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Green, D.

Publications and source records attributed to Green, D..

At least 19 recordsLinked to original sources

Assessing accelerometry as an alternative to electromyography for mouse sleep scoring

For sleep scoring in rodents, the use of electromyography (EMG) is considered the gold standard to assess muscle tone; however, EMG electrodes require invasive surgical implantation, are sensitive to muscular placement, can have extensive noise due to non-muscular signal contamination, and are at risk of failure due to mechanical stress. The use of an accelerometer (Acc) integrated on the recording headstage offers an alternative for movement detection. However, the degree of agreement between these two approaches has never been systematically evaluated. To understand if these tools allow similar scoring outcomes, seven trained scorers manually classified mouse sleep recordings using hippocampal local field potential (LFP) together with EMG or Acc. When comparing scoring between EMG and Acc, overall epoch-by-epoch accuracy exceeded 90% with a kappa score above 0.8, indicating excellent agreement. However, Acc was found to under classify Wake by 4.92% while overclassifying NREM sleep by 3.29%, possibly reflecting a decreased sensitivity of Acc to subtle changes in muscle tone used in distinguishing Wake from NREM sleep. Comparing EMG and Acc signal for agreed epochs vs disagreed epochs revealed a weaker correlation between the two signals for disagreed epochs, especially for Wake and NREM, suggesting that disagreements reflected genuine signal differences rather than scorer subjectivity. These findings support LFP/Acc as a valid approach to sleep scoring, however, it is noted that Acc based scoring slightly underestimated Wake epochs, favoring NREM sleep, relative to traditional EMG approach.

neuroscience↗

Cell intrinsic dynamics guide neuroblast ingression independent of tissue fluidity

Morphogenesis involves the coordination of multiple cellular processes that occur simultaneously within developing tissues. During early Drosophila embryogenesis, neuroblast (NB) ingression occurs concurrently with germ band extension (GBE), yet whether these processes interact mechanistically remains unclear. Here, we combine mathematical modelling with quantitative live imaging to investigate whether tissue-level mechanics during GBE influence NB ingression dynamics. Mathematical modelling predicted that reducing tissue fluidity through impaired cellular rearrangements should slow NB ingression by increasing mechanical resistance. Experimental analysis of mutants in which cell intercalation and GBE are disrupted revealed a dramatic reduction in tissue fluidity. However, NB ingression rates remained largely unaffected when tissue fluidity decreased. Incorporating cell-intrinsic myosin anisotropy and endocytosis-contractility coupling into our mathematical model rescued the rate of neuroblast ingression in solid-like tissues. Thus, our findings suggest that cell-intrinsic mechanisms, rather than tissue-level fluidity, maintain ingression kinetics. More broadly, these results illustrate how developmental systems can achieve robustness by insulating critical cellular events from tissue-level mechanical variability. Statement of SignificanceMorphogenesis requires coordination of cellular processes in tissues undergoing mechanical transitions. While recent work highlights the importance of tissue fluidity in morphogenesis, whether tissue-level mechanical changes influence concurrent cellular events remains unclear. Combining mathematical modelling with quantitative live imaging, we tested whether tissue fluidization during Drosophila germ-band extension regulates neuroblast ingression. Shape-based vertex models failed to predict tissue mechanical states when myosin was disrupted. Instead, incorporating cellular rearrangement delays recapitulated phenotypes independent of cell shape. Strikingly, we showed that neuroblast ingression remains robust despite tissue solidification in vivo. Biophysical modelling suggests that coupled cell contractility and endocytosis maintains robust ingression despite tissue solidification. Our work shows that developmental programs can be mechanically insulated from tissue-scale changes, thus enabling developmental robustness.

developmental biology↗

Positional cues, not Notch, direct Neuroblast selection during early neurogenesis in the Drosophila embryo

Notch-mediated lateral inhibition is a conserved patterning process that controls alternative cell fate decisions and produces regular cell fate patterns. Prevailing models posit that lateral inhibition singles-out cells from fields of initially equipotent cells by amplifying stochastic fluctuations of Notch or pre-existing fate biases. Here, we revisited the role of Notch in early Drosophila neurogenesis, studying the dynamics of Neuroblast specification by live imaging the transcription of two proneural genes, scute and lethal of scute. We found that proneural gene expression is biased spatially along the dorsal-ventral axis prior to germ band extension and that early proneural expression predicts Neuroblast fate acquisition. This indicated that Neuroblast specification is pre-patterned by positional cues. Additionally, positional cues appeared to instruct individual cells to delaminate in a correct stereotyped pattern in proneural mutant embryos. Finally, contrary to current models, Notch signaling, measured by E(spl)m8 expression, was not detectable within proneural clusters until after Neuroblasts had initiated delamination. This indicated that Notch functions to stabilize rather than initiate fate decisions. We therefore propose that positional cues, not Notch, single-out Neuroblasts during early Drosophila neurogenesis, challenging long-held assumptions about the role of Notch in Neuroblast selection.

developmental biology↗

Knowledge-informed multimodal cfDNA analysis improves sensitivity and generalization in cancer detection

Liquid biopsy offers a minimally invasive opportunity to detect and monitor cancers through analysis of cell-free DNA (cfDNA). However, current approaches face challenges of limited sensitivity at low tumor fractions, technical variability, and poor generalization across cohorts. Tumor-informed targeted methods offer high specificity but suffer from low sensitivity due to random sampling, tumor evolution and adaptation (including resistance mechanisms), and other sources of heterogeneity. Conversely, tumor-naive genome-wide methods can increase sensitivity but often sacrifice specificity, particularly at low tumor fractions. We developed Fragmentomics Analysis for Tumor Evaluation with AI (Fate-AI), a multimodal framework that integrates fragmentomic and methylation-derived features from low-pass whole-genome sequencing (LPWGS) and cell-free methylated DNA immunoprecipitation and high-throughput sequencing (cfMeDIP-seq). It employs a knowledge-informed strategy to select recurrently altered genomic regions and tissue-specific methylation loci to combine the advantages of tumor-naive approaches with the specificity of tumor-informed approaches. This approach derives robust per-sample normalized features that mitigate batch effects and enhance cross-cohort reproducibility. We evaluated Fate-AI on a total of 1,219 plasma samples spanning ten cancer types and healthy controls from multiple laboratories and sequencing centers, including 432 newly profiled cases (280 with both cfMeDIP-seq and LPWGS) together with 787 samples from four independent public datasets. Fate-AI achieved superior sensitivity and specificity compared to state-of-the-art methods, detecting tumor-derived signals at fractions as low as 10-5 in experimental dilutions. Fate-AI scores correlated with disease stage and tracked longitudinal progression, anticipating relapse months before clinical progression. Furthermore, Fate-AI enabled tissue-of-origin classification, with AUCs ranging from 0.84 to 0.97 across six cancer types. Collectively, our results demonstrate that Fate-AI provides a sensitive, generalizable, and clinically actionable platform for early detection, minimal residual disease monitoring, and tissue-of-origin classification, supporting its potential as a liquid biopsy framework in precision oncology.

cancer biology↗

RUNX2 inhibition disrupts a PAX3::FOXO1-RUNX2 feed-forward loop and dismantles oncogenic gene programs in fusion-positive rhabdomyosarcoma

Fusion-positive rhabdomyosarcoma is an aggressive pediatric cancer of skeletal muscle lineage, with a 5-year overall survival of <30% for high-risk disease, and <8% when metastatic. The PAX3::FOXO1 fusion gene, resulting from t(2:13), is a signature driver of fusion-positive rhabdomyosarcoma, but similar to other transcription-factor based fusion genes in other cancers, not currently pharmacologically tractable. To identify novel druggable proteins in fusion-positive rhabdomyosarcoma tumor tissue and cell lines, we performed mRNA-seq of RMS patient tumors and utilizing the human FP-RMS cell lines Rh30 and Rh4, found that the RUNX2 transcription factor was the top druggable dependency. In vitro loss of function studies using genetic (RNAi) or pharmacologic (small molecule CADD522) inhibition showed that RUNX2 suppression inhibited FP-RMS cell growth, induced myogenic differentiation and apoptosis, and phenocopied PAX3::FOXO1 suppression. In vivo loss of function studies using conditional (dox-inducible) or pharmacologic (small molecule CADD522) blockade of tumor growth in a xenograft model system showed that RUNX2 suppression inhibited tumor growth. Mechanistically, we identify a PAX3::FOXO1 feed-forward loop whereby PAX3::FOXO1 binds a RUNX2 enhancer to upregulate gene expression alongside MYOD1, while RUNX2 expression supports the expression of PAX3::FOXO1 at the mRNA and protein level. SignificanceRUNX2 inhibition reduces PAX3::FOXO1 expression and signaling, which impairs fusion-positive rhabdomyosarcoma oncogenic phenotypes. In vivo treatment with CADD522 decreased tumor growth and increased survival, indicating that RUNX2 is a promising therapeutic target.

cancer biology↗

The ancient evolution of far-red light photoacclimation in cyanobacteria

Cyanobacteria oxygenated the atmosphere of early Earth and continue to be key players in global carbon and nitrogen cycles. A phylogenetically diverse subset of extant cyanobacteria can perform photosynthesis with far-red light through a process called far-red light photoacclimation, or FaRLiP. This phenotype is enabled by a cluster of [~]20 genes, and involves the synthesis of red-shifted chlorophylls f and d, together with paralogues of the ubiquitous photosynthetic machinery used in visible light. The FaRLiP gene cluster is present in diverse, environmentally important cyanobacterial groups but its origin, evolutionary history, and connection to early biotic environments have remained unclear. This study takes advantage of the recent increase in (meta)genomic data to clarify this issue; sequence data mining, metagenomic assembly, and phylogenetic tree networks were used to recover more than 600 new FaRLiP gene sequences, corresponding to 52 new gene clusters. These data enable high-resolution phylogenetics and - by relying on multiple gene trees, together with gene arrangement conservation - support FaRLiP appearing early in cyanobacterial evolution. Sampling information shows that considerable FaRLiP diversity can be observed in microbialites to the present day, and the process may have been associated with microbial mats and stromatolite formation in the early Paleoproterozoic. The ancestral FaRLiP cluster was reconstructed, revealing a conserved intergenic regulatory sequence that has been maintained for billions of years. Taken together, our results indicate that oxygenic photosynthesis using far-red light may have played a significant role in Earths early history.

evolutionary biology↗

Spherical Phenotype Clustering

Phenotypic screening experiments produce many microscope images of cells under diverse perturbations, with biologically significant responses often subtle or difficult to identify visually. A central challenge is to extract image representations that distinguish activity from controls and group phenotypically similar perturbations. In this work we propose new adaptations of contrastive loss functions that incorporate experimental metadata as learned class vectors, and a geometrically inspired variant, called SPC, where class vectors are confined to the unit sphere and updated only by attractive terms (allowing more overlap of phenotypically similar classes). The approach is tested on two popular benchmarking datasets, BBBC021 and RxRx3-core; and we also evaluate performance on uncurated screens of HaCaT cells to gauge effectiveness in a realistic use-case scenario. We find we outperform prior methods across the three datasets and on a wide array of metrics measuring phenotype grouping, biological recall, drug-target interaction and mechanism-of-action inference. We also show we maintain this improved performance compared to models over 10x larger in parameter count, and that SPC can be used as an effective fine-tuning technique. The method is easy to implement and is well suited to settings with limited data or compute resources.

bioinformatics↗

Mitochondria-containing extracellular vesicles from mouse vs. human brain endothelial cells for ischemic stroke therapy

Ischemic stroke-induced mitochondrial dysfunction in the blood-brain barrier-forming brain endothelial cells (BECs) results in long-term neurological dysfunction post-stroke. We previously data from a pilot study where intravenous administration of human BEC (hBEC)-derived mitochondria-containing extracellular vesicles (EVs) showed a potential efficacy signal in a mouse middle cerebral artery occlusion (MCAo) model of stroke. We hypothesized that EVs harvested from donor species homologous to the recipient species (e.g., mouse) may improve therapeutic efficacy, and therefore, use of mouse BEC (mBEC)-derived EVs may improve post-stroke outcomes in MCAo mice. We investigated potential differences in the mitochondria transfer of EVs derived from the same species as the recipient cell (mBEC-EVs and recipient mBECs or hBECs-EVs and recipient hBECs) vs. cross-species EVs and recipient cells (mBEC-EVs and recipient hBECs or vice versa). Our results showed that while both hBEC- and mBEC-EVs transferred EV mitochondria, mBEC-EVs outperformed hBEC-EVs in increasing ATP levels and improved recipient mBEC mitochondrial function via increasing oxygen consumption rates. mBEC-EVs significantly reduced brain infarct volume and neurological deficit scores compared to vehicle-injected MCAo mice. The superior therapeutic efficacy of mBEC-EVs in a mouse MCAo stroke support the continued use of mBEC-EVs to optimize the therapeutic potential of mitochondria-containing EVs in preclinical mouse models. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=84 SRC="FIGDIR/small/575903v2_ufig1.gif" ALT="Figure 1"> View larger version (28K): org.highwire.dtl.DTLVardef@d1deb4org.highwire.dtl.DTLVardef@74157corg.highwire.dtl.DTLVardef@12eb991org.highwire.dtl.DTLVardef@990a47_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioengineering↗

Multi-omic temporal landscape of plasma and synovial fluid-derived extracellular vesicles using an experimental model of equine osteoarthritis

Extracellular vesicles contribute to osteoarthritis pathogenesis through their release into joint tissues and synovial fluid. Limited studies have profiled extracellular vesicles in osteoarthritic biofluids, such as plasma and synovial fluid. Due to the potential involvement in osteoarthritis pathogenesis, synovial fluid-derived extracellular vesicles have the potential to be direct biomarkers in the causal pathway of disease but also enable understanding of their role in disease progression. Utilizing a temporal model of early osteoarthritis, we defined the changes in matched synovial fluid and plasma-derived extracellular vesicle small non-coding RNA and protein cargo using small RNA sequencing and mass spectrometry proteomics. We explored the data with a multi-omic approach including time series clustering, factor analysis and gene enrichment interrogation. Chondrocyte signalling induced by temporal synovial fluid-derived extracellular vesicles derived from the model were analysed using luciferase-based transcription factor activity assays. Extracellular vesicle protein cargo appears to be more important during osteoarthritis progression than small non-coding RNA cargo. Cluster analysis revealed plasma-extracellular vesicles represented a time-dependant response to osteoarthritis induction, were principally derived from protein cargo and were associated with supramolecular complexes. Clusters for synovial fluid-derived extracellular vesicles were associated with an initial osteoarthritis response and represented immune/inflammatory pathways. Factor analysis revealed that plasma-derived extracellular vesicles correlated with day post induction and were primarily composed of proteins which may modulate lipid metabolism in osteoarthritis. Synovial fluid-derived extracellular vesicles significant factors represented intermediate filament and supramolecular complexes reflecting tissue repair responses to osteoarthritis induction. There was a significant interaction between time and osteoarthritis for cAMP response element, Nuclear factor-kappa B response element, serum response element and serum response factor response element reporters with a trend for osteoarthritis synovial fluid-derived EVs at later time points to have a more pronounced effect. Local and systemic osteoarthritis-associated changes in extracellular vesicle cargo profiles in this in vivo model provided a unique opportunity to understand their role in disease propagation and progression and may represent novel biomarkers to stage osteoarthritis.

molecular biology↗

Auditory cortex anatomy reflects multilingual phonological experience

This study explores the relationship between the anatomy of the auditory cortex and multilingual experience, shedding light on the complex mechanisms of auditory processing in humans. Integrating previous research on auditory information processing and the impact of bi- and multilingualism on brain structure, we investigate how the morphology of auditory brain regions reflects individuals language experience and, more specifically, their phonological repertoire. Leveraging two distinct samples comprising over 200 participants, each exposed to between 1 and 7 languages encompassing 36 different languages, we explore whether the morphological variability of auditory brain regions reflects individual language experience, specifically focusing on the phonological repertoire. Additionally, we examine the potential influence of typological distances between languages spoken by multilingual individuals on the neural signatures of multilingualism within the auditory cortex. Our findings revealed a relationship between the average thickness of the left and right second transverse temporal gyrus (TTG) and participants language experience. Model comparisons demonstrated that the inclusion of phoneme-level information in the language experience index accounted for the greatest variance in average TTG thickness (bilaterally). The direction of this effect was negative, indicating that a more extensive and more phonologically diverse language experience was associated with thinner cortices in the second TTG. Across two independent datasets, we provide robust evidence linking the degree of language experience and typological distance between languages to cortical thickness in early auditory brain regions. We propose that this phenomenon may reflect experience-driven pruning and neural efficiency, warranting further investigation through longitudinal studies of language acquisition. Moreover, our findings support the notion that experiences with typologically similar languages differ from those with typologically distant languages, offering valuable insights into the intricate relationship between language diversity and brain structure. Our findings also indicate that early auditory regions seem to represent phoneme-level cross-linguistic information, contrary to the most established models of language processing in the brain, which suggest that phonological processing happens in more lateral posterior STG and STS.

neuroscience↗

Dengue transmission risk in a changing climate: Bangladesh could experience a longer dengue fever season in the future

Our changing climate is already affecting the transmission of vector borne diseases such as dengue fever. This issue presents a significant public health concern for some nations, such as Bangladesh, which already experience regular seasonal outbreaks of dengue fever under present day conditions. To provide guidance for proactive public health planning to potentially mitigate future infections, we explore the impact of climate change on dengue infections by calculating the change in vectorial capacity of Aedes aegypti mosquito at a seasonal level for all regions in Bangladesh under two scenarios for future atmospheric greenhouse gas concentrations. For each of the four climate models used, and for both scenarios, our analysis reveals that the annual vectorial capacity remains at a level that would enable potential dengue epidemic transmission in all regions in Bangladesh. We found a slight decline in vectorial capacity in half of the regions examined during the last two decades of the 21st Century for the lower-concentration scenario, with a pronounced decline in vectorial capacity in all geographic regions beginning in 2060 for the higher-concentration scenario. The likely reason is that in many regions, warming is leading to sub-optimal mosquito breeding temperatures. However, seasonal differences in vectorial capacity dissipates as the climate warms, to the point that there is almost no observable seasonality for the higher-concentration scenario during the last two decades of this century. This finding suggests there is the potential for the dengue season to extend all year, with outbreaks occurring at any time. Consequently, disease surveillance and control activities would need to be geographically and temporally adapted to mitigate dengue epidemic risk in response to climate change.

ecology↗

The P2RX7B splice variant modulates osteosarcoma cell behaviour and metastatic properties

Osteosarcoma (OS) is the most common type of primary bone cancer affecting children and adolescents. OS has a high propensity to spread, meaning the disease is often incurable and fatal. There have been no improvements in survival rates for decades. This highlights an urgent need for development of novel therapeutic strategies. In this study, we have produced in vitro and in vivo data that demonstrates the role of purinergic signalling, specifically, the B isoform of the purinergic receptor P2RX7 (herein termed " P2RX7B"), in OS progression and metastasis. Our data shows that P2RX7B expression confers a survival advantage in TE85+P2RX7B and MNNG-HOS+ P2RX7B human OS cell lines in vitro that is minimised following treatment with A740003, a specific P2RX7 antagonist. P2RX7B expression reduced cell adhesion and P2RX7B activation promoted invasion and migration in vitro, suggesting a probable metastatic phenotype. Using an in vivo OS xenograft model, MNNG-HOS+P2RX7B tumours exhibited ectopic bone formation that was abrogated with A740003 treatment. An increased metastatic phenotype was further demonstrated in vivo as expression of P2RX7B in primary tumour cells increased the propensity of the tumour to metastasise to the lungs. RNA-seq identified a novel gene axis, FN1/LOX/PDGFB/IGFBP3/BMP4, downregulated in response to A740003 treatment. In conclusion, our data indicates for the first time a role for P2RX7B in OS tumour growth, progression and metastasis. We show that P2RX7B is a potential therapeutic target in human OS. Novelty and ImpactWe provide evidence for the pro-tumorigenic role of the B isoform of the P2RX7 purinergic receptor in osteosarcoma (OS). In addition to increasing proliferation, P2RX7B increases the cancerous properties of OS cells, reducing adhesion and increasing migration and invasion. In vivo, P2RX7B does not affect primary tumour growth, but does lead to an increased propensity to metastasize. RNA-seq revealed a new axis of oncogenic genes inhibited by the P2RX7 antagonist and this data could potentially lead to new targets for OS treatment.

cancer biology↗

Why the COVID-19 pandemic is a traumatic stressor

The COVID-19 pandemic does not fit into prevailing Post-traumatic Stress Disorder (PTSD) models, or diagnostic criteria, yet emerging research shows traumatic stress symptoms as a result of this ongoing global stressor. Current pathogenic event models focus on past, and largely direct, trauma exposure to certain kinds of life-threatening events. Nevertheless, among a sample of online participants (N = 1,040) in five western countries, we found participants had PTSD-like symptoms for events that had not happened and when participants had been directly (e.g., contact with virus) or indirectly exposed to COVID-19 (e.g., via media). Moreover, 13.2% of our sample were likely PTSD-positive, despite types of COVID-19 "exposure" (e.g., lockdown) not fitting DSM-5 criteria. The emotional impact of "worst" experienced/anticipated events best predicted PTSD-like symptoms. Our findings add to existing literature supporting a pathogenic event memory model of traumatic stress.

animal behavior and cognition↗

Antagonism of STAT3 signalling by Ebola virus

Many viruses target signal transducers and activators of transcription (STAT) 1 and 2 to antagonise antiviral interferon (IFN) signalling, but targeting of signalling by other STATs/cytokines, including STAT3/interleukin (IL-) 6 that regulate processes important to Ebola virus (EBOV) haemorrhagic fever, is poorly defined. We report that EBOV potently inhibits STAT3 responses to IL-6 family cytokines, and that this is mediated by the IFN-antagonist VP24. Mechanistic analysis indicates that VP24 effects a unique strategy combining distinct karyopherin-dependent and karyopherin-independent mechanisms to antagonise STAT3-STAT1 heterodimers and STAT3 homodimers, respectively. This appears to reflect distinct mechanisms of nuclear trafficking of the STAT3 complexes, revealed for the first time by our analysis of VP24 function. These findings are consistent with major roles for global inhibition of STAT3 signalling in EBOV infection, and provide new insights into the molecular mechanisms of STAT3 nuclear trafficking, significant to pathogen-host interactions, cell physiology and pathologies such as cancer. Author summaryEbola virus (EBOV) continues to pose a significant risk to human health globally, causing ongoing disease outbreaks with case-fatality rates between 40 and 60%. Suppression of immune responses is a critical component of EBOV haemorrhagic fever, but understanding of EBOV impact on signalling by cytokines other than interferon is limited. We find that infectious EBOV inhibits interleukin-6 cytokine signalling via antagonism of STAT3. The antagonistic strategy uniquely combines two distinct mechanisms, which appear to reflect differing nuclear trafficking mechanisms of critical STAT3 complexes. This provides fundamental insights into the mechanisms of pathogenesis of a lethal virus, and biology of STAT3, a critical player in immunity, development, growth and cancer.

microbiology↗

A quantised cyclin-based cell cycle model

Computational modelling is an important research tool, helping predict the outcome of proposed treatment plans or to illuminate the mechanics of tumour growth. In silico modelling has been used in every aspect of cancer research from DNA damage and repair, tumour growth, drug/tumour interactions, and mutational status. Indeed, modelling even holds potential in understanding the interactions between individual proteins on a single cell basis. Here, we present a computational model of the cell cycle network of the cyclin family of proteins (cyclin A, B, D and E). This model has been quantised using western blot and flow cytometry data from a synchronised HUVEC line to enable the determination of the absolute number of cyclin protein molecules per cell. This quantification allows the model to have stringent controls over the thresholds between transitions. The results show that the peak values obtained for the four cyclins are similar with cyclin B having a peak values of 5x106 to 9x106 molecules per cell. Comparing this value with the number of actin proteins, 5E8, shows that despite their importance, the level of cyclin family proteins are approximately 2 orders of magnitude lower. The efficiency of the model presented would also allow for its use as an internal component in more complex models such as a tumour growth model, in which each individual cell would have its own cell cycle calculated independently from neighbouring cells. Additionally, the model can also be used to help understand the impact of novel therapeutic interventions on cell cycle progression. Author SummaryProtein and gene networks control every physiological behaviour of cells, with the cell cycle being controlled by the network of genes that promote the cyclin family of proteins. These networks hold the key to creating accurate and relevant biological models. Normally these models are presented with relative protein concentrations without any real world counterpart to their outputs. The model presented within shows and advancement of this approach by calculating the absolute concentration of each cyclin protein in one cell as it progresses through the cell cycle. This model employs Boolean variables to represent the genetic network, either the gene is active or not, and continuous variables to represent the concentrations of the proteins. This hybridised approach allows for rapid calculations of the protein concentrations and of the cell cycle progression allowing for a model that could be easily incorporated into larger tumour models, allowing for the tracking of discrete cells within the tumour.

cell biology↗

Comparison of Cepheid Xpert Xpress and Abbott ID Now to Roche cobas for the Rapid Detection of SARS-CoV-2

The SARS-CoV-2 pandemic has created an urgent and unprecedented need for rapid large-scale diagnostic testing to inform timely patient management. This study compared two recently-authorized rapid tests, Cepheid Xpert Xpress SARS-CoV-2 and Abbott ID Now SARS-CoV-2 to the Roche cobas SARS-CoV-2 assay. A total of 113 nasopharyngeal swabs were tested, including 88 positives spanning the full range of observed Ct values on the cobas assay. Compared to cobas, the overall positive agreement was 73.9% with ID Now and 98.9% with Xpert. Negative agreement was 100% and 92.0% for ID Now and Xpert, respectively. Both ID Now and Xpert showed 100% positive agreement for medium and high viral concentrations (Ct value <30). However, for Ct values >30, positive agreement was 34.3% for ID Now and 97.1% for Xpert. These findings highlight an important limitation of ID Now for specimens collected in viral or universal transport media with low viral concentrations. Further studies are needed to evaluate the performance of ID Now for direct swabs.

microbiology↗

Unilateral vocal nerve resection alters neurogenesis in the avian song system in a region-specific manner

New neurons undergo a critical period soon after migration during which the behavior of the animal may result in the survival or culling of these cells. In the songbird song system, new neurons may be maintained in the song motor pathway with respect to motor progression toward a target song--during juvenile song learning, seasonal song restructuring, and experimentally manipulated song variability. However, it is not known whether the quality of song per se, without progressive improvement, may also influence new neuron survival. To test this idea, we experimentally altered song acoustic structure by unilateral denervation of the syrinx. We found no effect of aberrant song on numbers of new neurons in the HVC of the song motor pathway, a loss of left-side dominance in new neurons in the auditory region caudomedial nidopallium (NCM), and a bilateral decrease in new neurons in the basal ganglia nucleus Area X. We propose new neuron survival may be determined in response to behavioral feedback in accordance with the function of new neurons within a given brain region. Studying the effects of singing behaviors on new neurons across multiple brain regions that subserve singing may give rise to general rules underlying the regulation of new neuron survival across taxa and brain regions more broadly.

neuroscience↗

Accelerating iterative deconvolution and multiview fusion by orders of magnitude

We describe theoretical and practical advances in algorithm and software design, resulting in ten to several thousand-fold faster deconvolution and multiview fusion than previous methods. First, we adapt methods from medical imaging, showing that an unmatched back projector accelerates Richardson-Lucy deconvolution by at least 10-fold, in most cases requiring only a single iteration. Second, we show that improvements in 3D image-based registration with GPU processing result in speedups of 10-100-fold over CPU processing. Third, we show that deep learning can provide further accelerations, particularly for deconvolution with a spatially varying point spread function. We illustrate the power of our methods from the subcellular to millimeter spatial scale, on diverse samples including single cells, nematode and zebrafish embryos, and cleared mouse tissue. Finally, we show that our methods facilitate the use of new microscopes that improve spatial resolution, including dual-view cleared tissue light-sheet microscopy and reflective lattice light-sheet microscopy.

bioengineering↗