Background The inability to objectively diagnose childhood asthma before age five often results in both under‐treatment and over‐treatment of asthma in preschool children. Prediction tools for estimating a child's risk of developing asthma by school‐age could assist physicians in early asthma care for preschool children. This review aimed to systematically identify and critically appraise studies which either developed novel or updated existing prediction models for predicting school‐age asthma. Methods Three databases (MEDLINE, Embase and Web of Science Core Collection) were searched up to July 2019 to identify studies utilizing information from children ≤5 years of age to predict asthma in school‐age children (6‐13 years). Validation studies were evaluated as a secondary objective. Results Twenty‐four studies describing the development of 26 predictive models published between 2000 and 2019 were identified. Models were either regression‐based (n = 21) or utilized machine learning approaches (n = 5). Nine studies conducted validations of six regression‐based models. Fifteen (out of 21) models required additional clinical tests. Overall model performance, assessed by area under the receiver operating curve (AUC), ranged between 0.66 and 0.87. Models demonstrated moderate ability to either rule in or rule out asthma development, but not both. Where external validation was performed, models demonstrated modest generalizability (AUC range: 0.62‐0.83). Conclusion Existing prediction models demonstrated moderate predictive performance, often with modest generalizability when independently validated. Limitations of traditional methods have shown to impair predictive accuracy and resolution. Exploration of novel methods such as machine learning approaches may address these limitations for future school‐age asthma prediction.

Background Omalizumab and Mepolizumab are biologic drugs with proven efficacy in clinical trials. However, a better understanding of their real‐world effectiveness in severe asthma management is needed. Objectives To better understand the real‐world effectiveness of Omalizumab and Mepolizumab, elucidate the clinical phenotypes of patients treated with these drugs, identify baseline characteristics associated with biologic response and assess the spectrum of responses to these medications. Methods Using real‐world clinical data, we retrospectively phenotyped biologic naïve patients from the Wessex AsThma CoHort of difficult asthma (N = 478) commenced on Omalizumab (N = 105) or Mepolizumab (N = 62) compared to severe asthma patients not receiving biologics (SNB, N = 178). We also assessed multiple clinical endpoints and identified features associated with response. Results Compared to SNB, Omalizumab patients were younger, diagnosed with asthma earlier, and more likely to have rhinitis. Conversely, compared to SNB, Mepolizumab patients were predominantly older males, diagnosed with asthma later, and more likely to have nasal polyposis but less dysfunctional breathing. Both treatments reduced exacerbations, Acute Healthcare Encounters [AHE] (emergency department or hospital admissions), maintenance oral corticosteroid dose, and improved Asthma Control Questionnaire 6 (ACQ6) scores. Omalizumab response was independently associated with more baseline exacerbations (p = .024) but fewer AHE (p = .050) and absence of anxiety (p = .008). Lower baseline ACQ6 was independently associated with Mepolizumab response (p = .007). A composite group of non‐responders demonstrated significantly more psychopathologies and worse baseline subjective disease compared to responder groups. Conclusions and Clinical Relevance In a difficult asthma cohort, Omalizumab and Mepolizumab were used in distinct clinical phenotypes but were both multidimensionally efficacious. Certain baseline clinical characteristics were associated with poorer biologic responses, such as psychological co‐morbidity, which may assist clinicians in biologic selection. These characteristics also emphasize the need for comprehensive approaches to support these patients.

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Intracellular pH is a key parameter that influences many biochemical and metabolic pathways that can also be used as an indirect marker to monitor metabolic and intracellular processes. Herein, we utilise ratiometric fluorescent pH-sensitive nanosensors with an extended dynamic pH range to measure the intracellular pH of yeast (Saccharomyces cerevisiae) during glucose metabolism in real-time. Ratiometric fluorescent pH-sensitive nanosensors consisting of a polyacrylamide nanoparticle matrix covalently linked to two pH-sensitive fluorophores, Oregon green (OG) and 5(6)carboxyfluorescein (FAM), and a reference pH-insensitive fluorophore, 5(6)carboxytetramethylrhodamine (TAMRA), were synthesised. Nanosensors were functionalised with acrylamidopropyltrimethyl ammonium hydrochloride (ACTA) to confer a positive charge to the nanoparticle surfaces that facilitated nanosensor delivery to yeast cells, negating the need to use stress inducing techniques. The results showed that under glucose-starved conditions the intracellular pH of yeast population (n ≈ 200) was 4.67 ± 0.15. Upon addition of d-(+)-glucose (10 mM), this pH value decreased to pH 3.86 ± 0.13 over a period of 10 minutes followed by a gradual rise to a maximal pH of 5.21 ± 0.26, 25 minutes after glucose addition. 45 minutes after the addition of glucose, the intracellular pH of yeast cells returned to that of the glucose starved conditions. This study advances our understanding of the interplay between glucose metabolism and pH regulation in yeast cells, and indicates that the intracellular pH homestasis in yeast is highly regulated and demonstrates the utility of nanosensors for real-time intracellular pH measurements.

The present prevailing inflammatory paradigm in asthma is of T2-high inflammation orchestrated by key inflammatory cells like Type 2 helper lymphocytes, innate lymphoid cells group 2 and associated cytokines. Eosinophils are key components of this T2 inflammatory pathway and have become key therapeutic targets. Real-world evidence on the predominant T2-high nature of severe asthma is emerging. Various inflammatory biomarkers have been adopted in clinical practice to aid asthma characterization including airway measures such as bronchoscopic biopsy and lavage, induced sputum analysis, and fractional exhaled nitric oxide. Blood measures like eosinophil counts have also gained widespread usage and multicomponent algorithms combining different parameters are now appearing. There is also growing interest in potential future biomarkers including exhaled volatile organic compounds, micro RNAs and urinary biomarkers. Additionally, there is a growing realisation that asthma is a heterogeneous state with numerous phenotypes and associated treatable traits. These may show particular inflammatory patterns and merit-specific management approaches that could improve asthma patient outcomes. Inhaled corticosteroids (ICS) remain the mainstay of asthma management but their use earlier in the course of disease is being advocated. Recent evidence suggests potential roles for ICS in combination with long-acting beta-agonists (LABA) for as needed use in mild asthma whilst maintenance and reliever therapy regimes have gained widespread acceptance. Other anti-inflammatory strategies including ultra-fine particle ICS, leukotriene receptor antagonists and macrolide antibiotics may show efficacy in particular phenotypes too. Monoclonal antibody biologic therapies have recently entered clinical practice with significant impacts on asthma outcomes. Understanding of the efficacy and use of those agents is becoming clearer with a growing body of real-world evidence as is their potential applicability to other treatable comorbid traits. In conclusion, the evolving understanding of T2 driven inflammation alongside a treatable traits disease model is enhancing therapeutic approaches to address inflammation in asthma.

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Micro RNAs (miRNAs) are short, non-coding RNAs (Ribonucleic acids) with regulatory functions that could prove useful as biomarkers for asthma diagnosis and asthma severity-risk stratification. The objective of this systematic review is to identify panels of miRNAs that can be used to support asthma diagnosis and severity-risk assessment. Three databases (Medline, Embase, and SCOPUS) were searched up to 15 September 2020 to identify studies reporting differential expression of specific miRNAs in the tissues of adults and children with asthma. Studies reporting miRNAs associations in animal models that were also studied in humans were included in this review. We identified 75 studies that met our search criteria. Of these, 66 studies reported more than 200 miRNAs that are differentially expressed in asthma patients when compared to non-asthmatic controls. In addition, 16 studies reported 17 miRNAs that are differentially expressed with differences in asthma severity. We were able to construct two panels of miRNAs that are expressed in blood and can serve as core panels to further investigate the practicality and efficiency of using miRNAs as non-invasive biomarkers for asthma diagnosis and severity-risk assessment, respectively.

Aim: The aim of this study was to determine the effect of morphine on bladder cancer cell proliferation and apoptosis in vitro. Materials and Methods: MTT assay was used to measure percentage growth of RT-112 human bladder cancer cells after 72 hours of morphine/morphine + naloxone treatment. Expression of µ-opioid receptors was assessed by Western blot and finally, apoptotic assay with CellEvent Caspase-3/7 Green Detection Reagent was carried out using confocal microscopy. Results: The MTT assays showed that morphine increased RT-112 cell growth. Naloxone inhibited this growth enhancing effect. Western blot analysis regarding µ-opioid receptor expression in RT-112 cells remains inconclusive. Morphine was also found to decrease the rate of apoptosis of RT-112 cells, an effect which naloxone inhibited. Conclusions: This study provides evidence that morphine, at clinically relevant doses, causes RT-112 bladder cancer cell proliferation, possibly opioid receptor mediated and at least some of this effect might be due to decreased apoptosis. Clinically, this suggests that in patients with bladder cancer, managing pain with morphine might have detrimental consequences on patient outcomes and alternative pain relief should be considered if possible.