The Lund Fragmentation Process for a Multi-gluon String According to the Area Law

The Lund Area Law describes the probability for the production of a set of colourless hadrons from an initial set of partons, in the Lund string fragmentation model. In this paper we will present a general method to implement the Area Law for a multi-gluon string state. The partonic states are in general given by a perturbative QCD cascade and are consequently defined only down to a cutoff in the energy momentum fluctuations. We will show that our method defines the states down to the hadronic mass scale inside an analytically calculable scenario. We will then show that there is a differential version of our process which is closely related to the generalised rapidity range \lambda, which has been used as a measure on the partonic states. We identify \lambda as the area spanned between the directrix curve (the curve given by the parton energy momentum vectors laid out in colour order, which determines the string surface) and the average curve (to be called the P-curve) of the stochastic X-curves (curves obtained when the hadronic energy-momentum vectors are laid out in rank order). Finally we show that from the X-curve corresponding to a particular stochastic fragmentation situation it is possible to reproduce the directrix curve (up to one starting vector and a set of sign choices, one for each hadron).Comment: 1 title page + 36 pages, 20 figure

The Diagonalisation of the Lund Fragmentation Model I

We will in this note show that it is possible to diagonalise the Lund Fragmentation Model. We show that the basic original result, the Lund Area law, can be factorised into a product of transition operators, each describing the production of a single particle and the two adjacent breakup points (vertex positions) of the string field. The transition operator has a discrete spectrum of (orthonormal) eigenfunctions, describing the vertex positions (which in a dual way corresponds to the momentum transfers between the produced particles) and discrete eigenvalues, which only depend upon the particle produced. The eigenfunctions turn out to be the well-known two- dimensional harmonic oscillator functions and the eigenvalues are the analytic continuations of these functions to time-like values (corresponding to the particle mass). In this way all observables in the model can be expressed in terms of analytical formulas. In this note only the 1+1-dimensional version of the model is treated but we end with remarks on the extensions to gluonic radiation, transverse momentum generation etc, to be performed in future papers.Comment: 15 pages, 7 figure

Post-Mortem Metabolomics: A Novel Approach in Clinical Biomarker Discovery and a Potential Tool in Death Investigations

Metabolomics can be defined as the scientific field aiming at characterizing all low-weight molecules (so-called metabolites) in a biological system. At the time of death, the level and type of metabolites present will most likely reflect the events leading up to death. In this proof of concept study, we investigated the potential of post-mortem metabolomics by identifying post-mortem biomarkers, correlated these identified biomarkers with those reported in clinical metabolomics studies, and finally validated the models predictability of unknown autopsy cases. In this post-mortem metabolomics setting, ultra-high performance liquid chromatography-quadrupole time-of-flight mass spectrometry data from 404 post-mortem samples, including pneumonia cases and control cases, were processed using XCMS (R). Potential biomarkers were evaluated using principal component analysis and orthogonal partial least squares-discriminant analysis. Biomarkers were putatively annotated using an in-house database and the online databases METLIN and HMDB. The results showed that clear group separation was observed between pneumonia cases and control cases. The metabolites responsible for group separation belonged to a broad set of biological classes, such as amino acids, carnitines, lipids, nicotinamides, nucleotides, and steroids. Many of these metabolites have been reported as important in clinical manifestation of pneumonia. For the unknown autopsy cases, the sensitivity and specificity were 86 and 84%, respectively. This study successfully investigated the robustness and usability of post-mortem metabolomics in death investigations. The identified post-mortem biomarkers correlated well with biomarkers reported and identified through clinical research.</p

Autoimmune diseases, asthma and risk of haematological malignancies: A nationwide case-control study in Sweden

To investigate potential associations between several autoimmune diseases and haematological malignancies, we studied 39,908 cases of leukaemia, Hodgkin's disease, non-Hodgkin's lymphoma and myeloma that occurred during 1987-1999 in Sweden, and 149,344 controls. Hospital discharge diagnoses of psoriasis, Sjogren's syndrome, autoimmune haemolytic anaemia, idiopathic thrombocytopenic purpura, pernicious anaemia, multiple sclerosis, rheumatic fever or asthma from 1969 to 1999 were retrieved from the Swedish Hospital Discharge Registry. Psoriasis was positively associated with leukaemia, excluding chronic lymphocytic leukaemia, (odds ratio [OR] = 1.6, 95% confidence interval [CI] 1.1-2.3) and non-Hodgkin's lymphoma (OR = 1.6, 95% CI 1.3-2.1). Sjogren's syndrome increased the risks of all haematological malignancies combined (OR = 4.0, 95% CI 2.3-7.0), and of non-Hodgkin's lymphoma (OR = 6.4, 95% CI 3.5-12). These findings, together with increased risks of several haematological malignancies in autoimmune haemolytic anaemia and idiopathic thrombocytopenic purpura but not in asthma, suggest chronic autoimmunity and immune stimulation as mechanisms contributing to the development of haematological malignancies

Postmortem metabolomics as a high-throughput cause-of-death screening tool for human death investigations

Autopsy rates are declining globally, impacting cause-of-death (CoD) diagnoses and quality control. Postmortem metabolomics was evaluated for CoD screening using 4,282 human cases, encompassing CoD groups: acidosis, drug intoxication, hanging, ischemic heart disease (IHD), and pneumonia. Cases were split 3:1 into training and test sets. High-resolution mass spectrometry data from femoral blood were analyzed via orthogonal-partial least squares discriminant analysis (OPLS-DA) to discriminate CoD groups. OPLS-DA achieved an R2 = 0.52 and Q2 = 0.30, with true-positive prediction rates of 68% and 65% for training and test sets, respectively, across all groups. Specificity-optimized thresholds predicted 56% of test cases with a unique CoD, average 45% sensitivity, and average 96% specificity. Prediction accuracies varied: 98.7% for acidosis, 80.5% for drug intoxication, 81.6% for hanging, 73.1% for IHD, and 93.6% for pneumonia. This study demonstrates the potential of large-scale postmortem metabolomics for CoD screening, offering high specificity and enhancing throughput and decision-making in human death investigations.Funding Agencies|Swedish Research Council (Vetenskapsraring;det) [2023-01407]; Vinnova [2023-01407] Funding Source: Vinnova; Swedish Research Council [2023-01407] Funding Source: Swedish Research Council</p

Transcriptional profiling of human glioblastoma vessels indicates a key role of VEGF-A and TGF beta 2 in vascular abnormalization

Glioblastoma are aggressive astrocytic brain tumours characterized by microvascular proliferation and an abnormal vasculature, giving rise to brain oedema and increased patient morbidity. Here, we have characterized the transcriptome of tumour-associated blood vessels and describe a gene signature clearly associated with pleomorphic, pathologically altered vessels in human glioblastoma (grade IV glioma). We identified 95 genes differentially expressed in glioblastoma vessels, while no significant differences in gene expression were detected between vessels in non-malignant brain and grade II glioma. Differential vascular expression of ANGPT2, CD93, ESM1, ELTD1, FILIP1L and TENC1 in human glioblastoma was validated by immunohistochemistry, using a tissue microarray. Through qPCR analysis of gene induction in primary endothelial cells, we provide evidence that increased VEGF-A and TGF beta 2 signalling in the tumour microenvironment is sufficient to invoke many of the changes in gene expression noted in glioblastoma vessels. Notably, we found an enrichment of Smad target genes within the distinct gene signature of glioblastoma vessels and a significant increase of Smad signalling complexes in the vasculature of human glioblastoma in situ. This indicates a key role of TGF beta signalling in regulating vascular phenotype and suggests that, in addition to VEGF-A, TGF beta 2 may represent a new target for vascular normalization therapy. Copyright (c) 2012 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd