Similar Levels Of Correlation Research Articles

Relationship between brook charr (Salvelinus fontinalis) eDNA concentration and angling data in structured wildlife areas

AbstractAccurate management of exploited fish populations is essential to ensure their long‐term sustainability. The use of eDNA as a tool for providing information on population relative abundance offers much potential although few examples in a fishery context have been documented. In this study, we collected 600 water samples from 30 lakes in Québec (Canada) to document the relationship between brook charr (Salvelinus fontinalis) angling data and their lake's eDNA concentration. Model selection with angling data and environmental parameters was used to find the best predictive model for eDNA concentration. We found a strong correlation between the average fish density from current and previous years (fish harvested/ha, adj. R2 = 0.76) with the mean eDNA concentration among lakes, supporting the growing trends in the literature. We observed very similar levels of correlation either when eDNA and angling data were from the same year or different years. We also found a pronounced inter‐year difference in lakes' eDNA quantity measured in 2019 and 2020. We hypothesize that the main drivers for this difference were inter‐seasonal variation including water temperature and associated variation in fish behavior. These results support the usefulness of eDNA as a quantitative tool for exploited fish populations.

Can We Trust Real Time Measurements of Lung Deposited Surface Area Concentrations in Dust from Powder Nanomaterials?

A comparison between various methods for real-time measurements of lung deposited surface area (LDSA) using spherical particles and powder dust with specific surface area ranging from 0.03 to 112 m 2 g –1 was conducted. LDSA concentrations measured directly using Nanoparticle Surface Area Monitor (NSAM) and Aerotrak and were compared to LDSA concentrations recalculated from size distribution measurements using Electrical Low Pressure Impactor (ELPI) and Fast Mobility Particle Sizer (FMPS). FMPS and ELPI measurements were also compared to dust surface area concentrations estimated from gravimetrical filter measurements and specific surface areas. Measurement of LDSA showed very good correlation in measurements of spherical particles (R 2 > 0.97, Ratio 1.0 to 1.04). High surface area nanomaterial powders showed a fairly reliable correlation between NSAM and Aerotrak (R 2 0.73– 0.93) and a material-dependent offset in the ratios (1.04–2.8). However, the correlation and ratio were inconsistent for lower LDSA concentrations. Similar levels of correlation were observed for the NSAM and the FMPS for high surface area materials, but with the FMPS overestimating the LDSA concentration. The ELPI showed good correlation with NSAM data for high LDSA materials (R 2 0.87–0.93), but not for lower LDSA concentrations (R 2 0.50–0.72). Comparisons of respirable dust surface area from ELPI data correlated well (R 2 > 0.98) with that calculated from filter samples, but materials-specific exceptions were present. We conclude that there is currently insufficient reliability and comparability between methods in the measurement of LDSA concentrations. Further development is required to enable use of LDSA for reliable dose metric and regulatory enforcement of exposure.

Airborne laser scanning and digital stereo imagery measures of forest structure: comparative results and implications to forest mapping and inventory update

Airborne laser scanning (ALS) has demonstrated utility for forestry applications and has renewed interest in other forms of remotely sensed data, especially those that capture three-dimensional (3-D) forest characteristics. One such data source results from the advanced processing of high spatial resolution digital stereo imagery (DSI) to generate 3-D point clouds. From the derived point cloud, a digital surface model and forest vertical information with similarities to ALS can be generated. A key consideration is that when developing forestry related products such as a canopy height model (CHM), a high spatial resolution digital terrain model (DTM), typically from ALS, is required to normalize DSI elevations to heights above ground. In this paper we report on our investigations into the use of DSI-derived vertical information for capturing variations in forest structure and compare these results to those acquired using ALS. An ALS-derived DTM was used to provide the spatially detailed ground surface elevations to normalize DSI-derived heights. Similar metrics were calculated from the vertical information provided by both DSI and ALS. Comparisons revealed that ALS metrics provided a more detailed characterization of the canopy surface including canopy openings. Both DSI and ALS metrics had similar levels of correlation with forest structural attributes (e.g., height, volume, and biomass). DSI-based models predicted height, diameter, basal area, stem volume, and biomass with root mean square (RMS) accuracies of 11.2%, 21.7%, 23.6%, 24.5%, and 23.7%, respectively. The respective accuracies for the ALS-based predictions were 7.8%, 19.1%, 17.8%, 17.9%, and 17.5%. Change detection between ALS-derived CHM (time 1) and DSI-derived CHM (time 2) provided change estimates that demonstrated good agreement (r = 0.71) with two-date, ALS only, change outputs. For the single-layered, even-aged stands under investigation in this study, the DSI-derived vertical information is an appropriate and cost-effective data source for estimating and updating forest information. The accuracy of DSI information is based on a capability to measure the height of the upper canopy envelope with performance analogous to ALS. Forest attributes that are well captured and subsequently modeled from height metrics are best suited to estimation from DSI metrics, whereas ALS is more suitable for capturing stand density. Further investigation is required to better understand the performance of DSI-derived height products in more complex forest environments. Furthermore, the difference in variance captured between ALS and DSI-derived CHM also needs to be better understood in the context of change detection and inventory update considerations.

Correlation between direct ELISA, single epitope-based inhibition ELISA and Pseudovirion-based neutralization assay for measuring anti-HPV-16 and anti-HPV-18 antibody response after vaccination with the AS04-adjuvanted HPV-16/18 cervical cancer vaccine

To monitor immune status during clinical trials and after vaccine registration, several assays have been developed to measure type-specific human papillomavirus (HPV) serum antibody levels. These include neutralization assays, single epitope-based inhibition immunoassays, and direct enzyme-linked immunosorbent assays (ELISAs). Neutralization assays based on multiple epitopes and independent of vaccine material are considered the ‘gold standard’ for unbiased assessment of the protective potential of vaccine-induced antibodies. However, their use in large clinical trials is challenging. Here, we compare both the direct ELISA and the single epitope-based inhibition ELISA with the pseudovirion-based neutralization assay (PBNA) for HPV-16/18 antibody responses in vaccinated women enrolled in trials of Cervarix™, GSK's cervical cancer vaccine. The direct ELISA, which is based on multiple epitopes, was shown to have a higher degree of sensitivity and correlation with the PBNA when compared with the single epitope-based inhibition ELISA. Among double-positive results, high correlations were observed between the PBNA and the direct ELISA (0.70-0.88 for HPV-16 and 0.82-0.94 for HPV-18) and also with the single epitope-based inhibition ELISA (0.60-0.89 for HPV-16 and 0.57-0.96 for HPV-18) in women aged 15-25 years. The correlation persisted up to 6.4 years after primary vaccination. Similar levels of correlation were observed for adolescents aged 10-14 years and women aged 46-55 years. Therefore, the direct ELISA appears to be an excellent surrogate for neutralizing activity and can be used to evaluate antibody response induced by L1 VLP-based cervical cancer vaccines, regardless of time elapsed after vaccination (up to 6.4 years) and the age of the vaccine recipient.

The Relationship between Personality and the Symptoms of Depressive Illness

The Maudsley Personality Inventory and the Beck Depression Inventory, with additional items to assess depressive functional shift features and outlook on life values, were administered to 100 patients diagnosed as suffering from depressive illness. Patients' scores for questions eliciting information about symptoms assumed to be dependent on personality correlated at substantial and significant levels with N scale scores of the Maudsley Personality Inventory. Similar levels of correlation were found for the added items for assessing life values. Items believed to assess changes in functions independent of personality, such as the features of the Depressive Functional Shift, showed no correlation with either N or E scales of the Maudsley Personality Inventory, while demonstrating a substantial level of correlation with the depression scale. It is concluded that whereas changes in innate biological functions independent of environment are direct indications of the depressive illness process, psychological symptoms of the illness may reflect changes in personality dependent on upbringing, education and cultural background, thereby producing greater variation in this group of psychological symptoms.