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.

Aim To explore the potential targets and related signaling pathways of Agaricus blazei Murill (AbM ) extract in the treatment of chronic myeloid leukemia (CML) based on liquid chromatography mass spectrometry ( LC-MS ), network pharmacology, molecular docking, and were further verified by experiments in vitro. Methods The active components of AbM extract were retrieved from LC-MS, Swiss Target Prediction database was used to predict related targets, and CML disease target genes were obtained from Gen- eCards and DisGeNET databases. After screening the common targets of drug and CML, the protein-protein interaction network of the common targets was performed by STRING, and GO and KEGG enrichment a- nalysis were done by DAVID database. Cytoscape software was used to construct the network of target protein. Molecular docking was carried out by DockThor, and the Pymol software was used to make a visual picture. The inhibitory effect of AbM extract on leukemia cells K562 was determined by CCK-8 experiment, and the effect of AbM extract on the expression and phosphorylation level of related proteins was verified by Western blot. Results The prediction results showed that 126 active components of AbM extract, and 172 common targets were collected. KEGG pathway analysis results showed that PI3K/Akt/mTOR signaling pathway might play an important role in the treatment of CML disease. The IC

Natural products are important sources of drug discovery. However, the traditional methods of extraction and isolation, as well as chemical synthesis for obtaining natural products are associated with issues such as operational complexity, high costs, low efficiency, and environmental pollution. Constructing microbial cell factories through synthetic biology methods to produce medicinal natural products has the advantages of high efficiency, low cost, and environmental protection. Nevertheless, the scope and yield improvement of the products are limited by the limitations of enzymes in microbial cell factories. Protein engineering is considered one of the most effective approaches to overcome these limitations. This article introduces commonly used methods of protein engineering technology and summarizes its specific applications in improving enzyme performance, modifying the enzymatic environment, and promoting the development of synthetic biology tools in the field of pharmaceutical natural product synthesis. Furthermore, it analyzes the current bottlenecks and challenges in protein engineering and looks forward to its future application prospects, offering insights for the development and practical use of protein engineering technology.

This study aimed to investigate the therapeutic effects of Morinda officinalis iridoid glycosides (MOIG) on bone loss of rheumatoid arthritis (RA) rats, and the mechanism of osteoclast function and activity induced by lipopolysaccharide (LPS). RA rats were established by injecting bovin type II collagen. The Bio-ethic Committee of Zhejiang Chinese Medical University approved all experimental protocols associated with this study (IACUC-20180410-03). The collagen-induced arthritis (CIA) rats were administered drug by gavage for 8 weeks; the femoral trabecular micro-structure changes were observed in CIA rats by micro-CT; the LPS-induced osteoclasts model further observed the effect and mechanism of anti-inflammatory osteoporosis in vitro. The results indicated that MOIG could markedly increase bone mineral density (BMD) in CIA rats, improve trabecular micro-structure. In vitro studies demonstrated that MOIG could significantly inhibit osteoclastogensis and differentiation, suppress tartrate resistant acid phosphatase (TRAP) activity, F-actin ring formation, TNF receptor associated factor 6 (TRAF6) recruitment, and inhibitor of nuclear factor kappa-Bα (IκBα) degradation as well as p65 phosphorylation, thereby repressing nuclear factor kappa-B (NF-κB) signaling pathway activation. Subsequently, MOIG effectively inhibited osteoclast nuclear factor of activated T-cells c1 (NFATc1) and cellular oncogene Fos (c-Fos) expression, as well as bone resorption related protein activity including matrix metalloprotein 9 (MMP-9) and cathepsin K (CtsK). Meanwhile, MOIG also repressed the phosphorylation expression of Janus activating kinase 2 (JAK2) and signal transducer and activator of transcription 3 (STAT3), thereby inhibiting JAK2/STAT3 signaling pathway activation. Moreover, further studies found that MOIG could suppress glycogen synthase kinase-3β (GSK-3β) activity, and GSK-3β gene silencing could markedly inhibit oetsoclast F-actin ring formation as well as the phosphorylation expression of p65 and STAT3. Of note, compared with GSK-3β gene silencing group, there was no significant difference in the group treated with both MOIG with GSK-3β gene silencing simultaneously. Thus, the results suggested that MOIG may inhibit NF-κB signaling pathway and JAK2/STAT3 signaling pathway activation via regulating GSK-3β, thereby alleviating bone destruction in RA.

Objective To explore the efficacy and safety of recombinant human anti-severe acute respiratory syn-drome coronavirus 2(anti-SARS-CoV-2)monoclonal antibody injection(F61 injection)in the treatment of patients with coronavirus disease 2019(COVID-19)combined with renal damage.Methods Patients with COVID-19 and renal damage who visited the PLA General Hospital from January to February 2023 were selected.Subjects were randomly divided into two groups.Control group was treated with conventional anti-COVID-19 therapy,while trial group was treated with conventional anti-COVID-19 therapy combined with F61 injection.A 15-day follow-up was conducted after drug administration.Clinical symptoms,laboratory tests,electrocardiogram,and chest CT of pa-tients were performed to analyze the efficacy and safety of F61 injection.Results Twelve subjects(7 in trial group and 5 in control group)were included in study.Neither group had any clinical progression or death cases.The ave-rage time for negative conversion of nucleic acid of SARS-CoV-2 in control group and trial group were 3.2 days and 1.57 days(P=0.046),respectively.The scores of COVID-19 related target symptom in the trial group on the 3rd and 5th day after medication were both lower than those of the control group(both P＜0.05).According to the clinical staging and World Health Organization 10-point graded disease progression scale,both groups of subjects improved but didn't show statistical differences(P＞0.05).For safety,trial group didn't present any infusion-re-lated adverse event.Subjects in both groups demonstrated varying degrees of elevated blood glucose,elevated urine glucose,elevated urobilinogen,positive urine casts,and cardiac arrhythmia,but the differences were not statistica-lly significant(all P＞0.05).Conclusion F61 injection has initially demonstrated safety and clinical benefit in trea-ting patients with COVID-19 combined with renal damage.As the domestically produced drug,it has good clinical accessibility and may provide more options for clinical practice.

OBJECTIVE To develop a population pharmacokinetic （PPK） model for mycophenolate mofetil active metabolite mycophenolic acid （MPA） in children with primary IgA nephropathy， explore the factors affecting the pharmacokinetic parameters of MPA， and provide a basis for clinical individualized therapy. METHODS Retrospective collection was conducted on 636 concentrations and clinical data from 47 pediatric patients with primary IgA nephropathy. PPK analysis was carried out by using the nonlinear mixed-effects model； the covariates were tested with a stepwise method. Goodness-of-fit plots， Bootstrap and visual predictive check were employed to evaluate the final model. RESULTS The pharmacokinetics of MPA in children with IgA nephropathy in vivo conformed to the first-order absorption and elimination two-compartment model （objective function value of 3 276.31）. Covariate analysis suggested that body weight and albumin （ALB） levels were significant influencing factors on apparent clearance rate and apparent distribution volume. The typical values of PPK parameters of MPA in the final model were as follows： the central room had a distributed volume of 5.79 L， the clearance rate was 4.06 L/h， the volume of peripheral ventricular distribution was 430.93 L， the clearance rate between compartments was 15.40 L/h， the oral absorption rate constant was 1.29 h－1. After verification， most of the predicted corrected observed concentration points were within the 90% confidence interval of the predicted corrected simulated concentration， indicating that the MPA final model had good predictive performance. CONCLUSIONS The PPK model of MPA in children with primary IgA nephropathy is established in this study， identifying body weight and ALB levels are significant factors affecting MPA metabolism.