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Block selection in multiblock partial least squares for modeling genotype-phenotype relations in Saccharomyces
In data-based modeling, correlations between explanatory variables often lead to the formation of distinct gene blocks. This study focuses on identifying influential gene blocks and key variables within these blocks, with a particular application in mind: genotype-phenotype mapping in Saccharomyces. To overcome the challenges of a limited sample size, we use partial least squares (PLS). These gene blocks, which consist of combinations of genes, play a critical role in explaining phenotypic variations. Using partial least squares with multiple blocks, we propose a novel approach, weighted block importance on projection in partial least squares (BwIP-mbPLS), to identify influential gene blocks. Variable importance on projection is used to select significant genes within these blocks. Our study models copper chloride at 0.375mM and melibiose at 2% efficiency and rate in Saccharomyces cerevisiae yeast. Analysis based on silhouette index and total distance within clusters using k-means shows the classification of 5629 genes into 18 gene blocks. Remarkably, BwIP-mbPLS identifies 4 gene blocks on average and significantly improves the prediction of efficiency-based phenotypes. In contrast, traditional block importance in partial least squares projection identifies 6 gene blocks on average and shows comparable or better performance than BIP-mbPLS for rate-based phenotypes. Remarkably, most gene blocks contain fewer than 10 influential genes. Both proposed variants consistently outperform conventional approaches such as partial least squares and multi-block partial least squares in predicting phenotypes. These results highlight the potential of our methods for advancing data-based modeling and genotype-phenotype mapping.
Continuous cell lines derived from the Asian citrus psyllid, Diaphorina citri, harbor viruses and Wolbachia
Molecular dynamics simulations reveal efficient heavy metal ion removal by two-dimensional Cu-THQ metal-organic framework membrane
Fano resonated, ultrathin, flexible and ultrawideband absorption featured nano-metaatom structure with dispersion gap optimized for optical range applications
Engineering spatially-confined conduits to tune nerve self-organization and allodynic responses via YAP-mediated mechanotransduction
Counterintuitive DNA destabilization by monovalent salt at high concentrations due to overcharging
Influence of pre-processing criteria on analysis of accelerometry-based physical activity
Background Accelerometers are widely adopted for physical activity (PA) measurement. Accelerometry data require pre-processing before entering formal statistical analyses. Many pre-processing criteria may influence PA outcomes and the processed sample, impacting results in subsequent statistical analyses. Aim To study the implications of pre-processing criteria for accelerometer data on outputs of interest in physical activity studies. Methods We used the ActiGraph hip-worn accelerometry data from 538 adult Latino participants. We studied four most important domains of pre-processing criteria (wear-time, minimum wear-time, intensity level, and modified bouts). We examined the true sample size in pre-processed data, the moderate-to-vigorous physical activity (MVPA) outcome, and regression coefficients of age and gender predicting MVPA. Results Many pre-processing criteria have minimum impact to the output of interest. However, requirements for minimum wear-time can have high influence on subsequent analyses for MVPA. High requirements for wear-time (e.g., minimum of 5 days with more than 12 hours of wear-time per day) lead to weakened statistical efficiency in estimating the relationship between potential predictors and the MVPA outcome. Intensity levels using vector magnitude triaxial counts yielded drastically different results than those using conventional vertical axis counts. Conclusion Moderate changes in minimum wear-time can yield notably different output data and subsequently influence analyses assessing the impacts of interventions on MVPA behaviors. Processed data using vector magnitude and conventional vertical axis counts are not directly comparable. Sensitivity analyses using alternative pre-processing scenarios are highly recommended to verify the robustness of analyses for accelerometry data.
Label credibility correction based on cell morphological differences for cervical cells classification
Identification of disulfidptosis-related subtypes in gastric cancer and GAMT is a key gene during disulfidptosis
Comprehensive geological analysis and evaluation of the feasibility of renovating the Wanshunchang gas reservoir into a gas storage facility
Spectral convolutional neural network chip for in-sensor edge computing of incoherent natural light
Reducing transition costs towards carbon neutrality of China’s coal power plants
Correction: Can big data reduce urban environmental pollution? Evidence from China’s digital technology experimental zone
Exploring phytochemical, antioxidant, and antimicrobial properties of Plumeria pudica Jacq. leaves
AbstractSince the emergence of the coronavirus disease, there has been a notable surge in demand for herbal remedies with minimal or no adverse effects. Notably, existing vaccines and medications employed in its treatment have exhibited significant side effects, some of which have proven fatal. Consequently, there is an increasing focus on pharmacological research aimed at identifying optimal solutions to this challenge. This shift entails exploring organic alternatives to traditional medicines, involving the extraction of superior phytochemicals from plants for enhanced biomedical applications in treating various diseases and conditions. To evaluate the qualitative phytochemicals and the quantity of these phytochemicals present in the leaf extracts of the medicinally important plant Plumeria pudica Jacq. Also, the antioxidant property estimation and the study of the antimicrobial properties of the plant have been done in this research. The qualitative phytochemical analysis was done to evaluate the presence of various phytochemicals and to quantify these phytochemicals total content estimation of them was done. Also, phytochemical analysis was further enriched by LCMS-QTOF analysis for the presence of compounds. The determination of the antioxidant potential of the leaves was done by two assays, the reducing power assay and the DPPH(2,2-diphenyl-1-picrylhydrazyl) assay. With that the antimicrobial properties of the leaves were also put to test against four bacterial strains namely, Kocuria rhizophila, Pseudomonas aeruginosa, Klebsiella pneumonia, and E. coli. The results of the phytochemical evaluation indicated that both IPA and hydroalcoholic extracts exhibited a superior phytochemical composition, emphasizing the higher extractive potential of IPA compared to the non-polar petroleum ether extract. The quantitative analysis revealed the predominance of IPA extract as the quantity of phenols (101 mg GAE/g dry-weight of plant extract), flavonoids (402.2 mg QE/g dry-weight of plant extract), carbohydrates (336 mg GLU/g dry-weight of plant extract), and proteins (164 mg BSAE/g dry-weight of plant extract) were highest in the IPA extract. LC–MS QTOF analysis demonstrated the presence of significant phytocompounds in all leaf extracts that have pharmacological applications. Moreover, in antioxidant assays, the IPA extract showed the highest DPPH scavenging activity (66.85% of inhibition), with an IC50 value of 33.54 µg/mL, and the IPA extract exhibited the highest reducing power (1.5 absorbance), signifying robust antioxidant activity. Furthermore, the antimicrobial evaluation revealed that the aqueous and hydroalcoholic extracts displayed larger zones of inhibition compared to the other leaf extracts. And, during the antimicrobial activity interestingly most susceptibility was shown by Klebsiella pneumonia. This study concludes that the diverse extracts of P. pudica leaves possess remarkable phytoconstituent properties both qualitatively and quantitatively, suggesting their rich bioactive compound content and potential as novel sources for therapeutic applications.
Development of an advanced multimode refractive index plasmonic optical sensor utilizing split ring resonators for brain cancer cell detection
Correlation analysis of the triglyceride–glucose index and related parameters in metabolic dysfunction-associated fatty liver disease
Small molecule APOL1 inhibitors as a precision medicine approach for APOL1-mediated kidney disease
A synthetic methylotroph achieves accelerated cell growth by alleviating transcription-replication conflicts
Spatial analysis of socioeconomic data and its relationship with illicit crops in Nariño-Colombia
The Sustainable Development Goals (SDGs) aim to eradicate poverty and promote sustainable development; however, socioeconomic disparities persist globally, particularly in Colombia. With a Gini index of 0.556 in 2022, Colombia ranks among the most unequal countries in Latin America, with its southwest region of Nariño facing severe socioeconomic challenges. Concurrently, Nariño registers the highest levels of coca cultivation in Colombia, accounting for 65% of national cocaine production, reflecting the region’s precarious conditions. This study investigates the extent to which the spatial distribution of socioeconomic factors explains coca cultivation patterns in Nariño. Grounded in conflict economics, social capital, and social marginalization theories, the research constructs composite indices representing education, health, public services, economic conditions, and vulnerability. Using spatial analysis, it identifies areas with heightened poverty and vulnerability and examines their relationship with illicit crops. The findings highlight spatial non-stationarity in the factors influencing coca cultivation, offering region-specific insights and policy recommendations to combat illicit crops and foster sustainable development. These results provide a foundation for targeted interventions and contribute to broader strategies addressing inequality and illegal economies in Colombia.