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The expression of TRIM47, a member of the TRIM protein and E3 ubiquitin ligase families, is elevated in various cancers, such as non-small cell lung cancer and colorectal cancer, and is linked to poor prognosis. This study aimed to investigate the role of TRIM47 in gastric cancer development. Using The Cancer Genome Atlas-Stomach Adenocarcinoma (TCGA-STAD) dataset and analysis of 20 patient samples from our center, TRIM47 was found to be significantly up-regulated in gastric cancer tissues and associated with advanced N-stage and poor prognosis. We constructed stable TRIM47 knockdown and overexpressing gastric cancer cell lines. CCK8, EDU, colony formation, wound healing, and Transwell tests were used to evaluate the effects on cell proliferation, invasion, and migration. The results showed that TRIM47 knockdown inhibited the proliferation, migration and invasion of gastric cancer cells, while TRIM47 overexpression promoted these behaviors. These results were further confirmed in vivo. In the mechanism part, we found that TRIM47 interacts with CYLD protein. Moreover, TRIM47 promotes K48-linked ubiquitination, leading to the degradation of CYLD by the proteasome, thereby activating the NF-κB pathway and regulating the biological behavior of gastric cancer cells. Taken together, our study demonstrated that TRIM47 is involved in the proliferation and metastasis of gastric cancer through the CYLD/NF-κB pathway. [ABSTRACT FROM AUTHOR]

Seed aging is a complex process that involves various physiological and biochemical changes leading to a decline in seed viability during storage. However, the specific biomarkers for assessing the degree of seed aging in rice remain elusive. In this study, we isolated a golden hull mutant, gh15, from the indica rice Z15 by employing a radiation mutagenesis technique. Compared with the wild type (WT) Z15, the mutant gh15 displayed a golden hue in the hull, stem, and internodes, while no significant differences were observed in the key agronomic traits. A genetic analysis showed that the gh15 phenotype is regulated by a single recessive gene, which possibly encodes cinnamyl alcohol dehydrogenase OsCAD2. Significant differences of seed aging tolerance were observed between gh15 and WT after six months of natural storage and artificial aging treatment, with gh15 exhibiting a markedly lower aging tolerance compared to the WT. Haplotype assays indicated that the Hap2 of OsCAD2 was significantly associated with the dark coloration of the hull and lower seed aging tolerance. The molecular marker of OsCAD2 associated with seed color was explored in rice. These findings demonstrate that the golden hull serves as a potential biomarker for the rapid assessment of seed aging tolerance in rice. [ABSTRACT FROM AUTHOR]

This project utilized both field experiment and laboratory analyses to address the gap in understanding regarding the alterations in properties and functions of biochar, and the impact of heavy metal passivation in soil over long-term natural field aging. The study aimed to examine the changes in the physical and chemical characteristics of biochar over an extended period of natural aging. Additionally, it sought to analyze the impact and mechanisms of biochar in reducing of the harmful effects of the heavy metal cadmium (Cd) during the aging process. Both original and aged biochar conformed to the pseudo-second-order kinetics model and the Langmuir model. The aging process enhanced the adsorption of Cd by biochar and mitigated the leaching of Cd2+ into the soil. These findings provide a scientific basis for evaluating biochar’s environmental behavior and its potential use in the remediation of soil contaminated with heavy metals. [ABSTRACT FROM AUTHOR]

Pediatric trauma plays a crucial role in pediatric mortality, with traffic injuries and falls frequently cited as leading causes of significant injuries among children. A comprehensive investigation, including geographical factors, is essential for developing effective strategies to prevent injuries and alleviate the burden of pediatric trauma. This study involved a retrospective analysis of clinical data from pediatric patients admitted to our hospital's intensive care unit (ICU) due to trauma over a 10-year period. Comprehensive analyses were conducted to elucidate trends, demographics, injury patterns, and risk factors associated with these admissions. This retrospective study included 951 pediatric patients (mean age: 4.79 ± 3.24 years; mean weight: 18.45 ± 9.02 kg; median time to ICU admission post-injury: 10.86 ± 14.95 h). Among these patients, 422 (44.4%) underwent emergency surgery, and 466 (49%) required mechanical ventilation support, with a mean duration of 70.19 ± 146.62 h. The mean duration of ICU stay was 6.24 ± 8.01 days, and the overall mean hospitalization duration was 16.08 ± 15.56 days. The predominant cause of unintentional injury was traffic accidents (47.9%), followed by falls (42.5%) and burns/scalds (5.3%). Most incidents involved children aged 0–6 years (70.7%), with males comprising 60.0% of patients. Injury incidents predominantly occurred between 12 and 6 PM (44.5%) and on non-workdays (37.6%). The most common locations where injuries occurred were roadsides (49%) and rural areas (64.35%). Single-site injuries (58.78%) were more prevalent than multiple-site injuries (41.22%), and head injuries were the most common among single-site injuries (81.57%). At ICU admission, the mean injury severity score was 18.49 ± 8.86. Following active intervention, 871 patients (91.59%) showed improvement, while 80 (8.41%) succumbed to their injuries. Traffic injuries remain the primary cause of pediatric trauma leading to ICU admission, underscoring the importance of using appropriate child restraint systems and protective gear as fundamental preventive measures. The increased incidence of injuries among children aged < 6 years and those residing in rural areas highlights the need for targeted preventive strategies, necessitating tailored interventions and public policy formulations that address these high-risk populations. [ABSTRACT FROM AUTHOR]

Renewable energy accommodation in power grids leads to frequent load changes in power plants. Sensitive turbine fault monitoring technology is critical to ensure the stable operation of the power system. Existing techniques do not use information sufficiently and are not sensitive to early fault signs. To solve this problem, an unsupervised fault warning method based on hybrid information gain and a convolutional autoencoder (CAE) for turbine intermediate flux is proposed. A high-precision intermediate-stage flux prediction model is established using the CAE. The hybrid information gain calculation method is proposed to filter the features of multi-dimensional sensors. The Hampel filter for time series outlier detection is introduced to deal with factors such as sensor faults and noise. The proposed method achieves the highest fault diagnosis accuracy through experiments on real data compared to traditional methods. Real data experiments show that the proposed method relatively improves the diagnostic accuracy by an average of 2.12% compared to the gate recurrent unit networks, long short-term memory networks, and other traditional models. Meanwhile, the proposed hybrid information gain can effectively improve the detection accuracy of the traditional models, with a maximum of 1.89% relative accuracy improvement. The proposed method is noteworthy for its superiority and applicability. [ABSTRACT FROM AUTHOR]

Purpose: Melanoma is widely utilized as a prominent model for the development of immunotherapy, thought an inadequate immune response can occur. Moreover, the development of apoptosis-related therapies and combinations with other therapeutic strategies is impeded by the limited understanding of apoptosis's role within diverse tumor immune microenvironments (TMEs). Methods: Here, we constructed an apoptosis-related tumor microenvironment signature (ATM) and employ multi-dimensional analysis to understand the roles of apoptosis in tumor microenvironment. We further assessed the clinical applications of ATM in nine independent cohorts, and anticipated the impact of ATM on cellular drug response in cultured cells. Results: Our ATM model exhibits robust performance in survival prediction in multiple melanoma cohorts. Different ATM groups exhibited distinct molecular signatures and biological processes. The low ATM group exhibited significant enrichment in B cell activation-related pathways. What's more, plasma cells showed the lowest ATM score, highlighting their role as pivotal contributors in the ATM model. Mechanistically, the analysis of the interplay between plasma cells and other immune cells elucidated their crucial role in orchestrating an effective anti-tumor immune response. Significantly, the ATM signature exhibited associations with therapeutic efficacy of immune checkpoint blockade and the drug sensitivity of various agents, including FDA-approved and clinically utilized drugs targeting the VEGF signaling pathway. Finally, ATM was associated with tertiary lymphoid structures (TLS), exhibiting stronger patient stratification ability compared to classical "hot tumors". Conclusion: Our findings indicate that ATM is a prognostic factor and is associated with the immune response and drug sensitivity in melanoma. [ABSTRACT FROM AUTHOR]

Although rapid progression and a poor prognosis in influenza A virus (IAV) infection–induced acute exacerbation of chronic obstructive pulmonary disease (AECOPD) are frequently associated with metabolic energy disorders, the underlying mechanisms and rescue strategies remain unknown. We herein demonstrated that the level of resting energy expenditure increased significantly in IAV‐induced AECOPD patients and that cellular energy exhaustion emerged earlier and more significantly in IAV‐infected primary COPD bronchial epithelial (pDHBE) cells. The differentially expressed genes were enriched in the oxidative phosphorylation (OXPHOS) pathway; additionally, we consistently uncovered much earlier ATP exhaustion, more severe mitochondrial structural destruction and dysfunction, and OXPHOS impairment in IAV‐inoculated pDHBE cells, and these changes were rescued by melatonin. The level of OMA1‐dependent cleavage of OPA1 in the mitochondrial inner membrane and the shift in energy metabolism from OXPHOS to glycolysis were significantly increased in IAV‐infected pDHBE cells; however, these changes were rescued by OMA1‐siRNA or melatonin further treatment. Collectively, our data revealed that melatonin rescued IAV–induced cellular energy exhaustion via OMA1‐OPA1‐S to improve the clinical prognosis in COPD. This treatment may serve as a potential therapeutic agent for patients in which AECOPD is induced by IAV. [ABSTRACT FROM AUTHOR]

An inorganic hexalanthanide-oxo-cluster-encapsulated antimotungstate, K2Na3H43[Nd6(OH)6(H2O)6(B-α-SbW9O33)4]2·67H2O (1), has been successfully synthesized by a facile one-step hydrothermal reaction method. The tetrahedron-shaped two-shell {Nd6(OH)6(H2O)6(B-α-SbW9O33)4}(1a) polyanion is composed of a novel pure lanthanide-oxo {Nd6(μ3-OH)6(H2O)6} octahedron and {(B-α-SbW9O33)4} tetrahedron. After being effectively loaded onto a glassy carbon electrode (GCE) by electrostatic adsorption using polydiallyldimethyl ammonium chloride (PDDA)-functionalized multi-walled carbon nanotubes (MWCNTs), compound 1 exhibits electrochemical activity for the reduction of bromate ions with good selectivity, a high sensitivity of 186 μA mM−1 and a detection limit that has reached 1.9 μM. To the best of our knowledge, this is the first example of an amperometric bromate sensor based on Ln-containing antimotungstates, which will provide new materials for electrochemical sensors. [ABSTRACT FROM AUTHOR]

Purpose: To identify potential biomarkers and the molecular mechanisms associated with repeated implantation failure (RIF), three microarray datasets, GSE71331 (lncRNA + mRNA), GSE111974 (lncRNA + mRNA), and GSE71332 (miRNA), were retrieved from the Gene Expression Omnibus (GEO) database. Methods: The differentially expressed mRNAs (DEMs), lncRNAs (DElncRNAs), and miRNAs (DEmiRNAs) between normal control samples (C group) and RIF samples (RIF group) were identified, and then a module partition analysis was performed based on weighted correlation network analysis (WGCNA). Following enrichment analysis of the genes, the lncRNA-miRNA-mRNA interactions (ceRNA) were examined. The mRNAs in the ceRNA network were evaluated using the GSE58144 dataset. Finally, the key RNAs were verified using reverse transcription-quantitative polymerase chain reaction (RT-qPCR). Results: Fifty-three DEmiRNAs, 327 DEMs, and 13 DElncRNAs were identified between the C and RIF groups. According to WGCNA, the magenta module was positively correlated with RIF disease status. The lncRNA-mRNA interaction analysis based on genes in the magenta module revealed the intersecting lncRNAs, including peptidylprolyl isomerase E-like pseudogene (PPIEL) and the testis-specific transcript, y-Linked 14 (TTTY14); these lncRNAs are mainly involved in functions, such as plasma membrane organization. The ceRNA network analysis revealed several interactions, such as TTTY14-miR-6088-semaphorin 5 A (SEMA5A). Finally, SEMA5A and the zinc finger protein 555 (ZNF555) were identified to be significantly upregulated in the RIF group compared with those in the C group in the GSE58144 dataset. The RT-qPCR results aligned with the above results. Conclusions: Overall, TTTY14, ZNF555, SEMA5A, PPIEL, and miR-6088 could serve as novel biomarkers of RIF. Highlights: TTTY14, ZNF555, SEMA5A, PPIEL and miR-6088 could be serve as novel biomarkers of RIF. TTTY14 may participate in RIF progression by regulating the miR-6088/SEMA5A axis. This study provides new insights for the diagnosis and treatment of RIF. [ABSTRACT FROM AUTHOR]

Objectives: To develop a computed tomography (CT) radiomics-based interpretable machine learning (ML) model to predict the pathological grade of pancreatic neuroendocrine tumors (pNETs) in a non-invasive manner. Methods: Patients with pNETs who underwent contrast-enhanced abdominal CT between 2010 and 2022 were included in this retrospective study. Radiomics features were extracted, and five radiomics-based ML models, namely logistic regression (LR), random forest (RF), support vector machine (SVM), XGBoost, and GaussianNB, were developed. The performance of these models was evaluated using a time-independent testing set, and metrics such as sensitivity, specificity, accuracy, and the area under the receiver operating characteristic curve (AUC) were calculated. The accuracy of the radiomics model was compared to that of needle biopsy. The Shapley Additive Explanation (SHAP) tool and the correlation between radiomics and biological features were employed to explore the interpretability of the model. Results: A total of 122 patients (mean age: 50 ± 14 years; 53 male) were included in the training set, whereas 100 patients (mean age: 48 ± 13 years; 50 male) were included in the testing set. The AUCs for LR, SVM, RF, XGBoost, and GaussianNB were 0.758, 0.742, 0.779, 0.744, and 0.745, respectively, with corresponding accuracies of 73.0%, 70.0%, 77.0%, 71.9%, and 72.9%. The SHAP tool identified two features of the venous phase as the most significant, which showed significant differences among the Ki-67 index or mitotic count subgroups (p < 0.001). Conclusions: An interpretable radiomics-based RF model can effectively differentiate between G1 and G2/3 of pNETs, demonstrating favorable interpretability. Clinical relevance statement: The radiomics-based interpretable model developed in this study has significant clinical relevance as it offers a non-invasive method for assessing the pathological grade of pancreatic neuroendocrine tumors and holds promise as an important complementary tool to traditional tissue biopsy. Key Points: • A radiomics-based interpretable model was developed to predict the pathological grade of pNETs and compared with preoperative needle biopsy in terms of accuracy. • The model, based on CT radiomics, demonstrated favorable interpretability. • The radiomics model holds potential as a valuable complementary technique to preoperative needle biopsy; however, it should not be considered a replacement for biopsy. [ABSTRACT FROM AUTHOR]

This article, published in Chemistry of Natural Compounds, discusses the production of isoflavone metabolites and their microbial transformation by a soil-derived Saccharopolyspora antimicrobica DSMZ45119. Actinomycetes, specifically the Saccharopolyspora genus, have been a focus of research due to their production of biologically active secondary metabolites. The study implemented the one strain many compounds (OSMAC) approach to cultivate DSMZ45119 on six different media and analyzed the resulting metabolites. The researchers isolated and characterized six known isoflavone aglycones and glycosides from the strain. The article also discusses the antimicrobial, cytotoxic, immunosuppressive, and antioxidant activities of these compounds. The work was co-financed by grants from the Key Research Program of Hainan Province and the National Natural Science Foundation of China. [Extracted from the article]

Background: Identification of knee osteoarthritis (OA) pain phenotypes, their transition patterns, and risk factors for worse phenotypes, may guide prognosis and targeted treatment; however, few studies have described them. We aimed to investigate different pain phenotypes, their transition patterns, and potential risk factors for worse pain phenotypes. Methods: Utilizing data from the Osteoarthritis Initiative (OAI), pain severity was assessed using the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) pain subscale. We identified the activity-related pain phenotypes and estimated the transition probabilities of pain phenotypes from baseline to the 24-month using latent transition analysis. We examined the risk factors at baseline with the 24-month pain phenotypes and the transition of pain phenotypes. Results: In 4796 participants, we identified four distinct knee pain phenotypes at both baseline and 24-month follow-up: no pain, mild pain during activity (Mild P-A), mild pain during both rest and activity (Mild P-R-A), and moderate pain during both rest and activity (Mod P-R-A). 82.9% knees with no pain at baseline stayed the same at 24-month follow-up, 17.1% progressed to worse pain phenotypes. Among "Mild P-A" at baseline, 32.0% converted to no-pain, 12.8% progressed to "Mild P-R-A", and 53.2% remained. Approximately 46.1% of "Mild P-R-A" and 54.5% of "Mod P-R-A" at baseline experienced remission by 24-month. Female, non-whites, participants with higher depression score, higher body mass index (BMI), higher Kellgren and Lawrence (KL) grade, and knee injury history were more likely to be in the worse pain phenotypes, while participants aged 65 years or older and with higher education were less likely to be in worse pain phenotypes at 24-month follow-up visit. Risk factors for greater transition probability to worse pain phenotypes at 24-month included being female, non-whites, participants with higher depression score, higher BMI, and higher KL grade. Conclusions: We identified four distinct knee pain phenotypes. While the pain phenotypes remained stable in the majority of knees over 24 months period, substantial proportion of knees switched to different pain phenotypes. Several socio-demographics as well as radiographic lesions at baseline are associated with worse pain phenotypes at 24-month follow-up visit and transition of pain phenotypes. [ABSTRACT FROM AUTHOR]

Sirtuin 3 (SIRT3) shows distinct roles in reprogramming cell metabolism and shaping tumor phenotypes, mainly by deacetylating diverse substrates. The context-specific functions of SIRT3 may both promote and suppress tumorigenesis. Recent advances in SIRT3-targeted drug discovery, including inhibitors and activators, hold significant promise for cancer therapeutics. A deep understanding of the mechanisms of SIRT3-targeted small molecules could prompt the development of SIRT3-targeted therapy. Sirtuin 3 (SIRT3), an NAD+-dependent deacetylase, plays a key role in the modulation of metabolic reprogramming and regulation of cell death, as well as in shaping tumor phenotypes. Owing to its critical role in determining tumor-type specificity or the direction of tumor evolution, the development of small-molecule modulators of SIRT3, including inhibitors and activators, is of significant interest. In this review, we discuss recent studies on the oncogenic or tumor-suppressive functions of SIRT3, evaluate advances in SIRT3-targeted drug discovery, and present potential avenues for the design of small-molecule modulators of SIRT3 for cancer therapy. [ABSTRACT FROM AUTHOR]

Background: Patent foramen ovale (PFO) is a known cause of ischemic stroke in young adults and combined oral contraceptives (COCs) are widely used by women of reproductive age. If young women with PFO are taking COCs, they may be subjected to a synergistic increase in the occurrence of stroke, though reports of ischemic stroke in this population are rare. We report a woman of reproductive age who was taking COC suffered repetitive ischemic strokes before a patent foramen ovale (PFO) was detected and closed, which may raise concerns in this field. Case presentation: A 31-year-old woman presented to the emergency department with sudden-onset right upper- and lower-limb weakness and dysarthria for 1 hour, whose only risk factor of stroke was oral contraceptive use. On admission, she was alert with left gaze deviation, dysarthria, and right-sided hemiplegia. Her symptoms improved after receiving the revascularization therapy. About 24 hours later, her left eye experienced sudden painless vision loss. Then the PFO with a substantial right-to-left shunt was detected and then she received a trans-catheter closure of the defect. Over 3 months of follow-up, there were no signs of stroke, but visual loss persisted. Conclusion: This case of disabling stroke raises concerns regarding optimal management in primary and secondary prevention of stroke in young women on COCs with additional risk factors of stroke. [ABSTRACT FROM AUTHOR]

A 21-year-old woman with severe pulmonary hypertension and circulatory collapse was referred to our hospital for possible lung transplantation with extracorporeal membrane oxygenation support. Computed tomography revealed severe stenosis of all 4 pulmonary veins, and fibrosing mediastinitis was suspected. Surgical reconstruction of the pulmonary veins was performed, and extracorporeal membrane oxygenation support was weaned off. After surgery, pulmonary vascular resistance normalized. This successful case demonstrates that surgical pulmonary venous reconstruction is an important treatment for fibrosing mediastinitis induced by pulmonary venous stenosis and pulmonary hypertension. [ABSTRACT FROM AUTHOR]

Quantum vortices in Bose–Einstein condensates (BECs) are essential phenomena in condensed matter physics, and precisely locating their positions, especially the vortex core, is a precondition for studying their properties. With the rise of machine learning, there is a possibility to expedite the localization process and provide accurate predictions. However, traditional machine learning requires particular considerable amount of manual data annotation, leading to uncontrollable accuracy. In this paper, we utilize the U-Net method to detect vortex positions accurately at the pixel level and propose an Automatic Correction Labeling (ACL) approach to optimize the acquisition of data sets for vortex localization in BECs. This approach addresses inaccuracies in the labeled vortex positions and improves the accuracy of vortex localization, especially the vortex core positions, while enhancing the tolerance for human mislabeling. The main process involves Rough Labeling → Machine Learning → Probability Region Search → Data Relabeling → Machine Learning again. The objective of ACL is to secure more accurate labeled data for model retraining. Through vortex localization experiments conducted in a two-dimensional Bose-Einstein condensate, our results establish the following: 1. Even under conditions of biased and missing manual annotations, U-Net can still accurately locate vortex positions; 2. Vortices exhibit certain regularities, and training U-Net with a small number of samples yields excellent predictive consequences; 3. The machine learning vortex locator based on the ACL method effectively corrects errors in manually annotated data, significantly improving the model's performance metrics, thus enhancing the precision and metrics of vortex localization. This substantial advancement in the application of machine learning in vortex localization provides an effective way for vortex dynamics localization. Furthermore, this method of obtaining more accurate positions of approximate human labels through machine learning offers new insights for machine learning in other types of image recognition problems. [ABSTRACT FROM AUTHOR]

The coronal mass ejections (CMEs) observed by white-light coronagraphs, such as the Large Angle and Spectrometric Coronagraph (LASCO) C2/C3, commonly exhibit the three-part structure, with the bright leading edge as the outermost part. In this work, we extend previous work on the leading edge by performing a large-scale 3D magnetohydrodynamic numerical simulation on the evolution of an eruptive magnetic flux rope (MFR) in a near-Sun region based on a radially stretched calculation grid in spherical coordination and the incorporation of solar wind. In the early stage, the new simulation almost repeats the previous results, i.e., the expanding eruptive MFR and associated CME bubble interact with the ambient magnetic field, which leads to the appearance of the helical current ribbon/boundary (HCB) wrapping around the MFR. The HCB can be interpreted as a possible mechanism of the CME leading edge. Later, the CME bubble propagates self-consistently to a larger region beyond a few solar radii from the solar center, similar to the early stage of evolution. The continuous growth and propagation of the CME bubbles leading to the HCB can be traced across the entire near-Sun region. Furthermore, we can observe the HCB in the white-light synthetic images as a bright front feature in the large field of view of LASCO C2 and C3. [ABSTRACT FROM AUTHOR]

Background: Puberty marks the end of childhood and achieve sexual maturation and fertility. The role of hypothalamic proteins in regulating puberty onset is unclear. We performed a comprehensive differential proteomics and phosphoproteomics analysis in prepubertal and pubertal goats to determine the roles of hypothalamic proteins and phosphoproteins during the onset of puberty. Results: We used peptide and posttranslational modifications peptide quantification and statistical analyses, and identified 69 differentially expressed proteins from 5,057 proteins and 576 differentially expressed phosphopeptides from 1574 phosphorylated proteins. Combined proteomic and phosphoproteomics, 759 correlated proteins were identified, of which 5 were differentially expressed only at the protein level, and 201 were only differentially expressed at the phosphoprotein level. Pathway enrichment analyses revealed that the majority of correlated proteins were associated with glycolysis/gluconeogenesis, Fc gamma R-mediated phagocytosis, focal adhesion, GABAergic synapse, and Rap1 signaling pathway. These pathways are related to cell proliferation, neurocyte migration, and promoting the release of gonadotropin-releasing hormone in the hypothalamus. CTNNB1 occupied important locations in the protein-protein interaction network and is involved in focal adhesion. Conclusion: The results demonstrate that the proteins differentially expression only at the protein level or only differentially expressed at the phosphoprotein level and their related signalling pathways are crucial in regulating puberty in goats. These differentially expressed proteins and phosphorylated proteins may constitute the proteomic backgrounds between the two different stages. [ABSTRACT FROM AUTHOR]

Turbulence plays a key role in forming the complex geometry of the large-scale current sheet (CS) and fast energy release in a solar eruption. In this paper, we present full 3D high-resolution simulations for the process of a moderate coronal mass ejection (CME) and the thermodynamical evolution of the highly confined CS. Copious elongated blobs are generated owing to tearing and plasmoid instabilities, giving rise to a higher reconnection rate, and undergo the splitting, merging, and kinking processes in a more complex way in 3D. A detailed thermodynamical analysis shows that the CS is mainly heated by adiabatic and numerical viscous terms, and thermal conduction is the dominant factor that balances the energy inside the CS. Accordingly, the temperature of the CS reaches to a maximum of about 20 MK, and the range of temperatures is relatively narrow. From the face-on view in the synthetic Atmospheric Imaging Assembly 131 Å, the downflowing structures with similar morphology to supra-arcade downflows are mainly located between the post-flare loops and loop top, while moving blobs can extend spikes higher above the loop top. The downward-moving plasmoids can keep the twisted magnetic field configuration until the annihilation at the flare loop top, indicating that plasmoid reconnection dominates in the lower CS. Meanwhile, the upward-moving ones turn into turbulent structures before arriving at the bottom of the CME, implying that turbulent reconnection dominates in the upper CS. The spatial distributions of the turbulent energy and anisotropy are addressed, which show a significant variation in the spectra with height. [ABSTRACT FROM AUTHOR]

With the advancement of artificial intelligence (AI) and the Internet of Things (IoT), smart clothing, which has enormous growth potential, has developed to suit consumers' individualized demands in various areas. This paper aims to construct a model that integrates that technology acceptance model (TAM) and functionality-expressiveness-aesthetics (FEA) model to explore the key factors influencing consumers' smart clothing purchase intentions (PIs). Partial least squares structural equation modeling (PLS-SEM) was employed to analyze the data, complemented by fuzzy-set qualitative comparative analysis (fsQCA). The PLS-SEM results identified that the characteristics of functionality (FUN), expressiveness (EXP), and aesthetics (AES) positively and significantly affect perceived ease of use (PEOU), and only EXP affects perceived usefulness (PU). PU and PEOU positively impact consumers' attitudes (ATTs). Subsequently, PU and consumers' ATTs positively influence PIs. fsQCA revealed the nonlinear and complex interaction effects of the factors influencing consumers' smart clothing purchase behaviors and uncovered five necessary and six sufficient conditions for consumers' PIs. This paper furthers theoretical understanding by integrating the FEA model into the TAM. Additionally, on a practical level, it provides significant insights into consumers' intentions to purchase smart clothing. These findings serve as valuable tools for corporations and designers in strategizing the design and promotion of smart clothing. The results validate theoretical conceptions about smart clothing PIs and provide useful insights and marketing suggestions for smart clothing implementation and development. Moreover, this study is the first to explain smart clothing PIs using symmetric (PLS-SEM) and asymmetric (fsQCA) methods. [ABSTRACT FROM AUTHOR]

Chlorine-based disinfectants are widely used for disinfection in wastewater treatment. The mechanism of the effects of chlorinated disinfection by-products on cyanobacteria was unclear. Herein, the physiological effects of chloroacetic acid (CAA) on Microcystis aeruginosa (M. aeruginosa), including acute toxicity, oxidative stress, apoptosis, production of microcystin-LR (MC-LR), and the microcystin transportation-related gene mcyH transcript abundance have been investigated. CAA exposure resulted in a significant change in the cell ultrastructure, including thylakoid damage, disappearance of nucleoid, production of gas vacuoles, increase in starch granule, accumulation of lipid droplets, and disruption of cytoplasm membranes. Meanwhile, the apoptosis rate of M. aeruginosa increased with CAA concentration. The production of MC-LR was affected by CAA, and the transcript abundance of mcyH decreased. Our results suggested that CAA poses acute toxicity to M. aeruginosa , and it could cause oxidative damage, stimulate MC-LR production, and damage cell ultrastructure. This study may provide information about the minimum concentration of CAA in the water environment, which is safe for aquatic organisms, especially during the global coronavirus disease 2019 pandemic period. [Display omitted] [ABSTRACT FROM AUTHOR]

Background: The gefitinib resistance mechanism in non-small cell lung cancer (NSCLC) remains unclear, albeit exosomal circular RNA (circRNA) is known to possibly play a vital role in it. Methods: We employed high-throughput sequencing techniques to detect the expressions of exosomal circRNA both in gefitinib-resistant and gefitinib-sensitive cells in this study. The circKIF20B expression was determined in serum exosomes and tissues of patients by qRT-PCR. The structure, stability, and intracellular localization of circKIF20B were verified by Sanger sequencing, Ribonuclease R (RNase R)/actinomycin D (ACTD) treatments, and Fluorescence in situ hybridization (FISH). The functions of circKIF20B were investigated by 5-Ethynyl-20-deoxyuridine (EdU), flow cytometry, Cell Counting Kit-8 (CCK-8), oxygen consumption rate (OCR), and xenograft model. Co-culture experiments were performed to explore the potential ability of exosomal circKIF20B in treating gefitinib resistance. The downstream targets of circKIF20B were determined by luciferase assay, RNA pulldown, and RNA immunoprecipitation (RIP). Results: We found that circKIF20B was poorly expressed in the serum exosomes of gefitinib-resistant patients (n = 24) and the tumor tissues of patients with NSCLC (n = 85). CircKIF20B was negatively correlated with tumor size and tumor stage. Decreasing circKIF20B was found to promote gefitinib resistance by accelerating the cell cycle, inhibiting apoptosis, and enhancing mitochondrial oxidative phosphorylation (OXPHOS), whereas increasing circKIF20B was found to restore gefitinib sensitivity. Mechanistically, circKIF20B is bound to miR-615-3p for regulating the MEF2A and then altering the cell cycle, apoptosis, and mitochondrial OXPHOS. Overexpressing circKIF20B parental cells can restore sensitivity to gefitinib in the recipient cells by upregulating the exosomal circKIF20B expression. Conclusions: This study revealed a novel mechanism of circKIF20B/miR-615-3p/MEF2A signaling axis involving progression of gefitinib resistance in NSCLC. Exosomal circKIF20B is expected to be an easily accessible and alternative liquid biopsy candidate and potential therapeutic target in gefitinib-resistant NSCLC. [ABSTRACT FROM AUTHOR]

The light-sensitive albino tea plant can produce pale-yellow shoots with high levels of amino acids which are suitable to process high-quality tea. In order to understand the mechanism of the albino phenotype formation, the changes in the physio-chemical characteristics, chloroplast ultrastructure, chlorophyll-binding proteins, and the relevant gene expression were comprehensively investigated in the leaves of the light-sensitive albino cultivar 'Huangjinya' ('HJY') during short-term shading treatment. In the content of photosynthetic pigments, the ultrastructure of the chloroplast, and parameters of the photosynthesis in the leaves of 'HJY' could be gradually normalized along with the extension of the shading time, resulting in the leaf color transformed from pale yellow to green. BN-PAGE and SDS-PAGE revealed that function restoration of the photosynthetic apparatus was attributed to the proper formation of the pigment-protein complexes on the thylakoid membrane that benefited from the increased levels of the LHCII subunits in the shaded leaves of 'HJY', indicating the low level of LHCII subunits, especially the lack of the Lhcb1 might be responsible for the albino phenotype of the 'HJY' under natural light condition. The deficiency of the Lhcb1 was mainly subject to the strongly suppressed expression of the Lhcb1.x which might be modulated by the chloroplast retrograde signaling pathway GUN1 (GENOMES UNCOUPLED 1)-PTM (PHD type transcription factor with transmembrane domains)-ABI4 (ABSCISIC ACID INSENSITIVE 4). [ABSTRACT FROM AUTHOR]

To understand potential users' behavioral intention (BI) to adopt new energy vehicles (NEVs), a media-based perceptions and adoption model (MPAM) of NEVs geared toward potential NEV consumers was constructed based on social cognition theory, the technology acceptance model, the value acceptance model, perceived risk theory, and the MPAM of autonomous vehicles (AVs). A sample survey including 309 NEV potential users was conducted and the results were analyzed through SPSS 24.0 and SmartPLS 3.0 to test the model and verify the research hypotheses. The results show that mass media (MM) has a direct influence on users' social norms (SNs) and part of product perceptions, and an indirect influence on their BI to adopt NEVs; SNs have a direct influence on product perception, and also indirectly affect BI toward NEVs. Product perception directly and significantly affects BI; perceived usefulness (PU), perceived ease of use (PEOU), and perceived enjoyment (PE) have a positive and significant influence on BI, while both perceived cost (PC) and perceived risk (PR) have a negative and significant impact. This study is a theoretical extension of the technology acceptance model (TAM) to green product adoption scenarios, such as NEVs, in the face of the external stimuli from MM information; it proposes product perception variables and media information effects that are different from the MPAM of AVs. The results are expected to greatly promote NEV design and marketing. [ABSTRACT FROM AUTHOR]

Aristolochic acid I (AAI) can cause nephrotoxicity and is characterized by interstitial fibrosis. The C3a/C3aR axis of macrophages and matrix metalloproteinase-9 (MMP-9) play important roles in fibrosis, but whether they are involved in AAI-induced renal interstitial fibrosis and are related remains to be elucidated. In this study, we investigated whether C3a/C3aR axis of macrophages promotes renal interstitial fibrosis by regulating MMP-9 in aristolochic acid nephropathy (AAN). Intraperitoneal injection of AAI for 28 days successfully induced AAN in C57bl/6 mice. The content of C3a in the kidney of AAN mice was increased, and there was a significant distribution of macrophages in the renal tubules. The same results were observed in the in vitro experiment. We also explored the role and mechanism of macrophages after AAI administration in the epithelial–mesenchymal transformation (EMT) of renal tubular epithelial cells (RTECs) and found that AAI could activate the C3a/C3aR axis of macrophages to upregulate p65 expression in macrophages. p65 upregulated MMP-9 expression in macrophages not only directly but also by promoting the secretion if interleukin-6 by macrophages and then activating STAT3 in RTECs. The upregulation of MMP-9 expression could promote the EMT of RTECs. Taken together, our study demonstrated that the AAI-activated the C3a/C3aR axis of macrophages, which induced MMP-9 production, was one of the causes of renal interstitial fibrosis. Therefore, targeting the C3a/C3aR axis of macrophages is an effective therapeutic strategy for the prevention and treatment of renal interstitial fibrosis in AAN. [Display omitted] • Aristolochic acid I activates the C3a/C3aR axis of macrophages in aristolochic acid nephropathy. • Macrophages promote Aristolochic acid nephropathy via the C3a/C3aR/IL-6 pathway. • Upregulated MMP-9 expression accelerates the EMT of RTECs and aggravates renal interstitial fibrosis. [ABSTRACT FROM AUTHOR]

• Effective trend characterization method is necessary because of uncertain numerical distribution of interval grey numbers. • Interval grey numbers with center points are taken as research objects. • A grey interval prediction model combined with Markov model based on interval features is proposed for data modeling. • The proposed model corrects the interval deviations or irregularities making the uncertainty information clearer. • Examples of private car ownership and milk production in representative regions verify the efficacy of the proposed model. Data sequences represent complex changes in external environments or internal systems, and patterns of some index sequences have become more difficult to characterize using real number sequences. Considering the imbalances between regional development levels in terms of socioeconomic indicators, a discrete grey-Markov model based on interval distribution characteristics is proposed in this paper. Based on the classic discrete grey model, a difference coefficient sequence and median sequences of the upper and lower information domains, respectively, are introduced to establish differential equations for the representation and prediction of different development level trends. Furthermore, a combination of discrete grey models with the Markov model is used to modify the nonstationary data sequences and further improve the new model prediction accuracy. The parameter estimation and solution of the proposed model are organized using analytical methods, and the accuracy of the model is investigated. By fitting and predicting examples of private car ownership and milk production in representative unbalanced development regions, the results of the proposed model are compared with those of four other prediction models to verify its effectiveness. The results demonstrate that the prediction accuracy of the proposed model is better than those of other grey models in nonstationary data sequences. By capturing the interval features, this model achieves the goal of characterization of interval distribution information and further modification of the nonstationary series. [ABSTRACT FROM AUTHOR]

Background: Age at puberty is an important factor affecting goat fertility, with endocrine and genetic factors playing a crucial role in the onset of puberty. To better understand the relationship between endocrine and genetic factors and mechanisms underlying puberty onset in goats, reproductive hormone levels were analyzed by ELISA and ultraperformance liquid chromatography–multiple reaction monitoring–multistage/mass spectrometry and RNA sequencing was performed to analyze ovarian genes. Results: Serum follicle stimulating hormone, luteinizing hormone, estradiol, 11-deoxycortisol, 11-deoxycorticosterone, corticosterone, cortisone, and cortisol levels were found to be higher but progesterone were lower in pubertal goats as compared to those in prepubertal goats (P < 0.05). A total of 18,139 genes were identified in cDNA libraries, and 75 differentially expressed genes (DEGs) were identified (|log2 fold change|≥ 1, P ≤ 0.05), of which 32 were significantly up- and 43 were down-regulated in pubertal goats. Gene ontology enrichment analyses indicated that DEGs were mainly involved in "metabolic process," "signaling," "reproduction," and "growth." Further, DEGs were significantly enriched in 91 Kyoto Encyclopedia of Genes and Genomes pathways, including estrogen signaling pathway, steroid hormone biosynthesis, and cAMP signaling pathway. Bioinformatics analysis showed that PRLR and THBS1 were highly expressed in pubertal ovaries, and ZP3, ZP4, and ASTL showed low expression, suggesting their involvement in follicular development and lutealization. Conclusions: To summarize, serum hormone changes and ovarian DEGs expression were investigated in our study. Further studies are warranted to comprehensively explore the functions of DEGs in goat puberty. [ABSTRACT FROM AUTHOR]

1,1,1-Trichloroethane (1,1,1-TCA) is a typical organochloride solvent in groundwater that poses threats to human health and the environment due to its carcinogenesis and bioaccumulation. In this study, a novel composite with nanoscale zero-valent iron (nZVI) supported by polycaprolac-tone (PCL)-modified biochar (nZVI@PBC) was synthesized via solution intercalation and liquid-phase reduction to address the 1,1,1-TCA pollution problem in groundwater. The synergy effect and improvement mechanism of 1,1,1-TCA removal from simulated groundwater in the presence of nZVI@PBC coupling with Shewanella putrefaciens CN32 were investigated. The results were as follows: (1) The composite surface was rough and porous, and PCL and nZVI were loaded uniformly onto the biochar surface as micro-particles and nanoparticles, respectively; (2) the optimal mass ratio of PCL, biochar, and nZVI was 1:7:2, and the optimal composite dosage was 1.0% (w/v); (3) under the optimal conditions, nZVI@PBC + CN32 exhibited excellent removal performance for 1,1,1-TCA, with a removal rate of 82.98% within 360 h, while the maximum removal rate was only 41.44% in the nZVI + CN32 treatment; (4) the abundance of CN32 and the concentration of adsorbed Fe(II) in the nZVI@PBC + CN32 treatment were significantly higher than that in control treatments, while the total organic carbon (TOC) concentration first increased and then decreased during the culture process; (5) the major improvement mechanisms include the nZVI-mediated chemical reductive dechlorination and the CN32-mediated microbial dissimilatory iron reduction. In conclusion, the nZVI@PBC composite coupling with CN32 can be a potential technique to apply for 1,1,1-TCA removal in groundwater. [ABSTRACT FROM AUTHOR]

• Four errors in the traditional forecast model were identified and mitigated. • Grey forecast prediction model was developed for interval sequences. • Weight parameter comprehensively characterized the development trend of the interval. • Proposed model demonstrated superior performance in two real-world examples. With the increasing complexity of systems, it is difficult to describe a huge amount of information accurately with real numbers. To make predictions using uncertain information, this study uses interval numbers as descriptors and proposes a weight-adaptive fusion grey prediction model based on interval sequences (WAFGM(1,N) model). Unlike most interval prediction models; the proposed model uses the adaptive weight and compensation coefficient to directly predict interval grey numbers without converting interval sequences into real number sequences. Moreover, it improves the four errors of the traditional GM(1,N) model, thereby further improving model accuracy. First, by fully considering the integrity and interaction of the upper and lower boundaries of the interval, this study introduced a weight parameter to comprehensively characterize the development trend of the interval, and by optimizing the background value and adjusting the compensation coefficient, the univariate and multivariate weight-adaptive grey prediction models for interval prediction were constructed, respectively. Second, the interval development and driving coefficients, compensation coefficient, and weight parameter were estimated and optimized using the least squares method, accumulation method, and particle swarm algorithm, respectively. Finally, the WAFGM(1,N) model was constructed by combining the two models. The validity and applicability of the WAFGM(1,N) model were proved using two examples: the gross agricultural output value of Northeast China and the production of dairy products in the golden milk source areas. [ABSTRACT FROM AUTHOR]

Selecting the best knitted fabric with various comfort properties is considered a complicated multi-criteria decision-making (MCDM) issue that involves ambiguity and vagueness. In such scenarios, Pythagorean fuzzy sets (PFSs) provide an effective tool for addressing uncertainty and ambiguity in MCDM problems that contain human subjective evaluations and judgments. First, this research identifies the factors affecting the comfort of knitted fabrics as the evaluation criteria. Second, the Bayesian best-worst method (BBWM) is preferred for less pairwise comparisons and obtains highly reliable results with a probabilistic perspective for determining the criteria weights. Furthermore, due to its logical computation approach and ease of operation, the technique for order preference by similarity to ideal solution (TOPSIS) is commonly utilized for addressing MCDM problems. Therefore, this research proposes an innovative MCDM framework that combines the BBWM technique with Pythagorean fuzzy TOPSIS (PFTOPSIS). The BBWM determines the criteria weights, and the weighted sine similarity-based PFTOPSIS is utilized to rank alternatives. The proposed BBWM-PFTOPSIS approach was employed to solve a real-world case. Moreover, this article conducts a sensitivity analysis and three comparative analyses to reveal the efficiency and reliability of the BBWM-PFTOPSIS approach. The ranking results establish the viability and effectiveness of BBWM-PFTOPSIS. [ABSTRACT FROM AUTHOR]

Cotton fabric selection is a challenging task in the garment product design and development process, and the selection of optimal alternative under the presence of multiple decision criteria becomes complex, and hence it is considered as a multi-criteria decision-making (MCDM) problem. In addition, the selection process involves fuzziness and uncertainty. In this study, Pythagorean fuzzy sets (PFSs) are introduced to handle uncertain information. Elimination and choice translating reality (ELECTRE) is a well-known outranking method for solving MCDM problems. Therefore, we extend the ELECTRE method under the PFS environment, and a correlation-based closeness coefficient is proposed to compare Pythagorean fuzzy numbers (PFNs). This paper applies the proposed PF-ELECTRE approach in solving a practical case involving the ranking cotton fabrics. To exhibit the superiority and robustness of the suggested method, sensitivity analysis is performed to examine the impacts of weights variation, as well as a comparative analysis is carried out between the PF-ELECTRE with several existing MCDM methods. The research contributes to the advancement and development of outranking MCDM methods through a novel PF-ELECTRE approach that utilizes the weighted correlation coefficient. Moreover, the developed method can obtain reliable results and can be used to other textile domains. [ABSTRACT FROM AUTHOR]

Soil salinity is one of the major abiotic stresses limiting rice growth. Hybrids outperform their parents in salt tolerance in rice, while its mechanism is not completely understood. In this study, a higher seedling survival was observed after salt treatment in an inter-subspecific hybrid rice, Zhegengyou1578 (ZGY1578), compared with its maternal japonica Zhegeng7A (ZG7A) and paternal indica Zhehui1578 (ZH1578). A total of 2584 and 3061 differentially expressed genes (DEGs) with at least twofold changes were identified between ZGY1578 and ZG7A and between ZGY1578 and ZH1578, respectively, in roots under salt stress using the RNA sequencing (RNA-Seq) approach. The expressions of a larger number of DEGs in hybrid were lower or higher than those of both parents. The DEGs associated with transcription factors, hormones, and reactive oxygen species (ROS)–related genes might be involved in the heterosis of salt tolerance. The expressions of the majority of transcription factors and ethylene-, auxin-, and gibberellin-related genes, as well as peroxidase genes, were significantly higher in the hybrid ZGY1578 compared with those of both parents. The identified genes provide valuable clues to elucidate the heterosis of salt tolerance in inter-subspecific hybrid rice. [ABSTRACT FROM AUTHOR]

Azulene, a simple polar polycyclic aromatic hydrocarbon with connected electron donor and acceptor (DA), ignites the hope of designing second‐order nonlinear optical (NLO) molecular materials from pure nonpolar carbon nanomaterials. In this work, a butterfly‐shaped nanographene (π−DA−π) was designed by incorporating azulene between two coronenes. One more electron in a N atom or one electron fewer in a B atom with respect to a C atom can polarize charge distribution in carbon nanomaterials, and further doping of B and N in the designed butterfly‐shaped nanographene changes the system from π−DA−π to D−π−A, leading to strong NLO responses. For example, the largest static first hyperpolarizability even reaches 173.89×10−30 esu per heavy atom. The synergetic role of B, N and azulene in the nanographene is scrutinized, and such a doping strategy is found to provide an effective means for the design of carbon‐based functional materials. The strong second‐order NLO responses of these butterfly‐shaped carbon‐based nanographenes under external fields, for example, sum frequency generation and difference frequency generation, could inspire future experimental exploration. [ABSTRACT FROM AUTHOR]

The applied Graph HT ht is compared with Graph HT ht , Graph HT ht and Graph HT ht . Graph HT ht denotes the direction of commitment. On the basis of Graph HT ht from Eq. (5), we sort the alternatives in order of decreasing Graph HT ht . [Extracted from the article]

Polyinosinic-polycytidylic acid (poly I:C) is a synthetic analog of double-stranded RNA (dsRNA) that activates anti-infective innate immunity. The underlying mechanisms are identified as targeting pattern recognition receptors and Th1-inducing. However, whether poly I:C manipulates metabolism to implement this anti-infective function is unknown. Here, GC-MS based metabolomics was used to characterize metabolic profiles induced by different doses of poly I:C. Analysis on the dose-dependent metabolomes shows that elevation of the TCA cycle and malate with the increasing dose of ploy I:C forms the most characteristic feature of the poly I:C stimulation. Exogenous malate activates the TCA cycle and elevates survival of zebrafish infected with Vibrio alginolyticus , which is related to the elevated expression of il-1b, il-6, il-8, tnf-a , and c3b. These results reveal a previously unknown regulation of poly I:C that boosts the TCA cycle to enhance innate immunity against bacterial infection. • Metabolic profiles induced by different doses of poly I:C. was characterized. • Elevated TCA cycle and malate forms the most characteristic feature. • Malate boosts TCA cycle and elevates zebrafish survival post bacterial infection. • This is related to the elevated expression of il-1b, il-6, il-8, tnf-a , and c3b. • These reveal a metabolic modulation of poly I:C against bacterial infection. [ABSTRACT FROM AUTHOR]

Interstitial lung disease associated with rheumatoid arthritis (RA-ILD) can lead to interstitial fibrosis and even lung failure as a complication of rheumatoid arthritis (RA), and there is currently no effective treatment and related basic research. Studies have found that resveratrol (Res) can improve the progression of RA by regulating autophagy, and increasing evidence supports the connection between autophagy and common interstitial lung disease (ILD). We explored changes in autophagy levels in fibrotic lungs in RA-ILD and found that the level of autophagy is enhanced in the early stage but inhibited in the late stage. However, resveratrol treatment improved the level of autophagy and reversed the inhibition of autophagy, and attenuated fibrosis. We created corresponding cell models that exhibited the same phenotypic changes as animal models; under the effect of resveratrol, the level of fibrosis changed accordingly, and the fusion process of lysosomes and autophagosomes in autophagy was liberated from the inhibition state. Resveratrol effects were reversed by the addition of the late autophagy inhibitor chloroquine. These results suggest that resveratrol attenuates pulmonary fibrosis, increases autophagic flux, and modulates the autophagy–lysosome pathway, and particularly it may work by improving the formation of autophagic lysosomes, which may be an effective treatment for induced RA-ILD. [ABSTRACT FROM AUTHOR]

Polysaccharides from sea cucumbers are known for their biological activities, but little is known about those from sea cucumber viscera. The present study isolated a sulfated polysaccharide (SCVP-2) from the viscera of Apostichopus japonicas , which had a molecular weight of 209.1 kDa. SCVP-2 comprised 66.3 % total sugars, 2.1 % uronic acid, 4.5 % proteins, and 25.5 % sulfate groups, containing glucosamine, galactosamine, glucose, galactose, and fucose. FT-IR and NMR analyses identified SCVP-2 as a fucoidan sulfate with sulfation patterns of the fucose branches as Fuc2S, Fuc4S, and Fuc0S. SEM and AFM analyses showed irregular clusters and linear conformations. SCVP-2 demonstrated strong anti-inflammatory properties both in vitro and in vivo. In lipopolysaccharide (LPS)-induced inflammation in macrophage RAW264.7 cells, SCVP-2 significantly reduced nitric oxide (NO) and cytokine secretion (IL-1β, IL-6, TNF-α). Additionally, it downregulated the expression of these cytokine genes. Furthermore, the anti-inflammatory mechanism of SCVP-2 was related to the inhibition of the MAPKs and NF-κB pathways. SCVP-2's anti-inflammatory capacity was confirmed in acute inflammation models, including xylene-induced ear swelling and acetic acid-induced peritoneal capillary permeability, and in high-fat diet-induced systemic low-grade chronic inflammation. In conclusion, SCVP-2 exhibits significant anti-inflammatory activity, suggesting its potential for development as a functional food ingredient or therapeutic agent for inflammation-related diseases. [ABSTRACT FROM AUTHOR]

The detection of tyrosine kinase inhibitors (TKIs) in biological fluids is essential due to their critical role in cancer therapy and the variability in individual drug metabolism, which necessitates precise dosing. Traditional methods for analyzing TKIs in biological fluids, such as blood plasma, typically involve complex sample preparation techniques that can be resource-intensive, environmentally burdensome, and not sufficiently sensitive for low-concentration analytes. There is a pressing need for more efficient, economical, and environmentally friendly methods that can enhance sensitivity and throughput without compromising accuracy. This study explores the use of melt-blown polypropylene nonwoven (MBPP), commonly found in face masks, as a novel sorbent for pipette-tip micro-solid phase extraction (PT-μSPE). MBPP demonstrated excellent hydrophobicity and significant mesoporous adsorption capacity. An extraction device was fashioned by inserting a segment of MBPP (15 mg) into a 200 μL disposable plastic pipette tip, which was then attached to a 2.5 mL disposable plastic syringe. The MBPP's fabric form removes the need for a frit, allowing the extraction process to be completed in just 3 min through simple plunger manipulation. The method achieved extraction recoveries ranging from 60.5 % to nearly 100 %. Subsequent method validation using liquid chromatography-tandem mass spectrometry (LC-MS/MS) showed satisfactory linearity (coefficient of determination R2 > 0.993), accuracy (relative recoveries: 86.3%–114.8 %), and precision (relative standard deviation: 3.4%–11.3 %), with detection limits between 0.022 and 0.135 ng mL−1. The introduction of MBPP for PT-μSPE represents a significant advancement in the bioanalytical detection of TKIs, offering a highly efficient, cost-effective, and environmentally sustainable method. It compares favorably with existing techniques, offering advantages in terms of cost, environmental impact, and ease of use. This approach has the potential to be widely adopted for routine monitoring of TKIs in clinical settings. [Display omitted] • Melt-blown polypropylene nonwoven acts as an efficient and eco-economic sorbent. • In-syringe solid-phase micro-extraction of tyrosine kinase inhibitors is developed. • Simple pull/push operations enable sample preparation to be completed within 3 min. • Low detection limits (0.022–0.135 ng mL−1) were achieved for TKI analysis in plasma. • Three metrics: AES, GAPI, and AGREE, illustrate the method's excellent greenness. [ABSTRACT FROM AUTHOR]

Compared to conventional nucleic acid detection methods, label-free single nucleotide polymorphism (SNP) detection presents challenging due to the necessity of discerning single base mismatches, especially in the field of enzyme-free detection. In this study, we introduce a novel bulged-type DNA duplex probe designed to significantly amplify single-base differences. This probe is integrated with programmable DNA-based nanostructures to develop a sensitive, label-free biosensor for nonenzymatic SNP detection. The duplex probe with one bulge could selectively identify wild-typed DNA (WT) and mutant-type DNA (MT) based on a competitive strand displacement reaction mechanism. The hyperbranched HCR (HHCR) by incorporating of hairpin DNA into the DNA tetrahedron and surface-tethering on the portable screen printing electrode (SPCE) significantly favor the formation of negatively charged DNA nanostructure. We harnessed strong repulsion of DNA nanostructure towards the electroactive [Fe(CN)₆]³⁻/⁴⁻ in combination with electrochemical technique to create a label-free biosensor. This simple, enzyme-free and label-free biosensor could detect MT with a detection limit of 56 aM, even in multiple sequence backgrounds. The study served as the proof-of-concept for the integration of enzyme-free competitive mechanism and label-free strategy, which can be extended as a powerful tool to various fields. [ABSTRACT FROM AUTHOR]

Reservoir computing (RC) system, featured by its recursive structure, has been utilized for temporal signal processing, offering both low power consumption and high computational speed. This work reports on a novel input delay reservoir computing (ID-RC) system based on the oxide memristors, which can be applied to temporal signal prediction. The particle swarm optimization (PSO) algorithm is employed in the ID-RC system to obtain optimal hyperparameters for multi-step prediction in the Mackey-Glass task, with a normalized root-mean-square error (NRMSE) of only 0.09 at the 20th step. Significantly, by employing the ID-RC system in temporal signal prediction of the Hénon map and the nonlinear autoregressive moving average (NARMA10), small NRMSEs of 0.047 and 0.017 were achieved, respectively. The memristor-based ID-RC system turns out to be highly promising in forecasting of chaotic time series. [Display omitted] • A new architecture of input delay reservoir computing system (ID-RC) based on memristor has been proposed. • Experimental results demonstrate the superiority of our ID-RC system over the delay feedback reservoir (DFR) computing system. • The introduction of the Particle Swarm Optimization algorithm (PSO) to automatically search for optimal hyperparameters has achieved low Normalized root mean square error (NRMSE) for multi-step prediction of the Mackey-Glass temporal signal. • Utilizing this ID-RC system for Hénon map and NARMA10 temporal signal predictions also achieved low NRMSE. [ABSTRACT FROM AUTHOR]

Images captured in challenging conditions often suffer from the co-existence of low contrast and low resolution. However, most joint enhancement methods focus on fitting a direct mapping from degraded images to high-quality images, which proves insufficient to handle complex degradation. To mitigate this, we propose a novel semantic prior guided interactive network (MSIRNet) to enable effective image representation learning for joint low-light enhancement and super-resolution. Specifically, a local HE-based domain transfer strategy is developed to remedy the domain gap between low-light images and the recognition scope of a generic segmentation model, thereby obtaining a rich granularity of semantic prior. To represent hybrid-scale features with semantic attributes, we propose a multi-grained semantic progressive interaction module that formulates an omnidirectional blend self-attention mechanism, facilitating deep interaction between diverse semantic knowledge and visual features. Moreover, employing our feature normalized complementary module that perceives context and cross-feature relationships, MSIRNet adaptively integrates image features with the auxiliary visual atoms provided by the Codebook, endowing the model with high-fidelity reconstruction capability. Extensive experiments demonstrate the superior performance of our MSIRNet, showing its ability to restore visually and perceptually pleasing normal-light high-resolution images. • An interactive network for joint low-light image enhancement and super-resolution. • We propose a local HE-based domain transfer strategy to minimize the domain gap. • An omnidirectional blend attention mechanism for heterogeneous feature interaction. • Integrating visual information flows using a feature normalized complementary module. [ABSTRACT FROM AUTHOR]

Images captured under low-light conditions usually co-exist with low light and blur degradation. Most existing cascade and joint enhancement methods may provide undesirable results, suffering from severe artifacts, deteriorating blur, and unclear details. In this paper, we propose a novel network with structural priors, including high-frequency and edge, to enable effective image representation learning for joint low-light enhancement and deblurring. Specifically, we employ a Transformer backbone to explore the global clues of the image. To compensate for the inadequate local detail optimization, we propose a multi-patch perception pyramid block that models the correlation between different size patches and ambiguity, and identifies non-uniform deblurring spatial features, facilitating the reconstruction of potential high-frequency and edge information. Furthermore, a prior-guided reconstruction block based on the parallel attention mechanism is present to adaptively correct global image with statistical features, which helps guide the model to refine sharp texture and structure. Extensive experiments performed on simulated and real-world datasets demonstrate the efficacy of our proposed method in restoring low-light blurry and low-light images with increased visual perception compared to state-of-the-art methods. • Multi-structural priors are employed to joint low-light enhancement and deblurring. • A multi-patch perception pyramid block to remove non-uniform is proposed. • Prior-guided reconstruction block to adaptively correct global features is present. • The proposed method is extensively evaluated and attains superior performance. [ABSTRACT FROM AUTHOR]

Graphene-based nanomaterials have attracted significant attention for their potentials in biomedical and biotechnology applications in recent years, owing to the outstanding physical and chemical properties. However, the interaction mechanism and impact on biological activity of macro/micro biomolecules still require more concerns and further research in order to enhance their applicability in biosensors, etc. Herein, an integrated method has been developed to predict the protein bioactivity performance when interacting with nanomaterials for protein-based biosensor. Molecular dynamics simulation and molecular docking technique were consolidated to investigate several nanomaterials: C60 fullerene, single-walled carbon nanotube, pristine graphene and graphene oxide, and their effect when interacting with protein. The adsorption behavior, secondary structure changes and protein bioactivity changes were simulated, and the results of protein activity simulation were verified in combination with atomic force spectrum, circular dichroism spectrum fluorescence and electrochemical experiments. The best quantification alignment between bioactivity obtained by simulation and experiment measurements was further explored. The two proteins, RNase A and Exonuclease III, were regarded as analysis model for the proof of concept, and the prediction accuracy of protein bioactivity could reach up to 0.98. The study shows an easy-to-operate and systematic approach to predict the effects of graphene-based nanomaterials on protein bioactivity, which holds guiding significance for the design of protein-related biosensors. In addition, the proposed prediction model is not limited to carbon-based nanomaterials and can be extended to other types of nanomaterials. This facilitates the rapid, simple, and low-cost selection of efficient and biosafe nanomaterials candidates for protein-related applications in biosensing and biomedical systems. Fig. 1. Schematic illustration of in silico prediction. (a) Structure diagram of four GBNMs. (b) The conformational change process of protein to nanomaterial by molecular dynamic simulation. (c) The bioactivity simulation of protein by molecular docking. [Display omitted] • Interaction between protein and nanomaterial is crucial for biosensor performance. • A model integrating molecular dynamic and docking simulation predicts the bioactivity. • A model directly predicts protein activity on nanomaterials rather than by conformation changes. • The prediction accuracy of protein bioactivty could reach up to 0.98. • The prediction model can be extended to other types of protein and nanomaterials. [ABSTRACT FROM AUTHOR]

• The distribution of microplastics in Bosten Lake was affected by seasons. • The distribution of microplastics in Bosten Lake was affected by human activities. • The microbial community in Bosten Lake was more affected by the environment. • The relationship between MPS and microorganisms in Bosten Lake was studied. Microplastics (MPs), discovered in oceans, lakes, and rivers, can infiltrate the food chain through ingestion by organisms, potentially posing health risks. Our research is the first to study the composition and distribution of MPs in Bosten Lake's sediment. In May, the average abundance of MPs was 0.95±0.72 particles per 10 gs, and in October, it was 0.90±0.61 particles per 10 gs. Bohu Town had the highest MP abundance, with 1.75±0.35 particles per 10 gs in spring and 2 ± 0 particles per 10 gs in autumn. In May, 53 % of the MPs were transparent, while in October, black MPs constituted 58 %. The predominant morphology was fibrous, accounting for 61 % of the total. MPs in the size range of 0.2–1 mm made up 91 % and 66 % of the total in May and October, respectively. The most common types of MPs in May were polyethylene terephthalate (PET) at 40 % and polyethylene (PE) at 26 %. In October, PET was the most prevalent at 71 %, followed by poly(ether-ether-ketone)(PEEK) at 11 %. Certain microbial taxa, such as Actinobacteriota, Pseudomonas, and Vicinamibacteraceae, associated with MP degradation or complex carbon chain breakdown, were notably enriched in sediment areas with high MP concentrations. A significant positive correlation was observed between the abundance of MPs in sediments and Actinobacteriota. Additionally, the abundance of Thiobacillus, Ca.competibacter, and other bacteria involved in soil element cycling showed a significant positive correlation with the organic matter content in the sediments. Anaerobic bacteria like Thermoanaerobacterium displayed a significant positive correlation with water depth. Our study reveals the presence, composition, and distribution of MPs in Bosten Lake's sediments, shedding light on their potential ecological impact. [Display omitted] [ABSTRACT FROM AUTHOR]

Antibiotic treatment is regarded as an emergency measure to avoid disease occurrence of aquatic animals during metamorphosis in an aquaculture system, which is very common in hatcheries of bivalve mollusc larvae. However, it is still unclear how and to what extent the antibiotic addition affects the prokaryotic and eukaryotic microbial communities of marine bivalve larvae. We profiled the community compositions and dominant taxonomies of prokaryotic and eukaryotic microbiota of Kumamoto oyster (Crassostrea sikamea) larvae exposed to seawater with antibiotics in trace concentration. A total of 500,664 16S rRNA and 501,933 18S rRNA gene fragments were selected for classification, resulting in 714 prokaryotic Operational Taxonomic Units (OTUs) and 47 eukaryotic OTUs. Antibiotic exposure altered the structure of larval microbiome and increased the prokaryotic but decreased the eukaryotic microbial diversity. Larval microbiota was sensitive to antibiotics, as evidenced by alternation of the dominant bacterial phyla Proteobacteria, Bacteroidetes, Firmicutes, Chlamydiae, and Actinobacteria, and eukaryotic phyla Streptophyta, Cercozoa, Chlorophyta and Haptophyta. Similarly, a significant effect was observed at the family and genus level, especially the increased bacterial Devosiaceae, Microbacteriaceae, Halieaceae, Vibrionaceae families, and Devosia, Stappia and Vibrio genera, and eukaryotic Isochrysidaceae and TAGIRI1-linage family and Tisochrysis genus. These results indicate that antibiotic treatment may induce a shift in the larval microbiome, which may cause an unstable community structure and in turn affect the oyster health. [ABSTRACT FROM AUTHOR]

Low-light image enhancement can effectively assist high-level vision tasks that often fail in poor illumination conditions. Most previous data-driven methods, however, implemented enhancement directly from severely degraded low-light images that may provide undesirable enhancement results, including blurred detail, intensive noise, and distorted color. In this paper, inspired by a coarse-to-fine strategy, we propose an end-to-end image-level alignment with pixel-wise perceptual information enhancement pipeline for low-light image enhancement. A coarse adaptive global photometric alignment sub-network is constructed to reduce style differences, which facilitates improving illumination and revealing under-exposure area information. After the learned aligned image, a hierarchy pyramid enhancement sub-network is used to optimize image quality, which helps to remove amplified noise and enhance the local detail of low-light images. We also propose a multi-residual cascade attention block (MRCAB) that involves channel split and concatenation strategy, polarized self-attention mechanism, which leads to high-resolution reconstruction images in perceptual quality. Extensive experiments have demonstrated the effectiveness of our method on various datasets and significantly outperformed other state-of-the-art methods in detail and color reproduction. [ABSTRACT FROM AUTHOR]

Pathological process in Parkinson's disease (PD) is accompanied with functional and metabolic alterations. The time-varying properties of functional coherence and their coupling to regional perfusion are still rarely elucidated. To investigate early disruption of dynamic regional homogeneity (dReho) and neurovascular coupling in cognitively normal PD patients, dynamic neuronal synchronization and regional perfusion were measured using dReho and cerebral blood flow (CBF), respectively. Neurovascular coupling was assessed by CBF-ReHo correlation coefficient and CBF/ReHo ratio. Multivariate pattern analysis was conducted for the differentiating ability of each feature. Relative to healthy controls (HC) subjects, PD patients demonstrated increased dReho in middle temporal gyrus (MTG), rectus gyrus, middle occipital gyrus, and precuneus, whereas reduced dReho in putamen and supplementary motor area (SMA); while higher CBF/dReho ratio was located in putamen, SMA, paracentral lobule, and postcentral gyrus, whereas lower CBF/dReho ratio in superior temporal gyrus, MTG, precuneus, and angular gyrus (AG). Global and regional CBF-Reho decoupling were both observed in PD groups. The CBF/Reho ratio features achieved more powerful classification performance than other features. From the view of dynamic neural synchronization and neurovascular coupling, this study reinforced the insights into neural basis underlying PD and the potential role in the disease diagnosis and differentiation. [ABSTRACT FROM AUTHOR]

Purpose: Extensive research has shown that reversible decisions yield lower post-decision satisfaction than irreversible decisions. However, to date, little is known about how decision reversibility affects post-decision satisfaction. Based on regret theory, this study aimed to examine the mediating role of counterfactual thinking and anticipated regret in the association between decision reversibility and satisfaction. Methods: In this study (130 participants), participants were randomly assigned to two personnel decision situations with reversible and irreversible decision outcomes, and all participants completed questionnaires during the process of completing the decision task. The questionnaires used included the Counterfactual Thinking for Negative Events Scale, Anticipated Regret Scale, and satisfaction questionnaire. Finally, the data were statistically analyzed using the base package in R and PROCESS 3.5. Results: The results show that (1) Compared to irreversible decisions, reversible decisions have a significant negative impact on satisfaction. (2) Counterfactual thinking plays a mediating role between decision reversibility and satisfaction. (3) Compared with irreversible decisions, reversible decisions further lowered the level of post-decision satisfaction through the chain mediating effects of counterfactual thinking and anticipated regret. Conclusion: People's lowered levels of post-decision satisfaction in the reversible decision condition relate to increased levels of counterfactual thinking and anticipated regret. In addition, counterfactual thinking can play a mediating role alone, indicating that this variable may be critical in understanding the mechanisms by which decision reversibility affects satisfaction. This knowledge may be used to help people optimize their decision-making behavior. [ABSTRACT FROM AUTHOR]

Background: Changes in the abundance of ovarian proteins play a key role in the regulation of reproduction. However, to date, no studies have investigated such changes in pubescent goats. Herein we applied isobaric tags for relative and absolute quantitation (iTRAQ) and liquid chromatography–tandem mass spectrometry to analyze the expression levels of ovarian proteins in pre-pubertal (n = 3) and pubertal (n = 3) goats. Results: Overall, 7,550 proteins were recognized; 301 (176 up- and 125 downregulated) were identified as differentially abundant proteins (DAPs). Five DAPs were randomly selected for expression level validation by Western blotting; the results of Western blotting and iTRAQ analysis were consistent. Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis indicated that DAPs were enriched in olfactory transduction, glutathione metabolism, and calcium signaling pathways. Besides, gene ontology functional enrichment analysis revealed that several DAPs enriched in biological processes were associated with cellular process, biological regulation, metabolic process, and response to stimulus. Protein–protein interaction network showed that proteins interacting with CDK1, HSPA1A, and UCK2 were the most abundant. Conclusions: We identified 301 DAPs, which were enriched in olfactory transduction, glutathione metabolism, and calcium signaling pathways, suggesting the involvement of these processes in the onset of puberty. Further studies are warranted to more comprehensively explore the function of the identified DAPs and aforementioned signaling pathways to gain novel, deeper insights into the mechanisms underlying the onset of puberty. [ABSTRACT FROM AUTHOR]

A number of double coronal X-ray sources have been observed during solar flares by RHESSI, where the two sources reside at different sides of the inferred reconnection site. However, where and how these X-ray-emitting electrons are accelerated remains unclear. Here we present the first model of the double coronal hard X-ray (HXR) sources, where electrons are accelerated by a pair of termination shocks driven by bidirectional fast reconnection outflows. We model the acceleration and transport of electrons in the flare region by numerically solving the Parker transport equation using velocity and magnetic fields from the macroscopic magnetohydrodynamic simulation of a flux rope eruption. We show that electrons can be efficiently accelerated by the termination shocks and high-energy electrons mainly concentrate around the two shocks. The synthetic HXR emission images display two distinct sources extending to >100 keV below and above the reconnection region, with the upper source much fainter than the lower one. The HXR energy spectra of the two coronal sources show similar spectral slopes, consistent with the observations. Our simulation results suggest that the flare termination shock can be a promising particle acceleration mechanism in explaining the double-source nonthermal emissions in solar flares. [ABSTRACT FROM AUTHOR]