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A knowledge graph can effectively showcase the essential characteristics of data and is increasingly emerging as a significant means of integrating information in the field of artificial intelligence. Coronary artery plaque represents a significant etiology of cardiovascular events, posing a diagnostic challenge for clinicians who are confronted with a multitude of nonspecific symptoms. To visualize the hierarchical relationship network graph of the molecular mechanisms underlying plaque properties and symptom phenotypes, patient symptomatology was extracted from electronic health record data from real-world clinical settings. Phenotypic networks were constructed utilizing clinical data and protein‒protein interaction networks. Machine learning techniques, including convolutional neural networks, Dijkstra's algorithm, and gene ontology semantic similarity, were employed to quantify clinical and biological features within the network. The resulting features were then utilized to train a K-nearest neighbor model, yielding 23 symptoms, 41 association rules, and 61 hub genes across the three types of plaques studied, achieving an area under the curve of 92.5%. Weighted correlation network analysis and pathway enrichment were subsequently utilized to identify lipid status-related genes and inflammation-associated pathways that could help explain the differences in plaque properties. To confirm the validity of the network graph model, we conducted coexpression analysis of the hub genes to evaluate their potential diagnostic value. Additionally, we investigated immune cell infiltration, examined the correlations between hub genes and immune cells, and validated the reliability of the identified biological pathways. By integrating clinical data and molecular network information, this biomedical knowledge graph model effectively elucidated the potential molecular mechanisms that collude symptoms, diseases, and molecules. [ABSTRACT FROM AUTHOR]

As the most common form of epigenetic regulation by RNA, N6 methyladenosine (m6A) modification is closely involved in physiological processes, such as growth and development, stem cell renewal and differentiation, and DNA damage response. Meanwhile, its aberrant expression in cancer tissues promotes the development of malignant tumors, as well as plays important roles in proliferation, metastasis, drug resistance, immunity and prognosis. This close association between m6A and cancers has garnered substantial attention in recent years. An increasing number of small molecules have emerged as potential agents to target m6A regulators for cancer treatment. These molecules target the epigenetic level, enabling precise intervention in RNA modifications and efficiently disrupting the survival mechanisms of tumor cells, thus paving the way for novel approaches in cancer treatment. However, there is currently a lack of a comprehensive review on small molecules targeting m6A regulators for anti-tumor. Here, we have comprehensively summarized the classification and functions of m6A regulators, elucidating their interactions with the proliferation, metastasis, drug resistance, and immune responses in common cancers. Furthermore, we have provided a comprehensive overview on the development, mode of action, pharmacology and structure–activity relationships of small molecules targeting m6A regulators. Our aim is to offer insights for subsequent drug design and optimization, while also providing an outlook on future prospects for small molecule development targeting m6A. [ABSTRACT FROM AUTHOR]

Background: The identification of chemical–target interaction is key to pharmaceutical research and development, but the unclear materials basis and complex mechanisms of traditional medicine (TM) make it difficult, especially for low-content chemicals which are hard to test in experiments. In this research, we aim to apply the node2vec algorithm in the context of drug-herb interactions for expanding potential targets and taking advantage of molecular docking and experiments for verification. Methods: Regarding the widely reported risks between cardiovascular drugs and herbs, Salvia miltiorrhiza (Danshen, DS) and Ligusticum chuanxiong (Chuanxiong, CX), which are widely used in the treatment of cardiovascular disease (CVD), and approved drugs for CVD form the new dataset as an example. Three data groups DS-drug, CX-drug, and DS-CX-drug were applied to serve as the context of drug-herb interactions for link prediction. Three types of datasets were set under three groups, containing information from chemical-target connection (CTC), chemical-chemical connection (CCC) and protein–protein interaction (PPI) in increasing steps. Five algorithms, including node2vec, were applied as comparisons. Molecular docking and pharmacological experiments were used for verification. Results: Node2vec represented the best performance with average AUROC and AP values of 0.91 on the datasets "CTC, CCC, PPI". Targets of 32 herbal chemicals were identified within 43 predicted edges of herbal chemicals and drug targets. Among them, 11 potential chemical-drug target interactions showed better binding affinity by molecular docking. Further pharmacological experiments indicated caffeic acid increased the thermal stability of the protein GGT1 and ligustilide and low-content chemical neocryptotanshinone induced mRNA change of FGF2 and MTNR1A, respectively. Conclusions: The analytical framework and methods established in the study provide an important reference for researchers in discovering herb–drug interactions, alerting clinical risks, and understanding complex mechanisms of TM. [ABSTRACT FROM AUTHOR]

Background: PSMA PET/CT has shown excellent results in imaging of prostate cancer. However, some nonprostatic malignancies can also demonstrate 18 F-PSMA uptake, including primary lung cancer. 18 F-FDG PET/CT is widely employed in initial staging, response to therapy and follow-up assessment for lung cancer. Here we present an interesting case report on the different patterns of PSMA and FDG uptake between primary lung cancer and metastatic intrathoracic lymph node metastases in a patient with concurrent metastatic prostate cancer. Case presentation: A 70-year-old male underwent 18 F-FDG PET/CT and 18 F-PSMA-1007 PET/CT imaging due to suspicion primary lung cancer and prostate cancer. The patient eventually was diagnosed with non-small cell lung cancer (NSCLC) with mediastinal lymph node metastases and prostate cancer with left iliac lymph node and multiple bone metastases. Interestingly, our imaging revealed different patterns of tumor uptake detected on 18 F-FDG and 18 F-PSMA-1007 PET/CT in primary lung cancer and lymph node metastases. The primary lung lesion showed intense FDG uptake, and mild uptake with 18 F-PSMA-1007. Whereas the mediastinal lymph node metastases showed both intense FDG and PSMA uptake. The prostate lesion, left iliac lymph node, and multiple bone lesions showed significant PSMA uptake and negative FDG uptake. Conclusion: In this case, there was a homogeneity of 18 F-FDG intense uptake between LC and metastatic lymph nodes, but a heterogeneity in 18 F-PSMA-1007 uptake. It illustrated that these molecular probes reflect the diversity of tumor microenvironments, which may help us understand the differences of the tumor response to treatment. [ABSTRACT FROM AUTHOR]

Background: Altered glucose metabolism endows tumor cells with metabolic flexibility for biosynthesis requirements. Phosphoenolpyruvate carboxykinase 1 (PCK1), a key enzyme in the gluconeogenesis pathway, is downregulated in hepatocellular carcinoma (HCC) and predicts poor prognosis. Overexpression of PCK1 has been shown to suppress liver tumor growth, but the underlying mechanism remains unclear. Methods: mRNA and protein expression patterns of PCK1, AMPK, pAMPK, and the CDK/Rb/E2F pathway were determined using qRT-PCR and western blotting. Cell proliferation ability and cell cycle were assessed by MTS assay and flow cytometric analysis. The effect of PCK1 on tumor growth was examined in xenograft implantation models. Results: Both gain and loss-of-function experiments demonstrated that PCK1 deficiency promotes hepatoma cell proliferation through inactivation of AMPK, suppression of p27Kip1 expression, and stimulation of the CDK/Rb/E2F pathway, thereby accelerating cell cycle transition from the G1 to S phase under glucose-starved conditions. Overexpression of PCK1 reduced cellular ATP levels and enhanced AMPK phosphorylation and p27Kip1 expression but decreased Rb phosphorylation, leading to cell cycle arrest at G1. AMPK knockdown significantly reversed G1-phase arrest and growth inhibition of PCK1-expressing SK-Hep1 cells. In addition, the AMPK activator metformin remarkably suppressed the growth of PCK1-knockout PLC/PRF/5 cells and inhibited tumor growth in an orthotropic HCC mouse model. Conclusion: This study revealed that PCK1 negatively regulates cell cycle progression and hepatoma cell proliferation via the AMPK/p27Kip1 axis and supports a potential therapeutic and protective effect of metformin on HCC. [ABSTRACT FROM AUTHOR]

As the most common form of epigenetic regulation by RNA, N 6 methyladenosine (m 6 A) modification is closely involved in physiological processes, such as growth and development, stem cell renewal and differentiation, and DNA damage response. Meanwhile, its aberrant expression in cancer tissues promotes the development of malignant tumors, as well as plays important roles in proliferation, metastasis, drug resistance, immunity and prognosis. This close association between m 6 A and cancers has garnered substantial attention in recent years. An increasing number of small molecules have emerged as potential agents to target m 6 A regulators for cancer treatment. These molecules target the epigenetic level, enabling precise intervention in RNA modifications and efficiently disrupting the survival mechanisms of tumor cells, thus paving the way for novel approaches in cancer treatment. However, there is currently a lack of a comprehensive review on small molecules targeting m 6 A regulators for anti-tumor. Here, we have comprehensively summarized the classification and functions of m 6 A regulators, elucidating their interactions with the proliferation, metastasis, drug resistance, and immune responses in common cancers. Furthermore, we have provided a comprehensive overview on the development, mode of action, pharmacology and structure-activity relationships of small molecules targeting m 6 A regulators. Our aim is to offer insights for subsequent drug design and optimization, while also providing an outlook on future prospects for small molecule development targeting m 6 A., (© 2024. The Author(s).)

Background: Quantitative real-time reverse transcription PCR (qRT-PCR) requires a stable internal control to avoid misinterpretation of data or errors for gene expression normalization. However, there are still no validated reference genes for stable internal control in Poria cocos (Schw.) Wolf (Fuling). This study aims to validate the reference genes of P. cocos., Methods: This study firstly collected the 14 candidate reference genes by BLASTP from the genome of P. cocos for qRT-PCR analysis to determine the expression levels of 14 housekeeping genes (GAPDH, MAPK, β-Act, RPB2, RPB1-1, RPB1-2, his3-1, his3-2, APT, SAMDC, RP, β-Tub, EIF, and CYP) under different temperatures and in response to different plant hormones (indole-3-acetic acid, abscisic acid, 6-benzylaminopurine, methyl jasmonate, and gibberellic acid), and the threshold cycle (Ct) values. The results were analyzed by four programs (i.e., geNorm, NormFinder, BestKeeper, and RefFinder) for evaluating the candidate reference genes., Results: SAMDC, his3-2, RP, RPB2, and his3-1 were recommended as reference genes for treating P. cocos with indole-3-acetic acid, abscisic acid, 6-benzylaminopurine, methyl jasmonate, and gibberellic acid, respectively. Under different temperatures RPB2 was the most stable reference gene. CYP was the most stable gene for all 90 samples by RefFinder., Conclusion: SAMDC, his3-2, RP, RPB2, and his3-1 were evaluated to be suitable reference genes for P. cocos following different treatments. RPB2 was the most stable reference gene under different temperatures and CYP was the most stable gene in the mycelia under all six evaluated conditions.

Background: Cystic echinococcosis, caused by infection with Echinococcus granulosus, is one of the most widespread zoonotic helminth diseases. Modulation of host responses is an important strategy used by helminth parasites to promote infection. To better understand the mechanisms adopted by E. granulosus to escape host immune responses, we investigated the effects of excretory-secretory products (ES) and adult worm antigen (AWA) derived from adult E. granulosus on murine bone marrow-derived dendritic cells (BMDC)., Results: Compared with lipopolysaccharide (LPS), AWA, but not ES, induced BMDC maturation or stimulated BMDC cytokine production and co-stimulatory molecule expression (CD40, CD80 and MHC class II). Furthermore, ES-treated BMDCs pulsed with ovalbumin exhibited reduced co-stimulatory molecule expression in comparison with untreated BMDC, even in the presence of the strong Th1 inducer, CpG. Moreover, we detected the effects of ES-treated DC on T cell activation by an in vitro T cell priming assay. We observed that ES-treated BMDC co-cultured with DO11.10 transgenic CD4(+) T cells induced the generation of CD4(+)CD25(+)Foxp3(+) T cells. In addition, in contrast to AWA-treated BMDCs, which had markedly induced IFN-γ secretion and reduced of IL-4 levels in co-cultured T cells, ES-treated BMDCs did not modify their capacity to stimulate IFN-γ or IL-4 production by T cells., Conclusions: We conclude that ES of adult E. granulosus inhibited DC function, impaired the development of Th1 cells induced by CpG, and induced CD4(+)CD25(+)Foxp3(+) regulatory T cells in an IL-10-independent manner.

Background: Association between Cyclin D1 (CCND1) polymorphism and cervical cancer risk are conflicting with published articles. We performed a meta-analysis to investigate the association between CCND1 G870A polymorphism and cervical cancer risk., Methods: PubMed, Embase and CNKI data were researched to conduct a meta-analysis on the associations between CCND1 G870A polymorphism and cervical cancer risk. Ten published case-control studies including 2,864 patients with cervical cancer and 3,898 controls were collected in this meta-analysis. Odds ratio (OR) with 95% confidence interval (CI) were applied to assess the relationship; meta-regression, sensitivity analysis and cumulative analysis were also conducted to guarantee the strength of results., Results: Overall, no significant association between CCND1 G870A polymorphism and cervical cancer risk were found in allele contrast (A vs. G: OR=1.02, 95% CI=0.88-1.19, P=0.76 I2=74.5%), codominant model (GA vs. GG: OR=0.98, 95% CI=0.77-1.26, P=0.90 I2=69.1%; AA vs GG: OR=1.03, 95% CI=0.75-1.41, P=0.85 I2=75.9%), dominant model (GA + AA vs. GG: OR=1.00, 95% CI=0.78-1.28, P=0.99 I2=72.3%) and recessive model (AA vs GG + GA: OR=1.06, 95% CI=0.85-1.23, P=0.62, I2=70.1%). Similarly, in the stratified analysis by ethnicity, study design and genotyping type, no significant association detected in all genetic models either., Conclusions: Our meta-analysis indicated that CCND1 G870A might be not the crucial risk factor for the development of cervical cancer., Virtual Slides: The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/13000_2014_168.