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Purpose: Hepatocellular carcinoma (HCC) is a prevalent malignant tumor, often arising from hepatitis induced by the hepatitis B virus (HBV) in China. However, effective biomarkers for early diagnosis are lacking, leading to a 5-year overall survival rate of less than 20% among patients with advanced HCC. This study aims to identify serum biomarkers for early HCC diagnosis to enhance patient survival rates. Methods: We established an independent cohort comprising 27 healthy individuals, 13 patients with HBV-induced cirrhosis, 13 patients with hepatitis B-type HCC, and 8 patients who progressed from cirrhosis to hepatocellular carcinoma during follow-up. Serum metabolic abnormalities during the progression from cirrhosis to HCC were studied using untargeted metabolomics. Liquid chromatography-mass spectrometry-based metabolomics methods characterized the subjects’ serum metabolic profiles. Partial least squares discriminant analysis (PLS-DA) was employed to elucidate metabolic profile changes during the progression from cirrhosis to HCC. Differentially expressed metabolites (DEMs) between cirrhosis and HCC groups were identified using the LIMMA package in the R language. Two machine learning algorithms, Least Absolute Shrinkage and Selection Operator (LASSO), and Random Forest Classifier (RF), were used to identify key metabolic biomarkers involved in the progression from cirrhosis to HCC. Key metabolic biomarkers were further validated using targeted metabolomics in a new independent validation cohort comprising 25 healthy individuals and 25 patients with early-stage hepatocellular carcinoma. Results: A total of 155 serum metabolites were identified, of which 21/54 metabolites exhibited significant changes in HCC patients compared with cirrhosis patients and healthy individuals, respectively. PLS-DA clustering results demonstrated a significant change trend in the serum metabolic profile of patients with HBV-induced cirrhosis during the progression to HCC. Utilizing LASSO regression and RF algorithms, we confirmed 10 key metabolic biomarkers. Notably, 1-Methylnicotinamide (1-MNAM) exhibited a persistent and significant decrease in healthy individuals, cirrhosis, and HCC patients. Moreover, 1-MNAM levels in developing patients were significantly higher during the cirrhosis stage than in the HCC stage. Targeted metabolomic validation in an external cohort further confirmed the good diagnostic performance of 1-MNAM in early HCC detection. Conclusion: Our findings imply that 1-MNAM may be a specific biomarker for the progression of cirrhosis to HCC. [ABSTRACT FROM AUTHOR]

Statistical inference for high-dimensional survival data is important for obtaining valid scientific results in many research areas, including biomedical studies and financial risk management. In this paper, a novel framework for feature selection in Cox model is proposed, which achieves false discovery rate (FDR) control asymptotically. The key step is to construct a sequence of ranking statistics based on two independent estimators of the regression coefficients. The FDR control is reached by choosing a data-driven threshold along the ranking of symmetric-based statistics. The de-sparsified estimator and uneven data splitting strategy are employed to improve the robustness of variable selection results and the power in finite sample analysis. We establish the asymptotic FDR control property for the proposed approach at any designated level. Extensive simulation studies and an empirical application on a P2P loan dataset confirm the robustness of the proposed method in FDR control, and show that it often leads to higher power among competitors. [ABSTRACT FROM AUTHOR]

[Display omitted] • Hydrophobic ZIF-8/SA monolithic materials were fabricated via in situ synthesis. • The cooperation of SA, PDMS, and ZIF-8 significantly enhanced adsorption capacity. • The composites displayed rapid kinetic adsorption. • The composites have remarkable absorption recyclability. Microplastics (MPs), a newly emerging class of environmental contaminants, pose a severe threat to the entire ecosystem. The development of efficient and environmentally responsible adsorbents for removing the MPs is a particularly urgent research. Herein, a kind of monolithic ZIF-8 based adsorbents featuring stable hydrophobicity and micropore-mesopore-macropore hierarchical porous structure were fabricated by in situ growth of ZIF-8 nanoparticles on sodium alginate (SA) framework, and using polydimethylsiloxane (PDMS) as a hydrophobic agent. The monolithic nature of ZIF-8/SA allowed an easy solid–liquid separation process for adsorbents from water environment compared to powdered materials. The hierarchical porous structure ensures a remarkable MPs removal performance. The ZIF-8/SA showed high adsorption capacities of 594, 585, and 282 mg/g for polymethyl methacrylate (PMMA), poly (vinylidene difluoride) (PVDF), and polyvinyl chloride (PVC) respectively, and rapid adsorption kinetic progress within 120 min. The ZIF-8/SA adsorbents also exhibited excellent stability in the presence of interfering ions, acid/alkali, and humic acid, and displayed adsorption performance of > 70 % even in actual aquatic environment such as tap water, river water, and seawater. The results of characterizations showed that the synergistic effect of electrostatic interaction, hydrogen bonding, hydrophobic force, and van der Waals force was the main adsorption mechanism. The well-designed hydrophobic ZIF-8/SA monolithic materials would be promising to rapidly remove the MPs from the water environment. [ABSTRACT FROM AUTHOR]

Background and Aims Kalanchoideae is one of three subfamilies within Crassulaceae and contains four genera. Despite previous efforts, the phylogeny of Kalanchoideae remains inadequately resolved with persistent issues including low support, unstructured topologies and polytomies. This study aimed to address two central objectives: (1) resolving the pending phylogenetic questions within Kalanchoideae by using organelle-scale 'barcodes' (plastomes) and nuclear data; and (2) investigating interspecific diversity patterns among Kalanchoideae plastomes. Methods To explore the plastome evolution in Kalanchoideae, we newly sequenced 38 plastomes representing all four constituent genera (Adromischus , Cotyledon , Kalanchoe and Tylecodon). We performed comparative analyses of plastomic features, including GC and gene contents, gene distributions at the IR (inverted repeat) boundaries, nucleotide divergence, plastomic tRNA (pttRNA) structures and codon aversions. Additionally, phylogenetic inferences were inferred using both the plastomic dataset (79 genes) and nuclear dataset (1054 genes). Key Results Significant heterogeneities were observed in plastome lengths among Kalanchoideae, strongly correlated with LSC (large single copy) lengths. Informative diversities existed in the gene content at SSC/IRa (small single copy/inverted repeat a), with unique patterns individually identified in Adromischus leucophyllus and one major Kalanchoe clade. The ycf1 gene was assessed as a shared hypervariable region among all four genera, containing nine lineage-specific indels. Three pttRNAs exhibited unique structures specific to Kalanchoideae and the genera Adromischus and Kalanchoe. Moreover, 24 coding sequences revealed a total of 41 lineage-specific unused codons across all four constituent genera. The phyloplastomic inferences clearly depicted internal branching patterns in Kalanchoideae. Most notably, by both plastid- and nuclear-based phylogenies, our research offers the first evidence that Kalanchoe section Eukalanchoe is not monophyletic. Conclusions This study conducted comprehensive analyses on 38 newly reported Kalanchoideae plastomes. Importantly, our results not only reconstructed well-resolved phylogenies within Kalanchoideae, but also identified highly informative unique markers at the subfamily, genus and species levels. These findings significantly enhance our understanding of the evolutionary history of Kalanchoideae. [ABSTRACT FROM AUTHOR]

Sedum is the largest succulent genus in Crassulaceae. Because of predominant maternal inheritance, little recombination, and slow evolution, plastomes can serve as powerful super barcodes for inter- or intra-species phylogenetic analyses. While previous research has focused on plastomes between Sedum species, intra-species studies are scarce. Here, we sequenced plastomes from three Sedum species (Sedum alfredii, Sedum plumbizincicola, and Sedum japonicum) to understand their evolutionary relationships and plastome structural evolution. Our analyses revealed minimal size and GC content variation across species. However, gene distribution at IR boundaries, repeat structures, and codon usage patterns showed diversity at both inter-specific and intra-specific levels. Notably, an rps19 gene expansion and a bias toward A/T-ending codons were observed. Codon aversion motifs also varied, potentially serving as markers for future studies. Phylogenetic analyses confirmed the non-monophyly of Sedum and divided the Acre clade into two groups. Individuals from the same species clustered together, with strong support for the relationships between S. alfredii, S. tricarpum, and S. plumbizincicola. Additionally, S. japonicum clearly affiliates with the Acre clade. This study provides valuable insights into both intra-specific and intra-generic plastome variation in Sedum, as well as overall plastome evolution within the genus. [ABSTRACT FROM AUTHOR]

In the present work, the herb (Poria cocos (Schw.) Wolf) residue, as an environmentally friendly and renewable biomass source, was converted into novel biochar. Biochar/sodium alginate mixed matrix membrane was fabricated. On this basis, a biochar/sodium alginate mixed matrix membrane‐based in‐syringe solid‐phase extraction was developed combined with ultra‐high performance liquid chromatography‐tandem mass spectrometry to determine nitroimidazoles in water samples. The factors including times of exaction, type, and volume of elution solvent, and sample solution pH were thoroughly optimized. Then the correlation coefficient was 0.9995–0.9997. The limit of detection of four analytes was between 0.006 and 0.014 ng/mL, and the recovery was between 79.02% and 99.1%. Consequently, the established method would provide a new perspective on monitoring nitroimidazoles in water samples. [ABSTRACT FROM AUTHOR]

The decentralization and anonymity of blockchain have attracted significant attention. However, in recent years, there has been a rise in blockchain money laundering incidents, and anti-money laundering efforts have become crucial within the blockchain space. Blockchain money laundering differs from traditional financial money laundering as it does not provide account information, particularly in the case of Bitcoin. This absence of information makes it challenging for researchers to detect money laundering activities based on transaction data. We propose LB-GLAT, a novel Long-Term Bi-Graph Layer Attention Convolutional Network, to effectively capture the topological structure and attribute characteristics of money laundering on the blockchain transaction graph. LB-GLAT utilizes the transaction graph and the reverse transaction graph to solve the no-loop problem that results in the inability to capture the destination of blockchain transactions and designs a long-term layer attention mechanism to alleviate the over-smoothing problem. We implemented a series of experiments to evaluate LB-GLAT, which achieved state-of-art performance compared with other methods, presenting an accuracy of 0.9776, a precision of 0.9317, a recall of 0.8494, an F1−score of 0.8887, and an AUC of 0.9806. [ABSTRACT FROM AUTHOR]

It is of great significance to accurately identify soybean planting areas for ensuring agricultural and industrial production. High-resolution satellite remotely sensed imagery has greatly facilitated the effective extraction of soybean planting areas but novel methods are required to further improve the identification accuracy. Two typical planting areas of Linhu Town and Baili Town in Northern Anhui Province, China, were selected to explore the accurate extraction method. The 10 m multispectral and 2 m panchromatic Gaofen-1 (GF-1) image data were first fused to produce training, test, and validation data sets after the min–max standardization and data augmentation. The deep learning U-Net model was then adopted to perform the accurate extraction of soybean planting areas. Two vital influencing factors on the accuracies of the U-Net model, including cropping size and training epoch, were compared and discussed. Specifically, three cropping sizes of 128 × 128, 256 × 256, and 512 × 512 px, and 20, 40, 60, 80, and 100 training epochs were compared to optimally determine the values of the two parameters. To verify the extraction effect of the U-Net model, comparison experiments were also conducted based on the SegNet and DeepLabv3+. The results show that U-Net achieves the highest Accuracy of 92.31% with a Mean Intersection over Union (mIoU) of 81.35%, which is higher than SegNet with an improvement of nearly 4% in Accuracy and 10% on mIoU. In addition, the mIoU has been also improved by 8.89% compared with DeepLabv3+. This study provides an effective and easily operated approach to accurately derive soybean planting areas from satellite images. [ABSTRACT FROM AUTHOR]

In this study, zeolitic imidazole framework-8/cellulose membrane (ZIF-8/CM) was fabricated through an in situ synthesis method. The composite was installed in a dismountable filter and used as a sorbent for lab-made microextraction in packed syringe (MEPS). The entire MEPS procedure can be performed through simple operation of filtration, since the macroporous cellulose membrane was introduced as the substrate for ZIF-8 powder. Coupled to a high performance liquid chromatography tandem ultraviolet detector (HPLC-UV), the proposed method was applied for the analysis of tetracyclines in water samples. The extraction parameters, including the adsorbent type, sample solution pH, sample volume, type and volume of the elution solvent, were systematically studied. Under optimized conditions, desirable linearity (r > 0.99 for three analytes), high sensitivity (limit of detection: 0.1373–0.8917 μg L−1), good precision (RSD < 6.3%) and ideal recovery (72.9–97.6%) were obtained. The proposed method was demonstrated to be efficient, easily operative and environmentally friendly. [ABSTRACT FROM AUTHOR]

Vesicles, also known as "microparticles", are vesicle‐like structures that are released outside the cell in a "sprouting" manner when the cytoskeleton is changed during cell activation or apoptosis, with a diameter of about 100–1000 nm, and are carriers of material information exchange between cells. Tumor‐derived extracellular vesicles can effectively deliver drugs to the nucleus of tumor stem cells, thus effectively killing them without toxic side effects. The underlying mechanism involves the soft nature of tumor stem cells that allows better uptake of vesicles, and the entry of drug‐carrying vesicles into lysosomes and facilitation of lysosomal movement toward the nucleus to deliver drugs to the nucleus. Drug‐loaded vesicles have unique advantages, such as low immunogenicity, homing targeting ability, and the ability to break through the physiological barrier to tumor therapy. Tumor‐derived drug‐delivery vesicles have entered clinical trials for the treatment of malignant pleural effusions. In this review, we summarized the progress of basic and clinical research on tumor cell‐derived drug‐loaded vesicles for the treatment of malignant pleural effusion in recent years. [ABSTRACT FROM AUTHOR]

A local long-lived convective system developed at midnight over inland South China, producing record-breaking rainfall in Guangzhou on 7 May 2017. This study examines the physical processes responsible for nocturnal convection initiation (CI) and growth. Observational analyses show that the CI occurs in the warm sector under weakly forced synoptic conditions at 500 hPa, while moderate but nocturnally enhanced low-level southeasterlies with a mesoscale moist tongue at 925 hPa intrude inland from the northern South China Sea. Convection-permitting model results show that mesoscale low-level convergence and increased moisture at the leading edge of the southeasterlies are favorable for CI dynamically and thermodynamically. Local ascent and potential instability are further enhanced by orographic lifting and warm moist air from the urban surface, respectively, which trigger convection in northern Guangzhou. The mesoscale moist tongue of southeasterly flows then meets convectively generated outflows, thereby maintaining strong updrafts and continuously triggering back-building convective cells in eastern Guangzhou. Sensitivity tests are conducted to estimate the relative roles of ambient southeasterly moist tongue and urban thermal effects. The southeasterly moist tongue provides moisture that is crucial for CI, while warm moist air from the urban surface is lifted at the leading edge of the southeasterlies and locally facilitates convection. Therefore, the mesoscale processes of lifting and moistening due to nocturnal southeasterlies and their strong interaction with the local factors (orographic lifting, urban heating, and cold-pool-related ascent) provide the sustained lifting and instability crucial for triggering the local long-lived convective systems. The multiscale processes shed light on the understanding of the nocturnal warm-sector heavy rainfall inland. [ABSTRACT FROM AUTHOR]

Detecting anomalies in videos is a fundamental issue in public security. The majority of existing deep learning methods often perform anomaly detection based on the behavior or the trajectory of a single target. However, due to the overlaps of the crowd and the low-resolution of monitoring images, the segmentation of population is hard to implement and the features cannot be learned thoroughly, which make the methods be easily disturbed by visual elements and thus may lead to false detection sometimes. To tackle these problems, we propose the influence-aware attention to learn the representative attributes of the whole crowd. Walking pedestrians can be divided into numbers of flows, and in this paper, we aim to measure the consistency of movement patterns in the same stream and the interactions between different streams. Meanwhile, great importance is given to the relation between pedestrians and the circumstance for certain anomalies occur as a result of environmental issues. Specifically, the influence-aware attention module is composed of the motion attention and the location attention, which is designed to quantify the relations in the scene from spatial and temporal aspects. For the lack of abnormal samples, we utilize a dual generator-based framework to learn interactions among normal scenes. Experimental results on six benchmarks verify the effectiveness and robustness of our proposed method. [ABSTRACT FROM AUTHOR]

The 2020–2023 La Niña event, the third triple-dip occurrence since 1950, stands out for its unique characteristics when compared to the preceding events in 1973–1976 and 1998–2001. Unlike its predecessors, the latest event emerged without a preceding strong El Niño episode, starting from a state of weak discharge. Moreover, the resurgence of cold sea surface temperature (SST) anomalies during 2020–2023 showed a loose link to ocean-atmosphere variability in the northern subtropical Pacific. The spatial pattern of anomalous conditions in this recent event featured persistent SST cooling in the southeast tropical Pacific, accompanied by pronounced meridional southerly wind anomalies. Our comprehensive investigation indicates a minimal role of subsurface ocean dynamics, underscoring the exceptional strength of cross-equatorial meridional southerly wind anomalies as a primary driver of sustained negative sea surface temperature anomalies. By considering the influences of intra-basin and inter-basin factors, we propose that the observed patterns may be the combined outcome of interannual variability within the tropical Pacific and decadal variations beyond the tropics. Noteworthy contributions from the low-frequency components of the South Pacific Meridional Mode and the Atlantic Warm Pool further shape the dynamics of this event. Our findings underline the increasing importance of meridional winds in shaping the evolution of ENSO in recent decades. • The 2020–2023 triple-dip La Niña event did not occur after a strong El Niño event and initiated with a weak discharge state • The meridional southerly wind anomalies efficiently promoted the persistency of the negative SST anomalies during 2020–2023 • The South Pacific Meridional Mode and Atlantic Warm Pool jointly dominated the decadal anomalies of meridional southerlies [ABSTRACT FROM AUTHOR]

3D Stylization that creates stylized multi-view images is quite challenging, as it requires not only generating images which align with the desired style but also maintaining consistency across different perspectives. Most previous image style transfer methods focus on the 2D image domain and stylize each view independently, suffering from multi-view inconsistency. To tackle this challenging problem, we build on the neural radiance fields (NeRF) to stylize each 3D scene, as NeRF inherently ensures consistency across multiple perspectives, and has two sub-networks of geometry and appearance where appearance stylization cannot change the geometry. To enable arbitrary style transfer and more explicit and precise style adjustment, we introduce the CLIP model, which allows for style transfer based on either a text prompt or an arbitrary style image. We employ an ensemble of loss functions, of which CLIP loss ensures the similarity between the shared latent embeddings and generated style images, and Mask Loss is to constrain the 3D geometry to avoid non-smooth surface of NeRF. Experimental results demonstrate the effectiveness of our arbitrary 3D stylization generalized across diverse datasets. The proposed method outperforms most image-based and text-based 3D stylization models in terms of style transfer quality, producing pleasing images. • An arbitrary 3D stylization of radiance fields with text or images input. • CLIP style loss and Mask content loss for high-quality 3D artistic radiance fields. • Outperforms other 3D stylization models in style transfer quality. [ABSTRACT FROM AUTHOR]

Aspect-based sentiment analysis has achieved many results in recent years, but most of the research focuses on goods, services, and topics. The research in the medical field is very limited. Considering the problem that the fish disease descriptions contain large numbers of emotional tendencies but the existing data are insufficient in this field, a dataset named Diseases of Fish Animals (DFA) is constructed. In this paper, we propose a feature interaction model based on an adversarial strategy to learn the relationship between aspects and texts by improving the attention mechanism. Aiming at the problem that the fusion effect is reduced due to the difference in feature distribution space during the interaction process, an adversarial strategy is designed to align text and aspect features. Experiments are carried out on the DFA dataset, which involves 7 aspects and 3 sentiment polarity and contains more than 4700 samples. The experimental results show that the accuracy and F1 of the model are 87.07% and 87.19% respectively. Although the model proposed in this paper achieves the best results on DFA, there is still a certain gap for precision medicine diagnosis and further efforts are needed. [ABSTRACT FROM AUTHOR]

Antioxidants and UV stabilizers have some endocrine disrupting effects and liver toxicity. Both types of additives are still widely used in food contact plastics to improve the durability of plastic products. However, efficient and rapid detection of antioxidants and UV stabilizers has been a challenge due to the complexity of the plastic matrix and the low content of antioxidants and UV stabilizers. In this study, a sodium alginate/MOF-derived magnetic multistage pore carbon material (MIL-101(Fe)/SA-CAs) was developed, having the merits of abundant multistage pore structure, large specific surface area, and good magnetic separation properties. Thus, this material was selected as the sorbent for magnetic solid-phase extraction combined with a dissolution-precipitation method for the extraction and purification of antioxidants and UV stabilizers from polylactic acid food contact plastics. The extraction parameters such as sorbent type, sorbent dosage, sample solution pH, ionic strength, sorption time, elution solution type, volume, and time were investigated. Under the optimized conditions, all the analytes determined by UPLC-MS/MS showed good linear range (r > 0.99), detection limit (0.023–3.105 ng g−1), accuracy (70.6–102.3 %), and reproducibility (RSD<9.8 %). Further, the developed method was applied to determine the antioxidants and UV stabilizers in polylactic acid lunch boxes and straws, showing excellent applicability. The results showed that the antioxidants and UV stabilizers were detected in some of the samples, with a maximum detection of antioxidant 1010 at 7297 ng g−1. This study provided a sensitive, efficient, and environmentally friendly method for antioxidants and UV stabilizers in polylactic acid food contact plastics. The ideas for the design of environmentally friendly metal-organic frameworks and biomass composite multifunctional materials would promise in the sample pretreatment field for the emerging contaminants. [Display omitted] • MIL-101(Fe)/SA-CAs adsorbent was simple in preparation. • Multi-stage pore structure of the composite accomplished rapid target adsorption. • The established method allowed precise extraction from complex plastic matrices. • The adsorption of the target was a multimolecular layer with multiple interactions. [ABSTRACT FROM AUTHOR]

A novel rare earth separation system composed of lauric acid (LA) and primary ammonium (RNH 2) was studied. Compared with individual LA and RNH 2 , the mixed extraction system can significantly improve the extraction and separation ability of rare earth (RE). When LA and RNH 2 are mixed in an equal molar ratio, the synergistic coefficient for extracting Nd(III) in the system reaches 136.85. Effective separation of Nd from Co and Ni can be achieved, with the separation coefficients of 1503 and 2762 for Nd/Co and Nd/Ni, respectively. The ion association mechanism of developed extraction system can avoid the generation of saponification wastewater. Thus, the negative impact of saponification wastewater on the economy and environment can be reduced. The extraction system is simple to be prepared and easy to be stripped, which helps to reduce acid and alkali consumption. Application of this extraction system can effectively realize the separation of RE elements La, Ce, Pr, Nd and transition metals Co, Ni, Mn in nickel-metal hydride (NiMH) battery. This paper provides a new strategy for the development of ionic liquid saponification technology without saponified wastewater. [Display omitted] • LA-RNH 2 extraction system have pronounced synergistic effect on Nd. • The interaction between LA and RNH 2 provides a new strategy for saponification. • This ionic liquid saponification strategy can avoid saponification wastewater. • It has revealed application potential for the recovery of rare earth in NiMH battery. [ABSTRACT FROM AUTHOR]

Background: DNA-binding hot spots are dominant and fundamental residues that contribute most of the binding free energy yet accounting for a small portion of protein–DNA interfaces. As experimental methods for identifying hot spots are time-consuming and costly, high-efficiency computational approaches are emerging as alternative pathways to experimental methods. Results: Herein, we present a new computational method, termed inpPDH, for hot spot prediction. To improve the prediction performance, we extract hybrid features which incorporate traditional features and new interfacial neighbor properties. To remove redundant and irrelevant features, feature selection is employed using a two-step feature selection strategy. Finally, a subset of 7 optimal features are chosen to construct the predictor using support vector machine. The results on the benchmark dataset show that this proposed method yields significantly better prediction accuracy than those previously published methods in the literature. Moreover, a user-friendly web server for inpPDH is well established and is freely available at http://bioinfo.ahu.edu.cn/inpPDH. Conclusions: We have developed an accurate improved prediction model, inpPDH, for hot spot residues in protein–DNA binding interfaces by given the structure of a protein–DNA complex. Moreover, we identify a comprehensive and useful feature subset including the proposed interfacial neighbor features that has an important strength for identifying hot spot residues. Our results indicate that these features are more effective than the conventional features considered previously, and that the combination of interfacial neighbor features and traditional features may support the creation of a discriminative feature set for efficient prediction of hot spot residues in protein–DNA complexes. [ABSTRACT FROM AUTHOR]

Abstract  : In response to the challenges of accurately identifying event triggers and elements in long texts related to aquaculture, existing models struggle to differentiate between elements and triggers, as well as effectively recognize complete entity texts. To tackle this issue, this study proposes an algorithm for extracting fish disease events based on pseudo triggers and augmented event element data. The method starts by constructing pseudo samples using the original dataset. Two types of noise datasets are then generated: a trigger noise dataset constructed based on fish disease triggers and an entity noise dataset with varying levels of entity noise constructed based on fish disease entities. Next, three parallel neural networks are deployed to extract sample features from these datasets. The fish disease event extraction for the source dataset employs multi-label classification. For the trigger noise dataset, the sample features are activated using the sigmoid function, and the MRSE loss is utilized for optimization of this branch. For the entity noise dataset, the sample features are activated using the Relu function, and the XOR loss is used for optimization. Finally, the losses from the three branches are combined with weighted summation to obtain the fusion loss. The experimental results on the fish disease dataset used in this paper show that the proposed algorithm achieves an average accuracy of 78.71%, 78.95%, and 79.43% on F1, recall, and precision, respectively, which is a maximum improvement of 11.201%, 11.849%, and 12.421% in accuracy with respect to the baseline model on F1, recall, and precision, respectively. [ABSTRACT FROM AUTHOR]

[Display omitted] • P-O rather than P-C species are positively correlated with carbon interlayer spacing. • An expanded interspacing can allow more K-ions to insertion and accelerate them transfer. • The resulting products realize an excellent rate and high capacity, especially plateau capacity. Implanted phosphorus (P) atoms can greatly broaden carbon interlayer spacing and boost defect content, thus resulting in increased rate and capacity; however, different P-species (e.g., P-C and P-O) are how to affect interspacing and defect still remains unclear, and needs to be fundamentally explored. Herein, carbon materials with controllable P-C and P-O moieties (denoted as PNC-900-T, T = 0.2, 0.3, and 0.4) are first synthesized via a gas-steaming route. Detailed experimental analyses demonstrate that P-O species are positively correlated with interspacing, while P-C bonds devote more to enhancing defect. Besides, the introduced P-dopants can trigger the evolution of pore architecture from mesopores to micro/mesopores mixing and then to micropores. As such, the PNC-900–0.3 with the highest P-O proportion (74.8%) realizes the largest interspacing (0.377 nm), thus enabling more K-ions insertion and accelerating their migration. And its defect and micropores can function as active sites to promote the adsorption storage of K-ions. All these together contribute to high capacity, rate (232.3 mAh/g at 2 A/g), and a prolonged cycle lifespan (230.2 mAh/g over 2000 cycles). The effects of different P configurations on microstructure identified by this work provide an insight into the synthesis of other P-functionalized carbon. [ABSTRACT FROM AUTHOR]

• LA-RNH 2 extraction system have pronounced synergistic effect on Sm. • This study provides a new idea for the saponification of acidic extractant. • Ion association mechanism of the saponification strategy was investigated. • This ionic liquid saponification strategy can avoid saponification wastewater. • It has revealed application potential for the recovery of SmCo magnets. Acidic extractant is a kind of extractants commonly used in critical metal recovery industry, but the saponification wastewater generated during the saponification process inevitably causes environmental pollution. In order to develop a sustainable separation strategy for rare earth, the synergistic effect between lauric acid (LA) and primary amine N1923 (RNH 2 , with R = C 19 -C 23) was investigated in this paper. The study revealed that the hydrogen bond between LA and RNH 2 was helpful to realize the saponification of LA, thereby significantly improving the extraction and separation performance of LA. Unlike the quaternary ammonium or quaternary phosphonium in ionic liquid saponification studied in the previous study, RNH 2 can independently combine hydrogen ions to achieve the deprotonation of LA without adding alkali or basic resin, which makes the extraction and separation process more environmentally friendly. Aiming at the recovery of samarium cobalt (SmCo) magnet, the separation of Sm and Co in chloride medium was systematically studied. When LA and RNH 2 were combined in equal molar proportions to extract Sm, the extraction system demonstrated a high synergistic coefficient of 61.94, and separation coefficient of Sm and Co was remarkably high at 5326.2. It showed that the LA-RNH 2 extraction system for recovering Sm and Co from actual SmCo magnets could achieve 93.19 % recovery of Co, 90.53 % recovery of Sm and 16,222 Sm/Co separation factor. The LA-RNH 2 extraction system has shown potential applications in Sm/Co separation and waste SmCo magnet recovery processes. It also provides a novel strategy for the saponification of acidic extractant without alkali consumption and saponification wastewater discharge. [ABSTRACT FROM AUTHOR]

• We constructed SYG alleviates IgG-IC-induced acute lung injury via PPARγ target in vivio and vitro. • We identified SYG inhibits IgG-IC-induced pyroptosis in mice model and MH-S cells. • SYG may regulate the NLRP3/ASC/GSDMD/Caspase-1 pathway through Hdac11 by transcriptomic analysis flow analysis. Acute lung injury (ALI) is a life-threatening condition characterized by severe lung inflammation and tissue damage. In this study, we investigate the potential therapeutic efficacy of (+)-Syringaresinol (SYG), a natural compound known for its antioxidant and anti-inflammatory properties, in alleviating ALI induced by IgG immune complexes (IgG-IC). Using MH-S cells as a model, we explore SYG's ability to target peroxisome proliferator-activated receptor gamma (PPARγ) and its anti-inflammatory properties. Our comprehensive investigation aims to elucidate the specific molecular mechanisms underlying SYG's effects against pyroptosis, as revealed through transcriptomic analysis. Validation in C57BL/6 mice provides in vivo support. Our findings indicate that SYG effectively mitigates IgG-IC-induced lung damage, as evidenced by a significant reduction in lung inflammation and tissue injury. SYG treatment notably decreases pro-inflammatory cytokine levels (TNF-α, IL-6, IL-1β) in both lung tissue and cells. Molecular docking analysis reveals SYG's robust binding to PPARγ, leading to the inhibition of IgG-IC-induced inflammatory signaling pathways. Additionally, transcriptomic analysis unveils SYG's potential in suppressing macrophage pyroptosis, potentially through the downregulation of key inflammatory mediators (NLRP3, GSDMD, Caspase-1). In summary, our study presents compelling evidence supporting SYG as an effective therapeutic agent for ALI. SYG's activation of PPARγ contributes to the suppression of NF-κB and C/EBPs expression, thereby mitigating inflammation. Moreover, SYG demonstrates the ability to inhibit macrophage pyroptosis by targeting the NLRP3/GSDMD/caspase-1 axis. [ABSTRACT FROM AUTHOR]

Gas-liquid two-phase flow is closely related to the production and transportation of energy industries. A flow pattern analysis and identification method based on multi-scale power spectral entropy (MPSE) with pseudo-image encoding (PIE) is proposed. The resistance sensor array is used to collect gas-liquid two-phase flow information from the vertical upward pipeline, and the data is dimensionally reduced to simplify analysis. The MPSE is derived from the power spectrum of reduced-dimensional sequences to characterize the frequency domain complexity of the flow system at different scales. The optimal scale for spectral entropy analysis is further calculated to investigate the transition mechanism of gas-liquid two-phase flow patterns. In addition, the PIE algorithm is used to map the power spectrum into two-dimensional grayscale images to visualize the differences in frequency domain features of flow patterns. Combined with the deep learning model ResNeXt, the flow patterns are classified and compared with the traditional identification scheme. Results show that the proposed method can reveal the dynamic evolution behavior of gas-liquid two-phase flow from the frequency domain and achieve accurate identification of the flow patterns. • Gas/liquid two-phase flow information is collected using a resistance sensor array. • The multi-scale power spectral entropy can effectively reveal the transition mechanism of flow patterns. • Pseudo-image encoding can highlight the differences in frequency domain features between flow patterns. • The ResNeXt model can well distinguish the four patterns of gas/liquid two-phase flow. [ABSTRACT FROM AUTHOR]

DNA-binding hot spot residues of proteins are dominant and fundamental interface residues that contribute most of the binding free energy of protein–DNA interfaces. As experimental methods for identifying hot spots are expensive and time consuming, computational approaches are urgently required in predicting hot spots on a large scale. In this work, we systematically assessed a wide variety of 114 features from a combination of the protein sequence, structure, network and solvent accessible information and their combinations along with various feature selection strategies for hot spot prediction. We then trained and compared four commonly used machine learning models, namely, support vector machine (SVM), random forest, Naïve Bayes and k-nearest neighbor, for the identification of hot spots using 10-fold cross-validation and the independent test set. Our results show that (1) features based on the solvent accessible surface area have significant effect on hot spot prediction; (2) different but complementary features generally enhance the prediction performance; and (3) SVM outperforms other machine learning methods on both training and independent test sets. In an effort to improve predictive performance, we developed a feature-based method, namely, PrPDH (Prediction of Protein–DNA binding Hot spots), for the prediction of hot spots in protein–DNA binding interfaces using SVM based on the selected 10 optimal features. Comparative results on benchmark data sets indicate that our predictor is able to achieve generally better performance in predicting hot spots compared to the state-of-the-art predictors. A user-friendly web server for PrPDH is well established and is freely available at http://bioinfo.ahu.edu.cn:8080/PrPDH. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to examine stock market reactions and liquidity effects following the first bank loan announcement of zero-leverage firms. Design/methodology/approach: The authors use an event studies methodology in both a univariate and multivariate framework. The authors also use regression analysis. Findings: Using a sample of 96 zero-leverage firms listed on the FTSE 350 index over the time period of 2000–2015, the authors find evidence of a significant and permanent stock price increase as a result of the initial debt announcement. The loan announcement results in a sustained increase in trading volume and liquidity. This improvement continues to persist once the authors control for stock price and trading volume effects in both the short and long run. Furthermore, the authors examine the spread decomposition around the same period, and discover the adverse selection of the bid–ask spread is significantly related to the initial bank loan announcement. Research limitations/implications: The results can be attributed to the information cost/liquidity hypothesis, suggesting that investors demand a lower premium for trading stocks with more available information. Originality/value: This is the first paper to look at multiple industries, more than one loan and information asymmetry effects. [ABSTRACT FROM AUTHOR]

NaBr-mediated "bait and switch" mechanism can promote the formation of ZnO, and thus etches carbon matrix around the N -dopants. As a result, the fully formed N -doping and intrinsic carbon defect (N/DC) coupling sites can greatly improve capacitive behavior, so an excellent cycling stability with high reversible capacity is realized. [Display omitted] Coupling sites of nitrogen-dopants and intrinsic carbon defects (N/DC) are highly attractive to improve potassium-storage capacity and cycling stability, yet it is hard to effectively construct them. Herein, a novel strategy is proposed to establish abundant N/DC sites in N -doped carbon (ZIF8/NaBr-1-900) by pyrolyzing the mixture of metal–organic framework (ZIF8)/sodium bromide (NaBr). Systematic investigations disclose that the introduced NaBr can promote the full conversion of Zn-N 4 moieties into zinc oxide (ZnO) via a "bait and switch" mechanism. Such formed endogenous ZnO can etch the carbon matrix of the confined domains around the N dopants during pyrolysis process, and meanwhile the released N -atoms from Zn-N 4 moieties can largely form edge-N. As such, these N/DC coupling sites enable the resultant carbon to have a more significant capacitive behavior related to fast K-ion migration and high structural stability, leading to 255.3 mAh/g at 2 A/g with a prolonged cycle lifespan over 2000 cycles. Moreover, the assembled K-full battery presents a high energy density of 171.2 Wh kg−1 and excellent cyclability over 5000 cycles. This NaBr-mediated endogenous ZnO domain-confined etching strategy provides a new insight into the exploration of advanced carbon anode. [ABSTRACT FROM AUTHOR]

AIM: To verify the influence of type 2 diabetes mellitus (T2DM) on postextraction socket healing and subsequent first‐stage implant surgery. Materials and Methods: We analyzed pre‐extraction and postextraction cone beam computed tomography images of T2DM patients (n = 75) and paired nondiabetic controls to investigate changes in postextraction socket and ridge dimensions. The types of guided bone regeneration (GBR) surgeries were also compared. Three T2DM pig models were established to compare their postextraction socket healing with that of nondiabetic controls. Healing was quantitatively verified by microcomputed tomography. The osteogenic differentiation of mesenchymal stem cells (MSCs) was also compared. Results: Compared to nondiabetic controls, T2DM patients had higher socket width/depth values postextraction across all groups with different healing times. Among the T2DM patients, 62.7% could not receive first‐stage implant surgery within 6 months postextraction, and 54.7% received GBR surgery during first‐stage surgery. Ossification was not achieved in the socket center of the T2DM pig models after 3 months of healing. A decrease in osteogenic differentiation was observed in T2DM‐MSCs. Conclusions: T2DM interferes with the healing of the extraction socket and thus delays first‐stage implant surgery. This phenomenon may be due to the reduced osteogenic differentiation of MSCs in the sockets. [ABSTRACT FROM AUTHOR]

Volatiles with a pleasant smell are typical characteristics of both raw and cooked seafood. However, the effect of salinity on volatiles in marine bivalves remains unclear. In the current study, the volatiles in raw and cooked Sinonovacula constricta cultured under different salinities were investigated by head space-solid phase microextraction and gas chromatography-mass spectrometry. Overall 28 volatiles were identified in the raw samples and mainly comprised 1-pentanol (15.32-23.95%), 1,5-octadien-3-ol (14.20-16.73%) and 1-octen-3-ol (14.20-15.63%). A total of 41 volatiles, dominated by pentanal (32.33-46.80%), 1-pentanol (10.88-16.48%) and hexanal (5.64-13.70%), were determined in the cooked samples. Irrespective of whether they were raw or had been cooked, S. constricta cultured under high salinity possessed more abundant volatiles than those reared under low salinity. When the culture salinity of S. constricta was raised, changes in the volatile content occurred. For S. constricta cultured at low salinity, rearing at high salinity for several days prior to harvest could greatly improve the volatile content. This finding is of value for the improvement of volatiles important for odor and taste in other marine bivalves. [ABSTRACT FROM AUTHOR]

The protein kinase casein kinase 2 (CK2) exerts its influence on the metabolism of three major cellular substances by phosphorylating essential protein molecules involved in various cellular metabolic pathways. These substances include hormones, especially insulin, rate‐limiting enzymes, transcription factors of key genes, and cytokines. This regulatory role of CK2 is closely tied to important cellular processes such as cell proliferation and apoptosis. Additionally, tumor cells undergo metabolic reprogramming characterized by aerobic glycolysis, accelerated lipid β‐oxidation, and abnormally active glutamine metabolism. In this context, CK2, which is overexpressed in various tumors, also plays a pivotal role. Hence, this review aims to summarize the regulatory mechanisms of CK2 in diverse metabolic pathways and tumor development, providing novel insights for the diagnosis, treatment, and prognosis of metabolism‐related diseases and cancers. [ABSTRACT FROM AUTHOR]

Matrix complete dissolution combined with magnetic solid-phase extraction (MSPE) was applied to extract four benzotriazole ultraviolet stabilizers (BUVSs) from polyester curtains. Ultra-performance liquid chromatography tandem mass spectrometry was coupled to perform the content of trace BUVSs. The procedure was being developed in two steps. The polymer matrix was initially thoroughly dissolved by 1,1,1,3,3,3-hexafluoro-2-propanol (HFIP) followed by the addition of precipitant to separate the target from the dissolved polymer matrix. Next, triiron tetraoxide/biochar magnetic material was prepared and utilized as the sorbent for purification of the extract. Ultrasonic extraction coupled with the MSPE method and the proposed method was compared. Better extraction recovery of four BUVSs was acquired by the novel developed extraction method. The purification effect of the new extraction method was established by comparing the matrix effect of the polymer complete dissolution method and the polymer complete dissolution combined with the MSPE method. The extraction parameters were investigated. Under the optimized conditions, correlation coefficient (r) ranging from 0.9969 to 0.9997, limit of detection of 0.2 to 0.8 ng·g−1, and the recovery varied from 81.5 to 102.7% with RSD smaller than 10.7% were obtained for four BUVSs, respectively. This study provides a potential strategy for the efficient extraction and sensitive determination of BUVSs in polyester fibers samples. [ABSTRACT FROM AUTHOR]

This article explores the origin and evolution of the Y chromosome in kiwifruit. The sex determination of kiwifruit is genetically controlled by an XY system, and two Y-linked sex-determining genes, Shy Girl (SyGl) and Friendly Boy (FrBy), have been identified. The study examines the structural reorganization of the kiwifruit Y chromosome and identifies the sex-determining region (SDR) on chromosome 25 in A. chinensis and chromosome 12 in A. eriantha. The research also investigates the genomic diversity and evolutionary trajectories of the Y chromosome in kiwifruit. [Extracted from the article]

The facet capsular ligaments encapsulate the bilateral spinal facet joints and are common sources of painful injury due to afferent innervation. These ligaments exhibit architectural complexity, which is suspected to contribute to the experimentally observed lack of co-localization between macroscopic strain and microstructural tissue damage. The heterogeneous and multiscale nature of this ligament, combined with challenges in experimentally measuring its microscale mechanics, hinders the ability to understand sensory mechanisms under normal or injurious loading. Therefore, image-based, subject-specific, multiscale finite-element models were constructed to predict the mechanical responses of the human cervical facet capsular ligament under uniaxial tensile stretch. The models precisely simulated the force–displacement responses for all samples (R2=0.99±0.01) and showed promise in predicting the magnitude and location of peak regional strains at two different displacements. Yet, there was a loss of agreement between the model and experiment in terms of fiber organization at large tissue stretch, possibly due to a lack of accounting for tissue failure. The mean fiber stretch ratio predicted by the models was found to be significantly higher in regions that exhibited anomalous fiber realignment experimentally than in regions with normal realignment (p<0.002). The development of microstructural abnormalities was associated with the predicted fiber-level stretch (p<0.009), but not with the elemental maximum principal stress or maximum principal strain by logistic regression. The multiscale models elucidate a potential mechanical basis for predicting injury-prone tissue domains and for defining the relationships between macroscopic ligament stretch and microscale pathophysiology in the subfailure regime. [ABSTRACT FROM AUTHOR]

ABSTRACT: Injury to the spinal facet capsule, an innervated ligament with heterogeneous collagen organization, produces pain. Although mechanical facet joint trauma activates embedded afferents, it is unclear if, and how, the varied extracellular microstructure of its ligament affects sensory transduction for pain from mechanical inputs. To investigate the effects of macroscopic deformations on afferents in collagen matrices with different organizations, an in vitro neuron‐collagen construct (NCC) model was used. NCCs with either randomly organized or parallel aligned collagen fibers were used to mimic the varied microstructure in the facet capsular ligament. Embryonic rat dorsal root ganglia (DRG) were encapsulated in the NCCs; axonal outgrowth was uniform and in all directions in random NCCs, but parallel in aligned NCCs. NCCs underwent uniaxial stretch (0.25 ± 0.06 strain) corresponding to sub‐failure facet capsule strains that induce pain. Macroscopic NCC mechanics were measured and axonal expression of phosphorylated extracellular signal‐regulated kinase (pERK) and the neurotransmitter substance P (SP) was assayed at 1 day to assess neuronal activation and nociception. Stretch significantly upregulated pERK expression in both random and aligned gels (p < 0.001), with the increase in pERK being significantly higher (p = 0.013) in aligned than in random NCCs. That increase likely relates to the higher peak force (p = 0.025) and stronger axon alignment (p < 0.001) with stretch direction in the aligned NCCs. In contrast, SP expression was greater in stretched NCCs (p < 0.001) regardless of collagen organization. These findings suggest that collagen organization differentially modulates pain‐related neuronal signaling and support structural heterogeneity of ligament tissue as mediating sensory function. © 2017 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 36:770–777, 2018. [ABSTRACT FROM AUTHOR]

This study examines the diversity of low-level jet (LLJ) formation and related physical processes over southern China. A total of 171 LLJ formation events with enhanced daily southwesterlies and early-morning maximum wind speeds were observed during the mei-yu seasons of 1989–2018. The LLJs can be further categorized into four types based on the increases in the daily mean and diurnal amplitude of the low-level winds. Analysis of the synoptic-scale disturbances shows that the two types of LLJ formation (Q1 and Q4), which feature large increases of daily southerly wind components, are mainly induced by west-east dipole patterns of pressure change, in association with the enhanced southwest vortex and/or the western Pacific subtropical high (WPSH). In contrast, the other two types (Q2 and Q3), which feature relatively large increases in their daily westerly components, are related to a northwest-southeast dipole pattern of pressure change due to the mid-latitude trough and the WPSH. We further analyze the considerable variations in the diurnal thermal forcing among the LLJ formation events. The strong (weak) daytime heating of solar radiation leads to relatively large (small) increases in the diurnal amplitude of low-level winds in Q1 and Q2 (Q3 and Q4) types. Therefore, different combinations of synoptic-scale disturbances and diurnal thermal forcings are found to account for the diversity in LLJ formation and associated differences in downstream rainfall patterns. These results help to improve our understanding and prediction of the formation of LLJs. [ABSTRACT FROM AUTHOR]

As a representative of tumor immunotherapy, tumor vaccine can inhibit tumor growth by activating tumor-specific immune response, which has the advantages of relatively low toxicity and high efficiency, and has attracted much attention in recent years. However, there are still difficulties in how to effectively deliver tumor vaccines in vivo and make them work efficiently. It is a relatively mature method to load tumor specific antigens with suitable carriers to produce tumor vaccines. Here, a generally minimalist construction method of tumor nanovaccine was developed. A high-efficiency tumor nanovaccine (NV) was prepared in one step by a biomineralization-like method, which contained ovalbumin (OVA, model antigen), unmethylated cytosine-phosphate-guanine (CpG, adjuvant) and Mn-NP (carrier and adjuvant). NV not only showed good tumor preventive effect, but also could successfully inhibited tumor development and metastasis when combined with anti-PD-L1, and induced long-term immune memory effect. However, the method of screening tumor specific antigen to construct nanovaccine is cumbersome and tumors are heterogeneous. Therefore, surgically resected tumor tissue is the best source of antigens for preparing tumor vaccines. Next, based on the strong loading ability of the carrier, we designed a personalized tumor nanovaccine (PNV) using the supernatant of tumor abrasive fluid (STAF) as antigen based on the generally minimalist tumor nanovaccine construction strategy. PNV combined with anti-PD-L1 could successfully inhibit post-surgical tumor recurrence and induce strong and durable immune memory effects. This study presents a novel, general, and minimalist strategy to construct high-efficiency personalized nanovaccine, which has a wide range of potential applications in the field of tumor treatment. [ABSTRACT FROM AUTHOR]

The propagation of Love waves in the structure consisting of a nanosized piezoelectric film and a semi-infinite elastic substrate is investigated in the present paper with the consideration of surface effects. In our analysis, surface effects are taken into account in terms of the surface elasticity theory and the electrically-shorted conditions are adopted on the free surface of the piezoelectric film and the interface between the film and the substrate. This work focuses on the new features in the dispersion relations of different modes due to surface effects. It is found that with the existence of surface effects, the frequency dispersion of Love waves shows the distinct dependence on the thickness and the surface constants when the film thickness reduces to nanometers. In general, phase velocities of all dispersion modes increase with the decrease of the film thickness and the increase of the surface constants. However, surface effects play different functions in the frequency dispersions of different modes, especially for the first mode dispersion. Moreover, different forms of Love waves are observed in the first mode dispersion, depending on the presence of the surface effects on the surface and the interface. [ABSTRACT FROM AUTHOR]

Temperature dependent-electrical resistance of n-type Bi2Te3 was investigated under high pressure. Superconductivity was detected at 4.9 GPa with Tconset = 2.8 K. Resistance and Tc suggest that there are two electronic phase transitions below 10 GPa. We conjecture that the bulk insulating phase first changes to semimetal and then to metal. The evolution of the Hall coefficient is qualitatively consistent with the proposed electronic phase transition. The origin of superconductivity and topological properties are also discussed. [ABSTRACT FROM AUTHOR]

Abstract: Higher and more volatile liquid fossil fuel prices have had profound effects on international energy and wood product markets. Understanding this evolving economic and technological landscape requires economic models that capture the interconnections between energy markets and wood product markets, and can be used to forecast the impact of alternative policy and market incentives. The need for such an analytic framework is underscored by the consensus that efficiently produced wood bioenergy could provide many climate benefits compared to fossil-fuel intensive substitutes. A model is presented for analysis of how increased use of wood bioenergy, in the forms of fuelwood, cellulosic ethanol from woody biomass, and electricity produced from wood, might interact with global markets for wood products; liquid, solid, and gaseous fuels; and electricity produced from other sources. It links U.S. energy markets with wood product markets and endogenizes the demand for wood bioenergy with price-driven market clearing mechanisms. Projections made with the model point to a substantial increase in demand for woody cellulosic ethanol in the U.S. for the next 30 years if oil prices remain high. [Copyright &y& Elsevier]

• Nanofiber network with double fast Li+ and charge transfer pathways was designed. • The functional groups on the cellulose can induce self-assembly without binder. • The –OH on cellulose has hydrogen bond with F and promote desolvation of Li salt. • The electrode shows very high loading and excellent flexibility. • The battery with the electrode shows high volumetric energy density of 740 Wh/L. Thick electrodes with high loading are attractive for high-energy storage devices, but they face major challenges of slow ion transfer and poor mechanical stability. Carbon templates such as reduced graphene oxide and carbon nanotube can promote the electrons transfer of thick electrodes and enhance their strength, but they still exhibit a complex producing process, slow Li+ transfer and high cost. Herein, a nanofiber network with double fast Li+ and electrons transfer pathways by the self-assembly of carbon nanoparticles on the negatively charged natural cellulose fibers was designed. The abundant oxygen-containing functional groups from the cellulose fibers enabled the electrode with abundant negative charge which can adsorb the neutral particles with strong electrostatic interaction. And the Density Functional Theory calculation demonstrates that oxygen-containing functional groups also has stronger adsorption energy for PF 6 − anions in electrolyte which can promote the desolvation of the solvated Li salts, thus promote Li+ transfer. After integration with lithium iron phosphate, this network achieves a robust high-loaded electrode with good electrical conductivity and shortened ion transfer pathways without traditional current collector and binder. Based on the robust electrode structure and fast transfer kinetics of electrons and Li+, the batteries exhibit excellent cycle stability with capacity retention of 98 % after long 400 cycles and high volumetric energy density of 740 Wh/L, which greatly surpass the conventional batteries with coating LiFePO 4 (LFP) cathode. Given the low-cost raw materials and convenient operation, the design of self-standing flexible electrodes with high loading will offer a promising and effective strategy for other storage devices with high energy. [ABSTRACT FROM AUTHOR]

[Display omitted] • Ionic liquid was explored in the construction of phosphopeptide enrichment material. • Preparation of ionic liquid polymer microsphere by one-step polymerization. • Efficient and specific enrichment of phosphopeptides from cell lysate and serum. A Ti4+-functionalized ionic liquid polymer microsphere was proposed and prepared through free radical precipitation polymerization. The polymer microsphere demonstrates excellent performance on phosphopeptide enrichment, with a low detection limit (0.5 fmol) and good selectivity (1:2500). Through the analysis of HepG2 cell lysate using nano LC-MS/MS after material enrichment, a total of 1100 phosphopeptides and 733 phosphoproteins were identified. Additionally, in the serum of liver cancer patients, 69 phosphopeptides, 47 phosphoproteins, and 52 phosphorylation sites were identified, while healthy controls exhibited 55 phosphopeptides, 31 phosphoproteins, and 40 phosphorylation sites. Label-free quantification revealed 10 differentially expressed proteins (DEPs), with five proteins (FN1, SERPIND1, SERPINF2, IGFBP3, and MENT) being up-regulated and five proteins (SELENOP, PLG, SPP2, SERPINC1, and GP1BB) being down-regulated. These findings highlight the potential of the MBA-VImDOPA-Ti4+ polymer microsphere in specifically enriching phosphopeptides from clinical biological samples. [ABSTRACT FROM AUTHOR]

Biological rhythms denote the cyclical patterns of life activities anchored to a 24-hour cycle. Research shows that depression exhibits disturbances in biological rhythms. Yet, the relationship between these biological rhythms and concomitant anxiety symptoms is insufficiently investigated in structured clinical assessments. This multicenter study, carried out in four Chinese hospitals, comprehensively examined the relationship between anxiety and disruptions in biological rhythms among patients with depression. The study encompassed 218 patients diagnosed with depression and 205 matched healthy controls. The Chinese version of the Biological Rhythms Interview of Assessment in Neuropsychiatry was utilized to evaluate the participants' biological rhythms, focusing on four dimensions: sleep, activity, social, and diet. In patients with depression, there is a significant positive correlation between the severity of anxiety symptoms and the disturbances in biological rhythms. The severity of anxiety and depression, along with the quality of life, are independently associated with disruptions in biological rhythms. The mediation model reveals that anxiety symptoms mediate the relationship between depressive symptoms and biological rhythms. This research highlights the role of anxiety within the spectrum of depressive disorders and the associated disturbances in biological rhythms. Our findings shed light on potential pathways towards more targeted preventive strategies and therapeutic interventions for individuals battling depression and anxiety. [ABSTRACT FROM AUTHOR]

Since the onset of the coronavirus disease 2019 (COVID-19) pandemic, SARS-CoV-2 variants capable of breakthrough infections have attracted global attention. These variants have significant mutations in the receptor-binding domain (RBD) of the spike protein and the membrane (M) protein, which may imply an enhanced ability to evade immune responses. In this study, an examination of co-mutations within the spike RBD and their potential correlation with mutations in the M protein was conducted. The EVmutation method was utilized to analyze the distribution of the mutations to elucidate the relationship between the mutations in the spike RBD and the alterations in the M protein. Additionally, the Sequence-to-Sequence Transformer Model (S2STM) was employed to establish mapping between the amino acid sequences of the spike RBD and M proteins, offering a novel and efficient approach for streamlined sequence analysis and the exploration of their interrelationship. Certain mutations in the spike RBD, G339D-S373P-S375F and Q493R-Q498R-Y505, are associated with a heightened propensity for inducing mutations at specific sites within the M protein, especially sites 3 and 19/63. These results shed light on the concept of mutational synergy between the spike RBD and M proteins, illuminating a potential mechanism that could be driving the evolution of SARS-CoV-2. [ABSTRACT FROM AUTHOR]

MicroRNAs (miRNAs) are widely involved in various biological processes of plants and contribute to plant resistance against various pathogens. In this study, upon sugarcane mosaic virus (SCMV) infection, the accumulation of maize (Zea mays) miR398b (ZmmiR398b) was significantly reduced in resistant inbred line Chang7‐2, while it was increased in susceptible inbred line Mo17. Degradome sequencing analysis coupled with transient co‐expression assays revealed that ZmmiR398b can target Cu/Zn‐superoxidase dismutase2 (ZmCSD2), ZmCSD4, and ZmCSD9 in vivo, of which the expression levels were all upregulated by SCMV infection in Chang7‐2 and Mo17. Moreover, overexpressing ZmmiR398b (OE398b) exhibited increased susceptibility to SCMV infection, probably by increasing reactive oxygen species (ROS) accumulation, which were consistent with ZmCSD2/4/9‐silenced maize plants. By contrast, silencing ZmmiR398b (STTM398b) through short tandem target mimic (STTM) technology enhanced maize resistance to SCMV infection and decreased ROS levels. Interestingly, copper (Cu)‐gradient hydroponic experiments demonstrated that Cu deficiency promoted SCMV infection while Cu sufficiency inhibited SCMV infection by regulating accumulations of ZmmiR398b and ZmCSD2/4/9 in maize. These results revealed that manipulating the ZmmiR398b‐ZmCSD2/4/9‐ROS module provides a prospective strategy for developing SCMV‐tolerant maize varieties. [ABSTRACT FROM AUTHOR]

Previous studies have indicated that EPO maintains the M2 microglia phenotype that contributes to white matter repair after ischemic stroke in young mice (2 months old). However, the underlying mechanisms that regulate microglial polarization are poorly defined. This study investigated the neuroprotective effects of nonerythropoietic mutant EPO (MEPO) on white matter and the underlying mechanism in middle-aged (9-month-old) male mice following cerebral ischemia. Middle-aged male C57 BL/6 mice were treated with MEPO (5000 IU/kg) or vehicle after middle cerebral artery occlusion (MCAO) and reperfusion. The specific inhibitor AG490 was used to block the JAK2/STAT3 pathway. Neurological function was assessed by beam walking and adhesive removal tests. Immunofluorescence staining and western blotting were used to assess the severity of white matter injury, phenotypic changes in the microglia and the expression of the signaling molecules. MEPO significantly improved neurobehavioral outcomes, alleviated brain tissue loss, and ameliorated white matter injury after MCAO compared with the vehicle group. Moreover, MEPO promoted oligodendrogenesis by shifting microglia toward M2 polarization by promoting JAK2/STAT3 activation and inhibiting the expression of C/EBPβ at 14 days after cerebral ischemia-reperfusion. However, the MEPO's effect on microglial M2 polarization and oligodendrogenesis was largely suppressed by AG490 treatment. Collectively, these data indicate that MEPO treatment improves white matter integrity after cerebral ischemia, which may be partly explained by MEPO facilitating microglia toward the beneficial M2 phenotype to promote oligodendrogenesis via JAK2/STAT3 and the C/EBPβ signaling pathway. This study provides novel insight into MEPO treatment for ischemic stroke. [ABSTRACT FROM AUTHOR]

Objective: Type D personality is a psychosocial risk factor for cardiovascular events and in-stent restenosis (ISR), but the mechanisms involved are not well understood. This study aimed to evaluate the effects of dietary patterns on the association between Type D personality and ISR in patients with coronary artery disease treated with percutaneous coronary intervention (PCI).Methods: This cross-sectional study comprised a total of 230 post-PCI patients who were assessed for Type D personality, depression, dietary patterns, physical activity and medication adherence via self-administered questionnaires. ISR was assessed by coronary angiography.Results: Type D personality (odds ratio [OR], 3.35; 95% confidence interval [CI], 1.05-10.71, p=0.042), low fruit intake (OR, 0.30; 95% CI, 0.12-0.68, p=0.008) and low vegetable intake (OR, 0.48, 95% CI, 0.27-0.91, p=0.021) were independent risk factors for ISR after adjustment for psychosocial, lifestyle and cardiovascular risk factors. Mediation analyses revealed that Type D personality had a significant direct effect on the development of ISR (p<0.05). In addition, nutrients in fruits and vegetables, including vitamin C, vitamin E and fiber, were important mediators of the relationship between Type D personality and ISR (p<0.05), the percentage of total indirect effect was 24.65%.Conclusions: These findings suggested that the low intake of fruit and vegetables in Type D patients can predict ISR. The healthy dietary interventions to supply vitamin C, vitamin E and fiber may help to improve the prognosis in post-PCI patients with Type D personality. [ABSTRACT FROM AUTHOR]

Background: Identification of hot spots in protein-DNA interfaces provides crucial information for the research on protein-DNA interaction and drug design. As experimental methods for determining hot spots are time-consuming, labor-intensive and expensive, there is a need for developing reliable computational method to predict hot spots on a large scale. Results: Here, we proposed a new method named sxPDH based on supervised isometric feature mapping (S-ISOMAP) and extreme gradient boosting (XGBoost) to predict hot spots in protein-DNA complexes. We obtained 114 features from a combination of the protein sequence, structure, network and solvent accessible information, and systematically assessed various feature selection methods and feature dimensionality reduction methods based on manifold learning. The results show that the S-ISOMAP method is superior to other feature selection or manifold learning methods. XGBoost was then used to develop hot spots prediction model sxPDH based on the three dimensionality-reduced features obtained from S-ISOMAP. Conclusion: Our method sxPDH boosts prediction performance using S-ISOMAP and XGBoost. The AUC of the model is 0.773, and the F1 score is 0.713. Experimental results on benchmark dataset indicate that sxPDH can achieve generally better performance in predicting hot spots compared to the state-of-the-art methods. [ABSTRACT FROM AUTHOR]

Tailor rolled blanks (TRB) have been extensively used in the automotive industry because of lightweight. Through the flexible rolling process and appropriate annealing treatment, the target geometry, required mechanical properties, and good formability of TRB can be achieved. In this study, two types of annealing processes were attempted, i.e. batch annealing and continuous annealing. The effects of annealing parameters on the microstructure, mechanical properties and formability of HC340LA TRB were investigated. First, a series of batch annealing and continuous annealing were conducted on cold rolled TRB. Next, the microstructure distribution of TRB was evaluated. The mechanical properties and formability of annealed specimens were tested through the uniaxial tensile test and Erichsen cupping test, respectively. The results showed that the mechanical properties and formability were controlled by reduction, annealing type and annealing parameters. During the batch annealing, mechanical properties along the rolling direction were influenced by the degree of recrystallization and the average grain size, the formability increased with the increase of annealing temperature. TRB annealed at 700 °C for 60 min showed relatively homogeneous mechanical properties and good formability in the reduction range of 36–54 %. During continuous annealing, the mechanical properties and formability were determined by the degree of austenitization and the average grain size. TRB annealed at 930–950 °C for 3 min showed homogeneous mechanical properties and good formability for the entire range of reduction. [ABSTRACT FROM AUTHOR]