ObjectiveTo establish an ultra-performance liquid fingerprint and multi-components determination method for Naomaili granules. To evaluate the quality of different batches by chemometrics， and the anti-neuroinflammatory effects of water extract and main components of Naomaili granules were tested in vitro. MethodsThe similarity and common peaks of 27 batches of Naomaili granules were evaluated by using Ultra performance liquid chromatography （UPLC） fingerprint detection. Ultra-performance liquid chromatography-tandem mass spectrometry （UPLC-MS/MS） technology was used to determine the content of the index components in Naomaili granules and to evaluate the quality of different batches of Naomaili granules by chemometrics. LPS-induced BV-2 cell inflammation model was used to investigate the anti-neuroinflammatory effects of the water extract and main components of Naomaili granules. ResultsThe similarity of fingerprints of 27 batches of samples was > 0.90. A total of 32 common peaks were calibrated， and 23 of them were identified and assigned. In 27 batches of Naomaili granules， the mass fractions of 14 components that were stachydrine hydrochloride， leonurine hydrochloride， calycosin-7-O-glucoside， calycosin，tanshinoneⅠ， cryptotanshinone， tanshinoneⅡ_A， ginsenoside Rb₁， notoginsenoside R₁， ginsenoside Rg₁， paeoniflorin， albiflorin， lactiflorin， and salvianolic acid B were found to be 2.902-3.498， 0.233-0.343， 0.111-0.301， 0.07-0.152， 0.136-0.228， 0.195-0.390， 0.324-0.482， 1.056-1.435， 0.271-0.397， 1.318-1.649， 3.038-4.059， 2.263-3.455， 0.152-0.232， 2.931-3.991 mg∙g^-1， respectively. Multivariate statistical analysis showed that paeoniflorin， ginsenoside Rg₁， ginsenoside Rb₁ and staphylline hydrochloride were quality difference markers to control the stability of the preparation. The results of bioactive experiment showed that the water extract of Naomaili granules and the eight main components with high content in the prescription had a dose-dependent inhibitory effect on the release of NO in the cell supernatant. Among them， salvianolic acid B and ginsenoside Rb₁ had strong anti-inflammatory activity， with IC₅₀ values of （36.11±0.15） mg∙L^-1 and （27.24±0.54） mg∙L^-1， respectively. ConclusionThe quality evaluation method of Naomaili granules established in this study was accurate and reproducible. Four quality difference markers were screened out， and eight key pharmacodynamic substances of Naomaili granules against neuroinflammation were screened out by in vitro cell experiments.

Hepatocellular carcinoma(HCC)expresses abundant glycolytic enzymes and displays comprehensive glucose metabolism reprogramming.Aldolase A(ALDOA)plays a prominent role in glycolysis;however,little is known about its role in HCC development.In the present study,we aim to explore how ALDOA is involved in HCC proliferation.HCC proliferation was markedly suppressed both in vitro and in vivo following ALDOA knockout,which is consistent with ALDOA overexpression encouraging HCC prolifera-tion.Mechanistically,ALDOA knockout partially limits the glycolytic flux in HCC cells.Meanwhile,ALDOA translocated to nuclei and directly interacted with c-Jun to facilitate its Thr93 phosphorylation by P21-activated protein kinase;ALDOA knockout markedly diminished c-Jun Thr93 phosphorylation and then dampened c-Jun transcription function.A crucial site Y364 mutation in ALDOA disrupted its interaction with c-Jun,and Y364S ALDOA expression failed to rescue cell proliferation in ALDOA deletion cells.In HCC patients,the expression level of ALDOA was correlated with the phosphorylation level of c-Jun(Thr93)and poor prognosis.Remarkably,hepatic ALDOA was significantly upregulated in the promotion and progression stages of diethylnitrosamine-induced HCC models,and the knockdown of Aldoa strikingly decreased HCC development in vivo.Our study demonstrated that ALDOA is a vital driver for HCC development by activating c-Jun-mediated oncogene transcription,opening additional avenues for anti-cancer therapies.

Objective:To explore the differentially expressed tRNA-derived RNA fragment(tRF)and tRNA halves(tiRNA)in plasma of collagen-induced arthritis(CIA)rats,analyze the biological functions and related pathways of the tRF and tiRNAs target genes in order to identify new targets for diagnosis and therapy of rheumatoid arthritis(RA).Methods:Rat model of RA was estab-lished by injecting typeⅡ collagen.Arthritis index(AI)score and HE staining were conducted to evaluate the successfully establishment model.Illumina platform was used to obtain the tRF and tiRNA expression profiles.RT-qPCR was performed to validate expressions of tRF and tiRNA.Combining miRanda and TargetScan databases,the target genes of differentially expressed tRF and tiRNA were ob-tained.GO and KEGG enrichment analysis were used to annotate the functions of target genes.Results:A total of 25 tRFs and tiRNAs were significantly differentially expressed in plasma in rats after modeling,of which 23 were up-regulated and 2 were down-regulated.Besides,six specifically expressed tRFs and tiRNAs induced by CIA rats were screened,including Other-36:73-tRNA-Arg-CCT-4,Other-57:70-tRNA-Glu-CTC-1-M3,tRF-1:32-Gly-CCC-1-M2,tRF-1:31-Gly-CCC-1-M2,tRF-1:32-Pro-AGG-1-M4 and tRF-1:32-Glu-TTC-2-M2.GO analysis of target genes mainly involved organelle-associated items.What's more,KEGG analysis enriched multi-ple classical signal pathways associated with RA.Conclusion:Target genes of differentially expressed tRFs and tiRNAs in CIA rats may be involved in regulating important pathophysiological processes of RA and drug therapy targets.

Objective This study aimed to develop an automated method for syndrome element differenti-ation in Traditional Chinese Medicine(TCM).Methods We first constructed and trained an Instruction-tuned Multi-Task TCM text embedding model(Instr-MT-TCM)using four distinct TCM task datasets,including domain knowledge,synonymous terminology,syndrome differentiation and treatment,and TCM case labels.Subsequently,five TCM diagnostics experts holding master's degrees or higher were organized to screen a real-world TCM case dataset and annotate symptoms and signs.The purpose was to evaluate the F1-score of the proposed method—the combination of Instr-MT-TCM and a Large Language Model(LLM)—by comparing its performance against the manual annotation result on the syndrome element differentiation task.Finally,to validate its feasibility in real-world clinical settings,the method was applied to 48 prostate cancer cases to calculate the syndrome element scores.Results The Instr-MT-TCM model showed rapid performance improvement in its early training phase,achieving a Recall@1(R@1)of 0.848.Experts curated a dataset of 1,793 real-world clinical cases,covering 34 common diseases and 66 syndrome patterns.In the syndrome element differentiation task,the collaborative framework of LLM and Instr-MT-TCM achieved a mean F1-score of 0.927,outperforming the 0.512 from manual annota-tion.The syndrome element analysis revealed that the predominant elements of disease nature were fire(heat)and yin deficiency,while the main elements of disease location were bladder and kidney.Conclusion This study proposes and validates a novel method for automated TCM syndrome element dif-ferentiation based on the synergy between LLM and our custom Instr-MT-TCM model.Achieving a high F1-score(0.927)on real-world data,the method demonstrates excellent accuracy and generalization ability.Its application in prostate cancer analysis highlights its significant clinical potential,offering effective technical support,and a new research direction for intelligent TCM syndrome element differentiation.

This article reports the diagnosis and treatment of two cases of complex ureteral obstruction (UO) in transplanted kidneys managed at Tangdu Hospital of Air Force Medical University of PLA in 2023. UO is a challenging complication following kidney transplantation, with surgical repair being the primary treatment approach. Both patients underwent robot-assisted laparoscopic (RAL) anastomosis of the transplanted kidney collecting system with the autologous ureter. The procedures were successfully performed, and both recipients were discharged without complications. During a six-month postoperative follow-up, the morphology and function of the transplanted kidneys remained stable, with no recurrence of hydronephrosis, fever, pain, urinary frequency, or urgency. This case report provides new insights into the diagnosis and surgical management of complex UO in kidney transplant recipients.

The telomere structure in the cell nucleus is crucial for maintaining the stability and functions of chromosomes.Telomerase is a ribonucleoprotein reverse transcriptase,which catalyzes the elongation of telomeres using its own RNA as a template,thereby counteracting the shortening of telomeres caused by chromosome replication and cell division.Due to its overexpression in over 85％of malignant tumor cells,telomerase has emerged as a highly promising biomarker and a novel target for cancer therapy.In recent years,given the importance of precise quantification of telomerase activity in guiding medical diagnosis and treatment strategies,researchers have developed various high-performance telomerase detection techniques.Among these,electrochemical biosensing technique has cause much attention due to its high sensitivity,operational convenience,rapid response,and ease of miniaturization.This paper focused on the latest advances in electrochemical sensing technique for detection of telomerase activity,aiming to provide inspiration for designing novel telomerase activity detection strategies by elucidating three unique properties of telomerase primer extension products.

Lentiviral vectors(LVs)are key gene delivery tools for integrating target genes into the host genome,but they may also pose risks of insertional mutagenesis.The vector copy number(VCN)in cells is critical for determining the safety of gene modification.However,the reliability and accuracy of its quantification process are influenced by multiple factors.Developing cell reference materials with specific vector copy numbers represents a viable approach to enhance the reliability and consistency of measurement results,enabling quality control of the quantification process and traceability of outcomes.However,the preparation of such reference materials faces challenges in cell sample design,preparation protocols,and advanced quantification techniques.In this study,T lymphocyte cell line Jurkat-based reference materials with LV gene copy numbers of 1 and 2 copy/cell were developed.A high-precision duplex digital polymerase chain reaction(dPCR)method was established to quantify the LV gene and endogenous genes simultaneously.Additionally,the results of dPCR were cross-validated through next-generation sequencing and flow cytometric analysis.Ultimately,confocal microscopy characterization results showed that the developed cell reference materials had intact morphology.The quantification result of VCN-1 was(1.07±0.11)copy/cell,and that of VCN-2 was(2.09±0.21)copy/cell.These cell reference materials demonstrated compliance with stability and homogeneity requirements,and could be applied for quality control throughout the VCN measurement workflow and metrological traceability,improving the accuracy,comparability,and validity of copy number measurements.

Objective To explore the correlation between the actual age and the pulp chamber volume(PCV)and pulp dentinal index(PDI)of the right first molars based on cone beam computed tomog-raphy(CBCT)technology,and to construct an accurate and convenient model for age estimation.Methods CBCT image data of 1 857 Han adults(883 males and 974 females)from the Department of Stomatology,Affiliated Hospital of North Sichuan Medical College were collected.The data were di-vided into training and validation sets at a ratio of 8∶2.A total of 1 485 training samples were used to construct the age estimation model,and 372 samples were used to validate the accuracy of the model.The Mimics 21.0 software was used to measure the PCV and calculate the PDI of the right first molars.Their correlations with age and the differences between different sexes and tooth positions were analyzed.Results Both the PCV and the PDI of the first molars showed strong negative correla-tions with the actual age(r values ranged from 0.82 to 0.89).The differences in PCV and PDI be-tween different sexes and tooth positions were statistically significant(P<0.05).The age estimation model based on PDI was superior to that based on PCV.The model based on the PDI values of the two right first molars(y=73.72-44.15 x3-28.27 x4,where x3 and x4 are the PDI values of the right maxil-lary and mandibular first molars,respectively)was the best,with the R2 of 0.79 and the mean abso-lute error of 4.90 years.Conclusion Both PCV and PDI of the first molars are effective indicators for age estimation.The age estimation model based on the PDI is more convenient and accurate than that based on the PCV,providing a more effective method for age estimation in forensic practice.

Objective To construct an aptamer-functionalized carboxylated graphene oxide(CGO)fluo-rescent sensor to achieve highly sensitive and specific detection of ketamine(KET)and its metabolite norketamine(NK)using an aptamer capable of simultaneously recognizing KET and NK.Methods A specific aptamer for simultaneous recognition of KET and NK was screened using graphene oxide-sys-tematic evolution of ligand by exponential enrichment(GO-SELEX)and molecular docking tech-niques.The aptamer,labeled with Cy5 fluorescence,was chemically conjugated to CGO to construct an aptamer-functionalized CGO fluorescent sensor.By optimizing detection conditions,including the mass concentration of CGO,aptamer concentration,reaction temperature,and incubation time,quantita-tive analysis of the target analytes was achieved using the ratio of fluorescence intensity changes be-fore and after target addition.The stability of the sensor in biological matrices was evaluated by moni-toring fluorescence intensity changes over incubation time in blank blood and urine,in comparison with the traditional physical adsorption-based CGO fluorescent sensor.Spiked recovery experiments in blank blood and urine were conducted to compare performance with that of HPLC-MS/MS.Results A specific aptamer A5 was selected and chemically conjugated with CGO to construct the aptamer-functionalized CGO fluorescent sensor.Under optimized conditions,the proposed fluorescent sensor ex-hibited a linear detection range of 1.0-5.0 ng/mL for KET,with a limit of detection(LOD)of 0.86 ng/mL;while for NK,the linear detection range was 1.0-5.0 ng/mL,with an LOD of 0.70 ng/mL.Com-pared with the CGO fluorescent sensor constructed via physical adsorption,this sensor demonstrated greater stability in blood and urine.The spiked recovery rates of KET and NK in blank blood and urine ranged from 81.50%to 110.03%,exhibiting detection performance comparable to that of HPLC-MS/MS.Conclusion The aptamer screening method offers a novel approach for selecting aptamers tar-geting drugs and their metabolites.The constructed aptamer-functionalized CGO fluorescent sensor pro-vides an efficient and reliable strategy for the high-performance detection of KET and NK.