Developing bottom drifters to better understand the stranding locations of cold-stunned sea turtles in Cape Cod Bay, Massachusetts.

Every fall, juvenile sea turtles in the Northwest Atlantic Ocean are threatened by rapidly declining water temperatures. When sea turtles become hypothermic, or cold-stunned, they lose mobility-either at the surface, subsurface, or the bottom of the water column-and eventually strand at the shoreline where rescue teams associated with the Sea Turtle Stranding and Salvage Network may search for them. Understanding the effects of ocean currents on the potential stranding locations of cold-stunned sea turtles is essential to better understand stranding hotspots and increase the probability of successful discovery and recovery of turtles before they die in the cold temperatures. Traditional oceanographic drifters-instruments used to track currents-have been used to examine relationships between current and stranding locations in Cape Cod Bay, but these drifters are not representative of sea turtle morphology and do not assess how bottom currents affect stranding locations. To address these knowledge gaps, we designed new drifters that represent the shape and dimensions of sea turtles-one that can float at the surface and one that sinks to the bottom-to track both surface and bottom currents in Cape Cod Bay. We found a marked difference between the trajectories of our new drifter models and those that were previously used for similar research. These findings bring us one step closer to identifying the transport pathways for cold-stunned sea turtles and optimizing cold-stunned sea turtle search and rescue efforts in Cape Cod.

Non-marine turtle plays important functional roles in Indonesian ecosystems.

The Southeast Asian box turtle (Cuora amboinensis) is numerically the most important turtle exported from Indonesia. Listed as Vulnerable by the IUCN, this turtle is heavily harvested and exported for food and traditional medicine in China and for the pet trade primarily in the United States, Europe, and Japan. Despite its significance in global markets, relatively little is known about the species' ecology or importance to ecosystems. We conducted our research in a national park in Sulawesi, Indonesia, and our objectives were to quantify trophic breadth, capacity for seed dispersal between aquatic and terrestrial ecosystems, and whether ingestion of seeds by C. amboinensis enhances germination. We obtained diet samples from 200 individual turtles and found that the species is omnivorous, exhibiting an ontogenetic shift from more carnivorous to more omnivorous. Both subadults and adults scavenged on other vertebrates. In a seed passage experiment, turtles passed seeds for 2‒9 days after ingestion. Radio-tracked turtles moved, on average, about 35 m per day, indicating that seeds from ingested fruits, given seed passage durations, could be dispersed 70‒313 m from the parent tree and potentially between wetland and upland ecosystems. In a seed germination experiment, we found that ingestion of seeds by turtles enhanced germination, as compared with control seeds, for four of six plant species tested. Of these, two are common in the national park, making up a significant proportion of plant biomass in lowland swamp forest and around ephemeral pools in savanna, and are highly valued outside of the park for their lumber for construction of houses, furniture, and boats. Protection of C. amboinensis populations may be important for maintaining trophic linkages that benefit biodiversity, communities, and local economies.

Publisher Correction: Combining Biomarkers with EMR Data to Identify Patients in Different Phases of Sepsis.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

A microfluidic biochip platform for electrical quantification of proteins.

Sepsis, an adverse auto-immune response to an infection often causing life-threatening complications, results in the highest mortality and treatment cost of any illness in US hospitals. Several immune biomarker levels, including Interleukin 6 (IL-6), have shown a high correlation to the onset and progression of sepsis. Currently, no technology diagnoses and stratifies sepsis progression using biomarker levels. This paper reports a microfluidic biochip platform to detect proteins in undiluted human plasma samples. The device uses a differential enumeration platform that integrates Coulter counting principles, antigen specific capture chambers, and micro size bead based immunodetection to quantify cytokines. This microfluidic biochip was validated as a potential point of care technology by quantifying IL-6 from plasma samples (n = 29) with good correlation (R2 = 0.81) and agreement (Bland-Altman) compared to controls. In combination with previous applications, this point of care platform can potentially detect cell and protein biomarkers simultaneously for sepsis stratification.

Combining Biomarkers with EMR Data to Identify Patients in Different Phases of Sepsis.

Sepsis is a leading cause of death and is the most expensive condition to treat in U.S. hospitals. Despite targeted efforts to automate earlier detection of sepsis, current techniques rely exclusively on using either standard clinical data or novel biomarker measurements. In this study, we apply machine learning techniques to assess the predictive power of combining multiple biomarker measurements from a single blood sample with electronic medical record data (EMR) for the identification of patients in the early to peak phase of sepsis in a large community hospital setting. Combining biomarkers and EMR data achieved an area under the receiver operating characteristic (ROC) curve (AUC) of 0.81, while EMR data alone achieved an AUC of 0.75. Furthermore, a single measurement of six biomarkers (IL-6, nCD64, IL-1ra, PCT, MCP1, and G-CSF) yielded the same predictive power as collecting an additional 16 hours of EMR data(AUC of 0.80), suggesting that the biomarkers may be useful for identifying these patients earlier. Ultimately, supervised learning using a subset of biomarker and EMR data as features may be capable of identifying patients in the early to peak phase of sepsis in a diverse population and may provide a tool for more timely identification and intervention.

Incidence of chronic lymphocytic leukemia and monoclonal B-cell lymphocytosis in Calgary, Alberta, Canada.

This study provides an update on the incidence of chronic lymphocytic leukemia (CLL) and monoclonal B-cell lymphocytosis (MBL) in a major Canadian city using the 2008 World Health Organization (WHO) diagnostic criteria. Incidence calculations were performed using data from a centralized flow cytometry laboratory servicing southern Alberta, Canada. The age-standardized incidence of 4.01 cases of CLL per 100,000 person-years is nearly half the rate previously reported in Canada. Compared to previous criteria based on absolute lymphocyte count rather than absolute B-cell count, utilizing the 2008 WHO criteria resulted in a 47.6% decline in CLL incidence (8.42 cases per 100,000 using 1996 criteria). As a consequence, MBL rates are 64% higher. In contrast to 1996 criteria showing a peak CLL incidence between ages 70-74, age-specific incidence rates show a continuous increase with advancing age using the 2008 guidelines. We also report a higher male to female ratio of CLL than previous Canadian reports (1.80:1). CLL incidence in southern Alberta is lower than rates recently reported in the United States using the same criteria. This difference may be due in part to the low median age and the lower proportion of persons of Caucasian European ancestry present in our study population.

A classification tree approach for improving the utilization of flow cytometry testing of blood specimens for B-cell non-Hodgkin lymphoproliferative disorders.

We sought to improve the diagnostic efficiency of flow cytometry investigation on blood by developing data-driven ordering guidelines. Our goal was to improve flow cytometry utilization by decreasing negative testing, therefore reducing healthcare costs. We investigated several laboratory tests performed alongside flow cytometry to identify biomarkers useful in excluding non-leukemic bloods. Test results and patient demographic features were subjected to receiver-operator characteristic (ROC) curve, logistic regression and classification tree analyses to find significant predictors and develop decision rules. Our data show that, in the absence of a compelling clinical indication, flow cytometry testing is largely non-informative on bloods from patients less than 50 years of age having an absolute lymphocyte count (ALC) below 5.0 × 10(9)/L. For patients over age 50 having an ALC below this value, a ferritin value above 450 µg/L is counter-indicative of B-cell clonality. Using these guidelines, 26% of cases were correctly predicted as negative with greater than 97% accuracy.