Temporal stratification of amyotrophic lateral sclerosis patients using disease progression patterns.

Identifying groups of patients with similar disease progression patterns is key to understand disease heterogeneity, guide clinical decisions and improve patient care. In this paper, we propose a data-driven temporal stratification approach, ClusTric, combining triclustering and hierarchical clustering. The proposed approach enables the discovery of complex disease progression patterns not found by univariate temporal analyses. As a case study, we use Amyotrophic Lateral Sclerosis (ALS), a neurodegenerative disease with a non-linear and heterogeneous disease progression. In this context, we applied ClusTric to stratify a hospital-based population (Lisbon ALS Clinic dataset) and validate it in a clinical trial population. The results unravelled four clinically relevant disease progression groups: slow progressors, moderate bulbar and spinal progressors, and fast progressors. We compared ClusTric with a state-of-the-art method, showing its effectiveness in capturing the heterogeneity of ALS disease progression in a lower number of clinically relevant progression groups.

Biclustering data analysis: a comprehensive survey.

Biclustering, the simultaneous clustering of rows and columns of a data matrix, has proved its effectiveness in bioinformatics due to its capacity to produce local instead of global models, evolving from a key technique used in gene expression data analysis into one of the most used approaches for pattern discovery and identification of biological modules, used in both descriptive and predictive learning tasks. This survey presents a comprehensive overview of biclustering. It proposes an updated taxonomy for its fundamental components (bicluster, biclustering solution, biclustering algorithms, and evaluation measures) and applications. We unify scattered concepts in the literature with new definitions to accommodate the diversity of data types (such as tabular, network, and time series data) and the specificities of biological and biomedical data domains. We further propose a pipeline for biclustering data analysis and discuss practical aspects of incorporating biclustering in real-world applications. We highlight prominent application domains, particularly in bioinformatics, and identify typical biclusters to illustrate the analysis output. Moreover, we discuss important aspects to consider when choosing, applying, and evaluating a biclustering algorithm. We also relate biclustering with other data mining tasks (clustering, pattern mining, classification, triclustering, N-way clustering, and graph mining). Thus, it provides theoretical and practical guidance on biclustering data analysis, demonstrating its potential to uncover actionable insights from complex datasets.

Electric Current Application on Dental Implant Biofilms: Review.

The prevalence of complications due to the presence of biofilms in dental implant surfaces and their relationship with peri-implant diseases, namely peri-implantitis, remain difficult problems to overcome. The information available about the application of electric current on dental implant biofilms; its parameters, namely current level, voltage and exposure time; and related effects are still not enough to understand which individual mechanisms are caused by this technique, culminating in the decrease or eradication of the biofilm. The purpose of this narrative review, based on a systematic search, is to understand the effect of electric current directly applied to biofilms present in dental implants and which parameters are used. For the systematic search, electronic databases including MEDLINE/PubMed, Scopus, and Web of Science, up to and including November 2023, were searched. Seven studies were included. A 12-item checklist was used to assess their methodological quality. All studies used direct/constant electric current; however, that use was not achieved by the same protocol/set-up. Parameters such as current, voltage, resistance, and actuation time were different in all studies. Monospecies and multi-species biofilm were used in the substrate made of titanium. The results indicate that the use of constant and alternating electric current directly applied to dental implant's surfaces is a promising way to treat problems related to biofilms and peri-implant diseases. Future trials, namely in vivo tests, are necessary to reveal all the potential of this treatment.

Zirconia Dental Implants Surface Electric Stimulation Impact on Staphylococcus aureus.

Tooth loss during the lifetime of an individual is common. A strategy to treat partial or complete edentulous patients is the placement of dental implants. However, dental implants are subject to bacterial colonization and biofilm formation, which cause an infection named peri-implantitis. The existing long-term treatments for peri-implantitis are generally inefficient. Thus, an electrical circuit was produced with zirconia (Zr) samples using a hot-pressing technique to impregnate silver (Ag) through channels and holes to create a path by LASER texturing. The obtained specimens were characterized according to vitro cytotoxicity, to ensure ZrAg non-toxicity. Furthermore, samples were inoculated with Staphylococcus aureus using 6.5 mA of alternating current (AC). The current was delivered using a potentiostat and the influence on the bacterial concentration was assessed. Using AC, the specimens displayed no bacterial adhesion (Log 7 reduction). The in vitro results presented in this study suggest that this kind of treatment can be an alternative and promising strategy to treat and overcome bacterial adhesion around dental implants that can evolve to biofilm.

Mosquito (Diptera: Culicidae) Fauna of a Zoological Park in an Urban Setting: Analysis of Culex pipiens s.l. and Their Biotypes.

Mosquito-borne diseases (MBDs) are important emerging diseases that affect humans and animals. Zoological parks can work as early warning systems for the occurrence of MBDs. In this study, we characterized the mosquito fauna captured inside Lisbon Zoo from May 2018 to November 2019. An average of 2.4 mosquitos per trap/night were captured. Five mosquito species potentially causing MBDs, including Culex pipiens biotypes, were found in the zoo. The sympatric occurrence of Culex pipiens biotypes represents a risk factor for the epizootic transmission of West Nile virus and Usutu virus. The mosquito occurrence followed the expected seasonality, with the maximum densities during summer months. However, mosquito activity was detected in winter months in low numbers. The minimum temperature and the relative humidity (RH) on the day of capture showed a positive effect on Culex pipiens abundance. Contrary, the RH the week before capture and the average precipitation the week of capture had a negative effect. No invasive species were identified, nor have flaviviruses been detected in the mosquitoes. The implementation of biosecurity measures regarding the hygiene of the premises and the strict control of all the animals entering the zoo can justify the low prevalence of mosquitoes and the absence of flavivirus-infected mosquitoes.