Human cognition significantly influences expressed behavior and is intrinsically tied to authentic personality traits. Personality assessment plays a pivotal role in various fields, including psychology, education, social media, etc. However, traditional self-report questionnaires can only provide data based on what individuals are willing and able to disclose, thereby lacking objective. Moreover, automated measurements and peer assessments demand significant human effort and resources. In this paper, given the advantages of the Virtual Reality (VR) technique, we develop a VR simulator --- PersonalityScanner, to stimulate cognitive processes and simulate daily behaviors based on an immersive and interactive simulation environment, in which participants carry out a battery of engaging tasks that formulate a natural story of first-day at work. Through this simulator, we collect a synchronous multi-modal dataset with ten modalities, including first/third-person video, audio, text, eye tracking, facial microexpression, pose, depth data, log, and inertial measurement unit. By systematically examining the contributions of different modalities on revealing personality, we demonstrate the superior performance and effectiveness of PersonalityScanner.

Understanding the incidence of disease is often crucial for public policy decision-making, as observed during the COVID-19 pandemic. Estimating incidence is challenging, however, when the definition of incidence relies on tests that imperfectly measure disease, as in the case when assays with variable performance are used to detect the SARS-CoV-2 virus. To our knowledge, there are no pragmatic methods to address the bias introduced by the performance of labs in testing for the virus. In the setting of a longitudinal study, we developed a maximum likelihood estimation-based approach to estimate laboratory performance-adjusted incidence using the expectation-maximization algorithm. We constructed confidence intervals (CIs) using both bootstrapped-based and large-sample interval estimator approaches. We evaluated our methods through extensive simulation and applied them to a real-world study (TrackCOVID), where the primary goal was to determine the incidence of and risk factors for SARS-CoV-2 infection in the San Francisco Bay Area from July 2020 to March 2021. Our simulations demonstrated that our method converged rapidly with accurate estimates under a variety of scenarios. Bootstrapped-based CIs were comparable to the large-sample estimator CIs with a reasonable number of incident cases, shown via a simulation scenario based on the real TrackCOVID study. In more extreme simulated scenarios, the coverage of large-sample interval estimation outperformed the bootstrapped-based approach. Results from the application to the TrackCOVID study suggested that assuming perfect laboratory test performance can lead to an inaccurate inference of the incidence. Our flexible, pragmatic method can be extended to a variety of disease and study settings.

The stage I uterine malignant mixed mullerian tumor (MMMT) shows different potential for progression. We reason that MMMTs with high-grade carcinomatous component and positivity for HB-EGF are prone to recurrence/metastasis in the early stage. A retrospective clinical and histopathologic review with immunohistochemical staining for HB-EGF, EGFR, and integrin-α5 was performed for 62 surgically staged MMMT cases. Recurrence/metastasis (RM) is 6/18 (33%) in stage I disease. Of all the clinicopathologic variables and biomarkers analyzed for stage I MMMT, serous carcinomatous component (83% [5/6] versus 17% [1/12], P = .0015) and HB-EGF expression (100% [6/6] versus 50% [6/12], P=.0339) were significantly different between groups with RM and without RM. The presence of serous carcinoma in all stages was 83% (5/6) in stage I with RM, 8% (1/12) in stage I without RM, 20% (1/5) in stage II, 36.4% (8/22) in stage III and 64.7% (11/17) in stage IV; this was paralleled by HB-EGF expression of 100% (6/6), 50% (6/12), 40% (2/5), 50% (11/22) and 71% (12/17) with a correlation coefficient r=0.9131 (P=.027). HB-EGF and integrin-α5 were highly expressed in MMMTs bearing serous carcinoma component, compared to endometrioid and unclassifiable/miscellaneous subtypes (84.6%/47.6%/33.3%, P=.025 for HB-EGF; and 61.5%/42.9%/20.0%, P=.021 for integrin-α5). The EGFR positivity was comparable among the three subtypes (48.1%, 47.6% and 26.7%, P=.326). This study indicates that serous carcinomatous component championed by expression of HB-EGF predisposes to recurrence/metastasis in stage I MMMT. This process might involve integrin-α5 and does not seem to require overexpression of EGFR. Further study is required.

Objectives

This study sought to evaluate the influence of race/ethnicity on the relationship between body mass index (BMI) and mortality in heart failure with preserved ejection fraction (HFpEF) and HF with reduced EF (HFrEF) patients.

Background

Prior studies demonstrated an "obesity paradox" among overweight and obese patients, where they have a better HF prognosis than normal weight patients. Less is known about the relationship between BMI and mortality among diverse patients with HF, particularly given disparities in obesity and HF prevalence.

Methods

The authors used Get With The Guidelines-Heart Failure data to assess the relationship between BMI and in-hospital mortality by using logistic regression modeling. The authors assessed 30-day and 1-year rates of all-cause mortality following discharge by using Cox regression modeling.

Results

A total of 39,647 patients with HF were included (32,434 [81.8%] white subjects; 3,809 [9.6%] black subjects; 1,928 [4.9%] Hispanic subjects; 544 [1.4%] Asian subjects; and 932 [2.3%] other subjects); 59.7% of subjects had HFpEF, and 30.7% were obese. More black and Hispanic patients had Class I or higher obesity (BMI ≥30 kg/m²) than whites, Asians, or other racial/ethnic groups (p < 0.0001). Among subjects with HFpEF, higher BMI was associated with lower 30-day mortality, up to 30 kg/m² with a small risk increase above 30 kg/m² (BMI: 30 vs. 18.5 kg/m²), hazard ratio (HR) of 0.63 (95% confidence interval [CI]: 0.54 to 0.73). A modest relationship was observed in HFrEF subjects (BMI: 30 vs. 18.5 kg/m²; HR: 0.73; 95% CI: 0.60 to 0.89), with no risk increase above 30 kg/m². There were no significant interactions between BMI and race or ethnicity related to 30-day mortality (p > 0.05).

Conclusions

This work is one of the first suggesting the obesity paradox for 30-day mortality exists at all BMI levels in HFrEF but not in patients with HFpEF. Higher BMI was associated with lower 30-day mortality across racial/ethnic groups in a manner inconsistent with the J-shaped relationship noted for coronary artery disease. The differential slope of obesity and mortality among HFpEF and patients with HFrEF potentially suggests differing mechanistic factors, requiring further exploration.

Background

Postdischarge mortality following hospitalization for heart failure with reduced ejection fraction (HFrEF) has remained high and unchanged over the past 2 decades, despite effective therapies for HFrEF. We aimed to explore whether these patterns could in part be explained by changes in longitudinal risk profile and HF severity over time.

Methods

Among patients hospitalized for HF in the GWTG-HF registry from January 2005 to December 2018 with available data, we evaluated GWTG-HF and ADHERE risk scores, observing in-hospital mortality per-year. The risk profiles and outcomes were described overall and by subgroups based on ejection fraction (EF), diabetes mellitus (DM), sex, and age.

Results

Overall, 335,735 patients were included (50% HFrEF, 46% DM, 48% female, mean age 74 years). In-hospital mortality increased by 2.0% per year from 2005 to 2018. There was no significant change in mean GWTG-HF risk score overall or when stratified by EF groups (P = 0.46 HFrEF, p = 0.26 HF mid-range EF [HFmrEF], and P = 0.72 HF preserved EF [HFpEF]), age, sex, or presence of DM. The observed/expected ratio based on the GWTG-HF risk score was 0.93 (0.91-0.96), 0.83 (0.77-0.90), 0.92 (0.89-95) for HFrEF, HFmrEF, and HFpEF, respectively. Similar findings were seen when risk was assessed using ADHERE risk score.

Conclusions

There were no significant changes in average risk profiles among hospitalized HF patients over the study duration. These data do not support the notion that worsening risk profile explains the lack of improved outcomes despite therapeutic advances, underscoring the importance of aggressive implementation of guideline-recommended therapies and investigation of novel treatments.

Techniques for forming sophisticated, 3D mesostructures in advanced, functional materials are of rapidly growing interest, owing to their potential uses across a broad range of fundamental and applied areas of application. Recently developed approaches to 3D assembly that rely on controlled buckling mechanics serve as versatile routes to 3D mesostructures in a diverse range of high-quality materials and length scales of relevance for 3D microsystems with unusual function and/or enhanced performance. Nonlinear buckling and delamination behaviors in materials that combine both weak and strong interfaces are foundational to the assembly process, but they can be difficult to control, especially for complex geometries. This paper presents theoretical and experimental studies of the fundamental aspects of adhesion and delamination in this context. By quantifying the effects of various essential parameters on these processes, we establish general design diagrams for different material systems, taking into account 4 dominant delamination states (wrinkling, partial delamination of the weak interface, full delamination of the weak interface, and partial delamination of the strong interface). These diagrams provide guidelines for the selection of engineering parameters that avoid interface-related failure, as demonstrated by a series of examples in 3D helical mesostructures and mesostructures that are reconfigurable based on the control of loading-path trajectories. Three-dimensional micromechanical resonators with frequencies that can be selected between 2 distinct values serve as demonstrative examples.

Advances in complex oxide heteroepitaxy have highlighted the enormous potential of utilizing strain engineering via lattice mismatch to control ferroelectricity in thin-film heterostructures. This approach, however, lacks the ability to produce large and continuously variable strain states, thus limiting the potential for designing and tuning the desired properties of ferroelectric films. Here, we observe and explore dynamic strain-induced ferroelectricity in SrTiO₃ by laminating freestanding oxide films onto a stretchable polymer substrate. Using a combination of scanning probe microscopy, optical second harmonic generation measurements, and atomistic modeling, we demonstrate robust room-temperature ferroelectricity in SrTiO₃ with 2.0% uniaxial tensile strain, corroborated by the notable features of 180° ferroelectric domains and an extrapolated transition temperature of 400 K. Our work reveals the enormous potential of employing oxide membranes to create and enhance ferroelectricity in environmentally benign lead-free oxides, which hold great promise for applications ranging from non-volatile memories and microwave electronics.

The study was designed to compare intentions to receive COVID-19 vaccination by race-ethnicity, to identify beliefs that may mediate the association between race-ethnicity and intention to receive the vaccine and to identify the demographic factors and beliefs most strongly predictive of intention to receive a vaccine. Cross-sectional survey conducted from November 2020 to January 2021, nested within a longitudinal cohort study of the prevalence and incidence of SARS-CoV-2 among a general population-based sample of adults in six San Francisco Bay Area counties (called TrackCOVID). Study Cohort: In total, 3161 participants among the 3935 in the TrackCOVID parent cohort responded. Rates of high vaccine willingness were significantly lower among Black (41%), Latinx (55%), Asian (58%), Multi-racial (59%), and Other race (58%) respondents than among White respondents (72%). Black, Latinx, and Asian respondents were significantly more likely than White respondents to endorse lack of trust of government and health agencies as a reason not to get vaccinated. Participants' motivations and concerns about COVID-19 vaccination only partially explained racial-ethnic differences in vaccination willingness. Concerns about a rushed government vaccine approval process and potential bad reactions to the vaccine were the two most important factors predicting vaccination intention. Vaccine outreach campaigns must ensure that the disproportionate toll of COVID-19 on historically marginalized racial-ethnic communities is not compounded by inequities in vaccination. Efforts must emphasize messages that speak to the motivations and concerns of groups suffering most from health inequities to earn their trust to support informed decision making.

De novo truncations in Interferon Regulatory Factor 2 Binding Protein Like (IRF2BPL) lead to severe childhood-onset neurodegenerative disorders. To determine how loss of IRF2BPL causes neural dysfunction, we examined its function in Drosophila and zebrafish. Overexpression of either IRF2BPL or Pits, the Drosophila ortholog, represses Wnt transcription in flies. In contrast, neuronal depletion of Pits leads to increased wingless (wg) levels in the brain and is associated with axonal loss, whereas inhibition of Wg signaling is neuroprotective. Moreover, increased neuronal expression of wg in flies is sufficient to cause age-dependent axonal loss, similar to reduction of Pits. Loss of irf2bpl in zebrafish also causes neurological defects with an associated increase in wnt1 transcription and downstream signaling. WNT1 is also increased in patient-derived astrocytes, and pharmacological inhibition of Wnt suppresses the neurological phenotypes. Last, IRF2BPL and the Wnt antagonist, CKIα, physically and genetically interact, showing that IRF2BPL and CkIα antagonize Wnt transcription and signaling.

Background

Preventing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2_ infections in healthcare workers (HCWs) is critical for healthcare delivery. We aimed to estimate and characterize the prevalence and incidence of coronavirus disease 2019 (COVID-19) in a US HCW cohort and to identify risk factors associated with infection.

Methods

We conducted a longitudinal cohort study of HCWs at 3 Bay Area medical centers using serial surveys and SARS-CoV-2 viral and orthogonal serological testing, including measurement of neutralizing antibodies. We estimated baseline prevalence and cumulative incidence of COVID-19. We performed multivariable Cox proportional hazards models to estimate associations of baseline factors with incident infections and evaluated the impact of time-varying exposures on time to COVID-19 using marginal structural models.

Results

A total of 2435 HCWs contributed 768 person-years of follow-up time. We identified 21 of 2435 individuals with prevalent infection, resulting in a baseline prevalence of 0.86% (95% confidence interval [CI], .53%-1.32%). We identified 70 of 2414 incident infections (2.9%), yielding a cumulative incidence rate of 9.11 cases per 100 person-years (95% CI, 7.11-11.52). Community contact with a known COVID-19 case was most strongly correlated with increased hazard for infection (hazard ratio, 8.1 [95% CI, 3.8-17.5]). High-risk work-related exposures (ie, breach in protective measures) drove an association between work exposure and infection (hazard ratio, 2.5 [95% CI, 1.3-4.8). More cases were identified in HCWs when community case rates were high.

Conclusions

We observed modest COVID-19 incidence despite consistent exposure at work. Community contact was strongly associated with infections, but contact at work was not unless accompanied by high-risk exposure.