Deep learning prediction of likelihood of ICU admission and mortality in COVID-19 patients using clinical variables
Background This study aimed to develop a deep-learning model and a risk-score system using clinical variables to predict intensive care unit (ICU) admission and in-hospital mortality in COVID-19 patients. Methods This retrospective study consisted of 5,766 persons-under-investigation for COVID-19 between 7 February 2020 and 4 May 2020. Demographics, chronic comorbidities, vital signs, symptoms and laboratory tests at admission were collected. A deep neural network model and a risk-score system were constructed to predict ICU admission and in-hospital mortality. Prediction performance used the receiver operating characteristic area under the curve (AUC). Results The top ICU predictors were procalcitonin, lactate dehydrogenase, C-reactive protein, ferritin and oxygen saturation. The top mortality predictors were age, lactate dehydrogenase, procalcitonin, cardiac troponin, C-reactive protein and oxygen saturation. Age and troponin were unique top predictors for mortality but not ICU admission. The deep-learning model predicted ICU admission and mortality with an AUC of 0.780 (95% CI [0.760–0.785]) and 0.844 (95% CI [0.839–0.848]), respectively. The corresponding risk scores yielded an AUC of 0.728 (95% CI [0.726–0.729]) and 0.848 (95% CI [0.847–0.849]), respectively. Conclusions Deep learning and the resultant risk score have the potential to provide frontline physicians with quantitative tools to stratify patients more effectively in time-sensitive and resource-constrained circumstances.
Li et al. (2020) Deep learning prediction of likelihood of ICU admission and mortality in COVID-19 patients using clinical variables. PeerJ 8:e10337 https://doi.org/10.7717/peerj.10337
Transmissibility of coronavirus disease 2019 in Chinese cities with different dynamics of imported cases
Background Monitoring the reproduction number (Rt) of the disease could help determine whether there is sustained transmission in a population, but areas with similar epidemic trends could have different transmission dynamics given the risk from imported cases varied across regions. In this study, we examined the Rt of coronavirus disease 2019 (COVID-19) by taking different dynamics of imported cases into account and compared the transmissibility of COVID-19 at different intervention periods in Hangzhou and Shenzhen. Methods We obtained the daily aggregated counts of laboratory-confirmed imported and local cases of COVID-19 infections in Hangzhou and Shenzhen from January 1 to March 13, 2020. Daily Rt and piecewise Rt before and after Wuhan lockdown were estimated, accounting for imported cases. Results Since the epidemic of COVID-19 in Shenzhen was dominated by imported cases, Rt was around 0.1 to 0.7 before the Wuhan lockdown. After the lockdown of Wuhan and the initialization of measures in response to the outbreak, local transmission was well-controlled as indicated by a low estimated value of piecewise Rt, 0.15 (95% CI [0.09–0.21]). On the contrary, Rt obtained for Hangzhou ranged from 1.2 to 4.9 with a piecewise Rt of 2.55 (95% CI [2.13–2.97]) before the lockdown of Wuhan due to the surge in local cases. Because of the Wuhan lockdown and other outbreak response measures, Rt dropped below unity in mid-February. Conclusions Even though Shenzhen had more cases than Hangzhou, local transmission did not sustain probably due to limited transmission from imported cases owing to the reduction in local susceptibles as residents left the city during Chunyun. The lockdown measures and local outbreak responses helped reduce the local transmissibility.
Chong et al. (2020) Transmissibility of coronavirus disease 2019 in Chinese cities with different dynamics of imported cases. PeerJ 8:e10350 https://doi.org/10.7717/peerj.10350
BiSCoT: improving large eukaryotic genome assemblies with optical maps
Motivation Long read sequencing and Bionano Genomics optical maps are two techniques that, when used together, make it possible to reconstruct entire chromosome or chromosome arms structure. However, the existing tools are often too conservative and organization of contigs into scaffolds is not always optimal. Results We developed BiSCoT (Bionano SCaffolding COrrection Tool), a tool that post-processes files generated during a Bionano scaffolding in order to produce an assembly of greater contiguity and quality. BiSCoT was tested on a human genome and four publicly available plant genomes sequenced with Nanopore long reads and improved significantly the contiguity and quality of the assemblies. BiSCoT generates a fasta file of the assembly as well as an AGP file which describes the new organization of the input assembly. Availability BiSCoT and improved assemblies are freely available on GitHub at http://www.genoscope.cns.fr/biscot and Pypi at https://pypi.org/project/biscot/.
Istace et al. (2020) BiSCoT: improving large eukaryotic genome assemblies with optical maps. PeerJ 8:e10150 https://doi.org/10.7717/peerj.10150
Diversity of the gut microbiome in three grasshopper species using 16S rRNA and determination of cellulose digestibility
Background Grasshoppers are typical phytophagous pests, and they have large appetites with high utilization of plants fibers, the digestion of which may depend on the microorganisms in their intestines. Grasshoppers have the potential to be utilized in bioreactors, which could improve straw utilization efficiency in the future. In this study, we describe the gut microbiome in three species of grasshoppers, Oedaleus decorus asiaticus, Aiolopus tamulus and Shirakiacris shirakii, by constructing a 16S rDNA gene library and analyzed the digestibility of cellulose and hemicellulose in the grasshoppers by using moss black phenol colorimetry and anthrone colorimetry. Results There were 509,436 bacterial OTUs (Operational Taxonomic Units) detected in the guts of all the grasshoppers sampled. Among them, Proteobacteria and Firmicutes were the most common, Aiolopus tamulus had the highest bacterial diversity, and Shirakiacris shirakii had the highest bacterial species richness. The intestinal microflora structure varied between the different species of grasshopper, with Aiolopus tamulus and Shirakiacris shirakii being the most similar. Meanwhile, the time at which grasshopper specimens were collected also led to changes in the intestinal microflora structure in the same species of grasshoppers. Klebsiella may form the core elements of the microflora in the grasshopper intestinal tract. The digestibility of cellulose/hemicellulose among the three species grasshoppers varied (38.01/24.99%, 43.95/17.21% and 44.12/47.62%). LEfSe analysis and Spearman correlation coefficients showed that the hemicellulosic digestibility of Shirakiacris shirakii was significantly higher than that of the other two species of grasshopper, which may be related to the presence of Pseudomonas, Stenotrophomonas, Glutamicibacter, Corynebacterium, and Brachybacterium in Shirakiacris shirakii intestinal tract. Conclusion The intestinal microbial communities of the three grasshoppers species are similar on phylum level, but the dominant genera of different species grasshoppers are different. The cellulose digestibility of the three species of grasshoppers is relatively high, which may be correlated with the presence of some gut microbiome. Increasing the understanding of the structure and function of the grasshopper intestinal microflora will facilitate further research and the utilization of intestinal microorganisms in the future.
Wang et al. (2020) Diversity of the gut microbiome in three grasshopper species using 16S rRNA and determination of cellulose digestibility. PeerJ 8:e10194 https://doi.org/10.7717/peerj.10194
Characterizing carbonyl compounds and their sources in Fuzhou ambient air, southeast of China
In recent years, ozone (O3) concentrations in the southeastern coastal areas of China have shown a gradual upward trend. As precursors and intermediates in the formation of O3, carbonyl compounds play key roles in the atmospheric photochemical oxidation cycle. To explore the main pollution characteristics of carbonyl compounds in a typical coastal city in southeast China, ambient samples were collected in Fuzhou (the provincial capital of Fujian province, located on the southeast coast of China) and analyzed using high-performance liquid chromatography with ultraviolet detection. The study was continuously carried out at an urban site (Jinjishan) and a suburban site (Gushan) in Fuzhou from May 8 to 20, 2018. The total concentration of 16 carbonyl compounds at the urban site was 15.45 ± 11.18 ppbv, and the total concentration at the suburban site was 17.57 ± 12.77 ppbv. Formaldehyde (HCHO), acetaldehyde, and acetone were the main species detected in the samples, and acetone had the highest concentration among the species detected. The suburban site had a higher formaldehyde/acetaldehyde ratio and lower acetaldehyde/propionaldehyde ratio than the urban site, implying that biogenic sources potentially contributed to the carbonyl compound concentrations at the suburban site. The results of an observation-based model showed that anthropogenic hydrocarbons promoted HCHO production on May 17 at the urban site. Compared to biogenic emissions, anthropogenic activity is a more important source of carbonyl compounds.
Environmental Contamination and Remediation
He et al. (2020) Characterizing carbonyl compounds and their sources in Fuzhou ambient air, southeast of China. PeerJ 8:e10227 https://doi.org/10.7717/peerj.10227
Nuclear microsatellites reveal population genetic structuring and fine-scale pattern of hybridization in the Japanese mantis shrimp Oratosquilla oratoria
The interplay between historical and contemporary processes can produce complex patterns of genetic differentiation in the marine realm. Recent mitochondrial and nuclear sequence analyses revealed cryptic speciation in the Japanese mantis shrimp Oratosquilla oratoria. Herein, we applied nuclear microsatellite markers to examine patterns and causes of genetic differentiation in this morphotaxon. Population structure analyses revealed two genetically divergent and geographically structured clades in O. oratoria, one dominating the temperate zone of the Northwestern (NW) Pacific and the other occurring in the subtropical and tropical waters where are influenced by the Kuroshio Current. Two sympatric zones, one around the Changjiang Estuary in China coast and the other in the northern Japan Sea, were demonstrated to be hybrid zones where introgressive hybridization occurred asymmetrically. The interaction between historical climate shifts and contemporary factors (e.g., freshwater discharge, temperature gradient and isolation by distance) may contribute to the present-day genetic architecture in the Japanese mantis shrimp. Range shift induced by climate changes and oceanographic factors may promote hybridization and gene flow between the O. oratoria complex. Our results provide insights into the interacting mechanisms that give rise to diversification and speciation of coastal species in the NW Pacific.
Cheng et al. (2020) Nuclear microsatellites reveal population genetic structuring and fine-scale pattern of hybridization in the Japanese mantis shrimp Oratosquilla oratoria. PeerJ 8:e10270 https://doi.org/10.7717/peerj.10270
Trait differences among discrete morphs of a color polymorphic lizard, Podarcis erhardii
Color polymorphism defies evolutionary expectations as striking phenotypic variation is maintained within a single species. Color and other traits mediate social interactions, and stable polymorphism within a population is hypothesized to be related to correlational selection of other phenotypic traits among color morphs. Here, we report on a previously unknown throat color polymorphism in the Aegean Wall Lizard (Podarcis erhardii) and examine morph-correlated differences in traits important to social behavior and communication: maximum bite force capacity and chemical signal profile. We find that both sexes of P. erhardii have three color morphs: orange, yellow, and white. Moreover, orange males are significantly larger and tend to bite harder than yellow and white males. Although the established color polymorphism only partially matches the observed intraspecific variation in chemical signal signatures, the chemical profile of the secretions of orange males is significantly divergent from that of white males. Our findings suggest that morph colors are related to differences in traits that are crucial for social interactions and competitive ability, illustrating the need to look beyond color when studying polymorphism evolution.
Brock et al. (2020) Trait differences among discrete morphs of a color polymorphic lizard, Podarcis erhardii. PeerJ 8:e10284 https://doi.org/10.7717/peerj.10284
Robustness analysis in an inter-cities mobility network: modeling municipal, state and federal initiatives as failures and attacks toward SARS-CoV-2 containment
We present a robustness analysis of an inter-cities mobility complex network, motivated by the challenge of the COVID-19 pandemic and the seek for proper containment strategies. Brazilian data from 2016 are used to build a network with more than five thousand cities (nodes) and twenty-seven states with the edges representing the weekly flow of people between cities via terrestrial transports. Nodes are systematically isolated (removed from the network) either at random (failures) or guided by specific strategies (targeted attacks), and the impacts are assessed with three metrics: the number of components, the size of the giant component, and the total remaining flow of people. We propose strategies to identify which regions should be isolated first and their impact on people mobility. The results are compared with the so-called reactive strategy, which consists of isolating regions ordered by the date the first case of COVID-19 appeared. We assume that the nodes’ failures abstract individual municipal and state initiatives that are independent and possess a certain level of unpredictability. Differently, the targeted attacks are related to centralized strategies led by the federal government in agreement with municipalities and states. Removing a node means completely restricting the mobility of people between the referred city/state and the rest of the network. Results reveal that random failures do not cause a high impact on mobility restraint, but the coordinated isolation of specific cities with targeted attacks is crucial to detach entire network areas and thus prevent spreading. Moreover, the targeted attacks perform better than the reactive strategy for the three analyzed robustness metrics.
Spatial and Geographic Information Science
Freitas et al. (2020) Robustness analysis in an inter-cities mobility network: modeling municipal, state and federal initiatives as failures and attacks toward SARS-CoV-2 containment. PeerJ 8:e10287 https://doi.org/10.7717/peerj.10287
Deep-learning convolutional neural networks with transfer learning accurately classify COVID-19 lung infection on portable chest radiographs
Portable chest X-ray (pCXR) has become an indispensable tool in the management of Coronavirus Disease 2019 (COVID-19) lung infection. This study employed deep-learning convolutional neural networks to classify COVID-19 lung infections on pCXR from normal and related lung infections to potentially enable more timely and accurate diagnosis. This retrospect study employed deep-learning convolutional neural network (CNN) with transfer learning to classify based on pCXRs COVID-19 pneumonia (N = 455) on pCXR from normal (N = 532), bacterial pneumonia (N = 492), and non-COVID viral pneumonia (N = 552). The data was randomly split into 75% training and 25% testing, randomly. A five-fold cross-validation was used for the testing set separately. Performance was evaluated using receiver-operating curve analysis. Comparison was made with CNN operated on the whole pCXR and segmented lungs. CNN accurately classified COVID-19 pCXR from those of normal, bacterial pneumonia, and non-COVID-19 viral pneumonia patients in a multiclass model. The overall sensitivity, specificity, accuracy, and AUC were 0.79, 0.93, and 0.79, 0.85 respectively (whole pCXR), and were 0.91, 0.93, 0.88, and 0.89 (CXR of segmented lung). The performance was generally better using segmented lungs. Heatmaps showed that CNN accurately localized areas of hazy appearance, ground glass opacity and/or consolidation on the pCXR. Deep-learning convolutional neural network with transfer learning accurately classifies COVID-19 on portable chest X-ray against normal, bacterial pneumonia or non-COVID viral pneumonia. This approach has the potential to help radiologists and frontline physicians by providing more timely and accurate diagnosis.
Kikkisetti et al. (2020) Deep-learning convolutional neural networks with transfer learning accurately classify COVID-19 lung infection on portable chest radiographs. PeerJ 8:e10309 https://doi.org/10.7717/peerj.10309
An updated evolutionary study of the Notch family reveals a new ancient origin and novel invariable motifs as potential pharmacological targets
Notch family proteins play a key role in a variety of developmental processes by controlling cell fate decisions and operating in a great number of biological processes in several organ systems, such as hematopoiesis, somatogenesis, vasculogenesis, neurogenesis and homeostasis. The Notch signaling pathway is crucial for the majority of developmental programs and regulates multiple pathogenic processes. Notch family receptors’ activation has been largely related to its multiple effects in sustaining oncogenesis. The Notch signaling pathway constitutes an ancient and conserved mechanism for cell to cell communication. Much of what is known about Notch family proteins function comes from studies done in Caenorhabditis Elegans and Drosophila Melanogaster. Although, human Notch homologs had also been identified, the molecular mechanisms which modulate the Notch signaling pathway remained substantially unknown. In this study, an updated evolutionary analysis of the Notch family members among 603 different organisms of all kingdoms, from bacteria to humans, was performed in order to discover key regions that have been conserved throughout evolution and play a major role in the Notch signaling pathway. The major goal of this study is the presentation of a novel updated phylogenetic tree for the Notch family as a reliable phylogeny “map”, in order to correlate information of the closely related members and identify new possible pharmacological targets that can be used in pathogenic cases, including cancer.
Vlachakis et al. (2020) An updated evolutionary study of the Notch family reveals a new ancient origin and novel invariable motifs as potential pharmacological targets. PeerJ 8:e10334 https://doi.org/10.7717/peerj.10334