ObjectiveTransfer RNA-derived fragments (tRFs) are a recently characterized and rapidly expanding class of small non-coding RNAs, typically ranging from 13 to 50 nucleotides in length. They are derived from mature or precursor tRNA molecules through specific cleavage events and have been implicated in a wide range of cellular processes. Increasing evidence indicates that tRFs play important regulatory roles in gene expression, primarily by interacting with target messenger RNAs (mRNAs) to induce transcript degradation, in a manner partially analogous to microRNAs (miRNAs). However, despite their emerging biological relevance and potential roles in disease mechanisms, there remains a significant lack of computational tools capable of systematically predicting the interaction landscape between tRFs and their target mRNAs. Existing databases often rely on limited interaction features and lack the flexibility to accommodate novel or user-defined tRF sequences. The primary goal of this study was to develop a machine learning based prediction algorithm that enables high-throughput, accurate identification of tRF:mRNA binding events, thereby facilitating the functional analysis of tRF regulatory networks. MethodsWe began by assembling a manually curated dataset of 38 687 experimentally verified tRF:mRNA interaction pairs and extracting seven biologically informed features for each pair: (1) AU content of the binding site, (2) site pairing status, (3) binding region location, (4) number of binding sites per mRNA, (5) length of the longest consecutive complementary stretch, (6) total binding region length, and (7) seed sequence complementarity. Using this dataset and feature set, we trained 4 distinct machine learning classifiers—logistic regression, random forest, decision tree, and a multilayer perceptron (MLP)—to compare their ability to discriminate true interactions from non-interactions. Each model’s performance was evaluated using overall accuracy, receiver operating characteristic (ROC) curves, and the corresponding area under the ROC curve (AUC). The MLP consistently achieved the highest AUC among the four, and was therefore selected as the backbone of our prediction framework, which we named tRF Prospect. For biological validation, we retrieved 3 high-throughput RNA-seq datasets from the gene expression omnibus (GEO) in which individual tRFs were overexpressed: AS-tDR-007333 (GSE184690), tRF-3004b (GSE197091), and tRF-20-S998LO9D (GSE208381). Differential expression analysis of each dataset identified genes downregulated upon tRF overexpression, which we designated as putative targets. We then compared the predictions generated by tRF Prospect against those from three established tools—tRFTar, tRForest, and tRFTarget—by quantifying the number of predicted targets for each tRF and assessing concordance with the experimentally derived gene sets. ResultsThe proposed algorithm achieved high predictive accuracy, with an AUC of 0.934. Functional validation was conducted using transcriptome-wide RNA-seq datasets from cells overexpressing specific tRFs, confirming the model’s ability to accurately predict biologically relevant downregulation of mRNA targets. When benchmarked against established tools such as tRFTar, tRForest, and tRFTarget, tRF Prospect consistently demonstrated superior performance, both in terms of predictive precision and sensitivity, as well as in identifying a higher number of true-positive interactions. Moreover, unlike static databases that are limited to precomputed results, tRF Prospect supports real-time prediction for any user-defined tRF sequence, enhancing its applicability in exploratory and hypothesis-driven research. ConclusionThis study introduces tRF Prospect as a powerful and flexible computational tool for investigating tRF:mRNA interactions. By leveraging the predictive strength of deep learning and incorporating a broad spectrum of interaction-relevant features, it addresses key limitations of existing platforms. Specifically, tRF Prospect: (1) expands the range of detectable tRF and target types; (2) improves prediction accuracy through multilayer perceptron model; and (3) allows for dynamic, user-driven analysis beyond database constraints. Although the current version emphasizes miRNA-like repression mechanisms and faces challenges in accurately capturing 5'UTR-associated binding events, it nonetheless provides a critical foundation for future studies aiming to unravel the complex roles of tRFs in gene regulation, cellular function, and disease pathogenesis.

Objective To explore the acupoint selection rules of acupuncture treatment for cerebellar ataxia using data mining techniques.Methods Taking the related literature of acupuncture treatment of cerebellar ataxia as the retrieval content,the computer retrieval of China National Knowledge Internet(CNKI),China Biomedical Literature Database(SinoMed),Wanfang Data Knowledge Service Platform(Wanfang),China Science and Technology Journal Database(VIP),American Biomedical Information Retrieval System(PubMed)and other major databases.The eligible acupoints in the literature were entered into the Microsoft Excel 2021 software table to establish a database of acupoints frequency,meridian tropism,specific acupoints,distribution sites and other information for acupuncture treatment of cerebellar ataxia.SPSS Modeler 18.0 Apriori algorithm,SPSS Statistics 25.0 and SPSS Modeler 18.0 Web complex network were used to analyze the association rules of the included prescription acupoints,Ward cluster analysis and draw the tree diagram and the Web network diagram of high-frequency acupoints and core prescriptions.Results(1)A total of 93 articles were included,including 117 acupuncture prescriptions and 172 acupoints,with a total frequency of 1 199 times of acupoints.(2)The top 10 acupoints were Fengchi(GB20),Zusanli(ST36),Hegu(LI4),Baihui(DU20),Sanyinjiao(SP6),Taichong(LR3),Quchi(LI11),Yanglingquan(GB34),Wangu(GB12),and Tianzhu(BL10).(3)The top five meridians used frequently were gallbladder meridian of foot shaoyang,governor vessel(GV),stomach meridian of foot yangming,large intestine meridian of hand yangming and bladder meridian of foot taiyang.(4)The selection of acupoints is mainly based on the head,face,neck and lower limbs.(5)The highest frequency of the use of specific points is the intersection point.(6)The high-frequency acupoints for acupuncture treatment of cerebellar ataxia are Fengchi-Wangu,Fengchi-Tianzhu and Fengchi-Tianzhu-Wangu.The top 31 high-frequency acupoints(frequency＞10 times)can be divided into nine effective clusters.Conclusion Acupuncture treatment for cerebellar ataxia has formed a compatibility rule with the main principle of"regulating the mind and constraining the bones,extinguishing wind and stopping the movement",with the far and near acupoints as the main body,and attaches importance to the application of yang meridians with multiple qi and blood,presenting the basic acupoint prescription with Fengchi-Wanggu-Tianzhu as the core.

Objective:To investigate the impact of the deep-learning-based CT fractional flow reserve (CT-FFR) on clinical decision-making and long-term prognosis in patients with obstructive coronary heart disease.Methods:In this single-center retrospective cohort study, consecutive patients with obstructive coronary heart disease (with at least one stenosis≥50%) on their first coronary computed tomography angiography (CCTA) in Beijing Anzhen Hospital from February 2017 to July 2018 were included. Baseline clinical and CT characteristics were collected. Deep-learning-based CT-FFR and Leiden CCTA risk score were calculated. All patients enrolled were followed up for at least 5 years. The study endpoint was major adverse cardiovascular events (MACE), defined as the composite of cardiac death, nonfatal myocardial infarction, unstable angina requiring hospitalization, and unplanned revascularization. Receiver operating characteristic (ROC) curves were drawn to define the optimal cut-off point of the Leiden score in predicting the 5-year MACE, and survival analysis and Cox regression were performed to explore the related factors of MACE.Results:A total of 622 patients, aged 61 (54, 66) years, with 407 (65.4%) males were included. Diagnostic coronary angiography was performed in 78 patients after their baseline CCTA, with 34 (43.6%) patients had CT-FFR>0.80. During a follow-up time of 2 181 (2 093, 2 355) days, 155 patients (24.9%) suffered from MACE. ROC derived optimal cut-off point of Leiden score for predicting MACE was 15.48. Survival analysis found that male patients, Leiden risk score>15 and CT-FFR≤0.80 had worse prognosis. Multivariate Cox regression analysis identified CT-FFR≤0.80 as an robust and independent predictor of MACE ( HR=4.98, 95% CI 3.15-7.86, P<0.001). Conclusion:Deep-learning-based CT-FFR aids in clinical decision-making and the evaluation of long-term prognosis in patients with obstructive coronary heart disease.

Objective To investigate the effect of Yigong San(YGS)on learning and memory abilities of rats with lipopolysaccharide(LPS)-induced cognitive decline and explore its possible mechanism in light of intestinal microbiota.Methods Forty SD rats were randomly divided into control group,model group,donepezil(1.3 mg/kg)group,and high-dose(5.25 g/kg)and low-dose(2.63 g/kg)YGS treatment groups.After 24 days of treatment with the corresponding drugs or water by gavage,the rats in the latter 4 groups received an intraperitoneal injection of LPS(0.5 mg/kg)to establish models of Alzheimer's disease(AD).Water maze test and HE staining were used to evaluate the changes in learning and memory abilities and pathomorphology of the hippocampus.The changes in gut microbial species of the rats were analyzed with 16S rRNA sequencing,and the levels of IL-6,TNF-α,and IL-1β in the brain tissue and serum were detected using ELISA.Results Compared with the AD model group,the YGS-treated rats showed significantly shortened escape latency on day 5 after modeling,reduced neuronal degeneration and necrosis in the hippocampus,lowered pathological score of cell damage,and decreased levels IL-6,TNF-α and IL-1β in the brain tissue and serum.The YGS-treated rats showed also obvious reduction of Alpha diversity indicators(ACE and Chao1)of intestinal microbiota with significantly increased abundance of Prevotellaceae species at the family level and decreased abundance of Desulfovibrionaceae,which were involved in such metabolic signaling pathways as cell community prokaryotes,membrane transport,and energy metabolism.Conclusion YGS improves learning and memory abilities and hippocampal pathomorphology in AD rat models possibly by regulating the abundance of intestinal microbial species such as Prevotellaceae to affect the metabolic pathways for signal transduction,cofactors,and vitamin metabolism.

Objective To explore the mechanism by which Yigong San(YGS)improves learning and memory abilities of APP/PS1 transgenic mice in light of cerebral fluid metabolism regulation.Methods Three-month-old male APP/PS1 transgenic mice and wild-type C57BL/6 mice were both randomized into control group,model group,donepezil(1.67 mg/kg)group,and YGS(7.5 g/kg)group and received the corresponding treatments via gavage once daily for one month.After the treatments,the mice were assessed for learning and memory functions using Morris water maze test and examined for hippocampal and cortical pathologies and amyloid plaques using HE,immunohistochemical and thioflavin S staining;ELISA and Evans blue method were used for detecting Aβ1-40 and Aβ1-42 levels in the brain tissue and serum and assessing blood-brain barrier(BBB)integrity.Immunofluorescence colocalization was used to investigate AQP4 polarization on astrocytes.Western blotting was performed to detect the expressions of VE-cadherin,ZO-1,occludin,β-amyloid precursor protein(APP),BACE1,insulin-degrading enzyme(IDE),LRP1,RAGE,and AQP4 proteins.Results Compared with the control mice,APP/PS1 mice showed significant impairment of learning and memory abilities,increased degeneration or necrosis of hippocampal and cortical neurons,pathological scores,Aβ-positive plaques,elevated Aβ1-40 and Aβ1-42 levels in the brain tissue and serum,increased BBB permeability,upregulated RAGE expression,lowered expressions of VE-cadherin,LRP1,ZO-1,occludin,and AQP4 proteins,and reduced AQP4-expressing GFAP-positive cells.YGS treatment significantly improved the performance of the transgenic mice in Morris water maze test,reduced hippocampal and cortical pathologies and Aβ-positive plaques,and ameliorated the abnormal changes in Aβ1-40 and Aβ1-42 levels,BBB permeability,protein expressions of RAGE,VE-cadherin,LRP1,ZO-1,occludin and AQP4,and the number of AQP4-expressing GFAP-positive cells.Conclusion YGS improves learning and memory changes in APP/PS1 mice by ameliorating neuronal damage and Aβ pathology in the brain and regulating brain fluid metabolism.

Objective To study the in vitro expression of three phenylalanine hydroxylase(PAH)mutants(p.R243Q,p.R241C,and p.Y356X)and determine their pathogenicity.Methods Bioinformatics techniques were used to predict the impact of PAH mutants on the structure and function of PAH protein.Corresponding mutant plasmids of PAH were constructed and expressed in HEK293T cells.Quantitative reverse transcription polymerase chain reaction was used to measure the mRNA expression levels of the three PAH mutants,and their protein levels were assessed using Western blot and enzyme-linked immunosorbent assay.Results Bioinformatics analysis predicted that all three mutants were pathogenic.The mRNA expression levels of the p.R243Q and p.R241C mutants in HEK293T cells were similar to the mRNA expression level of the wild-type control(P>0.05),while the mRNA expression level of the p.Y356X mutant significantly decreased(P<0.05).The PAH protein expression levels of all three mutants were significantly reduced compared to the wild-type control(P<0.05).The extracellular concentration of PAH protein was reduced in the p.R241C and p.Y356X mutants compared to the wild-type control(P<0.05),while there was no significant difference between the p.R243Q mutant and the wild type control(P>0.05).Conclusions p.R243Q,p.R241C and p.Y356X mutants lead to reduced expression levels of PAH protein in eukaryotic cells,with p.R241C and p.Y356X mutants also affecting the function of PAH protein.These three PAH mutants are to be pathogenic.[Chinese Journal of Contemporary Pediatrics,2024,26(2):188-193]

Objective To investigate the effect of Yigong San(YGS)on learning and memory abilities of rats with lipopolysaccharide(LPS)-induced cognitive decline and explore its possible mechanism in light of intestinal microbiota.Methods Forty SD rats were randomly divided into control group,model group,donepezil(1.3 mg/kg)group,and high-dose(5.25 g/kg)and low-dose(2.63 g/kg)YGS treatment groups.After 24 days of treatment with the corresponding drugs or water by gavage,the rats in the latter 4 groups received an intraperitoneal injection of LPS(0.5 mg/kg)to establish models of Alzheimer's disease(AD).Water maze test and HE staining were used to evaluate the changes in learning and memory abilities and pathomorphology of the hippocampus.The changes in gut microbial species of the rats were analyzed with 16S rRNA sequencing,and the levels of IL-6,TNF-α,and IL-1β in the brain tissue and serum were detected using ELISA.Results Compared with the AD model group,the YGS-treated rats showed significantly shortened escape latency on day 5 after modeling,reduced neuronal degeneration and necrosis in the hippocampus,lowered pathological score of cell damage,and decreased levels IL-6,TNF-α and IL-1β in the brain tissue and serum.The YGS-treated rats showed also obvious reduction of Alpha diversity indicators(ACE and Chao1)of intestinal microbiota with significantly increased abundance of Prevotellaceae species at the family level and decreased abundance of Desulfovibrionaceae,which were involved in such metabolic signaling pathways as cell community prokaryotes,membrane transport,and energy metabolism.Conclusion YGS improves learning and memory abilities and hippocampal pathomorphology in AD rat models possibly by regulating the abundance of intestinal microbial species such as Prevotellaceae to affect the metabolic pathways for signal transduction,cofactors,and vitamin metabolism.

Objective To explore the mechanism by which Yigong San(YGS)improves learning and memory abilities of APP/PS1 transgenic mice in light of cerebral fluid metabolism regulation.Methods Three-month-old male APP/PS1 transgenic mice and wild-type C57BL/6 mice were both randomized into control group,model group,donepezil(1.67 mg/kg)group,and YGS(7.5 g/kg)group and received the corresponding treatments via gavage once daily for one month.After the treatments,the mice were assessed for learning and memory functions using Morris water maze test and examined for hippocampal and cortical pathologies and amyloid plaques using HE,immunohistochemical and thioflavin S staining;ELISA and Evans blue method were used for detecting Aβ1-40 and Aβ1-42 levels in the brain tissue and serum and assessing blood-brain barrier(BBB)integrity.Immunofluorescence colocalization was used to investigate AQP4 polarization on astrocytes.Western blotting was performed to detect the expressions of VE-cadherin,ZO-1,occludin,β-amyloid precursor protein(APP),BACE1,insulin-degrading enzyme(IDE),LRP1,RAGE,and AQP4 proteins.Results Compared with the control mice,APP/PS1 mice showed significant impairment of learning and memory abilities,increased degeneration or necrosis of hippocampal and cortical neurons,pathological scores,Aβ-positive plaques,elevated Aβ1-40 and Aβ1-42 levels in the brain tissue and serum,increased BBB permeability,upregulated RAGE expression,lowered expressions of VE-cadherin,LRP1,ZO-1,occludin,and AQP4 proteins,and reduced AQP4-expressing GFAP-positive cells.YGS treatment significantly improved the performance of the transgenic mice in Morris water maze test,reduced hippocampal and cortical pathologies and Aβ-positive plaques,and ameliorated the abnormal changes in Aβ1-40 and Aβ1-42 levels,BBB permeability,protein expressions of RAGE,VE-cadherin,LRP1,ZO-1,occludin and AQP4,and the number of AQP4-expressing GFAP-positive cells.Conclusion YGS improves learning and memory changes in APP/PS1 mice by ameliorating neuronal damage and Aβ pathology in the brain and regulating brain fluid metabolism.

We prepared 15 batches of Kaixin Powder benchmark samples with the decoction pieces of different batches. Further, we established the specific chromatograms and index component content determination method of Kaixin Powder benchmark samples and analyzed the peaks and similarity of the chromatograms. With sibiricose A5, sibiricose A6, polygalaxanthone Ⅲ, 3,6'-disinapoyl sucrose, ginsenoside Rb_1, β-asarone, α-asarone, and dehydropachymic acid as index components, the index component content determination method was established and 70%-130% of the mean content of each component was set as the range. The chromatograms of 15 batches of Kaixin Powder benchmark samples had a total of 22 characteristic peaks, among which 8 peaks were identified, which represented sibiricose A5, sibiricose A6, polygalaxanthone Ⅲ, 3,6'-disinapoyl sucrose, ginsenoside Rb_1, β-asarone, α-asarone, and dehydropachymic acid, respectively. The chromatograms shared the similarity of 0.992-0.999. The 15 batches of benchmark samples had sibiricose A5 of 0.34-0.55 mg·g~(-1), sibiricose A6 of 0.43-0.57 mg·g~(-1), polygalaxanthone Ⅲ of 0.12-0.19 mg·g~(-1), 3,6'-disinapoyl sucrose of 1.08-1.78 mg·g~(-1), ginsenoside Rb_1 of 0.33-0.62 mg·g~(-1), β-asarone of 2.34-3.72 mg·g~(-1), α-asarone of 0.11-0.22 mg·g~(-1), and dehydropachymic acid of 0.053-0.079 mg·g~(-1). This study established the specific chromatograms and index component content determination method of Kaixin Powder benchmark samples, and the method was simple, feasible, reproducible, and stable. This study provides a scientific basis for further research on the key chemical properties of the benchmark samples and preparations of Kaixin Powder.
Powders ; Ginsenosides ; Benchmarking ; Drugs, Chinese Herbal/chemistry* ; Sucrose ; Chromatography, High Pressure Liquid/methods*

Objective:To explore the current status of surgery for portal hypertension to grasp current status and future development of surgery in China.Methods:This study is jointly sponsored by China Hepatobiliary & Pancreatic Specialist Alliance & Portal Hypertension Alliance in China (CHESS).Comprehensive surveying is conducted for basic domestic situations of surgery for portal hypertension, including case load, surgical approaches, management of postoperative complications, primary effects, existing confusion and obstacles, liver transplantation(LT), laparoscopic procedures and transjugular intrahepatic portosystemic shunt(TIPS), etc.Results:A total of 8 512 cases of portal hypertension surgery are performed at 378 hospitals nationwide in 2021.Splenectomy plus devascularization predominated(53.0%)and laparoscopy accounted for 76.1%.Primary goal is preventing rebleeding(67.0%) and 72.8% of hospitals used preventive anticoagulants after conventional surgery.And 80.7% of teams believe that the formation of postoperative portal vein thrombosis is a surgical dilemma and 65.3% of hospitals practiced both laparoscopy and TIPS.The major reasons for patients with portal hypertension not receiving LT are due to a lack of qualifications for LT(69.3%)and economic factors(69.0%).Conclusions:Surgery is an integral part of management of portal hypertension in China.However, it is imperative to further standardize the grasp of surgical indications, the handling of surgical operation and the management of postoperative complications.Moreover, prospective, multi-center randomized controlled clinical studies should be performed.