In-depth study of pyroptosis-related genes and immune infiltration in colon cancer
Background Pyroptosis is a form of regulated necrosis that occurs in many cell and tissue types and plays a critical role in tumor progression. The diagnostic value of pyroptosis-related genes (PRGs) in colon cancer has been widely investigated. In the present study, we explored the relationship between PRG expression and colon cancer. Methods We retrieved genomic and clinical data pertaining to The Cancer Genome Atlas-Colon Adenocarcinoma from the UCSC Xena database, along with the corresponding genome annotation information from the GENCODE data portal. Utilising these data and a list of 33 pyrogenic genes, we performed principal component analysis and unsupervised clustering analysis to assess the pyroptosis subtypes. We analysed the differential expression between these subtypes to obtain PRGs, ultimately selecting 10 PRGs. We conducted Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, gene set variation analysis, protein–protein interaction, and immune infiltration analyses of these PRGs. We validated the expression of TNNC1 via immunohistochemistry (IHC) and real-time quantitative PCR. Results After rigorous screening, excluding patients with incomplete survival data and unmatched transcriptomes, we refined our study cohort to 431 patients. We performed differential mRNA analysis and identified 445 PRGs, 10 of which were selected as hub genes. These genes were associated with various immune cell types. Specifically, TNNC1 expression was positively associated with immature dendritic cells and NK CD56+ cells. IHC staining indicated higher TNNC1 expression levels in tumor samples. Notably, TNNC1 expression levels were high in all the colon cancer cell lines, particularly in SW480 cells. Conclusion In this study, we explored the characteristics of PRGs in colon cancer and identified novel biological targets for early individualised treatment and accurate diagnosis of colon cancer, thus contributing to the advancement of clinical oncology.
Shang et al. (2024) In-depth study of pyroptosis-related genes and immune infiltration in colon cancer. PeerJ 12:e18374 https://doi.org/10.7717/peerj.18374
Genomic evaluation of the probiotic and pathogenic features of Enterococcus faecalis from human breast milk and comparison with the isolates from animal milk and clinical specimens
Enterococcus faecalis is considered a probiotic, commensal lactic acid bacterium in human breast milk (HBM), but there are circulating antibiotic resistant and virulence determinants that could pose a risk in some strains. The study aimed to conduct genomic analysis of E. faecalis isolates recovered from HBM and animal milk and to evaluate their probiotic and pathogenic features through comparative genomics with isolates from clinical specimens (e.g., urine, wound, and blood). Genomic analysis of 61 isolates was performed, including E. faecalis isolates recovered from HBM in Saudi Arabia. Genome sequencing was conducted using the MiSeq system. The fewest antibiotic resistance genes (lsaA, tetM, ermB) were identified in isolates from HBM and animal milk compared to clinical isolates. Several known and unknown mutations in the gyrA and parC genes were observed in clinical isolates. However, 11 virulence genes were commonly found in more than 95% of isolates, and 13 virulence genes were consistently present in the HBM isolates. Phylogenetically, the HBM isolates from China clustered with the probiotic reference strain Symbioflor 1, but all isolates from HBM and animal milk clustered separately from the clinical reference strain V583. Subsystem functions 188 of 263 were common in all analyzed genome assemblies. Regardless of the source of isolation, genes associated with carbohydrate metabolism, fatty acid, and vitamin biosynthesis were commonly found in E. faecalis isolates. In conclusion, comparative genomic analysis can help distinguish the probiotic or pathogenic potential of E. faecalis based on genomic features.
Badr et al. (2024) Genomic evaluation of the probiotic and pathogenic features of Enterococcus faecalis from human breast milk and comparison with the isolates from animal milk and clinical specimens. PeerJ 12:e18392 https://doi.org/10.7717/peerj.18392
Forkhead box D subfamily genes in colorectal cancer: potential biomarkers and therapeutic targets
Background The forkhead box (FOX) family members regulate gene transcription and expression. FOX family members regulate various biological processes, such as cell proliferation and tumorigenesis. FOXD, a FOX protein subfamily, is associated with poor prognosis for various cancers. However, the potential clinical value of FOXD subfamily members in colorectal cancer (CRC) has not yet been elucidated. Therefore, in this study, we aimed to determine the role of the FOXD subfamily members in CRC development. Methods Using HTSeq-count data, clinical data, and single-nucleotide polymorphisms (obtained from The Cancer Genome Atlas Project), and bioinformatics analyses (using DESEQ2 software), we identified differentially expressed genes (DEGs) in CRC. Next, each DEG expression was validated in vitro using reverse transcription-quantitative polymerase chain reaction, western blotting, and immunohistochemistry (IHC). Results Among the FOXD subfamily members, the area under the receiver operating characteristic curve of FOXD3 was 0.949, indicating that FOXD3 has a high overall diagnostic accuracy for CRC. Gene Set Enrichment Analysis revealed that FOXD-DEGs were mainly related to pathways such as cytokine, cytokine, and extracellular matrix receptor interactions. Kaplan–Meier curves and nomograms showed that FOXD1, FOXD3, and FOXD4 were prognostically significant. In conclusion, FOXD subfamily members (especially FOXD3) could serve as diagnostic and prognostic biomarkers for CRC and an immunotherapy target in patients with CRC.
Chen et al. (2024) Forkhead box D subfamily genes in colorectal cancer: potential biomarkers and therapeutic targets. PeerJ 12:e18406 https://doi.org/10.7717/peerj.18406
Using a natural capital risk register to support the funding of seagrass habitat enhancement in Plymouth Sound
Seagrass is an important marine habitat that provides benefits to society in the form of ecosystem services. Services include the provision of food via fisheries, the regulation of water quality and the ability to sequester and store carbon. In the UK, seagrass beds are in decline, increasing the risk of ecosystem service loss. Current efforts to protect, restore and create seagrass habitat, beyond spatial management measures, rely on grant funding and donations. Emerging carbon, biodiversity and wider ecosystem service markets offering potential revenue sources could facilitate the enhancement of seagrass habitat at scale. Participation in ecosystem service markets, requires that projects deliver on the ecosystem service benefits defined. As the benefits will have been paid for, there are risks associated with not delivering on ecosystem service benefits. It is important that the risk is clearly defined. In this study we further the marine natural capital and risk register approach and apply the method to a case study area to support the development of sustainable funding options for seagrass habitat enhancement in Plymouth Sound, UK. Habitat Suitability modelling is also used to map potential areas for seagrass habitat enhancement. We find that, in the Plymouth Sound area, the risk of loss of ecosystem services for subtidal seagrass habitats is, at present, high. This is primarily linked to the declining extent and condition of subtidal seagrass assets. Under current governance, all of Plymouth Sound’s subtidal seagrass are within a Marine Protected Area, though this conservation designation does not guarantee that the seagrass bed is protected from damaging activity. Under current environmental conditions there is opportunity for widespread seagrass restoration and creation. Risk to seagrass beds and any future private funding could be reduced by governance actions that enable effective direct protection of the seagrass assets and mitigate harmful pressures (e.g., reduction of water pollution). Emerging financial ‘products’ from seagrass ecosystem services that can support restoration and creation, require a high degree of integrity. The natural capital asset and risk register framework can provide information to underpin product development. With the development of revenue streams from ecosystem services there is a need for more intentional governance and site-based monitoring of these habitats as natural capital assets. Further research is needed to define any social or economic outcomes. Synthesis and Application By assessing the risk to the status of seagrass assets through this approach, it is possible to determine the complementary governance actions needed to underpin investment in seagrass habitat enhancement. The methods are transferable to other locations where data exists to define the asset status. These specific findings are relevant nationally where similar vectors of risk (pressures) are identified.
Hooper et al. (2024) Using a natural capital risk register to support the funding of seagrass habitat enhancement in Plymouth Sound. PeerJ 12:e17969 https://doi.org/10.7717/peerj.17969
An interpretable deep learning model for detecting BRCA pathogenic variants of breast cancer from hematoxylin and eosin-stained pathological images
Background Determining the status of breast cancer susceptibility genes (BRCA) is crucial for guiding breast cancer treatment. Nevertheless, the need for BRCA genetic testing among breast cancer patients remains unmet due to high costs and limited resources. This study aimed to develop a Bi-directional Self-Attention Multiple Instance Learning (BiAMIL) algorithm to detect BRCA status from hematoxylin and eosin (H&E) pathological images. Methods A total of 319 histopathological slides from 254 breast cancer patients were included, comprising two dependent cohorts. Following image pre-processing, 633,484 tumor tiles from the training dataset were employed to train the self-developed deep-learning model. The performance of the network was evaluated in the internal and external test sets. Results BiAMIL achieved AUC values of 0.819 (95% CI [0.673–0.965]) in the internal test set, and 0.817 (95% CI [0.712–0.923]) in the external test set. To explore the relationship between BRCA status and interpretable morphological features in pathological images, we utilized Class Activation Mapping (CAM) technique and cluster analysis to investigate the connections between BRCA gene mutation status and tissue and cell features. Significantly, we observed that tumor-infiltrating lymphocytes and the morphological characteristics of tumor cells appeared to be potential features associated with BRCA status. Conclusions An interpretable deep neural network model based on the attention mechanism was developed to predict the BRCA status in breast cancer. Keywords: Breast cancer, BRCA, deep learning, self-attention, interpretability.
Li et al. (2024) An interpretable deep learning model for detecting BRCA pathogenic variants of breast cancer from hematoxylin and eosin-stained pathological images. PeerJ 12:e18098 https://doi.org/10.7717/peerj.18098
The impact of the filling technique with two sealers in bulk or associated with gutta-percha on the fatigue behavior and failure patterns of endodontically treated teeth
Background The present in vitro study aimed to evaluate the fatigue behavior of teeth filled with a calcium silicate-based sealer (Bio-C Sealer, BC) or an epoxy resin-based sealer (AH Plus, AH), in bulk or associated with gutta-percha as main core material. Methods Seventy-two sound human maxillary anterior teeth were initially selected. Sixty of them, were randomly chosen, and had their root canals prepared using nickel-titanium reciprocating instruments, being again randomly assigned to five experimental groups (n = 12): C+ (control + prepared but not filled); BC-B (BC in bulk); BC-GP (BC+ gutta-percha); AP-B (AH in bulk); AP-GP (AH+ gutta-percha). An additional negative control group (C−) was considered (n = 12), consisting only on sound teeth, without preparation and filling. The specimens were submitted to a survival analysis after the cyclic fatigue test. Results Sound teeth (C−) presented the best fatigue performance (P < 0.05), being similar only to the AP-GP group (P > 0.05). Despite that, all experimental groups showed similar fatigue behavior (P > 0.05) to C+ (BC-B = BC-GP = AP-B = AP-GP = C+). Based on that, it can be seen that the use of gutta-percha, as a main core material, associated with the AH Plus sealer, reestablished the mechanical fatigue performance of endodontically treated teeth comparable to sound teeth, still consisting on the most promising approach to rehabilitate such scenario. Teeth filled in bulk, had discreetly higher risk of premature failures and inferior fatigue performance.
Lena et al. (2024) The impact of the filling technique with two sealers in bulk or associated with gutta-percha on the fatigue behavior and failure patterns of endodontically treated teeth. PeerJ 12:e18221 https://doi.org/10.7717/peerj.18221
Seed priming enhances seed germination and plant growth in four neglected cultivars of Capsicum annuum L.
Priming is basically a water-based technique inducing controlled seed rehydration to trigger the metabolic processes normally activated during the early phase of germination. It is regarded as an ecofriendly approach alternative to fertilizers in traditional agriculture, but also a method to synchronize off-field crops and resume stored seeds, improving vigor, and allowing for a rapid, uniform seedling emergence. In this work we tested several methods of seed priming (i.e., hydro-priming, halopriming by KNO3, and acid priming with HCl) in four ancient and neglected cultivars of Capsicum annuum L., a crop species belonging to Solanaceae family cultivated worldwide. We followed germination performance, seedling growth and selected morphological traits, antioxidant production in the leaves, and protein content of the seeds. Apart from acid priming, which inhibited root emergence, both hydropriming and halopriming decreased the mean germination time in all cultivars. The best treatments were KNO3 6% for 96 h > KNO3 4% for 48 h > hydropriming for 24 h. In particular, KNO3 6% for 96 h in all four cultivars significantly increased plant growth, simple vigor index, development germination index, leaf antioxidant concentration and protein content in the seeds, in comparison to control and other priming treatments, indicating the prompt activation of pre-germinative processes.
Granata et al. (2024) Seed priming enhances seed germination and plant growth in four neglected cultivars of Capsicum annuum L.. PeerJ 12:e18293 https://doi.org/10.7717/peerj.18293
Genome-wide identification and expression analysis of the OSC gene family in Platycodon grandiflorus
Platycodon grandiflorus stands as one of the most extensively utilized traditional Chinese medicinal herbs, with triterpenoids and their derivatives serving as its primary medicinal components. Oxido squalene cyclase (OSC), serving as a crucial enzyme in the triterpenoid synthesis pathway, has the capability to enzymatically generate significant quantities of sterols and triterpenoid intermediates. While the OSC gene family has been identified in numerous species, bioinformatics research on this family remains scant. Presently, the specific members of this gene family in Platycodon grandiflorus have yet to be definitively determined. In this study, we successfully identified a total of 15 PgOSC genes within the genome of Platycodon grandiflorus by conducting homology comparisons. These genes were discovered to be unevenly distributed across the five chromosomes of the species, organized in the form of gene clusters. Subsequently, we conducted a thorough analysis of the OSC gene family’s evolutionary relationship by constructing a phylogenetic tree. Other characteristics of PgOSC family members, including gene structure, conserved motifs, protein three-dimensional structure, subcellular localization, and cis-acting elements were thoroughly characterized. Furthermore, We analyzed the expression of PgOSC gene in different tissues of Platycodon grandiflorus by qRT-PCR, and found that the expression of PgOSC genes in root was higher than that in stem and leaf. Upon comparing the effects of salt, heat, and drought treatments, we observed a significant induction of PgOSC gene expression in Platycodon grandiflorus specifically under salt stress conditions. In summary, this study comprehensively identified and analyzed the OSC gene family, aiming to provide basic biological information for exploring the members of PgOSC gene family.
Wang et al. (2024) Genome-wide identification and expression analysis of the OSC gene family in Platycodon grandiflorus. PeerJ 12:e18322 https://doi.org/10.7717/peerj.18322
Association of thyroid hormones with the severity of chronic kidney disease: a cross-sectional observational study at Tabuk, Saudi Arabia
Background The interplay between chronic kidney disease (CKD) and thyroid dysfunction is becoming more evident in the biomedical community. However, the intricacies of their relationship warrant deeper investigation to understand the clinical implications fully. Objective This study aims to systematically evaluate the correlation between thyroid hormone levels, including thyroid-stimulating hormone (TSH), triiodothyronine (T3), and thyroxine (T4), and markers of renal disease severity. These markers include serum creatinine, urea, and parathyroid hormone (PTH) levels in individuals diagnosed with CK). Methods We conducted a cross-sectional observational study involving a cohort of 86 participants with CKD recruited from the renal clinic at King Fahad Hospital in Tabuk. Biochemical parameters, encompassing plasma electrolytes and thyroid hormone concentrations, were quantitatively assessed. These measurements were performed with the aid of a Roche Cobas E411 analyzer. The Pearson correlation coefficient was employed to delineate the strength and direction of the associations between the thyroid function markers and renal disease indicators. Results The statistical analysis highlighted a generally weak correlation between the concentrations of thyroid hormones and the indicators of renal disease severity, with Pearson correlation coefficients between −0.319 and 0.815. Critically, no significant correlation was found between creatinine and thyroid hormones (TSH, T3, T4), nor was any substantial correlation between urea and thyroid hormones. Conversely, a robust positive correlation was noted between the levels of parathyroid hormone and serum creatinine (r = 0.718, p < 0.001). Conclusion The data suggests that thyroid hormone levels have a minimal correlation with the severity of renal disease markers. In contrast, the pronounced correlation between PTH and creatinine underscores the importance of considering PTH as a significant factor in managing and therapeutic intervention of CKD complications. These initial findings catalyze further research to thoroughly investigate the pathophysiological relationships and potential therapeutic targets concerning thyroid dysfunction in patients with renal impairment.
Awwaadh et al. (2024) Association of thyroid hormones with the severity of chronic kidney disease: a cross-sectional observational study at Tabuk, Saudi Arabia. PeerJ 12:e18338 https://doi.org/10.7717/peerj.18338
COADREADx: A comprehensive algorithmic dissection of colorectal cancer unravels salient biomarkers and actionable insights into its discrete progression
Background Colorectal cancer is a common condition with an uncommon burden of disease, heterogeneity in manifestation, and no definitive treatment in the advanced stages. Renewed efforts to unravel the genetic drivers of colorectal cancer progression are paramount. Early-stage detection contributes to the success of cancer therapy and increases the likelihood of a favorable prognosis. Here, we have executed a comprehensive computational workflow aimed at uncovering the discrete stagewise genomic drivers of colorectal cancer progression. Methods Using the TCGA COADREAD expression data and clinical metadata, we constructed stage-specific linear models as well as contrast models to identify stage-salient differentially expressed genes. Stage-salient differentially expressed genes with a significant monotone trend of expression across the stages were identified as progression-significant biomarkers. The stage-salient genes were benchmarked using normals-augmented dataset, and cross-referenced with existing knowledge. The candidate biomarkers were used to construct the feature space for learning an optimal model for the digital screening of early-stage colorectal cancers. The candidate biomarkers were also examined for constructing a prognostic model based on survival analysis. Results Among the biomarkers identified are: CRLF1, CALB2, STAC2, UCHL1, KCNG1 (stage-I salient), KLHL34, LPHN3, GREM2, ADCY5, PLAC2, DMRT3 (stage-II salient), PIGR, HABP2, SLC26A9 (stage-III salient), GABRD, DKK1, DLX3, CST6, HOTAIR (stage-IV salient), and CDH3, KRT80, AADACL2, OTOP2, FAM135B, HSP90AB1 (top linear model genes). In particular the study yielded 31 genes that are progression-significant such as ESM1, DKK1, SPDYC, IGFBP1, BIRC7, NKD1, CXCL13, VGLL1, PLAC1, SPERT, UPK2, and interestingly three members of the LY6G6 family. Significant monotonic linear model genes included HIGD1A, ACADS, PEX26, and SPIB. A feature space of just seven biomarkers, namely ESM1, DHRS7C, OTOP3, AADACL2, LPHN3, GABRD, and LPAR1, was sufficient to optimize a RandomForest model that achieved > 98% balanced accuracy (and performant recall) of cancer vs. normal on external validation. Design of an optimal multivariate model based on survival analysis yielded a prognostic panel of three stage-IV salient genes, namely HOTAIR, GABRD, and DKK1. Based on the above sparse signatures, we have developed COADREADx, a web-server for potentially assisting colorectal cancer screening and patient risk stratification. COADREADx provides uncertainty measures for its predictions and needs clinical validation. It has been deployed for experimental non-commercial use at: https://apalanialab.shinyapps.io/coadreadx/.
Palaniappan et al. (2024) COADREADx: A comprehensive algorithmic dissection of colorectal cancer unravels salient biomarkers and actionable insights into its discrete progression. PeerJ 12:e18347 https://doi.org/10.7717/peerj.18347