The rising price of oil is hurting consumers all over the world. There is growing interest in producing biofuels from non-food crops, such as sugarcane trash. Lignocellulosic biomass (e.g., sugarcane trash) is an abundant, inexpensive, and renewable resource. The patented MixAlco process is a cost-effective solution, which does not require sterility or the addition of expensive enzymes to convert lignocellulosic biomass to transportation fuels and valuable chemicals. In this study, the MixAlco process was used to convert sugarcane trash to carboxylic acids under thermophilic conditions. Lime-treated sugarcane trash (80%) and chicken manure (20%) was used as the feedstock in rotary 1-L fermentors. Ammonium bicarbonate buffer was used to mitigate the effects of product (carboxylic acid) inhibition. Marine inoculum was used because of the high adaptability of the mixed culture of microorganisms present. Iodoform solution was added to inhibit methanogenesis. Preliminary batch studies over a 20-day period produced 19.7 g/L of carboxylic acids. Sugarcane trash had the highest average yield (0.31 g total acid/g VS fed) and highest average conversion (0.70 g VS digested/g VS fed) among the three substrates compared. Countercurrent fermentations were performed at various volatile solid loading rates (VSLR) and liquid residence times (LRT). The highest acid productivity of 1.40 g/(L�d) was at a total acid concentration of 29.9 g/L. The highest conversion and yield were 0.64 g VS digested/g VS fed and 0.36 g total acid/g VS fed, respectively. The continuum particle distribution model (CPDM) was used to predict acid concentration at various VSLR and LRT. The average error in between the predicted and experimental acid concentration and conversion were 4.62% and 1.42%, respectively. The effectiveness of several pretreatment methods was evaluated using the CPDM method. The best-performing method was short-term, no-wash, oxidative lime pretreatment with ball milling. At an industrial-scale solids loading of 300 g VS/L liquid, the CPDM ?map? predicts a total acid concentration of 64.0 g/L at LRT of 30 days, VSLR of 7 g/(L�d), and conversion of 57%. Also high conversion of 76% and high acid concentration of 52 g/L are achieved at a VSLR of 4 g/(L�d) and LRT of 30 days.

With the inevitable depletion of the petroleum supply and increasing energy demands in the world, interest has been growing in bioconversion of lignocellulosic biomass (e.g., sugarcane bagasse). Lignocellulosic biomass is an abundant, inexpensive, and renewable resource. Most of current conversion technologies require expensive enzymes and sterility. In contrast, the patented MixAlco process requires no enzymes or sterility, making it attractive to convert lignocellulosic biomass to transportation fuels and valuable chemicals. This study focuses on pretreatment and thermophilic fermentation in the MixAlco process. Ammonium bicarbonate (NH4HCO3) was discovered to be a better pH buffer than previously widely used calcium carbonate (CaCO3) in anaerobic fermentations under thermophilic conditions (55°C). The desired pH should be controlled within 6.5 to 7.5. Over 85% acetate content in the product was found in paper fermentations and bagasse fermentations. Hot-lime-water-treated bagasse countercurrent fermentations buffered by ammonium bicarbonate achieved 50–60% higher total product concentrations than those using calcium carbonate. It was nearly double in paper batch fermentations if the pH was controlled around 7.0. Ammonium bicarbonate is a “weak” methane inhibitor, so a strong methane inhibitor (e.g., iodoform) is still required in ammonium bicarbonate buffered fermentations. Residual calcium salts did not show significant effects on ammonium bicarbonate buffered fermentations. Lake inocula from the Great Salt Lake, Utah, proved to be feasible in ammonium bicarbonate buffered fermentations. Under mesophilic conditions (40°C), the inoculum from the Great Salt Lake increased the total product concentration about 30%, compared to the marine inoculum. No significant fermentation performance difference, however, was found under thermophilic conditions. The Continuum Particle Distribution Model (CPDM) is a powerful tool to predict product concentrations and conversions for long-term countercurrent fermentations, based on batch fermentation data. The experimental acid concentrations and conversions agree well with the CPDM predictions (average absolute error < 15%). Aqueous ammonia treatment proved feasible for bagasse. Air-lime-treated bagasse had the highest acid concentration among the three treated bagasse. Air-lime treatment coupled with ammonium bicarbonate buffered fermentations is preferred for a “crop-tofuel” process. Aqueous ammonia treatment combined with ammonium bicarbonate buffered fermentations is a viable modification of the MixAlco process, if “ammonia recycle” is deployed.

Via mixed-culture fermentation, the MixAlcoTM produces carboxylic acids, which are chemically converted into industrial chemicals and hydrocarbon fuels. Using pilot fermentation data, The Continuum Particle Distribution Model (CPDM) overestimated acid concentration (30–90% error) but more closely estimated conversion (<15% error). Incorporating the effect of air into the model reduced the absolute error of all predictions by >50%. To analyze fermentation data with semi-continuous streams, the Slope method calculates the average flowrate of material from the slope of the moving cumulative sum with respect to time. Although the Slope method does not significantly improve accuracy, it dramatically reduces error compared to traditional techniques (>40% vs. <2%). Nutrients are essential for microbial growth and metabolism. For a four-bottle fermentation train, five nutrient contacting patterns (single-point nutrient addition to Fermentors F1, F2, F3, F4, and multi-point parallel addition) were investigated. Compared to the traditional nutrient contacting method (all nutrients fed to F1), the near-optimal feeding strategies improved exit yield, culture yield, process yield, exit acetate-equivalent yield, conversion, and total acid productivity by approximately 31%, 39%, 46%, 31%, 100%, and 19%, respectively. To estimate nitrogen concentration profiles, a segregated-nitrogen model uses separate mass balances for solid- and liquid-phase nitrogen; the nitrogen reaction flux between phases is assumed to be zero. Using five fermentation trains, each with a different nutrient contacting pattern, the model predictions capture basic behavior; therefore, it is a reasonable tool for estimating and controlling nitrogen profiles. To determine the optimal scenario for mixed-acid fermentations, an array of batch fermentations was performed that independently varied the C/N ratio and the blend of carbohydrate (office paper) and nutrient (wet chicken manure (CM)). Reactant was defined as non-acid volatile solids (NAVS). C/N ratios were based on non-acid carbon (CNA). A blend of 93% paper and 7% wet CM (dry basis) with a C/N ratio of 37 g CNA/g N had the highest culture yield (0.21 g acidproduced/g NAVSinitial), total acid productivity (0.84 g acidproduced/(Lliq·d)), and conversion (0.43 g NAVSconsumed/g NAVSinitial).

<p>Atopic dermatitis (AD) is a common pruritic skin disease in people and domestic animals that can be severely debilitating and stressful to the patient and the caregiver. The diagnosis of AD requires time consuming and expensive procedures, and treatment is often lifelong at considerable cost. Alterations in the lipid composition of the epidermis are a hallmark of the disease, and these may represent changes caused by the inflammation and defects in the lipid barrier. Liquid chromatography tandem mass spectrometry (LC-MS/MS) and, more recently, untargeted profiling using high-resolution time-of-flight instruments have been used to quantify the lipid composition in skin and other tissues, but these approaches are highly demanding in sample preparation and instrument time. In addition, these methods either detect only a limited number of lipids at the time or the identification of detected mass-to-charge ratio (m/z) is problematic when untargeted profiling is used. New lipidomic approaches that generate lipid profiles in a faster and more efficient manner can lead to a better understanding of these lipid changes. </p><p>The mass spectrometry analytical strategy used in this study, multiple reaction monitoring (MRM)-profiling, rapidly identifies discriminant lipids of the epidermis by flow injection. MRM-profiling is a small molecule accelerated discovery workflow performed in two parts using a triple quadrupole mass spectrometer with electrospray ionization as the ion source. Briefly, the first step consists of discovery experiments based on neutral loss and precursor ion scans to detect lipids in pooled samples by targeting class-specific chemical motifs such as polar heads of phospholipids or sphingoid bases of ceramides. The second step of the MRM-profiling is the screening of individual samples for the transitions detected in the discovery phase. </p><p>We first developed the experimental approach of the MRM-profiling methodology using epidermal samples of mice with AD-like inflammatory skin disease (chronic proliferative dermatitis, cpdm). Subsequently, we investigated lipid changes as the disease in mice progressed from minimal to severe. In order to select the most relevant ions, we utilized a two-tiered filter/wrapper feature-selection strategy. First, we built linear models linking the presence of every lipid monitored to disease stage information. The top 10 lipids, ranked based on η2 effect size, were used to build a predictive elastic-net (E-net) regression model linking the lipid ions detected by MRM-profiling with disease progression. The developed model accurately identified disease stages based on the variations in relative amounts of lipid ions corresponding to phosphatidylcholines, cholesterol esters, and glycerolipids-containing and eicosapentaenoic acid fatty acyl residues. Finally, we investigated the lipid profile of the epidermis in dogs with canine AD using the previously developed methodology. Epidermis from client owned patients and healthy controls were collected. Patients were sampled from affected and unaffected skin avoiding areas with secondary infections and the canine atopic dermatitis extent and severity index (CADESI-4) was recorded. The monitored lipids substantially separated the samples of healthy dogs from atopic dogs and distinguished the affected from the unaffected skin of patients. Samples were grouped into two cohorts for low-score and high-score CADESI-4, the first principal component was able to differentiate the control group from the low and high-score group. Differences in the lipid composition associated with low and high score CADESI-4 were significantly different only after separating the samples by sex of the dogs, demonstrating sexual dimorphism in the lipid changes associated with disease. The compositional data was feature extracted using the CADESI-4 to build linear models that identified oleic acid-containing triacylglycerides, long-chain acylcarnitines and sphingolipids as highly predictive lipids and were subsequently used to construct a predictive E-net regression. The lipid fingerprint obtained from the MRM-profiling was highly correlated (R2=0.89) with the classification of the standardized CADESI-4 score. </p><p>This research showed that changes in the lipid composition of the epidermis can be detected by MRM-profiling in atopic dogs even when the skin looks clinically healthy and that sex is a modifying factor in the lipid profile of canine atopic dermatitis (CAD). We expect that this research leads to a better understanding of the lipid changes in the epidermis during the onset of AD and as the chronic inflammatory process develops. The high prediction rate given by the lipid biomarkers for disease progression identified here by the machine learning strategy provides a potential molecular assessment tool for the diagnosis and monitoring of atopic dermatitis and the patient response to treatment.</p><div><br></div>