Age-related differences in flexibility in soccer players 8–19 years old
Background Muscle flexibility is a main component of health-related fitness and one of the basic components of fitness for the performance in some sports. Sport and health professionals require the flexibility profile of soccer to define quantitative aims in the training of flexibility. The aim of this study was to identify age-related differences in lower extremity flexibility in youth soccer players. Methods Seventy-two young male soccer players (age: 13.0 ± 3.1 y; body mass: 50.5 ± 15.3 kg; stature 158.2 ± 16.8 cm; BMI: 19.6 ± 2.6 kg/m2) completed this study. Measures of eleven passive hip (hip extension (HE), hip adduction with hip flexed 90°(HAD-HF90°), hip flexion with knee flexed (HF-KF) and extended (HF-KE), hip abduction with hip neutral (HAB) and hip flexed 90°(HAB-HF90°), hip external (HER) and internal (HIR) rotation), knee (knee flexion (KF)) and ankle dorsiflexion (ankle dorsiflexion with knee flexed (ADF-KF) and extended (ADF-KE)) ranges of motion (ROM) were taken. Descriptive statistics were calculated for hip, knee and ankle ROM measured separately by leg (dominant and non-dominant) and age-group (U10, U12, U14, U16 and U19). The data was analysed using a one-way analysis of variance (ANOVA) to examine the interaction of 11 ROM in the different players’ age-group. Results Generally, U10 and/or U12 soccer players obtain the highest mean value in almost all ROM evaluated (U10: HAD-HF [39.6° ± 4.3°], ADF-KE [32.3° ± 4.1°], HER [63.5° ± 5.6°] and HAB-HF90°[64.1° ± 7.5°]; U12: HE [17.7° ± 6.2°], HAB [35.6° ± 3.0], HIR [60.8° ± 4.7°] and KF [133.8° ± 7.1°]). Nonetheless, significant differences between the players’ age-groups are just found in HAD-HF90°(p = .042; ES = .136), HAB (p = .001; ES = .252), HIR (p = .001; ES = .251), HER (p < .001; ES = .321) and HAB-HF90°(p < .001; ES = .376) ROM, showing a progressive and irregular decrease in these ROM until the U19 team. Conclusion The findings of this study reinforce the necessity of prescribing exercises aimed at improving HAD-HF90° ROM in U16, HAB ROM in U14, HIR ROM in U16 and U19, HER ROM in U12 and U19, and HAB-HF90° ROM in U16 and U19 players within everyday soccer training routines.
Cejudo et al. (2019) Age-related differences in flexibility in soccer players 8–19 years old. PeerJ 7:e6236 https://doi.org/10.7717/peerj.6236
Improving the efficiency of the Fukui trap as a capture tool for the invasive European green crab (Carcinus maenas) in Newfoundland, Canada
The European green crab (Carcinus maenas) is a crustacean species native to European and North African coastlines that has become one of the world’s most successful marine invasive species. Targeted fishing programs aimed at removing green crabs from invaded ecosystems commonly use Fukui multi-species marine traps. Improving the efficiency of these traps would improve the ability to respond to green crab invasions. In this study, we developed four distinct trap modifications that were designed to facilitate the successful capture of green crabs, with the goal of improving the performance of the Fukui trap. We tested these modifications in situ during the summer of 2016 at two locations in Placentia Bay, Newfoundland. We discovered that three of our modified Fukui trap designs caught significantly more green crabs than the standard Fukui trap, increasing catch-per-unit-effort (CPUE) by as much as 81%. We conclude that our top-performing modifications have great potential for widespread use with existing Fukui traps that are being used for green crab removal efforts.
Bergshoeff et al. (2019) Improving the efficiency of the Fukui trap as a capture tool for the invasive European green crab (Carcinus maenas) in Newfoundland, Canada. PeerJ 7:e6308 https://doi.org/10.7717/peerj.6308
EGFR deficiency leads to impaired self-renewal and pluripotency of mouse embryonic stem cells
Background Self-renewal and pluripotency are considered as unwavering features of embryonic stem cells (ESCs). How ESCs regulate the self-renewal and differentiation is a central question in development and regenerative medicine research. Epidermal growth factor receptor (EGFR) was identified as a critical regulator in embryonic development, but its role in the maintenance of ESCs is poorly understood. Methods Here, EGFR was disrupted by its specific inhibitor AG1478 in mouse ESCs (mESCs), and its self-renewal and pluripotency were characterized according to their proliferation, expression of pluripotency markers, embryoid body (EB) formation, and mRNA expression patterns. We also used another EGFR inhibitor (gefitinib) and RNA interference assay to rule out the possibility of non-specific effects of AG1478. Results EGFR inhibition by AG1478 treatment in mESCs markedly reduced cell proliferation, caused cell cycle arrest at G0/G1 phase, and altered protein expressions of the cell cycle regulatory genes (CDK2 (decreased 11.3%) and proliferating cell nuclear antigen (decreased 25.2%)). The immunoreactivities and protein expression of pluripotency factors (OCT4 (decreased 26.9%)) also dramatically decreased, while the differentiation related genes (GATA4 (increased 1.6-fold)) were up-regulated in mESCs after EGFR inhibition. Meanwhile, EGFR inhibition in mESCs disrupted EB formation, indicating its impaired pluripotency. Additionally, the effects observed by EGFR inhibition with another inhibitor gefitinib and siRNA were consistent with those observed by AG1478 treatment in mESCs. These effects were manifested in the decreased expression of proliferative and pluripotency-related genes and the increased expression of genes involved in differentiation. Moreover, RNA-seq analysis displayed that transcript profiling was changed significantly after EGFR inhibition by AG1478. A large number of differentially expressed genes were involved in cell cycle, apoptotic process, epigenetic modification, and metabolic process, which were related to self-renewal and pluripotency, confirming that EGFR deficiency impaired self-renewal and pluripotency in mESCs. Conclusions Taken together, our results demonstrated the importance of EGFR in guarding the stemness of mESCs.
Yu et al. (2019) EGFR deficiency leads to impaired self-renewal and pluripotency of mouse embryonic stem cells. PeerJ 7:e6314 https://doi.org/10.7717/peerj.6314
Design, optimization and validation of genes commonly used in expression studies on DMH/AOM rat colon carcinogenesis model
Colorectal cancer (CRC), also known as colon cancer, is the third most common form of cancer worldwide in men and the second in women and is characterized by several genetic alterations, among them the expression of several genes. 1,2-dimethylhydrazine (DMH) and its metabolite azoxymethane (AOM) are procarcinogens commonly used to induce colon cancer in rats (DMH/AOM rat model). This rat model has been used to study changes in mRNA expression in genes involved in this pathological condition. However, a lack of proper detailed PCR primer design in the literature limits the reproducibility of the published data. The present study aims to design, optimize and validate the qPCR, in accordance with the MIQE (Minimum Information for Publication of Quantitative Real-Time PCR Experiments) guidelines, for seventeen genes commonly used in the DMH/AOM rat model of CRC (Apc, Aurka, Bax, Bcl2, β-catenin, Ccnd1, Cdkn1a, Cox2, Gsk3beta, IL-33, iNOs, Nrf2, p53, RelA, Smad4, Tnfα and Vegfa) and two reference genes (Actb or β-actin and B2m). The specificity of all primer pairs was empirically validated on agarose gel, and furthermore, the melting curve inspection was checked as was their efficiency (%) ranging from 90 to 110 with a correlation coefficient of r2 > 0.980. Finally, a pilot study was performed to compare the robustness of two candidate reference genes.
Bars-Cortina et al. (2019) Design, optimization and validation of genes commonly used in expression studies on DMH/AOM rat colon carcinogenesis model. PeerJ 7:e6372 https://doi.org/10.7717/peerj.6372
Designing online species identification tools for biological recording: the impact on data quality and citizen science learning
In recent years, the number and scale of environmental citizen science programmes that involve lay people in scientific research have increased rapidly. Many of these initiatives are concerned with the recording and identification of species, processes which are increasingly mediated through digital interfaces. Here, we address the growing need to understand the particular role of digital identification tools, both in generating scientific data and in supporting learning by lay people engaged in citizen science activities pertaining to biological recording communities. Starting from two well-known identification tools, namely identification keys and field guides, this study focuses on the decision-making and quality of learning processes underlying species identification tasks, by comparing three digital interfaces designed to identify bumblebee species. The three interfaces varied with respect to whether species were directly compared or filtered by matching on visual features; and whether the order of filters was directed by the interface or a user-driven open choice. A concurrent mixed-methods approach was adopted to compare how these different interfaces affected the ability of participants to make correct and quick species identifications, and to better understand how participants learned through using these interfaces. We found that the accuracy of identification and quality of learning were dependent upon the interface type, the difficulty of the specimen on the image being identified and the interaction between interface type and ‘image difficulty’. Specifically, interfaces based on filtering outperformed those based on direct visual comparison across all metrics, and an open choice of filters led to higher accuracy than the interface that directed the filtering. Our results have direct implications for the design of online identification technologies for biological recording, irrespective of whether the goal is to collect higher quality citizen science data, or to support user learning and engagement in these communities of practice.
Sharma et al. (2019) Designing online species identification tools for biological recording: the impact on data quality and citizen science learning. PeerJ 6:e5965 https://doi.org/10.7717/peerj.5965
Breast cancer detection using deep convolutional neural networks and support vector machines
It is important to detect breast cancer as early as possible. In this manuscript, a new methodology for classifying breast cancer using deep learning and some segmentation techniques are introduced. A new computer aided detection (CAD) system is proposed for classifying benign and malignant mass tumors in breast mammography images. In this CAD system, two segmentation approaches are used. The first approach involves determining the region of interest (ROI) manually, while the second approach uses the technique of threshold and region based. The deep convolutional neural network (DCNN) is used for feature extraction. A well-known DCNN architecture named AlexNet is used and is fine-tuned to classify two classes instead of 1,000 classes. The last fully connected (fc) layer is connected to the support vector machine (SVM) classifier to obtain better accuracy. The results are obtained using the following publicly available datasets (1) the digital database for screening mammography (DDSM); and (2) the Curated Breast Imaging Subset of DDSM (CBIS-DDSM). Training on a large number of data gives high accuracy rate. Nevertheless, the biomedical datasets contain a relatively small number of samples due to limited patient volume. Accordingly, data augmentation is a method for increasing the size of the input data by generating new data from the original input data. There are many forms for the data augmentation; the one used here is the rotation. The accuracy of the new-trained DCNN architecture is 71.01% when cropping the ROI manually from the mammogram. The highest area under the curve (AUC) achieved was 0.88 (88%) for the samples obtained from both segmentation techniques. Moreover, when using the samples obtained from the CBIS-DDSM, the accuracy of the DCNN is increased to 73.6%. Consequently, the SVM accuracy becomes 87.2% with an AUC equaling to 0.94 (94%). This is the highest AUC value compared to previous work using the same conditions.
Ragab et al. (2019) Breast cancer detection using deep convolutional neural networks and support vector machines. PeerJ 7:e6201 https://doi.org/10.7717/peerj.6201
A new segmentation algorithm for measuring CBCT images of nasal airway: a pilot study
Background Three-dimensional (3D) modeling of the nasal airway space is becoming increasingly important for assessment in breathing disorders. Processing cone beam computed tomography (CBCT) scans of this region is complicated, however, by the intricate anatomy of the sinuses compared to the simpler nasopharynx. A gold standard for these measures also is lacking. Previous work has shown that software programs can vary in accuracy and reproducibility outcomes of these measurements. This study reports the reproducibility and accuracy of an algorithm, airway segmentor (AS), designed for nasal airway space analysis using a 3D printed anthropomorphic nasal airway model. Methods To test reproducibility, two examiners independently used AS to edit and segment 10 nasal airway CBCT scans. The intra- and inter-examiner reproducibility of the nasal airway volume was evaluated using paired t-tests and intraclass correlation coefficients. For accuracy testing, the CBCT data for pairs of nasal cavities were 3D printed to form hollow shell models. The water-equivalent method was used to calculate the inner volume as the gold standard, and the models were then embedded into a dry human skull as a phantom and subjected to CBCT. AS, along with the software programs MIMICS 19.0 and INVIVO 5, was applied to calculate the inner volume of the models from the CBCT scan of the phantom. The accuracy was reported as a percentage of the gold standard. Results The intra-examiner reproducibility was high, and the inter-examiner reproducibility was clinically acceptable. AS and MIMICS presented accurate volume calculations, while INVIVO 5 significantly overestimated the mockup of the nasal airway volume. Conclusion With the aid of a 3D printing technique, the new algorithm AS was found to be a clinically reliable and accurate tool for the segmentation and reconstruction of the nasal airway space.
Zhang et al. (2019) A new segmentation algorithm for measuring CBCT images of nasal airway: a pilot study. PeerJ 7:e6246 https://doi.org/10.7717/peerj.6246
Genome-wide identification of long non-coding RNAs in tomato plants irradiated by neutrons followed by infection with Tomato yellow leaf curl virus
Long non-coding RNAs (lncRNAs) play an important role in regulating many biological processes. In this study, tomato seeds were first irradiated by neutrons. Eight tomato mutants were then selected and infected by Tomato yellow leaf curl virus (TYLCV). RNA sequencing followed by bioinformatics analyses identified 1,563 tomato lncRNAs. About half of the lncRNAs were derived from intergenic regions, whereas antisense lncRNAs accounted for 35%. There were fewer lncRNAs identified in our study than in other studies identifying tomato lncRNAs. Functional classification of 794 lncRNAs associated with tomato genes showed that many lncRNAs were associated with binding functions required for interactions with other molecules and localized in the cytosol and membrane. In addition, we identified 19 up-regulated and 11 down-regulated tomato lncRNAs by comparing TYLCV infected plants to non-infected plants using previously published data. Based on these results, the lncRNAs identified in this study provide important resources for characterization of tomato lncRNAs in response to TYLCV infection.
Zhou et al. (2019) Genome-wide identification of long non-coding RNAs in tomato plants irradiated by neutrons followed by infection with Tomato yellow leaf curl virus. PeerJ 7:e6286 https://doi.org/10.7717/peerj.6286
Gastric Helicobacter pylori infection perturbs human oral microbiota
Background We investigated the effects of gastric Helicobacter pylori infection on the daytime and overnight human oral microbiota. Methods Twenty four volunteers were recruited. Ten tested positive for H. pylori infection by the Carbon-14 Urea Breath Test, and the rest were negative. Two oral swabs were collected: one immediately after waking up in the morning and before brushing teeth, and another in the evening before teeth-brushing. DNA extract acquired from each swab was subjected to Illumina sequencing of 16S rRNA gene amplicons. The microbial abundance and composition were analysed in relation to H. pylori infection status. Results Helicobacter pylori-positive individuals had significant changes in the alpha and beta diversities in the daytime samples in comparison to those who were H. pylori negative. To identify which taxa could be significantly affected within the cohorts in the daytime, we employed the LEfSe method. When compared against UBT-negative samples, significantly higher abundances were detected in both Pseudomonas and Roseomonas, while Fusobacterium, Solobacterium, Haemophilus and Streptococcus were significantly decreased in the UBT-positive samples. Discussion Our data demonstrated that H. pylori infection affects the human daytime oral microbiota. The hitherto undocumented changes of several bacterial genera due to H. pylori infection require more studies to examine their potential health effects on affected individuals.
Chua et al. (2019) Gastric Helicobacter pylori infection perturbs human oral microbiota. PeerJ 7:e6336 https://doi.org/10.7717/peerj.6336
Optimizing influenza vaccine policies for controlling 2009-like pandemics and regular outbreaks
Background This study examined the effectiveness of various vaccine policies against influenza. The transmission rate was calculated by use of the time-series influenza-like illness case during the year of 2009 and recent epidemics in Taiwan. Methods We developed a stochastic compartmental model to analyze the transmission of influenza, where the population was stratified by location and age group, and the vaccine distribution was considered using the current policy. The simulation study compared the previous vaccine policy and a new policy with expanded coverage and various lengths of the vaccination campaign. The sensitivity analysis investigated different levels of vaccine efficacy to confirm the robustness of the recommended policies. Results Doubling vaccine coverage can decrease the number of infections effectively in the regular epidemic scenario. However, a peak of infections occurs if the duration of implementing vaccination is too long. In the 2009-like pandemic scenario, both increasing vaccine doses and reducing the program’s duration can mitigate infections, although the early outbreak restricts the effectiveness of vaccination programs. Conclusions The finding indicates that only increasing vaccine coverage can reduce influenza infections. To avoid the peak of infections, it is also necessary to execute the vaccination activity immediately. Vaccine efficacy significantly impacts the vaccination policy’s performance. When vaccine efficacy is low, neither increasing vaccination doses nor reducing vaccination timeframe prevents infections. Therefore, the variation in vaccine efficacy should be taken into account when making immunization policies against influenza.
Chen et al. (2019) Optimizing influenza vaccine policies for controlling 2009-like pandemics and regular outbreaks. PeerJ 7:e6340 https://doi.org/10.7717/peerj.6340