Search

Various studies have been conducted on applying intelligent recognition technology, especially speech recognition technology to improve English learning ability, mostly listening and speaking. However, few studies have touched on how image-to-text recognition technology can be used for writing. The present research was conducted to fill this gap by exploring the optimization of a deep-learning-based image captioning algorithm to facilitate English writing, so as to enable learners to break the time and space limitations and learn English writing (including sentence patterns, spelling, vocabulary, and grammar) anytime and anywhere by taking pictures. Therefore, this paper focused on image captioning based on CNN(Convolutional Neural Networks) and LSTM (Long Short-Term Memory), using DenseNet201 or Vision Transformer trained on the ImageNet-1K image classification dataset as the image encoder and LSTM as the decoder. First, pre-training was performed on the Flickr8k dataset. After selecting the best-trained model as the pre-trained weight model for the COCO dataset, fine-tuning optimization was performed on the COCO dataset, and the attention mechanism was used to design the ablation experiment. The BLEU-4, CIDEr, METEOR, and ROUGE evaluation indexes of the optimized model on the test set were 0.3437,1.121,0.2750, and 0.5117, respectively. The study results showed that the convergence of the model was accelerated and had better performance. The model was used to automatically caption 12 images that had never been used during the training process. The descriptions generated by the optimized image captioning algorithm have lexical and syntactic accuracy, and matched what the images expressed, showing that this improved algorithm could be used as a learning tool to help English learners improve lexical and syntactic acquisition to promote writing through the generated descriptions of the pictures taken anytime and anywhere in real-life situations.

This study presents a knowledge map of online education satisfaction research. To conduct bibliometric analysis, VOSviewer and Biblioshiny were utilized to analyze the co-authorship, co-citation, and co-occurrence network analysis of articles published on online education satisfaction between 2011 and 2022. The analysis aimed to show the research status, topics, and future research trends in the field. This paper reports the following findings: (1) There is a booming interest in research on online education in various countries and fields. (2) The most frequently studied target sample is undergraduate students' online education satisfaction; the most commonly used method is structural equation model combined with questionnaire survey; the most studied factors include students' individual factors, information technology tools, and their interaction with others; and the most studied variables include self-efficacy, motivation, perceived ease of use, perceived usefulness, expectation, and social existence. (3) Many fields, such as teacher satisfaction and the construction of new models and tools, remain underexplored. Future research should strengthen international cooperation, promote interdisciplinary research, and explore additional related fields.

Abstract In this paper we revisit the general phenomenon that scattering amplitudes of pions can be obtained from “dimensional reduction” of gluons in higher dimensions in a more general context. We show that such “dimensional reduction” operations universally turn gluons into pions regardless of details of interactions: under such operations any amplitude that is gauge invariant and contains only local simple poles becomes one that satisfies Adler zero in the soft limit. As two such examples, we show that starting from gluon amplitudes in both superstring and bosonic string theories, the operations produce “stringy” completion of pion scattering amplitudes to all orders in α′, with leading order given by non-linear sigma model amplitudes. Via Kawai-Lewellen-Tye relations, they give closed-stringy completion for Born-Infeld theory and the special Galileon theory, which are directly related to gravity amplitudes in closed-string theories. We also discuss how they naturally produce stringy models for mixed amplitudes of pions and colored scalars.

Abstract Background Urinary incontinence (UI) is closely related to obesity. The aim of this study is to evaluate the association of a novel anthropometric indicator weight-adjusted-waist index (WWI) with UI. Methods This cross-sectional study used the data from National Health and Nutrition Examination Survey (NHANES) 2001–2018. Weighted multivariable logistic regression was used to evaluate the relationship between WWI and three types of UI [stress UI (SUI), urgency UI (UUI), and mixed UI (MUI)]. The receiver operating characteristic (ROC) curve and Delong et al.’s test were utilized for comparison of the predictive capability for UI between WWI and body mass index (BMI), waist circumference (WC). Results A total of 41,614 participants were included in this study, of whom 23.57% had SUI, 19.24% had UUI, and 9.43% had MUI. In the fully adjusted model, WWI was positively associated with three types of UI [SUI: odds ratio (OR) = 1.19, 95%Confidence interval (CI) 1.13–1.25; UUI: OR = 1.18, 95%CI 1.13–1.24; MUI: OR = 1.19, 95%CI 1.11–1.27, all p

Abstract Background Rabies is a fatal zoonotic disease whose pathogenesis has not been fully elucidated, and vaccination is the only effective method for protecting against rabies virus infection. Most inactivated vaccines are produced using Vero cells, which are African green monkey kidney cells, to achieve large-scale production. However, there is a potential carcinogenic risk due to nonhuman DNA contamination. Thus, replacing Vero cells with human diploid cells may be a safer strategy. In this study, we developed a novel 2BS cell-adapted rabies virus strain and analysed its sequence, virulence and immunogenicity to determine its application potential as a human diploid cell inactivated vaccine. Methods and results The 2BS cell-adapted rabies virus strain 2aG4-B40 was established by passage for 40 generations and selection of plaques in 2BS cells. RNA sequence analysis revealed that mutations in 2BS cell-adapted strains were not located at key sites that regulate the production of neutralizing antibodies or virulence in the aG strain (GQ412744.1). The gradual increase in virulence (remaining above 7.0 logLD50/ml from the 40th to 55th generation) and antigen further indicated that these mutations may increase the affinity of the adapted strains for human diploid cells. Identification tests revealed that the 2BS cell-adapted virus strain was neutralized by anti-rabies serum, with a neutralization index of 19,952. PrEP and PEP vaccination and the NIH test further indicated that the vaccine prepared with the 2aG4-B40 strain had high neutralizing antibody levels (2.24 to 46.67 IU/ml), immunogenicity (protection index 270) and potency (average 11.6 IU/ml). Conclusions In this study, a 2BS cell-adapted strain of the 2aG4 rabies virus was obtained by passage for 40 generations. The results of sequencing analysis and titre determination of the adapted strain showed that the mutations in the adaptive process are not located at key sequence regions of the virus, and these mutations may enhance the affinity of the adapted strain for human diploid cells. Moreover, vaccines made from the adapted strain 2aG4-B40 had high potency and immunogenicity and could be an ideal candidate rabies virus strain for inactivated vaccine preparation.

Objective: To predict the mechanism of sea buckthorn in the treatment of alcoholic liver injury based on network pharmacology, and to verify the efficacy of sea buckthorn in the treatment of alcoholic liver injury by establishing an animal model of alcoholic liver injury in zebrafish. Methods: Through the traditional chinese medicine systems pharmacology (TCMSP) and Uniprot database, the effective components and their targets were collected. Venny2.1 was used to find the intersection targets. GeneCards and OMIM databases were used to collect and screen disease targets. STRING v12.0 database was used for PPI network analysis. PDB and PubChem were used to confirm protein structure and small molecular structure. The correlation network of sea buckthorn in the treatment of alcoholic liver injury was constructed by Cytoscape (Version 3.9.1) software network diagram. Gene ontology (GO) and Kyoto encyclopedia of genes (KEGG) database pathway enrichment analysis were performed on the common targets using the Metascape database. Functional verification was performed by zebrafish experiments: Wild-type AB strain zebrafish 3 days after fertilization (3 dpf) were selected. The normal group was fed with normal feeding water, and the other groups were fed in 2% anhydrous ethanol solution to establish an alcoholic liver injury model. Results: After screening, 33 active components of sea buckthorn were obtained, mainly including quercetin, sunflower, catechin and so on. There were 1434 potential targets for the treatment of alcoholic liver injury, including ADH1C, CTNNB1, TGFB1 and so on. The signaling pathways that regulate these core targets are mainly enriched in multiple signaling pathways such as lipid and atherosclerosis, fluid shear stress and atherosclerosis and PI3K-Akt signaling pathway. The results of animal experiments showed that sea buckthorn had the effect of reducing the opacity value of zebrafish liver in alcoholic liver injury model (P

Abstract Recently, nitrate (NO3 –) levels in winter pollution in eastern China have been increasing yearly and have become the main component of PM2.5. The factors contributing to this rise in surface NO3 – concentrations remain unclear, complicating the development of targeted pollution control measures. This study utilizes observational data from Shanghai during the winter 2019, alongside box model simulations, to recreate the NO3 − pollution event and identify the key factors in the growth process. The analysis demonstrated that a rise in winter ozone levels significantly promotes NO3 – production by facilitating NO x conversion via gas-phase and heterogeneous reactions. These findings could explain the correlation between the synchronous increase of surface ozone and NO3 − in recent years. Furthermore, simulation of control strategies for NO x and volatile organic compounds (VOCs) identified an approach centered on ozone reduction as notably effective in mitigating winter NO3 – pollution in the Yangtze River Delta.

ABSTRACT: Noncovalent interactions of 4 selected phenolic acids, including gallic acid (GA), caffeic acid (CA), chlorogenic acid (CGA), and rosmarinic acid (RA) with lactoferrin (LF) were investigated. Compound combined with LF in the binding constant of CA > GA > RA > CGA, driven by van der Waals and hydrogen bonding for GA, and hydrophobic forces for others. Conformation of LF was affected at secondary and ternary structure levels. Molecular docking indicated that GA and CA located in the same site near the iron of the C-lobe, whereas RA and CGA bound to the C2 and N-lobe, respectively. Significantly enhanced antioxidant activity of complexes was found compared with pure LF, as demonstrated by 2,2-diphenyl-1-picrylhydrazyl (DPPH), 2,2′-azinobis(2-ethylbenzothiazoline-6-sulfonate) (ABTS), and ferric reducing antioxidant power (FRAP) models. Caffeic acid, CGA, and RA significantly decreased the emulsifying stability index and improved foam ability of LF, and the effect of CA and RA was the most remarkable, respectively.

Understanding how hydrological factors interrelate is crucial when examining the impact of climate warming on snowmelt. However, these connections are often overlooked, leading to an unclear relationship between temperature and snowmelt. This study investigates the complex interplay between temperature and snowmelt in the Tibetan Plateau from 1961 to 2020, focusing on how extreme high-temperature events affect the frequency of extreme snowmelt. Using a structural equation model, we detected three temperature-related factors that predominantly influenced snowmelt and extreme snowmelt. The annual average temperature was found to have a significant indirect impact on snowmelt, mediated by changes in snowfall, snow depth and snow cover. By contrast, high-temperature days (daily maximum temperatures exceeding the 90th percentile) and heat waves (at least three consecutive high-temperature days) negatively affected extreme snowmelt directly or indirectly. The direct effect of increasing extreme temperature events was associated with an earlier onset of high-temperature periods, which accelerated snowmelt and shortened the duration of extreme snowmelt periods. Additionally, the reduction in snow cover owing to warming emerged as a main factor suppressing snowmelt and extreme snowmelt frequencies. We also revealed spatiotemporal variations in the temperature‒snowmelt relationship that highly depended on changes in snowmelt patterns. The study elucidated why warming suppresses snowmelt and extreme snowmelt events in the Tibetan Plateau, highlighting the mediating roles of snow-related and phenological factors. The findings will provide scientific support for climate simulation and water management policymaking in alpine regions worldwide.

The SC-CO2 jet drilling and completion technology can ensure the stability of coalbed methane wells, improve drilling speed and rock breaking efficiency, and has a wide application prospect. However, the high energy consumption and complex system of coal breaking limit its engineering application. The impact frequency of self-excited oscillation pulse SC-CO2 jet is the same as the natural frequency of coal and rock mass or satisfies the phase relationship, which can give full play to the resonance effect and achieve a better coal breaking effect. The nozzle structure is the key to affect the jet impact frequency. The existing frequency modulation method of self-resonating pulsed water jet is not suitable for the SC-CO2 jet. In order to realize the modulation of the impact frequency of the SC-CO2 jet, a large eddy simulation was used to study the influence law of different nozzle structures on the impact frequency of self-excited oscillation pulse SC-CO2 jet, and the influence degree of different nozzle structure parameters on jet impact frequency was obtained by weight analysis. The influence rule of nozzle structure on the jet impact frequency and the reliability of jet impact frequency modulation method are verified by jet impact frequency measurement experiment and coal breaking experiment. The results show that the diameter and length of the oscillating cavity, and the angle of the collision wall are the key factors affecting the jet impact frequency. The jet impact frequency can be substantially modulated by adjusting the structure of the oscillating cavity, so as to achieve the resonance effect. By adjusting the oscillating cavity structure, the jet impact frequency forms resonance with the inherent frequency of coal, then the coal breaking effect is significantly improved, and the smaller the resonance multiplier, the better the coal breaking effect of the jet, which can effectively improve the coal breaking efficiency. When the natural frequency of coal is 25 Hz, the outlet diameter of the upstream and downstream nozzle is set as 2.5 mm and 3.0 mm, and the diameter, length and angle of the oscillating chamber are adjusted to 10 mm, 3 mm and 120° respectively. The jet impact frequency reaches 25051.83 Hz, which is 1002.0 times of the natural frequency of coal and forms a resonance effect with the natural frequency of coal, effectively improves the coal breaking efficiency.

Abstract This research added rare Earth elements Ce to the P110-grade oil casing steel to reveal their influence on the inclusions and tensile properties. The content of cerium in the steel varied from 0 to 452 ppm. Based on the classical thermodynamic calculation, the predominance diagram of Re-containing inclusions in P110-grade steel was obtained. The evolution route of the inclusions composition with the increasing cerium content in the steel was xCaO⋅yAl2O3 → Al2O3–CeAlO3 → Ce2O3–CeAlO3 → Ce2O3–Ce2O2S → Ce2O2S, which agreed well with the thermodynamic analysis. As the cerium content at 235 ppm, the size of Ce containing inclusions has a minimal size at 2.82 μm. Suitable Ce content can modify the big-size xCaO⋅yAl2O3 inclusions into small-size Re-containing inclusions. The results demonstrate that the tensile performance of this steel can be improved as the cerium content increases from 0 to 235 ppm. However, once the cerium content exceeds 235 ppm, further increases in cerium content led to a decline in performance. The experimental results shows that the presence of large-sized Ce2O2S inclusions and the change of microstructure, will lead to the decrease in tensile performance.

Abstract Our research endeavors are directed towards unraveling the stem cell characteristics of lower-grade glioma patients, with the ultimate goal of formulating personalized treatment strategies. We computed enrichment stemness scores and performed consensus clustering to categorize phenotypes. Subsequently, we constructed a prognostic risk model using weighted gene correlation network analysis (WGCNA), random survival forest regression analysis as well as full subset regression analysis. To validate the expression differences of key genes, we employed experimental methods such as quantitative Polymerase Chain Reaction (qPCR) and assessed cell line proliferation, migration, and invasion. Three subtypes were assigned to patients diagnosed with LGG. Notably, Cluster 2 (C2), exhibiting the poorest survival outcomes, manifested characteristics indicative of the subtype characterized by immunosuppression. This was marked by elevated levels of M1 macrophages, activated mast cells, along with higher immune and stromal scores. Four hub genes—CDCA8, ORC1, DLGAP5, and SMC4—were identified and validated through cell experiments and qPCR. Subsequently, these validated genes were utilized to construct a stemness risk signature. Which revealed that Lower-Grade Glioma (LGG) patients with lower scores were more inclined to demonstrate favorable responses to immune therapy. Our study illuminates the stemness characteristics of gliomas, which lays the foundation for developing therapeutic approaches targeting CSCs and enhancing the efficacy of current immunotherapies. By identifying the stemness subtype and its correlation with prognosis and TME patterns in glioma patients, we aim to advance the development of personalized treatments, enhancing the ability to predict and improve overall patient prognosis.

Abstract Tigecycline is widely used for treating complicated bacterial infections for which there are no effective drugs. It inhibits bacterial protein translation by blocking the ribosomal A-site. However, even though it is also cytotoxic for human cells, the molecular mechanism of its inhibition remains unclear. Here, we present cryo-EM structures of tigecycline-bound human mitochondrial 55S, 39S, cytoplasmic 80S and yeast cytoplasmic 80S ribosomes. We find that at clinically relevant concentrations, tigecycline effectively targets human 55S mitoribosomes, potentially, by hindering A-site tRNA accommodation and by blocking the peptidyl transfer center. In contrast, tigecycline does not bind to human 80S ribosomes under physiological concentrations. However, at high tigecycline concentrations, in addition to blocking the A-site, both human and yeast 80S ribosomes bind tigecycline at another conserved binding site restricting the movement of the L1 stalk. In conclusion, the observed distinct binding properties of tigecycline may guide new pathways for drug design and therapy.

Abstract SARS-CoV-2 infection is initiated by Spike glycoprotein binding to the human angiotensin-converting enzyme 2 (ACE2) receptor via its receptor binding domain. Blocking this interaction has been proven to be an effective approach to inhibit virus infection. Here we report the discovery of a neutralizing nanobody named VHH60, which was directly produced from an engineering nanobody library based on a commercialized nanobody within a very short period. VHH60 competes with human ACE2 to bind the receptor binding domain of the Spike protein at S351, S470-471and S493-494 as determined by structural analysis, with an affinity of 2.56 nM. It inhibits infections of both ancestral SARS-CoV-2 strain and pseudotyped viruses harboring SARS-CoV-2 wildtype, key mutations or variants at the nanomolar level. Furthermore, VHH60 suppressed SARS-CoV-2 infection and propagation 50-fold better and protected mice from death for twice as long as the control group after SARS-CoV-2 nasal infections in vivo. Therefore, VHH60 is not only a powerful nanobody with a promising profile for disease control but also provides evidence for a highly effective and rapid approach to generating therapeutic nanobodies.

Abstract Background Pulmonary arteriovenous malformation (PAVM), also known as pulmonary arteriovenous fistula, is a rare vascular developmental anomaly. Most cases of PAVM are associated with hereditary hemorrhagic telangiectasia (HHT). Hemothorax associated with PAVM is even rarer, and management concerning this complication still challenges. Case presentation A 55-year-old man with sudden onset of dyspnea and chest pain was admitted to our hospital. He had a medical history of epistaxis, intraperitoneal germ cell tumor and PAVM. Chest unenhanced CT revealed the left-sided pleural effusion together with partial passive atelectasis and gradual increase at the interval of six days. Diagnostic thoracocentesis further revealed hemorrhagic effusion. CT angiography (CTA) showed tortuously dilated lumen of the left lower pulmonary artery and PAVM with the formation of aneurysm. Due to his family's refusal of surgery, the patient underwent transcatheter embolization therapy. However, the left pleural effusion did not significantly reduce and there was a slow drop in hemoglobin value even after interventional treatment, indicating the possibility of ongoing active bleeding. Eventually, the patient received lobectomy of the left lower lobe with a satisfactory outcome. Conclusions Massive hemothorax resulting from PAVM rupture into the pleural space can lead to fatal outcomes. CTA can accurately diagnose this pathologic condition. Transcatheter embolization is frequently used in the treatment of PAVM, but it may be challenging to achieve the desirable effect in patients with hemothorax. Combined with our case and literature review, direct radical surgery can lead to a successful outcome when PAVM complicated with hemothorax and a large diameter of the draining vein.

Abstract Background Acute kidney injury (AKI) is a common and serious condition, particularly among elderly patients. It is associated with high morbidity and mortality rates, further compounded by the need for continuous renal replacement therapy in severe cases. To improve clinical decision-making and patient management, there is a need for accurate prediction models that can identify patients at a high risk of mortality. Methods Data were extracted from the Dryad Digital Repository. Multivariate analysis was performed using least absolute shrinkage and selection operator (LASSO) logistic regression analysis to identify independent risk factors and construct a predictive nomogram for mortality within 28 days after continuous renal replacement therapy in elderly patients with acute kidney injury. The discrimination of the model was evaluated in the validation cohort using the area under the receiver operating characteristic curve (AUC), and calibration was evaluated using a calibration curve. The clinical utility of the model was assessed using decision curve analysis (DCA). Results A total of 606 participants were enrolled and randomly divided into two groups: a training cohort (n = 424) and a validation cohort (n = 182) in a 7:3 proportion. A risk prediction model was developed to identify independent predictors of 28-day mortality in elderly patients with AKI. The predictors included age, systolic blood pressure, creatinine, albumin, phosphorus, age-adjusted Charlson Comorbidity Index (CCI), Acute Physiology and Chronic Health Evaluation II (APACHE II) score, and sequential organ failure assessment (SOFA) score. These predictors were incorporated into a logistic model and presented in a user-friendly nomogram. In the validation cohort, the model demonstrated good predictive performance with an AUC of 0.799. The calibration curve showed that the model was well calibrated. Additionally, DCA revealed significant net benefits of the nomogram for clinical application. Conclusion The development of a nomogram for predicting 28-day mortality in elderly patients with AKI receiving continuous renal replacement therapy has the potential to improve prognostic accuracy and assist in clinical decision-making.

Abstract Background Amylose, a prebiotic found in yams is known to be beneficial for the gut microflora and is particularly advantageous for diabetic patients’ diet. However, the genetic machinery underlying amylose production remains elusive. A comprehensive characterization of the genetic basis of amylose content in yam tubers is a prerequisite for accelerating the genetic engineering of yams with respect to amylose content variation. Results To uncover the genetic variants underlying variation in amylose content, we evaluated amylose content in freshly harvested tubers from 150 accessions of Dioscorea zingibensis. With 30,000 high-quality single nucleotide polymorphisms (SNP), we performed a genome-wide association analysis (GWAS). The population structure analysis classified the D. zingiberensis accessions into three groups. A total of 115 significant loci were detected on four chromosomes. Of these, 112 significant SNPs (log10(p) = 5, q-value

Abstract The microscopic mechanism for the disappearance of superconductivity in overdoped cuprates is still under heated debate. Here we use scanning tunneling spectroscopy to investigate the evolution of quasiparticle interference phenomenon in Bi2Sr2CuO6+δ over a wide range of hole densities. We find that when the system enters the overdoped regime, a peculiar quasiparticle interference wavevector with arc-like pattern starts to emerge even at zero bias, and its intensity grows with increasing doping level. Its energy dispersion is incompatible with the octet model for d-wave superconductivity, but is highly consistent with the scattering interference of gapless normal carriers. The gapless quasiparticles are mainly located near the antinodes and are independent of temperature, consistent with the disorder scattering mechanism. We propose that a branch of normal fluid emerges from the pair-breaking scattering between flat antinodal bands in the quantum ground state, which is the primary cause for the reduction of superfluid density and suppression of superconductivity in overdoped cuprates.

Abstract Background Human liver cancer stem-like cells (HLCSLCs) are widely acknowledged as significant factors in the recurrence and eradication of hepatocellular carcinoma (HCC). The sustenance of HLCSLCs’ stemness is hypothesized to be intricately linked to the epigenetic process of DNA methylation modification of genes associated with anticancer properties. The present study aimed to elucidate the stemness-maintaining mechanism of HLCSLCs and provide a novel idea for the clearance of HLCSLCs. Methods The clinical relevance of DNMT1 and SOCS1 in hepatocellular carcinoma (HCC) patients was evaluated through the GEO and TCGA databases. Cellular immunofluorescence assay, methylation-specific PCR, chromatin immunoprecipitation were conducted to explore the expression of DNMT1 and SOCS1 and the regulatory relationship between them in HLCSLCs. Spheroid formation, soft agar colony formation, expression of stemness-associated molecules, and tumorigenicity of xenograft in nude mice were used to evaluate the stemness of HLCSLCs. Results The current analysis revealed a significant upregulation of DNMT1 and downregulation of SOCS1 in HCC tumor tissues compared to adjacent normal liver tissues. Furthermore, patients exhibiting an elevated DNMT1 expression or a reduced SOCS1 expression had low survival. This study illustrated the pronounced expression and activity of DNMT1 in HLCSLCs, which effectively targeted the promoter region of SOCS1 and induced hypermethylation, consequently suppressing the expression of SOCS1. Notably, the stemness of HLCSLCs was reduced upon treatment with DNMT1 inhibitors in a concentration-dependent manner. Additionally, the overexpression of SOCS1 in HLCSLCs significantly mitigated their stemness. The knockdown of SOCS1 expression reversed the effect of DNMT1 inhibitor on the stemness of HLCSLCs. DNMT1 directly binds to the SOCS1 promoter. In vivo, DNMT1 inhibitors suppressed SOCS1 expression and inhibited the growth of xenograft. Conclusion DNMT1 targets the promoter region of SOCS1, induces hypermethylation of its CpG islands, and silences its expression, thereby promoting the stemness of HLCSLCs.

Abstract Objective In this study, we examined the value of chest CT signs combined with peripheral blood eosinophil percentage in differentiating between pulmonary paragonimiasis and tuberculous pleurisy in children. Methods Patients with pulmonary paragonimiasis and tuberculous pleurisy were retrospectively enrolled from January 2019 to April 2023 at the Kunming Third People’s Hospital and Lincang People’s Hospital. There were 69 patients with pulmonary paragonimiasis (paragonimiasis group) and 89 patients with tuberculous pleurisy (tuberculosis group). Clinical symptoms, chest CT imaging findings, and laboratory test results were analyzed. Using binary logistic regression, an imaging model of CT signs and a combined model of CT signs and eosinophils were developed to calculate and compare the differential diagnostic performance of the two models. Results CT signs were used to establish the imaging model, and the receiver operating characteristic (ROC) curve was plotted. The area under the curve (AUC) was 0.856 (95% CI: 0.799–0.913), the sensitivity was 66.7%, and the specificity was 88.9%. The combined model was established using the CT signs and eosinophil percentage, and the ROC was plotted. The AUC curve was 0.950 (95% CI: 0.919–0.980), the sensitivity was 89.9%, and the specificity was 90.1%. The differential diagnostic efficiency of the combined model was higher than that of the imaging model, and the difference in AUC was statistically significant. Conclusion The combined model has a higher differential diagnosis efficiency than the imaging model in the differentiation of pulmonary paragonimiasis and tuberculous pleurisy in children. The presence of a tunnel sign on chest CT, the absence of pulmonary nodules, and an elevated percentage of peripheral blood eosinophils are indicative of pulmonary paragonimiasis in children.

Abstract The challenge of spatial resource allocation is pervasive across various domains such as transportation, industry, and daily life. As the scale of real-world issues continues to expand and demands for real-time solutions increase, traditional algorithms face significant computational pressures, struggling to achieve optimal efficiency and real-time capabilities. In recent years, with the escalating computational power of computers, the remarkable achievements of reinforcement learning in domains like Go and robotics have demonstrated its robust learning and sequential decision-making capabilities. Given these advancements, there has been a surge in novel methods employing reinforcement learning to tackle spatial resource allocation problems. These methods exhibit advantages such as rapid solution convergence and strong model generalization abilities, offering a new perspective on resolving spatial resource allocation problems. Despite the progress, reinforcement learning still faces hurdles when it comes to spatial resource allocation. There remains a gap in its ability to fully grasp the diversity and intricacy of real-world resources. The environmental models used in reinforcement learning may not always capture the spatial dynamics accurately. Moreover, in situations laden with strict and numerous constraints, reinforcement learning can sometimes fall short in offering feasible strategies. Consequently, this paper is dedicated to summarizing and reviewing current theoretical approaches and practical research that utilize reinforcement learning to address issues pertaining to spatial resource allocation. In addition, the paper accentuates several unresolved challenges that urgently necessitate future focus and exploration within this realm and proposes viable approaches for these challenges. This research furnishes valuable insights that may assist scholars in gaining a more nuanced understanding of the problems, opportunities, and potential directions concerning the application of reinforcement learning in spatial resource allocation.

Abstract The further practical applications of Li-rich layered oxides are impeded by voltage decay and redox asymmetry, which are closely related to the structural degradation involving irreversible transition metal migration. It has been demonstrated that the superstructure ordering in O2-type materials can effectively suppress voltage decay and redox asymmetry. Herein, we elucidate that the absence of this superstructure ordering arrangement in a Ru-based O2-type oxide can still facilitate the highly reversible transition metal migration. We certify that Ru in superstructure-free O2-type structure can unlock a quite different migration path from Mn in mostly studied cases. The highly reversible migration of Ru helps the cathode maintain the structural robustness, thus realizing terrific capacity retention with neglectable voltage decay and inhibited oxygen redox asymmetry. We untie the knot that the absence of superstructure ordering fails to enable a high-performance Li-rich layered oxide cathode material with suppressed voltage decay and redox asymmetry.

Abstract The potential for off-target mutations is a critical concern for the therapeutic application of CRISPR-Cas9 gene editing. Current detection methodologies, such as GUIDE-seq, exhibit limitations in oligonucleotide integration efficiency and sensitivity, which could hinder their utility in clinical settings. To address these issues, we introduce OliTag-seq, an in-cellulo assay specifically engineered to enhance the detection of off-target events. OliTag-seq employs a stable oligonucleotide for precise break tagging and an innovative triple-priming amplification strategy, significantly improving the scope and accuracy of off-target site identification. This method surpasses traditional assays by providing comprehensive coverage across various sgRNAs and genomic targets. Our research particularly highlights the superior sensitivity of induced pluripotent stem cells (iPSCs) in detecting off-target mutations, advocating for using patient-derived iPSCs for refined off-target analysis in therapeutic gene editing. Furthermore, we provide evidence that prolonged Cas9 expression and transient HDAC inhibitor treatments enhance the assay’s ability to uncover off-target events. OliTag-seq merges the high sensitivity typical of in vitro assays with the practical application of cellular contexts. This approach significantly improves the safety and efficacy profiles of CRISPR-Cas9 interventions in research and clinical environments, positioning it as an essential tool for the precise assessment and refinement of genome editing applications.

Abstract Introduction Dental implantation has emerged as an efficient substitute for missing teeth, which is essential for restoring oral function and aesthetics. Compared to traditional denture repair approaches, dental implants offer better stability and sustainability. The position, angle, and depth of dental implants are crucial factors for their long-term success and necessitate high-precision operation and technical support. Method We propose an integrated dual-arm high-precision oral implant surgery navigation positioning system and a corresponding control strategy. Compared with traditional implant robots, the integrated dual-arm design greatly shortens the preparation time before surgery and simplifies the operation process. We propose a novel control flow and module for the proposed structure, including an Occluded Target Tracking Module (OTTM) for occlusion tracking, a Planting Plan Development Module (PPDM) for generating implant plans, and a Path Formulation Module (PFM) for controlling the movement path of the two robot arms. Result Under the coordinated control of the aforementioned modules, the robot achieved excellent accuracy in clinical trials. The average angular error and entry point error for five patients who underwent implant surgery using the proposed robot were 2.1° and 0.39 mm, respectively. Conclusion In essence, our study introduces an integrated dual-arm high-precision navigation system for oral implant surgery, resolving issues like lengthy preoperative preparation and static surgical planning. Clinical results confirm its efficacy, emphasizing its accuracy and precision in guiding oral implant procedures.

Targeted protein degradation (TPD) represented by proteolysis targeting chimeras (PROTACs) marks a significant stride in drug discovery. A plethora of innovative technologies inspired by PROTAC have not only revolutionized the landscape of TPD but have the potential to unlock functionalities beyond degradation. Non-small-molecule-based approaches play an irreplaceable role in this field. A wide variety of agents spanning a broad chemical spectrum, including peptides, nucleic acids, antibodies, and even vaccines, which not only prove instrumental in overcoming the constraints of conventional small molecule entities but also provided rapidly renewing paradigms. Herein we summarize the burgeoning non-small molecule technological platforms inspired by PROTACs, including three major trajectories, to provide insights for the design strategies based on novel paradigms.

Recovery stress governs the prestress strengthening effect of Fe–Mn–Si-based shape memory alloys in civil engineering applications. Although the effects of grain size, texture, and precipitates on recovery stresses have been extensively studied, the generation of recovery stress has not been thoroughly discussed regarding martensite growth behavior, especially considering the interaction of martensite variants. This study investigates the stress recovery and ε martensite growth behavior of a Fe–30Mn–6Si–5Cr (wt.%) alloy subjected to varying levels of deformation. The Fe–30Mn–6Si–5Cr (wt.%) alloy exhibits a yield strength of approximately 450 MPa, with an ultimate elongation of 44 % and a tensile strength of 950 MPa observed in uniaxial incremental cyclic tensile tests. Additionally, the results reveal an initial increase in recovery stress with pre-strain, peaking at 7 %, followed by a subsequent decrease with further deformation. With increasing pre-strain, the primary ε martensites initially grow parallelly, followed by the appearance of secondary martensites with a different orientation, intersecting multiple parallel primary martensites along with the increasing density of dislocations and stacking faults. A microstructural mechanism is proposed to elucidate the stress recovery behavior, encompassing the impact of primary martensites and secondary martensites interaction, and the influence of dislocations and stacking faults. This work offers microstructural scenarios that help to understand the generation of recovery stress and provides guidance for regulating recovery stress in Fe–Mn–Si-based shape memory alloys for civil engineering applications requiring prestress strengthening.

BackgroundNonylphenol (NP) is a typical phenolic endocrine disruptor, and there are significant differences in NP concentration in different regions and water types. ObjectiveTo investigate the concentration of NP in three types (river, lake, and reservoir) of water sources in Hubei Province, and assess its ecological risk and population health risk. MethodsFifteen sampling points were set up at four river water sources (Liangtingshan Waterworks, Baishazhou Waterworks, Dijiao Waterworks, and Zongguan Waterworks), one lake water source (Liangzi Lake), and one reservoir water source (Fushui Reservoir). Water samples were collected from the 15 sampling points in June 2019 (wet season), October 2019 (level season), and December 2019 (dry season), respectively. The NP concentration in water samples was detected using ultra-high-performance liquid chromatography-tandem mass spectrometry, and the differences in NP concentration among groups were compared using variance analysis. The ecological risk and the health risk of NP were evaluated using risk quotient (RQ) and non-carcinogenic risk index (NCRI), respectively. ResultsThe detection rate of NP was 100%, with an average concentration of (18.10±15.00) ng·L−1 (5.45-92.71 ng·L−1). The average concentrations of NP during the level, wet, and dry seasons were (11.52±5.31) ng·L−1, (23.86±22.08) ng·L−1, and (18.93±9.51) ng·L−1, respectively, and the maximum concentrations were 24.62 ng·L−1, 92.71 ng·L−1, and 42.38 ng·L−1, respectively. The variance analysis showed no statistical difference in the NP concentration in the samples from rivers, lakes, and reservoirs in different periods (P>0.05). Only the water samples from the water source serving the Zongguan Waterworks showed an RQ (0.19) greater than 0.1 during the wet season, indicating a moderate risk. The RQ values of other water samples were all less than 0.1, indicating an overall relatively low ecological risk. The highest NCRI values during the level, wet, and dry seasons were 0.1459, 0.5492, and 0.2511, respectively, all less than 1, indicating an acceptable health risk level. ConclusionThe NP concentrations in all water sources in this study are at a relatively low level, which poses an acceptable risk level to human health.

Among central nervous system-associated malignancies, glioblastoma (GBM) is the most common and has the highest mortality rate. The high heterogeneity of GBM cell types and the complex tumor microenvironment frequently lead to tumor recurrence and sudden relapse in patients treated with temozolomide. In precision medicine, research on GBM treatment is increasingly focusing on molecular subtyping to precisely characterize the cellular and molecular heterogeneity, as well as the refractory nature of GBM toward therapy. Deep understanding of the different molecular expression patterns of GBM subtypes is critical. Researchers have recently proposed tetra fractional or tripartite methods for detecting GBM molecular subtypes. The various molecular subtypes of GBM show significant differences in gene expression patterns and biological behaviors. These subtypes also exhibit high plasticity in their regulatory pathways, oncogene expression, tumor microenvironment alterations, and differential responses to standard therapy. Herein, we summarize the current molecular typing scheme of GBM and the major molecular/genetic characteristics of each subtype. Furthermore, we review the mesenchymal transition mechanisms of GBM under various regulators.

Abstract Background The purpose of this study was to develop a nomogram for predicting in-hospital mortality in cirrhotic patients with acute kidney injury (AKI) in order to identify patients with a high risk of in-hospital death early. Methods This study collected data on cirrhotic patients with AKI from 2008 to 2019 using the Medical Information Mart for Intensive Care IV. Multivariate logistic regression was used to identify confounding factors related to in-hospital mortality, which were then integrated into the nomogram. The concordance index (C-Index) was used to evaluate the accuracy of the model predictions. The area under the curve (AUC) and decision curve analysis (DCA) was used to assess the predictive performance and clinical utility of the nomogram. Results The final study population included 886 cirrhotic patients with AKI, and 264 (29.8%) died in the hospital. After multivariate logistic regression, age, gender, cerebrovascular disease, heart rate, respiration rate, temperature, oxygen saturation, hemoglobin, blood urea nitrogen, serum creatinine, international normalized ratio, bilirubin, urine volume, and sequential organ failure assessment score were predictive factors of in-hospital mortality. In addition, the nomogram showed good accuracy in estimating the in-hospital mortality of patients. The calibration plots showed the best agreement with the actual presence of in-hospital mortality in patients. In addition, the AUC and DCA curves showed that the nomogram has good prediction accuracy and clinical value. Conclusions We have created a prognostic nomogram for predicting in-hospital death in cirrhotic patients with AKI, which may facilitate timely intervention to improve prognosis in these patients.

Abstract With the rapid advancement of sports analytics and fan engagement technologies, the volume and diversity of physique data generated by smart devices across various distributed sports platforms have grown significantly. Extracting insights and enhancing fan experiences from such data offer considerable benefits. Yet, this process unveils two primary challenges. Firstly, efficiently utilizing the vast datasets in sports analytics is daunting due to the complex nature of the sports industry. Secondly, the data collected from diverse sources and stored in distributed platforms contain sensitive information like fan preferences and athlete performance metrics, posing risks of privacy breaches. To address these challenges, we leverage an advanced Locality-Sensitive Hashing technique, known as PSDFP $$_{\text {ALSH}}$$ ALSH , tailored for the sports domain. This paper presents a new privacy-preserving method for sports data fusion and prediction in distributed environments, utilizing enhanced Locality-Sensitive Hashing to protect sensitive information while maintaining high data utility. Through extensive experimentation, our approach demonstrates superior performance over existing methods in terms of Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), and computational efficiency.

Abstract Background Severe fever with thrombocytopenia syndrome (SFTS) is an emerging infectious disease. SFTS virus (SFTSV) is transmitted by tick bites and contact with the blood or body fluids of SFTS patients. Animal-to-human transmission of SFTS has been reported in Japan, but not in China. In this study, the possible transmission route of two patients who fed and cared for farm-raised fur animals in a mink farm was explored. Method An epidemiological investigation and a genetic analysis of patients, animals and working environment were carried out. Results It was found that two patients had not been bitten by ticks and had no contact with patients infected with SFTS virus, but both of them had skinned the dying animals. 54.55% (12/22) of the farm workers were positive for SFTS virus antibody. By analyzing the large, medium and small segments sequences, the viral sequences from the two patients, animals and environments showed 99.9% homology. Conclusion It is suspected that the two patients may be directly infected by farm-raised animals, and that the virus may have been transmitted by aerosols when skinning dying animals. Transmission by direct blood contacts or animal bites cannot be ignored.

Abstract Background Dendrobium officinale Kimura et Migo, a renowned traditional Chinese orchid herb esteemed for its significant horticultural and medicinal value, thrives in adverse habitats and contends with various abiotic or biotic stresses. Acid invertases (AINV) are widely considered enzymes involved in regulating sucrose metabolism and have been revealed to participate in plant responses to environmental stress. Although members of AINV gene family have been identified and characterized in multiple plant genomes, detailed information regarding this gene family and its expression patterns remains unknown in D. officinale, despite their significance in polysaccharide biosynthesis. Results This study systematically analyzed the D. officinale genome and identified four DoAINV genes, which were classified into two subfamilies based on subcellular prediction and phylogenetic analysis. Comparison of gene structures and conserved motifs in DoAINV genes indicated a high-level conservation during their evolution history. The conserved amino acids and domains of DoAINV proteins were identified as pivotal for their functional roles. Additionally, cis-elements associated with responses to abiotic and biotic stress were found to be the most prevalent motif in all DoAINV genes, indicating their responsiveness to stress. Furthermore, bioinformatics analysis of transcriptome data, validated by quantitative real-time reverse transcription PCR (qRT-PCR), revealed distinct organ-specific expression patterns of DoAINV genes across various tissues and in response to abiotic stress. Examination of soluble sugar content and interaction networks provided insights into stress release and sucrose metabolism. Conclusions DoAINV genes are implicated in various activities including growth and development, stress response, and polysaccharide biosynthesis. These findings provide valuable insights into the AINV gene amily of D. officinale and will aid in further elucidating the functions of DoAINV genes.

Abstract Lead (Pb2+) toxification is a concerning, unaddressed global public health crisis that leads to 1 million deaths annually. Yet, public policies to address this issue have fallen short. This work harnesses the unique abilities of crown ethers, which selectively bind to specific ions. This study demonstrates the synergistic integration of highly-scalable silicon photonics, with crown ether amine conjugation via Fischer esterification in an environmentally-friendly fashion. This realizes an integrated photonic platform that enables the in-operando, highly-selective and quantitative detection of various ions. The development dispels the existing notion that Fischer esterification is restricted to organic compounds, facilitating the subsequent amine conjugation for various crown ethers. The presented platform is specifically engineered for selective Pb2+ detection, demonstrating a large dynamic detection range, and applicability to field samples. The compatibility of this platform with cost-effective manufacturing indicates the potential for pervasive implementation of the integrated photonic sensor technology to safeguard against societal Pb2+ poisoning.