The hypothesis of cancer stem cells has been proposed to explain the therapeutic failure in a variety of cancers including lung cancers. Previously, we demonstrated acquisition of ...epithelial-mesenchymal transition, a feature highly reminiscent of cancer stem-like cells, in gefitinib-resistant A549 cells (A549/GR). Here, we show that A549/GR cells contain a high proportion of CXCR4+ cells that are responsible for having high potential of self-renewal activity in vitro and tumorigenicity in vivo. A549/GR cells exhibited strong sphere-forming activity and high CXCR4 expression and SDF-1α secretion compared with parent cells. Pharmacological inhibition (AMD3100) and/or siRNA transfection targeting CXCR4 significantly suppressed sphere-forming activity in A549 and A549/GR cells, and in various non-small cell lung cancer (NSCLC) cell lines. A549/GR cells showed enhanced Akt, mTOR and STAT3 (Y705) phosphorylation. Pharmacological inhibition of phosphatidyl inositol 3-kinase or transfection with wild-type PTEN suppressed phosphorylation of Akt, mTOR and STAT3 (Y705), sphere formation, and CXCR4 expression in A549/GR cells, whereas mutant PTEN enhanced these events. Inhibition of STAT3 by WP1066 or siSTAT3 significantly suppressed the sphere formation, but not CXCR4 expression, indicating that STAT3 is a downstream effector of CXCR4-mediated signaling. FACS-sorted CXCR4+ A549/GR cells formed many large spheres, had self-renewal capacity, demonstrated radiation resistance in vitro and exhibited stronger tumorigenic potential in vivo than CXCR4- cells. Lentiviral-transduction of CXCR4 enhanced sphere formation and tumorigenicity in H460 and A549 cells, whereas introduction of siCXCR4 suppressed these activities in A549/GR cells. Our data indicate that CXCR4+ NSCLC cells are strong candidates for tumorigenic stem-like cancer cells that maintain stemness through a CXCR4-medated STAT3 pathway and provide a potential therapeutic target for eliminating these malignant cells in NSCLC.
We compare coincident thermospheric neutral wind observations made by the Michelson Interferometer for Global High‐Resolution Thermospheric Imaging (MIGHTI) on the Ionospheric Connection Explorer ...(ICON) spacecraft, and four ground‐based specular meteor radars (SMRs). Using the green‐line MIGHTI channel, we analyze 1158 coincidences between Dec 2019 and May 2020 in the altitude range from 94 to 104 km where the observations overlap. We find that the two datasets are strongly correlated (r = 0.82) with a small mean difference (4.5 m/s). Although this agreement is good, an analysis of known error sources (e.g., shot noise, calibration errors, and analysis assumptions) can only account for about a quarter of the disagreement variance. The unexplained variance is 27.8% of the total signal variance and could be caused by unknown errors. However, based on an analysis of the spatial and temporal averaging of the two measurement modalities, we suggest that some of the disagreement is likely caused by temporal variability of the wind on scales ≲70 min. The observed magnitudes agree well during the night, but during the day, MIGHTI observes 16%–25% faster winds than the SMRs. This remains unresolved but is similar in certain ways to previous SMR‐satellite comparisons.
Plain Language Summary
Although Earth's atmosphere becomes less dense at high altitudes where it transitions to space, the wind speed grows faster, often exceeding 100 m/s (225 mph). One barrier to better predictions of conditions in the near‐Earth space environment is obtaining knowledge of the wind in the thermosphere, the uppermost layer of the atmosphere. Measurements of the thermospheric wind are difficult to make and historically sparse. ICON, a new NASA mission launched in October 2019, carries the MIGHTI instrument to measure the wind from 90 to 300 km altitude. In this study we compare the observations of MIGHTI to those of meteor radars, which measure the wind from the ground by analysis of radio waves reflected by meteor trails. The results indicate good agreement between the datasets when they measure the wind at the same time and place. Specifically, with 1158 coincidences over the first 6 months of the ICON mission, the correlation is 0.82 and the average difference is 4.5 m/s. This study is important because it validates the MIGHTI data, giving confidence for subsequent studies using its data. It also quantifies limits to the agreement between space‐based and ground‐based winds, which is useful information for future studies combining them.
Key Points
Coincident wind measurements by ICON‐MIGHTI and specular meteor radars are strongly correlated (r = 0.82)
The mean discrepancy between the datasets is 4.5 m/s, validating the MIGHTI v03 zero reference
The RMS discrepancy is 26 m/s, which is attributed to inherent data errors and variability on time scales ≲70 min
Purpose
We evaluated the generalizability and accuracy of the IBM® MarketScan® Health Risk Assessment (HRA) data to assess its suitability as supplement to linked claims data.
Methods
We identified ...adult private insurance enrollees in the IBM® MarketScan® Commercial Claims & Encounters (CC&E) and HRA databases between 2012 and 2017. In the claims data, for each enrollee, we sampled the first calendar year with continuous enrollment indicating full capture of claims data and extracted linked HRA survey data if available. We compared HRA participants and non‐participants considering demographics, prevalences of chronic conditions, and healthcare utilization. Including the subsample with HRA data only, we estimated the negative predictive value (NPV) of obesity and smoking reported in the HRA against diagnosis code in the claims data.
Results
Between 2012 and 2017, 2 693 444 and 31 450 000 of HRA and non‐HRA participants were included in the study, respectively. Chronic diseases were similarly distributed between the two populations, with hypertension and hyperlipidemia representing the highest prevalence difference (1.4%). The two samples showed similar healthcare utilization. The proportion of false‐negatives for obesity and smoking information when relying on the HRA data compared to patients with positive diagnosis based on claims data was low (<1%). Prevalence estimates of both variables were similar to national estimates.
Conclusion
Our findings suggest that the overall HRA population may represent the overall claims population and HRA provides certain data elements with satisfactory accuracy.
Numerous paleomagnetic studies attribute the magnetization preserved within Apollo samples to an ancient dynamo. However, other works propose that lunar rocks were instead magnetized by either ...transient impact‐related magnetic fields on the Moon or by the return spacecraft. To test whether lunar samples could have been magnetized during return to Earth, sample handling, or transport, we exposed lunar rocks to 5–10 mT fields for varying durations. We then determined how easily these magnetic overprints could be removed and how paleointensity estimates are affected by the overprints and their removal. We found that magnetic overprints were cleaned by alternating field (AF) demagnetization to ∼10–30 mT for nearly all samples and that acceptable paleointensities may be obtained from higher AF levels. Therefore, high coercivity (>30 mT) magnetizations observed within lunar rocks are generally not magnetic contamination and were initially acquired on the Moon.
Plain Language Summary
Scientists study magnetism preserved within rocks to understand the histories of magnetic fields on planets. However, exposure to strong magnetic fields such as those produced by spacecraft electronics or magnets can partially remagnetize rocks. Therefore, it is important to rule out magnetic contamination in samples prior to making inferences about the histories of natural magnetic fields generated by planets or by meteorite impacts. We conducted a series of experiments wherein we intentionally exposed various rocks from the Moon to strong magnetic fields to (a) see how easily magnetic contamination could be removed and (b) understand how the contamination and secondary effects related to its removal could skew our interpretation of ancient lunar magnetic field intensities. We found that, in nearly all cases, techniques commonly used by rock magnetism specialists were able to successfully remove magnetic contamination without sacrificing accuracy in determining the intensity of ancient lunar magnetic fields from magnetically uncontaminated portions of rocks. Therefore, we conclude that much of the magnetization observed in lunar rocks is natural in origin and was acquired on the Moon.
Key Points
Magnetic fields associated with spacecraft transit or certain laboratory procedures may impart lunar samples with magnetic overprints
We find such magnetic contamination can be successfully cleaned from nearly all samples, enabling reliable paleointensity determinations
The modern lunar paleointensity record reflects magnetization acquired on the Moon from ancient dynamo fields or impact‐related fields
First results are presented from the conjugate maneuvers performed by NASA's Ionospheric Connection Explorer (ICON) spacecraft. During each several‐minute maneuver, ICON crosses the magnetic equator, ...measuring the plasma drift at the ∼600‐km apex of a magnetic field line and the neutral wind profiles (∼90–300 km altitude) along both ends of that field line. The analysis utilizes 149 pairs of maneuvers separated by ∼24 hr but at nearly the same location and local time. Principal component regression reveals that 39 ± 7% and 24 ± 9% of the day‐to‐day variance in the daytime vertical and zonal drift, respectively, is attributable to conjugate neutral winds. The remaining variance is likely driven by external potentials from non‐conjugate winds and geomagnetic activity (median Kp 2−). Zonal winds at 100–113 km and >120 km altitude are the primary drivers of conjugate vertical and zonal drift variance, respectively. These observations can test vertical‐coupling mechanisms in whole‐atmosphere models.
Plain Language Summary
The plasma that composes the ionosphere can change dramatically from one day to the next, exhibiting significant changes in its height and density which are not well predicted by models. This variability can have adverse impacts on satellite‐based navigation and communication systems, limiting their performance and availability. One of the key parameters that controls daytime ionospheric conditions is the upward and downward motion of plasma above 200 km, which affects the lifetime of newly created plasma. The force that puts the plasma in motion is electromotive, generated by the motion of the atmosphere (i.e., the wind) around 100–150 km that pushes charged particles across magnetic field lines. NASA's Ionospheric Connection Explorer is the first mission to directly observe these electrical generators, one at each “footpoint” of the arched magnetic field lines that thread the ionosphere and generator region. The results show that just under half of the day‐to‐day changes in ionospheric motion can be explained by this local generator mechanism. The major controller is the east‐west winds, with north‐south winds having only a minor influence on this mechanism.
Key Points
The first data set of simultaneous plasma drift and magnetically conjugate neutral winds in both hemispheres is presented
The day‐to‐day changes in winds account for 39 ± 7% and 24 ± 9% of the conjugate vertical and zonal daytime drift variance, respectively
Vertical drift variance is mainly driven by zonal winds at 100–113 km, and zonal drift variance is mainly driven by zonal winds above 120 km
Increasing globalization has created tremendous opportunities and challenges for organizations and societies. Consequently, a broad range of information technologies to better support the ...collaboration of diverse, and increasingly distributed, sets of participants is ever more utilized. Arguably, the success of such technology-mediated collaboration is dependent upon the quality of each individual's contributions; however, although individuals' motivations to do their best could be significantly influenced by the design of a system's human-computer interface, this area has received little attention within the context of group collaboration environments. We fill this gap by integrating research from human-computer interaction, motivation, and technology-supported group work to theoretically derive mechanisms for increasing each individual's motivation within a collective setting. Specifically, we manipulate the interface of a computer-mediated idea generation system (a widely used collaboration tool) to enhance the system's motivational affordance, i.e., the system's properties that fulfill users' motivational needs. Results from two studies demonstrate that by embedding the theoretically derived mechanisms "providing feedback" and "designing for optimal challenge" into the collaboration environment, significant performance gains were realized. The results suggest that even slight manipulations of the human-computer interface can contribute significantly to the successful design of a wide variety of group collaboration environments.
Existing dynamic graph embedding-based outlier detection methods mainly focus on the evolution of graphs and ignore the similarities among them. To overcome this limitation for the effective ...detection of abnormal climatic events from meteorological time series, we proposed a dynamic graph embedding model based on graph proximity, called DynGPE. Climatic events are represented as a graph where each vertex indicates meteorological data and each edge indicates a spurious relationship between two meteorological time series that are not causally related. The graph proximity is described as the distance between two graphs. DynGPE can cluster similar climatic events in the embedding space. Abnormal climatic events are distant from most of the other events and can be detected using outlier detection methods. We conducted experiments by applying three outlier detection methods (i.e., isolation forest, local outlier factor, and box plot) to real meteorological data. The results showed that DynGPE achieves better results than the baseline by 44.3% on average in terms of the F-measure. Isolation forest provides the best performance and stability. It achieved higher results than the local outlier factor and box plot methods, namely, by 15.4% and 78.9% on average, respectively.
MicroRNAs (miRNAs) are short, non‐coding RNAs that regulate gene expression at the post‐transcriptional level, which can be measured in cells, tissues, and body fluids including plasma. Differences ...in miRNA expression levels suggest an epigenetic mechanism and changed expression levels are emerging as a novel biomarker for various diseases. We attempted to identify circulating miRNAs associated with susceptibility to systemic lupus erythematosus (SLE) in the Korean population and elucidate their significance for clinical phenotype. An expression profiling analysis using miRNA polymerase chain reaction (PCR) array was conducted with pooled miRNA from 10 patients with SLE and 10 healthy controls (HCs). Nine miRNAs were differentially expressed between the SLE and HC. To verify this, we performed quantitative PCR for various miRNA from SLE patients (n = 70) and HCs (n = 40). The hsa‐miR‐30e‐5p, hsa‐miR‐92a‐3p, and hsa‐miR‐223‐3p were significantly up‐regulated in plasma of SLE patients (P = 0.048, P = 0.039, and P = 0.046, respectively). Especially, the hsa‐miR‐223‐3p was significantly associated with oral ulcer (P < 0.001) and lupus anticoagulant (P = 0.031). Thus, plasma hsa‐miR‐30e‐5p, hsa‐miR‐92a‐3p, and hsa‐miR‐223‐3p may be promising novel biomarkers in the diagnosis and clinical manifestation of SLE.
In near‐Earth space, variations in thermospheric composition have important implications for thermosphere‐ionosphere coupling. The ratio of O to N2 is often measured using far‐UV airglow ...observations. Taking such airglow observations from space, looking below the Earth's limb allows for the total column of O and N2 in the ionosphere to be determined. While these observations have enabled many previous studies, determining the impact of nonmigrating tides on thermospheric composition has proved difficult, owing to a small contamination of the signal by recombination of ionospheric O+. New ICON observations of far‐UV are presented here, and their general characteristics are shown. Using these, along with other observations and a global circulation model, we show that during the morning hours and at latitudes away from the peak of the equatorial ionospheric anomaly, the impact of nonmigrating tides on thermospheric composition can be observed. During March–April 2020, the column O/N2 ratio was seen to vary by 3–4% of the zonal mean. By comparing the amplitude of the variation observed with that in the model, both the utility of these observations and a pathway to enable future studies is shown.
Plain Language Summary
At high altitude in the atmosphere, mixing of the gas via turbulence becomes less important, and mix of atmospheric species begins to vary with altitude, depending on the mass of the atom or molecule. At these altitudes, the composition of the atmosphere can vary greatly with location and time in a manner not seen in the lower levels of the atmosphere. This same high‐altitude region overlaps with the charged particle environment known as the Earth's ionosphere. How the atmosphere and ionosphere interact is in‐part determined by the composition of the atmosphere. Measuring this composition is therefore important and is done regularly using observations in the far‐ultraviolet. These reveal much of the compositional variation, but a small contaminating signal from the ionosphere has made detecting some small changes produced by waves in the atmosphere a challenge. Here, new observations in the far‐UV are introduced and their general properties shown. By selecting a specific location and time and utilizing supporting data and a global model, we are able to show the change in the composition produced by a certain class of wave in the atmosphere. This demonstrates the utility of these new observations and provides a pathway to futures studies.
Key Points
An initial overview of the Ionospheric Connection Explorer‐far‐ultraviolet sublimb observations and derived column O/N2 ratios is presented
In the morning, away from the equatorial ionosphere, the impact of nonmigrating tides on O/N2 is shown clearly for the first time
Comparison of the tidal signature with the TIEGCM highlights basic agreement, with possible discrepancy in tidal vertical wavelength
Detailed knowledge on the prevalence of asymptomatic cases of coronavirus disease 2019 (COVID-19) and the clinical characteristics of mild COVID-19 is essential for effective control of the COVID-19 ...pandemic. We determined the prevalence of asymptomatic cases of COVID-19 and characterized the symptoms of patients with mild COVID-19.
Study participants were recruited from a community facility designated for the isolation of patients without moderate-to-severe symptoms of COVID-19 in South Korea. The prevalence of asymptomatic patients at admission and the detailed symptoms of mild COVID-19 were evaluated through a questionnaire-based survey. Diagnosis of COVID-19 was confirmed by real-time RT-PCR.
Of the 213 individuals with COVID-19, 41 (19.2%) were asymptomatic until admission. Among the remaining patients with mild COVID-19, the most common symptom was cough (40.1%; 69/172), followed by hyposmia (39.5%; 68/172) and sputum (39.5%; 68/172). Of the 68 individuals with hyposmia, 61 (90%) had accompanying symptoms such as hypogeusia, nasal congestion or rhinorrhoea. Fever (>37.5°C) was only observed in 20 (11.6%) individuals.
As much as one-fifth of individuals with COVID-19 remained asymptomatic from exposure to admission. Hyposmia was quite frequent among individuals with mild COVID-19, but fever was not. Social distancing should be strongly implemented to prevent disease transmission from asymptomatic individuals or those with mild and inconspicuous symptoms.
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