Enhanced regional terrestrial carbon uptake over Korea revealed by atmospheric CO2 measurements from 1999 to 2017

Understanding changes in terrestrial carbon balance is important to improve our knowledge of the regional carbon cycle and climate change. However, evaluating regional changes in the terrestrial carbon balance is challenging due to the lack of surface flux measurements. This study reveals that the terrestrial carbon uptake over the Republic of Korea has been enhanced from 1999 to 2017 by analyzing long‐term atmospheric CO₂ concentration measurements at the Anmyeondo Station (36.53°N, 126.32°E) located in the western coast. The influence of terrestrial carbon flux on atmospheric CO₂ concentrations (ΔCO₂) is estimated from the difference of CO₂ concentrations that were influenced by the land sector (through easterly winds) and the Yellow Sea sector (through westerly winds). We find a significant trend in ΔCO₂ of ?4.75 ppm per decade (p < .05) during the vegetation growing season (May through October), suggesting that the regional terrestrial carbon uptake has increased relative to the surrounding ocean areas. Combined analysis with satellite measured normalized difference vegetation index and gross primary production shows that the enhanced carbon uptake is associated with significant nationwide increases in vegetation and its production. Process‐based terrestrial model and inverse model simulations estimate that regional terrestrial carbon uptake increases by up to 18.9 and 8.0 Tg C for the study period, accounting for 13.4% and 5.7% of the average annual domestic carbon emissions, respectively. Atmospheric chemical transport model simulations indicate that the enhanced terrestrial carbon sink is the primary reason for the observed ΔCO₂ trend rather than anthropogenic emissions and atmospheric circulation changes. Our results highlight the fact that atmospheric CO₂ measurements could open up the possibility of detecting regional changes in the terrestrial carbon cycle even where anthropogenic emissions are not negligible.     

Comparison of forest above‐ground biomass from dynamic global vegetation models with spatially explicit remotely sensed observation‐based estimates

Gaps in our current understanding and quantification of biomass carbon stocks, particularly in tropics, lead to large uncertainty in future projections of the terrestrial carbon balance. We use the recently published GlobBiomass data set of forest above‐ground biomass (AGB) density for the year 2010, obtained from multiple remote sensing and in situ observations at 100 m spatial resolution to evaluate AGB estimated by nine dynamic global vegetation models (DGVMs). The global total forest AGB of the nine DGVMs is 365 ± 66 Pg C, the spread corresponding to the standard deviation between models, compared to 275 Pg C with an uncertainty of ~13.5% from GlobBiomass. Model‐data discrepancy in total forest AGB can be attributed to their discrepancies in the AGB density and/or forest area. While DGVMs represent the global spatial gradients of AGB density reasonably well, they only have modest ability to reproduce the regional spatial gradients of AGB density at scales below 1000 km. The 95th percentile of AGB density (AGB₉₅) in tropics can be considered as the potential maximum of AGB density which can be reached for a given annual precipitation. GlobBiomass data show local deficits of AGB density compared to the AGB₉₅, particularly in transitional and/or wet regions in tropics. We hypothesize that local human disturbances cause more AGB density deficits from GlobBiomass than from DGVMs, which rarely represent human disturbances. We then analyse empirical relationships between AGB density deficits and forest cover changes, population density, burned areas and livestock density. Regression analysis indicated that more than 40% of the spatial variance of AGB density deficits in South America and Africa can be explained; in Southeast Asia, these factors explain only ~25%. This result suggests TRENDY v6 DGVMs tend to underestimate biomass loss from diverse and widespread anthropogenic disturbances, and as a result overestimate turnover time in AGB.     

Advanced psychometric testing on a clinical screening tool to evaluate insomnia: sleep condition indicator in patients with advanced cancer

Sleep and Biological Rhythms - To examine the psychometric properties of the Sleep Condition Indicator (SCI) using different psychometric approaches [including classical test theory, Rasch models,...     

Exercise training reverses cardiac aging phenotypes associated with heart failure with preserved ejection fraction in male mice

Heart failure with preserved ejection fraction (HFpEF) is the most common type of HF in older adults. Although no pharmacological therapy has yet improved survival in HFpEF, exercise training (ExT) has emerged as the most effective intervention to improving functional outcomes in this age‐related disease. The molecular mechanisms by which ExT induces its beneficial effects in HFpEF, however, remain largely unknown. Given the strong association between aging and HFpEF, we hypothesized that ExT might reverse cardiac aging phenotypes that contribute to HFpEF pathophysiology and additionally provide a platform for novel mechanistic and therapeutic discovery. Here, we show that aged (24–30 months) C57BL/6 male mice recapitulate many of the hallmark features of HFpEF, including preserved left ventricular ejection fraction, subclinical systolic dysfunction, diastolic dysfunction, impaired cardiac reserves, exercise intolerance, and pathologic cardiac hypertrophy. Similar to older humans, ExT in old mice improved exercise capacity, diastolic function, and contractile reserves, while reducing pulmonary congestion. Interestingly, RNAseq of explanted hearts showed that ExT did not significantly modulate biological pathways targeted by conventional HF medications. However, it reversed multiple age‐related pathways, including the global downregulation of cell cycle pathways seen in aged hearts, which was associated with increased capillary density, but no effects on cardiac mass or fibrosis. Taken together, these data demonstrate that the aged C57BL/6 male mouse is a valuable model for studying the role of aging biology in HFpEF pathophysiology, and provide a molecular framework for how ExT potentially reverses cardiac aging phenotypes in HFpEF.     

Evolutionary heritage shapes tree distributions along an Amazon‐to‐Andes elevation gradient

Understanding how evolutionary constraints shape the elevational distributions of tree lineages provides valuable insight into the future of tropical montane forests under global change. With narrow elevational ranges, high taxonomic turnover, frequent habitat specialization, and exceptional levels of endemism, tropical montane forests and trees are predicted to be highly sensitive to environmental change. Using plot census data from a gradient traversing > 3,000 m in elevation on the Amazonian flank of the Peruvian Andes, we employ phylogenetic approaches to assess the influence of evolutionary heritage on distribution trends of trees at the genus‐level. We find that closely related lineages tend to occur at similar mean elevations, with sister genera pairs occurring a mean 254 m in elevation closer to each other than the mean elevational difference between non‐sister genera pairs. We also demonstrate phylogenetic clustering both above and below 1,750 m a.s.l, corresponding roughly to the cloud‐base ecotone. Belying these general trends, some lineages occur across many different elevations. However, these highly plastic lineages are not phylogenetically clustered. Overall, our findings suggest that tropical montane forests are home to unique tree lineage diversity, constrained by their evolutionary heritage and vulnerable to substantial losses under environmental changes, such as rising temperatures or an upward shift of the cloud‐base.     

Toward a phylogeny and biogeography of Diaphanosoma (Crustacea: Cladocera)

Aquatic Ecology - Diaphanosoma s.l., with 40+? described species, is the largest genus of the Sididae and the Ctenopoda, similar in many ways to the anomopod genus Daphnia. Here, we offer a c...     

Community-directed distributors—The “foot soldiers” in the fight to control and eliminate neglected tropical diseases

The neglected tropical diseases (NTDs) affect hundreds of millions of people, predominantly in rural, often difficult-to-access areas, poorly served by national health services. Here, we review the contributions of 4.8 million community-directed distributors (CDDs) of medicines over 2 decades in 146,000 communities in 27 sub-Saharan African countries to control or eliminate onchocerciasis and lymphatic filariasis (LF). We examine their role in the control of other NTDs, malaria, HIV/AIDS interventions, immunisation campaigns, and support to overstretched health service personnel. We are of the opinion that CDDs as community selected, trained, and experienced “foot soldiers,” some of whom were involved in the Ebola outbreak responses at the community level in Liberia, if retrained, can assist community leaders and support health workers (HWs) in the ongoing Coronavirus Disease 2019 (COVID-19) crisis. The review highlights the improved treatment coverage where there are women CDDs, the benefits and lessons from the work of CDDs, their long-term engagement, and the challenges they face in healthcare delivery. It underscores the value of utilising the CDD model for strong community engagement and recommends the model, with some review, to hasten the achievement of the NTD 2030 goal and assist the health system cope with evolving epidemics and other challenges. We propose that, based on the unprecedented progress made in the control of NTDs directly linked to community engagement and contributions of CDDs “foot soldiers,” they deserve regional and global recognition. We also suggest that the World Health Organization (WHO) and other international stakeholders promote policy and guidance for countries to adapt this model for the elimination of NTDs and to strengthen national health services. This will enhance the accomplishment of some Sustainable Development Goals (SDGs) by 2030 in sub-Saharan Africa.     

Quantitative Measurement of Phosphoproteome Response to Osmotic Stress in Arabidopsis Based on Library-Assisted eXtracted Ion Chromatogram (LAXIC)

Global phosphorylation changes in plants in response to environmental stress have been relatively poorly characterized to date. Here we introduce a novel mass spectrometry-based label-free quantitation method that facilitates systematic profiling plant phosphoproteome changes with high efficiency and accuracy. This method employs synthetic peptide libraries tailored specifically as internal standards for complex phosphopeptide samples and accordingly, a local normalization algorithm, LAXIC, which calculates phosphopeptide abundance normalized locally with co-eluting library peptides. Normalization was achieved in a small time frame centered to each phosphopeptide to compensate for the diverse ion suppression effect across retention time. The label-free LAXIC method was further treated with a linear regression function to accurately measure phosphoproteome responses to osmotic stress in Arabidopsis. Among 2027 unique phosphopeptides identified and 1850 quantified phosphopeptides in Arabidopsis samples, 468 regulated phosphopeptides representing 497 phosphosites have shown significant changes. Several known and novel components in the abiotic stress pathway were identified, illustrating the capability of this method to identify critical signaling events among dynamic and complex phosphorylation. Further assessment of those regulated proteins may help shed light on phosphorylation response to osmotic stress in plants.Phosphorylation plays a pivotal role in the regulation of a majority of cellular processes via signaling transduction pathways. During the last decade, quantitative phosphoproteomics has become a powerful and versatile platform to profile signaling pathways at a system-wide scale. Multiple signaling networks in different organisms have been characterized through global phosphorylation profiling (1–3), which has evolved over the years with highly optimized procedures for sample preparation and phosphopeptide enrichment, high resolution mass spectrometry, and data analysis algorithms to identify and quantify thousands of phosphorylation events (4–8).Quantitative phosphoproteomics can be achieved mainly by two major techniques, stable isotope labeling and label-free quantitation. Isotope labeling prior to liquid chromatography-mass spectrometry (LC-MS)¹ has been widely used, including metabolic labeling such as stable isotope labeling by amino acids in cell culture (SILAC), chemical labeling such as multiplexed isobaric tags for relative and absolute quantification (iTRAQ) and isotope-coded affinity tags (ICAT) (9–12). On the other hand, label-free quantitation has gained momentum in recent years (13–15), as no additional chemistry or sample preparation steps are required. Compared with stable isotope labeling, label-free quantitation has higher compatibility with the source of the samples, the number of samples for comparison, and the instrument choice.Many label-free approaches, in particular to phosphoproteomics, are based on ion intensity (16, 17), but they are relatively error-prone because of run-to-run variations in LC/MS performance (18). In theory, such systematic errors can be corrected by spiking an internal standard into every sample to be compared. Several methods based on internal standard spiking have been reported so far. Absolute quantification peptide technology (AQUA) (19), for example, uses synthetic peptides with isotope labeling for absolute quantitation. For a global quantitative proteomics study, it is unrealistic to spike-in all reference peptides. Another labeling reference method, spike-in SILAC appears to be a promising technique to quantify the proteome in vivo with multiplex capability and it can be extended to clinical samples (20). One solution to large-scale quantitation without any isotope labeling is pseudo internal standard approach (21), which selects endogenous house-keeping proteins as the internal standard so that no spike-in reagent is required. However, finding a good pseudo internal standard remains a challenge for phosphoproteome samples. Spike-in experiments are an alternative way to improve normalization profile. Some internal standard peptides such as MassPREP^TM (Waters) were already widely used. Other groups spiked an identical amount of standard protein into samples prior to protein digestion (22–24). There are two major normalization procedures. In one approach, sample peptides were normalized to the total peak intensity of spike-in peptides (25). Alternatively, the digested peptides were compared at first and the normalization factor was determined in different ways such as the median (26) or average of ratios (27). However, spiking an identical amount of standard proteins into phosphoproteomic samples before protein digestion may not be compatible with phosphoproteomic analyses which typically require a phosphopeptide enrichment step. Spectral counting has been extensively applied in large sets of proteomic samples because of its simplicity but the method is often not reliable for the quantitation of phosphoproteins, which are typically identified by single phosphopeptides with few spectra (28–30). Many software packages have been implemented to support the wide variety of those quantitation techniques, including commercial platforms such as Progenesis LC-MS^TM, Mascot Distiller^TM, PEAKS Q^TM, etc., as well as open-source software packages including MaxQuant (31), PEPPeR (32), Skyline (33), etc.In this study, we have devised a novel label-free quantitation strategy termed Library Assisted eXtracted Ion Chromatogram (LAXIC) for plant phosphoproteomic analyses with high accuracy and consistency (Fig. 1). The approach employs synthetic peptide libraries as the internal standard. These peptides were prepared to have proper properties for quality control assessments and mass spectrometric measurements. In particular, peptides were designed to elute sequentially over an entire LC gradient and to have suitable ionization efficiency and m/z values within the normally scanned mass range. Local normalization of peak intensity is performed using Loess Procedure, a data treatment adopted from cDNA microarray data analysis (34). To monitor the diverse ion suppression effect across retention time, the local normalization factors (LNFs) are determined by internal standard pairs in individual time windows. Finally, samples will be quantified with LNFs in order to correct variance of LC-MS conditions. This quantification occurs in a small time frame centered to each target peptide.Open in a separate windowFig. 1.Work flow for the LAXIC strategy to quantify the phosphorylation change in response to osmotic stress. A, Schematic representation of the LAXIC algorithm. First, all the chromatographic peaks were aligned and the ratios were calculated. Second, the normalization factors which equal to ratios of library peptide peaks between MS runs were chosen to construct normalization curve. Third, sample peptide peak ratios were normalized against predicted normalization factor corresponding to certain retention time. B, Schematic representation of quantitative phosphoproteomics. Plants either treated with mannitol or PBS were lysed and mixed proportionally at first. Following peptide digestion and enrichment, phosphopeptides were identified and further quantified through LAXIC incorporated with self-validating process using thelinear regression model to analyze the fold change (fold), linearity (R²) and accuracy (%Acc).Water deficit and salinity causes osmotic stress, which is a major environmental factor limiting plant agricultural productivity. Osmotic stress rapidly changes the metabolism, gene expression and development of plant cells by activating several signaling pathways. Several protein kinases have been characterized as key components in osmotic stress signaling. Arabidopsis histidine kinase AHK1 can complement the histidine kinase mutant yeast, which can act as the osmosensor in yeast (35). Overexpression of AHK1 gene increases the drought tolerance of transgenic plants in Arabidopsis (36). Similar to yeast, the MAPK kinase cascade is also involved in osmotic stress response in plants. It is reported that AtMPK3, AtMPK6, and tobacco SIPK can be activated by NaCl or mannitol, and play positive roles in osmotic signaling (37, 38). MKK7 and MKKK20 may act as the up-stream kinase in the kinase cascade (39). Involvement of some calcium-dependent protein kinases, such as AtCPK21, AtCPK6, and OsCPK7 (CDPK) in osmotic stress signaling has also been reported (40–42). Another kinase family, SNF1-related protein kinase (SnRK) 2, also participates in osmotic stress response. In Arabidopsis, there are ten members in the SnRK2 family. Five from the ten SnRK2s, SnRK2, 3, 6, 7, and 8, can be activated by abscisic acid (ABA) and play central roles in ABA-receptor coupled signaling (43, 44). Furthermore, all SnRK2s except SnRK2.9 can be activated by NaCl or mannitol treatment (43). The decuple mutant of SnRK2 showed a strong osmotic hypersensitive phenotype (45). It is proposed that protein kinases including MAPK and SnRK2s have a critical function in osmotic stress (46), but the detailed mechanism and downstream substrates or target signal components are not yet clarified. We applied, therefore, the LAXIC approach with a self-validating method (47) to profile the osmotic stress-dependent phosphoproteome in Arabidopsis by quantifying phosphorylation events before and after mannitol treatment. Among a total of over 2000 phosphopeptides, more than 400 of them are dependent on osmotic stress. Those phosphoproteins are present on enzymes participating in signaling networks that are involved in many processes such as signal transduction, cytoskeleton development, and apoptosis. Overall, LAXIC represents a powerful tool for label-free quantitative phosphoproteomics.