Caution in using the activated partial thromboplastin time to monitor argatroban in COVID-19 and vaccine-induced immune thrombocytopenia and thrombosis (VITT)

Introduction Argatroban is licensed for patients with heparin-induced thrombocytopenia and is conventionally monitored by activated partial thromboplastin time (APTT) ratio. The target range is 1.5 to 3.0 times the patients’ baseline APTT and not exceeding 100 s, however this baseline is not always known. APTT is known to plateau at higher levels of argatroban, and is influenced by coagulopathies, lupus anticoagulant and raised FVIII levels. It has been used as a treatment for COVID-19 and Vaccine-induced Immune Thrombocytopenia and Thrombosis (VITT). Some recent publications have favored the use of anti-IIa methods to determine the plasma drug concentration of argatroban. Methods Plasma of 60 samples from 3 COVID-19 patients and 54 samples from 5 VITT patients were tested by APTT ratio and anti-IIa method (dilute thrombin time dTT). Actin FS APTT ratios were derived from the baseline APTT of the patient and the mean normal APTT. Results Mean APTT ratio derived from baseline was 1.71 (COVID-19), 1.33 (VITT) compared to APTT ratio by mean normal 1.65 (COVID-19), 1.48 (VITT). dTT mean concentration was 0.64 µg/ml (COVID-19) 0.53 µg/ml (VITT) with poor correlations to COVID-19 baseline APTT ratio r2 = 0.1526 p <0.0001, mean normal r2 = 0.2188 p < 0.0001; VITT baseline APTT ratio r2 = 0.04 p < 0.001, VITT mean normal r2 = 0.0064 p < 0.001. Conclusions We believe that dTT is a superior method to monitor the concentration of argatroban, we have demonstrated significant differences between APTT ratios and dTT levels, which could have clinical impact. This is especially so in COVID-19 and VITT

Design, synthesis and biological assessment of novel N-substituted 3-(phthalimidin-2-yl)-2,6-dioxopiperidines and 3-substituted 2,6-dioxopiperidines for TNF-α inhibitory activity

Eight novel 2-(2,6-dioxopiperidin-3-yl)phthalimidine EM-12 dithiocarbamates 9 and 10, N-substituted 3-(phthalimidin-2-yl)-2,6-dioxopiperidines 11-14 and 3-substituted 2,6-dioxopiperidines 16 and 18 were synthesized as tumor necrosis factor-α (TNF-α) synthesis inhibitors. Synthesis involved utilization of a novel condensation approach, a one-pot reaction involving addition, iminium rearrangement and elimination, to generate the phthalimidine ring required for the creation of compounds 9-14. Agents were, thereafter, quantitatively assessed for their ability to suppress the synthesis on TNF-α in a lipopolysaccharide (LPS)-challenged mouse macrophage-like cellular screen, utilizing cultured RAW 264.7 cells. Whereas compounds 9, 14 and 16 exhibited potent TNF-α lowering activity, reducing TNF-α by up to 48% at 30 μM, compounds 12, 17 and 18 presented moderate TNF-α inhibitory action. The TNF-α lowering properties of these analogs proved more potent than that of revlimid (3) and thalidomide (1). In particular, N-dithiophthalimidomethyl-3-(phthalimidin-2-yl)-2,6-dioxopiperidine 14 not only possessed the greatest potency of the analogs to reduce TNF-α synthesis, but achieved this with minor cellular toxicity at 30 μM. The pharmacological focus of the presented compounds is towards the development of well-tolerated agents to ameliorate the neuroinflammation, that is, commonly associated with neurodegenerative disorders, epitomized by Alzheimer's disease and Parkinson's disease

An algorithm for identifying career lines from job history data

A comparatively simple method of uncovering the deep structure of career lines from job history data is described. Key decisions in the construction of the programming algorithm are related to substantive and theoretical ideas. Illustrations of the use of the method are offered, based on blue collar job histories from an American and a Dutch firm. Advantages, drawbacks and other applications of the program are discussed