Pretreatment Parameters Research Articles

Statistical Optimization and Bulk Scale Validation of the Effects of Cationic Pre-treatment of Cotton Fabric for Digital Printing with Reactive Dyes

ABSTRACT Digital printing has the potential of enabling cleaner printing or even dyeing of cotton fabrics. However, whilst effluent-free digital printing and dyeing of synthetic textile fabrics have seen some success, the same remain elusive for cotton fabrics. The study reported in this paper aimed to optimize the process parameters of cationic pre-treatment with a view to creating a cleaner cotton fabric digital printing process that could be sustainably implemented at bulk-scale production. Thus, process variables were screened using the one-factor-at-a-time approach to select optimum experimental regions. A Box–Behnken design was used to investigate the combined effect of selected factors namely amount of thickener (150–200 g/L), urea (75–125 g/L) and alkali (10–20 g/L) on the color strength, dye fixation and ink penetration of cationized and digital-printed cotton fabrics. The significant models showed excellent fitting of the data. The optimum levels of the factors, namely, amount of thickener, urea and alkali were found 200 g/L, 125 g/L and 10 g/L, respectively. The bulk-scale experiments carried out at optimum levels have shown that an average of ca. 52% of reactive ink, 37.5% of urea and 50% of alkali can be saved by digital printing of cationized cotton along with generation of nearly colorless effluent.

Diffusion-weighted MRI for predicting pathologic response to neoadjuvant chemotherapy in breast cancer: evaluation with mono-, bi-, and stretched-exponential models

BackgroundTo investigate the performance of diffusion-weighted (DW) MRI with mono-, bi- and stretched-exponential models in predicting pathologic complete response (pCR) to neoadjuvant chemotherapy (NACT) for breast cancer, and further outline a predictive model of pCR combining DW MRI parameters, contrast-enhanced (CE) MRI findings, and/or clinical-pathologic variables.MethodsIn this retrospective study, 144 women who underwent NACT and subsequently received surgery for invasive breast cancer were included. Breast MRI including multi-b-value DW imaging was performed before (pre-treatment), after two cycles (mid-treatment), and after all four cycles (post-treatment) of NACT. Quantitative DW imaging parameters were computed according to the mono-exponential (apparent diffusion coefficient [ADC]), bi-exponential (pseudodiffusion coefficient and perfusion fraction), and stretched-exponential (distributed diffusion coefficient and intravoxel heterogeneity index) models. Tumor size and relative enhancement ratio of the tumor were measured on contrast-enhanced MRI at each time point. Pre-treatment parameters and changes in parameters at mid- and post-treatment relative to baseline were compared between pCR and non-pCR groups. Receiver operating characteristic analysis and multivariate regression analysis were performed.ResultsOf the 144 patients, 54 (37.5%) achieved pCR after NACT. Overall, among all DW and CE MRI measures, flow-insensitive ADC change (ΔADC200,1000) at mid-treatment showed the highest diagnostic performance for predicting pCR, with an area under the receiver operating characteristic curve (AUC) of 0.831 (95% confidence interval [CI]: 0.747, 0.915; P < 0.001). The model combining pre-treatment estrogen receptor and human epidermal growth factor receptor 2 statuses and mid-treatment ΔADC200,1000 improved the AUC to 0.905 (95% CI: 0.843, 0.966; P < 0.001).ConclusionMono-exponential flow-insensitive ADC change at mid-treatment was a predictor of pCR after NACT in breast cancer.

Prognostic Factors in Primary Biliary Cholangitis: A Retrospective Study of Joint Slovak and Croatian Cohort of 249 Patients.

Objective: To identify pretreatment laboratory parameters associated with treatment response and to describe the relationship between treatment response and liver decompensation in patients with primary biliary cholangitis treated with ursodeoxycholic acid. Methods: We defined treatment response as both ALP ≤ 1.67 × ULN and total bilirubin ≤ 2 × ULN. Multiple logistic regression analyses were performed to adjust for confounding effects of sociodemographic variables. Results: Pretreatment total bilirubin ((TB); OR = 0.3388, 95%CI = 0.1671–0.6077), ALT (OR = 0.5306, 95%CI = 0.3830–0.7080), AST (OR = 0.4065, 95%CI = 0.2690–0.5834), ALP (OR = 0.3440, 95%CI = 0.2356–0.4723), total cholesterol ((TC); OR = 0.7730, 95%CI = 0.6242–0.9271), APRI (OR = 0.3375, 95%CI = 0.1833–0.5774), as well as pretreatment albumin (OR = 1.1612, 95%CI = 1.0706–1.2688) and ALT/ALP (OR = 2.4596, 95%CI = 1.2095–5.5472) were associated with treatment response after six months of treatment. Pretreatment TB (OR = 0.2777, 95%CI = 0.1288–0.5228), ALT (OR = 0.5968, 95%CI = 0.4354–0.7963), AST (OR = 0.4161, 95%CI = 0.2736–0.6076), ALP (OR = 0.4676, 95%CI = 0.3487–0.6048), APRI (OR = 0.2838, 95%CI = 0.1433–0.5141), as well as pretreatment albumin (OR = 1.2359, 95%CI = 1.1257–1.3714) and platelet count (OR = 1.0056, 95%CI = 1.0011–1.0103) were associated with treatment response after 12 months of treatment. Treatment response after 6 months of UDCA therapy is significantly associated with treatment response after 12 months of UDCA therapy (OR = 25.2976, 95% CI = 10.5881–68.4917). Treatment responses after 6 and 12 months of UDCA therapy decrease the risk of an episode of liver decompensation in PBC patients (OR = 12.1156, 95%CI = 3.7192–54.4826 and OR = 21.6000, 95%CI = 6.6319–97.3840, respectively). Conclusions: There are several pretreatment laboratory parameters associated with treatment response in patients with primary biliary cholangitis. Treatment response after six months is significantly associated with treatment response after 12 months of ursodeoxycholic acid (UDCA) therapy. Treatment responses after 6 and 12 months of UDCA decrease the risk of an episode of liver decompensation.

A Nomogram Predicting Progression Free Survival in Patients with Gastrointestinal Stromal Tumor Receiving Sunitinib: Incorporating Pre-Treatment and Post-Treatment Parameters.

Simple SummarySunitinib has been approved as the second-line targeted treatment for gastrointestinal stromal tumor (GIST) after imatinib failure. It is thus necessary to effectively assess prognosis after sunitinib use. However, the current assessment remains insufficient for the contemporary period. We examined prognostic factors influencing progression-free survival. Furthermore, we constructed a prognostic nomogram model using these significant pre-treatment and post-treatment variables.The present study aimed to construct a prognostic nomogram incorporating pre-treatment and post-treatment factors to predict progression-free survival (PFS) after use of sunitinib in patients with metastatic gastrointestinal stromal tumors (GISTs) following imatinib intolerance or failure. From 2007 to 2018, 109 metastatic GIST patients receiving sunitinib at Chang Gung Memorial Hospital, Taiwan, were enrolled. A prognostic nomogram to predict PFS was developed. Sixty-three male and forty-six female metastatic GIST patients, with a median age of 61 years (range: 15–91 years), received sunitinib. The median PFS for 109 patients is 9.93 months. For pre-treatment factors, male gender, body mass index more than 18.5 kg/m2, no sarcopenia status, higher lymphocyte count, lower platelet/lymphocyte ratio, good performance status, higher sunitinib dose, and non-liver metastasis were significantly associated with favorable PFS. For post-treatment factors, adverse events with hypertension, hand–foot skin reaction, and diarrhea were significantly associated with favorable PFS. However, only eight clinicopathological independent factors for PFS prediction were selected for prognostic nomogram establishment. The calibration curve for probability of PFS revealed good agreement between the nomogram prediction and actual observation. High risk patients will experience the lowest PFS. A prognostic nomogram integrating eight clinicopathological factors was constructed to assist prognostic prediction for individual patients with advanced GIST after sunitinib use.

Physical pretreatment of food waste for reducing hydrogen-consuming bacteria

Food waste is a complex organic substrate that is also potentially hosting a variety of microbial species. In Malaysia, the large amount of food waste that is available can cause health and environmental issues due to inadequate management that has created problems such as greenhouse gas emission and release of wastewater. The utilization of food waste for value-added products is an attractive solution to reduce the accumulation of food waste, however, demands a pretreatment step to prepare the food waste for a specific production process. One interesting application of food waste is for the production of biohydrogen, which requires food waste to be free from hydrogen-consuming bacteria (HCB). This study aims to investigate the effect of physical pretreatment on food waste and suggest the best pretreatment parameters. Food waste samples were pretreated with heat at 70 °C, 80 °C and 90 °C for 15 and 30 minutes and UV radiation for 10, 15 and 30 minutes before being cultured in aerobic condition. The reduction in aerobic bacteria was measured. Heat pretreatment at 70 °C for 15 and 30 minutes could be considered as the best pretreatment compared to the other since it recorded the highest reducing sugar concentration. Heat pretreatment at 70 °C for 15 and 30 minutes and UV radiation pretreatment for 15 minutes had a bactericidal effect and able to remove HCB. There is a high possibility that bacteria 2, 7 and 8 were hydrogen-producing bacteria (HPB).

A sustainable one-step pretreatment of cotton gray fabric with 18-crown-6 as phase transfer in supercritical carbon dioxide

With increasing awareness in environmental protection from the world, traditional pretreatment methods for textiles, which entail high costs and cause severe pollutions, can no longer meet the requirements of green and sustainable development in textile industry. Therefore, to explore a new pretreatment method to overcome those drawbacks is of great importance. In this work, green and environmentally friendly method was developed in supercritical carbon dioxide fluid to pretreat cotton gray fabric for removing various impurities with one step and one bath, by utilizing an 18-crown-6 phase transfer system. Various process parameters, such as the pH value of buffer solution, the dosage of phase transfer catalyst, hydrogen peroxide, buffer solution, and the system temperature, pressure, treatment duration, were investigated and optimized by employing the weight loss percent and the capillary rise height as assessment index. The obtained results show that the developed alkali-hydrogen peroxide one-step method involving the 18-crown-6 phase transfer system in supercritical carbon dioxide exhibits a good feasibility for the removal of various sizing agents and other impurities from cotton fabric, and a satisfactory pretreatment performance and efficiency were achieved. The pretreatment parameters showed an important and various effects on the pretreatment efficiency of cotton substrate during a phase transfer oxidative one-step process in supercritical carbon dioxide. Moreover, a phase transfer oxidative one-step process was also recommended for cotton gray fabric pretreatment in supercritical carbon dioxide, by achieving a fabric weight loss at 6.21% and a satisfactory capillary rise height at 8.0 cm under an optimized condition. Additionally, an oxidative one-step pretreatment mechanism by employing 18-crown-6 to phase transfer reactive species for cotton gray fabric in SCF-CO2 was further supposed.

Prediction of Pretreatment 18F-FDG-PET/CT Parameters on the Outcome of First-Line Therapy in Patients with Metastatic Breast Cancer.

Objective18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG-PET/CT) can provide prognostic information, especially 18F-FDG uptake has been proven to be a predictor for the prognosis of various tumors. Nevertheless, the prognosis of other PET parameters in the metastatic setting remains unclear. This study was aimed at investigating pretreatment parameters based on 18F-FDG-PET/CT so as to estimate the progression-free survival (PFS) of metastatic breast cancer (MBC) patients receiving first-line treatment.MethodsMBC patients who underwent a whole-body 18F-FDG-PET/CT prior to first-line therapy were enrolled. The heterogeneity parameter of PET/CT was analyzed, including heterogeneity index (HI) and general parameters (metabolic tumor volume (MTV), total lesion glycolysis (TLG), maximum standardized uptake value (SUVmax) and mean SUV (SUVmean). PFS was used to evaluate the treatment outcome. Kaplan–Meier method was adopted to carry out survival analysis and Log rank test was conducted to make a comparison.ResultsA total of 177 MBC patients were selected, in which 68 were in De novo stage IV. Thirty patients were human epidermal growth factor receptor 2 (HER2)-positive, 60 patients were triple-negative, and 87 patients were hormone receptor (HR)-positive and HER2-negative. In the whole population, patients with high baseline SUVmax, SUVmean, MTV, TLG or HI were associated with lower PFS (P=0.028, 0.005, 0.017, 0.026 and 0.035, respectively). Among the patients in De novo stage IV, those with high HI at baseline had significantly shorter PFS (P=0.001). In HR+/HER2- and HER2+ subgroups, only baseline HI showed the predictive value of PFS (P=0.023 and 0.049, respectively). In the triple-negative subgroup, high baseline SUVmax, MTV or TLG showed the predictive value of worse PFS (P=0.030, 0.011 and 0.023, respectively).ConclusionPretreatment 18F-FDG-PET/CT parameters show the predictive value of PFS in MBC patients receiving first-line treatment. However, predictive PET/CT parameters might be different in patients with different molecular subtypes and De novo stage IV.

A Random Forest Model for the Prediction of FOG Content in Inlet Wastewater from Urban WWTPs

The content of fats, oils, and greases (FOG) in wastewater, as a result of food preparation, both in homes and in different commercial and industrial activities, is a growing problem. In addition to the blockages generated in the sanitary networks, it also represents a difficulty for the performance of wastewater treatment plants (WWTP), increasing energy and maintenance costs and worsening the performance of downstream treatment processes. The pretreatment stage of these facilities is responsible for removing most of the FOG to avoid these problems. However, so far, optimization has been limited to the correct design and initial installation dimensioning. Proper management of this initial stage is left to the experience of the operators to adjust the process when changes occur in the characteristics of the wastewater inlet. The main difficulty is the large number of factors influencing these changes. In this work, a prediction model of the FOG content in the inlet water is presented. The model is capable of correctly predicting 98.45% of the cases in training and 72.73% in testing, with a relative error of 10%. It was developed using random forest (RF) and the good results obtained (R2 = 0.9348 and RMSE = 0.089 in test) will make it possible to improve operations in this initial stage. The good features of this machine learning algorithm had not been used, so far, in the modeling of pretreatment parameters. This novel approach will result in a global improvement in the performance of this type of facility allowing early adoption of adjustments to the pretreatment process to remove the maximum amount of FOG.

Nanobiocatalysts for efficacious bioconversion of ionic liquid pretreated sugarcane tops biomass to biofuel

This work aimed to study the hydrolysis of ionic liquid (IL) pretreated sugarcane tops (SCT) biomass with in-house developed IL-stable enzyme preparation, from a fungal isolate Aspergillus flavus PN3. Maximum reducing sugar yield (181.18 mg/g biomass) was obtained from tris (2-hydroxyethyl) methylammonium-methylsulfate ([TMA]MeSO4) pretreated biomass. Pretreatment parameters were optimized to attain enhanced sugar yield (1.57-fold). Functional mechanism of IL mediated pretreatment of SCT biomass was elucidated by SEM, XRD, FTIR and 1H NMR studies. Furthermore, nanobiocatalysts prepared by immobilization of enzyme preparation by covalent coupling on magnetic nanoparticles functionalized with amino-propyl triethoxysilane, were assessed for their hydrolytic efficacy and reusability. Nanobiocatalysts were examined by SEM and FTIR analysis for substantiation of immobilization. This is the first ever report of application of magnetic nanobiocatalysts for saccharification of IL-pretreated sugarcane tops biomass.

Prognostic Value of Metabolic Tumor Parameters in Pretreatment 18F-Fluorodeoxyglucose Positron Emission Tomography-Computed Tomography Scan in Advanced Non-Small Cell Lung Cancer.

Objective:This retrospective study aimed to investigate whether metabolic parameters of primary tumour i.e. maximum standardized uptake value (SUVmax), metabolic tumour volume (MTV) and total lesion glycolysis (TLG) predict overall survival (OS) in patients with advanced stage non-small cell lung cancer (NSCLC).Materials and Methods:SUVmax, MTV and TLG of the primary tumors were measured in staging 18F-Fluorodeoxyglucose Positron emission tomography- Computed tomography (18F-FDG PET/CT) scan of 97 NSCLC patients by gradient based tumour segmentation method. Prognostic ability was assessed for overall survival (OS) of the patients.Result:The median follow-up period of the study was 15.84 months (range 1.3 to 47.97 months).The estimated median OS was 11.29 months (range 1.37 to 38.63 months). Total of 40 (41.24%) patients had progressive disease and 21 (21.65%) patients died during the follow up period. Receiver Operating Characteristic (ROC) analysis showed that the area under the curve (AUC) for MTV was significant (area = 0.652 ± 0.065; 95% CI = 0.548 – 0.746; P = 0.020). Kaplan-Meier survival curves showed that the OS differences between the groups of patients who were dichotomized by the median value of MTV (38.76 ml, P = 0.0150) and TLG (301.69 ml, P = 0.0046) were significant. MTV (hazard ratio = 4.524; 95% CI = 1.244 – 16.451; P = 0.022) was found to be an independent prognostic factor for OS in multivariate analysis.Conclusion:MTV of the primary tumor is a potential prognostic parameter for OS in our population of advanced NSCLC patients independent of other risk factors.

Paris II and Rotterdam criteria are the best predictors of outcomes in patients with primary biliary cholangitis in Japan.

Biochemical response to treatment in patients with primary biliary cholangitis (PBC) reflects prognosis. However, the best predictive criteria to detect biochemical response remain undetermined. In addition, because these criteria need > 6months until definition, parameters that can estimate its results before initiating treatment are needed. We conducted a single-center retrospective study on 196 patients with PBC, followed up for at least 12months after initiating treatment. Kaplan-Meier analysis showed that Paris II (p = 0.002) and Rotterdam criteria (p = 0.001) could estimate the overall survival of PBC patients, whereas Paris II (p = 0.001), Rotterdam (p = 0.001), and Rochester criteria (p= 0.025) could estimate liver-related deaths. Cox hazard analysis revealed Paris II and Rotterdam criteria as significantly independent predictors of overall survival (hazard ratio (HR) 3.948, 95% CI 1.293-12.054, p = 0.016 and HR 6.040, 95% CI 1.969-18.527, p = 0.002, respectively) and liver-related deaths (HR 10.461, 95% CI 1.231-88.936, p = 0.032 and HR 10.824, 95% CI 1.252-93.572, p = 0.032, respectively). The results of Paris II criteria could be estimated by serum prothrombin time (Odds ratio (OR) 1.052, 95% CI 1.008-1.098, p = 0.021) and alanine transaminase level (OR 0.954, 95% CI 0.919-0.991, p = 0.014) whereas, those of Rotterdam criteria could be estimated by serum albumin level (OR 3.649, 95% CI 1.098-12.128, p = 0.035) at the time of diagnosis. This study highlights the best prediction criteria and pre-treatment parameters that facilitate the prognosis of PBC patients.

Computational Fluid Dynamics Analysis of Nasal Airway Changes after Treatment with C-Expander.

The use of the C-expander is an effective treatment modality for maxillary skeletal deficiencies which can cause ailments and significantly reduce life expectancy in late adolescents and young adults. However, the morphological and dynamic effects on the nasal airway have not been reported. The main goal of this study was to evaluate the nasal airway changes after the implementation of a C-expander. A sample of nine patients (8 females, 1 male, age range from 15 to 29 years) was included. The morphology parameters and nasal airway ventilation parameters of pretreatment and posttreatment were measured. All study data were normally distributed. A paired t-test was used to evaluate the changes before and after treatment. After expansion, the mean and standard deviation values of intercanine maxillary width (CMW) and intermolar maxillary width (MMW) increased from 35.75 ± 2.48 mm and 54.20 ± 3.17 mm to 37.87 ± 2.26 mm (P < 0.05) and 56.65 ± 3.10 mm (P < 0.05), respectively. The nasal cavity volume increased from 20320.00 ± 3468.25 mm3 to 23134.70 ± 3918.84 mm3 (P < 0.05). The nasal pressure drop decreased from 36.34 ± 3.99 Pa to 30.70 ± 3.17 Pa (P < 0.05), while the value of the maximum velocity decreased from 6.50 ± 0.31 m/s to 5.85 ± 0.37 m/s (P < 0.05). Nasal resistance dropped remarkably from 0.16 ± 0.14 Pa/ml/s to 0.08 ± 0.06 Pa/ml/s (P < 0.05). The use of C-expander can effectively broaden the area and volume of the nasal airway, having a positive effect in the reduction of nasal resistance and improvement of nasal airway ventilation. For patients suffering from maxillary width deficiency and respiratory disorders, a C-expander may be an alternative method to treat the disease.

Extraction of fish oil from fish heads using ultra-high pressure pre-treatment prior to enzymatic hydrolysis

Extraction of fish oil from fish byproducts not only increases the utilization rate of fish resources but also reduces environmental pollution. Extraction methods affect the recovery and quality of fish oil. In this study, fish oil was extracted from yellowfin tuna (Thunnus albacares) heads using enzymatic hydrolysis extraction after single ultra-high pressure pre-treatment (EHSUP). The processing parameters of extraction were optimized with a two-factor repeated experimental design. The results showed that ultra-high pressure pre-treatment of the tuna heads prior to enzymatic hydrolysis was suitable for extracting fish oil and effectively increased the oil yield. The optimum parameters of ultra-high pressure pre-treatment were 200 MPa for 10 min or 100 MPa for 20 min, and the optimum parameters of enzymatic hydrolysis were 1% papain and 55 °C for 60 min. Considering the fatty acid profiles and the oxidation stability, yellowfin tuna oil is a high-quality, docosahexaenoic acid (DHA)-based product with high economic value. Industrial relevanceUltra-high pressure treatment is a novel food processing technology. In general, the main disadvantage of enzymatic hydrolysis extraction is its lower oil recovery than that of solvent extraction. This study investigated the application of ultra-high pressure on fish byproducts prior to enzymatic hydrolysis oil extraction. The results showed that the oil recovery improved by subjecting the tuna heads to ultra-high pressure pre-treatment prior to enzymatic hydrolysis extraction. These results will provide a technical reference for efficiently extracting high-quality fish oil.

In-depth process parameter investigation into a protic ionic liquid pretreatment for 2G ethanol production

Protic ionic liquids (PILs) are promising pretreatment agents that can efficiently deconstruct lignocellulosic biomass for 2G ethanol production. PIL synthesis is less costly than that of aprotic imidazolium-based ILs thereby reducing the final ethanol price. However, a more comprehensive investigation is still necessary in order to better understand how PILs affect biomass during pretreatment. An investigation of process parameters was carried out for pretreatment of sugarcane bagasse using the PIL monoethanolammonium acetate, [MEA]OAc], focussing on main pretreatment parameters — time, temperature, solids loading, and water content. Optimal conditions were found to be 2 h, 150 °C, 15 wt% solids loading and 20 wt% water content. Lignin solubilization of almost 60 wt% was achieved with no carbohydrate losses, leading to 78.6% and 49% of cellulose and hemicellulose yields during saccharification. The addition of hemicellulases increased the hemicelluloses yield in saccharification to up to 66% with a high enzyme loading, 5.8 wt%. Ethanol, isopropanol, isoamyl alcohol and water were tested as anti-solvents; none of which led to higher sugar yields or modified recovered lignin structures, as confirmed by spectroscopic methods. Lignin analysis revealed the presence of S, G and H moieties, low degree of condensation, and a potential to produce aromatic compounds that could add value to the biorefinery.

Comparison of ormeloxifen and mifepristone in management of leiomyoma uterus

Aims and Objectives: To compare the effect of mifepristone and ormeloxifen on symptomatology, size and vascularity of fibroid and also to compare the compliance and side effects of both these drugs. Materials and Methods: This study was conducted in the department of obstetrics and gynecology at Swaroop Rani Nehru hospital, Allahabad and Kamla Nehru memorial hospital, Allahabad over a period of one year between 2016-2017 in 90 fibroid patients who gave consent for the study. Depending on their choice they were randomly divided into 2 groups. Group A included 44 fibroid patients who were given mifepristone and Group B included 46 fibroid patients were given ormeloxifen. Assessment of heavy menstrual bleeding by pictorial blood loss assessment chart, dysmenorrhea and dyspareunia by visual analogue scale, estimation of hemoglobin and repeat imaging to assess size, number, endometrial thickness, Doppler velocimetry of fibroid was done and all variables were compared in relation to pretreatment and post-treatment parameters by using chi square test. Results: 97.7% patients in group A and 95.6% patients in group B were compliant towards treatment. A significant reduction in HMB (group A-51.16% to 18.6% $ group B-45.45% to 20.45%),mean pbac score(group A-246.6 to 65.2;p Conclusion: Mifepristone and ormeloxifen were equally effective for symptomatic relief in fibroid patients. Myoma size was significantly reduced by mifepristone only, with notable endometrial hyperplasia whereas ormeloxifen causes significant reduction in endometrial thickness. No major side effects observed with any of them. Keywords: Mifepristone, Ormeloxifen, Leiomyoma, SERM, PBAC score.

Optimization of zero-waste hydrogen peroxide - Acetic acid pretreatment for sequential ethanol and methane production

In this study, the development of an environmentally friendly version of hydrogen peroxide – acetic acid (HPAC) pretreatment was investigated and optimized with two different approaches as maximum biofuel production optimization and cost optimization. Central composite design and response surface method were used for the experimental design and data analysis, respectively. In the experimental design, investigated HPAC pretreatment parameters were 50–100 °C reaction temperature, 6–24 h reaction time, 0–2 wt% HAc and 0–2 wt% H2O2. Significant ethanol production enhancement was observed only for the samples pretreated at 100 °C. This increase was due to the enhanced enzyme accessibility by the surface area increment and delignification, which were also revealed in SEM imaging and FTIR analysis. Maximum ethanol production was observed in 2% H2O2, 0% HAc, 24 h, and 100 °C pretreatment conditions as 81.65 mg EtOH/g total solid (TS) (103.49 L EtOH/tonne TS), corresponding 49.55% of the theoretical ethanol yield. Maximum methane production, on the other hand, was observed in 2% HAc, 0% H2O2, 100 °C, 6 h conditions as 363.82 mL CH4/g VS. In terms of net energy production, cost optimum pretreatment (1.87% HAc, 0% H2O2, 50 °C, and 6 h) was found be the most beneficial condition with 67.5% energy recovery.

Associations of Pretreatment Physical Status Parameters with Tolerance of Concurrent Chemoradiation and Survival in Patients with Non-small Cell Lung Cancer.

The aim of this study was to evaluate associations between pretreatment physical status parameters and tolerance of concurrent chemoradiation (cCHRT) and survival among patients with stage III non-small cell lung cancer (NSCLC). A retrospective cohort study was conducted among patients with stage III NSCLC who had received cCHRT between 2006 and 2015. Multivariate independent associations were analysed between the pretreatment parameters age, Charlson comorbidity index, World Health Organization performance status (WHO performance status), body mass index (BMI), fat-free mass index (FFMI), maximal handgrip strength, forced expiratory volume in one second and carbon monoxide lung diffusion capacity on the one hand with tolerance of cCHRT (defined as a received radiation dose at least equal to the prescribed radiation dose) and survival on the other hand. 527 of 577 patients (91.3%) tolerated cCHRT. A WHO performance status ≥ 2 (odds ratio (OR) 0.43) and BMI < 18.5kg/m2 (OR 0.36) were associated with poorer tolerance of cCHRT. In the total group, a WHO performance status ≥ 2 (hazard ratio (HR) 1.73), low FFMI (HR 1.23) and intolerance of cCHRT (HR 1.55) were associated with poorer survival. In patients with stage III NSCLC receiving cCHRT, poor WHO performance status and BMI < 18.5kg/m2 were independently associated with tolerance of cCHRT. Physical status parameters and intolerance of cCHRT were independently associated with poorer survival. Besides using this information for treatment decisions, optimizing physical status in patients at risk for intolerance of cCHRT might be a next step for improving treatment outcomes.

A Pretreatment Prognostic Score to Stratify Survival in Pancreatic Cancer.

The aim of this study was to develop and validate a pretreatment prognostic score in pancreatic cancer (PDAC). Pretreatment prognostication in PDAC is important for treatment decisions but remains challenging. Available prognostic tools are derived from selected cohorts of patients who underwent resection, excluding up to 20% of patients with exploration only, and do not adequately reflect the pretreatment scenario. Patients undergoing surgery for PDAC in Heidelberg from July 2006 to June 2014 were identified from a prospective database. Pretreatment parameters were extracted from the database and the laboratory information system. Parameters independently associated with overall survival by uni- and multivariable analyses were used to build a prognostic score. A contemporary cohort from Verona was used for external validation. In 1197 patients, multiple pretreatment parameters were associated with overall survival by univariable analyses. American Society of Anesthesiology classification, carbohydrate antigen 19-9 (CA19-9), carcinoembryonic antigen, C-reactive protein, albumin, and platelet count were independently associated with survival and were used to create the Heidelberg Prognostic Pancreatic Cancer (HELPP)-score. The HELPP-score was closely associated with overall survival (median survival between 31.3 and 4.8 months; 5-year survival rates between 35% and 0%) and was able to stratify survival in subgroups with or without resection as well as in CA19-9 nonsecretors. In the resected subgroup the HELPP-score stratified survival independently of pathological prognostic factors. The HELPP-score was externally validated and was superior to CA19-9 in both the development and validation cohorts. The HELPP-score is a readily available prognostic tool based on pretreatment routine parameters to stratify survival in PDAC independently of resection status and pathological tumor stage.

Association of Myeloperoxidase Gene Polymorphism With Iron Deficiency Anemia in Turkish Children.

This study was performed to investigate the gene polymorphisms of the myeloperoxidase (MPO) enzyme and to determine whether MPO gene polymorphisms influence the response to iron therapy in pediatric patients with iron deficiency anemia (IDA). In this case-control study, 50 Turkish children with IDA and 50 healthy controls were enrolled. Three MPO gene alleles were selected for genotyping in the study: GG, AG, and AA. The relationships of alleles with IDA were analyzed and compared in patients and controls. Pretreatment and posttreatment laboratory parameters and gene polymorphisms were compared in the patient group. There was a significant difference between patients with IDA and controls regarding genotype frequencies of the AA, GG, and AG alleles (P=0.005). However, the AG allele was found to be associated with variations in hemoglobin, red blood cell, hematocrit, mean corpuscular volumes, and mean corpuscular Hb concentrations levels. The frequency of AA, GG, and AG alleles of the MPO gene was potentially associated with changes in iron metabolism and the AG allele led to variations in various hemogram parameters.

Twelve-month post-treatment parameters are superior in predicting hepatocellular carcinoma in patients with chronic hepatitis B.

There are currently several prediction models for hepatocellular carcinoma (HCC) in chronic hepatitis B (CHB) receiving oral antiviral therapy. However, most models are based on pre-treatment clinical parameters. The current study aimed to develop a novel and practical prediction model for HCC by using both pre- and post-treatment parameters in this population. We included two treatment-naïve CHB cohorts who were initiated on oral antiviral therapies: the derivation cohort (n=1480, Korea prospective SAINT cohort) and the validation cohort (n=426, the US retrospective Stanford Bay cohort). We employed logistic regression, decision tree, lasso regression, support vector machine and random forest algorithms to develop the HCC prediction model and selected the most optimal method. We evaluated both pre-treatment and the 12-month clinical parameters on-treatment and found the 12-month on-treatment values to have superior HCC prediction performance. The lasso logistic regression algorithm using the presence of cirrhosis at baseline and alpha-foetoprotein and platelet at 12months showed the best performance (AUROC=0.843 in the derivation cohort. The model performed well in the external validation cohort (AUROC=0.844) and better than other existing prediction models including the APA, PAGE-B and GAG models (AUROC=0.769 to 0.818). We provided a simple-to-use HCC prediction model based on presence of cirrhosis at baseline and two objective laboratory markers (AFP and platelets) measured 12months after antiviral initiation. The model is highly accurate with excellent validation in an external cohort from a different country (AUROC 0.844) (Clinical trial number: KCT0003487).