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Abstract Background Age-dependent accumulation of lipofuscin in the retinal pigment epithelium (RPE) is closely related to the etiology of autosomal recessive Stargardt’s disease (STGD1) and dry age-related macular degeneration (AMD). N-retinylidene-N-retinylethanolamine (A2E) is a leading component of RPE lipofuscin that is highly susceptible to blue light. Ferroptosis is an iron-dependent form of non-apoptotic cell death characterized by the accumulation of lipid peroxides to a lethal level, which plays an important role in retinal diseases. However, it remains unknown whether A2E functions as a physiological trigger for eliciting blue light-induced ferroptosis of RPE cells. Methods A2E-loaded RPE cells and Abca4 −/− Rdh8 −/− mice were exposed to blue light, respectively. Western blotting, immunofluorescence staining, reactive oxygen species (ROS) staining, intracellular iron staining, lipid peroxidation staining, fundus imaging, optical coherence tomography (OCT), hematoxylin–eosin (HE) staining, and electroretinography (ERG) were utilized to elucidate the role of blue light in A2E induced ferroptosis in the RPE and its potential mechanisms. Results Exposure of A2E to blue light promoted ferroptotic cell death in RPE cells by elevating ferrous ion (Fe2+) levels and inhibiting the solute carrier family 7 membrane 11 (SLC7A11)-glutathione (GSH)-glutathione peroxidase 4 (GPX4) axis. GPX4 inactivation and ROS generated by Fe2+ overload and GSH depletion precipitated lipid peroxidation and subsequent ferroptosis in A2E-containing RPE cells upon exposure to blue light. In addition to GSH supplement, repressing either Fe2+ by deferiprone (DFP) or lipid peroxidation with ferrostatin-1 (Fer-1) significantly protected RPE cells against ferroptosis caused by blue light illumination of A2E. Abca4 −/− Rdh8 −/− mice featured by an accelerated deposition of A2E in the RPE is an animal model for STGD1 and dry AMD. It was observed that ferroptosis was indeed present in the RPE of Abca4 −/− Rdh8 −/− mice following exposure to blue light. Notably, alleviating ferroptosis by intraperitoneally injected Fer-1 effectively rescued retinal function and ameliorated RPE/photoreceptor degeneration in blue light-exposed Abca4 −/− Rdh8 −/− mice. Conclusions Our results suggest the importance of blue light in A2E-mediated ferroptosis in the RPE, and deeply broaden the understanding of mechanisms underlying RPE atrophy arising from lipofuscin accumulation in STGD1 and dry AMD.

Abstract Background Co-inhibition of immune checkpoints lymphocyte-activation gene 3 (LAG-3) and PD-1 is believed to enhance cancer immunotherapy through synergistic effects. Herein, we evaluate the safety and efficacy of IBI110 (anti-LAG-3 antibody) with sintilimab (an anti-PD-1 antibody) in Chinese patients with advanced solid tumors. Methods In this open-label phase I study, phase Ia dose escalation of IBI110 monotherapy and phase Ib combination dose escalation of IBI110 plus sintilimab were conducted in patients with advanced solid tumors. Additionally, phase Ib combination dose expansion of IBI110 plus sintilimab and chemotherapy was conducted in previously untreated, advanced squamous non-small cell lung cancer (sqNSCLC) and HER-2 negative gastric cancer (GC). In phase Ia dose escalation, patients received IBI110 monotherapy at 0.01/0.1/0.3/1/3/10/20 mg/kg Q3W. In phase Ib dose escalation, patients received IBI110 at 0.3/0.7/1.5/3/5/8/10 mg/kg Q3W plus sintilimab 200 mg Q3W. In phase Ib combination dose expansion, patients received IBI110 at recommended phase 2 dose (RP2D) plus sintilimab 200 mg Q3W and chemotherapy. The primary endpoints were safety, tolerability and efficacy including objective response rate (ORR), disease control rate (DCR), duration of response (DoR), progression-free survival (PFS) assessed by RECIST v1.1 and overall survival (OS). The secondary endpoints included pharmacokinetics, pharmacodynamics and immunogenicity. Results In phase Ia dose escalation (n = 28), treatment-related adverse events (TRAEs) occurred in 67.9% patients and grade ≥ 3 TRAEs occurred in 21.4% patients. In phase Ib combination dose escalation (n = 45), TRAEs occurred in 75.6% patients and grade ≥ 3 TRAEs occurred in 22.2% patients. No dose-limiting toxicity (DLT) was observed. The most common TRAE was anemia (17.9%, including 3.6% ≥ G3) in phase Ia dose escalation of IBI110 monotherapy (n = 28), aspartate aminotransferase increased (28.9%, all G1-G2) in phase Ib dose escalation of IBI110 plus sintilimab (n = 45), anemia (70.0%, all G1-G2) in phase Ib dose expansion in sqNSCLC (n = 20), and neutrophil count decreased (64.7%, including 17.6%≥ G3) in phase Ib dose expansion in GC (n = 17). The RP2D of IBI110 was determined at 200 mg (3 mg/kg) Q3W. ORR in phase Ia/Ib dose escalation was 3.6% with IBI110 monotherapy and 14% with IBI110 plus sintilimab. In phase Ib combination dose expansion of IBI110 plus sintilimab and chemotherapy, unconfirmed and confirmed ORR in sqNSCLC (n = 20) was 80.0% (95% CI, 56.3–94.3) and 75.0% (95% CI, 50.9–91.3), respectively and in GC (n = 17) was 88.2% (95% CI, 63.6–98.5) and 70.6% (95% CI, 44.0-89.7), respectively. Conclusions IBI110 monotherapy and in combination with sintilimab were well-tolerated in Chinese patients with advanced solid tumors. Encouraging efficacy of IBI110 in combination with sintilimab and chemotherapies was observed in sqNSCLC and GC. Trial registration ClinicalTrials.gov Identifier: NCT04085185.

Abstract Aiming at the frequency instability caused by insufficient energy in microgrids and the low willingness of grid source and load storage to participate in optimization, a microgrid source and load storage energy minimization method based on an improved competitive deep Q network algorithm and digital twin is proposed. We have constructed a basic framework structure for the coordinated operation of source grid load and energy storage, and analyzed the modules on the power supply side, grid side, load side, and energy storage side. Under the improved competitive deep Q network algorithm, modifications were made to the energy storage of microgrid loads. Based on the processing results, the objective function for optimizing microgrid source load energy storage is constructed using digital twin technology, and the optimization of the objective function is achieved to solve the optimization objective function for microgrid source load energy storage and complete the optimization of microgrid source load energy storage. The experimental results show that this method can control the distortion rate within 5.12%, with frequency fluctuations around 50.0 Hz, and relatively good MSE, MAE, and R2 values. This method can effectively control frequency fluctuations and has a good effect on optimizing energy storage for microgrid power sources and loads.

Abstract Background Identification of active components of traditional Chinese Medicine (TCM) and their respective targets is important for understanding the mechanisms underlying TCM efficacy. However, there are still no effective technical methods to achieve this. Methods Herein, we have established a method for rapidly identifying targets of a specific TCM and interrogating the targets with their corresponding active components based on Isothermal Shift Assay (iTSA) and database interrogation. Results We optimized iTSA workflow and identified 110 targets for Danhong injection (DHI) which is used as an effective remedy for cardiovascular and cerebrovascular diseases. Moreover, we identified the targets of the nine major ingredients found in DHI. Database interrogation found that the potential targets for DHI, in which we verified that ADK as the target for salvianolic acid A and ALDH1B1 as the target for protocatechualdehyde in DHI, respectively. Conclusion Overall, we established a novel paradigm model for the identification of targets and their respective ingredients in DHI, which facilitates the discovery of drug candidates and targets for improving disease management and contributes to revealing the underlying mechanisms of TCM and fostering TCM development and modernization. Graphical Abstract

Abstract Accurate segmentation of retinal blood vessels is crucial for enhancing diagnostic efficiency and preventing disease progression. However, the small size and complex structure of retinal blood vessels, coupled with low contrast in corresponding fundus images, pose significant challenges for this task. We propose a novel approach for retinal vessel segmentation, which combines the transformer and convolutional dual-path decoding U-Net (TCDDU-Net). We propose the selective dense connection swin transformer block, which converts the input feature map into patches, introduces MLPs to generate probabilities, and performs selective fusion at different stages. This structure forms a dense connection framework, enabling the capture of long-distance dependencies and effective fusion of features across different stages. The subsequent stage involves the design of the background decoder, which utilizes deformable convolution to learn the background information of retinal vessels by treating them as segmentation objects. This is then combined with the foreground decoder to form a dual-path decoding U-Net. Finally, the foreground segmentation results and the processed background segmentation results are fused to obtain the final retinal vessel segmentation map. To evaluate the effectiveness of our method, we performed experiments on the DRIVE, STARE, and CHASE datasets for retinal vessel segmentation. Experimental results show that the segmentation accuracies of our algorithms are 96.98, 97.40, and 97.23, and the AUC metrics are 98.68, 98.56, and 98.50, respectively.In addition, we evaluated our methods using F1 score, specificity, and sensitivity metrics. Through a comparative analysis, we found that our proposed TCDDU-Net method effectively improves retinal vessel segmentation performance and achieves impressive results on multiple datasets compared to existing methods.

BackgroundHuman Papillomavirus (HPV) infection is a ubiquitous sexually transmitted infection globally, frequently associated with sexual behaviors characterized by increased frequency and multiple partnerships. The relationship between varying levels of dietary iron intake and the occurrence of Human Papillomavirus (HPV) infection remains an unresolved question in the scientific community. The objective of our study was to investigate the potential relationship between the consumption of dietary iron and HPV infection.MethodsOur investigation drew upon comprehensive datasets from 7,819 participants enrolled in the National Health and Nutrition Examination Survey (NHANES) from 2005 to 2016. Employing a cross-sectional analytical framework, we delved into the potential correlation between dietary iron consumption and Human Papillomavirus infection. To statistically assess this relationship, we utilized weighted multivariate logistic regression models. Additionally, we implemented smooth curve fitting and threshold effect analysis, to delineate the complex, nonlinear association between iron intake and HPV infection. Furthermore, we conducted subgroup analyses.ResultsAfter adjusting for multiple confounding variables, our results demonstrated a statistically significant inverse association between iron intake and HPV infection (OR = 0.988, 95% CI: 0.979–0.998, p = 0.018). It’s worth noting that, in comparison to individuals in the quartile with the lowest iron intake, those in the highest quartile exhibited a 23.2% reduction in the odds of HPV infection for each incremental unit of iron intake (OR = 0.768, 95% CI: 0.634 to 0.930, p = 0.009). A refined analysis employing smoothing curve fitting techniques unveiled an L-shaped correlation, delineating a specific relationship between dietary iron intake and the incidence rate of Human Papillomavirus infection. When iron intake was

Periodontal disease stands the leading cause of tooth loss in adults. While scaling and root planning is considered the “gold standard” treatment, it is often insufficient in efficiently eliminating anaerobic bacteria from deep periodontal pockets. In this work, an antibiotic-free and photo-curing hyaluronic acid-Janus (H-Janus) antibacterial pack was developed to inhibit the growth and colonization of residual bacteria within the pockets for reducing the recurrence of periodontitis. Our results demonstrated that a 4 wt% precursor solution of the antibacterial packs could be molded into various shapes by exposure to UV irradiation for less than 1 min, allowing the packs to seamlessly fill the irregular spaces of periodontal pockets. In vitro studies showed that the antibacterial packs gradually released lauric acid and oxygen over 7 days, exhibiting significant anti-biofilm effects against both aerobic and anaerobic bacteria. Notably, animal experiments confirmed that H-Janus antibacterial packs markedly improved the clinical scores in rats with periodontitis by inhibiting bacterial growth, alleviating inflammation, and fostering the regeneration of periodontal tissues. In light of their precise elimination of bacterial colonization and modulation of the infectious microenvironment, the H-Janus antibacterial packs show promising therapeutic potential for preventing the recurrence of periodontal pathogens following scaling and root planning.

Abstract The recent development of nanobiomaterials has shed some light on the field of periodontal tissue regeneration. Laponite (LAP), an artificially synthesized two-dimensional (2D) disk-shaped nanosilicate, has garnered substantial attention in regenerative biomedical applications owing to its distinctive structure, exceptional biocompatibility and bioactivity. This study endeavors to comprehensively evaluate the influence of LAP on periodontal regeneration. The effects of LAP on periodontal ligament cells (PDLCs) on osteogenesis, cementogenesis and angiogenesis were systematically assessed, and the potential mechanism was explored through RNA sequencing. The results indicated that LAP improved osteogenic and cementogenic differentiation of PDLCs, the regulatory effects of LAP on PDLCs were closely correlated with activation of PI3K-AKT signaling pathway. Moreover, LAP enhanced angiogenesis indirectly via manipulating paracrine of PDLCs. Then, LAP was implanted into rat periodontal defect to confirm its regenerative potential. Both micro-CT and histological analysis indicated that LAP could facilitate periodontal tissue regeneration in vivo. These findings provide insights into the bioactivity and underlying mechanism of LAP on PDLCs, highlighting it might be a potential therapeutic option in periodontal therapy.

Abstract As the Internet of Vehicles advances, the demand for timely data acquisition by vehicle users continues to escalate, albeit confronted with the challenge of excessive data retrieval latency. The emergence of edge computing provides technical support for the development of vehicular networks by caching data in advance to reduce data acquisition latency. Therefore, how to effectively cache and query data becomes a key issue in addressing the timeliness of data acquisition in vehicular networks. In this paper, we investigate an efficient query optimization model to minimize data acquisition latency. Firstly, based on the distribution of data query frequencies across different servers, we propose an edge collaborative caching strategy using a tabu search algorithm. This strategy prioritizes high-traffic data by finding two optimal storage nodes for each high-traffic data in descending order of data popularity, ensuring a backup within the collaborative domain for each data segment. This not only reduces data transmission latency between nodes during task execution but also prevents single-point failures. Secondly, we deploy cuckoo filters on edge nodes to enable rapid localization of cached data nodes when users query data, thus reducing data processing latency. Finally, simulation results demonstrate that the proposed query optimization model outperforms other schemes in terms of average data query latency.

Abstract Urinary incontinence is a common complication in stroke survivors for whom new interventions are needed. This study investigated the therapeutic effect of low-frequency (LF) repeated transcranial magnetic stimulation (rTMS) on the contralesional primary motor cortex (M1) in patients with poststroke urinary incontinence (PSI). A total of 100 patients were randomly assigned to the rTMS group or sham-rTMS group on basis of the intervention they received. Both groups underwent five treatment sessions per week for 4 weeks. Data from the urodynamic examination were used as the primary outcome. The secondary outcome measures were questionnaires and pelvic floor surface electromyography. After 4 weeks of intervention, the maximum cystometric capacity (MCC), maximum detrusor pressure (Pdet.max), residual urine output, overactive bladder score (OABSS) (including frequency, urgency, and urgency urinary incontinence), and the ICIQ-UI SF improved significantly in the rTMS group compared with those in the sham-rTMS group (P 0.05). Our data confirmed that 4 weeks of LF-rTMS stimulation on the contralateral M1 positively affects poststroke urinary incontinence in several aspects, such as frequency, urgency urinary incontinence, MCC, end-filling Pdet, OABSS, and ICIQ-UI SF scores.

A comprehensive understanding of tumor heterogeneity, tumor microenvironment and the mechanisms of drug resistance is fundamental to advancing breast cancer research. While single-cell RNA sequencing has resolved the issue of “temporal dynamic expression” of genes at the single-cell level, the lack of spatial information still prevents us from gaining a comprehensive understanding of breast cancer. The introduction and application of spatial transcriptomics addresses this limitation. As the annual technical method of 2020, spatial transcriptomics preserves the spatial location of tissues and resolves RNA-seq data to help localize and differentiate the active expression of functional genes within a specific tissue region, enabling the study of spatial location attributes of gene locations and cellular tissue environments. In the context of breast cancer, spatial transcriptomics can assist in the identification of novel breast cancer subtypes and spatially discriminative features that show promise for individualized precise treatment. This article summarized the key technical approaches, recent advances in spatial transcriptomics and its applications in breast cancer, and discusses the limitations of current spatial transcriptomics methods and the prospects for future development, with a view to advancing the application of this technology in clinical practice.

Abstract Colitis, accompanied by the accumulation of reactive oxygen species (ROS) in the intestinal tract, is a risk factor for colorectal cancer (CRC). Our previous studies indicate that nicotinamide mononucleotide (NMN) replenishment reduces chronic inflammation. In this study, we confirm that NMN supplementation reduces inflammatory cytokine levels and oxidative tissue damage in an azoxymethane/dextran sulfate sodium (AOM/DSS)‐induced colitis‐associated cancer (CAC) model. Mice treated with NMN developed fewer colon tumors than untreated animals under the same AOM/DSS treatment conditions. Quantitative proteomic analysis revealed a decrease in signal transducer and activator of transcription 1 (STAT1) expression in the CAC model. We demonstrate that STAT1 overexpression induces G1 arrest by downregulating CDK6 expression and suppressing tumor cell proliferation and migration. Of note, H2O2 induced trioxidation of the STAT1 protein and promoted its degradation, which was partially reversed by NMN supplementation. Upon H2O2 treatment, Cys155 in STAT1 was oxidized to sulfonic acid, whereas the mutation of Cys155 to alanine abolished ROS‐mediated STAT1 degradation. These results indicate that oxidative stress induces STAT1 degradation in tumor cells and possibly in CAC tissues, whereas supplementation with NMN protects STAT1 from oxidation‐induced degradation and prevents tumorigenesis. This study provides experimental evidence for the development of NMN‐mediated chemoprevention strategies for CRC.

BackgroundThis study aims to investigate the clinicopathological and ultrasonography characteristics of combined hepatocellular-cholangiocarcinoma (cHCC-CCA) and its correlation with microvascular invasion (MVI), as well as the predictive value of contrast-enhanced ultrasound (CEUS) imaging.MethodsA retrospective analysis was conducted on 57 patients diagnosed with cHCC-CCA between November 2017 and May 2023 at Guizhou Provincial People’s Hospital. Among them, 27 patients were MVI-positive and 30 patients were MVI-negative, all of whom underwent preoperative CEUS within 2 weeks. Clinical data, ultrasonographic findings, and CEUS features were compared between the two groups to analyze the influencing factors and predictive value of MVI in cHCC-CCA patients.ResultsCompared to the MVI-negative group, the MVI-positive group showed a higher proportion of tumors with a maximum diameter greater than 5 cm, elevated alpha-fetoprotein (AFP) levels, low echo halo around the tumor, non-smooth tumor contour, peripheral irregular rim-like enhancement and early washout (≤60s) with nodular patterns on CEUS (P

Abstract BackgroundHealth-related rumors and misconceptions are spreading at an alarming rate, fueled by the rapid development of the internet and the exponential growth of social media platforms. This phenomenon has become a pressing global concern, as the dissemination of false information can have severe consequences, including widespread panic, social instability, and even public health crises. ObjectiveThe aim of the study is to compare the accuracy of rumor identification and the effectiveness of health science popularization between 2 generated large language models in Chinese (GPT-4 by OpenAI and Enhanced Representation through Knowledge Integration Bot [ERNIE Bot] 4.0 by Baidu). MethodsIn total, 20 health rumors and misconceptions, along with 10 health truths, were randomly inputted into GPT-4 and ERNIE Bot 4.0. We prompted them to determine whether the statements were rumors or misconceptions and provide explanations for their judgment. Further, we asked them to generate a health science popularization essay. We evaluated the outcomes in terms of accuracy, effectiveness, readability, and applicability. Accuracy was assessed by the rate of correctly identifying health-related rumors, misconceptions, and truths. Effectiveness was determined by the accuracy of the generated explanation, which was assessed collaboratively by 2 research team members with a PhD in nursing. Readability was calculated by the readability formula of Chinese health education materials. Applicability was evaluated by the Chinese Suitability Assessment of Materials. ResultsGPT-4 and ERNIE Bot 4.0 correctly identified all health rumors and misconceptions (100% accuracy rate). For truths, the accuracy rate was 70% (7/10) and 100% (10/10), respectively. Both mostly provided widely recognized viewpoints without obvious errors. The average readability score for the health essays was 2.92 (SD 0.85) for GPT-4 and 3.02 (SD 0.84) for ERNIE Bot 4.0 (PP ConclusionsERNIE Bot 4.0 demonstrated similar accuracy to GPT-4 in identifying Chinese rumors. Both provided widely accepted views, despite some inaccuracies. These insights enhance understanding and correct misunderstandings. For health essays, educators can learn from readable language styles of GLLMs. Finally, ERNIE Bot 4.0 aligns with Chinese expression habits, making it a good choice for a better Chinese reading experience.

Background Body mass index (BMI) is associated with diabetic nephropathy (DN). However, the mediator factors in the BMI-DN effects remain unclear.Methods Univariate and multivariate Mendelian randomization (MR) analysis were performed to estimate the association between six lifestyles (moderate to vigorous physical activity levels, years of schooling, BMI, nap during day, number of treatments/medications taken and coffee intake) and DN. MR Egger, Weighted median, Simple mode, and Weighted mode was supplemental methods to Inverse variance weighted. Sensitivity analysis included heterogeneity test, horizontal pleiotropy test, and Leave-One-Out. Additionally, mediation MR was conducted to evaluate the mediating role of lifestyles between BMI and DN. Finally, functional enrichment analysis based on the mediation MR results was performed.Results univariate and multivariate Mendelian randomization (MR) analysis were performed to estimate the association between six lifestyles (moderate to vigorous physical activity levels, years of schooling, BMI, nap during day, number of treatments/medications taken and coffee intake) and DN. MR Egger, Weighted median, Simple mode, and Weighted mode was supplemental methods to Inverse variance weighted. Sensitivity analysis included heterogeneity test, horizontal pleiotropy test, and Leave-One-Out. Additionally, mediation MR was conducted to evaluate the mediating role of lifestyles between BMI and DN. Finally, functional enrichment analysis based on the mediation MR results was performed.Conclusion our results supported mediation role of vigorous physical activity level and number of treatments/medications in BMI-DN effects.

Background Immigrants are disproportionately affected by cardiovascular disease burden. Heart health screenings, including blood pressure, fasting blood glucose (FBG), and blood cholesterol screenings, can help identify cardiovascular disease risk. Evidence on heart health screenings among diverse immigrant groups is still limited. This study examined the disparities in heart health screenings among the immigrant population compared with US‐born White adults. Methods and Results A cross‐sectional design was used to analyze data from the 2011 to 2018 National Health Interview Survey. Generalized linear models with Poisson distribution were applied to compare the prevalence of annual blood pressure, fasting blood glucose, and blood cholesterol screenings among Latino, Black, and Asian immigrants and US‐born White adults. The analysis included 145 149 adults (83.60% US‐born White adults, 9.55% Latino immigrants, 1.89% Black immigrants, and 4.96% Asian immigrants), with a mean age of 50 years and 53.62% women. Latino (adjusted odds ratio [aOR], 0.92 [95% CI, 0.91–0.93]) and Asian (aOR, 0.93 [95% CI, 0.92–0.94]) immigrants were less likely to have blood pressure screening than US‐born White adults. Latino (aOR, 1.22 [95% CI, 1.19–1.25]), Black (aOR, 1.15 [95% CI, 1.09–1.21]), and Asian (aOR, 1.12 [95% CI, 1.08–1.15]) immigrants were more likely to have fasting blood glucose screening, and Latino (aOR, 1.11 [95% CI, 1.09–1.13]), Black or (aOR, 1.12 [95% CI, 1.09–1.16]), and Asian (aOR, 1.05 [95% CI, 1.04–1.07]) immigrants were more likely to have blood cholesterol screening than US‐born White adults. Conclusions Latino and Asian immigrants have lower odds of annual blood pressure screenings than US‐born White adults. More studies exploring facilitators and barriers to the accessibility and use of heart health screenings are needed.

Abstract Object detection plays a vital role in remote sensing applications. Although object detection has achieved proud results in natural images, these methods are difficult to be directly applied to remote sensing images. Remote sensing images often have complex backgrounds and small objects, which results in a highly unbalanced distribution of foreground and complex background information. In order to solve the above problems, this paper proposes a multi-head channel and spatial trans-attention (MCSTA) module, which performs remote pixel interaction from the channel and spatial dimensions respectively to complete the attention feature capture function. It is a plug-and-play module that can be easily embedded in any other natural image object detection convolutional neural network, making it quickly applicable to remote sensing images. First, in order to reduce computational complexity and improve feature richness, we use a special linear convolution to obtain three projection features instead of the simple matrix multiplication transformation in Transformer. Second, we obtain trans-attention maps in different dimensions in a manner similar to the self-attention mechanism to capture the interrelationships of features in channels and spaces. In this process, we use a multi-head mechanism to perform parallel operations to improve speed. Furthermore, in order to avoid large-scale matrix operations, we specially designed an attention blocking mode to reduce computer memory usage and increase operation speed. Finally, we embedded the trans-attention module into YOLOv8, added a new detection head and optimized the feature fusion method, thus designing a lightweight small object detection model named TA-YOLO for remote sensing images. It has fewer parameters than the benchmark model YOLOv8, and its mAP on the PASCAL VOC and VisDrone data sets increased by 1.3% and 6.2% respectively. The experimental results prove the powerful function of the trans-attention module and the excellent performance of TA-YOLO.

Abstract Blockchain has penetrated in various fields, such as finance, healthcare, supply chain, and intelligent transportation, but the value exchange between different blockchains limits their expansion. Cross-chain technology, such as notary mechanism, enables asset exchanges between different blockchain networks. However, existing research still confronts problems such as single inherent value evaluation, collusion risk, credit evaluation and unreasonable resource allocation, making it difficult to ensure the security of cross-chain asset transactions. So this paper proposes a cross-chain asset trading scheme based on edge cloud storage to improve the reliability of notaries and the security of cross-chain value exchange. Firstly, introduce the entropy weight method to determine indicators and adopt multi indicator evaluation to reduce the risk of collusion between notaries and users; Secondly, design a multi-indicator credit evaluation method to improve the accuracy of the evaluation; Finally, design a new and old notary node share allocation method to improve the rationality of resource allocation.The experiment shows that the scheme designed in this paper can reduce the risk of collusion, more accurately screen out high credit nodes to act as notaries, and make resource allocation more reasonable.

Wireless Sensor Network (WSN) is a distributed sensor network composed a large number of nodes with low cost, low performance and self-management. The special structure of WSN brings both convenience and vulnerability. For example, a malicious participant can launch attacks by capturing a physical device. Therefore, node authentication that can resist malicious attacks is very important to network security. Recently, blockchain technology has shown the potential to enhance the security of the Internet of Things (IoT). In this paper, we propose a Blockchain-empowered Authentication Scheme (BAS) for WSN. In our scheme, all nodes are managed by utilizing the identity information stored on the blockchain. Besides, the simulation experiment about worm detection is executed on BAS, and the security is evaluated from detection and infection rate. The experiment results indicate that the proposed scheme can effectively inhibit the spread and infection of worms in the network.

Artificial materials for the potential treatment of bone defects are very trendy in such research fields. To investigate a hydrogel scaffold with better mechanical strength and osteoinductivity is always a challenge since brittle and soft properties are always the problems in traditional hydrogels. In our study, a novel gelatin/chitosan hydrogel crosslinked by a double network filled with lignin and calcium silicate is fabricated. Enhancements of mechanical strength, low swelling ratio, and improvement in osteoinductivity were achieved in this composite double network hydrogels. The results revealed that lignin was a key factor in raising the compressive strength and stability of the hydrogel because more hydrogen bonds were formed between lignin and the crosslinking network. Even after swelling equilibrium, the compressive strength remained almost unchanged. In addition, the hydrogel groups with a higher ratio of lignin also had lower cytotoxicity and improved osteoinductivity of pre-osteoblasts while the increasing concentration of calcium silicate progressively weakened these performances. Therefore, the gelatin/chitosan double network hydrogel reinforced by lignin would be a potential bone tissue-engineered artificial material.

Abstract Aiming at the problems of identifying storage pest tobacco pest beetles from images that have few object pixels and considerable image noise, and therefore suffer from lack of information and identifiable features, this paper proposes an automatic monitoring method of tobacco beetle based on Multi-scale Global residual Feature Pyramid Network and Dual-path Deformable Attention (MGrFPN-DDrGAM). Firstly, a Multi-scale Global residual Feature Pyramid Network (MGrFPN) is constructed to obtain rich high-level semantic features and more complete information on low-level features to reduce missed detection; Then, a Dual-path Deformable receptive field Guided Attention Module (DDrGAM) is designed to establish long-range channel dependence, guide the effective fusion of features and improve the localization accuracy of tobacco beetles by fitting the spatial geometric deformation features of and capturing the spatial information of feature maps with different scales to enrich the feature information in the channel and spatial. Finally, to simulate a real scene, a multi-scene tobacco beetle dataset is created. The dataset includes 28,080 images and manually labeled tobacco beetle objects. The experimental results show that under the framework of the Faster R-CNN algorithm, the detection precision and recall rate of this method can reach 91.4% and 98.4% when the intersection ratio (IoU) is 0.5. Compared with Faster R-CNN and FPN, when the intersection ratio (IoU) is 0.7, the detection precision is improved by 32.9% and 6.9%, respectively. The proposed method is superior to the current mainstream methods.

Abstract Oncolytic virotherapy holds promise for cancer treatment, but the factors determining its oncolytic activity remain unclear. Neutrophil extracellular traps (NETs) are associated with cancer progression, yet their formation mechanism and role in oncolytic virotherapy remain elusive. In this study, we demonstrate that, in glioma, upregulation of IGF2BP3 enhances the expression of E3 ubiquitin protein ligase MIB1, promoting FTO degradation via the ubiquitin-proteasome pathway. This results in increased m6A-mediated CSF3 release and NET formation. Oncolytic herpes simplex virus (oHSV) stimulates IGF2BP3-induced NET formation in malignant glioma. In glioma models in female mice, a BET inhibitor enhances the oncolytic activity of oHSV by impeding IGF2BP3-induced NETosis, reinforcing virus replication through BRD4 recruitment with the CDK9/RPB-1 complex to HSV gene promoters. Our findings unveil the regulation of m6A-mediated NET formation, highlight oncolytic virus-induced NETosis as a critical checkpoint hindering oncolytic potential, and propose targeting NETosis as a strategy to overcome resistance in oncolytic virotherapy.

Abstract Artificial intelligence and blockchain technology have become indispensable in the era of the digital economy, particularly in the field of financial financing. However, when it comes to supply chain finance (SCF), existing models primarily focus on risk identification and credit evaluation, neglecting the critical aspects of trust transfer continuity and reliability within the chain. To address this issue, this paper proposes a blockchain-based transitive trust model for SCF, which ensures seamless trust transfer from core enterprises to bottom suppliers during financing enterprise credit evaluation. The model utilizes multi-layer metrics to calculate the comprehensive trust value of underlying suppliers, serving as the basis for credit delivery. Additionally, the model stores transitive signature receivable warrants on the blockchain and utilizes splittable delivery of warrants to underlying suppliers. The model’s rationality and correctness are verified through experimental analysis, with results demonstrating that the transitive trust model enhances Small and Medium-Sized Enterprises’ (SMEs) trust at the bottom of the supply chain, thus alleviating financing difficulties for SMEs.

Abstract Cloud computing has data leakage from all parties, security protection of private data, and existing solutions do not provide a trade-off between security and overhead. With distributed data communication due to data barriers, information interaction security and data computation security have become challenges for secure computing. Combining cloud computing with secure multiparty computation can provide a higher level of data protection while maintaining the benefits of cloud computing. In this case, data can be stored in the cloud and computed through SMPC protocols, thus protecting the privacy and security of the data. However, multiple rounds of information interaction are often required, increasing the communication overhead, and the security strength is limited by the hardness assumption. In this paper, we work to achieve an optimal setting of the number of rounds in secure multi-party computation on the cloud to achieve a sublinear communication overhead and improve the security concept. A 2-round SMPC protocol is constructed in the framework of Universally Composable (UC). A 2-round SMPC protocol is constructed that uses multilinear maps based on the Learning from Errors (LWE) assumption. The participant encodes the input and sends it via broadcast to reduce the interaction, homomorphic computational encoding information for secure access to computational data and secure the SMPC protocol through UC security. This paper extends the participants to multiple parties, reduces the communication rounds to 2, the protocol achieves sublinear communication overhead in poly polynomial time, smaller setup size to poly(k), and static security is achieved.

Retinal diseases impair the normal function of the visual system, making accurate segmentation of retinal vessels crucial. This paper proposes an improved U-Net network, namely Mitigating Information Loss U-Net (MILU-Net), for retinal vessel segmentation. The network introduces the Multi-Scale Adaptive Detail Feature Fusion (MSADFF) module, ensuring effective fusion of features at different scales before skip connections to reduce information loss. Simultaneously, the Dual Path Upsampling (DPUS) module is employed to enhance image resolution and compensate for spatial and channel information. Experiments on the DRIVE/STARE datasets demonstrate that MILU-Net outperforms in accuracy, sensitivity, specificity, AUC, and F1-Score metrics. Compared to the original U-Net, MILU-Net shows improvements of 1.44% and 1.84% in AUC, as well as 7.15% and 6.35% in sensitivity. Compared to the advanced Attention U-Net, MILU-Net achieves increases of 1.20% and 0.45% in ACC, as well as 2.63% and 2.71% in F1-Score, respectively. These results indicate the significant advantages of MILU-Net in retinal vessel segmentation tasks.

To at the low robustness of the existing model for occluded object detection, an occluded object detection algorithm based on fuzzy sample anchor box IoU Matching degree Deviation Aware(IoU_MDA)is proposed. Firstly, fuzzy samples are defined based on Anchor-based, which reflects the degree of object occlusion. Secondly, IoU_MDA is proposed to quantify the degree of interference experienced by fuzzy samples. Then, IoU_MDA_Loss is constructed based on IoU_MDA, combined with IoU and the balance parameter $\Phi$ . To address class imbalance issues and enhance model generality, intra-class and inter-class fuzzy weights, and fuzzy sample focusing parameters are designed on the basis of the initial IoU_MDA_Loss. An occluded object training scheme is designed based on IoU perception, and non-fuzzy sample weight balancing parameters are constructed. Finally, IoU_MDA_Loss is merged with Focal Loss to obtain IoU_MDA_Focal Loss, simultaneously enhancing the detection performance of fuzzy samples and difficult-to-distinguish samples. The experimental results on the WiderPerson and VOC2007 datasets show that the mAP of IoU_MDA_Loss has increased by 2.04%, 2.36%, and IoU_MDA_Focal Loss has increased by 1.82%, 2.65%, respectively, compared to the baseline model. The detection performance surpasses current mainstream algorithms.

Abstract With the development of cloud computing and deep learning, an increasing number of artificial intelligence models have been applied to reality. Such as videos on cell phones can be uploaded to the cloud for storage, which is detected by cloud arithmetic. Nevertheless, achieving this goal requires frequent consideration of the security of the model, since videos or images that go to the cloud, it is very likely to receive an adversarial attack. Regarding object detection, there has however been slow advancement in robustness research in this area. This is because training a target detection model requires a lot of arithmetic and time. Moreover, the current research has only slightly reduced the gap between clean and adversarial samples. To alleviate this problem, we propose a uniform perspective object detection robustness model based on bilinear interpolation that can accurately identify clean and adversarial samples. We propose the robustness optimization based on uniform metric perspective (RPU) for feature learning of clean and adversarial samples, drawing on the fine-grained idea. Following this, we analyze the fragility of the adversarial samples and consequently use the proposed perturbation filtering verification (PVB) based on bilinear interpolation. With slightly degraded clean sample detection performance, it substantially improves the robustness of object detection. Extensive experiments on PASCAL VOC and MS COCO show that our model guarantees the detection performance of clean samples and increases the detection performance of adversarial samples. The work we did has been open-sourced on GitHub: https://github.com/KujouRiu/RPU-PVB .

Abstract Background Emerging evidence suggests the critical roles of N6-methyladenosine (m6A) RNA modification in tumorigenesis and tumor progression. However, the role of m6A in non-small cell lung cancer (NSCLC) is still unclear. This study aimed to explore the role of the m6A demethylase fat mass and obesity-associated protein (FTO) in the tumor metastasis of NSCLC. Methods A human m6A epitranscriptomic microarray analysis was used to identify downstream targets of FTO. Quantitative real-time PCR (qRT‒PCR) and western blotting were employed to evaluate the expression levels of FTO and FAP in NSCLC cell lines and tissues. Gain-of-function and loss-of-function assays were conducted in vivo and in vitro to assess the effects of FTO and FAP on NSCLC metastasis. M6A-RNA immunoprecipitation (MeRIP), RNA immunoprecipitation (RIP), luciferase reporter assays, and RNA stability assays were used to explore the mechanism of FTO action. Co-immunoprecipitation (co-IP) assays were used to determine the mechanism of FAP in NSCLC metastasis. Results FTO was upregulated and predicted poor prognosis in patients with NSCLC. FTO promoted cell migration and invasion in NSCLC, and the FAK inhibitor defactinib (VS6063) suppressed NSCLC metastasis induced by overexpression of FTO. Mechanistically, FTO facilitated NSCLC metastasis by modifying the m6A level of FAP in a YTHDF2-dependent manner. Moreover, FTO-mediated metastasis formation depended on the interactions between FAP and integrin family members, which further activated the FAK signaling. Conclusion Our current findings provided valuable insights into the role of FTO-mediated m6A demethylation modification in NSCLC metastasis. FTO was identified as a contributor to NSCLC metastasis through the activation of the FAP/integrin/FAK signaling, which may be a potential therapeutic target for NSCLC. Video Abstract

Abstract Despite improvements in medical and surgical therapies, a significant portion of patients with critical limb ischemia (CLI) are considered as “no option” for revascularization. In this work, a nitric oxide (NO)-boosted and activated nanovesicle regeneration kit (n-BANK) is constructed by decorating stem cell-derived nanoscale extracellular vesicles with NO nanocages. Our results demonstrate that n-BANKs could store NO in endothelial cells for subsequent release upon pericyte recruitment for CLI revascularization. Notably, n-BANKs enable endothelial cells to trigger eNOS activation and form tube-like structures. Subsequently, eNOS-derived NO robustly recruits pericytes to invest nascent endothelial cell tubes, giving rise to mature blood vessels. Consequently, n-BANKs confer complete revascularization in female mice following CLI, and thereby achieve limb preservation and restore the motor function. In light of n-BANK evoking pericyte-endothelial interactions to create functional vascular networks, it features promising therapeutic potential in revascularization to reduce CLI-related amputations, which potentially impact regeneration medicine.

Abstract Automatic segmentation of skin lesions is a critical step in Computer Aided Diagnosis (CAD) of melanoma. However, due to the blurring of the lesion boundary, uneven color distribution, and low image contrast, resulting in poor segmentation result. Aiming at the problem of difficult segmentation of skin lesions, this paper proposes an Attention-based Dual-path Feature Fusion Network (ADFFNet) for automatic skin lesion segmentation. Firstly, in the spatial path, a Boundary Refinement (BR) module is designed for the output of low-level features to filter out irrelevant background information and retain more boundary details of the lesion area. Secondly, in the context path, a Multi-scale Feature Selection (MFS) module is constructed for high-level feature output to capture multi-scale context information and use the attention mechanism to filter out redundant semantic information. Finally, we design a Dual-path Feature Fusion (DFF) module, which uses high-level global attention information to guide the step-by-step fusion of high-level semantic features and low-level detail features, which is beneficial to restore image detail information and further improve the pixel-level segmentation accuracy of skin lesion. In the experiment, the ISIC 2018 and PH2 datasets are employed to evaluate the effectiveness of the proposed method. It achieves a performance of 0.890/ 0.925 and 0.933 /0.954 on the F1-score and SE index, respectively. Comparative analysis with state-of-the-art segmentation methods reveals that the ADFFNet algorithm exhibits superior segmentation performance.

Abstract IDH1 mutations frequently occur early in human glioma. While IDH1 mutation has been shown to promote gliomagenesis via DNA and histone methylation, little is known regarding its regulation in antiviral immunity. Here, we discover that IDH1 mutation inhibits virus-induced interferon (IFN) antiviral responses in glioma cells. Mechanistically, D2HG produced by mutant IDH1 enhances the binding of DNMT1 to IRF3/7 promoters such that IRF3/7 are downregulated, leading to impaired type I IFN response in glioma cells, which enhances the susceptibility of gliomas to viral infection. Furthermore, we identify DNMT1 as a potential biomarker predicting which IDH1mut gliomas are most likely to respond to oncolytic virus. Finally, both D2HG and ectopic mutant IDH1 can potentiate the replication and oncolytic efficacy of VSVΔ51 in female mouse models. These findings reveal a pivotal role for IDH1 mutation in regulating antiviral response and demonstrate that IDH1 mutation confers sensitivity to oncolytic virotherapy.

BackgroundThe human gut microbiota has been identified as a potentially important factor influencing the development of COVID-19. It is believed that the disease primarily affects the organism through inflammatory pathways. With the aim of improving early diagnosis and targeted therapy, it is crucial to identify the specific gut microbiota associated with COVID-19 and to gain a deeper understanding of the underlying processes. The present study sought to investigate the potential causal relationship between the gut microbiota and COVID-19, and to determine the extent to which inflammatory proteins act as mediators in this relationship.MethodsBidirectional mendelian randomization (MR) and Two-step mediated MR analyses were applied to examine causative associations among 196 gut microbiota, 91 inflammatory proteins and COVID-19. The main analytical method used in the MR was the random effects inverse variance weighted (IVW) method. This was complemented by the Bayesian weighted Mendelian randomization (BWMR) method, which was utilized to test the hypothesis of MR. In order for the results to be deemed reliable, statistical significance was required for both methods. Validation was then carried out using an external dataset, and further meta-analyses were conducted to authenticate that the association was reliable.ResultsResults of our research indicated that seven gut microbiota were actively associated to the COVID-19 risk. Five inflammatory proteins were associated with COVID-19 risk, of which three were positively and two were negatively identified with COVID-19. Further validation was carried out using sensitivity analyses. Mediated MR results revealed that CCL2 was a possible mediator of causality of family Bifidobacteriaceae and order Bifidobacteriales with COVID-19, mediating at a ratio of 12.73%.ConclusionSuggesting a genetic causation between specific gut microbiota and COVID-19, our present research emphasizes the underlying mediating role of CCL2, an inflammatory factor, and contributes to a deeper understanding of the mechanism of action underlying COVID-19.

Abiotic stresses can increase the total fatty acid (TFA) and astaxanthin accumulation in microalgae. However, it remains unknown whether a unified signal transduction mechanism exists under different stresses. This study explored the link between nicotinamide adenine dinucleotide phosphate (NADPH) oxidase-derived reactive oxygen species (ROS) and the accumulation of fatty acids and astaxanthin in Chromochloris zofingiensis under three abiotic stresses. Results showed significant increases in fatty acid, astaxanthin, and ROS levels under nitrogen deficiency, phosphorus deficiency, and high-salinity stress. The introduction of the NADPH oxidase inhibitor diphenyleneiodonium (DPI) decreased the content of these components. This underscores the pivotal role of NADPH oxidase-derived ROS in the accumulation of fatty acid and astaxanthin under abiotic stress. Analysis of transcriptomes across three conditions following DPI addition revealed 1,445 shared differentially expressed genes (DEGs). Enrichment analysis revealed that biotin, betalain, thiamine, and glucosinolate may be important in stress responses. The heatmap demonstrated that DPI notably suppressed gene expression in the fatty acid and carotenoid biosynthesis pathways. Our findings underscore the pivotal role of NADPH oxidase-derived ROS in the accumulation of fatty acid and astaxanthin under abiotic stresses.

Abstract The traditional threshold secret sharing scheme only allows the participants’ sub-secret shares to be used once in the reconstruction process. Several multi-secret sharing schemes have been proposed that are related to cloud computing, aiming to improve reconstruction efficiency. Rational secret sharing is a technique that combines secret sharing with game theory. In traditional rational multi-secret sharing, participants must reconstruct all secrets, resulting in unnecessary overhead. Rational participants will act dishonestly to maximize their own interests, leading to a prisoner’s dilemma and incomplete secret reconstruction. Additionally, when sharing multiple secrets, the Dealer must distribute the sub-secret shares of all secrets to the participants, increasing overhead. In this paper, we propose a rational optional multi-secret sharing scheme based on a reputation mechanism that selectively reconstructs secrets according to participants’ needs in the context of cloud computing. Our scheme introduces a reputation mechanism to evaluate participants’ reputation values to avoid their dishonest behaviors. Furthermore, we adopt a broadcast encryption matrix so that participants only need to receive a single sub-secret share to participate in multi-secret reconstruction. Our security analysis shows that the proposed scheme can effectively constrain the self-interested behavior of rational participants and reduce the overhead in the process, thus multi-secret sharing scheme can provide more efficient and secure solutions for secret sharing in key management and distributive storage for the cloud scenarios.

Abstract Background The oocyte-to-embryo transition (OET) converts terminally differentiated gametes into a totipotent embryo and is critically controlled by maternal mRNAs and proteins, while the genome is silent until zygotic genome activation. How the transcriptome, translatome, and proteome are coordinated during this critical developmental window remains poorly understood. Results Utilizing a highly sensitive and quantitative mass spectrometry approach, we obtain high-quality proteome data spanning seven mouse stages, from full-grown oocyte (FGO) to blastocyst, using 100 oocytes/embryos at each stage. Integrative analyses reveal distinct proteome reprogramming compared to that of the transcriptome or translatome. FGO to 8-cell proteomes are dominated by FGO-stockpiled proteins, while the transcriptome and translatome are more dynamic. FGO-originated proteins frequently persist to blastocyst while corresponding transcripts are already downregulated or decayed. Improved concordance between protein and translation or transcription is observed for genes starting translation upon meiotic resumption, as well as those transcribed and translated only in embryos. Concordance between protein and transcription/translation is also observed for proteins with short half-lives. We built a kinetic model that predicts protein dynamics by incorporating both initial protein abundance in FGOs and translation kinetics across developmental stages. Conclusions Through integrative analyses of datasets generated by ultrasensitive methods, our study reveals that the proteome shows distinct dynamics compared to the translatome and transcriptome during mouse OET. We propose that the remarkably stable oocyte-originated proteome may help save resources to accommodate the demanding needs of growing embryos. This study will advance our understanding of mammalian OET and the fundamental principles governing gene expression.

Abstract As a common tumor with high incidence, osteosarcoma possesses extremely poor prognosis and high mortality. Improving the survival of osteosarcoma patients is still a great challenge due to the precipice of advancement in treatment. In this study, a combination strategy of gene therapy and photothermal therapy (PTT) is developed for efficient treatment of osteosarcoma. Two-dimensional (2D) FePS3 nanosheets are synthesized and functionalized by poly-L-lysine-PEG-folic acid (PPF) to fabricate a multifunctional nanoplatform (FePS@PPF) for further loading microRNAs inhibitor, miR-19a inhibitor (anti-miR-19a). The photothermal conversion efficiency of FePS@PPF is up to 47.1% under irradiation by 1064 nm laser. In vitro study shows that anti-miR-19a can be efficiently internalized into osteosarcoma cells through the protection and delivery of FePS@PPF nanaocarrier, which induces up-regulation of PTEN protein and down-regulation p-AKT protein. After intravenous injection, the FePS@PPF nanoplatform specifically accumulates to tumor site of osteosarcoma-bearing mice. The in vitro and in vivo investigations reveal that the combined PTT-gene therapy displays most significant tumor ablation compared with monotherapy. More importantly, the good biodegradability promotes FePS@PPF to be cleared from body avoiding potential toxicity of long-term retention. Our work not only develops a combined strategy of NIR-II PTT and gene therapy mediated by anti-miR-19a/FePS@PPF but also provides insights into the design and applications of other nanotherapeutic platforms.

Abstract Although various new biomaterials have enriched the methods for periodontal regeneration, their efficacy is still controversial, and the regeneration of damaged support tissue in the periodontium remains challenging. Laponite (LAP) nanosilicate is a layered two-dimensional nanoscale, ultrathin nanomaterial with a unique structure and brilliant biocompatibility and bioactivity. This study aimed to investigate the effects of nanosilicate-incorporated PCL (PCL/LAP) nanofibrous membranes on periodontal ligament cells (PDLCs) in vitro and periodontal regeneration in vivo. A PCL/LAP nanofibrous membrane was fabricated by an electrospinning method. The characterization of PCL/LAP nanofibrous membrane were determined by scanning electron microscopy (SEM), energy dispersive spectrum of X-ray (EDS), inductively coupled plasma mass spectrometry (ICP-MS) and tensile test. The proliferation and osteogenic differentiation of PDLCs on the PCL/LAP nanofibrous membrane were evaluated. A PDLCs and macrophage coculture system was used to explore the immunomodulatory effects of the PCL/LAP nanofibrous membrane. PCL/LAP nanofibrous membrane was implanted into rat calvarial and periodontal defects, and the regenerative potential was evaluated by microcomputed topography (micro-CT) and histological analysis. The PCL/LAP nanofibrous membrane showed good biocompatibility and bioactivity. It enhanced the proliferation and osteogenic differentiation of PDLCs. The PCL/LAP nanofibrous membrane also stimulated anti-inflammatory and pro-remodeling N2 neutrophil formation, regulated inflammatory responses and induced M2 macrophage polarization by orchestrating the immunomodulatory effects of PDLCs. The PCL/LAP nanofibrous membrane promoted rat calvarial defect repair and periodontal regeneration in vivo. LAP nanosilicate-incorporated PCL membrane is capable of mediating osteogenesis and immunomodulation of PDLCs in vitro and accelerating periodontal regeneration in vivo. It could be a promising biomaterial for periodontal regeneration therapy.

With the increase in port throughput and the development of the trend of large-scale ships, selecting applicable anchor positions for ships and ensuring the rational and comprehensive utilization of anchorage areas have become a key issue in utilizing the rate of anchorage resources, ensuring the safety of ships anchoring operations and promoting the development of the shipping industry. Existing anchor position selection and detection algorithm studies are limited to a two-dimensional plane for ship anchor position selection, with few studies considering intelligent detection algorithms for safe ship anchoring water depths based on three-dimensional space, considering conditions such as wind and waves. By considering water depth conditions and the objectives of anchorage safety issues, this study proposes an intelligent detection method for ship anchor detection to find the ship’s ideal anchor location in the anchorages by applying the Monte Carlo algorithm. In the processing step, in combination with the Monte Carlo random plane anchor position detection algorithm and Monte Carlo random sampling water depth detection method, the anchor position circle radius model, safe spacing model, anchoring area detection model and safe water depth model are used for examining the anchorage area for awaiting the ship in three-dimensions. To verify the accuracy of the proposed model, based on the scale of common ship types and considering the most conservative parameters, a series of simulation experiments are conducted to check whether the water depth meets the requirements and fully ensure the safety of the experimental results. The research results indicate that the detection almost cover the whole anchorage area and obtain safe water depth restrictions. This method helps to improve the efficiency of ship anchoring and makes actual anchoring operations safer. Under the premise of ensuring sufficient safe spacing between ships, the anchorage ground can accommodate more ships and simulate multi-type ship anchor position detection operations concerning various ship-type parameters to further ensure the safety of ship anchoring.

Pancreatic ductal adenocarcinoma (PDAC) is a highly prevalent digestive system malignancy, with a significant impact on public health, especially in the elderly population. The advent of the Human Genome Project has opened new avenues for precision medicine, allowing researchers to explore genetic markers and molecular targets for cancer diagnosis and treatment. Despite significant advances in genomic research, early diagnosis of pancreatic cancer remains elusive due to the lack of highly sensitive and specific markers. Therefore, there is a need for in-depth research to identify more precise and reliable diagnostic markers for pancreatic cancer. In this study, we utilized a combination of public databases from different sources to meticulously screen genes associated with prognosis in pancreatic cancer. We used gene differential analysis, univariate cox regression analysis, least absolute selection and shrinkage operator (LASSO) regression, and multivariate cox regression analysis to identify genes associated with prognosis. Subsequently, we constructed a scoring system, validated its validity using survival analysis and ROC analysis, and further confirmed its reliability by nomogram and decision curve analysis (DCA). We evaluated the diagnostic value of this scoring system for pancreatic cancer prognosis and validated the function of the genes using single cell data analysis. Our analysis identifies six genes, including GABRA3, IL20RB, CDK1, GPR87, TTYH3, and KCNA2, that were strongly associated with PDAC prognosis. Clinical prognostic models based on these genes showed strong predictive power not only in the training set but also in external datasets. Functional enrichment analysis revealed significant differences between high- and low-risk groups mainly in immune-related functions. Additionally, we explored the potential of the risk score as a marker for immunotherapy response and identified key factors within the tumor microenvironment. The single-cell RNA sequencing analysis further enriched our understanding of cell clusters and six hub genes expressions. This comprehensive investigation provides valuable insights into pancreatic PDAC and its intricate immune landscape. The identified genes and their functional significance underscore the importance of continued research into improving diagnosis and treatment strategies for PDAC.

Background Asian people in the United States have different sociodemographic and health‐related characteristics that might affect cardiovascular disease (CVD) risk by ethnicity and birthplace. However, they are often studied as a monolithic group in health care research. This study aimed to examine heterogeneity in CVD risk factors on the basis of birthplace among the 3 largest Asian subgroups (Chinese, Asian Indian, and Filipino) compared with US‐born non‐Hispanic White (NHW) adults. Methods and Results A cross‐sectional analysis was conducted using the 2010 to 2018 National Health Interview Survey data from 125 008 US‐born and foreign‐born Chinese, Asian Indian, Filipino, and US‐born NHW adults. Generalized linear models with Poisson distribution were used to examine the prevalence and prevalence ratios of self‐reported hypertension, diabetes, high cholesterol, physical inactivity, smoking, and overweight/obesity among Asian subgroups compared with US‐born NHW adults. The study included 118 979 US‐born NHW and 6029 Asian adults who self‐identified as Chinese (29%), Asian Indian (33%), and Filipino (38%). Participants' mean (±SD) age was 49±0.1 years, and 53% were females. In an adjusted analysis, foreign‐born Asian Indians had significantly higher prevalence of diabetes, physical inactivity, and overweight/obesity; foreign‐born Chinese had higher prevalence of physical inactivity, and foreign‐born Filipinos had higher prevalence of all 5 CVD risk factors except smoking compared with NHW adults. Conclusions This study revealed significant heterogeneity in the prevalence of CVD risk factors among Asian subgroups by ethnicity and birthplace, stressing the necessity of disaggregating Asian subgroup data. Providers should consider this heterogeneity in CVD risk factors and establish tailored CVD prevention plans for Asian subgroups.

BackgroundNumerous studies have suggested that the relationship between cardiovascular disease (CVD) risk and the usage of mobile health (mHealth) technology may vary depending on the total number of CVD risk factors present. However, whether higher CVD risk is associated with a greater likelihood of engaging in specific mHealth use among US adults is currently unknown. ObjectiveWe aim to assess the associations between the composite CVD risk and each component of mHealth use among US adults regardless of whether they have a history of CVD or not. MethodsThis study used cross-sectional data from the 2017 to 2020 Health Information National Trends Survey. The exposure was CVD risk (diabetes, hypertension, smoking, physical inactivity, and overweight or obesity). We defined low, moderate, and high CVD risk as having 0-1, 2-3, and 4-5 CVD risk factors, respectively. The outcome variables of interest were each component of mHealth use, including using mHealth to make health decisions, track health progress, share health information, and discuss health decisions with health providers. We used multivariable logistic regression models to examine the association between CVD risk and mHealth use adjusted for demographic factors. ResultsWe included 10,531 adults, with a mean age of 54 (SD 16.2) years. Among the included participants, 50.2% were men, 65.4% were non-Hispanic White, 41.9% used mHealth to make health decisions, 50.8% used mHealth to track health progress toward a health-related goal, 18.3% used mHealth to share health information with health providers, and 37.7% used mHealth to discuss health decisions with health providers (all are weighted percentages). Adults with moderate CVD risk were more likely to use mHealth to share health information with health providers (adjusted odds ratio 1.49, 95% CI 1.24-1.80) and discuss health decisions with health providers (1.22, 95% CI 1.04-1.44) compared to those with low CVD risk. Similarly, having high CVD risk was associated with higher odds of using mHealth to share health information with health providers (2.61, 95% CI 1.93-3.54) and discuss health decisions with health providers (1.56, 95% CI 1.17-2.10) compared to those with low CVD risk. Upon stratifying by age and gender, we observed age and gender disparities in the relationship between CVD risk and the usage of mHealth to discuss health decisions with health providers. ConclusionsAdults with a greater number of CVD risk factors were more likely to use mHealth to share health information with health providers and discuss health decisions with health providers. These findings suggest a promising avenue for enhancing health care communication and advancing both primary and secondary prevention efforts related to managing CVD risk factors through the effective usage of mHealth technology.

Steganography, the use of algorithms to embed secret information in a carrier image, is widely used in the field of information transmission, but steganalysis tools built using traditional steganographic algorithms can easily identify them. Steganography without embedding (SWE) can effectively resist detection by steganography analysis tools by mapping noise onto secret information and generating secret images from secret noise. However, most SWE still have problems with the small capacity of steganographic data and the difficulty of extracting the data. Based on the above problems, this paper proposes image steganography without embedding carrier secret information. The objective of this approach is to enhance the capacity of secret information and the accuracy of secret information extraction for the purpose of improving the performance of security network communication. The proposed technique exploits the carrier characteristics to generate the carrier secret tensor, which improves the accuracy of information extraction while ensuring the accuracy of secret information extraction. Furthermore, the Wasserstein distance is employed as a constraint for the discriminator, and weight clipping is introduced to enhance the secret information capacity and extraction accuracy. Experimental results show that the proposed method can improve the data extraction accuracy by 10.03% at the capacity of 2304 bits, which verifies the effectiveness and universality of the method. The research presented here introduces a new intelligent information steganography secure communication model for secure communication in networks, which can improve the information capacity and extraction accuracy of image steganography without embedding.

Abstract At present, iron oxide nanoparticles (IONPs) are widely used in the biomedical field. They have unique advantages in targeted drug delivery, imaging and disease treatment. However, there are many things to pay attention to. In this paper, we reviewed the fate of IONPs in different cells and the influence on the production, separation, delivery and treatment of extracellular vesicles. It aims to provide cutting-edge knowledge related to iron oxide nanoparticles. Only by ensuring the safety and effectiveness of IONPs can their application in biomedical research and clinic be further improved.

The mitochondrial genome of Camellia nitidissima was sequenced by Illumina and Pacbio sequencing. The results of sequences showed that a total length was 949,915 bp, and the GC content was 45.7% in assembled mitochondrial genome of C. nitidissima. 71 unigenes had been found, including 36 coding proteins and 35 non-coding proteins. Subsequently, the phylogenetic tree was built on 24 plants with the maximum-likelihood method, which had high bootstrap value and fited to the angiosperm phylogeny group classification (APG IV). The study’s findings unravel the taxonomic status of C. nitidissima and benefit the evolution study.

Rapeseed (Brassica napus) is an oil crop grown worldwide, making it a key plant species in molecular breeding research. However, the complexity of its polyploid genome increases sequencing costs and reduces sequencing accuracy. Target capture coupled with high-throughput sequencing is an efficient approach for detecting genetic variation at genomic regions or loci of interest. In this study, 588 resequenced accessions of rapeseed were used to develop a target capture sequencing SNP genotyping platform named BnaPan50T. The platform comprised 54,765, with 54,058 resequenced markers from the pan-genome, and 855 variant trait-associated markers for 12 agronomic traits. The capture quality of BnaPan50T was demonstrated well in 12 typical accessions. Compared with a conventional genotyping array, BnaPan50T has a high SNP density and a high proportion of SNPs in unique physical positions and in annotated functional genes, promising wide application. Target capture sequencing and whole-genome resequencing in 90 doubled-haploid lines yielded 60% specificity, 78% uniformity within tenfold coverage range, and 93% genotyping accuracy for the platform. BnaPan50T was used to construct a genetic map for quantitative trait loci (QTL) mapping, identify 21 unique QTL, and predict several candidate genes for yield-related traits in multiple environments. A set of 132 core SNP loci was selected from BnaPan50T to construct DNA fingerprints and germplasm identification resources. This study provides genomics resources to support target capture sequencing, genetic analysis and genomic breeding of rapeseed.

Abstract In oral squamous cell carcinoma (OSCC), a highly aggressive and frequently lethal malignancy, the role and action mechanism of the microtubule regulatory protein CDK5RAP2 have not been fully understood. Here, we show that CDK5RAP2 is highly expressed in OSCC and its expression correlates with clinical stage and lymph node metastasis of the disease. The expression of CDK5RAP2 is regulated by the Wnt signaling pathway. Depletion of CDK5RAP2 inhibits the tumorigenesis and migration of OSCC cells and alters the OSCC cancer stem (-like) cell (CSC) signature. Notably, suppression of CDK5RAP2 expression disrupts spindle orientation during mitosis. Collectively, these results identify CDK5RAP2 as a potential CSC marker and reveal a mechanism that controls the CSC population in OSCC.

[INLINE:1] Targeted muscle reinnervation has been proposed for reconstruction of neuromuscular function in amputees. However, it is unknown whether performing delayed targeted muscle reinnervation after nerve injury will affect restoration of function. In this rat nerve injury study, the median and musculocutaneous nerves of the forelimb were transected. The proximal median nerve stump was sutured to the distal musculocutaneous nerve stump immediately and 2 and 4 weeks after surgery to reinnervate the biceps brachii. After targeted muscle reinnervation, intramuscular myoelectric signals from the biceps brachii were recorded. Signal amplitude gradually increased with time. Biceps brachii myoelectric signals and muscle fiber morphology and grooming behavior did not significantly differ among rats subjected to delayed target muscle innervation for different periods. Targeted muscle reinnervation delayed for 4 weeks can acquire the same nerve function restoration effect as that of immediate reinnervation.

BackgroundAllergic rhinitis (AR) is a common nasal inflammatory disorder that severely affects an individual's quality of life (QoL) and poses a heavy financial burden. In addition to routine treatments, probiotic intervention has emerged as a promising strategy for preventing and alleviating allergic diseases. The main objective of this study was to determine the effect of a novel multi-strain probiotic mixture on AR symptoms and investigate potential targets underlying the probiotic intervention.MethodsA randomized, double-blind, placebo-controlled clinical study was conducted on AR patients who were allergic to autumnal pollens (n = 31). Placebo or a novel probiotic mixture, composed of Lactobacillus rhamnosus (L. rhamnosus) HN001, L. acidophilus NCFM, Bifidobacterium lactis (B. lactis) Bi-07, L. paracasei LPC-37, and L. reuteri LE16, was administered after 2 months. The therapeutic efficacy was evaluated by a symptom assessment scale. Before and during the pollen season, blood samples were collected, and peripheral blood mononuclear cells (PBMCs) were isolated for further tandem mass tags (TMTs)-based quantitative proteomic analyses. Potential targets and underlying pathological pathways were explored using bioinformatics methods.ResultsDuring the pollen season, the rhinoconjunctivitis symptom score of participants who were administered probiotics (probiotic group, n = 15) was significantly lower than those administered placebo (placebo group, n = 15) (P = 0.037). The proteomic analyses identified 60 differentially expressed proteins (DEPs) in the placebo group, and subsequent enrichment analyses enriched a series of pathways and biological processes, including signaling pathways of inflammation, coagulation cascade, lipid, carbohydrate and amino acid metabolic pathways, and transcription and translation processes. Least Absolute Shrinkage and Selection Operator (LASSO) regression extracted five main elements, namely, GSTO1, ATP2A2, MCM7, PROS1, and TRIM58, as signature proteins. A total of 17 DEPs were identified in the probiotic group, and there was no pathway enriched. Comparison of DEPs in the two groups revealed that the expression levels of the high-mobility group nucleosome-binding domain-containing protein 2 (HMGN2) and Histone H1.2 presented an opposite trend with different interventions.ConclusionOur data showed that AR symptoms alleviated after treatment with the novel multi-strain probiotic mixture, and the proteomic analyses suggested that HMGN2 and Histone H1.2 might be targets of probiotic intervention for seasonal AR.

Background: Mounting evidence indicates that complement components play a crucial role in cancer progression. Recent findings indicate that certain complement components display a significant rise in expression within esophageal squamous cell carcinoma (ESCC). However, the specific tumorigenic functions of these components remain unclear. This study focuses on investigating the expression pattern of C1r, elucidating a role for C1r in ESCC, as well as exploring underlying mechanisms controlled by C1r. Methods: The expression of C1r in ESCC tissues, malignant epithelial cells, and its relationship with survival were analyzed using the Gene Expression Omnibus (GEO) database and tissue microarrays. Single-cell RNA sequencing (scRNA-seq) was used to study the expression of C1r in malignant epithelial cells. C1r knockdown or C1r overexpression in cultured ESCC cells were used to assess the effects of C1r on proliferation, migration, invasion, cell-matrix adhesion, apoptosis, and growth of xenografted tumors in immunocompromised (nude) mice. Western blotting was used to detect the expression of MMP-1 and MMP-10 in C1r knockdown or C1r overexpressing ESCC cells. Results: C1r was highly expressed in ESCC tissues, malignant epithelial cells, and cultured ESCC cell lines. High C1r expression indicated a poor prognosis. Knockdown of C1r significantly suppressed the proliferation, migration, invasion, cell-matrix adhesion, and promoted apoptosis in cultured ESCC cells. Additionally, knockdown of C1r markedly inhibited tumor growth in nude mice. Overexpression of C1r had the opposite effects. C1r induced the expression of MMP-1 and MMP-10. Conclusions: C1r is highly expressed in ESCC and promotes the progression of this tumor type. Our findings suggest that C1r may serve as a novel prognostic biomarker and therapeutic target in ESCC.

Abstract High expression of CD38 in tissues is a characteristic of aging, resulting in a decline in nicotinamide adenine dinucleotide (NAD) and increasing cellular reactive oxygen species (ROS). However, whether CD38 increases susceptibility to ferroptosis remains largely unexplored. Our previous study showed that CD38 overexpression decreased dihydrofolate reductase (DHFR). In the present study, we confirmed that high expression of CD38 increased ROS levels and induced DHFR degradation, which was prevented by nicotinamide mononucleotide (NMN) replenishment. We further revealed that ROS-mediated sulfonation on Cys7 of DHFR induced its degradation via the autophagy and non-canonical proteasome pathways. Mutation of Cys7 to alanine abolished ROS-induced DHFR degradation. Moreover, oxidative degradation of DHFR was responsible for the increased ferroptosis susceptibility of cells in which CD38 was highly expressed. We also found that CD38 expression was higher in bone-marrow-derived macrophages (BMDMs) from aged mice than those from young mice, while the DHFR level was lower. Consequently, we demonstrated that BMDMs from aged mice were more susceptible to ferroptosis that can be reverted by NMN replenishment, suggesting that CD38 high expression rendered cells more susceptible to ferroptosis. Taken together, these results indicated that CD38-mediated NAD+ decline promoted DHFR oxidative degradation, thus resulting in increased cellular susceptibility to ferroptosis and suggesting that NMN replenishment may protect macrophages from ferroptosis in aged mice.