Rapid low-cost hyperspectral imaging system for quantitative assessment of infantile hemangioma

Hemangioma, the predominant benign tumor occurring in infancy, exhibits a wide range of prognoses and associated outcomes. The accurate determination of prognosis through noninvasive imaging modalities holds essential importance in enabling effective personalized treatment strategies and minimizing unnecessary surgical interventions for individual patients. The present study focuses on advancing the personalized prognosis of hemangioma by leveraging noninvasive optical sensing technologies by the development of a novel rapid hyperspectral sensor (image collection in 5 s, lateral resolution of 10 μm) that is capable of quantifying hemoglobin oxygenation and vascularization dynamics during the course of tumor evolution. We have developed a quantitative parameter for hemangioma assessment, that demonstrated agreement with the clinician's conclusion in 90% among all cases during clinical studies on six patients, who visited clinician from two to four times. The presented methodology has potential to be implemented as a supportive tool for accurate hemangioma diagnostics in clinics.

Full-optical photoacoustic imaging using speckle analysis and resolution enhancement by orthogonal pump patterns projection

This paper presents an approach for achieving full optical photoacoustic imaging with enhanced resolution utilizing speckle pattern analysis. The proposed technique involves projecting patterns derived from binary masks corresponding to orthogonal functions onto the target to elicit a photoacoustic signal. The resulting signal is then recorded using a high-speed camera and analyzed using correlation analysis of the speckle motion. Our results demonstrate the feasibility of this optical approach to achieve imaging with enhanced resolution without the need for physical contact with the target, opening up new possibilities for non-invasive medical imaging and other applications.

Electrical Heaters for Anti/De-Icing of Polymer Structures

The problem of icing for surfaces of engineering structures requires attention more and more every year. Active industrialization in permafrost zones is currently underway; marine transport in Arctic areas targets new goals; the requirements for aerodynamically critical surfaces of wind generators and aerospace products, serving at low temperatures, are increasing; and fiber-reinforced polymer composites find wide applicability in these structural applications demanding the problem of anti/de-icing to be addressed. The traditional manufacturing approaches are superimposed with the new technologies, such as 3D printers and robotics for laying heat wires or cheap and high-performance Thermal Sprayed methods for metallic cover manufacturing. Another next step in developing heaters for polymer structures is nano and micro additives to create electrically conductive heating networks within. In our study, we review and comparatively analyze the modern technologies of structure heating, based on resistive heating composites.

Host nucleases generate prespacers for primed adaptation in the E. coli type I-E CRISPR-Cas system

CRISPR-Cas systems provide prokaryotes with adaptive immunity against foreign nucleic acids. In Escherichia coli, immunity is acquired upon integration of 33-bp spacers into CRISPR arrays. DNA targets complementary to spacers get degraded and serve as a source of new spacers during a process called primed adaptation. Precursors of such spacers, prespacers, are ~33-bp double-stranded DNA fragments with a ~4-nt 3' overhang. The mechanism of prespacer generation is not clear. Here, we use FragSeq and biochemical approaches to determine enzymes involved in generation of defined prespacer ends. We demonstrate that RecJ is the main exonuclease trimming 5' ends of prespacer precursors, although its activity can be partially substituted by ExoVII. The RecBCD complex allows single strand-specific RecJ to process double-stranded regions flanking prespacers. Our results reveal intricate functional interactions of genome maintenance proteins with CRISPR interference and adaptation machineries during generation of prespacers capable of integration into CRISPR arrays.

Uncertainty-aware and interpretable evaluation of Cas9-gRNA and Cas12a-gRNA specificity for fully matched and partially mismatched targets with Deep Kernel Learning

The choice of guide RNA (gRNA) for CRISPR-based gene targeting is an essential step in gene editing applications, but the prediction of gRNA specificity remains challenging. Lack of transparency and focus on point estimates of efficiency disregarding the information on possible error sources in the model limit the power of existing Deep Learning-based methods. To overcome these problems, we present a new approach, a hybrid of Capsule Networks and Gaussian Processes. Our method predicts the cleavage efficiency of a gRNA with a corresponding confidence interval, which allows the user to incorporate information regarding possible model errors into the experimental design. We provide the first utilization of uncertainty estimation in computational gRNA design, which is a critical step toward accurate decision-making for future CRISPR applications. The proposed solution demonstrates acceptable confidence intervals for most test sets and shows regression quality similar to existing models. We introduce a set of criteria for gRNA selection based on off-target cleavage efficiency and its variance and present a collection of pre-computed gRNAs for human chromosome 22. Using Neural Network Interpretation methods, we show that our model rediscovers an established biological factor underlying cleavage efficiency, the importance of the seed region in gRNA.

The Arg/N-Degron Pathway-A Potential Running Back in Fine-Tuning the Inflammatory Response?

Recognition of danger signals by a cell initiates a powerful cascade of events generally leading to inflammation. Inflammatory caspases and several other proteases become activated and subsequently cleave their target proinflammatory mediators. The irreversible nature of this process implies that the newly generated proinflammatory fragments need to be sequestered, inhibited, or degraded in order to cancel the proinflammatory program or prevent chronic inflammation. The Arg/N-degron pathway is a ubiquitin-dependent proteolytic pathway that specifically degrades protein fragments bearing N-degrons, or destabilizing residues, which are recognized by the E3 ligases of the pathway. Here, we report that the Arg/N-degron pathway selectively degrades a number of proinflammatory fragments, including some activated inflammatory caspases, contributing in tuning inflammatory processes. Partial ablation of the Arg/N-degron pathway greatly increases IL-1β secretion, indicating the importance of this ubiquitous pathway in the initiation and resolution of inflammation. Thus, we propose a model wherein the Arg/N-degron pathway participates in the control of inflammation in two ways: in the generation of inflammatory signals by the degradation of inhibitory anti-inflammatory domains and as an “off switch” for inflammatory responses through the selective degradation of proinflammatory fragments.

Physical Activity Intervention for Loneliness (PAIL) in community-dwelling older adults: a randomised feasibility study

BACKGROUND

Low quality social relationships in older adults are strongly associated with feelings of loneliness. Physical activity interventions could reduce loneliness and improve psychological well-being, among other health benefits. The aim of this study was to examine the feasibility of a Physical Activity Intervention for Loneliness (PAIL) in community-dwelling older adults at risk of loneliness.

METHODS

The PAIL feasibility study was a 12-week randomized controlled feasibility trial (RCT) conducted in Birmingham, United Kingdom, from February 2018 to August 2018, and ran in two waves of data collection. Eligible participants were community-dwelling adults aged 60 years and older, sedentary (less than 20 min of moderate-to-vigorous PA (MVPA) a week), and at risk of loneliness. The intervention included once-weekly group walk and health education workshop up to 90 min per session in total, with a wait-listed (WL) control group. The primary feasibility outcomes were to estimate recruitment, retention rates and adherence to the intervention. Secondary outcome measures (not blinded assessment) were body mass index, blood pressure, physical activity and psychosocial variables. Process and outcome evaluations were conducted using focus groups interviews. The recruitment and retention progression criteria for the definitive large-scale RCT was set a-priori.

RESULTS

Forty-eight participants were recruited over 4 months with a recruitment rate of 25% (48/195); 52% (25/48) met the inclusion criteria and 100% (25/25) were randomised into the intervention (n = 12) and WL control groups (n = 13). Participants were 25 older adults (mean (SD) 68.5(8.05) years), 14 (56%) female, and 18 (72%) white. At 12 weeks, 10/12 (83.3%) intervention and 10/13 (76.9%) control participants completed the final assessments. The average attendance rate was 58.3% for the intervention group (range 33.0%-75.0%) and 42.3% (range 23.1%-69.2%) among controls. The a priori recruitment and retention criteria for progression were not met. No serious adverse events occurred. The focus group results identified three themes which showed overall positive experiences of participation in PAIL in terms of (1) study design and intervention; (2) walking sessions; and (3) health education workshops.

CONCLUSIONS

The findings suggest that community-dwelling older adults at risk of loneliness found the intervention and measures acceptable and could safely participate. However, a more extensive and robust strategy would be needed to support adequate recruitment of lonely older adults and adherence into a definitive RCT.

TRIAL REGISTRATION

Clinicaltrials.gov, NCT03458793.

Detecting T cell receptors involved in immune responses from single repertoire snapshots

Hypervariable T cell receptors (TCRs) play a key role in adaptive immunity, recognizing a vast diversity of pathogen-derived antigens. Our ability to extract clinically relevant information from large high-throughput sequencing of TCR repertoires (RepSeq) data is limited, because little is known about TCR-disease associations. We present Antigen-specific Lymphocyte Identification by Clustering of Expanded sequences (ALICE), a statistical approach that identifies TCR sequences actively involved in current immune responses from a single RepSeq sample and apply it to repertoires of patients with a variety of disorders - patients with autoimmune disease (ankylosing spondylitis [AS]), under cancer immunotherapy, or subject to an acute infection (live yellow fever [YF] vaccine). We validate the method with independent assays. ALICE requires no longitudinal data collection nor large cohorts, and it is directly applicable to most RepSeq datasets. Its results facilitate the identification of TCR variants associated with diseases and conditions, which can be used for diagnostics and rational vaccine design.

DoGNet: A deep architecture for synapse detection in multiplexed fluorescence images

Neuronal synapses transmit electrochemical signals between cells through the coordinated action of presynaptic vesicles, ion channels, scaffolding and adapter proteins, and membrane receptors. In situ structural characterization of numerous synaptic proteins simultaneously through multiplexed imaging facilitates a bottom-up approach to synapse classification and phenotypic description. Objective automation of efficient and reliable synapse detection within these datasets is essential for the high-throughput investigation of synaptic features. Convolutional neural networks can solve this generalized problem of synapse detection, however, these architectures require large numbers of training examples to optimize their thousands of parameters. We propose DoGNet, a neural network architecture that closes the gap between classical computer vision blob detectors, such as Difference of Gaussians (DoG) filters, and modern convolutional networks. DoGNet is optimized to analyze highly multiplexed microscopy data. Its small number of training parameters allows DoGNet to be trained with few examples, which facilitates its application to new datasets without overfitting. We evaluate the method on multiplexed fluorescence imaging data from both primary mouse neuronal cultures and mouse cortex tissue slices. We show that DoGNet outperforms convolutional networks with a low-to-moderate number of training examples, and DoGNet is efficiently transferred between datasets collected from separate research groups. DoGNet synapse localizations can then be used to guide the segmentation of individual synaptic protein locations and spatial extents, revealing their spatial organization and relative abundances within individual synapses. The source code is publicly available: https://github.com/kulikovv/dognet.

Natural variation of piRNA expression affects immunity to transposable elements

In the Drosophila germline, transposable elements (TEs) are silenced by PIWI-interacting RNA (piRNA) that originate from distinct genomic regions termed piRNA clusters and are processed by PIWI-subfamily Argonaute proteins. Here, we explore the variation in the ability to restrain an alien TE in different Drosophila strains. The I-element is a retrotransposon involved in the phenomenon of I-R hybrid dysgenesis in Drosophila melanogaster. Genomes of R strains do not contain active I-elements, but harbour remnants of ancestral I-related elements. The permissivity to I-element activity of R females, called reactivity, varies considerably in natural R populations, indicating the existence of a strong natural polymorphism in defense systems targeting transposons. To reveal the nature of such polymorphisms, we compared ovarian small RNAs between R strains with low and high reactivity and show that reactivity negatively correlates with the ancestral I-element-specific piRNA content. Analysis of piRNA clusters containing remnants of I-elements shows increased expression of the piRNA precursors and enrichment by the Heterochromatin Protein 1 homolog, Rhino, in weak R strains, which is in accordance with stronger piRNA expression by these regions. To explore the nature of the differences in piRNA production, we focused on two R strains, weak and strong, and showed that the efficiency of maternal inheritance of piRNAs as well as the I-element copy number are very similar in both strains. At the same time, germline and somatic uni-strand piRNA clusters generate more piRNAs in strains with low reactivity, suggesting the relationship between the efficiency of primary piRNA production and variable response to TE invasions. The strength of adaptive genome defense is likely driven by naturally occurring polymorphisms in the rapidly evolving piRNA pathway proteins. We hypothesize that hyper-efficient piRNA production is contributing to elimination of a telomeric retrotransposon HeT-A, which we have observed in one particular transposon-resistant R strain.

Transposon activity in the germline is suppressed by the PIWI-interacting RNA (piRNA) pathway. The resistance of natural Drosophila strains to transposon invasion varies considerably, but the nature of this variability is unknown. We discovered that natural variation in the efficiency of primary piRNA production in the germline causes dramatic differences in the susceptibility to expansion of a newly invaded transposon. A high level of piRNA production in the germline is achieved by increased expression of piRNA precursors. In one of the most transposon-resistant strains, increased content of primary piRNA is observed in both the germline and ovarian somatic cells. We suggest that polymorphisms in piRNA pathway factors are responsible for increased piRNA production. piRNA pathway proteins have been shown to be evolving rapidly under selective pressure. Our data are the first to describe a phenotype that might be caused by this kind of polymorphism. We also demonstrate a likely explanation as to why an overly active piRNA pathway can cause more harm than good in Drosophila: Highly efficient piRNA processing leads to elimination of domesticated telomeric retrotransposons essential for telomere elongation, an effect which has been observed in a natural strain that is extremely resistant to transposon invasion.