Candida SPP. Colonization in NICU: A 2-Year Surveillance Study

Introduction: Fungal infections are an important cause of increased morbidity and mortality in infants admitted to neonatal intensive care units (NICUs). In VLBW infants, Candida (C.) albicans is the third most common cause of neonatal late onset sepsis (LOS). The overall incidence of candidemia in NICU is increasing because of the longer survival and the invasive procedures related with the intensive care of extremely preterm infants. Prevention of candidemia in neonates is supported by the identification and adequate management of specific risk factors, including low birth weight, use of invasive devices, prolonged hospitalization and use of broad-spectrum antimicrobial agents. Effective prophylactic strategies have recently become available, but the identification of the best possible strategies to manage high-risk infants is still a priority. Prior colonization is a key risk factor for candidemia. For this reason, surveillance studies to monitor incidence, species distribution, and antifungal susceptibility profiles are mandatory. Materials and Methods: In 2013 and 2014, we performed a cohort, prospective surveillance study in our NICU, collecting weekly nasal and rectal swabs. For each patient, clinical and demographic data expected to affect Candida colonization were recorded. We evaluated Candida spp. colonization rate and assessed the related risk factors. Swabs were placed on Sabouraud agar and incubated at 30°C for 4 days. Candida growth on agar was confirmed by microscopic observation. Moreover, Candida spp. were identified through Candida chromogenic agar (ChromAgar Candida, Laboratorios Conda) and API® 20C AUX (Biomérieux). Statistical analysis was performed by EpiInfo (CDC software) using the chi square or the Fisher’s exact method, when indicated. We assumed as statistically significant a p-value < 0.05. Results: In this 2-year study, we enrolled 520 patients and we analyzed 1,259 nasal and 1,255 rectal swabs. From 472 out of 520 patients we collected complete microbiological, clinical and demographic data. 48 out of 472 (10.17%) patients tested positive for Candida spp. at least once. In particular, 26 patients tested positive for C. albicans, 16 for C. parapsilosis, 6 for C. glabrata and 1 each for C. guilliermondii and an environmental mold. All the colonized patients had their rectal samples positive, and 7 their nasal samples as well. 15 patients out of 472 (3.18%) had more than one rectal or nasal swab positive during their NICU stay. Importantly, 9 patients out of 15 tested negative at the first sampling, suggesting that they have acquired Candida spp. colonization during their stay. Table 1 summarizes data about risk factors for Candida colonization in the patients under study. No systemic infection by Candida spp. was reported during the study. Conclusion: Our experience suggest that an effective microbiological surveillance can allow for implementing proper, effective and timely control measures in a high-risk setting

Traffic simulation models calibration using speed-density relationship: An automated procedure based on genetic algorithm

This paper presents the first results of a research which applied a genetic algorithm to calibrate a microscopic traffic simulation model based on speed-density relationships. A large set of traffic data collected from the A22 Freeway, Italy, was used and a comparison was performed between the field measurements and the simulation outputs obtained for a test freeway segment by using the Aimsun microscopic simulator. The calibration was formulated as an optimization problem to be solved based on a genetic algorithm; the objective function was defined in order to minimize the differences between the simulated and real data sets in the speed-density graphs. For this purpose, the genetic algorithm tool in MATLAB®was applied. Keeping in mind the objective to automatize this process, the optimization technique was attached to Aimsun via a subroutine, so that the data transfer between the two programs could automatically happen. An external script written in Python allowed the MATLAB®software to interact with Aimsun software. A better match to the field data was reached with the optimization parameters set with the genetic algorithm. In order to check to what extent the model replicated reality, model validation was also addressed. Results showed that a genetic algorithm is usefully applicable in the calibration process of the microscopic traffic simulation model. Beneficial effects are expected by applying the suggested optimization technique since it searches for an optimum set of parameters through an efficient search method

Evaluation of cytokine polymorphisms (TNFα, IFNγ and IL-10) in Down patients with celiac disease

Background In Down syndrome there is an increased prevalence of coeliac disease, but the reasons for this association are yet unknown. Aims To evaluate a possible correlation between TNFα, IFNγ and IL-10 genotype polymorphisms with the susceptibility to coeliac disease in Down syndrome patients. Methods Single nucleotide polymorphisms of TNFα (−308G → A promoter region), IFNγ (+874T → A promoter region) and IL-10 (−1082G → A promoter region) have been studied in 10 Down patients with coeliac disease, in 40 Down patients without coeliac disease and in 220 healthy controls. Clinical features were also studied in coeliac disease–Down syndrome patients. Results The 10 coeliac disease–Down syndrome patients had a biopsy proven coeliac disease afterward a serological testing positive to antigliadin, antiendomysium and antitransglutaminase antibodies. Intestinal biopsy showed total atrophy in 6/10 and partial villous atrophy in 4/10 of them. All coeliac disease–Down syndrome patients had silent forms of coeliac disease and classical trisomy 21. No significant differences were observed for the IFNγ and IL-10 polymorphisms in the studied groups. A significant trend for increase of TNFα −308A positive frequency was observed in coeliac disease–Down syndrome patients compared to healthy controls (p = 0.043). Conclusions Single nucleotide polymorphisms of IFNγ and IL-10 do not play a role in predisposing Down syndrome patients to coeliac disease, while the TNFα −308 allele could be an additional genetic risk factor for coeliac disease in trisomy 21

Apolipoprotein E genotypic frequencies among Down syndrome patients imply early unsuccessful aging for ApoE4 carriers

Down syndrome (DS) might be considered a model for unsuccessful and early aging, possibly accelerated for those who carry the APOE4 allele associated with common age-related diseases, e.g., Alzheimer's disease and a poor prognosis after acute myocardial infarction, causing lower ApoE4 frequencies among the very old in general populations. We compared ApoE genotypic frequencies found for healthy adults (n = 211, age 90) to those found for DS patients (n = 106, mean age 9 years), all living in western Sicily. We found that the frequency of the ApoE23 genotype increased with age among the healthy adults (8.5%, 6.4%, 19.7%; p = 0.024) while ApoE34 frequency decreased (16.1%, 12.6%, 4.1%; p = 0.012). DS patients had APOE34 genotypic frequencies very similar to those found in septuagenarians (9%; p = 0.005). Analyzing results according to surviving rate of persons with DS, an age-related reduction of ApoE3/4 genotype frequency was found comparing =5 years old to >5 years old DS subjects. These results highlight DS as a model to understand the role of APOE4 allele in unsuccessful ageing considering that a number of proinflammatory supernumerary genes (Cu/Zn superoxide dismutase, Ets-2 transcription factors, Down syndrome critical region 1, stress-inducible factor, interferon-alpha receptor and the amyloid precursor protein) are located on chromosome 21 and are implied in the pathologic processes of DS