Long Non-Coding RNAs as Master Regulators in Cardiovascular Diseases

Cardiovascular disease is the leading cause of death in the United States, accounting for nearly one in every seven deaths. Over the last decade, various targeted therapeutics have been introduced, but there has been no corresponding improvement in patient survival. Since the mortality rate of cardiovascular disease has not been significantly decreased, efforts have been made to understand the link between heart disease and novel therapeutic targets such as non-coding RNAs. Among multiple non-coding RNAs, long non-coding RNA (lncRNA) has emerged as a novel therapeutic in cardiovascular medicine. LncRNAs are endogenous RNAs that contain over 200 nucleotides and regulate gene expression. Recent studies suggest critical roles of lncRNAs in modulating the initiation and progression of cardiovascular diseases. For example, aberrant lncRNA expression has been associated with the pathogenesis of ischemic heart failure. In this article, we present a synopsis of recent discoveries that link the roles and molecular interactions of lncRNAs to cardiovascular diseases. Moreover, we describe the prevalence of circulating lncRNAs and assess their potential utilities as biomarkers for diagnosis and prognosis of heart disease.     

Disseminated tuberculosis: A neglected entity in immunocompromised hemodialysis patients

End‐stage renal disease is considered a factor predisposing to increased risk of tuberculosis with frequent extrapulmonary localization. Although extrapulmonary tuberculosis has been observed for decades, disseminated tuberculosis, a major cause of morbidity and mortality in immunocompromised hosts, remains rather neglected. We report an unusual case of an immunocompromised patient with a late diagnosis and delayed treatment of genitourinary tuberculosis that subsequently led to the diagnosis of vertebral and miliary tuberculosis (disseminating tuberculosis). Therefore, increased awareness is warranted from physicians dealing with hemodialysis patients in order to avoid delays in diagnosis and treatment initiation.     

FogMed: A Fog-Based Framework for Disease Prognosis Based Medical Sensor Data Streams

Recently, an increasing number of works start investigating the combination of fog computing and electronic health (ehealth) applications. However, there are still numerous unresolved issues worth to be explored. For instance, there is a lack of investigation on the disease prediction in fog environment and only limited studies show, how the Quality of Service (QoS) levels of fog services and the data stream mining techniques influence each other to improve the disease prediction performance (e.g., accuracy and time efficiency). To address these issues, we propose a fog-based framework for disease prediction based on Medical sensor data streams, named FogMed. This framework aims to improve the disease prediction accuracy by achieving two objectives: QoS guarantee of fog services and anomaly prediction of Medical data streams. We build a virtual FogMed environment and conduct comprehensive experiments on the public ECG dataset to validate the performance of FogMed. The experiment results show that it performs better than the cloud computing model for processing tasks with different complexities in terms of time efficiency.     

Evaluating the commercial airliner cabin environment with different air distribution systems

Ventilation systems for commercial airliner cabins are important in reducing contaminant transport and maintaining thermal comfort. To evaluate the performance of a personalized displacement ventilation system, a conventional displacement ventilation system, and a mixing ventilation system, this study first used the Wells‐Riley equation integrated with CFD to obtain the SARS quanta value based on a specific SARS outbreak on a flight. This investigation then compared the three ventilation systems in a seven‐row section of a fully occupied, economy‐class cabin in Boeing 737 and Boeing 767 airplanes. The SARS quanta generation rate obtained for the index patient could be used in future studies. For all the assumed source locations, the passengers’ infection risk by air in the two planes was the highest with the mixing ventilation system, while the conventional displacement ventilation system produced the lowest risk. The personalized ventilation system performed the best in maintaining cabin thermal comfort and can also reduce the infection risk. This system is recommended for airplane cabins.     

Visualization analysis of heart diseases using two‐dimensional electrocardiogram sequences

During the last years, there have been large advances in the understanding of cardiac mechanics, and in particular shape, motion and deformation. However, it is important to comprehend how these features interrelate and how they can be interpreted to refine the clinical diagnosis. The goal of our study is to illustrate the use of two‐dimensional ultrasound cardiac motion sequences on some typical cardiac pathologies. The method is applied to preprocessed data from two‐dimensional ultrasound sequences of four different subjects, namely, two healthy volunteers, one patient with left ventricular mechanical dyssynchrony from the left bundle branch block, and one patient with hypertrophic cardiomyopathy. The interpretation based on these features is corroborated with other analyzing techniques such as electrocardiogram and visual interpretation by experienced clinical observers. The proposed method realizes a computer program, which allows the user to easily obtain and visualize information about myocardial shape, motion (displacement and velocity), and deformation (strain) along the left ventricle myocardium wall during the cardiac cycle.     

A Self-Healing Nanofiber-Based Self-Responsive Time-Temperature Indicator for Securing a Cold-Supply Chain

Perishable foods at undesired temperatures can generate foodborne illnesses that present significant societal costs. To certify refrigeration succession in a food-supply chain, a flexible, easy-to-interpret, damage-tolerant, and sensitive time-temperature indicator (TTI) that uses a self-healing nanofiber mat is devised. This mat is opaque when refrigerated due to nanofiber-induced light scattering, but becomes irreversibly transparent at room temperature through self-healing-induced interfibrillar fusion leading to the appearance of a warning sign. The mat monitors both freezer (−20 °C) and chiller (2 °C) successions and its timer is tunable over the 0.5–22.5 h range through control of the polymer composition and film thickness. The thin mat itself serves as both a temperature sensor and display; it does not require modularization, accurately measures localized or gradient heat, and functions even after crushing, cutting, and when weight-loaded in a manner that existing TTIs cannot. It also contains no drainable chemicals and is attachable to various shapes because it operates through an intrinsic physical response.     

贵州水晶葡萄病原真菌分离鉴定及室内抑菌活性测试

[目的]确定引起贵州水晶葡萄采后贮藏病害的病原真菌种类及室内筛选用于该病害的主要防治杀菌剂。[方法]对病原菌进行分离纯化鉴定,通过科赫法则确定致病菌种类;筛选12种商品杀菌剂对炭疽病菌进行抑菌活性测定,筛选出有效药剂,为防治该病害提供一定的理论依据。[结果]从贵州省凯里市水晶葡萄采后贮藏病害分离鉴定出3株病原菌,为青霉菌(Penicillium sp.)、炭疽病菌(Clletotrichum gloeosporioides)和链格孢菌(Alternaria sp.),采用科赫法则,对3株病原真菌进行刺伤回接,发现3株均为水晶葡萄在贮藏过程中的主要致病菌。12种杀菌剂对水晶葡萄炭疽病菌进行室内抑菌活性测试结果表明:均具有较好的抑制活性,其中50%咯菌腈WP、50%苯菌灵WP、42%噻菌灵SC和43%戊唑醇SC对水晶葡萄炭疽病菌抑制活性最好,其EC50值分别为0.1024、0.1386、0.1624、0.1974 mg/L。[结论]凯里水晶葡萄采后病害病菌为青霉菌、炭疽病菌和链格孢菌;筛选出12种药剂针对水晶葡萄采后病害炭疽病菌的药剂,其中50%咯菌腈WP对炭疽病菌具有较好抑制效果,为水晶葡萄采后贮藏病害防治提供理论基础。     

Pharmacotherapeutics and molecular docking studies of alpha-synuclein modulators as promising therapeutics for Parkinson’s disease

Parkinson’s disease (PD) is an age-related neurodegenerative ailment that affects dopamine-producing neurons in a specific area of the brain called the substantia nigra of the ventral midbrain. It is clinically characterized by movement disorder and marked with unusual synaptic protein alpha-synuclein accumulation in the brain. To date, only a few Food and Drug Administration (FDA) approved drugs are available on the market for the treatment of PD. Nonetheless, these drugs show parasympathomimetic related adverse events and remarkably higher toxicity; hence, it is important to find more efficacious molecules to treat PD. In our study, We chosen 22 natural compounds as inhibitors that potentially block the alpha-synuclein clump—the pathological hallmark of PD—and provide new avenues for its treatment. Most of these molecules exhibited good pharmacokinetic behaviors, making them decisively favorable drug candidates to cure PD. Molecular docking studies were performed to investigate the binding interactions between natural compounds and alpha-synuclein as anti-Parkinson drug targets. Among the examined compounds, curcumin and piperine emerged as promising phytochemicals with the highest binding affinity, key residual stable bindings and showed a good inhibitory features. Thus, the present study indicates that curcumin and piperine hold the potential to be developed as treatment options against PD. Experimental validations are needed for insights into their mechanism of action and potential clinical application.     

胆汁酸代谢调节炎症性肠病的作用机制及药物研发

炎症性肠病（IBD）是一种慢性复发性肠道炎症性疾病，发病率及非致死性疾病负担在全世界都有累加的趋势，其病因复杂，发病机制目前还未完全明确。胆汁酸（BAs）是胆汁的主要成份，其可通过与胆汁酸受体结合、调节肠道菌群等参与IBD的发生发展。本文着重讨论BAs代谢在IBD发病中的作用机制，以及基于BAs及其相关靶点的药物研发进展，为今后IBD的预防、治疗和预后研究奠定基础。