Search

Abstract Studies have used extensive clinical information to predict time-to-heart failure (HF) in patients with and without diabetes mellitus (DM). We aimed to determine a screening method using only computed tomography calcium scoring (CTCS) to assess HF risk. We analyzed CTCS scans from 1,998 patients (336 with type 2 diabetes) from a no-charge coronary artery calcium score registry (CLARIFY Study, Clinicaltrials.gov NCT04075162). We used deep learning to segment epicardial adipose tissue (EAT) and engineered radiomic features of calcifications (“calcium-omics”) and EAT (“fat-omics”). We developed models incorporating radiomics to predict risk of incident HF in patients with and without type 2 diabetes. At a median follow-up of 1.7 years, 5% had incident HF. In the overall cohort, fat-omics (C-index: 77.3) outperformed models using clinical factors, EAT volume, Agatston score, calcium-omics, and calcium-and-fat-omics to predict HF. For DM patients, the calcium-omics model (C-index: 81.8) outperformed other models. In conclusion, CTCS-based models combining calcium and fat-omics can predict incident HF, outperforming prediction scores based on clinical factors.Please check article title if captured correctly.YesPlease check and confirm that the authors and their respective affiliations have been correctly identified and amend if necessary.Yes

Abstract Background Silicosis has always been a serious global occupational health problem. Oral microbiota plays important roles in the development of lung disease. However, few studies have investigated the relationship between periodontal conditions, oral bacteria and silicosis disease. Method A single-center and cross-sectional study was conducted in 2019 in Sichuan Province, China, including a small sample of silicosis patient group and healthy control group. Demographic data and periodontal examinations measured by clinical attachment loss (CAL), bleeding on probing (BOP) and periodontal pocket (PD) were collected from each participant. Phenotypic changes were detected by histopathological staining. Next-generation sequencing targeting 16S ribosomal RNA was targeted to decipher the salivary microbiome of the two groups. Random forest, Least Absolute Shrinkage and Selection Operator (LASSO) logistic regression and multivariable logistic regression analysis were conducted to find potential indicators to distinguish silicosis. Results In general, 29 male healthy controls and 24 male silicosis patients were included. The proportion of CAL ≥ 3 mm in silicosis group was greater than control group, while the proportion of BOP (+) and PD ≥ 4 mm was reduced in silicosis group. The α-smooth muscle actin and fibronectin expression increased in gingiva of patients. The composition of salivary microbiota exhibited significant differences between the two groups, with silicosis patients demonstrating a lower diversity of salivary microbiota. Genus of Aggregatibacter [odds ratio (OR) = 0.000, p = 0.003] and Catonella (OR = 0.000, p = 0.049) were identified as biomarkers to distinguish silicosis. Conclusions The silicosis group exhibited worse CAL, improved BOP and PD, which may be related to the gingival fibrosis found in this study. The composition of the oral microbiota underwent significant changes, accompanied by a decrease in diversity, in patients with silicosis. Our study indicates that respirable crystalline silica exposure affects oral health, and alterations of oral microbiota might be implicated in silicosis. We primarily identified Aggregatibacter and Catonella as the potential indicators to distinguish silicosis patients from healthy controls.

Abstract Phytochrome interacting factors (PIFs) serve as crucial regulators in the light signal transduction pathway and also mediate light signals to regulate secondary metabolite synthesis in plants. However, the regulator role of PIFs in secondary metabolites often varies among different plants. Isorhynchophylline (IRN), an iconic secondary metabolite of Uncaria rhynchophylla, holds significant medicinal value. Low light induces the synthesis of IRN in previous research, but PIFs in U. rhynchophylla have not been studied to date. Building on this, we identified a PIF protein, UrPIF3, which possesses the typical conserved domains of the PIFs and is localized in the nucleus. Moreover, the expression level of UrPIF3 is consistently positively correlated with the expression of two key enzyme genes (UrSGD and UrSTR) in the IRN biosynthesis pathway, regardless of whether under low light or restoring light conditions. Yeast one-hybrid and dual-luciferase assays further demonstrated that UrPIF3 can directly upregulate UrSGD. Conversely, silencing UrPIF3 inhibits IRN synthesis, and significantly reduces the expression levels of UrSGD and UrSTR. In summary, our results suggest that under low light conditions, UrPIF3 can directly upregulate UrSGD and indirectly upregulate UrSTR, thereby promoting the synthesis of IRN.

Abstract As one of the most common malignancies, colorectal cancer (CRC) usually starts with a benign lesion and accumulates DNA damage as it progresses to full-fledged cancer. Glycyrrhizin (GL) has been found to alleviate tumor growth and inflammation, while the role of GL influences DNA damage response (DDR) in colorectal cancer remains unclear. GL exposure significantly reduced cell colony formation and viability with a concomitant increase in DNA fragmentation in CRC, meanwhile GL induced apoptosis by activating caspase-3. Moreover, GL induced cell cycle arrest in CRC cells at S phase, which was associated with decreased cyclin D1 in vitro. GL treatment significantly ameliorated tumor growth and promoted DDR in vivo. Mechanism analysis revealed that GL significantly downregulated the NHEJ pathway via inhibiting HMGB1. Finally, the expression of HMGB1 was abnormal regulated in CRC tissue than in adjacent normal tissues and associated with TNM stage and overall survival. Our findings indicate that HMGB1 may be a novel therapeutic target in CRC, a result that GL may serve as a promising drug for CRC treatment.

Abstract This study employed lignin-sulfonated (LS) to develop biobased carbon materials (LS-Cs) through a sulfur-doping approach to enhance their physicochemical properties, adsorption capabilities, and energy storage potentials. Various characterization techniques, including BET surface area analysis, SEM imaging, XPS, Raman spectroscopy, and elemental composition (CHNS), were employed to assess the quality of the LS-Cs adsorbent and electrode samples. Response Surface Methodology (RSM) was utilized for optimizing the two main properties (specific surface area, ABET, and mesopore area, AMESO) by evaluating three independent factors (i.e., activation temperature, ZnCl2:LS ratio, and sulfur content). According to the statistical analysis, ABET and AMESO were affected by ZnCl2 and sulfur content, while the pyrolysis temperature did not affect the responses in the studied conditions. It was found that increasing the ZnCl2 and sulfur contents led to an increment of the ABET and AMESO values. The LS-C materials exhibited very high ABETvalues up to 1993 m2 g−1 and with predominantly mesoporous features. The S-doping resulted in LS-Cs with high sulfur contents in their microstructures up to 15% (wt%). The LS-C materials were tested as adsorbents for sodium diclofenac (DCF) adsorption and reactive orange 16 dye (RO-16) and as electrodes for supercapacitors. The LS-Cs exhibited excellent adsorption capacity values for both molecules (197–372 mg g−1) for DCF, and (223–466 mg g−1) for RO-16. When tested as electrodes for supercapacitors, notably, LS-C3, which is a doped sample with sulfur, exhibited the best electrochemical performance, e.g. high specific capacitance (156 F/g at 50 mV/s), and delivered an excellent capacitance after 1000 cycles (63 F/g at 1 A/g), which denotes the noteworthy capacitive behavior of the S-doped electrode. Thus, the present work suggests an eco-friendly resource for developing effective, productive carbon materials for adsorbent and electrodes for SC application. However, further studies on the complete application of these materials as adsorbents and electrodes are needed for a deeper understanding of their behavior in environmental and energy storage applications.

Abstract Background Gegen Qinlian Decoction (GQD) is a classical traditional Chinese medicine (TCM) formula primarily utilized for treating gut disorders. GQD showed therapeutic effects on several diseases in clinical and animal studies by targeting gut microbes. Our recent studies also found that GQD efficiently alleviated anxiety in methamphetamine-withdrawn mice via regulating gut microbiome and metabolism. Given that various studies have indicated the link between the gut microbiome and the development of depression, here we endeavor to explore whether GQD can manage depression disorders by targeting the gut microbiome. Methods and materials The depression-like model was induced in rats through chronic unpredictable mild stress (CUMS) and the depression levels were determined using the sucrose preference test (SPT). To address the depression-like behavior in rats, oral administration of GQD was employed. The colon microbiome and metabolite patterns were determined by 16s rRNA sequencing and untargeted metabolomics, respectively. Results We found 6 weeks of CUMS can induce depression-like behavior in rats and 4 weeks of GQD treatment can significantly alleviate the depression-like behavior. GQD treatment can also ameliorate the histological lesions in the colon of CUMS rats. Then, CUMS increased the abundance of gut microbes, while GQD treatment can restore it to a lower level. We further discovered that the abundances of 19 bacteria at the genus level were changed with CUMS treatment, among which the abundances of Ruminococcus, Lachnoclostridium, Pygmaiobacter, Bacteroides, Pseudomonas, and Pseudomonas Family_XIII_AD3011_group were stored by GQD treatment. Besides, we identified the levels of 36 colon metabolites were changed with CUMS treatment, among which the levels of Fasciculic acid B, Spermine, Fludrocortisone acetate, alpha-Ketoglutaric acid, 2-Oxoglutaric acid, N’-(benzoyloxy)-2-(2,2-dichlorocyclopropyl) ethanimidamide, N6-Succinyl Adenosine Oleanolic acid, KQH, Ergosta-5,7,9(11),22-Tetraen-3-beta-Ol, Gentisic acid, 4-Hydroxyretinoic Acid, FAHFA (3:0/16:0), Leucine-enkephalin and N-lactoyl-phenylalanine can be restored by GQD treatment. Conclusion Our findings provide evidence supporting the therapeutic efficacy of GQD in alleviating depression-like behavior in CUMS rats, potentially being targeted on colon bacteria (especially the abundance of Ruminococcus and Bacteroides) and metabolites (especially the level of Oleanolic acid).

Abstract South China Karst is the world’s largest continuous karst zone and is becoming the hotspot of greening earth. However, the greening sustainability remains uncertain due to challenges from carbonate geological constraints and oversights in recognizing synergies within social-ecological systems. Here, the sustainability and drivers of tree cover restoration were quantitatively investigated in South China Karst. The area with tree cover increasing was 652,457 km2, about 33.67% of the study area. There were differences in ecological elements between karst and non-karst areas, and rural population decrease in undeveloped areas could greatly promote tree cover restoration. Moreover, the correlation degree of social-ecological network in karst area was obviously lower than that in non-karst area, indicating higher heterogeneity of social-ecological system in karst area. This study highlights the social-ecological effects on tree cover restoration in karst area, and a shift in focus from the natural ecosystem to coupled social-ecological systems is crucial for sustainable forest management.

In the dynamic field of the internet in modern life, networks are increasingly vulnerable to a diverse range of cyberattacks. Conventional intrusion detection systems based on machine learning techniques require a large number of samples for training. However, in some scenarios, only a limited number of malicious samples can be collected. To address the issue of insufficient training samples and unbalanced sample classes for intrusion detection system in real network environments, this paper proposes an intrusion detection method named DeepInsight–transfer learning–convolutional neural network (DI–TL–CNN), which is based on DI and TL. First, the DI method is used to convert the intrusion dataset into an image form suitable for CNN model input. The DI method can transform text while maintaining the semantic relationships between data points, thereby providing high-quality images. In this step, we map the 1D feature vector representation of the input data onto the 2D image representation using T-SNE and construct 2D grayscale images. In the second step, we train and optimize the VGG16 model through TL and fine-tuning, enhancing the model’s adaptability and performance. We propose six TL schemes by freezing and fine-tuning the parameters of different modules in the CNN model to enhance intrusion detection performance. In the TL process, the VGG16 model, pretrained on the ImageNet dataset, demonstrates promising results for generic image classification tasks. The bottom layers of CNN models often learn basic feature patterns that are applicable to various tasks, while the features acquired by the top layers of the model are specific to the target domain intrusion dataset. Fine-tuning allows the model to adjust the pretrained architecture’s higher-order features to better match the targeted dataset. During the training process, the bottom layers of the pretrained architecture are frozen, whereas the top layers are unfrozen for fine-tuning. The optimal intrusion detection model is determined through a comparison of the performance of the six TL schemes. Finally, the correctness and effectiveness of the proposed DI–TL–CNN method are validated on a dataset with insufficient training samples, using metrics such as accuracy, precision, recall, and F1-score. In the experiments, compared with existing state-of-the-art models for intrusion detection, the proposed method considerably enhances accuracy in the detection of network traffic data. The experimental results show that the DI–TL–CNN method is suitable for intrusion detection with small samples and unbalanced data, demonstrating the good application prospects of the method in complex networks.

Abstract Not all MET exon 14 skipping (METex14) NSCLC patients benefited from MET inhibitors. We hypothesized an inter-tumoral heterogeneity in METex14 NSCLC. Investigations at genomic and transcriptomic level were conducted in METex14 NSCLC samples from stage I-III and recurrent/metastatic patients as discovery and validation cohort. Four molecular subtypes were discovered. MET-Driven subtype, with the worst prognosis, displayed MET overexpression, enrichment of MET-related pathways, and higher infiltration of fibroblast and regulatory T cells. Immune-Activated subtype having the most idea long-term survival, had higher tertiary lymphoid structures, spatial co-option of PD-L1+ cancer cells, and GZMK+ CD8+ T cell. FGFR- and Bypass-Activated subtypes displayed FGFR2 overexpression and enrichments of multiple oncogenic pathways respectively. In the validation cohort, patients with MET-Driven subtype had better response to MET inhibitors than those with MET overexpression. Thus, molecular subtypes of METex14 NSCLC with distinct biological and clinical significance may indicate more precise therapeutic strategies for METex14 NSCLC patients.

Abstract Background The escalating impacts of global warming intensify the detrimental effects of heat stress on crop growth and yield. Among the earliest and most vulnerable sites of damage is Photosystem II (PSII). Plants exposed to recurring high temperatures develop heat stress memory, a phenomenon that enables them to retain information from previous stress events to better cope with subsequent one. Understanding the components and regulatory networks associated with heat stress memory is crucial for the development of heat-resistant crops. Results Physiological assays revealed that heat priming (HP) enabled tall fescue to possess higher Photosystem II photochemical activity when subjected to trigger stress. To investigate the underlying mechanisms of heat stress memory, we performed comparative proteomic analyses on tall fescue leaves at S0 (control), R4 (primed), and S5 (triggering), using an integrated approach of Tandem Mass Tag (TMT) labeling and Liquid Chromatography-Mass Spectrometry. A total of 3,851 proteins were detected, with quantitative information available for 3,835 proteins. Among these, we identified 1,423 differentially abundant proteins (DAPs), including 526 proteins that were classified as Heat Stress Memory Proteins (HSMPs). GO and KEGG enrichment analyses revealed that the HSMPs were primarily associated with the “autophagy” in R4 and with “PSII repair”, “HSP binding”, and “peptidase activity” in S5. Notably, we identified 7 chloroplast-localized HSMPs (HSP21, DJC77, EGY3, LHCA4, LQY1, PSBR and DEGP8, R4/S0 > 1.2, S5/S0 > 1.2), which were considered to be effectors linked to PSII heat stress memory, predominantly in cluster 4. Protein-protein interaction (PPI) analysis indicated that the ubiquitin-proteasome system, with key nodes at UPL3, RAD23b, and UCH3, might play a role in the selective retention of memory effectors in the R4 stage. Furthermore, we conducted RT-qPCR validation on 12 genes, and the results showed that in comparison to the S5 stage, the R4 stage exhibited reduced consistency between transcript and protein levels, providing additional evidence for post-transcriptional regulation in R4. Conclusions These findings provide valuable insights into the establishment of heat stress memory under recurring high-temperature episodes and offer a conceptual framework for breeding thermotolerant crops with improved PSII functionality.

Abstract This study addresses the challenges in large-scale unmanned aerial vehicle (UAV) clusters, specifically the scalability issues and limitations of using reactive routing protocols for inter-cluster routing. These traditional methods place an excessive burden on cluster heads and struggle to adapt to frequently changing topologies, leading to decreased network performance. To solve these problems, we propose an innovative inter-cluster routing protocol (ICRP), which is based on a hybrid ant colony algorithm. During the route establishment phase, ICRP uses this algorithm to identify the optimal relay node. This approach is inspired by the foraging behavior of Physarum polycephalum, combining factors such as the number of hops from the source node, the load condition of the node, and its weight in the pheromone calculation. In the route maintenance phase, ICRP uses a predictive repair and contraction mechanism to dynamically maintain routes, accommodating the high mobility of UAVs. Comparative simulations in OMNeT + + showed that this protocol surpasses ad-hoc on-demand distance vector (AODV), fuzzy-logic-assisted-AODV, and Enhanced-Ant-AODV routing protocols in packet delivery rate and end-to-end transmission delay. Furthermore, it showed superior adaptation to network environments with high-speed node mobility.

Abstract R-loop-triggered collateral single-stranded DNA (ssDNA) nuclease activity within Class 1 Type I CRISPR-Cas systems holds immense potential for nucleic acid detection. However, the hyperactive ssDNase activity of Cas3 introduces unwanted noise and false-positive results. In this study, we identified a novel Type I-A Cas3 variant derived from Thermococcus siculi, which remains in an auto-inhibited state until it is triggered by Cascade complex and R-loop formation. This Type I-A CRISPR-Cas3 system not only exhibits an expanded protospacer adjacent motif (PAM) recognition capability but also demonstrates remarkable intolerance towards mismatched sequences. Furthermore, it exhibits dual activation modes—responding to both DNA and RNA targets. The culmination of our research efforts has led to the development of the Hyper-Active-Verification Establishment (HAVE, 惠父). This innovation enables swift and precise human papillomavirus (HPV) diagnosis in clinical samples, providing a robust molecular diagnostic tool based on the Type I-A CRISPR-Cas3 system. Our findings contribute to understanding type I-A CRISPR-Cas3 system regulation and facilitate the creation of advanced diagnostic solutions with broad clinical applicability.

In this study, SiO2 containing PAO6 microcapsules were endowed with surface active groups by polydopamine (PSPMS). Then the modified microcapsules were in situ grafted into phenolic resin (PF@PSPMS) to control the dispersion and bonding in high viscosity resin. Further, the tribological properties of the PF coating and the prepared liner were analyzed. The results show that the life of PF@PSPMS-coating is 73 times longer than that of PF-coating, the friction coefficient (COF) is reduced by 78%. Meanwhiles the COF of the corresponding liner is reduced from 0.11 to 0.06, and the wear amount is reduced from 64.07 μm to 23.07 μm. The wear mechanism shows that the breakage of PSPMS release lubricating oil at the friction interface, forming a coordinated solid-liquid lubrication effect with PTFE. At the same time, the presence of lubricating oil can remove the debris on the surface of the friction pair and improve the quality of the transfer film. In addition, the dispersion of silica fragments at the friction interface is conducive to improving the hardness and wear resistance. This work provides a new method for the dispersion of microcapsules in the liner and further explains the anti-friction and wear mechanism of silica microcapsules in the liner system, confirming the effectiveness of microcapsules in the liner system.

In order to solve the problems of ignoring multi-dimensional load characteristics, cumbersome modeling process and long design cycle in the design process of hydraulic support in steeply dipping angle coal seam, combined with the load characteristics of hydraulic support in large dip angle pseudo-inclined working face, the design system of large dip angle hydraulic support is developed. Based on the comprehensive research methods of motion simulation, strength test and physical experiment, taking the design of ZY5000/15.5/38 hydraulic support for steeply dipping angle coal seam as an example, the mechanical model is established according to the multi-dimensional stress characteristics of hydraulic support in large dip angle pseudo-inclined stope. The spatial load characteristics of large dip angle hydraulic support are analyzed, and the mechanical linear matrix of top beam and shield beam of hydraulic support in pseudo-inclined working face is established. The design system of hydraulic support is built by using VB.NET as the development language combined with linear matrix and SOLIDWORKS secondary development modeling software, and a good human-computer interaction user interface is developed. The research and analysis show that the trajectory range of the front end of the top beam of the model hydraulic support generated by the system is about 48 mm, and the trajectory curve of the front end of the top beam of the support satisfies the characteristics of double torsion line. The maximum stress value of the model support is 146.7 MPa, which is far less than the equivalent stress value of the material yield, and the maximum deformation displacement is not more than 0.531 mm. The working resistance of the physical model hydraulic support with a similarity ratio of 1:5 is about 38 kN. The loading characteristics of the top beam and the shield beam of the support are tested under different conditions. The mechanical data of the model support in the experiment are basically consistent with the mechanical data generated by the system, and the experiment meets the motion requirements and bearing characteristics of the support in the stages of initial support, resistance increase, constant resistance and pressure relief. The research results reflect the good adaptability of the model hydraulic support under the design system, which has certain scientific and practical significance for enriching the design theory of hydraulic support in steeply dipping angle coal seam and guiding the design and production of hydraulic support.

Abstract Low glucose is a common microenvironment for rapidly growing solid tumors, which has developed multiple approaches to survive under glucose deprivation. However, the specific regulatory mechanism remains largely elusive. In this study, we demonstrate that glucose deprivation, while not amino acid or serum starvation, transactivates the expression of DCAF1. This enhances the K48-linked polyubiquitination and proteasome-dependent degradation of Rheb, inhibits mTORC1 activity, induces autophagy, and facilitates cancer cell survival under glucose deprivation conditions. This study identified DCAF1 as a new cellular glucose sensor and uncovered new insights into mechanism of DCAF1-mediated inactivation of Rheb-mTORC1 pathway for promoting cancer cell survival in response to glucose deprivation.

Abstract Humid heatwaves negatively affect human health due to the integrating effect of temperature and humidity, and thus the early warning and timely mitigating on climate extremes are essential. Yet, systematic assessment on the intra‐annual onset and end of humid heatwaves, which is associated to the occurrence of first and last humid heatwaves, are missing globally. Using a new station‐based data set of daily maximum wet‐bulb temperature, the start and end dates, cumulative anomaly and extremely humid heat of the first and last humid heatwaves in the Northern Hemisphere were explored. It was found that at 91.54% of stations, humid heatwaves started earlier or ended later in the period of 2001–2020 compared to 1981–2000. High cumulative anomalies of the first or last humid heatwaves were found in the mid‐ and high‐latitude regions. Average difference between all humid heatwaves and the first humid heatwaves in cumulative anomalies increased steadily at stations north of 35°N. At regional scales, South East Asia had become the most prominent area with intensification of intra‐annual onset and end of humid heatwaves and will experience more frequent extreme events by 2100. Our findings demonstrated more intensified characteristics of the intra‐annual onset and end of humid heatwaves, calling for global awareness.

The extensive utilization of natural polymers in tissue engineering is attributed to their excellent biocompatibility, degradability, and resemblance to the natural extracellular matrix. These polymers have a wide range of applications such as delivering therapeutic medicine, detecting diseases, sensing biological substances, promoting tissue regeneration, and treating diseases. This is a brief review of current developments in the properties and uses of widely used biomedical polymers derived from nature. Additionally, it explores the correlation between the characteristics and functions of these materials in different biomedical applications and highlights the prospective direction for the advancement of natural polymer materials in tissue engineering.

Detecting soil arsenic (As) contamination is crucial for designing efficient soil remediation strategies; however, traditional laboratory-based As detection techniques are time- and labour-intensive and are unsuitable for large-scale spatial analyses. To address this issue, we combined machine learning (ML) with visible-near-infrared (vis-NIR) spectroscopy to develop an efficient framework for As detection in soil. The optimal spectral preprocessing method was determined, and eight ML models were compared. The support vector classifier achieved optimal performance after subsequent hyperparameter tuning, with area under the curve (AUC) and accuracy values of 0.89 and 0.83, respectively. Important spectral bands at 471 and 2422 nm were identified by permutation importance and correspond to Fe-oxide and carbonate, respectively. These two wavelengths were included in the partial dependence plot (PDP), revealing that the likelihood of soil As contamination decreased with increasing reflectance at wavelengths of 471 and 2422 nm due to a decrease in Fe-oxide and carbonate content. Consistent with this finding, two-way PDP analysis revealed that the As content of soil increased with increasing Fe-oxide and carbonate content. The model’s classification performance was further improved using an ensemble technique based on three optimal ML models, resulting in increased AUC and accuracy values of 0.9 and 0.83, respectively. Overall, the framework presented in this study enabled the precise classification of soil As content at the continental scale, while also indirectly explained the complex relationships between As content and soil properties.

IntroductionAs a new and efficient method for obstacle removal, laser clearance has promising applications in eliminating tree obstacles in transmission lines. This paper aims to explore various aspects related to the laser ablation of tree obstacles in transmission lines through simulation and experimentation.MethodsThis paper employs simulation and experimentation to test the ignition time, burn-through time, peak temperature, and basic carbonization rate of various types of tree obstacles in transmission lines. Additionally, it analyzes the effects of tree density, laser power, clearance distance, and tree moisture content on laser ablation characteristics.ResultsThe results reveal that different types of tree obstacles exhibit distinct ablation characteristics. With increasing tree density, both the ignition and burn-through times increase, while the peak temperature and basic carbonization rate decrease. Additionally, laser power and clearance distance significantly influence laser ablation behavior. Higher laser energy density results in greater heat flux density, leading to shorter ignition and burn-through times and higher peak temperatures and carbonization rates. Moreover, the tree obstacle with the highest moisture content (58.4%) had the shortest burn-through time of 46.56 s, whereas the one with the lowest moisture content (14.8%) took the longest at 58.41 s, which demonstrates that increased moisture content enhances the laser ablation rate.DiscussionThese findings provide a basis for the application of laser-based tree obstacle removal in power transmission lines. The understanding of how different factors such as tree density, laser power, clearance distance, and moisture content affect the laser ablation process can help in optimizing the laser clearance operations for more efficient removal of tree obstacles in transmission lines.

This paper concentrates on the numerical investigation of slip-flow and heat transfer characteristics in the entry region of elliptical microchannels under isothermal or isoflux boundary conditions. Slip boundaries caused by rarefaction effect are implemented using user-defined functions. The impacts of Reynolds number (25≤ Re ≤ 1000), Knudsen number (0.01≤ Kn ≤ 0.1), Peclet number (17.5 ≤ Pe ≤ 700) and aspect ratio (0.2≤ ε ≤ 1) on the apparent friction factor Reynolds number product fappRe and local Nusselt number Nu(x) are discussed in detail. The results demonstrate that at the entrance region, fappRe decreases with increasing Re, especially for ε = 0.33, Kn = 0.01 and Re

ABSTRACT Crustaceans are important food sources worldwide and possess significant ecological status in the marine ecosystem. However, our understanding of the diversity and evolution of RNA viruses in crustaceans, especially in economic crustaceans, is still limited. Here, 106 batches of economic crustaceans including 13 species were collected from 24 locations in China during 2016–2021. We identified 90 RNA viruses, 69 of which were divergent from the known viruses. Viral transcripts were assigned to 18 different viral families/clades and three unclassified groups. Among the identified viruses, five were double-stranded RNA viruses, 74 were positive-sense single-stranded RNA (+ssRNA) viruses, nine were negative-sense single-stranded RNA (−ssRNA) viruses, and two belonged to an unclassified RNA virus group. Phylogenetic analyses showed that crustacean viruses were often clustered with viruses identified from invertebrates. Remarkably, most crustacean viruses were closely related to those from different host species along the same food chain or ecological aquatic niche. In addition, the genome structures of the newly discovered picornaviruses exhibited remarkable diversity. Our study significantly expands the diversity of viruses in important economic crustaceans and provides essential data for the risk assessment of the pathogens spreading in the global aquaculture industry.IMPORTANCEThe study delves into the largely uncharted territory of RNA viruses in crustaceans, which are not only vital for global food supply but also play a pivotal role in marine ecosystems. Focusing on economic crustaceans, the research uncovers 90 RNA viruses, with 69 being potentially new to science, highlighting the vast unknown viral diversity within these marine organisms. The findings reveal that these viruses are often related to those found in other invertebrates and tend to share close relationships with viruses from species within the same food web or habitat. This suggests that viruses may move between different marine species more frequently than previously thought. The discovery of such a wide variety of viruses, particularly the diverse genome structures of newly identified picornaviruses, is a significant leap forward in understanding the crustacean virology. This knowledge is crucial for managing disease risks in aquaculture and maintaining the balance of marine ecosystems.

Abstract Background Treating the coronal dens invaginatus (CDI) with pulp infection commonly involves the removal of invagination, which increases the risk of perforation and fracture, and compromises the tooth structure. Minimally invasive endodontic management of CDI is highly recommended. This report describes two cases of type II CDI with the application of personalized templates. Case presentation Two cases of type II CDI, affecting the main root canal in a maxillary canine and a lateral incisor, were diagnosed. A guided endodontics (GE) approach was applied. Cone-beam computed tomography and intraoral scans were imported and aligned in a virtual planning software to design debridement routes and templates. The MICRO principle (which involves the aspects of Mechanical (M) debridement, Irrigation (I), Access cavities (C), Rectilinear routes (R), and Obstruction (O)) was proposed for designing optimal debridement routes for future applications. The templates were innovatively personalized and designed to preserve the tooth structure maximally while effectively debriding the root canal. Root canal treatment with supplementary disinfection was then performed. The follow-up of the two patients revealed favorable clinical and radiographic outcomes. Conclusions The GE approach could be a feasible method for preserving healthy dental structure while effectively debriding the root canal, thereby achieving successful and minimally invasive endodontic treatment for CDI.

Abstract Background The faithful maintenance of DNA methylation homeostasis indispensably requires DNA methyltransferase 1 (DNMT1) in cancer progression. We previously identified DNMT1 as a potential candidate target for oral squamous cell carcinoma (OSCC). However, how the DNMT1- associated global DNA methylation is exploited to regulate OSCC remains unclear. Methods The shRNA-specific DNMT1 knockdown was employed to target DNMT1 on oral cancer cells in vitro, as was the use of DNMT1 inhibitors. A xenografted OSCC mouse model was established to determine the effect on tumor suppression. High-throughput microarrays of DNA methylation, bulk and single-cell RNA sequencing analysis, multiplex immunohistochemistry, functional sphere formation and protein immunoblotting were utilized to explore the molecular mechanism involved. Analysis of human samples revealed associations between DNMT1 expression, global DNA methylation and collaborative molecular signaling with oral malignant transformation. Results We investigated DNMT1 expression boosted steadily during oral malignant transformation in human samples, and its inhibition considerably minimized the tumorigenicity in vitro and in a xenografted OSCC model. DNMT1 overexpression was accompanied by the accumulation of cancer-specific DNA hypomethylation during oral carcinogenesis; conversely, DNMT1 knockdown caused atypically extensive genome-wide DNA hypomethylation in cancer cells and xenografted tumors. This novel DNMT1-remodeled DNA hypomethylation pattern hampered the dual activation of PI3K-AKT and CDK2-Rb and inactivated GSK3β collaboratively. When treating OSCC mice, targeting DNMT1 achieved greater anticancer efficacy than the PI3K inhibitor, and reduced the toxicity of blood glucose changes caused by the PI3K inhibitor or combination of PI3K and CDK inhibitors as well as adverse insulin feedback. Conclusions Targeting DNMT1 remodels a novel global DNA hypomethylation pattern to facilitate anticancer efficacy and minimize potential toxic effects via balanced signaling synergia. Our study suggests DNMT1 is a crucial gatekeeper regarding OSCC destiny and treatment outcome.

Abstract Whole-heart coronary calcium Agatston score is a well-established predictor of major adverse cardiovascular events (MACE), but it does not account for individual calcification features related to the pathophysiology of the disease (e.g., multiple-vessel disease, spread of the disease along the vessel, stable calcifications, numbers of lesions, and density). We used novel, hand-crafted calcification features (calcium-omics); Cox time-to-event modeling; elastic net; and up and down synthetic sampling methods for imbalanced data, to assess MACE risk. We used 2457 CT calcium score (CTCS) images enriched for MACE events from our large no-cost CLARIFY program (ClinicalTrials.gov Identifier: NCT04075162). Among calcium-omics features, numbers of calcifications, LAD mass, and diffusivity (a measure of spatial distribution) were especially important determinants of increased risk, with dense calcification (> 1000HU, stable calcifications) associated with reduced risk Our calcium-omics model with (training/testing, 80/20) gave C-index (80.5%/71.6%) and 2-year AUC (82.4%/74.8%). Although the C-index is notoriously impervious to model improvements, calcium-omics compared favorably to Agatston and gave a significant difference (P

Abstract Aqueous Zn-I flow batteries utilizing low-cost porous membranes are promising candidates for high-power-density large-scale energy storage. However, capacity loss and low Coulombic efficiency resulting from polyiodide cross-over hinder the grid-level battery performance. Here, we develop colloidal chemistry for iodine-starch catholytes, endowing enlarged-sized active materials by strong chemisorption-induced colloidal aggregation. The size-sieving effect effectively suppresses polyiodide cross-over, enabling the utilization of porous membranes with high ionic conductivity. The developed flow battery achieves a high-power density of 42 mW cm−2 at 37.5 mA cm−2 with a Coulombic efficiency of over 98% and prolonged cycling for 200 cycles at 32.4 Ah L−1 posolyte (50% state of charge), even at 50 °C. Furthermore, the scaled-up flow battery module integrating with photovoltaic packs demonstrates practical renewable energy storage capabilities. Cost analysis reveals a 14.3 times reduction in the installed cost due to the applicability of cheap porous membranes, indicating its potential competitiveness for grid energy storage.

Water-lubricating bearings made of polymer-matrix composites have provided a new approach to prolong the service lifetime of key component in marine propulsion system. However, it was still crucial to find a convenient and effective material to manufacture the water-lubricating bearing with ultralow friction. Herein, a new kind of polyetheretherketone (PEEK) composite with ultralow coefficient of friction (COF), high mechanical strength and thermal stability has been developed. An 80.7% decrease in the COF of PEEK was achieved by incorporating the fillers. A possible mechanism between the heterogeneous nucleation and mobility hindrance of PEEK chain segment caused by different fillers was proposed. The ultralow COF endowed the water-lubricating bearing with low running noise and reduced energy consumption. The high mechanical strength and thermal stability caused the superior carrying capacity and reliability. Therefore, the prepared PEEK composites can be a possibility to realize the water-lubricating bearing with high durability and long service lifetime.

Abstract Robot joints are the main structure for controlling the motion of the machine body, where the motion state of them directly affects the performance of the industrial robot. Due to the difficulty of obtaining the joint torque information of industrial robots, it is very hard to monitor the motion state of them. Based on the velocity and force driven by current of motors, we propose a novel Bayesian optimization framework to predict the joint motion state of industrial robot in this paper. Based on the temporal correlation of joint current and the correlation between the current and motion state of joint, we use the LSTM and BiLSTM to regressing prediction of the current and state of joint motor first. Then, the Bayesian optimization method is used to adjust the hyperparameters of our network, which realize the analysis of the joint motor current under different motion states and improve the accuracy of the prediction of joint motion states. Finally, we design the joint current acquisition platform of industrial robot based on Hall current sensors, which can collect joint currents without contact and generate experimental dataset. Comparing with the popular intelligent methods, the results show that our Bayesian optimization framework realizes a more accurate prediction of motion state for the four-axis industrial robot on the basis of contact-less current acquisition.

The hydraulic support is the core of the stability of the ‘surrounding rock and equipm ent’ system in the pitching oblique working face of steeply dipping coal seam. The existing hydraulic support structure can not meet the requirements of spatial stability of pitching oblique mining, which seriously affects the safe and efficient mining of working face under such conditions. Taking the pitching oblique working face of steeply dipping coal seam as the research background, the comprehensive research methods of engineering analogy, structural kinematics analysis and numerical simulation are used to analyze the stability characteristics of ‘support-surrounding rock’ in the pitching oblique working face of steeply dipping coal seam. Based on ZY7000/22/45 hydraulic support, a new parallelogram hydraulic support is invented, the structural rationality design is carried out, and the kinematic response characteristics of key components are analyzed.The research shows that the non-uniform filling of the caving gangue and the crushing, pressing and pushing effect of the gangue on the support are the key factors affecting the stability of the support. The parallelogram top beam and the base are more suitable for the pitching oblique working face. The arrangement of the top beam, base and column of the parallelogram support is parallelogram. The special-shaped shield beam, the rear connecting rod, the oil cylinder connecting rod and the base constitute a flexible four-link structure. The column of the parallelogram support is the main bearing structure, and the cylinder connecting rod is the main motion mechanism. The main influencing factors of its motion characteristics are the distance between the upper and lower column sockets and the distance between the front and rear connecting rods and the hinged position of the shield beam. The shield beam and the rear connecting rod are the key to the position and posture control of the support, and there is no double torsion line during the movement of the support. The research results provide a type selection for the support of this kind of working face, which ensures the safe production of this kind of coal seam to a certain extent.

Abstract Ultralight dark photons constitute a well-motivated candidate for dark matter. A coherent electromagnetic wave is expected to be induced by dark photons when coupled with Standard-Model photons through kinetic mixing mechanism, and should be spatially correlated within the de Broglie wavelength of dark photons. Here we report the first search for correlated dark-photon signals using a long-baseline network of 15 atomic magnetometers, which are situated in two separated meter-scale shield rooms with a distance of about 1700 km. Both the network’s multiple sensors and the shields large size significantly enhance the expected dark-photon electromagnetic signals, and long-baseline measurements confidently reduce many local noise sources. Using this network, we constrain the kinetic mixing coefficient of dark photon dark matter over the mass range 4.1 feV-2.1 peV, which represents the most stringent constraints derived from any terrestrial experiments operating over the aforementioned mass range. Our prospect indicates that future data releases may go beyond the astrophysical constraints from the cosmic microwave background and the plasma heating.

Abstract Purpose Patent processus vaginalis (PPV) is usually observed in pediatric abdominal surgery; however, robotic single-port surgery in repairing processus vaginalis has not been reported in children. Herein, we present our clinical experiences in single-port robotic surgeries for PPV repair to evaluate both efficacy and safety. Methods Retrospective analysis of patients underwent single-port robotic-assisted laparoscopic surgery for genitourinary diseases from May 2020 and May 2023 in our center. Among these patients, 21 children had PPV repaired at the same time. The case characteristics and follow-up data were recorded. Results Twenty-one of the 53 children were found to have PPV during genitourinary surgery. The simultaneous treatment of the primary disease and PPV with a single-port robotic-assisted platform was both convenient and safe. There was no significant increase in total operation time, and no excessive intraoperative hemorrhage was observed in any of the operations. There were no complications observed on follow-up. Conclusion With a high incidence of PPV in children, a single-port robotic-assisted procedure is feasible and effective if simultaneously performed when addressing a primary abdominal disease.

Abstract Endosomal single-stranded RNA-sensing Toll-like receptor-7/8 (TLR7/8) plays a pivotal role in inflammation and immune responses and autoimmune diseases. However, the mechanisms underlying the initiation of the TLR7/8-mediated autoimmune signaling remain to be fully elucidated. Here, we demonstrate that miR-574-5p is aberrantly upregulated in tissues of lupus prone mice and in the plasma of lupus patients, with its expression levels correlating with the disease activity. miR-574-5p binds to and activates human hTLR8 or its murine ortholog mTlr7 to elicit a series of MyD88-dependent immune and inflammatory responses. These responses include the overproduction of cytokines and interferons, the activation of STAT1 signaling and B lymphocytes, and the production of autoantigens. In a transgenic mouse model, the induction of miR-574-5p overexpression is associated with increased secretion of antinuclear and anti-dsDNA antibodies, increased IgG and C3 deposit in the kidney, elevated expression of inflammatory genes in the spleen. In lupus-prone mice, lentivirus-mediated silencing of miR-574-5p significantly ameliorates major symptoms associated with lupus and lupus nephritis. Collectively, these results suggest that the miR-574-5p-hTLR8/mTlr7 signaling is an important axis of immune and inflammatory responses, contributing significantly to the development of lupus and lupus nephritis.

The importance of determining the radon exhalation rate from water surface is emphasized by the increased use of radon and its daughter products as tracers in large-scale circulation studies of the atmosphere. There were many methods to measure radon exhalation from water surface. With the development of radon exhalation rate measurement methods and instruments on the surface of the soil, the rock and building materials, so the radon exhalation rate from water surface can be more accurately measured by applying these improved methods and instruments. In this paper, a cuboid accumulation chamber surrounded by foam boards and a RAD7 were used to measure the radon exhalation rate on the water surface at three different positions by Yixin lake. Each measurement was performed 2 h. The radon exhalation rate from the water surface was about 6 × 10−3 Bq m−2s−1. The thoron exhalation rate from the water surface also can be estimated, it is about 0.16 Bq m−2s−1. These results hint that the radon transmission from the lake bottom soil to water and then into the atmosphere.

Abstract Cocrystal engineering is an efficient and simple strategy to construct functional materials, especially for the exploitation of novel and multifunctional materials. Herein, we report two kinds of nucleic-acid-base cocrystal systems that imitate the strong hydrogen bond interactions constructed in the form of complementary base pairing. The two cocrystals studied exhibit different colors of phosphorescence from their monomeric counterparts and show the feature of rare high-temperature phosphorescence. Mechanistic studies reveal that the strong hydrogen bond network stabilizes the triplet state and suppresses non-radiative transitions, resulting in phosphorescence even at 425 K. Moreover, the isolation effects of the hydrogen bond network regulate the interactions between the phosphor groups, realizing the manipulation from aggregation to single-molecule phosphorescence. Benefiting from the long-lived triplet state with a high quantum yield, the generation of reactive oxygen species by energy transfer is also available to utilize for some applications such as in photodynamic therapy and broad-spectrum microbicidal effects. In vitro experiments show that the cocrystals efficiently kill bacteria on a tooth surface and significantly help prevent dental caries. This work not only provides deep insight into the relationship of the structure-properties of cocrystal systems, but also facilitates the design of multifunctional cocrystal materials and enriches their potential applications.

Abstract Endodontic diseases are a kind of chronic infectious oral disease. Common endodontic treatment concepts are based on the removal of inflamed or necrotic pulp tissue and the replacement by gutta-percha. However, it is very essential for endodontic treatment to debride the root canal system and prevent the root canal system from bacterial reinfection after root canal therapy (RCT). Recent research, encompassing bacterial etiology and advanced imaging techniques, contributes to our understanding of the root canal system’s anatomy intricacies and the technique sensitivity of RCT. Success in RCT hinges on factors like patients, infection severity, root canal anatomy, and treatment techniques. Therefore, improving disease management is a key issue to combat endodontic diseases and cure periapical lesions. The clinical difficulty assessment system of RCT is established based on patient conditions, tooth conditions, root canal configuration, and root canal needing retreatment, and emphasizes pre-treatment risk assessment for optimal outcomes. The findings suggest that the presence of risk factors may correlate with the challenge of achieving the high standard required for RCT. These insights contribute not only to improve education but also aid practitioners in treatment planning and referral decision-making within the field of endodontics.

Biomass waste-based, graphite-like material is an interesting alternative to fossil carbons in, for example, battery solutions. The aim was to produce carbon with a graphite-like structure from birch waste through catalytic modification with iron nitrate at relatively low temperatures. The study highlighted the effects of the Fe/birch mass ratio (0–20 mg Fe/g birch), heating temperature (750–900 °C), holding time (1–6 h), and heating rate (3–10 °C/min) on the carbon. The influence of each factor was demonstrated using a design of experiments (DoE) approach. Changes in yield, chemical composition, morphology, specific surface area, total pore volume, pore size distribution, particle size, tapped density, and conductivity were analyzed. The results showed that temperature affected the chemical content, yield, and conductivity. Iron-impregnation affected the structure of birch by modifying its total pore volume, tapped density, ID/IG value, and conductivity. The heating rate and holding time had relatively little effect. The highest conductivity (7.23 S/cm) was obtained when impregnated birch was pyrolyzed at the maximum temperature, holding time, and heating rate. However, the best graphitization result (ID/IG 0.98) was obtained when iron-impregnated birch was heated for 6 h at 750 °C at a heating rate of 3 °C/min.

In the present work, the static magnetic field (SMF) was applied in the L-PBF process of a typical γʹ strengthening Ni-based superalloy of GH4099 concerning the as-built and heat-treated conditions. The SMF during the L-PBF process can effectively refine the cellular str ucture, refine the grain size, promote the columnar to equiaxed transition (CET), and reduce the dislocation density. After the solution-aging procedure, the SMF samples exhibited a refined grain structure, suggesting that the tailored microstructure is inherited after the solution-aging treatment. The tensile test results show that by applying the SMF during the L-PBF process, the ductility can be notably improved on both building planes under the as-built and heat-treatment conditions, and the anisotropy along different directions can be reduced. It reveals that the SMF in L-PBF can be an effective method to modulate the microstructure and improve the comprehensive mechanical properties for γʹ strengthening Ni-based superalloys.

We previously reported that immunoglobulin superfamily member 9 (IGSF9) as a tumor specific immune checkpoint promoted the tumor immune escape, however, as an adhesion molecule, whether IGSF9 promotes tumor invasion and metastasis has not been reported. Here, the full length, the intracellular domain (ID) not extracellular domain (ECD) of IGSF9 could alter tumor cell morphology from a flat and polygonal shape to elongated strips, suggesting that IGSF9 signal pathway has the potential to mediate epithelial-to-mesenchymal transition (EMT). Real-time PCR and western blotting also showed that the mesenchymal markers were significantly up-regulated, and the epithelial markers were significantly down-regulated in IGSF9 and IGSF9-ID groups. Meanwhile, immunofluorescence showed that β-catenin was clearly translocated into the nucleus in IGSF9 and IGSF9-ID groups. The in vitro and in vivo data showed that IGSF9, IGSF9-ID and ECD could promote tumor invasion and metastasis. Mechanistically, IGSF9-ID could recruit GSK-3β to result in the accumulation and nuclear translocation of β-catenin to trigger EMT. Anti-IGSF9 could significantly inhibit the invasion and metastasis, and IGSF9 is an effective candidate for lung cancer therapy.

ABSTRACTThe launch of large language models (LLMs) like ChatGPT in late 2022 and the anticipated arrival of future GPT-x iterations have marked the beginning of the generative artificial intelligence (GAI) era. We conducted a systematic review of how to integrate LLMs including GPT and other GAI models into geospatial science, based on 293 papers obtained from four databases of academic publications – Web of Science (WoS), Scopus, SSRN and arXiv – 26 papers were eventually included for analysis. We statistically outlined the share of domains where LLMs and other GAI models, the type of data that have been used for these models, and the modelling tasks and roles that they play. We also pointed out the challenges and future directions for the next research agenda – along with which we could better position ourselves in the mainstream of science and the cutting-edge research paradigm as others leverage insights from the growing data deluge.

Abstract Spinal cord injury (SCI) is a severe neurological condition that frequently leads to significant sensory, motor, and autonomic dysfunction. This study sought to delineate the potential mechanistic underpinnings of extracellular vesicles (EVs) derived from ginsenoside Rg1‐pretreated neuronal cells (Rg1‐EVs) in ameliorating SCI. These results demonstrated that treatment with Rg1‐EVs substantially improved motor function in spinal cord‐injured mice. Rg1‐EVs enhance microglial polarization toward the M2 phenotype and repressed oxidative stress, thereby altering immune responses and decreasing inflammatory cytokine secretion. Moreover, Rg1‐EVs substantially diminish reactive oxygen species accumulation and enhanced neural tissue repair by regulating mitochondrial function. Proteomic profiling highlighted a significant enrichment of MYCBP2 in Rg1‐EVs, and functional assays confirmed that MYCBP2 knockdown counteracted the beneficial effects of Rg1‐EVs in vitro and in vivo. Mechanistically, MYCBP2 is implicated in the ubiquitination and degradation of S100A9, thereby promoting microglial M2‐phenotype polarization and reducing oxidative stress. Overall, these findings substantiated the pivotal role of Rg1‐EVs in neuronal protection and functional recovery following SCI through MYCBP2‐mediated ubiquitination of S100A9. This research offers novel mechanistic insights into therapeutic strategies against SCI and supports the clinical potential of Rg1‐EVs.

Abstract The low mechanical reliability and integration failure are key challenges hindering the commercialization of geometrically flexible batteries. This work proposes that the failure of directly integrating flexible batteries using traditional rigid adhesives is primarily due to the mismatch between the generated stress at the adhesive/substrate interface, and the maximum allowable stress. Accordingly, a stress redistribution adhesive layer (SRAL) strategy is conceived by using elastic adhesive to redistribute the generated stress. The function mechanism of the SRAL strategy is confirmed by theoretical finite element analysis. Experimentally, a polyurethane (PU) type elastic adhesive (with maximum strain of 1425%) is synthesized and used as the SRAL to integrate rigid cells on different flexible substrates to fabricate directly integrated flexible battery with robust output under various harsh environments, such as stretching, twisting, and even bending in water. The SRAL strategy is expected to be generally applicable in various flexible devices that involve the integration of rigid components onto flexible substrates.

ABSTRACT The gastric microbial community plays a fundamental role in gastric cancer (GC), and the two main anatomical subtypes of GC, non-cardia and cardia GC, are associated with different risk factors (Helicobacter pylori for non-cardia GC). To decipher the different microbial spatial communities of GC, we performed a multicenter retrospective analysis to characterize the gastric microbiota in 223 GC patients, including H. pylori-positive or -negative patients, with tumors and paired adjacent normal tissues, using third-generation sequencing. In the independent validation cohort, both dental plaque and GC tumoral tissue samples were collected and sequenced. The prevalence of H. pylori and oral-associated bacteria was verified using fluorescence in situ hybridization (FISH) assays in GC tumoral tissues and matched nontumoral tissues. We found that the vertical distribution of the gastric microbiota, at the upper, middle, and lower third sites of GC, was likely an important factor causing microbial diversity in GC tumor tissues. The oral-associated microbiota cluster, which included Veillonella parvula, Streptococcus oralis, and Prevotella intermedia, was more abundant in the upper third of the GC. However, H. pylori was more abundant in the lower third of the GC and exhibited a significantly high degree of microbial correlation. The oral-associated microbiota module was co-exclusive with H. pylori in the lower third site of the GC tumoral tissue. Importantly, H. pylori-negative GC patients with oral-associated gastric microbiota showed worse overall survival, while the increase in microbial abundance in H. pylori-positive GC patients showed no difference in overall survival. The prevalence of V. parvula in both the dental plaque and GC tissue samples was concordant in the independent validation phase. We showed that the oral-associated species V. parvula and S. oralis were correlated with overall survival. Our study highlights the roles of the oral-associated microbiota in the upper third of the GC. In addition, oral-associated species may serve as noninvasive screening tools for the management of GC and an independent prognostic factor for H. pylori-negative GCs.IMPORTANCEOur study highlights the roles of the oral-associated microbiota in the upper third of gastric cancer (GC).We showed that the oral-associated species Veillonella parvula and Streptococcus oralis were correlated with overall survival. In addition, oral-associated species may serve as noninvasive screening tools for the management of GC and an independent prognostic factor for Helicobacter pylori-negative GCs.

Net ecosystem productivity (NEP) is a crucial parameter for assessing the carbon cycle dynamics in terrestrial ecosystems. This study analyzed the spatial and temporal evolution characteristics and future trends of NEP in Henan Province over the past 20 years based on MOD17A3HGF, meteorological, and land-use data, employing the frequency counting method, trend test, Hurst index, and the center of gravity model. Various areas of changes in vegetation carbon sequestration were explored, and the driving factors were quantitatively assessed through correlation analysis, Sankey diagrams, and Geodetector. The results demonstrate that: 1) Continuous temporal changes in NEP in Henan, with annual average values fluctuating between 272.84 and 451.39 gC·m-2·a1, exhibiting an overall upward trend. 2) Spatially, there is a distinct distribution of NEP, concentrating more in the south and less in the north. While the study area generally experiences a dominant gradual enhancement of vegetation carbon sequestration capacity, the middle and north of Zhengzhou City exhibit a significant decline, which is expected to persist in the future. The migration of the centers of gravity of NEP over the past 20 years is characterized by stage-specific differentiation. 3) Among the various land cover types, forests have the strongest carbon sequestration capacity; however, cropland emerges as the province’s main source of NEP due to its extensive size. 4) The driving factors for spatial differentiation in NEP exhibit some temporal variability. Overall, climate factors and atmospheric pollution exert stronger influences, with the interactive explanatory power of the two-factor interaction being higher than that of the single factor. The results of this study can serve as a scientific theoretical basis for ecological policy-making and sustainable development in Henan Province.

X-ray Compton scattering experiments along with parallel first-principles computations were carried out on LiNiO2 to understand the effects of W doping on this cathode material for Li-ion batteries. By employing high-energy x rays exceeding 100 keV, an insight is gained into the fate of the W valence electrons, which are adduced to undergo transfer to empty O 2p energy bands within the active oxide matrix of the cathode. The substitution of W for Ni is shown to increase the electronic conductivity and to enhance the total magnetization per Ni atom. Our study demonstrates that an analysis of line shapes of Compton scattered x rays in combination with theoretical modeling can provide a precise method for an atomic level understanding of the nature of the doping process.

Abstract Mix‐dimensional heterojunctions (MDHJs) photodetectors (PDs) built from bulk and 2D materials are the research focus to develop hetero‐integrated and multifunctional optoelectronic sensor systems. However, it is still an open issue for achieving multiple effects synergistic characteristics to boost sensitivity and enrich the prospect in artificial bionic systems. Herein, electrically tunable Te/WSe2 MDHJs phototransistors are constructed, and an ultralow dark current below 0.1 pA and a large on/off rectification ratio of 106 is achieved. Photoconductive, photovoltaic, and photo‐thermoelectric conversions are simultaneously demonstrated by tuning the gate and bias. By these synergistic effects, responsivity and detectivity respectively reach 13.9 A W−1 and 1.37 × 1012 Jones with 400 times increment. The Te/WSe2 MDHJs PDs can function as artificial bionic visual systems due to the comparable response time to those of the human visual system and the presence of transient positive and negative response signals. This work offers an available strategy for intelligent optoelectronic devices with hetero‐integration and multifunctions.

The exceptional high-temperature mechanical properties of Ni-based superalloys are mainly stemmed from the L12 γ' phase, therefore it is crucial to discover Ni-based superalloys with high γ' solvus temperatures. Utilizing generative artificial intelligence, we have developed a framework to swiftly evaluate the γ' solvus temperature and tailor Ni-based superalloys, accelerating the process of discovering Ni-based superalloys. Physics-informed artificial neural network emerged as the optimal choice for reverse engineering, outperforming other models with an R2 score of 0.917 and a mean absolute error of 15 K. In the reverse design process, 20,000 virtual alloy samples were generated based on divide-and-conquer variational autoencoder which divides the dataset into distinct clusters by K-means algorithm provides a structured representation of the alloy composition space, thereby facilitating a more nuanced understanding of its inherent complexities. In a specific alloy design example, 563 samples were identified through screening based on criteria like γ' solvus temperature, composition deviation index, price, and density. Thermodynamic calculations were used to further screen Ni-based superalloys with exceptional high-temperature properties. The showcase of BA alloy discovery through generative artificial intelligence demonstrates the potential of our research to steer the creation of novel compositions for Ni-based superalloys with outstanding high-temperature properties.

Accurate real-time prediction of link quality is crucial for enhancing the reliable responsiveness of wearable devices within Wireless Wearable Sensor Networks (WWSNs). Specifically, the Signal-to-Noise Ratio (SNR), a pivotal parameter for predicting link quality, exhibits complex temporal characteristics influenced by stochastic and non-stochastic factors. To improve the accuracy of link quality prediction in WWSNs, we aim to explore a novel predictive model, introducing a filtering layer that seeks to enhance the precision of predicting upper and lower boundaries of link reliability confidence intervals. First, we adopt the SNR time series as the evaluation metric and decompose the SNR sequences into time-varying and stochastic standard deviation sequences by wavelet decomposition. Subsequently, we propose an innovative SCNN-LSTM model, incorporating the SincNet filtering layer to extract specific frequency components from the input SNR sequences. Afterward, integrating standard deviation sequences, the model predicts upper and lower boundaries of link reliability confidence intervals. Finally, we conduct the validation experiments on the public dataset LightGBM-LQP and our WWSN dataset Basketball shot. Compared to BPNN, ARIMA, and WNN, the evaluation matrices of MAE, RMSE, R2 in SCNN-LSTM have been improved, and the deviation between the predicted standard deviation and the actual standard deviation has reached the minimum of 0.1. The results demonstrate that SCNN-LSTM outperforms classical prediction models in predicting upper and lower limits of link reliability confidence intervals in WWSNs.