Search

Pain empathy, defined as the ability of one person to understand another person's pain, shows large individual variations. The anterior insula is the core region of the pain empathy network. However, the relationship between white matter (WM) properties of the fiber tracts connecting the anterior insula with other cortical regions and an individual's ability to modulate pain empathy remains largely unclear. In this study, we outline an automatic seed-based fiber streamline (sFS) analysis method and multivariate pattern analysis (MVPA) to predict the levels of pain empathy in healthy women and women with primary dysmenorrhoea (PDM). Using the sFS method, the anterior insula-based fiber tract network was divided into five fiber cluster groups. In healthy women, interindividual differences in pain empathy were predicted only by the WM properties of the five fiber cluster groups, suggesting that interindividual differences in pain empathy may rely on the connectivity of the anterior insula-based fiber tract network. In women with PDM, pain empathy could be predicted by a single cluster group. The mean WM properties along the anterior insular–rostroventral area of the inferior parietal lobule further mediated the effect of pain on empathy in patients with PDM. Our results suggest that chronic periodic pain may lead to maladaptive plastic changes, which could further impair empathy by making women with PDM feel more pain when they see other people experiencing pain. Our study also addresses an important gap in the analysis of the microstructural characteristics of seed-based fiber tract network.

Pain empathy is a complex form of psychological inference that enables us to understand how others feel in the context of pain. Since pain empathy may be grounded in our own pain experiences, it exhibits huge inter-individual variability. However, the neural mechanisms behind the individual differences in pain empathy and its association with pain perception are still poorly understood. In this study, we aimed to characterize brain mechanisms associated with individual differences in pain empathy in adult participants (n = 24). The 32-channel electroencephalography (EEG) was recorded at rest and during a pain empathy task, and participants viewed static visual stimuli of the limbs submitted to painful and nonpainful stimulation to solicit empathy. The pain sensitivity of each participant was measured using a series of direct current stimulations. In our results, the N2 of Fz and the LPP of P3 and P4 were affected by painful pictures. We found that both delta and alpha bands in the frontal and parietal cortex were involved in the regulation of pain empathy. For the delta band, a close relationship was found between average power, either in the resting or task state, and individual differences in pain empathy. It suggested that the spectral power in Fz's delta band may reflect subjective pain empathy across individuals. For the alpha band, the functional connectivity between Fz and P3 under painful picture stimulation was correlated to individuals' pain sensitivity. It indicated that the alpha band may reflect individual differences in pain sensitivity and be involved in pain empathy processing. Our results suggested the distinct role of the delta and alpha bands of EEG signals in pain empathy processing and may deepen our understanding of the neural mechanisms underpinning pain empathy.

Alzheimer’s disease (AD), the most common type of dementia, is an ageing-related progressive neurodegenerative brain disorder. Extracellular neuritic plaques composed of misfolded amyloid β (Aβ) proteins and intracellular neurofibrillary tangles formed by hyperphosphorylated tau protein are the two classical characteristics of AD. Aβ and tau pathologies induce neurite atrophy and neuronal apoptosis, leading to cognitive, language, and behavioral deficits. For decades, researchers have made great efforts to explore the pathogens and therapeutics of AD; however, its intrinsic mechanism remains unclear and there are still no well-established strategies to restore or even prevent this disease. Therefore, it would be beneficial for the establishment of novel therapeutic strategy to determine the intrinsic molecular mechanism that is interrelated with the initiation and progression of AD. A variety of evidence indicates that neuroinflammation plays a crucial role in the pathogenesis of AD. Nucleotide-binding oligomerization domain (NOD)-like receptor pyrin domain-containing protein 3 (NLRP3) is a key inflammasome sensor of cellular stress and infection that is involved in the innate immune system. In response to a wide range of stimuli like Aβ, NLRP3 assembles apoptosis-associated speck-like protein (ASC) and procaspase-1 into an inflammasome complex to induce the caspase-1 mediated secretion of interleukin (IL)-1β/IL-18 in M1 polarized microglia, triggering the pathophysiological changes and cognitive decline of AD. Therefore, targeting NLRP3 inflammasome seems an efficient path for AD treatment via regulating brain immune microenvironment. Furthermore, accumulating evidence indicates that traditional Chinese medicine (TCM) exerts beneficial effects on AD via NLRP3 inflammasome inactivation. In this review, we summarize current reports on the role and activated mechanisms of the NLRP3 inflammasome in the pathogenesis of AD. We also review the natural products for attenuating neuroinflammation by targeting NLRP3 inflammasome activation, which provides useful clues for developing novel AD treatments.

Forest parks are important for ecological conservation, recreation, and the health and well-being of the people who use them. However, forest parks located in urban areas often face the problem of crowding. To better understand perceived crowding in urban forest parks and to improve tourists’ recreation experiences and satisfaction, we constructed a conceptual model of the relationships between perceived crowding, emotion, and satisfaction with mechanisms of adjustment based on survey data from Dafu Mountain Forest Park in China. The results indicate that, in urban forest parks, perceived crowding significantly and negatively affects tourists’ satisfaction, but there is no significant difference in satisfaction between different activity types. Both positive and negative emotions have partially mediating effects on the relationship between perceived crowding and satisfaction. Crucially, our modeled mechanisms of adjustment play a moderating role in the effect of crowding on tourist satisfaction, and the choice of adjustment behaviors varies according to the activity type. This work enriches the research related to perceived crowding, mechanisms of adjustment, and satisfaction in tourist destinations and provides a theoretical basis for the future management of urban forest parks.

Panax quinquefolius L. has attracted extensive attention worldwide because of its prominent pharmacological properties on type 2 diabetes, cancers, central nervous system, and cardiovascular diseases. Ginsenosides are active phytochemicals of P. quinquefolius, which can be classified as propanaxdiol (PPD)-type, propanaxtriol (PPT)-type, oleanane-type, and ocotillol-type oligo-glycosides depending on the skeleton of aglycone. Recently, advanced analytical and isolated methods including ultra-performance liquid chromatography tandem with mass detector, preparative high-performance liquid chromatography, and high speed counter-current chromatography have been used to isolate and identify minor components in P. quinquefolius, which accelerates the clarification of the material basis. However, the poor bioavailability and undetermined bio-metabolism of most saponins have greatly hindered both the development of medicines and the identification of their real active constituents. Thus, it is essential to consider the bio-metabolism of constituents before and after absorption. In this review, we described the structures of minor ginsenosides in P. quinquefolius, including naturally occurring protype compounds and their in vivo metabolites. The preclinical and clinical pharmacological studies of the ginsenosides in the past few years were also summarized. The review will promote the reacquaint of minor saponins on the growing appreciation of their biological role in P. quinquefolius.

Evaluations have been made about the physicochemical stability in water-in-oil-in-water (W/O/W) emulsion loaded with resveratrol under different pH, NaCl concentration, temperature, and storage time. The in vitro digestion and Caco-2 cell transport were also investigated. Results showed W/O/W emulsion remained stable at pH 2–8, temperatures of 25–70 °C and could be stable storage for 77 days. With an increase in NaCl concentration from 1 to 500 mM, the zeta potential changed from −40 mV to −10 mV, but the droplets size didn’t show any significant change. The in vitro digestion showed W/O/W emulsion could maintain the structure until small intestine which could give higher protecting for resveratrol. Meanwhile, W/O/W emulsion could reduce the efflux rate of resveratrol across the Caco-2 cell monolayers and special complex of W/O/W emulsion could delay resveratrol release. Results indicated that W/O/W emulsion was suitable vehicle for resveratrol and could improve its bioavailability considering those complicated influence factors.

The construction of dams destroys the integrity of a watershed system and the continuity of natural water flow, creating a watershed with segmented and fragmented rivers. This, in turn, affects and even destroys the health and stability of the watershed ecosystem. This study selected the downstream area of Bengbu Sluice in the Huai River Basin of China as the study area. To address the increasingly prominent ecosystem degradation in the Huai River Basin, ecological flow thresholds were determined using habitat simulation and hydrological approaches for mutual validation. A multi-objective synergistic decision model incorporating ecological and socioeconomic objectives was developed to coordinate the economic and ecological water use conflicts in the study area. The optimal coordinated solution for the ecological flow of important biological habitats in the basin was determined with the multi-objective synergistic method. The results demonstrated that a coordinated solution could guarantee the ecological and economic water demands of the basin. The findings of this study can be used as a reference for scientific guidelines on future ecological operations in dam-controlled rivers.

This study aimed to explore the mechanism of fucoidan in chronic kidney disease (CKD)-triggered cognitive dysfunction. The adenine-induced ICR strain CKD mice model was applied, and RNA-Seq was performed for differential gene analysis between aged-CKD and normal mice. As a result, fucoidan (100 and 200 mg kg−1) significantly reversed adenine-induced high expression of urea, uric acid in urine, and creatinine in serum, as well as the novel object recognition memory and spatial memory deficits. RNA sequencing analysis indicated that oxidative and inflammatory signaling were involved in adenine-induced kidney injury and cognitive dysfunction; furthermore, fucoidan inhibited oxidative stress via GSK3β-Nrf2-HO-1 signaling and ameliorated inflammatory response through regulation of microglia/macrophage polarization in the kidney and hippocampus of CKD mice. Additionally, we clarified six hallmarks in the hippocampus and four in the kidney, which were correlated with CKD-triggered cognitive dysfunction. This study provides a theoretical basis for the application of fucoidan in the treatment of CKD-triggered memory deficits.

Benzothiazoles have played an important role in the field of biochemistry and medicinal chemistry due to their highly pharmaceutical and biological activity. The development of synthetic processes is undoubtedly one of the most significant problems facing researchers. In this review paper, we provided recent advances in the synthesis of benzothiazole compounds related to green chemistry from condensation of 2-aminobenzenethiol with aldehydes/ketones/acids/acyl chlorides and the cyclization of thioamide or carbon dioxide (CO2) as raw materials, and the future development trend and prospect of the synthesis of benzothiazoles were anticipated.

The focus of this paper is to apply an improved machine learning algorithm to realize the efficient and reliable identification and classification of network communication encrypted traffic, and to solve the challenges faced by traditional algorithms in analyzing encrypted traffic after adding encryption protocols. In this study, an enhanced random forest (ERF) algorithm is introduced to optimize the accuracy and efficiency of the identification and classification of encrypted network traffic. Compared with traditional methods, it aims to improve the identification ability of encrypted traffic and fill the knowledge gap in this field. Using the publicly available datasets and preprocessing the original PCAP format packets, the optimal combination of the relevant parameters of the tree was determined by grid search cross-validation, and the experimental results were evaluated in terms of performance using accuracy, precision, recall and F1 score, which showed that the average precision was more than 98 %, and that compared with the traditional algorithm, the error rate of the traffic test set was reduced, and the data of each performance evaluation index were better, which It shows that the advantages of the improved algorithm are obvious. In the experiment, the enhanced random forest and traditional random forest models were trained and tested on a series of data sets and the corresponding test errors were listed as the basis for judging the model quality. The experimental results show that the enhanced algorithm has good competitiveness. These findings have implications for cybersecurity professionals, researchers, and organizations, providing a practical solution to enhance threat detection and data privacy in the face of evolving encryption technologies. This study provides valuable insights for practitioners and decision-makers in the cybersecurity field. [ABSTRACT FROM AUTHOR]

Weibo short text information contains a large amount of network language, emoticons, etc., and due to the long-time span of the content, the emotions of the posts posted by people often change due to time or the occurrence of certain special events. Therefore, traditional sentiment analysis methods are not suitable for this task. This article proposes a CNNs-Bi LSTM sentiment analysis method that integrates attention mechanism. It combines convolutional neural networks and bidirectional short-term memory networks to obtain keyword information in text through attention mechanism, efficiently and accurately realizing data temporal and semantic information mining. Through experimental verification using Weibo public opinion data, the results show that this method achieves higher accuracy compared to other benchmark models and can fully utilize multidimensional matrices to capture rich text features, with certain advantages. [ABSTRACT FROM AUTHOR]

Copyright of Transformations in Business & Economics is the property of Vilnius University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Background IgA nephropathy (IgAN) is a common primary glomerulonephritis worldwide, and the improvement of glucocorticoid on the renal prognosis of IgAN patients with high risk of CKD progression remains unclear. Objective To explore the effect of glucocorticoid therapy on the therapeutic response and renal prognosis of IgAN patients with high risk of CKD progression. Methods IgAN patients with high risk of CKD progression were recruited in the First Affiliated Hospital of Zhengzhou University from January 2017 to October 2021 as study subjects and divided into the glucocorticoid treatment group and supportive treatment group according to whether glucocorticoid therapy was performed. Propensity matching method (PSM) was used to screen patients for cases by 1∶1 matching according to gender, age, 24 h urine protein and eGFR, the clinicopathological data of patients, disease remission, adverse reactions within 1 year were recorded. The patients were followed up from the date of initiation of supportive therapy until October 31, 2022. The primary endpoint event was defined as progression to end-stage renal disease (ESRD) or receiving dialysis. The composite endpoint event was defined as sustained decline in eGFR of more than 30% from baseline, or progression to ESRD, or receiving dialysis or death. Kaplan-Meier method was used to plot survival curves and log-rank test was used to compare differences in the cumulative incidence of the primary/composite endpoint events between the two groups of patients. Cox proportional hazards regression analysis was used to analyze the possible influencing factors of renal prognosis in IgAN patients with high risk of CKD progression. Results A total of 236 patients with primary IgAN met the inclusion criteria. After 1∶1 matching, 97 cases in the glucocorticoid treatment group were successfully matched with 97 cases in the supportive therapy group with balanced baseline data. The complete remission rate and partial remission rate of patients in the glucocorticoid treatment group were higher than those in supportive treatment group (χ2=6.171, P=0.013; χ2=3.973, P=0.046) . The median follow-up time was 18.00 (9.75, 28.00) months. Kaplan-Meier survival curve analysis showed that the cumulative incidence of primary endpoint event in the glucocorticoid treatment group was lower than the supportive treatment group (χ2=4.495, P=0.034) and the cumulative survival rate of composite endpoint event in the glucocorticoid therapy group was lower than the supportive therapy group (χ2=4.419, P=0.036) . Among the 236 patients who met the inclusion criteria, there were 177 patients with moderate proteinuria. After 1∶1 matching of the 177 patients on glucocorticoid treatment and supportive treatment by sex, age, 24 h urine protein and eGFR using PSM, 76 cases in each group were successfully matched. Kaplan-Meier survival curve analysis showed that the cumulative incidence of primary endpoint event in the patients on glucocorticoid treatment with moderate proteinuria was lower than those on supportive treatment with moderate proteinuria (χ2=4.127, P=0.042) ; and the cumulative survival rate of composite endpoint event in the patients on glucocorticoid treatment with moderate proteinuria was lower than those on supportive treatment with moderate proteinuria (χ2=4.934, P=0.026) . Multivariate Cox proportional hazard regression analysis showed that hemoglobin (HR=0.982) , serum creatinine (HR=1.019) , eGFR (HR=1.020) and 24-hour urine protein (HR=1.205) were influencing factors of primary endpoints event in IgAN patients with high risk of CKD progression. The incidence of infection in the glucocorticoid treatment group was higher than the supportive treatment group (P

Background and purpose: NCAPD2 is a protein-coding gene that plays a key role in cell proliferation, such as mitosis process. This study aimed to investigate the expression level and clinical value of NCAPD2 in glioma. Methods: The expression of NCAPD2 mRNA in various malignant tumor tissues was analyzed by GEPIA database. The expression level of NCAPD2 mRNA in glioma was analyzed by Ualcan, UCSC Xena and TIMER2.0 database. Immunohistochemical S-P method was used to detect and analyze the expression of NCAPD2 protein in normal brain tissue and glioma tissue, as well as the relationship between the overexpression of NCAPD2 protein and the clinicopathological features of glioma. The expression level of NCAPD2 in glioma cells was verified by Western blot. LinkedOmics database was used to explore genes co-expressed with NCAPD2. Metascape database and GoPlot database were used for enrichment analysis. Results: Database analysis showed that the expression of NCAPD2 was higher in various malignant tissues than in normal tissues (P ＜ 0.05), and the expression level of NCAPD2 was higher in isocitrate dehydrogenase 1 (IDH1) mutant-type glioma than in IDH1 wild-type glioma (P ＜ 0.05). Immunohistochemical results showed that NCAPD2 protein was mainly expressed in the nucleus and cytoplasm, and the positive expression rate and strong positive expression rate of NCAPD2 protein in glioma tissues were significantly higher than those in normal brain tissues (P ＜ 0.01). However, NCAPD2 protein was positively correlated with clinical classification of glioma patients (P ＜ 0.05). Western blot assay showed that the expression of NCAPD2 protein in glioma cells was significantly higher than in glial cells (P ＜ 0.05). GO enrichment analysis showed that NCAPD2 gene was mainly related to cell cycle progression (P ＜ 0.01). Conclusion: The overexpression of NCAPD2 in glioma is closely related to clinical grade and cell cycle progression, which indicates that NCAPD2 plays an important role in the occurrence and development of glioma.