Purpose High-dimensional image features that underlie COVID-19 pneumonia remain opaque. We aim to compare feature engineering and deep learning methods to gain insights into the image features that drive CT-based for COVID-19 pneumonia prediction, and uncover CT image features significant for COVID-19 pneumonia from deep learning and radiomics framework. Methods A total of 266 patients with COVID-19 and other viral pneumonia with clinical symptoms and CT signs similar to that of COVID-19 during the outbreak were retrospectively collected from three hospitals in China and the USA. All the pneumonia lesions on CT images were manually delineated by four radiologists. One hundred eighty-four patients (n = 93 COVID-19 positive; n = 91 COVID-19 negative; 24,216 pneumonia lesions from 12,001 CT image slices) from two hospitals from China served as discovery cohort for model development. Thirty-two patients (17 COVID-19 positive, 15 COVID-19 negative; 7883 pneumonia lesions from 3799 CT image slices) from a US hospital served as external validation cohort. A bi-directional adversarial network-based framework and PyRadiomics package were used to extract deep learning and radiomics features, respectively. Linear and Lasso classifiers were used to develop models predictive of COVID-19 versus non-COVID-19 viral pneumonia. Results 120-dimensional deep learning image features and 120-dimensional radiomics features were extracted. Linear and Lasso classifiers identified 32 high-dimensional deep learning image features and 4 radiomics features associated with COVID-19 pneumonia diagnosis (P < 0.0001). Both models achieved sensitivity > 73% and specificity > 75% on external validation cohort with slight superior performance for radiomics Lasso classifier. Human expert diagnostic performance improved (increase by 16.5% and 11.6% in sensitivity and specificity, respectively) when using a combined deep learning-radiomics model. Conclusions We uncover specific deep learning and radiomics features to add insight into interpretability of machine learning algorithms and compare deep learning and radiomics models for COVID-19 pneumonia that might serve to augment human diagnostic performance.

Summary Background Prisons are recognised as high-risk environments for tuberculosis, but there has been little systematic investigation of the global and regional incidence and prevalence of tuberculosis, and its determinants, in prisons. We did a systematic review and meta-analysis to assess the incidence and prevalence of tuberculosis in incarcerated populations by geographical region. Methods In this systematic review and meta-analysis, we searched MEDLINE, Embase, Web of Knowledge, and the LILACS electronic database from Jan 1, 1980, to Nov 15, 2020, for cross-sectional and cohort studies reporting the incidence of Mycobacterium tuberculosis infection, incidence of tuberculosis, or prevalence of tuberculosis among incarcerated individuals in all geographical regions. We extracted data from individual studies, and calculated pooled estimates of incidence and prevalence through hierarchical Bayesian meta-regression modelling. We also did subgroup analyses by region. Incidence rate ratios between prisons and the general population were calculated by dividing the incidence of tuberculosis in prisons by WHO estimates of the national population-level incidence. Findings We identified 159 relevant studies; 11 investigated the incidence of M tuberculosis infection (n=16 318), 51 investigated the incidence of tuberculosis (n=1 858 323), and 106 investigated the prevalence of tuberculosis (n=6 727 513) in incarcerated populations. The overall pooled incidence of M tuberculosis infection among prisoners was 15·0 (95% credible interval [CrI] 3·8–41·6) per 100 person-years. The incidence of tuberculosis (per 100 000 person-years) among prisoners was highest in studies from the WHO African (2190 [95% CrI 810–4840] cases) and South-East Asia (1550 [240–5300] cases) regions and in South America (970 [460–1860] cases), and lowest in North America (30 [20–50] cases) and the WHO Eastern Mediterranean region (270 [50–880] cases). The prevalence of tuberculosis was greater than 1000 per 100 000 prisoners in all global regions except for North America and the Western Pacific, and highest in the WHO South-East Asia region (1810 [95% CrI 670–4000] cases per 100 000 prisoners). The incidence rate ratio between prisons and the general population was much higher in South America (26·9; 95% CrI 17·1–40·1) than in other regions, but was nevertheless higher than ten in the WHO African (12·6; 6·2–22·3), Eastern Mediterranean (15·6; 6·5–32·5), and South-East Asia (11·7; 4·1–27·1) regions. Interpretation Globally, people in prison are at high risk of contracting M tuberculosis infection and developing tuberculosis, with consistent disparities between prisons and the general population across regions. Tuberculosis control programmes should prioritise preventive interventions among incarcerated populations. ...

Decoupling of the upper jaw bones-jaw kinesis-is a distinctive feature of the ray-finned fishes, but it is not clear how the innovation is related to the extraordinary diversity of feeding behaviours and feeding ecology in this group. We address this issue in a lineage of ray-finned fishes that is well known for its ecological and functional diversity-African rift lake cichlids. We sequenced ultraconserved elements to generate a phylogenomic tree of the Lake Tanganyika and Lake Malawi cichlid radiations. We filmed a diverse array of over 50 cichlid species capturing live prey and quantified the extent of jaw kinesis in the premaxillary and maxillary bones. Our combination of phylogenomic and kinematic data reveals a strong association between biting modes of feeding and reduced jaw kinesis, suggesting that the contrasting demands of biting and suction feeding have strongly influenced cranial evolution in both cichlid radiations.

Phylogenetic relationships amongst the robust capuchin monkeys (genus Sapajus) are poorly understood. Morphology-based taxonomies have recognized anywhere from one to twelve different species. The current IUCN (2017) classification lists eight robust capuchins: S. xanthosternos, S. nigritus, S. robustus, S. flavius, S. libidinosus, S. cay, S. apella and S. macrocephalus. Here, we assembled the first phylogenomic data set for Sapajus using ultra-conserved elements (UCEs) to reconstruct a capuchin phylogeny. All phylogenomic analyses strongly supported a deep divergence of Sapajus and Cebus clades within the capuchin monkeys, and provided support for Sapajus nigritus, S. robustus and S. xanthosternos as distinct species. However, the UCE phylogeny lumped the putative species S. cay, S. libidinosus, S. apella, S. macrocephalus, and S. flavius together as a single widespread lineage. A SNP phylogeny constructed from the UCE data was better resolved and recovered S. flavius and S. libidinosus as sister species; however, S. apella, S. macrocephalus, and S. cay individuals were recovered in two geographic clades, from northeastern and southwestern Amazon, rather than clustering by currently defined morphospecies. STRUCTURE analysis of population clustering revealed widespread admixture among Sapajus populations within the Amazon and even into the Cerrado and Atlantic Forest. Difficulty in assigning species by morphology may be a result of widespread population admixture facilitated through frequent movement across major rivers and even ecosystems by robust capuchin monkeys.

IMPORTANCE Epidemiological studies indicate a link between obsessive-compulsive disorder and infections, particularly streptococcal pharyngitis. Pediatric acute-onset neuropsychiatric syndrome (PANS) manifests suddenly with obsessions, compulsions, and other behavioral disturbances, often after an infectious trigger. The current working model suggests a unifying inflammatory process involving the central nervous system, particularly the basal ganglia. OBJECTIVE To investigate whether diffusion-weighted magnetic resonance imaging (DWI) detects microstructural abnormalities across the brain regions of children with PANS. DESIGN, SETTING, AND PARTICIPANTS Case-control study performed at a single-center, multidisciplinary clinic in the United States focusing on the evaluation and treatment of children with PANS. Sixty consecutive patients who underwent 3 Tesla (T) magnetic resonance imaging (MRI) before immunomodulation from September 3, 2012, to March 30, 2018, were retrospectively reviewed for study inclusion. Six patients were excluded by blinded investigators because of imaging or motion artifacts, 3 patients for major pathologies, and 17 patients for suboptimal atlas image registration. In total, 34 patients with PANS before initiation of treatment were compared with 64 pediatric control participants. MAIN OUTCOMES AND MEASURESUsing atlas-based MRI analysis, regional brain volume, diffusion, and cerebral blood flow were measured in the cerebral white matter, cerebral cortex, thalamus, caudate, putamen, pallidum, hippocampus, amygdala, nucleus accumbens, and brainstem.An age and sex-controlled multivariable analysis of covariance was used to compare patients with control participants. RESULTSThis study compared 34 patients with PANS (median age, 154 months; age range, 55-251 months; 17 girls and 17 boys) and 64 pediatric control participants (median age, 139 months; age range, 48-213 months); 41 girls and 23 boys). Multivariable analysis demonstrated a statistically significant difference in MRI parameters between patients with PANS and control participants (F 21,74 = 6.91; P < .001; partial η 2 = 0.662). All assessed brain regions had statistically significantly increased median diffusivity compared with 64 control participants. Specifically, the deep gray matter (eg, the thalamus, basal ganglia, and amygdala) demonstrated the most profound increases in diffusivity consistent with the cardinal clinical symptoms of obsessions, compulsions, emotional dysregulation, and sleep disturbances. No statistically significant differences were found regarding volume and cerebral blood flow. (continued) Key Points Question How does diffusion-weighted magnetic resonance imaging differ between patients with pediatric acuteonset neuropsychiatric syndrome and pediatric control participants? Findings In this case-control study of 34 consecutive patients with pediatric acute-onset neuropsychiatric syndrome who had 3 Tesla magnetic resonance imaging, all assessed brain regions, particularly the deep gray matter (eg, the thalamus, b...