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.

Leonurine(SCM-198)was discovered as one of the active constituents of the Herba Leonuri(HL).Now it can be artificially synthesized.Several recent researches has proven that it exhibits anti-inflammatory effect in several systems in animal models and cell culture in vitro.The key mechanism involves downgrading the activity of nuclear transcription factor-κB(NF-κB),thereby inhibiting the phosphorylation of several signal pathways such as PI3K/Akt,MAPK,ERK,and JNK,or upregulating the activity of Nrf2 related pathways,resulting in downregulated expression of inflammatory cytokines such as tumor necrosis factor-α(TNF-α),IL-1β,IL-2,IL-6,IL-8,inducible nitric oxide synthase(iNOS),cyclooxygenase-2(COX-2),chemokines,adhesion molecules,etc.Owing to the advantages of high safety and efficiency,the ease of administration,as well as its effectiveness in many organs and systems,leonurine has a widely prospect for future research and clinical applications.This article reviews the progress in the fundamental research of leonurine in multiple inflammation-related disease,and it could be expect to offer new possibilities for the treatment of these disease.

Background/Aims: Despite the high efficacy of direct-acting antivirals (DAAs), approximately 1–3% of hepatitis C virus (HCV) patients fail to achieve a sustained virological response. We conducted a nationwide study to investigate risk factors associated with DAA treatment failure. Machine-learning algorithms have been applied to discriminate subjects who may fail to respond to DAA therapy. Methods: We analyzed the Taiwan HCV Registry Program database to explore predictors of DAA failure in HCV patients. Fifty-five host and virological features were assessed using multivariate logistic regression, decision tree, random forest, eXtreme Gradient Boosting (XGBoost), and artificial neural network. The primary outcome was undetectable HCV RNA at 12 weeks after the end of treatment. Results: The training (n=23,955) and validation (n=10,346) datasets had similar baseline demographics, with an overall DAA failure rate of 1.6% (n=538). Multivariate logistic regression analysis revealed that liver cirrhosis, hepatocellular carcinoma, poor DAA adherence, and higher hemoglobin A1c were significantly associated with virological failure. XGBoost outperformed the other algorithms and logistic regression models, with an area under the receiver operating characteristic curve of 1.000 in the training dataset and 0.803 in the validation dataset. The top five predictors of treatment failure were HCV RNA, body mass index, α-fetoprotein, platelets, and FIB-4 index. The accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of the XGBoost model (cutoff value=0.5) were 99.5%, 69.7%, 99.9%, 97.4%, and 99.5%, respectively, for the entire dataset. Conclusions Machine learning algorithms effectively provide risk stratification for DAA failure and additional information on the factors associated with DAA failure.

Objective To analyze the genetic subtypes of human immunodeficiency virus (HIV) and the prevalence of pretreatment drug resistance in the newly reported HIV-infected men in Guangxi. Methods The stratified random sampling method was employed to select the newly reported HIV-infected men aged≥50 years old in 14 cities of Guangxi from January to June in 2020.The pol gene of HIV-1 was amplified by nested reverse transcription polymerase chain reaction and then sequenced.The mutation sites associated with drug resistance and the degree of drug resistance were then analyzed. Results A total of 615 HIV-infected men were included in the study.The genetic subtypes of CRF01_AE,CRF07_BC,and CRF08_BC accounted for 57.4% (353/615),17.1% (105/615),and 22.4% (138/615),respectively.The mutations associated with the resistance to nucleoside reverse transcriptase inhibitors (NRTI),non-nucleoside reverse transcriptase inhibitors (NNRTI),and protease inhibitors occurred in 8 (1.3%),18 (2.9%),and 0 patients,respectively.M184V (0.7%) and K103N (1.8%) were the mutations with the highest occurrence rates for the resistance to NRTIs and NNRTIs,respectively.Twenty-two (3.6%) patients were resistant to at least one type of inhibitors.Specifically,4 (0.7%),14 (2.3%),4 (0.7%),and 0 patients were resistant to NRTIs,NNRTIs,both NRTIs and NNRTIs,and protease inhibitors,respectively.The pretreatment resistance to NNRTIs had much higher frequency than that to NRTIs (2.9% vs.1.3%;χ²=3.929,P=0.047).The prevalence of pretreatment resistance to lamivudine,zidovudine,tenofovir,abacavir,rilpivirine,efavirenz,nevirapine,and lopinavir/ritonavir was 0.8%, 0.3%, 0.7%, 1.0%, 1.3%, 2.8%, 2.9%, and 0, respectively. Conclusions CRF01_AE,CRF07_BC,and CRF08_BC are the three major strains of HIV-infected men≥50 years old newly reported in Guangxi,2020,and the pretreatment drug resistance demonstrates low prevalence.
Male ; Humans ; Middle Aged ; Reverse Transcriptase Inhibitors/therapeutic use* ; HIV Infections/drug therapy* ; Drug Resistance, Viral/genetics* ; China/epidemiology* ; Mutation ; HIV-1/genetics* ; Protease Inhibitors/therapeutic use* ; Genotype

ObjectiveTo explore the practical value of environment-friendly sample release agent combined with ultrasound in the preparation of pathological tissue sections. MethodsFrom February 2013 to December 2022， 2 518 pathological specimens submitted by Foshan Municipal Hospital of Traditional Chinese Medicine were selected as the study objects. Two samples of the same specimen were randomly divided into two groups： the environment-friendly fast group， in which the pathological tissue sections were made by using the environment-friendly sample release agent combined with ultrasound； and the traditional group， in which formaldehyde， ethanol and xylene were used to make slices in the conventional way. The differences of hematoxylin （HE） staining effect， immunohistochemistry （IHC） staining effect and MDM2 gene detection result of atypical lipomatous tumor/highly differentiated liposarcoma （ALT/WDL） tissue sections between the two groups were compared. Results① The wax of the two groups' pathological tissues was dehydrated well and the tissue hardness was moderate. After HE staining， the sections of the two groups were intact， without cracks and tremor marks， and the contrast between nucleus and cytoplasm was appropriate， with good transparency， uniform staining， and no tissue loss. The excellent rate and score of HE staining in the environmental fast group were higher than those in the traditional group， but the difference was not statistically significant （χ² = 3.125，P₁ = 0.070；t = 0.965，P₂ = 0.334）. ②After IHC staining of the two groups of sections， the positive location of the cells was accurate， the staining was specific and uniform， the staining intensity was moderate， the staining sensitivity was good， and there was no tissue loss. The excellent rate of IHC staining and the positive rate of IHC staining in the environmental fast group were lower than those in the traditional group， but the difference was not statistically significant （χ₁² = 2.769，P₁ = 0.092；χ₂² = 0.800，P₂ = 0.375）. ③The background and outline of the two groups of WDL tissue sections were clear， the staining was uniform， the cells were clear and visible， the nuclear boundary was clear， the hybridization signal was clear and bright under the background fluorescence， and there was no miscellaneous signal. The two groups of sections were hybridized successfully， and MDM2 showed positive amplification. The number of cells successfully hybridized in the environment-friendly fast group was lower than that in the traditional group， but the difference was not statistically significant （t = 1.414，P = 0.230）. ConclusionsThe tissue treatment method of using environment-friendly sample release agent combined with ultrasound can ensure the detection effect of HE staining， IHC staining and MDM2 gene detection of pathological tissue sections， and is more efficient and environment-friendly， suitable for promotion and use in hospitals at all levels.

In the outbreak of COVID-19,triage procedures based on epidemiology were implemented in a local hospital in Changsha to control the transmission of SARS-CoV-2 and avoid healthcare-associated infection.This re-trospective study analyzed the data collected during the triage period and found that COVID-19 patients were en-riched 7 folds into the Section A designated for patients with obvious epidemiological history.On the other side,nearly triple amounts of visits were received at the Section B for patients without obvious epidemiological history.8 COVID-19 cases were spotted out of 247 suspected patients.More than 50％of the suspected patients were submi-tted to multiple rounds of nucleic acid analysis for SARS-CoV-2 infection.Of the 239 patients who were diagnosed as negative of the virus infection,188 were successfully revisited and none was reported as COVID-19 case.Of the 8 COVID-19 patients,3 were confirmed only after multiple rounds of nucleic acid analysis.Besides comorbidities,delayed sharing of epidemiological history added complexity to the diagnosis in practice.The triaging experience and strategy will be helpful for the control of infectious diseases in the future.

Objective To establish a ultra performance liquid chromatography(UPLC)fingerprint of extract of Cuscutae Semen,and analyze the relationship between the UPLC fingerprint and antioxidant activity.Methods The fingerprint of 11 batches of extract of Cuscutae Semen were determined by UPLC method,the antioxidant activity of Cuscutae Semen in vitro was determined by 1,1-diphenyl-2-picrylhydrazine radical,2,2-diazo-bis(3-ethylbenzothiazole-6-sulfonic acid)diamine salt,and the correlation between the fingerprints and antioxidant activity was analyzed by orthogonal partial least squares(OPLS)and gray correlation method.The key substances that contributed greatly to the antioxidant activity were selected.Results The extract of Cuscutae Semen contains 21 common peaks,all of which exhibited a similarity of more than 0.97.By comparing with the reference sample,10 peaks were identified,of which peak 5 was neochlorogenic acid,peak 8 was chlorogenic acid,peak 9 was cryptochlorogenic acid,peak 10 was caffeic acid,peak 12 was coumaric acid,peak 15 was hyperin,peak 16 was isoquercitrin,peak 17 was astragaloside,peak 20 was quercetin,and peak 21 was kaempferol.According to the grey correlation degree and OPLS results,the peaks 8,15,16 and 18 were positively correlated with the antioxidant activity,and were thus considered to be main effective components.Conclusion The antioxidant activity of Cuscutae Semen is the result of the combined effect of multiple components.The fingerprint and antioxidant spectrum analysis can provide evidential reference for further research of Cuscutae Semen.

Objective: To analyze the course of disease and epidemiological parameters of COVID-19 and provide evidence for making prevention and control strategies. Methods: To display the distribution of course of disease of the infectors who had close contacts with COVID-19 cases from January 1 to March 15, 2020 in Guangdong Provincial, the models of Lognormal, Weibull and gamma distribution were applied. A descriptive analysis was conducted on the basic characteristics and epidemiological parameters of course of disease. Results: In total, 515 of 11 580 close contacts were infected, with an attack rate about 4.4%, including 449 confirmed cases and 66 asymptomatic cases. Lognormal distribution was fitting best for latent period, incubation period, pre-symptomatic infection period of confirmed cases and infection period of asymptomatic cases; Gamma distribution was fitting best for infectious period and clinical symptom period of confirmed cases; Weibull distribution was fitting best for latent period of asymptomatic cases. The latent period, incubation period, pre-symptomatic infection period, infectious period and clinical symptoms period of confirmed cases were 4.50 (95%CI:3.86-5.13) days, 5.12 (95%CI:4.63-5.62) days, 0.87 (95%CI:0.67-1.07) days, 11.89 (95%CI:9.81-13.98) days and 22.00 (95%CI:21.24-22.77) days, respectively. The latent period and infectious period of asymptomatic cases were 8.88 (95%CI:6.89-10.86) days and 6.18 (95%CI:1.89-10.47) days, respectively. Conclusion: The estimated course of COVID-19 and related epidemiological parameters are similar to the existing data.
COVID-19 ; Cohort Studies ; Contact Tracing ; Humans ; Incidence ; Prospective Studies

Objective To evaluate the visual improvement of therapeutic plasma exchange (TPE) for refractory optic neuritis (ON) patients in acute phase.Methods Seventy-five affected eyes from 44 refractory ON patients with severe visual defect or resistance to high-dose intravenous methylprednisolone (IVMP) therapy,who were admitted to The Chinese PLA General Hospital between January 2015 and August 2016,were recruited and received TPE therapy.Among these patients,11 were male and 33 were female;the average age was 39.1 ± 13.9;31 patients had two affected eyes,13 patients had one affected eye.The course of the disease on the group of patients were more than 2 weeks,and the visual acuity worsened for more than 10 days and continued to deteriorate.TPE treatment was performed on all of the patients.BCVA was recorded before and 24 h after treatment,and the visual function was scored using visual outcome scale (VOS).At the same time,the adverse reactions of TPE treatment were observed.The paired t-test was used to compare the VOS before and after treatment.The correlation between VOS before and after treatment was analyzed by Linear-by-Linear correlation analysis.Results Among 75 affected eyes,the post-therapy VOS 3.89 ±2.13 was significantly improved from pre-therapy VOS 5.56± 1.69 (t=6.77,P＜0.001).Forty-eight of 75 eyes were improved at lease 1 score of VOS,the overall rate of visual improvement was 64.0％.Especially among the eyes with initial vision of light perception,an improved rate of 82.4％ was presented.75.0％ in those eyes with initial vision of count fingers and 67.7％ in no light perception.Linear-by-Linear correlation analysis showed a significant linear correlation between the scores of VOS before and after TPE treatment (r=0.398,P=0.01).During the course of TPE treatment,5 patients had mild adverse reactions such as low calcium reaction and allergic reaction and were well controlled after treatment.Conclusion Using TPE to treat refractory ON in acute phased can improve the visual function of patients.

Objective To investigate whether the protective effects of leonurine (SCM-198) against endotoxin induced uveitis (EIU) of SD rats caused by lipopolysaccharide (LPS) was existing,and discuss the underlying mechanisms.Methods Thirty-six normal healthy male SD rats were divided into 3 groups randomly with the same baseline bodyweight and feeding conditions.All rats received intragastric administration every day.The experimental group was devided into 4 subgroups,rats in these subgroups received SCM-198 intragastric administration by as the dose of 10,20,40 and 80 mg/kg bodyweight per day,rats in the negative control group received intragastric administration of normal saline 10 mL/kg per day,rats in the positive control group received intragastric administration ofdexamethasone (DEX) 0.5 mg/kg bodyweight per day.All rats received a 21-day-intragastric administration.The body weight of all rats was monitored every 7 days.The electroretinogram (ERG) examination was taken in the 18th day.All rats received a 100 mg S.typhi LPS intraperitoneal injection after the 21st intragastric administration.Twenty-four hours later,following anaesthesia,all rats received another ERG examination,and inflammation was scoring under microscope by 2 experienced ophthalmologists,after that the aqueous humor of all rats was collected from the left eye.The aqueous humor was kept in-80 ℃ immediately.Then the rats were sacrificed and the right eyes were immediately enucleated to finish the HE staining and immunohistochemistry (IHC) staining examination of tumor necrosis factor-α (TNF-α) and intercellular cell adhesion molecule-1 (ICAM-1).The total amount of protein in aqueous humor was detected by BCA test.Western blot was used to examine the expression of TNF-α,interleukin-1β (IL-1β),IL-6 and ICAM-1.All data was analyzed by SPSS 19.0,and differences were considered significant at P＜0.05.Results The body weight of the rats in positive control group was significantly lower (P＜0.05) than the experimental group and the negative control group after the 21-day-intragastric administration.The inflammatory score of experimental group was lower than that of the negative control group,but higher than the score of positive control group.The HE staining sections showed the similar results.The a wave of ERG in 0.01 cd of rats received 20 mg/kg SCM-198 daily intragastric administration after LPS injection was significantly lower than that before the LPS injection (P＜0.05),also lower than other groups after LPS injection.The expression of TNF-α,IL-6 and IL-1β in the aqueous humor of the rats in the subgroup of SCM-198 10 mg/kg daily intragastric administration was lower than other groups.Conclusions Intragastric administration of SCM-198 has protective effect against endotoxin induced uveitis in SD rats without obvious adverse reaction,which could alleviate the imflammatory reaction and the damage to the uvea construction.NF-κB plays an important role in the reaction.Thus,SCM-198 is a candidate potent compound with potential therapeutic applications in inflammation associated eye diseases.While the best mode and dose of administration should be further investigated.