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Abstract Background Although phytoplankton are important primary producers in food webs, they are relatively less studied in large rivers compared to other types of systems. To fill this research gap, we studied phytoplankton taxonomic and functional composition and their relationships with water quality, habitat, climate, and land use across 30 river sections in the middle and lower reaches of the Yangtze River during 2017–2018. Results Major observed phytoplankton groups were cyanobacteria, bacillariophyta, and chlorophyta. Phytoplankton total abundance, total biomass, and species richness significantly decreased in the dry season compared to the wet season, with the species and functional composition differing significantly between seasons. Phytoplankton species differences between seasons were mainly contributed by Oscillatoria sp., Pseudanabaena sp., and Melosira granulata. The dfferences in phytoplankton functional groups between seasons were mainly contributed by P (including Closterium sp., Melosira sp.), Lo (including Merismopedia sp., Peridinium sp., Ceratium sp., and Gymnodinium sp.), and J (including Pediastrum sp., Tetraedron sp., Crucigenia sp., Scenedesmus sp., and Coelastrum sp.). The variance partitioning showed that water quality (NO3-N, total suspended solids, turbidity) and habitat (water flow, river bank and river channel conditions) were critical factors in shaping phytoplankton patterns, followed by climate and land use. Conclusions Results indicated that there was significant seasonal variation of phytoplankton in the Yangtze River, with water quality and habitat primarily driving phytoplankton patterns. Our study contributes to the understanding of natural and anthropogenic factors that drive seasonal successional processes of phytoplankton in the Yangtze River. These findings have important implications for environmental management as well as towards the ecological restoration of large rivers.

Abstract Background Multi-drug-resistant organisms (MDROs) in gram-negative bacteria have caused a global epidemic, especially the bacterial resistance to carbapenem agents. Plasmid is the common vehicle for carrying antimicrobial resistance genes (ARGs), and the transmission of plasmids is also one of the important reasons for the emergence of MDROs. Different incompatibility group plasmid replicons are highly correlated with the acquisition, dissemination, and evolution of resistance genes. Based on this, the study aims to identify relevant characteristics of various plasmids and provide a theoretical foundation for clinical anti-infection treatment. Methods 330 gram-negative strains with different antimicrobial phenotypes from a tertiary hospital in Henan Province were included in this study to clarify the difference in incompatibility group plasmid replicons. Additionally, we combined the information from the PLSDB database to elaborate on the potential association between different plasmid replicons and ARGs. The VITEK mass spectrometer was used for species identification, and the VITEK-compact 2 automatic microbial system was used for the antimicrobial susceptibility test (AST). PCR-based replicon typing (PBRT) detected the plasmid profiles, and thirty-three different plasmid replicons were determined. All the carbapenem-resistant organisms (CROs) were tested for the carbapenemase genes. Results 21 plasmid replicon types were detected in this experiment, with the highest prevalence of IncFII, IncFIB, IncR, and IncFIA. Notably, the detection rate of IncX3 plasmids in CROs is higher, which is different in strains with other antimicrobial phenotypes. The number of plasmid replicons they carried increased with the strain resistance increase. Enterobacterales took a higher number of plasmid replicons than other gram-negative bacteria. The same strain tends to have more than one plasmid replicon type. IncF-type plasmids tend to be associated with MDROs. Combined with PLSDB database analysis, IncFII and IncX3 are critical platforms for taking bla KPC−2 and bla NDM. Conclusions MDROs tend to carry more complex plasmid replicons compared with non-MDROs. The plasmid replicons that are predominantly prevalent and associated with ARGs differ in various species. The wide distribution of IncF-type plasmids and their close association with MDROs should deserve our attention. Further investigation into the critical role of plasmids in the carriage, evolution, and transmission of ARGs is needed.

Abstract Osteosarcoma (OS) is the most common primary malignant tumor of bone. Remodelin, an inhibitor of the N (4)-Acetylcytidine (ac4C) acetylation modifying enzyme N-acetyltransferase 10 (NAT10), has been shown to have therapeutic effects on cancer in several studies, and our previous studies have confirmed the inhibitory effect of Remodelin on OS cells, however, the mechanism of action has not yet been elucidated. We used network pharmacological analysis to quantify the therapeutic targets of Remodelin against OS. acRIP-seq and RNA-seq were performed to investigate the inhibitory activity of Remodelin on acetylation and its effect on the transcriptome after intervening in OS cells U2OS with Remodelin in vitro. Key target genes were deduced based on their pharmacological properties, combined with network pharmacology results and sequencing results. Finally, the deduced target genes were validated with vitro experiments. Network pharmacological analysis showed that 2291 OS-related target genes and 369 Remodelin-related target genes were obtained, and 116 overlapping genes were identified as Remodelin targets for OS treatment. Sequencing results showed that a total of 13,736 statistically significant ac4C modification peaks were detected by acRIP-seq, including 6938 hypoacetylation modifications and 6798 hyperacetylation modifications. A total of 2350 statistically significant mRNAs were detected by RNA-seq, of which 830 were up-regulated and 1520 were down-regulated. Association analyses identified a total of 382 genes that were Hypoacetylated-down, consistent with inhibition of mRNA acetylation and expression by Remodelin. Five genes, CASP3, ESR2, FGFR2, IGF1 and MAPK1, were identified as key therapeutic targets of Remodelin against OS. Finally, in vitro experiments, CCK-8 and qRT-PCR demonstrated that Remodelin indeed inhibited the proliferation of OS cells and reduced the expression of three genes: ESR2, IGF1, and MAPK1. In conclusion, ESR2, IGF1 and MAPK1 were identified as key therapeutic targets of Remodelin against OS. This reveals the target of Remodelin's pharmacological action on OS and provides new ideas for the treatment of OS.

Abstract Wireless traffic prediction is vital for intelligent cellular network operations, such as load-aware resource management and predictive control. Traditional centralized training addresses this but poses issues like excessive data transmission, disregarding delays, and user privacy. Traditional federated learning methods can meet the requirement of jointly training models while protecting the privacy of all parties’ data. However, challenges arise when the local data features among participating parties exhibit inconsistency, making the training process difficult to sustain. Our study introduces an innovative framework for wireless traffic prediction based on split learning (SL) and vertical federated learning. Multiple edge clients collaboratively train high-quality prediction models by utilizing diverse traffic data while maintaining the confidentiality of raw data locally. Each participant individually trains dimension-specific prediction models with their respective data, and the outcomes are aggregated through collaboration. A partially global model is formed and shared among clients to address statistical heterogeneity in distributed machine learning. Extensive experiments on real-world datasets demonstrate our method’s superiority over current approaches, showcasing its potential for network traffic prediction and accurate forecasting.

Abstract Background The clinical course and surgical outcomes of undifferentiated sarcomatoid carcinoma of the pancreas (USCP) remain poorly characterized owing to its rarity. This study aimed to describe the histology, clinicopathologic features, perioperative outcomes, and overall survival (OS) of 23 resected USCP patients. Methods We retrospectively described the histology, clinicopathologic features, perioperative outcomes and OS of patients who underwent pancreatectomy with a final diagnosis of USCP in a single institution. Results A total of 23 patients were included in this study. Twelve patients were male, the median age at diagnosis was 61.5 ± 13.0 years (range: 35–89). Patients with USCP had no specific symptoms and characteristic imaging findings. The R0 resection was achieved in 21 cases. The En bloc resection and reconstruction of mesenteric–portal axis was undertaken in 9 patients. There were no deaths attributed to perioperative complications in this study. The intraoperative tumor-draining lymph nodes (TDLNs) dissection was undergone in 14 patients. The 1-, 3- and 5-year survival rates were 43.5%, 4.8% and 4.8% in the whole study, the median survival was 9.0 months. Only 1 patient had survived more than 5 years and was still alive at last follow-up. The presence of distant metastasis (p = 0.004) and the presence of pathologically confirmed mesenteric–portal axis invasion (p = 0.007) was independently associated with poor OS. Conclusions USCP was a rare subgroup of pancreatic malignancies with a bleak prognosis. To make a diagnose of USCP by imaging was quite difficult because of the absence of specific manifestations. Accurate diagnosis depended on pathological biopsy, and the IHC profile of USCP was mainly characterized by co-expression of epithelial and mesenchymal markers. A large proportion of patients have an early demise, especially for patients with distant metastasis and pathologically confirmed mesenteric–portal axis invasion. Long-term survival after radical resection of USCPs remains rare.

Abstract The treatment of critical-size bone defects with irregular shapes remains a major challenge in the field of orthopedics. Bone implants with adaptability to complex morphological bone defects, bone-adhesive properties, and potent osteogenic capacity are necessary. Here, a shape-adaptive, highly bone-adhesive, and ultrasound-powered injectable nanocomposite hydrogel is developed via dynamic covalent crosslinking of amine-modified piezoelectric nanoparticles and biopolymer hydrogel networks for electrically accelerated bone healing. Depending on the inorganic-organic interaction between the amino-modified piezoelectric nanoparticles and the bio-adhesive hydrogel network, the bone adhesive strength of the prepared hydrogel exhibited an approximately 3-fold increase. In response to ultrasound radiation, the nanocomposite hydrogel could generate a controllable electrical output (-41.16 to 61.82 mV) to enhance the osteogenic effect in vitro and in vivo significantly. Rat critical-size calvarial defect repair validates accelerated bone healing. In addition, bioinformatics analysis reveals that the ultrasound-responsive nanocomposite hydrogel enhanced the osteogenic differentiation of bone mesenchymal stem cells by increasing calcium ion influx and up-regulating the PI3K/AKT and MEK/ERK signaling pathways. Overall, the present work reveals a novel wireless ultrasound-powered bone-adhesive nanocomposite hydrogel that broadens the therapeutic horizons for irregular bone defects.

Introduction: Allotetraploid upland cotton (Gossypium hirsutum L.) is native to the Mesoamerican and Caribbean regions, had been improved in the southern United States by the mid-eighteenth century, was then dispersed worldwide. However, a Hainan Island Native Cotton (HIC) has long been grown extensively on Hainan Island, China. Objectives: Explore HIC’s evolutionary relationship and genomic diversity with other tetraploid cottons, its origin and whether it was used for YAZHOUBU (Yazhou cloth, World Intangible Cultural Heritage) weaving, and the role of structural variations (SVs) in upland cotton domestication. Methods: We assembled a high-quality genome of one HIC plant. We performed phylogenetic analysis, divergence time estimation, principal component analysis and population differentiation estimation using cotton assemblies and/or resequencing data. SVs were detected by whole-genome comparison. A F2 population was used for linkage analysis and to study effects of SVs. Buoyancy and salt water tolerance tests for seeds were conducted. Results: We found that the HIC belongs to G. purpurascens. G. purpurascens is best classified as a primitive race of G. hirsutum. The potential for long range transoceanic dispersal of G. purpurascens seeds was proved. A set of SVs, selective sweep regions between G. hirsutum races and cultivars, and quantitative trait loci (QTLs) of eleven agronomic traits were obtained. SVs, especially large-scale SVs, were found to have important effects on cotton domestication and improvement. Of them, eight large-scale inversions strongly associated with yield and fiber quality have probably undergone artificial selection in domestication. Conclusion: G. purpurascens including HIC is a primitive race of G. hirsutum, probably disperse to Hainan from Central America by floating on ocean currents, may have been partly domesticated, planted and was likely used for YAZHOUBU weaving in Hainan much earlier than the Pre-Columbian period. SV plays an important role in cotton domestication and improvement.

Deep learning methods, especially convolutional neural networks (CNNs) and vision transformers (ViTs), are frequently employed to perform semantic segmentation of high-resolution remotely sensed images. However, CNNs are constrained by their restricted receptive fields, while ViTs face challenges due to their quadratic complexity. Recently, the Mamba model, featuring linear complexity and a global receptive field, has gained extensive attention for vision tasks. In such tasks, images need to be serialized to form sequences compatible with the Mamba model. Numerous research efforts have explored scanning strategies to serialize images, aiming to enhance the Mamba model's understanding of images. However, the effectiveness of these scanning strategies remains uncertain. In this research, we conduct a comprehensive experimental investigation on the impact of mainstream scanning directions and their combinations on semantic segmentation of remotely sensed images. Through extensive experiments on the LoveDA, ISPRS Potsdam, ISPRS Vaihingen, and UAVid datasets, we demonstrate that no single scanning strategy outperforms others, regardless of their complexity or the number of scanning directions involved. A simple, single scanning direction is deemed sufficient for semantic segmentation of high-resolution remotely sensed images. Relevant directions for future research are also recommended.

Changes in land use and land cover (LULC) are critical for evaluating global spatiotemporal trends, especially regarding climate change and urbanization. This study investigates the dynamics of Landsat surface temperature (LST) in response to LULC changes and their effects on the seasonal microclimate in Kasur District, Pakistan. Using the Google Earth Engine platform, we employed a random forest algorithm to detect LULC changes (cropland, forest, built-up, fallow, barren, and water) and analyze seasonal spectral indices from Landsat imagery for 1988, 2002, and 2022. Significant LULC changes were observed, including a 9.8% increase in built-up areas, a 4.2% decrease in cropland, and a 1.4% decrease in forested areas, linked to urban heat island effects and population growth. Additionally, there was a 2.7% increase in fallow and open land, contributing to the district's impervious surface area. Significant correlations (p < 0.001) were found between LST and spectral indices—normalized difference vegetation index, enhanced vegetation index, and normalized difference built index (NDBI)—ranging from 0.7 to 0.8 in both winter and summer. In summer, the maximum LST increased from 43 °C in 1988 to 44 °C in 2002, with a linear correlation (R²) increase from 0.57 to 0.75 and a polynomial correlation (R²) increase from 0.63 to 0.76 with NDBI from 1988 to 2022. Understanding these dynamics is crucial as LULC changes and the resulting temperature variations have significant implications for local climate, agriculture, and human health. This study underscores the need for effective LULC policies to mitigate impacts, protect vegetation cover, and ensure sustainable land management. These findings provide valuable insights for policymakers and urban planners aiming to balance development with environmental sustainability.

Quantum computing is commonly considered one highly efficient computing method with the potential to revolutionize computation technology and solve problems that are currently unsolvable. However, due to the limitation of hardware equipment and an immature experimental base, quantum technology is still in its early stages and is far from achieving the expected performance, especially in solving large-scale complex problems. To break through these barriers, we propose a parallelized quantum annealing algorithm based on Lagrangian relaxation. The proposed algorithm divides the large-scale problem into several small problems and then employs multiple quantum computers to solve them. Our proposed approach overcomes the limited number of qubits and allows quantum computing to solve largescale optimization problems. Additionally, we incorporate a local search method to ensure this Lagrangian relaxation based quantum algorithm achieves an optimal solution. We use the proposed parallelized quantum annealing algorithm to solve optimal scheduling problems in network function virtualization networks. The problem is expressed in a linear optimization model that is NP-hard. Our proposed algorithm presents excellent time performance in solving this virtualized network functions scheduling problem, compared with the Lagrangian relaxation based classical algorithm.

This study addresses significant challenges within the field of remote sensing monitoring, including operational inefficiency, data confidentiality concerns, high hardware costs, and issues with data management and distribution. To tackle these problems, we introduce a synergistic remote sensing monitoring framework that leverages a bimodal cloud infrastructure, facilitated by cloud services to provide on-demand resource allocation and efficient management. Our research focuses on designing and developing an integrated operating system that optimizes remote sensing monitoring processes and enhances operational efficiency through the use of a mutual scheduling mechanism and rapid data indexing capabilities. The system is underpinned by a dual-state cloud service mechanism, combining the Memory Cloud (Flash Cloud) known for its high-speed data processing and the Storage Cloud (Persistent Cloud) for long-term data retention. This dual-state approach establishes a multi-level caching system to ensure quick access to frequently requested spatial data. Additionally, a two-tier security system is implemented to safeguard data integrity and confidentiality. Our “YunYao” geographic information service rendering engine, operating on this dual-state cloud platform, demonstrated remarkable performance advantages over mainstream platforms in identical testing environments. Specifically, it outperformed ArcGIS Desktop by over two times, exceeded GeoServer by more than four times, and was over seven times faster than ArcGIS Server in rendering speeds. Experimental and practical applications have shown that our system streamlines routine workflows and enhances work efficiency, making it a critical reference for remote sensing monitoring. Furthermore, a comparative analysis was conducted to quantitatively demonstrate the superior performance of our method in handling large volumes of remote sensing data(Including satellite imagery and UAV imagery). Despite these advancements, the integration of cloud service technology in the field of satellite remote sensing requires further development, particularly regarding the establishment of private clouds and the internal collaborative computing mechanisms within the remote sensing domain. Our research paves the way for future advancements and the eventual full integration of cloud service models into remote sensing monitoring.

Long-term failures in flexible converter valve equipment pose significant risks, potentially compromising operational efficiency or leading to complete malfunction. Accurately identifying equipment faults is essential to improve overall reliability and minimize downtime. This study introduces an innovative fault diagnosis method utilizing an attention mechanism. The method integrates a lightweight model incorporating one-dimension depthwise convolutional layers for spatial feature extraction and bidirectional long short-term memory for capturing temporal dynamics. A pioneering time-channel joint attention module enhances the extraction of fault-related data from time series and channel maps. Experimental results underscore the method’s efficacy in fault diagnosis under varying Gaussian noise conditions. Notably, the approach demonstrates remarkable consistency in accuracy across various experimental setups, underscoring its robust performance and potential applicability in real-world scenarios where reliability is critical. In addition, the proposed method has a moderate number of parameters and training time, indicating that the model can be embedded in front-end equipment.

Abstract Lung adenocarcinoma (LUAD) is a malignant tumor with high lethality, and the aim of this study was to identify promising biomarkers for LUAD. Using the TCGA-LUAD dataset as a discovery cohort, a novel joint framework VAEjMLP based on variational autoencoder (VAE) and multilayer perceptron (MLP) was proposed. And the Shapley Additive Explanations (SHAP) method was introduced to evaluate the contribution of feature genes to the classification decision, which helped us to develop a biologically meaningful biomarker potential scoring algorithm. Nineteen potential biomarkers for LUAD were identified, which were involved in the regulation of immune and metabolic functions in LUAD. A prognostic risk model for LUAD was constructed by the biomarkers HLA-DRB1, SCGB1A1, and HLA-DRB5 screened by Cox regression analysis, dividing the patients into high-risk and low-risk groups. The prognostic risk model was validated with external datasets. The low-risk group was characterized by enrichment of immune pathways and higher immune infiltration compared to the high-risk group. While, the high-risk group was accompanied by an increase in metabolic pathway activity. There were significant differences between the high- and low-risk groups in metabolic reprogramming of aerobic glycolysis, amino acids, and lipids, as well as in angiogenic activity, epithelial-mesenchymal transition, tumorigenic cytokines, and inflammatory response. Furthermore, high-risk patients were more sensitive to Afatinib, Gefitinib, and Gemcitabine as predicted by the pRRophetic algorithm. This study provides prognostic signatures capable of revealing the immune and metabolic landscapes for LUAD, and may shed light on the identification of other cancer biomarkers.

Abstract Background An appropriate prediction model for adverse prognosis before peritoneal dialysis (PD) is lacking. Thus, we retrospectively analysed patients who underwent PD to construct a predictive model for adverse prognoses using machine learning (ML). Methods A retrospective analysis was conducted on 873 patients who underwent PD from August 2007 to December 2020. A total of 824 patients who met the inclusion criteria were included in the analysis. Five commonly used ML algorithms were used for the initial model training. By using the area under the curve (AUC) and accuracy (ACC), we ranked the indicators with the highest impact and displayed them using the values of Shapley additive explanation (SHAP) version 0.41.0. The top 20 indicators were selected to build a compact model that is conducive to clinical application. All model-building steps were implemented in Python 3.8.3. Results At the end of follow-up, 353 patients withdrew from PD (converted to haemodialysis or died), and 471 patients continued receiving PD. In the complete model, the categorical boosting classifier (CatBoost) model exhibited the strongest performance (AUC = 0.80, 95% confidence interval [CI] = 0.76–0.83; ACC: 0.78, 95% CI = 0.72–0.83) and was selected for subsequent analysis. We reconstructed a compression model by extracting 20 key features ranked by the SHAP values, and the CatBoost model still showed the strongest performance (AUC = 0.79, ACC = 0.74). Conclusions The CatBoost model, which was built using the intelligent analysis technology of ML, demonstrated the best predictive performance. Therefore, our developed prediction model has potential value in patient screening before PD and hierarchical management after PD.

Abstract Electroconductive hydrogels offer a promising avenue for enhancing the repair efficacy of spinal cord injuries (SCI) by restoring disrupted electrical signals along the spinal cord’s conduction pathway. Nonetheless, the application of hydrogels composed of diverse electroconductive materials has demonstrated limited capacity to mitigate the post-SCI inflammatory response. Recent research has indicated that the transplantation of M2 microglia effectively fosters SCI recovery by attenuating the excessive inflammatory response. Exosomes (Exos), small vesicles discharged by cells carrying similar biological functions to their originating cells, present a compelling alternative to cellular transplantation. This investigation endeavors to exploit M2 microglia-derived exosomes (M2-Exos) successfully isolated and reversibly bonded to electroconductive hydrogels through hydrogen bonding for synergistic promotion of SCI repair to synergistically enhance SCI repair. In vitro experiments substantiated the significant capacity of M2-Exos-laden electroconductive hydrogels to stimulate the growth of neural stem cells and axons in the dorsal root ganglion and modulate microglial M2 polarization. Furthermore, M2-Exos demonstrated a remarkable ability to mitigate the initial inflammatory reaction within the injury site. When combined with the electroconductive hydrogel, M2-Exos worked synergistically to expedite neuronal and axonal regeneration, substantially enhancing the functional recovery of rats afflicted with SCI. These findings underscore the potential of M2-Exos as a valuable reparative factor, amplifying the efficacy of electroconductive hydrogels in their capacity to foster SCI rehabilitation.

The aim of this article is to investigate the optimization of electric vehicle charging and swapping for green logistics, as well as path planning considering urban impedance. We improved a road impedance function model suitable for urban road traffic in China to calculate the actual traffic time based on real-time traffic data and the intricate urban road environment. This model is then applied to address the delivery optimization problem. Furthermore, a robust computational approach is introduced to estimate battery degradation costs, accounting for environmental temperature and depth of discharge. The logistics delivery model is effectively tackled using genetic algorithms, and simulation results demonstrate the considerable advantages of electric vehicle swapping, effectively mitigating energy wastage and environmental pollution. Additionally, the integration of road impedance modeling for path optimization proves to significantly reduce logistics costs, time expenditures, and enhance logistics efficiency. A comprehensive sensitivity analysis is also conducted to elucidate the factors influencing electric vehicle battery degradation, revealing a direct correlation between higher temperatures, deeper discharge depth, and increased battery loss. The study underscores the paramount significance of this research for the development and optimization of urban green logistics systems.

Abstract Cockroaches are considered mechanical transmitters of infectious diseases, posing a threat to human health. This study assessed the potential of cockroaches in food-related environments to mechanically transmit intestinal pathogens. Cockroaches captured with traps were placed together into a low temperature refrigerator at − 80° for 2 h. Standard taxonomic keys and Fluorescent quantitative PCR techniques were applied for species identification and digestive tract etiological examination. A total of 360 cockroach traps were placed, with a positive rate of 20.8%, and 266 cockroaches were captured. In general, compared with other places and areas, the degree of infestation of cockroaches was more serious in catering places and kitchens. Blattella germanica were most found in catering places (40.2%), followed by Periplaneta fuliginosa in schools (22.2%). According to the life stage, among the 128 cockroach samples, 23 were positive for nymphs and 13 were positive for adults. There were statistically significant differences in the intestinal pathogen detection rates between nymphs and adults (P

Abstract Background Malignant progression is the major cause of poor prognosis in breast cancer (BC) patients. Plasma exosomal miRNAs have been reported to be involved in tumor progression, but their roles in BC remain unclear. Methods We performed plasma exosomal miRNA sequencing on 45 individuals, including healthy controls and nonmetastatic and metastatic BC patients. We examined the correlation between miRNA expression in tumor tissues and plasma exosomes in BC patients by qRT‒PCR. The effects of exosomal miR-361-3p on BC cells were determined by CellTiter-Glo, migration and wound healing assays. The target genes of miR-361-3p and downstream pathways were explored by dual-luciferase reporter assay, RNA knockdown, rescue experiments, and western blotting. We utilized murine xenograft model to further assess the impact of plasma exosomal miR-361-3p on the malignant progression of BC. Results We found that the expression level of plasma exosomal miR-361-3p gradually increased with malignant progression in BC patients, and the expression of miR-361-3p in plasma exosomes and BC tissues was positively correlated. Consistently, exosomal miR-361-3p enhanced the migration and proliferation of two BC cell lines, MDA-MB-231 and SK-BR-3. Furthermore, our data showed that miR-361-3p inhibited two novel target genes, ETV7 and BATF2, to activate the PAI-1/ERK pathway, leading to increased BC cell viability. Finally, the consistency of the in vivo experimental results supported that elevated plasma exosomal miR-361-3p promote the malignant progression of BC. Conclusions We found for the first time that plasma exosomal miR-361-3p was associated with malignant progression in BC patients. Mechanistically, exosomal miR-361-3p can enhance the migration and proliferation of BC cells by targeting the ETV7 and BATF2/PAI-1/ERK pathways. Our data suggest that plasma exosomal miR-361-3p has the potential to serve as a biomarker for predicting malignant progression in BC patients.

Wohlfahrtia magnifica is a species of fly that parasitizes Bactrian camels. The adult flies lay their larvae near the vulva of the camels, and these larvae develop and cause damage to the vaginal tissues, resulting in vaginal myiasis. Olfactory organs play an important role in the identification and location of host, foraging, mating and oviposition behavior of W. magnifica. Olfactory genes were identified by antennal transcriptome analysis. Twenty-four odor-binding proteins (OBPs) and two chemosensory proteins (CSPs) were identified in the antenna transcriptome of W. magnifica, and then the phylogenetic analysis of the olfactory genes of W. magnifica and other species was carried out. RTqPCR was used for the first time to analyze the expression profile of OBPs in the antenna tissues of the W. magnifica. In the tissue expression analysis of OBP genes, it was found that many of them showed obvious gender bias in antennae, indicating their different roles in identifying pheromones. These results will help to lay a foundation for the future research on the sense of smell of W. magnifica and help to better reveal the change of odor reception of W. magnifica and provide new ideas for the research on biological prevention and control of vaginal myiasis.

Abstract Background To find out if three-dimensional printing (3DP) off-the-shelf (OTS) prosthesis is superior to titanium mesh cages in anterior cervical corpectomy and fusion (ACCF) when treating single-segment degenerative cervical spondylotic myelopathy (DCSM). Methods DCSM patients underwent ACCF from January 2016 to January 2019 in a single center were included. Patients were divided into the 3DP group (28) and the TMC group (23). The hospital stays, operation time, intraoperative blood loss, and the cost of hospitalization were compared. The Japanese Orthopedic Association (JOA) scores and Neck Disability Index (NDI) were recorded pre-operatively, 1 day, 3, 6, 12, and 24 months post-operatively. Radiological data was measured to evaluate fusion, subsidence, and cervical lordosis. Patients were sent with SF-36 to assess their health-related quality of life (HRQoL). Results The differences in operative time, intraoperative blood loss, and hospital stay were not statistically significant between groups (p > 0.05). Postoperative dysphagia occurred in 2 cases in the 3DP group and 3 cases in the TMC group, which all relieved one week later. The difference in improvement of JOA and NDI between the two groups was not statistically significant (p > 0.05). No hardware failure was found and bony fusion was achieved in all cases except one in the 3DP group. The difference in cervical lordosis (CL), fused segmental angle (FSA), mean vertebral height (MVH), and subsidence rates between groups at each follow-up time point was not statistically significant and the results of the SF-36 were similar (p > 0.05). The total cost was higher in the 3DP group with its higher graft cost (p

Abstract Intelligent reflecting surface (IRS) stands as a promising technology to revolutionize wireless communication by manipulating incident signal amplitudes and phases to enhance system performance. While existing research primarily centers around optimizing the phase shifts of IRS, the deployment of IRS on movable platforms introduces a new degree of freedom in the design of IRS-assisted systems. Leveraging flexible deployment strategies for IRS holds the potential to further amplify network throughput and extend coverage. This paper addresses the challenging non-convex joint optimization problem of the movable IRS and proposes a dynamic optimization algorithm based on proximal policy optimization (PPO) for dynamically optimizing the aerial position and phase configuration of IRS. Simulation results show the effectiveness of the proposed approach, demonstrating significant performance improvements compared to communication schemes without IRS assistance and conventional static IRS-assisted methods.

Abstract Germline-somatic mutation interactions are universal and associated with tumorigenesis, but their role in breast cancer, especially in non-Caucasians, remains poorly characterized. We performed large-scale prospective targeted sequencing of matched tumor-blood samples from 4079 Chinese females, coupled with detailed clinical annotation, to map interactions between germline and somatic alterations. We discovered 368 pathogenic germline variants and identified 5 breast cancer DNA repair-associated genes (BCDGs; BRCA1/BRCA2/CHEK2/PALB2/TP53). BCDG mutation carriers, especially those with two-hit inactivation, demonstrated younger onset, higher tumor mutation burden, and greater clinical benefits from platinum drugs, PARP inhibitors, and immune checkpoint inhibitors. Furthermore, we leveraged a multiomics cohort to reveal that clinical benefits derived from two-hit events are associated with increased genome instability and an immune-activated tumor microenvironment. We also established an ethnicity-specific tool to predict BCDG mutation and two-hit status for genetic evaluation and therapeutic decisions. Overall, this study leveraged the large sequencing cohort of Chinese breast cancers, optimizing genomics-guided selection of DNA damaging-targeted therapy and immunotherapy within a broader population.

Abstract Background Kirsten rat sarcoma (KRAS) and mutant KRASG12D have been implicated in human cancers, but it remains unclear whether their activation requires ubiquitination. This study aimed to investigate whether and how F-box and leucine-rich repeat 6 (FBXL6) regulates KRAS and KRASG12D activity in hepatocellular carcinoma (HCC). Methods We constructed transgenic mouse strains LC (LSL-Fbxl6 KI/+ ;Alb-Cre, n = 13), KC (LSL-Kras G12D/+ ;Alb-Cre, n = 10) and KLC (LSL-Kras G12D/+ ;LSL-Fbxl6 KI/+ ;Alb-Cre, n = 12) mice, and then monitored HCC for 320 d. Multiomics approaches and pharmacological inhibitors were used to determine oncogenic signaling in the context of elevated FBXL6 and KRAS activation. Co‑immunoprecipitation (Co-IP), Western blotting, ubiquitination assay and RAS activity detection assay were employed to investigate the underlying molecular mechanism by which FBXL6 activates KRAS. The pathological relevance of the FBXL6/KRAS/extracellular signal-regulated kinase (ERK)/mammalian target of rapamycin (mTOR)/proteins of relevant evolutionary and lymphoid interest domain 2 (PRELID2) axis was evaluated in 129 paired samples from HCC patients. Results FBXL6 is highly expressed in HCC as well as other human cancers (P

Abstract Aerial base stations (AeBS), as crucial components of air-ground integrated networks, can serve as the edge nodes to provide flexible services to ground users. Optimizing the deployment of multiple AeBSs to maximize system energy efficiency is currently a prominent and actively researched topic in the AeBS-assisted edge-cloud computing network. In this paper, we deploy AeBSs using multi-agent deep reinforcement learning (MADRL). We describe the multi-AeBS deployment challenge as a decentralized partially observable Markov decision process (Dec-POMDP), taking into consideration the constrained observation range of AeBSs. The hypergraph convolution mix deep deterministic policy gradient (HCMIX-DDPG) algorithm is designed to maximize the system energy efficiency. The proposed algorithm uses the value decomposition framework to solve the lazy agent problem, and hypergraph convolutional (HGCN) network is introduced to strengthen the cooperative relationship between agents. Simulation results show that the suggested HCMIX-DDPG algorithm outperforms alternative baseline algorithms in the multi-AeBS deployment scenario.

Abstract Radiotherapy is an important strategy in the comprehensive treatment of esophageal squamous cell carcinoma (ESCC). However, effectiveness of radiotherapy is still restricted by radioresistance. Herein, we aimed to understand the mechanisms underlying ESCC radioresistance, for which we looked into the potential role of YY1. YY1 was upregulated in radioresistant tissues and correlated with poor prognosis of patients with ESCC. YY1 depletion enhanced the radiosensitivity of ESCC in vitro and in vivo. Multi-group sequencing showed that downregulation of YY1 inhibited the transcriptional activity of Kinesin Family Member 3B (KIF3B), which further activated the Hippo signaling pathway by interacting with Integrin-beta1 (ITGB1). Once the Hippo pathway was activated, its main effector, Yes-associated protein 1 (YAP1), was phosphorylated in the cytoplasm and its expression reduced in the nucleus, thus enhancing the radiosensitivity by regulating its targeted genes. Our study provides new insights into the mechanisms underlying ESCC radioresistance and highlights the potential role of YY1 as a therapeutic target for ESCC.

Pepper (Capsicum annuum L.) is an economically important crop containing capsaicinoids in the seed and placenta, which has various culinary, medical, and industrial applications. Late embryogenesis abundant (LEA) proteins are a large group of hydrophilic proteins participating in the plant stress response and seed development. However, to date there have been no genome‐wide analyses of the LEA gene family in pepper. In the present study, 82 LEA genes were identified in the C. annuum genome and classified into nine subfamilies. Most CaLEA genes contain few introns (≤ 2) and are unevenly distributed across 10 chromosomes. Eight pairs of tandem duplication genes and two pairs of segmental duplication genes were identified in the LEA gene family; these duplicated genes were highly conserved and may have performed similar functions during evolution. Expression profile analysis indicated that CaLEA genes exhibited different tissue expression patterns, especially during embryonic development and stress response, particularly in cold stress. Three out of five CaLEA genes showed induced expression upon cold treatment. In summary, we have comprehensively reviewed the LEA gene family in pepper, offering a new perspective on the evolution of this family.

ABSTRACT Introduction and aims Sarcopenia is a complication of diabetes mellitus, which can increase hospitalization and lead to poor outcomes. The present study investigated the relationship between the serum musclin concentration and the sarcopenia morbidity in Chinese middle–elderly patients with type 2 diabetes mellitus. Methods We recruited 220 patients with type 2 diabetes mellitus, all of whom completed gait speed, handgrip strength tests, and whole‐body dual‐energy x‐ray measurements to calculate the appendicular skeletal muscle mass index (ASMI). The patients were divided into sarcopenia (n = 110) and non‐sarcopenia groups (n = 110). The serum musclin concentration was measured using an enzyme‐linked immunosorbent assay. Results The serum musclin concentration was significantly lower in the sarcopenia group (712.82 pg/mL) than in the non‐sarcopenia group (922.53 pg/mL). The serum musclin concentration positively correlated with the whole‐body skeletal mass (r = 0.230; P = 0.001). Sarcopenia morbidity declined as the quartile of serum musclin concentration increased (P = 0.001), and a negative correlation was observed between the serum musclin concentration and the prevalence of sarcopenia (odds ratio = 0.998, P = 0.001). The correlation remained when quartiles were considered. Conclusions The serum musclin concentration is an independent protective factor for sarcopenia in Chinese middle‐elderly patients with type 2 diabetes mellitus.

Immunosuppression undermines intestinal barrier integrity. Cow placenta extract (CPE) primarily consists of active peptides with immunomodulatory and antioxidant effects. This study aimed to examine the preventive effect of CPE against intestinal damage induced by cyclophosphamide (Cy) in immunosuppressed mice. Thirty-six mice were randomly allocated into three groups: control group (C), model group (M), and treatment group (CPE). The mice in the CPE group were provided with 1500 mg/kg/day of CPE via gavage. In the last 3 days, mice in the groups M and CPE received intraperitoneal injections of 80 mg/kg/day of Cy. The results showed that CPE improved intestinal barrier function by decreasing serum d-Lactate (D-LA) levels and diamine oxidase (DAO) activity, while elevating the relative expression of Occludin, zonula occludens-1 (ZO-1), and mucin-2 (MUC-2) mRNA. Additionally, CPE improved the immune organ index and elevated the levels of secretory immunoglobulin A (sIgA), superoxide dismutase (SOD), interleukin-1beta (IL-1β), interleukin-4 (IL-4), interleukin-10 (IL-10), and tumor necrosis factor-α (TNF-α) in the intestine, thereby enhancing intestinal mucosal immune function. Furthermore, CPE improved the diversity of intestinal microbiota and increased the abundance of Candidatus_Saccharimonas, Psychrobacter, and Enterorhabdus, which promoted the proper functioning of the intestines. These findings suggest that CPE effectively ameliorates Cy-induced intestinal damage by enhancing the intestinal barrier, improving immune function, and restoring intestinal microbiota.

Laser scanning has become a popular technology for monitoring structural deformation due to its ability to rapidly obtain 3D point clouds that provide detailed information about structures. In this study, the deformation of a complex steel frame structure is estimated by comparing the associated point clouds captured at two epochs. To measure its deformations, it is essential to extract the bottom flanges of the steel beams in the captured point clouds. However, manual extraction of numerous bottom flanges is laborious and the separation of beam bottom flanges and webs is especially challenging. This study presents an algorithm-driven approach for extracting all beams’ bottom flanges of a complex steel frame. RANdom SAmple Consensus (RANSAC), Euclidean clustering, and an originally defined point feature is sequentially used to extract the beam bottom flanges. The beam bottom flanges extracted by the proposed method are used to estimate the deformation of the steel frame structure before and after the removal of temporary supports to beams. Compared to manual extraction, the proposed method achieved an accuracy of 0.89 in extracting the beam bottom flanges while saving hours of time. The maximum observed deformation of the steel beams is 100 mm at a location where the temporal support was unloaded. The proposed method significantly improves the efficiency of the deformation measurement of steel frame structures using laser scanning.

Postnatal developmental stages of lung parenchyma in rhesus monkeys is about one-third that of humans. Alveoli in humans are reported to be formed up to 8 yr of age. We used design-based stereological methods to estimate the number of alveoli ([N.sub.alv]) in male and female rhesus monkeys over the first 7 yr of life. Twenty-six rhesus monkeys (13 males ranging in age from 4 to 1,920 days and lung volumes from 41.7 to 602 [cm.sup.3], 13 females ranging in age from 22 to 2,675 days and lung volumes from 43.5 to 380 [cm.sup.3]) were necropsied and lungs fixed, isotropically oriented, fractionated, sampled, embedded, and sectioned for alveolar counting. Parenchymal, alveolar, alveolar duct core air, and interalveolar septal tissue volumes increased rapidly during the first 2 yr with slowed growth from 2 to 7 yr. The rate of change was greater in males than females. [N.sub.lv] also showed consistent growth throughout the study, with increases in [N.sub.lv] best predicted by increases in lung volume. However, mean alveolar volume showed little relationship with age, lung volume, or body weight but was larger in females and showed a greater size distribution than in males. Alveoli increase in number but not volume throughout postnatal development in rhesus monkeys. stereology; parenchyma; alveolar ducts; postnatal development

Geant4 is a software toolkit for the simulation of the passage of particles through matter. It is used by a large number of experiments and projects in a variety of application domains, including high energy physics, astrophysics and space science, medical physics and radiation protection. Its functionality and modeling capabilities continue to be extended, while its performance is enhanced. An overview of recent developments in diverse areas of the toolkit is presented. These include performance optimization for complex setups; improvements for the propagation in fields; new options for event biasing; and additions and improvements in geometry, physics processes and interactive capabilities. Index Terms--Electromagnetic interactions, hadronic interactions, object-oriented technology, particle interactions, physics validation, simulation.

Data from space-borne detectors and ground-level neutron monitors, together with radiation transport codes, are applied to calculate the single-event effects environments in the atmosphere due to large solar particle events. Calculations are validated against data from Concorde and show the importance of allowing for the increased penetration of particles to lower latitudes during geomagnetic storms. For the solar particle events studied, high-latitude subsonic routes are shown to experience higher neutron fluxes than Concorde routes. Upset rates for typical commercial memories are calculated for a number of situations, and implications for aircrew dose are discussed. Index Terms--Aircraft electronics, cosmic rays, dosimetry, neutron radiation effects, proton radiation effects, single-event effects, solar radiation.

Members of the Malvaceae family, including Corchorus spp., Gossypium spp., Bombax spp., and Ceiba spp., are important sources of natural fibers. In the past decade, the genomes of several Malvaceae species have been assembled; however, the evolutionary history of Malvaceae species and the differences in their fiber development remain to be clarified. Here, we report the genome assembly and annotation of two natural fiber plants from the Malvaceae, Bombax ceiba and Ceiba pentandra, whose assembled genome sizes are 783.56 Mb and 1575.47 Mb, respectively. Comparative analysis revealed that whole-genome duplication and Gypsy long terminal repeat retroelements have been the major causes of differences in chromosome number (2n = 14 to 2n = 96) and genome size (234 Mb to 2676 Mb) among Malvaceae species. We also used comparative genomic analyses to reconstruct the ancestral Malvaceae karyotype with 11 proto-chromosomes, providing new insights into the evolutionary trajectories of Malvaceae species. MYB-MIXTA-like 3 is relatively conserved among the Malvaceae and functions in fiber cell-fate determination in the epidermis. It appears to perform this function in any tissue where it is expressed, i.e. in fibers on the endocarp of B. ceiba and in ovule fibers of cotton. We identified a structural variation in a cellulose synthase gene and a higher copy number of cellulose synthase-like genes as possible causes of the finer, less spinnable, weaker fibers of B. ceiba. Our study provides two high-quality genomes of natural fiber plants and offers insights into the evolution of Malvaceae species and differences in their natural fiber formation and development through multi-omics analysis.

Monitoring forest carbon (C) stocks is essential to better assess their role in the global carbon balance, and to better model and predict long-term trends and inter-annual variability in atmospheric CO2 concentrations. On a national scale, national forest inventories (NFIs) can provide estimates of forest carbon stocks, but these estimates are only available in certain countries, are limited by time lags due to periodic revisits, and cannot provide spatially continuous mapping of forests. In this context, remote sensing offers many advantages for monitoring above-ground biomass (AGB) on a global scale with good spatial (50–100 m) and temporal (annual) resolutions. Remote sensing has been used for several decades to monitor vegetation. However, traditional methods of monitoring AGB using optical or microwave sensors are affected by saturation effects for moderately or densely vegetated canopies, limiting their performance. Low-frequency passive microwave remote sensing is less affected by these saturation effects: saturation only occurs at AGB levels of around 400 t/ha at L-band (frequency of around 1.4 GHz). Despite its coarse spatial resolution of the order of 25 km × 25 km, this method based on the L-VOD (vegetation optical depth at L-band) index has recently established itself as an essential approach for monitoring annual variations in forest AGB on a continental scale. Thus, L-VOD has been applied to forest monitoring in many continents and biomes: in the tropics (especially in the Amazon and Congo basins), in boreal regions (Siberia, Canada), in Europe, China, Australia, etc. However, no reference study has yet been published to analyze L-VOD in detail in terms of capabilities, validation and results. This paper fills this gap by presenting the physical principles of L-VOD calculation, analyzing the performance of L-VOD for monitoring AGB and reviewing the main applications of L-VOD for tracking the carbon balance of global vegetation over the last decade (2010–2019).

Background and aimTraumatic brain injury (TBI), a leading cause of high morbidity and mortality, represents a significant global public health challenge. Currently, no effective treatment for TBI exists. Curcumin, an active compound extracted from the root of Curcuma longa, has demonstrated neuroprotective properties both in vitro and in vivo. Notably, it has shown potential in reducing oxidative stress and inflammation and enhancing redox balance. This paper conducts a systematic review and meta-analysis to explore curcumin’s role in TBI animal models extensively. The findings offer valuable insights for future human clinical trials evaluating curcumin as a therapeutic supplement or nutraceutical in TBI management.MethodsComprehensive literature searches were conducted across MEDLINE, Embase, Cochrane, Web of Science, and Google Scholar databases. These searches aimed to identify relevant manuscripts in all languages, utilizing the keywords “curcumin” and “traumatic brain injury.”ResultsThe final quantitative analysis included 18 eligible articles corresponding to animal studies. The analysis revealed that curcumin significantly reduced inflammatory cytokines, including IL-1β (p = 0.000), IL-6 (p = 0.002), and TNF-α (p = 0.000), across various concentrations, time points, and administration routes. Additionally, curcumin markedly enhanced the activity of oxidative stress markers such as SOD (p = 0.000), Sir2 (p = 0.000), GPx (p = 0.000), and Nrf2 (p = 0.000), while reducing MDA (p = 0.000), 4-HNE (p = 0.001), and oxyprotein levels (p = 0.024). Furthermore, curcumin improved cerebral edema (p = 0.000) and upregulated neuroprotective factors like synapsin I (p = 0.019), BDNF (p = 0.000), and CREB (p = 0.000), without reducing mNSS (p = 0.144). About autophagy and apoptosis, curcumin increased the activity of Beclin-1 (p = 0.000) and Bcl-2 (p = 0.000), while decreasing caspase-3 (p = 0.000), the apoptosis index (p = 0.000), and P62 (p = 0.002).ConclusionCurcumin supplementation positively affects traumatic brain injury (TBI) by alleviating oxidative stress and inflammatory responses and promoting neuroprotection. It holds potential as a therapeutic agent for human TBI. However, this conclusion necessitates further substantiation through high-quality literature and additional randomized controlled trials (RCTs).Systematic Review Registrationhttps://www.crd.york.ac.uk/prospero/. The registration number of PROSPERO: CRD42023452685.

Articular cartilage injuries present a significant global challenge, particularly in the aging population. These injuries not only restrict movement due to primary damage but also exacerbate elderly degenerative lesions, leading to secondary cartilage injury and osteoarthritis. Addressing osteoarthritis and cartilage damage involves overcoming several technical challenges in biological treatment. The use of induced mesenchymal stem cells (iMSCs) with functional gene modifications emerges as a solution, providing a more stable and controllable source of Mesenchymal Stem Cells (MSCs) with reduced heterogeneity. Furthermore, In addition, this review encompasses strategies aimed at enhancing exosome efficacy, comprising the cultivation of MSCs in three-dimensional matrices, augmentation of functional constituents within MSC-derived exosomes, and modification of their surface characteristics. Finally, we delve into the mechanisms through which MSC-exosomes, sourced from diverse tissues, thwart osteoarthritis (OA) progression and facilitate cartilage repair. This review lays a foundational framework for engineering iMSC-exosomes treatment of patients suffering from osteoarthritis and articular cartilage injuries, highlighting cutting-edge research and potential therapeutic pathways.