Ancient hybridization underlies tuberization and radiation of the potato lineage.

Interspecific hybridization may trigger species radiation by creating allele combinations and traits. Cultivated potato and its 107 wild relatives from the Petota lineage all share the distinctive trait of underground tubers, but the underlying mechanisms for tuberization and its relationship to extensive species diversification remain unclear. Through analyses of 128 genomes, including 88 haplotype-resolved genomes, we revealed that Petota is of ancient hybrid origin, with all members exhibiting stable mixed genomic ancestry, derived from the Etuberosum and Tomato lineages ca.

Single-cell ligand-receptor profiling reveals an immunotherapy-responsive subtype and prognostic signature in triple-negative breast cancer.

Background: Triple-negative breast cancer (TNBC) is an aggressive form of cancer that lacks specific targeted therapies. Although ligand-receptor (LR) interactions play a crucial role in intercellular communication and contribute to tumor heterogeneity, their molecular details and potential as prognostic or predictive markers in TNBC have not been thoroughly investigated.

Methods: We analyzed single-cell RNA sequencing data to categorize TNBC into 12 subgroups and 10 distinct cell types.

Interaction effect between data discretization and data resampling for class-imbalanced medical datasets.

BackgroundData discretization is an important preprocessing step in data mining for the transfer of continuous feature values to discrete ones, which allows some specific data mining algorithms to construct more effective models and facilitates the data mining process. Because many medical domain datasets are class imbalanced, data resampling methods, including oversampling, undersampling, and hybrid sampling methods, have been widely applied to rebalance the training set, facilitating effective differentiation between majority and minority classes.ObjectiveHerein, we examine the effect of incorporating both data discretization and data resampling as steps in the analytical process on the classifier performance for class-imbalanced medical datasets.

Presence of Multiple Genetic Mutations Related to Insecticide Resistance in Chinese Field Samples of Two Phthorimaea Pest Species.

Potatoes hold the distinction of being the largest non-cereal food crop globally. The application of insecticides has been the most common technology for pest control. The repeated use of synthetic insecticides of the same chemical class and frequent applications have resulted in the emergence of insecticide resistance.

Supramolecular interactions between functional saccharide-based ionic liquids and cellulose macromolecules.

Interactions between polysaccharides and ionic liquids (ILs) at the molecular level are essential to elucidate the dissolution and/or plasticization mechanism of polysaccharides. Herein, saccharide-based ILs (SILs) were synthesized, and cellulose membrane was soaked in different SILs to evaluate the interactions between SILs and cellulose macromolecules. The relevant results showed that the addition of SILs into cellulose can effectively reduce the intra- and/or inter-molecular hydrogen bonds of polysaccharides.

Photomechaelectric Nanogenerators with Different Photoisomers and Dipole Units for Harvesting UV Light Energy.

To date, transforming environmental energy into electricity through a non-mechanical way is challenging. Herein, a series of photomechaelectric (PME) polyurethanes containing azobenzene-based photoisomer units and ionic liquid-based dipole units are synthesized, and corresponding PME nanogenerators (PME-NGs) to harvest electricity are fabricated. The dependence of the output performance of PME-NGs on the structure of the polyurethane is evaluated.

Combining data discretization and missing value imputation for incomplete medical datasets.

Data discretization aims to transform a set of continuous features into discrete features, thus simplifying the representation of information and making it easier to understand, use, and explain. In practice, users can take advantage of the discretization process to improve knowledge discovery and data analysis on medical domain problem datasets containing continuous features. However, certain feature values were frequently missing.

Deep learning based decision tree ensembles for incomplete medical datasets.

Background: In practice, the collected datasets for data analysis are usually incomplete as some data contain missing attribute values. Many related works focus on constructing specific models to produce estimations to replace the missing values, to make the original incomplete datasets become complete. Another type of solution is to directly handle the incomplete datasets without missing value imputation, with decision trees being the major technique for this purpose.

Functional analysis of acyl-CoA dehydrogenases and their application to C22 steroid production.

Acyl-CoA dehydrogenase (ChsE) is involved in the steroid side-chain degradation process. However, their function in vivo remains unclear. In this study, three ChsE, ChsE1-ChsE2, ChsE3, and ChsE4-ChsE5, were identified in Mycolicibacterium neoaurum, and their functions in vivo are studied and compared with those from Mycobacterium tuberculosis in vitro.

Multifunctional biological properties and phytochemical constituents of L. seed kernel extract for preventing skin aging.

This study aimed to investigate the potential of L. seed kernel extract, which is highly discarded by the global food processing industry, as a multifunctional bioactive ingredient for nutraceutical and cosmeceutical applications. Different extracting solvents were utilized, the extracts were then tested for their antioxidant activities using DPPH, ABTS radical scavenging assays, and inhibition of lipid peroxidation.

Effects of Linn. Fruit, Pulp, Leaf, and Seed on Oxidation, Inflammation, Tyrosinase, Matrix Metalloproteinase, Elastase, and Hyaluronidase Inhibition.

In this study, the potential of Linn. as a natural anti-aging, antioxidant, and skin whitening agent was studied. Various parts of , including fruit, leaf, seed, and pulp were sequentially extracted by maceration using -hexane, ethyl acetate, and ethanol, respectively.

Chemical Constituents, Antioxidant, Anti-MMPs, and Anti-Hyaluronidase Activities of Lindl. Leaf Extracts for Skin Aging and Skin Damage Prevention.

This study aimed to investigate the potential usage of Lindl. leaf extracts in the cosmetic industry. Matrix metalloproteinases (MMPs) and hyaluronidase inhibition of leaf extracts, prepared using reflux extraction with deionized water (RE) and 80% ethanol using Soxhlet's apparatus (SE), were determined.

Dermal Delivery Enhancement of Natural Anti-Ageing Compounds from Linn. Extract by Nanostructured Lipid Carriers.

This study aimed to develop nanodelivery systems for enhancing the Linn. extract delivery into the skin. Rosmarinic acid (RA) was used as a marker for the quantitative determination of the extract by high-performance liquid chromatography.

Investigation of high volume of CFBC ash on performance of basic magnesium sulfate cement.

Basic magnesium sulfate cement has the advantages of fast setting, high strength, high toughness, water resistance, corrosion resistance, etc. But the cost has become a reason for limiting its widespread application. With the widespread application of circulating fluidized bed combustion (CFBC) technology in China, the accumulation of CFBC ash is increasing.

Outlier Removal in Model-Based Missing Value Imputation for Medical Datasets.

Many real-world medical datasets contain some proportion of missing (attribute) values. In general, missing value imputation can be performed to solve this problem, which is to provide estimations for the missing values by a reasoning process based on the (complete) observed data. However, if the observed data contain some noisy information or outliers, the estimations of the missing values may not be reliable or may even be quite different from the real values.

Composition and Bioactivity of Essential Oil from Citrus grandis (L.) Osbeck 'Mato Peiyu' Leaf.

'Mato Peiyu' pomelo ( (L.) Osbeck 'Mato Peiyu') leaves from pruning are currently an agricultural waste. The aim of this study was to isolate essential oils from these leaves through steam distillation (SD) and solvent-free microwave extraction (SFME) and to evaluate their applicability to skin care by analyzing their antimicrobial, antioxidant (diphenyl-1-picrylhydrazyl scavenging assay, β-carotene/linoleic acid assay, and nitric oxide scavenging assay), anti-inflammatory (5-lipoxygenase inhibition assay), and antityrosinase activities.

SVM and SVM Ensembles in Breast Cancer Prediction.

Breast cancer is an all too common disease in women, making how to effectively predict it an active research problem. A number of statistical and machine learning techniques have been employed to develop various breast cancer prediction models. Among them, support vector machines (SVM) have been shown to outperform many related techniques.

Research performance of AACSB accredited institutions in Taiwan: before versus after accreditation.

Introduction: More and more universities are receiving accreditation from the Association to Advance Collegiate Schools of Business (AACSB), which is an international association for promoting quality teaching and learning at business schools. To be accredited, the schools are required to meet a number of standards ensuring that certain levels of teaching quality and students' learning are met. However, there are a variety of points of view espoused in the literature regarding the relationship between research and teaching, some studies have demonstrated that research and teaching these are complementary elements of learning, but others disagree with these findings.

On mining incomplete medical datasets: Ordering imputation and classification.

Background: To collect medical datasets, it is usually the case that a number of data samples contain some missing values. Performing the data mining task over the incomplete datasets is a difficult problem. In general, missing value imputation can be approached, which aims at providing estimations for missing values by reasoning from the observed data.

An efficient data preprocessing approach for large scale medical data mining.

Background: The size of medical datasets is usually very large, which directly affects the computational cost of the data mining process. Instance selection is a data preprocessing step in the knowledge discovery process, which can be employed to reduce storage requirements while also maintaining the mining quality. This process aims to filter out outliers (or noisy data) from a given (training) dataset.

Antioxidant and Anti-Inflammatory Properties of Longan (Dimocarpus longan Lour.) Pericarp.

This study examined the antioxidant and anti-inflammatory activities of the water extract of longan pericarp (WLP). The results showed that WLP exhibited radical scavenging, reducing activity and liposome protection activity. In addition, WLP also inhibited lipopolysaccharide (LPS)-induced nitric oxide (NO) production in macrophages.

Risk management strategy to increase the safety of workers in the nanomaterials industry.

In recent years, many engineered nanomaterials (NMs) have been produced, but increasing research has revealed that these may have toxicities far greater than conventional materials and cause significant adverse health effects. At present, there is insufficient data to determine the permissible concentrations of NMs in the workplace. There is also a lack of toxicity data and environmental monitoring results relating to complete health risk assessment.

Antimicrobial, antioxidant, and anti-inflammatory activities of essential oils from five selected herbs.

Eucalyptus bridgesiana, Cymbopogon martinii, Thymus vulgaris, Lindernia anagallis, and Pelargonium fragrans are five species of herbs used in Asia. Their essential oils were analyzed by GC-MS, and a total of 36 components were detected. The results of our study indicated that, except for the essential oil of P.