Potential planting regions of Pterocarpus santalinus (Fabaceae) under current and future climate in China based on MaxEnt modeling.

This study modeled the habitat distribution of Pterocarpus santalinus, a valuable rosewood species, across China under current and future climate scenarios (SSPs126, SSPs245, and SSPs585) using MaxEnt. Our findings reveal that the current suitable habitat, spanning approximately 409,600 km2, is primarily located in the central and southern parts of Guangdong, Guangxi, Fujian, and Yunnan, as well as in the Hainan provinces, along with the coastal regions of Taiwan, and the Sichuan-Chongqing border. The habitat's distribution is significantly influenced by climatic factors such as temperature seasonality (bio4), mean temperature of the wettest quarter (bio8), annual mean temperature (bio1), and annual precipitation (bio12), while terrain and soil factors play a lesser role. Under future climate scenarios, the suitable habitat for P. santalinus is projected to expand, with a northeastward shift in its distribution center. This research not only sheds light on the geoecological characteristics and geographical distribution of P. santalinus in China but also offers a scientific basis for planning its cultivation areas and enhancing cultivation efficiency under changing climate conditions.

Transferable non-invasive modal fusion-transformer (NIMFT) for end-to-end hand gesture recognition.

Objective.Recent studies have shown that integrating inertial measurement unit (IMU) signals with surface electromyographic (sEMG) can greatly improve hand gesture recognition (HGR) performance in applications such as prosthetic control and rehabilitation training. However, current deep learning models for multimodal HGR encounter difficulties in invasive modal fusion, complex feature extraction from heterogeneous signals, and limited inter-subject model generalization. To address these challenges, this study aims to develop an end-to-end and inter-subject transferable model that utilizes non-invasively fused sEMG and acceleration (ACC) data.Approach.The proposed non-invasive modal fusion-transformer (NIMFT) model utilizes 1D-convolutional neural networks-based patch embedding for local information extraction and employs a multi-head cross-attention (MCA) mechanism to non-invasively integrate sEMG and ACC signals, stabilizing the variability induced by sEMG. The proposed architecture undergoes detailed ablation studies after hyperparameter tuning. Transfer learning is employed by fine-tuning a pre-trained model on new subject and a comparative analysis is performed between the fine-tuning and subject-specific model. Additionally, the performance of NIMFT is compared to state-of-the-art fusion models.Main results.The NIMFT model achieved recognition accuracies of 93.91%, 91.02%, and 95.56% on the three action sets in the Ninapro DB2 dataset. The proposed embedding method and MCA outperformed the traditional invasive modal fusion transformer by 2.01% (embedding) and 1.23% (fusion), respectively. In comparison to subject-specific models, the fine-tuning model exhibited the highest average accuracy improvement of 2.26%, achieving a final accuracy of 96.13%. Moreover, the NIMFT model demonstrated superiority in terms of accuracy, recall, precision, and F1-score compared to the latest modal fusion models with similar model scale.Significance.The NIMFT is a novel end-to-end HGR model, utilizes a non-invasive MCA mechanism to integrate long-range intermodal information effectively. Compared to recent modal fusion models, it demonstrates superior performance in inter-subject experiments and offers higher training efficiency and accuracy levels through transfer learning than subject-specific approaches.

Natural resistance-associated macrophage proteins are involved in tolerance to heavy metal Cd2+ toxicity and resistance to bacterial wilt of peanut (Arachis hypogaea L.).

Peanut (Arachis hypogaea L.) is one of the most important oil and industrial crops. However, heavy-metal pollution and frequent soil diseases, poses a significant threat to the production of green and healthy peanuts. Herein, we investigated the effects of heavy metal Cd2+ toxicity to the peanuts, and screened out two peanut cultivars H108 and YZ 9102 with higher Cd2+-tolerance. RNA-seq revealed that Natural resistance-associated macrophage proteins (NRAMP)-like genes were involved in the Cd2+ stress tolerance in H108. Genome-wide identification revealed that 28, 13 and 9 Nramp-like genes existing in the A. hypogaea, A. duranensis and A. ipaensis, respectively. The 50 peanut NRAMP genes share conserved architectural characters, and they were classified into two groups. Expressions of AhNramps, particularly AhNramp4, AhNramp12, AhNramp19, and AhNramp25 could be greatly induced by not only cadmium toxicity, but also copper and zinc stresses. The expression profiles of AhNramp14, AhNramp16 and AhNramp25 showed significant differences in the H108 (resistance) and H107 (susceptible) under the infection of bacterial wilt. In addition, we found that the expression profiles of AhNramp14, AhNramp16, and AhNramp25 were greatly up- or down-regulated by the application of exogenous salicylic acid, methyl jasmonate, and abscisic acid. The AhNramp25, of which expression was affected by both heavy metal toxicity and bacterial wilt infection, were selected as strong candidate genes for peanut stress breeding. Our findings will provide an additional information required for further analysis of AhNramps involved in tolerance to heavy metal toxicity and resistance to bacterial wilt of peanut.

Dynamic N6 -methyladenosine RNA modification regulates peanut resistance to bacterial wilt.

N6 -methyladenosine (m6 A) is the most abundant mRNA modification in eukaryotes and is an important regulator of gene expression as well as many other critical biological processes. However, the characteristics and functions of m6 A in peanut (Arachis hypogea L.) resistance to bacterial wilt (BW) remain unknown. Here, we analyzed the dynamic of m6 A during infection of resistant (H108) and susceptible (H107) peanut accessions with Ralstonia solanacearum (R. solanacearum), the causative agent of BW. Throughout the transcriptome, we identified 'URUAY' as a highly conserved motif for m6 A in peanut. The majority of differential m6 A located within the 3' untranslated region (UTR) of the transcript, with fewer in the exons. Integrative analysis of RNA-Seq and m6 A methylomes suggests the correlation between m6 A and gene expression in peanut R. solanacearum infection, and functional analysis reveals that m6 A-associated genes were related to plant-pathogen interaction. Our experimental analysis suggests that AhALKBH15 is an m6 A demethylase in peanut, leading to decreased m6 A levels and upregulation of the resistance gene AhCQ2G6Y. The upregulation of AhCQ2G6Y expression appears to promote BW resistance in the H108 accession.

Comprehending the cuproptosis and cancer-immunity cycle network: delving into the immune landscape and its predictive role in breast cancer immunotherapy responses and clinical endpoints.

Background: The role of cuproptosis, a phenomenon associated with tumor metabolism and immunological identification, remains underexplored, particularly in relation to the cancer-immunity cycle (CIC) network. This study aims to rigorously examine the impact of the cuproptosis-CIC nexus on immune reactions and prognostic outcomes in patients with breast cancer (BC), striving to establish a comprehensive prognostic model. Methods: In the study, we segregated data obtained from TCGA, GEO, and ICGC using CICs retrieved from the TIP database. We constructed a genetic prognostic framework using the LASSO-Cox model, followed by its validation through Cox proportional hazards regression. This framework's validity was further confirmed with data from ICGC and GEO. Explorations of the tumor microenvironment were carried out through the application of ESTIMATE and CIBERSORT algorithms, as well as machine learning techniques, to identify potential treatment strategies. Single-cell sequencing methods were utilized to delineate the spatial distribution of key genes within the various cell types in the tumor milieu. To explore the critical role of the identified CICs, experiments were conducted focusing on cell survival and migration abilities. Results: In our research, we identified a set of 4 crucial cuproptosis-CICs that have a profound impact on patient longevity and their response to immunotherapy. By leveraging these identified CICs, we constructed a predictive model that efficiently estimates patient prognoses. Detailed analyses at the single-cell level showed that the significance of CICs. Experimental approaches, including CCK-8, Transwell, and wound healing assays, revealed that the protein HSPA9 restricts the growth and movement of breast cancer cells. Furthermore, our studies using immunofluorescence techniques demonstrated that suppressing HSPA9 leads to a notable increase in ceramide levels. Conclusion: This research outlines a network of cuproptosis-CICs and constructs a predictive nomogram. Our model holds great promise for healthcare professionals to personalize treatment approaches for individuals with breast cancer. The work provides insights into the complex relationship between the cuproptosis-CIC network and the cancer immune microenvironment, setting the stage for novel approaches to cancer immunotherapy. By focusing on the essential gene HSPA9 within the cancer-immunity cycle, this strategy has the potential to significantly improve the efficacy of treatments against breast cancer.

Coordinated Lipid Mobilization during Seed Development and Germination in Peanut (Arachis hypogaea L.).

Peanut (Arachis hypogaea L.) is one of the most important oil crops in the world due to its lipid-rich seeds. Lipid accumulation and degradation play crucial roles in peanut seed maturation and seedling establishment, respectively. Here, we utilized lipidomics and transcriptomics to comprehensively identify lipids and the associated functional genes that are important in the development and germination processes of a large-seed peanut variety. A total of 332 lipids were identified; triacylglycerols (TAGs) and diacylglycerols were the most abundant during seed maturation, constituting 70.43 and 16.11%, respectively, of the total lipids. Significant alterations in lipid profiles were observed throughout seed maturation and germination. Notably, TAG (18:1/18:1/18:2) and (18:1/18:2/18:2) peaked at 23386.63 and 23392.43 nmol/g, respectively, at the final stage of seed development. Levels of hydroxylated TAGs (HO-TAGs) increased significantly during the initial stage of germination. Accumulation patterns revealed an inverse relationship between free fatty acids and TAGs. Lipid degradation was determined to be regulated by diacylglycerol acyltransferase, triacylglycerol lipase, and associated transcription factors, predominantly yielding oleic acid, linoleic acid, and linolenic acid. Collectively, the results of this study provide valuable insights into lipid dynamics during the development and germination of large-seed peanuts, gene resources, and guiding future research into lipid accumulation in an economically important crop.

Morphological Characteristics and Expression Patterns of CmCYC2c of Different Flower Shapes in Chrysanthemum morifolium.

The chrysanthemum is widely used as a cut flower, potted flower, and garden flower worldwide and has high ornamental, edible, and medicinal value. The flower heads, composed of ray florets and disc florets, are the most diverse in terms of morphology among ornamental plants. Here, we compared and analyzed the developmental processes of different capitulum types as well as ray florets and disc florets. Morphological differentiation of the two florets occurred on the dorsal domain of the petals at stage Ⅳ of flower development, and differences in stamen development occurred at stage Ⅴ. The dorsal domain of the ray florets and the early stage of flower development were also an essential site and period, respectively, for the differences among capitulum types. In situ hybridization revealed that CmCYC2c, whose homologs are involved in the specification of floret identity in Asteraceae, was expressed in both the dorsal and ventral domains of the ray petals in the tubular-type chrysanthemum, whereas, it was differentially transcribed in the ray petals of flat- and spoon-type chrysanthemum cultivars and had lower or no expression in the dorsal domain and higher expression in the ventral domain at stage Ⅳ. Our study indicates that the expression pattern of CmCYC2c on the dorsal domain of the ray floret at stage Ⅳ contributes to the formation of diverse flower head types in chrysanthemums.

The mechanisms of perineuronal net abnormalities in contributing aging and neurological diseases.

The perineuronal net (PNN) is a highly latticed extracellular matrix in the central nervous system, which is composed of hyaluronic acid, proteoglycan, hyaluronan and proteoglycan link protein (Hapln), and tenascin. PNN is predominantly distributed in GABAergic interneurons expressing Parvalbumin (PV) and plays a critical role in synaptic function, learning and memory, oxidative stress, and inflammation. In addition, PNN's structure and function are also modulated by a variety of factors, including protein tyrosine phosphatase σ (PTPσ), orthodenticle homeo-box 2 (Otx2), and erb-b2 receptor tyrosine kinase 4 (ErbB4). Glycosaminoglycan (GAG), a component of proteoglycan, also influences PNN through its sulfate mode. PNN undergoes abnormal changes during aging and in various neurological diseases, such as Alzheimer's disease, Parkinson's disease, schizophrenia, autism spectrum disorder, and multiple sclerosis. Nevertheless, there is limited report on the relationship between PNN and aging or age-related neurological diseases. This review elaborates on the mechanisms governing PNN regulation and summarizes how PNN abnormalities contribute to aging and neurological diseases, offering insights for potential treatments.

FUL homologous gene CmFL1 is involved in regulating flowering time and floret numbers in Chrysanthemum morifolium.

Flowering time and floret numbers are important ornamental characteristics of chrysanthemums that control their adaptability and inflorescence morphology, respectively. The FRUITFULL (FUL) gene plays a key role in inducing flowering and inflorescence meristem development. In this study, we isolated a homolog of the MADS-box gene FUL, CmFUL-Like 1 (CmFL1), from chrysanthemum inflorescence buds. Quantitative RT-PCR and in situ analyses showed that CmFL1 was strongly expressed in young inflorescence buds. Overexpression of CmFL1 caused early flowering while co-suppression expression of CmFL1 increased the number of florets. Furthermore, the floral promoting factors CmSOC1, CmFDL1, and CmLFY were up-regulated in the shoot tips of transgenic plants. In addition, RNA-seq analysis of the transgenic plants suggested that certain differentially expressed genes (DEGs)-such as MADS-box, homeobox family, and ethylene pathway genes-may be involved in the inflorescence meristem development. GO pathway enrichment analysis showed that the differentially transcribed genes enriched the representation of the carbohydrate metabolic pathway, which is critical for flower development. Overall, our findings revealed the conserved function of CmFL1 in controlling flowering time along with a novel function in regulating the number of florets.

Evidence of synergy coordination patterns of upper-limb motor control in stroke patients with mild and moderate impairment.

Objectives: Previous studies showed that the central nervous system (CNS) controls movements by recruiting a low-dimensional set of modules, usually referred to as muscle synergies. Stroke alters the structure and recruitment patterns of muscle synergies, leading to abnormal motor performances. Some studies have shown that muscle synergies can be used as biomarkers for assessing motor function. However, coordination patterns of muscle synergies in post-stroke patients need more investigation to characterize how they are modified in functional movements. Methods: Thirteen mild-to-moderate stroke patients and twenty age-matched healthy subjects were recruited to perform two upper-limb movements, hand-to-mouth movement and reaching movement. Muscle synergies were extracted with nonnegative matrix factorization. We identified a set of reference synergies (i.e., averaged across healthy subjects) and typical synergies (i.e., averaged across stroke subjects) from the healthy group and stroke group respectively, and extracted affected synergies from each patient. Synergy similarity between groups was computed and analyzed. Synergy reconstruction analysis was performed to verify synergy coordination patterns in post-stroke patients. Results: On average, three synergies were extracted from both the healthy and stroke groups, while the mild impairment group had a significantly higher number of synergies than the healthy group. The similarity analysis showed that synergy structure was more consistent in the healthy group, and stroke instead altered synergy structure and induced more variability. Synergy reconstruction analysis at group and individual levels showed that muscle synergies of patients often showed a combination of healthy reference synergies in the analyzed movements. Finally, this study associated four synergy coordination patterns with patients: merging (equilibrium and disequilibrium), sharing (equilibrium and disequilibrium), losing, and preservation. The preservation was mainly represented in the mild impairment group, and the moderate impairment group showed more merging and sharing. Conclusion: This study concludes that stroke shows more synergy variability compared to the healthy group and the alterations of muscle synergies can be described as a combination of reference synergies by four synergy coordination patterns. These findings deepen the understanding of the underlying neurophysiological mechanisms and possible motor control strategies adopted by the CNS in post-stroke patients.

Comparative transcriptome analysis and flavonoid profiling of floral mutants reveals CmMYB11 regulating flavonoid biosynthesis in chrysanthemum.

Flavonoids, of which the major groups are flavones, flavonols, and anthocyanins, confer a variety of colors on plants. Bud sports with variation of floral colors occur occasionally during chrysanthemum cultivation. Although it has been reported that methylation at the promoter of CmMYB6 was related to anthocyanin contents, the regulatory networks of flavonoid biosynthesis still remain largely unknown in mutation of chrysanthemum. We compared phenotypes, pigment composition and transcriptomes in two chrysanthemum cultivars, 'Anastasia Dark Green' and 'Anastasia Pink', and regenerated bud sports of these cultivars with altered floral colors. Increased anthocyanins turned the 'Anastasia Dark Green' mutant red, while decreased anthocyanins turned the 'Anastasia Pink' mutant white. Moreover, total flavonoids were reduced in both mutants. Multiple flavonoid biosynthetic genes and regulatory genes encoding MYBs and bHLHs transcription factors were differentially expressed in pairwise comparisons of transcriptomes in 'Anastasia Dark Green' or 'Anastasia Pink' and their mutants at different flowering stages. Among these regulatory genes, the expression patterns of CmMYB6 and CmbHLH2 correlated to changes of anthocyanin contents, and down-regulation of CmMYB11 correlated to decreased total flavonoid contents in two mutants. CmMYB11 was shown to directly activate the promoter activities of CmCHS2, CmCHI, CmDFR, CmANS, CmFNS, and CmFLS. Furthermore, overexpression of CmMYB11 increased both flavonols and anthocyanins in tobacco petals. Our work provides new insights into regulatory networks involved in flavonoid biosynthesis and coloration in chrysanthemum.

Dynamic DNA methylation modification in peanut seed development.

Cytosine methylation is an important epigenetic modification involved in regulation of plant development. However, the epigenetic mechanisms governing peanut seed development remain unclear. Herein, we generated DNA methylation profiles of developmental seeds of peanut H2014 and its smaller seed mutant H1314 at 15 and 60 days after pegging (DAP, S1, S4). Accompanying seed development, globally elevated methylation was observed in both lines. The mutant had a higher methylation level of 31.1% than wild type at S4, and 27.1-35.9% of the differentially methylated regions (DMRs) between the two lines were distributed in promoter or genic regions at both stages. Integrated methylome and transcriptome analysis revealed important methylation variations closely associated with seed development. Furthermore, some genes showed significantly negative correlation of expression with the methylation level within promoter or gene body. The results provide insights into the roles of DNA methylation in peanut seed development.

PSW1, an LRR receptor kinase, regulates pod size in peanut.

Pod size is a key agronomic trait that greatly determines peanut yield, the regulatory genes and molecular mechanisms that controlling peanut pod size are still unclear. Here, we used quantitative trait locus analysis to identify a peanut pod size regulator, POD SIZE/WEIGHT1 (PSW1), and characterized the associated gene and protein. PSW1 encoded leucine-rich repeat receptor-like kinase (LRR-RLK) and positively regulated pod stemness. Mechanistically, this allele harbouring a 12-bp insertion in the promoter and a point mutation in the coding region of PSW1 causing a serine-to-isoleucine (S618I) substitution substantially increased mRNA abundance and the binding affinity of PSW1 for BRASSINOSTEROID INSENSITIVE1-ASSOCIATED RECEPTOR KINASE 1 (BAK1). Notably, PSW1HapII (super-large pod allele of PSW1) expression led to up-regulation of a positive regulator of pod stemness PLETHORA 1 (PLT1), thereby resulting in larger pod size. Moreover, overexpression of PSW1HapII increased seed/fruit size in multiple plant species. Our work thus discovers a conserved function of PSW1 that controls pod size and provides a valuable genetic resource for breeding high-yield crops.

Muscle synergies for evaluating upper limb in clinical applications: A systematic review.

Introduction: Muscle synergies have been proposed as a strategy employed by the central nervous system to control movements. Muscle synergy analysis is a well-established framework to examine the pathophysiological basis of neurological diseases and has been applied for analysis and assessment in clinical applications in the last decades, even if it has not yet been widely used in clinical diagnosis, rehabilitative treatment and interventions. Even if inconsistencies in the outputs among studies and lack of a normative pipeline including signal processing and synergy analysis limit the progress, common findings and results are identifiable as a basis for future research. Therefore, a literature review that summarizes methods and main findings of previous works on upper limb muscle synergies in clinical environment is needed to i) summarize the main findings so far, ii) highlight the barriers limiting their use in clinical applications, and iii) suggest future research directions needed for facilitating translation of experimental research to clinical scenarios. Methods: Articles in which muscle synergies were used to analyze and assess upper limb function in neurological impairments were reviewed. The literature research was conducted in Scopus, PubMed, and Web of Science. Experimental protocols (e.g., the aim of the study, number and type of participants, number and type of muscles, and tasks), methods (e.g., muscle synergy models and synergy extraction methods, signal processing methods), and the main findings of eligible studies were reported and discussed. Results: 383 articles were screened and 51 were selected, which involved a total of 13 diseases and 748 patients and 1155 participants. Each study investigated on average 15 ± 10 patients. Four to forty-one muscles were included in the muscle synergy analysis. Point-to-point reaching was the most used task. The preprocessing of EMG signals and algorithms for synergy extraction varied among studies, and non-negative matrix factorization was the most used method. Five EMG normalization methods and five methods for identifying the optimal number of synergies were used in the selected papers. Most of the studies report that analyses on synergy number, structure, and activations provide novel insights on the physiopathology of motor control that cannot be gained with standard clinical assessments, and suggest that muscle synergies may be useful to personalize therapies and to develop new therapeutic strategies. However, in the selected studies synergies were used only for assessment; different testing procedures were used and, in general, study-specific modifications of muscle synergies were observed; single session or longitudinal studies mainly aimed at assessing stroke (71% of the studies), even though other pathologies were also investigated. Synergy modifications were either study-specific or were not observed, with few analyses available for temporal coefficients. Thus, several barriers prevent wider adoption of muscle synergy analysis including a lack of standardized experimental protocols, signal processing procedures, and synergy extraction methods. A compromise in the design of the studies must be found to combine the systematicity of motor control studies and the feasibility of clinical studies. There are however several potential developments that might promote the use of muscle synergy analysis in clinical practice, including refined assessments based on synergistic approaches not allowed by other methods and the availability of novel models. Finally, neural substrates of muscle synergies are discussed, and possible future research directions are proposed. Conclusions: This review provides new perspectives about the challenges and open issues that need to be addressed in future work to achieve a better understanding of motor impairments and rehabilitative therapy using muscle synergies. These include the application of the methods on wider scales, standardization of procedures, inclusion of synergies in the clinical decisional process, assessment of temporal coefficients and temporal-based models, extensive work on the algorithms and understanding of the physio-pathological mechanisms of pathology, as well as the application and adaptation of synergy-based approaches to various rehabilitative scenarios for increasing the available evidence.

Hybrid weakness and continuous flowering caused by compound expression of FTLs in Chrysanthemum morifolium × Leucanthemum paludosum intergeneric hybridization.

Hybridization is an important evolutionary mechanism ubiquitous to plants. Previous studies have shown that hybrid polyploidization of cultivated chrysanthemum, 'Zhongshanzigui', and Leucanthemum paludosum exhibit spring-flowering traits. This study explores the function of the LpFTLs gene via the phenotype of A. thaliana after heterologous transformation of the LpFTLs gene, and analyzes the mechanism ofthe continuous flowering phenotype and heterosis of hybrid offspring. The results suggest that the flowering phenotype of hybrid offspring in spring may be related to the expression of the LpFTLs gene. Ectopic expression of Leucanthemum paludosumLpFTLs in Arabidopsis thaliana resulted in earlier flowering, indicating that the LpFTLs gene also affects the flowering time in L. paludosum. Compound expression of FTLs in C. morifolium × L. paludosum intergeneric hybridization directly leads to serious heterosis in the hybrid offspring. Moreover, continuous flowering appears to be accompanied by hybrid weakness under the balance of vegetative and reproductive growth. Therefore, in future studies on chrysanthemum breeding, a suitable balance point must be established to ensure the target flowering time under normal growth.

Number of trials and data structure affect the number and components of muscle synergies in upper-limb reaching movements.

Objective.Due to the variability of human movements, muscle activations vary among trials and subjects. However, few studies investigated how data organization methods for addressing variability impact the extracted muscle synergies.Approach.Fifteen healthy subjects performed a large set of upper limb multi-directional point-to-point reaching movements. Then, the study extracted muscle synergies under different data settings and investigated how data structure prior to synergy extraction, namely concatenation, averaging, and single trial, the number of considered trials, and the number of reaching directions affected the number and components of muscle synergies.Main results.The results showed that the number and components of synergies were significantly affected by the data structure. The concatenation method identified the highest number of synergies, and the averaging method usually found a smaller number of synergies. When the concatenated trials or reaching directions was lower than a minimum value, the number of synergies increased with the increase of the number of trials or reaching directions; however, when the number of trials or reaching directions reached a threshold, the number of synergies was usually constant or with less variation even when novel directions and trials were added. Similarity analysis also showed a slight increase when the number of trials or reaching directions was lower than a threshold. This study recommends that at least five trials and four reaching directions and the concatenation method are considered in muscle synergies analysis during upper limb tasks.Significance.This study makes the researchers focus on the variability analysis induced by the diseases rather than the techniques applied for synergies analysis and promotes applications of muscle synergies in clinical scenarios.

DWARF AND ROBUST PLANT regulates plant height via modulating gibberellin biosynthesis in chrysanthemum.

YABBY (YAB) genes are specifically expressed in abaxial cells of lateral organs and determine abaxial cell fate. However, most studies have focused on few model plants, and the molecular mechanisms of YAB genes are not well understood. Here, we identified a YAB transcription factor in chrysanthemum (Chrysanthemum morifolium), Dwarf and Robust Plant (CmDRP), that belongs to a distinct FILAMENTOUS FLOWER (FlL)/YAB3 sub-clade lost in Brassicaceae. CmDRP was expressed in various tissues but did not show any polar distribution in chrysanthemum. Overexpression of CmDRP resulted in a semi-dwarf phenotype with a significantly decreased active GA3 content, while reduced expression generated the opposite phenotype. Furthermore, plant height of transgenic plants was partially rescued through the exogenous application of GA3 and Paclobutrazol, and expression of the GA biosynthesis gene CmGA3ox1 was significantly altered in transgenic plants. Yeast one-hybrid, luciferase, and chromatin immunoprecipitation-qPCR analyses showed that CmDRP could directly bind to the CmGA3ox1 promoter and suppress its expression. Our research reveals a nonpolar expression pattern of a YAB family gene in dicots and demonstrates it regulates plant height through the GA pathway, which will deepen the understanding of the genetic and molecular mechanisms of YAB genes.

Species-Specific Gene Expansion of the Cellulose synthase Gene Superfamily in the Orchidaceae Family and Functional Divergence of Mannan Synthesis-Related Genes in Dendrobium officinale.

Plant Cellulose synthase genes constitute a supergene family that includes the Cellulose synthase (CesA) family and nine Cellulose synthase-like (Csl) families, the members of which are widely involved in the biosynthesis of cellulose and hemicellulose. However, little is known about the Cellulose synthase superfamily in the family Orchidaceae, one of the largest families of angiosperms. In the present study, we identified and systematically analyzed the CesA/Csl family members in three fully sequenced Orchidaceae species, i.e., Dendrobium officinale, Phalaenopsis equestris, and Apostasia shenzhenica. A total of 125 Cellulose synthase superfamily genes were identified in the three orchid species and classified into one CesA family and six Csl families: CslA, CslC, CslD, CslE, CslG, and CslH according to phylogenetic analysis involving nine representative plant species. We found species-specific expansion of certain gene families, such as the CslAs in D. officinale (19 members). The CesA/Csl families exhibited sequence divergence and conservation in terms of gene structure, phylogeny, and deduced protein sequence, indicating multiple origins via different evolutionary processes. The distribution of the DofCesA/DofCsl genes was investigated, and 14 tandemly duplicated genes were detected, implying that the expansion of DofCesA/DofCsl genes may have originated via gene duplication. Furthermore, the expression profiles of the DofCesA/DofCsl genes were investigated using transcriptome sequencing and quantitative Real-time PCR (qRT-PCR) analysis, which revealed functional divergence in different tissues and during different developmental stages of D. officinale. Three DofCesAs were highly expressed in the flower, whereas DofCslD and DofCslC family genes exhibited low expression levels in all tissues and at all developmental stages. The 19 DofCslAs were differentially expressed in the D. officinale stems at different developmental stages, among which six DofCslAs were expressed at low levels or not at all. Notably, two DofCslAs (DofCslA14 and DofCslA15) showed significantly high expression in the stems of D. officinale, indicating a vital role in mannan synthesis. These results indicate the functional redundancy and specialization of DofCslAs with respect to polysaccharide accumulation. In conclusion, our results provide insights into the evolution, structure, and expression patterns of CesA/Csl genes and provide a foundation for further gene functional analysis in Orchidaceae and other plant species.

Evaluation of Methods for the Extraction of Spatial Muscle Synergies.

Muscle synergies have been largely used in many application fields, including motor control studies, prosthesis control, movement classification, rehabilitation, and clinical studies. Due to the complexity of the motor control system, the full repertoire of the underlying synergies has been identified only for some classes of movements and scenarios. Several extraction methods have been used to extract muscle synergies. However, some of these methods may not effectively capture the nonlinear relationship between muscles and impose constraints on input signals or extracted synergies. Moreover, other approaches such as autoencoders (AEs), an unsupervised neural network, were recently introduced to study bioinspired control and movement classification. In this study, we evaluated the performance of five methods for the extraction of spatial muscle synergy, namely, principal component analysis (PCA), independent component analysis (ICA), factor analysis (FA), nonnegative matrix factorization (NMF), and AEs using simulated data and a publicly available database. To analyze the performance of the considered extraction methods with respect to several factors, we generated a comprehensive set of simulated data (ground truth), including spatial synergies and temporal coefficients. The signal-to-noise ratio (SNR) and the number of channels (NoC) varied when generating simulated data to evaluate their effects on ground truth reconstruction. This study also tested the efficacy of each synergy extraction method when coupled with standard classification methods, including K-nearest neighbors (KNN), linear discriminant analysis (LDA), support vector machines (SVM), and Random Forest (RF). The results showed that both SNR and NoC affected the outputs of the muscle synergy analysis. Although AEs showed better performance than FA in variance accounted for and PCA in synergy vector similarity and activation coefficient similarity, NMF and ICA outperformed the other three methods. Classification tasks showed that classification algorithms were sensitive to synergy extraction methods, while KNN and RF outperformed the other two methods for all extraction methods; in general, the classification accuracy of NMF and PCA was higher. Overall, the results suggest selecting suitable methods when performing muscle synergy-related analysis.