Evaluation of microbial proteolysis in meat products by capillary electrophoresis

AIMS: The available methods for evaluating proteolysis in meat products, particularly the contribution of micro-organisms, are expensive, time-consuming and require an unacceptable sample size. To minimize these problems, two capillary electrophoresis-based methods have been developed. METHODS AND RESULTS: Six Gram-positive, catalase-positive cocci, four moulds and three yeasts, isolated from dry-cured ham, were tested on sterile pork slices. Using the Capillary Gel Electrophoresis (CGE) method, changes in sarcoplasmic and myofibrillar proteins due to endogenous and microbial enzymes were detected. The Capillary Zone Electrophoresis (CZE) analysis allowed evaluation of bulk changes by micro-organisms in soluble nitrogen compounds. CONCLUSION: CGE analysis of myofibrillar proteins and CZE determination of soluble nitrogen compounds have proved to be valuable tools for evaluating proteolytic activity of endogenous and microbial origin. SIGNIFICANCE AND IMPACT OF THE STUDY: The CGE and CZE methods developed can be used for a rapid and sensitive analysis of proteolysis in meat products.     

Thyme and suico essential oils: promising natural tools for potato common scab control

• Potato common scab is a worldwide disease mainly caused by Streptomyces scabiei. It seriously affects potato crops by decreasing tuber quality. Essential oils (EO) are natural products with recognised antimicrobial properties. In this research, the antibacterial activities of thyme, oregano, suico and mint EO against S. scabiei were analysed.
• Infected tubers and soil samples were used for bacterial isolation; the obtained isolates were genetically identified. The chemical composition of the EO was determined by GC‐MS. The broth microdilution method was used to analyse antibacterial properties of EO.
• Thirty‐one bacterial isolates were obtained. The isolate chosen for antibacterial assays was morpho‐physiologically and genetically identified as S. scabiei. Thyme EO was mainly composed of thymol and o‐cymene; suico EO of dihydrotagetone, trans‐tagetone and verbenone; oregano EO of trans‐sabinene hydrate, thymol and ?‐terpinene; and mint EO of menthone and menthol. All the EO tested were effective against S. scabiei, but thyme and suico EO were the most successful, with a minimum inhibitory concentration of 0.068 g·l^?1 and 0.147 g·l^?1, respectively, and a minimum bactericidal concentration of 0.137 g·l^?1 and 0.147 g·l^?1, respectively. Scanning electron microscopy showed similar damage caused by both thyme and suico EO to the bacterial envelope. Total phenolic content of EO was not related to their antibacterial activity.
• Thyme and suico EO are effective antibacterial agents against S. scabiei, impeding bacterial viability and disturbing the bacterial cell envelope. These EO are promising tools for control of potato common scab.

     

High definition bronchoscopy: a randomized exploratory study of diagnostic value compared to standard white light bronchoscopy and autofluorescence bronchoscopy

Background

Videobronchoscopy is an essential diagnostic procedure for evaluation of the central airways and pivotal for the diagnosis and staging of lung cancer. Technological improvements have resulted in high definition (HD) images with advanced real time image enhancement techniques (i-scan).

Objectives

In this study we aimed to explore the sensitivity of HD+ i-scan bronchoscopy for detection of epithelial changes like vascular abnormalities and suspicious preinvasive lesions, and tumors.

Methods

In patients scheduled for a therapeutic or diagnostic procedure under general anesthesia videos of the bronchial tree were made using 5 videobronchoscopy modes in random order: normal white light videobronchoscopy (WLB), HD-bronchoscopy (HD), HD bronchoscopy with surface enhancement technique (i-scan1), HD with surface- and tone enhancement technique (i-scan2) and dual mode autofluorescence videobronchoscopy (AFB). The videos were scored in random order by two independent and blinded expert bronchoscopists.

Results

In 29 patients all videos were available for analysis. Vascular abnormalities were scored most frequently in HD + i-scan2 bronchoscopy (1.33 ± 0.29 abnormal or suspicious sites per patient) as compared to 0.12 ± 0.05 site for AFB (P = 0.003). Sites suspicious for preinvasive lesions were most frequently reported using AFB (0.74 ± 0.12 sites per patient) as compared to 0.17 ± 0.06 for both WLB and HD bronchoscopy (P = 0.003). Tumors were detected equally by all modalities. The preferred modality was HD bronchoscopy with i-scan (tone- plus surface and surface enhancement in respectively 38% and 35% of cases P = 0.006).

Conclusions

This study shows that high definition bronchoscopy with image enhancement technique may result in better detection of subtle vascular abnormalities in the airways. Since these abnormalities may be related to preneoplastic lesions and tumors this is of clinical relevance. Further investigations using this technique relating imaging to histology are warranted.     

The BioLexicon: a large-scale terminological resource for biomedical text mining

Background

Due to the rapidly expanding body of biomedical literature, biologists require increasingly sophisticated and efficient systems to help them to search for relevant information. Such systems should account for the multiple written variants used to represent biomedical concepts, and allow the user to search for specific pieces of knowledge (or events) involving these concepts, e.g., protein-protein interactions. Such functionality requires access to detailed information about words used in the biomedical literature. Existing databases and ontologies often have a specific focus and are oriented towards human use. Consequently, biological knowledge is dispersed amongst many resources, which often do not attempt to account for the large and frequently changing set of variants that appear in the literature. Additionally, such resources typically do not provide information about how terms relate to each other in texts to describe events.

Results

This article provides an overview of the design, construction and evaluation of a large-scale lexical and conceptual resource for the biomedical domain, the BioLexicon. The resource can be exploited by text mining tools at several levels, e.g., part-of-speech tagging, recognition of biomedical entities, and the extraction of events in which they are involved. As such, the BioLexicon must account for real usage of words in biomedical texts. In particular, the BioLexicon gathers together different types of terms from several existing data resources into a single, unified repository, and augments them with new term variants automatically extracted from biomedical literature. Extraction of events is facilitated through the inclusion of biologically pertinent verbs (around which events are typically organized) together with information about typical patterns of grammatical and semantic behaviour, which are acquired from domain-specific texts. In order to foster interoperability, the BioLexicon is modelled using the Lexical Markup Framework, an ISO standard.

Conclusions

The BioLexicon contains over 2.2 M lexical entries and over 1.8 M terminological variants, as well as over 3.3 M semantic relations, including over 2 M synonymy relations. Its exploitation can benefit both application developers and users. We demonstrate some such benefits by describing integration of the resource into a number of different tools, and evaluating improvements in performance that this can bring.     

Effects of seasonal and decadal warming on soil enzymatic activity in a P‐deficient Mediterranean shrubland

Soil enzymes are central in the response of terrestrial ecosystems to climate change, and their study can be crucial for the models’ implementation. We investigated for 1 year the effects of warming and seasonality on the potential activities of five soil extracellular enzymes and their relationships with soil moisture, phosphorus (P) concentration, and other soil parameters in a P‐limited Mediterranean semiarid shrubland. The site was continuously subjected to warming since 1999, and we compared data from this study to analogous data from 2004. Warming uniformly increased all enzymes activities, but only when a sufficient amount of soil water was available. Seasonality unevenly altered enzyme activities, thus affecting enzymatic stoichiometry. P deficiency affected enzymatic stoichiometry, favoring the activities of the phosphatases. The effect of warming was stronger in 2014 than 2004, excluding the hypothesis of acclimation of rhizospheric responses to higher temperatures and suggesting that further increases in extracellular enzymatic activities are to be expected if sufficient water is available. Climatic warming will likely generally stimulate soil enzymatic activities and accelerate nutrient mineralization and similar ecological processes such as the production and degradation of biomass and changes in community composition, but which will be limited by water availability, especially in Mediterranean soils in summer. Winters in such ecosystems will benefit from a general increase in activity and production, but biological activity could even decrease in summer, potentially leading to a negative overall balance of nutrient mineralization. This study suggests that a general increase in activity due to warming could lead to faster mineralization of soil organic matter and water consumption in colder climates, until one of these factors in turn becomes limiting. Such trade‐offs between water and temperature in relation with enzyme activity should be considered in biogeochemical models.     

Application of Artificial Intelligence/Machine Vision & Learning for the Development of a Live Single-cell Phenotypic Biomarker Test to Predict Prostate Cancer Tumor Aggressiveness

To assess the usefulness and applications of machine vision (MV) and machine learning (ML) techniques that have been used to develop a single cell-based phenotypic (live and fixed biomarkers) platform that correlates with tumor biological aggressiveness and risk stratification, 100 fresh prostate samples were acquired, and areas of prostate cancer were determined by post-surgery pathology reports logged by an independent pathologist. The prostate samples were dissociated into single-cell suspensions in the presence of an extracellular matrix formulation. These samples were analyzed via live-cell microscopy. Dynamic and fixed phenotypic biomarkers per cell were quantified using objective MV software and ML algorithms. The predictive nature of the ML algorithms was developed in two stages. First, random forest (RF) algorithms were developed using 70% of the samples. The developed algorithms were then tested for their predictive performance using the blinded test dataset that contained 30% of the samples in the second stage. Based on the ROC (receiver operating characteristic) curve analysis, thresholds were set to maximize both sensitivity and specificity. We determined the sensitivity and specificity of the assay by comparing the algorithm-generated predictions with adverse pathologic features in the radical prostatectomy (RP) specimens. Using MV and ML algorithms, the biomarkers predictive of adverse pathology at RP were ranked and a prostate cancer patient risk stratification test was developed that distinguishes patients based on surgical adverse pathology features. The ability to identify and track large numbers of individual cells over the length of the microscopy experimental monitoring cycles, in an automated way, created a large biomarker dataset of primary biomarkers. This biomarker dataset was then interrogated with ML algorithms used to correlate with post-surgical adverse pathology findings. Algorithms were generated that predicted adverse pathology with >0.85 sensitivity and specificity and an AUC (area under the curve) of >0.85. Phenotypic biomarkers provide cellular and molecular details that are informative for predicting post-surgical adverse pathologies when considering tumor biopsy samples. Artificial intelligence ML-based approaches for cancer risk stratification are emerging as important and powerful tools to compliment current measures of risk stratification. These techniques have capabilities to address tumor heterogeneity and the molecular complexity of prostate cancer. Specifically, the phenotypic test is a novel example of leveraging biomarkers and advances in MV and ML for developing a powerful prognostic and risk-stratification tool for prostate cancer patients.     

Novel dimeric structure of phage φ29-encoded protein p56: insights into uracil-DNA glycosylase inhibition

Protein p56 encoded by the Bacillus subtilis phage φ29 inhibits the host uracil-DNA glycosylase (UDG) activity. To get insights into the structural basis for this inhibition, the NMR solution structure of p56 has been determined. The inhibitor defines a novel dimeric fold, stabilized by a combination of polar and extensive hydrophobic interactions. Each polypeptide chain contains three stretches of anti-parallel β-sheets and a helical region linked by three short loops. In addition, microcalorimetry titration experiments showed that it forms a tight 2:1 complex with UDG, strongly suggesting that the dimer represents the functional form of the inhibitor. This was further confirmed by the functional analysis of p56 mutants unable to assemble into dimers. We have also shown that the highly anionic region of the inhibitor plays a significant role in the inhibition of UDG. Thus, based on these findings and taking into account previous results that revealed similarities between the association mode of p56 and the phage PBS-1/PBS-2-encoded inhibitor Ugi with UDG, we propose that protein p56 might inhibit the enzyme by mimicking its DNA substrate.     

Oxidative Stress in Rat Retina and Hippocampus after Chronic MDMA (‘ecstasy’) Administration

The effects of MDMA administration on oxidative stress markers in rat eye and hippocampus, and the neuroprotective effects of the antioxidant 3,4-dihydro-6-hydroxy-7-methoxy-2,2-dimethyl-1(2H)-benzopyran (CR-6) have been studied. MDMA effects on liver were used for comparison with those in eye and hippocampus and to test CR-6 protective effects. Another goal was to test for apoptosis in retinal cells, as it is known that happens in liver and brain. After 1 week of ecstasy administration, malondialdehyde (MDA) concentration increased, glutathione peroxidase (GPx) activity and glutathione (GSH) content decreased in liver, as previously described. MDA concentration increased and GPx activity decreased in hippocampus; whereas no change was observed in GSH concentration. MDMA decreased ocular GSH concentration and GPx activity; no change was observed in MDA concentration. The number of TUNEL-positive nuclei increased significantly in rat retinas after 1 week of MDMA administration. CR-6 normalized the modifications in liver, hippocampus and retina mentioned above.     

Quirks of dye nomenclature. 3. Trypan blue

Trypan blue is colorant from the 19^th century that has an association with Africa as a chemotherapeutic agent against protozoan (Trypanosomal) infections, which cause sleeping sickness. The dye still is used for staining biopsies, living cells and organisms, and it also has been used as a colorant for textiles.     

Clinical Patterns and Treatment Outcome in Patients with Melancholic,Atypical and Non-Melancholic Depressions

Objective

To assess sociodemographic, clinical and treatment factors as well as depression outcome in a large representative clinical sample of psychiatric depressive outpatients and to determine if melancholic and atypical depression can be differentiated from residual non-melancholic depressive conditions.

Subjects/Materials and Method

A prospective, naturalistic, multicentre, nationwide epidemiological study of 1455 depressive outpatients was undertaken. Severity of depressive symptoms was assessed by the Hamilton Depression Rating Scale (HDRS) and the Self Rated Inventory of Depressive Symptomatology (IDS-SR₃₀). IDS-SR₃₀ defines melancholic and atypical depression according to DSM-IV criteria. Assessments were carried out after 6–8 weeks of antidepressant treatment and after 14–20 weeks of continuation treatment.

Results

Melancholic patients (16.2%) were more severely depressed, had more depressive episodes and shorter episode duration than atypical (24.7%) and non-melancholic patients. Atypical depressive patients showed higher rates of co-morbid anxiety disorders and substance abuse. Melancholic patients showed lower rates of remission.

Conclusion

Our study supports a different clinical pattern and treatment outcome for melancholic and atypical depression subtypes.