Message in a bubble: the translational potential of extracellular vesicles

Extracellular vesicles (EVs) are small, membrane-enclosed vesicles released by cells into the extracellular milieu. They are found in all body fluids and contain a variety of functional cargo including DNA, RNA, proteins, glycoproteins and lipids, able to provoke phenotypic responses in cells, both locally and at distant sites. They are implicated in a wide array of physiological and pathological processes and hence have attracted considerable attention in recent years as potential therapeutic targets, drug delivery vehicles and biomarkers of disease. In this review we summarise the major functions of EVs in health and disease and discuss their translational potential, highlighting opportunities of – and challenges to – capitalising on our rapidly increasing understanding of EV biology for patient benefit

Femtosecond laser ablation of transparent microphotonic devices and computer-generated holograms

Femtosecond laser ablation allows direct patterning of engineering materials in industrial settings, for the production of photonic and holographic devices.</p

Femtosecond laser directed fabrication of optical diffusers

Optical diffusers are widely used in filament lamps, imaging systems, display technologies, lasers, and Light Emitting Diodes (LEDs). Here, a method for the fabrication of optical diffusers through femtosecond laser machining is demonstrated. Float glass surfaces were ablated with femtosecond laser light to form nanoscale ripples with dimensions comparable to the wavelength of visible light. These structures produce highly efficient and wide field of view diffusers. The machined patterns altered the average surface roughness, with the majority of particles in the range of a few hundred nanometers. The optical diffusion characteristic and a maximum diffusion angle of near 172° was achieved with optimum machining parameters. The transmission performance of the diffusers was measured to be ∼30% across the visible spectrum. The demonstrated technique has potential for producing low-cost large area optical devices. The process benefits from the flexibility of the laser writing method and enables the production of custom optical diffusers

Optical glucose sensors based on hexagonally-packed 2.5-dimensional photonic concavities imprinted in phenylboronic acid functionalized hydrogel films

Continuous glucose monitoring aims to achieve accurate control of blood glucose concentration to prevent hypo/hyperglycaemia in diabetic patients. Hydrogel-based systems have emerged as a reusable sensing platform to quantify biomarkers in high-risk patients at clinical and point-of-care settings. The capability to integrate hydrogel-based systems with optical transducers will provide quantitative and colorimetric measurements via spectrophotometric analyses of biomarkers. Here, we created an imprinting method to rapidly produce 2.5D photonic concavities in phenylboronic acid functionalized hydrogel films. Our method exploited diffraction properties of hexagonally-packed 2.5D photonic microscale concavities having a lattice spacing of 3.3 μm. Illumination of the 2.5D hexagonally-packed structure with a monochromatic light source in transmission mode allowed reversible and quantitative measurements of variation in the glucose concentration based on first order lattice interspace tracking. Reversible covalent phenylboronic acid coupling with cis-diols of glucose molecules expanded the hydrogel matrix by ∼2% and 34% in the presence of glucose concentrations of 1 mM and 200 mM, respectively. A Donnan osmotic pressure induced volumetric expansion of the hydrogel matrix due to increasing glucose concentrations (1–200 mM), resulted in a nanoscale modulation of the lattice interspace, and shifted the diffraction angle (∼45° to 36°) as well as the interspacing between the 1st order diffraction spots (∼8 to 3 mm). The sensor exhibited a maximum lattice spacing diffraction shift within a response time of 15 min in a reversible manner. The developed 2.5D photonic sensors may have application in medical point-of-care diagnostics, implantable chips, and wearable continuous glucose monitoring devices

The prevalence of diabetes and prediabetes in the adult population of Jeddah, Saudi Arabia- a community-based survey

BACKGROUND: Type 2 (T2DM) is believed to be common in Saudi Arabia, but data are limited. In this population survey, we determined the prevalence of T2DM and prediabetes. MATERIALS AND METHODS: A representative sample among residents aged ≥ 18 years of the city of Jeddah was obtained comprising both Saudi and non-Saudi families (N = 1420). Data on dietary, clinical and socio-demographic characteristics were collected and anthropometric measurements taken. Fasting plasma glucose and glycated hemoglobin (HbA1c) were used to diagnose diabetes and prediabetes employing American Diabetes Association criteria. Multiple logistic regression analysis was used to identify factors associated with T2DM. RESULTS: Age and sex standardized prevalence of prediabetes was 9.0% (95% CI 7.5-10.5); 9.4% (7.1-11.8) in men and 8.6% (6.6-10.6) in women. For DM it was 12.1% (10.7-13.5); 12.9% (10.7-13.5) in men and 11.4% (9.5-13.3) in women. The prevalence based on World Population as standard was 18.3% for DM and 11.9% for prediabetes. The prevalence of DM and prediabetes increased with age. Of people aged ≥50 years 46% of men and 44% of women had DM. Prediabetes and DM were associated with various measures of adiposity. DM was also associated with and family history of dyslipidemia in women, cardiovascular disease in men, and with hypertension, dyslipidemia and family history of diabetes in both sexes. DISCUSSION: Age was the strongest predictor of DM and prediabetes followed by obesity. Of people aged 50 years or over almost half had DM and another 10-15% had prediabetes leaving only a small proportion of people in this age group with normoglycemia. Since we did not use an oral glucose tolerance test the true prevalence of DM and prediabetes is thus likely to be even higher than reported here. These results demonstrate the urgent need to develop primary prevention strategies for type 2 diabetes in Saudi Arabia

Transcriptional analysis of Rhazya stricta in response to jasmonic acid

Background: Jasmonic acid (JA) is a signal transducer molecule that plays an important role in plant development and stress response; it can also efficiently stimulate secondary metabolism in plant cells. Results: RNA-Seq technology was applied to identify differentially expressed genes and study the time course of gene expression in Rhazya stricta in response to JA. Of more than 288 million total reads, approximately 27% were mapped to genes in the reference genome. Genes involved during the secondary metabolite pathways were up- or downregulated when treated with JA in R. stricta. Functional annotation and pathway analysis of all up- and downregulated genes identified many biological processes and molecular functions. Jasmonic acid biosynthetic, cell wall organization, and chlorophyll metabolic processes were upregulated at days 2, 6, and 12, respectively. Similarly, the molecular functions of calcium-transporting ATPase activity, ADP binding, and protein kinase activity were also upregulated at days 2, 6, and 12, respectively. Time-dependent transcriptional gene expression analysis showed that JA can induce signaling in the phenylpropanoid and aromatic acid pathways. These pathways are responsible for the production of secondary metabolites, which are essential for the development and environmental defense mechanism of R. stricta during stress conditions. Conclusions: Our results suggested that genes involved in flavonoid biosynthesis and aromatic acid synthesis pathways were upregulated during JA stress. However, monoterpenoid indole alkaloid (MIA) was unaffected by JA treatment. Hence, we can postulate that JA plays an important role in R. stricta during plant development and environmental stress conditions. How to cite: Hajrah, NH, Rabah SO, Alghamdi MK, et al. Transcriptional analysis of Rhazya stricta in response to jasmonic acid. Electron J Biotechnol 2021;50. https://doi.org/10.1016/j.ejbt.2021.01.00

Updated Guidance Regarding The Risk ofAllergic Reactions to COVID-19 Vaccines and Recommended Evaluation and Management: A GRADE Assessment, and International Consensus Approach

This guidance updates 2021 GRADE (Grading of Recommendations Assessment, Development and Evaluation) recommendations regarding immediate allergic reactions following coronavirus disease 2019 (COVID-19) vaccines and addresses revaccinating individuals with first-dose allergic reactions and allergy testing to determine revaccination outcomes. Recent meta-analyses assessed the incidence of severe allergic reactions to initial COVID-19 vaccination, risk of mRNA-COVID-19 revaccination after an initial reaction, and diagnostic accuracy of COVID-19 vaccine and vaccine excipient testing in predicting reactions. GRADE methods informed rating the certainty of evidence and strength of recommendations. A modified Delphi panel consisting of experts in allergy, anaphylaxis, vaccinology, infectious diseases, emergency medicine, and primary care from Australia, Canada, Europe, Japan, South Africa, the United Kingdom, and the United States formed the recommendations. We recommend vaccination for persons without COVID-19 vaccine excipient allergy and revaccination after a prior immediate allergic reaction. We suggest against \u3e 15-minute postvaccination observation. We recommend against mRNA vaccine or excipient skin testing to predict outcomes. We suggest revaccination of persons with an immediate allergic reaction to the mRNA vaccine or excipients be performed by a person with vaccine allergy expertise in a properly equipped setting. We suggest against premedication, split-dosing, or special precautions because of a comorbid allergic history

Effect of nocturnal hypoxemia on glycemic control among diabetic Saudi patients presenting with obstructive sleep apnea

BackgroundObstructive sleep apnea (OSA) is a prevalent disease that is associated with an increased incidence of type II diabetes mellitus (DM) if left untreated. We aimed to determine the association between glycosylated hemoglobin (HbA1c) levels and both nocturnal hypoxemia and apnea-hypopnea index (AHI) among a Saudi patients with OSA.MethodsA cross-sectional study that enrolled 103 adult patients diagnosed with DM and confirmed to have OSA by full night attended polysomnography between 2018 and 2021. Those who presented with acute illness, chronic obstructive pulmonary disease (COPD)/restrictive lung diseases causing sleep-related hypoxemia, or no available HbA1c level within 6 months before polysomnography were excluded from the study. Univariate and multivariate linear regression analyses between HbA1c levels and parameters of interest were tested.ResultsSixty-seven (65%) of the studied population had uncontrolled DM (HbA1c ≥7%). In univariate regression analysis, there was a significant positive association between HbA1c, and sleep time spent with an oxygen saturation below 90% (T90), female gender, and body mass index (BMI) (p&lt;0.05) but not AHI, or associated comorbidities (p&gt;0.05). In the multivariate analysis, HbA1c was positively associated with increasing T90 (p&lt;0.05), and ODI (p&lt;0.05), but not with AHI (p&gt;0.05).ConclusionNocturnal hypoxemia could be an important factor affecting glycemic control in patients with OSA suffering from DM irrespective of the severity of both diseases

Large-scale unit commitment under uncertainty: an updated literature survey

The Unit Commitment problem in energy management aims at finding the optimal production schedule of a set of generation units, while meeting various system-wide constraints. It has always been a large-scale, non-convex, difficult problem, especially in view of the fact that, due to operational requirements, it has to be solved in an unreasonably small time for its size. Recently, growing renewable energy shares have strongly increased the level of uncertainty in the system, making the (ideal) Unit Commitment model a large-scale, non-convex and uncertain (stochastic, robust, chance-constrained) program. We provide a survey of the literature on methods for the Uncertain Unit Commitment problem, in all its variants. We start with a review of the main contributions on solution methods for the deterministic versions of the problem, focussing on those based on mathematical programming techniques that are more relevant for the uncertain versions of the problem. We then present and categorize the approaches to the latter, while providing entry points to the relevant literature on optimization under uncertainty. This is an updated version of the paper "Large-scale Unit Commitment under uncertainty: a literature survey" that appeared in 4OR 13(2), 115--171 (2015); this version has over 170 more citations, most of which appeared in the last three years, proving how fast the literature on uncertain Unit Commitment evolves, and therefore the interest in this subject