ObjectiveTo explore the role of cucurbitacin B （CuB） in inducing ferroptosis in 4T1 cells and its mechanism. MethodsThe effects of CuB（0.2， 0.4， 0.8 μmol·L^-1）on the proliferation ability of 4T1 cells in vitro were detected using the methyl thiazolyl tetrazolium （MTT） assay. The clonogenic ability of 4T1 cells was detected by the plate cloning assay， and the levels of lactate dehydrogenase （LDH） in 4T1 cells were detected by the use of a kit. The mitochondrial membrane potential and reactive oxygen species （ROS） levels in 4T1 cells were detected by flow cytometry， and the mitochondrial ultrastructure of 4T1 cells was observed by transmission electron microscopy. The western blot was used to detect the expression of ferroptosis-related protein p53 in 4T1 cells， solute carrier family 7 member 11 （SCL7A11）， glutathione peroxidase 4 （GPX4）， long-chain acyl-CoA synthetase 4 （ACSL4）， transferrin receptor protein 1 （TFR1）， and ferritin heavy chain 1 （FTH1）. ResultsCompared with that in the blank group， the survival rate of 4T1 cells in CuB groups was significantly decreased （P<0.05）， and the number of cell clones in CuB groups was significantly reduced （P<0.01）. In addition， compared with that in the blank group， the leakage of LDH in cells in CuB groups was significantly increased （P<0.01）， and the mitochondrial membrane potential of cells in CuB groups decreased significantly （P<0.01）. Cellular ROS levels were significantly elevated in CuB groups （P<0.01）. The mitochondria of cells in CuB groups were obviously wrinkled， and the mitochondrial cristae were reduced or even disappeared. Compared with that in the blank group， the protein expression of p53， ACSL4， and TFR1 were significantly up-regulated in CuB groups （P<0.05）， and that of SLC7A11， GPX4， and FTH1 were significantly down-regulated （P<0.05）. ConclusionCuB may inhibit SLC7A11 and GPX4 expression by up-regulating the expression of p53， which in turn regulates the p53/SLC7A11/GPX4 signaling pathway axis and accelerates the generation of lipid peroxidation substrate by up-regulating the expression of ACSL4. It up-regulates TFR1 expression to promote cellular uptake of Fe³⁺ and down-regulates the expression of FTH1 to reduce the ability of iron storage， resulting in an elevated free Fe²⁺ level. It catalyzes the Fenton reaction， generates excess ROS， imbalances the antioxidant system and iron metabolism， and then induces ferroptosis in 4T1 cells.

ObjectiveTo explore the role of cucurbitacin B （CuB） in inducing ferroptosis in 4T1 cells and its mechanism. MethodsThe effects of CuB（0.2， 0.4， 0.8 μmol·L^-1）on the proliferation ability of 4T1 cells in vitro were detected using the methyl thiazolyl tetrazolium （MTT） assay. The clonogenic ability of 4T1 cells was detected by the plate cloning assay， and the levels of lactate dehydrogenase （LDH） in 4T1 cells were detected by the use of a kit. The mitochondrial membrane potential and reactive oxygen species （ROS） levels in 4T1 cells were detected by flow cytometry， and the mitochondrial ultrastructure of 4T1 cells was observed by transmission electron microscopy. The western blot was used to detect the expression of ferroptosis-related protein p53 in 4T1 cells， solute carrier family 7 member 11 （SCL7A11）， glutathione peroxidase 4 （GPX4）， long-chain acyl-CoA synthetase 4 （ACSL4）， transferrin receptor protein 1 （TFR1）， and ferritin heavy chain 1 （FTH1）. ResultsCompared with that in the blank group， the survival rate of 4T1 cells in CuB groups was significantly decreased （P<0.05）， and the number of cell clones in CuB groups was significantly reduced （P<0.01）. In addition， compared with that in the blank group， the leakage of LDH in cells in CuB groups was significantly increased （P<0.01）， and the mitochondrial membrane potential of cells in CuB groups decreased significantly （P<0.01）. Cellular ROS levels were significantly elevated in CuB groups （P<0.01）. The mitochondria of cells in CuB groups were obviously wrinkled， and the mitochondrial cristae were reduced or even disappeared. Compared with that in the blank group， the protein expression of p53， ACSL4， and TFR1 were significantly up-regulated in CuB groups （P<0.05）， and that of SLC7A11， GPX4， and FTH1 were significantly down-regulated （P<0.05）. ConclusionCuB may inhibit SLC7A11 and GPX4 expression by up-regulating the expression of p53， which in turn regulates the p53/SLC7A11/GPX4 signaling pathway axis and accelerates the generation of lipid peroxidation substrate by up-regulating the expression of ACSL4. It up-regulates TFR1 expression to promote cellular uptake of Fe³⁺ and down-regulates the expression of FTH1 to reduce the ability of iron storage， resulting in an elevated free Fe²⁺ level. It catalyzes the Fenton reaction， generates excess ROS， imbalances the antioxidant system and iron metabolism， and then induces ferroptosis in 4T1 cells.

Objective To investigate the effect and mechanism of miglitol on regulating the energy metabolism of brown adipocytes by activating UCP1 and preventing cold injury in mice after cold exposure. Methods Primary brown adipocytes were induced into mature adipocytes, the effect of miglitol on the viability of brown adipocytes was investigated by MTT method, the lipid droplet consumption level of cells after drug administration was investigated by Oil Red O staining technology, and the level of UCP1, a key protein of thermogenesis in brown adipocytes, was detected by Western blotting. The activity of anti-frostbite was investigated in cold exposure at 4 ℃ and −20 ℃. KM mice, which were randomly divided into control group, cold exposure group, miglitol group and all-trans retinoic acid group, and after 7 days of repeated administration, the body surface temperature of mice was detected by infrared thermal imaging system, the anal temperature change was detected by anal thermometer, and the expression levels of UCP1 and PGC1-α in adipose tissue were detected by immunoblotting. Results Compared with the control group, the lipid droplet consumption and UCP1 expression levels in brown adipocytes in the miglitol group were significantly increased. The levels of body surface temperature and rectal temperature increased significantly after cold exposure, and the levels of UCP1 and PGC1α in the brown adipose tissue of mice increased significantly, which indicated that the miglitol could activate the critical proteins UCP1 and PGC1α of the thermogenesis pathway, increase the thermogenesis of mice after cold exposure, and thus improve the effect of cold injury for toe swelling. Conclusion Miglitol could play a role in improving cold injury and body temperature in mice by increasing the level of UCP1 and PGC1α, which are key targets of the thermogenesis pathway to promote the thermogenesis of brown fat.

Objective To establish an HPLC method to determine the concentration of inositol nicotinate（IN） in rat skin, and study the pharmacokinetic characteristics of IN after transdermal administration of heparin sodium inositol nicotinate cream in rats. Methods HPLC method was used to establish a simple and rapid analytical method for the determination of IN concentration in the skin of rats at different time points after administration. The established method was used to study the pharmacokinetics of IN after transdermal administration of heparin sodium inositol nicotinate cream in rats, and the pharmacokinetic parameters were fitted with DAS software. Results The linearity of the analytical method was good in the concentration range of 0.25-20 μg/ml, the quantitative limit was 0.25 μg/ml, and the average recovery rate was 96.18%. The pharmacokinetic parameters of IN after transdermal administration of heparin sodium inositol nicotinate cream in rats were as follows: t_1/2 was （4.555±2.054） h, T_max was （6±0）h, C_max was （16.929±2.153）mg/L, AUC_0−t was （150.665±16.568） mg·h /L ,AUC_0−∞ was （161.074±23.917） mg·h /L, MRT_（0−t） was （9.044±0.618）h, MRT_{（0−∞）} was （10.444±1.91） h, CLz/F was （0.19±0.03） L/（h·kg）, and Vz/F was （1.19±0.437） L/（h·kg）. Conclusion IN could quickly penetrate the skin and accumulate in the skin for a long time, which was beneficial to the pharmacological action of drugs on the lesion site for a long time. The method is simple, rapid, specific and reproducible, which could be successfully applied to the pharmacokinetic study of IN after transdermal administration in rats.

Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.

Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.

Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.

OBJECTIVE: Lipid oxidation is involved in the pathogenesis of atherosclerosis and may be contribute to the development of Ischemic stroke (IS). However, the lipid profiles associated with IS have been poorly studied. We conducted a pilot study to identify potential IS-related lipid molecules and pathways using lipidomic profiling. METHODS: Serum lipidomic profiling was performed using LC-MS in 20 patients with IS and 20 age- and sex-matched healthy controls. Univariate and multivariate analyses were simultaneously performed to identify the differential lipids. Multiple testing was controlled for using a false discovery rate (FDR) approach. Enrichment analysis was performed using MetaboAnalyst software. RESULTS: Based on the 294 lipids assayed, principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) models were used to distinguish patients with IS from healthy controls. Fifty-six differential lipids were identified with an FDR-adjusted P less than 0.05 and variable influences in projection (VIP) greater than 1.0. These lipids were significantly enriched in glycerophospholipid metabolism (FDR-adjusted P = 0.009, impact score = 0.216). CONCLUSIONS Serum lipid profiles differed significantly between patients with IS and healthy controls. Thus, glycerophospholipid metabolism may be involved in the development of IS. These results provide initial evidence that lipid molecules and their related metabolites may serve as new biomarkers and potential therapeutic targets for IS.
Humans ; Pilot Projects ; Lipidomics ; Male ; Female ; Biomarkers/blood* ; Middle Aged ; Ischemic Stroke/blood* ; Aged ; China ; Lipids/blood* ; Adult ; Case-Control Studies ; East Asian People

OBJECTIVE: The objective of our study was to evaluate the vaccine effectiveness (VE) of the pentavalent rotavirus vaccine (RV5) among < 5-year-old children in three provinces of China during 2020-2024 via a propensity score-matched test-negative case-control study. METHODS: Electronic health records and immunization information systems were used to obtain data on acute gastroenteritis (AGE) cases tested for rotavirus (RV) infection. RV-positive cases were propensity score matched with RV-negative controls for age, visit month, and province. RESULTS: The study included 27,472 children with AGE aged 8 weeks to 4 years at the time of AGE diagnosis; 7.98% (2,192) were RV-positive. The VE (95% confidence interval, CI) of 1-2 and 3 doses of RV5 against any medically attended RV infection (inpatient or outpatient) was 57.6% (39.8%, 70.2%) and 67.2% (60.3%, 72.9%), respectively. Among children who received the 3rd dose before turning 5 months of age, 3-dose VE decreased from 70.4% (53.9%, 81.1%) (< 5 months since the 3rd dose) to 63.0% (49.1%, 73.0%) (≥ 1 year since the 3rd dose). The three-dose VE rate was 69.4% (41.3%, 84.0%) for RVGE hospitalization and 57.5% (38.9%, 70.5%) for outpatient-only medically attended RVGE. CONCLUSION Three-dose RV5 VE against rotavirus gastroenteritis (RVGE) in children aged < 5 years was higher than 1-2-dose VE. Three-dose VE decreased with time since the 3rd dose in children who received the 3rd dose before turning five months of age, but remained above 60% for at least one year. VE was higher for RVGE hospitalizations than for medically attended outpatient visits.
Humans ; Rotavirus Vaccines/immunology* ; China/epidemiology* ; Case-Control Studies ; Child, Preschool ; Infant ; Rotavirus Infections/epidemiology* ; Male ; Propensity Score ; Female ; Vaccine Efficacy ; Gastroenteritis/virology* ; Vaccines, Attenuated ; Rotavirus

OBJECTIVE: Recombination events are common and serve as the primary driving force of diverse human adenovirus (HAdV), particularly in children with acute respiratory tract infections (ARIs). Therefore, continual monitoring of these events is essential for effective viral surveillance and control. METHODS: Respiratory specimens were collected from children with ARIs between January 2022 and December 2023. The penton base, hexon, and fiber genes were amplified from HAdV-positive specimens and sequenced to determine the virus type. In cases with inconsistent typing results, genes were cloned into the pGEM-T vector to detect recombination events. Metagenomic next-generation sequencing (mNGS) was performed to characterize the recombinant HAdV genomes. RESULTS: Among 6,771 specimens, 277 (4.09%, 277/6,771) were positvie for HAdV, of which 157 (56.68%, 157/277) were successfully typed, with HAdV-B3 being the dominant type (91.08%, 143/157), and 14 (5.05%, 14/277) exhibited inconsistent typing results, six of which belonged to species B. The penton base genes of these six specimens were classified as HAdV-B7, whereas their hexon and fiber genes were classified as HAdV-B3, resulting in a recombinant genotype designated P7H3F3, which closely resembled HAdV-B114. Additionally, a partial gene encoding L1 52/55 kD was identified, which originated from HAdV-B16. CONCLUSION A novel recombinant, P7H3F3, was identified, containing sequences derived from HAdV-B3 and HAdV-B7, which is similar to HAdV-B114, along with additional sequences from HAdV-B16.
Humans ; Adenoviruses, Human/isolation & purification* ; Respiratory Tract Infections/epidemiology* ; Child, Preschool ; Child ; Recombination, Genetic ; Male ; Beijing/epidemiology* ; Infant ; Female ; Phylogeny ; Adenovirus Infections, Human/epidemiology* ; Acute Disease ; Genome, Viral