Classification of DNA Sequence Based on a Non-gradient Algorithm: Pseudoinverse Learners.

This chapter proposes a prototype-based classification approach for analyzing DNA barcodes that uses a spectral representation of DNA sequences and a non-gradient neural network. Biological sequences can be viewed as data components with higher non-fixed dimensions, which correspond to the length of the sequences. Through computational procedures such as one-hot encoding, numerical encoding plays an important role in DNA sequence evaluation (OHE). However, the OHE method has some disadvantages: (1) It does not add any details that could result in an additional predictive variable, and (2) if the variable has many classes, OHE significantly expands the feature space. To address these shortcomings, this chapter proposes a computationally efficient framework for classifying DNA sequences of living organisms in the image domain. A multilayer perceptron trained by a pseudoinverse learning autoencoder (PILAE) algorithm is used in the proposed strategy. The learning control parameters and the number of hidden layers do not have to be specified during the PILAE training process. As a result, the PILAE classifier outperforms other deep neural network (DNN) strategies such as the VGG-16 and Xception models.

Environmental impacts of industrial activities on floral coverage with special emphasis on detoxification enzyme activities in Cataglyphis savignyi as pollution biomarker.

The present study investigates the environmental impact of industrial activities on floral coverage within the major industrial district of Borg El-Arab City, Egypt. Additionally, it aims to evaluate the detoxification enzymatic activity of Cataglyphis savignyi as a pollution biomarker. To achieve this objective, seasonal soil samples were collected from the studied sites to determine soil properties and heavy metal concentrations. Furthermore, a seasonal specimen of C. savignyi was collected to study the enzymatic activity of acetylcholinesterase (AChE) and glutathione-S-transferase (GST). Heavy metal contamination pollution indices were calculated, and fourteen plant species were identified at the investigated sites for four successive seasons from 2020 to 2021. The soil physicochemical parameters significantly varied in the industrial sites compared to the control site. The accumulation of heavy metal contamination in soil for investigated sites followed the order Ni > As > Pb > Hg. Calculated Cdeg and PLI for industrial 3 revealed a very high degree of contamination, attributed to increased industrial activity from the chemical and silicate factories that characterize this region. The current results highlight the inhibition of GST levels in C. savignyi at the industrial site compared to the control site. In contrast, AChE increases, which might be due to heavy metals enhancing acetylcholine activity at synapses. Consequently, the antioxidant enzymatic activities are useful as biomarkers for assessing and monitoring environmental contamination. In conclusion, this study underscores insects as potent biomarkers for heavy metal contamination, marking a significant advancement in environmental monitoring. These bioindicators offer crucial insights into the impacts of climate change and industrial pollution. The research reveals distinct plant diversity variations and higher heavy metal content in industrial sites, indicating pronounced contamination. Additionally, the study highlights altered enzyme activities in insects, emphasizing their utility as biomarkers for assessing environmental contamination. This work represents a substantial leap forward in comprehending the complex dynamics between contamination and ecological balance.

Nosocomial blood stream infection in intensive care units at Assiut University Hospitals (Upper Egypt) with special reference to extended spectrum beta-lactamase producing organisms.

AIM: This study investigated the nosocomial blood stream infection (BSI) in the adult ICUs in Assiut university hospitals to evaluate the rate of infection in different ICUs, causative microorganisms, antimicrobial resistance, outcome of infection, risk factors, prevalence of extended spectrum B-lactamase producing organisms and molecular typing of Klebsiella pneumoniae strains to highlight the role of environment as a potential source of nosocomial BSI. METHODS: This study was conducted over a period of 12 months from January 2006 to December 2006. All Patients admitted to the different adult ICUs were monitored daily by attending physicians for subsequent development of nosocomial BSI. Blood cultures were collected from suspected patients to detect the causative organisms. After antimicrobial susceptibility testing, detection of ESBLs was conducted among gram negative isolates. Klebsiella pneumoniae isolates were tested by PCR to determine the most common group of B-lactamase genes responsible for resistance. Klebsiella pneumoniae isolates from infected patients and those isolated from the environment were typed by RAPD technique to investigate the role of environment in transmission of infection. RESULTS: The study included 2095 patients who were admitted to different ICUs at Assiut University Hospitals from January 2006 to December 2006. Blood samples were collected from infected patients for blood cultures. The colonies were identified and antibiotic sensitivities were performed. This study showed that the rate of nosocomial BSI was 75 per 1000 ICU admissions with the highest percentages in Trauma ICU (17%). Out of 159 patients with primary bloodstream infection, 61 patients died representing a crude mortality rate of 38%. Analysis of the organisms causing BSI showed that Gram positive organisms were reported in 69.1% (n = 121); MRSA was the most prevalent (18.9%), followed by methicillin resistant coagulase negative Staphylococci (16%). Gram negative bacilli were reported in 29.1% (n = 51). In this case, Klebsiella pneumoniae was the most common (10.3%) followed E coli (8.6%). Candida spp. was reported only in (1.7%) of isolates. Antibiotics sensitivities of Gram positive organisms showed that these organisms were mostly sensitive to vancomycin (90.1%), while Gram negative organisms were mostly sensitive to imipenem (90.2%). In this study we tested Gram negative isolates for the production of the ESBL enzyme and concluded that 64.7% (33/51) of patients' isolates and 20/135 (14.8%) environmental isolates were confirmed to be ESBL producers. The type of beta-lactamase gene was determined by polymerase chain reaction which showed that SHV was the main type. Molecular typing was done for 18 Klebsiella pneumoniae strains that caused nosocomial BSI and for the 36 Klebsiella pneumoniae strains which were isolated from the environmental samples by the RAPD method. The two environmental strains were identical, with one isolated from a patient, which confirms the serious role of the hospital environment in the spread of infections. CONCLUSION: Nosocomial BSI represents a current problem in Assiut University Hospitals, Egypt. Problems associated with BSI include infection with multidrug resistant pathogens (especially ESBLs) which are difficult to treat and are associated with increased mortality. Of all available anti-microbial agents, carbapenems are the most active and reliable treatment options for infections caused by ESBL isolates. However, overuse of carbapenems may lead to resistance of other Gram-negative organisms.