Taxonomic revision of the Pheidole megacephala species-group (Hymenoptera, Formicidae) from the Malagasy Region
Background The Malagasy Region, one of the top megadiversity regions, hosts one of the highest numbers of endemic and threatened organisms on earth. One of the most spectacular examples of ant radiation on the island has occurred in the hyperdiverse genus Pheidole. To this date, there are 135 described Madagascan Pheidole divided into 16 species-groups, and 97% of Malagasy species are endemic to the island. This study is a taxonomic revision of the Pheidole megacephala group, one of only two species-groups comprising a combination of native, endemic taxa and widely distributed introduced species. Methods The diversity of the Malagasy members of the megacephala group was assessed via application of qualitative morphological and DNA sequence data. Qualitative, external morphological characteristics (e.g., head shape, gaster sculpture, body colouration) were evaluated in order to create a priori grouping hypotheses, and confirm and improve species delimitation. Mitochondrial DNA sequences from cytochrome oxidase I (COI) gene fragments were analyzed to test the putative species previously delimited by morphological analyses. Results We recognize three species belonging to the megacephala group: P. megacephala (Fabricius, 1793), P. megatron Fischer & Fisher, 2013 and P. spinosa Forel, 1891 stat. nov. Pheidole spinosa is redescribed and elevated to the species level. The following names are recognized as junior synonyms of P. spinosa: P. megacephala scabrior Forel, 1891 syn. nov., P. picata Forel, 1891 syn. nov., P. picata gietleni Forel, 1905 syn. nov., P. picata bernhardae Emery, 1915 syn. nov., and P. decepticon Fischer & Fisher, 2013 syn. nov. The results are supplemented with an identification key to species for major workers of the megacephala group, high-resolution images for major and minor workers, and comments on the distribution and biology of all Malagasy members of the group. Our study revealed that Pheidole megacephala, a species listed among the 100 worst invasive species worldwide, occurs in both natural and disturbed sites in the Malagasy region. The two remaining members of the megacephala group, most likely endemic to this region, are also present in anthropogenic habitats and often co-occur with P. megacephala. It appears that the Malagasy members of the group are generalists and dominant in anthropogenic habitats. Additionally, we documented the presence of supermajors in colonies of P. spinosa—a phenomenon previously not known for this group.
Salata et al. (2022) Taxonomic revision of the Pheidole megacephala species-group (Hymenoptera, Formicidae) from the Malagasy Region. PeerJ 10:e13263 https://doi.org/10.7717/peerj.13263
Radar remote sensing-based inversion model of soil salt content at different depths under vegetation
Excessive soil salt content (SSC) seriously affects the crop growth and economic benefits in the agricultural production area. Prior research mainly focused on estimating the salinity in the top bare soil rather than in deep soil that is vital to crop growth. For this end, an experiment was carried out in the Hetao Irrigation District, Inner Mongolia, China. In the experiment, the SSC at different depths under vegetation was measured, and the Sentinel-1 radar images were obtained synchronously. The radar backscattering coefficients (VV and VH) were combined to construct multiple indices, whose sensitivity was then analyzed using the best subset selection (BSS). Meanwhile, four most commonly used algorithms, partial least squares regression (PLSR), quantile regression (QR), support vector machine (SVM), and extreme learning machine (ELM), were utilized to construct estimation models of salinity at the depths of 0–10, 10–20, 0–20, 20–40, 0–40, 40–60 and 0–60 cm before and after BSS, respectively. The results showed: (a) radar remote sensing can be used to estimate the salinity in the root zone of vegetation (0-30 cm); (b) after BSS, the correlation coefficients and estimation accuracy of the four monitoring models were all improved significantly; (c) the estimation accuracy of the four regression models was: SVM > QR > ELM > PLSR; and (d) among the seven sampling depths, 10–20 cm was the optimal inversion depth for all the four models, followed by 20–40 and 0–40 cm. Among the four models, SVM was higher in accuracy than the other three at 10–20 cm (RP2 = 0.67, RMSEP = 0.12%). These findings can provide valuable guidance for soil salinity monitoring and agricultural production in the arid or semi-arid areas under vegetation.
Spatial and Geographic Information Science
Chen et al. (2022) Radar remote sensing-based inversion model of soil salt content at different depths under vegetation. PeerJ 10:e13306 https://doi.org/10.7717/peerj.13306
Analysis of professional soccer players in competitive match play based on submaximum intensity periods
The main objective of this study is to analyse sub-maximum intensity periods (SubMIP’s) manifested by professional soccer players during official matches (number of events and time spent in each event), according to the player position, match halve and match, and also to group the players according to their SubMip values during the competition. Methods We collected a total of 247 individual records of 14 players using Global Positioning System (GPS) during 15 official league matches (Azerbaijan Premier League 2019–2020). We calculated both the number of SubMIPs events and the time each player spent in the SubMIPs zone (threshold of 85% MIP). We analysed the possible independence of the variables with the Kruskal–Wallis test and the possible specific relationships between the groups using a post-hoc analysis with Dunn’s test. In order to explore the possible distribution of physical demands in homogeneous groups, a cluster analysis was performed. Results The statistical analysis showed significant differences between the individual variables in the number of events and in the time spent by the player above the threshold in distance covered at speed >19.8 km/h (HSR), distance covered at speed >25.2 km/h (Sprint), acceleration density (AccDens), mean metabolic power (MetPow), metres per minute (Mmin) and high metabolic load distance >25.5 W/kg (HMLD). Differences were also found according to the playing position in MetPow, Mmin and between halves in AccDens, MetPow, Mmin. In the clustering based on the time spent by the player in SubMIPs, three main groups were described: (1) the centroid was located in lower values in each of the variables; (2) there were an accentuation of the AccDens variable; (3) all the variables, except AccDens, were accentuated. Conclusions The main differences with regard to SubMIPs were related to the player’s individual physical performance and not to position. However, the player’s position could act as an attractor and show significant differences during matches.
Caro et al. (2022) Analysis of professional soccer players in competitive match play based on submaximum intensity periods. PeerJ 10:e13309 https://doi.org/10.7717/peerj.13309
Integrated bioinformatics analysis for the identification of hub genes and signaling pathways related to circANRIL
Background Antisense noncoding RNA in the INK4 locus (ANRIL) is located on human chromosome 9p21, and modulation of ANRIL expression mediates susceptibility to some important human disease, including atherosclerosis (AS) and tumors, by affecting the cell cycle circANRIL and linear ANRIL are isoforms of ANRIL. However, it remains unclear whether these isoforms have distinct functions. In our research, we constructed a circANRIL overexpression plasmid, transfected it into HEK-293T cell line, and explored potential core genes and signaling pathways related to the important differential mechanisms between the circANRIL-overexpressing cell line and control cells through bioinformatics analysis. Methods Stable circANRIL-overexpressing (circANRIL-OE) HEK-293T cells and control cells were generated by infection with the circANRIL-OE lentiviral vector or a negative control vector, and successful transfection was confirmed by conventional flurescence microscopy and quantitative real-time PCR (qRT-PCR). Next, differentially expressed genes (DEGs) between circANRIL-OE cells and control cells were detected. Subsequently, Gene Ontology (GO) biological process (BP) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed to explore the principal functions of the significant DEGs. A protein–protein interaction (PPI) network and competing endogenous RNA (ceRNA) network were constructed in Cytoscape to determine circularRNA (circRNA)- microRNA(miRNA)-messenger RNA (mRNA) interactions and hub genes, and qRT-PCR was used to verify changes in the expression of these identified target genes. Results The successful construction of circANRIL-OE cells was confirmed by plasmid sequencing, visualization with fluorescence microscopy and qRT-PCR. A total of 1745 DEGs between the circANRIL-OE group and control were identified, GO BP analysis showed that these genes were mostly related to RNA biosynthesis and processing, regulation of transcription and signal transduction. The KEGG pathway analysis showed that the up regulated DEGs were mainly enriched in the MAPK signaling pathway. Five associated target genes were identified in the ceRNA network and biological function analyses. The mRNA levels of these five genes and ANRIL were detected by qRT-PCR, but only COL5A2 and WDR3 showed significantly different expression in circANRIL-OE cells.
Qin et al. (2022) Integrated bioinformatics analysis for the identification of hub genes and signaling pathways related to circANRIL. PeerJ 10:e13135 https://doi.org/10.7717/peerj.13135
Effect of steady-state aerobic exercise intensity and duration on the relationship between reserves of heart rate and oxygen uptake
Background The percentages of heart rate (%HRR) or oxygen uptake (%V̇O2R) reserve are used interchangeably for prescribing aerobic exercise intensity due to their assumed 1:1 relationship, although its validity is debated. This study aimed to assess if %HRR and %V̇O2R show a 1:1 relationship during steady-state exercise (SSE) and if exercise intensity and duration affect their relationship. Methods Eight physically active males (age 22.6 ± 1.2 years) were enrolled. Pre-exercise and maximal HR and V̇O2 were assessed on the first day. In the following 4 days, different SSEs were performed (running) combining the following randomly assigned durations and intensities: 15 min, 45 min, 60% HRR, 80% HRR. Post-exercise maximal HR and V̇O2 were assessed after each SSE. Using pre-exercise and post-exercise maximal values, the average HR and V̇O2 of the last 5 min of each SSE were converted into percentages of the reserves (%RES), which were computed in a 3-way RM-ANOVA (α = 0.05) to assess if they were affected by the prescription parameter (HRR or V̇O2R), exercise intensity (60% or 80% HRR), and duration (15 or 45 min). Results The %RES values were not affected by the prescription parameter (p = 0.056) or its interactions with intensity (p = 0.319) or duration and intensity (p = 0.117), while parameter and duration interaction was significant (p = 0.009). %HRRs and %V̇O2Rs did not differ in the 15-min SSEs (mean difference [MD] = 0.7 percentage points, p = 0.717), whereas %HRR was higher than %V̇O2R in the 45-min SSEs (MD = 6.7 percentage points, p = 0.009). Conclusion SSE duration affects the %HRR-%V̇O2R relationship, with %HRRs higher than %V̇O2Rs in SSEs of longer duration.
Ferri Marini et al. (2022) Effect of steady-state aerobic exercise intensity and duration on the relationship between reserves of heart rate and oxygen uptake. PeerJ 10:e13190 https://doi.org/10.7717/peerj.13190
Inflammatory bowel disease biomarkers of human gut microbiota selected via different feature selection methods
The tremendous boost in next generation sequencing and in the “omics” technologies makes it possible to characterize the human gut microbiome—the collective genomes of the microbial community that reside in our gastrointestinal tract. Although some of these microorganisms are considered to be essential regulators of our immune system, the alteration of the complexity and eubiotic state of microbiota might promote autoimmune and inflammatory disorders such as diabetes, rheumatoid arthritis, Inflammatory bowel diseases (IBD), obesity, and carcinogenesis. IBD, comprising Crohn’s disease and ulcerative colitis, is a gut-related, multifactorial disease with an unknown etiology. IBD presents defects in the detection and control of the gut microbiota, associated with unbalanced immune reactions, genetic mutations that confer susceptibility to the disease, and complex environmental conditions such as westernized lifestyle. Although some existing studies attempt to unveil the composition and functional capacity of the gut microbiome in relation to IBD diseases, a comprehensive picture of the gut microbiome in IBD patients is far from being complete. Due to the complexity of metagenomic studies, the applications of the state-of-the-art machine learning techniques became popular to address a wide range of questions in the field of metagenomic data analysis. In this regard, using IBD associated metagenomics dataset, this study utilizes both supervised and unsupervised machine learning algorithms, (i) to generate a classification model that aids IBD diagnosis, (ii) to discover IBD-associated biomarkers, (iii) to discover subgroups of IBD patients using k-means and hierarchical clustering approaches. To deal with the high dimensionality of features, we applied robust feature selection algorithms such as Conditional Mutual Information Maximization (CMIM), Fast Correlation Based Filter (FCBF), min redundancy max relevance (mRMR), Select K Best (SKB), Information Gain (IG) and Extreme Gradient Boosting (XGBoost). In our experiments with 100-fold Monte Carlo cross-validation (MCCV), XGBoost, IG, and SKB methods showed a considerable effect in terms of minimizing the microbiota used for the diagnosis of IBD and thus reducing the cost and time. We observed that compared to Decision Tree, Support Vector Machine, Logitboost, Adaboost, and stacking ensemble classifiers, our Random Forest classifier resulted in better performance measures for the classification of IBD. Our findings revealed potential microbiome-mediated mechanisms of IBD and these findings might be useful for the development of microbiome-based diagnostics.
Bakir-Gungor et al. (2022) Inflammatory bowel disease biomarkers of human gut microbiota selected via different feature selection methods. PeerJ 10:e13205 https://doi.org/10.7717/peerj.13205
A DNA barcode survey of insect biodiversity in Pakistan
Although Pakistan has rich biodiversity, many groups are poorly known, particularly insects. To address this gap, we employed DNA barcoding to survey its insect diversity. Specimens obtained through diverse collecting methods at 1,858 sites across Pakistan from 2010–2019 were examined for sequence variation in the 658 bp barcode region of the cytochrome c oxidase 1 (COI) gene. Sequences from nearly 49,000 specimens were assigned to 6,590 Barcode Index Numbers (BINs), a proxy for species, and most (88%) also possessed a representative image on the Barcode of Life Data System (BOLD). By coupling morphological inspections with barcode matches on BOLD, every BIN was assigned to an order (19) and most (99.8%) were placed to a family (362). However, just 40% of the BINs were assigned to a genus (1,375) and 21% to a species (1,364). Five orders (Coleoptera, Diptera, Hemiptera, Hymenoptera, Lepidoptera) accounted for 92% of the specimens and BINs. More than half of the BINs (59%) are so far only known from Pakistan, but others have also been reported from Bangladesh (13%), India (12%), and China (8%). Representing the first DNA barcode survey of the insect fauna in any South Asian country, this study provides the foundation for a complete inventory of the insect fauna in Pakistan while also contributing to the global DNA barcode reference library.
Ashfaq et al. (2022) A DNA barcode survey of insect biodiversity in Pakistan. PeerJ 10:e13267 https://doi.org/10.7717/peerj.13267
Spatial variability of microzooplankton grazing on phytoplankton in coastal southern Florida, USA
Microzooplankton are considered the primary consumers of phytoplankton in marine environments. Microzooplankton grazing rates on phytoplankton have been studied across the globe, but there are still large regions of the ocean that are understudied, such as sub-tropical coastal oceans. One of these regions is the coastal area around south Florida, USA. We measured microzooplankton grazing rates in two distinct environments around south Florida; the oligotrophic Florida Keys and the mesotrophic outflow from the Everglades. For 2-years from January 2018 to January 2020, we set up 55 dilution and light-dark bottle experiments at five stations to estimate the microzooplankton community grazing rate, instantaneous phytoplankton growth rate, and primary production. Our results suggest that microzooplankton are consuming a higher proportion of the primary production near the Everglades outflow compared to the Florida Keys. We also found that changes in phytoplankton growth rates are disconnected from changes in the microzooplankton grazing rates in the Florida Keys. Overall, the data from the Everglades outflow is what would be expected based on global patterns, but factors other than microzooplankton grazing are more important in controlling phytoplankton biomass in the Florida Keys.
Millette et al. (2022) Spatial variability of microzooplankton grazing on phytoplankton in coastal southern Florida, USA. PeerJ 10:e13291 https://doi.org/10.7717/peerj.13291
Association between laryngopharyngeal reflux and obstructive sleep apnea in adults
Background Obstructive sleep apnea syndrome (OSAS) and laryngopharyngeal reflux (LPR) have been found to coexist in the population. OSAS and LPR also share obesity as an important risk factor. However, the relationship between LPR and OSAS remains unclear. This study aimed to correlate LPR as measured by the Reflux Symptom Index (RSI) and the Reflux Finding Score (RFS) with OSAS. Methods This cross-sectional study included sixty-four subjects who underwent anamnesis to complete the RSI and the Epworth Sleeping Scale (ESS). The subjects were then divided into the OSAS and non-OSAS groups based on the Apnea-Hypopnea Index (AHI) obtained through a polysomnography examination. Both groups underwent a flexible fiberoptic nasopharyngolaryngoscopy examination to determine the RFS. LPR was identified based on the RSI and RFS. Results The mean BMI of the OSAS group significantly was higher than the non-OSAS group (p < 0.05). Most of the subjects in the OSAS group exhibited mild-moderate OSAS (AHI 10–29), and severe OSAS occurred in only seven subjects. The mean RSI and RFS values in the OSAS group did not differ significantly from the non-OSAS group (p = 0.34 and p = 0.36, respectively). The proportion of LPR between the mild-moderate OSAS group, the severe OSAS group, and the non-OSAS group did not differ significantly (p = 1.00). RSI and RFS did not significantly correlate with AHI. Based on RSI, the proportion of LPR between the ESS (+) and ESS (-) groups did not significantly differ (adjusted p = 0.062). The proportion of LPR based on RFS was almost equal between the ESS (+) and ESS (-) groups (p = 0.817). Conclusions The BMI of the OSAS group was significantly higher than the non-OSAS group. There was no significant difference in RSI and RFS between the OSAS and non-OSAS groups. There was no significant correlation between RSI and AHI, or between RFS and AHI. There was no significant difference in the proportion of RSI between the ESS (+) and the ESS (-) groups.
Tamin et al. (2022) Association between laryngopharyngeal reflux and obstructive sleep apnea in adults. PeerJ 10:e13303 https://doi.org/10.7717/peerj.13303
Do patterns of insect mortality in temperate and tropical zones have broader implications for insect ecology and pest management?
Background Understanding how biotic and abiotic factors affect insect mortality is crucial for both fundamental knowledge of population ecology and for successful pest management. However, because these factors are difficult to quantify and interpret, patterns and dynamics of insect mortality remain unclear, especially comparative mortality across climate zones. Life table analysis provides robust information for quantifying population mortality and population parameters. Methods In this study, we estimated cause-of-death probabilities and irreplaceable mortality (the portion of mortality that cannot be replaced by another cause or combination of causes) using a Multiple Decrement Life Table (MDLT) analysis of 268 insect life tables from 107 peer-reviewed journal articles. In particular, we analyzed insect mortality between temperate and tropical climate zones. Results Surprisingly, our results suggest that non-natural enemy factors (abiotic) were the major source of insect mortality in both temperate and tropical zones. In addition, we observed that irreplaceable mortality from predators in tropical zones was 3.7-fold greater than in temperate zones. In contrast, irreplaceable mortality from parasitoids and pathogens was low and not different between temperate and tropical zones. Surprisingly, we did not observe differences in natural enemy and non-natural enemy factors based on whether the insect species was native or non-native. We suggest that characterizing predation should be a high priority in tropical conditions. Furthermore, because mortality from parasitoids was low in both tropical and temperate zones, this mortality needs to be better understood, especially as it relates to biological control and integrated pest management.
Pinto et al. (2022) Do patterns of insect mortality in temperate and tropical zones have broader implications for insect ecology and pest management?. PeerJ 10:e13340 https://doi.org/10.7717/peerj.13340