Olfactory receptors (ORs) form the largest superfamily of G protein-coupled receptors (GPCRs). Traditionally recognized for their role in the nasal olfactory epithelium, where they mediate the sense of smell, accumulating evidence has firmly established their ectopic expression in non-olfactory tissues, including the intestine, lungs, and kidneys. The intestine, as the primary site for nutrient digestion and absorption, harbors a highly complex chemical environment. To adapt to this environment, the gut employs a sophisticated network of “chemosensors” to monitor luminal contents and maintain homeostasis. Among these sensors, intestinal ORs have emerged as crucial functional components, serving as a molecular bridge that connects environmental chemical signals—such as food-derived odorants—to specific physiological responses. This discovery has significantly deepened our understanding of how dietary flavors and compounds influence intestinal physiology at the molecular level. This review systematically summarizes the expression profiles, ligand classification, and biological functions of ORs within the gastrointestinal tract. Studies indicate that intestinal ORs exhibit distinct spatial distribution patterns across different gut segments and display cell-type specificity, particularly within enterocytes and enteroendocrine cells. These receptors function as versatile sensors capable of recognizing a wide variety of ligands, including exogenous dietary components, gut microbiota metabolites such as short-chain fatty acids, and endogenous small molecules like azelaic acid. Upon activation by specific ligands, intestinal ORs trigger intracellular signaling cascades, primarily involving the AC-cAMP-PKA pathway or calcium influx channels. A major focus of this review is to elucidate the molecular mechanisms by which these receptors regulate the secretion of gut hormones. Activation of specific ORs in enteroendocrine cells has been shown to stimulate the release of hormones such as glucagon-like peptide-1 (GLP-1), peptide YY (PYY), and serotonin (5-HT), thereby modulating systemic energy metabolism, glucose homeostasis, and gastrointestinal motility. Furthermore, the review addresses the critical roles of ORs in immune regulation and pathology. Evidence suggests that specific ORs contribute to the maintenance of intestinal immune homeostasis and may offer protection against inflammation. Beyond their involvement in inflammatory responses, ORs such as Olfr78 have been shown to regulate the differentiation and function of intestinal endocrine cells. Similarly, Olfr544 has been demonstrated to alleviate intestinal inflammation by remodeling the gut microbiome and metabolome. These findings collectively suggest that specific ORs hold promise as therapeutic targets for mitigating intestinal inflammation and maintaining gut homeostasis. Additionally, the review explores the emerging role of ORs in cancer. Although OR expression is often downregulated in tumor tissues compared to normal mucosa, activation of specific ORs by certain ligands can inhibit tumor cell proliferation and migration and induce apoptosis via pathways such as MEK/ERK and p38 MAPK. Conversely, other receptors, such as OR7C1, may serve as biomarkers for cancer-initiating cells. In conclusion, intestinal ORs represent a vital component of the gut’s sensory network. The review also discusses the translational potential of these findings. By elucidating the precise pairing relationships between dietary components and specific ORs, novel therapeutic strategies could be developed. Intestinal ORs may thus emerge as promising targets for nutritional and pharmacological interventions in metabolic diseases, inflammatory bowel diseases, and malignancies.

Plutonium isotopes(238Pu,239Pu,240Pu and 241Pu)in the environment are important"fingerprint"nuclides in the study of nuclear activity traceability.The content of plutonium isotopes in the environmental metrics is usually very low,and the measurement of these isotopes,especially 238Pu,using mass spectrometry is seriously interfered with by the coexisting 238U.The analysis of several plutonium isotopes in soil usually requires combination of multiple measurement techniques,which leads to a long analysis time and large uncertainty in the isotope ratio.In this work,the hydrous titanium oxide(HTiO)precipitated by the hydrolysis of titanium oxydichloride(TiOCl2)under near-neutral condition was used to preconcentrate plutonium from the soil digestion solution,and the highly efficient decontamination of 238U in the sample was achieved by TK200 resin column chromatography with a decontamination factor of 108.Simulation resuts of density functional theory(DFT)showed that NH3 was considered as a promising reaction gas to eliminate the interference of 238U from 238Pu measurement using mass spectrometry due to the significant discrepancy of the chemical reactivity of U+and Pu+with the reactive gas NH3.Experiments confirmed that by optimizing the flow rates of collision gas(He)and reaction gas(NH3),the interference of 238U could be effectively suppressed,and the decontamination factor of 238U was 104.Combined with chemical separation,the overall decontamination factor of 238U could reach 1012 by using the developed method.By combining chemical separation and tandem quadrupole inductively coupled plasmon-mass spectrometry(ICP-MS/MS)measurement,the simultaneous determination of four ultra-trace plutonium isotopes in soil was realized,and the detection limit of plutonium isotopes was at the femtogram level.Analysis of the international standard reference materials(NIST-SRM-4357 and IAEA-384)showed that the established method could be successfully used for the accurate analysis of ultra-trace four plutonium isotopes(238Pu,239Pu,240Pu and 241Pu)in soil samples.

Objective To explore the correlation between the actual age and the pulp chamber volume(PCV)and pulp dentinal index(PDI)of the right first molars based on cone beam computed tomog-raphy(CBCT)technology,and to construct an accurate and convenient model for age estimation.Methods CBCT image data of 1 857 Han adults(883 males and 974 females)from the Department of Stomatology,Affiliated Hospital of North Sichuan Medical College were collected.The data were di-vided into training and validation sets at a ratio of 8∶2.A total of 1 485 training samples were used to construct the age estimation model,and 372 samples were used to validate the accuracy of the model.The Mimics 21.0 software was used to measure the PCV and calculate the PDI of the right first molars.Their correlations with age and the differences between different sexes and tooth positions were analyzed.Results Both the PCV and the PDI of the first molars showed strong negative correla-tions with the actual age(r values ranged from 0.82 to 0.89).The differences in PCV and PDI be-tween different sexes and tooth positions were statistically significant(P<0.05).The age estimation model based on PDI was superior to that based on PCV.The model based on the PDI values of the two right first molars(y=73.72-44.15 x3-28.27 x4,where x3 and x4 are the PDI values of the right maxil-lary and mandibular first molars,respectively)was the best,with the R2 of 0.79 and the mean abso-lute error of 4.90 years.Conclusion Both PCV and PDI of the first molars are effective indicators for age estimation.The age estimation model based on the PDI is more convenient and accurate than that based on the PCV,providing a more effective method for age estimation in forensic practice.

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

Traditional Chinese medicine(TCM) capable of clearing heat and removing toxin is most commonly used in clinical practice and has the effect of removing fire-heat and toxin. Studies have shown that most of the Ilex plants have the effect of clearing heat and removing toxin, among which the varieties of I. cornuta, I. pubescens, I. rotunda, I. latifolia, and I. chinensis are most widely used. These plants generally contain triterpenoids and their glycosides, alkaloids, flavonoids, phenylpropanoids, and other chemical components, especially pentacyclic triterpenoids. According to their skeletons, pentacyclic triterpenoids can be divided into the oleanane type, the ursane type, the lupinane type, etc. Among them, ursane-type components are the most abundant, and 136 species have been found so far. These components have been proved to have pharmacological effects such as anti-inflammatory, anti-tumor, hypolipidemic, anti-thrombosis, cardiomyocyte-protective, antibacterial, and hepatoprotective effects. Therefore, this paper systematically reviews the domestic and foreign literature on Ilex plants with a focus on the research progress on pentacyclic triterpenoids and their pharmacological activities, aiming to provide reference for the development of TCM resources with the effect of clearing heat and removing toxin.
Ilex/chemistry* ; Plants, Medicinal/chemistry* ; Pentacyclic Triterpenes/pharmacology* ; Medicine, Chinese Traditional ; Drugs, Chinese Herbal/pharmacology* ; Humans ; Animals

Objective To explore the potential prognostic factors of patients with acute ischemic stroke(AIS)after undergoing endovascular mechanical thrombectomy and to construct an effective predictive model.Methods A retrospective analysis of clinical data was conducted on 202 patients with anterior circulation large vessel occlusion AIS from 2 stroke centers.All patients received endovascular mechanical thrombectomy treatment,with treatment and follow-up lasting at least 90 d.Basic demographic characteristics,medical records,and baseline blood biomarker data were collected,and the potential prognostic indicators for AIS after 90 d were screened using least absolute shrinkage and selection operator(LASSO)-logistic regression analysis.Results It was found that alcohol drinking(P=0.029),hypertension(P=0.001),diabetes mellitus(P=0.021),stroke or transient ischemic attack(P=0.049),systolic blood pressure on admission(P=0.009),diastolic blood pressure on admission(P=0.038),blood glucose(P=0.003),white blood cell count(P=0.001),neutrophil count(P=0.001),fibrinogen(P=0.010),systemic immune-inflammation index(P=0.008)and neutrophil-to-lymphocyte ratio(NLR)(P＜0.001)were associated with adverse clinical outcomes.Nine significant prognostic determinants were screened through LASSO-logistic regression analysis.Multivariate logistic regression analysis revealed that male sex(P=0.008),smoking history(P=0.013),hypertension(P=0.011),lymphocyte(P=0.028),fibrinogen(P=0.016),and NLR(P＜0.001)were significant predictive factors for poor prognosis in AIS patients after endovascular thrombectomy treatment.The constructed prognostic model had an accuracy of 76.2％,a sensitivity of 78.2％,a specificity of 71.7％,and a positive predictive value of 86.7％.Conclusion The predictive model established in this study can assist clinicians in identifying high-risk patients with AIS who have undergone endovascular thrombectomy,and it provide guidance for formulating individualized treatment strategies.

Hemorrhagic shock is a common clinical emergency that can aggravate cell injury after resuscitation. Astrocytes are crucial for the survival of neurons because they regulate the surrounding ionic microenvironment of neurons. Although hemorrhagic shock and resuscitation (HSR) injury can impair cognition, it remains unclear how this insult directly affects astrocytes. In this study, we established an HSR model by bleeding and re-transfusion in mice. The social interaction test and new object recognition test were applied to evaluate post-operative cognitive changes, and the results suggest that mice experience cognitive impairment following exposure to HSR. In the HSR group, the power spectral density of β and γ oscillations decreased, and the coupling of the θ oscillation phase and γ oscillation amplitude was abnormal, which indicated abnormal neuronal oscillation and cognitive impairment after HSR exposure. In brief, cognitive impairment in mice is strongly correlated with Ca²⁺ signal strength in lateral septum astrocytes following HSR.
Animals ; Astrocytes/metabolism* ; Shock, Hemorrhagic/metabolism* ; Resuscitation/adverse effects* ; Male ; Mice ; Calcium Signaling/physiology* ; Mice, Inbred C57BL ; Septal Nuclei/metabolism* ; Cognitive Dysfunction/etiology* ; Disease Models, Animal ; Cognition Disorders/etiology*

Objective To investigate the correlation between spread through air space (STAS) of sub-centimeter non-small cell lung cancer and clinical characteristics and radiological features, constructing a nomogram risk prediction model for STAS to provide a reference for the preoperative planning of sub-centimeter non-small cell lung cancer patients. Methods The data of patients with sub-centimeter non-small cell lung cancer who underwent surgical treatment in Nanjing Drum Tower Hospital from January 2022 to October 2023 were retrospectively collected. According to the pathological diagnosis of whether the tumor was accompanied with STAS, they were divided into a STAS positive group and a STAS negative group. The clinical and radiological data of the two groups were collected for univariate logistic regression analysis, and the variables with statistical differences were included in the multivariate analysis. Finally, independent risk factors for STAS were screened out and a nomogram model was constructed. The sensitivity and specificity were calculated based on the Youden index, and area under the curve (AUC), calibration plots and decision curve analysis (DCA) were used to evaluate the performance of the model. Results A total of 112 patients were collected, which included 17 patients in the STAS positive group, consisting of 11 males and 6 females, with a mean age of (59.0±10.3) years. The STAS negative group included 95 patients, with 30 males and 65 females, and a mean age of (56.8±10.3) years. Univariate logistic regression analysis showed that male, anti-GAGE7 antibody positive, mean CT value and spiculation were associated with the occurrence of STAS (P＜0.05). Multivariate regression analysis showed that associations between STAS and male (OR=5.974, 95%CI 1.495 to 23.872), anti-GAGE7 antibody positive (OR=11.760, 95%CI 1.619 to 85.408) and mean CT value (OR=1.008, 95%CI 1.004 to 1.013) were still significant (P＜0.05), while the association between STAS and spiculation was not significant anymore (P=0.438). Based on the above three independent predictors, a nomogram model of STAS in sub-centimeter non-small cell lung cancer was constructed. The AUC value of the model was 0.890, the sensitivity was 76.5%, and the specificity was 91.6%. The calibration curve was well fitted, suggesting that the model had a good prediction efficiency for STAS. The DCA plot showed that the model had a good clinically utility. Conclusion Male, anti-GAGE7 antibody positive and mean CT value are independent predictors of STAS positivity of sub-centimeter non-small cell lung cancer, and the nomogram model established in this study has a good predictive value and provides reference for preoperative planning of patients.

Biomolecular condensates are formed through phase separation of biomacromolecules such as proteins and RNAs. These condensates exhibit liquid-like properties that can futher transition into more stable material states. They form complex internal structures via multivalent weak interactions, enabling precise spatiotemporal regulations. However, the use of inconsistent and non-standardized terminology has become increasingly problematic, hindering academic exchange and the dissemination of scientific knowledge. Therefore, it is necessary to discuss the terminology related to biomolecular condensates in order to clarify concepts, promote interdisciplinary cooperation, enhance research efficiency, and support the healthy development of this field.

Liposomes serve as critical carriers for drugs and vaccines, with their biological effects influenced by their size. The microfluidic method, renowned for its precise control, reproducibility, and scalability, has been widely employed for liposome preparation. Although some studies have explored factors affecting liposomal size in microfluidic processes, most focus on small-sized liposomes, predominantly through experimental data analysis. However, the production of larger liposomes, which are equally significant, remains underexplored. In this work, we thoroughly investigate multiple variables influencing liposome size during microfluidic preparation and develop a machine learning (ML) model capable of accurately predicting liposomal size. Experimental validation was conducted using a staggered herringbone micromixer (SHM) chip. Our findings reveal that most investigated variables significantly influence liposomal size, often interrelating in complex ways. We evaluated the predictive performance of several widely-used ML algorithms, including ensemble methods, through cross-validation (CV) for both liposome size and polydispersity index (PDI). A standalone dataset was experimentally validated to assess the accuracy of the ML predictions, with results indicating that ensemble algorithms provided the most reliable predictions. Specifically, gradient boosting was selected for size prediction, while random forest was employed for PDI prediction. We successfully produced uniform large (600 nm) and small (100 nm) liposomes using the optimised experimental conditions derived from the ML models. In conclusion, this study presents a robust methodology that enables precise control over liposome size distribution, offering valuable insights for medicinal research applications.