Wait Till Next Year

SO Aunt Millie told me to come on down next weekend and bring a girl friend. Don\u27t you think you could come?\u27\u27 Catherine\u27s voice was eager and pleading..

Fast 2-Approximate All-Pairs Shortest Paths

In this paper, we revisit the classic approximate All-Pairs Shortest Paths (APSP) problem in undirected graphs. For unweighted graphs, we provide an algorithm for $2$-approximate APSP in $\tilde O(n^{2.5-r}+n^{\omega(r)})$ time, for any $r\in[0,1]$. This is $O(n^{2.032})$ time, using known bounds for rectangular matrix multiplication~$n^{\omega(r)}$~[Le Gall, Urrutia, SODA 2018]. Our result improves on the $\tilde{O}(n^{2.25})$ bound of [Roddity, STOC 2023], and on the $\tilde{O}(m\sqrt n+n^2)$ bound of [Baswana, Kavitha, SICOMP 2010] for graphs with $m\geq n^{1.532}$ edges. For weighted graphs, we obtain $(2+\epsilon)$-approximate APSP in $\tilde O(n^{3-r}+n^{\omega(r)})$ time, for any $r\in [0,1]$. This is $O(n^{2.214})$ time using known bounds for $\omega(r)$. It improves on the state of the art bound of $O(n^{2.25})$ by [Kavitha, Algorithmica 2012]. Our techniques further lead to improved bounds in a wide range of density for weighted graphs. In particular, for the sparse regime we construct a distance oracle in $\tilde O(mn^{2/3})$ time that supports $2$-approximate queries in constant time. For sparse graphs, the preprocessing time of the algorithm matches conditional lower bounds [Patrascu, Roditty, Thorup, FOCS 2012; Abboud, Bringmann, Fischer, STOC 2023]. To the best of our knowledge, this is the first 2-approximate distance oracle that has subquadratic preprocessing time in sparse graphs. We also obtain new bounds in the near additive regime for unweighted graphs. We give faster algorithms for $(1+\epsilon,k)$-approximate APSP, for $k=2,4,6,8$. We obtain these results by incorporating fast rectangular matrix multiplications into various combinatorial algorithms that carefully balance out distance computation on layers of sparse graphs preserving certain distance information

Formation of Compact Myelin Is Required for Maturation of the Axonal Cytoskeleton

Although traditional roles ascribed to myelinating glial cells are structural and supportive, the importance of compact myelin for proper functioning of the nervous system can be inferred from mutations in myelin proteins and neuropathologies associated with loss of myelin. Myelinating Schwann cells are known to affect local properties of peripheral axons (de Waegh et al., 1992), but little is known about effects of oligodendrocytes on CNS axons. The shiverer mutant mouse has a deletion in the myelin basic protein gene that eliminates compact myelin in the CNS. In shiverer mice, both local axonal features like phosphorylation of cytoskeletal proteins and neuronal perikaryon functions like cytoskeletal gene expression are altered. This leads to changes in the organization and composition of the axonal cytoskeleton in shiverer unmyelinated axons relative to age-matched wild-type myelinated fibers, although connectivity and patterns of neuronal activity are comparable. Remarkably, transgenic shiverer mice with thin myelin sheaths display an intermediate phenotype indicating that CNS neurons are sensitive to myelin sheath thickness. These results indicate that formation of a normal compact myelin sheath is required for normal maturation of the neuronal cytoskeleton in large CNS neurons

Formation of Compact Myelin Is Required for Maturation of the Axonal Cytoskeleton

Although traditional roles ascribed to myelinating glial cells are structural and supportive, the importance of compact myelin for proper functioning of the nervous system can be inferred from mutations in myelin proteins and neuropathologies associated with loss of myelin. Myelinating Schwann cells are known to affect local properties of peripheral axons (de Waegh et al., 1992), but little is known about effects of oligodendrocytes on CNS axons. The shiverer mutant mouse has a deletion in the myelin basic protein gene that eliminates compact myelin in the CNS. In shiverer mice, both local axonal features like phosphorylation of cytoskeletal proteins and neuronal perikaryon functions like cytoskeletal gene expression are altered. This leads to changes in the organization and composition of the axonal cytoskeleton in shiverer unmyelinated axons relative to age-matched wild-type myelinated fibers, although connectivity and patterns of neuronal activity are comparable. Remarkably, transgenic shiverer mice with thin myelin sheaths display an intermediate phenotype indicating that CNS neurons are sensitive to myelin sheath thickness. These results indicate that formation of a normal compact myelin sheath is required for normal maturation of the neuronal cytoskeleton in large CNS neurons

The Iowa Homemaker vol.20, no.2

Your College Home, Editor, page 1 Home Economics Cabinet, Florence Byrnes, page 2 Study on a Budget, Dorothy Lee Conquest, page 4 Forward March with Confidence, Eleanor White, page 6 Home Economist from Far Away, Ruby Jackson, page 7 It’s a Man’s World, Gaynold Carroll, page 8 Art, Music, and Literature Mingle, Nancy Mason, page 10 Who’s Who on Campus, Dorothy Anne Roost, page 11 What’s New in Home Economics, page 12 Women’s Athletics Will Enter New Home, Jeanette Foster, page 14 Personalize Your Letter Writing, Virginia Kirkpatrick, page 15 Behind Bright Jackets, Marjorie Thomas, page 16 Coed Concoctions, Marian Dougan, page 18 Alums in the News, Bette Simpson, page 20 Give Beauty a Chance, Ida Halpin, page 22 Journalistic Spindles, Ruth Jensen, page 2

Systemic, local, and imaging biomarkers of brain injury: more needed, and better use of those already established?

Much progress has been made over the past two decades in the treatment of severe acute brain injury, including traumatic brain injury and subarachnoid hemorrhage, resulting in a higher proportion of patients surviving with better outcomes. This has arisen from a combination of factors. These include improvements in procedures at the scene (pre-hospital) and in the hospital emergency department, advances in neuromonitoring in the intensive care unit, both continuously at the bedside and intermittently in scans, evolution and refinement of protocol-driven therapy for better management of patients, and advances in surgical procedures and rehabilitation. Nevertheless, many patients still experience varying degrees of long-term disabilities post-injury with consequent demands on carers and resources, and there is room for improvement. Biomarkers are a key aspect of neuromonitoring. A broad definition of a biomarker is any observable feature that can be used to inform on the state of the patient, e.g., a molecular species, a feature on a scan, or a monitoring characteristic, e.g., cerebrovascular pressure reactivity index. Biomarkers are usually quantitative measures, which can be utilized in diagnosis and monitoring of response to treatment. They are thus crucial to the development of therapies and may be utilized as surrogate endpoints in Phase II clinical trials. To date, there is no specific drug treatment for acute brain injury, and many seemingly promising agents emerging from pre-clinical animal models have failed in clinical trials. Large Phase III studies of clinical outcomes are costly, consuming time and resources. It is therefore important that adequate Phase II clinical studies with informative surrogate endpoints are performed employing appropriate biomarkers. In this article, we review some of the available systemic, local, and imaging biomarkers and technologies relevant in acute brain injury patients, and highlight gaps in the current state of knowledge.We gratefully acknowledge financial support as follows. Research support: the Medical Research Council (MRC, Grant Nos. G0600986 ID79068 and G1002277 ID98489) and the National Institute for Health Research Biomedical Research Centre (NIHR BRC) Cambridge (Neuroscience Theme; Brain Injury and Repair Theme). Authors’ support: Keri Linda H. Carpenter – NIHR BRC Cambridge (Neuroscience Theme; Brain Injury and Repair Theme); Ibrahim Jalloh – MRC (Grant no. G1002277 ID 98489) and NIHR BRC Cambridge; Adel Helmy – MRC/Royal College of Surgeons of England Clinical Research Training Fellowship (Grant no. G0802251) and Raymond and Beverly Sackler Fellowship; Virginia F. J. Newcombe–Health Foundation/Academy of Medical Sciences Clinician Scientist Fellowship; Richard J. Shannon–NIHR BRC (Neuroscience Theme; Brain Injury and Repair Theme); Angelos G. Kolias–Royal College of Surgeons of England Research Fellowship, NIHR Academic Clinical Fellowship, and a Raymond and Beverly Sackler Studentship; David Krishna Menon–NIHR Senior Investigator Award; Peter J. Hutchinson – NIHR Research Professorship, Academy of Medical Sciences/Health Foundation Senior Surgical Scientist Fellowship.This is the final published version. It first appeared at http://journal.frontiersin.org/article/10.3389/fneur.2015.00026/full#h13