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Chronic obstructive pulmonary disease (COPD) is a leading cause of death worldwide, however our understanding of cell specific mechanisms underlying COPD pathobiology remains incomplete. Here, we analyze single-cell RNA sequencing profiles of explanted lung tissue from subjects with advanced COPD or control lungs, and we validate findings using single-cell RNA sequencing of lungs from mice exposed to 10 months of cigarette smoke, RNA sequencing of isolated human alveolar epithelial cells, functional in vitro models, and in situ hybridization and immunostaining of human lung tissue samples. We identify a subpopulation of alveolar epithelial type II cells with transcriptional evidence for aberrant cellular metabolism and reduced cellular stress tolerance in COPD. Using transcriptomic network analyses, we predict capillary endothelial cells are inflamed in COPD, particularly through increased CXCL-motif chemokine signaling. Finally, we detect a high-metallothionein expressing macrophage subpopulation enriched in advanced COPD. Collectively, these findings highlight cell-specific mechanisms involved in the pathobiology of advanced COPD. Chronic obstructive pulmonary disease is a leading cause of death worldwide, while our understanding of cell-specific mechanisms underlying its pathobiology remains incomplete. Here the authors perform scRNA-seq of human lung tissue to identify transcriptional changes in alveolar niche cells associated with the disease.

Background: Because the use of insulin therapy can place a substantial burden on patients with diabetes, insulin administration should be as simple as possible. Objectives: The primary aim of this trial was to compare the use of 2 insulin delivery devices—one prefilled (NovoMix® 30 FlexPen® [FP]; Novo Nordisk, Copenhagen, Denmark) and the other reusable (HumaPen® Luxura™ [HL]; Eli Lilly and Company, Indianapolis, Indiana)—in patients with type 2 diabetes in terms of intuitiveness and training time. A secondary aim was to evaluate the ease of use and overall acceptance of the 2 devices. Methods: This was a randomized, open-label, comparative, crossover handling study in adult patients with type 2 diabetes who had been treated with oral antidiabetic drugs for ≥2 years and had no previous experience with insulin injection devices. Patients were randomly allocated to the intuitiveness group (no instruction in the use of the devices provided) or the instruction group (instruction provided). The time taken to deliver an injection into a cushion was measured for each device in both groups. Patients answered questionnaires concerning the intuitiveness and ease of use of the 2 devices, their trust and confidence in the devices to deliver the insulin dose, and their overall pen preference. Results: Sixty-one patients were enrolled in the study (70.5% male; mean [SD] age, 61.80 [7.60] years), 30 in the intuitiveness group and 31 in the instruction group. When all handling steps for the HL device were included, the mean (SD) injection time was significantly shorter for the FP device compared with the HL device in the intuitiveness group (1.21 [1.04] vs 1.74 [0.79] minutes, respectively; P = 0.035). The outcome was similar in the instruction group (0.71 [0.29] vs 1.09 [0.49] minutes; P < 0.001). When the time for cartridge insertion in the HL device was excluded, there was no significant difference in injection time for the respective devices in either group (intuitiveness group: 1.21 [1.04] and 1.07 [0.91] minutes; instruction group: 0.63 [0.35] and 0.71 [0.29] minutes). Twenty-two patients preferred the FP device in terms of ease of learning, compared with 8 patients preferring the HL device (P = 0.007). Conclusions: In this study, when all handling steps were included, the FP device was associated with significantly greater intuitiveness and a shorter injection time compared with the HL device. Further research is needed to determine whether these differences between devices are clinically meaningful.

Introduction The treatment of patients with type 2 diabetes uncontrolled on basal insulin and oral glucose-lowering drugs was investigated previously in the LixiLan-L trial. In the LixiLan-L trial, patients experienced a 6-week run-in with insulin glargine U100 (iGlar) as part of the screening phase, followed by treatment with a fixed-ratio combination of iGlar + lixisenatide (iGlarLixi) or iGlar alone over 30 weeks. In the study reported here, we investigated the achievement of glycemic control in those who completed the 30-week LixiLan-L trial, as assessed by change in glycated hemoglobin (HbA 1c ) levels from screening, both for the overall category and for screening HbA 1c subcategories. Methods This post hoc analysis of the LixiLan-L trial included both the screening phase and the treatment period for 30-week completers and evaluated the change in HbA 1c from screening to Week 30, patients reaching HbA 1c  < 7% at Week 30, and iGlar and lixisenatide (Lixi) doses at Week 30 overall and according to HbA 1c subcategory at screening (HbA 1c  ≤ 8%, 8% < HbA 1c  ≤ 9%, and HbA 1c  > 9%). Documented symptomatic hypoglycemia during the treatment period was also assessed. Results HbA 1c reductions (least squares mean) from screening to Week 30 were greater for iGlarLixi than iGlar, both overall (− 1.7 vs. − 1.1%) and in all subgroups (HbA 1c  ≤ 8%, 8% < HbA 1c  ≤ 9%, and HbA 1c  > 9%): − 1.1, − 1.4, − 2.4 (iGlarLixi) vs. − 0.5, − 1.0, − 1.8% (iGlar), respectively (all p  < 0.0001). The end-of-treatment mean HbA 1c level for iGlarLixi across all groups was < 7%. More patients achieved an HbA 1c of < 7% with iGlarLixi than with iGlar, both overall (59.9 vs. 31.2%) and within each subgroup [74.2, 54.7, 52.2 (iGlarLixi) vs. 37.2, 31.6, 23.5% (iGlar), respectively]. A higher initial screening HbA 1c corresponded with a greater mean reduction in HbA 1c for both treatment strategies. In all HbA 1c screening categories, the risk of hypoglycemia was not increased with iGlarLixi versus iGlar during the treatment phase. Conclusion iGlarLixi controlled HbA 1c levels more effectively than iGlar across all HbA 1c screening subgroups and in the overall study population without increasing the risk of hypoglycemia. Trial Registration Clinicaltrials.gov Identifier: NCT02058160. Funding Sanofi.

This study compares liraglutide versus common antihyperglycemic treatments in reducing hemoglobin A^sub 1c^ (A1C) values across multiple levels of baseline glycemic control and in reaching glycemic targets. Pooled patient data from 7 phase 3, multi-national, randomized controlled trials in patients with type 2 diabetes were stratified by baseline A1C values into 5 categories: ≤7.5%, >7.5% to 8.0%, >8.0% to 8.5%, >8.5% to 9.0%, and >9.0%. Irrespective of treatment, reductions in A1C levels were generally greater in groups with higher baseline A1C values. After 26 weeks of treatment, liraglutide produced the greatest reductions in A1C values across all baseline categories, ranging from 0.7% to 1.8% (baseline A1C categories ≤7.5% to >9.0%, respectively), followed by insulin glargine (0.3% to 1.5%) and then by glimepiride (0.4% to 1.3%). Across a wide spectrum of baseline A1C categories, liraglutide is an efficacious treatment option for patients with type 2 diabetes.

NovoPen®, the first insulin pen, was introduced in 1985. This review article is an update of a review paper published in 2006 on 20 years’ use of the NovoPen® family of insulin pens in the management of diabetes mellitus. The literature searches conducted in the earlier review article were updated with search results for new articles published since April 2005. This was followed by an iterative search of references cited in identified publications and by searches of abstracts from proceedings of major international diabetes conferences since 2005. Most of the original studies identified in the 2006 review showed that insulin regimens using the NovoPen® family of insulin pens were at least as effective (and in some cases superior) in maintaining glycaemic control and were as safe (in terms of hypoglycaemia) as conventional insulin regimens employing vials and syringes. Most patients preferred the various NovoPen® insulin pens over vials and syringes, with some evidence suggesting that the use of discreet devices, such as those of the NovoPen® family, facilitates intensive insulin therapy regimens, thereby helping to improve lifestyle flexibility. The new search results showed that the current generation of the device for the adult population, NovoPen® 4, retains these benefits and further meets patients’ needs by improving ease of use, convenience and discretion, which may be particularly important for those with manual dexterity, visual or auditory impairments. There was also evidence that healthcare professionals would be more likely to recommend NovoPen® 4 to their patients than other devices. The recently introduced NovoPen Echo®, designed specifically for the paediatric population, combines half-increment dosing with a memory function that can be used to retrieve information about the time and amount of the last dose, potentially reducing the fear of double dosing or missing a dose. Evidence obtained from the new searches suggested that paediatric patients, their parents and healthcare professionals were highly satisfied with NovoPen Echo® overall, with most paediatric patients rating it their favourite pen compared with other insulin pens. In conclusion, new data published over the last 5 years on the use of NovoPen® devices add to the large body of published evidence supporting the patient-related benefits of durable insulin injection pens in the treatment of diabetes since the first such pen was introduced in 1985. Together, the benefits of NovoPen® are considered likely to improve both patients’ quality of life and their compliance with therapy.

A Copenhagen native, Klaus Henning Jensen started his career working as a medical doctor in a hospital setting. An entrepreneur at heart, he drew from his background in physics and business administration to co-found a device company - successfully developing a new type of surgical screw for osteosynthesis of hip fractures. Klaus' career at Novo Nordisk spans almost a decade and is rooted in Global Medical Affairs. He has held a series of Medical Director and Vice President roles with responsibilities cutting across the entire Novo Nordisk (UK and Ireland) diabetes portfolio - medical devices, Victoza (liraglutide), Tresiba (insulin degludec), Ryzodeg (insulin degludec/insulin aspart) and Xultophy (insulin degludec/liraglutide), as well as other GLP-1 and insulin treatments - with medical and scientific responsibility for the R&D of several of these products. He now sits on the UK & Ireland leadership team as Head of Clinical, Medical and Regulatory.

To compare liraglutide versus common antihyperglycemic treatments in reducing hemoglobin A1c (A1C) values across multiple levels of baseline glycemic control and in reaching glycemic targets. Pooled patient data from 7 phase 3, multinational, randomized controlled trials in patients with type 2 diabetes were stratified by baseline A1C values into 5 categories: ≤7.5%, >7.5% to 8.0%, >8.0% to 8.5%, >8.5% to 9.0%, and y9.0%. The changes in A1C from baseline to week 26 of treatment and patient proportions reaching A1C targets of <7.0% and ≤6.5% were compared between liraglutide (1.8 mg daily) and sitagliptin, glimepiride, rosiglit-azone, exenatide, and insulin glargine across all baseline A1C categories. Irrespective of treatment, reductions in A1C levels were generally greater in groups with higher baseline A1C values. After 26 weeks of treatment, liraglutide produced the greatest reductions in A1C values across all baseline categories, ranging from 0.7% to 1.8% (baseline A1C categories ≤7.5% to >9.0%, respectively), followed by insulin glargine (0.3% to 1.5%) and then by glimepiride (0.4% to 1.3%). Generally, larger percentages of patients achieved the A1C target of ≤6.5% with liraglutide therapy across all baseline categories (from 62% of patients with A1C values ≤7.5% to 10% of patients with A1C values >9.0%) in comparison with other treatments (ranging from 49% to 0% of patients, respectively). Similarly, greater proportions of patients also reached the A1C target of <7.0% with liraglutide therapy across all baseline categories (from 83% of patients with A1C values ≤7.5% to 25% of patients with A1C values >9.0%) versus comparators (from 74% to 5% of patients, respectively). Across a wide spectrum of baseline A1C categories, liraglutide is an efficacious treatment option for patients with type 2 diabetes.

The properties of graphene nanoribbons (GNRs) make them good candidates for next-generation electronic materials. Whereas ‘top-down’ methods, such as the lithographical patterning of graphene and the unzipping of carbon nanotubes, give mixtures of different GNRs, structurally well-defined GNRs can be made using a ‘bottom-up’ organic synthesis approach through solution-mediated or surface-assisted cyclodehydrogenation reactions. Specifically, non-planar polyphenylene precursors were first ‘built up’ from small molecules, and then ‘graphitized’ and ‘planarized’ to yield GNRs. However, fabrication of processable and longitudinally well-extended GNRs has remained a major challenge. Here we report a bottom-up solution synthesis of long (>200 nm) liquid-phase-processable GNRs with a well-defined structure and a large optical bandgap of 1.88 eV. Self-assembled monolayers of GNRs can be observed by scanning probe microscopy, and non-contact time-resolved terahertz conductivity measurements reveal excellent charge-carrier mobility within individual GNRs. Such structurally well-defined GNRs may prove useful for fundamental studies of graphene nanostructures, as well as the development of GNR-based nanoelectronics. Liquid-phase-processable graphene nanoribbons (GNRs) over 200 nm long and with well-defined structures have now been synthesized by a bottom-up method, and are found to have a large optical bandgap of 1.88 eV. Scanning probe microscopy revealed highly ordered self-assembled monolayers of the GNRs, and the high intrinsic charge-carrier mobility of individual ribbons was characterized by terahertz spectroscopy.

•Cardiovascular risk factors are associated with older brain age.•Blood pressure is more strongly associated with white matter compared to gray matter.•Resting state functional connectivity provides lower brain-age prediction accuracy.•Brain-age prediction accuracy depends on sample size and age range. Brain age is becoming a widely applied imaging-based biomarker of neural aging and potential proxy for brain integrity and health. We estimated multimodal and modality-specific brain age in the Whitehall II (WHII) MRI cohort using machine learning and imaging-derived measures of gray matter (GM) morphology, white matter microstructure (WM), and resting state functional connectivity (FC). The results showed that the prediction accuracy improved when multiple imaging modalities were included in the model (R2 = 0.30, 95% CI [0.24, 0.36]). The modality-specific GM and WM models showed similar performance (R2 = 0.22 [0.16, 0.27] and R2 = 0.24 [0.18, 0.30], respectively), while the FC model showed the lowest prediction accuracy (R2 = 0.002 [-0.005, 0.008]), indicating that the FC features were less related to chronological age compared to structural measures. Follow-up analyses showed that FC predictions were similarly low in a matched sub-sample from UK Biobank, and although FC predictions were consistently lower than GM predictions, the accuracy improved with increasing sample size and age range. Cardiovascular risk factors, including high blood pressure, alcohol intake, and stroke risk score, were each associated with brain aging in the WHII cohort. Blood pressure showed a stronger association with white matter compared to gray matter, while no differences in the associations of alcohol intake and stroke risk with these modalities were observed. In conclusion, machine-learning based brain age prediction can reduce the dimensionality of neuroimaging data to provide meaningful biomarkers of individual brain aging. However, model performance depends on study-specific characteristics including sample size and age range, which may cause discrepancies in findings across studies.