Antibiotic resistance and molecular characterization of bacteremia Escherichia coli isolates from newborns in the United States.

Background: Escherichia coli is a major cause of neonatal sepsis. Contemporary antibiotic resistance data and molecular characterization of neonatal E. coli bacteremia isolates in the US are limited.

Route of infection alters virulence of neonatal septicemia Escherichia coli clinical isolates.

Escherichia coli is the leading cause of Gram-negative neonatal septicemia in the United States. Invasion and passage across the neonatal gut after ingestion of maternal E. coli strains produce bacteremia.

Facilitation of trace metal uptake in cells by inulin coating of metallic nanoparticles.

Trace elements such as zinc and iron are essential for the proper function of biochemical processes, and their uptake and bioavailability are dependent on their chemical form. Supplementation of trace metals through nanostructured materials is a new field, but its application raises concerns regarding their toxicity. Here, we compared the intracellular zinc uptake of different sources of zinc: zinc sulfate, and ZnO and α-FeO@ZnO nanoparticles, coated or uncoated with inulin, an edible and biocompatible polysaccharide.

Scaling Up Endocrine Disruption Effects from Individuals to Populations: Outcomes Depend on How Many Males a Population Needs.

Assessing how endocrine disrupting compounds (EDCs) affect population dynamics requires tracking males and females (and sex-reversed individuals) separately. A key component in any sex-specific model is the "mating function" (the relationship between sex ratio and reproductive success) but this relationship is not known for any fish species. Using a model, we found that EDC effects on fish populations strongly depend upon the shape of the mating function.

Photosynthetic efficiency predicts toxic effects of metal nanomaterials in phytoplankton.

High Throughput Screening (HTS) using in vitro assessments at the subcellular level has great promise for screening new chemicals and emerging contaminants to identify high-risk candidates, but their linkage to ecological impacts has seldom been evaluated. We tested whether a battery of subcellular HTS tests could be used to accurately predict population-level effects of engineered metal nanoparticles (ENPs) on marine phytoplankton, important primary producers that support oceanic food webs. To overcome well-known difficulties of estimating ecologically meaningful toxicity parameters, we used novel Dynamic Energy Budget and Toxicodynamic (DEBtox) modeling techniques to evaluate impacts of ENPs on population growth rates.

Changes in Menidia beryllina Gene Expression and In Vitro Hormone-Receptor Activation After Exposure to Estuarine Waters Near Treated Wastewater Outfalls.

Fishes in estuarine waters are frequently exposed to treated wastewater effluent, among numerous other sources of contaminants, yet the impacts of these anthropogenic chemicals are not well understood in these dynamic and important waterways. Inland silversides (Menidia beryllina) at an early stage of development [12 days posthatch (dph)] were exposed to waters from two estuarine wastewater-treatment outfall locations in a tidal estuary, the Sacramento/San Joaquin Delta (California, USA) that had varied hydrology and input volumes. The genomic response caused by endocrine-disrupting compounds (EDCs) in these waters was determined using quantitative polymerase chain reaction on a suite of hormonally regulated genes.

Transcriptomic changes underlie altered egg protein production and reduced fecundity in an estuarine model fish exposed to bifenthrin.

Pyrethroid pesticides are a class of insecticides found to have endocrine disrupting properties in vertebrates such as fishes and in human cell lines. Endocrine disrupting chemicals (EDCs) are environmental contaminants that mimic or alter the process of hormone signaling. In particular, EDCs that alter estrogen and androgen signaling pathways are of major concern for fishes because these EDCs may alter reproductive physiology, behavior, and ultimately sex ratio.

Copper oxide and zinc oxide nanomaterials act as inhibitors of multidrug resistance transport in sea urchin embryos: their role as chemosensitizers.

The ability of engineered nanomaterials (NMs) to act as inhibitors of ATP-binding cassette (ABC) efflux transporters in embryos of white sea urchin (Lytechinus pictus) was studied. Nanocopper oxide (nano-CuO), nanozinc oxide (nano-ZnO), and their corresponding metal ions (CuSO4 and ZnSO4) were used as target chemicals. The results showed that nano-CuO, nano-ZnO, CuSO4, and ZnSO4, even at relatively low concentrations (0.

Dynamical learning and tracking of tremor and dyskinesia from wearable sensors.

We have developed and evaluated several dynamical machine-learning algorithms that were designed to track the presence and severity of tremor and dyskinesia with 1-s resolution by analyzing signals collected from Parkinson's disease (PD) patients wearing small numbers of hybrid sensors with both 3-D accelerometeric and surface-electromyographic modalities. We tested the algorithms on a 44-h signal database built from hybrid sensors worn by eight PD patients and four healthy subjects who carried out unscripted and unconstrained activities of daily living in an apartment-like environment. Comparison of the performance of our machine-learning algorithms against independent clinical annotations of disorder presence and severity demonstrates that, despite their differing approaches to dynamic pattern classification, dynamic neural networks, dynamic support vector machines, and hidden Markov models were equally effective in keeping error rates of the dynamic tracking well below 10%.

Cost, effectiveness and environmental relevance of multidrug transporters in sea urchin embryos.

ATP-binding cassette transporters protect cells via efflux of xenobiotics and endogenous byproducts of detoxification. While the cost of this ATP-dependent extrusion is known at the molecular level, i.e.

High-resolution tracking of motor disorders in Parkinson's disease during unconstrained activity.

Parkinson's disease (PD) can present with a variety of motor disorders that fluctuate throughout the day, making assessment a challenging task. Paper-based measurement tools can be burdensome to the patient and clinician and lack the temporal resolution needed to accurately and objectively track changes in motor symptom severity throughout the day. Wearable sensor-based systems that continuously monitor PD motor disorders may help to solve this problem, although critical shortcomings persist in identifying multiple disorders at high temporal resolution during unconstrained activity.

Dynamic SVM detection of tremor and dyskinesia during unscripted and unconstrained activities.

In this paper, we report an experimental comparison of dynamic support vector machines (SVMs) to dynamic neural networks (DNNs) in the context of a system for detecting dyskinesia and tremor in Parkinson's disease (PD) patients wearing accelerometer (ACC) and surface electromyographic (sEMG) sensors while performing unscripted and unconstrained activities of daily living. These results indicate that SVMs and DNNs of comparable computational complexities yield approximately identical performance levels when using an identical set of input features.

An approach to detecting estrogenic endocrine disruption via choriogenin expression in an estuarine model fish species.

A large body of work has established a link between endocrine disrupting compounds (EDCs) and a number of abnormalities in fishes. However, most EDC studies use several standard laboratory denizens to assess impacts, so assumptions about sensitivity are primarily based on these few species. Additionally, existing methods rely on obtaining sufficient plasma to measure EDC biomarkers.

Detecting freezing-of-gait during unscripted and unconstrained activity.

We present a dynamic neural network (DNN) solution for detecting instances of freezing-of-gait (FoG) in Parkinson's disease (PD) patients while they perform unconstrained and unscripted activities. The input features to the DNN are derived from the outputs of three triaxial accelerometer (ACC) sensors and one surface electromyographic (EMG) sensor worn by the PD patient. The ACC sensors are placed on the shin and thigh of one leg and on one of the forearms while the EMG sensor is placed on the shin.

What is IPUS and how does it help resolve biosignal complexity?

Integrated Processing and Understanding of Signals (IPUS) combines signal processing and artificial intelligence approaches to develop algorithms for resolving signal complexity. It has also led to development over the last decade and a half of software tools for supporting the algorithm design process. The signals to be analyzed are the superposition of temporally localized and temporally overlapping signal components from broadly defined signal classes pertinent to the given application.

Resolving signal complexities for ambulatory monitoring of motor function in Parkinson's disease.

Automatic tracking of movement disorders in patients with Parkinson's disease (PD) is dependent on the ability of machine learning algorithms to resolve the complex and unpredictable characteristics of wearable sensor data. The challenge reflects the variety of movement disorders that fluctuate throughout the day which can be confounded by voluntary activities of daily life. Our approach is the development of multiple dynamic neural network (DNN) classifiers whose application are governed by a rule-based controller within the Integrated Processing and Understanding of Signals (IPUS) framework.

Resolving signal complexities for ambulatory monitoring of motor function in Parkinson's disease.

Automatic tracking of movement disorders in patients with Parkinson's disease (PD) is dependent on the ability of machine learning algorithms to resolve the complex and unpredictable characteristics of wearable sensor data. The challenge reflects the variety of movement disorders that fluctuate throughout the day which can be confounded by voluntary activities of daily life. Our approach is the development of multiple dynamic neural network (DNN) classifiers whose application are governed by a rule-based controller within the Integrated Processing and Understanding of Signals (IPUS) framework.

Dynamic neural network detection of tremor and dyskinesia from wearable sensor data.

We present a dynamic neural network (DNN) solution for detecting time-varying occurrences of tremor and dyskinesia at 1 s resolution from time series data acquired from surface electromyographic (sEMG) sensors and tri-axial accelerometers worn by patients with Parkinson's disease (PD). The networks were trained and tested on separate datasets, each containing approximately equal proportions of tremor, dyskinesia, and disorder-free data from 8 PD and 4 control subjects performing unscripted and unconstrained activities in an apartment-like environment. During DNN testing, tremor was detected with a sensitivity of 93% and a specificity of 95%, while dyskinesia was detected with a sensitivity of 91% and a specificity of 93%.

A comparison of terahertz pulsed imaging with transmission microradiography for depth measurement of enamel demineralisation in vitro.

Terahertz pulsed imaging (TPI) is a relatively new, non-ionising and non-destructive imaging technique for studying hard tissues which does not require tooth section preparation, unlike transmission microradiography (TMR). If TPI can measure the depths of caries/demineralisation lesions accurately the same tooth samples could be reused and remeasured during in vitro and in situ studies on de- and/or re-mineralisation. The aim of this study was to compare TPI and TMR for measuring the depths of a range of artificially induced bovine enamel demineralised lesions in vitro.

The genome of the sea urchin Strongylocentrotus purpuratus.

We report the sequence and analysis of the 814-megabase genome of the sea urchin Strongylocentrotus purpuratus, a model for developmental and systems biology. The sequencing strategy combined whole-genome shotgun and bacterial artificial chromosome (BAC) sequences. This use of BAC clones, aided by a pooling strategy, overcame difficulties associated with high heterozygosity of the genome.

The sea urchin embryo as a model for studying efflux transporters: roles and energy cost.

We describe the use of the sea urchin as a model for studying efflux transporters and estimating energy cost for the cytotoxin protective system provided by these transporters. The unfertilized egg has low transport activity, which increases to a new steady state shortly after fertilization. Activity results from p-glycoprotein (p-gp) and MRP type transporters which protect the embryo from cytotoxic drugs that can disrupt cell division or induce apoptosis.

Simulating the response of terahertz radiation to basal cell carcinoma using ex vivo spectroscopy measurements.

Studies of basal cell carcinoma using terahertz pulsed imaging have revealed a significant difference between regions of tumor and healthy tissue. These differences are manifested in the reflected pulse due to what is thought to be changes in refractive index and absorption. We present measurements of the refractive index and absorption coefficient of excised normal tissue and basal cell carcinoma using terahertz (THz) transmission spectroscopy.

Stability of response characteristics of a Delphi panel: application of bootstrap data expansion.

Background: Delphi surveys with panels of experts in a particular area of interest have been widely utilized in the fields of clinical medicine, nursing practice, medical education and healthcare services. Despite this wide applicability of the Delphi methodology, there is no clear identification of what constitutes a sufficient number of Delphi survey participants to ensure stability of results.

Methods: The study analyzed the response characteristics from the first round of a Delphi survey conducted with 23 experts in healthcare quality and patient safety.

Nondestructive analysis of tablet coating thicknesses using terahertz pulsed imaging.

An understanding of the finished structure of complex pharmaceutical coating is becoming desirable, because tablet coatings are now one of the preferred routes to control the release of active pharmaceutical ingredients. There are few nondestructive techniques capable of examining the coatings of compressed tablets; for example laser induced breakdown spectroscopy has been used but this is a destructive method. Terahertz pulsed imaging offers a potential technique to examine coatings quickly and nondestructively.

Terahertz pulse imaging: a pilot study of potential applications in dentistry.

The improvement in the detection of caries offers the possibility for dramatic improvement in dental healthcare. Current caries detection rates suggest that there may be scope for improvement. This paper describes a preliminary study to examine applications of terahertz pulse imaging (TPI) to caries detection.