Using residual analysis, auto- and cross-correlations to identify key processes for the calibration of the SWAT model in a data scarce region

Hydrological modeling poses a particular challenge in data scarce regions, which are often subject to dynamic change and thus of specific interest to hydrological modeling studies. When a small amount of data available for a catchment is opposed by extensive data requirements by the chosen hydrologic model, ways have to be found to extract as much information from the available data as possible. In a study conducted in the Xiangxi Catchment in the Three Gorges Region in China, the use of residual analysis as well as auto- and cross-correlations for enhanced model evaluation and for the identification of key processes governing the hydrological behavior of the catchment prior to model calibration was tested. The residuals were plotted versus various variables such as time, discharge and precipitation. Also, auto-correlations were calculated for measured and simulated discharge and cross-correlations of measured and simulated discharge with precipitation were analyzed. Results show that the analysis of residuals as well as auto- and cross-correlations can provide valuable information about the catchment response to rainfall events, which can be very helpful for calibration of hydrologic models in data scarce regions

Advances in proteomic and metabolomic profiling of neurodegenerative diseases

Proteomics and metabolomics are two emerging fields that hold promise to shine light on the molecular mechanisms causing neurodegenerative diseases. Research in this area may reveal and quantify specific metabolites and proteins that can be targeted by therapeutic interventions intended at halting or reversing the neurodegenerative process. This review aims at providing a general overview on the current status of proteomic and metabolomic profiling in neurodegenerative diseases. We focus on the most common neurodegenerative disorders, including Alzheimer's disease, Parkinson's disease, and amyotrophic lateral sclerosis. We discuss the relevance of state-of-the-art metabolomics and proteomics approaches and their potential for biomarker discovery. We critically review advancements made so far, highlighting how metabolomics and proteomics may have a significant impact in future therapeutic and biomarker development. Finally, we further outline technologies used so far as well as challenges and limitations, placing the current information in a future-facing context

Cloud busting: enstatite and quartz clouds in the atmosphere of 2M2224-0158

© The Author(s) 2021. Published by Oxford University Press on behalf of Royal Astronomical Society. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/).We present the most detailed data-driven exploration of cloud opacity in a substellar object to-date. We have tested over 60 combinations of cloud composition and structure, particle size distribution, scattering model, and gas phase composition assumptions against archival $1-15 {\rm \mu m}$ spectroscopy for the unusually red L4.5~dwarf 2MASSW~J2224438-015852 using the Brewster retrieval framework. We find that, within our framework, a model that includes enstatite and quartz cloud layers at shallow pressures, combined with a deep iron cloud deck fits the data best. This models assumes a Hansen distribution for particle sizes for each cloud, and Mie scattering. We retrieved particle effective radii of $\log_{10} a {\rm (\mu m)} = -1.41^{+0.18}_{-0.17}$ for enstatite, $-0.44^{+0.04}_{-0.20}$ for quartz, and $-0.77^{+0.05}_{-0.06}$ for iron. Our inferred cloud column densities suggest ${\rm (Mg/Si)} = 0.69^{+0.06}_{-0.08}$ if there are no other sinks for magnesium or silicon. Models that include forsterite alongside, or in place of, these cloud species are strongly rejected in favour of the above combination. We estimate a radius of $0.75 \pm 0.02$ Rjup, which is considerably smaller than predicted by evolutionary models for a field age object with the luminosity of 2M2224-0158. Models which assume vertically constant gas fractions are consistently preferred over models that assume thermochemical equilibrium. From our retrieved gas fractions we infer ${\rm [M/H]} = +0.38^{+0.07}_{-0.06}$ and ${\rm C/O} = 0.83^{+0.06}_{-0.07}$. Both these values are towards the upper end of the stellar distribution in the Solar neighbourhood, and are mutually consistent in this context. A composition toward the extremes of the local distribution is consistent with this target being an outlier in the ultracool dwarf population.Peer reviewe

Exploring the Ability of HST WFC3 G141 to Uncover Trends in Populations of Exoplanet Atmospheres Through a Homogeneous Transmission Survey of 70 Gaseous Planets

We present the analysis of the atmospheres of 70 gaseous extrasolar planets via transit spectroscopy with Hubble's Wide Field Camera 3 (WFC3). For over half of these, we statistically detect spectral modulation which our retrievals attribute to molecular species. Among these, we use Bayesian Hierarchical Modelling to search for chemical trends with bulk parameters. We use the extracted water abundance to infer the atmospheric metallicity and compare it to the planet's mass. We also run chemical equilibrium retrievals, fitting for the atmospheric metallicity directly. However, although previous studies have found evidence of a mass-metallicity trend, we find no such relation within our data. For the hotter planets within our sample, we find evidence for thermal dissociation of dihydrogen and water via the H$^-$ opacity. We suggest that the general lack of trends seen across this population study could be due to i) the insufficient spectral coverage offered by HST WFC3 G141, ii) the lack of a simple trend across the whole population, iii) the essentially random nature of the target selection for this study or iv) a combination of all the above. We set out how we can learn from this vast dataset going forward in an attempt to ensure comparative planetology can be undertaken in the future with facilities such as JWST, Twinkle and Ariel. We conclude that a wider simultaneous spectral coverage is required as well as a more structured approach to target selection.Comment: Accepted for publication in ApJ

Exploring the Ability of Hubble Space Telescope WFC3 G141 to Uncover Trends in Populations of Exoplanet Atmospheres through a Homogeneous Transmission Survey of 70 Gaseous Planets

We present analysis of the atmospheres of 70 gaseous extrasolar planets via transit spectroscopy with Hubble’s Wide Field Camera 3 (WFC3). For over half of these, we statistically detect spectral modulation that our retrievals attribute to molecular species. Among these, we use Bayesian hierarchical modeling to search for chemical trends with bulk parameters. We use the extracted water abundance to infer the atmospheric metallicity and compare it to the planet’s mass. We also run chemical equilibrium retrievals, fitting for the atmospheric metallicity directly. However, although previous studies have found evidence of a mass–metallicity trend, we find no such relation within our data. For the hotter planets within our sample, we find evidence for thermal dissociation of dihydrogen and water via the H− opacity. We suggest that the general lack of trends seen across this population study could be due to (i) the insufficient spectral coverage offered by the Hubble Space Telescope’s WFC3 G141 band, (ii) the lack of a simple trend across the whole population, (iii) the essentially random nature of the target selection for this study, or (iv) a combination of all the above. We set out how we can learn from this vast data set going forward in an attempt to ensure comparative planetology can be undertaken in the future with facilities such as the JWST, Twinkle, and Ariel. We conclude that a wider simultaneous spectral coverage is required as well as a more structured approach to target selection

A three-range approach enhances the prognostic utility of CSF biomarkers in Alzheimer's disease

Introduction: Alzheimer's disease consensus recommends biomarker dichotomization, a practice with well-described clinical strengths and methodological limitations. Although neuroimaging studies have explored alternative biomarker interpretation strategies, a formally defined three-range approach and its prognostic impact remains under-explored for cerebrospinal fluid (CSF) biomarkers. Methods: With two-graph receiver-operating characteristics based on different reference schemes, we derived three-range cut-points for CSF Elecsys biomarkers. According to baseline CSF status, we assessed the prognostic utility of this in predicting risk of clinical progression and longitudinal trajectories of cognitive decline and amyloid–beta (Aβ) positron emission tomography (PET) accumulation in non-demented individuals (Alzheimer's Disease Neuroimaging Initiative [ADNI]; n = 1246). In all analyses, we compared herein-derived three-range CSF cut-points to previously described binary ones. Results: In our main longitudinal analyses, we highlight CSF p-tau181/Aβ1-42 three-range cut-points derived based on the cognitively normal Aβ-PET negative versus dementia Aβ-PET positive reference scheme for best depicting a prognostically relevant biomarker abnormality range. Longitudinally, our approach revealed a divergent intermediate cognitive trajectory undetected by dichotomization and a clearly abnormal group at higher risk for cognitive decline, with power analyses suggesting the latter group as potential trial enrichment candidates. Furthermore, we demonstrate that individuals with intermediate-range CSF status have similar rates of Aβ deposition to those in the clearly abnormal group. Discussion: The proposed approach can refine clinico-biological prognostic assessment and potentially enhance trial recruitment, as it captures faster biomarker-related cognitive decline in comparison to binary cut-points. Although this approach has implications for trial recruitment and observational studies, further discussion is needed regarding clinical practice applications

Single-cell analysis reveals individual spore responses to simulated space vacuum

Outer space is a challenging environment for all forms of life, and dormant spores of bacteria have been frequently used to study the survival of terrestrial life in a space journey. Previous work showed that outer space vacuum alone can kill bacterial spores. However, the responses and mechanisms of resistance of individual spores to space vacuum are unclear. Here, we examined spores’ molecular changes under simulated space vacuum (~10−5 Pa) using micro-Raman spectroscopy and found that this vacuum did not cause significant denaturation of spore protein. Then, live-cell microscopy was developed to investigate the temporal events during germination, outgrowth, and growth of individual Bacillus spores. The results showed that after exposure to simulated space vacuum for 10 days, viability of spores of two Bacillus species was reduced up to 35%, but all spores retained their large Ca2 +-dipicolinic acid depot. Some of the killed spores did not germinate, and the remaining germinated but did not proceed to vegetative growth. The vacuum treatment slowed spore germination, and changed average times of all major germination events. In addition, viable vacuum-treated spores exhibited much greater sensitivity than untreated spores to dry heat and hyperosmotic stress. Among spores’ resistance mechanisms to high vacuum, DNA-protective α/β−type small acid-soluble proteins, and non- homologous end joining and base excision repair of DNA played the most important roles, especially against multiple cycles of vacuum treatment. Overall, these results give new insight into individual spore’s responses to space vacuum and provide new techniques for microorganism analysis at the single-cell level

Structural Basis for the Aminoacid Composition of Proteins from Halophilic Archea

In order to survive in highly saline environments, proteins from halophilic archea have evolved with biased amino acid compositions that have the capacity to reduce contacts with the solvent

β-Adrenergic Inhibition of Contractility in L6 Skeletal Muscle Cells

The β-adrenoceptors (β-ARs) control many cellular processes. Here, we show that β-ARs inhibit calcium depletion-induced cell contractility and subsequent cell detachment of L6 skeletal muscle cells. The mechanism underlying the cell detachment inhibition was studied by using a quantitative cell detachment assay. We demonstrate that cell detachment induced by depletion of extracellular calcium is due to myosin- and ROCK-dependent contractility. The β-AR inhibition of L6 skeletal muscle cell detachment was shown to be mediated by the β2-AR and increased cAMP but was surprisingly not dependent on the classical downstream effectors PKA or Epac, nor was it dependent on PKG, PI3K or PKC. However, inhibition of potassium channels blocks the β2-AR mediated effects. Furthermore, activation of potassium channels fully mimicked the results of β2-AR activation. In conclusion, we present a novel finding that β2-AR signaling inhibits contractility and thus cell detachment in L6 skeletal muscle cells by a cAMP and potassium channel dependent mechanism