How do households respond to uncertainty shocks?

Economic disruptions generally coincide with heightened uncertainty. In the United States, uncertainty increased sharply with the recent housing market crash, financial crisis, deep recession, and uneven recovery. In July 2010 Congressional testimony, Federal Reserve Chairman Bernanke described conditions as "unusually uncertain." The uncertain landscape was also cited as a factor in the slow recovery from the 2001 recession, when the March 2003 Federal Open Market Committee statement highlighted the "unusually large uncertainties" at the time. ; Uncertainty is a standard feature of most macroeconomic models, in which consumers and firms make decisions today based on expectations of an unknown (and hence uncertain) future. But in light of real-world events, economists have begun to think more critically about the role of uncertainty in the economy. Recent research has allowed the degree of uncertainty to vary over time and examined how these fluctuations affect business activity. The results have been mixed thus far, with some authors finding that fluctuations in uncertainty are a key factor in the business cycle, while others have found little such evidence. ; Knotek and Khan take a similar approach in studying levels of uncertainty that can vary over time, but they focus on household responses to changes in uncertainty. Because uncertainty can take many forms, they consider two measures of uncertainty, one based on references to uncertainty in newspaper articles and another derived from the stock market. ; While economic theory predicts sudden, sharp pullbacks of household purchases following increases in uncertainty, the empirical results suggest that household spending reductions are modest and may only appear after a considerable time has passed. In addition, movements in uncertainty account for only a small portion of the total fluctuations in household spending. These results suggest that variations in the amount of uncertainty--at least as they are commonly captured--do not appear to be a key factor driving household spending decisions and, in turn, economic weakness.

Time-series cardiovascular risk factors and receipt of screening for breast, cervical, and colon cancer: The Guideline Advantage

BACKGROUND: Cancer is the second leading cause of death in the United States. Cancer screenings can detect precancerous cells and allow for earlier diagnosis and treatment. Our purpose was to better understand risk factors for cancer screenings and assess the effect of cancer screenings on changes of Cardiovascular health (CVH) measures before and after cancer screenings among patients. METHODS: We used The Guideline Advantage (TGA)-American Heart Association ambulatory quality clinical data registry of electronic health record data (n = 362,533 patients) to investigate associations between time-series CVH measures and receipt of breast, cervical, and colon cancer screenings. Long short-term memory (LSTM) neural networks was employed to predict receipt of cancer screenings. We also compared the distributions of CVH factors between patients who received cancer screenings and those who did not. Finally, we examined and quantified changes in CVH measures among the screened and non-screened groups. RESULTS: Model performance was evaluated by the area under the receiver operator curve (AUROC): the average AUROC of 10 curves was 0.63 for breast, 0.70 for cervical, and 0.61 for colon cancer screening. Distribution comparison found that screened patients had a higher prevalence of poor CVH categories. CVH submetrics were improved for patients after cancer screenings. CONCLUSION: Deep learning algorithm could be used to investigate the associations between time-series CVH measures and cancer screenings in an ambulatory population. Patients with more adverse CVH profiles tend to be screened for cancers, and cancer screening may also prompt favorable changes in CVH. Cancer screenings may increase patient CVH health, thus potentially decreasing burden of disease and costs for the health system (e.g., cardiovascular diseases and cancers)

Towards Large-Scale Learned Solvers for Parametric PDEs with Model-Parallel Fourier Neural Operators

Fourier neural operators (FNOs) are a recently introduced neural network architecture for learning solution operators of partial differential equations (PDEs), which have been shown to perform significantly better than comparable approaches based on convolutional networks. Once trained, FNOs can achieve speed-ups of multiple orders of magnitude over conventional numerical PDE solvers. However, due to the high dimensionality of their input data and network weights, FNOs have so far only been applied to two-dimensional or small three-dimensional problems. To remove this limited problem-size barrier, we propose a model-parallel version of FNOs based on domain-decomposition of both the input data and network weights. We demonstrate that our model-parallel FNO is able to predict time-varying PDE solutions of over 3.2 billions variables on Summit using up to 768 GPUs and show an example of training a distributed FNO on the Azure cloud for simulating multiphase CO$_2$ dynamics in the Earth's subsurface

The antioxidant activity of some curcuminoids and chalcones

The antioxidant properties of the synthetic compound (C1)–(C8), which comprised 7 curcuminoids and a chalcone, were evaluated by two complementary assays, DPPH and β-carotene/linoleic acid. It was found that, in general, the free radical scavenging ability of (C1)–(C8) was concentration-dependent. Compounds (C1) and (C4), which contained (4-OH) phenolic groups, were found to be highly potent antioxidants with higher antioxidant values than BHT suggesting that synthetic curcuminoids are more potent antioxidants than standard antioxidants like BHT. Using β-carotene-linoleic acid assay, only the water-soluble 2, 4,6-trihydroxyphenolic chalcone (C5) showed 85.2 % inhibition of the formation of conjugated dienes reflecting on its potent antioxidant activity

Patterns of Mood and Personality Factors and Associations With STI/HIV-Related Drug and Sex Risk Among African American Male Inmates

Background: Research on the association between antisocial personality disorder (ASPD) with comorbid mental disorders and sexually transmitted infection (STI)/HIV risk among inmates is scant despite the high prevalence of psychopathology and of STI/HIV in this population. Methods: We used baseline data from Project DISRUPT, a cohort study conducted among incarcerated African American men (n = 207), to measure associations between ASPD and STI/HIV risk. We also conducted latent class analyses (LCAs) to identify subgroups defined by ASPD with comorbid stress, depression, and borderline personality disorder symptoms and measured associations between latent class membership and STI/HIV risk. Results: Approximately 15% had ASPD and 39% reported depression. Controlling for sociodemographics, stress, and depression, ASPD was independently associated with illicit [AOR = 3.23, 95% confidence interval (CI): 1.18–8.87] and injection drug use (AOR: 5.49, 95% CI: 1.23–24.42) but not with sexual risk. LCAs suggested that those at high risk of ASPD were likely to experience co-morbid mental disorders. ASPD comorbid with these disorders was linked to drug and sex risk. Conclusions: STI/HIV prevention for inmates should incorporate diagnosis and treatment of ASPD and comorbid disorders, and interventions to address ASPD-related factors (e.g., impulsivity) that drive STI/HIV risk

Altering Host Resistance to Infections through Microbial Transplantation

Host resistance to bacterial infections is thought to be dictated by host genetic factors. Infections by the natural murine enteric pathogen Citrobacter rodentium (used as a model of human enteropathogenic and enterohaemorrhagic E. coli infections) vary between mice strains, from mild self-resolving colonization in NIH Swiss mice to lethality in C3H/HeJ mice. However, no clear genetic component had been shown to be responsible for the differences observed with C. rodentium infections. Because the intestinal microbiota is important in regulating resistance to infection, and microbial composition is dependent on host genotype, it was tested whether variations in microbial composition between mouse strains contributed to differences in “host” susceptibility by transferring the microbiota of resistant mice to lethally susceptible mice prior to infection. Successful transfer of the microbiota from resistant to susceptible mice resulted in delayed pathogen colonization and mortality. Delayed mortality was associated with increased IL-22 mediated innate defense including antimicrobial peptides Reg3γ and Reg3β, and immunono-neutralization of IL-22 abrogated the beneficial effect of microbiota transfer. Conversely, depletion of the native microbiota in resistant mice by antibiotics and transfer of the susceptible mouse microbiota resulted in reduced innate defenses and greater pathology upon infection. This work demonstrates the importance of the microbiota and how it regulates mucosal immunity, providing an important factor in susceptibility to enteric infection. Transfer of resistance through microbial transplantation (bacteriotherapy) provides additional mechanisms to alter “host” resistance, and a novel means to alter enteric infection and to study host-pathogen interactions

Invited Commentary: Is Monitoring of Human Papillomavirus Infection for Viral Persistence Ready for Use in Cervical Cancer Screening?

Persistent cervical infections by approximately 15 carcinogenic genotypes of human papillomavirus (HPV) cause virtually all cases of cervical cancer and its immediate precancerous precursor, cervical intraepithelial neoplasia grade 3 or carcinoma in situ. As is shown in a meta-analysis by Koshiol et al. (Am J Epidemiol 2008;168:123–137), detection of carcinogenic HPV viral persistence could be used to identify women at the greatest risk of cervical precancer. Specifically, women who have carcinogenic HPV infection that persists for at least 1 year versus those whose infections clear are at significantly elevated risk of having or developing cervical precancer. However, before detection of HPV persistence can be used in cervical cancer screening, several considerations need to be addressed: 1) validation and Food and Drug Administration approval of a reliable HPV genotyping test, 2) rational clinical algorithms based on risk of precancer and cancer for the clinical management of HPV persistence, 3) clinician and patient acceptability of monitoring of HPV infections (including not responding excessively to the first positive HPV test and waiting 1–2 years for infections to either persist or resolve), and 4) patient compliance with recommended follow-up. Investigators will need to address these and other key issues in order to realize the potential utility of HPV viral monitoring for improving the accuracy of cervical cancer screening

Dissemination and implementation of an educational tool for veterans on complementary and alternative medicine: a case study

Background Predicting when and where pathogens will emerge is difficult, yet, as shown by the recent Ebola and Zika epidemics, effective and timely responses are key. It is therefore crucial to transition from reactive to proactive responses for these pathogens. To better identify priorities for outbreak mitigation and prevention, we developed a cohesive framework combining disparate methods and data sources, and assessed subnational pandemic potential for four viral haemorrhagic fevers in Africa, Crimean–Congo haemorrhagic fever, Ebola virus disease, Lassa fever, and Marburg virus disease. Methods In this multistage analysis, we quantified three stages underlying the potential of widespread viral haemorrhagic fever epidemics. Environmental suitability maps were used to define stage 1, index-case potential, which assesses populations at risk of infection due to spillover from zoonotic hosts or vectors, identifying where index cases could present. Stage 2, outbreak potential, iterates upon an existing framework, the Index for Risk Management, to measure potential for secondary spread in people within specific communities. For stage 3, epidemic potential, we combined local and international scale connectivity assessments with stage 2 to evaluate possible spread of local outbreaks nationally, regionally, and internationally. Findings We found epidemic potential to vary within Africa, with regions where viral haemorrhagic fever outbreaks have previously occurred (eg, western Africa) and areas currently considered non-endemic (eg, Cameroon and Ethiopia) both ranking highly. Tracking transitions between stages showed how an index case can escalate into a widespread epidemic in the absence of intervention (eg, Nigeria and Guinea). Our analysis showed Chad, Somalia, and South Sudan to be highly susceptible to any outbreak at subnational levels. Interpretation Our analysis provides a unified assessment of potential epidemic trajectories, with the aim of allowing national and international agencies to pre-emptively evaluate needs and target resources. Within each country, our framework identifies at-risk subnational locations in which to improve surveillance, diagnostic capabilities, and health systems in parallel with the design of policies for optimal responses at each stage. In conjunction with pandemic preparedness activities, assessments such as ours can identify regions where needs and provisions do not align, and thus should be targeted for future strengthening and support