PhyIN: trimming alignments by phylogenetic incompatibilities among neighbouring sites
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.
Maddison (2024) PhyIN: trimming alignments by phylogenetic incompatibilities among neighbouring sites. PeerJ 12:e18504 https://doi.org/10.7717/peerj.18504
CYP3A4 and CYP3A5: the crucial roles in clinical drug metabolism and the significant implications of genetic polymorphisms
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.
Zhang et al. (2024) CYP3A4 and CYP3A5: the crucial roles in clinical drug metabolism and the significant implications of genetic polymorphisms. PeerJ 12:e18636 https://doi.org/10.7717/peerj.18636
Effects of bamboo biochar on soil physicochemical properties and microbial diversity in tea gardens
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.
Zhang et al. (2024) Effects of bamboo biochar on soil physicochemical properties and microbial diversity in tea gardens. PeerJ 12:e18642 https://doi.org/10.7717/peerj.18642
A computational framework for processing time-series of earth observation data based on discrete convolution: global-scale historical Landsat cloud-free aggregates at 30 m spatial resolution
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.
Spatial and Geographic Information Science
Consoli et al. (2024) A computational framework for processing time-series of earth observation data based on discrete convolution: global-scale historical Landsat cloud-free aggregates at 30 m spatial resolution. PeerJ 12:e18585 https://doi.org/10.7717/peerj.18585
Identification and validation of apoptosis-related genes in acute myocardial infarction based on integrated bioinformatics methods
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.
Zhu et al. (2024) Identification and validation of apoptosis-related genes in acute myocardial infarction based on integrated bioinformatics methods. PeerJ 12:e18591 https://doi.org/10.7717/peerj.18591
Use of integrated population models for assessing density-dependence and juvenile survival in Northern Bobwhites (Colinus virginianus)
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.
Lewis et al. (2024) Use of integrated population models for assessing density-dependence and juvenile survival in Northern Bobwhites (Colinus virginianus). PeerJ 12:e18625 https://doi.org/10.7717/peerj.18625
DNA shuffling to improve crude-water interfacial activity in biosurfactants with OmpA protein of Escherichia coli
Surfactants are molecules derived primarily from petroleum that can reduce the surface tension at interfaces. Their slow degradation is a characteristic that could cause environmental issues. This and other factors contribute to the allure of biosurfactants today. Progress has been made in this area of research, which aims to satisfy the need for effective surfactants that are not harmful to the environment. In previous studies, we demonstrated the surface tension activity of the Escherichia coli transmembrane protein OmpA. Here, we carried out DNA shuffling on ompA to improve its interfacial activity. We evaluated changes in interfacial tension when exposing mutants to a water-oil interface to identify the most promising candidates. Two mutants reached an interfacial tension value lower (9.10 mN/m and 4.24 mN/m) than the original protein OmpA (14.98 mN/m). Since predicted isoelectric point values are far from neutral pH, the charge of the protein was a crucial factor in explaining the migration of proteins towards the interface. Low molecular weight mutants did not exhibit a significant difference in their migration to the interface.
Nuñez Velez et al. (2024) DNA shuffling to improve crude-water interfacial activity in biosurfactants with OmpA protein of Escherichia coli. PeerJ 12:e17239 https://doi.org/10.7717/peerj.17239
Studying turn performance, trunk control, and mobility in acute stroke subjects: a cross-sectional study
Background Stroke leads to various impairments like motor deficits, impaired trunk control and restricted mobility. However, rehabilitation professionals often underestimate the fundamental function of turning, which is essential for daily living activities like walking, cooking, or performing household chores. Impaired turning can be attributed to motor deficits post-stroke, resulting in restricted mobility and impaired trunk movement. Therefore, the present study aimed to determine the relationship between turn performance, trunk control, and mobility in stroke patients. Materials and Methods A total of 63 first-time supratentorial stroke (i.e., anterior circulation stroke) patients aged 18–90 years were recruited for the study. Turn performance was assessed by asking patients to walk for 10 feet comfortably, then take a 180° turn and return to the starting position. In addition, the duration and number of steps were recorded. Following this, the Trunk Impairment Scale (TIS) and Stroke Rehabilitation Assessment of Movement (STREAM) were used to assess trunk impairment and mobility, respectively. The group turn performance was analyzed using the Kruskal–Wallis test with a post hoc Mann–Whitney U test for between-group comparisons. The turn duration and turn steps were correlated with age, trunk control, and mobility using Spearman’s rank correlation. A regression analysis was performed to determine the association of turn performance with age, trunk control, and mobility among stroke patients. Results Thirty stroke patients had turning difficulty, and 33 did not. Hence, they were categorized into the turning difficulty (TD) and non-turning difficulty (NTD) groups. When correlated with turn duration and the number of steps taken by the stroke patients while turning, the STREAM and TIS scores revealed a significant negative correlation (p < 0.001). The subjects’ age showed a significant positive correlation with the turn duration and number of steps taken by stroke patients while turning (p < 0.001). A significant association was also found between turn performance and age and trunk control. However, there was no significant association between turn performance and mobility. Conclusion The observed associations highlight the complexity of turning ability and trunk control necessary to complete a turn safely. Additionally, with advancing age, turn performance and turning movement are compromised in stroke patients. This indicates that turning difficulty is more pronounced in older individuals with stroke.
Vasyani et al. (2024) Studying turn performance, trunk control, and mobility in acute stroke subjects: a cross-sectional study. PeerJ 12:e18501 https://doi.org/10.7717/peerj.18501
Phytochemical screening and in vitro antibacterial activity of Echinops kebericho Mesfin tuber extracts: experimental studies
Background The application of plant extracts and their phytochemicals as potential treatments for bacterial illnesses has increased significantly in the last few decades. In Ethiopia, Echinops kebericho Mesfin is widely used to treat a range of illnesses in humans and animals. This study aimed to evaluate the antibacterial activity and phytochemical screening of Echinops kebericho Mesfin. Methods We carried out an in vitro experimental study after collecting the plants from their natural habitats. Then macerated in absolute methanol and petroleum ether solvents and concentrated the extracts using a rotary evaporator. In the experiment, we used Standard cultures of E. coli, K. pneumoniae, S. aureus, and P. aeruginosa. The agar-well diffusion method evaluated the antibacterial activity of the plants. The agar dilution method determined the minimum inhibitory concentration of the plant extract. Results The percentage yield of the plant extracts ranged from 6.25% to 7.85%. The methanol extract of Echinops kebericho Mesfin had the highest inhibitory effect on S. aureus (ATCC 25923) (16.67 ± 0.58 mm), followed by E. coli (ATCC 25922) (11.0 ± 1.73 mm). Phytochemical screening of leaves from the methanol and petroleum ether extracts of the plant revealed the presence of phytochemicals such as alkaloids, flavonoids, tannins, and cardiac glycosides. The present study revealed that the extracts of these plants have antibacterial activity. However, researchers should conduct further studies on the safety margin and quantitative bioactive isolation of selected medicinal plants.
Negasa et al. (2024) Phytochemical screening and in vitro antibacterial activity of Echinops kebericho Mesfin tuber extracts: experimental studies. PeerJ 12:e18554 https://doi.org/10.7717/peerj.18554
Predicting epidermal growth factor receptor (EGFR) mutation status in non-small cell lung cancer (NSCLC) patients through logistic regression: a model incorporating clinical characteristics, computed tomography (CT) imaging features, and tumor marker levels
Background Approximately 60% of Asian populations with non-small cell lung cancer (NSCLC) harbor epidermal growth factor receptor (EGFR) gene mutations, marking it as a pivotal target for genotype-directed therapies. Currently, determining EGFR mutation status relies on DNA sequencing of histological or cytological specimens. This study presents a predictive model integrating clinical parameters, computed tomography (CT) characteristics, and serum tumor markers to forecast EGFR mutation status in NSCLC patients. Methods Retrospective data collection was conducted on NSCLC patients diagnosed between January 2018 and June 2019 at the First Affiliated Hospital of Zhengzhou University, with available molecular pathology results. Clinical information, CT imaging features, and serum tumor marker levels were compiled. Four distinct models were employed in constructing the diagnostic model. Model diagnostic efficacy was assessed through receiver operating characteristic (ROC) area under the curve (AUC) values and calibration curves. DeLong’s test was administered to validate model robustness. Results Our study encompassed 748 participants. Logistic regression modeling, trained with the aforementioned variables, demonstrated remarkable predictive capability, achieving an AUC of 0.805 (95% confidence interval (CI) [0.766–0.844]) in the primary cohort and 0.753 (95% CI [0.687–0.818]) in the validation cohort. Calibration plots suggested a favorable fit of the model to the data. Conclusions The developed logistic regression model emerges as a promising tool for forecasting EGFR mutation status. It holds potential to aid clinicians in more precisely identifying patients likely to benefit from EGFR molecular testing and facilitating targeted therapy decision-making, particularly in scenarios where molecular testing is impractical or inaccessible.
Hao et al. (2024) Predicting epidermal growth factor receptor (EGFR) mutation status in non-small cell lung cancer (NSCLC) patients through logistic regression: a model incorporating clinical characteristics, computed tomography (CT) imaging features, and tumor marker levels. PeerJ 12:e18618 https://doi.org/10.7717/peerj.18618