Biologische Vielfalt von auf Hexachlorocyclohexan und verwandten Verbindungen gewachsenen Biofilmgemeinschaften

γ-Hexachlorocyclohexane (γ-HCH) and 4,4`-dibromodiphenylether (BDE) are halogenated pollutants that persist in the environment for a long time. These compounds are very difficult for bacteria and fungi to degrade. However, bacteria and fungi can cooperate within a community making the degradation process easier. The purpose of this work was to determine the extent of the microbial potential for the degradation of γ-HCH and BDE in soils. This study assessed the diversity of bacteria and fungi from 12 soil samples collected around insecticide and pesticide producing factories in Egypt. From γ-HCH and BDE enrichment cultures, all samples yielded highly diverse microbes as revealed by the analyses of the16S rRNA genes for bacteria and 18S rRNA genes for fungi. Soil and sediment samples were used to inoculate γ-HCH and BDE microcrystals on a substratum (PermanoxTM) in microcosms to grow complex biofilm communities on γ-HCH and BDE. The biofilms were monitored over 42 days by community fingerprinting using single strand conformational polymorphism (SSCP) of 16S rRNA and 18S rRNA gene amplicons. All soil samples yielded biofilms on γ-HCH & BDE and SSCP analyses of the biofilms revealed rather diverse bacterial and fungal communities. The structural biofilm development was monitored by Confocal Laser Scanning Microscope (CLSM) using Bac Light Kit, for LIVE (green) / DEAD (red) bacteria and Nile Red to stain hydrophobic compounds and revealed highly diverse biofilms with a dominance of damaged cell at the end of the incubation. From the soil samples, several species were obtained and most of them could use γ-HCH and BDE as sole source of carbon in a minimal medium. While many Gram-positive bacteria were isolated this group was almost absent in the different biofilm communities. Bacteria and fungi in microbial communities play different roles and together they are able to form biofilms using γ-HCH and BDE as a carbon source acting as a functional diversity cooperation.γ-Hexachlorocyclohexan (γ-HCH) und 4,4`-Dibromdiphenylether (BDE) sind halogenierte Gefahrstoffe, welche lange in der Umwelt persistieren und für Bakterien und Pilze nur schwierig abzubauen sind. Bakterien und Pilze können jedoch in Gemeinschaften kooperieren und so den Abbauprozess erleichtern. Das Ziel dieser Arbeit war die Bestimmung des mikrobiellen Potentials in Böden für den Abbau von γ-HCH und BDE. Die Biodiversität von Bakterien und Pilzen wurde in 12 Bodenproben untersucht, welche um Insektizid- und Pestizid-produzierende Fabriken in Ägypten genommen wurden. Anreicherungskulturen auf γ-HCH und BDE ergaben bei allen Proben eine große Vielzahl unterschiedlicher Mikroorganismen, was anhand der Analysen der jeweiligen rRNA Gene gezeigt wurde. Die meisten Stämme konnten diese Substrate als einzige Kohlenstoff- und Energiequelle nutzen. Die Bodenproben wurden zudem als Inocula benutzt, um komplexe Biofilmgemeinschaften auf γ-HCH und BDE Mikrokristallen auf einem Substratum (PermanoxTM) in Mikrokosmen anzuziehen. Die Entwicklung der Biofilme wurde über 42 Tage mittels single strand conformational polymorphism (SSCP) von 16S rRNA und 18S rRNA Gen Amplicons verfolgt. Alle Bodenproben ergaben Biofilme auf γ-HCH & BDE und die SSCP Analysen der Biofilme zeigten recht diverse Bakterien- und Pilz-Gemeinschaften. Die strukturelle Entwicklung der Biofilme wurde durch konfokale Laser Raster-Mikroskopie (CLSM) verfolgt, wobei das Bac Light Kit, für lebende / tote Bakterien und Nilrot zur Färbung hydrophober Verbindungen eingesetzt wurden. Dabei zeigte sich eine große Vielfalt der Biofilme und eine Dominanz von geschädigten Zellen am Ende des Beobachtungszeitraumes. Während viele Gram-positive Bakterien isoliert wurden, fehlte diese Bakteriengruppe in den Biofilmgemeinschaften nahezu völlig. Bakterien und Pilze haben in mikrobiellen Gemeinschaften unterschiedliche Rollen, formen aber dennoch zusammen Biofilme, die zusammen diese Substrate als Kohlenstoffquelle nutzen

Endophytic Bacillus, Enterobacter, and Klebsiella enhance the growth and yield of maize

Endophytic bacteria are those that colonise the internal tissues of plant without negative impact on plant health. This work aims to isolate the endophytic bacteria colonising Triticum vulgare and Phragmites australis and evaluate their compatibility as biostimulants to maize. Three of the six obtained isolates were selected upon their surpassing ability to stimulate the growth of maize seedlings (maximum of 18% increase in germination and 2.4-fold increase in the number of lateral roots). These isolates were molecularly identified as Klebsiella MK2R2, Bacillus B2L2 and Enterobacter E1S2. The response of maize seedlings to the combined effect of these isolates revealed that Bacillus B2L2, containing treatments, surpassed the other treatments in growth vigour parameters and upon this result these treatments were applied in a field experiment either alone or in combination with 100% N fertilisation. Maize plants, inoculated with Klebsiella MK2R2 and Bacillus B2L2 either alone or in combination with Enterobacter E1S2 in the presence of urea, surpassed significantly other treatments as the weight of ear increased almost two times and the number of grains increased 1.8 times compared to the control values. It could be concluded that the obtained strains are compatible biostimulants to maize

Diagnostic accuracy of uterine artery doppler velocimetry in patients with placenta previa

Background; The placenta previa (PP) is an obstetric problem in which the placental tissue is improperly located inside the lower uterine segment. Aim and objectives: was to see how effective uterine artery Doppler velocimetry was in detecting unusually morbidly adhering placentas in patients who had had one or more prior caesarean sections with placenta previa. Subjects and methods; Cross-sectional research of 100 patients was undertaken in the Department of Gynecology and Obstetrics, El- Sayed Galal Hospital, AL- Azhar University. Result; Our results showed highly statistically significant correlation between the presence of abnormal lacunae and histopathological confirmation (P-value > 0.001). In addition, the overall Sensitivity, specificity, PPV, NPV and accuracy were 90%, 100%, 100%, 64.2%, 91.6%. This criterion showed very high sensitivity and specificity with very high positive predictive value and accuracy to become the most important criteria, Conclusion; As a result of this, we conclude that the accuracy of abnormal placental lacunae, loss of the reto-placental clear zone, myometrial thinning, and utero-vesical hypervascularity are the most critical ultrasound criteria for diagnosing placenta accreta in patients who had a previous CS with a placenta previa overlying the previous uterine scar

Plackett–Burman screening of physico-chemical variables affecting Citrus peel-mediated synthesis of silver nanoparticles and their antimicrobial activity

Abstract With the growing resistance of pathogenic microbes to traditional drugs, biogenic silver nanoparticles (SNPs) have recently drawn attention as potent antimicrobial agents. In the present study, SNPs synthesized with the aid of orange (Citrus sinensis) peel were engineered by screening variables affecting their properties via Plackett–Burman design. Among the variables screened (temperature, pH, shaking speed, incubation time, peel extract concentration, AgNO3 concentration and extract/AgNO3 volume ratio), pH was the only variable with significant effect on SNPs synthesis. Therefore, SNPs properties could be enhanced to possess highly regular shape with zeta size of 11.44 nm and zeta potential of − 23.7 mV. SNPs purified, capped and stabilized by cloud point extraction technique were then checked for their antimicrobial activity against Bacillus cereus, Listeria innocua, Listeria monocytogenes, Staphylococcus aureus, Enterobacter cloacae, Escherichia coli, Klebsiella pneumoniae, Pseudomonas aeruginosa, Salmonella typhimurium and Candida albicans. The maximum antimicrobial activity of SNPs was recorded against E. coli, L. monocytogenes and C. albicans with clear zone diameter of 33.2, 31.8 and 31.7 mm, respectively. Based on minimum inhibition concentration and minimum bactericidal concentration of SNPs (300 mg/l) as well as their effect on respiratory chain dehydrogenases, cellular sugar leakage, protein leakage and lipid peroxidation of microbial cells, E. coli was the most affected. Scanning electron microscopy, protein banding and DNA fragmentation proved obvious ultrastructural and molecular alterations of E. coli treated with SNPs. Thus, biogenic SNPs with enhanced properties can be synthesized with the aid of Citrus peel; and such engineered nanoparticles can be used as potent antimicrobial drug against E. coli

Microbial Sensing and Removal of Heavy Metals: Bioelectrochemical Detection and Removal of Chromium(VI) and Cadmium(II)

The presence of inorganic pollutants such as Cadmium(II) and Chromium(VI) could destroy our environment and ecosystem. To overcome this problem, much attention was directed to microbial technology, whereas some microorganisms could resist the toxic effects and decrease pollutants concentration while the microbial viability is sustained. Therefore, we built up a complementary strategy to study the biofilm formation of isolated strains under the stress of heavy metals. As target resistive organisms, Rhizobium-MAP7 and Rhodotorula ALT72 were identified. However, Pontoea agglumerans strains were exploited as the susceptible organism to the heavy metal exposure. Among the methods of sensing and analysis, bioelectrochemical measurements showed the most effective tools to study the susceptibility and resistivity to the heavy metals. The tested Rhizobium strain showed higher ability of removal of heavy metals and more resistive to metals ions since its cell viability was not strongly inhibited by the toxic metal ions over various concentrations. On the other hand, electrochemically active biofilm exhibited higher bioelectrochemical signals in presence of heavy metals ions. So by using the two strains, especially Rhizobium-MAP7, the detection and removal of heavy metals Cr(VI) and Cd(II) is highly supported and recommended

A personalized classification of behavioral severity of autism spectrum disorder using a comprehensive machine learning framework

Abstract Autism Spectrum Disorder (ASD) is characterized as a neurodevelopmental disorder with a heterogeneous nature, influenced by genetics and exhibiting diverse clinical presentations. In this study, we dissect Autism Spectrum Disorder (ASD) into its behavioral components, mirroring the diagnostic process used in clinical settings. Morphological features are extracted from magnetic resonance imaging (MRI) scans, found in the publicly available dataset ABIDE II, identifying the most discriminative features that differentiate ASD within various behavioral domains. Then, each subject is categorized as having severe, moderate, or mild ASD, or typical neurodevelopment (TD), based on the behavioral domains of the Social Responsiveness Scale (SRS). Through this study, multiple artificial intelligence (AI) models are utilized for feature selection and classifying each ASD severity and behavioural group. A multivariate feature selection algorithm, investigating four different classifiers with linear and non-linear hypotheses, is applied iteratively while shuffling the training-validation subjects to find the set of cortical regions with statistically significant association with ASD. A set of six classifiers are optimized and trained on the selected set of features using 5-fold cross-validation for the purpose of severity classification for each behavioural group. Our AI-based model achieved an average accuracy of 96%, computed as the mean accuracy across the top-performing AI models for feature selection and severity classification across the different behavioral groups. The proposed AI model has the ability to accurately differentiate between the functionalities of specific brain regions, such as the left and right caudal middle frontal regions. We propose an AI-based model that dissects ASD into behavioral components. For each behavioral component, the AI-based model is capable of identifying the brain regions which are associated with ASD as well as utilizing those regions for diagnosis. The proposed system can increase the speed and accuracy of the diagnostic process and result in improved outcomes for individuals with ASD, highlighting the potential of AI in this area

Association of Diaporthe longicolla with Black Zone Lines on Mature Soybean Plants

In 2014, during a survey for soybean (Glycine max L.) diseases in Illinois, Indiana, Iowa, Michigan, and South Dakota, zone lines were observed on the lower stems of soybean plants. The survey was performed by sampling two to three fields per state. In each field, at least five plants exhibiting zone lines were collected. Isolations were made from the zone lines by plating 1-cm pieces on potato dextrose agar. A total of 90 isolates producing black stromata in concentric patterns and alpha conidia were tentatively identified as Diaporthe longicolla (Hobbs) Santos, Vrandecic and Phillips. DNA was extracted from the mycelia of 10 representative isolates and the identity was confirmed by sequencing the internal transcribed spacer (ITS) region. Additionally, phylogenetic analysis combining translation elongation factor-1a and actin sequences was performed and the ten isolates grouped with the D. longicolla ex-type cultures in a well-supported clade (94% bootstrap support). A pathogenicity test was performed in the greenhouse by inserting D. longicolla-infested toothpicks into the lower stems of the soybean plants. To complete Koch\u27s postulates, D. longicolla was re-isolated from the zone lines of the inoculated plants and the pathogen identity was confirmed by sequencing the ITS gene