In search of induction and latency periods: Space-time interaction accounting for residential mobility, risk factors and covariates

<p>Abstract</p> <p>Background</p> <p>Space-time interaction arises when nearby cases occur at about the same time, and may be attributable to an infectious etiology or from exposures that cause a geographically localized increase in risk. But available techniques for detecting interaction do not account for residential mobility, nor do they evaluate sensitivity to induction and latency periods. This is an important problem for cancer, where latencies of a decade or more occur.</p> <p>Methods</p> <p>New case-only clustering techniques are developed that account for residential mobility, latency and induction periods, relevant covariates (such as age) and risk factors (such as smoking). The statistical behavior of the methods is evaluated using simulated data to assess type I error (false positives) and statistical power. These methods are applied to 374 cases from an ongoing study of bladder cancer in 11 counties in southeastern Michigan, and the ability of the methods to localize space-time interaction at the individual-level is demonstrated.</p> <p>Results</p> <p>Significant interaction is found for induction periods of ~5 years and latency ~19.5 years. Data are still being collected and the observed clusters may be attributable to differential sampling in the study area.</p> <p>Conclusion</p> <p>Residential histories are increasingly available, raising the possibility of routine surveillance in a manner that accounts for individual mobility and that incorporates models of cancer latency and induction. These new techniques provide a mechanism for identifying those geographic locations and times associated with increases in cancer risk <it>above and beyond </it>that expected given covariates and risk factors in geographically mobile populations.</p

Case-control geographic clustering for residential histories accounting for risk factors and covariates

BACKGROUND: Methods for analyzing space-time variation in risk in case-control studies typically ignore residential mobility. We develop an approach for analyzing case-control data for mobile individuals and apply it to study bladder cancer in 11 counties in southeastern Michigan. At this time data collection is incomplete and no inferences should be drawn – we analyze these data to demonstrate the novel methods. Global, local and focused clustering of residential histories for 219 cases and 437 controls is quantified using time-dependent nearest neighbor relationships. Business address histories for 268 industries that release known or suspected bladder cancer carcinogens are analyzed. A logistic model accounting for smoking, gender, age, race and education specifies the probability of being a case, and is incorporated into the cluster randomization procedures. Sensitivity of clustering to definition of the proximity metric is assessed for 1 to 75 k nearest neighbors. RESULTS: Global clustering is partly explained by the covariates but remains statistically significant at 12 of the 14 levels of k considered. After accounting for the covariates 26 Local clusters are found in Lapeer, Ingham, Oakland and Jackson counties, with the clusters in Ingham and Oakland counties appearing in 1950 and persisting to the present. Statistically significant focused clusters are found about the business address histories of 22 industries located in Oakland (19 clusters), Ingham (2) and Jackson (1) counties. Clusters in central and southeastern Oakland County appear in the 1930's and persist to the present day. CONCLUSION: These methods provide a systematic approach for evaluating a series of increasingly realistic alternative hypotheses regarding the sources of excess risk. So long as selection of cases and controls is population-based and not geographically biased, these tools can provide insights into geographic risk factors that were not specifically assessed in the case-control study design

The first trimester human trophoblast cell line ACH-3P: A novel tool to study autocrine/paracrine regulatory loops of human trophoblast subpopulations – TNF-α stimulates MMP15 expression

<p>Abstract</p> <p>Background</p> <p>The trophoblast compartment of the placenta comprises various subpopulations with distinct functions. They interact among each other by secreted signals thus forming autocrine or paracrine regulatory loops. We established a first trimester trophoblast cell line (ACH-3P) by fusion of primary human first trimester trophoblasts (week 12 of gestation) with a human choriocarcinoma cell line (AC1-1).</p> <p>Results</p> <p>Expression of trophoblast markers (cytokeratin-7, integrins, matrix metalloproteinases), invasion abilities and transcriptome of ACH-3P closely resembled primary trophoblasts. Morphology, cytogenetics and doubling time was similar to the parental AC1-1 cells. The different subpopulations of trophoblasts e.g., villous and extravillous trophoblasts also exist in ACH-3P cells and can be immuno-separated by HLA-G surface expression. HLA-G positive ACH-3P display pseudopodia and a stronger expression of extravillous trophoblast markers. Higher expression of insulin-like growth factor II receptor and human chorionic gonadotropin represents the basis for the known autocrine stimulation of extravillous trophoblasts.</p> <p>Conclusion</p> <p>We conclude that ACH-3P represent a tool to investigate interaction of syngeneic trophoblast subpopulations. These cells are particularly suited for studies into autocrine and paracrine regulation of various aspects of trophoblast function. As an example a novel effect of TNF-α on matrix metalloproteinase 15 in HLA-G positive ACH-3P and explants was found.</p

Post-COVID symptoms are associated with endotypes reflecting poor inflammatory and hemostatic modulation

IntroductionPersistent symptoms after COVID-19 infection (“long COVID”) negatively affects almost half of COVID-19 survivors. Despite its prevalence, its pathophysiology is poorly understood, with multiple host systems likely affected. Here, we followed patients from hospital to discharge and used a systems-biology approach to identify mechanisms of long COVID.MethodsRNA-seq was performed on whole blood collected early in hospital and 4-12 weeks after discharge from 24 adult COVID-19 patients (10 reported post-COVID symptoms after discharge). Differential gene expression analysis, pathway enrichment, and machine learning methods were used to identify underlying mechanisms for post-COVID symptom development.ResultsCompared to patients with post-COVID symptoms, patients without post-COVID symptoms had larger temporal gene expression changes associated with downregulation of inflammatory and coagulation genes over time. Patients could also be separated into three patient endotypes with differing mechanistic trajectories, which was validated in another published patient cohort. The “Resolved” endotype (lowest rate of post-COVID symptoms) had robust inflammatory and hemostatic responses in hospital that resolved after discharge. Conversely, the inflammatory/hemostatic responses of “Suppressive” and “Unresolved” endotypes (higher rates of patients with post-COVID symptoms) were persistently dampened and activated, respectively. These endotypes were accurately defined by specific blood gene expression signatures (6-7 genes) for potential clinical stratification.DiscussionThis study allowed analysis of long COVID whole blood transcriptomics trajectories while accounting for the issue of patient heterogeneity. Two of the three identified and externally validated endotypes (“Unresolved” and “Suppressive”) were associated with higher rates of post-COVID symptoms and either persistently activated or suppressed inflammation and coagulation processes. Gene biomarkers in blood could potentially be used clinically to stratify patients into different endotypes, paving the way for personalized long COVID treatment

Sphingolipid Modulation Activates Proteostasis Programs to Govern Human Hematopoietic Stem Cell Self-Renewal.

Cellular stress responses serve as crucial decision points balancing persistence or culling of hematopoietic stem cells (HSCs) for lifelong blood production. Although strong stressors cull HSCs, the linkage between stress programs and self-renewal properties that underlie human HSC maintenance remains unknown, particularly at quiescence exit when HSCs must also dynamically shift metabolic state. Here, we demonstrate distinct wiring of the sphingolipidome across the human hematopoietic hierarchy and find that genetic or pharmacologic modulation of the sphingolipid enzyme DEGS1 regulates lineage differentiation. Inhibition of DEGS1 in hematopoietic stem and progenitor cells during the transition from quiescence to cellular activation with N-(4-hydroxyphenyl) retinamide activates coordinated stress pathways that coalesce on endoplasmic reticulum stress and autophagy programs to maintain immunophenotypic and functional HSCs. Thus, our work identifies a linkage between sphingolipid metabolism, proteostatic quality control systems, and HSC self-renewal and provides therapeutic targets for improving HSC-based cellular therapeutics.E.L. is supported by Wellcome grant 107630/Z/15/Z and a core support grant from the Wellcome and MRC to the Wellcome-Medical Research Council Cambridge Stem Cell Institute. C.L. is supported by U.S. NIH, NCI Grant P01-CA097132. JED is supported by funds from the Princess Margaret Cancer Centre Foundation, Canadian Institutes for Health Research, Joint Canada-Israel Health Research Program, Terry Fox Foundation, and a Canada Research Chair

Modification and preservation of environmental signals in speleothems

Speleothems are primarily studied in order to generate archives of climatic change and results have led to significant advances in identifying and dating major shifts in the climate system. However, the climatological meaning of many speleothem records cannot be interpreted unequivocally; this is particularly so for more subtle shifts and shorter time periods, but the use of multiple proxies and improving understanding of formation mechanisms offers a clear way forward. An explicit description of speleothem records as time series draws attention to the nature and importance of the signal filtering processes by which the weather, the seasons and longer-term climatic and other environmental fluctuations become encoded in speleothems. We distinguish five sources of variation that influence speleothem geochemistry: atmospheric, vegetation/soil, karstic aquifer, primary speleothem crystal growth and secondary alteration and give specific examples of their influence. The direct role of climate diminishes progressively through these five factors. \ud \ud We identify and review a number of processes identified in recent and current work that bear significantly on the conventional interpretation of speleothem records, for example: \ud \ud 1) speleothem geochemistry can vary seasonally and hence a research need is to establish the proportion of growth attributable to different seasons and whether this varies over time. \ud \ud 2) whereas there has traditionally been a focus on monthly mean Ã�´18O data of atmospheric moisture, current work emphasizes the importance of understanding the synoptic processes that lead to characteristic isotope signals, since changing relative abundance of different weather types might 1Corresponding author, fax +44(0)1214145528, E-mail: [email protected] control their variation on the longer-term. \ud \ud 3) the ecosystem and soil zone overlying the cave fundamentally imprint the carbon and trace element signals and can show characteristic variations with time. \ud \ud 4) new modelling on aquifer plumbing allows quantification of the effects of aquifer mixing. \ud \ud 5) recent work has emphasized the importance and seasonal variability of CO2-degassing leading to calcite precipitation upflow of a depositional site on carbon isotope and trace element composition of speleothems. \ud \ud 6) Although much is known about the chemical partitioning between water and stalagmites, variability in relation to crystal growth mechanisms and kinetics is a research frontier. \ud \ud 7) Aragonite is susceptible to conversion to calcite with major loss of chemical information, but the controls on the rate of this process are obscure. \ud \ud Analytical factors are critical to generate high-resolution speleothem records. A variety of methods of trace element analysis are available, but standardization is a common problem with the most rapid methods. New stable isotope data on Irish stalagmite CC3 compares rapid laser-ablation techniques with the conventional analysis of micromilled powders and ion microprobe methods. A high degree of comparability between techniques for Ã�´18O is found on the mm-cm scale, but a previously described high-amplitude oxygen isotope excursion around 8.3 ka is identified as an analytical artefact related to fractionation of the laser-analysis associated with sample cracking. High-frequency variability of not less than 0.5o/oo may be an inherent feature of speleothem Ã�´18O records

Incident Tuberculosis during Antiretroviral Therapy Contributes to Suboptimal Immune Reconstitution in a Large Urban HIV Clinic in Sub-Saharan Africa

Antiretroviral therapy (ART) effectively decreases tuberculosis (TB) incidence long-term, but is associated with high TB incidence rates in the first 6 months. We sought to determine the incidence and the long-term effects of TB during ART on HIV treatment outcome, and the risk factors for incident TB during ART in a large urban HIV clinic in Uganda.Routinely collected longitudinal clinical data from all patients initiated on first-line ART was retrospectively analysed. 5,982 patients were included with a median baseline CD4+ T cell count (CD4 count) of 117 cells/mm(3) (interquartile range [IQR]; 42, 182). In the first 2 years, there were 336 (5.6%) incident TB events in 10,710 person-years (py) of follow-up (3.14 cases/100 pyar [95% CI 2.82-3.49]); incidence rates at 0-3, 3-6, 6-12 and 12-24 months were 11.25 (9.58-13.21), 6.27 (4.99-7.87), 2.47 (1.87-3.36) and 1.02 (0.80-1.31), respectively. Incident TB during ART was independently associated with baseline CD4 count of <50 cells/mm(3) (hazard ratio [HR] 1.84 [1.25-2.70], P = 0.002) and male gender (HR 1.68 [1.34-2.11], P<0.001). After two years on ART, the patients who had developed TB in the first 12 months had a significantly lower median CD4 count increase (184 cells/mm(3) [IQR; 107, 258, n = 118] vs 209 cells/mm(3) [124, 309, n = 2166], P = 0.01), a larger proportion of suboptimal immune reconstitution according to two definitions (increase in CD4 count <200 cells/mm(3): 57.4% vs 46.9%, P = 0.03, and absolute CD4 count <200 cells/mm(3): 30.4 vs 19.9%, P = 0.006), and a higher percentage of immunological failure according to the WHO criteria (13.6% vs 6.5%, P = 0.003). Incident TB during ART was independently associated with poor CD4 count recovery and fulfilling WHO immunological failure definitions.Incident TB during ART occurs most often within 3 months and in patients with CD4 counts less than 50 cells/mm(3). Incident TB during ART is associated with long-term impairment in immune recovery

Global, local and focused geographic clustering for case-control data with residential histories

BACKGROUND: This paper introduces a new approach for evaluating clustering in case-control data that accounts for residential histories. Although many statistics have been proposed for assessing local, focused and global clustering in health outcomes, few, if any, exist for evaluating clusters when individuals are mobile. METHODS: Local, global and focused tests for residential histories are developed based on sets of matrices of nearest neighbor relationships that reflect the changing topology of cases and controls. Exposure traces are defined that account for the latency between exposure and disease manifestation, and that use exposure windows whose duration may vary. Several of the methods so derived are applied to evaluate clustering of residential histories in a case-control study of bladder cancer in south eastern Michigan. These data are still being collected and the analysis is conducted for demonstration purposes only. RESULTS: Statistically significant clustering of residential histories of cases was found but is likely due to delayed reporting of cases by one of the hospitals participating in the study. CONCLUSION: Data with residential histories are preferable when causative exposures and disease latencies occur on a long enough time span that human mobility matters. To analyze such data, methods are needed that take residential histories into account

The History and Prehistory of Natural-Language Semantics

Contemporary natural-language semantics began with the assumption that the meaning of a sentence could be modeled by a single truth condition, or by an entity with a truth-condition. But with the recent explosion of dynamic semantics and pragmatics and of work on non- truth-conditional dimensions of linguistic meaning, we are now in the midst of a shift away from a truth-condition-centric view and toward the idea that a sentence’s meaning must be spelled out in terms of its various roles in conversation. This communicative turn in semantics raises historical questions: Why was truth-conditional semantics dominant in the first place, and why were the phenomena now driving the communicative turn initially ignored or misunderstood by truth-conditional semanticists? I offer a historical answer to both questions. The history of natural-language semantics—springing from the work of Donald Davidson and Richard Montague—began with a methodological toolkit that Frege, Tarski, Carnap, and others had created to better understand artificial languages. For them, the study of linguistic meaning was subservient to other explanatory goals in logic, philosophy, and the foundations of mathematics, and this subservience was reflected in the fact that they idealized away from all aspects of meaning that get in the way of a one-to-one correspondence between sentences and truth-conditions. The truth-conditional beginnings of natural- language semantics are best explained by the fact that, upon turning their attention to the empirical study of natural language, Davidson and Montague adopted the methodological toolkit assembled by Frege, Tarski, and Carnap and, along with it, their idealization away from non-truth-conditional semantic phenomena. But this pivot in explana- tory priorities toward natural language itself rendered the adoption of the truth-conditional idealization inappropriate. Lifting the truth-conditional idealization has forced semanticists to upend the conception of linguistic meaning that was originally embodied in their methodology