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.

Rheumatoid arthritis (RA) is a chronic autoimmune disease characterized by synovial inflammation, joint destruction, and functional impairment. Angiogenesis plays a key role in the pathological progression of RA with dysfunction of endothelial cells to promote synovial inflammation, sustain pannus formation, subsequently leading to joint damage. Colquhounia Root Tablets (CRT), a Chinese patent drug, has shown a satisfying clinical efficacy in treating RA, while the underlying mechanism by which CRT inhibits RA-associated angiogenesis remains unclear. In this study, we applied a research approach combining transcriptomic data analysis, bio-network mapping, and in vivo and in vitro experiments to explore the molecular mechanisms of CRT in suppressing angiogenesis in RA. Animal welfare and experimental procedures follow the regulations of the Animal Ethics Committee of Institute of Basic Theory for Chinese Medicine, China Academy of Chinese Medical Sciences (ratification number: IBTCMCACMS21-2307-06). Network analysis identified that key genes such as nucleotide-binding oligomerization domain-containing protein 2 (NOD2), SMAD family member 3 (SMAD3), and vascular endothelial growth factor A (VEGFA) significantly enriched in pathways related to NOD-like receptor signaling and VEGF signaling, indicating that CRT may inhibit angiogenesis by regulating vascular endothelial cell function with modulating angiogenesis-related pathways. In vivo data showed that CRT significantly reduced the positive expression of CD31 and VEGF in the ankle joint of adjuvant-induced arthritis (AIA) rats. In vitro data further confirmed that CRT effectively inhibited VEGF-induced migration, invasion, and tube formation in HUVECs, while significantly reduced the expression of angiogenesis-related factors VEGF/CD31/Ang-1, as well as the positive expression of VEGF and CD31 in HUVECs. Furthermore, CRT markedly decreased the protein expression of NOD2, VEGFA, and SMAD3. In conclusion, these findings indicate that CRT may inhibit the RA-related angiogenesis by targeting the NOD2/SMAD3/VEGF signaling axis to improve endothelial cell function, enriching the scientific connotation of CRT in inhibiting pathological angiogenesis in RA and also offer new insights for clinical prevention and treatment of RA.

ObjectiveBola-like short peptides exhibit novel self-assembly properties due to the formation of peptide dimers via hydrogen bonding interactions between their C-terminals. In this configuration, hydrophilic amino acids are distributed at both terminals, making these peptides behave similarly to Bola peptides. The electrostatic repulsive interactions arising from the hydrophilic amino acids at each terminal can be neutralized, thereby greatly promoting the lateral association of β-sheets. Consequently, assemblies with significantly larger widths are typically the dominant nanostructures for Bola-like peptides. To investigate the effect of hydrophilic amino acids on the self-assembly behavior of Bola-like peptides, the peptides Ac-RI₃-CONH₂ and Ac-HI₃-CONH₂ were designed and synthesized using the Bola-like peptide Ac-KI₃-CONH₂ as a template. Their self-assembly behavior was systematically examined. MethodsAtomic force microscopy (AFM) and transmission electron microscopy (TEM) were employed to characterize the morphology and size of the assemblies. The secondary structures of the assemblies were analyzed using circular dichroism (CD) and Fourier transform infrared (FTIR) spectroscopy. Small-angle neutron scattering (SANS) was used to obtain detailed structural information at a short-length scale. Based on these experimental results, the effects of hydrophilic amino acids on the self-assembly behavior of Bola-like short peptides were systematically analyzed, and the underlying formation mechanism was explored. ResultsThe aggregation process primarily involved three steps. First, peptide dimers were formed through hydrogen bonding interactions between their C-terminals. Within these dimers, the hydrophilic amino acids K, R, and H were positioned at both terminals, enabling the peptides to self-assemble in a manner similar to Bola peptides. Next, β-sheets were formed via hydrogen bonding interactions along the peptide backbone. Finally, self-assemblies were generated through the lateral association of β-sheets. The results demonstrated that both Ac-KI₃-CONH₂ and Ac-RI₃-CONH₂ could self-assemble into double-layer nanotubes with diameters of approximately 200 nm. These nanotubes were formed by the edge fusion of helical ribbons, which initially emerged from twisted ribbons. Notably, the primary assemblies of these peptides exhibited opposite chirality: nanofibers formed by Ac-KI₃-CONH₂ displayed left-handed chirality, whereas those formed by Ac-RI₃-CONH₂ exhibited right-handed chirality. This reversal in torsional direction was primarily attributed to the different abilities of K and R to form hydrogen bonds with water. In contrast, Ac-HI₃-CONH₂ formed narrower twisted ribbons with a significantly reduced width of approximately 30 nm, which was attributed to the strong steric hindrance caused by the imidazole rings. The multilayer height of these ribbons was mainly due to the unique structure of the imidazole rings, which can function as both hydrogen bond donors and acceptors, thereby promoting aggregate growth in the vertical direction. ConclusionThe final morphology of the self-assemblies resulted from a delicate balance of various non-covalent interactions. By altering the types of hydrophilic amino acid residues in Bola-like short peptides, the relative strength of non-covalent interactions that drive assembly formation can be effectively regulated, allowing precise control over the morphology and chirality of the assemblies. This study provides a simple and effective approach for constructing diverse self-assemblies and lays a theoretical foundation for the development of functional biomaterials.

Humans ; Vascular Stiffness ; Coal Mining ; Occupational Diseases/epidemiology* ; Risk Factors ; Coal ; Miners

Objective To investigate the clinical efficacy of Qiangli Pipa Syrup for the treatment of patients with acute exacerbation of chronic obstructive pulmonary disease(AECOPD),and to observe its effects on pulmonary function and interleukin 6(IL-6),C-reactive protein(CRP)and procalcitonin(PCT)levels in the patients.Methods Eighty patients with AECOPD of phlegm-heat obstructing the lung syndrome were randomly divided into the observation group and the control group,with 40 patients in each group.Patients in the control group were treated with conventional western medicine,and patients in the observation group were treated with Qiangli Pipa Syrup on the basis of treatment for the control group.Both groups were treated for 5 days.The two groups were observed in the changes of traditional Chinese medicine(TCM)syndrome scores(including cough,expectoration,shortness of breath,and wheezing),pulmonary function parameters[the forced expiratory volume in one second(FEV1)and the ratio of FEV1 to the forced vital capacity(FVC)(FEV1/FVC)],blood gas indicators[arterial partial pressure of oxygen(PaO2),blood oxygen saturation(SaO2)and arterial partial pressure of carbon dioxide(PaCO2)]and the levels of the inflammatory factors of IL-6,CRP,and PCT before and after treatment.Moreover,the clinical efficacy and safety of the patients in the two groups were evaluated.Results(1)After 5 days of treatment,the total effective rate of the observation group was 95.00%(38/40),and that of the control group was 77.50%(31/40).The intergroup comparison(tested by chi-square test)showed that the therapeutic effect of the observation group was significantly superior to that of the control group(P＜0.05).(2)After treatment,the TCM syndrome scores of cough,expectoration,shortness of breath,and wheezing in the two groups were reduced compared with those before treatment(P＜0.05),and the reduction in the observation group was significantly superior to that in the control group(P＜0.05).(3)After treatment,the pulmonary function parameters of FEV1/FVC and FEV1 in the two groups were improved compared with those before treatment(P＜0.05),and the improvement in the observation group was significantly superior to that in the control group(P＜0.05).(4)After treatment,the blood gas indicators of PaO2 and SaO2 levels in the two groups were increased compared with those before treatment(P＜0.05),and the PaCO2 level was decreased compared with that before treatment(P＜0.05).The increase of PaO2 and SaO2 levels and the decrease of PaCO2 level in the observation group were significantly superior to those in the control group(P＜0.05).(5)After treatment,the serum levels of inflammatory factors of IL-6,CRP,and PCT in the two groups were lower than those before treatment(P＜0.05),and the reduction in the observation group was significantly superior to that in the control group(P＜0.05).(6)The incidence of adverse reactions in the observation group was 10.00%(4/40),while that in the control group was 7.50%(3/40).There was no significant difference between the two groups(P＞0.05).Conclusion Qiangli Pipa Syrup exerts certain effect in treating patients with AECOPD of phlegm-heat obstructing the lung syndrome,which can effectively relieve the clinical symptoms,improve the pulmonary function and blood gas indicators,and inhibit inflammatory response of the patients,with high safety profile.

Superior vena cava syndrome(SVCS)is a group of clinical syndromes caused by obstruction of the superior vena cava and its major branches from various causes.Pulmonary artery stenosis(PS)is a complication of lung cancer or mediastinal tumours.SVCS combined with PS due to pulmonary metastases from bladder cancer is extremely rare and has not been reported in the literature.Here we reported an old male patient with pulmonary metastases from bladder cancer presenting with swelling of the head,neck and both upper limbs.SVCS combined with PS was clarified by pulmonary artery computed tomography angiography(CTA)and digital subtraction angiography(DSA).Endovascular stenting was used to treat SVCS.Angiography also showed that PS had not caused pulmonary hypertension and did not need to be treated.The swelling of the patient's head,neck and upper limbs was gradually reduced after the procedure.

OBJECTIVE:The rabbit model of steroid-induced osteonecrosis of femoral head is the most commonly used animal model of femoral head necrosis.The pathological changes of the femoral head are close to clinical practice,however,the conditions,methods and evaluation standards of animal models reported in and outside China are not uniform,which leads to the low scientific value of animal models and is difficult to popularize.This study aimed to clarify the influence of different mold-making conditions on the establishment of steroid-induced osteonecrosis of femoral head rabbit model and analyze the appropriate conditions for the successful model establishment. METHODS:We searched the CNKI,WanFang,VIP,CBM,WoS,PubMed and EMbsae databases for the literature on the modeling of steroid-induced osteonecrosis of femoral head rabbits up to April 1,2022,completed the screening of the literature according to the inclusion and exclusion criteria and literature quality evaluation,and extracted the outcome index data in the literature.RevMan Stata and ADDIS statistical software were used to conduct a meta-analysis of the included data. RESULTS:(1)A total of 82 articles with 1 366 rabbits were included in the study.The steroid-induced osteonecrosis of femoral head modeling methods were divided into three types:steroid-alone method,steroid combined lipopolysaccharide method and steroid combined serum method.Among these,33 articles used steroid-alone method;20 articles used steroid combined lipopolysaccharide method;29 articles used steroid combined serum method.(2)Meta-analysis results showed that the three modeling methods significantly increased the rate of empty bone lacunae in the femoral head of steroid-induced osteonecrosis of femoral head rabbits(P<0.001),and significantly decreased the ratio of the trabecular bone area in the femoral head of steroid-induced osteonecrosis of femoral head rabbits(P<0.001).The order of empty bone lacunae rate of each modeling method was:steroid combined with lipopolysaccharide method>steroid-alone method>steroid combined with serum method>normal group,and the order of trabecular bone area rate of each modeling method was:normal group>steroid combined with serum method>steroid-alone method>steroid combined with lipopolysaccharide method.(3)The results of subgroup analysis suggested that the rate of empty bone lacunae in the rabbit model induced by steroid alone might be related to the rabbit variety and the type of steroid used for modeling(difference between groups P<0.05),in which the combined effect amount of New Zealand white rabbits was higher than that of Chinese white rabbits(P<0.05)and Japanese white rabbits,and the combined effect amount of dexamethasone was higher than that of other steroids.The rate of empty bone lacunae induced by steroid combined with lipopolysaccharide was related to the administration mode of lipopolysaccharide and the type of steroid(P<0.05),among which the combined effect of methylprednisolone sodium succinate was significantly higher than that of other steroids(P<0.05),and the combined effect of prednisolone was significantly lower than that of other steroids(P<0.05).The combined effect of lipopolysaccharide 100 μg/kg×twice was significantly lower than 10 μg/kg×twice and 50 μg/kg×twice(P<0.05).The rate of empty bone lacunae in the model induced by steroid combined with serum was related to serum dose and steroid type(P<0.05),among which the combined effect amount of dexamethasone sodium phosphate was significantly higher than other steroid types(P<0.05),and the combined effect amount of dexamethasone was significantly lower than other steroid types(P<0.05);the combined effect amount of serum"10 mL/kg+6 mL/kg"combined dose was lower than other serum doses(P<0.05). CONCLUSION:(1)With the rate of empty bone lacunae and the ratio of trabecular bone area as the judgment standard for the successful establishment of the model,the three modeling methods can successfully construct the rabbit steroid-induced osteonecrosis of femoral head model,of which the steroid combined with lipopolysaccharide method is the best.(2)New Zealand white rabbits and dexamethasone are recommended when selecting the steroid-alone method.Methylprednisolone sodium succinate and low-dose lipopolysaccharide are recommended when selecting the steroid combined with lipopolysaccharide method.Dexamethasone sodium phosphate is recommended when selecting the steroid combined with serum modeling method.