Liver slice culture as a model for lipid metabolism in fish
Hepatic lipid metabolism is traditionally investigated in vitro using hepatocyte monocultures lacking the complex three-dimensional structure and interacting cell types essential liver function. Precision cut liver slice (PCLS) culture represents an alternative in vitro system, which benefits from retention of tissue architecture. Here, we present the first comprehensive evaluation of the PCLS method in fish (Atlantic salmon, Salmo salar L.) and validate it in the context of lipid metabolism using feeding trials, extensive transcriptomic data, and fatty acid measurements. We observe an initial period of post-slicing global transcriptome adjustment, which plateaued after 3 days in major metabolic pathways and stabilized through 9 days. PCLS fed alpha-linolenic acid (ALA) and insulin responded in a liver-like manner, increasing lipid biosynthesis gene expression. We identify interactions between insulin and ALA, where two PUFA biosynthesis genes that were induced by insulin or ALA alone, were highly down-regulated when insulin and ALA were combined. We also find that transcriptomic profiles of liver slices are exceedingly more similar to whole liver than hepatocyte monocultures, both for lipid metabolism and liver marker genes. PCLS culture opens new avenues for high throughput experimentation on the effect of “novel feed composition” and represent a promising new strategy for studying genotype-specific molecular features of metabolism.
Harvey et al. (2019) Liver slice culture as a model for lipid metabolism in fish. PeerJ 7:e7732 https://doi.org/10.7717/peerj.7732
Engrailed 1 overexpression as a potential prognostic marker in Lower Grade Glioma
Background Engrailed 1 (EN1), as a member of homeobox-containing transcription factors, participates in the development of the brain. High expressions of EN1 exist in various tumors. However, the role of EN1 in lower grade glioma (LGG) is still unknown. Methods Coefficients of Cox regression were examined by data mining among 13 cancer types using OncoLnc to validate EN1 expressions in LGG patients from The Cancer Genome Atlas database (TCGA). Bioinformatic analysis was performed by using R2 and the UCSC Xena browser based on the data from 273 glioma cases in GSE16011 from GEO datasets and 530 cases of LGG patients in TCGA. Cases in GSE16011 were divided into two groups according to IDH1 mutation status. Cases in TCGA-LGG were classified to subtypes according to histopathological results, IDH1 mutation status and 1p19q status. The Kaplan–Meier survival curves were performed to analyze the relationship between EN1 expressions and clinicopathological characteristics and survival time respectively. Results Cox regression results showed that LGG was ranked statistically first among 13 different cancer types according to the false discovery rate (FDR) correction. Results from GSE16011 showed that: glioma, LGG and LGG with IDH1 mutation patients with high EN1 expressions had significantly shorter 5, 10, and 15-year overall survival time (OS) (p < 0.001). Similar results from TCGA-LGG showed that LGG patients with high EN1 expressions had significantly shorter 15-year OS, irrespective of IDH1 mutation and 1p19q co-deletion (p < 0.001). The astrocytoma subgroup showed highest levels of EN1 expression and shortest 5, 10 and 15-year OS compared with oligoastrocytoma and oligodendroglioma (p < 0.05). Conclusion EN1 can be used as a prognostic marker in LGG patients, combined with IDH1 mutation and 1p19q co-deletion.
Zhu et al. (2019) Engrailed 1 overexpression as a potential prognostic marker in Lower Grade Glioma. PeerJ 7:e7414 https://doi.org/10.7717/peerj.7414
Seasonal and inter-annual community structure characteristics of zooplankton driven by water environment factors in a sub-lake of Lake Poyang, China
Background Sub-lakes are important for the maintenance of the ecosystem integrity of Lake Poyang, and zooplankton play an important role in its substance and energy flow. Methods A seasonal investigation of zooplankton was conducted in spring (April), summer (July), autumn (October) and winter (January of the following year) from 2012 to 2016 in a sub-lake of Lake Poyang. The aim of the present study was to understand the seasonal dynamics and interannual variation of zooplankton communities and their relationship to environmental factors. Results A total of 115 species were identified in all samples in the four years, which comprised of 87 Rotifera, 13 Cladocera and 15 Copepoda. Rotifera was the dominant group in terms of quantity, and its species richness and abundance were significantly higher when compared to Cladocera and Copepoda (P < 0.05), while Cladocera dominated in terms of biomass. The species richness of Rotifera exhibited a significant seasonal difference (P < 0.05). Both the density and biomass of zooplankton revealed significant seasonal differences (P < 0.05). In general, the density and biomass of zooplankton were higher in summer and autumn, when compared to winter and spring. Biodiversity indices were dramatically lower in spring than in the other seasons. The non-metric multidimensional scaling (NMDS) analysis suggested that these zooplankton communities can be divided into three groups: spring community, summer-autumn community, and winter community. The seasonal succession of zooplankton communities did not have interannual reproducibility. In high water level years, the dominant species of zooplankton (Cladocerans and Copepods) in the wet season had a lower density, and the result in low water level years was exactly the opposite. The redundancy analysis revealed that water temperature (WT), conductivity, pH and dissolved oxygen (DO) had significant effects on the zooplankton community. Conclusions The community structure of zooplankton has a significant seasonal pattern, but has no interannual repeatability. In high water level years, the dominant species of zooplankton (Cladocerans and Copepods) in the wet season had a lower density, and the result in low water level years was exactly the opposite. The density, biomass and diversity indices of zooplankton were significantly different in different seasons. The present study was helpful in the further understanding of the ecosystem stability of lakes connected with rivers, providing scientific guidance for the protection of lake wetlands.
Hu et al. (2019) Seasonal and inter-annual community structure characteristics of zooplankton driven by water environment factors in a sub-lake of Lake Poyang, China. PeerJ 7:e7590 https://doi.org/10.7717/peerj.7590
Nomogram for predicting cancer specific survival in inflammatory breast carcinoma: a SEER population-based study
The clinicopathological features of inflammatory breast carcinoma (IBC), the effect of therapeutic options on survival outcome and the identification of prognostic factors were investigated in this study. Information on IBC patients were extracted from the Surveillance, Epidemiology, and End Results (SEER) database between 2010 and 2015. Cox proportional hazard regression was used to determine potential significant prognostic factors of IBC. A nomogram was then constructed to evaluate patient survival based on certain variables. Univariate and multivariate analyses revealed that race (p < 0.001), M stage (p < 0.001), surgery (p = 0.010), chemotherapy (CT) (p < 0.001), tumor size (p = 0.010), estrogen receptor (p < 0.001), progesterone receptor (p = 0.04), and human epidermal growth factor receptor 2 (p < 0.001) were all independent risk factors. The concordance index (C-index) of the nomogram was 0.735, which showed good predictive efficiency. Survival analysis indicated that IBC patients without CT had poorer survival than those with CT (p < 0.001). Stratified analyses showed that modified radical mastectomy (MRM) had significant survival advantages over non-MRM in patients with stage IV IBC (p = 0.031). Patients treated with or without CT stratified by stage III and stage IV showed better survival than those without stage III and IV (p < 0.001). Trimodality therapy resulted in better survival than surgery combined with CT or CT alone (p < 0.001). Competing risk analysis also showed the same results. The nomogram was effectively applied to predict the 1, 3 and 5-year survival of IBC. Our nomogram showed relatively good accuracy with a C-index of 0.735 and is a visualized individually predictive tool for prognosis. Treatment strategy greatly affected the survival of patients. Trimodality therapy was the preferable therapeutic strategy for IBC. Further prospective studies are needed to validate these findings.
Zhang et al. (2019) Nomogram for predicting cancer specific survival in inflammatory breast carcinoma: a SEER population-based study. PeerJ 7:e7659 https://doi.org/10.7717/peerj.7659
Land use management based on multi-scenario allocation and trade-offs of ecosystem services in Wafangdian County, Liaoning Province, China
Developing effective methods to coordinate the trade-offs among ecosystem services (ES) is important for achieving inclusive growth and sustainable development, and has been the focus of scholars and ecosystem managers globally. Using remote sensing and geographic information system (GIS) data, our study examined Wafangdian County of Liaoning Province as a case study to reveal the spatiotemporal evolution of four ES (food supply [FS], net primary productivity [NPP], water yield [WY], and soil conservation [SC]) and changes among their interactions. Then, an ordered weighted averaging model was introduced to simulate the optimal scenario of ES allocation. Results showed that: (1) the spatial and temporal changes in ES were significant over 14 years. All ES presented an inverted U-shaped growth curve from 2000–2014. (2) Synergies were observed within provisioning services, and there were trade-offs between provisioning services and regulating services, as well as provisioning services and supporting services. (3) The optimal scenario for Wafangdian was scenario 5 (trade-off coefficient, 0.68). The allocation of FS, NPP, WY, and SC in scenario 5 were 0.187, 0.427, 0.131, and 0.063, respectively. Implementing each ES weight of optimal scenario in land use management contributed to achieving intercoordination of ES. We propose to coordinate land and sea management to restore natural habitats that were expanded into in the high ES area. It is our anticipation that this study could provide a scientific basis for optimizing the allocation of ES and improving land use structure of coastal zones in the future.
Spatial and Geographic Information Science
Zhao et al. (2019) Land use management based on multi-scenario allocation and trade-offs of ecosystem services in Wafangdian County, Liaoning Province, China. PeerJ 7:e7673 https://doi.org/10.7717/peerj.7673
Why the long face? Comparative shape analysis of miniature, pony, and other horse skulls reveals changes in ontogenetic growth
Background Much of the shape variation found in animals is based on allometry and heterochrony. Horses represent an excellent model to investigate patterns of size-shape variation among breeds that were intentionally bred for extreme small and large sizes. Methods We tested whether ponies (wither height < 148 cm) have a diverging size-shape relationship in skull shape as compared to regular-sized horse breeds (wither height > 148 cm, here-after called horses) during ontogenetic growth. We used a dataset of 194 specimens from 25 horse and 13 pony breeds, two of which are miniature breeds (wither height < 96.5 cm)—Falabella, Shetland. We applied three-dimensional geometric morphometrics, linear measurements, and multivariate analyses (Procrustes ANOVAs) to quantitatively examine and compare the ontogenetic trajectories between pony and horse breeds with an emphasis on the miniature breeds as an extreme case of artificial selection on size. Additionally, we tested for juvenile characteristics in adult horse and miniature breeds that could resemble “paedomorphosis”—retention of juvenile characteristics in adult stage; e.g. large eyes, large braincase-to-face-relationship, and large head-to-body relationship. Results Allometric regression of size on shape revealed that 42% of shape variation could be explained by variation in size in all breeds. The ontogenetic trajectories of ponies and horses vary in slope and therefore in rate of change per unit size, and length. The differences in trajectory lengths and slopes result in ponies having a similar skull shape in an older age stage than horses of the same size in a younger age stage. This pattern could cause the generally perceived “paedomorphic” appearance of ponies. Miniature breeds have larger heads in relation to wither height compared to horses, a non-paedomorphic feature in horses specifically. Also, rostra (faces) are longer in adult individuals than in juveniles across all kinds of breeds. This pattern can be explained by the long-face hypothesis for grazing ungulates and could possibly be caused by the mismatch of selection by humans for shorter rostra and the dentition of ruminants. Conclusions Miniature breed specimens do not exhibit any of the classical mammalian “paedomorphic” features (large orbits, large heads), except for the adult Falabella that has enlarged orbits, possibly because they are herbivorous ungulates that are affected by functional and metabolic constraints related to low nutrient-food consumption. Instead ponies, including miniature breeds, have faster and shorter ontogenetic growth compared to horses, resulting in adult pony skulls looking in part like juvenile horse skulls.
Heck et al. (2019) Why the long face? Comparative shape analysis of miniature, pony, and other horse skulls reveals changes in ontogenetic growth. PeerJ 7:e7678 https://doi.org/10.7717/peerj.7678
Effects of Lecanicillium lecanii strain JMC-01 on the physiology, biochemistry, and mortality of Bemisia tabaci Q-biotype nymphs
Background Lecanicillium lecanii is an entomopathogenic fungi, which was isolated from insects suffering from disease. Now, it is an effective bio-control resource that can control agricultural pests such as whitefly and aphids. There are many studies on the control of various agricultural pests by L. lecanii, but no report on its control of Bemisia tabaci biotype-Q exists. In this work, we studied the susceptibility of B. tabaci Q-biotype (from Ningxia, China) to L. lecanii JMC-01 in terms of nymph mortality and the changes in detoxifying protective enzymes activities. Methods B. tabaci nymphs were exposed to L. lecanii JMC-01 conidia by immersion with the host culture. Mortality was assessed daily for all nymph stages. The detoxifying and protective enzyme activity changes, weight changes, and fat, and water contents of the nymphs were determined spectrophotometrically. Results All instars of B. tabaci died after being infested with 1 × 108 conidia/mL. The 2nd-instar nymphs were the most susceptible, followed by the 3rd-instar nymphs. The corrected cumulative mortality of the 2nd- and 3rd-instar nymphs was 82.22% and 75.55%, respectively. The levels of detoxifying and protective enzymes initially increased and then decreased. The highest activities of carboxylesterase, acetylcholinesterase, peroxidase, and catalase occurred on the 3rd day, reaching 10.5, 0.32, 20, and 6.3 U/mg prot, respectively. These levels were 2.2-, 4.3-, 2.4-, and 1.4-fold the control levels, respectively. The highest activities of glutathione-S transferase and superoxide dismutase on the 2nd day were, respectively, 64 and 43.5 U/mg prot. These levels were, respectively, 2.7 and 1.1-fold that of the control level. The water and fat content in the infected B. tabaci nymphs decreased and differed significantly from the control levels. The weight increased continuously in the first 24 h, decreasing thereafter. At 72 h, the infestation level was about 0.78-fold that of the control level. Conclusions The studied L. lecanii JMC-01 strain is pathogenic to the B. tabaci Q-biotype. This strain interferes with the normal functioning of detoxifying and protective enzymes, and is also involved in the disruption of normal physiological metabolism in B. tabaci.
Xie et al. (2019) Effects of Lecanicillium lecanii strain JMC-01 on the physiology, biochemistry, and mortality of Bemisia tabaci Q-biotype nymphs. PeerJ 7:e7690 https://doi.org/10.7717/peerj.7690
The mineralization characteristics of organic carbon and particle composition analysis in reconstructed soil with different proportions of soft rock and sand
The organic carbon mineralization process reflects the release intensity of soil CO2. Therefore, the study of organic carbon mineralization and particle composition analysis of soft rock and sand compound soil can provide technical support and a theoretical basis for soil organic reconstruction (soil structure, materials and biological nutrition). Based on previous research, four treatments were selected: CK (soft rock:sand=0:1), C1 (soft rock:sand=1:5), C2 (soft rock:sand=1:2) and C3 (soft rock:sand=1:1), respectively. Specifically, we analyzed the organic carbon mineralization process and soil particle composition by lye absorption, laser granulometer, and scanning electron microscope. The results showed that there was no significant difference in organic carbon content between C1, C2 , and C3 treatments, but they were significantly higher than in the CK treatment (P < 0.05). The organic carbon mineralization rate in each treatment accords with a logarithmic function throughout the incubation period (P < 0.01), which can be divided into a rapid decline phase in days 1 to 11 followed by a steady decline phase in days 11 to 30. The cumulative mineralization on the 11th day reached 54.96%–74.44% of the total mineralization amount. At the end of the incubation, the cumulative mineralization and potential mineralizable organic carbon content of the C1, C2 and C3 treatments were significantly higher than those of the CK treatment. The cumulative mineralization rate was also the lowest in the C1 and C2 treatment. The turnover rate constant of soil organic carbon in each treatment was significantly lower than that of the CK treatment, and the residence time increased. With the increase of volume fraction of soft rock, the content of silt and clay particles increased gradually, the texture of soil changed from sandy soil to sandy loam, loam , and silty loam, respectively. With the increase of small particles, the structure of soil appear ed to collapse when the volume ratio of soft rock was 50%. A comprehensive mineralization index and scanning electron microscopy analysis, when the ratio of soft rock to sand volume was 1:5–1:2, this can effectively increase the accumulation of soil organic carbon. Then, the distribution of soil particles was more uniform, the soil structure was stable (not collapsed), and the mineralization level of unit organic carbon was lower. Our research results have practical significance for the large area popularization of soft rock and sand compound technology.
Guo et al. (2019) The mineralization characteristics of organic carbon and particle composition analysis in reconstructed soil with different proportions of soft rock and sand. PeerJ 7:e7707 https://doi.org/10.7717/peerj.7707
AURKB: a promising biomarker in clear cell renal cell carcinoma
Background Aurora kinase B (AURKB) is an important carcinogenic factor in various tumors, while its role in clear cell renal cell carcinoma (ccRCC) still remains unclear. This study aimed to investigate its prognostic value and mechanism of action in ccRCC. Methods Gene expression profiles and clinical data of ccRCC patients were downloaded from The Cancer Genome Atlas database. R software was utilized to analyze the expression and prognostic role of AURKB in ccRCC. Gene set enrichment analysis (GSEA) was used to analyze AURKB related signaling pathways in ccRCC. Results AURKB was expressed at higher levels in ccRCC tissues than normal kidney tissues. Increased AURKB expression in ccRCC correlated with high histological grade, pathological stage, T stage, N stage and distant metastasis (M stage). Kaplan-Meier survival analysis suggested that high AURKB expression patients had a worse prognosis than patients with low AURKB expression levels. Multivariate Cox analysis showed that AURKB expression is a prognostic factor of ccRCC. GSEA indicated that genes involved in autoimmune thyroid disease, intestinal immune network for IgA production, antigen processing and presentation, cytokine-cytokine receptor interaction, asthma, etc., were differentially enriched in the AURKB high expression phenotype. Conclusions AURKB is a promising biomarker for predicting prognosis of ccRCC patients and a potential therapeutic target. In addition, AURKB might regulate progression of ccRCC through modulating intestinal immune network for IgA production and cytokine-cytokine receptor interaction, etc. signaling pathways. However, more research is necessary to validate the findings.
Wan et al. (2019) AURKB: a promising biomarker in clear cell renal cell carcinoma. PeerJ 7:e7718 https://doi.org/10.7717/peerj.7718
Prediction model for patients with acute respiratory distress syndrome: use of a genetic algorithm to develop a neural network model
Background Acute respiratory distress syndrome (ARDS) is associated with significantly increased risk of death, and early risk stratification may help to choose the appropriate treatment. The study aimed to develop a neural network model by using a genetic algorithm (GA) for the prediction of mortality in patients with ARDS. Methods This was a secondary analysis of two multicenter randomized controlled trials conducted in forty-four hospitals that are members of the National Heart, Lung, and Blood Institute, founded to create an acute respiratory distress syndrome Clinical Trials Network. Model training and validation were performed using the SAILS and OMEGA studies, respectively. A GA was employed to screen variables in order to predict 90-day mortality, and a neural network model was trained for the prediction. This machine learning model was compared to the logistic regression model and APACHE III score in the validation cohort. Results A total number of 1,071 ARDS patients were included for analysis. The GA search identified seven important variables, which were age, AIDS, leukemia, metastatic tumor, hepatic failure, lowest albumin, and FiO2. A representative neural network model was constructed using the forward selection procedure. The area under the curve (AUC) of the neural network model evaluated with the validation cohort was 0.821 (95% CI [0.753–0.888]), which was greater than the APACHE III score (0.665; 95% CI [0.590–0.739]; p = 0.002 by Delong’s test) and logistic regression model, albeit not statistically significant (0.743; 95% CI [0.669–0.817], p = 0.130 by Delong’s test). Conclusions The study developed a neural network model using a GA, which outperformed conventional scoring systems for the prediction of mortality in ARDS patients.
Zhang (2019) Prediction model for patients with acute respiratory distress syndrome: use of a genetic algorithm to develop a neural network model. PeerJ 7:e7719 https://doi.org/10.7717/peerj.7719