Bite force data suggests relationship between acrodont tooth implantation and strong bite force
Extant and extinct reptiles exhibit numerous combinations of tooth implantation and attachment. Tooth implantation ranges from those possessing roots and lying within a socket (thecodonty), to teeth lying against the lingual wall of the jawbone (pleurodonty), to teeth without roots or sockets that are attached to the apex of the marginal jawbones (acrodonty). Attachment may be ligamentous (gomphosis) or via fusion (ankylosis). Generally speaking, adaptative reasonings are proposed as an underlying driver for evolutionary changes in some forms of tooth implantation and attachment. However, a substantiated adaptive hypothesis is lacking for the state of acrodont ankylosis that is seen in several lineages of Lepidosauria, a clade that is plesiomorphically pleurodont. The convergent evolution of acrodont ankylosis in several clades of lepidosaurs suggests a selective pressure shaped the evolution of the trait. We hypothesize that acrodont ankylosis as seen in Acrodonta and Sphenodon punctatus, is an adaptation either resulting from or allowing for a stronger bite force. We analyzed bite force data gathered from the literature to show that those taxa possessing acrodont dentition possess a stronger bite force on average than those taxa with pleurodont dentition. Dietary specialists with pleurodont dentition may also possess relatively high bite forces, though body size may also play a role in their ability to bite hard. Furthermore, our results have implications for the evolution of acrodont ankylosis and potential behaviors related to strong bite force that influenced the evolution of acrodonty within Acrodonta and Rhynchocephalia.
Jenkins et al. (2020) Bite force data suggests relationship between acrodont tooth implantation and strong bite force. PeerJ 8:e9468 https://doi.org/10.7717/peerj.9468
Comparative metabolomic analyses of Dendrobium officinale Kimura et Migo responding to UV-B radiation reveal variations in the metabolisms associated with its bioactive ingredients
Background Dendrobium officinale Kimura et Migo, a member of the genus Dendrobium, is a traditional Chinese medicine with high commercial value. The positive roles of UV-B radiation on active ingredient metabolism in various medicinal plants have been studied. However, the metabolic responses of D. officinale stems to UV-B treatment is largely unknown. Methods An untargeted metabolomics method was used to investigate the metabolic variations in D. officinale stems between the control and UV-B treatments. Results In total, 3,655 annotated metabolites, including 640 up- and 783 down-regulated metabolites, were identified and grouped into various primary metabolic categories. Then, a number of metabolites involved in the polysaccharide, alkaloid and flavonoid biosynthesis pathways were identified. For polysaccharide biosynthesis, several intermediate products, such as pyruvate, secologanate, tryptophan and secologanin, were significantly up-regulated by the UV-B treatment. For polysaccharide biosynthesis, many key fundamental building blocks, from the glycolysis, starch and sucrose metabolism, and fructose and mannose metabolism pathways, were induced by the UV-B treatment. For flavonoid metabolism, accumulations of several intermediate products of chalcone synthase, chalcone isomerase and flavanone 3-hydroxylase were affected by the UV-B treatment, indicating an involvement of UV-B in flavonoid biosynthesis. The UV-B induced accumulation of polysaccharides, alkaloids and flavonoids was confirmed by HPLC analysis. Our study will help to understand the effects of UV-B on the accumulation of active ingredients in D. officinale.
Chen et al. (2020) Comparative metabolomic analyses of Dendrobium officinale Kimura et Migo responding to UV-B radiation reveal variations in the metabolisms associated with its bioactive ingredients. PeerJ 8:e9107 https://doi.org/10.7717/peerj.9107
The genome of the butternut canker pathogen, Ophiognomonia clavigignenti-juglandacearum shows an elevated number of genes associated with secondary metabolism and protection from host resistance responses
Ophiognomonia clavigignenti-juglandacearum (Oc-j) is a plant pathogenic fungus that causes canker and branch dieback diseases in the hardwood tree butternut, Juglans cinerea. Oc-j is a member of the order of Diaporthales, which includes many other plant pathogenic species, several of which also infect hardwood tree species. In this study, we sequenced the genome of Oc-j and achieved a high-quality assembly and delineated its phylogeny within the Diaporthales order using a genome-wide multi-gene approach. We also further examined multiple gene families that might be involved in plant pathogenicity and degradation of complex biomass, which are relevant to a pathogenic life-style in a tree host. We found that the Oc-j genome contains a greater number of genes in these gene families compared to other species in the Diaporthales. These gene families include secreted CAZymes, kinases, cytochrome P450, efflux pumps, and secondary metabolism gene clusters. The large numbers of these genes provide Oc-j with an arsenal to cope with the specific ecological niche as a pathogen of the butternut tree.
Wu et al. (2020) The genome of the butternut canker pathogen, Ophiognomonia clavigignenti-juglandacearum shows an elevated number of genes associated with secondary metabolism and protection from host resistance responses. PeerJ 8:e9265 https://doi.org/10.7717/peerj.9265
A new species of freshwater crab genus Fredius Pretzmann, 1967 (Crustacea: Brachyura: Pseudothelphusidae) from a naturally isolated orographic forest enclave within the semiarid Caatinga in Ceará, northeastern Brazil
A new species of freshwater crab, Fredius ibiapaba, is described and illustrated from a mid-altitude forested patch in Ipú (Ibiapaba plateau, Ceará, northeastern Brazil), between 635 to 782 m. The new species can be separated from its congeners by the morphology of its first gonopod: proximal half remarkably swollen, sloping abruptly downwards distally to a nearly right-angular shoulder; mesial lobe much smaller than cephalic spine; cephalic lobe moderately developed; auxiliary lobe lip, delimiting field of apical spines, protruded all the way to distal margin of auxiliary lobe. Comparative 16S rDNA sequencing used to infer the phylogenetic placement of Fredius ibiapaba n. sp. revealed that it is the sister taxon of F. reflexifrons, a species which occurs allopatrically in the Amazon and Atlantic basin’s lowlands (<100 m). Fredius ibiapaba n. sp. and F. reflexifrons are highly dependent upon humidity and most probably were once part of an ancestral population living in a wide humid territory. Shrinking humid forests during several dry periods of the Tertiary and Quaternary likely have resulted in the fragmentation of the ancestral humid area and hence of the ancestral crab population. Fredius reflexifrons evolved and spread in a lowland, humid river basin (Amazon and Atlantic basins), whilst F. ibiapaba n. sp. evolved isolated on the top of a humid plateau. The two species are now separated by a vast intervening area occupied by the semiarid Caatinga
Santos et al. (2020) A new species of freshwater crab genus Fredius Pretzmann, 1967 (Crustacea: Brachyura: Pseudothelphusidae) from a naturally isolated orographic forest enclave within the semiarid Caatinga in Ceará, northeastern Brazil. PeerJ 8:e9370 https://doi.org/10.7717/peerj.9370
Shannon diversity index: a call to replace the original Shannon’s formula with unbiased estimator in the population genetics studies
Background The Shannon diversity index has been widely used in population genetics studies. Recently, it was proposed as a unifying measure of diversity at different levels—from genes and populations to whole species and ecosystems. The index, however, was proven to be negatively biased at small sample sizes. Modifications to the original Shannon’s formula have been proposed to obtain an unbiased estimator. Methods In this study, the performance of four different estimators of Shannon index—the original Shannon’s formula and those of Zahl, Chao and Shen and Chao et al.—was tested on simulated microsatellite data. Both the simulation and analysis of the results were performed in the R language environment. A new R function was created for the calculation of all four indices from the genind data format. Results Sample size dependence was detected in all the estimators analysed; however, the deviation from parametric values was substantially smaller in the derived measures than in the original Shannon’s formula. Error rate was negatively associated with population heterozygosity. Comparisons among loci showed that fast-mutating loci were less affected by the error, except for the original Shannon’s estimator which, in the smallest sample, was more strongly affected by loci with a higher number of alleles. The Zahl and Chao et al. estimators performed notably better than the original Shannon’s formula. Conclusion The results of this study show that the original Shannon index should no longer be used as a measure of genetic diversity and should be replaced by Zahl’s unbiased estimator.
Konopiński (2020) Shannon diversity index: a call to replace the original Shannon’s formula with unbiased estimator in the population genetics studies. PeerJ 8:e9391 https://doi.org/10.7717/peerj.9391
Using Bumble Bee Watch to investigate the accuracy and perception of bumble bee (Bombus spp.) identification by community scientists
Community science programs provide an opportunity to gather scientific data to inform conservation policy and management. This study examines the accuracy of community science identifications submitted to the North American Bumble Bee Watch program on a per species level and as compared to each species’ conservation status, as well as users (members of the public) and experts (those with expertise in the field of bumble bee biology) perceived ease of species identification. Photos of bumble bees (Hymenoptera: Apidae: Bombus) are submitted to the program by users and verified (species name corrected or assigned as necessary) by an expert. Over 22,000 records from over 4,900 users were used in the analyses. Accuracy was measured in two ways: percent agreement (percent of all records submitted correctly by users) and veracity (percent of all verified records submitted correctly by the users). Users generally perceived it harder to identify species than experts. User perceptions were not significantly different from the observed percent agreement or veracity, while expert perceptions were significantly different (overly optimistic) from the observed percent agreement but not the veracity. We compared user submitted names to final expert verified names and found that, for all species combined, the average percent agreement was 53.20% while the average veracity was 55.86%. There was a wide range in percent agreement values per species, although sample size and the role of chance did affect some species agreements. As the conservation status of species increased to higher levels of extinction risk, species were increasingly more likely to have a lower percent agreement but higher levels of veracity than species of least concern. For each species name submitted, the number of different species verified by experts varied from 1 to 32. Future research may investigate which factors relate to success in user identification through community science. These findings could play a role in informing the design of community science programs in the future, including for use in long-term and national-level monitoring of wild pollinators.
MacPhail et al. (2020) Using Bumble Bee Watch to investigate the accuracy and perception of bumble bee (Bombus spp.) identification by community scientists. PeerJ 8:e9412 https://doi.org/10.7717/peerj.9412
A preoperative nomogram for sepsis in percutaneous nephrolithotomy treating solitary, unilateral and proximal ureteral stones
Background Postoperative sepsis is a lethal complication for percutaneous nephrolithotomy (PCNL). An early predictive model combined local and systemic conditions is urgently needed to predict infectious events. We aim to determine the preoperative predictors of sepsis after PCNL in patients with unilateral, solitary, and proximal ureteral stones. Methods A total of 745 patients who underwent PCNL between January 2012 and December 2018 were retrospectively enrolled. Sepsis was defined based on the International Sepsis Definitions in 2001, and the preoperative factors were compared between the non-sepsis and sepsis groups. Univariable analysis and multivariable logistic regression analysis were conducted to determine the predictors for sepsis after PCNL. A nomogram was generated using the predictors. Results In this study, 35 patients (4.7%) developed sepsis after PCNL. Univariate analysis showed that post-PCNL sepsis was associated with the female, lower albumin, higher globulin, lower albumin globulin ratio (AGR < 1.5), preoperative fever, leukocytosis (WBC ≥ 10,000 cells/μL), positive urine culture, leukocyturia (≥50 cells/μL) and positive urine nitrite. Multivariate logistic regression analysis suggested that AGR < 1.5 (odds ratio [OR] = 5.068, 95% confidence interval [CI] [1.135–22.624], P = 0.033), positive urine culture (OR = 3.243, 95% CI [1.162–9.047], P = 0.025), leukocytosis (OR = 3.706, 95% CI [1.444–9.512], P = 0.006) and female (OR = 2.529, 95% CI [1.127–5.672], P = 0.024) were independent risk factors for sepsis. A nomogram was generated and displayed favorable fitting (Hosmer–Lemeshow test P = 0.797), discrimination (area under receiver operating characteristic curve was 0.807), and clinical usefulness by decision curve analysis. Conclusions Patients with certain preoperative characteristics, such as female, lower AGR, positive urine culture, and leukocytosis, who undergo PCNL may have a higher risk of developing sepsis. A cautious preoperative evaluation and optimized treatment strategy should be considered in these patients to minimize infectious complications.
Xun et al. (2020) A preoperative nomogram for sepsis in percutaneous nephrolithotomy treating solitary, unilateral and proximal ureteral stones. PeerJ 8:e9435 https://doi.org/10.7717/peerj.9435
Integrative analysis of competitive endogenous RNA network reveals the regulatory role of non-coding RNAs in high-glucose-induced human retinal endothelial cells
Background Increasing evidence has suggested that non-coding RNAs (ncRNAs) play critical roles in the pathogenesis of diabetic retinopathy (DR), but their underlying mechanisms remain unclear. The purpose of this study was to determine latent key genes and to structure a competing endogenous RNA (ceRNA) regulatory network to discover the potential molecular mechanisms governing the effects of high glucose on human retinal endothelial cells (HRECs). Methods We obtained microarray data for long non-coding RNA (lncRNA) and mRNA of high-glucose-induced HREC samples from NCBI GEO datasets. The ceRNA network was screened using intersecting prediction results from miRcode, TargetScan, miRTarBase and miRDB. The protein–protein interaction (PPI) network was constructed using the Search Tool for the Retrieval of Interacting Genes and hub genes were obtained using the cytoHubba app. The ClusterProfiler package was applied for performing Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. The expression of key RNAs was verified using the qRT-PCR method. A key ceRNA subnetwork was constructed based on the criticality of the genes and its binding sites were verified by luciferase reporter assay. The viability and apoptosis of HRECs were tested using the transfection of the miR-449c inhibitor. Results A total of 3,328 lncRNAs and 2,017 mRNAs were screened for differentially expressed (DE) profiles. The newly constructed ceRNA network was composed of 410 lncRNAs, 35 miRNAs and 122 mRNAs. The 10 hub genes were identified through the PPI network. GO and KEGG analysis revealed that DE mRNAs were mainly related to the positive regulation of the mRNA catabolic process, cell polarity, and the G1/S transition of mitotic and cell cycle signaling pathways. QRT-PCR was used to verify RNAs and the most important genes were screened out. A key ceRNA subnetwork OIP5-AS1/miR-449c/MYC was established. The binding site was verified by luciferase reporter assay. The expression levels of OIP5-AS1 and MYC increased after miR-449c inhibitor transfection, miR-449c decreased, HRECs activity increased, and apoptosis decreased, compared with the control group. Conclusion We successfully built the key ceRNA subnetwork, OIP5-AS1/miR-449c/MYC, by applying the GEO database for data analysis and mining. The results from the ceRNA network allow us to better understand the effect of ncRNAs on HRECs under hyperglycemic conditions and the pathogenesis of DR.
Cao et al. (2020) Integrative analysis of competitive endogenous RNA network reveals the regulatory role of non-coding RNAs in high-glucose-induced human retinal endothelial cells. PeerJ 8:e9452 https://doi.org/10.7717/peerj.9452
Gait characteristics in individuals with Parkinson’s disease during 1-minute treadmill walking
Background No previous study has examined the age-dependent characteristics of gait in individuals between 50 and 79 years simultaneously in healthy individuals and individuals with Parkinson’s disease (PD) over continuous gait cycles. This study aimed to investigate age-related differences in gait characteristics on individuals age ranged 50–79 years, including individuals with PD, during a 1-minute treadmill walking session. Additionally, we aimed to investigate the differences associated with spatiotemporal gait parameters and PD compared in age-matched individuals. Methods This study included 26 individuals with PD and 90 participants age ranged 50–79 years. The treadmill walking test at a self-preferred speed was performed for 1 min. The embedded inertial measurement unit sensor in the left and right outsoles-based system was used to collect gait characteristics based on tri-axial acceleration and tri-axial angular velocities. Results Participants aged >60 years had a decreased gait speed and shortened stride and step, which may demonstrate a distinct shift in aging (all p < 0.005). Individuals with PD showed more of a decrease in variables with a loss of consistency, including gait asymmetry (GA), phase coordination index (PCI) and coefficient of variation (CV) of all variables, than age-matched individuals (all p < 0.001). Gait speed, stride and step length, stance phase, variability, GA and PCI were the variables that highly depended on age and PD. Discussion Older adults could be considered those older than 60 years of age when gait alterations begin, such as a decreased gait speed as well as shortened stride and step length. On the other hand, a loss of consistency in spatiotemporal parameters and a higher GA and PCI could be used to identify individuals with PD. Thus, the CV of all spatiotemporal parameters, GA and PCI during walking could play an important role and be useful in identifying individuals with PD. Conclusion This study provided the notable aging pattern characteristics of gait in individuals >50 years, including individuals with PD. Increasing age after 60 years is associated with deterioration in spatiotemporal parameters of gait during continuous 1-minute treadmill walking. Additionally, GA, PCI and the CV of all variables could be used to identify PD which would be placed after 70 years of age. It may be useful to determine the decline of gait performance in general and among individuals with PD.
Noh et al. (2020) Gait characteristics in individuals with Parkinson’s disease during 1-minute treadmill walking. PeerJ 8:e9463 https://doi.org/10.7717/peerj.9463
Hemogram data as a tool for decision-making in COVID-19 management: applications to resource scarcity scenarios
Background COVID-19 pandemics has challenged emergency response systems worldwide, with widespread reports of essential services breakdown and collapse of health care structure. A critical element involves essential workforce management since current protocols recommend release from duty for symptomatic individuals, including essential personnel. Testing capacity is also problematic in several countries, where diagnosis demand outnumbers available local testing capacity. Purpose This work describes a machine learning model derived from hemogram exam data performed in symptomatic patients and how they can be used to predict qRT-PCR test results. Methods Hemogram exams data from 510 symptomatic patients (73 positives and 437 negatives) were used to model and predict qRT-PCR results through Naïve-Bayes algorithms. Different scarcity scenarios were simulated, including symptomatic essential workforce management and absence of diagnostic tests. Adjusts in assumed prior probabilities allow fine-tuning of the model, according to actual prediction context. Results Proposed models can predict COVID-19 qRT-PCR results in symptomatic individuals with high accuracy, sensitivity and specificity, yielding a 100% sensitivity and 22.6% specificity with a prior of 0.9999; 76.7% for both sensitivity and specificity with a prior of 0.2933; and 0% sensitivity and 100% specificity with a prior of 0.001. Regarding background scarcity context, resources allocation can be significantly improved when model-based patient selection is observed, compared to random choice. Conclusions Machine learning models can be derived from widely available, quick, and inexpensive exam data in order to predict qRT-PCR results used in COVID-19 diagnosis. These models can be used to assist strategic decision-making in resource scarcity scenarios, including personnel shortage, lack of medical resources, and testing insufficiency.
Avila et al. (2020) Hemogram data as a tool for decision-making in COVID-19 management: applications to resource scarcity scenarios. PeerJ 8:e9482 https://doi.org/10.7717/peerj.9482