Clot or Not? Reviewing the Reciprocal Regulation Between Lipids and Blood Clotting.

Both hyperlipidemia and thrombosis contribute to the risks of atherosclerotic cardiovascular diseases, which are the leading cause of death and reduced quality of life in survivors worldwide. The accumulation of lipid-rich plaques on arterial walls eventually leads to the rupture or erosion of vulnerable lesions, triggering excessive blood clotting and leading to adverse thrombotic events. Lipoproteins are highly dynamic particles that circulate in blood, carry insoluble lipids, and are associated with proteins, many of which are involved in blood clotting. A growing body of evidence suggests a reciprocal regulatory relationship between blood clotting and lipid metabolism. In this review article, we summarize the observations that lipoproteins and lipids impact the hemostatic system, and the clotting-related proteins influence lipid metabolism. We also highlight the gaps that need to be filled in this area of research.

Silicon Radical-Induced CH4 Dissociation for Uniform Graphene Coating on Silica Surface.

Due to the manufacturability of highly well-defined structures and wide-range versatility in its microstructure, SiO2 is an attractive template for synthesizing graphene frameworks with the desired pore structure. However, its intrinsic inertness constrains the graphene formation via methane chemical vapor deposition. This work overcomes this challenge by successfully achieving uniform graphene coating on a trimethylsilyl-modified SiO2 (denote TMS-MPS). Remarkably, the onset temperature for graphene growth dropped to 720 °C for the TMS-MPS, as compared to the 885 °C of the pristine SiO2. This is found to be mainly from the Si radicals formed from the decomposition of the surface TMS groups. Both experimental and computational results suggest a strong catalytic effect of the Si radicals on the CH4 dissociation. The surface engineering of SiO2 templates facilitates the synthesis of high-quality graphene sheets. As a result, the graphene-coated SiO2 composite exhibits a high electrical conductivity of 0.25 S cm-1. Moreover, the removal of the TMP-MPS template has released a graphene framework that replicates the parental TMS-MPS template on both micro- and nano- scales. This study provides tremendous insights into graphene growth chemistries as well as establishes a promising methodology for synthesizing graphene-based materials with pre-designed microstructures and porosity.

Characteristics of tandem repeat inheritance and sympathetic nerve involvement in GAA-FGF14 ataxia.

BACKGROUND: Intronic GAA repeat expansion ([GAA] ≥250) in FGF14 is associated with the late-onset neurodegenerative disorder, spinocerebellar ataxia 27B (SCA27B, GAA-FGF14 ataxia). We aim to determine the prevalence of the GAA repeat expansion in FGF14 in Chinese populations presenting late-onset cerebellar ataxia (LOCA) and evaluate the characteristics of tandem repeat inheritance, radiological features and sympathetic nerve involvement. METHODS: GAA-FGF14 repeat expansion was screened in an undiagnosed LOCA cohort (n = 664) and variations in repeat-length were analyzed in families of confirmed GAA-FGF14 ataxia patients. Brain magnetic resonance imaging (MRI) was used to evaluate the radiological feature in GAA-FGF14 ataxia patients. Clinical examinations and sympathetic skin response (SSR) recordings in GAA-FGF14 patients (n = 16) were used to quantify sympathetic nerve involvement. RESULTS: Two unrelated probands (2/664) were identified. Genetic screening for GAA-FGF14 repeat expansion was performed in 39 family members, 16 of whom were genetically diagnosed with GAA-FGF14 ataxia. Familial screening revealed expansion of GAA repeats in maternal transmissions, but contraction upon paternal transmission. Brain MRI showed slight to moderate cerebellar atrophy. SSR amplitude was lower in GAA-FGF14 patients in pre-symptomatic stage compared to healthy controls, and further decreased in the symptomatic stage. CONCLUSIONS: GAA-FGF14 ataxia was rare among Chinese LOCA cases. Parental gender appears to affect variability in GAA repeat number between generations. Reduced SSR amplitude is a prominent feature in GAA-FGF14 patients, even in the pre-symptomatic stage.

NPF and sNPF can regulate the feeding behaviour and affect the growth and antioxidant levels of the rice brown planthopper, Nilaparvata lugens.

Neuropeptide F (NPF) and short neuropeptide F (sNPF) are important neuropeptides and mainly affect feeding behaviour of insects. However, the regulation of insect feeding behaviour by NPF and sNPF appears to differ between species, and it is not clear how NPF and sNPF regulate the food intake of the brown planthopper (Nilaparvata lugens). Therefore, the functions of NPF and sNPF in regulating food intake and affecting the growth and antioxidant levels of N. lugens fed on host rice plants were investigated by knocking down NPF and sNPF respectively and simultaneously knocking down both of them by RNA interference. The results showed that NPF and sNPF were mainly expressed in the head of N. lugens, and N. lugens increased food intake after NPF and sNPF were knocked down, which was reflected in the prolonged duration of N4a and N4b waves in the electrical penetration graph (EPG) experiment after knocking down NPF and sNPF. In addition, knocking down NPF and sNPF led to the increase of body weight and mortality of N. lugens, and also led to the increase of antioxidant level of N. lugens. So it was concluded that NPF and sNPF could regulate food intake, maintain body weight stability and oxidative balance in N. lugens. Our study clarified the molecular mechanism of NPF and sNPF regulating feeding behaviour and affect the growth and antioxidant level of N. lugens.

Efficacy of revascularization in CTO patients based on hibernating myocardium therapy.

BACKGROUND: The effectiveness of percutaneous coronary intervention (PCI) for chronic total occlusion (CTO) is still uncertain, especially for patients with ischemic left ventricular dysfunction. This study aimed to assess hibernating myocardium (HM), as determined by single-photon emission computed tomography (SPECT) and 18F-FDG positron emission tomography (PET), and to compare the benefits of PCI and optimal medical therapy (OMT). METHODS: A retrospective study collected data from 332 patients with CTO and ischemic left ventricular dysfunction. The study compared patients who underwent PCI or OMT via propensity score matching (PSM) analysis which was performed with a 1:2 matching protocol using the nearest neighbour matching algorithm. The primary endpoint of the study was the occurrence of major adverse cardiac events (MACE), defined as a composite of cardiac death, readmission for worsening heart failure (WHF), revascularization and myocardial infarction (MI). RESULTS: After PSM, there were a total of 246 individuals in the PCI and OMT groups. Following Cox regression, hibernating myocardium/total perfusion defect (HM/TPD) was identified as an independent risk factor (hazard ratio (HR): 1.03, 95% confidence interval (CI): 1.008-1.052, p = .007). The cut-off value of HM/TPD was 38%. The results of the subgroup analysis suggest that for patients with HM/TPD >38%, the OMT group had a greater risk of MACE (p = .035). A sensitivity analysis restricting patients with single-vessel CTO lesions, HM/TPD remained an independent predictor (HR 1.025, 95% CI 1.008-1.043, p = .005). CONCLUSION: HM/TPD is an independent predictor of MACE, and for patients with HM/TPD > 38%, CTO-PCI had a lower risk of MACE compared with OMT. However, further validation is still needed through large-scale studies.

Temporal compressive edge imaging enabled by a lensless diffuser camera.

Lensless imagers based on diffusers or encoding masks enable high-dimensional imaging from a single-shot measurement and have been applied in various applications. However, to further extract image information such as edge detection, conventional post-processing filtering operations are needed after the reconstruction of the original object images in the diffuser imaging systems. Here, we present the concept of a temporal compressive edge detection method based on a lensless diffuser camera, which can directly recover a time sequence of edge images of a moving object from a single-shot measurement, without further post-processing steps. Our approach provides higher image quality during edge detection, compared with the "conventional post-processing method." We demonstrate the effectiveness of this approach by both numerical simulation and experiments. The proof-of-concept approach can be further developed with other image post-processing operations or versatile computer vision assignments toward task-oriented intelligent lensless imaging systems.

Machine learning-based coronary artery calcium score predicted from clinical variables as a prognostic indicator in patients referred for invasive coronary angiography.

OBJECTIVES: Utilising readily available clinical variables, we aimed to develop and validate a novel machine learning (ML) model to predict severe coronary calcification, and further assessed its prognostic significance. METHODS: This retrospective study enrolled patients who underwent coronary CT angiography and subsequent invasive coronary angiography. Multiple ML algorithms were used to train the models for predicting severe coronary calcification (cardiac CT-measured coronary artery calcium [CT-CAC] score ≥ 400). The ML-based CAC (ML-CAC) score derived from the ML predictive probability was stratified into quartiles for prognostic analysis. The primary endpoint was a composite of all-cause death, nonfatal myocardial infarction, or nonfatal stroke. RESULTS: Overall, 5785 patients were divided into training (80%) and test sets (20%). For clinical practicability, we selected the nine-feature support vector machine model with good and satisfactory performance regarding both discrimination and calibration based on five repetitions of the 10-fold cross-validation in the training set (mean AUC = 0.715, Brier score = 0.202), and based on the test in the test set (AUC = 0.753, Brier score = 0.191). In the test set cohort (n = 1137), the primary endpoint was observed in 50 (4.4%) patients during a median 2.8 years' follow-up. The ML-CAC system was significantly associated with an increased risk of the primary endpoint (adjusted hazard ratio for trend 2.26, 95% CI 1.35-3.79, p = 0.002). There was no significant difference in the prognostic value between the ML-CAC and CT-CAC systems (C-index, 0.67 vs. 0.69; p = 0.618). CONCLUSION: ML-CAC score predicted from clinical variables can serve as a novel prognostic indicator in patients referred for invasive coronary angiography. CLINICAL RELEVANCE STATEMENT: In patients referred for invasive coronary angiography who have not undergone preoperative CT-measured coronary artery calcium scoring, machine learning-based coronary artery calcium score assessment can serve as an alternative for predicting the prognosis. KEY POINTS: • The coronary artery calcium (CAC) score, a solid prognostic indicator, can be predicted using non-CT methods. • We developed a machine learning (ML)-CAC model utilising nine clinical variables to predict severe coronary calcification. • The ML-CAC system offers significant prognostic value in patients referred for invasive coronary angiography.

Comparison of intravascular lithotripsy versus rotational atherectomy for the treatment of severe coronary artery calcification.

BACKGROUND: Calcified lesions are one of the most challenging cases for PCI, where optimal angiographic results and satisfying outcomes are hard to achieve. METHODS: We evaluated the baseline clinical, procedures characteristics and outcomes of patients with severe coronary artery calcification (CAC) who underwent coronary intravascular lithotripsy (IVL) and rotational atherectomy (RA). RESULTS: Respectively 152 and 238 patients who underwent IVL and RA are enrolled from January 2023 to November 2023. Regarding demographic characteristics, the gender proportion, medical history of PCI and smoke history among groups reach statistical significance. Left anterior descending and right coronary artery were the main vessels treated in both groups. The 2.5 and 3.0 mm IVL balloons and 1.5 mm burr were the most commonly used. 99.3% cases were successfully implanted drug-eluting stents after IVL balloon pre-treatment, which was higher than in the group treated with RA. During hospitalization, there were no serious adverse events in the IVL group, but there were two adverse events in the RA group. Procedural complications were higher in the RA group than the IVL group (5.5% vs. 0.7%, P = 0.027). CONCLUSIONS: IVL appears to be safe and effective for the treatment of severe CAC lesions compared to RA.

Efficacy and safety of drug-coated balloons in chronic total coronary occlusion recanalization: a systematic review and meta-analysis.

BACKGROUND: With advancements in chronic total coronary occlusion (CTO) recanalization techniques and concepts, the success rate of recanalization has been steadily increasing. However, the current data are too limited to draw any reliable conclusions about the efficacy and safety of drug-coated balloons (DCBs) in CTO percutaneous coronary intervention (PCI). Herein, we conducted a meta-analysis to confirm the efficacy of DCB in CTO PCI. METHODS: We systematically searched PubMed, Web of Science and Embase from inception to July 25, 2023. The primary outcome was major advent cardiovascular events (MACE), including cardiac death, nonfatal myocardial infarction (MI), target lesion revascularization (TLR), and target vessel revascularization (TVR). The follow-up angiographic endpoints were late lumen enlargement (LLE), reocclusion and restenosis. RESULTS: Five studies with a total of 511 patients were included in the meta-analysis. Across studies, patients were predominantly male (72.9-85.7%) and over fifty years old. The summary estimate rate of MACE was 13.0% (95% CI 10.1%-15.9%, I2 = 0%, p = 0.428). The summary estimate rates of cardiac death and MI were 2.2% (95% CI 0.7%-3.7%, I2 = 0%, p = 0.873) and 1.2% (95% CI -0.2-2.6%, I2 = 13.7%, p = 0.314), respectively. Finally, the pooled incidences of TLR and TVR were 10.1% (95% CI 5.7%-14.5%, I2 = 51.7%, p = 0.082) and 7.1% (95% CI 3.0%-11.2%, I2 = 57.6%, p = 0.070), respectively. Finally, the summary estimate rates of LLE, reocclusion and restenosis were 59.4% (95% CI 53.5-65.3%, I2 = 0%, p = 0.742), 3.3% (95% CI 1.1-5.4%, I2 = 0%, p = 0.865) and 17.5% (95% CI 12.9-22.0%, I2 = 0%, p = 0.623), respectively. CONCLUSION: Accordingly, DCB has the potential to be used as a treatment for CTO in suitable patients.

Hepatocyte-secreted DPP4 in obesity promotes adipose inflammation and insulin resistance.

Obesity-induced metabolic disease involves functional integration among several organs via circulating factors, but little is known about crosstalk between liver and visceral adipose tissue (VAT). In obesity, VAT becomes populated with inflammatory adipose tissue macrophages (ATMs). In obese humans, there is a close correlation between adipose tissue inflammation and insulin resistance, and in obese mice, blocking systemic or ATM inflammation improves insulin sensitivity. However, processes that promote pathological adipose tissue inflammation in obesity are incompletely understood. Here we show that obesity in mice stimulates hepatocytes to synthesize and secrete dipeptidyl peptidase 4 (DPP4), which acts with plasma factor Xa to inflame ATMs. Silencing expression of DPP4 in hepatocytes suppresses inflammation of VAT and insulin resistance; however, a similar effect is not seen with the orally administered DPP4 inhibitor sitagliptin. Inflammation and insulin resistance are also suppressed by silencing expression of caveolin-1 or PAR2 in ATMs; these proteins mediate the actions of DPP4 and factor Xa, respectively. Thus, hepatocyte DPP4 promotes VAT inflammation and insulin resistance in obesity, and targeting this pathway may have metabolic benefits that are distinct from those observed with oral DPP4 inhibitors.

Shared molecular signatures between systemic lupus erythematosus and osteoporosis.

This study explores the molecular interplay between systemic lupus erythematosus (SLE) and osteoporosis (OP), aiming to uncover shared gene signatures and pathways for better treatment approaches. Leveraging microarray data from the Gene Expression Omnibus (GEO) database, we employed weighted gene coexpression network analysis to identify coexpression modules in SLE and OP, with subsequent protein-protein interaction analysis clarifying the connections among shared genes. Key genes were pinpointed using CytoHubba and random forest algorithms, validated across independent GEO datasets, and further analyzed through gene set enrichment analysis (GSEA) and immune infiltration studies. We discovered two highly correlated modules in SLE and OP, isolating 30 shared genes and identifying GBP1, SOCS1, IFI16, and XAF1 as central to both conditions. Notably, XAF1 and GBP1 mRNA levels were significantly elevated in the peripheral blood of SLE patients compared with healthy and RA counterparts, underscoring their potential as biomarkers. GSEA and immune infiltration analyses indicated pronounced immune and inflammatory responses, especially in interferon signaling pathways, implicating these core-shared gene networks in the diseases' pathogenesis. The findings highlight the involvement of GBP1, SOCS1, IFI16, and XAF1 in SLE with concurrent OP and suggest that targeting immune and inflammatory responses, particularly through interferon pathways, may offer therapeutic promise for these intertwined conditions.

Optical Monitoring of In Situ Iron Loading into Single, Native Ferritin Proteins.

Ferritin is a protein that stores and releases iron to prevent diseases associated with iron dysregulation in plants, animals, and bacteria. The conversion between iron-loaded holo-ferritin and empty apo-ferritin is an important process for iron regulation. To date, studies of ferritin have used either ensemble measurements to quantify the characteristics of a large number of proteins or single-molecule approaches to interrogate labeled or modified proteins. Here we demonstrate the first real-time study of the dynamics of iron ion loading and biomineralization within a single, unlabeled ferritin protein. Using optical nanotweezers, we trapped single apo- and holo-ferritins indefinitely, distinguished one from the other, and monitored their structural dynamics in real time. The study presented here deepens the understanding of the iron uptake mechanism of ferritin proteins, which may lead to new therapeutics for iron-related diseases.

Facile Fabrication of Hollow Nanoporous Carbon Architectures by Controlling MOF Crystalline Inhomogeneity for Ultra-Stable Na-Ion Storage.

Hollow nanoporous carbon architectures (HNCs) present significant utilitarian value for a wide variety of applications. Facile and efficient preparation of HNCs has long been pursued but still remains challenging. Herein, we for the first time demonstrate that single-component metal-organic frameworks (MOFs) crystals, rather than the widely reported hybrid ones which necessitate tedious operations for preparation, could enable the facile and versatile syntheses of functional HNCs. By controlling the growth kinetics, the MOFs crystals (STU-1) are readily engineered into different shapes with designated styles of crystalline inhomogeneity. A subsequent one-step pyrolysis of these MOFs with intraparticle difference can induce a simultaneous self-hollowing and carbonization process, thereby producing various functional HNCs including yolk-shell polyhedrons, hollow microspheres, mesoporous architectures, and superstructures. Superior to the existing methods, this synthetic strategy relies only on the complex nature of single-component MOFs crystals without involving tedious operations like coating, etching, or ligand exchange, making it convenient, efficient, and easy to scale up. An ultra-stable Na-ion battery anode is demonstrated by the HNCs with extraordinary cyclability (93 % capacity retention over 8000 cycles), highlighting a high level of functionality of the HNCs.

Multiple Accessible Redox-Active Sites in a Robust Covalent Organic Framework for High-Performance Potassium Storage.

Covalent organic framework (COF) materials with porous character and robust structure have significant applied implications for K-ion battery (KIB) anodes, but they are limited by the low reversible capacity and inferior rate capability. Here, based on theoretical calculations, we identified that a porous bulk COF featuring numerous pyrazines and carbonyls in the π-conjugated periodic skeleton could provide multiple accessible redox-active sites for high-performance potassium storage. Its porous structure with a surface-dominated storage mechanism enabled the fast and stable storage of K-ions. Its insolubility in organic electrolytes and small volumetric change after potassiation ensured a robust electrode for stable cycling. As a KIB anode, this bulk COF demonstrated an unprecedentedly outstanding combination of reversible capacity (423 mAh g-1 at 0.1 C), rate capability (185 mAh g-1 at 10 C), and cyclability. The theoretical simulation and comprehensive characterizations confirmed the active sites are contributed by C═O, C═N, and the cation-π effect.

Ultrafast Photocatalytic Detoxification of Mustard Gas Simulants by a Mesoporous Metal-Organic Framework with Dangling Porphyrin Molecules.

Developing effective catalysts to degrade chemical warfare agents is of great significance. Herein, a mesoporous MIL-101(Cr) composite material dangled with porphyrin molecules (denote as TCPP@MIL-101(Cr), TCPP = tetra(4-carboxyphenyl)porphyrin) is reported, which can be used as a heterogeneous photocatalyst for detoxification of mustard gas simulants 2-chloroethyl ethyl sulfide (CEES) to 2-chloroethyl ethyl sulfoxide (CEESO) with a half-life of 1 min. The catalytic performance of TCPP@MIL-101(Cr) is comparable to that of homogeneous molecular porphyrin. Mechanistic studies reveal that both 1 O2 and O2 •- are efficiently generated and play vital roles in the oxidation reaction. Gold nanoparticles (AuNPs) are attached to the TCPP@MIL-101(Cr) to further enhance the catalytic activity with a benchmark half-life of 45 s, which is the fastest record so far. A medical mask loaded TCPP@MIL-101(Cr) is fabricated for practical applications, which can selectively photoxidize CEES to CEESO under sunlight and air atmosphere, exhibiting the best degradation performance among the reported fabric-like composite materials.

Prominent Structural Dependence of Quantum Capacitance Unraveled by Nitrogen-Doped Graphene Mesosponge.

Porous carbons are important electrode materials for supercapacitors. One of the challenges associated with supercapacitors is improving their energy density without relying on pseudocapacitance, which is based on fast redox reactions that often shorten device lifetimes. A possible solution involves achieving high total capacitance (Ctot ), which comprises Helmholtz capacitance (CH ) and possibly quantum capacitance (CQ ), in high-surface carbon materials comprising minimally stacked graphene walls. In this work, a templating method is used to synthesize 3D mesoporous graphenes with largely identical pore structures (≈2100 m2 g-1 with an average pore size of ≈7 nm) but different concentrations of oxygen-containing functional groups (0.3-6.7 wt.%) and nitrogen dopants (0.1-4.5 wt.%). Thus, the impact of the heteroatom functionalities on Ctot is systematically investigated in an organic electrolyte excluding the effect of pore structures. It is found that heteroatom functionalities determine Ctot , resulting in the cyclic voltammetry curves being rectangular or butterfly-shaped. The nitrogen functionalities are found to significantly enhance Ctot owing to increased CQ .

Extreme Risk of Sudden Cardiac Death within Three Months after Revascularization in Patients with Ischemic Left Ventricular Systolic Dysfunction.

Background: The risk of sudden cardiac death (SCD) after coronary revascularization in patients with left ventricular (LV) systolic dysfunction has not been characterized completely. This study aims to evaluate the incidence and time course of SCD after revascularization in such patients. The determinants of SCD within 3 months after revascularization were also assessed. Methods: A cohort study of patients with reduced ejection fraction (EF ≤ 40%), who underwent revascularization was performed. The incidence of SCD was estimated to account for the competing risk of deaths due to other causes. Results: 2317 patients were enrolled. With a median follow-up of 3.5 years, 162 (32.1%) of the 504 deaths were due to SCD. The risk of SCD was highest in the first 3 months after revascularization, with an incidence rate of 0.37%/month. The event rate decreased to 0.12%/month, 0.08%/month, 0.09%/month, 0.14%/month, and 0.19%/month at 3-6 months, 6-12 months, 1-3 years, 3-5 years, and 5-10 years, respectively. A history of ventricular tachycardia/ventricular fibrillation (hazard ratio [HR], 5.55; 95% confidence interval [CI], 1.33-23.19; p = 0.019) and triple vessel disease (HR, 3.90; 95% CI, 1.38-11.05; p = 0.010) were associated with the risk of SCD within 3 months. However, preoperative EF (in 5% increments) was not predictive (HR per 5% increase, 0.98; 95% CI, 0.62-1.55; p = 0.935). Conclusions: For patients with LV dysfunction, the risk of SCD was the highest during the first 3 months after revascularization. Further risk classification and treatment strategy are warranted. Clinical Trial Registration: The name of the registry: Coronary Revascularization in Patients with Ischemic Heart Failure and Prevention of Sudden Cardiac Death. Registration number: ChiCTR2100044378.

Risk Factor Analysis and Multiple Predictive Machine Learning Models for Mortality in COVID-19: A Multicenter and Multi-Ethnic Cohort Study.

BACKGROUND: The COVID-19 pandemic presents a significant challenge to the global health care system. Implementing timely, accurate, and cost-effective screening approaches is crucial in preventing infections and saving lives by guiding disease management. OBJECTIVES: The study aimed to use machine learning algorithms to analyze clinical features from routine clinical data to identify risk factors and predict the mortality of COVID-19. METHODS: The data used in this research were originally collected for the study titled "Neurologic Syndromes Predict Higher In-Hospital Mortality in COVID-19." A total of 4711 patients with confirmed COVID-19 were enrolled consecutively from four hospitals. Three machine learning models, including random forest (RF), partial least squares discriminant analysis (PLS-DA), and support vector machine (SVM), were used to find risk factors and predict COVID-19 mortality. RESULTS: The predictive models were developed based on three machine learning algorithms. The RF model was trained with 20 variables and had a receiver operating characteristic (ROC) value of 0.859 (95% confidence interval [CI] 0.804-0.920). The PLS-DA model was trained with 20 variables and had a ROC value of 0.775 (95% CI 0.694-0.833). The SVM model was trained with 10 variables and had a ROC value of 0.828 (95% CI 0.785-0.865). The nine variables that were present in all three models were age, procalcitonin, ferritin, C-reactive protein, troponin, blood urea nitrogen, mean arterial pressure, aspartate transaminase, and alanine transaminase. CONCLUSION: This study developed and validated three machine learning prediction models for COVID-19 mortality based on accessible clinical features. The RF model showed the best performance among the three models. The nine variables identified in the models may warrant further investigation as potential prognostic indicators of severe COVID-19.

Elevated NRAS expression during DCIS is a potential driver for progression to basal-like properties and local invasiveness.

BACKGROUND: Ductal carcinoma in situ (DCIS) is the most common type of in situ premalignant breast cancers. What drives DCIS to invasive breast cancer is unclear. Basal-like invasive breast cancers are aggressive. We have previously shown that NRAS is highly expressed selectively in basal-like subtypes of invasive breast cancers and can promote their growth and progression. In this study, we investigated whether NRAS expression at the DCIS stage can control transition from luminal DCIS to basal-like invasive breast cancers. METHODS: Wilcoxon rank-sum test was performed to assess expression of NRAS in DCIS compared to invasive breast tumors in patients. NRAS mRNA levels were also determined by fluorescence in situ hybridization in patient tumor microarrays (TMAs) with concurrent normal, DCIS, and invasive breast cancer, and association of NRAS mRNA levels with DCIS and invasive breast cancer was assessed by paired Wilcoxon signed-rank test. Pearson's correlation was calculated between NRAS mRNA levels and basal biomarkers in the TMAs, as well as in patient datasets. RNA-seq data were generated in cell lines, and unsupervised hierarchical clustering was performed after combining with RNA-seq data from a previously published patient cohort. RESULTS: Invasive breast cancers showed higher NRAS mRNA levels compared to DCIS samples. These NRAShigh lesions were also enriched with basal-like features, such as basal gene expression signatures, lower ER, and higher p53 protein and Ki67 levels. We have shown previously that NRAS drives aggressive features in DCIS-like and basal-like SUM102PT cells. Here, we found that NRAS-silencing induced a shift to a luminal gene expression pattern. Conversely, NRAS overexpression in the luminal DCIS SUM225 cells induced a basal-like gene expression pattern, as well as an epithelial-to-mesenchymal transition signature. Furthermore, these cells formed disorganized mammospheres containing cell masses with an apparent reduction in adhesion. CONCLUSIONS: These data suggest that elevated NRAS levels in DCIS are not only a marker but can also control the emergence of basal-like features leading to more aggressive tumor activity, thus supporting the therapeutic hypothesis that targeting NRAS and/or downstream pathways may block disease progression for a subset of DCIS patients with high NRAS.

Observation of Topological p-Orbital Disclination States in Non-Euclidean Acoustic Metamaterials.

Disclinations-topological defects ubiquitously existing in various materials-can reveal the intrinsic band topology of the hosting material through the bulk-disclination correspondence. In low-dimensional materials and nanostructure such as graphene and fullerenes, disclinations yield curved surfaces and emergent non-Euclidean geometries that are crucial in understanding the properties of these materials. However, the bulk-disclination correspondence has never been studied in non-Euclidean geometry, nor in systems with p-orbital physics. Here, by creating p-orbital topological acoustic metamaterials with disclination-induced conic and hyperbolic surfaces, we demonstrate the rich emergent bound states arising from the interplay among the real-space geometry, the bulk band topology, and the p-orbital physics. This phenomenon is confirmed by clear experimental evidence that is consistent with theory and simulations. Our experiment paves the way toward topological phenomena in non-Euclidean geometries and will stimulate interesting research on, e.g., topological phenomena for electrons in nanomaterials with curved surfaces.