A laboratory method for parallel determination of platelet aggregation and thrombin generation

Optimal use of combinations of antiaggregating and antithrombotic drugs in vivo requires improved methods for testing of possible synergistic drug effects. Therefore, we developed an in vitro model that allows parallel evaluation of the influence of drugs on the time course of platelet aggregation inhibition and on thrombin generation inhibition. Platelet rich plasma samples were incubated with different amounts of antiaggregating and/or antithrombotic agents and the effects on thrombin generation, lag phase until the onset of platelet aggregation, and on inhibition of platelet aggregation were detected. Plasma activation was performed by addition of high (29 nM final concentration, "high coagulant challenge") or low (5 pM final concentration, "low coagulant challenge") amounts of tissue factor. Thus, platelet activation is initiated in our model by endogenously generated thrombin and not by exogenously added agonists, as usual in conventional evaluation of platelet aggregation. The combination of glycoprotein IIb/IIIa inhibitors (eptifibatide or abciximab) and anticoagulants (unfractionated heparin, low molecular weight heparin, or recombinant hirudin) used in this study exhibited an additive effect on prolongation of the lag phase until the onset of platelet aggregation. Under high but not under low coagulant challenge the combination of eptifibatide and anticoagulants had a synergistic inhibitory effect on platelet aggregation. Combination of abciximab and anticoagulants had no additive inhibitory effects on platelet aggregation under both high and low coagulant challenge. Under low coagulant challenge combination of eptifibatide but not abciximab with low molecular weight heparin significantly reduced the thrombin generation. We suggest that our laboratory method might be useful for pre-clinical testing of in vitro effects of glycoprotein IIb/IIIa inhibitors and anticoagulants.     

Novel Method for Three-Dimensional Facial Expression Recognition Using Self-Normalizing Neural Networks and Mobile Devices

Introduction To date, most ways to perform facial expression recognition rely on two-dimensional images, advanced approaches with three-dimensional data exist. These however demand stationary apparatuses and thus lack portability and possibilities to scale deployment. As human emotions, intent and even diseases may condense in distinct facial expressions or changes therein, the need for a portable yet capable solution is signified. Due to the superior informative value of three-dimensional data on facial morphology and because certain syndromes find expression in specific facial dysmorphisms, a solution should allow portable acquisition of true three-dimensional facial scans in real time. In this study we present a novel solution for the three-dimensional acquisition of facial geometry data and the recognition of facial expressions from it. The new technology presented here only requires the use of a smartphone or tablet with an integrated TrueDepth camera and enables real-time acquisition of the geometry and its categorization into distinct facial expressions. Material and Methods Our approach consisted of two parts: First, training data was acquired by asking a collective of 226 medical students to adopt defined facial expressions while their current facial morphology was captured by our specially developed app running on iPads, placed in front of the students. In total, the list of the facial expressions to be shown by the participants consisted of “disappointed”, “stressed”, “happy”, “sad” and “surprised”. Second, the data were used to train a self-normalizing neural network. A set of all factors describing the current facial expression at a time is referred to as “snapshot”. Results In total, over half a million snapshots were recorded in the study. Ultimately, the network achieved an overall accuracy of 80.54% after 400 epochs of training. In test, an overall accuracy of 81.15% was determined. Recall values differed by the category of a snapshot and ranged from 74.79% for “stressed” to 87.61% for “happy”. Precision showed similar results, whereas “sad” achieved the lowest value at 77.48% and “surprised” the highest at 86.87%. Conclusions With the present work it can be demonstrated that respectable results can be achieved even when using data sets with some challenges. Through various measures, already incorporated into an optimized version of our app, it is to be expected that the training results can be significantly improved and made more precise in the future. Currently a follow-up study with the new version of our app that encompasses the suggested alterations and adaptions, is being conducted. We aim to build a large and open database of facial scans not only for facial expression recognition but to perform disease recognition and to monitor diseases’ treatment progresses.     

Update Breast Cancer 2022 Part 4 – Advanced-Stage Breast Cancer

For the treatment of patients with advanced HER2-negative hormone receptor-positive breast cancer, several substances have been introduced into practice in recent years. In addition, other drugs are under development. A number of studies have been published over the past year which have shown either an advantage for progression-free survival or for overall survival. This review summarizes the latest results, which have been published at current congresses or in specialist journals, and classifies them in the clinical treatment context. In particular, the importance of therapy with CDK4/6 inhibitors – trastuzumab deruxtecan, sacituzumab govitecan and capivasertib – is discussed. For trastuzumab deruxtecan, an overall survival benefit in HER2-negative breast cancer with low HER2 expression (HER2-low expression) was reported in the Destiny-Breast-04 study. Similarly, there was an overall survival benefit in the FAKTION study with capivasertib. The lack of overall survival benefit for palbociclib in the first line of therapy raises the question of clinical classification.Key words: advanced breast cancer, chemotherapy, endocrine therapy, antibody drug conjugates     

Update Breast Cancer 2022 Part 5 – Early Stage Breast Cancer

The treatment of patients with early stage breast cancer has changed in recent years due to the introduction of pembrolizumab, olaparib, and abemaciclib. These and other drugs with the same class of active ingredient are currently in trial for various indications. This review article summarizes the latest results that have either been presented at major conferences such as the ESMO 2022 or published recently in international journals. This includes reports on newly discovered breast cancer genes, atezolizumab in neoadjuvant therapy in HER2-positive patients, long-term data from the APHINITY study, and on how preoperative peritumoral application of local anesthetics can influence the prognosis. We also present solid data on dynamic Ki-67 from the ADAPT studies.Key words: breast cancer, surgery, chemotherapy, therapy standard     

心身医学的主要问题

心身医学是一门研究躯体、心理、社会相互作用的过程及其与健康和疾病相关性的医学科学(躯体-心理-社会过程),因此心身医学是所有医学分支学科的基础方法,而其中的机能整体性和心理发生性方法是有区别的。机能整体性方法认为每种疾病有其社会心理因素(“我们是治疗生病的人而不     

Die Beziehungen der Schilddrüse zu den weiblichen Geschlechtsorganen

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Beiträge zur Lehre von den Hautströmen

Ohne ZusammenfassungSehliesslieh sei uns noch gestattet, unserem hochverehrten Lehrer, Herrn Prof. Hermann, ftir die vielfache l=Iilfe, welehe er dureh Rath und That unserer Arbeit angedeihen liess, unseren herzliehsten Dank zu sagen.     

Max Cloetta

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Eugen Rost zum Siebzigsten Geburtstage (24. Oktober 1940)

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Über eine der Röntgenwirkung ähnliche Chromosomenschädigung in den Epidermiszellen von Amphibienlarven nach Behandlung mit Neutralrot

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