High-Performance Plasma Biomarker Panel for Alzheimer's Disease Screening Using a Femtomolar-Level Label-Free Biosensing System.

Alzheimer's disease (AD) is the most common cause of dementia in older people. However, diagnosing AD through noncognitive methods, such as invasive cerebrospinal fluid sampling or radioactive positron emission tomography, has limited applications. Herein, the femtomolar levels of AD biomarkers amyloid ß 40 (Aß40), amyloid ß 42 (Aß42), phosphorylated tau 181 (P-tau181), phosphorylated tau 217 (P-tau217), and neurofilament light chain (NfL) were determined in human plasma in multicenter clinical cohorts using an ultrasensitive graphene field-effect transistor sensor. A machine-learning algorithm was also used to assemble these plasma biomarkers and optimize their performance in discriminating individual stages of Alzheimer's dementia progression. The "composite-info" biomarker panel, which combines these biomarkers and clinical information, considerably improved the staging performance in AD progression. It achieved an area under the curve of >0.94 in the receiver operator characteristic (ROC) curve. In addition, the panel demonstrated an advantage in the individual-based stage assessment compared with that of the Mini-Mental State Examination/Montreal Cognitive Assessment and nuclear magnetic resonance imaging. This study provides a composite biomarker panel for the screening and early diagnosis of AD using a rapid detection system.

Performance of the Cement Grouting Material and Optimization of the Mix Proportion for the Free Section of the Prestressed Anchor Bar.

Increasing the water-cement ratio and water-reducer dosage of cement slurry enhances its fluidity. However, a high water-cement ratio diminishes the beneficial effects of water reducers on fluidity. The stone content of the slurry decreases as the water-reducer dosage increases. Additionally, the water-cement ratio significantly affects stone content. However, when the water-cement ratio exceeds a threshold value, stone content decreases. Furthermore, the threshold value of the water-cement ratio decreases with increasing water-reducer dosage. Without the addition of the water reducer, as the water-cement ratio increases the overall integrity of the grout stone decreases. The addition of the water reducer alters the surface pore distribution, wherein "uniform small pores" change to "localized large pores." Based on the multi-objective optimization of Matlab, the recommended optimal mix composition for a slow-setting cement slurry is a water-cement ratio of 0.25 and water-reducer dosage of 1.5%. With the use of this optimized mix composition, the stone content and compressive strength increase by 7.8% and 145.6%, respectively, compared to those obtained using the recommended mix ratio in the specifications. Additionally, all relevant performance parameters meet the requirements specified by previous standards.

BDMCA: a big data management system for Chinese auditing.

The advent of big data technologies makes a profound impact on various facets of our lives, which also presents an opportunity for Chinese audits. However, the heterogeneity of multi-source audit data, the intricacy of converting Chinese into SQL, and the inefficiency of data processing methods present significant obstacles to the growth of Chinese audits. In this article, we proposed BDMCA, a big data management system designed for Chinese audits. We developed a hybrid management architecture for handling Chinese audit big data, that can alleviate the heterogeneity of multi-mode data. Moreover, we defined an R-HBase spatio-temporal meta-structure for auditing purposes, which exhibits almost linear response time and excellent scalability. Compared to MD-HBase, R-HBase performs 4.5× and 3× better in range query and kNN query, respectively. In addition, we leveraged the slot value filling method to generate templates and build a multi-topic presentation learning model MRo-SQL. MRo-SQL outperforms the state-of-the-art X-SQL parsing model with improvements in logical-form accuracy of up to 5.2%, and execution accuracy of up to 5.9%.

Animal models of Alzheimer's disease: Applications, evaluation, and perspectives.

Although great advances in elucidating the molecular basis and pathogenesis of Alzheimer's disease (AD) have been made and multifarious novel therapeutic approaches have been developed, AD remains an incurable disease. Evidence shows that AD neuropathology occurs decades before clinical presentation. AD is divided into three stages: preclinical stage, mild cognitive impairment (MCI), and AD dementia. In the natural world, some animals, such as non-human primates (NHPs) and canines, can develop spontaneous AD-like dementia. However, most animals do not develop AD. With the development of transgenic techniques, both invertebrate and vertebrate animals have been employed to uncover the mechanisms of AD and study treatment methods. Most AD research focuses on early-onset familial AD (FAD) because FAD is associated with specific genetic mutations. However, there are no well-established late-onset sporadic AD (SAD) animal models because SAD is not directly linked to any genetic mutation, and multiple environmental factors are involved. Moreover, the widely used animal models are not able to sufficiently recapitulate the pathological events that occur in the MCI or preclinical stages. This review summarizes the common models used to study AD, from yeast to NHP models, and discusses the different applications, evaluation methods, and challenges related to AD animal models, as well as prospects for the evolution of future studies.

Differences in action potential propagation speed and axon initial segment plasticity between neurons from Sprague-Dawley rats and C57BL/6 mice.

Action potentials (APs) in neurons are generated at the axon initial segment (AIS). AP dynamics, including initiation and propagation, are intimately associated with neuronal excitability and neurotransmitter release kinetics. Most learning and memory studies at the single-neuron level have relied on the use of animal models, most notably rodents. Here, we studied AP initiation and propagation in cultured hippocampal neurons from Sprague-Dawley (SD) rats and C57BL/6 (C57) mice with genetically encoded voltage indicator (GEVI)-based voltage imaging. Our data showed that APs traveled bidirectionally in neurons from both species; forward-propagating APs (fpAPs) had a different speed than backpropagating APs (bpAPs). Additionally, we observed distinct AP propagation characteristics in AISs emerging from the somatic envelope compared to those originating from dendrites. Compared with rat neurons, mouse neurons exhibited higher bpAP speed and lower fpAP speed, more distally located ankyrin G (AnkG) in AISs, and longer Nav1.2 lengths in AISs. Moreover, during AIS plasticity, AnkG and Nav1.2 showed distal shifts in location and shorter lengths of labeled AISs in rat neurons; in mouse neurons, however, they showed a longer AnkG-labeled length and more distal Nav1.2 location. Our findings suggest that hippocampal neurons in SD rats and C57 mice may have different AP propagation speeds, different AnkG and Nav1.2 patterns in the AIS, and different AIS plasticity properties, indicating that comparisons between these species must be carefully considered.

The Effect of the Swimmer's Trunk Oscillation on Dolphin Kick Performance Using a Computational Method with Multi-Body Motion: A Case Study.

The effect of a specific Chinese swimmer's trunk oscillation on dolphin kick was investigated in order to optimize competitive swimming movement. Using a numerical simulation method based on multi-body motion, different swimmer's trunk oscillation during a dolphin kick was analyzed. The simulation was conducted using 3D incompressible Navier−Stokes equations and renormalization group k-ε turbulence model, combined with the Volume of Fluid method to capture the water surface. The simulation's results were evaluated by comparing them with experimental data and with previous studies. The net streamwise forces, mean swimming velocity, and joint moments were also investigated. There was a positive correlation between the mean swimming velocity and the amplitudes of the swimmer's trunk oscillation, where the Pearson correlation coefficient was 0.986 and the selected model was statistically significant (p < 0.05). In addition, as the mean swimming velocity increased from 1.42 m/s in Variant 1 to 2 m/s in Variant 5, the maximum positive moments of joints increased by about 24.7% for the ankles, 27.4% for the knees, −3.9% for the hips, and 5.8% for the upper waist, whereas the maximum negative moments of joints increased by about 64.5% for the ankles, 28.1% for the knees, 23.1% for the hips, and 10.1% for the upper waist. The relationship between the trunk oscillation and the vortices was also investigated. Therefore, it is recommended that swimmers should try to increase the amplitudes of trunk oscillation to increase their swimming velocity. In order to achieve this goal, swimmers should increase strength training for the ankles, knees, and upper waist during the upkick. Moreover, extra strength training is warranted for the ankles, knees, hips, and upper waist during the downkick.

Hydrodynamic Characteristics of Different Undulatory Underwater Swimming Positions Based on Multi-Body Motion Numerical Simulation Method.

The study of hydrodynamic characteristics of swimming is the main way to optimize the swimming movement. The relationship between position, water depth, and swimming performance of undulatory underwater swimming are one of the main concerns of scholars. Therefore, the aim of this study is to analyze the swimming performance of three different undulatory underwater swimming positions under various swimming depths using a numerical simulation method based on multi-body motion. The simulation was conducted using 3D incompressible Navier-Stokes equations using the RNG k-ε turbulence closure equations, and in combination with the VOF method thus that we could include the water surface in our calculations. Different swimming depths based on the distance from the shoulder joint center to the initial water surface were considered. The velocity of the shoulder joint center was captured with a swimming motion monitoring system (KiSwim) and compared with the calculated results. The study found that there was a significant difference in the hydrodynamic characteristics of the three undulatory underwater swimming positions (i.e., the dorsal, lateral, and frontal positions) when swimming near the water surface, and the difference decreased as the swimming depth increased. There was a negative correlation (R(dorsal) = -0.928, R(frontal) = -0.937, R(lateral) = -0.930) between the swimming velocities of the three undulatory underwater swimming positions and the water depth (water depth = 0.2-0.7 m) and that the lateral position had the greatest average velocity. Therefore, it is recommended that swimmers travel at least 0.5 m below the water surface in any undulatory underwater swimming position in order to avoid excessive drag forces. As the swimmer approaches the water surface, the lateral position is worth considering, which has better velocity and hydrodynamic advantage than the other two undulatory underwater swimming positions.

Performance Improvement of Discretely Modulated Continuous-Variable Quantum Key Distribution with Untrusted Source via Heralded Hybrid Linear Amplifier.

In practical quantum communication networks, the scheme of continuous-variable quantum key distribution (CVQKD) faces a challenge that the entangled source is controlled by a malicious eavesdropper, and although it still can generate a positive key rate and security, its performance needs to be improved, especially in secret key rate and maximum transmission distance. In this paper, we proposed a method based on the four-state discrete modulation and a heralded hybrid linear amplifier to enhance the performance of CVQKD where the entangled source originates from malicious eavesdropper. The four-state CVQKD encodes information by nonorthogonal coherent states in phase space. It has better transmission distance than Gaussian modulation counterpart, especially at low signal-to-noise ratio (SNR). Moreover, the hybrid linear amplifier concatenates a deterministic linear amplifier (DLA) and a noiseless linear amplifier (NLA), which can improve the probability of amplification success and reduce the noise penalty caused by the measurement. Furthermore, the hybrid linear amplifier can raise the SNR of CVQKD and tune between two types of performance for high-gain mode and high noise-reduction mode, therefore it can extend the maximal transmission distance while the entangled source is untrusted.

Using mixed methods to design service quality evaluation indicator system of railway container multimodal transport.

Multimodal transport can bring the technical and economic advantages in different transportation modes into full play. While ensuring the level of service, it can reduce energy consumption and transport costs. Governments of most countries are actively promoting it. Therefore, it has become a research hot spot. Being a green, fast, and all-day transport mode, railways play an important role in multimodal transport. This article aims to analyze a multimodal transport service quality indicator system involving railways from the perspectives of customers, multimodal service providers, and governments. Qualitative and quantitative research methods were adopted to analyze the secondhand data of academic papers, government policy, and industry reports to clarify the quality characteristics of multimodal transport services. Using grounded theory and to analyze firsthand data from in-depth interviews with multimodal transport practitioners, 25 evaluation indicators of container multimodal transport service quality were chosen to be the evaluation index system. To test and improve the evaluation scale, 270 valid questionnaires were analyzed using SPSS 24.0 and AMOS 21.0 software, including reliability analysis, exploratory factor analysis, and confirmatory factor analysis. The results show that all the indicators meet the standard requirements and have good reliability and validity.

A Rapid Detection Method for Morphological Characteristics of Biological Cells Based on Phase Imaging.

This paper presents a rapid label-free method for the identification of morphological characteristics of biological cells. Based on quantitative phase microscopy as well as the connotation of phase value, the gradient operator of phase and the associated analytic processing are employed to determine the edge of different parts of the samples. A heterogeneous biological cell model is established by simulation to show the mechanism of this method and a polystyrene bead is selected as a sample to confirm its validity by optical experiment. The result agrees well with the actual situation and this approach is proved to have good antinoise ability. Furthermore, a neutrophil is investigated by this method. Based on the optical experiment and the related analysis, the basic structure characteristics of the cell are obtained. It is indicated that the method presented in this paper could be applied to rapid identification and classification of living cells.