High-resolution detection of copy number alterations in single cells with HiScanner.

Improvements in single-cell whole-genome sequencing (scWGS) assays have enabled detailed characterization of somatic copy number alterations (CNAs) at the single-cell level. Yet, current computational methods are mostly designed for detecting chromosome-scale changes in cancer samples with low sequencing coverage. Here, we introduce HiScanner (High-resolution Single-Cell Allelic copy Number callER), which combines read depth, B-allele frequency, and haplotype phasing to identify CNAs with high resolution. In simulated data, HiScanner consistently outperforms state-of-the-art methods across various CNA types and sizes. When applied to high-coverage scWGS data from human brain cells, HiScanner shows a superior ability to detect smaller CNAs, uncovering distinct CNA patterns between neurons and oligodendrocytes. For 179 cells we sequenced from longitudinal meningioma samples, integration of CNAs with point mutations revealed evolutionary trajectories of tumor cells. These findings show that HiScanner enables accurate characterization of frequency, clonality, and distribution of CNAs at the single-cell level in both non-neoplastic and neoplastic cells.

The immune landscape of sepsis and using immune clusters for identifying sepsis endotypes.

Background: The dysregulated immune response to sepsis still remains unclear. Stratification of sepsis patients into endotypes based on immune indicators is important for the future development of personalized therapies. We aimed to evaluate the immune landscape of sepsis and the use of immune clusters for identifying sepsis endotypes. Methods: The indicators involved in innate, cellular, and humoral immune cells, inhibitory immune cells, and cytokines were simultaneously assessed in 90 sepsis patients and 40 healthy controls. Unsupervised k-means cluster analysis of immune indicator data were used to identify patient clusters, and a random forest approach was used to build a prediction model for classifying sepsis endotypes. Results: We depicted that the impairment of innate and adaptive immunity accompanying increased inflammation was the most prominent feature in patients with sepsis. However, using immune indicators for distinguishing sepsis from bacteremia was difficult, most likely due to the considerable heterogeneity in sepsis patients. Cluster analysis of sepsis patients identified three immune clusters with different survival rates. Cluster 1 (36.7%) could be distinguished from the other clusters as being an "effector-type" cluster, whereas cluster 2 (34.4%) was a "potential-type" cluster, and cluster 3 (28.9%) was a "dysregulation-type" cluster, which showed the lowest survival rate. In addition, we established a prediction model based on immune indicator data, which accurately classified sepsis patients into three immune endotypes. Conclusion: We depicted the immune landscape of patients with sepsis and identified three distinct immune endotypes with different survival rates. Cluster membership could be predicted with a model based on immune data.

Identification of immune-related biomarkers for glaucoma using gene expression profiling.

Introduction: Glaucoma, a principal cause of irreversible vision loss, is characterized by intricate optic neuropathy involving significant immune mechanisms. This study seeks to elucidate the molecular and immune complexities of glaucoma, aiming to improve our understanding of its pathogenesis. Methods: Gene expression profiles from glaucoma patients were analyzed to identify immune-related differentially expressed genes (DEGs). Techniques used were weighted gene co-expression network analysis (WGCNA) for network building, machine learning algorithms for biomarker identification, establishment of subclusters related to immune reactions, and single-sample gene set enrichment analysis (ssGSEA) to explore hub genes' relationships with immune cell infiltration and immune pathway activation. Validation was performed using an NMDA-induced excitotoxicity model and RT-qPCR for hub gene expression measurement. Results: The study identified 409 DEGs differentiating healthy individuals from glaucoma patients, highlighting the immune response's significance in disease progression. Immune cell infiltration analysis revealed elevated levels of activated dendritic cells, natural killer cells, monocytes, and immature dendritic cells in glaucoma samples. Three hub genes, CD40LG, TEK, and MDK, were validated as potential diagnostic biomarkers for high-risk glaucoma patients, showing increased expression in the NMDA-induced excitotoxicity model. Discussion: The findings propose the three identified immune-related genes (IRGs) as novel diagnostic markers for glaucoma, offering new insights into the disease's pathogenesis and potential therapeutic targets. The strong correlation between these IRGs and immune responses underscores the intricate role of immunity in glaucoma, suggesting a shift in the approach to its diagnosis and treatment.

Mechanistic Insights into 1,2-bis(2,4,6-tribromophenoxy)ethane-Induced Male Reproductive Toxicity in Zebrafish.

The novel brominated flame retardant, 1,2-bis(2,4,6-tribromophenoxy)ethane (BTBPE), has increasingly been detected in environmental and biota samples. However, limited information is available regarding its toxicity, especially at environmentally relevant concentrations. In the present study, adult male zebrafish were exposed to varying concentrations of BTBPE (0, 0.01, 0.1, 1, and 10 µg/L) for 28 days. The results demonstrated underperformance in mating behavior and reproductive success of male zebrafish when paired with unexposed females. Additionally, a decline in sperm quality was confirmed in BTBPE-exposed male zebrafish, characterized by decreased total motility, decreased progressive motility, and increased morphological malformations. To elucidate the underlying mechanism, an integrated proteomic and phosphoproteomic analysis was performed, revealing a predominant impact on mitochondrial functions at the protein level and a universal response across different cellular compartments at the phosphorylation level. Ultrastructural damage, increased expression of apoptosis-inducing factor, and disordered respiratory chain confirmed the involvement of mitochondrial impairment in zebrafish testes. These findings not only provide valuable insights for future evaluations of the potential risks posed by BTBPE and similar chemicals but also underscore the need for further research into the impact of mitochondrial dysfunction on reproductive health.

Medical knowledge graph completion via fusion of entity description and type information.

Medical Knowledge Graphs (MKGs) are vital in propelling big data technologies in healthcare and facilitating the realization of medical intelligence. However, large-scale MKGs often exhibit characteristics of data sparsity and missing facts. Following the latest advances, knowledge embedding addresses these problems by performing knowledge graph completion. Most knowledge embedding algorithms rely solely on triplet structural information, overlooking the rich information hidden within entity property sets, leading to bottlenecks in performance enhancement when dealing with the intricate relations of MKGs. Inspired by the semantic sensitivity and explicit type constraints unique to the medical domain, we propose BioBERT-based graph embedding model. This model represents an evolvable framework that integrates graph embedding, language embedding, and type information, thereby optimizing the utility of MKGs. Our study utilizes not only WordNet as a benchmark dataset but also incorporates MedicalKG to compare and corroborate the specificity of medical knowledge. Experimental results on these datasets indicate that the proposed fusion framework achieves state-of-art (SOTA) performance compared to other baselines. We believe that this incremental improvement provides promising insights for future medical knowledge graph completion endeavors.

Experimental Study on Water-Plugging Performance of Grouted Concrete Crack.

In this paper, ordinary Portland cement, ultrafine cement, polyurethane, and epoxy resin were selected as typical grouting materials. Grouting simulation tests were first conducted to prepare the grouted concrete crack sample. The effect of concrete crack parameters (i.e., crack aperture and roughness), grout water-cement ratio, and grouting pressure on the water-plugging performance of different grouting materials was explored through the impermeability test. The microstructure of grouted concrete cracks was analyzed by means of scanning electron microscopy (SEM) and computed tomography (CT), and the difference in water-plugging performance of different grouting materials was explained at the micro level. The results show that the impermeability of the four grouting materials was ranked as follows: Epoxy resin > polyurethane > ultra-fine cement > ordinary Portland cement. The concrete cracks grouted by epoxy resin have the highest plugging failure water pressure and the lowest permeability, which is the optimal grouting material. The effectiveness of crack grouting in water-plugging was directly proportional to the grouting pressure, provided the pressure did not exceed a certain value. When the pressure surpassed the threshold, the increase in pressure did not have a significant impact on the water plugging performance. For the two cement-based materials, the threshold pressure was 1 MPa, while for the other two chemical grouts, it was 2 MPa. The two cement-based grouts with a water-cement ratio of 0.8 showed optimal water-plugging performance. The water-plugging performance of ordinary Portland cement paste, ultra-fine cement pastes, and polyurethane grout was negatively correlated with crack aperture and positively correlated with crack roughness. However, the water-plugging performance of epoxy resin grout was not affected by crack aperture or roughness.

Association between digital engagement and urban-rural disparities in Chinese women's depressive symptoms: A national-level cross-sectional study.

Objectives: This study aims to investigate the impact of digital engagement on urban-rural disparities in depressive symptoms among Chinese women. Methods: Using a dataset from the China Family Panel Studies (CFPS) wave 2020, this study analyzes the impact of digital engagement on the urban-rural disparity in women's depressive symptoms using multiple linear regression and recentered influence function (RIF) models. Furthermore, the extent to which digital engagement affects the urban-rural disparity in women's depressive symptoms was calculated using the RIF decomposition method. Results: Analysis showed that rural women had significantly higher levels of depressive symptoms compared to urban women; digital engagement significantly reduced women's depressive symptoms levels and mitigated the urban-rural disparity for women with moderate to high levels of depressive symptoms, and the mitigating effect was stronger for the highly depressed sample, but still widened the urban-rural disparity in women's depressive symptoms overall. In addition, the results of the RIF decomposition showed that digital engagement explained 28.28% of the urban-rural disparity in women's depressive symptoms. Conclusion: There is a significant disparity in depressive symptoms levels between urban and rural women in China. Digital engagement reduces women's depressive symptoms, but it also widens the depressive symptoms disparity between urban and rural women overall. Digital engagement is potentially positive for reducing women's depressive symptoms.

CD276-dependent efferocytosis by tumor-associated macrophages promotes immune evasion in bladder cancer.

Interplay between innate and adaptive immune cells is important for the antitumor immune response. However, the tumor microenvironment may turn immune suppressive, and tumor associated macrophages are playing a role in this transition. Here, we show that CD276, expressed on tumor-associated macrophages (TAM), play a role in diminishing the immune response against tumors. Using a model of tumors induced by N-butyl-N-(4-hydroxybutyl) nitrosamine in BLCA male mice we show that genetic ablation of CD276 in TAMs blocks efferocytosis and enhances the expression of the major histocompatibility complex class II (MHCII) of TAMs. This in turn increases CD4 + and cytotoxic CD8 + T cell infiltration of the tumor. Combined single cell RNA sequencing and functional experiments reveal that CD276 activates the lysosomal signaling pathway and the transcription factor JUN to regulate the expression of AXL and MerTK, resulting in enhanced efferocytosis in TAMs. Proving the principle, we show that simultaneous blockade of CD276 and PD-1 restrain tumor growth better than any of the components as a single intervention. Taken together, our study supports a role for CD276 in efferocytosis by TAMs, which is potentially targetable for combination immune therapy.

Incidence Rate of Secondary Glaucoma Following Congenital Cataract Surgery: An In-Depth Systematic Review and Meta-Analysis.

PURPOSE: To assess the incidence of secondary glaucoma in children following congenital cataract surgery. DESIGN: Systematic review and meta-analysis. METHODS: The PubMed, Embase, Cochrane Library, and Web of Science databases were searched from inception through March 16, 2023. Studies reporting congenital cataract surgery and glaucoma were enrolled. The quality of the selected studies was assessed using the Newcastle Ottawa Scale, and data analysis was executed utilizing R software. RESULTS: A total of 36 published studies with 3,151 patients (4,717 eyes) were included in the analysis. The incidence rate of glaucoma following congenital cataract surgery was 6.6% (95% CI: 3.9%, 9.9%). The incidence of secondary glaucoma in the primary intraocular lens (IOL) implantation group [3.3% (95% CI: 1.5%, 5.8%)] and the secondary IOL implantation group [3.5% (95% CI: 0%, 11.4%)] were lower compared to the aphakia group [13.5% (95% CI: 7.7%, 20.6%)]. The incidence rate among children with congenital cataracts from Asia [6.9% (95% CI: 4.1%, 10.4%)] was higher than that in European children [0.9% (95% CI: 0%, 3.0%)] (p < 0.01). A correlation was identified between the age at cataract surgery and the incidence of secondary glaucoma (p = 0.0215). CONCLUSIONS: This meta-analysis found that the incidence of secondary glaucoma following congenital cataract surgery is approximately 6.6%. Children with IOL implantation exhibit a lower incidence of secondary glaucoma, with a lower incidence noted in European children compared to their Asian counterparts. The age at cataract surgery is an important risk factor to consider.

The correlation between subendocardial viability ratio and the degree of coronary artery stenosis in patients with coronary heart disease and its predictive value for the incidence of short-term cardiovascular events.

OBJECTIVES: This study aimed to analyze the ability of subendocardial viability ratio (SEVR) to predict the degree of coronary artery stenosis and the relationship between SEVR and the incidence of short-term cardiovascular endpoint events. METHOD: The indexes of 243 patients with chest pain were collected.. Binary logistic regression analyses were performed using the dichotomous outcome of high and non-high SYNTAX scores. Receiver operating characteristic curves were employed to comparatively analyze the diagnostic efficiencies of the indices and models. A survival analysis combined with the Cox regression analysis was performed using the Kaplan-Meier method to understand the relationship between the SEVR and the incidence of cardiovascular events within 1 year in patients with coronary heart disease (CHD). RESULTS: SEVR was significantly lower (P < 0.05) in the high-stenosis group than control and low-stenosis groups. The diagnostic efficacy of SEVR [area under the curve (AUC) = 0.861] was better than those of age (AUC = 0.745), ABI (AUC = 0.739), and AIx@HR75 (AUC = 0.659). The cutoff SEVR was 1.105. In patients with confirmed CHD who had been discharged from the hospital for 1 year, only SEVR affected survival outcomes (hazard ratio = 0.010; 95% confidence interval: 0.001-0.418; P = 0.016). CONCLUSION: A significant decrease in SEVR predicted severe coronary artery stenosis, with a cutoff value of 1.105 and an accuracy of 0.861. In patients with CHD, the lower the SEVR, the higher was the rate of cardiovascular events at 1 year after hospital discharge.

Cadaverine and putrescine exposure influence carbon and nitrogen cycling genes in water and sediment of the Yellow River.

The response patterns of microbial functional genes involved in biogeochemical cycles to cadaver decay is a central topic of recent environmental sciences. However, the response mechanisms and pathways of the functional genes associated with the carbon (C) and nitrogen (N) cycling to cadaveric substances such as cadaverine and putrescine remain unclear. This study explored the variation of functional genes associated with C fixation, C degradation and N cycling and their influencing factors under cadaverine, putrescine and mixed treatments. Our results showed only putrescine significantly increased the alpha diversity of C fixation genes, while reducing the alpha diversity of N cycling genes in sediment. For the C cycling, the mixed treatment significantly decreased the total abundance of reductive acetyl-CoA pathway genes (i.e., acsB and acsE) and lig gene linked to lignin degradation in water, while only significantly increasing the hydroxypropionate-hydroxybutylate cycle (i.e., accA) gene abundance in sediment. For the N cycling, mixed treatment significantly decreased the abundance of the nitrification (i.e., amoB), denitrification (i.e., nirS3) genes in water and the assimilation pathway gene (i.e., gdhA) in sediment. Environmental factors (i.e., total carbon and total nitrogen) were all negatively associated with the genes of C and N cycling. Therefore, cadaverine and putrescine exposure may inhibit the pathway in C fixation and N cycling, while promoting C degradation. These findings can offer some new insight for the management of amine pollution caused by animal cadavers.

The characterization of protein lactylation in relation to cardiac metabolic reprogramming in neonatal mouse hearts.

In mammals, the neonatal heart can regenerate upon injury within a short time after birth, while adults lose this ability. Metabolic reprogramming has been demonstrated to be critical for cardiomyocyte proliferation in the neonatal heart. Here, we reveal that cardiac metabolic reprogramming could be regulated by altering global protein lactylation. By performing 4D label-free proteomics and lysine lactylation (Kla) omics analyses in mouse hearts at postnatal days 1, 5, and 7, 2297 Kla sites from 980 proteins are identified, among which 1262 Kla sites from 409 proteins are quantified. Functional clustering analysis reveals that the proteins with altered Kla sites are mainly involved in metabolic processes. The expression and Kla levels of proteins in glycolysis show a positive correlation while a negative correlation in fatty acid oxidation. Furthermore, we verify the Kla levels of several differentially modified proteins, including ACAT1, ACADL, ACADVL, PFKM, PKM, and NPM1. Overall, our study reports a comprehensive Kla map in the neonatal mouse heart, which will help to understand the regulatory network of metabolic reprogramming and cardiac regeneration.

The HEAT repeat protein HPO-27 is a lysosome fission factor.

Lysosomes are degradation and signalling centres crucial for homeostasis, development and ageing1. To meet diverse cellular demands, lysosomes remodel their morphology and function through constant fusion and fission2,3. Little is known about the molecular basis of fission. Here we identify HPO-27, a conserved HEAT repeat protein, as a lysosome scission factor in Caenorhabditis elegans. Loss of HPO-27 impairs lysosome fission and leads to an excessive tubular network that ultimately collapses. HPO-27 and its human homologue MROH1 are recruited to lysosomes by RAB-7 and enriched at scission sites. Super-resolution imaging, negative-staining electron microscopy and in vitro reconstitution assays reveal that HPO-27 and MROH1 self-assemble to mediate the constriction and scission of lysosomal tubules in worms and mammalian cells, respectively, and assemble to sever supported membrane tubes in vitro. Loss of HPO-27 affects lysosomal morphology, integrity and degradation activity, which impairs animal development and longevity. Thus, HPO-27 and MROH1 act as self-assembling scission factors to maintain lysosomal homeostasis and function.

Associations of environmental cadmium exposure with kidney damage: Exploring mediating DNA methylation sites in Chinese adults.

Environmental exposure is widely recognized as the primary sources of Cadmium (Cd) in the human body, and exposure to Cd is associated with kidney damage in adults. Nevertheless, the role of DNA methylation in Cd-induced kidney damage remains unclear. This study aimed to investigate the epigenome-wide association of environmental Cd-related DNA methylation changes with kidney damage. We included 300 non-smoking adults from the China in 2019. DNA methylation profiles were measured with Illumina Infinium MethylationEPIC BeadChip array. Linear mixed-effect model was employed to estimate the effects of urinary Cd with DNA methylation. Differentially methylated positions (DMPs) associated with urinary Cd were then tested for the association with kidney damage indicators. The mediation analysis was further applied to explore the potential DNA methylation based mediators. The prediction model was developed using a logistic regression model, and used 1000 bootstrap resampling for the internal validation. We identified 27 Cd-related DMPs mapped to 20 genes after the adjustment of false-discovery-rate for multiple testing among non-smoking adults. 17 DMPs were found to be associated with both urinary Cd and kidney damage, and 14 of these DMPs were newly identified within the Chinese. Mediation analysis revealed that DNA methylation of cg26907612 and cg16848624 mediated the Cd-related reduced kidney damage. In addition, ten variables were selected using the LASSO regression analysis and were utilized to develop the prediction model. It found that the nomogram model predicted the risk of kidney damage caused by environmental Cd with a corrected C-index of 0.779. Our findings revealed novel DMPs associated with both environmental Cd exposure and kidney damage among non-smoking adults, and developed an easy-to-use nomogram-illustrated model using these novel DMPs. These findings could provide a theoretical basis for formulating prevention and control strategies for kidney damage from the perspective of environmental pollution and epigenetic regulation.

Preliminary identification and semi-quantitative characterization of a multi-faceted high-stability alginate lyase from marine microbe Seonamhaeicola algicola with anti-biofilm effect on Pseudomonas aeruginosa.

Alginate lyases with unique characteristics for degrading alginate into size-defined oligosaccharide fractions, were considered as the potential agents for disrupting Pseudomonas aeruginosa biofilms. In our study, a novel endolytic PL-7 alginate lyase, named AlyG2, was cloned and expressed through Escherichia coli. This enzyme exhibited excellent properties: it maintained more than 85% activity at low temperatures of 4 °C and high temperatures of 70 °C. After 1 h of incubation at 4 °C, it still retained over 95% activity, demonstrating the ability to withstand low temperature. The acid-base and salt tolerance properties shown it preserves more than 50% activity in the pH range of 5.0 to 11.0 and in a high salt environment at 3000 mM NacCl, indicating its high stability in several aspects. More importantly, AlyG2 in our research was revealed to be effective at removing mature biofilms and inhibiting biofilm formation produced by Pseudomonas aeruginosa, and the inhibition and disruption rates were 47.25 ± 4.52% and 26.5 ± 6.72%, respectively. Additionally, the enzyme AlyG2 promoted biofilm disruption in combination with antibiotics, particularly manifesting the synergistic effect with erythromycin (FIC=0.5). In all, these results offered that AlyG2 with unique characteristics may be an effective technique for the clearance or disruption of biofilm produced by P. aeruginosa.

The association between per-/polyfluoroalkyl substances in serum and thyroid function parameters: A cross-sectional study on teenagers living near a Chinese fluorochemical industrial plant.

Thyroid hormones (THs) play an important role in a wide range of crucial biological functions related to growth and development, and thyroid antibodies (TAs) can influence the biosynthesis of THs. Epidemiological studies have indicated that per- and polyfluoroalkyl substances (PFAS) could induce thyroid disruption, but studies on teenagers living in areas with high PFAS exposure are limited. This cross-sectional study focused on 836 teenagers (11- 15 years) living near a Chinese fluorochemical industrial plant. Decreased levels of free thyroxine (FT4, ﹤9.6 pmol/L, abnormal rate = 19.0 %) and elevated levels of free triiodothyronine (FT3, ï¹¥6.15 pmol/L, abnormal rate = 29.8 %) were observed. Correlations of serum PFAS concentrations and TAs/THs were analyzed. Increased PFOA was identified as a risk factor of decreased FT4 by using unadjusted (OR: 11.346; 95 % CI: 6.029, 21.352, p < 0.001) and adjusted (OR: 12.566; 95 % CI: 6.549, 24.115, p < 0.001) logistic regression models. In addition, significantly negative correlations were found between log10 transformed PFOA and FT4 levels using linear (unadjusted: ß = -1.543, 95 % CI: -1.937, -1.148, p < 0.001; adjusted: ß = -1.534, 95 % CI: -1.930, -1.137, p < 0.001) and BKMR models. For abnormal FT3, a significantly positive association between PFHxS and FT3 levels was observed in a regression model (unadjusted: ß = -0.903, 95 % CI: -1.212, -0.595, p < 0.001; adjusted: ß = -0.894, 95 % CI: -1.204, -0.583, p < 0.001), and PFHxS was identified as a risk factor (unadjusted: OR: 4.387; 95 % CI: 2.619, 7.346, p < 0.001; adjusted: OR: 4.527; 95 % CI: 2.665, 7.688, p < 0.001). Sensitivity analyses confirmed the robustness of the above results. This study reported the elevated PFAS exposure and thyroid function of teenagers living near a fluorochemical industrial plant from China.

Utility of contrast-enhanced MRI radiomics features combined with clinical indicators for predicting induction chemotherapy response in primary central nervous system lymphoma.

PURPOSE: To assess the utility of combining contrast-enhanced magnetic resonance imaging (CE-MRI) radiomics features with clinical variables in predicting the response to induction chemotherapy (IC) for primary central nervous system lymphoma (PCNSL). METHODS: A total of 131 patients with PCNSL (101 in the training set and 30 in the testing set) who had undergone contrast-enhanced MRI scans were retrospectively analyzed. Pyradiomics was utilized to extract radiomics features, and the clinical variables of the patients were gathered. Radiomics prediction models were developed using different combinations of feature selection methods and machine learning models, and the best combination was ultimately chosen. We screened clinical variables associated with treatment outcomes and developed clinical prediction models. The predictive performance of radiomics model, clinical model, and combined model, which integrates the best radiomics model and clinical characteristics, was independently assessed and compared using Receiver Operating Characteristic (ROC) curves. RESULTS: In total, we extracted 1598 features. The best radiomics model we selected as the best utilized T-test and Recursive Feature Elimination (RFE) for feature selection and logistic regression for model building. Serum Interleukin 2 Receptor (IL-2R) and Eastern Cooperative Oncology Group (ECOG) Score were utilized to develop a clinical predictive model for assessing the response to induction chemotherapy. The results of the testing set revealed that the combined prediction model (radiomics and IL-2R) achieved the highest area under the ROC curve at 0.868 (0.683, 0.967), followed by the radiomics model at 0.857 (0.681, 0.957), and the clinical prediction model (IL-2R and ECOG) at 0.618 (0.413, 0.797). The combined model was significantly more accurate than the clinical model, with an AUC of 0.868 compared to 0.618 (P < 0.05). While the radiomics model had slightly better predictive power than the clinical model, this difference was not statistically significant (AUC, 0.857 vs. 0.618, P > 0.05). CONCLUSIONS: Our prediction model, which combines radiomics signatures from CE-MRI with serum IL-2R, can effectively stratify patients with PCNSL before high-dose methotrexate (HD-MTX) -based chemotherapy.

Fucoidan modulates SIRT1 and NLRP3 to alleviate hypertensive retinopathy: in vivo and in vitro insights.

BACKGROUND: Hypertension influences the inflammatory pathological changes in the retina. The function of the inflammasomes is significant. To see if Sirtuin 1 (SIRT1) regulates angiotensin II (Ang II)-induced hypertensive retinopathy and inflammation by modulating NOD-like receptor thermal protein domain associated protein 3 (NLRP3) inflammasome activation and the potential protective effects of fucoidan (FO) in mouse retinal vascular endothelial cells (mRECs) and mice retina. METHODS: The diagnosis of hypertensive retinopathy was made after three weeks of Ang II infusion (3000 ng/kg/min). One day prior to the commencement of Ang II infusion, the mice were treatment with NLRP3 inhibitor MCC950 (10 mg/kg/day, intraperitoneal injections) or FO (300 mg/kg/day, oral gavage). A blood pressure was recorded. Hematoxylin and eosin (H&E) staining was used to conduct pathological alterations, dihydroethidium bromide (DHE) was utilized to assess oxidative stress damage in the retina, and fluorescence angiography was used to identify vascular disorders in the eye. Using immunohistochemical labeling, NLRP3 expression was found. Reactive protein and mRNA expression levels in mouse retina and cells were assessed using Western blot and real-time quantitative polymerase chain reaction (RT-qPCR). RESULTS: NLRP3 inflammasome activation and SIRT1 decrease were brought about by Ang II infusion. Retinopathy and dysfunction were lessened by MCC950 target-induced NLRP3 inflammasome activation, while overexpression of SIRT1 had the opposite impact on NLRP3 inflammasome activation, indicating that SIRT1 functions as an upstream regulator of NLRP3 activity. FO may improve SIRT1 expression and decrease NLRP3 activation in retinopathy and dysfunction brought on by Ang II, and the effects were consistent across both in vivo and in vitro models. CONCLUSIONS: SIRT1 adversely regulates the NLRP3 inflammasome pathway, which in turn increases Ang II-induced inflammation and hypertensive retinopathy. FO may mitigate Ang II-induced retinopathy and dysfunction via modulating the expression of SIRT1/NLRP3. This implies practical approaches to the management of hypertensive retinopathy.

Predicting mechanical properties lower upper bound for cold-rolling strip by machine learning-based artificial intelligence.

The mechanical properties serve as crucial quality indicators for cold-rolled strips. For a long time, the mechanical properties mechanism and data-driven models can't comprehensively consider sufficient factors to achieve high-accuracy prediction due to the "data-isolated island" between production lines. In this research, we introduce a multi-process collaborative platform based on the industrial internet system. This platform is designed to enable real-time collection of diverse and heterogeneous data from both upstream and downstream processes of cold rolling. On this basis, a novel mechanical properties interval prediction model is proposed using the sparrow search algorithm to optimize fast learning network under the LUBE framework. We trained the model by using a dataset collected from a large steel plant. Based on the rolling theory and Pearson correlation coefficient, 25 features are selected as the inputs of the prediction model. The experimental results and comparison show that the proposed model is feasible and outperforms other machine learning models, such as the artificial bee colony algorithm optimized extreme learning machine and back propagation neural network model.