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Young adults are a high-risk population for developing smartphone addiction (SA), which bring about social issues. One theoretically and empirically supported proximal risk factor of SA is preference for smartphone-based internet applications (PSIA). However, most previous studies ignore gender difference and symptomatic heterogeneity of SA. Besides, many previous data analyses contain non-addicts, and the results derived might not be applicable to smartphone addicts. To bridging the gap, we used a symptom-level network analysis to assess gender differences in the links between preferences for 8 smartphone-based internet applications and 4 SA symptoms among young adults with high-level phone addiction (619 women and 415 men). The results showed that: (1) The relationship between the preference for video and the "loss of control" symptom was more pronounced in female addicts compared to their male counterparts. (2) Shopping app had stronger bridge centrality in women's smartphone applications-SA network, which was positively linked with more SA symptoms. (3) Our research identified marginal gender differences in smartphone addicts' psychological networks, with female addicts showing stronger links between social media/eBook preferences and withdrawal symptoms, and male addicts displaying a stronger connection between gaming/eBook and other smartphone activities. The study provides a visualized network association and network metrics for understanding the relationship between PSIA and SA. We propose adopting a selective processing hypothesis and an evolutionary psychology perspective to aid in understanding these gender differences. [ABSTRACT FROM AUTHOR]

Polyoxometalate (POM)-based materials are ideal candidates for implementing molecular memories, and rational POM molecule design is key to higher resistive switching (RS) performance. In this work, in order to obtain a deep structure–property correlation of POM-based memristors, three Anderson-based hybrids, i.e. two-component hybrids (MV)3(MnMo6O18L2)2·4DMF (1) and (MV)2[Cu(DMF)2](MnMo6O18L1)2·6DMF (2), and the three-component one (MV)2(Cu2I3)(MnMo6O18L2)·4CH3CN (3) (L = 2-(hydroxymethyl)-2-(pyridine-4-yl)-1,3-propanediol) have been structurally determined. These hybrids together with the precursors (methyl viologen (MV2+), CuI, and (MnMo6O18L2)) were further fabricated as memristors with the structure of ITO/active layer/Ag. Interestingly, three precursors are RS silent or have bad RS performance, but the incorporation of MV2+ in 1 and 2 can trigger the RS performances, and the further decoration of iodocuprate in 3 can render enhanced RS behavior (ON/OFF ratio: 2.32 × 102) with high thermal-tolerance temperature (240 °C) and extremely long-term stability. The RS mechanism could be assigned to the valence change (VC) induced by oxygen vacancy migrations. The presence of air-stable (MnMo6O18L2)3−-MV2+ donor–acceptor couples can stabilize the oxygen vacancies, which not only trigger the RS behaviors in ITO/1/Ag and ITO/2/Ag, but also result in extremely long-term stability in ITO/3/Ag. Besides, the oxygen vacancies can also be stabilized by Cu2I3 with intense cuprophilic interactions, which corresponds to enhanced RS properties in ITO/3/Ag. This mechanism could be validated by the following structural characters in 3: the stronger POM-MV2+ interactions, the better planarity of MV2+, the very short Cu⋯Cu distances and the ABAB-type packing fashion. The structure–property correlation in this work can provide a new strategy for the development of highly efficient and reliable memristors. [ABSTRACT FROM AUTHOR]

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This study aims to improve the predictive ability of financial brand data. help investors and decision-makers better identify different financial brands' performance, and reduce unnecessary financial risks. The stock prices of various financial brands are undertaken as the experimental objects. The characteristics of financial data and the original model network structure are analyzed based on the Internet of Things (IoT). The long short-term memory (LSIM) neural and the particle swarm optimization algorithm (PSO algorithm) are adopted to optimize the model's parameters, The autoregressive integrated moving average model (ARIMA) algorithm is used to analyze the spatio-temporal data, and a data prediction model for the financial brand based on the ARIMA-PSO-LSTM algorithm is proposed. In addition, the validity and effectiveness of the proposed model are proved through the analysis and testing of specific example data. It is found that the model based on the IoT shows higher processing speed in contrast to the conventional method: the model proposed in this study shows smaller errors and improved accuracy in dam prediction than the PSO-LSTM model and the LSTM model; the model presents better fitting effects and better performance compared with the latest research model. The experimental results reveal that combining the three algorithms can integrate the advantages of various algorithms, and the three algorithms can complement each other, thereby improving the ability of financial data analysis. The model established in this study shows high accuracy and good adaptability in identifying financial brands and predicting financial data. [ABSTRACT FROM AUTHOR]

Constructing structural materials from sustainable raw materials is considered an efficient way to reduce the potential threat posed by plastics. Nevertheless, challenges remain regarding combining excellent mechanical and thermal properties, especially the balance of strength and toughness. Here, we report a 3D nanofiber network interfacial design strategy to strengthen and toughen all‐natural structural materials simultaneously. The introduced protonated chitosan at the interface between the surface oxidized 3D nanonetwork of bacterial cellulose forms the interfacial interlocking structure of nanonetworks, achieving a robust physical connection and providing enough physical contact sites for chemical crosslinking. The obtained sustainable structural material successfully integrates excellent mechanical and thermal properties on the nanoscale of cellulose nanofibers, such as light weight, high strength, and superior thermal expansion coefficient. The relationship between structural design and comprehensive mechanical property improvement is analyzed in detail, providing a universal perspective to design sustainable high‐performance structural materials from nanoscale building blocks. [ABSTRACT FROM AUTHOR]

Background: Lymphoepithelioma-like carcinoma of the liver is a rare primary malignancy of the liver. The identification of lymphoepithelioma-like cholangiocarcinoma is very limited as there are currently very few reports of such cases. Although previous studies have reported the lymphoepithelioma-like cholangiocarcinoma pathologic features, few studies have revealed the clinic features, imaging characteristics, and clinical course and outcomes. This study was analyzed from multiple aspects such as contrast-enhanced ultrasound, magnetic resonance imaging, and pathological characteristics, aiming to improve the comprehensive understanding of this rare subtype of disease. Case Presentation: A 43-year-old female with a history of hepatitis B for over 20 years presented with a lesion found in the right lobe of her liver. After discussion by a multidisciplinary team (MDT), malignant tumors cannot be excluded based on contrast-enhanced ultrasound and MRI. Thus, we decided to perform surgery for the patient. Postoperative pathology confirmed lymphoepithelioma-like intrahepatic cholangiocarcinoma. After 3 months of follow-up, the patient was still alive and no recurrence was observed. Conclusion: The purpose of this article is to describe a rare case of lymphoepithelioma-like intrahepatic cholangiocarcinoma and analyze its contrast-enhanced ultrasound and contrast-enhanced MRI features, which will be helpful for physicians in diagnosing this disease. From the perspective of CEUS, the wedge-shaped highly enhanced area around the lesion in the arterial phase appears to be inflammatory but looks malignant based on the extremely fast washout. The lesion showed a low signal on T1WI, a high signal on T2WI and DWI, and an abnormal perfusion shadow can be seen behind the lesion. In particular, this subtype of cholangiocarcinoma has a good prognosis, the clinician should improve the recognition of the disease to strive for early diagnosis and therapy. [ABSTRACT FROM AUTHOR]

Calcium (Ca2+)- and zinc Zn2+-dependent nucleases play pivotal roles in plant nuclear DNA degradation in programmed cell death (PCD). However, the mechanisms by which these two nucleases co-participate in PCD-associated nuclear DNA degradation remain unclear. Here, the spatiotemporal expression patterns of two nucleases (CrCAN and CrENDO1) were analyzed qualitatively and quantitatively during PCD in secretory cavity formation in Citrus reticulata 'Chachi' fruits. Results show that the middle and late initial cell stages and lumen-forming stages are key stages for nuclear degradation during the secretory cavity development. CAN and ENDO1 exhibited potent in vitro DNA degradation activity at pH 8.0 and pH 5.5, respectively. Quantitative real-time reverse-transcription polymerase chain reaction, in situ hybridization assays, the subcellular localization of Ca2+ and Zn2+, and immunocytochemical localization showed that CrCAN was activated at the middle and late initial cell stages, while CrENDO1 was activated at the late initial cell and lumen-forming stages. Furthermore, we used immunocytochemical double-labelling to simultaneously locate CrCAN and CrENDO1. The DNA degradation activity of the two nucleases was verified by simulating the change of intracellular pH in vitro. Our results also showed that CrCAN and CrENDO1 worked respectively and co-participated in nuclear DNA degradation during PCD of secretory cavity cells. In conclusion, we propose the model for the synergistic effect of Ca2+- and Zn2+-dependent nucleases (CrCAN and CrENDO1) in co-participating in nuclear DNA degradation during secretory cavity cell PCD in Citrus fruits. Our findings provide direct experimental evidence for exploring different ion-dependent nucleases involved in nuclear degradation during plant PCD. [ABSTRACT FROM AUTHOR]

This study investigates the effects of Physcion on esophageal cancer and its possible mechanisms of action. Potential Physcion targets were identified using databases. Transcriptomic data from 17 esophageal cancer and adjacent tissues were analyzed to find differentially expressed genes, intersecting with potential targets to select 16 key genes. Their expression and distribution were evaluated in patient sequencing data. Diagnostic potential was assessed through differential gene expression and ROC curves. Pathway enrichment analysis was performed using KEGG, and molecular docking simulations were conducted to assess Physcion's binding affinity to key genes. In vitro assays complemented these findings. A total of 161 drug targets were identified, narrowing down to 16 pivotal genes. Expression patterns were examined across cell populations, and enrichment analysis showed significant PI3K/AKT pathway involvement. Molecular docking indicated strong binding of Physcion to HSP90AA1 and MMP2. In vitro assays confirmed Physcion's dose- and time-dependent impact on esophageal cancer cells, with significant DAPI staining effects. Physcion shows promise as a therapeutic agent for esophageal cancer. The study supports its potential for clinical development and future research in esophageal cancer treatment., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Competing Interests: None declared.

Background: Inguinal hernia in adults is a common and frequent disease in surgery, prone to occur in the elderly or in those with a weak abdominal wall. Despite its prevalence, Molecular mechanisms underlying inguinal hernia formation are unclear., Objective: This study aims to identify potential gene markers for inguinal hernia and available drugs., Methods: Pubmed2Ensembl text mining was used to identify genes related to "inguinal hernia" keywords. The GeneCodis system was used to specify GO biological process terms and KEGG pathways defined in the Kyoto Encyclopedia of Genes and Genomes (KEGG). The STRING tool was used to construct protein-protein interaction networks, which were then visualized using Cytoscape.CytoHubba and Molecular Complex Detection were utilized to analyze the module (MCODE). A GO and KEGG analysis of gene modules was conducted using the DAVID platform database. Hub genes are those that are concentrated in prominent modules. The druggene interaction database was also used to identify potential drugs for inguinal hernia patients based on their interactions between the hub genes. Finally, a Mendelian randomization study was conducted based on genome-wide association studies to determine whether hub genes cause inguinal hernias., Results: The identification of 96 genes associated with inguinal hernia was carried out using text mining techniques. It was constructed using PPI networks with 80 nodes and 476 edges, and the sequence of the genes was performed using CytoHubba. MCODE analysis identified three gene modules. Three modules contain 37 genes clustered as hub candidate genes associated with inguinal hernia patients. The PI3K-Akt, MAPK, AGE-RAGE, and HIF-1 pathways were found to be enriched in signaling pathways. Sixteen of the 37 genes were found to be targetable by 30 existing drugs. The relationship between hub genes and inguinal hernia was examined using Mendelian randomization. The research revealed nine genes that may be connected with inguinal hernia, such as POMC, CD40LG, TFRC, VWF, LOX, IGF2, BRCA1, TNF, and HGF in the plasma. By inverse variance weighting, ALB was associated with an increased risk of inguinal hernia with an OR of 1.203 (OR [95%] = 1,04 [1.012 to 1.089], p = 0.008)., Conclusion: We identified potential hub genes for inguinal hernia, predicted potential drugs for inguinal hernia, and reverse-validated potential genes by Mendelian randomization. This may provide further insights into asymptomatic pre-diagnostic methods and contribute to studies to understand the molecular mechanisms of risk genes associated with inguinal hernia., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)

Calcium (Ca2+)- and zinc Zn2+-dependent nucleases play pivotal roles in plant nuclear DNA degradation in programmed cell death (PCD). However, the mechanisms by which these two nucleases co-participate in PCD-associated nuclear DNA degradation remain unclear. Here, the spatiotemporal expression patterns of two nucleases (CrCAN and CrENDO1) were analyzed qualitatively and quantitatively during PCD in secretory cavity formation in Citrus reticulata 'Chachi' fruits. Results show that the middle and late initial cell stages and lumen-forming stages are key stages for nuclear degradation during the secretory cavity development. CAN and ENDO1 exhibited potent in vitro DNA degradation activity at pH 8.0 and pH 5.5, respectively. Quantitative real-time reverse-transcription polymerase chain reaction, in situ hybridization assays, the subcellular localization of Ca2+ and Zn2+, and immunocytochemical localization showed that CrCAN was activated at the middle and late initial cell stages, while CrENDO1 was activated at the late initial cell and lumen-forming stages. Furthermore, we used immunocytochemical double-labelling to simultaneously locate CrCAN and CrENDO1. The DNA degradation activity of the two nucleases was verified by simulating the change of intracellular pH in vitro. Our results also showed that CrCAN and CrENDO1 worked respectively and co-participated in nuclear DNA degradation during PCD of secretory cavity cells. In conclusion, we propose the model for the synergistic effect of Ca2+- and Zn2+-dependent nucleases (CrCAN and CrENDO1) in co-participating in nuclear DNA degradation during secretory cavity cell PCD in Citrus fruits. Our findings provide direct experimental evidence for exploring different ion-dependent nucleases involved in nuclear degradation during plant PCD., (© The Author(s) 2023. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)