High-speed, high-frequency ultrasound, \u3ci\u3ein utero\u3c/i\u3e vector-flow imaging of mouse embryos

Real-time imaging of the embryonic murine cardiovascular system is challenging due to the small size of the mouse embryo and rapid heart rate. High-frequency, linear-array ultrasound systems designed for small-animal imaging provide high-frame-rate and Doppler modes but are limited in regards to the field of view that can be imaged at fine-temporal and -spatial resolution. Here, a plane-wave imaging method was used to obtain high-speed image data from in utero mouse embryos and multi-angle, vector-flow algorithms were applied to the data to provide information on blood flow patterns in major organs. An 18-MHz linear array was used to acquire plane-wave data at absolute frame rates ≥10 kHz using a set of fixed transmission angles. After beamforming, vector-flow processing and image compounding, effective frame rates were on the order of 2 kHz. Data were acquired from the embryonic liver, heart and umbilical cord. Vector-flow results clearly revealed the complex nature of blood-flow patterns in the embryo with fine-temporal and -spatial resolution

Deep Mouse: An End-to-end Auto-context Refinement Framework for Brain Ventricle and Body Segmentation in Embryonic Mice Ultrasound Volumes

High-frequency ultrasound (HFU) is well suited for imaging embryonic mice due to its noninvasive and real-time characteristics. However, manual segmentation of the brain ventricles (BVs) and body requires substantial time and expertise. This work proposes a novel deep learning based end-to-end auto-context refinement framework, consisting of two stages. The first stage produces a low resolution segmentation of the BV and body simultaneously. The resulting probability map for each object (BV or body) is then used to crop a region of interest (ROI) around the target object in both the original image and the probability map to provide context to the refinement segmentation network. Joint training of the two stages provides significant improvement in Dice Similarity Coefficient (DSC) over using only the first stage (0.818 to 0.906 for the BV, and 0.919 to 0.934 for the body). The proposed method significantly reduces the inference time (102.36 to 0.09 s/volume around 1000x faster) while slightly improves the segmentation accuracy over the previous methods using slide-window approaches.Comment: Full Paper Submission to ISBI 202

Experience sampling reveals the role that covert goal states play in task-relevant behavior

Cognitive neuroscience has gained insight into covert states using experience sampling. Traditionally, this approach has focused on off-task states. However, task-relevant states are also maintained via covert processes. Our study examined whether experience sampling can also provide insights into covert goal-relevant states that support task performance. To address this question, we developed a neural state space, using dimensions of brain function variation, that allows neural correlates of overt and covert states to be examined in a common analytic space. We use this to describe brain activity during task performance, its relation to covert states identified via experience sampling, and links between individual variation in overt and covert states and task performance. Our study established deliberate task focus was linked to faster target detection, and brain states underlying this experience—and target detection—were associated with activity patterns emphasizing the fronto-parietal network. In contrast, brain states underlying off-task experiences—and vigilance periods—were linked to activity patterns emphasizing the default mode network. Our study shows experience sampling can not only describe covert states that are unrelated to the task at hand, but can also be used to highlight the role fronto-parietal regions play in the maintenance of covert task-relevant states

TESS asteroseismology of the known red-giant host stars HD 212771 and HD 203949

International audienc

Depsipeptide substrates for sortase-mediated N-terminal protein ligation

Technologies that allow the efficient chemical modification of proteins under mild conditions are widely sought after. Sortase-mediated peptide ligation provides a strategy for modifying the N or C terminus of proteins. This protocol describes the use of depsipeptide substrates (containing an ester linkage) with sortase A (SrtA) to completely modify proteins carrying a single N-terminal glycine residue under mild conditions in 4–6 h. The SrtA-mediated ligation reaction is reversible, so most labeling protocols that use this enzyme require a large excess of both substrate and sortase to produce high yields of ligation product. In contrast, switching to depsipeptide substrates effectively renders the reaction irreversible, allowing complete labeling of proteins with a small excess of substrate and catalytic quantities of sortase. Herein we describe the synthesis of depsipeptide substrates that contain an ester linkage between a threonine and glycolic acid residue and an N-terminal FITC fluorophore appended via a thiourea linkage. The synthesis of the depsipeptide substrate typically takes 2–3 d

Probing Real Sensory Worlds of Receivers with Unsupervised Clustering

The task of an organism to extract information about the external environment from sensory signals is based entirely on the analysis of ongoing afferent spike activity provided by the sense organs. We investigate the processing of auditory stimuli by an acoustic interneuron of insects. In contrast to most previous work we do this by using stimuli and neurophysiological recordings directly in the nocturnal tropical rainforest, where the insect communicates. Different from typical recordings in sound proof laboratories, strong environmental noise from multiple sound sources interferes with the perception of acoustic signals in these realistic scenarios. We apply a recently developed unsupervised machine learning algorithm based on probabilistic inference to find frequently occurring firing patterns in the response of the acoustic interneuron. We can thus ask how much information the central nervous system of the receiver can extract from bursts without ever being told which type and which variants of bursts are characteristic for particular stimuli. Our results show that the reliability of burst coding in the time domain is so high that identical stimuli lead to extremely similar spike pattern responses, even for different preparations on different dates, and even if one of the preparations is recorded outdoors and the other one in the sound proof lab. Simultaneous recordings in two preparations exposed to the same acoustic environment reveal that characteristics of burst patterns are largely preserved among individuals of the same species. Our study shows that burst coding can provide a reliable mechanism for acoustic insects to classify and discriminate signals under very noisy real-world conditions. This gives new insights into the neural mechanisms potentially used by bushcrickets to discriminate conspecific songs from sounds of predators in similar carrier frequency bands

Speaking of Contradiction

Whereas McGovern calls for a moratorium on the ever increasing (ab)use of the word ‘contradiction’, principally because scholars of work and employment fail to connect different levels of analysis and/or demonstrate how and why contradiction(s) lead to widespread instability and upheaval, it can be demonstrated how both can be achieved through the ‘system, society, dominance’ framework. In what follows, the empirical focus is on the safety-critical work of airport ground service providers (GSPs), where key elements of the employment relationship embody contradictions that can be traced to the (sub-)system (mode of production) of a Single European Aviation Market (SEAM) that is now dominated by low fares airlines (LFAs). Instead of a moratorium, scholars of work and employment need to reconnect with society and theoretically ground their analysis in a (capitalist) system beset with contradictions between the forces and relations of production

Primrose syndrome: Characterization of the phenotype in 42 patients

Primrose syndrome (PS; MIM# 259050) is characterized by intellectual disability (ID), macrocephaly, unusual facial features (frontal bossing, deeply set eyes, down-slanting palpebral fissures), calcified external ears, sparse body hair and distal muscle wasting. The syndrome is caused by de novo heterozygous missense variants in ZBTB20. Most of the 29 published patients are adults as characteristics appear more recognizable with age. We present 13 hitherto unpublished individuals and summarize the clinical and molecular findings in all 42 patients. Several signs and symptoms of PS develop during childhood, but the cardinal features, such as calcification of the external ears, cystic bone lesions, muscle wasting, and contractures typically develop between 10 and 16 years of age. Biochemically, anemia and increased alpha-fetoprotein levels are often present. Two adult males with PS developed a testicular tumor. Although PS should be regarded as a progressive entity, there are no indications that cognition becomes more impaired with age. No obvious genotype-phenotype correlation is present. A subgroup of patients with ZBTB20 variants may be associated with mild, nonspecific ID. Metabolic investigations suggest a disturbed mitochondrial fatty acid oxidation. We suggest a regular surveillance in all adult males with PS until it is clear whether or not there is a truly elevated risk of testicular cancer.This article is freely available via Open Access. Click on the Publisher URL to access it via the publisher's site.published version, accepted version (12 month embargo) submitted versio