Development of a large volume line scanning, high spectral range and resolution 3D hyperspectral photoluminescence imaging microscope for diamond and other high refractive index materials.

Hyperspectral photoluminescence (PL) imaging is a powerful technique that can be used to understand the spatial distribution of emitting species in many materials. Volumetric hyperspectral imaging of weakly emitting color centers often necessitates considerable data collection times when using commercial systems. We report the development of a line-scanning hyperspectral imaging microscope capable of measuring the luminescence emission spectra for diamond volumes up to 2.20 × 30.00 × 6.30 mm with a high lateral spatial resolution of 1-3 µm. In an single X-λ measurement, spectra covering a 711 nm range, in a band from 400-1100 nm, with a spectral resolution up to 0.25 nm can be acquired. Data sets can be acquired with 723 (X) × 643 (Y) × 1172 (λ) pixels at a rate of 6 minutes/planar image slice, allowing for volumetric hyperspectral imaging with high sampling. This instrument demonstrates the ability to detect emission from several different color centers in diamond both at the surface and internally, providing a non-destructive method to probe their 3D spatial distribution, and is currently not achievable with any other commonly used system or technique.

Cell Simulation as Cell Segmentation.

Single-cell spatial transcriptomics promises a highly detailed view of a cell's transcriptional state and microenvironment, yet inaccurate cell segmentation can render this data murky by misattributing large numbers of transcripts to nearby cells or conjuring nonexistent cells. We adopt methods from ab initio cell simulation to rapidly infer morphologically plausible cell boundaries that preserve cell type heterogeneity. Benchmarking applied to datasets generated by three commercial platforms show superior performance and computational efficiency of this approach compared with existing methods. We show that improved accuracy in cell segmentation aids greatly in detection of difficult to accurately segment tumor infiltrating immune cells such as neutrophils and T cells. Lastly, through improvements in our ability to delineate subsets of tumor infiltrating T cells, we show that CXCL13-expressing CD8+ T cells tend to be more closely associated with tumor cells than their CXCL13-negative counterparts in data generated from renal cell carcinoma patient samples. Proseg is available under at open source license at https://github.com/dcjones/proseg.

Characterization of Immunosuppressive Myeloid Cells in Merkel Cell Carcinoma: Correlation with Resistance to PD-1 Pathway Blockade.

PURPOSE: Merkel cell carcinoma (MCC) is a highly immunogenic skin cancer. Although essentially all MCCs are antigenic through viral antigens or high tumor mutation burden, MCC has a response rate of only approximately 50% to PD-(L)1 blockade suggesting barriers to T-cell responses. Prior studies of MCC immunobiology have focused on CD8 T-cell infiltration and their exhaustion status, while the role of innate immunity, particularly myeloid cells, in MCC remains underexplored. EXPERIMENTAL DESIGN: We utilized single-cell transcriptomics from 9 patients with MCC and multiplex IHC staining of 54 patients' preimmunotherapy tumors, to identify myeloid cells and evaluate association with immunotherapy response. RESULTS: Single-cell transcriptomics identified tumor-associated macrophages (TAM) as the dominant myeloid component within MCC tumors. These TAMs express an immunosuppressive gene signature characteristic of monocytic myeloid-derived suppressor cells and importantly express several targetable immune checkpoint molecules, including PD-L1 and LILRB receptors, that are not present on tumor cells. Analysis of 54 preimmunotherapy tumor samples showed that a subset of TAMs (CD163+, CD14+, S100A8+) selectively infiltrated tumors that had significant CD8 T cells. Indeed, higher TAM prevalence was associated with resistance to PD-1 blockade. While spatial interactions between TAMs and CD8 T cells were not associated with response, myeloid transcriptomic data showed evidence for cytokine signaling and expression of LILRB receptors, suggesting potential immunosuppressive mechanisms. CONCLUSIONS: This study further characterizes TAMs in MCC tumors and provides insights into their possible immunosuppressive mechanism. TAMs may reduce the likelihood of treatment response in MCC by counteracting the benefit of CD8 T-cell infiltration. See related commentary by Silk and Davar, p. 1076.

An information theoretic approach to detecting spatially varying genes.

A key step in spatial transcriptomics is identifying genes with spatially varying expression patterns. We adopt an information theoretic perspective to this problem by equating the degree of spatial coherence with the Jensen-Shannon divergence between pairs of nearby cells and pairs of distant cells. To avoid the notoriously difficult problem of estimating information theoretic divergences, we use modern approximation techniques to implement a computationally efficient algorithm designed to scale with in situ spatial transcriptomics technologies. In addition to being highly scalable, we show that our method, which we call maximization of spatial information (Maxspin), improves accuracy across several spatial transcriptomics platforms and a variety of simulations when compared with a variety of state-of-the-art methods. To further demonstrate the method, we generated in situ spatial transcriptomics data in a renal cell carcinoma sample using the CosMx Spatial Molecular Imager and used Maxspin to reveal novel spatial patterns of tumor cell gene expression.

Finale: impact of the ORCHESTRA/ENCORE programmes on Southern Ocean heat and carbon understanding.

The 5-year Ocean Regulation of Climate by Heat and Carbon Sequestration and Transports (ORCHESTRA) programme and its 1-year extension ENCORE (ENCORE is the National Capability ORCHESTRA Extension) was an approximately 11-million-pound programme involving seven UK research centres that finished in March 2022. The project sought to radically improve our ability to measure, understand and predict the exchange, storage and export of heat and carbon by the Southern Ocean. It achieved this through a series of milestone observational campaigns in combination with model development and analysis. Twelve cruises in the Weddell Sea and South Atlantic were undertaken, along with mooring, glider and profiler deployments and aircraft missions, all contributing to measurements of internal ocean and air-sea heat and carbon fluxes. Numerous forward and adjoint numerical experiments were developed and supported by the analysis of coupled climate models. The programme has resulted in over 100 peer-reviewed publications to date as well as significant impacts on climate assessments and policy and science coordination groups. Here, we summarize the research highlights of the programme and assess the progress achieved by ORCHESTRA/ENCORE and the questions it raises for the future. This article is part of a discussion meeting issue 'Heat and carbon uptake in the Southern Ocean: the state of the art and future priorities'.

Ventilation of the Southern Ocean Pycnocline.

Ocean ventilation is the transfer of tracers and young water from the surface down into the ocean interior. The tracers that can be transported to depth include anthropogenic heat and carbon, both of which are critical to understanding future climate trajectories. Ventilation occurs in both high- and midlatitude regions, but it is the southern midlatitudes that are responsible for the largest fraction of anthropogenic heat and carbon uptake; such Southern Ocean ventilation is the focus of this review. Southern Ocean ventilation occurs through a chain of interconnected mechanisms, including the zonally averaged meridional overturning circulation, localized subduction, eddy-driven mixing along isopycnals, and lateral transport by subtropical gyres. To unravel the complex pathways of ventilation and reconcile conflicting results, here we assess the relative contribution of each of thesemechanisms, emphasizing the three-dimensional and temporally varying nature of the ventilation of the Southern Ocean pycnocline. We conclude that Southern Ocean ventilation depends on multiple processes and that simplified frameworks that explain ventilation changes through a single process are insufficient.

Untangling local and remote influences in two major petrel habitats in the oligotrophic Southern Ocean.

Ocean circulation connects geographically distinct ecosystems across a wide range of spatial and temporal scales via exchanges of physical and biogeochemical properties. Remote oceanographic processes can be especially important for ecosystems in the Southern Ocean, where the Antarctic Circumpolar Current transports properties across ocean basins through both advection and mixing. Recent tracking studies have indicated the existence of two large-scale, open ocean habitats in the Southern Ocean used by grey petrels (Procellaria cinerea) from two populations (i.e., Kerguelen and Antipodes islands) during their nonbreeding season for extended periods during austral summer (i.e., October to February). In this work, we use a novel combination of large-scale oceanographic observations, surface drifter data, satellite-derived primary productivity, numerical adjoint sensitivity experiments, and output from a biogeochemical state estimate to examine local and remote influences on these grey petrel habitats. Our aim is to understand the oceanographic features that control these isolated foraging areas and to evaluate their ecological value as oligotrophic open ocean habitats. We estimate the minimum local primary productivity required to support these populations to be much <1% of the estimated local primary productivity. The region in the southeast Indian Ocean used by the birds from Kerguelen is connected by circulation to the productive Kerguelen shelf. In contrast, the region in the south-central Pacific Ocean used by seabirds from the Antipodes is relatively isolated suggesting it is more influenced by local factors or the cumulative effects of many seasonal cycles. This work exemplifies the potential use of predator distributions and oceanographic data to highlight areas of the open ocean that may be more dynamic and productive than previously thought. Our results highlight the need to consider advective connections between ecosystems in the Southern Ocean and to re-evaluate the ecological relevance of oligotrophic Southern Ocean regions from a conservation perspective.

Seasonal Arctic sea ice forecasting with probabilistic deep learning.

Anthropogenic warming has led to an unprecedented year-round reduction in Arctic sea ice extent. This has far-reaching consequences for indigenous and local communities, polar ecosystems, and global climate, motivating the need for accurate seasonal sea ice forecasts. While physics-based dynamical models can successfully forecast sea ice concentration several weeks ahead, they struggle to outperform simple statistical benchmarks at longer lead times. We present a probabilistic, deep learning sea ice forecasting system, IceNet. The system has been trained on climate simulations and observational data to forecast the next 6 months of monthly-averaged sea ice concentration maps. We show that IceNet advances the range of accurate sea ice forecasts, outperforming a state-of-the-art dynamical model in seasonal forecasts of summer sea ice, particularly for extreme sea ice events. This step-change in sea ice forecasting ability brings us closer to conservation tools that mitigate risks associated with rapid sea ice loss.

Polee: RNA-Seq analysis using approximate likelihood.

The analysis of mRNA transcript abundance with RNA-Seq is a central tool in molecular biology research, but often analyses fail to account for the uncertainty in these estimates, which can be significant, especially when trying to disentangle isoforms or duplicated genes. Preserving uncertainty necessitates a full probabilistic model of the all the sequencing reads, which quickly becomes intractable, as experiments can consist of billions of reads. To overcome these limitations, we propose a new method of approximating the likelihood function of a sparse mixture model, using a technique we call the Pólya tree transformation. We demonstrate that substituting this approximation for the real thing achieves most of the benefits with a fraction of the computational costs, leading to more accurate detection of differential transcript expression and transcript coexpression.

Metabolic Control over mTOR-Dependent Diapause-like State.

Regulation of embryonic diapause, dormancy that interrupts the tight connection between developmental stage and time, is still poorly understood. Here, we characterize the transcriptional and metabolite profiles of mouse diapause embryos and identify unique gene expression and metabolic signatures with activated lipolysis, glycolysis, and metabolic pathways regulated by AMPK. Lipolysis is increased due to mTORC2 repression, increasing fatty acids to support cell survival. We further show that starvation in pre-implantation ICM-derived mouse ESCs induces a reversible dormant state, transcriptionally mimicking the in vivo diapause stage. During starvation, Lkb1, an upstream kinase of AMPK, represses mTOR, which induces a reversible glycolytic and epigenetically H4K16Ac-negative, diapause-like state. Diapause furthermore activates expression of glutamine transporters SLC38A1/2. We show by genetic and small molecule inhibitors that glutamine transporters are essential for the H4K16Ac-negative, diapause state. These data suggest that mTORC1/2 inhibition, regulated by amino acid levels, is causal for diapause metabolism and epigenetic state.

Multidimensional luminescence microscope for imaging defect colour centres in diamond.

We report a multidimensional luminescence microscope providing hyperspectral imaging and time-resolved (luminescence lifetime) imaging for the study of luminescent diamond defects. The instrument includes crossed-polariser white light transmission microscopy to reveal any birefringence that would indicate strain in the diamond lattice. We demonstrate the application of this new instrument to detect defects in natural and synthetic diamonds including N3, nitrogen and silicon vacancies. Hyperspectral imaging provides contrast that is not apparent in conventional intensity images and the luminescence lifetime provides further contrast.

Comment on "Dissolved organic sulfur in the ocean: Biogeochemistry of a petagram inventory".

Ksionzek et al (Reports, 28 October 2016, p. 456) provide important data describing the distribution of dissolved organic sulfur (DOS) in the Atlantic Ocean. Here, we show that mixing between water masses is sufficient to explain the observed distribution of DOS, concluding that the turnover time of refractory DOS that Ksionzek et al present cannot be deduced from their data.

Analysis of stable isotope ratios in blood of tracked wandering albatrosses fails to distinguish a δ(13) C gradient within their winter foraging areas in the southwest Atlantic Ocean.

RATIONALE: The main limitation of isotopic tracking for inferring distribution is the lack of detailed reference maps of the isotopic landscape (i.e. isoscapes) in the marine environment. Here, we attempt to map the marine δ(13) C isoscape for the southwestern sector of the Atlantic Ocean, and assess any temporal variation using the wandering albatross as a model species. METHODS: Tracking data and blood and diet samples were collected monthly from wandering albatrosses rearing chicks at Bird Island, South Georgia, during the austral winter between May and October 2009. The δ(13) C and δ(15) N values were measured by mass spectrometry in plasma and blood cells, and related to highly accurate data on individual movements and feeding activity obtained using three types of device: GPS, activity (immersion) loggers and stomach temperature probes. RESULTS: The tracked birds foraged in waters to the north or northwest of South Georgia, including the Patagonian shelf-break, as far as 2000 km from the colony. The foraging region encompassed the two main fronts in the Southern Ocean (Polar and Subantarctic fronts). The δ(13) C values varied by only 2.1 ‰ in plasma and 2.5 ‰ in blood cells, and no relationships were found between the δ(13) C values in plasma and the mean latitude or longitude of landings or feeding events of each individual. CONCLUSIONS: The failure to distinguish a major biogeographic gradient in δ(13) C values suggest that these values in the south Atlantic Ocean are fairly homogeneous. There was no substantial variation among months in either the δ(13) C or the δ(15) N values of plasma or blood cells of tracked birds. As birds did not show a significant change in diet composition or foraging areas during the study period, these results provide no evidence for major temporal variation in stable isotope ratios in consumer tissues, or in the regional marine isoscape in the austral winter of 2009.

Let-7 family of microRNA is required for maturation and adult-like metabolism in stem cell-derived cardiomyocytes.

In metazoans, transition from fetal to adult heart is accompanied by a switch in energy metabolism-glycolysis to fatty acid oxidation. The molecular factors regulating this metabolic switch remain largely unexplored. We first demonstrate that the molecular signatures in 1-year (y) matured human embryonic stem cell-derived cardiomyocytes (hESC-CMs) are similar to those seen in in vivo-derived mature cardiac tissues, thus making them an excellent model to study human cardiac maturation. We further show that let-7 is the most highly up-regulated microRNA (miRNA) family during in vitro human cardiac maturation. Gain- and loss-of-function analyses of let-7g in hESC-CMs demonstrate it is both required and sufficient for maturation, but not for early differentiation of CMs. Overexpression of let-7 family members in hESC-CMs enhances cell size, sarcomere length, force of contraction, and respiratory capacity. Interestingly, large-scale expression data, target analysis, and metabolic flux assays suggest this let-7-driven CM maturation could be a result of down-regulation of the phosphoinositide 3 kinase (PI3K)/AKT protein kinase/insulin pathway and an up-regulation of fatty acid metabolism. These results indicate let-7 is an important mediator in augmenting metabolic energetics in maturing CMs. Promoting maturation of hESC-CMs with let-7 overexpression will be highly significant for basic and applied research.

Assessment and improvement of Indian-origin rhesus macaque and Mauritian-origin cynomolgus macaque genome annotations using deep transcriptome sequencing data.

BACKGROUND: The genome annotations of rhesus (Macaca mulatta) and cynomolgus (Macaca fascicularis) macaques, two of the most common non-human primate animal models, are limited. METHODS: We analyzed large-scale macaque RNA-based next-generation sequencing (RNAseq) data to identify un-annotated macaque transcripts. RESULTS: For both macaque species, we uncovered thousands of novel isoforms for annotated genes and thousands of un-annotated intergenic transcripts enriched with non-coding RNAs. We also identified thousands of transcript sequences which are partially or completely 'missing' from current macaque genome assemblies. We showed that many newly identified transcripts were differentially expressed during SIV infection of rhesus macaques or during Ebola virus infection of cynomolgus macaques. CONCLUSIONS: For two important macaque species, we uncovered thousands of novel isoforms and un-annotated intergenic transcripts including coding and non-coding RNAs, polyadenylated and non-polyadenylated transcripts. This resource will greatly improve future macaque studies, as demonstrated by their applications in infectious disease studies.

Compression of next-generation sequencing reads aided by highly efficient de novo assembly.

UNLABELLED: We present Quip, a lossless compression algorithm for next-generation sequencing data in the FASTQ and SAM/BAM formats. In addition to implementing reference-based compression, we have developed, to our knowledge, the first assembly-based compressor, using a novel de novo assembly algorithm. A probabilistic data structure is used to dramatically reduce the memory required by traditional de Bruijn graph assemblers, allowing millions of reads to be assembled very efficiently. Read sequences are then stored as positions within the assembled contigs. This is combined with statistical compression of read identifiers, quality scores, alignment information and sequences, effectively collapsing very large data sets to <15% of their original size with no loss of information. AVAILABILITY: Quip is freely available under the 3-clause BSD license from http://cs.washington.edu/homes/dcjones/quip.

A new approach to bias correction in RNA-Seq.

MOTIVATION: Quantification of sequence abundance in RNA-Seq experiments is often conflated by protocol-specific sequence bias. The exact sources of the bias are unknown, but may be influenced by polymerase chain reaction amplification, or differing primer affinities and mixtures, for example. The result is decreased accuracy in many applications, such as de novo gene annotation and transcript quantification. RESULTS: We present a new method to measure and correct for these influences using a simple graphical model. Our model does not rely on existing gene annotations, and model selection is performed automatically making it applicable with few assumptions. We evaluate our method on several datasets, and by multiple criteria, demonstrating that it effectively decreases bias and increases uniformity. Additionally, we provide theoretical and empirical results showing that the method is unlikely to have any effect on unbiased data, suggesting it can be applied with little risk of spurious adjustment. AVAILABILITY: The method is implemented in the seqbias R/Bioconductor package, available freely under the LGPL license from http://bioconductor.org CONTACT: dcjones@cs.washington.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

A self-learning fuzzy discrete event system for HIV/AIDS treatment regimen selection.

The U.S. Department of Health and Human Services Human Immunodeficiency Virus (HIV)/Acquired Immune Deficiency Syndrome (AIDS) treatment guidelines are modified several times per year to reflect the rapid evolution of the field (e.g., emergence of new antiretroviral drugs). As such, a treatment-decision support system that is capable of self-learning is highly desirable. Based on the fuzzy discrete event system (FDES) theory that we recently created, we have developed a self-learning HIV/AIDS regimen selection system for the initial round of combination antiretroviral therapy, one of the most complex therapies in medicine. The system consisted of a treatment objectives classifier, fuzzy finite state machine models for treatment regimens, and a genetic-algorithm-based optimizer. Supervised learning was achieved through automatically adjusting the parameters of the models by the optimizer. We focused on the four historically popular regimens with 32 associated treatment objectives involving the four most important clinical variables (potency, adherence, adverse effects, and future drug options). The learning targets for the objectives were produced by two expert AIDS physicians on the project, and their averaged overall agreement rate was 70.6%. The system's learning ability and new regimen suitability prediction capability were tested under various conditions of clinical importance. The prediction accuracy was found between 84.4% and 100%. Finally, we retrospectively evaluated the system using 23 patients treated by 11 experienced nonexpert faculty physicians and 12 patients treated by the two experts at our AIDS Clinical Center in 2001. The overall exact agreement between the 13 physicians' selections and the system's choices was 82.9% with the agreement for the two experts being both 100%. For the seven mismatched cases, the system actually chose more appropriate regimens in four cases and equivalent regimens in another two cases. It made a mistake in one case. These (preliminary) results show that 1) the System outperformed the nonexpert physicians and 2) it performed as well as the expert physicians did. This learning and prediction approach, as well as our original FDESs theory, is general purpose and can be applied to other medical or nonmedical problems.

A fuzzy discrete event system approach to determining optimal HIV/AIDS treatment regimens.

Treatment decision-making is complex and involves many factors. A systematic decision-making and optimization technology capable of handling variations and uncertainties of patient characteristics and physician's subjectivity is currently unavailable. We recently developed a novel general-purpose fuzzy discrete event systems theory for optimal decision-making. We now apply it to develop an innovative system for medical treatment, specifically for the first round of highly active antiretroviral therapy of human immunodeficiency virus/acquired immunodeficiency syndrome (HIV/AIDS) patients involving three historically widely used regimens. The objective is to develop such a system whose regimen choice for any given patient will exactly match expert AIDS physician's selection to produce the (anticipated) optimal treatment outcome. Our regimen selection system consists of a treatment objectives classifier, fuzzy finite state machine models for treatment regimens, and a genetic-algorithm-based optimizer. The optimizer enables the system to either emulate an individual doctor's decision-making or generate a regimen that simultaneously satisfies diverse treatment preferences of multiple physicians to the maximum extent. We used the optimizer to automatically learn the values of 26 parameters of the models. The learning was based on the consensus of AIDS specialists A and B on this project, whose exact agreement was only 35%. The performance of the resulting models was first assessed. We then carried out a retrospective study of the entire system using all the qualifying patients treated in our institution's AIDS Clinical Center in 2001. A total of 35 patients were treated by 13 specialists using the regimens (four and eight patients were treated by specialists A and B, respectively). We compared the actually prescribed regimens with those selected by the system using the same available information. The overall exact agreement was 82.9% (29 out of 35), with the exact agreement with specialists A and B both at 100%. The exact agreement for the remaining 11 physicians not involved in the system training was 73.9% (17 out of 23), an impressive result given the fact that expert opinion can be quite divergent for treatment decisions of such complexity. Our specialists also carefully examined the six mismatched cases and deemed that the system actually chose a more appropriate regimen for four of them. In the other two cases, either would be reasonable choices. Our approach has the capabilities of generalizing, learning, and representing knowledge even in the face of weak consensus, and being readily upgradeable to new medical knowledge. These are practically important features to medical applications in general, and HIV/AIDS treatment in particular, as national HIV/AIDS treatment guidelines are modified several times per year.

Age of sexual initiation and HIV-related behaviours: application of survival analysis.

Previous studies have consistently suggested positive associations between early sexual initiation and subsequent risky sexual behaviours, HIV/STD infection, adolescent pregnancy and substance use. In the present study, survival curves for rural-to-urban migrants in China with and without HIV-related behaviours were analysed to determine (1) the risk of initiating sex at each ageand (2) the association between sexual initiation and HIV-related behaviours.