The organoid co-culture model, as a novel tool for recreating a three-dimensional microenvironment to study cell-cell interactions, has demonstrated significant application potential in biomedical research in recent years. By simulating the in vivo tissue microenvironment, this model provides a more precise experimental platform for investigating complex cellular interactions, particularly in areas such as tumor immune evasion mechanisms, drug sensitivity testing, and the pathological characterization of neurodegenerative diseases, where it has demonstrated significant value. However, the organoid co-culture model still faces several challenges in terms of standardized procedures, large-scale cultivation, ethical guidelines, and future development. In particular, in the field of laboratory animal science, how to effectively combine organoids with traditional animal models, and how to select the most appropriate model for different research needs while exploring its potential for replacement, remain pressing issues. In the context of ethical approval and the replacement of animal experiments, the organoid co-culture model offers an experimental approach that better aligns with the "3R" principle (Replacement, Reduction, Refinement), potentially becoming an important tool for replacing traditional animal models. To this end, this paper reviews the latest advances and key challenges in this field, providing a detailed description of the construction methods for organoid co-culture models and discussing their applications in disease mechanism research and drug screening. The paper also systematically compares the organoid co-culture models with traditional animal models, exploring the criteria for selecting the appropriate model for specific applications. Furthermore, this paper discusses the potential value of organoid co-culture models as alternatives to animal experiments and anticipates future development trends of this technology. Through these discussions, the paper aims to promote the innovation and development of organoid co-culture technology and provide new perspectives and scientific evidence for future research.

The organoid co-culture model, as a novel tool for recreating a three-dimensional microenvironment to study cell-cell interactions, has demonstrated significant application potential in biomedical research in recent years. By simulating the in vivo tissue microenvironment, this model provides a more precise experimental platform for investigating complex cellular interactions, particularly in areas such as tumor immune evasion mechanisms, drug sensitivity testing, and the pathological characterization of neurodegenerative diseases, where it has demonstrated significant value. However, the organoid co-culture model still faces several challenges in terms of standardized procedures, large-scale cultivation, ethical guidelines, and future development. In particular, in the field of laboratory animal science, how to effectively combine organoids with traditional animal models, and how to select the most appropriate model for different research needs while exploring its potential for replacement, remain pressing issues. In the context of ethical approval and the replacement of animal experiments, the organoid co-culture model offers an experimental approach that better aligns with the "3R" principle (Replacement, Reduction, Refinement), potentially becoming an important tool for replacing traditional animal models. To this end, this paper reviews the latest advances and key challenges in this field, providing a detailed description of the construction methods for organoid co-culture models and discussing their applications in disease mechanism research and drug screening. The paper also systematically compares the organoid co-culture models with traditional animal models, exploring the criteria for selecting the appropriate model for specific applications. Furthermore, this paper discusses the potential value of organoid co-culture models as alternatives to animal experiments and anticipates future development trends of this technology. Through these discussions, the paper aims to promote the innovation and development of organoid co-culture technology and provide new perspectives and scientific evidence for future research.

Objective:To develop an artificial intelligence (AI)-based automatic scoring model for magnetic resonance imaging-detected extramural vascular invasion (AI-mrEMVI) and evaluate its performance and prognostic value in patients with rectal cancer.Methods:In this multicenter retrospective cohort study, a total of 2 501 rectal cancer patients from seven centers between November 2012 and December 2020 were included and divided into completely independent training ( n=1 830) and validation ( n=671) cohorts. A nnUNet-based AI-mrEMVI scoring model was constructed. Manual mrEMVI scores assigned by two radiologists served as the reference standard for accessing the accuracy of the AI-mrEMVI scoring. Kaplan-Meier survival analysis and Cox regression were used to evaluate the prognostic stratification ability of the AI-mrEMVI scores. The concordance index (C-index) was calculated to evaluate prognostic performance. Results:In the validation cohort, the manual mrEMVI scores were 0-2 in 425 patients (63.3%), 3 in 89 (13.4%), and 4 in 157 (23.4%). The AI-mrEMVI model identified 0-2 in 375 patients (55.9%), 3 in 95 (14.2%), and 4 in 201 (30.0%), with an overall accuracy of 81.1% (544/671, 95% CI 77.9%-84.0%). The 3-year disease-free survival (DFS) rates for patients with AI-mrEMVI scores of 0-2, 3, and 4 were 85.2%, 70.0%, and 58.2%, respectively, and the 5-year overall survival (OS) rates were 87.2%, 81.6%, and 62.6%, respectively (DFS: χ2=48.74, P<0.001; OS: χ2=30.04, P<0.001). Multivariable Cox regression showed that for DFS, AI-mrEMVI scores of 3 and 4 were associated with hazard ratios ( HR) of 1.75 (95% CI 1.11-2.77, P=0.016) and 2.65 (95% CI 1.86-3.78, P<0.001), respectively. For OS, an AI-mrEMVI score of 4 was associated with an HR of 2.56 (95% CI 1.62-4.03, P<0.001). The C-index values of the AI-mrEMVI scoring model for predicting DFS and OS were 0.647 (95% CI 0.608-0.686) and 0.650 (95% CI 0.598-0.702), respectively. Conclusion:The proposed AI-mrEMVI automatic scoring model demonstrated high diagnostic accuracy and performed favorably in predicting DFS and OS prognostic risk in patients with rectal cancer.

Objective To explore the impact of peptidylarginine deiminase 2(Padi2)-knockout on depressive-like behaviors in socially isolated mice.Methods Using CRISPR/Cas9 technology,a Padi2-knockout(Padi2-/-)mouse model with a C57BL/6J background was established,and the effect of Padi2 knockout was identified by genotyping and RT-qPCR detection.Six-week-old male Padi2-/- mice and wild-type C57BL/6J mice were selected and divided into normal rearing and social isolation groups,with 15 mice per group.The normal rearing group mice were housed with 5 mice per cage,and the social isolation group was housed with 1 mouse per cage,and weighed once a week.After 4 weeks,forced swimming and open field tests were conducted.After the behavioral experiments,brain tissues were taken from mice in each group,and changes in microglia in the brains were detected by immunofluorescence.Results We successfully established Padi2-/- mice.There was no difference in behavior between Padi2-/- mice and C57BL/6J mice in the normal rearing group.After social isolation,compared with C57BL/6J mice,Padi2-/- mice showed a significant increase in depressive symptoms,obvious weight gain,and a significant increase in the number of microglia in brain tissue.Conclusions Padi2 knockout exacerbated depressive-like behaviors and obesity in socially isolated mice,indicating that Padi2 is involved in the progression of depression and may be an effective target for the prevention and treatment of depression.

Objective To explore the impact of peptidylarginine deiminase 2(Padi2)-knockout on depressive-like behaviors in socially isolated mice.Methods Using CRISPR/Cas9 technology,a Padi2-knockout(Padi2-/-)mouse model with a C57BL/6J background was established,and the effect of Padi2 knockout was identified by genotyping and RT-qPCR detection.Six-week-old male Padi2-/- mice and wild-type C57BL/6J mice were selected and divided into normal rearing and social isolation groups,with 15 mice per group.The normal rearing group mice were housed with 5 mice per cage,and the social isolation group was housed with 1 mouse per cage,and weighed once a week.After 4 weeks,forced swimming and open field tests were conducted.After the behavioral experiments,brain tissues were taken from mice in each group,and changes in microglia in the brains were detected by immunofluorescence.Results We successfully established Padi2-/- mice.There was no difference in behavior between Padi2-/- mice and C57BL/6J mice in the normal rearing group.After social isolation,compared with C57BL/6J mice,Padi2-/- mice showed a significant increase in depressive symptoms,obvious weight gain,and a significant increase in the number of microglia in brain tissue.Conclusions Padi2 knockout exacerbated depressive-like behaviors and obesity in socially isolated mice,indicating that Padi2 is involved in the progression of depression and may be an effective target for the prevention and treatment of depression.

Objective:To develop an artificial intelligence (AI)-based automatic scoring model for magnetic resonance imaging-detected extramural vascular invasion (AI-mrEMVI) and evaluate its performance and prognostic value in patients with rectal cancer.Methods:In this multicenter retrospective cohort study, a total of 2 501 rectal cancer patients from seven centers between November 2012 and December 2020 were included and divided into completely independent training ( n=1 830) and validation ( n=671) cohorts. A nnUNet-based AI-mrEMVI scoring model was constructed. Manual mrEMVI scores assigned by two radiologists served as the reference standard for accessing the accuracy of the AI-mrEMVI scoring. Kaplan-Meier survival analysis and Cox regression were used to evaluate the prognostic stratification ability of the AI-mrEMVI scores. The concordance index (C-index) was calculated to evaluate prognostic performance. Results:In the validation cohort, the manual mrEMVI scores were 0-2 in 425 patients (63.3%), 3 in 89 (13.4%), and 4 in 157 (23.4%). The AI-mrEMVI model identified 0-2 in 375 patients (55.9%), 3 in 95 (14.2%), and 4 in 201 (30.0%), with an overall accuracy of 81.1% (544/671, 95% CI 77.9%-84.0%). The 3-year disease-free survival (DFS) rates for patients with AI-mrEMVI scores of 0-2, 3, and 4 were 85.2%, 70.0%, and 58.2%, respectively, and the 5-year overall survival (OS) rates were 87.2%, 81.6%, and 62.6%, respectively (DFS: χ2=48.74, P<0.001; OS: χ2=30.04, P<0.001). Multivariable Cox regression showed that for DFS, AI-mrEMVI scores of 3 and 4 were associated with hazard ratios ( HR) of 1.75 (95% CI 1.11-2.77, P=0.016) and 2.65 (95% CI 1.86-3.78, P<0.001), respectively. For OS, an AI-mrEMVI score of 4 was associated with an HR of 2.56 (95% CI 1.62-4.03, P<0.001). The C-index values of the AI-mrEMVI scoring model for predicting DFS and OS were 0.647 (95% CI 0.608-0.686) and 0.650 (95% CI 0.598-0.702), respectively. Conclusion:The proposed AI-mrEMVI automatic scoring model demonstrated high diagnostic accuracy and performed favorably in predicting DFS and OS prognostic risk in patients with rectal cancer.

Peptidylarginine deiminases 2(PADI2)is an enzyme that catalyzes the conversion of arginine residues to citrulline on protein peptides.Aberrant activation of PADI2 can induce excessive tissue inflammation and immune responses,thereby exacerbating the progression of autoimmune diseases(ADs).Through citrullination,PADI2 modifies protein structure and immunogenicity,influencing the production of autoantibodies and regulating the activity of immune cells such as neutrophils and macrophages.This review provides an overview of PADI2's functions and its pivotal role in ADs,with the objective of elucidating the mechanisms underlying ADs pathogenesis and identifying novel therapeutic targets and strategies for related diseases.

Peptidylarginine deiminases 2(PADI2)is an enzyme that catalyzes the conversion of arginine residues to citrulline on protein peptides.Aberrant activation of PADI2 can induce excessive tissue inflammation and immune responses,thereby exacerbating the progression of autoimmune diseases(ADs).Through citrullination,PADI2 modifies protein structure and immunogenicity,influencing the production of autoantibodies and regulating the activity of immune cells such as neutrophils and macrophages.This review provides an overview of PADI2's functions and its pivotal role in ADs,with the objective of elucidating the mechanisms underlying ADs pathogenesis and identifying novel therapeutic targets and strategies for related diseases.

Objective To systematically study the efficacy and safety of KRAS^G12C inhibitors in advanced solid tumors with KRAS^G12C-mutated. Methods Computer searches from PubMed, The Cochrane Library, Web of Science, Embase, CNKI, and CBM databases were conducted to collect clinical studies on KRAS^G12C inhibitors in advanced solid tumors with KRAS^G12C-mutated, with a search time from inception to October 12, 2022. Then, two investigators independently screened the literature, extracted information, assessed the risk of bias in included studies, and performed meta-analyses using RevMan 5.4 software. Results There were four publications included, all of which were single-arm clinical studies. The KRAS^G12C inhibitors that completed clinical phase Ⅰ and Ⅱ trials were sotorasib and adagrasib, with two publications each. A total of 388 and 394 patients were included in the efficacy evaluation and safety evaluation, respectively. Resultsof the Meta-analysis showed that the patients had objective response rate, overall disease control, and disease stabilization rates of 35%, 82%, and 45%, respectively. In addition, the rate of serious adverse events, general adverse events, and all adverse events in patients was 2%, 28%, and 79%, respectively. Moreover, the rate of partial remission of disease in NSCLC patients was 38%. Conclusion The KRAS^G12C inhibitors sotorasib and adagrasib exhibited good efficacy and high safety in advanced solid tumors.

Objective To explore the effects of ginsenoside Rg1 on blood-brain barrier, neuroinflammation and behavioral function of traumatic brain injury (TBI) mouse model.MethodsThe experiment was divided into two parts. In the first part, 27 SPF male BALB/c mice were randomly divided into blank group, sham operation group and TBI model group, with 9 mice in each group. TBI model group was made by controlled cortical impact (CCI) after craniotomy, while sham operation group was only performed craniotomy without any treatment, and the blank group was not treated at all. The effect of modeling was evaluated after operation. In the second part, 50 male BALB/c mice were randomly divided into sham operation group, three different drug dosage groups and solvent (DMSO) control group, with 8 mice in each group. The drug treatment groups were injected with ginsenoside Rg1 at the doses of 10, 20 and 40 mg/kg respectively 6 hours after TBI model had been successfully established, while the DMSO control group was given the same amount of 1% DMSO for one week, twice a day. Modified neurological severity scores (mNSS) were performed on the 1st, 3rd, 7th and 14th day after modeling, and the blood-brain barrier leakage was detected by Western blotting on the 3rd day after modeling. On the 14th and 16th day, the elevated cross maze test and water maze test were used to detect the neurobehavioral function. On the 28th day after anesthesia and perfusion, the brains were taken out, and the neuroinflammation such as activation of microglia and astrocytes was observed by immunofluorescence staining.ResultsThe expression level of MMP-9, a marker of blood-brain barrier, decreased in ginsenoside Rg1 treatment group (P<0.01). The number of microglia （Iba-1 positive) and astrocyte (GFAP positive) cells decreased significantly (P<0.05), which indicated that neuroinflammation was inhibited, and the best effect was achieved at the dosage of 20 mg/kg (P<0.01). The mNSS of mice in ginsenoside Rg1 treatment group were significantly lower than those in DMSO control group (P < 0.01), and the proportion of times they entered the open arm was significantly higher than that in DMSO control group (P < 0.05). The time ratio in the quadrant where the water maze experimental platform was located and the times of crossing the platform were significantly higher than those in control group (P < 0.05), and the dosage of 20 mg/kg had the best effect.ConclusionThe TBI mouse model was successfully constructed and applied to the study of ginsenoside Rg1 repair of mouse traumatic brain injury. Ginsenoside Rg1 can significantly improve blood-brain barrier, alleviate neuroinflammation and improve neurobehavioral function in TBI model mice, and the effect is the most significant at the dose of 20 mg/kg.