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PurposeThe relentless rise in antimicrobial resistance is a major societal challenge and requires, as part of its solution, a better understanding of bacterial colonization and infection. To facilitate this, we developed a highly efficient no-wash red optical molecular imaging agent that enables the rapid, selective, and specific visualization of Gram-positive bacteria through a bespoke optical fiber–based delivery/imaging endoscopic device.MethodsWe rationally designed a no-wash, red, Gram-positive-specific molecular imaging agent (Merocy-Van) based on vancomycin and an environmental merocyanine dye. We demonstrated the specificity and utility of the imaging agent in escalating in vitro and ex vivo whole human lung models (n = 3), utilizing a bespoke fiber–based delivery and imaging device, coupled to a wide-field, two-color endomicroscopy system.ResultsThe imaging agent (Merocy-Van) was specific to Gram-positive bacteria and enabled no-wash imaging of S. aureus within the alveolar space of whole ex vivo human lungs within 60 s of delivery into the field-of-view, using the novel imaging/delivery endomicroscopy device.ConclusionThis platform enables the rapid and specific detection of Gram-positive bacteria in the human lung.

Pulmonary-resident memory T cells (T ) and B cells (B ) orchestrate protective immunity to reinfection with respiratory pathogens. Developing methods for the detection of these populations would benefit both research and clinical settings. To address this need, we developed a novel immunolabelling approach combined with clinic-ready fibre-based optical endomicroscopy (OEM) to detect canonical markers of lymphocyte tissue residency in human lungs undergoing lung ventilation (EVLV). Initially, cells from human lung digests (confirmed to contain T /B populations using flow cytometry) were stained with CD69 and CD103/CD20 fluorescent antibodies and imaged using KronoScan, demonstrating it's ability to detect antibody labelled cells. We next instilled these pre-labelled cells into human lungs undergoing EVLV and confirmed they could still be visualised using both fluorescence intensity and lifetime imaging against background lung architecture. Finally, we instilled fluorescent CD69 and CD103/CD20 antibodies directly into the lung and were able to detect T /B following labelling within seconds of direct delivery of microdoses of fluorescently labelled antibodies. , no wash, immunolabelling with OEM imaging is a novel methodology with the potential to expand the experimental utility of EVLV and pre-clinical models.

The use of optical techniques to interrogate wide ranging samples from semiconductors to biological tissue for rapid analysis and diagnostics has gained wide adoption over the past decades. The desire to collect ever more spatially, spectrally and temporally detailed optical signatures for sample characterization has specifically driven a sharp rise in new optical microscopy technologies. Here we present a high-speed optical scanning microscope capable of capturing time resolved images across 512 spectral and 32 time channels in a single acquisition with the potential for ~0.2 frames per second (256 × 256 image pixels). Each pixel in the resulting images contains a detailed data cube for the study of diverse time resolved light driven phenomena. This is enabled by integration of system control electronics and on-chip processing which overcomes the challenges presented by high data volume and low imaging speed, often bottlenecks in previous systems. High data volumes from multidimensional imaging techniques can lead to slow collection and processing times. Here, the authors implement multispectral fluorescence lifetime imaging microscopy (FLIM) that uses time-correlated photon counting technology to reach simultaneously high imaging rates combined with high spectral and temporal resolution.

In this paper, we introduce our unique dataset of fluorescence lifetime imaging endo/microscopy (FLIM), containing over 100,000 different FLIM images collected from 18 pairs of cancer/non-cancer human lung tissues of 18 patients by our custom fibre-based FLIM system. The aim of providing this dataset is that more researchers from relevant fields can push forward this particular area of research. Afterwards, we describe the best practice of image post-processing suitable per the dataset. In addition, we propose a novel hierarchically aggregated multi-scale architecture to improve the binary classification performance of classic CNNs. The proposed model integrates the advantages of multi-scale feature extraction at different levels, where layer-wise global information is aggregated with branch-wise local information. We integrate the proposal, namely ResNetZ, into ResNet, and appraise it on the FLIM dataset. Since ResNetZ can be configured with a shortcut connection and the aggregations by Addition or Concatenation , we first evaluate the impact of different configurations on the performance. We thoroughly examine various ResNetZ variants to demonstrate the superiority. We also compare our model with a feature-level multi-scale model to illustrate the advantages and disadvantages of multi-scale architectures at different levels.

Bacterial infections remain among the biggest challenges to human health, leading to high antibiotic usage, morbidity, hospitalizations, and accounting for approximately 8 million deaths worldwide every year. The overuse of antibiotics and paucity of antimicrobial innovation has led to antimicrobial resistant pathogens that threaten to reverse key advances of modern medicine. Photodynamic therapeutics can kill bacteria but there are few agents that can ablate pathogens with minimal off-target effects. We describe nitrobenzoselenadiazoles as some of the first environmentally sensitive organic photosensitizers, and their adaptation to produce theranostics with optical detection and light-controlled antimicrobial activity. We combined nitrobenzoselenadiazoles with bacteria-targeting moieties (i.e., glucose-6-phosphate, amoxicillin, vancomycin) producing environmentally sensitive photodynamic agents. The labelled vancomycin conjugate was able to both visualize and eradicate multidrug resistant Gram-positive ESKAPE pathogens at nanomolar concentrations, including clinical isolates and those that form biofilms. Nitrobenzoselenadiazole conjugates are easily synthesized and display strong environment dependent ROS production. Due to their small size and non-invasive character, they unobtrusively label antimicrobial targeting moieties. We envisage that the simplicity and modularity of this chemical strategy will accelerate the rational design of new antimicrobial therapies for refractory bacterial infections.

Background The cuticle is an invisible glycosylated protein layer that covers the outside of the eggshell and forms a barrier to the transmission of microorganisms. Cuticle-specific staining and in situ absorbance measurements have been used to quantify cuticle deposition in several pure breeds of chicken. For brown eggs, a pre-stain and a post-stain absorbance measurement is required to correct for intrinsic absorption by the natural pigment. For white eggs, a post-stain absorbance measurement alone is sufficient to estimate cuticle deposition. The objective of the research was to estimate genetic parameters and provide data to promote adoption of the technique to increase cuticle deposition and reduce vertical transmission of microorganisms. Results For all pure breeds examined here, i.e. Rhode Island Red, two White Leghorns, White Rock and a broiler breed, the estimate of heritability for cuticle deposition from a meta-analysis was moderately high (0.38 ± 0.04). In the Rhode Island Red breed, the estimate of the genetic correlation between measurements recorded at early and late times during the egg-laying period was ~ 1. There was no negative genetic correlation between cuticle deposition and production traits. Estimates of the genetic correlation of cuticle deposition with shell color ranged from negative values or 0 in brown-egg layers to positive values in white- or tinted-egg layers. Using the intrinsic fluorescence of tryptophan in the cuticle proteins to quantify the amount of cuticle deposition failed because of complex quenching processes. Tryptophan fluorescence intensity at 330 nm was moderately heritable, but there was no evidence of a non-zero genetic correlation with cuticle deposition. This was complicated furthermore by a negative genetic correlation of fluorescence with color in brown eggs, due to the quenching of tryptophan fluorescence by energy transfer to protoporphyrin pigment. We also confirmed that removal of the cuticle increased reflection of ultraviolet wavelengths from the egg. Conclusions These results provide additional evidence for the need to incorporate cuticle deposition into breeding programs of egg- and meat-type birds in order to reduce vertical and horizontal transmission of potentially pathogenic organisms and to help improve biosecurity in poultry.

Autofluorescence lifetime images reveal unique characteristics of endogenous fluorescence in biological samples. Comprehensive understanding and clinical diagnosis rely on co-registration with the gold standard, histology images, which is extremely challenging due to the difference of both images. Here, we show an unsupervised image-to-image translation network that significantly improves the success of the co-registration using a conventional optimisation-based regression network, applicable to autofluorescence lifetime images at different emission wavelengths. A preliminary blind comparison by experienced researchers shows the superiority of our method on co-registration. The results also indicate that the approach is applicable to various image formats, like fluorescence in-tensity images. With the registration, stitching outcomes illustrate the distinct differences of the spectral lifetime across an unstained tissue, enabling macro-level rapid visual identification of lung cancer and cellular-level characterisation of cell variants and common types. The approach could be effortlessly extended to lifetime images beyond this range and other staining technologies. Using unsupervised image-to-image synthesis, homography regression-based co-registration of fluorescence-histology images is improved and can be used on various image formats across full-spectral emission wavelengths.