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Background Patients with acute pancreatitis (AP) exhibit specific phenotypes of gut microbiota associated with severity. Gut microbiota and host interact primarily through metabolites; regrettably, little is known about their roles in AP biological networks. This study examines how enterobacterial metabolites modulate the innate immune system in AP aggravation. Methods In AP, alterations in gut microbiota were detected via microbiomics, and the Lactobacillus metabolites of tryptophan were identified by liquid chromatography-tandem mass spectrometry (LC–MS/MS). By culturing Lactobacillus with tryptophan, differential metabolites were detected by LC–MS/MS. Lipopolysaccharide (LPS)-stimulated RAW264.7 cells and mice with cerulein plus LPS-induced AP were used to evaluate the biological effect of norharman on M1 macrophages activation in AP development. Further, RNA sequencing and lipid metabolomics were used for screening the therapeutic targets and pathways of norharman. Confocal microscopy assay was used to detect the structure of lipid rafts. Molecular docking was applied to predict the interaction between norharman and HDACs. Luciferase reporter assays and chromatin immunoprecipitation (ChIP) were used to explore the direct mechanism of norharman promoting Rftn1 expression. In addition, myeloid-specific Rftn1 knockout mice were used to verify the role of Rftn1 and the reversed effect of norharman. Results AP induced the dysfunction of gut microbiota and their metabolites, resulting in the suppression of Lactobacillus -mediated tryptophan metabolism pathway. The Lactobacillus metabolites of tryptophan, norharman, inhibited the release of inflammatory factor in vitro and in vivo, as a result of its optimal inhibitory action on M1 macrophages. Moreover, norharman blocked multiple inflammatory responses in AP exacerbation due to its ability to maintain the integrity of lipid rafts and restore the dysfunction of lipid metabolism. The mechanism of norharman’s activity involved inhibiting the enzyme activity of histone deacetylase (HDACs) to increase histone H3 at lysine 9/14 (H3K9/14) acetylation, which increased the transcription level of Rftn1 (Raftlin 1) to inhibit M1 macrophages’ activation. Conclusions The enterobacterial metabolite norharman can decrease HDACs activity to increase H3K9/14 acetylation of Rftn1 , which inhibits M1 macrophage activation and restores the balance of lipid metabolism to relieve multiple inflammatory responses. Therefore, norharman may be a promising prodrug to block AP aggravation. Graphical Abstract

Objective There are three categories of drugs that treat human epidermal growth factor receptor type 2 (HER-2) positive breast cancer: monoclonal antibodies (mAbs), antibody-drug conjugates (ADCs), and tyrosine kinase inhibitors (TKIs). The purpose of this study is to analyze and compare the adverse reactions of three classes of anti-HER-2 drugs to various body systems in patients based on the FDA Adverse Event Reporting System (FAERS). Methods All data reports were extracted from the FAERS between 2004 and 2024. Data mining of adverse events associated with anti-HER-2 drugs was carried out using disproportionality analysis. A multivariate logistic regression analysis was conducted to explore the risk factors associated with AEs leading to hospitalization. Results A total of 47,799 patients were screened for the three classes of drugs, among which ADC drugs caused the largest proportion of deaths. MAb has the strongest ADR signals associated with “cardiac disorders”. Moreover, trastuzumab was associated with a greater risk of cardiotoxicity. Logistic regression analysis revealed that the treatment with mAbs should be wary of serious adverse reactions in “infections and infestations” and “metabolism and nutrition disorders”. Moreover, “endocrine disorders” were the factor associated with the highest risk of prolonged hospitalization due to trastuzumab deruxtecan (T-DXd). The safety of tucatinib among TKI drugs is greater than that of other drugs. Conclusion In general, from the perspective of the effects of the three classes of drugs on the various body systems of patients, we should focus on mAb-associated “cardiac disorders”, ADC-associated “hepatobiliary disorders”, “respiratory, thoracic and mediastinal disorders”, and TKI-associated “gastrointestinal disorders.

Currently, both acute kidney injury (AKI) and chronic kidney disease (CKD) are considered to be the leading public health problems with gradually increasing incidence rates around the world. Rhein is a monomeric component of anthraquinone isolated from rhubarb, a traditional Chinese medicine. It has anti-inflammation, anti-oxidation, anti-apoptosis, anti-bacterial and other pharmacological activities, as well as a renal protective effects. Rhein exerts its nephroprotective effects mainly through decreasing hypoglycemic and hypolipidemic, playing anti-inflammatory, antioxidant and anti-fibrotic effects and regulating drug-transporters. However, the latest studies show that rhein also has potential kidney toxicity in case of large dosages and long use times. The present review highlights rhein’s molecular targets and its different effects on the kidney based on the available literature and clarifies that rhein regulates the function of the kidney in a positive and negative way. It will be helpful to conduct further studies on how to make full use of rhein in the kidney and to avoid kidney damage so as to make it an effective kidney protection drug.

With the advancement of computer technology, machine learning-based artificial intelligence technology has been increasingly integrated and applied in the fields of medicine, biology, and pharmacy, thereby facilitating their development. Transporters have important roles in influencing drug resistance, drug–drug interactions, and tissue-specific drug targeting. The investigation of drug transporter substrates and inhibitors is a crucial aspect of pharmaceutical development. However, long duration and high expenses pose significant challenges in the investigation of drug transporters. In this review, we discuss the present situation and challenges encountered in applying machine learning techniques to investigate drug transporters. The transporters involved include ABC transporters (P-gp, BCRP, MRPs, and BSEP) and SLC transporters (OAT, OATP, OCT, MATE1,2-K, and NET). The aim is to offer a point of reference for and assistance with the progression of drug transporter research, as well as the advancement of more efficient computer technology. Machine learning methods are valuable and attractive for helping with the study of drug transporter substrates and inhibitors, but continuous efforts are still needed to develop more accurate and reliable predictive models and to apply them in the screening process of drug development to improve efficiency and success rates.

Breast cancer is the most common cancer affecting women worldwide. Many genes are involved in the development of breast cancer, including the Kruppel Like Factor 12 ( KLF12 ) gene, which has been implicated in the development and progression of several cancers. However, the comprehensive regulatory network of KLF12 in breast cancer has not yet been fully elucidated. This study examined the role of KLF12 in breast cancer and its associated molecular mechanisms. KLF12 was found to promote the proliferation of breast cancer and inhibit apoptosis in response to genotoxic stress. Subsequent mechanistic studies showed that KLF12 inhibits the activity of the p53/p21 axis, specifically by interacting with p53 and affecting its protein stability via influencing the acetylation and ubiquitination of lysine370/372/373 at the C-terminus of p53. Furthermore, KLF12 disrupted the interaction between p53 and p300, thereby reducing the acetylation of p53 and stability. Meanwhile, KLF12 also inhibited the transcription of p21 independently of p53. These results suggest that KLF12 might have an important role in breast cancer and serve as a potential prognostic marker and therapeutic target.

The kidney is critical in the human body’s excretion of drugs and their metabolites. Renal transporters participate in actively secreting substances from the proximal tubular cells and reabsorbing them in the distal renal tubules. They can affect the clearance rates (CLr) of drugs and their metabolites, eventually influence the clinical efficiency and side effects of drugs, and may produce drug–drug interactions (DDIs) of clinical significance. Renal transporters and renal transporter-mediated DDIs have also been studied by many researchers. In this article, the main types of in vitro research models used for the study of renal transporter-mediated DDIs are membrane-based assays, cell-based assays, and the renal slice uptake model. In vivo research models include animal experiments, gene knockout animal models, positron emission tomography (PET) technology, and studies on human beings. In addition, in vitro–in vivo extrapolation (IVIVE), ex vivo kidney perfusion (EVKP) models, and, more recently, biomarker methods and in silico models are included. This article reviews the traditional research methods of renal transporter-mediated DDIs, updates the recent progress in the development of the methods, and then classifies and summarizes the advantages and disadvantages of each method. Through the sorting work conducted in this paper, it will be convenient for researchers at different learning stages to choose the best method for their own research based on their own subject’s situation when they are going to study DDIs mediated by renal transporters.

Hexaconazole, a triazole-class fungicide, demonstrates broad-spectrum protective and therapeutic activity against fungal pathogens, particularly those from Basidiomycota and Ascomycota, such as brown spot and powdery mildew. Despite its efficacy in controlling Actinidia brown spot disease in kiwifruit, excessive hexaconazole residues pose significant health risks due to its high toxicity. To address this challenge, a rapid analytical method for detecting hexaconazole residues in kiwifruit was developed using surface-enhanced Raman spectroscopy (SERS). The methodology employed silver colloid (C-AgNPs) as the active substrate and 1 mol/L NaCl as the aggregation agent, optimized through systematic testing, resulting in an optimal volume ratio of 400:225 between C-AgNPs and hexaconazole solution and a sequential mixing order of C-AgNPs + NaCl + Hexaconazole, followed by a 20 min incubation period. The characteristic Raman peak at 1584 cm−1 was identified as the spectral signature for hexaconazole quantification. Analytical validation revealed a linear detection range of 0.25–2.25 mg/L (R2 = 0.9870), precision with a relative standard deviation (RSD) of 1.7%, and an average recovery rate of 88.40–105.50%, confirming the method’s robustness. This approach enables rapid, non-destructive analysis with minimal sample pretreatment, offering high sensitivity and stability. This method demonstrates great potential for detecting hexaconazole residues in agricultural products.

Increasing crop production is necessary to feed the world’s expanding population, and crop breeders often utilize genetic variations to improve crop yield and quality. However, the narrow diversity of the wheat D genome seriously restricts its selective breeding. A practical solution is to exploit the genomic variations of Aegilops tauschii via introgression. Here, we established a rapid introgression platform for transferring the overall genetic variations of A. tauschii to elite wheats, thereby enriching the wheat germplasm pool. To accelerate the process, we assembled four new reference genomes, resequenced 278 accessions of A. tauschii and constructed the variation landscape of this wheat progenitor species. Genome comparisons highlighted diverse functional genes or novel haplotypes with potential applications in wheat improvement. We constructed the core germplasm of A. tauschii , including 85 accessions covering more than 99% of the species’ overall genetic variations. This was crossed with elite wheat cultivars to generate an A. tauschii -wheat synthetic octoploid wheat (A-WSOW) pool. Laboratory and field analysis with two examples of the introgression lines confirmed its great potential for wheat breeding. Our high-quality reference genomes, genomic variation landscape of A. tauschii and the A-WSOW pool provide valuable resources to facilitate gene discovery and breeding in wheat. An introgression platform for transferring genetic variations of Aegilops tauschii to hexaploid wheat is established based on synthetic octoploid wheat. Combined with newly generated genome resources of A. tauschii , it represents a powerful tool for wheat gene discovery and breeding.

Breast cancer is the most commonly diagnosed cancer, and its global impact is increasing. Its onset and progression are influenced by multiple cues, one of which is the disruption of the internal circadian clock. Cryptochrome 2 (Cry2) genetic dysregulation may lead to the development of some diseases and even tumors. In addition, post-translational modifications can alter the Cry2 function. Here, we aimed to elucidate the post-translational regulations of Cry2 and its role in breast cancer pathogenesis. We identified p300-drived acetylation as a novel Cry2 post-translational modification, which histone deacetylase 6 (HDAC6) could reverse. Furthermore, we found that Cry2 inhibits breast cancer proliferation, but its acetylation impairs this effect. Finally, bioinformatics analysis revealed that genes repressed by Cry2 in breast cancer were mainly enriched in the NF-κB pathway, and acetylation reversed this repression. Collectively, these results indicate a novel Cry2 regulation mechanism and provide a rationale for its role in breast tumorigenesis.

The development of liver diseases adversely affects global health, emerging as a prominent cause of mortality globally and imposing a significant economic strain on society. Gallic acid (GA) is the natural polyphenol that is present in a variety of plants, fruits, tea, traditional Chinese medicine and so on. This review was aimed to analyze the available literature on GA with a focus on its mechanism of action. Several literature databases were searched, including PubMed, Web of Science, Google Scholar, and Scopus to find relevant research on GA and liver disease over the last decade. Our finding indicate that GA can effectively reduce non-alcoholic liver injury, alcoholic liver disease, hepatic fibrosis, drug-induced liver injury, and liver cancer. GA displays remarkable antioxidant effects by activating nuclear factor erythroid 2-related factor (Nrf2) and the expression of antioxidant genes. Moreover, the anti-inflammatory mechanism is mainly related to the nuclear factor kappa B (NF-κB) signaling pathway and down-regulating some inflammation-related factors such as interleukin 1 (IL-1), interleukin 6 (IL-6), transforming growth factor-beta (TGF-β) and tumor necrosis factor alpha (TNF-α). GA mitigates non-alcoholic fatty liver disease (NAFLD) and alcoholic liver disease (ALD) through the reduction of lipid accumulation, achieved by modulating the AMP-activated protein kinase (AMPK) signaling pathway. In the context of liver cancer, GA additionally modulates the wnt/β-catenin and JAK/STAT3 signaling pathways, as well as their downstream molecular components. In this review, different studies indicate that GA have an excellent protective effect against various liver diseases associated with various signaling pathways.