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Background/Aims: Inflammation is an essential driver of colorectal cancer (CRC). Identifying phenotypes and targets associated with inflammation and cancer may be an effective way to treat CRC. Materials and Methods: R was used to analyze interleukin 6 cytokine family signal transducer (IL6ST) expression in The Cancer Genome Atlas Colon Adenocarcinoma database. Immunohistochemistry, western blotting, and quantitative PCR were used to detect IL6ST and ferroptosis-related genes expression in our cohort. Receiver operating characteristic curves evaluated the specificity and sensitivity of IL6ST to predict CRC. Cell counting kit-8 investigated cell viability. Mitochondrial morphology, total iron, and reactive oxygen species (ROS) levels were evaluated to assess cell ferroptosis. The correlation of IL6ST and immune cells filtration were also analyzed based on R. Results: IL6ST was significantly upregulated in CRC tissues (P < .05). The specificity and sensitivity of IL6ST for predicting CRC were high (area under the curve (AUC): 0.919, CI: 0.896-0.942). IL6ST was significantly associated with ferroptosis-related genes. IL6ST knockdown decreased SW480 cells viability (knockdown vs. vector, P = .004), promoted the ferroptosis phenotype, and increased iron accumulation (knockdown vs. vector P = .014) and ROS production (knockdown vs. vector P = .005). IL6ST upregulation increased SW620 cells viability (overexpression vs. blank, P = .001), inhibited the ferroptosis phenotype, and decreased iron accumulation (overexpression vs. vector P = 0.006) and ROS production (overexpression vs. vector P = .05). IL6ST increased FTH1 and GPX4 expression and reduced PTGS2, NOX1, and ACSL4 expression (P < .01). Additionally, IL6ST level is linked to immune cell infiltration. A higher enrichment score of T cells was observed in IL6ST up-regulated group. Conclusion: IL6ST inhibits ferroptosis and may be a potential novel therapeutic target in CRC via the modulation of ferroptosis.

Snow density is one of the basic properties used to describe snow cover characteristics, and it is critical for remote sensing retrieval, water resources assessment and modeling inputs. There are many instruments available to measure snow density in situ. However, there are measurement errors of snow density for bulk and layers or gravimetric and electronic instruments, which may affect the accuracy of remote sensing retrieval and model simulation. Especially in China, due to the noticeable heterogeneity of snowpacks, it is necessary to evaluate in detail the performance and applicability of snow density instruments in different snowpack conditions. This study evaluated the performance of different snow density instruments: the Federal Sampler, the model VS–43 snow density cylinder (VS–43), the wedge snow density cutter (WC1000 and WC250), and the Snow Fork. The average bulk snow density of all instrument measurements was set as the reference value for evaluation. The results showed that as compared with the reference, the VS–43 cylinder presented the best performance for bulk snow density measurement in the measured range with the lowest RMSE (11 kg m−3), BIAS (3 kg m−3), and MRE (1.6%). For layer observation, bulk snow density was overestimated by 8.1% with WC1000 and underestimated by 11.4% with Snow Fork which was the worst performance compared with the reference value, and there were greater measurement errors of snow density in the depth hoar than other snow layers. Compared with grassland, the uncertainty of snow density measurements was slightly lower in forests. Overall, the Federal Sampler and VS–43 cylinder are more suitable for bulk snow density measurement in deep snowpack regions across China, and it is recommended to use WC1000, WC250 and Snow Fork to measure the snow density of snow layers in the snow stratigraphy.

Spectroscopic data, particularly diffraction data, are essential for materials characterization due to their comprehensive crystallographic information. The current crystallographic phase identification, however, is very time consuming. To address this challenge, we have developed a real-time crystallographic phase identifier based on a convolutional self-attention neural network (CPICANN). Trained on 692 190 simulated powder X-ray diffraction (XRD) patterns from 23 073 distinct inorganic crystallographic information files, CPICANN demonstrates superior phase-identification power. Single-phase identification on simulated XRD patterns yields 98.5 and 87.5% accuracies with and without elemental information, respectively, outperforming JADE software (68.2 and 38.7%, respectively). Bi-phase identification on simulated XRD patterns achieves 84.2 and 51.5% accuracies, respectively. In experimental settings, CPICANN achieves an 80% identification accuracy, surpassing JADE software (61%). Integration of CPICANN into XRD refinement software will significantly advance the cutting-edge technology in XRD materials characterization.

The atmospheric correction of hyperspectral data stands as a fundamental step in quantitative applications, crucial for the accurate analysis of hyperspectral information. Zhuhai-1 hyperspectral data, characterized by its high spatial and spectral resolution, holds substantial potential and advantages for the quantification of water body information. Nonetheless, the adoption of more precise physical models for atmospheric correction often demands extensive satellite and ground environmental parameters, which pose practical challenges in applying physical models The Dark Object Subtraction (DOS), leveraging the intrinsic spectral characteristics of the imagery, offers an efficient alternative for achieving improved atmospheric correction results tailored to the data and study area. In this context, this study presents a Dark Object Subtraction for Water body information extraction (DOSW), specifically designed to advance the quantification of water body information in Zhuhai-1 hyperspectral data. The proposed method is rigorously evaluated by comparing the correction results from the Foshan region and Feilaixia Reservoir with standard and measured spectra of typical objects. The results demonstrate the accuracy of DOSW in atmospheric correction, with correlation coefficients exceeding 0.7 when compared to standard spectra for three representative objects. Notably, DOSW achieves exceptional accuracy in water body correction, achieving a correlation coefficient of 0.95 and an RMSE of 0.002 in the Feilaixia Reservoir, and a correlation coefficient of 0.72 and an RMSE of 0.005 in the Foshan region. Overall, the results underscore the efficacy of DOSW in accurately addressing atmospheric correction challenges to Zhuhai-1 hyperspectral data, effectively meeting the requirements of hyperspectral quantification applications.

Abstract Reliable projections of permafrost change are crucial for estimating permafrost carbon loss. However, potential model biases in surface air temperature may yield unrealistic projections of future permafrost area. Here, by leveraging the emergent relationship between equilibrium climate sensitivity and projected changes in mean annual air temperature over High Mountain Asia (HMA), we mitigate the overestimated local warming rates and excessive thawing of permafrost associated with the “hot model” problem in models participating in the Coupled Model Intercomparison Project phase 6. After constraint, permafrost area over HMA will reduce by 37%, 64% and 99% in 2081–2100 relative to present‐day under the SSP1‐2.6, SSP2‐4.5 and SSP5‐8.5 scenarios, respectively. In contrast, the unconstrained projections tend to overestimate the loss of permafrost area by nearly 10% under the low and mid‐emission scenarios due to the overestimation of local warming rates. These findings are crucial for policymaking and provide valuable insights into global permafrost projection.

Upon entering the marine environment, plastics are colonized by a plethora of microorganisms to form a plastisphere, influencing the fate and transport of the plastic debris and the health of marine ecosystems. The assembly of marine plastisphere is generally believed to be dominated by stochastic processes. However, it remains elusive whether microbial interaction in the assembly of plastisphere microbial communities is conserved or not. We analyzed the plastisphere microbiomes of 137 plastic debris samples from intertidal zones at different geographical locations and habitats (seagrass, coral, mangrove, beach, and open ocean) and compared them with the surrounding sediment and seawater microbiomes. Microbial community structures of the plastisphere from different locations were more similar to each other but differed substantially from the surrounding sediment and water microbiomes, implying a common mechanism of plastisphere assembly. We used different machine learning algorithms (Multinomial Logistic Regression, Support Vector Machine, Decision Trees, Random Forest, and Artificial Neural Networks) to classify plastic debris samples with high sensitivity based on the microbiome composition. Eukaryotic and prokaryotic phototrophic organisms such as green algae, diatoms, and cyanobacteria, were found to be enriched on the plastic surfaces. Network analysis revealed the central role of the phototrophic organisms in the formation and sustenance of the plastispheres. We found that phototrophs served as core members interacting strongly with heterotrophic organisms in marine plastisphere, irrespective of the sampling location, habitats, and polymer types. This would explain the stochastic assembly of the plastisphere along with conserved properties driven by the phototrophs in the surrounding environment. Our results highlight the importance of phototrophic organisms in shaping the marine plastisphere microbial communities.

ABSTRACTRussula is the largest genus in the Russulales and is widespread throughout the world. Almost all Russula species are known to be ectomycorrhizal with high ecological and edible values, and some are lethal poisonous. In this study, four new species belonging to the subgenus Russula crown clade are identified based on morphological and phylogenetic evidence from the Xizang Autonomous Region and other provinces of China. Morphologically, Russula paragraveolens (sect. Polychromae, subsect. Xerampelinae) is mainly characterised by a cherry red to blood red pileus centre, a reddish orange pileus margin; R. pseudograveolens (sect. Polychromae, subsect. Xerampelinae) is characterised by a violet brown to brownish red pileus centre, a pale red to pastel red pileus margin and short basidia; R. shigatseensis (sect. Flavisiccantes, subsect. Lepidinae) is characterised by a brownish orange to madder red pileus centre, pinkish red pileus margin, and having lateral branches or branches of hyphal terminations in pileipellis; R. yadongensis (sect. Tenellae, subsect. Laricinae) is characterised by a dark purplish red pileus centre with brownish purple tints and having isolated to clustered spines of spore ornamentations. Their distinct taxonomic status is confirmed by the positions of the four new species in both the ITS and 4-locus (nucLSU, mtSSU, rpb2, tef1) phylogenetic trees.

Abstract A key factor limiting the development of silicone rubber insulating materials is their short service life in harsh operating environments. The establishment of a self‐healing system is desired to improve the long‐term operational performance of silicone rubber and effectively extend its service life. In this study, poly(urea‐formaldehyde) microcapsules containing polydimethylsiloxane healing agents are prepared and a dual‐component microcapsule self‐healing system for silicone rubber material is established and optimised. In addition, the key factors affecting the self‐healing performance (such as microcapsule size, rupture rate, and microcapsule doping amount) are investigated. It is found that when SYLGARDTM 184 is used as the healing agent and matrix, with a 4:6 (A:B) doping ratio of dual‐component microcapsules and 20 phr doping amount, the self‐healing efficiency is approximately 51%. Furthermore, increasing the microcapsule rupture rate and the interface strength between the healing agent and the matrix can effectively improve the self‐healing performance. The relationships between key factors and self‐healing performance are theoretically revealed. Based on the relationships, the microcapsule self‐healing system can be appropriately designed. The results of this paper can provide a reference for the development of long‐life silicone rubber insulating materials.

Abstract Background Whole-genome duplication and long terminal repeat retrotransposons (LTR-RTs) amplification in organisms are essential factors that affect speciation, local adaptation, and diversification of organisms. Understanding the karyotype projection and LTR-RTs amplification could contribute to untangling evolutionary history. This study compared the karyotype and LTR-RTs evolution in the genomes of eight oaks, a dominant lineage in Northern Hemisphere forests. Results Karyotype projections showed that chromosomal evolution was relatively conservative in oaks, especially on chromosomes 1 and 7. Modern oak chromosomes formed through multiple fusions, fissions, and rearrangements after an ancestral triplication event. Species-specific chromosomal rearrangements revealed fragments preserved through natural selection and adaptive evolution. A total of 441,449 full-length LTR-RTs were identified from eight oak genomes, and the number of LTR-RTs for oaks from section Cyclobalanopsis was larger than in other sections. Recent amplification of the species-specific LTR-RTs lineages resulted in significant variation in the abundance and composition of LTR-RTs among oaks. The LTR-RTs insertion suppresses gene expression, and the suppressed intensity in gene regions was larger than in promoter regions. Some centromere and rearrangement regions indicated high-density peaks of LTR/Copia and LTR/Gypsy. Different centromeric regional repeat units (32, 78, 79 bp) were detected on different Q. glauca chromosomes. Conclusion Chromosome fusions and arm exchanges contribute to the formation of oak karyotypes. The composition and abundance of LTR-RTs are affected by its recent amplification. LTR-RTs random retrotransposition suppresses gene expression and is enriched in centromere and chromosomal rearrangement regions. This study provides novel insights into the evolutionary history of oak karyotypes and the organization, amplification, and function of LTR-RTs.

BackgroundThe active metabolite of benzo[a]pyrene (BaP), 7,8-dihydroxy-9,10-epoxybenzo[a]pyrene (BPDE), can form adducts with DNA, but the spectrum of BPDE-DNA adducts is unclear. ObjectiveTo identify the distribution of BPDE adduct sites and associated genes at the whole-genome level by chromatin immunoprecipitation followed by sequencing (ChIP-Seq), and serve as a basis for further exploring the toxicological mechanisms of BaP. MethodsHuman bronchial epithelial-like cells (16HBE) were cultured to the fourth generation inthe logarithmic growth phase. Cells were harvested and added to chromatin immunoprecipitation lysis buffer. The lysate was divided into experimental and control groups. The experimental group received a final concentration of 20 μmol·L−1 BPDE solution, while the control group received an equivalent volume of dimethyl sulfoxide solution. The cells were then incubated at 37 °C for 24 h. Chromatin fragments of 100-500 bp were obtained through sonication. BPDE-specific antibody (anti-BPDE 8E11) was used to enrich DNA fragments with BPDE adducts. High-throughput sequencing was conducted to detect BPDE adduct sites. The top 1000 peak sequences were subjected to motif analysis using MEME and DREME software. BPDE adduct target genes at the whole-genome level were annotated, and Gene Ontology (GO) functional analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of BPDE adduct target genes were conducted using bioinformatics techniques. ResultsThe high-throughput sequencing detected a total of 842 BPDE binding sites, distributed across various chromosomes. BPDE covalently bound to both coding and non-coding regions of genes, with 73.9% binding sites located in intergenic regions, 19.6% in intronic regions, and smaller proportions in upstream 2 kilobase, exonic, downstream 2 kilobase, and 5' untranslated regions. Regarding the top 1000 peak sequences, four reliable motifs were identified, revealing that sites rich in adenine (A) and guanine (G) were prone to binding. Through the enrichment analysis of binding sites, a total of 199 BPDE-adduct target genes were identified, with the majority located on chromosomes 1, 5, 7, 12, 17, and X. The GO analysis indicated that these target genes were mainly enriched in nucleic acid and protein binding, participating in the regulation of catalytic activity, transport activity, translation elongation factor activity, and playing important roles in cell division, differentiation, motility, substance transport, and information transfer. The KEGG analysis revealed that these target genes were primarily enriched in pathways related to cardiovascular diseases, cancer, and immune-inflammatory responses. ConclusionUsing ChIP-Seq, 199 BPDE adduct target genes at genome-wide level are identified, impacting biological functions such as cell division, differentiation, motility, substance transport, and information transfer. These genes are closely associated with cardiovascular diseases, tumors, and immune-inflammatory responses.

Abstract Accelerating the discovery of advanced materials is crucial for modern industries, aerospace, biomedicine, and energy. Nevertheless, only a small fraction of materials are currently under experimental investigation within the vast chemical space. Materials scientists are plagued by time-consuming and labor-intensive experiments due to lacking efficient material discovery strategies. Artificial intelligence (AI) has emerged as a promising instrument to bridge this gap. Although numerous AI toolkits or platforms for material science have been developed, they suffer from many shortcomings. These include primarily focusing on material property prediction and being unfriendly to material scientists lacking programming experience, especially performing poorly with limited data. Here, we developed MLMD, an AI platform for materials design. It is capable of effectively discovering novel materials with high-potential advanced properties end-to-end, utilizing model inference, surrogate optimization, and even working in situations of data scarcity based on active learning. Additionally, it integrates data analysis, descriptor refactoring, hyper-parameters auto-optimizing, and properties prediction. It also provides a web-based friendly interface without need programming and can be used anywhere, anytime. MLMD is dedicated to the integration of material experiment/computation and design, and accelerate the new material discovery with desired one or multiple properties. It demonstrates the strong power to direct experiments on various materials (perovskites, steel, high-entropy alloy, etc). MLMD will be an essential tool for materials scientists and facilitate the advancement of materials informatics.

Developing materials with multiple desired characteristics is a tremendous challenge, particularly in an elaborate material system. Herein, a machine learning assisted material design strategy was applied to simultaneously optimize dual target attributes by considering γ′ solvus temperature and alloy density of multi-component Co-based superalloys. To verify the soundness of our strategy, four alloys were selected and experimentally synthesized from >510,000 candidates, each of them possessing γ′ solvus temperature exceeding 1200 °C and alloy density below 8.3 g/cm3. Of those, Co-35Ni-12Al-5Ti-3V-3Cr-2Ta-2Mo (at.%) possesses the highest γ′ solvus temperature of 1250 °C and lower density of 8.2 g/cm3. This article validates a straightforward strategy to guide rapid discovery and fabrication of multi-component materials with desired dual-performance characteristics.

Accurate and efficient urban traffic flow prediction can help drivers identify road traffic conditions in real-time, consequently helping them avoid congestion and accidents to a certain extent. However, the existing methods for real-time urban traffic flow prediction focus on improving the model prediction accuracy or efficiency while ignoring the training efficiency, which results in a prediction system that lacks the scalability to integrate real-time traffic flow into the training procedure. To conduct accurate and real-time urban traffic flow prediction while considering the latest historical data and avoiding time-consuming online retraining, herein, we propose a scalable system for Predicting short-term URban traffic flow in real-time based on license Plate recognition data (PURP). First, to ensure prediction accuracy, PURP constructs the spatio-temporal contexts of traffic flow prediction from License Plate Recognition (LPR) data as effective characteristics. Subsequently, to utilize the recent data without retraining the model online, PURP uses the nonparametric method k-Nearest Neighbor (namely KNN) as the prediction framework because the KNN can efficiently identify the top-k most similar spatio-temporal contexts and make predictions based on these contexts without time-consuming model retraining online. The experimental results show that PURP retains strong prediction efficiency as the prediction period increases.

Anti-interferon-γ autoantibodies (AIGAs) syndrome is susceptible to disseminated opportunistic infections due to increased AIGAs, but its clinical immunological characteristics remain unrecognized. We conducted a prospective cohort study between January 2021 and December 2023, recruiting patients with opportunistic infections who were categorized into AIGAs-positive and AIGAs-negative groups. Clinical immunological data and outcomes were documented. A subset of AIGAs-positive patients received glucocorticoid treatment, and its effectiveness was evaluated. A total of 238 patients were enrolled, with 135 AIGAs-positive and 103 AIGAs-negative patients. AIGAs-positive patients showed higher rates of multiple pathogen dissemination, shorter progression-free survival (PFS), and increased exacerbation frequency. They also showed elevated erythrocyte sedimentation rate (ESR), globulin (GLB), immunoglobulin (Ig)G, IgE, and IgG4 levels. Among the 70 AIGAs-positive patients monitored for at least six months, three subtypes were identified: high AIGAs titer with immune damage, high AIGAs titer without immune damage, and low AIGAs titer without immune damage. Of the 55 patients followed for 1 year, decreasing AIGAs titer and immune indices (GLB, IgG, IgE, IgG4) were observed. Among the 31 patients with high AIGAs titer and immune damage treated with low-dose glucocorticoids at the stable phase, reductions were observed in immune indices and AIGAs titer in 67.74% of cases. In summary, AIGAs-positive patients exhibit infectious and immunological characteristics. Elevated AIGAs, IgG, IgG4, and IgE indicate abnormal immune damages. AIGAs titer generally decrease over time. Stable-phase AIGAs-positive patients can be categorized into three subtypes, with those having high AIGAs titer and increased immune indices potentially benefitting from glucocorticoid treatment.

Throughout history, the influenza A virus has caused numerous devastating global pandemics. Macrophages, as pivotal innate immune cells, exhibit a wide range of immune functions characterized by distinct polarization states, reflecting their intricate heterogeneity. In this study, we employed the time-resolved single-cell sequencing technique coupled with metabolic RNA labelling to elucidate the dynamic transcriptional changes in distinct polarized states of bone marrow-derived macrophages (BMDMs) upon infection with the influenza A virus. Our approach not only captures the temporal dimension of transcriptional activity, which is lacking in conventional scRNA-seq methods, but also reveals that M2-polarized Arg1_macrophage cluster is the sole state supporting successful replication of influenza A virus. Furthermore, we identified distinct antigen presentation capabilities to CD4+ T and CD8+ T cells across diverse polarized states of macrophages. Notably, the M1 phenotype, exhibited by (BMDMs) and murine alveolar macrophages (AMs), demonstrated superior conventional and cross-presentation abilities for exogenous antigens, with a particular emphasis on cross-presentation capacity. Additionally, as CD8+ T cell differentiation progressed, M1 polarization exhibited an enhanced capacity for cross-presentation. All three phenotypes of BMDMs, including M1, demonstrated robust presentation to CD4+ regulatory T cells, while displaying limited ability to present to naive CD4+ T cells. These findings offer novel insights into the immunological regulatory mechanisms governing distinct polarized states of macrophages, particularly their roles in restricting the replication of influenza A virus and modulating antigen-specific T cell responses through innate immunity.

ABSTRACTObjectives This study aimed at revealing the underlying mechanisms of the loss and gain of ceftazidime-avibactam susceptibility in a non-carbapenemase-producing hypervirulent Klebsiella pneumoniae (hvKp).Methods Here we longitudinally recovered 3 non-carbapenemase-producing K1-ST23 hvKp strains at a one-month interval (KP29105, KP29499 and KP30086) from an elderly male. Antimicrobial susceptibility testing, whole genome sequencing, transcriptomic sequencing, gene cloning, plasmid conjugation, quantitative real-time PCR (qRT-PCR), and SDS-PAGE (sodium dodecyl sulfate-polyacrylamide gel electrophoresis) were conducted.Results Among the 3 hvKp strains, KP29105 was resistant to the third- and fourth-generation cephalosporins, KP29499 acquired resistance to both ceftazidime-avibactam and carbapenems, while KP30086 restored its susceptibility to ceftazidime-avibactam, imipenem and meropenem but retained low-level resistance to ertapenem. KP29105 and KP29499 carried plasmid-encoded genes blaCTX-M-15 and blaCTX-M-71, respectively, but KP30086 lost both. Cloning of gene blaCTX-M-71 and conjugation experiment of blaCTX-M-71-carrying plasmid showed that the transformant and transconjugant were susceptible to ceftazidime-avibactam but had a more than 8-fold increase in MICs. Supplementation with an outer membrane permeabilizer could reduce the MIC of ceftazidime-avibactam by 32 folds, indicating that porins play a key role in ceftazidime-avibactam resistance. The OmpK35 of the 3 isolates was not expressed, and the OmpK36 of KP29499 and KP30086 had a novel amino acid substitution (L359R). SDS-PAGE and qRT-PCR showed that the expression of porin OmpK36 of KP29499 and KP30086 was significantly down-regulated compared with KP29105.Conclusions In summary, we reported the rare ceftazidime-avibactam resistance in a non-carbapenemase-producing hvKp strain. Resistance plasmid carrying blaCTX-M-71 and mutated OmpK36 had a synergetic effect on the resistance.

ABSTRACTTuberculosis (TB) caused by Mycobacterium tuberculosis (Mtb) persistently kills nearly 1.5 million lives per year in the world, whereas the only licensed TB vaccine BCG exhibits unsatisfactory efficacy in adults. Taking BCG as a vehicle to express Mtb antigens is a promising way to enhance its efficacy against Mtb infection. In this study, the immune efficacy of recombination BCG (rBCG-ECD003) expressing specific antigens ESAT-6, CFP-10, and nDnaK was evaluated at different time points after immunizing BALB/c mice. The results revealed that rBCG-ECD003 induced multiple Th1 cytokine secretion including IFN-γ, TNF-α, IL-2, and IL-12 when compared to the parental BCG. Under the action of PPD or ECD003, rBCG-ECD003 immunization resulted in a significant increase in the proportion of IL-2+ and IFN-γ+IL-2+ CD4+T cells. Importantly, rBCG-ECD003 induced a stronger long-term humoral immune response without compromising the safety of the parental BCG vaccine. By means of the protective efficacy assay in vitro, rBCG-ECD003 showed a greater capacity to inhibit Mtb growth in the long term. Collectively, these features of rBCG-ECD003 indicate long-term protection and the promising effect of controlling Mtb infection.

Currently, cables are manually installed in aircraft manufacturing scenarios. The utilization of robots in cable assemblies can enhance efficiency and ensure quality, presenting great promise for the future. However, the assembly process must control the shape of the cables, which is a significant challenge for robots. On the one hand, cables have high degrees of freedom in space, making accurate modeling of cable dynamics for robotic arm manipulation difficult; on the other hand, cable deformation has uncertainty, and the applied forces cause simultaneous deformation and motion, which is difficult to control. To address these problems, this study proposes a cable‐shape control method based on graph neural networks and online visual shape‐servoing. The method first approximates cable dynamics with a graph neural network. Then, in practice, the learnt model is used alongside visual‐based shape‐servoing to generate optimal robotic arm movements, controlling the cable to attain the desired shape. In the experiments, precise control of three different cable types is realized, and an example of a completed cable assembly is shown.

Abstract Direct recycling is a novel approach to overcoming the drawbacks of conventional lithium‐ion battery (LIB) recycling processes and has gained considerable attention from the academic and industrial sectors in recent years. The primary objective of directly recycling LIBs is to efficiently recover and restore the active electrode materials and other components in the solid phase while retaining electrochemical performance. This technology's advantages over traditional pyrometallurgy and hydrometallurgy are cost‐effectiveness, energy efficiency, and sustainability, and it preserves the material structure and morphology and can shorten the overall recycling path. This review extensively discusses the advancements in the direct recycling of LIBs, including battery sorting, pretreatment processes, separation of cathode and anode materials, and regeneration and quality enhancement of electrode materials. It encompasses various approaches to successfully regenerate high‐value electrode materials and streamlining the recovery process without compromising their electrochemical properties. Furthermore, we highlight key challenges in direct recycling when scaled from lab to industries in four perspectives: (1) battery design, (2) disassembling, (3) electrode delamination, and (4) commercialization and sustainability. Based on these challenges and changing market trends, a few strategies are discussed to aid direct recycling efforts, such as binders, electrolyte selection, and alternative battery designs; and recent transitions and technological advancements in the battery industry are presented.

In the context of energy transition and carbon neutrality strategies, distributed renewable energy is widely emerging on the distribution side. However, due to the volatility and randomness characteristics of distributed renewable energy, its full absorption poses a huge challenge to the economy and stable operation of the power grid. Flexible resources on the demand side, represented by air conditioners and electric vehicles, can participate in grid dispatching, improving the economic efficiency and reliability of system operation. To this end, this paper proposes an intraday dispatch strategy for demand-side flexible resources based on two-stage optimization. First, based on a generalized energy storage model, the adjustable flexibility of demand-side flexible resources is modeled. Second, to hinder the uncertainties related with markets and demand-side flexible resources, the rolling optimization is adopted for the optimal bidding, thus enabling demand-side flexible resources to participate in the intraday market with low risks of profit losses. Third, based on the bidding decision, real-time dispatch optimization is carried out to cope with the system operation deviation caused by forecast errors. Then, in the real-time control stage, the dispatch instructions are decomposed to the control units to achieve power tracking. Finally, the proposed method is simulated and verified on a test system. The results show that by coordinating the operation of demand-side flexible resources through two-stage optimization, the uncertainties of renewable energy output, market price, etc. Can be effectively overcome, and the economics of system operation can be improved.

Background: Lymphopenia is common in respiratory viral infection. However, no studies elucidated the impact of prolonged lymphopenia on worse outcome in the way of quantitative risk. Methods: Adult patients with laboratory-confirmed respiratory virus infection (influenza, SARS-CoV-2, and other viruses) between January 1st, 2016, and February 1st, 2023 were enrolled in this retrospective cohort study. Serial data of laboratory examination during hospitalization were acquired. The primary outcome was in-hospital all-cause death, and all information was obtained from the electronic medical records system. Legendre orthogonal polynomials (LOP), restricted cubic splines, and multivariable logistic regression were performed. Results: Finally, 2388 inpatients were involved in this study, including 436 patients with influenza, 1397 with SARS-CoV-2, and 319 with other respiratory virus infections. After being adjusted for age, corticosteroids, chronic kidney disease, chronic respiratory disease, cardiovascular disease, lymphopenia on admission and length of hospital stay, prolonged lymphopenia was significantly associated with death in influenza (OR 7.20, 95 % CI 2.27–22.77, p = 0. 0008 for lasting for 3–7 days; OR 17.80, 95 % CI 5.21–60.82, p

Summary: The decidua plays a crucial role in providing structural and trophic support to the developing conceptus before placentation. Following embryo attachment, embryonic components intimately interact with the decidual tissue. While evidence indicates the participation of embryo-derived factors in crosstalk with the uterus, the extent of their impact on post-implantation decidual development requires further investigation. Here, we utilize transgenic mouse models to selectively eliminate primary trophoblast giant cells (pTGCs), the embryonic cells that interface with maternal tissue at the forefront. pTGC ablation impairs decidualization and compromises decidual interferon response and lipid metabolism. Mechanistically, pTGCs release factors such as interferon kappa (IFNK) to strengthen the decidual interferon response and lipoprotein lipase (LPL) to enhance lipid accumulation within the decidua, thereby promoting decidualization. This study presents genetic and metabolomic evidence reinforcing the proactive role of pTGC-derived factors in mobilizing maternal resources to strengthen decidualization, facilitating the normal progression of early pregnancy.

This study employs text data analysis of annual government work reports from various provinces in China for the years 2015–2020. It constructs an index measuring the extent of government attention allocated to digital economic development (DED) at the government level. Simultaneously, it establishes a DED index system to measure the level of DED. The aim is to examine the impact of government attention on the level of DED. The research findings demonstrate that government attention significantly promotes the development of the DED. For every one-unit increase in government attention to the DED, the level of DED increases by 0.043 points. This result remains robust even after conducting sensitivity tests using instrumental variable methods and variable substitution methods. In further investigation, a threshold effect model is applied, revealing a marginal increasing effect of government attention on the level of DED. As the level of DED rises, the marginal contribution of government attention increases from 0.048 to 0.112. Using a spatial durbin model, it is found that government attention exhibits a positive spatial spillover effect on the level of DED.

The pathological features of intraductal oncocytic papillary neoplasm (IOPN) of the bile duct include tumor cells that are rich in eosinophilic cytoplasm and arranged in papillary structures. Herein, we report a missed case of IOPN of the bile duct because of concomitant gallstones. A 70-year-old woman was hospitalized with upper abdominal discomfort. The primary diagnosis was choledocholithiasis following imaging examination. However, an unidentified mass was detected after the gallstones were removed. The mass appeared as many papillary protuberances surrounded by fish-egg-like mucosa when viewed by the choledochoscope and was confirmed as IOPN by pathological examination. The patient underwent choledochectomy and no recurrence was observed at the 6-month follow-up examination. In this report, peroral choledochoscopy demonstrated its advantages for the diagnosis of biliary diseases and acquisition of tissue specimens. Therefore, it may solve the challenge related to the lack of preoperative pathological evidence for bile duct tumors.

ObjectiveTo investigate the clinical characteristics and risk factors of patients with SARS-CoV-2 Omicron variant infection complicated with cardiovascular diseases.MethodsA retrospective analysis of general clinical data was conducted on patients with SARS-CoV-2 omicron infection complicated with hypertension, coronary heart disease, and heart failure admitted to one hospital in Guangdong Province from December 1, 2022, to February 28, 2023. Clinical symptoms, laboratory tests, imaging examinations, treatment, and clinical outcomes were collected. Multivariate logistic regression analysis was used to analyze the risk factors for mortality in patients with SARS-CoV-2 Omicron variant infection complicated with cardiovascular diseases. ROC curves were drawn to evaluate the predictive value of CRP, D-dimer, and CK-MB in predicting the risk of death.ResultsA total of 364 confirmed cases were included, divided into the asymptomatic group, mild to moderate group, and severe to critically ill group based on the symptoms of COVID-19. There were 216 males (59.34%) and 148 females (40.66%), with a median age of 75 years. The differences between the three groups in terms of sex and age were statistically significant (p

Developing new materials through traditional trial-and-error is time-consuming and costly due to the vast potential compositions to explore. Moreover, some desirable properties are mutually exclusive, presenting challenges for materials design. Herein, we employed an active learning strategy to address the strength-ductility trade-off in SAC105 lead-free solders. We developed two Gaussian regression models, one for strength and one for elongation representing ductility. The Gaussian Upper Confidence Boundary algorithm, a Bayesian optimization method, was used to balance exploitation and exploration by considering prediction uncertainty. The variance weight was designed to decay with adaptive iterations. The two models were linearly combined and the maximal combined model recommended alloys on the Pareto front for experiments. After just three iterations, a new 91.4Sn-1.0Ag-0.5Cu-1.5Bi-4.4In-0.2Ti low-silver SAC solder was discovered, exhibiting 73.94±5.05 MPa strength and 24.37±5.92% elongation, representing the best comprehensive mechanical properties. Weldability experiments also showed excellent performance. Based on Ab initio molecular dynamics, a precise machine learning potential revealed the alloying mechanism in Sn-In solid solutions with quantum accuracy in systems of over 103 atoms, closely matching experimental X-ray diffraction pattern. To facilitate materials informatics development, all active learning algorithms was made open-source in our designed framework, Bgolearn.

Abstract As the fifth most common cancer in the world, gastric cancer (GC) ranks as the third major cause of cancer-related death globally. Although surgical resection and chemotherapy still remains the mainstay of potentially curative treatment for GC, chemotherapy resistance and adverse side effects limit their clinical applications. Thus, further investigation of the mechanisms of carcinogenesis in GC and discovery of novel biomarkers is of great concern. We herein report that the elevated expression of GPR137 is correlated with GC. Overexpression of GPR137 potentiates human gastric cancer AGS cell malignancy, including proliferation, migration, invasion, colony formation and xenograft growth in nude mice in vivo, whereas knockout of GPR137 by CRISPR/Cas9 gene editing exerts the opposite effects. Mechanistically, GPR137 could bind to MST, the upstream kinases in Hippo pathway, which disrupts the association of MST with LATS, subsequently activating the transcriptional co-activators, YAP and TAZ, and thereby triggering the target transcription and the alterations in GC cell biological actions consequently. Therefore, our findings may provide with the evidence of developing a potentially novel treatment method with specific target for GC.

Flexible load can optimize the load curve, which is an important means to promote renewable energy consumption. The peculiarities of electricity, heat, cooling and gas loads are analyzed in this paper, considering the fuzzy degree of human perception for water temperature, and the characteristic model of hot water load is established. Considering the fuzzy degree of human perception of ambient temperature, the characteristic model of cooling load is established by using PMV and PPD index. Meanwhile, considering four combinations of cut load, translatable load, transferable load and alternative load, and considering the coupling relationship of composite parts, different response models of load are established respectively. With the minimum cost of the system, including operation and compensation costs as the objective function, the optimization scheduling model of the regional integrated energy system is established, and the Gurobi solver is used for simulation analysis to solve the optimal output and load response curve of each piece of equipment. The results show that the load curve can be optimized, the flexible regulation ability of the regional integrated energy system can be enhanced, the energy loss of the system can be reduced, and the wind power consumption ability of the system can be increased by considering the integrated demand response.