title: PeerJ description: Articles published in PeerJ link: https://peerj.com/articles/index.rss3?journal=peerj&page=1066 creator: info@peerj.com PeerJ errorsTo: info@peerj.com PeerJ language: en title: Consistent administration of cetuximab is associated with favorable outcomes in recurrent/metastatic head and neck squamous cell carcinoma in an endemic carcinogen exposure area: a retrospective observational study link: https://peerj.com/articles/9862 last-modified: 2020-09-10 description: BackgroundThis study aimed to analyze the clinical outcomes associated with patients with recurrent/metastatic head and neck squamous cell carcinoma (RM HNSCC) who received cetuximab-based chemotherapy in a real-world clinical setting.MethodsClinical data were extracted from RM HNSCC patients diagnosed between 2016 and 2019. Kaplan–Meier survival estimates and Cox proportional hazards model were used for survival analyses.ResultsOf 106 RM HNSCC patients (mean age = 55.1 years), 38.7% exhibited recurrent disease and 61.3% had metastatic disease. The majority of patients showed a habit of addictive substance use, including alcohol (67.0%), betel nuts (71.7%), or tobacco (74.5%). The primary tumor sites included the oral cavity (64.1%), hypopharynx (19.8%), and oropharynx (16.0%). The median number of cetuximab cycles for the 106 patients was 11 (2–24). The disease control rate (DCR) was 48.1%, and the overall response rate (ORR) was 28.3%. The median progression-free survival (PFS) and overall survival (OS) were 5.0 and 9.23 months, respectively. Patients treated with more than 11 cycles of cetuximab exhibited a longer median PFS and median OS than did patients treated with less than 11 cycles (median PFS: 7.0 vs. 3.0 months, p < 0.001; OS: 12.43 vs. 4.46 months, p = 0.001). Patients without previous concurrent chemoradiotherapy (CRT) had a better median PFS than did those with previous CRT (6.0 vs. 4.0 months, p = 0.046). Multivariable analysis revealed that perineural invasion and fewer cycles of cetuximab (<11 cycles) were independent risk factors associated with disease progression. In addition, the reduction in treatment cycles of cetuximab and advanced lymph node metastasis were independent prognostic factors predicting poorer overall survival.ConclusionOur study provides important real-world data regarding cetuximab-containing treatment in RM HNSCC. Consistent administration of cetuximab could be associated with more favorable outcomes in RM HNSCC in endemic carcinogen exposure areas. creator: Hui-Ching Wang creator: Pei-Lin Liu creator: Pei-Chuan Lo creator: Yi-Tzu Chang creator: Leong-Perng Chan creator: Tsung-Jang Yeh creator: Hui-Hua Hsiao creator: Shih-Feng Cho uri: https://doi.org/10.7717/peerj.9862 license: https://creativecommons.org/licenses/by/4.0/ rights: ©2020 Wang et al. title: A survey of RNA secondary structural propensity encoded within human herpesvirus genomes: global comparisons and local motifs link: https://peerj.com/articles/9882 last-modified: 2020-09-10 description: There are nine herpesviruses known to infect humans, of which Epstein–Barr virus (EBV) is the most widely distributed (>90% of adults infected). This ubiquitous virus is implicated in a variety of cancers and autoimmune diseases. Previous analyses of the EBV genome revealed numerous regions with evidence of generating unusually stable and conserved RNA secondary structures and led to the discovery of a novel class of EBV non-coding (nc)RNAs: the stable intronic sequence (sis)RNAs. To gain a better understanding of the roles of RNA structure in EBV biology and pathogenicity, we revisit EBV using recently developed tools for genome-wide motif discovery and RNA structural characterization. This corroborated previous results and revealed novel motifs with potential functionality; one of which has been experimentally validated. Additionally, since many herpesviruses increasingly rival the seroprevalence of EBV (VZV, HHV-6 and HHV-7 being the most notable), analyses were expanded to include all sequenced human Herpesvirus RefSeq genomes, allowing for genomic comparisons. In total 10 genomes were analyzed, for EBV (types 1 and 2), HCMV, HHV-6A, HHV-6B, HHV-7, HSV-1, HSV-2, KSHV, and VZV. All resulting data were archived in the RNAStructuromeDB (https://structurome.bb.iastate.edu/herpesvirus) to make them available to a wide array of researchers. creator: Ryan J. Andrews creator: Collin A. O’Leary creator: Walter N. Moss uri: https://doi.org/10.7717/peerj.9882 license: https://creativecommons.org/licenses/by/4.0/ rights: ©2020 Andrews et al. title: Evaluation of different culture media to support in vitro growth and biofilm formation of bacterial vaginosis-associated anaerobes link: https://peerj.com/articles/9917 last-modified: 2020-09-10 description: BackgroundBacterial vaginosis (BV) is one of the most common vaginal infections worldwide. It is associated with the presence of a dense polymicrobial biofilm on the vaginal epithelium, formed mainly by Gardnerella species. The biofilm also contains other anaerobic species, but little is known about their role in BV development.AimTo evaluate the influence of different culture media on the planktonic and biofilm growth of six cultivable anaerobes frequently associated with BV, namely Gardnerella sp., Atopobium vaginae, Lactobacillus iners, Mobiluncus curtisii, Peptostreptococcus anaerobius and Prevotella bivia.MethodsA total of nine different culture media compositions, including commercially available and chemically defined media simulating genital tract secretions, were tested in this study. Planktonic cultures and biofilms were grown under anaerobic conditions (10% carbon dioxide, 10% helium and 80% nitrogen). Planktonic growth was assessed by optical density measurements, and biofilm formation was quantified by crystal violet staining.ResultsSignificant planktonic growth was observed for Gardnerella sp., A. vaginae and L. iners in New York City III broth, with or without ascorbic acid supplementation. Biofilm quantification showed high in vitro biofilm growth for Gardnerella sp., P. anaerobius and P. bivia in almost all culture media excluding Brucella broth. Contrary, only New York City III broth was able to promote biofilm formation for A. vaginae, L. iners and M. curtisii.ConclusionsOur data demonstrate that New York City III broth relative to the other tested media is the most conducive for future studies addressing polymicrobial biofilms development as this culture medium allowed the formation of significant levels of single-species biofilms. creator: Aliona S. Rosca creator: Joana Castro creator: Nuno Cerca uri: https://doi.org/10.7717/peerj.9917 license: https://creativecommons.org/licenses/by/4.0/ rights: © 2020 Rosca et al. title: A multi-class classification model for supporting the diagnosis of type II diabetes mellitus link: https://peerj.com/articles/9920 last-modified: 2020-09-10 description: BackgroundNumerous studies have utilized machine-learning techniques to predict the early onset of type 2 diabetes mellitus. However, fewer studies have been conducted to predict an appropriate diagnosis code for the type 2 diabetes mellitus condition. Further, ensemble techniques such as bagging and boosting have likewise been utilized to an even lesser extent. The present study aims to identify appropriate diagnosis codes for type 2 diabetes mellitus patients by means of building a multi-class prediction model which is both parsimonious and possessing minimum features. In addition, the importance of features for predicting diagnose code is provided.MethodsThis study included 149 patients who have contracted type 2 diabetes mellitus. The sample was collected from a large hospital in Taiwan from November, 2017 to May, 2018. Machine learning algorithms including instance-based, decision trees, deep neural network, and ensemble algorithms were all used to build the predictive models utilized in this study. Average accuracy, area under receiver operating characteristic curve, Matthew correlation coefficient, macro-precision, recall, weighted average of precision and recall, and model process time were subsequently used to assess the performance of the built models. Information gain and gain ratio were used in order to demonstrate feature importance.ResultsThe results showed that most algorithms, except for deep neural network, performed well in terms of all performance indices regardless of either the training or testing dataset that were used. Ten features and their importance to determine the diagnosis code of type 2 diabetes mellitus were identified. Our proposed predictive model can be further developed into a clinical diagnosis support system or integrated into existing healthcare information systems. Both methods of application can effectively support physicians whenever they are diagnosing type 2 diabetes mellitus patients in order to foster better patient-care planning. creator: Kuang-Ming Kuo creator: Paul Talley creator: YuHsi Kao creator: Chi Hsien Huang uri: https://doi.org/10.7717/peerj.9920 license: https://creativecommons.org/licenses/by/4.0/ rights: © 2020 Kuo et al. title: KEYLINK: towards a more integrative soil representation for inclusion in ecosystem scale models. I. review and model concept link: https://peerj.com/articles/9750 last-modified: 2020-09-09 description: The relatively poor simulation of the below-ground processes is a severe drawback for many ecosystem models, especially when predicting responses to climate change and management. For a meaningful estimation of ecosystem production and the cycling of water, energy, nutrients and carbon, the integration of soil processes and the exchanges at the surface is crucial. It is increasingly recognized that soil biota play an important role in soil organic carbon and nutrient cycling, shaping soil structure and hydrological properties through their activity, and in water and nutrient uptake by plants through mycorrhizal processes. In this article, we review the main soil biological actors (microbiota, fauna and roots) and their effects on soil functioning. We review to what extent they have been included in soil models and propose which of them could be included in ecosystem models. We show that the model representation of the soil food web, the impact of soil ecosystem engineers on soil structure and the related effects on hydrology and soil organic matter (SOM) stabilization are key issues in improving ecosystem-scale soil representation in models. Finally, we describe a new core model concept (KEYLINK) that integrates insights from SOM models, structural models and food web models to simulate the living soil at an ecosystem scale. creator: Gaby Deckmyn creator: Omar Flores creator: Mathias Mayer creator: Xavier Domene creator: Andrea Schnepf creator: Katrin Kuka creator: Kris Van Looy creator: Daniel P. Rasse creator: Maria J.I. Briones creator: Sébastien Barot creator: Matty Berg creator: Elena Vanguelova creator: Ivika Ostonen creator: Harry Vereecken creator: Laura M. Suz creator: Beat Frey creator: Aline Frossard creator: Alexei Tiunov creator: Jan Frouz creator: Tine Grebenc creator: Maarja Öpik creator: Mathieu Javaux creator: Alexei Uvarov creator: Olga Vindušková creator: Paul Henning Krogh creator: Oskar Franklin creator: Juan Jiménez creator: Jorge Curiel Yuste uri: https://doi.org/10.7717/peerj.9750 license: https://creativecommons.org/licenses/by/4.0/ rights: © 2020 Deckmyn et al. title: Omics approaches in Allium research: Progress and way ahead link: https://peerj.com/articles/9824 last-modified: 2020-09-09 description: BackgroundThe genus Allium (Family: Amaryllidaceae) is an economically important group of crops cultivated worldwide for their use as a vegetable and spices. Alliums are also well known for their nutraceutical properties. Among alliums, onion, garlic, leek, and chives cultivated worldwide. Despite their substantial economic and medicinal importance, the genome sequence of any of the Allium is not available, probably due to their large genome sizes. Recently evolved omics technologies are highly efficient and robust in elucidating molecular mechanisms of several complex life processes in plants. Omics technologies, such as genomics, transcriptomics, proteomics, metabolomics, metagenomics, etc. have the potential to open new avenues in research and improvement of allium crops where genome sequence information is limited. A significant amount of data has been generated using these technologies for various Allium species; it will help in understanding the key traits in Allium crops such as flowering, bulb development, flavonoid biosynthesis, male sterility and stress tolerance at molecular and metabolite level. This information will ultimately assist us in speeding up the breeding in Allium crops.MethodIn the present review, major omics approaches, and their progress, as well as potential applications in Allium crops, could be discussed in detail.ResultsHere, we have discussed the recent progress made in Allium research using omics technologies such as genomics, transcriptomics, micro RNAs, proteomics, metabolomics, and metagenomics. These omics interventions have been used in alliums for marker discovery, the study of the biotic and abiotic stress response, male sterility, organ development, flavonoid and bulb color, micro RNA discovery, and microbiome associated with Allium crops. Further, we also emphasized the integrated use of these omics platforms for a better understanding of the complex molecular mechanisms to speed up the breeding programs for better cultivars.ConclusionAll the information and literature provided in the present review throws light on the progress and potential of omics platforms in the research of Allium crops. We also mentioned a few research areas in Allium crops that need to be explored using omics technologies to get more insight. Overall, alliums are an under-studied group of plants, and thus, there is tremendous scope and need for research in Allium species. creator: Kiran Khandagale creator: Ram Krishna creator: Praveen Roylawar creator: Avinash B. Ade creator: Ashwini Benke creator: Bharat Shinde creator: Major Singh creator: Suresh J. Gawande creator: Ashutosh Rai uri: https://doi.org/10.7717/peerj.9824 license: https://creativecommons.org/licenses/by/4.0/ rights: ©2020 Khandagale et al. title: Assessment of postoperative health functioning after knee arthroplasty in relation to pain catastrophizing: a 6-month follow-up cohort study link: https://peerj.com/articles/9903 last-modified: 2020-09-09 description: BackgroundKnee arthroplasty (KA) is a typically successful surgical procedure commonly performed to alleviate painin participants with end-stage knee osteoarthritis. Despite its beneficial effects, a significant proportion of individuals with KA continue experiencing persistent pain and functional limitations. The purpose of this study was to assess the postoperative outcomes after KA in relation to postoperative pain catastrophizing.MethodsParticipants were recruited at a domiciliary physiotherapy service, using a prospective, observational, hypothesis-generating cohort design. Participants were divided into two groups based on their Pain Catastrophizing Scale (PCS) total score (50th percentile), which resulted in high and low PCS groups. The primary outcome measure was the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC). In addition, quality of life, walking speed, physical performance, range of motion, and pain were measured. Outcome measures were collected at baseline (1 week postoperatively) and at follow-up (1, 3, and 6 months postoperatively).ResultsA total of 60 participants (21 total KA and 39 unicompartmental KA) were recruited. Individuals with a higher degree of pain catastrophizing showed significantly higher WOMAC total scores at every follow-up, indicating poorer health functioning (p < 0.01). Similarly, the high PCS group showed higher WOMAC pain, stiffness and disability subscale scores (p < 0.05), poorer quality of life (p < 0.01), and poorer physical performance (p < 0.05) at every follow-up. In addition, the high PCS group achieved a slower walking speed at baseline and at 3 months follow-up (p < 0.05), and a higher degree of pain at rest, on walking and on knee flexion at every follow-up (p < 0.01, p < 0.05 and p < 0.05, respectively) except for walking pain at 3 months follow-up. No significant differences were observed between groups in range of motion, except for active knee extension at the 6-month follow-up (p < 0.05). Effect size was large at 1 month follow-up in WOMAC total score (r = 0.578) and pain intensity during knee flexion (r = 0.529). Longitudinal analyses revealed different improvement trends during the rehabilitation process between groups, with a lack of significant improvements in the high PCS group between the 3- and 6-month follow-up in WOMAC total score, WOMAC pain, WOMAC disability, quality of life, physical performance, active knee extension and resting pain (p > 0.05).ConclusionThe results of the present study suggest that participants with high postoperative pain catastrophizing might have poorer outcomes during the rehabilitation process after KA. Future work should seek to clarify if this relationship is causal. creator: Marc Terradas-Monllor creator: Mirari Ochandorena-Acha creator: Julio Salinas-Chesa creator: Sergi Ramírez creator: Hector Beltran-Alacreu uri: https://doi.org/10.7717/peerj.9903 license: https://creativecommons.org/licenses/by/4.0/ rights: ©2020 Terradas-Monllor et al. title: Effect of nest age and habitat variables on nest survival in Marsh Harrier (Circus aeruginosus) in a fishpond habitat link: https://peerj.com/articles/9929 last-modified: 2020-09-09 description: BackgroundOne important anti‐predator strategy adopted by birds involves nest site selection and timing of breeding. Nest-site selection by marsh-nesting birds often involves nest concealment and water depth as key features influencing nest survival. Marsh Harrier (Circus aeruginosus) is an obligate ground nester, which sets it apart from other raptors. The aim of the present study was to identify for the first time possible temporal and habitat factors affecting nest survival in Marsh Harrier. Understanding features which affect nest survival are essential for assessing relevant conservation strategies.MethodsTo understand the relative contributions of different temporal and habitat variables to brood losses, it is useful to determine the daily survival rate (DSR). We examined 82 Marsh Harrier nests located on fishponds in eastern Poland, where predation is the main cause of nest loss. Six habitat variables were measured for each active nest. DSR was calculated using known-fate models with the RMark package.ResultsThe best-supported model predicted that DSR decreased with nest age and was positively affected by the water depth and the diameter of reed stems, but not by the height or density of vegetation at the nest site. The distances of nests to the fishpond dyke and to open water received no support in the models. The chances of nest survival were lower if a neighbouring nest had been depredated. This result suggests that the Marsh Harrier is more susceptible to mammalian than avian predation and confirms the high level of predator pressure in fishpond habitats. creator: Urszula Zaremba creator: Zbigniew Kasprzykowski creator: Artur Golawski uri: https://doi.org/10.7717/peerj.9929 license: https://creativecommons.org/licenses/by/4.0/ rights: © 2020 Zaremba et al. title: A descriptive study of random forest algorithm for predicting COVID-19 patients outcome link: https://peerj.com/articles/9945 last-modified: 2020-09-09 description: BackgroundThe outbreak of coronavirus disease 2019 (COVID-19) that occurred in Wuhan, China, has become a global public health threat. It is necessary to identify indicators that can be used as optimal predictors for clinical outcomes of COVID-19 patients.MethodsThe clinical information from 126 patients diagnosed with COVID-19 were collected from Wuhan Fourth Hospital. Specific clinical characteristics, laboratory findings, treatments and clinical outcomes were analyzed from patients hospitalized for treatment from 1 February to 15 March 2020, and subsequently died or were discharged. A random forest (RF) algorithm was used to predict the prognoses of COVID-19 patients and identify the optimal diagnostic predictors for patients’ clinical prognoses.ResultsSeven of the 126 patients were excluded for losing endpoints, 103 of the remaining 119 patients were discharged (alive) and 16 died in the hospital. A synthetic minority over-sampling technique (SMOTE) was used to correct the imbalanced distribution of clinical patients. Recursive feature elimination (RFE) was used to select the optimal subset for analysis. Eleven clinical parameters, Myo, CD8, age, LDH, LMR, CD45, Th/Ts, dyspnea, NLR, D-Dimer and CK were chosen with AUC approximately 0.9905. The RF algorithm was built to predict the prognoses of COVID-19 patients based on the best subset, and the area under the ROC curve (AUC) of the test data was 100%. Moreover, two optimal clinical risk predictors, lactate dehydrogenase (LDH) and Myoglobin (Myo), were selected based on the Gini index. The univariable logistic analysis revealed a substantial increase in the risk for in-hospital mortality when Myo was higher than 80 ng/ml (OR = 7.54, 95% CI [3.42–16.63]) and LDH was higher than 500 U/L (OR = 4.90, 95% CI [2.13–11.25]).ConclusionWe applied an RF algorithm to predict the mortality of COVID-19 patients with high accuracy and identified LDH higher than 500 U/L and Myo higher than 80 ng/ml to be potential risk factors for the prognoses of COVID-19 patients in the early stage of the disease. creator: Jie Wang creator: Heping Yu creator: Qingquan Hua creator: Shuili Jing creator: Zhifen Liu creator: Xiang Peng creator: Cheng’an Cao creator: Yongwen Luo uri: https://doi.org/10.7717/peerj.9945 license: https://creativecommons.org/licenses/by/4.0/ rights: © 2020 Wang et al. title: Correlation between obesity and clinicopathological characteristics in patients with papillary thyroid cancer: a study of 1579 cases: a retrospective study link: https://peerj.com/articles/9675 last-modified: 2020-09-08 description: ObjectiveTo explore the relationship between body mass index (BMI) and clinicopathological characteristics in patients with papillary thyroid carcinoma (PTC).MethodsThe clinical data of 1,579 patients with PTC, admitted to our hospital from May 2016 to March 2017, were retrospectively analyzed. According to the different BMI of patients, it can be divided into underweight recombination (BMI < 18.5 kg/m), normal body recombination (18.5 ≤ BMI < 24.0 kg/m2), overweight recombination (24.0 ≤ BMI < 28.0 kg/m2) and obesity group (BMI ≥ 28.0 kg/m2). The clinicopathological characteristics of PTC in patients with different BMIs group were compared.ResultsIn our study, the risk for extrathyroidal extension (ETE), advanced T stage (T III/IV), and advanced tumor-node-metastasis stage (TNM III/IV) in the overweight group were higher, with OR (odds ratio) = 1.99(1.41–2.81), OR = 2.01(1.43–2.84), OR = 2.94(1.42–6.07), respectively, relative to the normal weight group. The risk for ETE and T III/IV stage in the obese group were higher, with OR = 1.82(1.23–2.71) and OR = 1.82(1.23–2.70), respectively, relative to the normal weight group.ConclusionBMI is associated with the invasiveness of PTC. There is a higher risk for ETE and TNM III/IV stage among patients with PTC in the overweight group and for ETE among patients with PTC in the obese group. creator: Huijuan Wang creator: Pingping Wang creator: Yu Wu creator: Xiukun Hou creator: Zechun Peng creator: Weiwei Yang creator: Lizhao Guan creator: Linfei Hu creator: Jingtai Zhi creator: Ming Gao creator: Xiangqian Zheng uri: https://doi.org/10.7717/peerj.9675 license: https://creativecommons.org/licenses/by/4.0/ rights: ©2020 Wang et al.