Explore the vast range of titles available.

The introduction of wire-free microcirculatory resistance index from functional angiography (angio-IMR) promises swift detection of coronary microvascular dysfunction, however it has not been properly validated. We sought to validate angio-IMR against invasive IMR and PET derived microvascular resistance (MVR). Moreover, we studied if angio-IMR could aid in the detection of ischemia with non-obstructive coronary arteries (INOCA). In this investigator-initiated study symptomatic patients underwent [ 15 O]H 2 O positron emission tomography (PET) and invasive angiography with 3-vessel fractional flow reserve (FFR). Invasive IMR was measured in 40 patients. Angio-IMR and QFR were computed retrospectively. MVR was defined as the ratio of mean distal coronary pressure to PET derived coronary flow. PET and QFR/angio-IMR analyses were performed by blinded core labs. The right coronary artery was excluded. A total of 211 patients (mean age 61 ± 9, 148 (70%) male) with 312 vessels with successful angio-IMR analyses were included. Angio-IMR correlated moderately with invasive IMR ( r  = 0.48, p  < 0.01), whereas no correlation was found between angio-IMR and MVR ( r =-0.07, p  = 0.25). Angio-IMR did not differ for vessels without obstructive coronary artery disease (CAD) (FFR-) but with reduced stress perfusion (PET+) compared to vessels without obstructive CAD (FFR-) with normal stress perfusion (PET-) (median 28.19 IQR 20.42–38.99 vs. 31.67 IQR 23.47–40.63, p  = 0.40). Angio-IMR correlated moderately with invasively measured IMR, whereas angio-IMR did not correlate with PET derived MVR. Moreover, angio-IMR did not reliably identify patients with INOCA. Graphical Abstract

The phosphatidylglycerolphosphate synthase (CDP-diacylglycerol: sn-glycerol-3-phosphate 3-phosphatidyltransferase, EC 2.7.8.5) is an essential enzyme in biosynthesis of cardiolipin. In this work we report the isolation, heterological cloning, molecular characterization and physical mapping of the Saccharomyces cerevisiae PEL1/PGS1 homologue from Kluyveromyces lactis. The pel1 mutant strain of S. cerevisiae was used to isolate this homologue by screening a K. lactis genomic library. The novel cloned gene was named KlPGS1. Its coding region was found to consist of 1623 bp. The corresponding protein exhibits 55% amino acid identity to its S. cerevisiae counterpart. The presence of the mitochondrial presequence indicates its mitochondrial localization. Sporulation and ascus dissection of diploids heterozygous for single-copy disruption of KlPGS1 revealed that the KlPGS1 gene, is essential in K. lactis. Using a DIG-dUTP-labeled DNA probe-originated from the KlPGS1 gene and Southern hybridization of contour-clamped homogeneous electric field (CHEF)-separated K. lactis chromosomal DNA, the KlPGS1 gene was assigned to chromosome I. The nucleotide sequence data reported in this paper were submitted to GenBank and assigned the Accession No. AY176328.

The introduction of wire-free microcirculatory resistance index from functional angiography (angio-IMR) promises swift detection of coronary microvascular dysfunction, however it has not been properly validated. We sought to validate angio-IMR against invasive IMR and PET derived microvascular resistance (MVR). Moreover, we studied if angio-IMR could aid in the detection of ischemia with non-obstructive coronary arteries (INOCA). In this investigator-initiated study symptomatic patients underwent [ O]H O positron emission tomography (PET) and invasive angiography with 3-vessel fractional flow reserve (FFR). Invasive IMR was measured in 40 patients. Angio-IMR and QFR were computed retrospectively. MVR was defined as the ratio of mean distal coronary pressure to PET derived coronary flow. PET and QFR/angio-IMR analyses were performed by blinded core labs. The right coronary artery was excluded. A total of 211 patients (mean age 61 ± 9, 148 (70%) male) with 312 vessels with successful angio-IMR analyses were included. Angio-IMR correlated moderately with invasive IMR (r = 0.48, p < 0.01), whereas no correlation was found between angio-IMR and MVR (r=-0.07, p = 0.25). Angio-IMR did not differ for vessels without obstructive coronary artery disease (CAD) (FFR-) but with reduced stress perfusion (PET+) compared to vessels without obstructive CAD (FFR-) with normal stress perfusion (PET-) (median 28.19 IQR 20.42-38.99 vs. 31.67 IQR 23.47-40.63, p = 0.40). Angio-IMR correlated moderately with invasively measured IMR, whereas angio-IMR did not correlate with PET derived MVR. Moreover, angio-IMR did not reliably identify patients with INOCA.

During the last years commercial hyperspectral imaging sensors have been miniaturized and their performance has been demonstrated on Unmanned Aerial Vehicles (UAV). However currently the commercial hyperspectral systems still require minimum payload capacity of approximately 3 kg, forcing usage of rather large UAVs. In this article we present a lightweight hyperspectral mapping system (HYMSY) for rotor-based UAVs, the novel processing chain for the system, and its potential for agricultural mapping and monitoring applications. The HYMSY consists of a custom-made pushbroom spectrometer (400–950 nm, 9 nm FWHM, 25 lines/s, 328 px/line), a photogrammetric camera, and a miniature GPS-Inertial Navigation System. The weight of HYMSY in ready-to-fly configuration is only 2.0 kg and it has been constructed mostly from off-the-shelf components. The processing chain uses a photogrammetric algorithm to produce a Digital Surface Model (DSM) and provides high accuracy orientation of the system over the DSM. The pushbroom data is georectified by projecting it onto the DSM with the support of photogrammetric orientations and the GPS-INS data. Since an up-to-date DSM is produced internally, no external data are required and the processing chain is capable to georectify pushbroom data fully automatically. The system has been adopted for several experimental flights related to agricultural and habitat monitoring applications. For a typical flight, an area of 2–10 ha was mapped, producing a RGB orthomosaic at 1–5 cm resolution, a DSM at 5–10 cm resolution, and a hyperspectral datacube at 10–50 cm resolution.

Accurate retrieval of grassland traits is important to support management of pasture production and phenotyping studies. In general, conventional methods used to measure forage yield and quality rely on costly destructive sampling and laboratory analysis, which is often not viable in practical applications. Optical imaging systems carried as payload in Unmanned Aerial Vehicles (UAVs) platforms have increasingly been proposed as alternative non-destructive solutions for crop characterization and monitoring. The vegetation spectral response in the visible and near-infrared wavelengths provides information on many aspects of its composition and structure. Combining spectral measurements and multivariate modelling approaches it is possible to represent the often complex relationship between canopy reflectance and specific plant traits. However, empirical models are limited and strictly represent characteristics of the observations used during model training, therefore having low generalization potential. A method to mitigate this issue consists of adding informative samples from the target domain (i.e., new observations) to the training dataset. This approach searches for a compromise between representing the variability in new data and selecting only a minimal number of additional samples for calibration transfer. In this study, a method to actively choose new training samples based on their spectral diversity and prediction uncertainty was implemented and tested using a multi-annual dataset. Accurate predictions were obtained using hyperspectral imagery and linear multivariate models (Partial Least Squares Regression—PLSR) for grassland dry matter (DM; R2 = 0.92, RMSE = 3.25 dt ha−1), nitrogen (N) content in % of DM (R2 = 0.58, RMSE = 0.27%) and N-uptake (R2 = 0.91, RMSE = 6.50 kg ha−1). In addition, the number of samples from the target dates added to the training dataset could be reduced by up to 77% and 74% for DM and N-related traits, respectively, after model transfer. Despite this reduction, RMSE values for optimal transfer sets (identified after validation and used as benchmark) were only 20–30% lower than those values obtained after model transfer based on prediction uncertainty reduction, indicating that loss of accuracy was relatively small. These results demonstrate that considerably simple approaches based on UAV hyperspectral data can be applied in preliminary grassland monitoring frameworks, even with limited datasets.

Endoplasmic reticulum associated degradation (ERAD) is a conserved mechanism to remove misfolded proteins from the ER by targeting them to the proteasome for degradation. To assess the role of ERAD in filamentous fungi, we have examined the consequences of disrupting putative ERAD components in the filamentous fungus Aspergillus niger. Deletion of derA, doaA, hrdC, mifA, or mnsA in A. niger yields viable strains, and with the exception of doaA, no significant growth phenotype is observed when compared to the parental strain. The gene deletion mutants were also made in A. niger strains containing single- or multicopies of a glucoamylase-glucuronidase (GlaGus) gene fusion. The induction of the unfolded protein response (UPR) target genes (bipA and pdiA) was dependent on the copy number of the heterologous gene and the ERAD gene deleted. The highest induction of UPR target genes was observed in ERAD mutants containing multiple copies of the GlaGus gene. Western blot analysis revealed that deletion of the derA gene in the multicopy GlaGus overexpressing strain resulted in a 6-fold increase in the intracellular amount of GlaGus protein detected. Our results suggest that impairing some components of the ERAD pathway in combination with high expression levels of the heterologous protein results in higher intracellular protein levels, indicating a delay in protein degradation. [PUBLICATION ABSTRACT]