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PURPOSE/OBJECTIVE(S) Long-term side effects of radiation therapy (RT) include fibrosis, poor wound healing and hormonal dysfunction. These may potentially deleteriously affect obstetric outcomes amongst female cancer survivors, but there is minimal data. We hypothesized that previous RT treatment would be associated with increased maternal and fetal complications. MATERIALS/METHODS We utilized the Nationwide Inpatient Sample (NIS) Healthcare Cost and Utilization Project, containing discharge data from 1,050 hospitals in 44 states, a 20% stratified sample of hospitals in the US. Inclusion criteria were women with a previously specified cancer diagnosis, now hospitalized for a birth between 2015 and 2017; there were no exclusion criteria. The incidence of maternal (i.e., organ failure, infections, transfusions) and obstetric (including eclampsia, abruption, fetal distress) complications was compared between those who had / had not previously received RT. Categorical variables were compared using chi-square test. In addition, composite endpoints of 'any maternal complication' and 'any fetal complication' were analyzed, with predictors assessed using logistic regression. RESULTS A total of 3215 patient hospitalizations were included in the study, of whom in 135 the mother had previous received RT. Median age - 31 years, 69% white, no sig. difference between those who did / did not receive RT. Cancer type was unevenly distributed between the two groups - RT patients had mostly lymphoma (36%), thyroid (25%) and breast (23%) cancer, whereas non-RT patients had thyroid (26%), melanoma (19%), breast (11%) and cervix (10%). Background maternal medical conditions: heart disease (OR 23.1, P < 0.001) and thyroid disease (OR 1.6, P < 0.04) were more common amongst those who had received RT. Regarding maternal medical complications, respiratory failure (OR 6.6, P < 0.01), and mechanical ventilation (OR 11.5, P = 0.01) were all more common in the 'received-RT' group. Regarding obstetric complication, none were associated with previous RT (of note, there were fewer cesarean sections in the previous RT group). On multivariate analysis for the composite endpoint 'obstetric complications' age (HR 1.02, P < 0.001), exposure to chemotherapy (HR 1.47, P = 0.01) and diabetes mellitus (HR 1.99, P = 0.06, borderline) were associated with poorer outcomes; there was no association with previous RT. On multivariate analysis for composite endpoint 'maternal complications', no single covariate was associated with a worse outcome. CONCLUSION Previously RT was associated with an increased risk of maternal respiratory medical complications at time of delivery. Conversely and reassuringly, previous RT was not associated with increased fetal complications at delivery. Out data legitimize current trends to minimize cardiac radiation exposure in young women, and provide guidance for the optimal medical care of cancer survivors at time of delivery.

Lung cancer is the most common cancer worldwide and the leading cause of cancer-related deaths in both men and women. Despite the development of novel therapeutic interventions, the 5-year survival rate for non-small cell lung cancer (NSCLC) patients remains low, demonstrating the necessity for novel treatments. One strategy to improve translational research is the development of surrogate models reflecting somatic mutations identified in lung cancer patients as these impact treatment responses. With the advent of CRISPR-mediated genome editing, gene deletion as well as site-directed integration of point mutations enabled us to model human malignancies in more detail than ever before. Here, we report that by using CRISPR/Cas9-mediated targeting of Trp53 and KRas, we recapitulated the classic murine NSCLC model Trp53fl/fl:lsl-KRasG12D/wt. Developing tumors were indistinguishable from Trp53fl/fl:lsl-KRasG12D/wt-derived tumors with regard to morphology, marker expression, and transcriptional profiles. We demonstrate the applicability of CRISPR for tumor modeling in vivo and ameliorating the need to use conventional genetically engineered mouse models. Furthermore, tumor onset was not only achieved in constitutive Cas9 expression but also in wild-type animals via infection of lung epithelial cells with two discrete AAVs encoding different parts of the CRISPR machinery. While conventional mouse models require extensive husbandry to integrate new genetic features allowing for gene targeting, basic molecular methods suffice to inflict the desired genetic alterations in vivo. Utilizing the CRISPR toolbox, in vivo cancer research and modeling is rapidly evolving and enables researchers to swiftly develop new, clinically relevant surrogate models for translational research.

A hallmark of aging is loss of differentiated cell identity. AgedDrosophilamidgut differentiated enterocytes (ECs) lose their identity, impairing tissue homeostasis. To discover identity regulators, we performed an RNAi screen targeting ubiquitin-related genes in ECs. Seventeen genes were identified, including the deubiquitinase Non-stop (CG4166). Lineage tracing established that acute loss of Non-stop in young ECs phenocopies aged ECs at cellular and tissue levels. Proteomic analysis unveiled that Non-stop maintains identity as part of a Non-stop identity complex (NIC) containing E(y)2, Sgf11, Cp190, (Mod) mdg4, and Nup98. Non-stop ensured chromatin accessibility, maintaining the EC-gene signature, and protected NIC subunit stability. Upon aging, the levels of Non-stop and NIC subunits declined, distorting the unique organization of the EC nucleus. Maintaining youthful levels of Non-stop in wildtype aged ECs safeguards NIC subunits, nuclear organization, and suppressed aging phenotypes. Thus, Non-stop and NIC, supervise EC identity and protects from premature aging.

Platelets are clearly central to thrombosis and hemostasis. In addition, more recently, evidence has emerged for non-hemostatic roles of platelets including inflammatory and immune reactions/responses. Platelets express immunologically relevant ligands and receptors, demonstrate adhesive interactions with endothelial cells, monocytes and neutrophils, and toll-like receptor (TLR) mediated responses. These properties make platelets central to innate and adaptive immunity and potential candidate key mediators of autoimmune disorders. Multiple sclerosis (MS) is the most common chronic autoimmune central nervous system (CNS) disease. An association between platelets and MS was first indicated by the increased adhesion of platelets to endothelial cells. This was followed by reports identifying structural and functional changes of platelets, their chronic activation in the peripheral blood of MS patients, platelet presence in MS lesions and the more recent revelation that these structural and functional abnormalities are associated with all MS forms and stages. Investigations based on the murine experimental autoimmune encephalomyelitis (EAE) MS model first revealed a contribution to EAE pathogenesis by exacerbation of CNS inflammation and an early role for platelets in EAE development via platelet-neuron and platelet-astrocyte associations, through sialated gangliosides in lipid rafts. Our own studies refined and extended these findings by identifying the critical timing of platelet accumulation in pre-clinical EAE and establishing an initiating and central rather than merely exacerbating role for platelets in disease development. Furthermore, we demonstrated platelet-neuron associations in EAE, coincident with behavioral changes, but preceding the earliest detectable autoreactive T cell accumulation. In combination, these findings establish a new paradigm by asserting that platelets play a neurodegenerative as well as a neuroinflammatory role in MS and therefore, that these two pathological processes are causally linked. This review will discuss the implications of these findings for our understanding of MS, for future applications for imaging toward early detection of MS, and for novel strategies for platelet-targeted treatment of MS.

Summary Mitochondria play a central role in lipid metabolism and can bind to lipid droplets. However, the role and functional specialization of the population of peridroplet mitochondria (PDMs) remain unclear, as methods to isolate functional PDMs were not developed until recently. Here, we describe an approach to isolate intact PDMs from murine brown adipose tissue based on their adherence to lipid droplets. PDMs isolated using our approach can be used to study their specialized function by respirometry. For complete information on the use and execution of this protocol, please refer to Benador et al. (2018)., Graphical abstract, Highlights • Isolation of peridroplet mitochondria (PDMs) from brown adipose tissue is described • The function of murine PDMs is analyzed using 96-well format respirometry • QC steps of PDM isolation by imaging and protein biochemistry are defined, Mitochondria play a central role in lipid metabolism and can bind to lipid droplets. However, the role and functional specialization of the population of peridroplet mitochondria (PDMs) remain unclear, as methods to isolate functional PDMs were not developed until recently. Here, we describe an approach to isolate intact PDMs from murine brown adipose tissue based on their adherence to lipid droplets. PDMs isolated using our approach can be used to study their specialized function by respirometry.

Lysosomes, membrane-bound organelles, play important roles in cellular processes including endocytosis, phagocytosis, and autophagy. Lysosomes maintain cellular homeostasis by generating a highly acidic environment of pH 4.5 - 5.0 and by housing hydrolytic enzymes that degrade engulfed biomolecules. Impairment of lysosomal function, especially in its acidification, is a driving force in the pathogenesis of diseases including neurodegeneration, cancer, metabolic disorders, and infectious diseases. Therefore, lysosomal pH is an attractive and targetable site for therapeutic intervention. Currently, there is a dearth of strategies or materials available to specifically modulate lysosomal acidification. This review focuses on the key aspects of how lysosomal pH is implicated in various diseases and discusses design strategies and molecular or nanoscale agents for lysosomal pH modulation, with the ultimate goal of developing novel therapeutic solutions.

Changes to mitochondrial architecture are associated with various adaptive and pathogenic processes. However, quantification of changes to mitochondrial structures is limited by the yet unmet challenge of defining the borders of each individual mitochondrion within an image. Here, we describe a novel method for segmenting primary brown adipocyte (BA) mitochondria images. We describe a granular approach to quantifying subcellular structures, particularly mitochondria in close proximity to lipid droplets: peridroplet mitochondria. In addition, we lay out a novel machine-learning-based mitochondrial segmentation method that eliminates the bias of manual mitochondrial segmentation and improves object recognition compared to conventional thresholding analyses. By applying these methods, we discovered a significant difference between cytosolic and peridroplet BA mitochondrial H2O2 production and validated the machine-learning algorithm in BA via norepinephrine-induced mitochondrial fragmentation and comparing manual analyses to the automated analysis. This approach provides a high-throughput analysis protocol to quantify ratiometric probes in subpopulations of mitochondria in adipocytes.

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Inefficient data transfer between computation and memory inspired emerging processing-in-memory (PIM) technologies. Many PIM solutions enable storage and processing using memristors in a crossbar-array structure, with techniques such as memristor-aided logic (MAGIC) used for computation. This approach provides highly-paralleled logic computation with minimal data movement. However, memristors are vulnerable to soft errors and standard error-correcting-code (ECC) techniques are difficult to implement without moving data outside the memory. We propose a novel technique for efficient ECC implementation along diagonals to support reliable computation inside the memory without explicitly reading the data. Our evaluation demonstrates an improvement of over eight orders of magnitude in reliability (mean time to failure) for an increase of about 26% in computation latency., Comment: Accepted to 58th Design Automation Conference (DAC) 2021

ispartof: AIR & SPACE LAW vol:46 issue:1 pages:1-27 status: published

The concept that extracellular vesicles (EVs) from the diet can be absorbed by the intestinal tract of the consuming organism, be bioavailable in various organs, and in-turn exert phenotypic changes is highly debatable. Here, we isolate EVs from both raw and commercial bovine milk and characterize them by electron microscopy, nanoparticle tracking analysis, western blotting, quantitative proteomics and small RNA sequencing analysis. Orally administered bovine milk-derived EVs survive the harsh degrading conditions of the gut, in mice, and is subsequently detected in multiple organs. Milk-derived EVs orally administered to mice implanted with colorectal and breast cancer cells reduce the primary tumor burden. Intriguingly, despite the reduction in primary tumor growth, milk-derived EVs accelerate metastasis in breast and pancreatic cancer mouse models. Proteomic and biochemical analysis reveal the induction of senescence and epithelial-to-mesenchymal transition in cancer cells upon treatment with milk-derived EVs. Timing of EV administration is critical as oral administration after resection of the primary tumor reverses the pro-metastatic effects of milk-derived EVs in breast cancer models. Taken together, our study provides context-based and opposing roles of milk-derived EVs as metastasis inducers and suppressors., Dietary extracellular vesicles (EVs) could potentially be absorbed by the intestinal tract of the host and exert multiple phenotypic changes. Here, the authors isolate and characterize EVs from raw and commercial bovine milk and show orally administered EVs to have a context specific role in promoting or suppressing primary tumor growth and metastasis in multiple mouse tumor models.

Methylmercury (CH3Hg+) binding to catalytically fundamental cysteine and selenocysteine of peroxide-reducing enzymes has long been postulated as the origin of its toxicological activity. Only very recently, CH3Hg+ binding to the selenocysteine of thioredoxin reductase has been directly observed [PickeringI. J.Inorg. Chem., 2020, 59, 2711−271832049511], but the precise influence of the toxicant on the peroxide-reducing potential of such a residue has never been investigated. In this work, we employ state-of-the-art density functional theory calculations to study the reactivity of molecular models of the free and toxified enzymes. Trends in activation energies are discussed with attention to the biological consequences and are rationalized within the chemically intuitive framework provided by the activation strain model. With respect to the free, protonated amino acids, CH3Hg+ binding promotes oxidation of the S or Se nucleus, suggesting that chalcogenoxide formation might occur in the toxified enzyme, even if the actual rate of peroxide reduction is almost certainly lowered as suggested by comparison with fully deprotonated amino acids models., The TOC shows a close-up on the catalytic pocket of a healthy (left) and sick (right) glutathione peroxidase. On the left, a selenocysteine can be seen interacting with hydrogen peroxide, while on the right, the relative methylmercury complex alters the peroxide-reducing potential of the chalcogen nucleus. These two situations have been investigated in this work.

Nowadays, data-intensive applications are gaining popularity and, together with this trend, processing-in-memory (PIM)-based systems are being given more attention and have become more relevant. This paper describes an analytical modeling tool called Bitlet that can be used, in a parameterized fashion, to estimate the performance and the power/energy of a PIM-based system and thereby assess the affinity of workloads for PIM as opposed to traditional computing. The tool uncovers interesting tradeoffs between, mainly, the PIM computation complexity (cycles required to perform a computation through PIM), the amount of memory used for PIM, the system memory bandwidth, and the data transfer size. Despite its simplicity, the model reveals new insights when applied to real-life examples. The model is demonstrated for several synthetic examples and then applied to explore the influence of different parameters on two systems - IMAGING and FloatPIM. Based on the demonstrations, insights about PIM and its combination with CPU are concluded., Comment: Accepted to ACM JETC

The so-called peroxidatic cysteines and selenocysteines in proteins reduce hydroperoxides through a dual attack to the peroxide bond in a two-step mechanism. First, a proton dislocation from the thiol/selenol to a close residue of the enzymatic pocket occurs. Then, a nucleophilic attack of the anionic cysteine/selenocysteine to one O atom takes place, while the proton is shuttled back to the second O atom, promoting the formation of a water molecule. In this computational study, we use a molecular model of GPx to demonstrate that the enzymatic environment significantly lowers the barrier of the latter SN2 step. Particularly, in our Se-based model the energy barriers for the two steps are 29.82 and 2.83 kcal mol−1, both higher than the corresponding barriers computed in the enzymatic cluster, i. e., 21.60 and null, respectively. Our results, obtained at SMD-B3LYP-D3(BJ)/6-311+G(d,p), cc-pVTZ//B3LYP-D3(BJ)/6-311G(d,p), cc-pVTZ level of theory, show that the mechanistic details can be well reproduced using an oversimplified model, but the energetics is definitively more favorable in the GPx active site. In addition, we pinpoint the role of the chalcogen in the peroxide reduction process, rooting the advantages of the presence of selenium in its acidic and nucleophilic properties.

Among the chalcogens, selenium is the key element for catalyzed H2O2 reduction. In organic synthesis, catalytic amounts of organo mono- and di-selenides are largely used in different classes of oxidations, in which H2O2 alone is poorly efficient. Biological hydroperoxide metabolism is dominated by peroxidases and thioredoxin reductases, which balance hydroperoxide challenge and contribute to redox regulation. When their selenocysteine is replaced by cysteine, the cellular antioxidant defense system is impaired. Finally, classes of organoselenides have been synthesized with the aim of mimicking the biological strategy of glutathione peroxidases, but their therapeutic application has so far been limited. Moreover, their therapeutic use may be doubted, because H2O2 is not only toxic but also serves as an important messenger. Therefore, over-optimization of H2O2 reduction may lead to unexpected disturbances of metabolic regulation. Common to all these systems is the nucleophilic attack of selenium to one oxygen of the peroxide bond promoting its disruption. In this contribution, we revisit selected examples from chemistry and biology, and, by using results from accurate quantum mechanical modelling, we provide an accurate unified picture of selenium’s capacity of reducing hydroperoxides. There is clear evidence that the selenoenzymes remain superior in terms of catalytic efficiency.

The word catalyst comes from the Greek κατα’λυσις, which means dissolution and was introduced in 1836 by the Swedish Berzelius [...]