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    Low-Income Suburban Residents in the San Francisco Bay Area Face Significant Housing and Transportation Issues

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    Growing poverty in America’s suburbs challenges their image as single-family residential communities for middle class, predominantly white families. Research shows that suburban areas now have the largest share of households under the poverty line. Since these areas have lower density development and lower levels of public transit service compared to urban areas, living in the suburbs may pose accessibility challenges for low-income households, particularly those without a personal vehicle. To explore housing and transportation issues associated with the suburbanization of poverty, we combined U.S. Census data from Contra Costa County, which has the highest rates of suburban poverty in the San Francisco Bay Area, and online and in-person surveys with individuals who earn less than 80% of the Area Median Income (AMI), around $75,000. This research identifies demographic and external factors that lead low- and moderate-income households to move to suburban areas, accessibility barriers faced by low- and moderate-income suburban households, and how transportation use and transportation and housing costs differ between urban and suburban low-income residents in the Bay Area

    On O-Constructions in Jarawara

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    The language Jarawara (Arauan, spoken in Brazil) exhibits a puzzling set of passive-like properties in its “O-Construction” (Dixon 2000, 2004). We argue that O-Constructions have a type of passive voice in some person combinations but not in others, and that they are unified in that they always have topic agreement on C with the internal argument. We relate this approach to recent research on Algonquian inverse systems (especially Oxford 2023a,b, 2024) which have also been argued to involve a passive-like voice-based alternation for specific person combinations. Our analysis captures facts about case, word order, divergences between C and T agreement, and the distribution of the passive-like prefix hi- (among other properties). Our findings provide support for the approach to person restrictions embodied in Oxford’s work and also demonstrate how topic agreement and the A system can interact. More generally, this work shows how a nuanced approach to passive constructions, and a willingness to separate agreement from voice, can lead to a cross-linguistically grounded analysis of what seems prima facie like an “unusual” construction

    An Integrated Framework for Infectious Disease Control Using Mathematical Modeling and Deep Learning.

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    Infectious diseases are a major global public health concern. Precise modeling and prediction methods are essential to develop effective strategies for disease control. However, data imbalance and the presence of noise and intensity inhomogeneity make disease detection more challenging. Goal: In this article, a novel infectious disease pattern prediction system is proposed by integrating deterministic and stochastic model benefits with the benefits of the deep learning model. Results: The combined benefits yield improvement in the performance of solution prediction. Moreover, the objective is also to investigate the influence of time delay on infection rates and rates associated with vaccination. Conclusions: In this proposed framework, at first, the global stability at disease free equilibrium is effectively analysed using Routh-Haurwitz criteria and Lyapunov method, and the endemic equilibrium is analysed using non-linear Volterra integral equations in the infectious disease model. Unlike the existing model, emphasis is given to suggesting a model that is capable of investigating stability while considering the effect of vaccination and migration rate. Next, the influence of vaccination on the rate of infection is effectively predicted using an efficient deep learning model by employing the long-term dependencies in sequential data. Thus making the prediction more accurate

    Defining and Validating Criteria to Identify Populations Who May Benefit From Home-Based Primary Care.

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    BACKGROUND: Home-based primary care (HBPC) is an important care delivery model for high-need older adults. Currently, target patient populations vary across HBPC programs, hindering expansion and large-scale evaluation. OBJECTIVES: Develop and validate criteria that identify appropriate HBPC target populations. RESEARCH DESIGN: A modified Delphi process was used to achieve expert consensus on criteria for identifying HBPC target populations. All criteria were defined and validated using linked data from Medicare claims and the National Health and Aging Trends Study (NHATS) (cohort n=21,727). Construct validation involved assessing demographics and health outcomes/expenditures for selected criteria. SUBJECTS: Delphi panelists (n=29) represented diverse professional perspectives. Criteria were validated on community-dwelling Medicare beneficiaries (age ≥70) enrolled in NHATS. MEASURES: Criteria were selected via Delphi questionnaires. For construct validation, sociodemographic characteristics of Medicare beneficiaries were self-reported in NHATS, and annual health care expenditures and mortality were obtained via linked Medicare claims. RESULTS: Panelists proposed an algorithm of criteria for HBPC target populations that included indicators for serious illness, functional impairment, and social isolation. The algorithms Delphi-selected criteria applied to 16.8% of Medicare beneficiaries. These HBPC target populations had higher annual health care costs [Med (IQR): 10,851(3316,31,556)vs.10,851 (3316, 31,556) vs. 2830 (913, 9574)] and higher 12-month mortality [15% (95% CI: 14, 17) vs. 5% (95% CI: 4, 5)] compared with the total validation cohort. CONCLUSIONS: We developed and validated an algorithm to define target populations for HBPC, which suggests a need for increased HBPC availability. By enabling objective identification of unmet demands for HBPC access or resources, this algorithm can foster robust evaluation and equitable expansion of HBPC

    Increasing a Quitline’s Reach to Low-Income Tobacco Users Through 211 Agencies

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    IntroductionLow-income individuals bear a disproportionate share of the burden of tobacco use. This study tested the feasibility of increasing a quitline's reach to low-income tobacco users by collaborating with 211 information and referral agencies, which primarily serve people experiencing economic hardship.Aims and methodsStudy participants (N = 114 888) were adult tobacco users referred to the California quitline by 211 agencies, referred by healthcare clinics, or self-referred from April 17, 2021 to December 31, 2023. All were offered telephone counseling. Those referred by 211 received $20 for completing one counseling session. A subset (n = 2021) was followed up at 7 months. Referral outcomes, baseline characteristics, counseling and quitting aid utilization, and quitting outcomes were analyzed by referral source in 2024.ResultsOver a 2.7-year period, 211 agencies referred 55 151 clients to the quitline. Participants referred by 211 were more than twice as likely as healthcare-referred participants to enroll in quitline services (34.0% vs. 15.9%, p < .0001). They were more likely than healthcare- and self-referred participants to be female, lesbian, gay, bisexual, transgender, or queer/questioning, Black or multiracial, younger, less educated, and Medicaid-insured; more likely to complete a first counseling session (64.2% vs. 59.7% and 55.7%; both ps < .0001); and completed a similar number of sessions, 2.4. They were less likely to use quitting aids. Quit rates (ie, 30-day point prevalence abstinence) at 7-month follow-up were similar for all three groups.ConclusionsA collaboration between a quitline and 211 agencies connected large numbers of underserved, low-income tobacco users to evidence-based cessation treatment.ImplicationsThe study shows that quitlines and 211 agencies can collaborate effectively to help low-income tobacco users quit. It shows that when offered a modest incentive, 211-referred participants engage in counseling as much as healthcare- and self-referred participants and are as likely to quit. If 211 agencies across the US referred at the same rate as agencies in this study, an estimated 65 000 additional tobacco users annually would receive treatment. Total reach at full implementation would likely be much higher. Quitline and 211 funders and other supporters should find ways to sustain these gains and expand their reach

    Predicting image memorability from evoked feelings

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    While viewing a visual stimulus, we often cannot tell whether it is inherently memorable or forgettable. However, the memorability of a stimulus can be quantified and partially predicted by a collection of conceptual and perceptual factors. Higher-level properties that represent the "meaningfulness" of a visual stimulus to viewers best predict whether it will be remembered or forgotten across a population. Here, we hypothesize that the feelings evoked by an image, operationalized as the valence and arousal dimensions of affect, significantly contribute to the memorability of scene images. We ran two complementary experiments to investigate the influence of affect on scene memorability, in the process creating a new image set (VAMOS) of hundreds of natural scene images for which we obtained valence, arousal, and memorability scores. From our first experiment, we found memorability to be highly reliable for scene images that span a wide range of evoked arousal and valence. From our second experiment, we found that both valence and arousal are significant but weak predictors of image memorability. Scene images were most memorable if they were slightly negatively valenced and highly arousing. Images that were extremely positive or unarousing were most forgettable. Valence and arousal together accounted for less than 8% of the variance in image memorability. These findings suggest that evoked affect contributes to the overall memorability of a scene image but, like other singular predictors, does not fully explain it. Instead, memorability is best explained by an assemblage of visual features that combine, in perhaps unintuitive ways, to predict what is likely to stick in our memory

    Energy and economic impacts of U.S. federal energy and water conservation standards adopted from 1987 through 2024

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    This paper presents estimates of the key impacts of U.S. national energy and water conservation standards adopted from 1987 through 2024. The standards for consumer products, commercial and industrial equipment, lighting products, and plumbing products include those set by legislation as well as standards adopted by the Department of Energy (DOE) through rulemaking. In 2024 alone, these standards are estimated to have saved an estimated 6.0 quads of primary energy, which is equivalent to 6.5% of total U.S. energy consumption, and 1.7 trillion gallons of water, which is equivalent to approximately 12% of the annual water withdrawals for public supply in the U.S in 2015. The estimated reduction in CO2 emissions associated with the standards in 2024 was 270 million metric tons, which is equivalent to 5.6% of total annual U.S. CO2 emissions from energy consumption. The annual savings in operating costs for households and businesses totaled 105billion,andtheaveragehouseholdsaved105 billion, and the average household saved 576 in operating costs as a result of standards on residential appliances and plumbing products. The estimated cumulative past and future energy and water savings from these standards amount to 307 quads of energy and almost 53 trillion gallons of water. The estimated cumulative CO2 emissions reduction from the standards come to 10.3 billion metric tons. Accounting for the increased upfront costs of more-efficient products and the energy and water cost savings over the products’ lifetime, the standards have a cumulative net present value of benefit of 3.2trillionusing3percentdiscountrateand3.2 trillion using 3 percent discount rate and 3.5 trillion using 7 percent discount rate when discounting past and future benefits to 2024

    Epigenetic Upregulation of Carotid Body Angiotensin Signaling Increases Blood Pressure

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    BackgroundEpigenetic changes can be shaped by a wide array of environmental cues, maternal health, and behaviors. One of the most detrimental behaviors to the developing fetus is nicotine exposure. Perinatal nicotine exposure remains a significant risk factor for cardiovascular health and, in particular, hypertension. Increased basal carotid body (CB) activity and excitation are significant contributors to hypertension. This study investigated the epigenetic changes to CB activity induced by perinatal nicotine exposure resulting in CB-mediated hypertension.MethodsWe used a rodent model of perinatal nicotine exposure and cell culture methods.ResultsWe show that the AgtR1 (angiotensin II type 1 receptor) is upregulated in the carotid bodies of nicotine-exposed offspring. These changes were attributed to an upregulation of genetic promotion as DNA methylation of AgtR1 occurred within intron regions, exemplifying an upregulation of genetic transcription for this gene. Nicotine increased angiotensin signaling in vitro. CB reactivity to angiotensin was increased in perinatal nicotine-exposed offspring compared with control offspring. Furthermore, CB denervation reduced arterial pressure because of suppressed efferent sympathetic activity in perinatal nicotine-exposed offspring.ConclusionsOur data demonstrate that perinatal nicotine exposure adversely affects CB afferent sensing, which augments efferent sympathetic activity to increase vasoconstrictor signaling and induce hypertension. Targeting angiotensin signaling in the carotid bodies may provide a way to alleviate hypertension acquired by adverse maternal uterine environments in general and perinatal nicotine exposure in particular

    Therapeutic Targeting and Structural Characterization of a Sotorasib-Modified KRAS G12C-MHC I Complex Demonstrate the Antitumor Efficacy of Hapten-Based Strategies.

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    Antibody-based therapies have emerged as a powerful strategy for the management of diverse cancers. Unfortunately, tumor-specific antigens remain challenging to identify and target. Recent work established that inhibitor-modified peptide adducts derived from KRAS G12C are competent for antigen presentation via MHC I and can be targeted by antibody-based therapeutics, offering a means to directly target an intracellular oncoprotein at the cell surface with combination therapies. Here, we validated the antigen display of haptenated KRAS G12C peptide fragments on tumors in mouse models treated with the FDA-approved KRAS G12C covalent inhibitor sotorasib using PET/CT imaging of an 89Zr-labeled P1B7 IgG antibody, which selectively binds sotorasib-modified KRAS G12C-MHC I complexes. Targeting this peptide-MHC I complex with radioligand therapy using 225Ac- or 177Lu-P1B7 IgG effectively inhibited tumor growth in combination with sotorasib. Elucidation of the 3.1 Å cryo-EM structure of P1B7 bound to a haptenated KRAS G12C peptide-MHC I complex confirmed that the sotorasib-modified KRAS G12C peptide is presented via a canonical binding pose and showed that P1B7 binds the complex in a T-cell receptor-like manner. Together, these findings demonstrate the potential value of targeting unique oncoprotein-derived, haptenated MHC I complexes with radioligand therapeutics and provide a structural framework for developing next generation antibodies. Significance: Radioligand therapy using an antibody targeting KRAS-derived, sotorasib-modified MHC I complexes elicits antitumor effects superior to those of sotorasib alone and provides a potential strategy to repurpose sotorasib as a hapten to overcome resistance

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