We follow up on the recently proposed Dynamic Response Surface Methodology (DRSM) [Klebanov and Georgakis Ind. Eng. Chem. Res. 2016, 55(14), 4022] as an effective data-driven approach for modeling time-varying outputs of batch processes with finite time durations. The present new DRSM methodology, DRSM-2, is capable of accurately modeling nonlinear continuous processes over both finite and semi-infinite time horizons as easily and accurately as modeling batch processes, as DRSM-1 did in the initial publication, cited above. The key innovation here is the introduction of an exponential transformation of time, converting the semi-infinite time duration into a finite one. We also propose a systematic model selection procedure to determine the optimal values of the decision parameters affecting the accuracy of the obtained DRSM-2 model. We demonstrate the power of the DRSM-2 approach in two representative processes, a continuous propylene polymerization and a semibatch penicillin fermentation. It is shown that the obtained data-driven models accurately represent the time-varying process outputs in both of the examined, and quite different, case studies.
To explore clinical characteristics which could be applied to predict pathologic complete response (pCR) for patients with locally advanced rectal cancer treated with neoadjuvant chemoradiotherapy (neo-CRT) and total mesorectal excision (TME). 297 patients with locally advanced rectal cancer (cT3-4 or cN+) who were treated with neo-CRT followed by TME were retrospectively reviewed. Clinical characteristics including age, gender, tumor distance from anus, serum CEA, hemoglobin levels before treatment and clinical TN stage were used to investigate the association with pCR after neo-CRT. Seventy-nine (26.6%) patients achieved pCR after neo-CRT. pCR were achieved in 42 (34.4%) patients in cT1-3 stage and 37 (21.1%) in cT4 stage. pCR rate was 36.4% and 16.4% for patients with pre-treatment serum CEA ≤5.33ng/ml and >5.33ng/ml, respectively. Uni- and multi-variate analyses revealed that pre-treatment serum CEA level ≤5.33ng/ml and clinical T stage, (i.e., cT1-3 versus cT4) were highly correlated with pCR (p < 0.05). Clinical T stage and pre-treatment serum CEA level were strongly associated with pCR for patients with locally advanced rectal cancer treated with neo-CRT followed by TME which could be applied as clinical predictors for pCR.
Stevioside, a diterpene glycoside component of Stevia rebaudiana, has been known to exhibit anti-inflammatory properties. To evaluate the effect and the possible mechanism of stevioside in lipopolysaccharide (LPS)-induced acute lung injury, male BALB/c mice were pretreated with stevioside or dexamethasone 1 h before intranasal instillation of LPS. Seven hours later, tumor necrosis factor-α, interleukin-1β, and interleukin-6 in bronchoalveolar lavage fluid (BALF) were measured by using enzyme-linked immunosorbent assay. The number of total cells, neutrophils, and macrophages in the BALF were also determined. The right lung was excised for histological examination and analysis of myeloperoxidase activity and nitrate/nitrite content. Cyclooxygenase 2 (COX-2), inducible NO synthase (iNOS), nuclear factor-kappa B (NF-κB), inhibitory kappa B protein were detected by western blot. The results showed that stevioside markedly attenuated the LPS-induced histological alterations in the lung. Stevioside inhibited the production of pro-inflammatory cytokines and the expression of COX-2 and iNOS induced by LPS. In addition, not only was the wet-to-dry weight ratio of lung tissue significantly decreased, the number of total cells, neutrophils, and macrophages in the BALF were also significantly reduced after treatment with stevioside. Moreover, western blotting showed that stevioside inhibited the phosphorylation of IκB-α and NF-κB caused by LPS. Taken together, our results suggest that anti-inflammatory effect of stevioside against the LPS-induced acute lung injury may be due to its ability of inhibition of the NF-κB signaling pathway. Stevioside may be a promising potential therapeutic reagent for acute lung injury treatment.
We use spatially resolved scanning tunnelling spectroscopy in Na(Fe1−xCox)As to investigate the impurity effect induced by Co dopants. The Co impurities are successfully identified and the spatial distribution of local density of state at different energies around these impurities are investigated. It is found that the spectrum shows negligible spatial variation at different positions near the Co impurity, although there is a continuum of the in-gap states which lift the zero-bias conductance to a finite value. Our results put constraints on the S± and S++ models and sharpen the debate on the role of scattering potentials induced by the Co dopants.
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