ACDA: implementation of an augmented drug synergy prediction algorithm.

Motivation: Drug synergy prediction is approached with machine learning techniques using molecular and pharmacological data. The published Cancer Drug Atlas (CDA) predicts a synergy outcome in cell-line models from drug target information, gene mutations and the models’ monotherapy drug sensitivity. We observed low performance of the CDA, 0.339, measured by Pearson correlation of predicted versus measured sensitivity on DrugComb datasets. Results: We augmented the approach CDA by applying a random forest regression and optimization via cross-validation hyper-parameter tuning and named it Augmented CDA (ACDA). We benchmarked the ACDA’s performance, which is 68% higher than that of the CDA when trained and validated on the same dataset spanning 10 tissues. We compared the performance of ACDA to one of the winning methods of the DREAM Drug Combination Prediction Challenge, the performance of which was lower than ACDA in 16 out of 19 cases. We further trained the ACDA on Novartis Institutes for BioMedical Research PDX encyclopedia data and generated sensitivity predictions for PDX models. Finally, we developed a novel approach to visualize synergy-prediction data. Availability and implementation: The source code is available at https://github.com/TheJacksonLaboratory/drug-synergy and the software package at PyPI. Contact: [email protected] or [email protected] Supplementary information: Supplementary data are available at Bioinformatics Advances online

Dupilumab responder types and predicting factors in patients with type 2 severe asthma:A real-world cohort study

Background: Severe asthma (SA) presents a considerable healthcare challenge despite optimal standard treatment. Dupilumab, which is effective in type 2 (T2) SA patients, demonstrates variable responses, categorizing patients as non-responders, partial responders, or those achieving clinical remission. However, real-world response rates remain underexplored. Additionally, understanding the characteristics of patients achieving clinical remission is crucial for predicting favourable responses to dupilumab.Objective: To investigate responder types and identify predictors of clinical remission and non-response induced by dupilumab in a real-world cohort of SA patients.Methods: We analyzed retrospective data from SA patients undergoing dupilumab treatment in a study conducted at Franciscus Gasthuis &amp; Vlietland hospital. Data were collected at baseline and at a 12 to 24-months follow-up (T = 12). Response rates were evaluated at T = 12. Predictors of non-response and clinical remission were investigated using multivariate logistic regression analysis with a stepwise forward variable selection approach. Results: Among the 175 patients screened, 136 met the inclusion criteria. At T = 12, 31.6 % achieved clinical remission, 47.1 % were partial responders and 21.3 % were non-responders. Predictors associated with clinical remission included high baseline blood eosinophil counts (BEC) and male sex. Conversely, younger age at baseline, low baseline total immunoglobin E (IgE) and low baseline fractional exhaled nitric oxide (FeNO) levels were identified as predictors of non-response. Conclusions: Dupilumab results in clinical disease remission in one-third of the treated patients. Clinical remission is predicted by high BEC and male sex, whereas low total IgE, low FeNO and younger age indicate a lower likelihood of response.</p

Integrating computationally assembled mouse transcript sequences with the Mouse Genome Informatics (MGI) database

Databases of experimentally generated and computationally derived transcript sequences are valuable resources for genome analysis and annotation. The utility of such databases is enhanced when the sequences they contain are integrated with such biological information as genomic location, gene function, gene expression and phenotypic variation. We present the analysis and results of a semi-automated process of connecting transcript assemblies with highly curated biological information for mouse genes that is available through the Mouse Genome Informatics (MGI) database

Korte termijn advies voedselreservering Oosterschelde; samenvattende rapportage in het kader van EVAII

In 1999 is na een tussentijdse evaluatie het beleidsbesluit Schelpdiervisserij Kustwateren 1999-2003 vastgesteld. Dit hield o.a. in dat het voedselreserveringsbeleid dat in de periode 1993-1998 van kracht was voor de Oosterschelde, werd gewijzigd: De hoeveelheid voedsel die in de periode voor 1999 werd gereserveerd voor vogels in de Oosterschelde, was gerelateerd aan de gemiddelde voedselbehoefte van de vogels die eind jaren 80 in dit gebied aanwezig waren. Deze gemiddelde voedselbehoefte was vastgesteld op 3,4 miljoen kilo kokkelvlees en 1,3 miljoen kilo mosselvlee

A NICER Discovery of a Low-Frequency Quasi-Periodic Oscillation in the Soft-Intermediate State of MAXI J1535-571

We present the discovery of a low-frequency $\approx 5.7$ Hz quasi-periodic oscillation (QPO) feature in observations of the black hole X-ray binary MAXI J1535-571 in its soft-intermediate state, obtained in September-October 2017 by the Neutron Star Interior Composition Explorer (NICER). The feature is relatively broad (compared to other low-frequency QPOs; quality factor $Q\approx 2$) and weak (1.9% rms in 3-10 keV), and is accompanied by a weak harmonic and low-amplitude broadband noise. These characteristics identify it as a weak Type A/B QPO, similar to ones previously identified in the soft-intermediate state of the transient black hole X-ray binary XTE J1550-564. The lag-energy spectrum of the QPO shows increasing soft lags towards lower energies, approaching 50 ms at 1 keV (with respect to a 3-10 keV continuum). This large phase shift has similar amplitude but opposite sign to that seen in Rossi X-ray Timing Explorer data for a Type B QPO from the transient black hole X-ray binary GX 339-4. Previous phase-resolved spectroscopy analysis of the Type B QPO in GX 339-4 pointed towards a precessing jet-like corona illuminating the accretion disk as the origin of the QPO signal. We suggest that this QPO in MAXI J1535-571 may have the same origin, with the different lag sign depending on the scale height of the emitting region and the observer inclination angle.Comment: Accepted for publication in ApJ Letter

Investigating the Nature of Variable Class I and Flat Spectrum Protostars Using 2-4μ\mum Spectroscopy

In this study I present new K and L$'$-band infrared photometry and 2-4$\mu$m spectra of ten Class I and flat spectrum stars forming within the Taurus dark cloud complex. Nine sources have H$_2$ {\it v}=0-1 S(1) emission, and some show multiple H$_2$ emission features in their K-band spectra. Photospheric absorptions characteristic to low mass stars are detected in five of the targets, and these stars were fit with models to determine spectral type, infrared accretion excess veiling (r$_K$ and r$_{L'}$) and dust temperatures, estimates of visual extinction and characteristics of the 3$\mu$m water-ice absorption. On average, the models found high extinction values, infrared accretion excess emission with blackbody temperatures in the 900-1050K range, and 3$\mu$m absorption profiles best fit by water frozen onto cold grains rather than thermally processed ice. Five techniques were used to estimate the extinction toward the stellar photospheres; most gave vastly different results. Analysis of emission line ratios suggests that the effect of infrared scattered light toward some protostars should not be neglected. For stars that exhibited Br$\gamma$ in emission, accretion luminosities were estimated using relations between L$_{acc}$ and Br$\gamma$ luminosity. The young stars in this sample were preferentially chosen as variables, but they do not have the accretion dominated luminosities necessary to put them in their main stage of mass-building. The characteristics of the 2-4$\mu$m spectra are placed in the context of existing multi-wavelength data, and five of the stars are more consistent with reddened Class IIs or stars in transition between Class I and II, rather than protostars embedded within massive remnant envelopes.Comment: Full resolution version available at: http://www.ess.sunysb.edu/tracy/tbeck_mar07_AJ.pdf. Accepted for Publication in the Astronomical Journal (March 2007

Laboratory and Theoretical Results on Interstellar Molecule Production by Grains in Molecular Clouds

Wetensch. publicatieFaculteit der Wiskunde en Natuurwetenschappe

Screen-detected breast cancers have a lower mitotic activity index

We know that screening for breast cancer leads to detection of smaller tumours with less lymph node metastases. Could it be possible that the decrease in mortality after screening is not only caused by this earlier stage, but also by a different mitotic activity index (MAI) of the tumours that are detected by screening? Is MAI a prognostic factor for recurrence-free survival? A retrospective study was carried out of 387 patients with breast cancer, treated at the University Hospital Nijmegen between January 1992 and September 1997. Ninety patients had screen-detected breast cancer, 297 patients had breast cancers detected outside the screening programme. The MAI, other prognostic factors and recurrence-free survival were determined. In non-screen-detected tumours the MAI is twice as high as in screen-detected tumours, even after correction for age took place. The MAI correlated well with other tumour characteristics. The MAI in itself is a prognostic factor for recurrence-free survival. Favourable outcome in screen detected breast cancer is not entirely caused by detecting cancer in early stages: quantitative features such as the MAI indicate a less malignant character of screen detected breast cancer. The MAI is an independent prognostic factor for recurrence-free survival. © 2000 Cancer Research Campaig

Voluntarily reported prescribing, monitoring and medication transfer errors in intensive care units in The Netherlands

Background Medication errors occur frequently in intensive care units (ICU). Voluntarily reported medication errors form an easily available source of information. Objective This study aimed to characterize prescribing, monitoring and medication transfer errors that were voluntarily reported in the ICU, in order to reveal medication safety issues. Setting This retrospective data analysis study included reports of medication errors from eleven Dutch ICU's from January 2016 to December 2017. Method We used data extractions from the incident reporting systems of the participating ICU's. The reports were transferred into one database and categorized into type of error, cause, medication (groups), and patient harm. Descriptive statistics were used to calculate the proportion of medication errors and the distribution of subcategories. Based on the analysis, ICU medication safety issues were revealed. Main outcome measure The main outcome measure was the proportion of prescribing, monitoring and medication transfer error reports. Results Prescribing errors were reported most frequently (n = 233, 33%), followed by medication transfer errors (n = 85, 12%) and monitoring errors (n = 27, 4%). Other findings were: medication transfer errors frequently caused serious harm, especially the omission of home medication involving the central nervous system and proton pump inhibitors; omissions and dosing errors occurred most frequently; protocol problems caused a quarter of the medication errors; and medications needing blood level monitoring (e.g. tacrolimus, vancomycin, heparin and insulin) were frequently involved. Conclusion This analysis of voluntarily reported prescribing, monitoring and medication transfer errors warrants several improvement measures in these processes, which may help to increase medication safety in the ICU