Rapid and accurate screening of cystic echinococcosis in sheep based on serum Fourier-transform infrared spectroscopy combined with machine learning algorithms.

Cystic echinococcosis (CE) in sheep is a serious zoonotic parasitic disease caused by Echinococcus granulosus sensu stricto (s.s.). Presently, the screening technology for CE in sheep is time-consuming and inaccurate, and novel screening technology is urgently needed. In this work, we combined machine-learning algorithms with Fourier transform infrared (FT-IR) spectroscopy of serum to establish a quick and accurate screening approach for CE in sheep. Serum samples from 77 E. granulosus s.s.-infected sheep to 121 healthy control sheep were measured by FT-IR spectrometer. To optimize the classification accuracy of the serum FI-TR method for the E. granulosus s.s.-infected sheep and healthy control sheep, principal component analysis (PCA), linear discriminant analysis, and support vector machine (SVM) algorithms were used to analyze the data. Among all the bands, 1500-1700 cm-1 band has the best classification effect; its diagnostic sensitivity, specificity, and accuracy of PCA-SVM were 100%, 95.74%, and 96.66%, respectively. The study showed that serum FT-IR spectroscopy combined with machine learning algorithms has great potential for rapid and accurate screening methods for the CE in sheep.

Characterization of antioxidant compounds extracted from Citrus reticulata cv. Chachiensis using UPLC-Q-TOF-MS/MS, FT-IR and scanning electron microscope.

Citrus reticulata cv. Chachiensis (CRC) has been widely used in many Chinese medicine prescriptions and developed as various health products. Due to its extensive biological activities, increased interest has focused on CRC as a potential source for the treatment of various diseases. However, there is no systematic and sufficient research on optimization and characterization of ultrasound extraction of antioxidant compounds from CRC up to now. In the present work, three parameters including ultrasonic amplitude (45, 55, 70, 85, 95 %), ultrasonic time (26, 40, 60, 80, 94 min) and ethanol concentration (16, 30, 50, 70, 84 %, v/v) were estimated using central-composite design. Determined optimum conditions, considering four responses (TPC, TFC, DPPH and ABTS) at the same time, were 72 % amplitude, 80 min and 70 % ethanol concentration. The maximum yields were TPC values (145.73 mg GAE/g), TFC values (135.21 mg QE/g), DPPH and ABTS scavenging capacity (87.88 and 76.18 mg TE/g, respectively). 55 phytochemicals were identified in the CRC extract using the UPLC-QTOF-MS/MS, 34 of which were flavonoids, which provided important support for various potential applications of CRC.

Prediction model optimization using full model selection with regression trees demonstrated with FTIR data from bovine milk.

Predictive modeling is the development of a model that is best able to predict an outcome based on given input variables. Model algorithms are different processes that are used to define functions that transform the data within models. Common algorithms include logistic regression (LR), linear discriminant analysis (LDA), classification and regression trees (CART), naïve Bayes (NB), and k-nearest neighbor (KNN). Data preprocessing option, such as feature extraction and reduction, and model algorithms are commonly selected empirically in epidemiological studies even though these decisions can significantly affect model performance. Accordingly, full model selection (FMS) methods were developed to provide a systematic approach to select predictive modeling methods; however, current limitations of FMS, such as its dependency on user-selected hyperparameters, have prevented their routine incorporation into analyses for model performance optimization. Here we present the use of regression trees as an innovative method to apply FMS. Regression tree FMS (rtFMS) requires the development of a model for every combination of predictive modeling method options under consideration. The iterated, cross-validation performances of these models are then passed through a regression tree for selection of a final model. We demonstrate the benefits of rtFMS using a milk Fourier transform infrared spectroscopy dataset, wherein we build prediction models for two blood metabolic health parameters in dairy cows, nonesterified fatty acids (NEFA) and ß-hydroxybutyrate acid (BHBA). The goal for building NEFA and BHBA prediction models is to provide a milk-based screening tool for metabolic health in dairy cattle that can be incorporated automatically in milk analysis routines. These models could be used in conjunction with physical exams, cow side tests, and other indications to initiate medical intervention. In contrast to previously reported FMS methods, rtFMS is not a black box, is simple to implement and interpret, it does not have hyperparameters, and it illustrates the relative importance of modeling options. Additionally, rtFMS allows for indirect comparisons among models developed using different datasets. Finally, rtFMS eliminates user bias due to personal preference for certain methods and rtFMS removes the dependency on published comparisons of methods. Thus, rtFMS provides clear benefits over the empirical selection of data preprocessing options and model algorithms.

Lignin Degradation Efficiency of Chemical Pre-Treatments on Banana Rachis Destined to Bioethanol Production.

Valuable biomass conversion processes are highly dependent on the use of effective pretreatments for lignocellulose degradation and enzymes for saccharification. Among the nowadays available treatments, chemical delignification represents a promising alternative to physical-mechanical treatments. Banana is one of the most important fruit crops around the world. After harvesting, it generates large amounts of rachis, a lignocellulosic residue, that could be used for second generation ethanol production, via saccharification and fermentation. In the present study, eight chemical pretreatments for lignin degradation (organosolv based on organic solvents, sodium hypochlorite, hypochlorous acid, hydrogen peroxide, alkaline hydrogen peroxide, and some combinations thereof) have been tested on banana rachis and the effects evaluated in terms of lignin removal, material losses, and chemical composition of pretreated material. Pretreatment based on lignin oxidation have demonstrated to reach the highest delignification yield, also in terms of monosaccharides recovery. In fact, all the delignified samples were then saccharified with enzymes (cellulase and beta-glucosidase) and hydrolysis efficiency was evaluated in terms of final sugars recovery before fermentation. Analysis of Fourier transform infrared spectra (FTIR) has been carried out on treated samples, in order to better understand the structural effects of delignification on lignocellulose. Active chlorine oxidations, hypochlorous acid in particular, were the best effective for lignin removal obtaining in the meanwhile the most promising cellulose-to-glucose conversion.

A microfluidic chip containing a molecularly imprinted polymer and a DNA aptamer for voltammetric determination of carbofuran.

An electrochemical microfluidic chip is described for the determination of the insecticide carbofuran. It is making use of a molecularly imprinted film (MIP) and a DNA aptamer as dual recognition units. The analyte (carbofuran) is transported to the MIP and captured at the identification site in the channel. Then, carbofuran is eluted with carbinol-acetic acid and transported to the DNA aptamer on the testing position of the chip. It is captured again, this time by the aptamer, and detected by differential pulse voltammetry (DPV). The dual recognition (by aptamer and MIP) results in outstanding selectivity. Additionally, graphene oxide-supported gold nanoparticles (GO-AuNPs) were used to improve the sensitivity of electrochemical detector. DPV response is linear in the 0.2 to 50 nM carbofuran concentration range at a potential of -1.2 V, with a 67 pM detection limit. The method has attractive features such as its potential for high throughput, high degree of automation, and high integration. Conceivably, the method may be extended to other analytes for which appropriate MIPs and aptamers are available. Graphical abstract Schematic of an electrochemical microfluidic chip for carbofuran detection based on a molecularly imprinted film (MIP) and a DNA aptamer as dual recognition units. In the chip, targets were recognized by MIP and aptamer, respectively. It shows promising potential for the design of electrochemical devices with high throughput, high automation, and high integration.

Magnetic mesoporous polymelamine-formaldehyde resin as an adsorbent for endocrine disrupting chemicals.

A magnetic mesoporous poly(melamine-formaldehyde) composite (Fe3O4-mPMF) was prepared via grafting poly(melamine-formaldehyde) onto the surface of amino-functionalized magnetite (Fe3O4) nanoparticles. The material was characterized by scanning electron micrography, transmission electron microscopy, X-ray diffraction, Fourier transform-infrared spectroscopy, nitrogen adsorption-desorption isotherms, and thermogravimetric analysis. It has a large surface area, a typical mesoporous structure, and a high thermal stability. It was employed as a magnetic sorbent for the solid phase extraction of the following endocrine disrupting chemicals (EDCs): Bisphenol A, 4-tert-butylphenol, 4-tert-octylphenol and nonylphenol. The EDCs were then quantified by HPLC. Under the optimized conditions, the response to the EDCs is linear in the range of 0.5-100 ng·mL-1, and the limits of detection are 0.02-0.1 ng·mL-1. The high adsorption capability of the Fe3O4-mPMF is mainly attributed to multiple interactions including π-stacking, hydrogen bonding, and hydrophobic interactions. The method was applied to the extraction of EDCs from spiked river water and bottled juice samples. The results demonstrated that the Fe3O4-mPMF is an efficient adsorbent for the extraction of organic compounds with large conjugated π-system, plenty of hydrogen-bonding sites, and strong hydrophobicity. Graphical abstract A magnetic mesoporous polymelamine-formaldehyde composite (Fe3O4-mPMF) was prepared and employed as a magnetic sorbent for the solid phase extraction of endocrine disrupting chemicals from river water and bottled juice samples prior to high-performance liquid chromatographic analysis.

Effects of ultrasonic treatment during acid hydrolysis on the yield, particle size and structure of cellulose nanocrystals.

Ultrasonic treatment is useful for the isolation of cellulose nanocrystals (CNCs). However, the effects of ultrasonic treatment on the structure and properties of CNCs have not been fully understood. We statistically analyzed the variations in yields and dimensions of CNCs prepared using acid hydrolysis, with or without ultrasonic treatment, and illustrated these variations by investigating the CNC structures. The results demonstrated that ultrasonic treatment promoted an increase in yields only for short hydrolysis times, while resulting in CNCs with shorter lengths and narrower dimension distributions. Furthermore, a prolonged acid attack under ultrasonic treatment caused a partial dissociation of cellulose hydrogen bond networks in the CNCs, ultimately resulting in the delamination and disorder of the cellulose crystalline structure, thus leading to a decrease in the width and thickness of the CNCs. This work provides more insights into the mechanisms of ultrasonic treatment on the structure and properties of CNCs.

Finding of polysaccharide-peptide complexes in Cordyceps militaris and evaluation of its acetylcholinesterase inhibition activity.

Acetylcholinesterase (AChE) inhibition enhances learning and cognitive ability for treatment of Alzheimer's disease. Polysaccharide-peptide complexes were identified in Cordyceps militaris (CPSPs) and characterized for their AChE inhibitory properties. Three polymers (CPSP-F1, -F2, and -F3) were extracted and separated by ultrasound-assisted extraction and diethylaminoethanol (DEAE)-Sepharose CL-6B column chromatography. Polysaccharide-peptide complexes were identified by DEAE-Sepharose CL-6B column chromatography and high-performance gel-filtration chromatography, Fourier transform infrared spectra, amino sugar composition analysis, and ß-elimination reaction to identify polysaccharide-peptide bond categories. Separation of CPSP can increase AChE inhibitory activity from the crude polysaccharide of C. militaris. CPSP-F1 and CPSP-F2 exhibited half maximal inhibitory concentrations of 32.2 ± 0.2 mg/mL and 5.3 ± 0.0 mg/mL. Thus, we identified polysaccharide-peptide complexes from C. militaris and suggest CPSP has great potential in AChE inhibition bioassay.

Insight into the roles of earthworm in vermicomposting of sewage sludge by determining the water-extracts through chemical and spectroscopic methods.

This work illustrated the effects of earthworm in vermicomposting (Eisenia fetida) by determining the water-extracts through chemical and spectroscopic methods. A field experiment with sludge as the only feed was subjected to vermicomposting and the control (without worms) for three weeks. Compared to the control, vermicomposting resulted in lower pH and water-extractable organic carbon (WEOC) along with higher electrical conductivity (EC). Moreover, vermicomposting caused nearly two times higher content of water-extractable nitrate (WEN-NO3(-)) than the control. Furthermore, fourier transform infrared spectra (FT-IR) revealed that vermicomposting promoted the hydrolysis/transformation of macromolecular organic matters and accelerated the degradation of polysaccharide-like and protein-like materials. Fluorescence spectroscopy also reflected vermicomposting led to higher humification degree than the control. In all, this study supplies a new view to assess the roles of earthworm in vermicomposting of sewage sludge by evaluating the water extracts.

Organic matter humification in vermifiltration process for domestic sewage sludge treatment by excitation-emission matrix fluorescence and Fourier transform infrared spectroscopy.

Performance of a conventional biofilter (BF) and two vermifilters (VFs, different heights) containing earthworms was investigated for domestic sewage sludge (DWS) treatment. Humic-acid like (HAL) fraction isolated from the influent sludge (IS) and effluent sludge of BF (ESBF) and VFs (ESVFs) were determined the elemental and functional composition, and structural characteristics using various analytical approaches. Results showed that performance of DWS treatment in the VFs was preferable to that in the BF. With respect to IS-HAL and ESBF-HAL, ESVFs-HAL had low C, H and N contents and C/O ratio, and high O, carboxyl and phenolic OH group contents, and C/N, C/H and E4/E6 ratios, and large molecular weight. The excitation-emission (Ex/Em) matrix spectra revealed that an additional peak was found at Ex/Em wavelength pairs of 345/435 nm in ESVFs-HAL. Further, Fourier transform infrared spectra showed that vermifiltration led to the loss of aliphatic materials and carbohydrates, and the enrichment of carbonyl and phenolic OH groups in HAL fractions. Additionally, the increase in VF height seemed to accelerate humification degree of organic matter in the effluent sludge. In summary, vermifiltration is alternate technology for transformation of organic matter into humic substances, and thus improves quality of DWS as soil organic fertilizer.

Genetic components of milk Fourier-transform infrared spectra used to predict breeding values for milk composition and quality traits in dairy goats.

The usual practice today is that milk component phenotypes are predicted using Fourier-transform infrared (FTIR) spectra and they are then, together with pedigree information, used in BLUP for calculation of individual estimated breeding values. Here, this is referred to as the indirect prediction (IP) approach. An alternative approach-a direct prediction (DP) method-is proposed, where genetic analyses are directly conducted on the milk FTIR spectral variables. Breeding values of all derived milk traits (protein, fat, fatty acid composition, and coagulation properties, among others) can then be predicted as traits correlated only to the genetic information of the spectra. For the DP, no need exists to predict the phenotypes before calculating breeding values for each of the traits-the genetic analysis is done once for the spectra, and is applicable to all traits derived from the spectra. The aim of the study was to compare the effects of DP and IP of milk composition and quality traits on prediction error variance (PEV) and genetic gain. A data set containing 27,927 milk FTIR spectral observations and milk composition phenotypes (fat, lactose, and protein) belonging to 14,869 goats of 271 herds was used for training and evaluating models. Partial least squares regression was used for calibrating prediction models for fat, protein, and lactose percentages. Restricted maximum likelihood was used to estimate variance components of the spectral variables after principal components analysis was applied to reduce the spectral dimension. Estimated breeding values were predicted for fat, lactose, and protein percentages using DP and IP methods. The DP approach reduced the mean PEV by 3.73, 4.07, and 7.04% for fat, lactose, and protein percentages, respectively, compared with the IP method. Given the reduction in PEV, relative genetic gains were 2.99, 2.78, and 4.85% for fat, lactose, and protein percentages, respectively. We concluded that more accurate estimated breeding values could be found using genetic components of milk FTIR spectra compared with single-trait animal model analyses on phenotypes predicted from the spectra separately. The potential and application is not only limited to milk FTIR spectra, but could also be extended to any spectroscopy techniques implemented in other species and for other traits.

Synthesis and characterization of chitosan tripolyphosphate nanoparticles and its encapsulation efficiency containing Russell's viper snake venom.

Chitosan Tripolyphosphate (CS/TPP) nanoparticle is a biodegradable and nontoxic polysaccharide, used as a carrier for drug delivery. The morphology and particle-size measurements of the nanoparticles were studied by field emission scanning electron microscopy and Fourier Transform Infrared Spectroscopy (FTIR). This study aims to evaluate the impact of Russell's viper venom encapsulation on various factors and loading capacity, in addition to explore the physicochemical structure of nanoparticles. FTIR confirmed that tripolyphosphoric groups of TPP linked with ammonium groups of CS in the nanoparticles. Our results showed that CS can react with TPP to form stable cationic nanoparticles. The results also showed that encapsulation efficiency of venom at different concentrations of 20, 40, 60, 500, and 1000 µg/mL were achieved for CS/TPP nanoparticles at different concentrations of 1.5, 2, and 3 mg/mL. The cytotoxicity of CS/TPP nanoparticles was evaluated by MTT (-3 (4, 5-Dimethylthiazol-2-yl)-2, 5-diphenyltetrazolium bromide, a tetrazole) assay.

Characterization, activity, and computer modeling of a molecular inclusion complex containing rifaldazine.

BACKGROUND: The purpose of this study was to develop, characterize, and investigate a molecular inclusion complex containing rifaldazine with good solubility and antibacterial activity. METHODS: Rifaldazine, a lipophilic molecule, was encapsulated into the hydrophobic cavity of ß-cyclodextrin to form a molecular inclusion complex (RAABCD) with good solubility. RAABCD was prepared in a short time using a solid-state grinding method. The inclusion ratio, binding constant, and change in Gibbs free energy were determined by a phase solubility diagram and/or ultraviolet-visible spectroscopy. Differential scanning calorimetry and Fourier transform infrared spectroscopy of RAABCD were performed. Morphological features of RAABCD were observed by photomicroscopy. The most likely optimal configuration for RAABCD was simulated by computer modeling. Broth macrodilution testing was done to investigate the antibacterial activity of RAABCD. RESULTS: The inclusion ratio, binding constant, and change in Gibbs free energy, determined by a phase solubility diagram and/or ultraviolet-visible spectroscopy were 1:1, 288.33/261.33 L/mol, and 32.29/31.73 kJ/mol, respectively. Differential scanning calorimetry and Fourier transformed infrared spectra of RAABCD confirmed the molecular interaction between rifaldazine and ß-cyclodextrin. The morphological difference between irregular and amorphous-shaped RAABCD and columnar-shaped rifaldazine further confirmed the molecular encapsulation of rifaldazine. The most likely optimal configuration for RAABCD was confirmed by computer modeling. Broth macrodilution testing indicated that RAABCD had good antibacterial activity. CONCLUSION: RAABCD had improved solubility and good activity, and might be a promising alternative for treatment of a range of bacterial infections.

Direct identification of Fritillaria cirrhosa, F. ia thunbergii and F. thunbergii var. chekiangensis by FTIR / 中草药

Object To identify Fritillaria cirrhosa D. Don., Fritillaria thunbergii Miq. and Fritillaria thunbergii Miq. var. chekiangensis Hsiao et K. C. Hsia. with FTIR.Methods Their IR spectra were obtained by direct FTIR.Results The infrared spectra of F. cirrhosa, F. thunbergii, F. thunbergii var. chekiangensis were different.Conclusion F. cirrhosa, F. thunbergii, and F. thunbergii var. chekiangensis were identified by FTIR directly, fastly and accurately.