Trajectory Tracking Error Using Fractional Order PID Control Law for Two‐Link Robot Manipulator via Fractional Adaptive Neural Networks

The problem of trajectory tracking of unknown nonlinear systems of fractional order is solved using fractional order dynamical neural networks. For this purpose, we obtained control laws and laws of adaptive weights online, obtained using the Lyapunov stability analysis methodology of fractional order. Numerical simulations illustrate the obtained theoretical results

Trajectory Tracking Using Adaptive Fractional PID Control of Biped Robots with Time-Delay Feedback

This paper presents the application of fractional order time-delay adaptive neural networks to the trajectory tracking for chaos synchronization between Fractional Order delayed plant, reference and fractional order time-delay adaptive neural networks. For this purpose, we obtained two control laws and laws of adaptive weights online, obtained using the fractional order Lyapunov-Krasovskii stability analysis methodology. The main methodologies, on which the approach is based, are fractional order PID the fractional order Lyapunov-Krasovskii functions methodology, although the results we obtain are applied to a wide class of non-linear systems, we will apply it in this chapter to a bipedal robot. The structure of the biped robot is designed with two degrees of freedom per leg, corresponding to the knee and hip joints. Since torso and ankle are not considered, it is obtained a 4-DOF system, and each leg, we try to force this biped robot to track a reference signal given by undamped Duffing equation. To verify the analytical results, an example of dynamical network is simulated, and two theorems are proposed to ensure the tracking of the nonlinear system. The tracking error is globally asymptotically stabilized by two control laws derived based on a Lyapunov-Krasovskii functional

dCas9-based epigenome editing suggests acquisition of histone methylation is not sufficient for target gene repression.

Distinct epigenomic profiles of histone marks have been associated with gene expression, but questions regarding the causal relationship remain. Here we investigated the activity of a broad collection of genomically targeted epigenetic regulators that could write epigenetic marks associated with a repressed chromatin state (G9A, SUV39H1, Krüppel-associated box (KRAB), DNMT3A as well as the first targetable versions of Ezh2 and Friend of GATA-1 (FOG1)). dCas9 fusions produced target gene repression over a range of 0- to 10-fold that varied by locus and cell type. dCpf1 fusions were unable to repress gene expression. The most persistent gene repression required the action of several effector domains; however, KRAB-dCas9 did not contribute to persistence in contrast to previous reports. A 'direct tethering' strategy attaching the Ezh2 methyltransferase enzyme to dCas9, as well as a 'recruitment' strategy attaching the N-terminal 45 residues of FOG1 to dCas9 to recruit the endogenous nucleosome remodeling and deacetylase complex, were both successful in targeted deposition of H3K27me3. Surprisingly, however, repression was not correlated with deposition of either H3K9me3 or H3K27me3. Our results suggest that so-called repressive histone modifications are not sufficient for gene repression. The easily programmable dCas9 toolkit allowed precise control of epigenetic information and dissection of the relationship between the epigenome and gene regulation

Adaptive fractional PID control of biped robots with time-delayed feedback

This paper presents the application of Fractional Order Time- Delay adaptive neural networks to the trajectory tracking for chaos synchronization between Fractional Order delayed plant, reference and Fractional Order Time-Delay adaptive neural networks. The proposed new control scheme is applied via simulations to control of a 4-DOF Biped Robot [1]. The main methodologies, on which the approach is based, are Fractional Order PID the Fractional Order Lyapunov-Krasovskii functions methodology. The structure of the biped robot is designed with two degrees of freedom per leg, corresponding to the knee and hip joints. Since torso and ankle are not considered, it is obtained a 4-DOF system, and each leg, we try to force this biped robot to track a reference signal given by undamped Duffing equation. The tracking error is globally asymptotically stabilized by two control laws derived based on a Lyapunov-Krasovski functional

Identification of a Serum-Induced Transcriptional Signature Associated With Type 1 Diabetes in the BioBreeding Rat

OBJECTIVE - Inflammatory mediators associated with type 1 diabetes are dilute and difficult to measure in the periphery, necessitating development of more sensitive and informative biomarkers for studying diabetogenic mechanisms, assessing preonset risk, and monitoring therapeutic interventions. RESEARCH DESIGN AND METHODS - We previously utilized a novel bioassay in which human type 1 diabetes sera were used to induce a disease-specific transcriptional signature in unrelated, healthy peripheral blood mononuclear cells (PBMCs). Here, we apply this strategy to investigate the inflammatory state associated with type 1 diabetes in biobreeding (BB) rats. RESULTS - Consistent with their common susceptibility, sera of both spontaneously diabetic BB DRlyp/lyp and diabetes inducible BB DR+/+ rats induced transcription of cytokines, immune receptors, and signaling molecules in PBMCs of healthy donor rats compared with control sera. Like the human type 1 diabetes signature, the DRlyp/lyp signature, which is associated with progression to diabetes, was differentiated from that of the DR+/+ by induction of many interleukin (IL)-1-regulated genes. Supplementing cultures with an IL-1 receptor antagonist (IL-1Ra) modulated the DRlyp/lyp signature (P < 10-6), while administration of IL-1Ra to DRlyp/lyp rats delayed onset (P = 0.007), and sera of treated animals did not induce the characteristic signature. Consistent with the presence of immunoregulatory cells in DR+/+ rats was induction of a signature possessing negative regulators of transcription and inflammation. CONCLUSIONS - Paralleling our human studies, serum signatures in BB rats reflect processes associated with progression to type 1 diabetes. Furthermore, these studies support the potential utility of this approach to detect changes in the inflammatory state during therapeutic intervention

Pharmacological risk factors associated with hospital readmission rates in a psychiatric cohort identified using prescriptome data mining

Background Worldwide, over 14% of individuals hospitalized for psychiatric reasons have readmissions to hospitals within 30 days after discharge. Predicting patients at risk and leveraging accelerated interventions can reduce the rates of early readmission, a negative clinical outcome (i.e., a treatment failure) that affects the quality of life of patient. To implement individualized interventions, it is necessary to predict those individuals at highest risk for 30-day readmission. In this study, our aim was to conduct a data-driven investigation to find the pharmacological factors influencing 30-day all-cause, intra- and interdepartmental readmissions after an index psychiatric admission, using the compendium of prescription data (prescriptome) from electronic medical records (EMR). Methods The data scientists in the project received a deidentified database from the Mount Sinai Data Warehouse, which was used to perform all analyses. Data was stored in a secured MySQL database, normalized and indexed using a unique hexadecimal identifier associated with the data for psychiatric illness visits. We used Bayesian logistic regression models to evaluate the association of prescription data with 30-day readmission risk. We constructed individual models and compiled results after adjusting for covariates, including drug exposure, age, and gender. We also performed digital comorbidity survey using EMR data combined with the estimation of shared genetic architecture using genomic annotations to disease phenotypes. Results Using an automated, data-driven approach, we identified prescription medications, side effects (primary side effects), and drug-drug interaction-induced side effects (secondary side effects) associated with readmission risk in a cohort of 1275 patients using prescriptome analytics. In our study, we identified 28 drugs associated with risk for readmission among psychiatric patients. Based on prescription data, Pravastatin had the highest risk of readmission (OR = 13.10; 95% CI (2.82, 60.8)). We also identified enrichment of primary side effects (n = 4006) and secondary side effects (n = 36) induced by prescription drugs in the subset of readmitted patients (n = 89) compared to the non-readmitted subgroup (n = 1186). Digital comorbidity analyses and shared genetic analyses further reveals that cardiovascular disease and psychiatric conditions are comorbid and share functional gene modules (cardiomyopathy and anxiety disorder: shared genes (n = 37; P = 1.06815E-06)). Conclusions Large scale prescriptome data is now available from EMRs and accessible for analytics that could improve healthcare outcomes. Such analyses could also drive hypothesis and data-driven research. In this study, we explored the utility of prescriptome data to identify factors driving readmission in a psychiatric cohort. Converging digital health data from EMRs and systems biology investigations reveal a subset of patient populations that have significant comorbidities with cardiovascular diseases are more likely to be readmitted. Further, the genetic architecture of psychiatric illness also suggests overlap with cardiovascular diseases. In summary, assessment of medications, side effects, and drug-drug interactions in a clinical setting as well as genomic information using a data mining approach could help to find factors that could help to lower readmission rates in patients with mental illness

An integrative ChIP-chip and gene expression profiling to model SMAD regulatory modules

<p>Abstract</p> <p>Background</p> <p>The TGF-β/SMAD pathway is part of a broader signaling network in which crosstalk between pathways occurs. While the molecular mechanisms of TGF-β/SMAD signaling pathway have been studied in detail, the global networks downstream of SMAD remain largely unknown. The regulatory effect of SMAD complex likely depends on transcriptional modules, in which the SMAD binding elements and partner transcription factor binding sites (SMAD modules) are present in specific context.</p> <p>Results</p> <p>To address this question and develop a computational model for SMAD modules, we simultaneously performed chromatin immunoprecipitation followed by microarray analysis (ChIP-chip) and mRNA expression profiling to identify TGF-β/SMAD regulated and synchronously coexpressed gene sets in ovarian surface epithelium. Intersecting the ChIP-chip and gene expression data yielded 150 direct targets, of which 141 were grouped into 3 co-expressed gene sets (sustained up-regulated, transient up-regulated and down-regulated), based on their temporal changes in expression after TGF-β activation. We developed a data-mining method driven by the Random Forest algorithm to model SMAD transcriptional modules in the target sequences. The predicted SMAD modules contain SMAD binding element and up to 2 of 7 other transcription factor binding sites (E2F, P53, LEF1, ELK1, COUPTF, PAX4 and DR1).</p> <p>Conclusion</p> <p>Together, the computational results further the understanding of the interactions between SMAD and other transcription factors at specific target promoters, and provide the basis for more targeted experimental verification of the co-regulatory modules.</p

Gradual polyploid genome evolution revealed by pan-genomic analysis of Brachypodium hybridum and its diploid progenitors

Our understanding of polyploid genome evolution is constrained because we cannot know the exact founders of a&nbsp;particular polyploid. To differentiate between founder effects and post polyploidization evolution, we use a pan-genomic approach to study the allotetraploid Brachypodium hybridum and its diploid progenitors. Comparative analysis suggests that most B. hybridum whole gene presence/absence variation is part of the standing variation in its diploid progenitors. Analysis of nuclear single nucleotide variants, plastomes and k-mers associated with retrotransposons reveals two independent origins for B. hybridum, ~1.4 and ~0.14 million years ago. Examination of gene expression in the younger B. hybridum lineage reveals no bias in overall subgenome expression. Our results are consistent with a gradual accumulation of genomic changes after polyploidization and a lack of subgenome expression dominance. Significantly, if we did not use a pan-genomic approach, we would grossly overestimate the number of genomic changes attributable to post polyploidization evolution

Evidence of Expanded Host Range and Mammalian-Associated Genetic Changes in a Duck H9N2 Influenza Virus Following Adaptation in Quail and Chickens

H9N2 avian influenza viruses continue to circulate worldwide; in Asia, H9N2 viruses have caused disease outbreaks and established lineages in land-based poultry. Some H9N2 strains are considered potentially pandemic because they have infected humans causing mild respiratory disease. In addition, some of these H9N2 strains replicate efficiently in mice without prior adaptation suggesting that H9N2 strains are expanding their host range. In order to understand the molecular basis of the interspecies transmission of H9N2 viruses, we adapted in the laboratory a wildtype duck H9N2 virus, influenza A/duck/Hong Kong/702/79 (WT702) virus, in quail and chickens through serial lung passages. We carried out comparative analysis of the replication and transmission in quail and chickens of WT702 and the viruses obtained after 23 serial passages in quail (QA23) followed by 10 serial passages in chickens (QA23CkA10). Although the WT702 virus can replicate and transmit in quail, it replicates poorly and does not transmit in chickens. In contrast, the QA23CkA10 virus was very efficient at replicating and transmitting in quail and chickens. Nucleotide sequence analysis of the QA23 and QA23CkA10 viruses compared to the WT702 virus indicated several nucleotide substitutions resulting in amino acid changes within the surface and internal proteins. In addition, a 21-amino acid deletion was found in the stalk of the NA protein of the QA23 virus and was maintained without further modification in the QA23CkA10 adapted virus. More importantly, both the QA23 and the QA23CkA10 viruses, unlike the WT702 virus, were able to readily infect mice, produce a large-plaque phenotype, showed faster replication kinetics in tissue culture, and resulted in the quick selection of the K627 amino acid mammalian-associated signature in PB2. These results are in agreement with the notion that adaptation of H9 viruses to land-based birds can lead to strains with expanded host range