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In this work, an electrode was developed to determine the dielectric properties of tissue phantoms using impedance measurements. For this purpose, a coaxial electrode design was selected as the most suitable electrode design. Three tissue phantoms (blood, fat, muscle) were prepared from distilled water, sodium chloride, 1,2-propanediol, agar, and gelatine, and then characterized. Measurements were performed using an impedance analyzer in a range between 1 kHz and 1 MHz. A comparison with literature values showed good correspondance of the permittivity values determined, thus proving the applicability of the electrode design. However, the conductivity values measured were different from literature values. In the future, alteration and minimization of the electrode can be done to further improve the characterization.

We present a basic principle and good practices of the rheology of polymers, particularly for teachers or lecturers at colleges or universities for educational purposes, as well as for beginner researchers who may refer to this article as their self-learning resources. Basic consideration of the experimental methods using parallel-plate oscillatory rheometer and step-by-step guidelines for the estimation of the power law dependence of storage, G′ and loss, G″ modulus as well as the estimation of the relaxation time at f cross G′−G′′ ${f}_{\,\mathrm{cross}}^{\,{G}^{\prime }-{G}^{\prime \prime }}$ at terminal zone using various approaches such as commercial graphical software, manual graphical approach and commercial rheometer software are highlighted. Good practices for data interpretation using different approaches are described and compared where the outcomes revealed the manual graphical approach or commercial graphical software yield comparable results with the commercial rheometer software. In order to have better insight, several examples and exercises which are applicable for teaching and self-learning activities are also provided.

Megan E Branda,1,2 Marleen Kunneman,1,3 Alejandra I Meza-Contreras,1,4 Nilay D Shah,5 Erik P Hess,6 Annie LeBlanc,7 Jane A Linderbaum,4 Danika M Nelson,4 Margaret R Mc Donah,8 Carrie Sanvick,9 Holly K Van Houten,10 Megan Coylewright,11 Sara R Dick,12 Henry H Ting,5 Victor M Montori1 1Knowledge and Evaluation Research Unit, Department of Medicine, Mayo Clinic, Rochester, MN, USA; 2Division of Clinical Trials and Biostatistics, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA; 3Medical Decision Making, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, Netherlands; 4Department of Cardiovascular Diseases, Mayo Clinic, Rochester, MN, USA; 5Delta Air Lines, Atlanta, GA, USA; 6Department of Emergency Medicine, Vanderbilt University Medical Center, Nashville, TN, USA; 7Faculty of Medicine, Laval University, Quebec City, Quebec, Canada; 8Mayo Clinic Health System, Mayo Clinic, Rochester, MN, USA; 9Department of Nursing, Mayo Clinic, Rochester, MN, USA; 10Robert D and Patricia E Kern Center for the Science of Healthcare Delivery, Mayo Clinic, Rochester, MN, USA; 11Section of Cardiovascular Medicine, Erlanger Heart and Lung Institute, Chattanooga, TN, USA; 12Education Project Management Office, Mayo Clinic, Rochester, MN, USACorrespondence: Victor M Montori, 200 First Street SW, Rochester, MN, 55905, USA, Tel +1 507-284-2511, Email Montori.victor@mayo.eduObjective: Adherence to guideline-recommended medications after acute myocardial infarction (AMI) is suboptimal. Patient fidelity to treatment regimens may be related to their knowledge of the risk of death following AMI, the pros and cons of medications, and to their involvement in treatment decisions. Shared decision-making may improve both patients’ knowledge and involvement in treatment decisions.Methods: In a pilot trial, patients hospitalized with AMI were randomized to the use of the AMI Choice conversation tool or to usual care. AMI Choice includes a pictogram of the patient’s estimated risk of mortality at 6 months with and without guideline-recommended medications, ie, aspirin, statins, beta-blockers, and angiotensin-converting enzyme inhibitors. Primary outcomes were patient knowledge and conflict with the decision made assessed via post-encounter surveys. Secondary outcomes were patient involvement in the decision-making process (observer-based OPTION12 scale) and 6-month medication adherence.Results: Patient knowledge of the expected survival benefit from taking medications was significantly higher (62% vs 16%, p< 0.0001) in the AMI Choice group (n = 53) compared to the usual care group (n = 53). Both groups reported similarly low levels of conflict with the decision to start the medications (13 (SD 24.2) vs 16 (SD 22) out of 100; p=0.16). The extent to which clinicians in the AMI Choice group involved their patients in the decision-making process was high (OPTION12 score 53 out of 100, SD 12). Medication adherence at 6-months was relatively high in both groups and not different between groups.Conclusion: The AMI Choice conversation tool improved patients’ knowledge of their estimated risk of short-term mortality after an AMI and the pros and cons of treatments to reduce this risk. The effect on patient fidelity to recommended medications of using this SDM tool and of SDM in general should be tested in larger trials enrolling patients at high risk for nonadherence.Trial Registration Number: NCT00888537.Keywords: shared decision making, acute myocardial infarction, adherence, randomized trial

Das Vorkommen resistenter Ungräser stellt für Landwirte und Beratung ein zusätzliches Problem für die langfristige Planung des Unkrautmanagements dar. Wir stellen hier einen Ansatz zur individuellen Risikoermittlung der Resistenzentwicklung und der Ableitung individueller Maßnahmen zur Resistenzvermeidung und Kontrolle von Ungräsern vor. Die Basis für die Entwicklung eines Beratungs- Algorithmus bildet dabei ein deutschlandweit durchgeführtes Monitoring der Jahre 2019-2021. Auf Basis dieser Daten, zusammen mit weiteren externen Daten, wird mit Hilfe von Verfahren des maschinellen Lernens ein Algorithmus erarbeitet, der frühzeitig auf Resistenz-Probleme einzelner Flächen hinweist und eine Anpassung von Maßnahmen vorschlägt. Ein Prototyp ist für die Saison 2022/23 geplant.

Der Befall und die Resistenzsituation von Alopecurus myosuroides Huds., Apera spica-venti (L.) P. Beauv., Bromus spp. und Lolium spp. wurden in den Jahren 2019-2021 untersucht. Es zeigt sich, dass gerade im Jahr 2021 der Befall höher war als in den Jahren davor. Resistenzen wurden gerade bei A. myosuroides und Lolium spp. sowohl bei den ACCase- als auch bei den ALS-Inhibitoren gefunden, während für Bromus spp. und A. spica-venti eher Probleme bei Sulfonylharnstoffen gefunden wurden. Zunehmend beobachten wir jedoch Fälle von Mischverungrasungen mehrerer resistenter Gräser, die die Landwirte zunehmend vor Probleme stellen.

Herbizidresistenzen nehmen zu und entwickeln sich diffizil. Pauschale Empfehlungen lösen keine Probleme, sondern verschärfen die Problematik vielfach. Es braucht dringend Lösungen auf Basis der einzelbetrieblichen Analyse. Auf Algorithmen basierende Entscheidungshilfen für das Management von Herbizidresistenzen müssen dafür unterschiedlichste Datensätze konsolidieren. Biologische Datensätze können nur durch messbare Parameter erhoben werden. Zur Bewertung der Herbizidwirkung auf Unkräuter liefert der Biotest an Nachkommen von Pflanzen der Feldpopulation bis heute die wichtigsten Daten. So kann eine komplexe Phänologie gut erfasst werden. Der Biotest bleibt aber sehr arbeits- und kostenaufwändig. Gleichzeitig braucht eine zuverlässige Modellierung eine hohe Stichprobenzahl mit möglichst geringer Redundanz der Daten. Die Lösung kann nur in einer qualitativen Erhöhung der Stichprobe bei gleichzeitiger Kostenreduktion liegen. Ein wesentlicher Teil liegt in der Umsetzung wissenschaftlicher Erkenntnis über die Zusammenhänge von Resistenzmechanismen und ihrer Ausprägung im Feld. Eine Bündelung verschiedener Datensätze zeigt: Wiederholende Muster lassen sich durch deutlich weniger Daten abbilden und so Redundanzen vermeiden. Moderne Verfahren zur Hochdurchsatz- Genotypisierung von Populationen eröffnen neue Möglichkeiten: Es werden zukünftig nicht mehr SNPs in einzelnen Pflanzen erfasst, sondern ihr Vorkommen wird prozentual aus Mischproben von 50 oder mehr Pflanzen ermittelt. Dieser Paradigmenwechsel ermöglicht nicht nur eine Reduktion der Kosten pro Datenpunkt, sondern liefert einen deutlich höheren Stichprobenumfang. Damit lassen sich repräsentative Daten mit geringem Aufwand erheben, die wiederum in dynamischen Modellen als Entscheidungshilfen der Praxis zur Verfügung gestellt werden können.

Ayse Dudu Altintas Dogan,1– 3 Ole Hilberg,2,3 Søren Hess,2,4 Torben Tranborg Jensen,1 Else-Marie Bladbjerg,2,5 Claus Bogh Juhl1,2,6 1Department of Medicine, Hospital South West Jutland, University Hospital of Southern Denmark, Esbjerg, Denmark; 2Department of Regional Health Research, Faculty of Health Sciences, University of Southern Denmark, Odense, Denmark; 3Department of Medicine, Lillebaelt Hospital, University Hospital of Southern Denmark, Vejle, Denmark; 4Department of Radiology and Nuclear Medicine, Hospital South West Jutland, University Hospital of Southern Denmark, Esbjerg, Denmark; 5Unit for Thrombosis Research, Department of Clinical Biochemistry, Hospital South West Jutland, University Hospital of Southern Denmark, Esbjerg, Denmark; 6Steno Diabetes Center, Odense, DenmarkCorrespondence: Ayse Dudu Altintas Dogan, Department of Medicine, Hospital South West Jutland, University Hospital of Southern Denmark, Finsensgade 35, Esbjerg, 6700, Denmark, Tel +45 22 71 50 90, Email ayse.dudu.altintas.dogans@rsyd.dkPurpose: Chronic obstructive pulmonary disease (COPD) affects millions of people worldwide. Obesity is commonly seen concomitantly with COPD. People with COPD have reduced quality of life, reduced physical activity, chronic respiratory symptoms, and may suffer from frequent clinical exacerbations. Liraglutide is a glucagon-like peptide-1 receptor agonist (GLP-1RA) approved for weight loss and treatment of type-2 diabetes mellitus. In addition, liraglutide exerts anti-inflammatory actions by reducing IL-6 and MCP-1 levels. We investigated the effect of liraglutide on pulmonary function in people suffering from obesity and COPD.Patients and Methods: In this controlled, double-blind trial, 40 people with obesity and COPD from two outpatient clinics were allocated randomly to receive liraglutide (3.0 mg, s.c.) or placebo (s.c.) for 40 weeks. At baseline and after 4, 20, 40, and 44 weeks, participants underwent pulmonary-function tests, 6-min walking test, and replied to a questionnaire regarding the clinical impact of COPD (COPD assessment test (CAT)-score).Results: Compared with placebo, liraglutide use resulted in significant weight loss, increased forced vital capacity (FVC) and carbon monoxide diffusion capacity, and improved CAT-score. We found no significant changes in forced expiratory volume in one second (FEV1), FEV1/FVC, or 6-min walking distance.Conclusion: In patients suffering from obesity and COPD, 40 weeks of treatment with liraglutide improved some measures of pulmonary function. Our study suggests that liraglutide at 3.0 mg may be appropriate treatment in patients with obesity and COPD.Keywords: GLP-1 RA, COPD, obesity, inflammation, spirometry

Jill A Ohar,1 Gary T Ferguson,2 Donald A Mahler,3 M Bradley Drummond,4 Rajiv Dhand,5 Roy A Pleasants,4,6 Antonio Anzueto,7 David MG Halpin,8 David B Price,9,10 Gail S Drescher,11 Haley M Hoy,12 John Haughney,9 Michael W Hess,13 Omar S Usmani14 1Section of Pulmonary, Critical Care, Allergy, and Immunology, School of Medicine, Wake Forest University, Winston-Salem, NC, USA; 2Pulmonary Research Institute of Southeast Michigan, Farmington Hills, MI, USA; 3Geisel School of Medicine at Dartmouth, Hanover, NH, USA; 4Division of Pulmonary Diseases and Critical Care Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA; 5Division of Pulmonary and Critical Care Medicine, Department of Medicine, University of Tennessee Graduate School of Medicine, Knoxville, TN, USA; 6Department of Quality, University of Michigan, Ann Arbor, MI, USA; 7Pulmonology Section, University of Texas Health, and South Texas Veterans Health Care System, San Antonio, TX, USA; 8University of Exeter Medical School, College of Medicine and Health, University of Exeter, Exeter, UK; 9Academic Primary Care, Division of Applied Health Sciences, University of Aberdeen, Aberdeen, UK; 10Observational and Pragmatic Research Institute, Singapore; 11Pulmonary Services Department, MedStar Washington Hospital Center, Washington, DC, USA; 12Transplant Center, Vanderbilt University Medical Center, Nashville, TN, USA; 13COPD Foundation, Kalamazoo, MI, USA; 14National Heart and Lung Institute, Imperial College London and Royal Brompton Hospital, London, UKCorrespondence: Jill A OharSection of Pulmonary, Critical Care, Allergy, and Immunology, School of Medicine, Wake Forest University, 1834 Wake Forest Road, Winston-Salem, NC 27109, USATel +1 336-716-8426Fax +1 336-716-7277Email johar@wakehealth.eduAbstract: Dry powder inhalers (DPIs) are breath actuated, and patients using DPIs need to generate an optimal inspiratory flow during the inhalation maneuver for effective drug delivery to the lungs. However, practical and standardized recommendations for measuring peak inspiratory flow (PIF)—a potential indicator for effective DPI use in chronic obstructive pulmonary disease (COPD)—are lacking. To evaluate recommended PIF assessment approaches, we reviewed the Instructions for Use of the In-Check™ DIAL and the prescribing information for eight DPIs approved for use in the treatment of COPD in the United States. To evaluate applied PIF assessment approaches, we conducted a PubMed search from inception to August 31, 2021, for reports of clinical and real-life studies where PIF was measured using the In-Check™ DIAL or through a DPI in patients with COPD. Evaluation of collective sources, including 47 applicable studies, showed that instructions related to the positioning of the patient with their DPI, instructions for exhalation before the inhalation maneuver, the inhalation maneuver itself, and post-inhalation breath-hold times varied, and in many instances, appeared vague and/or incomplete. We observed considerable variation in how PIF was measured in clinical and real-life studies, underscoring the need for a standardized method of PIF measurement. Standardization of technique will facilitate comparisons among studies. Based on these findings and our clinical and research experience, we propose specific recommendations for PIF measurement to standardize the process and better ensure accurate and reliable PIF values in clinical trials and in daily clinical practice.Keywords: chronic obstructive pulmonary disease, dry powder inhalers, peak inspiratory flow

Arthur R Brant,1 Suzann Pershing,1,2 Olivia Hess,1 David Rooney,1 Jeffrey Goldberg,1 Geoffrey Tabin,1,2 Sophia Y Wang1 1Byers Eye Institute, Stanford University, Stanford, CA, USA; 2VA Palo Alto Health Care System, Palo Alto, CA, USACorrespondence: Arthur R Brant Tel +1 330 651 7898Email abrant@Stanford.eduPurpose: To measure the COVID-19 pandemic impact on missed ophthalmology clinic visits and the influence of patient and eye disease characteristics on likelihood of missing clinic visits before and during the pandemic.Patients and Methods: A retrospective observational study analyzing eye clinic patients at a large tertiary care academic institution. We identified patients scheduled for eye care during pre-COVID-19 (January 1–February 29, 2020) and early COVID-19 (March 16–May 31, 2020) time periods. Missed appointment frequency and characteristics were evaluated during each time period. Multivariable logistic regression models were developed to examine adjusted odds of having at least one missed appointment during a given time period. Covariates included age, sex, race/ethnicity, marital status, preferred language (non-English vs English), insurance, distance from clinic, and diagnosis.Results: Overall, 82.0% (n = 11,998) of pre-COVID-19 patients completed all scheduled visits, compared to only 59.3% (n = 9020) during COVID-19. Missed visits increased dramatically in late March 2020, then improved week by week through the end of May 2020. General ophthalmology/cataract and strabismus clinics had the highest rates of missed clinic visits during the COVID-19 period; neuro-ophthalmology, retina, cornea, oculoplastics and glaucoma had the lowest. Females, Blacks, Hispanics, Asians, ages 50+, and married patients had higher adjusted odds of missing clinic visits, both pre-COVID-19 and during COVID-19. Asian, elderly, and cataract patients had the highest adjusted odds of missing clinic visits during COVID-19 and had significant increases in odds compared to pre-COVID-19. Non-married, diabetic macular edema, and wet age-related macular degeneration patients had the lowest adjusted odds of missed visits during COVID-19.Conclusion: Missed clinic visits increased dramatically during the COVID-19 pandemic, particularly among elderly and nonwhite patients. These findings reflect differences in eye care delivery during the pandemic, and they indicate opportunities to target barriers to care, even during non-pandemic eras.Keywords: COVID-19, healthcare utilization, disparities