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.

This study was aimed at establishing a method of ultra-fast quantitative PCR for Brucella detection.We used an exogenous recombinant plasmid as the internal reference and targeted the T4SS secretion system,an important Brucella viru-lence factor,to design specific primers and probes.The sensitivity,specificity,and repeatability of this method were evaluated,and a standard curve was constructed.The coincidence rate of detection findings with this method versus quantitative PCR was determined.This method markedly decreased the detection time to only 10 minutes.The standard curve demonstrated a good linear relationship(Y=-3.410 7x+38.357,R2=0.998 5)with a low minimum detection limit of 10 copies/μL.The method exhibited good specificity and did not specifically amplify several common clinical bacteria other than Brucella.The de-tection of three concentrations of positive plasmids yielded coefficients of variation(CVs)of 0.20％to 0.91％,thus demonstra-ting the method's excellent repeatability.Furthermore,140 clinical samples were analyzed concurrently with the fluorescence PCR method,which yielded a 100％compliance rate and consistent results.Our findings indicated that the Brucella ultra-fast quantitative PCR was ultrafast;had high sensitivity,high specificity,and good specificity;and can be used for the clinical de-tection of Brucella and emergency investigation of epidemics.Therefore,this method is valuable for the early diagnosis of Bru-cella.

Objective:To investigate the predictive value of endothelial activation and stress index(EASIX)for the prognosis of patients with mantle cell lymphoma(MCL).Methods:A retrospective analysis was conducted to assess prognosis and compare the clinical features of patients diagnosed with MCL who were admitted to the Affiliated Hospital of Xuzhou Medical University from January 2010 to June 2023,had therapeutic indications and received standard treatment.Results:A total of 66 patients were included and divided into high EASIX group and low EASIX group,according to a cutoff value of 0.97 determined by the receiver operating characteristic(ROC)curve.Multivariate Cox regression analysis showed that prealbumin＜0.2 g/L,high EASIX,and ECOG PS score ≥2 were independent risk factors influencing overall survival(OS)in MCL patients.The median OS of patients in the high and low EASIX group was 13.0 and 37.5 months,and the median progression-free survival was 8.8 and 26.0 months,respectively.The proportions of patients with ECOG PS score ≥2 and prealbumin＜0.2 g/L at onset significantly increased in the high EASIX group compared to those in the low EASIX group.Conclusion:At the time of initial diagnosis,EASIX can serve as an independent prognostic indicator impacting OS in patients with MCL.Furthermore,patients in the high EASIX group experience a poorer prognosis and shorter survival duration compared with those in the low EASIX group.

Objective:To investigate whether a distant-image screen display has an inhibitory effect on children's nearwork-induced transient myopia (NITM).Methods:A prospective self-controlled study was conducted.From March 2022 to March 2023, 120 pediatric volunteers, aged 4 to 12 years, with a mean age of (5.0±2.2) years, were recruited at Tianjin Eye Hospital.Subjects with refractive errors underwent tests wearing corrective lenses.Subjects were categorized based on accommodative response into three groups: accommodative lead (16 subjects, 32 eyes), accommodative equivalent (48 subjects, 96 eyes), and accommodative lag (56 subjects, 112 eyes). Subjects were also divided by myopia status into myopic (20 subjects, 40 eyes) and non-myopic (100 subjects, 200 eyes) groups.Using a random number table, the subjects were assigned to first view video images for 30 minutes on either an iPad or a distant light screen display.After a two-hour rest between the two sessions, the viewing modality was switched.Visual acuity, refractive power, lens thickness, NITM degree, and NITM recovery time were recorded before and after viewing videos via both modalities.Visual acuity, lens thickness, NITM degree, and recovery time following video viewing via the two modalities across different accommodation types and refractive types were compared.This study adhered to the Declaration of Helsinki.The study protocol was approved by the Ethics Committee of Tianjin Eye Hospital (No.2022099), and all guardians of the subjects provided informed consent for this study.Results:The NITM degree and recovery time after watching videos on a distant-image screen display were (0.00±0.36)D and (25.33±15.48) seconds, respectively.The NITM degree and recovery time after watching videos on an iPad were (-0.20±0.40)D and (33.33±17.68) seconds, respectively.Compared with watching videos on an iPad, watching videos on a distant-image screen display resulted in better immediate distance vision, lower myopic refractive power, thinner lens thickness, lower NITM degree, and shorter recovery time, with statistically significant differences ( t=-7.688, 7.842, -4.210, 2.331, -2.887; all P<0.05). After viewing the distant-image screen display and iPad, there was no significant difference in the overall comparison of visual acuity change, lens thickness change, NITM degree and NITM recovery time among the accommodative lead, accommodative equivalent and accommodative lag groups ( H=0.584, 4.923, 1.514, 2.634; all P>0.05. H=3.265, 1.884, 1.606, 1.922; all P>0.05), and there was also no significant difference between the myopic and non-myopic groups ( Z=-1.555, -1.700, -0.254, -2.336; all P>0.05. Z=-1.125, -0.446, -1.033, -0.759; all P>0.05). Conclusions:The use of a distant-image screen display can reduce the NITM caused by near viewing and shorten the NITM recovery time, which is effective for children with different refractive states and accommodative types.

Objective To propose a multiple regression-variational auto-encoders(MR-VAE)model to realize precise and non-invasive prediction of intra-abdominal pressure(IAP)in critically ill patients.Methods At first,a dataset was constructed by retrospectively analysing baseline characteristics and clinical indicators of 100 critically ill patients admitted to the Intensive Care Unit of Daping Hospital of Army Medical University between 30 August 2019 and 30 March 2021.Then,a MR-VAE prediction model was developed by integrating a feedforward neural network for supervised regression onto a variational autoencoder(VAE)framework and incorporating multiple regression strategies to mitigate feature interference.Finally,the MR-VAE model had its performance evaluated by its comparison with five classical models including support vector machines(SVM),convolutional neural networks(CNN),Scikit-learn integrated model(SIM),multi-layer perceptron(MLP)and K-nearest neighbors(KNN),and its prediction accuracy verified by testing the data of 10 randomly selected patients.Results The MR-VAE model behaved the best when compared with the five classical models,with a mean squared error(MSE)of 0.207,a root mean square error(RMSE)of 0.454,a mean absolute error(MAE)of 0.361,a median absolute deviation(MAD)of 0.243,an explained variance score(EVS)of 0.814 and a R2of 0.823,which also outperformed the five models in fitting performance,convergence and final loss.In random sample testing,the MR-VAE model exhibited high consistency between predicted and actual values.Conclusion The MR-VAE model proposed can accurately predict IAP,which has great potential in reducing the repeated measurements of IAP in critically ill patients and providing new ideas for the early diagnosis and treatment of IAH.

Objective To propose a multiple regression-variational auto-encoders(MR-VAE)model to realize precise and non-invasive prediction of intra-abdominal pressure(IAP)in critically ill patients.Methods At first,a dataset was constructed by retrospectively analysing baseline characteristics and clinical indicators of 100 critically ill patients admitted to the Intensive Care Unit of Daping Hospital of Army Medical University between 30 August 2019 and 30 March 2021.Then,a MR-VAE prediction model was developed by integrating a feedforward neural network for supervised regression onto a variational autoencoder(VAE)framework and incorporating multiple regression strategies to mitigate feature interference.Finally,the MR-VAE model had its performance evaluated by its comparison with five classical models including support vector machines(SVM),convolutional neural networks(CNN),Scikit-learn integrated model(SIM),multi-layer perceptron(MLP)and K-nearest neighbors(KNN),and its prediction accuracy verified by testing the data of 10 randomly selected patients.Results The MR-VAE model behaved the best when compared with the five classical models,with a mean squared error(MSE)of 0.207,a root mean square error(RMSE)of 0.454,a mean absolute error(MAE)of 0.361,a median absolute deviation(MAD)of 0.243,an explained variance score(EVS)of 0.814 and a R2of 0.823,which also outperformed the five models in fitting performance,convergence and final loss.In random sample testing,the MR-VAE model exhibited high consistency between predicted and actual values.Conclusion The MR-VAE model proposed can accurately predict IAP,which has great potential in reducing the repeated measurements of IAP in critically ill patients and providing new ideas for the early diagnosis and treatment of IAH.

AIM To establish the quantitative models for gallic acid,mononucleoside,loganin,resveratrol,and rhein in Yishen Xiezhuo Mixture.METHODS HPLC was adopted in the content determination of various effective components,after which the near-infrared spectroscopy(NIRS)data were collected in 128 batches of samples and pretreatment was conducted,competitive adaptive reweighting sampling(CARS)algorithm was used for screening wavelength,partial least square method(PLS)regression analysis was performed.RESULTS There were no significant differences between the predicted values obtained by PLS models and measured values obtained by HPLC for various effective components(P＞0.05).CONCLUSION The quantitative models established by NIRS combined with chemometrics display good predictive performance,which can be used for the rapid determination of effective components in Yishen Xiezhuo Mixture,and provide a reference for the rapid monitoring of other traditional Chinese medicine preparations in production processes.

Immobilized enzyme-based enzyme electrode biosensors, characterized by high sensitivity and efficiency, strong specificity, and compact size, demonstrate broad application prospects in life science research, disease diagnosis and monitoring, etc. Immobilization of enzyme is a critical step in determining the performance (stability, sensitivity, and reproducibility) of the biosensors. Random immobilization (physical adsorption, covalent cross-linking, etc.) can easily bring about problems, such as decreased enzyme activity and relatively unstable immobilization. Whereas, directional immobilization utilizing amino acid residue mutation, affinity peptide fusion, or nucleotide-specific binding to restrict the orientation of the enzymes provides new possibilities to solve the problems caused by random immobilization. In this paper, the principles, advantages and disadvantages and the application progress of enzyme electrode biosensors of different directional immobilization strategies for enzyme molecular sensing elements by specific amino acids (lysine, histidine, cysteine, unnatural amino acid) with functional groups introduced based on site-specific mutation, affinity peptides (gold binding peptides, carbon binding peptides, carbohydrate binding domains) fused through genetic engineering, and specific binding between nucleotides and target enzymes (proteins) were reviewed, and the application fields, advantages and limitations of various immobilized enzyme interface characterization techniques were discussed, hoping to provide theoretical and technical guidance for the creation of high-performance enzyme sensing elements and the manufacture of enzyme electrode sensors.

Jiuwei Xifeng Granules have become a Chinese patent medicine in the market. Because the formula contains Os Draconis, a top-level protected fossil of ancient organisms, the formula was to be improved by replacing Os Draconis with Ostreae Concha. To evaluate whether the improved formula has the same effectiveness and safety as the original formula, a randomized, double-blind, parallel-controlled, equivalence clinical trial was conducted. This study enrolled 288 tic disorder(TD) of children and assigned them into two groups in 1∶1. The treatment group and control group took the modified formula and original formula, respectively. The treatment lasted for 6 weeks, and follow-up visits were conducted at weeks 2, 4, and 6. The primary efficacy endpoint was the difference in Yale global tic severity scale(YGTSS)-total tic severity(TTS) score from baseline after 6 weeks of treatment. The results showed that after 6 weeks of treatment, the declines in YGTSS-TSS score showed no statistically significant difference between the two groups. The difference in YGTSS-TSS score(treatment group-control group) and the 95%CI of the full analysis set(FAS) were-0.17[-1.42, 1.08] and those of per-protocol set(PPS) were 0.29[-0.97, 1.56], which were within the equivalence boundary [-3, 3]. The equivalence test was therefore concluded. The two groups showed no significant differences in the secondary efficacy endpoints of effective rate for TD, total score and factor scores of YGTSS, clinical global impressions-severity(CGI-S) score, traditional Chinese medicine(TCM) response rate, or symptom disappearance rate, and thus a complete evidence chain with the primary outcome was formed. A total of 6 adverse reactions were reported, including 4(2.82%) cases in the treatment group and 2(1.41%) cases in the control group, which showed no statistically significant difference between the two groups. No serious suspected unexpected adverse reactions were reported, and no laboratory test results indicated serious clinically significant abnormalities. The results support the replacement of Os Draconis by Ostreae Concha in the original formula, and the efficacy and safety of the modified formula are consistent with those of the original formula.
Adolescent ; Child ; Child, Preschool ; Female ; Humans ; Male ; Double-Blind Method ; Drugs, Chinese Herbal/therapeutic use* ; Tic Disorders/drug therapy* ; Treatment Outcome

This study aimed to explore the effects and mechanisms of total extracts from Anthriscus sylvestris on pulmonary hypertension in rats. Sixty male SD rats were divided into normal(NC) group, model(M) group, positive drug sildenafil(Y) group, low-dose A. sylvestris(ES-L) group, medium-dose A. sylvestris(ES-M) group, and high-dose A. sylvestris(ES-H) group. On day 1, rats were intraperitoneally injected with monocrotaline(60 mg·kg~(-1)) to induce pulmonary hypertension, and the rat model was established on day 28. From days 15 to 28, intragastric administration of the respective treatments was performed. After modeling and treatment, small animal echocardiography was used to detect the right heart function of the rats. Arterial blood gas was measured using a blood gas analyzer. Hematoxylin and eosin(HE) staining and Masson staining were performed to observe cardiopulmonary pathological damage. Flow cytometry was used to detect apoptosis in the lung and myocardial tissues and reactive oxygen species(ROS) levels. Western blot was applied to detect the expression levels of transforming growth factor-β1(TGF-β1), phosphorylated mothers against decapentaplegic homolog 3(p-Smad3), Smad3, tissue plasminogen activator(t-PA), and plasminogen activator inhibitor-1(PAI-1) in lung tissue. A blood routine analyzer was used to measure inflammatory immune cell levels in the blood. Enzyme-linked immunosorbent assay(ELISA) was used to detect the expression levels of P-selectin and thromboxane A2(TXA2) in plasma. The results showed that, compared with the NC group, right heart hypertrophy index, right ventricular free wall thickness, right heart internal diameter, partial carbon dioxide pressure(PaCO_2), apoptosis in cardiopulmonary tissue, and ROS levels were significantly increased in the M group. In contrast, the ratio of pulmonary blood flow acceleration time(PAT)/ejection time(PET), right cardiac output, change rate of right ventricular systolic area, systolic displacement of the tricuspid ring, oxygen partial pressure(PaO_2), and blood oxygen saturation(SaO_2) were significantly decreased in the M group. After administration of the total extract of A. sylvestris, right heart function and blood gas levels were significantly improved, while apoptosis in cardiopulmonary tissue and ROS levels significantly decreased. Further testing revealed that the total extract of A. sylvestris significantly decreased the levels of interleukin-1β(IL-1β), interleukin-6(IL-6), and PAI-1 proteins in lung tissue, while increasing the expression of t-PA. Additionally, the extract reduced the levels of inflammatory cells such as leukocytes, lymphocytes, granulocytes, and monocytes in the blood, as well as the levels of P-selectin and TXA2 in plasma. Metabolomics results showed that the total extract of A. sylvestris significantly affected metabolic pathways, including arginine biosynthesis, tyrosine metabolism, and taurine and hypotaurine metabolism. In conclusion, the total extract of A. sylvestris may exert an anti-pulmonary hypertension effect by inhibiting the TGF-β1/Smad3 signaling pathway, thereby alleviating immune-inflammatory responses and thrombosis.
Animals ; Male ; Smad3 Protein/metabolism* ; Transforming Growth Factor beta1/metabolism* ; Rats, Sprague-Dawley ; Rats ; Signal Transduction/drug effects* ; Hypertension, Pulmonary/genetics* ; Thrombosis/immunology* ; Drugs, Chinese Herbal/administration & dosage* ; Humans ; Apoptosis/drug effects*