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BackgroundAs smartphone has been widely used, understanding how depression correlates with social behavior on smartphones can be beneficial for early diagnosis of depression. An enormous amount of research relied on self-report questionnaires, which is not objective. Only recently the increased availability of rich data about human behavior in digital space has provided new perspectives for the investigation of individual differences. ObjectiveThe objective of this study was to explore depressed Chinese individuals’ social behavior in digital space through metadata collected via smartphones. MethodsA total of 120 participants were recruited to carry a smartphone with a metadata collection app (MobileSens). At the end of metadata collection, they were instructed to complete the Center for Epidemiological Studies-Depression Scale (CES-D). We then separated participants into nondepressed and depressed groups based on their scores on CES-D. From the metadata of smartphone usage, we extracted 44 features, including traditional social behaviors such as making calls and sending SMS text messages, and the usage of social apps (eg, WeChat and Sina Weibo, 2 popular social apps in China). The 2-way ANOVA (nondepressed vs depressed × male vs female) and multiple logistic regression analysis were conducted to investigate differences in social behaviors on smartphones among users. ResultsThe results found depressed users received less calls from contacts (all day: F1,116=3.995, P=.048, η2=0.033; afternoon: F1,116=5.278, P=.02, η2=0.044), and used social apps more frequently (all day: F1,116=6.801, P=.01, η2=0.055; evening: F1,116=6.902, P=.01, η2=0.056) than nondepressed ones. In the depressed group, females used Weibo more frequently than males (all day: F1,116=11.744, P=.001, η2=0.092; morning: F1,116=9.105, P=.003, η2=0.073; afternoon: F1,116=14.224, P

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Concrete structures frequently manifest diverse defects throughout their manufacturing and usage processes due to factors such as design, construction, environmental conditions and distress mechanisms. In this paper, a multilevel convolutional neural network (CNN) combined with array ultrasonic testing (AUT) is proposed for identifying the locations of hole defects in concrete structures. By refining the detection area layer by layer, AUT is used to collect ultrasonic signals containing hole defect information, and the original echo signal is input to CNN for the classification of hole locations. The advantage of the proposed method is that the corresponding defect location information can be obtained directly from the input ultrasonic signal without manual discrimination. It effectively addresses the issue of traditional methods being insufficiently accurate when dealing with complex structures or hidden defects. The analysis process is as follows. First, COMSOL-Multiphysics finite element software is utilized to simulate the AUT detection process and generate a large amount of ultrasonic echo data. Next, the extracted signal data are trained and learned using the proposed multilevel CNN approach to achieve progressive localization of internal structural defects. Afterwards, a comparative analysis is conducted between the proposed multilevel CNN method and traditional CNN approaches. The results show that the defect localization accuracy of the proposed multilevel CNN approach improved from 85.38% to 95.27% compared to traditional CNN methods. Furthermore, the computation time required for this process is reduced, indicating that the method not only achieves higher recognition precision but also operates with greater efficiency. Finally, a simple experimental verification is conducted; the results show that this method has strong robustness in recognizing noisy ultrasonic signals, provides effective solutions, and can be used as a reference for future defect detection. [ABSTRACT FROM AUTHOR]

Idiopathic short stature (ISS) is a common childhood condition with largely unknown underlying causes. Recent research highlights the role of circulating exosomes in the pathogenesis of various disorders, but their connection to ISS remains unexplored. In the experiments, human chondrocytes are cocultured with plasma exosomes from ISS patients, leading to impaired chondrocyte growth and bone formation. Elevated levels of a specific long non‐coding RNA (lncRNA), ISSRL, are identified as a distinguishing factor in ISS, boasting high specificity and sensitivity. Silencing ISSRL in ISS plasma exosomes reverses the inhibition of chondrocyte proliferation and bone formation. Conversely, overexpression of ISSRL in chondrocytes impedes their growth and bone formation, revealing its mechanism of action through the miR‐877‐3p/GZMB axis. Subsequently, exosomes (CT‐Exo‐siISSRL‐oeGH) with precise cartilage‐targeting abilities are engineered, loaded with customized siRNA for ISSRL and growth hormone. This innovative approach offers a therapeutic strategy to address ISS by rectifying abnormal non‐coding RNA expression in growth plate cartilage and delivering growth hormone with precision to promote bone growth. This research provides valuable insights into ISS diagnosis and treatment, highlighting the potential of engineered exosomes. [ABSTRACT FROM AUTHOR]

In the critical period of strengthening the construction of ecological civilization, the construction of forest cities has become an important measure to promote urban ecosystem restoration and achieve sustainable development. Based on the mechanism of forest city promoting green development, the construction of a national forest city is regarded as a "quasi-natural experiment". Using China's urban panel data from 2005 to 2019, the impact of national forest city construction on urban green total factor productivity was evaluated using Multistage asymptotic double difference. The results show that National Forest Cities with environmental regulation can significantly promote regional green total factor productivity, which is still valid after a series of Robustness tests. Mechanism analysis shows that forest city construction not only affects territorial spatial planning but also forms a linkage with green technology innovation, mutual promotion and mutual promotion to jointly promote the sustainable development goals. This paper argues that building a national forest city is an important measure to achieve China's sustainable development goals in the new era, but in the process of policy implementation, it is necessary to implement the national forest city selection system according to local conditions. [ABSTRACT FROM AUTHOR]

Objective: To .study the improving effect of Anemarrhenae Rhizoma-Phellodendri Chinensis Cortex herb pair(Zhi Bai) on cognitive impairment in D-galactose(D-gal) administered mice, and to explore the mechanism of Zhi Bai in improving cognitive impairment through the AMPK/mTOR signaling pathway. Methods: Seventy-five C57BL/6J mice were randomly divided into five groups: the control group, the model group (D-gal 125 mg/kg), the piracetam group (468 mg/kg), the Zhi Bai group (4.5 g/kg), and the mTOR inhibitor group (everolimus, RAD001, 3 mg/kg), with 15 mice in each group. The aging mouse model was established using D-gal, followed by 8 weeks of oral administration of Zhi Bai decoction. Cognitive functions in aging mice were assessed using the Morris water maze and novel object recognition tests. Hippocampal tissue pathology was observed using hematoxylin and eosin (H& E) staining; neuronal and synaptic pathological morphology in the hippocampal region was examined with Nissl and Golgi staining. Hippocampal tissues were collected to determine the levels of adenosine triphosphate (ATP) in the brain. The protein expression levels of ubiquitin-binding protein 62 (P62), Beclin-1 associated with myosin, light chain kinase BCL2 (Beclin-1), synaptophysin (Syn), postsynaptic density protein-95 (PSD-95), AMP-activated protein kinase (AMPK), and mTOR in the hippocampus were detected by Western blot. The gene expression levels of Syn, AMPK, and mTOR in the hippocampus were measured using quantitative real-time PCR (qRT-PCR). Results: Compared to the control group, the model group mice showed significant cognitive impairment in the Morris water maze and novel object recognition tests (P<0.01). In the model group, there was a reduction in cell numbers, loose cell arrangement, and irregular neuronal morphology, a significant decrease in Nissl bodies, and a decrease in dendritic branch and spine density in the hippocampal region. ATP levels, as well as P62, Syn, PSD-95, and mTOR protein expressions in the hippocampus of the model group, were significantly reduced (P<0.01), while Beclin-1 expression was significantly increased (P<0.01). The ratio of pAMPK to AMPK protein content and the expression of AMPK genes were significantly elevated (P<0.01), whereas Syn and mTOR gene expressions were significantly decreased (P<0.01). Compared to the model group, cognitive function was significantly improved in the piracetam and Zhi Bai groups, as evidenced by a significant reduction in the latency period in the Morris water maze test (P<0.01), increased platform crossing numbers and target quadrant dwell time (P<0.01), and a significant increase in the novel object recognition index (P< 0.01). Dendritic spine density in the hippocampal region was significantly increased (P<0.01), and neuronal damage was alleviated to some extent. ATP levels and P62, Syn, PSD-95, and mTOR protein expressions in the hippocampus were significantly increased (P<0.01, P<0.05), Beclin-1 protein expression was significantly reduced (P<0.01), and the ratio of pAMPK to AMPK protein content and AMPK gene expression were significantly decreased (P<0.01, P<0.05), with Syn and mTOR gene expressions significantly elevated (P<0.01). The results for the RAD001 inhibitor group were similar to the model group, but Zhi Bai treatment led to a recalibration of these indicators. Conclusion: Zhi Bai may inhibit excessive autophagy of neurons, enhance synaptic plasticity and improve D-gal-induced cognitive impairment in mice by activating the AMPK/mTOR signaling pathway. [ABSTRACT FROM AUTHOR]