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Abstract Protein Disulfide-Isomerase A2 (PDIA2) is a gene that encodes proteins, responsible for protein folding and modification within cells. The development and course of many disorders are intimately linked to the aberrant expression of PDIA2. Nevertheless, more research is necessary to fully understand PDIA2’s biological significance in pan-cancer, notably in prostate cancer (PCa). PDIA2 expression is elevated in various tumors and closely related to patient prognosis. Patients with prostate cancer who express PDIA2 high in particular have a bad prognosis in terms of progression-free survival. In addition, the upregulation of PDIA2 expression in prostate cancer patients is accompanied by higher Gleason scores, advanced tumor staging, lymph node metastasis, and elevated PSA levels. Detailed experiments further demonstrate that PDIA2 is a carcinogenic gene affecting prostate cancer cells’ response to dasatinib therapy. For patients with prostate cancer, there is a clear positive connection between the expression level of PDIA2 and a bad prognosis. The prostate cancer treatment efficacy of dasatinib is hampered by PDIA2, which is intimately linked to the growth, invasion, and metastasis of PCa cells. In summary, our research highlights the potential of PDIA2 as a biomarker for the diagnosis and management of PCa.

Background: The prognostic value of body temperature in sepsis-induced coagulopathy (SIC) remains unclear. In this study we aimed to investigate the association between temperature and mortality among SIC patients. Methods: We analyzed data for 9,860 SIC patients from an intensive care database. Patients were categorized by maximum temperature in the first 24 hours into the following: ≤36.0°C; 36.0–37.0°C; 37.0–38.0°C; 38.0–39.0°C; and ≥39.0°C. The primary outcome was 28-day mortality. We used multivariate regression to analyze the temperature-mortality association. Results: The 37.0–38.0°C, 38.0–39.0°C and ≥39.0°C groups correlated with lower 28-day mortality (adjusted HR 0.70, 0.76 and 0.72, respectively), while the

Abstract Assimilatory nitrate reduction and methane (CH4) oxidation by bacteria play important roles in carbon (C) and nitrogen (N) biogeochemical cycles. Here, an investigation of enzymatic assimilatory nitrate reduction and CH4 oxidation by Methylobacter sp. YHQ from the wetlands is presented, specifically concentrating on N and oxygen (O) isotope fractionation with various initial nitrate and oxygen concentrations. The N enrichment factors (15 ε assimilation) increased from 4.2 ± 0.7‰ to 6.9 ±1.3‰ and the O isotope enrichment factors (18 ε assimilation) increased from 2.7 ± 0.9‰ to 4.7 ± 0.8‰ during nitrate assimilation when initial nitrate concentrations increased from 0.9 mM to 2 mM. Similar 18 ε and 15 ε values were observed at different oxygen concentrations. The values of 18 ε and 15 ε provided vital parameters for the assessment of assimilatory nitrate reduction via the Rayleigh equation approach. The ratios of O and N isotope enrichment factors (18 ε:15 ε)assimilation ranged from 0.64 ± 0.15 to 0.74 ± 0.18 during nitrate assimilation by Methylobacter sp. YHQ with Nas, which were different from (18 ε:15 ε)assimilation for assimilatory eukaryotic nitrate reductase (eukNR) from literature data. Thus, N and O isotope fractionation could be useful tools to distinguish eukNR from Nas during nitrate assimilation. Additionally, the rates of CH4 oxidation and nitrate reduction were evaluated with a reaction-based kinetic model, and it quantitatively described the enzymatic reactions of nitrate assimilation. Combining dual N-O isotope analysis with kinetic modeling provides new insights into the microbially driven C-N interactions. Graphical Abstract

Abstract Color-changing melon is an ornamental and edible fruit. Aiming at the problems of slow detection speed and high deployment cost for Color-changing melon in intelligent agriculture equipment, this study proposes a lightweight detection model YOLOv8-CML.Firstly, a lightweight Faster-Block is introduced to reduce the number of memory accesses while reducing redundant computation, and a lighter C2f structure is obtained. Then, the lightweight C2f module fusing EMA module is constructed in Backbone to collect multi-scale spatial information more efficiently and reduce the interference of complex background on the recognition effect. Next, the idea of shared parameters is utilized to redesign the detection head to simplify the model further. Finally, the α-IoU loss function is adopted better to measure the overlap between the predicted and real frames using the α hyperparameter, improving the recognition accuracy. The experimental results show that compared to the YOLOv8n model, the parametric and computational ratios of the improved YOLOv8-CML model decreased by 42.9% and 51.8%, respectively. In addition, the model size is only 3.7 MB, and the inference speed is improved by 6.9%, while mAP@0.5, accuracy, and FPS are also improved. Our proposed model provides a vital reference for deploying Color-changing melon picking robots.

Abstract This study delves into the micro-occurrence states and enrichment mechanisms of residual oil, pivotal for advancing the production from tight sandstone reservoirs, particularly from the Chang 8 Member of the Upper Triassic Yanchang Formation, Ordos Basin. Through an analysis of 23 core samples, employing high-pressure mercury injection, field emission scanning electron microscopy, thin section, and X-ray diffraction techniques, distinct reservoir types were categorized. The utilization of environmental scanning electron microscope, multi-solvent continuous extraction, and an oil components separation system facilitated an intricate analysis of residual oil micro-occurrence states and their subsequent effects on porosity and permeability reduction across varying reservoir types. The findings accentuate the integral role of reservoir type in determining residual oil distribution within tight sandstone reservoirs. Favorable pore throat sorting and connectivity in specified reservoir types are identified as conducive to residual oil enrichment with a higher concentration of light components. In contrast, elevated carbonatite and clay content in other reservoir types leads to adsorption of heavy components, disrupting pore throat connectivity, and impeding crude oil filling. The varied interactions between oil and rock, oil–oil, and pore throat sealing significantly impact the distribution of oil components of residual oil, culminating in a notable reduction of porosity and permeability by 2.63% and 0.197 mD, with corresponding reduction rates of 27.19% and 46.69%, respectively. The insights derived from this study furnish a theoretical foundation for augmenting tight oil recovery and comprehending the enrichment mechanism of residual oil driven by the heterogeneity of tight sandstone reservoirs.

Abstract Background Congenital heart disease (CHD) is a prevalent congenital cardiac malformation, which lacks effective early biological diagnosis and intervention. MicroRNAs, as epigenetic regulators of cardiac development, provide potential biomarkers for the diagnosis and treatment of CHD. However, the mechanisms underlying miRNAs-mediated regulation of cardiac development and CHD malformation remain to be further elucidated. This study aimed to explore the function of microRNA-20b-5p (miR-20b-5p) in cardiac development and CHD pathogenesis. Methods and results miRNA expression profiling identified that miR-20b-5p was significantly downregulated during a 12-day cardiac differentiation of human embryonic stem cells (hESCs), whereas it was markedly upregulated in plasma samples of atrial septal defect (ASD) patients. Our results further revealed that miR-20b-5p suppressed hESCs-derived cardiac differentiation by targeting tet methylcytosine dioxygenase 2 (TET2) and 5-hydroxymethylcytosine, leading to a reduction in key cardiac transcription factors including GATA4, NKX2.5, TBX5, MYH6 and cTnT. Additionally, knockdown of TET2 significantly inhibited cardiac differentiation, which could be partially restored by miR-20b-5p inhibition. Conclusions Collectively, this study provides compelling evidence that miR-20b-5p functions as an inhibitory regulator in hESCs-derived cardiac differentiation by targeting TET2, highlighting its potential as a biomarker for ASD.

Color-changing melons are a kind of cucurbit plant that combines ornamental and food. With the aim of increasing the efficiency of harvesting Color-changing melon fruits while reducing the deployment cost of detection models on agricultural equipment, this study presents an improved YOLOv8s network approach that uses model pruning and knowledge distillation techniques. The method first merges Dilated Wise Residual (DWR) and Dilated Reparam Block (DRB) to reconstruct the C2f module in the Backbone for better feature fusion. Next, we designed a multilevel scale fusion feature pyramid network (HS-PAN) to enrich semantic information and strengthen localization information to enhance the detection of Color-changing melon fruits with different maturity levels. Finally, we used Layer-Adaptive Sparsity Pruning and Block-Correlation Knowledge Distillation to simplify the model and recover its accuracy. In the Color-changing melon images dataset, the mAP0.5 of the improved model reaches 96.1%, the detection speed is 9.1% faster than YOLOv8s, the number of Params is reduced from 6.47M to 1.14M, the number of computed FLOPs is reduced from 22.8GFLOPs to 7.5GFLOPs. The model’s size has also decreased from 12.64MB to 2.47MB, and the performance of the improved YOLOv8 is significantly more outstanding than other lightweight networks. The experimental results verify the effectiveness of the proposed method in complex scenarios, which provides a reference basis and technical support for the subsequent automatic picking of Color-changing melons.

The unique pectoral fin swinging propulsion method of biomimetic robotic manta ray is more suitable for long-term underwater operations in wind and wave environments. Relevant research has been conducted both in China and abroad, but there are problems in the current research on biomimetic robotic manta ray, such as weak driving ability, low control accuracy, and poor biomimetic effects. This article took the natural manta ray as a biomimetic prototype, analyzed its biological characteristics and motion mechanism, and constructed its kinematics and dynamics models, thus providing a theoretical basis for the system design of the biomimetic robotic manta ray. The mechanical structure and control system were also designed. The experiments of straight forward swimming, in situ turning, and dynamic sinking and floating were carried out under simulated wave environments to test the performance of the biomimetic robotic manta ray in complex environments, verifying the motion performance and application prospect of biomimetic robotic manta ray.

Immune checkpoint blockade (ICB) therapy is a revolutionary approach to treat cancers, but still have limited clinical applications. Accumulating evidence pinpoints the immunosuppressive characteristics of the tumor microenvironment (TME) as one major obstacle. The TME, characterized by acidity, hypoxia and elevated ROS levels, exerts its detrimental effects on infiltrating anti-tumor immune cells. Here, we developed a TME-responsive and immunotherapeutic catalase-loaded calcium carbonate nanoparticles (termed as CAT@CaCO3 NPs) as the simple yet versatile multi-modulator for TME remodeling. CaCO3 NPs can consume protons in the acidic TME to normalize the TME pH. CAT catalyzed the decomposition of ROS and thus generated O2. The released Ca2+ led to Ca2+ overload in the tumor cells which then triggered the release of damage-associated molecular patterns (DAMP) signals to initiate anti-tumor immune responses, including tumor antigen presentation by dendritic cells. Meanwhile, CAT@CaCO3 NPs-induced immunosupportive TME also promoted the polarization of the M2 tumor-associated macrophages to the M1 phenotype, further enhancing tumor antigen presentation. Consequently, T cell-mediated anti-tumor responses were activated, the efficacy of which was further boosted by aPD-1 immune checkpoint blockade. Our study demonstrated that local treatment of CAT@CaCO3 NPs and aPD-1 combination can effectively evoke local and systemic anti-tumor immune responses, inhibiting the growth of treated tumors and distant diseases.

Land use classification of high-precision satellite images using semantic segmentation methods has become mainstream. In this field, global context information plays an irreplaceable role. However, most current methods struggle to effectively utilize this global context, which results in low segmentation accuracy, especially in scenes with similar objects, small targets, or obscured by shadows. To address the above issues, this article introduces SFMRNet—the network that integrates the advantages of Transformer and convolutional neural network (CNN)—and designs various modules to utilize the power of contextual information as much as possible. First, we design a specific enhanced feature fusion module (SEFFM) that selectively enhances spatial or channel information of feature maps before fusion, effectively mitigating small interclass differences. Second, our proposed multibranch feature refinement module (MFRM) facilitates the interaction between different feature layers and refines these features to enhance multiscale characterization. This improves the segmentation of small-sized targets and addresses the occlusion issues. Finally, comprehensive testing and detailed ablation analysis are conducted on three datasets: the ISPRS Vaihingen, ISPRS Potsdam, and LoveDA land use classification datasets. The results demonstrate that SFMRNet exhibits superior segmentation capabilities compared to existing advanced methods.

Abstract Acute lung injury (ALI) as well as its more severe form, acute respiratory distress syndrome (ARDS), frequently leads to an uncontrolled inflammatory response. N6-methyladenosine (m6A) modification was associated with the progression of several inflammatory diseases. However, the role of methyltransferase-like 14 (METTL14)-mediated m6A methylation in ALI/ARDS remains unclear. Here, we reported an increase in overall expression levels of m6A and METTL14 in circulating monocyte-derived macrophages recruited to the lung following ALI, which is correlated with the severity of lung injury. We further demonstrated the critical function of METTL14 in activating NOD-like receptor pyrin domain-containing protein 3 (NLRP3) inflammasome in vitro and in mouse models of ALI/ARDS, and validated NLRP3 as the downstream target of METTL14 by the m6A RNA immunoprecipitation (MeRIP) and RIP assays. Mechanistically, METTL14-methylated NLRP3 transcripts were subsequently recognized by insulin-like growth factor 2 mRNA-binding protein 2 (IGF2BP2), an m6A reader, which stabilized NLRP3 mRNA. Furthermore, we observed that IGF2BP2 knockdown diminished LPS-induced ALI in mice by downregulating NLRP3 expression. In summation, our study revealed that the molecular mechanism underlying the pathogenesis of ALI/ARDS involves METTL14-mediated activation of NLRP3 inflammasome in an IGF2BP2 dependent manner, thereby demonstrating the potential of METTL14 and IGF2BP2 as promising biomarkers and therapeutic targets for ALI/ARDS treatment.

Abstract Background At present, much evidence shows that many cancers have a high risk of thrombosis. Several studies have shown the prognostic value of platelet-related parameters and coagulation indexes in prostate cancer (PCa). However, the association between platelet-related parameters, coagulation indexes and bone metastasis of Pca is unclear. Methods A total of 234 pathologically diagnosed patients with Pca were consecutively collected and stratified into the bone metastasis group and non-bone metastasis group according to the results of the bone scan. ROC curve analysis was used to explore the auxiliary predictive value of single and combined parameters for bone metastasis in Pca patients. Univariate and multivariate Logistic regression analyses were used to determine the relationship between platelet-related parameters, coagulation indexes, and bone metastasis of Pca. Results Platelet count (PLT), fibrinogen (Fib), prostate-specific antigen (PSA), and D-dimer (DD) levels of the bone metastasis group were significantly higher than the non-bone metastasis group (P = 0.010, P

The application of remote sensing technology for water quality monitoring has attracted much attention recently. Remote sensing inversion in coastal waters with complex hydrodynamics for non-optically active parameters such as total nitrogen (TN) and total phosphorus (TP) remains a challenge. Existing studies build the relationships between remote sensing spectral data and TN/TP directly or indirectly via the mediation of optically active parameters (e.g., total suspended solids). Such models are often prone to overfitting, performing well with the training set but underperforming with the testing set, even though both datasets are from the same region. Using the Hong Kong coastal region as a case study, we address this issue by incorporating spatial covariates such as hydrometeorological and locational variables as additional input features for machine learning-based inversion models. The proposed model effectively alleviates overfitting while maintaining a decent level of accuracy (R2 exceeding 0.7) during the training, validation and testing steps. The gap between model R2 values in training and testing sets is controlled within 7%. A bootstrap uncertainty analysis shows significantly improved model performance as compared to the model with only remote sensing inputs. We further employ the Shapely Additive Explanations (SHAP) analysis to explore each input’s contribution to the model prediction, verifying the important role of hydrometeorological and locational variables. Our results provide a new perspective for the development of remote sensing inversion models for TN and TP in similar coastal waters.

To accurately estimate the 6D pose of objects, most methods employ a two-stage algorithm. While such two-stage algorithms achieve high accuracy, they are often slow. Additionally, many approaches utilize encoding–decoding to obtain the 6D pose, with many employing bilinear sampling for decoding. However, bilinear sampling tends to sacrifice the accuracy of precise features. In our research, we propose a novel solution that utilizes implicit representation as a bridge between discrete feature maps and continuous feature maps. We represent the feature map as a coordinate field, where each coordinate pair corresponds to a feature value. These feature values are then used to estimate feature maps of arbitrary scales, replacing upsampling for decoding. We apply the proposed implicit module to a bidirectional fusion feature pyramid network. Based on this implicit module, we propose three network branches: a class estimation branch, a bounding box estimation branch, and the final pose estimation branch. For this pose estimation branch, we propose a miniature dual-stream network, which estimates object surface features and complements the relationship between 2D and 3D. We represent the rotation component using the SVD (Singular Value Decomposition) representation method, resulting in a more accurate object pose. We achieved satisfactory experimental results on the widely used 6D pose estimation benchmark dataset Linemod. This innovative approach provides a more convenient solution for 6D object pose estimation.

Background Parkinson’s disease (PD) is a common degenerative disease caused by abnormal accumulation of α-synuclein. The glymphatic pathway is essential for removing macromolecular proteins including α-synuclein from the brain, which flows into deep cervical lymph nodes (DCLNs) through meningeal lymphatics. As a terminal station for the cerebral lymphatic system drainage, DCLNs can be easily assessed clinically. Objectives Although the drainage function of the cerebral lymphatic system is impaired in PD, the correlation between DCLNs and PD remains unknown. Design Single-center retrospective cross-sectional study. Methods The size of the DCLNs were measured using ultrasound. The Movement Disorder Society Sponsored Revision Unified Parkinson’s Disease Rating Scale and other scales were used to assess PD motor and non-motor symptoms. Results Compared with the healthy control (HC) and the atypical Parkinson’s disease (AP) groups, the size of the second and third DCLNs in the Parkinson’s disease (PD) group was significantly smaller ( P < .05). The width diameter of the third DCLN (DCLN3(y)) was significantly smaller in the PD group than in the AP group ( P = .014). DCLN3(y) combined with a variety of clinical features improved the sensitivity of AP identification (sensitivity = .813). Conclusion DCLNs were able to distinguish HC, PD and AP and were mainly located in Robbins ΙΙA level. PD and AP were associated with different factors that influenced the size of the DCLNs. DCLN3(y) plays an important role in differentiating PD from AP, which, combined with other clinical features, has the ability to distinguish PD from AP; in particular, the sensitivity of AP diagnosis was improved.

Furin is a pro-protein convertase that moves between the trans-Golgi network and cell surface in the secretory pathway. We have previously reported that cerebral overexpression of furin promotes cognitive functions in mice. Here, by generating the brain-specific furin conditional knockout (cKO) mice, we investigated the role of furin in brain development. We found that furin deficiency caused early death and growth retardation. Magnetic resonance imaging showed severe hydrocephalus. In the brain of furin cKO mice, impaired ciliogenesis and the derangement of microtubule structures appeared along with the down-regulated expression of RAB28, a ciliary vesicle protein. In line with the widespread neuronal loss, ependymal cell layers were damaged. Further proteomics analysis revealed that cell adhesion molecules including astrocyte-enriched ITGB8 and BCAR1 were altered in furin cKO mice; and astrocyte overgrowth was accompanied by the reduced expression of SOX9, indicating a disrupted differentiation into ependymal cells. Together, whereas alteration of RAB28 expression correlated with the role of vesicle trafficking in ciliogenesis, dysfunctional astrocytes might be involved in ependymal damage contributing to hydrocephalus in furin cKO mice. The structural and molecular alterations provided a clue for further studying the potential mechanisms of furin.

The solubility and transformation of cadmium (Cd) are controlled by paddy soil pH, whereas paddy soil pH varies during flooding and drainage and is significantly controlled by flooding durations. However, there is still a lack of modeling approaches for simulating the impact of flooding durations on pH fluctuation and concomitant Cd effectiveness in Cd-polluted acidic paddy soils. Herein, laboratory findings combined with a process-based numerical modeling method were used to quantify the observed key geochemical processes of Fe/C/N/S and the accompanying Cd partitioning dynamics during flooding and drainage. During flooding stage, the number of protons consumed by Fe(III), NO3−, and SO42− reduction increased with flooding durations, resulting in an increase of pH, which enhanced Cd immobilization and reduced Cd potential risk. After entering drainage stage, the number of protons released from Fe(II), NH4+, and S2− oxidation increased with flooding time, leading to pH decrease, which increased Cd release. A process-based kinetic model fitting results showed that Fe(III) reduction and Fe(II) oxidation were key processes that increased and decreased pH, respectively, and that increasing flooding durations were not beneficial to Cd immobilization during flooding and drainage processes. The results of this study shed light on the impact of redox state of paddy soil on Cd dynamics under different flooding durations and provide a theoretical approach to quantify the contribution of key processes controlling changes in metal species, which can be used to simulate the dynamic behavior of heavy metals in paddy soil under different natural conditions by coupling other significant processes.

The lower limits of petrophysical properties for an effective reservoir are among the key parameters for assessing hydrocarbon reserves and are therefore directly related to hydrocarbon exploration and development strategies. However, the lower limits for marine sandstone gas reservoirs are still not clear and the impact factors also remain to be discussed. This study analysed the lower petrophysical property limits of an effective sandstone reservoir in the Qiongdongnan Basin using porosity, permeability and gas testing. The results showed that the lower porosity and permeability limits of effective reservoirs developed in the deltas are 8.9% and 1.2 × 10−3 μm2, respectively, and 11.3% and 4.0 × 10−3 μm2 in the submarine canyons and fans, respectively. Sedimentary facies, sediment transport distance, grain size and burial depth of sandstone significantly influence the lower physical property limits. The lower porosity and permeability limits increase with the increase in sediment transport distance as well as the decrease in sandstone grain size and burial depth. Sediment sources and sedimentary facies determine whether sandstone can become an effective reservoir in the Qiongdongnan Basin. Specifically, the sediment source dramatically influences the petrophysical properties of sandstone. The sandstone sourced from the Red River has higher porosity and permeability, followed by the sandstone sourced from the Hainan Uplift, and the sandstone sourced from the palaeo-uplift within the basin has the lowest porosity and permeability. The feldspar dissolution by CO2 and organic acid is the primary formation mechanism of the effective reservoir in the Lingshui Formation, whereas the dissolution of glauconite is more common in the sandstone reservoirs of the Sanya and Meishan formations.

AimThe objective of our study was to investigate the potential association between the triglyceride and glucose (TyG) index and the occurrence of prehypertension or hypertension in a cohort of normoglycemic Japanese subjects.MethodsThe NAGALA physical examination program was conducted in 1994 at Murakami Memorial Hospital in Gifu City, Japan. For our retrospective study, we selected 15,450 participants who had taken part in this program. Our aim was to explore the potential link between the TyG index, a surrogate marker for insulin resistance, and the presence of prehypertension (pre-HTN) or hypertension (HTN). Our analysis included adjustments for clinical demographic attributes and serum biomarkers. Logistic regression was employed to assess the relationship between the TyG index and the likelihood of pre-HTN or HTN.ResultsA total of 15,450 study subjects were included in our analysis. Notably, the prevalence of both pre-HTN and HTN displayed an ascending trend with increasing quartiles of the TyG index. In our comprehensive multivariable logistic regression analysis, when evaluating TyG as a continuous variable, the adjusted odds ratio (OR) for pre-HTN was OR 1.31 [95% CI 1.11-1.56], while for HTN, it was OR 1.76 [95% CI 1.24-2.5] within the fully adjusted model (model 3). When TyG was stratified into quartiles within model 3, the adjusted ORs for pre-HTN were OR 1.16 [95% CI 1.02-1.31], OR 1.22 [95% CI 1.06-1.41], and OR 1.31 [95% CI 1.08-1.59], respectively, using quartile 1 as the reference. The adjusted ORs for HTN in quartiles 2, 3, and 4 were OR 1.22 [95% CI 0.89-1.66], OR 1.4 [95% CI 1.02-1.91], and OR 1.48 [95% CI 1.02-2.15], respectively, within the same model and analysis, with quartile 1 as the reference. Subgroup analysis indicated that the TyG index exhibited a significant positive correlation with the risk of hypertension or prehypertension, except in the subgroup aged ≥65 years.ConclusionOur study highlights a robust correlation between the TyG index and the likelihood of pre-HTN or HTN in normoglycemic Japanese subjects. This underscores the potential clinical relevance of the TyG index in refining early hypertension management strategies. Nonetheless, the validation of these findings necessitates larger studies with extended follow-up periods.

Introduction: The 5-year survival of gastric cancer (GC) patients with advanced stage remains poor. Some evidence has indicated that tryptophan metabolism may induce cancer progression through immunosuppressive responses and promote the malignancy of cancer cells. The role of tryptophan and its metabolism should be explored for an in-depth understanding of molecular mechanisms during GC development.Material and methods: We utilized the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) dataset to screen tryptophan metabolism-associated genes via single sample gene set enrichment analysis (ssGSEA) and correlation analysis. Consensus clustering analysis was employed to construct different molecular subtypes. Most common differentially expressed genes (DEGs) were determined from the molecular subtypes. Univariate cox analysis as well as lasso were performed to establish a tryptophan metabolism-associated gene signature. Gene Set Enrichment Analysis (GSEA) was utilized to evaluate signaling pathways. ESTIMATE, ssGSEA, and TIDE were used for the evaluation of the gastric tumor microenvironment.Results: Two tryptophan metabolism-associated gene molecular subtypes were constructed. Compared to the C2 subtype, the C1 subtype showed better prognosis with increased CD4 positive memory T cells as well as activated dendritic cells (DCs) infiltration and suppressed M2-phenotype macrophages inside the tumor microenvironment. The immune checkpoint was downregulated in the C1 subtype. A total of eight key genes, EFNA3, GPX3, RGS2, CXCR4, SGCE, ADH4, CST2, and GPC3, were screened for the establishment of a prognostic risk model.Conclusion: This study concluded that the tryptophan metabolism-associated genes can be applied in GC prognostic prediction. The risk model established in the current study was highly accurate in GC survival prediction.

Abstract Aiming at solving the performance degradation of federated learning (FL) under heterogeneous data distribution, personalized FL (PFL) was proposed. It is designed to produce a dedicated model for each client. However, the existing PFL solution only focuses on the performance of personalized model, ignoring the performance of global model, which will affect the willingness of new clients to participate. In order to solve this problem, this paper proposes a new PFL solution, a two‐stage PFL based on sparse pretraining, which can not only train a sparse personalized model for each client, but also obtain a sparse global model. The whole training process is divided into sparse pretraining and sparse personalized training, which focus on the performance of global model and personalized model respectively. Also, we propose a mask sparse aggregation technique to maintain the sparsity of the global model in the sparse personalized training stage. Experimental results show that compared with existing algorithms, our proposed algorithm can improve the accuracy of the global model while maintaining advanced personalized model accuracy, and has higher communication efficiency.

Abstract The CRISPR-Cas9 technology has changed the landscape of genome editing and has demonstrated extraordinary potential for treating otherwise incurable diseases. Engineering strategies to enable efficient intracellular delivery of CRISPR-Cas9 components has been a central theme for broadening the impact of the CRISPR-Cas9 technology. Various non-viral delivery systems for CRISPR-Cas9 have been investigated given their favorable safety profiles over viral systems. Many recent efforts have been focused on the development of stimuli-responsive non-viral CRISPR-Cas9 delivery systems, with the goal of achieving efficient and precise genome editing. Stimuli-responsive nanoplatforms are capable of sensing and responding to particular triggers, such as innate biological cues and external stimuli, for controlled CRISPR-Cas9 genome editing. In this Review, we overview the recent advances in stimuli-responsive nanoformulations for CRISPR-Cas9 delivery, highlight the rationale of stimuli and formulation designs, and summarize their biomedical applications.

Abstract Gastric cancer is a common type of gastrointestinal malignant tumor in China. The mechanism of the development and progression of gastric cancer remains the continuing research focus. The tumor microenvironment plays an important role in the development and progression of tumors. The present study used single-cell sequencing data to characterize the microenvironment of gastric cancer, investigate the effects of oxidative stress on gastric cancer microenvironmental cells through the comparison between cancer tissue and normal tissue, and identify the key genes associated with gastric cancer patients’ survival. The results showed that compared with normal gastric tissue, gastric cancer tissue had a decreased oxidative stress response, weaker oxidative detoxification ability, and increased oxidative stress-induced cell death. In the different types of single cells of gastric cancer microenvironment, the oxidative stress response of T cell was increased, the ability of oxidative detoxification was enhanced, and the oxidative stress-induced cell death was exacerbate. Mucous cell showed the same trend as gastric cancer cells: decreased oxidative stress response, weak oxidative detoxification ability, and weakened oxidative stress-induced cell death. Moreover, TRIM62, MET, and HBA1, which were significantly associated with oxidative stress, may be biomarkers for the prognosis of gastric cancer. High expression of TRIM62 indicated a good prognosis, while MET and HBA1 indicated a poor prognosis, which will be confirmed by further clinical studies.

The authors use optical tweezers to show that the folding of repeats-in-toxin (RTX) block-iv in adenylate cyclase is templated by the folded RTX block-v. The findings suggest a possible mechanism for transmitting the folding signal in the RTX domain.

Circular RNAs (circRNAs) have important potential in modulating vascular smooth muscle cell (VSMC) activity, but their roles in abdominal aortic aneurysm (AAA) are unknown. We performed in situ hybridization and immunohistochemistry and determined that circChordc1 (cysteine and histidine-rich domain containing 1) was markedly downregulated in aneurysm tissue compared with normal arteries. A gene gain and loss strategy was used to confirm that circChordc1 transformed VSMCs into a contracted phenotype and improved their growth, which significantly suppressed aneurysm formation and reduced the risk of rupture in mouse models of angiotensin (Ang) II- and CaCl2-induced AAA. RNA pull-down, immunoprecipitation, and immunoblotting indicated that circChordc1 facilitated the VSMC phenotype and growth determination by binding to vimentin and ANXA2 (annexin A2), which not only increased vimentin phosphorylation to promote its degradation but also promoted the interaction between ANXA2 and glycogen synthase kinase 3 beta (GSK3β) to induce the nuclear entry of β-catenin. Thus, our present study revealed that circChordc1 optimized the VSMC phenotype and improved their growth by inducing vimentin degradation and increasing the activity of the GSK3β/β-catenin pathway, thereby extenuating vascular wall remodeling and reversing pathological aneurysm progression.

The exploration of the spatiotemporal variations and influencing factors of grain yield in major grain-producing regions is greatly important to maintain stable and sustainable agriculture. Taking Henan Province and Heilongjiang Province as examples, this study reveals the spatiotemporal characteristics of grain yield at the county level by using multisource data on the economy, society, and natural geography from 2000 to 2021 and employing methods such as coefficients of variation, standard deviational ellipses, and spatial autocorrelation analysis. Moreover, geographical detector and geographically weighted regression models are combined to explore the differences in significant influencing factors between these provinces and the spatial heterogeneity of regression coefficients, respectively. The following findings are drawn: (1) Grain yield in both provinces gradually increased, with notable differences in the annual growth rate, the proportion, and at the county level. (2) The number of high-yield counties significantly increased and their spatial distribution became more concentrated, indicating a notable shift in the main regions. (3) The overall spatial correlation of grain yield steadily increased, and the local spatial correlation transitioned from random distribution to gradual aggregation. (4) There were significant differences in the influencing factors, where geographical environment, socio-economic factors, and input factors all affected both provinces. In summary, this study provides a scientific reference for governments worldwide to formulate rational and effective food production policies, thereby contributing to global food security and sustainable social development.

Tight oil is a great potential resource for unconventional oil exploration and development. Determining the content of adsorbed tight oil in sandstone reservoirs and the factors controlling its content is crucial for the evaluation and development of tight oil resources. Using fluorescence petrography, environmental scanning electron microscopy, porosity as well as permeability analyses, high-pressure mercury intrusion, and nuclear magnetic resonance imaging, the present study analyzed the occurrence form, location, and relative content of free and adsorbed tight oils and effect of controlling factors on the content of adsorbed tight oil in sandstone reservoirs of the Chang 8 member in the Huaqing area of the Ordos Basin. The free tight oil mainly exists in residual intergranular, intergranular dissolved, intragranular dissolved, and dissolution-enlarged pores as well as some throats in the form of flakes with various areas and slender strips. The adsorbed tight oil mainly occurs on the surfaces of the mineral particles and mica fragments as well as in fractures, some throats or the intragranular as well as intergranular dissolved pores in the form of films with variable thicknesses and long strips. The lower limit of the pore radius at which free tight oil occurs in sandstone is approximately 0.1 μm and the adsorbed tight oil occurs on the surface of mineral particles and in spaces with pore radii of 0.02–0.3 μm. The contribution of free tight oil to total tight oil in the present study has highest and lowest content of 60.95% and 32.48%, respectively, with an average content of 50.14%. The contribution of adsorbed tight oil to total tight oil has highest and lowest content of 67.52% and 39.05%, respectively, with an average content of 49.86%. The content of adsorbed tight oil is generally proportional to the median pressure and inversely proportional to the porosity as well as permeability of the reservoir; particularly, porosity is relevant. The content of adsorbed tight oil is inversely proportional to the quartz content and directly proportional to the feldspar, carbonate cement, and clay mineral content of the sandstone.

The difference of leaf disease images within the class is large but the difference between the class is small, so it is very important to represent the features of the local area of the target. Moreover, the complex network occupies a large amount of computer memory and wastes a large amount of computing resources, which is difficult to meet the needs of low-cost terminals. This paper proposes a fine-grained disease categorization method based on attention network to solve the problem. In “Classification Model”, attention mechanism is used to increase identification ability. “Reconstruction-Generation Model” were added during training and the “Classification Model” have to pay more attention to differentiate areas to find differences instead of paying more attention to global features. And adversarial loss was applied to distinguish the generated image from the original image to suppress the noise introduced by the “Discrimination Model”. Due to the feature that “Reconstruction-Generation Model” and “Discrimination Model” are only used in training and do not participate in the operation of inference phase, which cannot increase the complexity of the model. Compared with the traditional classification network, the method of generalization ability enhancement further enhances the identification accuracy. And the method needs less memory but can achieve low performance terminal real-time identification of peach and tomato leaf diseases. And it can be applied in other crop disease identification fields with the similar application scenarios.

There is great potential for tight oil as an alternative to conventional fossil fuels throughout the world. Adsorption, mineralogy, and pore structure of tight sandstone are very important factors for the efficient development of adsorbed tight oil from tight sandstone oil reservoirs. In this study, the occurrence morphology of tight oil adsorbed to varying pore structures was examined, as well as the relationship between adsorption content and occurrence morphology. X-ray energy dispersive spectra, environmental scanning electron microscope observations, and thin fluorescence sections were used to describe the occurrence morphology of adsorbed tight oil in tight sandstone reservoirs. It was found that adsorbed tight oil can be classified into five types: emulsion, cluster, throat, thin-film, and isolation, with average contents of 34.9%, 14.5%, 3.1%, 42.7%, and 4.7%, respectively. In addition, a Soxhlet extraction was developed with four pore structures to describe the geological effects of adsorbed tight oil in reservoirs. The adsorption content of tight oil ranges from 4.015 mg/g to 16.987 mg/g, with an average of 10.115 mg/g. The order of adsorption content for different occurrence morphologies is as follows: emulsion form > throat form > cluster form > isolation form > thin-film form. It is the size and connectivity of the porous throat that determines the desorption efficiency of tight oil. An important outcome of this study can be the introduction of rational development plans and the improvement of oil recovery efficiency for tight oil reservoirs.

Necroptosis, a kind of programmed necrotic cell apoptosis, is the gatekeeper for the host to defend against the invasion of pathogens. It helps to regulate different biological processes regarding human cancer. Nevertheless, studies that determine the impact of death on triple-negative breast cancer (TNBC) are scarce. Therefore, this paper has comprehensively examined the expression as well as clinical significance of necroptosis in TNBC. ConsensusClusterPlus was used to establish a stable molecular classification that used the expression regarding the necroptosis-linked genes. The clinical and immune characteristics of different subclasses were evaluated. Then, the weighted gene coexpression network analysis (WGCNA) assisted in determining key modules, and we selected the genes exhibiting obvious association with necroptosis prognosis through the relationship with prognosis. The univariate Cox regression analysis together with least absolute shrinkage and selection operator (LASSO) techniques served for the construction of the necroptosis-related prognostic risk score (NPRS) model, and the pathway characteristics of NPRS model grouping were further studied. Finally, the NPRS, taking into account the clinicopathological features, used the decision tree model for enhancing the prognostic model as well as the survival prediction. First, two stable molecular subtypes with different prognosis and immune characteristics were identified using necroptosis marker genes. Then, the key modules were identified, and 10 genes significantly related to the prognosis of necroptosis were selected. Then, the clinical prognostic model of NPRS was developed considering the prognosis-linked necroptosis genes. Finally, the NPRS model, taking into account the clinicopathological features, adopted the decision tree model for enhancing the prognostic model as well as the survival prediction. Herein, two new molecular subgroups considering necroptosis-linked genes are proposed, and an NPRS model composed of 10 genes is developed, which maybe assist in the personalized treatment and clinical treatment guidance of TNBC patients.

Disasters are becoming the norm in this world, which also poses challenges to architects. Many needs to build temporary buildings may occur at the same time randomly around all over the world. Constructing an efficient and economical solution is the motivation of this research. Through a comprehensive review of all past related researches and architectural practices, “convenience” and “recyclability” have been identified as two important features of temporary buildings in the post-pandemic era. In this article, we carry on a novel research of discrete architecture. Based on the design paradigm of discrete architecture, this research uses the three main components of S/U/P to develop a Lego Architecture design method by combining with the Grasshopper plug-in under the Rhino platform to write a program that automatically generates the target plan. Then, a typical design scheme for physical construction verification and structural optimization is selected to ensure landing and safety. Originating from the thinking of productization, this research attempts to package the design methods and related knowledge into a systematic solution, relying on an open construction system framework to achieve a rapid, simple and safe construction of temporary buildings after disasters.

Aims: Metabolic switching during heart development contributes to postnatal cardiomyocyte (CM) cell cycle exit and loss of regenerative capacity in the mammalian heart. Metabolic control has potential for developing effective CM proliferation strategies. We sought to determine whether lactate dehydrogenase A (LDHA) regulated CM proliferation by inducing metabolic reprogramming. Methods and results: LDHA expression was high in P1 hearts and significantly decreased during postnatal heart development. CM-specific LDHA knockout mice were generated using CRISPR/Cas9 technology. CM-specific LDHA knockout inhibited CM proliferation, leading to worse cardiac function and a lower survival rate in the neonatal apical resection model. In contrast, CM-specific overexpression of LDHA promoted CM proliferation and cardiac repair post-MI. The α-MHC-H2B-mCh/CAG-eGFP-anillin system was used to confirm the proliferative effect triggered by LDHA on P7 CMs and adult hearts. Metabolomics, proteomics and Co-IP experiments indicated that LDHA-mediated succinyl coenzyme A reduction inhibited succinylation-dependent ubiquitination of thioredoxin reductase 1 (Txnrd1), which alleviated ROS and thereby promoted CM proliferation. In addition, flow cytometry and western blotting showed that LDHA-driven lactate production created a beneficial cardiac regenerative microenvironment by inducing M2 macrophage polarization. Conclusions: LDHA-mediated metabolic reprogramming promoted CM proliferation by alleviating ROS and inducing M2 macrophage polarization, indicating that LDHA might be an effective target for promoting cardiac repair post-MI.

BackgroundRed blood cell distribution width (RDW) to albumin ratio (RAR) is associated with poor prognosis in diabetic comorbidities and cancer. However, the association between RAR and prognosis in patients with sepsis remains unclear, which was investigated in this study.MethodsWe conducted a retrospective cohort study based on the Medical Information Mart for Intensive Care (MIMIC) IV version 2.0 database. The primary outcome of this study was 28-day mortality. Secondary outcomes included 90-day mortality, in-hospital mortality, length of hospital stay, and length of intensive care unit (ICU) stay. Multivariate regression analysis and subgroup analysis were performed to investigate the association between RAR and prognosis in patients with sepsis.ResultsA total of 14,639 participants were included in this study. The mean age of the participants was 65.2 ± 16.3 years and the mean RAR was 5.5 ± 1.9 % /g/dl. For 28-day mortality, after adjusting for covariates, HRs [95% confidence intervals (CIs)] for tertiles 2 (4.4–5.8) and 3 (RAR > 5.8) were 1.33 (1.20, 1.46) and 1.98 (1.79, 2.19), respectively. Similar results were observed for 90-day mortality and in-hospital mortality. According to Kaplan-Meier curve analysis, the higher RAR group had higher 28-day mortality and 90-day mortality.ConclusionOur study shows that RAR is significantly associated with poor clinical prognosis in sepsis. The higher the RAR, the higher the 28-day, 90-day, and in-hospital mortality.

Chitin synthases (CHSs) are vital enzymes for the synthesis of chitin and play important and differential roles in fungal development, cell wall integrity, environmental adaptation, virulence, and metabolism in fungi. However, except for ChsC, a class III CHS, little is known about the functions of CHSs in Aspergillus niger, an important fungus that is widely applied in the fermentation industry and food processing, as well as a spoilage fungus of food and a human pathogen. This study showed the important functions of ChsA, a class II CHS, in A. niger using multi-phenotypic and transcriptional analyses under various conditions. The deletion of chsA led to severe defects in conidiation on different media and resulted in the formation of smaller and less compact pellets with less septa in hyphal cells during submerged fermentation. Compared with the WT, the ΔchsA mutants exhibited less chitin content, reduced growth under the stresses of cell wall-disturbing and oxidative agents, more released protoplasts, a thicker conidial wall, decreased production of amylases, pectinases, cellulases, and malic acid, and increased citric acid production. However, ΔchsA mutants displayed insignificant changes in their sensitivity to osmotic agents and infection ability on apple. These findings concurred with the alteration in the transcript levels and enzymatic activities of some phenotype-related genes. Conclusively, ChsA is important for cell wall integrity and mycelial morphology, and acts as a positive regulator of conidiation, cellular responses to oxidative stresses, and the production of malic acid and some enzymes, but negatively regulates the citric acid production in A. niger.

Iron (Fe) migration in soil-plants is a critical part of Fe biogeochemical cycling in the earth surface system. Fe isotope fractionation analysis in the soil-rice system is promising for quantitatively assessing various pathways and clarifying Fe transformation processes. However, the mechanisms of Fe isotope fractionation in the soil-rice system are not well understood. In this study, the Fe isotopic compositions (δ56Fe) of rhizosphere soils, pore water, Fe plaque, and rice plant tissues at the jointing and mature stages of the plants were determined. The rice plants were slightly enriched in heavier δ56Fe by ∼0.3‰ relative to the soil, and the stele and cortex showed similar δ56Fe values, indicating that the uptake of Fe by rice plants predominantly occurred via Fe(III)-phytosiderophores (Fe(III)-PS) chelation, but not Fe(III) reduction. Additionally, at both the jointing and mature stages, the rice plant tissues showed similar δ56Fe values. However, the Fe isotope fractionation between the roots and stems (Δ56Feroot−stem) was 1.39 ± 0.13‰, which is similar to the previously Ab initio-calculated values between Fe(III)-citrate and Fe(III)- 2-deoxymugineic acid (DMA), indicating that both the phloem and xylem have similar δ56Fe values, and the major Fe-chelating substances in the phloem of the rice plants are Fe(III)-DMA and Fe(II)- Nicotianamine (NA). Therefore, this study demonstrates that Fe isotope fractionation can be used as a signature for interpreting the Fe uptake and translocation mechanism in the soil-rice system.

Cancer metastasis is the leading cause of death in patients, here, the authors show disrupting tumor vasculature could recruit and activate anti-PD-L1 engineered platelet at metastatic tumor sites to block the PD-1/PD-L1 crosstalk and enhance the anticancer immunotherapy.

Amyloidogenesis is one of the key pathophysiological changes in Alzheimer’s disease (AD). Accumulation of the toxic Aβ results from the catalytic processing of β-amyloid precursor protein (APP) associated β-amyloid converting enzyme 1 (BACE1) activity. It is reported that dead-box helicase 17 (DDX17) controls RNA metabolism and is involved in the development of multiple diseases. However, whether DDX17 might play a role in amyloidogenesis has not been documented. In the present study, we found that DDX17 protein level was significantly increased in HEK and SH-SY5Y cells that stably express full-length APP (HEK-APP and Y5Y-APP) and in the brain of APP/PS1 mice, an animal model of AD. DDX17 knockdown, as opposed to DDX17 overexpression, markedly reduced the protein levels of BACE1 and the β-amyloid peptide (Aβ) in Y5Y-APP cells. We further found that DDX17-mediated enhancement of BACE1 was selectively attenuated by translation inhibitors. Specifically, DDX17 selectively interacted with the 5′ untranslated region (5′UTR) of BACE1 mRNA, and deletion of the 5′UTR abolished the effect of DDX17 on luciferase activity or protein level of BACE1. Here, we show that the enhanced expression of DDX17 in AD was associated with amyloidogenesis; through the 5′UTR-dependent BACE1 translation, DDX17 might serve as an important mediator contributing to the progression of AD.

Governmental attention towards the high-quality development of the Yellow River basin has brought new development opportunities for the hotel industry. This study aims to reveal the spatial-temporal evolution patterns and influencing factors of hotels in the Yellow River Basin from 2012 to 2022, based on economic, social, and physical geographic data of 190,000 hotels in the Yellow River flowing. With the help of a GIS technology system, the spatial-temporal evolution patterns of all hotels, star hotels, and ordinary hotels were explored, respectively. Then, the significant influencing factors of these patterns were revealed by using geographic detector and Person correlation analysis. The following conclusions were drawn: (1) the overall scale of the hotel industry in the Yellow River Basin expanded year by year, achieving rapid growth from 2016, and fluctuating around 2020 due to the impact of the novel coronavirus epidemic; the overall spatial distribution had significant regional differences, showing the structural characteristics of “southeast more, northwest less”; (2) there was a great difference in the degree of spatial autocorrelation agglomeration among prefecture-level cities, and the degree of agglomeration of both the hotel industry as a whole and general hotels decreased year by year, showing a random distribution in 2022; star hotels were always distributed randomly. Additionally, a strong synergistic correlation was shown between the number of ordinary hotels and the number of star hotels in local space; (3) overall, the development of the hotel industry was significantly affected by seven factors: structural force, macro force, ecological force, internal power, consumption power, intermediary power, and external power. There were differences in the forces acting on different types of hotels, which gives a pattern recognition in-depth.

In order to investigate pore structure characteristics of Wufeng and Longmaxi Formations shales in the Sichuan Basin, the organic geochemical parameter and petrologic experiments, N2 and CO2 adsorptions, field emission scanning electron microscopy analysis and helium porosity measurement are carried out. Results showed that the thermal maturity of shales belong to over-maturity stage with TOC content and porosity of 1.84%–6.82% and 2.6%–5.1%, respectively. The TOC content has a good correlation with quartz, weak correlation with clay and no correlation with carbonate, indicating that the organic matter is mainly controlled by quartz content. The N2 and CO2 specific surface areas of organic-rich shale is generally 16.86–29.71 m2/g and 13.76–26.47 m2/g, respectively and the average N2 and CO2 specific surface area of organic-poor shale are 8.91 m2/g and 9.11 m2/g respectively, which indicating that the organic-rich shale has higher specific surface area, pore volume and smaller average pore diameter than that of organic-poor shale. The specific surface area in organic-rich shale is mainly contributed by micropores, while the pore volume is mainly contributed by mesopores, followed by micropores. There is a very strong correlation between TOC and CO2 and N2 specific surface area, indicating that pores were controlled by organic matter. Both porosity and specific surface have a positive relation when clay content is less than 28% for organic-rich shale, and its correlation is not obvious when clay content is more than 28% for organic-poor shale, indicating that the clay has a certain effect on reservoir.

Microbial degradation is considered as an attractive method to eliminate exposure to aflatoxin B1 (AFB1), the most toxic mycotoxin that causes great economic losses and brings a serious threat to human and animal health, in food and feed. In this study, Bacillus amyloliquefaciens WF2020, isolated from naturally fermented pickles, could effectively degrade AFB1 ranging from 1 to 8 μg/ml, and the optimum temperature and pH value were 37–45°C and 8.0, respectively. Moreover, B. amyloliquefaciens WF2020 was considered to be a potential probiotic due to the synthesis of active compounds, absence of virulence genes, susceptibility to various antibiotics, and enhanced lifespan of Caenorhabditis elegans. Extracellular enzymes or proteins played a major role in AFB1 degradation mediated by B. amyloliquefaciens WF2020 into metabolites with low or no mutagenicity and toxicity to C. elegans. AFB1 degradation by the cell-free supernatant was stable up to 70°C, with an optimal pH of 8.0, and the cell-free supernatant could still degrade AFB1 by 37.16% after boiling for 20 min. Furthermore, B. amyloliquefaciens WF2020 caused a slight defect in fungal growth and completely inhibited AFB1 production when co-incubated with Aspergillus flavus. Additionally, B. amyloliquefaciens WF2020 suppressed the expression of 10 aflatoxin pathway genes and 2 transcription factors (alfR and alfS), suggesting that B. amyloliquefaciens WF2020 might inhibit AFB1 synthesis in A. flavus. These results indicate that B. amyloliquefaciens WF2020 and/or its extracellular enzymes or proteins have a promising potential to be applied in protecting food and feed from AFB1 contamination.

Identifying effective drugs to delay the progression of aortic aneurysms is a formidable challenge in vascular medicine. Methyltransferase-like 3 (METTL3) plays a key role in catalyzing the formation of N6-methyladenosine (m6A), but despite the functional importance of METTL3 and m6A in various fundamental biological processes, their roles in abdominal aortic aneurysm (AAA) are unknown. Here, we found that METTL3 knockdown in apolipoprotein E-deficient (ApoE−/−) mice treated with angiotensin II suppressed the formation of AAAs, while METTL3 overexpression exerted the opposite effects. Similar results were obtained in a calcium chloride (CaCl2)-induced mouse AAA model. Mechanistically, METTL3-dependent m6A methylation promoted primary microRNA-34a (miR-34a, pri-miR34a) maturation through DGCR8. Moreover, miR-34a overexpression significantly decreased SIRT1 expression and aggravated AAA formation, while miR-34a deficiency produced the opposite effects. In a rescue experiment, miR-34a knockdown or forced expression of SIRT1 partially attenuated the protective effects of METTL3 deficiency against AAA formation. Our studies reveal an important role for METTL3/m6A-mediated miR-34a maturation in AAA formation and provide a novel therapeutic target and diagnostic biomarker for AAA treatment.

Abstract Background Transcatheter aortic valve implantation (TAVI) has been a favored option for the patient who suffered from symptomatic aortic stenosis. However, the efficacy and safety outcomes in novel oral anticoagulants (NOACs) versus Vitamin-K antagonist (VKA) for post-TAVI patients are still controversial. This meta-analysis aims at comparing the clinical outcome and safety of NOACs and VKA in the patients after receiving TAVI. Method We searched literature articles in all reachable databases, and observational study as well as randomized controlled trial would be included in order to perform a comprehensive analysis. All-cause mortality, major or life-threatening bleeding, disabling or nondisabling stroke were main pooled outcome measures. Subgroup analysis and meta-regression were adopted to explore heterogeneity. Assessment of bias was performed under the suggestion of Cochrane’s Collaboration Tool. Results We collected 3841 non-duplicate citations from PubMed, Embase, Cochrane and ClinicalTrials.gov, and eventually 7 studies were included for this meta-analysis. As a result, VKA showed priority against NOACs in the field of anti-thromboembolism (4435 participants, RR:1.44, 95% CI: 1.05 to 1.99, I2 = 0%, P = 0.02). Conclusion With corroborative analysis of severe complications, VKA is shown to be more protective on post-TAVI patients in disabling or nondisabling stroke scenario but not in mortality or bleeding event.

In recent years, neuroscientists have discovered that the neural information is encoded by spike trains with precise times. Supervised learning algorithm based on the precise times for spiking neurons becomes an important research field. Although many existing algorithms have the excellent learning ability, most of their mechanisms still have some complex computations and certain limitations. Moreover, the discontinuity of spiking process also makes it very difficult to build an efficient algorithm. This paper proposes a supervised learning algorithm for spiking neurons using the kernel function of spike trains based on a unit of pair-spike. Firstly, we comprehensively divide the intervals of spike trains. Then, we construct an optimal selection and computation method of spikes based on the unit of pair-spike. This method avoids some wrong computations and reduces the computational cost by using each effective input spike only once in every epoch. Finally, we use the kernel function defined by an inner product operator to solve the computing problem of discontinue spike process and multiple output spikes. The proposed algorithm is successfully applied to many learning tasks of spike trains, where the effect of our optimal selection and computation method is verified and the influence of learning factors such as learning kernel, learning rate, and learning epoch is analyzed. Moreover, compared with other algorithms, all experimental results show that our proposed algorithm has the higher learning accuracy and good learning efficiency.

Spectrum prediction is a key enabler of a range of emerging applications, from adaptive spectrum sensing to agile and proactive decision making, for dynamic spectrum access. Due to the fact that spectrum sensors easily experience an issue of missing readings and anomaly pollution, spectrum prediction with incomplete and corrupted historical observations has caused extensive concern. In this paper, we aim to tackle the challenging problem on how to accurately and efficiently recover the missing values from corrupted historical spectrum observations for approaching the limit of predictability in the spectrum prediction tasks. Specially, we first formulate a hankelized time-structured spectrum tensor that can naturally preserve both spectral and temporal dependencies among the historical spectrum observations. We then model the spectrum data recovery problem as tensor completion with its latent low-rank structure and sparse anomaly property. To efficiently solve the optimization problem, we design a robust online spectrum data recovery algorithm based on the alternating direction method. In addition, we also introduce the concept of maximum predictability to reveal the harmful effects of missing data and anomalies, as well as to evaluate the effectiveness of our proposed algorithm from an information theory perspective. Extensive experimental evaluations on the real-world spectrum observation dataset show that the proposed algorithm achieves significantly better spectrum data recovery performance in terms of both recovery accuracy and computation efficiency. It also indicates that not only the predictability of the frequency bands but also the prediction accuracy of any predictive algorithm can be improved by the proposed algorithm.

The Upper Ordovician Wufeng Formation and Lower Silurian Longmaxi Formation black shales are the critical targets for shale gas exploration in the Sichuan Basin of South China. The enrichment of organic matter (OM) in shale is the basis for the generation of large-scale shale gas; however, its controlling factors in Wufeng-Longmaxi shales are still under debate, and few studies have focused on the edge of the Sichuan Basin. Based on the mineral composition, total organic carbon (TOC), and systematic inorganic geochemistry analysis of 72 core samples from Wufeng and Longmaxi formations in Well Xike 1, southeastern Sichuan Basin, the sedimentary conditions (palaeoclimate, palaeoredox, and palaeoproductivity) were reconstructed, and the controlling factors of OM enrichment were identified. The mineral compositions are dominated by quartz, clay minerals, calcite, and feldspar, associated with minor dolomite, pyrite, and anhydrite. The TOC contents (0.31%-6.84%, avg. 2.22%) show an upward decreasing trend from the Wufeng Formation to Longmaxi Formation. The chemical index of alteration (CIA) ranges from 65 to 71 (avg. 69), indicating warm and humid climate with moderate weathering. The diagrams of Al2O3-TiO2, TiO2-Zr, Zr/Sc-Th/Sc, La/Th-Hf, and La-Th-Sc jointly indicate the contribution from felsic and intermediate rock weathering. The P/Al, Cu/Al, and Ni/Al ratios suggest that marine paleoproductivity was relatively high in the Wufeng Formation and relatively low to moderate in the Longmaxi Formation. The V/Cr, V/Sc, U/Th, MoEF/UEF, and Corg/P ratios indicate that the bottom water was anoxic during the Wufeng Formation deposition and then fluctuating dysoxic and/or oxic in the overlying Longmaxi Formation. The TOC content was positively correlated with productivity proxies (P/Al, Cu/Al, and Ni/Al) as well as redox proxies (U/Th, V/Cr, MoEF/UEF, and Corg/P), indicating that the OM accumulation in Wufeng-Longmaxi shales is mainly controlled by high productivity and anoxic bottom water conditions.