Application of the adaptive Monte Carlo method for uncertainty evaluation in the determination of total testosterone in human serum by triple isotope dilution mass spectrometry.

The measurement uncertainty is a crucial quantitative parameter for assessing the reliability of the result. The study aimed to propose a new budget for uncertainty evaluation of a reference measurement procedure for the determination of total testosterone in human serum. The adaptive Monte Carlo method (aMCM) was used for the propagation of probability distributions assigned to various input quantities to determine the uncertainty of the testosterone concentration. The basic principles of the propagation and the statistical analysis were described based on the experimental results of the quality control serum sample. The analysis of the number of Monte Carlo trials was discussed. The procedure of validation of the GUM uncertainty framework using the aMCM was also provided. The number of Monte Carlo trials was 2.974 × 106 when the results had stabilized. The total testosterone concentration was 16.02 nmol/L, and the standard uncertainty was 0.30 nmol/L. The coverage interval at coverage probability of 95% was 15.45 to 16.62 nmol/L, while the probability distribution for testosterone concentration was approximately described by a Gaussian distribution. The validation of results was not passed as the expanded uncertainty result obtained by the aMCM was slightly lower, about 7%, than that by the GUM uncertainty framework with consistent results of the concentration.

Ni-Al layered double hydroxide-coupled layered mesoporous titanium dioxide (Ni-Al LDH/LM-TiO2) composites with integrated adsorption-photocatalysis performance.

Nickel aluminum layered double hydroxides (Ni-Al LDHs) and layered mesoporous titanium dioxide (LM-TiO2) were prepared via a simple precipitation process and novel precipitation-peptization method, respectively, and Ni-Al LDH-coupled LM-TiO2 (Ni-Al LDH/LM-TiO2) composites with dual adsorption and photodegradation properties were obtained via the hydrothermal approach. The adsorption and photocatalytic properties were investigated in detail with methyl orange as the target, and the coupling mechanism was systematically studied. The sample with the best performance was recovered after photocatalytic degradation, which was labeled as 11% Ni-Al LDH/LM TiO2(ST), and characterization and stability studies were carried out. The results showed that Ni-Al LDHs showed good adsorption for pollutants. Ni-Al LDH coupling enhanced the absorption of UV and visible light, and the transmission and separation of photogenerated carriers were also significantly promoted, which was conducive to improving the photocatalytic activity. After treatment in the dark for 30 min, the adsorption of methyl orange by 11% Ni-Al LDHs/LM-TiO2 reached 55.18%. Under illumination for 30 min, the decolorization rate of methyl orange solution reached 87.54%, and the composites also showed an excellent recycling performance and stability.

Ultrasound image intelligent diagnosis in community-acquired pneumonia of children using convolutional neural network-based transfer learning.

Background: Studies show that lung ultrasound (LUS) can accurately diagnose community-acquired pneumonia (CAP) and keep children away from radiation, however, it takes a long time and requires experienced doctors. Therefore, a robust, automatic and computer-based diagnosis of LUS is essential. Objective: To construct and analyze convolutional neural networks (CNNs) based on transfer learning (TL) to explore the feasibility of ultrasound image diagnosis and grading in CAP of children. Methods: 89 children expected to receive a diagnosis of CAP were prospectively enrolled. Clinical data were collected, a LUS images database was established comprising 916 LUS images, and the diagnostic values of LUS in CAP were analyzed. We employed pre-trained models (AlexNet, VGG 16, VGG 19, Inception v3, ResNet 18, ResNet 50, DenseNet 121 and DenseNet 201) to perform CAP diagnosis and grading on the LUS database and evaluated the performance of each model. Results: Among the 89 children, 24 were in the non-CAP group, and 65 were finally diagnosed with CAP, including 44 in the mild group and 21 in the severe group. LUS was highly consistent with clinical diagnosis, CXR and chest CT (kappa values = 0.943, 0.837, 0.835). Experimental results revealed that, after k-fold cross-validation, Inception v3 obtained the best diagnosis accuracy, PPV, sensitivity and AUC of 0.87 ± 0.02, 0.90 ± 0.03, 0.92 ± 0.04 and 0.82 ± 0.04, respectively, for our dataset out of all pre-trained models. As a result, best accuracy, PPV and specificity of 0.75 ± 0.03, 0.89 ± 0.05 and 0.80 ± 0.10 were achieved for severity classification in Inception v3. Conclusions: LUS is a reliable method for diagnosing CAP in children. Experiments showed that, after transfer learning, the CNN models successfully diagnosed and classified LUS of CAP in children; of these, the Inception v3 achieves the best performance and may serve as a tool for the further research and development of AI automatic diagnosis LUS system in clinical applications. Registration: www.chictr.org.cn ChiCTR2200057328.

Machine English Translation Evaluation System Based on BP Neural Network Algorithm.

In order to solve the problems of machine translation efficiency and translation quality, this paper proposes an English translation evaluation system based on the BP neural network algorithm. This method provides users with a more intelligent machine translation service experience. With the help of the BP neural network algorithm, taking English online translation as the research object, Google's translation quality is the best, with an error frequency of only 167, while Baidu translation and iFLYTEK translation in China have a high error rate of 266 and 301, respectively, which is much higher than Google translation. A model of machine translation evaluation based on the neural network algorithm is proposed to better solve the disadvantages of traditional English machine translation. The results show that the machine translation system based on the neural network algorithm can further optimize the problems existing in machine translation, such as insufficient use of information and large scale of model parameters, and further improve the performance of neural network machine translation.

A new method for the evaluation of measurement uncertainty in strict accordance with measurement model: Determination of total thyroxine in human serum by triple isotope dilution mass spectrometry.

The rigorous and reasonable evaluation of uncertainty is crucial for the reliability of the results of a reference measurement procedure. A new uncertainty budget is proposed for uncertainty evaluation of a reference measurement procedure for total thyroxine in human serum based on isotope dilution liquid chromatography-mass spectrometry. In this work, a measurement model for uncertainty evaluation of triple isotope dilution-mass spectrometry was established. The propagation of uncertainties assigned to various input quantities was expressed in strict accordance with the measurement model. A detailed description of the uncertainty evaluation process for the measurement result of a specific serum is given, including the estimate of the input quantities and the determination of the combined standard uncertainty. The expanded uncertainty of the specific human serum (at coverage probability of 95%) was 4.8 nmol/L at the concentration level of 113.6 nmol/L.

High-Capacity Molecular Scale Conversion Anode Enabled by Hybridizing Cluster-Type Framework of High Loading with Amino-Functionalized Graphene.

Exploring high-capacity anodes with multielectron reaction, sufficient charge/mass transfer, and suppressed volume expansion is highly desired. The open frameworks consisting of independent structure units, which possess conversion reaction potentiality, can meet these demands and show advantages over routine insertion-type open frameworks with at most one-electron transfer or conversion materials with compact ligand linkage. Here, we report a class of electrochemically stable cluster-like polyoxometalates (POMs) as such open framework anodes. Their high loading and low solubility are enabled by Al- or Si-driven polymerization and hybridization with positively charged graphene, which immobilizes polyanions of POMs and improves their electric contact. Al-based POM composite (NAM-EDAG) for Li-storage achieves a high reversible capacity above 1000 mAh g(-1) and tolerates a long-term cycling with more than 1100 cycles and a current density up to 20 A g(-1). A six-electron conversion reaction occurring at molecular scale and the consequent optimized distribution of products benefiting from original open framework are also responsible for the high electroactivity. POM-based open frameworks give inspiration for exploring advanced, less soluble (or insoluble) framework materials made up of electroactive molecule or cluster moieties for Li- and Na-storage.

Fabrication of a novel nanocomposite Ag/graphene@SiO2-NaLuF4:Yb,Gd,Er for large enhancement upconversion luminescence.

Upconversion nanocrystals have a lot of advantages over other fluorescent materials. However, their applications are still limited due to their comparatively low upconversion luminescence (UCL). In the present study, a novel nanocomposite of Ag/graphene@SiO2-NaLuF4:Yb,Gd,Er for enhancing UCL was fabricated successfully, and its morphology, crystalline phase, composition, and fluorescent property were investigated. It is interesting to find that the Ag/graphene@SiO2-NaLuF4:Yb,Gd,Er and Ag@SiO2-NaLuF4:Yb,Gd,Er nanocomposites showed high UCL enhancements of 52- and 10-fold compared to the control of Ag-free nanocomposite SiO2-NaLuF4:Yb,Gd,Er, respectively. The enhancement of 52-fold is greater than those reported in our previous studies and some papers. Moreover, the measured life times of the Ag-presented nanocrystals were longer than that of Ag-absent counterparts. These enhancements of UCL can be ascribed to the effect of metal-enhanced fluorescence, which is caused by the enhancement of the local electric field. The UCL intensity of Ag/graphene@SiO2-NaLuF4:Yb,Gd,Er was 5.2-fold higher than that of Ag@SiO2-NaLuF4:Yb,Gd,Er, indicating that graphene presented in the fabricated nanocomposite structure favors metal-enhanced UCL. The small-sized Ag nanoparticles anchored on the graphene sheet mutually enhanced each other's polarizability and surface plasmon resonance, resulting in a big metal-enhanced UCL. This study provides a new strategy for effectively enhancing the UCL of upconversion nanocrystals. The enhancement potentially increases the overall upconversion nanocrystal detectability for highly sensitive biological, medical, and optical detections.

Synthesis of a novel core-shell nanocomposite Ag@SiO2@Lu2O3:Gd/Yb/Er for large enhancing upconversion luminescence and bioimaging.

Upconversion nanocrystals have many advantages over other fluorescent materials. However, their upconversion luminescence intensities are not desirable, limiting their applications for highly sensitive detection. Therefore, it is really important to enhance upconversion luminescent intensities of upconversion nanocrystals. In the present study, a novel Ag core and upconversion nanocrystal shell based nanocomposite Ag@SiO2@Lu2O3:Gd/Yb/Er for metal-enhanced upconversion luminescence was fabricated successfully, and its morphology, crystalline phase, composition, optical property, and cell imaging application were investigated. It was found that a maximum upconversion luminescence enhancement of 30-fold was obtained in comparison with the control without a silver core, and the nanocomposite exhibited bright upconversion luminescence when it was used for imaging with HeLa cells. This enhancement potentially increases the overall upconversion nanocrystal detectability, endowing the nanocomposite with a potential capability for highly sensitive biological, medical, and optical detection.

Synthesis of NaLuF4-based nanocrystals and large enhancement of upconversion luminescence of NaLuF4:Gd, Yb, Er by coating an active shell for bioimaging.

A series of NaLuF4-based hexagonal phase upconversion nanocrystals (UCNs) were synthesized by a facile solvothermal method and the properties of the UCNs were investigated. The results show that the as-prepared nanocrystals exhibit pure hexagonal lattice structures, uniform morphologies, high monodispersities and excellent upconversion luminescence. The upconversion luminescence (UCL) intensities of the UCNs can be enhanced by coating with a shell of NaLuF4. More interestingly, the UCL intensities of active-shell coated nanocrystals (NaLuF4:Gd, Yb, Er@NaLuF4:Yb, Ho and NaLuF4:Gd, Yb, Er@NaLuF4:Yb) are remarkably higher than that of inert-shell coated nanocrystals (NaLuF4:Gd, Yb, Er@NaLuF4), and NaLuF4:Gd, Yb, Er@NaLuF4:Yb, Ho is higher than NaLuF4:Gd, Yb, Er@NaLuF4:Yb. The mechanisms of upconversion luminescence enhancement are discussed in detail. The bioimaging application of the nanocrystals showed that bright upconversion luminescence was observed when UCNs-labeled HeLa cells were excited with 980 nm light. This study presents a facile method for the synthesis of NaLuF4-based upconversion nanocrystals with intense luminescence that can be used as potential fluorescent probes for sensitive bioimaging, and the suggested mechanism could provide new insights into fabrication of upconversion materials with high upconversion fluorescence.

Enhancing upconversion luminescence of NaYF4:Yb/Er nanocrystals by Mo(3+) doping and their application in bioimaging.

Enhancement of upconversion luminescence is imperative for the applications of upconversion nanocrystals (UCNs). In this work, we investigated the upconversion luminescence enhancement of NaYF4:Yb/Er by Mo(3+) ion doping. It was found that the upconversion luminescence intensities of the green and red emissions of UCNs co-doped with 10 mol% Mo(3+) ions were enhanced by 6 and 8 times, respectively. This enhancement offers a potential increase in the overall detectability of upconversion nanocrystals. HeLa cell imaging using NaYF4:Yb/Er/Mo as luminescent probes showed bright upconversion fluorescence. Moreover, the Mo(3+) doping endowed the UCNs with excellent paramagnetic behavior. It is expected that the as-prepared UCNs with a high upconversion luminescence and excellent paramagnetic properties could be promising bi-functional nanoprobes for sensitive multi-modal bioimaging and other optical applications.