Neurocritical care involves complex pathophysiological mechanisms, and its incidence is higher, injuries are more severe, and treatment is more challenging in high-altitude environments. This consensus, based on the latest domestic and international evidence-based medical data, establishes a standardized, goal-oriented framework for neurocritical care management applicable in high-altitude regions and nationwide. The consensus was developed following international standards for evidence quality assessment and underwent two rounds of Delphi expert consultation, resulting in 32 recommendation statements covering three parts: management systems, monitoring and assessment, and core strategies. Key updates include: advocating for the establishment of independent neurocritical care units and implementing precise tiered diagnosis and treatment based on the "Five Differences in Critical Care" concept; constructing a "trinity" multimodal brain monitoring system centered on cerebral blood flow, cerebral oxygenation, and brain function, emphasizing routine bedside transcranial Doppler ultrasound, cerebral oximetry, and continuous electroencephalography monitoring; shifting management strategies from mild hypothermia therapy to targeted temperature management, and defining the "446" target management pathway for the supercritical stage; emphasizing the assessment of static and dynamic cerebrovascular autoregulation functions through multimodal methods to achieve individualized optimal mean arterial pressure management; elevating cerebrospinal fluid management goals to the level of "glymphatic system" function maintenance; implementing a multidisciplinary collaborative, whole-process management model focusing on patients' long-term neurological functional outcomes; de-escalation criteria include multidimensional indicators such as recovery of brain structure, restoration of cerebrovascular autoregulation, improvement in cerebrospinal fluid dynamics, and reduction in biomarker levels; and integrating cutting-edge technologies like artificial intelligence into post-critical care management and rehabilitation planning. This consensus systematically integrates the entire process of neurocritical care management, reflecting the modern connotation of goal-oriented, dynamic, and multimodal integration in neurocritical care medicine. It aims to adapt to new trends such as deepening understanding of pathophysiological mechanisms, the integration of medicine and engineering, and the empowerment of artificial intelligence, thereby further advancing the discipline of critical care medicine.

OBJECTIVE To confirm trigger items for adverse drug reaction （ADR） induced by bevacizumab， to identify and analyze the occurrence of related ADR， and to establish a predictive model for severe adverse reaction （SAR） caused by this drug. METHODS Based on the global trigger tool （GTT） theory， and referencing the GTT White Paper， drug package inserts and relevant literature， trigger items for bevacizumab-related ADR were confirmed using a single-round Delphi method. Utilizing these established items， electronic medical records of relevant patients at Guilin People’s Hospital from January 2020 to September 2024 were actively screened via the China Hospital Pharmacovigilance System. Pharmacists then identified and tallied the occurrence of bevacizumab-induced ADR. Data from patients with any positive trigger item served as the study subjects （divided into training and test sets at a ratio of 7∶3）， candidate feature variables were selected from 39 related variables using the Boruta algorithm， and the multivariable Logistic regression analysis was performed with the occurrence of SAR as the dependent variable. Based on these candidate features， Logistic Regression， Extreme Gradient Boosting， Light Gradient Boosting Machine， Random Forest， and Categorical Boosting models were constructed. Model performance was evaluated using metrics including the area under the curve （AUC） of receiver operating characteristic curve and recall rate. The Shapley Additive exPlanations （SHAP） method was applied to analyze and interpret the contribution of each variable. A nomogram was constructed based on the optimal model. RESULTS A total of 38 trigger items for active monitoring of bevacizumab-related ADR were determined， comprising 17 laboratory indicators， 13 clinical manifestations， and 8 intervention measures. In total， 483 patients with positive trigger items were included， and 318 patients with bevacizumab-induced ADR were identified， including 83 SARs. The positive predictive values for the trigger items and cases were 43.57% （708/1 625） and 63.84% （318/483）， respectively. Bevacizumab-induced ADR involved 7 systems/organs， with the hematological system being the most frequently involved （64.15%）. The Boruta algorithm selected 7 vari ables： serum potassium， hematocrit， albumin-to-globulin ratio， prealbumin， hypertension history， age and red blood cell count. Multivariable Logistic regression showed that elevated serum potassium levels were associated with a decreased risk of bevacizumab-induced SAR （OR＝0.234， P ＝0.002）， while a history of hypertension （OR＝2.642， P ＝0.006） and increased age （OR＝1.040， P ＝0.025） were associated with an increased risk. The Logistic Regression model demonstrated superior performance with higher AUC， F1 score and recall rate （0.761， 0.447， 0.607）， compared to other models. SHAP evaluation results indicated that variables such as serum potassium， hematocrit， and age ranked highest in importance. CONCLUSIONS Totally 38 trigger entries have been successfully identified for active screening of bevacizumab-related ADR. Elevated serum potassium levels are a protective factor against bevacizumab-induced SAR， whereas the hypertension history and increased age are risk factors. The Logistic Regression model is the optimal predictive model.

ObjectivePancreatic ductal adenocarcinoma (PDAC) exhibits a limited response to current treatments due to its dense fibrotic stroma and highly immunosuppressive tumor microenvironment. In recent years, advancements in cellular immunotherapy, particularly chimeric antigen receptor macrophage (CAR-M) therapy, have offered new hope for pancreatic cancer treatment. Although CAR-M therapy demonstrates dual potential in directly killing tumor cells and remodeling the immune microenvironment, it still faces challenges such as complex in vitro preparation processes and low in vivo targeting and delivery efficiency. Therefore, developing strategies for efficient and targeted in vivo delivery of CAR genes has become crucial for overcoming current therapeutic limitations. This study aims to develop an orally administrable nano-gene delivery system for the targeted delivery of CAR genes to pancreatic tumor sites. MethodsCore nano-gene particles (PNP/pCAR) were constructed by loading plasmid DNA encoding CAR (pCAR) with cationic polypeptides (PNP). Subsequently, PNP/pCAR was surface-modified with β-glucan to prepare the targeted nanoparticles (βGlus-PNP/pCAR). The loading efficiency of PNP for pCAR was quantitatively assessed by gel retardation assay. The particle size, Zeta potential, morphology, and storage stability of PNP/pCAR were characterized using a Malvern particle size analyzer and transmission electron microscopy. At the cellular level, RAW 264.7 macrophages were selected. The cytotoxicity of PNP/pCAR was evaluated using the CCK-8 assay. The cellular uptake efficiency and lysosomal escape ability of the nanoparticles were assessed via flow cytometry and confocal microscopy. Transfection efficiency was quantitatively evaluated by detecting the expression of the reporter gene GFP using flow cytometry. At the in vivo level, an orthotopic pancreatic cancer mouse model was established. Cy7-labeled βGlus-PNP/pCAR nanoparticles were administered orally, and the fluorescence distribution in mice was dynamically monitored at 1, 2, 4, 8, and 16 h post-administration using a small animal in vivo imaging system. Forty-eight hours after oral gavage, the mice were euthanized, and pancreatic tumor tissues were collected for further analysis of intratumoral fluorescence signals using the imaging system. Additionally, βGlus-PNP/pCAR-GFP nanoparticles loaded with the reporter gene (GFP) were administered orally. Forty-eight hours post-administration, pancreatic tumor tissues were harvested to prepare frozen sections, and GFP expression was observed and analyzed under a fluorescence microscope. ResultsThe PNP carrier exhibited a high loading capacity for pCAR. The successfully prepared PNP/pCAR nanoparticles were regular spheres with a hydrodynamic diameter of approximately (120±10) nm and a Zeta potential of about +(6±1) mV. They maintained good structural stability after incubation in PBS buffer for 7 d. Cell experiments demonstrated that PNP/pCAR exhibited no significant cytotoxicity in RAW 264.7 cells while being efficiently internalized and effectively escaping lysosomal degradation. The transfection positive rate of PNP/pCAR-GFP in RAW 264.7 cells reached (25±3)%, surpassing that of Lipofectamine 2000-loaded pCAR-GFP (Lipo/pCAR-GFP), which was (20±1)%.In vivo experiments revealed that, compared to unmodified PNP/pCAR, βGlus-PNP/pCAR exhibited strongerin situ pancreatic tumor targeting ability after oral administration. Furthermore, oral administration of βGlus-PNP/pCAR-GFP resulted in significant GFP protein expression detectable within pancreatic tumor tissues. ConclusionThis study successfully constructed and validated an orally administrable, pancreatic cancer-targeting polypeptide-based nano-gene delivery system. It provides an important technological foundation in delivery systems and experimental basis for the subsequent development of in situ CAR-M-based therapeutic strategies for pancreatic cancer.

ObjectivePancreatic ductal adenocarcinoma (PDAC) exhibits a limited response to current treatments due to its dense fibrotic stroma and highly immunosuppressive tumor microenvironment. In recent years, advancements in cellular immunotherapy, particularly chimeric antigen receptor macrophage (CAR-M) therapy, have offered new hope for pancreatic cancer treatment. Although CAR-M therapy demonstrates dual potential in directly killing tumor cells and remodeling the immune microenvironment, it still faces challenges such as complex in vitro preparation processes and low in vivo targeting and delivery efficiency. Therefore, developing strategies for efficient and targeted in vivo delivery of CAR genes has become crucial for overcoming current therapeutic limitations. This study aims to develop an orally administrable nano-gene delivery system for the targeted delivery of CAR genes to pancreatic tumor sites. MethodsCore nano-gene particles (PNP/pCAR) were constructed by loading plasmid DNA encoding CAR (pCAR) with cationic polypeptides (PNP). Subsequently, PNP/pCAR was surface-modified with β-glucan to prepare the targeted nanoparticles (βGlus-PNP/pCAR). The loading efficiency of PNP for pCAR was quantitatively assessed by gel retardation assay. The particle size, Zeta potential, morphology, and storage stability of PNP/pCAR were characterized using a Malvern particle size analyzer and transmission electron microscopy. At the cellular level, RAW 264.7 macrophages were selected. The cytotoxicity of PNP/pCAR was evaluated using the CCK-8 assay. The cellular uptake efficiency and lysosomal escape ability of the nanoparticles were assessed via flow cytometry and confocal microscopy. Transfection efficiency was quantitatively evaluated by detecting the expression of the reporter gene GFP using flow cytometry. At the in vivo level, an orthotopic pancreatic cancer mouse model was established. Cy7-labeled βGlus-PNP/pCAR nanoparticles were administered orally, and the fluorescence distribution in mice was dynamically monitored at 1, 2, 4, 8, and 16 h post-administration using a small animal in vivo imaging system. Forty-eight hours after oral gavage, the mice were euthanized, and pancreatic tumor tissues were collected for further analysis of intratumoral fluorescence signals using the imaging system. Additionally, βGlus-PNP/pCAR-GFP nanoparticles loaded with the reporter gene (GFP) were administered orally. Forty-eight hours post-administration, pancreatic tumor tissues were harvested to prepare frozen sections, and GFP expression was observed and analyzed under a fluorescence microscope. ResultsThe PNP carrier exhibited a high loading capacity for pCAR. The successfully prepared PNP/pCAR nanoparticles were regular spheres with a hydrodynamic diameter of approximately (120±10) nm and a Zeta potential of about +(6±1) mV. They maintained good structural stability after incubation in PBS buffer for 7 d. Cell experiments demonstrated that PNP/pCAR exhibited no significant cytotoxicity in RAW 264.7 cells while being efficiently internalized and effectively escaping lysosomal degradation. The transfection positive rate of PNP/pCAR-GFP in RAW 264.7 cells reached (25±3)%, surpassing that of Lipofectamine 2000-loaded pCAR-GFP (Lipo/pCAR-GFP), which was (20±1)%.In vivo experiments revealed that, compared to unmodified PNP/pCAR, βGlus-PNP/pCAR exhibited strongerin situ pancreatic tumor targeting ability after oral administration. Furthermore, oral administration of βGlus-PNP/pCAR-GFP resulted in significant GFP protein expression detectable within pancreatic tumor tissues. ConclusionThis study successfully constructed and validated an orally administrable, pancreatic cancer-targeting polypeptide-based nano-gene delivery system. It provides an important technological foundation in delivery systems and experimental basis for the subsequent development of in situ CAR-M-based therapeutic strategies for pancreatic cancer.

Objective To construct a lung cancer surgery-oriented disease-specific database covering the entire perioperative care pathway, thereby improving the quality and usability of key surgical data elements. Methods Real-world clinical data were extracted from a single-center thoracic surgery department. A standardized data model was established based on the open electronic health record (openEHR) standard. Large language model (LLM), optical character recognition (OCR), and artificial intelligence (AI)-driven techniques were employed to extract, structure, and perform quality control on unstructured clinical narratives, imaging reports, and radiological data, with a focus on capturing surgically relevant perioperative indicator. Results A multimodal database comprising 19 917 patients was established, including 7 930 males and 11 987 females, with ages ranging from 15 to 97 (61.7±9.7) years. The database includes 582 structured data variables, textual report data corresponding to 69 clinical indicators, 13 000 pulmonary function test PDF reports, and chest CT imaging data from 16 884 patients. This database comprehensively covers major information relevant to surgical diagnosis and treatment of lung cancer, significantly improving the completeness and granularity of surgical detail data. Large language models (LLMs) and optical character recognition (OCR) technologies enhanced the efficiency of converting unstructured data into structured formats, while a multi-level manual verification process ensured data accuracy and traceability. The database supports real-world research including comparisons of surgical procedures, prediction of postoperative complications, prognosis assessment, and multimodal data association analyses.

ObjectiveChronic atrophic gastritis (CAG) is usually diagnosed by gastroscopy and histopathological biopsy. These procedures remain the reference standard, but their invasive nature and resource requirements may limit their use in large-scale population screening and repeated follow-up. A convenient and reproducible method for noninvasive auxiliary screening may help identify individuals who require further endoscopic assessment. Fingertip photoplethysmography (PPG) provides a noninvasive recording of peripheral pulse waves and allows harmonic features to be extracted from the signal. In this study, the so-called meridian-related variables were defined as PPG-derived harmonic parameters labelled according to meridian nomenclature, rather than as direct measurements of meridian physiology. This study aimed to compare these harmonic parameters between patients with CAG and non-CAG controls, identify parameters that remained different after age adjustment, and develop a multivariable model for noninvasive auxiliary screening and pre-endoscopic risk stratification of CAG. MethodsA total of 343 participants were included, comprising 171 patients with CAG and 172 non-CAG controls. CAG diagnosis was established using gastroscopy and histopathology as the reference standard. Fingertip PPG signals were collected using a PPG-based pulse acquisition device. Eight PPG-derived harmonic parameters labelled according to meridian nomenclature were extracted for analysis. Between-group differences were first assessed using nonparametric tests. Age-adjusted analyses were then performed to reduce potential confounding by age. The false discovery rate (FDR) method was applied for multiple-comparison correction. A multivariable logistic regression model integrating age and multiple harmonic parameters was constructed. Model performance was evaluated using receiver operating characteristic (ROC) analysis and the area under the curve (AUC). Internal validation performance was assessed using stratified five-fold cross-validation and bootstrap optimism correction. Threshold performance was examined using both a high-specificity strategy and a Youden index-based cutoff. Decision curve analysis was used to evaluate the model’s net clinical benefit across a range of threshold probabilities. ResultsAll eight harmonic parameters were non-normally distributed. In the univariate analysis, the stomach-labelled harmonic parameter (ST), bladder-labelled harmonic parameter (BL), and liver-labelled harmonic parameter (LR) differed between the CAG and non-CAG groups. After age adjustment and FDR correction, only ST and BL remained statistically significant. Compared with non-CAG controls, patients with CAG showed higher ST values and lower BL values. This finding indicates an associated differential harmonic pattern that was not fully explained by age distribution. However, the discriminative ability of a single harmonic parameter was limited. The best-performing single indicator was ST, with an AUC of 0.652 (95% CI: 0.595-0.707). The multivariable model integrating age and multiple harmonic parameters achieved an AUC of 0.791 (95% CI: 0.743-0.835), representing an improvement of 0.139 over ST alone. In internal validation, stratified five-fold cross-validation yielded a mean AUC of 0.753 (95% CI: 0.715-0.781), and the bootstrap optimism-corrected AUC was 0.748. These results suggest that the model retained moderate discriminative performance after internal validation.At a specificity of at least 95%, the model achieved a sensitivity of only 40.4% (95% CI: 25.7%-49.7%). This high-specificity cutoff may be suboptimal as the preferred threshold for an initial screening setting because of the potential risk of missed CAG cases. The Youden index-based optimal cutoff was 0.419, corresponding to a sensitivity of 80.7% and a specificity of 62.8%. This threshold may better match the practical aim of noninvasive auxiliary screening, where sensitivity is usually prioritized to reduce missed cases. Decision curve analysis showed that, within a threshold probability range of 10%-55%, the model provided higher net clinical benefit than the reference strategies of recommending gastroscopy for all participants or for none. ConclusionPatients with CAG showed associated harmonic differences in fingertip PPG-derived features, mainly characterized by higher ST and lower BL values after age adjustment and FDR correction. Compared with a single harmonic parameter, the multivariable model showed better overall discrimination and retained moderate internal validation performance. These findings suggest that PPG-derived harmonic parameters labelled according to meridian nomenclature may provide auxiliary information for noninvasive auxiliary screening and front-line triage before gastroscopic confirmation in CAG. The present results support further validation rather than immediate clinical implementation. External validation in independent, multicenter, and preferably prospective screening cohorts is needed to assess the model’s generalizability, screening performance, and potential clinical utility.

ObjectiveChronic atrophic gastritis (CAG) is usually diagnosed by gastroscopy and histopathological biopsy. These procedures remain the reference standard, but their invasive nature and resource requirements may limit their use in large-scale population screening and repeated follow-up. A convenient and reproducible method for noninvasive auxiliary screening may help identify individuals who require further endoscopic assessment. Fingertip photoplethysmography (PPG) provides a noninvasive recording of peripheral pulse waves and allows harmonic features to be extracted from the signal. In this study, the so-called meridian-related variables were defined as PPG-derived harmonic parameters labelled according to meridian nomenclature, rather than as direct measurements of meridian physiology. This study aimed to compare these harmonic parameters between patients with CAG and non-CAG controls, identify parameters that remained different after age adjustment, and develop a multivariable model for noninvasive auxiliary screening and pre-endoscopic risk stratification of CAG. MethodsA total of 343 participants were included, comprising 171 patients with CAG and 172 non-CAG controls. CAG diagnosis was established using gastroscopy and histopathology as the reference standard. Fingertip PPG signals were collected using a PPG-based pulse acquisition device. Eight PPG-derived harmonic parameters labelled according to meridian nomenclature were extracted for analysis. Between-group differences were first assessed using nonparametric tests. Age-adjusted analyses were then performed to reduce potential confounding by age. The false discovery rate (FDR) method was applied for multiple-comparison correction. A multivariable logistic regression model integrating age and multiple harmonic parameters was constructed. Model performance was evaluated using receiver operating characteristic (ROC) analysis and the area under the curve (AUC). Internal validation performance was assessed using stratified five-fold cross-validation and bootstrap optimism correction. Threshold performance was examined using both a high-specificity strategy and a Youden index-based cutoff. Decision curve analysis was used to evaluate the model’s net clinical benefit across a range of threshold probabilities. ResultsAll eight harmonic parameters were non-normally distributed. In the univariate analysis, the stomach-labelled harmonic parameter (ST), bladder-labelled harmonic parameter (BL), and liver-labelled harmonic parameter (LR) differed between the CAG and non-CAG groups. After age adjustment and FDR correction, only ST and BL remained statistically significant. Compared with non-CAG controls, patients with CAG showed higher ST values and lower BL values. This finding indicates an associated differential harmonic pattern that was not fully explained by age distribution. However, the discriminative ability of a single harmonic parameter was limited. The best-performing single indicator was ST, with an AUC of 0.652 (95% CI: 0.595-0.707). The multivariable model integrating age and multiple harmonic parameters achieved an AUC of 0.791 (95% CI: 0.743-0.835), representing an improvement of 0.139 over ST alone. In internal validation, stratified five-fold cross-validation yielded a mean AUC of 0.753 (95% CI: 0.715-0.781), and the bootstrap optimism-corrected AUC was 0.748. These results suggest that the model retained moderate discriminative performance after internal validation.At a specificity of at least 95%, the model achieved a sensitivity of only 40.4% (95% CI: 25.7%-49.7%). This high-specificity cutoff may be suboptimal as the preferred threshold for an initial screening setting because of the potential risk of missed CAG cases. The Youden index-based optimal cutoff was 0.419, corresponding to a sensitivity of 80.7% and a specificity of 62.8%. This threshold may better match the practical aim of noninvasive auxiliary screening, where sensitivity is usually prioritized to reduce missed cases. Decision curve analysis showed that, within a threshold probability range of 10%-55%, the model provided higher net clinical benefit than the reference strategies of recommending gastroscopy for all participants or for none. ConclusionPatients with CAG showed associated harmonic differences in fingertip PPG-derived features, mainly characterized by higher ST and lower BL values after age adjustment and FDR correction. Compared with a single harmonic parameter, the multivariable model showed better overall discrimination and retained moderate internal validation performance. These findings suggest that PPG-derived harmonic parameters labelled according to meridian nomenclature may provide auxiliary information for noninvasive auxiliary screening and front-line triage before gastroscopic confirmation in CAG. The present results support further validation rather than immediate clinical implementation. External validation in independent, multicenter, and preferably prospective screening cohorts is needed to assess the model’s generalizability, screening performance, and potential clinical utility.

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.

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.