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Abstract Aluminium foam sandwich panels (AFSPs) have a high impact resistance and are suitable for a wide range of engineering applications. To improve corrosion resistance, this paper proposes an anti-corrosion sandwich panel with stainless steel as the upper sheet. Drop hammer impact tests were performed on a total of ten AFSPs to investigate their dynamic response and failure patterns. To assess the deformation performance of AFSPs, a laser displacement meter was used to obtain the bottom centre displacement. The effects of the impact energy and the thickness of each component of AFSPs on the peak impact force and deformation performance were studied. Test results showed that the thickness of each component had notable effects on the impactor and bottom displacements. In addition, the effect of the unit mass of the components in AFSPs on decreasing the bottom displacement was discussed. Compared to increasing the aluminium foam and lower sheet thicknesses, increasing the upper sheet thickness was more effective in decreasing the bottom displacement. A finite element model of AFSPs was developed to conduct parameter analysis, indicating that impactors with larger diameters resulted in higher peak forces and reduced deformation of AFSPs.

Abstract TET2 is a critical gene that regulates DNA methylation, encoding a dioxygenase protein that plays a vital role in the regulation of genomic methylation and other epigenetic modifications, as well as in hematopoiesis. Mutations in TET2 are present in 7%–28% of adult acute myeloid leukemia (AML) patients. Despite this, the precise mechanisms by which TET2 mutations contribute to malignant transformation and how these insights can be leveraged to enhance treatment strategies for AML patients with TET2 mutations remain unclear. In this review, we provide an overview of the functions of TET2, the effects of its mutations, its role in clonal hematopoiesis, and the possible mechanisms of leukemogenesis. Additionally, we explore the mutational landscape across different AML subtypes and present recent promising preclinical research findings.

Abstract All-polymer aqueous batteries, featuring electrodes and electrolytes made entirely from polymers, advance wearable electronics through their processing ease, inherent safety, and sustainability. Challenges persist with the instability of polymer electrode redox products in aqueous environments, which fail to achieve high performance in all-polymer aqueous batteries. Here, we report a polymer-aqueous electrolyte designed to stabilize polymer electrode redox products by modulating the solvation layers and forming a solid-electrolyte interphase. Polyaniline is selected as an example for its dual functionality as a cathode or anode working by p/n doping mechanisms. This approach pioneers the application of polyaniline as an anode and enhances the high-voltage stability of polyaniline cathode in an aqueous electrolyte. The resulting all-polymer aqueous sodium-ion battery with polyaniline as symmetric electrodes exhibits a high capacity of 139 mAh/g, energy density of 153 Wh/kg, and a retention of over 92% after 4800 cycles. Spectroscopic characterizations have elucidated the hydration structure, solid-electrolyte interphase, and dual-ion doping mechanism. Large-scale all-polymer flexible batteries are fabricated with excellent flexibility and recyclability, heralding a paradigmatic approach to sustainable, wearable energy storage.

Abstract Graphene is being increasingly used as an interesting transducer membrane in micro- and nanoelectromechanical systems (MEMS and NEMS, respectively) due to its atomical thickness, extremely high carrier mobility, high mechanical strength, and piezoresistive electromechanical transductions. NEMS devices based on graphene feature increased sensitivity, reduced size, and new functionalities. In this review, we discuss the merits of graphene as a functional material for MEMS and NEMS, the related properties of graphene, the transduction mechanisms of graphene MEMS and NEMS, typical transfer methods for integrating graphene with MEMS substrates, methods for fabricating suspended graphene, and graphene patterning and electrical contact. Consequently, we provide an overview of devices based on suspended and nonsuspended graphene structures. Finally, we discuss the potential and challenges of applications of graphene in MEMS and NEMS. Owing to its unique features, graphene is a promising material for emerging MEMS, NEMS, and sensor applications.

Neutrophils, which originate from the bone marrow and are characterized by a segmented nucleus and a brief lifespan, have a crucial role in the body’s defense against infections and acute inflammation. Recent research has uncovered the complex roles of neutrophils as regulators in tumorigenesis, during which neutrophils exhibit a dualistic nature that promotes or inhibits tumor progression. This adaptability is pivotal within the tumor microenvironment (TME). In this review, we provide a comprehensive characterization of neutrophil plasticity and heterogeneity, aiming to illuminate current research findings and discuss potential therapeutic avenues. By delineating the intricate interplay of neutrophils in the TME, this review further underscores the urgent need to understand the dual functions of neutrophils with particular emphasis on the anti-tumor effects to facilitate the development of effective therapeutic strategies against cancer.

Abstract Iron is an essential biomineral in the human body. Here, we describe a subset of iron-loaded cancer-associated fibroblasts, termed as FerroCAFs, that utilize iron to induce immunosuppression in prostate cancer and predict an unfavorable clinical outcome. FerroCAFs secrete myeloid cell-associated proteins, including CCL2, CSF1 and CXCL1, to recruit immunosuppressive myeloid cells. We report the presence of FerroCAFs in prostate cancer from both mice and human, as well as in human lung and ovarian cancers, and identify a conserved cell surface marker, the poliovirus receptor. Mechanistically, the accumulated iron in FerroCAFs is caused by Hmox1-mediated iron release from heme degradation. The intracellular iron activates the Kdm6b, an iron-dependent epigenetic enzyme, to induce an accessible chromatin state and transcription of myeloid cell-associated protein genes. Targeting the FerroCAFs by inhibiting the Hmox1/iron/Kdm6b signaling axis incurs anti-tumor immunity and tumor suppression. Collectively, we report an iron-loaded FerroCAF cluster that drives immunosuppression through an iron-dependent epigenetic reprogramming mechanism and reveal promising therapeutic targets to boost anti-tumor immunity.

Abstract With the development of artificial intelligence, the application of unmanned ground vehicles (UGV) in outdoor hazardous scenarios has received more attention. However, the terrains in these environments are often complex and undulating, which also pose higher challenges to the multi‐UGV path planning and task assignment (MUPPTA) optimization. To efficiently improve the multi‐UGV collaboration in 3D environments, a MUPPTA method is proposed based on double deep Q learning network (DDQN) and ant colony optimization (ACO) to jointly optimize the path planning and task assignment decisions of multiple UGVs. The authors first comprehensively consider the characteristics of the 3D environments, and model the MUPPTA problem as a combinatorial optimization problem. To tackle it, the original problem is decomposed into the multi‐UGV path planning sub‐problem and task assignment sub‐problem, and solve them separately. First, the path planning sub‐problem in the 3D environments is transformed into a Markov decision process (MDP) model, and a multi‐UGV path planning algorithm based on DDQN (MUPP‐DDQN) is proposed to obtain the optimal paths and actual path costs between tasks through extensive offline learning and training. Based on this, a multi‐UGV task assignment algorithm is further proposed based on ACO (MUTA‐ACO) to solve the task assignment sub‐problem and achieve the optimal task assignment solution. Simulation results show that the proposed method is more cost‐effective and time‐saving compared to other comparison algorithms.

Ejaculation is regulated by the central nervous system. However, the central pathophysiology of primary intravaginal anejaculation (PIAJ) is unclear. The present study aimed to examine the changes in regional brain activity and functional connectivity underlying PIAJ. A total of 20 PIAJ patients and 16 healthy controls (HCs) were enrolled from September 2020 to September 2022 in the Department of Andrology, Nanjing Drum Tower Hospital (Nanjing, China). Magnetic resonance imaging data were acquired from all participants and then were preprocessed. The measures of fractional amplitude of low-frequency fluctuation (fALFF), regional homogeneity (ReHo), and functional connectivity (FC) were calculated and compared between the groups. PIAJ patients showed increased fALFF values in the left precuneus compared with HCs. Additionally, PIAJ patients showed increased ReHo values in the left precuneus, left postcentral gyrus, left superior occipital gyrus, left calcarine fissure, right precuneus, and right middle temporal gyrus, and decreased ReHo values in the left inferior parietal gyrus, compared with HCs. Finally, brain regions with altered fALFF and ReHo values in PIAJ patients showed increased FC with widespread cortical regions, which included the frontal, parietal, temporal, and occipital regions, compared with HCs. In conclusion, increased regional brain activity in the parietal, temporal, and occipital regions, and increased FC between these brain regions, may be associated with PIAJ occurrence.

Diffuse midline glioma (DMG), H3K27-altered, is lethal pediatric-type, high-grade, localized to the midline region of the central nervous system. Effective treatment guidelines are absent, and clinical trials are preferred for primary or recurrent DMG patients. Recently, epigenetic agent-based immunotherapy has exhibited promising therapeutic effects in the clinical setting. However, the underlying mechanisms remain a mystery. The rare DMG tumor samples from biopsy or resection largely impede basic research, by using patient-derived tumor cells which better recapitulate the parental tumor's heterogeneity compared to established cell lines. As an epigenetic reprogramming disease, DMG exhibits a global loss of H3K27 trimethylation (H3K27me3) and a gain of H3K27 acetylation (H3K27ac). Analysis of multiple epigenetic marks is fundamentally necessary. However, traditional techniques cannot allow ultra-low input and high-throughput. Herein we have developed a new method called high-throughput in situ tagged immunoprecipitation sequencing (HiTIP-seq), which uses an integrated superhydrophobic microwell array technology (InSMART). We were able to perform 100 parallel assays from as few as 100 cells per microwell on a single chip. We applied the technology to profile epigenetic alterations of three-dimensional (3D) cell cultures derived from DMG patients. Our HiTIP-seq integrated with RNA sequencing (RNA-seq) analysis revealed that the combination of epigenetic agents (panobinostat and tazemetostat), reprogrammed histone modifications and drove transcriptome changes. Among them, Wnt inhibitory factor 1 (WIF1) has a gain of H3K27ac and a loss of H3K27me3, which leads to the upregulated expression. Altogether, HiTIP-seq is a versatile method for high-throughput analysis of histone modifications, suitable for both DMG research and studying rare 3D models.

Abstract To address the problem of dense crowd face detection in complex environments, this paper proposes a face detection model named Deep and Compact Face Detection (DCFD), which adopts an improved lightweight EfficientNetV2 network to replace the backbone network of RetinaFace. A large kernel attention mechanism is introduced to address the face detection task more accurately. The backbone network, an improved efficient channel attention (ECA) mechanism, is added to further improve the algorithm performance. The feature fusion module is an improved neural architecture search feature pyramid network (NAS-FPN) that significantly improves the face detection accuracy in different scenes. To balance the training process of positive and negative samples, we use the focus loss function to replace the traditional cross-entropy loss function. In different environments, the DCFD algorithm has shown efficient face detection performance. This algorithm provides not only a feasible and effective solution for solving the problem of face detection in dense groups but also an important basis for improving the accuracy of face detection models in practical applications.

There has been considerable discussion for more than 50 years of how scientists and practitioners in elite level sport can work collaboratively to ensure that evidence-based practice augments the sport performance and human development of elite amateur and professional athletes. The bridging of these two, often disparate competencies, science and practice, though considered at the conceptual level, continues to be scarcely evidenced within the international sport science community. Much of the research that frames the experiences of elite athletes and their consequent needs, is heavily influenced by scientists, often without direct reciprocity to bridge science, theory, and applied context. The knowledge influencing these interventions has derived from qualitative methods, such as semi-structured interviews, surveys, and focus groups, as well as a breadth of psychometric assessments. Though these approaches to gathering robust data are a necessary part of inquiry, they often produce decontextualized data collection strategies and results, which can lead to generalized, ineffective practices in sport performance environments. Within this submission, the first author cooperated with an international team of scientist-practitioners who are well versed in elite sport to delineate ecologically sound science-practice reciprocity. The authors consider the strengths and weaknesses of conventional qualitative research strategies in terms of their utility and the parlance of evidence into intervention and world-class performance. Two emerging, context driven approaches to inquiry are proposed; arts-based methods and an idiosyncratic approach to ethnography to encourage the reader toward an expanded selection of inquiry approaches from which better understanding and intervention can be generated. This contribution conclude with summary points to open further possibilities for innovative science to practice approaches.

Abstract The giant river prawn (Macrobrachium rosenbergii) is one of the most widely cultured crustacean species. In recent years, its aquaculture has faced challenges, including the degradation of germplasm resources and the emergence of viral diseases. Genomic information can be a valuable resource for developing molecular breeding programs for this important aquaculture species. Here we constructed a high-quality reference genome for M. rosenbergii by integrating Nanopore, Illumina, and high-throughput chromosome conformation capture (Hi-C) technologies. The final genome assembly is 3.18 Gb in size, with scaffold N50 and contig N50 of 62.73 Mb and 8.92 Mb, respectively. Approximately 98.6% of the assembled sequences were anchored into 59 pseudo-chromosomes. Benchmarking Universal Single-Copy Orthologs (BUSCO) benchmark of the genome assembly reached 94.5%. Repetitive sequences comprise 43.77% of the assembled genome, and 17,436 protein-coding genes were annotated. The high-quality genome of M. rosenbergii will empower molecular breeding efforts and provide invaluable resources for comparative genomic analysis of decapod species.

Abstract The shale’s multi-scale mechanical behaviors were investigated to understand the time-dependent damage characteristics induced by shale–fluid interaction. The test results indicate that, as fluid–shale interaction proceeds, the mechanical strength of shale has undergone a weakened to an enhanced process as interaction proceeds, and the size distribution of fragments tends to be more uniform, leading to a positive correlation between the mechanical strength and fractal dimension. Within 2 weeks of fluid–shale interaction show a decreasing trend for the fractal dimension of fragments in post-failure and cause less than 2 mm for the dominant size of fragments. The dominant size increases to greater than 30 mm when the fluid–shale interaction is over 2 weeks. Finally, the correlation dimension associated with ring counts of acoustic emission (AE) at each loading stage is determined in terms of the G-P algorithm to predict the damage degree of shale.

Abstract Human pose estimation is an important task in computer vision, which can provide key point detection of human body and obtain bone information. At present, human pose estimation is mainly utilized for detection of large targets, and there is no solution for detection of small targets. This paper proposes a multi-channel spatial information feature based human pose (MCSF-Pose) estimation algorithm to address the issue of medium and small targets inaccurate detection of human key points in scenarios involving occlusion and multiple poses. The MCSF-Pose network is a bottom-up regression network. Firstly, an UP-Focus module is designed to expand the feature information while reducing parameter computation during the up-sampling process. Then, the channel segmentation strategy is adopted to cut the features, and the feature information of multiple dimensions is retained through different convolutional groups, which reduces the parameter lightweight network model and makes up for the loss of the feature information associated with the depth of the network. Finally, the three-layer PANet structure is designed to reduce the complexity of the model. With the aid of the structure, it also to improve the detection accuracy and anti-interference ability of human key points. The experimental results indicate that the proposed algorithm outperforms YOLO-Pose and other human pose estimation algorithms on COCO2017 and MPII human pose datasets.

Abstract To develop and validate a diagnostic prediction model based on blood parameters for predicting the pertussis in children. A retrospective study of 477 children with suspected pertussis at Zigong First People’s Hospital was performed between January 2020 and December 2021. The patients were randomly divided into training cohort and validation cohort. Stepwise regression and R software was performed to develop and validate the model. Stepwise regression analysis showed that white blood cell (WBC), hematocrit (HCT), lymphocyte (LYMPH), C-reactive protein (CRP) and platelet distribution width to mean platelet volume ratio (PDW-MPV-R) were found to be independent factors associated with pertussis. The model containing WBC, CRP and PDW-MPV-R had the best performance. The area under curve (ROC, 0.77 for the training cohort and 0.80 for the validation cohort) of the model indicated satisfactory discriminative ability. The sensitivity and specificity of the model were 72.1% and 72.6% in training cohort and 74% and 72.1%, respectively, in validation cohort. Based on the ROC analysis, calibration plots, and decision curve analysis, we concluded that the model exhibited excellent performance. A model based on blood parameters is sufficiently accurate to predict the probability of pertussis in children, and may provide some reference for clinical decisions.

Abstract Background Neuroendocrine prostate cancer (NEPC), a lethal subset of prostate cancer (PCa), is characterized by loss of AR signaling and resistance to AR-targeted therapy. While it is well reported that second-generation AR blockers induce neuroendocrine (NE) trans-differentiation of castration-resistant prostate cancer (CRPC) to promote the occurrence of NEPC, and pluripotent transcription factors might be potential regulators, the underlying molecular mechanisms remain unclear. Methods We analyzed the data from public databsets to screen candidate genes and then focused on SOX4, a regulator of NE trans-differentiation. The expression changes of SOX4 and its relationship with tumor progression were validated in clinical tumor tissues. We evaluated malignant characteristics related to NEPC in prostate cancer cell lines with stable overexpression or knockdown of SOX4 in vitro. Tumor xenografts were analyzed after inoculating the relevant cell lines into nude mice. RNA-seq, ATAC-seq, non-targeted metabolomics analysis, as well as molecular and biochemical assays were carried out to determine the mechanism. Results We screened public datasets and identified that expression of SOX4 was significantly elevated in NEPC. Overexpressing SOX4 in C4-2B cells increased cell proliferation and migration, upregulated the expression of NE marker genes, and inhibited AR expression. Consistently, inhibition of SOX4 expression in DU-145 and PC-3 cells reduced the above malignant phenotypes and repressed the expression of NE marker genes. For the in vivo assay, we found that knockdown of SOX4 inhibited tumor growth of subcutaneous xenografts in castrated nude mice which were concomitantly treated with enzalutamide (ENZ). Mechanically, we identified that one of the key enzymes in gluconeogenesis, PCK2, was a novel target of SOX4. The activation of carbohydrate metabolism reprogramming by SOX4 could promote NE trans-differentiation via the SOX4/PCK2 pathway. Conclusions Our findings reveal that SOX4 promotes NE trans-differentiation both in vitro and in vivo via directly enhancing PCK2 activity to activate carbohydrate metabolism reprogramming. The SOX4/PCK2 pathway and its downstream changes might be novel targets for blocking NE trans-differentiation.

Abstract Hydrogels are extensively explored as biomaterials for tissue scaffolds, and their controlled fabrication has been the subject of wide investigation. However, the tedious mechanical property adjusting process through formula control hindered their application for diverse tissue scaffolds. To overcome this limitation, we proposed a two-step process to realize simple adjustment of mechanical modulus over a broad range, by combining digital light processing (DLP) and post-processing steps. UV-curable hydrogels (polyacrylamide-alginate) are 3D printed via DLP, with the ability to create complex 3D patterns. Subsequent post-processing with Fe3+ ions bath induces secondary crosslinking of hydrogel scaffolds, tuning the modulus as required through soaking in solutions with different Fe3+ concentrations. This innovative two-step process offers high-precision (10 μm) and broad modulus adjusting capability (15.8–345 kPa), covering a broad range of tissues in the human body. As a practical demonstration, hydrogel scaffolds with tissue-mimicking patterns were printed for cultivating cardiac tissue and vascular scaffolds, which can effectively support tissue growth and induce tissue morphologies.

Abstract Background The advances in deep learning-based pathological image analysis have invoked tremendous insights into cancer prognostication. Still, lack of interpretability remains a significant barrier to clinical application. Methods We established an integrative prognostic neural network for intrahepatic cholangiocarcinoma (iCCA), towards a comprehensive evaluation of both architectural and fine-grained information from whole-slide images. Then, leveraging on multi-modal data, we conducted extensive interrogative approaches to the models, to extract and visualize the morphological features that most correlated with clinical outcome and underlying molecular alterations. Results The models were developed and optimized on 373 iCCA patients from our center and demonstrated consistent accuracy and robustness on both internal (n = 213) and external (n = 168) cohorts. The occlusion sensitivity map revealed that the distribution of tertiary lymphoid structures, the geometric traits of the invasive margin, the relative composition of tumor parenchyma and stroma, the extent of necrosis, the presence of the disseminated foci, and the tumor-adjacent micro-vessels were the determining architectural features that impacted on prognosis. Quantifiable morphological vector extracted by CellProfiler demonstrated that tumor nuclei from high-risk patients exhibited significant larger size, more distorted shape, with less prominent nuclear envelope and textural contrast. The multi-omics data (n = 187) further revealed key molecular alterations left morphological imprints that could be attended by the network, including glycolysis, hypoxia, apical junction, mTORC1 signaling, and immune infiltration. Conclusions We proposed an interpretable deep-learning framework to gain insights into the biological behavior of iCCA. Most of the significant morphological prognosticators perceived by the network are comprehensible to human minds. Graphical Abstract

Abstract Strongly correlated materials respond sensitively to external perturbations such as strain, pressure, and doping. In the recently discovered superconducting infinite-layer nickelates, the superconducting transition temperature can be enhanced via only ~ 1% compressive strain-tuning with the root of such enhancement still being elusive. Using resonant inelastic x-ray scattering (RIXS), we investigate the magnetic excitations in infinite-layer PrNiO2 thin films grown on two different substrates, namely SrTiO3 (STO) and (LaAlO3)0.3(Sr2TaAlO6)0.7 (LSAT) enforcing different strain on the nickelates films. The magnon bandwidth of PrNiO2 shows only marginal response to strain-tuning, in sharp contrast to the enhancement of the superconducting transition temperature T c in the doped superconducting samples. These results suggest the bandwidth of spin excitations of the parent compounds is similar under strain while T c in the doped ones is not, and thus provide important empirics for the understanding of superconductivity in infinite-layer nickelates.

Maximizing the development of renewable energy plays a critical role in mitigating the climate crisis. Marginal land provides space for the development of biomass energy; however, it remains unclear how the amount and spatial distribution of marginal land that is suitable for energy crop development will change in the future. Here, we project energy marginal land changes in China following the shared socioeconomic pathway (SSP) and/or representative concentration path (RCP). We provide datasets of marginal land, agriculturally suitable land, and potentially suitable for energy crops under historical scenarios and six future scenarios (i.e. SSP1–1.9, SSP1–2.6, SSP4–3.4, SSP2–4.5, SSP4–6.0, and SSP3–7.0) for the period 2020–2100, with a spatial resolution of 5 km. Under the six scenarios, from 2020–2100, the area of suitable marginal land ranged from 1.90–16.28 (Jatropha curcas L.) to 37.37–73.97 (Panicum virgatum L.) (×104 km2), depending on the choice of energy crops and climate scenario. Based on the growing suitability of eight important bioenergy crops—Ricinus communis L., Saccharum officinarum L., Pistacia chinensis Bunge, Panicum virgatum L., Jatropha curcas L., Miscanthus giganteus J., Manihot esculenta Crantz, and Sorghum bicolor Moench—our dataset can be used to identify suitable locations for specific energy crops. This new synthetic dataset could support the development of multiscenario-based solutions related to carbon neutrality, ecosystem services, and energy transition.

Aqueous Zn batteries are promising candidates for grid-scale renewable energy storage. Foil electrodes have been widely investigated and applied as anode materials for aqueous Zn batteries, however, they suffer from limited surface area and severe interfacial issues including metallic dendrites and corrosion side reactions, limiting the depth of discharge (DOD) of the foil electrode materials. Herein, a low-temperature replacement reaction is utilized to in-situ construct a three-dimensional (3D) corrosion-resistant interface for deeply rechargeable Zn foil electrodes. Specifically, the deliberate low-temperature environment controlled the replacement rate between polycrystalline Zn metal and oxalic acid, producing a Zn foil electrode with distinct 3D corrosion-resistant interface (3DCI-Zn), which differed from conventional two-dimensional (2D) protective structure and showed an order of magnitude higher surface area. Consequently, the 3DCI-Zn electrode exhibited dendrite-free and anti-corrosion properties, and achieved stable plating/stripping performance for 1000 ​h at 10 ​mA ​cm−2 and 10 mAh cm−2 with a remarkable DOD of 79 ​%. After pairing with a MnO2 cathode with a high areal capacity of 4.2 mAh cm−2, the pouch cells delivered 168 ​Wh L−1 and a capacity retention of 89.7 % after 100 cycles with a low negative/positive (N/P) ratio of 3:1.

Continuous tobacco monocropping has caused soil degradation and yield reduction in China. Intercropping, as a specific and efficient cropping pattern, is highly associated with the enhancement of soil quality and land-use efficiency. Tobacco (Nicotiana tabacum L.)- Isatis (Isatis tinctoria L.) intercropping can significantly alleviate pests and diseases, and improve soil potential and fertility in tobacco fields. In this study, comparative analysis of three different tobacco-Isatis intercropping (B2, B3, B4) and tobacco monocropping (B1) on the soil nutrients, enzyme activities, and microbial community were conducted. B2, B3, and B4 importantly increased the contents of organic matter, available potassium, and available phosphorus content of the soil by 17.38%, 7.76%, and 2.78%, respectively. Moreover, B2 enhanced the activities of sucrase, urease, and catalase of soil by 2.35 times, 3.16 times, and 4.47 times, respectively, and B3 enhanced the activities of sucrase, urease, and catalase of soil by 2.74 times, 3.22 times, and 3.11 times, respectively. The intercropping pattern also optimized the structure of the soil microbial community. The relative abundances of Acidobacteriota, Chloroflexi, Gemmatimonadota, Planctomycetota, Nitrospirota, and Verrucomicrobiota in B3 and B4 were higher than those in B1. Positive links in soil bacterial correlation networks accounted for 47%, and soil bacteria formed a highly interactive and complex network. And compared with the B1, Ascomycota and Basidiomycota were lower abundance in B2 and B4, Ascomycota were lower abundance in B3 and Mortierellomycota were lower abundance in B2 and B3. Compared with monocropping, the chemical composition of tobacco leaves was harmoniously improved and the total production value of tobacco fields was significantly higher. The content of reducing sugar, total sugar, nicotine, potassium, and two-sugar ratio of leaves were increased after intercropping. The proportion of top-grade tobacco leaves after roasting in B2, B3, and B4 treatments were increased by 8.19%, 16.74%, and 27.32%, respectively. The study constructs insights into microbial community interactions at in tobacco/Isatis intercropping systems, and may facilitate the further development of tobacco/Isatis intercropping systems.

China’s agricultural production suffers significant constraints due to low water productivity (WP) and partial factor productivity for nitrogen (PFPN). The pivotal solution to enhance maize yield, WP, and PFPN is through optimizing field management practices. However, previous studies primarily focused on the effects of individual or coupled field management practices on maize yield, WP, or PFPN in an area or land mass, so it is necessary to conduct a comprehensive quantitative analysis of various field management practices on maize yield, WP, and PFPN at the national scale. In this study, we compiled 286 studies encompassing 6959 pairs of experimental data spanning from 1990 to 2023. Meta-analysis was conducted to observe the variations in maize yield, WP, and PFPN across diverse field management practices (straw returning, nitrogen fertilizer application, irrigation practice, and tillage practice) on a national scale. The results showed that nitrogen fertilizer application (215 kg N ha−1) was the most effective in enhancing maize yield and WP by 68.1 % and 54.8 %, respectively. Additionally, irrigation had the most substantial impact on PFPN, enhancing 16.8 %. Straw mulching, application of slow and controlled release fertilizers, drip irrigation, and subsoiling were identified as the most effective practices in increasing maize yield, WP, and PFPN by Random forest model. Maize straw returning could reduce nitrogen fertilizer application by 20 kg ha−1, while increasing WP and PFPN by 4.2 % and 11.6 %, respectively. Moreover, straw returning could reduce water consumption by 23–60 mm, while increasing WP and PFPN by 2.9 % and 6.8 %, respectively. These findings can provide a reference for the formulation of comprehensive management strategies for sustainable maize production in China and globally.

The autogenous self-sealing model has been researched in previous work, which could help to characterize the self-sealing process with crystalline products. The model outcome was presented in the form of leakage water flow, which demonstrates the self-sealing capacity or the recovery of watertightness. While in the research area of cement-based material self-sealing, the expansive agent cannot be neglectable, for example the superabsorbent polymer (SAP). Especially for the building components exposed to free water, an efficient water flow blockage after cracking is crucial to ensure stable service. Hence in this study, the self-sealing process of a granular expansive agent inside the crack of cement-based material was simulated. The model outputs were compared with experimental results to verify the reliability. Additionally, the autogenous self-sealing model was incorporated into this model to simulate the “crystallization-expansion” synergetic self-sealing. The contribution of crystalline product and expanded EA to water flow blockage were compared during the crystallizing process. Overall, this model is of great use to evaluate the role of expansive agent on water flow blockage after the cement-based material cracking in hydraulic engineering or engineering components exposed to water.

Summary: Cardiovascular diseases (CVDs) and metabolic disorders (MDs) have surfaced as formidable challenges to global health, significantly imperiling human well-being. Recently, microneedles (MNs) have garnered substantial interest within the realms of CVD and MD research. Offering a departure from conventional diagnostic and therapeutic methodologies, MNs present a non-invasive, safe, and user-friendly modality for both monitoring and treatment, thereby marking substantial strides and attaining pivotal achievements in this avant-garde domain, while also unfurling promising avenues for future inquiry. This thorough review encapsulates the latest developments in employing MNs for both the surveillance and management of CVDs and MDs. Initially, it succinctly outlines the foundational principles and approaches of MNs in disease surveillance and therapy. Subsequently, it delves into the pioneering utilizations of MNs in the surveillance and management of CVDs and MDs. Ultimately, this discourse synthesizes and concludes the primary findings of this investigation, additionally prognosticating on the trajectory of MN technology.

Abstract Background Gallbladder cancer (GBC) is the most common and lethal malignancy of the biliary tract that lacks effective therapy. In many GBC cases, infiltration into adjacent organs or distant metastasis happened long before the diagnosis, especially the direct liver invasion, which is the most common and unfavorable way of spreading. Methods Single-cell RNA sequencing (scRNA-seq), spatial transcriptomics (ST), proteomics, and multiplexed immunohistochemistry (mIHC) were performed on GBC across multiple tumor stages to characterize the tumor microenvironment (TME), focusing specifically on the preferential enrichment of neutrophils in GBC liver invasion (GBC-LI). Results Multi-model Analysis reveals the immunosuppressive TME of GBC-LI that was characterized by the enrichment of neutrophils at the invasive front. We identified the context-dependent transcriptional states of neutrophils, with the Tumor-Modifying state being associated with oxidized low-density lipoprotein (oxLDL) metabolism. In vitro assays showed that the direct cell-cell contact between GBC cells and neutrophils led to the drastic increase in oxLDL uptake of neutrophils, which was primarily mediated by the elevated OLR1 on neutrophils. The oxLDL-absorbing neutrophils displayed a higher potential to promote tumor invasion while demonstrating lower cancer cytotoxicity. Finally, we identified a neutrophil-promoting niche at the invasive front of GBC-LI that constituted of KRT17+ GBC cells, neutrophils, and surrounding fibroblasts, which may help cultivate the oxLDL-absorbing neutrophils. Conclusions Our study reveals the existence of a subset of pro-tumoral neutrophils with a unique ability to absorb oxLDL via OLR1, a phenomenon induced through cell-cell contact with KRT17+ GBC cells in GBC-LI.

Abstract The superconducting gap symmetry is crucial in understanding the underlying superconductivity mechanism. Angle-resolved photoemission spectroscopy (ARPES) has played a key role in determining the gap symmetry in unconventional superconductors. However, it has been considered so far that ARPES can only measure the magnitude of the superconducting gap but not its phase; the phase has to be detected by other phase-sensitive techniques. Here we propose a method to directly detect the superconducting gap sign by ARPES. This method is successfully validated in a cuprate superconductor Bi2Sr2CaCu2O8+δ with a well-known d-wave gap symmetry. When two bands have a strong interband interaction, the resulted electronic structures in the superconducting state are sensitive to the relative gap sign between the two bands. Our present work provides an approach to detect the gap sign and can be applied to various superconductors, particularly those with multiple orbitals like the iron-based superconductors.

Abstract Background Taraxacum kok-saghyz Rodin (TKS) is a highly potential source of natural rubber (NR) due to its wide range of suitable planting areas, strong adaptability, and suitability for mechanized planting and harvesting. However, current methods for detecting NR content are relatively cumbersome, necessitating the development of a rapid detection model. This study used near-infrared spectroscopy technology to establish a rapid detection model for NR content in TKS root segments and powder samples. The K445 strain at different growth stages within a year and 129 TKS samples hybridized with dandelion were used to obtain their near-infrared spectral data. The rubber content in the root of the samples was detected using the alkaline boiling method. The Monte Carlo sampling method (MCS) was used to filter abnormal data from the root segments of TKS and powder samples, respectively. The SPXY algorithm was used to divide the training set and validation set in a 3:1 ratio. The original spectrum was preprocessed using moving window smoothing (MWS), standard normalized variate (SNV), multiplicative scatter correction (MSC), and first derivative (FD) algorithms. The competitive adaptive reweighted sampling (CARS) algorithm and the corresponding chemical characteristic bands of NR were used to screen the bands. Partial least squares (PLS), random forest (RF), Lightweight gradient augmentation machine (LightGBM), and convolutional neural network (CNN) algorithms were employed to establish a model using the optimal spectral processing method for three different bands: full band, CARS algorithm, and chemical characteristic bands corresponding to NR. The model with the best predictive performance for high rubber content intervals (rubber content > 15%) was identified. Result The results indicated that the optimal rubber content prediction models for TKS root segments and powder samples were MWS–FD CASR–RF and MWS–FD chemical characteristic band RF, respectively. Their respective $${\text{R}}_{{\text{P}}}^{2}$$ R P 2 , RMSEP, and RPDP values were 0.951, 0.979, 1.814, 1.133, 4.498, and 6.845. In the high rubber content range, the model based on the LightGBM algorithm had the best prediction performance, with the RMSEP of the root segments and powder samples being 0.752 and 0.918, respectively. Conclusions This research indicates that dried TKS root powder samples are more appropriate for constructing a rubber content prediction model than segmented samples, and the predictive capability of root powder samples is superior to that of root segmented samples. Especially in the elevated rubber content range, the model formulated using the LightGBM algorithm has superior predictive performance, which could offer a theoretical basis for the rapid detection technology of TKS content in the future.

Abstract Background Neuroendocrine prostate cancer (NEPC) is a lethal subset of prostate cancer which is characterized by neuroendocrine differentiation and loss of androgen receptor (AR) signaling. Growing evidence reveals that cell lineage plasticity is crucial in the failure of NEPC therapies. Although studies suggest the involvement of the neural transcription factor PAX6 in drug resistance, its specific role in NEPC remains unclear. Methods The expression of PAX6 in NEPC was identified via bioinformatics and immunohistochemistry. CCK8 assay, colony formation assay, tumorsphere formation assay and apoptosis assay were used to illustrate the key role of PAX6 in the progression of in vitro. ChIP and Dual-luciferase reporter assays were conducted to confirm the binding sequences of AR in the promoter region of PAX6, as well as the binding sequences of PAX6 in the promoter regions of STAT5A and MET. For in vivo validation, the xenograft model representing NEPC subtype underwent pathological analysis to verify the significant role of PAX6 in disease progression. Complementary diagnoses were established through public clinical datasets and transcriptome sequencing of specific cell lines. ATAC-seq was used to detect the chromatin accessibility of specific cell lines. Results PAX6 expression was significantly elevated in NEPC and negatively regulated by AR signaling. Activation of PAX6 in non-NEPC cells led to NE trans-differentiation, while knock-down of PAX6 in NEPC cells inhibited the development and progression of NEPC. Importantly, loss of AR resulted in an enhanced expression of PAX6, which reprogramed the lineage plasticity of prostate cancer cells to develop NE phenotypes through the MET/STAT5A signaling pathway. Through ATAC-seq, we found that a high expression level of PAX6 elicited enhanced chromatin accessibility, mainly through attenuation of H4K20me3, which typically causes chromatin silence in cancer cells. Conclusion This study reveals a novel neural transcription factor PAX6 could drive NEPC progression and suggest that it might serve as a potential therapeutic target for the management of NEPC.

Abstract Background Genome-scale metabolic models (GEMs) serve as effective tools for understanding cellular phenotypes and predicting engineering targets in the development of industrial strain. Enzyme-constrained genome-scale metabolic models (ecGEMs) have emerged as a valuable advancement, providing more accurate predictions and unveiling new engineering targets compared to models lacking enzyme constraints. In 2022, a stoichiometric GEM, iDL1450, was reconstructed for the industrially significant fungus Myceliophthora thermophila. To enhance the GEM’s performance, an ecGEM was developed for M. thermophila in this study. Results Initially, the model iDL1450 underwent refinement and updates, resulting in a new version named iYW1475. These updates included adjustments to biomass components, correction of gene-protein-reaction (GPR) rules, and a consensus on metabolites. Subsequently, the first ecGEM for M. thermophila was constructed using machine learning-based k cat data predicted by TurNuP within the ECMpy framework. During the construction, three versions of ecGEMs were developed based on three distinct k cat collection methods, namely AutoPACMEN, DLKcat and TurNuP. After comparison, the ecGEM constructed using TurNuP-predicted k cat values performed better in several aspects and was selected as the definitive version of ecGEM for M. thermophila (ecMTM). Comparing ecMTM to iYW1475, the solution space was reduced and the growth simulation results more closely resembled realistic cellular phenotypes. Metabolic adjustment simulated by ecMTM revealed a trade-off between biomass yield and enzyme usage efficiency at varying glucose uptake rates. Notably, hierarchical utilization of five carbon sources derived from plant biomass hydrolysis was accurately captured and explained by ecMTM. Furthermore, based on enzyme cost considerations, ecMTM successfully predicted reported targets for metabolic engineering modification and introduced some new potential targets for chemicals produced in M. thermophila. Conclusions In this study, the incorporation of enzyme constraint to iYW1475 not only improved prediction accuracy but also broadened the model’s applicability. This research demonstrates the effectiveness of integrating of machine learning-based k cat data in the construction of ecGEMs especially in situations where there is limited measured enzyme kinetic parameters for a specific organism.

As widely used energy-absorbing protective materials, the application of aluminum foam sandwich (AFS) panels remains constrained by the inherently low mechanical properties of the foam core. The incorporation of copper-coated carbon fibers (Cf) has proven to be effective in improving the mechanical properties of aluminum foam. Yet, the understanding of its foaming process and microstructure is still limited. In this work, AFS and Cf/AFS were fabricated by the packing rolling powder metallurgy method. The foaming behavior of AFS and Cf/AFS during elevated temperatures was in situ observed using synchrotron radiation X-ray imaging technology to investigate the effect of Cf on bubble nucleation, growth, and foam stability. Furthermore, the macroscopic pore size distribution, microscopic microstructure, and compressive mechanical properties of AFS and Cf/AFS were analyzed. The results showed that the existence of Cf greatly increases the nucleation rate, improves the foaming stability, and prevents the formation of localized abnormally large bubbles during the early nucleation and growth process. Meanwhile, Cf/AFS exhibited finer pore diameters and fewer pore defects than AFS. The distribution of Cf with excellent wettability along the pore wall prevented liquid film rupture and reduced coalescence. The compression experiment indicated that, in comparison to AFS, the compressive strength and energy absorption capacity of Cf/AFS have increased by approximately 40.6% and 84.8%, respectively.

To investigate the hot deformation characteristics, workability, and interfacial microstructure of the titanium/steel bimetallic composite, hot compression simulations were carried out on the TA1/SUS430 composite within the temperatures of 750 °C–1050 °C, accompanied by strain rates spanning from 0.01 s⁻1–10 s⁻1. The hyperbolic sine Arrhenius constitutive equation and back-propagation artificial neural network (BP-ANN) model for flow stresses of this bimetallic composite were developed. 2D and 3D hot processing maps were established to study processability. The results revealed the calculated average activation energy (Q) was 277.9671 kJ/mol. The BP-ANN model demonstrated higher prediction accuracy than the Arrhenius model, with a correlation coefficient (R2) of 0.99947. As the strain increases, the area of the unstable region in the processing map expands, and the failure mode is characterized by the formation of microcracks at the bonded interface. Interfacial exfoliation manifested under elevated temperature and high strain rate deformation conditions. High power dissipation (η) values were observed within the processing parameters of 875°C–950 °C/0.01 s−1-0.03 s−1. The bimetal exhibited superior deformation coordination at low strain rates. TiC predominantly constituted the interface products at lower temperatures, while at higher temperatures, phases containing both Fe and Ti dominated. Furthermore, the deformed steel stratum manifested a pronounced cubic orientation //CD and a less dominant recrystallized γ orientation. This γ texture attenuated progressively with increased deformation temperatures, while the strain rate has less impact.

Slipform construction is widely used for building deep-buried vertical and inclined shaft concrete linings due to its efficiency and cost advantages. The adhesion of the interface during demoulding is crucial for the efficiency and quality of slip form construction. In this paper, a novel approach is proposed to reduce the adhesion between concrete and formwork based on electroosmotic technology. A self-designed concrete electroosmotic demoulding device was developed to simulate the electroosmotic slip-form construction of the shaft lining. The variations in parameters such as current and permeability during electroosmosis were analyzed, and the impact of electroosmotic parameters on the adhesion and demoulding quality of concrete was investigated. The results indicate that the electroosmotic method can significantly reduce the adhesion. Concrete demoulding defects are significantly reduced and smoother after electroosmotic treatment. This study provides a scientific basis and technical support for optimizing concrete construction demoulding technology.

The aim of the present study was to address the effect of high hydrostatic pressure (HHP) on bioactive compounds and antioxidant activity of Nelumbo nucifera (Lotus) bee pollen (LBP). The total phenolic contents (TPC) and free amino acids were determined and flavonoid composition was identified by UPLC-Triple-TOF-MS. Five analytical methods including DPPH, ABTS, reducing power, FRAP, and silver nanoparticles antioxidant capacity were used for the antioxidant activity analysis. The results revealed a significant increase in the TPC and free amino acid compositions after HHP treatment. The DPPH, ABTS, reducing power, FRAP, and AgNPAC of the extracted fractions were augmented by over 13.94, 2.9, 2.68, 85, and 2.6 times, respectively. PCA analysis showed a strong correlation between TPC, some distinct flavonoids, and antioxidant activities. These results indicated that HHP enhances the antioxidant activity of LBP via increase in amino acids, TPC, and some flavonoids such as Licoagrone, Kuwanon K, Cyanidin 3-rutinoside, etc.

Ice cementation and ice-substrate adfreeze force are the primary contributors to the high bearing capacity of pile foundations in cold regions and the stability of frozen walls in areas subjected to artificial freezing. Given the significant temperature sensitivity of ice’s shear rheology, engineering structures in ice or ice-rich soils continue to deform even under constant external loads. A thorough understanding of shear creep and the long-term adfreeze force at the ice-substrate interface is essential for predicting the continuous deformation of these structures. However, research into the shear creep behavior at frozen interfaces has historically been constrained by the precision of temperature control in experimental settings and the complexity of load paths in shear testing devices. In this study, a temperature- and stress-control device for interface shear creep is assembled firstly, and multilevel loading-unloading creep tests on steel pipes embedded in layered frozen ice were conducted. Through the decoupling of deformation progression, the viscoelastic and viscoplastic shear behaviors at the steel-ice interface under various temperatures and shear stresses were characterized, the principle of sustainable interfacial shear creep along with its underlying physical mechanism were proposed. Subsequently, with the aid of a modified nonlinear Burger model, various interfacial shear creep parameters were derived. Results reveal that the interfacial generalized shear modulus continuously improves but with a gradually weakening degree until a point of accelerating creep is reached. Additionally, the long-term adfreeze force is found to be less than half of the short-term strength, which significantly decreases as the temperature approaches the water phase transition zone. Interestingly, the stress exponent associated with the interfacial steady creep rate is considerably smaller than that predicted by Glen’s law. This research provides a theoretical basis instrumental in the engineering design in cold regions and those structures employing artificial freezing techniques.

We propose an acoustic-mechanical metasurface with simultaneous sound absorption and vibration reduction functionalities. This acoustic-mechanical feature results from a nonlocal coupling effect in the designed composite meta-structure. A nonlocal meta-mesh is designed at the acoustic-mechanical interface and embedded in the metasurface array to connect adjacent unit cells, which can make a nonlocal coupling effect. This effect can improve the acoustic property, which strengthens sound absorption by 58.6 %, and the mechanical interface strengthens vibration acceleration reduction by 88.45 %. The resulting nonlocal acoustic-mechanical metasurface achieves an average absorption coefficient of higher than 0.9 within 267–638 Hz, and a vibration level difference of 18.75 dB within 490–920 Hz. The sample has an ultra-thin thickness of 8.5 cm (λ/14 for the lowest working frequency) and is lightweight (305.1 g), whose weight reduction reaches 42.8 % compared with conventional designs with similar functionalities. Our proposed design strategy will be enlightened for multi-functional acoustic-mechanical coupling meta-device.

Increasing farmers’ grain profits is crucial for enhancing the sustainability of grain production and ensuring food security. As a widely applied agricultural management means at present, agricultural productive services are of great significance to study whether they can help increase farmers’ grain profits. This paper uses the micro-farmer data from the 2020 China Rural Revitalization Survey (CRRS). It employs an endogenous switching regression model and causal mediation analysis methods, which can address endogenous issues, to examine the impact of agricultural productive services on farmers’ grain profits and their underlying mechanisms. The results show: (1) Agricultural productive services significantly increase farmers’ grain profits and this conclusion is still robust after the robustness test. (2) The mechanism analysis indicates that agricultural productive services increase farmers’ grain profits through three pathways: yield enhancement, cost reduction, and efficiency improvement. (3) The heterogeneity analysis shows that agricultural productive services have a greater impact on increasing grain profits for farmers with lower grain profits, smaller operating scales, and lower degrees of farmland fragmentation. Our findings suggest that increasing support for agricultural productive services, fully leveraging the radiative driving role of service providers, and offering farmers various forms of productive services will be key measures to enhance farmers’ grain profits, promote sustainable grain production, and ensure food security.