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Gender disparities in treatment are apparent across many areas of healthcare. There has been little research into whether clozapine prescription, the first-line treatment for treatment-resistant schizophrenia (TRS), is affected by patient gender.

This retrospective cohort study identified 2244 patients with TRS within the South London and Maudsley NHS Trust, by using a bespoke method validated against a gold-standard, manually coded, dataset of TRS cases. The outcome and exposures were identified from the free-text using natural language processing applications (including machine learning and rules-based approaches) and from information entered in structured fields. Multivariable logistic regression was carried out to calculate the odds ratios for clozapine prescription according to patients' gender, and adjusting for numerous potential confounders including sociodemographic, clinical (e.g., psychiatric comorbidities and substance use), neutropenia, functional factors (e.g., problems with occupation), anduch as increased hospitalisation, mortality, and poorer quality of life.Escherichia coli O157H7, a Shiga-producing E. coli is a major pathogenic E. coli strain which since the early 1980s has become a crucial food and water-borne pathogen. Several management strategies can be applied to control the spread of infection; however early diagnosis represents the optimum preventive strategy to minimize the infection. Therefore, it is crucial to detect this pathogen in a fast and efficient manner in order to reduce the morbidity and mortality. Currently used gold standard tests rely on culture and pre-enrichment of E. coli O157H7 from the contaminated source; they are time consuming and laborious. Molecular methods such as polymerase chain reaction are sensitive; however, they require expensive instrumentation. Therefore, there is a requirement for Accurate, Sensitive, Specific, User friendly, Rapid, Equipment free and Deliverable (ASSURED) detection methods for use in the laboratory and in the field. Emerging technologies such as isothermal amplification methods, biosensors, surface enhanced Raman Spectroscopy, paper-based diagnostics and smartphone-based digital methods are recognized as new approaches in the field of E. coli O157H7 diagnostics and are discussed in this review. Mobile PCR and CRISPR-Cas diagnostic platforms have been identified as new tools in E. coli O157H7 POC diagnostics with the potential for implementation by industry. This review describes advances and progress in the field of E. coli O157H7 diagnosis in the context of food and water industry. The focus is on emerging high throughput point-of-care (POC) E. coli O157H7 diagnostics and the requirement for the transformation to service routine diagnostics in the food and water industry.Biofilms are formed by microorganisms protected by a self-produced matrix, most often attached to a surface. In the food processing environments biofilms endanger the product safety by the transmission of spoilage and pathogenic bacteria. In this study, we characterised the biofilm formation of the following eleven strains isolated from biofilms in a meat-processing environment Acinetobacter harbinensis BF1, Arthrobacter sp. BF1, Brochothrix thermosphacta BF1, Carnobacterium maltaromaticum BF1, Kocuria salsicia BF1, Lactococcus piscium BF1, Microbacterium sp. BF1, Pseudomonas fragi BF1, Psychrobacter sp. BF1, Rhodococcus erythropolis BF1, Stenotrophomonas sp. BF1. We applied whole- genome sequencing and subsequent genome analysis to elucidate genetic features associated with the biofilm lifestyle. We furthermore determined the motility and studied biofilm formation on stainless steel using a static mono-species biofilm model mimicking the meat processing environment. The biomass and the EPS components carbohyly carbohydrates. Carbohydrates were detected in biofilms of all strains ranging from 0.5 to 4.3 μg glucose equivalents/cm2. Overall, the Microbacterium sp. strain showed the highest biofilm forming ability with high bacterial load (8.7 log CFU/cm2) and high amounts of carbohydrates (2.2 μg glucose equivalents/cm2), proteins (present in all experiments) and eDNA (549 ng/cm2). In contrast, Brochothrix thermosphacta was a weak biofilm former, showing low bacterial load and low levels of carbohydrates in the matrix (6.2 log CFU/cm2 and 0.5 μg glucose equivalents/cm2). This study contributes to our understanding of the biofilm forming ability of bacteria highly abundant in the meat processing environment, which is crucial to develop strategies to prevent and reduce biofilm formation in the food producing environment.Bacterial spores are important in food processing due to their ubiquity, resistance to high temperature and chemical inactivation. This work aims to study the effect of ultraviolet C (UVC) on the spores of Bacillus subtilis and Bacillus velezensis at a molecular and individual level to guide in deciding on the right parameters that must be applied during the processing of liquid foods. The spores were treated with UVC using phosphate buffer saline (PBS) as a suspension medium and their lethality rate was determined for each sample. Purified spore samples of B. velezensis and B. subtilis were treated under one pass in a UVC reactor to inactivate the spores. The resistance pattern of the spores to UVC treatment was determined using dipicolinic acid (Ca-DPA) band of spectral analysis obtained from Raman spectroscopy. Flow cytometry analysis was also done to determine the effect of the UVC treatment on the spore samples at the molecular level. Samples were processed for SEM and the percentage spore surface hydropo design the best parameters during processing.The present work mainly investigated the effects of prepared chitosan‑sodium alginate-nisin (CS-SA-N) preservatives on the quality and bacterial phase of Penaeus vannamei shrimp during cold storage. Results showed that CS-SA-N preservatives treated samples had the lower pH, total volatile basic nitrogen (TVB-N), total viable count (TVC), and freeness (K) values than those of untreated ones during cold storage. The sensory evaluation results indicated that CS-SA-N preservatives treated shrimps had the higher comprehensive scores than those of untreated ones during whole storage. Microbial community of all samples was dominated by Proteobacteria. The initial predominant bacteria of fresh shrimps were Sphingomonas, Carnobacterium and Psychrobacter. Psychrobacter, Pseudomonas, and Shewanella, Acinetobacter and Vibrio were the predominant bacteria of untreated samples. CS-SA-N preservatives significantly decreased predominant microbial numbers by inhibiting the growth of Psychrobacter, Vibrio, Acinetobacter and Carnobacterium during cold storage. Therefore, the CS-SA-N preservatives could be used to prolong the shelf life of shrimp and guarantee its quality.A stochastic model that predicts the maximum specific growth rate (μmax) of Bacillus cereus sensu lato as a function of temperature was developed. The model integrates the intra-species variability by incorporating distributions of cardinal parameters (Tmin, Topt, Tmax) in the model. Growth rate data were generated for 22 strains, covering 5 major phylogenetic groups of B. cereus, and their cardinal temperatures identified. Published growth rate data were also incorporated in the model fitting, resulting in a set of 33 strains. Based on their cardinal temperatures, we identified clusters of Bacillus cereus strains that show similar response to temperature and these clusters were considered separately in the stochastic model. Interestingly, the μopt values for psychrotrophic strains were found to be significantly lower than those obtained for mesophilic strains. The model developed within this work takes into account some correlations existing between parameters (μopt, Tmin, Topt, Tmax). In particular, the relationship highlighted between the b-slope of the Ratkowsky model and Tmin (doi https//doi.org/10.3389/fmicb.2017.01890) was adapted to the case of the popular Cardinal Temperature Model. This resulted in a reduced model in which μopt is replaced by a function of Tmin, Topt and 2 strain-independent parameters. A correlation between the Tmin parameter and the experimental minimal growth temperature was also highlighted and integrated in the model for improved predictions near the temperature growth limits. Compared to the classical approach, the model developed in this study leads to improved predictions for temperatures around Tmin and more realistic tails for the predicted distributions of μmax. It can be useful for describing the variability of the Bacillus cereus Group in Quantitative Microbial Risk Assessment (QMRA). An example of application of the stochastic model to Reconstituted Infant Formulae (RIF) was proposed.The fourth industrial revolution is set to integrate entire manufacturing processes using industrial digital technologies such as the Internet of Things, Cloud Computing, and machine learning to improve process productivity, efficiency, and sustainability. Sensors collect the real-time data required to optimise manufacturing processes and are therefore a key technology in this transformation. Ultrasonic sensors have benefits of being low-cost, in-line, non-invasive, and able to operate in opaque systems. Supervised machine learning models can correlate ultrasonic sensor data to useful information about the manufacturing materials and processes. However, this requires a reference measurement of the process material to label each data point for model training. Glesatinib Labelled data is often difficult to obtain in factory environments, and so a method of training models without this is desirable. This work compares two domain adaptation methods to transfer models across processes, so that no labelled data is required tored to study various effects such as changing sensor location between source and target domains.An audio navigation system is a very useful tool for driving path guidance with less distraction. However, the influence of the audio navigation system on driver behavior, especially in complicated road environments, is still not entirely clear. This study aims to investigate navigation prompt timing (NPT), navigation prompt message (NPM), and their combination in an audio navigation system on driving behavior on an urban expressway with five exits. Driving simulator technology was used to reproduce the experimental environment and obtain driver behavior data. Four indicators-speed, standard deviation of speed, absolute values of acceleration, and depth of accelerator-were selected to examine the main and interactive effects of NPT, NPM, and their combination based on repeated measures analysis of variance. The results show that the driver's psychological state and operation of the vehicle on the urban expressway were affected by the prompt timing and messages of the audio navigation system. An interaction effect existed between prompt timing and prompt messages of the system, and this effect adjusted the effect on the driver's psychological state and vehicle operation caused by these two important factors. This study contributes to our understanding of the influence of audio navigation systems on driver behavior in complex road environments and thus lays a foundation for developing standard audio navigation broadcast guidelines to improve drivers' acceptance of navigation systems, reduce drivers' cognitive workload, and improve the level of vehicle operation safety.
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