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.

Background Asthma poses a serious threat to children's growth, development, and mental health, thus there has been an increasing focus on the control of asthma morbidity in children and the assessment of its risk factors. A growing body of research has found that exposure to ambient air pollutants an significatly increase the risk of childhood asthma. Objective To understand the changes of ambient air pollutant concentrations in Nanjing and asthma outpatient visits to Nanjing Children's Hospital, and to quantitatively analyze the effects of exposure to different ambient air pollutants on children's asthma outpatient visits. Methods Daily data of ambient air pollutants fine particulate matter (PM_2.5), inhalable particle (PM₁₀), sulfur dioxide (SO₂), nitrogen dioxide (NO₂), carbon monoxide (CO), ozone (O₃), meteorological factors (air temperature & relative humidity), and outpatient visits due to asthma in the hospital from January 1, 2019 to December 31, 2023 were collected, and a generalized additive model based on quasi poisson distributions was used to quantitatively analyze the short-term effects of ambient air pollutant exposure on outpatient visits due to asthma in the hospital. Results The annual average concentrations of PM_2.5, PM₁₀, SO₂, and NO₂ in Nanjing from 2019 to 2023 did not exceed the national limits. For single-day lagged effects, the single-pollutant model showed that the effects of PM_2.5, PM₁₀, NO₂, and CO on children's asthma outpatient visits were greatest for every 10 units increase at lag0, with excess risk (ER) of 1.39% (95%CI: 0.65%, 2.14%), 1.46% (95%CI: 0.97%, 1.95%), 5.46% (95%CI: 4.36%, 6.57%), and 0.18% (95%CI: 0.11%, 0.26%), respectively, and SO₂ reached the maximum effect at lag1, with an ER of 23.15% (95%CI: 13.57%, 33.53%) for each 10 units increase in concentration. Different pollutants reached their maximum cumulative lag effects at different time. The PM₁₀, PM_2.5, SO₂, NO₂, and CO showed the largest cumulative lag effects at lag01, lag01, lag02, lag02, and lag03, respectively, with ERs of 1.35% (95%CI: 0.77%, 1.92%), 0.96% (95%CI: 0.10%, 1.83%), 28.50% (95%CI: 15.49%, 42.98%), 6.92% (95%CI: 5.53%, 8.33%), and 0.31% (95%CI: 0.20%, 0.42%), respectively. The influences of PM_2.5 and PM₁₀ on outpatient visits due to asthma in the hospital became more pronounced with advancing age, while the associations with NO₂, SO₂, and CO were weakened as children grew older. Conclusion Ambient air pollutants (PM_2.5, PM₁₀, SO₂, NO₂, CO) can increase childhood asthma visits, and different pollutants have varied effects on the number of asthmatic children's visits at different ages.

Objective To analyze the current research status and hotspot issues of performance assessment in tertia-ry public hospitals in China,providing reference for subsequent research and practice.Methods Using"performance assessment of tertiary public hospitals"as the main keyword,a total of 520 articles were retrieved from the CNKI ac-ademic journal database from January 30,2019,to January 30,2024.After further screening of literature based on the inclusion and exclusion criteria,a total of 364 eligible articles were obtained.Visual analysis was conducted using the VOSviewer tool.Results The number of publications increased annually from 2019 to 2021,with a decline ob-served in 2022-2023."Chinese Journal of Health"published the most articles on performance assessment in tertiary public hospitals.Research institutions mainly focused on universities,health administrative departments,and hospi-tals.The hotspot clusters of research included performance assessment,public hospitals,target management,high-quality development,tertiary hospitals,and operational efficiency.Conclusion Performance assessment in tertia-ry public hospitals has received widespread attention,with rich connotations and obvious guiding effects,but further research is needed to deepen and explore related topics.

Objective To analyze the current research status and hotspot issues of performance assessment in tertia-ry public hospitals in China,providing reference for subsequent research and practice.Methods Using"performance assessment of tertiary public hospitals"as the main keyword,a total of 520 articles were retrieved from the CNKI ac-ademic journal database from January 30,2019,to January 30,2024.After further screening of literature based on the inclusion and exclusion criteria,a total of 364 eligible articles were obtained.Visual analysis was conducted using the VOSviewer tool.Results The number of publications increased annually from 2019 to 2021,with a decline ob-served in 2022-2023."Chinese Journal of Health"published the most articles on performance assessment in tertiary public hospitals.Research institutions mainly focused on universities,health administrative departments,and hospi-tals.The hotspot clusters of research included performance assessment,public hospitals,target management,high-quality development,tertiary hospitals,and operational efficiency.Conclusion Performance assessment in tertia-ry public hospitals has received widespread attention,with rich connotations and obvious guiding effects,but further research is needed to deepen and explore related topics.

Objective To analyze the current research status and hotspot issues of performance assessment in tertia-ry public hospitals in China,providing reference for subsequent research and practice.Methods Using"performance assessment of tertiary public hospitals"as the main keyword,a total of 520 articles were retrieved from the CNKI ac-ademic journal database from January 30,2019,to January 30,2024.After further screening of literature based on the inclusion and exclusion criteria,a total of 364 eligible articles were obtained.Visual analysis was conducted using the VOSviewer tool.Results The number of publications increased annually from 2019 to 2021,with a decline ob-served in 2022-2023."Chinese Journal of Health"published the most articles on performance assessment in tertiary public hospitals.Research institutions mainly focused on universities,health administrative departments,and hospi-tals.The hotspot clusters of research included performance assessment,public hospitals,target management,high-quality development,tertiary hospitals,and operational efficiency.Conclusion Performance assessment in tertia-ry public hospitals has received widespread attention,with rich connotations and obvious guiding effects,but further research is needed to deepen and explore related topics.

Objective To analyze the current research status and hotspot issues of performance assessment in tertia-ry public hospitals in China,providing reference for subsequent research and practice.Methods Using"performance assessment of tertiary public hospitals"as the main keyword,a total of 520 articles were retrieved from the CNKI ac-ademic journal database from January 30,2019,to January 30,2024.After further screening of literature based on the inclusion and exclusion criteria,a total of 364 eligible articles were obtained.Visual analysis was conducted using the VOSviewer tool.Results The number of publications increased annually from 2019 to 2021,with a decline ob-served in 2022-2023."Chinese Journal of Health"published the most articles on performance assessment in tertiary public hospitals.Research institutions mainly focused on universities,health administrative departments,and hospi-tals.The hotspot clusters of research included performance assessment,public hospitals,target management,high-quality development,tertiary hospitals,and operational efficiency.Conclusion Performance assessment in tertia-ry public hospitals has received widespread attention,with rich connotations and obvious guiding effects,but further research is needed to deepen and explore related topics.

Objective To analyze the current research status and hotspot issues of performance assessment in tertia-ry public hospitals in China,providing reference for subsequent research and practice.Methods Using"performance assessment of tertiary public hospitals"as the main keyword,a total of 520 articles were retrieved from the CNKI ac-ademic journal database from January 30,2019,to January 30,2024.After further screening of literature based on the inclusion and exclusion criteria,a total of 364 eligible articles were obtained.Visual analysis was conducted using the VOSviewer tool.Results The number of publications increased annually from 2019 to 2021,with a decline ob-served in 2022-2023."Chinese Journal of Health"published the most articles on performance assessment in tertiary public hospitals.Research institutions mainly focused on universities,health administrative departments,and hospi-tals.The hotspot clusters of research included performance assessment,public hospitals,target management,high-quality development,tertiary hospitals,and operational efficiency.Conclusion Performance assessment in tertia-ry public hospitals has received widespread attention,with rich connotations and obvious guiding effects,but further research is needed to deepen and explore related topics.

Objective To analyze the current research status and hotspot issues of performance assessment in tertia-ry public hospitals in China,providing reference for subsequent research and practice.Methods Using"performance assessment of tertiary public hospitals"as the main keyword,a total of 520 articles were retrieved from the CNKI ac-ademic journal database from January 30,2019,to January 30,2024.After further screening of literature based on the inclusion and exclusion criteria,a total of 364 eligible articles were obtained.Visual analysis was conducted using the VOSviewer tool.Results The number of publications increased annually from 2019 to 2021,with a decline ob-served in 2022-2023."Chinese Journal of Health"published the most articles on performance assessment in tertiary public hospitals.Research institutions mainly focused on universities,health administrative departments,and hospi-tals.The hotspot clusters of research included performance assessment,public hospitals,target management,high-quality development,tertiary hospitals,and operational efficiency.Conclusion Performance assessment in tertia-ry public hospitals has received widespread attention,with rich connotations and obvious guiding effects,but further research is needed to deepen and explore related topics.

Objective To analyze the current research status and hotspot issues of performance assessment in tertia-ry public hospitals in China,providing reference for subsequent research and practice.Methods Using"performance assessment of tertiary public hospitals"as the main keyword,a total of 520 articles were retrieved from the CNKI ac-ademic journal database from January 30,2019,to January 30,2024.After further screening of literature based on the inclusion and exclusion criteria,a total of 364 eligible articles were obtained.Visual analysis was conducted using the VOSviewer tool.Results The number of publications increased annually from 2019 to 2021,with a decline ob-served in 2022-2023."Chinese Journal of Health"published the most articles on performance assessment in tertiary public hospitals.Research institutions mainly focused on universities,health administrative departments,and hospi-tals.The hotspot clusters of research included performance assessment,public hospitals,target management,high-quality development,tertiary hospitals,and operational efficiency.Conclusion Performance assessment in tertia-ry public hospitals has received widespread attention,with rich connotations and obvious guiding effects,but further research is needed to deepen and explore related topics.

Objective:To evaluate the diagnostic efficacy and practicality of the Jaundice color card (JCard) as a screening tool for neonatal jaundice.Methods:Following the standards for reporting of diagnostic accuracy studies (STARD) statement, a multicenter prospective study was conducted in 9 hospitals in China from October 2019 to September 2021. A total of 845 newborns who were admitted to the hospital or outpatient department for liver function testing due to their own diseases. The inclusion criteria were a gestational age of ≥35 weeks, a birth weight of ≥2 000 g, and an age of ≤28 days. The neonate′s parents used the JCard to measure jaundice at the neonate′s cheek. Within 2 hours of the JCard measurement, transcutaneous bilirubin (TcB) was measured with a JH20-1B device and total serum bilirubin (TSB) was detected. The Pearson′s correlation analysis, Bland-Altman plots and the receiver operating characteristic (ROC) curve were used for statistic analysis.Results:Out of the 854 newborns, 445 were male and 409 were female; 46 were born at 35-36 weeks of gestational age and 808 were born at ≥37 weeks of gestational age. Additionally, 432 cases were aged 0-3 days, 236 cases were aged 4-7 days, and 186 cases were aged 8-28 days. The TSB level was (227.4±89.6) μmol/L, with a range of 23.7-717.0 μmol/L. The JCard level was (221.4±77.0) μmol/L and the TcB level was (252.5±76.0) μmol/L. Both the JCard and TcB values showed good correlation ( r=0.77 and 0.80, respectively) and agreements (96.0% (820/854) and 95.2% (813/854) of samples fell within the 95% limits of agreement, respectively) with TSB. The JCard value of 12 had a sensitivity of 0.93 and specificity of 0.75 for identifying a TSB ≥205.2?μmol/L, and a sensitivity of 1.00 and specificity of 0.35 for identifying a TSB ≥342.0?μmol/L. The TcB value of 205.2?μmol/L had a sensitivity of 0.97 and specificity of 0.60 for identifying TSB levels of 205.2 μmol/L, and a sensitivity of 1.00 and specificity of 0.26 for identifying TSB levels of 342.0 μmol/L. The areas under the ROC curve (AUC) of JCard for identifying TSB levels of 153.9, 205.2, 256.5, and 342.0 μmol/L were 0.96, 0.92, 0.83, and 0.83, respectively. The AUC of TcB were 0.94, 0.91, 0.86, and 0.87, respectively. There were both no significant differences between the AUC of JCard and TcB in identifying TSB levels of 153.9 and 205.2 μmol/L (both P>0.05). However, the AUC of JCard were both lower than those of TcB in identifying TSB levels of 256.5 and 342.0 μmol/L (both P<0.05). Conclusions:JCard can be used to classify different levels of bilirubin, but its diagnostic efficacy decreases with increasing bilirubin levels. When TSB level are ≤205.2 μmol/L, its diagnostic efficacy is equivalent to that of the JH20-1B. To prevent the misdiagnosis of severe jaundice, it is recommended that parents use a low JCard score, such as 12, to identify severe hyperbilirubinemia (TSB ≥342.0 μmol/L).