Design and testing of sorbents for CO2 separation of post-combustion and natural gas sweetening applications

In post-combustion processes, sorbents with both high capacity and selectivity are required for reducing the cost of carbon capture. Although physisorbents have the advantage of low energy consumption for regeneration, it remains a challenge to obtain both high capacity and sufficient CO2/N2 selectivity at the same time. A novel N-doped hierarchical carbon has been developed, which exhibits record-high Henry’s law CO2/N2 selectivity among physisorptive carbons while having a high CO2 adsorption capacity. Specifically, the synthesis involves the rational design of a modified pyrrole molecule that can co-assemble with the soft Pluronic template via hydrogen bonding and electrostatic interactions to give rise to mesopores followed by carbonization. The low-temperature carbonization and activation processes allow for the development of ultra-small pores (d2 affinity. Furthermore, the described work provides a strategy to initiate the development of rationally-designed porous conjugated polymer structures and carbon-based materials for various potential applications. In addition to post-combustion capture, natural gas sweetening is another topic of interest. Natural gas, having the lowest carbon intensity compared to coal and petroleum, is projected to increase in production and consumption in the coming decades. However, a drawback associated with natural gas is that it contains considerable amounts of CO2 at the recovery well, making on-site CO2 capture necessary. Solid sorbents are advantageous over traditional amine scrubbing due to their relatively low regeneration energies and non-corrosive nature. However, it remains a challenge to improve the sorbent’s CO2 capacity at elevated pressures relevant to natural gas purification. A series of porous carbons have been developed, which were derived from an intrinsic 3D hierarchical nanostructured polymer hydrogel, with simple and effective tunability over the pore size distribution. The optimized surface area reached a record-high of 4196 m2 g-1 among carbon-based materials. This high surface area along with the abundant micro/narrow mesopores (1.94 cm3 g-1 with d \u3c 4 nm) results in a record-high CO2 capacity (28.3 mmol g-1 at 25 °C and 30 bar) among carbons. This carbon also showed reasonable CO2/CH4 selectivity and excellent cyclability. In addition, this work for the first time combines experimental studies with first-principle molecular simulations for high-pressure CO2 adsorption on porous sorbents. It was found that at elevated pressures, the CO2 density in the adsorbed phase is significantly enhanced in the micro- and narrow mesopores with quantitative values provided for CO2 density. Furthermore, surface nitrogen functionalities have a trivial contribution to the CO2 uptake at high pressures. These findings emphasize the importance of being able to tune a sorbent’s pore size to achieve high CO2 uptake. Thus, the simulation studies help in our understanding of our sorbent’s superior performance as well as provides useful insight into future sorbent development

Accurate detection of spontaneous seizures using a generalized linear model with external validation

Objective Seizure detection is a major facet of electroencephalography (EEG) analysis in neurocritical care, epilepsy diagnosis and management, and the instantiation of novel therapies such as closed-loop stimulation or optogenetic control of seizures. It is also of increased importance in high-throughput, robust, and reproducible pre-clinical research. However, seizure detectors are not widely relied upon in either clinical or research settings due to limited validation. In this study, we create a high-performance seizure-detection approach, validated in multiple data sets, with the intention that such a system could be available to users for multiple purposes. Methods We introduce a generalized linear model trained on 141 EEG signal features for classification of seizures in continuous EEG for two data sets. In the first (Focal Epilepsy) data set consisting of 16 rats with focal epilepsy, we collected 1012 spontaneous seizures over 3 months of 24/7 recording. We trained a generalized linear model on the 141 features representing 20 feature classes, including univariate and multivariate, linear and nonlinear, time, and frequency domains. We tested performance on multiple hold-out test data sets. We then used the trained model in a second (Multifocal Epilepsy) data set consisting of 96 rats with 2883 spontaneous multifocal seizures. Results From the Focal Epilepsy data set, we built a pooled classifier with an Area Under the Receiver Operating Characteristic (AUROC) of 0.995 and leave-one-out classifiers with an AUROC of 0.962. We validated our method within the independently constructed Multifocal Epilepsy data set, resulting in a pooled AUROC of 0.963. We separately validated a model trained exclusively on the Focal Epilepsy data set and tested on the held-out Multifocal Epilepsy data set with an AUROC of 0.890. Latency to detection was under 5 seconds for over 80% of seizures and under 12 seconds for over 99% of seizures. Significance This method achieves the highest performance published for seizure detection on multiple independent data sets. This method of seizure detection can be applied to automated EEG analysis pipelines as well as closed loop interventional approaches, and can be especially useful in the setting of research using animals in which there is an increased need for standardization and high-throughput analysis of large number of seizures

Genetic mechanisms of critical illness in COVID-19.

Host-mediated lung inflammation is present1, and drives mortality2, in the critical illness caused by coronavirus disease 2019 (COVID-19). Host genetic variants associated with critical illness may identify mechanistic targets for therapeutic development3. Here we report the results of the GenOMICC (Genetics Of Mortality In Critical Care) genome-wide association study in 2,244 critically ill patients with COVID-19 from 208 UK intensive care units. We have identified and replicated the following new genome-wide significant associations: on chromosome 12q24.13 (rs10735079, P = 1.65 × 10-8) in a gene cluster that encodes antiviral restriction enzyme activators (OAS1, OAS2 and OAS3); on chromosome 19p13.2 (rs74956615, P = 2.3 × 10-8) near the gene that encodes tyrosine kinase 2 (TYK2); on chromosome 19p13.3 (rs2109069, P = 3.98 ×  10-12) within the gene that encodes dipeptidyl peptidase 9 (DPP9); and on chromosome 21q22.1 (rs2236757, P = 4.99 × 10-8) in the interferon receptor gene IFNAR2. We identified potential targets for repurposing of licensed medications: using Mendelian randomization, we found evidence that low expression of IFNAR2, or high expression of TYK2, are associated with life-threatening disease; and transcriptome-wide association in lung tissue revealed that high expression of the monocyte-macrophage chemotactic receptor CCR2 is associated with severe COVID-19. Our results identify robust genetic signals relating to key host antiviral defence mechanisms and mediators of inflammatory organ damage in COVID-19. Both mechanisms may be amenable to targeted treatment with existing drugs. However, large-scale randomized clinical trials will be essential before any change to clinical practice

The Institute of Medical and Biological Engineering Knee Dataset

This data collection contains all MR and CT images collected on cadaveric knees, as well as corresponding outcomes of computational and experimental preclinical models developed to test existing and emerging knee therapies (ethics REC 18/EM/0224)

Are More Alternatives Better for Decision-Makers? A Note on the Role of Decision Cost

While the traditional economic wisdom believes that an individual will become better off by being given a larger opportunity set to choose from, in this paper we question this belief and build a formal theoretical model that introduces decision costs into the rational decision process. We show, under some reasonable conditions, that a larger feasible set may actually lower an individual’s level of satisfaction. This provides a solid economic underpinning for the Simon prediction. Copyright Springer 2005bounded rationality, considered subset, decision cost, D11, D83,

Community recommendations on biobank governance: Results from a deliberative community engagement in California

<div><p>United States-based biorepositories are on the cusp of substantial change in regulatory oversight at the same time that they are increasingly including samples and data from large populations, e.g. all patients in healthcare system. It is appropriate to engage stakeholders from these populations in new governance arrangements. We sought to describe community recommendations for biorepository governance and oversight using deliberative community engagement (DCE), a qualitative research method designed to elicit lay perspectives on complex technical issues. We asked for stakeholders to provide input on governance of large biorepositories at the University of California (UC), a public university. We defined state residents as stakeholders and recruited residents from two large metropolitan areas, Los Angeles (LA) and San Francisco (SF). In LA, we recruited English and Spanish speakers; in SF the DCE was conducted in English only. We recruited individuals who had completed the 2009 California Health Interview Survey and were willing to be re-contacted for future studies. Using stratified random sampling (by age, education, race/ethnicity), we contacted 162 potential deliberants of whom 53 agreed to participate and 51 completed the 4-day DCE in June (LA) and September-October (SF), 2013. Each DCE included discussion among deliberants facilitated by a trained staff and simultaneously-translated in LA. Deliberants also received a briefing book describing biorepository operations and regulation. During the final day of the DCE, deliberants voted on governance and oversight recommendations using an audience response system. This paper describes 23 recommendations (of 57 total) that address issues including: educating the public, sharing samples broadly, monitoring researcher behavior, using informative consent procedures, and involving community members in a transparent process of biobank governance. This project demonstrates the feasibility of obtaining meaningful input on biorepository governance from diverse lay stakeholders. Such input should be considered as research institutions respond to changes in biorepository regulation.</p></div