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Background The rates of first and multiple recurrence of diabetic foot ulcers (DFUs) are increasing annually worldwide, and the risk of early recurrence is higher than the distant recurrence. There are numerous risk factors for DFUs recurrence, and there is a lack of systematic screening. Therefore, there is a need to explore the risk factors for DFUs recurrence in order to identify high-risk population of recurrence at an early stage. Objective To explore the predictive value of Logistic regression (LR), support vector machine (SVM), BP neural network model (BPNN) in the recurrence risk of DFUs. Methods From January 2020 to October 2021, a total of patients with DFUs attending the Department of Burn Plastic Surgery, Endocrinology and Wound Ostomy Outpatient Department in General Hospital of Ningxia Medical University were selected as the research objects and divided into the recurrence group (n=116, 29.7%) and non-recurrence group (n=274, 70.3%) according to the recurrence of DFUs within 1 year after discharge. General information was collected and compared between the two groups of patients, including sociodemographic characteristics, medical history assessment and clinical case information. The Diabetes Foot Self-care Behavior Scale (DFSBS) was used to assess the self-management behavior of diabetes foot in patients and chronic diseases risk perception questionnaire was used to assess the risk perception level of DFUs among patients. Multivariable Logistic regression analysis was used to explore the influencing factors of DFUs recurrence in patients within 1 year after discharge. The patients were divided into training and test sets according to the ratio of 7 to 3, the LR, SVM and BPNN recurrence risk prediction models were developed based on Logistic regression variable screening strategy. The receiver operating characteristic (ROC) curves of each model were plotted to predict the recurrence risk of DFUs. Results There were significant differences in BMI, living alone, duration of diabetes, history of smoking, history of alcohol consumption, history of involved toe amputation, classification of diabetic foot ulcers, ankle-brachial index, glycated hemoglobin, sole ulcer, toe involvement, walking impairment, osteomyelitis, multidrug-resistant bacteria infection, diabetic peripheral neuropathy, lower limb atherosclerosis, self-management behavior of diabetes foot, level of risk perception in both groups of DFUs patients (P

How to improve classroom teaching evaluation so that it can really play the role of guidance, motivation, and promotion of evaluation in the new classroom model is a problem that needs to be solved urgently. This paper first introduces the concepts of fuzzy hierarchical analysis and fuzzy comprehensive evaluation, defines the fuzzy judgment matrix, designs a multi-level fuzzy comprehensive judgment algorithm, and constructs a fuzzy hierarchical analysis-fuzzy comprehensive evaluation model. Then, the generalized fuzzy decision tree model is constructed to achieve a clearer and more effective hierarchical categorization of teaching quality evaluation indexes, and the teaching evaluation index system is established accordingly. Teaching quality evaluation is carried out in the English classrooms of three different teachers in a university, and it is found that the classification effect of this paper’s algorithm is better than that of other comparative algorithms in each evaluation index on the datasets FLAGS and BIRDS. In the university’s teaching quality evaluation validation for three English teachers, X, W, and Y, the comprehensive evaluation scores given by this paper’s method are 94.98, 85.92, and 73.32, respectively, which are in line with the actual teaching situation of the three teachers. This study provides new ideas and methods for reforming classroom teaching evaluation.

Peanut is a significant source of protein for human consumption. One of the primary objectives in peanut breeding is the development of new cultivars with enhanced nutritional values. To further this goal, a genome‐wide association study (GWAS) was conducted to analyze seed amino acids contents in 390 diverse peanut accessions collected worldwide, mainly from China, India, and the United States, in 2017 and 2018. These accessions were assessed for their content of 10 different amino acids. Variations in amino acids contents were observed, and arginine (Arg) was found to have the highest average value among all the amino acids quantified. The geographical distribution of the accessions also revealed variations in amino acids contents. High and positive correlation coefficients were observed among the amino acids, suggesting linked metabolic pathways or genetic regulation. A total of 88 single nucleotide polymorphisms (SNPs) spanning various chromosomes were identified, each associated with different amino acids. By using a combination of GWAS, expression anlaysis, and genomic polymorphisim comparisions, the Ahy_A09g041582 (LAC15) gene located on chromrosome A09 was identified as the key candidate which might be involved in plant growth and regulation and may alter amino acids levels. Expression analysis indicated that Ahy_A09g041582 has higher expressions in the shells and seeds than other genes located in the candidate region. This study may help with marker‐based breeding of peanuts with higher nutritional value and offers fresh insights into the genetic basis of the amino acids contents of peanuts. [ABSTRACT FROM AUTHOR]

Summary: Although the regulatory mechanisms of dark and light‐induced plant morphogenesis have been broadly investigated, the biological process in peanuts has not been systematically explored on single‐cell resolution. Herein, 10 cell clusters were characterized using scRNA‐seq‐identified marker genes, based on 13 409 and 11 296 single cells from 1‐week‐old peanut seedling leaves grown under dark and light conditions. 6104 genes and 50 transcription factors (TFs) displayed significant expression patterns in distinct cell clusters, which provided gene resources for profiling dark/light‐induced candidate genes. Further pseudo‐time trajectory and cell cycle evidence supported that dark repressed the cell division and perturbed normal cell cycle, especially the PORA abundances correlated with 11 TFs highly enriched in mesophyll to restrict the chlorophyllide synthesis. Additionally, light repressed the epidermis cell developmental trajectory extending by inhibiting the growth hormone pathway, and 21 TFs probably contributed to the different genes transcriptional dynamic. Eventually, peanut AHL17 was identified from the profile of differentially expressed TFs, which encoded protein located in the nucleus promoted leaf epidermal cell enlargement when ectopically overexpressed in Arabidopsis through the regulatory phytohormone pathway. Overall, our study presents the different gene atlases in peanut etiolated and green seedlings, providing novel biological insights to elucidate light‐induced leaf cell development at the single‐cell level. [ABSTRACT FROM AUTHOR]

Key message: A first creation of high oleic acid peanut varieties by using transcription activator-like effecter nucleases (TALENs) mediated targeted mutagenesis of Fatty Acid Desaturase 2 (FAD2).Abstract: Transcription activator like effector nucleases (TALENs), which allow the precise editing of DNA, have already been developed and applied for genome engineering in diverse organisms. However, they are scarcely used in higher plant study and crop improvement, especially in allopolyploid plants. In the present study, we aimed to create targeted mutagenesis by TALENs in peanut. Targeted mutations in the conserved coding sequence of Arachis hypogaea fatty acid desaturase 2 (AhFAD2) were created by TALENs. Genetic stability of AhFAD2 mutations was identified by DNA sequencing in up to 9.52 and 4.11% of the regeneration plants at two different targeted sites, respectively. Mutation frequencies among AhFAD2 mutant lines were significantly correlated to oleic acid accumulation. Genetically, stable individuals of positive mutant lines displayed a 0.5-2 fold increase in the oleic acid content compared with non-transgenic controls. This finding suggested that TALEN-mediated targeted mutagenesis could increase the oleic acid content in edible peanut oil. Furthermore, this was the first report on peanut genome editing event, and the obtained high oleic mutants could serve for peanut breeding project. [ABSTRACT FROM AUTHOR]

A characteristic feature of peanut is the subterranean fructification, geocarpy, in which the gynophore ('peg'), a specialized organ that transitions from upward growth habit to downward outgrowth upon fertilization, drives the developing pod into the soil for subsequent development underground. As a step towards understanding this phenomenon, we explore the developmental dynamics of the peanut pod transcriptome at 11 successive stages. We identified 110 217 transcripts across developmental stages and quantified their abundance along a pod developmental gradient in pod wall. We found that the majority of transcripts were differentially expressed along the developmental gradient as well as identified temporal programs of gene expression, including hundreds of transcription factors. Thought to be an adaptation to particularly harsh subterranean environments, both up- and down-regulated gene sets in pod wall were enriched for response to a broad array of stimuli, like gravity, light and subterranean environmental factors. We also identified hundreds of transcripts associated with gravitropism and photomorphogenesis, which may be involved in the geocarpy. Collectively, this study forms a transcriptional baseline for geocarpy in peanut as well as provides a considerable body of evidence that transcriptional regulation in peanut aerial and subterranean fruits is complex. [ABSTRACT FROM AUTHOR]