title: PeerJ description: Articles published in PeerJ link: https://peerj.com/articles/index.rss3?journal=peerj&page=1228 creator: info@peerj.com PeerJ errorsTo: info@peerj.com PeerJ language: en title: The landscape and prognostic value of tumor-infiltrating immune cells in gastric cancer link: https://peerj.com/articles/7993 last-modified: 2019-12-10 description: BackgroundGastric cancer (GC) is the fourth most frequently diagnosed malignancy and the second leading cause of cancer-associated mortality worldwide. The tumor microenvironment, especially tumor-infiltrating immune cells (TIICs), exhibits crucial roles both in promoting and inhibiting cancer growth. The aim of the present study was to evaluate the landscape of TIICs and develop a prognostic nomogram in GC.Materials and MethodsA gene expression profile obtained from a dataset from The Cancer Genome Atlas (TCGA) was used to quantify the proportion of 22 TIICs in GC by the CIBERSORT algorithm. LASSO regression analysis and multivariate Cox regression were applied to select the best survival-related TIICs and develop an immunoscore formula. Based on the immunoscore and clinical information, a prognostic nomogram was built, and the predictive accuracy of it was evaluated by the area under the curve (AUC) of the receiver operating characteristic curve (ROC) and the calibration plot. Furthermore, the nomogram was validated by data from the International Cancer Genome Consortium (ICGC) dataset.ResultsIn the GC samples, macrophages (25.3%), resting memory CD4 T cells (16.2%) and CD8 T cells (9.7%) were the most abundant among 22 TIICs. Seven TIICs were filtered out and used to develop an immunoscore formula. The AUC of the prognostic nomogram in the TCGA set was 0.772, similar to that in the ICGC set (0.730) and whole set (0.748), and significantly superior to that of TNM staging alone (0.591). The calibration plot demonstrated an outstanding consistency between the prediction and actual observation. Survival analysis revealed that patients with GC in the high-immunoscore group exhibited a poor clinical outcome. The result of multivariate analysis revealed that the immunoscore was an independent prognostic factor.DiscussionThe immunoscore could be used to reinforce the clinical outcome prediction ability of the TNM staging system and provide a convenient tool for risk assessment and treatment selection for patients with GC. creator: Linhai Li creator: Yiming Ouyang creator: Wenrong Wang creator: Dezhi Hou creator: Yu Zhu uri: https://doi.org/10.7717/peerj.7993 license: https://creativecommons.org/licenses/by/4.0/ rights: ©2019 Li et al. title: Cellular components in tumor microenvironment of neuroblastoma and the prognostic value link: https://peerj.com/articles/8017 last-modified: 2019-12-10 description: BackgroundTumor 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.MethodsxCell 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.ResultsWe 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.ConclusionThis 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. creator: Xiaodan Zhong creator: Yutong Zhang creator: Linyu Wang creator: Hao Zhang creator: Haiming Liu creator: Yuanning Liu uri: https://doi.org/10.7717/peerj.8017 license: https://creativecommons.org/licenses/by/4.0/ rights: ©2019 Zhong et al. title: motoRneuron: an open-source R toolbox for time-domain motor unit analyses link: https://peerj.com/articles/7907 last-modified: 2019-12-10 description: 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. creator: Andrew J. Tweedell creator: Matthew S. Tenan uri: https://doi.org/10.7717/peerj.7907 license: https://creativecommons.org/publicdomain/zero/1.0/ rights: title: Species recovery and recolonization of past habitats: lessons for science and conservation from sea otters in estuaries link: https://peerj.com/articles/8100 last-modified: 2019-12-10 description: 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. creator: Brent B. Hughes creator: Kerstin Wasson creator: M. Tim Tinker creator: Susan L. Williams creator: Lilian P. Carswell creator: Katharyn E. Boyer creator: Michael W. Beck creator: Ron Eby creator: Robert Scoles creator: Michelle Staedler creator: Sarah Espinosa creator: Margot Hessing-Lewis creator: Erin U. Foster creator: Kathryn M. Beheshti creator: Tracy M. Grimes creator: Benjamin H. Becker creator: Lisa Needles creator: Joseph A. Tomoleoni creator: Jane Rudebusch creator: Ellen Hines creator: Brian R. Silliman uri: https://doi.org/10.7717/peerj.8100 license: https://creativecommons.org/licenses/by/4.0/ rights: © 2019 Hughes et al. title: Exploring profile and potential influencers of vaginal microbiome among asymptomatic pregnant Chinese women link: https://peerj.com/articles/8172 last-modified: 2019-12-10 description: BackgroundThis 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.MethodsA 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.ResultsThe 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).ConclusionThe 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. creator: Yining He creator: Yun Huang creator: Zhengyin Zhang creator: Fengping Yu creator: Yingjie Zheng uri: https://doi.org/10.7717/peerj.8172 license: https://creativecommons.org/licenses/by/4.0/ rights: ©2019 He et al. title: The accumulation of Mn and Cu in the morphological parts of Solidago canadensis under different soil conditions link: https://peerj.com/articles/8175 last-modified: 2019-12-10 description: 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. creator: Aleksandra Bielecka creator: Elżbieta Królak uri: https://doi.org/10.7717/peerj.8175 license: https://creativecommons.org/licenses/by/4.0/ rights: ©2019 Bielecka and Królak title: Retrospective clinical study of renin-angiotensin system blockers in lung cancer patients with hypertension link: https://peerj.com/articles/8188 last-modified: 2019-12-10 description: PurposeRenin-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.MethodsThere 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.ResultsSignificant 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).ConclusionIn 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. creator: Jie Wei creator: Zhiyang Zhou creator: Zhijie Xu creator: Shuangshuang Zeng creator: Xi Chen creator: Xiang Wang creator: Wanli Liu creator: Min Liu creator: Zhicheng Gong creator: Yuanliang Yan uri: https://doi.org/10.7717/peerj.8188 license: https://creativecommons.org/licenses/by/4.0/ rights: ©2019 Wei et al. title: A comparison of random-field-theory and false-discovery-rate inference results in the analysis of registered one-dimensional biomechanical datasets link: https://peerj.com/articles/8189 last-modified: 2019-12-10 description: BackgroundThe 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.MethodsWe 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.ResultsOur 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.DiscussionRFT 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. creator: Hanaa Naouma creator: Todd C. Pataky uri: https://doi.org/10.7717/peerj.8189 license: https://creativecommons.org/licenses/by/4.0/ rights: ©2019 Naouma and Pataky title: Differentiation between maxillary and malar midface position within the facial profile link: https://peerj.com/articles/8200 last-modified: 2019-12-10 description: AimsTo define midfacial position differentiating maxillary and zygomatic regions and to evaluate the corresponding cephalometric characteristics discerning midfacial flatness and fullness.Material and MethodsA 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.ResultsAll 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.ConclusionMidface 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. creator: Chimène Chalala creator: Joseph G. Ghafari uri: https://doi.org/10.7717/peerj.8200 license: https://creativecommons.org/licenses/by/4.0/ rights: © 2019 Chalala and Ghafari title: Concentration-dependent polymorphism of insulin amyloid fibrils link: https://peerj.com/articles/8208 last-modified: 2019-12-10 description: 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. creator: Andrius Sakalauskas creator: Mantas Ziaunys creator: Vytautas Smirnovas uri: https://doi.org/10.7717/peerj.8208 license: https://creativecommons.org/licenses/by/4.0/ rights: ©2019 Sakalauskas et al.