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Hypertrophic cardiomyopathy(HCM) is one of the most common hereditary cardiomyopathy, the most serious outcome of which is sudden cardiac death(SCD). Early recognition and prevention may delay or avoid the onset of cardiac arrest. Therefore, it is important to identify the high-risk factors of SCD in patients with HCM and prevent cardiac arrest. At present, the recognized high risk factors mainly include family history of sudden death, non-sustained ventricular tachycardia, severe left ventricular hypertrophy, unexplained syncope, end-stage HCM with left ventricular ejection fraction < 50%, left ventricular systolic dysfunction of any size, and extensive late gadolinium enhancement. The main preventive measures involvemedical treatment, surgical septal myectomy, alcohol septal ablation, and implantable cardiac defibrillator. This article mainly focuses on the identification of high-risk factors and prevention strategies of SCD caused by HCM, and reviews the latest progress of diagnosis, treatment and prevention of HCM, to provide guidance for prevention of SCD caused by HCM.

BACKGROUND Heavy metals and polycyclic aromatic hydrocarbons (PAHs) are the ecological research focus because of their teratogenicity, carcinogenicity, and mutagenicity. Hainan Island is China's first ecological civilization pilot area, and the continuous acceleration of urbanization will increase the pressure on environmental protection in the estuary area. The Changhua River, the Luodai River, and the Sanya River are important seagoing rivers in Hainan Island. At present, there is a lack of reports on heavy metals and polycyclic aromatic hydrocarbons in the sediments of the Changhua and Luodai Rivers, and there are differences in the related research results of the Sanya River. OBJECTIVES To understand the characteristics, source, and ecological risk of heavy metals and PAHs in surface sediments from the estuary of the Changhua, Luodai, and Sanya Rivers in Hainan Island. METHODS Sediment samples from the three estuaries were collected. Inductively coupled plasma-mass spectrometry/optical emission spectrometry (ICP-MS/OES) and atomic fluorescence spectrometry were used to determine the content of heavy metals (As, Cd, Cr, Cu, Hg, Ni, Pb, Zn). Gas chromatography-mass spectrometry was used to determine the content of PAHs. Source apportionment was further explored based on the correlation analysis and composition of the contaminants, and the ecological risk evaluation was carried out with the potential ecological risk index (PERI) and sediment quality guidelines (SQGs). RESULTS The average contents of As, Cd, Cr, Cu, Hg, Ni, Pb, and Zn in the sediments of Changhua River were 3.24, 0.03, 7.03, 5.33, 0.007, 3.06, 16.9, and 14.1mg/kg, respectively. The corresponding values of these metals in Luodai River were 4.81, 0.02, 7.69, 4.56, 0.010, 3.29, 18.3, and 14.7mg/kg, and the corresponding values in Sanya River were 5.83, 0.05, 15.3, 8.28, 0.021, 4.91, 21.4, and 29.8mg/kg. Exception to As, the concentration of other heavy metals in the sediments were below or close to the Hainan soil baseline, showing little heavy metals accumulation effect. The contents of PAHs in the sediment range from 3.48 to 56.6μg/kg, from 8.72 to 56.8μg/kg, and from 6.41 to 573.9μg/kg for the Changhua, Luodai, and Sanya River, respectively. Compared with other regions, the sediment PAHs content in the study area was relatively low. CONCLUSIONS Arsenic in the estuarine sediments of the three rivers and Cd, Cu in the Sanya River are strongly influenced by anthropogenic factors, while the regional background mainly influences the remaining elements. PAHs originated mostly from the low-temperature combustion of biomass. The ecological risk evaluation demonstrates that the biotoxic effect of the heavy metals and PAHs is not obvious, mostly with low ecological risk. The present study on heavy metals and PAHs contamination in surface sediments of the three estuaries will provide a reference for future research.

Children tend to produce words earlier when they are connected to a variety of other words along the phonological and semantic dimensions. Though these semantic and phonological connectivity effects have been extensively documented, little is known about their underlying developmental mechanism. One possibility is that learning is driven by lexical network growth where highly connected words in the child's early lexicon enable learning of similar words. Another possibility is that learning is driven by highly connected words in the external learning environment, instead of highly connected words in the early internal lexicon. The present study tests both scenarios systematically in both the phonological and semantic domains across 10 languages. We show that phonological and semantic connectivity in the learning environment drives growth in both production- and comprehension-based vocabularies, even controlling for word frequency and length. This pattern of findings suggests a word learning process where children harness their statistical learning abilities to detect and learn highly connected words in the learning environment.

Children tend to produce words earlier when they are connected toa variety of other words along both the phonological and semanticdimensions. Though this connectivity effect has been extensivelydocumented, little is known about the underlying developmentalmechanism. One view suggests that learning is primarily drivenby a network growth model where highly connected words in thechild’s early lexicon attract similar words. Another view suggeststhat learning is driven by highly connected words in the externallearning environment instead of highly connected words in the earlyinternal lexicon. The present study tests both scenarios system-atically in both the phonological and semantic domains, and across8 languages. We show that external connectivity in the learningenvironment drives growth in both the semantic and the phonolog-ical networks, and that this pattern is consistent cross-linguistically.The findings suggest a word learning mechanism where childrenharness their statistical learning abilities to (indirectly) detect andlearn highly connected words in the learning environment.

We explore miR‐150‐5p in atherosclerosis (AS). The AS model was constructed using Apo E−/− mice with an injection of the miR-150-5p mimic or an inhibitor. Pathological characteristics were assessed using Oil red O staining and Masson staining. Quantitative reverse transcription-polymerase chain reaction (qRT-PCR) and Western blot were used to analyze the expressions of microRNA-150-5p (miR-150-5p), STAT1, α-SMA (α-smooth muscle actin) and proliferating cell nuclear antigen (PCNA). Targetscan and dual-luciferase reporter assay were used to analyze the interaction between miR-150-5p and STAT1. The viability, migration, cell cycle and α-SMA and PCNA expressions in oxidized low-density lipoprotein (ox-LDL)-stimulated primary human aortic smooth muscle cells (ASMCs) were assessed using molecular experiments. miR-150-5p was reduced in both AS mice and ox-LDL-stimulated human aortic smooth muscle cells but STAT1 had the opposite effect. The miR‐150‐5p inhibitor alleviated the increase of lipid plaque and reduced collagen accumulation in the aortas during AS. Upregulation of α-SMA and PCNA was reversed by miR-150-5p upregulation. STAT1 was targeted by miR‐150‐5p, and overexpressed miR-150-5p weakened the ox-LDL-induced increase of viability and migration abilities and blocked cell cycle in ASMCs, but overexpressed STAT1 blocked the effect of the miR‐150‐5p mimic. This paper demonstrates that miR-150-5p has potential as a therapeutic target in AS, with plaque stabilization by regulating ASMC proliferation and migration via STAT1.