ObjectivePrimary liver cancer, predominantly hepatocellular carcinoma (HCC), is a significant global health issue, ranking as the sixth most diagnosed cancer and the third leading cause of cancer-related mortality. Accurate and early diagnosis of HCC is crucial for effective treatment, as HCC and non-HCC malignancies like intrahepatic cholangiocarcinoma (ICC) exhibit different prognoses and treatment responses. Traditional diagnostic methods, including liver biopsy and contrast-enhanced ultrasound (CEUS), face limitations in applicability and objectivity. The primary objective of this study was to develop an advanced, light-weighted classification network capable of distinguishing HCC from other non-HCC malignancies by leveraging the automatic analysis of brightness changes in CEUS images. The ultimate goal was to create a user-friendly and cost-efficient computer-aided diagnostic tool that could assist radiologists in making more accurate and efficient clinical decisions. MethodsThis retrospective study encompassed a total of 161 patients, comprising 131 diagnosed with HCC and 30 with non-HCC malignancies. To achieve accurate tumor detection, the YOLOX network was employed to identify the region of interest (ROI) on both B-mode ultrasound and CEUS images. A custom-developed algorithm was then utilized to extract brightness change curves from the tumor and adjacent liver parenchyma regions within the CEUS images. These curves provided critical data for the subsequent analysis and classification process. To analyze the extracted brightness change curves and classify the malignancies, we developed and compared several models. These included one-dimensional convolutional neural networks (1D-ResNet, 1D-ConvNeXt, and 1D-CNN), as well as traditional machine-learning methods such as support vector machine (SVM), ensemble learning (EL), k-nearest neighbor (KNN), and decision tree (DT). The diagnostic performance of each method in distinguishing HCC from non-HCC malignancies was rigorously evaluated using four key metrics: area under the receiver operating characteristic (AUC), accuracy (ACC), sensitivity (SE), and specificity (SP). ResultsThe evaluation of the machine-learning methods revealed AUC values of 0.70 for SVM, 0.56 for ensemble learning, 0.63 for KNN, and 0.72 for the decision tree. These results indicated moderate to fair performance in classifying the malignancies based on the brightness change curves. In contrast, the deep learning models demonstrated significantly higher AUCs, with 1D-ResNet achieving an AUC of 0.72, 1D-ConvNeXt reaching 0.82, and 1D-CNN obtaining the highest AUC of 0.84. Moreover, under the five-fold cross-validation scheme, the 1D-CNN model outperformed other models in both accuracy and specificity. Specifically, it achieved accuracy improvements of 3.8% to 10.0% and specificity enhancements of 6.6% to 43.3% over competing approaches. The superior performance of the 1D-CNN model highlighted its potential as a powerful tool for accurate classification. ConclusionThe 1D-CNN model proved to be the most effective in differentiating HCC from non-HCC malignancies, surpassing both traditional machine-learning methods and other deep learning models. This study successfully developed a user-friendly and cost-efficient computer-aided diagnostic solution that would significantly enhances radiologists’ diagnostic capabilities. By improving the accuracy and efficiency of clinical decision-making, this tool has the potential to positively impact patient care and outcomes. Future work may focus on further refining the model and exploring its integration with multimodal ultrasound data to maximize its accuracy and applicability.

The auxin/indole-3-acetic acid (Aux/IAA) gene family is an important regulator for plant growth hormone signaling, involved in plant growth, development, as well as response to environmental stresses. In the present study, we identified SmIAA7 which is potentially associated with Salvia miltiorrhiza leaf development through comparatively analyzed the transcriptome data from different pinnate leaves. SmIAA7 was successfully isolated from S. miltiorrhiza using the specific primers. Then subsequent bioinformatic analysis, prokaryotic expression and purification, subcellular localization, and induction expression analysis under auxin and abiotic stress were performed. The full-length of SmIAA7 contained an ORF of 684 bp encoding a protein of 227 amino acid with a molecular weight of 25.3 kD. Conserved domain analysis showed that SmIAA7 contains the conserved Aux_IAA domain (pfam02309). Sequence analysis and phylogenetic tree analysis results indicated SmIAA7 was phylogenetically close to IAA7 and IAA14 from other plants, suggesting SmIAA7 involved in plant growth and development as well as response to environmental stresses. The prokaryotic expression vector pET28a-SmIAA7 was constructed and SmIAA7 recombinant protein was successfully expressed in E. coli Rosetta (DE3) strain. Subcellular localization experiment demonstrated that SmIAA7 localized in the nucleus of plant cells. Real-time fluorescence quantitative PCR results showed that the expression level of SmIAA7 was upregulated in response to auxin. Drought, low temperature, and salt stress significantly increased the transcript level of SmIAA7 gene. This study lays a foundation for further elucidating the role of SmIAA7 in leaf development, signal transduction, and stress defense in S. miltiorrhiza.

Metabolites produced as intermediaries or end-products of microbial metabolism provide crucial signals for health and diseases, such as metabolic dysfunction-associated steatotic liver disease (MASLD). These metabolites include products of the bacterial metabolism of dietary substrates, modification of host molecules (such as bile acids [BAs], trimethylamine-N-oxide, and short-chain fatty acids), or products directly derived from bacteria. Recent studies have provided new insights into the association between MASLD and the risk of developing chronic kidney disease (CKD). Furthermore, alterations in microbiota composition and metabolite profiles, notably altered BAs, have been described in studies investigating the association between MASLD and the risk of CKD. This narrative review discusses alterations of specific classes of metabolites, BAs, fructose, vitamin D, and microbiota composition that may be implicated in the link between MASLD and CKD.

Metabolites produced as intermediaries or end-products of microbial metabolism provide crucial signals for health and diseases, such as metabolic dysfunction-associated steatotic liver disease (MASLD). These metabolites include products of the bacterial metabolism of dietary substrates, modification of host molecules (such as bile acids [BAs], trimethylamine-N-oxide, and short-chain fatty acids), or products directly derived from bacteria. Recent studies have provided new insights into the association between MASLD and the risk of developing chronic kidney disease (CKD). Furthermore, alterations in microbiota composition and metabolite profiles, notably altered BAs, have been described in studies investigating the association between MASLD and the risk of CKD. This narrative review discusses alterations of specific classes of metabolites, BAs, fructose, vitamin D, and microbiota composition that may be implicated in the link between MASLD and CKD.

Metabolites produced as intermediaries or end-products of microbial metabolism provide crucial signals for health and diseases, such as metabolic dysfunction-associated steatotic liver disease (MASLD). These metabolites include products of the bacterial metabolism of dietary substrates, modification of host molecules (such as bile acids [BAs], trimethylamine-N-oxide, and short-chain fatty acids), or products directly derived from bacteria. Recent studies have provided new insights into the association between MASLD and the risk of developing chronic kidney disease (CKD). Furthermore, alterations in microbiota composition and metabolite profiles, notably altered BAs, have been described in studies investigating the association between MASLD and the risk of CKD. This narrative review discusses alterations of specific classes of metabolites, BAs, fructose, vitamin D, and microbiota composition that may be implicated in the link between MASLD and CKD.

Background Nitrogen dioxide (NO₂), a crucial component of traffic pollutants, has been shown in studies to exert toxic effects on the nervous system. However, there is a limited body of research examining the relationship between NO₂ exposure and neurological disorders in children. Objective To explore the impact of short-term NO₂ exposure on the outpatient visits due to pediatric neurological diseases in Shijiazhuang. Methods From 2013 to 2021, we collected outpatient data related to neurological diseases at the Children's Hospital in Shijiazhuang, Hebei Province. We also collected air pollution data and meteorological data of the same city. The air pollution data included daily average concentrations of inhalable particles (PM₁₀), fine particulate matter (PM_2.5), sulfur dioxide (SO₂), NO₂, carbon monoxide (CO), and daily maximum 8-hour average concentration of ozone (O₃). The meteorological data comprised daily average atmospheric pressure, temperature, relative humidity, wind speed, and sunshine duration. Employing a time-stratified case-crossover design, we used conditional logistic regression models to analyze the association between NO₂ and pediatric outpatient visits for neurological diseases. Stratification analyses were conducted based on gender (male, female) and age groups (0-6 years, 7-14 years). Results The study included a total of 154348 valid pediatric outpatient visits for neurological diseases. The daily average concentration of NO₂ was 49.3 μg·m⁻³ for the study period. The results from the single-pollutant model indicated that NO₂ increased the risk of pediatric neurological outpatient visits, with the highest association observed at lag0. Specifically, for every 10 μg·m⁻³ increase in atmospheric NO₂ exposure, there was a 1.40% increase (95%CI: 1.05%, 1.74%) in pediatric neurological outpatient visits. The stratification analyses revealed that increased atmospheric NO₂ exposure was associated with an elevated risk of neurological outpatient visits for girls (ER=1.54, 95%CI: 1.01, 2.08) and children aged 7-14 years (ER=2.35, 95%CI: 1.68, 3.02). Even after introducing PM_2.5 (ER=1.96, 95%CI: 1.49, 2.43), SO₂ (ER=2.09, 95%CI: 1.62, 2.55), and O₃ (ER=1.40, 95%CI: 1.06, 1.74) to the models, the impact of NO₂ exposure on pediatric neurological outpatient visits remained statistically significant. The results of the multi-pollutant model also indicated a significant association (ER=2.53, 95%CI: 1.97, 3.08). Conclusion The effect of short-term exposure to atmospheric NO₂ on the outpatient visits of children with neurological diseases in Shijiazhuang is acute and independent, especially for children aged 7-14.

Aim To investigate the effect of quercetin on the aging model of bone marrow mesenchymal stem cells established under microgravity. Methods Using 3D gyroscope, a aging model of bone marrow mesenchymal stem cells was constructed, and after receiving quercetin and microgravity treatment, the anti-aging effect of the quercetin was evaluated by detecting related proteins and oxidation indexes. Results Compared to the control group, the expressions of age-related proteins p21, pi6, p53 and RB in the microgravity group significantly increased, while the expressions of cyclin D1 and lamin B1 significantly decreased, with statistical significance (P<0.05). In the microgravity group, mitochondrial membrane potential significantly decreased (P<0.05), ROS accumulation significantly increased (P <0.05), SOD content significantly decreased and MDA content significantly increased (P<0.05). Compared to the microgravity group, the expressions of age-related proteins p21, pi6, p53 and RB in the quercetin group significantly decreased, while the expressions of cyclin D1 and lamin B1 significantly increased, with statistical significance (P<0.05). In the quercetin group, mitochondrial membrane potential significantly increased (P<0.05), ROS accumulation significantly decreased (P<0.05), SOD content significantly increased and MDA content significantly decreased (P<0.05). Conclusions Quercetin can resist oxidation, protect mitochondrial function and normal cell cycle, thus delaying the aging of bone marrow mesenchymal stem cells induced by microgravity.

Aim To explore the effects of Lycium berry seed oil on Nrf2/ARE pathway and oxidative damage in testis of subacute aging rats. Methods Fifty out of 60 male SD rats, aged 8 weeks, were subcutaneously injected with 125 mg • kg"D-galactosidase in the neck for 8 weeks to establish a subacute senescent rat model. The presence of senescent cells was observed using P-galactosidase ((3-gal), while testicular morphology was examined using HE staining. Serum levels of testosterone (testosterone, T), follicle-stimulating hormone ( follicle stimulating hormone, FSH ) , luteinizing hormone ( luteinizing hormone, LH ) , superoxide dis-mutase ( superoxide dismutase, SOD ) , glutathione ( glutathione, GSH) and malondialdehyde ( malondial-dehyde, MDA) were measured through ELISA, and the expressions of factors related to aging, oxidative damage, and the Nrf2/ARE pathway were assessed via immunohistochemical analysis and Western blotting. Results After successfully identifying the model, the morphology of the testis was improved and the intervention of Lycium seed oil led to a down-regulation in the expression of [3-gal and -yH2AX. The serum levels of SOD, GSH, T, and FSH increased while MDA and LH decreased (P 0. 05) . Additionally, there was an up-regulated expression of Nrf2, GCLC, NQOl, and SOD2 proteins in testicular tissue ( P 0. 05 ) and nuclear expression of Nrf2 in sertoli cells. Conclusion Lycium barbarum seed oil may reduce oxidative damage in testes of subacute senescent rats by activating the Nrf2/ARE signaling pathway.

Osteoarthritis （OA） is a common degenerative joint disease with a rising incidence rate year by year. Treatment often relies on analgesics and non-steroidal anti-inflammatory drugs （NSAIDs）， which can lead to gastrointestinal damage with long-term use and the recurrence of symptoms. Chinese medicine has a long history of preventing and treating OA， with widespread application and fewer side effects. It offers unique advantages such as a broad treatment scope， multiple targets， and pathways. The effective components of Chinese medicine can reduce the content of reactive oxygen species （ROS）， relieve oxidative stress （OS） damage， and increase the antioxidant capacity of the body by interfering with the expression of biomarkers of OS response such as malondialdehyde （MDA） and superoxide dismutase （SOD）. Through the modulation of signaling pathways such as nuclear factor E₂-related factor 2 （Nrf2）/heme oxygenase-1 （HO-1）， phosphatidylinositol 3-kinase （PI3K）/protein kinase B （Akt）， nuclear factor kappa B （NF-κB）， c-Jun N-terminal kinase （JNK）， NOD-like receptor protein 3 （NLRP3）， and osteoprotegerin （OPG）， they downregulated the expression of inflammatory factors such as interleukin-6 （IL-6）， interleukin-1β （IL-1β）， and tumor necrosis factor-α （TNF-α）， thereby effectively relieving local joint inflammation， protecting chondrocytes and bone tissue， inhibiting chondrocyte apoptosis， and further alleviating the progression of OA. Currently， there are still certain limitations in the medical research status and development trends of OA， necessitating the continued advancement of traditional Chinese medicine. This paper reviewed the literature on the regulation of OS response by effective components of Chinese medicine for the prevention and treatment of OA， providing new directions and ideas for future research.

OBJECTIVE To analyze the chemical constituents and components absorbed into plasma of the extract of Ardisia crenata and to elucidate its possible pharmacodynamic material basis. METHODS Overall， 12 rats were randomly assigned to the blank group （n＝6） and A. crenata group （n＝6） by the paired comparison method. The drug was administered once daily in the morning and afternoon for three days. Serum samples were prepared from serum after redosing on 4th day. The UPLC-QE-HF-MS/ MS was used to analyze and identify the chemical constituents in A. crenata extract and serum samples. Compound Discoverer 3.0 was employed for retention time correction， peak identification， and peak extraction. According to the secondary mass spectrometry information， the Thermo mzCloud online and Thermo mzVault local databases， referring to the relevant literature and control quality spectrum information were used to preliminarily identify the chemical constituents and components absorbed into plasma of A. crenata. RESULTS A total of 34 compounds were identified from the extract of A. crenata， mainly coumarins， flavonoids， organic acids， amino acids， including bergenin， quercetin， gallic acid， L-pyroglutamic acid， etc. Besides， 5 components absorbed into plasma were identified from serum samples: L-pyroglutamic acid， syringic acid， bergenin， cinnabar root saponin A， and mycophenolic acid. CONCLUSIONS L-pyroglutamic acid， syringic acid， bergenin， cinnabar root saponin A， and mycophenolic acid may act as the pharmacodynamic material basis of A. crenata.