Classical cadherins are calcium-dependent cell-cell adhesion proteins that play key roles in the formation and maintenance of tissues. Deficiencies in cadherin adhesion are hallmarks of numerous cancers. In this article, we review recent biophysical studies on the regulation of cadherin structure and adhesion. We begin by reviewing distinct cadherin binding conformations, their biophysical properties, and their response to mechanical stimuli. We then describe biophysical guidelines for engineering Abs that can regulate adhesion by either stabilizing or destabilizing cadherin interactions. Finally, we review molecular mechanisms by which cytoplasmic proteins regulate the conformation of cadherin extracellular regions from the inside out.

We combine proximity labeling and single molecule binding assays to discover transmembrane protein interactions in cells. We first screen for candidate binding partners by tagging the extracellular and cytoplasmic regions of a "bait" protein with BioID biotin ligase and identify proximal proteins that are biotin tagged on both their extracellular and intracellular regions. We then test direct binding interactions between proximal proteins and the bait, using single molecule atomic force microscope binding assays. Using this approach, we identify binding partners for the extracellular region of E-cadherin, an essential cell-cell adhesion protein. We show that the desmosomal proteins desmoglein-2 and desmocollin-3, the focal adhesion protein integrin-α2β1, the receptor tyrosine kinase ligand ephrin-B1, and the classical cadherin P-cadherin, all directly interact with E-cadherin ectodomains. Our data shows that combining extracellular and cytoplasmic proximal tagging with a biophysical binding assay increases the precision with which transmembrane ectodomain interactors can be identified.

Purpose

This study examined differences in smoking prevalence and differences in associations between family functioning, self-image and adolescent smoking behavior among four Asian-American subgroups.

Methods

Statistical analyses were conducted on responses about their smoking behaviors from 1139 students who self-identified as Chinese-Americans, Filipino-Americans, Korean-Americans, and Vietnamese-Americans.

Results

Significant differences in the prevalence of ever-tried smoking and 30-day smoking were found across subgroups, but there were no overall gender differences. Korean-American adolescents reported the highest lifetime smoking and 30-day smoking rates, followed by Vietnamese- and Filipino-Americans. Chinese-Americans reported the lowest smoking rates. There were also differences in the associations between smoking and family functioning and self-image across the four subgroups. High family functioning was inversely associated with smoking for Chinese- and Korean-American adolescents, but not for Filipino- and Vietnamese-Americans. On the other hand, high self-image was associated with decreased risk of smoking for Filipino- and Vietnamese-Americans, but not for the other two subgroups.

Conclusion

Findings of this study demonstrate that family functioning and self-image varied across Asian-American subgroups. This suggests the need to understand etiological differences between the groups as well as potential implications for prevention cessation programs.

Background

Readmissions after hospitalization for pneumonia are common, but the few risk-prediction models have poor to modest predictive ability. Data routinely collected in the electronic health record (EHR) may improve prediction.

Objective

To develop pneumonia-specific readmission risk-prediction models using EHR data from the first day and from the entire hospital stay ("full stay").

Design

Observational cohort study using stepwise-backward selection and cross-validation.

Subjects

Consecutive pneumonia hospitalizations from 6 diverse hospitals in north Texas from 2009-2010.

Measures

All-cause nonelective 30-day readmissions, ascertained from 75 regional hospitals.

Results

Of 1463 patients, 13.6% were readmitted. The first-day pneumonia-specific model included sociodemographic factors, prior hospitalizations, thrombocytosis, and a modified pneumonia severity index; the full-stay model included disposition status, vital sign instabilities on discharge, and an updated pneumonia severity index calculated using values from the day of discharge as additional predictors. The full-stay pneumonia-specific model outperformed the first-day model (C statistic 0.731 vs 0.695; P = 0.02; net reclassification index = 0.08). Compared to a validated multi-condition readmission model, the Centers for Medicare and Medicaid Services pneumonia model, and 2 commonly used pneumonia severity of illness scores, the full-stay pneumonia-specific model had better discrimination (C statistic range 0.604-0.681; P < 0.01 for all comparisons), predicted a broader range of risk, and better reclassified individuals by their true risk (net reclassification index range, 0.09-0.18).

Conclusions

EHR data collected from the entire hospitalization can accurately predict readmission risk among patients hospitalized for pneumonia. This approach outperforms a first-day pneumonia-specific model, the Centers for Medicare and Medicaid Services pneumonia model, and 2 commonly used pneumonia severity of illness scores. Journal of Hospital Medicine 2017;12:209-216.

Background

Vital sign instability on discharge could be a clinically objective means of assessing readiness and safety for discharge; however, the association between vital sign instability on discharge and post-hospital outcomes is unclear.

Objective

To assess the association between vital sign instability at hospital discharge and post-discharge adverse outcomes.

Design

Multi-center observational cohort study using electronic health record data. Abnormalities in temperature, heart rate, blood pressure, respiratory rate, and oxygen saturation were assessed within 24 hours of discharge. We used logistic regression adjusted for predictors of 30-day death and readmission.

Participants

Adults (≥18 years) with a hospitalization to any medicine service in 2009-2010 at six hospitals (safety-net, community, teaching, and non-teaching) in north Texas.

Main measures

Death or non-elective readmission within 30 days after discharge.

Key results

Of 32,835 individuals, 18.7 % were discharged with one or more vital sign instabilities. Overall, 12.8 % of individuals with no instabilities on discharge died or were readmitted, compared to 16.9 % with one instability, 21.2 % with two instabilities, and 26.0 % with three or more instabilities (p < 0.001). The presence of any (≥1) instability was associated with higher risk-adjusted odds of either death or readmission (AOR 1.36, 95 % CI 1.26-1.48), and was more strongly associated with death (AOR 2.31, 95 % CI 1.91-2.79). Individuals with three or more instabilities had nearly fourfold increased odds of death (AOR 3.91, 95 % CI 1.69-9.06) and increased odds of 30-day readmission (AOR 1.36, 95 % 0.81-2.30) compared to individuals with no instabilities. Having two or more vital sign instabilities at discharge had a positive predictive value of 22 % and positive likelihood ratio of 1.8 for 30-day death or readmission.

Conclusions

Vital sign instability on discharge is associated with increased risk-adjusted rates of 30-day mortality and readmission. These simple vital sign criteria could be used to assess safety for discharge, and to reduce 30-day mortality and readmissions.

Purpose

To examine disparities and changes over time in the population-level distribution of smokers along a cigarette quitting continuum among African American smokers compared with non-Hispanic Whites.

Methods

Secondary data analyses of the 1999, 2002, 2005, and 2008 California Tobacco Surveys (CTS). The CTS are large, random-digit-dialed, population-based surveys designed to assess changes in tobacco use in California. The number of survey respondents ranged from n = 6,744 to n = 12,876 across CTS years. Current smoking behavior (daily or nondaily smoking), number of cigarettes smoked per day, intention to quit in the next 6 months, length of most recent quit attempt among current smokers, and total length of time quit among former smokers were assessed and used to recreate the quitting continuum model.

Results

While current smoking rates were significantly higher among African Americans compared with non-Hispanic Whites across all years, cigarette consumption rates were lower among African Americans in all years. There were significant increases in the proportion of former smokers who had been quit for at least 12 months from 1999 (African Americans, 26.8% ± 5.5%; non-Hispanic Whites, 36.8% ± 1.6%) to 2008 (African Americans, 43.6% ± 4.1%; non-Hispanic Whites, 57.4% ± 2.9%). The proportion of African American former smokers in each CTS year was significantly lower than that of non-Hispanic Whites.

Conclusions

Despite positive progression along the quitting continuum for both African American and non-Hispanic White smokers, the overall distribution was less favorable for African Americans. The lower smoking consumption levels among African Americans, combined with the lower rates of successful smoking cessation, suggest that cigarette addiction and the quitting process may be different for African American smokers.

Abstract Background Short-term laboratory evolution of bacteria followed by genomic sequencing provides insight into the mechanism of adaptive evolution, such as the number of mutations needed for adaptation, genotype-phenotype relationships, and the reproducibility of adaptive outcomes. Results In the present study, we describe the genome sequencing of 11 endpoints of Escherichia coli that underwent 60-day laboratory adaptive evolution under growth rate selection pressure in lactate minimal media. Two to eight mutations were identified per endpoint. Generally, each endpoint acquired mutations to different genes. The most notable exception was an 82 base-pair deletion in the rph-pyrE operon that appeared in 7 of the 11 adapted strains. This mutation conferred an approximately 15% increase to the growth rate when experimentally introduced to the wild-type background and resulted in an approximately 30% increase to growth rate when introduced to a background already harboring two adaptive mutations. Additionally, most endpoints had a mutation in a regulatory gene (crp or relA, for example) or the RNA polymerase. Conclusions The 82 base-pair deletion found in the rph-pyrE operon of many endpoints may function to relieve a pyrimidine biosynthesis defect present in MG1655. In contrast, a variety of regulators acquire mutations in the different endpoints, suggesting flexibility in overcoming regulatory challenges in the adaptation.

Background

Incorporating clinical information from the full hospital course may improve prediction of 30-day readmissions.

Objective

To develop an all-cause readmissions risk-prediction model incorporating electronic health record (EHR) data from the full hospital stay, and to compare "full-stay" model performance to a "first day" and 2 other validated models, LACE (includes Length of stay, Acute [nonelective] admission status, Charlson Comorbidity Index, and Emergency department visits in the past year), and HOSPITAL (includes Hemoglobin at discharge, discharge from Oncology service, Sodium level at discharge, Procedure during index hospitalization, Index hospitalization Type [nonelective], number of Admissions in the past year, and Length of stay).

Design

Observational cohort study.

Subjects

All medicine discharges between November 2009 and October 2010 from 6 hospitals in North Texas, including safety net, teaching, and nonteaching sites.

Measures

Thirty-day nonelective readmissions were ascertained from 75 regional hospitals.

Results

Among 32,922 admissions (validation = 16,430), 12.7% were readmitted. In addition to many first-day factors, we identified hospital-acquired Clostridium difficile infection (adjusted odds ratio [AOR]: 2.03, 95% confidence interval [CI]: 1.18-3.48), vital sign instability on discharge (AOR: 1.25, 95% CI: 1.15-1.36), hyponatremia on discharge (AOR: 1.34, 95% CI: 1.18-1.51), and length of stay (AOR: 1.06, 95% CI: 1.04-1.07) as significant predictors. The full-stay model had better discrimination than other models though the improvement was modest (C statistic 0.69 vs 0.64-0.67). It was also modestly better in identifying patients at highest risk for readmission (likelihood ratio +2.4 vs. 1.8-2.1) and in reclassifying individuals (net reclassification index 0.02-0.06).

Conclusions

Incorporating clinically granular EHR data from the full hospital stay modestly improves prediction of 30-day readmissions. Given limited improvement in prediction despite incorporation of data on hospital complications, clinical instabilities, and trajectory, our findings suggest that many factors influencing readmissions remain unaccounted for. Further improvements in readmission models will likely require accounting for psychosocial and behavioral factors not currently captured by EHRs. Journal of Hospital Medicine 2016;11:473-480. © 2016 Society of Hospital Medicine.

Abstract: Introduction: Despite growing public health efforts to discourage teens from using hazardous tobacco products, their use of ENDS (electronic nicotine delivery system) remain piqued due to direct youth targeting by tobacco and vaping companies. ENDs especially e-cigs most often have a fruit or candy flavor that are particularly attractive to young people and may have high nicotine - which is highly addicting. Methods: 1) analyzed national/local nicotine product use in youth by gender, age, and racial/ethnic groups, 2) explored socio-ecological context of tobacco/vape shops via geo-spatial mapping within Los Angeles Service Planning Area 3 (SPA 3), 3) conducted environmental scan of social media platforms combined with Google and Yellow Pages searches. Results: Population level results were drawn from US Census, 2013-2017 American Community Survey (ACS) and California Tobacco Facts and Figures, 2019. 13.5% middle schoolers and 37.7% high schoolers reported ever using e-cigarettes. Use of basic or disposable devices was associated with younger age especially among Latinos (5% reported use in the past month compared to < 3% among other ethnicities). To explore socioecological contexts of tobacco and vape shops in SPA 3. Regardless of income, a higher number of tobacco and vape shops appear to correspond with higher percentage ethnic minorities. Lower income cities tended to have more tobacco and vape shops compared to very high-income cities. Tobacco products cost less in neighborhoods with a lower median household income and in neighborhoods with a higher proportion of Hispanic residents, even after adjusting for store type.Additionally, prior to the presentation, we will conduct geospatial mapping analysis: We will utilize open GIS software (QGIS) and open web map tools (Leaflet) to geocode locations of smoke/vape shops and overlay them with city demography to illustrate their spatial relationships and proximity to various neighborhoods. Discussion: Sustained implementation of population-based tobacco, including vaping, prevention and control strategies, in coordination with the Food and Drug Administration, are critical to reducing tobacco use including vaping and initiation among all U.S. population especially ethnic minorities and youths. There are associations of Tobacco Products marketing (price, placement, promotion, or product availability) with a neighborhood demographic (socioeconomic challenged, minority race/ethnicity and high traffic volume). Vape shops are more likely to be concentrated in low resourced communities with less political clout - these areas tend to be minority dense with fewer restrictions. Findings could inform initiatives aimed at a stronger licensing requirement for vape shops and federal and state-level regulations of this industry to prevent tobacco/vape shop from targeting minority and other socially challenged groups. Citation Format: Kimlin T. Ashing, Brian Tiep, Jonjon Macalintal, Sophia Yeung, Timothy O'Connor, Bin Xie, Udochukwu Obodo, Ming-Hsiang Tsou, Gaole Song, Faith Abuan, Christyl Dawson. A geospatial approach to explore the socioecological context of tobacco and vape shop locations [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr CT087.