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SUMMARY 1. The evaluation of the age and growth of animal populations is essential for understanding and predicting how populations will respond to changes in environmental conditions and anthropogenic stressors. 2. We used a novel, von Bertalanffy hierarchical modelling approach to quantify relationships between the growth of three freshwater mussel species and various site- and watershed-level factors including seasonal discharge, land cover and stream size in the lower Flint River Basin, Georgia, U.S.A. 3. Our modelling approach quantified the mussel-to-mussel variation in the von Bertalanffy parameters and accounted for biases associated with multiple measurements made on each mussel specimen, which are generally not accounted for as sources of bias in age and growth studies. 4. Modelling results suggested that maximum shell size parameter and the Brody growth coefficient varied across species, on average, 19 and 33%, respectively, among individual mussels within sample sites. The variation was related to short-term high streamflows during the spring season, stream size, channel geomorphology and land cover in the watershed. 5. This study provides insight to the factors affecting the growth of stream-dwelling freshwater mussels. Although hierarchical von Bertalanffy growth models are rarely used for freshwater mussel age and growth studies, this approach can provide important information regarding the ecology of freshwater mussels.

Objectives: The relationships between simple testicular sizes, including the testicular length, width, and depth and testicular function were evaluated to determine the usefulness of measuring these simple parameters. Methods: The mean of right and left testicular length, width and depth were measured in 408 men with infertility (mean age, 35.9 ± 5.3 years) using ultrasonography. The ultrasonographic testicular volumes were calculated as the length x width x depth x 0.71. To evaluate the relationship between the testicular size and function, the patients were divided into seven to ten groups according to each testicular size parameter. Results: The mean testicular volume, length, depth, and width were 13.4 ml, 3.86 cm, 1.80 cm, and 2.59 cm, respectively. These three testicular dimensions significantly correlated with sperm density, total sperm count, total motile sperm count, serum follicle-stimulating hormone and luteinizing hormone equal to ultrasonographic testicular volume. The mean sperm density was in the oligozoospermic range in patients with a mean testicular volume below 10 ml, a mean length below 3.5 cm, a mean depth below 1.75 cm, and a mean width below 2.5 cm. The mean total sperm count was subnormal in patients with a mean testicular volume below 10 ml, a mean length below 3.5 cm, a mean depth below 1.5 cm, and a mean width below 2.25 cm. Conclusions: The testicular length, width, and depth measured by ultrasonography significantly correlated with the testicular function as well as the ultrasonographic testicular volume. A simple measurement of the testicular length, width, and depth is useful for evaluating the testicular function.

Purpose: To introduce and investigate effective diameter ratios as a new patient metric for use in computed tomography protocol selection as a supplement to patient-specific size parameter data. Methods: The metrics of outer effective diameter and inner effective diameter were measured for 7 post-mortem subjects scanned with a standardized chest/abdomen/pelvis (CAP) protocol on a 320-slice MDCT scanner. The outer effective diameter was calculated by obtaining the anterior/posterior and lateral dimensions of the imaged anatomy at the middle of the scan range using Effective Diameter= SQRT(AP height*Lat Width). The inner effective diameter was calculated with the same equation using the AP and Lat dimensions of the anatomy excluding the adipose tissue. The ratio of outer to inner effective diameter was calculated for each subject. A relationship to BMI, weight, and CTDI conversion coefficients was investigated. Results: For the largest subject with BMI of 43.85 kg/m2 and weight of 255 lbs the diameter ratio was calculated as 1.33. For the second largest subject with BMI of 33.5 kg/m2 and weight of 192.4 lbs the diameter ratio was measured as 1.43, indicating a larger percentage of adipose tissue in the second largest subject’s anatomical composition. For the smallest subject at BMI of 17.4more » kg/m2 and weight of 86 lbs a similar tissue composition was indicated as a subject with BMI of 24.2 kg/m2 and weight of 136 lbs as they had the same diameter ratios of 1.11. Conclusion: The diameter ratio proves to contain information about anatomical composition that the BMI and weight alone do not. The utility of this metric is still being examined but could prove useful for determining MDCT techniques and for giving a more in depth detail of the composition of a patient’s body habitus.« less

A comparison of experimental diffusion coefficients in aqueous solutions of electrolytes with those calculated by Onsager-Fuoss and Pikal theories is presented. The influence of the ion size parameter a, “distance of closest approach” of ions, on the variation of diffusion coefficients with concentration is discussed.

Purpose: AAPM Task Group (TG) 204 described the Size‐Specific Dose Estimate (SSDE) using effective diameter (ED) as the size parameter in the conversion tables. The purpose of this investigation was to assess the effect on SSDE when a different size metric, water equivalent diameter (WED), was used with the conversion tables; and to compare these values to results from detailed Monte Carlo (MC) simulations. Methods: For a set of 101 thoracic and 82 abdomen/pelvis scans, including adult and pediatric patients, both ED and WED were calculated at the middle of the scan length. Each size metric was used as the input value to the SSDE conversion tables in TG204 to obtain two sets of SSDE values (SSDEED and SSDEWED). Additionally, voxelized patient models were generated from original scans and used in MC simulations to estimate dose to liver, spleen, and kidneys in the abdomen/pelvis, as well as lung and glandular breast tissue in the thoracic examinations under fixed tube current mode. SSDEED, SSDEWED were compared to organ doses by calculating percent differences and Root Mean Square errors. Results: For the abdomen, SSDEED and SSDEWED resulted in different RMSE from organ dose (for kidneys 8.8% and 6.4%, respectively) while SSDEWED demonstrated higher correlation with kidney dose than SSDEED (0.89 and 0.78, respectively). Similarly, for thorax, SSDEED and SSDEWED showed different RMSE (for lung 17.0% and 13.1%, respectively), with higher correlation for SSDEWED than SSDEED (0.92 and 0.78, respectively). Conclusion: Generated conversion factors based on ED appear to be applicable to WED and as originally assumed using WED not only improves dose estimates in the thorax but it also improves estimates in the abdomen. It is worth mentioning that these conclusions only apply to fixed tube current examinations while for tube current modulated (TCM) exams new set of conversion factors are recommended. Dr. Michael McNitt‐Gray Institutional research agreement, Siemens AG Recipient research support Siemens AG Consultant, Flaherty Sensabaugh Bonasso PLLC Consultant, Fulbright and Jaworski, LLC Maryam Khatonabadi: ipient research support Siemens AG