How good are your fits? Unbinned multivariate goodness-of-fit tests in high energy physics

Multivariate analyses play an important role in high energy physics. Such analyses often involve performing an unbinned maximum likelihood fit of a probability density function (p.d.f.) to the data. This paper explores a variety of unbinned methods for determining the goodness of fit of the p.d.f. to the data. The application and performance of each method is discussed in the context of a real-life high energy physics analysis (a Dalitz-plot analysis). Several of the methods presented in this paper can also be used for the non-parametric determination of whether two samples originate from the same parent p.d.f. This can be used, e.g., to determine the quality of a detector Monte Carlo simulation without the need for a parametric expression of the efficiency.Comment: 32 pages, 12 figure

Results of Phase II Clinical Trial MPD-RC 101: Allogeneic Hematopoietic Stem Cell Transplantation Conditioned with Fludarabine/Melphalan in Patients with Myelofibrosis

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Homotransplantation of the liver in a patientwith hepatoma and hereditary tyrosinemia

A girl with hereditary tyrosinemia, diagnosed at 6 months of age, was treated with a diet restricted inphenylalanine and tyrosine. At 91/2 years of age she developed an acutely enlarged liver and spleen, and the diagnosis of hepatocarcinoma was made. The patient received a liver transplant and tyrosine metabolites became normal while she was receiving a regular diet. Three months later, an infected thrombosis of the portal vein caused her death. Liver transplant appears to be an effective method of enzyme replacement in tyrosinemia and should be considered for prevention of hepatoma. © 1978 The C. V. Mosby Company

Quantitative PCR tissue expression profiling of the human SGLT2 gene and related family members

SGLT2 (for “Sodium GLucose coTransporter” protein 2) is the major protein responsible for glucose reabsorption in the kidney and its inhibition has been the focus of drug discovery efforts to treat type 2 diabetes. In order to better clarify the human tissue distribution of expression of SGLT2 and related members of this cotransporter class, we performed TaqMan™ (Applied Biosystems, Foster City, CA, USA) quantitative polymerase chain reaction (PCR) analysis of SGLT2 and other sodium/glucose transporter genes on RNAs from 72 normal tissues from three different individuals. We consistently observe that SGLT2 is highly kidney specific while SGLT5 is highly kidney abundant; SGLT1, sodium-dependent amino acid transporter (SAAT1), and SGLT4 are highly abundant in small intestine and skeletal muscle; SGLT6 is expressed in the central nervous system; and sodium myoinositol cotransporter is ubiquitously expressed across all human tissues

From TgO/GABA-AT, GABA, and T-263 Mutant to Conception of Toxoplasma

Toxoplasma gondii causes morbidity, mortality, and disseminates widely via cat sexual stages. Here, we find T. gondii ornithine aminotransferase (OAT) is conserved across phyla. We solve TgO/GABA-AT structures with bound inactivators at 1.55 Å and identify an inactivator selective for TgO/GABA-AT over human OAT and GABA-AT. However, abrogating TgO/GABA-AT genetically does not diminish replication, virulence, cyst-formation, or eliminate cat's oocyst shedding. Increased sporozoite/merozoite TgO/GABA-AT expression led to our study of a mutagenized clone with oocyst formation blocked, arresting after forming male and female gametes, with “Rosetta stone”-like mutations in genes expressed in merozoites. Mutations are similar to those in organisms from plants to mammals, causing defects in conception and zygote formation, affecting merozoite capacitation, pH/ionicity/sodium-GABA concentrations, drawing attention to cyclic AMP/PKA, and genes enhancing energy or substrate formation in TgO/GABA-AT-related-pathways. These candidates potentially influence merozoite's capacity to make gametes that fuse to become zygotes, thereby contaminating environments and causing disease

Overlap of Genetic Risk between Interstitial Lung Abnormalities and Idiopathic Pulmonary Fibrosis

Rationale: Interstitial lung abnormalities (ILAs) are associated with the highest genetic risk locus for idiopathic pulmonary fibrosis (IPF); however, the extent to which there are unique associations among individuals with ILAs or additional overlap with IPF is not known.Objectives: To perform a genome-wide association study (GWAS) of ILAs.Methods: ILAs and a subpleural-predominant subtype were assessed on chest computed tomography (CT) scans in the AGES (Age Gene/Environment Susceptibility), COPDGene (Genetic Epidemiology of Chronic Obstructive Pulmonary Disease [COPD]), Framingham Heart, ECLIPSE (Evaluation of COPD Longitudinally to Identify Predictive Surrogate End-points), MESA (Multi-Ethnic Study of Atherosclerosis), and SPIROMICS (Subpopulations and Intermediate Outcome Measures in COPD Study) studies. We performed a GWAS of ILAs in each cohort and combined the results using a meta-analysis. We assessed for overlapping associations in independent GWASs of IPF.Measurements and Main Results: Genome-wide genotyping data were available for 1,699 individuals with ILAs and 10,274 control subjects. The MUC5B (mucin 5B) promoter variant rs35705950 was significantly associated with both ILAs (P = 2.6 × 10-27) and subpleural ILAs (P = 1.6 × 10-29). We discovered novel genome-wide associations near IPO11 (rs6886640, P = 3.8 × 10-8) and FCF1P3 (rs73199442, P = 4.8 × 10-8) with ILAs, and near HTRE1 (rs7744971, P = 4.2 × 10-8) with subpleural-predominant ILAs. These novel associations were not associated with IPF. Among 12 previously reported IPF GWAS loci, five (DPP9, DSP, FAM13A, IVD, and MUC5B) were significantly associated (P < 0.05/12) with ILAs.Conclusions: In a GWAS of ILAs in six studies, we confirmed the association with a MUC5B promoter variant and found strong evidence for an effect of previously described IPF loci; however, novel ILA associations were not associated with IPF. These findings highlight common genetically driven biologic pathways between ILAs and IPF, and also suggest distinct ones

Comprehensive analysis of epigenetic clocks reveals associations between disproportionate biological ageing and hippocampal volume

The concept of age acceleration, the difference between biological age and chronological age, is of growing interest, particularly with respect to age-related disorders, such as Alzheimer’s Disease (AD). Whilst studies have reported associations with AD risk and related phenotypes, there remains a lack of consensus on these associations. Here we aimed to comprehensively investigate the relationship between five recognised measures of age acceleration, based on DNA methylation patterns (DNAm age), and cross-sectional and longitudinal cognition and AD-related neuroimaging phenotypes (volumetric MRI and Amyloid-β PET) in the Australian Imaging, Biomarkers and Lifestyle (AIBL) and the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Significant associations were observed between age acceleration using the Hannum epigenetic clock and cross-sectional hippocampal volume in AIBL and replicated in ADNI. In AIBL, several other findings were observed cross-sectionally, including a significant association between hippocampal volume and the Hannum and Phenoage epigenetic clocks. Further, significant associations were also observed between hippocampal volume and the Zhang and Phenoage epigenetic clocks within Amyloid-β positive individuals. However, these were not validated within the ADNI cohort. No associations between age acceleration and other Alzheimer’s disease-related phenotypes, including measures of cognition or brain Amyloid-β burden, were observed, and there was no association with longitudinal change in any phenotype. This study presents a link between age acceleration, as determined using DNA methylation, and hippocampal volume that was statistically significant across two highly characterised cohorts. The results presented in this study contribute to a growing literature that supports the role of epigenetic modifications in ageing and AD-related phenotypes

Uncovering the heterogeneity and temporal complexity of neurodegenerative diseases with Subtype and Stage Inference

The heterogeneity of neurodegenerative diseases is a key confound to disease understanding and treatment development, as study cohorts typically include multiple phenotypes on distinct disease trajectories. Here we introduce a machine-learning technique\u2014Subtype and Stage Inference (SuStaIn)\u2014able to uncover data-driven disease phenotypes with distinct temporal progression patterns, from widely available cross-sectional patient studies. Results from imaging studies in two neurodegenerative diseases reveal subgroups and their distinct trajectories of regional neurodegeneration. In genetic frontotemporal dementia, SuStaIn identifies genotypes from imaging alone, validating its ability to identify subtypes; further the technique reveals within-genotype heterogeneity. In Alzheimer\u2019s disease, SuStaIn uncovers three subtypes, uniquely characterising their temporal complexity. SuStaIn provides fine-grained patient stratification, which substantially enhances the ability to predict conversion between diagnostic categories over standard models that ignore subtype (p = 7.18 7 10 124 ) or temporal stage (p = 3.96 7 10 125 ). SuStaIn offers new promise for enabling disease subtype discovery and precision medicine