Longterm survey (7 years) in a population at risk for Lyme borreliosis: what happens to the seropositive individuals?

In 1986, a 26% seroprevalence of IgG- anti-Borrelia burgdorferi antibodies was observed among 950 orienteers and the incidence of new clinical infections was 0.8%. In 1993, a total of 305 seropositive orienteers were reexamined. During that time, 15 cases (4.9%) of definite/probable Lyme disease occurred in this seropositive group (12 skin manifestations and 3 monoarticular joint manifestations). Among the 12 definite cases, 9 showed new clinical infections (7 EM, 1 acrodermatitis chronica atrophicans, 1 arthritis), and 3 were recurrent (2 EM, 1 arthritis). The annual incidence (0.8%) in this seropositive group was identical to the incidence observed among the whole population in 1986. The individual antibody titer decreased slightly but the seroreversion rate was low (7%). Serology was not very helpful in identifying clinical cases and evolutions, and it can be stated, that a positive serology is much more frequent in this risk group than clinical disease

Session 4. Training

Subtitling short films to improve writing and translation skills / Noa Talaván (Universidad Nacional de Educación a Distancia), Pilar Rodríguez-Arancón (Universidad Nacional de Educación a Distancia) ; Exploring audiovisual translation in vocational education and training: free commentary in teacher training / Jennifer Lertola (Università del Piemonte Orientale) ; The relation between subtitle reading, cognitive load and comprehension in Emi lecture / Senne M. Van Hoecke (University of Antwerp), Iris Schrijver (University of Antwerp), Isabelle R. Robert (University of Antwerp) ; Accessible filmmaker: towards the definition of a professional profile / Florencia Fascioli Álvarez (Universidade de Vigo & Universidad Católica del Uruguay). Chair: Juan Pedro Rica (Universidad Complutense de Madrid

Cytoprotective Efficacy and Mechanisms of the Liposoluble Iron Chelator 2,2Ј-Dipyridyl in the Rat Photothrombotic Ischemic Stroke Model

ABSTRACT We examined the efficacy of the liposoluble iron chelator 2,2Ј-dipyridyl (DP) in reducing histological damage in rats submitted to cerebral ischemia and the mechanisms involved in the potential cytoprotection. For this purpose, DP (20 mg/kg, i.p.) was administered 15 min before and 1 h after induction of cortical photothrombotic vascular occlusion in rat. Histological studies were performed to assess infarct volume (at days 1 and 3 postischemia) and astromicroglial activation (at day 3 postischemia). Damage to endothelial and neuronal cells was evaluated at day 1 postischemia by quantitative measurements of Evans Blue extravasation and N-acetylaspartate levels, respectively. Cerebral blood flow was recorded in the ischemic core by laser-Doppler flowmetry within the 15 min to 2 h period after photothrombosis. At 4-h postischemia, radical oxygen species (ROS) production was evaluated by measuring brain glutathione concentrations. The cortical expression of the proteins heme oxygenase-1 (HO-1) and hypoxia-inducible factor-1␣ (HIF-1␣) was analyzed by Western blotting at day 1 postischemia. Infarct volume and ischemic damage to endothelial and neuronal cells were significantly reduced by DP treatment. This cytoprotection was associated with a reduction in ROS production, perfusion deficits, and astrocytic activation. DP treatment also resulted in significant changes in HO-1 (ϩ100%) and HIF-1␣ (Ϫ50%) protein expression at the level of the ischemic core. These results report the efficacy of the liposoluble iron chelator DP in reducing histological damage induced by permanent focal ischemia

Development and evaluation of uncertainty quantifying machine learning models to predict piperacillin plasma concentrations in critically ill patients

Background: Beta-lactam antimicrobial concentrations are frequently suboptimal in critically ill patients. Population pharmacokinetic (PopPK) modeling is the golden standard to predict drug concentrations. However, currently available PopPK models often lack predictive accuracy, making them less suited to guide dosing regimen adaptations. Furthermore, many currently developed models for clinical applications often lack uncertainty quantification. We, therefore, aimed to develop machine learning (ML) models for the prediction of piperacillin plasma concentrations while also providing uncertainty quantification with the aim of clinical practice. Methods: Blood samples for piperacillin analysis were prospectively collected from critically ill patients receiving continuous infusion of piperacillin/tazobactam. Interpretable ML models for the prediction of piperacillin concentrations were designed using CatBoost and Gaussian processes. Distribution-based Uncertainty Quantification was added to the CatBoost model using a proposed Quantile Ensemble method, useable for any model optimizing a quantile function. These models are subsequently evaluated using the distribution coverage error, a proposed interpretable uncertainty quantification calibration metric. Development and internal evaluation of the ML models were performed on the Ghent University Hospital database (752 piperacillin concentrations from 282 patients). Ensuing, ML models were compared with a published PopPK model on a database from the University Medical Centre of Groningen where a different dosing regimen is used (46 piperacillin concentrations from 15 patients.). Results: The best performing model was the Catboost model with an RMSE and R-2 of 31.94-0.64 and 33.53-0.60 for internal evaluation with and without previous concentration. Furthermore, the results prove the added value of the proposed Quantile Ensemble model in providing clinically useful individualized uncertainty predictions and show the limits of homoscedastic methods like Gaussian Processes in clinical applications. Conclusions: Our results show that ML models can consistently estimate piperacillin concentrations with acceptable and high predictive accuracy when identical dosing regimens as in the training data are used while providing highly relevant uncertainty predictions. However, generalization capabilities to other dosing schemes are limited. Notwithstanding, incorporating ML models in therapeutic drug monitoring programs seems definitely promising and the current work provides a basis for validating the model in clinical practice

A paucigranulocytic asthma host environment promotes the emergence of virulent influenza viral variants

Influenza virus has a high mutation rate, such that within one host different viral variants can emerge. Evidence suggests that influenza virus variants are more prevalent in pregnant and/or obese individuals due to their impaired interferon response. We have recently shown that the non-allergic, paucigranulocytic subtype of asthma is associated with impaired type I interferon production. Here, we seek to address if this is associated with an increased emergence of influenza virus variants. Compared to controls, mice with paucigranulocytic asthma had increased disease severity and an increased emergence of influenza virus variants. Specifically, PB1 mutations exclusively detected in asthmatic mice were associated with increased polymerase activity. Furthermore, asthmatic host-derived virus led to increased disease severity in wild-type mice. Taken together, these data suggest that at least a subset of patients with asthma may be more susceptible to severe influenza and may be a possible source of new influenza virus variants

MRSA in Conventional and Alternative Retail Pork Products

In order to examine the prevalence of Staphylococcus aureus on retail pork, three hundred ninety-five pork samples were collected from a total of 36 stores in Iowa, Minnesota, and New Jersey. S. aureus was isolated from 256 samples (64.8%, 95% confidence interval [CI] 59.9%–69.5%). S. aureus was isolated from 67.3% (202/300) of conventional pork samples and from 56.8% (54/95) of alternative pork samples (labeled “raised without antibiotics” or “raised without antibiotic growth promotants”). Two hundred and thirty samples (58.2%, 95% CI 53.2%–63.1%) were found to carry methicillin-sensitive S. aureus (MSSA). MSSA was isolated from 61.0% (183/300) of conventional samples and from 49.5% (47/95) of alternative samples. Twenty-six pork samples (6.6%, 95% CI 4.3%–9.5%) carried methicillin-resistant S. aureus (MRSA). No statistically significant differences were observed for the prevalence of S. aureus in general, or MSSA or MRSA specifically, when comparing pork products from conventionally raised swine and swine raised without antibiotics, a finding that contrasts with a prior study from the Netherlands examining both conventional and “biologic” meat products. In our study spa types associated with “livestock-associated” ST398 (t034, t011) were found in 26.9% of the MRSA isolates, while 46.2% were spa types t002 and t008—common human types of MRSA that also have been found in live swine. The study represents the largest sampling of raw meat products for MRSA contamination to date in the U.S. MRSA prevalence on pork products was higher than in previous U.S.-conducted studies, although similar to that in Canadian studies

Impact of index hopping and bias towards the reference allele on accuracy of genotype calls from low-coverage sequencing

Abstract Background Inherent sources of error and bias that affect the quality of sequence data include index hopping and bias towards the reference allele. The impact of these artefacts is likely greater for low-coverage data than for high-coverage data because low-coverage data has scant information and many standard tools for processing sequence data were designed for high-coverage data. With the proliferation of cost-effective low-coverage sequencing, there is a need to understand the impact of these errors and bias on resulting genotype calls from low-coverage sequencing. Results We used a dataset of 26 pigs sequenced both at 2× with multiplexing and at 30× without multiplexing to show that index hopping and bias towards the reference allele due to alignment had little impact on genotype calls. However, pruning of alternative haplotypes supported by a number of reads below a predefined threshold, which is a default and desired step of some variant callers for removing potential sequencing errors in high-coverage data, introduced an unexpected bias towards the reference allele when applied to low-coverage sequence data. This bias reduced best-guess genotype concordance of low-coverage sequence data by 19.0 absolute percentage points. Conclusions We propose a simple pipeline to correct the preferential bias towards the reference allele that can occur during variant discovery and we recommend that users of low-coverage sequence data be wary of unexpected biases that may be produced by bioinformatic tools that were designed for high-coverage sequence data

An ontology-based nurse call management system (oNCS) with probabilistic priority assessment

<p>Abstract</p> <p>Background</p> <p>The current, place-oriented nurse call systems are very static. A patient can only make calls with a button which is fixed to a wall of a room. Moreover, the system does not take into account various factors specific to a situation. In the future, there will be an evolution to a mobile button for each patient so that they can walk around freely and still make calls. The system would become person-oriented and the available context information should be taken into account to assign the correct nurse to a call.</p> <p>The aim of this research is (1) the design of a software platform that supports the transition to mobile and wireless nurse call buttons in hospitals and residential care and (2) the design of a sophisticated nurse call algorithm. This algorithm dynamically adapts to the situation at hand by taking the profile information of staff members and patients into account. Additionally, the priority of a call probabilistically depends on the risk factors, assigned to a patient.</p> <p>Methods</p> <p>The <it>ontology-based Nurse Call System (oNCS) </it>was developed as an extension of a <it>Context-Aware Service Platform</it>. An ontology is used to manage the profile information. Rules implement the novel nurse call algorithm that takes all this information into account. Probabilistic reasoning algorithms are designed to determine the priority of a call based on the risk factors of the patient.</p> <p>Results</p> <p>The <it>oNCS </it>system is evaluated through a prototype implementation and simulations, based on a detailed dataset obtained from Ghent University Hospital. The arrival times of nurses at the location of a call, the workload distribution of calls amongst nurses and the assignment of priorities to calls are compared for the <it>oNCS </it><it>system </it>and the current, place-oriented nurse call system. Additionally, the performance of the system is discussed.</p> <p>Conclusions</p> <p>The execution time of the nurse call algorithm is on average 50.333 ms. Moreover, the <it>oNCS system </it>significantly improves the assignment of nurses to calls. Calls generally have a nurse present faster and the workload-distribution amongst the nurses improves.</p

The epidemiology and factors associated with nocturnal enuresis among boarding and daytime school children in southeast of Turkey: a cross sectional study

<p>Abstract</p> <p>Background</p> <p>Nocturnal enuresis is an important problem among young children living in Turkey. The purpose of this study was to determine the possible differences in the prevalence of enuresis between children in boarding school and daytime school and the association of enuresis with sociodemographic factors.</p> <p>Methods</p> <p>This was a cross-sectional survey. A total of 562 self-administered questionnaires were distrubuted to parents from two different types of schools. One of them was a day-time school and the other was a boarding school. To describe enuresis the ICD-10 definition of at least one wet night per month for three consecutive months was used. Chi-square test and a logistic regression model was used to identify significant predictive factors for enuresis.</p> <p>Results</p> <p>The overall prevalence of nocturnal enuresis was 14.9%. The prevalence of nocturnal enuresis declined with age. Of the 6 year old children 33.3% still wetted their beds, while the ratio was 2.6% for 15 years-olds. There was no significant difference in prevalence of nocturnal enuresis between boys and girls (14.3% versus 16. 8%). Enuresis was reported as 18.5% among children attending day time school and among those 11.5% attending boarding school (p < 0.05). Prevalence of enuresis was increased in children living in villages, with low income and with positive family history (p < 0.05). After multivariate analysis, history of urinary tract infection (OR = 2.02), age (OR = 1.28), low monthly income (OR = 2.86) and family history of enuresis (OR = 3.64) were factors associated with enuresis. 46.4% of parents and 57.1% of enuretic children were significantly concerned about the impact of enuresis.</p> <p>Conclusion</p> <p>Enuresis was more frequent among children attending daytime school when compared to boarding school. Our findings suggest that nocturnal enuresis is a common problem among school children, especially with low income, smaller age, family history of enuresis and history of urinary tract infection. Enuresis is a pediatric public health problem and efforts at all levels should be made such as preventive, etiological and curative.</p