Influence of Dead Cells Killed by Industrial Biocides (BAC and DBNPA) on Biofilm Formation.

Industrial biocides aim to keep water systems microbiologically controlled and to minimize biofouling. However, the resulting dead cells are usually not removed from the water streams and can influence the growth of the remaining live cells in planktonic and sessile states. This study aims to understand the effect of dead Pseudomonas fluorescens cells killed by industrial biocides-benzalkonium chloride (BAC) and 2,2-dibromo-3-nitrilopropionamide (DBNPA)-on biofilm formation. Additionally, the effect of different dead/live cell ratios (50.00% and 99.99%) was studied. The inoculum was recirculated in a Parallel Plate Flow Cell (PPFC). The overall results indicate that dead cells greatly affect biofilm properties. Inoculum with DBNPA-dead cells led to more active (higher ATP content and metabolic activity) and thicker biofilm layers in comparison to BAC-dead cells, which seems to be linked to the mechanism of action by which the cells were killed. Furthermore, higher dead cell ratios (99.99%) in the inoculum led to more active (higher culturability, metabolic activity and ATP content) and cohesive/compact and uniformly distributed biofilms in comparison with the 50.00% dead cell ratio. The design of future disinfection strategies must consider the contribution of dead cells to the biofilm build-up, as they might negatively affect water system operations.

3D Optical Coherence Tomography image processing in BISCAP: characterization of biofilm structure and properties.

MOTIVATION: BISCAP is a state-of-the-art tool for automatically characterizing biofilm images obtained from Optical Coherence Tomography. Limited availability of other software tools is reported in the field. BISCAP's first version processes 2D images only. Processing 3D images is a problem of greater scientific relevance since it deals with the entire structure of biofilms instead of their 2D slices. RESULTS: Building on the image-processing principles and algorithms proposed earlier for 2D images, these were adapted to the 3D case, and a more general implementation of BISCAP was developed. The primary goal concerns the extension of the initial methodology to incorporate the depth axis in 3D images; multiple improvements were also made to boost computational performance. The calculation of structural properties and visual outputs was extended to offer new insights into the 3D structure of biofilms. BISCAP was tested using 3D images of biofilms with different morphologies, consistently delivering accurate characterizations of 3D structures in a few minutes using standard laptop machines. Low user dependency is required for image analysis. AVAILABILITY AND IMPLEMENTATION: BISCAP is available from https://github.com/diogonarciso/BISCAP. All images used in the tutorials and the validation examples are available from https://web.fe.up.pt/∼fgm/biscap3d.

The Effectiveness of Pilates Training Interventions on Older Adults' Balance: A Systematic Review and Meta-Analysis of Randomized Controlled Trials.

BACKGROUND AND OBJECTIVES: Pilates training intervention programs have gained attention as a potential approach to enhancing balance in older adults, thereby reducing the risk of falls. In light of these considerations, this systematic review and meta-analysis aimed to critically evaluate the existing evidence and determine the effect of Pilates training intervention programs on older adults' balance. MATERIALS AND METHODS: The literature was searched through the PubMed, Web of Science, and Scopus databases from inception until July 2023. The primary keywords used for the literature search included "elderly" or "older adults" and "pilates training" and "balance". RESULTS: The systematic review through qualitative analysis showed robust evidence about the efficacy of Pilates intervention programs in improving older adults' balance. The pooled meta-analysis of static and dynamic balance showed that eight (53%) out of a total fifteen analyzed interventions presented a significant effect of Pilates in improving the participants' balance, without between-study heterogeneity. In addition, the meta-analysis regarding dynamic balance showed that six (67%) out of nine analyzed interventions presented a significant effect of Pilates in improving the participants' balance, without heterogeneity between studies. Similarly, the meta-analysis regarding static balance showed that four (50%) out of eight analyzed studies presented significant effects on the older adults' balance, where moderate between-study heterogeneity was found. Sensitivity analysis showed that three studies reduced the between-study heterogeneity (19, 17.6, and 17%), regressing from moderate to low heterogeneity, p < 0.05. CONCLUSIONS: This systematic review and meta-analysis underscores the potential of Pilates training as a valuable intervention to enhance balance in the elderly population.

Characterization of biofilm structure and properties via processing of 2D optical coherence tomography images in BISCAP.

MOTIVATION: Processing of Optical Coherence Tomography (OCT) biofilm images is currently restricted to a set of custom-made MATLAB scripts. None of the tools currently available for biofilm image processing (including those developed for Confocal Laser Scanning Microscopy-CLSM) enable a fully automatic processing of 2D OCT images. RESULTS: A novel software tool entitled Biofilm Imaging and Structure Classification Automatic Processor (BISCAP) is presented. It was developed specifically for the automatic processing of 2D OCT biofilm images. The proposed approach makes use of some of the key principles used in CLSM image processing, and introduces a novel thresholding algorithm and substratum detection strategy. Two complementary pixel continuity checks are executed, enabling very detailed pixel characterizations. BISCAP delivers common structural biofilm parameters and a set of processed images for biofilm analysis. A novel biofilm 'compaction parameter' is suggested. The proposed strategy was tested on a set of 300 images with highly satisfactory results obtained. BISCAP is a Python-based standalone application, not requiring any programming knowledge or property licenses, and where all operations are managed via an intuitive Graphical User Interface. The automatic nature of this image processing strategy decreases biasing problems associated to human-perception and allows a reliable comparison of outputs. AVAILABILITY AND IMPLEMENTATION: BISCAP and a collection of biofilm images obtained from OCT scans can be found at: https://github.com/diogonarciso/BISCAP. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.