Search

Aim Megathermal rain forests and mangroves are much smaller in extent today than in the early Cenozoic, primarily owing to global cooling and drying trends since the Eocene–Oligocene transition (c. 34 Ma). The general reduction of these biomes is hypothesized to shape the diversity and biogeographical history of tropical plant clades. However, this has rarely been examined owing to a paucity of good fossil records of tropical taxa and the difficulty in assigning them to modern clades. Here, we evaluate the role that Cenozoic climate change might have played in shaping the diversity and biogeography of tropical plants through time. Location Global. Time period Cenozoic, 66 Ma to present. Major taxa studied Four palm clades (Calaminae, Eugeissoneae, Mauritiinae and Nypoideae) and their fossil pollen record. Methods We compiled fossil pollen occurrence records for each focal palm lineage to reconstruct their diversity and biogeographical distribution throughout the Cenozoic. We use climatic niche models to project the distribution of climatically suitable areas for each lineage in the past, using palaeoclimatic data for the Cenozoic. Results For most palm lineages examined, global pollen taxonomic diversity declined throughout the Cenozoic. Geographical ranges for each focal lineage contracted globally and experienced regional-scale extinctions (e.g., Afrotropics), particularly after the Miocene. However, climatic niche models trained on extant species of these focal lineages often predict the presence of climatically suitable habitat in areas where these lineages went extinct. Main conclusions Globally, the decline in megathermal rain forest and mangrove extent might have led to declines in diversity and range contractions in some megathermal plant taxa throughout the Cenozoic. Although global climatic trends are an important backdrop for the biogeography and diversity of tropical groups at global scales, their continental- or regional-scale biogeographical trajectories might be more dependent on regional abiotic and biotic contexts.

As Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) continues to spread, characterization of its antibody epitopes, emerging strains, related coronaviruses, and even the human proteome in naturally infected patients can guide the development of effective vaccines and therapies. Since traditional epitope identification tools are dependent upon pre-defined peptide sequences, they are not readily adaptable to diverse viral proteomes. The Serum Epitope Repertoire Analysis (SERA) platform leverages a high diversity random bacterial display library to identify proteome-independent epitope binding specificities which are then analyzed in the context of organisms of interest. When evaluating immune response in the context of SARS-CoV-2, we identify dominant epitope regions and motifs which demonstrate potential to classify mild from severe disease and relate to neutralization activity. We highlight SARS-CoV-2 epitopes that are cross-reactive with other coronaviruses and demonstrate decreased epitope signal for mutant SARS-CoV-2 strains. Collectively, the evolution of SARS-CoV-2 mutants towards reduced antibody response highlight the importance of data-driven development of the vaccines and therapies to treat COVID-19., Using a high throughput, random bacterial peptide display approach applied to patient serum samples, Haynes, Kamath, Bozekowski et al identify the antigens and epitopes that elicit a SARS-CoV-2 humoral response. They identify differences depending on disease severity and further in silico analysis suggests decreased epitope signal for Q677P but not for D614G mutant SARSCoV-2 strains.

Background The COVID-19 pandemic has shined a harsh light on a critical deficiency in our health care system: our inability to access important information about patients’ values, goals, and preferences in the electronic health record (EHR). At Memorial Sloan Kettering Cancer Center (MSK), we have integrated and systematized health-related values discussions led by oncology nurses for newly diagnosed cancer patients as part of routine comprehensive cancer care. Such conversations include not only the patient’s wishes for care at the end of life but also more holistic personal values, including sources of strength, concerns, hopes, and their definition of an acceptable quality of life. In addition, health care providers use a structured template to document their discussions of patient goals of care. Objective To provide ready access to key information about the patient as a person with individual values, goals, and preferences, we undertook the creation of the Patient Values Tab in our center’s EHR to display this information in a single, central location. Here, we describe the interprofessional, interdisciplinary, iterative process and user-centered design methodology that we applied to build this novel functionality as well as our initial implementation experience and plans for evaluation. Methods We first convened a working group of experts from multiple departments, including medical oncology, health informatics, information systems, nursing informatics, nursing education, and supportive care, and a user experience designer. We conducted in-depth, semistructured, audiorecorded interviews of over 100 key stakeholders. The working group sought consensus on the tab’s main content, homing in on high-priority areas identified by the stakeholders. The core content was mapped to various EHR data sources. We established a set of high-level design principles to guide our process. Our user experience designer then created wireframes of the tab design. The designer conducted usability testing with physicians, nurses, and other health professionals. Data validation testing was conducted. Results We have already deployed the Patient Values Tab to a pilot sample of users in the MSK Gastrointestinal Medical Oncology Service, including physicians, advanced practice providers, nurses, and administrative staff. We have early evidence of the positive impact of this EHR innovation. Audit logs show increasing use. Many of the initial user comments have been enthusiastically positive, while others have provided constructive suggestions for additional tab refinements with respect to format and content. Conclusions It is our challenge and obligation to enrich the EHR with information about the patient as a person. Realization of this capability is a pressing public health need requiring the collaboration of technological experts with a broad range of clinical leaders, users, patients, and families to achieve solutions that are both principled and practical. Our new Patient Values Tab represents a step forward in this important direction.

Despite the high level of morbidity and mortality worldwide, there is increasing evidence for asymptomatic carriers of the novel coronavirus SARS-CoV-2. We analyzed blood specimens from 1,559 healthy blood donors, collected in the greater New York metropolitan area between the months of March and July 2020 for antibodies to SARS-CoV-2 virus. Using our proprietary technology, SERA (Serum Epitope Repertoire Analysis), we observed a significant increase in SARS-CoV-2 seropositivity rates over the four-month period, from 0% [95% CI: 0 - 1.5%] (March) to 11.6% [6.0 - 21.2%] (July). Follow-up ELISA tests using S1 and nucleocapsid viral proteins confirmed most of these results. Our findings are consistent with seroprevalence studies within the region and with reports that SARS-COV-2 infections can be asymptomatic or cause only mild symptoms.IMPORTANCEThe COVID-19 pandemic, caused by the novel coronavirus SARS-CoV-2, has caused vast morbidity and mortality worldwide, yet several studies indicate that there may be a significant number of infected people who are asymptomatic or exhibit mild symptoms. In this study, samples were collected from healthy blood donors in a region of rapidly increasing disease burden (New York metropolitan area) and we hypothesized that a subset would be seropositive to SARS-CoV-2. People who experienced mild or no symptoms during SARS-CoV-2 infection may represent a source for convalescent plasma donors.

BACKGROUND The COVID-19 pandemic has shined a harsh light on a critical deficiency in our health care system: our inability to access important information about patients’ values, goals, and preferences in the electronic health record (EHR). At Memorial Sloan Kettering Cancer Center (MSK), we have integrated and systematized health-related values discussions led by oncology nurses for newly diagnosed cancer patients as part of routine comprehensive cancer care. Such conversations include not only the patient’s wishes for care at the end of life but also more holistic personal values, including sources of strength, concerns, hopes, and their definition of an acceptable quality of life. In addition, health care providers use a structured template to document their discussions of patient goals of care. OBJECTIVE To provide ready access to key information about the patient as a person with individual values, goals, and preferences, we undertook the creation of the Patient Values Tab in our center’s EHR to display this information in a single, central location. Here, we describe the interprofessional, interdisciplinary, iterative process and user-centered design methodology that we applied to build this novel functionality as well as our initial implementation experience and plans for evaluation. METHODS We first convened a working group of experts from multiple departments, including medical oncology, health informatics, information systems, nursing informatics, nursing education, and supportive care, and a user experience designer. We conducted in-depth, semistructured, audiorecorded interviews of over 100 key stakeholders. The working group sought consensus on the tab’s main content, homing in on high-priority areas identified by the stakeholders. The core content was mapped to various EHR data sources. We established a set of high-level design principles to guide our process. Our user experience designer then created wireframes of the tab design. The designer conducted usability testing with physicians, nurses, and other health professionals. Data validation testing was conducted. RESULTS We have already deployed the Patient Values Tab to a pilot sample of users in the MSK Gastrointestinal Medical Oncology Service, including physicians, advanced practice providers, nurses, and administrative staff. We have early evidence of the positive impact of this EHR innovation. Audit logs show increasing use. Many of the initial user comments have been enthusiastically positive, while others have provided constructive suggestions for additional tab refinements with respect to format and content. CONCLUSIONS It is our challenge and obligation to enrich the EHR with information about the patient as a person. Realization of this capability is a pressing public health need requiring the collaboration of technological experts with a broad range of clinical leaders, users, patients, and families to achieve solutions that are both principled and practical. Our new Patient Values Tab represents a step forward in this important direction.

The advancing art of microsimulation modeling is driving a growing interest in vehicle trajectory databases. These can be rich sources of travel information, providing origin–destination patterns, path choices, travel times or delays, and lane changing behavior. These metrics have historically been difficult to acquire, and even with the approach of the big-data era, it remains a challenge to collect high-quality, granular vehicle trajectory data. This paper describes how use of state-of-the-practice time-lapse aerial photography (TLAP), acquired continuously for up to several hours at 1-s frame rates, can produce trajectory data sets with high granularity. These surveys involve the use of airborne digital cameras held in stationary positions about one mile above the ground, to record the movement of virtually all highway vehicles in defined study areas. In this paper, TLAP’s differences from similar military imaging capabilities, such as wide-area motion imagery, are discussed, to explain how TLAP can be affordable for highway traffic studies. Then local survey design and execution for a study in the Phoenix, Arizona, area are presented. Flight and photography survey planning, image alignment, and data extraction methods are discussed; and study output and graphics are presented near the end. Big data someday will likely be magically able to supply all the field data needed for complex analysis or simulation of specific study areas; for now, however, 1-s TLAP can provide many of those benefits.

The comparison of related genomes has emerged as a powerful lens for genome interpretation. Here we report the sequencing and comparative analysis of 29 eutherian genomes. We confirm that at least 5.5% of the human genome has undergone purifying selection, and locate constrained elements covering ~4.2% of the genome. We use evolutionary signatures and comparisons with experimental data sets to suggest candidate functions for ~60% of constrained bases. These elements reveal a small number of new coding exons, candidate stop codon readthrough events and over 10,000 regions of overlapping synonymous constraint within protein-coding exons. We find 220 candidate RNA structural families, and nearly a million elements overlapping potential promoter, enhancer and insulator regions. We report specific amino acid residues that have undergone positive selection, 280,000 non-coding elements exapted from mobile elements and more than 1,000 primate- and human-accelerated elements. Overlap with disease-associated variants indicates that our findings will be relevant for studies of human biology, health and disease., National Human Genome Research Institute (U.S.), National Institute of General Medical Sciences (U.S.) (Grant number GM82901), National Science Foundation (U.S.). Postdoctural Fellowship (Award 0905968), National Science Foundation (U.S.). Career (0644282), National Institutes of Health (U.S.) (R01-HG004037), Alfred P. Sloan Foundation., Austrian Science Fund. Erwin Schrodinger Fellowship

One of the most common tasks you need to perform when working with a new database technology is importing and syncing data from another data source. This chapter explores what you should consider before beginning that process. It discusses the processes and tools for importing data into Neo4j and how to select the best process or tool for a specific situation.

This chapter will focus on using Spring Data Neo4j as well as creating a working application that integrates the five graph model types covered in Chapter 3. As with other languages that offer drivers for Neo4j, the integration takes place using a Neo4j server instance with Spring Data Neo4j (SDN) API and related libraries (henceforth referred to collectively as SDN. The chapter will be divided into the following topics

This chapter covers the requirements for running Neo4j as well as the steps for installing an instance of the Neo4j database on your computer. To set you on the path to mastering data management with Neo4j, I introduce the Neo4j Browser tool and walk you through the basics of the Neo4j query language, Cypher.

Purpose: This study examined the relationship between muscle glutamine, muscle glycogen, and plasma glutamine concentrations over 3 d of high-intensity exercise during which dietary carbohydrate (CHO) intake varied. Methods: Five endurance-trained men completed two exercise trials in randomized order, over a 14-d period. Each trial required subjects to perform 50 min of high-intensity continuous and interval exercise on three consecutive days while consuming a diet that provided 45% of the energy as CHO or a diet in which CHO provided 70% of the total energy. Four days of inactivity and consumption of a 55% CHO diet separated the two randomized trials. Menus and food were provided for the subjects and all food and drink consumed were weighed and recorded for later analysis. Before exercise on the first day of each trial, at the start of exercise on day 3 and on completion of exercise on day 3, muscle was biopsied from the vastus lateralis for the analysis of glutamine and glycogen concentrations. Venous blood was sampled before and twice after exercise on each day for the analysis of plasma glutamine and cortisol concentrations. Results: Mean plasma glutamine concentration was significantly higher during the 70% CHO exercise trial when compared with the 45% CHO trial (P < 0.05). Glycogen decreased by the same magnitude during both trials and there was no relationship between changes in plasma glutamine and changes in muscle glycogen concentration. Muscle glutamine concentration did not change in either trial. Conclusions: These data suggest that the influence of carbohydrate intake upon the concentration of plasma glutamine is not mediated through the concentration of intramuscular glycogen.