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Background: Due to its effective osteogenic ability, BMP9 is a promising candidate for bone regeneration medicine. Whereas, BMP9 can also induce adipogenesis simultaneously. LCN2 is a cytokine associated with osteogenesis and adipogenesis. Reducing the adipogenic potential may be a feasible measure to enhance the osteogenic capability of BMP9. Objective: The objective of the study was to explore the role of LCN2 in regulating the BMP9-initialized osteogenic and adipogenic differentiation in mouse embryonic fibroblasts (MEFs), and clarify the possible underlying mechanism. Methods: Histochemical stain, western blot, real-time PCR, laser confocal, immunoprecipitation, cranial defect repair, and fetal limb culture assays were used to evaluate the effects of LCN2 on BMP9-induced osteogenic and adipogenic differentiation, as well as Wnt/β-catenin signaling. Results: LCN2 was down-regulated by BMP9. The BMP9-induced osteogenic markers were inhibited by LCN2 overexpression, but the adipogenic markers were increased; LCN2 knockdown exhibited opposite effects. Similar results were found in bone defect repair and fetal limb culture tests. The level of β-catenin nucleus translocation was found to be reduced by LCN2 overexpression, but increased by LCN2 knockdown. The inhibitory effect of LCN2 overexpression on the osteogenic capability of BMP9 was reversed by β-catenin overexpression; whereas, the effect of LCN2 knockdown on promoting BMP9 osteogenic potential was almost eliminated by β-catenin knockdown. LCN2 could bind with LRP6 specifically, and the inhibitory effect of LCN2 on the osteogenic potential of BMP9 could not be enhanced by LRP6 knockdown. Conclusion: LCN2 inhibits the BMP9-induced osteogenic differentiation but promotes its adipogenic potential in MEFs, which may be partially mediated by reducing Wnt/β-catenin signaling via binding with LRP6.

To solve the problem of poor face recognition performance in unrestricted environments. A face recognition algorithm based on improved residual IR-ResNet-SE is designed. Firstly, the IR structure is added to the 34-layer residual network to reduce the variability of different features; Secondly, we add the channel attention module to increase the weight of important channel features; Finally, the Arcface loss function is used to improve the classification ability of the model. The LFW, AgeDB, and AR datasets reflect unrestricted factors such as pose, age, expression, occlusion, and illumination. The algorithm proposed in this paper is experimented on these three datasets. The experimental results show that the IR-ResNet-SE algorithm proposed in this paper can achieve 99.74% accuracy in the dataset LFW. And it has excellent robustness in face recognition under unrestricted conditions. &nbsp

Background Hypertension affects 31.1% of adults worldwide, with higher prevalence of great than 60% in elderly. Advanced hypertension stage was associated with the higher risk of mortality. However, little is known about the age-specific association of stage of hypertension at diagnosis on cardiovascular mortality or all-cause mortality. Therefore, we aim to explore this age-specific association among the hypertensive elderly through stratified and interaction analyses. Methods This cohort study included 125,978 elderly hypertensive patients aged 60+ years from Shanghai of China. Cox regression was used to estimate the independent and joint effect of hypertension stage and age at diagnosis on cardiovascular and all-cause mortality. Interactions were evaluated both additively and multiplicatively. Multiplicative interaction was examined by the Wald test of the interaction term. Additive interaction was assessed by relative excess risk due to interaction (RERI). All analyses were performed stratified by sex. Results 28,250 patients died during the follow-up up to 8.85 years, and 13,164 died of cardiovascular events. Older age and advanced hypertension stage were risk factors of cardiovascular mortality and all-cause mortality. Besides, smoking, rarely exercise, BMI Conclusions Diagnosed with stage 3 hypertension was associated with higher risks of cardiovascular mortality and all-cause mortality, which were stronger among patients with age at diagnosis of 60–69 years compared with those with age at diagnosis of 70–85 years. Therefore, for the younger part of the elderly, the Department of Health should pay more attention to treating patients with stage 3 hypertension.

Nutrient-depleted soil is a major constraint for crop production, particularly for fruits. Here, we investigated the different response of nitrogen (N), phosphorus (P), and potassium (K) deficiency on the growth and development of strawberry (Fragaria ×ananassa Duch.) in sand culture under greenhouse conditions. Compared with K, the lack of N or P is more unfavorable to strawberry growth and development. N deficiency affected shoot-root (S/R) ratio at different growth stages, and decreased the shoot biomass. P deficiency greatly increased the N content but decreased K content of the plants, which means P is of advantage to regulate the absorption and utilization of N and K nutrients in plants. Meanwhile, P has a profound influence on fruit quality, such as total soluble (TSS) sugar content. K deficiency is not conducive to fruit coloring and the formation of high-quality commercial fruits. The results contribute to a better understanding of the difference of N, P, or K deficiency on strawberry growth, nutrient absorption, and fruit quality during the whole growth period.

Under ideal illumination conditions, the existing face recognition algorithms can obtain better recognition results.However, under non-uniform illumination conditions, the performance of the face recognition algorithm will be greatly reduced. Moreover, the commonfacial image classification modelshavelowprecisionandspeed. To address these problems, this paper proposes a non-uniform illumination face recognition method based on the improved MobileNetV1, and constructs a lightweight feature extraction network with MobileNetV1 as the core. To reduce the influence of non-uniform illumination on the face image, we use the MSRCR algorithm to preprocess the face image. A lightweight I-MobileNet model is proposed. We introduce the attention module into the MobileNetV1 model, which enhances the feature extraction capability of the network and improves the recognition performance. At the same time, the model parameters are optimized with Arcface loss function to increase the distance between classes and reduce the distance within classes. Compared with the original MobileNetV1 model, our method shows a significant improvement in recognition accuracy. In comparison with other network models, experiments conducted on the Extended Yale B dataset with the I-MobileNet model demonstrate the effectiveness of the method. &nbsp

PurposeThis study aims to explore whether gratification matters in influencing consumers' attitudes towards purchase in the context of livestream shopping and the antecedents that lead to consumers' gratification perceptions.Design/methodology/approachFour technology affordances (i.e. modality affordance, agency affordance, interactivity affordance and navigability affordance) and two gratifications (information gratification and entertainment gratification) are identified, and the relationships among the technology affordances, gratifications and purchase intention are examined. The model is tested using structural equation modeling.FindingsThe result shows that both information and entertainment gratification are positively associated with consumer purchase intention. No significant results have been uncovered with the relationship between interactivity affordance and entertainment gratification, while the rest relationships of gratification and its antecedents are positively associated.Originality/valueThe findings of this study uncover the antecedents and consequences of gratification in the context of livestreaming from technology affordance perspective. The uncovered relationships among technology affordance, gratification, purchase intention as well as the moderation roles aroused by price consciousness contribute to the extant literature.

In the setting of federated optimization, where a global model is aggregated periodically, step asynchronism occurs when participants conduct model training by efficiently utilizing their computational resources. It is well acknowledged that step asynchronism leads to objective inconsistency under non-i.i.d. data, which degrades the model's accuracy. To address this issue, we propose a new algorithm FedaGrac, which calibrates the local direction to a predictive global orientation. Taking advantage of the estimated orientation, we guarantee that the aggregated model does not excessively deviate from the global optimum while fully utilizing the local updates of faster nodes. We theoretically prove that FedaGrac holds an improved order of convergence rate than the state-of-the-art approaches and eliminates the negative effect of step asynchronism. Empirical results show that our algorithm accelerates the training and enhances the final accuracy., Comment: Accepted by IEEE Transactions on Parallel and Distributed Systems

Background: Atherosclerosis is a chronic inflammatory disease, in which macrophages determine the progression of atherosclerotic plaques. However, no studies have investigated how METTL3 (methyltransferase like 3) in macrophages affects atherosclerotic plaque formation in vivo. Additionally, whether Braf mRNA is modified by METTL3-dependent N6-methyladenosine (m6A) methylation remains unknown. Methods: We analyzed single-cell sequencing data of atherosclerotic plaques in mice fed with a high fat diet for different periods. Mettl3 fl/fl Lyz 2 cre Apoe –/– mice and littermate control Mettl3 fl/fl Apoe –/– mice were generated and fed high fat diet for 14 weeks. In vitro, we stimulated peritoneal macrophages with ox-LDL (oxidized low-density lipoprotein) and tested the mRNA and protein expression levels of inflammatory factors and molecules regulating ERK (extracellular signal-regulated kinase) phosphorylation. To find METTL3 targets in macrophages, we performed m6A-methylated RNA immunoprecipitation sequencing and m6A-methylated RNA immunoprecipitation-qPCR. Further, point mutation experiments were used to explore m6A-methylated adenine. Using RNA immunoprecipitation assay, we explored m6A methylation-writing protein bound to Braf mRNA. Results: In vivo, METTL3 expression in macrophages increased with the progression of atherosclerosis. Myeloid cell–specific METTL3 deletion negatively regulated atherosclerosis progression and the inflammatory response. In vitro, METTL3 knockdown or knockout in macrophages attenuated ox-LDL-mediated ERK phosphorylation rather than JNK (c-Jun N-terminal kinase) and p38 phosphorylation and reduced the level of inflammatory factors by affecting BRAF protein expression. The negative regulation of inflammation response caused by METTL3 knockout was rescued by overexpression of BRAF. In mechanism, METTL3 targeted adenine (39725126 in chromosome 6) on the Braf mRNA. Then, YTHDF1 could bind to m6A-methylated Braf mRNA and promoted its translation. Conclusions: Myeloid cell–specific Mettl3 deficiency suppressed hyperlipidemia-induced atherosclerotic plaque formation and attenuated atherosclerotic inflammation. We identified Braf mRNA as a novel target of METTL3 in the activation of the ox-LDL-induced ERK pathway and inflammatory response in macrophages. METTL3 may represent a potential target for the treatment of atherosclerosis.

The Oral Proficiency Interview (OPI) is an effective tool for assessing language learners’ speaking ability. While it is commonly employed in institutional contexts, the OPI has been criticized for not granting due attention to the assistance that the tester offers to the learner. Dynamic Assessment (DA), rooted in Vygotsky’s theory of the development of human higher psychological functions, believes the use of different forms of mediation, when tailored to learners’ needs, enables learners to perform beyond their current level, thus providing insights into their emerging abilities. This study explores the use of DA within the OPI framework. Through a microgenetic analysis of the mediation-learner interactions observed in a series of mock OPI sessions conducted in Mandarin Chinese, we identified the mediation and reciprocity typological moves that are significant to learner development. The analysis showed DA’s potential for not only pinpointing areas of difficulty but also identifying the learner’s Zone of Proximal Development (ZPD) and supporting their microgenetic progress. The findings indicate that DA would add an important, yet long neglected, dimension to the OPI framework.