Protein quality control is maintained by a number of integrated cellular pathways that monitor the folding and functionality of the cellular proteome. Defects in these pathways lead to the accumulation of misfolded or faulty proteins that may become insoluble and aggregate over time. Protein aggregates significantly contribute to the development of a number of human diseases such as amyotrophic lateral sclerosis, Huntington's disease, and Alzheimer's disease. In vitro, imaging-based, cellular studies have defined key biomolecular components that recognize and clear aggregates; however, no unifying method is available to quantify cellular aggregates, limiting our ability to reproducibly and accurately quantify these structures. Here we describe an ImageJ macro called AggreCount to identify and measure protein aggregates in cells. AggreCount is designed to be intuitive, easy to use, and customizable for different types of aggregates observed in cells. Minimal experience in coding is required to utilize the script. Based on a user-defined image, AggreCount will report a number of metrics: (i) total number of cellular aggregates, (ii) percentage of cells with aggregates, (iii) aggregates per cell, (iv) area of aggregates, and (v) localization of aggregates (cytosol, perinuclear, or nuclear). A data table of aggregate information on a per cell basis, as well as a summary table, is provided for further data analysis. We demonstrate the versatility of AggreCount by analyzing a number of different cellular aggregates including aggresomes, stress granules, and inclusion bodies caused by huntingtin polyglutamine expansion.

Elisa Vidal
Dec 1, 2020; 61:1733-1746
Research Articles

Douglas A. Andres
Dec 1, 2020; 61:1537-1537
Images in Lipid Research

In SAS Retail Space Management, it should be possible to click on any location object, then Show Properties, and change the location fill color. This can be done on the gray-filled objects. However, w

Titles and footnotes do not span the entire width of the page when you use the COLUMNS= option with a value that is greater than 1 with the TAGSETS.RTF_SAMPLE tagset. When a value that is greater than 1 is specified for th

Since the publication of the Age-Related Eye Disease Study (AREDS2) in 2013, the macular pigment carotenoids lutein and zeaxanthin have become well known to both the eye care community and the public. It is a fascinating aspect of evolution that primates have repurposed photoprotective pigments and binding proteins from plants and insects to protect and enhance visual acuity. Moreover, utilization of these plant-derived nutrients has been widely embraced for preventing vision loss from age-related macular degeneration (AMD). More recently, there has been growing awareness that these nutrients can also play a role in improving visual performance in adults. On the other hand, the potential benefits of lutein and zeaxanthin supplementation at very young ages have been underappreciated. In this review, we examine the biochemical mechanisms and supportive data for lutein and zeaxanthin supplementation throughout the lifespan, with particular emphasis on prenatal supplementation. We propose that prenatal nutritional recommendations may aim at improving maternal and infant carotenoid status. Prenatal supplementation with lutein and zeaxanthin might enhance infant visual development and performance and may even prevent retinopathy of prematurity, possibilities that should be examined in future clinical studies.

Spatial changes of FAs in the retina in response to different dietary n-3 formulations have never been explored, although a diet rich in EPA and DHA is recommended to protect the retina against the effects of aging. In this study, Wistar rats were fed for 8 weeks with balanced diet including either EPA-containing phospholipids (PLs), EPA-containing TGs, DHA-containing PLs, or DHA-containing TGs. Qualitative changes in FA composition of plasma, erythrocytes, and retina were evaluated by gas chromatography-flame ionization detector. Following the different dietary intakes, changes to the quantity and spatial organization of PC and PE species in retina were determined by LC coupled to MS/MS and MALDI coupled to MS imaging. The omega-3 content in the lipids of plasma and erythrocytes suggests that PLs as well as TGs are good omega-3 carriers for retina. However, a significant increase in DHA content in retina was observed, especially molecular species as di-DHA-containing PC and PE, as well as an increase in very long chain PUFAs (more than 28 carbons) following PL-EPA and TG-DHA diets only. All supplemented diets triggered spatial organization changes of DHA in the photoreceptor layer around the optic nerve. Taken together, these findings suggest that dietary omega-3 supplementation can modify the content of FAs in the rat retina.

After ejaculation, mammalian spermatozoa must undergo a process known as capacitation in order to successfully fertilize the oocyte. Several post-translational modifications occur during capacitation, including sialylation, which despite being limited to a few proteins, seems to be essential for proper sperm-oocyte interaction. Regardless of its importance, to date, no single study has ever identified nor quantified which glycoproteins bearing terminal sialic acid (Sia) are altered during capacitation. Here we characterize sialylation during mouse sperm capacitation. Using tandem MS coupled with liquid chromatography (LC–MS/MS), we found 142 nonreductant peptides, with 9 of them showing potential modifications on their sialylated oligosaccharides during capacitation. As such, N-linked sialoglycopeptides from C4b-binding protein, endothelial lipase (EL), serine proteases 39 and 52, testis-expressed protein 101 and zonadhesin were reduced following capacitation. In contrast, mitochondrial aconitate hydratase (aconitase; ACO2), a TCA cycle enzyme, was the only protein to show an increase in Sia content during capacitation. Interestingly, although the loss of Sia within EL (N62) was accompanied by a reduction in its phospholipase A₁ activity, a decrease in the activity of ACO2 (i.e. stereospecific isomerization of citrate to isocitrate) occurred when sialylation increased (N612). The latter was confirmed by N612D recombinant protein tagged with both His and GFP. The replacement of Sia for the negatively charged Aspartic acid in the N612D mutant caused complete loss of aconitase activity compared with the WT. Computer modeling show that N612 sits atop the catalytic site of ACO2. The introduction of Sia causes a large conformational change in the alpha helix, essentially, distorting the active site, leading to complete loss of function. These findings suggest that the switch from oxidative phosphorylation, over to glycolysis that occurs during capacitation may come about through sialylation of ACO2.

Amino acid hydroxylation is a common post-translational modification, which generally regulates protein interactions or adds a functional group that can be further modified. Such hydroxylation is currently considered irreversible, necessitating the degradation and re-synthesis of the entire protein to reset the modification. Here we present evidence that the cellular machinery can reverse FIH-mediated asparagine hydroxylation on intact proteins. These data suggest that asparagine hydroxylation is a flexible and dynamic post-translational modification akin to modifications involved in regulating signaling networks, such as phosphorylation, methylation and ubiquitylation.

Despite the crucial function of the small intestine in nutrient uptake our understanding of the molecular events underlying the digestive function is still rudimentary. Recent studies demonstrated that enterocytes do not direct the entire dietary triacylglycerol toward immediate chylomicron synthesis. Especially after high-fat challenges, parts of the resynthesized triacylglycerol are packaged into cytosolic lipid droplets for transient storage in the endothelial layer of the small intestine. The reason for this temporary storage of triacylglycerol is not completely understood. To utilize lipids from cytosolic lipid droplets for chylomicron synthesis in the endoplasmic reticulum, stored triacylglycerol has to be hydrolyzed either by cytosolic lipolysis or lipophagy. Interestingly, triacylglycerol storage and chylomicron secretion rates are unevenly distributed along the small intestine, with the proximal jejunum exhibiting the highest intermittent storage capacity. We hypothesize that correlating hydrolytic enzyme activities with the reported distribution of triacylglycerol storage and chylomicron secretion in different sections of the small intestine is a promising strategy to determine key enzymes in triacylglycerol remobilization. We employed a serine hydrolase specific activity-based labeling approach in combination with quantitative proteomics to identify and rank hydrolases based on their relative activity in 11 sections of the small intestine. Moreover, we identified several clusters of enzymes showing similar activity distribution along the small intestine. Merging our activity-based results with substrate specificity and subcellular localization known from previous studies, carboxylesterase 2e and arylacetamide deacetylase emerge as promising candidates for triacylglycerol mobilization from cytosolic lipid droplets in enterocytes.

Sparkling wine is an alcoholic beverage enjoyed around the world. The sensory properties of sparkling wine depend on a complex interplay between the chemical and biochemical components in the final product. Glycoproteins have been linked to positive and negative qualities in sparkling wine, but the glycosylation profiles of sparkling wine have not been previously investigated in detail. We analysed the glyco/proteome of sparkling wines using protein- and glycopeptide-centric approaches. We developed an automated workflow that created ion libraries to analyse Sequential Window Acquisition of all THeoretical mass spectra (SWATH) Data Independent Acquisition (DIA) mass spectrometry data based on glycopeptides identified by Byonic. We applied our workflow to three pairs of experimental sparkling wines to assess the effects of aging on lees and of different yeast strains used in the Liqueur de Tirage for secondary fermentation. We found that aging a cuvée on lees for 24 months compared to 8 months led to a dramatic decrease in overall protein abundance and an enrichment in large glycans at specific sites in some proteins. Secondary fermentation of a Riesling wine with Saccharomyces cerevisiae yeast strain Siha4 produced more yeast proteins and glycoproteins than with S. cerevisiae yeast strain DV10. The abundance and glycosylation profiles of grape glycoproteins were also different between grape varieties. This work represents the first in-depth study into protein- and peptide-specific glycosylation in sparkling wines and describes a quantitative glycoproteomic SWATH/DIA workflow that is broadly applicable to other sample types.

Cells continually degrade and replace damaged proteins. However, the high energetic demand of protein turnover generates reactive oxygen species (ROS) that compromise the long-term health of the proteome. Thus, the relationship between aging, protein turnover and energetic demand remains unclear. Here, we used a proteomic approach to measure rates of protein turnover within primary fibroblasts isolated from a number of species with diverse lifespans including the longest-lived mammal, the bowhead whale. We show that organismal lifespan is negatively correlated with turnover rates of highly abundant proteins. In comparison to mice, cells from long-lived naked mole rats have slower rates of protein turnover, lower levels of ATP production and reduced ROS levels. Despite having slower rates of protein turnover, naked mole rat cells tolerate protein misfolding stress more effectively than mouse cells. We suggest that in lieu of rapid constitutive turnover, long-lived species may have evolved more energetically efficient mechanisms for selective detection and clearance of damaged proteins.

Quantification of ¹⁸F-FDG PET images is useful for accurate diagnosis and evaluation of various brain diseases, including brain tumors, epilepsy, dementia, and Parkinson disease. However, accurate quantification of ¹⁸F-FDG PET images requires matched 3-dimensional T₁ MRI scans of the same individuals to provide detailed information on brain anatomy. In this paper, we propose a transfer learning approach to adapt a pretrained deep neural network model from amyloid PET to spatially normalize ¹⁸F-FDG PET images without the need for 3-dimensional MRI. Methods: The proposed method is based on a deep learning model for automatic spatial normalization of ¹⁸F-FDG brain PET images, which was developed by fine-tuning a pretrained model for amyloid PET using only 103 ¹⁸F-FDG PET and MR images. After training, the algorithm was tested on 65 internal and 78 external test sets. All T₁ MR images with a 1-mm isotropic voxel size were processed with FreeSurfer software to provide cortical segmentation maps used to extract a ground-truth regional SUV ratio using cerebellar gray matter as a reference region. These values were compared with those from spatial normalization-based quantification methods using the proposed method and statistical parametric mapping software. Results: The proposed method showed superior spatial normalization compared with statistical parametric mapping, as evidenced by increased normalized mutual information and better size and shape matching in PET images. Quantitative evaluation revealed a consistently higher SUV ratio correlation and intraclass correlation coefficients for the proposed method across various brain regions in both internal and external datasets. The remarkably good correlation and intraclass correlation coefficient values of the proposed method for the external dataset are noteworthy, considering the dataset’s different ethnic distribution and the use of different PET scanners and image reconstruction algorithms. Conclusion: This study successfully applied transfer learning to a deep neural network for ¹⁸F-FDG PET spatial normalization, demonstrating its resource efficiency and improved performance. This highlights the efficacy of transfer learning, which requires a smaller number of datasets than does the original network training, thus increasing the potential for broader use of deep learning–based brain PET spatial normalization techniques for various clinical and research radiotracers.

More than 500,000 space heaters from GoveeLife and GoveeSmart Electric are being recalled because of safety issues, according to the U.S. Consumer Product Safety Commission.

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SAN ANTONIO, Nov. 5, 2024 — Rackspace Technology has announced the expansion of Rackspace Spot with a new geographic location and an on-demand GPU-as-a-Service powered by NVIDIA. The expansion comes […]

The post Rackspace Expands Spot Platform with On-Demand NVIDIA GPU-as-a-Service for AI Workloads appeared first on HPCwire.

U.S. Space Force has made public the prototypes of its new uniforms, which immediately drew comparisons to those worn in Star Trek and other science fiction franchises.

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TROY, Mich., Oct. 17, 2024 — Altair, a global leader in computational intelligence, is proud to announce its collaboration with Motivo, a product engineering firm for clients in the mobility, […]

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SAN ANTONIO, Nov. 1, 2024 — Rackspace Technology, a leading hybrid, multicloud, and AI technology services company, announced that it has signed a Strategic Collaboration Agreement (SCA) with Amazon Web […]

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SpaceX has reportedly struck a deal with LG Energy Solution Ltd. to supply cylindrical lithium-ion batteries for Elon Musk's Starship rocket, expected to launch early next year, according to industry sources.

TROY, Mich., Nov. 12, 2024 — Altair, a global leader in computational intelligence, has entered into collaboration agreement with the European Space Agency (ESA) through the ESA Partnership Initiative for […]

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SpaceX launched 23 Starlink satellites from Cape Canaveral Space Force Center on Wednesday to match its own record of launches in one year.

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The three NASA astronauts that were part of the SpaceX Crew-8 aboard Crew Dragon Endeavour will speak publicly today for the first time since their mission returned to earth late last month.

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Roger Dooley's Brainfluence has been translated into eleven languages, but the new Spanish reading is the first audio audio translation.

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Neural decoding is a tool for understanding how activities from a population of neurons inside the brain relate to the outside world and for engineering applications such as brain–machine interfaces. However, neural decoding studies mainly focused on different decoding algorithms rather than different neuron types which could use different coding strategies. In this study, we used two-photon calcium imaging to assess three auditory spatial decoders (space map, opponent channel, and population pattern) in excitatory and inhibitory neurons in the dorsal inferior colliculus of male and female mice. Our findings revealed a clustering of excitatory neurons that prefer similar interaural level difference (ILD), the primary spatial cues in mice, while inhibitory neurons showed random local ILD organization. We found that inhibitory neurons displayed lower decoding variability under the opponent channel decoder, while excitatory neurons achieved higher decoding accuracy under the space map and population pattern decoders. Further analysis revealed that the inhibitory neurons’ preference for ILD off the midline and the excitatory neurons’ heterogeneous ILD tuning account for their decoding differences. Additionally, we discovered a sharper ILD tuning in the inhibitory neurons. Our computational model, linking this to increased presynaptic inhibitory inputs, was corroborated using monaural and binaural stimuli. Overall, this study provides experimental and computational insight into how excitatory and inhibitory neurons uniquely contribute to the coding of sound locations.

It is well established that holding information in working memory (WM) elicits sustained stimulus-specific patterns of neural activity. Nevertheless, here we provide evidence for a distinct class of neural activity that tracks the number of individuated items in working memory, independent of the type of visual features stored. We present two EEG studies of young adults of both sexes that provide robust evidence for a signal tracking the number of individuated representations in working memory, regardless of the specific feature values stored. In Study 1, subjects maintained either colors or orientations across separate blocks in a single session. We found near-perfect generalization of the load signal between these two conditions, despite being able to simultaneously decode which feature had been voluntarily stored. In Study 2, participants attended to two features with very distinct cortical representations: color and motion coherence. We again found evidence for a neural load signal that robustly generalized across these distinct visual features, even though cortically disparate regions process color and motion coherence. Moreover, representational similarity analysis provided converging evidence for a content-independent load signal, while simultaneously showing that unique variance in EEG activity tracked the specific features that were stored. We posit that this load signal reflects a content-independent "pointer" operation that binds objects to the current context while parallel but distinct neural signals represent the features that are stored for each item in memory.

Words offer a unique opportunity to separate the processing mechanisms of object subcomponents from those of the whole object, because the phonological or semantic information provided by the word subcomponents (i.e., sublexical information) can conflict with that provided by the whole word (i.e., lexical information). Previous studies have revealed some of the specific brain regions and temporal information involved in sublexical information processing. However, a comprehensive spatiotemporal neural network for sublexical processing remains to be fully elucidated due to the low temporal or spatial resolutions of previous neuroimaging studies. In this study, we recorded stereoelectroencephalography signals with high spatial and temporal resolutions from a large sample of 39 epilepsy patients (both sexes) during a Chinese character oral reading task. We explored the activated brain regions and their connectivity related to three sublexical effects: phonological regularity (whether the whole character's pronunciation aligns with its phonetic radical), phonological consistency (whether characters with the same phonetic radical share the same pronunciation), and semantic transparency (whether the whole character's meaning aligns with its semantic radical). The results revealed that sublexical effects existed in the inferior frontal gyrus, precentral and postcentral gyri, temporal lobe, and middle occipital gyrus. Additionally, connectivity from the middle occipital gyrus to the postcentral gyrus and from postcentral gyrus to the fusiform gyrus was associated with the sublexical effects. These findings provide valuable insights into the spatiotemporal dynamics of sublexical processing and object recognition in the brain.

Systemic study of pathogenic pathways and interrelationships underlying genes associated with Alzheimer's disease (AD) facilitates the identification of new targets for effective treatments. Recently available large-scale multiomics datasets provide opportunities to use computational approaches for such studies. Here, we devised a novel disease gene identification (digID) computational framework that consists of a semi-supervised deep learning classifier to predict AD-associated genes and a protein–protein interaction (PPI) network-based analysis to prioritize the importance of these predicted genes in AD. digID predicted 1,529 AD-associated genes and revealed potentially new AD molecular mechanisms and therapeutic targets including GNAI1 and GNB1, two G-protein subunits that regulate cell signaling, and KNG1, an upstream modulator of CDC42 small G-protein signaling and mediator of inflammation and candidate coregulator of amyloid precursor protein (APP). Analysis of mRNA expression validated their dysregulation in AD brains but further revealed the significant spatial patterns in different brain regions as well as among different subregions of the frontal cortex and hippocampi. Super-resolution STochastic Optical Reconstruction Microscopy (STORM) further demonstrated their subcellular colocalization and molecular interactions with APP in a transgenic mouse model of both sexes with AD-like mutations. These studies support the predictions made by digID while highlighting the importance of concurrent biological validation of computationally identified gene clusters as potential new AD therapeutic targets.