A Markov decision process embedded with predictive modeling: a modeling approach from system dynamics mathematical models, agent-based models to a clinical decision making

Doctor of PhilosophyDepartment of Industrial & Manufacturing Systems EngineeringDavid H. Ben-AriehChih-Hang WuPatients who suffer from sepsis or septic shock are of great concern in the healthcare system. Recent data indicate that more than 900,000 severe sepsis or septic shock cases developed in the United States with mortality rates between 20% and 80%. In the United States alone, almost $17 billion is spent each year for the treatment of patients with sepsis. Clinical trials of treatments for sepsis have been extensively studied in the last 30 years, but there is no general agreement of the effectiveness of the proposed treatments for sepsis. Therefore, it is necessary to find accurate and effective tools that can help physicians predict the progression of disease in a patient-specific way, and then provide physicians recommendation on the treatment of sepsis to lower risk for patients dying from sepsis. The goal of this research is to develop a risk assessment tool and a risk management tool for sepsis. In order to achieve this goal, two system dynamic mathematical models (SDMMs) are initially developed to predict dynamic patterns of sepsis progression in innate immunity and adaptive immunity. The two SDMMs are able to identify key indicators and key processes of inflammatory responses to an infection, and a sepsis progression. Second, an integrated-mathematical-multi-agent-based model (IMMABM) is developed to capture the stochastic nature embedded in the development of inflammatory responses to a sepsis. Unlike existing agent-based models, this agent-based model is enhanced by incorporating developed SDMMs and extensive experimental data. With the risk assessment tools, a Markov decision process (MDP) is proposed, as a risk management tool, to apply to clinical decision-makings on sepsis. With extensive computational studies, the major contributions of this research are to firstly develop risk assessment tools to identify the risk of sepsis development during the immune system responding to an infection, and secondly propose a decision-making framework to manage the risk of infected individuals dying from sepsis. The methodology and modeling framework used in this dissertation can be expanded to other disease situations and treatment applications, and have a broad impact to the research area related to computational modeling, biology, medical decision-making, and industrial engineering

IL-17A Upregulates Keratin 17 Expression in Keratinocytes through STAT1- and STAT3-Dependent Mechanisms

Psoriasis, an immunological skin disease, is characterized by epidermal hyperproliferation, chronic inflammation, and an accumulation of infiltrating T cells. IL-17A is a key cytokine that has a critical role in the pathogenesis of psoriasis. Keratin 17 (K17) is strongly expressed in psoriatic lesions but not in normal skin. Thus, K17 expression is regarded as a hallmark of psoriasis. We previously reported that the K17/T cells/cytokine autoimmune loop was involved in psoriasis. However, the relationship between IL-17A and K17 has yet to be determined. In the present study, IL-17A-induced K17 expression was confirmed in cultured keratinocytes in both mRNA and protein levels. In addition, increased K17 expression was found in the epidermis of IL-17A-injected mouse skin. The regulatory mechanism of K17 expression was further investigated. We found that both the signal transducer and activator of transcription (STAT) 1 and STAT3 pathways were involved in the upregulation of K17 expression induced by IL-17A, and that such regulation could be partially suppressed by STAT1 or STAT3 small interfering RNA and inhibitor. Our data suggest that IL-17A can upregulate K17 expression in keratinocytes in a dose-dependent manner through STAT1- and STAT3-dependent mechanisms. The results indicate that IL-17A might be an important cytokine in the K17/T cells/cytokine autoimmune loop associated with psoriasis

(2E,6E)-2,6-Bis(4-ethoxy­benzyl­idene)cyclo­hexa­none

The title compound, C24H26O3, was prepared by the condensation reaction of 4-ethoxy­benzaldehyde with cyclo­hexa­none. The mol­ecule has crystallographic mirror symmetry and exhibits a butterfly-shaped geometry, with a dihedral angle of 5.46 (1)° between the two benzene rings. Weak inter­molecular C—H⋯π inter­actions help stabilize the crystal structure

Superposition Meet-in-the-Middle Attacks: Updates on Fundamental Security of AES-like Hashing

The Meet-in-the-Middle approach is one of the most powerful cryptanalysis techniques, demonstrated by its applications in preimage attacks on the full MD4, MD5, Tiger, HAVAL, and Haraka-512 v2 hash functions, and key recovery of the full block cipher KTANTAN. The success relies on the separation of a primitive into two independent chunks, where each active cell of the state is used to represent only one chunk or is otherwise considered unusable once mixed. We observe that some of such cells are linearly mixed and can be as useful as the independent ones. This leads to the introduction of superposition states and a whole suite of accompanied techniques, which we incorporate into the MILP-based search framework proposed by Bao et al. at EUROCRYPT 2021 and Dong et al. at CRYPTO 2021, and find applications on a wide range of AES-like hash functions and block ciphers

Application of mNGS in the study of pulmonary microbiome in pneumoconiosis complicated with pulmonary infection patients and exploration of potential biomarkers

BackgroundPneumoconiosis patients have a high prevalence of pulmonary infections, which can complicate diagnosis and treatment. And there is no comprehensive study of the microbiome of patients with pneumoconiosis. The application of metagenomic next-generation sequencing (mNGS) fills the gap to some extent by analyzing the lung microbiota of pneumoconiosis population while achieving accurate diagnosis.MethodsWe retrospectively analyzed 44 patients with suspected pneumoconiosis complicated with pulmonary infection between Jan 2020 and Nov 2022. Bronchoalveolar lavage fluid (BALF) specimens from 44 patients were collected and tested using the mNGS technology.ResultsAmong the lung microbiome of pneumoconiosis patients with complicated pulmonary infection (P group), the most frequently detected bacteria and fungi at the genus level were Streptococcus and Aspergillus, at the species level were Streptococcus pneumoniae and Aspergillus flavus, respectively, and the most frequently detected DNA virus was Human gammaherpesvirus 4. There was no significant difference in α diversity between the P group and the non-pneumoconiosis patients complicated with pulmonary infection group (Non-P group) in pulmonary flora, while P< 0.01 for β diversity analysis, and the differential species between the two groups were Mycobacterium colombiense and Fusobacterium nucleatum. In addition, we monitored a high distribution of Malassezia and Pneumocystis in the P group, while herpes virus was detected in the majority of samples.ConclusionsOverall, we not only revealed a comprehensive lung microbiome profile of pneumoconiosis patients, but also compared the differences between their microbiome and that of non-pneumoconiosis complicated with pulmonary infection patients. This provides a good basis for a better understanding of the relationship between pneumoconiosis and microorganisms, and for the search of potential biomarkers

Harpin-induced expression and transgenic overexpression of the phloem protein gene AtPP2-A1 in Arabidopsis repress phloem feeding of the green peach aphid Myzus persicae

<p>Abstract</p> <p>Background</p> <p>Treatment of plants with HrpN_Ea, a protein of harpin group produced by Gram-negative plant pathogenic bacteria, induces plant resistance to insect herbivores, including the green peach aphid <it>Myzus persicae</it>, a generalist phloem-feeding insect. Under attacks by phloem-feeding insects, plants defend themselves using the phloem-based defense mechanism, which is supposed to involve the phloem protein 2 (PP2), one of the most abundant proteins in the phloem sap. The purpose of this study was to obtain genetic evidence for the function of the <it>Arabidopsis thaliana </it>(Arabidopsis) PP2-encoding gene <it>AtPP2-A1 </it>in resistance to <it>M. persicae </it>when the plant was treated with HrpN_Eaand after the plant was transformed with <it>AtPP2-A1</it>.</p> <p>Results</p> <p>The electrical penetration graph technique was used to visualize the phloem-feeding activities of apterous agamic <it>M. persicae </it>females on leaves of Arabidopsis plants treated with HrpN_Eaand an inactive protein control, respectively. A repression of phloem feeding was induced by HrpN_Eain wild-type (WT) Arabidopsis but not in <it>atpp2-a1</it>/E/142, the plant mutant that had a defect in the <it>AtPP2-A1 </it>gene, the most HrpN_Ea-responsive of 30 <it>AtPP2 </it>genes. In WT rather than <it>atpp2-a1</it>/E/142, the deterrent effect of HrpN_Eatreatment on the phloem-feeding activity accompanied an enhancement of <it>AtPP2-A1 </it>expression. In PP2OETAt (<it>AtPP2-A1</it>-overexpression transgenic <it>Arabidopsis thaliana</it>) plants, abundant amounts of the <it>AtPP2-A1 </it>gene transcript were detected in different organs, including leaves, stems, calyces, and petals. All these organs had a deterrent effect on the phloem-feeding activity compared with the same organs of the transgenic control plant. When a large-scale aphid population was monitored for 24 hours, there was a significant decrease in the number of aphids that colonized leaves of HrpN_Ea-treated WT and PP2OETAt plants, respectively, compared with control plants.</p> <p>Conclusions</p> <p>The repression in phloem-feeding activities of <it>M. persicae </it>as a result of <it>AtPP2-A1 </it>overexpression, and as a deterrent effect of HrpN_Eatreatment in WT Arabidopsis rather than the <it>atpp2-a1</it>/E/142 mutant suggest that <it>AtPP2-A1 </it>plays a role in plant resistance to the insect, particularly at the phloem-feeding stage. The accompanied change of aphid population in leaf colonies suggests that the function of <it>AtPP2-A1 </it>is related to colonization of the plant.</p