A new method for an objective, χ2\chi^2-based spectroscopic analysis of early-type stars

A precise quantitative spectral analysis - encompassing atmospheric parameter and chemical elemental abundance determination - is time consuming due to its iterative nature and the multi-parameter space to be explored, especially when done "by eye". A robust automated fitting technique that is as trustworthy as traditional methods would allow for large samples of stars to be analyzed in a consistent manner in reasonable time. We present a semi-automated quantitative spectral analysis technique for early-type stars based on the concept of $\chi^2$ minimization. The method's main features are: far less subjective than typical "by eye" methods, correction for inaccurate continuum normalization, consideration of the whole useful spectral range, simultaneous sampling of the entire multi-parameter space (effective temperature, surface gravity, microturbulence, macroturbulence, projected rotational velocity, radial velocity, elemental abundances) to find the global best solution, applicable also to composite spectra. The method is fast, robust and reliable as seen from formal tests and from a comparison with previous analyses. Consistent quantitative spectral analyses of large samples of early-type stars can be performed quickly with very high accuracy.Comment: 32 pages, 4 figures, Astronomy and Astrophysics, accepte

Hesitation Processing Analysis Using Continuous Mouse-Tracking and Gamification

Betz S, Székély E, Zarrieß S, Schröer M, Schade L, Wagner P. Hesitation Processing Analysis Using Continuous Mouse-Tracking and Gamification. In: Wendemuth A, Böck R, Siegert I, eds. Elektronische Sprachsignalverarbeitung 2020. Tagungsband der 31. Konferenz. Studientexte zur Sprachkommunikation. Vol 95. Dresden: TUD Press; 2020: 85-92

Effect of Processing Intensity on Immunologically Active Bovine Milk Serum Proteins

Consumption of raw cow's milk instead of industrially processed milk has been reported to protect children from developing asthma, allergies, and respiratory infections. Several heat-sensitive milk serum proteins have been implied in this effect though unbiased assessment of milk proteins in general is missing. The aim of this study was to compare the native milk serum proteome between raw cow's milk and various industrially applied processing methods, i.e., homogenization, fat separation, pasteurization, ultra-heat treatment (UHT), treatment for extended shelf-life (ESL), and conventional boiling. Each processing method was applied to the same three pools of raw milk. Levels of detectable proteins were quantified by liquid chromatography/tandem mass spectrometry following filter aided sample preparation. In total, 364 milk serum proteins were identified. The 140 proteins detectable in 66% of all samples were entered in a hierarchical cluster analysis. The resulting proteomics pattern separated mainly as high (boiling, UHT, ESL) versus no/low heat treatment (raw, skimmed, pasteurized). Comparing these two groups revealed 23 individual proteins significantly reduced by heating, e.g., lactoferrin (log2-fold change = -0.37, p = 0.004), lactoperoxidase (log2-fold change = -0.33, p = 0.001), and lactadherin (log2-fold change = -0.22, p = 0.020). The abundance of these heat sensitive proteins found in higher quantity in native cow's milk compared to heat treated milk, renders them potential candidates for protection from asthma, allergies, and respiratory infections

Targeted panel sequencing in the routine diagnosis of mature T- and NK-cell lymphomas: report of 128 cases from two German reference centers

Diagnosing any of the more than 30 types of T-cell lymphomas is considered a challenging task for many pathologists and currently requires morphological expertise as well as the integration of clinical data, immunophenotype, flow cytometry and clonality analyses. Even considering all available information, some margin of doubt might remain using the current diagnostic procedures. In recent times, the genetic landscape of most T-cell lymphomas has been elucidated, showing a number of diagnostically relevant mutations. In addition, recent data indicate that some of these genetic alterations might bear prognostic and predictive value. Extensive genetic analyses, such as whole exome or large panel sequencing are still expensive and time consuming, therefore limiting their application in routine diagnostic. We therefore devoted our effort to develop a lean approach for genetic analysis of T-cell lymphomas, focusing on maximum efficiency rather than exhaustively covering all possible targets. Here we report the results generated with our small amplicon-based panel that could be used routinely on paraffin-embedded and even decalcified samples, on a single sample basis in parallel with other NGS-panels used in our routine diagnostic lab, in a relatively short time and with limited costs. We tested 128 available samples from two German reference centers as part of our routine work up (among which 116 T-cell lymphomas), which is the largest routine diagnostic series reported to date. Our results showed that this assay had a very high rate of technical success (97%) and could detect mutations in the majority (79%) of tested T-cell lymphoma samples

Switch in KRAS mutational status during an unusual course of disease in a patient with advanced pancreatic adenocarcinoma: implications for translational research

Background: Despite the introduction of novel effective treatment regimens like gemcitabine plus nab-paclitaxel and FOLFIRINOX, pancreatic ductal adenocarcinoma (PDAC) remains one of the most aggressive epithelial tumors. Among the genetic alterations frequently found in PDAC, mutations in the KRAS gene might play a prognostic role regarding overall survival and may also have the potential to predict the efficacy of anti-EGFR treatment. Case presentation: We report the clinical case of a 69 year old Caucasian female that was diagnosed with histologically confirmed locally advanced PDAC with lymph node involvement in August 2010. At the time of first diagnosis, tumor tissue obtained from an open regional lymph node biopsy showed a poorly differentiated adenocarcinoma with a wild type sequence within exon 2 (codon 12/13) of the KRAS gene. The patient initially received single-agent gemcitabine and a subsequent 5-FU-based chemoradiotherapy with a sequential maintenance chemotherapy with oral capecitabine resulting in a long term disease control. Local disease progression occurred in May 2014 and the patient underwent pancreaticoduodenectomy in September 2014. A novel KRAS gene mutation (c. 35G > T, p. G12 V) in exon 2 (codon 12) was detected within the surgical specimen. As of January 2016 the patient is still alive and without evidence of the underlying disease. Conclusions: Specifically in the context of clinical trials and translational research in PDAC a re-assessment of molecular biomarkers, i.e. KRAS, at defined time points (e.g. relapse, disease progression, unusual clinical course) may be indicated in order to detect a potential switch in biomarker status during the course of disease

An integrated molecular risk score early in life for subsequent childhood asthma risk.

BACKGROUND Numerous children present with early wheeze symptoms, yet solely a subgroup develops childhood asthma. Early identification of children at risk is key for clinical monitoring, timely patient-tailored treatment, and preventing chronic, severe sequelae. For early prediction of childhood asthma, we aimed to define an integrated risk score combining established risk factors with genome-wide molecular markers at birth, complemented by subsequent clinical symptoms/diagnoses (wheezing, atopic dermatitis, food allergy). METHODS Three longitudinal birth cohorts (PAULINA/PAULCHEN, n = 190 + 93 = 283, PASTURE, n = 1133) were used to predict childhood asthma (age 5-11) including epidemiological characteristics and molecular markers: genotype, DNA methylation and mRNA expression (RNASeq/NanoString). Apparent (ap) and optimism-corrected (oc) performance (AUC/R2) was assessed leveraging evidence from independent studies (Naïve-Bayes approach) combined with high-dimensional logistic regression models (LASSO). RESULTS Asthma prediction with epidemiological characteristics at birth (maternal asthma, sex, farm environment) yielded an ocAUC = 0.65. Inclusion of molecular markers as predictors resulted in an improvement in apparent prediction performance, however, for optimism-corrected performance only a moderate increase was observed (upto ocAUC = 0.68). The greatest discriminate power was reached by adding the first symptoms/diagnosis (up to ocAUC = 0.76; increase of 0.08, p = .002). Longitudinal analysis of selected mRNA expression in PASTURE (cord blood, 1, 4.5, 6 years) showed that expression at age six had the strongest association with asthma and correlation of genes getting larger over time (r = .59, p < .001, 4.5-6 years). CONCLUSION Applying epidemiological predictors alone showed moderate predictive abilities. Molecular markers from birth modestly improved prediction. Allergic symptoms/diagnoses enhanced the power of prediction, which is important for clinical practice and for the design of future studies with molecular markers

3D Visualization, Skeletonization and Branching Analysis of Blood Vessels in Angiogenesis

Angiogenesis is the process of new blood vessels growing from existing vasculature. Visualizing them as a three-dimensional (3D) model is a challenging, yet relevant, task as it would be of great help to researchers, pathologists, and medical doctors. A branching analysis on the 3D model would further facilitate research and diagnostic purposes. In this paper, a pipeline of vision algorithms is elaborated to visualize and analyze blood vessels in 3D from formalin-fixed paraffin-embedded (FFPE) granulation tissue sections with two different staining methods. First, a U-net neural network is used to segment blood vessels from the tissues. Second, image registration is used to align the consecutive images. Coarse registration using an image-intensity optimization technique, followed by finetuning using a neural network based on Spatial Transformers, results in an excellent alignment of images. Lastly, the corresponding segmented masks depicting the blood vessels are aligned and interpolated using the results of the image registration, resulting in a visualized 3D model. Additionally, a skeletonization algorithm is used to analyze the branching characteristics of the 3D vascular model. In summary, computer vision and deep learning is used to reconstruct, visualize and analyze a 3D vascular model from a set of parallel tissue samples. Our technique opens innovative perspectives in the pathophysiological understanding of vascular morphogenesis under different pathophysiological conditions and its potential diagnostic role

Causal Agents of Hop Dying

Stockfaule Hopfenpflanzen im Hopfenanbaugebiet Spalt bei Nürnberg weisen Befall mit dem Gefäßparasiten Ceratocystis paradoxa auf. Aus Bodenproben von über 100-jährigen Hopfengärten konnten die Pilze Fusarium oxysporum und F. equiseti isoliert werden. Bei der mikroskopischen Untersuchung von Hopfenwurzeln wurden Pilze der Gattungen Rhizoctonia und Pythium gefunden, die als Wurzelfäule-Erreger bekannt sind. An Faserwurzeln war starker Befall mit Hopfen-Zystennematoden (Heterodera humili), sowie an Haarwurzeln Befall mit Strahlenpilzen (Actinomycetes) zu erkennen, die für Bodenmüdigkeitserscheinungen verantwortlich sind.Rotten hop-stocks in the hop growing area of Spalt near Nuremberg were attacked by the vessels-invading fungus Ceratocystis paradoxa. The fungi Fusarium oxysporum and F. equiseti could be isolated from soil of a 100 years old hop garden. By microscopic examination, fungi of the genera Rhizoctonia and Pythium were found, which are known as root rot pathogens. The filamentous roots were severely attacked by hop cyst nematodes (Heterodera humili), and the hairy roots were infested with Actinomycetes, both responsible for the soil exhaustion syndrom

Isotopic measurements in water vapor, precipitation, and seawater during EUREC4^4A

n early 2020, an international team set out to investigate trade-wind cumulus clouds and their coupling to the large-scale circulation through the field campaign EUREC$^4$A: ElUcidating the RolE of Clouds-Circulation Coupling in ClimAte. Focused on the western tropical Atlantic near Barbados, EUREC$^4$A deployed a number of innovative observational strategies, including a large network of water isotopic measurements collectively known as EUREC$^4$A-iso, to study the tropical shallow convective environment. The goal of the isotopic measurements was to elucidate processes that regulate the hydroclimate state – for example, by identifying moisture sources, quantifying mixing between atmospheric layers, characterizing the microphysics that influence the formation and persistence of clouds and precipitation, and providing an extra constraint in the evaluation of numerical simulations. During the field experiment, researchers deployed seven water vapor isotopic analyzers on two aircraft, on three ships, and at the Barbados Cloud Observatory (BCO). Precipitation was collected for isotopic analysis at the BCO and from aboard four ships. In addition, three ships collected seawater for isotopic analysis. All told, the in situ data span the period 5 January–22 February 2020 and cover the approximate area 6 to 16° N and 50 to 60° W, with water vapor isotope ratios measured from a few meters above sea level to the mid-free troposphere and seawater samples spanning the ocean surface to several kilometers depth. This paper describes the full EUREC$^4$A isotopic in situ data collection – providing extensive information about sampling strategies and data uncertainties – and also guides readers to complementary remotely sensed water vapor isotope ratios. All field data have been made publicly available even if they are affected by known biases, as is the case for high-altitude aircraft measurements, one of the two BCO ground-based water vapor time series, and select rain and seawater samples from the ships. Publication of these data reflects a desire to promote dialogue around improving water isotope measurement strategies for the future. The remaining, high-quality data create unprecedented opportunities to close water isotopic budgets and evaluate water fluxes and their influence on cloudiness in the trade-wind environment. The full list of dataset DOIs and notes on data quality flags are provided in Table 3 of Sect. 5 (“Data availability”)