Cellular components in tumor microenvironment of neuroblastoma and the prognostic value
Background Tumor microenvironment (TME) contributes to tumor development, progression, and treatment response. In this study, we detailed the cell composition of the TME in neuroblastoma (NB) and constructed a cell risk score model to predict the prognosis of NB. Methods xCell score was calculated through transcriptomic data from the datasets GSE49711 and GSE45480 based on the xCell algorithm. The random forest method was employed to select important features and the coefficient was obtained via multivariate cox regression analysis to construct a prognostic model, and the performance was validated in another two independent datasets, GSE16476 and TARGET-NBL. Results We found that both immune and non-immune cells varies significantly in different prognostic groups, and were correlated with survival time. The proposed prognostic cell risk score (pCRS) model we constructed can be an independent prognostic indicator for overall survival (OS) and event-free survival (EFS) (training: OS, HR 1.579, EFS, HR 1.563; validation: OS, HR 1.665, 3.848, EFS, HR 2.203, all p-values < 0.01) and only independent prognostic factor in International Neuroblastoma Risk Group high risk patients (HR 1.339, 3.631; p-value 1.76e–2, 3.71e–5), rather than MYCN amplification. Besides, pCRS model showed good performance in grouping, in discriminating MYCN status, the area under the curve (AUC) was 0.889, 0.933, and 0.861 in GSE49711, GSE45480, and GSE16476, respectively. In separating high risk groups, the AUC was 0.904 in GSE49711. Conclusion This study details the cellular components in the TME of NB through gene expression data, the proposed pCRS model might provide a basis for treatment selection of high risk patients or targeting cellular components of TME in NB.
Zhong et al. (2019) Cellular components in tumor microenvironment of neuroblastoma and the prognostic value. PeerJ 7:e8017 https://doi.org/10.7717/peerj.8017
motoRneuron: an open-source R toolbox for time-domain motor unit analyses
Motor unit synchronization is the tendency of motor neurons and their associated muscle fibers to discharge near-simultaneously. It has been theorized as a control mechanism for force generation by common excitatory inputs to these motor neurons. Magnitude of synchronization is calculated from peaks in cross-correlation histograms between motor unit discharge trains. However, there are many different methods for detecting these peaks and even more indices for calculating synchronization from them. Methodology is diverse, typically laboratory-specific and requires expensive software, like Matlab or LabView. This lack of standardization makes it difficult to draw definitive conclusions about motor unit synchronization. A free, open-source toolbox, “motoRneuron”, for the R programming language, has been developed which contains functions for calculating time domain synchronization using different methods found in the literature. The objective of this paper is to detail the toolbox’s functionality and present a case study showing how the same synchronization index can differ when different methods are used to compute it. A pair of motor unit action potential trains were collected from the forearm during a isometric finger flexion task using fine wire electromyography. The motoRneuron package was used to analyze the discharge time of the motor units for time-domain synchronization. The primary function “mu_synch” automatically performed the cross-correlation analysis using three different peak detection methods, the cumulative sum method, the z-score method, and a subjective visual method. As function parameters defined by the user, only first order recurrence intervals were calculated and a 1 ms bin width was used to create the cross correlation histogram. Output from the function were six common synchronization indices, the common input strength (CIS), k′, k′ − 1, E, S, and Synch Index. In general, there was a high degree of synchronization between the two motor units. However, there was a varying degree of synchronization between methods. For example, the widely used CIS index, which represents a rate of synchronized discharges, shows a 45% difference between the visual and z-score methods. This singular example demonstrates how a lack of consensus in motor unit synchronization methodologies may lead to substantially differing results between studies. The motoRneuron toolbox provides researchers with a standard interface and software to examine time-domain motor unit synchronization.
Tweedell et al. (2019) motoRneuron: an open-source R toolbox for time-domain motor unit analyses. PeerJ 7:e7907 https://doi.org/10.7717/peerj.7907
Species recovery and recolonization of past habitats: lessons for science and conservation from sea otters in estuaries
Recovering species are often limited to much smaller areas than they historically occupied. Conservation planning for the recovering species is often based on this limited range, which may simply be an artifact of where the surviving population persisted. Southern sea otters (Enhydra lutris nereis) were hunted nearly to extinction but recovered from a small remnant population on a remote stretch of the California outer coast, where most of their recovery has occurred. However, studies of recently-recolonized estuaries have revealed that estuaries can provide southern sea otters with high quality habitats featuring shallow waters, high production and ample food, limited predators, and protected haul-out opportunities. Moreover, sea otters can have strong effects on estuarine ecosystems, fostering seagrass resilience through their consumption of invertebrate prey. Using a combination of literature reviews, population modeling, and prey surveys we explored the former estuarine habitats outside the current southern sea otter range to determine if these estuarine habitats can support healthy sea otter populations. We found the majority of studies and conservation efforts have focused on populations in exposed, rocky coastal habitats. Yet historical evidence indicates that sea otters were also formerly ubiquitous in estuaries. Our habitat-specific population growth model for California’s largest estuary—San Francisco Bay—determined that it alone can support about 6,600 sea otters, more than double the 2018 California population. Prey surveys in estuaries currently with (Elkhorn Slough and Morro Bay) and without (San Francisco Bay and Drakes Estero) sea otters indicated that the availability of prey, especially crabs, is sufficient to support healthy sea otter populations. Combining historical evidence with our results, we show that conservation practitioners could consider former estuarine habitats as targets for sea otter and ecosystem restoration. This study reveals the importance of understanding how recovering species interact with all the ecosystems they historically occupied, both for improved conservation of the recovering species and for successful restoration of ecosystem functions and processes.
Hughes et al. (2019) Species recovery and recolonization of past habitats: lessons for science and conservation from sea otters in estuaries. PeerJ 7:e8100 https://doi.org/10.7717/peerj.8100
Exploring profile and potential influencers of vaginal microbiome among asymptomatic pregnant Chinese women
Background This study was designed to explore the profile and potential influencers of the vaginal microbiome (VMB) among asymptomatic pregnant Chinese women and its possible association with pregnancy outcomes. Methods A prospective study was conducted among pregnant Chinese women receiving regular prenatal care at a hospital in Shanghai, China from March 2017 to March 2018. Vaginal swabs were obtained from 113 asymptomatic pregnant women in mid-pregnancy and sequenced by the V3–V4 region of 16S rRNA on an Ion S5™ XL platform. Demographic characteristics and major pregnancy outcomes were collected through questionnaires and electronic medical records. Results The predominant vaginal community state types (CSTs) were CST I (45.1%) and CST III (31.9%). Participants were divided into a lactobacilli-dominant group (LD, CST I/II/III/I–III/V, n = 100, 88.5%) and a less lactobacilli-dominant group (LLD, CST IV-A/B, n = 13, 11.5%). Women in the LLD group showed an increased alpha diversity [median (interquartile range, IQR): 2.41 (1.67, 2.49) vs. 0.30 (0.17, 0.59), P < 0.001], which was related to a lower pre-pregnancy body mass index (BMI) (P = 0.012), and a greater instance of passive smoking (P = 0.033). The relative abundance of Lactobacillus was correlated positively with the pre-pregnancy BMI (r = 0.177, P = 0.041), but negatively with passive smoking (r = − 0.204, P = 0.030). Conclusion The vaginal flora of asymptomatic pregnant Chinese women was mostly dominated by Lactobacillus crispatus and L. iners. A lower BMI and greater instance of passive smoking may contribute to a less lactobacilli-dominant VMB. However, a larger sample size is needed.
He et al. (2019) Exploring profile and potential influencers of vaginal microbiome among asymptomatic pregnant Chinese women. PeerJ 7:e8172 https://doi.org/10.7717/peerj.8172
The accumulation of Mn and Cu in the morphological parts of Solidago canadensis under different soil conditions
Solidago canadensis L. is a drought-tolerant, invasive plant, characterized by a large biomass of underground and aboveground parts. The aim of this study was to assess the accumulation of manganese (Mn) and copper (Cu) in the roots and rhizomes and the stems, leaves, and inflorescence parts in S. canadensis from two locations that differed in soil pH, organic carbon, and Mn and Cu concentrations. The concentration of the metals in the samples was determined by the AAS method; the pH was determined by the potentiometric method; and the content of organic carbon was determined using Tiurin’s method. The concentration of Mn and Cu in the roots of S. candensis correlated with the concentrations of the metals in the soil without regard to the soil condition or its organic carbon content. With a low soil pH and organic carbon content, Mn accumulation per 1 ramet in the aboveground parts of S. canadensis consisted over 50% of the total Mn content in the plant. In neutral or alkaline soils, the amount of Mn per 1 ramet accumulated in underground parts was over 60%. Regardless of the soil conditions, about 35% of Mn accumulated in rhizomes. Approximately 60% of copper accumulated in the underground parts of S. candensis (45% in rhizomes) without regard to the soil reaction or organic carbon content. The ability of the plant to accumulate large amounts of metals disposes Solidago canadensis as a candidate for the phytoremediation of soils contaminated with heavy metals.
Environmental Contamination and Remediation
Bielecka et al. (2019) The accumulation of Mn and Cu in the morphological parts of Solidago canadensis under different soil conditions. PeerJ 7:e8175 https://doi.org/10.7717/peerj.8175
Retrospective clinical study of renin-angiotensin system blockers in lung cancer patients with hypertension
Purpose Renin-angiotensin system blockers (RASBs), which include angiotensin-converting enzyme inhibitors (ACEIs) and angiotensin-2 receptor 1 blockers (ARBs), have been reported to be associated with lung cancer metastasis, radiotherapy and chemotherapy. Until now, very limited clinical data for RASBs’ diagnostic and prognostic effects has existed for lung cancer chemotherapy in Chinese patients. Methods There were a total of 678 lung cancer patients with hypertension, of which 461 (68%) were in the non-RASBs group and 217 (32%) were in the RASBs group. Patients’ gender, age, smoking status, histologic differentiation, tumor size, pathological grade, lymph node metastasis, pathological stage and progression-free survival (PFS) were retrospectively analyzed between these two groups. The clinical effects of ACEIs and ARBs in lung cancer patients were compared via t tests, and χ2 test, and potential prognostic factors for progression-free survival (PFS) were evaluated by Kaplan–Meier analysis. Results Significant differences were observed in lymph node metastasis between the RASBs and non-RASBs groups. The RASBs group (62.8% vs 71.7%, p = 0.037) and ARBs group (60.0% vs 71.7%, p = 0.030) had lower lymph node metastasis, and patients with RASBs had a lower pathological stage than those in non-RASBs groups (67.1% vs 77.4%, p = 0.044 ). The PFS of the RASBs (10.7 vs. 6.7 months, p = 0.040) and ACEIs (12.9 vs 6.7 months, p = 0.021) groups were longer than that of the non-RASBs group, while no statistical difference was shown between the ACEIs and ARBs groups. Moreover, the significant results of PFS were further confirmed in pathological stage III–IV patients. In the non-RASB group, 55% of patients took calcium channel blockers (CCBs), and the ACEIs group have a significantly longer PFS compared to the non-CCBs group (6.4 vs 12.9 months, p = 0.036). Conclusion In this study, we showed that the use of RASBs is a positive factor for pathological stage and prognosis of lung cancer patients. Therefore, it is necessary to actively evaluate medical history, especially the use of anti-hypertension medication, in patients with lung cancer and reflect medical history in the treatment and management plans of these patients.
Wei et al. (2019) Retrospective clinical study of renin-angiotensin system blockers in lung cancer patients with hypertension. PeerJ 7:e8188 https://doi.org/10.7717/peerj.8188
A comparison of random-field-theory and false-discovery-rate inference results in the analysis of registered one-dimensional biomechanical datasets
Background The inflation of falsely rejected hypotheses associated with multiple hypothesis testing is seen as a threat to the knowledge base in the scientific literature. One of the most recently developed statistical constructs to deal with this problem is the false discovery rate (FDR), which aims to control the proportion of the falsely rejected null hypotheses among those that are rejected. FDR has been applied to a variety of problems, especially for the analysis of 3-D brain images in the field of Neuroimaging, where the predominant form of statistical inference involves the more conventional control of false positives, through Gaussian random field theory (RFT). In this study we considered FDR and RFT as alternative methods for handling multiple testing in the analysis of 1-D continuum data. The field of biomechanics has recently adopted RFT, but to our knowledge FDR has not previously been used to analyze 1-D biomechanical data, nor has there been a consideration of how FDR vs. RFT can affect biomechanical interpretations. Methods We reanalyzed a variety of publicly available experimental datasets to understand the characteristics which contribute to the convergence and divergence of RFT and FDR results. We also ran a variety of numerical simulations involving smooth, random Gaussian 1-D data, with and without true signal, to provide complementary explanations for the experimental results. Results Our results suggest that RFT and FDR thresholds (the critical test statistic value used to judge statistical significance) were qualitatively identical for many experimental datasets, but were highly dissimilar for others, involving non-trivial changes in data interpretation. Simulation results clarified that RFT and FDR thresholds converge as the true signal weakens and diverge when the signal is broad in terms of the proportion of the continuum size it occupies. Results also showed that, while sample size affected the relation between RFT and FDR results for small sample sizes (<15), this relation was stable for larger sample sizes, wherein only the nature of the true signal was important. Discussion RFT and FDR thresholds are both computationally efficient because both are parametric, but only FDR has the ability to adapt to the signal features of particular datasets, wherein the threshold lowers with signal strength for a gain in sensitivity. Additional advantages and limitations of these two techniques as discussed further. This article is accompanied by freely available software for implementing FDR analyses involving 1-D data and scripts to replicate our results.
Naouma et al. (2019) A comparison of random-field-theory and false-discovery-rate inference results in the analysis of registered one-dimensional biomechanical datasets. PeerJ 7:e8189 https://doi.org/10.7717/peerj.8189
Differentiation between maxillary and malar midface position within the facial profile
Aims To define midfacial position differentiating maxillary and zygomatic regions and to evaluate the corresponding cephalometric characteristics discerning midfacial flatness and fullness. Material and Methods A total of 183 pretreatment lateral cephalometric radiographs of non-growing orthodontic patients (age 25.98 ± 8.43 years) screened at our university orthodontic clinic. The lateral cephalographs of the orthodontic patients were stratified in four groups: flat, normal toward flat, normal toward full, full,according to distances from nasion and sella to points J and G (NJ, SJ, NG and SG). J is the midpoint of the distance connecting orbitale to point A, and G the center of the triangle connecting orbit, key ridge and pterygomaxillary fissure. Statistics included the Kendall tau-b test for best associations among measurements. Results All measurements were statistically significantly different between flat and full groups. The highest associations were between NJ and SJ (τb = 0.71; p < 0.001) and NG and SG (τb = 0.70; p < 0.001). Flat midfaces were characterized by canting of the cranial base and palatal plane, hyperdivergent pattern and maxillary retrognathism. The opposite was true for fuller midfaces. Conclusion Midface skeletal location was assessed differentially in the naso-maxillary and malo-zygomatic structures differentially. Craniofacial characteristics were identified according to this stratification, indicating the potential for application in facial diagnosis and need for testing on 3D cone-beam computed tomography images.
Chalala et al. (2019) Differentiation between maxillary and malar midface position within the facial profile. PeerJ 7:e8200 https://doi.org/10.7717/peerj.8200
Concentration-dependent polymorphism of insulin amyloid fibrils
Protein aggregation into highly structured fibrils has long been associated with several neurodegenerative disorders, such as Alzheimer’s or Parkinson’s disease. Polymorphism of amyloid fibrils increases the complexity of disease mechanisms and may be one of the reasons for the slow progress in drug research. Here we report protein concentration as another factor leading to polymorphism of insulin amyloid fibrils. Moreover, our data suggests that insulin amyloid conformation can self-replicate only via elongation, while seed-induced nucleation will lead to environment-defined conformation of fibrils. As similar observations were already described for a couple of other amyloid proteins, we suggest it to be a generic mechanism for self-replication of different amyloid fibril conformations.
Sakalauskas et al. (2019) Concentration-dependent polymorphism of insulin amyloid fibrils. PeerJ 7:e8208 https://doi.org/10.7717/peerj.8208
Icaritin, an inhibitor of beta-site amyloid cleaving enzyme-1, inhibits secretion of amyloid precursor protein in APP-PS1-HEK293 cells by impeding the amyloidogenic pathway
Background Icaritin (ICT) is a prenylflavonoid derivative from Epimedium brevicornum Maxim. ICT has been shown to have neuroprotective effects. We investigate how ICT affects secretion of amyloid precursor protein (APP). Methods We exposed APP-PS1-HEK293 cells to ICT to investigate its effect on beta-site amyloid cleaving enzyme (BACE)1. Cell viability was evaluated by MTT and lactate dehydrogenase (LDH) assays. The half-maximal inhibitory concentration (IC50) of ICT for BACE1 was measured using fluorescence resonance energy transfer. Effects of ICT on the mRNA expression of APP were assessed by quantitative polymerase chain reaction, and protein expression was measured by western blotting and immunofluorescence. Results Icaritin inhibited BACE1 activity and IC50 was 5.70 ± 1.09 μM. Compared with the control group, at ICT concentrations of 5 μM and 10 μM, the viability increased and LDH leakage decreased in APP-PS1-293 cells. Also, mRNA expression of A disintegrin and metalloproteinase domain-containing protein 10 (ADAM10) increased, while that of BACE1 and presenilin-1 (PS1) decreased, upon ICT treatment. Western blotting and immunofluorescence confirmed that protein expression of ADAM10, BACE1 and PS1 showed the same trend. Expression of the APP fragments sAPPβ and C-terminal fragment β decreased, while that of sAPPα increased, upon ICT treatment. Expression of amyloid β peptides in APP-PS1-HEK293 cells was lower in ICT-treated groups compared with that in the control group. Conclusions Icaritin, as a BACE1 inhibitor, inhibits APP secretion in APP-PS1-HEK293 cells by impeding the amyloidogenic pathway.
Feng et al. (2019) Icaritin, an inhibitor of beta-site amyloid cleaving enzyme-1, inhibits secretion of amyloid precursor protein in APP-PS1-HEK293 cells by impeding the amyloidogenic pathway. PeerJ 7:e8219 https://doi.org/10.7717/peerj.8219