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.

Patients with severe trauma require an extremely timely treatment and transfusion plays an irreplaceable role in the emergency treatment of such patients. An increasing number of evidence-based medicinal evidences and clinical practices suggest that patients with severe traumatic bleeding benefit from early transfusion of low-titer group O whole blood or hemostatic resuscitation with red blood cells, plasma and platelet of a balanced ratio. However, the current domestic mode of blood supply cannot fully meet the requirements of timely and effective blood transfusion for emergency treatment of patients with severe trauma in clinical practice. In order to solve the key problems in blood supply and blood transfusion strategies for emergency treatment of severe trauma, Branch of Clinical Transfusion Medicine of Chinese Medical Association, Group for Trauma Emergency Care and Multiple Injuries of Trauma Branch of Chinese Medical Association, Young Scholar Group of Disaster Medicine Branch of Chinese Medical Association organized domestic experts of blood transfusion medicine and trauma treatment to jointly formulate Chinese expert consensus on blood support mode and blood transfusion strategies for emergency treatment of severe trauma patients ( version 2024). Based on the evidence-based medical evidence and Delphi method of expert consultation and voting, 10 recommendations were put forward from two aspects of blood support mode and transfusion strategies, aiming to provide a reference for transfusion resuscitation in the emergency treatment of severe trauma and further improve the success rate of treatment of patients with severe trauma.

Objective:To explore the efficacy of subcutaneous injection of granulocyte-macrophage colony-stimulating factor (GM-CSF) in preventing invasive fungal disease (IFD) in patients with multiple myeloma (MM).Methods:The clinical data of 222 patients who were admitted to the Second Hospital of Harbin Medical University from January 2015 to June 2021 were retrospectively analyzed. The patients was given GM-CSF (3-5 μg·kg -1·d -1, GM-CSF group) or granulocyte colony-stimulating factor (G-CSF, 2-5 μg·kg -1·d -1, G-CSF group) when neutrophils (ANC) ≤1.5×10 9/L after induction chemotherapy. Patients were discontinued when white blood cell count (WBC) ≥10.0×10 9/L. The incidence of IFD (including confirmed, clinical and proposed diagnosis) and breakthrough invasive fungal infections was compared between the two groups. Results:The incidence of IFD was 8.1% (18/222) in all patients. The incidence of IFD was 3.5% (3/85) and 10.9% (15/137) in the GM-CSF and G-CSF groups, respectively, and the difference between the two groups was statistically significant ( χ2 = 3.88, P = 0.049). In 9 patients of GM-CSF group receiving fungal infection prophylaxis and in 15 patients of G-CSF group receiving fungal infection prophylaxis, the incidence of breakthrough invasive fungal infections was 0 and 7 cases, respectively, and the difference between the two groups was statistically significant ( P = 0.022). Conclusions:GM-CSF application in MM patients can reduce the incidence of IFD and breakthrough invasive fungal infections.

Objective: To evaluate the recognition of acute respiratory infection (ARI) by a pretrained model based on electronic medical records (EMRs). Methods: 38 581 EMRs were obtained from Chongqing University Three Gorges Hospital in December 2021. Bidirectional encoder representation from transformers (BERT) pretrained model was used to identify ARI in EMRs. The results of medical professionals were considered as the gold standard to calculate the sensitivity, specificity, Kappa value, and area under the curve of the receiver operating characteristic (AUC). Results: There were 3 817 EMRs in the test set, with 1 200 ARIs. A total of 1 205 cases were determined as ARI by the model, with a sensitivity of 92.67% (1 112/1 200) and a specificity of 96.45% (2 524/2 617). The model identified ARI with similar accuracy in males and females (AUCs 0.95 and 0.94, respectively), and was more accurate in identifying ARI cases in those aged less than 18 than in adults 18-59 and adults 60 and older (AUCs 0.94, 0.89 and 0.94, respectively). The current model had a better identification of ARIs in outpatient patients than that in hospitalized patients, with AUCs of 0.74 and 0.95, respectively. Conclusion: The use of the BERT pretrained model based on EMRs has a good performance in the recognition of ARI cases, especially for the outpatients and juveniles. It shows a great potential to be applied to the monitoring of ARI cases in medical institutions.
Adult ; Male ; Female ; Humans ; Electronic Health Records ; Respiratory Tract Infections/diagnosis* ; Outpatients

OBJECTIVE To study the quality grade stand ard of the premature Forsythia suspensa . METHODS A total of 138 batches of premature F. suspensa were collected from the main producing areas of F. suspensa in China. According to 2020 edition of Chinese Pharmacopoeia ，the contents of impurities ，moisture，ethanol-soluble extract ，volatile oil ，forsythin and forsythoside A in the premature F. suspense were determined ，and the qualified samples were screened. AHP-PCA mixed weighting method was used to give comprehensive weight to the indicators （except for the limit of impurity ）. The comprehensive score of the samples was calculated. The suggestions on the quality grade division of premature F. suspensa were put forward according to cluster analysis of K-mean value. RESULTS & CONCLUSIONS The contents of impurities ，moisture，ethanol-soluble extract ，volatile oil ，forsythin and forsythoside A in the premature F. suspense were 0-7.80％，1.60％-8.18％，13.13％-61.60％，0.21％-3.47％，0.02％-2.15％ and 0.79％-14.04％，respectively；average contents of them were 1.24％，4.97％，34.88％，2.01％，0.42％，6.86％，respectively. Totally 47 batches of 138 batches were qualified in all indexes. It is suggested that the quality grade of the premature F. suspense can be divided into three grades ：in first grade of F. suspense ，the contents of volatile oil ，forsythin，forsythoside A ， ethanol-soluble extract and moisture were ≥2.40％，≥0.59％，≥8.34％，≥38.66％ and ≤4.99％，respectively；in second grade of F. suspense ，the contents of above indicators were ≥2.26％，≥0.41％，≥7.47％，≥32.58％ and ≤5.33％，respectively；in third grade of F. suspense ，the contents of above indicators were ≥2.15％，≥0.32％，≥4.60％，≥31.52％ and≤7.23％，respectively.

Based on the idea of multi-target drug design, taking p-aminosalicylic acid (PAS) as the parent nucleus, the unreported target molecules TM1 and TM2 were designed with PAS, isonicotinic acid and fluoroquinolone as three structural units conjugated by different linkers. Sixteen target molecules were synthesized by multi-step reaction, and their activities against Mycobacterium tuberculosis and human pathogenic bacteria were evaluated. The results showed that the anti-tuberculosis activity of TM2a was stronger than those of the assayed fluoroquinolones, while TM1a was comparable to that of clinafloxacin, the most active compound of the positive control fluoroquinolones; TM1a showed the strongest inhibitory activity to all almost tested strains, TM1b and TM2a showed very strong inhibitory activity to most strains, and TM1h/2h had strong inhibitory activity to some strains; The inhibitory activities of TM1a/1h on Staphylococcus aureus ATCC14125 are much stronger than those of fluoroquinolones, which eminently deserves further study. The hemolysis test results showed that the highly active molecules TM1a and TM2a exhibited relative safety below the concentrations of 8 and 32 μg·mL^-1, respectively. In this study, a new hybrid molecule of three molecular pharmacophores with PAS as the parent nucleus was synthesized for the first time, and some of which have highly strong antibacterial activity, which provides a new idea for the research and development of antibiotics.

OBJECTIVE: To investigate the effect of protein kinase A (PKA) activation on aggregation funetion of platelets in vitro. METHODS: The peripheral blood of healthy adults were collected, and the washed platelets were gained from collected peripheral blood. The washed platelets were treated with PKA activator Forskolin, then the platelet aggregation was induced by using Ristocetin, Thrombin, Collagen and ADP respectively, the platelet aggregation level was detected by the platelet aggregator. RESULTS: Compared with the controls, 5 μmol/L forskolin significantly inhibited ADP and collagen-induced platelet aggregation (P＜0.001), and showed mild inhibiting effect on Thrombin-induced platelet aggregation (P＜0.05). 2.5-10 μmol/L forskolin significantly inhibited ADP and Collagen -induced platelet aggregation (P＜0.001); but not showed significantly inhibitory effects on Ristocetin-induced platelet aggregation (P＞0.05). CONCLUSION PKA activation inhibits agonists-induced platelet aggregation.
Blood Platelets ; Cyclic AMP-Dependent Protein Kinases ; Humans ; Platelet Aggregation ; Platelet Aggregation Inhibitors ; Ristocetin ; Thrombin

BACKGROUND: Pulmonary deportation of hydatidiform mole is an exceedingly rare entity. The underlying mechanisms and proper management strategies remain unclear based on sporadic case reports over the past six decades. This study aimed to investigate the clinical features and rational treatment of patients with benign molar pregnancies with pulmonary deportation based on our experience. METHODS: Medical records of 20 cases of hydatidiform mole with pulmonary deportation were retrospectively reviewed at Peking Union Medical College Hospital from November 2006 to May 2019. The detailed information of all patients was recorded and analyzed. Patients were divided into different groups according to their characteristics and Mann-Whitney U test was used to compare the duration to achieve a normal β-human chorionic gonadotrophin (β-hCG) level after the first evacuation among groups. RESULTS: Initial pulmonary computed tomography scans showed suspected bilateral, left and right chest deportation of hydatidiform mole in 12, four, and four patients, respectively, with the maximum nodular diameter ranging from 0.6 to 1.2 cm. Ten patients achieved lesion resolution while the remaining ten patients achieved decreases in the size of their pulmonary lesions. The median duration to achieve a normal β-hCG level after the first evacuation was 15.5 (13.0, 21.9) weeks. There was no significant difference in the duration to achieve a normal β-hCG level after the first evacuation between two groups based on age (≥40 years vs. < 40 years: 15.8 [12.2, 21.5] weeks vs. 15.5 [12.9, 23.0] weeks, Z = 0.094, P = 0.925), type of antecedent mole (partial mole vs. complete mole: 15.2 [12.5, 27.4] weeks vs. 15.9 [12.9, 21.5] weeks, Z = 0.165, P = 0.869), distribution of pulmonary nodules (bilateral lungs vs. unilateral lung: 15.2 [12.8, 22.5] weeks vs. 15.9 [13.2, 22.2] weeks, Z = 0.386, P = 0.700), maximum size of pulmonary nodules (>0.5 cm vs. ≤0.5 cm: 13.0 [11.3, 17.2] weeks vs. 16.0 [14.5, 23.8] weeks, Z = 1.815, P = 0.070), and number of uterine evacuations (once vs. twice or three times: 15.0 [13.0, 16.3] weeks vs. 16.0 [12.8, 23.9] weeks, Z = 0.832, P = 0.405). The post-molar cohort was followed up for 17 to 139 months, and no gestational trophoblastic neoplasia was observed. CONCLUSIONS No surgeries other than uterine evacuation and no chemotherapy regimens are recommended for such patients if they achieve satisfactory decreases in the level of hCG and gradual decrease or disappearance of pulmonary deportation nodules. Patients should be informed about the necessity of long-term follow-up. More collaborative international studies on this exceedingly rare condition may guide decisions regarding optimal management strategies.

Physical fatigue often appears after stroke, which may influence rehabilitation training and recovery. This paper introduced the causes, clinical manifestations and related factors of physical fatigue after stroke. Energy metabolism increases after stroke, which may play a role in physical fatigue after stroke, and can be managed in some ways. It is needed to research the application of energy metabolism measure in physical fatigue after stroke further.

Objective Make use of image dentate nucleus and the veins around it on susceptibility weighted images (SWI), explore the correlation between the location of hilum of dentate nucleus and the venous variation of dentate nucleus. Methods Selecting 51 healthy adults (24 men, 27 women) at the age between 18 and 30 years old to get the original images on 3. 0T MR. Process the original images by minimum intensity projections (mIP) observed and analyzed the morphology of dentate nucleus and veins around it on original and processed images. Results The length of dentate nucleus was (16. 64±0. 20)mm, and the width was (8. 36±0. 14)mm. There was no significant difference between bilateral dentate nucleus. The median angle of the long axis of the dentate nucleus was 26. 80° (interquartile distance was 34. 58°). The venous network of dentate nucleus was formed in 2 groups of veins: the lateral group, drained by the vein of the horizontal fissure and nuclear vein; the medial group, drained by vermian vein and central vein of dentate nucleus. These two groups had been further typing as follows: the lateral anterior group drained by the nuclear vein, finally opening to superior petrosal sinus; the lateral median group had plenty of small veins of lateral dentate nucleus converge into the vein of the horizontal fissure; the lateral posterior group drained by a lot of very small veins converging to vermian veins or medullary veins; the medial anterior group that the central vein of dentate nucleus and the paravermian vein were jointed at hilum of dentate nucleus, opening into straight sinus; the medial posterior group usually converged into tributaries of vermian vein, or converged with paravermian vein into tributaries of vermian vein. Totally 75. 49% of hilums of dentate nucleus were located at upper inner quadrant, the other 24. 51% of them were located at lower inner quadrant. Conclusion Dentate nucleus and its veins are clearly visible on the susceptibility weighted images, and the location of the hilum of dentate nucleus may be related to the abouchement of paravermian vein.