39 research outputs found

    Incubator embedded cell culture imaging system (EmSight) based on Fourier ptychographic microscopy

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    Multi-day tracking of cells in culture systems can provide valuable information in bioscience experiments. We report the development of a cell culture imaging system, named EmSight, which incorporates multiple compact Fourier ptychographic microscopes with a standard multiwell imaging plate. The system is housed in an incubator and presently incorporates six microscopes. By using the same low magnification objective lenses as the objective and the tube lens, the EmSight is configured as a 1:1 imaging system that, providing large field-of-view (FOV) imaging onto a low-cost CMOS imaging sensor. The EmSight improves the image resolution by capturing a series of images of the sample at varying illumination angles; the instrument reconstructs a higher-resolution image by using the iterative Fourier ptychographic algorithm. In addition to providing high-resolution brightfield and phase imaging, the EmSight is also capable of fluorescence imaging at the native resolution of the objectives. We characterized the system using a phase Siemens star target, and show four-fold improved coherent resolution (synthetic NA of 0.42) and a depth of field of 0.2 mm. To conduct live, long-term dopaminergic neuron imaging, we cultured ventral midbrain from mice driving eGFP from the tyrosine hydroxylase promoter. The EmSight system tracks movements of dopaminergic neurons over a 21 day period

    Evaluating associations between the benefits and risks of drug therapy in type 2 diabetes:A joint modelling approach

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    This is the author accepted manuscript. The final version is available from Dove Medical Press via the DOI in this record.Data statement: No additional data are available from the authors although the individual participant data from the ADOPT trial used in this study are available from GlaxoSmithKline on application via www.clinicalstudydatarequest.comObjective: Precision medicine drug therapy seeks to maximise efficacy and minimise harm for individual patients. This will be difficult if drug response and side-effects are positively associated, meaning patients likely to respond best are at increased risk of side-effects. We applied joint longitudinal-survival models to evaluate associations between drug response (longitudinal outcome) and risk of side-effects (survival outcome) for patients initiating type 2 diabetes therapy. Study Design and Setting: Participants were randomised to metformin, sulfonylurea or thiazolidinedione therapy in the ADOPT drug-efficacy trial (n=4,351). Joint models were parameterised for: 1) current HbA1c response (change from baseline in HbA1c); 2) cumulative HbA1c response (total HbA1c change). Results: With metformin, greater HbA1c response did not increase risk of gastrointestinal events (Hazard ratio (HR) per 1% absolute greater current response 0.82 (95% confidence interval 0.67,1.01); HR per 1% higher cumulative response 0.90 (0.81,1.00)). With sulfonylureas, greater current response was associated with increased risk of hypoglycaemia (HR 1.41 (1.04,1.91)). With thiazolidinediones, greater response was associated with increased risk of oedema (current HR 1.45 (1.05,2.01); cumulative 1.22 (1.07,1.38)) but not fracture. Conclusion: Joint modelling provides a useful framework to evaluate the association between response to a drug and risk of developing side-effects. There may be great potential for widespread application of joint modelling to evaluate the risks and benefits of both new and established medications.This work was supported by the Medical Research Council (UK) (Grant MR/N00633X/1). ATH is a NIHR Senior Investigator and a Wellcome Trust Senior Investigator. ERP is a Wellcome Trust New Investigator (102820/Z/13/Z). AGJ is supported by an NIHR Clinician Scientist award. ATH and BMS are supported by the NIHR Exeter Clinical Research Facility. WEH received additional support from IQVIA and the National Institute for Health Research (NIHR) Collaboration for Leadership in Applied Health Research and Care South West Peninsula (NIHR CLAHRC South West Peninsula)

    Menthol Alone Upregulates Midbrain nAChRs, Alters nAChR Subtype Stoichiometry, Alters Dopamine Neuron Firing Frequency, and Prevents Nicotine Reward

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    Upregulation of β2 subunit-containing (β2*) nicotinic acetylcholine receptors (nAChRs) is implicated in several aspects of nicotine addiction, and menthol cigarette smokers tend to upregulate β2* nAChRs more than nonmenthol cigarette smokers. We investigated the effect of long-term menthol alone on midbrain neurons containing nAChRs. In midbrain dopaminergic (DA) neurons from mice containing fluorescent nAChR subunits, menthol alone increased the number of α4 and α6 nAChR subunits, but this upregulation did not occur in midbrain GABAergic neurons. Thus, chronic menthol produces a cell-type-selective upregulation of α4* nAChRs, complementing that of chronic nicotine alone, which upregulates α4 subunit-containing (α4*) nAChRs in GABAergic but not DA neurons. In mouse brain slices and cultured midbrain neurons, menthol reduced DA neuron firing frequency and altered DA neuron excitability following nAChR activation. Furthermore, menthol exposure before nicotine abolished nicotine reward-related behavior in mice. In neuroblastoma cells transfected with fluorescent nAChR subunits, exposure to 500 nM menthol alone also increased nAChR number and favored the formation of (α4)_3(β2)_2 nAChRs; this contrasts with the action of nicotine itself, which favors (α4)_2(β2)_3 nAChRs. Menthol alone also increases the number of α6β2 receptors that exclude the β3 subunit. Thus, menthol stabilizes lower-sensitivity α4* and α6 subunit-containing nAChRs, possibly by acting as a chemical chaperone. The abolition of nicotine reward-related behavior may be mediated through menthol's ability to stabilize lower-sensitivity nAChRs and alter DA neuron excitability. We conclude that menthol is more than a tobacco flavorant: administered alone chronically, it alters midbrain DA neurons of the nicotine reward-related pathway

    Transcriptional regulation by nicotine in dopaminergic neurons

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    Dopaminergic neurons in the substantia nigra pars compacta (SNc) degenerate in Parkinson's disease. These neurons robustly express several nicotinic acetylcholine receptor (nAChR) subtypes. Smoking appears to be neuroprotective for Parkinson's disease but the mechanism is unknown. To determine whether chronic nicotine-induced changes in gene expression contribute to the neuroprotective effects of smoking, we develop methods to measure the effect of prolonged nicotine exposure on the SNc neuronal transcriptome in an unbiased manner. Twenty neurons were collected using laser-capture microscopy and transcriptional changes were assessed using RNA deep sequencing. These results are the first whole-transcriptome analyses of chronic nicotinic treatment in SNc neurons. Overall, 129 genes were significantly regulated: 67 upregulated, 62 downregulated. Nicotine-induced relief of endoplasmic reticulum (ER) stress has been postulated as a potential mechanism for the neuroprotective effects of smoking. Chronic nicotine did not significantly affect the expression of ER stress-related genes, nor of dopamine-related or nAChR genes, but it did modulate expression of 129 genes that could be relevant to the neuroprotective effects of smoking, including genes involved in (1) the ubiquitin-proteasome pathway, (2) cell cycle regulation, (3) chromatin modification, and (4) DNA binding and RNA regulation. We also report preliminary transcriptome data for single-cell dopaminergic and GABAergic neurons isolated from midbrain cultures. These novel techniques will facilitate advances in understanding the mechanisms taking place at the cellular level and may have applications elsewhere in the fields of neuroscience and molecular biology. The results give an emerging picture of the role of nicotine on the SNc and on dopaminergic neurons

    Smoking-Relevant Nicotine Concentration Attenuates the Unfolded Protein Response in Dopaminergic Neurons

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    Retrospective epidemiological studies show an inverse correlation between susceptibility to Parkinson's disease and a person's history of tobacco use. Animal model studies suggest nicotine as a neuroprotective agent and nicotinic acetylcholine (ACh) receptors (nAChRs) as targets for neuroprotection, but the underlying neuroprotective mechanism(s) are unknown. We cultured mouse ventral midbrain neurons for 3 weeks. Ten to 20% of neurons were dopaminergic (DA), revealed by tyrosine hydroxylase (TH) immunoreactivity. We evoked mild endoplasmic reticulum (ER) stress with tunicamycin (Tu), producing modest increases in the level of nuclear ATF6, phosphorylated eukaryotic initiation factor 2α, nuclear XBP1, and the downstream proapoptotic effector nuclear C/EBP homologous protein. We incubated cultures for 2 weeks with 200 nm nicotine, the approximate steady-state concentration between cigarette smoking or vaping, or during nicotine patch use. Nicotine incubation suppressed Tu-induced ER stress and the unfolded protein response (UPR). Study of mice with fluorescent nAChR subunits showed that the cultured TH+ neurons displayed α4, α6, and β3 nAChR subunit expression and ACh-evoked currents. Gene expression profile in cultures from TH-eGFP mice showed that the TH+ neurons also express several other genes associated with DA release. Nicotine also upregulated ACh-induced currents in DA neurons by ∼2.5-fold. Thus, nicotine, at a concentration too low to activate an appreciable fraction of plasma membrane nAChRs, induces two sequelae of pharmacological chaperoning in the ER: UPR suppression and nAChR upregulation. Therefore, one mechanism of neuroprotection by nicotine is pharmacological chaperoning, leading to UPR suppression. Measuring this pathway may help in assessing neuroprotection

    Time trends in prescribing of type 2 diabetes drugs, glycaemic response and risk factors:a retrospective analysis of primary care data, 2010-2017

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    This is the author accepted manuscript. The final version is available on open access from Wiley via the DOI in this recordAim: Prescribing in type 2 diabetes has changed markedly in recent years, with increasing use of newer, more expensive glucose-lowering drugs. We aimed to describe population-level time trends in both prescribing patterns and short-term patient outcomes (HbA1c, weight, blood pressure, hypoglycemia and treatment discontinuation) after initiating new therapy. Materials and methods: We studied 81,532 UK patients with type 2 diabetes initiating a first to fourth line drug in primary care between 2010-2017 inclusive (Clinical Practice Research Datalink). Trends in new prescriptions and subsequent six and twelve-month adjusted changes in glycemic response (reduction in HbA1c), weight, blood pressure, and rates of hypoglycemia and treatment discontinuation were examined. Results: DPP4-inhibitor use second-line near doubled (41% of new prescriptions in 2017 vs. 22% 2010), replacing sulfonylureas as the most common second-line drug (29% 2017 vs. 53% 2010). SGLT2-inhibitors, introduced in 2013, comprised 17% of new first-fourth line prescriptions by 2017. First-line use of metformin remained stable (91% of new prescriptions in 2017 vs. 91% 2010). Over the study period there was little change in average glycemic response and treatment discontinuation. There was a modest reduction in weight second and third-line (second line 2017 vs. 2010: -1.5 kg (95%CI -1.9;-1.1), p<0.001), and a slight reduction in systolic blood pressure first to third-line (2017 vs. 2010 difference range -1.7 to -2.1 mmHg, all p<0.001). Hypoglycemia rates decreased second-line (incidence rate ratio 0.94 per-year (95%CI 0.88;1.00, p=0.04)), mirroring the decline in use of sulfonylureas. 4 Conclusions: Recent changes in prescribing of therapy in type 2 diabetes have not led to a change in glycemic response and have resulted in modest improvements in other population-level short-term patient outcomes.Medical Research Council (MRC)National Institute for Health Research (NIHR)Wellcome Trus

    Patient stratification for determining optimal second-line and third-line therapy for type 2 diabetes:the TriMaster study

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    This is the author accepted manuscript. The final version is available from Nature Research via the DOI in this recordData availability: To minimize the risk of patient re-identification, de-identified individual patient-level clinical data are available under restricted access. Requests for access to anonymized individual participant data and study documents should be made to the corresponding author and will be reviewed by the Peninsula Research Bank Steering Committee. Access to data through the Peninsula Research Bank will be granted for requests with scientifically valid questions by academic teams with the necessary skills appropriate for the research. Data that can be shared will be released with the relevant transfer agreement.Code availability: Requests for access to code should be made to the corresponding author and will be reviewed by the Peninsula Research Bank Steering Committee. Access to code through the Peninsula Research Bank will be granted for requests with scientifically valid questions by academic teams with the necessary skills appropriate for the research. Code will be released by the lead statistician.Precision medicine aims to treat an individual based on their clinical characteristics. A differential drug response, critical to using these features for therapy selection, has never been examined directly in type 2 diabetes. In this study, we tested two hypotheses: (1) individuals with body mass index (BMI) > 30 kg/m2, compared to BMI ≤ 30 kg/m2, have greater glucose lowering with thiazolidinediones than with DPP4 inhibitors, and (2) individuals with estimated glomerular filtration rate (eGFR) 60-90 ml/min/1.73 m2, compared to eGFR >90 ml/min/1.73 m2, have greater glucose lowering with DPP4 inhibitors than with SGLT2 inhibitors. The primary endpoint for both hypotheses was the achieved HbA1c difference between strata for the two drugs. In total, 525 people with type 2 diabetes participated in this UK-based randomized, double-blind, three-way crossover trial of 16 weeks of treatment with each of sitagliptin 100 mg once daily, canagliflozin 100 mg once daily and pioglitazone 30 mg once daily added to metformin alone or metformin plus sulfonylurea. Overall, the achieved HbA1c was similar for the three drugs: pioglitazone 59.6 mmol/mol, sitagliptin 60.0 mmol/mol and canagliflozin 60.6 mmol/mol (P = 0.2). Participants with BMI > 30 kg/m2, compared to BMI ≤ 30 kg/m2, had a 2.88 mmol/mol (95% confidence interval (CI): 0.98, 4.79) lower HbA1c on pioglitazone than on sitagliptin (n = 356, P = 0.003). Participants with eGFR 60-90 ml/min/1.73 m2, compared to eGFR >90 ml/min/1.73 m2, had a 2.90 mmol/mol (95% CI: 1.19, 4.61) lower HbA1c on sitagliptin than on canagliflozin (n = 342, P = 0.001). There were 2,201 adverse events reported, and 447/525 (85%) randomized participants experienced an adverse event on at least one of the study drugs. In this precision medicine trial in type 2 diabetes, our findings support the use of simple, routinely available clinical measures to identify the drug class most likely to deliver the greatest glycemic reduction for a given patient. (ClinicalTrials.gov registration: NCT02653209 ; ISRCTN registration: 12039221 .).Medical Research Council (MRC)National Institute for Health and Care Research (NIHR

    Development of a treatment selection algorithm for SGLT2 and DPP-4 inhibitor therapies in people with type 2 diabetes:a retrospective cohort study

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    Background: Current treatment guidelines do not provide recommendations to support the selection of treatment for most people with type 2 diabetes. We aimed to develop and validate an algorithm to allow selection of optimal treatment based on glycaemic response, weight change, and tolerability outcomes when choosing between SGLT2 inhibitor or DPP-4 inhibitor therapies. Methods: In this retrospective cohort study, we identified patients initiating SGLT2 and DPP-4 inhibitor therapies after Jan 1, 2013, from the UK Clinical Practice Research Datalink (CPRD). We excluded those who received SGLT2 or DPP-4 inhibitors as first-line treatment or insulin at the same time, had estimated glomerular filtration rate (eGFR) of less than 45 mL/min per 1·73 m2, or did not have a valid baseline glycated haemoglobin (HbA1c) measure (&lt;53 or ≥120 mmol/mol). The primary efficacy outcome was the HbA1c value reached 6 months after drug initiation, adjusted for baseline HbA1c. Clinical features associated with differential HbA1c outcome on the two therapies were identified in CPRD (n=26 877), and replicated in reanalysis of 14 clinical trials (n=10 414). An algorithm to predict individual-level differential HbA1c outcome on the two therapies was developed in CPRD (derivation; n=14 069) and validated in head-to-head trials (n=2499) and CPRD (independent validation; n=9376). In CPRD, we further explored heterogeneity in 6-month weight change and treatment discontinuation. Findings: Among 10 253 patients initiating SGLT2 inhibitors and 16 624 patients initiating DPP-4 inhibitors in CPRD, baseline HbA1c, age, BMI, eGFR, and alanine aminotransferase were associated with differential HbA1c outcome with SGLT2 inhibitor and DPP-4 inhibitor therapies. The median age of participants was 62·0 years (IQR 55·0–70·0). 10 016 (37·3%) were women and 16 861 (62·7%) were men. An algorithm based on these five features identified a subgroup, representing around four in ten CPRD patients, with a 5 mmol/mol or greater observed benefit with SGLT2 inhibitors in all validation cohorts (CPRD 8·8 mmol/mol [95% CI 7·8–9·8]; CANTATA-D and CANTATA-D2 trials 5·8 mmol/mol [3·9–7·7]; BI1245.20 trial 6·6 mmol/mol [2·2–11·0]). In CPRD, predicted differential HbA1c response with SGLT2 inhibitor and DPP-4 inhibitor therapies was not associated with weight change. Overall treatment discontinuation within 6 months was similar in patients predicted to have an HbA1c benefit with SGLT2 inhibitors over DPP-4 inhibitors (median 15·2% [13·2–20·3] vs 14·4% [12·9–16·7]). A smaller subgroup predicted to have greater HbA1c reduction with DPP-4 inhibitors were twice as likely to discontinue SGLT2 inhibitors than DPP-4 inhibitors (median 26·8% [23·4–31·0] vs 14·8% [12·9–16·8]). Interpretation: A validated treatment selection algorithm for SGLT2 inhibitor and DPP-4 inhibitor therapies can support decisions on optimal treatment for people with type 2 diabetes. Funding: BHF-Turing Cardiovascular Data Science Award and the UK Medical Research Council

    Risk factors for genital infections in people initiating SGLT2 inhibitors and their impact on discontinuation

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    Introduction: To identify risk factors, absolute risk, and impact on treatment discontinuation of genital infections with sodium-glucose co-transporter-2 inhibitors (SGLT2i). Research design and methods: We assessed the relationship between baseline characteristics and genital infection in 21 004 people with type 2 diabetes initiating SGLT2i and 55 471 controls initiating dipeptidyl peptidase-4 inhibitors (DPP4i) in a UK primary care database. We assessed absolute risk of infection in those with key risk factors and the association between early genital infection and treatment discontinuation. Results: Genital infection was substantially more common in those treated with SGLT2i (8.1% within 1 year) than DPP4i (1.8%). Key predictors of infection with SGLT2i were female sex (HR 3.64; 95% CI 3.23 to 4.11) and history of genital infection; &lt;1 year before initiation (HR 4.38; 3.73 to 5.13), 1–5 years (HR 3.04; 2.64 to 3.51), and &gt;5 years (HR 1.79; 1.55 to 2.07). Baseline HbA1c was not associated with infection risk for SGLT2i, in contrast to DPP4i where risk increased with higher HbA1c. One-year absolute risk of genital infection with SGLT2i was highest for those with a history of prior infection (females 23.7%, males 12.1%), compared with those without (females 10.8%, males 2.7%). Early genital infection was associated with a similar discontinuation risk for SGLT2i (HR 1.48; 1.21–1.80) and DPP4i (HR 1.58; 1.21–2.07). Conclusions: Female sex and history of prior infection are simple features that can identify subgroups at greatly increased risk of genital infections with SGLT2i therapy. These data can be used to risk-stratify patients. High HbA1c is not a risk factor for genital infections with SGLT2i

    Erratum to: Methods for evaluating medical tests and biomarkers

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    [This corrects the article DOI: 10.1186/s41512-016-0001-y.]
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