Being close or being alone: How Social ostracism affects solitude preference.

Social ostracism refers to the phenomenon of being excluded from social interactions and not being accepted by society. While previous research has examined its impact on prosocial and antisocial behaviour, few studies have investigated how individuals respond to ostracism by seeking solitude. Therefore, our study aims to explore the association between social ostracism and solitude seeking as well as the potential psychological mechanisms involved. We conducted three studies involving 488 Chinese students (59% female) and found that (a) long-term ostracism experiences positively correlated with preference for solitude, (b) short-term ostracism did not immediately lead to solitude seeking but increased the desire to establish new connections with others and (c) hostile assessment and negative emotions played a chain mediation role in the relationship between social ostracism and solitude seeking. These findings provide new insights and empirical evidence for understanding the relationship between social ostracism and solitude-seeking.

A novel cholesterol metabolism-related ferroptosis pathway in hepatocellular carcinoma.

BACKGROUND: Emerging studies have reported the contribution of cholesterol to hepatocellular carcinoma (HCC) progression. However, the specific role and mechanism of cholesterol metabolism on spontaneous and progressive HCC development from the point of view of ferroptosis are still worth exploring. The present study aimed to reveal a novel mechanism of cholesterol metabolism-related ferroptosis in hepatocellular carcinoma cells. METHODS: Two microarray datasets (GSE25097, GSE22058) related to HCC were downloaded from Gene Expression Omnibus (GEO) datasets. Metabolomics analysis was performed by ultra performance liquid chromatography - tandem mass spectrometer (UPLC-MS/MS). The cholesterol-related proteins were downloaded from HMBD. Ferroptosis-related genes were extracted from FerrDb database. Data sets were separated into two groups. GSE25097 was used to identify ferroptosis-related genes, and GSE22058 was used to verify results. During these processes, chemical-protein interaction (CPI), protein-protein interaction (PPI), the Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were conducted. Multivariate logistic regression analysis was used to test the associated pathway. RESULTS: We identified 8 differentially expressed ferroptosis-related genes (HAMP, PTGS2, IL1B, ALOX15B, CDKN2A, RRM2, NQO1 and KIF20A) and 4 differentially expressed cholesterol-related genes (LCAT, CH25H, CEL and CYP7A1). Furthermore, based on the predicted results with STITCH, we identified indomethacin and IL1B as the essential node for cholesterol-mediated ferroptosis in hepatocellular carcinoma cell. Multivariate logistic regression analysis showed the activities of plasma IL1B in liver cancer patients enrolled have been significantly affected by the level of plasma cholesterol (P < 0.001) and the test result of IL1B is a predictor variable causing the changes of serum Fe levels (P < 0.001). CONCLUSIONS: Our findings shed new light on the association between cholesterol metabolism and ferroptosis in HCC, and suggest that IL1B is the necessary node for cholesterol to lead to ferroptosis process in HCC. Also, we identified the potential role of indomethacin in adjuvant therapy of HCC with complications of abnormal cholesterol metabolism.

Influence of Alcohol on Intracerebral Hemorrhage: From Oxidative Stress to Glial Cell Activation.

The intricate relationship between alcohol consumption and intracerebral hemorrhage (ICH) presents a nuanced field of study, especially concerning the dose-dependent impact on secondary brain injury (SBI). Recognizing the established risks associated with heavy drinking, this review delves deeper into the less understood territories of low to moderate alcohol consumption. By systematically analyzing recent studies, we uncover critical insights into how varying alcohol intake levels modulate ICH risk through mechanisms such as microglial activation, oxidative stress, and the protective potential of polyphenols. This analysis extends beyond the hypertensive effects of heavy alcohol use to explore the complex molecular pathophysiology involved in alcohol-related ICH. Our findings indicate that while heavy alcohol use unequivocally exacerbates ICH risk, moderate consumption and its associated polyphenols may offer neuroprotective effects against SBI, albeit within a finely balanced threshold. This review highlights the significant gaps in current understanding and underscores the urgent need for targeted research to elucidate these complex interactions. Through this comprehensive examination, we aim to inform more nuanced public health policies and intervention strategies, taking into account the diverse effects of alcohol consumption on ICH risk.

Strategies for utilizing covalent organic frameworks as host materials for the integration and delivery of bioactives.

Covalent organic frameworks (COFs), a new and developing class of porous framework materials, are considered a type of promising carrier for the integration and delivery of bioactives, which have diverse fascinating merits, such as a large specific surface area, designable and specific porosity, stable and orderly framework structure, and various active sites. However, owing to the significant differences among bioactives (including drugs, proteins, nucleic acid, and exosomes), such as size, structure, and physicochemical properties, the interaction between COFs and bioactives also varies. In this review, we firstly summarize three strategies for the construction of single or hybrid COF-based matrices for the delivery of cargos, including encapsulation, covalent binding, and coordination bonding. Besides, their smart response release behaviors are also categorized. Subsequently, the applications of cargo@COF biocomposites in biomedicine are comprehensively summarized, including tumor therapy, central nervous system (CNS) modulation, biomarker analysis, bioimaging, and anti-bacterial therapy. Finally, the challenges and opportunities in this field are briefly discussed.

Examining Transcriptomic Alterations in Rat Models of Intracerebral Hemorrhage and Severe Intracerebral Hemorrhage.

Intracerebral hemorrhage (ICH) is a life-threatening condition associated with significant morbidity and mortality. This study investigates transcriptomic alterations in rodent models of ICH and severe ICH to shed light on the genetic pathways involved in hemorrhagic brain injury. We performed principal component analysis, revealing distinct principal component segments of normal rats compared to ICH and severe ICH rats. We employed heatmaps and volcano plots to identify differentially expressed genes and utilized bar plots and KEGG pathway analysis to elucidate the molecular pathways involved. We identified a multitude of differentially expressed genes in both the ICH and severe ICH models. Our results revealed 5679 common genes among the normal, ICH, and severe ICH groups in the upregulated genes group, and 1196 common genes in the downregulated genes, respectively. A volcano plot comparing these groups further highlighted common genes, including PDPN, TIMP1, SERPINE1, TUBB6, and CD44. These findings underscore the complex interplay of genes involved in inflammation, oxidative stress, and neuronal damage. Furthermore, pathway enrichment analysis uncovered key signaling pathways, including the TNF signaling pathway, protein processing in the endoplasmic reticulum, MAPK signaling pathway, and Fc gamma R-mediated phagocytosis, implicated in the pathogenesis of ICH.

Cross-patch feature interactive net with edge refinement for retinal vessel segmentation.

Retinal vessel segmentation based on deep learning is an important auxiliary method for assisting clinical doctors in diagnosing retinal diseases. However, existing methods often produce mis-segmentation when dealing with low contrast images and thin blood vessels, which affects the continuity and integrity of the vessel skeleton. In addition, existing deep learning methods tend to lose a lot of detailed information during training, which affects the accuracy of segmentation. To address these issues, we propose a novel dual-decoder based Cross-patch Feature Interactive Net with Edge Refinement (CFI-Net) for end-to-end retinal vessel segmentation. In the encoder part, a joint refinement down-sampling method (JRDM) is proposed to compress feature information in the process of reducing image size, so as to reduce the loss of thin vessels and vessel edge information during the encoding process. In the decoder part, we adopt a dual-path model based on edge detection, and propose a Cross-patch Interactive Attention Mechanism (CIAM) in the main path to enhancing multi-scale spatial channel features and transferring cross-spatial information. Consequently, it improve the network's ability to segment complete and continuous vessel skeletons, reducing vessel segmentation fractures. Finally, the Adaptive Spatial Context Guide Method (ASCGM) is proposed to fuse the prediction results of the two decoder paths, which enhances segmentation details while removing part of the background noise. We evaluated our model on two retinal image datasets and one coronary angiography dataset, achieving outstanding performance in segmentation comprehensive assessment metrics such as AUC and CAL. The experimental results showed that the proposed CFI-Net has superior segmentation performance compared with other existing methods, especially for thin vessels and vessel edges. The code is available at https://github.com/kita0420/CFI-Net.

Understanding cellulose pyrolysis via ab initio deep learning potential field.

Comprehensive and dynamic studies of cellulose pyrolysis reaction mechanisms are crucial in designing experiments and processes with enhanced safety, efficiency, and sustainability. The details of the pyrolysis mechanism are not readily available from experiments but can be better described via molecular dynamics (MD) simulations. However, the large size of cellulose molecules challenges accurate ab initio MD simulations, while existing reactive force field parameters lack precision. In this work, precise ab initio deep learning potentials field (DPLF) are developed and applied in MD simulations to facilitate the study of cellulose pyrolysis mechanisms. The formation mechanism and production rate of both valuable and greenhouse products from cellulose at temperatures larger than 1073 K are comprehensively described. This study underscores the critical role of advanced simulation techniques, particularly DLPF, in achieving efficient and accurate understanding of cellulose pyrolysis mechanisms, thus promoting wider industrial applications.

Ultrasonic liquid exfoliation for producing graphene materials from rice stem: Investigating cellular components and functionalities.

This study investigates a prospective and straightforward method for producing graphene material derived from biomass, examining the influence of plant cell composition and functions. The experimental outcomes highlight ultrasound's crucial role in synthesizing graphene material sourced from biomass. Ultrasound, a pivotal element in the experiment, significantly affects graphene production from biomass by working synergistically with the liquid components in the solvent system. Notably, the ethanol content reduces the solution's surface tension, facilitating the effective dispersion of biochar and graphene oxide sheets throughout the process. Simultaneously, the water content maintains the solution's polarity, enhancing the cavitation effect induced by ultrasound. Biomass-derived graphene is exfoliated utilizing an ultrasonic bath system (134.4 W, 40 kHz, 0.5 W/cm2) from biochar. The as-synthesized graphene oxide exhibits a structure comprising a few layers while remaining intact, featuring abundant functional groups. Interestingly, the resulting product displays nanopores with an approximate diameter of 100 nm. These nanopores are attributed to preserving specific cell structures, particularly those with specialized cell wall structures or secondary metabolite deposits from biomass resources. The study's findings shed light on the impact of cellular structure on synthesizing graphene material sourced from biomass, emphasizing the potential application of ultrasound as a promising approach in graphene production.

Effectiveness of Chinese Herbal Medicine as a Complementary Treatment for Neutropenia Prevention and Immunity Modulation During Chemotherapy in Patients With Breast Cancer: Protocol for a Real-World Pragmatic Clinical Trial.

BACKGROUND: In recent years, advancements in cancer treatment have enabled cancer cell inhibition, leading to improved patient outcomes. However, the side effects of chemotherapy, especially leukopenia, impact patients' ability to tolerate their treatments and affect their quality of life. Traditional Chinese medicine is thought to provide complementary cancer treatment to improve the quality of life and prolong survival time among patients with cancer. OBJECTIVE: This study aims to evaluate the effectiveness of Chinese herbal medicine (CHM) as a complementary treatment for neutropenia prevention and immunity modulation during chemotherapy in patients with breast cancer. METHODS: We will conduct a real-world pragmatic clinical trial to evaluate the effectiveness of CHM as a supplementary therapy to prevent neutropenia in patients with breast cancer undergoing chemotherapy. Patients will be classified into CHM or non-CHM groups based on whether they received CHM during chemotherapy. Using generalized estimating equations or repeated measures ANOVA, we will assess differences in white blood cell counts, absolute neutrophil counts, immune cells, and programmed cell death protein 1 (PD-1) expression levels between the 2 groups. RESULTS: This study was approved by the research ethics committee of Hualien Tzu Chi Hospital (IRB 110-168-A). The enrollment process began in September 2021 and will stop in December 2024. A total of 140 patients will be recruited. Data cleaning and analysis are expected to finish in the middle of 2025. CONCLUSIONS: Traditional Chinese medicine is the most commonly used complementary medicine, and it has been reported to significantly alleviate chemotherapy-related side effects. This study's findings may contribute to developing effective interventions targeting chemotherapy-related neutropenia among patients with breast cancer in clinical practice. TRIAL REGISTRATION: International Traditional Medicine Clinical Trial Registry ITMCTR2023000054; https://tinyurl.com/yc353hes. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/55662.