Transposon mutagenesis in a hyper-invasive clinical isolate of Campylobacter jejuni reveals a number of genes with potential roles in invasion

Transposon mutagenesis has been applied to a hyper-invasive clinical isolate of Campylobacter jejuni, 01/51. A random transposon mutant library was screened in an in vitro assay of invasion and 26 mutants with a significant reduction in invasion were identified. Given that the invasion potential of C. jejuni is relatively poor compared to other enteric pathogens, the use of a hyper-invasive strain was advantageous as it greatly facilitated the identification of mutants with reduced invasion. The location of the transposon insertion in 23 of these mutants has been determined; all but three of the insertions are in genes also present in the genome-sequenced strain NCTC 11168. Eight of the mutants contain transposon insertions in one region of the genome (∼14 kb), which when compared with the genome of NCTC 11168 overlaps with one of the previously reported plasticity regions and is likely to be involved in genomic variation between strains. Further characterization of one of the mutants within this region has identified a gene that might be involved in adhesion to host cells

Parallel Approaches to Accelerate Bayesian Decision Trees

Markov Chain Monte Carlo (MCMC) is a well-established family of algorithms primarily used in Bayesian statistics to sample from a target distribution when direct sampling is challenging. Existing work on Bayesian decision trees uses MCMC. Unfortunately, this can be slow, especially when considering large volumes of data. It is hard to parallelise the accept-reject component of the MCMC. None-the-less, we propose two methods for exploiting parallelism in the MCMC: in the first, we replace the MCMC with another numerical Bayesian approach, the Sequential Monte Carlo (SMC) sampler, which has the appealing property that it is an inherently parallel algorithm; in the second, we consider data partitioning. Both methods use multi-core processing with a HighPerformance Computing (HPC) resource. We test the two methods in various study settings to determine which method is the most beneficial for each test case. Experiments show that data partitioning has limited utility in the settings we consider and that the use of the SMC sampler can improve run-time (compared to the sequential implementation) by up to a factor of 343

Novel Decision Forest Building Techniques by Utilising Correlation Coefficient Methods

Decision Forests have attracted the academic community’s interest mainly due to their simplicity and transparency. This paper proposes two novel decision forest building techniques, called Maximal Information Coefficient Forest (MICF) and Pearson’s Correlation Coefficient Forest (PCCF). The proposed new algorithms use Pearson’s Correlation Coefficient (PCC) and Maximal Information Coefficient (MIC) as extra measures of the classification capacity score of each feature. Using those approaches, we improve the picking of the most convenient feature at each splitting node, the feature with the greatest Gain Ratio. We conduct experiments on 12 datasets that are available in the publicly accessible UCI machine learning repository. Our experimental results indicate that the proposed methods have the best average ensemble accuracy rank of 1.3 (for MICF) and 3.0 (for PCCF), compared to their closest competitor, Random Forest (RF), which has an average rank of 4.3. Additionally, the results from Friedman and Bonferroni-Dunn tests indicate statistically significant improvement

Bayesian Decision Trees Inspired from Evolutionary Algorithms

Bayesian Decision Trees (DTs) are generally considered a more advanced and accurate model than a regular Decision Tree (DT) because they can handle complex and uncertain data. Existing work on Bayesian DTs uses Markov Chain Monte Carlo (MCMC) with an accept-reject mechanism and sample using naive proposals to proceed to the next iteration, which can be slow because of the burn-in time needed. We can reduce the burn-in period by proposing a more sophisticated way of sampling or by designing a different numerical Bayesian approach. In this paper, we propose a replacement of the MCMC with an inherently parallel algorithm, the Sequential Monte Carlo (SMC), and a more effective sampling strategy inspired by the Evolutionary Algorithms (EA). Experiments show that SMC combined with the EA can produce more accurate results compared to MCMC in 100 times fewer iterations.Comment: arXiv admin note: text overlap with arXiv:2301.0909

PinR mediates the generation of reversible population diversity in Streptococcus zooepidemicus

Opportunistic pathogens must adapt to and survive in a wide range of complex ecosystems. Streptococcus zooepidemicus is an opportunistic pathogen of horses and many other animals, including humans. The assembly of different surface architecture phenotypes from one genotype is likely to be crucial to the successful exploitation of such an opportunistic lifestyle. Construction of a series of mutants revealed that a serine recombinase, PinR, inverts 114 bp of the promoter of SZO_08560, which is bordered by GTAGACTTTA and TAAAGTCTAC inverted repeats. Inversion acts as a switch, controlling the transcription of this sortase-processed protein, which may enhance the attachment of S. zooepidemicus to equine trachea. The genome of a recently sequenced strain of S. zooepidemicus, 2329 (Sz2329), was found to contain a disruptive internal inversion of 7 kb of the FimIV pilus locus, which is bordered by TAGAAA and TTTCTA inverted repeats. This strain lacks pinR and this inversion may have become irreversible following the loss of this recombinase. Active inversion of FimIV was detected in three strains of S. zooepidemicus, 1770 (Sz1770), B260863 (SzB260863) and H050840501 (SzH050840501), all of which encoded pinR. A deletion mutant of Sz1770 that lacked pinR was no longer capable of inverting its internal region of FimIV. The data highlight redundancy in the PinR sequence recognition motif around a short TAGA consensus and suggest that PinR can reversibly influence the wider surface architecture of S. zooepidemicus, providing this organism with a bet-hedging solution to survival in fluctuating environments

The accuracy of interpretation of emergency abdominal CT in adult patients who present with non-traumatic abdominal pain: results of a UK national audit.

: To evaluate major/minor discrepancy rates for provisional (initial) and addendum (supplementary senior review) emergency computed tomography (CT) reports in patients presenting with non-traumatic abdominal pain. : Ethical approval for this type of study is not required in the UK. All radiology departments with an approved lead for audit registered with the Royal College of Radiologists were invited to participate in this retrospective audit. The first 50 consecutive patients (25 surgical, 25 non-surgical) who underwent emergency abdominal CT for non-traumatic abdominal pain in 2013 were included. Statistical analyses were performed to identify organisational and report/patient-related variables that might be associated with major discrepancy. : One hundred and nine (58%) of 188 departments supplied data to the study with a total of 4,931 patients (2,568 surgical, 2,363 non-surgical). The audit standard for provisional report major discrepancy was achieved for registrars (target &lt;10%, achieved 4.6%), for on-site consultants (target &lt;5%, achieved 3.1%) and consultant addendum (target &lt;5%, achieved 2.9%). Off-site reporters failed to meet the standard target (&lt;5%, achieved 8.7% overall and 12.7% in surgical patients). The standard for patients coming to harm was not met in the surgical group (target &lt;1%, achieved 1.5%) and was narrowly missed overall (target &lt;1%, achieved 1%). : This study should be used to provide impetus to improve aspects of out-of-hours CT reporting. Clear benefits of CT interpretation/review by on-site and more senior (consultant) radiologists have been demonstrated.<br/

Dose de-escalation of intrapleural tissue plasminogen activator therapy for pleural infection. The alteplase dose assessment for Pleural infection Therapy project

Rationale: Intrapleural therapy with a combination of tissue plasminogen activator (tPA) 10 mg and DNase 5 mg administered twice daily has been shown in randomized and open-label studies to successfully manage over 90% of patients with pleural infection without surgery. Potential bleeding risks associated with intrapleural tPA and its costs remain important concerns. The aim of the ongoing Alteplase Dose Assessment for Pleural infection Therapy (ADAPT) project is to investigate the efficacy and safety of dose de-escalation for intrapleural tPA. The first of several planned studies is presented here. Objectives: To evaluate the efficacy and safety of a reduced starting dose regimen of 5 mg of tPA with 5 mg of DNase administered intrapleurally for pleural infection. Methods: Consecutive patients with pleural infection at four participating centers in Australia, the United Kingdom, and New Zealand were included in this observational, open-label study. Treatment was initiated with tPA 5 mg and DNase 5 mg twice daily. Subsequent dose escalation was permitted at the discretion of the attending physician. Data relating to treatment success, radiological and systemic inflammatory changes (blood C-reactive protein), volume of fluid drained, length of hospital stay, and treatment complications were extracted retrospectively from the medical records. Results: We evaluated 61 patients (41 males; age, 57 ± 16 yr). Most patients (n = 58 [93.4%]) were successfully treated without requiring surgery for pleural infection. Treatment success was corroborated by clearance of pleural opacities visualized by chest radiography (from 42% [interquartile range, 22–58] to 16% [8–31] of hemithorax; P &lt; 0.001), increase in pleural fluid drainage (from 175 ml in the 24 h preceding treatment to 2,025 ml [interquartile range, 1,247–2,984] over 72 h of therapy; P &lt;  0.05) and a reduction in blood C-reactive protein (P &lt; 0.05). Seven patients (11.5%) had dose escalation of tPA to 10 mg. Three patients underwent surgery. Three patients (4.9%) received blood transfusions for gradual pleural blood loss; none were hemodynamically compromised. Pain requiring escalation of analgesia affected 36% of patients; none required cessation of therapy. Conclusions: These pilot data suggest that a starting dose of 5 mg of tPA administered intrapleurally twice daily in combination with 5 mg of DNase for the treatment of pl

Overcoming undesirable knowledge redundancy in territorial clusters

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An O(log2N) Fully-Balanced Resampling Algorithm for Particle Filters on Distributed Memory Architectures

Resampling is a well-known statistical algorithm that is commonly applied in the context of Particle Filters (PFs) in order to perform state estimation for non-linear non-Gaussian dynamic models. As the models become more complex and accurate, the run-time of PF applications becomes increasingly slow. Parallel computing can help to address this. However, resampling (and, hence, PFs as well) necessarily involves a bottleneck, the redistribution step, which is notoriously challenging to parallelize if using textbook parallel computing techniques. A state-of-the-art redistribution takes O((log2N)2) computations on Distributed Memory (DM) architectures, which most supercomputers adopt, whereas redistribution can be performed in O(log2N) on Shared Memory (SM) architectures, such as GPU or mainstream CPUs. In this paper, we propose a novel parallel redistribution for DM that achieves an O(log2N) time complexity. We also present empirical results that indicate that our novel approach outperforms the O((log2N)2) approach.</jats:p

Learning from innovative practitioners: Evidence for the sustainability and resilience of pasture fed livestock systems

There is an urgent need for transformational change in agriculture to address current and future issues caused by climate change, biodiversity loss and socio-ecological disruption. But change is slow to come and is hindered by a lack of transdisciplinary evidence on potential approaches which take a systems approach. The research described here was co-developed with the Pasture Fed Livestock Association in the UK to objectively evidence their practices. These include producing pasture-based meat from livestock fed on pasture and pasture-based forages alone. This approach sits alongside wider aims of fitting their practices with the ecological conditions on each individual farm to facilitate optimal production and working collaboratively through a forum for sharing knowledge. The research provides strong indications that the PFLA approach to livestock production is resilient and viable, as well as contributing to wider public goods delivery, despite variability within and between farms. It also reveals that learning and adaption of practice (through farmer experience) is central to farming using agro-ecological approaches. This fluidity of practice presents challenges for reductionist approaches to "measuring" agricultural innovations