Sequential ultrasound assisted deep eutectic solvent-based protein extraction from Sacha inchi meal biomass: towards circular bioeconomy.

The need for high-quality dietary proteins has risen over the years with improvements in the quality of life. Deep eutectic solvents (DESs) have been regarded as potential green alternatives to conventional organic solvents for protein extraction from press cake biomass, meeting the needs of sustainable development goals. Sacha inchi seed meal (SIM) is generated as a by-product of the seed oil extraction industries containing high protein content. The current study presents a novel ultrasound assisted DES method for the extraction of SIM protein in a sequential manner. Four different DESs were screened, out of which choline chloride (ChCl)/glycerol (1:2) gave promising results in protein recovery and was further selected. The sequential ultrasound-ChCl/glycerol could effectively extract high total crude protein content (77.43%) from SIM biomass compared to alone ultrasound (29.21%) or ChCl/glycerol (58.32%) treatment strategies. The SIM protein extracted from ultrasound-ChCl/glycerol exhibited high solubility (94.39%) at alkaline pH and highest in vitro digestibility (71.16%) by digestive enzymes (pepsin and trypsin). The protein characterization by SDS-PAGE and FTIR elucidated the structural properties and presence of different functional groups of SIM protein. Overall, the sequential ultrasound-ChCl/glycerol revealed its significant potential for one-step biorefining of the waste Sacha inchi meal biomass for circular bioeconomy.

Transcranial brain atlas-based optimization for functional near-infrared spectroscopy optode arrangement: Theory, algorithm, and application.

The quality of optode arrangement is crucial for group imaging studies when using functional near-infrared spectroscopy (fNIRS). Previous studies have demonstrated the promising effectiveness of using transcranial brain atlases (TBAs), in a manual and intuition-based way, to guide optode arrangement when individual structural MRI data are unavailable. However, the theoretical basis of using TBA to optimize optode arrangement remains unclear, which leads to manual and subjective application. In this study, we first describe the theoretical basis of TBA-based optimization of optode arrangement using a mathematical framework. Second, based on the theoretical basis, an algorithm is proposed for automatically arranging optodes on a virtual scalp. The resultant montage is placed onto the head of each participant guided by a low-cost and portable navigation system. We compared our method with the widely used 10/20-system-assisted optode arrangement procedure, using finger-tapping and working memory tasks as examples of both low- and high-level cognitive systems. Performance, including optode montage designs, locations on each participant's scalp, brain activation, as well as ground truth indices derived from individual MRI data were evaluated. The results give convergent support for our method's ability to provide more accurate, consistent and efficient optode arrangements for fNIRS group imaging than the 10/20 method.

Type II Collagen from Cartilage of Acipenser baerii Promotes Wound Healing in Human Dermal Fibroblasts and in Mouse Skin.

Type II collagen is an important component of cartilage; however, little is known about its effect on skin wound healing. In this study, type II collagen was extracted from the cartilage of Acipenser baerii and its effect on in vitro and in vivo wound healing was compared to type I collagen derived from tilapia skin. Sturgeon cartilage collagen (SCC) was composed of α1 chains and with a thermal denaturation (Td) at 22.5 and melting temperature (Tm) at 72.5 °C. Coating SCC potentiated proliferation, migration, and invasion of human dermal fibroblast adult (HDFa) cells. Furthermore, SCC upregulated the gene expression of extracellular matrix (ECM) components (col Iα1, col IIIα1, elastin, and Has2) and epithelial-mesenchymal transition (EMT) molecules (N-cadherin, Snail, and MMP-1) in HDFa. Pretreatment with Akt and mitogen-activated protein kinase (MAPK) inhibitors significantly attenuated the HDFa invasion caused by SCC. In mice, the application of SCC on dorsal wounds effectively facilitated wound healing as evidenced by 40-59% wound contraction, whereas the untreated wounds were 18%. We observed that SCC reduced inflammation, promoted granulation, tissue formation, and ECM deposition, as well as re-epithelialization in skin wounds. In addition, SCC markedly upregulated the production of growth factors in the dermis, and dermal and subcutaneous white adipose tissue; in contrast, the administration of tilapia skin collagen (TSC) characterized by typical type I collagen was mainly expressed in the epidermis. Collectively, these findings indicate SCC accelerated wound healing by targeting fibroblast in vitro and in vivo.

α,ß-Double Electrophilic Addition of Allene-1,3-Dicarboxylic Esters for the Construction of Polysubstituted Furans by KI/tert-Butyl Hydroperoxide (TBHP)-Promoted Oxidative Annulation.

An unprecedented KI/tert-butyl hydroperoxide promoted tandem Michael addition/oxidative annulation of allene-1,3-dicarboxylic esters and 1,3-dicarbonyl compounds has been developed. This procedure provides a new, facile, and transition-metal-free synthetic approach to afford polysubstituted furans in moderate to excellent yields (up to 93 %). This method first establishes a α,ß-double electrophilic reaction mode of allene-1,3-dicarboxylic esters to form 1,3-dicarbonyl compounds.

Regioselective metal-free one-pot synthesis of functionalized 2-aminothiophene derivatives.

A facile metal-free synthesis of 2-aminothiophene derivatives by the reaction of 2-ynals with thioamides in alcohols has been developed. This transformation allows the assembly of 2-aminothienyl ether derivatives via a well-designed aldol condensation/regioselective intramolecular cyclization/conjugate addition cascade reaction and provides a straightforward synthetic protocol for constructing 2,3,5-trisubstituted 2-aminothiophenes.

Skin decontamination efficacy of potassium ketoxime on rabbits exposed to sulfur mustard.

CONTEXT: The chemical weapon sulfur mustard (SM) is a blister agent, and currently, there is no effective antidote. OBJECTIVE: To evaluate the decontamination efficacy of potassium ketoxime against SM and preliminarily elucidate its decontamination mechanism. MATERIALS AND METHODS: Potassium ketoxime reacted with SM, and SM residues were tested at different time intervals by T-135 colorimetry after the reaction. Rabbit skin was topically exposed to 2 mg/cm(2) SM, treated with potassium ketoxime 1 min later, and observed after 6, 12, and 24 h. Gas chromatography-mass spectroscopy was employed to screen and identify the main products of potassium ketoxime decontamination of SM. RESULTS: Potassium ketoxime had a great effect against SM contamination. With a mass ratio of decontaminant: SM of 50:1, decontamination rates against SM were 87.5% after 30 s, 95.9% after 1 min, and 99.0% after 5 min. Fifteen minutes after exposure to SM, the untreated group showed clear erythema lesions, whereas the experimental group showed no clear erythema lesions within 6 h. After 12 and 24 h, the areas of damaged skin in the experimental group were 0.038 and 0.125 cm(2), respectively, compared with 2.21 and 2.65 cm(2) in the control group. Histopathological analysis revealed that treatment with potassium ketoxime also reduced inflammation-induced damage. CONCLUSION: The results of this study indicate that potassium ketoxime reacted rapidly and completely with SM, and thus, it was found to be a suitable and effective skin decontaminant against SM. The decontamination reaction mechanism is mainly related to nucleophilic substitution.

Synergistic microwave and acidic deep eutectic solvent-based pretreatment of Theobroma cacao pod husk biomass for xylooligosaccharides production.

The bioconversion of lignocellulosic biomass into novel bioproducts is crucial for sustainable biorefineries, providing an integrated solution for circular economy objectives. The current study investigated a novel microwave-assisted acidic deep eutectic solvent (DES) pretreatment of waste cocoa pod husk (CPH) biomass to extract xylooligosaccharides (XOS). The sequential DES (choline chloride/citric acid, molar ratio 1:1) and microwave (450W) pretreatment of CPH biomass was effective in 67.3% xylan removal with a 52% XOS yield from total xylan. Among different XOS of varying degrees of polymerization, a higher xylobiose content corresponding to 69.3% of the total XOS (68.22 mg/g CPH) from liquid fraction was observed. Enzymatic hydrolysis of residual xylan from pretreated CPH biomass with low commercial xylanase (10 IU/g) concentration yielded 24.2% XOS. The MW-ChCl/citric acid synergistic pretreatment approach holds great promise for developing a cost-effective and environmentally friendly method contributing to the sustainable production of XOS from agricultural waste streams.

Advances in machine learning technology for sustainable biofuel production systems in lignocellulosic biorefineries.

In view of the global climate change concerns, the society is approaching towards the development of 'green' and renewable energies for sustainable future. The non-renewable fossil fuels may be largely replaced by renewable energy sources, which could facilitate sustainable growth, energy development and lessen the reliance on conventional energy sources. The traditional methods employed in biorefineries to estimate the data values for the biofuel production systems are often complicated, time-consuming and labour-intensive. Modern machine learning (ML) technologies hold enormous potential in managing high-dimensional complex scientific tasks and improving decision-making in energy distribution networks and systems. The data-driven probabilistic ML algorithms could be applied to smart biofuel systems and networks that may reduce the cost of experimental research while providing accurate estimates of product yields. The current review demonstrates a thorough understanding of the application of different ML models to regulate and monitor the production of biofuels from waste biomass through prediction, optimization and real-time monitoring. The in-depth analysis of the most recent advancements in ML-assisted biofuel production methods, including thermochemical and biochemical processes is provided. Moreover, the ML models in addressing the issues of biofuel supply chains, case studies, scientific challenges and future direction in ML applications are also summarized.

Bioprocess development for the production of xylooligosaccharide prebiotics from agro-industrial lignocellulosic waste.

The development of sustainable biorefineries and bioeconomy has been the mandate of most of the governments with major focus on restricting the climate change concerns and finding new strategies to maintain the global food supply chain. Xylooligosaccharides (XOS) are short-chain oligomers which due to their excellent prebiotic potential in the nutraceutical sector has attracted intense research focus in the recent years. The agro-industrial crop and food waste can be utilized for the production of XOS which are derived from hemicellulose fraction (xylan) of the lignocellulosic materials. The extraction of xylan, is traditionally achieved by acidic and alkaline pretreatments which, however, have limited industrial applications. The inclusion of cutting-edge and environmentally beneficial pretreatment methods and technologies such as deep eutectic solvents and green catalysts are preferred. Moreover, the extraction of xylans from biomass using combinatorial pretreatment approaches may help in economizing the whole bioprocess. The current review outlines the factors involved in the xylan extraction and depolymerization processes from different lignocellulosic biomass and the subsequent enzymatic hydrolysis for XOS production. The different types of oligosaccharides and their prebiotic potential for the growth of healthy gut bacteria have also been explained. The introduction of modern molecular technologies has also made it possible to identify enzymes and microorganisms with the desired characteristics for usage in XOS industrial production processes.

Journey of lignin from a roadblock to bridge for lignocellulose biorefineries: A comprehensive review.

The grave concerns arisen as a result of environmental pollution and diminishing fossil fuel reserves in the 21st century have shifted the focus on the use of sustainable and environment friendly alternative resources. Lignocellulosic biomass constituted by cellulose, hemicellulose and lignin is an abundantly available natural bioresource. Lignin, a natural biopolymer has over the years gained much importance as a high value material with commercial importance. The present review provides an in-depth knowledge on the journey of lignin from being considered a roadblock to a bridge connecting diverse industries with widescale applications. The successful valorization of lignin for the production of bio-based platform chemicals and fuels has been the subject of intensive investigation. A deeper understanding of lignin characteristics and factors governing the biomass conversion into valuable products can support improved biomass consumption. The components of lignocellulosic biomass might be totally transformed into a variety of value-added products with the improvements in bioprocess techniques that valorize lignin. In this review, the recent advances in the lignin extraction and depolymerization methods that may help in achieving the cost-economics of the bioprocess are summarized and compared. The industrial potential of lignin-derived products such as aromatics, biopolymers, biofuels and agrochemicals are also outlined. Additionally, assessment of the recent research trends in lignin valorization into value-added chemicals has been done and present scenario of technological-industrial applications of lignin with economic perspectives is highlighted.

Development of lignocellulosic biorefineries for the sustainable production of biofuels: Towards circular bioeconomy.

The idea of environment friendly and affordable renewable energy resources has prompted the industry to focus on the set up of biorefineries for sustainable bioeconomy. Lignocellulosic biomass (LCB) is considered as an abundantly available renewable feedstock for the production of biofuels which can potentially reduce the dependence on petrochemical refineries. By utilizing various conversion technologies, an integrated biorefinery platform of LCB can be created, embracing the idea of the 'circular bioeconomy'. The development of effective pretreatment methods and biocatalytic systems by various bioengineering and machine learning approaches could reduce the bioprocessing costs, thereby making biomass-based biorefinery more sustainable. This review summarizes the development and advances in the lignocellulosic biorefineries from the LCB to the final product stage using various different state-of-the-art approaches for the progress of circular bioeconomy. The life cycle assessment which generates knowledge on the environmental impacts related to biofuel production chains is also summarized.

Insights into the recent advances of agro-industrial waste valorization for sustainable biogas production.

Recent years have seen a transition to a sustainable circular economy model that uses agro-industrial waste biomass waste to produce energy while reducing trash and greenhouse gas emissions. Biogas production from lignocellulosic biomass (LCB) is an alternative option in the hunt for clean and renewable fuels. Different approaches are employed to transform the LCB to biogas, including pretreatment, anaerobic digestion (AD), and biogas upgradation to biomethane. To maintain process stability and improve AD performance, machine learning (ML) tools are being applied in real-time monitoring, predicting, and optimizing the biogas production process. An environmental life cycle assessment approach for biogas production systems is essential to calculate greenhouse gas emissions. The current review presents a detailed overview of the utilization of agro-waste for sustainable biogas production. Different methods of waste biomass processing and valorization are discussed that contribute towards developing an efficient agro-waste to biogas-based circular economy.

Deep eutectic solvents as promising pretreatment agents for sustainable lignocellulosic biorefineries: A review.

Increasing reliance on non-renewable fuels has shifted research attention to environmentally friendly and sustainable energy sources.The inherently recalcitrant nature of lignocellulosic biomass (LCB) makes downstream processing of the bioprocess challenging. Deep eutectic solvents (DESs) are popular and inexpensive green liquids found effective for LCB valorisation. DESs have negligible vapor-pressure and are non-flammable, recyclable, cost-economic, and thermochemically stable. This review provides a detailed overview on the DESs types, properties and their role in effective delignification and enzymatic digestibility of polysaccharides for cost-effective conversion of LCB into biofuels and bioproducts. The conglomeration of DESs with assistive pretreatment techniques can augment the process of biomass deconstruction. The current challenges in upscaling the DESs-based pretreatment technology up to commercial scale is summarized, with possible solutions and future directions. These insights would fill the knowledge-gaps to towards development of lignocellulosic biorefineries and to address the global energy crisis and environment issues.

An arginine decarboxylase gene PtADC from Poncirus trifoliata confers abiotic stress tolerance and promotes primary root growth in Arabidopsis.

Arginine decarboxylase (ADC) is an important enzyme responsible for polyamine synthesis under stress conditions. In this study, the gene encoding ADC in Poncirus trifoliata (PtADC) was isolated and it existed as a single-copy member. Transcript levels of PtADC were up-regulated by low temperature and dehydration. Overexpression of PtADC in an Arabidopsis thaliana ADC mutant adc1-1 promoted putrescine synthesis in the transgenic line and the stomatal density was reverted to that in the wild type. The transgenic line showed enhanced resistance to high osmoticum, dehydration, long-term drought, and cold stress compared with the wild type and the mutant. The accumulation of reactive oxygen species (ROS) in the transgenic line was appreciably decreased under the stresses, but ROS scavenging capacity was compromised when the transgenic plants were treated with the ADC inhibitor D-arginine prior to stress treatment. In addition, the transgenic line had longer roots than the wild type and the mutant under both normal and stressful conditions, consistent with larger cell number and length of the root meristematic zone. Taken together, these results demonstrated that PtADC is involved in tolerance to multiple stresses, and its function may be due, at least partly, to efficient ROS elimination and to its influence on root growth conducive to drought tolerance.

NIRS-ICA: A MATLAB Toolbox for Independent Component Analysis Applied in fNIRS Studies.

Independent component analysis (ICA) is a multivariate approach that has been widely used in analyzing brain imaging data. In the field of functional near-infrared spectroscopy (fNIRS), its promising effectiveness has been shown in both removing noise and extracting neuronal activity-related sources. The application of ICA remains challenging due to its complexity in usage, and an easy-to-use toolbox dedicated to ICA processing is still lacking in the fNIRS community. In this study, we propose NIRS-ICA, an open-source MATLAB toolbox to ease the difficulty of ICA application for fNIRS studies. NIRS-ICA incorporates commonly used ICA algorithms for source separation, user-friendly GUI, and quantitative evaluation metrics assisting source selection, which facilitate both removing noise and extracting neuronal activity-related sources. The options used in the processing can also be reported easily, which promotes using ICA in a more reproducible way. The proposed toolbox is validated and demonstrated based on both simulative and real fNIRS datasets. We expect the release of the toolbox will extent the application for ICA in the fNIRS community.

Subchronic oral toxicity evaluation of gold nanoparticles in male and female mice.

Gold nanoparticles (AuNPs) are biocompatible nanomaterials with potential application in the food industry. The safety of AuNPs oral consumption remains inconclusive, and information on possible long-term toxicity is limited. The current study aimed to evaluate the subchronic oral toxicity of AuNPs in male and female Institute of Cancer Research (ICR) mice. Citrate-coated spherical AuNPs with 53 nm diameters were prepared and orally administered to the mice. No mortality or clinical abnormalities were observed following daily administration of AuNPs at the dosages of 0.2, 2, and 20 mg/kg for 90 days. There was no significant difference in body weight or the relative organs' weights between the control and AuNPs-treated mice. No gross abnormalities or histopathological changes were observed except that the male mice treated with high dose (20 mg/kg AuNPs) showed minor infiltration in the kidneys, and female mice showed a reduced A/G ratio and elevated platelet indices. Overall, the 90-day long-term oral consumption of AuNPs did not cause significant toxicity in mice.

Corrigendum: Feasibility of Functional Near-Infrared Spectroscopy (fNIRS) to Investigate the Mirror Neuron System: An Experimental Study in a Real-Life Situation.

[This corrects the article DOI: 10.3389/fnhum.2018.00086.].

Determination of Polycyclic Aromatic Hydrocarbons in Sludge from Water and Wastewater Treatment Plants by GC-MS.

The qualitative and quantitative analysis of 16 polycyclic aromatic hydrocarbons (PAHs) in sludge samples from drinking water treatment plants (DWTP) and wastewater treatment plants (WWTP) were established using gas chromatography-mass spectrometry (GC-MS). The method was suitable to quantify PAHs in the sludge of DWTP and WWTP and it was confirmed by the relevant quality assurance/quality control (QA/QC) procedures. The recovery of individual PAHs in the spiked samples ranged from 74.3% to 108.7%. Detection limits of the analytical procedure were 0.0010-0.0046 mg/kg dw for individual PAHs. This method was used to determine the concentration of PAHs in the selected two DWTP and four WWTP sludge samples. The results showed that the total PAHs (∑PAHs) were in low levels which ranged from 0.0668 to 0.1357 mg/kg dw, and 0.5342-1.0666 mg/kg dw for DWTP and WWTP respectively. The 3- & 4-ring PAHs were predominant in DWTP sludge, ranging from 77.4% to 82.7%; the 4-ring PAHs were predominant in WWTP sludge, ranging from 40.7% to 47.6%. The PAHs of DWTP sludge are mainly composed of 3-ring phenanthrene and anthracene and 4-ring pyrene, and chrysene. The PAHs of WWTP sludge are dominated by 4-ring fluoranthene, pyrene, and chrysene. The detected PAHs concentration should be undoubtedly considered for agriculture in sludge applications based on the limits of the EU regulations. The results of this study can be used for regular monitoring to establish a reference for sludge management and application to agriculture.

Angiography with the 256-multislice spiral computed tomography and its application in evaluating atherosclerotic plaque and cerebral ischemia.

Ulceration of carotid arterial plaque is associated with cerebral events. Detection of ulcerated plaques will benefit patient from stroke and other ischemic events. The aim of this study was to evaluate morphology of atherosclerotic plaques in the carotid arteries and to assess its clinical impact in predicting cerebral events.A total of 386 patients were examined with 256-multislice spiral computed tomographic angiography (MSCTA).It was found that 356 of the 386 patients had cerebral ischemic symptoms. Specifically, 35 patients had amaurosis fugax (AmF), 178 had transient ischemic attack (TIA), and 143 had ischemic stroke. Abnormal images were found in 658 carotid arteries by MSCTA. Of the 658 abnormal images of carotid arteries, besides the 34 cases of carotid arterial occlusion, 624 cases were atherosclerotic plaques. Of the 624 plaques, 394 (63.2%) were smooth surface plaques, 161 (25.8%) were irregular surface plaques, and 69 (11.1%) were ulcerated plaques. Incidence of ulcerated plaque was higher in the ischemic stroke patients (13.1%) compared with that in the TIA group (10.3%), AmF group (6.6%), or symptom-free group (9.4%) although it was not statistically significant (P = .288). However, there was significant difference in the incidence of ischemic stroke between the ulcerated (20/69, 28.9%) and nonulcerated groups (69/555, 12.4%, P < .05, odds ratio = 2.875).These findings suggested that 256-MSCTA is an advanced imaging tool to determine not only arterial stenosis but also morphologic assessment of atherosclerotic plaques, which will benefit the patients by predicting the cerebral events in advance.

Feasibility of Functional Near-Infrared Spectroscopy (fNIRS) to Investigate the Mirror Neuron System: An Experimental Study in a Real-Life Situation.

The mirror neuron system (MNS), mainly including the premotor cortex (PMC), inferior frontal gyrus (IFG), superior parietal lobule (SPL), and rostral inferior parietal lobule (IPL), has attracted extensive attention as a possible neural mechanism of social interaction. Owing to high ecological validity, functional near-infrared spectroscopy (fNIRS) has become an ideal approach for exploring the MNS. Unfortunately, for the feasibility of fNIRS to detect the MNS, none of the four dominant regions were found in previous studies, implying a very limited capacity of fNIRS to investigate the MNS. Here, we adopted an experimental paradigm in a real-life situation to evaluate whether the MNS activity, including four dominant regions, can be detected by using fNIRS. Specifically, 30 right-handed subjects were asked to complete a table-setting task that included action execution and action observation. A double density probe configuration covered the four regions of the MNS in the left hemisphere. We used a traditional channel-based group analysis and also a ROI-based group analysis to find which regions are activated during both action execution and action observation. The results showed that the IFG, adjacent PMC, SPL, and IPL were involved in both conditions, indicating the feasibility of fNIRS to detect the MNS. Our findings provide a foundation for future research to explore the functional role of the MNS in social interaction and various disorders using fNIRS.