Atlantic Ocean Heat Transport Enabled by Indo-Pacific Heat Uptake and Mixing

The ocean transports vast amounts of heat around the planet, helping to regulate regional climate. One important component of this heat transport is the movement of warm water from equatorial regions toward the poles, with colder water flowing in return. Here, we introduce a framework relating meridional heat transport to the diabatic processes of surface forcing and turbulent mixing that move heat across temperature classes. Applied to a (1/4)° global ocean model the framework highlights the role of the tropical Indo‐Pacific in the global ocean heat transport. A large fraction of the northward heat transport in the Atlantic is ultimately sourced from heat uptake in the eastern tropical Pacific. Turbulent mixing moves heat from the warm, shallow Indo‐Pacific circulation to the cold deeper‐reaching Atlantic circulation. Our results underscore a renewed focus on the tropical oceans and their role in global circulation pathways

The influence of warming patterns on passive ocean heat uptake

The climate's response to forcing depends on how efficiently heat is absorbed by the ocean. Much, if not most, of this ocean heat uptake results from the passive transport of warm surface waters into the ocean's interior. Here we examine how geographic patterns of surface warming influence the efficiency of this passive heat uptake process. We show that the average pattern of surface warming in CMIP5 damps passive ocean heat uptake efficiency by nearly 25%, as compared to homogeneous surface warming. This “pattern effect” occurs because strong ventilation and weak surface warming are robustly colocated, particularly in the Southern Ocean. However, variations in warming patterns across CMIP5 do not drive significant ensemble spread in passive ocean heat uptake efficiency. This spread is likely linked to intermodel differences in ocean circulation, which our idealized results suggest may be dominated by differences in Southern Ocean and subtropical ventilation processes

Atlantic Ocean Heat Transport Enabled by Indo-Pacific Heat Uptake and Mixing

The ocean transports vast amounts of heat around the planet, helping to regulate regional climate. One important component of this heat transport is the movement of warm water from equatorial regions toward the poles, with colder water flowing in return. Here, we introduce a framework relating meridional heat transport to the diabatic processes of surface forcing and turbulent mixing that move heat across temperature classes. Applied to a (1/4)° global ocean model the framework highlights the role of the tropical Indo‐Pacific in the global ocean heat transport. A large fraction of the northward heat transport in the Atlantic is ultimately sourced from heat uptake in the eastern tropical Pacific. Turbulent mixing moves heat from the warm, shallow Indo‐Pacific circulation to the cold deeper‐reaching Atlantic circulation. Our results underscore a renewed focus on the tropical oceans and their role in global circulation pathways

The transcriptome of the endometrium and placenta is associated with pregnancy development but not lactation status in dairy cows

peer-reviewedInfertility in lactating dairy cows is explained partially by the metabolic state associated with high milk production. The hypothesis was that lactating and nonlactating cows would differ in endometrial and placental transcriptomes during early pregnancy (day 28 to 42) and this difference would explain the predisposition for lactating cows to have embryonic loss at that time. Cows were either milked or not milked after calving. Reproductive [endometrium (caruncular and intercaruncular) and placenta] and liver tissues were collected on day 28, 35, and 42 of pregnancy. The hypothesis was rejected because no effect of lactation on mRNA abundance within reproductive tissues was found. Large differences within liver demonstrated the utility of the model to test an effect of lactation on tissue gene expression. Major changes in gene expression in reproductive tissues across time were found. Greater activation of the transcriptome for the recruitment and activation of macrophages was found in the endometrium and placenta. Changes in glucose metabolism between day 28 and 42 included greater mRNA abundance of rate-limiting genes for gluconeogenesis in intercaruncular endometrium and evidence for the establishment of aerobic glycolysis (Warburg effect) in the placenta. Temporal changes were predicted to be controlled by CSF1, PDGFB, TGFB1, and JUN. Production of nitric oxide and reactive oxygen species by macrophages was identified as a mechanism to promote angiogenesis in the endometrium. Reported differences in pregnancy development for lactating vs. nonlactating cows could be explained by systemic glucose availability to the conceptus and appeared to be independent of the endometrial and placental transcriptomes

X-Ray-Emitting Stars Identified from the ROSAT All-Sky Survey and the Sloan Digital Sky Survey

The ROSAT All-Sky Survey (RASS) was the first imaging X-ray survey of the entire sky. While X-ray source counterparts are known to range from distant quasars to nearby M dwarfs, the RASS data alone are often insufficient to determine the nature of an X-ray source. As a result, large-scale follow-up programs are required to construct samples of known X-ray emitters. We use optical data produced by the Sloan Digital Sky Survey (SDSS) to identify 709 stellar X-ray emitters cataloged in the RASS and falling within the SDSS Data Release 1 footprint. Most of these are bright stars with coronal X-ray emission unsuitable for SDSS spectroscopy, which is designed for fainter objects (g > 15 mag). Instead, we use SDSS photometry, correlations with the Two Micron All Sky Survey and other catalogs, and spectroscopy from the Apache Point Observatory 3.5 m telescope to identify these stellar X-ray counterparts. Our sample of 707 X-ray-emitting F, G, K, and M stars is one of the largest X-ray-selected samples of such stars. We derive distances to these stars using photometric parallax relations appropriate for dwarfs on the main sequence, and use these distances to calculate LX. We also identify a previously unknown cataclysmic variable (CV) as a RASS counterpart. Separately, we use correlations of the RASS and the SDSS spectroscopic catalogs of CVs and white dwarfs (WDs) to study the properties of these rarer X-ray-emitting stars. We examine the relationship between (fX/fg) and the equivalent width of the Hbeta emission line for 46 X-ray-emitting CVs and discuss tentative classifications for a subset based on these quantities. We identify 17 new X-ray-emitting DA (hydrogen) WDs, of which three are newly identified WDs. (abridged)Comment: 23 pages, 15 figures, 8 tables; full catalog available online onl

Mortality Among Adults With Cancer Undergoing Chemotherapy or Immunotherapy and Infected With COVID-19

Importance: Large cohorts of patients with active cancers and COVID-19 infection are needed to provide evidence of the association of recent cancer treatment and cancer type with COVID-19 mortality. // Objective: To evaluate whether systemic anticancer treatments (SACTs), tumor subtypes, patient demographic characteristics (age and sex), and comorbidities are associated with COVID-19 mortality. // Design, Setting, and Participants: The UK Coronavirus Cancer Monitoring Project (UKCCMP) is a prospective cohort study conducted at 69 UK cancer hospitals among adult patients (≥18 years) with an active cancer and a clinical diagnosis of COVID-19. Patients registered from March 18 to August 1, 2020, were included in this analysis. // Exposures: SACT, tumor subtype, patient demographic characteristics (eg, age, sex, body mass index, race and ethnicity, smoking history), and comorbidities were investigated. // Main Outcomes and Measures: The primary end point was all-cause mortality within the primary hospitalization. // Results: Overall, 2515 of 2786 patients registered during the study period were included; 1464 (58%) were men; and the median (IQR) age was 72 (62-80) years. The mortality rate was 38% (966 patients). The data suggest an association between higher mortality in patients with hematological malignant neoplasms irrespective of recent SACT, particularly in those with acute leukemias or myelodysplastic syndrome (OR, 2.16; 95% CI, 1.30-3.60) and myeloma or plasmacytoma (OR, 1.53; 95% CI, 1.04-2.26). Lung cancer was also significantly associated with higher COVID-19–related mortality (OR, 1.58; 95% CI, 1.11-2.25). No association between higher mortality and receiving chemotherapy in the 4 weeks before COVID-19 diagnosis was observed after correcting for the crucial confounders of age, sex, and comorbidities. An association between lower mortality and receiving immunotherapy in the 4 weeks before COVID-19 diagnosis was observed (immunotherapy vs no cancer therapy: OR, 0.52; 95% CI, 0.31-0.86). // Conclusions and Relevance: The findings of this study of patients with active cancer suggest that recent SACT is not associated with inferior outcomes from COVID-19 infection. This has relevance for the care of patients with cancer requiring treatment, particularly in countries experiencing an increase in COVID-19 case numbers. Important differences in outcomes among patients with hematological and lung cancers were observed

An international effort towards developing standards for best practices in analysis, interpretation and reporting of clinical genome sequencing results in the CLARITY Challenge

There is tremendous potential for genome sequencing to improve clinical diagnosis and care once it becomes routinely accessible, but this will require formalizing research methods into clinical best practices in the areas of sequence data generation, analysis, interpretation and reporting. The CLARITY Challenge was designed to spur convergence in methods for diagnosing genetic disease starting from clinical case history and genome sequencing data. DNA samples were obtained from three families with heritable genetic disorders and genomic sequence data were donated by sequencing platform vendors. The challenge was to analyze and interpret these data with the goals of identifying disease-causing variants and reporting the findings in a clinically useful format. Participating contestant groups were solicited broadly, and an independent panel of judges evaluated their performance. RESULTS: A total of 30 international groups were engaged. The entries reveal a general convergence of practices on most elements of the analysis and interpretation process. However, even given this commonality of approach, only two groups identified the consensus candidate variants in all disease cases, demonstrating a need for consistent fine-tuning of the generally accepted methods. There was greater diversity of the final clinical report content and in the patient consenting process, demonstrating that these areas require additional exploration and standardization. CONCLUSIONS: The CLARITY Challenge provides a comprehensive assessment of current practices for using genome sequencing to diagnose and report genetic diseases. There is remarkable convergence in bioinformatic techniques, but medical interpretation and reporting are areas that require further development by many groups

Where Did I Go Wrong with My Model? Ten Tips for Getting Results in SEM

Those new to structural equation modeling (SEM) often encounter problems with convergence, software errors, or poor fitting models. Some basic suggestions are offered to help reduce these problems and avoid some common error messages encountered when first testing models. The tips concern initial data management steps, specification of latent variables, avoidance of factor identification problems, special precautions when estimating means, addressing poor measurement model fit, using multistep testing, fitting full structural models, attentiveness to interpretation pitfalls, and troubleshooting software warnings and errors. The advice provided is intended to help save time, effort, and trials and tribulations often encountered by beginner modelers

Increasing the usability of climate science in political decision-making

Abstract As climate-science graduate students at the University of Washington, we had the opportunity to engage in a political process focused on implementing legislation to reduce greenhouse gas emissions in Washington State. Our insights gained from this rare, first-hand, experience may be particularly relevant to other climate scientists. We argue that inflexible research goals within the United States climate-science community limit the relevance of the knowledge our community creates. The mismatch between climate-science research and the information needs of policy makers, while widely acknowledged in certain domains, has yet to be fully appreciated within many earth science disciplines. Broadening the climate-science training of graduate students to include education on the uses of climate information outside of academic settings would both inform and motivate new research directions, and engender validation of non-traditional research within disciplinary cultures