We extend the scaled-and-shifted Kiefer-Wolfowitz (SSKW) algorithm developed by Broadie, Cicek, and Zeevi (2009) to multiple dimensions. The salient feature of this algorithm is that it makes adjustments of the tuning parameters that adapt to the underlying problem characteristics. We compare the performance of this algorithm to the traditional Kiefer-Wolfowitz (KW) one and observe significant improvement in the finite-time performance on some stylized test functions and a multidimensional newsvendor problem.

Introduction The objective of the present research was to evaluate the possible association between the N-terminal pro-brain type natriuretic peptide (NT-proBNP) levels and in-hospital mortality in coronavirus disease 2019 (COVID-19) pneumonia patients who did not have pre-existing heart failure (HF). Methods A total of 137 consecutive patients without pre-existing HF and hospitalized due to COVID-19 pneumonia were enrolled into the current research. The main outcome of the research was the in-hospital death. The independent parameters linked with the in-hospital death were determined by multivariable analysis. Results A total of 26 deaths with an in-hospital mortality rate of 18.9% was noted. Those who died were older with an increased frequency of co-morbidities such as hypertension, chronic kidney disease, coronary artery disease, stroke and dementia. They had also increased white blood cell (WBC) counts and had elevated glucose, creatinine, troponin I, and NT-pro-BNP levels but had decreased levels of hemoglobin. By multivariable analysis; age, NT-pro-BNP, WBC, troponin I, and creatinine levels were independently linked with the in-hospital mortality. After ROC evaluation, the ideal value of the NT-pro-BNP to predict the in-hospital mortality was found as 260 ng/L reflecting a sensitivity of 82% and a specificity of 93% (AUC:0.86; 95% CI: 0.76–0.97). Conclusion The current research clearly shows that the NT-proBNP levels are independently linked with the in-hospital mortality rates in subjects with COVID-19 pneumonia and without HF. Thus, we believe that this biomarker can be used as a valuable prognostic parameter in such cases. FUNDunding Acknowledgement Type of funding sources: None. Figure 1

In response to different stimuli many transcription factors (TFs) display different activation dynamics that trigger the expression of specific sets of target genes, suggesting that promoters have a way to decode them. Combining optogenetics, deep learning-based image analysis and mathematical modeling, we find that decoding of TF dynamics occurs only when the coupling between TF binding and transcription pre-initiation complex formation is inefficient and that the ability of a promoter to decode TF dynamics gets amplified by inefficient translation initiation. Furthermore, we propose a theoretical mechanism based on phase separation that would allow a promoter to be activated better by pulsatile than sustained TF signals. These results provide an understanding on how TF dynamics are decoded in mammalian cells, which is important to develop optimal strategies to counteract disease conditions, and suggest ways to achieve multiplexing in synthetic pathways.

Despite the benefi ts of Coronary Artery Bypass Graft surgery, 15% to 25% of patients develop graft closure within one year following the procedure. The patency rate of grafts mainly predicts both the short-and long-term benefi t from surgery. Here we report a patient diagnosed as acute coronary syndrome fi ve months after surgery with signifi cant stenosis of multiple saphenous vein grafts.