Redefining Cardiac Biomarkers in Predicting Mortality of Inpatients With COVID-19

The prognostic power of circulating cardiac biomarkers, their utility, and pattern of release in coronavirus disease 2019 (COVID-19) patients have not been clearly defined. In this multicentered retrospective study, we enrolled 3219 patients with diagnosed COVID-19 admitted to 9 hospitals from December 31, 2019 to March 4, 2020, to estimate the associations and prognostic power of circulating cardiac injury markers with the poor outcomes of COVID-19. In the mixed-effects Cox model, after adjusting for age, sex, and comorbidities, the adjusted hazard ratio of 28-day mortality for hs-cTnI (high-sensitivity cardiac troponin I) was 7.12 ([95% CI, 4.60-11.03] P\u3c0.001), (NT-pro)BNP (N-terminal pro-B-type natriuretic peptide or brain natriuretic peptide) was 5.11 ([95% CI, 3.50-7.47] P\u3c0.001), CK (creatine phosphokinase)-MB was 4.86 ([95% CI, 3.33-7.09] P\u3c0.001), MYO (myoglobin) was 4.50 ([95% CI, 3.18-6.36] P\u3c0.001), and CK was 3.56 ([95% CI, 2.53-5.02] P\u3c0.001). The cutoffs of those cardiac biomarkers for effective prognosis of 28-day mortality of COVID-19 were found to be much lower than for regular heart disease at about 19%-50% of the currently recommended thresholds. Patients with elevated cardiac injury markers above the newly established cutoffs were associated with significantly increased risk of COVID-19 death. In conclusion, cardiac biomarker elevations are significantly associated with 28-day death in patients with COVID-19. The prognostic cutoff values of these biomarkers might be much lower than the current reference standards. These findings can assist in better management of COVID-19 patients to improve outcomes. Importantly, the newly established cutoff levels of COVID-19-associated cardiac biomarkers may serve as useful criteria for the future prospective studies and clinical trials

Redefining cardiac biomarkers in predicting mortality and adverse outcomes of inpatients with COVID-19

The prognostic power of circulating cardiac biomarkers, their utility and pattern of release in coronavirus disease 2019 (COVID-19) patients have not been clearly defined. In this multi-centered retrospective study, we enrolled 3,219 patients with diagnosed COVID-19 admitted to 9 hospitals from December 31, 2019 to March 4, 2020, to estimate the associations and prognostic power of circulating cardiac injury markers with the poor outcomes of COVID-19. In the mixed-effect Cox model, after adjusting for age, gender and comorbidities, the adjusted hazard ratios of 28-day mortality for high-sensitivity cardiac troponin I (hs-cTnI) was 7.12 (95%CI, 4.60-11.03; P<0.001), NT-proB-type natriuretic peptide (NT-proBNP) was 5.11 (95%CI, 3.50-7.47; P<0.001), CK-MB was 4.86 (95%CI, 3.33-7.09; P<0.001), myoglobin was 4.50 (95%CI, 3.18-6.36; P < 0.001), and CK was 3.56 (95%CI, 2.53-5.02; P < 0.001). The cutoffs of those cardiac biomarkers for effective prognosis of 28-day mortality of COVID-19 were found to be much lower than for regular heart disease at about 49% of the currently recommended thresholds. Patients with elevated cardiac injury markers above the newly established cutoffs were associated with significantly increased risk of COVID-19 death. In conclusion, cardiac biomarker elevations are significantly associated with 28-day death in patients with COVID-19. The prognostic cutoffs for of these values might be much lower than the current reference standards. These findings can assist better management of COVID-19 patients to improve outcomes. Importantly, the newly established cutoff levels of COVID-19 associated cardiac biomarkers may serve as useful criteria for the future prospective studies and clinical trials

Morphological diversity of single neurons in molecularly defined cell types.

Dendritic and axonal morphology reflects the input and output of neurons and is a defining feature of neuronal types1,2, yet our knowledge of its diversity remains limited. Here, to systematically examine complete single-neuron morphologies on a brain-wide scale, we established a pipeline encompassing sparse labelling, whole-brain imaging, reconstruction, registration and analysis. We fully reconstructed 1,741 neurons from cortex, claustrum, thalamus, striatum and other brain regions in mice. We identified 11 major projection neuron types with distinct morphological features and corresponding transcriptomic identities. Extensive projectional diversity was found within each of these major types, on the basis of which some types were clustered into more refined subtypes. This diversity follows a set of generalizable principles that govern long-range axonal projections at different levels, including molecular correspondence, divergent or convergent projection, axon termination pattern, regional specificity, topography, and individual cell variability. Although clear concordance with transcriptomic profiles is evident at the level of major projection type, fine-grained morphological diversity often does not readily correlate with transcriptomic subtypes derived from unsupervised clustering, highlighting the need for single-cell cross-modality studies. Overall, our study demonstrates the crucial need for quantitative description of complete single-cell anatomy in cell-type classification, as single-cell morphological diversity reveals a plethora of ways in which different cell types and their individual members may contribute to the configuration and function of their respective circuits

Comparative cellular analysis of motor cortex in human, marmoset and mouse

The primary motor cortex (M1) is essential for voluntary fine-motor control and is functionally conserved across mammals1. Here, using high-throughput transcriptomic and epigenomic profiling of more than 450,000 single nuclei in humans, marmoset monkeys and mice, we demonstrate a broadly conserved cellular makeup of this region, with similarities that mirror evolutionary distance and are consistent between the transcriptome and epigenome. The core conserved molecular identities of neuronal and non-neuronal cell types allow us to generate a cross-species consensus classification of cell types, and to infer conserved properties of cell types across species. Despite the overall conservation, however, many species-dependent specializations are apparent, including differences in cell-type proportions, gene expression, DNA methylation and chromatin state. Few cell-type marker genes are conserved across species, revealing a short list of candidate genes and regulatory mechanisms that are responsible for conserved features of homologous cell types, such as the GABAergic chandelier cells. This consensus transcriptomic classification allows us to use patch-seq (a combination of whole-cell patch-clamp recordings, RNA sequencing and morphological characterization) to identify corticospinal Betz cells from layer 5 in non-human primates and humans, and to characterize their highly specialized physiology and anatomy. These findings highlight the robust molecular underpinnings of cell-type diversity in M1 across mammals, and point to the genes and regulatory pathways responsible for the functional identity of cell types and their species-specific adaptations

A multimodal cell census and atlas of the mammalian primary motor cortex

ABSTRACT We report the generation of a multimodal cell census and atlas of the mammalian primary motor cortex (MOp or M1) as the initial product of the BRAIN Initiative Cell Census Network (BICCN). This was achieved by coordinated large-scale analyses of single-cell transcriptomes, chromatin accessibility, DNA methylomes, spatially resolved single-cell transcriptomes, morphological and electrophysiological properties, and cellular resolution input-output mapping, integrated through cross-modal computational analysis. Together, our results advance the collective knowledge and understanding of brain cell type organization: First, our study reveals a unified molecular genetic landscape of cortical cell types that congruently integrates their transcriptome, open chromatin and DNA methylation maps. Second, cross-species analysis achieves a unified taxonomy of transcriptomic types and their hierarchical organization that are conserved from mouse to marmoset and human. Third, cross-modal analysis provides compelling evidence for the epigenomic, transcriptomic, and gene regulatory basis of neuronal phenotypes such as their physiological and anatomical properties, demonstrating the biological validity and genomic underpinning of neuron types and subtypes. Fourth, in situ single-cell transcriptomics provides a spatially-resolved cell type atlas of the motor cortex. Fifth, integrated transcriptomic, epigenomic and anatomical analyses reveal the correspondence between neural circuits and transcriptomic cell types. We further present an extensive genetic toolset for targeting and fate mapping glutamatergic projection neuron types toward linking their developmental trajectory to their circuit function. Together, our results establish a unified and mechanistic framework of neuronal cell type organization that integrates multi-layered molecular genetic and spatial information with multi-faceted phenotypic properties

A mathematical model for container port integrated scheduling and optimization problem

International audienceTraditionally, container terminal optimizations are excused separately and sequentially. As the seaside and landside operations interact intensively, the sequential planning approaches often hinder obtaining sufficient resource utilization, especially for transshipment hubs. Facing the challenge of simultaneous optimization of berth allocation, quay crane assignment and yard allocation, this paper makes an attempt to remedy the situation of sub-optimizations made by different agents, by devising a comprehensive mathematical model, with the aim of benefiting port operators. Regarding that some transit containers typically require temporary yard stowage, the effect of yard stowage allocation, a major factor to the port operational cost, is elaborated in the paper. The main contribution of this work is the presentation of a compact mixed integer linear programming model

The evolution of cooperation on fragmented landscapes: the spatial Hamilton rule

Question: How does habitat destruction affect the evolution of cooperation? Methods: Differential equations of the probabilities for different states in pairwise sites based on the Prisoner’s Dilemma game in a regular network. Key assumptions: Individuals play the Prisoner’s Dilemma game with other individuals on directly connected (adjacent) sites. Individuals’ average payoff affects the birth rate. The population undergoes a birth–death process. Habitat loss and fragmentation in the network affect the population dynamics and the invasion and persistence of cooperation. Predictions: (1) The evolution of cooperation is made possible through non-random encounters in a spatially local process. (2) Derive a spatial Hamilton rule whereby the proportion of cooperators among the neighbouring individuals of a cooperator serves the same role of relatedness as in kin selection, which is consistent with other forms of Hamilton rules. (3) The evolution of cooperation becomes easier in harsh environments. (4) The co-existence of multiple strategies in a species can maintain population size at a constant level.We are grateful to Yoh Iwasa, Jeffrey Fletcher, Tadeusz Platkowski, Weini Huang, and Marius-Ionut Ochea for helpful discussion of this work during the 2009 IIASA Conference on the ‘Evolution of Cooperation: Models and Theories’. This work was supported by the National Basic Research Program (973 Program) (#2007CB109107), the NRF Blue Skies Research Programme, and the DST-NRF Centre of Excellence for Invasion Biology at Stellenbosch University

A polynomial-time heuristic for the quay crane double-cycling problem with internal-reshuffling operations

International audienceOne of great challenges in seaport management is how to handle containers under reshuffling, called reshuffles. Repositioning reshuffles in a bay (internal reshuffling) can improve the efficiency of quay cranes and help ports to reduce ship turn-around time. This paper studies the quay crane double-cycling problem with internal-reshuffling operations, and presents a fast solution algorithm. To reduce the number of operations necessary to turn around a bay of a vessel, the problem is first formulated as a new integer program. A polynomial-time heuristic is then developed. The analysis is made on the worst-case error bound of the proposed algorithm. Results are presented for a suite of combinations of problem instances with different bay sizes and workload scenarios. Comparisons are made between our algorithm and the start-of-the-art heuristic. The computational results demonstrate that our model can be solved more efficiently with CPLEX than the model proposed by Meisel and Wichmann (2010), and the proposed algorithm can well solve real-world problem instances within several seconds