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Despite extensive research on astrocytic Ca2+ in synaptic transmission, its contribution to the modulation of sensory transmission during different brain states remains largely unknown. Here, by using two-photon microscopy and whole-cell recordings, we show two distinct astrocytic Ca2+ signals in the murine barrel cortex: a small, long-lasting Ca2+ increase during sleep and a large, widespread but short-lasting Ca2+ spike when aroused. The large Ca2+ wave in aroused mice was inositol trisphosphate (IP3)-dependent, evoked by the locus coeruleus-norepinephrine system, and enhanced sensory input, contributing to reliable sensory transmission. However, the small Ca2+ transient was IP3-independent and contributed to decreased extracellular K+, hyperpolarization of the neurons, and suppression of sensory transmission. These events respond to different pharmacological inputs and contribute to distinct sleep and arousal functions by modulating the efficacy of sensory transmission. Together, our data demonstrate an important function for astrocytes in sleep and arousal states via astrocytic Ca2+ waves.

Evidence suggests that complex interactions between the immune system and brain have important etiological and therapeutic implications in schizophrenia. However, the detailed cellular and molecular basis of immune dysfunction in schizophrenia remains poorly characterized. To better understand the immune changes and molecular pathways, we systemically compared the cytokine responses of peripheral blood mononuclear cells (PBMCs) derived from patients with schizophrenia and controls against bacterial, fungal, and purified microbial ligands, and identified aberrant cytokine response patterns to various pathogens, as well as reduced cytokine production after stimulation with muramyl dipeptide (MDP) in schizophrenia. Subsequently, we performed single-cell RNA sequencing on unstimulated and stimulated PBMCs from patients and controls and revealed widespread suppression of antiviral and inflammatory programs as well as impaired chemokine/cytokine-receptor interaction networks in various immune cell subpopulations of schizophrenic patients after MDP stimulation. Moreover, serum MDP levels were elevated in these patients and correlated with the course of the disease, suggesting increased bacterial translocation along with disease progression. In vitro assays revealed that MDP pretreatment altered the functional response of normal PBMCs to its re-stimulation, which partially recapitulated the impaired immune function in schizophrenia. In conclusion, we delineated the molecular and cellular landscape of impaired immune function in schizophrenia, and proposed a mutual interplay between innate immune impairment, reduced pathogen clearance, increased MDP translocation along schizophrenia development, and blunted innate immune response. These findings provide new insights into the pathogenic mechanisms that drive systemic immune activation, neuroinflammation, and brain abnormalities in schizophrenia.

Since the first outbreak in December 2019, SARS-CoV-2 has been constantly evolving and five variants have been classified as Variant of Concern (VOC) by the World Health Organization (WHO). These VOCs were found to enhance transmission and/or decrease neutralization capabilities of monoclonal antibodies and vaccine-induced antibodies. Here, we successfully designed and produced a recombinant COVID-19 vaccine in CHO cells at a high yield. The vaccine antigen contains four hot spot substitutions, K417N, E484K, N501Y and D614G, based on a prefusion-stabilized spike trimer of SARS-CoV-2 (S-6P) and formulated with an Alum/CpG 7909 dual adjuvant system. Results of immunogenicity studies showed that the variant vaccine elicited robust cross-neutralizing antibody responses against SARS-CoV-2 prototype (Wuhan) strain and all 5 VOCs. It further, stimulated a TH1 (T Helper type 1) cytokine profile and substantial CD4+ T cell responses in BALB/c mice and rhesus macaques were recorded. Protective efficacy of the vaccine candidate was evaluated in hamster and rhesus macaque models of SARS-CoV-2. In Golden Syrian hamsters challenged with Beta or Delta strains, the vaccine candidate reduced the viral loads in nasal turbinates and lung tissues, accompanied by significant weight gain and relieved inflammation in the lungs. In rhesus macaque challenged with prototype SARS-CoV-2, the vaccine candidate decreased viral shedding in throat, anal, blood swabs over time, reduced viral loads of bronchus and lung tissue, and effectively relieved the lung pathological inflammatory response. Together, our data demonstrated the broadly neutralizing activity and efficacy of the variant vaccine against both prototype and current VOCs of SARS-CoV-2, justifying further clinical development.

The complex micro-slip phenomenon of the contact interface will lead to the nonlinear stiffness of the connection structure, as well as the structural damping and energy dissipation. As the most important connection structure of the combination rotor, the mechanical properties of bolted flange joint interface are needed in the dynamic analysis of the combined rotor. Therefore, it is urgent to model and test the friction contact interface in the nonlinear dynamic analysis of rotor. In this paper, two sets of mechanical characteristics test system were built to test the dynamic parameters of tangential and bending directions of the bolted flange joint interface. Then, the mechanical behavior and the change regularities of dynamics parameters were studied under different external excitation, bolt distribution and tightening torque. The results show that once the bolt preload is above the rated torque, stiffness softening behavior is not significant; and then the tangential stiffness of the joint interface tends to be stable, with the variation range of 8.08∼8.96e8 N/m; the equivalent bending stiffness coefficient is about 3.38∼3.83e6 N·m/rad. With the decrease of bolt preload, the external excitation and the number of bolts have a significant effect on the stiffness reduction of the joint. Finally, the change interval of the dynamics parameters of the interface obtained by the experiment provide basis for the uncertainty dynamic analysis and optimization of the rotor.

The rock joint roughness greatly affects the mechanical behaviors and permeability characteristics of rock mass. To accurately and effectively estimate the roughness of rock joints, an appropriate sampling interval is required to be specified during the point cloud collection using laser scanning systems and the roughness coefficient calculation. Firstly, seventeen point clouds of rock joints with sampling size ranging from 60×60 to 2000×2000 mm was collected using a terrestrial laser scanner in the field to investigate the effect of sampling size on the selection of the appropriate sampling interval. Then, a portable laser scanner was employed to acquire the dense point clouds of thirteen small-scale rock joint specimens, which have various roughness levels, to assess the influence of roughness level on the appropriate sampling interval. Furthermore, fitting analyses were performed to establish relationships between the appropriate sampling interval vs. sampling size and the appropriate sampling interval vs. roughness level, respectively. The results show that the curves of sampling interval vs. roughness coefficient followed a power distribution, and the inflection point with the maximum curvature could be regarded as the appropriate sampling interval; the appropriate sampling interval increased with the sampling size, while a negative correlation between the appropriate sampling interval and roughness level was observed. To facilitate the application of findings into practical engineering, a simplified workflow was provided to determine the appropriate sampling interval: 0.015×sampling size and 0.03×sampling size were recommended to be considered as appropriate sampling intervals for the rock joints with high-level and low-level roughness, respectively.

It has been reported that schizophrenia (SCZ) and inflammatory bowel disease (IBD) are related. However, whether there is a bidirectional interaction between them remains unclear. The aim of this study was to conduct a bidirectional Mendelian randomization (MR) analysis to elucidate the causal relationship between SCZ and IBD and its subtypes, including Crohn’s disease (CD) and ulcerative colitis (UC). Single-nucleotide polymorphisms (SNPs) extracted from the summary data of genome-wide association studies were used as genetic instruments. MR was performed using the inverse-variance-weighted method. The MR-Egger and weighted median methods were used for sensitivity analyses. Analysis using 70 SNPs as genetic instruments showed that SCZ was associated with an increased risk of IBD (OR = 1.14, 95% CI: 1.09–1.20, P = 9.21 × 10−8), CD (OR = 1.16, 95% CI: 1.07–1.25, P = 1.42 × 10−4), and UC (OR = 1.14, 95% CI: 1.07–1.21, P = 2.72 × 10−5). The results of the sensitivity analyses were robust and no evidence of pleiotropy was observed. Bidirectional MR analyses showed no causal effects of IBD, CD, or UC on SCZ. This study suggests that SCZ has causal effects on IBD and its subtypes, whereas IBD has no effect on SCZ. Brain-gut axis interactions may help clarify the causal relationship between SCZ and IBD. However, further studies are needed to elucidate the biological mechanisms behind the brain-gut interactions.

Accumulating evidence suggests that gut microbiota plays a role in the pathogenesis of schizophrenia via the microbiota-gut-brain axis. This study sought to investigate whether transplantation of fecal microbiota from drug-free patients with schizophrenia into specific pathogen-free mice could cause schizophrenia-like behavioral abnormalities. The results revealed that transplantation of fecal microbiota from schizophrenic patients into antibiotic-treated mice caused behavioral abnormalities such as psychomotor hyperactivity, impaired learning and memory in the recipient animals. These mice also showed elevation of the kynurenine-kynurenic acid pathway of tryptophan degradation in both periphery and brain, as well as increased basal extracellular dopamine in prefrontal cortex and 5-hydroxytryptamine in hippocampus, compared with their counterparts receiving feces from healthy controls. Furthermore, colonic luminal filtrates from the mice transplanted with patients' fecal microbiota increased both kynurenic acid synthesis and kynurenine aminotransferase II activity in cultured hepatocytes and forebrain cortical slices. Sixty species of donor-derived bacteria showed significant difference between the mice colonized with the patients' and the controls' fecal microbiota, highlighting 78 differentially enriched functional modules including tryptophan biosynthesis function. In conclusion, our study suggests that the abnormalities in the composition of gut microbiota contribute to the pathogenesis of schizophrenia partially through the manipulation of tryptophan-kynurenine metabolism.

Landslide is one of the most common geological hazards, which causes a large number of property damage and loss of life in China every year. This case study was a 330-kV transmission line project located in Longnan City, Gansu Province, China, which is known as an area prone to landslides. A hybrid model of fractal theory-information value-random forests algorithm (FT-IV-RF) was proposed to evaluate the landslide susceptibility. First, sixteen landslide conditioning factors and pre-existing landslide events were selected as the initial evaluation indexes of landslide susceptibility from four datasets (geology, topography, climate and environment, and landslide inventory). Second, Pearson coefficient and sensitivity analyses were conducted to extract ten landslide conditioning factors with small correlation and large contribution to landslide occurrence from sixteen factors. Third, the weight of each class for a given factor were determined by using a combination of fractal theory and information value algorithms, which was regarded as one of input parameters and used to select the training samples in the random forest model. Four, k-means clustering was performed to classify the landslide susceptibility indices, which were predicted using the random forest model, into five levels to produce the landslide susceptibility map of the study area. Furthermore, the proposed model of FT-IV-RF model was validated by comparing with results obtained using information value (IV), back-propagation neural network (BPNN), and fuzzy logic (FL) models. Good agreements on the susceptibility estimation were observed among four models, and the hybrid model had the largest area under the curve (AUC) value of 0.996, indicating a good performance of the proposed hybrid model.

Background Prophylactic vaccines are critical in preventing hand, foot, and mouth disease (HFMD) primarily caused by human enterovirus 71 (EV71) infection. Children aged less than 5 years are especially susceptible to EV71 infections. In addition to the development of vaccines containing the inactivated virus, those containing virus-like particles (VLPs) with repeated antigens also constitute an effective preventive strategy for EV71 infections, with safety and productivity advantages. We previously developed a fusion protein composed with truncated peptides of the EV71 capsid protein, which assembled into spherical particles. This study aimed to assess the immunoprotective effects of this fusion protein as a vaccine candidate in a mouse model of EV71 infection. Methods To evaluate the protective effect of fusion protein vaccine candidate, neonatal mice born by immunized female mice, as well as normal neonatal mice immunized twice were infected with EV71 virus. Whereafter, the survival rates, clinical scores and viral loads were measured. Results The high dosage and booster immunization helped induce specific serum antibodies with high neutralization titers, which were transferred to neonatal mice, thereby facilitating effective resistance towards EV71 infection. An active immune response was also observed in neonatal mice which generated following immunization. Conclusions The present results suggest that this fusion protein is a suitable vaccine candidate in treating EV71 infections.

Over the last decade, Fengcheng oil field rich in heavy oil geological reserves has had a broad prospect of exploration. The reservoirs are mainly composed of high porosity, high permeability sandstone and conglomerate in study area. The reservoir characteristics led to poor fluid and gas injection causing ground surface deformation with the injection of gas and fluid and threatened the safety of nearby construction facilities. Interferometric Synthetic Aperture Radar (InSAR) technology has been used to identify ground surface deformation with high precision, which is widely used in various fields. This paper adopted Small Baseline Subset InSAR (SBAS-InSAR) method to monitor oil field for the period of February 2007 to September 2010. In this study, the Fengcheng oil field in Xinjiang served as an example; we measured subsurface fluid and gas injection-induced ground surface deformation by SBAS-InSAR technique and investigated the causes of observed deformation. The results showed significant uplift over Fengcheng oil field and testified the feasibility of SBAS-InSAR method. The Phased Arrary L-band Synthetic Aperture Radar (PALSAR) datasets outcome revealed ground surface maximum cumulative uplift for 4 years was 40 cm in the line of sight (LOS) direction, and annual average deformation rates were ranging from − 80 to 120 mm/year. Further, the time series analysis based on monitoring results found that the causes of ground surface uplift were related to the increase in pore pressure under the reservoir, and the surface deformation area corresponded to the production well position of study area. Therefore, InSAR technique is an essential tool for the ground surface deformation monitoring due to fluid and gas injection in heavy oil field, ensuring the safety of personnel and property.

The focus of the research presented here is the development of an efficient analytical model for the time-domain simulation of the evolution of a train of a three-dimensional steep random waves and its associated flow. Of particular interest here is the development of a tool that not only accurately predicts the surface elevation history of this wave train, but also the kinematics within the waves, particularly near the free surface. Fenton (Advances in coastal and ocean engineering, vol 5, World Scientific, Singapore, pp 241–324, 1999) reviews the rich literature of various computational models for water waves and is divided between analytical approaches that develop systems of equations to describe the evolution of waves in space and time, and computational approaches such as CFD (which will not be the focus here). What is required to analyze properly the practical ocean engineering problem described in the motivation below is a theory that predicts the three-dimensional evolution of waves that simultaneously has four essential characteristics: deep-water, random broadband seaways, steep waves (close to breaking), and demonstrated accuracy in both wave shape and near-surface wave kinematics. The number and variety of theories that satisfy some but not all of these characteristics is too voluminous to reference here; dynamic theories that exhibit the confluence of all four characteristics are apparently nonexistent. The intent of this paper is to make a step in the direction of filling this void by extending the Green–Naghdi theory of deep-water waves. It is shown that higher level GN models using distributed directors do have a bandwidth that is significantly larger than former GN models and have the same computational effort as using the traditional directors. The bandwidths achieved with the new approach are large enough to be useful in the context of many ocean engineering problems. Applications of these models to random wave situations will be reported in a subsequent article.

The effects of chloride concentration, applied potential and time on the passive film of Cu-Zn-Ni ternary alloy in alkaline solution were systematically investigated using potentiodynamic and potentiostatic polarizations, electrochemical impedance spectroscopy, Mott–Schottky analysis, laser confocal microscopy, atomic force microscopy and x-ray photoelectron spectroscopy. Results showed that the pitting potential decreased as a linear function of log( $$ a_{{{\text{Cl}}^{ - } }} $$ ), and the size of pits extended faster in the horizontal direction than in the vertical direction. The passive oxide film formed on Cu-Zn-Ni alloy mainly exhibited p-type semiconductor behavior, which was consistent with cuprous and nickel oxide, the main components in the film. The density of cation vacancy (approximately 1020-1021 cm−3) increased with potentiostatic time but reduced by the increasing potentials. The kinetics of passive film growth followed a parabolic law D = m * tn, where m is a constant considered as the initial growth rate and n is the time exponent. Subsequent to the formation of a compact and coherent passive film at higher potential, it was hard for an ion to migrate or for an aggressive ion to penetrate, which indicated better corrosion resistance for passive film formed under higher potential.

Landslides cause damages to land and infrastructure and pose serious threat to human survival. To prepare a landslide susceptibility map of the region in Longnan, City Gansu Province, with a 330-kV transmission line, 10 parameters were selected by correlation analysis and sensitivity analysis from initial 18 and five different methods were used, including analytical hierarchy process (AHP), information value (IV), fractal theory (FT), back propagation neural network (BPNN), support vector machine (SVM). The susceptibility maps were validated through receiver operating characteristic (ROC) and cumulative landslides percentage curves based on 77 existing landslide events. The results indicate that BPNN and SVM model are most accurate, time-saving and easily implemented. All of the five methods accurately predict the spatial distribution of landslides and can be well applied to landslide susceptibility mapping. What needs to be emphasized is that the machine learning methods have the advantages of high efficiency, accurate prediction, time-saving, convenient implementation, which are relatively new and better evaluation models of susceptibility.

An innovative hydrodynamic theory and numerical model were developed to help improve the efficiency, accuracy, and convergence of the numerical prediction of wave drift forces on two side-by-side deepwater floating bodies. The wave drift forces were expressed by the double integration of source strength and the corresponding Green function on the body surface, which is consistent with the far field formula based on momentum conservation and sharing the advantage of near field calculations providing the drift force on each body. Numerical results were validated through comparing the general far field model and pressure integral model, as well as the middle field model developed using the software HydroStar.

In this work, Green-Naghdi (GN) equations with general weight functions were derived in a simple way. A wave-absorbing beach was also considered in the general GN equations. A numerical solution for a level higher than 4 was not feasible in the past with the original GN equations. The GN equations for shallow water waves were simplified here, which make the application of high level (higher than 4) equations feasible. The linear dispersion relationships of the first seven levels were presented. The accuracy of dispersion relationships increased as the level increased. Level 7 GN equations are capable of simulating waves out to wave ve number times depth kd < 26. Numerical simulation of nonlinear water waves was performed by use of Level 5 and 7 GN equations, which will be presented in the next paper.

Green-Naghdi (G-N) theory is a fully nonlinear theory for water waves. Some researchers call it a fully nonlinear Boussinesq model. Different degrees of complexity of G-N theory are distinguished by “levels” where the higher the level, the more complicated and presumably more accurate the theory is. In the research presented here a comparison was made between two different levels of G-N theory, specifically level II and level III G-N restricted theories. A linear analytical solution for level III G-N restricted theory was given. Waves on a planar beach and shoaling waves were both simulated with these two G-N theories. It was shown for the first time that level III G-N restricted theory can also be used to predict fluid velocity in shallow water. A level III G-N restricted theory is recommended instead of a level II G-N restricted theory when simulating fully nonlinear shallow water waves.

Whether grazing response of species abundance can be predicted by plant functional trait remains a challenge untested in a specific ecosystem. We measured species abundance and relevant functional traits for 30 common component species in a moderately grazed and a control community over 3 years (2005, 2006 and 2007) in a Kobresia capillifolia dominated alpine meadow on the Tibetan Plateau. Our objective was to examine species response to grazing and to test the relationship between the response of species abundance and functional traits in grazed and control habitats. Our results showed: i) in terms of species relative abundance and saturated height (the maximum height of an adult individual), most component species significantly decrease in response to moderate grazing and the effect differed among species and between functional groups. ii) The response of species abundance was significantly negatively correlated with saturated height, but not correlated with specific leaf area or seed size. We concluded that the response direction of species abundance to grazing can be predicted by functional traits, whereas it is a weak predictor of the extent of grazing response in species abundance.

Platinum has been one of the highly needed mineral resources in China. The geochemical exploration at two survey scales was applied in telescoping ore targets for the first time in Eastern Yunnan Pt geochemical province that was delineated using Pt data from flood plain sediments with extra-low sampling density. Our study was based on the delineations and assessments of both regional and local Pt anomalies using the Pt data by analyzing with C-OES the composite samples with two sampling densities. The composite samples were obtained by recomposing at two sampling densities the original stream sediment samples collected by the National Geochemical Mapping Project. Semi-variograms were used to quantitatively describe the variability of Pt anomalies and further analyze the factors controlling the variability. Pt resource potentials of both the regional Pt anomalies and the local Pt anomalies in the study area were estimated based on the geochemical block methods, respectively. It comes to the conclusions as follows. (1) From the regional to local Pt anomaly, the factors controlling their variability from the deep seated faults-basalts turn into the basalts-branch faults, which suggest that Semi-variograms could identify the geological factors controlling the variability of the Pt anomalies identified by the Pt data from the stream sediments with different sampling densities. (2) There exist two types of Pt anomalies in the study area. One is those displaying at sampling densities, and its average Pt concentration significantly increases with sampling density increasing. The other is getting weaker and/or disappears with sampling density increasing. This shows that TOTGEMS could gradually eliminate non-ore anomalies and keep ore anomalies. (3) The average Pt concentration of the local Pt anomaly blocks delineated using Pt data from stream sediments with sampling density of one composite per 16 km2 is twice as much as that of the regional Pt anomaly blocks delineated using Pt data from stream sediments with sampling density of one composite per 64 km2. The Pt resource amount of the local Pt anomaly blocks is 60% of the regional anomaly blocks, but the area of the former is just 35% of the latter, which suggests that the Pt resource amount is mainly concentrated in its local anomalies, and that TOTGEMS has a good exploration function that efficiently approaches ore targets.