Traces of Archaic Mitochondrial Lineages Persist in Austronesian-Speaking Formosan Populations

Genetic affinities between aboriginal Taiwanese and populations from Oceania and Southeast Asia have previously been explored through analyses of mitochondrial DNA (mtDNA), Y chromosomal DNA, and human leukocyte antigen loci. Recent genetic studies have supported the “slow boat” and “entangled bank” models according to which the Polynesian migration can be seen as an expansion from Melanesia without any major direct genetic thread leading back to its initiation from Taiwan. We assessed mtDNA variation in 640 individuals from nine tribes of the central mountain ranges and east coast regions of Taiwan. In contrast to the Han populations, the tribes showed a low frequency of haplogroups D4 and G, and an absence of haplogroups A, C, Z, M9, and M10. Also, more than 85% of the maternal lineages were nested within haplogroups B4, B5a, F1a, F3b, E, and M7. Although indicating a common origin of the populations of insular Southeast Asia and Oceania, most mtDNA lineages in Taiwanese aboriginal populations are grouped separately from those found in China and the Taiwan general (Han) population, suggesting a prevalence in the Taiwanese aboriginal gene pool of its initial late Pleistocene settlers. Interestingly, from complete mtDNA sequencing information, most B4a lineages were associated with three coding region substitutions, defining a new subclade, B4a1a, that endorses the origin of Polynesian migration from Taiwan. Coalescence times of B4a1a were 13.2 ± 3.8 thousand years (or 9.3 ± 2.5 thousand years in Papuans and Polynesians). Considering the lack of a common specific Y chromosomal element shared by the Taiwanese aboriginals and Polynesians, the mtDNA evidence provided here is also consistent with the suggestion that the proto-Oceanic societies would have been mainly matrilocal

Prediction of crop coefficients from fraction of ground cover and height. Background and validation using ground and remote sensing data

ReviewThe current study aims at reviewing and providing advances on methods for estimating and applying crop coefficients from observations of ground cover and vegetation height. The review first focuses on the relationships between single Kc and basal Kcb and various parameters including the fraction of ground covered by the canopy (fc), the leaf area index (LAI), the fraction of ground shaded by the canopy (fshad), the fraction of intercepted light (flight) and intercepted photosynthetic active radiation (fIPAR). These relationships were first studied in the 1970’s, for annual crops, and later, in the last decennia, for tree and vine perennials. Research has now provided a variety of methods to observe and measure fc and height (h) using both ground and remote sensing tools, which has favored the further development of Kc related functions. In the past, these relationships were not used predictively but to support the understanding of dynamics of Kc and Kcb in relation to the processes of evapotranspiration or transpiration, inclusive of the role of soil evaporation. Later, the approach proposed by Allen and Pereira (2009), the A&P approach, used fc and height (h) or LAI data to define a crop density coefficient that was used to directly estimate Kc and Kcb values for a variety of annual and perennial crops in both research and practice. It is opportune to review the A&P method in the context of a variety of studies that have derived Kc and Kcb values from field measured data with simultaneously observed ground cover fc and height. Applications used to test the approach include various tree and vine crops (olive, pear, and lemon orchards and vineyards), vegetable crops (pea, onion and tomato crops), field crops (barley, wheat, maize, sunflower, canola, cotton and soybean crops), as well as a grassland and a Bermudagrass pasture. Comparisons of Kcb values computed with the A &P method produced regression coefficients close to 1.0 and coefficients of determination≥0.90, except for orchards. Results indicate that the A&P approach can produce estimates of potential Kcb, using vegetation characteristics alone, within reasonable or acceptable error, and are useful for refining Kcb for conditions of plant spacing, size and density that differ from standard values. The comparisons provide parameters appropriate to applications for the tested crops. In addition, the A&P approach was applied with remotely sensed fc data for a variety of crops in California using the Satellite Irrigation Management Support (SIMS) framework. Daily SIMS crop ET (ETc-SIMS) produced Kcb values using the FAO56 and A&P approaches. Combination of satellite derived fc and Kcb values with ETo data from Spatial CIMIS (California Irrigation Management Information System) produced ET estimates that were compared with daily actual crop ET derived from energy balance calculations from micrometeorological instrumentation (ETc EB).Results produced coefficients of regression of 1.05 for field crops and 1.08 for woody crops, and R2 values of 0.81 and 0.91, respectively. These values suggest that daily ETc-SIMS -based ET can be accurately estimated within reasonable error and that the A&P approach is appropriate to support that estimation. It is likely that accuracy can be improved via progress in remote sensing determination of fc. Tabulated Kcb results and calculation parameters are presented in a companion paper in this Special Issueinfo:eu-repo/semantics/publishedVersio

Discerning Tumor Status from Unstructured MRI Reports—Completeness of Information in Existing Reports and Utility of Automated Natural Language Processing

Information in electronic medical records is often in an unstructured free-text format. This format presents challenges for expedient data retrieval and may fail to convey important findings. Natural language processing (NLP) is an emerging technique for rapid and efficient clinical data retrieval. While proven in disease detection, the utility of NLP in discerning disease progression from free-text reports is untested. We aimed to (1) assess whether unstructured radiology reports contained sufficient information for tumor status classification; (2) develop an NLP-based data extraction tool to determine tumor status from unstructured reports; and (3) compare NLP and human tumor status classification outcomes. Consecutive follow-up brain tumor magnetic resonance imaging reports (2000–­2007) from a tertiary center were manually annotated using consensus guidelines on tumor status. Reports were randomized to NLP training (70%) or testing (30%) groups. The NLP tool utilized a support vector machines model with statistical and rule-based outcomes. Most reports had sufficient information for tumor status classification, although 0.8% did not describe status despite reference to prior examinations. Tumor size was unreported in 68.7% of documents, while 50.3% lacked data on change magnitude when there was detectable progression or regression. Using retrospective human classification as the gold standard, NLP achieved 80.6% sensitivity and 91.6% specificity for tumor status determination (mean positive predictive value, 82.4%; negative predictive value, 92.0%). In conclusion, most reports contained sufficient information for tumor status determination, though variable features were used to describe status. NLP demonstrated good accuracy for tumor status classification and may have novel application for automated disease status classification from electronic databases

Prediction of crop coefficients from fraction of ground cover and height: Practical application to vegetable, field and fruit crops with focus on parameterization

Research PaperThe A&P approach, developed by Allen and Pereira (2009), estimates single and basal crop coefficients (Kc and Kcb) from the observed fraction of ground cover (fc) and crop height (h). The practical application of the A&P for several crops was reviewed and tested in a companion paper (Pereira et al., 2020). The current study further addresses the derivation of optimal values for A&P parameter values representing canopy transparency (ML) and stomatal adjustment (Fr), and tests the resulting model performance. Values reported in literature of ML and Fr were analysed. Optimal ML and Fr values were derived by a numerical search that minimized the differences between Kcb A&P with standard Kcb for vegetable, field, and fruit crops as tabulated by Pereira et al. (2021a, 2021b) and Rallo et al. (2021). Sources for fc were literature reviews supplemented by a remote sensing survey. Computed Kcb and Kc for mid- and end-season together with associated parameters values were tabulated. To improve the usability of the ML and Fr parameters a cross validation was performed, which consisted of the linear regression between Kcb computed by A&P and observed Kcb relative to independent data sets obtained from field observations. Results show that both series of Kcb match well, with regression coefficients very close to 1.0, coefficients of determination near 1.0, and root mean square errors (RMSE) of 0.06 for the annual crops and RMSE = 0.07 for the trees and vines. These errors represent less than 10% of most of the computed tabulated Kcb. The tabulated Fr and ML of this paper can be regarded as defaults to support A&P field practice when observations of fc and h are performed. Therefore, the A&P approach shows to be appropriate for use in irrigation scheduling and planning when fc and h are observed using ground and/or remote sensing, hence supporting irrigation water savingsinfo:eu-repo/semantics/publishedVersio

Genome-wide identification of Ago2 binding sites from mouse embryonic stem cells with and without mature microRNAs

MicroRNAs (miRNAs) are 19–22-nucleotide noncoding RNAs that post-transcriptionally regulate mRNA targets. We have identified endogenous miRNA binding sites in mouse embryonic stem cells (mESCs), by performing photo-cross-linking immunoprecipitation using antibodies to Argonaute (Ago2) followed by deep sequencing of RNAs (CLIP-seq). We also performed CLIP-seq in Dicer[superscript −/−] mESCs that lack mature miRNAs, allowing us to define whether the association of Ago2 with the identified sites was miRNA dependent. A significantly enriched motif, GCACUU, was identified only in wild-type mESCs in 3′ untranslated and coding regions. This motif matches the seed of a miRNA family that constitutes ~68% of the mESC miRNA population. Unexpectedly, a G-rich motif was enriched in sequences cross-linked to Ago2 in both the presence and absence of miRNAs. Expression analysis and reporter assays confirmed that the seed-related motif confers miRNA-directed regulation on host mRNAs and that the G-rich motif can modulate this regulation.Leukemia & Lymphoma Society of AmericaUnited States. Public Health Service (Grant R01-GM34277)United States. Public Health Service (Grant R01-CA133404)National Cancer Institute (U.S.) (Grant P01-CA42063)National Cancer Institute (U.S.) Cancer Center Support (Grant P30-CA14051

Ectopic T Cell Receptor-α Locus Control Region Activity in B Cells Is Suppressed by Direct Linkage to Two Flanking Genes at Once

The molecular mechanisms regulating the activity of the TCRα gene are required for the production of the circulating T cell repertoire. Elements of the mouse TCRα locus control region (LCR) play a role in these processes. We previously reported that TCRα LCR DNA supports a gene expression pattern that mimics proper thymus-stage, TCRα gene-like developmental regulation. It also produces transcription of linked reporter genes in peripheral T cells. However, TCRα LCR-driven transgenes display ectopic transcription in B cells in multiple reporter gene systems. The reasons for this important deviation from the normal TCRα gene regulation pattern are unclear. In its natural locus, two genes flank the TCRα LCR, TCRα (upstream) and Dad1 (downstream). We investigated the significance of this gene arrangement to TCRα LCR activity by examining transgenic mice bearing a construct where the LCR was flanked by two separate reporter genes. Surprisingly, the presence of a second, distinct, reporter gene downstream of the LCR virtually eliminated the ectopic B cell expression of the upstream reporter observed in earlier studies. Downstream reporter gene activity was unaffected by the presence of a second gene upstream of the LCR. Our findings indicate that a gene arrangement in which the TCRα LCR is flanked by two distinct transcription units helps to restrict its activity, selectively, on its 5′-flanking gene, the natural TCRα gene position with respect to the LCR. Consistent with these findings, a TCRα/Dad1 locus bacterial artificial chromosome dual-reporter construct did not display the ectopic upstream (TCRα) reporter expression in B cells previously reported for single TCRα transgenes

Assessment of nerve involvement in the lumbar spine: agreement between magnetic resonance imaging, physical examination and pain drawing findings

<p>Abstract</p> <p>Background</p> <p>Detection of nerve involvement originating in the spine is a primary concern in the assessment of spine symptoms. Magnetic resonance imaging (MRI) has become the diagnostic method of choice for this detection. However, the agreement between MRI and other diagnostic methods for detecting nerve involvement has not been fully evaluated. The aim of this diagnostic study was to evaluate the agreement between nerve involvement visible in MRI and findings of nerve involvement detected in a structured physical examination and a simplified pain drawing.</p> <p>Methods</p> <p>Sixty-one consecutive patients referred for MRI of the lumbar spine were - without knowledge of MRI findings - assessed for nerve involvement with a simplified pain drawing and a structured physical examination. Agreement between findings was calculated as overall agreement, the p value for McNemar's exact test, specificity, sensitivity, and positive and negative predictive values.</p> <p>Results</p> <p>MRI-visible nerve involvement was significantly less common than, and showed weak agreement with, physical examination and pain drawing findings of nerve involvement in corresponding body segments. In spine segment L4-5, where most findings of nerve involvement were detected, the mean sensitivity of MRI-visible nerve involvement to a positive neurological test in the physical examination ranged from 16-37%. The mean specificity of MRI-visible nerve involvement in the same segment ranged from 61-77%. Positive and negative predictive values of MRI-visible nerve involvement in segment L4-5 ranged from 22-78% and 28-56% respectively.</p> <p>Conclusion</p> <p>In patients with long-standing nerve root symptoms referred for lumbar MRI, MRI-visible nerve involvement significantly underestimates the presence of nerve involvement detected by a physical examination and a pain drawing. A structured physical examination and a simplified pain drawing may reveal that many patients with "MRI-invisible" lumbar symptoms need treatment aimed at nerve involvement. Factors other than present MRI-visible nerve involvement may be responsible for findings of nerve involvement in the physical examination and the pain drawing.</p

The global methane budget 2000-2017

Understanding and quantifying the global methane (CH4) budget is important for assessing realistic pathways to mitigate climate change. Atmospheric emissions and concentrations of CH4 continue to increase, making CH4 the second most important human-influenced greenhouse gas in terms of climate forcing, after carbon dioxide (CO2). The relative importance of CH4 compared to CO2 depends on its shorter atmospheric lifetime, stronger warming potential, and variations in atmospheric growth rate over the past decade, the causes of which are still debated. Two major challenges in reducing uncertainties in the atmospheric growth rate arise from the variety of geographically overlapping CH4 sources and from the destruction of CH4 by short-lived hydroxyl radicals (OH). To address these challenges, we have established a consortium of multidisciplinary scientists under the umbrella of the Global Carbon Project to synthesize and stimulate new research aimed at improving and regularly updating the global methane budget. Following Saunois et al. (2016), we present here the second version of the living review paper dedicated to the decadal methane budget, integrating results of top-down studies (atmospheric observations within an atmospheric inverse-modelling framework) and bottom-up estimates (including process-based models for estimating land surface emissions and atmospheric chemistry, inventories of anthropogenic emissions, and data-driven extrapolations). For the 2008-2017 decade, global methane emissions are estimated by atmospheric inversions (a top-down approach) to be 576 Tg CH4 yr-1 (range 550-594, corresponding to the minimum and maximum estimates of the model ensemble). Of this total, 359 Tg CH4 yr-1 or ĝ1/4 60 % is attributed to anthropogenic sources, that is emissions caused by direct human activity (i.e. anthropogenic emissions; range 336-376 Tg CH4 yr-1 or 50 %-65 %). The mean annual total emission for the new decade (2008-2017) is 29 Tg CH4 yr-1 larger than our estimate for the previous decade (2000-2009), and 24 Tg CH4 yr-1 larger than the one reported in the previous budget for 2003-2012 (Saunois et al., 2016). Since 2012, global CH4 emissions have been tracking the warmest scenarios assessed by the Intergovernmental Panel on Climate Change. Bottom-up methods suggest almost 30 % larger global emissions (737 Tg CH4 yr-1, range 594-881) than top-down inversion methods. Indeed, bottom-up estimates for natural sources such as natural wetlands, other inland water systems, and geological sources are higher than top-down estimates. The atmospheric constraints on the top-down budget suggest that at least some of these bottom-up emissions are overestimated. The latitudinal distribution of atmospheric observation-based emissions indicates a predominance of tropical emissions (ĝ1/4 65 % of the global budget, &lt; 30ĝ  N) compared to mid-latitudes (ĝ1/4 30 %, 30-60ĝ  N) and high northern latitudes (ĝ1/4 4 %, 60-90ĝ  N). The most important source of uncertainty in the methane budget is attributable to natural emissions, especially those from wetlands and other inland waters. Some of our global source estimates are smaller than those in previously published budgets (Saunois et al., 2016; Kirschke et al., 2013). In particular wetland emissions are about 35 Tg CH4 yr-1 lower due to improved partition wetlands and other inland waters. Emissions from geological sources and wild animals are also found to be smaller by 7 Tg CH4 yr-1 by 8 Tg CH4 yr-1, respectively. However, the overall discrepancy between bottom-up and top-down estimates has been reduced by only 5 % compared to Saunois et al. (2016), due to a higher estimate of emissions from inland waters, highlighting the need for more detailed research on emissions factors. Priorities for improving the methane budget include (i) a global, high-resolution map of water-saturated soils and inundated areas emitting methane based on a robust classification of different types of emitting habitats; (ii) further development of process-based models for inland-water emissions; (iii) intensification of methane observations at local scales (e.g., FLUXNET-CH4 measurements) and urban-scale monitoring to constrain bottom-up land surface models, and at regional scales (surface networks and satellites) to constrain atmospheric inversions; (iv) improvements of transport models and the representation of photochemical sinks in top-down inversions; and (v) development of a 3D variational inversion system using isotopic and/or co-emitted species such as ethane to improve source partitioning. The data presented here can be downloaded from https://doi.org/10.18160/GCP-CH4-2019 (Saunois et al., 2020) and from the Global Carbon Project

The global methane budget 2000–2017

Understanding and quantifying the global methane (CH4) budget is important for assessing realistic pathways to mitigate climate change. Atmospheric emissions and concentrations of CH4 continue to increase, making CH4 the second most important human-influenced greenhouse gas in terms of climate forcing, after carbon dioxide (CO2). The relative importance of CH4 compared to CO2 depends on its shorter atmospheric lifetime, stronger warming potential, and variations in atmospheric growth rate over the past decade, the causes of which are still debated. Two major challenges in reducing uncertainties in the atmospheric growth rate arise from the variety of geographically overlapping CH4 sources and from the destruction of CH4 by short-lived hydroxyl radicals (OH). To address these challenges, we have established a consortium of multidisciplinary scientists under the umbrella of the Global Carbon Project to synthesize and stimulate new research aimed at improving and regularly updating the global methane budget. Following Saunois et al. (2016), we present here the second version of the living review paper dedicated to the decadal methane budget, integrating results of top-down studies (atmospheric observations within an atmospheric inverse-modelling framework) and bottom-up estimates (including process-based models for estimating land surface emissions and atmospheric chemistry, inventories of anthropogenic emissions, and data-driven extrapolations). For the 2008–2017 decade, global methane emissions are estimated by atmospheric inversions (a top-down approach) to be 576 Tg CH4 yr−1 (range 550–594, corresponding to the minimum and maximum estimates of the model ensemble). Of this total, 359 Tg CH4 yr−1 or ∼ 60 % is attributed to anthropogenic sources, that is emissions caused by direct human activity (i.e. anthropogenic emissions; range 336–376 Tg CH4 yr−1 or 50 %–65 %). The mean annual total emission for the new decade (2008–2017) is 29 Tg CH4 yr−1 larger than our estimate for the previous decade (2000–2009), and 24 Tg CH4 yr−1 larger than the one reported in the previous budget for 2003–2012 (Saunois et al., 2016). Since 2012, global CH4 emissions have been tracking the warmest scenarios assessed by the Intergovernmental Panel on Climate Change. Bottom-up methods suggest almost 30 % larger global emissions (737 Tg CH4 yr−1, range 594–881) than top-down inversion methods. Indeed, bottom-up estimates for natural sources such as natural wetlands, other inland water systems, and geological sources are higher than top-down estimates. The atmospheric constraints on the top-down budget suggest that at least some of these bottom-up emissions are overestimated. The latitudinal distribution of atmospheric observation-based emissions indicates a predominance of tropical emissions (∼ 65 % of the global budget, < 30∘ N) compared to mid-latitudes (∼ 30 %, 30–60∘ N) and high northern latitudes (∼ 4 %, 60–90∘ N). The most important source of uncertainty in the methane budget is attributable to natural emissions, especially those from wetlands and other inland waters. Some of our global source estimates are smaller than those in previously published budgets (Saunois et al., 2016; Kirschke et al., 2013). In particular wetland emissions are about 35 Tg CH4 yr−1 lower due to improved partition wetlands and other inland waters. Emissions from geological sources and wild animals are also found to be smaller by 7 Tg CH4 yr−1 by 8 Tg CH4 yr−1, respectively. However, the overall discrepancy between bottom-up and top-down estimates has been reduced by only 5 % compared to Saunois et al. (2016), due to a higher estimate of emissions from inland waters, highlighting the need for more detailed research on emissions factors. Priorities for improving the methane budget include (i) a global, high-resolution map of water-saturated soils and inundated areas emitting methane based on a robust classification of different types of emitting habitats; (ii) further development of process-based models for inland-water emissions; (iii) intensification of methane observations at local scales (e.g., FLUXNET-CH4 measurements) and urban-scale monitoring to constrain bottom-up land surface models, and at regional scales (surface networks and satellites) to constrain atmospheric inversions; (iv) improvements of transport models and the representation of photochemical sinks in top-down inversions; and (v) development of a 3D variational inversion system using isotopic and/or co-emitted species such as ethane to improve source partitioning