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.

Guided by the concept of quality by design(QbD), this study optimizes the calcination and quenching process of calcined Magnetitum and establishes the XRD characteristic spectra of calcined Magnetitum, providing a scientific basis for the formulation of quality standards. Based on the processing methods and quality requirements of Magnetitum in the Chinese Pharmacopoeia, the critical process parameters(CPPs) identified were calcination temperature, calcination time, particle size, laying thickness, and the number of vinegar quenching cycles. The critical quality attributes(CQAs) included Fe mass fraction, Fe~(2+) dissolution, and surface color. The weight coefficients were determined by combining Analytic Hierarchy Process(AHP) and the criteria importance though intercrieria correlation(CRITIC) method, and the calcination process was optimized using orthogonal experimentation. Surface color was selected as a CQA, and based on the principle of color value, the surface color of calcined Magnetitum was objectively quantified. The vinegar quenching process was then optimized to determine the best processing conditions. X-ray diffraction(XRD) was used to establish the characteristic spectra of calcined Magnetitum, and methods such as similarity evaluation, cluster analysis, and orthogonal partial least squares-discriminant analysis(OPLS-DA) were used to evaluate the quality of the spectra. The optimized calcined Magnetitum preparation process was found to be calcination at 750 ℃ for 1 h, with a laying thickness of 4 cm, a particle size of 0.4-0.8 cm, and one vinegar quenching cycle(Magnetitum-vinegar ratio 10∶3), which was stable and feasible. The XRD characteristic spectra analysis method, featuring 9 common peaks as fingerprint information, was established. The average correlation coefficient ranged from 0.839 5-0.988 1, and the average angle cosine ranged from 0.914 4 to 0.995 6, indicating good similarity. Cluster analysis results showed that Magnetitum and calcined Magnetitum could be grouped together, with similar compositions. OPLS-DA discriminant analysis identified three key characteristic peaks, with Fe_2O_3 being the distinguishing component between the two. The final optimized processing method is stable and feasible, and the XRD characteristic spectra of calcined Magnetitum was initially established, providing a reference for subsequent quality control and the formulation of quality standards for calcined Magnetitum.
X-Ray Diffraction/methods* ; Drugs, Chinese Herbal/chemistry* ; Quality Control ; Particle Size

The AP2/ERF transcription factor family is a class of transcription factors widely present in plants, playing a crucial role in regulating flowering, flower development, flower opening, and flower senescence. Based on transcriptome data from flower, leaf, and stem samples of two Lonicera macranthoides varieties, 117 L. macranthoides AP2/ERF family members were identified, including 14 AP2 subfamily members, 61 ERF subfamily members, 40 DREB subfamily members, and 2 RAV subfamily members. Bioinformatics and differential gene expression analyses were performed using NCBI, ExPASy, SOMPA, and other platforms, and the expression patterns of L. macranthoides AP2/ERF transcription factors were validated via qRT-PCR. The results indicated that the 117 LmAP2/ERF members exhibited both similarities and variations in protein physicochemical properties, AP2 domains, family evolution, and protein functions. Differential gene expression analysis revealed that AP2/ERF transcription factors were primarily differentially expressed in the flowers of the two L. macranthoides varieties, with the differentially expressed genes mainly belonging to the ERF and DREB subfamilies. Further analysis identified three AP2 subfamily genes and two ERF subfamily genes as potential regulators of flower development, two ERF subfamily genes involved in flower opening, and two ERF subfamily genes along with one DREB subfamily gene involved in flower senescence. Based on family evolution and expression analyses, it is speculated that AP2/ERF transcription factors can regulate flower development, opening, and senescence in L. macranthoides, with ERF subfamily genes potentially serving as key regulators of flowering duration. These findings provide a theoretical foundation for further research into the specific functions of the AP2/ERF transcription factor family in L. macranthoides and offer important theoretical insights into the molecular mechanisms underlying floral phenotypic differences among its varieties.
Plant Proteins/chemistry* ; Gene Expression Regulation, Plant ; Transcription Factors/chemistry* ; Lonicera/classification* ; Flowers/metabolism* ; Phylogeny ; Gene Expression Profiling ; Multigene Family

Background:Intestinal microbiota dysbiosis and impaired intestinal barrier,leading to bacterial translocation,are involved in acute pancreatitis(AP)exacerbation.Antimicrobial peptides participate in the regulation of intestinal microbiota,yet their changes and roles in the course of AP are unclear.Aims:To investigate the dynamic changes and significance of antimicrobial peptides in the ileum and pancreas among three classical AP models.Methods:Three AP mouse models were established by using cathelicidin plus lipopolysaccharide(CAE+LPS),sodium taurocholate(N-Tau)and L-arginine(L-Arg),respectively.The pathological changes of pancreatic and ileal tissues were observed and scored.Real-time PCR was applied to detect the expression levels of the proinflammatory cytokines,and antimicrobial peptides including lysozyme(LZM),secretory phospholipase A2(sPLA2),angiogenin 4(Ang4),regenerating islet-derived protein 3(REG3)family,β-defensin family,cathelicidin-related antimicrobial peptide(CRAMP),and glycoprotein 2(GP2)in ileum and/or pancreas.The association between expressions of antimicrobial peptides and the injuries of pancreas and ileum was analyzed.Results:Pancreatic and ileal injuries could be observed in all three AP models in different time points with various degrees.The pathological scores of the CAE+LPS and N-Tau models reached the highest level and then declined from 0-72 h,while those of L-Arg model progressively increased within 72 hours.Compared with the corresponding controls,the mRNA levels of LZM,sPLA2,and Ang4 in ileal tissue,and the mRNA levels of CRAMP,GP2,and β-defensins in pancreatic tissue,were generally downregulated in all three AP models(all P<0.05).CAE+LPS and N-Tau models showed a trend of initial decrease followed by partial recovery,while L-Arg model exhibited a gradual downregulation trend.The mRNA levels of REG3β and REG3γ in ileum upregulated and reached the peak at 48 h or 24 h and downregulated significantly at 72 h in all three AP models(all P<0.05);while in pancreatic tissue,both REG3β and REG3γ were generally upregulated in all three AP models(all P<0.05),but fell back in CAE+LPS and N-Tau models at 72 h.The mRNA levels of ileal β-defensins upregulated significantly in the early stage of the disease(12 h)in all three AP models(all P<0.05),and then gradually decreased.Spearman correlation coefficient analysis showed that the expressions of ileal LZM,sPLA2,and Ang4,as well as the pancreatic CRAMP,GP2,and β-defensins,were significantly negatively correlated with the pancreatic and ileal pathological scores in all three AP models(all P<0.05);but the expression of REG3β in the pancreas was significantly positively correlated with the pancreatic and ileal pathological scores(all P<0.05).Conclusions:The expressions of LZM,sPLA2,and Ang4 in the ileum,as well as the expressions of CRAMP,GP2,β-defensin family,and REG3β in the pancreas of the three classical AP models,dynamically changed with the severity of the disease.Ileal and pancreatic antimicrobial peptides may affect the injuries of pancreas and intestine during AP by regulating intestinal microbiota.

Photodynamic therapy is an emerging cancer therapy with clinical prospects, which plays a specific role in the tumor site and causes less harm to the human body. However, the toxicity of small molecules of hydrophobic photosensitizer, the tumor hypoxia microenvironment, and the biodegradability of nano-carrier systems affect its antitumor efficacy and metabolic clearance in vivo. In this paper, hexachloroplatinic acid was used as a novel oxidizing agent to initiate oxidative polymerization of pyrrole/amino pyrrole to achieve the amino functionalization; further reduced platinum acid anion in the nanostructures into platinum nanoclusters by sodium borohydride as a reducing agent to fabricate platinum nanocluster-doped polypyrrole nanoparticles (PtPPy); and finally, this functional nanoparticles delivering meso-tetra (4-carboxyphenyl) porphine (TCPP) were obtained by amide-bonded coupling of photosensitizers TCPP drug (PtPPy@T). The nanomedicine had a spherical structure, uniform morphology, a particle size of 91.93 ± 13.45 nm, and a zeta potential of -18.39 ± 1.4 mV. Experiments demonstrated that PtPPy@T could react with hydrogen peroxide overexpressed in the tumor to generate a large amount of oxygen, which could relieve the tumor hypoxia microenvironment, and at the same time, provided a sufficient substrate for the subsequent PDT; using 658 nm laser irradiation, the photodynamic effect of PtPPy@T was activated, which catalyzed the conversion of oxygen to singlet oxygen, thus triggering oxidative damage and inducing apoptosis in tumor cells; experimental studies showed that the PtPPy@T nanomedicine had a better tumor inhibitory effect in vivo and in vitro. All animal experiments were approved by the Institutional Animal Care and Use Committee of the Institute of Radiological Medicine, Chinese Academy of Medical Sciences and Peking Union Medical College (IRM/2-IACUC-2312-006).

Objective Lentivirus-mediated interference with synaptic nuclear protein γ(SNCG)in human oral squamous cell carcinoma was established to study the role of SNCG in the migration and invasion of oral squamous cell carcinoma.Methods Oral cancer CAL27 cells were infected with LV-shNC and LV-shSNCG constructed by lentivirus vector,respective,and then selected with puromycin to obtain cell lines stably interfering with SNCG,which were named NC group and experimental group,respectively.Detect the expression of SNCG through real-time quantitative polymerase chain reaction(qRT-PCR)and Western blot experiments;Transwell and scratch experiments were used to detect changes in migration and invasion ability.Results Compared with the NC group,the experimental group showed an 80％reduction in SNCG mRNA expression(P＜0.01).The relative expression level of SNCG protein was also decreased in the experimental group compared to the NC group(P＜0.01).In the NC group and the experimental group,the migration area percentages at 36 hours were 0.54±0.06 and 0.40±0.02,respectively;and at 48 hours were 0.83±0.01 and 0.47±0.05,respectively.The experimental group showed decrease in migration area compared to the NC group,and these differences were statistically significant(P＜0.05,P＜0.001).Compared to the NC group,the migration and invasion cell numbers in the experimental group(98.00±13.49 and 88.00±5.72)were significantly reduced to(48.00±2.16 and 49.00±2.94),and these differences were statistically significant(P＜0.01,P＜0.001).Conclusion Interference of SNCG expression can significantly reduce the migration and invasion ability of oral squamous cell carcinoma cells.

Photothermal therapy is a new type of tumor therapy that uses near-infrared laser to specifically activate the photothermal agent accumulated in the lesion site, so as to achieve thermal ablation of cancer cells. However, the long metabolic cycle and difficult clearance of photothermal agent materials in vivo are also one of the major obstacles hindering their clinical transformation. In this work, we used hemoglobin as a novel stabilizer, hexachloroplatinic acid as a novel oxidant, and pyrrole as a monomer to prepare hemoglobin-stabilized platinum-based polypyrrole nanoparticles (Hb@PtP) by a one-step oxidative polymerization method and investigated in detail to study their physicochemical properties, such as morphology and structure. After polyethylene glycol modification, the particle size of obtained Hb@PtPP was 99.08 ± 8.3 nm and the zeta potential was -18.7 ± 1.2 mV. Transmission electron microscopy showed that the Hb@PtPP nanoparticles exhibited irregular spherical shape and uniform dispersion in the system. Under the irradiation of 808 nm laser with different power densities, Hb@PtPP showed power density-dependent temperature-raising behavior, and CCK-8 and dead-live staining experiments confirmed that they could effectively exert the photothermal effect to kill tumor cells. Small living animal imaging results demonstrated that Hb@PtPP had good tumor targeting and retention ability, and achieved tumor growth inhibition and ablation in vivo under laser excitation. All animal experiments involved in the study were performed in accordance with the program approved by the Animal Care and Use Committee of the Chinese Academy of Medical Sciences, Beijing Union Medical College, Institute of Radiation Medicine [IRM/2-IACUC-2312-005].

Objective To investigate the incidence rate,clinical characteristics,and prognosis of neonatal stroke in Shenzhen,China.Methods Led by Shenzhen Children's Hospital,the Shenzhen Neonatal Data Collaboration Network organized 21 institutions to collect 36 cases of neonatal stroke from January 2020 to December 2022.The incidence,clinical characteristics,treatment,and prognosis of neonatal stroke in Shenzhen were analyzed.Results The incidence rate of neonatal stroke in 21 hospitals from 2020 to 2022 was 1/15 137,1/6 060,and 1/7 704,respectively.Ischemic stroke accounted for 75％(27/36);boys accounted for 64％(23/36).Among the 36 neonates,31(86％)had disease onset within 3 days after birth,and 19(53％)had convulsion as the initial presentation.Cerebral MRI showed that 22 neonates(61％)had left cerebral infarction and 13(36％)had basal ganglia infarction.Magnetic resonance angiography was performed for 12 neonates,among whom 9(75％)had involvement of the middle cerebral artery.Electroencephalography was performed for 29 neonates,with sharp waves in 21 neonates(72％)and seizures in 10 neonates(34％).Symptomatic/supportive treatment varied across different hospitals.Neonatal Behavioral Neurological Assessment was performed for 12 neonates(33％,12/36),with a mean score of(32±4)points.The prognosis of 27 neonates was followed up to around 12 months of age,with 44％(12/27)of the neonates having a good prognosis.Conclusions Ischemic stroke is the main type of neonatal stroke,often with convulsions as the initial presentation,involvement of the middle cerebral artery,sharp waves on electroencephalography,and a relatively low neurodevelopment score.Symptomatic/supportive treatment is the main treatment method,and some neonates tend to have a poor prognosis.

Objective To investigate the risk factors for bronchopulmonary dysplasia(BPD)in twin preterm infants with a gestational age of<34 weeks,and to provide a basis for early identification of BPD in twin preterm infants in clinical practice.Methods A retrospective analysis was performed for the twin preterm infants with a gestational age of<34 weeks who were admitted to 22 hospitals nationwide from January 2018 to December 2020.According to their conditions,they were divided into group A(both twins had BPD),group B(only one twin had BPD),and group C(neither twin had BPD).The risk factors for BPD in twin preterm infants were analyzed.Further analysis was conducted on group B to investigate the postnatal risk factors for BPD within twins.Results A total of 904 pairs of twins with a gestational age of<34 weeks were included in this study.The multivariate logistic regression analysis showed that compared with group C,birth weight discordance of>25%between the twins was an independent risk factor for BPD in one of the twins(OR=3.370,95%CI:1.500-7.568,P<0.05),and high gestational age at birth was a protective factor against BPD(P<0.05).The conditional logistic regression analysis of group B showed that small-for-gestational-age(SGA)birth was an independent risk factor for BPD in individual twins(OR=5.017,95%CI:1.040-24.190,P<0.05).Conclusions The development of BPD in twin preterm infants is associated with gestational age,birth weight discordance between the twins,and SGA birth.

Objective:To explore the causes of platelet aggregation in version 6.4 Trima Accel automated blood collection system and the effect of 2 intervention measures.Methods:The data on platelet aggregation(n=61)and non-aggregation(n=323)of 61 donors in 2020 were collected and the causes of aggregation were analyzed.Then the 72 donors with platelet aggregation in 2021 were randomized into intervention group A(increasing the anticoagulant-to-blood ratio)and intervention group B(wrapping the donor's arm with an electric blanket to keep warm and improve the blood flow speed).The collection time,average blood flow speed,number of machine alarms,anticoagulant usage,deaggregation and citrate reaction of the two groups were compared.Results:Platelet aggregation was negatively correlated with the average blood flow speed(r=-0.394)and positively correlated with the collection time(r=0.458).The equations for predicting aggregation and non-aggregation were constructed based on Bayesian and Fisher discriminant analysis,and the predicted accuracy was 77.1％.The comparison of the effects of two intervention measures showed that the average blood flow speed in group B was higher than that in group A;the collection time,number of machine alarms,anticoagulant usage and proportion of citrate reaction in blood donors in group B were all lower than those in Group A,all these differences were significant(P＜0.05).In the entire cohort in 2021,90.28％of the products were immediately deaggregated after collection,and 9.72％of the products were deaggregated within 4 hours.There was no statistically significant difference in deaggregation between the two intervention groups(P＞0.05).Conclusion:During apheresis platelet collection,the predictive equations for aggregation and non-aggregation can be used to predict the occurrence probability of aggregation,and the intervention can be made in advance.Both intervention measures are effective in reducing platelet aggregation,however,measure B has the advantages of improving the speed of blood collection,shortening the collection time,reducing the alarm frequency and the anticoagulant usage,and reducing the incidence of citrate reaction in blood donors.