Proteomics-based screening and antibiotic resistance assessment of clinical and sub-clinical Brucella species: An evolution of brucellosis infection control

Brucellae are intracellular sneaky bacteria and they can elude the host’s defensive mechanisms, resulting in therapeutic failure. Therefore, the goal of this investigation was to rapid identification of Brucella species collected from animals and humans in Saudi Arabia, as well as to evaluate their resistance to antibiotics. On selective media, 364 animal samples as well as 70 human blood samples were cultured. Serological and biochemical approaches were initially used to identify a total of 25 probable cultured isolates. The proteomics of Brucella species were identified using the MALDI Biotyper (MBT) system, which was subsequently verified using real-time polymerase chain reaction (real-time PCR) and microfluidic electrophoresis assays. Both Brucella melitensis (B. melitensis) and Brucella abortus (B. abortus) were tested for antimicrobial susceptibility using Kirby Bauer method and the E-test. In total, 25 samples were positive for Brucella and included 11 B. melitensis and 14 B. abortus isolates. Twenty-two out of 25 (88%) and 24/25 (96%) of Brucella strains were recognized through the Vitek 2 Compact system. While MBT was magnificently identified 100% of the strains at the species level with a score value more than or equal to 2.00. Trimethoprim-sulfamethoxazole, rifampin, ampicillin-sulbactam, and ampicillin resistance in B. melitensis was 36.36%, 31.82%, 27.27%, and 22.70%, respectively. Rifampin, trimethoprim-sulfamethoxazole, ampicillin, and ampicillin-sulbactam resistance was found in 35.71%, 32.14%, 32.14%, and 28.57% of B. abortus isolates, correspondingly. MBT confirmed by microfluidic electrophoresis is a successful approach for identifying Brucella species at the species level. The resistance of B. melitensis and B. abortus to various antibiotics should be investigated in future studies.

Multiple Antimicrobial Effects of Hybrid Peptides Synthesized Based on the Sequence of Ribosomal S1 Protein from Staphylococcus aureus

The need to develop new antimicrobial peptides is due to the high resistance of pathogenic bacteria to traditional antibiotics now and in the future. The creation of synthetic peptide constructs is a common and successful approach to the development of new antimicrobial peptides. In this work, we use a simple, flexible, and scalable technique to create hybrid antimicrobial peptides containing amyloidogenic regions of the ribosomal S1 protein from Staphylococcus aureus. While the cell-penetrating peptide allows the peptide to enter the bacterial cell, the amyloidogenic site provides an antimicrobial effect by coaggregating with functional bacterial proteins. We have demonstrated the antimicrobial effects of the R23F, R23DI, and R23EI hybrid peptides against Staphylococcus aureus, methicillin-resistant S. aureus (MRSA), Pseudomonas aeruginosa, Escherichia coli, and Bacillus cereus. R23F, R23DI, and R23EI can be used as antimicrobial peptides against Gram-positive and Gram-negative bacteria resistant to traditional antibiotics.

An Effective Approach Based on Improved Convolutionary Neural Network Classifier for the Detection of Diabetic Retinopathy

In diabetic individuals, diabetic retinopathy (DR) causes blindness. Therefore, detecting diabetic retinopathy at an early stage decreases vision loss. An successful approach for diabetic retinopathy prediction is discussed in this article. In the beginning, the input pictures of human retinal fundus images are preprocessed using histogram equalisation followed by Gabor filtering to reduce noise for enhancement. Then, using the Watershed method, segmentation is performed, and the features are retrieved through feature extraction. The best optimum features are selected using PCA (principal component analysis) approach. The morphological based post processing scheme was employed to further enhance the quality of selected features. At last, the classification approach is carried with the utilization of Google NET CNN classifier to classify/predict the retinal image as normal, abnormal, and severe. Google NET CNN has been developed with limited preprocessing step to distinguish visual features directly from image pixels. The findings are then evaluated and the efficacy of the new method is contrasted with other current methods. The quantitative findings were evaluated for Accuracy, precision, reliability, positive predictive levels and false predictive levels in parameters and were seen to deliver better results than current techniques.

281 Home delivery of the communicator for remote monitoring of cardiac implantable devices: a multicentre experience during the COVID-19 lockdown

Aims During the COVID-19 pandemic in-person visits for patients with cardiac implantable electronic devices should be replaced by remote monitoring (RM), in order to prevent viral transmission. A direct home-delivery service of the RM communicator has been implemented at 49 Italian arrhythmia centres. Methods and results According to individual patient preference or the organizational decision of the centre, patients were assigned to the home-delivery group or the standard in-clinic delivery group. In the former case, patients received telephone training on the activation process and use of the communicator. In June 2020, the centres were asked to reply to an ad hoc questionnaire to describe and evaluate their experience in the previous 3 months. RM was activated in 1324 patients: 821 (62%) received the communicator at home and the communicator was activated remotely. Activation required one additional call in 49% of cases, and the median time needed to complete the activation process was 15 min (25th–75th percentile: 10–20). 753 (92%) patients were able to complete the correct activation of the system. At the time when the questionnaire was completed, 743 (90%) communicators were regularly transmitting data. The service was generally deemed useful (96% of respondents) in facilitating the activation of RM during the COVID-19 pandemic and possibly beyond. Conclusions Home delivery of the communicator proved to be a successful approach to system activation, and received positive feedback from clinicians. The increased use of a RM protocol will reduce risks for both providers and patients, while maintaining high-quality care.

Dynamic classification approach using scalable ensemble of autoencoders to classify data with drift

The problem of classification under concept drift conditions is investigated. The importance of anomaly detection is emphasized as a key feature of successful approach to operate with adversarial attacks and data poisoning. An approach to classification in the context of both drift and anomalies is introduced. It is based on ensemble of one-class classifiers, implemented by neural network autoencoders. Numeric parameters and supplementary logic are also supposed to distinguish between different classification cases. The quality of classifiers is estimated by original characteristics (EDCA), which examine both training set area and the area around it. The proposed approach is evaluated on synthetic data to highlight its properties in various conditions including normal, drift, new class and anomaly cases.

A Systematic Approach to the Development of Cilostazol Nanosuspension by Liquid Antisolvent Precipitation (LASP) and Its Combination with Ultrasound

Nanosizing is an approach to improve the dissolution rate of poorly soluble drugs. The first aim of this work was to develop nanosuspension of cilostazol with liquid antisolvent precipitation (LASP) and its combination with ultrasound. Second, to systematically study the effect of bottom-up processing factors on precipitated particles’ size and identify the optimal settings for the best reduction. After solvent and stabilizer screening, in-depth process characterization and optimization was performed using Design of Experiments. The work discusses the influence of critical factors found with statistical analysis: feed concentration, stabilizer amount, stirring speed and ultrasound energy governed by time and amplitude. LASP alone only generated particle size of a few microns, but combination with ultrasound was successful in nanosizing (d10 = 0.06, d50 = 0.33, d90 = 1.45 µm). Micro- and nanosuspension’s stability, particle morphology and solid state were studied. Nanosuspension displayed higher apparent solubility than equilibrium and superior dissolution rate over coarse cilostazol and microsuspension. A bottom-up method of precipitation-sonication was demonstrated to be a successful approach to improve the dissolution characteristics of poorly soluble, BCS class II drug cilostazol by reducing its particle size below micron scale, while retaining nanosuspension stability and unchanged crystalline form.

N M R Studies of Coal

<p>Carbon-13 CP/MAS NMR was used to study a selection of fifty-seven New Zealand coals and ten Australian coals. The coal rank varied from lignite to semianthracite. A qualitative survey of the plant origins of NMR signals was followed by an EPR study of the unpaired spin-species in coal. The quantitative reliability of the NMR response of coal was analysed in relaxation and "visibility" studies. Different approaches to the problem of accounting for intensity in spinning-side-band (SSB) signals were assessed. The most successful approach was found to be the complete computer simulation of the spectrum from combinations of SSB intensity patterns broadened by a mixture of Lorentzian and Gaussian lineshapes. This method of analysis produced oxygen contents that showed a good correlation with oxygen contents (by difference) from Ultimate analysis. The resultant carbon, hydrogen and oxygen functional group analyses allowed considerable insight into the depositional influences on, and alteration of, the coal structure with increasing degree of coalification.</p>

N M R Studies of Coal

<p>Carbon-13 CP/MAS NMR was used to study a selection of fifty-seven New Zealand coals and ten Australian coals. The coal rank varied from lignite to semianthracite. A qualitative survey of the plant origins of NMR signals was followed by an EPR study of the unpaired spin-species in coal. The quantitative reliability of the NMR response of coal was analysed in relaxation and "visibility" studies. Different approaches to the problem of accounting for intensity in spinning-side-band (SSB) signals were assessed. The most successful approach was found to be the complete computer simulation of the spectrum from combinations of SSB intensity patterns broadened by a mixture of Lorentzian and Gaussian lineshapes. This method of analysis produced oxygen contents that showed a good correlation with oxygen contents (by difference) from Ultimate analysis. The resultant carbon, hydrogen and oxygen functional group analyses allowed considerable insight into the depositional influences on, and alteration of, the coal structure with increasing degree of coalification.</p>

N M R Studies of Coal

<p>Carbon-13 CP/MAS NMR was used to study a selection of fifty-seven New Zealand coals and ten Australian coals. The coal rank varied from lignite to semianthracite. A qualitative survey of the plant origins of NMR signals was followed by an EPR study of the unpaired spin-species in coal. The quantitative reliability of the NMR response of coal was analysed in relaxation and "visibility" studies. Different approaches to the problem of accounting for intensity in spinning-side-band (SSB) signals were assessed. The most successful approach was found to be the complete computer simulation of the spectrum from combinations of SSB intensity patterns broadened by a mixture of Lorentzian and Gaussian lineshapes. This method of analysis produced oxygen contents that showed a good correlation with oxygen contents (by difference) from Ultimate analysis. The resultant carbon, hydrogen and oxygen functional group analyses allowed considerable insight into the depositional influences on, and alteration of, the coal structure with increasing degree of coalification.</p>