Evidence for an Intermediate-mass Milky Way from Gaia DR2 Halo Globular Cluster Motions

We estimate the mass of the Milky Way (MW) within 21.1 kpc using the kinematics of halo globular clusters (GCs) determined by Gaia. The second Gaia data release (DR2) contained a catalogue of absolute proper motions (PMs) for a set of Galactic GCs and satellite galaxies measured using Gaia DR2 data. We select from the catalogue only halo GCs, identifying a total of 34 GCs spanning $2.0 < r < 21.1$ kpc, and use their 3D kinematics to estimate the anisotropy over this range to be $\beta = 0.46^{+0.15}_{-0.19}$, in good agreement, though slightly lower than, a recent estimate for a sample of halo GCs using HST PM measurements further out in the halo. We then use the Gaia kinematics to estimate the mass of the MW inside the outermost GC to be $M(< 21.1 \mathrm{kpc}) = 0.21^{+0.04}_{-0.03} 10^{12} \mathrm{M_\odot}$, which corresponds to a circular velocity of $v_\mathrm{circ}(21.1 \mathrm{kpc}) = 206^{+19}_{-16}$ km/s. The implied virial mass is $M_\mathrm{virial} = 1.28^{+0.97}_{-0.48} 10^{12} \mathrm{M_\odot}$. The error bars encompass the uncertainties on the anisotropy and on the density profile of the MW dark halo, and the scatter inherent in the mass estimator we use. We get improved estimates when we combine the Gaia and HST samples to provide kinematics for 46 GCs out to 39.5 kpc: $\beta = 0.52^{+0.11}_{-0.14}$, $M(< 39.5 \mathrm{kpc}) = 0.42^{+0.07}_{-0.06} 10^{12} \mathrm{M_\odot}$, and $M_\mathrm{virial} = 1.54^{+0.75}_{-0.44} 10^{12} \mathrm{M_\odot}$. We show that these results are robust to potential substructure in the halo GC distribution. While a wide range of MW virial masses have been advocated in the literature, from below $10^{12} \mathrm{M_\odot}$ to above $2 \times 10^{12}\mathrm{M_\odot}$, these new data imply that an intermediate mass is most likely

Rapid iron loading in a pregnant woman with transfusion-dependent thalassemia after brief cessation of iron chelation therapy

In general, in women with transfusion-dependent thalassemia, during pregnancy, iron chelation therapy is ceased. We report a splenectomized patient, who was an excellent complier with chelation therapy, who before embarking on a pregnancy showed no evidence of iron overload, with normal cardiac, thyroid function and glucose metabolism. Laboratory findings showed ferritin 67 μg/L, myocardial T2* of 34 ms and liver magnetic resonance imaging (MRI) liver iron concentration of 1 mg/g dry weight. She became pregnant by in vitro fertilization in October 2006, delivery occurred in June 2007. She breast fed for 2 months. After 12 months without iron chelation, ferritin was 1583 μg/L. Quantitative MRI showed myocardial T2* of 27 ms, that the liver iron concentration had increased to 11.3 mg/g dry weight, indicative of moderate to heavy iron load. This case demonstrates that iron overload can develop rapidly and that physicians caring for patients with transfusion-dependent thalassemia should be particularly alert to any discontinuation of chelation therapy over time

Characterizing Performance Gaps of a Code-Based Dementia Algorithm in a Population-Based Cohort of Cognitive Aging

BACKGROUND: Multiple algorithms with variable performance have been developed to identify dementia using combinations of billing codes and medication data that are widely available from electronic health records (EHR). If the characteristics of misclassified patients are clearly identified, modifying existing algorithms to improve performance may be possible. OBJECTIVE: To examine the performance of a code-based algorithm to identify dementia cases in the population-based Mayo Clinic Study of Aging (MCSA) where dementia diagnosis (i.e., reference standard) is actively assessed through routine follow-up and describe the characteristics of persons incorrectly categorized. METHODS: There were 5,316 participants (age at baseline (mean (SD)): 73.3 (9.68) years; 50.7% male) without dementia at baseline and available EHR data. ICD-9/10 codes and prescription medications for dementia were extracted between baseline and one year after an MCSA dementia diagnosis or last follow-up. Fisher\u27s exact or Kruskal-Wallis tests were used to compare characteristics between groups. RESULTS: Algorithm sensitivity and specificity were 0.70 (95% CI: 0.67, 0.74) and 0.95 (95% CI: 0.95, 0.96). False positives (i.e., participants falsely diagnosed with dementia by the algorithm) were older, with higher Charlson comorbidity index, more likely to have mild cognitive impairment (MCI), and longer follow-up (versus true negatives). False negatives (versus true positives) were older, more likely to have MCI, or have more functional limitations. CONCLUSIONS: We observed a moderate-high performance of the code-based diagnosis method against the population-based MCSA reference standard dementia diagnosis. Older participants and those with MCI at baseline were more likely to be misclassified

Dementia Prediction in Older Adults Using Sex-Specific Health Trajectory Clustering

With increasing number of people living with dementia, the problem of late diagnosis significantly impacts a person\u27s quality of life while early signs of dementia may provide useful insights to facilitate better treatment plans. With time, this progressive neurodegenerative syndrome could progress from mild cognitive impairment to dementia. A pattern of health conditions can be characterized in unsupervised manner to help predict this progress. As a significant extension to our previous work with streaming clustering model, we consider additional information for predicting dementia onset. With empirical observations, we discover the importance of examining sex and age to predict dementia onset. To this end, we propose a sex-specific model with age-constraint for predicting dementia onset and validate the effectiveness of our models using data from Mayo Clinic Study of Aging (MCSA). The proposed sex-specific models for older adult populations (\u3e=65 years of age) outperformed the previous models with F-score of 77% and 78% for male-specific and female-specific models, respectively. Our experiments of sex-specific temporal clustering of features in older adults demonstrate the potential of more personalized models for early alerts of dementia

Structure and function of the Rad9-binding region of the DNA-damage checkpoint adaptor TopBP1

TopBP1 is a scaffold protein that coordinates activation of the DNA-damage-checkpoint response by coupling binding of the 9-1-1 checkpoint clamp at sites of ssDNA, to activation of the ATR-ATRIP checkpoint kinase complex. We have now determined the crystal structure of the N-terminal region of human TopBP1, revealing an unexpected triple-BRCT domain structure. The arrangement of the BRCT domains differs significantly from previously described tandem BRCT domain structures, and presents two distinct sites for binding phosphopeptides in the second and third BRCT domains. We show that the site in the second but not third BRCT domain in the N-terminus of TopBP1, provides specific interaction with a phosphorylated motif at pSer387 in Rad9, which can be generated by CK2

Neonatal Plasma Polarizes TLR4-Mediated Cytokine Responses towards Low IL-12p70 and High IL-10 Production via Distinct Factors

Human neonates are highly susceptible to infection, which may be due in part to impaired innate immune function. Neonatal Toll-like receptor (TLR) responses are biased against the generation of pro-inflammatory/Th1-polarizing cytokines, yet the underlying mechanisms are incompletely defined. Here, we demonstrate that neonatal plasma polarizes TLR4-mediated cytokine production. When exposed to cord blood plasma, mononuclear cells (MCs) produced significantly lower TLR4-mediated IL-12p70 and higher IL-10 compared to MC exposed to adult plasma. Suppression by neonatal plasma of TLR4-mediated IL-12p70 production, but not induction of TLR4-mediated IL-10 production, was maintained up to the age of 1 month. Cord blood plasma conferred a similar pattern of MC cytokine responses to TLR3 and TLR8 agonists, demonstrating activity towards both MyD88-dependent and MyD88-independent agonists. The factor causing increased TLR4-mediated IL-10 production by cord blood plasma was heat-labile, lost after protein depletion and independent of lipoprotein binding protein (LBP) or soluble CD14 (sCD14). The factor causing inhibition of TLR4-mediated IL-12p70 production by cord blood plasma was resistant to heat inactivation or protein depletion and was independent of IL-10, vitamin D and prostaglandin E2. In conclusion, human neonatal plasma contains at least two distinct factors that suppress TLR4-mediated IL-12p70 production or induce IL-10 or production. Further identification of these factors will provide insight into the ontogeny of innate immune development and might identify novel targets for the prevention and treatment of neonatal infection

Antileishmanial High-Throughput Drug Screening Reveals Drug Candidates with New Scaffolds

Drugs currently available for leishmaniasis treatment often show parasite resistance, highly toxic side effects and prohibitive costs commonly incompatible with patients from the tropical endemic countries. In this sense, there is an urgent need for new drugs as a treatment solution for this neglected disease. Here we show the development and implementation of an automated high-throughput viability screening assay for the discovery of new drugs against Leishmania. Assay validation was done with Leishmania promastigote forms, including the screening of 4,000 compounds with known pharmacological properties. In an attempt to find new compounds with leishmanicidal properties, 26,500 structurally diverse chemical compounds were screened. A cut-off of 70% growth inhibition in the primary screening led to the identification of 567 active compounds. Cellular toxicity and selectivity were responsible for the exclusion of 78% of the pre-selected compounds. The activity of the remaining 124 compounds was confirmed against the intramacrophagic amastigote form of the parasite. In vitro microsomal stability and cytochrome P450 (CYP) inhibition of the two most active compounds from this screening effort were assessed to obtain preliminary information on their metabolism in the host. The HTS approach employed here resulted in the discovery of two new antileishmanial compounds, bringing promising candidates to the leishmaniasis drug discovery pipeline

Computational Prediction and Molecular Characterization of an Oomycete Effector and the Cognate Arabidopsis Resistance Gene

Hyaloperonospora arabidopsidis (Hpa) is an obligate biotroph oomycete pathogen of the model plant Arabidopsis thaliana and contains a large set of effector proteins that are translocated to the host to exert virulence functions or trigger immune responses. These effectors are characterized by conserved amino-terminal translocation sequences and highly divergent carboxyl-terminal functional domains. The availability of the Hpa genome sequence allowed the computational prediction of effectors and the development of effector delivery systems enabled validation of the predicted effectors in Arabidopsis. In this study, we identified a novel effector ATR39-1 by computational methods, which was found to trigger a resistance response in the Arabidopsis ecotype Weiningen (Wei-0). The allelic variant of this effector, ATR39-2, is not recognized, and two amino acid residues were identified and shown to be critical for this loss of recognition. The resistance protein responsible for recognition of the ATR39-1 effector in Arabidopsis is RPP39 and was identified by map-based cloning. RPP39 is a member of the CC-NBS-LRR family of resistance proteins and requires the signaling gene NDR1 for full activity. Recognition of ATR39-1 in Wei-0 does not inhibit growth of Hpa strains expressing the effector, suggesting complex mechanisms of pathogen evasion of recognition, and is similar to what has been shown in several other cases of plant-oomycete interactions. Identification of this resistance gene/effector pair adds to our knowledge of plant resistance mechanisms and provides the basis for further functional analyses

Secretome-Based Identification of ULBP2 as a Novel Serum Marker for Pancreatic Cancer Detection

BACKGROUND: To discover novel markers for improving the efficacy of pancreatic cancer (PC) diagnosis, the secretome of two PC cell lines (BxPC-3 and MIA PaCa-2) was profiled. UL16 binding protein 2 (ULBP2), one of the proteins identified in the PC cell secretome, was selected for evaluation as a biomarker for PC detection because its mRNA level was also found to be significantly elevated in PC tissues. METHODS: ULBP2 expression in PC tissues from 67 patients was studied by immunohistochemistry. ULBP2 serum levels in 154 PC patients and 142 healthy controls were measured by bead-based immunoassay, and the efficacy of serum ULBP2 for PC detection was compared with the widely used serological PC marker carbohydrate antigen 19-9 (CA 19-9). RESULTS: Immunohistochemical analyses revealed an elevated expression of ULPB2 in PC tissues compared with adjacent non-cancerous tissues. Meanwhile, the serum levels of ULBP2 among all PC patients (n = 154) and in early-stage cancer patients were significantly higher than those in healthy controls (p<0.0001). The combination of ULBP2 and CA 19-9 outperformed each marker alone in distinguishing PC patients from healthy individuals. Importantly, an analysis of the area under receiver operating characteristic curves showed that ULBP2 was superior to CA 19-9 in discriminating patients with early-stage PC from healthy controls. CONCLUSIONS: Collectively, our results indicate that ULBP2 may represent a novel and useful serum biomarker for pancreatic cancer primary screening

ERCC2 2251A>C genetic polymorphism was highly correlated with early relapse in high-risk stage II and stage III colorectal cancer patients: A preliminary study

<p>Abstract</p> <p>Background</p> <p>Early relapse in colorectal cancer (CRC) patients is attributed mainly to the higher malignant entity (such as an unfavorable genotype, deeper tumor invasion, lymph node metastasis and advance cancer stage) and poor response to chemotherapy. Several investigations have demonstrated that genetic polymorphisms in drug-targeted genes, metabolizing enzymes, and DNA-repairing enzymes are all strongly correlated with inter-individual differences in the efficacy and toxicity of many treatment regimens. This preliminary study attempts to identify the correlation between genetic polymorphisms and clinicopathological features of CRC, and evaluates the relationship between genetic polymorphisms and chemotherapeutic susceptibility of Taiwanese CRC patients. To our knowledge, this study discusses, for the first time, early cancer relapse and its indication by multiple genes.</p> <p>Methods</p> <p>Six gene polymorphisms functional in drug-metabolism – <it>GSTP1 </it>Ile105Val, <it>ABCB1 </it>Ile1145Ile, <it>MTHFR </it>Ala222Val, <it>TYMS </it>double (2R) or triple (3R) tandem repeat – and DNA-repair genes – <it>ERCC2 </it>Lys751Gln and <it>XRCC1 A</it>rg399Gln – were assessed in 201 CRC patients using a polymerase chain reaction-restriction fragment-length polymorphism (PCR-RFLP) technique and DNA sequencing. Patients were diagnosed as either high-risk stage II (T2 and 3 N0 M0) or III (any T N1 and 2 M0) and were administered adjuvant chemotherapy regimens that included 5-fluorouracil (5FU) and leucovorin (LV). The correlations between genetic polymorphisms and patient clinicopathological features and relapses were investigated.</p> <p>Results</p> <p>In this study, the distributions of <it>GSTP1 </it>(<it>P </it>= 0.003), <it>ABCB1 </it>(<it>P </it>= 0.001), <it>TYMS </it>(<it>P </it>< 0.0001), <it>ERCC2 </it>(<it>P </it>< 0.0001) and <it>XRCC1 </it>(<it>P </it>= 0.006) genotypes in the Asian population, with the exception of <it>MTHFR </it>(<it>P </it>= 0.081), differed significantly from their distributions in a Caucasian population. However, the unfavorable genotype <it>ERCC2 </it>2251A>C (<it>P </it>= 0.006), tumor invasion depth (<it>P </it>= 0.025), lymph node metastasis (<it>P </it>= 0.011) and cancer stage (<it>P </it>= 0.008) were significantly correlated with early relapse. Patients carrying the <it>ERCC2 </it>2251AC or2251CC genotypes had a significantly increased risk of early relapse (OR = 3.294, 95% CI, 1.272–8.532).</p> <p>Conclusion</p> <p>We suggest that <it>ERCC2 </it>2251A>C alleles may be genetic predictors of early CRC relapse.</p