BACKGROUND: The transcription factor POU2F1 regulates the expression levels of microRNAs in neoplasia. However, the miR-29b1/a cluster modulated by POU2F1 in gastric cancer (GC) remains unknown. METHODS: Gene expression in GC cells was evaluated using reverse-transcription polymerase chain reaction (PCR), western blotting, immunohistochemistry, and RNA in situ hybridization. Co-immunoprecipitation was performed to evaluate protein interactions. Transwell migration and invasion assays were performed to investigate the biological behavior of GC cells. MiR-29b1/a cluster promoter analysis and luciferase activity assay for the 3'-UTR study were performed in GC cells. In vivo tumor metastasis was evaluated in nude mice. RESULTS: POU2F1 is overexpressed in GC cell lines and binds to the miR-29b1/a cluster promoter. POU2F1 is upregulated, whereas mature miR-29b-3p and miR-29a-3p are downregulated in GC tissues. POU2F1 promotes GC metastasis by inhibiting miR-29b-3p or miR-29a-3p expression in vitro and in vivo . Furthermore, PIK3R1 and/or PIK3R3 are direct targets of miR-29b-3p and/or miR-29a-3p , and the ectopic expression of PIK3R1 or PIK3R3 reverses the suppressive effect of mature miR-29b-3p and/or miR-29a-3p on GC cell metastasis and invasion. Additionally, the interaction of PIK3R1 with PIK3R3 promotes migration and invasion, and miR-29b-3p , miR-29a-3p , PIK3R1 , and PIK3R3 regulate migration and invasion via the phosphatidylinositol 3-kinase/protein kinase B/mammalian target of rapamycin (PI3K/Akt/mTOR) pathway in GC cells. In addition, POU2F1 , PIK3R1 , and PIK3R3 expression levels negatively correlated with miR-29b-3p and miR-29a-3p expression levels in GC tissue samples. CONCLUSIONS The POU2F1 - miR-29b-3p / miR-29a-3p-PIK3R1 / PIK3R1 signaling axis regulates tumor progression and may be a promising therapeutic target for GC.
MicroRNAs/metabolism* ; Humans ; Stomach Neoplasms/pathology* ; Cell Line, Tumor ; Cell Movement/physiology* ; Phosphatidylinositol 3-Kinases/metabolism* ; Animals ; Mice ; Octamer Transcription Factor-1/metabolism* ; Mice, Nude ; Class Ia Phosphatidylinositol 3-Kinase/metabolism* ; Neoplasm Invasiveness ; Gene Expression Regulation, Neoplastic/genetics* ; Male ; Immunohistochemistry ; Female

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 investigate the epidemiological characteristics and effectiveness of emergency responses to epidemic foci in Guangzhou City in 2024, so as to optimization of the dengue fever control strategy in Guangzhou City. Methods All data pertaining to dengue fever cases in Guangzhou City in 2024 were collected from the National Notifiable Infectious Disease Surveillance Information Reporting System. The temporal, spatial and population distributions of dengue fever cases and sources of infections were descriptively analyzed, and the effectiveness of emergency responses to epidemic foci of dengue fever was evaluated through standard space index (SSI), the interval from disease onset to case reporting and the percentage of isolation in hospital. Results A total of 3 656 dengue fever cases were reported in Guangzhou City in 2024, including 3 102 local cases and 554 imported cases. Of all cases, 67.86% (2 481 cases) occurred at ages of 20 to 59 years, and the three most common occupations included housework/unemployment (793 cases, 21.69%), business servants (744 cases, 20.35%) and retirees (669 cases, 18.30%). The peak of dengue fever epidemics was concentrated during the period from the 39th to the 45th weeks in 2024, when a total of 2 317 local cases were reported, accounting for 74.69% of all local cases in 2024. Dengue fever cases were reported across all 11 districts in Guangzhou City in 2024, with local cases concentrated in Baiyun District (754 cases, 24.31%), Liwan District (398 cases, 12.83%), Panyu District (365 cases, 11.77%), Haizhu District (332 cases, 10.70%) and Tianhe District (328 cases, 10.57%). Imported dengue fever cases were predominantly domestically imported (492 cases, 88.81%), with the majority imported from Foshan City (377 cases), and overseas imported cases were predominantly imported from southeastern Asian countries. The mean proportion of case isolation in hospital was 9.16% (284/3 102), and the mean interval from disease onset to case reporting was (3.99 ± 2.70) days, while the percentages of mosquito density meeting the required standard were 61.68% (462/ 749) and 66.32% (126/190) on the 4th and 7th day of emergency responses to epidemic foci, respectively. Conclusions The prevention and control cycle of dengue fever in Guangzhou in 2024 took longer than in previous years, with a larger scale of the epidemic. Although some progress has been made in epidemic management, there are still problems such as unsustainable mosquito vector control and low hospitalization isolation rates for cases. Further optimization of control measures in mosquito vector control, case monitoring and management is required to improve the effectiveness of dengue fever control measures.

To improve the quality evaluation system of Hibisci Mutabilis Folium, this study established high performance liquid chromatography(HPLC) fingerprints of Hibisci Mutabilis Folium and evaluated the quality differences of medicinal materials from different places of production by chemometrics. Furthermore, a content measurement method of differential components was established based on quantitative analysis of multi-components by single-marker(QAMS). The fingerprints of 17 batches of Hibisci Mutabilis Folium from different places of production were constructed, with a total of 19 common peaks marked and seven components confirmed. The similarity between the sample fingerprints and the reference fingerprints ranged from 0.890 to 0.974. By utilizing principal component analysis(PCA), hierarchical cluster analysis(HCA), and orthogonal partial least squares-discriminant analysis(OPLS-DA), the chemical patterns of fingerprints were identified. Five components that could be used to evaluate the quality differences of Hibisci Mutabilis Folium were screened, namely peak 6(quercetin 3-O-β-robinobioside), peak 7(rutin), peak 9(kaempferol-3-O-β-robinobioside), peak 10(kaempferol-3-O-rutinoside), and peak 14(tiliroside). The relative correction factors of isoquercitrin, kaempferol-3-O-β-robinobioside, kaempferol-3-O-rutinoside, kaempferol-3-O-β-D-glucoside, and tiliroside were measured with rutin as the internal reference. The QAMS method was established for the content measurement of six flavonoids, and the results showed there was no significant difference compared to the results obtained by an external standard method. In summary, the HPLC fingerprints and QAMS method established in the study, demonstrating stability and accuracy, can provide a reference for the overall quality evaluation of Hibisci Mutabilis Folium.
Chromatography, High Pressure Liquid/methods* ; Drugs, Chinese Herbal/chemistry* ; Quality Control ; Principal Component Analysis

OBJECTIVE: To explore clinical characteristics, lesion sites and correlation differences of different types of diabetic foot gangrene, and to provide evidence-based basis for clinical classification of diabetic foot gangrene. METHODS: A retrospective analysis was conducted on 266 patients with newly diagnosed diabetic foot gangrene who were admitted from January 2018 to December 2018, including 183 males and 83 females, aged from 35 to 92 years old with an average of (69.55±10.84) years old, and they were divided into wet gangrene group and dry gangrene group according to the different natures of gangrene. There were 139 patients in wet gangrene group, including 98 males and 41 females, aged from 35 to 90 years old with an average of (68.95±10.93) years old. There were 127 patients in dry gangrene group, including 85 males and 42 females, aged from 38 to 92 years old with an average of (70.21±10.75) years old. Body mass index (BMI), waist-to-hip ratio (WHR), body temperature, skin temperature difference between the affected and healthy sides of the lower extremities, and Wagner grade between two groups were recorded to evaluate symptoms and signs. The white blood cell count (WBC), neutrophil percentage (NEUT%), and C-reactive protein (C-reactive protein), erythrocyte sedimentation rate (ESR), procalcitonin (PCT), and interleukin-6 (IL-6) in peripheral blood between two groups were detected and compared to evaluate the infection status;the severity of diabetic peripheral neuropathy (DPN) was evaluated by using Toronto Clinical Scoring System (TCSS);the degree of pain in patients with diabetic foot gangrene was evaluated by numerical rating scale (NRS); ankle-brachial index (ABI) and popliteal artery blood flow velocity were used to evaluate the degree of arterial lesions. Spearman correlation analysis was used to analyze the correlations between gangrene TCSS, ABI and age, BMI, WHR, body temperature, calf skin temperature difference, WBC, NEUT%, CRP, ESR, PCT, IL-6, NRS, and Wagner classification indicators. RESULTS: The body temperature, skin temperature difference between the affected and healthy sides of the lower extremities, Wagner grade, WBC, NEUT%, CRP, ESR, PCT, IL-6, TCSS score, ABI, and popliteal artery blood flow velocity in wet gangrene group were higher than those in dry gangrene group (P<0.01), and BMI, WHR, and NRS score in dry gangrene group were higher than those in wet gangrene group;the differences were all statistically significant (P<0.01). The results of Spearman correlation analysis showed TCSS score of gangrene patients was correlated with body temperature (r=0.214), calf skin temperature difference (r=0.364), WBC (r=0.240), NEUT% (r=0.291), CRP (r=0.347), ESR (r=0.167), PCT (r=0.241), IL-6 (r=0.316), and popliteal fossa arterial blood flow velocity (r=0.261) and Wagner grade (r=0.273) were positively correlated, and the differences were statistically significant (P<0.01). ABI was negatively correlated with age (r=-0.183), BMI (r=-0.252), WHR (r=-0.288), and NRS score (r=-0.354), and the differences were statistically significant (P<0.01). CONCLUSION Diabetic foot gangrene is an extremely difficult and critical disease. Wet gangrene has a significant synergic effect with infection and neuropathy, while dry gangrene is closely related to vascular occlusion. The main contradiction of gangrene could be revealed through blood vessels, nerves and infection, providing evidence-based basis for the selection of debridement timing, anti-infection strategies and revascularization, with the aim of reducing the risk of amputation.
Humans ; Male ; Female ; Aged ; Middle Aged ; Diabetic Foot/diagnosis* ; Aged, 80 and over ; Adult ; Retrospective Studies ; Gangrene/physiopathology* ; C-Reactive Protein

OBJECTIVE: To investigate the characteristics of gut microbiota changes in patients with acute myeloid leukemia (AML) undergoing induction chemotherapy and to explore the relationship between infectious complications and gut microbiota. METHODS: Fecal samples were collected from 37 newly diagnosed AML patients at four time points: before induction chemotherapy, during chemotherapy, during the neutropenic phase, and during the recovery phase. Metagenomic sequencing was used to analyze the dynamic changes in gut microbiota. Correlation analyses were conducted to assess the relationship between changes in gut microbiota and the occurrence of infectious complications. RESULTS: During chemotherapy, the gut microbiota α-diversity (Shannon index) of AML patients exhibited significant fluctuations. Specifically, the diversity decreased significantly during induction chemotherapy, further declined during the neutropenic phase (P < 0.05, compared to baseline), and gradually recovered during the recovery phase, though not fully returning to baseline levels.The abundances of beneficial bacteria, such as Firmicutes and Bacteroidetes, gradually decreased during chemotherapy, whereas the abundances of opportunistic pathogens, including Enterococcus, Klebsiella, and Escherichia coli, progressively increased.Analysis of the dynamic changes in gut microbiota of seven patients with bloodstream infections revealed that the bloodstream infection pathogens could be detected in the gut microbiota of the corresponding patients, with their abundance gradually increasing during the course of infection. This finding suggests that bloodstream infections may be associated with opportunistic pathogens originating from the gut microbiota.Compared to non-infected patients, the baseline samples of infected patients showed a significantly lower relative abundance of Bacteroidetes (P < 0.05). Regression analysis indicated that Bacteroidetes abundance is an independent predictive factor for infectious complications (P < 0.05, OR =13.143). CONCLUSION During induction chemotherapy in AML patients, gut microbiota α-diversity fluctuates significantly, and the abundance of opportunistic pathogens increase, which may be associated with bloodstream infections. Patients with lower baseline Bacteroidetes abundance are more prone to infections, and its abundance can serve as an independent predictor of infectious complications.
Humans ; Gastrointestinal Microbiome ; Leukemia, Myeloid, Acute/microbiology* ; Induction Chemotherapy ; Feces/microbiology* ; Male ; Female ; Middle Aged

Coronavirus disease 2019 (COVID-19) is an acute infectious respiratory disease that has been prevalent since December 2019. Chinese medicine (CM) has demonstrated its unique advantages in the fight against COVID-19 in the areas of disease prevention, improvement of clinical symptoms, and control of disease progression. This review summarized the relevant material components of CM in the treatment of COVID-19 by searching the relevant literature and reports on CM in the treatment of COVID-19 and combining with the physiological and pathological characteristics of the novel coronavirus. On the basis of sorting out experimental methods in vivo and in vitro, the mechanism of herb action was further clarified in terms of inhibiting virus invasion and replication and improving related complications. The aim of the article is to explore the strengths and characteristics of CM in the treatment of COVID-19, and to provide a basis for the research and scientific, standardized treatment of COVID-19 with CM.
Humans ; Drugs, Chinese Herbal/pharmacology* ; COVID-19 Drug Treatment ; SARS-CoV-2/drug effects* ; COVID-19/therapy* ; Medicine, Chinese Traditional/methods* ; Antiviral Agents/pharmacology* ; Animals

Objective To investigate the protective effect of dexmedetomidine(Dex)pretreatment on myocardial ischemia-reperfusion mice and the effect of Nod-like receptor protein 3(NLRP3)inflammatory signaling pathway.Methods C57BL/6J mice were randomly divided into sham group(only threading without ligation),model group(recovery after ligation of left anterior descending coronary artery),positive group(modeling after intraperitoneal injection of 1 mg·kg-1 trimetazidine),Dex group(modeling after intraperitoneal injection of 20 μg·kg-1 dexmedetomidine),MCC950 group(modeling after intraperitoneal injection of 10 mg·kg-1 NLRP3 inhibitor MCC950),12 mice in each group.Cardiac function indexes were detected at 24 h after reperfusion,the expression level of related proteins in myocardial tissue was detected by Western blot,enzyme-linked immunosorbent assay(ELISA)was used to detect the expression level of serum factor,myocardial antioxidant index was detected by kit method,and apoptosis was detected by Tunel method.Results The NLRP3 protein expression levels of sham group,model group,positive group,Dex group and MCC950 group were 0.31±0.05,1.06±0.07,0.52±0.05,0.65±0.07 and 0.39±0.04,respectively;the expression levels of apoptosis-associated granuloid protein(ASC)were 0.27±0.08,0.88±0.09,0.46±0.05,0.59±0.07 and 0.34±0.04,respectively;CK-MB levels were(25.64±2.94),(102.08±7.04),(49.61±7.70),(60.86±5.24)and(63.24±5.38)U·L-1,respectively;IL-6 levels were(104.78±10.73),(231.54±15.56),(158.20±16.54),(165.10±14.77)and(141.17±14.08)pg·mL-1,respectively;Tunel positive cell rates were(4.34±0.16)％,(25.98±1.58)％,(8.74±0.93)％,(11.06±1.07)％and(9.19±0.88)％,respectively.Sham group were compared with model group;Dex group and MCC950 group were compared with model group,the above indexes were statistically significant(all P＜0.05).Conclusion Dexmedetomidine preconditioning may prevent ischemia-reperfusion myocardial injury by inhibiting NLRP3/ASC/caspase-1 inflammatory pathway,inflammatory response and myocardial cell apoptosis.

The study analyzes the upgrade and application of LightSpeed VCT Console,aiming to explore the principle,method and advantages of this technology,and verify its effectiveness in practical scenarios.After the introduction of the basic principle of LightSpeed VCT Console which uses machine learning algorithms and large-scale image training data to improve and transform low-quality images,the application cases of LightSpeed VCT Console in reducing noise and suppressing artifacts after upgrading are discussed in details,and the excellent performance of this technology in improving image quality is demonstrated.Finally,the characteristics and differences of LightSpeed VCT Console and other image transformation technologies are compared,and the further development direction of Lightspeed VCT Console in image processing is discussed.