Single vesicle imaging indicates distinct modes of rapid membrane retrieval during nerve growth

<p>Abstract</p> <p>Background</p> <p>During nerve growth, cytoplasmic vesicles add new membrane preferentially to the growth cone located at the distal tip of extending axons. Growth cone membrane is also retrieved locally, and asymmetric retrieval facilitates membrane remodeling during growth cone repulsion by a chemorepellent gradient. Moreover, growth inhibitory factors can stimulate bulk membrane retrieval and induce growth cone collapse. Despite these functional insights, the processes mediating local membrane remodeling during axon extension remain poorly defined.</p> <p>Results</p> <p>To investigate the spatial and temporal dynamics of membrane retrieval in actively extending growth cones, we have used a transient labeling and optical recording method that can resolve single vesicle events. Live-cell confocal imaging revealed rapid membrane retrieval by distinct endocytic modes based on spatial distribution in <it>Xenopus </it>spinal neuron growth cones. These modes include endocytic "hot-spots" triggered at the base of filopodia, at the lateral margins of lamellipodia, and along dorsal ridges of the growth cone. Additionally, waves of endocytosis were induced when individual filopodia detached from the substrate and fused with the growth cone dorsal surface or with other filopodia. Vesicle formation at sites of membrane remodeling by self-contact required F-actin polymerization. Moreover, bulk membrane retrieval by macroendocytosis correlated positively with the substrate-dependent rate of axon extension and required the function of Rho-family GTPases.</p> <p>Conclusions</p> <p>This study provides insight into the dynamic membrane remodeling processes essential for nerve growth by identifying several distinct modes of rapid membrane retrieval in the growth cone during axon extension. We found that endocytic membrane retrieval is intensified at specific subdomains and may drive the dynamic membrane ruffling and re-absorption of filopodia and lamellipodia in actively extending growth cones. The findings offer a platform for determining the molecular mechanisms of distinct endocytic processes that may remodel the surface distribution of receptors, ion channels and other membrane-associated proteins locally to drive growth cone extension and chemotactic guidance.</p

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

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

Population Monte Carlo algorithms

We give a cross-disciplinary survey on ``population'' Monte Carlo algorithms. In these algorithms, a set of ``walkers'' or ``particles'' is used as a representation of a high-dimensional vector. The computation is carried out by a random walk and split/deletion of these objects. The algorithms are developed in various fields in physics and statistical sciences and called by lots of different terms -- ``quantum Monte Carlo'', ``transfer-matrix Monte Carlo'', ``Monte Carlo filter (particle filter)'',``sequential Monte Carlo'' and ``PERM'' etc. Here we discuss them in a coherent framework. We also touch on related algorithms -- genetic algorithms and annealed importance sampling.Comment: Title is changed (Population-based Monte Carlo -> Population Monte Carlo). A number of small but important corrections and additions. References are also added. Original Version is read at 2000 Workshop on Information-Based Induction Sciences (July 17-18, 2000, Syuzenji, Shizuoka, Japan). No figure

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

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

Wind Orchestra: Sketches

Program listing performers and works performe

Glucocorticoids Target Ependymal Glia and Inhibit Repair of the Injured Spinal Cord

Following injury, the mammalian spinal cord forms a glial scar and fails to regenerate. In contrast, vertebrate fish spinal cord tissue regenerates significantly to restore function. Cord transection in zebrafish (Danio rerio) initially causes paralysis and neural cell death. Subsequently, ependymal glia proliferate, bipolar glia extend across the lesion, and new neurons are born; axons from spared and nascent neurons extend along trans-lesional glial bridges to restore functional connectivity. Here we report that glucocorticoids, used in the clinical management of spinal cord injury, directly inhibit neural repair by targeting ependymal glia independently of hematogenous cells and microglia. After transecting injury, the glucocorticoid receptor in ependymal glia is regulated differentially in zebrafish (becoming inactive) vs. the rat (becoming active). Glucocorticoid blockade of neural regeneration via a direct effect on ependymal glia has important therapeutic implications for the putative benefit of corticosteroids in early management of spinal cord injury

Temporal variability is a personalized feature of the human microbiome

Background: It is now apparent that the complex microbial communities found on and in the human body vary across individuals. What has largely been missing from previous studies is an understanding of how these communities vary over time within individuals. To the extent to which it has been considered, it is often assumed that temporal variability is negligible for healthy adults. Here we address this gap in understanding by profiling the forehead, gut (fecal), palm, and tongue microbial communities in 85 adults, weekly over 3 months. Results: We found that skin (forehead and palm) varied most in the number of taxa present, whereas gut and tongue communities varied more in the relative abundances of taxa. Within each body habitat, there was a wide range of temporal variability across the study population, with some individuals harboring more variable communities than others. The best predictor of these differences in variability across individuals was microbial diversity; individuals with more diverse gut or tongue communities were more stable in composition than individuals with less diverse communities. Conclusions: Longitudinal sampling of a relatively large number of individuals allowed us to observe high levels of temporal variability in both diversity and community structure in all body habitats studied. These findings suggest that temporal dynamics may need to be considered when attempting to link changes in microbiome structure to changes in health status. Furthermore, our findings show that, not only is the composition of an individual's microbiome highly personalized, but their degree of temporal variability is also a personalized feature

A Genomic Pathway Approach to a Complex Disease: Axon Guidance and Parkinson Disease

While major inroads have been made in identifying the genetic causes of rare Mendelian disorders, little progress has been made in the discovery of common gene variations that predispose to complex diseases. The single gene variants that have been shown to associate reproducibly with complex diseases typically have small effect sizes or attributable risks. However, the joint actions of common gene variants within pathways may play a major role in predisposing to complex diseases (the paradigm of complex genetics). The goal of this study was to determine whether polymorphism in a candidate pathway (axon guidance) predisposed to a complex disease (Parkinson disease [PD]). We mined a whole-genome association dataset and identified single nucleotide polymorphisms (SNPs) that were within axon-guidance pathway genes. We then constructed models of axon-guidance pathway SNPs that predicted three outcomes: PD susceptibility (odds ratio = 90.8, p = 4.64 × 10−38), survival free of PD (hazards ratio = 19.0, p = 5.43 × 10−48), and PD age at onset (R2 = 0.68, p = 1.68 × 10−51). By contrast, models constructed from thousands of random selections of genomic SNPs predicted the three PD outcomes poorly. Mining of a second whole-genome association dataset and mining of an expression profiling dataset also supported a role for many axon-guidance pathway genes in PD. These findings could have important implications regarding the pathogenesis of PD. This genomic pathway approach may also offer insights into other complex diseases such as Alzheimer disease, diabetes mellitus, nicotine and alcohol dependence, and several cancers

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

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

Development of a Protocol for Obtaining Biological Samples for Genetic Testing from Remote Individuals

Pharmacogenomic sequencing allows individuals to learn more about how they will respond to certain medications but requires shipping of a biological sample. One complication of sending biological samples to remote laboratories is stability. Blood generally yields sufficient quantities of high-quality DNA but requires a clinic visit. Saliva and buccal swabs are routinely used for DNA extractions, but the DNA quality is notoriously low due to the presence of bacteria in the mouth. Additionally, elderly individuals have difficulty producing enough saliva for testing, and the tubes contain several milliliters of liquid and shipping requires special considerations. Dried blood spot cards, which serve as an alternative to saliva and buccal swabs, yield high-quality DNA and ship easily, but may produce a lower yield. This project aims to determine which biological sample methods can reasonably be obtained from remote individuals