Identification of Molds with Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry: Performance of the Newly Developed MSI-2 Application in Comparison with the Bruker Filamentous Fungi Database and MSI-1.

Matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) represents a promising tool for the rapid and efficient identification of molds, but improvements are still necessary to achieve satisfactory results when identifying cryptic species. Here, we aimed to validate a new web application, MSI-2, which replaces MSI-1, an application that was built and deployed online in 2017. For the evaluation, we gathered 633 challenging isolates obtained from daily hospital practice that were first identified with DNA-based methods, and we submitted their corresponding mass spectra to three identification programs (Bruker, MSI-1, and MSI-2). The MSI-2 application had a better identification performance at the species level than MSI-1 and Bruker, reaching 83.25% correct identifications, compared with 63.19% (MSI-1), 38.07% (Bruker with a 1.7 threshold), and 21.8% (Bruker with a 2.0 threshold). The MSI-2 application performed especially well for Aspergillus and Fusarium species, including for many cryptic species, reaching 90% correct identifications for Aspergillus species and 78% for Fusarium species compared to 69% and 43% with MSI-1. Such an improvement may have a positive impact on patient management by facilitating the identification of cryptic species potentially associated with a specific antifungal resistance profile.

Validation of a New Web Application for Identification of Fungi by Use of Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry.

Matrix-assisted laser desorption ionization-time of flight (MALDI-TOF) mass spectrometry has emerged as a reliable technique to identify molds involved in human diseases, including dermatophytes, provided that exhaustive reference databases are available. This study assessed an online identification application based on original algorithms and an extensive in-house reference database comprising 11,851 spectra (938 fungal species and 246 fungal genera). Validation criteria were established using an initial panel of 422 molds, including dermatophytes, previously identified via DNA sequencing (126 species). The application was further assessed using a separate panel of 501 cultured clinical isolates (88 mold taxa including dermatophytes) derived from five hospital laboratories. A total of 438 (87.35%) isolates were correctly identified at the species level, while 26 (5.22%) were assigned to the correct genus but the wrong species and 37 (7.43%) were not identified, since the defined threshold of 20 was not reached. The use of the Bruker Daltonics database included in the MALDI Biotyper software resulted in a much higher rate of unidentified isolates (39.76 and 74.30% using the score thresholds 1.7 and 2.0, respectively). Moreover, the identification delay of the online application remained compatible with real-time online queries (0.15 s per spectrum), and the application was faster than identifications using the MALDI Biotyper software. This is the first study to assess an online identification system based on MALDI-TOF spectrum analysis. We have successfully applied this approach to identify molds, including dermatophytes, for which diversity is insufficiently represented in commercial databases. This free-access application is available to medical mycologists to improve fungal identification.

Real Time Estimator to Perform Targeted Biopsies With a Free-Wrist Robot Despite Large Deformations of the Insertion Orifice.

In the context of keyhole surgery, and more particularly of uterine biopsy, the fine automatic movements of a surgical instrument held by a robot with 3 active DOF's require an exact knowledge of the point of rotation of the instrument. However, this center of rotation is not fixed and moves during an examination. This paper deals with a new method of detecting and updating the interaction matrix linking the movements of the robot with the surgical instrument. This is based on the method of updating the Jacobian matrix which is named the "Broyden method". It is able to take into account body tissue deformations in real time in order to improve the pointing task for automatic movements of a surgical instrument in an unknown environment.

Description of an integrated management system for invasive mosquitoes at entry-exit ports in Zhejiang, China.

BACKGROUND: As mosquitoes are one of the most harmful creatures in the world, recent high-frequency interceptions of invasive mosquito species have emphasized the need to enhance the biological security of the Zhejiang Province in China. As such, an integrated management system should be implemented to monitor the vectors of mosquito-borne diseases during data digitization and the processing of permanent E-forms and provide an online one-stop identification service. METHODS: This system is a semi-open network built on the latest Microsoft.NET Framework, Active Server Page.NET (ASP.NET) and Internet Information Services (IIS) for the Windows 2000 service as a basic infrastructure platform. This creates a physical separation between the data input as the back-page intranet and the online automated Lucid identification as the front-page internet through the digital interchange platform and security firewall. RESULTS: This system mainly comprises three core modules: automated statistical analysis of operational data, online vector identification and digital specimen storage management, in addition to accessory modules. The joint analysis of invasive and native data collected between 2011 and 2017 at 14 surveillance points in the Zhejiang Province, excluding Ningbo Port, provided insights into the geographical differences in species abundance and the dynamic nature of seasonal interception within the statistical analysis module. Most importantly, multi-access keys to mosquitoes based on Lucid software were loaded in the module for vector identification. Subscribers can utilize this procedure for the online identification of 2 subfamilies, 10 genera and 33 mosquitoes by selecting any typical morphological feature in the classification system that matches the current images at hand. CONCLUSIONS: Our report suggests that this system can enhance the ability to master the basic information on invasive mosquitoes and satisfy the increasing requirements for public health safety in the integrated management of vector-borne diseases.

A faunistic review of the Iranian species of Sphingonotus (Orthoptera, Oedipodinae) with an online key to species.

Sphingonotus is a species-rich genus of band-winged grasshoppers (Oedipodinae), comprising more than 170 species, with its diversity hotspots in the Mediterranean, and in Central and Eastern Asia. Iran represents one of the countries with the highest species diversity for the genus with a total of 31 recorded species. However, no study so far has provided a faunistic overview and no identification keys are available. Here, we present an annotated list of all Sphingonotus species found in Iran derived from records from field observations, museum collections and literature data. Based on morphological and distribution data we synonymize Sphingonotus intutus Saussure, 1888 syn. nov. under Sphingonotus nebulosus persa Saussure, 1884 and Sphingonotus obscuratus transcaspicus Uvarov, 1925 syn. nov. under Sphingonotus obscuratus brunneri Saussure, 1884. We present images of representative specimens (mostly types) of all species, as well as distribution maps and ecological data. Finally, we provide an online key to all known species of Sphingonotus from Iran, which will continuously be updated.

Adaptive MPC based on MIMO ARX-Laguerre model.

This paper proposes a method for synthesizing an adaptive predictive controller using a reduced complexity model. This latter is given by the projection of the ARX model on Laguerre bases. The resulting model is entitled MIMO ARX-Laguerre and it is characterized by an easy recursive representation. The adaptive predictive control law is computed based on multi-step-ahead finite-element predictors, identified directly from experimental input/output data. The model is tuned in each iteration by an online identification algorithms of both model parameters and Laguerre poles. The proposed approach avoids time consuming numerical optimization algorithms associated with most common linear predictive control strategies, which makes it suitable for real-time implementation. The method is used to synthesize and test in numerical simulations adaptive predictive controllers for the CSTR process benchmark.

A free-access online key to identify Amazonian ferns.

There is urgent need for more data on species distributions in order to improve conservation planning. A crucial but challenging aspect of producing high-quality data is the correct identification of organisms. Traditional printed floras and dichotomous keys are difficult to use for someone not familiar with the technical jargon. In poorly known areas, such as Amazonia, they also become quickly outdated as new species are described or ranges extended. Recently, online tools have allowed developing dynamic, interactive, and accessible keys that make species identification possible for a broader public. In order to facilitate identifying plants collected in field inventories, we developed an internet-based free-access tool to identify Amazonian fern species. We focused on ferns, because they are easy to collect and their edaphic affinities are relatively well known, so they can be used as an indicator group for habitat mapping. Our key includes 302 terrestrial and aquatic entities mainly from lowland Amazonian forests. It is a free-access key, so the user can freely choose which morphological features to use and in which order to assess them. All taxa are richly illustrated, so specimens can be identified by a combination of character choices, visual comparison, and written descriptions. The identification tool was developed in Lucid 3.5 software and it is available at http://keyserver.lucidcentral.org:8080/sandbox/keys.jsp.