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"Research Findings:" Playfulness is an important personality tendency with an important role in the well-being, mental health, and various other aspects of an individual's life. Previous studies have shown that the development of children's playfulness is related to parents' playfulness. However, limited research has been conducted on how parental playfulness influences children's playfulness. The present study used a mixed-methods design to examine the impact of parents' playfulness on their children's playfulness and explore the mechanism of the impacting process. Questionnaires were administered to participants, who comprised 360 parents of preschool children, to test the relationship between parental and children's playfulness and explore the roles of parenting styles and parent-child relationships as the quantitative element of the study. The qualitative element comprised semi-structured interviews with 10 parents selected from the quantitative part. The results suggest that there was significant positive correlation between parental and children's playfulness and democratic parenting and intimate parent-child relationships had a chain mediating effect on this relationship. Further, parents' attitudes toward playfulness, constraints on children's play, and parental support for children in play were also the factors that influence the relationship between parental and children's playfulness. "Practice or Policy:" These findings provide approaches of interventions aimed at cultivating a higher level of playfulness, and simultaneously promoting the overall development of children.

Objective: To explore the diagnostic value of real-time shear wave elastography (SWE) in hepatic hemangioma (ANGI) and hepatocellular carcinoma (HCC). Methods: A total of 88 patients diagnosed with angiosarcoma (ANGI) or hepatocellular carcinoma (HCC) in our department from February 2019 to February 2020 were included in this study. These patients were assigned to two groups based on pathological diagnosis: the ANGI group (n = 42) and the HCC group (n = 46). All patients underwent SWE examination, and the clinical efficacy was analyzed by comparing the average value of Young's modulus of the two groups and plotting the receiver operator characteristic (ROC) curve. Results: There was no significant difference in lesion diameter between ANGI and HCC patients (P > 0.05). The ANGI group exhibited a significantly higher average Young's modulus for both the lesions and the adjacent liver tissues compared to the HCC group (P < 0.001); The area under the curve (AUC) of the average value of Young’s modulus of the lesion to ANGI and HCC was 0.875 (95% CI = 0.795-0.955). Conclusion: SWE demonstrates high diagnostic accuracy in distinguishing ANGI from HCC, providing valuable clinical evidence for differentiating between the two diseases.

Abstract Bone cancer pain (BCP) represents a prevalent symptom among cancer patients with bone metastases, yet its underlying mechanisms remain elusive. This study investigated the transcriptional regulation mechanism of Kv7(KCNQ)/M potassium channels in DRG neurons and its involvement in the development of BCP in rats. We show that HDAC2-mediated transcriptional repression of kcnq2/kcnq3 genes, which encode Kv7(KCNQ)/M potassium channels in dorsal root ganglion (DRG), contributes to the sensitization of DRG neurons and the pathogenesis of BCP in rats. Also, HDAC2 requires the formation of a corepressor complex with MeCP2 and Sin3A to execute transcriptional regulation of kcnq2/kcnq3 genes. Moreover, EREG is identified as an upstream signal molecule for HDAC2-mediated kcnq2/kcnq3 genes transcription repression. Activation of EREG/EGFR-ERK-Runx1 signaling, followed by the induction of HDAC2-mediated transcriptional repression of kcnq2/kcnq3 genes in DRG neurons, leads to neuronal hyperexcitability and pain hypersensitivity in tumor-bearing rats. Consequently, the activation of EREG/EGFR-ERK-Runx1 signaling, along with the subsequent transcriptional repression of kcnq2/kcnq3 genes by HDAC2 in DRG neurons, underlies the sensitization of DRG neurons and the pathogenesis of BCP in rats. These findings uncover a potentially targetable mechanism contributing to bone metastasis-associated pain in cancer patients.

Anilines and phenols are recognized as challenging organic pollutants in industrial wastewater. Herein, the coupled treatment of aniline and phenol in water was achieved through electrochemical oxidation-induced copolymerization. After the electrolysis (1,300 mA for 10 h) in the solution of aniline and phenol (200 mL, each at a concentration of 5 g/L), the organic compounds were efficiently precipitated from their mixed solution by copolymerization. These insoluble copolymers could be easily separated by filtration and collected as brown powders, and the average removal rate of aniline and phenol was calculated as 0.6 mol/h m2 in this coupled electrolysis. The chemical oxygen demand (COD) test of the filtrates showed that it reached up to 98% of the COD removal ratio. Moreover, mixed solutions containing multiple aniline and phenol derivatives were also applicable for this coupled treatment strategy, and they were efficiently removed together after electrolysis. HIGHLIGHTS Aniline and phenol with high concentrations (1–5 g/L) in water can be removed as insoluble copolymers by electrochemical-coupled treatment.; This protocol featuring electrochemical copolymerization avoids the complete oxidation of the organic pollutants to CO2, thus dramatically improving the removal efficiency and reducing energy consumption.;

Summary: Fate determination of neural stem cells (NSCs) is crucial for cortex development and is closely linked to neurodevelopmental disorders when gene expression networks are disrupted. The transcriptional corepressor chromodomain Y-like (CDYL) is widely expressed across diverse cell populations within the human embryonic cortex. However, its precise role in cortical development remains unclear. Here, we show that CDYL is critical for human cortical neurogenesis and that its deficiency leads to a substantial increase in gamma-aminobutyric acid (GABA)-ergic neurons in cortical organoids. Subsequently, neuronatin (NNAT) is identified as a significant target of CDYL, and its abnormal expression obviously influences the fate commitment of cortical NSCs. Cross-species comparisons of CDYL targets unravel a distinct developmental trajectory between human cortical organoids and the mouse cortex at an analogous stage. Collectively, our data provide insight into the evolutionary roles of CDYL in human cortex development, emphasizing its critical function in maintaining the fate of human cortical NSCs.

To study the graded alcohol precipitation components of fucoidan from Undaria pinnatifida and its hypoglycemic activity in vitro, this study used Undaria pinnatifida as raw material, extracted Undaria pinnatifida fucoidan gum through CaCl2 solution, and precipitated it step by step to obtain four sets of polysaccharide samples (UPP-45, UPP-55, UPP-65, and UPP-75). Determined their molecular weight, total sugar content, uronic acid content, protein content, sulfate content and monosaccharide composition and analyzed by ultraviolet spectrum (UV), Fourier transform infrared spectra(FT-IR) and scanning electron microscopy(SEM). The inhibition of polysaccharides on α-amylase and α-glucosidase was determined to explore their hypoglycemic activity in vitro. The results showed that the higher the concentration of alcohol precipitation, the higher the proportion of small molecular weight polysaccharide. The highest total sugar content of UPP-65 was 84.38%, and the protein of the crude polysaccharide and sulfate contents of UPP-45 were significantly different from those of other components (P

Abstract The circadian clock regulates animal physiological activities. How temperature reorganizes circadian-dependent physiological activities remains elusive. Here, using in-vivo two-photon imaging with the temperature control device, we investigated the response of the Drosophila central circadian circuit to temperature variation and identified that DN1as serves as the most sensitive temperature-sensing neurons. The circadian clock gate DN1a’s diurnal temperature response. Trans-synaptic tracing, connectome analysis, and functional imaging data reveal that DN1as bidirectionally targets two circadian neuronal subsets: activity-related E cells and sleep-promoting DN3s. Specifically, behavioral data demonstrate that the DN1a-E cell circuit modulates the evening locomotion peak in response to cold temperature, while the DN1a-DN3 circuit controls the warm temperature-induced nocturnal sleep reduction. Our findings systematically and comprehensively illustrate how the central circadian circuit dynamically integrates temperature and light signals to effectively coordinate wakefulness and sleep at different times of the day, shedding light on the conserved neural mechanisms underlying temperature-regulated circadian physiology in animals.

Traffic accident data-based portrait plays a vital role in accident cause investigation, relationship reasoning, prevention, and control. The traffic accident data tend to be multisourced with increasingly hidden and complicated accident relationships. The existing reported research focus more on traffic drivers' measurement of penalty, the relationship among drivers, cars, and dates, etc. How to use multisource data based on deep learning, especially based on the Chinese recent unstructured data and structured data to establish accident portrait for individual and groups of accident drivers, still lacks. Moreover, how to perform multisource accident data label extraction, identity, and relationship extraction are still challenging problems. This paper proposes a multisource accident datasets-driven deep learning-based traffic accident portrait method. Our multisource accident datasets-driven deep learning model is composed of the following three submodels: (1) the structured data accident model using our accident feature-driven bidirectional long short-term memory (Bi-LSTM) and accident feature-driven bidirectional conditional random field (Bi-CRF) model to extract labels, (2) the unstructured traffic accident data model using our accident feature-driven piecewise convolutional neural network (PCNN) model to identify the extracted labels, and (3) the semistructured traffic accident data processing model. Moreover, to solve the problem of how to construct hidden relationship among the multisource accident data, a multisource accident data visualization method based on traffic accident knowledge graph where the accident relational inference algorithm is to complete the hidden relationship between traffic accident data labels is used and then data are visualized using the traffic accident knowledge graph. This paper uses the NER dataset of the People's Daily and a manually labeled dataset to test the Bi-LSTM+Bi-CRF model, and it acquires the highest scores of 0.9562 and 0.9779 compared with several other models. This paper uses the DuIE dataset and a manually labeled dataset to test the PCNN model, and it acquires the highest scores of 0.9674 and 0.9108 compared with several other models. Experiments verified our model's merits than other models in regards to accident label extraction, accident identity identification, and accident relationship extraction., Author(s): Chun-Hao Wang [1,2]; Yue-Tian-Si Ji [3]; Li Ruan (corresponding author) [2,3]; Joshua Luhwago [3]; Yin-Xuan Saw [3]; Sokhey Kim [3]; Tao Ruan [4]; Li-Min Xiao [3]; Rui-Jue Zhou [3] [...]

Abstract Reconfigurable intelligent surfaces (RISs) have attracted a great deal of interest due to the potential contributions to the next‐generation wireless networks. This letter proposes an enhancement to the physical layer security (PLS) of a multi‐hop RIS‐assisted underwater optical wireless communication (UOWC) system. Owing to the complexity of the underwater environment, a security‐based adaptive RIS (SA‐RIS) clustering strategy, which aims to reflect optical signals among clusters to improve the performance of the overall system, is evaluated. By combining the underwater channel model, the closed‐form expressions of probability density function (PDF) and cumulative distribution function (CDF) are derived. Moreover, by increasing the numbers of RIS clusters, the performance metrics such as secrecy outage probability (SOP) and average secrecy capacity (ASC) are evaluated under different scenarios. The obtained results demonstrated that, in contrast to the case without preventing the eavesdropper, the proposed strategy in evasion scenarios could improve the SOP significantly. It can be concluded that the system secrecy performances are further improved by assigning different RIS clusters with proper channel quality.

Silicosis, caused by silica exposure, is the most widespread and deadliest occupational disease. However, effective treatments are lacking. Therefore, it is crucial to elucidate the mechanisms and targets involved in the development of silicosis. We investigated the basic processes of silicosis development and onset at different exposure durations (2 or 4 weeks) using various techniques such as histopathology, immunohistochemistry, Enzyme linked immunosorbent assay(ELISA),16 S rRNA, and untargeted metabolomics.These results indicate that exposure to silica leads to progressive damage to lung tissue with significant deterioration observed over time. Time-dependent cytokines such as the IL-4, IL-13, and IL-6 are detected in lung lavage fluid, the model group consistently exhibited elevated levels of these cytokines, indicating a persistent and worsening inflammatory response in the lungs. Meanwhile, HE and Masson results show that 4-week exposure to silica causes more obvious lung injury and pulmonary fibrosis. Besides, the model group consistently exhibited a distinct lung bacterial population, known as the Lachnospiraceae_NK4A136_group, regardless of exposure duration. However, with increasing exposure duration, specific temporal changes were observed in lung bacterial populations, including Haliangium, Allobaculum, and Sandaracinus (at 4 weeks; p < 0.05). Furthermore, our study revealed a strong correlation between the mechanism of silica-induced lung injury and three factors: oxidative stress, impaired lipid metabolism, and imbalanced amino acid metabolism. We observed a close correlation between cytokine levels, changes in lung microbiota, and metabolic disturbances during various exposure periods. These findings propose that a possible mechanism of silica-induced lung injury involves the interplay of cytokines, lung microbiota, and metabolites.

Abstract Background Sufentanil-induced cough is common during the induction of anesthesia. The objective of this study was to determine whether pretreatment with a small dose of esketamine is effective in treating sufentanil-induced cough. Methods 220 patients were screened, and 200 patients who had scheduled elective surgery and were between 18 and 70 years old were randomly divided into two groups. Before sufentanil was administered, esketamine group (group K) was injected with 0.15 mg/kg esketamine at 5 s, and control group (group C) was administered with the same volume. Within 1 min after sufentanil(0.4ug/kg) injection during induction, cough incidence and severity were evaluated. After sufentanil was injected, we recorded its hemodynamic changes and side effects. Results In the esketamine group (group K) and control group (group C), there was an incidence of cough of 5 and 34%, respectively. The esketamine group (group K) had a significantly lower incidence and severity of cough compared to the control group (group C) immediately after sufentanil injection (P 0.05). Conclusion In our study, we found that sufentanil-induced cough was significantly reduced by pretreatment with 0.15 mg/kg esketamine, but with no significant changes in the hemodynamic status. Trial registration Chinese Clinical Trial Registry (ChiCTR2200063821, registered date: 17/09/2022), http://www.chictr.org.cn

Abstract Nuclear factor Y (NF-Y) gene family is an important transcription factor composed of three subfamilies of NF-YA, NF-YB and NF-YC, which is involved in plant growth, development and stress response. In this study, 63 tobacco NF-Y genes (NtNF-Ys) were identified in Nicotiana tabacum L., including 17 NtNF-YAs, 30 NtNF-YBs and 16 NtNF-YCs. Phylogenetic analysis revealed ten pairs of orthologues from tomato and tobacco and 25 pairs of paralogues from tobacco. The gene structure of NtNF-YAs exhibited similarities, whereas the gene structure of NtNF-YBs and NtNF-YCs displayed significant differences. The NtNF-Ys of the same subfamily exhibited a consistent distribution of motifs and protein 3D structure. The protein interaction network revealed that NtNF-YC12 and NtNF-YC5 exhibited the highest connectivity. Many cis-acting elements related to light, stress and hormone response were found in the promoter of NtNF-Ys. Transcriptome analysis showed that more than half of the NtNF-Y genes were expressed in all tissues, and NtNF-YB9/B14/B15/B16/B17/B29 were specifically expressed in roots. A total of 15, 12, 5, and 6 NtNF-Y genes were found to respond to cold, drought, salt, and alkali stresses, respectively. The results of this study will lay a foundation for further study of NF-Y genes in tobacco and other Solanaceae plants.

Background: Metagenomic Next-Generation Sequencing (mNGS) is a rapid, non-culture-based, high-throughput technique for pathogen diagnosis. Despite its numerous advantages, only a few studies have investigated its use in patients undergoing allogeneic hematopoietic stem cell transplantation (allo-HSCT). Methods: We conducted a retrospective analysis of 404 mNGS tests performed on 264 patients after allo-HSCT. The tests were divided into three groups (Phase A, B, C) based on the time spent hospitalized post-transplantation, and we evaluated the analytical performance of mNGS in comparison with conventional microbiological tests (CMT), while also analyzing its clinical utility for clinical impacts. Results: Metagenomic sequencing demonstrated a significantly higher rate of positive microbiological findings as compared to CMT (334/404 (82.7 %) vs. 159/404 (39.4 %), respectively, P

The IEEE 802.11bf-based wireless fidelity (WiFi) indoor positioning system has gained significant attention recently. It is important to recognize that multi-user online positioning occurs in real wireless environments. This paper proposes an indoor positioning sensing strategy that includes an optimized preprocessing process and a new machine learning (ML) method called NKCK. The NKCK method can be broken down into three components: neighborhood component analysis (NCA) for dimensionality reduction, K-means clustering, and K-nearest neighbor (KNN) classification with cross-validation (CV). The KNN algorithm is particularly suitable for our dataset since it effectively classifies data based on proximity, relying on the spatial relationships between points. Experimental results indicate that the NKCK method outperforms traditional methods, achieving reductions in error rates of 82.4% compared to naive Bayes (NB), 85.0% compared to random forest (RF), 72.1% compared to support vector machine (SVM), 64.7% compared to multilayer perceptron (MLP), 50.0% compared to density-based spatial clustering of applications with noise (DBSCAN)-based methods, 42.0% compared to linear discriminant analysis (LDA)-based channel state information (CSI) amplitude fingerprinting, and 33.0% compared to principal component analysis (PCA)-based approaches. Due to the sensitivity of CSI, our multi-user online positioning system faces challenges in detecting dynamic human activities, such as human tracking, which requires further investigation in the future.

Summary: Intervertebral disc is a highly rhythmical tissue. As a key factor linking biorhythm and inflammatory response, the shielding effect of NR1D1 in the process of intervertebral disc degeneration remains unclear. Here, we first confirmed that NR1D1 in the nucleus pulposus tissue presents periodic rhythmic changes and decreases in expression with intervertebral disc degeneration. Second, when NR1D1 was activated by SR9009 in vitro, NLRP3 inflammasome assembly and IL-1β production were inhibited, while ECM synthesis was increased. Finally, the vivo experiments further confirmed that the activation of NR1D1 can delay the process of disc degeneration to a certain extent. Mechanistically, we demonstrate that NR1D1 can bind to IL-1β and NLRP3 promoters, and that the NR1D1/NLRP3/IL-1β pathway is involved in this process. Our results demonstrate that the activation of NR1D1 can effectively reduce IL-1β secretion, alleviate LPS-induced NPMSC pyroptosis, and protect ECM degeneration.