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Background/purpose: Oral lichen planus (OLP) is a chronic inflammatory disease with obscure etiopathogenesis. Macrophages play an important role in interaction between innate and adaptive immunity. This study aimed to investigate the macrophage phenotypes and obtain more comprehensive gene characteristics of macrophages in OLP. Materials and methods: Double cluster of differentiation (CD) 68/CD86 and CD68/CD206 immunofluorescence staining was conducted in 11 biopsy-proven OLP tissue samples and 5 health control (HC) to represent M1 and M2 macrophages, respectively. The number of positively stained cells was manually counted, and the density was calculated. Furtherly, OLP single-cell dataset GSE211630 was downloaded from Gene Expression Omnibus. Gene characteristics and functional analysis of the macrophages were elucidated. Results: In the OLP group, the densities of M1 (P

Abstract Japanese encephalitis is an acute infectious disease of the central nervous system caused by neurotropic Japanese encephalitis virus (JEV). As a member of TAM (Tyro3, Axl and Mertk) family, Mertk has involved in multiple biological processes by engaging with its bridging ligands Gas6 and Protein S, including invasion of pathogens, phagocytosis of apoptotic cells, inflammatory response regulation, and the maintenance of blood brain barrier (BBB) integrity. However, its role in encephalitis caused by JEV infection has not been studied in detail. Here, we found that Mertk−/− mice exhibited higher mortality and more rapid disease progression than wild-type mice after JEV challenge. There were no significant differences in viral load and cytokines expression level in peripheral tissues between Wild type and Mertk−/− mice. Furthermore, the absence of Mertk had little effect on the inflammatory response and immunopathological damage while it can cause an increased viral load in the brain. For the in vitro model of BBB, Mertk was shown to maintain the integrity of the BBB. In vivo, Mertk−/− mice exhibited higher BBB permeability and lower BBB integrity. Taken together, our findings demonstrate that Mertk acts as a protective factor in the development of encephalitis induced by JEV infection, which is mainly associated with its beneficial effect on BBB integrity, rather than its regulation of inflammatory response.

Abstract Reservoir dam structure is critical to protect public life and property and has always been attention worldwide. However, a systematic approach to assessing the safety risks of reservoir dam structure (RDS) is still required. This study presents a holistic framework for evaluating the safety risk of RDS and develops an evaluation index system. A risk assessment model is constructed based on the cloud and Dempster-Shafer (D-S) evidence theories. The model's validity is confirmed through an empirical analysis of the XY reservoir project. This study offers theoretical insights and practical solutions for managers to facilitate decision-making and supports the advancement of industry standards.

Abstract Tandem repeats (TRs) are genomic regions that tandemly change in repeat number, which are often multiallelic. Their characteristics and contributions to gene expression and quantitative traits in rice are largely unknown. Here, we survey rice TR variations based on 231 genome assemblies and the rice pan-genome graph. We identify 227,391 multiallelic TR loci, including 54,416 TR variations that are absent from the Nipponbare reference genome. Only 1/3 TR variations show strong linkage with nearby bi-allelic variants (SNPs, Indels and PAVs). Using 193 panicle and 202 leaf transcriptomic data, we reveal 485 and 511 TRs act as QTLs independently of other bi-allelic variations to nearby gene expression, respectively. Using plant height and grain width as examples, we identify and validate TRs contributions to rice agronomic trait variations. These findings would enhance our understanding of the functions of multiallelic variants and facilitate rice molecular breeding.

Abstract Background As of September 2023, more than 1,000 cases of monkeypox (mpox) have been reported in China. Based on the available evidence, men who have sex with men (MSM) are at high risk for mpox infection. This study aimed to analyses the self-reported infection status, knowledge, attitude and influencing factors of monkeypox among MSM in Jiaxing City, China. Methods A web-based cross-sectional survey was conducted in September 2023 to gather data on participants’ socio-demographic profiles, mpox-related knowledge, sexual behavior characteristics, and other potentially related information to mpox knowledge. Multivariate regression modeling was employed to analyze the factors influencing the level of mpox-related knowledge. Results A total of 562 MSM were recruited; 4.3% self-reported being HIV-positive, 83.3% of respondents had heard of mpox, and 2.3% of them reported having suspected symptoms. 89.7% of respondents were willing to be vaccinated against mpox, but only 24.8% had a high level of knowledge about mpox. The main factors influencing knowledge of mpox were education level, household registration, homosexual anal intercourse in the past 6 months, and taking the HIV pre-exposure prophylaxis (PrEP). Conclusions Knowledge of mpox among MSM living in the Jiaxing area needs to be enhanced, but willingness to get vaccinated is high. Educational level, household location, sexual behavior and PrEP use have important effects on knowledge of mpox. Individuals exhibiting symptoms indicative of suspected mpox had a diminutive consultation frequency, and it is imperative to augment screening efforts for mpox symptoms within specific demographic groups to prevent the underreporting of mpox cases.

Abstract Over the last decade, a number of clinical trials have reported effects of chronic treatment with intranasal oxytocin on autistic symptoms but with inconsistent findings. Autism is a heterogeneous disorder and one factor which may influence treatment outcome is whether a subtype of individuals is more sensitive to oxytocin. In a recent cross-over trial on 41 young autistic children we reported that 44% showed a reliable improvement in clinical symptoms (Autism Diagnostic Observation Schedule, ADOS-2) after a placebo-controlled, 6-week intranasal oxytocin intervention where treatment was given every other day followed by a period of positive social interaction. In the current re-assessment of the data, we used an unsupervised data-driven cluster analysis approach to identify autism subtypes using 23 different demographic, social subtype, endocrine, eye-tracking and clinical symptom measures taken before treatment and this revealed an optimum of two different subtypes. We then assessed the proportion of identified responders to oxytocin and found that while 61.5% of one subtype included responders only 13.3% of the other did so. During the placebo phase there was no difference between the two subtypes for the small proportion of responders (19.2% vs 6.7%). This oxytocin-sensitive subtype also showed overall significant post-treatment clinical and eye-tracking measure changes. The oxytocin-sensitive subtype was primarily characterized at baseline by lower initial clinical severity (ADOS-2) and greater interest in the eye-region of emotional faces. These features alone were nearly as efficient in identifying the two subtypes as all 23 baseline measures and this easy-to-conduct approach may help rapidly and objectively screen for oxytocin responders. Future clinical trials using oxytocin interventions may therefore achieve greater success by focusing on children with this specific autism subtype and help develop individualized oxytocin intervention.

Background/purpose: Oral lichen planus (OLP) is a chronic inflammatory disease with unknown mechanisms of pathogenesis. Keratin 17 (KRT17) is a protein that regulates numerous cellular processes. This study aimed to explore the expression of KRT17 in OLP and its correlation with the severity of OLP. Materials and methods: RNA sequencing using epithelium from 5 OLP patients and 5 health control (HC) was performed, followed by functional analysis. The validation cohort of 20 OLP and 20 HC tissues were used to investigate positive area value of KRT17 by immunohistochemical analysis. Reticular, erosive and ulcerative (REU) scores were used for measuring the severity of OLP. Results: A total of 15493 genes were detected, of which 1492 genes were significantly up-regulated in OLP and 622 were down-regulated. The mRNA expression of KRT17 was elevated by 13.09-fold in OLP compared to that in HC. Pathway analysis demonstrated high KRT17 expression was associated with multiple biological processes. The median of percentage of KRT17 positive area value was 19.30 % in OLP and 0.01 % in HC (P

Abstract Background Fibrogenesis within ovarian endometrioma (endometrioma), mainly induced by transforming growth factor-β (TGF-β), is characterized by myofibroblast over-activation and excessive extracellular matrix (ECM) deposition, contributing to endometrioma-associated symptoms such as infertility by impairing ovarian reserve and oocyte quality. However, the precise molecular mechanisms that underpin the endometrioma- associated fibrosis progression induced by TGF-β remain poorly understood. Methods The expression level of lysine acetyltransferase 14 (KAT14) was validated in endometrium biopsies from patients with endometrioma and healthy controls, and the transcription level of KAT14 was further confirmed by analyzing a published single-cell transcriptome (scRNA-seq) dataset of endometriosis. We used overexpression, knockout, and knockdown approaches in immortalized human endometrial stromal cells (HESCs) or human primary ectopic endometrial stromal cells (EcESCs) to determine the role of KAT14 in TGF-β-induced fibrosis. Furthermore, an adeno-associated virus (AAV) carrying KAT14-shRNA was used in an endometriosis mice model to assess the role of KAT14 in vivo. Results KAT14 was upregulated in ectopic lesions from endometrioma patients and predominantly expressed in activated fibroblasts. In vitro studies showed that KAT14 overexpression significantly promoted a TGF-β-induced profibrotic response in endometrial stromal cells, while KAT14 silencing showed adverse effects that could be rescued by KAT14 re-enhancement. In vivo, Kat14 knockdown ameliorated fibrosis in the ectopic lesions of the endometriosis mouse model. Mechanistically, we showed that KAT14 directly interacted with serum response factor (SRF) to promote the expression of α-smooth muscle actin (α-SMA) by increasing histone H4 acetylation at promoter regions; this is necessary for TGF-β-induced ECM production and myofibroblast differentiation. In addition, the knockdown or pharmacological inhibition of SRF significantly attenuated KAT14-mediating profibrotic effects under TGF-β treatment. Notably, the KAT14/SRF complex was abundant in endometrioma samples and positively correlated with α-SMA expression, further supporting the key role of KAT14/SRF complex in the progression of endometrioma-associated fibrogenesis. Conclusion Our results shed light on KAT14 as a key effector of TGF-β–induced ECM production and myofibroblast differentiation in EcESCs by promoting histone H4 acetylation via co-operating with SRF, representing a potential therapeutic target for endometrioma-associated fibrosis.

Enzymes play a significant role in mediating inflammatory and immune responses in periodontitis. Effective diagnosis, timely treatment, and continuous management of periodontal enzymes are essential to prevent undesirable consequences; however, this remains a significant challenge. Nanoparticles (NPs) have attracted significant attention in biomedicine because of their advantageous nanosized effects. NPs are conjugated with specific enzyme substrates at responsive sites that are triggered by periodontitis enzyme biomarkers, leading to functional or characteristic changes. In contrast, NPs with enzyme-mimetic activities exhibit catalytic activity, effectively destroying pathogenic biofilms and modulating the immune response in periodontitis. The unique properties of enzyme-targeting NPs have enabled the development of biosensors and fluorescent probes capable of identifying enzyme biomarkers associated with periodontitis. Enzyme-responsive and enzyme-mimetic NPs both exert therapeutic applications in the treatment of periodontitis. In this review, we provide a comprehensive overview of the enzymes associated with periodontitis, the mechanisms of enzyme-responsive and enzyme-mimetic NPs, recent advancements in the use of NPs for detecting these enzymes, and the therapeutic applications of NPs in targeting or mimicking enzyme functions. We also discuss the challenges and prospects of using NPs in the diagnosis and treatment of periodontitis.

Summary: Background: Accurate staging of liver fibrosis (LF) is essential for clinical management in chronic liver disease. While non-contrast MRI (NC-MRI) yields valuable information for liver assessment, its effectiveness in predicting LF remains underexplored. This study aimed to develop and validate artificial intelligence (AI)-powered models utilizing NC-MRI for staging LF. Methods: A total of 1726 patients from Shengjing Hospital of China Medical University, registered between October 2003 and October 2022, were retrospectively collected, and divided into development (n = 1208) and internal test (n = 518) cohorts. An external test cohort consisting of 337 individuals from six centers, registered between June 2015 and November 2022, were also included. All participants underwent NC-MRI (T1-weighted imaging, T1WI; and T2-fat-suppressed imaging, T2FS) and liver biopsies. Two classification models (CMs), named T1 and T2FS, were trained on respective image types using 3D contextual transformer networks and evaluated on both test cohorts. Additionally, three CMs—Clinic, Image, and Fusion—were developed using clinical features, T1 and T2FS scores, and their integration via logistic regression. Classification effectiveness of CMs was assessed using the area under the receiver operating characteristic curve (AUC). A comparison was conducted between the optimal models (OMs) with highest AUC and other methods (transient elastography, five serum biomarkers, and six radiologists). Findings: Fusion models (i.e., OM) yielded the highest AUC among the CMs, achieving AUCs of 0.810 for significant fibrosis, 0.881 for advanced fibrosis, and 0.918 for cirrhosis in the internal test cohort, and 0.808, 0.868, and 0.925, respectively, in the external test cohort. The OMs demonstrated superior performance in AUC, significantly surpassing transient elastography (only for staging ≥ F2 and ≥ F3 grades), serum biomarkers, and three junior radiologists for staging LF. Radiologists, with the aid of the OMs, can achieve a higher AUC in LF assessment. Interpretation: AI-powered models utilizing NC-MRI, including T1WI and T2FS, accurately stage LF. Funding: National Natural Science Foundation of China (No. 82071885); General Program of the Liaoning Provincial Department of Education (LJKMZ20221160); Liaoning Province Science and Technology Joint Plan (2023JH2/101700127); the Leading Young Talent Program of Xingliao Yingcai in Liaoning Province (XLYC2203037).

Human capital plays a vital role in poverty-stricken households' efforts to cope with external shocks. Improving the human capital of poverty-stricken households to help them address external shocks can enhance the sustainability of poverty-stricken household livelihoods and support poverty alleviation. In this study, households with dependent children and older members were selected from questionnaires covering 6,463 poverty-stricken households from 33 poverty alleviation districts and counties in Chongqing municipality, China. Multiple linear regression model and stepwise regression methods were then used to compare the effects of the number of household members supported and the number of those working on the increase in income among poverty-stricken and nonpoverty-stricken households. Finally, the correlations between policy measures, dependent household members and household labor were examined. The results show the following: (1) Policy measures can alleviate the negative impact of a household's dependent population on household income. (2) Poverty-stricken households' access to policy support is closely related to the characteristics of their human capital. The household's dependent members and laborers are effectively protected by safety net and cargo net policies. (3) Policy measures can mitigate the impact of COVID-19 on the income of nonagricultural laborers while increasing the income of agricultural laborers. The findings show that the ability of poverty-stricken households to overcome poverty and deal with external shocks can be increased by revitalizing rural industries, linking the development of rural industries with the income of poverty-stricken households, and rationally using rural labor resources.

Nonylphenol (NP), an endocrine disruptor, has been demonstrated to be a harmful environmental contaminant and toxic to organisms. In this study, to address concerns regarding the immunotoxicity of NP, we treated clam Ruditapes philippinarum hemocytes with NP in vitro and explored the underlying mechanisms of NP-induced extracellular traps (ETs). NP could induce the formation of hemocytes ETs in a dose-dependent manner. Transcriptomics analysis revealed changes of signaling pathway involved in immunity and energy metabolism in hemocytes after NP stimulation. In this process, both reactive oxygen species (ROS) and myeloperoxidase (MPO) were up-regulated. Moreover, mitogen-activated protein kinase (MAPK) signaling pathway was proved to be activated in the formation of NP-induced ETs, manifested as enhanced phosphorylation of extracellular signal-regulated kinase (ERK) but not p38 or c-Jun N-terminal kinase (JNK). In the presence of U0126, an ERK phosphorylation inhibitor, the NP-induced expression of NADPH oxidase enzyme (NOX) was significantly decreased, which further alleviated the ROS production and ultimately limited the release of ETs. NP exposure increased glucose uptake, along with enhanced activities of glycolysis-related enzymes such as hexokinase (HK) and pyruvate kinase (PK). After inhibiting glycolysis by the inhibitor 2-DG, the formation of NP-induced ETs was significantly suppressed. ERK could regulate mTOR signaling and the PI3K/AKT pathway, potentially directing ETs formation by orchestrating the glycolysis through the activation of key transcription factors c-Myc and HIF-1α. Collectively, the results preliminary confirm that the ERK-NOX-ROS axis and glycolysis are involved in NP-induced ETs formation, contributing to the cellular immunotoxicity in clam.

IntroductionAutoimmune encephalitis (AE) comprises a group of inflammatory brain disorders mediated by autoimmune responses. Anti–N-methyl-D-aspartate receptor (NMDAR) encephalitis, anti–leucine-rich glioma-inactivated 1 (LGI1) encephalitis, and anti–γ-aminobutyric acid-B receptor (GABABR) encephalitis are the most prevalent forms, characterized by the presence of antibodies against neuronal cell-surface antigens. Efgartigimod, an antagonist of the neonatal Fc receptor, has proven efficacy in myasthenia gravis treatment. This clinical case report describes the clinical progression and functional outcomes of AE in three patients who received efgartigimod treatment.Case presentationsCase 1 was a 60-year-old man exhibiting memory impairment and psychiatric disturbances over 11 days. Case 2 was a 38-year-old man with a 1-month history of rapid cognitive decline and seizures. Case 3 was a 68-year-old woman with mental behavioral changes and seizures for 4 months. Anti-GABABR, anti-LGI1, and anti-NMDAR antibodies were confirmed in the respective patients’ cerebrospinal fluid or serum. All three patients experienced marked and swift symptomatic relief after four cycles of efgartigimod treatment, with no complication.ConclusionCurrent first-line and second-line treatments for AE have limitations, and efgartigimod has demonstrated potential in the rapid and efficacious treatment of AE, emerging as a promising option for the management of this disease.

Background and purposeThe baseline glucose-to-potassium ratio (GPR) is associated with poor outcomes in patients with acute brain injury and intracranial hemorrhage. However, the impact of serum GPR on clinical outcomes after endovascular thrombectomy (EVT) is unclear. This study aimed to evaluate the association between the GPR at admission and functional outcomes at 90 days after EVT.MethodsWe retrospectively reviewed our database for patients with acute ischemic stroke involving an anterior circulation large-vessel occlusion who received EVT between October 2019 and December 2021. The baseline serum GPR was measured after admission. The primary outcome was a 90-day poor outcome, which was defined as a modified Rankin scale score of 3–6.ResultsA total of 273 patients (mean age, 70.9 ± 11.9 years; 161 men) were finally included for analyses. During the 90-day follow-up, 151 patients (55.3%) experienced an unfavorable outcome. After adjusting for demographic characteristics and other potential confounders, the increased GPR was significantly associated with a higher risk of a 90-day poor outcome (odds ratio, 1.852; 95% confidence interval, 1.276–2.688, p = 0.001). Similar results were observed when the GPR was analyzed as a categorical variable. In addition, the restricted cubic spline observed a positive and linear association between the GPR and poor outcomes at 90 days (p = 0.329 for linearity; p = 0.001 for linearity).ConclusionOur study found that ischemic stroke patients with the higher GPR at admission were more likely to have an unfavorable prognosis at 3 months, suggesting that GPR may be a potential prognostic biomarker for ischemic stroke after EVT.

Resistance to cisplatin presents a major obstacle in managing advanced-stage cervical cancer. Cuproptosis, a newly identified form of cell death induced by copper ions, has potential in overcoming chemoresistance. But the application of cuproptosis in cervical cancer resistant to cisplatin has not yet been reported. In this study, treatment with Elsm-Cu in cervical cancer cells induced cuproptosis, affecting cell proliferation and apoptosis was found. Moreover, cuproptosis in cervical cancer cells was significantly induced by baicalein. The combination of baicalein and cisplatin exhibited a synergistic effect on cervical cancer cells by promoting apoptosis and inhibiting cell viability via the induction of cuproptosis. Animal experiments demonstrated that this combination significantly suppressed tumor growth. Upon treating cells with SC79 (Akt agonist), a significant inhibition of the expression of cuproptosis-related proteins SDHB and FDX1 were observed, indicating that baicalein induced cuproptosis through the Akt pathway. These results indicated that baicalein, mediated through the Akt pathway to induce cuproptosis, had the potential to improve the sensitivity of cervical cancer cells to cisplatin.

PurposeDistinguished from cuproptosis and ferroptosis, disulfidptosis has been described as a newly discovered form of non-programmed cell death tightly associated with glucose metabolism. However, the prognostic profile of disulfidptosis-related lncRNAs (DRLRs) in ovarian cancer (OC) and their biological mechanisms need to be further elucidated.Materials and methodsFirst, we downloaded the profiles of RNA transcriptome, clinical information for OC patients from the TCGA database. Generated from Cox regression analysis, prognostic lncRNAs were utilized to identify the risk signature by least absolute shrinkage and selection operator analysis. Then, we explored the intimate correlations between disulfidptosis and lncRNAs. What’s more, we performed a series of systemic analyses to assess the robustness of the model and unravel its relationship with the immune microenvironment comprehensively.ResultsWe identified two DRLR clusters, in which OC patients with low-risk scores exhibited a favorable prognosis, up-regulated immune cell infiltrations and enhanced sensitivity to immunotherapy. Furthermore, validation of the signature by clinical features and Cox analysis demonstrated remarkable consistency, suggesting the universal applicability of our model. It’s worth noting that high-risk patients showed more positive responses to immune checkpoint inhibitors and potential chemotherapeutic drugs.ConclusionOur findings provided valuable insights into DRLRs in OC for the first time, which indicated an excellent clinical value in the selection of management strategies, spreading brilliant horizons into individualized therapy.

Abstract The Patient-Reported Outcomes Measurement Information System 29-item Profile version 2.1 (PROMIS-29 V2.1) is a widely utilized self-reported instrument for assessing health outcomes from the patients’ perspectives. This study aimed to evaluate the psychometric properties of the PROMIS-29 V2.1 Chinese version among patients with hematological malignancy. Conducted as a cross-sectional, this research was approved by the Medical Ethical Committee of the Institute of Hematology and Blood Diseases Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College (registration number QTJC2022002-EC-1). We employed convenience sampling to enroll eligible patients with hematological malignancy from four tertiary hospitals in Tianjin, Shandong, Jiangsu, and Anhui province in China between June and August 2023. Participants were asked to complete a socio-demographic information questionnaire, the PROMIS-29 V2.1, and the Functional Assessment of Cancer Therapy-General (FACT-G). We assessed the reliability, ceiling and floor effects, structural, convergent discriminant and criterion validity of the PROMIS-29 V2.1. A total of 354 patients with a mean age of 46.93 years was included in the final analysis. The reliability of the PROMIS-29 V2.1 was affirmed, with Cronbach’s α for the domains ranging from 0.787 to 0.968. Except sleep disturbance, the other six domains had ceiling effects, which were seen on physical function (26.0%), anxiety (37.0%), depression (40.4%), fatigue (18.4%), social roles (18.9%) and pain interference (43.2%), respectively. Criterion validity was supported by significant correlations between the PROMIS-29 V2.1 and FACT-G scores, as determined by the Spearman correlation test (P

Abstract Cimicifugae Rhizoma, generally known as “Sheng Ma” in China, has great medicinal and dietary values. Cimicifugae Rhizoma is the dried rhizome of Cimicifuga foetida L., Cimicifuga dahurica (Turcz.) Maxim. and Cimicifuga heracleifolia Kom., which has been used to treat wind-heat headache, tooth pain, aphtha, sore throat, prolapse of anus and uterine prolapse in traditional Chinese medicine. This review systematically presents the traditional uses, phytochemistry, pharmacology, clinical studies, quality control and toxicity of Cimicifugae Rhizoma in order to propose scientific evidence for its rational utilization and product development. Herein, 348 compounds isolated or identified from the herb are summarized in this review, mainly including triterpenoid saponins, phenylpropanoids, chromones, alkaloids, terpenoids and flavonoids. The crude extracts and its constituents had various pharmacological properties such as anti-inflammatory, antitumor, antiviral, antioxidant, neuroprotective, anti-osteoporosis and relieving menopausal symptoms. The recent research progress of Cimicifugae Rhizoma in ethnopharmacology, phytochemistry and pharmacological effects demonstrates the effectiveness of its utilization and supplies valuable guidance for further research. This review will provide a basis for the future development and utilization of Cimicifugae Rhizoma.

Abstract Background Anorectal malformation is a common congenital problem occurring in 1 in 5,000 births and has a spectrum of anatomical presentations, requiring individualized surgical treatments for normal growth. Delayed extubation or reintubation may result in a longer intensive care unit (ICU) stay and hospital stay, increased mortality, prolonged duration of mechanical ventilation, increased tracheostomy rate, and higher hospital costs. Extensive studies have focused on the role of risk factors in early extubation during major infant surgery such as Cardiac surgery, neurosurgery, and liver surgery. However, no study has mentioned the influencing factors of delayed extubation in neonates and infants undergoing angioplasty surgery. Materials and Methods We performed a retrospective study of neonates and infants who underwent anorectal malformation surgery between June 2018 and June 2022. The principal goal of this study was to observe the incidence of delayed extubation in pediatric anorectal malformation surgery. The secondary goals were to identify the factors associated with delayed extubation in these infants. Results We collected data describing 123 patients who had anorectal malformations from 2019 to 2022. It shows that 74(60.2%) in the normal intubation group and 49(39.8%) in the longer extubation. In the final model, anesthesia methods were independently associated with delayed extubation (P

Abstract Two-dimensional nanofluidics based on naturally abundant clay are good candidates for harvesting osmotic energy between the sea and river from the perspective of commercialization and environmental sustainability. However, clay-based nanofluidics outputting long-term considerable osmotic power remains extremely challenging to achieve due to the lack of surface charge and mechanical strength. Here, a two-dimensional all-natural nanofluidic (2D-NNF) is developed as a robust and highly efficient osmotic energy generator based on an interlocking configuration of stacked montmorillonite nanosheets (from natural clay) and their intercalated cellulose nanofibers (from natural wood). The generated nano-confined interlamellar channels with abundant surface and space negative charges facilitate selective and fast hopping transport of cations in the 2D-NNF. This contributes to an osmotic power output of ~8.61 W m−2 by mixing artificial seawater and river water, higher than other reported state-of-the-art 2D nanofluidics. According to detailed life cycle assessments (LCA), the 2D-NNF demonstrates great advantages in resource consumption (1/14), greenhouse gas emissions (1/9), and production costs (1/13) compared with the mainstream 2D nanofluidics, promising good sustainability for large-scale and highly-efficient osmotic power generation.

Abstract We aimed to identify the druggable cell-intrinsic vulnerabilities and target-based drug therapies for PitNETs using the high-throughput drug screening (HTS) and genomic sequencing methods. We examined 9 patient-derived PitNET primary cells in HTS. Based on the screening results, the potential target genes were analyzed with genomic sequencing from a total of 180 PitNETs. We identified and verified one of the most potentially effective drugs, which targeted the Histone deacetylases (HDACs) both in in vitro and in vivo PitNET models. Further RNA sequencing revealed underlying molecular mechanisms following treatment with the representative HDACs inhibitor, Panobinostat. The HTS generated a total of 20,736 single-agent dose responses which were enriched among multiple inhibitors for various oncogenic targets, including HDACs, PI3K, mTOR, and proteasome. Among these drugs, HDAC inhibitors (HDACIs) were, on average, the most potent drug class. Further studies using in vitro, in vivo, and isolated PitNET primary cell models validated HDACIs, especially Panobinostat, as a promising therapeutic agent. Transcriptional surveys revealed substantial alterations to the Nrf2 signaling following Panobinostat treatment. Moreover, Nrf2 is highly expressed in PitNETs. The combination of Panobinostat and Nrf2 inhibitor ML385 had a synergistic effect on PitNET suppression. The current study revealed a class of effective anti-PitNET drugs, HDACIs, based on the HTS and genomic sequencing. One of the representative compounds, Panobinostat, may be a potential drug for PitNET treatment via Nrf2-mediated redox modulation. Combination of Panobinostat and ML385 further enhance the effectiveness for PitNET treatment.

Abstract Objective Mice are routinely utilized as animal models of drug-induced liver injury (DILI), however, there are significant differences in the pathogenesis between mice and humans. This study aimed to compare gene expression between humans and mice in acetaminophen (APAP)-induced liver injury (AILI), and investigate the similarities and differences in biological processes between the two species. Methods A pair of public datasets (GSE218879 and GSE120652) obtained from GEO were analyzed using “Limma” package in R language, and differentially expressed genes (DEGs) were identified, including co-expressed DEGs (co-DEGs) and specific-expressed DEGS (specific-DEGs). Analysis of Gene Set Enrichment Analysis (GSEA), Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were performed analyses for specific-DEGs and co-DEGs. The co-DEGs were also used to construct transcription factor (TF)-gene network, gene-miRNA interactions network and protein-protein interaction (PPI) network for analyzing hub genes. Results Mouse samples contained 1052 up-regulated genes and 1064 down-regulated genes, while human samples contained 1156 up-regulated genes and 1557 down-regulated genes. After taking the intersection between the DEGs, only 154 co-down-regulated and 89 co-up-regulated DEGs were identified, with a proportion of less than 10%. It was suggested that significant differences in gene expression between mice and humans in drug-induced liver injury. Mouse-specific-DEGs predominantly engaged in processes related to apoptosis and endoplasmic reticulum stress, while human-specific-DEGs were concentrated around catabolic process. Analysis of co-regulated genes reveals showed that they were mainly enriched in biosynthetic and metabolism-related processes. Then a PPI network which contains 189 nodes and 380 edges was constructed from the co-DEGs and two modules were obtained by Mcode. We screened out 10 hub genes by three algorithms of Degree, MCC and MNC, including CYP7A1, LSS, SREBF1, FASN, CD44, SPP1, ITGAV, ANXA5, LGALS3 and PDGFRA. Besides, TFs such as FOXC1, HINFP, NFKB1, miRNAs like mir-744-5p, mir-335-5p, mir-149-3p, mir-218-5p, mir-10a-5p may be the key regulatory factors of hub genes. Conclusions The DEGs of AILI mice models and those of patients were compared, and common biological processes were identified. The signaling pathways and hub genes in co-expression were identified between mice and humans through a series of bioinformatics analyses, which may be more valuable to reveal molecular mechanisms of AILI.

Constitutive activation of GNAQ/11 is the initiative oncogenic event in uveal melanoma (UM). Direct targeting GNAQ/11 has yet to be proven feasible as they are vital for a plethora of cellular functions. In search of genetic vulnerability for UM, we found that inhibition of euchromatic histone lysine methyltransferase 2 (EHMT2) expression or activity significantly reduced the proliferation and migration capacity of cancer cells. Notably, elevated expression of EHMT2 had been validated in UM samples. Furthermore, Kaplan–Meier survival analysis indicated high EHMT2 protein level was related to poor recurrence-free survival and a more advanced T stage. Chromatin immunoprecipitation sequencing analysis and the following mechanistic investigation showed that ARHGAP29 was a downstream target of EHMT2. Its transcription was suppressed by EHMT2 in a methyltransferase-dependent pattern in GNAQ/11-mutant UM cells, leading to elevated RhoA activity. Rescuing constitutively active RhoA in UM cells lacking EHMT2 restored oncogenic phenotypes. Simultaneously blocking EHMT2 and GNAQ/11 signaling in vitro and in vivo showed a synergistic effect on UM growth, suggesting the driver role of these two key molecules. In summary, our study shows evidence for an epigenetic program of EHMT2 regulation that influences UM progression and indicates inhibiting EHMT2 and MEK/ERK simultaneously as a therapeutic strategy in GNAQ/11-mutant UM.

Abstract Polymeric room‐temperature phosphorescence (RTP) materials especially multicolor RTP systems hold great promise in concrete applications. A key feature in these applications is a triplet charge transfer transition. Aromatic electron donors and electron acceptors are often essential to ensure persistent RTP. There is much interest in fabricating non‐aromatic charge‐transfer‐mediated RTP materials and it still remains a formidable challenge to achieve color‐tunable RTP via charge transfer. Herein, a charge‐transfer‐mediated RTP material by embedding quinoline derivatives within a non‐aromatic polymer matrix such as polyacrylamide (PAM) or polyvinyl alcohol (PVA) is developed. Through‐space charge transfer (TSCT) is achieved upon alkali‐ or heat treatment to realize a long phosphorescence lifetime of up to 629.90 ms, high phosphorescence quantum yield of up to 20.51%, and a green‐to‐blue afterglow for more than 20 s at room temperature. This color‐tunable RTP emerges from a nonaromatic polymer to single phosphor charge transfer that has rarely been reported before. This finding suggests that an effective and simple approach can deliver new color‐tunable RTP materials for applications including multicolor display, information encryption, and gas detection.

Acidic bacterial biofilms-associated enamel white spot lesions (WSLs) are one of the hallmarks of early caries, causing demineralization and decomposition of dental hard tissues. Therefore, to effectively prevent and treat WSLs, it is important to inhibit the activity of cariogenic bacteria while promoting the remineralization of demineralized enamel. Amorphous calcium phosphate (ACP) favors hard tissue remineralization due to its biological activity and ability to release large amounts of Ca2+ and PO43-. However, ACP-based biomineralization technology is not effective due to its lack of antimicrobial properties. Here, carboxymethyl chitosan (CMCS) was employed as a reducing agent and stabilizer, and dual-functional nanohybrids CMCS/AuNPs/ACP with biofilm resistance and mineralization properties were successfully synthesized. The addition of AuNPs enhances the antimicrobial activity and participates in regulating the formation of hydroxyapatite (HAp). The nanohybrids exhibited significant destructive effects against cariogenic bacteria and their biofilms and showed bactericidal activity under bacteria-induced acidic conditions. More importantly, this nanohybrids showed superior results in promoting the remineralization of demineralized enamel, compared to fluoride and CMCS/ACP in vitro. The CMCS/AuNPs/ACP nanohybrids not only reverse the cariogenic microenvironment at the microbial level, but also promote self-repairing of enamel WSLs regarding the microstructure. The present work offers a theoretical and experimental basis for using the CMCS/AuNPs/ACP nanohybrids as a potential dual-functional agent for the clinical treatment of enamel WSLs.

PurposeThis study aimed to develop and validate a radiogenomics nomogram for predicting microvascular invasion (MVI) in hepatocellular carcinoma (HCC) on the basis of MRI and microRNAs (miRNAs).Materials and methodsThis cohort study included 168 patients (training cohort: n = 116; validation cohort: n = 52) with pathologically confirmed HCC, who underwent preoperative MRI and plasma miRNA examination. Univariate and multivariate logistic regressions were used to identify independent risk factors associated with MVI. These risk factors were used to produce a nomogram. The performance of the nomogram was evaluated by receiver operating characteristic curve (ROC) analysis, sensitivity, specificity, accuracy, and F1-score. Decision curve analysis was performed to determine whether the nomogram was clinically useful.ResultsThe independent risk factors for MVI were maximum tumor length, rad-score, and miRNA-21 (all P < 0.001). The sensitivity, specificity, accuracy, and F1-score of the nomogram in the validation cohort were 0.970, 0.722, 0.884, and 0.916, respectively. The AUC of the nomogram was 0.900 (95% CI: 0.808–0.992) in the validation cohort, higher than that of any other single factor model (maximum tumor length, rad-score, and miRNA-21).ConclusionThe radiogenomics nomogram shows satisfactory predictive performance in predicting MVI in HCC and provides a feasible and practical reference for tumor treatment decisions.

Background and objectiveBleeding following endoscopic variceal ligation (EVL) may occur as a result of numerous factors, including a diameter of esophageal varices (EV) that is too large to be completely ligated. The present study aimed to develop an artificial intelligence-based endoscopic virtual ruler (EVR) to measure the diameter of EV with a view to finding more suitable cases for EVL.MethodsThe present study was a multicenter retrospective study that included a total of 1,062 EVLs in 727 patients with liver cirrhosis with EV, who underwent EVL from April 2016 to March 2023. Patients were divided into early rebleeding (n = 80) and non-rebleeding groups (n = 982) according to whether postoperative bleeding occurred at 6 weeks. The characteristics of patient baseline data, the status of rebleeding at 6 weeks after surgery and the survival status at 6 weeks after rebleeding were analyzed.ResultsThe early rebleeding rate following 1,062 EVL procedures was 7.5%, and the mortality rate at 6 weeks after bleeding was 16.5%. Results of the one-way binary logistic regression analysis demonstrated that the risk factors for early rebleeding following EVL included: high TB (P = 0.009), low Alb (P = 0.001), high PT (P = 0.004), PVT (P = 0.026), HCC (P = 0.018), high Child-Pugh score (P < 0.001), Child-Pugh grade C(P < 0.001), high MELD score(P = 0.004), Japanese variceal grade F3 (P < 0.001), diameter of EV (P < 0.001), and number of ligature rings (P = 0.029). Results of the multifactorial binary logistic regression analysis demonstrated that Child-Pugh grade C (P = 0.007), Japanese variceal grade F3 (P = 0.009), and diameter of EV (P < 0.001) may exhibit potential in predicting early rebleeding following EVL. ROC analysis demonstrated that the area under curve (AUC) for EV diameter was 0.848, and the AUC for Japanese variceal grade was 0.635, which was statistically significant (P < 0.001). Thus, results of the present study demonstrated that EV diameter was more optimal in predicting early rebleeding following EVL than Japanese variceal grade criteria. The cut-off value of EV diameter was calculated to be 1.35 cm (sensitivity, 70.0%; specificity, 89.2%).ConclusionIf the diameter of EV is ≥1.4 cm, there may be a high risk of early rebleeding following EVL surgery; thus, we recommend caution with EVL.

This study aimed to utilize Enterococcus lactis S-15 for the preparation of fermented shrimp gels. The gel properties and the gelation mechanism of proteins were investigated under acid-induced denaturation and protein degradation, and the quality of the gel was evaluated. Results showed that the pH of the shrimp surimi decreased from 7.35 to 4.74. The optimal gel strength observed at 24 h of fermentation was 326.41 g × cm, and disulfide bonds played a crucial role in the fermented gel. The fermented gel exhibited higher cooking loss rates and freeze-thaw loss rates compared to the heat-induced gel (control). However, fermented gels exhibited high overall acceptability both before and after cooking. The volatile basic nitrogen content in the fermented gel remained below 28.00 mg/100 g, within the safe range, and no histamine was detected. The results provide valuable data for the development and reprocessing of fermented shrimp surimi gel.

Abstract Background Sepsis can cause immune dysregulation and multiple organ failure in patients and eventually lead to death. The gut microbiota has demonstrated its precise therapeutic potential in the treatment of various diseases. This study aimed to discuss the structural changes of the gut microbiota in patients with sepsis and to analyze the differences in the gut microbiota of patients with different prognoses. Methods We conducted a multicenter study in which rectal swab specimens were collected on the first and third days of sepsis diagnosis. A total of 70 specimens were collected, and gut microbiota information was obtained by 16S rRNA analysis. Results The relative abundance of Enterococcus decreased in rectal swab specimens during the first three days of diagnosis in patients with sepsis, while the relative abundance of inflammation-associated Bacillus species such as Escherichia coli, Enterobacteriaceae, and Bacteroidetes increased. By comparing the differences in the flora of the survival group and the death group, we found that the abundance of Veillonella and Ruminococcus in the death group showed an increasing trend (p

Abstract Background This study aims to assess the influence of early serum phosphate fluctuation on the short-term prognosis of sepsis patients. Methods This retrospective study used the Medical Information Mart for Intensive Care IV database to analyze serum phosphate levels in sepsis patients within 3 days of ICU admission. According to the absolute value of delta serum phosphate (the maximum value minus the minimum value of serum phosphorus measured within three days), the patients were divided into four groups, 0–1.3, 1.4–2.0, 2.1–3.1, and ≥ 3.2 mg/dl. Meanwhile, the direction of delta serum phosphate was compared. With the serum phosphate change group of 0–1.3 mg/dl as the reference group, the relationship between delta serum phosphate and in-hospital mortality and 28-day mortality was analyzed by multivariate Logistics regression analysis. Results The study involved 1375 sepsis patients. Serum phosphate changes (0–1.3, 1.4–2.0, 2.1–3.1, and ≥ 3.2 mg/dl) correlated with in-hospital and 28-day mortality variations (p = 0.005, p = 0.008). Much higher serum phosphate fluctuation elevated in-hospital and 28-day mortality. Compared to the 0–1.3 mg/dl change group, adjusted odds ratios (OR) in other groups for in-hospital mortality were 1.25 (0.86–1.81), 1.28 (0.88–1.86), and 1.63 (1.10–2.43), and for 28-day mortality were 1.21 (0.86–1.72), 1.10 (0.77–1.57), and 1.49 (1.03–2.19). Under the trend of increasing serum phosphate, the ORs of in-hospital mortality and 28-day mortality in ≥ 3.2 mg/dl group were 2.52 and 2.01, respectively. Conclusion In conclude, the delta serum phosphate ≥ 3.2 mg/dl was associated with in-hospital mortality and 28-day mortality in patients with sepsis.

To solve the problem of tuning the weight coefficient matrices of Linear Quadratic Regulator (LQR) for vehicle active suspension system, a multi-strategy Advanced Snake Optimizer-Linear Quadratic Regulator (ASO-LQR) is proposed based on the Snake Optimizer (SO). Firstly, the dynamic model of four-freedom-degree half vehicle active suspension is established, and the LQR is set up. Secondly, the multi-strategy Advanced Snake Optimizer (ASO) is designed to address the problems of slow convergence speed and low optimization accuracy of the SO. Wherein the quality of initial snake swarm is improved through the good-point set and oppositional learning; the algorithm’s capabilities of global exploration and local exploitation are enhanced by utilizing the adaptive oscillating weight; the crossover-mutation operator of Genetic Algorithm (GA) for parallel search of solution space as well as the Levy Flight perturbation of optimal solutions is introduced to avoid local optima. Then, the ASO is combined with the LQR by a fitness function including suspension performance indexes to reduce system vibration. Finally, compared with other algorithms, such as SO, GA, Adaptive Particle Swarm Optimization (APSO), et al., the proposed ASO has higher optimization accuracy and faster convergence speed. On the above basis, through the simulation tests of C-class road, bump road and speed generalization on the C-class road, the ASO-LQR-controlled active suspension (ASO-LQR-ASS) can improve vibration damping performance more effectively.

Temperature, as a key indicator of climate change, is a constant object of research focus due to its importance in accurate forecasting. Traditional meteorological models have limitations in handling complex temperature data, and deep recurrent network techniques, known for their excellent performance in capturing long-term dependencies in time series, offer new possibilities for climate prediction. This paper adopts a decomposition strategy to address the temporal features of meteorological data and proposes a decomposition-prediction model combining seasonal and trend decomposition using LOESS and gated recurrent unit (STL-GRU) neural networks. By applying this model to datasets from three different regions in Gansu Province, China, the effectiveness of the model is demonstrated. The results show that the combination of decomposition methods and deep learning techniques improves the accuracy of seasonal variations and long-term prediction trends of temperature data, and the root-mean-square errors of the proposed model in the prediction of three real surface temperature datasets are 1.7707, 1.2681, and 1.4166, respectively.

Effective fault diagnosis is crucial for ensuring the safe and reliable operation of machinery. Despite satisfactory achievements of deep learning in fault diagnosis, acquiring large labeled datasets remains a challenge in practical industrial scenarios. In addition, machinery often operates under varying load or speed conditions, which leads to diverse distributions of collected samples. Consequently, a model trained on one distribution (source domain) encounters difficulties in adapting to another distribution (target domain). To solve the problem, this paper introduces unsupervised domain adaptation method, and also proposed unsupervised dynamic domain adaptation network (UDDAN) for fault diagnosis in bearings under variable working conditions. Specifically, the multi-scale dilated convolution module is integrated into Squeeze-and-Excitation ResNeXt (SE-ResNeXt) as a feature extractor, which not only allows the model to introduce an attention mechanism, but also enhances its multi-scale information extraction capability. The domain adaptation is achieved by minimizing the difference between the two distributions through maximum mean difference (MMD). Furthermore, the innovatively designed loss function enables the model to dynamically allocate weights between the source and target domain knowledge during the domain adaptation. Extensive experiments are conducted on two datasets, and the proposed method achieves a diagnostic accuracy of up to 99.16% in typical scenarios, while also demonstrating significant robustness in noisy environments.

With the rapid rise of online classrooms, monitoring student engagement is critical but challenging for educators. This work explores how artificial intelligence (AI) and big data techniques can automatically evaluate student concentration levels in online courses. We developed an end-to-end ResTCN model combining ResNet and temporal convolutional networks (TCN) to extract spatial and temporal video features. Further, we introduced a CutMix data augmentation method and an efficient channel attention (ECA) module to enhance model training. Evaluated on a public dataset of student videos, our approach achieved 63.28% accuracy in classifying student engagement, outperforming state-of-the-art methods. The contributions are a novel spatiotemporal neural architecture, data augmentation strategy, and attention mechanism tailored for the student engagement recognition task. This demonstrates the potential of AI in creating smart education systems.

In gradient echo MRI, quantitative susceptibility mapping (QSM) quantifies the magnetic susceptibility distributions of tissues, which has great potential in detecting brain diseases. However, QSM reconstruction is an ill-conditional inversion problem because of the zeros in the frequency domain of the dipole kernel. The intrinsic nature of the ill-posedness would affect the accuracy of quantifying tissue susceptibility. Recently, deep learning-based methods have been proposed to improve accuracy by suppressing the streaking artifacts. In this work, we proposed a hybrid architecture to enforce data consistency by involving numerical optimization blocks within convolutional neural networks (CNN), which aimed to reconstruct high-quality QSM images, referred to as NoQSM-net. The Calculation of Susceptibility through Multiple Orientation Sampling (COSMOS) QSM maps were used as labels for training. The performance of the proposed method was evaluated on two healthy volunteers and brain images of patients with diseases. Our experiments showed that the proposed method achieved good performance in terms of quantitative metrics and could effectively suppress artifacts in reconstructed QSM images, demonstrating its potential for future applications. For experiments on patients with multiple sclerosis (MS), the proposed method could better detect lesion regions in the results of NoQSM-net.

Isocorydine (ICD) exhibits strong antitumor effects on numerous human cell lines. However, the anticancer activity of ICD against oral squamous cell carcinoma (OSCC) has not been reported. The anticancer activity, migration and invasion ability, and changes in the cytoskeleton morphology and mechanical properties of ICD in OSCC were determined. Changes in the contents of reactive oxygen species (ROS), the mitochondrial membrane potential (MMP), ATP, and mitochondrial respiratory chain complex enzymes Ⅰ–Ⅳ in cancer cells were studied. ICD significantly inhibited the proliferation of oral tongue squamous cells (Cal-27), with an IC50 of 0.61 mM after 24 h of treatment. The invasion, migration, and adhesion of cancer cells were decreased, and cytoskeletal actin was deformed and depolymerized. In comparison to an untreated group, the activities of mitochondrial respiratory chain complex enzymes I-IV were significantly decreased by 50.72%, 27.39%, 77.27%, and 73.89%, respectively. The ROS production increased, the MMP decreased by 43.65%, and the ATP content decreased to 17.1 ± 0.001 (mmol/mL); ultimately, the apoptosis rate of cancer cells increased up to 10.57% after 24 h of action. These findings suggest that ICD exerted an obvious anticancer activity against OSCC and may inhibit Cal-27 proliferation and growth by causing mitochondrial dysfunction and interrupting cellular energy.

Abstract Background Observational studies have suggested a suspected association between gastroesophageal reflux disease (GERD) and respiratory diseases, but the causality remains equivocal. The goal of this study was to evaluate the causal role of GERD in respiratory diseases by employing Mendelian randomization (MR) studies. Methods We conducted Mendelian randomization analysis based on summary data of genome-wide association studies (GWASs) and three MR statistical techniques (inverse variance weighted, weighted median and MR-Egger) were employed to assess the probable causal relationship between GERD and the risk of respiratory diseases. Sensitivity analysis was also carried out to ensure more trustworthy results, which involves examining the heterogeneity, pleiotropy and leave-one-SNP-out method. We also identified 33 relevant genes and explored their distribution in 26 normal tissues. Results In the analysis, for every unit increase in developing GERD, the odds ratio for developing COPD, bronchitis, pneumonia, lung cancer and pulmonary embolism rose by 72% (ORIVW = 1.72, 95% CI 1.50; 1.99), 19% (ORIVW = 1.19, 95% CI 1.11; 1.28), 16% (ORIVW = 1.16, 95% CI 1.07; 1.26), 0. 3% (ORIVW = 1.003, 95% CI 1.0012; 1.0043) and 33% (ORIVW = 1.33, 95% CI 1.12; 1.58), respectively, in comparison with non-GERD cases. In addition, neither heterogeneity nor pleiotropy was found in the study. This study also found that gene expression was higher in the central nervous system and brain tissue than in other normal tissues. Conclusions This study provided evidence that people who developed GERD had a higher risk of developing COPD, bronchitis, pneumonia, lung cancer and pulmonary embolism. Our research suggests physicians to give effective treatments for GERD on respiratory diseases. By exploring the gene expression, our study may also help to reveal the role played by the central nervous system and brain tissue in developing respiratory diseases caused by GERD.

Background: Chronic rhinosinusitis with nasal polyps (CRSwNP) is a common chronic inflammatory disease of the nasal cavity and paranasal sinuses. The role of neutrophils in the pathogenesis of CRSwNP has attracted more attention in recent years, due to its association with more severe disease and reduced steroid responsiveness. Lipocalin-2 (LCN2) has been found to modulate neutrophils infiltration in other neutrophilic inflammation including inflammatory bowel disease, rheumatoid arthritis, and psoriasis. The aim was to evaluate the expression and regulator role of LCN2 in neutrophilic inflammation in CRSwNP, and its role as a potential biomarker predicting non-eosinophilic CRSwNP (neCRSwNP). Methods: Bioinformatic analysis, immunostainings, real-time PCR and ELISA were used to analyze the expression and location of LCN2 in nasal tissues. The expression of proinflammatory mediators were assessed in nasal tissues and secretions. LCN2 production in human nasal epithelial cells (HNECs) and neutrophils, as well as its role in neutrophilic inflammation was evaluated by in vitro experiments. Results: LCN2 was mainly located in neutrophils and HNECs of nasal polyps. LCN2 expression was also significantly higher in the polyp tissue and nasal secretions from patients with neCRSwNP. The LCN2 levels were positively correlated with type 3 inflammation markers, including G-CSF, IL-8, and IL-17. LCN2 expression could be upregulated by IL-17 A and TNF-α in HNECs, and LCN2 could also promote the expression of IL-8 in dispersed polyp cells and HNECs. Conclusions: LCN2 could serve as a novel biomarker predicting patients with neCRSwNP, and the increased expression of LCN2 may participate in the pathogenesis of neCRSwNP.

Rural household energy transition from biomass energy to modern energy is essential for poverty alleviation and sustainable development. Existing studies have explored the determinants of rural household energy transition, but few of them consider household energy availability for modern energy, which is crucial for rural household energy consumption especially in energy poverty areas such as the Tibetan Plateau. This study establishes an analytical framework for exploring the determinants of rural household energy transition by considering household energy availability and household characteristics. By employing the Tobit model, the empirical analysis of Pumqu River Basin (PRB) of the Tibetan Plateau is conducted. The results show that (1) biomass energy is still the dominant energy source in the PRB, with 99.27% of users and 90.77% of rural household energy consumption. (2) The limited energy accessibility in the PRB plays a significant negative role in accelerating rural household energy transition. (3) Educational level of householder, per capita living space, the number of rural household appliances, and community organizations are the drivers for rural household energy transition, whereas per capita livestock number and per capita grassland areas are the constraints. The findings of this study can help decision makers formulate effective measures to promote rural household energy transition in energy poverty area. The framework introduced can be extended for application to examine the determinants of rural household energy transition in other regions.

To study the characteristics and sources of nitrogen in the Baiyangdian Lake, this research conducted water quality monitoring during three hydrological periods (normal period, flood period, and dry period), and 165 pieces of routine water quality monitoring data were collected from the three national control sections for Baiyangdian Lake and its inflow rivers. By integrating water chemical analysis with multivariate statistical techniques, the study comprehensively investigated the spatiotemporal variation patterns of nitrogen in Baiyangdian Lake and identified the sources of nitrogen pollution. The results showed that the concentration of total nitrogen (TN) was highest during the dry period, reaching an average of 0.924 mg/L, and 31.3% of the sites exceeded the national Grade III surface water quality standard, reflecting a potential risk of nitrogen pollution. Based on the ion ratio method and principal component analysis (PCA), the main sources of nitrogen pollution in Baiyangdian Lake were identified as manure and domestic sewage, with agricultural fertilizers also having a certain impact on water nitrogen pollution. In addition, the study also compared the nitrogen concentration in Baiyangdian Lake with several important lakes in China. The results showed that the concentrations of TN and ammonium nitrogen (NH4+-N) in Baiyangdian Lake are lower than those in lakes in areas with similar human activity intensity, indicating that the water quality of Baiyangdian is relatively good. This study can provide a scientific basis for water quality management and pollution prevention for Baiyangdian Lake.

The stability issue of perovskite solar cells (PSCs) has long been of concern to researchers. Poly (3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS) is commonly used as a hole transport layer (HTL) in the inverted PSCs to achieve efficient and stable performance. However, PEDOT:PSS can corrode ITO, affecting device efficiency. Moreover, the hydrophilic nature of PEDOT:PSS compromises device stability. In this work, Poly (3-hexylthiophene-2,5-diyl) (P3HT), known for its good hydrophobicity, was used to modify the surface of PEDOT:PSS, reducing its water absorption and thereby enhancing the efficiency and stability of PSCs. The results reveal that incorporating P3HT effectively enhances the hydrophobicity of PEDOT:PSS. Furthermore, it fosters the development of large-grain perovskite film on the PEDOT:PSS/P3HT bilayer. This enhancement leads to a power conversion efficiency (PCE) of 19.78% for PSCs, with an increase by 16% than that of reference cells (17.04% of PCE). Following a duration of 1000 h, the PCE for the device modified with P3HT remains above 90%, while the PCE of the reference device is below 70%. These findings suggest that using P3HT in conjunction with PEDOT:PSS as a bilayer HTL can concurrently and proficiently improve the efficiency and stability of PSCs.

With the wide application of wind energy as a clean energy source, to cope with the challenge of increasing maintenance difficulty brought about by the development of large-scale wind power equipment, it is crucial to monitor the operating status of wind turbines in real time and accurately identify the specific location of faults. In this study, a CNN-LSTM-based wind motor fault detection model is constructed for four types of typical faults, namely gearbox faults, electrical faults, yaw faults, and pitch faults of wind motors, combining CNN’s advantages of excelling in feature extraction and LSTM’s advantages of dealing with long-time sequence data, to achieve the simultaneous detection of multiple fault types. The accuracy of the CNN-LSTM-based wind turbine fault detection model reaches 90.06%, and optimal results are achieved for the effective discovery of yaw system faults, pitch system faults, and gearbox faults, obtaining 94.09%, 96.46%, and 97.39%, respectively. The CNN-LSTM wind turbine fault detection model proposed in this study improves the fault detection effect, avoids the further deterioration of faults, provides direction for preventive maintenance, reduces downtime loss due to restorative maintenance, and is essential for the sustainable use of wind turbines and maintenance of wind turbine service life, which helps to improve the operation and maintenance level of wind farms.

Ischemia-reperfusion injury (IRI) encompasses the damage resulting from the restoration of blood supply following tissue ischemia. This phenomenon commonly occurs in clinical scenarios such as hemorrhagic shock, severe trauma, organ transplantation, and thrombolytic therapy. Despite its prevalence, existing treatments exhibit limited efficacy against IRI. Vagus nerve stimulation (VNS) is a widely utilized technique for modulating the autonomic nervous system. Numerous studies have demonstrated that VNS significantly reduces IRI in various organs, including the heart, brain, and liver. This article reviews the pathological processes during IRI and summarizes the role and possible mechanisms of VNS in IRI of different organs. Furthermore, this review addresses the current challenges of VNS clinical applications, providing a novel perspective on IRI treatment.

Streamflow and flood forecasting remains one of the long-standing challenges in hydrology. Traditional physically based models are hampered by sparse parameters and complex calibration procedures particularly in ungauged catchments. We propose a novel hybrid deep learning model termed encoder-decoder double-layer long short-term memory (ED-DLSTM) to address streamflow forecasting at global scale for all (gauged and ungauged) catchments. Using historical datasets, ED-DLSTM yields a mean Nash-Sutcliffe efficiency coefficient (NSE) of 0.75 across more than 2,000 catchments from the United States, Canada, Central Europe, and the United Kingdom, highlighting improvements by the state-of-the-art machine learning over traditional hydrologic models. Moreover, ED-DLSTM is applied to 160 ungauged catchments in Chile and 76.9% of catchments obtain NSE >0 in the best situation. The interpretability of cross-region capacities of ED-DLSTM are established through the cell state induced by adding a spatial attribute encoding module, which can spontaneously form hydrological regionalization effects after performing spatial coding for different catchments. The study demonstrates the potential of deep leaning methods to overcome the ubiquitous lack of hydrologic information and deficiencies in physical model structure and parameterization.

IntroductionFace recognition has been a longstanding subject of interest in the fields of cognitive neuroscience and computer vision research. One key focus has been to understand the relative importance of different facial features in identifying individuals. Previous studies in humans have demonstrated the crucial role of eyebrows in face recognition, potentially even surpassing the importance of the eyes. However, eyebrows are not only vital for face recognition but also play a significant role in recognizing facial expressions and intentions, which might occur simultaneously and influence the face recognition process.MethodsTo address these challenges, our current study aimed to leverage the power of deep convolutional neural networks (DCNNs), an artificial face recognition system, which can be specifically tailored for face recognition tasks. In this study, we investigated the relative importance of various facial features in face recognition by selectively blocking feature information from the input to the DCNN. Additionally, we conducted experiments in which we systematically blurred the information related to eyebrows to varying degrees.ResultsOur findings aligned with previous human research, revealing that eyebrows are the most critical feature for face recognition, followed by eyes, mouth, and nose, in that order. The results demonstrated that the presence of eyebrows was more crucial than their specific high-frequency details, such as edges and textures, compared to other facial features, where the details also played a significant role. Furthermore, our results revealed that, unlike other facial features, the activation map indicated that the significance of eyebrows areas could not be readily adjusted to compensate for the absence of eyebrow information. This finding explains why masking eyebrows led to more significant deficits in face recognition performance. Additionally, we observed a synergistic relationship among facial features, providing evidence for holistic processing of faces within the DCNN.DiscussionOverall, our study sheds light on the underlying mechanisms of face recognition and underscores the potential of using DCNNs as valuable tools for further exploration in this field.

In plant horticulture, furrow fertilizing is a common method to promote plant nutrient absorption and to effectively avoid fertilizer waste. Considering the high resistance caused by soil compaction in southern orchards, an energy-saving ditching device was proposed. A standard ditching blade with self-excited vibration device was designed, and operated in sandy clay with a tillage depth of 30cm. To conduct self-excited vibration ditching experiments, a simulation model of the interaction between soil and the ditching mechanism was established by coupling the ADAMS and EDEM software. To begin with, the ditching device model was first set up, taking into account its motion and morphological characteristics. Then, the MBD-DEM coupling method was employed to investigate the interaction mechanism and the effect of ditching between the soil particles and the ditching blade. Afterwards, the time-domain and frequency-domain characteristics of vibration signals during the ditching process were analyzed using the fast fourier transform (FFT) method, and the energy distribution characteristics were extracted using power spectral density (PSD). The experimental results revealed that the vibrations ditching device has reciprocating displacement in the Dx direction and torsional displacements in the θy and θz directions during operation, verifying the correctness of the coupling simulation and the effectiveness of vibrations ditching resistance reduction. Also, a load vibrations ditching bench test was conducted, and the results demonstrated that the self-excited vibrations ditching device, compared with common ditching device, achieved a reduction in ditching resistance of up to 12.3%. The reasonable parameters of spring stiffness, spring damping, and spring quality in self-excited vibrations ditching device can achieve a satisfied ditching performance with relatively low torque consumption at an appropriate speed.

BackgroundThe COVID-19 pandemic has presented unique challenges to individuals worldwide, with a significant focus on the impact on sleep. However, the precise mechanisms through which emotional and cognitive variables mediate this relationship remain unclear. To expand our comprehensive understanding of variables, the present study utilizes the Preventive Stress Management theory, to test the relationship between perceived social support and sleep quality, as well as the effect of perceived COVID-19 stress, hope, negative emotions and coping styles.MethodsData were collected in March 2022 from 1,034 college students in two universities located in Liaoning Province, China, using an online survey platform regarding perceived social support, perceived COVID-19 stress, sleep quality, hope, negative emotions and coping styles. The moderated mediation model were conducted using Process macro program (Model 6) and the syntax in SPSS.ResultsThe results revealed perceived COVID-19 stress and negative emotions sequentially mediated the negative relationship between perceived social support and sleep quality. Furthermore, hope and coping styles were found to moderate the sequential mediating effect.ConclusionThe present study sheds light on the pathways that affect sleep quality among college students during the COVID-19 pandemic. Findings highlight the protective roles played by positive social and personal resources, such as perceived social support, hope, and effective coping styles, against sleep problems. These insights have important implications for the development of targeted interventions to improve sleep outcomes during this challenging time.

The multiple species characteristics of traditional Chinese medicines (TCMs) are crucial for expanding TCMs sources, meeting the needs of the pharmaceutical industry and ensuring clinical requirements. It’s also one of the significant factors affecting the quality control of TCMs. Systematic differential analysis of original species in TCMs is an important link in achieving comprehensive quality control, ensuring the effectiveness and safety of clinical medication. The study aims to establish a reliable and efficient approach to screen combinatorial discriminatory quality markers for rapid differentiation of original species by metabolomics coupled with DNA barcoding as a case of Cimicifugae Rhizoma. DNA barcoding is used to identify the origin of Cimicifugae Rhizoma. The data-dependent acquisition mode integrated with the computerized intelligent filtering system was established for in-depth characterization of metabolites from Cimicifugae Rhizoma using ultra-high performance liquid chromatography to quadrupole time-of-flight mass spectrometry (UHPLC-Q-TOF-MS). The untargeted metabolomics combined with multivariate statistical analysis was performed to screen and identify the potential combinatorial discriminatory quality markers. Finally, quantitative analysis and predictive model of these markers were employed to validate the feasibility of this strategy to distinguish the original species. Based on the scores of variable importance in projection greater than 1.0 and t-test (p