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The bulb of Fritillaria species called “Bei Mu” is a well-known traditional Chinese medicine. We have reported some potential off-target effects of “Bei Mu” due to peimine’s blockade of hERG (human Ether-a-go-go-Related Gene) channels. This research investigated the modulatory effects of three major alkaloid analogs of “Bei Mu” and their cooperative effects on hERG channels using manual whole-cell patch-clamp techniques. Results showed that peiminine and sipeimine blocked hERG currents with IC50s of 36.8 ± 2.5 μM and 47.6 ± 9.8 μM, which were close to that of peimine (26.1 ± 3.5 μM). Peiminine-induced blockade increased with increasing depolarizing strengths, durations, and frequencies, which suggested a preferential binding to open or inactivated states. The reduced blockade by the less inactivating S631A mutation supported peiminine‘s inactivation preference. Molecular docking and dynamics simulations confirmed the hERG-blocking activities of the three alkaloids and provided further insight into potential mechanisms. We also discovered antagonistic effects of the three alkaloids at nearly all concentrations tested, which might help reduce potential cardiotoxicities. To our knowledge, this is the first study to investigate combination effects of chemicals from one herb on hERG channels. In conclusion, peiminine and sipeimine can block hERG channels in a way similar to peimine, but antagonistic effects exist among them.

Transcription factors (TFs) can affect gene expression by binding to certain specific DNA sequences. This binding process of TFs may be modulated by DNA methylation. A subset of TFs that serve as methylation readers preferentially binds to certain methylated DNA and is defined as TFPM. The identification of TFPMs enhances our understanding of DNA methylation’s role in gene regulation. However, their experimental identification is resource-demanding. In this study, we propose a novel two-step computational approach to classify TFs and TFPMs. First, we employed a fine-tuned ProtBERT model to differentiate between the classes of TFs and non-TFs. Second, we combined the Reduced Amino Acid Category (RAAC) with K-mer and SVM to predict the potential of TFs to bind to methylated DNA. Comparative experiments demonstrate that our proposed methods outperform all existing approaches and emphasize the efficiency of our computational framework in classifying TFs and TFPMs. Cross-species validation on an independent mouse dataset further demonstrates the generalizability of our proposed framework In addition, we conducted predictions on all human transcription factors and found that most of the top 20 proteins belong to the Krueppel C2H2-type Zinc-finger family. So far, some studies have demonstrated a partial correlation between this family and DNA methylation and confirmed the preference of some of its members, thereby showing the robustness of our approach.

In the modern world, wearable smart devices are continuously used to monitor people’s health. This study aims to develop an automatic mental stress detection system for researchers based on Electrocardiogram (ECG) signals from smart T-shirts using machine learning classifiers. We used 20 subjects, including 10 from mental stress (after twelve hours of continuous work in the laboratory) and 10 from normal (after completing the sleep or without any work). We also applied three scoring techniques: Chalder Fatigue Scale (CFS), Specific Fatigue Scale (SFS), Depression, Anxiety, and Stress Scale (DASS), to confirm the mental stress. The total duration of ECG recording was 1800 min, including 1200 min during mental stress and 600 min during normal. We calculated two types of features, such as demographic and extracted by ECG signal. In addition, we used Decision Tree (DT), Naive Bayes (NB), Random Forest (RF), and Logistic Regression (LR) to classify the intra-subject (mental stress and normal) and inter-subject classification. The DT leave-one-out model has better performance in terms of recall (93.30%), specificity (96.70%), precision (94.40%), accuracy (93.30%), and F1 (93.50%) in the intra-subject classification. Additionally, The classification accuracy of the system in classifying inter-subjects is 94.10% when using a DT classifier. However, our findings suggest that the wearable smart T-shirt based on the DT classifier may be used in big data applications and health monitoring. Mental stress can lead to mitochondrial dysfunction, oxidative stress, blood pressure, cardiovascular disease, and various health problems. Therefore, real-time ECG signals help assess cardiovascular and related risk factors in the initial stage based on machine learning techniques.

Hepatitis B virus (HBV) infection is a major driver of hepatocellular carcinoma (HCC), yet the mechanisms by which HBV triggers HCC and how it interacts with the immune system remain largely undefined. In this study, 53 immune-related key genes involved in HBV-associated HCC progression were identified. By analyzing the mean C-index of 101 machine learning models, the optimal model—combining stepwise Cox regression (forward) with RSF—was developed to characterize the immune risk index. Patients in the high-risk group exhibited worse survival outcomes and increased infiltration of immunosuppressive cells. Integrating PPI analysis with machine learning, SPP1, GHR, and ESR1 emerged as promising druggable targets, with SPP1 notably overexpressed in tumors and linked to adverse outcomes. ScRNA-seq analysis revealed SPP1 was predominantly expressed in angio-TAMs, which may impair anti-tumor immunity by limiting T and NK cell infiltration. It also involved in tumor progression via angiogenesis and EMT pathways. Drug prediction and molecular docking identified small molecules such as myricetin and mefloquine that can target the aforementioned key immune genes, thereby modulating the immune landscape of HBV-HCC. Repurposing these established drugs represents a novel therapeutic avenue, offering both efficacy and expedited clinical translation for HBV-HCC.

Stomach adenocarcinoma (STAD) is a type of cancer which often at itsadvanced stage apon diagnosis and mortality in clinical practice. Several factors influencethe prognosis of STAD, including the expression and regulation of immune cells in the tumor microenvironment. We here investigated the biomarkers related to the diagnosis and prognosis of gastric cancer, hoping to provide insights for the diagnosis and treatment of gastric cancer in the future. STAD and normal patient RNA sequencing data sets were accessed from the cancer genome atlas (TCGA database). Differential genes were determined and obtained by using the R package DESeq2. The stromal, immune, and ESTIMATE scores are calculated by the ESTIMATE algorithm, followed by the modular genes screening using the R package WGCNA. Subsequently, the intersection between the modular gene and the differential gene was taken and the STRING database was used for PPI network module analysis. The R packages clusterProfiler, enrichplot, and ggplot2 were used for GO and KEGG enrichment analysis. Cox regression analysis was used to screen survival-related genes, and finally, the R package Venn Diagram was used to take the intersection and obtain 7 hub genes. The time-dependent ROC curve and Kaplan–Meier survival curve were used to find the SERPINE1 gene, which plays a critical role in prognosis. Finally, the expression pattern, clinical characteristics, and regulatory mechanism of SERPINE1 were analyzed in STAD. We revealed that the expression of SERPINE1 was significantly increased in the samples from STAD compared with normal samples. Cox regression, time-dependent ROC, and Kaplan–Meier survival analyses demonstrated that SERPINE1 was significantly related to the adverse prognosis of STAD patients. The expression of SERPINE1 increased with the progression of T, N, and M classification of the tumor. In addition, the results of immune infiltration analysis indicated that the immune cells’ expression were higher in high SERPINE1 expression group than that in low SERPINE1 expression group, including CD4 + T cells, B cells, CD8 + T cells, macrophages, neutrophils and other immune cells. SERPINE1 was closely related to immune cells in the STAD immune microenvironment and had a synergistic effect with the immune checkpoints PD1 and PD-L1. In conclusion, we proved that SERPINE1 is a promising prognostic and diagnostic biomarker for STAD and a potential target for immunotherapy.

2-Aminoethoxydiphenyl borate (2-APB), a boron-containing compound, is a multitarget compound with potential as a drug precursor and exerts various effects in systems of the human body. Ion channels are among the reported targets of 2-APB. The effects of 2-APB on voltage-gated potassium channels (KV) have been reported, but the types of KV channels that 2-APB inhibits and the inhibitory mechanism remain unknown. In this paper, we discovered that 2-APB acted as an inhibitor of three representative human KV1 channels. 2-APB significantly blocked A-type Kv channel KV1.4 in a concentration-dependent manner, with an IC50 of 67.3 μM, while it inhibited the delayed outward rectifier channels KV1.2 and KV1.3, with IC50s of 310.4 μM and 454.9 μM, respectively. Further studies on KV1.4 showed that V549, T551, A553, and L554 at the cavity region and N-terminal played significant roles in 2-APB’s effects on the KV1.4 channel. The results also indicated the importance of fast inactivation gating in determining the different effects of 2-APB on three channels. Interestingly, a current facilitation phenomenon by a short prepulse after 2-APB application was discovered for the first time. The docked modeling revealed that 2-APB could form hydrogen bonds with different sites in the cavity region of three channels, and the inhibition constants showed a similar trend to the experimental results. These findings revealed new molecular targets of 2-APB and demonstrated that 2-APB’s effects on KV1 channels might be part of the reason for the diverse bioactivities of 2-APB in the human body and in animal models of human disease.

In the Research Topic “Herbal Medical Products for Metabolic Diseases - New Integrated Pharmacological Approaches”, 11 articles were published, mainly focusing on plant metabolites, including TCM, for the treatment of metabolic diseases. Ariyantoprovided an overview of the efficacy of botanical drugs in the treatment of metabolic diseases through epigenetic modifications in his review paper to provide insight into the research and development strategies for botanical drugs as pharmacotherapies for metabolic diseases. [...]the integration of natural products and traditional medicine with modern therapeutic approaches for comprehensive treatment strategies has been addressed. [...]some areas are not covered, such as detailed research on specific molecular mechanisms and pathways involved in all plant metabolites, comparative studies between botanical drugs and modern pharmacological treatments, long-term clinical trials and safety profiles, standardized formulations, dosages and quality control of botanical drugs, etc., Overall, this Research Topic highlights the recent advances in botanical drugs for various interrelated metabolic diseases such as T2DM, obesity, cancer and NAFLD and emphasizes the importance of further research and integration with modern medicine. Conflict of interest The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

TWIK1 (K2P1.1/KCNK1) belongs to the potassium channels of the two-pore domain. Its current is very small and difficult to measure. In this work, we used a 100 mM NH4+ extracellular solution to increase TWIK1 current in its stable cell line expressed in HEK293. Then, the inhibition of magnolol on TWIK1 was observed via a whole-cell patch clamp experiment, and it was found that magnolol had a significant inhibitory effect on TWIK1 (IC50 = 6.21 ± 0.13 μM). By molecular docking and alanine scanning mutagenesis, the IC50 of TWIK1 mutants G229A, T225A, I140A, L223A, and S224A was 20.77 ± 3.20, 21.81 ± 7.93, 10.22 ± 1.07, 9.55 ± 1.62, and 7.43 ± 3.20 μM, respectively. Thus, we conclude that the inhibition of the TWIK1 channel by magnolol is related to G229 and T225 on the P2- pore helix.

Shaogan Fuzi Decoction (SGFD), one of the classical prescriptions of Chinese Medicine, has a long history in the treatment of rheumatoid arthritis (RA), but definitive studies on its efficacy and mechanism of action are lacking. This study aims to elucidate the pharmacodynamic role of SGFD against RA and the potential mechanisms based on a combination of network pharmacology and experimental verification. The RA model in rats was induced by intradermal injection of bovine type Ⅱ collagen and incomplete Freund’s adjuvant at the tail root. SGFD was administered once a day by oral gavage for 4 weeks. After SGFD administration, rat’s arthritis index (AI) score and paw swelling decreased to some extent, and synovial inflammation, vascular hyperplasia, and cartilage destruction of the ankle joint were improved. Simultaneously, thymus and spleen index and serum levels of C-reactive protein (CRP) were lowered. Network pharmacology revealed that quercetin, kaempferol, naringenin, formononetin isorhamnetin and licochalcone A were the potentialiy active components, and IL6, TP53, TNF, PTGS2, MAPK3 and IL-1β were potential key targets for SGFD in the treatment of RA. Ingredients-targets molecular docking showed that the components had the high binding activity to these target proteins. The mechanism of SGFD for RA involves various biological functions and is closely correlated with TNF signaling pathway, Osteoclast differentiation, T cell receptor signaling pathway, mitogen-activated protein kinase (MAPK) signaling pathway, NF-κB signaling pathway, toll-like receptor signaling pathway, and so on. Western blot and ELISA showed that the expression of toll-like receptor 4 (TLR4), nuclear factor kappa-B (NF-κB) p65, phosphorylated c-Jun N-terminal kinase (p-JNK), p-p38, phosphorylated extracellular regulated kinase (p-ERK) and TNF-α was significantly upregulated in the synovium of RA rats, and the levels of serum inflammatory factors were significantly increased. SGFD inhibits the activation of the TLR4/NF-κB/MAPK pathway and the expression/production of pro-inflammatory cytokines. In summary, SGFD could improve the symptoms and inflammatory response in collagen-induced arthritis (CIA) rat model. The mechanism might be related to the regulation of TLR4/MAPKs/NF-κB signaling pathway and the reduction of inflammatory factor release, which partially confirms the results predicted by network pharmacology.

With-no-lysine (WNK) kinases play vital roles in abiotic stress response, circadian rhythms, and regulation of flowering time in rice, Arabidopsis, and Glycine max. However, there are no previous reports of WNKs in the Bambusoideae, although genome sequences are available for diploid, tetraploid, and hexaploid bamboo species. In the present study, we identified 41 WNK genes in five bamboo species and analysed gene evolution, phylogenetic relationship, physical and chemical properties, cis -elements, and conserved motifs. We predicted the structure of PeWNK proteins of moso bamboo and determined the exposed, buried, structural and functional amino acids. Real-time qPCR analysis revealed that PeWNK5 , PeWNK7 , PeWNK8 , and PeWNK11 genes are involved in circadian rhythms. Analysis of gene expression of different organs at different developmental stages revealed that PeWNK genes are tissue-specific. Analysis of various abiotic stress transcriptome data (drought, salt, SA, and ABA) revealed significant gene expression levels in all PeWNKs except PeWNK11 . In particular, PeWNK8 and PeWNK9 were significantly down- and up-regulated, respectively, after abiotic stress treatment. A co-expression network of PeWNK genes also showed that PeWNK2 , PeWNK4 , PeWNK7 , and PeWNK8 were co-expressed with transcriptional regulators related to abiotic stress. In conclusion, our study identified the PeWNKs of moso bamboo involved in circadian rhythms and abiotic stress response. In addition, this study serves as a guide for future functional genomic studies of the WNK genes of the Bambusoideae.