Optimizing entropy weight model to accurately predict variation of pharmaceuticals and personal care products in the estuaries and coasts of the South China.

Pharmaceuticals and personal care products (PPCPs) have raised increasing concern worldwide due to their continuous release and potential hazards to the ecosystem and human health. This study optimized the entropy weight model (EW-WRSR) that combines entropy weight with multi-criteria decision analysis to investigate pollution patterns of PPCPs in the coasts and estuaries. The results revealed that occurrences of PPCPs from the 1940s to the present were consistent with using PPCPs, different types of human activities, and local urban development. This helped better understand the history of PPCP contamination and evaluate the uncertainty of EW-WRSR. The model predicted hotspots of PPCPs that were consistent with the actual situation, indicating that PPCPs mainly enter the nearshore ecosystem by the form of sewage discharge and residual aquaculture. This study can provide method that identifying highly contaminated regions on a global scale.

Intelligent skin-removal photoacoustic computed tomography for human based on deep learning.

Photoacoustic computed tomography (PACT) has centimeter-level imaging ability and can be used to detect the human body. However, strong photoacoustic signals from skin cover deep tissue information, hindering the frontal display and analysis of photoacoustic images of deep regions of interest. Therefore, we propose a 2.5 D deep learning model based on feature pyramid structure and single-type skin annotation to extract the skin region, and design a mask generation algorithm to remove skin automatically. PACT imaging experiments on the human periphery blood vessel verified the correctness our proposed skin-removal method. Compared with previous studies, our method exhibits high robustness to the uneven illumination, irregular skin boundary, and reconstruction artifacts in the images, and the reconstruction errors of PACT images decreased by 20% ~ 90% with a 1.65 dB improvement in the signal-to-noise ratio at the same time. This study may provide a promising way for high-definition PACT imaging of deep tissues.

Hepatic miR-363 promotes non-alcoholic fatty liver disease by suppressing INSIG1.

Non-alcoholic fatty liver disease (NAFLD) constitutes one of major worldwide health problem which typically progressively results in non-alcoholic steatohepatitis (NASH) and eventually cirrhosis and liver cancer. Liver-specific deletion of INSIG1 promotes SREBP1 nuclear translocation to activate downstream lipogenic genes expression, leading to lipid accumulation. However, the underlying pathogenesis of NAFLD, and particularly involved in miRNA participation are still to be thoroughly explored. Here, we found that miR-363-3p was significantly overexpressed in high-fat, high-cholesterol (HFHC) diet mice liver tissue and fatty acid-induced steatosis cells. miR-363-3p directly targets INSIG1 to inhibit its expression, thereby facilitating the cleavage of SREBP and nuclear translocation to activate subsequent transcription of lipogenic genes in vitro and in vivo. In addition, we identified apigenin, a natural flavonoid compound, inhibited miR-363-3p expression to up-regulate INSIG1 and suppress nuclear translocation of SREBP1, thereby down-regulated lipogenic genes expression in steatosis cells and HFHC diet mice liver tissues. Taken together, our results demonstrated that miR-363-3p as a key regulator of hepatic lipid homeostasis targeted INSIG1, and apigenin alleviated NAFLD through the miR-363-3p/INSIG1/SREBP1 pathway. This indicates that reduction of miR-363-3p levels as a possible treatment of hepatic steatosis and provides a potential new therapeutic strategy for targeting miRNA to ameliorate NAFLD.

Intact painful sensation but enhanced non-painful sensation in individuals with autistic traits.

Somatosensory abnormalities are commonly recognized as diagnostic criteria in autism spectrum disorder (ASD), and may also exist in individuals with autistic traits. The present research included two studies to explore the painful and non-painful sensation and their cognitive-neurological mechanisms of individuals with autistic traits. Study 1 included 358 participants to assess the relationship between autistic traits and pain/non-pain sensitivities using questionnaires: the Autism Spectrum Quotient (AQ), the Pain Sensitivity Questionnaire, and the Highly Sensitive Person Scale, respectively. Study 1 found that autistic traits were positively correlated with non-pain sensitivity, but not associated with pain sensitivity. Study 2 recruited 1,167 participants whose autistic traits were assessed using the AQ. Subsequently, thirty-three participants who scored within the top 10% and bottom 10% on the AQ were selected into High-AQ and Low-AQ groups, respectively, to explore the cognitive-neural responses of individuals with autistic traits to both painful and non-painful stimuli with event-related potential (ERP) technology. Results of Study 2 showed that the High-AQ group showed higher intensity ratings, more negative emotional reactions, and larger N1 amplitudes than the Low-AQ group to the non-painful stimuli, but no difference of response to the painful stimuli was found between High-AQ and Low-AQ groups. These findings suggest that individuals with autistic traits may experience enhanced non-painful sensation but intact painful sensation.

Changes in the Objective Vision Quality of Adolescents in a Mesopic Visual Environment After Wearing Orthokeratology Lenses: A Prospective Study.

PURPOSE: This study aimed to investigate changes in objective vision quality in mesopic environments in teenagers with myopia after wearing orthokeratology (OK) lenses. METHODS: This prospective clinical study included 45 patients (80 eyes) who received OK lenses at the First Affiliated Hospital of Jinan University from March 2021 to September 2021. An Optical Path Difference-Scan III refractive power/corneal analyzer was used to determine the corneal topographic parameters (corneal e, corneal Q, surface asymmetry index (SAI), and surface regularity index (SRI)), higher-order aberrations (HOAs), axial length (AL) change, lens decentration, induced astigmatism, target power, and Strehl ratio (SR) in a mesopic visual environment after wearing OK lenses for 6 months. In addition, corneal morphological parameters, HOAs, and SR were analyzed in a mesopic visual environment. Finally, we investigated the correlations among corneal morphology, HOAs, AL change, lens decentration, induced astigmatism, and SR. RESULTS: The SAI value was significantly higher (P<0.01), and the corneal e was significantly lower (P<0.01), in a mesopic visual environment after wearing OK lenses for 1 week than baseline. A significant increase was observed in total HOAs and spherical aberrations, compared with before the OK lenses were worn (P<0.01). In addition, SR in the mesopic visual environment decreased significantly after wearing the lenses (P<0.01). No significant differences were observed (P>0.05) among the 1-week, 1-month, 3-month, and 6-month follow-up findings. After 6 months, AL and lens decentration did not differ significantly compared with before (P>0.05), whereas induced astigmatism significantly increased (P<0.05). Negative correlations were observed between corneal Q, SAI, SRI, HOAs, induced astigmatism, and SR, and positive correlations were found between corneal e, AL change, lens decentration, and SR, after wearing OK lenses. KEY POINTS: • Wearing orthokeratology lenses significantly altered corneal morphology and HOAs in myopic teenagers within 1 week. • The changes that we observed in the eyes of adolescents with myopia after wearing orthokeratology lenses decreased vision quality in mesopic environments. • Strehl ratio is significantly correlated with multiple parameters, including HOAs, AL change, and lens decentration. CONCLUSIONS: In teenagers with myopia wearing OK lenses, significant changes in vision quality and corneal morphology were observed, leading to increased aberrations and affecting optical imaging quality. Furthermore, SR is significantly correlated with multiple parameters, including HOAs, AL change, and lens decentration. REGISTRATION NUMBER: This study is registered with the United States Clinical Trials Registry under registration number NCT04929119.

Follicular fluid lipidomics analysis reveals altered lipid signatures in patients with polycystic ovary syndrome.

BACKGROUND: This research investigates the metabolic profiles of follicular fluid (FF) samples from patients with polycystic ovary syndrome (PCOS) undergoing in vitro fertilisation and aims to identify diagnostic and therapeutic biomarkers for PCOS through lipidomic analysis. METHODS: We performed non-targeted lipid analysis of FF samples from women with PCOS (n = 6) and normal controls (n = 6) using ultra-high-performance liquid chromatography-tandem mass spectrometry. Differential lipids between the two groups were screened using multidimensional statistical analysis, followed by fold change analysis and t-tests to identify potential PCOS biomarkers. RESULTS: Multivariate statistical analysis revealed significant differences in FF lipid levels between the PCOS and control groups. Five different lipids were selected as standards, with p < .05. Phosphatidylcholine (PC), the main differentially expressed lipid, was significantly increased in the FF of the POCS group and was closely related to other lipids. CONCLUSIONS: Using ultra-high-performance liquid chromatography-tandem mass spectrometry, we investigated lipid biomarkers based on FF lipidomics to provide useful information for the discovery of diagnostic markers for PCOS. Our study identified five distinct lipids as potential markers of PCOS, with PC being the primary aberrant lipid found in the FF of patients with PCOS.

Follicular fluid (FF) is a complex microenvironment involved in oocyte growth, follicular maturation and germ cell­somatic cell communication. All metabolites during oocyte growth are collected from the FF. This study used lipidomic analysis to identify differences in FF lipids between normal women and those diagnosed with polycystic ovary syndrome (PCOS). The pathogenesis of PCOS is associated with abnormal metabolism of glyceroglycolipids and sphingomyelin. Here, we found that phosphatidylcholine is the main abnormal lipid in FF in patients with PCOS. Our study informs the future research into the development of diagnostic markers for PCOS to be used in clinical practice.

Transcription factor TaNF-YB2 interacts with partners TaNF-YA7/YC7 and transcriptionally activates distinct stress-defensive genes to modulate drought tolerance in T. Aestivum.

BACKGROUND: Drought stress limits significantly the crop productivity. However, plants have evolved various strategies to cope with the drought conditions by adopting complex molecular, biochemical, and physiological mechanisms. Members of the nuclear factor Y (NF-Y) transcription factor (TF) family constitute one of the largest TF classes and are involved in plant responses to abiotic stresses. RESULTS: TaNF-YB2, a NY-YB subfamily gene in T. aestivum, was characterized in this study focusing on its role in mediating plant adaptation to drought stress. Yeast two-hybrid (Y-2 H), biomolecular fluoresence complementation (BiFC), and Co-immunoprecipitation (Co-IP) assays indicated that TaNF-YB2 interacts with the NF-YA member TaNF-YA7 and NF-YC family member TaNF-YC7, which constitutes a heterotrimer TaNF-YB2/TaNF-YA7/TaNF-YC7. The TaNF-YB2 transcripts are induced in roots and aerial tissues upon drought signaling; GUS histochemical staining analysis demonstrated the roles of cis-regulatory elements ABRE and MYB situated in TaNF-YB2 promoter to contribute to target gene response to drought. Transgene analysis on TaNF-YB2 confirmed its functions in regulating drought adaptation via modulating stomata movement, osmolyte biosynthesis, and reactive oxygen species (ROS) homeostasis. TaNF-YB2 possessed the abilities in transcriptionally activating TaP5CS2, the P5CS family gene involving proline biosynthesis and TaSOD1, TaCAT5, and TaPOD5, the genes encoding antioxidant enzymes. Positive correlations were found between yield and the TaNF-YB2 transcripts in a core panel constituting 45 wheat cultivars under drought condition, in which two types of major haplotypes including TaNF-YB2-Hap1 and -Hap2 were included, with the former conferring more TaNF-YB2 transcripts and stronger plant drought tolerance. CONCLUSIONS: TaNF-YB2 is transcriptional response to drought stress. It is an essential regulator in mediating plant drought adaptation by modulating the physiological processes associated with stomatal movement, osmolyte biosynthesis, and reactive oxygen species (ROS) homeostasis, depending on its role in transcriptionally regulating stress response genes. Our research deepens the understanding of plant drought stress underlying NF-Y TF family and provides gene resource in efforts for molecular breeding the drought-tolerant cultivars in T. aestivum.

Effects of xenogeneic transplantation of umbilical cord-derived mesenchymal stem cells combined with irbesartan on renal podocyte damage in diabetic rats.

BACKGROUND: The leading cause of end-stage renal disease (ESRD) is diabetic nephropathy (DN). Podocyte damage is an early event in the development of DN. Currently, there is no effective treatment strategy that can slow the progression of DN or reverse its onset. The role of mesenchymal stem cells (MSCs) transplantation in diabetes and its complications has been extensively studied, and diabetic nephropathy has been a major focus. Irbesartan exerts reno-protective effects independent of lowering blood pressure, can reduce the incidence of proteinuria in rats, and is widely used clinically. However, it remains undetermined whether the combined utilization of the angiotensin II receptor antagonist irbesartan and MSCs could enhance efficacy in addressing DN. METHODS: A commonly used method for modeling type 2 diabetic nephropathy (T2DN) was established using a high-fat diet and a single low-dose injection of STZ (35 mg/kg). The animals were divided into the following 5 groups: (1) the control group (CON), (2) the diabetic nephropathy group (DN), (3) the mesenchymal stem cells treatment group (MSCs), (4) the irbesartan treatment group (Irb), and (5) the combined administration group (MSC + Irb). MSCs (2 × 106 cells/rat) were injected every 10 days through the tail vein for a total of three injections; irbesartan (30 mg/kg/d) was administered by gavage. Additionally, the safety and homing of mesenchymal stem cells were verified using positron emission tomography (PET) imaging. RESULTS: The combination treatment significantly reduced the UACR, kidney index, IGPTT, HOMA-IR, BUN, serum creatine, and related inflammatory factor levels and significantly improved renal function parameters and the expression of proteins related to glomerular podocyte injury in rats. Moreover, MSCs can homing target to damaged kidneys. CONCLUSIONS: Compared to the administration of MSCs or irbesartan alone, the combination of MSCs and irbesartan exerted better protective effects on glomerular podocyte injury, providing new ideas for the clinical application of mesenchymal stem cells.

Recognition of screening out hierarchical toxic contaminants tuned by quantified pseudo-components from complex engineering co-combustion.

Co-combustion of industrial and municipal solid wastes has emerged as the most promising disposal technology, yet its effect on unknown contaminants generation remains rarely revealed due to waste complexity. Hence, six batches of large-scale engineering experiments were designed in an incinerator of 650 t/d, which overcame the inauthenticity and deviation of laboratory tests. 953-1772 non-targeted compounds were screened in fly ash. Targeting the impact of co-combustion, a pseudo-component matrix model was innovatively integrated to quantitatively extract nine components from complex wastes grouped into biomass and plastic. Thus, the influence was evaluated across eight dimensions, covering molecular characteristics and toxicity. The effect of co-combustion with biomass pseudo-components was insignificant. However, co-combustion with high ratios of plastic pseudo-components induced higher potential risks, significantly promoting the formation of unsaturated hydrocarbons, highly unsaturated compounds (DBE≥15), and cyclic compounds by 19 %- 49 %, 17 %- 31 %, and 7 %- 27 %, respectively. Especially, blending with high ratios of PET plastic pseudo-components produced more species of contaminants. Unique 2 Level I toxicants, bromomethyl benzene and benzofuran-2-carbaldehyde, as well as 4 Level II toxicants, were locked, receiving no concern in previous combustion. The results highlighted risks during high proportion plastics co-combustion, which can help pollution reduction by tuning source wastes to enable healthy co-combustion.

Complete genome sequence of Enterococcus faecalis B05.

Enterococcus faecalis, a gram-positive bacterium, is the main intestinal bacteria in humans and animals. We report here the complete genome sequence of E. faecalis B05, whose genome length is 2,745,741 bp, containing 2,503 protein-coding genes, with a GC content of 37.64%.

Simultaneous removal of noise and correction of motion warping in neuron calcium imaging using a pipeline structure of self-supervised deep learning models.

Calcium imaging is susceptible to motion distortions and background noises, particularly for monitoring active animals under low-dose laser irradiation, and hence unavoidably hinder the critical analysis of neural functions. Current research efforts tend to focus on either denoising or dewarping and do not provide effective methods for videos distorted by both noises and motion artifacts simultaneously. We found that when a self-supervised denoising model of DeepCAD [Nat. Methods18, 1359 (2021)10.1038/s41592-021-01225-0] is used on the calcium imaging contaminated by noise and motion warping, it can remove the motion artifacts effectively but with regenerated noises. To address this issue, we develop a two-level deep-learning (DL) pipeline to dewarp and denoise the calcium imaging video sequentially. The pipeline consists of two 3D self-supervised DL models that do not require warp-free and high signal-to-noise ratio (SNR) observations for network optimization. Specifically, a high-frequency enhancement block is presented in the denoising network to restore more structure information in the denoising process; a hierarchical perception module and a multi-scale attention module are designed in the dewarping network to tackle distortions of various sizes. Experiments conducted on seven videos from two-photon and confocal imaging systems demonstrate that our two-level DL pipeline can restore high-clarity neuron images distorted by both motion warping and background noises. Compared to typical DeepCAD, our denoising model achieves a significant improvement of approximately 30% in image resolution and up to 28% in signal-to-noise ratio; compared to traditional dewarping and denoising methods, our proposed pipeline network recovers more neurons, enhancing signal fidelity and improving data correlation among frames by 35% and 60% respectively. This work may provide an attractive method for long-term neural activity monitoring in awake animals and also facilitate functional analysis of neural circuits.

Microglial purinergic signaling in Alzheimer's disease.

Alzheimer's disease (AD) is a progressive and fatal neurodegenerative disease. The prevalent features of AD pathogenesis are the appearance of ß-amyloid (Aß) plaques and neurofibrillary tangles, which cause microglial activation, synaptic deficiency, and neuronal loss. Microglia accompanies AD pathological processes and is also linked to cognitive deficits. Purinergic signaling has been shown to play a complex and tight interplay with the chemotaxis, phagocytosis, and production of pro-inflammatory factors in microglia, which is an important mechanism for regulating microglia activation. Here, we review recent evidence for interactions between AD, microglia, and purinergic signaling and find that the purinergic P2 receptors pertinently expressed on microglia are the ionotropic receptors P2X4 and P2X7, and the subtypes of P2YRs expressed by microglia are metabotropic receptors P2Y2, P2Y6, P2Y12, and P2Y13. The adenosine P1 receptors expressed in microglia include A1R, A2AR, and A2BR. Among them, the activation of P2X4, P2X7, and adenosine A1, A2A receptors expressed in microglia can aggravate the pathological process of AD, whereas P2Y2, P2Y6, P2Y12, and P2Y13 receptors expressed by microglia can induce neuroprotective effects. However, A1R activation also has a strong neuroprotective effect and has a significant anti-inflammatory effect in chronic neuroinflammation. These receptors regulate a variety of pathophysiological processes in AD, including APP processing, Aß production, tau phosphorylation, neuroinflammation, synaptic dysfunction, and mitochondrial dysfunction. This review also provides key pharmacological advances in purinergic signaling receptors.

Effectiveness of instant versus text messaging intervention on antiretroviral therapy adherence among men who have sex with men living with HIV.

Objective: This study aimed to compare the effectiveness of instant versus text messaging intervention (TMI) on antiretroviral therapy (ART) adherence among men who have sex with men (MSM) living with HIV. Methods: This study was conducted in an infectious disease hospital of Jinan, China from October 2020 to June 2021, using non-randomized concurrent controlled design to compare the effectiveness of instant messaging intervention (IMI) versus TMI. The intervention strategies (health messaging, medication reminder, and peer education) and contents were consistent between the two groups, and the difference was service delivery method and type of information. The primary outcome was the proportion of achieving optimal ART adherence, defined as never missing any doses and delayed any doses more than 1 hour. Results: A total of 217 participants (including 72 in TMI group and 145 in IMI group) were included in the study. The proportion of achieving optimal adherence was higher in IMI group than TMI group at the first follow-up (90.2% versus 77.6%, p = 0.021) and second follow-up (86.5% versus 76.6%, p = 0.083). The effect of IMI versus TMI on improving ART adherence was found not to be statistically significant (risk ratio (RR) = 1.93, 95% confidence interval (CI): 0.95-3.94) in complete-case analysis. However, when excluding participants who did not adhere to the interventions, a significant improvement was observed (RR = 2.77, 95%CI: 1.21-6.38). More participants in IMI group expressed highly rated satisfaction to the intervention services than those in TMI group (67.3% versus 50.0%). Conclusions: The IMI demonstrated superior efficacy over TMI in improving ART adherence and satisfaction with intervention services. It is suggested that future digital health interventions targeting ART adherence should prioritize instant messaging with multimedia information in areas with Internet access. Trial registration: The study was registered at the Chinese Clinical Trial Register (ChiCTR), with number [ChiCTR2000041282].

Decreasing Greenhouse Gas Emissions from the Municipal Solid Waste Sector in Chinese Cites.

Municipal solid waste (MSW) management systems play a crucial role in greenhouse gas (GHG) emissions in China. Although the government has implemented many policies to improve the MSW management system, the impact of these improvements on city-level GHG emission reduction remains largely unexplored. This study conducted a comprehensive analysis of both direct and downstream GHG emissions from the MSW sector, encompassing sanitary landfill, dump, incineration, and biological treatment, across 352 Chinese cities from 2001 to 2021 by adopting inventory methods recommended by the Intergovernmental Panel on Climate Change (IPCC). The results reveal that (1) GHG emissions from the MSW sector in China peaked at 70.6 Tg of CO2 equiv in 2018, followed by a significant decline to 47.6 Tg of CO2 equiv in 2021, (2) cities with the highest GHG emission reduction benefits in the MSW sector were historical emission hotspots over the past 2 decades, and (3) with the potential achievement of zero-landfilling policy by 2030, an additional reduction of 203.7 Tg of CO2 equiv is projected, with the emission reduction focus toward cities in South China (21.9%), Northeast China (17.8%), and Southwest China (17.3%). This study highlights that, even without explicit emission reduction targets for the MSW sector, the improvements of this sector have significantly reduced GHG emissions in China.

Development and validation of the parental health literacy scale for children with asthma (PHLSCA).

OBJECTIVE: This study aimed to develop and validate an instrument to assess the health literacy of parents of children with asthma in a Chinese context. METHODS: The preliminary Parental Health Literacy Scale for Children with Asthma (PHLSCA) was developed based on a literature review and refined to 45 items through two rounds of expert consultation using the Delphi method. A total of 481 parents of children with asthma were recruited from seven hospitals across four provinces in China between February and April 2019. Principal component analysis (PCA) and confirmatory factor analysis were conducted to evaluate the structural and construct validity of the scale. RESULTS: The development and validation processes led to a 38 items scale comprising three subscales, namely: Health Knowledge (11 items), Health Skills (19 items) and Health Behavior (8 items). The scale demonstrated good reliability, with an internal consistency of Cronbach's α = 0.956 and a split-half reliability of r = 0.887 (p < 0.01). The Item Content Validity Index (I-CVI) ranged from 0.81 to 1.00, and the Scale-CVI was 0.842. The correlation coefficients and factor analysis results indicated good construct validity, with the factors explaining 59.33% to 62.90% of the variance in each subscale. CONCLUSIONS: The final version of the questionnaire (PHLSCA) has been demonstrated to be a valid and reliable tool for assessing the health literacy of parents of Chinese children with asthma.

ATN-Res2Unet: an advanced deep learning network for the elimination of saturation artifacts in endoscopy optical coherence tomography.

Endoscopic optical coherence tomography (OCT) possesses the capability to non-invasively image internal lumens; however, it is susceptible to saturation artifacts arising from robust reflective structures. In this study, we introduce an innovative deep learning network, ATN-Res2Unet, designed to mitigate saturation artifacts in endoscopic OCT images. This is achieved through the integration of multi-scale perception, multi-attention mechanisms, and frequency domain filters. To address the challenge of obtaining ground truth in endoscopic OCT, we propose a method for constructing training data pairs. Experimental in vivo data substantiates the effectiveness of ATN-Res2Unet in reducing diverse artifacts while preserving structural information. Comparative analysis with prior studies reveals a notable enhancement, with average quantitative indicators increasing by 45.4-83.8%. Significantly, this study marks the inaugural exploration of leveraging deep learning to eradicate artifacts from endoscopic OCT images, presenting considerable potential for clinical applications.

Origin of the light-induced spin currents in heavy metal/magnetic insulator bilayers.

Light-induced spin currents with the faster response is essential for the more efficient information transmission and processing. Herein, we systematically explore the effect of light illumination energy and direction on the light-induced spin currents in the W/Y3Fe5O12 heterojunction. Light-induced spin currents can be clearly categorized into two types. One is excited by the low light intensity, which mainly involves the photo-generated spin current from spin photovoltaic effect. The other is caused by the high light intensity, which is the light-thermally induced spin current and mainly excited by spin Seebeck effect. Under low light-intensity illumination, light-thermally induced temperature gradient is very small so that spin Seebeck effect can be neglected. Furthermore, the mechanism on spin photovoltaic effect is fully elucidated, where the photo-generated spin current in Y3Fe5O12 mainly originates from the process of spin precession induced by photons. These findings provide some deep insights into the origin of light-induced spin current.

SOAT1 regulates cholesterol metabolism to induce EMT in hepatocellular carcinoma.

Cholesterol metabolism reprogramming is one of the significant characteristics of hepatocellular carcinoma (HCC). Cholesterol increases the risk of epithelial-mesenchymal transition (EMT) in cancer. Sterol O-acyltransferases 1 (SOAT1) maintains the cholesterol homeostasis. However, the exact mechanistic contribution of SOAT1 to EMT in HCC remains unclear. Here we demonstrated that SOAT1 positively related to poor prognosis of HCC, EMT markers and promoted cell migration and invasion in vitro, which was mediated by the increased cholesterol in plasmalemma and cholesterol esters accumulation. Furthermore, we reported that SOAT1 disrupted cholesterol metabolism homeostasis to accelerate tumorigenesis and development in HCC xenograft and NAFLD-HCC. Also, we detected that nootkatone, a sesquiterpene ketone, inhibited EMT by targeting SOAT1 in vitro and in vivo. Collectively, our finding indicated that SOAT1 promotes EMT and contributes to hepatocarcinogenesis by increasing cholesterol esterification, which is suppressed efficiently by nootkatone. This study demonstrated that SOAT1 is a potential biomarker and therapeutic target in NAFLD-HCC and SOAT1-targeting inhibitors are expected to be the potential new therapeutic treatment for HCC.

Nano-integrating green and low-carbon concepts into ideological and political education in higher education institutions through K-means clustering.

Universities and colleges play a pivotal role in the pursuit of a future that is sustainable through their pedagogical efforts and the execution of state-of-the-art research endeavors aimed at mitigating the effects of climate change. Higher Education Institutions (HEIs) serve as crucial catalysts in advancing sustainable development. HEIs are increasingly embracing precise measures to reduce their carbon footprint (CF) while also educating students on global sustainability. These nano-methods provide a quantitative framework for assessing a campus's sustainability efforts in line with Green Campus (GC) initiatives to lower carbon emissions align with GC goals. This study employs K-means clustering to analyze the integration of green and low-carbon principles in higher education political and ideological studies. Its goal is to identify patterns, assess teaching effectiveness, and improve sustainability education, aligning with Green Campus initiatives to enhance institutional contributions to sustainable growth through informed pedagogical strategies. Input data includes curriculum content, teaching methods, student engagement, and institutional goals related to sustainability. Seeking to improve sustainability education align with Green Campus initiatives, higher education can strategically enhance their contributions to long-term sustainability and growth through effective pedagogical approaches. Cluster 3 has the lowest WCSS value of 1200, indicating tighter cohesion and less variability within this cluster compared to Cluster 1 (1500) and Cluster 2 (1800). Cluster 3 stands out with the highest silhouette score of 0.7, suggesting well-defined and distinct clusters, while Cluster 2 has the lowest score of 0.4, indicating some overlap or ambiguity in data points. Cluster 1 has the lowest Davies-Bouldin Index of 0.4, implying better separation between clusters compared to Cluster 2 (0.6) and Cluster 3 (0.5). Cluster 3 is well-defined and cohesive, showing strong integration of green practices. Cluster 1 displays good separation and cohesion, while Cluster 2 requires refinement due to potential overlap in sustainability integration.