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We conducted a proteomic analysis using mass spectrometry to identify and validate protein biomarkers for accurately predicting recurrence risk in gastrointestinal stromal tumors (GIST) patients, focusing on differentially expressed proteins in metastatic versus primary GIST tissues. We selected five biomarkers—GPX4, RBM4, TPM3, PFKFB2, and PGAM5—and validated their expressions in primary tumors of recurrent and non-recurrent GIST patients via immunohistochemistry. Our analysis of the association between these biomarkers with recurrence-free survival (RFS) and overall survival (OS), along with their interrelationships, revealed that immunohistochemistry confirmed significantly higher expressions of these biomarkers in primary GIST tissues of recurrent patients. Kaplan-Meier survival analysis showed that high expressions of GPX4, RBM4, TPM3, PFKFB2, and PGAM5 correlated with lower RFS, and GPX4 and RBM4 with lower OS. All biomarker pairs showed positive associations, with high expressions correlating with increased recurrence rates, and GPX4 and RBM4 with higher mortality rates. In conclusion, the biomarkers GPX4, RBM4, TPM3, PFKFB2, and PGAM5 are clinically relevant for predicting GIST recurrence, with their high expressions in primary tumors linked to poorer RFS and OS. They serve as potential prognostic indicators, enabling early treatment and improved outcomes. The observed interrelationships among these biomarkers further validate their accuracy in predicting GIST recurrence.

The issue of whether CoCrFeNi is a single-phase or dual-phase high-entropy alloy (HEA) has long been in dispute. In this study, CoCrFeNi has been verified to be a dual-phase HEA composed of dendritic phases with an FCC structure and inter-dendritic phases with a BCC structure. The BCC phases within inter-dendritic regions are identified as Cr3O oxides which form inevitably under the arc-melting process. Undercooling treatment under a strong magnetic field can regulate the composition and precipitation of the BCC phase, refine the grain size, and enhance the solid solubility, consequently, the mechanical performances of CoCrFeNi HEA are effectively enhanced.

Abstract Background Gastric cancer (GC) remains a malignant tumor with high morbidity and mortality, accounting for approximately 1,080,000 diagnosed cases and 770,000 deaths worldwide annually. Disulfidptosis, characterized by the stress-induced abnormal accumulation of disulfide, is a recently identified form of programmed cell death. Substantial studies have demonstrated the significant influence of immune clearance on tumor progression. Therefore, we aimed to explore the intrinsic correlations between disulfidptosis and immune-related genes (IRGs) in GC, as well as the potential value of disulfidptosis-related immune genes (DRIGs) as biomarkers. Methods This study incorporated the single-cell RNA sequencing (scRNA-seq) dataset GSE183904 and transcriptome RNA sequencing of GC from the TCGA database. Disulfidptosis-related genes (DRGs) and IRGs were derived from the representative literature on both cell disulfidptosis and immunity. The expression and distribution of DRGs were investigated at the single-cell level in different GC cell types. Pearson correlation analysis was used to identify the IRGs closely related to disulfidptosis. The prognostic signature of DRIGs was established using Cox and LASSO analyses. We then analyzed and evaluated the differences in long-term prognosis, Gene Set Enrichment Analysis (GSEA), immune infiltration, mutation profile, CD274 expression, and response to chemotherapeutic drugs between the two groups. A tissue array containing 63 paired GC specimens was used to verify the expression of 4 DRIGs and disulfidptosis regulator SLC7A11 through immunohistochemistry staining. Results The scRNA-seq analysis found that SLC7A11, SLC3A2, RPN1 and NCKAP1 were enriched in specific cell types and closely related to immune infiltration. Four DIRGs (GLA, HIF-1α, VPS35 and CDC37) were successfully identified to establish a signature to potently predict the survival time of GC patients. Patients with high risk scores generally experienced worse prognoses and exhibited greater resistant to classical chemotherapy drugs. Furthermore, the expression of GLA, HIF-1α, VPS35, CDC37 and SLC7A11 were elevated in GC tissues. A high expression of GLA, HIF-1α, VPS35 or CDC37 was associated with more advanced clinical stage of GC and increased SLC7A11 expression. Conclusion Current study first highlights the potential value of DRIGs as biomarkers in GC. We successfully constructed a robust model incorporating four DRIGs to accurately predict the survival time and clinicopathological characteristics of GC patients.

Abstract Background and purpose Ferroptosis is a form of regulated cell death characterized by iron-dependent lipid peroxidation. Its role in cancer metastasis remains unclear. In this study, we aimed to investigate the potential involvement of ferroptosis in gastric cancer (GC) metastasis. Methods GC cells (AGS, MKN45, HGC27) were used to explore the role of ferroptosis in single and clustered cells with extracellular matrix (ECM) detachment in vitro. We overexpressed glutathione peroxidase 4 (GPX4) to inhibit ferroptosis and assessed the changes in cell proliferation, migration, invasion, and epithelial-mesenchymal transition (EMT). Then tumor tissues from 54 GC patients with and without lymphatic metastasis were collected for immunohistochemical staining to investigate the expression of ferroptosis and EMT markers. Finally, Kaplan–Meier survival curves were used to investigate the relationship between overall survival and expression of GPX4 in 178 GC patients. Results Detached single cells had lower viability than adherent cells, but cell clustering improved their survival under matrix-detached conditions. Detached single cells exhibited an induction of iron-dependent reactive oxygen species (ROS) accumulation, glutathione (GSH) depletion, lipid peroxidation, upregulation of ACSL4, TFRC and HO-1, increased iron levels, and changes in mitochondrial morphology. Opposite effects were observed in detached clustered cells, including the upregulation of the ferroptosis suppressors GPX4 and SLC7A11. Overexpression of GPX4 inhibited ferroptosis and promoted GC cell proliferation, migration, invasion, and EMT. Immunohistochemical analysis of tumor tissues from GC patients indicated that lymphatic metastasis was associated with higher potential for ferroptosis inhibition and EMT induction. Finally, Kaplan–Meier survival curves demonstrated a significant decrease in overall survival among GC patients with high GPX4 expression. Conclusions Our study provides the first evidence that inhibition of ferroptosis is a crucial mechanism promoting GC metastasis. GPX4 may be a valuable prognostic factor for GC patients. These findings suggest that targeting ferroptosis inhibition may be a promising strategy for GC patients with metastatic potential. Trial registration The ethical approval code of this study in Institutional Review Board of Peking Union Medical College Hospital is No: K1447.

Abstract Smoking is the leading risk factor for chronic obstructive pulmonary disease (COPD) worldwide, yet many people who never smoke develop COPD. We perform a longitudinal analysis of COPD in the UK Biobank to derive and validate the Socioeconomic and Environmental Risk Score which captures additive and cumulative environmental, behavioral, and socioeconomic exposure risks beyond tobacco smoking. The Socioeconomic and Environmental Risk Score is more predictive of COPD than smoking status and pack-years. Individuals in the highest decile of the risk score have a greater risk for incident COPD compared to the remaining population. Never smokers in the highest decile of exposure risk are more likely to develop COPD than previous and current smokers in the lowest decile. In general, the prediction accuracy of the Social and Environmental Risk Score is lower in non-European populations. While smoking status is often considered in screening COPD, our finding highlights the importance of other non-smoking environmental and socioeconomic variables.

The relationship between the local structures and the thermodynamic properties of metallic liquids has been a fundamental issue, which significantly impacts the comprehensive performances of metallic materials. The temperature-induced structure evolution in CoxBy alloy liquids, involving CoB, Co2B, Co3B, and Co23B6, was investigated using ab initio molecular dynamics simulations. The results show that the clusters of icosahedral-like polyhedrons are found predominantly in all alloys at low temperature, while the heating induces the decrease in ideal icosahedral and the increase in defected icosahedral. At high temperature, the polyhedron clusters decrease significantly and the ideal icosahedra transforms into smaller short-range polyhedrons, signifying the temperature-induced chemical structure change from long-range to short-range ordering. The aggregation of B atoms at high temperature is confirmed by atomic configuration, charge density, and B-centered Voronoi polyhedrons, and the α-Co single phase is observed below 1600 K. This study is helpful for understanding the local structure variability in eutectic Co-B alloys and guiding solidification path in theory.

BackgroundColorectal cancer (CRC) is one of the most common malignant tumors primarily affecting individuals over the age of 50 years. Recent studies have suggested that the dysbiosis of the gut microbiota, a community of microorganisms in the human gut, is closely associated with the occurrence and development of CRC. Additionally, inflammatory factors (IFs) have also been reported to play a significant role in the development of CRC. However, the causal relationships between the gut microbiota, IFs, and CRC remain unclear.MethodsIn this study, we performed Mendelian randomization (MR) analysis using publicly available genome-wide association study (GWAS) data to explore the causal relationship between the gut microbiota, IFs, and CRC. The gut microbiota GWAS data were obtained from the MiBioGen study, while the IFs GWAS data were derived from the comprehensive analysis of three independent cohorts. Causal relationship analysis was conducted using appropriate instrumental variables (IVs) and statistical models.ResultsMR analysis of the gut microbiota and CRC revealed a negative correlation between the Lachnospiraceae species in the gut and CRC risk, while a positive correlation was observed between Porphyromonadaceae species, Lachnospiraceae UCG010 genus, Lachnospira genus, and Sellimonas genus in the gut, and CRC risk. Additionally, we observed a causal relationship between IL-10 and CRC risk. These findings suggest that the dysbiosis of the gut microbiota might be associated with an increased risk of CRC and that specific bacterial groups may play a crucial role in the occurrence and development of CRC.ConclusionUsing MR analysis, this study revealed the causal relationships between the gut microbiota, IFs, and CRC. The negative correlation between the Lachnospiraceae species in the gut and CRC risk, as well as the causal relationship between IL-10 and CRC, provide important clues for the potential roles of gut microbiota regulation and inflammatory factor control in the prevention and treatment of CRC.

Isobam is widely used for fabricating ceramics through spontaneous gelation and has attracted considerable interest. However, the disadvantage of the Isobam system is the low gelation strength. The effects of suitable additives and the mechanism by which they effectively enhance the green body strength and the rheological behavior of an aluminum nitride (AlN) slurry with 50 vol% solid loading were investigated using polyethyleneimine (PEI), hydantoin epoxy resin, and trimethylolpropane triglycidyl ether (TMPGE). Results showed that the additives acted as both dispersants and cross-linkers in the AlN suspension using the Isobam gelling system. The flexural strength of the AlN green body increased by 42%, 204%, and 268% with the addition of 1 wt% PEI, 1 wt% hydantoin epoxy resin, and 0.5 wt% TMPGE, respectively. After sintering at 1700 °C, the AlN ceramic with 0.5 wt% TMPGE had flexural strength and thermal conductivity of 235 MPa and 166.44 W/(m·K), respectively, showing superior performance to the ceramics without additives.

In this study, ternary Cu52Co24Fe24 immiscible alloys are prepared with varying undercoolings and under a high magnetic field. The microstructure evolution and properties of the alloys are investigated. The temperature range of the immiscible gap is determined using CALPHAD. According to the excess Gibbs free energy of liquid, the addition of Fe promotes the demixing tendency of the Cu–Co–Fe ternary system during solidification. With the application of a magnetic field, the (Fe, Co)-rich phases transform from a globular shape to an elongated form along the direction of the magnetic field during solidification, which is due to the existence of the counteracting behavior of the interparticle magnetic dipole-dipole force at the critical droplet size. Under a high magnetic field, the obtained samples had a more dispersed minority phase, higher microhardness and better conductivity. However, the saturation magnetization of the samples with large undercooling decreases with increasing magnetic field due to the suppression of the phase separation behavior under a high magnetic field. This study proposes a novel technology for preparing immiscible alloys with excellent properties by applying a superimposed magnetic field during solidification.

Yantai is a traditional region of marine economy. Marine ranch is the basic unit of the industry. The new generation of marine engineering equipment provides the conditions, as well as the foundation, for the value chain innovation of local marine ranching. It is significant to study and explore the innovation mechanism of the value chain to enhance the competitive advantage of Yantai marine ranches. In this paper, two typical marine ranches in Yantai area were selected as the research objects. Through on the spot interviews, visits and relevant web pages, the survey data were obtained. The qualitative research method of "grounded theory" was used to encode the data and test the theoretical saturation. The logical framework describing the innovation mechanism of the value chain was deduced. Furtherly, with the framework, two selected case ranches were analyzed. The conclusion was: the innovation of the value chain of the case ranch was triggered by both internal and external conditions; innovation knowledge came from the internal and external technical knowledge or management knowledge of the enterprise, and was often the result of the integration of internal and external knowledge; new knowledge was organically integrated into value chain activities, forming new products and processes, and realizing value chain innovation; value chain innovation had produced economic, social and ecological effects.

Over the past four decades, obesity in children of all ages has increased worldwide, which has intensified the search for innovative intervention strategies. Serious games, a youth-friendly form of intervention designed with educational or behavioral goals, are emerging as a potential solution to this health challenge. To analyze the effectiveness of serious games in improving body composition, physical activity, and dietary change, we performed a systematic review and meta-analysis of randomized controlled trials (RCTs) from PubMed, Web of Science, EMBASE, and Scopus databases. Pooled standardized mean differences (SMD) were calculated for 20 studies (n = 2238 the intervention group; n = 1983 in the control group) using random-effect models. The intervention group demonstrated a slightly better, although non-significant, body composition score, with a pooled SMD of −0.26 (95% CI: −0.61 to 0.09). The pooled effect tends to be stronger with longer duration of intervention (−0.40 [95% CI: −0.96, 0.16] for >3 months vs. −0.02 [95% CI: −0.33, 0.30] for ≤3 months), although the difference was not statistically significant (p-difference = 0.24). As for the specific pathways leading to better weight control, improvements in dietary habits due to serious game interventions were not significant, while a direct positive effect of serious games on increasing physical activity was observed (pooled SMD = 0.61 [95% CI: 0.04 to 1.19]). While the impact of serious game interventions on body composition and dietary changes is limited, their effectiveness in increasing physical activity is notable. Serious games show potential as tools for overweight/obesity control among children and adolescents but may require longer intervention to sustain its effect.

Abstract Background Gastric cancer (GC) is a malignant tumour, with high morbidity and mortality rates worldwide. The occurrence and development of GC is a complex process involving genetic changes in tumour cells and the influence of the surrounding tumour microenvironment (TME). Accumulative evidence shows that tumour‐associated macrophages (TAMs) play a vital role in GC, acting as plentiful and active infiltrating inflammatory cells in the TME. Main body In this review, the different functions and mechanisms of TAMs in GC progression, including the conversion of phenotypic subtypes; promotion of tumour proliferation, invasion and migration; induction of chemoresistance; promotion of angiogenesis; modulation of immunosuppression; reprogramming of metabolism; and interaction with the microbial community are summarised. Although the role of TAMs in GC remains controversial in clinical settings, clarifying their significance in the treatment selection and prognostic prediction of GC could support optimising TAM‐centred clinicaltherapy. Conclusion In summary, we reviewed the the phenotypic polarisation, function and molecular mechanism of TAMs and their potential applications in the treatment selection and prognostic prediction of GC.

Introduction Sleep is vital to human health, and sleep staging is an essential process in sleep assessment. However, manual classification is an inefficient task. Along with the increased demand for portable sleep quality detection devices, lightweight automatic sleep staging needs to be developed. Methods This study proposes a novel attention-based lightweight deep learning model called LWSleepNet. A depthwise separable multi-resolution convolutional neural network is introduced to analyze the input feature map and captures features at multiple frequencies using two different sized convolutional kernels. The temporal feature extraction module divides the input into patches and feeds them into a multi-head attention block to extract time-dependent information from sleep recordings. The model's convolution operations are replaced with depthwise separable convolutions to minimize its number of parameters and computational cost. The model's performance on two public datasets (Sleep-EDF-20 and Sleep-EDF-78) was evaluated and compared with those of previous studies. Then, an ablation study and sensitivity analysis were performed to evaluate further each module. Results LWSleepNet achieves an accuracy of 86.6% and Macro-F1 score of 79.2% for the Sleep-EDF-20 dataset and an accuracy of 81.5% and Macro-F1 score of 74.3% for the Sleep-EDF-78 dataset with only 55.3 million floating-point operations per second and 180 K parameters. Conclusion On two public datasets, LWSleepNet maintains excellent prediction performance while substantially reducing the number of parameters, demonstrating that our proposed Light multiresolution convolutional neural network and temporal feature extraction modules can provide excellent portability and accuracy and can be easily integrated into portable sleep monitoring devices.

IntroductionThe modernized lifestyle has been paralleled by an epidemic of inflammatory bowel disease (IBD). Excessive consumption of cold beverages is especially common among the modern humans. However, whether cold stress contributes directly to the gut barrier and gut–brain axis is not clear.MethodsWe conducted a cold stress model induced by cold water. The mice were treated with 14 consecutive days of intragastric cold or common water administration. We observed changes in gut transit and gut barrier in the colon. We also employed RNA sequencing-based transcriptomic analysis to identify the genes potentially driving gut injury, and simultaneously examined the gut microbiota and metabolites in the feces.ResultsWe found that cold stress disturbed the intestinal function and increased gut permeability. A set of core genes related to immune responses were consistently overexpressed in the cold stress group. Additionally, cold stress induced decreased bacterial diversity, ecological network, and increased pathogens mainly belonging to Proteobacteria. The dopamine signaling pathway-related metabolites were largely reduced in the cold stress group.ConclusionThis study revealed that cold stress could trigger an IBD-like phenotype in mice, implying that cold stress is a possible risk factor for IBD development.

The attenuation of soil organic carbon and the destruction of soil microbial structure are common manifestations of grassland degradation. The addition of exogenous organic carbon and microorganisms may be an effective way to quickly restore degraded grassland, but corresponding evaluations are still rare. We investigated the effects of effective microorganisms (EM) and biochar addition on vegetation biomass, microorganisms and soil properties in degraded alpine grassland. The treatments included a control (no biochar or EM addition, CK), EM addition (250 mL m−2 EM, M), biochar addition (4.00 kg m−2 biochar, C) and a mixture of biochar and EM (4.00 kg m−2 biochar and 250 mL m−2 EM, C+M). C, M and C+M rapidly increased vegetation biomass, soil organic carbon (TOC), total nitrogen (TN), available nitrogen (NH4+-N, NO3−-N), available phosphorus (AP), total microbial biomass (MB), bacteria and fungus biomass in the soil, and also altered the microbial community structure. The content of soil nutrients in the C treatment was the highest, followed by C+M. The vegetation biomass and microbial biomass were the greatest in the C+M treatment, and increased by 101.04~198.52% and 22.14~45.41%, respectively. C+M can also enhance the presence of saprotrophic fungi, thereby facilitating the augmentation of both plant and soil nutrients. Overall, the biochar combined with EM addition had a synergistic effect on the restoration of degraded alpine grasslands.

A (Fe, Cr)-free Co39.2Ni39.2Al21.6 eutectic medium-entropy alloy (EMEA) was designed and fabricated to study the microstructure and its evolution during slow solidification under different intensities of high static magnetic field (0 T, 5 T and 10 T). It was found that the original microstructure was characterized by FCC/BCC mixed herringbone eutectics consisting of two types of lamellar structures: a curved and wormy anomalous eutectic in the fringe, and a straight and long regular eutectic in the center. Nano-sized L10-type martensite layers are also distributed on the BCC lamellar as the martensitic transformation product. The FCC and BCC phases were enriched in Co and Al elements, respectively, while Ni element was distributed homogenously in both phases. With increasing magnetic field intensity, the herringbone eutectic structures remained stable, without the formation of a primary phase, while the phase constitution and the orientation relationships in the eutectic structures remained unchanged, with no obvious magnetically induced alignments. However, the lamellar spacing of the regular lamellar eutectic decreased significantly from 3.3 μm (0 T) to 1.93 μm (10 T); by contrast, the volume fraction of the anomalous eutectics increased considerably from 28.35% (0 T) to 55.14% (10 T), and the assumption that the imposed convection and destabilization of lamellar eutectics is controlled by the magnetic field is discussed in depth. Our results show a great potential for tailoring microstructures and properties by applying a strong magnetic field during the solidification process of EMEAs.

Abstract Background Exosomal microRNAs (miRs) derived from mesenchymal stem cells (MSCs) have been shown to play roles in the pathophysiological processes of sepsis. Moreover, miR-27b is highly enriched in MSC-derived exosomes. Herein, we aimed to investigate the potential role and downstream molecular mechanism of exosomal miR-27b in sepsis. Methods Inflammation was induced in bone marrow-derived macrophages (BMDMs) by lipopolysaccharide (LPS), and mice were made septic by cecal ligation and puncture (CLP). The expression pattern of miR-27b in MSC-derived exosomes was characterized using RT-qPCR, and its downstream gene was predicted by in silico analysis. The binding affinity between miR-27b, Jumonji D3 (JMJD3), or nuclear factor κB (NF-κB) was characterized to identify the underlying mechanism. We induced miR-27b overexpression or downregulation, along with silencing of JMJD3 or NF-κB to examine their effects on sepsis. The production of pro-inflammatory cytokines TNF-α, IL-1β, and IL-6 was detected by ELISA. Results miR-27b was highly expressed in MSC-derived exosomes. Mechanistic investigations showed that miR-27b targeted JMJD3. miR-27b decreased expression of pro-inflammatory genes by inhibiting the recruitment of JMJD3 and NF-κB at gene promoter region. Through this, MSC-derived exosomal miR-27b diminished production of pro-inflammatory cytokines in LPS-treated BMDMs and septic mice, which could be rescued by upregulation of JMJD3 and NF-κB. Besides, in vitro findings were reproduced by in vivo findings. Conclusion These data demonstrated that exosomal miR-27b derived from MSCs inhibited the development of sepsis by downregulating JMJD3 and inactivating the NF-κB signaling pathway.

The degradation of the grassland system has severely threatened the safety of the ecological environment and animal husbandry. The supplement of key substances lost due to degradation is widely used to accelerate the restoration of the degraded grassland ecosystem. In this study, we investigated the effects of biochar and nitrogen addition on soil properties and microorganisms of degraded alpine grassland. The experimental treatments consisted of the control without any addition, only nitrogen addition (10 gN/m2), only biochar addition (4.00 kg/m2 biochar), and the mixed addition of biochar and nitrogen (4.00 kg/m2 biochar and 10 gN/m2 nitrogen, respectively). Adding N alone did not significantly change the pH, total organic carbon (TOC), total nitrogen (TN), microbial biomass (MB), and the composition proportion of microbes of the soil, but increased the contents of soil water content (SWC), NH4+-N, NO3–-N, available phosphorus (AP), and the biomass of bacteria and fungi. The addition of biochar or the mixture of biochar and nitrogen increased the contents of pH, TOC, TN, MB, SWC, NH4+-N, NO3–-N, AP, bacteria, and fungi in the soil and changed the structure of the soil microbial community. The increasing intensity of AP, bacteria, and fungi under the addition of biochar or the mixture of biochar and nitrogen was significantly greater than that under N addition alone. These results indicated that the separated addition of nitrogen and biochar and the mixed addition of biochar and nitrogen all improved the soil condition of the moderate–severe degraded alpine grassland, but the mixed addition of biochar and nitrogen could be a better strategy to remediate the degraded alpine grassland.

Using natural succession to restore degraded grassland is mainly achieved by self-adjusting the structure and relationship of the internal components of grassland ecosystems. Microorganisms play an important role in the restoration of grassland ecosystems; however, there is no systematic research summary on how microbial communities respond to natural restoration succession in degraded grasslands. In this study, related research results in recent years were summarized and analyzed using meta-analysis. Results showed that soil microbes displayed no significant changes at the early stage (≤5 years) of natural restoration succession, but significantly increased at the following stage (6–10 years) of restoration succession, before decreasing with the continuation of succession. Changes in microbial activity mainly occurred in the 0–20 cm soil depth layer. Numbers of bacteria, fungi, and actinomycetes significantly increased at the six to 10 year stage of restoration succession. When restoration succession ceased after 10 years, most microorganisms began to decrease. During natural restoration succession, the diversity of fungi and bacteroidetes increased, while chloroflexi diversity decreased. These results indicated that the optimal period for the natural restoration succession of degraded grassland was approximately 10 years to ensure that the microbes of the grassland system returned to relatively high levels.

Root traits have an important impact on plant growth, which reflects the adaptation of plants to nutrients. This paper describes the focus and progress of root traits research and provides references for future research. Based on the Web of Science online database, articles related to root traits from 2000–2021 were evaluated using bibliometric methods. The results showed that the study of root traits has been growing steadily in the last two decades. Wang Yan is the author with the highest number of published papers, the most citations and the highest H-index. The top three published countries are the USA, China and India. The top three institutions are the University of Western Australia, China Agricultural University and Nanjing Agricultural University. Plant and Soil, Frontiers in Plant Science and PLoS One have the highest number of published articles. In terms of co-occurrence of keyword analysis, growth, soil and plant diversity are highly correlated with root traits. It was found that cooperation between authors, institutions and countries are not close enough and that z global network of cooperation has not yet been formed. Therefore, worldwide cooperation should be strengthened to promote resource sharing and the openness of relevant mechanisms.

As a severe neurological deficit, intracerebral hemorrhage (ICH) is associated with overwhelming mortality. Subsequent oxidative stress and neurological dysfunction are likely to cause secondary brain injury. Therefore, this study sought to define the role of Krüppel-like factor 6 (KLF6) and underlying mechanism in oxidative stress and neurological dysfunction following ICH. An in vivo model of ICH was established in rats by injection of autologous blood, and an in vitro ICH cell model was developed in hippocampal neurons by oxyhemoglobin (OxyHb) exposure. Next, gain- and loss-of-function assays were performed in vivo and in vitro to clarify the effect of KLF6 on neurological dysfunction and oxidative stress in ICH rats and neuronal apoptosis and mitochondrial reactive oxygen species in OxyHb-induced hippocampal neurons. KLF6, nuclear factor erythroid 2–related factor 2 (Nrf2), and heme oxygenase 1 (HO-1) were highly expressed in hippocampal tissues of ICH rats, whereas sirtuin 5 (SIRT5) presented a poor expression. Mechanistically, KLF6 bound to the SIRT5 promoter and transcriptionally repressed SIRT5 to activate the Nrf2/HO-1 signaling pathway. KLF6 silencing alleviated neurological dysfunction and oxidative stress in ICH rats and diminished oxidative stress and neuronal apoptosis in OxyHb-induced neurons, whereas SIRT5 overexpression negated its effect. To sum up, KLF6 silencing elevated SIRT5 expression to inactivate the Nrf2/HO-1 signaling pathway, thus attenuating oxidative stress and neurological dysfunction after ICH.

This study establishes a compartment model for the categorized COVID-19 risk area. In this model, the compartments represent administrative regions at different transmission risk levels instead of individuals in traditional epidemic models. The county-level regions are partitioned into High-risk (H), Medium-risk (M), and Low-risk (L) areas dynamically according to the current number of confirmed cases. These risk areas are communicable by the movement of individuals. An LMH model is established with ordinary differential equations (ODEs). The basic reproduction number R0 is derived for the transmission of risk areas to determine whether the pandemic is controlled. The stability of this LHM model is investigated by a Lyapunov function and Poincare–Bendixson theorem. We prove that the disease-free equilibrium (R0 < 1) is globally asymptotically stable and the disease will die out. The endemic equilibrium (R0 > 1) is locally and globally asymptotically stable, and the disease will become endemic. The numerical simulation and data analysis support the previous theoretical proofs. For the first time, the compartment model is applied to investigate the dynamics of the transmission of the COVID-19 risk area. This work should be of great value in the development of precision region-specific containment strategies.

Stroke has been the leading cause of adult morbidity and mortality over the past several years. After an ischemic stroke attack, many dormant or reversibly injured brain cells exist in the penumbra area. However, the pathological processes and unique cell information in the penumbra area of an acute ischemic stroke remain elusive. We applied unbiased single cell sequencing in combination with bulk RNA-seq analysis to investigate the heterogeneity of each cell type in the early stages of ischemic stroke and to detect early possible therapeutic targets to help cell survival. We used these analyses to study the mouse brain penumbra during this phase. Our results reveal the impact of ischemic stroke on specific genes and pathways of different cell types and the alterations of cell differentiation trajectories, suggesting potential pathological mechanisms and therapeutic targets. In addition to classical gene markers, single-cell genomics demonstrates unique information on subclusters of several cell types and metabolism changes in an ischemic stroke. These findings suggest that Gadd45b in microglia, Cyr61 in astrocytes, and Sgk3 in oligodendrocytes may play a subcluster-specific role in cell death or survival in the early stages of ischemic stroke. Moreover, RNA-scope multiplex in situ hybridization and immunofluorescence staining were applied to selected target gene markers to validate and confirm the existence of these cell subtypes and molecular changes during acute stage of ischemic stroke.

Recently, there has been much attention in the use of machine learning methods, particularly deep learning for stock price prediction. A major limitation of conventional deep learning is uncertainty quantification in predictions which affect investor confidence. Bayesian neural networks feature Bayesian inference for providing inference (training) of model parameters that provides a rigorous methodology for uncertainty quantification in predictions. Markov Chain Monte Carlo (MCMC) sampling methods have been prominent in implementing inference of Bayesian neural networks; however certain limitations existed due to a large number of parameters and the need for better computational resources. Recently, there has been much progress in the area of Bayesian neural networks given the use of Langevin gradients with parallel tempering MCMC that can be implemented in a parallel computing environment. The COVID-19 pandemic had a drastic impact in the world economy and stock markets given different levels of lockdowns due to rise and fall of daily infections. It is important to investigate the performance of related forecasting models during the COVID-19 pandemic given the volatility in stock markets. In this paper, we use novel Bayesian neural networks for multi-step-ahead stock price forecasting before and during COVID-19. We also investigate if the pre-COVID-19 datasets are useful of modelling stock price forecasting during COVID-19. Our results indicate due to high volatility in the stock-price during COVID-19, it is more challenging to provide forecasting. However, we found that Bayesian neural networks could provide reasonable predictions with uncertainty quantification despite high market volatility during the first peak of the COVID-19 pandemic.

The large proportion of asymptomatic patients is the major cause leading to the COVID-19 pandemic which is still a significant threat to the whole world. A six-dimensional ODE system (SEIAQR epidemical model) is established to study the dynamics of COVID-19 spreading considering infection by exposed, infected, and asymptomatic cases. The basic reproduction number derived from the model is more comprehensive including the contribution from the exposed, infected, and asymptomatic patients. For this more complex six-dimensional ODE system, we investigate the global and local stability of disease-free equilibrium, as well as the endemic equilibrium, whereas most studies overlooked asymptomatic infection or some other virus transmission features. In the sensitivity analysis, the parameters related to the asymptomatic play a significant role not only in the basic reproduction number R0. It is also found that the asymptomatic infection greatly affected the endemic equilibrium. Either in completely eradicating the disease or achieving a more realistic goal to reduce the COVID-19 cases in an endemic equilibrium, the importance of controlling the asymptomatic infection should be emphasized. The three-dimensional phase diagrams demonstrate the convergence point of the COVID-19 spreading under different initial conditions. In particular, massive infections will occur as shown in the phase diagram quantitatively in the case R0>1. Moreover, two four-dimensional contour maps of Rt are given varying with different parameters, which can offer better intuitive instructions on the control of the pandemic by adjusting policy-related parameters.

The undercooling (∆T) dependencies of the solidification pathways, microstructural evolution, and recalescence behaviors of undercooled Co-18.5at.%B eutectic alloys were systematically explored. Up to four possible solidification pathways were identified: (1) A lamellar eutectic structure consisting of the FCC–Co and Co3B phase forms, with extremely low ΔT; (2) The FCC–Co phase primarily forms, followed by the eutectic growth of the FCC–Co and Co2B phases when ΔT < 100 K; (3) As the ΔT increases further, the FCC–Co phase primarily forms, followed by the metastable Co23B6 phase with the trace of an FCC–Co and Co23B6 eutectic; (4) When the ΔT increases to 277 K, the FCC–Co phase primarily forms, followed by an FCC–Co and Co3B eutectic, which is similar in composition to the microstructure formed with low ΔT. The mechanisms of the microstructural evolution and the phase selection are interpreted on the basis of the composition segregation, the skewed coupled zone, the strain-induced transformation, and the solute trapping. Moreover, the prenucleation of the primary FCC–Co phase was also detected from an analysis of the different recalescence behaviors. The present work not only enriches our knowledge about the phase selection behavior in the undercooled Co–B system, but also provides us with guidance for controlling the microstructures and properties practically.

Abstract Background Nearly 6 million deaths and over a half trillion dollars in healthcare costs worldwide are attributed to tobacco smoking each year. Extensive research efforts have been pursued to elucidate the molecular underpinnings of smoking addiction and facilitate cessation. In this study, we genotyped and obtained both resting state and task-based functional magnetic resonance imaging from 64 non-smokers and 42 smokers. Smokers were imaged after having smoked normally (“sated”) and after having not smoked for at least 12 h (“abstinent”). Results While abstinent smokers did not differ from non-smokers with respect to pairwise resting state functional connectivities (RSFCs) between 12 brain regions of interest, RSFCs involving the caudate and putamen of sated smokers significantly differed from those of non-smokers (P

Abstract High magnetic field is a powerful tool to tune the microstructure and improve the properties of materials. In this report, the nucleation behavior of undercooled Co76Sn24 near eutectic alloy under strong homogeneous and gradient magnetic fields have been investigated using glass slag fluxing method in a 12 T superconducting magnet. The mean undercooling of the undercooled melt is not altered by homogeneous magnetic field but depressed by gradient magnetic field. The highest temperature during recalescence is strongly altered by magnetic field, where an enhancement effect is observed under gradient magnetic field and an opposite effect in homogeneous magnetic field. The reason is interpreted by discussion about the magnetic field on the thermodynamics of nucleation and also the purifying effect of the glass slag, the magnetic properties and the magnetic force exerted on the undercooled melt.

Immiscible alloy is a kind of functional metal material with broad application prospects in industry and electronic fields, which has aroused extensive attention in recent decades. In the solidification process of metallic material processing, various attractive phenomena can be realized by applying a high magnetic field (HMF), including the nucleation and growth of alloys and microstructure evolution, etc. The selectivity provided by Lorentz force, thermoelectric magnetic force, and magnetic force or a combination of magnetic field effects can effectively control the solidification process of the melt. Recent advances in the understanding of the development of immiscible alloys in the solidification microstructure induced by HMF are reviewed. In this review, the immiscible alloy systems are introduced and inspected, with the main focus on the relationship between the migration behavior of the phase and evolution of the solidification microstructure under HMF. Special attention is paid to the mechanism of microstructure evolution caused by the magnetic field and its influence on performance. The ability of HMF to overcome microstructural heterogeneity in the solidification process provides freedom to design and modify new functional immiscible materials with desired physical properties. This review aims to offer an overview of the latest progress in HMF processing of immiscible alloys.

The oxidation of alcohols to carbonyl compounds is one of the most developed and investigated reactions in organic synthesis due to its easiness of conduct and the usefulness of its products. However, most current systems of oxidizing alcohols require stoichiometric oxidants that create large amounts of waste harmful to the environment. Thus, finding suitable catalytic systems for the specialized oxidation of different alcohols is desirable. This review critically examines various catalysts utilized in the catalytic oxidation of alcohols to carbonyl compounds within the framework of green chemistry. In short, traditional transition metal-based catalysts find their use in oxidizing various benzylic alcohols; TEMPO-based catalysts can be used for selective oxidation of primary alcohols to aldehydes or carboxylic acids under different conditions; biological enzymes apply to natural chemicals such as saccharides; and heterogeneous catalysts are recommended when dealing with reactive substrates in large scales. [ABSTRACT FROM AUTHOR]