Gene Signatures and Oncology Treatment Implications.

Gene expression signatures (GES) are a powerful tool in oncology used for classification, prognostication, and therapeutic response prediction of malignancies. In this article, we review the disease site guidelines by the National Comprehensive Cancer Network that use GES for treatment planning and clinical use. We identified 4 cancer types for which treatment decisions are frequently influenced by GES.

Cell-Cell Fusion in NSCLC Confers a Fitness Benefit Under Drug Selection.

Cell-cell fusion has been implicated in various physiological and pathological processes, including cancer progression. This study investigated the role of cell-cell fusion in non-small cell lung cancer (NSCLC), focusing on its contribution to chemoresistance and tumor evolution. By co-culturing drug-sensitive and drug-resistant NSCLC cell lines, we observed spontaneous cell-cell fusion events, particularly under gefitinib selection.

Cell-cell fusion in cancer: The next cancer hallmark?

In this review, we consider the role of cell-cell fusion in cancer development and progression through an evolutionary lens. We begin by summarizing the origins of fusion proteins (fusogens), of which there are many distinct classes that have evolved through convergent evolution. We then use an evolutionary framework to highlight how the persistence of fusion over generations and across different organisms can be attributed to traits that increase fitness secondary to fusion; these traits map well to the expanded hallmarks of cancer.

Reinforcement learning informs optimal treatment strategies to limit antibiotic resistance.

Antimicrobial resistance was estimated to be associated with 4.95 million deaths worldwide in 2019. It is possible to frame the antimicrobial resistance problem as a feedback-control problem.

Factors Associated With Food Insecurity Among a Community-Based Sample of Older Adults in a North Florida County.

Food insecurity impacts the lives of 7.6 million U.S.

Evolution-Informed Strategies for Combating Drug Resistance in Cancer.

The ever-changing nature of cancer poses the most difficult challenge oncologists face today. Cancer's remarkable adaptability has inspired many to work toward understanding the evolutionary dynamics that underlie this disease in hopes of learning new ways to fight it. Eco-evolutionary dynamics of a tumor are not accounted for in most standard treatment regimens, but exploiting them would help us combat treatment-resistant effectively.

Crosstalkr: An open-source R package to facilitate drug target identification.

In the last few decades, interest in graph-based analysis of biological networks has grown substantially. Protein-protein interaction networks are one of the most common biological networks, and represent the molecular relationships between every known protein and every other known protein. Integration of these interactomic data into bioinformatic pipelines may increase the translational potential of discoveries made through analysis of multi-omic datasets.

Reinforcement Learning informs optimal treatment strategies to limit antibiotic resistance.

Antimicrobial resistance was estimated to be associated with 4.95 million deaths worldwide in 2019. It is possible to frame the antimicrobial resistance problem as a feedback-control problem.

Network potential identifies therapeutic miRNA cocktails in Ewing sarcoma.

MicroRNA (miRNA)-based therapies are an emerging class of targeted therapeutics with many potential applications. Ewing Sarcoma patients could benefit dramatically from personalized miRNA therapy due to inter-patient heterogeneity and a lack of druggable (to this point) targets. However, because of the broad effects miRNAs may have on different cells and tissues, trials of miRNA therapies have struggled due to severe toxicity and unanticipated immune response.

Public health utility of cause of death data: applying empirical algorithms to improve data quality.

Background: Accurate, comprehensive, cause-specific mortality estimates are crucial for informing public health decision making worldwide. Incorrectly or vaguely assigned deaths, defined as garbage-coded deaths, mask the true cause distribution. The Global Burden of Disease (GBD) study has developed methods to create comparable, timely, cause-specific mortality estimates; an impactful data processing method is the reallocation of garbage-coded deaths to a plausible underlying cause of death.

Quantitative measurements of forward head in college-aged students: A conformational study of intra-rater and inter-rater reliability of a novel Posture Measuring Device.

Introduction: Medical professionals frequently encounter forward head postures (FHP) in the treatment of cervical spine pain. In the clinical setting, FHP measurements are often described subjectively using the phrase, "patient demonstrates forward head posture." There are reliable tools that can objectively measure FHP, but they are not frequently used in the clinical setting on a regular basis because the tools are unavailable, inconvenient or overly time-consuming.

UV-C tower for point-of-care decontamination of filtering facepiece respirators.

Background: Filtering facepiece respirators (FFR) are critical for protecting essential personnel and limiting the spread of disease. Due to the current COVID-19 pandemic, FFR supplies are dwindling in many health systems, necessitating re-use of potentially contaminated FFR. Multiple decontamination solutions have been developed to meet this pressing need, including systems designed for bulk decontamination of FFR using vaporous hydrogen peroxide or ultraviolet-C (UV-C) radiation.

Mapping 123 million neonatal, infant and child deaths between 2000 and 2017.

Since 2000, many countries have achieved considerable success in improving child survival, but localized progress remains unclear. To inform efforts towards United Nations Sustainable Development Goal 3.2-to end preventable child deaths by 2030-we need consistently estimated data at the subnational level regarding child mortality rates and trends.

Identifying residual hotspots and mapping lower respiratory infection morbidity and mortality in African children from 2000 to 2017.

Lower respiratory infections (LRIs) are the leading cause of death in children under the age of 5, despite the existence of vaccines against many of their aetiologies. Furthermore, more than half of these deaths occur in Africa. Geospatial models can provide highly detailed estimates of trends subnationally, at the level where implementation of health policies has the greatest impact.

Potential survival benefits from optimized chemotherapy implementation in advanced ovarian cancer: Projections from a microsimulation model.

Background: Ovarian cancer is often diagnosed in advanced stages, when survival is poor. Treatment advances have been made, but are inconsistently implemented. Our purpose was to project the maximum life expectancy gains that could be achieved in women with stage IIIC epithelial ovarian cancer if the implementation of available chemotherapy regimens could be optimized.

Mapping exclusive breastfeeding in Africa between 2000 and 2017.

Exclusive breastfeeding (EBF)-giving infants only breast-milk (and medications, oral rehydration salts and vitamins as needed) with no additional food or drink for their first six months of life-is one of the most effective strategies for preventing child mortality. Despite these advantages, only 37% of infants under 6 months of age in Africa were exclusively breastfed in 2017, and the practice of EBF varies by population. Here, we present a fine-scale geospatial analysis of EBF prevalence and trends in 49 African countries from 2000-2017, providing policy-relevant administrative- and national-level estimates.

The current and future global distribution and population at risk of dengue.

Dengue is a mosquito-borne viral infection that has spread throughout the tropical world over the past 60 years and now affects over half the world's population. The geographical range of dengue is expected to further expand due to ongoing global phenomena including climate change and urbanization. We applied statistical mapping techniques to the most extensive database of case locations to date to predict global environmental suitability for the virus as of 2015.

Mapping HIV prevalence in sub-Saharan Africa between 2000 and 2017.

HIV/AIDS is a leading cause of disease burden in sub-Saharan Africa. Existing evidence has demonstrated that there is substantial local variation in the prevalence of HIV; however, subnational variation has not been investigated at a high spatial resolution across the continent. Here we explore within-country variation at a 5 × 5-km resolution in sub-Saharan Africa by estimating the prevalence of HIV among adults (aged 15-49 years) and the corresponding number of people living with HIV from 2000 to 2017.

Past and future spread of the arbovirus vectors Aedes aegypti and Aedes albopictus.

The global population at risk from mosquito-borne diseases-including dengue, yellow fever, chikungunya and Zika-is expanding in concert with changes in the distribution of two key vectors: Aedes aegypti and Aedes albopictus. The distribution of these species is largely driven by both human movement and the presence of suitable climate. Using statistical mapping techniques, we show that human movement patterns explain the spread of both species in Europe and the United States following their introduction.

Prevention of Prescription Opioid Misuse and Projected Overdose Deaths in the United States.

Importance: Deaths due to opioid overdose have tripled in the last decade. Efforts to curb this trend have focused on restricting the prescription opioid supply; however, the near-term effects of such efforts are unknown.

Objective: To project effects of interventions to lower prescription opioid misuse on opioid overdose deaths from 2016 to 2025.

Testing for Verification Bias in Reported Malignancy Risks for Side-Branch Intraductal Papillary Mucinous Neoplasms: A Simulation Modeling Approach.

Objective: The objective of our study was to test for the possibility that published malignancy risks for side-branch intraductal papillary mucinous neoplasms (IPMNs) are overestimates, likely due to verification bias.

Materials And Methods: We tested for possible verification bias using simulation modeling techniques. First, in age-defined hypothetical cohorts of 10 million persons, we projected the frequency of pancreatic ductal adenocarcinoma (PDAC) arising from side-branch IPMNs over 5 years using published estimates of their prevalence (4.

Effect of PD-L1 testing on the cost-effectiveness and budget impact of pembrolizumab for advanced urothelial carcinoma of the bladder in the United States.

Purpose: Our purpose was to evaluate the effect of PD-L1 testing on the cost-effectiveness of pembrolizumab for second-line treatment of advanced urothelial carcinoma in the bladder from the U.S. societal perspective.

Progression to pancreatic ductal adenocarcinoma from pancreatic intraepithelial neoplasia: Results of a simulation model.

Objectives: To gain insight into the natural history and carcinogenesis pathway of Pancreatic Intraepithelial Neoplasia (PanIN) lesions by building a calibrated simulation model of PanIN progression to pancreatic ductal adenocarcinoma (PDAC) METHODS: We revised a previously validated simulation model of solid PDAC, calibrating the model to fit data from the National Cancer Institute's Surveillance, Epidemiology, and End Results program and published literature on PanIN prevalence by age. We estimated the likelihood of progression from PanIN states (1, 2, and 3) to PDAC and the time between PanIN onset and PDAC (dwell time). We evaluated a hypothetical intervention to test for and treat PanIN 3 lesions to estimate the potential benefits from PanIN detection.