An update and review of arthropod vector sensory systems: Potential targets for behavioural manipulation by parasites and other disease agents.

For over a century, vector ecology has been a mainstay of vector-borne disease control. Much of this research has focused on the sensory ecology of blood-feeding arthropods (black flies, mosquitoes, ticks, etc.) with terrestrial vertebrate hosts. Of particular interest are the cues and sensory systems that drive host seeking and host feeding behaviours as they are critical for a vector to locate and feed from a host. An important yet overlooked component of arthropod vector ecology are the phenotypic changes observed in infected vectors that increase disease transmission. While our fundamental understanding of sensory mechanisms in disease vectors has drastically increased due to recent advances in genome engineering, for example, the advent of CRISPR-Cas9, and high-throughput "big data" approaches (genomics, proteomics, transcriptomics, etc.), we still do not know if and how parasites manipulate vector behaviour. Here, we review the latest research on arthropod vector sensory systems and propose key mechanisms that disease agents may alter to increase transmission.

Comparison of Care Quality Metrics in 2-Sided Risk Medicare Advantage vs Fee-for-Service Medicare Programs.

Importance: Medicare Advantage is associated with improved health outcomes, increased care efficiency, and lower out-of-pocket costs compared with fee-for-service (FFS) Medicare. When engaged in 2-sided risk arrangements, physicians are incented to offer high value for patients; however, no studies have explored the quality and efficiency outcomes in 2-sided risk Medicare Advantage models compared with FFS Medicare. Objective: To compare quality and efficiency of care between physicians using a Medicare Advantage 2-sided risk model and FFS Medicare. Design, Setting, and Participants: This retrospective cohort analysis with exact and propensity score-matched design used claims data from January 1, 2018, to December 31, 2019. Participants included beneficiaries enrolled in a Medicare Advantage 2-sided risk model (ie, physicians assumed the financial risk of total costs of care) and those in an FFS Medicare program in a 5% limited data set with part A and B coverage residing in 6 states (Arizona, California, Florida, Nevada, Texas, and Utah). Data were analyzed from February 1 to June 15, 2022. Exposures: Medicare Advantage 2-sided risk model seen in practices that are part of a nationwide health care delivery organization compared with traditional FFS Medicare. Main Outcomes and Measures: Comparative analysis of 8 quality and efficiency metrics in populations enrolled in a 2-sided risk-model Medicare Advantage program and 5% FFS Medicare. Results: In this analytic cohort of 316 312 individuals (158 156 in each group), 46.11% were men and 53.89% were women; 32.72% were aged 65-69 years, 29.44% were aged 70-74 years, 19.05% were aged 75-79 years, 10.84% were aged 80-85 years, and 7.95% were 85 years or older. The Medicare Advantage model was associated with care of higher quality and efficiency in all 8 metrics compared with the FFS model. This included lower odds of inpatient admission (-18%; odds ratio [OR], 0.82 [95% CI, 0.79-0.84]), inpatient admission through the emergency department (ED) (-6%; OR, 0.94 [95% CI, 0.91-0.97]), ED visits (-11%; OR, 0.89 [95% CI, 0.86-0.91]), avoidable ED visits (-14%; OR, 0.86 [95% CI, 0.82-0.89]), 30-day inpatient readmission (-9%; rate ratio, 0.91 [95% CI, 0.86-0.98]), admission for stroke or myocardial infarction (-10%; OR, 0.90 [95% CI, 0.83-0.98]), and hospitalization for chronic obstructive pulmonary disease or asthma exacerbation (-44%; OR, 0.56 [95% CI, 0.50-0.62]). Conclusions and Relevance: The improvements observed in this study may be partly or fully attributed to the Medicare Advantage model. The Medicare Advantage risk adjustment system appears to be meeting its intended goal by aligning the capitation payments to the health care burden of the individual beneficiary and aggregate population served, thus providing revenue to develop infrastructure that supports improvements in quality and efficiency for the patients enrolled in Medicare Advantage models with 2-sided risk.

OrderRex clinical user testing: a randomized trial of recommender system decision support on simulated cases.

OBJECTIVE: To assess usability and usefulness of a machine learning-based order recommender system applied to simulated clinical cases. MATERIALS AND METHODS: 43 physicians entered orders for 5 simulated clinical cases using a clinical order entry interface with or without access to a previously developed automated order recommender system. Cases were randomly allocated to the recommender system in a 3:2 ratio. A panel of clinicians scored whether the orders placed were clinically appropriate. Our primary outcome included the difference in clinical appropriateness scores. Secondary outcomes included total number of orders, case time, and survey responses. RESULTS: Clinical appropriateness scores per order were comparable for cases randomized to the order recommender system (mean difference -0.11 order per score, 95% CI: [-0.41, 0.20]). Physicians using the recommender placed more orders (median 16 vs 15 orders, incidence rate ratio 1.09, 95%CI: [1.01-1.17]). Case times were comparable with the recommender system. Order suggestions generated from the recommender system were more likely to match physician needs than standard manual search options. Physicians used recommender suggestions in 98% of available cases. Approximately 95% of participants agreed the system would be useful for their workflows. DISCUSSION: User testing with a simulated electronic medical record interface can assess the value of machine learning and clinical decision support tools for clinician usability and acceptance before live deployments. CONCLUSIONS: Clinicians can use and accept machine learned clinical order recommendations integrated into an electronic order entry interface in a simulated setting. The clinical appropriateness of orders entered was comparable even when supported by automated recommendations.

Physician Usage and Acceptance of a Machine Learning Recommender System for Simulated Clinical Order Entry.

Clinical decision support tools that automatically disseminate patterns of clinical orders have the potential to improve patient care by reducing errors of omission and streamlining physician workflows. However, it is unknown if physicians will accept such tools or how their behavior will be affected. In this randomized controlled study, we exposed 34 licensed physicians to a clinical order entry interface and five simulated emergency cases, with randomized availability of a previously developed clinical order recommender system. With the recommender available, physicians spent similar time per case (6.7 minutes), but placed more total orders (17.1 vs. 15.8). The recommender demonstrated superior recall (59% vs 41%) and precision (25% vs 17%) compared to manual search results, and was positively received by physicians recognizing workflow benefits. Further studies must assess the potential clinical impact towards a future where electronic health records automatically anticipate clinical needs.

Geographic and Longitudinal Trends in Media Framing of Obesity in the United States.

OBJECTIVE: The media's framing of public health issues is closely linked to public opinion on these issues and support for interventions to address them. This study characterized geographic and temporal variation in the US media's framing of obesity across states from 2006 to 2015. METHODS: Newspaper articles that mentioned the term obesity were drawn from Access World News (NewsBank, Inc., Naples, Florida), a comprehensive online database (N = 364,288). This study employed automated content analysis, a machine learning technique, to categorize articles as (1) attributing obesity to individual-level causes (e.g., lifestyle behaviors), (2) attributing obesity to environmental/systemic causes (e.g., neighborhood walkability), (3) attributing obesity to both individual-level causes and environmental/systemic causes, or (4) articles without any such attribution framework. RESULTS: Nationwide across all years, a higher proportion of articles focused on individual-level attribution of obesity than environmental-level attribution or both. Missouri and Idaho had the highest proportions of articles with an individual framework, and Nevada, Arkansas, and Wisconsin had the highest proportions of articles with an environmental framework. CONCLUSIONS: This analysis demonstrates that US media sources heavily focus on an individual framing of obesity, which may be informing public perceptions of obesity. By highlighting differences in obesity media portrayal, this study could inform research to understand why particular states represent outliers and how this may affect obesity policy making.

Context is Key: Using the Audit Log to Capture Contextual Factors Affecting Stroke Care Processes.

High quality patient care through timely, precise and efficacious management depends not only on the clinical presentation of a patient, but the context of the care environment to which they present. Understanding and improving factors that affect streamlined workflow, such as provider or department busyness or experience, are essential to improving these care processes, but have been difficult to measure with traditional approaches and clinical data sources. In this exploratory data analysis, we aim to determine whether such contextual factors can be captured for important clinical processes by taking advantage of non-traditional data sources like EHR audit logs which passively track the electronic behavior of clinical teams. Our results illustrate the potential of defining multiple measures of contextual factors and their correlation with key care processes. We illustrate this using thrombolytic (tPA) treatment for ischemic stroke as an example process, but the measurement approaches can be generalized to multiple scenarios.

Effects of mTOR Inhibitors on Components of the Salvador-Warts-Hippo Pathway.

The MST/Salvador-Warts-Hippo and mTOR/Akt/PI3K growth signaling pathways have been established as important modulators of cell growth, proliferation and cell survival in controlling organ size in Drosophila and mammals. Here, we sought to determine the role of the MST family of kinases, some of which are components of the Hippo pathway, and their closely related Sterile 20-like kinases (STK) as candidates for mediating cross-talk between the Hippo and mTOR pathways. Expression analysis in the HepG2 and MCF7 cell lines demonstrated common expression of MST1/2/4, MAP4K3/4/5, STK 24 (MST3), STK25, STK39, Pak1, SLK, Stradα/ß and TAO2. All components of the Hippo signaling pathway are present in both cell lines except for YAP1 in MCF7 cells. mTOR inhibition via rapamycin decreases TAZ levels in HepG2 but not MCF7 cells and increases TEAD1 levels in MCF7 but not HepG2 cells, suggesting a selective role of the mTOR pathway in regulating these Hippo targets in a cell type-specific manner. Furthermore, the cellular localization of TAZ changes in response to mTORC1/2 inhibitors and Akt inhibition. These findings demonstrate the mTOR-dependent regulation of Hippo signaling at the level of the transcriptional regulators TAZ and TEAD1 and highlight the potential role for mTOR inhibitors in regulating Hippo-signaling dependent tumors.