Toxigenic Vibrio cholerae evolution and establishment of reservoirs in aquatic ecosystems.

The spread of cholera in the midst of an epidemic is largely driven by direct transmission from person to person, although it is well-recognized that Vibrio cholerae is also capable of growth and long-term survival in aquatic ecosystems. While prior studies have shown that aquatic reservoirs are important in the persistence of the disease on the Indian subcontinent, an epidemiological view postulating that locally evolving environmental V. cholerae contributes to outbreaks outside Asia remains debated. The single-source introduction of toxigenic V. cholerae O1 in Haiti, one of the largest outbreaks occurring this century, with 812,586 suspected cases and 9,606 deaths reported through July 2018, provided a unique opportunity to evaluate the role of aquatic reservoirs and assess bacterial transmission dynamics across environmental boundaries. To this end, we investigated the phylogeography of both clinical and aquatic toxigenic V. cholerae O1 isolates and show robust evidence of the establishment of aquatic reservoirs as well as ongoing evolution of V. cholerae isolates from aquatic sites. Novel environmental lineages emerged from sequential population bottlenecks, carrying mutations potentially involved in adaptation to the aquatic ecosystem. Based on such empirical data, we developed a mixed-transmission dynamic model of V. cholerae, where aquatic reservoirs actively contribute to genetic diversification and epidemic emergence, which underscores the complexity of transmission pathways in epidemics and endemic settings and the need for long-term investments in cholera control at both human and environmental levels.

Prediction or interpretability?

The journal published a review of the literature on recursive partition in epidemiological research comparing two decision tree methods: classification and regression trees (CARTs) and conditional inference trees (CITs). There are two sources of potential confusion in the paper for readers: one lies in the definition and the comparison of CITs and CARTs, while the other is more general and it refers to the use of hyper-parameters and their tuning through resampling techniques.

Telomere length and cancer mortality in American Indians: the Strong Heart Study.

The objective of this study was to investigate whether leukocyte telomere length (LTL) predicts the risk for cancer mortality among American Indians participating in the Strong Heart Study (1989-1991). Participants (aged 45-74 years) were followed annually until December 2015 to collect information on morbidity/mortality. LTL was measured by qPCR using genomic DNA isolated from peripheral blood. The association between LTL and risk for cancer mortality was examined using a multivariable Cox proportional hazard model, adjusting for age, gender, education, study site, smoking, alcohol use, physical activity, systolic blood pressure, fasting blood glucose, obesity, and low- and high-density lipoprotein. Of 1945 participants (mean age 56.10 ± 8.17 at baseline, 57% women) followed for an average 20.5 years, 220 died of cancer. Results showed that longer LTL at baseline significantly predicts an increased risk of cancer death among females (HR 1.57, 95% CI 1.08-2.30), but not males (HR 0.74, 95% CI 0.49-1.12) (p for interaction 0.009). Specifically, compared with the women with the longest LTL (fourth quartile), those in the third, second, and first quartiles showed 53%, 41%, and 44% reduced risk for cancer death, respectively. The findings highlight the importance of sex-specific analysis in future telomere research.

Bias in the intervention in prediction measure in random forests: illustrations and recommendations.

SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

On what to permute in test-based approaches for variable importance measures in Random Forests.

MOTIVATION: In bioinformatics applications, it is currently customary to permute the outcome variable in order to produce inference on covariates to test novel methods or statistics whose distributions are poorly known. The seminal publication of Altmann et al. in Bioinformatics uses the same permutation scheme to obtain P-values that can be treated as corrected measure of feature importance to rectify the bias of the Gini variable importance in Random Forests. Since then, such method has been used in applied work to also draw statistical conclusions on variable importance measures from resulting P-values. RESULTS: In this paper, we show that permuting the outcome may produce unexpected results, including P-values with undesirable properties and illustrate how more refined permutation schemes can be appropriate to obtain desirable results, including high power in discovering relevant variables. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

The revival of the Gini importance?

Motivation: Random forests are fast, flexible and represent a robust approach to analyze high dimensional data. A key advantage over alternative machine learning algorithms are variable importance measures, which can be used to identify relevant features or perform variable selection. Measures based on the impurity reduction of splits, such as the Gini importance, are popular because they are simple and fast to compute. However, they are biased in favor of variables with many possible split points and high minor allele frequency. Results: We set up a fast approach to debias impurity-based variable importance measures for classification, regression and survival forests. We show that it creates a variable importance measure which is unbiased with regard to the number of categories and minor allele frequency and almost as fast as the standard impurity importance. As a result, it is now possible to compute reliable importance estimates without the extra computing cost of permutations. Further, we combine the importance measure with a fast testing procedure, producing p-values for variable importance with almost no computational overhead to the creation of the random forest. Applications to gene expression and genome-wide association data show that the proposed method is powerful and computationally efficient. Availability and implementation: The procedure is included in the ranger package, available at https://cran.r-project.org/package=ranger and https://github.com/imbs-hl/ranger. Supplementary information: Supplementary data are available at Bioinformatics online.

Suitability of Sludge Biotic Index (SBI), Sludge Index (SI) and filamentous bacteria analysis for assessing activated sludge process performance: the case of piggery slaughterhouse wastewater.

Piggery slaughterhouse wastewater poses serious issues in terms of disposal feasibility and environmental impact, due to its huge organic load and variability. It is commonly treated by means of activated sludge processes, whose performance, in case of municipal wastewater, can be monitored by means of specific analyses, such as Sludge Biotic Index (SBI), Sludge Index (SI) and floc and filamentous bacteria observation. Therefore, this paper was aimed at assessing the applicability of these techniques to piggery slaughterhouse sewage. A plant located in Northern Italy was monitored for 1 year. Physical, chemical and operation parameters were measured; the activated sludge community (ciliates, flagellates, amoebae and small metazoa) was analysed for calculating SBI and SI. Floc and filamentous bacteria were examined and described accordingly with internationally adopted criteria. The results showed the full applicability of the studied techniques for optimizing the operation of a piggery slaughterhouse wastewater treatment plant.

Neurological diseases and health care utilization among first-generation immigrants.

Migrants may constitute a risk group and should have specific targets for health policy. To identify their health needs, it is important to investigate their epidemiological profile and their access to health services. The aim of this study was to identify the pattern of hospital and neurological services use among immigrants living in Brescia (Italy). The analysis took into account the records of 45,645 immigrants admitted to the ER (Emergency Room) as well as the discharge data of 6419 patients hospitalized in the Department of Neurology of the Azienda Ospedaliera Spedali Civili di Brescia, over a 3.5 years period. To take confounding factors into account, immigrant patients admitted to the department of Neurology were compared to a selection of Italian patients matched by age and sex. The main objectives were to explore causes of admission of the immigrant population-along with socio-demographic characteristics-to the Emergency Room and to the Neurology Units. Immigrants showed a similar pattern of hospital use to the Italian patients, although with a higher frequency of infective diseases and traumatic injuries. They also showed a higher mean Diagnosis-Related Group (DRG) weight than the Italians. Average length of hospitalization was longer in immigrant population. However, the use of neurological services by migrants is less than their demographic share. Poorer economic and social conditions, as well as a worse labor market experienced by immigrants may expose them to risk factors for injuries and infective diseases. Reducing the language and bureaucratic barriers, as well as enhancing cross-cultural skills of physicians, might be crucial in decreasing the length and the cost of hospitalization.