SOLUBLE ST2 AND CD163 AS POTENTIALBIOMARKERS TO DIFFERENTIATE PRIMARY HEMOPHAGOCYTIC LYMPHOHISTIOCYTOSIS FROM MACROPHAGE ACTIVATION SYNDROME

Abstract Background and Objective: The differentiation of primary haemophagocytic lymphohistiocytosis (pHLH) and macrophage activation syndrome (MAS) poses a challenge to hematologists. The aim of this study was (1) to compare the levels of soluble ST2 (sST2), sCD163, IL-10, IFN-γ, TNF-α and IL-18 in patients with pHLH and MAS and (2) to investigate whether they can help differentiate the two diseases. Methods: A total of 54 participants were recruited in this study, including 12 pHLH patients, 22 MAS patients and 20 healthy subjects. We measured the levels of sST2 and sCD163 in serum by ELISA. The serum levels of IL-10, IFN-γ, TNF-α and IL-18 were detected using a Luminex 200 instrument. Results: The serum levels of sST2 and sCD163 in MAS patients were markedly higher than that in pHLH patients (363.13 ± 307.24 ng/ml vs 80.75 ± 87.04 ng/ml, P = 0.004; 3532.72 ± 2479.68 ng/ml vs 1731.96 ± 1262.07 ng/ml, P = 0.046). There was no significant difference in the expression of IFN-γ (306.89 ± 281.60 pg/ml vs 562.43 ± 399.86 pg/ml), IL-10 (20.40 ± 30.49 pg/ml vs 8.3 ± 13.14 pg/ml), IL-18 (463.33 ± 597.04 pg/ml vs 1247.82 ± 1318.58 pg/ml) and TNF-α (61.48 ± 84.69 pg/ml vs 106.10 ±77.21 pg/ml) between pHLH and MAS. Conclusion: Patients with pHLH and MAS show some differences in cytokine profiles. The elevated levels of IFN-γ, IL-10, IL-18 and TNF-α can contribute to the diagnosis of HLH, but may not discriminate pHLH from MAS. Levels of sST2 and sCD163 may serve as markers to distinguish pHLH from MAS

Geographical variations in maternal dietary patterns during pregnancy associated with birth weight in Shaanxi province, Northwestern China

The geographical variation of maternal dietary patterns related to birth outcomes is important for improving the health of mothers and children; however, it is currently unknown. Thus, the objective of the study was to investigate geographical variations of maternal dietary pattern during pregnancy, and evaluate the spatial varying association of maternal dietary patterns in pregnancy with abnormal birth weight. A population-based cross-sectional study was conducted in Shaanxi province in Northwest China in 2013 to evaluate the relationship between abnormal birth weight and dietary pattern using the Geographically Weighted Logistic Regression (GWLR). Three dietary patterns during pregnancy were extracted through factor analysis, explaining approximately 45.8% of the variability of food intake. Approximately 81.6% of mothers with higher scores on the equilibrium pattern was more unlikely to have small for gestational age (SGA) infants, with the lower OR observed in Central and South Shaanxi. The snacks pattern was positively associated with low birth weight (LBW) for 23.2% of participants, with the highest OR in Central Shaanxi. Among about 80.0% of participants with higher scores on the snacks pattern living in South and Central Shaanxi, there was a higher risk for SGA. The OR values tend to descend from South to North Shaanxi. The OR values of the negative association between prudent pattern and LBW decreased from South to North Shaanxi among approximately 59.3% of participants. The prudent pattern was also negatively associated with the increasing risk of fetal macrosomia among 19.2% of participants living mainly in South Shaanxi. The association of maternal dietary patterns during pregnancy with abnormal birth weight varied geographically across Shaanxi province. The findings emphasize the importance of geographical distribution to improve the dietary patterns among disadvantaged pregnant women

AI is a viable alternative to high throughput screening: a 318-target study

: High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery

The evolution of self-control

This work was supported by the National Evolutionary Synthesis Center (NESCent) through support of a working group led by C.L.N. and B.H. NESCent is supported by the National Science Foundation (NSF) EF-0905606. For training in phylogenetic comparative methods, we thank the AnthroTree Workshop (supported by NSF BCS-0923791). Y.S. thanks the National Natural Science Foundation of China (Project 31170995) and National Basic Research Program (973 Program: 2010CB833904). E.E.B. thanks the Duke Vertical Integration Program and the Duke Undergraduate Research Support Office. J.M.P. was supported by a Newton International Fellowship from the Royal Society and the British Academy. L.R.S. thanks the James S. McDonnell Foundation for Award 220020242. L.J.N.B. and M.L.P. acknowledge the National Institutes of Mental Health (R01-MH096875 and R01-MH089484), a Duke Institute for Brain Sciences Incubator Award (to M.L.P.), and a Duke Center for Interdisciplinary Decision Sciences Fellowship (to L.J.N.B.). E.V. and E.A. thank the Programma Nazionale per la Ricerca–Consiglio Nazionale delle Ricerche (CNR) Aging Program 2012–2014 for financial support, Roma Capitale–Museo Civico di Zoologia and Fondazione Bioparco for hosting the Istituto di Scienze e Tecnologie della Cognizione–CNR Unit of Cognitive Primatology and Primate Centre, and Massimiliano Bianchi and Simone Catarinacci for assistance with capuchin monkeys. K.F. thanks the Japan Society for the Promotion of Science (JSPS) for Grant-in-Aid for Scientific Research 20220004. F. Aureli thanks the Stages in the Evolution and Development of Sign Use project (Contract 012-984 NESTPathfinder) and the Integrating Cooperation Research Across Europe project (Contract 043318), both funded by the European Community’s Sixth Framework Programme (FP6/2002–2006). F. Amici was supported by Humboldt Research Fellowship for Postdoctoral Researchers (Humboldt ID 1138999). L.F.J. and M.M.D. acknowledge NSF Electrical, Communications, and Cyber Systems Grant 1028319 (to L.F.J.) and an NSF Graduate Fellowship (to M.M.D.). C.H. thanks Grant-in-Aid for JSPS Fellows (10J04395). A.T. thanks Research Fellowships of the JSPS for Young Scientists (21264). F.R. and Z.V. acknowledge Austrian Science Fund (FWF) Project P21244-B17, the European Research Council (ERC) under the European Union’s Seventh Framework Programme (FP/2007–2013)/ERC Grant Agreement 311870 (to F.R.), Vienna Science and Technology Fund Project CS11-026 (to Z.V.), and many private sponsors, including Royal Canin for financial support and the Game Park Ernstbrunn for hosting the Wolf Science Center. S.M.R. thanks the Natural Sciences and Engineering Research Council (Canada). J.K.Y. thanks the US Department of Agriculture–Wildlife Services–National Wildlife Research Center. J.F.C. thanks the James S. McDonnell Foundation and Alfred P. Sloan Foundation. E.L.M. and B.H. thank the Duke Lemur Center and acknowledge National Institutes of Health Grant 5 R03 HD070649-02 and NSF Grants DGE-1106401, NSF-BCS-27552, and NSF-BCS-25172. This is Publication 1265 of the Duke Lemur Center.Cognition presents evolutionary research with one of its greatest challenges. Cognitive evolution has been explained at the proximate level by shifts in absolute and relative brain volume and at the ultimate level by differences in social and dietary complexity. However, no study has integrated the experimental and phylogenetic approach at the scale required to rigorously test these explanations. Instead, previous research has largely relied on various measures of brain size as proxies for cognitive abilities. We experimentally evaluated these major evolutionary explanations by quantitatively comparing the cognitive performance of 567 individuals representing 36 species on two problem-solving tasks measuring self-control. Phylogenetic analysis revealed that absolute brain volume best predicted performance across species and accounted for considerably more variance than brain volume controlling for body mass. This result corroborates recent advances in evolutionary neurobiology and illustrates the cognitive consequences of cortical reorganization through increases in brain volume. Within primates, dietary breadth but not social group size was a strong predictor of species differences in self-control. Our results implicate robust evolutionary relationships between dietary breadth, absolute brain volume, and self-control. These findings provide a significant first step toward quantifying the primate cognitive phenome and explaining the process of cognitive evolution.PostprintPeer reviewe