Ocular conditions and dry eye due to traditional and new forms of smoking: A review

Addiction to cigarette smoking has high prevalence rates recorded worldwide. Smoking has been linked to several life-threatening systemic conditions such as cancer, heart attack and stroke, in addition to a range of ocular pathologies. In recent years, electronic cigarettes (EC) have emerged as alternatives to smoking. ECs are nicotine delivery devices which produce an aerosol by heating, rather than combusting, a liquid which contains nicotine, flavours and preservatives. This review focuses on the association of traditional and new forms of smoking with dry eye disease, contact lens wear and four other common ocular diseases: cataract, age-related macular degeneration, glaucoma and Graves’ ophthalmopathy. It is concluded that smoking and vaping appear as a risk factor for the aforementioned ocular conditions. An evidence-based, clear link between cigarette smoking, or EC vaping and ocular problems is yet to be discovered.     

Clinical Characteristics and Outcomes of Type 2 Diabetes Patients Infected with COVID-19: A Retrospective Study

Diabetes and its related metabolic disorders have been reported as the leading comorbidities in patients with coronavirus disease 2019 (COVID-19). This clinical study aims to investigate the clinical features, radiographic and laboratory tests, complications, treatments, and clinical outcomes in COVID-19 patients with or without diabetes. This retrospective study included 208 hospitalized patients (≥ 45 years old) with laboratory-confirmed COVID-19 during the period between 12 January and 25 March 2020. Information from the medical record, including clinical features, radiographic and laboratory tests, complications, treatments, and clinical outcomes, were extracted for the analysis. 96 (46.2%) patients had comorbidity with type 2 diabetes. In COVID-19 patients with type 2 diabetes, the coexistence of hypertension (58.3% vs 31.2%), coronary heart disease (17.1% vs 8.0%), and chronic kidney diseases (6.2% vs 0%) was significantly higher than in COVID-19 patients without type 2 diabetes. The frequency and degree of abnormalities in computed tomography (CT) chest scans in COVID-19 patients with type 2 diabetes were markedly increased, including ground-glass opacity (85.6% vs 64.9%, P < 0.001) and bilateral patchy shadowing (76.7% vs 37.8%, P < 0.001). In addition, the levels of blood glucose (7.23 mmol·L⁻¹ (interquartile range (IQR): 5.80–9.29) vs 5.46 mmol·L⁻¹ (IQR: 5.00–6.46)), blood low-density lipoprotein cholesterol (LDL-C) (2.21 mmol·L⁻¹ (IQR: 1.67–2.76) vs 1.75 mmol·L⁻¹ (IQR: 1.27–2.01)), and systolic pressure (130 mmHg (IQR: 120–142) vs 122 mmHg (IQR: 110–137)) (1 mmHg = 133.3 Pa) in COVID-19 patients with diabetes were significantly higher than in patients without diabetes (P < 0.001). The coexistence of type 2 diabetes and other metabolic disorders is common in patients with COVID-19, which may potentiate the morbidity and aggravate COVID-19 progression. Optimal management of the metabolic hemostasis of glucose and lipids is the key to ensuring better clinical outcomes. Increased clinical vigilance is warranted for COVID-19 patients with diabetes and other metabolic diseases that are fundamental and chronic conditions.     

Estimating epidemic coupling between populations from the time to invasion

Identifying the mechanisms by which diseases spread among populations is important for understanding and forecasting patterns of epidemics and pandemics. Estimating transmission coupling among populations is challenging because transmission events are difficult to observe in practice, and connectivity among populations is often obscured by local disease dynamics. We consider the common situation in which an epidemic is seeded in one population and later spreads to a second population. We present a method for estimating transmission coupling between the two populations, assuming they can be modelled as susceptible–infected–removed (SIR) systems. We show that the strength of coupling between the two populations can be estimated from the time taken for the disease to invade the second population. Confidence in the estimate is low if only a single invasion event has been observed, but is substantially improved if numerous independent invasion events are observed. Our analysis of this simplest, idealized scenario represents a first step toward developing and verifying methods for estimating epidemic coupling among populations in an ever-more-connected global human population.     

基于深度学习的番茄叶部病害识别模型

番茄叶病种类多、成因复杂,其预防和识别难度较大。传统基于机器学习的方法多靠人工识别,需要一定的专家经验,且具有主观性强、识别准确率不高等缺点。为实现番茄叶病特征的自动提取,并提高识别准确率,提出一种基于深度学习的番茄叶病识别模型。该模型基于卷积神经网络对番茄叶部病害特征进行自动提取,获得高维特征后,采用PCA降维算法去除冗余特征;从增大类间距离并减小类内距离的角度改进了softmax分类器,提高了识别准确率。将该模型在CrowdAI提供的数据集上进行了仿真验证,结果表明,该模型能够对番茄叶部常见10种病害进行自动提取特征和识别,综合识别准确率达到95%以上。     

红外热成像在乳腺疾病检测的应用研究

乳腺疾病已严重危害女性身心健康,其中乳腺癌更位居全球范围内女性癌症发病率和死亡率首位,因此乳腺癌的早期发现意义重大。传统结构影像学早期检测疾病具有一定局限性,而红外热成像作为功能成像技术可为乳腺癌的早期筛查提供有效线索。因此本文主要就红外热成像在乳腺疾病的早期检测及预后评估的应用价值进行综述。     

Role of Post-translational Modifications in Alzheimer's Disease

The global burden of Alzheimer's disease (AD) is growing. Valiant efforts to develop clinical candidates for treatment have continuously met with failure. Currently available palliative treatments are temporary and there is a constant need to search for reliable disease pathways, biomarkers and drug targets for developing diagnostic and therapeutic tools to address the unmet medical needs of AD. Challenges in drug-discovery efforts raise further questions about the strategies of current conventional diagnosis; drug design; and understanding of disease pathways, biomarkers and targets. In this context, post-translational modifications (PTMs) regulate protein trafficking, function and degradation, and their in-depth study plays a significant role in the identification of novel biomarkers and drug targets. Aberrant PTMs of disease-relevant proteins could trigger pathological pathways, leading to disease progression. Advancements in proteomics enable the generation of patterns or signatures of such modifications, and thus, provide a versatile platform to develop biomarkers based on PTMs. In addition, understanding and targeting the aberrant PTMs of various proteins provide viable avenues for addressing AD drug-discovery challenges. This review highlights numerous PTMs of proteins relevant to AD and provides an overview of their adverse effects on the protein structure, function and aggregation propensity that contribute to the disease pathology. A critical discussion offers suggestions of methods to develop PTM signatures and interfere with aberrant PTMs to develop viable diagnostic and therapeutic interventions in AD.     

Fair‐Weather Friends: Evidence of Lipoxin Dysregulation in Neurodegeneration

Lipoxins (LXs) are autacoids, specialized proresolving lipid mediators (SPMs) acting locally in a paracrine or autocrine fashion. They belong to a complex superfamily of dietary small polyunsaturated fatty acid (PUFA)–metabolites, which direct potent cellular responses to resolve inflammation and restore tissue homeostasis. Together, these SPM activities have been intensely studied in systemic inflammation and acute injury or infection, but less is known about LX signaling and activities in the central nervous system. LXs are derived from arachidonic acid, an omega‐6 PUFA. In addition to well‐established roles in systemic inflammation resolution, they have increasingly become implicated in regulating neuroinflammatory and neurodegenerative processes. In particular, chronic inflammation plays a central role in Alzheimer's disease (AD) etiology, and dysregulated LX production and activities have been reported in a variety of AD rodent models and clinical tissue samples, yet with complex and sometimes conflicting results. In addition, reduced LX production following retinal injury has been reported recently by the authors, and an intriguing direct neuronal activity promoting survival and homeostasis in retinal and cortical neurons is demonstrated. Here, the authors review and clarify this growing literature and suggest new research directions to further elaborate the role of lipoxins in neurodegeneration.     

Association of Dietary Phytosterols with Cardiovascular Disease Biomarkers in Humans

Cardiovascular disease (CVD) is a leading cause of death worldwide. Elevated concentrations of serum total cholesterol (TC) and low-density lipoprotein cholesterol (LDL-C) are major lipid biomarkers that contribute to the risk of CVD. Phytosterols well known for their cholesterol-lowering ability, are non-nutritive compounds that are naturally found in plant-based foods and can be classified into plant sterols and plant stanols. Numerous clinical trials demonstrated that 2 g phytosterols per day have LDL-C lowering efficacy ranges of 8–10%. Some observational studies also showed an inverse association between phytosterols and LDL-C reduction. Beyond the cholesterol-lowering beneficial effects of phytosterols, the association of phytosterols with CVD risk events such as coronary artery disease and premature atherosclerosis in sitosterolemia patients have also been reported. Furthermore, there is an increasing demand to determine the association of circulating phytosterols with vascular health biomarkers such as arterial stiffness biomarkers. Therefore, this review aims to examine the ability of phytosterols for CVD risk prevention by reviewing the current data that looks at the association between dietary phytosterols intake and serum lipid biomarkers, and the impact of circulating phytosterols level on vascular health biomarkers. The clinical studies in which the impact of phytosterols on vascular function is investigated show minor but beneficial phytosterols effects over vascular health. The aforementioned vascular health biomarkers are pulse wave velocity, augmentation index, and arterial blood pressure. The current review will serve to begin to address the research gap that exists between the association of dietary phytosterols with CVD risk biomarkers.