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Abstract Improvements in the polarization of environmentally-friendly perovskite ferroelectrics have proved to be a challenging task in order to replace the toxic Pb-based counterparts. In contrast to common methods by complex chemical composition designs, we have formed Mn-inlaid antiphase boundaries in Mn-doped (K,Na)NbO3 thin films using pulsed laser deposition method. Here, we observed that mono- or bi-atomic layer of Mn has been identified to inlay along the antiphase boundaries to balance the charges originated from the deficiency of alkali ions and to induce the strain in the KNN films. Thus, rectangular saturated polarization-electric field hysteresis loops have been achieved, with a significantly improved twice remanent polarization of 114 μC/cm2 with an applied electric field of 606 kV/cm, which can be comparable to that of the typical Pb-based thin films. Moreover, we directly see the Mn occupation at the A-site of KNN perovskite structure using atomic-scale microstructure and composition analysis. The Mn-inlaid antiphase boundary can further enrich the understanding of perovskite crystal structure and give more possibilities for the design and optimization of perovskite materials.

Abstract The Baishi landslide was located in the western part of Beichuan County, Sichuan Province, China. The landslide experienced multiple minor collapses at the front part, accompanying with numerous tensile cracks. To comprehensively grasp the stability conditions and predict the moment of failure of the landslide, deformation monitoring of the landslide has been carried out from the moment that the landslide was reported until it failed. This study analyzed the different phases of landslide deformation and its failure mechanism through the analysis of monitoring data. The result showed that the failure manifests both the retrogressive and advancing features. The landslide was divided into several zones based on the spatial variation of the deformation characteristics. Moreover, the improved tangential angle criterion is applied to categorize the deformation phases of a landslide. Investigating the surface displacement vectors and vector angles of landslides plays a significant role for ascertaining the failure and sliding mechanism. The monitoring results revealed that the front part of the landslide played a key role in the stability of the landslide. Therefore, the monitoring data from this zone were crucial for predicting the moment of complete landslide failure.

Abstract The application environment for concrete is becoming increasingly complex, accompanied by an intensification of its functional requirements. This paper presents a method for developing self-compacting concrete with conductive properties using limonite and graphite as the concrete conductive phases. In the process of concrete preparation, the limonite is initially treated by a pre-wetting method to prevent the surface depression caused by the addition of limonite during the concrete curing process. The second stage of the process involved optimising different proportions of limonite and graphite and different dosages of water-reducing agent, defoamer and dispersant to prepare concrete. The influence of different dosages of limonite and graphite and different dosages of water-reducing agent on the mechanics and electrical conductivity of concrete was studied in order to obtain self-compacting conductive concrete with performance indicators meeting the requirements of self-compacting and electrical conductivity. The results demonstrate that the mechanical and electrical properties of self-compacting conductive concrete prepared with polycarboxylic acid superplasticizer and retarding superplasticizer combined with superplasticizer are satisfactory, and the composite superplasticizer can function in conjunction with dispersant. The self-compaction index, slump expansion, expansion time T50 and J-ring expansion of fluid concrete meet the requisite standards. Once the concrete has reached the designated curing age, its compressive strength and flexural strength align with the anticipated design expectations, while its resistivity meets the stipulated conductivity index requirements.

Abstract This study aims to evaluate the biomechanical performance of the Gamma 3 nail with an anti-rotation screw (GNS) and compare it to two established gold-standard methods for treating unstable femoral neck fractures (UFNFs). Synthetic bone models were prepared with Pauwels’ type III osteotomy and an additional posterior wedge. Three different implant configurations were tested: three cannulated crews (3CS) in an inverted triangle configuration, a dynamic hip screw with an anti-rotation screw (DHSS), and GNS. Non-destructive cyclic axial loading was applied at 7° adduction, with 1000 cycles ranging from 100 to 1000 N. Subsequently, a construct failure test was conducted using progressive axial compression, and fracture reduction loss was recorded. The average axial stiffness was 321 ± 52 N/mm for 3CS, 430 ± 71 N/mm for DHSS, and 519 ± 104 N/mm for GNS. The average ultimate failure loads were 2699.3 N for 3CS, 3427.1 N for DHSS, and 3758.9 N for GNS. GNS demonstrated significantly greater axial stiffness compared to the other two groups (P

Abstract Macrophages played an important role in the progression and treatment of head and neck squamous cell carcinoma (HNSCC). We employed weighted gene co-expression network analysis (WGCNA) to identify macrophage-related genes (MRGs) and classify patients with HNSCC into two distinct subtypes. A macrophage-related risk signature (MRS) model, comprising nine genes: IGF2BP2, PPP1R14C, SLC7A5, KRT9, RAC2, NTN4, CTLA4, APOC1, and CYP27A1, was formulated by integrating 101 machine learning algorithm combinations. We observed lower overall survival (OS) in the high-risk group and the high-risk group showed elevated expression levels in most of the immune checkpoint and human leukocyte antigen (HLA) genes, suggesting a strong immune evasion capacity. Correspondingly, TIDE score positively correlated with risk score, implying that high-risk tumors may resist immunotherapy more effectively. At the single-cell level, we noted macrophages in the tumor microenvironment (TME) predominantly stalled in the G2/M phase, potentially hindering epithelial-mesenchymal transition and playing a crucial role in the inhibition of tumor progression. Finally, the proliferation and migration abilities of HNSCC cells significantly decreased after the expression of IGF2BP2 and SLC7A5 reduced. It also decreased migration ability of macrophages and facilitated their polarization towards the M1 direction. Our study constructed a novel MRS for HNSCC, which could serve as an indicator for predicting the prognosis, immune infiltration and immunotherapy for HNSCC patients.

Abstract Previous studies have revealed that thyroid hormone (TH) levels are associated with the risk of diabetic peripheral neuropathy (DPN) in euthyroid patients with type 2 diabetes mellitus (T2DM). However, the relationship between TH sensitivity, a complementary method for assessing thyroid function, and DPN remains unclear. This study aimed to investigate the correlation between DPN and TH sensitivity in euthyroid patients with T2DM. Exactly 708 euthyroid adults with T2DM were retrospectively enrolled. The FT3/FT4 ratio was used to estimate peripheral TH sensitivity. Central TH sensitivity was assessed using the Thyrotroph T4 Resistance Index (TT4RI), Thyroid-Stimulating Hormone Index (TSHI), Thyroid Feedback Quantile-based Index (TFQI), and Parametric TFQI (PTFQI). DPN was assessed using neurologic symptoms, signs, and nerve conduction velocity tests. The relationship between DPN and TH sensitivity was examined using logistic regression analysis. We observed that an elevated FT3/FT4 ratio was associated with DPN (OR = 1.36, 95%CI: 1.13–1.63, p = 0.0012). For each standard deviation (SD) increase in the TT4RI, TSHI, TFQI, and PTFQI, the OR of DPN was 0.80 (95%CI: 0.68–0.94, p = 0.0078), 0.72 (95%CI: 0.60–0.86, p = 0.0002), 0.69 (95%CI: 0.58–0.83, p

Abstract The existing diagnostic methods of epilepsy have great limitations, and more reliable and less difficult diagnostic methods are needed. We collected serum samples of adult patients with first-diagnosed epilepsy (EPs) and seizure control patients (EPRs) for non-targeted metabolomics detection and found that they were both significantly altered, with increased expression of nicotine addiction, linoleic acid metabolism, purine metabolism, and other metabolic pathways. The diagnostic model based on 4 differential metabolites achieved a diagnostic efficiency of 99.4% in the training cohort and 100% in the validation cohort. In addition, the association analysis of oral flora, serum metabolism, and clinical indicators also provided a new angle to analyze the mechanism of epilepsy. In conclusion, this study characterized the serum metabolic characteristics of EPs and EPRs and the changes before and after epilepsy control based on a large cohort, demonstrating the potential of metabolites as non-invasive diagnostic tools for epilepsy.

Abstract Global climate change and the collection of environmental protection taxes are accelerating the green transformation of thermal power enterprises. This study selected Chinese thermal power listed companies as samples and used a dynamic three-stage (operational, green transformation, and market performance) network DEA model to evaluate their transformation efficiency and corporate performance. This paper incorporates targeted indicators such as ESG (environment, society, governance) and stock prices into the model and conducts a comparative study on the basis of macro policies and the geographical location of the enterprise. A comparative analysis was conducted on the efficiency of enterprises before and after the adjustment of the environmental tax burden, using the environmental tax burden as an exogenous variable. Thus, the following conclusions can be drawn: there is a certain positive correlation between the collaborative efficiency of the two links of thermal power enterprises and the economic development of their respective regions. Moreover, the green transformation efficiency of most thermal power enterprises is superior to the market performance efficiency. The environmental tax burden mainly improves the overall efficiency of thermal power enterprises by improving their operational efficiency and efficiency in the green transformation stage without affecting market performance. To further improve efficiency, thermal power enterprises should actively communicate with stakeholders to strive for more financial relief.

Abstract Microbot collectives can cooperate to accomplish complex tasks that are difficult for a single individual. However, various force-induced microbot collectives maintained by weak magnetic, light, and electric fields still face challenges such as unstable connections, the need for a continuous external stimuli source, and imprecise individual control. Here, we construct magnetic and light-driven ant microbot collectives capable of reconfiguring multiple assembled architectures with robustness. This methodology utilizes a flexible two-photon polymerization strategy to fabricate microbots consisting of magnetic photoresist, hydrogel, and metal nanoparticles. Under the cooperation of magnetic and light fields, the microbots can reversibly and selectively assemble (e.g., 90° assembly and 180° assembly) into various morphologies. Moreover, we demonstrate the ability of assembled microbots to cross a one-body-length gap and their adaptive capability to move through a constriction and transport microcargo. Our strategy will broaden the abilities of clustered microbots, including gap traversal, micro-object manipulation, and drug delivery.

Abstract Deep coal‐rock formations are subjected to complex stress environments characterized by high static stresses and dynamic disturbances. To study the damage, fracture, and energy evolution characteristics of coal‐rock under dynamic–static combined loading, a new multiscale constitutive model for coal‐rock under dynamic–static combined loading is proposed based on micromechanics, and it is implemented into the LS‐DYNA solver. A numerical model of coal‐rock Split Hopkinson Pressure Bar under dynamic–static combined loading is established using LS‐DYNA, and research on the mechanical and energy evolution characteristics of coal‐rock under one‐dimensional and three‐dimensional dynamic–static combined loading is conducted. The results show that under one‐dimensional dynamic–static combined loading, with the increase of precompression, the dynamic peak stress linearly decreases while the combined peak stress linearly increases, and the dissipated energy of the specimen shows a decreasing trend. The fracture patterns of the coal‐rock specimen include internal shear fracture and external tensile fracture, and eventually, these two modes of fracture intersect to form macroscopic mesh cracks. As the axial pressure increases, the degree of specimen fragmentation gradually increases. Under three‐dimensional dynamic–static combined loading, with the increase of preconfining pressure, the stress–strain curve of the specimen will transition from “stress drop” to “stress rebound” after the peak. The peak stress increases with the increase of confining pressure, and the energy dissipation density of the specimen increases first and then decreases with the increase of confining pressure. With the increase of confining pressure, the hoop deformation of the specimen plays a constraining role, and the degree of specimen fracture gradually weakens, and the time of fracture occurrence gradually delays. The research results contribute to revealing the mechanical and energy mechanisms of rockburst disasters in deep coal mines.

Abstract High spatio-temporal resolution estimates of electricity consumption are essential for formulating effective energy transition strategies. However, the data availability is limited by complex spatio-temporal heterogeneity and insufficient multi-source feature fusion. To address these issues, this study introduces an innovative downscaling method that combines multi-source data with machine learning and spatial interpolation techniques. The method’s accuracy showed significant improvements, with determination coefficients (R 2) increasing by 30.1% and 33.4% over the baseline model in two evaluation datasets. With this advanced model, we estimated monthly electricity consumption across 1 km x 1 km grid for 280 Chinese cities from 2012 to 2019. Our dataset is highly consistent with officially released electricity consumption of different industries (Pearson correlation coefficients within 0.83 - 0.91). Moreover, our data can reflect the electricity consumption patterns of different urban land uses compared to other datasets. This study bridges a significant gap in fine-grained electricity consumption data, providing a robust foundation for the development of sustainable energy policies.

Abstract Ecological water replenishment is an important measure for conserving water sources and improving the water environment. To explore the evolution and causes of groundwater chemistry after ecological water replenishment in the Jialu River, this study utilized groundwater monitoring data from 2015 to 2019 following ecological water replenishment. Various methods, including Piper’s trilinear diagram, Gibbs diagram, principal component analysis, and ion ratio analysis, were employed for research purposes. The results indicate that (1) since the implementation of ecological water replenishment in the Jialu River, there has been a general downwards trend in total dissolved solids (TDS) in groundwater. The dominant cation in groundwater is Ca2+, whereas HCO3 − is the dominant anion. The concentration of cations in groundwater has generally decreased, with noticeable reductions in SO4 2− and Cl− concentrations in the upper reaches of the recharge river contributing to improved groundwater quality. (2) A comparison with 2015 reveals a gradual transition at sampling points from chemical types such as HCO3-Ca·Mg and HCO3·Cl–Ca·Mg to an ecological water replenishment chemical type (HCO3-Ca).

Abstract As computer image processing and digital technologies advance, creating an efficient method for classifying sports images is crucial for the rapid retrieval and management of large image datasets. Traditional manual methods for classifying sports images are impractical for large-scale data and often inaccurate when distinguishing similar images. This paper introduces an SE module that adaptively adjusts the weights of input feature mapping channels, and a Res module that excels in deep feature extraction, preventing gradient vanishing, multi-scale processing, and enhancing generalization in image recognition. Through extensive experimentation on network structure adjustments, the SE-RES-CNN neural network model is applied to sports image classification. The model is trained on a sports image classification dataset from Kaggle, alongside VGG-16 and ResNet50 models. Training results show that the proposed SE-RES-CNN model improves classification accuracy by approximately 5% compared to VGG-16 and ResNet50 models. Testing revealed that the SE-RES-CNN model classifies 100 out of 500 sports images in 6 s, achieving an accuracy rate of up to 98% and a single prediction time of 0.012 s. This validates the model's accuracy and effectiveness, significantly enhancing sports image retrieval and classification efficiency. This validates the model's accuracy and effectiveness, significantly enhancing sports image retrieval and classification efficiency.

Abstract To investigate whether peritumoral edema (PE) could enhance deep learning radiomic (DLR) model in predicting axillary lymph node metastasis (ALNM) burden in breast cancer. Invasive breast cancer patients with preoperative MRI were retrospectively enrolled and categorized into low (

Abstract Fire and explosion hazards pose significant safety concerns in the processing and storage of biomass particles, warranting the safe utilization of these particles. This study employed scanning electron microscopy, thermogravimetric analysis, and cone calorimetry to investigate the thermal hazards and toxicity of raw biomass particles from four prevalent agricultural crops in China: rice, sorghum, corn, and reed. Among the samples, corn exhibited the highest heat output of 8006.82 J/g throughout the thermal decomposition process. The quantitative evaluation of critical heat flux, heat release rate intensity, fire growth rate index (FIGRA), post-ignition fire acceleration (PIFA) and flashover potential (X) revealed a substantial fire risk inherent to all the examined straw samples. Notably, corn displayed the lowest FIGRA value of 8.30 kW/m2 s, while rice demonstrated the minimum PIFA value of 16.11 kW/m2 s. Moreover, the X values for all four biomass particle types exceeded 10 under varying external heat flux levels, indicating their high propensity for fire hazards. Analysis of CO and CO2 emissions during combustion showed all four biomass samples exhibited high concentrations throughout, from the initial stages to the end. The present study offers crucial insights for formulating comprehensive fire safety guidelines tailored to the storage and processing of biomass particles.

Abstract Polyploidization presents an unusual challenge for species with sex chromosomes, as it can lead to complex combinations of sex chromosomes that disrupt reproductive development. This is particularly true for allopolyploidization between species with different sex chromosome systems. Here, we assemble haplotype-resolved chromosome-level genomes of a female allotetraploid weeping willow (Salix babylonica) and a male diploid S. dunnii. We show that weeping willow arose from crosses between a female ancestor from the Salix-clade, which has XY sex chromosomes on chromosome 7, and a male ancestor from the Vetrix-clade, which has ancestral XY sex chromosomes on chromosome 15. We find that weeping willow has one pair of sex chromosomes, ZW on chromosome 15, that derived from the ancestral XY sex chromosomes in the male ancestor of the Vetrix-clade. Moreover, the ancestral 7X chromosomes from the female ancestor of the Salix-clade have reverted to autosomal inheritance. Duplicated intact ARR17-like genes on the four homologous chromosomes 19 likely have contributed to the maintenance of dioecy during polyploidization and sex chromosome turnover. Taken together, our results suggest the rapid evolution and reversion of sex chromosomes following allopolyploidization in weeping willow.

Abstract Mammalian TIP60 is a multi-functional enzyme with histone acetylation and histone dimer exchange activities. It plays roles in diverse cellular processes including transcription, DNA repair, cell cycle control, and embryonic development. Here we report the cryo-electron microscopy structures of the human TIP60 complex with the core subcomplex and TRRAP module refined to 3.2-Å resolution. The structures show that EP400 acts as a backbone integrating the motor module, the ARP module, and the TRRAP module. The RUVBL1-RUVBL2 hexamer serves as a rigid core for the assembly of EP400 ATPase and YL1 in the motor module. In the ARP module, an ACTL6A-ACTB heterodimer and an extra ACTL6A make hydrophobic contacts with EP400 HSA helix, buttressed by network interactions among DMAP1, EPC1, and EP400. The ARP module stably associates with the motor module but is flexibly tethered to the TRRAP module, exhibiting a unique feature of human TIP60. The architecture of the nucleosome-bound human TIP60 reveals an unengaged nucleosome that is located between the core subcomplex and the TRRAP module. Our work illustrates the molecular architecture of human TIP60 and provides architectural insights into how this complex is bound by the nucleosome.

Abstract Severe fever with thrombocytopenia syndrome virus (SFTSV) is an emerging bunyavirus that causes severe viral hemorrhagic fever and thrombocytopenia syndrome with a fatality rate of up to 30%. No licensed vaccines or therapeutics are currently available for humans. Here, we develop seven monoclonal antibodies (mAbs) against SFTSV surface glycoprotein Gn. Mechanistic studies show that three neutralizing mAbs (S2A5, S1G3, and S1H7) block multiple steps during SFTSV infection, including viral attachment and membrane fusion, whereas another neutralizing mAb (B1G11) primarily inhibits the viral attachment step. Epitope binning and X-ray crystallographic analyses reveal four distinct antigenic sites on Gn, three of which have not previously been reported, corresponding to domain I, domain II, and spanning domain I and domain II. One of the most potent neutralizing mAbs, S2A5, binds to a conserved epitope on Gn domain I and broadly neutralizes infection of six SFTSV strains corresponding to genotypes A to F. A single dose treatment of S2A5 affords both pre- and post-exposure protection of mice against lethal SFTSV challenge without apparent weight loss. Our results support the importance of glycoprotein Gn for eliciting a robust humoral response and pave a path for developing prophylactic and therapeutic antibodies against SFTSV infection.

Abstract Post-translational addition of O-linked N-acetylglucosamine (O-GlcNAc) to proteins is commonly associated with a variety of stress responses and cellular processes in eukaryotes, but its potential roles in bacteria are unclear. Here, we show that protein HmwC acts as an O-GlcNAc transferase (OGT) responsible for O-GlcNAcylation of multiple proteins in Yersinia pestis, a flea-borne pathogen responsible for plague. We identify 64 O-GlcNAcylated proteins (comprising 65 sites) with differential abundance under conditions mimicking the mammalian host (Mh) and flea vector (Fv) environments. Deletion of hmwC, encoding a putative OGT, structurally distinct from any existing member of the GT41 family, results in reduced O-GlcNAcylation, reduced growth, and alterations in virulence properties and survival under stress. Purified HmwC can modify target proteins in vitro using UDP-GlcNAc as sugar donor. One of the target proteins, OsdY, promotes Y. pestis survival under oxidative stress conditions. Thus, our results support that regulation of antioxidative responses through O-GlcNAcylation may be a conserved process shared by prokaryotes and eukaryotes.

Abstract Mixed emotions have attracted increasing interest recently, but existing datasets rarely focus on mixed emotion recognition from multimodal signals, hindering the affective computing of mixed emotions. On this basis, we present a multimodal dataset with four kinds of signals recorded while watching mixed and non-mixed emotion videos. To ensure effective emotion induction, we first implemented a rule-based video filtering step to select the videos that could elicit stronger positive, negative, and mixed emotions. Then, an experiment with 80 participants was conducted, in which the data of EEG, GSR, PPG, and frontal face videos were recorded while they watched the selected video clips. We also recorded the subjective emotional rating on PANAS, VAD, and amusement-disgust dimensions. In total, the dataset consists of multimodal signal data and self-assessment data from 73 participants. We also present technical validations for emotion induction and mixed emotion classification from physiological signals and face videos. The average accuracy of the 3-class classification (i.e., positive, negative, and mixed) can reach 80.96% when using SVM and features from all modalities, which indicates the possibility of identifying mixed emotional states.

Abstract This study aimed to investigate whether class A1 scavenger receptor (SR-A1) regulated macrophage polarization and gut microbial alteration during intestinal inflammation of colitis. A murine colitis model was established by feeding with dextran sulfate sodium (DSS), and treatment groups were injected intravenously with SR-A1 antibody. Results showed a preventive effect on colitis symptoms and fewer inflammatory cell infiltrates in treatment groups. Down-regulation of inflammatory cytokines and up-regulation of anti-inflammatory cytokine related to macrophages were seen in murine PBMC and LPMC after injected with SR-A1 antibody. The percentage of M2 macrophages was also elevated in treatment groups. In addition, SR-A1 antibody treatment resulted in the decreased apoptosis and increased proliferation of colonic epithelial cells. Other findings indicated that SR-A1 antibody injection could mediate its anti-inflammatory effect via inhibiting TLR4-MyD88-NF-kB signaling pathway and alterating the gut microbiota composition. Our research identified SR-A1 as a potential therapeutic target in inflammatory bowel disease (IBD).

Abstract The limitations associated with conventional cancer treatment modalities, particularly for breast cancer, underscore the imperative for developing safer and more productive drug delivery systems. A promising strategy that has emerged is the combination of chemotherapy with gas therapy. We synthesized curcumin-loaded amorphous calcium carbonate nanoparticles (Cur-CaCO3) via a gas diffusion reaction in the present study. Subsequently, a "one-step" ethanol injection method was employed to fabricate lipid-coated calcium carbonate nanoparticles (Cur-CaCO3@LA-Lip) loaded with L-arginine, aimed at harnessing the synergistic effects of chemotherapy and nitric oxide to enhance antitumor efficacy. Transmission electron microscopy analysis revealed that Cur-CaCO3@LA-Lip nanoparticles were subspherical with a distinct lipid layer encapsulating the periphery. Fourier transform infrared spectroscopy, X-ray powder diffraction, and differential scanning calorimetry results confirmed the successful synthesis of Cur-CaCO3@LA-Lip. The nanoparticles exhibited significant drug loading capacities of 8.89% for curcumin and 3.1% for L-arginine. In vitro and in vivo assessments demonstrated that Cur-CaCO3@LA-Lip nanoparticles facilitated sustained release of curcumin and exhibited high cellular uptake, substantial tumor accumulation, and excellent biocompatibility. Additionally, the nanoparticles showed robust cytotoxicity and potent antitumor efficacy, suggesting their potential as a formidable candidate for breast cancer therapy.

Abstract Enhanced recovery after surgery (ERAS) has been successfully integrated into a diverse array of surgical fields to improve the quality and efficacy of treatment intervention. Nonetheless, the application of the ERAS protocol for patients with diabetic foot ulcer (DFU) subsequent to undergoing surgical procedures has not been previously explored. Therefore, this study aimed to investigate the effect of an enhanced recovery protocol on perioperative outcomes in patients with DFU following surgical procedures. A retrospective analysis was conducted on 112 patients with DFU who underwent surgery between January 2020 and December 2021 at a tertiary referral care center. In total, 57 patients received standard perioperative care (the non-ERAS group), and 55 patients received ERAS care (the ERAS group). The primary outcomes included the length of stay (LOS), wound healing time, patient satisfaction, and costs, serving as the basis for assessing the effectiveness of the two approaches. Secondary outcomes included preoperative anxiety (APAIS score), nutritional status (PG-SGA), pain (NRS score), the incidence of lower-extremity deep vein thrombosis (DVT), the reduction in lower-limb circumference, and the activity of daily living scale (Barthel Index). The ERAS group exhibited significantly shorter LOS (11.36 vs. 26.74 days; P 0.05). By reducing the LOS and hospital costs, and by minimizing perioperative complications, the ERAS protocol improves the quality and efficacy of treatment intervention in patients with DFU who underwent surgical procedures. Trial registration number: ChiCTR 2200064223 (Registration Date: 30/09/2022).

Abstract The combination of cisplatin and pemetrexed remains the gold standard chemotherapy for malignant pleural mesothelioma (MPM), although resistance and poor response pose a significant challenge. Cytidine deaminase (CDA) is a key enzyme in the nucleotide salvage pathway and is involved in the adaptive stress response to chemotherapy. The cytidine analog capecitabine and its metabolite 5′-deoxy-5-fluorocytidine (5’-DFCR) are converted via CDA to 5-fluorouracil, which affects DNA and RNA metabolism. This study investigated a schedule-dependent treatment strategy, proposing that initial chemotherapy induces CDA expression, sensitizing cells to subsequent capecitabine treatment. Basal CDA protein expression was low in different mesothelioma cell lines but increased in the corresponding xenografts. Standard chemotherapy increased CDA protein levels in MPM cells in vitro and in vivo in a schedule-dependent manner. This was associated with epithelial-to-mesenchymal transition and with HIF-1alpha expression at the transcriptional level. In addition, pretreatment with cisplatin and pemetrexed in combination sensitized MPM xenografts to capecitabine. Analysis of a tissue microarray (TMA) consisting of samples from 98 human MPM patients revealed that most human MPM samples had negative CDA expression. While survival curves based on CDA expression in matched samples clearly separated, significance was not reached due to the limited sample size. In non-matched samples, CDA expression before but not after neoadjuvant therapy was significantly associated with worse overall survival. In conclusion, chemotherapy increases CDA expression in xenografts, which is consistent with our in vitro results in MPM and lung cancer. A subset of matched patient samples showed increased CDA expression after therapy, suggesting that a schedule-dependent treatment strategy based on chemotherapy and capecitabine may benefit a selected MPM patient population.

Abstract The relationship between green and grey urban infrastructure, local meteorological conditions, and traffic-related air pollution is complex and dynamic. This case study examined the effect of evolving morphologies around a city square park in Dublin and explores the twin impacts of local urban development (grey) and maturing parks (green) on particulate matter (PM) pollution. A fixed air quality monitoring campaign and computational fluid dynamic modelling (ENVI-met) were used to assess current (baseline) and future scenarios. The baseline results presented the distribution of PM in the study area, with bimodal (PM2.5) and unimodal (PM10) diurnal profiles. The optimal vegetation height for air quality within the park also differed by wind direction with 21 m vegetation optimal for parallel winds (10.45% reduction) and 7 m vegetation optimal for perpendicular winds (30.36% reduction). Increased building heights led to higher PM2.5 concentrations on both footpaths ranging from 25.3 to 37.0% under perpendicular winds, whilst increasing the height of leeward buildings increased PM2.5 concentrations by up to 30.9% under parallel winds. The findings from this study provide evidence of the importance of more in-depth analysis of green and grey urban infrastructure in the urban planning decision-making process to avoid deteriorating air quality conditions around city square parks.

Abstract This research presents a novel approach to address the complexities of heterogeneous lung cancer dynamics through the development of a Fractional-Order Model. Focusing on the optimization of combination therapy, the model integrates immunotherapy and targeted therapy with the specific aim of minimizing side effects. Notably, our approach incorporates a clever fusion of Proportional-Integral-Derivative (PID) feedback controls alongside the optimization process. Unlike previous studies, our model incorporates essential equations accounting for the interaction between regular and mutated cancer cells, delineates the dynamics between immune cells and mutated cancer cells, enhances immune cell cytotoxic activity, and elucidates the influence of genetic mutations on the spread of cancer cells. This refined model offers a comprehensive understanding of lung cancer progression, providing a valuable tool for the development of personalized and effective treatment strategies. the findings underscore the potential of the optimized treatment strategy in achieving key therapeutic goals, including primary tumor control, metastasis limitation, immune response enhancement, and controlled genetic mutations. The dynamic and adaptive nature of the treatment approach, coupled with economic considerations and memory effects, positions the research at the forefront of advancing precision and personalized cancer therapeutics.

Abstract As major terrestrial carbon sinks, forests play an important role in mitigating climate change. The relationship between the seasonal uptake of carbon and its allocation to woody biomass remains poorly understood, leaving a significant gap in our capacity to predict carbon sequestration by forests. Here, we compare the intra-annual dynamics of carbon fluxes and wood formation across the Northern hemisphere, from carbon assimilation and the formation of non-structural carbon compounds to their incorporation in woody tissues. We show temporally coupled seasonal peaks of carbon assimilation (GPP) and wood cell differentiation, while the two processes are substantially decoupled during off-peak periods. Peaks of cambial activity occur substantially earlier compared to GPP, suggesting the buffer role of non-structural carbohydrates between the processes of carbon assimilation and allocation to wood. Our findings suggest that high-resolution seasonal data of ecosystem carbon fluxes, wood formation and the associated physiological processes may reduce uncertainties in carbon source-sink relationships at different spatial scales, from stand to ecosystem levels.

Abstract In tactile sensing, decoding the journey from afferent tactile signals to efferent motor commands is a significant challenge primarily due to the difficulty in capturing population-level afferent nerve signals during active touch. This study integrates a finite element hand model with a neural dynamic model by using microneurography data to predict neural responses based on contact biomechanics and membrane transduction dynamics. This research focuses specifically on tactile sensation and its direct translation into motor actions. Evaluations of muscle synergy during in -vivo experiments revealed transduction functions linking tactile signals and muscle activation. These functions suggest similar sensorimotor strategies for grasping influenced by object size and weight. The decoded transduction mechanism was validated by restoring human-like sensorimotor performance on a tendon-driven biomimetic hand. This research advances our understanding of translating tactile sensation into motor actions, offering valuable insights into prosthetic design, robotics, and the development of next-generation prosthetics with neuromorphic tactile feedback.

Abstract Immune checkpoint inhibitor (ICI)-induced myocarditis involves intensive immune/inflammation activation; however, its molecular basis is unclear. Here, we show that gasdermin-E (GSDME), a gasdermin family member, drives ICI-induced myocarditis. Pyroptosis mediated by GSDME, but not the canonical GSDMD, is activated in myocardial tissue of mice and cancer patients with ICI-induced myocarditis. Deficiency of GSDME in male mice alleviates ICI-induced cardiac infiltration of T cells, macrophages, and monocytes, as well as mitochondrial damage and inflammation. Restoration of GSDME expression specifically in cardiomyocytes, rather than myeloid cells, in GSDME-deficient mice reproduces ICI-induced myocarditis. Mechanistically, quantitative proteomics reveal that GSDME-dependent pyroptosis promotes cell death and mitochondrial DNA release, which in turn activates cGAS-STING signaling, triggering a robust interferon response and myocardial immune/inflammation activation. Pharmacological blockade of GSDME attenuates ICI-induced myocarditis and improves long-term survival in mice. Our findings may advance the understanding of ICI-induced myocarditis and suggest that targeting the GSDME-cGAS-STING-interferon axis may help prevent and manage ICI-associated myocarditis.

Abstract SuFEx click chemistry demonstrates remarkable molecular assembly capabilities. However, the effective utilization of alkyl sulfonyl fluoride hubs in SuFEx chemistry, particularly in reactions with alcohols and primary amines, presents considerable challenges. This study pioneers an intramolecular chalcogen bonding activated SuFEx (S-SuFEx) click chemistry employing alkyl sulfonyl fluorides with γ-S as the activating group. The ChB-activated alkyl sulfonyl fluorides can react smoothly with phenols, alcohols, and amines, exhibiting enhanced reactivity compared to SO2F2. Excellent yields have been achieved with all 75 tested substrates. Pioneering the application of S-SuFEx chemistry, we highlight its immense potential in organic-inorganic linking, considering the critical role of interfacial covalent bonding in material fabrication. The S-SuFEx hub 1c, incorporating a trialkoxy silane group has been specifically designed and synthesized for organic-inorganic linking. In a simple step, 1c efficiently anchors various organic compounds onto surfaces of inorganic materials, forming functionalized surfaces with properties such as antibacterial activity, hydrophobicity, and fluorescence.

Abstract Ferroelectrics as emerging and attractive catalysts have shown tremendous potential for applications including wastewater treatment, hydrogen production, nitrogen fixation, and organic synthesis, etc. In this study, we demonstrate that molecular ferroelectric crystal TMCM-CdCl3 (TMCM = trimethylchloromethylammonium) with multiaxial ferroelectricity and superior piezoelectricity has an effective catalytic activity on the direct construction of the pharmacologically important substituted quinoline derivatives via one-pot [3 + 2 + 1] annulation of anilines and terminal alkynes by using N,N-dimethylformamide (DMF) as the carbon source. The recrystallized TMCM-CdCl3 crystals from DMF remain well ferroelectricity and piezoelectricity. Upon ultrasonic condition, periodic changes in polarization contribute to the release of free charges from the surface of the ferroelectric domains in nano size, which then quickly interacts with the substrates in the solution to trigger the pivotal redox process. Our work advances the molecular ferroelectric crystal as a catalytic route to organic synthesis, not only providing valuable direction for molecular ferroelectrics but also further enriching the executable range of ferroelectric catalysis.

Abstract Demyelination is a common pathological feature in a wide range of diseases, characterized by the loss of myelin sheath and myelin-supporting oligodendrocytes. These losses lead to impaired axonal function, increased vulnerability of axons to damage, and result in significant brain atrophy and neuro-axonal degeneration. Multiple pathomolecular processes contribute to neuroinflammation, oligodendrocyte cell death, and progressive neuronal dysfunction. In this study, we use the cuprizone mouse model of demyelination to investigate long-term non-invasive gamma entrainment using sensory stimulation as a potential therapeutic intervention for promoting myelination and reducing neuroinflammation in male mice. Here, we show that multisensory gamma stimulation mitigates demyelination, promotes oligodendrogenesis, preserves functional integrity and synaptic plasticity, attenuates oligodendrocyte ferroptosis-induced cell death, and reduces brain inflammation. Thus, the protective effects of multisensory gamma stimulation on myelin and anti-neuroinflammatory properties support its potential as a therapeutic approach for demyelinating disorders.

Abstract The skeleton has been suggested to function as an endocrine organ controlling whole organism energy balance, however the mediators of this effect and their molecular links remain unclear. Here, utilizing Schnurri-3−/− (Shn3 −/− ) mice with augmented osteoblast activity, we show Shn3 −/− mice display resistance against diet-induced obesity and enhanced white adipose tissue (WAT) browning. Conditional deletion of Shn3 in osteoblasts but not adipocytes recapitulates lean phenotype of Shn3 −/− mice, indicating this phenotype is driven by skeleton. We further demonstrate osteoblasts lacking Shn3 can secrete cytokines to promote WAT browning. Among them, we identify a C-terminal fragment of SLIT2 (SLIT2-C), primarily secreted by osteoblasts, as a Shn3-regulated osteokine that mediates WAT browning. Lastly, AAV-mediated Shn3 silencing phenocopies the lean phenotype and augmented glucose metabolism. Altogether, our findings establish a novel bone-fat signaling axis via SHN3 regulated SLIT2-C production in osteoblasts, offering a potential therapeutic target to address both osteoporosis and metabolic syndrome.

Closely related chewing lice in the Philopterus-complex are typically morphologically homogeneous, with the most significant differences often being in the male genitalia. However, in many groups within this complex the male genitalia are reduced and lacking one or more element, with the remaining components often at least partially fused. This is not least the case in the genus Philopteroides Mey, 2004, in which the male mesosome is often reduced and other characters are largely homogeneous throughout the genus. A phylogeny of the group based on a combination of mitochondrial and nuclear genes suggests that the species presently placed in Philopteroides belong to three different clades, which do not form a monophyletic group together. We here redefine Philopteroides morphologically, and describe two of these clades as new genera: Stasiasticopterus n. gen. for the species on bulbuls, and Coronedax n. gen. for species on monarch flycatchers. These genera can be separated from each other and from Philopteroides only by some characters of the male genitalia, but possibly also by characters of the preantennal head and female genitalia. In addition, we describe a new species of Coronedax, Coronedax longiceps sp. n. and provide an overview of the morphology of the male genitalia in the three genera treated.

Abstract The Dunhuang murals, a significant part of Chinese heritage, have suffered deterioration primarily due to environmental and chemical factors, notably salt damage. This study proposes a sophisticated method that synergizes Fractional Order Differentiation (FOD) and Partial Least Squares Regression (PLSR) to accurately invert the phosphate content in the mural plaster of the Dunhuang paintings. The focal points of the research include: (1) To address the issue of information loss and reduced modeling precision caused by integer-order differentiation algorithms, the FOD method is employed for preprocessing spectral data. This approach ensures the fine spectral differences in the phosphate content of the mural plaster are precisely captured, (2) Utilizing PLSR, the study models the spectral bands identified at a significance level of 0.01 with measured conductivity values, thereby enabling the precise prediction of the phosphate content in the murals. The research outcomes reveal: (1) The FOD method can elucidate the nonlinear characteristics and variation patterns of the mural samples in the spectral data. As the order increases from zero to two, the number of spectral bands meeting the 0.01 significance test initially decreases and then increases. The highest absolute value of the positive correlation coefficient is observed at the 1.9 order, corresponding to the 2077 nm band, (2) For predicting the phosphate content in the murals, the model at the 1.9 order is most suitable for inversion. This model, after cross-validation, achieves a maximum R2 value of 0.861. This study created an efficient FOD-based model for estimating phosphate in mural plaster.

Abstract With the development of wireless communication technology, Ultra-Wideband (UWB) has become an important solution for indoor positioning. In complex indoor environments, the influence of non-line-of-sight (NLOS) factors leads to increased positioning errors. To improve the positioning accuracy, fuzzy iterative self-organizing data analysis clustering algorithm (ISODATA) is introduced to process a large amount of UWB data to reduce the influence of NLOS factors, and to stabilize positioning error within 2 cm, enhances the accuracy of the positioning system. To further improve the running efficiency of the algorithm, FPGA is used to accelerate the key computational part of the algorithm, compared with running on the MATLAB platform, which improves the speed about 100 times, enhances the algorithm’s computational speed dramatically.

Abstract The precise forecasting of air quality is of great significance as an integral component of early warning systems. This remains a formidable challenge owing to the limited information of emission source and the considerable uncertainties inherent in dynamic processes. To improve the accuracy of air quality forecasting, this work proposes a new spatiotemporal hybrid deep learning model based on variational mode decomposition (VMD), graph attention networks (GAT) and bi-directional long short-term memory (BiLSTM), referred to as VMD–GAT–BiLSTM, for air quality forecasting. The proposed model initially employ a VMD to decompose original PM2.5 data into a series of relatively stable sub-sequences, thus reducing the influence of unknown factors on model prediction capabilities. For each sub-sequence, a GAT is then designed to explore deep spatial relationships among different monitoring stations. Next, a BiLSTM is utilized to learn the temporal features of each decomposed sub-sequence. Finally, the forecasting results of each decomposed sub-sequence are aggregated and summed as the final air quality prediction results. Experiment results on the collected Beijing air quality dataset show that the proposed model presents superior performance to other used methods on both short-term and long-term air quality forecasting tasks.

Abstract Disasters caused by mine water inflows significantly threaten the safety of coal mining operations. Deep mining complicates the acquisition of hydrogeological parameters, the mechanics of water inrush, and the prediction of sudden changes in mine water inflow. Traditional models and singular machine learning approaches often fail to accurately forecast abrupt shifts in mine water inflows. This study introduces a novel coupled decomposition-optimization-deep learning model that integrates Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN), Northern Goshawk Optimization (NGO), and Long Short-Term Memory (LSTM) networks. We evaluate three types of mine water inflow forecasting methods: a singular time series prediction model, a decomposition-prediction coupled model, and a decomposition-optimization-prediction coupled model, assessing their ability to capture sudden changes in data trends and their prediction accuracy. Results show that the singular prediction model is optimal with a sliding input step of 3 and a maximum of 400 epochs. Compared to the CEEMDAN-LSTM model, the CEEMDAN-NGO-LSTM model demonstrates superior performance in predicting local extreme shifts in mine water inflow volumes. Specifically, the CEEMDAN-NGO-LSTM model achieves scores of 96.578 in MAE, 1.471% in MAPE, 122.143 in RMSE, and 0.958 in NSE, representing average performance improvements of 44.950% and 19.400% over the LSTM model and CEEMDAN-LSTM model, respectively. Additionally, this model provides the most accurate predictions of mine water inflow volumes over the next five days. Therefore, the decomposition-optimization-prediction coupled model presents a novel technical solution for the safety monitoring of smart mines, offering significant theoretical and practical value for ensuring safe mining operations.

Abstract With regard to deep mining in metal mines, an investigation into the failure mode of deep fractured rock masses and their corresponding acoustic emission signal characteristics is conducted via uniaxial compression tests. Subsequently, a fractal damage renormalization group mechanical model is developed to explain the behavior of those fractured rock masses. Employing the bonded block model (BBM) numerical simulation method, fracture process in synthetic rock samples is analyzed, thereby validating the efficacy of the mechanical model. The numerical simulations highlight the critical role of fractures expansion in underlying the deterioration of rock mass strength. As the peak load decreases, the fracture fractal dimension increases, leading to a significant 14.2% reduction in compressive strength accompanied by an approximate 8.7% rise in average fracture fractal dimension. A comparative analysis of tetrahedral and voronoi block synthetic rock samples reveals the tetrahedral block samples exhibit a superior ability to depict the fracture behavior of fractured rock masses. Specifically, they offer a more accurate simulation of acoustic emission characteristics and failure modes. Furthermore, variations in the fracture fractal dimension with respect to the hole defect’s position are observed, with the maximum value occurring along the vertical axis of the hole defect. This observation underscores the potential utility of visually monitoring deep rock fracture dynamics as an effective mean for quantitatively evaluating fracture damage and strength degradation in deep rock formations.

Abstract For the polarization multiplexing requirements in all-optical networks, this work presents a compact all-fiber polarization beam splitter (PBS) based on dual-core photonic crystal fiber (PCF) and an elliptical gold layer. Numerical analysis using the finite element method (FEM) demonstrates that the mode modulation effect of the central gold layer effectively reduces the dimensions of the proposed PBS. By determining reasonable structural parameters of the proposed PCF, the coupling length ratio (CLR) between X- and Y-polarized super-modes can approach 2, achieving a minimal device length of 0.122 mm. The PBS exhibits a maximum extinction ratio (ER) of − 65 dB at 1.55 μm, with an operating bandwidth spanning 100 nm (1.5–1.6 μm) and a stable insertion loss (IL) of ~ 1.5 dB at 1.55 μm. Furthermore, the manufacture feasibility and performance verification scheme are also investigated. It is widely anticipated that the designed PBS will play a crucial role in the ongoing development process of miniaturization and integration of photonic devices.

Abstract The eyes provide insights into psychology, potentially offering a distinctive perspective for psychological health profiles. However, there exist a notable deficiency in datasets that simultaneously encompass eye features and psychological assessments. To address this gap, our study presents a dataset that included Fundus Photography, Psychological Assessment, Retina Characteristics, and Multimodal Imaging (FPRM). FPRM dataset comprise fundus images at different wavelengths (548 nm and 605 nm), image of oxygen saturation for the retina and 8 specific retinal vessels, videos of retinal blood flow and pupillary light reflex, along with 61 items of multimodal quantitative measurement from 384 participants. Additionally, it features psychological assessments across five dimensions (geriatric depression, generalized anxiety disorder, insomnia, activities of daily living, and deterioration), accompanied by fundus photographs and 6 items of retina characteristics from 1683 participants. FPRM dataset is the first to integrate multimodal ophthalmic data and psychological assessments, not only advancing the development of machine learning applications but also facilitating in-depth research into the relationship between eye health and psychological health profiles.

In the design of photoharvesting and photoresponsive supramolecular systems in aqueous medium, the fabrication of amphiphilic photoswitches enables a noninvasive functional response through photoirradiation. Although most aqueous supramolecular assemblies are driven by high-energy and biodamaging UV light, we have previously reported a design of amphiphilic donor–acceptor Stenhouse adducts (DASAs) controlled by white light. Herein, we present a series of DASA amphiphiles (DAs) with minor structural modifications on the alkyl linker chain length connecting the DASA motif with the hydrophilic moiety. The excellent photoswitchability in organic medium and the photoresponsiveness in aqueous medium, driven by visible light, were investigated by UV–vis absorption spectroscopy. The assembled supramolecular nanostructures were confirmed by electron microscopy, while the supramolecular packing was revealed by X-ray diffraction analysis. Upon visible-light irradiation, significant transformations of the DA geometry enabled transformations of the supramolecular assemblies on a microscopic scale, subsequently disassembling macroscopic soft scaffolds of DAs. The current work shows promising use for the fabrication of visible-light-controlled macroscopic scaffolds, offering the next generation of biomedical materials with visible-light-controlled microenvironments and future soft-robotic systems.

Abstract The utilization of high-risk test cases constitutes an effective approach to enhance the safety testing of autonomous vehicles (AVs) and enhance their efficiency. This research paper presents a derivation of 2052 high-hazard pre-crash scenarios for testing autonomous driving, which were based on 23 high-hazard cut-in accident scenarios from the National Automobile Accident In-Depth Investigation System (NAIS) through combining importance sampling and combined testing methods. Compared to the direct combination of the original distribution after sampling, the proposed method has a 2.92 times higher crash rate of 69.32% for the test case set in this paper. It also has a 5.8 times higher rate of triggering Automatic Emergency Braking (AEB), improving hazardous scenario coverage. Using the proposed method, the generated parameters of the cut-in accident scenario test set were compared with those of the cut-in test scenarios included in existing Chinese autonomous driving test protocols and standards. The velocity of the ego-vehicle obtained using the proposed method matched those in the existing protocols, whereas the velocity, time gap, and time to collision of the target vehicle were significantly lower than those existing protocols indicating scenarios obtained from accident data can enrich the selection of testing scenarios for autonomous driving.

Abstract The supply chain for prefabricated buildings (PB) currently grapples with pressing challenges. In order to ensure the safe and stable development of the prefabricated building supply chains (PBSC), this study aims to identify the key factors and internal mechanisms affecting the PBSC, and propose a supply chain resilience enhancement mechanism, so as to promote the sustainable development of the PB industry. The study combined a literature review and survey data to identify key resilience factors in PBSC. A Structural Equation Model (SEM) was used to explore the relationships between these factors. System dynamics were applied to create a simulation model, assessing the resilience impact level and conducting sensitivity analysis. The results show that the transportation and procurement processes are the most significant factors influencing supply chain resilience. The external environmental factors wielded a more pronounced impact on the overall evaluation of supply chain resilience than the delivery and use processes, but delivery and use processes are more sensitive. The study uses the Pressure-State-Response (PSR) model to suggest strategies for enhancing supply chain resilience. This study contributes to more sustainable and efficient construction practices by offering an innovative theoretical framework to analyze the factors influencing PBSC resilience and proposing enhancement strategies.

Abstract How to accurately assess logistics industry efficiency to identify production issues and provide support for optimizing logistics efficiency has become a current research challenge. Range adjust measure (RAM) is a method for efficiency assessment in data envelopment analysis. Currently, the RAM model only applies under the variable returns to scale condition and not to other conditions. This paper aims to establish a modified RAM (MRAM) model by revising the ranges for inputs and outputs of the RAM model. Under the constant returns to scale (CRS) condition, we first develop the RAM-CRS model. Then, by introducing radial models to define the lower bounds of inputs and the upper bounds of outputs, the MRAM is proposed. The logistics data from 18 provinces are collected to validate the practicality of the MRAM model. We compare the results of the MRAM with those of the RAM-CRS and conclude that the range bounds under RAM-CRS are too tight, which results in efficiency values at a relatively low level. The MRAM with modified bounds appropriately alleviates this restriction. We also compare the MRAM and the additive model. The results show that the efficiency of the MRAM is more accurate.

Abstract In plants, the conserved plant-specific photoreceptor UV RESISTANCE LOCUS 8 (UVR8) perceives ultraviolet-B (UV-B) light and mediates UV-B-induced photomorphogenesis and stress acclimation. In this study, we reveal that UV-B light treatment shortens seedlings, increases stem thickness, and enhances UV-B stress tolerance in rice (Oryza sativa) via its two UV-B photoreceptors OsUVR8a and OsUVR8b. Although the rice and Arabidopsis (Arabidopsis thaliana) UVR8 (AtUVR8) photoreceptors all form monomers in response to UV-B light, OsUVR8a, and OsUVR8b function is only partially conserved with respect to AtUVR8 in UV-B-induced photomorphogenesis and stress acclimation. UV-B light and CONSTITUTIVELY PHOTOMORPHOGENIC 1 (COP1) promote the nuclear accumulation of AtUVR8; by contrast, OsUVR8a and OsUVR8b constitutively localize to the nucleus via their own nuclear localization signals, independently of UV-B light and the RING-finger mutation of OsCOP1. We show that OsCOP1 negatively regulates UV-B responses, and shows weak interaction with OsUVR8s, which is ascribed to the N terminus of OsCOP1, which is conserved in several monocots. Furthermore, transcriptome analysis demonstrates that UV-B-responsive gene expression differs globally between Arabidopsis and rice, illuminating the evolutionary divergence of UV-B light signaling pathways between monocot and dicot plants.

Abstract DNA base editing technologies predominantly utilize engineered deaminases, limiting their ability to edit thymine and guanine directly. In this study, we successfully achieve base editing of both cytidine and thymine by leveraging the translesion DNA synthesis pathway through the engineering of uracil-DNA glycosylase (UNG). Employing structure-based rational design, exploration of homologous proteins, and mutation screening, we identify a Deinococcus radiodurans UNG mutant capable of effectively editing thymine. When fused with the nickase Cas9, the engineered DrUNG protein facilitates efficient thymine base editing at endogenous sites, achieving editing efficiencies up to 55% without enrichment and exhibiting minimal cellular toxicity. This thymine base editor (TBE) exhibits high editing specificity and significantly restores IDUA enzyme activity in cells derived from patients with Hurler syndrome. TBEs represent efficient, specific, and low-toxicity approaches to base editing with potential applications in treating relevant diseases.

Abstract Carbon materials with defect-rich structure are highly demanded for various electrochemical scenes, but encountering a conflict with the deteriorative intrinsic conductivity. Herein, we build a highway-mediated nanoarchitecture that consists of the ordered pseudographitic nanodomains among disordered highly nitrogen-doped segments through a supramolecular self-assembly strategy. The “order-in-disorder” nanosheet-like carbon obtained at 800 °C (O/D NSLC-800) achieves a tradeoff with high defect degree (21.9 at% of doped nitrogen) and compensated electrical conductivity simultaneously. As expected, symmetrical O/D NSLC-800 electrodes exhibit superior capacitive deionization (CDI) performance, including brackish water desalination (≈82 mgNaCl g−1 at a cell voltage of 1.6 V in a 1000 mg L−1 NaCl solution) and reusage of actual refining circulating cooling water, outperforming most of the reported state-of-the-art CDI electrodes. The implanted pseudographitic nanodomains lower the resistance and activation energy of charge transfer, which motivates the synergy of hosting sites of multiple nitrogen configurations. Our findings shed light on electrically conductive nanoarchitecture design of defect-rich materials for advanced electrochemical applications based on molecular-level modulation.

Abstract As we know, valley-Hall kink states or pseudospin helical edge states are excited by polarized-momentum-locking [left-handed circular polarization (LCP) and right-handed circular polarization (RCP)] because the valley-Hall kink modes or pseudospin polarized modes have intrinsic and local chirality, which is difficult for these states to achieve phase modulation. Here we theoretically design and study a compatible topological photonic system with coexistence of photonic quantum Hall phase and pseudospin Hall phase, which is composed of gyromagnetic photonic crystals with a deformed honeycomb lattice containing six cylinders. A typical kind of hybrid topological waveguide states with pseudospin-characteristic, magnetic field-dependent, and strong robustness against backscattering and perfect electric conductor (PEC) is realized in the present system. Furthermore, we re-design a structure with intersection-liked, achieve splitting for one-way pseudospin quantum Hall edge states by using phase modulation. Robustness of the one-way pseudospin-quantum Hall edge states in splitting has been demonstrated as well. Additionally, PEC inserted in transport channel brings optical path difference in waveguide transmission, which would influence splitting for hybrid topological waveguide states in phase difference modulation. This work not only provides a new way for manipulation (i.e., phase modulation) of hybrid topological waveguide states in compatible topological photonic system from distinct topological classes but also has potential in various applications, such as sensing, signal processing, and on-chip communications.

Abstract Lipid peroxidation and mitochondrial damage impair insulin sensitivity in skeletal muscle. Sirtuin-1 (SIRT1) protects mitochondria and activates under energy restriction. Dapagliflozin (Dapa) is an antihyperglycaemic agent that belongs to the sodium-glucose cotransporter-2 (SGLT2) inhibitors. Evidence shows that Dapa can induce nutrient deprivation effects, providing additional metabolic benefits. This study investigates whether Dapa can trigger nutrient deprivation to activate SIRT1 and enhance insulin sensitivity in skeletal muscle. We treated diet-induced obese (DIO) mice with Dapa and measured metabolic parameters, lipid accumulation, oxidative stress, mitochondrial function, and glucose utilization in skeletal muscle. β-hydroxybutyric acid (β-HB) was intervened in C2C12 myotubes. The role of SIRT1 was verified by RNA interference. We found that Dapa treatment induced nutrient deprivation state and reduced lipid deposition and oxidative stress, improved mitochondrial function and glucose tolerance in skeletal muscle. The same positive effects were observed after β-HB intervening for C2C12 myotubes, and the promoting effects on glucose utilization were diminished by SIRT1 RNA interference. Thus, Dapa promotes a nutrient deprivation state and enhances skeletal muscle insulin sensitivity via SIRT1 activation. In this study, we identified a novel hypoglycemic mechanism of Dapa and the potential mechanistic targets.