Comparing Machine Learning Methods for Estimating Heterogeneous Treatment Effects by Combining Data from Multiple Randomized Controlled Trials

Individualized treatment decisions can improve health outcomes, but using data to make these decisions in a reliable, precise, and generalizable way is challenging with a single dataset. Leveraging multiple randomized controlled trials allows for the combination of datasets with unconfounded treatment assignment to improve the power to estimate heterogeneous treatment effects. This paper discusses several non-parametric approaches for estimating heterogeneous treatment effects using data from multiple trials. We extend single-study methods to a scenario with multiple trials and explore their performance through a simulation study, with data generation scenarios that have differing levels of cross-trial heterogeneity. The simulations demonstrate that methods that directly allow for heterogeneity of the treatment effect across trials perform better than methods that do not, and that the choice of single-study method matters based on the functional form of the treatment effect. Finally, we discuss which methods perform well in each setting and then apply them to four randomized controlled trials to examine effect heterogeneity of treatments for major depressive disorder

GRAPHENE BASED FLEXIBLE GAS SENSORS

<p>Graphene is a novel carbon material with great promise for a range of applications due to its electronic and mechanical properties. Its two-dimensional nature translates to a high sensitivity to surface chemical interactions thereby making it an ideal platform for sensors. Graphene's electronic properties are not degraded due to mechanical flexing or strain (Kim, K. S., et al. nature 07719, 2009) offering another advantage for flexible sensors integrated into numerous systems including fabrics, etc. </p><p>We have demonstrated a graphene NO2 sensor on a solid substrate (100nm SiO2/heavily doped silicon). Three different methods were used to synthesize graphene and the sensor fabrication process was optimized accordingly. Water is used as a controllable p-type dopant in graphene to study the relationship between doping and graphene's response to NO2. Experimental results show that interface water between graphene and the supporting SiO2 substrate induces higher p-doping in graphene, leading to a higher sensitivity to NO2, consistent with theoretical predications (Zhang, Y. et al., Nanotechnology 20(2009) 185504). </p><p>We have also demonstrated a flexible and stretchable graphene-based sensor. Few layer graphene, grown on a Ni substrate, is etched and transferred to a highly stretchable polymer substrate (VHB from 3M) with preloaded stress, followed by metal contact formation to construct a flexible, stretchable sensor. With up to 500% deformation caused by compressive stress, graphene still shows stable electrical response to NO2. Our results suggest that higher compressive stress results in smaller sheet resistance and higher sensitivity to NO2. </p><p>A possible molecular detection sensor utilizing Surface Enhanced Raman Spectrum (SERS) based on a graphene/gallium nanoparticles platform is also studied. By correlating the enhancement of the graphene Raman modes with metal coverage, we propose that the Ga transfers electrons to the graphene creating local regions of enhanced electron concentration modifying the Raman scattering in graphene.</p>Dissertatio

Experimental and theoretical study on the extraction of keratin from human hair using protic ionic liquids

Keratin, the naturally derived biomaterials have been developed and widely applied in many different fields. Among the resources containing keratin, human hair is one of the most abundant natural fibers rich in keratin and one of the most abundant waste materials produced by humans. It is critical for both value-added human hair utilization and environmental protection if suitable solvents for the dissolution and regeneration of the keratin were developed. Ionic liquids (ILs) have been evidenced to be the green solvents to extract keratin from waste human hair. In this work, five novel Protic ILs were designed and synthesized in one step with inexpensive raw materials under mild conditions. The effect of different anions and cations, temperature, and water content on the dissolution ability of Protic ILs for human hair was investigated in depth. The best IL [MEA]HCOO with high solubilization capacity (9 h, 130 degrees C) for human hair was finally obtained by considering the time required for complete hair dissolution and the properties of regenerated keratin. The results of FTIR, XRD, and TGA showed that the a-helix structure of regenerated keratin was not destroyed. The recycling result indicates that the dissolution ability of [MEA]HCOO for human hair kept stable after 5 times recovery. Furthermore, the density functional theory (DFT) calculations and independent gradient model (IGM) analysis uncover the dissolution of human hair by ILs through synergistic interaction between the cations and anions of ILs. (c) 2022 Elsevier B.V. All rights reserved

Experimental and theoretical study on the extraction of keratin from human hair using protic ionic liquids

Keratin, the naturally derived biomaterials have been developed and widely applied in many different fields. Among the resources containing keratin, human hair is one of the most abundant natural fibers rich in keratin and one of the most abundant waste materials produced by humans. It is critical for both value-added human hair utilization and environmental protection if suitable solvents for the dissolution and regeneration of the keratin were developed. Ionic liquids (ILs) have been evidenced to be the green solvents to extract keratin from waste human hair. In this work, five novel Protic ILs were designed and synthesized in one step with inexpensive raw materials under mild conditions. The effect of different anions and cations, temperature, and water content on the dissolution ability of Protic ILs for human hair was investigated in depth. The best IL [MEA]HCOO with high solubilization capacity (9 h, 130 degrees C) for human hair was finally obtained by considering the time required for complete hair dissolution and the properties of regenerated keratin. The results of FTIR, XRD, and TGA showed that the a-helix structure of regenerated keratin was not destroyed. The recycling result indicates that the dissolution ability of [MEA]HCOO for human hair kept stable after 5 times recovery. Furthermore, the density functional theory (DFT) calculations and independent gradient model (IGM) analysis uncover the dissolution of human hair by ILs through synergistic interaction between the cations and anions of ILs. (c) 2022 Elsevier B.V. All rights reserved

Implementation and Continuous Monitoring of an Electronic Health Record Embedded Readmissions Clinical Decision Support Tool

Unplanned hospital readmissions represent a significant health care value problem with high costs and poor quality of care. A significant percentage of readmissions could be prevented if clinical inpatient teams were better able to predict which patients were at higher risk for readmission. Many of the current clinical decision support models that predict readmissions are not configured to integrate closely with the electronic health record or alert providers in real-time prior to discharge about a patient&rsquo;s risk for readmission. We report on the implementation and monitoring of the Epic electronic health record&mdash;&ldquo;Unplanned readmission model version 1&rdquo;&mdash;over 2 years from 1/1/2018&ndash;12/31/2019. For patients discharged during this time, the predictive capability to discern high risk discharges was reflected in an AUC/C-statistic at our three hospitals of 0.716&ndash;0.760 for all patients and 0.676&ndash;0.695 for general medicine patients. The model had a positive predictive value ranging from 0.217&ndash;0.248 for all patients. We also present our methods in monitoring the model over time for trend changes, as well as common readmissions reduction strategies triggered by the score

Malnutrition and immune cell subsets in children undergoing kidney transplantation.

BACKGROUND: Malnutrition, including obesity and undernutrition, among children is increasing in prevalence and is common among children on renal replacement therapy. The effect of malnutrition on the pre-transplant immune system and how the pediatric immune system responds to the insult of both immunosuppression and allotransplantation is unknown. We examined the relationship of nutritional status with post-transplant outcomes and characterized the peripheral immune cell phenotypes of children from the Immune Development of Pediatric Transplant (IMPACT) study. METHODS: Ninety-eight patients from the IMPACT study were classified as having obesity, undernutrition, or normal nutrition-based pre-transplant measurements. Incidence of infectious and alloimmune outcomes at 1-year post-transplantation was compared between nutritional groups using Grays test and Fine-Gray subdistribution hazards model. Event-free survival was estimated by Kaplan-Meier method and compared between groups. Differences in immune cell subsets between nutritional groups over time were determined using generalized estimating equations accounting for the correlation between repeated measurements. RESULTS: We did not observe that nutritional status was associated with infectious or alloimmune events or event-free survival post-transplant. We demonstrated that children with obesity had distinct T-and B-cell signatures relative to those with undernutrition and normal nutrition, even when controlling for immunosuppression. Children with obesity had a lower frequency of CD8 Tnaive cells 9-month post-transplant (p &lt; .001), a higher frequency of CD4 CD57 + PD1- T cells, and lower frequencies of CD57-PD1+ CD8 and CD57-PD1- CD8 T cells at 12-month transplant (p &lt; .05 for all). CONCLUSIONS: Children with obesity have distinct immunophenotypes that may influence the tailoring of immunosuppression

Relationship between antithymocyte globulin, T cell phenotypes, and clinical outcomes in pediatric kidney transplantation

Depletional induction using antithymocyte globulin (ATG) reduces rates of acute rejection in adult kidney transplant recipients, yet little is known about its effects in children. Using a longitudinal cohort of 103 patients in the Immune Development in Pediatric Transplant (IMPACT) study, we compared T cell phenotypes after ATG or non-ATG induction. We examined the effects of ATG on the early clinical outcomes of alloimmune events (development of de novo donor specific antibody and/or biopsy proven rejection) and infection events (viremia/viral infections). Long-term patient and graft outcomes were examined using the Scientific Registry of Transplant Recipients. After ATG induction, although absolute counts of CD4 and CD8 T cells were lower, patients had higher percentages of CD4 and CD8 memory T cells with a concomitant decrease in frequency of naïve T cells compared to non-ATG induction. In adjusted and unadjusted models, ATG induction was associated with increased early event-free survival, with no difference in long-term patient or allograft survival. Decreased CD4+ naïve and increased CD4+ effector memory T cell frequencies were associated with improved clinical outcomes. Though immunologic parameters are drastically altered with ATG induction, long-term clinical benefits remain unclear in pediatric patients

Identification of tyrosine-9 of MAVS as critical target for inducible phosphorylation that determines activation.

BACKGROUND: Innate immunity to viruses involves receptors such as RIG-I, which senses viral RNA and triggers an IFN-β signaling pathway involving the outer mitochondrial membrane protein MAVS. However, the functional status of MAVS phosphorylation remains elusive. METHODOLOGY/PRINCIPAL FINDINGS: Here we demonstrate for the first time that MAVS undergoes extensive tyrosine phosphorylation upon viral infection, indicating that MAVS phosphorylation might play an important role in MAVS function. A tyrosine-scanning mutational analysis revealed that MAVS tyrosine-9 (Y9) is a phosphorylation site that is required for IFN-β signaling. Indeed, MAVS Y9F mutation severely impaired TRAF3/TRAF6 recruitment and displayed decreased tyrosine phosphorylation in response to VSV infection compared to wild type MAVS. Functionally, MAVS Y9 phosphorylation contributed to MAVS antiviral function without interfering with its apoptosis property. CONCLUSIONS/SIGNIFICANCE: These experiments identify a novel residue of MAVS that is crucially involved in the recruitment of TRAF3/TRAF6 and in downstream propagation of MAVS signaling