Search

Abstract Revealing the influence of confining pressure on the propagation and formation mechanism of rock cracks under particle impact is significant to deep rock excavation. In this study, the three-dimensional fracture reconstruction of the rock after particle impact was carried out by CT scanning, and the stress and crack field evolution of the rock under particle impact were analyzed by PFC2D discrete element numerical simulation. The results demonstrate that after particles impact, a fracture zone and intergranular main crack propagation zone are formed in the rock. The shear stress and tensile stress caused by compressive stress are the main reasons for the formation of the fracture zone, while the formation of the intergranular main crack propagation zone is mainly due to tangential derived tensile stress. The confining pressure induces prestress between rock particles such that the derived tensile stress needs to overcome the initial compressive stress between the particles to form tensile fractures. And the increase in the confining pressure leads to increases in the proportion of shear cracks and friction effects between rock particles, resulting in an increase in energy consumption for the same number of cracks. From a macroscopic perspective, the confining pressure can effectively inhibit the generation of cracks.

Abstract The Hoek–Brown (H–B) criterion has found widespread application in numerous rock engineering projects. However, its efficacy is compromised by an underestimation of rock strength due to its neglect of the influence of the intermediate principal stress ( $$\sigma_{2}$$ σ 2 ). Experimental evidence underscores the significant impact of $$\sigma_{2}$$ σ 2 . Consequently, there exists an imperative to formulate a three-dimensional (3D) criterion. In this study, a new deviatoric function with two additional parameters ( $$k$$ k and $$A$$ A ) is developed firstly, which ensure compliance with the prerequisites of smoothness and convexity. In addition, the parameters $$k$$ k and $$A$$ A are bonded with the weakening effect of the Lode angle ( $$\theta_{\sigma }$$ θ σ ) and the strengthening effect of the mean stress ( $$\sigma_{m}$$ σ m ), respectively. Then a new 3D strength criterion for rocks is proposed by combining this new deviatoric function and the triaxial compression meridian function of the original H–B criterion. Four distinct sets of test data encompassing various rock types are employed to validate the proposed criterion. The results demonstrate that the proposed criterion adeptly captures the strength characteristics of the four rock types, providing a good depiction of failure surfaces within the 3D principal stress space. Comparative analyses involve the utilization of several existing 3D H–B criteria for strength predictions. The proposed criterion exhibits superior fitting performance for all the selected rocks.

The H9N2 subtype of avian influenza virus (AIV) is widely prevalent in poultry and wild birds globally, and has become the predominant subtype circulating in poultry in China. The H9N2 AIV can directly or indirectly (by serving as a “donor virus”) infect humans, posing a significant threat to public health. Currently, there is a lack of in-depth research on the prevalence of H9N2 viruses in Shanxi Province, central China. In this study, we isolated 14 H9N2 AIVs from October 2020 to April 2022 in Shanxi Province, and genetic analysis revealed that these viruses belonged to 7 different genotypes. Our study on animals revealed that the H9N2 strains we identified displayed high transmission efficiency among chicken populations, and exhibited diverse replication abilities within these birds. These viruses could replicate efficiently in the lungs of mice, with one strain also demonstrating the capacity to reproduce in organs like the brain and kidneys. At the cellular level, the replication ability of different H9N2 strains was evaluated using plaque formation assays and multi-step growth curve assays, revealing significant differences in the replication and proliferation efficiency of the various H9N2 viruses at the cellular level. The antigenicity analysis suggested that these isolates could be classified into 2 separate antigenic clusters. Our research provides crucial data to help understand the prevalence and biological characteristics of H9N2 AIVs in central China. It also highlights the necessity of enhancing the surveillance of H9N2 AIVs.

Brassica oleracea has been developed into many important crops, including cabbage, kale, cauliflower, broccoli and so on. The genome and gene annotation of cabbage (cultivar JZS), a representative morphotype of B. oleracea, has been widely used as a common reference in biological research. Although its genome assembly has been updated twice, the current gene annotation still lacks information on untranslated regions (UTRs) and alternative splicing (AS). Here, we constructed a high-quality gene annotation (JZSv3) using a full-length transcriptome acquired by nanopore sequencing, yielding a total of 59 452 genes and 75 684 transcripts. Additionally, we re-analyzed the previously reported transcriptome data related to the development of different tissues and cold response using JZSv3 as a reference, and found that 3843 out of 11 908 differentially expressed genes (DEGs) underwent AS during the development of different tissues and 309 out of 903 cold-related genes underwent AS in response to cold stress. Meanwhile, we also identified many AS genes, including BolLHCB5 and BolHSP70, that displayed distinct expression patterns within variant transcripts of the same gene, highlighting the importance of JZSv3 as a pivotal reference for AS analysis. Overall, JZSv3 provides a valuable resource for exploring gene function, especially for obtaining a deeper understanding of AS regulation mechanisms.

ABSTRACT: α-Lactalbumin (α-lac), a natural food-sourced protein, exhibits high biocompatibility as delivery systems for small bioactive molecules or RNA. However, their potential clinical application as a delivery system is greatly limited due to the lack of targeting to desired tissues, such as tumors. Here, a delivery system/nanocarrier of nanotube (NT) was fabricated by the self-assembly of peptides hydrolyzed from α-lac. Among the loading of anti-tumor agents of doxorubicin (Dox) and siRNA, NTs were conjugated with the tLyp-1 peptide to specifically target the neuropilin 1 receptor, which exists on the membrane of MDA-MB-231 cancer cells. The micromorphology of NTs was not affected during the processes of loading and targeting modification. Additionally, no significant changes in the size and zeta potential of the tLyp-1/NTs/Dox/siRNA nanocarrier were observed when stored in phosphate buffered saline for 7 days, indicating outstanding stability. Moreover, both the cellular uptake efficiency and tumor accumulation effects of NTs on MDA-MB-231 breast cancer cells were significantly improved after modification with tLyp-1. The relative viability of MDA-MB-231 cells was decreased by 70.1% in vitro after treatment with tLyp-1/NTs/Dox/siRNA (5 μg/mL Dox). Finally, a synergistic anticancer effect of Dox and siRNA co-loaded in tLyp-1/NTs was achieved in the anticancer treatment of MDA-MB-231 tumor-bearing mice. These findings indicate that food-sourced protein α‑lac nanocarriers could be used for the co-delivery of bioactive molecules and RNA, achieving synergistic and efficient therapeutic effects.

Regulating macrophage phenotypes to reconcile the conflict between bacterial suppression and tissue regeneration is ideal for treating infectious skin wounds. Here, an injectable immunoregulatory hydrogel (SrmE20) that sequentially drives macrophage phenotypic polarization (M0 to M1, then to M2) was constructed by integrating anti-inflammatory components and proinflammatory solvents. In vitro experiments demonstrated that the proinflammatory solvent ethanol stabilized the hydrogel structure, maintained the phenolic hydroxyl group activity, and achieved macrophages' proinflammatory transition (M0 to M1) to enhance antibacterial effects. With ethanol depletion, the hydrogel's cations and phenolic hydroxyl groups synergistically regulated macrophages' anti-inflammatory transition (M1 to M2) to initiate regeneration. In the anti-contraction full-thickness wound model with infection, this hydrogel effectively eliminated bacteria and even achieved anti-inflammatory M2 macrophage accumulation at three days post-surgery, accelerated angiogenesis and collagen deposition. By sequentially driving macrophage phenotypic polarization, this injectable immunoregulatory hydrogel will bring new guidance for the care and treatment of infected wounds.

The development of passive NOx adsorbers with cost-benefit and high NOx storage capacity remains an on-going challenge to after-treatment technologies at lower temperatures associated with cold-start NOx emissions. Herein, Cs1Mg3Al catalyst prepared by sol–gel method was cyclic tested in NOx storage under 5 vol% water. At 100 °C, the NOx storage capacity (1219 μmol g−1) was much higher than that of Pt/BaO/Al2O3 (610 μmol g−1). This provided new insights for non-noble metal catalysts in low-temperature passive NOx adsorption. The addition of Cs improved the mobility of oxygen species and thus improved the NOx storage capacity. The XRD, XPS, IR spectra and in situ DRIFTs with NH3 probe showed an interaction between CsOx and AlOx sites via oxygen species formed on Cs1Mg3Al catalyst. The improved mobility of oxygen species inferred from O2-TPD was consistent with high NOx storage capacity related to enhanced formation of nitrate and additional nitrite species by NOx oxidation. Moreover, the addition of Mg might improve the stability of Cs1Mg3Al by stabilizing surface active oxygen species in cyclic experiments.

Abstract Background Mediterranean diet rich in polyphenolic compounds holds great promise to prevent and alleviate multiple sclerosis (MS), a central nervous system autoimmune disease associated with gut microbiome dysbiosis. Health-promoting effects of natural polyphenols with low bioavailability could be attributed to gut microbiota reconstruction. However, its underlying mechanism of action remains elusive, resulting in rare therapies have proposed for polyphenol-targeted modulation of gut microbiota for the treatment of MS. Results We found that oral ellagic acid (EA), a natural polyphenol rich in the Mediterranean diet, effectively halted the progression of experimental autoimmune encephalomyelitis (EAE), the animal model of MS, via regulating a microbiota-metabolites-immunity axis. EA remodeled the gut microbiome composition and particularly increased the relative abundances of short-chain fatty acids -producing bacteria like Alloprevotella. Propionate (C3) was most significantly up-regulated by EA, and integrative modeling revealed a strong negative correlation between Alloprevotella or C3 and the pathological symptoms of EAE. Gut microbiota depletion negated the alleviating effects of EA on EAE, whereas oral administration of Alloprevotella rava mimicked the beneficial effects of EA on EAE. Moreover, EA directly promoted Alloprevotella rava (DSM 22548) growth and C3 production in vitro. The cell-free supernatants of Alloprevotella rava co-culture with EA suppressed Th17 differentiation by modulating acetylation in cell models. C3 can alleviate EAE development, and the mechanism may be through inhibiting HDAC activity and up-regulating acetylation thereby reducing inflammatory cytokines secreted by pathogenic Th17 cells. Conclusions Our study identifies EA as a novel and potentially effective prebiotic for improving MS and other autoimmune diseases via the microbiota-metabolites-immunity axis. Video Abstract

Abstract Background The incidence of rabies exposure is high and increasing in China, leading to an urgent demand of rabies post-exposure prophylaxis (PEP) clinics for the injured. However, the spatial accessibility and inequality of rabies-exposed patients to rabies PEP clinics is less known in China. Methods Based on rabies exposure data, PEP clinic data, and resident travel origin-destination (OD) matrix data in Guangzhou City, China, we first described the incidence of rabies exposure in Guangzhou from 2020 to 2022. Then, the Gaussian two-step floating catchment area method (2SFCA) was used to analyze the spatial accessibility of rabies-exposed patients to rabies PEP clinics in Guangzhou, and the Gini coefficient and Moran’s I statistics were utilized to evaluate the inequality and clustering of accessibility scores. Results From 2020 to 2022, a total of 524,160 cases of rabies exposure were reported in Guangzhou, and the incidence showed a significant increasing trend, with an average annual incidence of 932.0/100,000. Spatial accessibility analysis revealed that the overall spatial accessibility scores for three scenarios (threshold of driving duration [d0] = 30 min, 45 min, and 60 min) were 0.30 (95% CI: 0.07, 0.87), 0.28 (95% CI: 0.11, 0.53) and 0.28 (95% CI: 0.14, 0.44), respectively. Conghua, Huangpu, Zengcheng and Nansha districts had the higher accessibility scores, while Haizhu, Liwan, and Yuexiu districts exhibited lower spatial accessibility scores. The Gini coefficient and Moran’s I statistics showed that there were certain inequality and clustering in the accessibility to rabies PEP clinics in Guangzhou. Conclusions This study clarifies the heterogeneity of spatial accessibility to rabies PEP clinics, and provide valuable insights for resource allocation to achieve the WHO target of zero human dog-mediated rabies deaths by 2030.

Abstract During extensive periods without rain, known as dry-downs, decreasing soil moisture (SM) induces plant water stress at the point when it limits evapotranspiration, defining a critical SM threshold (θcrit). Better quantification of θcrit is needed for improving future projections of climate and water resources, food production, and ecosystem vulnerability. Here, we combine systematic satellite observations of the diurnal amplitude of land surface temperature (dLST) and SM during dry-downs, corroborated by in-situ data from flux towers, to generate the observation-based global map of θcrit. We find an average global θcrit of 0.19 m3/m3, varying from 0.12 m3/m3 in arid ecosystems to 0.26 m3/m3 in humid ecosystems. θcrit simulated by Earth System Models is overestimated in dry areas and underestimated in wet areas. The global observed pattern of θcrit reflects plant adaptation to soil available water and atmospheric demand. Using explainable machine learning, we show that aridity index, leaf area and soil texture are the most influential drivers. Moreover, we show that the annual fraction of days with water stress, when SM stays below θcrit, has increased in the past four decades. Our results have important implications for understanding the inception of water stress in models and identifying SM tipping points.

Abstract The emergence of convolutional neural network (CNN) and transformer has recently facilitated significant advances in image super-resolution (SR) tasks. However, these networks commonly construct complex structures, having huge model parameters and high computational costs, to boost reconstruction performance. In addition, they do not consider the structural prior well, which is not conducive to high-quality image reconstruction. In this work, we devise a lightweight interactive feature inference network (IFIN), complementing the strengths of CNN and Transformer, for effective image SR reconstruction. Specifically, the interactive feature aggregation module (IFAM), implemented by structure-aware attention block (SAAB), Swin Transformer block (SWTB), and enhanced spatial adaptive block (ESAB), serves as the network backbone, progressively extracts more dedicated features to facilitate the reconstruction of high-frequency details in the image. SAAB adaptively recalibrates local salient structural information, and SWTB effectively captures rich global information. Further, ESAB synergetically complements local and global priors to ensure the consistent fusion of diverse features, achieving high-quality reconstruction of images. Comprehensive experiments reveal that our proposed networks attain state-of-the-art reconstruction accuracy on benchmark datasets while maintaining low computational demands. Our code and results are available at: https://github.com/wwaannggllii/IFIN .

Abstract The fluorescent light-up aptamer RhoBAST, which binds and activates the fluorophore–quencher conjugate tetramethylrhodamine-dinitroaniline with high affinity, super high brightness, remarkable photostability, and fast exchange kinetics, exhibits excellent performance in super-resolution RNA imaging. Here we determine the co-crystal structure of RhoBAST in complex with tetramethylrhodamine-dinitroaniline to elucidate the molecular basis for ligand binding and fluorescence activation. The structure exhibits an asymmetric “A”-like architecture for RhoBAST with a semi-open binding pocket harboring the xanthene of tetramethylrhodamine at the tip, while the dinitroaniline quencher stacks over the phenyl of tetramethylrhodamine instead of being fully released. Molecular dynamics simulations show highly heterogeneous conformational ensembles with the contact-but-unstacked fluorophore–quencher conformation for both free and bound tetramethylrhodamine-dinitroaniline being predominant. The simulations also show that, upon RNA binding, the fraction of xanthene-dinitroaniline stacked conformation significantly decreases in free tetramethylrhodamine-dinitroaniline. This highlights the importance of releasing dinitroaniline from xanthene tetramethylrhodamine to unquench the RhoBAST–tetramethylrhodamine-dinitroaniline complex. Using SAXS and ITC, we characterized the magnesium dependency of the folding and binding mode of RhoBAST in solution and indicated its strong structural robustness. The structures and binding modes of relevant fluorescent light-up aptamers are compared, providing mechanistic insights for rational design and optimization of this important fluorescent light-up aptamer-ligand system.

Objective The Cruise Home Port Station on Chongqing Rail Transit Line 9 is constructed from in-situ expansion of the existing interval tunnel (including a connecting passage). Due to the complex geological conditions, the initial stress field of surrounding rock, and the structure of the existing interval tunnel, analysis and research of the complex mechanical behavior of the interval tunnel during construction is essential to ensure engineering safety. Method After outlining the overview of the excavation project, a three-dimensional finite element numerical model, utilizing an anisotropic jointed rock mass elastoplastic model, is established. The model geometric features, geological characteristics, structural features, and procedural characteristics are further determined. Three measurement lines (connecting passage centerline, left-line large-mileage interval tunnel centerline, right-line small-mileage interval tunnel centerline) are selected for analyzing land subsidence above these three lines and deformation around the left-line and right-line tunnels. Simulation values are compared with measured values to study the deformation characteristics of surrounding rock and structure during the construction process of interval tunnel expansion and excavation. Result & Conclusion The comparison of model-simulated and construction-measured results indicate that the established finite element model is reasonable. The connecting passage expansion and excavation construction leads to a significant increase in convergence deformation around the tunnel, with the maximum deformation occurring at the intersection of the existing connecting passage and the construction main tunnel. Therefore, backfilling with spoil inside the connecting passage is recommended to ensure the safety and smooth implementation of tunnel excavation construction.

Abstract Background Preeclampsia is a pregnancy-specific disease leading to maternal and perinatal morbidity. Hypertension and inflammation are the main characteristics of preeclampsia. Many factors can lead to hypertension and inflammation, including gut microbiota which plays an important role in hypertension and inflammation in humans. However, alterations to the gut microbiome and fecal metabolome, and their relationships in severe preeclampsia are not well known. This study aims to identify biomarkers significantly associated with severe preeclampsia and provide a knowledge base for treatments regulating the gut microbiome. Methods In this study, fecal samples were collected from individuals with severe preeclampsia and healthy controls for shotgun metagenomic sequencing to evaluate changes in gut microbiota composition. Quantitative polymerase chain reaction analysis was used to validate the reliability of our shotgun metagenomic sequencing results. Additionally, untargeted metabolomics analysis was performed to measure fecal metabolome concentrations. Results We identified several Lactobacillaceae that were significantly enriched in the gut of healthy controls, including Limosilactobacillus fermentum, the key biomarker distinguishing severe preeclampsia from healthy controls. Limosilactobacillus fermentum was significantly associated with shifts in KEGG Orthology (KO) genes and KEGG pathways of the gut microbiome in severe preeclampsia, such as flagellar assembly. Untargeted fecal metabolome analysis found that severe preeclampsia had higher concentrations of Phenylpropanoate and Agmatine. Increased concentrations of Phenylpropanoate and Agmatine were associated with the abundance of Limosilactobacillus fermentum. Furthermore, all metabolites with higher abundances in healthy controls were enriched in the arginine and proline metabolism pathway. Conclusion Our research indicates that changes in metabolites, possibly due to the gut microbe Limosilactobacillus fermentum, can contribute to the development of severe preeclampsia. This study provides insights into the interaction between gut microbiome and fecal metabolites and offers a basis for improving severe preeclampsia by modulating the gut microbiome.

Abstract Releasing pre-strained two-dimensional nanomembranes to assemble on-chip three-dimensional devices is crucial for upcoming advanced electronic and optoelectronic applications. However, the release process is affected by many unclear factors, hindering the transition from laboratory to industrial applications. Here, we propose a quasistatic multilevel finite element modeling to assemble three-dimensional structures from two-dimensional nanomembranes and offer verification results by various bilayer nanomembranes. Take Si/Cr nanomembrane as an example, we confirm that the three-dimensional structural formation is governed by both the minimum energy state and the geometric constraints imposed by the edges of the sacrificial layer. Large-scale, high-yield fabrication of three-dimensional structures is achieved, and two distinct three-dimensional structures are assembled from the same precursor. Six types of three-dimensional Si/Cr photodetectors are then prepared to resolve the incident angle of light with a deep neural network model, opening up possibilities for the design and manufacturing methods of More-than-Moore-era devices.

Abstract Tuberculosis (TB) poses significant challenges due to its high transmissibility within populations and intrinsic resistance to treatment, rendering it a formidable respiratory disease with a substantial susceptibility burden. This study was designed to identify new potential therapeutic targets for TB and establish a diagnostic model. mRNA expression data for TB were from GEO database, followed by conducting differential expression analysis. The top 50 genes with differential expression were subjected to GO and KEGG enrichment analyses. To establish a PPI network, the STRING database was utilized, and hub genes were identified utilizing five algorithms (EPC, MCC, MNC, Radiality, and Stress) within the cytoHubba plugin of Cytoscape software. Furthermore, a hub gene co-expression network was constructed using the GeneMANIA database. Consistency clustering was performed on hub genes, and ssGSEA was utilized to analyze the extent of immune infiltration in different subgroups. LASSO analysis was employed to construct a diagnostic model, and ROC curves were used for validation. Through the analysis of GEO data, a total of 159 genes were identified as differentially expressed. Further, GO and KEGG enrichment analyses revealed that these genes were mainly enriched in viral defense, symbiotic defense, and innate immune response-related pathways. Hub genes, including DDX58, IFIT2, IFIH1, RSAD2, IFI44L, OAS2, OAS1, OASL, IFIT1, IFIT3, MX1, STAT1, and ISG15, were identified using cytoHubba analysis of the PPI network. The GeneMANIA analysis unmasked that the co-expression rate of hub genes was 81.55%, and the physical interaction rate was 12.27%. Consistency clustering divided TB patients into two subgroups, and ssGSEA revealed different degrees of immune infiltration in different subgroups. LASSO analysis identified IFIT1, IFIT2, IFIT3, IFIH1, RSAD2, OAS1, OAS2, and STAT1 as eight immune-related key genes, and a diagnostic model was constructed. The ROC curve demonstrated that the model exhibited excellent diagnostic performance. DDX58, IFIT2, IFIH1, RSAD2, IFI44L, OAS2, OAS1, OASL, IFIT1, IFIT3, MX1, STAT1, and ISG15 were hub genes in TB, and the diagnostic model based on eight immune-related key genes exhibited good diagnostic performance.

Abstract Background Glioblastoma multiforme (GBM) is a highly aggressive brain tumor with a poor prognosis. Current treatment options are limited and often ineffective. CAR T cell therapy has shown success in treating hematologic malignancies, and there is growing interest in its potential application in solid tumors, including GBM. However, current CAR T therapy lacks clinical efficacy against GBM due to tumor-related resistance mechanisms and CAR T cell deficiencies. Therefore, there is a need to improve CAR T cell therapy efficacy in GBM. Methods We conducted large-scale CRISPR interference (CRISPRi) screens in GBM cell line U87 MG cells co-cultured with B7-H3 targeting CAR T cells to identify genetic modifiers that can enhance CAR T cell-mediated tumor killing. Flow cytometry-based tumor killing assay and CAR T cell activation assay were performed to validate screening hits. Bioinformatic analyses on bulk and single-cell RNA sequencing data and the TCGA database were employed to elucidate the mechanism underlying enhanced CAR T efficacy upon knocking down the selected screening hits in U87 MG cells. Results We established B7-H3 as a targetable antigen for CAR T therapy in GBM. Through large-scale CRISPRi screening, we discovered genetic modifiers in GBM cells, including ARPC4, PI4KA, ATP6V1A, UBA1, and NDUFV1, that regulated the efficacy of CAR T cell-mediated tumor killing. Furthermore, we discovered that TNFSF15 was upregulated in both ARPC4 and NDUFV1 knockdown GBM cells and revealed an immunostimulatory role of TNFSF15 in modulating tumor-CAR T interaction to enhance CAR T cell efficacy. Conclusions Our study highlights the power of CRISPR-based genetic screening in investigating tumor-CAR T interaction and identifies potential druggable targets in tumor cells that confer resistance to CAR T cell killing. Furthermore, we devised targeted strategies that synergize with CAR T therapy against GBM. These findings shed light on the development of novel combinatorial strategies for effective immunotherapy of GBM and other solid tumors.

TTFields is a novel FDA-approved technology utilized for treating glioblastoma multiforme (GBM) within the brain. Presently, the effectiveness of therapy is evaluated through MRI imaging at random two-month intervals. Electrical impedance is an important and effective parameter for reflecting changes in tissue properties. In TTFields treatment for brain tumors, electrodes attached to the scalp deliver electric field energy to the tumor region. We hypothesize that these electrodes can also serve as sensors to detect impedance changes caused by tumor alterations in real time, thus continuously assessing the effectiveness of the treatment. In this work, we propose and scrutinize this hypothesis by conducting an in silico study to confirm the potential feasibility of the proposed concept. Our results indicate that the impedance amplitude change measured between opposing TTFields electrode arrays utilizing voltage and frequency of 50 V and 200 kHz (typical TTFields treatment parameters), has enough resolution (> 1mm) and Signal-to-Noise Ratio (> 40 dB) to evaluate tumor size change in the head. The impedance detection technique may be a significant augmentation to TTFields cancer treatment, enabling the continuous evaluation of safety and efficacy throughout the procedure.

Understanding the impacts of drought on plant photosynthetic phenology and physiology is essential for accurately predicting annual gross primary productivity (GPP) and global carbon cycles. While droughts in different seasons can have different effects on plant growth and photosynthesis, a comprehensive understanding of how plant photosynthetic phenology and physiology respond to different seasons’ droughts and their temporal changes is lacking. Here, we comprehensively evaluated the drought sensitivities of plant photosynthetic phenology and physiology and their temporal trends in the past two decades, using the start/end of the photosynthetic seasons (SOS/EOS) and peak GPP (GPPmax) derived from FLUXNET ground observations since the 1990s and remote-sensing data (2001–2020) over the globe. Our results show that spring droughts leads to delayed SOS in arid ecosystems and advanced SOS in humid ecosystems. In contrast, droughts in summer and autumn generally advance EOS. In addition, spring droughts decrease GPPmax in arid regions but increase it in humid regions, whereas summer droughts lead to significant GPPmax reductions. More importantly, we observed significant increases in the drought sensitivity of SOS, EOS, and GPPmax over the last two decades, which is driven by long-term decreases in background soil moisture and increases in atmospheric water deficit under climate change. Furthermore, these increasing trends were projected to persist in the 21st century under Shared Socioeconomic Pathways 8.5 and 4.0. Overall, our findings underscore the critical role of drought timing in shaping ecosystem responses and highlight the growing vulnerability of ecosystem phenology and physiology to drought, which may restrict the increases in terrestrial carbon uptake under warming.

Solar-induced chlorophyll fluorescence (SIF) is strongly correlated with gross primary productivity (GPP). Satellite-observed canopy SIF (SIFobs) captures only a part of the total leaf-emitted SIF (SIFtotal); therefore, SIFobs may hinder the interpretation of the physiological mechanism for GPP estimation. Furthermore, there are still significant discrepancies in the estimated SIFobs escape ratio (fesc) from the canopy to the leaf level with current methods. Here, we selected several vegetation canopy variables and downscaled SIFobs based on the Soil Canopy Observation, Photochemistry and Energy fluxes (SCOPE) model from the canopy to the leaf level using machine learning (ML) algorithms and then applied our method to the TROPOspheric Monitoring Instrument (TROPOMI) near-infrared (NIR) SIFobs. The results showed that simulating the fesc with SIFobs, TROPOMI NIR reflectance, and the fraction of photosynthetically active radiation (FPAR) avoided the effects of different sun-sensor geometry conditions introduced by different sensors and was more suitable for satellite-observed SIFobs downscaling. Our downscaled SIFtotal also correlated well with the flux site GPP in areas with sparse vegetation types. SIFtotal better reflected the photosynthetic differences among vegetation types and showed an enhanced relationship with absorbed photosynthetically active radiation (APAR) compared with SIFobs. We provide an efficient canopy-to-leaf SIFobs downscaling method improved SIFtotal and GPP estimation, and our results also demonstrated the potential for using SIFobs as vegetation information in sparse coverage areas.

Abstract Ecosystem‐scale photosynthetic efficiency (EPE) is proposed as an effective indicator to quantify gross primary productivity (GPP), but how the coupling between EPE and GPP varies as vegetation resilience decreases has not been evaluated. Here, we quantified forest resilience with optimized Bayesian models. With the use of multisource satellite and modeling data, our study revealed that forests on the Loess Plateau and in the Qinba Mountains in China are experiencing rapid resilience loss and are already facing mortality warnings after 2010. Reductions in resilience also drove the marked decoupling of GPP from EPE. Notably, the decline in resilience was accompanied by a decrease in EPE in about 74% of the forests while GPP increased. The mechanism underlying this decoupling could be attributed to enhanced atmospheric water demand and soil water constraints. The dynamic relationships found here could help to improve forest mortality models and enhance photosynthesis‐based GPP evaluation.

Abstract Background Beta 2‐microglobulin (β2‐MG) is a component of the class I major histocompatibility complex (MHCI) and has recently been reported to be involved in type 2 diabetes mellitus (T2DM) and cardiovascular disease. However, the association of β2‐MG with left ventricular hypertrophy (LVH) in T2DM patients remains unknown. This study aims to investigate the correlation between serum β2‐MG and LVH in T2DM patients. Methods The retrospective analysis included 4602 eligible T2DM patients, divided into LVH and non‐LVH groups based on echocardiography results. Serum β2‐MG levels were measured, and participants were categorized into four groups (Q1–Q4) by their serum β2‐MG quartile. The relationship of serum β2‐MG level with LVH was evaluated using logistic regression, restricted cubic spline (RCS), subgroup analysis, and machine learning. Results The prevalence of LVH in T2DM patients was 31.12%. Each standard deviation increase in serum β2‐MG level corresponded to a 1.17‐fold increase in the prevalence of LVH [OR = 1.17, (95% CI: 1.05–1.31); p = 0.006]. When considering β2‐MG as a categorical variable (quartile), Q3 [OR = 1.36, (95% CI: 1.09–1.69); p = 0.007] and Q4 [OR = 1.77, (95% CI: 1.36–2.31); p

Background: Since 1990 s, China has witnessed a widespread transition to clean cooking fuels, presenting an opportunity to investigate whether household fuel transition could mitigate obesity risk and reconcile inconsistencies in the literature regarding the association between cooking fuels and obesity. Methods: The China Health and Nutrition Survey (CHNS) is a prospective cohort study covering 12 provinces of China (1989–2015). Participants were classified into persistent cleaner fuel users, fuel transitioners, and persistent polluting fuel users according to self-reported primary cooking fuels. Obesity and central obesity were defined as BMI ≥ 28.0 kg/m2 and waist circumference ≥ 90 cm in men and ≥ 85 cm in women according to Chinese criteria. Findings: Among 13,032 participants, 3657 (28.06 %) were persistent cleaner fuel users; 5264 (40.39 %) transitioned from using polluting fuels to cleaner fuels after the baseline survey; and 4111 (31.55 %) were persistent polluting fuel users. During the period of follow-up of 9.0 ± 6.8 years, 1248 (9.58 %) participants were classified into the obesity category, and 4703 (36.09 %) into the central obesity category. Persistent polluting fuel users had a significantly higher risk of developing obesity (hazard ratio [HR]: 1.45, 95 %CI: 1.22–1.72) and central obesity (HR: 1.32, 95 %CI: 1.21–1.44), compared to persistent cleaner fuel users. Persistent polluting fuel use was positively associated with developing obesity in women (HR: 1.64, 95 %CI: 1.30–2.06), but not in men. Subgroup analyses showed higher HR of persistent polluting fuel use among individuals aged 18–44 years (HR: 2.04, 95 %CI: 1.62–2.56). In contrast, the transitioners did not exhibit a significantly different risk of developing obesity (HR: 0.94, 95 %CI: 0.80–1.10) compared to persistent cleaner fuel users, which was consistent across different sex, age and urbanicity. Similar trends were observed for developing central obesity. Interpretation: Persistent polluting fuel use increased obesity risk while the obesity risk of the transition to cleaner fuels was similar to persistent use of cleaner fuels. The finding underscores the significance of advocating for the adoption of cleaner fuels as a strategy to mitigate the disease burden associated with obesity.

Based on the solid waste-based modification, green shear-thickening functionalized ballistic composites were prepared. Silica aerosols were obtained from solid waste diatomaceous earth through sol–gel preparation, gel aging, and supercritical drying. The modified silica aerosols acted as the dispersed phase, regulating the green shear-thickening liquid. A comparison was made between the performance of the modified shear-thickening liquid (SG@STF) and traditional shear-thickening liquids. By modifying solid waste based shear thickener (SG@STF) Combined with aramid fabric (AF) to test Ballistic performance. Characterization tests revealed that the rheological properties of SG@STF were significantly enhanced by increasing the volume fraction of the dispersed phase in STF from 50 % to 60 %. This enhancement was attributed to the addition of reactive functional groups on the surface of the silica sol. Yarn pull-out tests demonstrated that SG@STF/AF improved the tensile strength by 120 % compared to AF fabric, thanks to its superior friction properties. Ballistic tests showed that SG@STF increased the ballistic ultimate velocity of AF fabric by 105 %, elevating AF’s ballistic limiting velocity from 51 m/s to 105 m/s. Consequently, SG@STF/AF exhibited superior ballistic properties compared to AF fabric. The doping of SG enhanced the friction between yarns and increased the load-bearing area of the fabrics, thereby improving the ballistic properties of SG@STF/AF and achieving the desired modulation of their ballistic properties.

Abstract Diamond possesses excellent thermal conductivity and tunable bandgap. Currently, the high‐pressure, high‐temperature, and chemical vapor deposition methods are the most promising strategies for the commercial‐scale production of synthetic diamond. Although diamond has been extensively employed in jewelry and cutting/grinding tasks, the realization of its high‐end applications through microstructure engineering has long been sought. Herein, we discuss the microstructures encountered in diamond and further concentrate on cutting‐edge investigations utilizing electron microscopy techniques to illuminate the transition mechanism between graphite and diamond during the synthesis and device constructions. The impacts of distinct microstructures on the electrical applications of diamond, especially the photoelectrical, electrical, and thermal properties, are elaborated. The recently reported elastic and plastic deformations revealed through in situ microscopy techniques are also summarized. Finally, the limitations, perspectives, and corresponding solutions are proposed.

Summary: X-ray detection is crucial across various sectors, but traditional techniques face challenges such as inefficient data transmission, redundant sensing, high power consumption, and complexity. The innovative idea of a retinomorphic X-ray detector shows great potential. However, its implementation has been hindered by the absence of active layers capable of both detecting X-rays and serving as memory storage. In response to this critical gap, our study integrates hybrid perovskite with hydrion-conductive organic cations to develop a groundbreaking retinomorphic X-ray detector. This novel device stands at the nexus of technological innovation, utilizing X-ray detection, memory, and preprocessing capabilities within a single hardware platform. The core mechanism underlying this innovation lies in the transport of electrons and holes within the metal halide octahedral frameworks, enabling precise X-ray detection. Concurrently, the hydrion movement through organic cations endows the device with short-term resistive memory, facilitating rapid data processing and retrieval. Notably, our retinomorphic X-ray detector boasts an array of formidable features, including reconfigurable short-term memory, a linear response curve, and an extended retention time. In practical terms, this translates into the efficient capture of motion projections with minimal redundant data, achieving a compression ratio of 18.06% and an impressive recognition accuracy of up to 98.6%. In essence, our prototype represents a paradigm shift in X-ray detection technology. With its transformative capabilities, this retinomorphic hardware is poised to revolutionize the existing X-ray detection landscape.

With the gradual implementation of China’s deep-earth engineering strategy, deep resource extraction and underground space construction have brought in some new opportunities, but they also face many challenges, with extreme geological conditions such as high geopathic stresses, high ground temperatures and hard rock bodies popping up all the time. Rock breaking technology is the main engineering activity for all resource extraction and underground space construction, and it is the main factor determining the construction process and engineering efficiency. Under extreme geological conditions, tool-based rock breaking technology has become a key technical bottleneck to affect the smooth implementation of deep-earth engineering strategy due to fast tool wear and low rock breaking efficiency. In order to solve the problem of high-efficiency rock breaking in deep-earth and to guarantee the smooth implementation of deep-earth engineering strategy, there is an urgent need for a revolutionary rock breaking technology. As an important supplement to the tool-based breaking technology, the non-tool rock breaking technology is a feasible solution to break through the bottleneck of the tool-based breaking technology. To this end, the non-tool rock breaking technology is summarized into three types of technological systems, namely, impact rock breaking, thermal stress rock breaking and erosion and abrasion rock breaking. Sixteen types of rock breaking technologies, such as water jets, lasers and abrasive air jets, etc., are systematically analyzed. Also, the history of the development of each technology and their technical principles are summarized, and the advantages of the rock breaking and the technological bottlenecks are analyzed. It is concluded that the main reasons why the current non-tool rock-breaking technologies are not widely used in resource extraction and underground space construction are high energy consumption, poor adoptability and complex technical equipment. Compared with tool-based breaking, non-tool breaking technology has a lower energy utilization rate for breaking rock. The specific energy consumption of water jet breaking is 40−70 times that of a tool breaking. Microwave, laser and plasma technologies require high-standard operation environment and cannot be applied in drilling, tunneling and other restricted and harsh environments. In order to solve the problem of rock breaking in extreme geological conditions, the idea of synergistic rock breaking by multiple non-tool rock breaking technologies is proposed, giving full play to the technological advantages of each non-tool rock breaking technology. The rock breaking concept of unloading high geo-stress by jet slit and breaking hard rock by particle impact volume is constructed to minimize the energy consumption of rock breaking, simplify the system equipment, and provide a theoretical support for the development of non-tool rock breaking technology.

Abstract Patients with advanced gastric cancer typically face a grim prognosis. This phase 1a (dose escalation) and phase 1b (dose expansion) study investigated safety and efficacy of first-line camrelizumab plus apatinib and chemotherapy for advanced gastric or gastroesophageal junction adenocarcinoma. The primary endpoints included maximum tolerated dose (MTD) in phase 1a and objective response rate (ORR) across phase 1a and 1b. Phase 1a tested three dose regimens of camrelizumab, apatinib, oxaliplatin, and S-1. Dose regimen 1: camrelizumab 200 mg on day 1, apatinib 250 mg every other day, oxaliplatin 100 mg/m² on day 1, and S-1 40 mg twice a day on days 1–14. Dose regimen 2: same as dose regimen 1, but oxaliplatin 130 mg/m². Dose regimen 3: same as dose regimen 2, but apatinib 250 mg daily. Thirty-four patients were included (9 in phase 1a, 25 in phase 1b). No dose-limiting toxicities occurred so no MTD was identified. Dose 3 was set for the recommended phase 2 doses and administered in phase 1b. The confirmed ORR was 76.5% (95% CI 58.8–89.3). The median progression-free survival was 8.4 months (95% CI 5.9-not evaluable [NE]), and the median overall survival (OS) was not mature (11.6-NE). Ten patients underwent surgery after treatment and the multidisciplinary team evaluation. Among 24 patients without surgery, the median OS was 19.6 months (7.8-NE). Eighteen patients (52.9%) developed grade ≥ 3 treatment-emergent adverse events. Camrelizumab plus apatinib and chemotherapy showed favorable clinical outcomes and manageable safety for untreated advanced gastric cancer (ChiCTR2000034109).

Chinese cabbage (Brassica rapa ssp. pekinensis) has a long cultivation history and is one of the vegetable crops with the largest cultivation area in China. However, salt stress severely damages photosynthesis and hormone metabolism, nutritional balances, and results in ion toxicity in plants. To better understand the mechanisms of salt-induced growth inhibition in Chinese cabbage, RNA-seq and physiological index determination were conducted to explore the impacts of salt stress on carbon cycle metabolism and photosynthesis in Chinese cabbage. Here, we found that the number of thylakoids and grana lamellae and the content of starch granules and chlorophyll in the leaves of Chinese cabbage under salt stress showed a time-dependent response, first increasing and then decreasing. Chinese cabbage increased the transcript levels of genes related to the photosynthetic apparatus and carbon metabolism under salt stress, probably in an attempt to alleviate damage to the photosynthetic system and enhance CO2 fixation and energy metabolism. The transcription of genes related to starch and sucrose synthesis and degradation were also enhanced; this might have been an attempt to maintain intracellular osmotic pressure by increasing soluble sugar concentrations. Soluble sugars could also be used as potential reactive oxygen species (ROS) scavengers, in concert with peroxidase (POD) enzymes, to eliminate ROS that accumulate during metabolic processes. Our study characterizes the synergistic response network of carbon metabolism and photosynthesis under salt stress.

Abstract The presence of light absorption and scattering in underwater conditions results in underwater images with missing details, low contrast, and color bias. The current deep learning-based methods bring unlimited potential for underwater image restoration (UIR) tasks. These methods, however, do not adequately take into account the inconsistency of the attenuation of different color channels and spatial regions when performing image restoration. To solve these gaps, we propose a dual information modulation network (DIMN) for accurate UIR tasks. To be specific, we design a multi-information enhancement module (MIEM), empowered by spatial-aware attention block (SAAB) and multi-scale structural Transformer block (MSTB), to guide the inductive bias of image degradation processes under nonhomogeneous media distributions. SAAB focuses on different spatial locations, capturing more spatial-aware cues to correct color deviations and recover details. MSTB utilizes the difference and complementarity between features at different scales to effectively complement the network’s structural and global perceptual capabilities, enhancing image sharpness and contrast further. Experimental results reveal that the proposed DIMN exceeds most state-of-the-art UIR methods. Our code and results are available at: https://github.com/wwaannggllii/DIMN .

Abstract Efficient CO2 separation technologies are essential for mitigating climate change. Compared to traditional thermochemical methods, electrochemically mediated carbon capture using redox-tunable sorbents emerges as a promising alternative due to its versatility and energy efficiency. However, the undesirable linear free-energy relationship between redox potential and CO2 binding affinity in existing chemistry makes it fundamentally challenging to optimise key sorbent properties independently via chemical modifications. Here, we demonstrate a design paradigm for electrochemically mediated carbon capture sorbents, which breaks the undesirable scaling relationship by leveraging intramolecular hydrogen bonding in isoindigo derivatives. The redox potentials of isoindigos can be anodically shifted by >350 mV to impart sorbents with high oxygen stability without compromising CO2 binding, culminating in a system with minimised parasitic reactions. With the synthetic space presented, our effort provides a generalisable strategy to finetune interactions between redox-active organic molecules and CO2, addressing a longstanding challenge in developing effective carbon capture methods driven by non-conventional stimuli.

Abstract The assembly of oligopeptide and polypeptide molecules can reconstruct various ordered advanced structures through intermolecular interactions to achieve protein-like biofunction. Here, we develop a “molecular velcro”-inspired peptide and gelatin co-assembly strategy, in which amphiphilic supramolecular tripeptides are attached to the molecular chain of gelatin methacryloyl via intra-/intermolecular interactions. We perform molecular docking and dynamics simulations to demonstrate the feasibility of this strategy and reveal the advanced structural transition of the co-assembled hydrogel, which brings more ordered β-sheet content and 10-fold or more compressive strength improvement. We conduct transcriptome analysis to reveal the role of co-assembled hydrogel in promoting cell proliferation and chondrogenic differentiation. Subcutaneous implantation evaluation confirms considerably reduced inflammatory responses and immunogenicity in comparison with type I collagen. We demonstrate that bone mesenchymal stem cells-laden co-assembled hydrogel can be stably fixed in rabbit knee joint defects by photocuring, which significantly facilitates hyaline cartilage regeneration after three months. This co-assembly strategy provides an approach for developing cartilage regenerative biomaterials.

Abstract Alternative polyadenylation plays an important role in cancer initiation and progression; however, current transcriptome-wide association studies mostly ignore alternative polyadenylation when identifying putative cancer susceptibility genes. Here, we perform a pan-cancer 3′ untranslated region alternative polyadenylation transcriptome-wide association analysis by integrating 55 well-powered (n > 50,000) genome-wide association studies datasets across 22 major cancer types with alternative polyadenylation quantification from 23,955 RNA sequencing samples across 7,574 individuals. We find that genetic variants associated with alternative polyadenylation are co-localized with 28.57% of cancer loci and contribute a significant portion of cancer heritability. We further identify 642 significant cancer susceptibility genes predicted to modulate cancer risk via alternative polyadenylation, 62.46% of which have been overlooked by traditional expression- and splicing- studies. As proof of principle validation, we show that alternative alleles facilitate 3′ untranslated region lengthening of CRLS1 gene leading to increased protein abundance and promoted proliferation of breast cancer cells. Together, our study highlights the significant role of alternative polyadenylation in discovering new cancer susceptibility genes and provides a strong foundational framework for enhancing our understanding of the etiology underlying human cancers.

Abstract Micro/nanorobots hold exciting prospects for biomedical and even clinical applications due to their small size and high controllability. However, it is still a big challenge to maneuver micro/nanorobots into narrow spaces with high deformability and adaptability to perform complicated biomedical tasks. Here, we report a light-controlled soft bio-microrobots (called “Ebot”) based on Euglena gracilis that are capable of performing multiple tasks in narrow microenvironments including intestinal mucosa with high controllability, deformability and adaptability. The motion of the Ebot can be precisely navigated via light-controlled polygonal flagellum beating. Moreover, the Ebot shows highly controlled deformability with different light illumination duration, which allows it to pass through narrow and curved microchannels with high adaptability. With these features, Ebots are able to execute multiple tasks, such as targeted drug delivery, selective removal of diseased cells in intestinal mucosa, as well as photodynamic therapy. This light-controlled Ebot provides a new bio-microrobotic tool, with many new possibilities for biomedical task execution in narrow and complicated spaces where conventional tools are difficult to access due to the lack of deformability and bio-adaptability.

Building information serves as a critical foundational dataset in the fields of urban planning, smart cities and surveying and mapping, and high-resolution remote sensing (HRRS) imagery has become a vital data source for extracting building information. However, automatically extracting building information from HRRS imagery using a single feature or method remains a challenging task. On one hand, buildings exhibit significant variations in terms of their size, color, geometric structures, and other aspects. On the other hand, there are also numerous features in the environment that bear spectral and morphological resemblances to buildings. In this article, we proposed a multifeature fusion framework based on Dempster–Shafer (D-S) theory that consists of two steps for automated building extraction from HRRS imagery. The initial D-S fusion step involves two branches: object-level and pixel-level feature fusion. Then the outcomes are further combined to derive the ultimate building confidence information. In the framework, we introduced a proportional consistency and centroid consistency index to convert pixel-level features to object-level features, thereby facilitating their fusion. In addition, we proposed an initialization module for the basic probability assignment formula, enabling the elimination of the impact of nonbuilding objects and simplifying the construction process of BPAF. The experimental results based on the Nanjing, WHU, and Washington datasets demonstrate the effectiveness of our method, the accuracy outperforms the other four advanced algorithms.

Abstract Breast cancer is the second leading cause of death in women worldwide, with triple-negative breast cancer (TNBC) having the worst prognosis. Although there are numerous studies on TNBC, there is no effective treatment for it, and it is still a major problem today. Studies on PIWI-interacting RNAs (piRNAs) are increasing and investigating the mechanism of piRNAs in the proliferation and metastasis of TNBC may lead to new potential treatment targets. Here, we identified a novel piRNA, piR-YBX1, which was downregulated in TNBC compared to matched normal breast tissue. Overexpression of piR-YBX1 significantly inhibited the proliferation, migration, invasion ability of TNBC cells both in vivo and in vitro. Mechanistically, piR-YBX1 could bind directly to mRNA of Y-box binding protein 1 (YBX1) and overexpression of piR-YBX1 downregulated YBX1 in both mRNA and protein levels, while the function of piR-YBX1 could be partly rescued by overexpression of YBX1. In addition, YBX1 could bind to RAF1 which is the key molecule in the MAPK signaling pathway, and overexpression of piR-YBX1 inhibited the p-MEK and p-ERK1/2, which can be reverted by YBX1. In conclusion, our findings discovered that the piR-YBX1/YBX1/MAPK axis suppresses the proliferation and metastasis of TNBC and therefore piR-YBX1 has the potential to be an effective therapeutic agent for breast cancer.

Abstract Aiming at the problems of low target detection accuracy and high leakage rate of the current traditional weld surface defect detection methods and existing detection models, an improved YOLOv7 pipeline weld surface defect detection model is proposed to improve detection results. In the improved model, a Le-HorBlock module is designed, and it is introduced into the back of fourth CBS module of the backbone network, which preserves the characteristics of high-order information by realizing second-order spatial interaction, thus enhancing the ability of the network to extract features in weld defect images. The coordinate attention (CoordAtt) block is introduced to enhance the representation ability of target features, suppress interference. The CIoU loss function in YOLOv7 network model is replaced by the SIoU, so as to optimize the loss function, reduce the freedom of the loss function, and accelerate convergence. And a new large-scale pipeline weld surface defect dataset containing 2000 images of pipeline welds with weld defects is used in the proposed model. In the experimental comparison, the improved YOLOv7 network model has greatly improved the missed detection rate compared with the original network. The experimental results show that the improved YOLOv7 network model mAP@80.5 can reach 78.6%, which is 15.9% higher than the original model, and the detection effect is better than the original network and other classical target detection networks.

Abstract Demyelination and failure of remyelination in the central nervous system (CNS) characterize a number of neurological disorders. Spontaneous remyelination in demyelinating diseases is limited, as oligodendrocyte precursor cells (OPCs), which are often present in demyelinated lesions in abundance, mostly fail to differentiate into oligodendrocytes, the myelinating cells in the CNS. In addition to OPCs, the lesions are assembled numbers of activated resident microglia/infiltrated macrophages; however, the mechanisms and potential role of interactions between the microglia/macrophages and OPCs are poorly understood. Here, we generated a transcriptional profile of exosomes from activated microglia, and found that miR-615-5p was elevated. miR-615-5p bound to 3′UTR of myelin regulator factor (MYRF), a crucial myelination transcription factor expressed in oligodendrocyte lineage cells. Mechanistically, exosomes from activated microglia transferred miR-615-5p to OPCs, which directly bound to MYRF and inhibited OPC maturation. Furthermore, an effect of AAV expressing miR-615-5p sponge in microglia was tested in experimental autoimmune encephalomyelitis (EAE) and cuprizone (CPZ)-induced demyelination model, the classical mouse models of multiple sclerosis. miR-615-5p sponge effectively alleviated disease progression and promoted remyelination. This study identifies miR-615-5p/MYRF as a new target for the therapy of demyelinating diseases.

Abstract Genomic DNA exhibits high heterogeneity in terms of its dynamic within the nucleus, its structure and functional roles. CRISPR-based imaging approaches can image genomic loci in living cells. However, conventional CRISPR-based tools involve expressing constitutively fluorescent proteins, resulting in high background and nonspecific nucleolar signal. Here, we construct fluorogenic CRISPR (fCRISPR) to overcome these issues. fCRISPR is designed with dCas9, an engineered sgRNA, and a fluorogenic protein. Fluorogenic proteins are degraded unless they are bound to specific RNA hairpins. These hairpins are inserted into sgRNA, resulting in dCas9: sgRNA: fluorogenic protein ternary complexes that enable fluorogenic DNA imaging. With fCRISPR, we image various genomic DNA in different human cells with high signal-to-noise ratio and sensitivity. Furthermore, fCRISPR tracks chromosomes dynamics and length. fCRISPR also allows DNA double-strand breaks (DSBs) and repair to be tracked in real time. Taken together, fCRISPR offers a high-contrast and sensitive platform for imaging genomic loci.

With the rapid development of Earth observation technology and deep learning, building extraction from remotely sensed imagery based on deep convolutional neural networks has attracted wide attention in recent years. However, due to the heterogeneity of building shapes and sizes and the complexity of the surrounding objects, current building extraction methods still have challenges in boundary accuracy and complete building extraction. For these purposes, we proposed a low-level feature enhancement and multiscale attention pyramid aggregation network (LFEMAP-Net) that considers building boundary information and multiscale feature expression to obtain higher accuracy building extraction. First, a low-level feature enhancement model is proposed based on the prior edge information to enhance the representation of spatial details, effectively addressing issues related to information loss and fuzzy boundaries. Additionally, a multiscale attention pyramid aggregation model is developed during the decoding stage to facilitate the fusion of features from different scales, thereby enhancing the extraction of building features. The experimental results on two publicly available datasets validate that LFEMAP-Net can overcome building extraction interruptions and boundary blur in complex scenes, and achieve boundary optimization and complete segmentation of buildings and achieve better performance than other advanced semantic segmentation models.

The therapeutic potential of Annexin A1, an important member of the Annexin superfamily, has become evident in results of experiments with multiple human systems and animal models. The anti-inflammatory and pro-resolving effects of Annexin A1 are characteristic of pathologies involving the nervous system. In this review, we initially describe the expression sites of Annexin A1, then outline the mechanisms by which Annexin A1 maintains the neurological homeostasis through either formyl peptide receptor 2 or other molecular approaches; and, finally, we discuss the neuroregenerative potential qualities of Annexin A1. The eye and the nervous system are anatomically and functionally connected, but the association between visual system pathogenesis, especially in the retina, and Annexin A1 alterations has not been well summarized. Therefore, we explain the beneficial effects of Annexin A1 for ocular diseases, especially for retinal diseases and glaucoma on the basis of published findings, and we explore present and future delivery strategies for Annexin A1 to the retina.

Rice breeders have developed numerous hybrid rice varieties with high yield and improved quality over the years. However, limited information is available on the stability of quality traits in high-quality rice. This study determined the stability of quality traits in two high-quality hybrid rice varieties, Zhuliangyou 570 (ZLY570) and Huazheyou 261 (HZY261), across different ecological regions and agronomic practices through on-farm research and field experiments. The on-farm research was conducted across nine provinces in southern China in 2021–2023, and field experiments with two sowing dates and six nitrogen treatments were performed in Hunan Province in 2022 and 2023. Results indicated that in both on-farm research and field experiments, both varieties exhibited a high coefficient of variation (CV) in chalky grain rate and chalkiness degree, followed by head rice rate, amylose and protein contents, traits including brown and milled rice rates, and length-to-width ratio revealed a low CV. The chalky grain rate and chalkiness degree of both varieties displayed poor stability, followed by head rice rate and amylose content. In contrast, brown and milled rice rates, length-to-width ratio, and protein content demonstrated high stability in the genotype plus genotype × environment interaction biplot analysis. However, the maximum value of chalky grain rate and chalkiness degree were only 8.43 % and 1.83 % for ZLY570, and 9.12 % and 2.05 % for HZY261, respectively. Both varieties revealed a high range (R) in head rice rate and amylose content, but a low R in protein content. Furthermore, the head rice rate and amylose content varied widely, while protein content showed narrower variability. These results suggest that high-quality hybrid rice exhibits poor stability in terms of head rice rate and amylose content. In contrast, it demonstrates relatively high stability in brown and milled rice rates, length-to-width ratio, chalky grain rate, chalkiness degree, and protein content.

Deep rocks are typically under a true-triaxial stress state. The strength of deep rock is thus dictated by both the direction and magnitude of principal stresses. The formulation of three-dimensional strength criterion for rocks is thus essential for evaluating the stability of deep-buried rock structures. With advancements in true-triaxial experimental instrumentation, several three-dimensional strength criteria have been proposed, necessitating a systematic review and consolidation of these criteria. This review first introduces the concept of three-dimensional stress state. Subsequently, classical strength criteria such as the Mohr-Coulomb Criterion, the Hoek-Brown criterion, and the Drucker-Prager criterion are reiterated. However, these traditional strength criteria inadequately describe rock strength under true-triaxial stress conditions. To better capture the influence of intermediate principal stress, hydrostatic pressure, and Lode angle on rock strength, researchers have revised classical strength criteria. Modified strength criteria and unified strength criteria based on classical formulations are also introduced. Notably, the unified strength criterion incorporates multiple single criteria and demonstrates wider applicability. Furthermore, beyond macroscopic strength criteria, this review also discusses micromechanical strength criteria, where the stress state and crack propagation govern rock mechanical behaviors. This comprehensive review may serve as a valuable source for addressing the problem of deep rock strength in energy extraction and other rock engineering applications.

An increasing number of people undergo anesthesia and surgery. Perioperative neurocognitive and depressive disorders are common central nervous system complications with similar pathogeneses. These conditions pose a deleterious threat to human health and a significant societal burden. In recent years, numerous studies have focused on the role of the gut microbiota and its metabolites in the central nervous system via the gut-brain axis. Its involvement in perioperative neurocognitive and depressive disorders has attracted considerable attention. This review aimed to elucidate the role of the gut microbiota and its metabolites in the pathogenesis of perioperative neurocognitive and depressive disorders, as well as the value of targeted interventions and treatments.

ABSTRACT: The wide distribution and diverse varieties of chickens make them important models for studying genetic adaptation. The aim of this study was to identify genes that alter heat adaptation in commercial chicken breeds by comparing genetic differences between tropical and cold-resistant chickens. We analyzed whole-genome resequencing data of 186 chickens across various regions in Asia, including the following breeds: Bian chickens (B), Dagu chickens (DG), Beijing-You chickens (BY), and Gallus gallus jabouillei from China; Gallus gallus murghi from India; Vietnam native chickens (VN); Thailand native chickens (TN) and Gallus gallus spadiceus from Thailand; and Indonesia native chickens (IN), Gallus gallus gallus, and Gallus gallus bankiva from Indonesia. In total, 5,454,765 SNPs were identified for further analyses. Population genetic structure analysis revealed that each local chicken breed had undergone independent evolution. Additionally, when K = 5, B, BY, and DG chickens shared a common ancestor and exhibited high levels of inbreeding, suggesting that northern cold-resistant chickens are likely the result of artificial selection. In contrast, the runs of homozygosity (ROH) and the ROH-based genomic inbreeding coefficient (FROH) results for IN, TN, and VN chickens showed low levels of inbreeding. Low population differentiation index values indicated low differentiation levels, suggesting low genetic diversity in tropical chickens, implying increased vulnerability to environmental changes, decreased adaptability, and disease resistance. Whole-genome selection sweep analysis revealed 69 candidate genes, including LGR4, G6PC, and NBR1, between tropical and cold-resistant chickens. The genes were further subjected to GO and KEGG enrichment analyses, revealing that most of the genes were primarily enriched in biological synthesis processes, metabolic processes, central nervous system development, ion transmembrane transport, and the Wnt signaling pathway. Our study identified heat adaptation genes and their functions in chickens that primarily affect chickens in high-temperature environments through metabolic pathways. These heat-resistance genes provide a theoretical basis for improving the heat-adaptation capacity of commercial chicken breeds.

Diabetic wounds pose a clinical challenge due to persistent inflammation, severe bacterial infections, inadequate vascularization, and pronounced oxidative stress. Current therapeutic modalities fail to provide satisfactory outcomes in managing these conditions, resulting in considerable patient distress. Two-dimensional nanomaterials (2DNMs), characterized by their unique nanosheet structures, expansive surface areas, and remarkable physicochemical properties, have garnered considerable attention for their potential in therapeutic applications. Emerging 2DNMs can be loaded with various pharmacological agents, including small molecules, metal ions, and liposomes. Moreover, they can be integrated with various biomaterials such as hydrogels, microneedles, and microspheres, thus demonstrating unprecedented advantages in expediting the healing process of diabetic wounds. Moreover, 2DNMs exhibit exceptional performance characteristics, including high biocompatibility, effective antimicrobial properties, optimal phototherapeutic effects, and enhanced electrostimulation capabilities. These properties enable them to modulate the wound microenvironment, leading to widespread application in tissue repair with remarkable outcomes. This review delineates several emerging 2DNMs, such as graphene and its derivatives, black phosphorus, MXenes, and transition metal dichalcogenides, in the context of diabetic wound repair. Furthermore, it elucidates the translational challenges and future perspectives of 2DNMs in wound healing treatments. Overall, 2DNMs present a highly promising strategy for ameliorating diabetic wounds, thus providing novel avenues for diagnostic and therapeutic strategies in diabetic wound management.

Tumor treating fields (TTFields) are a type of sinusoidal alternating current electric field that has proven effective in inhibiting the reproduction of dividing tumor cells. Despite their recognized impact, the precise biophysical mechanisms underlying the unique effects of TTFields remain unknown. Many of the previous studies predominantly attribute the inhibitory effects of TTFields to mitotic disruption, with intracellular microtubules identified as crucial targets. However, this conceptual framework lacks substantiation at the mesoscopic level. This study addresses the existing gap by constructing force models for tubulin and other key subcellular structures involved in microtubule electrophysiological activities under TTFields exposure. The primary objective is to explore whether the electric force or torque exerted by TTFields significantly influences the normal structure and activities of microtubules. Initially, we examine the potential effect on the dynamic stability of microtubule structures by calculating the electric field torque on the tubulin dimer orientation. Furthermore, given the importance of electrostatics in microtubule-associated activities, such as chromosome segregation and substance transport of kinesin during mitosis, we investigate the interaction between TTFields and these electrostatic processes. Our data show that the electrodynamic effects of TTFields are most likely too weak to disrupt normal microtubule electrophysiological activities significantly. Consequently, we posit that the observed cytoskeleton destruction in mitosis is more likely attributable to non-mechanical mechanisms.

Abstract Multiple lines of evidence confirm a widespread increase in vegetation growth across China over the past few decades. The relationship between vegetation growth and water availability is thought to be becoming stronger under climate change, that is, water constraints on vegetation growth have been increasing. However, our understanding of how water constraints have influenced these vegetation greening trends, especially those climate change‐driven ones, remains limited. Here, we conduct a comprehensive evaluation of recent water constraints and their implications for vegetation growth in China between 1982 and 2015. By analyzing the spatiotemporal patterns of the relationship between vegetation growth and water availability, we reveal recent water constraints and their changes hidden within an overall greening trend in China. Further analysis demonstrates that two climate change‐related categories, defined broadly as “climate” (e.g., air temperature, precipitation, and so on) and “CO2” (i.e., atmospheric carbon dioxide), have exerted varying levels of importance in regulating vegetation growth across different water constraints. With increasing water constraints, the proportion of the climate‐dominated area has significantly risen, while that of the CO2‐dominated area has sharply declined. Our findings highlight that water constraints can mediate the dominance of climate and atmospheric CO2 on vegetation growth. This has the great potential to exacerbate the uncertainty surrounding current and future sustainable vegetation greening trends.

Abstract Along with the increasing integration density and decreased feature size of current semiconductor technology, heterointegration of the Si‐based devices with diamond has acted as a promising strategy to relieve the existing heat dissipation problem. As one of the heterointegration methods, the microwave plasma chemical vapor deposition (MPCVD) method is utilized to synthesize large‐scale diamond films on a Si substrate, while distinct structures appear at the Si‐diamond interface. Investigation of the formation mechanisms and modulation strategies of the interface is crucial to optimize the heat dissipation behaviors. By taking advantage of electron microscopy, the formation of the epitaxial β‐SiC interlayer is found to be caused by the interaction between the anisotropically sputtered Si and the deposited amorphous carbon. Compared with the randomly oriented β‐SiC interlayer, larger diamond grain sizes can be obtained on the epitaxial β‐SiC interlayer under the same synthesis condition. Moreover, due to the competitive interfacial reactions, the epitaxial β‐SiC interlayer thickness can be reduced by increasing the CH4/H2 ratio (from 3% to 10%), while further increase in the ratio (to 20%) can lead to the broken of the epitaxial relationship. The above findings are expected to provide interfacial design strategies for multiple large‐scale diamond applications.