Stem cells and fluid flow drive cyst formation in an invertebrate excretory organ.

Cystic kidney diseases (CKDs) affect millions of people worldwide. The defining pathological features are fluid-filled cysts developing from nephric tubules due to defective flow sensing, cell proliferation and differentiation. The underlying molecular mechanisms, however, remain poorly understood, and the derived excretory systems of established invertebrate models (Caenorhabditis elegans and Drosophila melanogaster) are unsuitable to model CKDs. Systematic structure/function comparisons revealed that the combination of ultrafiltration and flow-associated filtrate modification that is central to CKD etiology is remarkably conserved between the planarian excretory system and the vertebrate nephron. Consistently, both RNA-mediated genetic interference (RNAi) of planarian orthologues of human CKD genes and inhibition of tubule flow led to tubular cystogenesis that share many features with vertebrate CKDs, suggesting deep mechanistic conservation. Our results demonstrate a common evolutionary origin of animal excretory systems and establish planarians as a novel and experimentally accessible invertebrate model for the study of human kidney pathologies

How artificial intelligence and machine learning can help healthcare systems respond to COVID-19

The COVID-19 global pandemic is a threat not only to the health of millions of individuals, but also to the stability of infrastructure and economies around the world. The disease will inevitably place an overwhelming burden on healthcare systems that cannot be effectively dealt with by existing facilities or responses based on conventional approaches. We believe that a rigorous clinical and societal response can only be mounted by using intelligence derived from a variety of data sources to better utilize scarce healthcare resources, provide per- sonalized patient management plans, inform policy, and expedite clinical trials. In this paper, we introduce five of the most important challenges in responding to COVID-19 and show how each of them can be addressed by recent develop- ments in machine learning (ML) and artificial intelligence (AI). We argue that the integration of these techniques into local, national, and international healthcare systems will save lives, and propose specific methods by which implementation can happen swiftly and efficiently. We offer to extend these resources and knowledge to assist policymakers seeking to implement these techniques

Gene expression profiling of CD8+ T cells predicts prognosis in patients with Crohn disease and ulcerative colitis.

Crohn disease (CD) and ulcerative colitis (UC) are increasingly common, chronic forms of inflammatory bowel disease. The behavior of these diseases varies unpredictably among patients. Identification of reliable prognostic biomarkers would enable treatment to be personalized so that patients destined to experience aggressive disease could receive appropriately potent therapies from diagnosis, while those who will experience more indolent disease are not exposed to the risks and side effects of unnecessary immunosuppression. Using transcriptional profiling of circulating T cells isolated from patients with CD and UC, we identified analogous CD8+ T cell transcriptional signatures that divided patients into 2 otherwise indistinguishable subgroups. In both UC and CD, patients in these subgroups subsequently experienced very different disease courses. A substantially higher incidence of frequently relapsing disease was experienced by those patients in the subgroup defined by elevated expression of genes involved in antigen-dependent T cell responses, including signaling initiated by both IL-7 and TCR ligation - pathways previously associated with prognosis in unrelated autoimmune diseases. No equivalent correlation was observed with CD4+ T cell gene expression. This suggests that the course of otherwise distinct autoimmune and inflammatory conditions may be influenced by common pathways and identifies what we believe to be the first biomarker that can predict prognosis in both UC and CD from diagnosis, a major step toward personalized therapy

Spatial temporal patterns in childhood leukaemia: further evidence for an infectious origin. EUROCLUS project.

The EUROCLUS project included information on residence at diagnosis for 13351 cases of childhood leukaemia diagnosed in the period 1980-89 in defined geographical regions in 17 countries. A formal algorithm permits identification of small census areas as containing case excesses. The present analysis examines spatial-temporal patterns of the cases (n = 970) within these clustered areas. The objectives were, first, to compare these results with those from an analysis conducted for UK data for the period 1966-83, and, second, to extend them to consider infant leukaemias. A modification of the Knox test investigates, within the small areas, temporal overlap between cases in a subgroup of interest at a putative critical time and all other cases at any time between birth and diagnosis. Critical times were specified in advance as follows: for cases of acute lymphoblastic leukaemia aged 2-4 years, the 18-month period preceding diagnosis; for cases of total leukaemia aged 5-14 years, 1 year before to 1 year after birth; and for infant cases (diagnosed < 1 year), 1 year before to 6 months after birth. Each of the analyses found evidence of excess space-time overlap compared with that expected; these were 10% (P = 0.005), 15% (P= 0.0002) and 26% (P= 0.03) respectively. The results are interpreted in terms of an infectious origin of childhood leukaemia

Locating positions of {\gamma}-ray--emitting regions in blazars

We propose a new method to locate the gamma-ray--emitting positions R_g from the measured time lags T_ob of gamma-ray emission relative to broad emission lines. The method is also applicable to lower frequencies. R_g depends on parameters T_ob, R_BLR, v_d and theta, where R_BLR is the size of broad-line region, v_d is the travelling speed of disturbances down the jet and theta is the viewing angle of the jet axis to the line of sight. As T_ob=0, T_ob<0 or T_ob>0, the broad lines zero-lag, lag or lead the gamma-rays, respectively. It is applied to 3C 273, in which the lines and the radio emission have enough data, but the gamma-rays have not. We find T_ob0 for the 5, 8, 15, 22 and 37 GHz emission relative to the broad lines Ha, Hb and Hg. The lag may be positive or negative, however current data do not allow to discriminate between the two cases. The measured lags are on the order of years. For a given line, T_ob generally decreases as radio frequency increases. This trend most likely results from the radiative cooling of relativistic electrons. The negative lags have an average of T_ob=-2.86 years for the 37 GHz emission, which represents that the lines lag the radio emission. The positive lags have T_ob=3.20 years, which represents that the lines lead the radio emission. We obtain the radio emitting positions R_radio=0.40--2.62 pc and R_radio=9.43--62.31 pc for the negative and positive lags, respectively. From the constraint of R_g </~ R_radio (e.g. Dermer & Schlickeiser 1994; Jorstad et al. 2001), we have R_g </~ 0.40--2.62 pc for the negative lags. For the positive lags, 4.67--30.81<R_g </~ 9.43--62.31 pc. These estimated R_g are consistent with those of other researches. These agreements confirm the reliability of the method and assumptions. The method may be also applicable to BL Lacertae objects, in which broad lines were detected.Comment: 13 pages, 8 figures, MNRAS, acceptanc

Spatial clustering of childhood leukaemia: summary results from the EUROCLUS project.

The interpretation of reports of clusters of childhood leukaemia is difficult, first because little is known about the causes of the disease, and second because there is insufficient information on whether cases show a generalized tendency to cluster geographically. The EUROCLUS project is a European collaborative study whose primary objective is to determine whether the residence locations of cases at diagnosis show a general tendency towards spatial clustering. The second objective is to interpret any patterns observed and, in particular, to see if clustering can be explained in terms of either infectious agents or environmental hazards as aetiological agents. The spatial distribution of 13351 cases of childhood leukaemia diagnosed in 17 countries between 1980 and 1989 has been analysed using the Potthoff-Whittinghill method. The overall results show statistically significant evidence of clustering of total childhood leukaemia within small census areas (P=0.03) but the magnitude of the clustering is small (extra-Poisson component of variance (%) = 1.7 with 90% confidence interval 0.2-3.1). The clustering is most marked in areas that have intermediate population density (150-499 persons km[-2]). It cannot be attributed to any specific age group at diagnosis or cell type and involves spatial aggregation of cases of different ages and cell types. The results indicate that intense clusters are a rare phenomenon that merit careful investigation, although aetiological insights are more likely to come from investigation of large numbers of cases. We present a method for detecting clustering that is simple and readily available to cancer registries and similar groups

An infectious aetiology for childhood brain tumours? Evidence from space–time clustering and seasonality analyses

To investigate whether infections or other environmental exposures may be involved in the aetiology of childhood central nervous system tumours, we have analysed for space–time clustering and seasonality using population-based data from the North West of England for the period 1954 to 1998. Knox tests for space–time interactions between cases were applied with fixed thresholds of close in space, <5 km, and close in time, <1 year apart. Addresses at birth and diagnosis were used. Tests were repeated replacing geographical distance with distance to the Nth nearest neighbour. N was chosen such that the mean distance was 5 km. Data were also examined by a second order procedure based on K-functions. Tests for heterogeneity and Edwards' test for sinusoidal variation were applied to examine changes of incidence with month of birth or diagnosis. There was strong evidence of space–time clustering, particularly involving cases of astrocytoma and ependymoma. Analyses of seasonal variation showed excesses of cases born in the late Autumn or Winter. Results are consistent with a role for infections in a proportion of cases from these diagnostic groups. Further studies are needed to identify putative infectious agents

J/psi suppression at forward rapidity in Au+Au collisions at sqrt(s_NN)=39 and 62.4 GeV

We present measurements of the J/psi invariant yields in sqrt(s_NN)=39 and 62.4 GeV Au+Au collisions at forward rapidity (1.2<|y|<2.2). Invariant yields are presented as a function of both collision centrality and transverse momentum. Nuclear modifications are obtained for central relative to peripheral Au+Au collisions (R_CP) and for various centrality selections in Au+Au relative to scaled p+p cross sections obtained from other measurements (R_AA). The observed suppression patterns at 39 and 62.4 GeV are quite similar to those previously measured at 200 GeV. This similar suppression presents a challenge to theoretical models that contain various competing mechanisms with different energy dependencies, some of which cause suppression and others enhancement.Comment: 365 authors, 10 pages, 11 figures, 4 tables. Submitted to Phys. Rev. C. Plain text data tables for the points plotted in figures for this and previous PHENIX publications are (or will be) publicly available at http://www.phenix.bnl.gov/papers.htm

Childhood solid tumours in relation to population mixing around the time of birth

In a retrospective cohort study of 673 787 live births in the Northern Region of England, 1975 - 1994, we investigated whether a higher level of population mixing around birth was a risk factor for solid tumours, by diagnostic group (Hodgkin's disease, brain and spinal tumours, neuroblastoma, other solid tumours), diagnosed during 1975-2001 under age 15 years. Logistic regression was used to relate risk to population mixing, based on (i) all movers and (ii) incomers from outside the region. Both ward and county district level analyses were performed. There was a decreased risk of brain and spinal tumours with increasing population mixing based on incomers from outside the region (OR for trend across three categories = 0.79, 95% CI: 0.66-0.95, P = 0.01 in the ward level analysis). Although this may be because of chance, it is consistent with a role of exposure to infection and immunological response in the aetiology of these tumours. For other tumour groups, there was no consistent evidence of an association between risk and population mixing