Geometry of River Networks II: Distributions of Component Size and Number

The structure of a river network may be seen as a discrete set of nested sub-networks built out of individual stream segments. These network components are assigned an integral stream order via a hierarchical and discrete ordering method. Exponential relationships, known as Horton's laws, between stream order and ensemble-averaged quantities pertaining to network components are observed. We extend these observations to incorporate fluctuations and all higher moments by developing functional relationships between distributions. The relationships determined are drawn from a combination of theoretical analysis, analysis of real river networks including the Mississippi, Amazon and Nile, and numerical simulations on a model of directed, random networks. Underlying distributions of stream segment lengths are identified as exponential. Combinations of these distributions form single-humped distributions with exponential tails, the sums of which are in turn shown to give power law distributions of stream lengths. Distributions of basin area and stream segment frequency are also addressed. The calculations identify a single length-scale as a measure of size fluctuations in network components. This article is the second in a series of three addressing the geometry of river networks.Comment: 16 pages, 13 figures, 4 tables, Revtex4, submitted to PR

Epidemiología molecular de Bartonella henselae en gatos callejeros y de albergue en Zaragoza, España

Fundamentos: Bartonella henselae produce la enfermedad del araña- zo del gato en las personas y se considera infradiagnosticada. El objetivo fue detectar y cuantificar la carga de ácido desoxiribonucleico (ADN) de B. henselae en muestras de sangre y orales de gatos callejeros y de albergue de Zaragoza, España y analizar su relación con factores epidemiológicos y clínicos. Métodos: Se estudiaron 47 gatos. El ADN de B. henselae,se detectó mediante reacción en cadena de la polimerasa en tiempo real (qPCR) en sangre y muestras orales. Se usó el paquete estadístico SPSS para analizar la positividad de las muestras pareadas y su relación con factores epidemioló- gicos (edad, sexo, origen, mes de muestreo, presencia de pulgas/garrapatas) y clínicos (estado de salud y presencia de lesiones orales). Se realizó un análisis de regresión logística para conocer la asociación entre la presencia en sangre y cavidad oral y el resto de las variables. Resultados: el 23,40% de las muestras de sangre y el 27,65% de las orales portaba el ADN de B. henselae. Se observó débil correlación de la positividad de las muestras pareadas (kappa= 0,33; p 0,05) entre la presencia de ADN de B. henselae en las muestras y los factores epidemiológicos y clínicos. Los gatos con lesiones orales portaban una carga más elevada de ADN (3,12/1x106 células) en la boca que los que no tenían lesiones (2,58 /1por106 células), (p=0,032). Conclusiones: La detección de ADN de B. henselae en sangre no pare- ce estar relacionada con su presencia en cavidad oral y viceversa. Los gatos positivos con lesiones orales pueden significar mayor riesgo de infección por B. henselae para las personas que los manejan

Extension of Murray's law using a non-Newtonian model of blood flow

<p>Abstract</p> <p>Background</p> <p>So far, none of the existing methods on Murray's law deal with the non-Newtonian behavior of blood flow although the non-Newtonian approach for blood flow modelling looks more accurate.</p> <p>Modeling</p> <p>In the present paper, Murray's law which is applicable to an arterial bifurcation, is generalized to a non-Newtonian blood flow model (power-law model). When the vessel size reaches the capillary limitation, blood can be modeled using a non-Newtonian constitutive equation. It is assumed two different constraints in addition to the pumping power: the volume constraint or the surface constraint (related to the internal surface of the vessel). For a seek of generality, the relationships are given for an arbitrary number of daughter vessels. It is shown that for a cost function including the volume constraint, classical Murray's law remains valid (i.e. Σ<it>R</it>^{<it>c </it>}= <it>cste </it>with <it>c </it>= 3 is verified and is independent of <it>n</it>, the dimensionless index in the viscosity equation; <it>R </it>being the radius of the vessel). On the contrary, for a cost function including the surface constraint, different values of <it>c </it>may be calculated depending on the value of <it>n</it>.</p> <p>Results</p> <p>We find that <it>c </it>varies for blood from 2.42 to 3 depending on the constraint and the fluid properties. For the Newtonian model, the surface constraint leads to <it>c </it>= 2.5. The cost function (based on the surface constraint) can be related to entropy generation, by dividing it by the temperature.</p> <p>Conclusion</p> <p>It is demonstrated that the entropy generated in all the daughter vessels is greater than the entropy generated in the parent vessel. Furthermore, it is shown that the difference of entropy generation between the parent and daughter vessels is smaller for a non-Newtonian fluid than for a Newtonian fluid.</p

The AIQ Meta-Testbed: Pragmatically Bridging Academic AI Testing and Industrial Q Needs

AI solutions seem to appear in any and all application domains. As AI becomes more pervasive, the importance of quality assurance increases. Unfortunately, there is no consensus on what artificial intelligence means and interpretations range from simple statistical analysis to sentient humanoid robots. On top of that, quality is a notoriously hard concept to pinpoint. What does this mean for AI quality? In this paper, we share our working definition and a pragmatic approach to address the corresponding quality assurance with a focus on testing. Finally, we present our ongoing work on establishing the AIQ Meta-Testbed.Comment: Accepted for publication in the Proc. of the Software Quality Days 2021, Vienna, Austri

Patogenicidade de metarhizium anisopliae sobre o carrapato Rhipicephalus (Boophilus) Microplus (Canestrini, 1887) (Acari: Ixodidae) in vitro.

Publicação origem em CD

Quantification of fractional flow reserve based on angiographic image data

Coronary angiography provides excellent visualization of coronary arteries, but has limitations in assessing the clinical significance of a coronary stenosis. Fractional flow reserve (FFR) has been shown to be reliable in discerning stenoses responsible for inducible ischemia. The purpose of this study is to validate a technique for FFR quantification using angiographic image data. The study was carried out on 10 anesthetized, closed-chest swine using angioplasty balloon catheters to produce partial occlusion. Angiography based FFR was calculated from an angiographically measured ratio of coronary blood flow to arterial lumen volume. Pressure-based FFR was measured from a ratio of distal coronary pressure to aortic pressure. Pressure-wire measurements of FFR (FFRP) correlated linearly with angiographic volume-derived measurements of FFR (FFRV) according to the equation: FFRP = 0.41 FFRV + 0.52 (P-value < 0.001). The correlation coefficient and standard error of estimate were 0.85 and 0.07, respectively. This is the first study to provide an angiographic method to quantify FFR in swine. Angiographic FFR can potentially provide an assessment of the physiological severity of a coronary stenosis during routine diagnostic cardiac catheterization without a need to cross a stenosis with a pressure-wire

Central nervous system immune interactome is a function of cancer lineage, tumor microenvironment, and STAT3 expression.

BACKGROUNDImmune cell profiling of primary and metastatic CNS tumors has been focused on the tumor, not the tumor microenvironment (TME), or has been analyzed via biopsies.METHODSEn bloc resections of gliomas (n = 10) and lung metastases (n = 10) were analyzed via tissue segmentation and high-dimension Opal 7-color multiplex imaging. Single-cell RNA analyses were used to infer immune cell functionality.RESULTSWithin gliomas, T cells were localized in the infiltrating edge and perivascular space of tumors, while residing mostly in the stroma of metastatic tumors. CD163+ macrophages were evident throughout the TME of metastatic tumors, whereas in gliomas, CD68+, CD11c+CD68+, and CD11c+CD68+CD163+ cell subtypes were commonly observed. In lung metastases, T cells interacted with CD163+ macrophages as dyads and clusters at the brain-tumor interface and within the tumor itself and as clusters within the necrotic core. In contrast, gliomas typically lacked dyad and cluster interactions, except for T cell CD68+ cell dyads within the tumor. Analysis of transcriptomic data in glioblastomas revealed that innate immune cells expressed both proinflammatory and immunosuppressive gene signatures.CONCLUSIONOur results show that immunosuppressive macrophages are abundant within the TME and that the immune cell interactome between cancer lineages is distinct. Further, these data provide information for evaluating the role of different immune cell populations in brain tumor growth and therapeutic responses.FUNDINGThis study was supported by the NIH (NS120547), a Developmental research project award (P50CA221747), ReMission Alliance, institutional funding from Northwestern University and the Lurie Comprehensive Cancer Center, and gifts from the Mosky family and Perry McKay. Performed in the Flow Cytometry & Cellular Imaging Core Facility at MD Anderson Cancer Center, this study received support in part from the NIH (CA016672) and the National Cancer Institute (NCI) Research Specialist award 1 (R50 CA243707). Additional support was provided by CCSG Bioinformatics Shared Resource 5 (P30 CA046592), a gift from Agilent Technologies, a Research Scholar Grant from the American Cancer Society (RSG-16-005-01), a Precision Health Investigator Award from University of Michigan (U-M) Precision Health, the NCI (R37-CA214955), startup institutional research funds from U-M, and a Biomedical Informatics & Data Science Training Grant (T32GM141746)