Computed tomography-based radiomics machine learning models for prediction of histological invasiveness with sub-centimeter subsolid pulmonary nodules: a retrospective study
To improve the accuracy of preoperative diagnoses and avoid over- or undertreatment, we aimed to develop and compare computed tomography-based radiomics machine learning models for the prediction of histological invasiveness using sub-centimeter subsolid pulmonary nodules. Three predictive models based on radiomics were built using three machine learning classifiers to discriminate the invasiveness of the sub-centimeter subsolid pulmonary nodules. A total of 203 sub-centimeter nodules from 177 patients were collected and assigned randomly to the training set (n = 143) or test set (n = 60). The areas under the curve of the predictive models were 0.743 (95% confidence interval CI [0.661–0.824]) for the logistic regression, 0.828 (95% CI [0.76–0.896]) for the support vector machine, and 0.917 (95% CI [0.869–0.965]) for the XGBoost classifier models in the training set, and 0.803 (95% CI [0.694–0.913]), 0.726 (95% CI [0.598–0.854]), and 0.874 (95% CI [0.776–0.972]) in the test set, respectively. In addition, the decision curve showed that the XGBoost model added more net benefit within the range of 0.06 to 0.93.
Zhang et al. (2023) Computed tomography-based radiomics machine learning models for prediction of histological invasiveness with sub-centimeter subsolid pulmonary nodules: a retrospective study. PeerJ 11:e14559 https://doi.org/10.7717/peerj.14559
Isopsoralen suppresses receptor activator of nuclear factor kappa-β ligand-induced osteoclastogenesis by inhibiting the NF-κB signaling
Osteoporosis is a serious systemic metabolic bone system disease.This study aimed to identify the target genes of isopsoralen and the signaling pathways involved in the differential expression of the genes involved in osteoclast differentiation. We hypothesized that isopsoralen may inhibit osteoclast differentiation by blocking the nuclear factor kappa-B (NF-κB) signaling pathway and verified our hypothesis through basic experiments. The 3-(4, 5-dimethylthiazol-2-yl)-2, 5-diphenyltetrazolium bromide (MTT) assay was used to detect the effect of isopsoralen on the proliferation and viability of primary mouse bone marrow monocytes (BMMCs). The effect of isopsoralen on receptor activator of nuclear factor kappa-B ligand (RANKL)-induced osteoclast differentiation was determined by using tartrate-resistant acid phosphatase (TRAP) staining. Quantitative real-time PCR (qRT-PCR) and Western blot were used to detect the expression of the related genes and proteins. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway of isopsoralen target genes were obtained through comprehensive analysis using the STITCH database, Cytoscape 3.8.2, and R-Studio software. Differentially expressed genes (DEGs) were found in osteoclasts induced by RANKL before and after 3 days using R-Studio, following which KEGG analysis was performed. Next, enrichment analysis was performed on the KEGG pathway shared by the target genes of isopsoralen and the differentially expressed genes during osteoclast differentiation to predict the signaling pathway underlying the inhibition of osteoclast differentiation by isopsoralen. Finally, Western blot was used to detect the effect of isopsoralen on the activation of signaling pathways to verify the results of our bioinformatics analysis. Based on the enrichment analysis of isopsoralen target genes and differentially expressed genes during osteoclastogenesis, we believe that isopsoralen can inhibit RANKL-induced osteoclastogenesis by inhibiting the NF-κB signaling pathway.
Zhan et al. (2023) Isopsoralen suppresses receptor activator of nuclear factor kappa-β ligand-induced osteoclastogenesis by inhibiting the NF-κB signaling. PeerJ 11:e14560 https://doi.org/10.7717/peerj.14560
No detectable changes in reproductive behaviour of Caenorhabditis elegans males after 97 generations under obligatory outcrossing
In Caenorhabditis elegans, a species reproducing mostly via self-fertilization, numerous signatures of selfing syndrome are observed, including differences in reproductive behaviour compared to related obligatory outcrossing species. In this study we investigated the effect of nearly 100 generations of obligatory outcrossing on several characteristics of male reproductive behaviour. A genetically uniform ancestral population carrying a mutation changing the reproductive system to obligatory outcrossing was split into four independent populations. We predicted that the transition from the natural reproductive system, where males were extremely rare, to obligatory outcrossing, where males comprise 50% of the population and are necessary for reproduction, will increase the selection pressure on higher effectiveness of mating behaviour. Several characteristics of male mating behaviour during a 15 min interaction as well as copulation success were compared between the ancestral and evolved populations. No significant differences in male mating behaviour or fertilization success were detected between generations 1 and 97 of obligatory outcrossing populations. We found, however, that longer contact with females increased chances of successful copulation, although this effect did not differ between populations. We conclude that either selection acting on male mating behaviour has not been strong enough, or mutational input of new adaptive variants has not been sufficient to cause noticeable behavioural differences after 97 generations of evolution starting from genetically uniform population.
Antoł et al. (2023) No detectable changes in reproductive behaviour of Caenorhabditis elegans males after 97 generations under obligatory outcrossing. PeerJ 11:e14572 https://doi.org/10.7717/peerj.14572
Pemafibrate prevents choroidal neovascularization in a mouse model of neovascular age-related macular degeneration
Background Pathological choroidal neovascularization (CNV) is one of the major causes of visual impairment in neovascular age-related macular degeneration (AMD). CNV has been suppressed by using anti-vascular endothelial growth factor (VEGF) antibodies. However, some clinical cases have demonstrated the failure of anti-VEGF therapies. Furthermore, anti-VEGF agents might induce the development of ocular atrophy. Recently, peroxisome proliferator-activated receptor alpha (PPARα) activation using pemafibrate treatment was suggested as one of the promising therapeutic targets in the prevention of ocular ischemia. However, the preventive role of pemafibrate remains unclear in CNV. We aimed to examine the preventive role of pemafibrate on laser-induced pathological CNV. Methods Adult male C57BL/6 mice were orally supplied pemafibrate (0.5 mg/kg) for four days, followed by laser irradiation. Then, pemafibrate was consecutively given to mice with the same condition. CNV was visualized with isolectin-IB4. The eye (retina and/or retinal pigment epithelium [RPE]-choroid), liver, and serum were used for biomolecular analyses. Results We found that pemafibrate administration suppressed CNV volumes. Pemafibrate administration activated PPARα downstream genes in the liver and eye (especially, RPE-choroid). Furthermore, pemafibrate administration elevated serum fibroblast growth factor 21 levels and reduced serum levels of triglycerides. Conclusions Our data suggest a promising pemafibrate therapy for suppressing CNV in AMD.
Lee et al. (2023) Pemafibrate prevents choroidal neovascularization in a mouse model of neovascular age-related macular degeneration. PeerJ 11:e14611 https://doi.org/10.7717/peerj.14611
Comprehensive analysis of fatty acid metabolism-related gene signatures for predicting prognosis in patients with prostate cancer
Fatty acid metabolism (FAM) is an important factor in tumorigenesis and development. However, whether fatty acid metabolism (FAM)-related genes are associated with prostate cancer (PCa) prognosis is not known. Therefore, we established a novel prognostic model based on FAM-related genes to predict biochemical recurrence in PCa patients. First, PCa sequencing data were acquired from TCGA as the training cohort and GSE21032 as the validation cohort. Second, a prostate cancer prognostic model containing 10 FAM-related genes was constructed using univariate Cox and LASSO. Principal component analysis and t-distributed stochastic neighbour embedding analysis showed that the model was highly effective. Third, PCa patients were divided into high- and low-risk groups according to the model risk score. Survival analysis, ROC curve analysis, and independent prognostic analysis showed that the high-risk group had short recurrence-free survival (RFS), and the risk score was an independent diagnostic factor with diagnostic value in PCa patients. External validation using GSE21032 also showed that the prognostic model had high reliability. A nomogram based on a prognostic model was constructed for clinical use. Fourth, tumor immune correlation analyses, such as the ESTIMATE, CIBERSORT algorithm, and ssGSEA, showed that the high-risk group had higher immune cell infiltration, lower tumour purity, and worse RFS. Various immune checkpoints were expressed at higher levels in high-risk patients. In summary, this prognostic model is a promising prognostic biomarker for PCa that should improve the prognosis of PCa patients. These data provide new ideas for antitumour immunotherapy and have good potential value for the development of targeted drugs.
Wang et al. (2023) Comprehensive analysis of fatty acid metabolism-related gene signatures for predicting prognosis in patients with prostate cancer. PeerJ 11:e14646 https://doi.org/10.7717/peerj.14646
CMTM6 is highly expressed in lung adenocarcinoma and can be used as a biomarker of a poor diagnosis
Background CMTM6 which is chemokine-like factor (CKLF)-like Marvel transmembrane domain containing family member 6 is involved in the occurrence and progression of various tumors. However, the role of CMTM6 is still unclear in lung adenocarcinoma (LUAD). Methods Immunohistochemical, Western blotting and RT‒PCR methods were used to detect the expression of CMTM6 in LUAD. Cox regression and the Kaplan‒Meier method were performed to assess overall survival. Immunogenic features were evaluated according to immune cell infiltrations, immune checkpoints. The sensitivity to chemotherapy agents was estimated using the pRRophetic package. Results In LUAD, the expression of CMTM6 was obviously upregulated and was significantly associated with T stage (p = 0.008) and lymph node metastasis (p = 0.018). Multivariate Cox regression analysis demonstrated that CMTM6 was a specialty prognostic risk factor. Based on GSEA enrichment analysis, we found that high expression of CMTM6 is associated with multiple immune signaling pathways. The group with high CMTM6 expression showed a positive association with various types of tumor-infiltrating cells. Moreover, a total of 36 chemotherapeutic drugs were significantly correlated with the expression of CMTM6. Among them, two chemotherapeutic drugs had better therapeutic effects in the high CMTM6 expression group, while 34 chemotherapeutic drugs had therapeutic effects in the low CMTM6 expression group. Conclusion This study confirmed that CMTM6 is highly expressed in LUAD and is a new independent poor prognostic factor. In addition, the high expression of CMTM6 is closely related to the tumor microenvironment and immunotherapy, providing new ideas for the treatment of posterior LUAD.
Jia et al. (2023) CMTM6 is highly expressed in lung adenocarcinoma and can be used as a biomarker of a poor diagnosis. PeerJ 11:e14668 https://doi.org/10.7717/peerj.14668
The complex role of transcription factor GAGA in germline death during Drosophila spermatogenesis: transcriptomic and bioinformatic analyses
The GAGA protein (also known as GAF) is a transcription factor encoded by the Trl gene in D. melanogaster. GAGA is involved in the regulation of transcription of many genes at all stages of fly development and life. Recently, we investigated the participation of GAGA in spermatogenesis and discovered that Trl mutants experience massive degradation of germline cells in the testes. Trl underexpression induces autophagic death of spermatocytes, thereby leading to reduced testis size. Here, we aimed to determine the role of the transcription factor GAGA in the regulation of ectopic germline cell death. We investigated how Trl underexpression affects gene expression in the testes. We identified 15,993 genes in three biological replicates of our RNA-seq analysis and compared transcript levels between hypomorphic TrlR85/Trl362 and Oregon testes. A total of 2,437 differentially expressed genes were found, including 1,686 upregulated and 751 downregulated genes. At the transcriptional level, we detected the development of cellular stress in the Trl-mutant testes: downregulation of the genes normally expressed in the testes (indicating slowed or abrogated spermatocyte differentiation) and increased expression of metabolic and proteolysis-related genes, including stress response long noncoding RNAs. Nonetheless, in the Flybase Gene Ontology lists of genes related to cell death, autophagy, or stress, there was no enrichment with GAGA-binding sites. Furthermore, we did not identify any specific GAGA-dependent cell death pathway that could regulate spermatocyte death. Thus, our data suggest that GAGA deficiency in male germline cells leads to an imbalance of metabolic processes, impaired mitochondrial function, and cell death due to cellular stress.
Fedorova et al. (2023) The complex role of transcription factor GAGA in germline death during Drosophila spermatogenesis: transcriptomic and bioinformatic analyses. PeerJ 11:e14063 https://doi.org/10.7717/peerj.14063
Substantial changes in Gaseous pollutants and health effects during COVID-19 in Delhi, India
Background Coronavirus disease has affected the entire population worldwide in terms of physical and environmental consequences. Therefore, the current study demonstrates the changes in the concentration of gaseous pollutants and their health effects during the COVID-19 pandemic in Delhi, the national capital city of India. Methodology In the present study, secondary data on gaseous pollutants such as nitrogen dioxide (NO2), carbon monoxide (CO), sulfur dioxide (SO2), ammonia (NH3), and ozone (O3) were collected from the Central Pollution Control Board (CPCB) on a daily basis. Data were collected from January 1, 2020, to September 30, 2020, to determine the relative changes (%) in gaseous pollutants for pre-lockdown, lockdown, and unlockdown stages of COVID-19. Results The current findings for gaseous pollutants reveal that concentration declined in the range of 51%–83% (NO), 40%–69% (NOx), 31%–60% (NO2), and 25%–40% (NH3) during the lockdown compared to pre-lockdown period, respectively. The drastic decrease in gaseous pollutants was observed due to restricted measures during lockdown periods. The level of ozone was observed to be higher during the lockdown periods as compared to the pre-lockdown period. These gaseous pollutants are linked between the health risk assessment and hazard identification for non-carcinogenic. However, in infants (0–1 yr), Health Quotient (HQ) for daily and annual groups was found to be higher than the rest of the exposed group (toddlers, children, and adults) in all the periods. Conclusion The air quality values for pre-lockdown were calculated to be “poor category to “very poor” category in all zones of Delhi, whereas, during the lockdown period, the air quality levels for all zones were calculated as “satisfactory,” except for Northeast Delhi, which displayed the “moderate” category. The computed HQ for daily chronic exposure for each pollutant across the child and adult groups was more than 1 (HQ > 1), which indicated a high probability to induce adverse health outcomes.
Environmental Contamination and Remediation
Singh et al. (2023) Substantial changes in Gaseous pollutants and health effects during COVID-19 in Delhi, India. PeerJ 11:e14489 https://doi.org/10.7717/peerj.14489
Clasnip: a web-based intraspecies classifier and multi-locus sequence typing for pathogenic microorganisms using fragmented sequences
Bioinformatic approaches for the identification of microorganisms have evolved rapidly, but existing methods are time-consuming, complicated or expensive for massive screening of pathogens and their non-pathogenic relatives. Also, bioinformatic classifiers usually lack automatically generated performance statistics for specific databases. To address this problem, we developed Clasnip (www.clasnip.com), an easy-to-use web-based platform for the classification and similarity evaluation of closely related microorganisms at interspecies and intraspecies levels. Clasnip mainly consists of two modules: database building and sample classification. In database building, labeled nucleotide sequences are mapped to a reference sequence, and then single nucleotide polymorphisms (SNPs) statistics are generated. A probability model of SNPs and classification groups is built using Hidden Markov Models and solved using the maximum likelihood method. Database performance is estimated using three replicates of two-fold cross-validation. Sensitivity (recall), specificity (selectivity), precision, accuracy and other metrics are computed for all samples, training sets, and test sets. In sample classification, Clasnip accepts inputs of genes, short fragments, contigs and even whole genomes. It can report classification probability and a multi-locus sequence typing table for SNPs. The classification performance was tested using short sequences of 16S, 16–23S and 50S rRNA regions for 12 haplotypes of Candidatus Liberibacter solanacearum (CLso), a regulated plant pathogen associated with severe disease in economically important Apiaceous and Solanaceous crops. The program was able to classify CLso samples with even only 1–2 SNPs available, and achieved 97.2%, 98.8% and 100.0% accuracy based on 16S, 16–23S, and 50S rRNA sequences, respectively. In comparison with all existing 12 haplotypes, we proposed that to be classified as a new haplotype, given samples have at least 2 SNPs in the combined region of 16S rRNA (OA2/Lsc2) and 16–23S IGS (Lp Frag 4–1611F/Lp Frag 4–480R) regions, and 2 SNPs in the 50S rplJ/rplL (CL514F/CL514R) regions. Besides, we have included the databases for differentiating Dickeya spp., Pectobacterium spp. and Clavibacter spp. In addition to bacteria, we also tested Clasnip performance on potato virus Y (PVY). 251 PVY genomes were 100% correctly classified into seven groups (PVYC, PVYN, PVYO, PVYNTN, PVYN:O, Poha, and Chile3). In conclusion, Clasnip is a statistically sound and user-friendly bioinformatic application for microorganism classification at the intraspecies level. Clasnip service is freely available at www.clasnip.com.
Chuan et al. (2023) Clasnip: a web-based intraspecies classifier and multi-locus sequence typing for pathogenic microorganisms using fragmented sequences. PeerJ 11:e14490 https://doi.org/10.7717/peerj.14490
How to measure ego-resiliency in the face of various life-changing crises: Measurement invariance, convergent and discriminant validity and reliability of the Polish version of the Revised Ego-Resiliency Scale (ER89-R12)
This study examines the generalizability of the latent structure of the Polish version of the Ego-Resiliency Scale (ER89-R12), a brief self-report scale that measures ego-resiliency. We investigated the measurement invariance, validity, and reliability of ER89-R12 among three groups of individuals who were facing various major, long-term, life-changing crises (N = 512): parents of children with Down’s syndrome, women with breast cancer, and individuals after divorce. The analysis of the measurement invariance confirmed the two-factor structure of the questionnaire and the high reliability of this measure in those studied groups. A multigroup confirmatory factor analysis provided evidence of configural, metric, scalar, and residual invariance across the three groups. Moreover, the correlation patterns were similar across the groups. Ego-resiliency was strongly and consistently positively correlated with mental health: psychological well-being, perceived social support, self-esteem, and post-traumatic growth, and negatively correlated with perceived stress. The presented results indicate the potential usefulness of the ER89-R12 tool in studies on people experiencing various crises in their lives.
Kołodziej-Zaleska et al. (2023) How to measure ego-resiliency in the face of various life-changing crises: Measurement invariance, convergent and discriminant validity and reliability of the Polish version of the Revised Ego-Resiliency Scale (ER89-R12). PeerJ 11:e14499 https://doi.org/10.7717/peerj.14499