A microchip optomechanical accelerometer

The monitoring of accelerations is essential for a variety of applications ranging from inertial navigation to consumer electronics. The basic operation principle of an accelerometer is to measure the displacement of a flexibly mounted test mass; sensitive displacement measurement can be realized using capacitive, piezo-electric, tunnel-current, or optical methods. While optical readout provides superior displacement resolution and resilience to electromagnetic interference, current optical accelerometers either do not allow for chip-scale integration or require bulky test masses. Here we demonstrate an optomechanical accelerometer that employs ultra-sensitive all-optical displacement read-out using a planar photonic crystal cavity monolithically integrated with a nano-tethered test mass of high mechanical Q-factor. This device architecture allows for full on-chip integration and achieves a broadband acceleration resolution of 10 \mu g/rt-Hz, a bandwidth greater than 20 kHz, and a dynamic range of 50 dB with sub-milliwatt optical power requirements. Moreover, the nano-gram test masses used here allow for optomechanical back-action in the form of cooling or the optical spring effect, setting the stage for a new class of motional sensors.Comment: 16 pages, 9 figure

Constraints on Non-Newtonian Gravity from Recent Casimir Force Measurements

Corrections to Newton's gravitational law inspired by extra dimensional physics and by the exchange of light and massless elementary particles between the atoms of two macrobodies are considered. These corrections can be described by the potentials of Yukawa-type and by the power-type potentials with different powers. The strongest up to date constraints on the corrections to Newton's gravitational law are reviewed following from the E\"{o}tvos- and Cavendish-type experiments and from the measurements of the Casimir and van der Waals force. We show that the recent measurements of the Casimir force gave the possibility to strengthen the previously known constraints on the constants of hypothetical interactions up to several thousand times in a wide interaction range. Further strengthening is expected in near future that makes Casimir force measurements a prospective test for the predictions of fundamental physical theories.Comment: 20 pages, crckbked.cls is used, to be published in: Proceedings of the 18th Course of the School on Cosmology and Gravitation: The Gravitational Constant. Generalized Gravitational Theories and Experiments (30 April- 10 May 2003, Erice). Ed. by G. T. Gillies, V. N. Melnikov and V. de Sabbata, 20pp. (Kluwer, in print, 2003

Gene prediction in metagenomic fragments: A large scale machine learning approach

<p>Abstract</p> <p>Background</p> <p>Metagenomics is an approach to the characterization of microbial genomes via the direct isolation of genomic sequences from the environment without prior cultivation. The amount of metagenomic sequence data is growing fast while computational methods for metagenome analysis are still in their infancy. In contrast to genomic sequences of single species, which can usually be assembled and analyzed by many available methods, a large proportion of metagenome data remains as unassembled anonymous sequencing reads. One of the aims of all metagenomic sequencing projects is the identification of novel genes. Short length, for example, Sanger sequencing yields on average 700 bp fragments, and unknown phylogenetic origin of most fragments require approaches to gene prediction that are different from the currently available methods for genomes of single species. In particular, the large size of metagenomic samples requires fast and accurate methods with small numbers of false positive predictions.</p> <p>Results</p> <p>We introduce a novel gene prediction algorithm for metagenomic fragments based on a two-stage machine learning approach. In the first stage, we use linear discriminants for monocodon usage, dicodon usage and translation initiation sites to extract features from DNA sequences. In the second stage, an artificial neural network combines these features with open reading frame length and fragment GC-content to compute the probability that this open reading frame encodes a protein. This probability is used for the classification and scoring of gene candidates. With large scale training, our method provides fast single fragment predictions with good sensitivity and specificity on artificially fragmented genomic DNA. Additionally, this method is able to predict translation initiation sites accurately and distinguishes complete from incomplete genes with high reliability.</p> <p>Conclusion</p> <p>Large scale machine learning methods are well-suited for gene prediction in metagenomic DNA fragments. In particular, the combination of linear discriminants and neural networks is promising and should be considered for integration into metagenomic analysis pipelines. The data sets can be downloaded from the URL provided (see Availability and requirements section).</p

Clinical significance of altered nm23-H1, EGFR, RB and p53 expression in bilharzial bladder cancer

<p>Abstract</p> <p>Background</p> <p>Clinical characterization of bladder carcinomas is still inadequate using the standard clinico-pathological prognostic markers. We assessed the correlation between <it>nm23-H1</it>, <it>Rb, EGFR </it>and <it>p53 </it>in relation to the clinical outcome of patients with muscle invasive bilharzial bladder cancer (MI-BBC).</p> <p>Methods</p> <p><it>nm23-H1</it>, <it>Rb, EGFR and p53 </it>expression was assessed in 59 MI-BBC patients using immunohistochemistry and reverse transcription (RT-PCR) and was correlated to the standard clinico-pathological prognostic factors, patient's outcome and the overall survival (OS) rate.</p> <p>Results</p> <p>Overexpression of <it>EGFR </it>and <it>p53 </it>proteins was detected in 66.1% and 35.6%; respectively. Loss of <it>nm23-H1</it>and <it>Rb </it>proteins was detected in 42.4% and 57.6%; respectively. Increased <it>EGFR and </it>loss of <it>nm23-H1 </it>RNA were detected in 61.5% and 36.5%; respectively. There was a statistically significant correlation between <it>p53 </it>and <it>EGFR </it>overexpression (<it>p </it>< 0.0001), <it>nm23 </it>loss (protein and RNA), lymph node status (<it>p </it>< 0.0001); between the incidence of local recurrence and <it>EGFR </it>RNA overexpression (p= 0.003) as well as between the incidence of metastasis and altered <it>Rb </it>expression (<it>p </it>= 0.026), <it>p53 </it>overexpression (<it>p </it>< 0.0001) and mutation (<it>p </it>= 0.04). Advanced disease stage correlated significantly with increased <it>EGFR </it>(protein and RNA) (<it>p </it>= 0.003 & 0.01), reduced <it>nm23-H1 </it>RNA (<it>p </it>= 0.02), altered <it>Rb </it>(<it>p </it>= 0.023), and <it>p53 </it>overexpression (<it>p </it>= 0.004). OS rates correlated significantly, in univariate analysis, with <it>p53 </it>overexpression (<it>p </it>= 0.011), increased <it>EGFR </it>(protein and RNA, <it>p </it>= 0.034&0.031), <it>nm23-H1 RNA </it>loss (<it>p </it>= 0.021) and aberrations of ≥ 2 genes. However, multivariate analysis showed that only high <it>EGFR </it>overexpression, metastatic recurrence, high tumor grade and the combination of ≥ 2 affected markers were independent prognostic factors.</p> <p>Conclusion</p> <p><it>nm23-H1, EGFR </it>and <it>p53 </it>could be used as prognostic biomarkers in MI-BBC patients. In addition to the standard pathological prognostic factors, a combination of these markers (≥ 2) has synergistic effects in stratifying patients into variable risk groups. The higher is the number of altered biomarkers, the higher will be the risk of disease progression and death.</p

Clinical Use and Therapeutic Potential of IVIG/SCIG, Plasma-Derived IgA or IgM, and Other Alternative Immunoglobulin Preparations

Intravenous and subcutaneous immunoglobulin preparations, consisting of IgG class antibodies, are increasingly used to treat a broad range of pathological conditions, including humoral immune deficiencies, as well as acute and chronic inflammatory or autoimmune disorders. A plethora of Fab- or Fc-mediated immune regulatory mechanisms has been described that might act separately or in concert, depending on pathogenesis or stage of clinical condition. Attempts have been undertaken to improve the efficacy of polyclonal IgG preparations, including the identification of relevant subfractions, mild chemical modification of molecules, or modification of carbohydrate side chains. Furthermore, plasma-derived IgA or IgM preparations may exhibit characteristics that might be exploited therapeutically. The need for improved treatment strategies without increase in plasma demand is a goal and might be achieved by more optimal use of plasma-derived proteins, including the IgA and the IgM fractions. This article provides an overview on the current knowledge and future strategies to improve the efficacy of regular IgG preparations and discusses the potential of human plasma-derived IgA, IgM, and preparations composed of mixtures of IgG, IgA, and IgM

Multi-messenger observations of a binary neutron star merger

On 2017 August 17 a binary neutron star coalescence candidate (later designated GW170817) with merger time 12:41:04 UTC was observed through gravitational waves by the Advanced LIGO and Advanced Virgo detectors. The Fermi Gamma-ray Burst Monitor independently detected a gamma-ray burst (GRB 170817A) with a time delay of ~1.7 s with respect to the merger time. From the gravitational-wave signal, the source was initially localized to a sky region of 31 deg2 at a luminosity distance of 40+8-8 Mpc and with component masses consistent with neutron stars. The component masses were later measured to be in the range 0.86 to 2.26 Mo. An extensive observing campaign was launched across the electromagnetic spectrum leading to the discovery of a bright optical transient (SSS17a, now with the IAU identification of AT 2017gfo) in NGC 4993 (at ~40 Mpc) less than 11 hours after the merger by the One- Meter, Two Hemisphere (1M2H) team using the 1 m Swope Telescope. The optical transient was independently detected by multiple teams within an hour. Subsequent observations targeted the object and its environment. Early ultraviolet observations revealed a blue transient that faded within 48 hours. Optical and infrared observations showed a redward evolution over ~10 days. Following early non-detections, X-ray and radio emission were discovered at the transient’s position ~9 and ~16 days, respectively, after the merger. Both the X-ray and radio emission likely arise from a physical process that is distinct from the one that generates the UV/optical/near-infrared emission. No ultra-high-energy gamma-rays and no neutrino candidates consistent with the source were found in follow-up searches. These observations support the hypothesis that GW170817 was produced by the merger of two neutron stars in NGC4993 followed by a short gamma-ray burst (GRB 170817A) and a kilonova/macronova powered by the radioactive decay of r-process nuclei synthesized in the ejecta