RENAL DEPOSITION OF SOLUBLE IMMUNE COMPLEXES IN MICE BEARING B-16 MELANOMA : CHARACTERIZATION OF COMPLEXES AND RELATIONSHIP TO TUMOR PROGRESS

Histologic and immunofluorescence studies of the kidneys of mice bearing a progressive melanoma show a proliferative glomerulonephritis associated with immune complex deposition in the mesangium and along the glomerular basement membrane This immune complex disease is distinct from the age-associated disease of the C57BL/6J host strain and the complexes can be shown to consist of soluble tumor antigen and antitumor antibody. Furthermore, the intensity of IgG complex deposition correlates directly with tumor progress (size and metastases) and inversely with mononuclear leukocyte infiltration of the tumor. In vitro assays for lymphocyte cytotoxicity and humoral antibody were found to be less reliable indicators of tumor progress. The possible role of circulating soluble tumor antigen in modifying the immune response to tumors is discussed

Optimal bias correction of the log-periodogram estimator of the fractional parameter: a jackknife approach

We use the jackknife to bias correct the log-periodogram regression (LPR) estimator of the fractional parameter in a stationary fractionally integrated model. The weights for the jackknife estimator are chosen in such a way that bias reduction is achieved without the usual increase in asymptotic variance, with the estimator viewed as ‘optimal’ in this sense. The theoretical results are valid under both the non-overlapping and moving-block sub-sampling schemes that can be used in the jackknife technique, and do not require the assumption of Gaussianity for the data generating process. A Monte Carlo study explores the finite sample performance of different versions of the jackknife estimator, under a variety of scenarios. The simulation experiments reveal that when the weights are constructed using the parameter values of the true data generating process, a version of the optimal jackknife estimator almost always out-performs alternative semi-parametric bias-corrected estimators. A feasible version of the jackknife estimator, in which the weights are constructed using estimates of the unknown parameters, whilst not dominant overall, is still the least biased estimator in some cases. Even when misspecified short run dynamics are assumed in the construction of the weights, the feasible jackknife estimator still shows significant reduction in bias under certain designs. As is not surprising, parametric maximum likelihood estimation out-performs all semi-parametric methods when the true values of the short memory parameters are known, but is dominated by the semi-parametric methods (in terms of bias) when the short memory parameters need to be estimated, and in particular when the model is misspecified

Issues in the estimation of mis-specified models of fractionally integrated processes

This short paper provides a comprehensive set of new theoretical results on the impact of mis-specifying the short run dynamics in fractionally integrated processes. We show that four alternative parametric estimators – frequency domain maximum likelihood, Whittle, time domain maximum likelihood and conditional sum of squares – converge to the same pseudo-true value under common mis-specification, and that they possess a common asymptotic distribution. The results are derived assuming the true data generating mechanism is a fractional linear process driven by a martingale difference innovation. A completely general parametric specification for the short run dynamics of the estimated (mis-specified) fractional model is considered, and with long memory, short memory and antipersistence in both the model and the data generating mechanism accommodated. The paper can be seen as extending an existing line of research on mis-specification in fractional models, important contributions to which have appeared in Journal of Econometrics. It also complements a range of existing asymptotic results on estimation in correctly specified fractional models. Open problems in the area are the subject of the final discussion

Tract-Based Spatial Statistics in Preterm-Born Neonates Predicts Cognitive and Motor Outcomes at 18 Months.

BACKGROUND AND PURPOSE: Adverse neurodevelopmental outcome is common in children born preterm. Early sensitive predictors of neurodevelopmental outcome such as MR imaging are needed. Tract-based spatial statistics, a diffusion MR imaging analysis method, performed at term-equivalent age (40 weeks) is a promising predictor of neurodevelopmental outcomes in children born very preterm. We sought to determine the association of tract-based spatial statistics findings before term-equivalent age with neurodevelopmental outcome at 18-months corrected age. MATERIALS AND METHODS: Of 180 neonates (born at 24-32-weeks\u27 gestation) enrolled, 153 had DTI acquired early at 32 weeks\u27 postmenstrual age and 105 had DTI acquired later at 39.6 weeks\u27 postmenstrual age. Voxelwise statistics were calculated by performing tract-based spatial statistics on DTI that was aligned to age-appropriate templates. At 18-month corrected age, 166 neonates underwent neurodevelopmental assessment by using the Bayley Scales of Infant Development, 3rd ed, and the Peabody Developmental Motor Scales, 2nd ed. RESULTS: Tract-based spatial statistics analysis applied to early-acquired scans (postmenstrual age of 30-33 weeks) indicated a limited significant positive association between motor skills and axial diffusivity and radial diffusivity values in the corpus callosum, internal and external/extreme capsules, and midbrain (P \u3c .05, corrected). In contrast, for term scans (postmenstrual age of 37-41 weeks), tract-based spatial statistics analysis showed a significant relationship between both motor and cognitive scores with fractional anisotropy in the corpus callosum and corticospinal tracts (P \u3c .05, corrected). Tract-based spatial statistics in a limited subset of neonates (n = 22) scanned at CONCLUSIONS: The strength of the association between fractional anisotropy values and neurodevelopmental outcome scores increased from early-to-late-acquired scans in preterm-born neonates, consistent with brain dysmaturation in this population

User needs assessment for climate services in Zambia

Between February and April 2021 research was conducted to assess the user needs of selected farmer groups in Zambia for farmer centric agrometeorological information services. Specifically, it aimed to: • Identify the types of weather information and agronomic advice that farmers currently receive, the sources that they use and how satisfied they are with the information they receive; • Better understand the effects of climate variability and change on different agricultural activities and the decisions farmers are able to make; and • Enable farmers to identify what weather and climate information, services and agronomic advice they need and how they would like to access it. The results were then presented to key stakeholders and used in an ideation process to help design potential climate services for implementation at scale. Key findings from the user research are that: • Respondents articulated a demand for information and advice on a range of different weather variables at a range of different timescales to aid both their long-term planning and more immediate decisions. • There is a gap between the climate and weather information and services that are produced (by Zambia Meteorological Department) and those that farmers are accessing. • The complexities of challenges facing respondents, and the variety of different decisions affected, means that addressing these challenges is not simply about the provision of climate information but supporting farmers to contextualise and use this information. Farmers outlined a range of existing practices that they use to address challenges that are related to weather and climate. Many of these practices address multiple challenges and are often proactive rather than reactive options for farmers. • Engaging farmers with climate services requires a range of different and complimentary approaches. Radio is the most commonly used and requested going forward. Extension staff, lead farmers and farmer groups are important sources of information and support in farmer decision making. Climate services products should be designed with the aim to address multiple farmer ‘problems’. For example, information on the amount of rainfall to expect in a season can aid decision making on choice of land preparation and cultivation methods, choice of crop variety, weeding, as well requirements for pest and disease management in cattle

Targeted next generation sequencing of pancreatic solid pseudopapillary neoplasms show mutations in Wnt signaling pathway genes.

Solid pseudopapillary neoplasms of the pancreas are rare neoplasms that have been shown to harbor recurrent somatic pathogenic variants in the beta-catenin gene, CTNNB1. Here, we used targeted next generation sequencing to analyze these tumors for other associated mutations. Six cases of solid pseudopapillary neoplasms were studied. DNA extracted from formalin-fixed paraffin embedded tissue blocks was analyzed using the Ion Torrent platform, with the 50-gene Ampliseq Cancer Hotspot Panel v2 (CHPv2), with further variant validation performed by Sanger sequencing. Four tumors (67%) were confirmed to harbor mutations within CTNNB1, two with c.109T > G p.(Ser37Ala) and two with c.94G > A p.(Asp32Asn). One case showed a frameshift deletion in the Adenomatous Polyposis Coli gene, APC c.3964delG p.(Glu1322Lysfs*93) with a variant allele frequency of 42.6%. Sanger sequencing on non-tumoral tissue confirmed the variant was somatic. The patient with the APC mutation developed metastasis and died. In addition to the four cases harboring CTNNB1 variants, we found a case characterized by poor outcome, showing a rare frameshift deletion in the APC gene. Since the APC product interacts with beta-catenin, APC variants may, in addition to CTNNB1, contribute to the pathogenesis of solid pseudopapillary neoplasms via the Wnt signaling pathway

Brain Injury Patterns in Hypoglycemia in Neonatal Encephalopathy

ABSTRACT BACKGROUND AND PURPOSE: Low glucose values are often seen in term infants with NE, including HIE, yet the contribution of hypoglycemia to the pattern of neurologic injury remains unclear. We hypothesized that MR features of neonatal hypoglycemia could be detected, superimposed on the predominant HIE injury pattern

On verifying ATL transformations using 'off-the-shelf' SMT solvers

International audienceMDE is a software development process where models constitute pivotal elements of the software to be built. If models are well-specified, transformations can be employed for various purposes, e.g., to produce final code. However, transformations are only meaningful when they are 'correct': they must produce valid models from valid input models. A valid model has conformance to its meta-model and fulfils its constraints, usually written in OCL. In this paper, we propose a novel methodology to perform automatic, unbounded verification of ATL transformations. Its main component is a novel first-order semantics for ATL transformations, based on the interpretation of the corresponding rules and their execution semantics as first-order predicates. Although, our semantics is not complete, it does cover a significant subset of the ATL language. Using this semantics, transformation correctness can be automatically verified with respect to non-trivial OCL pre- and postconditions by using SMT solvers, e.g. Z3 and Yices