35 research outputs found

    The \u3cem\u3eChlamydomonas\u3c/em\u3e Genome Reveals the Evolution of Key Animal and Plant Functions

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    Chlamydomonas reinhardtii is a unicellular green alga whose lineage diverged from land plants over 1 billion years ago. It is a model system for studying chloroplast-based photosynthesis, as well as the structure, assembly, and function of eukaryotic flagella (cilia), which were inherited from the common ancestor of plants and animals, but lost in land plants. We sequenced the ∼120-megabase nuclear genome of Chlamydomonas and performed comparative phylogenomic analyses, identifying genes encoding uncharacterized proteins that are likely associated with the function and biogenesis of chloroplasts or eukaryotic flagella. Analyses of the Chlamydomonas genome advance our understanding of the ancestral eukaryotic cell, reveal previously unknown genes associated with photosynthetic and flagellar functions, and establish links between ciliopathy and the composition and function of flagella

    Global Carbon Budget 2023

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    Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere in a changing climate is critical to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe and synthesize data sets and methodology to quantify the five major components of the global carbon budget and their uncertainties. Fossil CO2 emissions (EFOS) are based on energy statistics and cement production data, while emissions from land-use change (ELUC), mainly deforestation, are based on land-use and land-use change data and bookkeeping models. Atmospheric CO2 concentration is measured directly, and its growth rate (GATM) is computed from the annual changes in concentration. The ocean CO2 sink (SOCEAN) is estimated with global ocean biogeochemistry models and observation-based f CO2 products. The terrestrial CO2 sink (SLAND) is estimated with dynamic global vegetation models. Additional lines of evidence on land and ocean sinks are provided by atmospheric inversions, atmospheric oxygen measurements, and Earth system models. The resulting carbon budget imbalance (BIM), the difference between the estimated total emissions and the estimated changes in the atmosphere, ocean, and terrestrial biosphere, is a measure of imperfect data and incomplete understanding of the contemporary carbon cycle. All uncertainties are reported as ±1σ. For the year 2022, EFOS increased by 0.9 % relative to 2021, with fossil emissions at 9.9 ± 0.5 Gt C yr−1 (10.2 ± 0.5 Gt C yr−1 when the cement carbonation sink is not included), and ELUC was 1.2 ± 0.7 Gt C yr−1, for a total anthropogenic CO2 emission (including the cement carbonation sink) of 11.1 ± 0.8 Gt C yr−1 (40.7±3.2 Gt CO2 yr−1). Also, for 2022, GATM was 4.6±0.2 Gt C yr−1 (2.18±0.1 ppm yr−1; ppm denotes parts per million), SOCEAN was 2.8 ± 0.4 Gt C yr−1, and SLAND was 3.8 ± 0.8 Gt C yr−1, with a BIM of −0.1 Gt C yr−1 (i.e. total estimated sources marginally too low or sinks marginally too high). The global atmospheric CO2 concentration averaged over 2022 reached 417.1 ± 0.1 ppm. Preliminary data for 2023 suggest an increase in EFOS relative to 2022 of +1.1 % (0.0 % to 2.1 %) globally and atmospheric CO2 concentration reaching 419.3 ppm, 51 % above the pre-industrial level (around 278 ppm in 1750). Overall, the mean of and trend in the components of the global carbon budget are consistently estimated over the period 1959–2022, with a near-zero overall budget imbalance, although discrepancies of up to around 1 Gt C yr−1 persist for the representation of annual to semi-decadal variability in CO2 fluxes. Comparison of estimates from multiple approaches and observations shows the following: (1) a persistent large uncertainty in the estimate of land-use changes emissions, (2) a low agreement between the different methods on the magnitude of the land CO2 flux in the northern extra-tropics, and (3) a discrepancy between the different methods on the strength of the ocean sink over the last decade. This living-data update documents changes in methods and data sets applied to this most recent global carbon budget as well as evolving community understanding of the global carbon cycle. The data presented in this work are available at https://doi.org/10.18160/GCP-2023 (Friedlingstein et al., 2023)

    On the probability of lymph node negativity in pN0-staged prostate cancer-a theoretically derived rule of thumb for adjuvant needs

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    PURPOSE: The extent of lymphadenectomy and clinical features influence the risk of occult nodes in node-negative prostate cancer. We derived a simple estimation model for the negative predictive value (npv) of histopathologically node-negative prostate cancer patients (pN0) to guide adjuvant treatment. METHODS: Approximations of sensitivities in detecting lymph node metastasis from current publications depending on the number of removed lymph nodes were used for a theoretical deduction of a simplified formulation of npv assuming a false node positivity of 0. RESULTS: A theoretical formula of npv = p(N0IpN0) = (100 − prevalence) / (100 − sensitivity × prevalence) was calculated (sensitivity and preoperative prevalence in %). Depending on the number of removed lymph nodes (nLN), the sensitivity of pN0-staged prostate cancer was derived for three sensitivity levels accordingly: sensitivity = f(nLN) = 9 × nLN /100 for 0 ≤ nLN ≤ 8 and f(nLN) = (nLN + 70) /100 for 9 ≤ nLN ≤ 29 and f(nLN) = 1 for nLN ≥ 30. CONCLUSION: We developed a theoretical formula for estimation of the npv in pN0-staged prostate cancer patients. It is a sine qua non to use the formula in a clinically experienced context before deciding to electively irradiate pelvic lymph nodes or to intensify adjuvant systemic treatment

    Complete and Incomplete Resection for Progressive Glioblastoma Prolongs Post-Progression Survival

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    OBJECTIVE: The role of resection in progressive glioblastoma (GBM) to prolong survival is still controversial. The aim of this study was to determine 1) the predictors of post-progression survival (PPS) in progressive GBM and 2) which subgroups of patients would benefit from recurrent resection. METHODS: We have conducted a retrospective bicentric cohort study on isocitrate dehydrogenase (IDH) wild-type GBM treated in our hospitals between 2006 and 2015. Kaplan-Maier analyses and univariable and multivariable Cox regressions were performed to identify predictors and their influence on PPS. RESULTS: Of 589 patients with progressive IDH wild-type GBM, 355 patients were included in analyses. Median PPS of all patients was 9 months (95% CI 8.0-10.0), with complete resection 12 months (95% CI 9.7-14.3, n=81), incomplete resection 11 months (95% CI 8.9-13.1, n=70) and without resection 7 months (95% CI 06-08, n=204). Multivariable Cox regression demonstrated a benefit for PPS with complete (HR 0.67, CI 0.49-0.90) and incomplete resection (HR 0.73, 95% CI 0.51-1.04) and confirmed methylation of the O6-methylguanine-DNA-methyltransferase (MGMT) gene promoter, lower age at diagnosis, absence of deep brain and multilocular localization, higher Karnofsky Performance Status (KPS) and recurrent therapies to be associated with longer PPS. In contrast, traditional eloquence and duration of progression-free survival had no effect on PPS. Subgroup analyses showed that all subgroups of confirmed predictors benefited from resection, except for patients in poor condition with a KPS <70. CONCLUSIONS: Out data suggest a role for complete and incomplete recurrent resection in progressive GBM patients regardless of methylation of MGMT, age, or adjuvant therapy but not in patients with a poor clinical condition with a KPS <70
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