Mild pentachlorophenol-mediated uncoupling of mitochondria depletes ATP but does not cause an oxidized redox state or dopaminergic neurodegeneration in .

Aims: Mitochondrial dysfunction is implicated in several diseases, including neurological disorders such as Parkinson's disease. However, there is uncertainty about which of the many mechanisms by which mitochondrial function can be disrupted may lead to neurodegeneration. Pentachlorophenol (PCP) is an organic pollutant reported to cause mitochondrial dysfunction including oxidative stress and mitochondrial uncoupling.

Nonionic Ethoxylated Surfactants Induce Adipogenesis in 3T3-L1 Cells.

Recent studies have demonstrated that a number of environmental contaminants can act as metabolic disruptors and modulate metabolic function both in vitro and in vivo. 3T3-L1 mouse preadipocytes are commonly utilized to assess perturbations to adipogenesis, providing insight into environmental contaminants that may impact in vivo metabolic health. This study sought to assess whether various alkylphenol ethoxylates and alcohol ethoxylates (APEOs and AEOs, respectively), ubiquitous contaminants used in common household products, could disrupt metabolic health.

The Association Between Geographic Density of Infectious Disease Physicians and Limb Preservation in Patients With Diabetic Foot Ulcers.

Background: Avoiding major (above-ankle) amputation in patients with diabetic foot ulcers is best accomplished by multidisciplinary care teams with access to infectious disease specialists. However, access to infectious disease physicians is partially influenced by geography. We assessed the effect of living in a hospital referral region with a high geographic density of infectious disease physicians on major amputation for patients with diabetic foot ulcers.

Overcoming the Challenges of Unstructured Data in Multisite, Electronic Medical Record-based Abstraction.

Background: Unstructured data encountered during retrospective electronic medical record (EMR) abstraction has routinely been identified as challenging to reliably abstract, as these data are often recorded as free text, without limitations to format or structure. There is increased interest in reliably abstracting this type of data given its prominent role in care coordination and communication, yet limited methodological guidance exists.

Objectives: As standard abstraction approaches resulted in substandard data reliability for unstructured data elements collected as part of a multisite, retrospective EMR study of hospital discharge communication quality, our goal was to develop, apply and examine the utility of a phase-based approach to reliably abstract unstructured data.

Detection of pharmaceuticals and personal care products (PPCPs) in near-shore habitats of southern Lake Michigan.

Pharmaceuticals and personal care products (PPCPs) have been documented throughout the United States freshwaters but research has focused largely on lotic systems. Because PPCPs are designed to have a physiological effect, it is likely that they may also influence aquatic organisms. Thus, PPCPs may negatively impact aquatic ecosystems.

Using a triple-quadrupole mass spectrometer in accurate mass mode and an ion correlation program to identify compounds.

Atomic masses and isotopic abundances are independent and complementary properties for discriminating among ion compositions. The number of possible ion compositions is greatly reduced by accurately measuring exact masses of monoisotopic ions and the relative isotopic abundances (RIAs) of the ions greater in mass by +1 Da and +2 Da. When both properties are measured, a mass error limit of 6-10 mDa (< 31 ppm at 320 Da) and an RIA error limit of 10% are generally adequate for determining unique ion compositions for precursor and fragment ions produced from small molecules (less than 320 Da in this study).

Use of artificial neural networks for the accurate prediction of peptide liquid chromatography elution times in proteome analyses.

The use of artificial neural networks (ANNs) is described for predicting the reversed-phase liquid chromatography retention times of peptides enzymatically digested from proteome-wide proteins. To enable the accurate comparison of the numerous LC/MS data sets, a genetic algorithm was developed to normalize the peptide retention data into a range (from 0 to 1), improving the peptide elution time reproducibility to approximately 1%. The network developed in this study was based on amino acid residue composition and consists of 20 input nodes, 2 hidden nodes, and 1 output node.