Modeling Enterococcus densities measured by quantitative polymerase chain reaction and membrane filtration using environmental conditions at four Great Lakes beaches

Data collected by the US Environmental Protection Agency (EPA) during the summer months of 2003 and 2004 at four US Great Lakes beaches were analyzed using linear regression analysis to identify relationships between meteorological, physical water characteristics, and beach characteristics data and the fecal indicator bacteria, Enterococcus. Water samples were analyzed for Enterococcus densities by quantitative polymerase chain reaction (qPCR) and membrane filtration (MF). This paper investigates the ability of regression models to accurately predict Enterococcus densities above or below a threshold value, using environmental data on a beach-by-beach basis for both methods. The ability to create statistical models for real-time water quality analysis would allow beach managers to make more accurate decisions regarding beach safety. Results from linear regression models indicate that environmental factors explain more of the variability in Enterococcus densities measured by MF than Enterococcus densities measured by qPCR. Results also show that models for both methods did not perform well at predicting occurrences in which water quality levels exceeded a threshold.     

Online classification of single EEG trials during finger movements.

Many offline studies have explored the feasibility of EEG potentials related to single limb movements for a brain-computer interface (BCI) control signal. However, only few functional online single-trial BCI systems have been reported. We investigated whether inexperienced subjects could control a BCI accurately by means of visually-cued left versus right index finger movements, performed every 2 s, after only a 20-min training period. Ten subjects tried to move a circle from the center to a target location at the left or right side of the computer screen by moving their left or right index finger. The classifier was updated after each trial using the correct class labels, enabling up-to-date feedback to the subjects throughout the training. Therefore, a separate data collection session for optimizing the classification algorithm was not needed. When the performance of the BCI was tested, the classifier was not updated. Seven of the ten subjects were able to control the BCI well. They could choose the correct target in 84%-100% of the cases, 3.5-7.7 times a minute. Their mean single trial classification rate was 80% and bit rate 10 bits/min. These results encourage the development of BCIs for paralyzed persons based on detection of single-trial movement attempts.     

Infant mortality review as a vehicle for quality improvement in a local health department

BACKGROUND: Many communities across the United States have established fetal and infant mortality review (FIMR) programs as a way of gaining insight into the causes of such deaths and of devising and implementing ways to improve the health of pregnant women and their infants. IMR PROCESS: The IMR process in the Jefferson County Department of Health in Birmingham, Alabama, evolved in a somewhat different fashion than that in other communities. A technical review team reviews all the infant deaths in the county, with particular attention to each woman's pregnancy history. A community review team reviews composite cases that illustrate some particular problem that might lead to infant mortality, such as teenage pregnancy or short intervals between pregnancies. This team provides insights into cultural patterns and a community perspective on the problems. Recommendations from the two teams are acted on by the health department, with the assistance of other agencies as needed. IMPACT OF THE IMR PROCESS: The IMR process has been used to increase community agency participation in health department activities, improve health department procedures, increase health department staff acceptance of a new and controversial program (Healthy Start), and offer services to women who need them. CONCLUSIONS: IMR has become a mechanism for CQI in the health department, embodying many of the principles of CQI, including the use of teams, focus on a team mission, and examination of processes, not individuals. The program offers a model of how to reduce rates of fetal and infant mortality.     

Effect of a Mutant Danbaekkong Allele on Soybean Seed Yield,Protein, and Oil Concentration

There is a known negative correlation between soybean [Glycine max [L.] Merr.] seed protein and oil and between protein and yield. This challenges breeders to increase protein concentration while maintaining oil concentration and yield. The objective of this study was to determine if marker-assisted selection for the Danbaekkong (Dan) protein allele on chromosome 20 influences seed yield and quality traits in near isogenic genetic backgrounds. A population of 24 F₇-derived near isogenic lines (NIL) of soybean was created by crossing G03-3101 × LD00-2817P. The 24 NIL consisted of 12 wild type (WT) and 12 mutant Dan type lines. These NIL were grown in 2016 and 2017 field seasons in replicated field trials in nine environments, with six in Tennessee and one each in Arkansas, Missouri, and North Carolina. There were significant (P < 0.05) differences in yield, protein, and oil concentrations between the two experimental groups. The Dan group had significantly (P < 0.05) more protein (421 g kg⁻¹), less oil (192 g kg⁻¹), and lower yield (3143 kg ha⁻¹) than the WT group (390 g kg⁻¹ protein, 210 g kg⁻¹ oil, and 3281 kg ha⁻¹ yield). These results support previous research and corroborate the overall negative genetic correlations. Nevertheless, seed yield of several higher-protein Dan lines MC-13, MC-16, MC-19, and MC-24 exceeded seed yield of lower protein WT lines MC-2, MC-3, MC-6, and MC-10. The higher-protein lines represent genetic resources for reducing the negative correlation between protein and yield.     

Sensitivity of condition indices to changing density in a white-tailed deer population

The ways in which comprehensive condition profiles, incorporating morphometric, histologic, physiologic, and diet quality indices, responded to changes in density of a white-tailed deer (Odocoileus virginianus) population were examined. Changes in these condition indices were monitored in a northeastern Oklahoma deer herd as density declined from peaks of 80 and 72 deer/km2 in 1989 and 1990 (high-density) to lows of 39 and 41 deer/km2 in 1991 and 1992 (reduced-density), respectively. Compared to a reference population (6 deer/km2), deer sampled during high-density exhibited classic signs of nutritional stress such as low body and visceral organ masses (except elevated adrenal gland mass), low fecal nitrogen levels, reduced concentrations of serum albumin, elevated serum creatinine concentrations, and a high prevalence of parasitic infections. Although density declined by one half over the 4-yr study, gross indices of condition (in particular body mass and size) remained largely unchanged. However, selected organ masses, serum albumin and non-protein nitrogen constituents, and fecal nitrogen indices reflected improvements in nutritional status with reductions in density. Many commonly used indices of deer condition (fat reserves, hematocrit, total serum protein, and blood urea nitrogen) were not responsive to fluctuations in density.     

Kinetic Model for Signal Binding to the Quorum Sensing Regulator LasR

We propose a kinetic model for the activation of the las regulon in the opportunistic pathogen Pseudomonas aeruginosa. The model is based on in vitro data and accounts for the LasR dimerization and consecutive activation by binding of two OdDHL signal molecules. Experimentally, the production of the active LasR quorum-sensing regulator was studied in an Escherichia coli background as a function of signal molecule concentration. The functional activity of the regulator was monitored via a GFP reporter fusion to lasB expressed from the native lasB promoter. The new data shows that the active form of the LasR dimer binds two signal molecules cooperatively and that the timescale for reaching saturation is independent of the signal molecule concentration. This favors a picture where the dimerized regulator is protected against proteases and remains protected as it is activated through binding of two successive signal molecules. In absence of signal molecules, the dimerized regulator can dissociate and degrade through proteolytic turnover of the monomer. This resolves the apparent contradiction between our data and recent reports that the fully protected dimer is able to “degrade” when the induction of LasR ceases.     

Factors influencing the variation in tenderness of seven major beef muscles from three Angus and Brahman breed crosses

Beef carcasses (n=30) from 3/4 Angus (A)×1/4 Brahman (B), 1/4A×3/4B, and 1/2A×1/2B F(1) crosses were used to evaluate breed type, electrical stimulation, and postmortem aging on the M. semimembranosus (SM), M. semitendinosus (ST), M. biceps femoris (BF), M. vastus lateralis (VL), M. gluteus medius (GM), M. longissimus dorsi lumborum (LD), and M. triceps brachii (TB). Shear force values decreased with increased postmortem aging to a greater extent in steaks from 3/4A×1/4B than steaks from the other breed types. Shear force values for steaks from the round (SM, ST, BF, VL) were higher than steaks from the loin (LD, GM) and chuck (TB) for both electrically stimulated and non-electrically stimulated muscles. In the LD muscle, calpastatin activities were similar among breed types. Muscle type played the greatest role in determining tenderness.     

Automatic multi-modal intelligent seizure acquisition (MISA) system for detection of motor seizures from electromyographic data and motion data

The objective is to develop a non-invasive automatic method for detection of epileptic seizures with motor manifestations. Ten healthy subjects who simulated seizures and one patient participated in the study. Surface electromyography (sEMG) and motion sensor features were extracted as energy measures of reconstructed sub-bands from the discrete wavelet transformation (DWT) and the wavelet packet transformation (WPT). Based on the extracted features all data segments were classified using a support vector machine (SVM) algorithm as simulated seizure or normal activity. A case study of the seizure from the patient showed that the simulated seizures were visually similar to the epileptic one. The multi-modal intelligent seizure acquisition (MISA) system showed high sensitivity, short detection latency and low false detection rate. The results showed superiority of the multi-modal detection system compared to the uni-modal one. The presented system has a promising potential for seizure detection based on multi-modal data.