Quantitative Physiologically-Based Sleep Modeling: Dynamical Analysis and Clinical Applications

In this thesis, a recently developed physiologically-based model of the sleep-wake switch is analyzed and applied to a variety of clinically-relevant protocols. In contrast to phenomenological models, which have dominated sleep modeling in the past, the present work demonstrates the advantages of the physiologically-based approach. Dynamical and linear stability analyses of the Phillips-Robinson sleep model allow us to create a general framework for determining its response to arbitrary external stimuli. The effects of near-stable wake and sleep ghosts on the model’s dynamics are found to have implications for arousal during sleep, sleep deprivation, and sleep inertia. Impulsive sensory stimuli during sleep are modeled modeled according to their known physiological mechanism. The predicted arousal threshold variation matches experimental data from the literature. In simulating a sleep fragmentation protocol, the model simultaneously reproduces the body temperature and arousal threshold variation measured in another existing clinical study. In the second part of the thesis, we simulate sleep deprivation by introducing a wake-effort drive that is required to maintain wakefulness during normal sleeping periods. We interpret this drive both physiologically and psychologically, and demonstrate quantitative agreement between the model’s output and experimental subjective fatigue-related data. As well as subjective fatigue, the model is simultaneously able to reproduce adrenaline excretion and body temperature variations. In the final part of the thesis, the model is extended to include the orexinergic neurons of the lateral hypothalamic area. Due to the dynamics of the orexin group, the extended model exhibits sleep inertia, and an inhibitory circadian projection to the orexin group produces a postlunch dip in performance – both of which are well-known behavioral features. Including both homeostatic and circadian inputs to the orexin group, the model produces a waking arousal variation that quantitatively matches published clinical data

Metals Additive Manufacturing Development at Harvest Technologies

Harvest Technologies received an EOS M280 in April of 2013 for the production of metal parts through additive manufacturing (AM). Inconel 718 was chosen as a starting material due to its high-end applications in the oil and aerospace industries. Two major areas are of high priority in understanding the machine: (1) mechanical property characterization and (2) geometrical production capability through building prototype models. The following is a working document of Harvest’ progression in developing knowledge in the field of metals AM.Mechanical Engineerin

Robust Design of Negative Stiffness Elements Fabricated by Selective Laser Sintering

Constrained negative stiffness structures have been shown to possess desirable vibration isolation properties because of their ability to provide low dynamic stiffness, resulting in low transmissibility over a wide range of frequencies. In this research, selective laser sintering (SLS) is an integral part of a model-design-build-test process for investigating the vibration isolation capabilities of negative stiffness structures in the form of axially compressed beams. SLS provides geometric design freedom and rapid fabrication capabilities for validating dynamic models of structural behavior and guiding the design process toward iterative improvements. SLS also introduces some geometric and dimensional variability that can significantly degrade the performance of the structure. In this paper, an iterative model-design-build-test process for negative stiffness structures is described and presented with an analysis of the impact of SLS-induced imperfections on the results.Mechanical Engineerin

Comparison of AlSi10Mg and Al 6061 Processed through DMLS

Direct Metal Laser Sintering (DMLS) processing of aluminum alloys has been primarily limited to a casting grade of aluminum, AlSi10Mg. The reasons for the choice of AlSi10Mg by machine manufacturers are presently unknown; however, it is suspected that the reduced coefficient of thermal expansion (CTE) due to the presence of Silicon may enhance DMLS processability. Aluminum 6061 (Al 6061) is a commonly used alloy across a wide range of industries and applications, and Harvest has observed a high interest in DMLS-manufactured Al 6061 products. However, the higher CTE value potentially presents greater challenges in controlling the shrinkage-induced warp common during DMLS. The work presented in this paper was performed in an effort to understand differences in manufacturability as well as mechanical properties of DMLS-processed AlSi10Mg and Al 6061.Mechanical Engineerin

Object size determines the spatial spread of visual time

A key question for temporal processing research is how the nervous system extracts event duration, despite a notable lack of neural structures dedicated to duration encoding. This is in stark contrast to the orderly arrangement of neurons tasked with spatial processing. In the current study, we examine the linkage between the spatial and temporal domains. We use sensory adaptation techniques to generate aftereffects where perceived duration is either compressed or expanded in the opposite direction to the adapting stimulus’ duration. Our results indicate that these aftereffects are broadly tuned, extending over an area approximately five times the size of the stimulus. This region is directly related to the size of the adapting stimulus – the larger the adapting stimulus the greater the spatial spread of the aftereffect. We construct a simple model to test predictions based on overlapping adapted vs non-adapted neuronal populations and show that our effects cannot be explained by any single, fixed-scale neural filtering. Rather, our effects are best explained by a self scaled mechanism underpinned by duration selective neurons that also pool spatial information across earlier stages of visual processing

Alterations to the Gastrointestinal Microbiome Associated with Methamphetamine Use among Young Men who have Sex with Men.

Methamphetamine (MA) use is a major public health problem in the United States, especially among people living with HIV (PLWH). Many MA-induced neurotoxic effects are mediated by inflammation and gut microbiota may play a role in this process, yet the effects of MA on the microbiome have not been adequately explored. Therefore, we performed 16S rRNA gene sequencing on rectal swab samples from 381 men who have sex with men, 48% of whom were PLWH and 41% of whom used MA. We compared microbiome composition between MA users and non-users while testing for potential interactions with HIV and controlling for numerous confounders using inverse probability of treatment weighting. We found that MA use explained significant variation in overall composition (R2 = 0.005, p = 0.008) and was associated with elevated Finegoldia, Parvimonas, Peptoniphilus, and Porphyromonas and reduced Butyricicoccus and Faecalibacterium, among others. Genera including Actinomyces and Streptobacillus interacted with HIV status, such that they were increased in HIV+ MA users. Finegoldia and Peptoniphilus increased with increasing frequency of MA use, among others. In summary, MA use was associated with a microbial imbalance favoring pro-inflammatory bacteria, including some with neuroactive potential and others that have previously been associated with poor HIV outcomes

Machine Learning Prediction of COVID-19 Severity Levels From Salivaomics Data

The clinical spectrum of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the strain of coronavirus that caused the COVID-19 pandemic, is broad, extending from asymptomatic infection to severe immunopulmonary reactions that, if not categorized properly, may be life-threatening. Researchers rate COVID-19 patients on a scale from 1 to 8 according to the severity level of COVID-19, 1 being healthy and 8 being extremely sick, based on a multitude of factors including number of clinic visits, days since the first sign of symptoms, and more. However, there are two issues with the current state of severity level designation. Firstly, there exists variation among researchers in determining these patient scores, which may lead to improper treatment. Secondly, researchers use a variety of metrics to determine patient severity level, including metrics involving plasma collection that require invasive procedures. This project aims to remedy both issues by introducing a machine learning framework that unifies severity level designations based on noninvasive saliva biomarkers. Our results show that we can successfully use machine learning on salivaomics data to predict the severity level of COVID-19 patients, indicating the presence of viral load using saliva biomarkers

Relative and Absolute Risk Reductions in Cardiovascular and Kidney Outcomes With Canagliflozin Across KDIGO Risk Categories:Findings From the CANVAS Program

Rationale & Objective: Canagliflozin reduces the risk for cardiovascular and kidney outcomes in type 2 diabetes. This study aimed to assess the relative and absolute effects of canagliflozin on clinical outcomes across different KDIGO (Kidney Disease: Improving Global Outcomes) risk categories based on estimated glomerular filtration rate (eGFR) and urinary albumin-creatinine ratio. Study Design: Post hoc analysis of the CANagliflozin cardioVascular Assessment Study (CANVAS) Program. Settings & Participants: The CANVAS Program randomly assigned 10,142 participants with type 2 diabetes at high cardiovascular risk and with eGFR ≥ 30 mL/min/1.73 m2 to treatment with canagliflozin or placebo. Intervention(s): Canagliflozin or matching placebo. Outcomes: The primary outcome was a composite of cardiovascular death, nonfatal myocardial infarction, or nonfatal stroke, with a set of other cardiovascular and kidney prespecified outcomes. Results: Of 10,142 participants, 10,031 (98.9%) had available baseline eGFR and urinary albumin-creatinine ratio data. The proportion of participants in low-, moderate-, high-, and very high–risk KDIGO categories was 58.6%, 25.8%, 10.6%, and 5.0%, respectively. The relative effect of canagliflozin on the primary outcome (HR, 0.86; 95% CI, 0.75-0.97) was consistent across KDIGO risk categories (P trend = 0.2), with similar results for other cardiovascular and kidney outcomes. Absolute reductions in the primary outcome were greater within higher KDIGO risk categories (P trend = 0.03) with a similar pattern of effect for the composite of cardiovascular death or hospitalization for heart failure (P trend = 0.06) and for chronic eGFR slope (P trend = 0.04). Limitations: Predominantly a low kidney risk population, relatively few participants in higher KDIGO risk categories, and exclusion of individuals with eGFR < 30 mL/min/1.73 m2. Conclusions: Although the relative effects of canagliflozin are similar across KDIGO risk categories, absolute risk reductions are likely greater for individuals at higher KDIGO risk. The KDIGO classification system may be able to identify individuals who might derive greater benefits for end-organ protection from treatment with canagliflozin. Funding: This post hoc analysis was not specifically funded. The original CANVAS Program trials were funded by Janssen Research & Development, LLC and were conducted as a collaboration between the funder, an academic steering committee, and an academic research organization, George Clinical. Trial Registration: The original trials of the CANVAS Program were registered at ClinicalTrials.gov with study numbers NCT01032629 and NCT01989754

Deficiency of Th17 cells in hyper IgE syndrome due to mutations in STAT3

Hyper–immunoglobulin E syndrome (HIES) is a primary immune deficiency characterized by abnormal and devastating susceptibility to a narrow spectrum of infections, most commonly Staphylococcus aureus and Candida albicans. Recent investigations have identified mutations in STAT3 in the majority of HIES patients studied. Despite the identification of the genetic cause of HIES, the mechanisms underlying the pathological features of this disease remain to be elucidated. Here, we demonstrate a failure of CD4+ T cells harboring heterozygous STAT3 mutations to generate interleukin 17–secreting (i.e., T helper [Th]17) cells in vivo and in vitro due to a failure to express sufficient levels of the Th17-specific transcriptional regulator retinoid-related orphan receptor γt. Because Th17 cells are enriched for cells with specificities against fungal antigens, our results may explain the pattern of infection susceptibility characteristic of patients with HIES. Furthermore, they underscore the importance of Th17 responses in normal host defense against the common pathogens S. aureus and C. albicans

HbA1c variability in adults with type 1 diabetes on continuous subcutaneous insulin infusion (CSII) therapy compared to multiple daily injection (MDI) treatment

Objective To determine if continuous subcutaneous insulin infusion (CSII) therapy is associated with lower glycated haemoglobin (HbA1c) variability (long-term glycaemic variability; GV) relative to multiple daily injection (MDI) treatment in adults with type 1 diabetes mellitus (T1DM). Design Retrospective audit. Setting and participants Clinic records from 506 adults with T1DM from two tertiary Australian hospitals. Outcome measures Long-term GV was assessed by HbA1c SD and coefficient of variation (CV) in adults on established MDI or CSII therapy, and in a subset changing from MDI to CSII. Results Adults (n=506, (164 CSII), 50% women, mean±SD age 38.0±15.3 years, 17.0±13.7 years diabetes, mean HbA1c 7.8%±1.2% (62±13 mmol/mol) on CSII, 8.0%±1.5% (64±16 mmol/mol) on MDI) were followed for 4.1±3.6 years. CSII use was associated with lower GV (HbA1c SD: CSII vs MDI 0.5%±0.41% (6±6 mmol/mol) vs 0.7%±0.7% (9±8 mmol/mol)) and CV: CSII vs MDI 6.7%±4.6% (10±10 mmol/mol) vs 9.3%±7.3% (14±13 mmol/mol), both p<0.001. Fifty-six adults (73% female, age 36±13 years, 16±13 years diabetes, HbA1c 7.8%±0.8% (62±9 mmol/mol)) transitioned from MDI to CSII. Mean HbA1c fell by 0.4%. GV from 1 year post-CSII commencement decreased significantly, HbA1c SD pre-CSII versus post-CSII 0.7%±0.5% (8±5 mmol/mol) vs 0.4%±0.4% (5±4 mmol/mol); p<0.001, and HbA1c CV 9.2%±5.5% (13±8 mmol/mol) vs 6.1%±3.9% (9±5 mmol/mol); p<0.001. Conclusions In clinical practice with T1DM adults relative to MDI, CSII therapy is associated with lower HbA1c GV