Evaluation of homologous recombination deficiency (HRD) score and immuno-tumor microenvironment (iTME) as biomarkers of soft tissue sarcoma (STS) survival and response to immune checkpoint inhibitor therapy.

11568 Background: Soft tissue sarcoma (STS) are highly heterogenous in both histology and underlying genetic alterations, resulting in heterogenous outcomes of standard therapy. With recent stride of immunotherapies in oncology it is crucial to find the optimal match of the new therapies to disease subtypes. HRDScore and iTME parameters are two top candidate biomarkers to predict clinical outcomes in complex diseases such as STS. Methods: We prospectively profiled 102 Chinese STS patients who had received more than 1 line of prior treatment, mainly chemo-drugs. We then classified the patients according to their HRDScore (calculated from WES data using the Richardson method, ref. Telli M.L. et al. Clin. Cancer Res. 2016) and iTME parameters (calculated from RNAseq data using CIBERSORT method). Lastly, we tested the correlation of HRDScore or iTME with patient survival and clinic outcomes of anti-PD-1/L1 based combination therapy. Results: The histological subtypes of the patients included 32 LMS, 44 LPS, and 26 others (such as UPS, clear cell, myxofibrosarcoma, uterus LMS etc.). The top mutation genes (frequency > 5%) included TP53 29%, KMT2C 16%, NOTCH2 9%, ATRX 8%, NF1 8%, RB1 8% and PTEN 6%. The patients could be classified to HRD-high or HRD-low (HRDScore > or < = 42). Alternatively, unsupervised clustering of iTME revealed three patient subgroups (named iTME-I, -II, and -III). While all the three groups are characterized by a generally suppressed immune environment, iTME-I have high proportion of M0 macrophages and median M2 macrophages; iTME-II have high proportion of M2 macrophages but low M0 cells; and iTME-type III are low in both M0 and M2 cells. No significant M1 cells present in all the three iTME groups. Patient survivals were correlated with the iTME types but not HRDScore in Kaplan-Meyer analysis. The trend of survival time was iTME-III > iTME-II > iTME-I, with an HR = 0.156 for iTME-III over iTME-I (p = 0.008, log-rank test). Treatment response of anti-PD-1/L1 based combination therapies also showed a positive correlation to iTME-III, but not HRDScore although the small sample size prevented a definitive conclusion. Clinical evaluation of the 22 patients who received anti-PD-1/L1 therapy showed 1 PD (20%) and 4 SD/PR (80%) in iTME-III, 4 PD (40%) and 6 SD/PR (60%) in iTME-II, and 1 PD (33%) and 2 SD (67%) in iTME-I. Conclusions: iTME is a better biomarker than HRDScore in STS for survival and treatment outcomes. Differential Infiltration of M0 and M2 macrophages can distinguish patients with different survival and response to anti-PD-1/L1 combination therapy. The iTME subtypes may be used for treatment screen of combination immunotherapy but larger and randomized clinical studies are required to validate the discovery.

Ceilometers as planetary boundary layer height detectors and a corrective tool for COSMO and IFS models

The significance of planetary boundary layer (PBL) height detection is apparent in various fields, especially in air pollution dispersion assessments. Numerical weather models produce a high spatial and temporal resolution of PBL heights; however, their performance requires validation. This necessity is addressed here by an array of eight ceilometers; a radiosonde; and two models – the Integrated Forecast System (IFS) global model and COnsortium for Small-scale MOdeling (COSMO) regional model. The ceilometers were analyzed with the wavelet covariance transform method, and the radiosonde and models with the parcel method and the bulk Richardson method. Good agreement for PBL height was found between the ceilometer and the adjacent Bet Dagan radiosonde (33 m a.s.l.) at 11:00 UTC launching time (N=91 d, ME =4 m, RMSE =143 m, R=0.83). The models' estimations were then compared to the ceilometers' results in an additional five diverse regions where only ceilometers operate. A correction tool was established based on the altitude (h) and distance from shoreline (d) of eight ceilometer sites in various climate regions, from the shoreline of Tel Aviv (h=5 m a.s.l., d=0.05 km) to eastern elevated Jerusalem (h=830 m a.s.l., d=53 km) and southern arid Hazerim (h=200 m a.s.l., d=44 km). The tool examined the COSMO PBL height approximations based on the parcel method. Results from a 14 August 2015 case study, between 09:00 and 14:00 UTC, showed the tool decreased the PBL height at the shoreline and in the inner strip of Israel by ∼100 m and increased the elevated sites of Jerusalem and Hazerim up to ∼400 m, and ∼600 m, respectively. Cross-validation revealed good results without Bet Dagan. However, without measurements from Jerusalem, the tool underestimated Jerusalem's PBL height by up to ∼600 m.

Ceilometers as planetary boundary layer detectors and a corrective tool for ECMWF and COSMO NWP models

The growing importance of the planetary boundary layer (PBL) height detection is apparent in various fields, from air pollution analysis to weather prediction. In recent years micro-lidars such as ceilometers have been recognized as an efficient tool for such measurements. Here, the daytime summer PBL height is measured by eight ceilometers throughout Israel, along with with radiosonde profiles, the global IFS model, and the regional COSMO model. The analysis focused on three PBL height evaluation methods: the bulk Richardson method, the parcel method, and the wavelet covariance transform method. The best agreement between the PBL heights derived from a single radiosonde site on 33 summer days was found by the adjacent ceilometer (mean error = 12 m, RMSE = 97 m). Spatial analysis of the PBL heights derived from the models on 13 days in reference to five ceilometer measurement sites revealed COSMO evaluations by the bulk Richardson method (COSMOR) produced the best results for both flat (mean error = 19 m, RMSE = 203 m) and elevated terrain (mean error = −6 m, RMSE = 251 m). To improve COSMOR results, a regression tool was assimilated based on the PBL height difference between COSMOR and ceilometers. The regression is based on the altitude and distance from the shoreline for eight ceilometer sites.

Iterative Methods for Solving a System of Linear Equations in a Bipolar Fuzzy Environment

We develop the solution procedures to solve the bipolar fuzzy linear system of equations (BFLSEs) with some iterative methods namely Richardson method, extrapolated Richardson (ER) method, Jacobi method, Jacobi over-relaxation (JOR) method, Gauss–Seidel (GS) method, extrapolated Gauss-Seidel (EGS) method and successive over-relaxation (SOR) method. Moreover, we discuss the properties of convergence of these iterative methods. By showing the validity of these methods, an example having exact solution is described. The numerical computation shows that the SOR method with ω = 1 . 25 is more accurate as compared to the other iterative methods.

Summertime Urban Mixing Layer Height over Sofia, Bulgaria

Mixing layer height (MLH) is a crucial parameter for air quality modelling that is still not routinely measured. Common methods for MLH determination use atmospheric profiles recorded by radiosonde but this process suffers from coarse temporal resolution since the balloon is usually launched only twice a day. Recently, cheap ceilometers are gaining popularity in the retrieval of MLH diurnal evolution based on aerosol profiles. This study presents a comparison between proprietary (Jenoptik) and freely available (STRAT) algorithms to retrieve MLH diurnal cycle over an urban area. The comparison was conducted in the summer season when MLH is above the full overlapping height of the ceilometer in order to minimize negative impact of the biaxial LiDAR’s drawback. Moreover, fogs or very low clouds which can deteriorate the ceilometer retrieval accuracy are very unlikely to be present in summer. The MLHs determined from the ceilometer were verified against those measured from the radiosonde, which were estimated using the parcel, lapse rate, and Richardson methods (the Richardson method was used as a reference in this study). We found that the STRAT and Jenoptik methods gave lower MLH values than radiosonde with an underestimation of about 150 m and 650 m, respectively. Additionally, STRAT showed some potential in tracking the MLH diurnal evolution, especially during the day. A daily MLH maximum of about 2000 m was found in the late afternoon (18–19 LT). The Jenoptik algorithm showed comparable results to the STRAT algorithm during the night (although both methods sometimes misleadingly reported residual or advected layers as the mixing layer (ML)). During the morning transition the Jenoptik algorithm outperformed STRAT, which suffers from abrupt changes in MLH due to integrated layer attribution. However, daytime performance of Jenoptik was worse, especially in the afternoon when the algorithm often cannot estimate any MLH (in the period 13–16 LT the method reports MLHs in only 15–30% of all cases). This makes day-to-day tracing of MLH diurnal evolution virtually impracticable. This problem is possibly due to its early version (JO-CloVis 8.80, 2009) and issues with real-time processing of a single profile combined with the low signal-to-noise ratio of the ceilometer. Both LiDAR-based algorithms have trouble in the evening transition since they rely on aerosol signature which is more affected by the mixing processes in the past hours than the current turbulent mixing.