Constructing an efficient and easy-to-operate multigene expression system is currently a crucial part of plant genetic engineering. In this study, a fragment carrying three independent gene expression cassettes and the expression unit of the gene-silencing suppressor protein(RNA silencing suppressor 19 kDa protein, P19) simultaneously was designed and constructed. This fragment was cloned into the commonly used plant expression vector pCAMBIA300, and the plasmid pC1300-TP2-P19 was obtained. Each gene expression cassette consists of different promoters, fusion tags, and terminators. The target gene can be flexibly inserted into the corresponding site through enzymatic digestion and ligation or recombination and fused with different protein tags, which provides great convenience for subsequent detection. The enhanced green fluorescent protein(eGFP) reporter gene was individually constructed into each expression cassette to verify the feasibility of this vector system. The results of tobacco transient expression and laser-confocal microscopy showed that each expression cassette presented independent and normal expression. Meanwhile, the three key enzyme genes in the betanin synthesis pathway, BvCYP76AD, BvDODA1, and DbDOPA5GT, were constructed into the three expression cassettes. The results of tobacco transient expression phenotype, protein immunoblotting(Western blot), and chemical detection of product demonstrated that the three exogenous genes were highly expressed, and the target compound betanin was successfully produced. The above results indicated that the constructed multigene expression system for plants in this study was efficient and reliable and can achieve the co-transformation of multiple plant genes. It can provide a reliable vector platform for the analysis of plant natural product synthesis pathways, functional verification, and plant metabolic engineering.
Nicotiana/metabolism* ; Genetic Vectors/metabolism* ; Gene Expression Regulation, Plant ; Plant Proteins/metabolism* ; Plants, Genetically Modified/metabolism* ; Genetic Engineering/methods* ; Green Fluorescent Proteins/metabolism* ; Gene Expression

Dormant tumor cells constitute a population of cancer cells that reside in a non-proliferative or low-proliferative state, typically arrested in the G0/G1 phase and exhibiting minimal mitotic activity. These cells are commonly observed across multiple cancer types, including breast, lung, and ovarian cancers, and represent a central cellular component of minimal residual disease (MRD) following surgical resection of the primary tumor. Dormant cells are closely associated with long-term clinical latency and late-stage relapse. Due to their quiescent nature, dormant cells are intrinsically resistant to conventional therapies—such as chemotherapy and radiotherapy—that preferentially target rapidly dividing cells. In addition, they display enhanced anti-apoptotic capacity and immune evasion, rendering them particularly difficult to eradicate. More critically, in response to microenvironmental changes or activation of specific signaling pathways, dormant cells can re-enter the cell cycle and initiate metastatic outgrowth or tumor recurrence. This ability to escape dormancy underscores their clinical threat and positions their effective detection and elimination as a major challenge in contemporary cancer treatment. Hypoxia, a hallmark of the solid tumor microenvironment, has been widely recognized as a potent inducer of tumor cell dormancy. However, the molecular mechanisms by which tumor cells sense and respond to hypoxic stress—initiating the transition into dormancy—remain poorly defined. In particular, the lack of a systems-level understanding of the dynamic and multifactorial regulatory landscape has impeded the identification of actionable targets and constrained the development of effective therapeutic strategies. Accumulating evidence indicates that hypoxia-induced dormancy tumor cells are accompanied by a suite of adaptive phenotypes, including cell cycle arrest, global suppression of protein synthesis, metabolic reprogramming, autophagy activation, resistance to apoptosis, immune evasion, and therapy tolerance. These changes are orchestrated by multiple converging signaling pathways—such as PI3K-AKT-mTOR, Ras-Raf-MEK-ERK, and AMPK—that together constitute a highly dynamic and interconnected regulatory network. While individual pathways have been studied in depth, most investigations remain reductionist and fail to capture the temporal progression and network-level coordination underlying dormancy transitions. Systems biology offers a powerful framework to address this complexity. By integrating high-throughput multi-omics data—such as transcriptomics and proteomics—researchers can reconstruct global regulatory networks encompassing the key signaling axes involved in dormancy regulation. These networks facilitate the identification of core regulatory modules and elucidate functional interactions among key effectors. When combined with dynamic modeling approaches—such as ordinary differential equations—these frameworks enable the simulation of temporal behaviors of critical signaling nodes, including phosphorylated AMPK (p-AMPK), phosphorylated S6 (p-S6), and the p38/ERK activity ratio, providing insights into how their dynamic changes govern transitions between proliferation and dormancy. Beyond mapping trajectories from proliferation to dormancy and from shallow to deep dormancy, such dynamic regulatory models support topological analyses to identify central hubs and molecular switches. Key factors—such as NR2F1, mTORC1, ULK1, HIF-1α, and DYRK1A—have emerged as pivotal nodes within these networks and represent promising therapeutic targets. Constructing an integrative, systems-level regulatory framework—anchored in multi-pathway coordination, omics-layer integration, and dynamic modeling—is thus essential for decoding the architecture and progression of tumor dormancy. Such a framework not only advances mechanistic understanding but also lays the foundation for precision therapies targeting dormant tumor cells during the MRD phase, addressing a critical unmet need in cancer management.

Polygonati Rhizoma demonstrates significant potential for addressing both chronic and hidden hunger. The supply of high-quality seedlings is a primary factor influencing the development of the Polygonati Rhizoma industry. Warm water soaking is often used in agriculture to promote the rapid germination of seeds, while its application and molecular mechanism in Polygonati Rhizoma have not been reported. To rapidly obtain high-quality seedlings, this study treated Polygonatum kingianum var. grandifolium seeds with sand storage at low temperatures, warm water soaking, and cultivation temperature gradients. The results showed that the culture at 25 ℃ or sand storage at 4 ℃ for 2 months rapidly broke the seed dormancy of P. kingianum var. grandifolium, while the culture at 20 ℃ or sand storage at 4 ℃ for 1 month failed to break the seed dormancy. Soaking seeds in 60 ℃ warm water further increased the germination rate, germination potential, and germination index. Specifically, the seeds soaked at 60 ℃ and cultured at 25 ℃ without sand storage treatment(Aa25) achieved a germination rate of 78. 67%±1. 53% on day 42 and 83. 40%±4. 63% on day 77. The seeds pretreated with sand storage at 4 ℃ for 2 months, soaked in 60 ℃ water, and then cultured at 25 ℃ achieved a germination rate comparable to that of Aa25 on day 77. Transcriptomic analysis indicated that warm water soaking might promote germination by triggering reactive oxygen species( ROS), inducing the expression of heat shock factors( HSFs) and heat shock proteins( HSPs), which accelerated DNA replication, transcript maturation, translation, and processing, thereby facilitating the accumulation and turnover of genetic materials. According to the results of indoor controlled experiments and field practices, maintaining a germination and seedling cultivation environment at approximately 25 ℃ was crucial for the one-year seedling cultivation of P. kingianum var. grandifolium.
Germination ; Seedlings/genetics* ; Water/metabolism* ; Seeds/metabolism* ; Polygonatum/genetics* ; Temperature ; Plant Proteins/genetics* ; Plant Dormancy

OBJECTIVE: To investigate lymph node metastasis (LNM) in the prostatic anterior fat pad (PAFP) of PCa patients after robot-assisted radical prostatectomy (RARP), and analyze the clinicopathological features and prognosis of LNM in the PAFP. METHODS: We retrospectively analyzed the clinicopathological data on 1 003 cases of PCa treated by RARP in the Department of Urology of PLA General Hospital from January 2017 to December 2022. All the patients underwent routine removal of the PAFP during RARP and pathological examination, with the results of all the specimens examined and reported by pathologists. Based on the presence and locations of LNM, we grouped the patients for statistical analysis, compared the clinicopathological features between different groups using the Student's t, Mann-Whitney U and Chi-square tests, and conducted survival analyses using the Kaplan-Meier and Log-rank methods and survival curves generated by Rstudio. RESULTS: Lymph nodes were detected in 77 (7.7%) of the 1 003 PAFP samples, and LNM in 11 (14.3%) of the 77 cases, with a positive rate of 1.1% (11/1 003). Of the 11 positive cases, 9 were found in the upgraded pathological N stage, and the other 2 complicated by pelvic LNM. The patients with postoperative pathological stage≥T3 constituted a significantly higher proportion in the PAFP LNM than in the non-PAFP LNM group (81.8% ［9/11］ vs 36.2% ［359/992］, P = 0.005), and so did the cases with Gleason score ≥8 (87.5% ［7/8］ vs 35.5% ［279/786］, P = 0.009). No statistically significant differences were observed in the clinicopathological features and biochemical recurrence-free survival between the patients with PAFP LNM only and those with pelvic LNM only. CONCLUSION The PAFP is a potential route to LNM, and patients with LNM in the PAFP are characterized by poor pathological features. There is no statistically significant difference in biochemical recurrence-free survival between the patients with PAFP LNM only and those with pelvic LNM only. Routine removal of the PAFP and independent pathological examination of the specimen during RARP is of great clinical significance.
Humans ; Male ; Prostatectomy/methods* ; Robotic Surgical Procedures ; Lymphatic Metastasis ; Retrospective Studies ; Prognosis ; Prostatic Neoplasms/pathology* ; Adipose Tissue/pathology* ; Prostate/pathology* ; Lymph Nodes/pathology* ; Middle Aged ; Aged

ObjectiveTo improve the quality standard of Yuanhu Zhitong oral liquid in order to strengthen the quality control of this oral liquid. MethodThin layer chromatography（TLC） was used for the qualitative identification of Corydalis Rhizoma and Angelicae Dahuricae Radix in Yuanhu Zhitong oral liquid by taking tetrahydropalmatine， corydaline reference substances and Corydalis Rhizoma reference medicinal materials as reference， and cyclohexane-trichloromethane-methanol（5∶3∶0.5） as developing solvent， Corydalis Rhizoma was identified using GF254 glass thin layer plate under ultraviolet light（365 nm）. And taking petroleum ether（60-90 ℃） -ether-formic acid（10∶10∶1） as developing solvent， Angelicae Dahuricae Radix was identified using a silica gel G TLC plate under ultraviolet light（305 nm）. High performance liquid chromatography（HPLC） was performed on a Waters XSelect HSS T3 column（4.6 mm×250 mm， 5 μm） with acetonitrile（A）-0.1% glacial acetic acid solution（adjusted pH to 6.1 by triethylamine）（B） as the mobile phase for gradient elution（0-10 min， 20%-30%A； 10-25 min， 30%-40%A； 25-40 min， 40%-50%A； 40-60 min， 50%-60%A）， the detection wavelength was set at 280 nm， then the fingerprint of Yuanhu Zhitong oral liquid was established， and the contents of tetrahydropalmatine and corydaline were determined. ResultIn the thin layer chromatograms， the corresponding spots of Yuanhu Zhitong oral liquid， the reference substances and reference medicinal materials were clear， with good separation and strong specificity. A total of 12 common peaks were identified in 10 batches of Yuanhu Zhitong oral liquid samples， and the peaks of berberine hydrochloride， dehydrocorydaline， glaucine， tetrahydropalmatine and corydaline. The similarities between the 10 batches of samples and the control fingerprint were all >0.90. The results of determination showed that the concentrations of corydaline and tetrahydropalmatine had good linearity with paek area in the range of 0.038 6-0.193 0， 0.034 0-0.170 0 g·L^-1， respectively. The methodological investigation was qualified， and the contents of corydaline and tetrahydropalmatine in 10 batches of Yuanhu Zhitong oral liquid samples were 0.077 5-0.142 9、0.126 1-0.178 2 g·L^-1， respectively. ConclusionThe established TLC， fingerprint and determination are simple， specific and reproducible， which can be used to improve the quality control standard of Yuanhu Zhitong oral liquid.

Fraction absorbed (Fa) is an important parameter to describe the absorption level of oral drugs, and an important basis for the development and optimization of the formulation process. Because it is easily confused with the concept of absolute bioavailability, it has not received enough attention from the industry. There are many complex factors affecting Fa. There are three time-related factors that directly affect the extent of Fa: the release time, the absorption time, and the residence time. The relationship between these three time-related factors determines the extent of Fa. Generally, we are more concerned about the apparent factors that affect the extent of Fa, including independent variables and covariates; The independent variables include administered dose, route, dosage form, etc. The covariates are divided into internal and external factors, and external factors include food factors, drug interactions, etc. Internal causes include age, sex, disease, etc. This paper analyzes and systematically combs how independent variables and covariates directly or indirectly affect the three time-related factors by affecting the body's physiology and internal environment, thus changing the complex process of Fa. Understanding this theoretical framework can better optimize the independent variables to reduce the impact of covariates on Fa. In addition, this paper also introduces the latest progress of prediction and evaluation of Fa, including the progress of complex dissolution device and the status of software prediction.

Patients with severe trauma require an extremely timely treatment and transfusion plays an irreplaceable role in the emergency treatment of such patients. An increasing number of evidence-based medicinal evidences and clinical practices suggest that patients with severe traumatic bleeding benefit from early transfusion of low-titer group O whole blood or hemostatic resuscitation with red blood cells, plasma and platelet of a balanced ratio. However, the current domestic mode of blood supply cannot fully meet the requirements of timely and effective blood transfusion for emergency treatment of patients with severe trauma in clinical practice. In order to solve the key problems in blood supply and blood transfusion strategies for emergency treatment of severe trauma, Branch of Clinical Transfusion Medicine of Chinese Medical Association, Group for Trauma Emergency Care and Multiple Injuries of Trauma Branch of Chinese Medical Association, Young Scholar Group of Disaster Medicine Branch of Chinese Medical Association organized domestic experts of blood transfusion medicine and trauma treatment to jointly formulate Chinese expert consensus on blood support mode and blood transfusion strategies for emergency treatment of severe trauma patients ( version 2024). Based on the evidence-based medical evidence and Delphi method of expert consultation and voting, 10 recommendations were put forward from two aspects of blood support mode and transfusion strategies, aiming to provide a reference for transfusion resuscitation in the emergency treatment of severe trauma and further improve the success rate of treatment of patients with severe trauma.

Objective To develop an MRI-based habitat radiomics model for the preoperative prediction of endometrial cancer(EC)molecular subtypes.Methods Patients with pathologically proven EC from two hospitals were included in the training(n=270)and testing(n=70)cohorts.All patients had preoperative MRI and histological and molecular diagnoses.First,the tumor was divided into habitat subregions based on diffusion-weighted imaging(DWI)and contrast-enhanced(CE)images.Subsequently,habitat radiomic features were extracted from different subregions of T1-weighted imaging(T1WI),T2-weighted imaging(T2WI),DWI,and CE images.Three machine learning classifiers,including logistic regression,support vector machines,and random forests,were applied to develop predictive models for p53-abnormal endometrial cancer,with model performance validated.The model demonstrating the best overall predictive performance was selected as the habitat radiomics model.Using the same procedure,a whole-region radiomics model based on T1WI,T2WI,DWI,and CE sequences and a clinical model were constructed.The performance of the models was evaluated using receiver operating characteristic curves,and DeLong's test was employed to compare differences between the models.Decision curve analysis was used to assess the clinical benefits of the models'application.Results After feature selection,eight habitat radiomic features were retained to construct the habitat radiomics model,ten features for the whole-region radiomics model,and three clinical features for the clinical model.The habitat radiomics model achieved the highest area under the curve(AUC),with 0.855(0.788-0.922)in the training cohort and 0.769(0.631-0.907)in the testing cohort.DeLong's test showed that the habitat radiomics model outperformed the whole-region radiomics model in the training cohort(P=0.001),but there was no significant difference in the testing cohort(P=0.543).In both cohorts,the habitat radiomics model outperformed the clinical model(P=0.007,training cohort;P=0.038,testing cohort).Decision curve analysis(DCA)demonstrated that this model provided clinical benefit for diagnosis within a threshold probability range of approximately 0.2-0.8.Conclusion The MRI-based habitat radiomics model can accurately predict p53-abnormal EC,outperforming both the whole-region radiomics model and the clinical model,and is useful for the non-invasive molecular subtyping of endometrial cancer before surgery.

Objective To monitor the susceptibility of clinical isolates to antimicrobial agents in tertiary hospitals in major regions of China in 2022.Methods Clinical isolates from 58 hospitals in China were tested for antimicrobial susceptibility using a unified protocol based on disc diffusion method or automated testing systems.Results were interpreted using the 2022 Clinical &Laboratory Standards Institute(CLSI)breakpoints.Results A total of 318 013 clinical isolates were collected from January 1,2022 to December 31,2022,of which 29.5％were gram-positive and 70.5％were gram-negative.The prevalence of methicillin-resistant strains in Staphylococcus aureus,Staphylococcus epidermidis and other coagulase-negative Staphylococcus species(excluding Staphylococcus pseudintermedius and Staphylococcus schleiferi)was 28.3％,76.7％and 77.9％,respectively.Overall,94.0％of MRSA strains were susceptible to trimethoprim-sulfamethoxazole and 90.8％of MRSE strains were susceptible to rifampicin.No vancomycin-resistant strains were found.Enterococcus faecalis showed significantly lower resistance rates to most antimicrobial agents tested than Enterococcus faecium.A few vancomycin-resistant strains were identified in both E.faecalis and E.faecium.The prevalence of penicillin-susceptible Streptococcus pneumoniae was 94.2％in the isolates from children and 95.7％in the isolates from adults.The resistance rate to carbapenems was lower than 13.1％in most Enterobacterales species except for Klebsiella,21.7％-23.1％of which were resistant to carbapenems.Most Enterobacterales isolates were highly susceptible to tigecycline,colistin and polymyxin B,with resistance rates ranging from 0.1％to 13.3％.The prevalence of meropenem-resistant strains decreased from 23.5％in 2019 to 18.0％in 2022 in Pseudomonas aeruginosa,and decreased from 79.0％in 2019 to 72.5％in 2022 in Acinetobacter baumannii.Conclusions The resistance of clinical isolates to the commonly used antimicrobial agents is still increasing in tertiary hospitals.However,the prevalence of important carbapenem-resistant organisms such as carbapenem-resistant K.pneumoniae,P.aeruginosa,and A.baumannii showed a downward trend in recent years.This finding suggests that the strategy of combining antimicrobial resistance surveillance with multidisciplinary concerted action works well in curbing the spread of resistant bacteria.

Objective To investigate the distribution and antimicrobial resistance profiles of the common pathogens isolated from urine from 2015 to 2021 in the CHINET Antimicrobial Resistance Surveillance Program.Methods The bacterial strains were isolated from urine and identified routinely in 51 hospitals across China in the CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021.Antimicrobial susceptibility was determined by Kirby-Bauer method,automatic microbiological analysis system and E-test according to the unified protocol.Results A total of 261 893 nonduplicate strains were isolated from urine specimen from 2015 to 2021,of which gram-positive bacteria accounted for 23.8％(62 219/261 893),and gram-negative bacteria 76.2％(199 674/261 893).The most common species were E.coli(46.7％),E.faecium(10.4％),K.pneumoniae(9.8％),E.faecalis(8.7％),P.mirabilis(3.5％),P.aeruginosa(3.4％),SS.agalactiae(2.6％),and E.cloacae(2.1％).The strains were more frequently isolated from inpatients versus outpatients and emergency patients,from females versus males,and from adults versus children.The prevalence of ESBLs-producing strains in E.coli,K.pneumoniae and P.mirabilis was 53.2％,52.8％and 37.0％,respectively.The prevalence of carbapenem-resistant strains in E.coli,K.pneumoniae,P.aeruginosa and A.baumannii was 1.7％,18.5％,16.4％,and 40.3％,respectively.Lower than 10％of the E.faecalis isolates were resistant to ampicillin,nitrofurantoin,linezolid,vancomycin,teicoplanin and fosfomycin.More than 90％of the E.faecium isolates were ressitant to ampicillin,levofloxacin and erythromycin.The percentage of strains resistant to vancomycin,linezolid or teicoplanin was＜2％.The E.coli,K.pneumoniae,P.aeruginosa and A.baumannii strains isolated from ICU inpatients showed significantly higher resistance rates than the corresponding strains isolated from outpatients and non-ICU inpatients.Conclusions E.coli,Enterococcus and K.pneumoniae are the most common pathogens in urinary tract infection.The bacterial species and antimicrobial resistance of urinary isolates vary with different populations.More attention should be paid to antimicrobial resistance surveillance and reduce the irrational use of antimicrobial agents.