Search Results (10)

In this work, we describe the implementation of an infrastructure of conversational chatbots by using natural language processing and training within the Rasa framework. We use this infrastructure to create a chatbot assistant for the users of a bioinformatics suite. This suite provides a customized interface solution for omic pipelines and workflows, and it is named GPRO. The infrastructure has also been used to build another chatbot for a Laboratory Information Management System (LIMS). The two chatbots (namely, Genie and Abu) have been built on an open framework that uses natural language understanding (NLU) and machine learning techniques to understand user queries and respond to them. Users can seamlessly interact with the chatbot to receive support on navigating the GPRO pipelines and workflows. The chatbot provides a bridge between users and the wealth of bioinformatics knowledge available online. Full article

This study describes the roles of laboratory information management systems (LIMS) in multi-site genetics studies in Africa. We used the HiGeneS Africa project as a case study. The study participants were recruited in six African countries between 2019 to 2021. The Baobab LIMS, a server–client-based system (an African-led innovation) was used for the coordination of the biospecimen. The development phase of the LIMS showcased the team formation, data collection, biospecimen collection, and shipment strategies. The implementation phase showcased the biospecimen registration, processing, and quality control (QC) analytics. The sample QC was done using Nanodrop, Qubit, and PicoGreen/gDNATapestation assays. The results showed that a total of 3144 study participants were recruited from Cameroon, Ghana, Mali, Rwanda, Senegal, and South Africa. The biospecimen registration provided a comprehensive registry that included patient demographics, genetic information, and clinical and blood/saliva samples from the proband and family relatives. The QC analyzes identified 30 samples that failed QC, linked to overdue storage in the freezer before DNA extraction. The LIMS components implemented in this project formed a structure that can be upscaled to artificial intelligence-based LIMS. In conclusion, this study represents the largest and the most diverse collection of biospecimens for the genetic study of hearing impairment in Africa to date. A well-characterized LIMS should be recommended for multi-site molecular studies, particularly in Africa, to enhance African participation in global genomic medicine. Full article

In a chemical analysis laboratory, sample detection via most analytical devices obtains raw data and processes it to validate data reports, including raw data filtering, editing, effectiveness evaluation, error correction, etc. This process is usually carried out manually by analysts. When the sample detection volume is large, the data processing involved becomes time-consuming and laborious, and manual errors may be introduced. In addition, analytical laboratories typically use a variety of analytical devices with different measurement principles, leading to the use of various heterogeneous control software systems from different vendors with different export data formats. Different formats introduce difficulties to laboratory automation. This paper proposes a modular data evaluation system that uses a global unified management and maintenance mode that can automatically filter data, evaluate quality, generate valid reports, and distribute reports. This modular software design concept allows the proposed system to be applied to different analytical devices; its integration into existing laboratory information management systems (LIMS) could maximise automation and improve the analysis and testing quality and efficiency in a chemical analysis laboratory, while meeting the analysis and testing requirements. Full article

As newborn screening programs transition from paper-based data exchange toward automated, electronic methods, significant data exchange challenges must be overcome. This article outlines a data model that maps newborn screening data elements associated with patient demographic information, birthing facilities, laboratories, result reporting, and follow-up care to the LOINC, SNOMED CT, ICD-10-CM, and HL7 healthcare standards. The described framework lays the foundation for the implementation of standardized electronic data exchange across newborn screening programs, leading to greater data interoperability. The use of this model can accelerate the implementation of electronic data exchange between healthcare providers and newborn screening programs, which would ultimately improve health outcomes for all newborns and standardize data exchange across programs. Full article

In the case of rapid outbreaks of infectious diseases in remote locations, the lack of real-time information from the field and rapid spread of misinformation can be a major issue. To improve situational awareness and decision-making at all levels of operational deployment, there is an urgent need for accurate, reliable, and timely results from patients from the affected area. This requires a robust and fast channel of communication connecting first responders on-site, crisis managers, decision-makers, and the institutions involved in the survey of the crisis at national, regional, and international levels. This has been the rationale sustaining the development of advanced communication tools in the Biological Light Fieldable Laboratory for Emergencies (B-LiFE). The benefit of terrestrial (TETRA, LTE, 5G, and Wi-Fi-Fi) and SatCom communications is illustrated through a series of missions and exercises conducted in the previous five years. These tools were used by B-LiFE operators to provide accurate, comprehensive, timely, and relevant information and services in real time. The focus of this article is to discuss the development and benefits of the integration of multi-mission, multi-user nomadic, rapidly deployable telecommunication nodes for emergency uses (TEN) in the capacity of B-LiFE. Providing reliable communication channels through TEN enables the development and use of an ICT toolbox called MIML_LIMS (multi-institution, multi-mission, multi-laboratory LIMS), a tool which is mandatory for efficient and secure data management and data sharing by a mobile laboratory. Full article

This paper reports the results of serological tests for the detection of antibodies against Leishmania spp. in Abruzzo and Molise regions from 2009 to 2014, with the aim of evaluating the presence and distribution of canine leishmaniasis. Data were extracted from the Laboratory Information Management System (LIMS) of the Istituto Zooprofilattico Sperimentale of Abruzzo and Molise, and then the dog identification numbers were matched with those stored in the Canine Registries of the two regions to get information about the age of dogs at time of testing. Dogs were considered positive when having an IFAT (Indirect Fluorescent Antibody Test) titer ≥1:80. In total, 41,631 dogs were tested, 85.3% from Abruzzo and 14.7% from Molise. At the provincial level, the percentage of positive dogs ranged from 5.2% (L’Aquila, Abruzzo region) to 21.8% (Campobasso, Molise region). Findings are consistent with the hypothesis that in the coastal areas, the relationships between the host, the vector, and the agent are more favorable for the spreading of CanL, and it seems that densely populated urban internal areas have less favorable conditions. Being a dog hosted in a kennel seems not to be a factor increasing the probability that dogs show positivity, even in long-term sheltering conditions. Full article

Previous research has shown that a MALDI-MS technique can be used to screen for sickle cell disease (SCD), and that a system combining automated sample preparation, MALDI-MS analysis and classification software is a relevant approach for first-line, high-throughput SCD screening. In order to achieve a high-throughput “plug and play” approach while detecting “non-standard” profiles that might prompt the misclassification of a sample, we have incorporated various sets of alerts into the decision support software. These included “biological alert” indicators of a newborn’s clinical status (e. g., detecting samples with no or low HbA), and “technical alerts” indicators for the most common non-standard profiles, i.e., those which might otherwise lead to sample misclassification. We evaluated these alerts by applying them to two datasets (produced by different laboratories). Despite the random generation of abnormal spectra by one-off technical faults or due to the nature and quality of the samples, the use of alerts fully secured the process of automatic sample classification. Firstly, cases of β-thalassemia were detected. Secondly, after a visual check on the tagged profiles and reanalysis of the corresponding biological samples, all the samples were correctly reclassified without prompting further alerts. All of the samples for which the results were not tagged were well classified (i.e., sensitivity and specificity = 1). The alerts were mainly designed for detecting false-negative classifications; all the FAS samples misclassified by the software as FA (a false negative) were marked with an alert. The implementation of alerts in the NeoScreening^® Laboratory Information Management System’s decision support software opens up perspectives for the safe, reliable, automated classification of samples, with a visual check solely on abnormal results or samples. It should now be possible to evaluate the combination of the NeoSickle^® analytical solution and the NeoScreening^® Laboratory Information Management System in a real-life, prospective study of first-line SCD screening. Full article

Information Management Systems are the central process management and communication hub for many newborn screening programs. In late 2014, Newborn Screening Ontario (NSO) undertook an end to end assessment of its information management needs which resulted in a project to develop a flexible IS Information Systems (IS) ecosystem and related process changes. This enabled NSO to better manage its current and future work-flows and communication needs. An idealized vision of a Screening Information Management System (SIMS) was developed that was refined into enterprise and functional architectures. This was followed by the development of technical specifications, user requirements and procurement. In undertaking a holistic full product lifecycle redesign approach, a number of change management challenges were faced by NSO across the entire program. Strong leadership support and full program engagement are key for overall project success. It is anticipated that improvements in program flexibility and the ability to innovate will outweigh the efforts and costs. Full article

The Translational Genomics Core (TGC) at Partners Personalized Medicine (PPM) serves as a fee-for-service core laboratory for Partners Healthcare researchers, providing access to technology platforms and analysis pipelines for genomic, transcriptomic, and epigenomic research projects. The interaction of the TGC with various components of PPM provides it with a unique infrastructure that allows for greater IT and bioinformatics opportunities, such as sample tracking and data analysis. The following article describes some of the unique opportunities available to an academic research core operating within PPM, such the ability to develop analysis pipelines with a dedicated bioinformatics team and maintain a flexible Laboratory Information Management System (LIMS) with the support of an internal IT team, as well as the operational challenges encountered to respond to emerging technologies, diverse investigator needs, and high staff turnover. In addition, the implementation and operational role of the TGC in the Partners Biobank genotyping project of over 25,000 samples is presented as an example of core activities working with other components of PPM. Full article

One of the most crucial characteristics of day-to-day laboratory information management is the collection, storage and retrieval of information about research subjects and environmental or biomedical samples. An efficient link between sample data and experimental results is absolutely important for the successful outcome of a collaborative project. Currently available software solutions are largely limited to large scale, expensive commercial Laboratory Information Management Systems (LIMS). Acquiring such LIMS indeed can bring laboratory information management to a higher level, but most of the times this requires a sufficient investment of money, time and technical efforts. There is a clear need for a light weighted open source system which can easily be managed on local servers and handled by individual researchers. Here we present a software named SaDA for storing, retrieving and analyzing data originated from microorganism monitoring experiments. SaDA is fully integrated in the management of environmental samples, oligonucleotide sequences, microarray data and the subsequent downstream analysis procedures. It is simple and generic software, and can be extended and customized for various environmental and biomedical studies. Full article