A data processing module for acoustic doppler current meters

This report describes the development of a Data Processing Module (DPM) designed for use with an RD Instruments Acoustic Doppler Current Meter (ADCM). The DPM is a self-powered unit in its own pressure case and its use requires no modification to the current meter. The motivation for this work was the desire for real-time monitoring and data transmission from an ADCM deployed at a remote site. The DPM serves as an interface between the ADCM and a satellite telemetry package consisting of a controller, an Argos Platform Transmit Terminal, and an antenna. The DPM accepts the data stream from the ADCM, processes the data and sends out the processed data upon request from the telemetry controller. The output of the ADCM is processed by eliminating unnecessary data combining quality control information into a small number of summary parameters, and averaging the remaining data in depth and time. For the implementation described here, eight data records of 719 bytes each, output from the ADCM at 15 minute intervals, were processed and averged over 2 hr intervals to produce a 34 byte output array.Funding was provided by the Office of Naval Research under Contract No. N00014-89-J-1288

Ariel - Volume 10 Number 3

Executive Editors Madalyn Schaefgen David Reich Business Manager David Reich News Editors Medical College Edward Zurad CAHS John Guardiani World Mark Zwanger Features Editors Meg Trexler Jim O\u27Brien Editorials Editor Jeffrey Banyas Photography and Sports Editor Stuart Singer Commons Editor Brenda Peterso

Nuclear microenvironments modulate transcription from low-affinity enhancers

Transcription factors bind low-affinity DNA sequences for only short durations. It is not clear how brief, low-affinity interactions can drive efficient transcription. Here, we report that the transcription factor Ultrabithorax (Ubx) utilizes low-affinity binding sites in the Drosophila melanogaster shavenbaby (svb) locus and related enhancers in nuclear microenvironments of high Ubx concentrations. Related enhancers colocalize to the same microenvironments independently of their chromosomal location, suggesting that microenvironments are highly differentiated transcription domains. Manipulating the affinity of svb enhancers revealed an inverse relationship between enhancer affinity and Ubx concentration required for transcriptional activation. The Ubx cofactor, Homothorax (Hth), was co-enriched with Ubx near enhancers that require Hth, even though Ubx and Hth did not co-localize throughout the nucleus. Thus, microenvironments of high local transcription factor and cofactor concentrations could help low-affinity sites overcome their kinetic inefficiency. Mechanisms that generate these microenvironments could be a general feature of eukaryotic transcriptional regulation

Electromagnetic induced transparency and slow light in interacting quantum degenerate atomic gases

We systematically develop the full quantum theory for the electromagnetic induced transparency (EIT) and slow light properties in ultracold Bose and Fermi gases. It shows a very different property from the classical theory which assumes frozen atomic motion. For example, the speed of light inside the atomic gases can be changed dramatically near the Bose-Einstein condensation temperature, while the presence of the Fermi sea can destroy the EIT effect even at zero temperature. From experimental point of view, such quantum EIT property is mostly manifested in the counter-propagating excitation schemes in either the low-lying Rydberg transition with a narrow line width or in the D2 transitions with a very weak coupling field. We further investigate the interaction effects on the EIT for a weakly interacting Bose-Einstein condensate, showing an inhomogeneous broadening of the EIT profile and nontrivial change of the light speed due to the quantum many-body effects beyond mean field energy shifts.Comment: 7 figure

In silico design and performance of peptide microarrays for breast cancer tumour-auto-antibody testing

The simplicity and potential of minimally invasive testing using sera from patients makes auto-antibody based biomarkers a very promising tool for use in cancer diagnostics. Protein microarrays have been used for the identification of such auto-antibody signatures. Because high throughput protein expression and purification is laborious, synthetic peptides might be a good alternative for microarray generation and multiplexed analyses. In this study, we designed 1185 antigenic peptides, deduced from proteins expressed by 642 cDNA expression clones found to be sero-reactive in both breast tumour patients and controls. The sero-reactive proteins and the corresponding peptides were used for the production of protein and peptide microarrays. Serum samples from females with benign and malignant breast tumours and healthy control sera (n=16 per group) were then analysed. Correct classification of the serum samples on peptide microarrays were 78% for discrimination of ‘malignant versus healthy controls’, 72% for ‘benign versus malignant’ and 94% for ‘benign versus controls’. On protein arrays, correct classification for these contrasts was 69%, 59% and 59%, respectively. The over-representation analysis of the classifiers derived from class prediction showed enrichment of genes associated with ribosomes, spliceosomes, endocytosis and the pentose phosphate pathway. Sequence analyses of the peptides with the highest sero-reactivity demonstrated enrichment of the zinc-finger domain. Peptides’ sero-reactivities were found negatively correlated with hydrophobicity and positively correlated with positive charge, high inter-residue protein contact energies and a secondary structure propensity bias. This study hints at the possibility of using in silico designed antigenic peptide microarrays as an alternative to protein microarrays for the improvement of tumour auto-antibody based diagnostics

Evaluation of auto-antibody serum biomarkers for breast cancer screening and in silico analysis of sero-reactive proteins

Aberrantly expressed proteins in tumours evoke an immunological response. These immunogenic proteins can serve as potential biomarkers for the early diagnosis of cancers. In this study, we performed a candidate marker screen on macroarrays containing 38,016 human proteins, derived from a human fetal-brain expression library, with the pools of sera from breast cancer patients (1 pool of benign samples, 3 pools of ductal carcinoma and 2 pools of lobular carcinoma) and 1 pool of sera from healthy women. A panel of 642 sero-reactive clones were deduced from these macroarray experiments which include 284 in-frame clones. Over-representation analyses of the sero-reactive in-frame clones enabled the identification of the sets of genes over-expressed in various pathways of the functional categories (KEGG, Transpath, Pfam and GO). Protein microarrays, generated using the His-tag proteins derived from the macroarray experiments, were used to evaluate the sera from breast cancer patients (24 malignant, 16 benign) and 20 control individuals. Using the PAM algorithm we elucidated a panel of 50 clones which enabled the correct classification prediction of 93% of the breast-nodule positive group (benign & malignant) sera from healthy individuals’ sera with 100% sensitivity and 85% specificity. This was followed by over-representation analysis of the significant clones derived from the class prediction

Stratification of HPV-induced cervical pathology using the virally encoded molecular marker E4 in combination with p16 or MCM.

High-risk human papillomavirus (HPV) types cause cervical lesions of varying severity, ranging from transient productive infections to high-grade neoplasia. Disease stratification requires the examination of lesional pathology, and possibly also the detection of biomarkers. P16(INK4a) and MCM are established surrogates of high-risk HPV E6/E7 activity, and can be extensively expressed in high-grade lesions. Here we have combined these two cellular biomarkers with detection of the abundant HPV-encoded E4 protein in order to identify both productive and transforming lesions. This approach has allowed us to distinguish true papillomavirus infections from similar pathologies, and has allowed us to divide the heterogeneous CIN2 category into those that are CIN1-like and express E4, and those that more closely resemble nonproductive CIN3. To achieve this, 530 lesional areas were evaluated according to standard pathology criteria and by using a multiple staining approach that allows us to superimpose biomarker patterns either singly or in combination onto an annotated hematoxylin and eosin (H&E) image. Conventional grading of neoplasia was established by review panel, and compared directly with the composite molecular pathology visualized on the same tissue section. The detection of E4 coincided with the onset of vacuolation, becoming abundant in koilocytes as the MCM marker declined and cells lost their defined nuclear margins as visualized by standard H&E staining. Of the dual marker approaches, p16(INK4a) and E4 appeared most promising, with E4 generally identifying areas of low-grade disease even when p16(INK4a) was present. Extensive p16(INK4a) expression usually coincided with an absence of E4 expression or its focal retention in sporadic cells within the lesion. Our results suggest that a straightforward molecular evaluation of HPV life-cycle deregulation in cervical neoplasia may help improve disease stratification, and that this can be achieved using complementary molecular biomarker pairs such as MCM/E4 or, more promisingly, p16(INK4a)/E4 as an adjunct to conventional pathology.JD, HG, YS, and ZW were funded by the UK Medical Research Council. RvB was funded by the Stichting Pathologie Ontwikkeling en Onderzoek (SPOO) Foundation, The Netherlands.This is the author accepted manuscript. The final version is available via NPG at http://www.nature.com/modpathol/journal/vaop/ncurrent/full/modpathol201552a.html#ack