Radiotherapy treatment strategies should be personalized based on the radiosensitivity of individual tumors. Clonogenic assays are the gold standard method for in vitro assessment of radiosensitivity. Reproducibility is the critical factor for scientific rigor; however, this is reduced by insufficient reporting of methodologies. In reality, the reporting standards of methodologies pertaining to clonogenic assays remain unclear. To address this, we performed a literature search and qualitative analysis of the reporting of methodologies pertaining to clonogenic assays. A comprehensive literature review identified 1672 papers that report the radiosensitivity of human cancer cells based on clonogenic assays. From the identified papers, important experimental parameters (i.e. number of biological replicates, technical replicates, radiation source and dose rate) were recorded and analyzed. We found that, among the studies, (i) 30.5% did not report biological or technical replicates; (ii) 47.0% did not use biological or technical replicates; (iii) 3.8% did not report the radiation source; and (iv) 32.3% did not report the dose rate. These data suggest that reporting of methodologies pertaining to clonogenic assays in a considerable number of previously published studies is insufficient, thereby threatening reproducibility. find more This highlights the need to raise awareness of standardization of the methodologies used to conduct clonogenic assays.Multi-omics data, that is, datasets containing different types of high-dimensional molecular variables, are increasingly often generated for the investigation of various diseases. Nevertheless, questions remain regarding the usefulness of multi-omics data for the prediction of disease outcomes such as survival time. It is also unclear which methods are most appropriate to derive such prediction models. We aim to give some answers to these questions through a large-scale benchmark study using real data. Different prediction methods from machine learning and statistics were applied on 18 multi-omics cancer datasets (35 to 1000 observations, up to 100 000 variables) from the database 'The Cancer Genome Atlas' (TCGA). The considered outcome was the (censored) survival time. Eleven methods based on boosting, penalized regression and random forest were compared, comprising both methods that do and that do not take the group structure of the omics variables into account. The Kaplan-Meier estimate and a Cox model using only clinical variables were used as reference methods. The methods were compared using several repetitions of 5-fold cross-validation. Uno's C-index and the integrated Brier score served as performance metrics. The results indicate that methods taking into account the multi-omics structure have a slightly better prediction performance. Taking this structure into account can protect the predictive information in low-dimensional groups-especially clinical variables-from not being exploited during prediction. Moreover, only the block forest method outperformed the Cox model on average, and only slightly. This indicates, as a by-product of our study, that in the considered TCGA studies the utility of multi-omics data for prediction purposes was limited. Contactmoritz.herrmann@stat.uni-muenchen.de, +49 89 2180 3198 Supplementary information Supplementary data are available at Briefings in Bioinformatics online. All analyses are reproducible using R code freely available on Github.To design a new breast vacuum bag to reduce global and local setup errors in post-mastectomy radiation therapy (PMRT). A total of 24 PMRT patients were immobilized with an old vacuum bag and 26 PMRT patients were immobilized with a new vacuum bag. The registration results were analysed using four regions of interest (ROI) the global ROI [including the whole region of the planning target volume (PTV), GROI], the supraclavicular area (SROI), the ipsilateral chest wall region (CROI) and the ipsilateral arm region (AROI). The global and local setup errors of the two groups were compared. The global setup errors of the new vacuum group were significantly smaller than those in the old vacuum group with the exception of yaw axes (P less then 0.05). The systematic error (Σ) and random error (σ) ranged from 1.21 to 2.13 mm. In the new vacuum group, the local setup errors in the medial-lateral (ML) direction and roll axes for CROI (the Σ and σ ranged from 0.65 to 1.35 mm), and the local setup errors in ML and superior-inferior (SI) directions for SROI were significantly smaller than those in the old vacuum group. The total required PTV margins for the chest wall in ML, SI, and anterior-posterior (AP) were 4.40, 3.12 and 3.77 mm respectively. The new vacuum bag can significantly reduce the global setup errors and local setup errors in PMRT. The respiratory motion of the chest wall was negligible, and the 5 mm PTV margin could cover the local setup errors in PMRT using the new vacuum bag with cone beam CT (CBCT) correction.Drug repositioning has been an important ally in the search for new antifungal drugs. Statins are drugs that act to prevent sterol synthesis in both humans and fungi and for this reason they are promissory candidates to be repositioned to treat mycoses. In this study we evaluated the antifungal activity of atorvastatin by in vitro tests to determine the minimum inhibitory concentration against azole resistant Candida albicans and its mechanisms of action. Moreover, the efficacy of both atorvastatin-loaded oral and vaginal emulgels (0.75%, 1.5% and 3% w/w) was evaluated by means of in vivo experimental models of oral and vulvovaginal candidiasis, respectively. The results showed that atorvastatin minimal inhibitory concentration against C. albicans was 31.25 μg/ml. In oral candidiasis experiments, the group treated with oral emulgel containing 3.0% atorvastatin showcased total reduction in fungal load after nine days of treatment. Intravaginal delivery atorvastatin emulgel showed considerable effectiveness at ida albicans.Rapid and simple methods for the determination of Jiahuangxianjunzuo (JHXJZ) in paddy water, brown rice, soil and rice straw was developed and validated. This method involved the use of ultrahigh-performance liquid chromatography equipped with photodiode array detector. The most important factor was chromatographic conditions, as identified through an orthogonal experimental design. This method showed good recoveries and precisions, thereby indicating its suitability for monitoring of JHXJZ residues in paddy water, brown rice, soil and rice straw. Furthermore, hydrolysis experiment was conducted in the laboratory under pH = 7 buffer solutions, and its degradation product was identified as 2-(4-fluorophenyl)-5-methoxy-1,3,4-oxadiazole by high-resolution mass spectrometry. JHXJZ has a major degradation pathway in the water which the OH- nucleophilic attack the C5 of 1,3,4-oxadiazole ring. Then it leaves mesyl to form intermediate 5-(4-fluorophenyl)-1,3,4-oxadiazol-2-ol and the intermediate combined with methanol formed the degradation product 2-(4-fluorophenyl)-5-methoxy-1,3,4-oxadiazole by the loss of one H2O.