Bootstrapping multiple systems estimates to account for model selection

Multiple systems estimation is a standard approach to quantifying hidden populations where data sources are based on lists of known cases. A typical modelling approach is to fit a Poisson loglinear model to the numbers of cases observed in each possible combination of the lists. It is necessary to decide which interaction parameters to include in the model, and information criterion approaches are often used for model selection. Difficulties in the context of multiple systems estimation may arise due to sparse or nil counts based on the intersection of lists, and care must be taken when information criterion approaches are used for model selection due to issues relating to the existence of estimates and identifiability of the model. Confidence intervals are often reported conditional on the model selected, providing an over-optimistic impression of the accuracy of the estimation. A bootstrap approach is a natural way to account for the model selection procedure. However, because the model selection step has to be carried out for every bootstrap replication, there may be a high or even prohibitive computational burden. We explore the merit of modifying the model selection procedure in the bootstrap to look only among a subset of models, chosen on the basis of their information criterion score on the original data. This provides large computational gains with little apparent effect on inference. Another model selection approach considered and investigated is a downhill search approach among models, possibly with multiple starting points.Comment: 21 pages, 5 figures, 6 table

Peroxisome Proliferator-Activated Receptor (PPAR): Balance for Survival in Parasitic Infections

Parasitic infections induce a magnitude of host responses. At the opposite ends of the spectrum are those that ensure the host's needs to eliminate the invaders and to minimize damage to its own tissues. This review analyzes how parasites would manipulate immunity by activating the immunosuppressive nuclear factor, peroxisome proliferator-activated receptors (PPARs) with type 2 cytokines and free fatty acids from arachidonic acid metabolism. PPARs limit the action of type 1 immunity, in which classically activated macrophages act through the production of proinflammatory signals, to spare the parasites. They also favor the development of alternately activated macrophages which control inflammation so the host would not be destroyed. Possibly, the nuclear factors hold a pivotal role in the establishment of chronic infection by delicately balancing the pro- and anti-inflammatory signaling mechanisms and their ligands may be used as combination therapeutics to limit host pathology

Multiple Systems Estimation for Sparse Capture Data: Inferential Challenges When There Are Nonoverlapping Lists

© 2020 American Statistical Association. Multiple systems estimation strategies have recently been applied to quantify hard-to-reach populations, particularly when estimating the number of victims of human trafficking and modern slavery. In such contexts, it is not uncommon to see sparse or even no overlap between some of the lists on which the estimates are based. These create difficulties in model fitting and selection, and we develop inference procedures to address these challenges. The approach is based on Poisson log-linear regression modeling. Issues investigated in detail include taking proper account of data sparsity in the estimation procedure, as well as the existence and identifiability of maximum likelihood estimates. A stepwise method for choosing the most suitable parameters is developed, together with a bootstrap approach to finding confidence intervals for the total population size. We apply the strategy to two empirical datasets of trafficking in US regions, and find that the approach results in stable, reasonable estimates. An accompanying R software implementation has been made publicly available. Supplementary materials for this article are available online

Effect of real-time computer-aided polyp detection system (ENDO-AID) on adenoma detection in endoscopists-in-training: a randomized trial

Background The effect of computer-aided polyp detection (CADe) on adenoma detection rate (ADR) among endoscopists-in-training remains unknown. Methods We performed a single-blind, parallel-group, randomized controlled trial in Hong Kong between April 2021 and July 2022 (NCT04838951). Eligible subjects undergoing screening/surveillance/diagnostic colonoscopies were randomized 1:1 to receive colonoscopies with CADe (ENDO-AID(OIP-1), Olympus Co., Japan) or not (control) during withdrawal. Procedures were performed by endoscopists-in-training with <500 procedures and <3 years’ experience. Randomization was stratified by patient age, sex, and endoscopist experience (beginner vs intermediate-level, <200 vs 200-500 procedures). Image enhancement and distal attachment devices were disallowed. Subjects with incomplete colonoscopies or inadequate bowel preparation were excluded. Treatment allocation was blinded to outcome assessors. The primary outcome was ADR. Secondary outcomes were ADR for different adenoma sizes and locations, mean number of adenomas, and non-neoplastic resection rate. Results 386 and 380 subjects were randomized to CADe and control groups, respectively. The overall ADR was significantly higher in CADe than control group (57.5% vs 44.5%, adjusted relative risk 1.41, 95%CI 1.17-1.72, p<0.001). The ADRs for <5mm (40.4% vs 25.0%) and 5-10mm adenomas (36.8% vs 29.2%) were higher in CADe group. The ADRs were higher in CADe group in both right (42.0% vs 30.8%) and left colon (34.5% vs 27.6%), but there was no significant difference in advanced ADR. The ADRs were higher in CADe group among beginners (60.0% vs 41.9%) and intermediate-level endoscopists (56.5% vs 45.5%). Mean number of adenomas (1.48 vs 0.86) and non-neoplastic resection rate were higher in CADe group (52.1% vs 35.0%). Conclusions Among endoscopists-in-training, the use of CADe during colonoscopies was associated with increased overall ADR. (ClinicalTrials.gov: NCT04838951

A Cross-Sectional Characterization of Insulin Resistance by Phenotype and Insulin Clamp in East Asian Americans with Type 1 and Type 2 Diabetes

Classic features of type 1 and type 2 diabetes may not apply in Asian Americans, due to shared absence of common HLA DR-DQ genotype, low prevalence of positive anti-islet antibodies and low BMI in both types of diabetes. Our objective was to characterize diabetic phenotypes in Asian Americans by clamp and clinical features.This was a cross-sectional study conducted in a referral center. Thirty East young Asian American adult volunteers (27.6±5.5 years) with type 1, type 2 diabetes or controls underwent hyperinsulinemic euglycemic clamp to assess insulin resistance and DEXA to assess adiposity.Gender, BMI, waist/hip ratio, leptin, LDL, anti-GAD, anti-IA2 antibodies and C-reactive protein were similar among three groups. Serum C-peptide, adiponectin, free fatty acid, HDL concentrations and truncal fat by DEXA, were different between diabetic groups. Glucose disposal rate by clamp was lowest in type 2 diabetes, followed by type 1 diabetes and controls (5.43±2.70, 7.62±2.59, 8.61±2.37 mg/min/kg, respectively, p = 0.001). Free fatty acid concentration universally plummeted during steady state of the clamp procedure regardless of diabetes types in all three groups. Adipocyte fatty acid binding protein in the entire cohort (r = -0.625, p = 0.04) and controls (r = -0.869, p = 0.046) correlated best with insulin resistance, independent of BMI.Type 2 diabetes in Asian Americans was associated with insulin resistance despite having low BMI as type 1 diabetes, suggesting a potential role for targeting insulin resistance apart from weight loss. Adipocyte fatty acid binding protein, strongly associated with insulin resistance, independent of adiposity in the young Asian American population, may potentially serve as a biomarker to identify at-risk individuals. Larger studies are needed to confirm this finding

Innovations and advances in instrumentation at the W. M. Keck Observatory

Since the start of operations in 1993, the twin 10 meter W. M. Keck Observatory telescopes have continued to maximize their scientific impact and to produce transformative discoveries that keep the observing community on the frontiers of astronomical research. Upgraded capabilities and new instrumentation are provided though collaborative partnerships with Caltech and UC instrument development teams. The observatory adapts and responds to the observers’ evolving needs as defined in the observatory’s strategic plan, periodically refreshed in collaboration with the science community. This paper summarizes the performance of recently commissioned infrastructure projects, technology upgrades, and new additions to the suite of instrumentation at the observatory. We will also provide a status of projects currently in the design or development phase, and since we need to keep our eye on the future, we mention projects in exploratory phases that originate from our strategic plan. Recently commissioned projects include telescope control system upgrades, OSIRIS spectrometer and imager upgrades, and deployments of the Keck Cosmic Web Imager (KCWI), the Near-Infrared Echellette Spectrometer (NIRES), and the Keck I Deployable Tertiary Mirror (KIDM3). Under development are upgrades to the NIRSPEC instrument and adaptive optics (AO) system. Major instrumentation in design phases include the Keck Cosmic Reionization Mapper and the Keck Planet Finder. Future instrumentation studies and proposals underway include a Ground Layer Adaptive Optics system, NIRC2 upgrades, the energy sensitive instrument KRAKENS, an integral field spectrograph LIGER, and a laser tomography AO upgrade. Last, we briefly discuss recovering MOSFIRE and its return to science operations

Machine-Learning Methods Enable Exhaustive Searches for Active Bimetallic Facets and Reveal Active Site Motifs for CO_2 Reduction

Bimetallic catalysts are promising for the most difficult thermal and electrochemical reactions, but modeling the many diverse active sites on polycrystalline samples is an open challenge. We present a general framework for addressing this complexity in a systematic and predictive fashion. Active sites for every stable low-index facet of a bimetallic crystal are enumerated and cataloged, yielding hundreds of possible active sites. The activity of these sites is explored in parallel using a neural-network-based surrogate model to share information between the many density functional theory (DFT) relaxations, resulting in activity estimates with an order of magnitude fewer explicit DFT calculations. Sites with interesting activity were found and provide targets for follow-up calculations. This process was applied to the electrochemical reduction of CO_2 on nickel gallium bimetallics and indicated that most facets had similar activity to Ni surfaces, but a few exposed Ni sites with a very favorable on-top CO configuration. This motif emerged naturally from the predictive modeling and represents a class of intermetallic CO_2 reduction catalysts. These sites rationalize recent experimental reports of nickel gallium activity and why previous materials screens missed this exciting material. Most importantly these methods suggest that bimetallic catalysts will be discovered by studying facet reactivity and diversity of active sites more systematically

Endometrial regenerative cells: A novel stem cell population

Angiogenesis is a critical component of the proliferative endometrial phase of the menstrual cycle. Thus, we hypothesized that a stem cell-like population exist and can be isolated from menstrual blood. Mononuclear cells collected from the menstrual blood contained a subpopulation of adherent cells which could be maintained in tissue culture for >68 doublings and retained expression of the markers CD9, CD29, CD41a, CD44, CD59, CD73, CD90 and CD105, without karyotypic abnormalities. Proliferative rate of the cells was significantly higher than control umbilical cord derived mesenchymal stem cells, with doubling occurring every 19.4 hours. These cells, which we termed "Endometrial Regenerative Cells" (ERC) were capable of differentiating into 9 lineages: cardiomyocytic, respiratory epithelial, neurocytic, myocytic, endothelial, pancreatic, hepatic, adipocytic, and osteogenic. Additionally, ERC produced MMP3, MMP10, GM-CSF, angiopoietin-2 and PDGF-BB at 10–100,000 fold higher levels than two control cord blood derived mesenchymal stem cell lines. Given the ease of extraction and pluripotency of this cell population, we propose ERC as a novel alternative to current stem cells sources