1,221 research outputs found
Investigations of different strategies for high frequency regeneration of Dendrobium malones ‘Victory’
Regeneration of orchid, Dendrobium malones “Victory”, has been established by direct differentiation and through callus formation. With direct thin leaf section differentiation method, the number of protocorm like bodies (PLBs) formed from Thin Section (TS) explants obtainedfrom a single leaf was 10 times more than that from a single whole leaf, in a short time period. This therefore suggested that the proliferation potential is distributed all along the seedling leaves and morphogenically competent cells were not limited in the basal ends or the tips of the leaves in TS of orchid leaf cultures. Full MS media supplemented with auxins/cytokinins either in single orin combination along with peptone, yeast extract, casein hydrolysate (each at 100 mg/l), banana powder (40 g/l), 15% coconut water and 2% sucrose have shown excellent results for high frequency regeneration in orchid cultures. In many higher plants, regenerating leaves responded by developing proliferative loci in some “Predetermined Regenerative” cells in the dermal layers by tissue culture methods
Use of whole genome sequencing of commensal Escherichia coli in pigs for antimicrobial resistance surveillance, United Kingdom, 2018
BackgroundSurveillance of commensal Escherichia coli, a possible reservoir of antimicrobial resistance (AMR) genes, is important as they pose a risk to human and animal health. Most surveillance activities rely on phenotypic characterisation, but whole genome sequencing (WGS) presents an alternative.AimIn this retrospective study, we tested 515 E. coli isolated from pigs to evaluate the use of WGS to predict resistance phenotype.MethodsMinimum inhibitory concentration (MIC) was determined for nine antimicrobials of clinical and veterinary importance. Deviation from wild-type, fully-susceptible MIC was assessed using European Committee on Antimicrobial Susceptibility Testing (EUCAST) epidemiological cut-off (ECOFF) values. Presence of AMR genes and mutations were determined using APHA SeqFinder. Statistical two-by-two table analysis and Cohen's kappa (k) test were applied to assess genotype and phenotype concordance.ResultsOverall, correlation of WGS with susceptibility to the nine antimicrobials was 98.9% for test specificity, and 97.5% for the positive predictive value of a test. The overall kappa score (k = 0.914) indicated AMR gene presence was highly predictive of reduced susceptibility and showed excellent correlation with MIC. However, there was variation for each antimicrobial; five showed excellent correlation; four very good and one moderate. Suggested ECOFF adjustments increased concordance between genotypic data and kappa values for four antimicrobials.ConclusionWGS is a powerful tool for accurately predicting AMR that can be used for national surveillance purposes. Additionally, it can detect resistance genes from a wider panel of antimicrobials whose phenotypes are currently not monitored but may be of importance in the future
Detection of a Novel, and Likely Ancestral, Tn916-Like Element from a Human Saliva Metagenomic Library
Tn916 is a conjugative transposon (CTn) and the first reported and most well characterised of the Tn916/Tn1545 family of CTns. Tn916-like elements have a characteristic modular structure and different members of this family have been identified based on similarities and variations in these modules. In addition to carrying genes encoding proteins required for their conjugation, Tn916-like elements also carry accessory, antimicrobial resistance genes; most commonly the tetracycline resistance gene, tet(M). Our study aimed to identify and characterise tetracycline resistance genes from the human saliva metagenome using a functional metagenomic approach. We identified a tetracycline-resistant clone, TT31, the sequencing of which revealed it to encode both tet(M) and tet(L). Comparison of the TT31 sequence with the accessory, regulation, and recombination modules of other Tn916-like elements indicated that a partial Tn916-like element encoding a truncated orf9 was cloned in TT31. Analysis indicated that a previous insertion within the truncated orf9 created the full length orf9 found in most Tn916-like transposons; demonstrating that orf9 is, in fact, the result of a gene fusion event. Thus, we hypothesise that the Tn916-like element cloned in TT31 likely represents an ancestral Tn916
Prevalence and severity of depression among undergraduate students in Karachi, Pakistan: a cross sectional study
Purpose: To highlight the prevalence and severity of depression among undergraduate students in public and private universities in Karachi, Pakistan.Methods: In this cross-sectional study a total of 408 undergraduate students from both public and private universities in Karachi, Pakistan completed Zung Self-Rating Depression Scale (SDS) questionnaire to appraise the presence and extent of depression among the participants. Their sociodemographic characteristics such as age, gender and course of study as well as drug use data were also collected and analyzed.Results: Depression prevalence was 53.43 % (38.07 % for males and 61.00 % for females). A significant disparity in the prevalence of depression across ethnicity was observed. Less than 50 % (n = 163) of the students were satisfied with their duration of degree course work while 111 (27.20 %) participants were not sure about this. The intensity of depression increased with declining satisfaction level (Gamma = 0.264, p = 0.001) which affected the performance and results of students during their studies. A majority of the participants (89 %, n = 358) of our study have never used medicines to alter their mood.Conclusion: The findings of this study highlight the importance of understanding the unique strains and mental health effect of university education on undergraduate students, especially female students.Keywords: Depression, Undergraduate students, Mood alteration, Zung self-rating depression scale (SDS), Mental health, Risk assessmen
Novel Inducers of the Envelope Stress Response BaeSR in Salmonella Typhimurium: BaeR Is Critically Required for Tungstate Waste Disposal
The RpoE and CpxR regulated envelope stress responses are extremely important for SalmonellaTyphimurium to cause infection in a range of hosts. Until now the role for BaeSR in both the Salmonella Typhimurium response to stress and its contribution to infection have not been fully elucidated. Here we demonstrate stationary phase growth, iron and sodium tungstate as novel inducers of the BaeRregulon, with BaeR critically required for Salmonella resistance to sodium tungstate. We show that functional overlap between the resistance nodulation-cell division (RND) multidrug transporters, MdtA, AcrD and AcrB exists for the waste disposal of tungstate from the cell. We also point to a role for enterobactinsiderophores in the protection of enteric organisms from tungstate, akin to the scenario in nitrogen fixing bacteria. Surprisingly, BaeR is the first envelope stress response pathway investigated in S. Typhimurium that is not required for murine typhoid in either ityS or ityR mouse backgrounds. BaeR is therefore either required for survival in larger mammals such as pigs or calves, an avian host such as chickens, or survival out with the host altogether where Salmonella and related enterics must survive in soil and water
XMM-Newton Observations of the Cataclysmic Variable GW Lib
XMM-Newton observations of the accreting, pulsating white dwarf in the
quiescent dwarf nova GW Librae were conducted to determine if the non-radial
pulsations present in previous UV and optical data affect the X-ray emission.
The non-radial pulsations are evident in the simultaneous Optical Monitor data
but are not detected in X-ray with an upper limit on the pulsation amplitude of
0.092 mags. The best fits to the X-ray spectrum are with a low temperature
diffuse gas model or a multi-temperature cooling flow model, with a strong
OVIII line, similar to other short period dwarf novae, but with a lower
temperature range than evident in normal short period dwarf novae. The lack of
pulsations and the spectrum likely indicate that the boundary layer does not
extend to the surface of the white dwarf.Comment: 16 pages, 4 figures; accepted for publication in A
Introducing medical parasitology at the University of Makeni, Sierra Leone
The file attached to this record is the author's final peer reviewed version.Capacity building in Sierra Leone (West Africa) is critical to prevent potential future outbreaks similar to
the 2013-16 Ebola outbreak that had devastating effects for the country and its poorly developed
healthcare system. De Montfort University (DMU) in the United Kingdom (UK), in collaboration with
parasitologists from the Spanish Universities of San Pablo CEU and Miguel Hernández de Elche, is
leading a project to build the teaching and research capabilities of medical parasitology at the University
of Makeni (UniMak, Sierra Leone). This project has two objectives: a) to introduce and enhance the
teaching of medical parasitology, both theoretical and practical; and b) to implement and develop
parasitology research related to important emerging human parasites such as Cryptosporidium spp. due
to their public health significance. Two UniMak academics, hired to help initiate and implement the
research part of the project, shared their culturally sensitive public health expertise to broker parasitology
research in communities and perform a comprehensive environmental monitoring study for the detection
of different emerging human parasites. The presence of targeted parasites are being studied
microscopically using different staining techniques, which in turn have allowed UniMak’s academics to
learn these techniques to develop new practicals in parasitology. To train UniMak’s academics and
develop both parts of our project, a DMU researcher visited UniMak for two weeks in April 2019 and
provided a voluntary short training course in basic parasitology, which is currently not taught in any of
their programmes, and was attended by 31 students. These sessions covered basic introduction to
medical parasitology and life-cycle, pathogenesis, detection, treatment and prevention of: a) coccidian
parasites (Cryptosporidium, Cyclospora and Cystoisospora); b) Giardia intestinalis, Entamoeba and
free-living amoebas; c) malaria and d) microsporidia. A theoretical session on common staining
techniques was also provided. To facilitate the teaching and learning of these parasites, the novel
resource DMU e-Parasitology was used, a package developed by the above participating universities
and biomedical scientists from the UK National Health Service (NHS): http://parasitology.dmu.ac.uk/
index.htm. Following the two weeks of training, UniMak’s academics performed different curriculum
modifications to the undergraduate programme ‘Public Health: Medical Laboratory Sciences’, which
includes the introduction of new practicals in parasitology and changes to enhance the content of
medical parasitology that will be subjected to examination. Thus, a new voluntary practical on Kinyoun
stain for the detection of coccidian parasites was introduced in the final year module of ‘Medical
Bacteriology and Parasitology’; eighteen students in pairs processed faecal samples from pigs provided
by the Department of Agriculture and Food Security from a nearby farm. Academics at UniMak used the
Kinyoun staining unit (available at http://parasitology.dmu.ac.uk/learn/lab/Kinyoun/story_html5.html; [1])
to deliver this practical. Although our project is at a preliminary stage, it has been shown to be effective
in promoting the introduction and establishment of medical parasitology at UniMak and could be viewed
as a case-study for other universities in low-income countries to promote the United Nations (UN)
Sustainable Development Goals (SDGs) and improve public health understanding of infectious
diseases
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A process for analysis of microarray comparative genomics hybridisation studies for bacterial genomes
<p>Abstract</p> <p>Background</p> <p>Microarray based comparative genomic hybridisation (CGH) experiments have been used to study numerous biological problems including understanding genome plasticity in pathogenic bacteria. Typically such experiments produce large data sets that are difficult for biologists to handle. Although there are some programmes available for interpretation of bacterial transcriptomics data and CGH microarray data for looking at genetic stability in oncogenes, there are none specifically to understand the mosaic nature of bacterial genomes. Consequently a bottle neck still persists in accurate processing and mathematical analysis of these data. To address this shortfall we have produced a simple and robust CGH microarray data analysis process that may be automated in the future to understand bacterial genomic diversity.</p> <p>Results</p> <p>The process involves five steps: cleaning, normalisation, estimating gene presence and absence or divergence, validation, and analysis of data from test against three reference strains simultaneously. Each stage of the process is described and we have compared a number of methods available for characterising bacterial genomic diversity, for calculating the cut-off between gene presence and absence or divergence, and shown that a simple dynamic approach using a kernel density estimator performed better than both established, as well as a more sophisticated mixture modelling technique. We have also shown that current methods commonly used for CGH microarray analysis in tumour and cancer cell lines are not appropriate for analysing our data.</p> <p>Conclusion</p> <p>After carrying out the analysis and validation for three sequenced <it>Escherichia coli </it>strains, CGH microarray data from 19 <it>E. coli </it>O157 pathogenic test strains were used to demonstrate the benefits of applying this simple and robust process to CGH microarray studies using bacterial genomes.</p
Approach to Data Science with Multiscale Information Theory
Data Science is a multidisciplinary field that plays a crucial role in
extracting valuable insights and knowledge from large and intricate datasets.
Within the realm of Data Science, two fundamental components are Information
Theory (IT) and Statistical Mechanics (SM), which provide a theoretical
framework for understanding dataset properties. IT enables efficient storage
and transmission of information, while SM focuses on the behavior of systems
comprising numerous interacting components. In the context of data science, SM
allows us to model complex interactions among variables within a dataset. By
leveraging these tools, data scientists can gain a profound understanding of
data properties, leading to the development of advanced models and algorithms
for analysis and interpretation. Consequently, data science has the potential
to drive accurate predictions and enhance decision-making across various
domains, including finance, marketing, healthcare, and scientific research.
In this paper, we apply this data science framework to a large and intricate
quantum mechanical system composed of particles. Our research demonstrates that
the dynamic and probabilistic nature of such systems can be effectively
addressed using a Multiscale Entropic Dynamics (MED) approach, derived from the
Boltzmann methods of SM. Through the MED approach, we can describe the system's
dynamics by formulating a general form of the Nonlinear Schr\"odinger equation
and how it can be applied to various systems with particles and
quasi-particles, such as electrons, plasmons, polarons, and solitons. By
employing this innovative approach, we pave the way for a deeper understanding
of quantum mechanical systems and their behaviors within complex materials.Comment: 12 page
Explaining deep neural networks: A survey on the global interpretation methods
A substantial amount of research has been carried out in Explainable Artificial Intelligence (XAI) models,
especially in those which explain the deep architectures of neural networks. A number of XAI approaches have been proposed to achieve trust in Artificial Intelligence (AI) models as well as provide explainability of specific decisions made within these models. Among these approaches, global interpretation methods have emerged as the prominent methods of explainability because they have the strength to explain every feature and the structure of the model. This survey attempts to provide a comprehensive review
of global interpretation methods that completely explain the behaviour of the AI models. We present a taxonomy of the available global interpretations models and systematically highlight the critical features and algorithms that differentiate them from local as well as hybrid models of explainability. Through examples and case studies from the literature, we evaluate the strengths and weaknesses of the global interpretation models and assess challenges when these methods are put into practice. We conclude the paper by providing the future directions of research in how the existing challenges in global interpretation methods could be addressed and what values and opportunities could be realized by the resolution
of these challenges
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