GPU-Accelerated RSF Level Set Evolution for Large-Scale Microvascular Segmentation.

Microvascular networks are challenging to model because these structures are currently near the diffraction limit for most advanced three-dimensional imaging modalities, including confocal and light sheet microscopy. This makes semantic segmentation difficult, because individual components of these networks fluctuate within the confines of individual pixels. Level set methods are ideally suited to solve this problem by providing surface and topological constraints on the resulting model, however these active contour techniques are extremely time intensive and impractical for terabyte-scale images.

Geographic Origin may Affect Outcomes for Hispanic Patients with Non-Small Cell Lung Cancer in the United States.

Background: Social determinants of health thoroughly explored in the literature include insurance status, race, and ethnicity. There are over 50 million self-identifying Hispanics in the United States. This, however, represents a heterogeneous population.

Sotorasib as First-Line Treatment for Advanced KRAS G12C-Mutated Non-Small Cell Lung Carcinoma: A Case Report.

Mutations in the gene are the most common gain-of-function mutations found in lung adenocarcinomas. The most common mutation, KRAS G12C, is present in 13% of lung adenocarcinomas. Sotorasib (AMG-510) is an irreversible small molecule inhibitor targeting KRAS G12C.

Social disparities in pain management provision in stage IV lung cancer: A national registry analysis.

A strong association exists between pain and lung cancer (LC). Focusing on the disparities in pain referral in LC patients, we are aiming to characterize the prevalence and patterns of referrals to pain management (PM) in Stage IV non-small-cell LC (NSLC) and small-cell LC (SCLC). We sampled the National Cancer Database for de novo stage IV LC (2004-2016).

Analysis of the first genetic engineering attribution challenge.

The ability to identify the designer of engineered biological sequences-termed genetic engineering attribution (GEA)-would help ensure due credit for biotechnological innovation, while holding designers accountable to the communities they affect. Here, we present the results of the first Genetic Engineering Attribution Challenge, a public data-science competition to advance GEA techniques. Top-scoring teams dramatically outperformed previous models at identifying the true lab-of-origin of engineered plasmid sequences, including an increase in top-1 and top-10 accuracy of 10 percentage points.

Insidious Insights: Implications of viral vector engineering for pathogen enhancement.

Optimizing viral vectors and their properties will be important for improving the effectiveness and safety of clinical gene therapy. However, such research may generate dual-use insights relevant to the enhancement of pandemic pathogens. In particular, reliable and generalizable methods of immune evasion could increase viral fitness sufficient to cause a new pandemic.

Meta-Analysis of Survival and Development of a Prognostic Nomogram for Malignant Pleural Mesothelioma Treated with Systemic Chemotherapy.

(1) Purpose: Malignant pleural mesothelioma (MPM) is a rare cancer with an aggressive course. For patients who are medically inoperable or surgically unresectable, multi-agent systemic chemotherapy remains an accepted standard-of-care. The purpose of this meta-analysis is to provide baseline summative survival estimates as well as evaluate the influence of prognostic variables to provide comparative estimates for future trial designs.

Low-N protein engineering with data-efficient deep learning.

Protein engineering has enormous academic and industrial potential. However, it is limited by the lack of experimental assays that are consistent with the design goal and sufficiently high throughput to find rare, enhanced variants. Here we introduce a machine learning-guided paradigm that can use as few as 24 functionally assayed mutant sequences to build an accurate virtual fitness landscape and screen ten million sequences via in silico directed evolution.

Effect of immunotherapy on overall survival in limited-stage small cell lung carcinoma: a national cancer database analysis.

Background: While immune-based therapies have been approved for extensive-stage small cell lung cancer, there is limited data on the efficacy of immunotherapy in patients with limited-stage disease.

Methods: We used the National Cancer Database to first evaluate factors associated with the inclusion of immunotherapy as part of the initial therapeutic course in patients diagnosed with limited-stage small cell lung cancer (LS-SCLC). Consequently, we evaluated the impact of this immunotherapy on 2-year and 5-year overall survival (OS).

Phase 1 cohort expansion study of LY3023414, a dual PI3K/mTOR inhibitor, in patients with advanced mesothelioma.

BACKGROUND LY3023414 is a selective, ATP competitive inhibitor of class I PI3K isoforms, mTORC1/2 and DNA-PK. A Phase 1 dose escalation, 200 mg twice daily (BID) of LY3023414 was the determined recommended phase 2 dose (RP2D). We report the antitumor activity and safety of LY3023414 monotherapy in patients with advanced mesothelioma.

Serum soluble mesothelin-related protein (SMRP) and fibulin-3 levels correlate with baseline malignant pleural mesothelioma (MPM) tumor volumes but are not useful as biomarkers of response in an immunotherapy trial.

Objectives: Soluble mesothelin-related protein (SMRP) and fibulin-3 serum levels may serve as diagnostic and prognostic biomarkers of malignant pleural mesothelioma (MPM). Here, we evaluate these markers for correlation to tumor volume, prognosis and response assessment in a clinical trial of immunogene therapy in combination with chemotherapy.

Materials And Methods: Serial serum levels of SMRP and fibulin-3 were measured in adult patients with biopsy-proven MPM enrolled in two prospective clinical trials.

Bidirectional contact tracing could dramatically improve COVID-19 control.

Contact tracing is critical to controlling COVID-19, but most protocols only "forward-trace" to notify people who were recently exposed. Using a stochastic branching-process model, we find that "bidirectional" tracing to identify infector individuals and their other infectees robustly improves outbreak control. In our model, bidirectional tracing more than doubles the reduction in effective reproduction number (R) achieved by forward-tracing alone, while dramatically increasing resilience to low case ascertainment and test sensitivity.

The biosecurity benefits of genetic engineering attribution.

Biology can be misused, and the risk of this causing widespread harm increases in step with the rapid march of technological progress. A key security challenge involves attribution: determining, in the wake of a human-caused biological event, who was responsible. Recent scientific developments have demonstrated a capability for detecting whether an organism involved in such an event has been genetically modified and, if modified, to infer from its genetic sequence its likely lab of origin.

A machine learning toolkit for genetic engineering attribution to facilitate biosecurity.

The promise of biotechnology is tempered by its potential for accidental or deliberate misuse. Reliably identifying telltale signatures characteristic to different genetic designers, termed 'genetic engineering attribution', would deter misuse, yet is still considered unsolved. Here, we show that recurrent neural networks trained on DNA motifs and basic phenotype data can reach 70% attribution accuracy in distinguishing between over 1,300 labs.

Delayed-Phase Enhancement for Evaluation of Malignant Pleural Mesothelioma on Computed Tomography: A Prospective Cohort Study.

Background: Radiologic assessment of malignant pleural mesothelioma (MPM) on computed tomography (CT) imaging can be limited by similar attenuations of MPM and adjacent tissues. This can result in inaccuracies in defining the presence and extent of pleural tumor burden. We hypothesized that increasing the time delay for pleural enhancement will optimize discrimination between MPM and noncancerous tissues on CT.

Practical and cost-effective model to build and sustain a cardio-oncology program.

Background: Cardio-Oncology (CO) is a new subspecialty that thrives mostly in large academic quaternary centers. This study describes how to establish a successful cardio-oncology program, with limited resources, in order to effectively manage the unique care required by this patient population.

Methods: Clinical data was collected from 25 consecutive months.

Checkpoint inhibitor-induced myocarditis and myasthenia gravis in a recurrent/metastatic thymic carcinoma patient: a case report.

Background: Pembrolizumab, an immune checkpoint inhibitor (ICI), is an IgG4 antibody that blocks interaction between programmed cell death protein 1 and programmed death-ligand 1. Myocarditis, an immune-related adverse event, has been reported in thymic epithelial tumours. Pembrolizumab has also been associated with development/exacerbation of myasthenia gravis (MG).

A Multimodal Approach to Evaluate for Cardiac Metastasis in a Case of Non-Small Cell Lung Cancer.

Malignancies have demonstrated the ability to metastasize to cardiac tissue. However, an optimal diagnostic algorithm for cardiac tumors has not yet been established, due at least in part to the scarcity of symptomatic cases. Several case reports describe how the usage of F-labeled fluorodeoxyglucose positron emission tomography (F-FDG PET) incidentally revealed cardiac neoplasia.

Unified rational protein engineering with sequence-based deep representation learning.

Rational protein engineering requires a holistic understanding of protein function. Here, we apply deep learning to unlabeled amino-acid sequences to distill the fundamental features of a protein into a statistical representation that is semantically rich and structurally, evolutionarily and biophysically grounded. We show that the simplest models built on top of this unified representation (UniRep) are broadly applicable and generalize to unseen regions of sequence space.

Impact of and Co-Mutations on Outcomes After First-Line Systemic Therapy Among Patients With -Mutated Advanced Non-Small-Cell Lung Cancer.

Purpose: The gene encodes a serine/threonine protein kinase that regulates cell polarity and functions as a tumor suppressor. Patients with non-small-cell lung cancer (NSCLC) and mutations often have other co-mutations. We evaluated the impact of and co-mutations on outcomes after first-line systemic therapy for patients with metastatic or recurrent NSCLC that harbors mutations.

Pembrolizumab After Completion of Locally Ablative Therapy for Oligometastatic Non-Small Cell Lung Cancer: A Phase 2 Trial.

Importance: Patients with oligometastatic non-small cell lung cancer (NSCLC) may benefit from locally ablative therapy (LAT) such as surgery or stereotactic radiotherapy. Prior studies were conducted before the advent of immunotherapy, and a strong biological rationale for the use of immunotherapy exists in a minimal residual disease state.

Objective: To evaluate whether the addition of pembrolizumab after LAT improves outcomes for patients with oligometastatic NSCLC.