Newly Identified Mycobacterium africanum Lineage 10, Central Africa.

Analysis of genome sequencing data from >100,000 genomes of Mycobacterium tuberculosis complex using TB-Annotator software revealed a previously unknown lineage, proposed name L10, in central Africa. Phylogenetic reconstruction suggests L10 could represent a missing link in the evolutionary and geographic migration histories of M. africanum.

Cross-Layer Federated Learning for Lightweight IoT Intrusion Detection Systems.

With the proliferation of IoT devices, ensuring the security and privacy of these devices and their associated data has become a critical challenge. In this paper, we propose a federated sampling and lightweight intrusion-detection system for IoT networks that use K-meansfor sampling network traffic and identifying anomalies in a semi-supervised way. The system is designed to preserve data privacy by performing local clustering on each device and sharing only summary statistics with a central aggregator. The proposed system is particularly suitable for resource-constrained IoT devices such as sensors with limited computational and storage capabilities. We evaluate the system's performance using the publicly available NSL-KDD dataset. Our experiments and simulations demonstrate the effectiveness and efficiency of the proposed intrusion-detection system, highlighting the trade-offs between precision and recall when sharing statistics between workers and the coordinator. Notably, our experiments show that the proposed federated IDS can increase the true-positive rate up to 10% when the workers and the coordinator collaborate.

Characterization of a Driven Two-Level Quantum System by Supervised Learning.

We investigate the extent to which a two-level quantum system subjected to an external time-dependent drive can be characterized by supervised learning. We apply this approach to the case of bang-bang control and the estimation of the offset and the final distance to a given target state. For any control protocol, the goal is to find the mapping between the offset and the distance. This mapping is interpolated using a neural network. The estimate is global in the sense that no a priori knowledge is required on the relation to be determined. Different neural network algorithms are tested on a series of data sets. We show that the mapping can be reproduced with very high precision in the direct case when the offset is known, while obstacles appear in the indirect case starting from the distance to the target. We point out the limits of the estimation procedure with respect to the properties of the mapping to be interpolated. We discuss the physical relevance of the different results.

Economic burden in non-Hodgkin lymphoma survivors: The French Lymphoma Study Association SIMONAL cross-sectional study.

BACKGROUND: No study has focused on the economic burden in non-Hodgkin lymphoma (NHL) survivors, even though this knowledge is essential. This study reports on health care resource use and associated health care costs as well as related factors in a series of 1671 French long-term NHL survivors. METHODS: Health care costs were measured from the payer perspective. Only direct medical costs (medical consultations, outpatient treatments, hospitalizations, and medical transport) in the past 12 months were included (reference year 2015). Multiple linear regression was used to search for explanatory factors of health care costs. RESULTS: In total, 1100 survivors (66%) reported having used at least 1 health care resource, and 867 (52%) reported having used at least 1 outpatient treatment. After the authors accounted for missing data, the mean health care cost was estimated at €702 ± €2221. Hospitalizations and outpatient treatments were the main cost drivers. Sensitivity analyses confirmed the robustness of the results. For the 1100 survivors who reported using at least 1 health care resource, the mean health care cost was €1067 ± €2268. Several factors demonstrated statistically significant relationships with health care costs. For instance, cardiovascular disorders increased costs by 66% ± 16%. In contrast, rituximab or autologous stem cell transplantation as initial therapy had no effect on health care costs. CONCLUSIONS: The consideration of economic constraints in health care is now a reality. This retrospective study reports on a better understanding of health care resource use and associated health care costs as well as related factors. It may help health care professionals in their ongoing efforts to design person-centered health care pathways.

CRISPRbuilder-TB: "CRISPR-builder for tuberculosis". Exhaustive reconstruction of the CRISPR locus in mycobacterium tuberculosis complex using SRA.

Mycobacterium tuberculosis complex (MTC) CRISPR locus diversity has long been studied solely investigating the presence/absence of a known set of spacers. Unveiling the genetic mechanisms of its evolution requires a more exhaustive reconstruction in a large amount of representative strains. In this article, we point out and resolve, with a new pipeline, the problem of CRISPR reconstruction based directly on short read sequences in M. tuberculosis. We first show that the process we set up, that we coin as "CRISPRbuilder-TB" (https://github.com/cguyeux/CRISPRbuilder-TB), allows an efficient reconstruction of simulated or real CRISPRs, even when including complex evolutionary steps like the insertions of mobile elements. Compared to more generalist tools, the whole process is much more precise and robust, and requires only minimal manual investigation. Second, we show that more than 1/3 of the currently complete genomes available for this complex in the public databases contain largely erroneous CRISPR loci. Third, we highlight how both the classical experimental in vitro approach and the basic in silico spoligotyping provided by existing analytic tools miss a whole diversity of this locus in MTC, by not capturing duplications, spacer and direct repeats variants, and IS6110 insertion locations. This description is extended in a second article that describes MTC-CRISPR diversity and suggests general rules for its evolution. This work opens perspectives for an in-depth exploration of M. tuberculosis CRISPR loci diversity and of mechanisms involved in its evolution and its functionality, as well as its adaptation to other CRISPR locus-harboring bacterial species.

OSIP1 is a self-assembling DUF3129 protein required to protect fungal cells from toxins and stressors.

Secreted proteins are key players in fungal physiology and cell protection against external stressing agents and antifungals. Oak stress-induced protein 1 (OSIP1) is a fungal-specific protein with unknown function. By using Podospora anserina and Phanerochaete chrysosporium as models, we combined both in vivo functional approaches and biophysical characterization of OSIP1 recombinant protein. The P. anserina OSIP1Δ mutant showed an increased sensitivity to the antifungal caspofungin compared to the wild type. This correlated with the production of a weakened extracellular exopolysaccharide/protein matrix (ECM). Since the recombinant OSIP1 from P. chrysosporium self-assembled as fibers and was capable of gelation, it is likely that OSIP1 is linked to ECM formation that acts as a physical barrier preventing drug toxicity. Moreover, compared to the wild type, the OSIP1Δ mutant was more sensitive to oak extractives including chaotropic phenols and benzenes. It exhibited a strongly modified secretome pattern and an increased production of proteins associated to the cell-wall integrity signalling pathway, when grown on oak sawdust. This demonstrates that OSIP1 has also an important role in fungal resistance to extractive-induced stress.

Machine learning-based forecasting of firemen ambulances' turnaround time in hospitals, considering the COVID-19 impact.

When ambulances' turnaround time (TT) in emergency departments is prolonged, it not only affects the victim severely but also causes unavailability of resources in emergency medical services (EMSs) and, consequently, leaves a locality unprotected. This problem may worsen with abnormal situations, e.g., the current coronavirus disease 2019 (COVID-19) pandemic. Taking this into consideration, this paper presents a first study on the COVID-19 impact on ambulances' TT by analyzing historical data from the Departmental Fire and Rescue Service of the Doubs (SDIS 25), in France, for three hospitals. Because the TTs of SDIS 25 ambulances increased, this paper also calculated and analyzed the number of breakdowns in services, which augmented due to shortage of ambulances that return on service in time. It is, therefore, vital to have a decision-support tool to better reallocate resources by knowing the time EMSs ambulances and personnel will be in use. Thus, this paper proposes a novel two-stage methodology based on machine learning (ML) models to forecast the TT of each ambulance in a given time and hospital. The first stage uses a multivariate model of regularly spaced time series to predict the average TT (AvTT) per hour, which considers temporal variables and external ones (e.g., COVID-19 statistics, weather data). The second stage utilizes a multivariate irregularly spaced time series model, which considers temporal variables of each ambulance departure, type of intervention, external variables, and the previously predicted AvTT as inputs. Four state-of-the-art ML models were considered in this paper, namely, Light Gradient Boosted Machine, Multilayer Perceptron, Long Short-Term Memory, and Prophet. As shown in the results, the proposed methodology provided remarkable results for practical purposes. The AvTT accuracies obtained for the three hospitals were 90.16%, 97.02%, and 93.09%. And the TT accuracies were 74.42%, 86.63%, and 76.67%, all with an error margin of ± 10 min.

Unexpected diversity of CRISPR unveils some evolutionary patterns of repeated sequences in Mycobacterium tuberculosis.

BACKGROUND: Diversity of the CRISPR locus of Mycobacterium tuberculosis complex has been studied since 1997 for molecular epidemiology purposes. By targeting solely the 43 spacers present in the two first sequenced genomes (H37Rv and BCG), it gave a biased idea of CRISPR diversity and ignored diversity in the neighbouring cas-genes. RESULTS: We set up tailored pipelines to explore the diversity of CRISPR-cas locus in Short Reads. We analyzed data from a representative set of 198 clinical isolates as evidenced by well-characterized SNPs. We found a relatively low diversity in terms of spacers: we recovered only the 68 spacers that had been described in 2000. We found no partial or global inversions in the sequences, letting always the Direct Variant Repeats (DVR) in the same order. In contrast, we found an unexpected diversity in the form of: SNPs in spacers and in Direct Repeats, duplications of various length, and insertions at various locations of the IS6110 insertion sequence, as well as blocks of DVR deletions. The diversity was in part specific to lineages. When reconstructing evolutionary steps of the locus, we found no evidence for SNP reversal. DVR deletions were linked to recombination between IS6110 insertions or between Direct Repeats. CONCLUSION: This work definitively shows that CRISPR locus of M. tuberculosis did not evolve by classical CRISPR adaptation (incorporation of new spacers) since the last most recent common ancestor of virulent lineages. The evolutionary mechanisms that we discovered could be involved in bacterial adaptation but in a way that remains to be identified.

Complex evolutionary history of coffees revealed by full plastid genomes and 28,800 nuclear SNP analyses, with particular emphasis on Coffea canephora (Robusta coffee).

For decades coffees were associated with the genus Coffea. In 2011, the closely related genus Psilanthus was subsumed into Coffea. However, results obtained in 2017-based on 28,800 nuclear SNPs-indicated that there is not substantial phylogenetic support for this incorporation. In addition, a recent study of 16 plastid full-genome sequences highlighted an incongruous placement of Coffea canephora (Robusta coffee) between maternal and nuclear trees. In this study, similar global features of the plastid genomes of Psilanthus and Coffea are observed. In agreement with morphological and physiological traits, the nuclear phylogenetic tree clearly separates Psilanthus from Coffea (with exception to C. rhamnifolia, closer to Psilanthus than to Coffea). In contrast, the maternal molecular tree was incongruent with both morphological and nuclear differentiation, with four main clades observed, two of which include both Psilanthus and Coffea species, and two with either Psilanthus or Coffea species. Interestingly, Coffea and Psilanthus taxa sampled in West and Central Africa are members of the same group. Several mechanisms such as the retention of ancestral polymorphisms due to incomplete lineage sorting, hybridization leading to homoploidy (without chromosome doubling) and alloploidy (for C. arabica) are involved in the evolutionary history of the coffee species. While sharing similar morphological characteristics, the genetic relationships within C. canephora have shown that some populations are well differentiated and genetically isolated. Given the position of its closely-related species, we may also consider C. canephora to be undergoing a long process of speciation with an intermediate step of (sub-)speciation.

panISa: ab initio detection of insertion sequences in bacterial genomes from short read sequence data.

Motivation: The advent of next-generation sequencing has boosted the analysis of bacterial genome evolution. Insertion sequence (IS) elements play a key role in prokaryotic genome organization and evolution, but their repetitions in genomes complicate their detection from short-read data. Results: PanISa is a software pipeline that identifies IS insertions ab initio in bacterial genomes from short-read data. It is a highly sensitive and precise tool based on the detection of read-mapping patterns at the insertion site. PanISa performs better than existing IS detection systems as it is based on a database-free approach. We applied it to a high-risk clone lineage of the pathogenic species Pseudomonas aeruginosa, and report 43 insertions of five different ISs (among which three are new) and a burst of ISPa1635 in a hypermutator isolate. Availability and implementation: PanISa is implemented in Python and released as an open source software (GPL3) at https://github.com/bvalot/panISa. Supplementary information: Supplementary data are available at Bioinformatics online.

Comparison of metaheuristics to measure gene effects on phylogenetic supports and topologies.

BACKGROUND: A huge and continuous increase in the number of completely sequenced chloroplast genomes, available for evolutionary and functional studies in plants, has been observed during the past years. Consequently, it appears possible to build large-scale phylogenetic trees of plant species. However, building such a tree that is well-supported can be a difficult task, even when a subset of close plant species is considered. Usually, the difficulty raises from a few core genes disturbing the phylogenetic information, due for example from problems of homoplasy. Fortunately, a reliable phylogenetic tree can be obtained once these problematic genes are identified and removed from the analysis.Therefore, in this paper we address the problem of finding the largest subset of core genomes which allows to build the best supported tree. RESULTS: As an exhaustive study of all core genes combination is untractable in practice, since the combinatorics of the situation made it computationally infeasible, we investigate three well-known metaheuristics to solve this optimization problem. More precisely, we design and compare distributed approaches using genetic algorithm, particle swarm optimization, and simulated annealing. The latter approach is a new contribution and therefore is described in details, whereas the two former ones have been already studied in previous works. They have been designed de novo in a new platform, and new experiments have been achieved on a larger set of chloroplasts, to compare together these three metaheuristics. CONCLUSIONS: The ways genes affect both tree topology and supports are assessed using statistical tools like Lasso or dummy logistic regression, in an hybrid approach of the genetic algorithm. By doing so, we are able to provide the most supported trees based on the largest subsets of core genes.

Simulation-based estimation of branching models for LTR retrotransposons.

Motivation: LTR retrotransposons are mobile elements that are able, like retroviruses, to copy and move inside eukaryotic genomes. In the present work, we propose a branching model for studying the propagation of LTR retrotransposons in these genomes. This model allows us to take into account both the positions and the degradation level of LTR retrotransposons copies. In our model, the duplication rate is also allowed to vary with the degradation level. Results: Various functions have been implemented in order to simulate their spread and visualization tools are proposed. Based on these simulation tools, we have developed a first method to evaluate the parameters of this propagation model. We applied this method to the study of the spread of the transposable elements ROO, GYPSY and DM412 on a chromosome of Drosophila melanogaster . Availability and Implementation: Our proposal has been implemented using Python software. Source code is freely available on the web at https://github.com/SergeMOULIN/retrotransposons-spread . Contact: serge.moulin@univ-fcomte.fr. Supplementary information: are available at Bioinformatics online.

Efficient Hybrid Emergency Aware MAC Protocol for Wireless Body Sensor Networks.

In Body Sensor Networks (BSNs), two types of events should be addressed: periodic and emergency events. Traffic rate is usually low during periodic observation, and becomes very high upon emergency. One of the main and challenging requirements of BSNs is to design Medium Access Control (MAC) protocols that guarantee immediate and reliable transmission of data in emergency situations, while maintaining high energy efficiency in non-emergency conditions. In this paper, we propose a new emergency aware hybrid DTDMA/DS-CDMA protocol that can accommodate BSN traffic variations by addressing emergency and periodic traffic requirements. It takes advantage of the high delay efficiency of DS-CDMA in traffic burst, and the high energy efficiency of DTDMA in periodic traffic. The proposed scheme is evaluated in terms of delay, packet drop percentage, and energy consumption. Different OPNET simulations are performed for various number of nodes carrying emergency data, and for various payload sizes. The protocol performance is compared to other existing hybrid protocols. Results show that the proposed scheme outperforms the others in terms of delay and packet drop percentage for different number of nodes carrying emergency data, as well as for different payload sizes. It also offers the highest energy efficiency during periodic observation, while adjusting the energy consumption during emergency by assigning spreading codes only to nodes holding emergency data.

A Bregman-proximal point algorithm for robust non-negative matrix factorization with possible missing values and outliers - application to gene expression analysis.

BACKGROUND: Non-Negative Matrix factorization has become an essential tool for feature extraction in a wide spectrum of applications. In the present work, our objective is to extend the applicability of the method to the case of missing and/or corrupted data due to outliers. RESULTS: An essential property for missing data imputation and detection of outliers is that the uncorrupted data matrix is low rank, i.e. has only a small number of degrees of freedom. We devise a new version of the Bregman proximal idea which preserves nonnegativity and mix it with the Augmented Lagrangian approach for simultaneous reconstruction of the features of interest and detection of the outliers using a sparsity promoting ℓ 1 penality. CONCLUSIONS: An application to the analysis of gene expression data of patients with bladder cancer is finally proposed.

Dendrochemical assessment of mercury releases from a pond and dredged-sediment landfill impacted by a chlor-alkali plant.

Although current Hg emissions from industrial activities may be accurately monitored, evidence of past releases to the atmosphere must rely on one or more environmental proxies. We used Hg concentrations in tree cores collected from poplars and willows to investigate the historical changes of Hg emissions from a dredged sediment landfill and compared them to a nearby control location. Our results demonstrated the potential value of using dendrochemistry to record historical Hg emissions from past industrial activities.

Population structure and antimicrobial susceptibility of Pseudomonas aeruginosa from animal infections in France.

BACKGROUND: Pseudomonas aeruginosa is a major human pathogen, which also affects animals. It is thought that P. aeruginosa has a non-clonal epidemic population structure, with distinct isolates found in humans, animals or the environment. However, very little is known about the structure of the P. aeruginosa population from diseased animals. Data on antimicrobial resistance are also scarce. RESULTS: Thirty-four already registered and 19 new MLST profiles were identified. Interestingly, a few clones were more prevalent, and clones associated to human outbreaks were also detected. Multidrug resistance phenotypes were overall rare. CONCLUSION: We highlight the non clonal structure of the population and show a higher prevalence of specific clones, possibly correlating with higher pathogenicity. The low proportion of antimicrobial resistance contrasts with the high resistance rate of human isolates.

Wastewater treatment plants release large amounts of extended-spectrum ß-lactamase-producing Escherichia coli into the environment.

BACKGROUND: The determinants of the spread of extended-spectrum ß-lactamase-producing Escherichia coli (ESBLEC) in the community remain unclear. To evaluate its dissemination in the environment, we analyzed the ESBLEC population throughout an urban wastewater network. METHODS: Samples were collected weekly, over a 10-week period, from 11 sites throughout the wastewater network of Besançon city (France). Total E. coli and ESBLEC loads were determined for each sample. As a control, we analyzed 51 clinical ESBLEC isolates collected at our hospital. We genotyped both environmental and clinical ESBLEC by pulsed-field gel electrophoresis and multilocus sequence typing and identified their blaESBL genes by sequencing. RESULTS: The E. coli load was higher in urban wastewater than in hospital wastewater (7.5 × 10(5) vs 3.5 × 10(5) CFU/mL, respectively). ESBLEC was recovered from almost all the environmental samples and accounted for 0.3% of total E. coli in the untreated water upstream from the wastewater treatment plant (WWTP). The ESBLEC load was higher in hospital wastewater than in community wastewater (27 × 10(3) vs 0.8 × 10(3) CFU/mL, respectively). Treatment by the WWTP eliminated 98% and 94% of total E. coli and ESBLEC, respectively. The genotyping revealed considerable diversity within both environmental and clinical ESBLEC and the overrepresentation of some clonal complexes. Most of the sequence types displayed by the clinical isolates were also found in the environment. CTX-M enzymes were the most common enzymes whatever the origin of the isolates. CONCLUSIONS: The treatment at the WWTP led to the relative enrichment of ESBLEC. We estimated that >600 billion of ESBLEC are released into the river Doubs daily and the sludge produced by the WWTP, used as fertilizer, contains 2.6 × 10(5) ESBLEC per gram.

Advancements and Challenges in Handwritten Text Recognition: A Comprehensive Survey.

Handwritten Text Recognition (HTR) is essential for digitizing historical documents in different kinds of archives. In this study, we introduce a hybrid form archive written in French: the Belfort civil registers of births. The digitization of these historical documents is challenging due to their unique characteristics such as writing style variations, overlapped characters and words, and marginal annotations. The objective of this survey paper is to summarize research on handwritten text documents and provide research directions toward effectively transcribing this French dataset. To achieve this goal, we presented a brief survey of several modern and historical HTR offline systems of different international languages, and the top state-of-the-art contributions reported of the French language specifically. The survey classifies the HTR systems based on techniques employed, datasets used, publication years, and the level of recognition. Furthermore, an analysis of the systems' accuracies is presented, highlighting the best-performing approach. We have also showcased the performance of some HTR commercial systems. In addition, this paper presents a summarization of the HTR datasets that publicly available, especially those identified as benchmark datasets in the International Conference on Document Analysis and Recognition (ICDAR) and the International Conference on Frontiers in Handwriting Recognition (ICFHR) competitions. This paper, therefore, presents updated state-of-the-art research in HTR and highlights new directions in the research field.

Towards a better understanding of the long-lasting evolutionary history of Mycobacterium tuberculosis.

The daily increasing sequencing of Mycobacterium tuberculosis has made it possible to establish an advanced phylogeny of this bacterium. It currently includes 9 lineages mainly affecting humans, completed by animal lineages, which form the Mycobacterium tuberculosis complex. Inherited from various historical approaches, this phylogeny is now based on Single Nucleotide Polymorphisms (SNPs), of which updates are frequently proposed. We present here evidence that the task needs refinements: some lineages have currently suboptimal defining SNPs, and many sublineages still need to be named and characterized. These findings are based on a new tool specifically designed to index the entire existing sequencing data. In this article, we focus on lineages 4.5, 4.7, 6 and 7. We take the opportunity to present some evidence that TB-annotator shows strong relevance, identifying well supported sublineages, as well as good global agreement with previous findings.