Ultraparamagnetic cells formed through intracellular oxidation and chelation of paramagnetic iron

Making cells magnetic is a long‐standing goal of chemical biology, aiming to enable the separation of cells from complex biological samples and their visualization in vivo using magnetic resonance imaging (MRI). Previous efforts towards this goal, focused on engineering cells to biomineralize superparamagnetic or ferromagnetic iron oxides, have been largely unsuccessful due to the stringent required chemical conditions. Here, we introduce an alternative approach to making cells magnetic, focused on biochemically maximizing cellular paramagnetism. We show that a novel genetic construct combining the functions of ferroxidation and iron chelation enables engineered bacterial cells to accumulate iron in “ultraparamagnetic” macromolecular complexes, allowing these cells to be trapped with magnetic fields and imaged with MRI in vitro and in vivo. We characterize the properties of these cells and complexes using magnetometry, nuclear magnetic resonance, biochemical assays, and computational modeling to elucidate the unique mechanisms and capabilities of this paramagnetic concept

Comments on the Mechanism of Aging of Antimony Doped Tin Oxide Based Electrochromic Devices

Electrochromic effects of antimony doped tin oxide (ATO) nanoparticles are investigated to probe device yellowing (degradation). Voltage vs contrast ratio curves exhibit hysteresis, i.e., image-sticking phenomena due to irreversible charge insertion. X-ray, impedance and optical b* studies suggest that the yellowing/charge trapping is nanoparticle size-dependent with 4 nm size particles exhibiting the least yellowing. Yellowing results in increased impedances of electrode–electrolyte interface and electrode corrosion. Plausible sources of discoloration are formation of insulating complex alkali oxide film, carrier inversion (n-to-p type) through electrochemical Li doping, redeposition of the corroded electrode material and perhaps residual concentration of charge-transfer species

Ultraparamagnetic cells formed through intracellular oxidation and chelation of paramagnetic iron

Making cells magnetic is a long‐standing goal of chemical biology, aiming to enable the separation of cells from complex biological samples and their visualization in vivo using magnetic resonance imaging (MRI). Previous efforts towards this goal, focused on engineering cells to biomineralize superparamagnetic or ferromagnetic iron oxides, have been largely unsuccessful due to the stringent required chemical conditions. Here, we introduce an alternative approach to making cells magnetic, focused on biochemically maximizing cellular paramagnetism. We show that a novel genetic construct combining the functions of ferroxidation and iron chelation enables engineered bacterial cells to accumulate iron in “ultraparamagnetic” macromolecular complexes, allowing these cells to be trapped with magnetic fields and imaged with MRI in vitro and in vivo. We characterize the properties of these cells and complexes using magnetometry, nuclear magnetic resonance, biochemical assays, and computational modeling to elucidate the unique mechanisms and capabilities of this paramagnetic concept

Peregrine: A Pattern-Aware Graph Mining System

Graph mining workloads aim to extract structural properties of a graph by exploring its subgraph structures. General purpose graph mining systems provide a generic runtime to explore subgraph structures of interest with the help of user-defined functions that guide the overall exploration process. However, the state-of-the-art graph mining systems remain largely oblivious to the shape (or pattern) of the subgraphs that they mine. This causes them to: (a) explore unnecessary subgraphs; (b) perform expensive computations on the explored subgraphs; and, (c) hold intermediate partial subgraphs in memory; all of which affect their overall performance. Furthermore, their programming models are often tied to their underlying exploration strategies, which makes it difficult for domain users to express complex mining tasks. In this paper, we develop Peregrine, a pattern-aware graph mining system that directly explores the subgraphs of interest while avoiding exploration of unnecessary subgraphs, and simultaneously bypassing expensive computations throughout the mining process. We design a pattern-based programming model that treats "graph patterns" as first class constructs and enables Peregrine to extract the semantics of patterns, which it uses to guide its exploration. Our evaluation shows that Peregrine outperforms state-of-the-art distributed and single machine graph mining systems, and scales to complex mining tasks on larger graphs, while retaining simplicity and expressivity with its "pattern-first" programming approach.Comment: This is the full version of the paper appearing in the European Conference on Computer Systems (EuroSys), 202

BOB CAT: a Large-Scale Review and Delphi Consensus for Management of Barrett’s Esophagus With No Dysplasia, Indefinite for, or Low-Grade Dysplasia

OBJECTIVES: Barrett’s esophagus (BE) is a common premalignant lesion for which surveillance is recommended. This strategy is limited by considerable variations in clinical practice. We conducted an international, multidisciplinary, systematic search and evidence-based review of BE and provided consensus recommendations for clinical use in patients with nondysplastic, indefinite, and low-grade dysplasia (LGD). METHODS: We defined the scope, proposed statements, and searched electronic databases, yielding 20,558 publications that were screened, selected online, and formed the evidence base. We used a Delphi consensus process, with an 80% agreement threshold, using GRADE (Grading of Recommendations Assessment, Development and Evaluation) to categorize the quality of evidence and strength of recommendations. RESULTS: In total, 80% of respondents agreed with 55 of 127 statements in the final voting rounds. Population endoscopic screening is not recommended and screening should target only very high-risk cases of males aged over 60 years with chronic uncontrolled reflux. A new international definition of BE was agreed upon. For any degree of dysplasia, at least two specialist gastrointestinal (GI) pathologists are required. Risk factors for cancer include male gender, length of BE, and central obesity. Endoscopic resection should be used for visible, nodular areas. Surveillance is not recommended for <5 years of life expectancy. Management strategies for indefinite dysplasia (IND) and LGD were identified, including a de-escalation strategy for lower-risk patients and escalation to intervention with follow-up for higher-risk patients. CONCLUSIONS: In this uniquely large consensus process in gastroenterology, we made key clinical recommendations for the escalation/de-escalation of BE in clinical practice. We made strong recommendations for the prioritization of future research

Ionization yield measurement in a germanium CDMSlite detector using photo-neutron sources

Two photo-neutron sources, $^{88}$Y$^{9}$Be and $^{124}$Sb$^{9}$Be, have been used to investigate the ionization yield of nuclear recoils in the CDMSlite germanium detectors by the SuperCDMS collaboration. This work evaluates the yield for nuclear recoil energies between 1 keV and 7 keV at a temperature of $\sim$ 50 mK. We use a Geant4 simulation to model the neutron spectrum assuming a charge yield model that is a generalization of the standard Lindhard model and consists of two energy dependent parameters. We perform a likelihood analysis using the simulated neutron spectrum, modeled background, and experimental data to obtain the best fit values of the yield model. The ionization yield between recoil energies of 1 keV and 7 keV is shown to be significantly lower than predicted by the standard Lindhard model for germanium. There is a general lack of agreement among different experiments using a variety of techniques studying the low-energy range of the nuclear recoil yield, which is most critical for interpretation of direct dark matter searches. This suggests complexity in the physical process that many direct detection experiments use to model their primary signal detection mechanism and highlights the need for further studies to clarify underlying systematic effects that have not been well understood up to this point

Search for low-mass dark matter via bremsstrahlung radiation and the Migdal effect in SuperCDMS

We present a new analysis of previously published SuperCDMS data using a profile likelihood framework to search for sub-GeV dark matter (DM) particles through two inelastic scattering channels: bremsstrahlung radiation and the Migdal effect. By considering these possible inelastic scattering channels, experimental sensitivity can be extended to DM masses that are undetectable through the DM-nucleon elastic scattering channel, given the energy threshold of current experiments. We exclude DM masses down to 220  MeV/c2 at 2.7×10−30  cm2 via the bremsstrahlung channel. The Migdal channel search provides overall considerably more stringent limits and excludes DM masses down to 30  MeV/c2 at 5.0×10−30  cm2