The influence of internal pressure and neuromuscular agents on C. elegans biomechanics: an empirical and multi-compartmental in silico modelling study.

The function of a specific tissue and its biomechanics are interdependent, with pathologies or ageing often being intertwined with structural decline. The biomechanics of Caenorhabditis elegans, a model organism widely used in pharmacological and ageing research, has been established as biomarker for healthy ageing. However, the properties of the constituent tissues, and their contribution to the overall mechanical characteristics of the organism, remain relatively unknown. In this study we investigated the biomechanics of healthy C. elegans cuticle, muscle tissue, and pseudocoelom using a combination of indentation experiments and in silico modelling. We performed stiffness measurements using an atomic force microscope. To approximate the nematode's cylindrical body we used a novel three-compartment nonlinear finite element model, enabling us to analyse of how changes in the elasticity of individual compartments affect the bulk stiffness. We then fine-tuned the parameters of the model to match the simulation force-indentation output to the experimental data. To test the finite element model, we modified distinct compartments experimentally. Our in silico results, in agreement with previous studies, suggest that hyperosmotic shock reduces stiffness by decreasing the internal pressure. Unexpectedly, treatment with the neuromuscular agent aldicarb, traditionally associated with muscle contraction, reduced stiffness by decreasing the internal pressure. Furthermore, our finite element model can offer insights into how drugs, mutations, or processes such as ageing target individual tissues.

Detection of acute promyelocytic leukemia in peripheral blood and bone marrow with annotation-free deep learning.

While optical microscopy inspection of blood films and bone marrow aspirates by a hematologist is a crucial step in establishing diagnosis of acute leukemia, especially in low-resource settings where other diagnostic modalities are not available, the task remains time-consuming and prone to human inconsistencies. This has an impact especially in cases of Acute Promyelocytic Leukemia (APL) that require urgent treatment. Integration of automated computational hematopathology into clinical workflows can improve the throughput of these services and reduce cognitive human error. However, a major bottleneck in deploying such systems is a lack of sufficient cell morphological object-labels annotations to train deep learning models. We overcome this by leveraging patient diagnostic labels to train weakly-supervised models that detect different types of acute leukemia. We introduce a deep learning approach, Multiple Instance Learning for Leukocyte Identification (MILLIE), able to perform automated reliable analysis of blood films with minimal supervision. Without being trained to classify individual cells, MILLIE differentiates between acute lymphoblastic and myeloblastic leukemia in blood films. More importantly, MILLIE detects APL in blood films (AUC 0.94 ± 0.04) and in bone marrow aspirates (AUC 0.99 ± 0.01). MILLIE is a viable solution to augment the throughput of clinical pathways that require assessment of blood film microscopy.

Content aware multi-focus image fusion for high-magnification blood film microscopy.

Automated digital high-magnification optical microscopy is key to accelerating biology research and improving pathology clinical pathways. High magnification objectives with large numerical apertures are usually preferred to resolve the fine structural details of biological samples, but they have a very limited depth-of-field. Depending on the thickness of the sample, analysis of specimens typically requires the acquisition of multiple images at different focal planes for each field-of-view, followed by the fusion of these planes into an extended depth-of-field image. This translates into low scanning speeds, increased storage space, and processing time not suitable for high-throughput clinical use. We introduce a novel content-aware multi-focus image fusion approach based on deep learning which extends the depth-of-field of high magnification objectives effectively. We demonstrate the method with three examples, showing that highly accurate, detailed, extended depth of field images can be obtained at a lower axial sampling rate, using 2-fold fewer focal planes than normally required.

Optical mesoscopy, machine learning, and computational microscopy enable high information content diagnostic imaging of blood films.

Automated image-based assessment of blood films has tremendous potential to support clinical haematology within overstretched healthcare systems. To achieve this, efficient and reliable digital capture of the rich diagnostic information contained within a blood film is a critical first step. However, this is often challenging, and in many cases entirely unfeasible, with the microscopes typically used in haematology due to the fundamental trade-off between magnification and spatial resolution. To address this, we investigated three state-of-the-art approaches to microscopic imaging of blood films which leverage recent advances in optical and computational imaging and analysis to increase the information capture capacity of the optical microscope: optical mesoscopy, which uses a giant microscope objective (Mesolens) to enable high-resolution imaging at low magnification; Fourier ptychographic microscopy, a computational imaging method which relies on oblique illumination with a series of LEDs to capture high-resolution information; and deep neural networks which can be trained to increase the quality of low magnification, low resolution images. We compare and contrast the performance of these techniques for blood film imaging for the exemplar case of Giemsa-stained peripheral blood smears. Using computational image analysis and shape-based object classification, we demonstrate their use for automated analysis of red blood cell morphology and visualization and detection of small blood-borne parasites such as the malarial parasite Plasmodium falciparum. Our results demonstrate that these new methods greatly increase the information capturing capacity of the light microscope, with transformative potential for haematology and more generally across digital pathology. © 2021 The Authors. The Journal of Pathology published by John Wiley & Sons, Ltd. on behalf of The Pathological Society of Great Britain and Ireland.

Data-driven malaria prevalence prediction in large densely populated urban holoendemic sub-Saharan West Africa.

Over 200 million malaria cases globally lead to half-million deaths annually. The development of malaria prevalence prediction systems to support malaria care pathways has been hindered by lack of data, a tendency towards universal "monolithic" models (one-size-fits-all-regions) and a focus on long lead time predictions. Current systems do not provide short-term local predictions at an accuracy suitable for deployment in clinical practice. Here we show a data-driven approach that reliably produces one-month-ahead prevalence prediction within a densely populated all-year-round malaria metropolis of over 3.5 million inhabitants situated in Nigeria which has one of the largest global burdens of P. falciparum malaria. We estimate one-month-ahead prevalence in a unique 22-years prospective regional dataset of > 9 × 104 participants attending our healthcare services. Our system agrees with both magnitude and direction of the prediction on validation data achieving MAE ≤ 6 × 10-2, MSE ≤ 7 × 10-3, PCC (median 0.63, IQR 0.3) and with more than 80% of estimates within a (+ 0.1 to - 0.05) error-tolerance range which is clinically relevant for decision-support in our holoendemic setting. Our data-driven approach could facilitate healthcare systems to harness their own data to support local malaria care pathways.

Expert-level automated malaria diagnosis on routine blood films with deep neural networks.

Over 200 million malaria cases globally lead to half a million deaths annually. Accurate malaria diagnosis remains a challenge. Automated imaging processing approaches to analyze Thick Blood Films (TBF) could provide scalable solutions, for urban healthcare providers in the holoendemic malaria sub-Saharan region. Although several approaches have been attempted to identify malaria parasites in TBF, none have achieved negative and positive predictive performance suitable for clinical use in the west sub-Saharan region. While malaria parasite object detection remains an intermediary step in achieving automatic patient diagnosis, training state-of-the-art deep-learning object detectors requires the human-expert labor-intensive process of labeling a large dataset of digitized TBF. To overcome these challenges and to achieve a clinically usable system, we show a novel approach. It leverages routine clinical-microscopy labels from our quality-controlled malaria clinics, to train a Deep Malaria Convolutional Neural Network classifier (DeepMCNN) for automated malaria diagnosis. Our system also provides total Malaria Parasite (MP) and White Blood Cell (WBC) counts allowing parasitemia estimation in MP/µL, as recommended by the WHO. Prospective validation of the DeepMCNN achieves sensitivity/specificity of 0.92/0.90 against expert-level malaria diagnosis. Our approach PPV/NPV performance is of 0.92/0.90, which is clinically usable in our holoendemic settings in the densely populated metropolis of Ibadan. It is located within the most populous African country (Nigeria) and with one of the largest burdens of Plasmodium falciparum malaria. Our openly available method is of importance for strategies aimed to scale malaria diagnosis in urban regions where daily assessment of thousands of specimens is required.

Digital refocusing and extended depth of field reconstruction in Fourier ptychographic microscopy.

Fourier ptychography microscopy (FPM) is a recently developed microscopic imaging method that allows the recovery of a high-resolution complex image by combining a sequence of bright and darkfield images acquired under inclined illumination. The capacity of FPM for high resolution imaging at low magnification makes it particularly attractive for applications in digital pathology which require imaging of large specimens such as tissue sections and blood films. To date most applications of FPM have been limited to imaging thin samples, simplifying both image reconstruction and analysis. In this work we show that, for samples of intermediate thickness (defined here as less than the depth of field of a raw captured image), numerical propagation of the reconstructed complex field allows effective digital refocusing of FPM images. The results are validated by comparison against images obtained with an equivalent high numerical aperture objective lens. We find that post reconstruction refocusing (PRR) yields images comparable in quality to adding a defocus term to the pupil function within the reconstruction algorithm, while reducing computing time by several orders of magnitude. We apply PRR to visualize FPM images of Giemsa-stained peripheral blood films and present a novel image processing pipeline to construct an effective extended depth of field image which optimally displays the 3D sample structure in a 2D image. We also show how digital refocusing allows effective correction of the chromatic focus shifts inherent to the low magnification objective lenses used in FPM setups, improving the overall quality of color FPM images.

Activation of RHO-1 in cholinergic motor neurons competes with dopamine signalling to control locomotion.

The small GTPase RhoA plays a crucial role in the regulation of neuronal signalling to generate behaviour. In the developing nervous system RhoA is known to regulate the actin cytoskeleton, however the effectors of RhoA-signalling in adult neurons remain largely unidentified. We have previously shown that activation of the RhoA ortholog (RHO-1) in C. elegans cholinergic motor neurons triggers hyperactivity of these neurons and loopy locomotion with exaggerated body bends. This is achieved in part through increased diacylglycerol (DAG) levels and the recruitment of the synaptic vesicle protein UNC-13 to synaptic release sites, however other pathways remain to be identified. Dopamine, which is negatively regulated by the dopamine re-uptake transporter (DAT), has a central role in modulating locomotion in both humans and C. elegans. In this study we identify a new pathway in which RHO-1 regulates locomotory behaviour by repressing dopamine signalling, via DAT-1, linking these two pathways together. We observed an upregulation of dat-1 expression when RHO-1 is activated and show that loss of DAT-1 inhibits the loopy locomotion phenotype caused by RHO-1 activation. Reducing dopamine signalling in dat-1 mutants through mutations in genes involved in dopamine synthesis or in the dopamine receptor DOP-1 restores the ability of RHO-1 to trigger loopy locomotion in dat-1 mutants. Taken together, we show that negative regulation of dopamine signalling via DAT-1 is necessary for the neuronal RHO-1 pathway to regulate locomotion.

Three-dimensional behavioural phenotyping of freely moving C. elegans using quantitative light field microscopy.

Behavioural phenotyping of model organisms is widely used to investigate fundamental aspects of organism biology, from the functioning of the nervous system to the effects of genetic mutations, as well as for screening new drug compounds. However, our capacity to observe and quantify the full range and complexity of behavioural responses is limited by the inability of conventional microscopy techniques to capture volumetric image information at sufficient speed. In this article we describe how combining light field microscopy with computational depth estimation provides a new method for fast, quantitative assessment of 3D posture and movement of the model organism Caenorhabditis elegans (C. elegans). We apply this technique to compare the behaviour of cuticle collagen mutants, finding significant differences in 3D posture and locomotion. We demonstrate the ability of quantitative light field microscopy to provide new fundamental insights into C. elegans locomotion by analysing the 3D postural modes of a freely swimming worm. Finally, we consider relative merits of the method and its broader application for phenotypic imaging of other organisms and for other volumetric bioimaging applications.

Determining the biomechanics of touch sensation in C. elegans.

The sense of touch is a fundamental mechanism that nearly all organisms use to interact with their surroundings. However, the process of mechanotransduction whereby a mechanical stimulus gives rise to a neuronal response is not well understood. In this paper we present an investigation of the biomechanics of touch using the model organism C. elegans. By developing a custom micromanipulation and force sensing system around a high resolution optical microscope, we measured the spatial deformation of the organism's cuticle and force response to controlled uniaxial indentations. We combined these experimental results with anatomical data to create a multilayer computational biomechanical model of the organism and accurately derive its material properties such as the elastic modulus and poisson's ratio. We demonstrate the utility of this model by combining it with previously published electrophysiological data to provide quantitative insights into different biomechanical states for mechanotransduction, including the first estimate of the sensitivity of an individual mechanoreceptor to an applied stimulus (parameterised as strain energy density). We also interpret empirical behavioural data to estimate the minimum number of mechanoreceptors which must be activated to elicit a behavioural response.

In-vivo high resolution AFM topographic imaging of Caenorhabditis elegans reveals previously unreported surface structures of cuticle mutants.

Atomic force microscopy (AFM) is a powerful method for topographic imaging of surfaces with nanometer resolution. AFM offers significant advantages over scanning electron microscopy (SEM) including the acquisition of quantitative 3D-images and biomechanical information. More importantly, for in-vivo biological imaging, AFM does not require sample dehydration/labeling. We show for the first time high-resolution topographical images of the cuticle of the model organism C. elegans under physiological conditions using AFM. C. elegans is used extensively for drug screening and to study pathogen adherence in innate immunity; both applications highly depend on the integrity of the nematode's cuticle. Mutations affecting both drug adsorption and pathogen clearance have been proposed to relate to changes in the cuticle structure, but never visually examined in high resolution. In this study we use AFM to visualize the topography of wild-type adult C. elegans as well as several cuticle collagen mutants and describe previously unseen anatomical differences.

Investigation of mechanosensation in C. elegans using light field calcium imaging.

We describe a new experimental approach to investigate touch sensation in the model organism C. elegans using light field deconvolution microscopy. By combining fast volumetric image acquisition with controlled indentation of the organism using a high sensitivity force transducer, we are able to simultaneously measure activity in multiple touch receptor neurons expressing the calcium ion indicator GCaMP6s. By varying the applied mechanical stimulus we show how this method can be used to quantify touch sensitivity in C. elegans. We describe some of the challenges of performing light field calcium imaging in moving samples and demonstrate that they can be overcome by simple data processing.

TLX activates MASH1 for induction of neuronal lineage commitment of adult hippocampal neuroprogenitors.

The orphan nuclear receptor TLX has been proposed to act as a repressor of cell cycle inhibitors to maintain the neural stem cells in an undifferentiated state, and prevents commitment into astrocyte lineages. However, little is known about the mechanism of TLX in neuronal lineage commitment and differentiation. A majority of adult rat hippocampus-derived progenitors (AHPs) cultured in the presence of FGF express a high level of TLX and a fraction of these cells also express the proneural gene MASH1. Upon FGF withdrawal, TLX rapidly decreased, while MASH1 was intensely expressed within 1h, decreasing gradually to disappear at 24h. Adenoviral transduction of TLX in AHP cells in the absence of FGF transiently increased cell proliferation, however, later resulted in neuronal differentiation by inducing MASH1, Neurogenin1, DCX, and MAP2ab. Furthermore, TLX directly targets and activates the MASH1 promoter through interaction with Sp1, recruiting co-activators whereas dismissing the co-repressor HDAC4. Conversely, silencing of TLX in AHPs decreased beta-III tubulin and DCX expression and promoted glial differentiation. Our results thus suggest that TLX not only acts as a repressor of cell cycle and glial differentiation but also activates neuronal lineage commitment in AHPs.

Characterization of neuroprogenitor cells expressing the PDGF beta-receptor within the subventricular zone of postnatal mice.

We report a considerable number of cells in the ventricular and the subventricular zones (SVZ) of newborn mice to stain positive for the PDGF beta-receptor (PDGFRB). Many of them also stained for nestin and/or GFAP but less frequently for the neuroblast marker doublecortin and for the mitotic marker Ki-67. The SVZ of mice with nestin-Cre conditional deletion of PDGFRB expressed the receptor only on blood vessels and was devoid of any morphological abnormality. PDGFRB(-/-) neurospheres showed a higher rate of apoptosis without any significant decrease in proliferation. They demonstrated reduced capacities of migration and neuronal differentiation in response to not only PDGF-BB but also bFGF. Furthermore, the PDGFR kinase inhibitor STI571 blocked the effects of bFGF in control neurosphere cultures. bFGF increased the activity of the PDGFRB promoter as well as the expression and phosphorylation of PDGFRB. These results suggest the presence of the signaling convergence between PDGF and FGF. PDGFRB is needed for survival, and the effects of bFGF in migration and neural differentiation of the cells may be potentiated by induction of PDGFRB.

Mechanism of MASH1 induction by ASK1 and ATRA in adult neural progenitors.

The molecular mechanisms underlying differentiation and lineage commitment in neural stem cells are just beginning to be understood, however the molecules involved in this process and their functions remain largely unknown. Here we studied the effects and downstream signals of apoptosis signal-regulating kinase 1 (ASK1) together with all-trans retinoic acid (ATRA) on neuronal differentiation in adult hippocampus-derived progenitor (AHP) cells. Following ASK1 over-expression and ATRA treatment in AHPs, a larger number of cells differentiated into neurons and the MASH1 promoter became activated. Analyzing downstream effector molecules of ASK1 or ATRA targeting the MASH1 promoter revealed that the myocyte enhancer factor 2C (MEF2C) mediated ASK1 signalling, while activation of Sp1 was involved in ATRA signalling. Chromatin immunoprecipitation assay on the promoter revealed that ASK1 induced binding of MEF2C and Ca(2+)/calmodulin-dependent kinase II to the MASH1 promoter. Taken together, ASK1 and ATRA activate MEF2C and Sp1, respectively, and up-regulate MASH1 protein expression.

Transplantation of human embryonic stem cell-derived cells to a rat model of Parkinson's disease: effect of in vitro differentiation on graft survival and teratoma formation.

Human embryonic stem cells (hESCs) have been proposed as a source of dopamine (DA) neurons for transplantation in Parkinson's disease (PD). We have investigated the effect of in vitro predifferentiation on in vivo survival and differentiation of hESCs implanted into the 6-OHDA (6-hydroxydopamine)-lesion rat model of PD. The hESCs were cocultured with PA6 cells for 16, 20, or 23 days, leading to the in vitro differentiation into DA neurons. Grafted hESC-derived cells survived well and expressed neuronal markers. However, very few exhibited a DA neuron phenotype. Reversal of lesion-induced motor deficits was not observed. Rats grafted with hESCs predifferentiated in vitro for 16 days developed severe teratomas, whereas most rats grafted with hESCs predifferentiated for 20 and 23 days remained healthy until the end of the experiment. This indicates that prolonged in vitro differentiation of hESCs is essential for preventing formation of teratomas.

ASK1 inhibits astroglial development via p38 mitogen-activated protein kinase and promotes neuronal differentiation in adult hippocampus-derived progenitor cells.

The mechanisms controlling differentiation and lineage specification of neural stem cells are still poorly understood, and many of the molecules involved in this process and their specific functions are yet unknown. We investigated the effect of apoptosis signal-regulating kinase 1 (ASK1) on neural stem cells by infecting adult hippocampus-derived rat progenitors with an adenovirus encoding the constitutively active form of ASK1. Following ASK1 overexpression, a significantly larger number of cells differentiated into neurons and a substantial increase in Mash1 transcription was observed. Moreover, a marked depletion of glial cells was observed, persisting even after additional treatment of ASK1-infected cultures with potent glia inducers such as leukemia inhibitory factor and bone morphogenetic protein. Analysis of the promoter for glial fibrillary acidic protein revealed that ASK1 acts as a potent inhibitor of glial-specific gene transcription. However, the signal transducers and activators of transcription 3 (STAT3)-binding site in the promoter was dispensable, while the activation of p38 mitogen-activated protein kinase was crucial for this effect, suggesting the presence of a novel mechanism for the inhibition of glial differentiation.