Lineage-specific intolerance to oncogenic drivers restricts histological transformation.

Lung adenocarcinoma (LUAD) and small cell lung cancer (SCLC) are thought to originate from different epithelial cell types in the lung. Intriguingly, LUAD can histologically transform into SCLC after treatment with targeted therapies. In this study, we designed models to follow the conversion of LUAD to SCLC and found that the barrier to histological transformation converges on tolerance to Myc, which we implicate as a lineage-specific driver of the pulmonary neuroendocrine cell. Histological transformations are frequently accompanied by activation of the Akt pathway. Manipulating this pathway permitted tolerance to Myc as an oncogenic driver, producing rare, stem-like cells that transcriptionally resemble the pulmonary basal lineage. These findings suggest that histological transformation may require the plasticity inherent to the basal stem cell, enabling tolerance to previously incompatible oncogenic driver programs.

Application of the Key Characteristics of Carcinogens to Bisphenol A.

The ten key characteristics (KCs) of carcinogens are based on characteristics of known human carcinogens and encompass many types of endpoints. We propose that an objective review of the large amount of cancer mechanistic evidence for the chemical bisphenol A (BPA) can be achieved through use of these KCs. A search on metabolic and mechanistic data relevant to the carcinogenicity of BPA was conducted and web-based software tools were used to screen and organize the results. We applied the KCs to systematically identify, organize, and summarize mechanistic information for BPA, and to bring relevant carcinogenic mechanisms into focus. For some KCs with very large data sets, we utilized reviews focused on specific endpoints. Over 3000 studies for BPA from various data streams (exposed humans, animals, in vitro and cell-free systems) were identified. Mechanistic data relevant to each of the ten KCs were identified, with receptor-mediated effects, epigenetic alterations, oxidative stress, and cell proliferation being especially data rich. Reactive and bioactive metabolites are also associated with a number of KCs. This review demonstrates how the KCs can be applied to evaluate mechanistic data, especially for data-rich chemicals. While individual entities may have different approaches for the incorporation of mechanistic data in cancer hazard identification, the KCs provide a practical framework for conducting an objective examination of the available mechanistic data without a priori assumptions on mode of action. This analysis of the mechanistic data available for BPA suggests multiple and inter-connected mechanisms through which this chemical can act.

LKB1 suppresses growth and promotes the internalization of EGFR through the PIKFYVE lipid kinase.

The tumor suppressor LKB1 is a serine/threonine protein kinase that is frequently mutated in human lung adenocarcinoma (LUAD). LKB1 regulates a complex signaling network that is known to control cell polarity and metabolism; however, the pathways that mediate the tumor suppressive activity of LKB1 are incompletely defined. To identify mechanisms of LKB1- mediated growth suppression we developed a spheroid-based cell culture assay to study LKB1- dependent growth. Using this assay, along with genome-wide CRISPR screens and validation with orthogonal methods, we discovered that LKB1 suppresses growth, in part, by activating the PIKFYVE lipid kinase, which promotes the internalization of wild-type EGFR. Our findings reveal a new mechanism of regulation of EGFR, which may have implications for the treatment of LKB1 -mutant LUAD.

Early Financial Impact of the COVID-19 Pandemic on U.S. Hospitals.

GOAL: The COVID-19 pandemic has left a significant impact on hospitals' operations, expenses, and revenues. However, little is known about the pandemic's financial impact on rural and urban hospitals. Our main objective was to analyze how hospital profitability changed during the first year of the pandemic. We specifically studied the association between COVID-19 infections and hospitalizations and county-level variables with operating margins (OMs) and total margins (TMs). METHODS: We obtained data from Medicare Cost Reports, the American Hospital Association Annual Survey Database, and the Centers for Disease Control and Prevention/Agency for Toxic Substances and Disease Registry (CDC/ATSDR) for 2012-2020. Our final dataset consisted of an unbalanced panel with 17,510 observations for urban hospitals and 17,876 observations for rural hospitals. We estimated separate hospital fixed-effects models for urban and rural hospitals' OMs and TMs. The fixed-effects models controlled for time-invariant differences across hospitals. PRINCIPAL FINDINGS: In our review of the early impact of the COVID-19 pandemic on rural and urban hospitals' profits as well as trends in OMs and TMs from 2012 to 2020, we found that OMs were inversely related to the duration of hospitals' exposure to infections in urban and rural locations. In contrast, TMs and hospitals' exposures had a positive relationship. Government relief funds, a source of nonoperating revenue, apparently allowed most hospitals to avoid financial distress from the pandemic. We also found a positive relationship between the magnitude of weekly adult hospitalizations and OMs in urban and rural hospitals. Size, participation in group purchasing organizations (GPOs), and occupancy rates were positively related to OMs, with size and participation in GPOs relating to scale economies and occupancy rates reflecting capital efficiencies. PRACTICAL APPLICATIONS: Hospitals' OMs have been declining since 2014. The pandemic made this decline worse, especially for rural hospitals. Federal relief funds, along with investment income, helped hospitals remain financially solvent during the pandemic. However, investment income and temporary federal aid are insufficient to sustain financial well-being. Executives need to explore cost-saving opportunities such as joining a GPO. Small rural hospitals with low occupancy and low community COVID-19 hospitalization rates have been particularly vulnerable to the financial impact of the pandemic. Although federal relief funds have limited hospital financial distress induced by the pandemic, we maintain that the funds should have been more effectively targeted, as the mean TM increased to its highest level in a decade. The disparate results of our analysis of OMs and TMs illustrate the utility of using multiple measures of profitability.

Were hospitals with sustained high performance more successful at reducing mortality during the pandemic's second wave?

BACKGROUND: In 2019, the COVID-19 pandemic emerged. Variation in COVID-19 patient outcomes between hospitals was later reported. PURPOSE: This study aims to determine whether sustainers-hospitals with sustained high performance on Hospital Value-Based Purchasing Total Performance Score (HVBP-TPS)-more effectively responded to the pandemic and therefore had better patient outcomes. METHODOLOGY: We calculated hospital-specific risk-standardized event rates using deidentified patient-level data from the UnitedHealth Group Clinical Discovery Database. HVBP-TPS from 2016 to 2019 were obtained from Centers for Medicare & Medicaid Services. Hospital characteristics were obtained from the American Hospital Association Annual Survey Database (2019), and county-level predictors were obtained from the Area Health Resource File. We use a repeated-measures regression model assuming an AR(1) type correlation structure to test whether sustainers had lower mortality rates than nonsustainers during the first wave (spring 2020) and the second wave (October to December 2020) of the pandemic. RESULTS: Sustainers did not have significantly lower COVID-19 mortality rates during the first wave of the pandemic, but they had lower COVID-19 mortality rates during the second wave compared to nonsustainers. Larger hospitals, teaching hospitals, and hospitals with higher occupancy rates had higher mortality rates. CONCLUSION: During the first wave of the pandemic, mortality rates did not differ between sustainers and nonsustainers. However, sustainers had lower mortality rates than nonsustainers in the second wave, most likely because of their knowledge management capabilities and existing structures and resources that enable them to develop new processes and routines to care for patients in times of crisis. Therefore, a consistently high level of performance over the years on HVBP-TPS is associated with high levels of performance on COVID-19 patient outcomes. PRACTICE IMPLICATIONS: Investing in identifying the knowledge, processes, and resources that foster the dynamic capabilities needed to achieve superior performance in HVBP might enable hospitals to utilize these capabilities to adapt more effectively to future changes and uncertainty.

Is there an association between hospital staffing levels and inpatient-COVID-19 mortality rates?

OBJECTIVE: This study aims to investigate the relationship between RNs and hospital-based medical specialties staffing levels with inpatient COVID-19 mortality rates. METHODS: We relied on data from AHA Annual Survey Database, Area Health Resource File, and UnitedHealth Group Clinical Discovery Database. In phase 1 of the analysis, we estimated the risk-standardized event rates (RSERs) based on 95,915 patients in the UnitedHealth Group Database 1,398 hospitals. We then used beta regression to analyze the association between hospital- and county- level factors with risk-standardized inpatient COVID-19 mortality rates from March 1, 2020, through December 31, 2020. RESULTS: Higher staffing levels of RNs and emergency medicine physicians were associated with lower COVID-19 mortality rates. Moreover, larger teaching hospitals located in urban settings had higher COVID-19 mortality rates. Finally, counties with greater social vulnerability, specifically in terms of housing type and transportation, and those with high infection rates had the worst patient mortality rates. CONCLUSION: Higher staffing levels are associated with lower inpatient mortality rates for COVID-19 patients. More research is needed to determine appropriate staffing levels and how staffing levels interact with other factors such as teams, leadership, and culture to impact patient care during pandemics.

The interaction between high-level electronic medical record adoption and hospitalist staffing levels: A focus on value-based purchasing.

OBJECTIVE: This study sought to understand the relationship of hospital performance with high-level electronic medical record (EMR) adoption, hospitalists staffing levels, and their potential interaction. MATERIALS AND METHODS: We evaluated 2,699 non-federal, general acute hospitals using 2016 data merged from four data sources. We performed ordinal logistic regression of hospitals' total performance score (TPS) on their EMR capability and hospitalists staffing level while controlling for other market- and individual-level characteristics. RESULTS: Hospitalists staffing level is shown to be positively correlated with TPS. High-level EMR adoption is associated with both short-term and long-term improvement on TPS. Large, urban, non-federal government hospitals, and academic medical centers tend to have lower TPS compared to their respective counterparts. Hospitals belonging to medium- or large-sized healthcare systems have lower TPS. Higher registered nurse (RN) staffing level is associated with higher TPS, while higher percentage of Medicare or Medicaid share of inpatient days is associated with lower TPS. DISCUSSION: Although the main effects of hospitalists staffing level and EMR capability are significant, their interaction is not, suggesting that hospitalists and EMR act through separate mechanisms to help hospitals achieve better performance. When hospitals are not able to invest on both simultaneously, given financial constraints, they can still reap the full benefits from each. CONCLUSION: Hospitalists staffing level and EMR capability are both positively correlated with hospitals' TPS, and they act independently to bolster hospital performance.

Estimated Cancer Risks Associated with Nitrosamine Contamination in Commonly Used Medications.

Many nitrosamines are potent carcinogens, with more than 30 listed under California's Proposition 65. Recently, nitrosamine contamination of commonly used drugs for treatment of hypertension, heartburn, and type 2 diabetes has prompted numerous Food and Drug Administration (FDA) recalls in the US. These contaminants include the carcinogens NDMA (N-nitrosodimethylamine) and NDEA (N-nitrosodiethylamine) and the animal tumorigen NMBA (N-nitroso-N-methyl-4-aminobutyric acid). NMBA and NDEA are metabolically and/or structurally related to NDMA, an N-nitrosomethyl-n-alkylamine (NMA), and 12 other carcinogenic NMAs. These nitrosamines exhibit common genotoxic and tumorigenic activities, with shared target tumor sites amongst chemicals and within a given laboratory animal species. We use the drug valsartan as a case study to estimate the additional cancer risks associated with NDMA and NDEA contamination, based on nitrosamine levels reported by the US FDA, cancer potencies developed by California's Proposition 65 program and the US Environmental Protection Agency (EPA), and specific exposure scenarios. These estimates suggest that nitrosamine contamination in drugs that are used long-term can increase cancer risks and pose a serious concern to public health.

Sustainers: Hospitals with sustained superior performance.

PURPOSE: The purpose of this article was to investigate the organizational and market-level variables associated with sustained superior hospital performance on Value-Based Purchasing total performance scores (TPS). METHODOLOGY: TPS for 2014 through 2017 was obtained from the Centers for Medicare & Medicaid Services Hospital Compare website. Market-level data were from the 2017 Area Health Resource File, and hospital-level data were from the 2014 American Hospital Association Annual Survey database. We specified a logistic regression model to identify significant predictors of hospitals with sustained superior performance on TPS, that is, "sustainers." PRINCIPAL FINDINGS: Only 8.4% of hospitals were classified as sustainers. Hospitals located in rural markets with a high Medicare Advantage penetration had a higher likelihood of being classified as sustainers. High RN staffing levels, lower Medicare share of inpatient days, not-for-profit ownership, and small size were all significant organizational predictors of sustained superior performance. CONCLUSIONS: Both modifiable characteristics, such as nurse staffing levels, and nonmodifiable characteristics, such as rural markets and small hospital size, are associated with the likelihood of hospitals sustaining superior performance over time. PRACTICE IMPLICATIONS: Managers need to carefully examine their staffing levels as they pursue interventions to sustain high TPS overtime. Moreover, factors such as Medicare share of inpatient days and size need to be considered when understanding barriers to sustained performance on Value-Based Purchasing domains.

Reflective and Reflexive Stress Responses of Older Adults to Three Gaming Experiences In Relation to Their Cognitive Abilities: Mixed Methods Crossover Study.

BACKGROUND: The gamification of digital health provisions for older adults (eg, for rehabilitation) is a growing trend; however, many older adults are not familiar with digital games. This lack of experience could cause stress and thus impede participants' motivations to adopt these technologies. OBJECTIVE: This crossover longitudinal multifactorial study aimed to examine the interactions between game difficulty, appraisal, cognitive ability, and physiological and cognitive responses that indicate game stress using the Affective Game Planning for Health Applications framework. METHODS: A total of 18 volunteers (mean age 71 years, SD 4.5; 12 women) completed a three-session study to evaluate different genres of games in increasing order of difficulty (S1-BrainGame, S2-CarRace, and S3-Exergame). Each session included an identical sequence of activities (t1-Baseline, t2-Picture encode, t3-Play, t4-Stroop test, t5-Play, and t6-Picture recall), a repeated sampling of salivary cortisol, and time-tagged ambulatory data from a wrist-worn device. Generalized estimating equations were used to investigate the effect of session×activity or session×activity×cognitive ability on physiology and cognitive performance. Scores derived from the Montreal Cognitive Assessment (MoCA) test were used to define cognitive ability (MoCA-high: MoCA>27, n=11/18). Kruskal-Wallis tests were used to test session or session×group effects on the scores of the postgame appraisal questionnaire. RESULTS: Session×activity effects were significant on all ambulatory measures (χ210>20; P<.001) other than cortisol (P=.37). Compared with S1 and S2, S3 was associated with approximately 10 bpm higher heart rate (P<.001) and approximately 5 muS higher electrodermal activity (P<.001), which were both independent of the movement caused by the exergame. Compared with S1, we measured a moderate but statistically significant drop in the rate of hits in immediate recall and rate of delayed recall in S3. The low-MoCA group did not differ from the high-MoCA group in general characteristics (age, general self-efficacy, and perceived stress) but was more likely to agree with statements such as digital games are too hard to learn. In addition, the low-MoCA group was more likely to dislike the gaming experience and find it useless, uninteresting, and visually more intense (χ21>4; P<.04). Group differences in ambulatory signals did not reach statistical significance; however, the rate of cortisol decline with respect to the baseline was significantly larger in the low-MoCA group. CONCLUSIONS: Our results show that the experience of playing digital games was not stressful for our participants. Comparatively, the neurophysiological effects of exergame were more pronounced in the low-MoCA group, suggesting greater potential of this genre of games for cognitive and physical stimulation by gamified interventions; however, the need for enjoyment of this type of challenging game must be addressed.

Hospitalists staffing levels and hospital performance.

OBJECTIVE (OR STUDY QUESTION): To examine the association between hospitalists staffing levels and contract type with CMS Total Performance Score (TPS). DATA SOURCES/STUDY SETTING: Total performance scores were obtained from CMS, hospital-level data from the 2015 American Hospital Association Annual Survey Database, and unemployment rates from the Area Resource Health File. STUDY DESIGN: We used cluster analysis to classify hospitals based on the distribution of various hospitalist contracts, and we used regression analysis to examine the association between TPS and hospitalist staffing levels and contract distributions. Hospital-level predictors included hospitalists staffing levels, RN staffing levels, and Magnet status. Market-level variables were unemployment rates and competition. PRINCIPAL FINDINGS: Higher staffing levels of employed hospitalists or hospitalists with a group contract are associated with higher TPS (with coefficient estimates of 0.85 and 0.83, respectively, and the same standard error of 0.22). Higher staffing levels of hospitalists under individual contract are negatively associated with TPS (with coefficient estimate of -0.43 and standard error of 0.21). Based on the regression analysis using hospital clusters as independent variables, hospitals with individual contracts or without hospitalists providing care had significantly worse TPS compared to hospitals that predominantly employ hospitalists (with coefficient estimate of -1.80 and standard error of 0.61). Magnet status, RN staffing levels, and small and medium size were positively associated with TPS. Medicare share of inpatient days, teaching status, AMCs, and for-profit and public nonfederal ownership were negatively associated with TPS. CONCLUSIONS: Adequate hospitalist staffing level is important for hospitals to achieve better performance. Hospitals need to consider the mix of arrangements or contracts that they have with hospitalists.

Cancer Hazard Identification Integrating Human Variability: The Case of Coumarin.

Coumarin is a naturally occurring sweet-smelling benzopyrone that may be extracted from plants or synthesized for commercial uses. Its uses include as a flavoring agent, fragrance enhancer, and odor-masking additive. We reviewed and evaluated the scientific evidence on the carcinogenicity of coumarin, integrating information from carcinogenicity studies in animals with mechanistic and other relevant data, including data from toxicogenomic, genotoxicity, and metabolism studies, and studies of human variability of a key enzyme, CYP2A6. Increases in tumors were observed in multiple studies in rats and mice in multiple tissues. Our functional pathway analysis identified several common cancer-related biological processes/pathways affected by coumarin in rat liver following in vivo exposure and in human primary hepatocytes exposed in vitro. When coumarin 7-hydroxylation by CYP2A6 is compromised, this can lead to a shift in metabolism to the 3,4-epoxidation pathway and increased generation of electrophilic metabolites. Mechanistic data align with 3 key characteristics of carcinogens, namely formation of electrophilic metabolites, genotoxicity, and induction of oxidative stress. Considerations of metabolism, human variability in CYP2A6 activity, and coumarin hepatotoxicity in susceptible individuals provide additional support for carcinogenicity concern. Our analysis illustrates the importance of integrating information on human variability in the cancer hazard identification process.

On the unsupervised analysis of domain-specific Chinese texts.

With the growing availability of digitized text data both publicly and privately, there is a great need for effective computational tools to automatically extract information from texts. Because the Chinese language differs most significantly from alphabet-based languages in not specifying word boundaries, most existing Chinese text-mining methods require a prespecified vocabulary and/or a large relevant training corpus, which may not be available in some applications. We introduce an unsupervised method, top-down word discovery and segmentation (TopWORDS), for simultaneously discovering and segmenting words and phrases from large volumes of unstructured Chinese texts, and propose ways to order discovered words and conduct higher-level context analyses. TopWORDS is particularly useful for mining online and domain-specific texts where the underlying vocabulary is unknown or the texts of interest differ significantly from available training corpora. When outputs from TopWORDS are fed into context analysis tools such as topic modeling, word embedding, and association pattern finding, the results are as good as or better than that from using outputs of a supervised segmentation method.