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.

Objective To explore the relationship between osteoporosis and carotid atherosclerosis in patients with coronary heart disease aged≥60 years and analyze prevention suggestions. Methods The clinical data of 380 patients with coronary heart disease aged≥60 years who underwent various examinations in the hospital between April 2024 and April 2025 were retrospectively analyzed. According to the bone mineral density (BMD) classification criteria, the patients were divided into osteoporosis group and non-osteoporosis group. The differences in general data and carotid atherosclerosis-related indicators were compared between osteoporosis group and non-osteoporosis group. Pearson method was used to analyze the correlation between carotid atherosclerosis indicators and clinical indicators in patients with coronary heart disease aged≥60 years. According to the IMT detection thickness in patients with coronary heart disease and osteoporosis aged≥60 years were divided into IMT thickening group and IMT non-thickening group and between plaque group and non-plaque group, and the differences in BMD and bone metabolism indicators were compared. Binary logistics analysis was adopted to analyze the risk factors of IMT thickening and carotid plaque formation in patients with coronary heart disease≥60 years old. Results Age and duration of osteoporosis group TC、LDL-C、CTX、 Carotid artery IMT and carotid atherosclerosis degree were higher than those in the non osteoporosis group, the difference was statistically significant (P<0.05). BMI, OPG, OCN, 25 (OH) D, BMD, carotid artery elasticity coefficient were lower than those in the non osteoporosis group, the difference was statistically significant (P<0.05). Carotid IMT, carotid atherosclerosis degree, and carotid elasticity coefficient were significantly correlated with age, course of disease, TC, LDL-C, CTX, BMI, OPG, OCN, BMD, and 25 (OH) D of coronary heart disease patients ≥60 years old (P<0.05). OPG, OCN, BMD and 25(OH)D in IMT thickening group and plaque group were lower compared to IMT non-thickening group and non-plaque group (P<0.05) while CTX was significantly higher than that in IMT non-thickening group and non-plaque group (P<0.05). Binary logistics regression analysis showed that OPG, OCN, BMD, 25(OH)D and CTX were associated with IMT thickening in patients with coronary heart disease and osteoporosis aged≥60 years (P<0.05). OPG, OCN and BMD were associated with carotid plaque formation in patients with coronary heart disease complicated with osteoporosis aged≥60 years (P<0.05). Conclusion There is a significant correlation between osteoporosis and arteriosclerosis in patients with coronary heart disease aged≥60 years. As the bone mass decreases, the manifestations of arteriosclerosis become become more and more obvious, which needs attention and prevention.

ObjectiveTo investigate the clinical efficacy and safety of iguratimod combined with the Chinese medicine Runzaoling in the treatment of primary Sjögren's syndrome （pSS）. MethodSeventy-two patients treated in the Department of Rheumatology and Immunology of the Second Affiliated Hospital of Guizhou University of Traditional Chinese Medicine（TCM） from January 2021 to June 2022 who met the Western medical diagnosis of pSS and had the TCM syndrome of Yin deficiency and heat toxin syndrome were randomly assigned into an observation group and a control group， with 36 patients in each group. The observation group was treated with iguratimod combined with Runzaoling， and the control group was treated with iguratimod. The treatment in both groups lasted for 12 weeks. The clinical symptoms， EULAR Sjogren's syndrome patient reported index （ESSPRI）， EULAR Sjögren's syndrome disease activity index （ESSDAI）， erythrocyte sedimentation Rate （ESR）， C-reactive protein （CRP）， immunoglobulin （IgG）， Schirmer score， and saliva flow of the two groups were determined before and after treatment. Furthermore， the incidence of adverse reactions was compared between the two groups. ResultThe total response rate in the observation group was 75.0% （27 patients with response and 9 patients with no response）， which was higher than that （61.11%， 22 patients with response and 14 patients without response） in the control group （P<0.05）. After treatment， the ESSPRI， ESSDAI， and TCM syndrome scores in both groups decreased and the decreases were more obvious in the observation group than in the control group （P<0.05）. The treatment in both groups recovered the ESR， CRP， IgG， Schirmer score， and saliva flow （P<0.05）. Moreover， the observation outperformed the control group in terms of the ESR， CRP， IgG， and saliva flow （P<0.05） and had no significant difference in the Schirmer score compared with the control group. During the treatment period， 2 patients in the observation group had nausea， and 1 patient had an abnormal liver function， which were relieved after symptomatic treatment and did not affect the treatment. In the control group， 1 patient withdrew from the study due to rashes and showed no special discomfort in the follow-up 4 weeks， and 1 patient had nausea， which was relieved after symptomatic treatment. ConclusionIguratimod combined with Runzaoling has good clinical efficacy and safety in the treatment of pSS.

Objective To establish a rapid high performance liquid chromatography-tandem mass spectrometry(HPLC-MS/MS)method for the determination of linezolid and vancomycin in trace plasma/serum from pediatric patients with severe infection.Methods The plasma/serum specimens(10 μL)were precipitated by methanol,then the supernatant was injected for detection directly.The internal standards were linezolid-D3 and norvancomycin.The chromatographic separation was performed with gradient elution on a Kinetex? EVO C18 column(30.0 mm × 2.1 mm,2.6 μm)using water and acetonitrile,each containing 0.1％formic acid,as mobile phase.The flow rate was 0.5 mL·min-1 and column temperature was 40 ℃.The injection volume was 2 μL and the total run time was 2 min.For mass spectrometry,electrospray ionization source was chosen,positive ion monitoring was used with multi-reaction monitoring(MRM)mode.The selectivity,lower limit of quantification(LLOQ)& calibration curve,accuracy & precision,recovery,matrix effect,stability,cross detection of plasma and serum samples,evaluation of hemolytic and hyperlipidemic effect were investigated.Results The retention times of linezolid,vancomycin,internal standard linezolid-D3 and norvancomycin were 1.18,1.03,1.17 and 1.01 min,respectively.The calibration curves of linezolid and vancomycin were y=8.95 × 10-1x+3.49 × 10-3(r=0.997 1)and y=3.13 × 10-1x+6.93 × 10-2(r=0.997 4),with the linear ranges of 0.2-25.6 μg·mL-1 and 1-128 μg·mL-1,and the lower limits of quantification were 0.2 μg·mL-1 and 1 μg·mL-1,respectively.The intra-run and inter-run precisions relative standard deviation(RSD)were both less than 9.55％.The average extraction recoveries of the two drugs were 96.24％-104.57％.The RSDs of internal standards-normalized matrix effect were no more than 7.58％.Plasma and serum matrix samples could be cross-detected.The maximum tolerable hemolysis degree of linezolid and vancomycin were 2％and 5％,respectively,and the hyperlipidemic effect did not affect the quantitation.The stability of the samples was good under test conditions.This method was successfully applied to the analysis of plasma samples from 28 pediatric patients with severe infection in our hospital.Conclusion This assay is sample-saving,simple,rapid,accurate and robust,widely used,which can be applied to combination medication studies of linezolid and vancomycin and their therapeutic drug monitoring in pediatric patients.

To promote the development of extracellular vesicles of herbal medicine especially the establishment of standardization, led by the National Expert Committee on Research and Application of Chinese Herbal Vesicles, research experts in the field of herbal medicine and extracellular vesicles were invited nationwide with the support of the Expert Committee on Research and Application of Chinese Herbal Vesicles, Professional Committee on Extracellular Vesicle Research and Application, Chinese Society of Research Hospitals and the Guangdong Engineering Research Center of Chinese Herbal Vesicles. Based on the collation of relevant literature, we have adopted the Delphi method, the consensus meeting method combined with the nominal group method to form a discussion draft of "Consensus statement on research and application of Chinese herbal medicine derived extracellular vesicles-like particles (2023)". The first draft was discussed in online and offline meetings on October 12, 14, November 2, 2022 and April and May 2023 on the current status of research, nomenclature, isolation methods, quality standards and research applications of extracellular vesicles of Chinese herbal medicines, and 13 consensus opinions were finally formed. At the Third Academic Conference on Research and Application of Chinese Herbal Vesicles, held on May 26, 2023, Kewei Zhao, convenor of the consensus, presented and read the consensus to the experts of the Expert Committee on Research and Application of Chinese Herbal Vesicles. The consensus highlights the characteristics and advantages of Chinese medicine, inherits the essence, and keeps the righteousness and innovation, aiming to provide a reference for colleagues engaged in research and application of Chinese herbal vesicles at home and abroad, decode the mystery behind Chinese herbal vesicles together, establish a safe, effective and controllable accurate Chinese herbal vesicle prevention and treatment system, and build a bridge for Chinese medicine to the world.

The 2024 American Society of Clinical Oncology Gastrointestinal Cancers Symposium (ASCO-GI) was held in San Francisco, the USA from January 18th to 20th, 2024 (local time). The multiple studies presented in this symposium will have a significant impact on the clinical practice of esophageal cancer. This article will focus on the surgical methods of esophageal cancer, perioperative immunotherapy, drug therapy for advanced esophageal cancer, rescue treatment after immunotherapy resistance, and other relevant aspects. It aims to summarize and interpret the significant advancements in the field of esophageal cancer presented in this symposium.

Consciousness and unconsciousness represent a compelling topic in psychology and neuroscience, embodying a dynamic interplay between two fundamental cognitive states. Understanding the cognitive and neural mechanisms underlying their interaction poses a significant challenge. While previous studies have predominantly focused on the impact of attention on consciousness, the influence of attention on unconscious processes has often been overlooked. However, the role of attention in modulating unconscious information processing is paramount, as it can regulate various aspects of unconscious visual processing, including simple visual information, semantic content, and emotional stimuli. Within the visual processing pathway, attention operates at early levels to modulate unconscious visual processing, starting at least from the eye-of-origin and visual orientations. In the semantic system, attention can top-down enhance unconscious semantic processes in a goal-dependent manner, enhancing goal-relevant processes while suppressing goal-irrelevant ones. In the emotional system, attentional load, in addition to target relevance, can regulate unconscious emotional processing. These findings suggest that the regulatory role of attention on unconscious processes depends on both goal relevance and the amount of attentional resources. Specifically, the goal-relevance of unconscious processes determines the direction of attentional modulation, while the amount of attentional resources allocated determines the extent of modulation. The once-prevailing notion that unconscious processing is automatic and not subject to attentional modulation has been gradually overturned. Current studies indicate that attention can modulate both conscious and unconscious processes, providing a new perspective on the relationship between attention and consciousness. Spatial attention can operate independently from consciousness at the neural representation level. Furthermore, other factors tightly related to attention, such as goal-related task sets, working memory, and attentional load, can all impact unconscious processes. These findings collectively suggest that attention and consciousness are functionally dissociated, supporting the idea that attention is necessary for both conscious and some unconscious processes. In conclusion, unconscious information processing is a complex and intriguing field where attention plays a crucial role. Continued in-depth research in this area is needed to deepen our understanding of how the human brain processes unconscious information and how attention exerts its regulatory influence. This not only requires studying the commonalities and specificities of different types of attention but also examining the sharing and individuality among different sensory modalities and cognitive modules. Theoretically, this not only helps us understand the mechanisms of attention but also sheds light on the mechanisms of consciousness. Studying these issues is also of practical value. Importantly, the organization and regulation of unconscious processes are closely related to human survival and development. For example, while rapid unconscious emotional processes (such as unconscious fear) are beneficial for rapid threat responses and increased survival chances, excessive and uncontrolled unconscious emotional processes can lead to anxiety disorders, phobias, and other mental disorders. Furthermore, while repeated perceptual and behavioral training can improve efficiency by forming highly automated unconscious processes, excessively stubborn unconscious processes can hinder the learning of new skills. Studying the role of attention in regulating these unconscious processes can help develop new intervention methods to maintain mental health and improve behavioral performance.

Lipopolysaccharides (LPS) are major outer membrane components of Gram-negative bacteria. Unlike most Gram-negative bacteria, Acinetobacter baumannii can still survive and acquire polymyxin resistance after complete loss of LPS. Previous studies of LPS-deficient Acinetobacter baumannii mostly focused on LPS-deficient strains induced by polymyxin, whose background was complex and unstable. To investigate LPS loss-mediated polymyxin resistant-Acinetobacter baumannii, this study constructed a stable and clear background LPS-deficient strain by knocking out lpxC gene in Acinetobacter baumannii ATCC 19606 with CIRSPR/Cas9, and then studied the phenotypic changes of the lpxC-deficient strain including morphology, growth rate, antibiotic susceptibility, virulence, membrane permeability, and membrane potential. Animal experiments were approved by the Animal Care and Welfare Committee Institute of Medicinal Biotechnology, CAMS and PUMC (approval number: IMB-20240119D₉). The results indicated that the lpxC gene of Acinetobacter baumannii ATCC 19606 was successfully knocked out. After losing the lpxC, the strain underwent the morphological change from rod-shaped to spherical. Furthermore, it leads to reduced growth rate, enhanced membrane permeability, decreased membrane potential, lower virulence, and increased antibiotic susceptibility to β-lactams, quinolones, aminoglycosides, macrolides, glycopeptides. The lpxC deletion results in significant changes in membrane homeostasis and adaptability of Acinetobacter baumannii. Understanding the phenotypic changes of colistin-resistant Acinetobacter baumannii mediated by LPS loss is useful for exploring the resistance mechanism of Acinetobacter baumannii and developing new therapeutic strategies.

Objective To explore the relationship between serum growth differentiation factor-15(GDF-15),chemerin,pentraxin 3(PTX3)levels and obesity,insulin resistance and inflammatory factors in patients with type 2 diabetes mellitus(T2DM),and to construct and evaluate the predictive efficacy.Methods A total of 231 T2DM patients admitted to the hospital from February 2020 to September 2022 were selected as T2DM group.Another 100 healthy subjects who came to the hospital for physical examination during the same period were selected as the control group.Serum GDF-15,chemerin and PTX3 levels of the two groups were detected and compared by enzyme-linked immunosorbent assay(ELISA).Clinical data of the two groups were collected and compared.Pearson correlation analysis and multiple linear regression were used to analyze the relationship between serum GDF-15,chemerin,PTX3 levels and obesity,insulin resistance and inflammation.Multivariate Logistic regression was used to evaluate the independent risk factors for T2DM development,and the com-bined prediction model of serum GDF-15,chemerin and PTX3 was constructed,and receiver operating charac-teristic(ROC)curve was plotted to evaluate its predictive efficacy for T2DM development.Results Compared with the control group,body mass index(BMI),waist-to-hip ratio(WHR),systolic blood pressure,total cho-lesterol,triglyceride,fasting blood glucose,fasting insulin(FINS),homeostasis model assessment of insulin re-sistance(HOMA-1R),interleukin(IL)-1β,IL-6,GDF-15,chemerin and PTX3 were all increased in T2DM group,and the differences were statistically significant(P＜0.05).Pearson correlation analysis showed that se-rum GDF-15,chemerin and PTX3 levels were positively correlated with BMI,WHR,FINS,HOMA-IR,IL-1βand IL-6 in T2DM group(P＜0.05).Multiple linear regression analysis showed that BMI,FINS,HOMA-IR,IL-1β and IL-6 were positively correlated with serum GDF-15,chemerin and PTX3 levels(P＜0.05).Multiva-riate Logistic regression analysis showed that the increase of serum GDF-15,chemerin and PTX3 levels was an independent risk factor for T2DM development(P＜0.05).ROC curve analysis results showed that the com-bined prediction model of serum GDF-15,chemerin and PTX3 had better prediction efficiency,and its area un-der the curve,sensitivity,specificity and accuracy were higher than those applied alone.Conclusion The levels of GDF-15,chemerin and PTX3 in serum of T2DM patients are elevated,and their levels increase with the ex-acerbation of obesity,insulin resistance and inflammatory response in T2DM patients.The combined predic-tion model constructed in this study has good predictive efficacy and has high predictive value for the occur-rence of T2DM.

ObjectiveThis study aimed to observe the impact of sinomenine hydrochloride on the proliferation of fibroblasts and the mRNA expression of related genes in knee joint adhesion and contracture in rabbits. Additionally, we sought to explore its potential mechanisms in combating knee joint adhesion and contracture. MethodsFibroblasts were cultured in vitro, and experimental groups with varying concentrations of sinomenine hydrochloride were established alongside a control group. Cell proliferation was assessed using the CCK-8 assay. Changes in the mRNA expression of fibroblast-related genes following sinomenine hydrochloride treatment were evaluated using RT-qPCR. The impact of the drug on serum levels of inflammatory cytokines was determined using the ELISA method, and the expression of related proteins was assessed using Western blot. ResultsSinomenine hydrochloride was found to inhibit fibroblast viability, with viability decreasing as the concentration of sinomenine hydrochloride increased. The effects of sinomenine hydrochloride in all experimental groups were highly significant (P<0.05). At the mRNA expression level, compared to the control group, sinomenine hydrochloride led to a significant downregulation of inflammatory cytokines in all groups (P<0.05). Additionally, the expression levels of apoptosis-related proteins significantly increased, while Bcl-2 mRNA expression decreased (P<0.05). The mRNA expression levels of the PI3K/mTOR/AKT3 signaling pathway also decreased (P<0.05). At the protein expression level, in comparison to the control group, the levels of inflammatory cytokines IL-6, IL-8, IL-1β, and TGF-β were significantly downregulated in the middle and high-dose sinomenine hydrochloride groups (P<0.05). The expression levels of cleaved-PARP, cleaved caspase-3/7, and Bax increased and were positively correlated with the dose, while the expression levels of the anti-apoptotic protein Bcl-2 and the PI3K/AKT3/mTOR signaling pathway were negatively correlated with the dose. Sinomenine hydrochloride exhibited a significant inhibitory effect on the viability of rabbit knee joint fibroblasts, which may be associated with the downregulation of inflammatory cytokines IL-6, IL-8, and IL-1β, promotion of apoptosis-related proteins cleaved-PARP, cleaved caspase-3/7, and Bax, suppression of Bcl-2 expression, and inhibition of gene expression in the downstream PI3K/AKT3/mTOR signaling pathway. ConclusionSinomenine hydrochloride can inhibit the inflammatory response of fibroblasts in adhesive knee joints and accelerate fibroblast apoptosis. This mechanism may offer a novel approach to improving and treating knee joint adhesion.