Hybrid Approach to Colony-Forming Unit Counting Problem Using Multi-Loss U-Net Reformulation.

Colony-Forming Unit (CFU) counting is a complex problem without a universal solution in biomedical and food safety domains. A multitude of sophisticated heuristics and segmentation-driven approaches have been proposed by researchers. However, U-Net remains the most frequently cited and used deep learning method in these domains. The latter approach provides a segmentation output map and requires an additional counting procedure to calculate unique segmented regions and detect microbial colonies. However, due to pixel-based targets, it tends to generate irrelevant artifacts or errant pixels, leading to inaccurate and mixed post-processing results. In response to these challenges, this paper proposes a novel hybrid counting approach, incorporating a multi-loss U-Net reformulation and a post-processing Petri dish localization algorithm. Firstly, a unique innovation lies in the multi-loss U-Net reformulation. An additional loss term is introduced in the bottleneck U-Net layer, focusing on the delivery of an auxiliary signal that indicates where to look for distinct CFUs. Secondly, the novel localization algorithm automatically incorporates an agar plate and its bezel into the CFU counting techniques. Finally, the proposition is further enhanced by the integration of a fully automated solution, which comprises a specially designed uniform Petri dish illumination system and a counting web application. The latter application directly receives images from the camera, processes them, and sends the segmentation results to the user. This feature provides an opportunity to correct the CFU counts, offering a feedback loop that contributes to the continued development of the deep learning model. Through extensive experimentation, the authors of this paper have found that all probed multi-loss U-Net architectures incorporated into the proposed hybrid approach consistently outperformed their single-loss counterparts, as well as other comparable models such as self-normalized density maps and YOLOv6, by at least 1% to 3% in mean absolute and symmetric mean absolute percentage errors. Further significant improvements were also reported through the means of the novel localization algorithm. This reaffirms the effectiveness of the proposed hybrid solution in addressing contemporary challenges of precise in vitro CFU counting.

Caught red handed: modeling and confirmation of the myeloperoxidase ceruloplasmin alpha-thrombin complex.

The work is devoted to the study of the structural characteristics of the myeloperoxidase-ceruloplasmin-thrombin complex using small-angle neutron scattering methods in combination with computer modeling, as well as surface plasmon resonance and solid-phase enzyme assay. We have previously shown that the functioning of active myeloperoxidase during inflammation, despite the presence in the blood of an excess of ceruloplasmin which inhibits its activity, is possible due to the partial proteolysis of ceruloplasmin by thrombin. In this study, the myeloperoxidase-ceruloplasmin-thrombin heterohexamer was obtained in vitro. The building of a heterohexamer full-atomic model in silico, considering the glycosylation of the constituent proteins, confirmed the absence of steric barriers for the formation of protein-protein contacts. It was shown that the partial proteolysis of ceruloplasmin does not affect its ability to bind to myeloperoxidase, and a structural model of the heterohexamer was obtained using the small-angle neutron scattering method.

Multi-Class CNN for Classification of Multispectral and Autofluorescence Skin Lesion Clinical Images.

In this work, we propose to use an artificial neural network to classify limited data of clinical multispectral and autofluorescence images of skin lesions. Although the amount of data is limited, the deep convolutional neural network classification of skin lesions using a multi-modal image set is studied and proposed for the first time. The unique dataset consists of spectral reflectance images acquired under 526 nm, 663 nm, 964 nm, and autofluorescence images under 405 nm LED excitation. The augmentation algorithm was applied for multi-modal clinical images of different skin lesion groups to expand the training datasets. It was concluded from saliency maps that the classification performed by the convolutional neural network is based on the distribution of the major skin chromophores and endogenous fluorophores. The resulting classification confusion matrices, as well as the performance of trained neural networks, have been investigated and discussed.

At the Pulse of Time: Machine Vision in Retinal Videos.

Spontaneous venous pulsations (SVP) are a common finding in healthy people. The absence of SVP is associated with rapid progression in glaucoma and increased intracranial pressure. Traditionally, SVP has been documented qualitatively by clinicians during biomicroscopy. Nowadays numerous imaging devices recording the fundus exist. Hence, video data for objectification of SVP is readily available. Still, these clinical datasets are afflicted with various quality issues and artifacts. In this machine vision based study, we explore methods to overcome challenges in identifying SVP in fundus videos of varying quality and provide a detailed protocol thereof. Hereby, we aim to lower the burden of access of implementing machine vision in clinical video datasets and quantification of SVP.

DDAO Controlled Synthesis of Organo-Modified Silica Nanoparticles with Encapsulated Fluorescent Boron Dipyrrins and Study of Their Uptake by Cancerous Cells.

The design of cargo carriers with high biocompatibility, unique morphological characteristics, and capability of strong bonding of fluorescent dye is highly important for the development of a platform for smart imaging and diagnostics. In this paper, BODIPY-doped silica nanoparticles were prepared through a "one-pot" soft-template method using a sol-gel process. Several sol-gel precursors have been used in sol-gel synthesis in the presence of soft-template to obtain the silica-based materials with the most appropriate morphological features for the immobilization of BODIPY molecules. Obtained silica particles have been shown to be non-cytotoxic and can be effectively internalized into the cervical cancer cell line (HeLa). The described method of synthesis allows us to obtain silica-based carriers with an immobilized fluorescent dye that provide the possibility for real-time imaging and detection of these carriers.

Anaplasmosis: experimental immunodeficient state model.

OBJECTIVE: Introduction: The recently described anaplasmosis infection is widespread but concerns to the insufficiently known group of diseases. The aim of our research is the development of uniform biological model for reproducing of artificial immunodeficient state by experimental anaplasmosis. PATIENTS AND METHODS: Materials and methods: Algorithm of experimental anaplasmosis reproducing, consisted of such consecutive stages: 1) artificial forming of the immunodeficient state at nonlinear white mise (Mus musculus L.); 2) preparation of the tested biological material samples; 3) inoculation by prepared samples of the laboratory animals with the artificially formed immunodeficient state; 4) sampling from the dead or slaughtered (by the method of chloroformed anesthesia) experimental animals of sectional material (organs and targets tissues); 5) verification of aetiology by express detection of causative agents by the method of PCR in the selected samples of sectional material. RESULTS: Results: Biological model of experimental anaplasmosis have been created suitable for realization of both diagnostic and epidemiological, epizootic, ecobiological and other researches of different origin biological material samples, including samples of solid and liquid consistency material. Formed model realised in premature death of experimental animals in 17.4 % cases; resulted in an onset of disease clinical signs without death during the term of supervision in 43.8 % cases; coursed in the absence of the expressed symptoms of infection in 31.3 % cases. CONCLUSION: Conclusions: Developed biological model of experimental anaplasmosis consists in that as laboratory animals with the increased sensitiveness to the infection and accumulation of causative agent are used white nonlinear mice with the artificially formed immunodeficient state.

Measuring biological age in mice using differential mass spectrometry.

Aging is an ill-defined process that increases the risk of morbidity and mortality. Aging is also heterogeneous meaning that biological and chronological age can differ. Here, we used unbiased differential mass spectrometry to quantify thousands of proteins in mouse liver and select those that that consistently change in expression as mice age. A panel of 14 proteins from inbred C57BL/6 mice was used to equate chronological and biological age in this reference population, against which other mice could be compared. This "biological age calculator" identified two strains of f1 hybrid mice as biologically younger than inbred mice and progeroid mice as being biologically older. In an independent validation experiment, the calculator identified mice treated with rapamycin, known to extend lifespan of mice, as 18% younger than mice fed a placebo diet. This demonstrates that it is possible to measure subtle changes in biologic age in mammals using a proteomics approach.

High Resolution Discovery Proteomics Reveals Candidate Disease Progression Markers of Alzheimer's Disease in Human Cerebrospinal Fluid.

Disease modifying treatments for Alzheimer's disease (AD) constitute a major goal in medicine. Current trends suggest that biomarkers reflective of AD neuropathology and modifiable by treatment would provide supportive evidence for disease modification. Nevertheless, a lack of quantitative tools to assess disease modifying treatment effects remains a major hurdle. Cerebrospinal fluid (CSF) biochemical markers such as total tau, p-tau and Ab42 are well established markers of AD; however, global quantitative biochemical changes in CSF in AD disease progression remain largely uncharacterized. Here we applied a high resolution open discovery platform, dMS, to profile a cross-sectional cohort of lumbar CSF from post-mortem diagnosed AD patients versus those from non-AD/non-demented (control) patients. Multiple markers were identified to be statistically significant in the cohort tested. We selected two markers SME-1 (p<0.0001) and SME-2 (p = 0.0004) for evaluation in a second independent longitudinal cohort of human CSF from post-mortem diagnosed AD patients and age-matched and case-matched control patients. In cohort-2, SME-1, identified as neuronal secretory protein VGF, and SME-2, identified as neuronal pentraxin receptor-1 (NPTXR), in AD were 21% (p = 0.039) and 17% (p = 0.026) lower, at baseline, respectively, than in controls. Linear mixed model analysis in the longitudinal cohort estimate a decrease in the levels of VGF and NPTXR at the rate of 10.9% and 6.9% per year in the AD patients, whereas both markers increased in controls. Because these markers are detected by mass spectrometry without the need for antibody reagents, targeted MS based assays provide a clear translation path for evaluating selected AD disease-progression markers with high analytical precision in the clinic.

Application of an end-to-end biomarker discovery platform to identify target engagement markers in cerebrospinal fluid by high resolution differential mass spectrometry.

The rapid identification of protein biomarkers in biofluids is important to drug discovery and development. Here, we describe a general proteomic approach for the discovery and identification of proteins that exhibit a statistically significant difference in abundance in cerebrospinal fluid (CSF) before and after pharmacological intervention. This approach, differential mass spectrometry (dMS), is based on the analysis of full scan mass spectrometry data. The dMS workflow does not require complex mixing and pooling strategies, or isotope labeling techniques. Accordingly, clinical samples can be analyzed individually, allowing the use of longitudinal designs and within-subject data analysis in which each subject acts as its own control. As a proof of concept, we performed multifactorial dMS analyses on CSF samples drawn at 6 time points from n = 6 cisterna magna ported (CMP) rhesus monkeys treated with 2 potent gamma secretase inhibitors (GSI) or comparable vehicle in a 3-way crossover study that included a total of 108 individual CSF samples. Using analysis of variance and statistical filtering on the aligned and normalized LC-MS data sets, we detected 26 features that were significantly altered in CSF by drug treatment. Of those 26 features, which belong to 10 distinct isotopic distributions, 20 were identified by MS/MS as 7 peptides from CD99, a cell surface protein. Six features from the remaining 3 isotopic distributions were not identified. A subsequent analysis showed that the relative abundance of these 26 features showed the same temporal profile as the ELISA measured levels of CSF A beta 42 peptide, a known pharmacodynamic marker for gamma-secretase inhibition. These data demonstrate that dMS is a promising approach for the discovery, quantification, and identification of candidate target engagement biomarkers in CSF.

Dynamic host energetics and cytoskeletal proteomes in human immunodeficiency virus type 1-infected human primary CD4 cells: analysis by multiplexed label-free mass spectrometry.

We report on a proteomic analysis of ex vivo human immunodeficiency virus (HIV) type 1 infection in human primary CD4 cells by shotgun liquid chromatography-tandem mass spectrometry analysis, revealing two distinct proteomic profiles at two phases of virus replication. Relative to mock-infected cells, 168 signature proteins exhibited abundance changes at the first sign of Gag p24 production (8 h postinfection [p.i.]) or the peak of virus replication (24 h p.i.); interestingly, most of the changes were exclusive to only one phase of virus replication. Based on characterization by functional ontology and known human-HIV protein interactions, we observed the enrichment for protein abundance increases pertaining to protein synthesis and nucleasomal reorganization amid an otherwise placid cellular proteome at the first sign of HIV replication. In contrast, we observed indications of decreased protein turnover, concomitant with heightened DNA repair activities and preludes to apoptosis, in the presence of robust virus replication. We also observed hints of disruptions in protein and small molecule trafficking. Our label-free proteomic strategy allowed us to perform multiplexed comparisons-we buttressed our detection specificity with the use of a reverse transcriptase inhibitor as a counterscreen, enabling highlighting of cellular protein abundance changes unique to robust virus replication as opposed to viral entry. In conjunction with complementary high-throughput screens for cellular partners of HIV, we put forth a model pinpointing specific rerouting of cellular biosynthetic, energetic, and trafficking pathways as HIV replication accelerates in human primary CD4 cells.