This study investigated long-term interannual changes in summer circulation and hydrology in the East China Sea (ECS) by performing 35-year high-resolution ocean model simulation from 1981 to 2015. The sea surface temperature (SST) warming trend was considerably weaker in summer than in winter. To the east of the Yangtze Estuary, the interannual variation of SST in summer was mainly dominated by horizontal advection associated with variations in the Taiwan warm current and heat flux in the offshore region north of the Yangtze Estuary. Baroclinic circulation during summer played a crucial role in subsurface mixing. Near the surface, the significant atmospheric wind mode (EOF1) and Kuroshio mode (EOF2) dominate interannual variations in ocean circulation. In the subsurface, local wind around the Tsushima Strait dominated the interannual ocean variation. Anomalous northeasterly winds induced a southwestward pressure gradient due to topographical confinement. These anomalies propagated to the south along the continental shelf through topographic Rossby waves. This study identified two types of anomalous features based on combinations of surface and subsurface EOFs. The combination represents an in-phase contribution between wind and Kuroshio forcings and between the surface and subsurface circulation that enhances the hydrological variability in the ECS. The implication on the relevant biogeochemical and ecological studies in the East China Sea is also very crucial at the interannual time scale.

This study uses a coupled atmosphere-ocean model with different numerical settings to investigate the mean and eddy momentum transfer processes responsible for Typhoon Muifa's (2011) early rapid intensification (RI). Three experiments are conducted. Two use the coupled model with a horizontal resolution of either 1 km (HRL) or 3 km (LRL). The third (NoTCFB) is the same as LRL but excludes tropical cyclone (TC)-induced sea-surface temperature (SST) cooling. HRL reasonably reproduces Muifa's intensity during its rapid intensification and weakening periods. The azimuthal mean tangential and radial momentum budgets are analysed before the RI rates diverge between HRL and LRL. Results show that the dominant processes responsible for Muifa's intensification are different in HRL and LRL. For HRL, the net eddy effect intensifies the storm's circulation and contracts the eyewall during early RI, and it dominates the net mean-flow effect inside the radius of maximum wind (RMW), except near the surface and between 2 and 5 km close to the RMW. In contrast, the mean and eddy effects in LRL almost cancel inside the RMW, while the mean-flow effects dominate and intensify tangential winds outside. Without TC-induced SST cooling, Muifa in NoTCFB reaches a similar storm intensity as in HRL but its rapid weakening rate is substantially underestimated. The dominant mechanisms for tangential wind intensification in NoTCFB are similar to those in LRL, but their magnitudes are larger, implying a misrepresentation of the dominant momentum transfer processes in NoTCFB during RI. For the radial momentum budget analysis, the dominant processes are similar among the three experiments except for some differences in their locations and strengths.

OBJECTIVE: The year 2020 was predominated by the coronavirus disease 2019 (COVID-19) pandemic. The objective of this article is to review the areas in which clinical information systems (CIS) can be and have been utilized to support and enhance the response of healthcare systems to pandemics, focusing on COVID-19. METHODS: PubMed/MEDLINE, Google Scholar, the tables of contents of major informatics journals, and the bibliographies of articles were searched for studies pertaining to CIS, pandemics, and COVID-19 through October 2020. The most informative and detailed studies were highlighted, while many others were referenced. RESULTS: CIS were heavily relied upon by health systems and governmental agencies worldwide in response to COVID-19. Technology-based screening tools were developed to assist rapid case identification and appropriate triaging. Clinical care was supported by utilizing the electronic health record (EHR) to onboard frontline providers to new protocols, offer clinical decision support, and improve systems for diagnostic testing. Telehealth became the most rapidly adopted medical trend in recent history and an essential strategy for allowing safe and effective access to medical care. Artificial intelligence and machine learning algorithms were developed to enhance screening, diagnostic imaging, and predictive analytics - though evidence of improved outcomes remains limited. Geographic information systems and big data enabled real-time dashboards vital for epidemic monitoring, hospital preparedness strategies, and health policy decision making. Digital contact tracing systems were implemented to assist a labor-intensive task with the aim of curbing transmission. Large scale data sharing, effective health information exchange, and interoperability of EHRs remain challenges for the informatics community with immense clinical and academic potential. CIS must be used in combination with engaged stakeholders and operational change management in order to meaningfully improve patient outcomes. CONCLUSION: Managing a pandemic requires widespread, timely, and effective distribution of reliable information. In the past year, CIS and informaticists made prominent and influential contributions in the global response to the COVID-19 pandemic.

By exciting subtropical teleconnections, sea surface temperature (SST) anomalies in the North Tropical Atlantic (NTA) during boreal spring can trigger El Niño-Southern Oscillation (ENSO) events in the following boreal winter, thereby providing a precursor for ENSO predictability. However, this NTA-ENSO connection is not stationary, and it varies considerably over multidecadal timescales, which cannot be directly explained by the Atlantic multidecadal oscillation or the global warming trend. Here we show that multidecadal changes in the NTA-ENSO connection are principally controlled by multidecadal variability associated with the North Atlantic Oscillation (NAO). During the positive phase of the NAO, the amplification of the NTA impact on ENSO mainly arises from strengthening of the boreal spring mean precipitation over the equatorial Atlantic and enhancement of the persistence of NTA SST anomalies, which enhance the NTA influence by exciting stronger and more persistent subtropical teleconnections. Our findings show that multidecadal variability of the NAO is key to understanding the impacts of the NTA SST on the tropical Pacific Ocean.

This study examines the modifications of air-sea coupling processes by dust-radiation-cloud interactions over the North Atlantic Ocean using a high-resolution coupled atmosphere-wave-ocean-dust (AWOD) regional model. The dust-induced mechanisms that are responsible for changes of sea surface temperature (SST) and latent and sensible heat fluxes (LHF/SHF) are also examined. Two 3-month numerical experiments are conducted, and they differ only in the activation and deactivation of dust-radiation-cloud interactions. Model results show that the dust significantly reduces surface downward radiation fluxes (SDRF) over the ocean with the maximum change of 20-30 W m^-2. Over the dust plume region, the dust effect creates a low-pressure anomaly and a cyclonic circulation anomaly, which drives a positive wind stress curl anomaly, thereby reducing sea surface height and mixed layer depth. However, the SST change by dust, ranging from -0.5 to 0.5 K, has a great spatial variation which differs from the dust plume shape. Dust cools SST around the West African coast, except under the maximum dust plume ridge, and extends westward asymmetrically along the northern and southern edges of the dust plume. Dust unexpectedly warms SST over a large area of the western tropical North Atlantic and north of the dust plume. These SST changes are controlled by different mechanisms. Unlike the SST change pattern, the LHF and SHF changes are mostly reduced underneath the dust plume region, though they are different in detail due to different dominant factors, and increased south of the dust plume over the tropic.

Background

In the National Lung Screening Trial, 96.4% of nodules had benign etiology. To avoid unnecessary actions and exposure to harm, individuals with benign disease must be identified. We describe herein the analytical validation of a multi-analyte immunoassay for characterizing the risk that a lung nodule found on CT is malignant. Those at lower risk may be considered for serial surveillance to avoid unnecessary and potentially harmful procedures. While those nodules characterized at higher risk may be appropriate for more aggressive actions.

Objective

To validate the analytical performance of multiplexed plasma protein assays used in a novel test for lung nodule characterization.

Methods

A multiplexed immunoassay panel for the measurement of plasma proteins in current smokers who present with a lung nodule on CT scan was evaluated in a clinical testing laboratory. Assay analytical sensitivity, reproducibility, precision, and recovery of Epidermal Growth Factor Receptor (EGFR), Prosurfactant protein B (ProSB), and Tissue Inhibitor of Metalloproteinases 1 (TIMP1) from human EDTA plasma samples were evaluated across multiple runs, lots, and technicians. Interfering substances and sample pre-analytical storage conditions were evaluated for their effect on analyte recovery. The lung nodule risk score reproducibility was assessed across multiple lots.

Results

The assay sensitivities were 0.10 ng/mL EGFR, 0.02 ng/mL ProSB, and 0.29 ng/mL TIMP1 with over three orders of magnitude in the assay dynamic ranges. The assays and analytes are robust to pre-analytical sample handling and the plasma can be stored for up to 4 days at 4°C either when freshy collected or thawed after long-term storage at -80°C. Total imprecision after 20 days of testing remained under 9% for all three assays. Risk score variability remained within a ± 10% risk score range.

Conclusions

The three protein assays comprising the multi-analyte plasma test for lung nodule characterization performed quite acceptably in a clinical laboratory.

Multi-year El Niño events induce severe and persistent floods and droughts worldwide, with significant socioeconomic impacts, but the causes of their long-lasting behaviors are still not fully understood. Here we present a two-way feedback mechanism between the tropics and extratropics to argue that extratropical atmospheric variability associated with the North Pacific Oscillation (NPO) is a key source of multi-year El Niño events. The NPO during boreal winter can trigger a Central Pacific El Niño during the subsequent winter, which excites atmospheric teleconnections to the extratropics that re-energize the NPO variability, then re-triggers another El Niño event in the following winter, finally resulting in persistent El Niño-like states. Model experiments, with the NPO forcing assimilated to constrain atmospheric circulation, reproduce the observed connection between NPO forcing and the occurrence of multi-year El Niño events. Future projections of Coupled Model Intercomparison Project phases 5 and 6 models demonstrate that with enhanced NPO variability under future anthropogenic forcing, more frequent multi-year El Niño events should be expected. We conclude that properly accounting for the effects of the NPO on the evolution of El Niño events may improve multi-year El Niño prediction and projection.

Background

The increase in lung cancer screening is intensifying the need for a noninvasive test to characterize the many indeterminate pulmonary nodules (IPN) discovered. Correctly identifying non-cancerous nodules is needed to reduce overdiagnosis and overtreatment. Alternatively, early identification of malignant nodules may represent a potentially curable form of lung cancer.

Objective

To develop and validate a plasma-based multiplexed protein assay for classifying IPN by discriminating between those with a lung cancer diagnosis established pathologically and those found to be clinically and radiographically stable for at least one year.

Methods

Using a novel technology, we developed assays for plasma proteins associated with lung cancer into a panel for characterizing the risk that an IPN found on chest imaging is malignant. The assay panel was evaluated with a cohort of 277 samples, all from current smokers with an IPN 4-30 mm. Subjects were divided into training and test sets to identify a Support Vector Machine (SVM) model for risk classification containing those proteins and clinical factors that added discriminatory information to the Veteran's Affairs (VA) Clinical Factors Model. The algorithm was then evaluated in an independent validation cohort.

Results

Among the 97 validation study subjects, 68 were grouped as having intermediate risk by the VA model of which the SVM model correctly identified 44 (65%) of these intermediate-risk samples as low (n=16) or high risk (n=28). The SVM model negative predictive value (NPV) was 94% and its sensitivity was 94%.

Conclusion

The performance of the novel plasma protein biomarker assay supports its use as a noninvasive risk assessment aid for characterizing IPN. The high NPV of the SVM model suggests its application as a rule-out test to increase the confidence of providers to avoid aggressive interventions for their patients for whom the VA model result is an inconclusive, intermediate risk.

Giant magnetoresistive (GMR) nanosensors provide a novel approach for measuring protein concentrations in blood for medical diagnosis. Using an in vivo mouse radiation model, we developed protocols for measuring Flt3 ligand (Flt3lg) and serum amyloid A1 (Saa1) in small amounts of blood collected during the first week after X-ray exposures of sham, 0.1, 1, 2, 3, or 6 Gy. Flt3lg concentrations showed excellent dose discrimination at ≥ 1 Gy in the time window of 1 to 7 days after exposure except 1 Gy at day 7. Saa1 dose response was limited to the first two days after exposure. A multiplex assay with both proteins showed improved dose classification accuracy. Our magneto-nanosensor assay demonstrates the dose and time responses, low-dose sensitivity, small volume requirements, and rapid speed that have important advantages in radiation triage biodosimetry.