SERPINA3, FGA, AGP1, ITIH3 and SAA1 as novel biomarkers for eosinophilic granulomatosis with polyangiitis diagnosis and activity assessment.

OBJECTIVE: To identify novel biomarkers for diagnosis and prediction of active eosinophilic granulomatosis with polyangiitis (EGPA) through data-independent acquisition (DIA) analysis. METHODS: Plasma from 11 EGPA patients and 10 healthy controls (HCs) were analyzed through DIA to identify potential biomarkers. The results were validated in 32 EGPA patients, 24 disease controls (DCs), and 20 HCs using enzyme-linked immunosorbent assay (ELISA). The receiver operating characteristic (ROC) curve was used to assess the diagnostic value of candidate biomarkers. RESULTS: Thirty-five differentially expressed proteins (DEPs) (24 upregulated and 11 downregulated) were screened between EGPA and HC groups. Five proteins, including serine proteinase inhibitor A3 (SERPINA3), alpha-fibrinogen (FGA), alpha-1 acid glycoprotein 1(AGP1), inter-alpha-trypsin inhibitor heavy chain H3 (ITIH3), and serum amyloid A1 (SAA1), were significantly upregulated in EGPA compared with HCs. Apart from SAA1, all proteins were also higher in EGPA patients compared with DCs. Furthermore, a panel of SERPINA3 and SAA1 exhibited potential diagnostic value for EGPA with an area under the curve (AUC) of 0.953, while a panel of SERPINA3, FGA, AGP1, and ITIH3 showed good discriminative power to differentiate EGPA from DCs with AUC of 0.926. Moreover, SERPINA3, FGA, and AGP levels were significantly higher in active EGPA and correlated well with disease activity. A combination of SERPINA3 and AGP1 exhibited an excellent AUC of 0.918 for disease activity assessment. CONCLUSION: SERPINA3, FGA, AGP1, ITIH3 and SAA1 were identified as potential biomarkers for EGPA diagnosis and disease activity assessment. Among them, as a single biomarker, SERPINA3 has the best diagnostic performance.

Peripheral neutrophils and oxidative stress-associated molecules for predicting the severity of asthma: a cross-sectional study based on multidimensional assessment.

Objectives: This study aims to explore the relationship between the severity of asthma and neutrophils and related oxidative stress-associated molecules in peripheral blood and induced sputum. Methods: A total of 67 subjects were included in this study, namely, 25 patients with severe asthma and 42 patients with non-severe asthma. Clinical data, induced sputum and peripheral blood were collected. Lung function and molecules related to oxidative stress in induced sputum and peripheral blood of asthma patients were detected. The relationship between neutrophils and asthma severity was analyzed. HDAC2 mRNA and protein expression levels and HDAC2 activity were also analyzed. Multivariate logistic regression was performed to select statistically significant variables. Results: The absolute value of neutrophils and percentage of neutrophils were higher in the severe asthma patients. These two values were used to predict the severity of asthma by ROC analysis, with the best cutoff values being 4.55 × 109/L (sensitivity 83.3%, specificity 64.0%) and 55.15% (sensitivity 54.8%, specificity 88.0%). The ROS concentration of neutrophils in the induced sputum samples and the 8-iso-PGF2α concentration in the peripheral blood samples were higher in the severe asthma group (P = 0.012; P = 0.044), whereas there was reduced HDAC2 protein activity in PBMCs (P < 0.001). A logistic equation and a nomogram were created to give a precise prediction of disease severity. Conclusion: Oxidative stress is increased in severe asthma patients. Peripheral blood neutrophils and 8-iso-PGF2α can be used as biomarkers to predict the severity of asthma. A prediction model was created for evaluating asthma severity.

Statistical Assessment of High-Performance Scaled Double-Gate Transistors from Monolayer WS2.

Scaling of monolayer transition metal dichalcogenide (TMD) field-effect transistors (FETs) is an important step toward evaluating the application space of TMD materials. Although some work on ultrashort channel monolayer (ML) TMD FETs has been published, there exist no comprehensive studies that assess their performance in a statistically relevant manner, providing critical insights into the impact of the device geometry. Part of the reason for the absence of such a study is the substantial variability of TMD devices when processes are not carefully controlled. In this work, we show a statistical study of ultrashort channel double-gated ML WS2 FETs exhibiting excellent device performance and limited device-to-device variations. From a detailed analysis of cross-sectional scanning transmission electron microscopy (STEM) images and careful technology computer aided design (TCAD) simulations, we evaluated, in particular, an unexpected deterioration of the subthreshold characteristics for our shortest devices. Two potential candidates for the observed behavior were identified, i.e., buckling of the TMD on the substrate and loss of gate control due to the source geometry and the high-k dielectric between the metal gate and the metal source electrode.

Cost-effectiveness analysis of continuous subcutaneous insulin infusion versus multiple daily insulin for treatment of children with type 1 diabetes.

OBJECTIVE: To evaluate the health economics of using continuous subcutaneous insulin infusion (CSII) therapy versus multiple daily injections (MDI) therapy in children and adolescent patients with type 1 diabetes (T1D) in Qingdao, China. METHODS: A long-term cost-effectiveness analysis was conducted using the IQVIA Core Diabetes Model (CDM). The baseline characteristics of the simulated cohorts were obtained from 213 pediatric T1D patients who received care with CSII(104 cases) or MDI(109 cases) in Qingdao from 1 January 2015 to 31 March 2019. In the essential case, the expenditure of the complications and treatment of the disease with both therapies were evaluated in Chinese currency from the perspective of healthcare system. In a secondary analysis, the model used a 70-year time horizon, and a discount rate of 5% was applied to all future health outcomes and costs. A one-way sensitivity analysis was conducted on delta HbA1c, different prices of insulin pump, price of each upgrade cycle rates and different discount rates. Uncertainty was also evaluated by the probability sensitivity analysis and scenario analysis. RESULTS: In the base-case analysis, the lifetime total costs were lower for CSII group at ¥630,871 per patient compared with ¥672,672 for MDI group. The quality-adjusted life years (QALYs) gained were 11.612 and 11.197 for patients treated with CSII group and MDI group, respectively. The CSII group was cost-saving compared to MDI group. The feasibility of CSII group being cost-effective was 100% under the threshold of 3 times per capita GDP of China in 2019 (¥212,676) which was indicated from the probabilistic sensitivity analysis. Regarding scenario analysis, the ICER of the CSII group compared to MDI was between -151,583 and 153,366 RMB/QALYs, which is cost-effective. CONCLUSIONS: This economic evaluation compared CSII therapy versus MDI therapy for T1D children and adolescent patients in China and findings indicate that CSII should be considered a preferred treatment modality to MDI.

Actualizing a High-Energy Bipolar-Stacked Solid-State Battery with Low-Cost Mechanically Robust Nylon Mesh-Reinforced Composite Polymer Electrolyte Membranes.

To meet the rapidly growing and diversified demand for energy storage, advanced rechargeable batteries with high-performance materials and efficient battery configuration are widely being exploited and developed. Bipolar-stacked electrode coupling with solid-state electrolytes enables achieving batteries with high output voltage, high energy density, and simple components. Here, a polymer electrolyte membrane is designed with polyethylene oxide containing bis(trifluoromethanesulfonyl)-imide as the electrolyte, succinonitrile as the plasticizer, and nylon mesh as a reinforcement for the bipolar-stacked battery. The as-prepared nylon mesh-reinforced polymer electrolyte membrane shows advantageous features, that is, excellent ionic conductivity (3.38 × 10-4 S cm-1) at room temperature, low interface impedance, and good tolerance against the expansion caused by the plating/stripping of the Li anode and the electrode upon cycling. When used as a polymer electrolyte membrane in the bipolar-stacked battery, the LiFePO4(LFP)-Li4Ti5O12(LTO) cell with three cells connected in series delivers a higher discharge voltage (5.4 V) and a volumetric energy density (0.328 mW h cm-3), nearly 3 times as much as that of the LFP-LTO battery. In addition, LiFePO4-Li pouch cells using the polymer electrolyte membrane can sustain the abuse tests including bending, cutting, and nail penetration well. These results pave a new avenue to develop high-performance polymer electrolyte membranes and allow for the design of high-voltage and volumetric energy density bipolar-stacked batteries.

Attention-Guided Discriminative Region Localization and Label Distribution Learning for Bone Age Assessment.

Bone age assessment (BAA) is clinically important as it can be used to diagnose endocrine and metabolic disorders during child development. Existing deep learning based methods for classifying bone age use the global image as input, or exploit local information by annotating extra bounding boxes or key points. However, training with the global image underutilizes discriminative local information, while providing extra annotations is expensive and subjective. In this paper, we propose an attention-guided approach to automatically localize the discriminative regions for BAA without any extra annotations. Specifically, we first train a classification model to learn the attention maps of the discriminative regions, finding the hand region, the most discriminative region (the carpal bones), and the next most discriminative region (the metacarpal bones). Guided by those attention maps, we then crop the informative local regions from the original image and aggregate different regions for BAA. Instead of taking BAA as a general regression task, which is suboptimal due to the label ambiguity problem in the age label space, we propose using joint age distribution learning and expectation regression, which makes use of the ordinal relationship among hand images with different individual ages and leads to more robust age estimation. Extensive experiments are conducted on the RSNA pediatric bone age data set. Without using extra manual annotations, our method achieves competitive results compared with existing state-of-the-art deep learning-based methods that require manual annotation. Code is available at https://github.com/chenchao666/Bone-Age-Assessment.

Clinical Outcome and Cost-Effectiveness Analysis of CSII Versus MDI in Children and Adolescent With Type 1 Diabetes Mellitus in a Public Health Care System of China.

Objectives: To evaluate the clinical and economic consequences of continuous subcutaneous insulin infusion (CSII) vs. multiple daily injections (MDI) in children and adolescents with type 1 diabetes mellitus (T1DM) from a public health care system in developed areas of developing country, considering changes in glycemic Control, daily insulin requirements, lipid profile, body mass index (BMI), frequency of severe hypoglycemia and Diabetic Ketoacidosis (DKA) and diabetic complications. Methods: This was a retrospective cohort study of children and adolescents with T1DM. Data were collected at baseline and the end of every year including glycated hemoglobin (HbA1c), insulin dose, lipid profile, blood pressure, and adverse events (severe hypoglycemia and DKA). The Cost-effectiveness analysis was performed using the IQVIA CORE Diabetes Model (CDM) to simulate diabetes progression by utilizing the clinical data obtained from the two groups. The main outcome measures were Life Expectancy, Quality adjusted life years (QALYs), Total Costs and Incremental Costs and Effectiveness Ratio (ICER) of CSII compared with MDI in Chinese pediatric patients with T1DM in Qingdao City (60 years). Results: Mean HbA1c values and daily insulin doses were significantly lower in those receiving CSII therapy throughout follow-up. Mean direct lifetime costs were ¥ 67,137 higher with CSII treatment than with MDI for pediatric patients. Treatment with CSII was associated with an improvement in life expectancy of 0.41 years for pediatric patients compared with MDI based on CORE diabetes model simulation. The corresponding gains in QALYs were 0.42. These data produced corresponding ICER is ¥ 161,815 per QALY for pediatric T1DM patients in Qingdao. Sensitivity analyses suggested that our base-case assumptions were mostly robust. Conclusions: CSII is associated with improved long-term clinical outcomes compared with MDI. Based on this model analysis, CSII appears to be more cost-effective for the Qingdao TIDM pediatric population and health care system.

Score for predicting overall survival in pancreatic adenocarcinoma patients with positive lymph nodes after surgery: a novel nomogram-based risk assessment.

BACKGROUND: Pancreatic adenocarcinoma (PaC) patients with positive lymph nodes (PLNs) have a dismal prognosis and lack a specific prognostic stage. This study aimed to construct a nomogram for the prediction of overall survival (OS) in these patients. METHODS: A total of 1,340 patients screened from the Surveillance, Epidemiology, and End Results database were included and randomly divided at a ratio of 7:3 into a training set (n=940) and an internal validation set (n=400). Cox regression analyses were conducted to select independent predictors in the training set, and a nomogram was constructed. The model was verified in the internal validation set and in an external validation set, which comprised 64 patients from a Chinese institute. RESULTS: Six independent prognostic factors (age at diagnosis, tumor grade, lymph node ratio, T stage, radiotherapy, and chemotherapy) were identified in PaC patients with PLNs and were entered into the nomogram. The final model had a higher C-index for predicting OS than the American Joint Committee on Cancer-8th edition staging system (training set: 0.658 vs. 0.546; internal validation set: 0.661 vs. 0.546; external validation set: 0.691 vs. 0.581). The 1-, 2-, and 3-year area under the receiver operating characteristic curve values indicated better discrimination power for the established nomogram with respect to the prediction of OS in the training, internal validation, and external validation sets than for the American Joint Committee on Cancer-8th edition staging system. Furthermore, the nomogram performed well in both calibration and decision curve analyses (DCA) of clinical applicability. OS in PaC patients with PLNs was significantly distinguished among the three risk groups stratified according to the nomogram score (P<0.001). CONCLUSIONS: The well-calibrated nomogram was determined to be extremely efficient in predicting survival, and defining a high-risk population based on the nomogram score among PaC patients with PLNs after surgery.

Spin-torque devices with hard axis initialization as Stochastic Binary Neurons.

Employing the probabilistic nature of unstable nano-magnet switching has recently emerged as a path towards unconventional computational systems such as neuromorphic or Bayesian networks. In this letter, we demonstrate proof-of-concept stochastic binary operation using hard axis initialization of nano-magnets and control of their output state probability (activation function) by means of input currents. Our method provides a natural path towards addition of weighted inputs from various sources, mimicking the integration function of neurons. In our experiment, spin orbit torque (SOT) is employed to "drive" nano-magnets with perpendicular magnetic anisotropy (PMA) -to their metastable state, i.e. in-plane hard axis. Next, the probability of relaxing into one magnetization state (+mi) or the other (-mi) is controlled using an Oersted field generated by an electrically isolated current loop, which acts as a "charge" input to the device. The final state of the magnet is read out by the anomalous Hall effect (AHE), demonstrating that the magnetization can be probabilistically manipulated and output through charge currents, closing the loop from charge-to-spin and spin-to-charge conversion. Based on these building blocks, a two-node directed network is successfully demonstrated where the status of the second node is determined by the probabilistic output of the previous node and a weighted connection between them. We have also studied the effects of various magnetic properties, such as magnet size and anisotropic field on the stochastic operation of individual devices through Monte Carlo simulations of Landau Lifshitz Gilbert (LLG) equation. The three-terminal stochastic devices demonstrated here are a critical step towards building energy efficient spin based neural networks and show the potential for a new application space.

Serial cfDNA assessment of response and resistance to EGFR-TKI for patients with EGFR-L858R mutant lung cancer from a prospective clinical trial.

BACKGROUND: Detecting epidermal growth factor receptor (EGFR) activating mutations in plasma could guide EGFR-tyrosine kinase inhibitor (EGFR-TKI) treatment for advanced non-small cell lung cancer (NSCLC). However, dynamic quantitative changes of plasma EGFR mutations during the whole course of EGFR-TKI treatment and its correlation with clinical outcomes were not determined. The aim of this study was to measure changes of plasma EGFR L858R mutation during EGFR-TKI treatment and to determine its correlation with the response and resistance to EGFR-TKI. METHODS: This study was a pre-planned exploratory analysis of a randomized phase III trial conducted from 2009 to 2014 comparing erlotinib with gefitinib in advanced NSCLC harboring EGFR mutations in tumor (CTONG0901). Totally, 256 patients were enrolled in CTONG0901 and randomized to receive erlotinib or gefitinib. One hundred and eight patients harbored L858R mutation in their tumors and 80 patients provided serial blood samples as pre-planned scheduled. Serial plasma L858R was detected using quantitative polymerase chain reaction. Dynamic types of plasma L858R were analyzed using Ward's hierarchical clustering method. Progression-free survival (PFS) and overall survival (OS) were compared between different types. RESULTS: As a whole, the quantity of L858R decreased and reached the lowest level at the time of best response to EGFR-TKI. After the analysis of Ward's hierarchical clustering method, two dynamic types were found. In 61 patients, L858R increased to its highest level when disease progressed (ascend type), while in 19 patients, L858R maintained a stable level when disease progressed (stable type). Median PFS was 11.1 months (95 % CI, 6.6-15.6) and 7.5 months (95 % CI, 1.4-13.6) in patients with ascend and stable types, respectively (P = 0.023). Median OS was 19.7 months (95 % CI, 16.5-22.9) and 16.0 months (95 % CI, 13.4-18.5), respectively (P = 0.050). CONCLUSIONS: This is the first report finding two different dynamic types of plasma L858R mutation during EGFR-TKI treatment based on a prospective randomized study. Different dynamic types were correlated with benefits from EGFR-TKI. The impact of plasma L858R levels at disease progression on subsequent treatment strategy needs further exploration. TRIAL REGISTRATION: ClinicalTrials.gov, NCT01024413.

A nontoxic and low-cost hydrothermal route for synthesis of hierarchical Cu2ZnSnS4 particles.

We explore a facile and nontoxic hydrothermal route for synthesis of a Cu2ZnSnS4 nanocrystalline material by using l-cysteine as the sulfur source and ethylenediaminetetraacetic acid (EDTA) as the complexing agent. The effects of the amount of EDTA, the mole ratio of the three metal ions, and the hydrothermal temperature and time on the phase composition of the obtained product have been systematically investigated. The addition of EDTA and an excessive dose of ZnCl2 in the hydrothermal reaction system favor the generation of kesterite Cu2ZnSnS4. Pure kesterite Cu2ZnSnS4 has been synthesized at 180°C for 12 h from the reaction system containing 2 mmol of EDTA at 2:2:1 of Cu/Zn/Sn. It is confirmed by Raman spectroscopy that those binary and ternary phases are absent in the kesterite Cu2ZnSnS4 product. The kesterite Cu2ZnSnS4 material synthesized by the hydrothermal process consists of flower-like particles with 250 to 400 nm in size. It is revealed that the flower-like particles are assembled from single-crystal Cu2ZnSnS4 nanoflakes with ca. 20 nm in size. The band gap of the Cu2ZnSnS4 nanocrystalline material is estimated to be 1.55 eV. The films fabricated from the hierarchical Cu2ZnSnS4 particles exhibit fast photocurrent responses under intermittent visible-light irradiation, implying that they show potentials for use in solar cells and photocatalysis.