ObjectiveIn order to provide a reference for the optimization of preparation process of stir-fried Glycyrrhizae Radix et Rhizoma（sf-GRR）， the quality changes during the processing was studied. MethodsGlycyrrhizae Radix et Rhizoma was processed by stir-frying for 17 min， and samples were collected every 1 min during the processing. The appearance color of the samples was determined by visual analysis technology， the moisture and extract of the process samples were detected by the drying method and the hot extraction method of alcohol-soluble extract in the general rules of the 2020 edition of Chinese Pharmacopoeia（part Ⅳ）， and the contents of liquiritin apioside， liquiritin， isoliquiritin apioside， isoliquiritin， licoricesaponin G₂ and glycyrrhizic acid in the process samples were determined by high performance liquid chromatography（HPLC）. Then principal component analysis（PCA）， partial least squares-discriminant analysis（PLS-DA） and Spearman correlation analysis were used for clustering， discrimination and correlation analysis of the appearance color， moisture， extract and the contents of six internal components. Based on artificial neural network and random forest algorithm， the prediction model of processing degree of sf-GRR was established. On this basis， based on the five principles of quality marker（Q-Maker）， explore the monitoring Q-Maker of sf-GRR. ResultsThe color of Glycyrrhizae Radix et Rhizoma deepened after stir-frying， and the appearance color of the sample changed from light yellow to dark yellow during processing. During the stir-frying process， the moisture content showed a decreasing trend with the extension of processing time， while the extract content showed an increasing trend with the extension of processing time. After stir-frying， the contents of liquiritin apioside， liquiritin and licoricesaponin G₂ showed an overall decreasing trend， while the contents of isoliquiritin apioside and isoliquiritin increased， and the content of glycyrrhizic acid increased slightly. The correlation analysis showed that moisture was positively correlated with brightness（L^*） and red/green value（a^*）， and negatively correlated with yellow/blue value（b^*） and total color difference（E^*ab）. Isoliquiritin apioside and isoliquiritin had negative correlation with L^* and a^*， and positive correlation with b^* and E^*ab. The processing process of sf-GRR could be divided into two stages of the early stage（0-14 min） and the late stage（15-17 min）， and could be divided into three stages of the early stage（0-6 min）， the middle stage（7-14 min） and the late stage（15-17 min） by combining the moisture， extract， the contents of 6 components and color values. Based on artificial neural network analysis and random forest algorithm， isoliquiritin apioside， isoliquiritin， liquiritin and glycyrrhizic acid were selected as monitoring markers for sf-GRR. ConclusionBased on the analysis of the exterior-interior indicators of process samples of sf-GRR， this paper ultimately identifies four processing monitoring markers， which can provide a basis for optimizing the processing technology of sf-GRR.

Immobilized enzyme-based enzyme electrode biosensors, characterized by high sensitivity and efficiency, strong specificity, and compact size, demonstrate broad application prospects in life science research, disease diagnosis and monitoring, etc. Immobilization of enzyme is a critical step in determining the performance (stability, sensitivity, and reproducibility) of the biosensors. Random immobilization (physical adsorption, covalent cross-linking, etc.) can easily bring about problems, such as decreased enzyme activity and relatively unstable immobilization. Whereas, directional immobilization utilizing amino acid residue mutation, affinity peptide fusion, or nucleotide-specific binding to restrict the orientation of the enzymes provides new possibilities to solve the problems caused by random immobilization. In this paper, the principles, advantages and disadvantages and the application progress of enzyme electrode biosensors of different directional immobilization strategies for enzyme molecular sensing elements by specific amino acids (lysine, histidine, cysteine, unnatural amino acid) with functional groups introduced based on site-specific mutation, affinity peptides (gold binding peptides, carbon binding peptides, carbohydrate binding domains) fused through genetic engineering, and specific binding between nucleotides and target enzymes (proteins) were reviewed, and the application fields, advantages and limitations of various immobilized enzyme interface characterization techniques were discussed, hoping to provide theoretical and technical guidance for the creation of high-performance enzyme sensing elements and the manufacture of enzyme electrode sensors.

Collagen is a major structural protein in the matrix of animal cells and the most widely distributed and abundant functional protein in mammals. Collagen’s good biocompatibility, biodegradability and biological activity make it a very valuable biomaterial. According to the source of collagen, it can be broadly categorized into two types: one is animal collagen; the other is recombinant collagen. Animal collagen is mainly extracted and purified from animal connective tissues by chemical methods, such as acid, alkali and enzyme methods, etc. Recombinant collagen refers to collagen produced by gene splicing technology, where the amino acid sequence is first designed and improved according to one’s own needs, and the gene sequence of improved recombinant collagen is highly consistent with that of human beings, and then the designed gene sequence is cloned into the appropriate vector, and then transferred to the appropriate expression vector. The designed gene sequence is cloned into a suitable vector, and then transferred to a suitable expression system for full expression, and finally the target protein is obtained by extraction and purification technology. Recombinant collagen has excellent histocompatibility and water solubility, can be directly absorbed by the human body and participate in the construction of collagen, remodeling of the extracellular matrix, cell growth, wound healing and site filling, etc., which has demonstrated significant effects, and has become the focus of the development of modern biomedical materials. This paper firstly elaborates the structure, type, and tissue distribution of human collagen, as well as the associated genetic diseases of different types of collagen, then introduces the specific process of producing animal source collagen and recombinant collagen, explains the advantages of recombinant collagen production method, and then introduces the various systems of expressing recombinant collagen, as well as their advantages and disadvantages, and finally briefly introduces the application of animal collagen, focusing on the use of animal collagen in the development of biopharmaceutical materials. In terms of application, it focuses on the use of animal disease models exploring the application effects of recombinant collagen in wound hemostasis, wound repair, corneal therapy, female pelvic floor dysfunction (FPFD), vaginal atrophy (VA) and vaginal dryness, thin endometritis (TE), chronic endometritis (CE), bone tissue regeneration in vivo, cardiovascular diseases, breast cancer (BC) and anti-aging. The mechanism of action of recombinant collagen in the treatment of FPFD and CE was introduced, and the clinical application and curative effect of recombinant collagen in skin burn, skin wound, dermatitis, acne and menopausal urogenital syndrome (GSM) were summarized. From the exploratory studies and clinical applications, it is evident that recombinant collagen has demonstrated surprising effects in the treatment of all types of diseases, such as reducing inflammation, promoting cell proliferation, migration and adhesion, increasing collagen deposition, and remodeling the extracellular matrix. At the end of the review, the challenges faced by recombinant collagen are summarized: to develop new recombinant collagen types and dosage forms, to explore the mechanism of action of recombinant collagen, and to provide an outlook for the future development and application of recombinant collagen.

OBJECTIVE To analyze the clinical characteristics of aplastic anemia （AA）/pure red cell aplasia （PRCA） induced by pembrolizumab， and provide reference for clinical safe drug use. METHODS Using search terms as “pembrolizumab”， “keytruda”， “anemia” and “aplastic anemia” in both Chinese and English， the literature related to AA/PRCA induced by pembrolizumab were retrieved from PubMed， Embase， CNKI， Wanfang and VIP databases， and then analyzed descriptively and statistically. RESULTS A total of 10 patients were included from 10 literature； among these 10 patients， there were 5 males and 5 females， with 5 patients being aged 65 or above. The primary disease was mainly metastatic melanoma （4 cases）. AA/PRCA occurred 13 d-3 years after the first dose of pembrolizumab. The main clinical manifestations included fatigue， dyspnea， oral/nasal bleeding， diffuse purpura， etc.； 8 cases developed moderate anemia and 2 cases developed severe anemia. After discontinuation and receiving supportive therapy， 5 cases improved， 1 case worsened in anemia， and 4 cases died. CONCLUSIONS When using pembrolizumab in clinical practice， blood routine should be regularly monitored. When AA/PRCA and other related symptoms occur， pembrolizumab should be stopped in time and a therapy regimen should be formulated according to the patient’ condition， to ensure the safety of medication.

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.

The assessment of adverse drug events is an important basis for clinical safety evaluation and post-marketing risk control of drugs,and its causality assessment is gaining increasing attention.The existing methods for assessing the causal relationship between drugs and the occurrence of adverse reactions can be broadly classified into three categories:global introspective methods,standardized methods,and probabilistic methods.At present,there is no systematic introduction of the operational details of the various methods in the domestic literature.This paper compares representative causality assessment methods in terms of definition and concept,methodological steps,industry evaluation and advantages and disadvantages,clarifies the basic process of determining the causality of adverse drug reactions,and discusses how to further improve the adverse drug reaction monitoring and evaluation system,with a view to providing a reference for drug development and pharmacovigilance work in China.