The Intersection of Grand Strategies in Turkey-Russia Relations: Reflections of Smart Alignment and Flexible Competition in the International Arena

Evaluating Turkey-Russia relations is a dilemma, as the two countries fluctuate between perceptions of mutual historical hostility and strategic partnership. An alternative perspective is needed to get beyond the impasse of this dilemma. The main purpose of this study is to explain the common aspects of the grand strategies of Turkey and Russia within the framework of the pattern and to evaluate the policies of both countries in Syria, Libya, and the South Caucasus where the interests of both intersect and occasional conflict. We propose that Turkey-Russia relations can best be defined around the concepts of ‘smart alignment’ and ‘flexible competition.’ Their bilateral relations cannot be considered black or white in the abstract, but rather take place in the ‘gray zone.’ Alternative scenarios for the future of bilateral relations are presented in the conclusion.

Changes in stroke volume induced by lung recruitment maneuver can predict fluid responsiveness during intraoperative lung-protective ventilation in prone position

Background The present study aimed to evaluate the reliability of hemodynamic changes induced by lung recruitment maneuver (LRM) in predicting stroke volume (SV) increase after fluid loading (FL) in prone position. Methods Thirty patients undergoing spine surgery in prone position were enrolled. Lung-protective ventilation (tidal volume, 6–7 mL/kg; positive end-expiratory pressure, 5 cmH2O) was provided to all patients. LRM (30 cmH2O for 30 s) was performed. Hemodynamic variables including mean arterial pressure (MAP), heart rate, SV, SV variation (SVV), and pulse pressure variation (PPV) were simultaneously recorded before, during, and at 5 min after LRM and after FL (250 mL in 10 min). Receiver operating characteristic curves were generated to evaluate the predictability of SVV, PPV, and SV decrease by LRM (ΔSVLRM) for SV responders (SV increase after FL > 10%). The gray zone approach was applied for ΔSVLRM. Results Areas under the curve (AUCs) for ΔSVLRM, SVV, and PPV to predict SV responders were 0.778 (95% confidence interval: 0.590–0.909), 0.563 (0.371–0.743), and 0.502 (0.315–0.689), respectively. The optimal threshold for ΔSVLRM was 30% (sensitivity, 92.3%; specificity, 70.6%). With the gray zone approach, the inconclusive values ranged 25 to 75% for ΔSVLRM (including 50% of enrolled patients). Conclusion In prone position, LRM-induced SV decrease predicted SV increase after FL with higher reliability than traditional dynamic indices. On the other hand, considering the relatively large gray zone in this study, future research is needed to further improve the clinical significance. Trial registration UMIN Clinical Trial Registry UMIN000027966. Registered 28th June 2017.

Rotational Activity around an Obstacle in 2D Cardiac Tissue in Presence of Cellular Heterogeneity

Waves of electrical excitation rotating around an obstacle is one of the important mechanisms of dangerous cardiac arrhythmias occurring in the heart damaged by a post-infarction scar. Such a scar is also surrounded by the region of heterogeneity called a gray zone. In this paper, we perform the first comprehensive numerical study of various regimes of wave rotation around an obstacle surrounded by a gray zone. We use the TP06 cellular ionic model for human cardiomyocytes and study how the period and the pattern of wave rotation depend on the radius of a circular obstacle and the width of a circular gray zone. Our main conclusions are the following. The wave rotation regimes can be subdivided into three main classes: (1) functional rotation, (2) scar rotation and the newly found (3) gray zone rotation regimes. In the scar rotation regime, the wave rotates around the obstacle, while in the gray zone regime, the wave rotates around the gray zone. As a result, the period of rotation is determined by the perimeter of the scar, or gray zone perimeter correspondingly. The transition from the scar to the gray rotation regimes can be determined from the minimal period principle, formulated in this paper. We have also observed additional regimes associated with two types of dynamical instabilities which may affect or not affect the period of rotation. The results of this study can help to identify the factors determining the period of arrhythmias in post-infarction patients.

On the application and grid-size sensitivity of the urban dispersion model CAIRDIO for the simulation of a real city and realistic meteorology

There is a gap between the need for city-wide air-quality simulations considering the intra-urban variability and mircoscale dispersion features and the computational capacities that conventional urban microscale models require. This gap can be bridged by targeting model applications on the gray zone situated between the mesoscale and large-eddy scale. The urban dispersion model CAIRDIO is a new contribution to the class of computational-fluid dynamics models operating in this scale range. It uses a diffuse-obstacle boundary method to represent buildings as physical obstacles at gray-zone resolutions in the order of tens of meters. The main objective of this approach is to find an acceptable compromise between computationally inexpensive grid sizes for spatially comprehensive applications and the required accuracy in the description of building and boundary-layer effects. For this purpose, CAIRDIO is applied in dispersion simulation of black carbon and particulate matter for an entire mid-size city using an uniform horizontal resolution of 40 m in this paper. For evaluation, the simulation results are compared with measurements from 5 operational air monitoring stations, which are representative for the urban background and high-traffic roads, respectively. Moreover, the comparison includes the mesoscale host simulation, which provides the boundary conditions. The temporal variability of the concentration measurements at the background sites was largely influenced only by the characteristics of the mixing layer. As a consequence, the model results were not significantly dependent on spatial resolution, so that the mesoscale simulation also performed reasonably well. At the traffic sites, however, concentrations were in addition markedly influenced by the proximity to road-traffic sources and the surrounding building environment. Here, the mesoscale simulation indiscriminately reproduced almost the same urban-background profiles, which resulted in a large positive model bias. On the other hand, the CAIRDIO simulation was able to respond to the significantly amplified diurnal variability with its pronounced rush-hour peaks. This resulted in a consistent improvement of the model deviation to mea- surements compared to the mesoscale simulation. Nevertheless, discrepancies to measurements remain in the 40 m-CAIRDIO simulation, e.g., an underestimation of peak concentrations at two traffic sites inside narrow street canyons. To further research resolution sensitivity, the horizontal grid spacing of locally nested CAIRDIO domains is refined down to 5 m. While for the street canyons the representation of peak concentrations can be improved using horizontal grid spacings of up to 10 m, no further improvements beyond this resolution can be observed. This suggests that the too low peak concentrations with the default grid spacing of 40 m result from an inadequate representation of the traffic emissions inside narrow street canyons. If the total gain in accuracy due to the grid refinements is put in relation to the remaining model error, the improvements are only modest. In conclusion, the proposed gray-scale modeling is a promising downscaling approach for urban air-quality applications. Nevertheless, the results also show that aspects other than the actual resolution of flow patterns and numerical effects can determine the simulations at the urban microscale.

Alpha-L-Fucosidase Has Diagnostic Value in Prostate Cancer With “Gray-Zone PSA” and Inhibits Cancer Progression via Regulating Glycosylation

BackgroundThis study aimed to explore the diagnostic value of alpha-l-fucosidase (AFU) in prostate cancer (PCa) patients with “gray-zone PSA” and to investigate the correlation between AFU expression and clinicopathological characteristics of PCa patients.MethodsThe level of AFU and other necessary clinicopathological variables of patients were retrieved from electronic medical records. The transcriptome profiling and clinical information of PCa patients were obtained from The Cancer Genome Atlas (TCGA) database. The protein level of AFU in tissue was assessed by immunohistochemistry (IHC). All the data were processed by appropriate analysis methods. The p-value of <0.05 was considered statistically significant.ResultsAFU showed ideal diagnostic value for PCa with prostate-specific antigen (PSA) levels ranging from 4 to 10 ng/ml, and its optimal cutoffs were 19.5 U/L. Beyond this, low AFU expression was associated with high pathological grade, T stage and N stage, more postoperative residual tumors, and poor primary therapy outcome, as well as shorter progression-free interval. The Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis illustrated that FUCA1/FUCA2 exerted tumor-suppressive function by regulating the glycosylation.ConclusionsAFU (<19.5 U/L) could effectively distinguish the PCa from the patients with “gray-zone PSA”, and low expression of AFU was an independent unfavorable predictor for the clinicopathological characteristics of PCa patients.

Two Novel Ceramide-Like Molecules and miR-5100 Levels as Biomarkers Improve Prediction of Prostate Cancer in Gray-Zone PSA

Reliable liquid biopsy-based tools able to accurately discriminate prostate cancer (PCa) from benign prostatic hyperplasia (BPH), when PSA is within the “gray zone” (PSA 4–10), are still urgent. We analyzed plasma samples from a cohort of 102 consecutively recruited patients with PSA levels between 4 and 16 ng/ml, using the SANIST-Cloud Ion Mobility Metabolomic Mass Spectrometry platform, combined with the analysis of a panel of circulating microRNAs (miR). By coupling CIMS ion mobility technology with SANIST, we were able to reveal three new structures among the most differentially expressed metabolites in PCa vs. BPH. In particular, two were classified as polyunsaturated ceramide ester-like and one as polysaturated glycerol ester-like. Penalized logistic regression was applied to build a model to predict PCa, using six circulating miR, seven circulating metabolites, and demographic/clinical variables, as covariates. Four circulating metabolites, miR-5100, and age were selected by the model, and the corresponding prediction score gave an AUC of 0.76 (C.I. = 0.66–0.85). At a specified cut-off, no high-risk tumor was misclassified, and 22 out of 53 BPH were correctly identified, reducing by 40% the false positives of PSA. We developed and applied a novel, minimally invasive, liquid biopsy-based powerful tool to characterize novel metabolites and identified new potential non-invasive biomarkers to better predict PCa, when PSA is uninformative as a tool for precision medicine in genitourinary cancers.