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Summary: Despite substantial lignocellulose conversion during mycelial growth, previous transcriptome and proteome studies have not yet revealed how secretomes from the edible mushroom Agaricus bisporus develop and whether they modify lignin models in vitro. To clarify these aspects, A. bisporus secretomes collected throughout a 15-day industrial substrate production and from axenic lab-cultures were subjected to proteomics, and tested on polysaccharides and lignin models. Secretomes (day 6–15) comprised A. bisporus endo-acting and substituent-removing glycoside hydrolases, whereas β-xylosidase and glucosidase activities gradually decreased. Laccases appeared from day 6 onwards. From day 10 onwards, many oxidoreductases were found, with numerous multicopper oxidases (MCO), aryl alcohol oxidases (AAO), glyoxal oxidases (GLOX), a manganese peroxidase (MnP), and unspecific peroxygenases (UPO). Secretomes modified dimeric lignin models, thereby catalyzing syringylglycerol-β-guaiacyl ether (SBG) cleavage, guaiacylglycerol-β-guaiacyl ether (GBG) polymerization, and non-phenolic veratrylglycerol-β-guaiacyl ether (VBG) oxidation. We explored A. bisporus secretomes and insights obtained can help to better understand biomass valorization.

Summary: Niemann-Pick disease type C (NP-C) is a genetic lysosomal disorder associated with progressive neurodegenerative phenotypes. Its therapeutic options are very limited. Here, we show that lithium treatment improves ataxia and feeding phenotypes, attenuates cerebellar inflammation and degeneration, and extends survival in Npc1 mouse models. In addition, lithium suppresses STING activation, SREBP2 processing to its mature form and the expression of the target genes in the Npc1 mice and in Npc1-deficient fibroblasts. Lithium impedes STING/SREBP2 transport from the ER to the Golgi, a step required for STING activation and SREBP2 processing, probably by lowering cytosolic calcium concentrations. This effect of lithium on STING/SREBP2 transport provides a mechanistic explanation for lithium’s effects on Npc1 mice. Thus, this study reveals a potential therapeutic option for NP-C patients as well as a strategy to reduce active STING/SREBP2 pathway.

Summary: Efficient utilization of agro-industrial waste, such as sugar beet pulp, is crucial for the bio-based economy. The fungus Aspergillus niger possesses a wide array of enzymes that degrade complex plant biomass substrates, and several regulators have been reported to play a role in their production. The role of the regulators GaaR, AraR, and RhaR in sugar beet pectin degradation has previously been reported. However, genetic regulation of the degradation of sugar beet pulp has not been assessed in detail. In this study, we generated a set of single and combinatorial deletion mutants targeting the pectinolytic regulators GaaR, AraR, RhaR, and GalX as well as the (hemi-)cellulolytic regulators XlnR and ClrB to address their relative contribution to the utilization of sugar beet pulp. We show that A. niger has a flexible regulatory network, adapting to the utilization of (hemi-)cellulose at early timepoints when pectin degradation is impaired.

Reservoir facies modeling is an important way to express the sedimentary characteristics of the target area. Conventional deterministic modeling, target-based stochastic simulation, and two-point geostatistical stochastic modeling methods are difficult to characterize the complex sedimentary microfacies structure. Multi-point geostatistics (MPG) method can learn a priori geological model and can realize multi-point correlation simulation in space, while deep neural network can express nonlinear relationship well. This article comprehensively utilizes the advantages of the two to try to optimize the multi-point geostatistical reservoir facies modeling algorithm based on the Deep Forward Neural Network (DFNN). Through the optimization design of the multi-grid training data organization form and repeated simulation of grid nodes, the simulation results of diverse modeling algorithm parameters, data conditions and deposition types of sedimentary microfacies models were compared. The results show that by optimizing the organization of multi-grid training data and repeated simulation of nodes, it is easier to obtain a random simulation close to the real target, and the simulation of sedimentary microfacies of different scales and different sedimentary types can be performed.

Abstract Despite the advances in antibody-guided cell typing and mass spectrometry-based proteomics, their integration is hindered by challenges for processing rare cells in the heterogeneous tissue context. Here, we introduce Spatial and Cell-type Proteomics (SCPro), which combines multiplexed imaging and flow cytometry with ion exchange-based protein aggregation capture technology to characterize spatial proteome heterogeneity with single-cell resolution. The SCPro is employed to explore the pancreatic tumor microenvironment and reveals the spatial alternations of over 5000 proteins by automatically dissecting up to 100 single cells guided by multi-color imaging of centimeter-scale formalin-fixed, paraffin-embedded tissue slide. To enhance cell-type resolution, we characterize the proteome of 14 different cell types by sorting up to 1000 cells from the same tumor, which allows us to deconvolute the spatial distribution of immune cell subtypes and leads to the discovery of subtypes of regulatory T cells. Together, the SCPro provides a multimodal spatial proteomics approach for profiling tissue proteome heterogeneity.

Abstract Patients who develop chimeric antigen receptor (CAR) T-cell-related immune effector cell-associated neurotoxicity syndrome (ICANS) frequently undergo evaluation with electroencephalography (EEG). We hypothesize that EEG features and Synek scale score, a measure of degree of EEG abnormality, are associated with ICANS severity. Here, we performed a retrospective review of 125 adult patients at Memorial Sloan Kettering Cancer Center (MSKCC) who received CAR-T cell therapy from 2010 to 2019, including 53 patients with B-acute lymphoblastic leukemia treated with 1928z CAR T cells (NCT01044069) and 72 patients with large B-cell lymphoma (LBCL) treated with the commercial CAR T products axicabtagene ciloleucel or tisagenlecleucel. We collected video EEG monitoring (27 with B-ALL and 20 with LBCL) and recorded daily EEG features, Synek scores, and ICANS grade for 47 eligible patients. Synek scale and ICANS grade were positively correlated (correlation coefficient 0.47, 95% CI: 0.31–0.60). This was further corroborated in the univariable model associating high Synek scale (3 or 4) with high ICANS grade (OR = 15.2; 95%CI:7.8–29.7, p

Abstract Percutaneous kyphoplasty (PKP) is an effective, minimally invasive treatment for Kummell’s disease, but challenges like cement leakage, fracture, and displacement remain. This study explores the use of PKP with a mesh-hold bone filling container for this disease.A retrospective analysis was conducted on nine Kummell’s disease cases treated with this technique at a spinal surgery department from June 2016 to May 2022. Pre- and postoperative evaluations included X-rays, CT scans, and 3D reconstructions. Parameters like vertebral heights, kyphotic angle, operation time, blood loss, and bone cement issues were measured. Efficacy was assessed using ODI and VAS scores.Statistical analysis showed no significant difference in posterior vertebral height before and after treatment. All other indexes improved significantly postoperatively and at follow-up. No cement leakage or displacement occurred.PKP with a mesh-hold bone filling container is a promising treatment for Kummell’s disease. It enhances reduction quality, ensures adequate bone cement filling, and reduces issues related to cement leakage, fracture, and displacement.

Abstract Multiple myeloma (MM) is a hematological malignancy characterized by the unrestricted proliferation of plasma cells that secrete immunoglobulin in the bone marrow. Extracted primarily from Anemone raddeana regel, Raddeanin A (RA) is a natural triterpenoid saponin compound with anti-inflammatory and anti-tumor activities. However, most research on the anti-tumor effects of RA has concentrated on solid tumors, with little exploration into non-solid tumors like MM. Furthermore, there is a dearth of research investigating the interplay between RA and MM, encompassing their interaction targets and mechanisms. This study aims to delve into the biological activity and molecular mechanism of RA’s anti-MM properties through the lens of network pharmacology and experimental validation. The findings from GO enrichment analysis, KEGG enrichment analysis, and molecular docking prediction suggested a potential correlation between the MAPK signaling pathway, including the MAPK1 gene (also known as ERK2), and the impact of RA on MM. Results from the CCK-8 assay revealed a time-dependent and concentration-dependent inhibition of proliferation in MM cell lines treated with RA. Notably, in the cell lines used for the test, the IC50 values for MM.1 S cells were 1.616 µM at 24 H and 1.058 µM at 48 H, for MM.1R cells were 3.905 µM at 24 H and 2.18 µM at 48 H, while for RPMI 8226 cells, they were 6.091 µM at 24 H and 3.438 µM at 48 H. The PI, Annexin V-FITC/PI, and JC-1 staining showed that RA could arrest the cell cycle in the G2 phase, cause apoptosis, and induce the change of mitochondrial membrane potential (MMP) in MM cells. Treated with RA, the Western blot analysis showed that the expression levels of Bim, Cleaved Caspase 3/9, and Cleaved PARP were increased, and the expression level of Mcl-1 was decreased in MM cells. Concurrently, the phosphorylated protein expression levels of p-ERK1/2, p-MSK1, p-P90RSK, and p-MEK1/2 were diminished following RA treatment. These results suggest that RA has the activity of anti-MM, and the MAPK/ERK signaling pathway is involved in the growth inhibition effect of RA on MM cells via cycle arrest and mitochondrial-pathway-dependent apoptosis.

Abstract The gamut and EOTF (Electro-Optical Transfer Function) of a display together determine its color performance. Gamut determines the range of displayable colors, and the EOTF determines the color accuracy and depth. Image reproduction often comprises two parts: the image source and the display terminal. To ensure the universality of different terminals, the image source is generally produced in a standardized gamut standard, while the terminal pursues a wider gamut and more spectacular color performance. As a widely welcomed form of display, WCGDs (Wide Color Gamut Displays) boast stunning color performance. However, certain colors in WCGDs displays are oversaturated, which is unacceptable to the human eye. This paper analyzes the oversaturation problem of WCGDs. Firstly, a display model based on EOTF and gamut parameters is established. Then the color point vector field varies with EOTF is derived and the drift of luminance and chromaticity are analyzed separately. Finally, two strategies are present to optimize the color oversaturation problem of WCGDs based on the analysis conclusions and verify its effectiveness. This paper presents a detailed analysis and possible strategy for color oversaturation in WCGDs, providing a theoretical basis for the accurate color reproduction and efficient color management of WCGDs.

Abstract Accurate and efficient detection and segmentation of the urine formed element plays a vital role in the clinical diagnosis and treatment of many diseases, such as urinary system diseases, kidney diseases, and other diseases. However, artificial microscopy is subjective, and time- consuming. The mainstream detection and instance segmentation algorithms lack adequate accuracy and speed for the urine formed element due to small and dense targets. Therefore, this study proposes a quick one-stage urine formed element instance segmentation model based on YOLOv5n. The approach first employs a backbone architecture to extract features named shallow graphical features and semantic features from urine cells. Next, the neck network combines shallow graphical features with different deep semantic features, obtaining multi-scale, and multi-level features. Finally, according to these multi-level features, the head network of YOLOv5n integrates a small FCN network into the YOLOv5 detector. It obtains the location, classification, and segmentation results of the targets. To validate the superiority of this approach in terms of speed and accuracy, a special urine formed element dataset including 500 images was created. Experimental results show that the YOLOv5n method achieves a Mean Average Precision (mAP) at intersection over the union threshold of 0.5 (mAP50) with 91.8%, and Frames Per Second (FPS) of 63.3. Compared to Mask R-CNN and YOLOv8, its FPS increased by 62.6 and 60.9, respectively, resulting in nearly a hundred-fold speedup, and its mAP50 also increased by 3.6 and 1.4% points in accuracy, respectively. Additionally, the YOLOv5n obtains a superior balance of accuracy and speed in comparisons with SOLOv2, BoxInst, and ConvNeXt V2. This study developed a new automated analysis of urinary particles based on deep learning, and this method is expected to be used for the automated analysis and detection of the urine formed element. The experimental results also demonstrate that YOLOv5n can achieve more accurate and faster instance segmentation of urine formed element, providing technical support for clinical disease diagnosis.

Abstract Organ/space surgical site infection (SSI) are common after pancreaticoduodenectomy (PD). There is limited research on the clinical impact of intraoperative lavage fluid contamination in patients undergoing PD. One hundred five patients who underwent PD between August 2022 and July 2023 were retrospectively enrolled. The intraoperative bile and peritoneal lavage were collected for bacterial culture. Postoperative drainage bacterial cultures were performed every 2–3 days thereafter until drains were all removed. The bacteria isolated from intraoperative lavage fluid, intraoperative bile, and postoperative drainage fluid were examined in detail. The risk factors associated with positive intraoperative lavage fluid culture were analyzed through both univariate and multivariate analyses. Organ/space SSI occurred in 59(56.2%) of the 105 patients. The positivity rates of cultures in intraoperative lavage fluid, intraoperative bile, and postoperative drainage fluid were found to be 41.0%, 67.6%, and 84.8%, respectively. Patients with positive intraoperative lavage fluid culture had a significantly higher occurrence of organ/space SSI compared to the negative group (69.0% vs. 29.4%, P

Abstract Somatic variations can give rise to bud sports with advantageous traits, serving as the foundation for bud sport breeding in perennial plants. Here, we report a fully phased genome assembly of ‘Fuji’ apple, enabling comprehensive identification of somatic variants across 74 clonally propagated ‘Fuji’ varieties. Phylogenetic analysis indicates that spur-type and early-maturation traits in ‘Fuji’ sport varieties arise from multiple independent events. Several putative functional somatic variants have been identified, including a spur-type-specific deletion in the promoter of the TCP transcription factor gene MdTCP11. DNA methylation level of the deletion-associated miniature inverted-repeat transposable element is lower in spur-type varieties compared to standard-type varieties, while the expression of MdTCP11 is significantly higher. Overexpression of MdTCP11 in apple decreases plant height, highlighting its important role in the development of spur-type apple varieties. This study sheds light on the cloning history of ‘Fuji’ and provides valuable resources for apple breeding.

Abstract Gliomas exhibit high heterogeneity and poor prognosis. Despite substantial progress has been made at the genomic and transcriptomic levels, comprehensive proteomic characterization and its implications remain largely unexplored. In this study, we perform proteomic profiling of gliomas using 343 formalin-fixed and paraffin-embedded tumor samples and 53 normal-appearing brain samples from 188 patients, integrating these data with genomic panel information and clinical outcomes. The proteomic analysis uncovers two distinct subgroups: Subgroup 1, the metabolic neural subgroup, enriched in metabolic enzymes and neurotransmitter receptor proteins, and Subgroup 2, the immune subgroup, marked by upregulation of immune and inflammatory proteins. These proteomic subgroups show significant differences in prognosis, tumorigenesis, microenvironment dysregulation, and potential therapeutics, highlighting the critical roles of metabolic and immune processes in glioma biology and patient outcomes. Through a detailed investigation of metabolic pathways guided by our proteomic findings, dihydropyrimidine dehydrogenase (DPYD) and thymidine phosphorylase (TYMP) emerge as potential prognostic biomarkers linked to the reprogramming of nucleotide metabolism. Functional validation in patient-derived glioma stem cells and animal models highlights nucleotide metabolism as a promising therapy target for gliomas. This integrated multi-omics analysis introduces a proteomic classification for gliomas and identifies DPYD and TYMP as key metabolic biomarkers, offering insights into glioma pathogenesis and potential treatment strategies.

Abstract The transient voltage stability of modern power systems is challenged by the increasing uncertainty on source‐load dual sides. To cope with it, a robust optimal configuration method for dynamic VAR compensators (DVCs) is proposed. First, a series of power‐flow scenarios are generated with uncertainty and correlation considered, where nonparametric kernel density estimation is used to predict the marginal distribution of wind speeds and combined Copula function is employed to characterize correlations between nearby wind farms. Then, the variation‐of‐information indicator is introduced to assess the similarity among power‐flow (PF) scenarios, and representative PF (RPF) scenarios are screened with the help of Spectral clustering algorithm. Finally, locating and sizing of DVCs for RPF scenarios are achieved. By synthesizing the compensation schemes for RPF scenarios, the robust configuration scheme is suggested. Simulation studies in the modified New England 10‐machine 39‐bus system show the proposed method can ensure transient voltage security of the studied power system under source‐load uncertainty.

There are many heavy oil reservoirs in offshore oilfields in China. Steam and multiple thermal fluid stimulation technologies are of increasing interest and have been applied to an increasing number of projects. During the stimulation or displacement of heavy oil reservoirs during thermal recovery, several factors, such as reservoir heterogeneity, are prone to cause channeling phenomena and affect the thermal recovery effect of steam stimulation. According to the unique requirements for the stimulation of multiple thermal fluids for offshore heavy oil, this study used transmission, blocking and relieving, heat resistance and a comprehensive evaluation of parallel sand tube experiments to conduct a screening evaluation of plugging systems for the stimulation of multiple thermal fluids, screen out a commonly used plugging agent in the current stage and propose corresponding guidance for the selection basis. The results show that foam, gel, foam gel and temperature-sensitive gel systems have a good transmission performance, whereas the oil sludge exhibits a poorer performance. The phenolic resin system exhibits great plugging properties, followed by oily sludge, temperature-sensitive gel, gel, foam gel and foam. Considering about washing resistance properties, phenolic resin system shows the best quality, followed by oily sludge and temperature-sensitive gel. The oily sludge system brings the best performance in plugging a high-permeability channel than phenolic resin gel and temperature-sensitive gel.

Research on the modeling of rock mechanics parameters is of great significance to the exploration of oil and gas. The use of logging data with the Kriging interpolation to study rock mechanics parameters has been proven to be effective in reservoir prediction and other oilfield applications and can provide additional data. However, there will sometimes be a great deviation due to the limited samples and the strong heterogeneity of a layer. To solve this problem, a new approach was proposed to calibrate rock mechanical models through the statistical analysis of logging data. A module was developed to calibrate rock mechanics parameters automatically, which was then applied to the Wangyao area of the Ansai oilfield. This method significantly improved the accuracy of rock mechanics modeling.

Phage-derived peptidoglycan hydrolases (i.e. lysins) are considered promising alternatives to conventional antibiotics due to their direct peptidoglycan degradation activity and low risk of resistance development. The discovery of these enzymes is often hampered by the limited availability of phage genomes. Herein, we report a new strategy to mine active peptidoglycan hydrolases from bacterial proteomes by lysin-derived antimicrobial peptide-primed screening. As a proof-of-concept, five peptidoglycan hydrolases from the Acinetobacter baumannii proteome (PHAb7-PHAb11) were identified using PlyF307 lysin-derived peptide as a template. Among them, PHAb10 and PHAb11 showed potent bactericidal activity against multiple pathogens even after treatment at 100°C for 1 hr, while the other three were thermosensitive. We solved the crystal structures of PHAb8, PHAb10, and PHAb11 and unveiled that hyper-thermostable PHAb10 underwent a unique folding-refolding thermodynamic scheme mediated by a dimer-monomer transition, while thermosensitive PHAb8 formed a monomer. Two mouse models of bacterial infection further demonstrated the safety and efficacy of PHAb10. In conclusion, our antimicrobial peptide-primed strategy provides new clues for the discovery of promising antimicrobial drugs.

The submergence depth directly affects the safety of semi-submersible marine structures due to that the submergence depth significantly impacts on the hydrodynamic characteristics and wave loads of structures excited by extreme wave. This paper studies the influence of submergence depth on the hydrodynamic and wave load characteristics of semi-submersible structures by establishing a numerical model of the interaction between solitary waves and semi-submersible structures based on the SPH model and Rayleigh theory. Furthermore, equations for transmission coefficient, reflection coefficient, and wave load are fitted. The calculated wave heights of solitary wave propagation test case are in good agreement with the theoretical values. The maximum relative error of the wave peak is 8.4%. The calculated wave loads of submerged horizontal plates test case has a consistent trend with the experimental data. The maximum relative error of wave load peak and valley is 54% (absolute error 0.37 N). Furthermore, the interaction between solitary waves and structures with different submergence depths is investigated by using the meshless numerical model. It is found that the reflection coefficient first increases and then decreases with increasing submergence depth, and reaching a maximum value of 0.39 at the submergence depth equal to 0.0 m. On the contrary, the transmission coefficient decreases first and then increases with the increase of submergence depth. The minimum value of transmission coefficient is 0.36 with the submergence depth of 0.3 m. As the submergence depth increased, the horizontal wave load peak of the structure gradually increases, and the maximum value of 0.13 is obtained at the submergence depth of 0.7 m. The peak of vertical wave load rapidly increases with the increase of submergence depth and then gradually decreases while the trough gradually decreases with increasing submergence depth.

Tissue engineering has brought new possibilities for the treatment of spinal cord injury. Two important components for tissue engineering of the spinal cord include a suitable cell source and scaffold. In our study, we investigated induced mouse embryonic fibroblasts (MEFs) directly reprogrammed into neural stem cells (iNSCs), as a cell source. Three-dimensional (3D) electrospun poly (lactide-co-glycolide)/polyethylene glycol (PLGA-PEG) nanofiber scaffolds were used for iNSCs adhesion and growth. Cell growth, survival and proliferation on the scaffolds were investigated. Scanning electron microscopy (SEM) and nuclei staining were used to assess cell growth on the scaffolds. Scaffolds with iNSCs were then transplanted into transected rat spinal cords. Two or 8 weeks following transplantation, immunofluorescence was performed to determine iNSC survival and differentiation within the scaffolds. Functional recovery was assessed using the Basso, Beattie, Bresnahan (BBB) Scale. Results indicated that iNSCs showed similar morphological features with wild-type neural stem cells (wt-NSCs), and expressed a variety of neural stem cell marker genes. Furthermore, iNSCs were shown to survive, with the ability to self-renew and undergo neural differentiation into neurons and glial cells within the 3D scaffolds in vivo. The iNSC-seeded scaffolds restored the continuity of the spinal cord and reduced cavity formation. Additionally, iNSC-seeded scaffolds contributed to functional recovery of the spinal cord. Therefore, PLGA-PEG scaffolds seeded with iNSCs may serve as promising supporting transplants for repairing spinal cord injury (SCI).

The sterile insect technique (SIT) stands as an eco-friendly approach for mosquito control, but it is impeded by the limited availability of γ-ray radiation source. This research sought to investigate a different radiation source—the Varian Clinac 23EX linear accelerator, which is frequently used for X-ray therapy in cancer treatment. Evaluation parameters including emergence rate, average survival time, induced sterility (IS), male mating competitiveness of irradiated males and fecundity (the number of eggs per female per batch), and the egg hatch rate of females mated with irradiated males were assessed to gauge the application potential of this cancer treatment equipment in the realm of the SIT. The results indicated that X-rays from radiation therapy equipment can effectively suppress the hatch rate of offspring mosquitoes without adversely affecting the emergence rate of irradiated males or the fecundity of females. In addition, at an X-ray dose of 60 Gy, the induced sterility in Ae. aegypti was comparable to the sterility induced by 40 Gy of γ-rays with both treatments resulting in 99.6% sterility. Interestingly, when a release ratio of 7:1 (irradiated males:unirradiated males) was used to competitively mate with females, the IS results resulted by 60 Gy X-rays and 40 Gy γ-rays were still at 70.3% and 73.7%, respectively. In conclusion, the results underscored the potential of the Varian Clinac 23EX linear accelerator as an X-ray source in SIT research.

The 7A04 Al alloy is a commonly used lightweight metal material; however, its low wear resistance limits its application. In this study, the wear resistance of this alloy was improved by preparing micro-arc oxidation (MAO) coatings, MAO/MoS2 composite coatings, and hard-anodized (HA) coatings on its surface. The friction and wear behaviors of these three coatings with diamond-like coated (DLC) rings under oil lubrication conditions were investigated using a ring–block friction tester. The wear rates of the coatings on the block surfaces were determined using laser confocal microscopy, and the wear trajectories of the coatings were examined using scanning electron microscopy. The results indicated that, among the three coatings, the MAO/MoS2 coating had the lowest coefficient of friction of 0.059, whereas the HA coating had the lowest wear rate of 1.47 × 10−6 mm/Nm. The MAO/MoS2 coatings exhibited excellent antifriction properties compared to the other coatings, whereas the HA coatings exhibited excellent anti-wear properties. The porous structure of the MAO coatings stored lubricant and replenished the lubrication film under oil lubrication. Meanwhile, the introduced MoS2 enhanced the densification of the coating and functioned as a solid lubricant. The HA coating exhibited good wear resistance owing to the dense structure of the amorphous-phase aluminum oxide. The mechanisms of abrasive and adhesive wear of the coatings under oil lubrication conditions and the optimization of the tribological properties by the solid–liquid synergistic lubrication effect were investigated. This study provides an effective method for the surface modification of Al alloys with potential applications in the aerospace and automotive industries.

The integration of ground-penetrating radar (GPR) with unmanned aerial vehicles (UAVs) enables efficient non-contact detection, performing exceptionally well in complex terrains and extreme environments. However, challenges in data processing and interpretation remain significant obstacles to fully utilizing this technology. To mitigate the effects of numerical dispersion, this paper develops a high-order finite-difference time-domain (FDTD(2,4)) three-dimensional code suitable for airborne GPR numerical simulations. The simulation results are compared with traditional FDTD methods, validating the accuracy of the proposed approach. Additionally, a Kirchhoff migration algorithm that considers the influence of the air layer is developed for airborne GPR. Different processing strategies are applied to flat and undulating terrain models, significantly improving the identification of shallowly buried targets. Particularly under undulating terrain conditions, the energy ratio method is introduced, effectively suppressing the interference of surface reflections caused by terrain variations. This innovative approach offers a new technical pathway for efficient GPR data processing in complex terrains. The study provides new insights and methods for the practical application of airborne GPR.

In the context of drought events caused by global warming, there is limited understanding of vegetation loss caused by drought and the subsequent recovery of vegetation after drought ends. However, employing a single index representing a specific vegetation characteristic to explore drought’s impact on vegetation may overlook vegetation features and introduce increased uncertainty. We applied the enhanced vegetation index (EVI), fraction of vegetation cover (FVC), gross primary production (GPP), leaf area index (LAI), and our constructed remote sensing vegetation index (RSVI) to assess vegetation drought in Central Asia. We analyzed the differences in drought experiences for different climatic regions and vegetation types and vegetation loss and recovery following drought events. The results indicate that during drought years (2012 and 2019), the differences in vegetation drought across climatic regions were considerable. The vegetation in arid, semiarid, and Mediterranean climate regions was more susceptible to drought. The different indices used to assess vegetation loss exhibited varying degrees of dynamic changes, with vegetation in a state of mild drought experiencing more significantly during drought events. The different vegetation assessment indices exhibited significant variations during the drought recovery periods (with a recovery period of 16 days: EVI of 85%, FVC of 50%, GPP of 84%, LAI of 61%, and RSVI of 44%). Moreover, the required recovery periods tended to decrease from arid to humid climates, influenced by both climate regions and vegetation types. Sensitivity analysis indicated that the primary climatic factors leading to vegetation loss varied depending on the assessment indices used. The proposed RSVI demonstrates high sensitivity, correlation, and interpretability to dry–wet variations and can be used to assess the impact of drought on vegetation. These findings are essential for water resource management and the implementation of measures that mitigate vegetation drought.

Transformer-based methods have demonstrated impressive performance in image super-resolution tasks. However, when applied to large-scale Earth observation images, the existing transformers encounter two significant challenges: (1) insufficient consideration of spatial correlation between adjacent ground objects; and (2) performance bottlenecks due to the underutilization of the upsample module. To address these issues, we propose a novel distance-enhanced strip attention transformer (DESAT). The DESAT integrates distance priors, easily obtainable from remote sensing images, into the strip window self-attention mechanism to capture spatial correlations more effectively. To further enhance the transfer of deep features into high-resolution outputs, we designed an attention-enhanced upsample block, which combines the pixel shuffle layer with an attention-based upsample branch implemented through the overlapping window self-attention mechanism. Additionally, to better simulate real-world scenarios, we constructed a new cross-sensor super-resolution dataset using Gaofen-6 satellite imagery. Extensive experiments on both simulated and real-world remote sensing datasets demonstrate that the DESAT outperforms state-of-the-art models by up to 1.17 dB along with superior qualitative results. Furthermore, the DESAT achieves more competitive performance in real-world tasks, effectively balancing spatial detail reconstruction and spectral transform, making it highly suitable for practical remote sensing super-resolution applications.

Citrus rust mites (Phyllocoptruta oleivora Ashmead) are a major pest in citrus orchards, significantly affecting fruit quality and yield. Effective management of these mites is crucial for maintaining the economic viability of citrus production. This study investigated the ecological distribution of citrus rust mites and their natural predator, A. largoensis, in a mandarin orchard in Zengcheng District, Guangzhou City, of China. This research focused on population densities across different orchard sections and assessed the impact of mite infestations on the biochemical composition of mandarins, including vitamin C, soluble solids, acidity, and mineral content. Results showed that citrus rust mite populations were highest in the southern and western sections of the orchard. Infested fruits had reduced vitamin C and soluble solids but increased acidity and calcium levels. A. largoensis exhibited a strong functional (Type II) and numerical response, with higher predation rates and reproductive output for moderate prey densities. The findings emphasize the importance of targeted pest management strategies in citrus rust mite hotspots and highlight A. largoensis as a promising biological control agent. Future research should optimize its use in integrated pest management programs by focusing on areas of the orchard with high mite densities.

Induced pluripotent stem cells (iPSCs) are of great clinical interest for they are derived from one’s own somatic cells and have the potential of committed differentiation without immunological rejection after autografting. However, the use of viral and other modified vectors may still cause tumorigenesis due to chromosome insertion mutation, leading to limited practical use. iPSCs generated by reprogramming proteins overcome the potential safety risk and complicated manipulation procedures, thus they own better application prospective, yet some technical difficulties need to be studied and resolved, for instance, low reprogramming efficiency, unclear transduction, and reprogramming mechanism. In this paper, we summarize the current progress of proteins reprogramming technology for generation of iPSCs and discuss the promising efficiency-improved reprogramming methods by proteins plus other kinds of chemical compounds.

As an essential dimension of economic inequality, consumption inequality is tightly associated with public welfare. This study investigates the effect of consumption inequality on individuals' subjective well-being (SWB) in China using data from the 2014, 2018, and 2020 China Family Panel Studies. The findings indicate that consumption inequality has a significant negative impact on SWB. Specifically, for every unit increase in consumption inequality, the probability of individuals rating their SWB as "Happy" and "Very happy" decreases by 0.37% and 5.45% respectively. In addition, individuals' confidence about their future serves as an intermediary in the connection between consumption inequality and SWB. The investigation of heterogeneity evidences that the adverse impact of consumption inequality on SWB is more pronounced in terms of subsistence and development expenditures. Consumption inequality affects SWB more seriously among lower-income and urban residents. Overall, this study holds important implications for addressing economic inequality to bolster individuals' welfare.

Abstract The improvement of heat transfer inside the solar heat exchangers is important for the development of solar energy in an urban area. In this study, the usage of a non-uniform magnetic field on the thermal efficiency of the nanofluid (Fe3O4) streaming inside the U-turn pipe of solar heat exchangers is examined. Computational fluid dynamic is applied to visualize the nanofluid flow inside the solar heat exchanger. The role of magnetic intensity and Reynolds number on thermal efficiency are fully investigated. The effect of single and triple sources of the magnetic field is also studied in our research. Obtained results indicate that the usage of the magnetic field results in the production of vortex in the base fluid and heat transfer improves inside the domain. Our finding indicates that the usage of the magnetic field with Mn = 25 K would improve the average heat transfer by about 21% along the U-turn pipe of solar heat exchangers.

Abstract A low concentration of Te4+ doping is found to be capable of endowing the lead‐free Cs2SnCl6 perovskites with excellent photoluminescence quantum yield (PLQY), while further increasing Te4+ concentration leads to PLQY deterioration. The mechanism behind the improved PLQY is intensively studied and reported elsewhere. However, little work is conducted to understand the decreased PLQY at high doping levels and to explore its implications for non‐PL‐related applications. Here, it is demonstrated that the Te4+‐incorporated Cs2SnCl6 can be promising candidate for efficient CO2 photocatalysis. An optimum photocatalytic performance is achieved when Te4+ concentration reaches as high as 50%, at which point significant PL quenching has occurred. Through a detailed spectral characterization, such concentration‐dependent functionality is attributed to systematic changes in both electronic and local crystal structure, which allow a robust regulation of excitation energy relaxation channels. These findings expand the scope of available photocatalysts for CO2 reduction and also inform synthetic planning for the preparation of multifunctional Pb‐free metal halide perovskites.

Scientific knowledge has been shown to be a key contributor to corporate technological innovation; hence, modern inventive firms place a strong emphasis on scientific research. However, little is known about how the knowledge linkage between science and technology (ST linkage) of corporations fosters their technological innovation. In an effort to fill this vacuum in the literature, we investigate how multiple properties of ST linkage influence corporate technological innovation. We conducted a Zero-inflated Negative Binomial regression using scientific publications, patents, and firm-level data from 671 pharmaceutical and 686 semiconductor corporations to test our hypotheses. We find that the higher the proportion of corporations citing their published scientific publications in patents, the more likely they are to produce more patents, and corporate technological innovation benefits from the utilization of scientific knowledge produced in the early stages. Furthermore, the positive effects of the aforementioned factors on the technological innovation performance of corporations are present in both scientific research strategies (e.g., independent vs. joint research). These findings contribute to the understanding of the underlying mechanism of corporate basic research facilitating technological innovation. This study also provides meaningful advice regarding how corporations can enhance their technological innovation through scientific research. • As corporations cite their scientific publications more in patents, they are likely to produce more patents. • Corporate technological innovation benefits from the utilization of scientific knowledge produced in the early stages. • The positive effects of the aforementioned factors on the technological innovation performance of corporations are present in both scientific research strategies (e.g., independent vs. joint research). The positive effects are present in both scientific research strategies (e.g., independent vs. joint research). • Citing more joint scientific research outputs helps semiconductor corporations generate more patents with better quality. [ABSTRACT FROM AUTHOR]

Abstract Compare Zcalc with other formulas on spherical equivalent prediction errors (PE) and explore the relationship between PE and ocular parameters. Optimize 709 IOL power calculation. 114 eyes with age-related cataract and preoperative regular corneal astigmatism of more than 1.5D were included. They underwent cataract surgery followed by implantation of a toric intraocular lens (Zeiss Torbi 709 M) calculated by Zcalc formula. The prediction errors of spherical equivalent (SE) were analysed 3 months post-surgery. The refractive prediction errors of Zcalc, Barrett Universal II, Kane, and K6 formulas were 0.07 ± 0.63D, − 0.36 ± 0.65D, − 0.41 ± 0.67D, and − 0.31 ± 0.66D, respectively. Statistically significant difference were observed between Zcalc and other formulas. The Zcalc was prone to positive deviation, Barrett Universal II, Kane and K6 were prone to negative deviation. When the axial length is greater than 29.0 mm, the prediction errors of Kane is higher, and prone to negative deviation. Prediction errors of Zcalc are small in all eyes and prone to positive deviation. For more accurate prediction, we recommend Barrett Universal II formula for 709 IOL power calculation.

Abstract Fluorouracil-based chemotherapy responses in colorectal cancer (CRC) patients vary widely, highlighting the role of pharmacogenomics in developing better predictive models. We analyzed 379 CRC patients receiving fluorouracil-based chemotherapy, collecting data on fluorouracil metabolism-related SNPs (TYMS, MTHFR, DPYD, RRM1), blood inflammatory markers, and clinical status. Six machine learning models—K-nearest neighbors, support vector machine, gradient boosting decision trees (GBDT), eXtreme Gradient Boosting (XGBoost), LightGBM, and random forest—were compared against multivariate logistic regression and a deep learning model (i.e., multilayer perceptron, MLP). Feature importance analysis highlighted seven predictors: histological grade, N and M staging, monocyte count, platelet-to-lymphocyte ratio, MTHFR rs1801131, and RRM1 rs11030918. In a five-fold cross-validation, XGBoost and GBDT exhibited superior performance, with Area Under Curve (AUC) of 0.88 ± 0.02. XGBoost excelled in identifying favorable prognosis (recall = 0.939). GBDT demonstrated balance in recognizing both categories, with a recall for favorable prognosis of 0.908 and a precision for unfavorable prognosis of 0.863. MLP had a similar AUC (0.87) with high precision for favorable prognosis (recall = 0.946). In external validation, XGBoost model achieved an accuracy of 0.79. An online prognostic tool based on XGBoost was developed, integrating metabolism-related SNPs and inflammatory markers, enhancing CRC treatment precision and supporting tailored chemotherapy.

Abstract With the widespread use of high-strength concrete structures (HC), the impact of pore structure on their performance has become a current research focus. The mechanism by which different curing conditions and freeze-thaw cycles influence the evolution of pore structure remains unclear. Therefore, this study systematically investigated the frost resistance of high-strength concrete under different curing conditions, measured the mass loss rate, compressive strength, and relative dynamic elastic modulus of concrete under freeze-thaw cycles. Utilizing low-field nuclear magnetic resonance (NMR) technology, this study analyzed the evolution of pore structure in HC under freeze-thaw cycles. Additionally, the fractal dimension was used to evaluate the change of concrete internal pore structure, so as to reflect the influence of pore structure on the mechanical properties of concrete subjected to freeze-thaw cycles, and then evaluated the freeze-thaw damage of HC. The experimental results indicated that the steam curing regimes led to an increase in the porosity of HC, thereby influencing its frost resistance. Steam-cured high-strength concrete (SMHC) exhibited a higher degradation rate under freeze-thaw cycles, resulting in a greater level of deterioration compared to standard curing high-strength concrete (SDHC), even under the same number of freeze-thaw cycles.

Abstract Ecosystem gross primary productivity (GPP) is the largest carbon flux between the atmosphere and biosphere and is strongly influenced by soil moisture. However, the response and acclimation of GPP to soil moisture remain poorly understood, leading to large uncertainties in characterizing the impact of soil moisture on GPP in Earth system models. Here we analyze the GPP-soil moisture response curves at 143 sites from the global FLUXNET. We find that GPP at 108 sites exhibits hump-shaped response curves with increasing soil moisture, and an apparent optimum soil moisture ( $${{\rm{SM}}}^{{\rm{GPP}}}_{{\rm{opt}}}$$ SM opt GPP , at which GPP reaches the maximum) exists widely with large variability among sites and biomes around the globe. Variation in $${{\rm{SM}}}^{{\rm{GPP}}}_{{\rm{opt}}}$$ SM opt GPP is mostly explained by local water availability, with drier ecosystems having lower $${{\rm{SM}}}^{{\rm{GPP}}}_{{\rm{opt}}}$$ SM opt GPP than wetter ecosystems, reflecting the water acclimation of $${{\rm{SM}}}^{{\rm{GPP}}}_{{\rm{opt}}}$$ SM opt GPP . This acclimation is further supported by a field experiment that only manipulates water and keeps other factors constant, which shows a downward shift in $${{\rm{SM}}}^{{\rm{GPP}}}_{{\rm{opt}}}$$ SM opt GPP after long-term water deficit, and thus a lower soil water requirement to maximize GPP. These results provide compelling evidence for the widespread $${{\rm{SM}}}^{{\rm{GPP}}}_{{\rm{opt}}}$$ SM opt GPP and its acclimation, shedding new light on understanding and predicting carbon-climate feedbacks.

Abstract Counterintuitive temperature dependence of isospin flavor polarization has recently been found in twisted bilayer graphene, where unpolarized electrons in a Fermi liquid become a spin–valley polarized insulator upon heating. So far, the effect has been limited to v = +/−1 (one electron/hole per superlattice cell), leaving open questions such as whether it is a general property of symmetry-breaking electronic phases. Here, by studying a rhombohedral trilayer graphene/boron nitride moiré superlattice, we report that at v = −3 a resistive peak emerges at elevated temperatures or in parallel magnetic fields. Concomitantly, the Hall carrier density tends to reset at the integer filling, signaling spin–valley flavor symmetry breaking. These phenomena can also be observed at v = −1 and −2 when the displacement field is large enough to suppress correlated insulators at low temperatures. Our results greatly expand the scope for observing the counterintuitive temperature dependence of flavor polarization, i.e., the regimes proximal to symmetry-breaking phases where the flavor polarization order strongly fluctuates, encouraging more experimental and theoretical exploration of isospin flavor polarization dynamics in flat-band moiré systems.

Abstract The optomechanical motion of a gold nanoparticle (GNP) dimer—a pair of optically bound GNPs—in fluid, manipulated by a Bessel beam, is theoretically studied using the multiple multipole (MMP) method. Since a Bessel beam possesses orbital angular momentum (OAM) and spin angular momentum (SAM) simultaneously, complicated rigid-body motions of the dimer can be induced. The mechanism involves the equilibrium between the optical force with the reactive drag force exerted by the fluid. Our results demonstrate that the dimer rotates around its center of mass (COM), while the COM performs an orbital revolution around the optical axis. Additionally, each individual GNP undergoes spinning. The directions of the GNPs’ spin and the orbital revolution of COM depend on the handedness and the order (topological charge) of Bessel beam, respectively. Nevertheless, the rotation direction of the dimer depends on the size of GNP. In the case of a smaller dimer, the direction of dimer’s rotation with respect to the COM is consistent with the handedness of the light. Conversely, a larger dimer performs a reverse rotation, accompanied by a precession during the orbital revolution. There are multiple turning points in the radius of the GNP for the alternating rotation of the dimer caused by positive or negative optical torque. Our finding may provide an insight to the optomechanical manipulation of optical vortexes on the motions of GNP clusters.

Abstract Alpha oscillations are associated with various psychiatric disorders, with many studies focusing on the prefrontal cortex, where transcranial alternating current stimulation (TACS) is applied in the alpha frequency band. This approach often involves selecting individualized alpha frequencies to resonate with their endogenous alpha oscillations. While strong alpha oscillations (8–13 Hz) are typically induced when the eyes are closed, they can also occur during the resting state with eyes open. However, it remains unclear whether these alpha oscillations share a common neural generation mechanism. Exploring which of these alpha oscillations is more suitable as a stable alpha peak frequency is a question of significant interest. Therefore, to systematically study this issue, we specifically collected resting-state electroencephalographic (EEG) data from the prefrontal region of 40 individuals, under both eyes-open and closed- eye conditions, with multiple follow-ups extending up to nine months. Through spectral analysis on each person’s entire dataset and averaging the results, we observed a significant positive correlation between the alpha-band power in the eyes-open and the eyes-closed states, in terms of both absolute power and relative power. Further analysis revealed that this correlation was primarily contributed by the periodic activity within the alpha band. Upon modelling the oscillatory components, we discovered distinct differences in the oscillatory characteristics-such as number of the alpha sub-oscillations between the eyes-open state and the eyes-closed state. Our study is the first to systematically explored the relationship between alpha oscillations in the prefrontal cortex in the eyes-open and eyes-closed states, identifying both shared part of the neural generation mechanism and some distinct neural mechanisms that are unique to each state.

Abstract Magnetotactic bacteria (MTB) combine passive alignment with the Earth magnetic field with a chemotactic response (magneto-chemotaxis) to reach their optimal living depth in chemically stratified environments. Current magneto-aerotaxis models fail to explain the occurrence of MTB far below the oxic-anoxic interface and the coexistence of MTB cells with opposite magnetotactic polarity at depths that are unrelated with the redox gradient. Here we propose a modified model of polar magnetotaxis which explains these observations, as well as the distinct concentration profiles and magnetotactic advantages of two types of MTB inhabiting a freshwater sediment: a group of unidentified cocci (MC), and a giant rod-shaped bacterium (MB) apparently identical to M. bavaricum (MB). This model assumed that magnetotactic polarity is set by a threshold mechanism in counter gradients of oxygen and a second group of repellents, with, in case of MB, includes H+ ions. MTB possessing this type of polar magnetotaxis can shuttle between two limit depths across the redox gradient (redox taxis), as previously postulated for M. bavaricum and other members of the Nitrospirota group. The magnetotaxis of MB and MC is predominantly dipolar whenever the presence of a magnetic field ensures a magnetotactic advantage. In addition, MB can overcome unfavorable magnetic field configurations through a temporal sensing mechanism. The availability of threshold and temporal sensing mechanisms of different substances can generate a rich variety of responses by different types of MTB, enabling them to exploit multiple ecological niches.

Abstract Given the limited capacity to accurately determine the necessity for intubation in intensive care unit settings, this study aimed to develop and externally validate an interpretable machine learning model capable of predicting the need for intubation among ICU patients. Seven widely used machine learning (ML) algorithms were employed to construct the prediction models. Adult patients from the Medical Information Mart for Intensive Care IV database who stayed in the ICU for longer than 24 h were included in the development and internal validation. The model was subsequently externally validated using the eICU-CRD database. In addition, the SHapley Additive exPlanations method was employed to interpret the influence of individual parameters on the predictions made by the model. A total of 11,988 patients were included in the final cohort for this study. The CatBoost model demonstrated the best performance (AUC: 0.881). In the external validation set, the efficacy of our model was also confirmed (AUC: 0.750), which suggests robust generalization capabilities. The Glasgow Coma Scale (GCS), body mass index (BMI), arterial partial pressure of oxygen (PaO2), respiratory rate (RR) and length of stay (LOS) before ICU were the top 5 features of the CatBoost model with the greatest impact. We developed an externally validated CatBoost model that accurately predicts the need for intubation in ICU patients within 24 to 96 h of admission, facilitating clinical decision-making and has the potential to improve patient outcomes. The prediction model utilizes readily obtainable monitoring parameters and integrates the SHAP method to enhance interpretability, providing clinicians with clear insights into the factors influencing predictions.

Abstract Photothermal superhydrophobic coatings are supposed promising to prevent ice accumulation on infrastructures but often experience significant performance degradation in real icing conditions and lack mechanical robustness. Here, we report design of robust photothermal superhydrophobic coatings with three-tier hierarchical micro-/nano-/nanostructures by deposition of nanosized MOFs on natural attapulgite nanorods, fluorination, controlled phase separation of a hydrophobic adhesive and spraying assembly. Phase separation degree and adhesive content significantly influence the coatings’ properties by regulating the structural parameters and morphology. In simulated/real icing environments, the coatings simultaneously show (i) high superhydrophobicity and stable Cassie-Baxter states due to their low-surface-energy, three-tier micro-/nano-/nanostructure, (ii) excellent photothermal effect primarily due to nanosized MOFs, and (iii) good mechanical robustness by the phase-separated adhesive, reinforcement with attapulgite and the coatings’ self-similar structure. Accordingly, combined with low thermal conductivity, the coatings exhibit remarkable anti-icing/frosting (e.g., no freezing in at least 150 min and almost free of frost in 25 min) and de-icing/frosting performances (e.g., fast de-icing in 12.7 min and fast de-frosting in 16.7 min) in such environments. Furthermore, we realize large-scale preparation of the coatings at reasonable costs. The coatings have great application potential for anti-icing and de-icing in the real world by efficiently using natural sunlight.

Abstract Dissecting the genetic basis of seed traits in wheat is impeded by limited genetic polymorphisms and significant variations caused by environmental conditions and seed position in a spikelet. Seed performance is largely determined by endosperm development controlled by spatiotemporal variation in gene activities, which is greatly affected by chromatin status. Here, we map genome-wide dynamic distributions of H3K27me3, H3K4me3 and H3K9ac modifications and profile gene transcription across wheat endosperm development. The combinatorial effects of active and repressive marks ensure spatiotemporal dynamic gene expression, especially for starch biosynthesis. By scanning the transcription factor binding motifs in the ATAC-seq peaks, hub regulators are identified from the regulatory network. In addition, we observe significant correlations between sequence polymorphisms of hub regulators and variations in seed traits in a germplasm population. Thus, the analysis of genomic regulatory activities together with genetic variation provides a robust approach to dissect seed traits in bread wheat.

Abstract Pharmaceutical drug dosage forms are critical for ensuring the effective and safe delivery of active pharmaceutical ingredients to patients. However, traditional formulation development often relies on extensive lab and animal experimentation, which can be time-consuming and costly. This manuscript presents a generative artificial intelligence method that creates digital versions of drug products from images of exemplar products. This approach employs an image generator guided by critical quality attributes, such as particle size and drug loading, to create realistic digital product variations that can be analyzed and optimized digitally. This paper shows how this method was validated through two case studies: one for the determination of the amount of material that will create a percolating network in an oral tablet product and another for the optimization of drug distribution in a long-acting HIV inhibitor implant. The results demonstrate that the generative AI method accurately predicts a percolation threshold of 4.2% weight of microcrystalline cellulose and generates implant formulations with controlled drug loading and particle size distributions. Comparisons with real samples reveal that the synthesized structures exhibit comparable particle size distributions and transport properties in release media.

Abstract Immune checkpoint blockade (ICB) therapy has emerged as a new therapeutic paradigm for a variety of advanced cancers, but wide clinical application is hindered by low response rate. Here we use a peptide-based, biomimetic, self-assembly strategy to generate a nanoparticle, TPM1, for binding PD-L1 on tumour cell surface. Upon binding with PD-L1, TPM1 transforms into fibrillar networks in situ to facilitate the aggregation of both bound and unbound PD-L1, thereby resulting in the blockade of the PD-1/PD-L1 pathway. Characterizations of TPM1 manifest a prolonged retention in tumour ( > 7 days) and anti-cancer effects associated with reinvigorating CD8+ T cells in multiple mice tumour models. Our results thus hint TPM1 as a potential strategy for enhancing the ICB efficacy.

Abstract The clinical treatments of maxillofacial bone defects pose significant challenges due to complex microenvironments, including severe inflammation, high levels of reactive oxygen species (ROS), and potential bacterial infection. Herein, we propose the de novo design of an efficient, versatile, and precise electron-donable heterojunction with synergetic Ru-Cu pair sites (Ru-Cu/EDHJ) for superior biocatalytic regeneration of inflammatory mandible defects and pH-controlled antibacterial therapies. Our studies demonstrate that the unique structure of Ru-Cu/EDHJ enhances the electron density of Ru atoms and optimizes the binding strength of oxygen species, thus improving enzyme-like catalytic performance. Strikingly, this biocompatible Ru-Cu/EDHJ can efficiently switch between ROS scavenging in neutral media and ROS generation in acidic media, thus simultaneously exhibiting superior repair functions and bioadaptive antibacterial properties in treating mandible defects in male mice. We believe synthesizing such biocatalytic heterojunctions with exceptional enzyme-like capabilities will offer a promising pathway for engineering ROS biocatalytic materials to treat trauma, tumors, or infection-caused maxillofacial bone defects.

Abstract Amidst growing concerns over climate-induced extreme weather events, precise flood forecasting becomes imperative, especially in regions like the Chaersen Basin where data scarcity compounds the challenge. Traditional hydrologic models, while reliable, often fall short in areas with insufficient observational data. This study introduces a hybrid modeling approach that combines the deep learning capabilities of the Informer model with the robust hydrological simulation by the WRF-Hydro model to enhance runoff predictions in such data-sparse regions. Trained initially on the diverse and extensive CAMELS dataset in the United States, the Informer model successfully applied its learned insights to predict runoff in the Chaersen Basin, leveraging transfer learning to bridge data gaps. Concurrently, the WRF-Hydro model, when integrated with The Global Forecast System (GFS) data, provided a basis for comparison and further refinement of flood prediction accuracy. The integration of these models resulted in a significant improvement in prediction precision. The synergy between the Informer’s advanced pattern recognition and the physical modeling strength of the WRF-Hydro significantly enhanced the prediction accuracy. The final predictions for the years 2015 and 2016 demonstrated notable increases in the Nash–Sutcliffe Efficiency (NSE) and the Index of Agreement (IOA) metrics, confirming the effectiveness of the hybrid model in capturing complex hydrological dynamics during runoff predictions. Specifically, in 2015, the NSE improved from 0.5 with WRF-Hydro and 0.63 with the Informer model to 0.66 using the hybrid model, while in 2016, the NSE increased from 0.42 to 0.76. Similarly, the IOA in 2015 rose from 0.83 with WRF-Hydro and 0.84 with the Informer model to 0.87 using the hybrid approach, and in 2016, it increased from 0.78 to 0.92. Further investigation into the respective contributions of the WRF-Hydro and the Informer models revealed that the hybrid model achieved the optimal performance when the contribution of the Informer model was maintained between 60%-80%.

Abstract The primary objective of this study was to identify the factors associated with the development of depressive symptoms in elderly breast cancer (BC) patients and to construct a nomogram model for predicting these symptoms. We recruited 409 patients undergoing BC treatment in the breast departments of two tertiary-level hospitals in Jiangsu Province from November 2023 to April 2024 as our study cohort. Participants were categorized into depressed and non-depressed groups based on their clinical outcomes. Univariate and multivariate logistic regression analyses were employed to identify independent risk factors for depression among BC patients. Multivariate analysis revealed that monthly income, pain score, family support score, and physical activity score significantly influenced the onset of depression in older BC patients (P

Abstract This study aimed to investigate the impact of physical activity indicators monitored by the POLAR accelerometer on body obesity indicators, metabolic syndrome parameters, and energy metabolism hormones in postmenopausal women. Was included 71 participants from this study program (68.8 ± 4.3 years). We divided participants into LPA and MVPA groups based on their level of moderate to vigorous physical activity per week; Physical activity levels over 7 days were assessed using a POLAR accelerometer, with daily step counts and sedentary time recorded. Measurements included waist circumference, visceral fat volume, body fat percentage, blood pressure, fasting blood glucose, triglyceride levels, HDL cholesterol, and energy metabolism hormone levels (leptin, resistin, adiponectin). The MVPA group displayed lower waist circumference, body fat percentage, abdominal fat, and BMI compared to the LPA group (p

Abstract The relative risk and benefits of Laparoscopic liver resection (LLR) are still controversial. This study aimed to evaluate perioperative and survival outcomes for three primary malignant liver tumors related outcomes following LLR. Data from three Homogeneous-High-Volume-Expert-Centers were collected. Multivariable logistic regression analysis was performed for the association between LLR, and major complications defined as Clavien-Dindo Classification grade ≥ II. Multivariable Cox proportional hazards regression was used to explore the impact of LLR on primary malignant liver tumor survival. Overall, 5886 patients underwent liver resection, of which 1991 underwent LLR. After adjusting for covariables, LLR had significantly lower rate of CDC grade ≥ II (OR = 0.56, 95% CI: 0.48–0.67, P 0.05). LLR was associated with lower rate of major complications, especially in women, non-drinkers, those without a history of abdominal surgery, and those with normal platelet. For primary malignant liver tumors, the survival outcomes did not differ significantly between LLR and OLR.

Abstract Idiopathic inflammatory myopathy (IIM) with autoantibodies recognizing the signal recognition particle (SRP) is characterized by prominent proximal weakness, infrequent extramuscular involvement, dramatically elevated creatine kinase levels, and myofiber necrosis with few inflammatory cell infiltrates in muscle tissue. To enhance understanding of the clinically used diagnosis and treatment of this disease, this study presents a single-center experience and analysis of a Chinese cohort with anti-SRP IIM. The most recent European Neuromuscular Center criteria were used to include Anti-SRP IIM patients from September 2016 to November 2019. Prior to treatment initiation, all sera were collected for the detection of anti-SRP autoantibodies and other myositis-related autoantibodies. Muscle strength, concurrent autoimmune conditions, comorbidities like interstitial lung disease (ILD), treatment outcomes, and follow-up results were also documented. Univariate logistic regression was employed to determine factors affecting prognosis. Among 271 patients with IIM, we identified 23 (8.5%) patients with anti-SRP IIM. Lower limb muscle weakness was frequently more severe. Interstitial lung disease (ILD) was observed in 50% of anti-SRP IIM patients. The presence of ILD may serve as a predictor of a poor prognosis, as revealed by univariate logistic regression analysis (odds ratio, 3.8, 95% CI: 1.0-6.8, p = 0.05).This Chinese Anti-SRP IIM cohort from Hunan province seems to have higher incidences of ILD, and associated ILD may be a risk factor for a poor prognosis. To fully understand the specific role of the anti-SRP autoantibody in this unique subset with ILD, further research is necessary.