State-Selective Metabolic Labeling of Cellular Proteins

Transcriptional activity from a specified promoter can provide a useful marker for the physiological state of a cell. Here we introduce a method for selective tagging of proteins made in cells in which specified promoters are active. Tagged proteins can be modified with affinity reagents for enrichment or with fluorescent dyes for visualization. The method allows state-selective analysis of the proteome, whereby proteins synthesized in predetermined physiological states can be identified. The approach is demonstrated by proteome-wide labeling of bacterial proteins upon activation of the P_(BAD) promoter and the SoxRS regulon and provides a basis for analysis of more complex systems including spatially heterogeneous microbial cultures and biofilms

The Admissions Process in Occupational Therapy Education: Investigating Academic and Non-academic Metrics in the Applicant Selection Process

The overall goal for any admissions process is to analyze criteria and identify the prospective students that have the highest potential for success in the program’s curriculum and in the field as a practicing clinician. The purpose of this study was to examine common academic and non-academic criteria utilized in occupational therapy (OT) admission processes and determine what criteria are used by programs with 100% student pass ratings on their National Board for Certification in Occupational Therapy (NBCOT) exam following completion of an OT program. Admissions criteria components and NBCOT pass rates were collected from the top 107 OT programs, as reported by US News and World Report, using publicly available websites for each program and the NBCOT webpage. Descriptive statistics were recorded regarding the frequency of utilizing various admissions criteria. Chi-square tests were utilized to examine the relationship between each admissions criteria component and the NBCOT pass rate. Admissions criteria frequently utilized by the top OT programs included a bachelor’s degree prior to matriculation (90.99% programs), minimum undergraduate GPA (55.86%), personal statement (90.09%), letters of recommendation (97.30%), observation hours (74.77%), and an interview (61.26%). Few programs required applicants to submit a minimum math/science GPA (11.71%) or a writing sample (40.54%). Results did not reveal a statistically significant difference between analyzed criteria groups. It is likely that NBCOT pass rates are impacted by other factors that were not publicly available or included in this study

Green Edge ice camp campaigns : understanding the processes controlling the under-ice Arctic phytoplankton spring bloom

The Green Edge initiative was developed to investigate the processes controlling the primary productivity and fate of organic matter produced during the Arctic phytoplankton spring bloom (PSB) and to determine its role in the ecosystem. Two field campaigns were conducted in 2015 and 2016 at an ice camp located on landfast sea ice southeast of Qikiqtarjuaq Island in Baffin Bay (67.4797∘ N, 63.7895∘ W). During both expeditions, a large suite of physical, chemical and biological variables was measured beneath a consolidated sea-ice cover from the surface to the bottom (at 360 m depth) to better understand the factors driving the PSB. Key variables, such as conservative temperature, absolute salinity, radiance, irradiance, nutrient concentrations, chlorophyll a concentration, bacteria, phytoplankton and zooplankton abundance and taxonomy, and carbon stocks and fluxes were routinely measured at the ice camp. Meteorological and snow-relevant variables were also monitored. Here, we present the results of a joint effort to tidy and standardize the collected datasets, which will facilitate their reuse in other Arctic studies

Correction for Johansson et al., An open challenge to advance probabilistic forecasting for dengue epidemics.

Correction for “An open challenge to advance probabilistic forecasting for dengue epidemics,” by Michael A. Johansson, Karyn M. Apfeldorf, Scott Dobson, Jason Devita, Anna L. Buczak, Benjamin Baugher, Linda J. Moniz, Thomas Bagley, Steven M. Babin, Erhan Guven, Teresa K. Yamana, Jeffrey Shaman, Terry Moschou, Nick Lothian, Aaron Lane, Grant Osborne, Gao Jiang, Logan C. Brooks, David C. Farrow, Sangwon Hyun, Ryan J. Tibshirani, Roni Rosenfeld, Justin Lessler, Nicholas G. Reich, Derek A. T. Cummings, Stephen A. Lauer, Sean M. Moore, Hannah E. Clapham, Rachel Lowe, Trevor C. Bailey, Markel García-Díez, Marilia Sá Carvalho, Xavier Rodó, Tridip Sardar, Richard Paul, Evan L. Ray, Krzysztof Sakrejda, Alexandria C. Brown, Xi Meng, Osonde Osoba, Raffaele Vardavas, David Manheim, Melinda Moore, Dhananjai M. Rao, Travis C. Porco, Sarah Ackley, Fengchen Liu, Lee Worden, Matteo Convertino, Yang Liu, Abraham Reddy, Eloy Ortiz, Jorge Rivero, Humberto Brito, Alicia Juarrero, Leah R. Johnson, Robert B. Gramacy, Jeremy M. Cohen, Erin A. Mordecai, Courtney C. Murdock, Jason R. Rohr, Sadie J. Ryan, Anna M. Stewart-Ibarra, Daniel P. Weikel, Antarpreet Jutla, Rakibul Khan, Marissa Poultney, Rita R. Colwell, Brenda Rivera-García, Christopher M. Barker, Jesse E. Bell, Matthew Biggerstaff, David Swerdlow, Luis Mier-y-Teran-Romero, Brett M. Forshey, Juli Trtanj, Jason Asher, Matt Clay, Harold S. Margolis, Andrew M. Hebbeler, Dylan George, and Jean-Paul Chretien, which was first published November 11, 2019; 10.1073/pnas.1909865116. The authors note that the affiliation for Xavier Rodó should instead appear as Catalan Institution for Research and Advanced Studies (ICREA) and Climate and Health Program, Barcelona Institute for Global Health (ISGlobal). The corrected author and affiliation lines appear below. The online version has been corrected

An open challenge to advance probabilistic forecasting for dengue epidemics.

A wide range of research has promised new tools for forecasting infectious disease dynamics, but little of that research is currently being applied in practice, because tools do not address key public health needs, do not produce probabilistic forecasts, have not been evaluated on external data, or do not provide sufficient forecast skill to be useful. We developed an open collaborative forecasting challenge to assess probabilistic forecasts for seasonal epidemics of dengue, a major global public health problem. Sixteen teams used a variety of methods and data to generate forecasts for 3 epidemiological targets (peak incidence, the week of the peak, and total incidence) over 8 dengue seasons in Iquitos, Peru and San Juan, Puerto Rico. Forecast skill was highly variable across teams and targets. While numerous forecasts showed high skill for midseason situational awareness, early season skill was low, and skill was generally lowest for high incidence seasons, those for which forecasts would be most valuable. A comparison of modeling approaches revealed that average forecast skill was lower for models including biologically meaningful data and mechanisms and that both multimodel and multiteam ensemble forecasts consistently outperformed individual model forecasts. Leveraging these insights, data, and the forecasting framework will be critical to improve forecast skill and the application of forecasts in real time for epidemic preparedness and response. Moreover, key components of this project-integration with public health needs, a common forecasting framework, shared and standardized data, and open participation-can help advance infectious disease forecasting beyond dengue

Role for Social Media in Pediatric Liver Disease: Caregiver and Provider Perspectives

To better understand the benefits and harms of engagement with online pediatric liver disease communities within social media. We conducted a survey of caregivers of children with liver disease participating in online pediatric liver disease communities within social media, as well as a survey of healthcare providers (e.g., physicians, surgeons, nurse coordinators) from this field to better understand the perceived benefits and harms of participation. Among 138 caregivers of children with liver disease that completed the survey, 97.8% agreed social media was a good place to learn about patient experiences and 88% agreed it was a good source of general information. Among caregivers, 84.8% agreed social media helps them to better advocate for their child. While 18% agreed that the information over social media was equal to the information from their healthcare team and 19% neither agreed/disagreed, only 3% indicated they would use this information to change care without telling their provider; in contrast, among 217 healthcare providers, 55% believed social media may lead caregivers to change management without telling their team. Engagement with online disease-specific communities in social media yields several benefits for caregivers and, in contrast to healthcare providers' concerns, participation is unlikely to lead to problems including caregivers changing the treatment plan without first discussing these plans with their team. Openness between caregivers and medical teams about the role for social media can help to improve trust and maximize the potential benefits of engagement with these groups

State-Selective Metabolic Labeling of Cellular Proteins

Transcriptional activity from a specified promoter can provide a useful marker for the physiological state of a cell. Here we introduce a method for selective tagging of proteins made in cells in which specified promoters are active. Tagged proteins can be modified with affinity reagents for enrichment or with fluorescent dyes for visualization. The method allows state-selective analysis of the proteome, whereby proteins synthesized in predetermined physiological states can be identified. The approach is demonstrated by proteome-wide labeling of bacterial proteins upon activation of the P_BAD promoter and the SoxRS regulon and provides a basis for analysis of more complex systems including spatially heterogeneous microbial cultures and biofilms