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Abstract Background Head and neck squamous cell carcinoma (HNSCC) is the sixth most prevalent malignancy worldwide, with high incidence and poor survival rates. RBP1 is highly expressed in several kinds of cancer and plays a potential prognostic factor. However, the relationship between RBP1 and HNSCC were analyzed based on The Cancer Genome Atlas (TCGA) database. Materials and methods RBP1 expression and clinical information were obtained from the Cancer Genome Atlas (TCGA) database. Tumor tissue and adjacent normal tissue of 6 HNSCC patients were collected to analyze the RBP1 mRNA expression level by quantitative PCR. Cox regression analysis was used to evaluate the prognostic values of RBP1 and clinical data in HNSCC. A nomogram was also established to predict the impact of RBP1 on prognosis based on Cox multivariate results. The methylation level of RBP1 in HNSC and its prognosis were analyzed in UALACN and MethSurv. Finally, the potential biological functions of RBP1 were investigated using gene set enrichment analysis (GSEA) and single sample GSEA (ssGSEA). Results The mRNA expression levels of RBP1 were highly expressed in HNSCC tissue. The Cox analyses demonstrate that highly-expressed RBP1 is an independent prognosis marker(P

Abstract Against the backdrop of the deep integration of culture and technology, research and practice in digitization of intangible cultural heritage has continued to deepen. However, due to the lack of data and training, it is still very difficult to apply artificial intelligence to the field of cultural heritage protection. This article integrates image generation technology into the digital protection of Peking opera facial makeup, using a self-built Peking opera facial makeup dataset. Based on the StyleGAN2 network, we propose a style generative cooperative training network Co-StyleGAN2, which integrates the adaptive data augmentation (ADA) to alleviate the problem of discriminator overfitting and introduces the idea of cooperative training to stabilize the training process. We design a Peking opera facial makeup image transform conditional generation network TC-StyleGAN2 which is transferred from unconditional generation network. The weights of the unconditional pre-training model are fixed, and an adaptive filtering modulation module is added to modulate the category parameters to complete the conversion from unconditional to conditional StyleGAN2 to deal with the training difficulty of conditional GANs on limited data, which suffer from severe mode collapse. The experimental results show that the proposed training strategy is better than the comparison algorithms, and the image generation quality and diversity have been improved.

Abstract Background In the era of immunotherapy, neoadjuvant immunochemotherapy (NAIC) for the treatment of locally advanced esophageal squamous cell carcinoma (ESCC) is used clinically but lacks of high‐level clinical evidence. This study aimed to compare the safety and long‐term efficacy of NAIC followed by minimally invasive esophagectomy (MIE) with those of neoadjuvant chemotherapy (NAC) followed by MIE. Methods A prospective, single‐center, open‐label, randomized phase III clinical trial was conducted at Henan Cancer Hospital, Zhengzhou, China. Patients were randomly assigned to receive either neoadjuvant toripalimab (240 mg) plus paclitaxel (175 mg/m2) + cisplatin (75 mg/m2) (toripalimab group) or paclitaxel + cisplatin alone (chemotherapy group) every 3 weeks for 2 cycles. After surgery, the toripalimab group received toripalimab (240 mg every 3 weeks for up to 6 months). The primary endpoint was event‐free survival (EFS). The pathological complete response (pCR) and overall survival (OS) were key secondary endpoints. Adverse events (AEs) and quality of life were also assessed. Results Between May 15, 2020 and August 13, 2021, 252 ESCC patients ranging from T1N1‐3M0 to T2‐3N0‐3M0 were enrolled for interim analysis, with 127 in the toripalimab group and 125 in the chemotherapy group. The 1‐year EFS rate was 77.9% in the toripalimab group compared to 64.3% in the chemotherapy group (hazard ratio [HR] = 0.62; 95% confidence interval [CI] = 0.39 to 1.00; P = 0.05). The 1‐year OS rates were 94.1% and 83.0% in the toripalimab and chemotherapy groups, respectively (HR = 0.48; 95% CI = 0.24 to 0.97; P = 0.037). The patients in the toripalimab group had a higher pCR rate (18.6% vs. 4.6%; P = 0.001). The rates of postoperative Clavien‐Dindo grade IIIb or higher morbidity were 9.8% in the toripalimab group and 6.8% in the chemotherapy group, with no significant difference observed (P = 0.460). The rates of grade 3 or 4 treatment‐related AEs did not differ between the two groups (12.5% versus 12.4%). Conclusions The interim results of this ongoing trial showed that in resectable ESCC, the addition of perioperative toripalimab to NAC is safe, may improve OS and might change the standard treatment in the future.

Stance detection is the view towards a specific target by a given context (e.g. tweets, commercial reviews). Target-related knowledge is often needed to assist stance detection models in understanding the target well and making detection correctly. However, prevailing works for knowledge-infused stance detection predominantly incorporate target knowledge from a singular source that lacks knowledge verification in limited domain knowledge. The low-resource training data further increase the challenge for the data-driven large models in this task. To address those challenges, we propose a collaborative knowledge infusion approach for low-resource stance detection tasks, employing a combination of aligned knowledge enhancement and efficient parameter learning techniques. Specifically, our stance detection approach leverages target background knowledge collaboratively from different knowledge sources with the help of knowledge alignment. Additionally, we also introduce the parameter-efficient collaborative adaptor with a staged optimization algorithm, which collaboratively addresses the challenges associated with low-resource stance detection tasks from both network structure and learning perspectives. To assess the effectiveness of our method, we conduct extensive experiments on three public stance detection datasets, including low-resource and cross-target settings. The results demonstrate significant performance improvements compared to the existing stance detection approaches.

Abstract Background Maxillary expansion is an important treatment method for maxillary transverse hypoplasia. Different methods of maxillary expansion should be carried out depending on the midpalatal suture maturation levels, and the diagnosis was validated by palatal plane cone beam computed tomography (CBCT) images by orthodontists, while such a method suffered from low efficiency and strong subjectivity. This study develops and evaluates an enhanced vision transformer (ViT) to automatically classify CBCT images of midpalatal sutures with different maturation stages. Methods In recent years, the use of convolutional neural network (CNN) to classify images of midpalatal suture with different maturation stages has brought positive significance to the decision of the clinical maxillary expansion method. However, CNN cannot adequately learn the long-distance dependencies between images and features, which are also required for global recognition of midpalatal suture CBCT images. The Self-Attention of ViT has the function of capturing the relationship between long-distance pixels of the image. However, it lacks the inductive bias of CNN and needs more data training. To solve this problem, a CNN-enhanced ViT model based on transfer learning is proposed to classify midpalatal suture CBCT images. In this study, 2518 CBCT images of the palate plane are collected, and the images are divided into 1259 images as the training set, 506 images as the verification set, and 753 images as the test set. After the training set image preprocessing, the CNN-enhanced ViT model is trained and adjusted, and the generalization ability of the model is tested on the test set. Results The classification accuracy of our proposed ViT model is 95.75%, and its Macro-averaging Area under the receiver operating characteristic Curve (AUC) and Micro-averaging AUC are 97.89% and 98.36% respectively on our data test set. The classification accuracy of the best performing CNN model EfficientnetV2_S was 93.76% on our data test set. The classification accuracy of the clinician is 89.10% on our data test set. Conclusions The experimental results show that this method can effectively complete CBCT images classification of midpalatal suture maturation stages, and the performance is better than a clinician. Therefore, the model can provide a valuable reference for orthodontists and assist them in making correct a diagnosis.

The test time of impulse tunnels is short, and the heat flux transducers can be easily interfered in the test time. Thus the aerothermal test data analysis of impulse tunnels is complex and usually carried out manually, which leads to low efficiency and nonuniform standards. In this paper, the signals of heat transducers used in the 1 m gun/shock dual-mode impulse tunnel at the China Academy of Aerospace Aerodynamics were investigated. A series of key parameters, e.g., the FFT voltage profile, the correlation profile of nozzle total pressure and transducer heat flux, as well as the time derivative of the heat flux profile, were determined. The characterization capabilities of these parameters with respect to significant features, e.g., the start/end time of the nozzle flow, the time boundary of different operation modes and the effectiveness of the transducer profiles, were certified. Moreover, a profile effectiveness estimation model, a test time interval selection algorithm and a transducer valid time selection algorithm were developed based on convolutional neural networks and density-based clustering algorithms. Thereby the aerothermal test data of impulse tunnels can be analyzed automatically with these data-driven methods. The results show that the accuracy of the profile effectiveness estimation model is as high as 98%. According to the comparison between algorithm and manual results in dealing with 3 568 profiles, about 91% of the results show a difference of less than 10%, which implies that the data-driven method has the value of application to wind tunnel tests.

Abstract Theretra japonica is an important pollinator and agricultural pest in the family Sphingidae with a wide range of host plants. High-quality genomic resources facilitate investigations into behavioral ecology, morphological and physiological adaptations, and the evolution of genomic architecture. However, chromosome-level genome of T. japonica is still lacking. Here we sequenced and assembled the high-quality genome of T. japonica by combining PacBio long reads, Illumina short reads, and Hi-C data. The genome was contained in 95 scaffolds with an accumulated length of 409.55 Mb (BUSCO calculated a genome completeness of 99.2%). The 29 pseudochromosomes had a combined length of 403.77 Mb, with a mapping rate of 98.59%. The genomic characterisation of T. japonica will contribute to further studies for Sphingidae and Lepidoptera.

Abstract Pancreatic cancer, predominantly pancreatic ductal adenocarcinoma (PDAC), remains a highly lethal malignancy with limited therapeutic options and a dismal prognosis. By targeting the underlying molecular abnormalities responsible for PDAC development and progression, gene therapy offers a promising strategy to overcome the challenges posed by conventional radiotherapy and chemotherapy. This study sought to explore the therapeutic potential of small activating RNAs (saRNAs) specifically targeting the CCAAT/enhancer-binding protein alpha (CEBPA) gene in PDAC. To overcome the challenges associated with saRNA delivery, tetrahedral framework nucleic acids (tFNAs) were rationally engineered as nanocarriers. These tFNAs were further functionalized with a truncated transferrin receptor aptamer (tTR14) to enhance targeting specificity for PDAC cells. The constructed tFNA-based saRNA formulation demonstrated exceptional stability, efficient saRNA release ability, substantial cellular uptake, biocompatibility, and nontoxicity. In vitro experiments revealed successful intracellular delivery of CEBPA-saRNA utilizing tTR14-decorated tFNA nanocarriers, resulting in significant activation of tumor suppressor genes, namely, CEBPA and its downstream effector P21, leading to notable inhibition of PDAC cell proliferation. Moreover, in a mouse model of PDAC, the tTR14-decorated tFNA-mediated delivery of CEBPA-saRNA effectively upregulated the expression of the CEBPA and P21 genes, consequently suppressing tumor growth. These compelling findings highlight the potential utility of saRNA delivered via a designed tFNA nanocarrier to induce the activation of tumor suppressor genes as an innovative therapeutic approach for PDAC.

Abstract Methyltransferase-like 3 (METTL3) is a crucial element of N6-methyladenosine (m6A) modifications and has been extensively studied for its involvement in diverse biological and pathological processes. In this study, we explored how METTL3 affects the differentiation of stem cells from the apical papilla (SCAPs) into odonto/osteoblastic lineages through gain- and loss-of-function experiments. The m6A modification levels were assessed using m6A dot blot and activity quantification experiments. In addition, we employed Me-RIP microarray experiments to identify specific targets modified by METTL3. Furthermore, we elucidated the molecular mechanism underlying METTL3 function through dual-luciferase reporter gene experiments and rescue experiments. Our findings indicated that METTL3+/− mice exhibited significant root dysplasia and increased bone loss. The m6A level and odonto/osteoblastic differentiation capacity were affected by the overexpression or inhibition of METTL3. This effect was attributed to the acceleration of pre-miR-665 degradation by METTL3-mediated m6A methylation in cooperation with the “reader” protein YTHDF2. Additionally, the targeting of distal-less homeobox 3 (DLX3) by miR-665 and the potential direct regulation of DLX3 expression by METTL3, mediated by the “reader” protein YTHDF1, were demonstrated. Overall, the METTL3/pre-miR-665/DLX3 pathway might provide a new target for SCAP-based tooth root/maxillofacial bone tissue regeneration.

ObjectiveThis paper aims to analyzes the shock response characteristics of a large-scale floating shock platform (LFSP) subjected to underwater explosion. MethodsThe acoustic-solid coupling approach is used as the basis for the numerical simulation. The validity of the calculation method used in this paper is verified by comparing the experimental data with simulation, and the shock response characteristics of the location of interest in the LFSP's inner bottm plating is investigated in terms of its longitudinal section distribution as well as the effects of changes in the horizontal distance to the blast source on the whole shock environment of LFSP's inner bottom structure, thereby the LFSP's shock response prediction formula is obtained by fitting method.ResultsThe results indicate that the shock response characteristics of the locations (i.e. outer and inner plates, longitudinal section in centre plane) distributed along the longitudinal section of the inner bottom structure are basically the same. The shock response amplitude of the front and back sides of the floating platform are small, while that of the middle is large. The shock responses of the outer and inner plates differ, and the spectral velocity of the inner plate is greater than that of the outer plate, while the spectral displacement of the outer plate is greater than that of the inner plate.ConclusionsThe measurement points within the inner bottom plating are excited so spikes appear in the shock spectral lines, resulting in the spectral velocity of the inner plate is higher than that of the outer plate. The horizontal distance of bottom plate to the blast source is smaller so the shock response is stronger, bringing about a greater spectral displacement of the outer plate than that of the inner plate.

While widespread urban greening is documented, how these efforts translate into changes in a city’s cooling potential remains unanswered. Here, we employed multi-satellite observations to assess the spatial dynamics and temporal variations in tree cooling efficiency (TCE) over 550 cities worldwide from 2002 to 2020. Our study identified substantial interannual variability of TCE across cities, especially in developing regions like Africa, Asia, and South America. Conversely, cities in Europe and the United States, characterized by a larger share of urban trees, exhibited a markedly lower degree of year-to-year fluctuations. Despite the prevalent urban vegetation expansion, which may not considerably enhance the cooling capability, we revealed a significant association between the tree cover level and the magnitude of temporal dynamics in TCE. This study highlights that tree cover improvement may play a crucial role in contributing to the stability of tree cooling potential under a changing climate.

Objective: To use ultra-widefield swept-source optical coherence tomography angiography (UWF SS-OCTA) to evaluate the choroidal features of neovascular age-related macular degeneration (nAMD) and type 1 macular neovascularization (MNV) attributable to central serous chorioretinopathy (CSC). Method: A cross-sectional research was carried out to examine patients with type 1 MNV due to CSC (50 eyes) and nAMD (98 eyes) utilizing UWF SS-OCTA examinations. The scan procedure covered a vertical 20 mm × horizontal 24 mm region with 9 subfields. A typical set of 68 healthy eyes was used for comparison. The effects of different diagnoses on choroidal parameters were assessed using covariance tests, using gender and age as variables. Results: The research showed that all choroidal characteristics were age-related (all p < 0.05). The calculated marginal averages of choroidal thickness (ChT) and choroidal volume (CV) in the central area were substantially lower in the nAMD group than in the CSC group and the normal group after age differences were taken into account (all p < 0.05). In both the superotemporal and temporal areas, the CSC group had a greater choroidal vascular index (CVI) compared to the nAMD group (p < 0.05). Additionally, the CSC group had a greater temporal area choriocapillaris density (CCD) than the nAMD group (p < 0.05). Conclusion: At the choroidal level, type 1 MNV due to CSC and nAMD may be distinguished by UWF SS-OCTA. Compared to the nAMD affected eyes, the CSC affected eyes had increased ChT, CV, CVI, and CCD in several areas. The two diseases could be distinguished based on ChT and CV.

The excessive utilization of petroleum-based plastic products has led to a pervasive environmental and human health threat. In response, the adoption of bioplastics derived from biomass has emerged as the foremost alternative to conventional plastics, owing to their inherent biodegradability and sustainability. The present study demonstrates the preparation of a biodegradable and cost-effective lignocellulosic bioplastic by utilizing dissolving bamboo leaf powder with deep eutectic solvents (DES) and regenerating lignin in situ. The DES was synthesized through a one-step heating and stirring method using choline chloride (ChCl) and anhydrous oxalic acid. The crystallinity of the bioplastics is enhanced by DES pretreatment, thereby improving the internal structural order of the material. Moreover, lignin regeneration reduces the pore size within the bioplastics and contributes to a more compact internal structure. The prepared lignocellulosic bioplastics exhibit remarkable mechanical strength, with a tensile strength of 113 MPa. Additionally, they demonstrate good water stability, as evidenced by a contact angle of 55.52°. Moreover, these bioplastics possess an exceptional biodegradability with a degradation rate exceeding 98% after 60 days. This study presents an innovative approach for the high-value utilization of bamboo leaf resources.

Global CO2 emissions have been an essential topic of the environmental discussion. Still, empirical data is needed to support arguments that high-quality government actions could reduce these emissions. By analyzing data from 137 nations from 2000 to 2020, we offer strong evidence that state policies focused on promoting healthy ecosystems, sustainable economic growth, and transcendent legislative changes are capable of decreasing CO2 emissions. Based on our findings, there are essentially three critical institutional factors that need to be improved for environmental policies to be efficient: the concept of law, which protects citizens' intellectual property rights; citizens' speech, which allows them to participate in elections and represent themselves freely, and the management of corruption. Policies aimed at promoting economic growth, lowering oil and gas use, enhancing the usage of green energy by the public and private sectors, and enhancing such institutional factors are all necessary components of a climate-friendly financial strategy.

Abstract Chili pepper (Capsicum) is known for its unique fruit pungency due to the presence of capsaicinoids. The evolutionary history of capsaicinoid biosynthesis and the mechanism of their tissue specificity remain obscure due to the lack of high-quality Capsicum genomes. Here, we report two telomere-to-telomere (T2T) gap-free genomes of C. annuum and its wild nonpungent relative C. rhomboideum to investigate the evolution of fruit pungency in chili peppers. We precisely delineate Capsicum centromeres, which lack high-copy tandem repeats but are extensively invaded by CRM retrotransposons. Through phylogenomic analyses, we estimate the evolutionary timing of capsaicinoid biosynthesis. We reveal disrupted coding and regulatory regions of key biosynthesis genes in nonpungent species. We also find conserved placenta-specific accessible chromatin regions, which likely allow for tissue-specific biosynthetic gene coregulation and capsaicinoid accumulation. These T2T genomic resources will accelerate chili pepper genetic improvement and help to understand Capsicum genome evolution.

Abstract Background The rumen microbiome enables ruminants to digest otherwise indigestible feedstuffs, thereby facilitating the production of high-quality protein, albeit with suboptimal efficiency and producing methane. Despite extensive research delineating associations between the rumen microbiome and ruminant production traits, the functional roles of the pervasive and diverse rumen virome remain to be determined. Results Leveraging a recent comprehensive rumen virome database, this study analyzes virus-microbe linkages, at both species and strain levels, across 551 rumen metagenomes, elucidating patterns of microbial and viral diversity, co-occurrence, and virus-microbe interactions. Additionally, this study assesses the potential role of rumen viruses in microbial diversification by analyzing prophages found in rumen metagenome-assembled genomes. Employing CRISPR–Cas spacer-based matching and virus-microbe co-occurrence network analysis, this study suggests that the viruses in the rumen may regulate microbes at strain and community levels through both antagonistic and mutualistic interactions. Moreover, this study establishes that the rumen virome demonstrates responsiveness to dietary shifts and associations with key animal production traits, including feed efficiency, lactation performance, weight gain, and methane emissions. Conclusions These findings provide a substantive framework for further investigations to unravel the functional roles of the virome in the rumen in shaping the microbiome and influencing overall animal production performance. Video Abstract

The rumen microbiome digests plant feedstuff that would be otherwise indigestible and provides most of the metabolizable energy and protein the host animals need. Until recently, research efforts have primarily been directed to bacteria and archaea, leaving the protozoa, fungi, and viruses much less understood. Protozoa contribute to feed digestion and fermentation, but as predators, they affect the microbiome and its function by regulating the abundance and activities of other rumen microbes both in a top-down (by directly killing the prey) and bottom-up (by affecting the metabolism of other microbes) manner. Rumen viruses (or phages, used interchangeably below) are diverse and abundant but the least understood. They are also predators (intracellular “predators”) because of their lytic lifecycle, although they can co-exist peacefully with their hosts and reprogram host metabolism, buttressing host ecological fitness. In doing so, rumen viruses also affect the rumen microbiome in both a top-down and a bottom-up manner. Here we review the recent advancement in understanding both types of predators, focusing on their potential impact on the rumen microbiome and functions.

Online learning became a necessity in many places during the COVID-19 pandemic. In the case of Hong Kong SAR, the pandemic provided a unique opportunity to establish blended learning as a norm. The authors discuss the insights and challenges related to delivering mathematics lessons online in a secondary school during and after the pandemic. A three-year-long case study was conducted to examine the differences in perceptions between a teacher and his five students regarding online mathematics instruction during the suspension of traditional in-class lessons in 2020 and after the resumption of traditional instruction in 2023. The Social-Ecological Approach with domains of structure, agency, and cultural practice was applied in the study, which investigated the perceived benefits of blended learning for both the students and the teachers. Data was collected via interviews. The study explored technological challenges, curriculum adaptations, and the impact of parental support on blended learning. Looking ahead, leveraging motivators like easy access while mitigating distractors through disciplined strategies can optimize blended learning environments. The insights gained from this study provide valuable guidance on the effectiveness of instructional strategies and technological tools, highlighting the features of best practices for future blended learning approaches. Furthermore, the paper provides valuable information for policymakers, educators, and educational technology developers.

Abstract In response to the suboptimal efficiency observed in the network configuration and administration of 5G photovoltaic base stations (PVBSs), as well as the inherent limitations in accurately forecasting photovoltaic power during inclement weather conditions, this research article introduces a concise and effective method for short‐term power prediction of PVBSs when subjected to non‐sunny weather conditions, leveraging the paradigm of software defined networking. This method ingeniously amalgamates the improved Northern Goshawk optimized back propagation neural network (INGO‐BP) and recurrent generative adversarial networks (RGAN). The investigation commences by delineating a comprehensive PVBS system framework underpinned by SDN principles. Subsequently, it employs the Pearson correlation coefficient technique and principal component analysis for the judicious selection of pertinent features from the PVBS photovoltaic dataset, thereby ameliorating the issue of multicollinearity within the predictive model. To culminate the research endeavour, the INGO algorithm is enlisted to optimize the weightings and bias parameters of the BP neural network, while RGAN is harnessed for the acquisition of distinctive distribution patterns in photovoltaic data across diverse meteorological conditions. This augmentation enhances the model's capacity to discern the intricate long‐term mappings between photovoltaic power and meteorological data. The empirical findings substantiate the elevated accuracy of the INGO‐BP prediction model across sunny, cloudy, and rainy weather conditions, with a discernible enhancement in predictive accuracy for PVBS performance under non‐sunny weather conditions facilitated by data augmentation via RGAN.

Abstract Objective In this study, we used ultra-wide field swept-source optical coherence tomography angiography (UWF SS-OCTA) to assess changes in retinal thickness (RT) and choroidal parameters in individuals who had received a diagnosis of central serous chorioretinopathy (CSC). Methods The study encompassed the evaluation of 59 eyes from 47 patients with a diagnosis of CSC, alongside 33 fellow eyes and 31 eyes from healthy individuals (controls). The parameters assessed included RT, choroidal thickness (CT), choriocapillaris density, vascular density of the large choroidal vessel layer, three-dimensional choroidal vascularity index (3D-CVI), choroidal vessel volume per unit area (mCVV/a), and choroidal stroma volume per unit area (mCSV/a). Results Metrics including mCVV/a, mCSV/a, 3D-CVI, CT, and RT exhibited significantly elevated values in the eyes affected by CSC compared to those of the control group across nine subfields. Moreover, a substantial number of the subfields in both CSC-affected and fellow eyes exhibited increased values for mCVV/a, mCSV/a, 3D-CVI, CT, and RT when compared with the control group. Additionally, acute and chronic CSC subfields demonstrated significantly elevated values for mCVV/a, mCSV/a, 3D-CVI, CT, and RT in comparison to healthy control eyes. Notably, specific subfields associated with complex and atypical forms of CSC revealed higher metrics compared to those of the control group. Conclusion In conclusion, the UWF SS-OCTA proved to be a valuable tool for exploring the anatomical etiology and clinical classification and diagnosis of CSC.

Abstract Mine slope stability and mining sustainability are related to the local geological structures, which could change the rock mass structure in deep mining. After 20 years mining in a mudstone mine, western China, the slope structure transforms from anti-dipping structure into a bedding structure by a recently discovered fault (F1), further inducing the two landslides (Landslide #I and Landslide #II). Landslide investigation suggested the residual deposits in Landslide #I first slid over 100 m and overburdened the rear of Landslide #II. The bedding rock with weak interlayers at footwall is separated from the anti-dipping rock at the hanging wall by F1. After excavation, a weak interlayer was exposed and softened by rainfall, resulting in the slip of footwall rock mass and further inducing large scale toppling deformation. The fragmented rock mass sliding along a weak interlayer triggers consequent deformation of adjacent slope, reducing safety reserve of the open mine. The discrete element analysis reveals that the bedding rock mass of footwall slid once the weak interlayer was exposed by mining. And retrogressive deformation transmitted to the hanging wall and induced bending and toppling deformation of anti-dipping rock mass. Mine feasibility assessment should recognize the potential deep geological structures as important in the future.

Abstract Background Klippel–Feil syndrome (KFS) is a rare congenital disorder characterized by the fusion of two or more cervical vertebrae during early prenatal development. This fusion results from a failure of segmentation during the first trimester. Although six genes have previously been associated with KFS, they account for only a small proportion of cases. Among the distinct subtypes of KFS, “sandwich fusion” involving concurrent fusion of C0-1 and C2-3 vertebrae is particularly noteworthy due to its heightened risk for atlantoaxial dislocation. In this study, we aimed to investigate novel candidate mutations in patients with “sandwich fusion.” Methods We collected and analyzed clinical data from 21 patients diagnosed with “sandwich fusion.” Whole-exome sequencing (WES) was performed, followed by rigorous bioinformatics analyses. Our focus was on the six known KFS-related genes (GDF3, GDF6, MEOX1, PAX1, RIPPLY2, and MYO18). Suspicious mutations were subsequently validated through in vitro experiments. Results Our investigation revealed two novel exonic mutations in the FGFR2 gene, which had not previously been associated with KFS. Notably, the c.1750A > G variant in Exon 13 of FGFR2 was situated within the tyrosine kinase domain of the protein, in close proximity to several established post-translational modification sites. In vitro experiments demonstrated that this certain mutation significantly impacted the function of FGFR2. Furthermore, we identified four heterozygous candidate variants in two genes (PAX1 and MYO18B) in two patients, with three of these variants predicted to have potential clinical significance directly linked to KFS. Conclusions This study encompassed the largest cohort of patients with the unique “sandwich fusion” subtype of KFS and employed WES to explore candidate mutations associated with this condition. Our findings unveiled novel variants in PAX1, MYO18B, and FGFR2 as potential risk mutations specific to this subtype of KFS.

Abstract Microtubule-associated protein 1a (Map1a) is a microtubule (MT) regulatory protein that binds to the MT protofilaments in mammalian cells to promote MT stabilization. Maps work with MT cleavage proteins and other MT catastrophe-inducing proteins to confer MT dynamics to support changes in the Sertoli cell shape to sustain spermatogenesis. However, no functional studies are found in the literature to probe its role in spermatogenesis. Using an RNAi approach, coupled with the use of toxicant-induced testis (in vivo)- and Sertoli cell (in vitro)-injury models, RNA-Seq analysis, transcriptome profiling, and relevant bioinformatics analysis, immunofluorescence analysis, and pertinent biochemical assays for cytoskeletal organization, we have delineated the functional role of Map1a in Sertoli cells and testes. Map1a was shown to support MT structural organization, and its knockdown (KD) also perturbed the structural organization of actin, vimentin, and septin cytoskeletons as these cytoskeletons are intimately related, working in concert to support spermatogenesis. More importantly, cadmium-induced Sertoli cell injury that perturbed the MT structural organization across the cell cytoplasm was associated with disruptive changes in the distribution of Map1a and a surge in p-p38-MAPK (phosphorylated p38-mitogen-activated protein kinase) expression but not total p38-MAPK. These findings thus support the notion that p-p38-MAPK activation is involved in cadmium-induced Sertoli cell injury. This conclusion was supported by studies using doramapimod, a specific p38-MAPK phosphorylation (activation) inhibitor, which was capable of restoring the cadmium-induced disruptive structural organization of MTs across the Sertoli cell cytoplasm. In summary: this study provides mechanistic insights regarding restoration of toxicant-induced Sertoli cell and testis injury and male infertility.

Abstract Michaelis constant (KM) is one of essential parameters for enzymes kinetics in the fields of protein engineering, enzyme engineering, and synthetic biology. As overwhelming experimental measurements of KM are difficult and time-consuming, prediction of the KM values from machine and deep learning models would increase the pace of the enzymes kinetics studies. Existing machine and deep learning models are limited to the specific enzymes, i.e., a minority of enzymes or wildtype enzymes. Here, we used a deep learning framework PaddlePaddle to implement a machine and deep learning approach (GraphKM) for KM prediction of wildtype and mutant enzymes. GraphKM is composed by graph neural networks (GNN), fully connected layers and gradient boosting framework. We represented the substrates through molecular graph and the enzymes through a pretrained transformer-based language model to construct the model inputs. We compared the difference of the model results made by the different GNN (GIN, GAT, GCN, and GAT-GCN). The GAT-GCN-based model generally outperformed. To evaluate the prediction performance of the GraphKM and other reported KM prediction models, we collected an independent KM dataset (HXKm) from literatures.

Commercially pure titanium (CP–Ti) took advantages of low stiffness, high corrosion resistance and bio-compatibility, implying an ideal structural material in aerospace, military and medical industries. However, its insufficient mechanical properties have always been the long-standing obstacle for the industrial applications. In this work, we have achieved a superior strong and ductile CP-Ti via active atmosphere-assisted selective laser melting (SLM) and subsequent rolling treatment. By incorporating the active N2 atmosphere during SLM, mechanical properties of CP-Ti were substantially improved, microhardness of the lyaers with 10 at.% and 100 at.% was 63 % and 174.3 % higher than that of CP-Ti with 182.3 HV0.2, the compressive strength of 10 sample was 27.1 % higher than that of 10 L sample when the strain was 52.2 %, and ultimate tensile strength of 10 sample reached 928 MPa with an elongation of 25.6 %, and ultimate tensile strength and elongation of 10 L sample were enhanced simultaneously by 58.3 % and 13.6 % relative to CP-Ti sample. These were attributed to the interstitial strengthening induced by N atoms. After rolling treatment, the mechanical properties of N-doping layers could enhance furtherly. Macroscale cracking along the rolling direction never occur in the 10 L sample during the repeatedly rolling treatment, which could depend to high tolerability of sandwich layers for high-density dislocations. Meanwhile, rolling treatment played an important role for refining grain to enhance the strength further.

ABSTRACTUrban Green Space (UGS) plays a crucial socio-cultural role in improving the quality of life. Assessment of quantity, quality, and accessibility determines whether the UGS are important social benefits. The travel preference of urban residents is a good indicator for the social relevance of UGS. This study integrates remote sensing and geographic big data to quantitatively analyze and evaluate the social benefits of urban green space. We propose a Green Social Benefit Index (GSBI) based on remote sensing retrieval and classification of urban green space. The GSBI is combined with the data on population mobility to investigate the influence of urban green space on residents’ behavior. The results show that urban residents prefer to move around in places with a higher quantity and quality of urban green space. The magnitude of the influence of urban green spatial features on population heat difference shows that accessibility > quantity > quality. The social benefits of urban green space are higher in middle centers compared to urban centers and city borders. The relationship between urban mobility and urban green space may suggest how to improve the distribution of green space in urban areas. This study could be a reference for the government planning department.

IntroductionHead and neck cancer (HNC) is a complex disease, and multiple risk factors can lead to its progression. Observational studies indicated that herpes simplex virus (HSV) may be correlated with the risk of HNC. However, the causal effects and direction between them were still unclear.MethodsThis study utilized a Mendelian randomization (MR) approach for causality assessment between HSV infection and Head and neck cancer based on the latest public health data and Genome-Wide Association Study (GWAS) data. The causal effects were estimated using IVW, weighted median, and MR-Egger. A reverse MR analysis was subsequently performed. Cochrans Q test, MR‐Egger intercept test, leave one out analysis, and the funnel plot were all used in sensitivity analyses.ResultsGenetically predicted higher level of HSV-1 IgG was causally related to HNC (OR=1.0019, 95%CI=1.0003–1.0036, p=0.0186, IVW) and oral and oropharyngeal cancer (OR=1.0018, 95%CI=1.0004–1.0033, p=0.0105, IVW). The reverse MR analysis did not demonstrate a reverse causal relationship between HSV and HNC. However, HSV-2 infection was not causally related to HNC data and oropharyngeal cancer data. Sensitivity analysis was performed and revealed no heterogeneity and horizontal pleiotropy.ConclusionCollectively, a significant association was noted between HSV infection and increased risk of HNC, providing valuable insights into the etiology of this malignancy. Further in-depth study is needed to validate these findings and elucidate the underpinning mechanisms.

In recent decades, the Mountain Excavation and City Construction (MECC) activities have become the main way of acquiring land for construction in densely populated cities. In China, for example, Lanzhou City is one of the typical cities for MECC, which has significantly changed the landscape and resulted in the surface deformation. To monitor accurately surface deformation, the height changes cannot be ignored, as it changes from meters to more than 70 m due to the MECC. In this study, a new time-series Interferometric Synthetic Aperture Radar (InSAR) algorithm is proposed to stepwise estimate the ground height changes and deformation, where the onset of height changes is firstly detected automatically for each pixel. Then height changes and deformation are estimated with different SAR datasets for different pixels. Experimental test on Lanzhou city shows that the ground height changes vary between 70 m and −80 m from October 2014 to May 2022, and the correlation between the multi-track results is over 0.89. Meanwhile, the correlation with the ICESat-2 height changes results reaches 0.94. In addition, two-dimensional (2D) deformation is recovered by fusing ascending and descending deformation, where subsidence with slight rebound phenomena is revealed at the center of the landfill area. Finally, finite difference model (FDM) is employed to simulate the land filling process, which can well explain the 2D surface deformation.

Non-alcoholic fatty liver disease (NAFLD), particularly advanced non-alcoholic steatohepatitis (NASH), leads to irreversible liver damage. This study investigated the therapeutic effects and potential mechanism of a novel extract from traditional Chinese medicine Alisma orientale (Sam.) Juzep (AE) on free fatty acid (FFA)-induced HepG2 cell model and high-fat diet (HFD) + carbon tetrachloride (CCl4)-induced mouse model of NASH. C57BL/6 J mice were fed a HFD for 10 weeks. Subsequently, the mice were injected with CCl4 to induce NASH and simultaneously treated with AE at daily doses of 50, 100, and 200 mg/kg for 4 weeks. At the end of the treatment, animals were fasted for 12 h and then sacrificed. Blood samples and liver tissues were collected for analysis. Lipid profiles, oxidative stress, and histopathology were examined. Additionally, a polymerase chain reaction (PCR) array was used to predict the molecular targets and potential mechanisms involved, which were further validated in vivo and in vitro. The results demonstrated that AE reversed liver damage (plasma levels of alanine aminotransferase (ALT), aspartate aminotransferase (AST), hepatocyte ballooning, hepatic steatosis, and NAS score), the accumulation of hepatic lipids (TG and TC), and oxidative stress (MDA and GSH). PCR array analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis revealed that AE protects against NASH by regulating the adipocytokine signaling pathway and influencing nuclear receptors such as PPARα. Furthermore, AE increased the expression of peroxisome proliferator-activated receptor gamma coactivator-1α (PPARGC1α) and reversed the decreased expression of PPARα in NASH mice. Moreover, in HepG2 cells, AE reduced FFA-induced lipid accumulation and oxidative stress, which was dependent on PPARα up-regulation. Overall, our findings suggest that AE may serve as a potential therapeutic approach for NASH by inhibiting lipid accumulation and reducing oxidative stress specifically through the PPARα pathway.

Abstract Mid-infrared hyperspectral imaging has become an indispensable tool to spatially resolve chemical information in a wide variety of samples. However, acquiring three-dimensional data cubes is typically time-consuming due to the limited speed of raster scanning or wavelength tuning, which impedes real-time visualization with high spatial definition across broad spectral bands. Here, we devise and implement a high-speed, wide-field mid-infrared hyperspectral imaging system relying on broadband parametric upconversion of high-brightness supercontinuum illumination at the Fourier plane. The upconverted replica is spectrally decomposed by a rapid acousto-optic tunable filter, which records high-definition monochromatic images at a frame rate of 10 kHz based on a megapixel silicon camera. Consequently, the hyperspectral imager allows us to acquire 100 spectral bands over 2600-4085 cm−1 in 10 ms, corresponding to a refreshing rate of 100 Hz. Moreover, the angular dependence of phase matching in the image upconversion is leveraged to realize snapshot operation with spatial multiplexing for multiple spectral channels, which may further boost the spectral imaging rate. The high acquisition rate, wide-field operation, and broadband spectral coverage could open new possibilities for high-throughput characterization of transient processes in material and life sciences.

Abstract Objective This study was to investigate the underlying mechanism by which Saikosaponin D (SSD) mitigates the inflammatory response associated with osteoarthritis (OA) and regulates autophagy through upregulation of microRNA (miR)-199-3p and downregulation of transcription Factor-4 (TCF4). Methods A mouse OA model was established. Mice were intragastrically administered with SSD (0, 5, 10 μmol/L) or injected with miR-199-3p antagomir into the knee. Then, pathological changes in cartilage tissues were observed. Normal chondrocytes and OA chondrocytes were isolated and identified. Chondrocytes were treated with SSD and/or transfected with oligonucleotides or plasmid vectors targeting miR-199-3p and TCF4. Cell viability, apoptosis, inflammation, and autophagy were assessed. miR-199-3p and TCF4 expressions were measured, and their targeting relationship was analyzed. Results In in vivo experiments, SSD ameliorated cartilage histopathological damage, decreased inflammatory factor content and promoted autophagy in OA mice. miR-199-3p expression was downregulated and TCF4 expression was upregulated in cartilage tissues of OA mice. miR-199-3p expression was upregulated and TCF4 expression was downregulated after SSD treatment. Downregulation of miR-199-3p attenuated the effect of SSD on OA mice. In in vitro experiments, SSD inhibited the inflammatory response and promoted autophagy in OA chondrocytes. Downregulation of miR-199-3p attenuated the effect of SSD on OA chondrocytes. In addition, upregulation of miR-199-3p alone inhibited inflammatory responses and promoted autophagy in OA chondrocytes. miR-199-3p targeted TCF4. Upregulation of TCF4 attenuated the effects of miR-199-3p upregulation on OA chondrocytes. Conclusions SSD alleviates inflammatory response and mediates autophagy in OA via elevating miR-199-3p to target TCF4.

In the global effort to promote green energy policies, understanding and optimizing boiler combustion processes in coal-fired power plants is crucial. During unit start-ups, shutdowns, and load deep peak regulation, significant energy-saving potential can be harnessed in boilers. This paper focuses on a 600MW supercritical coal-fired power unit and presents an improved Least Squares Support Vector Machine (LS-SVM) model with refined initial parameters. By combining the improved LS-SVM with Affinity Propagation (AP) clustering, a combustion efficiency model for boilers is constructed. The experimental results demonstrate that the AP-based improved LS-SVM model not only reduces computational complexity and training time but also enhances predictive accuracy and generalization performance.

Abstract Background Immune checkpoint inhibitors (ICIs) can improve survivals of metastatic triple negative breast cancer (mTNBC); however, we still seek circulating blood biomarkers to predict the efficacy of ICIs. Materials and methods In this study, we analyzed the data of ICIs treated mTNBC collected in Anhui Medical University affiliated hospitals from 2018 to 2023. The counts of lymphocytes, monocytes, platelets, and ratio indexes (NLR, MLR, PLR) in peripheral blood were investigated via the Kaplan-Meier curves and the Cox proportional-hazards model. Results The total of 50 mTNBC patients were treated with ICIs. High level of peripheral lymphocytes and low level of NLR and MLR at baseline and post the first cycle of ICIs play the predictable role of immunotherapies. Lymphocytes counts (HR = 0.280; 95% CI: 0.095–0.823; p = 0.021) and NLR (HR = 1.150; 95% CI: 1.052–1.257; p = 0.002) are significantly correlated with overall survival. High NLR also increases the risk of disease progression (HR = 2.189; 95% CI:1.085–4.414; p = 0.029). When NLR at baseline ≥ 2.75, the hazard of death (HR = 2.575; 95% CI:1.217–5.447; p = 0.013) and disease progression (HR = 2.189; 95% CI: 1.085–4.414; p = 0.029) significantly rise. HER-2 expression and anti-tumor therapy lines are statistically correlated with survivals. Conclusions Before the initiation of ICIs, enriched peripheral lymphocytes and poor neutrophils and NLR contribute to the prediction of survivals.

Abstract With more and more interconnected smart devices (ISDs) accessing the Internet of Things (IoT), massive and diverse tasks need to be transformed and computed. Mobile edge computing enables the offloading of tasks to nearby servers to enhance processing efficiency, which makes ISDs idle, causing resource waste and failing to satisfy the high real‐time requirements of tasks. Besides, when tasks with different priorities are processed in the order they are generated, it will be difficult for IoT to guarantee a timely response to high‐priority tasks. To address the aforementioned issues, we establish an edge‐terminal‐local architecture by software‐defined networking to centrally manage idle ISD resource (2ISDR). Then the proposed two‐step scheduling mechanism with preemptive priority queue ensures the real‐time responses to high‐priority tasks, and the minimum resource allocation coefficients make offloading effective. Finally, we also propose a modified NSGA‐III algorithm named MNSGA‐III, which is designed to make decisions about offloading and solve resource allocation for tasks, and we correct infeasible solutions by a two‐step correction function to ensure the feasibility of MNSGA‐III. Experimental results show that the method can ensure a timely response to high‐priority tasks and optimize processing time, energy consumption, and economic cost through the utilization of 2ISDR.

Total of 384 healthy 38-week-old hens were randomly divided into four treatments. Layers in four groups were fed a basal diet and a basal diet with Cd at the level of 15, 30 and 60 mg/kg for nine weeks. Results showed that Cd could dose-dependently deposited in magnum and a positive correlation occurred between the accumulation of Cd in magnum and Cd content in egg whites. When compared with control group, 60 mg/kg Cd decreased magnum ovomucin, ovalbumin, lysozyme and ovomucoid gene expressions, but increased avidin gene expression obviously. Hens receiving 60 mg/kg Cd exhibited a significant decrease in egg white ovalbumin content and its proportion in total protein and increase in total cholesterol and LDLC levels in serum and yolk. The level of GSH and activities of T-SOD and CAT in magnum and GSH-Px activity in egg white were decreased significantly, while MDA level in both magnum and egg white was increased obviously in 60 mg/kg Cd group. Besides, Cd induced oxidative stress, inflammation, endoplasmic reticulum stress (ERS) and mitophagy accompanied by a significant up-regulation of the expressions of Keap1, IL1β, TNFα, NF-κB, p65, p-p65, Grp78, CHOP, ATF4, ATF6, IRE1α, Grp94, PINK1, Parkin, Fundc1, GRP75, VDAC1, MCU, MFF, Bnip3 and LC3I/II and a significant down-regulation of the expressions of Nrf2, HO-1, SOD1, SOD2, SOD3, MFN1, MFN2 and PGC1α. These results indicated that Cd can increase serum and yolk cholesterol level and induce magnum oxidative stress, inflammation, ERS and mitophagy through Nrf2/NF-κB and IRE1α/IP3R/GRP75/VDAC1/MCU pathways, thus disrupting egg white composition.Highlights Cd exposure disrupted the synthesis of egg white protein in oviduct magnum and destroyed antioxidant status and protein composition in egg white. Cd exposure significant enhanced serum and yolk total cholesterol and LDL cholesterol levels. Cd exposure induced magnum oxidative stress, inflammation, ERS and mitophagy through Nrf2/NF-κB and IRE1α/IP3R/GRP75/VDAC1/MCU pathways.

Surface quality represents a critical challenge in additive manufacturing (AM), with surface roughness serving as a key parameter that influences this aspect. In the aerospace industry, the surface roughness of the aviation components is a very important parameter. In this study, a typical Al alloy, AlSi10Mg, was selected to study its surface roughness when using Laser Powder Bed Fusion (LPBF). Two Random Forest (RF) models were established to predict the upper surface roughness of printed samples based on laser power, laser scanning speed, and hatch distance. Through the study, it is found that a two-dimensional (2D) RF model is successful in predicting surface roughness values based on experimental data. The best and minimum surface roughness is 2.98 μm, which is the minimum known without remelting. More than two-thirds of the samples had a surface roughness of less than 7.7 μm. The maximum surface roughness is 11.28 μm. And the coefficient of determination (R2) of the model was 0.9, also suggesting that the surface roughness of 3D-printed Al alloys can be predicted using ML approaches such as the RF model. This study helps to understand the relationship between printing parameters and surface roughness and helps print components with better surface quality.

Previous studies have demonstrated that the surface curvature of cylindrical magnetic nonawires can induce fascinating dynamic magnetization properties. It was recently proposed that ferromagnetic nanotubes can be utilized as skyrmion guides, enabling the avoidance of the annihilation of skyrmions in the lateral boundaries as in flat thin-film strips. In this work, we demonstrate via micromagnetic simulation that multiple skyrmions can be stabilized in a cross-section of a ferromagnetic nanotube with interfacial Dzyaloshinskii–Moriya interaction (iDMI). When uniformly arranged, these skyrmions together can perform as a crystal lattice for spin waves (SWs) propagating in the nanotube. Our simulations show that the skyrmion lattice can contribute a chiral effect to the SW passing through, namely a circular polarization of the SW. The handedness of the polarization is found to be determined by the polarity of the skyrmions. A physical explanation of the observed effect is provided based on the exchange of angular momentum between SWs and skyrmions during the scattering process. Our results display more possibilities to exploit magnetic nanotubes as SW and skyrmion guide in the development of novel spintronic devices.

This study examined the influence of chlorogenic acid (CGA) on gut antioxidant status, morphology, barrier function, immunity, and cecal microbiota in late-peak laying hens. A total of 240 Hy-Line Brown hens, aged 43 weeks, were randomly assigned to four groups, the basal diet +0, 400, 600, and 800 mg/kg CGA, for 12 weeks. The results revealed that CGA significantly reduced ileal H2O2 and malondialdehyde levels; increased duodenal height, ileal villus height, and villus height-to-crypt depth ratio; while decreasing jejunal crypt depth. The 600 and 800 mg/kg CGA significantly upregulated the duodenal, jejunal, and ileal ZO-1 and occludin gene expression; increased IgG levels in serum and ileum; and upregulated ileal IgA gene expression. The 600 mg/kg CGA significantly upregulated CD3D and CD4 gene expression, while downregulating IL-1β gene expression in duodenum, jejunum, and ileum. Moreover, CGA changed the gut microbiota structure. The SCFA-producing bacteria unclassified_f__Peptostreptococcaceae, unclassified_f_Oscillospiraceae, Pseudoflavonifractor, Lachnospiraceae_FCS020_group, Oscillospira, Elusimicrobium, Eubacterium_ventriosum_group, Intestinimonas, and norank_f_Coriobacteriales_Incertae_Sedis were significantly enriched in the 400, 600, and/or 800 mg/kg CGA groups. The bacteria Lactobacillus, Bacillus, and Akkermansia were significantly enriched in the 600 mg/kg CGA group. Conclusively, dietary CGA (600–800 mg/kg) improved intestinal antioxidant status, morphology, barrier and immune function, and beneficial microbiota growth in late-peak laying hens.

Underwater acoustic target recognition has always played a pivotal role in ocean remote sensing. By analyzing and processing ship-radiated signals, it is possible to determine the type and nature of a target. Historically, traditional signal processing techniques have been employed for target recognition in underwater environments, which often exhibit limitations in accuracy and efficiency. In response to these limitations, the integration of artificial intelligence (AI) methods, particularly those leveraging machine learning and deep learning, has attracted increasing attention in recent years. Compared to traditional methods, these intelligent recognition techniques can autonomously, efficiently, and accurately identify underwater targets. This paper comprehensively reviews the contributions of intelligent techniques in underwater acoustic target recognition and outlines potential future directions, offering a forward-looking perspective on how ongoing advancements in AI can further revolutionize underwater acoustic target recognition in ocean remote sensing.

BackgroundThe relationship between gut microbiota composition and coronary heart disease (CHD) has been recently reported in several observational studies. However, the causal effect of gut microbiota on coronary heart disease is uncharted.ObjectiveThis study attempted to investigate the effect of gut microbiota on coronary heart disease by Mendelian randomization (MR) analysis.MethodsThrough the two-sample MR method, single-nucleotide polymorphisms relevant to gut microbiota were selected as instrument variables to evaluate the causal association between gut microbiota and the risk of CHD.ResultsAccording to the selection criteria of the inverse variance-weighted average method, Class Actinobacteria, Class Lentisphaeria, Family Clostridiales vadinBB60group, Genus Clostridium innocuum group, Genus Bifidobacterium, Genus Butyricicoccus, Genus Oxalobacter, Genus Turicibacter, and Order Victivallales, presented a suggestive association with coronary heart disease.ConclusionThis two-sample Mendelian randomization study found that gut microbiota was causally associated with coronary heart disease. Further randomized controlled trials are needed to clarify the protective effect of probiotics on coronary heart disease and their specific protective mechanisms.

BackgroundThe value of semiquantitative resting myocardial perfusion imaging (MPI) in coronary artery disease (CAD) is limited. At present, quantitative MPI can be performed by a new cadmium zinc tellurium single-photon emission computed tomography (CZT-SPECT) scan. The quantitative index of resting myocardial blood flow (MBF) has received little attention, and its manifestations and clinical value in the presence of unstable coronary blood flow have not been clarified.PurposeIn patients with ST-segment elevation myocardial infarction (STEMI), whether resting MBF can provide additional value of blood flow than semi-quantitative resting MPI is not sure. We also explored the influencing factors of resting MBF.MethodsThis was a retrospective clinical study. We included 75 patients with STEMI in the subacute phase who underwent resting MPI and dynamic scans after reperfusion therapy. General patient information, STEMI-related data, MPI, gated MPI (G-MPI), and resting MBF data were collected and recorded. According to the clinically provided culprit vessels, the resting MBF was divided into ischemic MBF and non-ischemic MBF. The paired Wilcoxon signed-rank test was used for resting MBF. The receiver operating characteristic (ROC) curves were used to determine the optimal threshold for ischemia, and multiple linear regression analysis was used to analyze the influencing factors of resting MBF.ResultsThere was a statistically significant difference between the ischemic MBF and non-ischemic MBF [0.59 (0.47–0.72) vs. 0.76 (0.64–0.93), p

Abstract Background Microglial activation in the spinal trigeminal nucleus (STN) plays a crucial role in the development of trigeminal neuralgia (TN). The involvement of adenosine monophosphate-activated protein kinase (AMPK) and N-methyl-D-aspartate receptor 1 (NMDAR1, NR1) in TN has been established. Initial evidence suggests that stem cells from human exfoliated deciduous teeth (SHED) have a potential therapeutic effect in attenuating TN. In this study, we propose that SHED-derived exosomes (SHED-Exos) may alleviate TN by inhibiting microglial activation. This study sought to assess the curative effect of SHED-Exos administrated through the tail vein on a unilateral infraorbital nerve chronic constriction injury (CCI-ION) model in mice to reveal the role of SHED-Exos in TN and further clarify the potential mechanism. Results Animals subjected to CCI-ION were administered SHED-Exos extracted by differential ultracentrifugation. SHED-Exos significantly alleviated TN in CCI mice (increasing the mechanical threshold and reducing p-NR1) and suppressed microglial activation (indicated by the levels of TNF-α, IL-1β and IBA-1, as well as p-AMPK) in vivo and in vitro. Notably, SHED-Exos worked in a concentration dependent manner. Mechanistically, miR-24-3p-upregulated SHED-Exos exerted a more significant effect, while miR-24-3p-inhibited SHED-Exos had a weakened effect. Bioinformatics analysis and luciferase reporter assays were utilized for target gene prediction and verification between miR-24-3p and IL1R1. Moreover, miR-24-3p targeted the IL1R1/p-p38 MAPK pathway in microglia was increased in CCI mice, and participated in microglial activation in the STN. Conclusions miR-24-3p-encapsulated SHED-Exos attenuated TN by suppressing microglial activation in the STN of CCI mice. Mechanistically, miR-24-3p blocked p-p38 MAPK signaling by targeting IL1R1. Theoretically, targeted delivery of miR-24-3p may offer a potential strategy for TN. Graphical Abstract

Abstract Background Building interprofessional working relationships between general practitioners (GPs) and pharmacists is essential to ensure high-quality patient care. However, there is limited Chinese literature on GP–pharmacist collaboration, and few studies have explored GPs’ experiences with pharmacist integration into general practices. This study aimed to investigate GPs’ attitudes towards and frequency of collaboration with pharmacists in China. Methods This cross-sectional study used an online self-administered questionnaire integrating two scales, ATCI-GP and FICI-GP, which had been translated and validated to investigate 3,248 GPs from February 15 to March 15, 2023 across Zhejiang Province, China. Descriptive analyses were used, and the factors associated with GPs’ frequency of collaboration with pharmacists were explored using logistic regression analysis. Results A total of 2,487 GPs (76.6%) responded and consented to participate in the survey; 52.3% were male and the mean age was 35.4 years. Most GPs agreed that they shared common goals and objectives with pharmacists when caring for patients (90.0%), and pharmacists were open to working with them on patients’ medication management (80.8%). However, half of the GPs did not change or seldom changed the patient’s medication on the pharmacist’s advice (51.4%). Logistic regression analysis showed that GPs who were older and had more years of practice were more likely to agree that pharmacists were willing to collaborate, had common goals for treatment and that they would change the patient’s medication on the advice of the pharmacist. GPs who had regular communication protocols (adjusted odds ratio1 [aOR1] = 1.88, 95% CI 1.45–2.45; aOR2 = 3.33, 95% CI 2.76–4.02), participated in joint continuing education (aOR1 = 1.87, 95% CI 1.44–2.43; aOR2 = 2.27, 95% CI 1.91–2.70), provided recommendations for medication review (aOR1 = 3.01, 95% CI 2.07–4.38; aOR2 = 3.50, 95% CI 2.51–4.86), and communicated with pharmacists during resident training (aOR1 = 2.15, 95% CI 1.78–2.60; aOR2 = 1.38, 95% CI 1.18–1.62) were associated with a more positive attitude towards and higher frequency of cooperation. Conclusions GPs in China displayed a positive attitude towards cooperating with pharmacists, but they did not demonstrate a similar level of practice. As environmental determinants impact interdisciplinary collaboration, healthcare managers and policy-makers need to implement measures that foster a supportive environment conducive to interdisciplinary collaboration.

Abstract Purpose The aim of this study was to evaluate and summarize the developmental rules of the ocular anterior segment of neonates by means of wild-field digital imaging system. Methods We used the wide-field digital imaging system to sequentially capture images of the neonates’ eyes within 42 days after delivery, including the ocular surface, anterior segment, and fundus. At the same time, basic information at the time of birth and examination was collected. Results Among 248 newborns, 51.21% were male. Abnormalities of the anterior segment such as visualization of anterior chamber angle vessels (79.03%) and iris vessels (51.21%), iris process (42.34%), persistent pupillary membranes (19.35%), albinism, congenital cataracts, corneal leucoma, and subconjunctival hemorrhage were observed in this study. There were significant differences in the appearance of iris vessels among different sex, gestational age and birth weight, postmenstrual age and weight at the time of examination and iris color groups. The iris vessels were more visualized in males relative to females (OR = 6.313, 95% CI 2.529–15.759). The greater the postmenstrual age at the time of examination, the lower the visualization of iris vessels (OR = 0.377, 95% CI 0.247–0.575). In addition, although visualization of anterior chamber angle vessels differed within the birth gestation age and weight at examination groups, there was no significant correlation by regression analysis. Conclusions The anterior segment of perinatal neonates can be visualized by the wide-field digital imaging system. The neonatal iris and anterior chamber angle are immature, and the visible vessels at the anterior chamber angle that vanish later than the surface of the iris are characteristic structures.

Excessive ground deformation caused by shield tunneling of urban metro will seriously affect the normal use of surrounding structures, and even cause engineering accidents. In view of the problems that the data dimension in traditional prediction methods is too large, which easily leads to lower accuracy and complex calculation, this study proposes an extreme learning machine (ELM) prediction model based on the principal component analysis (PCA) algorithm and Harris Hawk optimization algorithm (HHO). Ten influence factors are preliminarily selected from the geological, geometric and shield parameters. PCA is used to separate and extract five principal component variables from the 10 dimensional arrays as the input of the model. HHO is used to optimize the input layer weights and hidden layer threshold parameters of the ELM model, and the optimal solution of the prediction model is obtained. The monitoring data of the Yiguang section of Kunming Rail Transit Line 5 are used for simulation verification, and the model is compared with the BP neural network, RBF and non-optimized ELM model. The results show that the root mean square error of the PCA-HHO-ELM prediction model is 0.1435, the average absolute error is 0.0262, and the determination coefficient R2 is 0.9596. Compared with other models, this model has better prediction performance. Compared with the non-optimized ELM, HHO can improve the prediction accuracy and generalization ability of ELM. The PCA-HHO-ELM model can reliably predict the maximum ground settlement induced by shield, and can provide a more feasible new idea for similar deformation prediction.

Abstract Word recognition during the reading of continuous text has received much attention. While a large body of research has investigated how linguistic properties of words affect eye movements during reading, it remains to be established how individual differences in reading skills affect momentary cognitive processes during sentence reading among typically developing Chinese readers. The present study set out to test the joint influences of word properties and individual reading skills on eye movements during reading among Chinese children. We recorded eye movements of 30 grade 3 (G3) children and 27 grade 5 (G5) children when they read sentences silently for comprehension. Predictors of linear mixed models included word frequency, visual complexity, and launch site distance, in addition to the participants’ offline psychometric performances in rapid naming, morphological awareness, word segmenting, and character recognition. The results showed that word properties affected word recognition during sentence reading in both G3 and G5 children. Moreover, word segmenting predicted the G3 children’s fixation durations and the G5 children’s fixation location, whereas rapid naming predicted the G5 children’s fixation duration. Implications are discussed based on the current findings, in light of how different literacy skills contribute to reading development.

Zinc oxide (ZnO) nanoparticles, as a non-toxic, harmless, and low-cost photocatalytic material, have attracted much attention from the scientific and industrial communities. However, due to their small particle size and high surface energy, ZnO nanoparticles are prone to agglomeration. In addition, ZnO nanoparticles only have catalytic activity and electron–hole pairing under ultraviolet light. Therefore, Copper(I) oxide (Cu2O)-ZnO/cellulose composites with excellent photocatalytic performance were fabricated by loading Cu2O crystals and using cellulose fiber substrate in this work. Cu2O can increase the light absorption range (including ultraviolet light and visible light) of ZnO/cellulose composites. Moreover, Cellulose fibers can improve the contact area to pollution and photostability of the Cu2O/ZnO nanoparticles, thereby enhancing the photocatalytic activity. The Cu2O-ZnO/cellulose composite showed the highest photocatalytic activity for Methyl orange (MO) degradation, which was approximately 40% and 10% times higher than those of the ZnO/cellulose and Cu2O/ZnO composites, respectively. Moreover, the degradation rate of phenol reached 100% within 80 min. The highly enhanced activity of the Cu2O-ZnO/cellulose composite is attributed to the enlargement of the light absorption range and the formation of heterojunctions between the counterparts, which effectively suppress the recombination of the photogenerated charge carriers. Overall, this work aims to improve the photocatalytic activities of ZnO/cellulose composites by loading Cu2O crystals, hoping to provide a novel and efficient photocatalyst for wastewater treatment.

Abstract The diverse rumen virome can modulate the rumen microbiome, but it remains largely unexplored. Here, we mine 975 published rumen metagenomes for viral sequences, create a global rumen virome database (RVD), and analyze the rumen virome for diversity, virus-host linkages, and potential roles in affecting rumen functions. Containing 397,180 species-level viral operational taxonomic units (vOTUs), RVD substantially increases the detection rate of rumen viruses from metagenomes compared with IMG/VR V3. Most of the classified vOTUs belong to Caudovirales, differing from those found in the human gut. The rumen virome is predicted to infect the core rumen microbiome, including fiber degraders and methanogens, carries diverse auxiliary metabolic genes, and thus likely impacts the rumen ecosystem in both a top-down and a bottom-up manner. RVD and the findings provide useful resources and a baseline framework for future research to investigate how viruses may impact the rumen ecosystem and digestive physiology.

Abstract Optical cavities are essential for enhancing the sensitivity of molecular absorption spectroscopy, which finds widespread high-sensitivity gas sensing applications. However, the use of high-finesse cavities confines the wavelength range of operation and prevents broader applications. Here, we take a different approach to ultrasensitive molecular spectroscopy, namely dual-comb optomechanical spectroscopy (DCOS), by integrating the high-resolution multiplexing capabilities of dual-comb spectroscopy with cavity optomechanics through photoacoustic coupling. By exciting the molecules photoacoustically with dual-frequency combs and sensing the molecular-vibration-induced ultrasound waves with a cavity-coupled mechanical resonator, we measure high-resolution broadband ( > 2 THz) overtone spectra for acetylene gas and obtain a normalized noise equivalent absorption coefficient of 1.71 × 10−11 cm−1·W·Hz−1/2 with 30 GHz simultaneous spectral bandwidth. Importantly, the optomechanical resonator allows broadband dual-comb excitation. Our approach not only enriches the practical applications of the emerging cavity optomechanics technology but also offers intriguing possibilities for multi-species trace gas detection.

With the development of urban engineering construction, the issue of construction engineering accidents has become more and more prominent. The geotechnical parameter interval obtained by using the traditional methods cannot meet the needs of actual engineering. Based on the idea of unsupervised learning, the peaty soil with the worst engineering properties is considered, and 8 physical indexes are selected as the input set. The principal component analysis (PCA) algorithm is used to realize the dimensionality reduction of multi-sample and multi-parameter decoupling, and the correlation and sensitivity of each physical index is obtained. Combined with its correlation and sensitivity, the comprehensive evaluation value of physical indexes of peat soil with different buried depths is given. The k-means clustering is used to analyze the relationship among physical index, and comprehensive evaluation value and engineering characteristics of peaty soil provide a theoretical basis for the selection of geotechnical parameters. The supervised learning method-BP neural network algorithm is used to analyze the unsupervised results and verify the accuracy of the (PCA—k-means) algorithm model. The normal samples obtained by clustering analysis are optimized by a variety of truncation methods to obtain a reliable value range, and the value results are compared with the actual engineering values to verify the rationality of the model engineering parameters. The algorithm model is of good engineering application value. The research results can provide references for engineering investigation, design and construction parameter values, and also provide a new analysis method for geotechnical parameter value analyses.