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Background: Patients with Alzheimer’s disease (AD) have considerably increased globally as a result of population aging, placing a significant burden on the global economy and the medical system. The outcome of clinical trials for AD immunotherapy that solely targeted amyloid-β (Aβ) or phosphorylated tau protein (p-Tau) was unsatisfactory. Therefore, blocking both Aβ and p-Tau’s pathological processes simultaneously while also preventing their interaction may be the key to developing an effective AD therapy. Objective: To develop a novel immunotherapy based on bispecific tandem scFv (TaFv) against AD. Methods: Bispecific single-chain antibody that targets both Aβ and p-Tau were obtained using E. coli expression system. Biological ability of TaFvs were determined by ELISA, SDS-PAGE, and immunohistochemical assay. Recombinant adeno-associated virus 9 (rAAV9) were packaged to create TaFv. The in vivo activity of rAAV9 were detected in mouse, using biophotonic imaging and frozen section methods. Results: The outcomes demonstrated that both Aβ and p-Tau had a high affinity for the bispecific TaFv. Additionally, it can bind to the amyloid plaques and neuronal tangles in the brain slices of an AD mouse model. Moreover, the rAAV9 could infect neuronal cells, transverse the blood-brain barrier, and express TaFv in the mouse brain. Conclusion: This novel immunotherapy offers a fresh concept for the immunotherapy of AD and successfully delivers the double target antibody into the brain, acting on both pathogenic substances Aβ and p-Tau.

This study examines the effects of supply reliability, risk aversion, and wealth on the optimal order strategy of retailers in the case of uncertain demand by measuring the degree of risk aversion. A more practical model of optimal ordering strategy is proposed, considering supply reliability, demand uncertainty, risk aversion, and retailer wealth, in which two random variables, supply reliability factors and demand, are introduced into the retailer’s function of expected utility. To avoid nonconvergence at both ends, the demand follows a triangular rather than a normal distribution. It is found that the optimal order quantity will increase with the improvement of supply reliability when the risk-averse degree is fixed. The results also show that the optimal order quantity of risk-averse retailers is smaller than that of risk-neutral retailers. Additionally, the optimal order quantity for the risk-averse retailer decreases as the degree of risk aversion increases, when supply reliability is fixed. Further research shows that the retailer is a constant absolute risk aversion (CARA). That means retailer’s wealth has nothing to do with the risk aversion and changes in the retailer’s wealth will not affect the retailer’s optimal order quantity. This study provides valuable insights for sustainable supply chain management and marketing.

The mechanical characteristics of high-strength steel (HSS) at high temperatures vary significantly from those of mild steel, so fire design regulations derived from mild steel cannot be transferred to HSS structures. Therefore, this paper investigates the fire resistance of beams made of HSSs, which will facilitate the design and application of HSS structures. Due to the heat dissipation of the concrete floor, steel beams are generally heated from three sides, and the temperature distribution in the steel beam cross-section is nonuniform. For such cases, the fire resistance of HSS beams is assessed using finite element models (FEMs) with nonuniform temperature distribution. A Ramberg–Osgood model was used to predict stress–strain relationships of Q460, Q690, and Q960 HSSs at elevated temperatures, and the model was verified by material tests. In the FEM, the proposed stress–strain relationships of HSSs at elevated temperatures, initial geometric imperfections and residual stress are considered for better accuracy. After verifying the established model against experimental results, the influence of nonuniform temperature distribution, load pattern, steel grade, and slenderness ratio on the resistance of HSS beams is investigated by conducting parametric analyses using the verified FEM. It is found that the critical bending moment of steel beams at elevated temperatures associated with lateral-torsional buckling highly depends on the reduction of elastic modulus of steel. By comparing FEM results with EN 1993-1-2, it is evident that EN 1993-1-2 is unsuitable for assessing the fire resistance of HSS beams. Therefore, the expression specified in EN 1993-1-2 is modified by fitting the finite analysis results to more accurately evaluate the fire resistance of HSS beams considering the nonuniform temperature distribution.

The implementation of green development has become an important choice for countries seeking the harmonious development of the economy and the environment. The National Ecological Civilization Pilot Zone is an innovative institutional mechanism for exploring green development in China. This study utilizes the National Ecological Civilization Pilot Zone policy as a quasi-natural experiment. Adopting data from 290 prefecture-level and above cities in China during 2014–2019 as the research object, this study matches the propensity score and improved differences-in-differences to assess the impact of green development mechanism innovation on regional total-factor environmental efficiency. The results show that this innovation had a significant impact on the improvement of total-factor environmental efficiency. Compared with non-pilot cities, the implementation of pilot zone areas contributed 16.78% to the growth of total-factor environmental efficiency in the experimental group cities. In addition, further analysis shows that mechanism innovation is more effective in areas with high pollution and high resource consumption. This study enriches the research on evaluation of the impact of innovation in green development mechanisms and provides a reference for further promoting pilot national ecological civilization zones.

Transient electromagnetic method (TEM) is one of the major tools to image the subsurface resistivity. The gradient-based inversion of TEM data only provides a unique solution using a subjectively defined regularization penalty, leaving the uncertainty of the solution unaddressed. The Bayesian method can be used to estimate the model parameters, as well as quantify their uncertainty. However, it requires far higher computational costs than gradient-based inversion, which limits the Bayesian inversion of TEM data to 1-D assumptions. We propose an accelerated Bayesian method based on Markov chain Monte Carlo (MCMC) subposteriors to perform full 2-D inversion of TEM data. A robust scheme is designed to divide the model space of a TEM profile into subspaces so that independent MCMC chains can be used to update the parameters in each subspace in parallel. The division is based on the coverage of the source loops using a cumulative sensitivity matrix. Then, the subposteriors obtained at each subspace are merged to approximate the full posterior of the model space using a weighting strategy. A numerical test of a 2-D valley model is used to validate the proposed method. The Bayesian inversion successfully obtained posterior that converges to the true model. The median model makes a good inference of the model parameters, while the probability density function gives their uncertainty estimates. The statistical model of interest can be further extracted from the model ensemble. The proposed method provides an effective framework for Bayesian inversion of TEM data with a multidimensional forward operator.

MXene aerogels with a three-dimensional (3D) network structure have attracted increasing attention for lightweight electromagnetic wave absorbers. It is intriguing to expand their absorption band, i.e., to the booming terahertz (THz) region, and explore multifunctionality. Herein, we assemble MXene (Ti

Background Normal lipid metabolism is a key process to maintaining cellular immune function and energy metabolism of macrophages, but Mycobacterium tuberculosis (MTB) infection can cause lipid metabolism disorder of macrophages, resulting in granuloma or intracellular retention. Methods Recombinant BCG with virulence protein Rv3874 or Rv3875(rBCG-Rv3874 and rBCG-Rv3875)were constructed. Transcriptomics and High-performance liquid chromatography-mass spectrometry (HPLC-MS) metabonomics studies were performed using rBCG infected macrophage samples. Extensive and variation difference analyses were conducted on transcription and lipid metabolism levels compared with the control group. Results A fact is that 7100 genes were changed in the rBCG-Rv3874 group and 1263 genes were changed in the rBCG-Rv3875 group at the RNA-seq level. A total of 612 and 485 substances were detected in the non-targeted positive and negative ion mode of lipid metabolism, and a total of 1240 and 210 metabolites were detected in the targeted positive and negative ion mode of lipid metabolism. Finally, it was found that the lipid changes related to the sphingomyelin (SM) metabolic pathway were the most obvious. 220 kinds of SM metabolites were detected by positive ion detection, and it was found that more ceramide, ceramide-1-phosphate, and SM were enriched in the rBCG-Rv3874 group than in rBCG-Rv3875 group. Conclusion MTB virulence proteins Rv3874 and Rv3875 can affect the sphingolipid metabolism of macrophages and it's associated with phagocytosis, apoptosis, and inflammatory processes.

Self-assembled photonic structures have greatly expanded the paradigm of optical materials due to their ease of access, the richness of results offered and the strong interaction with light. Among them, photonic heterostructure shows unprecedent advances in exploring novel optical responses that only can be realized by interfaces or multiple components. In this work, we realize visible and infrared dual-band anti-counterfeiting using metamaterial (MM) - photonic crystal (PhC) heterostructures for the first time. Sedimentation of TiO2 nanoparticles in horizontal mode and polystyrene (PS) microspheres in vertical mode self-assembles a van der Waals interface, connecting TiO2 MM to PS PhC. Difference of characteristic length scales between two components support photonic bandgap engineering in the visible band, and creates a concrete interface at mid-infrared to prevent interference. Consequently, the encoded TiO2 MM is hidden by structurally colored PS PhC and visualized either by adding refractive index matching liquid or by thermal imaging. The well-defined compatibility of optical modes and facility in interface treatments further paves the way for multifunctional photonic heterostructures.

In many scientific fields, the continuous operation of ultra-stable lasers is crucial for applications. To speed up the frequency stabilization process in case of the occurence of unexpected interruptions, a prompt frequency stabilization approach based on an improved mean shift algorithm is proposed and verified with a homemade laser system. We developed a double-loop feedback controller to steer the laser frequency with fast and slow channels, respectively. In this study, an improved mean shift algorithm is utilized to intelligently search for the transmission signal, which involves adaptively updating the sliding window radius and incorporating a Gaussian kernel function to update the shift vector. The number of lock points on the left and right sides of the central point determines the scanning direction to search for the transmission signal quickly. The laser is intentionally interrupted 306 times within 10,000 s to evaluate the relocking performance. The median auto-locking time of the laser is improved from 16 s to 4 s. By beating with another ultra-stable laser system, the laser frequency instability is measured to be less than 2.1×10−14 and the linewidth is 5 Hz. This work improves the adaptation and relocking ability of the ultra-stable laser in a complex environment.

Desert expansions can cause tremendous losses to human well-being. However, the process of shifting from the non-desert state to the desert state, a representation of a system regime shift, remains unclear on the global scale. Clarifying the underpinning pattern, predictors and signals of this process is of great value in advancing understanding of both ecosystem resilience and sustainable developments. Here, we combine the climate classification map and long-term observational land cover data to assess the global desert distribution and its changes from 2000 to 2019. The identified desert areas cover approximately 7.53% of the global land in the past two decades. Only approximately 16.03% of these deserts shows expanding trends, especially in countries such as Tunisia, Tajikistan and Peru. After assessing 26 climatic, ecological and socioeconomic factors that could potentially modify desert expansion rates, vegetation cover diversity was identified as the strongest predictor in both hot and cold deserts, followed by cattle density in hot deserts and desert size in cold deserts. In addition, pronounced high fluctuation in satellite vegetation productivity and flickering between land cover states could serve as two signals for desert conversion and fast expansion, respectively. Our results provide not only a long-term overview of global desert changing patterns but also possible guidance for constraining desert expansion.

Disease-modifying passive immunotherapies focusing on removal of abnormal phosphorylated Tau (p-Tau) constitute promising treatments for Alzheimer's disease (AD). Although several prior immunotherapies targeting p-Tau appear to be beneficial against AD, they have limitations such as the low blood-brain barrier (BBB) penetration rate, short half-life of antibodies, and the likelihood of inflammation. To address these issues, we designed a novel immunotherapy for AD. To this end, a single chain antibody (scFv) targeting p-Tau was generated, and a recombinant adeno-associated virus that can cross the BBB (rAAV/BBB) was used as a vector to express scFv for at least 22 weeks in the mouse brain. Results showed that the scFv constructed in this study had a high affinity to p-Tau and could bind to neuronal tangles in the section of brains of AD model mice. Moreover, the rAAV/BBB could cross the BBB, infect neuronal cells, and express scFv. This novel immunotherapy could effectively deliver scFv into the brain and resulted in a continuous expression of scFv in vivo, suggesting its potential for the treatment of AD.

Since multiple studies have reported that small nucleolar RNAs (snoRNAs) can be serve as prognostic biomarkers for cancers, however, the prognostic values of snoRNAs in lung adenocarcinoma (LUAD) remain unclear. Therefore, the main work of this study is to identify the prognostic snoRNAs of LUAD and conduct a comprehensive analysis. The Cancer Genome Atlas LUAD cohort whole-genome RNA-sequencing dataset is included in this study, prognostic analysis and multiple bioinformatics approaches are used for comprehensive analysis and identification of prognostic snoRNAs. There were seven LUAD prognostic snoRNAs were screened in current study. We also constructed a novel expression signature containing five LUAD prognostic snoRNAs (snoU109, SNORA5A, SNORA70, SNORD104 and U3). Survival analysis of this expression signature reveals that LUAD patients with high risk score was significantly related to an unfavourable overall survival (adjusted P = 0.01, adjusted hazard ratio = 1.476, 95% confidence interval = 1.096-1.987). Functional analysis indicated that LUAD patients with different risk score phenotypes had significant differences in cell cycle, apoptosis, integrin, transforming growth factor beta, ErbB, nuclear factor kappa B, mitogen-activated protein kinase, phosphatidylinositol-3-kinase and toll like receptor signaling pathway. Immune microenvironment analysis also indicated that there were significant differences in immune microenvironment scores among LUAD patients with different risk score. In conclusion, this study identified an novel expression signature containing five LUAD prognostic snoRNAs, which may be serve as an independent prognostic indicator for LUAD patients.

The Poisson–Nernst–Planck (PNP) model plays an important role in simulating nanopore systems. In nanopore simulations, the large-size nanopore system and convection-domination Nernst–Planck (NP) equations will bring convergence difficulties and numerical instability problems. Therefore, we propose an improved finite element method (FEM) with an inverse averaging technique to solve the three-dimensional PNP model, named inverse averaging FEM (IAFEM). At first, the Slotboom variables are introduced aiming at transforming non-symmetric NP equations into self-adjoint second-order elliptic equations with exponentially behaved coefficients. Then, these exponential coefficients are approximated with their harmonic averages, which are calculated with an inverse averaging technique on every edge of each tetrahedral element in the grid. Our scheme shows good convergence when simulating single or porous nanopore systems. In addition, it is still stable when the NP equations are convection domination. Our method can also guarantee the conservation of computed currents well, which is the advantage that many stabilization schemes do not possess. Our numerical experiments on benchmark problems verify the accuracy and robustness of our scheme. The numerical results also show that the method performs better than the standard FEM when dealing with convection-domination problems. A successful simulation combined with realistic chemical experiments is also presented to illustrate that the IAFEM is still effective for three-dimensional interconnected nanopore systems.

Frequency modulation technology has been widely used in many fields to get rid of the limitation of the 1/f flicker noise. However, the residual amplitude modulation (RAM) seriously deteriorates the detection accuracy of frequency modulation technology. Especially, for fiber electro-optic modulator (f-EOM), the RAM cannot be minimized by the conventional technique commonly used for free-space EOM such as careful mechanical adjustment or using a wedged crystal EOM. This can limit the use of f-EOM in high-performance detection techniques. In an ultra-stable laser system, the existence of the RAM has become one of the important factors limiting the frequency stability. This paper develops a dual-loop active feedback servo system to minimize the RAM. The voltage and temperature dependence of the EOM are measured to design a suitable active RAM reduction controller. To verify its ability, the active RAM reduction system is placed in an ultra-stable laser system for testing. The RAM noise is suppressed to less than 1 ppm and the corresponding laser frequency stability is 1×10−16. The RAM-reduced frequency stabilization is lower than the thermal noise limit of the reference cavity, so the RAM will not be the main factor affecting the laser frequency stability in the ultra-stable laser system.

Ultra-narrow linewidth laser plays a very important role in the high-precision optical frequency transfer via optical fibers. We have designed and realized a compact portable laser system for transportable communication band ultra-narrow linewidth laser. Based on the method of topology optimization design, a stable optical board is developed. Designed and developed a series of small optical grade devices without exercise rules, making the optical system more stable. The optical system we designed is suitable for transportable ultra-narrow linewidth laser.

As a measure of ecosystems' contribution to human well-being, the concept of Gross Ecosystem Product (GEP) is an integrated monetary index for the evaluation of final ecosystem services, which has attracted widespread attention around the world. In China, both national and local governments have launched a series of GEP accounting pilot projects, with the aim to incorporate this new concept into real world decision-making. However, a critical review of these practices remains lacking, especially regarding their current status and problems. In this study, by performing a systematic review and data integration of current literature and government documents, we comprehensively described the GEP accounting practices in China, including pilot project's coverage, accounting methods, and policy application. Then, we identified five major problems in current GEP accounting practices in China, which prevent GEP from being accurately measured in the short term. We proposed that GEP accounting should be a constantly evolving process with both long-term and short-term improvement goals. More in detail, the accuracy issues in GEP accounting require longer periods of time to resolve; while its repeatability, comparability, and applicability should be improved in the short term, so that it can be incorporated into decision-making. In response to these challenges, we suggested the adaptation of GEP accounting index screening principles as a possible future direction, which can help to apply GEP results in the current stages of decision making. By improving GEP concept and accounting, it will be possible to establish a unified comparable GEP accounting system and reduce the gap between the GEP and decision-making.