Signal domain adaptation network for limited-view optoacoustic tomography

Optoacoustic (OA) imaging is based on optical excitation of biological tissues with nanosecond-duration laser pulses and detection of ultrasound (US) waves generated by thermoelastic expansion following light absorption. The image quality and fidelity of OA images critically depend on the extent of tomographic coverage provided by the US detector arrays. However, full tomographic coverage is not always possible due to experimental constraints. One major challenge concerns an efficient integration between OA and pulse-echo US measurements using the same transducer array. A common approach toward the hybridization consists in using standard linear transducer arrays, which readily results in arc-type artifacts and distorted shapes in OA images due to the limited angular coverage. Deep learning methods have been proposed to mitigate limited-view artifacts in OA reconstructions by mapping artifactual to artifact-free (ground truth) images. However, acquisition of ground truth data with full angular coverage is not always possible, particularly when using handheld probes in a clinical setting. Deep learning methods operating in the image domain are then commonly based on networks trained on simulated data. This approach is yet incapable of transferring the learned features between two domains, which results in poor performance on experimental data. Here, we propose a signal domain adaptation network (SDAN) consisting of i) a domain adaptation network to reduce the domain gap between simulated and experimental signals and ii) a sides prediction network to complement the missing signals in limited-view OA datasets acquired from a human forearm by means of a handheld linear transducer array. The proposed method showed improved performance in reducing limited-view artifacts without the need for ground truth signals from full tomographic acquisitions.

Model-based correction of rapid thermal confounds in fluorescence neuroimaging of targeted perturbation

Significance

An array of techniques for targeted neuromodulation is emerging, with high potential in brain research and therapy. Calcium imaging or other forms of functional fluorescence imaging are central solutions for monitoring cortical neural responses to targeted neuromodulation, but often are confounded by thermal effects that are inter-mixed with neural responses.

Aim

Here, we develop and demonstrate a method for effectively suppressing fluorescent thermal transients from calcium responses.

Approach

We use high precision phased-array 3 MHz focused ultrasound delivery integrated with fiberscope-based widefield fluorescence to monitor cortex-wide calcium changes. Our approach for detecting the neural activation first takes advantage of the high inter-hemispheric correlation of resting state Ca 2 + dynamics and then removes the ultrasound-induced thermal effect by subtracting its simulated spatio-temporal signature from the processed profile.

Results

The focused 350    μ m -sized ultrasound stimulus triggered rapid localized activation events dominated by transient thermal responses produced by ultrasound. By employing bioheat equation to model the ultrasound heat deposition, we can recover putative neural responses to ultrasound.

Conclusions

The developed method for canceling transient thermal fluorescence quenching could also find applications with optical stimulation techniques to monitor thermal effects and disentangle them from neural responses. This approach may help deepen our understanding of the mechanisms and macroscopic effects of ultrasound neuromodulation, further paving the way for tailoring the stimulation regimes toward specific applications.

Deep learning of image- and time-domain data enhances the visibility of structures in optoacoustic tomography

Images rendered with common optoacoustic system implementations are often afflicted with distortions and poor visibility of structures, hindering reliable image interpretation and quantification of bio-chrome distribution. Among the practical limitations contributing to artifactual reconstructions are insufficient tomographic detection coverage and suboptimal illumination geometry, as well as inability to accurately account for acoustic reflections and speed of sound heterogeneities in the imaged tissues. Here we developed a convolutional neural network (CNN) approach for enhancement of optoacoustic image quality which combines training on both time-resolved signals and tomographic reconstructions. Reference human finger data for training the CNN were recorded using a full-ring array system that provides optimal tomographic coverage around the imaged object. The reconstructions were further refined with a dedicated algorithm that minimizes acoustic reflection artifacts induced by acoustically mismatch structures, such as bones. The combined methodology is shown to outperform other learning-based methods solely operating on image-domain data.

Analyzing the influence of microstructured surfaces on the lactic acid production of Lactobacillus delbrueckii lactis in a flow-through cell system

Microorganisms growing in biofilms might be possible biocatalysts for future biotechnological production processes. Attached to a surface and embedded in an extracellular polymeric matrix, they create their preferred environment and form robust cultures for continuous systems. With the objective of implementing highly efficient processes, productive biofilms need to be understood comprehensively. In this study, the influence of microstructured metallic surfaces on biofilm productivity was researched. To conduct this study, titanium and stainless steel sheets were polished, micromilled, as well as coated with particles. Subsequently, the metal sheets were exposed to the lactic acid producing Lactobacillus delbrueckii subsp. lactis under laminar and homogeneous flow conditions in a custom-built flow cell. A proof-of-concept showed that biofilm formation in the system only occurred on the designated substratum. Following a 24-h batch cultivation for primary biofilm development, the culture was continuously provided with glucose containing medium. As different experimental series have indicated, the process resulted to be stable for up to eleven days. Primary metabolite productivity averaged around 6-7 g/(L h). Interestingly, the productivity was shown to be affected neither by the type of metal, nor by the applied microstructures. Nevertheless, a higher dry biomass weight determined on micro-milled substratum indicates a complementary differentiation of biofilm components in future experiments.

Novel materials for biofilm reactors and their characterization

The application of adherently growing microorganisms for biotechnological production processes is established, but it is still a niche technology with only a small economic impact. However, novel approaches are under development for new types of biofilm reactors. In this context, increasingly more microstructured metal surfaces are being investigated, and they show positive effects on the bacterial growth and the biofilm establishment. However, for comparison of the data, the different surface materials have to correspond in their different characteristics, such as wettability and chemical composition. Also, new materials, such as plastic composite supports, were developed. To understand the interaction between these new materials and the biofilm-producing microorganisms, different surface science methods have to be applied to reveal a detailed knowledge of the surface characteristics. In conclusion, microstructured surfaces show a high potential for enhanced biofilm growth, probably accompanied by an enhanced productivity of the microorganisms.

Gene regulation of pteridine reductase 1 in leishmania promastigotes and amastigotes using a full-length antisense construct

BACKGROUND

Pteridine metabolic pathway is unusual features of Leishmania, which is necessary for the growth of parasite. Leishmania has evolved a complex and versatile pteridine salvage network which has the ability of scavenging a wide area of the conjugated and unconjugated pteridines especially folate and biopterin. In this study, we focus on the inhibition of ptr1 gene expression.

METHODS

L. major ptr1 gene was cloned into pcDNA3 and digested using KpnI and BamHI. The gene was subcloned so that antisense will transcribe and called pcDNA-rPTR. Leishmania major was cultured and late logarithmic-phase promastigotes were harvested. The promastigotes were divided into two groups. One group was transfected with 50 µg of pcDNA-rPTR, whereas the other group was transfected with pcDNA3. Transfected cells were cultured and plated onto semi-solid media. Mouse pritonean macrophages were transfected using pcDNA-rPTR-tansfected promastigotes. Western blotting was performed on mouse transfected pritonean macrophages and extracts from transfected promastigotes of L. major using a L. major ptr1 antibody raised in rabbits.

RESULTS

The PTR1 protein was not expressed in pcDNA-rPTR- tansfected promastigotes and mouse macrophage transfected with pcDNA-rPTR- tansfected promastigotes.

CONCLUSION

This approach might be used to study the pteridine salvage pathway in Leishmania or to assess the possibility of using gene expression inhibition in the treatment of leishmaniasis.