Anger is an emotion that affects everyone regardless of culture, class, race, or gender-but at the same time, being angry always results from the circumstances in which people find themselves. InOn ...Anger, Sue J. Kim opens a stimulating dialogue between cognitive studies and cultural studies to argue that anger is always socially and historically constructed and complexly ideological, and that the predominant individualistic conceptions of anger are insufficient to explain its collective, structural, and historical nature.
On Angerexamines the dynamics of racial anger in global late capitalism, bringing into conversation work on political anger in ethnic, postcolonial, and cultural studies with recent studies on emotion in cognitive studies. Kim uses a variety of literary and media texts to show how narratives serve as a means of reflecting on experiences of anger and also how we think about anger-its triggers, its deeper causes, its wrongness or rightness. The narratives she studies include the filmCrash, Maxine Hong Kingston'sThe Woman Warrior, Tsitsi Dangarembga'sNervous ConditionsandThe Book of Not, Ngugi wa Thiong'o'sDevil on the CrossandWizard of the Crow, and the HBO seriesThe Wire. Kim concludes by distinguishing frustration and outrage from anger through a consideration of Stéphane Hessel's call to arms,Indignez-vous!One of the few works that focuses on both anger and race,On Angerdemonstrates that race-including whiteness-is central to our conceptions and experiences of anger.
Deformation measurement is a key process in traction force microscopy (TFM). Conventionally, particle image velocimetry (PIV) or correlation-based particle tracking velocimetry (cPTV) have been used ...for such a purpose. Using simulated bead images, we show that those methods fail to capture large displacement vectors and that it is due to a poor cross-correlation. Here, to redeem the potential large vectors, we propose a two-step deformation tracking algorithm that combines cPTV, which performs better for small displacements than PIV methods, and newly-designed retracking algorithm that exploits statistically confident vectors from the initial cPTV to guide the selection of correlation peak which are not necessarily the global maximum. As a result, the new method, named 'cPTV-Retracking', or cPTVR, was able to track more than 92% of large vectors whereas conventional methods could track 43-77% of those. Correspondingly, traction force reconstructed from cPTVR showed better recovery of large traction than the old methods. cPTVR applied on the experimental bead images has shown a better resolving power of the traction with different-sized cell-matrix adhesions than conventional methods. Altogether, cPTVR method enhances the accuracy of TFM in the case of large deformations present in soft substrates. We share this advance via our TFMPackage software.
The authors propose reinvigorating and extending the traditional social history beyond its narrow range of risk behaviors to enable clinicians to address negative health outcomes imposed by social ...determinants of health. In this Perspective, they outline a novel, practical medical vulnerability assessment questionnaire that operationalizes for clinical practice the social science concept of "structural vulnerability." A structural vulnerability assessment tool designed to highlight the pathways through which specific local hierarchies and broader sets of power relationships exacerbate individual patients' health problems is presented to help clinicians identify patients likely to benefit from additional multidisciplinary health and social services. To illustrate how the tool could be implemented in time- and resource-limited settings (e.g., emergency department), the authors contrast two cases of structurally vulnerable patients with differing outcomes. Operationalizing structural vulnerability in clinical practice and introducing it in medical education can help health care practitioners think more clearly, critically, and practically about the ways social structures make people sick. Use of the assessment tool could promote "structural competency," a potential new medical education priority, to improve understanding of how social conditions and practical logistics undermine the capacities of patients to access health care, adhere to treatment, and modify lifestyles successfully. Adoption of a structural vulnerability framework in health care could also justify the mobilization of resources inside and outside clinical settings to improve a patient's immediate access to care and long-term health outcomes. Ultimately, the concept may orient health care providers toward policy leadership to reduce health disparities and foster health equity.
Currently, the United States has the largest number of reported coronavirus disease 2019 (COVID-19) cases and deaths globally. Using a geographically diverse surveillance network, we describe risk ...factors for severe outcomes among adults hospitalized with COVID-19.
We analyzed data from 2491 adults hospitalized with laboratory-confirmed COVID-19 between 1 March-2 May 2020, as identified through the Coronavirus Disease 2019-Associated Hospitalization Surveillance Network, which comprises 154 acute-care hospitals in 74 counties in 13 states. We used multivariable analyses to assess associations between age, sex, race and ethnicity, and underlying conditions with intensive care unit (ICU) admission and in-hospital mortality.
The data show that 92% of patients had ≥1 underlying condition; 32% required ICU admission; 19% required invasive mechanical ventilation; and 17% died. Independent factors associated with ICU admission included ages 50-64, 65-74, 75-84, and ≥85 years versus 18-39 years (adjusted risk ratios aRRs, 1.53, 1.65, 1.84, and 1.43, respectively); male sex (aRR, 1.34); obesity (aRR, 1.31); immunosuppression (aRR, 1.29); and diabetes (aRR, 1.13). Independent factors associated with in-hospital mortality included ages 50-64, 65-74, 75-84, and ≥ 85 years versus 18-39 years (aRRs, 3.11, 5.77, 7.67, and 10.98, respectively); male sex (aRR, 1.30); immunosuppression (aRR, 1.39); renal disease (aRR, 1.33); chronic lung disease (aRR 1.31); cardiovascular disease (aRR, 1.28); neurologic disorders (aRR, 1.25); and diabetes (aRR, 1.19).
In-hospital mortality increased markedly with increasing age. Aggressive implementation of prevention strategies, including social distancing and rigorous hand hygiene, may benefit the population as a whole, as well as those at highest risk for COVID-19-related complications.
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