Pittsbird9677

31 Gy(RBE) of proton therapy plans.

The effect of breathing motion on the robustness of proton therapy treatment plans for this patient group is minor and not of clinical significance. U73122 supplier Based on this patient group, a deep-inspiration breath hold seems to be unnecessary to improve robustness for these patients.

The effect of breathing motion on the robustness of proton therapy treatment plans for this patient group is minor and not of clinical significance. Based on this patient group, a deep-inspiration breath hold seems to be unnecessary to improve robustness for these patients.

Risk-scoring systems for surgical aortic valve replacement (AVR) were largely derived from sternotomy cases. We evaluated the accuracy of current risk scores in predicting outcomes after minimally invasive AVR (mini-AVR). Because transcatheter AVR (TAVR) is being considered for use in low-risk patients with aortic stenosis, accurate mini-AVR risk assessment is necessary.

We reviewed 1,018 consecutive isolated mini-AVR cases (2009 to 2015). After excluding patients with Society of Thoracic Surgeons Predicted Risk of Mortality (STS-PROM) scores ≥4, we calculated each patient's European System for Cardiac Operative Risk Evaluation (EuroSCORE) II, TAVR Risk Score (TAVR-RS), and age, creatinine, and ejection fraction score (ACEF). We compared all 4 scores' accuracy in predicting mini-AVR 30-day mortality by computing each score's observed-to-expected mortality ratio (OE). Area under the receiver operating characteristic (ROC) curves tested discrimination, and the Hosmer-Lemeshow goodness-of-fit tested calibration.

Among 941 patients (mean age, 72 ± 12 years), 6 deaths occurred within 30 days (actual mortality rate, 0.6%). All 4 scoring systems overpredicted expected mortality after mini-AVR ACEF (1.4%), EuroSCORE II (1.9%), STS-PROM (2.0%), and TAVR-RS (2.1%). STS-PROM best estimated risk for patients with STS-PROM scores 0 to <1 (0.6 OE), ACEF for patients with STS-PROM scores 2 to <3 (0.6 OE), and TAVR-RS for patients with STS-PROM scores 3 to <4 (0.7 OE). ROC curves showed only fair discrimination and calibration across all risk scores.

In low-risk patients who underwent mini-AVR, current surgical scoring systems overpredicted mortality 2-to-3-fold. Alternative dedicated scoring systems for mini-AVR are needed for more accurate outcomes assessment.

In low-risk patients who underwent mini-AVR, current surgical scoring systems overpredicted mortality 2-to-3-fold. Alternative dedicated scoring systems for mini-AVR are needed for more accurate outcomes assessment.Laccases are a group of oxidases that catalyze the oxidation of a wide range of electron rich substrates like phenolic compounds, lignin and aromatic amines. They are of interest because of their potential to be used in environmental and industrial applications. In this research, potent laccase producer fungi were screened and isolated from olive mill wastewater (OMW). One of the 23 isolated fungi was identified as Galactomyces geotrichum based on 18S rDNA sequence analysis that detected good laccase activity. Produced laccase had a molecular weight of 55 kDa that was confirmed by zymogram analysis. This is the first report about the optimization of laccase Production by G. geotrichum under solid-state fermentation. The optimization was made by the Taguchi design of experiments (DOE) methodology. An orthogonal array (L25) was designed using Minitab 19 software to study four effective process factors in five levels for laccase production. The optimum condition derived was; moisture content (80%), fermentation time (14 day), CuSO4⋅5H2O as the inducer (300 μM), glucose as a co-substrate (5 g/L). Maximum laccase activity of 52.86 (U/g of dry substrate) was obtained using optimum fermentation condition. This study aimed to better understand the laccase producing microorganisms in OMW and take them to OMW treatment that is rich in phenolic compounds.

We tested whether a procedure in a hexapod simulator can cause incorrect assumptions of the bank angle (i.e., the "leans") in airline pilots as well as incorrect interpretations of the attitude indicator (AI).

The effect of the leans on interpretation errors has previously been demonstrated in nonpilots. In-flight, incorrect assumptions can arise due to misleading roll cues (spatial disorientation).

Pilots (

= 18) performed 36 runs, in which they were asked to roll to wings level using only the AI. They received roll cues before the AI was shown, which matched with the AI bank angle direction in most runs, but which were toward the opposite direction in a leans-opposite condition (four runs). In a baseline condition (four runs), they received no roll cues. To test whether pilots responded to the AI, the AI sometimes showed wings level following roll cues in a leans-level condition (four runs).

Overall, pilots made significantly more errors in the leans-opposite (19.4%) compared to the baseline (6.9%) or leans-level condition (0.0%). There was a pronounced learning effect in the leans-opposite condition, as 38.9% of pilots made an error in the first exposure to this condition. Experience (i.e., flight hours) had no significant effects.

The leans procedure was effective in inducing AI misinterpretations and control input errors in pilots.

The procedure can be used in spatial disorientation demonstrations. The results underline the importance of unambiguous displays that should be able to quickly correct incorrect assumptions due to spatial disorientation.

The procedure can be used in spatial disorientation demonstrations. The results underline the importance of unambiguous displays that should be able to quickly correct incorrect assumptions due to spatial disorientation.

To develop a bleeding-pattern prediction model to inform counselling on amount and regularity of bleeding after levonorgestrel-releasing intrauterine system (LNG-IUS) placement.

Fixed-cluster and regression-tree models were developed using bleeding data pooled from two clinical trials of LNG-IUSs. Models were trained and cross-validated on LNG-IUS 12 data, then applied to LNG-IUS 20 and LNG-IUS 8 data. Three clusters were generated for the fixed-cluster model predominantly amenorrhoea; predominantly spotting; and predominantly bleeding. A random-forest model predicted the future-bleeding cluster, then the probability of cycle regularity was calculated. In the regression-tree model, women were assigned by the model to less- or more-bleeding groups.

With LNG-IUS 12 (

 = 1351) in the fixed-cluster model, 70.4% of women were correctly classified. The correct classification rates for LNG-IUS 20 (

 = 216) and LNG-IUS 8 (

 = 1300) were 72.2% and 69.0%. The probability distribution for cycle regularity showed regular and irregular bleeding were best separated with LNG-IUS 12 data, and less well with LNG-IUS 20 and LNG-IUS 8 data.