Inflammatory diseases (IDs) are a general term of diseases characterized by chronic inflammation as the primary pathogenetic mechanism, which seriously affect the quality of patient′s life and cause significant social and medical burden. Current drugs for IDs include nonsteroidal anti-inflammatory drugs, corticosteroids, immunomodulators, biologics, and antioxidants, but these drugs may cause gastrointestinal side effects, induce or worsen infections, and cause non-response or intolerance. Given the outstanding performance of metal polyphenol network (MPN) in the fields of drug delivery, biomedical imaging, and catalytic therapy, its application in the diagnosis and treatment of IDs has attracted much attention and significant progress has been made. In this paper, we first provide an overview of the types of IDs and their generating mechanisms, then sort out and summarize the different forms of MPN in recent years, and finally discuss in detail the characteristics of MPN and their latest research progress in the diagnosis and treatment of IDs. This research may provide useful references for scientific research and clinical practice in the related fields.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Isoliquiritigenin (ISL) is an active chalcone compound isolated from licorice. It possesses anti-inflammatory and anti-oxidative activities. In our previous study, we uncovered a great potential of ISL in treatment of type 2 diabetes mellitus (T2DM). Therefore, this study aims to reveal the mechanism underlying the alleviatory effects of ISL on T2DM-induced glycolipid metabolism disorder. High-fat-high-sugar diet (HFD) combined with intraperitoneal injection of streptozotocin (STZ) were used to establish T2DM mice model. All animal experiments were carried out with approval of the Committee of Ethics at Beijing University of Chinese Medicine. HepG2 cells were used in in vitro experiments, and sodium palmitate (SP) was applied to establish insulin resistance (IR) model cells. The effects of ISL on body weight, fasting blood glucose levels, and pathological changes in the livers of mice were examined. Enzyme-linked immune sorbent assay (ELISA) and real-time quantitative PCR (RT-qPCR) were applied to detect the regulatory effects of ISL on key targets involved in glucolipid metabolism. Additionally, molecular docking and analytical dynamics simulation methods were used to analyze the interaction between ISL and key target protein. The results indicate that ISL significantly downregulates the transcriptional levels and inhibits the activities of key enzymes involved in gluconeogenesis, including pyruvate carboxylase (PC), phosphoenolpyruvate carboxykinase (PEPCK), and fructose-1, 6-bisphosphatase (FBP). It also downregulates the transcriptional and protein levels of hepatocyte nuclear factor 4α (HNF4α) and cAMP response element binding protein (CREB), the two transcriptional factors involved in gluconeogenesis. Thus, ISL inhibits hepatic gluconeogenesis in T2DM mice. In addition, ISL reduces total cholesterol (TC) and triglyceride (TG) levels in the livers of T2DM mice. Moreover, ISL downregulates the mRNA levels of lipogenesis genes and upregulates those of genes involved in fatty acid oxidation, lipid uptake, and lipid export. In conclusion, ISL suppresses hepatic gluconeogenesis, promotes lipolysis, and restrains lipogenesis in T2DM mice, thereby improving the abnormal glycolipid metabolism caused by T2DM.

Objective To compare the effects of 20 mg qd and 10 mg bidadministration of iprrazole enteric-coated tablets on the control of gastric acid in healthy subjects.Methods A randomized,single-center,parallel controlled trial was designed to include 8 healthy subjects.Randomly divided into 2 groups,20 mg qd administration group:20 mg enteric-coated tablets of iprrazole in the morning;10 mg bid administration group:10 mg enteric-coated tablets of iprrazole in the morning and 10 mg in the evening.The pH values in the stomach of the subjects before and 24 h after administration were monitored by pH meter.The plasma concentration of iprazole after administration was determined by HPLC-MS/MS.The main pharmacokinetic parameters were calculated by Phoenix WinNonlin(V8.0)software.Results The PK parameters of iprrazole enteric-coated tablets and reference preparations in fasting group were as follows:The Cmax of 20 mg qd group and 10 mg bid group were(595.75±131.15)and(283.50±96.98)ng·mL-1;AUC0-t were(5 531.94±784.35)and(4 686.67±898.23)h·ng·mL-1;AUC0-∞ were(6 003.19±538.59)and(7 361.48±1 816.77)h·ng·mL-1,respectively.The mean time percentage of gastric pH＞3 after 20 mg qd and 10 mg bid were 82.64％and 61.92％,and the median gastric pH within 24 h were 6.25±1.49 and 3.53±2.05,respectively.The mean gastric pH values within 24 h were 5.71±1.36 and 4.23±1.45,respectively.The correlation analysis of pharmacokinetic/pharmacodynamics showed that there was no significant correlation between the peak concentration of drug in plasma and the inhibitory effect of acid.Conclusion Compared with the 20 mg qd group and the 10 mg bid group,the acid inhibition effect is better,the administration times are less,and the safety of the two administration regimes is good.

The success of the Human Genome Project has significantly deepened our understanding of genomics and catalyzed a growing focus on proteomics, as researchers aim to decipher the complex relationship between genes and proteins. Given the central role of proteins in regulating physiological processes—including DNA replication, metabolic reactions, signal transduction, pH balance, and cellular structure—developing advanced protein sequencing technologies is critical. Proteins are fundamental to nearly all biological activities, making their detailed study essential for understanding cellular functions and disease mechanisms. The Edman degradation method, developed in the 1950s, was a breakthrough in sequencing short peptides. However, its limitations in read length (fewer than 50 amino acids) and slow cycle time fall short of modern demands. Mass spectrometry has since emerged as the gold standard in protein sequencing due to its high accuracy, throughput, and reproducibility. The method is enhanced by a robust sample preparation workflow and advances in mass spectrometry technology. Despite these strengths, mass spectrometry faces limitations in dynamic range, sensitivity, read length, and sequence coverage, hindering complete de novo protein sequencing. These technological gaps underscore the need for innovative methods to provide more detailed and accurate protein sequence data. In the past decade, new protein sequencing methods, including tunneling current, fluorescence fingerprinting, and real-time dynamic fluorescence, have shown significant developmental potential. However, these methods are not yet ready for widespread application, as each still faces technical hurdles. Meanwhile, advances in nanopore DNA sequencing have sparked interest in applying nanopore technology to protein sequencing, particularly owing to its speed, convenience, and cost-effectiveness. Unlike DNA sequencing, protein sequencing presents greater challenges due to proteins’ complex three-dimensional structures, heterogeneous electrical charges, difficulties in directional movement, and diverse amino acid compositions, further complicated by post-translational modifications. Researchers have made significant strides in addressing these challenges, such as using unfolding enzymes, high temperatures, high voltage, and deformers to unravel protein structures, and employing charged sequences and electroosmotic flow to control peptide translocation. The latest strategies for nanopore protein sequencing can be broadly categorized into three approaches: strand sequencing, enzyme-assisted nanopore sequencing, and nanopore fingerprinting. In strand sequencing, dragging a protein-oligonucleotide conjugate through a nanopore with the aid of protein motors generates stepped current signals produced by the peptide strand. In enzyme-assisted nanopore sequencing, 20 proteinogenic amino acids and various post-translational modifications have been distinguished using nanopores, and sequencing of short peptides has also been demonstrated. In nanopore fingerprinting, polypeptide fragments resulting from protease digestion of a protein can be identified through nanopore sensing. Despite these advances, further improvements in protein engineering, data processing, identification accuracy, and read length are needed to make these strategies practically useful. This review provides an overview of the current major approaches to nanopore protein sequencing, emphasizing the strategies, recent advances, breakthroughs and challenges in nanopore protein sequencing. As nanopore technology continues to evolve, it is expected to offer more efficient and accurate sequencing solutions in proteomics, potentially leading to new technological breakthroughs in biochemistry and biomedicine.

The dynamin superfamily protein (DSP) encompasses a group of large GTPases that are involved in various membrane remodeling processes within the cell. These proteins are characterized by their ability to hydrolyze GTP, which provides the energy necessary for their function in membrane fission, fusion, and tubulation activities. Dynamin superfamily proteins play critical roles in cellular processes such as endocytosis, organelle division, and vesicle trafficking. It is typically classified into classical dynamins and dynamin-related proteins (Drp), which have distinct roles and structural features. Understanding these proteins is crucial for comprehending their functions in cellular processes, particularly in membrane dynamics and organelle maintenance. Classical dynamins are primarily involved in clathrin-mediated endocytosis (CME), a process crucial for the internalization of receptors and other membrane components from the cell surface into the cell. These proteins are best known for their role in pinching off vesicles from the plasma membrane. Structually, classical dynamins are composed of a GTPase domain, a middle domain, a pleckstrin homology (PH) domain that binds phosphoinositides, a GTPase effector domain (GED), and a proline-rich domain (PRD) that interacts with SH3 domain-containing proteins. Functionally, the classical dynamins wrap around the neck of budding vesicles, using GTP hydrolysis to constrict and eventually acting as a “membrane scissor” to cut the vesicle from the membrane. In mammals, there are three major isoforms: dynamin 1 (predominantly expressed in neurons), dynamin 2 (ubiquitously expressed), and dynamin 3 (expressed in testes, lungs, and neurons). Recent studies have also revealed some non-classical functions of classical dynamins, such as regulating the initiation and stabilization of clathrin-coated pits (CCPs) at the early stages of CME, influencing the formation of the actin cytoskeleton and cell division. Drps share structural similarities with classical dynamins but are involved in a variety of different cellular processes, primarily related to the maintenance and remodeling of organelles, and can be mainly categorized into “mediating membrane fission”, “mediating membrane fusion” and “non-membrane-dependent functions”. Proteins like Drp1 are crucial for mitochondrial division, while others like Fis1, Mfn1, and Mfn2 are involved in mitochondrial and peroxisomal fission and fusion processes, which are essential for the maintenance of mitochondrial and peroxisomal integrity and affect energy production and apoptosis. Proteins like the Mx protein family exhibit antiviral properties by interfering with viral replication or assembly, which is critical for the innate immune response to viral infections. Some other proteins are involved in the formation of tubular structures from membranes, which is crucial for the maintenance of organelle morphology, particularly in the endoplasmic reticulum and Golgi apparatus. Studies on dynamin superfamily proteins have been extensive and have significantly advanced our understanding of cellular biology, disease mechanisms, and therapeutic potential. These studies encompass a broad range of disciplines, including molecular biology, biochemistry, cell biology, genetics, and pharmacology. By comprehensively summarizing and organizing the structural features and functions of various members of the dynamin superfamily protein, this review not only deepens the understanding of its molecular mechanisms, but also provides valuable insights for clinical drug research related to human diseases, potentially driving further advancements in the field.