Probabilistic Modeling of Process Systems with Application to Risk Assessment and Fault Detection

Three new methods of joint probability estimation (modeling), a maximum-likelihood maximum-entropy method, a constrained maximum-entropy method, and a copula-based method called the rolling pin (RP) method, were developed. Compared to many existing probabilistic modeling methods such as Bayesian networks and copulas, the developed methods yield models that have better performance in terms of flexibility, interpretability and computational tractability. These methods can be used readily to model process systems and perform risk analysis and fault detection at steady state conditions, and can be coupled with appropriate mathematical tools to develop dynamic probabilistic models. Also, a method of performing probabilistic inference using RP-estimated joint probability distributions was introduced; this method is superior to Bayesian networks in several aspects. The RP method was also applied successfully to identify regression models that have high level of flexibility and are appealing in terms of computational costs.Ph.D., Chemical Engineering -- Drexel University, 201

Process/Equipment Design Implications for Control System Cybersecurity

An emerging challenge for process safety is process control system cybersecurity. An attacker could gain control of the process actuators through the control system or communication policies within control loops and potentially drive the process state to unsafe conditions. Cybersecurity has traditionally been handled as an information technology (IT) problem in the process industries. In the literature for cybersecurity specifically of control systems, there has been work aimed at developing control designs that seek to fight cyberattacks by either giving the system appropriate response mechanisms once attacks are detected or seeking to make the attacks difficult to perform. In this work, we begin an exploration into the implications of process and equipment design for enhancing the ability of chemical processes to maintain safe operation during cyberattacks on the process control systems

Sequential LASER ART and CRISPR treatments eliminate HIV-1 in a subset of infected humanized mice

Elimination of HIV-1 requires clearance and removal of integrated proviral DNA from infected cells and tissues. Here, sequential long-acting slow-effective release antiviral therapy (LASER ART) and CRISPR-Cas9 demonstrate viral clearance in latent infectious reservoirs in HIV-1 infected humanized mice. HIV-1 subgenomic DNA fragments, spanning the long terminal repeats and the Gag gene, are excised in vivo, resulting in elimination of integrated proviral DNA; virus is not detected in blood, lymphoid tissue, bone marrow and brain by nested and digital-droplet PCR as well as RNAscope tests. No CRISPR-Cas9 mediated off-target effects are detected. Adoptive transfer of human immunocytes from dual treated, virus-free animals to uninfected humanized mice fails to produce infectious progeny virus. In contrast, HIV-1 is readily detected following sole LASER ART or CRISPR-Cas9 treatment. These data provide proof-of-concept that permanent viral elimination is possible

Molecular and Cellular Impact of Inflammatory Extracellular Vesicles (EVs) Derived from M1 and M2 Macrophages on Neural Action Potentials

Several factors can contribute to neuroinflammatory disorders, such as cytokine and chemokines that are produced and released from peripherally derived immune cells or from locally activated cells such as microglia and perivascular macrophages in the brain. The primary function of these cells is to clear inflammation; however, following inflammation, circulating monocytes are recruited to the central nervous system (CNS). Monocyte-derived macrophages in the CNS play pivotal roles in mediating neuroinflammatory responses. Macrophages are heterogeneous both in normal and in pathological conditions due to their plasticity, and they are classified in two main subsets, classically activated (M1) or alternatively activated (M2). There is accumulating evidence suggesting that extracellular vesicles (EVs) released from activated immune cells may play crucial roles in mediating inflammation. However, a possible role of EVs released from immune cells such as M1 and M2 macrophages on neuronal functions in the brain is not known. In order to investigate the molecular and cellular impacts of macrophages and EVs released from macrophage subtypes on neuronal functions, we used a recently established in vitro M1 and M2 macrophage culture model and isolated and characterized EVs from these macrophage subtypes, treated primary neurons with M1 or M2 EVs, and analyzed the extracellular action potentials of neurons with microelectrode array studies (MEA). Our results introduce evidence on the interfering role of inflammatory EVs released from macrophages in interneuronal signal transmission processes, with implications in the pathogenesis of neuroinflammatory diseases induced by a variety of inflammatory insults

Toxicology knowledge graph for structural birth defects

Abstract Background Birth defects are functional and structural abnormalities that impact about 1 in 33 births in the United States. They have been attributed to genetic and other factors such as drugs, cosmetics, food, and environmental pollutants during pregnancy, but for most birth defects there are no known causes. Methods To further characterize associations between small molecule compounds and their potential to induce specific birth abnormalities, we gathered knowledge from multiple sources to construct a reproductive toxicity Knowledge Graph (ReproTox-KG) with a focus on associations between birth defects, drugs, and genes. Specifically, we gathered data from drug/birth-defect associations from co-mentions in published abstracts, gene/birth-defect associations from genetic studies, drug- and preclinical-compound-induced gene expression changes in cell lines, known drug targets, genetic burden scores for human genes, and placental crossing scores for small molecules. Results Using ReproTox-KG and semi-supervised learning (SSL), we scored >30,000 preclinical small molecules for their potential to cross the placenta and induce birth defects, and identified >500 birth-defect/gene/drug cliques that can be used to explain molecular mechanisms for drug-induced birth defects. The ReproTox-KG can be accessed via a web-based user interface available at https://maayanlab.cloud/reprotox-kg . This site enables users to explore the associations between birth defects, approved and preclinical drugs, and all human genes. Conclusions ReproTox-KG provides a resource for exploring knowledge about the molecular mechanisms of birth defects with the potential of predicting the likelihood of genes and preclinical small molecules to induce birth defects