Making wood inspection easier: FTIR spectroscopy and machine learning for Brazilian native commercial wood species identification.

The molecular structure of wood is mainly based on cellulose, lignin, and hemicellulose. However, low concentrations of lipids, phenolic compounds, terpenoids, fatty acids, resin acids, and waxes can also be found. In general, their color, smell, texture, quantity, and distribution of pores are used in human sensory analysis to identify native wood species, which may lead to erroneous classification, impairing quality control and inspection of commercialized wood. This study developed a fast and accurate method to discriminate Brazilian native commercial wood species using Fourier Transform Infrared Spectroscopy (FTIR) and machine learning algorithms. It not only solves the limitations of traditional methods but also goes beyond as it allows fast analyses to be obtained at low cost and high accuracy. In this work, we provide the identification of five Brazilian native wood species: Angelim-pedra (Hymenolobium petraeum Ducke), Cambara (Gochnatia polymorpha), Cedrinho (Erisma uncinatum), Champagne (Dipteryx odorata), and Peroba do Norte (Goupia glabra Aubl). The results showed the great potential of FTIR and multivariate analysis for wood sample classification; here, the Linear SVM differentiated the five wood species with an accuracy of 98%. The developed method allows industries, laboratories, companies, and control bodies to identify the nature of the wood product after being extracted and semi-manufactured.

Photodynamic inactivation of methicillin-resistant Staphylococcus aureus by using Giemsa dye as a photosensitizer.

The rise of antibiotic-resistant bacteria calls for innovative approaches to combat multidrug-resistant strains. Here, the potential of the standard histological stain, Giemsa, to act as a photosensitizer (PS) for antimicrobial photodynamic inactivation (aPDI) against methicillin-sensitive Staphylococcus aureus (MSSA) and methicillin-resistant Staphylococcus aureus (MRSA) strains is reported. Bioassays were performed using various Giemsa concentrations (ranging from 0.0 to 20.0 µM) under 625 nm illumination at a light dose of 30 J cm-2. Remarkably, Giemsa completely inhibited the growth of MSSA and MRSA bacterial colonies for concentrations at 10 µM and higher but exhibited no inhibitory effect without light exposure. Partition coefficient analysis revealed Giemsa's affinity for membranes. Furthermore, we quantified the production of reactive oxygen species (ROS) and singlet oxygen (1O2) to elucidate the aPDI mechanisms underlying bacterial inactivation mediated by Giemsa. These findings highlight Giemsa stain's potential as a PS in aPDI for targeting multidrug-resistant bacteria.

A fluorescence-based multivariate method for biodiesel quantification in undiluted diesel-biodiesel blends without sample preparation.

In this work, excitation-emission matrices (EEMs) were used in association with parallel factor analysis (PARAFAC) to assess biodiesel content in undiluted diesel-biodiesel blends (DBBs) without pre-sample preparation. EEMs were decomposed using the PARAFAC (EEMs-PARAFAC), and the loading values of the PARAFAC component as a function of biodiesel content in the blends were used to build an analytical model to quantify the biodiesel content in DBBs. The proposed model presenting a limit of detection (LOD) and a limit of quantification (LOQ) of 2.5% and 11% w/w, respectively, successfully predicted the biodiesel content in the validation samples. The robustness of the model was confirmed by a close analysis of the root mean square error of prediction, standard error of prediction, relative standard deviation of prediction, and Bias. Therefore, an accurate and robust analytical model based on EEMs-PARAFAC was developed to quantify the biodiesel content in undiluted DBBs without sample preparation.

Gene duplication as a major force driving the genome expansion in some giant viruses.

IMPORTANCE: Giant viruses are noteworthy not only due to their enormous particles but also because of their gigantic genomes. In this context, a fundamental question has persisted: how did these genomes evolve? Here we present the discovery of cedratvirus pambiensis, featuring the largest genome ever described for a cedratvirus. Our data suggest that the larger size of the genome can be attributed to an unprecedented number of duplicated genes. Further investigation of this phenomenon in other viruses has illuminated gene duplication as a key evolutionary mechanism driving genome expansion in diverse giant viruses. Although gene duplication has been described as a recurrent event in cellular organisms, our data highlights its potential as a pivotal event in the evolution of gigantic viral genomes.

Automated Matching of Patients to Clinical Trials: A Patient-Centric Natural Language Processing Approach for Pediatric Leukemia.

PURPOSE: Matching patients to clinical trials is cumbersome and costly. Attempts have been made to automate the matching process; however, most have used a trial-centric approach, which focuses on a single trial. In this study, we developed a patient-centric matching tool that matches patient-specific demographic and clinical information with free-text clinical trial inclusion and exclusion criteria extracted using natural language processing to return a list of relevant clinical trials ordered by the patient's likelihood of eligibility. MATERIALS AND METHODS: Records from pediatric leukemia clinical trials were downloaded from ClinicalTrials.gov. Regular expressions were used to discretize and extract individual trial criteria. A multilabel support vector machine (SVM) was trained to classify sentence embeddings of criteria into relevant clinical categories. Labeled criteria were parsed using regular expressions to extract numbers, comparators, and relationships. In the validation phase, a patient-trial match score was generated for each trial and returned in the form of a ranked list for each patient. RESULTS: In total, 5,251 discretized criteria were extracted from 216 protocols. The most frequent criterion was previous chemotherapy/biologics (17%). The multilabel SVM demonstrated a pooled accuracy of 75%. The text processing pipeline was able to automatically extract 68% of eligibility criteria rules, as compared with 80% in a manual version of the tool. Automated matching was accomplished in approximately 4 seconds, as compared with several hours using manual derivation. CONCLUSION: To our knowledge, this project represents the first open-source attempt to generate a patient-centric clinical trial matching tool. The tool demonstrated acceptable performance when compared with a manual version, and it has potential to save time and money when matching patients to trials.

Miniaturized 3D-Printed Cell Enables Water/Ethanol Quantification Using Electrochemical Impedance Spectroscopy.

A miniaturized and low-cost electrochemical 3D-printed system for rapid and accurate quantification of ethanol content in ethanol fuel using electrochemical impedance spectroscopy (EIS) was developed. The monolithic design of the system incorporates insulating thermoplastic electrode separators, with only the cover being mobile, allowing for easy assembly and handling. The portable device, measuring approximately 26 × 24 mm, has a maximum capacity of 1 mL, making it suitable for lab-on-a-chip and portable analysis. By utilizing the dielectric constant of ethanol and ethanol fuel mixtures with water, the miniaturized EIS cell quantifies ethanol content effectively. To validate its performance, we compared measurements from four gas stations with a digital densimeter, and the values obtained from the proposed system matched perfectly. Our miniaturized and low-cost electrochemical 3D-printed device can be printed and assembled in two hours, offering a cost-effective solution for fast and precise ethanol quantification. Its versatility, affordability, and compatibility with lab-on-a-chip platforms make it easily applicable, including for fuel quality control and on-site analysis in remote locations.

Environmentally Safe Photodynamic Control of Aedes aegypti Using Sunlight-Activated Synthetic Curcumin: Photodegradation, Aquatic Ecotoxicity, and Field Trial.

This study reports curcumin as an efficient photolarvicide against Aedes aegypti larvae under natural light illumination. Larval mortality and pupal formation were monitored daily for 21 days under simulated field conditions. In a sucrose-containing formulation, a lethal time 50 (LT50) of 3 days was found using curcumin at 4.6 mg L-1. This formulation promoted no larval toxicity in the absence of illumination, and sucrose alone did not induce larval phototoxicity. The photodegradation byproducts (intermediates) of curcumin were determined and the photodegradation mechanisms proposed. Intermediates with m/z 194, 278, and 370 were found and characterized using LC-MS. The ecotoxicity of the byproducts on non-target organisms (Daphnia, fish, and green algae) indicates that the intermediates do not exhibit any destructive potential for aquatic organisms. The results of photodegradation and ecotoxicity suggest that curcumin is environmentally safe for non-target organisms and, therefore, can be considered for population control of Ae. aegypti.

A new strategy for canine visceral leishmaniasis diagnosis based on FTIR spectroscopy and machine learning.

Visceral leishmaniasis is a neglected disease caused by protozoan parasites of the genus Leishmania. The successful control of the disease depends on its accurate and early diagnosis, which is usually made by combining clinical symptoms with laboratory tests such as serological, parasitological, and molecular tests. However, early diagnosis based on serological tests may exhibit low accuracy due to lack of specificity caused by cross-reactivities with other pathogens, and sensitivity issues related, among other reasons, to disease stage, leading to misdiagnosis. In this study was investigated the use of mid-infrared spectroscopy and multivariate analysis to perform a fast, accurate, and easy canine visceral leishmaniasis diagnosis. Canine blood sera of 20 noninfected, 20 Leishmania infantum, and eight Trypanosoma evansi infected dogs were studied. The data demonstrate that principal component analysis with machine learning algorithms achieved an overall accuracy above 85% in the diagnosis.

Eco-Friendly Production of AuNPs and Their Impact on the Oil Oxidative Stability.

Vegetable oils have been used for different applications and, more recently, as an active host medium to obtain nanoparticles for employment in bionanotechnological applications. Nevertheless, oils are very susceptible to oxidation during production, storage, and transportation because of their chemical composition. Consequently, any modification in their production must be accompanied by an analysis of the oxidative stability. In this study, naked and biocompatible gold nanoparticles (AuNPs) were grown on sunflower oil during sputtering deposition using different deposition times. Size and morphology were determined by transmission electron microscopy (TEM) and their concentrations were found by inductively coupled plasma-optical emission spectroscopy (ICP-OES). Rancimat® method was employed to evaluate the AuNPs influence on the oxidative stability of the vegetable oil. Well-dispersed quasi-spherical NPs were produced with a mean diameter in the 2.9-3.7 nm range and they were concentration-dependent on the deposition time. A concentration of about 11 mg/L, 38 mg/L, and 225 mg/L of AuNPs was obtained for a deposition time of 5 min, 15 min, and 30 min, respectively. The results also revealed that AuNPs negatively affected the oxidative stability of the sunflower oil and exponentially reduced the induction period (IP) with the increase in AuNPs content. IP reductions of 63%, 77%, and 81% were determined for the AuNPs containing samples at 11 mg/L, 38 mg/L, and 225 mg/L. For the first time, it is reported that naked AuNPs promote the rapid degradation of vegetable oil and this points out the need for attention relative to the quality of vegetable oils used to host metal nanoparticles.

FTIR spectroscopy with machine learning: A new approach to animal DNA polymorphism screening.

Technological advances in recent decades, especially in molecular genetics, have enabled the detection of genetic DNA markers associated with productive characteristics in animals. However, the prospection of polymorphisms based on DNA sequencing is still expensive for the reality of many food-producing regions around the world, such as Brazil, demanding more accessible prospecting methods. In the present study, the Fourier transform infrared spectroscopy (FTIR) and machine learning algorithms were used to identify single nucleotide polymorphism (SNP) in animal DNA. The fragments of bovine DNA with well-known polymorphisms were used as a model. The DNA fragments were produced and genotyped by PCR-RFLP and classified according to the genotype (homozygous or heterozygous). FTIR spectra of DNA fragments were analyzed by principal component analysis (PCA) and machine learning algorithms. The best results exhibited 75-95% accuracy in the classification of bovine genotypes. Therefore, FTIR spectroscopy and multivariate analysis can be used as an alternative tool for prospecting polymorphisms in animal DNA. The method can contribute with studies to identify genetic markers associated with animal production and indirectly with food production itself, and reduce pressure on available natural resources.

An atomic model for the human septin hexamer by cryo-EM.

In order to form functional filaments, human septins must assemble into hetero-oligomeric rod-like particles which polymerize end-to-end. The rules governing the assembly of these particles and the subsequent filaments are incompletely understood. Although crystallographic approaches have been successful in studying the separate components of the system, there has been difficulty in obtaining high resolution structures of the full particle. Here we report a first cryo-EM structure for a hexameric rod composed of human septins 2, 6 and 7 with a global resolution of ~3.6 Å and a local resolution of between ~3.0 Å and ~5.0 Å. By fitting the previously determined high-resolution crystal structures of the component subunits into the cryo-EM map, we are able to provide an essentially complete model for the particle. This exposes SEPT2 NC-interfaces at the termini of the hexamer and leaves internal cavities between the SEPT6-SEPT7 pairs. The floor of the cavity is formed by the two α0 helices including their polybasic regions. These are locked into place between the two subunits by interactions made with the α5 and α6 helices of the neighbouring monomer together with its polyacidic region. The cavity may serve to provide space allowing the subunits to move with respect to one another. The elongated particle shows a tendency to bend at its centre where two copies of SEPT7 form a homodimeric G-interface. Such bending is almost certainly related to the ability of septin filaments to recognize and even induce membrane curvature.

Low-cost transcriptional diagnostic to accurately categorize lymphomas in low- and middle-income countries.

Inadequate diagnostics compromise cancer care across lower- and middle-income countries (LMICs). We hypothesized that an inexpensive gene expression assay using paraffin-embedded biopsy specimens from LMICs could distinguish lymphoma subtypes without pathologist input. We reviewed all biopsy specimens obtained at the Instituto de Cancerología y Hospital Dr. Bernardo Del Valle in Guatemala City between 2006 and 2018 for suspicion of lymphoma. Diagnoses were established based on the World Health Organization classification and then binned into 9 categories: nonmalignant, aggressive B-cell, diffuse large B-cell, follicular, Hodgkin, mantle cell, marginal zone, natural killer/T-cell, or mature T-cell lymphoma. We established a chemical ligation probe-based assay (CLPA) that quantifies expression of 37 genes by capillary electrophoresis with reagent/consumable cost of approximately $10/sample. To assign bins based on gene expression, 13 models were evaluated as candidate base learners, and class probabilities from each model were then used as predictors in an extreme gradient boosting super learner. Cases with call probabilities < 60% were classified as indeterminate. Four (2%) of 194 biopsy specimens in storage <3 years experienced assay failure. Diagnostic samples were divided into 70% (n = 397) training and 30% (n = 163) validation cohorts. Overall accuracy for the validation cohort was 86% (95% confidence interval [CI]: 80%-91%). After excluding 28 (17%) indeterminate calls, accuracy increased to 94% (95% CI: 89%-97%). Concordance was 97% for a set of high-probability calls (n = 37) assayed by CLPA in both the United States and Guatemala. Accuracy for a cohort of relapsed/refractory biopsy specimens (n = 39) was 79% and 88%, respectively, after excluding indeterminate cases. Machine-learning analysis of gene expression accurately classifies paraffin-embedded lymphoma biopsy specimens and could transform diagnosis in LMICs.

Intestinal proteases profiling from Anticarsia gemmatalis and their binding to inhibitors.

Although the importance of intestinal hydrolases is recognized, there is little information on the intestinal proteome of lepidopterans such as Anticarsia gemmatalis. Thus, we carried out the proteomic analysis of the A. gemmatalis intestine to characterize the proteases by LC/MS. We examined the interactions of proteins identified with protease inhibitors (PI) using molecular docking. We found 54 expressed antigens for intestinal protease, suggesting multiple important isoforms. The hydrolytic arsenal featured allows for a more comprehensive understanding of insect feeding. The docking analysis showed that the soybean PI (SKTI) could bind efficiently with the trypsin sequences and, therefore, insect resistance does not seem to involve changing the sequences of the PI binding site. In addition, a SERPIN was identified and the interaction analysis showed the inhibitor binding site is in contact with the catalytic site of trypsin, possibly acting as a regulator. In addition, this SERPIN and the identified PI sequences can be targets for the control of proteolytic activity in the caterpillar intestine and serve as a support for the rational design of a molecule with greater stability, less prone to cleavage by proteases and viable for the control of insect pests such as A. gemmatalis.

There is direct relationship between bone bridge length and coracoclavicular fixation resistance to failure: Biomechanical study in a porcine model.

BACKGROUND: This study aims to evaluate the relation between coracoclavicular resistance to failure and the distance between clavicular tunnels. The hypothesis is that a greater clavicular bone bridge between tunnels achieves a stronger coracoclavicular fixation. METHODS: Descriptive Laboratory Study. Thirty-six (36) coracoclavicular models were constructed utilizing porcine metatarsals. Coracoclavicular stabilizations were performed using a subcoracoid loop fixation configuration through two clavicular tunnels, tied at the clavicle's superior cortex using a locking knot. Models were randomly assigned to 1 of 3 experimental groups of variable bone bridge length between clavicular tunnels: 5 mm, 10 mm, and 15 mm. Each group had 12 models. Fixation resistance was assessed through the ultimate failure point under an axial load to failure trial. Failure patterns were documented. A one-way ANOVA test was used, and a Tukey post hoc as needed (P < 0.05). FINDINGS: Mean strength per bone bridge length: 5 mm = 312 N (Range: 182-442 N); 10 mm = 430 N (Range: 368-595 N); 15 mm = 595 N (Range: 441-978 N). The 15 mm group had a significantly higher ultimate failure point than the other two groups: 5 mm (P < 0.001) and 10 mm (P < 0.001). All fixations systematically failed by a superior cortex clavicle fracture at the midpoint between tunnels. INTERPRETATION: A direct relationship between bone bridge length and coracoclavicular resistance to failure was demonstrated, being the 15 mm length a significantly higher strength construct in a tied loop model.

Nucleophilic Fluorination with KF Catalyzed by 18-Crown-6 and Bulky Diols: A Theoretical and Experimental Study.

The activation of potassium fluoride for nucleophilic fluorination of alkyl halides is an important challenge because of the high lattice energy of this salt and its low solubility in many polar aprotic solvents. Crown ethers have been used for increasing the solubilization of KF during several decades. Nevertheless, these macrocycles are not enough to produce a high reaction rate. In this work, theoretical methods were used for designing a synergic combination of bulky diols with crown ethers able to accelerate this kind of reaction. The calculations have predicted that the bulky diol 1,4-Bis(2-hydroxy-2-propyl)benzene, which has distant hydroxyl groups, is able to catalyze nucleophilic fluorination in combination with 18-crown-6 via two hydrogen bonds to the SN2 transition state. Experimental studies following the theoretical predictions have confirmed the catalytic effect and the estimated kinetic data point out that the bulky diol at 1 mol L-1 in combination with 18-crown-6 is able to produce an 18-fold increase in the reaction rate in relation to crown ether catalysis only. The reaction produces 46% yield of fluorination after 24 h at moderate temperature of 82 °C, with minimal formation of the side elimination product. Thus, this work presents an improved method for fluorination with KF salt.

Photodynamic Inactivation of Methicillin-Resistant Staphylococcus aureus by a Natural Food Colorant (E-141ii).

This study evaluates the photosensitizing effectiveness of sodium copper chlorophyllin, a natural green colorant commonly used as a food additive (E-141ii), to inactivate methicillin-sensitive and methicillin-resistant Staphylococcus aureus under red-light illumination. Antimicrobial photodynamic inactivation (aPDI) was tested on a methicillin-sensitive reference strain (ATCC 25923) and a methicillin-resistant Staphylococcus aureus strain (GenBank accession number Mh087437) isolated from a clinical sample. The photoinactivation efficacy was investigated by exposing the bacterial strains to different E-141ii concentrations (0.0, 1.0, 2.5, 5.0, 10.0, and 20.0 µM) and to red light (625 nm) at 30 J cm-2. The results showed that E-141ii itself did not prevent bacterial growth for all tested concentrations when cultures were placed in the dark. By contrast, E-141ii photoinactivated both methicillin-sensitive Staphylococcus aureus (MSSA) and methicillin-resistant Staphylococcus aureus (MRSA) under red-light illumination. However, different dose responses were observed for MSSA and MRSA. Whilst the MSSA growth was inhibited to the detection limit of the method with E-141ii at 2.5 µM, >10 µM concentrations were required to inhibit the growth of MRSA. The data also suggest that E-141ii can produce reactive oxygen species (ROS) via Type I reaction by electron transfer from its first excited singlet state to oxygen molecules. Our findings demonstrate that the tested food colorant has great potential to be used in aPDI of MRSA.

Soybean seed vigor discrimination by using infrared spectroscopy and machine learning algorithms.

A novel approach to distinguish soybean seed vigor based on Fourier transform infrared spectroscopy (FTIR) associated with chemometric methods is presented. Batches with high and low vigor soybean seeds were analyzed. Support vector machine (SVM), K-nearest neighbors (KNN), and discriminant analysis were applied to the raw spectral and reduced-dimensionality data from PCA (principal component analysis). Proteins, fatty acids, and amides were identified as the main molecules responsible for the discrimination of the batches. The cross-validation tests pointed out that high vigor soybean seeds were successfully discriminated from low vigor ones with an accuracy of 100%. These findings indicate FTIR spectroscopy associated with multivariate analysis as a new alternative approach to discriminate seed vigor.

Optimization of aqueous two-phase micellar system for partial purification of L-asparaginase from Penicillium sp. grown in wheat bran as agro-industrial residue.

L-asparaginase has been used in the remission of malignant neoplasms such as acute lymphoblastic leukemia. The search for new sources of this enzyme has become attractive for therapeutics. Traditional methods for biomolecule purification involve several steps. A two-phase system may be a good strategy to anticipate one of these stages. This study aimed to produce and purify a fungal L-asparaginase through an aqueous two-phase micellar system (ATPMS) using Triton X-114. The fungus Penicillium sp.-encoded 2DSST1 was isolated from Cerrado soil. Plackett-Burman design followed by a 24 full factorial design was used to determine the best conditions to produce L-asparaginase. The evaluated variables were L-asparagine, L-proline, wheat bran, potato dextrose broth, ammonium sulfate, yeast extract, sucrose and glucose concentrations, incubation temperature, incubation period, and initial pH of the culture medium. L-asparaginase quantification was valued by the formation of ß-aspartyl hydroxamate. The significant positive variables, L-asparagine, L-proline, potato dextrose broth, and sucrose concentrations, were evaluated at 2 levels (+ 1 and - 1) with triplicate of the central point. After 34 runs, maximum activity (2.33 IU/mL) was achieved at the factorial design central point. A central composite design was performed in ATPMS at two levels (+ 1 and - 1) varying Triton X-114 concentration (w/v), separation phase temperature, and crude extract concentration (w/v). The L-asparaginase partition coefficient (K) was considered the experimental design response. Out of the 16 systems that were examined, the most promising presented a purification factor of 1.4 and a yield of 100%.

Portland Cement/Acrocomia Aculeata Endocarp Bricks: Thermal Insulation and Mechanical Properties.

In the last few decades, Portland/residue composites have been researched due to their technological and environmental advantages. In this study, residues of Acrocomia aculeata (Jacq.) Lodd endocarp (AE) were introduced in the Portland cement-soil (PC) matrix in different concentrations (0, 5, 10, 15, 20, and 50 wt%) to produce PC/AE bricks. The characterization of the microstructures of the bricks indicate agglomerates of AE particles with increased humidity in small regions distributed throughout the matrix. Mid-infrared and laser-induced breakdown spectroscopy, along with thermogravimetry, indicated that AE contained mainly lignin and cellulose, as well as inorganic chemical elements such as Mg and Si. X-ray studies revealed that AE did not affect the crystallographic properties of the Portland/AE bricks. The findings indicate that the use of AE improved the thermal insulation capability of the composites with a small impact on the compressive strength.

Noncompetitive tight-binding inhibition of Anticarsia gemmatalis trypsins by Adenanthera pavonina protease inhibitor affects larvae survival.

The economic loss in soybean crops caused by the Lepidoptera insects has encouraged the search for new strategies to control this pest, which are currently based on synthetic insecticides. This paper evaluated the ability of ApTI (Adenanthera pavonina trypsin inhibitor) to inhibit trypsin-like proteins from Anticarsia gemmatalis by docking, molecular dynamics, and enzymatic and survival assay. The docking and molecular dynamic simulation between trypsin and ApTI were performed using the program CLUSPRO and NAMD, respectively. The inhibitory constant Ki and the inhibition type were determined through chromogenic assays. The survival assay of neonatal larvae under treatment with artificial diet supplemented with ApTI was also performed. The ApTI binding site was predicted to block substrate access to trypsin due to four interactions with the enzyme, producing a complex with a surface area of 1,183.7 Å2 . The kinetic analysis revealed a noncompetitive tight-binding mechanism. The survival curves obtained using Kaplan-Meier estimators indicated that the highest larvae mortality was 60%, using 1.2 mg of ApTI per 100 ml of artificial diet. The in vitro, in vivo, and in silico studies demonstrated that ApTI is a strong noncompetitive inhibitor of trypsin with biotechnological potential for the control of A. gemmatalis insect.