable zone, where it receives a flux from its star that is approximately 86% of Earth's insolation. In contrast to some other low-mass stars that host Earth-sized planets in their habitable zones, TOI-700 exhibits low levels of stellar activity, presenting a valuable opportunity to study potentially rocky planets over a wide range of conditions affecting atmospheric escape. While atmospheric characterization of TOI-700 d with the James Webb Space Telescope (JWST) will be challenging, the larger sub-Neptune, TOI-700 c (R = 2.63 R⊕), will be an excellent target for JWST and future space-based observatories. TESS is scheduled to once again observe the Southern Hemisphere, and it will monitor TOI-700 for an additional 11 sectors in its extended mission. These observations should allow further constraints on the known planet parameters and searches for additional planets and transit timing variations in the system