A Metal-Free Direct Decarboxylative Fluoroacylation of Indole Carboxylic Acids with Fluorinated Acids.

A straightforward preparation of diversified fluorinated indol-3-yl ketones was developed by the direct decarboxylative fluoroacylation of indole carboxylic acids. The reaction could be performed on a gram scale under net conditions. Neither a metal catalyst nor an additive was employed. This methodology featured simple reaction conditions, high efficiency, exclusive selectivity, a broad substrate scope, and easy operation, which allowed it to meet the green chemistry requirement of the modern pharmaceutical industry. Control experiments confirmed that a radical process might be involved in the tandem decarboxylative fluoroacylation sequence.

Femoral Anteversion Angle as a Predictor of Anterior Hip Labral Length in Patients With Femoroacetabular Impingement Syndrome.

Background: The relationship between hip rotational abnormalities and hip labral size has not been fully investigated. Purposes: To (1) examine the correlation between rotational abnormalities of the hip and labral size, while also identifying other predictive values for hip labral size, and (2) explore whether femoral torsion will lead to increased labral size. Study Design: Cross-sectional study; Level of evidence, 3. Methods: A total of 180 patients (180 hips) with femoroacetabular impingement syndrome (FAIS) (mean age, 36.81 ± 10.17 years; 67 male, 113 female) who underwent hip arthroscopic surgery between January 2021 and May 2022 were included. The femoral version (FV), acetabular version, and combined version angles were measured on computed tomography, and the labral length and height at the 12-o'clock and 3-o'clock positions were measured on magnetic resonance imaging. The hips were categorized into 3 groups based on FV angle: small (SFV; <10°); moderate (MFV; ≥10° and ≤20°), and large (LFV; >20°), and group comparisons were performed. Linear correlation and regression analysis were employed. Results: Predictive factors for labral length were FV angle (ß = 0.298; P = .02), sex (ß = -0.302; P < .001), and age (ß = -0.169; P = .016) at 3 o'clock and lateral center-edge angle (LCEA; ß = -0.208; P = .005) and age (ß = -0.186; P = .011) at 12 o'clock. FV angle was positively correlated with labral length at 3 o'clock (r = 0.267; P < .001) and negatively correlated with age (r = -0.222; P = .003) and female sex (r = -0.202; P = .006). LCEA (r = -0.227; P = .002) and age (r = -0.205; P = .006) were negatively correlated with labral length at 12 o'clock. Labral length at 3 o'clock was significantly different between the LFV (n = 49 hips), MFV (n = 65 hips), and SFV (n = 66 hips) groups (9.85 ± 2.28, 8.89 ± 2.44, and 8.30 ± 2.05 mm, respectively; P = .027 for LFV vs MFV; P < .001 for LFV vs SFV). Conclusion: Patients with FAIS who exhibited a higher FV angle were at a greater likelihood of having a larger anterior labral length. Increased femoral anteversion and decreased LCEA, male sex, and younger age were significantly associated with longer hip labral length.

Individual and joint associations of air pollutants exposure with semen quality: A retrospective longitudinal study in Wenzhou, China.

PURPOSE: The impact of air pollution on semen quality has been confirmed, yet the joint effect remains unclear. We evaluate the individual and joint associations of particulate (PM2.5 and PM10) and gaseous pollutants (NO2, SO2, O3 and CO) with semen quality. METHODS: We included 5,114 men in this study from 2014 to 2022. The individual and joint associations were measured by multiple linear regression models. RESULTS: Sperm motility and semen volume were inversely associated with pollutant concentrations during every stage of sperm development, especially at lag days 0-9 and 10-14 (all P < 0.05). Stratified analyses showed that the study pollutants (except CO) had a positive effect on semen concentration during the stage of sperm development, especially in spring and autumn, while a decreased total sperm number was associated with CO (all P < 0.05). However, joint associations of particulate and gaseous pollutants with semen quality parameters were not statistically significant (all P > 0.05). CONCLUSIONS: During all stages of sperm development, particulate and gaseous pollutants had individual negative impacts on sperm motility and semen volume, and these impacts were less pronounced in spring and autumn. Our findings highlight the importance and necessity of reducing the exposure to pollutants especially in the critical stage of sperm development to improve semen quality.

Correction: Luo et al. Role of Recognition MicroRNAs in Hemaphysalis longicornis and Theileria orientalis Interactions. Pathogens 2024, 13, 288.

In the original publication [...].

Role of Recognition MicroRNAs in Hemaphysalis longicornis and Theileria orientalis Interactions.

Ticks are an important type of pathogen transmission vector, and pathogens not only cause serious harm to livestock but can also infect humans. Because of the roles that ticks play in disease transmission, reducing tick pathogen infectivity has become increasingly important and requires the identification and characterization of these pathogens and their interaction mechanisms. In this study, we determined the miRNA expression profile of Hemaphysalis longicornis infected with Theileria orientalis, predicted the target genes of miRNAs involved in this infection process, and investigated the role of miRNA target recognition during host-pathogen interactions. The results showed that longipain is a target gene of miR-5309, which was differentially expressed at different developmental stages and in various tissues in the control group. However, the miR-5309 level was reduced in the infection group. Analysis of the interaction between miRNA and the target gene showed that miR-5309 negatively regulated the expression of the longipain protein during the infection of H. longicornis with T. orientalis. To verify this inference, we compared longipain with the blocking agent orientalis. In this study, the expression of longipain was upregulated by the inhibition of miR-5309 in ticks, and the ability of the antibody produced by the tick-derived protein to attenuate T. orientalis infection was verified through animal immunity and antigen-antibody binding tests. The results showed that expression of the longipain + GST fusion protein caused the cattle to produce antibodies that could be successfully captured by ticks, and cellular immunity was subsequently activated in the ticks, resulting in a subtractive effect on T. orientalis infection. This research provides ideas for the control of ticks and tickborne diseases and a research basis for studying the mechanism underlying the interaction between ticks and pathogens.

Music emotion recognition based on temporal convolutional attention network using EEG.

Music is one of the primary ways to evoke human emotions. However, the feeling of music is subjective, making it difficult to determine which emotions music triggers in a given individual. In order to correctly identify emotional problems caused by different types of music, we first created an electroencephalogram (EEG) data set stimulated by four different types of music (fear, happiness, calm, and sadness). Secondly, the differential entropy features of EEG were extracted, and then the emotion recognition model CNN-SA-BiLSTM was established to extract the temporal features of EEG, and the recognition performance of the model was improved by using the global perception ability of the self-attention mechanism. The effectiveness of the model was further verified by the ablation experiment. The classification accuracy of this method in the valence and arousal dimensions is 93.45% and 96.36%, respectively. By applying our method to a publicly available EEG dataset DEAP, we evaluated the generalization and reliability of our method. In addition, we further investigate the effects of different EEG bands and multi-band combinations on music emotion recognition, and the results confirm relevant neuroscience studies. Compared with other representative music emotion recognition works, this method has better classification performance, and provides a promising framework for the future research of emotion recognition system based on brain computer interface.

Using machine learning methods to study the tumour microenvironment and its biomarkers in osteosarcoma metastasis.

Background: The long-term prognosis for patients with osteosarcoma (OS) metastasis remains unfavourable, highlighting the urgent need for research that explores potential biomarkers using innovative methodologies. Methods: This study explored potential biomarkers for OS metastasis by analysing data from the Cancer Genome Atlas Program (TCGA) and Gene Expression Omnibus (GEO) databases. The synthetic minority oversampling technique (SMOTE) was employed to tackle class imbalances, while genes were selected using four feature selection algorithms (Monte Carlo feature selection [MCFS], Borota, minimum-redundancy maximum-relevance [mRMR], and light gradient-boosting machine [LightGBM]) based on the gene expression matrix. Four machine learning (ML) algorithms (support vector machine [SVM], extreme gradient boosting [XGBoost], random forest [RF], and k-nearest neighbours [kNN]) were utilized to determine the optimal number of genes for building the model. Interpretable machine learning (IML) was applied to construct prediction networks, revealing potential relationships among the selected genes. Additionally, enrichment analysis, survival analysis, and immune infiltration were performed on the featured genes. Results: In DS1, DS2, and DS3, the IML algorithm identified 53, 45, and 46 features, respectively. Using the merged gene set, we obtained a total of 79 interpretable prediction rules for OS metastasis. We subsequently conducted an in-depth investigation on 39 crucial molecules associated with predicting OS metastasis, elucidating their roles within the tumour microenvironment. Importantly, we found that certain genes act as both predictors and differentially expressed genes. Finally, our study unveiled statistically significant differences in survival between the high and low expression groups of TRIP4, S100A9, SELL and SLC11A1, and there was a certain correlation between these genes and 22 various immune cells. Conclusions: The biomarkers discovered in this study hold significant implications for personalized therapies, potentially enhancing the clinical prognosis of patients with OS.

Neural correlates of musical familiarity: a functional magnetic resonance study.

Existing neuroimaging studies on neural correlates of musical familiarity often employ a familiar vs. unfamiliar contrast analysis. This singular analytical approach reveals associations between explicit musical memory and musical familiarity. However, is the neural activity associated with musical familiarity solely related to explicit musical memory, or could it also be related to implicit musical memory? To address this, we presented 130 song excerpts of varying familiarity to 21 participants. While acquiring their brain activity using functional magnetic resonance imaging (fMRI), we asked the participants to rate the familiarity of each song on a five-point scale. To comprehensively analyze the neural correlates of musical familiarity, we examined it from four perspectives: the intensity of local neural activity, patterns of local neural activity, global neural activity patterns, and functional connectivity. The results from these four approaches were consistent and revealed that musical familiarity is related to the activity of both explicit and implicit musical memory networks. Our findings suggest that: (1) musical familiarity is also associated with implicit musical memory, and (2) there is a cooperative and competitive interaction between the two types of musical memory in the perception of music.

Boosting Reinforcement Learning via Hierarchical Game Playing With State Relay.

Due to its wide application, deep reinforcement learning (DRL) has been extensively studied in the motion planning community in recent years. However, in the current DRL research, regardless of task completion, the state information of the agent will be reset afterward. This leads to a low sample utilization rate and hinders further explorations of the environment. Moreover, in the initial training stage, the agent has a weak learning ability in general, which affects the training efficiency in complex tasks. In this study, a new hierarchical reinforcement learning (HRL) framework dubbed hierarchical learning based on game playing with state relay (HGR) is proposed. In particular, we introduce an auxiliary penalty to regulate task difficulty, and one training mechanism, the state relay mechanism, is designed. The relay mechanism can make full use of the intermediate states of the agent and expand the environment exploration of low-level policy. Our algorithm can improve the sample utilization rate, reduce the sparse reward problem, and thereby enhance the training performance in complex environments. Simulation tests are carried out on two public experiment platforms, i.e., MazeBase and MuJoCo, to verify the effectiveness of the proposed method. The results show that HGR significantly benefits the reinforcement learning (RL) area.

Genetic Model Identification and Major QTL Mapping for Petiole Thickness in Non-Heading Chinese Cabbage.

Petioles of non-heading Chinese cabbage are not only an important edible part but also a conduit for nutrient transport, holding significant agricultural and research value. In this study, we conducted a comprehensive genetic analysis of petiole-related traits using a segregating population. Modern quantitative genetic approaches were applied to investigate the genetic regulation of petiole thickness. The results indicated that petiole thickness is a quantitative trait, and the identified genetic model was consistent with two pairs of additive-dominant main genes and additive-dominant polygenes (2MG-AD). BSA-seq analysis identified a major effect of QTL controlling petiole thickness on chromosome A09: 42.08-45.09 Mb, spanning 3.01 Mb, designated as QTL-BrLH9. Utilizing InDel markers, the interval was narrowed down to 51 kb, encompassing 14 genes with annotations for 10 of them. Within the interval, four mutated genes were detected. Combined with gene annotation, protein sequence analysis, and homology alignment, it was found that BraA09g063520.3C's homologous gene SMXL6 in Arabidopsis (Arabidopsis thaliana (L.) Heynh) is an inhibitor of the coding and synthesis of the strigolactone pathway. Strigolactone (SLs) plays an important role in plant growth and development. The cloning results showed that multiple frameshift mutations and non-synonymous mutations occurred on the exon. The qPCR results showed that the expression of the gene was significantly different between the two parents at the adult stage, so it was speculated that it would lead to changes in petiole thickness. BraA09g063520.3C was predicted as the final candidate gene.

Micro-Expression Recognition Based on Nodal Efficiency in the EEG Functional Networks.

Micro-expression recognition based on ima- ges has made some progress, yet limitations persist. For instance, image-based recognition of micro-expressions is affected by factors such as ambient light, changes in head posture, and facial occlusion. The high temporal resolution of electroencephalogram (EEG) technology can record brain activity associated with micro-expressions and identify them objectively from a neurophysiological standpoint. Accordingly, this study introduces a novel method for recognizing micro-expressions using node efficiency features of brain networks derived from EEG signals. We designed a real-time Supervision and Emotional Expression Suppression (SEES) experimental paradigm to collect video and EEG data reflecting micro- and macro-expression states from 70 participants experiencing positive emotions. By constructing functional brain networks based on graph theory, we analyzed the network efficiencies at both macro- and micro-levels. The participants exhibited lower connection density, global efficiency, and nodal efficiency in the alpha, beta, and gamma networks during micro-expressions compared to macro-expressions. We then selected the optimal subset of nodal efficiency features using a random forest algorithm and applied them to various classifiers, including Support Vector Machine (SVM), Gradient-Boosted Decision Tree (GBDT), Logistic Regression (LR), Random Forest (RF), and eXtreme Gradient Boosting (XGBoost). These classifiers achieved promising accuracy in micro-expression recognition, with SVM exhibiting the highest accuracy of 92.6% when 15 channels were selected. This study provides a new neuroscientific indicator for recognizing micro-expressions based on EEG signals, thereby broadening the potential applications for micro-expression recognition.

Insight into Hyalomma anatolicum biology by comparative genomics analyses.

Hyalomma anatolicum is an obligatory blood-sucking ectoparasite and contributes to the transmission of Crimean-Congo haemorrhagic fever (CCHF) virus, Theileria spp. and Babesia spp. Progress in exploring the adaptive strategy of this ectoparasite and developing tools to fight it has been hindered by the lack of a complete genome. Herein, we assembled the genome using diverse sources of data from multiple sequencing platforms and annotated the 1.96 Gb genome of Hy. anatolicum. Comparative genome analyses and the predicted protein encoding genes reveal unique facets of this genome, including gene family expansion associated with blood feeding and digestion, multi-gene families involved in detoxification, a great number of neuropeptides and corresponding receptors regulating tick growth, development, and reproduction, and glutathione S-transferase genes playing roles in insecticide resistance and detoxification of multiple xenobiotic factors. This high quality reference genome provides fundamental data for obtaining insights into a variety of aspects of tick biology and developing novel strategies to fight notorious tick vectors of human and animal pathogens.

Clinical value of folate receptor-positive circulating tumor cells in patients with esophageal squamous cell carcinomas: a retrospective study.

BACKGROUND: The aim of the study is to explore the role of preoperative folate receptor-positive circulating tumor cell (FR+CTC) levels in predicting disease-free survival (DFS) and overall survival (OS) in patients with esophageal squamous cell carcinomas (ESCC). METHODS: Three ml blood samples were prospectively drawn from ESCC patients, and ligand-targeted polymerase chain reaction (LT-PCR) was used for the quantification of FR+CTCs. Other serum indicators were measured by traditional methods. Clinicopathological characteristics were obtained from the hospital medical record system, DFS and OS data were obtained by follow-up. The correlation between clinico-pathological characteristics, DFS, and OS and FR+CTCs were analyzed, respectively. Risk factors potentially affecting DFS and OS were explored by Cox regression analysis. RESULTS: there were no significant correlations between FR+CTCs and patient age, sex, albumin, pre-albumin, C-reactive protein (CRP), ferritin and CRP/Albumin ratio, tumor size, grade of differentiation, lymph node metastasis, TNM stage, perineural invasion/vessel invasion (all P > 0.05). Nevertheless, preoperative FR+CTCs were an independent prognostic factor for DFS (HR 2.7; 95% CI 1.31-, P = 0.007) and OS (HR 3.37; 95% CI 1.06-, P = 0.04). DFS was significantly shorter for patients with post-operative FR+CTCs ≥ 17.42 FU/3ml compared with patients < 17.42 FU/3ml (P = 0.0012). For OS, it was shorter for patients with FR+CTCs ≥ 17.42 FU/3ml compared with patients < 17.42 FU/3ml, however, the difference did not reach statistical significance (P = 0.51). CONCLUSIONS: ESCC patients with high FR+CTCs tend to have a worse prognosis. FR+CTCs may monitor the recurrence of cancers in time, accurately assess patient prognosis, and guide clinical decision-making. TRIAL REGISTRATION: The study was approved by the Sichuan Cancer Hospital & Institute Ethics Committee (No. SCCHEC-02-2022-050).

Site-Selective Synthesis of Antitumor C5-Aminated Indoles via Neighboring Aldehyde Group Assisted Catellani Reaction.

A palladium/norbornene (NBE) cooperative catalytic system was developed to access C5-aminated indoles, starting from readily available C4-idonated indoles. Good yields and exclusive site selectivity were achieved for a broad substrate scope, including drug molecule core architectures. Control experiments found that both aldehyde on the C3 position and sulfonyl protecting group on the N1 position were vital for the transformation. Preliminary bioactivity evaluation identified a promising leading compound 3af with potent antitumor proliferative activity against several cancer cells.

Interferon-stimulated gene 15 facilitates BTV replication through interacting with the NS1 protein.

Bluetongue virus (BTV) infection effectively activates the innate immune response, followed by the expression of interferon (IFN) and multiple interferon-stimulated genes (ISGs). ISG15 is one of the most induced ISGs, and often plays a role in inhibiting virus replication. This study aims to explore the role and specific mechanisms of ovine ISG15 (oISG15) in BTV infection. We found that the transcription level of oISG15 was upregulated in a time-dependent and BTV multiplicity of infection-dependent manner. The overexpression of exogenous oISG15 enhances BTV replication, whereas the knockdown of endogenous oISG15 inhibits BTV replication. The viral protein in wild-type oISG15-overexpressed cells and ISGylation defective oISG15-overexpressed cells have no significant differences, which indicated that oISG15 promoted BTV replication in an ISGylation-independent manner. A co-immunoprecipitation assay showed that four viral BTV proteins-VP3, VP4, VP5, and NS1-interacted with oISG15. We also found that the VP4 and NS1 proteins associated with ubiquitin via co-immunoprecipitation, and that oISG15 overexpression improved the stability of both proteins. Further results showed that the degradation of NS1 was involved in lysine 63-linked polyubiquitin. This suggested that oISG15 may interfere with NS1 degradation via the autophagy pathway. This study provides new insights on the interaction between BTV and ISG15, and enriches our understanding of the regulation and biological function of ISG15 with virus replication.

Improved analysis ZIC-HILIC-HCD-Orbitrap method for mapping the glycopeptide by mass spectrometry.

Glycosylation is one of the most common post-translational modifications (PTMs). Protein glycosylation analysis is the bottleneck to deeply understand their functions. At present, the LC-MS analysis of glycosylated post-translational modification is mainly focused on the analysis of glycopeptides. However, the factors affecting the identification of glycopeptides were not fully elucidated. In the paper, we have carefully studied the factors, e.g., HILIC materials, search engines, protein amount, gradient duration, extraction solution, etc. According to the results, HILIC materials were the most important factors affecting the glycopeptides identification, and the amphoteric sulfoalkyl betaine stationary phase enriched glycopeptides 6-fold more compared to the amphiphilic ion-bonded fully porous spherical silica stationary phase. We explored the influence of the extraction solutions on glycan identification. Comparing sodium dodecyl sulfate (SDS) and urea (UA), the results showed that N-glycolylneuraminic acid (NeuGc) type of glycan content was found to be increased 1.4-fold in the SDS compared to UA. Besides, we explored the influence of the search engine on glycopeptide identification. Comparing pGlyco3.0 and MSFragger-Glyco, it was observed that pGlyco3.0 outperformed MSFragger-Glyco in identifying glycopeptides. Then, using our optimized method we found that there was a significant difference in the distribution of monosaccharide types in plasma and brain tissue, e.g., the content of NeuAc in brain was 5-fold higher than that in plasma. To importantly, two glycoproteins (Neurexin-2 and SUN domain-containing protein 2) were also found for the first time by our method. In summary, we have comprehensively studied the factors influencing glycopeptide identification than any previous research, and the optimized method could be widely used for identifying the glycoproteins or glycolpeptides biomarkers for disease detection and therapeutic targets.

Resected lymph nodes and survival of patients with esophageal squamous cell carcinoma: an observational study.

BACKGROUND: The incidence and mortality of esophageal cancer are high. Therefore, the authors aimed to investigate how the number of dissected lymph nodes (LNs) during esophagectomy for esophageal squamous cell carcinoma impacts overall survival (OS), particularly that of patients with positive LNs. MATERIALS AND METHODS: Data from 2010 to 2017 were obtained from the Sichuan Cancer Hospital and Institute Esophageal Cancer Case Management Database. Participants were divided into two groups: patients with negative lymph nodes (N0) and patients with positive lymph nodes (N+). The median number of resected LNs during surgery was 24; therefore, patients with 15-23 and those with 24 or more resected LNs were assigned to subgroups A and B, respectively. RESULTS: After a median follow-up of 60.33 months, 1624 patients who underwent esophagectomy were evaluated; 60.53 and 39.47% had a pathological diagnosis of N+ or N0, respectively. The median OS was 33.9 months for the N+ group; however, the N0 group did not achieve the median OS. The mean OS was 84.9 months. In the N+ group, the median OS times of subgroups A and B were 31.2 and 37.1 months, respectively. The OS rates at 1, 3, and 5 years were 82, 43, and 34%, respectively, for subgroup A of the N+ group; they were 86, 51, and 38%, respectively, for subgroup B of the N+ group. Subgroups A and B of the N0 group exhibited no statistically significant differences. CONCLUSION: Increasing the number of LNs harvested during surgery to 24 or more could improve the OS of patients with positive LNs but not that of patients with negative LNs.

Comparative genomics reveals unique features of two Babesia motasi subspecies: Babesia motasi lintanensis and Babesia motasi hebeiensis.

Parasites of the Babesia genus are prevalent worldwide and infect a wide diversity of domestic animals and humans. Herein, using Oxford Nanopore Technology and Illumina sequencing technologies, we sequenced two Babesia subspecies, Babesia motasi lintanensis and Babesia motasi hebeiensis. We identified 3,815 one-to-one ortholog genes that are specific to ovine Babesia spp. Phylogenetic analysis reveals that the two B. motasi subspecies form a distinct clade from other piroplasmas. Consistent with their phylogenetic position, comparative genomic analysis reveals that these two ovine Babesia spp. share higher colinearity with Babesia bovis than with Babesia microti. Concerning the speciation date, B. m. lintanensis split from B. m. hebeiensis approximately 17 million years ago. Genes correlated to transcription, translation, protein modification and degradation, as well as differential/specialized gene family expansions in these two subspecies may favor adaptation to vertebrate and tick hosts. The close relationship between B. m. lintanensis and B. m. hebeiensis is underlined by a high degree of genomic synteny. Compositions of most invasion, virulence, development, and gene transcript regulation-related multigene families, including spherical body protein, variant erythrocyte surface antigen, glycosylphosphatidylinositol anchored proteins, and transcription factor Apetala 2 genes, is largely conserved, but in contrast to this conserved situation, we observe major differences in species-specific genes that may be involved in multiple functions in parasite biology. For the first time in Babesia spp., we find abundant fragments of long terminal repeat-retrotransposons in these two species. We provide fundamental information to characterize the genomes of B. m. lintanensis and B. m. hebeiensis, providing insights into the evolution of B. motasi group parasites.

Effects of Valine and Urea on Carbon and Nitrogen Accumulation and Lignin Content in Peach Trees.

Nitrogen availability and uptake levels can affect nutrient accumulation in plants. In this study, the effects of valine and urea supplementation on the growth of new shoots, lignin content, and carbon and the nitrogen metabolism of 'Ruiguang 39/peach' were investigated. Relative to fertilization with urea, the application of valine inhibited shoot longitudinal growth, reduced the number of secondary shoots in autumn, and increased the degree of shoot lignification. The application of valine also increased the protein level of sucrose synthase (SS) and sucrose phosphate synthase (SPS) in plant leaves, phloem, and xylem, thereby increasing the soluble sugar and starch content. It also resulted in an increase in nitrate reductase (NR), glutamine synthase (GS), and glutamate synthase (GOGAT) protein levels, with an increase in plant contents of ammonium nitrogen, nitrate nitrogen, and soluble proteins. Although urea application increased the protein level of carbon- and nitrogen-metabolizing enzymes, the increase in plant growth reduced the overall nutrient accumulation and lignin content per unit tree mass. In conclusion, the application of valine has a positive effect on increasing the accumulation of carbon and nitrogen nutrients in peach trees and increasing the lignin content.