Interferon stimulating factor STING, a transmembrane protein residing in the endoplasmic reticulum, is extensively involved in the sensing and transduction of intracellular signals and serves as a crucial component of the innate immune system. STING is capable of directly or indirectly responding to abnormal DNA originating from diverse sources within the cytoplasm, thereby fulfilling its classical antiviral and antitumor functions. Structurally, STING is composed of 4 transmembrane helices, a cytoplasmic ligand binding domain (LBD), and a C terminal tail structure (CTT). The transmembrane domain (TM), which is formed by the transmembrane helical structures, anchors STING to the endoplasmic reticulum, while the LBD is in charge of binding to cyclic dinucleotides (CDNs). The classical second messenger, cyclic guanosine monophosphate-adenosine monophosphate (cGAMP), represents a key upstream molecule for STING activation. Once cGAMP binds to LBD, STING experiences conformational alterations, which subsequently lead to the recruitment of Tank-binding kinase 1 (TBK1) via the CTT domain. This, in turn, mediates interferon secretion and promotes the activation and migration of dendritic cells, T cells, and natural killer cells. Additionally, STING is able to activate nuclear factor-κB (NF-κB), thereby initiating the synthesis and release of inflammatory factors and augmenting the body’s immune response. In recent years, an increasing number of studies have disclosed the non-classical functions of STING. It has been found that STING plays a significant role in organelle regulation. STING is not only implicated in the quality control systems of organelles such as mitochondria and endoplasmic reticulum but also modulates the functions of these organelles. For instance, STING can influence key aspects of organelle quality control, including mitochondrial fission and fusion, mitophagy, and endoplasmic reticulum stress. This regulatory effect is not unidirectional; rather, it is subject to organelle feedback regulation, thereby forming a complex interaction network. STING also exerts a monitoring function on the nucleus and ribosomes, which further enhances the role of the cGAS-STING pathway in infection-related immunity. The interaction mechanism between STING and organelles is highly intricate, which, within a certain range, enhances the cells’ capacity to respond to external stimuli and survival pressure. However, once the balance of this interaction is disrupted, it may result in the occurrence and development of inflammatory diseases, such as aseptic inflammation and autoimmune diseases. Excessive activation or malfunction of STING may trigger an over-exuberant inflammatory response, which subsequently leads to tissue damage and pathological states. This review recapitulates the recent interactions between STING and diverse organelles, encompassing its multifarious functions in antiviral, antitumor, organelle regulation, and immune regulation. These investigations not only deepen the comprehension of molecular mechanisms underlying STING but also offer novel concepts for the exploration of human disease pathogenesis and the development of potential treatment strategies. In the future, with further probing into STING function and its regulatory mechanisms, it is anticipated to pioneer new approaches for the treatment of complex diseases such as inflammatory diseases and tumors.

Objective This study analyzed the chemical structures of two unknown substances in e-liquid using methods such as nuclear magnetic resonance(NMR),infrared spectroscopy(IR),and mass spectrometry(MS).Methods After separating,purifying,and freeze-drying two suspicious substances from e-liquid,GC-MS analysis was used to obtain the mass spectrum characteristic ion fragments and fragmentation patterns of unknown compounds.The precise mass numbers were measured by high-resolution mass spectrometry,and proton numbers and their assignments,carbon types,and fluorine atom numbers and positions were obtained by combining 1HNMR,13CNMR,and 19FNMR.The functional groups were then analyzed by infrared spectroscopy.Results Through data analysis,the molecular formulas of the two suspicious substances are C13H13FN2O2 and C14H15FN2O2,respectively.Their structures were determined to be etomidate derivatives:1-(o-fluoromethylphenyl)imidazole-5-carboxylic acid methyl ester and 1-(o-fluoromethylphenyl)imidazole-5-carboxylic acid ethyl ester.Conclusion The structural data of two substances obtained in this study in terms of mass spectrometry,nuclear magnetic resonance,and infrared spectroscopy provide support for combating crimes involving the two substances,and provide reference for the regulation and detection of the two drugs.

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: T cell dysfunction, which includes exhaustion, anergy, and senescence, is a distinct T cell differentiation state that occurs after antigen exposure. Although T cell dysfunction has been a cornerstone of cancer immunotherapy, its potential in transplant research, while not yet as extensively explored, is attracting growing interest. Interferon regulatory factor 4 (IRF4) has been shown to play a pivotal role in inducing T cell dysfunction. METHODS: A novel ultra-low-dose combination of Trametinib and Rapamycin, targeting IRF4 inhibition, was employed to investigate T cell proliferation, apoptosis, cytokine secretion, expression of T-cell dysfunction-associated molecules, effects of mitogen-activated protein kinase (MAPK) and mammalian target of rapamycin (mTOR) signaling pathways, and allograft survival in both in vitro and BALB/c to C57BL/6 mouse cardiac transplantation models. RESULTS: In vitro , blockade of IRF4 in T cells effectively inhibited T cell proliferation, increased apoptosis, and significantly upregulated the expression of programmed cell death protein 1 (PD-1), Helios, CD160, and cytotoxic T lymphocyte-associated antigen (CTLA-4), markers of T cell dysfunction. Furthermore, it suppressed the secretion of pro-inflammatory cytokines interferon (IFN)-γ and interleukin (IL)-17. Combining ultra-low-dose Trametinib (0.1 mg·kg -1 ·day -1 ) and Rapamycin (0.1 mg·kg -1 ·day -1 ) demonstrably extended graft survival, with 4 out of 5 mice exceeding 100 days post-transplantation. Moreover, analysis of grafts at day 7 confirmed sustained IFN regulatory factor 4 (IRF4) inhibition, enhanced PD-1 expression, and suppressed IFN-γ secretion, reinforcing the in vivo efficacy of this IRF4-targeting approach. The combination of Trametinib and Rapamycin synergistically inhibited the MAPK and mTOR signaling network, leading to a more pronounced suppression of IRF4 expression. CONCLUSIONS Targeting IRF4, a key regulator of T cell dysfunction, presents a promising avenue for inducing transplant immune tolerance. In this study, we demonstrate that a novel ultra-low-dose combination of Trametinib and Rapamycin synergistically suppresses the MAPK and mTOR signaling network, leading to profound IRF4 inhibition, promoting allograft acceptance, and offering a potential new therapeutic strategy for improved transplant outcomes. However, further research is necessary to elucidate the underlying pharmacological mechanisms and facilitate translation to clinical practice.
Animals ; Mice ; Mice, Inbred BALB C ; Mice, Inbred C57BL ; Interferon Regulatory Factors/metabolism* ; Heart Transplantation/methods* ; T-Lymphocytes/immunology* ; Sirolimus/therapeutic use* ; Pyridones/therapeutic use* ; Graft Survival/drug effects* ; Pyrimidinones/therapeutic use* ; Cell Proliferation/drug effects* ; Apoptosis/drug effects* ; Male ; Signal Transduction/drug effects*

The aim of this study was to investigate the contribution of lung zinc ions to pathogenesis of lung ischemia/reperfusion (I/R) injury in rats. Male Sprague Dawley (SD) rats were randomly divided into control group, lung I/R group (I/R group), lung I/R + low-dose zinc chloride group (LZnCl₂+I/R group), lung I/R + high-dose ZnCl₂ group (HZnCl₂+I/R group), lung I/R + medium-dose ZnCl₂ group (MZnCl₂+I/R group) and TPEN+MZnCl₂+I/R group (n = 8 in each group). Inductively coupled plasma mass spectrometry (ICP-MS) was used to measure the concentration of zinc ions in lung tissue. The degree of lung tissue injury was analyzed by observing HE staining, alveolar damage index, lung wet/dry weight ratio and lung tissue gross changes. TUNEL staining was used to detect cellular apoptosis in lung tissue. Western blot and RT-qPCR were used to determine the protein expression levels of caspase-3 and ZIP8, as well as the mRNA expression levels of zinc transporters (ZIP, ZNT) in lung tissue. The mitochondrial membrane potential (MMP) of lung tissue was detected by JC-1 MMP detection kit. The results showed that, compared with the control group, the lung tissue damage, lung wet/dry weight ratio and alveolar damage index were significantly increased in the I/R group. And in the lung tissue, the concentration of Zn²⁺ was markedly decreased, while the cleaved caspase-3/caspase-3 ratio and apoptotic levels were significantly increased. The expression levels of ZIP8 mRNA and protein were down-regulated significantly, while the mRNA expression of other zinc transporters remained unchanged. There was also a significant decrease in MMP. Compared with the I/R group, both MZnCl₂+I/R group and HZnCl₂+I/R group exhibited significantly reduced lung tissue injury, lung wet/dry weight ratio and alveolar damage index, increased Zn²⁺ concentration, decreased ratio of cleaved caspase-3/caspase-3 and apoptosis, and up-regulated expression levels of ZIP8 mRNA and protein. In addition, the MMP was significantly increased in the lung tissue. Zn²⁺ chelating agent TPEN reversed the above-mentioned protective effects of medium-dose ZnCl₂ on the lung tissue in the I/R group. The aforementioned results suggest that exogenous administration of ZnCl₂ can improve lung I/R injury in rats.
Animals ; Reperfusion Injury/pathology* ; Male ; Rats, Sprague-Dawley ; Rats ; Chlorides/administration & dosage* ; Lung/pathology* ; Zinc Compounds/administration & dosage* ; Apoptosis/drug effects* ; Caspase 3/metabolism* ; Cation Transport Proteins/metabolism*

The chemical constituents of the petroleum ether extract derived from the 90% ethanol extract of Elephantopus scaber were investigated. By silica gel column chromatography, C_(18), MCI column chromatography and semi-preparative high performance liquid chromatography, ten compounds were isolated. Their structures were identified as 3β-hydroxy-6β,7β-epoxytaraxeran-14-ene(1), 3β-hydroxyolean-12-en-28-oic acid(2), D-friedoolean-14-ene-3β,7α-diol(3), 3β-hydroxy-11α-methoxyolean-12-ene(4), 3β-hydroxyolean-11,13(18)-diene(5), 11α-hydroxy-β-amyrin(6), betulinic acid(7), 3β-hydroxy-30-norlupan-20-one(8), 6-acetonylchelerythrine(9), and 4',5'-dehydrodiodictyonema A(10) by analysis of the 1D NMR, 2D NMR, MS, and IR spectral data. Among them, compound 1 was a new triterpene and other compounds except compounds 2 and 7 were isolated from this plant for the first time.
Triterpenes/isolation & purification* ; Drugs, Chinese Herbal/isolation & purification* ; Molecular Structure ; Asteraceae/chemistry* ; Chromatography, High Pressure Liquid ; Magnetic Resonance Spectroscopy

This study aims to explore the mechanism of Jiaotai Pills in treating depression based on metabolomics and network pharmacology. The chemical constituents of Jiaotai Pills were identified by UHPLC-Orbitrap Exploris 480, and the targets of Jiaotai Pills and depression were retrieved from online databases. STRING and Cytoscape 3.7.2 were used to construct the protein-protein interaction network of core targets of Jiaotai Pills in treating depression and the "compound-target-pathway" network. DAVID was used for Gene Ontology(GO) function and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway enrichment analyses of the core targets. The mouse model of depression was established with chronic unpredictable mild stress(CUMS) and treated with different doses of Jiaotai Pills. The behavioral changes and pathological changes in the hippocampus were observed. UHPLC-Orbitrap Exploris 120 was used for metabolic profiling of the serum, from which the differential metabolites and related metabolic pathways were screened. A "metabolite-reaction-enzyme-gene" network was constructed for the integrated analysis of metabolomics and network pharmacology. A total of 34 chemical components of Jiaotai Pills were identified, and 143 core targets of Jiaotai Pills in treating depression were predicted, which were mainly involved in the arginine and proline, sphingolipid, and neurotrophin metabolism signaling pathways. The results of animal experiments showed that Jiaotai Pills alleviated the depression behaviors and pathological changes in the hippocampus of the mouse model of CUMS-induced depression. In addition, Jiaotai Pills reversed the levels of 32 metabolites involved in various pathways such as arginine and proline metabolism, sphingolipid metabolism, and porphyrin metabolism in the serum of model mice. The integrated analysis showed that arginine and proline metabolism, cysteine and methionine metabolism, and porphyrin metabolism might be the key pathways in the treatment of depression with Jiaotai Pills. In conclusion, metabolomics combined with network pharmacology clarifies the antidepressant mechanism of Jiaotai Pills, which may provide a basis for the clinical application of Jiaotai Pills in treating depression.
Animals ; Drugs, Chinese Herbal/chemistry* ; Depression/genetics* ; Mice ; Network Pharmacology ; Metabolomics ; Male ; Disease Models, Animal ; Humans ; Protein Interaction Maps/drug effects* ; Antidepressive Agents

The chemical constituents of the chloroform extract of the 90% methanol extract obtained from the dried branches and leaves of Croton lauioides were investigated. By using silica gel column chromatography, C_(18 )column chromatography, MCI column chromatography, and semi-preparative high-performance liquid chromatography(HPLC), six compounds were isolated. Their structures were identified as lauioidine(1), 2α-methoxy-8α-hydroxy-6-oxogermacra-1(10),7(11)-dien-8,12-olide(2), myrrhanolide B(3), gossweilone(4), 6β,7β-epox-4α-hydroxyguaian-10-ene(5), and 4(15)-eudesmane-1β,5α-diol(6) by analyzing the HR-ESI-MS, IR, ECD, 1D NMR and 2D NMR data, as well as their physicochemical properties. All compounds were isolated from C. lauioides for the first time, among which compound 1 is a new nor-clerodane diterpenoid.
Croton/chemistry* ; Diterpenes, Clerodane/isolation & purification* ; Molecular Structure ; Drugs, Chinese Herbal/isolation & purification* ; Magnetic Resonance Spectroscopy ; Chromatography, High Pressure Liquid

Objective:To evaluate the clinical efficacy of methylation sensitive-high resolution melting curve (MS-HRM) detection of IFN-induced protein 44-like (IFI44L) gene methylation in the diagnosis of systemic lupus erythematosus (SLE), as well as the relationship between IFI44L gene markers and the early onset of SLE.Methods:From February 2020 to September 2022, the MS-HRM was used to detect the methylation level of the IFI44L gene in peripheral blood mononuclear cells of 602 SLE patients and 524 other autoimmune disease patients (excluding SLE) from Beijing Peking Union Medical College Hospital, Guangdong Provincial People′s Hospital, and Shenzhen People′s Hospital, totaling 1 126 patients. Compared with the 2012 SLICC criteria, the suspected cases were followed up for 6 months until the onset and clinical diagnosis of SLE were confirmed. The measurement data of normal distribution were expressed as mean±SD, and the consistency analysis was performed using the Kappa consistency test. The clinical diagnostic efficacy indicators were calculated using the receiver operating characteristic (ROC) curve. Results:RR (95% CI) of early suspected cases was 17.06 (9.43, 30.82). The results of IFI44L gene methylation level were in good agreement with the 2012 SLICC criteria, and the sensitivity, specificity and total coincidence rate were 90.53%, 92.56% and 91.47%, respectively. The Kappa value (95% CI) was 0.829(0.796, 0.862) ( P<0.001). The diagnostic efficiency of IFI44L gene methylation level ( Kappa value 0.817) was superior to anti-nuclear antibody, anti-SM antibody and anti-dsDNA antibody ( Kappa value 0.418, 0.216 and 0.440, respectively). The Kappa values (95% CI) of methylation between MS-HRM and pyrosequencing was 0.861(0.806, 0.916), P<0.001. Conclusion:The hypomethylation of IFI44L gene methylation level detected by MS-HRM is closely related to the occurrence and development of SLE, and its diagnostic performance is better than that of three autoantibodies in SLE diagnosis, which can be used for the early diagnosis of SLE.

Objective:To evaluate the clinical efficacy of a novel reduction device in the treatment of A3N0/1 thoracolumbar fracture using navigation-assisted techniques.Methods:A retrospective analysis was conducted on 45 patients (29 males, 16 females; mean age 40.67±16.11 years, range 24-57) with thoracolumbar fractures who underwent fracture reduction and pedicle screw fixation via the Wiltse approach at Zhengzhou Orthopaedic Hospital between January 2022 and January 2023. Injury levels included: T 10 in 2 cases, T 11 in 5 cases, T 12 in 13 cases, L 1 in 20 cases, L 2 in 3 cases, L 3 in 2 cases. All patients underwent fracture reduction via the Wiltse approach using the spinal fracture reduction instrument for vertebral body reduction. Among them, 20 patients received O-arm navigation-assisted internal fixation and vertebral reduction (O-arm group), while 25 received C-arm fluoroscopy-guided internal fixation and vertebral reduction (C-arm group). Operative time, intraoperative blood loss, vertebral reduction time using the instrument, first-time screw placement success rate, screw placement accuracy, and complications were compared. Mid-vertebral body height ratio (MVBHr), local Cobb angle of the fractured vertebra, visual analogue scale (VAS) score, and Oswestry disability index (ODI) were compared preoperatively, at 1 week postoperatively, 3 months postoperatively, and final follow-up. Results:All surgeries were successfully completed in both groups. Operative time was significantly shorter in the O-arm group (106.8±14.4 min) than in the C-arm group (119.1±16.4 min, P<0.05). All patients were followed up for a mean duration of 15.9±3.9 months (range 12-20 months). Vertebral reduction time was significantly shorter in the O-arm group (11.0±2.2 min) than in the C-arm group (20.4±5.7 min, P<0.05). The first-time screw placement success rate was significantly higher in the O-arm group (100%) than in the C-arm group (95.3%, P<0.05). Screw placement accuracy (Grade I) was significantly higher in the O-arm group (117 screws, 97.5%) than in the C-arm group (136 screws, 90.7%, P<0.05). No cases of wrong-level surgery, infection, or spinal cord/nerve injury occurred. Both groups showed significant improvements in MVBHr, Cobb angle, VAS, and ODI at all postoperative time points compared to preoperative values ( P<0.05). At final follow-up, the O-arm group demonstrated significantly better outcomes than the C-arm group in MVBHr (90.6%±4.5% vs. 86.4%±6.9%, P<0.05), Cobb angle (7.6°±1.8° vs. 10.1°±3.2°, P<0.05), VAS (1.3±0.4 vs. 1.7±0.6, P<0.05), and ODI (4.6%±1.9% vs. 7.7%±2.0%, P<0.01). Conclusion:O-arm navigation-assisted intrasegmental push reduction for A3N0/1 type thoracolumbar fractures demonstrates advantages including faster and more accurate screw placement, precise reduction with improved outcomes, and significant postoperative pain relief.