Background: Computed tomography (CT) enables quantification of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, helping in outcome prediction. Methods: From 1 to 22 March 2020, patients with pneumonia symptoms, positive lung CT scan, and confirmed SARS-CoV-2 on reverse transcription-polymerase chain reaction (RT-PCR) were consecutively enrolled. Clinical data was collected. Outcome was defined as favourable or adverse (i.e., need for mechanical ventilation or death) and registered over a period of 10 days following CT. Volume of disease (VoD) on CT was calculated semi-automatically. Multiple linear regression was used to predict VoD by clinical/laboratory data. To predict outcome, important features were selected using a priori analysis and subsequently used to train 4 different models. Results: A total of 106 consecutive patients were enrolled (median age 63.5 years, range 26-95 years; 41/106 women, 38.7%). Median duration of symptoms and C-reactive protein (CRP) was 5 days (range 1-30) and 4.94 mg/L (range 0.1-28.3), respectively. Median VoD was 249.5 cm 3 (range 9.9-1505) and was predicted by lymphocyte percentage (p = 0.008) and CRP (p < 0.001). Important variables for outcome prediction included CRP (area under the curve [AUC] 0.77), VoD (AUC 0.75), age (AUC 0.72), lymphocyte percentage (AUC 0.70), coronary calcification (AUC 0.68), and presence of comorbidities (AUC 0.66). Support vector machine had the best performance in outcome prediction, yielding an AUC of 0.92. Conclusions: Measuring the VoD using a simple CT post-processing tool estimates SARS-CoV-2 burden. CT and clinical data together enable accurate prediction of short-term clinical outcome.

Photogrammetry (PH) is relatively cheap, easy to use, flexible and portable but its power and limitations have not been fully explored for studies of small animals. Here we assessed the accuracy of PH for the reconstruction of 3D digital models of bat skulls by evaluating its potential for evolutionary morphology studies at interspecific (19 species) level. Its reliability was assessed against the performance of micro CT scan (µCT) and laser scan techniques (LS). We used 3D geometric morphometrics and comparative methods to quantify the amount of size and shape variation due to the scanning technique and assess the strength of the biological signal in relation to both the technique error and phylogenetic uncertainty. We found only minor variation among techniques. Levels of random error (repeatability and procrustes variance) were similar in all techniques and no systematic error was observed (as evidenced from principal component analysis). Similar levels of phylogenetic signal, allometries and correlations with ecological variables (frequency of maximum energy and bite force) were detected among techniques. Phylogenetic uncertainty interacted with technique error but without affecting the biological conclusions driven by the evolutionary analyses. Our study confirms the accuracy of PH for the reconstruction of challenging specimens. These results encourage the use of PH as a reliable and highly accessible tool for the study of macro evolutionary processes of small mammals.

Based on the results, objective guidelines are provided to minimize information loss when using smoothing and decimation on 3D meshes.

The evolutionary relationship between the base and face of the cranium is a major topic of interest in primatology. Such areas of the skull possibly respond to different selective pressures. Yet, they are often said to be tightly integrated. In this paper, we analyzed shape variability in the cranial base and the facial complex in Cercopithecoidea and Hominoidea. We used a landmark-based approach to single out the effects of size (evolutionary allometry), morphological integration, modularity, and phylogeny (under Brownian motion) on skull shape variability. Our results demonstrate that the cranial base and the facial complex exhibit different responses to different factors, which produces a little degree of morphological integration between them. Facial shape variation appears primarily influenced by body size and sexual dimorphism, whereas the cranial base is mostly influenced by functional factors. The different adaptations affecting the two modules suggest they are best studied as separate and independent units, and that-at least when dealing with Catarrhines-caution must be posed with the notion of strong cranial integration that is commonly invoked for the evolution of their skull shape.

Both methods demonstrated to be much faster, cheaper, and more accurate than other conventional approaches. The tools we presented are available as add-ons in existing software within the R platform. Because of ease of application, and unrestrained availability of the methods proposed, these tools can be widely used by paleoanthropologists, paleontologists and anatomists.