Paraneoplastic pemphigus regression after thymoma resection

<p>Abstract</p> <p>Background</p> <p>Among human neoplasms thymomas are associated with highest frequency with paraneoplastic autoimmune diseases.</p> <p>Case presentation</p> <p>A case of a 42-year-old woman with paraneoplastic pemphigus as the first manifestation of thymoma is reported. Transsternal complete thymoma resection achieved pemphigus regression. The clinical correlations between pemphigus and thymoma are presented.</p> <p>Conclusion</p> <p>Our case report provides further evidence for the important role of autoantibodies in the pathogenesis of paraneoplastic skin diseases in thymoma patients. It also documents the improvement of the associated pemphigus after radical treatment of the thymoma.</p

Thorough investigation of the phenolic profile of reputable Greek honey varieties:varietal discrimination and floral markers identification using liquid chromatography–high-resolution mass spectrometry

Honey is a highly consumed commodity due to its potential health benefits upon certain consumption, resulting in a high market price. This fact indicates the need to protect honey from fraudulent acts by delivering comprehensive analytical methodologies. In this study, targeted, suspect and non-targeted metabolomic workflows were applied to identify botanical origin markers of Greek honey. Blossom honey samples (n = 62) and the unifloral fir (n = 10), oak (n = 24), pine (n = 39) and thyme (n = 34) honeys were analyzed using an ultra-high-performance liquid chromatography hybrid quadrupole time-of-flight mass spectrometry (UHPLC-q-TOF-MS) system. Several potential authenticity markers were revealed from the application of different metabolomic workflows. In detail, based on quantitative targeted analysis, three blossom honey markers were found, namely, galangin, pinocembrin and chrysin, while gallic acid concentration was found to be significantly higher in oak honey. Using suspect screening workflow, 12 additional bioactive compounds were identified and semi-quantified, achieving comprehensive metabolomic honey characterization. Lastly, by combining non-targeted screening with advanced chemometrics, it was possible to discriminate thyme from blossom honey and develop binary discriminatory models with high predictive power. In conclusion, a holistic approach to assessing the botanical origin of Greek honey is presented, highlighting the complementarity of the three applied metabolomic approaches

WRF Physics Ensemble Performance Evaluation over Continental and Coastal Regions in Germany

WRF is used to simulate eight extreme precipitation events that occurred over the regions of Schleswig–Holstein and Baden–Wurttemberg in Germany. The events were chosen from the German Weather Service (DWD) catalog and exceeded the DWD’s warning level 3 (i.e., rainfall > 40 mm/h). A two-way nesting approach is used with 9 and 3 km spatial resolutions. Initial and boundary conditions are obtained from the ERA5 dataset at 0.25° × 0.25°. To model each event, thirty different parameterization configurations were used, accounting for all possible combinations of five microphysics (MP), three cumulus (CU), and two planetary boundary layer (PBL) parameterization methods, yielding a total of 240 simulations. TOPSIS multicriteria analysis technique is employed to determine the performance skill of each setup and rank them, using six categorical and five statistical metrics. Resolution increase from 9 to 3 km did not improve forecasting accuracy temporally or in intensity. According to TOPSIS ranking, when treating each event individually, the ideal parameterizations combination is spatiotemporally dependent, with certain members ranking higher. When all events are considered, the Morrison double-moment MP–Grell–Freitas CU–YSU PBL combination works best with a frequency of occurrence in the top five performing scenarios of 30%, 47.5%, and 57.5% respectively

Sensitivity Assessment of WRF Parameterizations over Europe

Evaluation of the performance of the parameterization schemes used in the WRF model is assessed for temperature and precipitation over Europe at 36 km by 36 km grid resolution using gridded data from the ECA &amp; D 0.25° regular grid. Simulations are performed for a winter (i.e., January 2015) and a summer (i.e., July 2015) month using the two way nesting approach. A step-wise decision approach is followed, beginning with 18 simulations for the various microphysics schemes followed by 45 more, concerning all of the model’s PBL, Cumulus, Long-wave, Short-wave and Land Surface schemes. The best performing scheme at each step is chosen by integrating the entropy weighting method ‘Technique for Order Performance by Similarity to Ideal Solution’ (TOPSIS). The concluding scheme set consists of the Mansell-Ziegler-Bruning microphysics scheme, the Bougeault-Lacarrere PBL scheme, the Kain-Fritsch cumulus scheme, the RRTMG scheme for short-wave, the New Goddard for long-wave radiation and a seasonal-variable sensitive option for the Land Surface scheme

Investigating the WRF Temperature and Precipitation Performance Sensitivity to Spatial Resolution over Central Europe

The grid size resolution effect on the annual and seasonal simulated mean, maximum and minimum daily temperatures and precipitation is assessed using the Advanced Research Weather Research and Forecasting model (ARW-WRF, hereafter WRF) that dynamically downscales the National Centers for Environmental Prediction’s final (NCEP FNL) Operational Global Analysis data. Simulations were conducted over central Europe for the year 2015 using 36, 12 and 4 km grid resolutions. Evaluation is done using daily E-OBS data. Several performance metrics and the bias adjusted equitable threat score (BAETS) for precipitation are used. Results show that model performance for mean, maximum and minimum temperature improves when increasing the spatial resolution from 36 to 12 km, with no significant added value when further increasing it to 4 km. Model performance for precipitation is slightly worsened when increasing the spatial resolution from 36 to 12 km while further increasing it to 4 km has minor effect. However, simulated and observed precipitation data are in quite good agreement in areas with precipitation rates below 3 mm/day for all three grid resolutions. The annual mean fraction of observed and/or forecast events that were correctly predicted (BAETS), when increasing the grid size resolution from 36 to 12 and 4 km, suggests a slight modification on average over the domain. During summer the model presents significantly lower BAETS skill score compared to the rest of the seasons

Efficacy of Administration of an Angiotensin Converting Enzyme Inhibitor for Two Years on Autonomic and Peripheral Neuropathy in Patients with Diabetes Mellitus

Aim. To evaluate the effect of quinapril on diabetic cardiovascular autonomic neuropathy (CAN) and peripheral neuropathy (DPN). Patients and Methods. Sixty-three consecutive patients with diabetes mellitus [43% males, 27 with type 1 DM, mean age 52 years (range 22–65)], definite DCAN [abnormal results in 2 cardiovascular autonomic reflex tests (CARTs)], and DPN were randomized to quinapril 20 mg/day (group A, n=31) or placebo (group B, n=32) for 2 years. Patients with hypertension or coronary heart disease were excluded. To detect DPN and DCAN, the Michigan Neuropathy Screening Instrument Questionnaire and Examination (MNSIQ and MNSIE), measurement of vibration perception threshold with biothesiometer (BIO), and CARTs [R-R variation during deep breathing [assessed by expiration/inspiration ratio (E/I), mean circular resultant (MCR), and standard deviation (SD)], Valsalva maneuver (Vals), 30 : 15 ratio, and orthostatic hypotension (OH)] were used. Results. In group A, E/I, MCR, and SD increased (p for all comparisons < 0.05). Other indices (Vals, 30 : 15, OH, MNSIQ, MNSIE, and BIO) did not change. In group B, all CART indices deteriorated, except Vals, which did not change. MNSIQ, MNSIE, and BIO did not change. Conclusions. Treatment with quinapril improves DCAN (mainly parasympathetic dysfunction). Improved autonomic balance may improve the long-term outcome of diabetic patients

A Comparative Assessment of Cardiovascular Autonomic Reflex Testing and Cardiac 123

Aim. To compare the cardiovascular autonomic reflex tests (CARTs) with cardiac sympathetic innervation imaging with 123I-metaiodobenzylguanidine (MIBG) in patients with type 1 diabetes mellitus (T1DM). Patients and Methods. Forty-nine patients (29 males, mean age 36 ± 10 years, mean T1DM duration 19 ± 6 years) without cardiovascular risk factors were prospectively enrolled. Participants were evaluated for autonomic dysfunction by assessing the mean circular resultant (MCR), Valsalva maneuver (Vals), postural index (PI), and orthostatic hypotension (OH). Within one month from the performance of these tests, patients underwent cardiac MIBG imaging and the ratio of the heart to upper mediastinum count density (H/M) at 4 hours postinjection was calculated (abnormal values, H/M < 1.80). Results. Twenty-nine patients (59%) had abnormal CARTs, and 37 (76%) patients had an H/M_4 < 1.80 (p=0.456). MCR, PI, Vals, and OH were abnormal in 29 (59%), 8 (16%), 5 (10%), and 11 (22%) patients, respectively. When using H/M_4 < 1.80 as the reference standard, a cutoff point of ≥2 abnormal CARTs had a sensitivity of 100% but a specificity of only 33% for determining CAN. Conclusions. CARTs are not closely associated with 123I-MIBG measurements, which can detect autonomic dysfunction more efficiently than the former. In comparison to semiquantitative cardiac MIBG assessment, the recommended threshold of ≥2 abnormal CARTs to define cardiovascular autonomic dysfunction is highly sensitive but of limited specificity and is independently determined by the duration of T1DM

Protargetminer As A Proteome Signature Library Of Anticancer Molecules For Functional Discovery

Deconvolution of targets and action mechanisms of anticancer compounds is fundamental in drug development. Here, we report on ProTargetMiner as a publicly available expandable proteome signature library of anticancer molecules in cancer cell lines. Based on 287 A549 adenocarcinoma proteomes affected by 56 compounds, the main dataset contains 7,328 proteins and 1,307,859 refined protein-drug pairs. These proteomic signatures cluster by compound targets and action mechanisms. The targets and mechanistic proteins are deconvoluted by partial least square modeling, provided through the website http://protargetminer.genexplain.com. For 9 molecules representing the most diverse mechanisms and the common cancer cell lines MCF-7, RKO and A549, deep proteome datasets are obtained. Combining data from the three cell lines highlights common drug targets and cell-specific differences. The database can be easily extended and merged with new compound signatures. ProTargetMiner serves as a chemical proteomics resource for the cancer research community, and can become a valuable tool in drug discovery., Anticancer drugs often have widespread effects on the cellular proteome. Here, the authors generate a proteome signature library of drug-treated cancer cell lines and develop a software tool to deconvolute drug targets and gain insights into their mechanisms of action.PubMedWoSScopu