Preliminary estimation of fat depth in the lamb short loin using a hyperspectral camera

© 2018 CSIRO. The objectives of the present study were to describe the approach used for classifying surface tissue, and for estimating fat depth in lamb short loins and validating the approach. Fat versus non-fat pixels were classified and then used to estimate the fat depth for each pixel in the hyperspectral image. Estimated reflectance, instead of image intensity or radiance, was used as the input feature for classification. The relationship between reflectance and the fat/non-fat classification label was learnt using support vector machines. Gaussian processes were used to learn regression for fat depth as a function of reflectance. Data to train and test the machine learning algorithms was collected by scanning 16 short loins. The near-infrared hyperspectral camera captured lines of data of the side of the short loin (i.e. with the subcutaneous fat facing the camera). Advanced single-lens reflex camera took photos of the same cuts from above, such that a ground truth of fat depth could be semi-automatically extracted and associated with the hyperspectral data. A subset of the data was used to train the machine learning model, and to test it. The results of classifying pixels as either fat or non-fat achieved a 96% accuracy. Fat depths of up to 12 mm were estimated, with an R 2 of 0.59, a mean absolute bias of 1.72 mm and root mean square error of 2.34 mm. The techniques developed and validated in the present study will be used to estimate fat coverage to predict total fat, and, subsequently, lean meat yield in the carcass

Analysis of factors influencing the ultrasonic fetal weight estimation

Objective: The aim of our study was the evaluation of sonographic fetal weight estimation taking into consideration 9 of the most important factors of influence on the precision of the estimation. Methods: We analyzed 820 singleton pregnancies from 22 to 42 weeks of gestational age. We evaluated 9 different factors that potentially influence the precision of sonographic weight estimation ( time interval between estimation and delivery, experts vs. less experienced investigator, fetal gender, gestational age, fetal weight, maternal BMI, amniotic fluid index, presentation of the fetus, location of the placenta). Finally, we compared the results of the fetal weight estimation of the fetuses with poor scanning conditions to those presenting good scanning conditions. Results: Of the 9 evaluated factors that may influence accuracy of fetal weight estimation, only a short interval between sonographic weight estimation and delivery (0-7 vs. 8-14 days) had a statistically significant impact. Conclusion: Of all known factors of influence, only a time interval of more than 7 days between estimation and delivery had a negative impact on the estimation

Allosteric Modulation of the HIV-1 gp120-gp41 Association Site by Adjacent gp120 Variable Region 1 (V1) N-Glycans Linked to Neutralization Sensitivity

The HIV-1 gp120-gp41 complex, which mediates viral fusion and cellular entry, undergoes rapid evolution within its external glycan shield to enable escape from neutralizing antibody (NAb). Understanding how conserved protein determinants retain functionality in the context of such evolution is important for their evaluation and exploitation as potential drug and/ or vaccine targets. In this study, we examined how the conserved gp120-gp41 association site, formed by the N- and Cterminal segments of gp120 and the disulfide-bonded region (DSR) of gp41, adapts to glycan changes that are linked to neutralization sensitivity. To this end, a DSR mutant virus (K601D) with defective gp120-association was sequentially passaged in peripheral blood mononuclear cells to select suppressor mutations. We reasoned that the locations of suppressors point to structural elements that are functionally linked to the gp120-gp41 association site. In culture 1, gp120 association and viral replication was restored by loss of the conserved glycan at Asn136 in V1 (T138N mutation) inconjunction with the L494I substitution in C5 within the association site. In culture 2, replication was restored with deletion of the N139INN sequence, which ablates the overlapping Asn141-Asn142-Ser-Ser potential N-linked glycosylation sequons inV1, in conjunction with D601N in the DSR. The 136 and 142 glycan mutations appeared to exert their suppressive effects by altering the dependence of gp120-gp41 interactions on the DSR residues, Leu593, Trp596 and Lys601. The 136 and/or 142glycan mutations increased the sensitivity of HIV-1 pseudovirions to the glycan-dependent NAbs 2G12 and PG16, and also pooled IgG obtained from HIV-1-infected individuals. Thus adjacent V1 glycans allosterically modulate the distal gp120-gp41 association site. We propose that this represents a mechanism for functional adaptation of the gp120-gp41 association site to an evolving glycan shield in a setting of NAb selection

HIV-1 Envelope Subregion Length Variation during Disease Progression

The V3 loop of the HIV-1 Env protein is the primary determinant of viral coreceptor usage, whereas the V1V2 loop region is thought to influence coreceptor binding and participate in shielding of neutralization-sensitive regions of the Env glycoprotein gp120 from antibody responses. The functional properties and antigenicity of V1V2 are influenced by changes in amino acid sequence, sequence length and patterns of N-linked glycosylation. However, how these polymorphisms relate to HIV pathogenesis is not fully understood. We examined 5185 HIV-1 gp120 nucleotide sequence fragments and clinical data from 154 individuals (152 were infected with HIV-1 Subtype B). Sequences were aligned, translated, manually edited and separated into V1V2, C2, V3, C3, V4, C4 and V5 subregions. V1-V5 and subregion lengths were calculated, and potential N-linked glycosylation sites (PNLGS) counted. Loop lengths and PNLGS were examined as a function of time since infection, CD4 count, viral load, and calendar year in cross-sectional and longitudinal analyses. V1V2 length and PNLGS increased significantly through chronic infection before declining in late-stage infection. In cross-sectional analyses, V1V2 length also increased by calendar year between 1984 and 2004 in subjects with early and mid-stage illness. Our observations suggest that there is little selection for loop length at the time of transmission; following infection, HIV-1 adapts to host immune responses through increased V1V2 length and/or addition of carbohydrate moieties at N-linked glycosylation sites. V1V2 shortening during early and late-stage infection may reflect ineffective host immunity. Transmission from donors with chronic illness may have caused the modest increase in V1V2 length observed during the course of the pandemic

Comparison of subsequent injury categorisation (SIC) models and their application in a sporting population

Background: The original subsequent injury categorisation (SIC-1.0) model aimed to classify relationships between chronological injury sequences to provide insight into the complexity and causation of subsequent injury occurrence. An updated model has recently been published. Comparison of the data coded according to the original and revised subsequent injury categorisation (SIC-1.0 and SIC-2.0) models has yet been formally compared. Methods: Medical attention injury data was prospectively collected for 42 elite water polo players over an 8 month surveillance period. The SIC-1.0 and SIC-2.0 models were retrospectively applied to the injury data. The injury categorisation from the two models was compared using descriptive statistics. Results: Seventy-four injuries were sustained by the 42 players (median = 2, range = 0-5), of which 32 injuries (43.2%) occurred subsequent to a previous injury. The majority of subsequent injuries were coded as occurring at a different site and being of a different nature, while also being considered clinically unrelated to the previous injury (SIC-1.0 category 10 = 57.9%; SIC-2.0 clinical category 16 = 54.4%). Application of the SIC-2.0 model resulted in a greater distribution of category allocation compared to the SIC-1.0 model that reflects a greater precision in the SIC-2.0 model. Conclusions: Subsequent injury categorisation of sport injury data can be undertaken using either the original (SIC-1.0) or the revised (SIC-2.0) model to obtain similar results. However, the SIC-2.0 model offers the ability to identify a larger number of mutually exclusive categories, while not relying on clinical adjudication for category allocation. The increased precision of SIC-2.0 is advantageous for clinical application and consideration of injury relationships