BACKGROUND:Oxaliplatin (OXA) is widely used in the treatment of gastrointestinal malignancies such as colorectal cancer. However, oxaliplatin-induced peripheral neuropathy (OIPN) is a common and distinctive adverse effect, with a high incidence rate. Characterized by numbness and paresthesia in the extremities, OIPN is dose-limiting, often irreversible, and significantly impacts patients' quality of life. Current assessment relies primarily on subjective symptoms, and effective predictive models are lacking. METHODS:This single-center retrospective cohort study included 829 colorectal cancer patients receiving oxaliplatin chemotherapy. Fourteen core features were screened from 104 potential variables using Lasso regression, Boruta algorithm, Recursive Elimination Feature with Cross-Validation (REFCV), and Gradient Boosting Decision Trees (GBDT). Five machine learning models were developed and evaluated. Model optimization was performed using fivefold cross-validation, and performance was assessed via metrics including the area under the receiver operating characteristic curve (AUC), calibration curve, and decision curve analysis (DCA). SHAP (SHapley Additive exPlanations) analysis was employed to interpret the model, and an online risk calculator was developed. RESULTS:The GBDT model demonstrated the best performance, with an AUC of 0.997 (95% CI: 0.994-1.000) in the training set, 0.908 (0.854-0.962) in the validation folds, and 0.892 (0.837-0.947) in the internal test set. High calibration accuracy was observed, and DCA showed significant net benefit. SHAP analysis identified cumulative oxaliplatin dose (Total OXA), body mass index (BMI), carcinoembryonic antigen (CEA), apolipoprotein A1 (APOA-1), Sex, and cold exposure (ETCO) as the top six core predictors for OIPN, with total OXA exhibiting the most significant and dose-dependent impact. CONCLUSION:This study demonstrates that the GBDT machine learning model effectively predicts OIPN risk in colorectal cancer patients. Combined with SHAP analysis, the model's interpretability is enhanced. The developed online calculator provides a reliable tool for early clinical identification of high-risk patients and personalized intervention strategies.

BackgroundSintilimab-induced rash is a significant clinical challenge in lung cancer treatment, often necessitating therapy interruption or discontinuation and thereby compromising patient outcomes. The underlying mechanisms of this adverse event remain poorly understood. This study aimed to investigate potential predictive biomarkers and mechanisms of sintilimab-induced rash through metabolomic profiling.MethodsA total of 55 patients with lung cancer who received sintilimab were enrolled, including 32 who developed rash and 23 matched controls without rash. Blood samples were collected before sintilimab infusion and at rash onset. Comprehensive clinical data were recorded. Untargeted metabolomic analysis of plasma was performed using ultra-high-performance liquid chromatography–tandem mass spectrometry (UHPLC–MS/MS). Differential metabolites were identified and analyzed using pathway enrichment, univariate analysis (AUC ≥0.800), and SHAP analysis.ResultsNo significant differences were observed between groups in demographic characteristics or most clinical parameters. However, the rash group exhibited significantly elevated total bile acids glucose (GLU), and basophil percentage (BAS%), along with reduced AST/ALT ratio, alkaline phosphatase lactate dehydrogenase phosphorus (P), neutrophil count (NEU), and high-sensitivity C-reactive protein (hsCRP) (P < 0.05). Metabolomic analysis identified 92 differentially expressed metabolites. Pathway enrichment revealed alterations in oxytocin signaling, GnRH signaling, platelet activation, FcγR-mediated phagocytosis, retrograde endocannabinoid signaling, pantothenate and CoA biosynthesis, FcεRI signaling, and aldosterone synthesis and secretion. Univariate analysis identified 25 metabolites with high predictive value (AUC ≥0.800), and SHAP analysis highlighted 20 metabolites. Cross-comparison identified five overlapping metabolites: N,N,N-trimethyl-L-histidine, laurolactam, 2-naphthalenesulfonic acid, limonenecarboxylic acid, and N-lauroylsarcosine.ConclusionDistinct clinical and metabolomic alterations are associated with sintilimab-induced rash in lung cancer patients. The identified differential metabolites may serve as predictive biomarkers and potential therapeutic targets, providing new insights for clinical management and mechanistic research into immune-related adverse events.

Background:Oxaliplatin-induced peripheral neuropathy (OIPN) is an important adverse reaction in patients with gastric cancer treated with oxaliplatin, but there is no objective biomarkers for changes in OIPN in patients after multiple rounds of chemotherapy. This research aimed to identify serum metabolic biomarkers using longitudinal untargeted metabolomics for early detection of OIPN progression in gastric cancer patients receiving repeated chemotherapy. Methods:Eighty-four serum samples of the same gastric cancer patient (n=42) before and after receiving oxaliplatin chemotherapy twice were collected. The metabolic profiles of serum samples were acquired using an untargeted metabolomics approach based on ultra-high-performance liquid chromatography-Q-Exactive Orbitrap tandem mass spectrometry (UHPLC-Q-Exactive Orbitrap-MS/MS). Multivariate statistical analysis, receiver operating characteristic (ROC) curve analysis, SHapley Additive exPlanations (SHAP) analysis, and pathway enrichment analysis were used to identify potential biomarkers and metabolic pathways. Results:A total of 16 differentially expressed metabolites (DEMs) were screened in discovery set, which belonged to amino acids and derivatives, lipids and derivatives, organic acids and derivatives, and others, mainly involved in amino acid metabolism, lipid metabolism, and nervous system metabolism. Four DEMs (including norepinephrine, 9,10-DHOME, 5-hydroxyindoleacetic acid, and procollagen 5-hydroxy-lysine) showed certain predictive ability for OIPN in the same gastric cancer patient before and after receiving oxaliplatin chemotherapy twice. Thirty-three DEMs were discovered in validation set, notably, norepinephrine emerged as a metabolite exhibiting consistent and notable statistical differences in both the discovery and validation sets. Conclusions:These findings demonstrate the alterations of serum metabolic profiles in patients before and after receiving oxaliplatin chemotherapy, which may deliver valuable biomarkers for early identification and outcome prediction of OIPN progression.

Background Oxaliplatin, a third-generation platinum-based antineoplastic agent, is widely used in the treatment of gastrointestinal malignancies such as colorectal cancer. However, oxaliplatin-induced peripheral neuropathy (OIPN) is a common and distinctive adverse effect, with a high incidence rate. Characterized by numbness and paresthesia in the extremities, OIPN is dose-limiting, often irreversible, and significantly impacts patients' quality of life. Current assessment relies primarily on subjective symptoms, and effective predictive models are lacking. Methods This single-center retrospective cohort study included 829 colorectal cancer patients receiving oxaliplatin chemotherapy. Fourteen core features were screened from 104 potential variables using Lasso regression, Boruta algorithm, REFCV, and GBDT. Five machine learning models (XGBoost, Random Forest, AdaBoost, GBDT, and GNB) were developed and evaluated. Model optimization was performed using 5-fold cross-validation, and performance was assessed via metrics including the area under the receiver operating characteristic curve (AUC), calibration curve, and decision curve analysis (DCA). SHAP analysis was employed to interpret the model, and an online risk calculator was developed. Results The GBDT model demonstrated the best performance, with an AUC of 0.997 (95% CI: 0.994–1.000) in the training set, 0.908 (0.854–0.962) in the validation set, and 0.892 (0.837–0.947) in the external test set. High calibration accuracy was observed, and DCA showed significant net benefit. SHAP analysis identified Total-OXA, BMI, CEA, APOA-1, Sex, and ETCO as the top six core predictors for OIPN, with Total-OXA exhibiting the most significant and dose-dependent impact. Conclusion This study demonstrates that the GBDT machine learning model effectively predicts OIPN risk in colorectal cancer patients. Combined with SHAP analysis, the model's interpretability is enhanced. The developed online calculator provides a reliable tool for early clinical identification of high-risk patients and personalized intervention strategies.

Background:Oxaliplatin-induced peripheral neuropathy (OIPN) poses a significant challenge for patients with colorectal tumor, often resulting in treatment interruption or discontinuation and subsequent treatment failure. Herein, a longitudinal untargeted metabolomic study to reveal the metabolomic profiles and biomarkers associated with the progression of OIPN. Methods:A prospective cohort of 129 colorectal cancer patients receiving oxaliplatin-based chemotherapy was stratified into four OIPN severity grades (Level 0-3). Serum samples underwent untargeted LC-MS/MS metabolomic analysis, detecting 521 metabolites. Multivariate statistical models and SHAP-guided random forest algorithms were employed to prioritize biomarkers. Machine learning validation included six classifiers assessed via ROC-AUC. Results:The cumulative dose of Oxaliplatin chemotherapy plays an important role in OIPN. At the same time, our findings implied that the occurrence of OIPN may be associated with the progression of the disease and the patients' tumor markers (CEA, CA19-9, CA72-4), as well as immune response and inflammation (ANC, PLT), and metabolic and liver function abnormalities (GGT and UA) (P<0.05).Multivariate statistical analysis combined with SHAP-guided machine learning identified six biomarkers, including thiabendazole, 1-methylxanthine, imidazol-5-yl-pyruvate, 5-hydroxypentanoic acid, spermidine, and 4'-oxolividamine that consistently distinguished OIPN patients (Level 1-3) from non-OIPN controls (Level 0). Machine learning models, validated across six classifiers, demonstrated near-perfect discrimination for early-stage OIPN (AUC nearly 1). However, differentiation between intermediate OIPN grades (Level 1 vs 2, Level 1 vs 3, Level 2 vs 3) yielded lower predictive accuracy (AUC: 0.549-0.843), likely due to cohort size limitations and reliance on subjective sensory-based grading. Pathway enrichment analysis highlighted dysregulation in ABC transporters, central carbon metabolism in cancer, amino acid metabolism, and linoleic acid metabolism, suggesting potential roles in OIPN pathogenesis. Conclusions:These findings suggest that the selected biomarkers could serve as a foundation for the prediction and management of OIPN in colorectal cancer patients.

The composition and profile of amino acids in Rubus chingii (R. chingii) Hu serve as critical indicators of its nutritional quality. A comprehensive understanding of the amino acid metabolism within R. chingii is instrumental in the formulation and innovation of functional foods derived from this species. Utilizing advanced techniques such as wide-ranging untargeted metabolomics, transcriptome analysis, interaction network mapping, heat map analysis, and quantitative real-time PCR, we conducted a comprehensive assessment of the quality attributes across four distinct developmental stages of R. chingii. Our meticulous analysis uncovered a rich tapestry of 76 distinct amino acids and their derivatives within the developmental stages of R. chingii. The spectrum of essential amino acids was not only broad but also displayed a high degree of variety. Notably, leucine, lysine, and phenylalanine stood out as the most abundant amino acids, underscoring their significant presence throughout the growth cycle of R. chingii. The proportion of essential amino acids relative to the total amino acid content in R. chingii exhibited a notable trajectory of change throughout its developmental stages. It began with 30.92% in the immature green phase, advanced to 31.04% during the transition from green to yellow, peaked at 33.62% in the yellow to red stage, and then moderated to 30.43% in the full red phase. This pattern suggests a strategic modulation of amino acid composition, aligning with the evolving nutritional requirements and metabolic shifts as the fruit matures. Concurrent analysis of interaction networks and heat maps, alongside comprehensive profiling of amino acid metabolism and transcriptomic examination, was conducted to elucidate the intricate dynamics of cellular processes. The results showed that seven differentially expressed genes (DEGs) played important roles in amino acid metabolism, including PFK, BCAT1, TSB, ASA, ACO, TOM2AH3, and BCAT2. The expression patterns of seven DEGs conformed closely to the findings revealed by the preceding RNA-seq analysis. In this investigation, we elucidated the regulatory mechanisms underlying amino acid metabolism across the four distinct developmental stages of R. chingii through comprehensive amino acid profiling and transcriptomic analysis. These insights lay the groundwork for the development of novel functional food applications utilizing R. chingii.

Oxapliplatin-induced peripheral neuropathy (OIPN) is a significant adverse effect encountered in patients with colorectal cancer undergoing oxaliplatin therapy. However, the pathogenesis of OIPN remains unclear. This study aimed to identify potential diagnostic biomarkers for OIPN and discover the metabolic pathways associated with the disease. Serum samples were collected from 218 subjects, including patients with OIPN and control (CONT). The metabolite profiles were analyzed using nontargeted liquid chromatography-mass spectrometry (LC-MS) serum metabolomics method. Subsequently, differentially altered metabolites were identified and evaluated through multivariate statistical analyses. In this study, patients with OIPN and CONT were distinguished by ten significant metabolites. The levels of racemethionine, O-acetylcarnitine, stearolic acid, aminoadipic acid, iminoarginine, galactaric acid, and all-trans-retinoic acid were increased, whereas the levels of 3-methyl-L-tyrosine, 5-aminopentanoic acid, and erythritol compared were found to be diminished in patients with OIPN when compared to the CONT. Through receiver operating characteristic (ROC) curve analysis, racemethionine, stearolic acid, 5-aminopentanoic acid, erythritol, aminoadipic acid, and all-trans-retinoic acid were pinpointed as promising biomarkers for OIPN. Significantly altered pathways included amino acids (arginine biosynthesis, beta-alanine metabolism, arginine and proline metabolism, alanine, aspartate and glutamate metabolism, lysine degradation, and phenylalanine, tyrosine and tryptophan biosynthesis), lipid (linoleic acid metabolism and the biosynthesis of unsaturated fatty acids), and energy metabolism. This study, by identifying serum biomarkers and dissecting metabolic pathways, offers a groundbreaking perspective on the susceptibility mechanisms underlying OIPN. It stands as an invaluable resource for the adjunctive diagnosis of OIPN, with the potential to diminish the incidence of adverse reactions and to enhance the objectivity and reliability of clinical diagnoses of OIPN.

Oxaliplatin (L-OHP), a third-generation platinum-based anti-tumor drug, finds widespread application in the first-line treatment of metastatic colorectal cancer. Despite its efficacy, the drug's usage is curtailed by a litany of side effects, with L-OHP-induced peripheral neuropathy (OIPN) being the most debilitating. This condition can be classified into varying degrees of severity. Employing serum metabolomics, a high-sensitivity, high-throughput technique, holds promise as a method to identify biomarkers for clinical assessment and monitoring of OIPN patients across different severity levels. In our study, we analyzed serum metabolites in patients with different OIPN levels using ultra-performance liquid chromatography-high resolution mass spectrometry. By employing statistical analyses and pathway enrichment studies, we aimed to identify potential biomarkers and metabolic pathways. Our findings characterized the serum metabolic profiles of patients with varying OIPN levels. Notably, pathway analysis revealed a significant correlation with lipid metabolism, amino acid metabolism, and energy metabolism. Multivariate statistical analysis and receiver operator characteristic curve evaluation pointed to anhalamine and glycochenodeoxycholic acid as potential biomarkers for OIPN C and A, which suggest that serum metabolomics may serve as a potent tool for exploring the metabolic status of patients suffering from diverse diseases and for discovering novel biomarkers.

The traditional Chinese herb Rubus chingii Hu (R. chingii) is widely used in clinical practice due to its beneficial effects. Flavonoids are the important class of pharmacological substances in R. chingii, however, the molecular mechanism underlying the differences in active flavonoid contents in R. chingii at different developmental stages remain poorly understood. In this experiment, we selected four developmental stages (GG, GY, YR, RR) of R. chingii as the research material. We studied the untargeted and targeted metabolic profiles of flavonoids in different periods of R. chingii, combining full-length and comparative transcriptome analyses. Functional analyses were conducted on genes implicated in flavonoid differences. GG and RR displayed relatively higher and lower contents of flavonols, flavones, flavanols, flavanones, and isoflavonoid, respectively. RNA-seq analyses showed structural genes such as RcPAL, RcC4H, Rc4CL, RcCHS, RcCHI, RcF3H, RcF3'H, and RcFLS in flavonoid biosynthesis pathway were upregulated in GG, which were essential for the accumulation flavanones, flavones, and flavonols (effective components). qRT-PCR analyses investigated that six structural genes RcCHI, RcF3H, 2 RcCHS, and 2 Rc4CL, two TFs RcMYB308 and RcMYB123 had a consistent expression pattern with which in transcriptome. Also, an interaction network showed that the RcMYB308 could positively regulate Ka3R, Qu, Qu3G, AS, Hy, Ti through RcF3H. Furthermore, Subcellular localization analysis revealed that RcMYB308 was localization to the nucleus. In tobacco, RcMYB308 was overexpressed, resulting in higher flavonoids, RcF3H, RcF3'H, RcCHI, and RcFLS. RcMYB308 upregulated RcF3H in dual-luciferase assays. These results provide new insights for further understanding the molecular mechanism regulating flavonol biosynthesis in R. chingii fruit, and also provide a potential MYB regulator for molecular breeding of R. chingii.

Apocyni Veneti Folium (AVF) is a salt-tolerant medicinal halophyte and soil salinity is a main stress affecting its quality. Molecular bases involved in quality evaluation and ecological adaptations to abiotic constraints can be explored using omics tools. In the study, AVF was treated with four levels of salt stress (control, 100, 200 and 300 mM NaCl, respectively) and subjected to de novo-based RNA-sequencing. We constructed GO and KEGG analysis on the obtained DEGs. After molecular phylogenetic analysis, we isolated and characterized one representative and up-regulated candidate gene AvUGT (Tr_AVENL_25169) encoding UDP-glucosyltransferase under salt stress. Results showed that the obtained clean reads were assembled into a total of 54,276 high-quality unigenes. Notably, specific genes related to flavonoid glucoside biosynthesis and salt-tolerant regulation, such as genes encoding transcription factors, transporters, glucosyltransferase, heat shock protein and plant hormone signal transduction-related protein, preferentially up-regulated by low level of salt. Combined with previous metabonomic analysis, the results revealed key genes that contribute to elucidate the reduced salt toxicity in AVF. Furthermore, the transcript profiles of UGT genes were consistent with the accumulation of flavonoid glycosides in AVF; the candidate gene AvUGT probably plays a critical role in biosynthesis of flavonoid glucosides in response to salt environment. These results provided a basis for future research on the regulatory mechanism of salt stress of medicinal halophyte AVF.

The fruits of Rubus chingii Hu have high medicinal and nutritional values. However, the metabolite profiles of R. chingii, especially the alterations during different development stages of fruit, have not been comprehensively analyzed, hindering the effective utilization of the unique species. In this study, we comprehensively analyzed the metabolites of R. chingii fruit at four developmental stages using systematic untargeted and targeted liquid chromatography-mass spectrometry metabolomics analysis and identified 682 metabolites. Significant changes were observed in metabolite accumulation and composition in fruits during the different developmental stages. The contents of the index components, kaempferol-3-O-rutinoside and ellagic acid, were the highest in immature fruit. The analysis identified 64 differentially expressed flavonoids and 39 differentially expressed phenolic acids; the accumulation of most of these differentially expressed metabolites decreased with the developmental stages of fruit from immaturity to maturity. These results confirmed that the developmental stages of fruit are a critical factor in determining its secondary metabolite compositions. This study elucidated the metabolic profile of R. chingii fruit at different stages of development to understand the dynamic changes in metabolites.

Background: Lung cancer remains one of the leading cancers with increasing mortality rates in the world, the clinicians in our hospital summarized “Fu Zheng Fang (FZF)” as Chinese medicine prescription with good therapeutic effect and low adverse reactions to treat lung cancer. Objective: To give an in-depth study on the essence and internal rules of the effect of FZF. Method: Serums samples from twenty lung cancer patients and whom accepted FZF were subjected to metabolomic profiling using UPLC-Q-Exactive-MS combined with multivariate statistical analysis. Result: 17 significantly differential metabolites were found in NC and FZF group, which were mainly participated in phenylalanine metabolism, apelin signaling pathway, sphingolipid signaling pathway, and others. Seven metabolites were increased in FZF group relative to NC group, while ten metabolites were decreased in FZF group, most of them were proved to be consistent with previous experiments. This indicated that FZF had a definite therapeutic effect on lung cancer by regulating the contents of metabolites through amino acid metabolism, metabolism of cofactors and vitamins, carbohydrate metabolism, and cancer. Conclusion: This study provides a deeper insight into the comprehensive understanding of molecular mechanisms of FZF treatment against lung cancer.

Grapes are one of the world's largest fruit crops, which are rich in nutrients and taste. Summer Black, Gui Fei, Kyoho Grape, Giant Rose, Shine Muscat, and Rosario Bianco are the six most popular table grapes in Wuxi city, Jiangsu province. Owing to the lack of comprehensive investigations of metabolites in table grapes, the metabolic causes of differences in their taste are unknown. In this study, metabolites of six table grapes were profiled using ultra-high-performance liquid chromatography-Q-Exactive Orbitrap tandem mass spectrometry combined with multivariate analysis. Orthogonal partial least squares discriminant analysis discriminated among the metabolites of these varieties. Metabolic pathway analysis revealed that carbohydrate and amino acid metabolisms were highly conserved among these varieties. Our results suggest that the taste differences in the six table grape varieties can be explained by variations in composition and abundance of carbohydrates, organic acids, amino acids, and polyphenols. This study provides comprehensive insights into the underlying metabolic causes of taste variation in table grapes.

目的:评价临床药师参与万古霉素治疗药物监测对患者疗效与安全性的影响,以促进万古霉素的规范、合理使用.方法:选取2016年6月—2020年6月江南大学附属医院收治的使用万古霉素治疗且行治疗药物监测的102例确诊或疑似耐甲氧西林金黄色葡萄球菌(methicillin-resistant Staphylococcus aureus,MRSA)感染患者作为研究对象,根据是否实施临床药师干预,将其分为干预组(n=50)和非干预组(n=52);考察患者的科室分布与感染类型情况、不同性别患者的年龄和万古霉素血药谷浓度情况,以及2组患者不同万古霉素血药谷浓度范围内的疗效和治疗期间的不良反应发生率.结果:102患者主要分布在呼吸内科36例(占35.29％)、重症医学科25例(占24.51％)和肾内科10例(占9.80％),而其主要的感染部位为肺部(75例,占73.53％)和血液系统(15例,占14.71％);干预组患者的总有效率和治疗窗内有效率均高于非干预组,但经组间比较其差异均无统计学意义(P＞0.05);2组患者治疗期间的不良反应发生率经比较其差异无统计学意义(P＞0.05),但干预组患者无肾功能不全发生.结论:临床药师针对确诊或疑似MRSA感染开展万古霉素治疗药物监测,有助于提高患者的疗效,减少肾损伤的发生.

Background: Fu Zheng Fang (FZF) is an important Chinese medicine prescription for tumor treatment in our hospital, which has two different types, traditional Chinese medicine (TCM) decoction pieces and TCM formula granules. Objective: This study aimed to determine the effective composition of the drug FZF. Methods: In this research, FZF decoction pieces and FZF formula granules were collected and their composition, determined by HPLC-Q-Exactive Orbitrap/MS, and multivariate statistical analysis, was applied to distinguish differential metabolite patterns between two groups. Results: A clear cut difference in the composition of the two groups was observed. 124 differential chemical compositions could be identified in positive mode, while 59 differential chemical compositions could be identified in negative mode. The differential chemical compositions were mainly concentrated in flavonoids, organic acids, fatty acids, amino acids compounds, and presenting different change rules, mainly involved in the flavonoid biosynthesis, flavone and flavonol biosynthesis two metabolic pathways. Conclusion: This study provides basic information that may be of use in the formulation of the drug in different dosages and in the examination of their efficacy.

Background. Pseudostellariae Radix (PR) is an important traditional Chinese herbal medicine with vast clinical consumptions, which has two different dosage forms, PR decoction pieces and PR formula granules. However, these two forms are bound to have an impact on the accumulation of the effective components in PR, so the effectiveness of clinical use cannot be guaranteed. Objective. To determine the effective composition of PR. Methods. In this research, PR decoction pieces and formula granules were collected, and their composition was detected by HPLC-Q-Exactive Orbitrap/MS; multivariate statistical analysis was used to distinguish differential metabolites between PR decoction pieces and formula granules. Results. A clear cut difference in the composition of the two groups was observed. 98 differential chemical constituents could be identified in the positive mode, while 52 differential chemical compositions could be identified in the negative mode. The differential chemical compositions were mainly concentrated in flavonoids, organic acids, fatty acids, and amino acids and present different change rules, mainly involved in the isoquinoline alkaloid biosynthesis metabolic pathways. Conclusions. This study provides basic information to reveal the influence law of different dosage forms on the metabolite synthesis and quality formation mechanism of PR.

Prunella vulgaris L. is a moderately salt tolerant plant commonly found in China and Europe, whose spica (Prunellae Spica) has been used as a traditional medicine. The scant transcriptomic and genomic resources of Prunellae Spica have greatly hindered further exploration of the underlying salt tolerance mechanism of this species. To clarify the genetic basis of its salt tolerance, high-throughput sequencing of mRNAs was employed for de novo transcriptome assembly differential expression analysis of Prunellae Spica under salt stress. 118,664 unigenes were obtained by assembling pooled reads from all libraries with 68,119 sequences annotated. A total of 3857 unigenes were differentially expressed under low, medium and high salt stress, including 2456 up-regulated and 1401 down-regulated DEGs, respectively. Gene ontology analysis revealed that salt stress-related categories involving 'catalytic activity', 'binding', 'metabolic process' and 'cellular process' were highly enriched. KEGG pathway annotation showed that the DEGs from different salt stress treatment groups were mainly enriched in the pathways of translation, signal transduction, carbohydrate metabolism, energy metabolism, lipid metabolism and amino acid metabolism, accounting for over 60% of all DEGs. Finally, it showed that the results of quantitative real-time polymerase chain reaction (qRT-PCR) analysis for 10 unigenes that randomly selected were significantly consistent with RNA-seq data, which further assisted in the selection of salt stress-responsive candidate genes in Prunellae Spica. This study represents a significant step forward in understanding the salt tolerance mechanism of Prunellae Spica, and also provides a significant transcriptomic resource for future work.

Soil salinity is a major abiotic stress that limits plant growth and productivity. Understanding the mechanisms of plant salinity tolerance can facilitate engineering for quality improvement. Apocynum venetum L. exhibits tolerance to salinity. Due to the lack of a genomic database, RNA-seq based transcriptomics and isobaric tag for relative and absolute quantitation (iTRAQ) based proteomic profiles of Apocyni Veneti Folium (leaves of Apocynum venetum L.) exposure to four levels of salt treatments (0, 100, 200 and 300 mM NaCl, respectively) were performed. A total of 143, 162 and 167 differentially expressed proteins (DEPs) were found between salt-treated Apocyni Veneti Folium compared with control, respectively. They were mainly involved in carbohydrate and energy metabolism, biosynthesis of metabolites and signal transduction. Furthermore, results showed that carbon and nitrogen metabolisms were altered under salt stress; low and moderate levels of salt stress enhanced photosynthetic functions and ramped up carbohydrate metabolism. However, severe salt stress depressed biosynthesis of secondary metabolites, consistent with the metabolomics results. It is worth emphasizing that some key salt-responsive proteins, such as dehydrin 1, annexin, pathogenesis-related protein, prolyl oligopeptidase, peroxidase, cinnamyl alcohol dehydrogenase, 4-hydroxycinnamoyl-CoA ligase 3, cytochrome P450 CYP73A120, were screened. These novel proteins provide a good starting point for further research into their functions using genetic or other approaches. In addition, a weak correlation between the abundance of DEPs and the corresponding differentially expressed genes highlighted the effect of post-transcriptional modifications and the importance of employing proteomics and transcriptomics to analyze global protein level changes. In conclusion, the protein profiles indicate that halophyte uses a multipronged approach to overcome salt stress, and provides some novel information on revealing the mechanisms of adaption and quality formation.

为探讨不同剂型对太子参代谢物合成积累的影响,采用高效液相色谱-串联四级杆轨道阱质谱(HPLC-Q-Exactive Orbitrap/MS)结合多元统计分析技术对太子参传统中药饮片和配方颗粒的差异化学成分进行研究.基于HPLC-Q-Exactive Orbitrap/MS代谢组学技术,结合软件数据库搜索进行成分鉴定.采用主成分分析(PCA),偏最小二乘法判别分析(PLS-DA)和正交最小二乘法判别分析(OPLS-DA)等方法筛选和鉴定差异化学成分.结果 显示,太子参传统中药饮片和配方颗粒样品中化学成分能够显著区分,在正、负离子模式下分别找到98个和52个差异化学成分,这些差异化学成分主要集中在黄酮、有机酸、脂肪酸、氨基酸类化合物中且呈现不同的变化规律,主要涉及异喹啉生物碱生物合成代谢.该结果可为揭示不同剂型对太子参代谢物合成积累的影响规律提供基础资料.

Background: Xanthium sibiricum is a well-known traditional Chinese medicine (TCM) that has been commonly used to treat rhinitis and related nasal diseases. The aim of this study was to develop a comprehensive analytical method based on high-performance liquid chromatographyelectrospray ionization coupled with triple quadrupole-linear ion trap mass spectrometry (LC-ESIQTRAP- MS/MS) for the simultaneous determination of phenolic acids, anthraquinones, and flavonoids in the aerial part and fruit of Xanthium sibiricum. Methods: The separation was completed on Agilent ZORBAX SB-C18 column (250 × 4.6 mm, 5μm) using methanol and 0.2% (v/v) aqueous formic acid as the mobile phase. The target components were analyzed in negative ion mode with accurate and sensitive multiple reaction monitoring (MRM) mode. Results: The correlation coefficients of all the calibration curves were higher than 0.9994. Relative standard deviations of intra- and inter-day precisions of the eighteen components were all lower than 2.87% and the recoveries were in the range from 97.73% to 101.82%. The validated method was successfully applied to possess forty Xanthium sibiricum samples (Xanthii Herba, Xanthii Fructus, and processed Xanthii Fructus) collected from different places in P. R. China. Furthermore, principal component analysis (PCA) was performed to evaluate and classify the samples according to the contents of the eighteen bioactive components. Conclusion: All the results demonstrated that the developed method was useful and could be applied for the overall assessment of the quality of Xanthii Herba and Xanthii Fructus.