Two-dimensional Janus SbTeBr/SbSI heterostructures as multifunctional optoelectronic systems with efficient carrier separation.

The stacking of two-dimensional (2D) materials is a highly effective approach in the design of high-performance optoelectronic devices. In this study, we propose a novel Janus monolayer-based 2D/2D van der Waals heterostructure (vdWH) called SbTeBr/SbSI. Starting from its most stable binding configuration, we systematically examined its electronic, optical, mechanical and dynamical properties. The SbTeBr/SbSI vdWH exhibits a type II band arrangement, with an indirect bandgap of 1.28 eV and strong light absorption capabilities in the visible range, achieving an absorption coefficient of 4 × 105 cm-1. These desirable properties suggest that SbTeBr/SbSI holds promise as a material for solar cells, potentially achieving a power conversion efficiency of 8.3%. The dipole-induced electric field in the SbTeBr/SbSI vdWH leads to significant differences in the mobilities of different carriers, which is a critical aspect in suppressing the recombination of photogenerated carriers. Additionally, according to the simulations of nonadiabatic molecular dynamics, a long electron-hole recombination time of 133 ps is predicted. Thus, the SbTeBr/SbSI heterostructure enables efficient charge separation, demonstrating its potential as a high-performance optoelectronic material.

Electroacupuncture alleviates neuropathic pain caused by SNL by promoting M2 microglia polarization through PD-L1.

As a common clinical disease, neuropathic pain is difficult to be cured with drugs. The occurrence and progression of pain is closely related to the response of spinal microglia. Aspartof the regulation of microglialactivity,PD-L1 playsacriticalrole. Loss of PD-L1 promoted the polarization of M1-like microglia. Increased expression of PD-L1 promoted M2-like polarization. Electroacupuncture has a significant analgesic effect in clinical practice, but its specific mechanism remains to be further explored. In this study, we verified the role of PD-L1 in EA analgesia and the underlying molecular mechanism through spinal nerve ligation (SNL) in rats and lipopolysaccharide (LPS)-treated BV2 microglial cells. Forbehavioralstudiesofrats,mechanical withdrawal threshold (MWT) and thermal withdrawal latency (TWL) were measured, and spinal cord neuros were examined under transmission electron microscopyto determine changes to their myelin structure. The expression levels of PD-L1 and M1/M2-specific markers in rat spinal cord and BV2 microglial cells were measured by enzyme-linked immunosorbent assay, flow cytometry, immunofluorescence staining and Western blot analysis. Our study showed that EA increased the pain threshold, reduced the destruction of myelin structure, promoted the expression of PD-L1 and PD-1, inhibited the MAPK signaling pathway, and promoted the conversion of microglial polarization from the M1 phenotype to the M2 phenotype in SNL rats. PD-L1 knockdown reversed these effects of EA. In addition, PD-L1 knockdown activated the MAPK signaling pathway, promoted microglial polarization to the M1 phenotype, decreased the expression of anti-inflammatory mediators and increased the expression of proinflammatory factors in LPS-stimulated BV2 microglial cells. Our results showed that EA may regulate the excitability of primary afferent neurons through PD-L1 and then inhibit the MAPK signaling pathway to promote the transformation of activated M1 microglia into M2 microglia, reduce inflammatory reactions, and finally achieve analgesic effects. A therapy targeting PD-L1 may be an effective strategy for treating neuropathic pain.

First Detection and Tunneling Time of a Quantum Walk.

We consider the first detection problem for a one-dimensional quantum walk with repeated local measurements. Employing the stroboscopic projective measurement protocol and the renewal equation, we study the effect of tunneling on the detection time. Specifically, we study the continuous-time quantum walk on an infinite tight-binding lattice for two typical situations with physical reality. The first is the case of a quantum walk in the absence of tunneling with a Gaussian initial state. The second is the case where a barrier is added to the system. It is shown that the transition of the decay behavior of the first detection probability can be observed by modifying the initial condition, and in the presence of a tunneling barrier, the particle can be detected earlier than the impurity-free lattice. This suggests that the evolution of the walker is expedited when it tunnels through the barrier under repeated measurement. The first detection tunneling time is introduced to investigate the tunneling time of the quantum walk. In addition, we analyze the critical transitive point by deriving an asymptotic formula.

Electroacupuncture inhibits dendritic spine remodeling through the srGAP3-Rac1 signaling pathway in rats with SNL.

Previous studies have shown that peripheral nerve injury can lead to abnormal dendritic spine remodeling in spinal dorsal horn neurons. Inhibition of abnormal dendritic spine remodeling can relieve neuropathic pain. Electroacupuncture (EA) has a beneficial effect on the treatment of neuropathic pain, but the specific mechanism remains unclear. Evidence has shown that slit-robo GTPase activating protein 3 (srGAP3) and Rho GTPase (Rac1) play very important roles in dendritic spine remodeling. Here, we used srGAP3 siRNA and Rac1 activator CN04 to confirm the relationship between SrGAP3 and Rac1 and their roles in improving neuropathic pain with EA. Spinal nerve ligation (SNL) was used as the experimental model, and thermal withdrawal latency (TWL), mechanical withdrawal threshold (MWT), Western blotting, immunohistochemistry and Golgi-Cox staining were used to examine changes in behavioral performance, protein expression and dendritic spines. More dendritic spines and higher expression levels of srGAP3 were found in the initial phase of neuropathic pain. During the maintenance phase, dendritic spines were more mature, which was consistent with lower expression levels of srGAP3 and higher expression levels of Rac1-GTP. EA during the maintenance phase reduced the density and maturity of dendritic spines of rats with SNL, increased the levels of srGAP3 and reduced the levels of Rac1-GTP, while srGAP3 siRNA and CN04 reversed the therapeutic effects of EA. These results suggest that dendritic spines have different manifestations in different stages of neuropathic pain and that EA may inhibit the abnormal dendritic spine remodeling by regulating the srGAP3/Rac1 signaling pathway to alleviate neuropathic pain.

Crop cultivation planning with fuzzy estimation using water wave optimization.

In a complex agricultural region, determine the appropriate crop for each plot of land to maximize the expected total profit is the key problem in cultivation management. However, many factors such as cost, yield, and selling price are typically uncertain, which causes an exact programming method impractical. In this paper, we present a problem of crop cultivation planning, where the uncertain factors are estimated as fuzzy parameters. We adapt an efficient evolutionary algorithm, water wave optimization (WWO), to solve this problem, where each solution is evaluated based on three metrics including the expected, optimistic and pessimistic values, the combination of which enables the algorithm to search credible solutions under uncertain conditions. Test results on a set of agricultural regions in East China showed that the solutions of our fuzzy optimization approach obtained significantly higher profits than those of non-fuzzy optimization methods based on only the expected values.

Predicting Demands of COVID-19 Prevention and Control Materials via Co-Evolutionary Transfer Learning.

The novel coronavirus pneumonia (COVID-19) has created great demands for medical resources. Determining these demands timely and accurately is critically important for the prevention and control of the pandemic. However, even if the infection rate has been estimated, the demands of many medical materials are still difficult to estimate due to their complex relationships with the infection rate and insufficient historical data. To alleviate the difficulties, we propose a co-evolutionary transfer learning (CETL) method for predicting the demands of a set of medical materials, which is important in COVID-19 prevention and control. CETL reuses material demand knowledge not only from other epidemics, such as severe acute respiratory syndrome (SARS) and bird flu but also from natural and manmade disasters. The knowledge or data of these related tasks can also be relatively few and imbalanced. In CETL, each prediction task is implemented by a fuzzy deep contractive autoencoder (CAE), and all prediction networks are cooperatively evolved, simultaneously using intrapopulation evolution to learn task-specific knowledge in each domain and using interpopulation evolution to learn common knowledge shared across the domains. Experimental results show that CETL achieves high prediction accuracies compared to selected state-of-the-art transfer learning and multitask learning models on datasets during two stages of COVID-19 spreading in China.

Integration of machine learning prediction and heuristic optimization for mask delivery in COVID-19.

The novel coronavirus pneumonia (COVID-19) has created huge demands for medical masks that need to be delivered to a lot of demand points to protect citizens. The efficiency of delivery is critical to the prevention and control of the epidemic. However, the huge demands for masks and massive number of demand points scattered make the problem highly complex. Moreover, the actual demands are often obtained late, and hence the time duration for solution calculation and mask delivery is often very limited. Based on our practical experience of medical mask delivery in response to COVID-19 in China, we present a hybrid machine learning and heuristic optimization method, which uses a deep learning model to predict the demand of each region, schedules first-echelon vehicles to pre-distribute the predicted number of masks from depot(s) to regional facilities in advance, reassigns demand points among different regions to balance the deviations of predicted demands from actual demands, and finally routes second-echelon vehicles to efficiently deliver masks to the demand points in each region. For the subproblems of demand point reassignment and two-batch routing whose complexities are significantly lower, we propose variable neighborhood tabu search heuristics to efficiently solve them. Application of the proposed method in emergency mask delivery in three megacities in China during the peak of COVID-19 demonstrated its significant performance advantages over other methods without pre-distribution or reassignment. We also discuss key success factors and lessons learned to facilitate the extension of our method to a wider range of problems.

Electroacupuncture inhibits dendritic spine remodeling through the srGAP3-Rac1 signaling pathway in rats with SNL

Previous studies have shown that peripheral nerve injury can lead to abnormal dendritic spine remodeling in spinal dorsal horn neurons. Inhibition of abnormal dendritic spine remodeling can relieve neuropathic pain. Electroacupuncture (EA) has a beneficial effect on the treatment of neuropathic pain, but the specific mechanism remains unclear. Evidence has shown that slit-robo GTPase activating protein 3 (srGAP3) and Rho GTPase (Rac1) play very important roles in dendritic spine remodeling. Here, we used srGAP3 siRNA and Rac1 activator CN04 to confirm the relationship between SrGAP3 and Rac1 and their roles in improving neuropathic pain with EA. Spinal nerve ligation (SNL) was used as the experimental model, and thermal withdrawal latency (TWL), mechanical withdrawal threshold (MWT), Western blotting, immunohistochemistry and Golgi-Cox staining were used to examine changes in behavioral performance, protein expression and dendritic spines. More dendritic spines and higher expression levels of srGAP3 were found in the initial phase of neuropathic pain. During the maintenance phase, dendritic spines were more mature, which was consistent with lower expression levels of srGAP3 and higher expression levels of Rac1-GTP. EA during the maintenance phase reduced the density and maturity of dendritic spines of rats with SNL, increased the levels of srGAP3 and reduced the levels of Rac1-GTP, while srGAP3 siRNA and CN04 reversed the therapeutic effects of EA. These results suggest that dendritic spines have different manifestations in different stages of neuropathic pain and that EA may inhibit the abnormal dendritic spine remodeling by regulating the srGAP3/Rac1 signaling pathway to alleviate neuropathic pain.

Photogenerated carrier dynamics at the B4C3/g-C3N4 interface.

Developing van der Waals (vdW) heterostructures is an excellent approach for optimizing exceptional optoelectronic and photocatalytic properties of materials; therefore, researching the interface dynamics of charge carriers at the two-dimensional vdW heterojunction is of great significance. In this work, we perform time-dependent ab initio non-adiabatic molecular dynamics simulations to study the dynamics of charge transfer at the B4C3/g-C3N4 heterostructure. The simulations show that the charge transfer between B4C3/g-C3N4 layers is mainly caused by the non-adiabatic mechanism. The non-adiabatic mechanism leads to a higher charge-transfer efficiency and slows down the process of interlayer electron-hole recombination, thereby promoting the separation of photogenerated electron-hole pairs. Our investigation provides essential insights into understanding the dynamics of charge transfer for the B4C3/g-C3N4 heterostructure, which provides guidance for photocatalytic water splitting and optoelectrical applications.

Electroacupuncture pre-treatment alleviates sepsis-induced cardiac inflammation and dysfunction by inhibiting the calpain-2/STAT3 pathway.

Electroacupuncture (EA) has both anti-inflammatory and cardio-protective effects. Activation of calpain pathway is involved in several myocardiopathy. In sepsis, the role of calpain-2-regulated STAT3 in cardio-protective mechanism of electroacupuncture remains unclear. In this study, we aimed to elucidate the mechanism by which electroacupuncture reduces cardiac inflammation and apoptosis and improves cardiac function during sepsis. Electroacupuncture pretreatment for 7 days was applied in septic cardiomyopathy model induced by lipopolysaccharide (LPS). lipopolysaccharide-induced sepsis was associated with a dramatically systemic inflammation and cardiac dysfunction, which was alleviated by electroacupuncture pre-treatment. Lipopolysaccharide resulted in increases of pro-inflammatory factors (TNF-α,IL1ßand IL-6) and apoptosis (TUNEL staining and BAX/Bcl2) via activation of calpain-2/STAT3 pathway.Electroacupuncture pre-treatment inhibited LPS-induced activation of cardiac calpain-2/STAT3 signalling and ameliorated inflammatory and apoptosis. Additionally, inhibition of calpain-2 expression using the corresponding siRNA decreased the Phosphorylation of STAT3,pro-inflammatory factors and apoptosis in lipopolysaccharide- treated cardiomyocytes, confirming that calpain-2 activated p-STAT3 participate in septic cardiomyopathy. Furthermore, suppression of STAT3 by stattic enhanced anti-inflammatory and anti-apoptosis effects of electroacupuncture. These findings reveal mechanisms of electroacupuncture preconditioning protection against cardiac inflammation and apoptosis in sepsis mouse via calpain-2/STAT3 pathway and may provide novel targets for clinical treatments of the sepsis-induced cardiac dysfunction.

[Application of Immune Checkpoint Inhibitors in EGFR Mutant 
Advanced Non-small Cell Lung Cancer].

In recent years, immune checkpoint inhibitors (ICIs) have greatly improved the survival rate of non-small cell lung cancer (NSCLC) patients without driver mutation. Compared with wild-type tumors, tumors with epidermal growth factor receptor (EGFR) mutations have greater heterogeneity in immune microenvironment characteristics such as programmed cell death ligand 1 (PD-L1) and tumor mutational burden (TMB). Whether ICIs is suitable for NSCLC patients with EGFR mutation has been controversial. Clinical studies have shown that immunomonotherapy has no significant effect on patients with EGFR mutant NSCLC. ICIs combined with chemotherapy and antiangiogenic drugs show good survival benefits. This paper overviews the clinical research and related mechanism of ICIs single drug or combination therapy inadvanced NSCLC patients with EGFR mutation.
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A robust multi-objective model for healthcare resource management and location planning during pandemics.

In this study, we consider the problem of healthcare resource management and location planning problem during the early stages of a pandemic/epidemic under demand uncertainty. Our main ambition is to improve the preparedness level and response effectiveness of healthcare authorities in fighting pandemics/epidemics by implementing analytical techniques. Building on lessons from the Chinese experience in the COVID-19 outbreak, we first develop a deterministic multi-objective mixed integer linear program (MILP) which determines the location and size of new pandemic hospitals (strategic level planning), periodic regional health resource re-allocations (tactical level planning) and daily patient-hospital assignments (operational level planning). Taking the forecasted number of cases along a planning horizon as an input, the model minimizes the weighted sum of the number of rejected patients, total travel distance, and installation cost of hospitals subject to real-world constraints and organizational rules. Next, accounting for the uncertainty in the spread speed of the disease, we employ an across scenario robust (ASR) model and reformulate the robust counterpart of the deterministic MILP. The ASR attains relatively more realistic solutions by considering multiple scenarios simultaneously while ensuring a predefined threshold of relative regret for the individual scenarios. Finally, we demonstrate the performance of proposed models on the case of Wuhan, China. Taking the 51 days worth of confirmed COVID-19 case data as an input, we solve both deterministic and robust models and discuss the impact of all three level decisions to the quality and performance of healthcare services during the pandemic. Our case study results show that although it is a challenging task to make strategic level decisions based on uncertain forecasted data, an immediate action can considerably improve the response effectiveness of healthcare authorities. Another important observation is that, the installation times of pandemic hospitals have significant impact on the system performance in fighting with the shortage of beds and facilities.

Water Treadmill Training Ameliorates Neurite Outgrowth Inhibition Associated with NGR/RhoA/ROCK by Inhibiting Astrocyte Activation following Spinal Cord Injury.

Spinal cord injury (SCI) often results in damage to or degeneration of axons. Crosstalk between astrocytes and neurons plays a pivotal role in neurite outgrowth following SCI. Rehabilitative training is a recognized method for the treatment of SCI, but the specific mechanism underlying its effect on axonal outgrowth in the central nervous system (CNS) has not yet been determined. A total of 190 adult male SD rats weighing 200-250 g were randomly divided into eight groups for use as animal models of SCI. Rats were subjected to water treadmill training (TT) for 7 or 14 d. The Basso-Beattie-Bresnahan (BBB) motor function scale, hematoxylin-eosin (HE) staining, Nissl staining, Western blotting, and immunofluorescence were used to measure tissue morphology and the degree of neurological deficit and to determine quantitative expression and accurate localization of the corresponding proteins. We found that TT decreased tissue structure damage and improved functional recovery. TT also promoted the regeneration of neurons and reduced SCI-induced apoptosis SCI around the lesion, as well as significantly increasing the expression of GAP43 and NF200 after SCI. In addition, TT significantly inhibited the injury-induced increase in the expression of proinflammatory factors. Moreover, TT reduced the activation of astrocytes and microglia, accompanied by the reduced expression of C3d and increased expression of S100A10. Finally, TT effectively reduced the level of chondroitin sulfate proteoglycan (CSPG) surrounding the lesion and inhibited the NGR/RhoA/ROCK signaling pathway in neurons after SCI. Overall, we found that TT played a novel role in recovery from SCI by promoting axonal outgrowth associated with NGR/RhoA/ROCK signaling by inhibiting astrocyte activation after SCI.

Witnessing localization of a quantum state via quantum speed limits in a driven avoided-level crossing system.

In this work, we investigate the witnessing of the localization of quantum states through quantum speed limits (QSLs) in a two-level driven avoided-level crossing system. As the characteristic natures of the localized quantum states, the QSL presents the periodic oscillations and coherence. The coherence partition of QSL is much bigger than the population partition of QSL. Our study gives us the possibilities to manipulate dynamics of quantum states locally by employing the coherent destruction of tunneling, which is significant in quantum information process. In addition, we analyze the effects of the rotating-wave approximation and the generalized Van Vleck approach on QSL and show that they wipe out the quantum coherence.

A Differential Evolution Algorithm With Adaptive Niching and K-Means Operation for Data Clustering.

Clustering, as an important part of data mining, is inherently a challenging problem. This article proposes a differential evolution algorithm with adaptive niching and k -means operation (denoted as DE_ANS_AKO) for partitional data clustering. Within the proposed algorithm, an adaptive niching scheme, which can dynamically adjust the size of each niche in the population, is devised and integrated to prevent premature convergence of evolutionary search, thus appropriately searching the space to identify the optimal or near-optimal solution. Furthermore, to improve the search efficiency, an adaptive k -means operation has been designed and employed at the niche level of population. The performance of the proposed algorithm has been evaluated on synthetic as well as real datasets and compared with related methods. The experimental results reveal that the proposed algorithm is able to reliably and efficiently deliver high quality clustering solutions and generally outperforms related methods implemented for comparisons.

Histone lysine methacrylation is a dynamic post-translational modification regulated by HAT1 and SIRT2.

Histone lysine crotonylation is a posttranslational modification with demonstrated functions in transcriptional regulation. Here we report the discovery of a new type of histone posttranslational modification, lysine methacrylation (Kmea), corresponding to a structural isomer of crotonyllysine. We validate the identity of this modification using diverse chemical approaches and further confirm the occurrence of this type of histone mark by pan specific and site-specific anti-methacryllysine antibodies. In total, we identify 27 Kmea modified histone sites in HeLa cells using affinity enrichment with a pan Kmea antibody and mass spectrometry. Subsequent biochemical studies show that histone Kmea is a dynamic mark, which is controlled by HAT1 as a methacryltransferase and SIRT2 as a de-methacrylase. Altogether, these investigations uncover a new type of enzyme-catalyzed histone modification and suggest that methacrylyl-CoA generating metabolism is part of a growing number of epigenome-associated metabolic pathways.

Quantum Speed Limit Quantified by the Changing Rate of Phase.

The quantum speed limit is important in determining the minimum evolution time of a quantum system, and thus is essential for quantum community. In this Letter, we derive a novel unified quantum speed limit bound for Hermitian and non-Hermitian quantum systems. The bound is quantified by the changing rate of phase of the quantum system, which represents the transmission mode of the quantum states over their evolution. The bound leads to further insights beyond the previous bounds on concrete evolution modes of the quantum system, such as horizontal or parallel transition or horizontal joining of the two quantum states in Hilbert space. The bound is linked to the feasibility of the evolutions of the state vectors, and provides a tighter upper bound. In addition, the generalized Margolus-Levitin bound is discussed.

[Research Progress of Fusion Genes RET in Non-small Cell Lung Cancer].

In the past 20 years, with the development of molecular biology, the treatment of non-small cell lung cancer (NSCLC) has been developing. Targeted therapy has improved the survival period of patients with positive mutation of tumor driver gene. More and more targets have been found gradually. Drugs targeting different driving genes have brought the treatment of NSCLC into a promising target era. Among the many driving genes of NSCLC, the fusion of transfection proto oncogene (RET) is the addition of the epidermal growth factor receptor (EGFR), analytic lymphama kinase (ALK) and c-ros oncogene 1-receptor tyrosine kinase (ROS1) are emerging targets. Targeted drugs for RET gene fusion have been constantly updated. Recently, new high selective RET inhibitors blu-667 and loxo-292 have made important breakthroughs. This paper will review the review of the fusion mutation of RET gene in NSCLC, the detection methods, clinicopathological characteristics, targeted treatment and the research progress after drug resistance.
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Multi-Objective Optimization of Integrated Civilian-Military Scheduling of Medical Supplies for Epidemic Prevention and Control.

In a large-scale epidemic, such as the novel coronavirus pneumonia (COVID-19), there is huge demand for a variety of medical supplies, such as medical masks, ventilators, and sickbeds. Resources from civilian medical services are often not sufficient for fully satisfying all of these demands. Resources from military medical services, which are normally reserved for military use, can be an effective supplement to these demands. In this paper, we formulate a problem of integrated civilian-military scheduling of medical supplies for epidemic prevention and control, the aim of which is to simultaneously maximize the overall satisfaction rate of the medical supplies and minimize the total scheduling cost, while keeping a minimum ratio of medical supplies reservation for military use. We propose a multi-objective water wave optimization (WWO) algorithm in order to efficiently solve this problem. Computational results on a set of problem instances constructed based on real COVID-19 data demonstrate the effectiveness of the proposed method.

Anomalously Low Dielectric Constant of Ordered Interfacial Water.

Despite considerable effort, the dielectric constant of interfacial water at solid surfaces is still not fully understood, thus hindering our understanding of the ubiquitous physical interactions in many materials and biological surfaces. In this study, we used molecular dynamics simulations to show that the parallel dielectric constant at the solid/water interface depends on solid-water interactions as well as the interfacial water structure on various solid crystal faces. In particular, ordered water structures can lead to a significant reduction (∼44%) in the parallel dielectric constant at the solid/water interface compared with that of bulk water. This sharp decrease in the parallel dielectric constant can be attributed to the specific antiferroelectric ordered structure of interfacial water molecules, which significantly suppresses the amplitude of the dipolar fluctuation associated with both the number of hydrogen bonds and the degree of order of interfacial water.