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.

This study aims to investigate the effect of salvianolic acid B (Sal B), the active ingredient of Salvia miltiorrhiza, on H9C2 cardiomyocytes injured by oxygen and glucose deprivation/reperfusion (OGD/R) through regulating mitochondrial fission and fusion. The process of myocardial ischemia-reperfusion injury was simulated by establishing OGD/R model. The cell proliferation and cytotoxicity detection kit (cell counting kit-8, CCK-8) was used to detect cell viability; the kit method was used to detect intracellular reactive oxygen species (ROS), total glutathione (t-GSH), nitric oxide (NO) content, protein expression levels of mitochondrial fission and fusion, apoptosis-related detection by Western blot. Mitochondrial permeability transition pore (MPTP) detection kit and Hoechst 33342 fluorescence was used to observe the opening level of MPTP, and molecular docking technology was used to determine the molecular target of Sal B. The results showed that relative to control group, OGD/R injury reduced cell viability, increased the content of ROS, decreased the content of t-GSH and NO. Furthermore, OGD/R injury increased the protein expression levels of dynamin-related protein 1 (Drp1), mitofusions 2 (Mfn2), Bcl-2 associated X protein (Bax) and cysteinyl aspartate specific proteinase 3 (caspase 3), and decreased the protein expression levels of Mfn1, increased MPTP opening level. Compared with the OGD/R group, it was observed that Sal B had a protective effect at concentrations ranging from 6.25 to 100 μmol·L^-1. Sal B decreased the content of ROS, increased the content of t-GSH and NO, and Western blot showed that Sal B decreased the protein expression levels of Drp1, Mfn2, Bax and caspase 3, increased the protein expression level of Mfn1, and decreased the opening level of MPTP. In summary, Sal B may inhibit the opening of MPTP, reduce cell apoptosis and reduce OGD/R damage in H9C2 cells by regulating the balance of oxidation and anti-oxidation, mitochondrial fission and fusion, thereby providing a scientific basis for the use of Sal B in the treatment of myocardial ischemia reperfusion injury.

Chronic pelvic inflammatory disease(CPID)is a common chronic inflammatory disease in women,and has a long course and is easy to relapse.Danggui Shaoyao Powder is from Jin Gui Yao Lve(Synopsis of the Golden Chamber),which was a commonly-used formula for the treatment of women's abdominal pain in ancient medical records.It is now often used in the treatment of CPID and has achieved satisfactory therapeutic effect.The article summarizes and analyzes the achievements in the clinical research and experimental study of Danggui Shaoyao Powder in the treatment of CPID over the past 10 years,and invesigates the clinical efficacy of Danggui Shaoyao Powder in the treatment of CPID and its therapeutic mechanism.In the field of clinical studies,Danggui Shaoyao Powder for the treatment of CPID was used by modification,or alone,or in combination with antibiotics and Chinese medicine external treatment,and its combined use was effective on significantly improving the indicators of inflammatory response and immune function,alleviating the clinical signs and symptoms such as pain,and did not increase the incidence of adverse reactions compared with the application of western medicines alone.In the field of experimental studies,Danggui Shaoyao Powder played the therapeutic role in CPID by decreasing the adhesion of endothelial cells,regulating the degradation of extracellular matrix,improving the level of inflammatory factors,and down-regulating the expression of proteins related to the nuclear factor κB(NF-κB)pathway.

Platycodonis Radix is the dry root of Platycodon grandiflorum of Campanulaceae, which has a variety of pharmacological effects and is a commonly used bulk Chinese medicine. In this study, the chloroplast genome sequences of six P. grandiflorum from different producing areas has been sequenced with Illumina HiSeq X Ten platform. The specific DNA barcodes were screened, and the germplasm resources and genetic diversity were analyzed according to the specific barcodes. The total length of the chloroplast genome of 6 P. grandiflorum samples was 172 260-172 275 bp, and all chloroplast genomes showed a typical circular tetrad structure and encoded 141 genes. The comparative genomics analysis and results of amplification efficiency demonstrated that trnG-UCC and ndhG_ndhF were the potential specific DNA barcodes for identification the germplasm resources of P. grandiflorum. A total of 305 P. grandiflorum samples were collected from 15 production areas in 9 provinces, for which the fragments of trnG-UCC and ndhG_ndhF were amplificated and the sequences were analyzed. The results showed that trnG-UCC and ndhG_ndhF have 5 and 11 mutation sites, respectively, and 5 and 7 haplotypes were identified, respectively. The combined analysis of the two sequences formed 13 haplotypes (named Hap1-Hap13), and Hap4 is the main genotype, followed by Hap1. The unique haplotypes possessed by the three producing areas can be used as DNA molecular tags in this area to distinguish from the germplasm resources of P. grandiflorum from other areas. The haplotype diversity, nucleotide diversity and genetic distance were 0.94, 4.79×10^-3 and 0.000 0-0.020 3, respectively, suggesting that the genetic diversity was abundant and intraspecific kinship was relatively close. This study laid a foundation for the identification of P. grandiflorum, the protection and utilization of germplasm resources, and molecular breeding.

Objective To explore the differential diagnostic indicators of adult-onset Still's disease(AOSD)from other fever of unknown origin(FUO).Methods The clinical data and laboratory indicators of 177 AOSD patients and 163 FUO patients who were hospitalized in the First Affiliated Hospital of Army Medical University from January 2010 to May 2021 were collected,and the patients were randomly divided into training group and verification group.Statistically significant variables were extracted from univariate analysis for receiver operating characteristic(ROC)curve analysis and the best cut-off value of the variables was obtained.The differential diagnostic indicators were extracted by multivariate logistic regression analysis and nomogram model was constructed.ROC curve,calibration curve,and decision curve analysis were used to evaluate the accuracy and stability of nomogram.Results Univariate analysis revealed that there were significant differences in 4 clinical features(arthralgia,rash,pharyngeal pain,myalgia)and 14 laboratory parameters[white blood cell count(WBC),monocyte percentage,neutrophil percentage,lymphocyte percentage,platelet count,C-reactive protein,interleukin-6(IL-6),ferritin,globulin,immunoglobulin A,and immunoglobulin G(IgG),creatine kinase,creatinine and complement C3].Multivariate analysis suggested that arthralgia,WBC≥9.995×109/L,IL-6≥98.13 ng/L,ferritin≥507.37 ng/ml,globulin≤36.58g/L,IgG≤13.59g/L,complement C3≥1.27 g/L were related with AOSD.The area under curve(AUC)values of training group and verification group were 0.917(95%CI 0.883-0.951)and 0.869(95%CI 0.802-0.936),respectively.The calibration curves showed good consistency.The decision curve analysis showed that training group and verification group had a large positive rate of return in the wide risk range of 5%-85%and 10%-85%,respectively.Conclusions This study has established a relatively accurate AOSD differential diagnosis model.The combination of arthralgia,WBC,IL-6,ferritin,globulin,IgG and complement C3 may help to distinguish AOSD from other causes of FUO.

Nanozyme is novel nanoparticle with enzyme-like activity, which can be classified into peroxidase-like nanozyme, catalase-like nanozyme, superoxide dismutase-like nanozyme, oxidase-like nanozyme and hydrolase-like nanozyme according to the type of reaction they catalyze. Since researchers first discovered Fe₃O₄ nanoparticles with peroxidase-like activity in 2007, a variety of nanoparticles have been successively found to have catalytic activity and applied in bioassays, inflammation control, antioxidant damage and tumor therapy, playing a key role in disease diagnosis and treatment. We summarize the use of nanozymes with different classes of enzymatic activity in the diagnosis and treatment of diseases and describe the main factors influencing nanozyme activity. A Mn-based peroxidase-like nanozyme that induces the reduction of glutathione in tumors to produce glutathione disulfide and Mn²⁺, which induces the production of reative oxygen species (ROS) in tumor cells by breaking down H₂O₂ in physiological media through Fenton-like action, thereby inhibiting tumor cell growth. To address the limitation of tumor tissue hypoxia during photodynamic tumor therapy, the effect of photodynamic therapy is significantly enhanced by using hydrogen peroxide nanozymes to catalyze the production of oxygen from H₂O₂. In pathological states, where excess superoxide radicals are produced in the body, superoxide dismutase-like nanozymes are able to selectively regulate intracellular ROS levels, thereby protecting normal cells and slowing down the degradation of cellular function. Based on this principle, an engineered nanosponge has been designed to rapidly scavenge free radicals and deliver oxygen in time to save nerve cells before thrombolysis. Starvation therapy, in which glucose oxidase catalyzes the hydrolysis of glucose to gluconic acid and hydrogen peroxide in cancer cells with the involvement of oxygen, attenuates glycolysis and the production of intermediate metabolites such as nucleotides, lipids and amino acids, was used to synthesize an oxidase-like nanozyme that achieved effective inhibition of tumor growth. Furthermore, by fine-tuning the Lewis acidity of the metal cluster to improve the intrinsic activity of the hydrolase nanozyme and providing a shortened ligand length to increase the density of its active site, a hydrolase-like nanozyme was successfully synthesized that is capable of cleaving phosphate bonds, amide bonds, glycosidic bonds and even biofilms with high efficiency in hydrolyzing the substrate. All these effects depend on the size, morphology, composition, surface modification and environmental media of the nanozyme, which are important aspects to consider in order to improve the catalytic efficiency of the nanozyme and have important implications for the development of nanozyme. Although some progress has been made in the research of nanozymes in disease treatment and diagnosis, there are still some problems, for example, the catalytic rate of nanozymes is still difficult to reach the level of natural enzymes in vivo, and the toxic effects of some heavy metal nanozymes material itself. Therefore, the construction of nanozyme systems with multiple functions, good biocompatibility and high targeting efficiency, and their large-scale application in diagnosis and treatment is still an urgent problem to be solved. (1) To improve the selectivity and specificity of nanozymes. By using antibody coupling, the nanoparticles are able to specifically bind to antigens that are overexpressed in certain cancer cells. It also significantly improves cellular internalization through antigen-mediated endocytosis and enhances the enrichment of nanozymes in target tissues, thereby improving targeting during tumor therapy. Some exogenous stimuli such as laser and ultrasound are used as triggers to control the activation of nanozymes and achieve specific activation of nanozyme. (2) To explore more practical and safer nanozymes and their catalytic mechanisms: biocompatible, clinically proven material molecules can be used for the synthesis of nanoparticles. (3) To solve the problem of its standardization and promote the large-scale clinical application of nanozymes in biomonitoring. Thus, it can go out of the laboratory and face the market to serve human health in more fields, which is one of the future trends of nanozyme development.