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AbstractWidespread innovation from artificial intelligence and machine learning (AI/ML) tools presents a lucrative opportunity for the nuclear industry to improve state-of-the-art analyses (e.g. condition monitoring, remote operation, etc.) due to increased data visibility. In recent years, the risk posed by collaborative data exchange has received increased attention due, in part, to a potential adversary’s ability to reverse-engineer intercepted data using domain knowledge and AI/ML tools. While the efficacy of typical encryption has been proven during passive communication and data storage, collaborative exchange typically requires decryption for extended analyses by a third-party, which poses an intrinsic risk due to these trustworthiness concerns. The directed infusion of data (DIOD)11 A.Al Rashdan and H.Abdel-Khalik, Deceptive Infusion of Data, Non-Provisional Patent, Application No. 63/227,389, September 2022. paradigm presented in this paper discusses a novel data masking technique that relies on preserving the usable information of proprietary data while concealing its identity via reduced-order modeling. In contrast to existing state-of-the-art data masking methods, DIOD does not impose limiting assumptions, computational overheads, or induced uncertainties, thereby allowing for secure and flexible data-level security that does not alter the inferential content of the data. This paper focuses on the application of DIOD to a process-based simulation wherein a leaking reservoir with a controlled inlet pump is simulated under various experimental conditions with the goal of producing masked data that preserve the information given by anomalies. These experiments included the injection of statistically significant anomalies, subtle anomalies that occurred over an extended period, and the addition of several independent anomalous states. Each experiment showed that a classifier will identify the same anomalies whether it analyzes the original or masked data. An additional experiment also tested the case of corrupted labeling information wherein labels were arbitrarily randomized, and the loss in labeling accuracy was about the same for both datasets. Each of these experiments show that data obfuscated by DIOD may be utilized in the place of real data for a variety of condition monitoring scenarios with no loss in performance.A.Al Rashdan and H.Abdel-Khalik, Deceptive Infusion of Data, Non-Provisional Patent, Application No. 63/227,389, September 2022. [ABSTRACT FROM AUTHOR]

Enterohemorrhagic E. coli (EHEC) is considered to be the most dangerous pathotype of E. coli, as it causes severe conditions such as hemorrhagic colitis (HC) and hemolytic uremic syndrome (HUS). Antibiotic treatment of EHEC infections is generally not recommended since it may promote the production of the Shiga toxin (Stx) and lead to worsened symptoms. This study explores how exposure to the fluoroquinolone ciprofloxacin reorganizes the transcriptome and proteome of EHEC O157:H7 strain EDL933, with special emphasis on virulence-associated factors. As expected, exposure to ciprofloxacin caused an extensive upregulation of SOS-response- and Stx-phage proteins, including Stx. A range of other virulence-associated factors were also upregulated, including many genes encoded by the LEE-pathogenicity island, the enterohemolysin gene (ehxA), as well as several genes and proteins involved in LPS production. However, a large proportion of the genes and proteins (17 and 8%, respectively) whose expression was upregulated upon ciprofloxacin exposure (17 and 8%, respectively) are not functionally assigned. This indicates a knowledge gap in our understanding of mechanisms involved in EHECs response to antibiotic-induced stress. Altogether, the results contribute to better understanding of how exposure to ciprofloxacin influences the virulome of EHEC and generates a knowledge base for further studies on how EHEC responds to antibiotic-induced stress. A deeper understanding on how EHEC responds to antibiotics will facilitate development of novel and safer treatments for EHEC infections. [ABSTRACT FROM AUTHOR]

Piscine red blood cells (RBC) are nucleated and have been characterized as mediators of immune responses in addition to their role in gas exchange. Salmonid RBC are major target cells of Piscine orthoreovirus-1 (PRV-1), the etiological agent of heart and skeletal muscle inflammation (HSMI) in farmed Atlantic salmon (Salmo salar). PRV-1 replicates in RBC ex vivo, but no viral amplification has been possible in available A. salmon cell lines. To compare RBC basal transcripts and transcriptional responses to PRV-1 in the early phase of infection with non-susceptible cells, we exposed A. salmon RBC, Atlantic salmon kidney cells (ASK) and Salmon head kidney cells (SHK-1) to PRV-1 for 24 h. The RNAseq analysis of RBC supported their previous characterization as pluripotent cells, as they expressed a wide repertoire of genes encoding pattern recognition receptors (PRRs), cytokine receptors, and genes implicated in antiviral activities. The comparison of RBC to ASK and SHK-1 revealed immune cell features exclusively expressed in RBC, such as genes involved in chemotactic activity in response to inflammation. Differential expression analysis of RBC exposed to PRV-1 showed 46 significantly induced genes (≥ 2-fold upregulation) linked to the antiviral response pathway, including RNA-specific PRRs and interferon (IFN) response factors. In SHK1, PRV induced a more potent or faster antiviral response (213 genes induced). ASK cells showed a differential response pattern (12 genes induced, 18 suppressed) less characterized by the dsRNA-induced antiviral pathway. Despite these differences, the RIG-I-like receptor 3 (RLR3) in the family of cytosolic dsRNA receptors was significantly induced in all PRV-1 exposed cells. IFN regulatory factor 1 (IRF1) was significantly induced in RBC only, in contrast to IRF3/IRF7 induced in SHK-1. Differences in IRF expression and activity may potentially affect viral propagation. [ABSTRACT FROM AUTHOR]

Strømme syndrome is an ultra-rare primary ciliopathy with clinical variability. The syndrome is caused by bi-allelic variants in CENPF, a protein with key roles in both chromosomal segregation and ciliogenesis. We report three unrelated patients with Strømme syndrome and, using high-throughput sequencing approaches, we identified novel pathogenic variants in CENPF, including one structural variant, giving a genetic diagnosis to the patients. Patient 1 was a premature baby who died at 26 days with congenital malformations affecting many organs including the brain, eyes, and intestine. She was homozygous for a donor splice variant in CENPF, NM_016343.3:c.1068+1G>A, causing skipping of exon 7, resulting in a frameshift. Patient 2 was a female with intestinal atresia, microcephaly, and a Peters anomaly. She had normal developmental milestones at the age of 7 years. She is compound heterozygous for CENPF NM_016343.3:c.5920dup and c.8991del, both frameshift. Patient 3 was a male with anomalies of the brain, eye, intestine, and kidneys. He was compound heterozygous for CENPF p.(Glu298Ter), and a 5323 bp deletion covering exon 1. CENPF exon 1 is flanked by repetitive sequences that may represent a site of a recurrent structural variation, which should be a focus in patients with Strømme syndrome of unknown etiology. [ABSTRACT FROM AUTHOR]

Context: Active acromegaly is characterized by lipolysis-induced insulin resistance, which suggests adipose tissue (AT) as a primary driver of metabolic aberrations. Objective: To study the gene expression landscape in AT in patients with acromegaly before and after disease control in order to understand the changes and to identify disease-specific biomarkers. Methods: RNA sequencing was performed on paired subcutaneous adipose tissue (SAT) biopsies from six patients with acromegaly at time of diagnosis and after curative surgery. Clustering and pathway analyses were performed in order to identify disease activity-dependent genes. In a larger patient cohort (n = 23), the corresponding proteins were measured in serum by immunoassay. Correlations between growth hormone (GH), insulin-like growth factor I (IGF-I), visceral AT (VAT), SAT, total AT, and serum proteins were analyzed. Results: 743 genes were significantly differentially expressed (P-adjusted < .05) in SAT before and after disease control. The patients clustered according to disease activity. Pathways related to inflammation, cell adhesion and extracellular matrix, GH and insulin signaling, and fatty acid oxidation were differentially expressed. Serum levels of HTRA1, METRNL, S100A8/A9, and PDGFD significantly increased after disease control (P < .05). VAT correlated with HTRA1 (R = 0.73) and S100A8/A9 (R = 0.55) (P < .05 for both). Conclusion: AT in active acromegaly is associated with a gene expression profile of fibrosis and inflammation, which may corroborate the hypermetabolic state and provide a means for identifying novel biomarkers. [ABSTRACT FROM AUTHOR]

Business analytics augmented by artificial intelligence and machine learning (AI/ML) have revolutionized the role of data in the modern world. In recent years, businesses have incorporated data into their decision-making process for better prediction, risk assessment, content creation, etc. While such businesses often seek to leverage the full use of their data through third-party AI/ML services, they are often hampered by the risks of data leaks, reverse engineering, stolen technology, etc., that often have disastrous consequences for businesses and their stakeholders alike. This is especially relevant to the nuclear industry where proprietors are reluctant to share nuclear data for fear of misuse despite their willingness to integrate the additional insight provided by AI/ML applications and remain competitive. Thus, there arises a need for data masking prior to its transmission that obfuscates proprietary information while preserving the information relevant for AI/ML applications. In order to meet the needs of industrial data that are significantly different from those of data warehouses, previous work proposed an efficient time and space-scalable data masking paradigm known as the deceptive infusion of data (DIOD) methodology. The present work expands upon this work by leveraging existing reverse-engineering capabilities to facilitate the decomposition of industrial data into its proprietary and AI/ML-relevant parts, referred to as fundamental and inference metadata, respectively. Both sets of metadata are further obfuscated in accordance with the DIOD methodology to create the DIOD rendition of the industrial data, which is rendered immune to reverse engineering by discarding proprietary information and preserving only AI/ML-relevant information. Additionally, constraints of the original DIOD paper are relaxed using mutual information by configuring the methodology to the target AI/ML application to unlock the full potential of the DIOD methodology. Since the present work focuses on the nuclear industry, data from a nuclear reactor is transformed into that from a nonlinear spring-mass system with different levels of data masking as required by the generic system and the target AI/ML application. [ABSTRACT FROM AUTHOR]

The widespread digitization of critical industrial systems such as nuclear reactors has led to the development of digital twins and/or the adoption of artificial intelligence techniques for simulating baseline behavior and performing predictive maintenance. Such analytical tools, referred to as anomaly detection techniques, rely on features extracted from data that describe the underlying physical process. While these anomaly detection systems may work well with simulated data, their real-world applications are often hindered by the presence of noise. In some cases, noise may obscure subtle anomalies that may carry information about incipient stages of system faults. These subtle variations may also be the result of malicious intrusion such as so-called false data injection attack, equipment degradation causing sensor drift, or other natural disturbances in the process or the sensors. Consequently, there is a need to extract features that are robust to noise and also denoise data in a manner that aids machine-learning (ML) tools in diagnostics. In this regard, this paper presents a singular value decomposition-based statistical data-driven approach for feature extraction, denoted by randomized window decomposition, to capture the underlying physics of the system. Additionally, the features are used to denoise data to reveal subtle anomalies while also preserving relevant information for ML algorithms. The denoising algorithm is demonstrated using a RELAP5 simulation of a representative nuclear reactor with virtual noise. [ABSTRACT FROM AUTHOR]

This work addresses how analysts of a high-valued system (e.g., nuclear reactor, aircraft turbine designs) can extract findable, accessible, interoperable, and reusable scientific data for public dissemination to artificial intelligence and machine-learning (AI/ML) researchers in a manner that cannot be reverse-engineered, potentially compromising sensitive or proprietary information. State-of-the-art methods address this problem through data masking techniques, which allow access to a subset of the information while obfuscating private and potentially identifying information (e.g., personally identifying medical data). These methods are unsuitable for industrial engineering processes, where AI/ML tools need explicit access to all the data available to draw the best inference about the system to help optimize its performance and identify its vulnerabilities, etc. Our novel deceptive infusion of data paradigm provides a solution to this conundrum by developing a mathematical approach capable of concealing the identity of the system while providing full access to all the features employed by AI/ML tools to ensure their optimal performance. [ABSTRACT FROM AUTHOR]

Protective cellular immune responses have been difficult to study in fish, due to lack of basic understanding of their T cell populations, and tools to study them. Cellular immunity is thus mostly ignored in vaccination and infection studies compared to humoral responses. High throughput sequencing, as well as access to well assembled genomes, now advances studies of cellular responses. Here we have used such resources to describe organization of T cell receptor beta genes in Atlantic salmon. Salmonids experienced a unique whole genome duplication approximately 94 million years ago, which provided these species with many functional duplicate genes, where some duplicates have evolved new functions or sub-functions of the original gene copy. This is also the case for T cell receptor beta, where Atlantic salmon has retained two paralogue T cell receptor beta regions on chromosomes 01 and 09. Compared to catfish and zebrafish, the genomic organization in both regions is unique, each chromosomal region organized with dual variable- diversity- joining- constant genes in a head to head orientation. Sequence identity of the chromosomal constant sequences between TRB01 and TRB09 is suggestive of rapid diversification, with only 67 percent as opposed to the average 82-90 percent for other duplicated genes. Using virus challenged samples we find both regions expressing bona fide functional T cell receptor beta molecules. Adding the 292 variable T cell receptor alpha genes to the 100 variable TRB genes from 14 subgroups, Atlantic salmon has one of the most diverse T cell receptor alpha beta repertoire of any vertebrate studied so far. Perhaps salmonid cellular immunity is more advanced than we have imagined. [ABSTRACT FROM AUTHOR]

As industries take advantage of the widely adopted digitalization of industrial control systems, concerns are heightened about their potential vulnerabilities to adversarial attacks. False data injection attack is one of the most realistic threats because the attack could be as simple as performing a reply attack allowing attackers to circumvent conventional anomaly detection methods. This attack scenario is real for critical systems, e.g., nuclear reactors, chemical plants, etc., because physics-based simulators for a wide range of critical systems can be found in the open market providing the means to generate physics-conforming attack. The state-of-the-art monitoring techniques have proven effective in detecting sudden variations from established recurring patterns, derived by model-based or data-driven techniques, considered to represent normal behavior. This paper further develops a new method designed to detect subtle variations expected with stealthy attacks that rely on intimate knowledge of the system. The method employs physics modeling and feature engineering to design mathematical features that can detect subtle deviations from normal process variation. This work extends the method to real-time analysis and employs a new denoising filter to ensure resiliency to noise, i.e., ability to distinguish subtle variations from normal process noise. The method applicability is exemplified using a hypothesized triangle attack, recently demonstrated to be extremely effective in bypassing detection by conventional monitoring techniques, applied to a representative nuclear reactor system model using the RELAP5 computer code. [ABSTRACT FROM AUTHOR]

During the last decade, paternal effects on embryo development have been found to have greater importance than previously believed. In domestic cattle, embryo mortality is an issue of concern, causing huge economical losses for the dairy cattle industry. In attempts to reveal the paternal influence on embryo death, recent approaches have used transcriptome profiling of the embryo to find genes and pathways affected by different phenotypes in the bull. For practical and economic reasons, most such studies have used in vitro produced embryos. The aim of the present study was to investigate the differences in the global transcriptome of in vivo produced embryos, derived from sires with either high or low field fertility measured as the non-return rate (NRR) on day 56 after first AI of the inseminated cows. Superovulated heifers (n = 14) in the age span of 12–15 months were artificially inseminated with semen from either high fertility (n = 6) or low fertility (n = 6) bulls. On day seven after insemination, embryos were retrieved through uterine flushing. Embryos with first grade quality and IETS stage 5 (early blastocyst), 6 (blastocyst) or 7 (expanded blastocyst) were selected for further processing. In total, RNA extracted from 24 embryos was sequenced using Illumina sequencing, followed by differential expression analysis and gene set enrichment analysis. We found 62 genes differentially expressed between the two groups (adj. p -value<0.05), of which several genes and their linked pathways could explain the different developmental capacity. Transcripts highly expressed in the embryos from low fertility bulls were related to sterol metabolism and terpenoid backbone synthesis, while transcripts highly expressed in the high fertility embryos were linked to anti-apoptosis and the regulation of cytokine signaling. The leukocyte transendothelial migration and insulin signaling pathways were associated with enrichments in both groups. We also found some highly expressed transcripts in both groups which can be considered as new candidates in the regulation of embryo development. The present study is an important step in defining the paternal influence in embryonic development. Our results suggest that the sire's genetic contribution affects several important processes linked to pre-and peri implantation regulation in the developing embryo. [ABSTRACT FROM AUTHOR]

In the face of advanced persistent threat actors, existing information technology (IT) defenses as well as some of the more recent operational technology (OT) defenses have been shown to become increasingly vulnerable, especially for critical infrastructure systems with well-established technical know-how. For example, data deception attacks have demonstrated their ability to mislead human operators and statistical detectors alike for a wide range of systems, e.g., electric grid, chemical and nuclear plants, etc. To combat this challenge, our previous work has introduced a new modeling paradigm, called covert cognizance (C2), serving as an active OT defense that allows a critical system to build self-awareness about its past performance, with the awareness parameters covertly embedded into its own state function, precluding the need for additional courier variables. Further, the embedding process employs one-time-pad randomization to blind artificial intelligence (AI)–based learning and ensures zero impact on system state. This paper employs one of the competing AI-based learning algorithms, i.e., the long short-term memory neural network in a supervised learning setting, to validate the C2 embedding process. This is achieved by presenting the network with many labeled samples, distinguishing the original state function from the one containing the embedded self-awareness parameters. A nuclear reactor model is employed for demonstration. [ABSTRACT FROM AUTHOR]

Can predictive models develop cognizance or awareness of how they have been used? Can models detect if they are being manipulated or executed in nonauthorized manners? Can a software track information propagation through its subroutines to improve execution efficiency? Can this be achieved in a covert manner, i.e., avoiding the use of additional variables, additional lines of code, and conventional logging files, and instead rely directly on the physics being simulated to develop the required cognizance? Achieving these goals under the looming threat of insiders is considered an open challenging problem. This paper introduces a new modeling paradigm to covertly develop cognizance that is of critical value when predictive software is used in both adversarial and nonadversarial settings. Given the wide range of applications possible with this new modeling paradigm, the paper will focus on introducing the mathematical theory and limit the initial demonstration to a physics-based model of a nuclear reactor. This model describes a representative industrial control system of a nuclear reactor model containing two coupled subsystems: a heat-producing core and a steam generator. The goal is to demonstrate how each subsystem physics model can remain cognizant of the state of the subsystem. The proposed methodology will provide communication solutions for future reactor technologies to enable advanced reactor control and remote reactor operations. [ABSTRACT FROM AUTHOR]

Abstract Background Toll-like receptors (Tlrs) are major molecular pattern recognition receptors of the innate immune system. Atlantic cod (Gadus morhua) is the first vertebrate known to have lost most of the mammalian Tlr orthologues, particularly all bacterial recognising and other cell surface Tlrs. On the other hand, its genome encodes a unique repertoire of teleost-specific Tlrs. The aim of this study was to investigate if these duplicate Tlrs have been retained through adaptive evolution to compensate for the lack of other cell surface Tlrs in the cod genome. Results In this study, one tlr21, 12 tlr22 and two tlr23 genes representing the teleost-specific Tlr family have been cloned and characterised in cod. Phylogenetic analysis grouped all tlr22 genes under a single clade, indicating that the multiple cod paralogues have arisen through lineage-specific duplications. All tlrs examined were transcribed in immune-related tissues as well as in stomach, gut and gonads of adult cod and were differentially expressed during early development. These tlrs were also differentially regulated following immune challenge by immersion with Vibrio anguillarum, indicating their role in the immune response. An increase in water temperature from 4 to 12°C was associated with a 5.5-fold down-regulation of tlr22d transcript levels in spleen. Maximum likelihood analysis with different evolution models revealed that tlr22 genes are under positive selection. A total of 24 codons were found to be positively selected, of which 19 are in the ligand binding region of ectodomain. Conclusion Positive selection pressure coupled with experimental evidence of differential expression strongly support the hypothesis that teleost-specific tlr paralogues in cod are undergoing neofunctionalisation and can recognise bacterial pathogen-associated molecular patterns to compensate for the lack of other cell surface Tlrs.

Induction of cellular immune responses rely on Major histocompatibility complex (MHC) molecules presenting pathogenic peptides to T cells. Peptide processing, transport, loading and editing is a constitutive process in most cell types, but is accelerated upon infection. Recently, an unexpected complexity in the number of functional genes involved in MHC class I peptide cleavage, peptide transport, peptide loading and editing was found in teleosts, originating from the second and third whole genome duplication events. Salmonids have expanded upon this with functional duplicates also from a fourth unique salmonid whole genome duplication. However, little is known about how individual gene duplicates respond in the context of stimulation. Here we set out to investigate how interferon gamma (IFNg) regulates the transcription of immune genes in Atlantic salmon with particular focus on gene duplicates and MHC pathways. We identified a range of response patterns in Atlantic salmon gene duplicates, with upregulation of all duplicates for some genes, like interferon regulatory factor 1 (IRF1) and interferon induced protein 44-like (IFI44.L), but only induction of one or a few duplicates of other genes, such as TAPBP and ERAP2. A master regulator turned out to be the IRF1 and not the enhanceosome as seen in mammals. If IRF1 also collaborates with CIITA and possibly NLRC5 in regulating IFNg induction of MHCI and MHCII expression in Atlantic salmon, as in zebrafish, remains to be established. Altogether, our results show the importance of deciphering between gene duplicates, as they often respond very differently to stimulation and may have different biological functions. [ABSTRACT FROM AUTHOR]

High-throughput sequencing has emerged as the favoured method to study microRNA (miRNA) expression, but biases introduced during library preparation have been reported. We recently compared the performance (sensitivity, reliability, titration response and differential expression) of six commercially-available kits on synthetic miRNAs and human RNA, where library preparation was performed by the vendors. We hereby supplement this study with data from two further commonly used kits (NEBNext, NEXTflex) whose manufacturers initially declined to participate. NEXTflex demonstrated the highest sensitivity, which may reflect its use of partially-randomized adapter sequences, but overall performance was lower than the QIAseq and TailorMix kits. NEBNext showed intermediate performance. We reaffirm that biases are kit specific, complicating the comparison of miRNA datasets generated using different kits. [ABSTRACT FROM AUTHOR]

High-throughput sequencing is increasingly favoured to assay the presence and abundance of microRNAs (miRNAs) in biological samples, even from low RNA amounts, and a number of commercial vendors now offer kits that allow miRNA sequencing from sub-nanogram (ng) inputs. Although biases introduced during library preparation have been documented, the relative performance of current reagent kits has not been investigated in detail. Here, six commercial kits capable of handling <100ng total RNA input were used for library preparation, performed by kit manufactures, on synthetic miRNAs of known quantities and human total RNA samples. We compared the performance of miRNA detection sensitivity, reliability, titration response and the ability to detect differentially expressed miRNAs. In addition, we assessed the use of unique molecular identifiers (UMI) sequence tags in one kit. We observed differences in detection sensitivity and ability to identify differentially expressed miRNAs between the kits, but none were able to detect the full repertoire of synthetic miRNAs. The reliability within the replicates of all kits was good, while larger differences were observed between the kits, although none could accurately quantify the relative levels of the majority of miRNAs. UMI tags, at least within the input ranges tested, offered little advantage to improve data utility. In conclusion, biases in miRNA abundance are heavily influenced by the kit used for library preparation, suggesting that comparisons of datasets prepared by different procedures should be made with caution. This article is intended to assist researchers select the most appropriate kit for their experimental conditions. [ABSTRACT FROM AUTHOR]

Listeria monocytogenes, the causative agent of the serious food-borne disease listeriosis, can rapidly adapt to a wide-range of environmental stresses, including visible light. This study shows that exposure of the L. monocytogenes EGDe strain to low-intensity broad spectrum visible light inhibited bacterial growth and caused altered multicellular behavior during growth on semi-solid agar as compared to when the bacteria were grown in complete darkness. These light-dependent changes were observed regardless of the presence of the blue light receptor (Lmo0799) and the stressosome regulator Sigma B (SigB), which have been suggested to be important for the ability of L. monocytogenes to respond to blue light. A genome wide transcriptional analysis revealed that exposure of L. monocytogenes EGDe to broad- spectrum visible light caused altered expression of 2409 genes belonging to 18 metabolic pathways, as compared to bacteria grown in darkness. The light-dependent differentially expressed genes are involved in functions such as glycan metabolism, cell wall synthesis, chemotaxis, flagellar synthesis and resistance to oxidative stress. Exposure to light conferred reduced bacterial motility in semi-solid agar, which correlates well with the light-dependent reduction in transcript levels of flagellar and chemotaxis genes. Similar light-induced reduction in growth and motility was also observed in two different L. monocytogenes food isolates, suggesting that these responses are typical for L. monocytogenes. Together, the results show that even relatively small doses of broad-spectrum visible light causes genome-wide transcriptional changes, reduced growth and motility in L. monocytogenes. [ABSTRACT FROM AUTHOR]

This study was performed to investigate the effects of dietary inclusion of 20% rapeseed meal (RSM) as an alternative to soybean meal (SBM) in a three-month feeding experiment with growing finishing pigs. Dietary alteration affected growth performance, several carcass traits and transcriptional responses in the skeletal muscle, but did not affect measured meat quality traits. In general, pigs fed the RSM test diet exhibited reduced growth performance compared to pigs on SBM control diet. Significant transcriptional changes in the skeletal muscle of growing pigs fed RSM diet were likely the consequence of an increased amount of fiber and higher polyunsaturated fatty acids, and presence of bioactive phytochemicals, such as glucosinolates. RNAseq pipeline using Tophat2-Cuffdiff identified 57 upregulated and 63 downregulated genes in RSM compared to SBM pigs. Significantly enriched among downregulated pathways was p53–mediated signalling involved in cellular proliferation, while activation of negative growth regulators (IER5, KLF10, BTG2, KLF11, RETREG1, PRUNE2) in RSM fed pigs provided further evidence for reduced proliferation and increased cellular death, in accordance with the observed reduction in performance traits. Upregulation of well-known metabolic controllers (PDK4, UCP3, ESRRG and ESRRB), involved in energy homeostasis (glucose and lipid metabolism, and mitochondrial function), suggested less available energy and nutrients in RSM pigs. Furthermore, several genes supported more pronounced proteolysis (ABTB1, OTUD1, PADI2, SPP1) and reduced protein synthesis (THBS1, HSF4, AP1S2) in RSM muscle tissue. In parallel, higher levels of NR4A3, PDK4 and FGF21, and a drop in adropin, ELOVL6 and CIDEC/FSP27 indicated increased lipolysis and fatty acid oxidation, reflective of lower dressing percentage. Finally, pigs exposed to RSM showed greater expression level of genes responsive to oxidative stress, indicated by upregulation of GPX1, GPX2, and TXNIP. [ABSTRACT FROM AUTHOR]

Antigen presenting cells (APCs) in the thymus play an essential role in the establishment of central tolerance, i.e. the generation of a repertoire of functional and self-tolerant T cells to prevent autoimmunity. In this study, we have compared the transcriptomes of four primary APCs from human thymus (mTECs, CD19+ B cells, CD141+ and CD123+ DCs). We investigated a set of genes including the HLA genes, genes encoding transcriptional regulators and finally, tissue-enriched genes, i.e, genes with a five-fold higher expression in a particular human tissue. We show that thymic CD141+ DCs express the highest levels of all classical HLA genes and 67% (14/21) of the HLA class I and II pathway genes investigated in this study. CD141+ DCs also expressed the highest levels of the transcriptional regulator DEAF1, whereas AIRE and FEZF2 expression were mainly found in primary human mTECs. We found expression of “tissue enriched genes” from the Human Protein Atlas (HPA) in all four APC types, but the mTECs were clearly dominating in the number of uniquely expressed tissue enriched genes (20% in mTECs, 7% in CD19+ B cells, 4% in CD123+ DCs and 2% in CD141+ DCs). The tissue enriched genes also overlapped with reported human autoantigens. This is, to our knowledge, the first study that performs RNA sequencing of mTECs, CD19+ B cells, CD141+ and CD123+ DCs isolated from the same individuals and provides insight into the transcriptomes of these human thymic APCs. [ABSTRACT FROM AUTHOR]

Background: Activated T helper type 2 (Th2) cells are believed to play a pivotal role in allergic airway inflammation, but which cells attract and activate Th2 cells locally have not been fully determined. Recently, it was shown in an experimental human model of allergic rhinitis (AR) that activated monocytes rapidly accumulate in the nasal mucosa after local allergen challenge, where they promote recruitment of Th2 cells and eosinophils. Objective: To investigate whether monocytes are recruited to the lungs in paediatric asthma. Methods: Tissue samples obtained from children and adolescents with fatal asthma attack (n = 12), age‐matched non‐atopic controls (n = 9) and allergen‐challenged AR patients (n = 8) were subjected to in situ immunostaining. Results: Monocytes, identified as CD68+S100A8/A9+ cells, were significantly increased in the lower airway mucosa and in the alveoli of fatal asthma patients compared with control individuals. Interestingly, cellular aggregates containing CD68+S100A8/A9+ monocytes obstructing the lumen of bronchioles were found in asthmatics (8 out of 12) but not in controls. Analysing tissue specimens from challenged AR patients, we confirmed that co‐staining with CD68 and S100A8/A9 was a valid method to identify recently recruited monocytes. We also showed that the vast majority of accumulating monocytes both in the lungs and in the nasal mucosa expressed matrix metalloproteinase 10, suggesting that this protein may be involved in their migration within the tissue. Conclusions and clinical relevance: Monocytes accumulated in the lungs of children and adolescents with fatal asthma attack. This finding strongly suggests that monocytes are directly involved in the immunopathology of asthma and that these pro‐inflammatory cells are potential targets for therapy. [ABSTRACT FROM AUTHOR]

Objective: Reliable biomarkers associated with aggressiveness of non-functioning gonadotroph adenomas (GAs) are lacking. As the growth of tumor remnants is highly variable, molecular markers for growth potential prediction are necessary. We hypothesized that fast- and slow-growing GAs present different gene expression profiles and reliable biomarkers for tumor growth potential could be identified, focusing on the specific role of epithelial-mesenchymal transition (EMT). Design and methods: Eight GAs selected for RNA sequencing were equally divided into fast- and slow-growing group by the tumor volume doubling time (TVDT) median (27.75 months). Data were analyzed by tophat2, cufflinks and cummeRbund pipeline. 40 genes were selected for RT-qPCR validation in 20 GAs based on significance, fold-change and pathway analyses. The effect of silencing MTDH (metadherin) and EMCN (endomucin) on in vitro migration of human adenoma cells was evaluated. Results: 350 genes were significantly differentially expressed (282 genes upregulated and 68 downregulated in the fast group, P-adjusted <0.05). Among 40 selected genes, 11 showed associations with TVDT (--0.669