title: PeerJ description: Articles published in PeerJ link: https://peerj.com/articles/index.rss3?journal=peerj&page=727 creator: info@peerj.com PeerJ errorsTo: info@peerj.com PeerJ language: en title: Effectiveness of digital mental health interventions for university students: an umbrella review link: https://peerj.com/articles/13111 last-modified: 2022-03-31 description: BackgroundPoor mental health among university students remains a pressing public health issue. Over the past few years, digital health interventions have been developed and considered promising in increasing psychological wellbeing among university students. Therefore, this umbrella review aims to synthesize evidence on digital health interventions targeting university students and to evaluate their effectiveness.MethodsA systematic literature search was performed in April 2021 searching PubMed, Psychology and Behavioural Science Collection, Web of Science, ERIC, and Scopus for systematic reviews and meta-analyses on digital mental health interventions targeting university students. The review protocol was registered in the International Prospective Register of Systematic Reviews PROSPERO [CRD42021234773].ResultsThe initital literature search resulted in 806 records of which seven remained after duplicates were removed and evaluated against the inclusion criteria. Effectiveness was reported and categorized into the following six delivery types: (a) web-based, online/computer-delivered interventions (b) computer-based Cognitive Behavior Therapy (CBT), (c) mobile applications and short message service (d) virtual reality interventions (e) skills training (f) relaxation and exposure-based therapy. Results indicated web-based online/computer delivered-interventions were effective or at least partially effective at decressing depression, anxiety, stress and eating disorder symptoms. This was similar for skills-training interventions, CBT-based intervention and mobile applications. However, digital mental health interventions using virtual reality and relaxation, exposure-based therapy was inconclusive. Due to the variation in study settings and inconsistencies in reporting, effectiveness was greatly dependent on the delivery format, targeted mental health problem and targeted purpose group.ConclusionThe findings provide evidence for the beneficial effect of digital mental health interventions for university students. However, this review calls for a more systematic approach in testing and reporting the effectiveness of digital mental health interventions. creator: Sophia Harith creator: Insa Backhaus creator: Najihah Mohbin creator: Huyen Thi Ngo creator: Selina Khoo uri: https://doi.org/10.7717/peerj.13111 license: https://creativecommons.org/licenses/by/4.0/ rights: © 2022 Harith et al. title: Insight into the cryptic diversity and phylogeography of the peculiar fried egg jellyfish Phacellophora (Cnidaria, Scyphozoa, Ulmaridae) link: https://peerj.com/articles/13125 last-modified: 2022-03-31 description: The fried egg jellyfish Phacellophora camtschatica (senso lato) is a morphologically peculiar and conspicuous species occurring mostly in the cold waters of the North Pacific. It is less common in the cold waters of the NW Atlantic, and occasionally has been reported in the Mediterranean, Arctic, East and South Pacific, and E, SW and NE Atlantic. However, sightings of this scyphozoan jellyfish have intensified during the past two to three decades in Macaronesia, the Iberian Peninsula and the Mediterranean. These jellyfish are known to be voracious predators of other jellies, but also of other taxa, including fish of commercial interest. Therefore, Phacellophora aggregations may threaten local fisheries, aquaculture, and local biodiversity structuring. We report the first known occurrences of Phacellophora in the Azores Islands, which apparently become more frequent in recent years of the past decade. We confirm, through DNA barcoding of COI and 16S mitochondrial markers, the genetic identity of Phacellophora occurring in the Azores (NE Atlantic). We reveal, with COI sequence data, three (potentially four) cryptic species within the Phacellophora camtschatica complex. Two Phacellophora species co-occur in the North Pacific. In the North Atlantic (and possibly in the Mediterranean) one or two distinct species exist. Three nominal species of the genus that are currently synonymized, with type localities in the N Pacific, NW Atlantic, and the Mediterranean, need reassessment. The morphotypes previously defined for the four putative species names given for Phacellophora might be eventually differentiated by the number and disposition of the marginal lappets of umbrellae. This morphologic character has to be further inspected in vouchers of the four genetic lineages of Phacellophora, to decide between the description of new species, and the resurrection of junior synonyms through the designation of neotypes with DNA Barcodes, to validate the identity of the cryptic taxa detected. More haplotype sampling is necessary across the distribution of the genus to further investigate the genetic diversity and phylogeographic history of Phacellophora. The high genetic relatedness of Phacellophora from the cold NW Atlantic and the sub-tropical shores of the Azores, revealed by 16S and COI sequence data, suggests a recent invasion, in terms of geologic time, of the temperate waters of the NE Atlantic (and possibly of the Mediterranean). The medusivorous habits of Phacellophora, and especially its predation on the mauve stinger (Pelagia spp.) which frequently blooms in Macaronesia and Mediterranean waters, could relate to the recent reports of Phacellophora in the Azores, Madeira, Canary Islands, and the Mediterranean.More investment, including on scientific staff, is necessary to catalog, DNA barcode and monitor jellyfish dynamics more accurately worldwide. creator: Carlos J. Moura creator: Nikolai Ropa creator: Bruno Ivo Magalhães creator: João M. Gonçalves uri: https://doi.org/10.7717/peerj.13125 license: https://creativecommons.org/licenses/by/4.0/ rights: © 2022 Moura et al. title: Continuous mutation of SARS-CoV-2 during migration via three routes at the beginning of the pandemic link: https://peerj.com/articles/12681 last-modified: 2022-03-30 description: BackgroundIt remains unclear how severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection started, spread worldwide, and mutated to result in the present variants. This difficulty can be attributed to the limitations associated with the analytical methodology for presenting the differences among genomic sequences. In this study, we critically analysed the early data to explain the start and spread of the pandemic.MethodsObjective analyses of the RNA sequences of earlier variants of SARS-CoV-2 (up to September 1, 2020, available in DDBJ and GISAID) were performed using Principal Component Analysis (PCA). The results were compared with information on the collection dates and location. The PCA was also conducted for 12 variants of interest to the WHO as of September 2021, and compared with earlier data.ResultsThe pandemic began in Wuhan, China. This strain was suspected to be related to other reported animal viruses; however, they had a minimal similarity. The strain then spreads via three routes while accumulating mutations. Several viral subgroups were identified along the routes, each with a large number of patients reported, indicating high infectivity to humans. These routes were only confirmed by the early data analysis, because newer variants would have more mutations, and would be preferentially be examined by PCA if they were included. On the original axes found in the early variants, the newer variants revealed that they retained previously acquired mutations, which helped to reveal the viral ancestors of the newer variants. The rate of mutation was found to be comparable to that of the influenza H1N1 virus, which causes recurrent seasonal epidemics. Another threat imposed by SARS-CoV-2 is that if the pandemic cannot be contained, new variants may emerge annually, preventing herd immunity. creator: Tomokazu Konishi uri: https://doi.org/10.7717/peerj.12681 license: https://creativecommons.org/licenses/by/4.0/ rights: ©2022 Konishi title: Expression profiles and transcript properties of fast-twitch and slow-twitch muscles in a deep-sea highly migratory fish, Pseudocaranx dentex link: https://peerj.com/articles/12720 last-modified: 2022-03-30 description: Fast-twitch and slow-twitch muscles are the two principal skeletal muscle types in teleost with obvious differences in metabolic and contractile phenotypes. The molecular mechanisms that control and maintain the different muscle types remain unclear yet. Pseudocaranx dentex is a highly mobile active pelagic fish with distinctly differentiated fast-twitch and slow-twitch muscles. Meanwhile, P. dentex has become a potential target species for deep-sea aquaculture because of its considerable economic value. To elucidate the molecular characteristics in the two muscle types of P. dentex, we generated 122 million and 130 million clean reads from fast-twitch and slow-witch muscles using RNA-Seq, respectively. Comparative transcriptome analysis revealed that 2,862 genes were differentially expressed. According to GO and KEGG analysis, the differentially expressed genes (DEGs) were mainly enriched in energy metabolism and skeletal muscle structure related pathways. Difference in the expression levels of specific genes for glycolytic and lipolysis provided molecular evidence for the differences in energy metabolic pathway between fast-twitch and slow-twitch muscles of P. dentex. Numerous genes encoding key enzymes of mitochondrial oxidative phosphorylation pathway were significantly upregulated at the mRNA expression level suggested slow-twitch muscle had a higher oxidative phosphorylation to ensure more energy supply. Meanwhile, expression patterns of the main skeletal muscle developmental genes were characterized, and the expression signatures of Sox8, Myod1, Calpain-3, Myogenin, and five insulin-like growth factors indicated that more myogenic cells of fast-twitch muscle in the differentiating state. The analysis of important skeletal muscle structural genes showed that muscle type-specific expression of myosin, troponin and tropomyosin may lead to the phenotypic structure differentiation. RT-qPCR analysis of twelve DEGs showed a good correlation with the transcriptome data and confirmed the reliability of the results presented in the study. The large-scale transcriptomic data generated in this study provided an overall insight into the thorough gene expression profiles of skeletal muscle in a highly mobile active pelagic fish, which could be valuable for further studies on molecular mechanisms responsible for the diversity and function of skeletal muscle. creator: Huan Wang creator: Busu Li creator: Long Yang creator: Chen Jiang creator: Tao Zhang creator: Shufang Liu creator: Zhimeng Zhuang uri: https://doi.org/10.7717/peerj.12720 license: https://creativecommons.org/licenses/by/4.0/ rights: © 2022 Wang et al. title: Oviducal gland transcriptomics of Octopus maya through physiological stages and the negative effects of temperature on fertilization link: https://peerj.com/articles/12895 last-modified: 2022-03-30 description: BackgroundElevated temperatures reduce fertilization and egg-laying rates in the octopus species. However, the molecular mechanisms that control the onset of fertilization and egg-laying in the octopus’ oviducal gland are still unclear; and the effect of temperature on the expression of key reproductive genes is unknown. This study aims to better understand the molecular bases of octopus fertilization and egg-laying, and how they are affected by elevated temperatures.MethodRNA-seq of oviducal glands was performed for samples before, during, and after fertilization and their transcriptomic profiles were compared. Also, at the fertilization stage, the optimal and thermal-stress conditions were contrasted. Expression levels of key reproductive genes were validated via RT-qPCR.ResultsIn mated females before egg-laying, genes required for the synthesis of spermine, spermidine, which may prevent premature fertilization, and the myomodulin neuropeptide were upregulated. Among the genes with higher expression at the fertilization stage, we found those encoding the receptors of serotonin, dopamine, and progesterone; genes involved in the assembly and motility of the sperm flagellum; genes that participate in the interaction between male and female gametes; and genes associated with the synthesis of eggshell mucoproteins. At temperatures above the optimal range for reproduction, mated females reduced the fertilization rate. This response coincided with the upregulation of myomodulin and APGW-amide neuropeptides. Also, genes associated with fertilization like LGALS3, VWC2, and Pcsk1 were downregulated at elevated temperatures. Similarly, in senescent females, genes involved in fertilization were downregulated but those involved in the metabolism of steroid hormones like SRD5A1 were highly expressed. creator: Oscar E. Juárez creator: Lousiana Arreola-Meraz creator: Edna Sánchez-Castrejón creator: Omar Hernando Avila-Poveda creator: Laura L. López-Galindo creator: Carlos Rosas creator: Clara E. Galindo-Sánchez uri: https://doi.org/10.7717/peerj.12895 license: https://creativecommons.org/licenses/by/4.0/ rights: © 2022 Juárez et al. title: Heart rate variability, mood and performance: a pilot study on the interrelation of these variables in amateur road cyclists link: https://peerj.com/articles/13094 last-modified: 2022-03-30 description: ObjectiveThe present study seeks to explore the relationship between measures of cycling training on a given day and the heart rate variability (HRV) and mood states obtained the following morning. The association between HRV and mood state is also studied, as is the relationship between internal and external measures of training.MethodsDuring a 6-week period, five recreational road cyclists collected 123 recordings of morning HRV and morning mood, and 66 recordings of training power and rate of perceived exertion (RPE). Training power was used as an external measure of performance and RPE as an internal measure of performance. The HRV parameters used in the study were the mean of RR intervals (mean RR) and the standard deviation of all RR intervals (SDNN) as time domain analysis, and the normalized high frequency band (HFnu), normalized low frequency band (LFnu) and the ratio between low and high frequency bands, as frequency domain analysis. Mood was measured using a 10-point cognitive scale.ResultsIt was found that the higher the training power on a given day, the lower the HFnu and the higher LF/HF were on the following morning. At the same time, results showed an inverse relationship between training and mood, so the tougher a training session, the lower the mood the following day. A relationship between morning HRV and mood was also found, so that the higher mean RR and HFnu, the more positive the mood (r = 0.497 and r = 0.420 respectively; p < 0.001). Finally, RPE correlated positively with external power load variables (IF: r = 0.545; p < 0.001).ConclusionAltogether, the results indicate a relationship between training of cyclists on a given day and their morning HRV and mood state on the following day. Mood and HRV also seem positively related. It is argued that developing a monitoring system that considers external and internal training loads, together with morning mood, could help understand the state of the individual, enabling feedback to athletes to facilitate the adaptation to training and to prevent problems associated with overtraining. However, more research is needed to further understand the association between the different variables considered. creator: Carla Alfonso creator: Lluis Capdevila uri: https://doi.org/10.7717/peerj.13094 license: https://creativecommons.org/licenses/by/4.0/ rights: © 2022 Alfonso and Capdevila title: RNA sequencing reveals the emerging role of bronchoalveolar lavage fluid exosome lncRNAs in acute lung injury link: https://peerj.com/articles/13159 last-modified: 2022-03-30 description: BackgroundBronchoalveolar lavage fluid (BALF) exosomes possess different properties in different diseases, which are mediated through microRNAs (miRNAs) and long noncoding RNAs (lncRNAs), among others. By sequencing the differentially expressed lncRNAs in BALF exosomes, we seek potential targets for the diagnosis and treatment of acute lung injury (ALI).MethodsConsidering that human and rat genes are about 80% similar, ALI was induced using lipopolysaccharide in six male Wistar rats, with six rats as control (all weighing 200 ± 20 g and aged 6–8 weeks). BALF exosomes were obtained 24 h after ALI. The exosomes in BALF were extracted by ultracentrifugation. The differential expression of BALF exosomal lncRNAs in BALF was analyzed by RNA sequencing. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed to predict the functions of differentially expressed lncRNAs, which were confirmed by reverse transcription–polymerase chain reaction.ResultsCompared with the control group, the ALI group displayed a higher wet/dry ratio, tumor necrosis factor-α levels, and interleukin-6 levels (all P < 0.001). The airway injection of exosomes in rats led to significant infiltration by neutrophils. A total of 2,958 differentially expressed exosomal lncRNAs were identified, including 2,524 upregulated and 434 downregulated ones. Five lncRNAs confirmed the reliability of the sequencing data. The top three GO functions were phagocytic vesicle membrane, regulation of receptor biosynthesis process, and I-SMAD binding. Salmonella infection, Toll-like receptor signaling pathway, and osteoclast differentiation were the most enriched KEGG pathways. The lncRNA–miRNA interaction network of the five confirmed lncRNAs could be predicted using miRDB.ConclusionsBALF-derived exosomes play an important role in ALI development and help identify potential therapeutic targets related to ALI. creator: Meijuan Song creator: Xiuwei Zhang creator: Yizhou Gao creator: Bing Wan creator: Jinqiang Wang creator: Jinghang Li creator: Yuanyuan Song creator: Xiaowei Shen creator: Li Wang creator: Mao Huang creator: Xiaowei Wang uri: https://doi.org/10.7717/peerj.13159 license: https://creativecommons.org/licenses/by/4.0/ rights: © 2022 Song et al. title: ExhauFS: exhaustive search-based feature selection for classification and survival regression link: https://peerj.com/articles/13200 last-modified: 2022-03-30 description: Feature selection is one of the main techniques used to prevent overfitting in machine learning applications. The most straightforward approach for feature selection is an exhaustive search: one can go over all possible feature combinations and pick up the model with the highest accuracy. This method together with its optimizations were actively used in biomedical research, however, publicly available implementation is missing. We present ExhauFS—the user-friendly command-line implementation of the exhaustive search approach for classification and survival regression. Aside from tool description, we included three application examples in the manuscript to comprehensively review the implemented functionality. First, we executed ExhauFS on a toy cervical cancer dataset to illustrate basic concepts. Then, multi-cohort microarray breast cancer datasets were used to construct gene signatures for 5-year recurrence classification. The vast majority of signatures constructed by ExhauFS passed 0.65 threshold of sensitivity and specificity on all datasets, including the validation one. Moreover, a number of gene signatures demonstrated reliable performance on independent RNA-seq dataset without any coefficient re-tuning, i.e., turned out to be cross-platform. Finally, Cox survival regression models were used to fit isomiR signatures for overall survival prediction for patients with colorectal cancer. Similarly to the previous example, the major part of models passed the pre-defined concordance index threshold 0.65 on all datasets. In both real-world scenarios (breast and colorectal cancer datasets), ExhauFS was benchmarked against state-of-the-art feature selection models, including L1-regularized sparse models. In case of breast cancer, we were unable to construct reliable cross-platform classifiers using alternative feature selection approaches. In case of colorectal cancer not a single model passed the same 0.65 threshold. Source codes and documentation of ExhauFS are available on GitHub: https://github.com/s-a-nersisyan/ExhauFS. creator: Stepan Nersisyan creator: Victor Novosad creator: Alexei Galatenko creator: Andrey Sokolov creator: Grigoriy Bokov creator: Alexander Konovalov creator: Dmitry Alekseev creator: Alexander Tonevitsky uri: https://doi.org/10.7717/peerj.13200 license: https://creativecommons.org/licenses/by/4.0/ rights: ©2022 Nersisyan et al. title: Machine learning driven by environmental covariates to estimate high-resolution PM2.5 in data-poor regions link: https://peerj.com/articles/13203 last-modified: 2022-03-30 description: PM2.5, which refers to fine particles with an equivalent aerodynamic diameter of less than or equal to 2.5 µm, can not only affect air quality but also endanger public health. Nevertheless, the spatial distribution of PM2.5 is not well understood in data-poor regions where monitoring stations are scarce. Therefore, we constructed a random forest (RF) model and a bagging algorithm model based on ground-monitored PM2.5 data, aerosol optical depth (AOD) and meteorological data, and auxiliary geographical variables to accurately estimate the spatial distribution of PM2.5 concentrations in Xinjiang during 2015–2020 at a resolution of 1 km. Through 10-fold cross-validation (CV), the RF model and bagging algorithm model were verified and compared. The results showed the following: (1) The RF model achieved better model performance and thus can be used to estimate the PM2.5 concentration at a relatively high resolution. (2) The PM2.5 concentrations were high in southern Xinjiang and low in northern Xinjiang. The high values were concentrated mainly in the Tarim Basin, while most areas of northern Xinjiang maintained low PM2.5 levels year-round. (3) The PM2.5 values in Xinjiang showed significant seasonality, with the seasonally averaged concentrations decreasing as follows: winter (71.95 µg m−3) > spring (64.76 µg m−3) > autumn (46.01 µg m−3) > summer (43.40 µg m−3). Our model provides a way to monitor air quality in data-scarce places, thereby advancing efforts to achieve sustainable development in the future. creator: XiaoYe Jin creator: Jianli Ding creator: Xiangyu Ge creator: Jie Liu creator: Boqiang Xie creator: Shuang Zhao creator: Qiaozhen Zhao uri: https://doi.org/10.7717/peerj.13203 license: https://creativecommons.org/licenses/by-nc/4.0 rights: ©2022 Jin et al. title: Bioinformatical analysis identifies PDLIM3 as a potential biomarker associated with immune infiltration in patients with endometriosis link: https://peerj.com/articles/13218 last-modified: 2022-03-30 description: BackgroundEndometriosis is a chronic systemic disease, whose classic symptoms are pelvic pain and infertility. This disease seriously reduces the life quality of patients. The pathogenesis, recognition and treatment of endometriosis is still unclear, and cannot be over emphasized. The aim of our study was to investigate the potential biomarker of endometriosis for the mechanism and treatment.MethodsUsing GSE11691, GSE23339 and GSE5108 datasets, differentially expressed genes (DEGs) were identified between endometriosis and normal samples. The functions of DEGs were reflected by the analysis of gene ontology (GO), pathway enrichment and gene set enrichment analysis (GSEA). The LASSO regression model was performed to identify candidate biomarkers. The receiver operating characteristic curve (ROC) was used to evaluate discriminatory ability of candidate biomarkers. The predictive value of the markers in endometriosis were further validated in the GSE120103 dataset. Then, the expression level of biomarkers was detected by qRT-PCR and Western blot. Finally, the relationship between candidate biomarker expression and immune infiltration was estimated using CIBERSORT.ResultsA total of 42 genes were identified, which were mainly involved in cytokine–cytokine receptor interaction, systemic lupus erythematosus and chemokine signaling pathway. We confirmed PDLIM3 was a specific biomarker in endometriosis (AUC = 0.955) and validated in the GSE120103 dataset (AUC = 0.836). The mRNA and protein expression level of PDLIM3 in endometriosis tissue was significantly higher than normal. Immune cell infiltration analysis revealed that PDLIM3 was correlated with M2 macrophages, neutrophils, CD4+ memory resting T cells, gamma delta T cells, M1 Macrophages, resting mast cells, follicular helper T cells, activated NK cells, CD8+ T cells, regulatory T cells (Tregs), naive B cells, plasma cells and resting NK cells. creator: Lei Gan creator: Jiani Sun creator: Jing Sun uri: https://doi.org/10.7717/peerj.13218 license: https://creativecommons.org/licenses/by/4.0/ rights: © 2022 Gan et al.