Proanthocyanidins reduce cellular function in the most globally diagnosed cancers in vitro
Background Growing evidence indicates that proanthocyanidins (PACs) may be effective in treating and preventing various cancers. The fundamental mechanism of PACs inhibiting the proliferation at cellular and molecular levels in most of the cancer types remains unclear. Objective The anticancer efficacy of PACs was investigated in vitro using three human cancer cell lines: human colorectal adenocarcinoma (HT-29), human breast carcinoma (MCF-7), and human prostatic adenocarcinoma (PC-3). Methods Cytotoxicity was evaluated by MTT assay, while cell proliferation was measured by trypan blue exclusion method. Cell migration was measured by wound healing assay, and DAPI staining was used to evaluate apoptotic nucleus morphology. RT-PCR was used to analyze the expression of Bax and Bcl-2, and caspase enzyme activity assay was measured by caspase colorimetric assay. Results PACs could inhibit both cellular viability and proliferation in a concentration- and time-dependent fashion in all investigated cells. Further, all tested cells showed similarly decreased migration after 24- and 48-h PAC treatment. We observed increased apoptotic nucleus morphology in treated cells (p ≤ 0.01). BAX expression significantly increased in HT-29 (p < 0.01), PC-3(p < 0.01), and MCF-7 (p < 0.05) cells, while BCL-2 expression significantly declined (p < 0.05). Caspase activities were significantly increased in all tested cancer cell lines after 24-h PAC treatment. Conclusion PACs may have potential therapeutic properties against colorectal, breast, and prostate cancer.
Albogami (2020) Proanthocyanidins reduce cellular function in the most globally diagnosed cancers in vitro. PeerJ 8:e9910 https://doi.org/10.7717/peerj.9910
Carbon emission and water use efficiency response to tillage methods and planting patterns of winter wheat in the North China Plain
Background Implementing sustainable farming practices for winter wheat (Triticum aestivum L.) in the North China Plain may be a way to reduce carbon emissions. No tillage generally results in less net CO2 loss from farmland, but no tillage also reduces the grain yield and water use efficiency (WUE) of winter wheat. Wide-precision planting of winter wheat may enhance the grain yield and WUE; however, it is not known precisely how tillage and planting patterns affect CO2 exchange, grain yield and WUE. Methods In this study, two tillage methods (conventional tillage, T and no tillage, NT) and two planting patterns (conventional planting, C and wide-precision planting, W) were used in two consecutive winter wheat growing seasons. Results Compared with the T treatments, the NT treatments had significantly lower cumulative net CO2 emissions in 2015–2016 and 2016–2017 (30.8 and 21.3%, respectively), and had lower grain yields (9.0 and 9.4%, respectively) and WUE (6.0 and 7.2%, respectively). The W treatments had a compensating effect on grain yield failure and reduced cumulative net CO2 emissions more than C treatments, thereby increasing WUE, reducing carbon emissions per unit water consumption, and increasing the yield carbon utilization efficiency (YCUE). The lowest cumulative CO2 emissions and highest YCUE were observed for NT with W treatment. Results from this analogous tillage experiment indicated that NT and W farming practices provide an option for reducing carbon emissions and enhancing WUE and YCUE for sustainable winter wheat development.
Ma et al. (2020) Carbon emission and water use efficiency response to tillage methods and planting patterns of winter wheat in the North China Plain. PeerJ 8:e9912 https://doi.org/10.7717/peerj.9912
Development of a novel nanoflow liquid chromatography-parallel reaction monitoring mass spectrometry-based method for quantification of angiotensin peptides in HUVEC cultures
Background This study aimed to develop an analytical method using liquid chromatography tandem mass spectrometry (LC-MS/MS) for the determination of angiotensin (Ang) I, Ang (1-9), Ang II, Ang (1-7), Ang (1-5), Ang III, Ang IV in human umbilical vein endothelial cell (HUVEC) culture supernatant. Methods HUVEC culture supernatant was added with gradient concentrations (0.05–1,000 ng/ml) of standard solutions of the Ang peptides. These samples underwent C18 solid-phase extraction and separation using a preconcentration nano-liquid chromatography mass spectrometry system. The target peptides were detected by a Q Exactive quadrupole orbitrap high-resolution mass spectrometer in the parallel reaction monitoring mode. Ang converting enzyme (ACE) in HUVECs was silenced to examine Ang I metabolism. Results The limit of detection was 0.1 pg for Ang II and Ang III, and 0.5 pg for Ang (1-9), Ang (1-7), and Ang (1-5). The linear detection range was 0.1–2,000 pg (0.05–1,000 ng/ml) for Ang II and Ang III, and 0.5–2,000 pg (0.25–1,000 ng/ml) for Ang (1-9) and Ang (1-5). Intra-day and inter-day precisions (relative standard deviation) were <10%. Ang II, Ang III, Ang IV, and Ang (1-5) were positively correlated with ACE expression by HUVECs, while Ang I, Ang (1-7), and Ang (1-9) were negatively correlated. Conclusion The nanoflow liquid chromatography-parallel reaction monitoring mass spectrometry-based methodology established in this study can evaluate the Ang peptides simultaneously in HUVEC culture supernatant.
He et al. (2020) Development of a novel nanoflow liquid chromatography-parallel reaction monitoring mass spectrometry-based method for quantification of angiotensin peptides in HUVEC cultures. PeerJ 8:e9941 https://doi.org/10.7717/peerj.9941
Numerical investigation of microbial quorum sensing under various flow conditions
Microorganisms efficiently coordinate phenotype expressions through a decision-making process known as quorum sensing (QS). We investigated QS amongst distinct, spatially distributed microbial aggregates under various flow conditions using a process-driven numerical model. Model simulations assess the conditions suitable for QS induction and quantify the importance of advective transport of signaling molecules. In addition, advection dilutes signaling molecules so that faster flow conditions require higher microbial densities, faster signal production rates, or higher sensitivities to signaling molecules to induce QS. However, autoinduction of signal production can substantially increase the transport distance of signaling molecules in both upstream and downstream directions. We present empirical approximations to the solutions of the advection–diffusion–reaction equation that describe the concentration profiles of signaling molecules for a wide range of flow and reaction rates. These empirical relationships, which predict the distribution of dissolved solutes along pore channels, allow to quantitatively estimate the effective communication distances amongst multiple microbial aggregates without further numerical simulations.
Jung et al. (2020) Numerical investigation of microbial quorum sensing under various flow conditions. PeerJ 8:e9942 https://doi.org/10.7717/peerj.9942
TET1 may contribute to hypoxia-induced epithelial to mesenchymal transition of endometrial epithelial cells in endometriosis
Background Endometriosis (EMs) is a non-malignant gynecological disease, whose pathogenesis remains to be clarified. Recent studies have found that hypoxia induces epithelial-mesenchymal transition (EMT) as well as epigenetic modification in EMs. However, the relationship between EMT and demethylation modification under hypoxia status in EMs remains unknown. Methods The expression of N-cadherin, E-cadherin and TET1 in normal endometria, eutopic endometria and ovarian endometriomas was assessed by immunohistochemistry and immunofluorescence double staining. 5-hmC was detected by fluorescence-based ELISA kit using a specific 5-hmC antibody. Overexpression and inhibition of TET1 or hypoxia-inducible factor 2α (HIF-2α) were performed by plasmid and siRNA transfection. The expression of HIF-2α, TET1 and EMT markers in Ishikawa (ISK) cells (widely used as endometrial epithelial cells) was evaluated by western blotting. The interaction of HIF-2α and TET1 was analyzed by chromatin immunoprecipitation. Results Demethylation enzyme TET1 (ten-eleven translocation1) was elevated in glandular epithelium of ovarian endometrioma, along with the activation of EMT (increased expression of N-cadherin, and decreased expression of E-cadherin) and global increase of epigenetic modification marker 5-hmC(5-hydroxymethylcytosine). Besides, endometriosis lesions had more TET1 and N-cadherin co-localized cells. Further study showed that ISK cells exhibited enhanced EMT, and increased expression of TET1 and HIF-2α under hypoxic condition. Hypoxia-induced EMT was partly regulated by TET1 and HIF-2α. HIF-2α inhibition mitigated TET1 expression changes provoked by hypoxia. Conclusions Hypoxia induces the expression of TET1 regulated by HIF-2α, thus may promote EMT in endometriosis.
Wu et al. (2020) TET1 may contribute to hypoxia-induced epithelial to mesenchymal transition of endometrial epithelial cells in endometriosis. PeerJ 8:e9950 https://doi.org/10.7717/peerj.9950
Prophet forecasting model: a machine learning approach to predict the concentration of air pollutants (PM2.5, PM10, O3, NO2, SO2, CO) in Seoul, South Korea
Amidst recent industrialization in South Korea, Seoul has experienced high levels of air pollution, an issue that is magnified due to a lack of effective air pollution prediction techniques. In this study, the Prophet forecasting model (PFM) was used to predict both short-term and long-term air pollution in Seoul. The air pollutants forecasted in this study were PM2.5, PM10, O3, NO2, SO2, and CO, air pollutants responsible for numerous health conditions upon long-term exposure. Current chemical models to predict air pollution require complex source lists making them difficult to use. Machine learning models have also been implemented however their requirement of meteorological parameters render the models ineffective as additional models and infrastructure need to be in place to model meteorology. To address this, a model needs to be created that can accurately predict pollution based on time. A dataset containing three years worth of hourly air quality measurements in Seoul was sourced from the Seoul Open Data Plaza. To optimize the model, PFM has the following parameters: model type, changepoints, seasonality, holidays, and error. Cross validation was performed on the 2017–18 data; then, the model predicted 2019 values. To compare the predicted and actual values and determine the accuracy of the model, the statistical indicators: mean squared error (MSE), mean absolute error (MAE), root mean squared error (RMSE), and coverage were used. PFM predicted PM2.5 and PM10 with a MAE value of 12.6 µg/m3 and 19.6 µg/m3, respectively. PFM also predicted SO2 and CO with a MAE value of 0.00124 ppm and 0.207 ppm, respectively. PFM’s prediction of PM2.5 and PM10 had a MAE approximately 2 times and 4 times less, respectively, than comparable models. PFM’s prediction of SO2and CO had a MAE approximately five times and 50 times less, respectively, than comparable models. In most cases, PFM’s ability to accurately forecast the concentration of air pollutants in Seoul up to one year in advance outperformed similar models proposed in literature. This study addresses the limitations of the prior two PFM studies by expanding the modelled air pollutants from three pollutants to six pollutants while increasing the prediction time from 3 days to 1 year. This is also the first research to use PFM in Seoul, Korea. To achieve more accurate results, a larger air pollution dataset needs to be implemented with PFM. In the future, PFM should be used to predict and model air pollution in other regions, especially those without advanced infrastructure to model meteorology alongside air pollution. In Seoul, Seoul’s government can use PFM to accurately predict air pollution concentrations and plan accordingly.
Environmental Contamination and Remediation
Spatial and Geographic Information Science
Shen et al. (2020) Prophet forecasting model: a machine learning approach to predict the concentration of air pollutants (PM2.5, PM10, O3, NO2, SO2, CO) in Seoul, South Korea. PeerJ 8:e9961 https://doi.org/10.7717/peerj.9961
Seasonal and successional dynamics of size-dependent plant demographic rates in a tropical dry forest
Tropical forests are globally important for biodiversity conservation and climate change mitigation but are being converted to other land uses. Conversion of seasonally dry tropical forests (SDTF) is particularly high while their protection is low. Secondary succession allows forests to recover their structure, diversity and composition after conversion and subsequent abandonment and is influenced by demographic rates of the constituent species. However, how these rates vary between seasons for different plant sizes at different successional stages in SDTF is not known. The effect of seasonal drought may be more severe early in succession, when temperature and radiation are high, while competition and density-dependent processes may be more important at later stages, when vegetation is tall and dense. Besides, the effects of seasonality and successional stage may vary with plant size. Large plants can better compete with small plants for limiting resources and may also have a greater capacity to withstand stress. We asked how size-dependent density, species density, recruitment and mortality varied between seasons and successional stages in a SDTF. We monitored a chronosequence in Yucatan, Mexico, over six years in three 0.1 ha plots in each of three successional stages: early (3–5 years-old), intermediate (18–20 years-old) and advanced (>50 years-old). Recruitment, mortality and species gain and loss rates were calculated from wet and dry season censuses separately for large (diameter > 5 cm) and small (1–5 cm in diameter) plants. We used linear mixed-effects models to assess the effects of successional stage, seasonality and their changes through time on demographic rates and on plant and species density. Seasonality affected demographic rates and density of large plants, which exhibited high wet-season recruitment and species gain rates at the early stage and high wet-season mortality at the intermediate stage, resulting in an increase in plant and species density early in succession followed by a subsequent stabilization. Small plant density decreased steadily after only 5 years of land abandonment, whereas species density increased with successional stage. A decline in species dominance may be responsible for these contrasting patterns. Seasonality, successional stage and their changes through time had a stronger influence on large plants, likely because of large among-plot variation of small plants. Notwithstanding the short duration of our study, our results suggest that climate-change driven decreases in rainy season precipitation may have an influence on successional dynamics in our study forest as strong as, or even stronger than, prolonged or severe droughts during the dry season.
Saenz-Pedroza et al. (2020) Seasonal and successional dynamics of size-dependent plant demographic rates in a tropical dry forest. PeerJ 8:e9636 https://doi.org/10.7717/peerj.9636
Rediscovery of Cyperus flavescens (Cyperaceae) on the northeast periphery of its range in Europe
In recent years, three large populations of Cyperus flavescens were found in Poland, the richest occurrence of this species in over 30 years. The goal of this research is to determine the habitat factors lead to the mass occurrence of C. flavescens and the present situation of that species and its habitat in Central Europe. Soil conditions of the three populations were studied. To determine the correlation between the occurrence and abundance of species and the chemical parameters of the soil, the DCA and CCA methods were used. The DCA of environmental Ellenberg values was made for all relevés known from Poland. The occurrence of C. flavescens in plant communities in Central Europe was studied. The maximum entropy method was used for potential distribution analysis of C. flavescens. All analyzed traits are important for this species and none has an advantage over another, so the environmental factor affecting the occurrence of C. flavescens is different from the tested. Analysis on Ellenberg values indicate that the longest gradients are temperature, moisture and nutrients. The analysis of vegetation data involving Cyperus flavescens available from Central Europe indicates that this species occurs mainly in the company of Juncus bufonius and Plantago intermedia, whereas other species of the Isoëto-Nanojuncetea class appear rarely. In MaxEnt analysis based on bioclimatic variables, the most important variable is BIO1 (Annual Mean Temperature). The results of our observation indicate that anthropogenic factors such as grazing livestock have a positive effect on the occurrence of the species. It is also very likely that the species is promoted by very warm summers with only short periods of heavy rains. A map of the potential distribution of C. flavescens in Central Europe created according historical and future data show an extension of the range of potential habitats to the north and east.
Marciniuk et al. (2020) Rediscovery of Cyperus flavescens (Cyperaceae) on the northeast periphery of its range in Europe. PeerJ 8:e9837 https://doi.org/10.7717/peerj.9837
Potential role of cellular miRNAs in coronavirus-host interplay
Host miRNAs are known as important regulators of virus replication and pathogenesis. They can interact with various viruses through several possible mechanisms including direct binding of viral RNA. Identification of human miRNAs involved in coronavirus-host interplay becomes important due to the ongoing COVID-19 pandemic. In this article we performed computational prediction of high-confidence direct interactions between miRNAs and seven human coronavirus RNAs. As a result, we identified six miRNAs (miR-21-3p, miR-195-5p, miR-16-5p, miR-3065-5p, miR-424-5p and miR-421) with high binding probability across all analyzed viruses. Further bioinformatic analysis of binding sites revealed high conservativity of miRNA binding regions within RNAs of human coronaviruses and their strains. In order to discover the entire miRNA-virus interplay we further analyzed lungs miRNome of SARS-CoV infected mice using publicly available miRNA sequencing data. We found that miRNA miR-21-3p has the largest probability of binding the human coronavirus RNAs and being dramatically up-regulated in mouse lungs during infection induced by SARS-CoV.
Nersisyan et al. (2020) Potential role of cellular miRNAs in coronavirus-host interplay. PeerJ 8:e9994 https://doi.org/10.7717/peerj.9994
Unexpected diversity in the host-generalist oribatid mite Paraleius leontonychus (Oribatida, Scheloribatidae) phoretic on Palearctic bark beetles
Bark beetles are feared as pests in forestry but they also support a large number of other taxa that exploit the beetles and their galleries. Among arthropods, mites are the largest taxon associated with bark beetles. Many of these mites are phoretic and often involved in complex interactions with the beetles and other organisms. Within the oribatid mite family Scheloribatidae, only two of the three nominal species of Paraleius have been frequently found in galleries of bark beetles and on the beetles themselves. One of the species, P. leontonychus, has a wide distribution range spanning over three ecozones of the world and is believed to be a host generalist, reported from numerous bark beetle and tree species. In the present study, phylogenetic analyses of one mitochondrial and two nuclear genes identified six well supported, fairly divergent clades within P. leontonychus which we consider to represent distinct species based on molecular species delimitation methods and largely congruent clustering in mitochondrial and nuclear gene trees. These species do not tend to be strictly host specific and might occur syntopically. Moreover, mito-nuclear discordance indicates a case of past hybridization/introgression among distinct Paraleius species, the first case of interspecific hybridization reported in mites other than ticks.
Schäffer et al. (2020) Unexpected diversity in the host-generalist oribatid mite Paraleius leontonychus (Oribatida, Scheloribatidae) phoretic on Palearctic bark beetles. PeerJ 8:e9710 https://doi.org/10.7717/peerj.9710