PeerJ最新文献

Background: Chronic lymphocytic leukemia (CLL) is a common adult leukemia characterized by the accumulation of neoplastic mature B cells in blood, bone marrow, lymph nodes, and spleen. The disease biology remains unresolved in many aspects, including the processes underlying the disease progression and relapses. However, studying CLL in vitro poses a considerable challenge due to its complexity and dependency on the microenvironment. Several approaches are utilized to overcome this issue, such as co-culture of CLL cells with other cell types, supplementing culture media with growth factors, or setting up a three-dimensional (3D) culture. Previous studies have shown that 3D cultures, compared to conventional ones, can lead to enhanced cell survival and altered gene expression. 3D cultures can also give valuable information while testing treatment response in vitro since they mimic the cell spatial organization more accurately than conventional culture.

Methods: In our study, we investigated the behavior of CLL cells in two types of material: (i) solid porous collagen scaffolds and (ii) gel composed of carboxymethyl cellulose and polyethylene glycol (CMC-PEG). We studied CLL cells' distribution, morphology, and viability in these materials by a transmitted-light and confocal microscopy. We also measured the metabolic activity of cultured cells. Additionally, the expression levels of MYC, VCAM1, MCL1, CXCR4, and CCL4 genes in CLL cells were studied by qPCR to observe whether our novel culture approaches lead to increased adhesion, lower apoptotic rates, or activation of cell signaling in relation to the enhanced contact with co-cultured cells.

Results: Both materials were biocompatible, translucent, and permeable, as assessed by metabolic assays, cell staining, and microscopy. While collagen scaffolds featured easy manipulation, washability, transferability, and biodegradability, CMC-PEG was advantageous for its easy preparation process and low variability in the number of accommodated cells. Both materials promoted cell-to-cell and cell-to-matrix interactions due to the scaffold structure and generation of cell aggregates. The metabolic activity of CLL cells cultured in CMC-PEG gel was similar to or higher than in conventional culture. Compared to the conventional culture, there was (i) a lower expression of VCAM1 in both materials, (ii) a higher expression of CCL4 in collagen scaffolds, and (iii) a lower expression of CXCR4 and MCL1 (transcript variant 2) in collagen scaffolds, while it was higher in a CMC-PEG gel. Hence, culture in the material can suppress the expression of a pro-apoptotic gene (MCL1 in collagen scaffolds) or replicate certain gene expression patterns attributed to CLL cells in lymphoid organs (low CXCR4, high CCL4 in collagen scaffolds) or blood (high CXCR4 in CMC-PEG).

Background: Cervical cancer remains a significant global health concern, ranking as the fourth most prevalent cancer among women worldwide. Human papillomaviruses (HPV) transcribe many genes that might be responsible for cervical cancer development. This study aims to investigate the correlation between the expression of HPV16 early genes and the mRNA expression of human FOXO3a, a tumor suppressor gene, in association with various stages of cervical precancerous lesions.

Methods: Eighty-five positive HPV16 DNA cervical swab samples were recruited and categorized based on cytology stages, i.e., negative for intraepithelial lesion or malignancy (NILM), atypical squamous cells of undetermined significance (ASC-US), low-grade squamous intraepithelial lesion (LSIL), atypical squamous cell cannot exclude HSIL (ASC-H), high-grade squamous intraepithelial lesion (HSIL). RT-qPCR was performed to amplify HPV16E1, E4, E6, E6*I, E7, and human FOXO3a mRNA expression in all samples. The relative expression of those genes was calculated using GAPDH as a control. Detection of FOXO3a mRNA expression in the cervical cancer cell line by RT-qPCR and meta-analysis of FOXO3a expression using the RNA-Seq dataset by GEPIA2 were analyzed to support the conclusions.

Results: Among the cervical samples, HPV16E1 and E7 were significantly increased expression correlating to disease severity. HPV16E4 mRNA expression was 100% detected in all LSIL samples, with a significant increase observed from normal to LSIL stages. Conversely, FOXO3a mRNA expression decreased with disease severity, and the lowest expression was observed in HSIL/squamous cell carcinoma (SCC) samples. In addition, similar results of FOXO3a downregulation were also found in the cervical cancer cell line and RNA-Seq dataset of cervical cancer samples.

Conclusion: HPV16 early mRNA levels, including E1 and E7, increase during cancer progression, and downregulation of FOXO3a mRNA is a characteristic of cervical cancer cells and HSIL/SCC. Additionally, HPV16E4 mRNA expression was consistently detected in all LSIL samples, suggesting the presence of active viral replication. These findings might lead to further investigation into the interplay between HPV gene expression and host cell factors for targeted therapeutic strategies in cervical cancer management.

Background: Forage production in tropical soils is primarily limited by nutrient deficiencies, especially nitrogen (N) and phosphorus (P). The use of phosphate rock by plants is limited by its low and slow P availability and microbial phosphate solubilization is the main mechanism for P bioavailability in the soil-root system. The objectives of this study were (i) select a nitrogen-fixing bacteria which could be used as a co-inoculant with the Penicillium rugulosum IR94MF1 phosphate-solubilizing fungus and (ii) evaluate under field conditions the effect of inoculation combined with phosphate rock (PR) application on yield and nutrient absorption of a Urochloa decumbens pasture which was previously established in a low-fertility, acidic soil.

Methods: Various laboratory and greenhouse tests allowed for the selection of Enterobacter cloacae C17 as the co-inoculant bacteria with the IR94MF1 fungus. Later, under field conditions, a factorial, completely randomized block design was used to evaluate the inoculation with the IR94MF1 fungus, the IR94MF1+C17 co-inoculation, and a non-inoculated control. Two levels of fertilization with PR treatment (0 kg/ha and 200 kg/ha P₂O₅) were applied to each.

Results: During five consecutive harvests it was observed that the addition of biofertilizers significantly increased (p < 0.05) the herbage mass and N and P assimilation compared to the non-inoculated control. However, no statistically significant differences were observed for the PR application as P source.

Conclusion: P. rugulosum IR94MF1 is capable of solubilizing and accumulating P from the phosphate rock, making it available for plants growing in acid soils with low N content. These inoculants represent a good option as biofertilizers for tropical grasses already established in acidic soils with low N content.

Biochar, a carbon-rich material that has attracted considerable interest in interdisciplinary research, is produced through a process known as pyrolysis, which involves the thermal decomposition of organic material in the absence of oxygen. Bamboo biochar is a specific type of biochar, manufactured from bamboo straw through carbonisation at 800 °C and subsequent filtration through a 100-mesh sieve. There is currently a lack of research into the potential benefits of bamboo biochar in improving soil quality in tea gardens. The aim of this study was to investigate the effect of bamboo biochar on the physicochemical properties, enzymatic activity, and microbial community structure of tea garden soils. The results demonstrate that the integration of bamboo biochar into the soil significantly enhanced the soil pH, total nitrogen, available nitrogen, total phosphorus, available phosphorus, available potassium, and slowly available potassium by 15.3%, 52.0%, 91.5%, 91%, 48.4%, 94.2%, and 107.7%, respectively. In addition, soil acid phosphatase activity decreased significantly by 52.5%. In contrast, the activities of sucrase, catalase, and β-glucosidase increased substantially by 54.0%, 68.7%, and 68.4%, respectively, when organic fertilizer and bamboo biochar were applied concurrently. Additionally, the Shannon, Simpson, and Pielou diversity indices of the microbial communities were significantly enhanced. Following the incorporation of bamboo biochar in the soil samples, the relative abundance of Proteobacteria increased significantly, whereas that of Acidobacteria decreased. Various concentrations of bamboo biochar markedly influenced microbial markers in the soil. The results of this study suggest that the application of bamboo biochar to soil may modestly improve its physicochemical properties, enzyme activity, and microbial community structure. These findings provide a foundation for future investigations on soil ecological restoration.

Many of the complex behaviours of humans involve the production of nonadjacent dependencies between sequence elements, which in part can be generated through the hierarchical organization of sequences. To understand how these structural properties of human behaviours evolved, we can gain valuable insight from studying the sequential behaviours of nonhuman animals. Among the behaviours of nonhuman apes, tool use has been hypothesised to be a domain of behaviour which likely involves hierarchical organization, and may therefore possess nonadjacent dependencies between sequential actions. However thus far, evidence supporting hierarchical organization of great-ape tool use comes from methodologies which have been criticised in their objectivity. Additionally, the extent to which nonadjacent dependencies appear in primate action sequences during tool use has not been formally investigated. We used estimations of mutual information (MI)-a measure of dependency strength between sequence elements-to evaluate both the extent to which wild chimpanzees produce nonadjacent dependencies during a naturalistic tool-use task (nut cracking), as well as how sequences of actions are likely organized during tool use. Half of adult chimpanzees produced nonadjacent dependencies at significantly greater sequential distances than comparable, nonhierarchical Markov models once repeated actions had been accounted for. Additionally, for the majority of chimpanzees, MI decay with increasing sequential distance included a power-law relationship, which is a key indicator that the action sequences produced by chimpanzees likely entail some degree of hierarchical organization. Our analysis offered the greatest support for a system of organization where short subroutines of actions (2-8 actions long) are hierarchically arranged into longer sequences-a finding which is consistent with previous qualitative descriptions of ape tool-use behaviours. Interindividual variability was detected within our analysis in both the maximum distance dependencies were detected, and the most likely structuring mechanism for sequential action organization. We discuss these results in light of possible interindividual variation in the systems of action organization used by chimpanzees during tool use, in addition to methodological considerations for applications of MI estimations to sequential behaviours. Moreover, we discuss our main findings alongside hypotheses for the coevolution of complex syntax in language and tool-action across hominin evolutionary history.

CYP3A, a key member of the cytochrome P450 (CYP450) superfamily, is integral to drug metabolism, processing a substantial portion of medications. Their role in drug metabolism is particularly prominent, as CYP3A4 and CYP3A5 metabolize approximately 30-50% of known drugs. The genetic polymorphism of CYP3A4/5 is significant inter-individual variability in enzymatic activity, which can result in different pharmacokinetic profiles in response to the same drug among individuals. These polymorphisms can lead to either increased drug toxicity or reduced therapeutic effects, requiring dosage adjustments based on genetic profiles. Consequently, the study of the enzymatic activity of CYP3A4/5 gene variants is of great importance for the formulation of personalized treatment regimens. This article first reviews the role of CYP3A4/5 in drug metabolism in the human body, including inhibitors and inducers of CYP3A4/5 and drug-drug interactions. In terms of genetic polymorphism, it discusses the detection methods, enzymatic kinetic characteristics, and clinical guidelines for CYP3A5. Finally, the article summarizes the importance of CYP3A4/5 in clinical applications, including personalized therapy, management of drug-drug interactions, and adjustment of drug doses. This review contributes to the understanding of the functions and genetic characteristics of CYP3A4/5, allowing for more effective clinical outcomes through optimized drug therapy.

In phylogenomics, regions of low alignment reliability and high noise are typically trimmed from multiple sequence alignments before they are used in phylogenetic inference. I introduce a new trimming tool, PhyIN, which deletes regions in which a large proportion of sites (characters) have conflicting phylogenetic signal. It does not require inference of a phylogenetic tree, as it finds neighbouring characters that cannot agree on any possible tree. In phylogenomic data of ultraconserved elements (UCE), PhyIN effectively finds the boundaries between chaotic (conflicted) and orderly regions of alignments with data for only a single locus. Its ability to work on individual loci allows it to preserve discord between gene trees and species trees.

Management of wildlife populations is most effective with a thorough understanding of the interplay among vital rates, population growth, and density-dependent feedback; however, measuring all relevant vital rates and assessing density-dependence can prove challenging. Integrated population models have been proposed as a method to address these issues, as they allow for direct modeling of density-dependent pathways and inference on parameters without direct data. We developed integrated population models from a 25-year demography dataset of Northern Bobwhites (Colinus virginianus) from southern Georgia, USA, to assess the demographic drivers of population growth rates and to estimate the strength of multiple density-dependent processes simultaneously. Furthermore, we utilize a novel approach combining breeding productivity and post-breeding abundance and age-and-sex ratio data to infer juvenile survival. Population abundance was relatively stable for the first 14 years of the study but began growing after 2012, showing that bobwhite populations may be stable or exhibit positive population growth in areas of intensive management. Variation in breeding and non-breeding survival drove changes in population growth in a few years; however, population growth rates were most affected by productivity across the entire study duration. A similar pattern was observed for density-dependence, with relatively stronger negative effects of density on productivity than on survival. Our novel modeling approach required an informative prior but was successful at updating the prior distribution for juvenile survival. Our results show that integrated population models provide an attractive and flexible method for directly modeling all relevant density-dependent processes and for combining breeding and post-breeding data to estimate juvenile survival in the absence of direct data.

Background: Acute myocardial infarction (AMI) is one of the most serious cardiovascular diseases. Apoptosis is a type of programmed cell death that causes DNA degradation and chromatin condensation. The role of apoptosis in AMI progression remains unclear.

Methods: Three AMI-related microarray datasets (GSE48060, GSE66360 and GSE97320) were obtained from the Gene Expression Omnibus database and combined for further analysis. Differential expression analysis and enrichment analysis were performed on the combined dataset to identify differentially expressed genes (DEGs). Apoptosis-related genes (ARGs) were screened through the intersection of genes associated with apoptosis in previous studies and DEGs. The expression pattern of ARGs was studied on the basis of their raw expression data. Three machine learning algorithms, Least Absolute Shrinkage and Selection Operator (LASSO), support vector machine-recursive feature elimination (SVM-RFE), and Random Forest (RF) were utilized to screen crucial genes in these ARGs. Immune infiltration was estimated by single sample gene set enrichment analysis (ssGSEA). Corresponding online databases were used to predict miRNAs, transcription factors (TFs) and therapeutic agents of crucial genes. A nomogram clinical prediction model of the crucial genes was constructed and evaluated. The Mendelian randomization analysis was employed to investigate whether there is a causal relationship between apoptosis and AMI. Finally, an AMI mouse model was established, and apoptosis in the hearts of AMI mice was assessed via TUNEL staining. qRT-PCR was employed to validate these crucial genes in the hearts of AMI mice. The external dataset GSE59867 was used for further validating the crucial genes.

Results: Fifteen ARGs (GADD45A, DDIT3, FEZ1, PMAIP1, IER3, IFNGR1, CDKN1A, GNA15, IL1B, EREG, BCL10, JUN, EGR3, GADD45B, and CD14) were identified. Six crucial genes (CDKN1A, BCL10, PMAIP1, IL1B, GNA15, and CD14) were screened from ARGs by machine learning. A total of 102 miRNAs, 13 TFs and 23 therapeutic drugs were predicted targeting these crucial genes. The clinical prediction model of the crucial genes has shown good predictive capability. The Mendelian randomization analysis demonstrated that apoptosis is a risk factor for AMI. Lastly, the expression of CDKN1A, CD14 and IL1B was verified in the AMI mouse model and external dataset.

Conclusions: In this study, ARGs were screened by machine learning algorithms, and verified by qRT-PCR in the AMI mouse model. Finally, we demonstrated that CDKN1A, CD14 and IL1B were the crucial genes involved in apoptosis in AMI. These genes may provide new target for the recognition and intervention of apoptosis in AMI.

Processing large collections of earth observation (EO) time-series, often petabyte-sized, such as NASA's Landsat and ESA's Sentinel missions, can be computationally prohibitive and costly. Despite their name, even the Analysis Ready Data (ARD) versions of such collections can rarely be used as direct input for modeling because of cloud presence and/or prohibitive storage size. Existing solutions for readily using these data are not openly available, are poor in performance, or lack flexibility. Addressing this issue, we developed TSIRF (Time-Series Iteration-free Reconstruction Framework), a computational framework that can be used to apply diverse time-series processing tasks, such as temporal aggregation and time-series reconstruction by simply adjusting the convolution kernel. As the first large-scale application, TSIRF was employed to process the entire Global Land Analysis and Discovery (GLAD) ARD Landsat archive, producing a cloud-free bi-monthly aggregated product. This process, covering seven Landsat bands globally from 1997 to 2022, with more than two trillion pixels and for each one a time-series of 156 samples in the aggregated product, required approximately 28 hours of computation using 1248 Intel^® Xeon^® Gold 6248R CPUs. The quality of the result was assessed using a benchmark dataset derived from the aggregated product and comparing different imputation strategies. The resulting reconstructed images can be used as input for machine learning models or to map biophysical indices. To further limit the storage size the produced data was saved as 8-bit Cloud-Optimized GeoTIFFs (COG). With the hosting of about 20 TB per band/index for an entire 30 m resolution bi-monthly historical time-series distributed as open data, the product enables seamless, fast, and affordable access to the Landsat archive for environmental monitoring and analysis applications.