Analysis Of Interactions Research Articles

Spatial cell interplay networks of regulatory T cells predict recurrence in patients with operable non-small cell lung cancer

BackgroundThe interplay between regulatory T cells (Tregs) and neighboring cells, which is pivotal for anti-tumor immunity and closely linked to patient prognosis, remains to be fully elucidated.MethodsTissue microarrays of 261 operable NSCLC patients were stained by multiplex immunofluorescence (mIF) assay, and the interaction between Tregs and neighboring cells in the tumor microenvironment (TME) was evaluated. Employing various machine learning algorithms, we developed a spatial immune signature to predict the prognosis of NSCLC patients. Additionally, we explored the interplay between programmed death-1/programmed death ligand-1 (PD-1/PD-L1) interactions and their relationship with Tregs.ResultsSurvival analysis indicated that the interplay between Tregs and neighboring cells in the invasive margin (IM) and tumor center was associated with recurrence in NSCLC patients. We integrated the intersection of the three algorithms to identify four crucial spatial immune features [P(CD8+Treg to CK) in IM, P(CD8+Treg to CD4) in IM, N(CD4+Treg to CK) in IM, N(CD4+Tcon to CK) in IM] and employed these characteristics to establish SIS, an independent prognosticator of recurrence in NSCLC patients [HR = 2.34, 95% CI (1.53, 3.58), P < 0.001]. Furthermore, analysis of cell interactions demonstrated that a higher number of Tregs contributed to higher PD-L1+ cells surrounded by PD-1+ cells (P < 0.001) with shorter distances (P = 0.004).ConclusionWe dissected the cell interplay network within the TME, uncovering the spatial architecture and intricate interactions between Tregs and neighboring cells, along with their impact on the prognosis of NSCLC patients.

A descriptive analysis of drug-drug interactions and corresponding adverse drug reactions in multimorbid older inpatients: findings from the SENATOR trial.

Drug-drug interactions (DDIs) are prevalent among multimorbid and polymedicated older adults and can increase the risk of adverse drug reactions (ADRs), hospital admissions, and mortality. This study describes the incidence and prevalence of 66 clinically relevant DDIs and analyses the occurrence of 12 corresponding predefined ADRs in older inpatients enrolled in the SENATOR trial. The sub-study of the SENATOR trial that involved 1537 multimorbid older inpatients, recruited from 2016 to 2018 in six academic teaching hospitals in Belgium, Iceland, Ireland, Italy, Scotland, and Spain respectively, and analysed 66 potentially clinically significant DDIs. Descriptive analysis determined DDI and corresponding ADR prevalence/incidence. At baseline (median age: 78 [72, 84], 52.8% male), the prevalence of patients with DDIs was high (50.9%), increased during hospitalisation (55.2%) and reduced to 49.7% after 12weeks. The most common DDIs were: ≥ 2potassium reducing drugs (17.1%), ≥ 3centrally acting drugs (9.0%), and SSRI + loop/thiazide diuretic (7.2%). Of all participants, one-third experienced a prevalent (36.6%)/incident (35.8%) ADR. Major serum electrolyte disturbance had the highest incidence (10.7%)/prevalence (11.5%). Incident ADRs were more common in patients with DDIs (p = 0.013). A higher prevalence of new onset falls (p = 0.013), major constipation (p = 0.004), and major serum electrolyte disturbances (p = 0.006) was observed in patients with related and thus potentially causal DDIs. Clinicians should, be aware of DDIs and the involved drug classes that can lead to an increased rate of ADRs in older multimorbid inpatients. Regularly reevaluating the appropriateness of the frequently prescribed drug classesand initiating judicious deprescribing is recommended.

Understanding protein adsorption on silica mesoporous materials through thermodynamic simulations

This work presents a molecular thermodynamic theory to study protein interactions within a charge-regulating silica-like nanopore structure. The theory accounts for electrostatic interactions, steric repulsions, finite-size entropic effects, and protonation equilibrium of silanol groups on silica and protein residue side-chains. Coarse-grained representations of proteins based on their 3D crystallographic structures are employed. We evaluate the influence of pH, salt concentration, and pore size on the adsorption of selected proteins (cytochrome c, lysozyme, and myoglobin) in both single- and binary-protein solutions. The surface charge density on the nanopore walls is less negative than on the adjacent planar surface, primarily influenced by pH and salt concentration. Adsorption within the nanopore from single protein solutions exhibits a non-monotonic behavior with pH, increasing with decreasing salt concentration and diminishing pore size. Analysis of the effective interactions between proteins and silica surfaces indicates that adsorption is enhanced when the protein size matches that of the nanopore. Evaluation of various adsorption pathways indicates minimized free energy when the protein enters the nanopore through its edge and contacts its cylindrical walls. In binary solutions, the presence of another protein significantly alters the affinity of a protein for the silica surfaces, potentially preventing its adsorption, and affects its organization on these surfaces upon adsorption.

Advanced orthogonal analysis of multi-factorial interactions influencing co-combustion performance and pollution reduction potential of coal gangue and biomass in oxy-fuel combustion conditions

In the current scenario of increasing energy scarcity and stricter environmental protection requirements, the utilization of coal gangue and biomass energy is gaining attention worldwide. Biomass and coal gangue are complementary in nature, and their co-combustion can improve the burnout efficiency of coal gangue and reduce pollutant emissions. In this study, coal gangue and wheat straw are selected as research subjects, the optimal process conditions for their co-combustion under the coupling of multiple parameters in oxy-fuel atmosphere through orthogonal experiments are investigated. The results indicate that the most significant factor influencing combustion characteristics is the heating rate. When the biomass content is 45 %, O2 concentration is 50 %, heating rate is 30℃/min and particle size is 180–250μm, the flammability and comprehensive combustion indexes of the samples are maximized, which indicates the optimum combustion characteristics. The primary factor affecting pollutant release is biomass content. When the biomass content is 45 %, O2 concentration is 75 %, combustion temperature is 700℃, and particle size is 180–250μm, the pollutant release concentration is minimized.

The role of functional emotion circuits in distinct dimensions of psychopathology in youth

Several mental disorders emerge during childhood or adolescence and are often characterized by socioemotional difficulties, including alterations in emotion perception. Emotional facial expressions are processed in discrete functional brain modules whose connectivity patterns encode emotion categories, but the involvement of these neural circuits in psychopathology in youth is poorly understood. This study examined the associations between activation and functional connectivity patterns in emotion circuits and psychopathology during development. We used task-based fMRI data from the Philadelphia Neurodevelopmental Cohort (PNC, N = 1221, 8–23 years) and conducted generalized psycho-physiological interaction (gPPI) analyses. Measures of psychopathology were derived from an independent component analysis of questionnaire data. The results showed positive associations between identifying fearful, sad, and angry faces and depressive symptoms, and a negative relationship between sadness recognition and positive psychosis symptoms. We found a positive main effect of depressive symptoms on BOLD activation in regions overlapping with the default mode network, while individuals reporting higher levels of norm-violating behavior exhibited emotion-specific lower functional connectivity within regions of the salience network and between modules that overlapped with the salience and default mode network. Our findings illustrate the relevance of functional connectivity patterns underlying emotion processing for behavioral problems in children and adolescents.

Sequential query prediction based on multi-armed bandits with ensemble of transformer experts and immediate feedback

AbstractWe study the problem of predicting the next query to be recommended in interactive data exploratory analysis to guide users to correct content. Current query prediction approaches are based on sequence-to-sequence learning, exploiting past interaction data. However, due to the resource-hungry training process, such approaches fail to adapt to immediate user feedback. Immediate feedback is essential and considered as a signal of the user’s intent. We contribute with a novel query prediction ensemble mechanism, which adapts to immediate feedback relying on multi-armed bandits framework. Our mechanism, an extension to the popular Exp3 algorithm, augments Transformer-based language models for query predictions by combining predictions from experts, thus dynamically building a candidate set during exploration. Immediate feedback is leveraged to choose the appropriate prediction in a probabilistic fashion. We provide comprehensive large-scale experimental and comparative assessment using a popular online literature discovery service, which showcases that our mechanism (i) improves the per-round regret substantially against state-of-the-art Transformer-based models and (ii) shows the superiority of causal language modelling over masked language modelling for query recommendations.

Police interviews in a non-native context: Misconstructions and possible solutions

Section 6(2) of the Constitution of the Republic of South Africa serves as the material cornerstone for promoting the equitable use of all official languages in government departments. This right, however, is not always granted equitably to the greater society, such as the police who use English as a second language. This is problematic because in 2015 writers like Ralarala highlighted in forensic linguistics how difficult it can be for police to generate incisive English reports. The present article contributes to the discussion, but from an applied linguistic standpoint. It sheds some light on the nuances in both written and oral accounts that impact the exactness of a police statement. The data in the study (observations and handwritten statements) were analysed through the interaction and error analysis technique. The results of the research reveal that police use their linguistic capacity to generate target language structures that as a result render the text difficult to understand. This could make it difficult to understand how the actual incident occurred, making police reports less reliable as evidence in court. The results of the study are expected to highlight the language difficulties in the police and help in improving their statement-taking ability.

PMart Web Application: Marketplace for Interactive Analysis of Panomics Data.

PMart is a web-based tool for reproducible quality control, exploratory data analysis, statistical analysis, and interactive visualization of 'omics data, based on the functionality of the pmartR R package. The newly improved user interface supports more 'omics data types, additional statistical capabilities, and enhanced options for creating downloadable graphics. PMart supports the analysis of label-free and isobaric-labeled (e.g., TMT, iTRAQ) proteomics, nuclear magnetic resonance (NMR) and mass-spectrometry (MS)-based metabolomics, MS-based lipidomics, and ribonucleic acid sequencing (RNA-seq) transcriptomics data. At the end of a PMart session, a report is available that summarizes the processing steps performed and includes the pmartR R package functions used to execute the data processing. In addition, built-in safeguards in the backend code prevent users from utilizing methods that are inappropriate based on omics data type. PMart is a user-friendly interface for conducting exploratory data analysis and statistical comparisons of omics data without programming.

Investigation of the relationship between COVID-19 and pancreatic cancer using bioinformatics and systems biology approaches.

The coronavirus disease 2019 (COVID-19) pandemic, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus, poses a huge threat to human health. Pancreatic cancer (PC) is a malignant tumor with high mortality. Research suggests that infection with SARS-CoV-2 may increase disease severity and risk of death in patients with pancreatic cancer, while pancreatic cancer may also increase the likelihood of contracting SARS-CoV-2, but the link is unclear. This study investigated the transcriptional profiles of COVID-19 and PC patients, along with their respective healthy controls, using bioinformatics and systems biology approaches to uncover the molecular mechanisms linking the 2 diseases. Specifically, gene expression data for COVID-19 and PC patients were obtained from the Gene Expression Omnibus datasets, and common differentially expressed genes (DEGs) were identified. Gene ontology and pathway enrichment analyses were performed on the common DEGs to elucidate the regulatory relationships between the diseases. Additionally, hub genes were identified by constructing a protein-protein interaction network from the shared DEGs. Using these hub genes, we conducted regulatory network analyses of microRNA/transcription factors-genes relationships, and predicted potential drugs for treating COVID-19 and PC. A total of 1722 and 2979 DEGs were identified from the transcriptome data of PC (GSE119794) and COVID-19 (GSE196822), respectively. Among these, 236 common DEGs were found between COVID-19 and PC based on protein-protein interaction analysis. Functional enrichment analysis indicated that these shared DEGs were involved in pathways related to viral genome replication and tumorigenesis. Additionally, 10 hub genes, including extra spindle pole bodies like 1, holliday junction recognition protein, marker of proliferation Ki-67, kinesin family member 4A, cyclin-dependent kinase 1, topoisomerase II alpha, cyclin B2, ubiquitin-conjugating enzyme E2 C, aurora kinase B, and targeting protein for Xklp2, were identified. Regulatory network analysis revealed 42 transcription factors and 23 microRNAs as transcriptional regulatory signals. Importantly, lucanthone, etoposide, troglitazone, resveratrol, calcitriol, ciclopirox, dasatinib, enterolactone, methotrexate, and irinotecan emerged as potential therapeutic agents against both COVID-19 and PC. This study unveils potential shared pathogenic mechanisms between PC and COVID-19, offering novel insights for future research and therapeutic strategies for the treatment of PC and SARS-CoV-2 infection.

Genome-wide identification and molecular evolution of elongation family of very long chain fatty acids proteins in Cyrtotrachelus buqueti

To reveal the molecular function of elongation family of very long chain fatty acids(ELO) protein in Cyrtotrachelus buqueti, we have identified 15 ELO proteins from C.buqueti genome. 15 CbuELO proteins were located on four chromosomes. Their isoelectric points ranged from 9.22 to 9.68, and they were alkaline. These CbuELO proteins were stable and hydrophobic. CbuELO proteins had transmembrane movement, and had multiple phosphorylation sites. The secondary structure of CbuELO proteins was mainly α-helix. A total of 10 conserved motifs were identified in CbuELO protein family. Phylogenetic analysis showed that molecular evolutionary relationships of ELO protein family between C. buqueti and Tribolium castaneum was the closest. Developmental transcriptome analysis indicated that CbuELO10, CbuELO13 and CbuELO02 genes were key enzyme genes that determine the synthesis of very long chain fatty acids in pupae and eggs, CbuELO6 and CbuELO7 were that in the male, and CbuELO8 and CbuELO11 were that in the larva. Transcriptome analysis under different temperature conditions indicated that CbuELO1, CbuELO5, CbuELO12 and CbuELO14 participated in regulating temperature stress responses. Transcriptome analysis at different feeding times showed CbuELO12 gene expression level in all feeding time periods was significant downregulation. The qRT-PCR experiment verified expression level changes of CbuELO gene family under different temperature and feeding time conditions. Protein-protein interaction analysis showed that 9 CbuELO proteins were related to each other, CbuELO1, CbuELO4 and CbuELO12 had more than one interaction relationship. These results lay a theoretical foundation for further studying its molecular function during growth and development of C. buqueti.

The Association of Vitamin B-12 Plasma Concentration with Stroke Incidence According to Sex

BackgroundPrevious studies reported that vitamin B-12 deficiency is associated with an increased risk of stroke. However, studies examining the association between excessive vitamin B-12 and stroke risk are limited. Our study aimed to investigate the relationship between excessive vitamin B-12 concentrations and risk of stroke and explore whether this association varies according to sex. MethodsUtilizing the Korean Genome Epidemiology Study (KoGES) prospective cohort data, our primary exposure variables were vitamin B-12 plasma concentration and sex. The occurrence of stroke served as the main outcome of interest. Hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated using Cox regression analysis. An interaction analysis was conducted to assess the interaction effect of vitamin B-12 and sex on stroke incidence. ResultsCox proportional logistic regression analysis, adjusting for confounders, showed that excessive vitamin B-12 did not significantly alter stroke risk (HR: 1.22, 95% CI: 0.82, 1.71) and revealed no significant sex-based differences in stroke risk (HR: 0.90, 95% CI: 0.75, 1.04). However, interaction analysis indicated that excessive vitamin B-12 was linked to a significant increase in stroke risk in males (HR: 1.81, 95% CI: 1.10, 2.99) but not in females (HR: 1.04, 95% CI: 0.66, 1.60), with statistically significant interaction effect (P < 0.01). ConclusionsOur study demonstrated that although excessive vitamin B-12 alone does not significantly increase stroke risk, it increases risk in males when considering the interaction with sex.

Association of prenatal vitamin E levels with child asthma and wheeze.

We investigated the individual and interaction effects of maternal plasma 𝛂- and ϒ-tocopherol levels (vitamin E isomers) on child asthma and wheeze at age 8-9. Mother-child dyads were enrolled between 2006 and 2011 into the Conditions Affecting Neurocognitive Development and Learning in Early Childhood (CANDLE) prenatal cohort. Maternal second-trimester samples were analyzed for tocopherol and lipid concentrations. We assessed child asthma/wheeze using the International Study of Asthma and Allergies in Childhood (ISAAC) and other self-reported Ent wheeze. In multivariable logistic regression analyses, we assessed associations between vitamin E isomers and child asthma/wheeze outcomes (n = 847 mother-child dyads) and tested for prespecified interaction terms. Median cholesterol-corrected tocopherol levels (interquartile range (IQR)) were 5.0 (4.3-5.7) and 0.8 (0.7-0.9) (umol/mmol) for 𝛂- and ϒ-tocopherol, respectively. Associations between 𝛂-tocopherol and asthma outcome variables were inverse but not statistically significant. In contrast, for ϒ-tocopherol, associations were in the positive direction, but also nonsignificant. Interactions analysis between tocopherols did not reach statistical significance for any outcome. Among children of women with a history of asthma, the likelihood of ever asthma in the child appears to be decreasing with increasing maternal 𝛂-tocopherol levels, whereas this trend was not observed among those without a history of asthma (p-interaction = .05). We observed no associations for prenatal 𝛂- or ϒ-tocopherol concentrations with child asthma/wheeze. We detected some evidence of effect modification by maternal asthma history in associations between 𝛂-tocopherol and child asthma.

Three-dimensional pseudocontinuous arterial spin labeling with dual postlabeling delay for reflecting cerebral blood flow regulation in patients with hydrocephalus: a retrospective cross-sectional study.

Three-dimensional pseudo-continuous arterial spin-labeling (3D pCASL) with dual postlabeling delay (PLD) captures both early and delayed cerebral blood flow (CBF), yet its potential in reflecting blood flow regulation in hydrocephalus patients remains uncertain. This study investigated the hemodynamic characteristics in patients with hydrocephalus and whether the difference in cerebral blood flow using short and long PLDs (ΔCBF = CBFPLD =2.5 s - CBFPLD =1.5 s) could reflect cerebral regulation and further aimed to demonstrate the associations between regional ΔCBF and the degree of ventricular dilatation. This retrospective study included consecutive patients with hydrocephalus and control participants attending The Second Affiliated Hospital of Nanchang University from December 2017 to December 2022. The CBF in 18 brain regions was manually delineated by two radiologists. Regional CBF and ΔCBF were compared via covariance analyses. The associations between ΔCBF and the degree of ventricular dilatation were investigated using linear regression analyses and interaction analysis. In total, 58 patients with communicating hydrocephalus, 57 patients with obstructive hydrocephalus, and 52 controls were analyzed. CBF of the hydrocephalus groups was lower than that of the control group at the shorter PLD. CBF was higher at a longer PLD, with no difference between the hydrocephalus groups and the control group in some regions. The hydrocephalus groups showed a higher ΔCBF compared to the control group. Furthermore, in the left medial watershed (10.6±5.66 vs. 7.01±5.88 mL/100 g/min; P=0.038), communicating hydrocephalus exhibited greater ΔCBF than did obstructive hydrocephalus. ΔCBF of the right posterior external watershed [adjusted β: 0.276; 95% confidence interval (CI): 0.047-0.505; P=0.019] and right parietal cortex (adjusted β: 0.277; 95% CI: 0.056-0.498; P=0.015) in the obstructive hydrocephalus group and ΔCBF of the left internal watershed (adjusted β: 0.274; 95% CI: 0.013-0.536; P=0.040) in the communicating hydrocephalus group were associated with the degree of ventricular dilatation, respectively. Patients with hydrocephalus showed cerebral regulation in maintaining adequate CBF, resulting in longer arterial transit times. The ability to regulate CBF in brain regions represented by the watershed was associated with the degree of ventricular dilation.

Identification and expression of prognostic-related genes in kidney renal clear cell carcinoma and their possible regulatory mechanisms.

Many factors affect the prognosis of kidney renal clear cell carcinoma (KIRC). Early diagnosis can significantly improve the prognosis of KIRC patients. Therefore, a method needs to be developed to diagnose KIRC early, predict patient prognosis, and improve personalized treatments. The objective of this study is to utilize bioinformatics tools and public database resources to identify differentially expressed genes (DEGs) between renal cancer tissues and adjacent normal tissues, and to further screen for prognostic-related genes (PRGs) of KIRC. KIRC was studied using R language and FunRich software and several databases, including the Gene Expression Omnibus (GEO), The Cancer Genome Atlas (TCGA), the University of Alabama at Birmingham cancer data analysis Portal (UALCAN), and Tumor Immune Estimation Resource (TIMER) databases. Moreover, quantitative real-time polymerase chain reaction (qRT-PCR) was used to validate the expression of multiple genes in KIRC and adjacent normal tissues. There were substantial differences in immune cell infiltration between the KIRC and adjacent normal tissues in the GSE40435 and GSE46699 datasets. In addition, we screened multiple PRGs of KIRC by combining the GEO and TCGA data. The UALCAN database verified that some representative PRGs were differently expressed depending on the lymph node metastasis status, grade, and stage of KIRC. The qRT-PCR results confirmed the expression of the PRGs in KIRC and adjacent normal tissues. Through the GO and KEGG analyses, interaction analysis, and TIMER database, we found that the prognosis of KIRC was closely related to immune microenvironment and vascular endothelial growth factor (VEGF)/VEGF receptor (VEGFR) signaling. Our findings could contribute to the prognosis prediction of KIRC, the selection of personalized treatments, and the early diagnosis of KIRC.

Neighborhood-Level Disparities in Hypertension Prevalence and Treatment Among Middle-Aged Adults

Hypertension in middle-aged adults (35-50 years) is associated with poorer health outcomes in late life. Understanding how hypertension varies by race and ethnicity across levels of neighborhood disadvantage may allow for better characterization of persistent disparities. To evaluate spatial patterns of hypertension diagnosis and treatment by neighborhood socioeconomic position and racial and ethnic composition. In this cross-sectional study of middle-aged adults in Cuyahoga County, Ohio, who encountered primary care in 2019, geocoded electronic health record data were linked to the area deprivation index (ADI), a neighborhood disadvantage measure, at the US Census Block Group level (ie, neighborhood). Neighborhoods were stratified by ADI quintiles, with the highest quintile indicating the most disadvantage. Data were analyzed between August 7, 2023, and June 1, 2024. Essential hypertension. The primary outcome was a clinician diagnosis of essential hypertension. Spatial analysis was used to characterize neighborhood-level patterns of hypertension prevalence and treatment. Interaction analysis was used to compare hypertension prevalence by racial and ethnic group within similar ADI quintiles. A total of 56 387 adults (median [IQR] age, 43.1 [39.1-46.9] years; 59.8% female) across 1157 neighborhoods, which comprised 3.4% Asian, 31.1% Black, 5.5% Hispanic, and 60.0% White patients, were analyzed. A gradient of hypertension prevalence across ADI quintiles was observed, with the highest vs lowest ADI quintile neighborhoods having a higher hypertension rate (50.7% vs 25.5%) and a lower treatment rate (61.3% vs 64.5%). Of the 315 neighborhoods with predominantly Black (>75%) patient populations, 200 (63%) had a hypertension rate greater than 35% combined with a treatment rate of less than 70%; only 31 of 263 neighborhoods (11.8%) comprising 5% or less Black patient populations met this same criterion. Compared with a spatial model without covariates, inclusion of ADI and percentage of Black patients accounted for 91% of variation in hypertension diagnosis prevalence among men and 98% among women. Men had a higher prevalence of hypertension than women across race and ADI quintiles, but the association of ADI and hypertension risk was stronger in women. Sex prevalence differences were smallest between Black men and women, particularly in the highest ADI quintile (1689 [60.0%] and 2592 [56.0%], respectively). These findings show an association between neighborhood deprivation and hypertension prevalence, with disparities observed particularly among Black patients, emphasizing a need for structural interventions to improve community health.

Machine Learning Meets Physics-based Modeling: A Mass-spring System to Predict Protein-ligand Binding Affinity.

Computational assessment of the energetics of protein-ligand complexes is a challenge in the early stages of drug discovery. Previous comparative studies on computational methods to calculate the binding affinity showed that targeted scoring functions outperform universal models. The goal here is to review the application of a simple physics-based model to estimate the binding. The focus is on a mass-spring system developed to predict binding affinity against cyclin-dependent kinase. Publications in PubMed were searched to find mass-spring models to predict binding affinity. Crystal structures of cyclin-dependent kinases found in the protein data bank and two web servers to calculate affinity based on the atomic coordinates were employed. One recent study showed how a simple physics-based scoring function (named Taba) could contribute to the analysis of protein-ligand interactions. Taba methodology outperforms robust physics-based models implemented in docking programs such as AutoDock4 and Molegro Virtual Docker. Predictive metrics of 27 scoring functions and energy terms highlight the superior performance of the Taba scoring function for cyclin- dependent kinase. The recent progress of machine learning methods and the availability of these techniques through free libraries boosted the development of more accurate models to address protein-ligand interactions. Combining a naïve mass-spring system with machine-learning techniques generated a targeted scoring function with superior predictive performance to estimate pKi.

Active Heme Metabolism Suppresses Macrophage Phagocytosis via the TLR4/Type I IFN Signaling/CD36 in Uterine Endometrial Cancer.

Uterine endometrial cancer (UEC) is a common gynecological estrogen-dependent carcinoma, usually accompanied by intermenstrual bleeding. Active heme metabolism frequently plays an increasingly important role in many diseases, especially in cancers. Tumor-associated macrophages (TAMs) are the major population in the immune microenvironment of UEC. However, the roles of heme metabolisms in the crosstalk between UEC cells (UECCs) and macrophages are unclear. In our study, by using TCGA database analysis, integration analysis of the protein-protein interaction (PPI) network and sample RNA transcriptome sequencing were done. The expression level of both heme-associated molecules and iron metabolism-related molecules were measured by quantitative real-time polymerase chain reaction. Heme level detection was done through dehydrohorseradish peroxidase assay. In addition to immunohistochemistry, phagocytosis assay of macrophages, immunofluorescence staining, intracellular ferrous iron staining, as well as enzyme-linked immune sorbent assay were performed. In the study, we verified that heme accumulation in UECCs is apparently higher than in endometrial epithelium cells. Low expression of succinate dehydrogenase B under the regulation of estrogen contributes to over-production of succinate and heme accumulation in UECC. More importantly, excessive heme in UECCs impaired macrophage phagocytosis by regulation of CD36. Mechanistically, this process is dependent on toll-like receptor (TLR4)/type I interferons alpha (IFN Iα) regulatory axis in macrophage. Collectively, these findings elucidate that active heme metabolism of UECCs directly decreases phagocytosis by controlling the secretion of TLR4-mediated IFN Iα and the expression of CD36, and further contributing to the immune escape of UEC.

Frequency-domain analysis of fluid-structure interaction in aircraft hydraulic pipeline systems: numerical and experimental studies

Frequency-domain analysis of fluid-structure interaction in aircraft hydraulic pipeline systems: numerical and experimental studies

Numerical analysis of ultrasound-mediated microbubble interactions in vascular systems: Effects on shear stress and vessel mechanics

The present study concerns the numerical modeling of microbubble oscillation within an elastic microvessel, aiming to enhance the safety and efficacy of ultrasound-mediated drug delivery and diagnostic imaging. The success of such applications depends on a thorough understanding of microbubble–vessel interactions. Despite some progress, the critical impact of the stabilizing shell around gas core has remained underexplored. To address this, we developed a novel numerical approach that models the stabilizing shell. Additionally, there is novelty in modeling consequent vascular deformation in response to complicated spatiotemporal microbubble oscillations. The novel approach was implemented for shear stress evaluation as a critical factor in vascular permeability. Finally, our unique approach offered novel insights into microbubble–vessel interactions under diverse acoustic conditions. Results indicated substantial impact of shell properties and acoustic parameters on induced shear stress. With a fourfold increase in acoustic pressure amplitude, 15.6-fold and sixfold increases were observed in maximum shear stress at 1 and 3 MHz, respectively. Also, the peak shear stress could reach up to 15.6 kPa for a shell elasticity of 0.2 N/m at 2.5 MHz. Furthermore, decreasing microvessel/bubble size ratio from 3 to 1.5 increased maximum shear stress from 5.1 to 24.3 kPa. These findings are crucial for optimizing ultrasound parameters in clinical applications, potentially improving treatment outcomes while minimizing risk of vessel damage. However, while our model demonstrated high fidelity in reproducing experimental observations, it is limited by assumptions of vessel geometry and homogeneity of vessel properties. Future work can improve our findings through in vitro experimental measurements.

Imbibition models quantifying interfacial interactions: Based on nuclear magnetic resonance investigation and coupled structural characteristics

An investigation into spontaneous imbibition in porous media is of paramount scientific significance in various projects. However, a precise understanding of the interaction mechanisms between media structural characteristics and imbibition remains elusive, and quantitative analysis of the interfacial interaction is lacking. Therefore, to mitigate the influence of dispersion, this study first investigates cyclic imbibition experiments of coal samples to explore the interaction mechanism between pore-fracture structure (PFS) and imbibition. Nuclear magnetic resonance is used to visualize water transport during imbibition across all scales. Subsequently, the slake durability index is suggested to clarify the coupling relationship between water–coal interactions and imbibition. Two more comprehensive and accurate imbibition models are established, based on pore size and comprehensive seepage parameters, respectively. The results demonstrate that both new models exhibit superior conformity with experimental data compared to traditional models. The memory factor quantifies interface interaction within these models. Sensitivity analysis reveals that strong interface interaction diminishes the effective imbibition ratio, while the structural characteristics of porous media significantly influence the interaction. Furthermore, the fractal dimension quantitatively characterizes the PFS features of coal samples. An exploration of the relationship between fractal dimension and memory factor indicates the influence of porous media heterogeneity on imbibition.