LPMLE3 : a novel 1-D approach to study water flow in streambeds using heat as a tracer

We introduce LPMLE3, a new 1-D approach to quantify vertical water flow components at streambeds using temperature data collected in different depths. LPMLE3 solves the partial differential equation for coupled water flow and heat transport in the frequency domain. Unlike other 1-D approaches it does not assume a semi-infinite halfspace with the location of the lower boundary condition approaching infinity. Instead, it uses local upper and lower boundary conditions. As such, the streambed can be divided into finite subdomains bound at the top and bottom by a temperature-time series. Information from a third temperature sensor within each subdomain is then used for parameter estimation. LPMLE3 applies a low order local polynomial to separate periodic and transient parts (including the noise contributions) of a temperature-time series and calculates the frequency response of each subdomain to a known temperature input at the streambed top. A maximum-likelihood estimator is used to estimate the vertical component of water flow, thermal diffusivity, and their uncertainties for each streambed subdomain and provides information regarding model quality. We tested the method on synthetic temperature data generated with the numerical model STRIVE and demonstrate how the vertical flow component can be quantified for field data collected in a Belgian stream. We show that by using the results in additional analyses, nonvertical flow components could be identified and by making certain assumptions they could be quantified for each subdomain. LPMLE3 performed well on both simulated and field data and can be considered a valuable addition to the existing 1-D methods

Alzheimer's early detection in post-acute COVID-19 syndrome: a systematic review and expert consensus on preclinical assessments.

The risk of developing Alzheimer's disease (AD) in older adults increasingly is being discussed in the literature on Post-Acute COVID-19 Syndrome (PACS). Remote digital Assessments for Preclinical AD (RAPAs) are becoming more important in screening for early AD, and should always be available for PACS patients, especially for patients at risk of AD. This systematic review examines the potential for using RAPA to identify impairments in PACS patients, scrutinizes the supporting evidence, and describes the recommendations of experts regarding their use. We conducted a thorough search using the PubMed and Embase databases. Systematic reviews (with or without meta-analysis), narrative reviews, and observational studies that assessed patients with PACS on specific RAPAs were included. The RAPAs that were identified looked for impairments in olfactory, eye-tracking, graphical, speech and language, central auditory, or spatial navigation abilities. The recommendations' final grades were determined by evaluating the strength of the evidence and by having a consensus discussion about the results of the Delphi rounds among an international Delphi consensus panel called IMPACT, sponsored by the French National Research Agency. The consensus panel included 11 international experts from France, Switzerland, and Canada. Based on the available evidence, olfaction is the most long-lasting impairment found in PACS patients. However, while olfaction is the most prevalent impairment, expert consensus statements recommend that AD olfactory screening should not be used on patients with a history of PACS at this point in time. Experts recommend that olfactory screenings can only be recommended once those under study have reported full recovery. This is particularly important for the deployment of the olfactory identification subdimension. The expert assessment that more long-term studies are needed after a period of full recovery, suggests that this consensus statement requires an update in a few years. Based on available evidence, olfaction could be long-lasting in PACS patients. However, according to expert consensus statements, AD olfactory screening is not recommended for patients with a history of PACS until complete recovery has been confirmed in the literature, particularly for the identification sub-dimension. This consensus statement may require an update in a few years

Critical point network for drainage between rough surfaces

In this paper, we present a network method for computing two-phase flows between two rough surfaces with significant contact areas. Low-capillary number drainage is investigated here since one-phase flows have been previously investigated in other contributions. An invasion percolation algorithm is presented for modeling slow displacement of a wetting fluid by a non wetting one between two rough surfaces. Short-correlated Gaussian process is used to model random rough surfaces.The algorithm is based on a network description of the fracture aperture field. The network is constructed from the identification of critical points (saddles and maxima) of the aperture field. The invasion potential is determined from examining drainage process in a flat mini-channel. A direct comparison between numerical prediction and experimental visualizations on an identical geometry has been performed for one realization of an artificial fracture with a moderate fractional contact area of about 0.3. A good agreement is found between predictions and observations

Correcting for non-periodic behaviour in perturbative experiments: application to heat pulse propagation and modulated gas-puff experiments

This paper introduces a recent innovation in dealing with non-periodic behavior often referred to as transients. These transients can be the result from unforced response due to the initial condition and other drifts which are a source of error when performing and interpreting Fourier analysis on measurement data. Fourier analysis is particularly relevant in system identification used to build feedback controllers and the analysis of various pulsed experiments such as heat pulse propagation studies. The basic idea behind the methodology is that transients are continuous complex-valued smooth functions in the Fourier domain which can be estimated from the Fourier data. Then, these smooth functions can be approximately subtracted from the data such that only periodic components are retained. The merit of the approach is shown in two experimental examples, i.e., heat pulse propagation (core transport analysis) and radiation front movement due to gas puffing. The examples show that the quality of the data is significantly improved such that it allows new interpretation of the results even for non-ideal measurements.</p

A cohort of 17 patients with kyphoscoliotic Ehlers-Danlos syndrome caused by biallelic mutations in FKBP14: expansion of the clinical and mutational spectrum and description of the natural history.

PurposeIn 2012 we reported in six individuals a clinical condition almost indistinguishable from PLOD1-kyphoscoliotic Ehlers-Danlos syndrome (PLOD1-kEDS), caused by biallelic mutations in FKBP14, and characterized by progressive kyphoscoliosis, myopathy, and hearing loss in addition to connective tissue abnormalities such as joint hypermobility and hyperelastic skin. FKBP14 is an ER-resident protein belonging to the family of FK506-binding peptidyl-prolyl cis-trans isomerases (PPIases); it catalyzes the folding of type III collagen and interacts with type III, type VI, and type X collagens. Only nine affected individuals have been reported to date.MethodsWe report on a cohort of 17 individuals with FKBP14-kEDS and the follow-up of three previously reported patients, and provide an extensive overview of the disorder and its natural history based on clinical, biochemical, and molecular genetics data.ResultsBased on the frequency of the clinical features of 23 patients from the present and previous cohorts, we define major and minor features of FKBP14-kEDS. We show that myopathy is confirmed by histology and muscle imaging only in some patients, and that hearing impairment is predominantly sensorineural and may not be present in all individuals.ConclusionOur data further support the extensive clinical overlap with PLOD1-kEDS and show that vascular complications are rare manifestations of FKBP14-kEDS

Correcting for non-periodic behaviour in perturbative experiments: application to heat pulse propagation and modulated gas-puff experiments

This paper introduces a recent innovation in dealing with non-periodic behavior often referred to as transients in perturbative experiments. These transients can be the result from the unforced response due to the initial condition and other slow trends in the measurement data and are a source of error when performing and interpreting Fourier spectra. Fourier analysis is particularly relevant in system identification used to build feedback controllers and the analysis of various pulsed experiments such as heat pulse propagation studies. The basic idea behind the methodology is that transients are continuous complex-valued smooth functions in the Fourier domain which can be estimated from the Fourier data. Then, these smooth functions can be subtracted from the data such that only periodic components are retained. The merit of the approach is shown in two experimental examples, i.e. heat pulse propagation (core transport analysis) and radiation front movement due to gas puffing in the divertor. The examples show that the quality of the data is significantly improved such that it allows for new interpretation of the results even for non-ideal measurements

Overlapping SETBP1 gain-of-function mutations in Schinzel-Giedion syndrome and hematologic malignancies

Schinzel-Giedion syndrome (SGS) is a rare developmental disorder characterized by multiple malformations, severe neurological alterations and increased risk of malignancy. SGS is caused by de novo germline mutations clustering to a 12bp hotspot in exon 4 of SETBP1. Mutations in this hotspot disrupt a degron, a signal for the regulation of protein degradation, and lead to the accumulation of SETBP1 protein. Overlapping SETBP1 hotspot mutations have been observed recurrently as somatic events in leukemia. We collected clinical information of 47 SGS patients (including 26 novel cases) with germline SETBP1 mutations and of four individuals with a milder phenotype caused by de novo germline mutations adjacent to the SETBP1 hotspot. Different mutations within and around the SETBP1 hotspot have varying effects on SETBP1 stability and protein levels in vitro and in in silico modeling. Substitutions in SETBP1 residue I871 result in a weak increase in protein levels and mutations affecting this residue are significantly more frequent in SGS than in leukemia. On the other hand, substitutions in residue D868 lead to the largest increase in protein levels. Individuals with germline mutations affecting D868 have enhanced cell proliferation in vitro and higher incidence of cancer compared to patients with other germline SETBP1 mutations. Our findings substantiate that, despite their overlap, somatic SETBP1 mutations driving malignancy are more disruptive to the degron than germline SETBP1 mutations causing SGS. Additionally, this suggests that the functional threshold for the development of cancer driven by the disruption of the SETBP1 degron is higher than for the alteration in prenatal development in SGS. Drawing on previous studies of somatic SETBP1 mutations in leukemia, our results reveal a genotype-phenotype correlation in germline SETBP1 mutations spanning a molecular, cellular and clinical phenotype

Finding Diagnostically Useful Patterns in Quantitative Phenotypic Data.

Trio-based whole-exome sequence (WES) data have established confident genetic diagnoses in ∼40% of previously undiagnosed individuals recruited to the Deciphering Developmental Disorders (DDD) study. Here we aim to use the breadth of phenotypic information recorded in DDD to augment diagnosis and disease variant discovery in probands. Median Euclidean distances (mEuD) were employed as a simple measure of similarity of quantitative phenotypic data within sets of ≥10 individuals with plausibly causative de novo mutations (DNM) in 28 different developmental disorder genes. 13/28 (46.4%) showed significant similarity for growth or developmental milestone metrics, 10/28 (35.7%) showed similarity in HPO term usage, and 12/28 (43%) showed no phenotypic similarity. Pairwise comparisons of individuals with high-impact inherited variants to the 32 individuals with causative DNM in ANKRD11 using only growth z-scores highlighted 5 likely causative inherited variants and two unrecognized DNM resulting in an 18% diagnostic uplift for this gene. Using an independent approach, naive Bayes classification of growth and developmental data produced reasonably discriminative models for the 24 DNM genes with sufficiently complete data. An unsupervised naive Bayes classification of 6,993 probands with WES data and sufficient phenotypic information defined 23 in silico syndromes (ISSs) and was used to test a "phenotype first" approach to the discovery of causative genotypes using WES variants strictly filtered on allele frequency, mutation consequence, and evidence of constraint in humans. This highlighted heterozygous de novo nonsynonymous variants in SPTBN2 as causative in three DDD probands

Erratum to: 36th International Symposium on Intensive Care and Emergency Medicine

[This corrects the article DOI: 10.1186/s13054-016-1208-6.]