Extraction Process of Amino Acids with Deep Eutectic Solvents-Based Supported Liquid Membranes

The separation and purification process of amino acids (AAs) accounts for 80% of the total production cost. So the development of new technology for the separation and purification of AAs is very important. In this research, supported liquid membranes (SLMs) based on deep eutectic solvents (DESs) were successfully applied for the extraction of AAs. A series of DESs were designed, synthesized, and screened to obtain suitable ones as the supported phase. Some important factors, such as effect of types of DESs and membranes, pH and concentration of Trp were investigated. Higher extraction efficiency was achieved. ChCl/PTS was found to be the most efficient one. Results show that the initial concentration of Trp in the feed phase is 0.1 mM, and pH = 1.0 in the feed phase and pH = 13.0 in receiving phase is optimal for extraction, under which the extraction efficiency can reach 86.1%. ChCl/PTS/Asp (1/4/1) of SLM has the best stability, the weight loss of SLM is 0.38%. Finally, ¹H NMR shows that the hydrogen bonding interaction between DESs and Trp is probably the main driven force for this specific process. This research would provide a new process for the separation and purification of AAs with SILMs technique

Additional file 2: of Exosome-mediated transfer of lncRNA PART1 induces gefitinib resistance in esophageal squamous cell carcinoma via functioning as a competing endogenous RNA

Table S2. Fold change of deregulated lncRNAs between gefitinib-resistant cells and -parental cells. (DOC 30 kb

Additional file 1: of Exosome-mediated transfer of lncRNA PART1 induces gefitinib resistance in esophageal squamous cell carcinoma via functioning as a competing endogenous RNA

Table S1. Information of the RT-qPCR primer sequences and siRNA sequences. (DOC 47 kb

Additional file 3: of Exosome-mediated transfer of lncRNA PART1 induces gefitinib resistance in esophageal squamous cell carcinoma via functioning as a competing endogenous RNA

Figure S1. Knockdown of STAT1 suppressed expression of PART1. a RT-qPCR verification of the silence of STAT1 after transfection of specific small interfere RNAs. b RT-qPCR analysis of lncRNA PART1 expression after STAT1 was silenced. ***P < 0.001 compared to si-NC group. (DOC 879 kb

Extraction Process of Dibenzothiophene with New Distillable Amine-Based Protic Ionic Liquids

In this study, two kinds of amine-based protic ionic liquids (PILs), namely, 2-[2-(dimethylamino)­ethoxy] ethanol propionate ([DMEE]­[CO₂Et]) and 3-(dimethylamino)-propanenitrile propionate ([DMAPN]­[CO₂Et]), were introduced into the desulfurization process for the first time. Some important parameters, such as stirring speed, ionic liquid (IL) dosage, initial concentration, etc., were investigated. According to the experiments, the sulfur content in the model oil can be effectively removed from 1600 to about 650 ppm by a single extraction cycle. After five cycles, the sulfur content could reach up to 19 ppm and the deep desulfurization was achieved. Most important, the recycling of PILs was realized by vacuumed distillation. The properties and extraction efficiency of PILs have no change after recycling. At the same time, the extraction mechanisms were probed. The results show that the hydrogen bond formed between the sulfur of dibenzothiophene (DBT) and the active hydrogen of PIL accounts for the high desulfurization efficiencies. This novel process would provide a new route for extraction desulfurization of diesel fuels

Decision analytic model schematic.

<p>& Irrespective of mode of feeding patterns, infants accepted NVP promptly and daily for 6 weeks. ART, antiretroviral therapy; ARV, antiretroviral prophylaxis; sdNVP, single dose nevirapine; sdTDF, single dose Tenofovir; FTC,emtricitabine; AZT, Zidovudine; FDC, fixed dose combination,(TDF, FTC/3TC, EFV); 3TC,Lamivudine; EFV, Efavirenz.</p

Structure of decision analytic model.

<p>ART, antiretroviral therapy.</p

Data_Sheet_1_Effect of ambient temperature and other environmental factors on stroke emergency department visits in Beijing: A distributed lag non-linear model.pdf

BackgroundMost studies have focused on the relationship between ambient temperature and stroke mortality, but studies on the relationship between ambient temperature and stroke occurrence are still limited and inconsistent.ObjectiveThis study aimed to analyze the effect of ambient temperature and other environmental factors on emergency stroke visits in Beijing.MethodsOur study utilized stroke visit data from the Beijing Red Cross Emergency Medical Center during 2017–2018, and applied a generalized additive model (GAM) as well as a distributed lag non-linear model (DLNM), respectively, regarding the direct, lagged, and cumulative effects of ambient temperature alone and with correction for other environmental factors on stroke occurrence.ResultsWith a total of 26,984 emergency stroke patients in 2017–2018, both cold and hot effects were observed and weakened after correction for other environmental factors. Compared to the reference temperature, in the multi-factor model, extreme cold (−10°C) reached a maximum relative risk (RR) of 1.20 [95% Confidence Interval (CI): 1.09, 1.32] at lag 14 days, and extreme hot (30°C) had a maximum RR of 1.07 (95% CI: 1.04, 1.11) at lag 6 days. The cumulative effect of extreme cold reached a maximum of 2.02 (95% CI: 1.11, 3.67) at lag 0–14 days, whereas the cumulative effect of extreme hot temperature is greatest at lag 0–10 days, but no statistically significant effect was found. In addition, ischemic stroke patients, the elderly, and males were more susceptible to the effects of cold temperature.ConclusionsThere is a non-linear relationship between ambient temperature and stroke occurrence, with cold temperature having a greater and longer-lasting impact than hot temperature.</p

References and input probabilities for the decision analytic model.

<p>ART, antiretroviral therapy; ARV, antiretroviral prophylaxis; sdNVP, single dose nevirapine; sdTDF, single dose Tenofovir; FTC, emtricitabine; AZT, Zidovudine; FDC, (TDF, FTC/3TC, EFV); 3TC,Lamivudine; EFV, Efavirenz; HAART, highly active antiretroviral therapy.</p

References and input cost estimates for the decision analytic model.

<p>ELISA, enzyme-linked immunosorbent assay; HAART, highly active antiretroviral therapy; ART, antiretroviral prophylaxis; ARV, antiretroviral prophylaxis; sdNVP, single dose nevirapine; sdTDF, single dose Tenofovir; FTC, emtricitabine; AZT, Zidovudine; FDC, (TDF, FTC/3TC, EFV); 3TC,Lamivudine; EFV, Efavirenz.</p