Surgical Proposition of a Slow-Growing Calvarial Exostosis in a Female Patient With a Congenital Iris Cyst of the Anterior Chamber and Mandibular Tori.

We present an unusual case of a woman in her early 50s with a slow-growing calvarial exostosis. Exostoses are bony spurs or osteomas extending outward beyond a bone's surface and may be benign or malignant. Calvarial exostoses are a less common bone tumor that can occur in the population. We present a case of a rare, slow-growing calvarial exostosis with a combination of mandibular tori and a congenital iris cyst. We discuss differentials of this exostosis and different syndromes that may cause it such as hereditary multiple exostoses and Gardner syndrome. The current article aims to spread awareness of this atypical presentation of exostoses and present our institution's surgical proposition for removing a calvarial exostosis to obtain a further histological analysis of its composition. As these masses may commonly be benign, a definitive diagnosis cannot be made through imaging alone to rule out more threatening conditions. We have addressed radiological findings and diagnostic and treatment options offered to the patient. The patient decided not to move forward with removing the mass and would continue to monitor and return should she notice any unusual or acute changes.

Rethinking the applicability domain analysis in QSAR models.

Notwithstanding the wide adoption of the OECD principles (or best practices) for QSAR modeling, disparities between in silico predictions and experimental results are frequent, suggesting that model predictions are often too optimistic. Of these OECD principles, the applicability domain (AD) estimation has been recognized in several reports in the literature to be one of the most challenging, implying that the actual reliability measures of model predictions are often unreliable. Applying tree-based error analysis workflows on 5 QSAR models reported in the literature and available in the QsarDB repository, i.e., androgen receptor bioactivity (agonists, antagonists, and binders, respectively) and membrane permeability (highest membrane permeability and the intrinsic permeability), we demonstrate that predictions erroneously tagged as reliable (AD prediction errors) overwhelmingly correspond to instances in subspaces (cohorts) with the highest prediction error rates, highlighting the inhomogeneity of the AD space. In this sense, we call for more stringent AD analysis guidelines which require the incorporation of model error analysis schemes, to provide critical insight on the reliability of underlying AD algorithms. Additionally, any selected AD method should be rigorously validated to demonstrate its suitability for the model space over which it is applied. These steps will ultimately contribute to more accurate estimations of the reliability of model predictions. Finally, error analysis may also be useful in "rational" model refinement in that data expansion efforts and model retraining are focused on cohorts with the highest error rates.

Complex Networks Analyses of Antibiofilm Peptides: An Emerging Tool for Next-Generation Antimicrobials' Discovery.

Microbial biofilms cause several environmental and industrial issues, even affecting human health. Although they have long represented a threat due to their resistance to antibiotics, there are currently no approved antibiofilm agents for clinical treatments. The multi-functionality of antimicrobial peptides (AMPs), including their antibiofilm activity and their potential to target multiple microbes, has motivated the synthesis of AMPs and their relatives for developing antibiofilm agents for clinical purposes. Antibiofilm peptides (ABFPs) have been organized in databases that have allowed the building of prediction tools which have assisted in the discovery/design of new antibiofilm agents. However, the complex network approach has not yet been explored as an assistant tool for this aim. Herein, a kind of similarity network called the half-space proximal network (HSPN) is applied to represent/analyze the chemical space of ABFPs, aiming to identify privileged scaffolds for the development of next-generation antimicrobials that are able to target both planktonic and biofilm microbial forms. Such analyses also considered the metadata associated with the ABFPs, such as origin, other activities, targets, etc., in which the relationships were projected by multilayer networks called metadata networks (METNs). From the complex networks' mining, a reduced but informative set of 66 ABFPs was extracted, representing the original antibiofilm space. This subset contained the most central to atypical ABFPs, some of them having the desired properties for developing next-generation antimicrobials. Therefore, this subset is advisable for assisting the search for/design of both new antibiofilms and antimicrobial agents. The provided ABFP motifs list, discovered within the HSPN communities, is also useful for the same purpose.

Indigenous-Amazonian Traditional Medicine's Usage of the Tobacco Plant: A Transdisciplinary Ethnopsychological Mixed-Methods Case Study.

Harmful usage of tobacco is a global public health problem associated with adverse health effects and addiction. Yet, in the Peruvian Amazon, the native region of Nicotiana rustica L., this plant is used in remarkably different manners: it is considered a potent medicinal plant, applied in liquid form for oral ingestion to treat mental health problems, a common and ancient healing practice in this region. Using a transdisciplinary field research approach with mixed ethnopsychological methods, this work aimed to report for the first time a case study in this context. The intervention took place in the Peruvian Amazon (Loreto) and involved ritual tobacco ingestion in a weeklong retreat-like frame, administered by a specialized traditional Amazonian healer. The patient was a 37-year-old woman with diagnosed mood, anxiety, and attention deficit disorders, as well as a chronic somatic condition. We applied qualitative experience-sampling during and quantitative symptom assessments pre- and post-treatment. Our findings offer a detailed description of the experiential therapeutic process during the treatment week and suggest clinically relevant improvements in patient well-being. This work is significant in view of the globally prevalent harmful uses of tobacco and the current scientific trend of revisiting herbal psychoactives (e.g., cannabis, psilocybin) for their therapeutic potentials.

Searching glycolate oxidase inhibitors based on QSAR, molecular docking, and molecular dynamic simulation approaches.

Primary hyperoxaluria type 1 (PHT1) treatment is mainly focused on inhibiting the enzyme glycolate oxidase, which plays a pivotal role in the production of glyoxylate, which undergoes oxidation to produce oxalate. When the renal secretion capacity exceeds, calcium oxalate forms stones that accumulate in the kidneys. In this respect, detailed QSAR analysis, molecular docking, and dynamics simulations of a series of inhibitors containing glycolic, glyoxylic, and salicylic acid groups have been performed employing different regression machine learning techniques. Three robust models with less than 9 descriptors-based on a tenfold cross (Q2 CV) and external (Q2 EXT) validation-were found i.e., MLR1 (Q2 CV = 0.893, Q2 EXT = 0.897), RF1 (Q2 CV = 0.889, Q2 EXT = 0.907), and IBK1 (Q2 CV = 0.891, Q2 EXT = 0.907). An ensemble model was built by averaging the predicted pIC50 of the three models, obtaining a Q2 EXT = 0.933. Physicochemical properties such as charge, electronegativity, hardness, softness, van der Waals volume, and polarizability were considered as attributes to build the models. To get more insight into the potential biological activity of the compouds studied herein, docking and dynamic analysis were carried out, finding the hydrophobic and polar residues show important interactions with the ligands. A screening of the DrugBank database V.5.1.7 was performed, leading to the proposal of seven commercial drugs within the applicability domain of the models, that can be suggested as possible PHT1 treatment.

Fuzzy spherical truncation-based multi-linear protein descriptors: From their definition to application in structural-related predictions.

This study introduces a set of fuzzy spherically truncated three-dimensional (3D) multi-linear descriptors for proteins. These indices codify geometric structural information from kth spherically truncated spatial-(dis)similarity two-tuple and three-tuple tensors. The coefficients of these truncated tensors are calculated by applying a smoothing value to the 3D structural encoding based on the relationships between two and three amino acids of a protein embedded into a sphere. At considering, the geometrical center of the protein matches with center of the sphere, the distance between each amino acid involved in any specific interaction and the geometrical center of the protein can be computed. Then, the fuzzy membership degree of each amino acid from an spherical region of interest is computed by fuzzy membership functions (FMFs). The truncation value is finally a combination of the membership degrees from interacting amino acids, by applying the arithmetic mean as fusion rule. Several fuzzy membership functions with diverse biases on the calculation of amino acids memberships (e.g., Z-shaped (close to the center), PI-shaped (middle region), and A-Gaussian (far from the center)) were considered as well as traditional truncation functions (e.g., Switching). Such truncation functions were comparatively evaluated by exploring: 1) the frequency of membership degrees, 2) the variability and orthogonality analyses among them based on the Shannon Entropy's and Principal Component's methods, respectively, and 3) the prediction performance of alignment-free prediction of protein folding rates and structural classes. These analyses unraveled the singularity of the proposed fuzzy spherically truncated MDs with respect to the classical (non-truncated) ones and respect to the MDs truncated with traditional functions. They also showed an improved prediction power by attaining an external correlation coefficient of 95.82% in the folding rate modelling and an accuracy of 100% in distinguishing structural protein classes. These outcomes are better than the ones attained by existing approaches, justifying the theoretical contribution of this report. Thus, the fuzzy spherically truncated-based protein descriptors from MuLiMs-MCoMPAs (http://tomocomd.com/mulims-mcompas) are promising alignment-free predictors for modeling protein functions and properties.

Current developments in the resistance, quality, and production of entomopathogenic fungi.

There is a worldwide concern to achieve food security with a sustainable approach, including the generation and implementation of techniques for the production of high-quality chemical-free crops. This food revolution has promoted the development and consolidation of programmes for integrated pest management. Some of those programmes include the use of diverse organisms (biological control agents) to suppress populations of pests potentially harmful to the crops. Among these biological control agents are entomopathogenic fungi that are highly effective in suppressing a diversity of insects and have, therefore, been produced and marketed throughout the world. However, the bottleneck for applying entomopathogenic fungi is the production of propagules (blastospores and conidia) with resistance to environment conditions and abiotic factors, maintaining high quality in terms of virulence. Therefore, this manuscript presents recent studies related to increasing resistance and quality using different bioreactors to produce conidia. The above presents a global panorama related to current developments that contribute to improving the resistance, quality, and production of entomopathogenic fungal propagules.

Sucrose Hydrolysis in a Continuous Packed-Bed Reactor with Auto-immobilise Aspergillus niger Biocatalyst Obtained by Solid-State Fermentation.

Invertase from Aspergillus niger C28B25 was produced by solid-state fermentation (SSF). Fermented solids were used directly as a biocatalyst for batch and continuous hydrolysis of sucrose in a packed-bed reactor under different operational conditions with various temperatures, sucrose concentrations, and feed flow rates. The SSF allowed obtaining a biocatalyst with an invertase activity of 82.2 U/g db. The biocatalyst maintained its activity in the range of 40 to 70 °C for at least 70 h of continuous operation. In a 20-mL packed bed reactor, the highest hydrolysis rate (12.3 g/g db h) was obtained at 40 °C with 2 M sucrose. Continuous hydrolysis in 20-mL and 200-mL reactors at 60 °C led to sucrose hydrolysis above 60% (8.5 residence times) and above 55% (4.5 residence times), respectively. The auto-immobilised biocatalyst produced by SSF without recovery, purification, and immobilisation stages offers an economical alternative for developing accessible biocatalysts that can be applied in batch or continuous sucrose hydrolysis processes. This study shows the potential of biocatalyst production by SSF for other enzymatic systems.

Relationship between lipopeptide biosurfactant and primary metabolite production by Bacillus strains in solid-state and submerged fermentation.

The relationship between lipopeptide and primary metabolite production by Bacillus spp. in solid-state fermentation (SSF) and submerged fermentation (SmF) was evaluated. Four wild-type strains and one mutant strain (unable to develop biofilm) were assessed in SSF and SmF, using a defined medium and polyurethane foam as inert support for SSF. Strain ATCC 21,332 in SSF presented the highest lipopeptide production. The wild-type strains revealed higher lipopeptide and biomass production and lower synthesis of primary metabolites in SSF than in SmF. However, the mutant strain showed a slightly higher production of primary metabolites in SSF than in SmF. Carbon balance analysis showed that the carbon flux was mainly directed to lipopeptides in SSF, whereas in SmF, it was directed to the production of primary metabolites and the carbon flux to lipopeptides is inversely related to primary metabolites in both types of cultures.

Jasmonic acid biosynthesis by fungi: derivatives, first evidence on biochemical pathways and culture conditions for production.

Jasmonic acid (JA) and its derivatives called jasmonates (JAs) are lipid-derived signalling molecules that are produced by plants and certain fungi. Beside this function, JAs have a great variety of applications in flavours and fragrances production. In addition, they may have a high potential in agriculture. JAs protect plants against infections. Although there is much information on the biosynthesis and function of JA concerning plants, knowledge on these aspects is still scarce for fungi. Taking into account the practical importance of JAs, the objective of this review is to summarize knowledge on the occurrence of JAs from fungal culture media, their biosynthetic pathways and the culture conditions for optimal JA production as an alternative source for the production of these valuable metabolites.

"Tobacco Is the Chief Medicinal Plant in My Work": Therapeutic Uses of Tobacco in Peruvian Amazonian Medicine Exemplified by the Work of a Maestro Tabaquero.

INTRODUCTION: Harmful usage of tobacco is a public health problem of global concern and, in many countries, the main risk factor for non-communicable diseases. Yet, in the Peruvian Amazon, the geographical region believed to be tobacco's historical birthplace, this plant is associated with a strikingly different usage and repute: Tobacco (especially Nicotiana rustica L.) in this area is described as a potent medicinal plant, used topically or via ingestion to treat a variety of health conditions. The goal of this transdisciplinary field study was to investigate clinical applications of the tobacco plant as per Amazonian medicine exemplified in the practice of a reputed Maestro Tabaquero, an Amazonian traditional healer whose medical specialization focuses on tobacco-based treatments. METHODS: Using a transdisciplinary clinical approach, we conducted in-depth interviews with the tabaquero applying the systematizing expert interview method, in order to map modes of preparation and administration, indications, contraindications, effects, risks, adverse effects, and systemic aspects of tobacco-based remedies. RESULTS: The informant's descriptions revealed refined knowledge on this plant's therapeutic properties and scope, safety profile, and application techniques. The main indications mentioned included "problems of the mind," of the respiratory system, parasitic illnesses (intestinal/skin), gout, and Amazonian epistemic conditions described as spiritual-energetic in nature. A liquid remedy taken orally was his most commonly used preparation, with acute/sub-acute effects involving a pronounced psychoactive component (altered state of consciousness) and physiological response (emesis, nausea). A skilled tabaquero that knows how to dose, administer, and intervene in case of adverse effects was considered imperative for safe treatment delivery. CONCLUSIONS: To our knowledge, this is the first study employing a transdisciplinary clinical approach to examine therapeutic applications of tobacco by an Amazonian tabaquero. Our findings significantly contribute to the growing research literature on Amazonian medicine and emergent psychedelic-assisted therapies and could, in the long-term, open new treatment avenues in several domains. Forthcoming studies should assess toxicity/safety and clinical outcomes of patients receiving Amazonian tobacco-based treatment.

Solid-state fermentation increases secretome complexity in Aspergillus brasiliensis.

Aspergillus is used for the industrial production of enzymes and organic acids, mainly by submerged fermentation (SmF). However, solid-state fermentation (SSF) offers several advantages over SmF. Although differences related to lower catabolite repression and substrate inhibition, as well as higher extracellular enzyme production in SSF compared to SmF have been shown, the mechanisms undelaying such differences are still unknown. To explain some differences among SSF and SmF, the secretome of Aspergillus brasiliensis obtained from cultures in a homogeneous physiological state with high glucose concentrations was analyzed. Of the regulated proteins produced by SmF, 74% were downregulated by increasing the glucose concentration, whereas all those produced by SSF were upregulated. The most abundant and upregulated protein found in SSF was the transaldolase, which could perform a moonlighting function in fungal adhesion to the solid support. This study evidenced that SSF: (i) improves the kinetic parameters in relation to SmF, (ii) prevents the catabolite repression, (iii) increases the branching level of hyphae and oxidative metabolism, as well as the concentration and diversity of secreted proteins, and (iv) favors the secretion of typically intracellular proteins that could be involved in fungal adhesion. All these differences can be related to the fact that molds are more specialized to growth in solid materials because they mimic their natural habitat.

Computer and Experimental Simulation of Alloxazine Synthesis from Gamma Irradiation of Amino Acids on Iceland Spar: A Prebiotic Chemistry Perspective.

On ancient Earth, environmental conditions favored prebiotic chemical reactions. In the Archean, some molecules with conjugated rings might have been synthesized, displaying structural stability in the Archean in the presence of ionizing radiation and hydration-dehydration events. Additionally, it is suggested that on ancient Earth, calcite was a common mineral promoting organic compound synthesis. In the present work a study of the interaction of amino acid mixtures with the (104) surface of calcite is presented. Our preliminary results show the abiotic synthesis of alloxazine (a flavin with relevant photochemical properties). Computer simulations were performed in HyperChem 8.0.1. by means of MM+ molecular mechanics and PM3 semi-empirical methods, in 27 possible amino acid trimers of alanine, glycine and lysine. Alloxazine formation is possible by the gamma irradiation of amino acids. The computer simulations show that trimers GGG and GGA promote the further transformation from diketopiperazines (DKP's) and KGK to alloxazine. The computer simulations with free radicals are not stable when alloxazine is interacting with the calcite surface. Experiments in anoxygenic environments with hydration-dehydration events in gamma irradiated samples allow the abiotic formation of flavins, DKP's and a heterocycle compound with possible relevance in prebiotic chemistry.

LEGO-based generalized set of two linear algebraic 3D bio-macro-molecular descriptors: Theory and validation by QSARs.

Novel 3D protein descriptors based on bilinear, quadratic and linear algebraic maps in Rn are proposed. The latter employs the kth 2-tuple (dis) similarity matrix to codify information related to covalent and non-covalent interactions in these biopolymers. The calculation of the inter-amino acid distances is generalized by using several dis-similarity coefficients, where normalization procedures based on the simple stochastic and mutual probability schemes are applied. A new local-fragment approach based on amino acid-types and amino acid-groups is proposed to characterize regions of interest in proteins. Topological and geometric macromolecular cutoffs are defined using local and total indices to highlight non-covalent interactions existing between the side-chains of each amino acid. Moreover, local and total indices calculations are generalized considering a LEGO approach, by using several aggregation operators. Collinearity and variability analyses are performed to evaluate every generalizing component applied to the definition of these novel indices. These experiments are oriented to reduce the number of MDs obtained for performing prediction models. The predictive power of the proposed indices was evaluated using two benchmark datasets, folding rate and secondary structural classification of proteins. The proposed MDs are modeled using the following strategies: Multiple Linear Regression (MLR) and Support Vector Machine (SVM), respectively. The best regression model developed for the folding rate of proteins yields a cross-validation coefficient of 0.875 (Test Set) and the best model developed for secondary structural classification obtained 98% of instances correctly classified (Test Set). These statistical parameters are superior to the ones obtained with existing MDs reported in the literature. Overall, the new theoretical generalization enhanced the information extraction into the MDs, allowing a better correlation between these two evaluated benchmark datasets and the proposed indices. The optimal theoretical configurations defined for the calculation of these MDs consider low collinearity and less information redundancy among them. These theoretical configurations and the software are available at http://tomocomd.com/mulims-mcompas.

MuLiMs-MCoMPAs: A Novel Multiplatform Framework to Compute Tensor Algebra-Based Three-Dimensional Protein Descriptors.

This report introduces the MuLiMs-MCoMPAs software (acronym for Multi-Linear Maps based on N-Metric and Contact Matrices of 3D Protein and Amino-acid weightings), designed to compute tensor-based 3D protein structural descriptors by applying two- and three-linear algebraic forms. Moreover, these descriptors contemplate generalizing components such as novel 3D protein structural representations, (dis)similarity metrics, and multimetrics to extract geometrical related information between two and three amino acids, weighting schemes based on amino acid properties, matrix normalization procedures that consider simple-stochastic and mutual probability transformations, topological and geometrical cutoffs, amino acid, and group-based MD calculations, and aggregation operators for merging amino acidic and group MDs. The MuLiMs-MCoMPAs software, which belongs to the ToMoCoMD-CAMPS suite, was developed in Java (version 1.8) using the Chemistry Development Kit (CDK) (version 1.4.19) and the Jmol libraries. This software implemented a divide-and-conquer strategy to parallelize the computation of the indices as well as modules for data preprocessing and batch computing functionalities. Furthermore, it consists of two components: (i) a desktop-graphical user interface (GUI) and (ii) an API library. The relevance of this novel approach is demonstrated through two analyses that considered Shannon's entropy-based variability and a principal component analysis. These studies showed that the MuLiMs-MCoMPAs' three-linear descriptor family contains higher informational entropy than several other descriptors generated with available computation tools. Moreover, the MuLiMs-MCoMPAs indices capture additional orthogonal information to the one codified by the available calculation approaches. As a result, two sets of suggested theoretical configurations that contain 13648 two-linear indices and 20263 three-linear indices are available for download at tomocomd.com . Furthermore, as a demonstration of the applicability and easy integration of the MuLiMs library into a QSAR-based expert system, a software application (ProStAF) was generated to predict SCOP protein structural classes and folding rate. It can thus be anticipated that the MuLiMs-MCoMPAs framework will turn into a valuable contribution to the chem- and bioinformatics research fields.

Modificaciones del espacio óseo posterior para terceros molares desde la infancia hasta la adolescencia / Modifications of the posterior bony space for third molars from childhood to adolescence

Introducción: Del crecimiento de los maxilares depende en gran medida la correcta disposición de los dientes, especialmente de los terceros molares, que son los últimos en brotar. Objetivo: Estimar los cambios en el espacio óseo posterior según la edad y su relación con variables epidemiológicas. Métodos: Se realizó un estudio observacional, descriptivo y transversal en niños pertenecientes al Policlínico Docente "José Martí Pérez" de Santiago de Cuba, de mayo de 2016 a febrero de 2017, para lo cual se utilizaron radiografías panorámicas en las mediciones, analizadas según las variables edad, sexo y color de la piel. Resultados: Sobresalió que la diferencia del espacio óseo posterior de la infancia a la adolescencia fue de 9 mm para el molar 18, de 8,1 para el 28, de 12,5 para el 38 y de 11,5 para el 48; no se observaron diferencias significativas en cuanto a sexo y color de la piel. Conclusiones: Con la evaluación de la magnitud dimensional de dicho espacio es posible predecir el crecimiento de los maxilares para dar ubicación a los terceros molares en el transcurso de la infancia a la adolescencia.

Introduction: The correct disposition of teeth depends in great measure on the growth of maxillary, especially the third molars that are the last ones in eruption. Objective: To estimate the changes in the posterior bony space according to age and its relationship with epidemic variables. Methods: An observational, descriptive and cross-sectional study was carried out in children belonging to José Martí Pérez Teaching Polyclinic in Santiago de Cuba, from May, 2016 to February, 2017, for which panoramic X-rays were used in the measures, analyzed according to age, sex and color of the skin. Results: It was remarkable that the difference of the posterior bony space from childhood to adolescence was 9 mm for 18 molar, of 8.1 for 28 molar, of 12.5 for 38 molar and of 11.5 for 48 molar; significant differences were not observed between sex and color of the skin. Conclusions: With the evaluation of the dimensional magnitude of this space it is possible to predict the growth of the maxillary to give location to the third molars during the course from the childhood to the adolescence.

Tensor Algebra-based Geometrical (3D) Biomacro-Molecular Descriptors for Protein Research: Theory, Applications and Comparison with other Methods.

In this report, a new type of tridimensional (3D) biomacro-molecular descriptors for proteins are proposed. These descriptors make use of multi-linear algebra concepts based on the application of 3-linear forms (i.e., Canonical Trilinear (Tr), Trilinear Cubic (TrC), Trilinear-Quadratic-Bilinear (TrQB) and so on) as a specific case of the N-linear algebraic forms. The definition of the kth 3-tuple similarity-dissimilarity spatial matrices (Tensor's Form) are used for the transformation and for the representation of the existing chemical information available in the relationships between three amino acids of a protein. Several metrics (Minkowski-type, wave-edge, etc) and multi-metrics (Triangle area, Bond-angle, etc) are proposed for the interaction information extraction, as well as probabilistic transformations (e.g., simple stochastic and mutual probability) to achieve matrix normalization. A generalized procedure considering amino acid level-based indices that can be fused together by using aggregator operators for descriptors calculations is proposed. The obtained results demonstrated that the new proposed 3D biomacro-molecular indices perform better than other approaches in the SCOP-based discrimination and the prediction of folding rate of proteins by using simple linear parametrical models. It can be concluded that the proposed method allows the definition of 3D biomacro-molecular descriptors that contain orthogonal information capable of providing better models for applications in protein science.

Enzymatically assisted isolation of high-quality cellulose nanoparticles from water hyacinth stems.

High quality cellulose nanoparticles (CNP) were isolated from water hyacinth stem cellulose (Cel-WH) extracted via successive thermochemical and alkaline-peroxide treatments, and further enzymatically hydrolysed using the commercial cellulase complex, NS22086, at 50ºC. The maximum CNP concentration was reached after 120 min of enzymatic hydrolysis, with a hydrodynamic diameter in the order of 200-250 nm and an increase of 5% in crystallinity as compared with Cel-WH. The obtained rod-shaped cellulose nanocrystals, as revealed by atomic force microscopy (AFM), exhibited a nominal diameter of 15.6-29.4 nm, a length of 56-184.8 nm, and a height of 2.85-6.43 nm, indicating a low tendency to form aggregates. In the present study, it was found that water hyacinth stems are a valuable source for the isolation of high-quality CNP using an environmentally friendly procedure, with potential applications in nanomedicine and nanopharmacology.

Use of water hyacinth as a substrate for the production of filamentous fungal hydrolytic enzymes in solid-state fermentation.

The objective of the present work was to evaluate the water hyacinth (WH) as a substrate for the production of hydrolytic enzymes (cellulases and hemicellulases) of 100 strains of filamentous fungi under conditions of solid growth. Five fungal strains, identified as Trichoderma harzianum, Trichoderma atroviride, Penicillium griseofulvum, Penicillium commune and Aspergillus versicolor, were selected and studied for their ability to grow on water hyacinth as a substrate and carbon source only, evaluating hydrolytic enzymatic activities (α-l-arabinofuranosidase, cellulase, xylanase and ß-d-xylopyranosidase) and extracellular protein per g of water hyacinth dry matter (gdm). The five strains selected were able to produce the four enzymes studied; however, T. harzianum strain PBCA produces the highest xylanase (149.3 ± 14.3 IU/gdm at 108 h), cellulase (16.4 ± 0.6 IU/gdm at 84 h) and ß-d-xylopyranosidase (127.7 ± 14.8 IU/gdm at 48 h). In contrast, the fungus with the highest α-l-arabinofuranosidase activity was A. versicolor, with 129.8 ± 13.3 IU/gdm after 108 h. In conclusion, T. harzianum showed the best production of the hydrolytic enzymes studied, using as a matrix and carbon source, water hyacinth. In addition, catalytic activities of arabinofuranosidase and xylopyranosidase were reported for the first time in T. versicolor and T. harzianum.

A cloud-based computer-aided detection system improves identification of lung nodules on computed tomography scans of patients with extra-thoracic malignancies.

OBJECTIVES: To compare unassisted and CAD-assisted detection and time efficiency of radiologists in reporting lung nodules on CT scans taken from patients with extra-thoracic malignancies using a Cloud-based system. MATERIALS AND METHODS: Three radiologists searched for pulmonary nodules in patients with extra-thoracic malignancy who underwent CT (slice thickness/spacing 2 mm/1.7 mm) between September 2015 and March 2016. All nodules detected by unassisted reading were measured and coordinates were uploaded on a cloud-based system. CAD marks were then reviewed by the same readers using the cloud-based interface. To establish the reference standard all nodules ≥ 3 mm detected by at least one radiologist were validated by two additional experienced radiologists in consensus. Reader detection rate and reporting time with and without CAD were compared. The study was approved by the local ethics committee. All patients signed written informed consent. RESULTS: The series included 225 patients (age range 21-90 years, mean 62 years), including 75 patients having at least one nodule, for a total of 215 nodules. Stand-alone CAD sensitivity for lesions ≥ 3 mm was 85% (183/215, 95% CI: 82-91); mean false-positive rate per scan was 3.8. Sensitivity across readers in detecting lesions ≥ 3 mm was statistically higher using CAD: 65% (95% CI: 61-69) versus 88% (95% CI: 86-91, p<0.01). Reading time increased by 11% using CAD (296 s vs. 329 s; p<0.05). CONCLUSION: In patients with extra-thoracic malignancies, CAD-assisted reading improves detection of ≥ 3-mm lung nodules on CT, slightly increasing reading time. KEY POINTS: • CAD-assisted reading improves the detection of lung nodules compared with unassisted reading on CT scans of patients with primary extra-thoracic tumour, slightly increasing reading time. • Cloud-based CAD systems may represent a cost-effective solution since CAD results can be reviewed while a separated cloud back-end is taking care of computations. • Early identification of lung nodules by CAD-assisted interpretation of CT scans in patients with extra-thoracic primary tumours is of paramount importance as it could anticipate surgery and extend patient life expectancy.