Miracle-dz/UniFAR-FTUs huggingface dataset:
Impact of A1 Asymmetry on the Woven EndoBridge Device in Anterior Communicating Artery Aneurysms

BACKGROUND AND PURPOSE: Woven EndoBridge (WEB) devices are increasingly used to treat intracranial aneurysms. A1 asymmetry contributes to anterior communicating artery aneurysm formation and to treatment instability after coiling. We sought to evaluate whether A1 asymmetry had an impact on angiographic outcome in anterior communicating artery aneurysms treated with the WEB. MATERIALS AND METHODS: Anterior communicating artery aneurysms treated between July 2012 and July 2020 with the WEB from an institutional review board–approved database were reviewed. A1 asymmetry was categorized as the following: absence of the A1 segment on 1 side (unilateral A1) versus bilateral A1. Univariate and multivariable analyses assessed independent predictors of adequate (WEB Occlusion Scale A, B, and C) and complete occlusion (WEB Occlusion Scale A and B). RESULTS: Forty-eight individual aneurysms (47 patients) were included in the final analysis, of which 16 (33%) were acutely ruptured. The mean size was 6.5 (SD, 2.2) mm. Adequate and complete occlusion was achieved in 33 (69%) and 30 (63%) cases, respectively. Unilateral A1 was associated with significantly higher rates of adequate (92% versus 60% for bilateral A1; P = .03) and complete occlusion (92% versus 50% for bilateral A1; P < .01). Multivariable logistic regression confirmed unilateral A1 as an independent predictor of both adequate (OR = 10.6; 95% CI, 1.6–220.7; P = .04) and complete occlusion (OR = 9.5, 95% CI, 1.5–190.2; P = .04. A sensitivity analysis comparing unilateral “functional” A1 with bilateral “functional” A1 showed similar results. WEB shape modification was not influenced by the unilateral A1 configuration (P = .70). CONCLUSIONS: Anterior communicating artery aneurysms with a unilateral A1 configuration treated with WEB devices are associated with better angiographic outcome than those with bilateral A1. This finding supports the hypothesis that WEB devices are resistant to unilateral flow in the aneurysm as opposed to coils.
Optimization of the Sample Preparation Procedure for the Conversion of Enriched 28Si Single Crystal to Enriched Gaseous 28SiF4

This work is a detailed study of the investigation of the optimization of the procedure for the conversion of highly enriched 28 Si single crystal into gaseous silicon tetrafluoride ( 28 SiF 4 ) with the highest purity ever achieved. The gaseous 28 Si-F 4 of highest possible purity is required for the determination of silicon molar mass via performing silicon isotope ratio measurements on highly enriched 28 Si (> 99.99% of 28 Si) using electron impact gas mass spectrometry. The problem is in avoiding the contamination of enriched 28 Si samples with silicon of natural isotopic composition. The maximal allowed contamination is in order of 10 -9 g of silicon of natural isotopic composition. The sample preparation of highly enriched 28 Si samples is the largest contributor to the relative combined uncertainty of silicon isotope ratio measure-ments, which should not exceed 1 x 10 -4 . Accordingly this contribution affects the relative combined uncertainty of silicon molar mass. The experiments necessary to achieve this uncertainty in the procedure were carefully designed to avoid superfluous work and to reduce the costs which might be high due to the required quantities of very expensive enriched 28 Si samples. The optimal sample preparation conditions (and execution of these measurements) obtained within this work are part of the large-scale experiments designed for the calibration of Si isotope ratio measurements of highly enriched 28 Si, needed for the final determination of Si molar mass as one of the input quantities needed for determination of the Avogadro constant.
Animal models of chronic and recurrent Pseudomonas aeruginosa lung infection: significance of macrolide treatment

Abstract Animal models of human diseases are invaluable and inevitable elements in identifying and testing novel treatments for serious diseases, including severe infections. Planning and conducting investigator‐initiated human trials are generally accepted as being enormously challenging. In contrast, it is often underestimated how much planning, including background and modifying experiments, is needed to establish a relevant infectious disease animal model. However, representative animal infectious models, well designed to test generated hypotheses, are useful to improve our understanding of pathogenesis, virulence factors and host response and to identify novel treatment candidates and therapeutic strategies. Such results can subsequently proceed to clinical testing if suitable. The present review aims at presenting all the pulmonary Pseudomonas aeruginosa infectious models we have knowledge of and the detailed descriptions of established animal models in our laboratory focusing on macrolide therapy are presented.
Protection of Beta Boswellic Acid against Streptozotocin-induced Alzheimerʼs Model by Reduction of Tau Phosphorylation Level and Enhancement of Reelin Expression

Abstract Alzheimerʼs disease is a growing general health concern with huge implications for individuals and society. Beta boswellic acid, a major compound of the Boswellia serrata plant, has long been used for the treatment of various inflammatory diseases. The exact mechanism of beta boswellic acid action in Alzheimerʼs disease pathogenesis remains unclear. In the current study, the protective effect of beta boswellic acid on streptozotocin-induced sporadic Alzheimerʼs disease was surveyed. Alzheimerʼs disease model was induced using streptozotocin followed by an assessment of the treatment effects of beta boswellic acid in the presence of streptozotocin. The prevention effect of beta boswellic acid on Alzheimerʼs disease induction by streptozotocin was evaluated. Behavioral activities in the treated rats were evaluated. Histological analysis was performed. Phosphorylation of tau protein at residues Ser396 and Ser404 and the expression of reelin protein were determined. Glial fibrillary acidic protein immunofluorescence staining was applied in the hippocampus regions. Our findings indicated that beta boswellic acid decreased traveled distance and escape latency in the prevention (beta boswellic acid + streptozotocin) and treatment (streptozotocin + beta boswellic acid) groups compared to control during the acquisition test. It increased “time spent” (%) in the target quadrant. Reelin level was enhanced in rats treated with beta boswellic acid. Tau hyperphosphorylation (p-tau404) and glial fibrillary acidic protein were decreased in the prevention group while the expression of reelin protein in both groups was increased. We could suggest that the anti-inflammatory property of beta boswellic acid is one of the main factors involving in the improvement of learning and memory in rats. Therefore the antineurodegenerative effect of beta boswellic acid may be due to its ability to reactivate reelin protein.
Economic viability and carbon footprint of switchgrass for cellulosic biofuels: Insights from a spatial multi‐feedstock procurement landscape analysis

We study a situation in which a multi‐feedstock cellulosic biofuel plant can procure stover from productive cropland and switchgrass from marginal land, where growing corn for stover is typically not profitable. We calibrate our model to growing conditions in a promising area of Indiana, USA. We find that cost‐minimizing biorefineries are likely to include switchgrass in the mix of feedstocks despite their high cost of production relative to corn stover. This is because the biorefinery can reduce cost by buying switchgrass grown on marginal land near the plant instead of paying to cover high transportation costs to procure stover from more distant suppliers. Moreover, the share of switchgrass will rise further if the procurement region is constrained by transaction costs or natural barriers. This is because procuring switchgrass can alleviate the cost of paying to induce land conversion to corn to procure additional stover from the intensive margin. Under the assumption that switchgrass is grown on marginal land, inclusion of switchgrass in the feedstock mix not only reduces the cost of producing biofuels but also their carbon footprint without displacing food crops. A key caveat is that high transaction costs of contracting for switchgrass and/or farmers’ reluctance to grow switchgrass on marginal land can severely undermine its inclusion in the feedstock mix. However, these forces may be countervailed by a differential subsidy for biofuels that include a higher share of switchgrass, which would be warranted because of their lower carbon footprint.
CO2 emission mitigation through fuel transition on Danish CHP and district heating plants

The study analysed how carbon dynamics were influenced by the transition from coal or natural gas to forest biomass on a number of district heat and combined heat and power plants in Denmark. For 10 plants, we calculated the cumulative net carbon emissions over time (t) from the fuel transition (CCE(t)) and carbon payback time (CPT), a measure of the time it takes for a fuel transition to biomass to reduce the amount of carbon emitted to the atmosphere relative to a continuation of using fossil fuels. Subsequently, we derived the relative cumulative net carbon emissions (RCCE(t)), as a measure of the carbon emission savings/costs induced by the fuel transition. Finally, we performed sensitivity analyses of key parameters, with special focus on emissions from indirect/market mediated effects. For fuel transitions from coal to biomass, CPT ranged from 0 to 13 years indicating that carbon emission benefits were achieved at the latest after 13 years. Relative cumulative net carbon emissions 30 years after the fuel transition (RCCE(30)) ranged from 0.29 to 0.85 corresponding to emission savings of 15–71% relative to continued use of coal. For fuel transitions from natural gas to biomass, CPT ranged from 9 to 34 years and RCCE(30) from 0.81 to 1.03. Sensitivity analyses showed that the use of truly residual biomass (harvest residues or industrial residues with no alternative use), biomass harvest from productive forests and short transport distances are instrumental in achieving a short carbon payback time and large emission savings. The quantification of indirect or market mediated GHG emissions is controversial and uncertain. We analysed additional carbon emissions related to indirect land use change (iLUC), indirect wood use change (iWUC) and indirect fuel use change (iFUC). Including iLUC added 1–4 years, iWUC added 1–3 years and iFUC added 1 year to the mean CPT.
Motif-based phosphoproteome clustering improves modeling and interpretation

Cell signaling is orchestrated in part through a network of protein kinases and phosphatases. Dysregulation of kinase signaling is widespread in diseases such as cancer and is readily targetable through inhibitors of kinase enzymatic activity. Mass spectrometry-based analysis of kinase signaling can provide a global view of kinase signaling regulation but making sense of these data is complicated by its stochastic coverage of the proteome, measurement of substrates rather than kinase signaling itself, and the scale of the data collected. Here, we implement a dual data and motif clustering strategy (DDMC) that simultaneously clusters substrate peptides into similarly regulated groups based on their variation within an experiment and their sequence profile. We show that this can help to identify putative upstream kinases and supply more robust clustering. We apply this clustering to large-scale clinical proteomic profiling of lung cancer and identify conserved proteomic signatures of tumorigenicity, genetic mutations, and tumor immune infiltration. We propose that DDMC provides a general and flexible clustering strategy for the analysis of phosphoproteomic data. One-sentence Summary DDMC is a general and flexible strategy for phosphoproteomic analysis by clustering phosphopeptides using both their phosphorylation abundance and sequence motifs.
VSTseed: periodic spaced seeds for reads with substitutions

Motivation Technical progress in computer hardware made it possible to access and process large amounts of data even on budget workstations. Therefore new or existing alignment algorithms may use large index files to increase performance. Spaced seeds with large weights reduce the number of possible locations of a read within a reference sequence. Optimal patterns for spaced seeds may guarantee to align reads even with several substitutions. Results For reads of 64–200 bp periodic spaced seeds of 32, 40, 48, 56, 64 weights are found that guarantee to locate all positions within a reference sequence for a specified number of point mutations. SIMD instructions to convert masked reads into 64, 80, 96, 112, 128-bit numbers are provided. Availability C codes to generate spaced seeds and find optimal SIMD instructions for them are freely available under MIT license at https://github.com/vtman/VSTseed
Solute carrier 5A5 regulates systemic glucose homeostasis by mediating glucose absorption in the Drosophila midgut

The small intestine is the first organ that is exposed to and absorbs dietary glucose and thus represents the first of a continuum of events that modulates normal systemic glucose homeostasis. A better understanding of the regulation of intestinal glucose transporters is therefore pertinent to our efforts in curbing metabolic disorders. However, so far, the mechanisms known to regulate SGLT1, the primary intestinal glucose transporter, are mainly elucidated from in vitro studies. The Drosophila midgut, functional equivalence of the small intestine, could serve as an efficient in vivo model system for studying intestinal glucose transporter regulation; however, no glucose transporter has yet been identified in the midgut. Here, we report that the Drosophila Solute Carrier 5A5 (dSLC5A5) is homologous to SGLT1 and is highly expressed in the midgut. The knockdown of dSLC5A5 decreases systemic and circulating sugar levels and decreases glucose uptake into the enterocytes. In contrary, the overexpression of dSLC5A5 elevates systemic and circulating sugar levels and promotes glucose uptake into the enterocytes. We show that dSLC5A5 undergoes dynamin-dependent endocytosis in the enterocyte apical membrane, and that dSLC5A5 endocytosis is essential for the glucose uptake capability of dSLC5A5. Moreover, we provide evidence supporting that intracellular lysosomal degradation of endocytosed dSLC5A5 plays a significant role in the maintenance of dSLC5A5 level in the enterocyte apical membrane. We further show that short-term exposure to glucose upregulates SLC5A5 abundance in the enterocyte apical membrane. Finally, we show that the loss or gain of dSLC5A5 ameliorates or exacerbates the high sugar diet (HSD)-mediated glucose metabolic defects. Together, our studies uncovered the first Drosophila glucose transporter in the midgut and reveal new mechanisms that regulate glucose transporters in the enterocyte apical membranes.
Frontal cortical functional connectivity is impacted by anaesthesia in macaques

A critical aspect of neuroscience is to establish whether and how brain networks evolved across primates. To date, most comparative studies have used resting-state functional Magnetic Resonance Imaging (rs-fMRI) in anaesthetized non-human primates and in awake humans. However, anaesthesia strongly affects rs-fMRI signals. The present study investigated the impact of the awareness state (anaesthesia vs. awake) within the same group of macaque monkeys on the rs-fMRI functional connectivity (FC) organization of a well characterized network in the human brain, the cingulo-frontal lateral network. Results in awake macaques revealed a similar FC pattern to that previously uncovered in the human brain. Rostral seeds in the cingulate sulcus exhibited stronger correlation strength with rostral compared to caudal lateral frontal cortical areas while caudal seeds in the cingulate sulcus displayed stronger correlation strength with caudal compared to anterior lateral frontal cortical areas. Critically, this inverse rostro-caudal functional gradient was abolished under anaesthesia. This study demonstrates that the FC pattern of cingulo-frontal cortical networks is preserved from macaque to human but some of its properties can only be observed in the awake state, warranting significant caution when comparing FC patterns across species under different states.
Most primary olfactory neurons have individually neutral effects on behavior

Animals use olfactory receptors to navigate mates, food, and danger. However, for complex olfactory systems, it is unknown what proportion of primary olfactory sensory neurons can individually drive avoidance or attraction. Similarly, the rules that govern behavioral responses to receptor combinations are unclear. We used optogenetic analysis in Drosophila to map the behavior elicited by olfactory-receptor neuron (ORN) classes: just one-fifth of ORN-types drove either avoidance or attraction. Although wind and hunger are closely linked to olfaction, neither had much effect on single-class responses. Several pooling rules have been invoked to explain how ORN types combine their behavioral influences; we activated two-way combinations and compared patterns of single- and double-ORN responses: these comparisons were inconsistent with simple pooling. We conclude that the majority of primary olfactory sensory neurons have neutral behavioral effects individually, but participate in broad, odor-elicited ensembles with potent behavioral effects arising from complex interactions.
Megakaryocyte derived immune-stimulating cells regulate host-defense immunity against bacterial pathogens

Megakaryocytes (MKs) continuously produce platelets to support hemostasis and form a niche for hematopoietic stem cell maintenance in the bone marrow. MKs are also involved in inflammation responses; however, the mechanism remains poorly understood. Here, using single-cell sequencing we identified an MK-derived immune-stimulating cell (MDIC) population exhibiting both MK-specific and immune characteristics, which highly expresses CXCR4 and immune response genes to participate in host-protective response against bacteria. MDICs interact with myeloid cells to promote their migration and stimulate the bacterial phagocytosis of macrophages and neutrophils by producing TNFα and IL-6. CXCR4high MDICs egress circulation and infiltrate into the spleen, liver, and lung upon bacterial infection. Ablation of MKs suppresses the innate immune response and T cell activation to impair the anti-bacterial effects in mice under the Listeria monocytogenes challenge. Using hematopoietic stem/progenitor cell lineage-tracing mouse line, we show that MDICs are generated from infection-induced emergency megakaryopoiesis in response to bacterial infection. Overall, we identify MDICs as an MK subpopulation, which regulates host-defense immune response against bacterial infection.
MARCO+ lymphatic endothelial cells sequester arboviruses to limit viremia and viral dissemination

While viremia in the vertebrate host is a major determinant of arboviral reservoir competency, transmission efficiency, and disease severity, immune mechanisms that control arboviral viremia are poorly defined. Here, we identify critical roles for the scavenger receptor MARCO in controlling viremia during arthritogenic alphavirus infections in mice. Following subcutaneous inoculation, alphavirus particles drain via the lymph and are rapidly captured by MARCO+ lymphatic endothelial cells (LECs) in the draining lymph node (dLN), limiting viral spread to the bloodstream. Upon reaching the bloodstream, alphavirus particles are cleared from the circulation by MARCO-expressing Kupffer cells in the liver, limiting viremia and further viral dissemination. MARCO-mediated accumulation of alphavirus particles in the dLN and liver is an important host defense mechanism as viremia and viral tissue burdens are elevated in MARCO-/- mice and disease is more severe. These findings uncover a previously unrecognized arbovirus scavenging role for LECs and improve our mechanistic understanding of viremia control during arboviral infections.
Benchmarking of deep learning algorithms for 3D instance segmentation of confocal image datasets

Segmenting three dimensional microscopy images is essential for understanding phenomena like morphogenesis, cell division, cellular growth and genetic expression patterns. Recently, deep learning (DL) pipelines have been developed which claim to provide high accuracy segmentation of cellular images and are increasingly considered as the state-of-the-art for image segmentation problems. However, it remains difficult to define their relative performances as the concurrent diversity and lack of uniform evaluation strategies makes it difficult to know how their results compare. In this paper, we first made an inventory of the available DL methods for 3 dimensional (3D) cell segmentation. We next implemented and quantitatively compared a number of representative DL pipelines, alongside a highly efficient non-DL method named MARS. The DL methods were trained on a common dataset of 3D cellular confocal microscopy images. Their segmentation accuracies were also tested in the presence of different image artifacts. A specific method for segmentation quality evaluation was adopted which isolates segmentation errors due to under/over segmentation. This is complemented with a 3D visualization strategy for interactive exploration of segmentation quality. Our analysis shows that the DL pipelines have different levels of accuracy. Two of them, which are end to end 3D and were originally designed for cell boundary detection, show high performance, and offer clear advantages in terms of adaptability to new data. Author summary In recent years a number of deep learning (DL) algorithms based on computational neural networks have been developed which claim to achieve high accuracy and automatic segmentation of 3D microscopy images. Although these algorithms have received considerable attention in the literature, it is difficult to evaluate their relative performances, while it remains unclear whether they really perform better than other, more classical segmentation methods. To clarify these issues, we performed a detailed, quantitative analysis of a number of representative DL pipelines for cell instance segmentation from 3D confocal microscopy image datasets. We developed a protocol for benchmarking the performances of such DL based segmentation pipelines using common training and test datasets, evaluation metrics and visualizations. Using this protocol, we evaluated and compared four different DL pipelines to identify their strengths and limitations. A high performance non-DL method was also included in the evaluation. We show that DL pipelines may show significant differences in their performances depending on their model architecture and pipeline components but overall show excellent adaptability to unseen data. We also show that our benchmarking protocol could be extended to a variety of segmentation pipelines and datasets.