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  • Open Access
    Authors: 
    World Bank;
    Publisher: Washington, DC: World Bank
    Country: United States

    Although global economic activity is recovering and output in Europe and Central Asia (ECA) is expected to grow in 2021, containing COVID-19 remains a challenge in the region. Enterprise survey data for the emerging and developing countries in the region show that COVID-19 had a profound and heterogeneous impact on firms. Smaller, younger, and female-run businesses were hit harder and had greater difficulty recovering. But the crisis also played a cleansing role and economic activity in ECA appears to have been reallocated toward more productive firms during the crisis, particularly in countries with more competitive markets. Firms with high pre-crisis labor productivity experienced significantly smaller drops in sales and employment than firms with low pre-crisis labor productivity and were also more likely to adapt to the crisis by increasing online activity and remote work. Many governments in ECA implemented broad policy support schemes to address the initial economic fallout from the crisis. Overall, this government support was more likely to go to less productive and larger firms, regardless of the level of their pre-crisis innovation. As economies enter the economic recovery phase, it will be important for policy makers in all countries to phase out broad policy support measures as soon as appropriate and focus on fostering a competitive business environment, which is key to a strong recovery, resilience to future crises, and sustainable, long-term economic growth.

  • Open Access English
    Authors: 
    Jue, Erik; Ismagilov, Rustem F.;
    Country: United States

    In response to the rapidly evolving COVID-19 pandemic, the U.S. Food and Drug Administration (FDA) has rapidly issued 49 emergency use authorizations (EUAs) for SARS-CoV-2 in vitro diagnostic test-kits. A critical metric in the performance evaluation for a diagnostic test kit is the analytical sensitivity, which is measured by the limit of detection (LOD). Commercial RNA stocks with known titers are used to determine LOD. We identified a problem with the titer reported for the commercial stocks when examining the analytical sensitivity of the reverse transcription quantitative PCR (RT-qPCR) protocol that is recommended by the Centers for Disease Control and Prevention (CDC) using plasmid DNA from Integrated DNA Technologies (IDT), synthetic RNA from BEI Resources (BEI), and extracted genomic RNA from BEI. We detected 3/3 positives for reactions containing synthetic RNA at a concentration of 0.1 copies/reaction (based on the supplier's label concentration). The apparent better-than-single-molecule performance is a statistically highly unlikely event, indicating a potential inaccuracy in the supplier's quantification of the stock material. Using an ultrasensitive and precise assay, reverse transcription digital PCR (RT-dPCR), we independently quantified concentrations of commercial SARS-CoV-2 plasmid DNA and SARS-CoV-2 RNA stocks. For plasmid DNA, the actual concentration measured by RT-dPCR was 11% of the nominal label concentration. For synthetic RNA, the actual concentration measured by RT-dPCR for one lot was 770% of the label concentration and for a different lot was 57% of the label concentration. For genomic RNA, the concentration measured by RT-dPCR for one lot was 240% of the label concentration and for a different lot it was 300% of the label concentration. This SARS-CoV-2 genomic RNA from BEI Resources has been used in at least 11 approved FDA Emergency Use Authorizations as of April 27, 2020. Such deviations of reported RNA or DNA stock concentrations from true concentrations can result in inaccurate quantification and calculation of LOD. Precise and accurate reporting of DNA and RNA stock concentrations by commercial suppliers will enable accurate quantification of assay performance, which is urgently needed to improve evaluation of different assays by diagnostic developers and regulatory bodies.

  • Open Access English
    Authors: 
    Bracken, Colton;
    Publisher: eScholarship, University of California
    Country: United States

    Antibodies and antibody-like molecules are broadly used as biochemical reagents and therapeutics. They are highly valued as probes that can distinguish between protein targets with extraordinary molecular detail. A deep understanding of natural antibody structure and function has enabled the development of fully synthetic human antibody libraries for in vitro display. These synthetic libraries recapitulate the sophistication of molecular recognition in antibody complementarity determining regions (CDRs) and in vitro display permits exquisite control over selection conditions. Thus, protein engineers can tailor-make antibodies to bind challenging and non-conventional targets.Here, we describe three examples of protein engineering that leverage synthetic antibody libraries and in vitro display technologies to generate binders to novel epitopes. In Chapter 1, we utilize recombinant antibody pairs to target the post-translational modification (PTM) phosphotyrosine (pY) in folded protein epitopes. In Chapter 2, we develop and deploy a single-domain antibody (sdAb) library to rapidly identify inhibitors to SARS-CoV-2 viral entry. In Chapter 3, we utilize chemo-epitope specific sdAbs to create small-molecule-dependent switches and further engineer them to control cellular therapies.

  • Open Access English
    Authors: 
    Rakka, Mariam;
    Publisher: eScholarship, University of California
    Country: United States

    In-Memory Computing (IMC) is considered a great candidate to replace the von-Neumann computing architecture to overcome the memory wall. Content Addressable Memories (CAMs) are the main building blocks in IMC-based architectures, such as the associative processors, and they are being used to accelerate machine learning tasks such as inference on Decision Trees (DTs). Decision trees are popular and powerful tools for data classification. Accelerating the decision tree search is crucial for on-the-edge applications that have limited power and latency budget. In this paper, we first present a juxtaposition between the capacitive and resistive sensing schemes in 2 Transistor-2 Resistive (2T-2R) Ternary CAMs (TCAMs). A Figure of Merit (FOM), function of the dynamic range, latency, and energy, is defined to have a fair comparison between the two sensing techniques. A mathematical model for the transient behavior of both sensing schemes is derived and verified through SPICE simulations. We then study the performance of the two schemes with an in-memory addition application and the results reveal that resistive sensing has an edge in that context. In addition, we propose a CAM Compiler for DT inference acceleration. In particular, we propose a novel ”adaptive-precision” scheme that results in a compact implementation and enables an efficient bijective mapping to TCAMs while maintaining high inference accuracies. Also, a Resistive-CAM (ReCAM) functional synthesizer is developed for mapping the decision tree to the ReCAM arrays with the capacitive sensing scheme and performing functional simulations for energy, latency, and accuracy evaluations. We study the decision tree accuracy under hardware non-idealities including device defects, manufacturing variability, and input encoding noise. We test our framework on various DT datasets including Give Me Some Credit, Titanic, and COVID-19. Our results reveal up to 42.4% energy savings and up to 17.8x better energy-delay-area product compared to the state-of-art hardware accelerators and up to 333 million decisions per sec for the pipelined implementation.

  • Open Access English
    Authors: 
    Bachas, Pierre; Brockmeyer, Anne; Harris, Tom; Semelet, Camille;
    Publisher: World Bank, Washington, DC
    Country: United States

    The COVID19 (coronavirus) pandemic and associated containment measures are expected to cause far-reaching damage to economies around the world. Firms are suffering from reduced demand due to movement restrictions, from reduced labor supply and from constraints to sourcing material inputs. The breakup of otherwise healthy businesses in response to a temporary shock implies large social costs. Governments are therefore intent on designing emergency policies to keep businesses afloat. In this brief, the authors present simulations using firm-level tax records from Ethiopia, which vary the duration of the lockdown and the relative impact across sectors.

  • Open Access English
    Authors: 
    Garcia, Katherine Arias;
    Publisher: eScholarship, University of California
    Country: United States

    Only 5% of the graduates from medical schools identify as Latinx (AAMC, 2019). While, in the state of California, the growing Latinx and bilingual community is expected to exceed 40% of the state’s population with only 5% Latinx physicians (Martinez et al., 2019). Diversity of the physician workforce is important because underrepresented students are more likely to work as a physician in underserved communities, such as urban and rural communities (Mitchell & Lassiter, 2006). The field of higher education is lacking research on Latinx student persistence in premedical studies in higher education. Moreover, the literature on underrepresented STEM students is lacking an analysis of the cultural assets that Students of Color bring with them into STEM. Through this dissertation, I advance STEM research by applying asset-based theoretical frameworks and culturally relevant methodology in order to center Latinx first-generation premedical students voices and experiences. Guided by the following theories, Community Cultural Wealth (CCW) (Yosso, 2005), Latinx STEM Student Success Model (Rendón et al., 2019) and Chicana/Latina Feminist Epistemology (Fierros & Delgado Bernal, 2016), this dissertation aims to take on an assetbased approach and use culturally-sensitive methodology to understand the persistence of Latinx students in medicine. Yosso’s CCW (2005) provides a foundation in viewing students of color entering the college environment with cultural assets and to further center Latinx premedical students, the Latinx Student STEM Success Model (Rendón et al., 2019) is applied to explore Latinx cultural assets, strengths developed from families/communities and knowledge that Latinx students have gained that are related to the Latinx asset (Rendón, Nora & Kanagala, 2014). Additionally, I employ pláticas, a culturally-sensitive methodology that draws from Chicana/Latina Feminist Epistemology (Fierros & Delgado Bernal, 2016), which acknowledges and centers Chicana/Latina scholars way of knowing and knowledge (Fierros & Delgado Bernal, 2016). This study is based on twenty four Latinx premed students from a large research university, an emerging Hispanic-Serving Institution. Each participant completed two pláticas, for a total of forty-eight pláticas, observations of the Latinx PremedInitiative sessions and website content review of activities.Findings are presented in the three articles focusing on cultural assets of Latinx students during their undergraduate years, such as navigational, resistance, giving back and a methodological article. This study presents novel findings of the use of cultural assets of Latinx students in premedical studies. Latinx premedical students use the following, navigational and resistance asset as they navigated the COVID-19 pandemic and giving back asset is related to student’s physician career aspirations to serve underserved communities and address health inequities. Additionally, pláticas methodology is introduced to call for a reframing of methodologies in STEM education research to provide a culturally relevant methodology to engage Latinx Students and advance STEM education research on Latinx students. Research on Latinx STEM students has focused on the attrition of Latinx students in STEM, however I find that Latinx students are persisting and creating meaningful pathways for themselves that is inclusive of their cultural background.This dissertation is significant because it provides an asset-based approach and culturally sensitive use of pláticas on Latinx students to identify the cultural assets Latinx students use as they persists towards medical school. I also provide recommendations for institutions of higher education to embrace and leverage cultural assets, to reimagine graduatepathways for Latinx students to persist towards their medical dreams.

  • Open Access English
    Authors: 
    Brizzi, Andrea; Whittaker, Charles; Servo, Luciana MS; Hawryluk, Iwona; Prete, Carlos A; de Souza, William M; Aguiar, Renato S; Araujo, Leonardo JT; Bastos, Leonardo S; Blenkinsop, Alexandra; +31 more
    Country: Belgium

    The SARS-CoV-2 Gamma variant spread rapidly across Brazil, causing substantial infection and death waves. We use individual-level patient records following hospitalisation with suspected or confirmed COVID-19 to document the extensive shocks in hospital fatality rates that followed Gamma's spread across 14 state capitals, and in which more than half of hospitalised patients died over sustained time periods. We show that extensive fluctuations in COVID-19 in-hospital fatality rates also existed prior to Gamma's detection, and were largely transient after Gamma's detection, subsiding with hospital demand. Using a Bayesian fatality rate model, we find that the geographic and temporal fluctuations in Brazil's COVID-19 in-hospital fatality rates are primarily associated with geographic inequities and shortages in healthcare capacity. We project that approximately half of Brazil's COVID-19 deaths in hospitals could have been avoided without pre-pandemic geographic inequities and without pandemic healthcare pressure. Our results suggest that investments in healthcare resources, healthcare optimization, and pandemic preparedness are critical to minimize population wide mortality and morbidity caused by highly transmissible and deadly pathogens such as SARS-CoV-2, especially in low- and middle-income countries. NOTE: The following manuscript has appeared as 'Report 46 - Factors driving extensive spatial and temporal fluctuations in COVID-19 fatality rates in Brazilian hospitals' at https://spiral.imperial.ac.uk:8443/handle/10044/1/91875 . ONE SENTENCE SUMMARY: COVID-19 in-hospital fatality rates fluctuate dramatically in Brazil, and these fluctuations are primarily associated with geographic inequities and shortages in healthcare capacity. ispartof: medRxiv ispartof: medRxiv ispartof: location:United States status: Published online

  • Open Access
    Authors: 
    Dudas, Gytis; Bedford, Trevor;
    Publisher: figshare
    Project: NIH | Real-time tracking of vir... (5R35GM119774-03)

    Additional file 5 Maximum likelihood inference of masked sequence location from genomes (left) and GP sequences (right) via a CTMC model implemented in TreeTime. Horizontal bars indicate the posterior distribution of masked tip locations coloured by country (Sierra Leone in blue, Liberia in red, Guinea in green) and location (lighter colours indicate administrative divisions lying towards west of the country). The correct location of each tip is outlined in white with the smaller plot to the right showing only the probability of the correct location. Bars marked with an open circle indicate cases where the correct location is within the 95% credible set and solid circles indicate cases where the location with the most probability is also the correct location. Genomes still perform better in terms of correct guess (0.432 probability that best guess location is true location for genomes versus 0.259 for GP), cross entropy (12012.800 nats for genome versus 24397.109 nats for GP) and mean probability-weighted great circle distance between true location population centroid and estimated location population centroid (87.568 km for genome versus 124.909 km for GP).

  • Open Access English
    Authors: 
    Van Puyvelde, Bart; Van Uytfanghe, Katleen; Van Oudenhove, Laurence; Gabriels, Ralf; Van Royen, Tessa; Matthys, Arne; Razavi, Morteza; Yip, Richard; Pearson, Terry; van Hulle, Marijn; +11 more
    Country: Belgium

    INTRODUCTION The pandemic readiness toolbox needs to be extended, providing diagnostic tools that target different biomolecules, using orthogonal experimental setups and fit-for-purpose specification of detection. Here we build on a previous Cov-MS effort that used liquid chromatography-mass spectrometry (LC-MS) and describe a method that allows accurate, high throughput measurement of SARS-CoV-2 nucleocapsid (N) protein. MATERIALS and METHODS We used Stable Isotope Standards and Capture by Anti-Peptide Antibodies (SISCAPA) technology to enrich and quantify proteotypic peptides of the N protein from trypsin-digested samples from COVID-19 patients. RESULTS The Cov2MS assay was shown to be compatible with a variety of sample matrices including nasopharyngeal swabs, saliva and blood plasma and increased the sensitivity into the attomole range, up to a 1000-fold increase compared to direct detection in matrix. In addition, a strong positive correlation was observed between the SISCAPA antigen assay and qPCR detection beyond a quantification cycle (Cq) of 30-31, the level where no live virus can be cultured from patients. The automatable “addition only” sample preparation, digestion protocol, peptide enrichment and subsequent reduced dependency upon LC allow analysis of up to 500 samples per day per MS instrument. Importantly, peptide enrichment allowed detection of N protein in a pooled sample containing a single PCR positive sample mixed with 31 PCR negative samples, without loss in sensitivity. MS can easily be multiplexed and we also propose target peptides for Influenza A and B virus detection. CONCLUSIONS The Cov2MS assay described is agnostic with respect to the sample matrix or pooling strategy used for increasing throughput and can be easily multiplexed. Additionally, the assay eliminates interferences due to protein-protein interactions including those caused by anti-virus antibodies. The assay can be adapted to test for many different pathogens and could provide a tool enabling longitudinal epidemiological monitoring of large numbers of pathogens within a population, applied as an early warning system.

  • Open Access English
    Authors: 
    Saslavsky, Daniel; Rastogi, Cordula;
    Publisher: World Bank, Washington, DC
    Country: United States

    Air connectivity is at the center of the COVID-19 (Coronavirus) crisis. Global air cargo capacity has dropped substantially since most commercial passenger flights have been cancelled or grounded worldwide. Air cargo operators are trying to satisfy the existing demand, and also support pandemic-related relief efforts, mostly with freighters, and also with repurposed passenger widebody aircrafts (carrying freight in the main cabin). The economic impact for developing countries is likely to be felt directly through the loss of cargo capacity and skyrocketing air cargo rates, as well as cascading effects from all-cargo operations. Governments should coordinate and work with industry to ease regulatory and operational restrictions on air cargo operations to ensure market access, essential operations, and timely turnaround at airports and hubs. Many passenger airlines (responsible for hauling half of air cargo globally) will require financial support or restructuring, in a context of prolonged revenue starvation and assets’ immobility.

Advanced search in
Research products
arrow_drop_down
Searching FieldsTerms
Any field
arrow_drop_down
includes
arrow_drop_down
Include:
1,274 Research products, page 1 of 128
  • Open Access
    Authors: 
    World Bank;
    Publisher: Washington, DC: World Bank
    Country: United States

    Although global economic activity is recovering and output in Europe and Central Asia (ECA) is expected to grow in 2021, containing COVID-19 remains a challenge in the region. Enterprise survey data for the emerging and developing countries in the region show that COVID-19 had a profound and heterogeneous impact on firms. Smaller, younger, and female-run businesses were hit harder and had greater difficulty recovering. But the crisis also played a cleansing role and economic activity in ECA appears to have been reallocated toward more productive firms during the crisis, particularly in countries with more competitive markets. Firms with high pre-crisis labor productivity experienced significantly smaller drops in sales and employment than firms with low pre-crisis labor productivity and were also more likely to adapt to the crisis by increasing online activity and remote work. Many governments in ECA implemented broad policy support schemes to address the initial economic fallout from the crisis. Overall, this government support was more likely to go to less productive and larger firms, regardless of the level of their pre-crisis innovation. As economies enter the economic recovery phase, it will be important for policy makers in all countries to phase out broad policy support measures as soon as appropriate and focus on fostering a competitive business environment, which is key to a strong recovery, resilience to future crises, and sustainable, long-term economic growth.

  • Open Access English
    Authors: 
    Jue, Erik; Ismagilov, Rustem F.;
    Country: United States

    In response to the rapidly evolving COVID-19 pandemic, the U.S. Food and Drug Administration (FDA) has rapidly issued 49 emergency use authorizations (EUAs) for SARS-CoV-2 in vitro diagnostic test-kits. A critical metric in the performance evaluation for a diagnostic test kit is the analytical sensitivity, which is measured by the limit of detection (LOD). Commercial RNA stocks with known titers are used to determine LOD. We identified a problem with the titer reported for the commercial stocks when examining the analytical sensitivity of the reverse transcription quantitative PCR (RT-qPCR) protocol that is recommended by the Centers for Disease Control and Prevention (CDC) using plasmid DNA from Integrated DNA Technologies (IDT), synthetic RNA from BEI Resources (BEI), and extracted genomic RNA from BEI. We detected 3/3 positives for reactions containing synthetic RNA at a concentration of 0.1 copies/reaction (based on the supplier's label concentration). The apparent better-than-single-molecule performance is a statistically highly unlikely event, indicating a potential inaccuracy in the supplier's quantification of the stock material. Using an ultrasensitive and precise assay, reverse transcription digital PCR (RT-dPCR), we independently quantified concentrations of commercial SARS-CoV-2 plasmid DNA and SARS-CoV-2 RNA stocks. For plasmid DNA, the actual concentration measured by RT-dPCR was 11% of the nominal label concentration. For synthetic RNA, the actual concentration measured by RT-dPCR for one lot was 770% of the label concentration and for a different lot was 57% of the label concentration. For genomic RNA, the concentration measured by RT-dPCR for one lot was 240% of the label concentration and for a different lot it was 300% of the label concentration. This SARS-CoV-2 genomic RNA from BEI Resources has been used in at least 11 approved FDA Emergency Use Authorizations as of April 27, 2020. Such deviations of reported RNA or DNA stock concentrations from true concentrations can result in inaccurate quantification and calculation of LOD. Precise and accurate reporting of DNA and RNA stock concentrations by commercial suppliers will enable accurate quantification of assay performance, which is urgently needed to improve evaluation of different assays by diagnostic developers and regulatory bodies.

  • Open Access English
    Authors: 
    Bracken, Colton;
    Publisher: eScholarship, University of California
    Country: United States

    Antibodies and antibody-like molecules are broadly used as biochemical reagents and therapeutics. They are highly valued as probes that can distinguish between protein targets with extraordinary molecular detail. A deep understanding of natural antibody structure and function has enabled the development of fully synthetic human antibody libraries for in vitro display. These synthetic libraries recapitulate the sophistication of molecular recognition in antibody complementarity determining regions (CDRs) and in vitro display permits exquisite control over selection conditions. Thus, protein engineers can tailor-make antibodies to bind challenging and non-conventional targets.Here, we describe three examples of protein engineering that leverage synthetic antibody libraries and in vitro display technologies to generate binders to novel epitopes. In Chapter 1, we utilize recombinant antibody pairs to target the post-translational modification (PTM) phosphotyrosine (pY) in folded protein epitopes. In Chapter 2, we develop and deploy a single-domain antibody (sdAb) library to rapidly identify inhibitors to SARS-CoV-2 viral entry. In Chapter 3, we utilize chemo-epitope specific sdAbs to create small-molecule-dependent switches and further engineer them to control cellular therapies.

  • Open Access English
    Authors: 
    Rakka, Mariam;
    Publisher: eScholarship, University of California
    Country: United States

    In-Memory Computing (IMC) is considered a great candidate to replace the von-Neumann computing architecture to overcome the memory wall. Content Addressable Memories (CAMs) are the main building blocks in IMC-based architectures, such as the associative processors, and they are being used to accelerate machine learning tasks such as inference on Decision Trees (DTs). Decision trees are popular and powerful tools for data classification. Accelerating the decision tree search is crucial for on-the-edge applications that have limited power and latency budget. In this paper, we first present a juxtaposition between the capacitive and resistive sensing schemes in 2 Transistor-2 Resistive (2T-2R) Ternary CAMs (TCAMs). A Figure of Merit (FOM), function of the dynamic range, latency, and energy, is defined to have a fair comparison between the two sensing techniques. A mathematical model for the transient behavior of both sensing schemes is derived and verified through SPICE simulations. We then study the performance of the two schemes with an in-memory addition application and the results reveal that resistive sensing has an edge in that context. In addition, we propose a CAM Compiler for DT inference acceleration. In particular, we propose a novel ”adaptive-precision” scheme that results in a compact implementation and enables an efficient bijective mapping to TCAMs while maintaining high inference accuracies. Also, a Resistive-CAM (ReCAM) functional synthesizer is developed for mapping the decision tree to the ReCAM arrays with the capacitive sensing scheme and performing functional simulations for energy, latency, and accuracy evaluations. We study the decision tree accuracy under hardware non-idealities including device defects, manufacturing variability, and input encoding noise. We test our framework on various DT datasets including Give Me Some Credit, Titanic, and COVID-19. Our results reveal up to 42.4% energy savings and up to 17.8x better energy-delay-area product compared to the state-of-art hardware accelerators and up to 333 million decisions per sec for the pipelined implementation.

  • Open Access English
    Authors: 
    Bachas, Pierre; Brockmeyer, Anne; Harris, Tom; Semelet, Camille;
    Publisher: World Bank, Washington, DC
    Country: United States

    The COVID19 (coronavirus) pandemic and associated containment measures are expected to cause far-reaching damage to economies around the world. Firms are suffering from reduced demand due to movement restrictions, from reduced labor supply and from constraints to sourcing material inputs. The breakup of otherwise healthy businesses in response to a temporary shock implies large social costs. Governments are therefore intent on designing emergency policies to keep businesses afloat. In this brief, the authors present simulations using firm-level tax records from Ethiopia, which vary the duration of the lockdown and the relative impact across sectors.

  • Open Access English
    Authors: 
    Garcia, Katherine Arias;
    Publisher: eScholarship, University of California
    Country: United States

    Only 5% of the graduates from medical schools identify as Latinx (AAMC, 2019). While, in the state of California, the growing Latinx and bilingual community is expected to exceed 40% of the state’s population with only 5% Latinx physicians (Martinez et al., 2019). Diversity of the physician workforce is important because underrepresented students are more likely to work as a physician in underserved communities, such as urban and rural communities (Mitchell & Lassiter, 2006). The field of higher education is lacking research on Latinx student persistence in premedical studies in higher education. Moreover, the literature on underrepresented STEM students is lacking an analysis of the cultural assets that Students of Color bring with them into STEM. Through this dissertation, I advance STEM research by applying asset-based theoretical frameworks and culturally relevant methodology in order to center Latinx first-generation premedical students voices and experiences. Guided by the following theories, Community Cultural Wealth (CCW) (Yosso, 2005), Latinx STEM Student Success Model (Rendón et al., 2019) and Chicana/Latina Feminist Epistemology (Fierros & Delgado Bernal, 2016), this dissertation aims to take on an assetbased approach and use culturally-sensitive methodology to understand the persistence of Latinx students in medicine. Yosso’s CCW (2005) provides a foundation in viewing students of color entering the college environment with cultural assets and to further center Latinx premedical students, the Latinx Student STEM Success Model (Rendón et al., 2019) is applied to explore Latinx cultural assets, strengths developed from families/communities and knowledge that Latinx students have gained that are related to the Latinx asset (Rendón, Nora & Kanagala, 2014). Additionally, I employ pláticas, a culturally-sensitive methodology that draws from Chicana/Latina Feminist Epistemology (Fierros & Delgado Bernal, 2016), which acknowledges and centers Chicana/Latina scholars way of knowing and knowledge (Fierros & Delgado Bernal, 2016). This study is based on twenty four Latinx premed students from a large research university, an emerging Hispanic-Serving Institution. Each participant completed two pláticas, for a total of forty-eight pláticas, observations of the Latinx PremedInitiative sessions and website content review of activities.Findings are presented in the three articles focusing on cultural assets of Latinx students during their undergraduate years, such as navigational, resistance, giving back and a methodological article. This study presents novel findings of the use of cultural assets of Latinx students in premedical studies. Latinx premedical students use the following, navigational and resistance asset as they navigated the COVID-19 pandemic and giving back asset is related to student’s physician career aspirations to serve underserved communities and address health inequities. Additionally, pláticas methodology is introduced to call for a reframing of methodologies in STEM education research to provide a culturally relevant methodology to engage Latinx Students and advance STEM education research on Latinx students. Research on Latinx STEM students has focused on the attrition of Latinx students in STEM, however I find that Latinx students are persisting and creating meaningful pathways for themselves that is inclusive of their cultural background.This dissertation is significant because it provides an asset-based approach and culturally sensitive use of pláticas on Latinx students to identify the cultural assets Latinx students use as they persists towards medical school. I also provide recommendations for institutions of higher education to embrace and leverage cultural assets, to reimagine graduatepathways for Latinx students to persist towards their medical dreams.

  • Open Access English
    Authors: 
    Brizzi, Andrea; Whittaker, Charles; Servo, Luciana MS; Hawryluk, Iwona; Prete, Carlos A; de Souza, William M; Aguiar, Renato S; Araujo, Leonardo JT; Bastos, Leonardo S; Blenkinsop, Alexandra; +31 more
    Country: Belgium

    The SARS-CoV-2 Gamma variant spread rapidly across Brazil, causing substantial infection and death waves. We use individual-level patient records following hospitalisation with suspected or confirmed COVID-19 to document the extensive shocks in hospital fatality rates that followed Gamma's spread across 14 state capitals, and in which more than half of hospitalised patients died over sustained time periods. We show that extensive fluctuations in COVID-19 in-hospital fatality rates also existed prior to Gamma's detection, and were largely transient after Gamma's detection, subsiding with hospital demand. Using a Bayesian fatality rate model, we find that the geographic and temporal fluctuations in Brazil's COVID-19 in-hospital fatality rates are primarily associated with geographic inequities and shortages in healthcare capacity. We project that approximately half of Brazil's COVID-19 deaths in hospitals could have been avoided without pre-pandemic geographic inequities and without pandemic healthcare pressure. Our results suggest that investments in healthcare resources, healthcare optimization, and pandemic preparedness are critical to minimize population wide mortality and morbidity caused by highly transmissible and deadly pathogens such as SARS-CoV-2, especially in low- and middle-income countries. NOTE: The following manuscript has appeared as 'Report 46 - Factors driving extensive spatial and temporal fluctuations in COVID-19 fatality rates in Brazilian hospitals' at https://spiral.imperial.ac.uk:8443/handle/10044/1/91875 . ONE SENTENCE SUMMARY: COVID-19 in-hospital fatality rates fluctuate dramatically in Brazil, and these fluctuations are primarily associated with geographic inequities and shortages in healthcare capacity. ispartof: medRxiv ispartof: medRxiv ispartof: location:United States status: Published online

  • Open Access
    Authors: 
    Dudas, Gytis; Bedford, Trevor;
    Publisher: figshare
    Project: NIH | Real-time tracking of vir... (5R35GM119774-03)

    Additional file 5 Maximum likelihood inference of masked sequence location from genomes (left) and GP sequences (right) via a CTMC model implemented in TreeTime. Horizontal bars indicate the posterior distribution of masked tip locations coloured by country (Sierra Leone in blue, Liberia in red, Guinea in green) and location (lighter colours indicate administrative divisions lying towards west of the country). The correct location of each tip is outlined in white with the smaller plot to the right showing only the probability of the correct location. Bars marked with an open circle indicate cases where the correct location is within the 95% credible set and solid circles indicate cases where the location with the most probability is also the correct location. Genomes still perform better in terms of correct guess (0.432 probability that best guess location is true location for genomes versus 0.259 for GP), cross entropy (12012.800 nats for genome versus 24397.109 nats for GP) and mean probability-weighted great circle distance between true location population centroid and estimated location population centroid (87.568 km for genome versus 124.909 km for GP).

  • Open Access English
    Authors: 
    Van Puyvelde, Bart; Van Uytfanghe, Katleen; Van Oudenhove, Laurence; Gabriels, Ralf; Van Royen, Tessa; Matthys, Arne; Razavi, Morteza; Yip, Richard; Pearson, Terry; van Hulle, Marijn; +11 more
    Country: Belgium

    INTRODUCTION The pandemic readiness toolbox needs to be extended, providing diagnostic tools that target different biomolecules, using orthogonal experimental setups and fit-for-purpose specification of detection. Here we build on a previous Cov-MS effort that used liquid chromatography-mass spectrometry (LC-MS) and describe a method that allows accurate, high throughput measurement of SARS-CoV-2 nucleocapsid (N) protein. MATERIALS and METHODS We used Stable Isotope Standards and Capture by Anti-Peptide Antibodies (SISCAPA) technology to enrich and quantify proteotypic peptides of the N protein from trypsin-digested samples from COVID-19 patients. RESULTS The Cov2MS assay was shown to be compatible with a variety of sample matrices including nasopharyngeal swabs, saliva and blood plasma and increased the sensitivity into the attomole range, up to a 1000-fold increase compared to direct detection in matrix. In addition, a strong positive correlation was observed between the SISCAPA antigen assay and qPCR detection beyond a quantification cycle (Cq) of 30-31, the level where no live virus can be cultured from patients. The automatable “addition only” sample preparation, digestion protocol, peptide enrichment and subsequent reduced dependency upon LC allow analysis of up to 500 samples per day per MS instrument. Importantly, peptide enrichment allowed detection of N protein in a pooled sample containing a single PCR positive sample mixed with 31 PCR negative samples, without loss in sensitivity. MS can easily be multiplexed and we also propose target peptides for Influenza A and B virus detection. CONCLUSIONS The Cov2MS assay described is agnostic with respect to the sample matrix or pooling strategy used for increasing throughput and can be easily multiplexed. Additionally, the assay eliminates interferences due to protein-protein interactions including those caused by anti-virus antibodies. The assay can be adapted to test for many different pathogens and could provide a tool enabling longitudinal epidemiological monitoring of large numbers of pathogens within a population, applied as an early warning system.

  • Open Access English
    Authors: 
    Saslavsky, Daniel; Rastogi, Cordula;
    Publisher: World Bank, Washington, DC
    Country: United States

    Air connectivity is at the center of the COVID-19 (Coronavirus) crisis. Global air cargo capacity has dropped substantially since most commercial passenger flights have been cancelled or grounded worldwide. Air cargo operators are trying to satisfy the existing demand, and also support pandemic-related relief efforts, mostly with freighters, and also with repurposed passenger widebody aircrafts (carrying freight in the main cabin). The economic impact for developing countries is likely to be felt directly through the loss of cargo capacity and skyrocketing air cargo rates, as well as cascading effects from all-cargo operations. Governments should coordinate and work with industry to ease regulatory and operational restrictions on air cargo operations to ensure market access, essential operations, and timely turnaround at airports and hubs. Many passenger airlines (responsible for hauling half of air cargo globally) will require financial support or restructuring, in a context of prolonged revenue starvation and assets’ immobility.

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