The molecular cytoarchitecture of the adult mouse brain.

The function of the mammalian brain relies upon the specification and spatial positioning of diversely specialized cell types. Yet, the molecular identities of the cell types and their positions within individual anatomical structures remain incompletely known. To construct a comprehensive atlas of cell types in each brain structure, we paired high-throughput single-nucleus RNA sequencing with Slide-seq1,2-a recently developed spatial transcriptomics method with near-cellular resolution-across the entire mouse brain. Integration of these datasets revealed the cell type composition of each neuroanatomical structure. Cell type diversity was found to be remarkably high in the midbrain, hindbrain and hypothalamus, with most clusters requiring a combination of at least three discrete gene expression markers to uniquely define them. Using these data, we developed a framework for genetically accessing each cell type, comprehensively characterized neuropeptide and neurotransmitter signalling, elucidated region-specific specializations in activity-regulated gene expression and ascertained the heritability enrichment of neurological and psychiatric phenotypes. These data, available as an online resource ( www.BrainCellData.org ), should find diverse applications across neuroscience, including the construction of new genetic tools and the prioritization of specific cell types and circuits in the study of brain diseases.

Molecular hallmarks of heterochronic parabiosis at single-cell resolution.

The ability to slow or reverse biological ageing would have major implications for mitigating disease risk and maintaining vitality1. Although an increasing number of interventions show promise for rejuvenation2, their effectiveness on disparate cell types across the body and the molecular pathways susceptible to rejuvenation remain largely unexplored. Here we performed single-cell RNA sequencing on 20 organs to reveal cell-type-specific responses to young and aged blood in heterochronic parabiosis. Adipose mesenchymal stromal cells, haematopoietic stem cells and hepatocytes are among those cell types that are especially responsive. On the pathway level, young blood invokes new gene sets in addition to reversing established ageing patterns, with the global rescue of genes encoding electron transport chain subunits pinpointing a prominent role of mitochondrial function in parabiosis-mediated rejuvenation. We observed an almost universal loss of gene expression with age that is largely mimicked by parabiosis: aged blood reduces global gene expression, and young blood restores it in select cell types. Together, these data lay the groundwork for a systemic understanding of the interplay between blood-borne factors and cellular integrity.

Ageing hallmarks exhibit organ-specific temporal signatures.

Ageing is the single greatest cause of disease and death worldwide, and understanding the associated processes could vastly improve quality of life. Although major categories of ageing damage have been identified-such as altered intercellular communication, loss of proteostasis and eroded mitochondrial function1-these deleterious processes interact with extraordinary complexity within and between organs, and a comprehensive, whole-organism analysis of ageing dynamics has been lacking. Here we performed bulk RNA sequencing of 17 organs and plasma proteomics at 10 ages across the lifespan of Mus musculus, and integrated these findings with data from the accompanying Tabula Muris Senis2-or 'Mouse Ageing Cell Atlas'-which follows on from the original Tabula Muris3. We reveal linear and nonlinear shifts in gene expression during ageing, with the associated genes clustered in consistent trajectory groups with coherent biological functions-including extracellular matrix regulation, unfolded protein binding, mitochondrial function, and inflammatory and immune response. Notably, these gene sets show similar expression across tissues, differing only in the amplitude and the age of onset of expression. Widespread activation of immune cells is especially pronounced, and is first detectable in white adipose depots during middle age. Single-cell RNA sequencing confirms the accumulation of T cells and B cells in adipose tissue-including plasma cells that express immunoglobulin J-which also accrue concurrently across diverse organs. Finally, we show how gene expression shifts in distinct tissues are highly correlated with corresponding protein levels in plasma, thus potentially contributing to the ageing of the systemic circulation. Together, these data demonstrate a similar yet asynchronous inter- and intra-organ progression of ageing, providing a foundation from which to track systemic sources of declining health at old age.

Serum miRNA improves the accuracy of a multivariate index assay for triage of an adnexal mass.

OBJECTIVE: To determine whether a multimodal assay combining serum microRNA with protein biomarkers and metadata improves triage assessment of an adnexal mass. METHODS: Serum samples from 468 training subjects (191 cancer cases and 277 benign adnexal mass controls or healthy controls) were analyzed for seven protein biomarkers and 180 miRNA. Circulating analyte data were combined with age and menopausal status (metadata) into a neural network model to classify samples as cases or controls. Forward regression with ten-fold cross-validation minimized the dimensionality of the model while maximizing linear separation between cases and controls. Model validation proceeded using both internal (44 cases and 56 controls) and external validation sets (51 cases and 59 controls). RESULTS: The total study population comprised 678 subjects, including 286 cases and 392 controls. Overall, 290 (43%) of the subjects were premenopausal. A panel of 10 miRNA delivered optimal performance when combined with protein and metadata features. The combined model improved the Receiver Operator Characteristic Area Under the Curve (ROC AUC) on the internal (AUC = 0.9; 95% CI 0.81-0.95) and external validation sets (AUC = 0.95; 95% CI 0.90-0.98) compared to miRNA alone or proteins plus metadata (without miRNA). On external validation, the combined model offered 92% sensitivity at 80% specificity overall, with 80% and 100% sensitivity for early and late-stage cancers, respectively, including 78% sensitivity for early-stage, serous ovarian cancers and 82% sensitivity for early-stage, non-serous cancers. CONCLUSIONS: A multimodal assay combining miRNA with protein biomarkers, age, and menopausal status improves surgical triage of an adnexal mass.

Using high-frequency monitoring data to quantify city-wide suspended-sediment load and evaluate TMDL goals.

Excess sediment is a common reason water bodies in the USA become listed as impaired resulting in total maximum daily loads (TMDL) that require municipalities to invest millions of dollars annually on management practices aimed at reducing suspended-sediment loads (SSLs), yet monitoring data are rarely used to quantify SSLs and track TMDL progress. A monitoring network was created to quantify the SSL from the City of Roanoke, Virginia, USA (CoR), to the Roanoke River and Tinker Creek and help guide TMDL assessment and implementation. Suspended-sediment concentrations were estimated between 2020 and 2022 from high-frequency turbidity data using surrogate linear-regression models. Sixty-one percent of the total three-year SSL resulted from five large storm events. The average suspended-sediment yield from the CoR (58.1 metric tons/km2/year) was similar to other urban watersheds in the Eastern United States; however, the yield was nearly five times larger than the TMDL allocation (12.2 metric tons/km2/year). The TMDL allocated load was modeled based on a predominantly forested reference watershed and may not be a practical target for highly impervious watersheds within the CoR. The TMDL model used daily input data which likely does not capture the full range of SSLs during storm events, particularly from flashy urban streams. The average SSL following the five large storm events doubled that of the CoR's annual allocated load from the TMDL. The results of this study highlight the importance of using high-frequency monitoring data to accurately estimate SSLs and evaluate TMDLs in urban areas.

Fast and robust imputation for miRNA expression data using constrained least squares.

BACKGROUND: High dimensional transcriptome profiling, whether through next generation sequencing techniques or high-throughput arrays, may result in scattered variables with missing data. Data imputation is a common strategy to maximize the inclusion of samples by using statistical techniques to fill in missing values. However, many data imputation methods are cumbersome and risk introduction of systematic bias. RESULTS: We present a new data imputation method using constrained least squares and algorithms from the inverse problems literature and present applications for this technique in miRNA expression analysis. The proposed technique is shown to offer an imputation orders of magnitude faster, with greater than or equal accuracy when compared to similar methods from the literature. CONCLUSIONS: This study offers a robust and efficient algorithm for data imputation, which can be used, e.g., to improve cancer prediction accuracy in the presence of missing data.

Compressed sensing two-dimensional Bragg scatter imaging.

Here we introduce a new reconstruction technique for two-dimensional Bragg scattering tomography (BST), based on the Radon transform models of Webber and Miller [Inverse Probl. Imaging15, 683 (2021).10.3934/ipi.2021010]. Our method uses a combination of ideas from multibang control and microlocal analysis to construct an objective function which can regularize the BST artifacts; specifically the boundary artifacts due to sharp cutoff in sinogram space (as observed in [arXiv preprint, arXiv:2007.00208 (2020)]), and artifacts arising from approximations made in constructing the model used for inversion. We then test our algorithm in a variety of Monte Carlo (MC) simulated examples of practical interest in airport baggage screening and threat detection. The data used in our studies is generated with a novel Monte-Carlo code presented here. The model, which is available from the authors upon request, captures both the Bragg scatter effects described by BST as well as beam attenuation and Compton scatter.

Kinome rewiring reveals AURKA limits PI3K-pathway inhibitor efficacy in breast cancer.

Dysregulation of the PI3K-AKT-mTOR signaling network is a prominent feature of breast cancers. However, clinical responses to drugs targeting this pathway have been modest, possibly because of dynamic changes in cellular signaling that drive resistance and limit drug efficacy. Using a quantitative chemoproteomics approach, we mapped kinome dynamics in response to inhibitors of this pathway and identified signaling changes that correlate with drug sensitivity. Maintenance of AURKA after drug treatment was associated with resistance in breast cancer models. Incomplete inhibition of AURKA was a common source of therapy failure, and combinations of PI3K, AKT or mTOR inhibitors with the AURKA inhibitor MLN8237 were highly synergistic and durably suppressed mTOR signaling, resulting in apoptosis and tumor regression in vivo. This signaling map identifies survival factors whose presence limits the efficacy of targeted therapies and reveals new drug combinations that may unlock the full potential of PI3K-AKT-mTOR pathway inhibitors in breast cancer.

An Optimized Chromatographic Strategy for Multiplexing In Parallel Reaction Monitoring Mass Spectrometry: Insights from Quantitation of Activated Kinases.

Reliable quantitation of protein abundances in defined sets of cellular proteins is critical to numerous biological applications. Traditional immunodetection-based methods are limited by the quality and availability of specific antibodies, especially for site-specific post-translational modifications. Targeted proteomic methods, including the recently developed parallel reaction monitoring (PRM) mass spectrometry, have enabled accurate quantitative measurements of up to a few hundred specific target peptides. However, the degree of practical multiplexing in label-free PRM workflows remains a significant limitation for the technique. Here we present a strategy for significantly increasing multiplexing in label-free PRM that takes advantage of the superior separation characteristics and retention time stability of meter-scale monolithic silica-C18 column-based chromatography. We show the utility of the approach in quantifying kinase abundances downstream of previously developed active kinase enrichment methodology based on multidrug inhibitor beads. We examine kinase activation dynamics in response to three different MAP kinase inhibitors in colorectal carcinoma cells and demonstrate reliable quantitation of over 800 target peptides from over 150 kinases in a single label-free PRM run. The kinase activity profiles obtained from these analyses reveal compensatory activation of TGF-ß family receptors as a response to MAPK blockade. The gains achieved using this label-free PRM multiplexing strategy will benefit a wide array of biological applications.

Interpreting cancer genomes using systematic host network perturbations by tumour virus proteins.

Genotypic differences greatly influence susceptibility and resistance to disease. Understanding genotype-phenotype relationships requires that phenotypes be viewed as manifestations of network properties, rather than simply as the result of individual genomic variations. Genome sequencing efforts have identified numerous germline mutations, and large numbers of somatic genomic alterations, associated with a predisposition to cancer. However, it remains difficult to distinguish background, or 'passenger', cancer mutations from causal, or 'driver', mutations in these data sets. Human viruses intrinsically depend on their host cell during the course of infection and can elicit pathological phenotypes similar to those arising from mutations. Here we test the hypothesis that genomic variations and tumour viruses may cause cancer through related mechanisms, by systematically examining host interactome and transcriptome network perturbations caused by DNA tumour virus proteins. The resulting integrated viral perturbation data reflects rewiring of the host cell networks, and highlights pathways, such as Notch signalling and apoptosis, that go awry in cancer. We show that systematic analyses of host targets of viral proteins can identify cancer genes with a success rate on a par with their identification through functional genomics and large-scale cataloguing of tumour mutations. Together, these complementary approaches increase the specificity of cancer gene identification. Combining systems-level studies of pathogen-encoded gene products with genomic approaches will facilitate the prioritization of cancer-causing driver genes to advance the understanding of the genetic basis of human cancer.

Rapid surface water intervention performance comparison for urban planning.

Surface water flooding can be a significant source of damage and disruption in urban areas. The complexity of urban surfaces, the need for spatially disaggregated approaches and the multiplicity of interventions makes management challenging from a number of perspectives. This research responds to the challenge of selecting appropriate surface water management interventions by applying a fast assessment framework to generate evidence for comparing strategies at low resource cost during initial design. This is demonstrated by simulating flood dynamics and comparing damage costs in 144 flood scenarios. The main finding of this work is that a high-level quantitative assessment of large numbers of scenarios is capable of providing evidence to identify performance trends and consider resilience to extreme events at an early stage of planning.

An examination of MCE filter morphology and implications on preparation and analysis of air samples for asbestos.

Morphological imperfections of mixed-cellulose ester filters and their possible influence on sample preparation and analysis of asbestos were examined. Filters were identified with large regions of non-porous "dead zones" which could negatively affect fiber deposition and, therefore, fiber recovery and analysis by Transmission Electron Microscopy (TEM). As these imperfections are effectively erased during the preparation of the sample, they may not be readily observed by TEM. Un-collapsed filters as well as those collapsed using dimethylformamide (DMF) and two acetone techniques were examined. In order to minimize negative sampling and analytical bias, it is suggested that MCE samples be collapsed utilizing a 35% DMF solution, etched with a correctly calibrated low-temperature etcher, carbon coated using a rotating and tilted stage, and analyzed with a strong analyst-independent grid square opening randomization scheme.

The role of plantigrady and heel-strike in the mechanics and energetics of human walking with implications for the evolution of the human foot.

Human bipedal locomotion is characterized by a habitual heel-strike (HS) plantigrade gait, yet the significance of walking foot-posture is not well understood. To date, researchers have not fully investigated the costs of non-heel-strike (NHS) walking. Therefore, we examined walking speed, walk-to-run transition speed, estimated locomotor costs (lower limb muscle volume activated during walking), impact transient (rapid increase in ground force at touchdown) and effective limb length (ELL) in subjects (n=14) who walked at self-selected speeds using HS and NHS gaits. HS walking increases ELL compared with NHS walking since the center of pressure translates anteriorly from heel touchdown to toe-off. NHS gaits led to decreased absolute walking speeds (P=0.012) and walk-to-run transition speeds (P=0.0025), and increased estimated locomotor energy costs (P<0.0001) compared with HS gaits. These differences lost significance after using the dynamic similarity hypothesis to account for the effects of foot landing posture on ELL. Thus, reduced locomotor costs and increased maximum walking speeds in HS gaits are linked to the increased ELL compared with NHS gaits. However, HS walking significantly increases impact transient values at all speeds (P<0.0001). These trade-offs may be key to understanding the functional benefits of HS walking. Given the current debate over the locomotor mechanics of early hominins and the range of foot landing postures used by nonhuman apes, we suggest the consistent use of HS gaits provides key locomotor advantages to striding bipeds and may have appeared early in hominin evolution.

An ontogenetic framework linking locomotion and trabecular bone architecture with applications for reconstructing hominin life history.

The ontogeny of bipedal walking is considered uniquely challenging, due in part to the balance requirements of single limb support. Thus, locomotor development in humans and our bipedal ancestors may track developmental milestones including the maturation of the neuromuscular control system. Here, we examined the ontogeny of locomotor mechanics in children aged 1-8, and bone growth and development in an age-matched skeletal sample to identify bony markers of locomotor development. We show that step-to-step variation in mediolateral tibia angle relative to the vertical decreases with age, an indication that older children increase stability. Analyses of trabecular bone architecture in the distal tibia of an age-matched skeletal sample (the Norris Farms #36 archaeological skeletal collection) show a bony signal of this shift in locomotor stability. Using a grid of eleven cubic volumes of interest (VOI) in the distal metaphysis of each tibia, we show that the degree of anisotropy (DA) of trabecular struts changes with age. Intra-individual variation in DA across these VOIs is generally high at young ages, likely reflecting variation in loading due to kinematic instability. With increasing age, mean DA converges on higher values and becomes less variable across the distal tibia. We believe the ontogeny of distal tibia trabecular architecture reflects the development of locomotor stability in bipeds. We suggest this novel bony marker of development may be used to assess the relationship between locomotor development and other life history milestones in fossil hominins.

C/EBPα and DEK coordinately regulate myeloid differentiation.

The transcription factor C/EBPα is a critical mediator of myeloid differentiation and is often functionally impaired in acute myeloid leukemia. Recent studies have suggested that oncogenic FLT3 activity disrupts wild-type C/EBPα function via phosphorylation on serine 21 (S21). Despite the apparent role of pS21 as a negative regulator of C/EBPα transcription activity, the mechanism by which phosphorylation tips the balance between transcriptionally competent and inhibited forms remains unresolved. In the present study, we used immuno-affinity purification combined with quantitative mass spectrometry to delineate the proteins associated with C/EBPα on chromatin. We identified DEK, a protein with genetic links to leukemia, as a member of the C/EBPα complexes, and demonstrate that this association is disrupted by S21 phosphorylation. We confirmed that DEK is recruited specifically to chromatin with C/EBPα to enhance GCSFR3 promoter activation. In addition, we demonstrated that genetic depletion of DEK reduces the ability of C/EBPα to drive the expression of granulocytic target genes in vitro and disrupts G-CSF-mediated granulocytic differentiation of fresh human BM-derived CD34(+) cells. Our data suggest that C/EBPα and DEK coordinately activate myeloid gene expression and that S21 phosphorylation on wild-type C/EBPα mediates protein interactions that regulate the differentiation capacity of hematopoietic progenitors.

Global perspectives on groundwater infiltration to sewer networks: A threat to urban sustainability.

While existing studies on sewer networks have explored topics such as surface water inflow, limited research has delved into groundwater infiltration (GWI). This study aims to fill this void by providing a comprehensive overview of quantitative analyses of GWI in sewer networks plus current status, limitations and future perspectives, considering the most relevant peer-reviewed research, including 83 studies. We propose dividing the existing research into two main groups: (1) phreatic zone, and (2) vadose zone. Most research has focused on the latter, mainly considering Rainfall-Derived Inflow and Infiltration (RDII), including surface water inflow and GWI. The ratio of each is not frequently separated; otherwise, there may be some assumptions, e.g. in dry weather and assuming zero surface water inflow. We also divided the employed approaches in different categories from physically-based numerical models, to simpler ones, e.g. water budget analysis. In fact, a combination of approaches may be applied to find the intricate characteristics of 'urban groundwater' or 'urban karst.' The findings revealed a heightened vulnerability of sewer networks to GWI, due to climate change (CC) and its associated repercussions, e.g. sea level rise (SLR), making the coastal cities the most vulnerable regions. In future research, the criticality of pre-emptive measures and monitoring of networks, especially near the coastline, is emphasised to ensure the resilience and adaptability of sewer networks in the context of GWI amid the potential impacts of CC. However, current monitoring practices lack widespread evidence for spatiotemporal analysis of GWI quantity.

Effects of clinical covariates on serum miRNA expression among women without ovarian cancer.

BACKGROUND: Serum microRNAs (miRNAs) are potential biomarkers for ovarian cancer; however, many factors may influence miRNA expression. To understand potential confounders in miRNA analysis, we examined how sociodemographic factors and comorbidities, including known ovarian cancer risk factors, influence serum miRNA levels in women without ovarian cancer. METHODS: Data from 1,576 women from the Mass General Brigham Biobank collected between 2012 and 2019, excluding subjects previously or subsequently diagnosed with ovarian cancer, were examined. Using a focused panel of 179 miRNA probes optimized for serum profiling, miRNA expression was measured by flow cytometry using the Abcam Fireplex® assay and correlated with subjects' electronic medical records. RESULTS: The study population broadly reflected the New England population. The median age of subjects was 49 years, 34% were current or prior smokers, 33% were obese (BMI >30kg/m2), 49% were postmenopausal, and 11% had undergone prior bilateral oophorectomy. Significant differences in miRNA expression were observed among ovarian risk factors such as age, obesity, menopause, BRCA1 or BRCA2 germline mutations or breast cancer in family history. Additionally, miRNA expression was significantly altered by prior bilateral oophorectomy, hypertension, and hypercholesterolemia. Other variables, such as smoking, parity, age at menarche, hormonal replacement therapy, oral contraception, breast, endometrial, or colon cancer, and diabetes were not associated with significant changes in the panel when corrected for multiple testing. CONCLUSIONS: Serum miRNA expression patterns are significantly affected by patient demographics, exposure history, and medical comorbidities. IMPACT: Understanding confounders in serum miRNA expression is important for refining clinical assays for cancer screening.

Differences in Serum miRNA Profiles by Race, Ethnicity, and Socioeconomic Status: Implications for Developing an Equitable Ovarian Cancer Screening Test.

Serum miRNAs are promising biomarkers for several clinical conditions, including ovarian cancer. To inform equitable implementation of these tests, we investigated the effects of race, ethnicity, and socioeconomic status on serum miRNA profiles. Serum samples from a large institutional biobank were analyzed using a custom panel of 179 miRNA species highly expressed in human serum, measured using the Abcam Fireplex assay via flow cytometry. Data were log-transformed prior to analysis. Differences in miRNA by race and ethnicity were assessed using logistic regression. Pairwise t tests analyzed racial and ethnic differences among eight miRNAs previously associated with ovarian cancer risk. Pearson correlations determined the relationship between mean miRNA expression and the social deprivation index (SDI) for Massachusetts residents. Of 1,586 patients (76.9% white, non-Hispanic), compared with white, non-Hispanic patients, those from other racial and ethnic groups were younger (41.9 years ± 13.2 vs. 51.3 ± 15.1, P < 0.01) and had fewer comorbidities (3.5 comorbidities ± 2.7 vs. 4.6 ± 2.8, P < 0.01). On logistic regression, miRNAs predicted race and ethnicity at an AUC of 0.69 (95% confidence interval, 0.66-0.72), which remained consistent when stratified by most comorbidities. Among eight miRNAs previously associated with ovarian cancer risk, seven significantly varied by race and ethnicity (all P < 0.01). There were no significant differences in SDI for any of these eight miRNAs. miRNA expression is significantly influenced by race and ethnicity, which remained consistent after controlling for confounders. Understanding baseline differences in biomarker test characteristics prior to clinical implementation is essential to ensure instruments perform comparably across diverse populations. PREVENTION RELEVANCE: This study aimed to understand factors affecting miRNA expression, to ensure we create equitable screening tests for ovarian cancer that perform well in diverse populations. The goal is to ensure that we are detecting ovarian cancer cases earlier (secondary prevention) in women of all races, ethnic backgrounds, and socioeconomic means.

Library dependent LC-MS/MS acquisition via mzAPI/Live.

The use of MS for characterization of small molecules, nucleotides, and proteins in model organisms as well as primary tissues and clinical samples continues to proliferate at a rapid pace. The complexity and dynamic range of target analytes in biological systems hinders comprehensive analysis and simultaneously drives improvements in instrument hardware and software. As a result, state-of-the-art commercial mass spectrometers are equipped with sophisticated embedded control systems that provide robust acquisition methods accessed through intuitive graphical interfaces. Although optimized for speed, these preconfigured scan functions are otherwise closed to end-user customization beyond simple, analytical-centric parameters supplied by the manufacturer. Here, we present an open-source framework (mzAPI/Live) that enables users to generate arbitrarily complex LC-MS(n) acquisition methods via simple Python scripting. As a powerful proof-of-concept, we demonstrate real-time assignment of tandem mass spectra through rapid query of NIST peptide libraries. This represents an unprecedented capability to make acquisition decisions based on knowledge of analyte structures determined during the run itself, thus providing a path toward biology-driven MS data acquisition for the broader community.