Inborn Errors of Metabolism in the Era of Untargeted Metabolomics and Lipidomics.

Inborn errors of metabolism (IEMs) are a group of inherited diseases with variable incidences. IEMs are caused by disrupting enzyme activities in specific metabolic pathways by genetic mutations, either directly or indirectly by cofactor deficiencies, causing altered levels of compounds associated with these pathways. While IEMs may present with multiple overlapping symptoms and metabolites, early and accurate diagnosis of IEMs is critical for the long-term health of affected subjects. The prevalence of IEMs differs between countries, likely because different IEM classifications and IEM screening methods are used. Currently, newborn screening programs exclusively use targeted metabolic assays that focus on limited panels of compounds for selected IEM diseases. Such targeted approaches face the problem of false negative and false positive diagnoses that could be overcome if metabolic screening adopted analyses of a broader range of analytes. Hence, we here review the prospects of using untargeted metabolomics for IEM screening. Untargeted metabolomics and lipidomics do not rely on predefined target lists and can detect as many metabolites as possible in a sample, allowing to screen for many metabolic pathways simultaneously. Examples are given for nontargeted analyses of IEMs, and prospects and limitations of different metabolomics methods are discussed. We conclude that dedicated studies are needed to compare accuracy and robustness of targeted and untargeted methods with respect to widening the scope of IEM diagnostics

A hyprid technique for human footprint recognition

Biometrics has concerned a great care recently due to its important in the life that starts from civil applications to security and recently terrorism. A Footprint recognition is one of the personal identifications based on biometric measurements.  The aim of this research is to design a proper and reliable biometric system for human footprint recognition named (FRBS) that stands for Footprint Recognition Biometric System. In addition, to construct a human footprint database which it is very helpful for various use in scientific application e.g. for authentication. There exist many biometrics databases for other identity but very rare for footprint. As well as the existing one are very limited. This paper presents a robust hyprid techniques which merges between Image Processing with Artificial Intelligent technique via Ant Colony Optimization (ACO) to recognize human footprint.  (ACO) plays the essential role that rise the performance and the quality of the results in the biometric system via feature selection. The set of the selected features was treated as exploratory information, and selects the optimum feature set in standings of feature set size. Life RGB footprint images from nine persons with ten images per person constructed from life visual dataset. At first, the visual dataset was pre-processed operations. Each resultant image detects footprint that is cropped to portions represented by three blocks. The first block is for fingers, the second block refers to the center of the foot and the last one determines the heel. Then features were extracted from each image and stored in Excel file to be entered to Ant Colony Optimization Algorithm. The experimental outcomes of the system show that the proposed algorithm evaluates optimal results with smaller feature set comparing with other algorithms. Experimental outcomes show that our algorithm obtains an efficient and accurate result about 100% accuracy in comparison with other researches on the same field

Mixed Statistical Matching Approaches Using a Latent Class Model: Simulation Studies

In the era of data revolution, availability and presence of data is a huge wealth that has to be utilized. Instead of making new surveys, benefit can be made from data that already exists. As, enormous amounts of data become available, it is becoming essential to undertake research that involves integrating data from multiple sources in order to make the best use out of it. Statistical Data Integration (SDI) is the statistical tool for considering this issue. SDI can be used to integrate data files that have common units, and it also allows to merge unrelated files that do not share any common units, depending on the input data. The convenient method of data integration is determined according to the nature of the input data. SDI has two main methods, Record Linkage (RL) and Statistical Matching (SM). SM techniques typically aim to achieve a complete data file from different sources which do not contain the same units. There are a number of traditional matching techniques mentioned in the literature. Among these techniques, there are various approaches for continuous data, but not as many methods for categorical data. This paper proposes a Statistical Matching technique for categorical data based on latent class models within a Bayesian framework. Dirichlet Process Mixture of Product of Multinomial distributions model is used in Statistical Matching throughout this paper which is a fully Bayesian estimation method for latent class models. Performance of the proposed latent class model used for Statistical Matching is evaluated using an empirical comparison with several existing matching procedures based on simulation studies

Sugar Alcohols Have a Key Role in Pathogenesis of Chronic Liver Disease and Hepatocellular Carcinoma in Whole Blood and Liver Tissues.

The major risk factors for hepatocellular carcinoma (HCC) are hepatitis C and B viral infections that proceed to Chronic Liver Disease (CLD). Yet, the early diagnosis and treatment of HCC are challenging because the pathogenesis of HCC is not fully defined. To better understand the onset and development of HCC, untargeted GC-TOF MS metabolomics data were acquired from resected human HCC tissues and their paired non-tumor hepatic tissues (n = 46). Blood samples of the same HCC subjects (n = 23) were compared to CLD (n = 15) and healthy control (n = 15) blood samples. The participants were recruited from the National Liver Institute in Egypt. The GC-TOF MS data yielded 194 structurally annotated compounds. The most strikingly significant alteration was found for the class of sugar alcohols that were up-regulated in blood of HCC patients compared to CLD subjects (p < 2.4 × 10-12) and CLD compared to healthy controls (p = 4.1 × 10-7). In HCC tissues, sugar alcohols were the most significant (p < 1 × 10-6) class differentiating resected HCC tissues from non-malignant hepatic tissues for all HCC patients. Alteration of sugar alcohol levels in liver tissues also defined early-stage HCC from their paired non-malignant hepatic tissues (p = 2.7 × 10-6). In blood, sugar alcohols differentiated HCC from CLD subjects with an ROC-curve of 0.875 compared to 0.685 for the classic HCC biomarker alpha-fetoprotein. Blood sugar alcohol levels steadily increased from healthy controls to CLD to early stages of HCC and finally, to late-stage HCC patients. The increase in sugar alcohol levels indicates a role of aldo-keto reductases in the pathogenesis of HCC, possibly opening novel diagnostic and therapeutic options after in-depth validation

Inhibitory Activity of Silver Nanoparticles and Sodium Hypochlorite against Biofilm Produced by Salmonellae Isolated from Poultry Farms

Salmonella typhimurium and Salmonella enteritidis are among the predominant Salmonella serotypes in the Egyptian poultry farms. Salmonella has the ability to build up biofilms on a variety of surfaces. The antibiofilm activities of silver nanoparticles (AgNPs) and sodium hypochlorite (NaOCL) on prevention and controlling of biofilm by Salmonella spp. was estimated. Silver nanoparticles exhibited bactericidal activity against both S. typhimurium and S. enteritidis with MIC value at 15 µg/ml, while, that of NaOCL was 1600 µg/ml. AgNPs (25 ug/ml) could inhibit biofilm formation at percentages of 84.96% and 78.85% against S. typhimurium and S. enteritidis, respectively. A percentage of 87 % biofilm removal by AgNPS after 3 h contact with the built-up biofilm produced by S. typhimurium and S. enteritidis was recorded. NaOCL (2200 µg/ml) exhibited inhibition percentages of biofilm formation at 83.89% and 75.76% against S. typhimurium and S. enteritidis, respectively. While, biofilm removal percentages after 2 h contact between NaOCL (2200 µg/ml) with the formed biofilm by S. typhimurium and S. enteritidis were 87.42% and 89.37%, respectively. It can be concluded that AgNPs and NaOCl were able to promote a significant reduction of biofilm formation by S. typhimurium and S. enteritidis. Also, AgNPs and NaOCl effectively oppress the mature biofilms formed and the antibiofilm efficiency increased with the increase of contact time with the biofilms

Silver Nanoparticles and Sodium Hypochlorite Inhibitory Effects on Biofilm Produced by Pseudomonas aeruginosa from Poultry Farms

In Egypt, pseudomonas infection is one of the most important problems facing poultry production. Pseudomonas spp. is recognized as a major food spoiler and environmental contaminant. Biofilm formation by P. aeruginosa has an important role in the bacterial pathogenesis as well as persistence in the environment. The antibacterial and antibiofilm activities of AgNPs and NaOCL were evaluated against P. aeruginosa isolated from chicken farms. MIC and MBC of AgNPs against planktonic cells of P. aeruginosa were 15 and 20µg/ml, respectively. While those of NaOCL were 2200 and 2600 µg/ml, respectively. The highest inhibition percentages of biofilm formation (97.9%) was observed when P. aeruginosa treated with AgNPs (25µg/ml). While, 87.5% biofilm removal percentage was achieved after treating the established biofilm with 25 µg/ml AgNPs for 2.5 h. Moreover, NaOCL (2800 µg/ml) was able to cause 96.6% inhibition of biofilm formation and 90.3% biofilm removal after 1.5 h contact. The current study revealed that AgNPs and NaOCL were able to promote a significant reduction and removal of the mature biofilms formed by P. aeruginosa and the antibiofilm efficiency increased with the increase of its contact times with the biofilms

Phytoremediation of Nutrients and Organic Carbon from Sago Mill Effluent using Water Hyacinth (Eichhornia crassipes)

The aim of this study was to investigate the ability of floating water hyacinth (Eichhornia crassipes) to survive under selected concentrations of sago mill effluent (SME) and determine the nutrient uptake by the plant. Phytoremediation at 10, 15, and 20% (VSME/Vwater) SME concentrations by water hyacinth was conducted under greenhouse conditions for 30 d in a batch type experiment. After 30 d of phytoremediation, the removal efficiency of chemical oxygen demand, ammonia and phosphorus from SME wastewater were (86.4% to 97.2%), (91.4% to 97.3%) and (80.4 to 97.2%), respectively. The results proved the efficiency of water hyacinth to polish SME wastewater

The impact of herbal infusion consumption on oxidative stress and cancer: The good, the bad, the misunderstood

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. The release of reactive oxygen species (ROS) and oxidative stress is associated with the development of many ailments, including cardiovascular diseases, diabetes and cancer. The causal link between oxidative stress and cancer is well established and antioxidants are suggested as a protective mechanism against cancer development. Recently, an increase in the consumption of antioxidant supplements was observed globally. The main sources of these antioxidants include fruits, vegetables, and beverage. Herbal infusions are highly popular beverages consumed daily for different reasons. Studies showed the potent antioxidant effects of plants used in the preparation of some herbal infusions. Such herbal infusions represent an important source of antioxidants and can be used as a dietary protection against cancer. However, uncontrolled consumption of herbal infusions may cause toxicity and reduced antioxidant activity. In this review, eleven widely consumed herbal infusions were evaluated for their antioxidant capacities, anticancer potential and possible toxicity. These herbal infusions are highly popular and consumed as daily drinks in different countries. Studies discussed in this review will provide a solid ground for researchers to have better understanding of the use of herbal infusions to reduce oxidative stress and as protective supplements against cancer development

Antimicrobial resistance among migrants in Europe: a systematic review and meta-analysis

BACKGROUND: Rates of antimicrobial resistance (AMR) are rising globally and there is concern that increased migration is contributing to the burden of antibiotic resistance in Europe. However, the effect of migration on the burden of AMR in Europe has not yet been comprehensively examined. Therefore, we did a systematic review and meta-analysis to identify and synthesise data for AMR carriage or infection in migrants to Europe to examine differences in patterns of AMR across migrant groups and in different settings. METHODS: For this systematic review and meta-analysis, we searched MEDLINE, Embase, PubMed, and Scopus with no language restrictions from Jan 1, 2000, to Jan 18, 2017, for primary data from observational studies reporting antibacterial resistance in common bacterial pathogens among migrants to 21 European Union-15 and European Economic Area countries. To be eligible for inclusion, studies had to report data on carriage or infection with laboratory-confirmed antibiotic-resistant organisms in migrant populations. We extracted data from eligible studies and assessed quality using piloted, standardised forms. We did not examine drug resistance in tuberculosis and excluded articles solely reporting on this parameter. We also excluded articles in which migrant status was determined by ethnicity, country of birth of participants' parents, or was not defined, and articles in which data were not disaggregated by migrant status. Outcomes were carriage of or infection with antibiotic-resistant organisms. We used random-effects models to calculate the pooled prevalence of each outcome. The study protocol is registered with PROSPERO, number CRD42016043681. FINDINGS: We identified 2274 articles, of which 23 observational studies reporting on antibiotic resistance in 2319 migrants were included. The pooled prevalence of any AMR carriage or AMR infection in migrants was 25·4% (95% CI 19·1-31·8; I2 =98%), including meticillin-resistant Staphylococcus aureus (7·8%, 4·8-10·7; I2 =92%) and antibiotic-resistant Gram-negative bacteria (27·2%, 17·6-36·8; I2 =94%). The pooled prevalence of any AMR carriage or infection was higher in refugees and asylum seekers (33·0%, 18·3-47·6; I2 =98%) than in other migrant groups (6·6%, 1·8-11·3; I2 =92%). The pooled prevalence of antibiotic-resistant organisms was slightly higher in high-migrant community settings (33·1%, 11·1-55·1; I2 =96%) than in migrants in hospitals (24·3%, 16·1-32·6; I2 =98%). We did not find evidence of high rates of transmission of AMR from migrant to host populations. INTERPRETATION: Migrants are exposed to conditions favouring the emergence of drug resistance during transit and in host countries in Europe. Increased antibiotic resistance among refugees and asylum seekers and in high-migrant community settings (such as refugee camps and detention facilities) highlights the need for improved living conditions, access to health care, and initiatives to facilitate detection of and appropriate high-quality treatment for antibiotic-resistant infections during transit and in host countries. Protocols for the prevention and control of infection and for antibiotic surveillance need to be integrated in all aspects of health care, which should be accessible for all migrant groups, and should target determinants of AMR before, during, and after migration. FUNDING: UK National Institute for Health Research Imperial Biomedical Research Centre, Imperial College Healthcare Charity, the Wellcome Trust, and UK National Institute for Health Research Health Protection Research Unit in Healthcare-associated Infections and Antimictobial Resistance at Imperial College London