Objective To preliminary explore the imaging manifestations of digital breast tomosynthesis (DBT) and contrast-enhanced mammography (CEM) in triple-negative breast cancer (TNBC) patients with different levels of human epidermal growth factor receptor 2 (HER2) expression. Methods A retrospective analysis was conducted on TNBC patients who underwent preoperative DBT or CEM examinations at Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine from January 2018 to December 2019 and Shanghai Second People’s Hospital from January 2022 to May 2025. Clinical data, pathological and immunohistochemical results, and imaging data were collected. Results A total of 69 TNBC patients pathologically confirmed as invasive ductal carcinoma were included, among which 34 underwent DBT and 35 underwent CEM. Among these patients, 34 (49.28%) had HER2-low expression and 35 (50.72%) had HER2-zero expression. DBT results showed that the proportion of spiculation signs in HER2-low group (n＝14) was significantly higher than that in HER2-zero group (n＝20; P＝0.009, P_adj＝0.045). However, there were no significant differences in breast density type, mass shape, or calcification between the two groups. CEM results showed that on low-energy images, the proportion of spiculation signs in the HER2-low group (n＝20) was higher than that in the HER2-zero group (n＝15; P＝0.011, P_adj＝0.077). Results of CEM showed that on reconstructed images, differences in background parenchymal enhancement and mass enhancement patterns between the two groups were not statistically significant; in both groups, heterogeneous enhancement was the most common, followed by homogeneous enhancement, with ring enhancement being the least common. Conclusions TNBC with low HER2 expression and TNBC with zero HER2 expression may have potential differences in the presentation of spiculation signs on DBT. However, the correlation between CEM manifestations and TNBC with different HER2 expression levels requires further research.

P-glycoprotein (P-gp) is a transmembrane protein widely involved in the absorption, distribution, metabolism, excretion, and toxicity (ADMET) of drugs within the human body. Accurate prediction of P-gp inhibitors and substrates is crucial for drug discovery and toxicological assessment. However, existing models rely on limited molecular information, leading to suboptimal model performance for predicting P-gp inhibitors and substrates. To overcome this challenge, we compiled an extensive dataset from public databases and literature, consisting of 5,943 P-gp inhibitors and 4,018 substrates, notable for their high quantity, quality, and structural uniqueness. In addition, we curated two external test sets to validate the model's generalization capability. Subsequently, we developed a multimodal graph contrastive learning (GCL) model for the prediction of P-gp inhibitors and substrates (MC-PGP). This framework integrates three types of features from Simplified Molecular Input Line Entry System (SMILES) sequences, molecular fingerprints, and molecular graphs using an attention-based fusion strategy to generate a unified molecular representation. Furthermore, we employed a GCL approach to enhance structural representations by aligning local and global structures. Extensive experimental results highlight the superior performance of MC-PGP, which achieves improvements in the area under the curve of receiver operating characteristic (AUC-ROC) of 9.82% and 10.62% on the external P-gp inhibitor and external P-gp substrate datasets, respectively, compared with 12 state-of-the-art methods. Furthermore, the interpretability analysis of all three molecular feature types offers comprehensive and complementary insights, demonstrating that MC-PGP effectively identifies key functional groups involved in P-gp interactions. These chemically intuitive insights provide valuable guidance for the design and optimization of drug candidates.

P-glycoprotein(P-gp)is a transmembrane protein widely involved in the absorption,distribution,metabolism,excretion,and toxicity(ADMET)of drugs within the human body.Accurate prediction of P-gp inhibitors and substrates is crucial for drug discovery and toxicological assessment.However,existing models rely on limited molecular information,leading to suboptimal model performance for predicting P-gp inhibitors and substrates.To overcome this challenge,we compiled an extensive dataset from public databases and literature,consisting of 5,943 P-gp inhibitors and 4,018 substrates,notable for their high quantity,quality,and structural uniqueness.In addition,we curated two external test sets to validate the model's generalization capability.Subsequently,we developed a multimodal graph contrastive learning(GCL)model for the prediction of P-gp inhibitors and substrates(MC-PGP).This framework integrates three types of features from Simplified Molecular Input Line Entry System(SMILES)sequences,molecular fingerprints,and molecular graphs using an attention-based fusion strategy to generate a unified mo-lecular representation.Furthermore,we employed a GCL approach to enhance structural representations by aligning local and global structures.Extensive experimental results highlight the superior perfor-mance of MC-PGP,which achieves improvements in the area under the curve of receiver operating characteristic(AUC-ROC)of 9.82％and 10.62％on the external P-gp inhibitor and external P-gp substrate datasets,respectively,compared with 12 state-of-the-art methods.Furthermore,the interpretability analysis of all three molecular feature types offers comprehensive and complementary insights,demonstrating that MC-PGP effectively identifies key functional groups involved in P-gp interactions.These chemically intuitive insights provide valuable guidance for the design and optimization of drug candidates.

Inflammation, abnormal cholesterol metabolism, and macrophage infiltration are involved in the destruction of the extracellular matrix of the nucleus pulposus (NP), culminating in intervertebral disc degeneration (IDD). Whether nimbolide (Nim), a natural extract, can alleviate IDD is unclear. In this study, we demonstrated that Nim promotes cholesterol efflux and inhibits the activation of the nuclear factor kappa B (NF-κB) and mitogen-activated protein kinase (MAPK) signaling pathways by activating sirtuin 1 (SIRT1) in nucleus pulposus cells (NPCs) during inflammation. Thus, Nim balanced matrix anabolism and catabolism of NPCs. However, the inhibition of SIRT1 significantly attenuated the effects of Nim. We also found that Nim promoted the expression of SIRT1 in RAW 264.7, which enhanced the proportion of M2 macrophages by facilitating cholesterol homeostasis reprogramming and impeded M1-like macrophages polarization by blocking the activation of inflammatory signaling. Based on these results, Nim can improve the microenvironment and facilitate matrix metabolism equilibrium in NPCs. Furthermore, in vivo treatment with Nim delayed IDD progression by boosting SIRT1 expression, modulating macrophage polarization and preserving the extracellular matrix. In conclusion, Nim may represent a novel therapeutic strategy for treating IDD.

Objective:To investigate the changes and clinical significance of neuron specific enolase (NSE) and S-100β protein levels in cerebrospinal fluid of children with viral encephalitis and meningitis.Methods:Sixty children with viral encephalitis and meningitis admitted to The Second Hospital of Jiaxing from February 2018 to December 2020 were included in the observation group. An additional 30 children without central nervous system diseases who concurrently received treatment in the same hospital were included in the control group. The value of NSE and S-100β protein levels in the diagnosis and treatment of viral encephalitis and meningitis in chiblren were analyzed.Results:NSE and S-100β protein levels in the observation group were (17.683 ± 1.321) μg/L and (1.755 ± 0.129) μg/L, respectively, which were significantly higher than (5.267 ± 0.907) μg/L and (0.827 ± 0.172) μg/L in the control group ( t = 46.25, 28.65, both P < 0.001). NSE and S-100β protein levels in children with mild viral encephalitis and meningitis were (15.219 ± 0.870) μg/L and (1.456 ± 0.113) μg/L, respectively, which were significantly lower than (19.893 ± 1.066) μg/L and (2.014 ± 0.085) μg/L in children with severe viral encephalitis and meningitis ( t = -18.69, -21.32, both P < 0.001). In children with viral encephalitis and meningitis, NSE and S-100β protein levels during the acute phase were (17.250 ± 1.188) μg/L and (1.683 ± 0.096) μg/L, respectively, which were significantly higher than (11.150 ± 0.971) μg/L and (1.147 ± 0.098) μg/L during the convalescence phase ( t = 30.79, 30.27, both P < 0.001). Conclusion:NSE and S-100β protein levels in cerebrospinal fluid of children with viral encephalitis and meningitis can help evaluate the severity of viral encephalitis and meningitis in children, providing important clinical application value for judging the development and prognosis of viral encephalitis and meningitis.

Given that the current Newcastle disease virus (NDV) infection in wild birds poses the threat to poultry, surveillance of Newcastle disease in captive wild birds was carried out in Jilin, China in 2018. Here, an NDV strain obtained from toco toucan was firstly characterized.The results showed that the F gene of the NDV isolate Toucan/China/3/2018 is classified as genotype II in class II. Sequence analysis of the F0 cleavage site was 113 RQGR/L 117 , which supports the result of the intracerebral pathogenicity index assay indicating classification of the isolate as low-pathogenicity. Experimental infection demonstrated that Toucan/ China/3/2018 can effectively replicate and transmit among chickens. To our knowledge, this is the first report on genetically and pathogenically characterizing NDV strain isolated from toucan, which enriches the epidemiological information of NDV in wild birds.

APOBEC-1 Deaminase ; genetics ; Clustered Regularly Interspaced Short Palindromic Repeats ; Codon, Terminator ; Gene Editing ; methods ; Humans ; Zygote ; beta-Globins ; genetics

Objective Through systematically reviewing the reliability and validity of depression scales of Chinese version in adults in China to evaluate the psychometric properties of depression scales for different groups.Methods Eligible studies published before 6 May 2016 were retrieved from the following database:CNKI,Wanfang,PubMed and Embase.The HSROC model of the diagnostic test accuracy (DTA) for Meta-analysis was used to calculate the pooled sensitivity and specificity of the PHQ-9.Results A total of 44 papers evaluating the performance of depression scales were included.Results showed that the reliability and validity of the common depression scales were eligible,including the Beck depression inventory (BDI),the Hamilton depression scale (HAMD),the center epidemiological studies depression scale (CES-D),the patient health questionnaire (PHQ) and the Geriatric depression scale (GDS).The Cronbach's coefficient of most tools were larger than 0.8,while the test-retest reliability and split-half reliability were larger than 0.7,indicating good internal consistency and stability.The criterion validity,convergent validity,discrimination validity and screening validity were acceptable though different cut-off points were recommended by different studies.The pooled sensitivity of the 11 studies evaluating PHQ-9 was 0.88 (95％CI:0.85-0.91) while the pooled specificity was 0.89 (95％CI:0.82-0.94),which demonstrated the applicability of PHQ-9 in screening depression.Conclusion The reliability and validity of different depression scales of Chinese version are acceptable.The characteristics of different tools and study population should be taken into consideration when choosing a specific scale.

Studies on cell signaling pay more attention to spatial dynamics and how such diverse organization can relate to high order of cellular capabilities. To overview the specificity of cell signaling, we integrated human receptome data with proteome spatial expression profiles to systematically investigate the specificity of receptors and receptor-triggered transduction networks across 62 normal cell types and 14 cancer types. Six percent receptors showed cell-type-specific expression, and 4% signaling networks presented enriched cell-specific proteins induced by the receptors. We introduced a concept of "response context" to annotate the cell-type dependent signaling networks. We found that most cells respond similarly to the same stimulus, as the "response contexts" presented high functional similarity. Despite this, the subtle spatial diversity can be observed from the difference in network architectures. The architecture of the signaling networks in nerve cells displayed less completeness than that in glandular cells, which indicated cellular-context dependent signaling patterns are elaborately spatially organized. Likewise, in cancer cells most signaling networks were generally dysfunctional and less complete than that in normal cells. However, glioma emerged hyper-activated transduction mechanism in malignant state. Receptor ATP6AP2 and TNFRSF21 induced rennin-angiotensin and apoptosis signaling were found likely to explain the glioma-specific mechanism. This work represents an effort to decipher context-specific signaling network from spatial dimension. Our results indicated that although a majority of cells engage general signaling response with subtle differences, the spatial dynamics of cell signaling can not only deepen our insights into different signaling mechanisms, but also help understand cell signaling in disease.
Cell Line ; Databases, Protein ; Gene Expression Profiling ; Humans ; Metabolic Networks and Pathways ; Neoplasms ; metabolism ; pathology ; Proteome ; analysis ; Receptors, Cell Surface ; metabolism ; Receptors, Tumor Necrosis Factor ; metabolism ; Signal Transduction ; Vacuolar Proton-Translocating ATPases ; metabolism

Insulin resistance in insulin sensitive organ results in metabolic disorder such as hyperglycemia, hyperinsulinemia and hyper triglyceridemia which are common features of type 2 diabetes.Insulin resistance in liver cells mainly causes impaired glycogen synthesis, failed to suppress glucose production which is the major contribution to hyperglycemia.FGF-21 as a new metabolic regulator can control fasting blood glucose.The mechanism of FGF-21 effects on regulating plasma glucose has little to known.In order to establish an in vitro insulin resistant model of liver cells and evaluate the effects and mechanism of FGF-21 on glucose metabolism in the cell model, HepG2 cells were incubated with 10-7 mol/L insulin for 24 h to build insulin-resistant cell model.To evaluate the cells for insulin resistance, the cells were stimulated with fresh insulin for 24 h and the glucose uptake by these cells was carried out.The insulin-resistant cells were treated with different concentrations of FGF-21 for 24 h and insulin-treated cells were used as a control.The glucose uptake by the cells was detected by the method of glucose oxidizes/peroxides(GOD-POD);the synergy between insulin and FGF-21 was evaluated.The mRNA expression of GLUT1 in the insulin-resistant cells was detected by the real-time PCR.Glycogen synthesis of the cells was examined by the anthrone method.The results showed that HepG2 cells treated with 10-7 mol/L insulin for 24 h became resistant to insulin and the insulin resistance status was maintained for 48 h without change of cell morphology.FGF-21 could stimulate glucose consumption of the insulin-resistant model in a dose-dependent manner.The glucose consumption and glycogen synthesis of the insulin-resistant model were significantly improved by FGF-21 treatment.FGF-21 showed strong synergy with insulin in glucose uptake and glycogen synthesis of the model cells.While the cells became resistant to insulin, FGF-21 could increase the mRNA expression of GLUT1.Thus, It is concluded that FGF-21 stimulates glucose uptake in insulin resistant HepG2 cells through GLUT1 expression, stimulates glycogen synthesis and improves the glucose metabolism in the insulin resistant liver cell model.