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Abstract Sepsis is a severe infectious disease with high mortality. However, the indicators used to evaluate its severity and prognosis are relatively complicated. The systemic inflammatory response index (SIRI), a new inflammatory indicator, has shown good predictive value in chronic infection, stroke, and cancer. The purpose of this study was to investigate the connection between sepsis and SIRI and evaluate its predictive usefulness. A total of 401 patients with sepsis were included in this study. Multiple linear regression and logistic regression analyses were performed to evaluate the relationship between SIRI and sepsis. The restricted cubic spline (RCS) method was employed to illustrate the dose-response relationship. The area under the curve (AUC) and decision curve analysis (DCA) were used to evaluate the prognostic value of SIRI. Multiple linear regression analysis revealed a significant positive correlation between SIRI and both blood cell count and Sequential Organ Failure Assessment (SOFA) score. Additionally, higher SIRI levels were significantly linked to a higher risk of sepsis worsening, according to logistic regression analysis. The RCS curve demonstrated that the risk of poor prognosis rose with increasing SIRI, particularly when SIRI exceeded 6.1. Furthermore, AUC and DCA results showed that SIRI had superior predictive value compared to traditional indicators. A higher SIRI is linked to a worse prognosis and more severe sepsis. SIRI may serve as a novel prognostic indicator in sepsis, though further clinical studies are necessary to confirm these findings.

Abstract Plants, with intricate molecular networks for environmental adaptation, offer groundbreaking potential for reprogramming with predictive genetic circuits. However, realizing this goal is challenging due to the long cultivation cycle of plants, as well as the lack of reproducible, quantitative methods and well-characterized genetic parts. Here, we establish a rapid (~10 days), quantitative, and predictive framework in plants. A group of orthogonal sensors, modular synthetic promoters, and NOT gates are constructed and quantitatively characterized. A predictive model is developed to predict the designed circuits’ behavior accurately. Our versatile and robust framework, validated by constructing 21 two-input circuits with high prediction accuracy (R 2 = 0.81), enables multi-state phenotype control in both Arabidopsis thaliana and Nicotiana benthamiana in response to chemical inducers. Our study achieves predictable design and application of synthetic circuits in plants, offering valuable tools for the rapid engineering of plant traits in biotechnology and agriculture.

Abstract “Exercise is medicine” emphasizes personalized prescriptions for better efficacy. Current guidelines need more support for personalized prescriptions, posing scientific challenges. Facing those challenges, we gathered data from established guidelines, databases, and articles to develop the Exercise Medicine Ontology (EXMO), intending to offer comprehensive support for personalized exercise prescriptions. EXMO was constructed using the Ontology Development 101 methodology, incorporating Open Biological and Biomedical Ontology Foundry principles. EXMO v1.0 comprises 434 classes and 9,732 axioms, encompassing physical activity terms, health status terms, exercise prescription terms, and other related concepts. It has successfully undergone expert evaluation and consistency validation using the ELK and JFact reasoners. EXMO has the potential to provide a much-needed standard for individualized exercise prescription. Beyond prescription standardization, EXMO can also be an excellent tool for supporting databases and recommendation systems. In the future, it could serve as a valuable reference for developing sub-ontologies and facilitating the formation of an ontology network.

Abstract Background Prolonged postoperative ileus (PPOI) reportedly leads to compromised postoperative recovery and increased healthcare costs. However, the evidence for this claim was obtained from studies that included patients with both primary and secondary PPOI. How primary PPOI affects the hospital length of stay (LOS) and healthcare costs is not well documented. A multicenter cohort analysis was performed to investigate the potentially detrimental effect of primary PPOI on hospital LOS and healthcare costs. Methods In total, 2083 patients who underwent open abdominal surgery from 22 tertiary hospitals in China were prospectively registered in a PPOI cohort. Of these, 1863 patients without secondary PPOI were analyzed. Poisson regression for hospital LOS and log-transformed linear regression for healthcare costs were performed to identify whether primary PPOI was an independent risk factor. Results The incidence of primary PPOI was 13.2% (246/1863). The median LOS was significantly longer in the PPOI than non-PPOI group (12 vs. 11 days, p

Abstract Immune checkpoint inhibitors (ICI) represent new anticancer agents and have been used worldwide. However, ICI can potentially induce life-threatening severe cutaneous adverse reaction (SCAR), such as Stevens-Johnson syndrome/toxic epidermal necrolysis (SJS/TEN), hindering continuous ICI therapy. We examine 6 cohorts including 25 ICI-induced SJS/TEN patients and conduct single-cell RNA sequencing (scRNA-seq) analysis, which shows overexpression of macrophage-derived CXCL10 that recruits CXCR3+ cytotoxic T lymphocytes (CTL) in blister cells from ICI-SJS/TEN skin lesions. ScRNA expression profiles and ex vivo blocking studies further identify TNF signaling as a pathway responsible for macrophage-derived CXCL10 and CTL activation. Based on the trajectory analysis, ICI-activated T cells from whole blood are proposed to serve as the initial cells involved in inflammation, that lead to monocytes differentiating into macrophages and increasing their susceptibility to migrate to the lesion sites. Compared with systemic corticosteroids treatment, ICI-induced SJS/TEN patients treated with biologic TNF blockade showed a significantly rapid recovery and no recurrence of SCAR with continuous ICI therapy. Our findings identify that macrophage-eliciting CTL contribute to the pathogenesis of ICI-induced epidermal necrolysis and provide potential therapeutic targets for the management and prevention of SCAR induced by ICI therapy.

Abstract Intraventricular hemorrhage (IVH) occurs in approximately 30–50% patients with spontaneous intracerebral hemorrhage (ICH), with a high 30-day mortality rate. Excess accumulation of parenchymal or ventricular blood associated with the development of acute hydrocephalus leads to poor outcomes. The prediction of shunt dependency is important to identify patients susceptible to requiring permanent shunt placement and benefit from the diversion. This retrospective analytical study aimed to establish a predictive model of shunt dependency in patients with IVH. This study included 179 patients with primary IVH with supratentorial origin or spontaneous ICH with extension into the ventricles between 2015 and 2021. Patients were grouped into “shunt required” and “shunt not required” groups. Variables, including age, sex, preexisting hypertension and diabetes, initial Glasgow Coma Scale scores, ICH location and volume, urokinase administration, modified Graeb score (mGraeb score), and bicaudate index, were analyzed. The shunt required group had significantly higher mGraeb scores (12.0 (6.5–15.0) vs. 7.0 (4.0–12.0), p = 0.001) and higher bicaudate index (0.20 (0.17–0.23) vs. 0.16 (0.13–0.18), P

Abstract Background Differences of sex development (DSD) are congenital conditions in which chromosomal, gonadal, or phenotypic sex is atypical. In more than 50% of human DSD cases, a molecular diagnosis is not available. In intensively farmed pig populations, the incidence of XX DSD pigs is relatively high, leading to economic losses for pig breeders. Interestingly, in the majority of 38, XX DSD pigs, gonads still develop into testis-like structures or ovotestes despite the absence of the testis-determining gene (SRY). However, the current understanding of the molecular background of XX DSD pigs remains limited. Methods Anatomical and histological characteristics of XX DSD pigs were analysed using necropsy and HE staining. We employed whole-genome sequencing (WGS) with 10× Genomics technology and used de novo assembly methodology to study normal female and XX DSD pigs. Finally, the identified variants were validated in 32 XX DSD pigs, and the expression levels of the candidate variants in the gonads of XX DSD pigs were further examined. Results XX DSD pigs are characterised by the intersex reproductive organs and the absence of germ cells in the seminiferous tubules of the gonads. We identified 4,950 single-nucleotide polymorphisms (SNPs) from non-synonymous mutations in XX DSD pigs. Cohort validation results highlighted two specific SNPs, “c.218T > C” in the “Interferon-induced transmembrane protein 1 gene (IFITM1)” and “c.1043C > G” in the “Newborn ovary homeobox gene (NOBOX)”, which were found exclusively in XX DSD pigs. Moreover, we verified 14 candidate structural variants (SVs) from 1,474 SVs, identifying a 70 bp deletion fragment in intron 5 of the WW domain-containing oxidoreductase gene (WWOX) in 62.5% of XX DSD pigs. The expression levels of these three candidate genes in the gonads of XX DSD pigs were significantly different from those of normal female pigs. Conclusion The nucleotide changes of IFITM1 (c.218T > C), NOBOX (c.1043 C > G), and a 70 bp deletion fragment of the WWOX were the most dominant variants among XX DSD pigs. This study provides a theoretical basis for better understanding the molecular background of XX DSD pigs. Plain language summary DSD are conditions affecting development of the gonads or genitalia. These disorders can happen in many different types of animals, including pigs, goats, dogs, and people. In people, DSD happens in about 0.02–0.13% of births, and in pigs, the rate is between 0.08% and 0.75%. Pigs have a common type of DSD where the animal has female chromosomes (38, XX) but no SRY gene, which is usually found on the Y chromosome in males. XX DSD pigs may look like both males and females on the outside and have testis-like or ovotestis (a mix of ovary and testis) gonads inside. XX DSD pigs often lead to not being able to have piglets, slower growth, lower chance of survival, and poorer meat quality. Here, we used a method called whole-genome de novo sequencing to look for variants in the DNA of XX DSD pigs. We then checked these differences in a larger group of pigs. Our results reveal the nucleotide changes in IFITM1 (c.218T > C), NOBOX (c.1043 C > G), and a 70 bp deletion fragment in intron 5 of the WWOX, all linked to XX DSD pigs. The expression levels of these three genes were also different in the gonads of XX DSD pigs compared to normal female pigs. These variants are expected to serve as valuable molecular markers for XX DSD pigs. Because pigs are a lot like humans in their genes, physiology, and body structure, this research could help us learn more about what causes DSD in people.

The effect of technology on primary students' self-regulated vocabulary learning (SRVL) over time and its dynamic relationship with vocabulary outcomes have been scarcely studied. This quasi-experimental study reports a longitudinal inquiry into the effect of a mobile-assisted self-regulation scheme on primary students' SRVL and the relationship between the changes in the perceived SRVL skills and vocabulary learning outcome. The study lasted seven months. Participants were 174 Grade 4 students (89 girls) from four classes at a primary school in Mainland China. Two classes were randomly assigned to the experimental and control groups. Students in both groups used the app named Vocab+, the former with and the latter without a mobile-assisted self-regulation scheme. Data collection included questionnaires on students' perceived SRVL skills and vocabulary tests. Latent Growth Modelling (LGM) was used to analyse data. The results showed that perceived SRVL skills and vocabulary learning outcomes increased over time. The findings further revealed that students in the experimental group exhibited a steeper increasing trend in perceived SRVL skills and vocabulary learning outcomes. Besides, the association between the growth rates of students' perception of SRVL skills and vocabulary learning outcomes was stronger with the experimental group than with the control group. Our results provided theoretical implications for understanding the relationship between SRVL skills and vocabulary learning outcomes from a developmental perspective.

Protozoan infections (e.g., malaria, trypanosomiasis, and toxoplasmosis) pose a considerable global burden on public health and socioeconomic problems, leading to high rates of morbidity and mortality. Due to the limited arsenal of effective drugs for these diseases, which are associated with devastating side effects and escalating drug resistance, there is an urgent need for innovative antiprotozoal drugs. The emergence of drug repurposing offers a low-cost approach to discovering new therapies for protozoan diseases. In this review, we summarize recent advances in drug repurposing for various human protozoan diseases and explore cost-effective strategies to identify viable new treatments. We highlight the cross-applicability of repurposed drugs across diverse diseases and harness common chemical motifs to provide new insights into drug design, facilitating the discovery of new antiprotozoal drugs. Challenges and opportunities in the field are discussed, delineating novel directions for ongoing and future research.

Glycosaminoglycan (GAG) molecules on the surface of red blood cells play an important regulatory role in the invasion of merozoites of apicomplexan protozoa. Heparan sulfate, a type of GAG molecule, has been identified as an important receptor facilitating the invasion of red blood cells by these parasites. Proteins in the parasite that exhibit strong affinity for heparin may play a pivotal role in this invasion process. This study aims to use proteomics to identify Babesia microti proteins with high binding affinity to heparin. Bioinformatics was utilized to analyze the subcellular localization and biological functions of these proteins. Candidate genes encoding proteins with strong heparin affinity will be expressed in a prokaryotic system to produce recombinant proteins. The interaction between these recombinant proteins and heparin will be characterized through heparin-binding experiments and other methods. Initially, a mouse model of B. microti was established and high-density B. microti were obtained. Heparin affinity chromatography was then used to purify natural B. microti proteins that can bind to heparin, identifying 186 B. microti proteins via ESI-MS that specifically interact with heparin. Further studies were carried out to analyze those specific proteins with unique peptide segments of two or more, yielding 15 B. microti proteins, most of which are cell surface proteins and secretory proteins. Based on mass spectrometry identification and subsequent analyses, BMSA5-1-1, B. microti peptidyl-prolyl cis-trans isomerase (BmPPIase), and chaperonin were selected for further study due to their potential impact on the invasion of red blood cells by B. microti. These candidate proteins were expressed as recombinant proteins using a prokaryotic expression system. In vitro heparin-binding assays demonstrated that these recombinant proteins specifically bind to heparin. Notably, BmPPIase and chaperonin recombinant proteins exhibited activity in specific heparin binding. Molecular interaction studies further confirmed the strong interaction between BmPPIase and heparin. In conclusion, this study used proteomic methods to identify 186 specific B. microti proteins with specific binding affinity to heparin, providing in-depth analysis of 15 key proteins. The findings confirmed that BmPPIase and chaperonin specifically bind to heparin, with molecular interaction experiments substantiating the strong interaction between BmPPIase and heparin.

The rapid development of generative artificial intelligence (GenAI) tools has given rise to a growing discussion of the potential challenges and benefits that the use of these technologies may present in the field of education. This study examines the acceptance of the use of GenAI tools for teaching and learning among primary and secondary school teachers in Hong Kong. It uses an extension of the technology acceptance model (TAM) with a modified framework that incorporates two key factors: self-efficacy and subjective norm. Data were collected from a sample of 367 primary and secondary school teachers in Hong Kong using questionnaires containing items for six constructs: self-efficacy, perceived usefulness, perceived ease of use, attitude towards using, subjective norm, and behavioural intention. The results show that fostering teachers' self-efficacy, perceived usefulness, and attitude is essential for successfully increasing their behavioural intention to use GenAI tools. Subjective norm was also found to influence teachers' behavioural intention. To enhance teachers' effective use of GenAI for teaching, teacher development programmes should focus on equipping teachers with comprehensive conceptual knowledge and skills and an understanding of the application of these tools to teaching and learning. Policy support to create a conducive environment for the use of GenAI in teaching and learning would also be beneficial. The study has theoretical implications in its extension of the TAM model as well as implications for enhancing teachers’ AI literacy and developing pedagogies for the meaningful use of GenAI tools for teaching and learning in K–12 settings.

Abstract The ankle joint, which connects the lower limbs and the sole of the foot, is prone to sprain during walking and sports, which leads to ankle arthritis. Supratroleolar osteotomy is an ankle preserving operation for the treatment of ankle arthritis, in which the osteotomy is an important fixing and supporting part. In order to avoid stress shielding effect as much as possible, the osteotomy block is designed as a porous structure. In this study, the osteotomy block was designed based on three-period minimal surface, and the designed structure was manufactured by 3D printing. The mechanical properties of different structures were studied by mechanical test and finite element simulation. In mechanical tests, the Gyroid structure showed a progressive failure mechanism from bottom to bottom, while the Diamond structure showed a shear failure zone at 45° Angle, which was not conducive to energy absorption and was more prone to brittle fracture than the Gyroid structure. Therefore, the Gyroid structure is valuable for further research in the development of porous osteotomy.

Background: Liquid biopsy-based biomarkers, including circulating tumor DNA (ctDNA) and blood tumor mutational burden (bTMB), are recognized as promising predictors of prognoses and responses to immune checkpoint inhibitors (ICIs), despite insufficient sensitivity of single biomarker detection. This research aims to determine whether the combinatorial utility of longitudinal ctDNA with bTMB analysis could improve the prognostic and predictive effects. Methods: This prospective two-center cohort trial, consisting of discovery and validation datasets, enrolled unresectable locally advanced non-small-cell lung cancer (LA-NSCLC) patients and assigned them to chemoradiotherapy (CRT) or CRT + consolidation ICI cohorts from 2018 to 2022. Blood specimens were collected pretreatment, 4 weeks post-CRT, and at progression to assess bTMB and ctDNA using 486-gene next-generation sequencing. Dynamic ∆bTMB was calculated as post-CRT bTMB minus baseline bTMB levels. Decision curve analyses were performed to calculate Concordance index (C-index). Results: One hundred twenty-eight patients were enrolled. In the discovery dataset (n = 73), patients treated with CRT and consolidation ICI had significantly longer overall survival (OS; median not reached [NR] vs 20.2 months; P < 0.001) and progression-free survival (PFS; median 25.2 vs 11.4 months; P = 0.011) than those without ICI. Longitudinal analysis demonstrated a significant decrease in ctDNA abundance post-CRT (P < 0.001) but a relative increase with disease progression. Post-CRT detectable residual ctDNA correlated with significantly shorter OS (median 18.3 months vs NR; P = 0.001) and PFS (median 7.3 vs 25.2 months; P < 0.001). For patients with residual ctDNA, consolidation ICI brought significantly greater OS (median NR vs 14.8 months; P = 0.005) and PFS (median 13.8 vs 6.2 months; P = 0.028) benefit, but no significant difference for patients with ctDNA clearance. Dynamic ∆bTMB was predictive of prognosis. Patients with residual ctDNA and increased ∆bTMB (∆bTMB > 0) had significantly worse OS (median 9.0 vs 23.0 months vs NR; P < 0.001) and PFS (median 3.4 vs 7.3 vs 25.2 months; P < 0.001). The combinatorial model integrating post-CRT ctDNA with ∆bTMB had optimal predictive effects on OS (C-index = 0.723) and PFS (C-index = 0.693), outperforming individual features. In the independent validation set, we confirmed residual ctDNA predicted poorer PFS (median 50.8 vs 14.3 months; P = 0.026) but identified more consolidation ICI benefit (median NR vs 8.3 months; P = 0.039). The combined model exhibited a stable predictive advantage (C-index = 0.742 for PFS). Conclusions: The multiparameter assay integrating qualitative residual ctDNA testing with quantitative ∆bTMB dynamics improves patient prognostic risk stratification and efficacy predictions, allowing for personalized consolidation therapy for LA-NSCLC.

The hypoxic microenvironment, characterized by significantly reduced oxygen levels within tissues, has emerged as a critical factor in the pathogenesis and progression of various autoimmune diseases (AIDs). Central to this process is the hypoxia-inducible factor-1 (HIF-1), which orchestrates a wide array of cellular responses under low oxygen conditions. This review delves into the multifaceted roles of the hypoxic microenvironment in modulating immune cell function, particularly highlighting its impact on immune activation, metabolic reprogramming, and angiogenesis. Specific focus is given to the mechanisms by which hypoxia contributes to the development and exacerbation of diseases such as rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), multiple sclerosis (MS), and dermatomyositis (DM). In these conditions, the hypoxic microenvironment not only disrupts immune tolerance but also enhances inflammatory responses and promotes tissue damage. The review also discusses emerging therapeutic strategies aimed at targeting the hypoxic pathways, including the application of HIF-1α inhibitors, mTOR inhibitors, and other modulators of the hypoxic response. By providing a comprehensive overview of the interplay between hypoxia and immune dysfunction in AIDs, this review offers new perspectives on the underlying mechanisms of these diseases and highlights potential avenues for therapeutic intervention.

ABSTRACT Introduction There is an urgent clinical need to accurately predict the risk for disease progression in post‐treatment NSCLC patients, yet current ctDNA mutation profiling approaches are limited by low sensitivity. We represent a non‐invasive liquid biopsy assay utilizing cfDNA neomer profiling for predicting disease progression in 44 inoperable localized NSCLC patients. Methods A total of 97 plasma samples were collected at various time points during or post‐treatments (TP1: 39, TP2: 33, TP3: 25). cfDNA neomer profiling, generated based on target sequencing data, was used to fit survival support vector machine models for each time point. Leave‐one‐out cross‐validation (LOOCV) was performed to evaluate the models' predictive performances. Results Our cfDNA neomer profiling assay showed excellent performance in detecting patients with a high risk for disease progression. At TP1, the high‐risk patients detected by our model showed an increased risk of 3.62 times (hazard ratio [HR] = 3.62, p = 0.0026) for disease progression, compared to 3.91 times (HR = 3.91, p = 0.0022) and 4.00 times (HR = 4.00, p = 0.019) for TP2 and TP3. These neomer profiling determined HRs were higher than the ctDNA mutation‐based results (HR = 2.08, p = 0.074; HR = 1.49, p = 0.61) at TP1 and TP3. At TP1, the predictive model reached 40% sensitivity at 92.9% specificity, outperforming the mutation‐based method (40% sensitivity at 78.6% specificity), while the combination results reached a higher sensitivity (60%). Finally, the longitudinal analysis showed that the combination of neomer and ctDNA mutation‐based results could predict disease progression with an excellent sensitivity of 88.9% at 80% specificity. Conclusion In conclusion, we developed a cfDNA neomer profiling assay for predicting disease progression in inoperable NSCLC patients. This assay showed increased predicting power during and post‐treatment compared to the ctDNA mutation‐based method, thus illustrating a great clinical potential to guide treatment decisions in inoperable NSCLC patients. Trial Registration ClinicalTrials.gov: NCT04014465

Lately, as a subset of human-centric studies, vision-oriented human action recognition has emerged as a pivotal research area, given its broad applicability in fields like healthcare, video surveillance, autonomous driving, sports, and education. This brief applies Lie algebra and standard bone length data to represent human skeleton data. A multi-layer long short-term memory (LSTM) recurrent neural network and convolutional neural network (CNN) are applied for human motion recognition. Finally, the trained network weights are converted into the crossbar-based memristor circuit, which can accelerate the network inference, reduce energy consumption, and obtain an excellent computing performance.

Reliable prediction of traffic accidents is crucial for the identification of potential hazards in advance, formulation of effective preventative measures, and reduction of accident incidence. Existing neural network-based models generally suffer from a limited field of perception and poor long-term dependency capturing abilities, which severely restrict their performance. To address the inherent shortcomings of current traffic prediction models, we propose the Traffic Transformer for multidimensional, multi-step traffic accident prediction. Initially, raw datasets chronicling sporadic traffic accidents are transformed into multivariate, regularly sampled sequences that are amenable to sequential modeling through a temporal discretization process. Subsequently, Traffic Transformer captures and learns the hidden relationships between any elements of the input sequence, constructing accurate prediction for multiple forthcoming intervals of traffic accidents. Our proposed Traffic Transformer employs the sophisticated multi-head attention mechanism in lieu of the widely used recurrent architecture. This significant shift enhances the model's ability to capture long-range dependencies within time series data. Moreover, it facilitates a more flexible and comprehensive learning of diverse hidden patterns within the sequences. It also offers the versatility of convenient extension and transference to other diverse time series forecasting tasks, demonstrating robust potential for further development in this field. Extensive comparative experiments conducted on a real-world dataset from Qatar demonstrate that our proposed Traffic Transformer model significantly outperforms existing mainstream time series forecasting models across all evaluation metrics and forecast horizons. Notably, its Mean Absolute Percentage Error reaches a minimal value of only 4.43%, which is substantially lower than the error rates observed in other models. This remarkable performance underscores the Traffic Transformer's state-of-the-art level of in predictive accuracy.

By integrating the successful case of the European Union emissions trading system, this study proposes a water emissions trading system, a novel method of reducing water pollution. Assuming that upstream governments allocate initial quotas to upstream businesses as the compensation standard, this approach defines the foundational principles of market trading mechanisms and establishes a robust watershed ecological compensation model to address challenges in water pollution prevention. To be specific, the government establishes a reasonable initial quota for upstream enterprises, which can be used to limit the emissions of upstream pollution. When enterprises exceed their allocated emissions quota, they face financial penalties. Conversely, these emissions rights can be transformed into profitable assets by participating in the trading market as a form of ecological compensation. Numerical simulations demonstrate that various pollutant emissions from upstream businesses will have various effects on the profits of other businesses. Businesses in the upstream region received reimbursement from the assigned emission rights through the market mechanism, demonstrating that ecological compensation for the watershed can be achieved through the market mechanism. This novel market trading system aims at controlling emissions management from the perspectives of individual enterprises and ultimately optimizing the aquatic environment. HIGHLIGHT The article establishes a water emissions trading mechanism. We establish this mechanism to control the amount of emission from each enterprise. Then we achieve the purpose of optimizing the water environment.;

Raptors can change the shape and area of their wings to an exceptional degree in a fast and efficient manner, surpassing other birds, insects, or bats. Some researchers have focused on the functional properties of muscle skeletons, mechanics, and flapping robot design. However, the wing motion of the birds of prey has not been measured quantitatively, and synthetic bionic wings with morphing abilities similar to raptors are far from reality. Therefore, in the current study, a 3D suspension system for holding bird carcasses was designed and fabricated to fasten the wings of Falco Peregrinus with a series of morphing postures. Subsequently, the wing skeleton of the falcon was scanned during extending motions using the computed tomography (CT) approach to obtain three consecutive poses. Subsequently, the skeleton was reconstructed to identify the contribution of the forelimb bones to the extending/folding motions. Inspired by these findings, we propose a simple mechanical model with four bones to form a wing-morphing mechanism using the proposed pose optimisation method. Finally, a bionic wing mechanism was implemented to imitate the motion of the falcon wing—divided into inner and outer wings with folding and twisting motions. The results show that the proposed four-bar mechanism can track bone motion paths with high fidelity.

Abstract Background Following China’s official designation as malaria-free country by WHO, the imported malaria has emerged as a significant determinant impacting the malaria reestablishment within China. The objective of this study is to explore the application prospects of machine learning algorithms in imported malaria risk assessment of China. Methods The data of imported malaria cases in China from 2011 to 2019 was provided by China CDC; historical epidemic data of malaria endemic country was obtained from World Malaria Report, and the other data used in this study are open access data. All the data processing and model construction based on R, and map visualization used ArcGIS software. Results A total of 27,088 malaria cases imported into China from 85 countries between 2011 and 2019. After data preprocessing and classification, clean dataset has 765 rows (85 * 9) and 11 cols. Six machine learning models was constructed based on the training set, and Random Forest model demonstrated the best performance in model evaluation. According to RF, the highest feature importance were the number of malaria deaths and Indigenous malaria cases. The RF model demonstrated high accuracy in forecasting risk for the year 2019, achieving commendable accuracy rate of 95.3%. This result aligns well with the observed outcomes, indicating the model’s reliability in predicting risk levels. Conclusions Machine learning algorithms have reliable application prospects in risk assessment of imported malaria in China. This study provides a new methodological reference for the risk assessment and control strategies adjusting of imported malaria in China.

Traditional surveying methods have various drawbacks in monitoring cable-stayed bridge deformations. Global Navigation Satellite System (GNSS) technology is increasingly recognized for its critical role in structural deformation monitoring, providing precise measurements for various structural applications. Accurate signal extraction is essential for reliable deformation monitoring, as it directly influences the quality of the detected structural changes. However, effective signal extraction from GNSS data remains a challenging task due to the presence of noise and complex signal components. This study integrates Complementary Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) and wavelet packet decomposition (WPD) to extract GNSS deformation monitoring signals for the ropeway pillar. The proposed approach effectively mitigates high-frequency noise interference and modal mixing in GNSS signals, thereby enhancing the accuracy and reliability of deformation measurements. Simulation experiments and real-world scenario applications with operational field data processing demonstrate the effectiveness of the proposed method. This research contributes to advancing GNSS-based deformation monitoring techniques, offering a robust solution for detecting and analyzing subtle structural changes in various engineering contexts.

Abstract Polar fluorinated arenes can promote organic free radical reactions, which have attracted scientists’ interest in recent years. However, it is still unknown how these solvents interact weakly with organic radical molecules to influence their reactivity. In this study, we investigated how organic free radicals aggregate in five polar fluorocarbon solvents, and demonstrated that different substituents can influence their aggregation behaviors. In these solvents, small organic radicals with simple substituents maintain a homogeneous solution; however, radicals with substituents that form intermolecular hydrogen bonds or with long‐chain aliphatic hydrocarbons tend to aggregate in them, whereas substituents of long‐chain aliphatic hydrocarbons tend to promote aggregation better. The critical aggregation concentrations of these aggregates are measured by concentration‐dependent UV–visible spectroscopy. Their topological morphologies are all spherical based on TEM. The compactness and rotational motivation speed of radical molecules within these aggregates are determined by EPR spectroscopy. The particle sizes of these aggregates are determined by analyzing their cyclic voltammograms. Most excitingly, electrochemical experiments reveal that the aggregation behaviors of free radical molecules with intermolecular hydrogen bonds can significantly increase their catalytic rate for electro‐oxidizing benzyl alcohol in such a solvent. The results of this study indicate that in polar fluorinated arenes organic radical molecules’ aggregation behaviors are related to their structures. This may provide guidelines for regulating organic radical reactivity in these solvents in the future.

B-cell Chronic Lymphocytic Leukemia (B-CLL) is a malignancy caused by the clonal expansion of mature B lymphocytes bearing a CD5+CD19+ (B1) phenotype. However, the origin of B-CLL remains controversial. We showed previously that STYK1/NOK transgenic mice develop a CLL-like disease. Using this model system in this study, we attempt to define the stage of CLL initiation. Here, we show that the phenotype of STYK1/NOK-induced B-CLL is heterogeneous. The expanded B1 lymphocyte pool was detected within peripheral lymphoid organs and was frequently associated with the expansions of memory B cells. Despite this immunophenotypic heterogeneity, suppression of B cell development at an early stage consistently occurred within the bone marrow (BM) of STYK1/NOK-tg mice. Overall, we suggest that enforced expression of STYK1/NOK in transgenic mice might significantly predispose BM hematopoietic stem cells (HSCs) towards the development of B-CLL.

The primary objective of this study was to examine the aromatic composition characteristics of six varieties of sugar-roasted 'Yanshan chestnuts' and to discern the distinctions in taste and odor between them. The volatile flavor constituents and pivotal aroma compounds of these sugar-roasted Chinese chestnuts were scrutinized using headspace solid-phase microextraction (HS-SPME) in conjunction with gas chromatography-mass spectrometry (GC-MS) and the odor activity value (OAV) method. Additionally, the volatile odor components and taste were assessed using electronic nose and tongue technologies. Results showed that, a total of 57 compounds were detected via GC-MS in the volatile components of these six types of sugar-roasted Castanea mollissima, which included 19 esters, 12 alcohols, 5 aldehydes, 5 ketones, 4 alkenes, 4 benzodiazepines, 2 amines, and 6 other components. Among these, 23 constituents with an OAV greater than 1 were identified as the key aroma components of the sugar-roasted chestnuts. The electronic nose evaluation illustrated that the predominant volatile odor components of the six sugar-roasted Castanea mollissima were alcohols, aldehydes, ketones, nitrogen oxides, organic sulfides, inorganic sulfides, and methyl groups. Furthermore, the electronic tongue analysis indicated that these six roasted chestnuts exhibited similar taste indices. The richness and umami sensor demonstrated the most substantial response to the different roasted chestnuts, while the sour and astringent tastes were the least prominent. The main taste indices of the roasted chestnuts were determined to be richness, umami, sweetness, saltiness, bitterness, and a lingering bitter aftertaste. The volatile flavor components and their quantities differed among the six types of sugar-roasted chestnuts, implying that the volatile flavor components vary among different sugar-roasted chestnut varieties, and the levels of the same compound also differ between varieties. The use of principal component analysis (PCA), radar chromatogram analysis, and GC-MS technology combined with electronic nose/tongue technologies proved to be an effective means to distinguish the differences in flavor among different varieties of sugar-roasted Chinese chestnuts and identify the key aroma components. This research provides a theoretical foundation for future flavor research on different sugar-roasted Chinese chestnut varieties.

This paper presents a novel design method for multifunctional filtering diplexers integrated with single-pole double-throw switches having three operating modes: Modes 1–3. Modes 1 and 2 involve the operation of switchable filters with different frequencies, which are suitable for time-division duplexing (TDD) systems. Mode 3 involves the operation of switchable diplexers, which are suitable for TDD and frequency-division duplexing (FDD) systems. The proposed design method is based on distributed coupling technology and can thus offer a high degree of design flexibility, particularly in terms of controlling the filter order, bandwidth, and number of channels. To demonstrate the feasibility and design flexibility of the proposed method, it was used to design and fabricate second- and fourth-order multifunctional diplexers; the designed diplexers were then assessed through electromagnetic simulations and experimental measurements. The simulation results were in good agreement with the experimental results, thereby validating the feasibility and design flexibility of the proposed method. The results indicated that the second- and fourth-order multifunctional diplexers occupied small circuit areas (approximately $0.098 {\lambda }_{g}^{2}$ and $0.198 {\lambda }_{g}^{2}$ , respectively). In addition to their multifunctional characteristics and high design flexibility, the multifunctional diplexers exhibited satisfactory performance, including an in-band insertion loss of < 2.5 dB in the ON state, an in-band attenuation of >42 dB in the OFF state, and a port-to-port isolation of >48 dB.

Crowd behavior recognition plays a critical role in various domains, including public safety, event management, and urban planning. Understanding crowd dynamics and detecting behaviors based on violence levels are crucial for preventing incidents and maintaining order in crowded environments. However, traditional surveillance methods fall short of providing comprehensive and real-time insights into complex crowd behavior patterns and fail to distinguish different violence levels within crowds that affect proactive decision-making. Moreover, most of the current systems do not provide reliable secure data transmission and are not viable in protecting the privacy of individuals. This paper designs an end-to-end secure and smart surveillance system, namely PublicVision, that transmits CCTV data securely to a remote central hub where a deep learning (DL) model based on Swin Transformer is utilized to identify and analyze crowd behaviors. A novel video dataset was created to train the DL model that identifies crowds based on size and violence level. The proposed system incorporates end-to-end security by creating a Dynamic Multipoint Virtual Private Network (DMVPN) and leverages the property of IP Security (IPSec) and Firewall for confidentiality and integrity during transmission and storage. Experiment analysis and real-time inference using DeepStream Software Development Kit (SDK) proved that the proposed system has significant implications for public safety, security, and crowd management in various contexts, including public spaces, transportation hubs, and large-scale events.

Objective To investigate the effects of micro RNA-222-3p (miR-222-3p) on the proliferation, apoptosis and invasion of oral squamous cell carcinoma (OSCC) CAL-27 cells.Methods qRT-PCR was used to detect the expression of miR-222-3p in CAL-27 cells and normal oral keratinocyte cell line (hNOK). CAL-27 cells were cultured and divided into control group (NC group), inhibitor NC group (transfected negative control plasmid ) and miR-222-3p inhibitor group (transfected into miR-222-3p inhibitor). MTT, flow cytometry and Trasnwell method were used to detect the changes of cell proliferation, apoptosis and invasion ability, respectively, and Western Blot was used to detect the expression of BAX, Bcl-2, MMP-2, N-cadherin and E-cadherin.Results The expression of miR-222-3p in CAL-27 cells was significantly higher than that of hNOK cells (P

BackgroundKnee osteoarthritis (KOA) is one of most prevalent and fastest-growing causes of pain, impaired mobility, and poor quality of life in the rapidly aging population worldwide. There is a lack of high-quality evidence on the efficacy of traditional Chinese medicine (TCM), particularly acupuncture, and a lack of KOA practice guidelines that are tailored to unique population demographics and tropical climates. ObjectiveOur HARMOKnee (Heat and Acupuncture to Manage Osteoarthritis of the Knee) trial aims to address these gaps by evaluating the short- and medium-term clinical and cost-effectiveness of acupuncture with heat therapy in addition to standard care, compared to standard care alone. Through a robust process and economic evaluation, we aim to inform evidence-based practice for patients with KOA to facilitate the large-scale implementation of a comprehensive and holistic model of care that harmonizes elements of Western medicine and TCM. We hypothesize that acupuncture with heat therapy as an adjunct to standard care is clinically more effective than standard care alone. MethodsA multicenter, pragmatic, parallel-arm, single-blinded, effectiveness-implementation hybrid randomized controlled trial will be conducted. We intend to recruit 100 patients with KOA randomized to either the control arm (standard care only) or intervention arm (acupuncture with heat therapy, in addition to standard care). The inclusion criteria are being a community ambulator and having primary KOA, excluding patients with secondary arthritis or previous knee replacements. The primary outcome measure is the Knee Osteoarthritis Outcome Score at 6 weeks. Secondary outcome measures include psychological, physical, quality of life, satisfaction, and global outcome measures at 6, 12, and 26 weeks. A mixed method approach through an embedded process evaluation will facilitate large-scale implementation. An economic evaluation will be performed to assess financial sustainability. ResultsPatient enrollment has been ongoing since August 2022. The recruitment process is anticipated to conclude by July 2024, and the findings will be analyzed and publicized as they are obtained. As of November 6, 2023, our patient enrollment stands at 65 individuals. ConclusionsThe findings of our HARMOKnee study will contribute substantial evidence to the current body of literature regarding the effectiveness of acupuncture treatment for KOA. Additionally, we aim to facilitate the creation of standardized national guidelines for evidence-based practice that are specifically tailored to our unique population demographics. Furthermore, we seek to promote the adoption and integration of acupuncture and heat therapy into existing treatment models. Trial RegistrationClinicalTrials.gov NCT05507619; https://clinicaltrials.gov/study/NCT05507619 International Registered Report Identifier (IRRID)DERR1-10.2196/54352

Abstract Background Complications and diagnostic efficiency for liver biopsy are main concerns for clinicians. This study aimed to assess the safety and efficacy of transjugular liver biopsy (TJLB) compared with percutaneous liver biopsy (PLB) when patients had equal level of liver function and number of passes, using propensity score matching (PSM). Methods The clinical and pathological data of patients who received TJLB or PLB between January 2012 and October 2022 were collected. Matching factors included age, gender, cirrhosis, portal hypertension, liver function, creatinine, number of passes, hemodialysis, history of anti-coagulation and anti-platelet, and comorbidities. Coagulation indexes were not considered as matching factors due to different indications of the two techniques. Results 2711 PLBs and 30 TJLBs were evaluated. By PSM, 75 patients (50 PLBs, 25 TJLBs) were matched. The complication rates for TJLB and PLB were 4.0% (1/25) and 10.0% (5/50) (P > 0.05). Two PLBs had hepatic hemorrhage, one of which required only close monitoring (Grade 1) and the other needed hemostasis and rehydration therapy (Grade 2). The other 3 cases presented with mild abdominal pain (Grade 1). And only one TJLB presented with mild pain. The median number of complete portal tracts were 6.0 and 10.0 for TJLBs and PLBs (P 0.05). Conclusion TJLB is an effective invasive diagnostic procedure that expands indications for liver biopsy with reliable diagnostic quality.

Abstract Purpose Fat infiltration (FI) of the deep neck extensor muscles has been shown to be associated with poor outcomes in cervical injury, mechanical neck pain, and axial symptoms after cervical spine surgery. However, information is scarce on the severity of FI in cervical extensors associated with different clinical syndromes in patients with cervical spondylosis. Objective To investigate the relationship between the severity of FI in the cervical multifidus musculature and its clinical correlates in the syndromes and sagittal alignment of patients with cervical spondylosis. Methods This study was conducted as a retrospective study of twenty-eight healthy volunteers (HV) together with sixty-six patients who underwent cervical radiculopathy (CR), degenerative myelopathy (DM), and axial joint pain (AJP) from January 2020 to March 2022. MRI was used to measure the fat cross-sectional area (FCSA), functional muscle cross-sectional area (FMCSA), total muscle cross-sectional area (TMCSA), FI ratio of the cervical multifidus musculature at each cervical level from the C3 to C6 segments and the cervical lordosis angle in the included subjects. Results The difference in the FCSA and FI ratio in patient groups with cervical spondylosis was significantly greater than that of the HV group (P

Abstract Efficient and accurate semantic segmentation is crucial for autonomous driving scene parsing. Capturing detailed information and semantic information efficiently through two‐branch networks has been widely utilised in real‐time semantic segmentation. This study proposes a network named MRFNet based on two‐branch strategy to solve the problem of accuracy and speed of segmentation in urban scenes. Many real‐time networks do not comprehensively consider contextual information from sub‐regions in different directions and at different scales. To handle this problem, a Multi‐directional Feature Refinement Module (MFRM) which has three sub‐paths to capture information at different scales and directions is proposed. And MFRM reduces computation by using strip pooling and dilated convolution operations. In particular, the authors propose a Feature Cross‐guide Aggregation Module to aggregate detailed information and contextual information through the mutual guidance of detailed information and semantic information. This module guides the extraction of feature maps in a more precise direction. Experiments on Cityscapes and CamVid datasets demonstrate the effectiveness of our method by achieving a balance between accuracy and inference speed. Specially, on single 1080Ti GPU, our method yields 78.9% mean intersection over union (mIoU) and 77.4% mIoU at speed of 144.5 frames per second (FPS) and 120.8 FPS on Cityscapes and CamVid datasets respectively.

Abstract Background Dendritic Cell Cytokine-induced killer cell (DC-CIK) coculture treatment in cancer immunotherapy has been shown to be effective. However, the cost of DC- CIK therapy is prohibitive for many patients, and the lack of standard manufacturing processes and treatment strategies are major limitations. Our study used tumor lysate as a tumor-associated antigen source and DCs and CIK cells in coculture. We developed an efficient method to obtain autologous DCs- and CIK cells from peripheral blood. We used flow cytometry to assess DC activation and the cytometric bead array assay to quantify cytokines secreted by CIK cells. Results We evaluated the antitumor activity of DC- CIK coculture in vitro with the K562 cell line. We demonstrated that a manufacturing process employing frozen immature DCs can yield the lowest loss with the highest economic benefits. DC-CIK coculture can effectively upgrade CIK cells’ immunological specificity to tumors in the presence of tumor-associated antigens. Conclusion In vitro experiments revealed that when the DC- CIK cell ratio was 1: 20 in the coculture, CIK cells secreted the highest number of cytokines on the 14th day and the antitumor immune effect showed the highest potency. CIK cells’ cytotoxicity to K562 cells was highest when the CIK: K562 cell ratio was 25: 1. We developed an efficient manufacturing process for DC- CIK coculture, while also establishing the optimal DC- CIK cell ratio for immunological activity and the best cytotoxic CIK: K562 cell ratio.

Hepatitis A virus (HAV), a member of the genus Hepatovirus (Picornaviridae HepV), remains a significant viral pathogen, frequently causing enterically transmitted hepatitis worldwide. In this study, we conducted an epidemiological survey of HepVs carried by small terrestrial mammals in the wild in Yunnan Province, China. Utilizing HepV-specific broad-spectrum RT-PCR, next-generation sequencing (NGS), and QNome nanopore sequencing (QNS) techniques, we identified and characterized two novel HepVs provisionally named EpMa-HAV and EpLe-HAV, discovered in the long-tailed mountain shrew (Episoriculus macrurus) and long-tailed brown-toothed shrew (Episoriculus leucops), respectively. Our sequence and phylogenetic analyses of EpMa-HAV and EpLe-HAV indicated that they belong to the species Hepatovirus I (HepV-I) clade II, also known as the Chinese shrew HepV clade. Notably, the codon usage bias pattern of novel shrew HepVs is consistent with that of previously identified Chinese shrew HepV. Furthermore, our structural analysis demonstrated that shrew HepVs differ from other mammalian HepVs in RNA secondary structure and exhibit variances in key protein sites. Overall, the discovery of two novel HepVs in shrews expands the host range of HepV and underscores the existence of genetically diverse animal homologs of human HAV within the genus HepV.

Objective: We examined the relationships between infants’ growth trajectories and prenatal exposure to air pollution, which is still under-investigated. Methods: A birth cohort study was constructed using medical records of pregnant women and infants born between 2015 and 2019 in Foshan, China. Using satellite-based spatial-temporal models, prenatal exposure to air pollutants including particulate matter with an aerodynamic dimension of < 2.5 µm (PM2.5), sulfur dioxide (SO2), nitrogen dioxide (NO2), and ozone (O3) was assessed at each woman's residence. Latent class growth modeling was used to identify trajectories of physical (body length and weight) growth and neurodevelopment, which were repeatedly measured within 1 year after birth. Logistic regression models were used to investigate the associations between prenatal exposure to air pollution and the risks of growth disorders, adjusting for an array of potential confounders. Results: We identified two growth trajectories for body length [normal: 3829 (93%); retardation: 288 (7%)], three for weight [normal: 2475 (59.6%); retardation: 390 (9.4%); overgrowth: 1287 (31%)], and two for neurodevelopment [normal: 956 (66.1%); retardation: 491 (33.9%)]. For exposure over whole pregnancy, SO2 was associated with an increased risk of body length retardation (OR for per 1 µg/m3 increment: 1.09, 95%CI: 1.01–1.17); PM2.5 (OR: 1.05, 95%CI: 1.03–1.07), SO2 (OR: 1.15, 95%CI: 1.08–1.22), and NO2 (OR: 1.05, 95%CI: 1.03–1.07) were positively associated with neurodevelopmental retardation. Such associations appeared stronger for exposures over the first and second trimesters. No significant associations were detected for weight growth. Conclusions: Maternal exposure to air pollution during pregnancy was associated with higher risks of impairments in both physical growth, particularly body length, and neurodevelopment.

Corals and their associated microbiota form a “holobiont,” which includes symbiotic algae and other associated microbiota dominated by bacteria. The composition of holobiont is influenced by various environmental factors, such as increasing sea water temperatures. Previous studies of the effects of temperature changes on coral physiology and associated bacterial communities have been conducted based on stable water temperatures set by mean temperatures, or by slowly increasing/decreasing temperatures. However, the daily temperature fluctuations that corals experience in nature are not stable. The current understanding of the effects of large daily temperature fluctuations on coral and associated bacterial community dynamics is limited. Hence, we conducted a four-week tank experiment using different large daily temperature fluctuations (±5 °C and ±7 °C) accompanied by continuous warming conditions (26 °C to 29 °C) to investigate the effects on two common reef-building corals, Stylophora pistillata and Pocillopora acuta. During the experiment, the activity of coral host catalase and superoxide dismutase were measured, the photosynthetic ability of symbiotic algae was recorded, and the variation in bacterial communities was analyzed using the V6-V8 region of 16S rDNA. According to the results, different parts of the holobionts of two coral species exhibited varying response rates to the continuous warming conditions and diurnal temperature fluctuations. Additionally, it was found that diurnal temperature fluctuations may mitigate the heat stress on the host and reduce the changes in bacterial response to warming. Therefore, it is suggested that the holobionts of different coral species may adopt different adaptation and survival strategies in response to diurnal temperature fluctuations and warming. Finally, based on the response of these two coral species under the conditions of diurnal temperature fluctuations and continuous warming, Acinetobacter and Rhodobacteraceae were identified as potential indicator coral-associated bacteria. This is the first study to investigate the tripartite dynamic response of coral, symbiotic algae and bacteria to daily temperature fluctuations.

The objective of this study was to evaluate the feasibility, safety, and effectiveness of intravenous stem cell delivery utilizing ultrasound-targeted microbubble destruction (UTMD) in a rat model of middle cerebral artery occlusion (MCAO), while investigating the underlying mechanisms. Acute cerebral infarction (ACI) was induced surgically in adult rats to create the MCAO rat model. Intravenous injection of SonoVue microbubbles and bone marrow–derived mesenchymal stem cells (BMSC) was performed concurrently, with or without ultrasound targeting the stroke. The animals were divided into four groups: sham-operated group, ACI-MCAO rats treated with phosphate-buffered saline (ACI+PBS), rats receiving intravenous delivery of BMSC expressing green fluorescent protein (GFP-BMSC; ACI+BMSC), and rats receiving intravenous GFP-BMSC with simultaneous UTMD exposure (ACI+BMSC+UTMD). The efficacy of the treatments was assessed by evaluating the animals’ neurological function using the Longa score and examining histopathological changes such as cerebral infarct volume, cerebral edema, and cell apoptosis. A rat cytokine array was utilized to identify the potential cytokines that may be responsible for the therapeutic effect of UTMD-mediated BMSC treatment. Optimal UTMD parameters resulted in an increase in blood–brain barrier (BBB) permeability after 30 min, which returned to baseline 72 h later without causing any residual injury. UTMD application significantly increased the homing of intravenously delivered BMSC, resulting in a 2.2-fold increase in GFP-BMSC cell count on day 3 and a 2.6-fold increase on day 7 compared with intravenous delivery alone. This effect persisted for up to 6 weeks after injection. Intravenous BMSC delivery significantly reduced the volume of cerebral infarct and decreased cerebral edema, leading to a lower Longa score. Furthermore, this effect was further enhanced by UTMD. Acute cerebral infarction induced by MCAO led to elevated matrix metalloproteinase 8 (MMP8) levels in the cerebrospinal fluid, which were significantly reduced following UTMD-mediated BMSC treatment. U ltrasound-targeted microbubble destruction facilitates the migration and homing of BMSC into the brain, possibly by transiently increasing blood–brain barrier (BBB) permeability, thereby improving therapeutic outcomes in an ACI rat model. The observed effect may be partly attributed to modulation of MMP8 levels. Advances in knowledge: UTMD-mediated intravenously delivered BMSC transplantation led to a significant increase in cell homing and reduction of MMP8 levels, resulting in increased therapeutic effect in an acute ischemic cerebral infarction model.

The aim of this study was to examine whether motivation, support, basic-needs satisfaction, and social skills in physical education lessons differed among Chinese secondary students from rural areas depending on their sociodemographic profiles. Two hundred and seven students enrolled in a camp organized by a non-profit organization in Chengdu province (15.8 ± 0.8 years, 74% female and 26% male) completed validated Chinese versions of the pertinent questionnaires. Appropriate social skills were perceived higher by women that by men (z = 2.2; p = 0.014; r = 0.16). Inappropriate social skills (z = 2.9; p = 0.021; r = 0.22) were perceived higher among those students with lower annual home income (50,000 yuan or less). Perceived autonomy support (z = 2.9; p = 0.002; r = 0.20), basic-needs satisfaction (z = 2.9; p = 0.002; r = 0.20), and physical-education motivation (z = 4.2; p

Abstract Unsupervised image translation (UIT) studies the mapping between two image domains. Since such mappings are under-constrained, existing research has pursued various desirable properties such as distributional matching or two-way consistency. In this paper, we re-examine UIT from a new perspective: distributional semantics consistency, based on the observation that data variations contain semantics, e.g., shoes varying in colors. Further, the semantics can be multi-dimensional, e.g., shoes also varying in style, functionality, etc. Given two image domains, matching these semantic dimensions during UIT will produce mappings with explicable correspondences, which has not been investigated previously. We propose distributional semantics mapping (DSM), the first UIT method which explicitly matches semantics between two domains. We show that distributional semantics has been rarely considered within and beyond UIT, even though it is a common problem in deep learning. We evaluate DSM on several benchmark datasets, demonstrating its general ability to capture distributional semantics. Extensive comparisons show that DSM not only produces explicable mappings, but also improves image quality in general.

Green tea was made from one bud with two leaves from the tea cultivar Longjing 43 by stir frying, roasting, steaming or sun drying. Stir bar sorptive extraction (SBSE) combined with gas chromatography-olfactometry-mass spectrometry (GC-O-MS) was applied to analyze the influence of different manufacturing processes on the key aroma-active compounds of green tea. The results showed that 31, 27, 25 and 30 key aroma-active compounds were respectively identified from stir-fried green tea, roasted green tea, steamed green tea and sun-dried green tea, which all had floral, fruity and green flavors. Totally, 13 key aroma-active compounds were common to these 4 types of green tea, including β-ionone, naphthalene, linalool, linalool oxide I, geraniol, 1-octene-3-ol, 2-heptanone, heptanal, hexanal, (Z)-3-hexenyl acetate, (E,E)-2,4-decadienal, α-ionone, and phenylethyl alcohol. It was found that β-ocimene and (Z)-hex-3-enyl 2-methylbutyrate contributed greatly to the aroma characteristics of stir-fried green tea; 2-pentylfuran, phenylacetaldehyde and α-terpineol contributed greatly to the aroma characteristics of roasted green tea; and geranylacetone, γ-terpinene and α-citral contributed greatly to the aroma characteristics of sun-dried green tea. The results obtained from this study will help to understand the formation mechanism of green tea aroma quality and to develop directional processing and regulation technologies for green tea aroma quality.