An Implementation of Trust Chain Framework with Hierarchical Content Identifier Mechanism by Using Blockchain Technology.

Advances in information technology (IT) and operation technology (OT) accelerate the development of manufacturing systems (MS) consisting of integrated circuits (ICs), modules, and systems, toward Industry 4.0. However, the existing MS does not support comprehensive identity forensics for the whole system, limiting its ability to adapt to equipment authentication difficulties. Furthermore, the development of trust imposed during their crosswise collaborations with suppliers and other manufacturers in the supply chain is poorly maintained. In this paper, a trust chain framework with a comprehensive identification mechanism is implemented for the designed MS system, which is based and created on the private blockchain in conjunction with decentralized database systems to boost the flexibility, traceability, and identification of the IC-module-system. Practical implementations are developed using a functional prototype. First, the decentralized application (DApp) and the smart contracts are proposed for constructing the new trust chain under the proposed comprehensive identification mechanism by using blockchain technology. In addition, the blockchain addresses of IC, module, and system are automatically registered to InterPlanetary File System (IPFS), individually. In addition, their corresponding hierarchical CID (content identifier) values are organized by using Merkle DAG (Directed Acyclic Graph), which is employed via the hierarchical content identifier mechanism (HCIDM) proposed in this paper. Based on insights obtained from this analysis, the trust chain based on HCIDM can be applied to any MS system, for example, this trust chain could be used to prevent the counterfeit modules and ICs employed in the monitoring system of a semiconductor factory environment. The evaluation results show that the proposed scheme could work in practice under the much lower costs, compared to the public blockchain, with a total cost of 0.002094 Ether. Finally, this research is developed an innovation trust chain mechanism that could be provided the system-level security for any MS toward Industrial 4.0 in order to meet the requirements of both manufacturing innovation and product innovation in Sustainable Development Goals (SDGs).

Automated Detection of Celiac Disease on Duodenal Biopsy Slides: A Deep Learning Approach.

CONTEXT: Celiac disease (CD) prevalence and diagnosis have increased substantially in recent years. The current gold standard for CD confirmation is visual examination of duodenal mucosal biopsies. An accurate computer-aided biopsy analysis system using deep learning can help pathologists diagnose CD more efficiently. SUBJECTS AND METHODS: In this study, we trained a deep learning model to detect CD on duodenal biopsy images. Our model uses a state-of-the-art residual convolutional neural network to evaluate patches of duodenal tissue and then aggregates those predictions for whole-slide classification. We tested the model on an independent set of 212 images and evaluated its classification results against reference standards established by pathologists. RESULTS: Our model identified CD, normal tissue, and nonspecific duodenitis with accuracies of 95.3%, 91.0%, and 89.2%, respectively. The area under the receiver operating characteristic curve was >0.95 for all classes. CONCLUSIONS: We have developed an automated biopsy analysis system that achieves high performance in detecting CD on biopsy slides. Our system can highlight areas of interest and provide preliminary classification of duodenal biopsies before review by pathologists. This technology has great potential for improving the accuracy and efficiency of CD diagnosis.

Generative Image Translation for Data Augmentation in Colorectal Histopathology Images.

We present an image translation approach to generate augmented data for mitigating data imbalances in a dataset of histopathology images of colorectal polyps, adenomatous tumors that can lead to colorectal cancer if left untreated. By applying cycle-consistent generative adversarial networks (CycleGANs) to a source domain of normal colonic mucosa images, we generate synthetic colorectal polyp images that belong to diagnostically less common polyp classes. Generated images maintain the general structure of their source image but exhibit adenomatous features that can be enhanced with our proposed filtration module, called Path-Rank-Filter. We evaluate the quality of generated images through Turing tests with four gastrointestinal pathologists, finding that at least two of the four pathologists could not identify generated images at a statistically significant level. Finally, we demonstrate that using CycleGAN-generated images to augment training data improves the AUC of a convolutional neural network for detecting sessile serrated adenomas by over 10%, suggesting that our approach might warrant further research for other histopathology image classification tasks.

In silico mapping of quantitative trait loci (QTL) regulating the milk ionome in mice identifies a milk iron locus on chromosome 1.

The breast-feeding neonate depends on mother's milk for both macronutrients and micronutrients including minerals. The goals of the present study were to document the effects of genetic background in mice on milk concentrations of select minerals and to use genome-wide association study (GWAS) to identify quantitative trait loci (QTL) regulating milk mineral concentrations. Milk samples from lactating mice in each of 31 different inbred strains of the mouse diversity panel (MDP) were analyzed by inductively coupled plasma-optical emission spectroscopy to determine the concentrations of calcium (Ca), copper (Cu), iron (Fe), potassium (K), magnesium (Mg), sodium (Na), phosphorus (P), sulfur (S), and zinc (Zn). GWAS identified a single pleiotropic milk mineral concentration QTL (Mmcq) on chromosome 3 for Ca, Mg, and P. For the remaining minerals, six QTL were detected for Fe, four for K, three for Zn, and one for S. Intersecting the Mmcq with published chromatin immunoprecipitation sequence data identified 15 out of 4633 high-linkage disequilibrium single-nucleotide polymorphisms that resided in signal transducer and activation of transcription 5 (STAT5) binding regions. A milk Fe-associated locus (Mmcq9) on chromosome 1 contained an SNP that localized to a STAT5 binding region and intersected with a HOMER motif predicted to bind the transcriptional regulator E74-Like ETS transcription factor 5. This locus also contained the genes for solute carrier family (Slc) members Slc9a2, Slc9a4, Slc39a10, and Slc40a1. Expression analysis of these transporters supports the conclusion that Slc9a2 and Slc40a1 within the mammary gland could mediate the effect of Mmcq9 on milk Fe concentration.

Greater Occipital Nerve Injection versus Oral Steroids for Short Term Prophylaxis of Cluster Headache: A Retrospective Comparative Study.

OBJECTIVE: To investigate our experience with oral steroid and greater occipital nerve (GON) injection with steroid as transitional treatments for cluster headache. BACKGROUND: Cluster headache is a primary headache disorder characterized by multiple episodes of intense unilateral pain with autonomic features. During cluster headache attacks, transitional therapies are useful while prophylactic dosages are initiated or increased. There are limited data comparing the efficacy of oral versus injected transitional treatments. METHODS: We retrospectively reviewed charts for patients evaluated with cluster headache at our center and captured episodes of transitional therapy utilized from 1995 to 2014. Treatment benefit was categorized into complete, partial, or no response. RESULTS: Forty-three patients received transitional therapy over a total of 151 encounters, of which 140 were available for analysis. Encounters featured oral steroids (81, 57.9%) and GON injection (59, 42.1%). Of the 40 patients with treatment response data available, 24 patients received only one type of transitional therapy and 16 patients received both therapies. More encounters featuring oral steroids versus GON injections led to at least a partial response (82.7% vs 64.4%) and to a lesser extent a complete response (50.6% vs 35.6%). Among 16 patients treated with both therapies, 8 (50%) responded to both and 6 (37.5%) responded only to oral steroids. CONCLUSIONS: Our single-center, retrospective data suggest the majority of patients with cluster headache responded to both prednisone and GON injections for transitional treatment, with a higher response to oral steroids. Our results may inform study design for a randomized trial, which is warranted.

The major pathway by which polymeric formula reduces inflammation in intestinal epithelial cells: a microarray-based analysis.

Nutritional therapy is well established as a means to induce remission in active Crohn's disease (CD). Evidence indicates that exclusive enteral nutrition (EEN) therapy for CD both alters the intestinal microbiota and directly suppresses the inflammatory response in the intestinal mucosa. However, the pathway(s) through which EEN suppresses inflammation is still unknown. Therefore, the aim of the current study was to use microarray technology to investigate the major pathway by which polymeric formula (PF) alters inflammatory processes in epithelial cells in vitro. HT-29 cells were grown to confluence and then co-cultured with tumour necrosis factor (TNF)-α (100 ng/ml) for 5 h in the presence or absence of PF, as used for EEN. Following incubation, RNA was extracted and subjected to polymerase chain reaction (PCR) and microarray analysis. Enzyme-linked immunosorbent assays were employed to evaluate cytokine protein levels. Neither TNF-α nor PF had a toxic effect on cells over the experimental period. Microarray analysis showed that PF modulated the expression of genes specifically linked to nuclear factor (NF)-κB, resulting in downregulation of a number of genes in this pathway. These findings were further confirmed by real-time PCR of selected dysregulated genes as well as reduced expression of IL-6 and IL-8 proteins following PF treatment. The results arising from this study provide evidence that PF alters the inflammatory responses in intestinal epithelial cells through modulation of the NF-κB pathway.

T-cell activation and early gene response in dogs.

T-cells play a crucial role in canine immunoregulation and defence against invading pathogens. Proliferation is fundamental to T-cell differentiation, homeostasis and immune response. Initiation of proliferation following receptor mediated stimuli requires a temporally programmed gene response that can be identified as immediate-early, mid- and late phases. The immediate-early response genes in T-cell activation engage the cell cycle machinery and promote subsequent gene activation events. Genes involved in this immediate-early response in dogs are yet to be identified. The present study was undertaken to characterise the early T-cell gene response in dogs to improve understanding of the genetic mechanisms regulating immune function. Gene expression profiles were characterised using canine gene expression microarrays and quantitative reverse transcription PCR (qRT-PCR), and paired samples from eleven dogs. Significant functional annotation clusters were identified following stimulation with phytohemagluttinin (PHA) (5µg/ml), including the Toll-like receptor signaling pathway and phosphorylation pathways. Using strict statistical criteria, 13 individual genes were found to be differentially expressed, nine of which have ontologies that relate to proliferation and cell cycle control. These included, prostaglandin-endoperoxide synthase 2 (PTGS2/COX2), early growth response 1 (EGR1), growth arrest and DNA damage-inducible gene (GADD45B), phorbol-12-myristate-13-acetate-induced protein 1 (PMAIP1), V-FOS FBJ murine osteosarcoma viral oncogene homolog (FOS), early growth response 2 (EGR2), hemogen (HEMGN), polo-like kinase 2 (PLK2) and polo-like kinase 3 (PLK3). Differential gene expression was re-examined using qRT-PCR, which confirmed that EGR1, EGR2, PMAIP1, PTGS2, FOS and GADD45B were significantly upregulated in stimulated cells and ALAS2 downregulated. PTGS2 and EGR1 showed the highest levels of response in these dogs. Both of these genes are involved in cell cycle regulation. This study provides a comprehensive analysis of the early T-cell gene response to activation in dogs.

Photodamage: all signs lead to actinic keratosis and early squamous cell carcinoma.

Ultraviolet (UV) radiation is likely to drive the initiation and progression of skin cancer from actinic keratosis to squamous cell carcinoma. Signs of photodamage occur at multiple steps. UV radiation damages many cellular constituents, including lipids, proteins and DNA, all of which are likely to contribute to UV-induced skin cancer. Two biological events culminating from photodamage are mutations in the genes critical to the control of cell division, differentiation and invasion and immunosuppression. DNA photodamage, if unrepaired prior to cell division, can result in the incorporation of an incorrect nucleotide into newly synthesised DNA. Mutations in critical genes contribute to carcinogenesis. Photodamage to proteins such as those involved in DNA repair or proteins or lipids involved in cellular signalling can interfere with this repair process and contribute to mutagenesis. Mutations in key genes, including TP53, BRM, PTCH1, and HRAS, contribute to skin carcinogenesis. UV also damages immunity. Photodamage to DNA and signalling lipids as well as other molecular changes are detrimental to the key cells that regulate immunity. Photodamaged dendritic cells and altered responses by mast cells lead to the activation of T and B regulatory cells that suppress immunity to the protein products of UV-mutated genes. This stops the immune response from its protective function of destroying mutated cells, enabling the transformed cells to progress to skin cancer. UV appears to play a pivotal role at each of these steps, and therefore, signs of photodamage point to the development of skin cancer.

An integrated genomics approach to identify genetic regions associated with neonatal growth trait in mice.

Neonatal growth during the early post-partum period is closely associated with lactation performance. Neonatal growth reflects milk output and is a complex variable trait among inbred mouse strains, but few studies have compared this trait systematically across more than a few strains. In the present study, 11 inbred strains of mice were measured for a neonatal growth phenotype during the first eight days of lactation. Significant differences in neonatal growth trait were observed with QSi5 (3.71±0.05 g) and DBA/1J (2.67±0.06 g) strains defining the two extremes of the phenotype. In silico association analysis was performed for trait variability using the high density SNP information on inbred strains of mice. We found strong evidence to refine a previously identified large neonatal growth QTL on mouse chromosome 9, Neogq1. When an integrated strategy that combined fine mapping and analysis of mammary transcriptome expression profiles of lactating mice with divergent phenotypes was applied, we identified neogenin (Neo1), a gene important for mammary gland morphogenesis, as a likely quantitative trait gene (QTG) underlying the Neogq1 QTL in mice.

Identification of gene sets and pathways associated with lactation performance in mice.

Mammary transcriptome analyses across the lactation cycle and transgenic animal studies have identified candidate genes for mammogenesis, lactogenesis and involution; however, there is a lack of information on pathways that contribute to lactation performance. Previously we have shown significant differences in lactation performance, mammary gland histology, and gene expression profiles during lactation [lactation day 9 (L9)] between CBA/CaH (CBA) and the superior performing QSi5 strains of mice. In the present study, we compared these strains at midpregnancy [pregnancy day 12 (P12)] and utilized these data along with data from a 14th generation of intercross (AIL) to develop an integrative analysis of lactation performance. Additional analysis by quantitative reverse transcription PCR examined the correlation between expression profiles of lactation candidate genes and lactation performance across six inbred strains of mice. The analysis demonstrated that the mammary epithelial content per unit area was similar between CBA and QSi5 mice at P12, while differential expression was detected in 354 mammary genes (false discovery rate < 0.1). Gene ontology and functional annotation analyses showed that functional annotation terms associated with cell division and proliferation were the most enriched in the differentially expressed genes between these two strains at P12. Further analysis revealed that genes associated with neuroactive ligand-receptor interaction and calcium signaling pathways were significantly upregulated and positively correlated with lactation performance, while genes associated with cell cycle and DNA replication pathways were downregulated and positively correlated with lactation performance. There was also a significant negative correlation between Grb10 expression and lactation performance. In summary, using an integrative genomic approach we have identified key genes and pathways associated with lactation performance.

An integrative genomic analysis of the superior fecundity phenotype in QSi5 mice.

Laboratory inbred mouse models are a valuable resource to identify quantitative trait loci (QTL) for complex reproductive performance traits. Advances in mouse genomics and high density single nucleotide polymorphism mapping has enabled genome-wide association studies to identify genes linked with specific phenotypes. Gene expression profiles of reproductive tissues also provide potentially useful information for identifying genes that play an important role. We have developed a highly fecund inbred strain, QSi5, with accompanying genotyping for comparative analysis of reproductive performance. Here we analyzed the QSi5 phenotype using a comparative analysis with fecundity data derived from 22 inbred strains of mice from the Mouse Phenome Project, and integration with published expression data from mouse ovary development. Using a haplotype association approach, 400 fecundity-associated regions (FDR < 0.05) with 499 underlying genes were identified. The most significant associations were located on Chromosomes 14, 8, and 6, and the genes underlying these regions were extracted. When these genes were analyzed for expression in an ovarian development profile (GSE6916) several distinctive co-expression patterns across each developmental stage were identified. The genetic analysis also refined 21 fecundity associated intervals on Chromosomes 1, 6, 9, 13, and 17 that overlapped with previously reported reproductive performance QTL. The combined use of phenotypic and in silico data with an integrative genomic analysis provides a powerful tool for elucidating the molecular mechanisms underlying fecundity.

The impact of ABCG2 on bovine mammary epithelial cell proliferation.

The ATP-binding cassette transporter, ABCG2, has been identified as a gene of significance in the regulation of bovine lactation by a number of gene mapping studies yet its role in lactational physiology remains unclear. We have used the potent ABCG2 specific inhibitor, Ko143, to investigate role of ABCG2 in primary bovine mammary epithelial cell (BMEC) proliferation and differentiation. After incubation with Ko143, the proliferation rate of BMECs was reduced at 48 and 72 hours by up to 80% (P < 0.001), and the effect was dose-dependent (approximately 40% with 10 nM Ko143 and 80% with 20 nM Ko143). Morphological changes in BMEC mammosphere formation were not observed when co-incubated with Ko143. Our results suggested that ABCG2 plays a role in mammary epithelial cell proliferation and that functional polymorphisms in this gene may influence the cellular compartment of the mammary gland and potentially milk production.

Variation in immunophenotype of lactating mice.

Immunological factors have been shown to play a crucial role in mammary remodelling in rodent models of lactation, particularly at the stage of mammary involution. However, the relationship between immunological factors and the ability of normal mammary gland to produce milk, as well as the genetic components contributing to lactation performance remain largely unknown. In this study, we assessed the lactation and immunological phenotypes of 11 inbred mouse strains, namely 129X1/SvJ (129), A/J, AKR, C3H/HeJ (C3H), CBA/CaH (CBA), C57BL/6J (C57), DBA/1J, DBA/2J, FVB/N (FVB), QSi5 and SJL/J (SJL) to identify potential links. Leukocyte analyses showed no direct link between the fraction of splenic leukocytes and lactation performance. However, significant strain differences were discovered in the fraction of CD8+ T lymphocytes (P=0.016) and CD11b+Gr-1 mid-low monocytes (P<0.001). Cytokine profiles in plasma were examined and a subset of plasma cytokines, namely CCL2, CCL3, CCL5, CSF2, CSF3, IL10, IL15, IL1B, IL4, IL5, IL7 and TNF, were fitted to a linear regression model for prediction of lactation performance (R-sq=62%, S=0.309). Significant strain differences in the plasma cytokine levels were also discovered amongst these inbred strains. Analysis of immunological phenotypes showed strong correlations between splenic immune cell subsets and their regulating cytokine levels in plasma. The results demonstrate the extent of genetic variability in the immunological phenotypes of lactating mice, and provide a basis for understanding the role of cytokines in milk production, and identifying potential biomarkers of lactation performance.

Developmental regulation of mitochondrial biogenesis and function in the mouse mammary gland during a prolonged lactation cycle.

The regulation of mitochondrial biogenesis and function in the lactating mammary cell is poorly understood. The goal of this study was to use proteomics to relate temporal changes in mammary cell mitochondrial function during lactation to changes in the proteins that make up this organelle. The hypothesis tested was that changes in mammary cell mitochondrial biogenesis and function during lactation would be accounted for by coordinated changes in the proteins of the electron transport chain and that some of these proteins might be linked by their expression patterns to PPARGC1α and AMP kinase. The mitochondrial proteome was studied along with markers of mitochondrial biogenesis and function in mammary tissue collected from mice over the course of a single prolonged lactation cycle. Mammary tissue concentrations of AMP and ADP were increased (P < 0.05) during early lactation and then declined with prolonged lactation. Similar changes were also observed for mitochondrial ATP synthesis activity, mitochondrial mass and DNA copy number. Analysis of the mammary cell mitochondrial proteome identified 244 unique proteins. Of these, only two proteins of the electron transport chain were found to increase during early lactation. In contrast, coordinated changes in numerous electron transport chain proteins were observed both during mid- and late lactation. There were six proteins that could be directly linked to PPARGC1α through network analysis. Abundance of PPARGC-1α and phosphorylation of AMP kinase was highest on day 2 postpartum. The results suggest that the increases in mammary mitochondria ATP synthesis activity during early lactation results from changes in only a limited number proteins. In addition, decreases in a handful of proteins linked to lipid oxidation could be temporally linked to decreases in PPARGC1α and phospho-AMP kinase suggesting potential roles for these proteins in coordinating mammary gland metabolism during early lactation.