Atherogenic lipoproteins in subclinical hypothyroidism and their relationship with hepatic lipase activity: Response to replacement treatment with levothyroxine

Background: Qualitative lipoprotein changes, such as an increase in fasting remnants, are reported in subclinical hypothyroidism (SCH). It was hypothesized that such changes are due to reduced hepatic lipase (HL) activity in SCH: HL is an enzyme regulated by thyroid hormones, and is involved in the degradation of triglyceride (TG)-rich remnants. This study aimed to quantify remnant-like lipoproteins (RLP), small dense LDL (sdLDL), and HL activity in women with SCH, and to assess these parameters after levothyroxine replacement therapy. Methods: This was an observational cross-sectional study with a subsequent longitudinal follow-up. Findings in women with thyrotropin levels >4.5 mIU/L (SH group) were compared with age- and body mass index (BMI)-matched euthyroid women (control group). In addition, a subgroup analysis was undertaken in SCH women who chose to receive levothyroxine treatment (0.9 μg/kg/day) for 6 months. RLP was quantified by measuring cholesterol (RLP-C) and triglycerides (RLP-TG) after immunoaffinity chromatography, and sdLDL by automated standardized methods; HL activity was measured in post-heparin plasma. Results: The SCH group included 37 women; 29 women were included in the control group. In addition, 22 women with SCH were included in the subgroup analysis (levothyroxine treatment). Significantly higher RLP values were observed in the SCH group than in the control group: RLP-C (median [range], mg/dL): 20.3 (5.8-66.8) versus 10.2 (2.7-36.3), p = 0.005; RLP-TG (mg/dL): 26.3 (3.2-123.3) versus 12.1 (2.5-61.6), p = 0.033. HL activity (mean ± standard deviation [SD], μmol free fatty acid/mL post-heparin plasma.h) - 9.83 ± 4.25 versus 9.92 ± 5.20, p = 0.707 - and sdLDL levels (mg/dL) - 23.1 ± 10.7 versus 22.6 ± 8.4, p = 0.83 - were similar. After levothyroxine, RLP-C decreased - 21.5 (5.8-66.8) versus 17.2 (4.1-45.6), p = 0.023 - and HL increased - 9.75 ± 4.04 versus 11.86 ± 4.58, p = 0.012 - in the subgroup of SCH women. No changes in sdLDL were observed. Conclusions: Women with SCH have higher RLP levels than matched controls do, but their RLP-C levels decrease significantly following levothyroxine therapy. Furthermore, HL activity also increases after levothyroxine therapy and can be interpreted as a possible explanation for the decrease in RLP-C.Fil: Brenta, Gabriela. Unidad Asistencial Doctor César Milstein; ArgentinaFil: Berg, Gabriela Alicia. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Departamento de Bioquímica Clínica; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Miksztowicz, Verónica Julieta. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Departamento de Bioquímica Clínica; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Lopez, Graciela Ines. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Departamento de Bioquímica Clínica; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Lucero, Diego Martín. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Departamento de Bioquímica Clínica; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Faingold, María Cristina. Unidad Asistencial Doctor César Milstein; ArgentinaFil: Murakami, Masami. Gunma University Graduate School Of Medicine; JapónFil: Machima, Tetsudo. Gunma University Graduate School Of Medicine; JapónFil: Nakajima, Katsuyuki. Graduate School Of Health Sciences, Gunma University; JapónFil: Schreier, Laura Ester. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Departamento de Bioquímica Clínica; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentin

Kinase Inhibitor Profile For Human Nek1, Nek6, And Nek7 And Analysis Of The Structural Basis For Inhibitor Specificity.

Human Neks are a conserved protein kinase family related to cell cycle progression and cell division and are considered potential drug targets for the treatment of cancer and other pathologies. We screened the activation loop mutant kinases hNek1 and hNek2, wild-type hNek7, and five hNek6 variants in different activation/phosphorylation statesand compared them against 85 compounds using thermal shift denaturation. We identified three compounds with significant Tm shifts: JNK Inhibitor II for hNek1(Δ262-1258)-(T162A), Isogranulatimide for hNek6(S206A), andGSK-3 Inhibitor XIII for hNek7wt. Each one of these compounds was also validated by reducing the kinases activity by at least 25%. The binding sites for these compounds were identified by in silico docking at the ATP-binding site of the respective hNeks. Potential inhibitors were first screened by thermal shift assays, had their efficiency tested by a kinase assay, and were finally analyzed by molecular docking. Our findings corroborate the idea of ATP-competitive inhibition for hNek1 and hNek6 and suggest a novel non-competitive inhibition for hNek7 in regard to GSK-3 Inhibitor XIII. Our results demonstrate that our approach is useful for finding promising general and specific hNekscandidate inhibitors, which may also function as scaffolds to design more potent and selective inhibitors.201176-9

Phylogenetic diversity of Amazonian tree communities

Aim: To examine variation in the phylogenetic diversity (PD) of tree communities across geographical and environmental gradients in Amazonia. Location: Two hundred and eighty-three c. 1 ha forest inventory plots from across Amazonia. Methods: We evaluated PD as the total phylogenetic branch length across species in each plot (PDss), the mean pairwise phylogenetic distance between species (MPD), the mean nearest taxon distance (MNTD) and their equivalents standardized for species richness (ses.PDss, ses.MPD, ses.MNTD). We compared PD of tree communities growing (1) on substrates of varying geological age; and (2) in environments with varying ecophysiological barriers to growth and survival. Results: PDss is strongly positively correlated with species richness (SR), whereas MNTD has a negative correlation. Communities on geologically young- and intermediate-aged substrates (western and central Amazonia respectively) have the highest SR, and therefore the highest PDss and the lowest MNTD. We find that the youngest and oldest substrates (the latter on the Brazilian and Guiana Shields) have the highest ses.PDss and ses.MNTD. MPD and ses.MPD are strongly correlated with how evenly taxa are distributed among the three principal angiosperm clades and are both highest in western Amazonia. Meanwhile, seasonally dry tropical forest (SDTF) and forests on white sands have low PD, as evaluated by any metric. Main conclusions: High ses.PDss and ses.MNTD reflect greater lineage diversity in communities. We suggest that high ses.PDss and ses.MNTD in western Amazonia results from its favourable, easy-to-colonize environment, whereas high values in the Brazilian and Guianan Shields may be due to accumulation of lineages over a longer period of time. White-sand forests and SDTF are dominated by close relatives from fewer lineages, perhaps reflecting ecophysiological barriers that are difficult to surmount evolutionarily. Because MPD and ses.MPD do not reflect lineage diversity per se, we suggest that PDss, ses.PDss and ses.MNTD may be the most useful diversity metrics for setting large-scale conservation priorities

Variation in stem mortality rates determines patterns of above-ground biomass in Amazonian forests: implications for dynamic global vegetation models

Understanding the processes that determine above-ground biomass (AGB) in Amazonian forests is important for predicting the sensitivity of these ecosystems to environmental change and for designing and evaluating dynamic global vegetation models (DGVMs). AGB is determined by inputs from woody productivity [woody net primary productivity (NPP)] and the rate at which carbon is lost through tree mortality. Here, we test whether two direct metrics of tree mortality (the absolute rate of woody biomass loss and the rate of stem mortality) and/or woody NPP, control variation in AGB among 167 plots in intact forest across Amazonia. We then compare these relationships and the observed variation in AGB and woody NPP with the predictions of four DGVMs. The observations show that stem mortality rates, rather than absolute rates of woody biomass loss, are the most important predictor of AGB, which is consistent with the importance of stand size structure for determining spatial variation in AGB. The relationship between stem mortality rates and AGB varies among different regions of Amazonia, indicating that variation in wood density and height/diameter relationships also influences AGB. In contrast to previous findings, we find that woody NPP is not correlated with stem mortality rates and is weakly positively correlated with AGB. Across the four models, basin-wide average AGB is similar to the mean of the observations. However, the models consistently overestimate woody NPP and poorly represent the spatial patterns of both AGB and woody NPP estimated using plot data. In marked contrast to the observations, DGVMs typically show strong positive relationships between woody NPP and AGB. Resolving these differences will require incorporating forest size structure, mechanistic models of stem mortality and variation in functional composition in DGVMs

Birmingham Environment for Academic Research : Case studies volume 3

This collection of case studies was brought together to showcase the extent and diversity of research that is supported by the University of Birmingham’s Environment for Academic Research (BEAR). BEAR is a collection of contemporary IT resources designed to help research. The following case studies demonstrate how BEAR services such as the Research Data Store (RDS), BEAR software and the University supercomputer BlueBEAR are integral to the progression of important research across disciplines. BlueBEAR is a key component of BEAR, providing compute power and specialist applications free to enable staff and students to delve deeper into their research. Upgraded in 2023, the cluster includes many large memory nodes and a GPU service alongside standard compute nodes. Alongside BlueBEAR, the RDS is a popular choice amongst researchers to securely store their working research data. As of publication, more than 5000 researchers across all five colleges were actively using BlueBEAR and/or the RDS. In this volume, we showcase case studies representing diverse research from every college. From estimating snow coverage to modelling second language acquisition, we show how BEAR services are enabling exciting and important research across the university

Variation in stem mortality rates determines patterns of above-ground biomass in Amazonian forests: implications for dynamic global vegetation models

This is the final version of the article. Available from Wiley via the DOI in this record.Understanding the processes that determine above-ground biomass (AGB) in Amazonian forests is important for predicting the sensitivity of these ecosystems to environmental change and for designing and evaluating dynamic global vegetation models (DGVMs). AGB is determined by inputs from woody productivity [woody net primary productivity (NPP)] and the rate at which carbon is lost through tree mortality. Here, we test whether two direct metrics of tree mortality (the absolute rate of woody biomass loss and the rate of stem mortality) and/or woody NPP, control variation in AGB among 167 plots in intact forest across Amazonia. We then compare these relationships and the observed variation in AGB and woody NPP with the predictions of four DGVMs. The observations show that stem mortality rates, rather than absolute rates of woody biomass loss, are the most important predictor of AGB, which is consistent with the importance of stand size structure for determining spatial variation in AGB. The relationship between stem mortality rates and AGB varies among different regions of Amazonia, indicating that variation in wood density and height/diameter relationships also influences AGB. In contrast to previous findings, we find that woody NPP is not correlated with stem mortality rates and is weakly positively correlated with AGB. Across the four models, basin-wide average AGB is similar to the mean of the observations. However, the models consistently overestimate woody NPP and poorly represent the spatial patterns of both AGB and woody NPP estimated using plot data. In marked contrast to the observations, DGVMs typically show strong positive relationships between woody NPP and AGB. Resolving these differences will require incorporating forest size structure, mechanistic models of stem mortality and variation in functional composition in DGVMs.This paper is a product of the European Union's Seventh Framework Programme AMAZALERT project (282664). The field data used in this study have been generated by the RAINFOR network, which has been supported by a Gordon and Betty Moore Foundation grant, the European Union's Seventh Framework Programme projects 283080, ‘GEOCARBON’; and 282664, ‘AMAZALERT’; ERC grant ‘Tropical Forests in the Changing Earth System’), and Natural Environment Research Council (NERC) Urgency, Consortium and Standard Grants ‘AMAZONICA’ (NE/F005806/1), ‘TROBIT’ (NE/D005590/1) and ‘Niche Evolution of South American Trees’ (NE/I028122/1). Additional data were included from the Tropical Ecology Assessment and Monitoring (TEAM) Network – a collaboration between Conservation International, the Missouri Botanical Garden, the Smithsonian Institution and the Wildlife Conservation Society, and partly funded by these institutions, the Gordon and Betty Moore Foundation, and other donors. Fieldwork was also partially supported by Conselho Nacional de Desenvolvimento Científico e Tecnológico of Brazil (CNPq), project Programa de Pesquisas Ecológicas de Longa Duração (PELD-403725/2012-7). A.R. acknowledges funding from the Helmholtz Alliance ‘Remote Sensing and Earth System Dynamics’; L.P., M.P.C. E.A. and M.T. are partially funded by the EU FP7 project ‘ROBIN’ (283093), with co-funding for E.A. from the Dutch Ministry of Economic Affairs (KB-14-003-030); B.C. [was supported in part by the US DOE (BER) NGEE-Tropics project (subcontract to LANL). O.L.P. is supported by an ERC Advanced Grant and is a Royal Society-Wolfson Research Merit Award holder. P.M. acknowledges support from ARC grant FT110100457 and NERC grants NE/J011002/1, and T.R.B. acknowledges support from a Leverhulme Trust Research Fellowship

Evolutionary Heritage Influences Amazon Tree Ecology

Lineages tend to retain ecological characteristics of their ancestors through time. However, for some traits, selection during evolutionary history may have also played a role in determining trait values. To address the relative importance of these processes requires large-scale quantification of traits and evolutionary relationships among species. The Amazonian tree flora comprises a high diversity of angiosperm lineages and species with widely differing life-history characteristics, providing an excellent system to investigate the combined influences of evolutionary heritage and selection in determining trait variation. We used trait data related to the major axes of life-history variation among tropical trees (e.g. growth and mortality rates) from 577 inventory plots in closed-canopy forest, mapped onto a phylogenetic hypothesis spanning more than 300 genera including all major angiosperm clades to test for evolutionary constraints on traits. We found significant phylogenetic signal (PS) for all traits, consistent with evolutionarily related genera having more similar characteristics than expected by chance. Although there is also evidence for repeated evolution of pioneer and shade tolerant life-history strategies within independent lineages, the existence of significant PS allows clearer predictions of the links between evolutionary diversity, ecosystem function and the response of tropical forests to global change

Evolutionary Heritage Influences Amazon Tree Ecology

Lineages tend to retain ecological characteristics of their ancestors through time. However, for some traits, selection during evolutionary history may have also played a role in determining trait values. To address the relative importance of these processes requires large-scale quantification of traits and evolutionary relationships among species. The Amazonian tree flora comprises a high diversity of angiosperm lineages and species with widely differing life-history characteristics, providing an excellent system to investigate the combined influences of evolutionary heritage and selection in determining trait variation. We used trait data related to the major axes of life-history variation among tropical trees (e.g. growth and mortality rates) from 577 inventory plots in closed-canopy forest, mapped onto a phylogenetic hypothesis spanning more than 300 genera including all major angiosperm clades to test for evolutionary constraints on traits. We found significant phylogenetic signal (PS) for all traits, consistent with evolutionarily related genera having more similar characteristics than expected by chance. Although there is also evidence for repeated evolution of pioneer and shade tolerant life-history strategies within independent lineages, the existence of significant PS allows clearer predictions of the links between evolutionary diversity, ecosystem function and the response of tropical forests to global change

Hyperdominance in Amazonian Forest Carbon Cycling

While Amazonian forests are extraordinarily diverse, the abundance of trees is skewed strongly towards relatively few ‘hyperdominant’ species. In addition to their diversity, Amazonian trees are a key component of the global carbon cycle, assimilating and storing more carbon than any other ecosystem on Earth. Here we ask, using a unique data set of 530 forest plots, if the functions of storing and producing woody carbon are concentrated in a small number of tree species, whether the most abundant species also dominate carbon cycling, and whether dominant species are characterized by specific functional traits. We find that dominance of forest function is even more concentrated in a few species than is dominance of tree abundance, with only ≈1% of Amazon tree species responsible for 50% of carbon storage and productivity. Although those species that contribute most to biomass and productivity are often abundant, species maximum size is also influential, while the identity and ranking of dominant species varies by function and by region

Metabolomics, machine learning and immunohistochemistry to predict succinate dehydrogenase mutational status in phaeochromocytomas and paragangliomas

Phaeochromocytomas and paragangliomas (PPGLs) are rare neuroendocrine tumours with a hereditary background inover one-third of patients. Mutations in succinate dehydrogenase (SDH) genes increase the risk for PPGLs and severalother tumours. Mutations in subunit B (SDHB) in particular are a risk factor for metastatic disease, further highlight-ing the importance of identifying SDHx mutations for patient management. Genetic variants of unknown signi-cance, where implications for the patient and family members are unclear, are a problem for interpretation. Forsuch cases, reliable methods for evaluating protein functionality are required. Immunohistochemistry for SDHB(SDHB-IHC) is the method of choice but does not assess functionality at the enzymatic level. Liquid chromatogra-phy–mass spectrometry-based measurements of metabolite precursors and products of enzymatic reactions providean alternative method. Here, we compare SDHB-IHC with metabolite proling in 189 tumours from 187 PPGLpatients. Besides evaluating succinate:fumarate ratios (SFRs), machine learning algorithms were developed to estab-lish predictive models for interpreting metabolite data. Metabolite proling showed higher diagnostic specicitycompared to SDHB-IHC (99.2% versus 92.5%, p = 0.021), whereas sensitivity was comparable. Application of machine learning algorithms to metabolite proles improved predictive ability over that of the SFR, in particular forhard-to-interpret cases of head and neck paragangliomas (AUC 0.9821 versus 0.9613, p = 0.044). Importantly, thecombination of metabolite proling with SDHB-IHC has complementary utility, as SDHB-IHC correctly classied allbut one of the false negatives from metabolite proling strategies, while metabolite proling correctly classied allbut one of the false negatives/positives from SDHB-IHC. From 186 tumours with conrmed status of SDHx variantpathogenicity, the combination of the two methods resulted in 185 correct predictions, highlighting the benets ofboth strategies for patient management