Collagen-based materials, renowned for their biocompatibility and minimal immunogenicity, serve as exemplary substrates in a myriad of biomedical applications. Collagen-based micro/nanogels, in particular, are valued for their increased surface area, tunable degradation rates, and ability to facilitate targeted drug delivery, making them instrumental in advanced therapeutics and tissue engineering endeavors. Although extensive reviews on micro/nanogels exist, they tend to cover a wide range of biomaterials and lack a specific focus on collagen-based materials. The current review offers an in-depth look into the manufacturing technologies, drug release mechanisms, and biomedical applications of collagen-based micro/nanogels to address this gap. First, we provide an overview of the synthetic strategies that allow the precise control of the size, shape, and mechanical strength of these collagen-based micro/nanogels by controlling the degree of cross-linking of the materials. These properties are crucial for their performance in biomedical applications. We then highlight the environmental responsiveness of these collagen-based micro/nanogels, particularly their sensitivity to enzymes and pH, which enables controlled drug release under various pathological conditions. The discussion then expands to include their applications in cancer therapy, antimicrobial treatments, bone tissue repair, and imaging diagnosis, emphasizing their versatility and potential in these critical areas. The challenges and future perspectives of collagen-based micro/nanogels in the field are discussed at the end of the review, with an emphasis on the translation to clinical practice. This comprehensive review serves as a valuable resource for researchers, clinicians, and scientists alike, providing insights into the current state and future directions of collagen-based micro/nanogel research and development.
Collagen/chemistry* ; Drug Delivery Systems/methods* ; Humans ; Tissue Engineering/methods* ; Animals ; Biocompatible Materials/chemistry*

[This corrects the article DOI: 10.1016/j.apsb.2021.10.012.].

Receptor-interacting protein kinase 1 (RIPK1) plays an essential role in regulating the necroptosis and apoptosis in cerebral ischemia-reperfusion (I/R) injury. However, the regulation of RIPK1 kinase activity after cerebral I/R injury remains largely unknown. In this study, we found the downregulation of protein arginine methyltransferase 1 (PRMT1) was induced by cerebral I/R injury, which negatively correlated with the activation of RIPK1. Mechanistically, we proved that PRMT1 directly interacted with RIPK1 and catalyzed its asymmetric dimethylarginine, which then blocked RIPK1 homodimerization and suppressed its kinase activity. Moreover, pharmacological inhibition or genetic ablation of PRMT1 aggravated I/R injury by promoting RIPK1-mediated necroptosis and apoptosis, while PRMT1 overexpression protected against I/R injury by suppressing RIPK1 activation. Our findings revealed the molecular regulation of RIPK1 activation and demonstrated PRMT1 would be a potential therapeutic target for the treatment of ischemic stroke.

Objective:To explore the effectiveness of 18F-deuterated-Florbetapir (D3FSP) PET/CT imaging in detecting β-amyloid (Aβ) deposition in the brain and its correlation with plasma biomarkers. Methods:A retrospective analysis was conducted on 79 patients (32 males, 47 females; age(66±7)years) who underwent 18F-D3FSP PET/CT imaging from June 2022 to November 2023 at the First Affiliated Hospital, Guangzhou Medical University, as a part of the Greater Bay Area Healthy Aging Brain Longitudinal Cohort Study (GHABS). Based on the Alzheimer′s Disease Neuroimaging Initiative cohort standard protocol, patients were categorized into cognitively unimpaired (CU) group, mild cognitive impairment (MCI) group, and Alzheimer′s disease (AD) group. Brain regions were segmented using the AW workstation and the SUV ratio (SUVR) was calculated with the cerebellum as the reference region. One-way analysis of variance, Bonferroni correction and Pearson correlation analysis were used to analyze data. The ROC curve analysis was used to analyze the cut-off value and the diagnostic efficacy of SUVR. Results:There were 48, 15 and 16 cases in CU, MCI and AD groups respectively. During the transition from CU to MCI and then to AD, there was a rising trend in SUVR ( F values: 11.15-22.38, all P<0.001) across the whole brain and various brain regions (bilateral frontal lobes, bilateral anterior cingulate gyrus, bilateral precuneus, bilateral parietal lobes, bilateral lateral temporal lobes, and bilateral occipital lobes). SUVRs of the right anterior cingulate gyrus and bilateral precuneus were different between the CU and MCI groups (all P<0.017), and those of bilateral frontal lobes, right precuneus, bilateral parietal lobes, bilateral lateral temporal lobes, and bilateral occipital lobes were different between the MCI and AD groups (all P<0.017). SUVRs of brain regions were negatively correlated with cognitive scale scores ( r values: from -0.57 to -0.37, all P<0.001), and were positively correlated with plasma phosphorylated tau181 (p-tau181, r values: 0.50-0.61, all P<0.001). The ROC curve analysis suggested that the cut-off value of SUVR in the precuneus for distinguishing CU from AD was 1.20, with the AUC, sensitivity, specificity and accuracy of 0.85, 12/16, 91.7%(44/48)and 87.5%(56/64), respectively. Conclusion:18F-D3FSP PET/CT imaging has good clinical application value in assessing the deposition sites and the extent of Aβ in the brain, which is related to clinical cognition and plasma p-tau181 level.

Objective : To explore the risk factors of fever after hysterectomy in patients with uterine fibroids，and establish a nomogram prediction model to provide theoretical guidance for clinical diagnosis and treatment． Methods : The data of patients who underwent hysterectomy due to uterine fibroids were collected and randomly divided into training group and validation group at 6 ∶ 4．Univariate and multivariate analyses were performed by χ2 test and Lo- gistic regression model analysis．The nomogram was established based on the results of multivariate analysis，the calibration curve and receiver operating characteristic，curve were used to evaluate the prediction ability and accura- cy of the nomogram．The decision curve reflected the clinical application value of the model. Results : Among 264 patients in the training group，33 patients had fever，and the postoperative disease rate was 12. 5%．The results of univariate and multivariate analysis showed that anemia，preoperative curettage，operation scope and operation time were independent risk factors for fever after hysterectomy in patients with uterine fibroids．The internal and external calibration curves had a good fit with the actual observation results，with an average error of 0. 031 and 0. 025，re- spectively．The area under receiver operating characteristic curve of the internal and external verification of the no- mogramare 0. 788 and 0. 712，respectively，reflecting the good predictive ability of the model．The decision curve showed that the model had good clinical benefit in a certain threshold range． Conclusion Based on multivariate a- nalysis，the independent risk factors of fever after hysterectomy in patients with uterine fibroids，including anemia， preoperative curettage，operation scope and operation time．In addition，we established a nomogram with good pre- dictive ability and accuracy，which is helpful for clinicians to timely manage fever after hysterectomy in patients with uterine fibroids and guide clinical individualized treatment.

Objective:To investigate effects of extract of pinellia(EP)on proliferation and apoptosis of airway smooth muscle cells(ASMCs)in asthmatic rats and its mechanism.Methods:Asthma rat model was constructed by sensitization and challenge with ovalbumin and rat ASMCs were isolated and cultured.Immunofluorescence staining was used to identify α-actin in ASMCs.After iden-tifying as meeting characteristics of ASMCs,ASMCs were divided into control group,model group,EP group,Compound C group and EP+Compound C group.MTT was used to detect cell proliferation activity;flow cytometry was used to detect cell apoptosis;ELISA was used to detect levels of inflammatory factors IL-6 and TNF-α in cell supernatant;Western blot was used to detect expressions of CyclinD1,proliferating cell nuclear antigen(PCNA),Bcl-2 associated X protein(Bax),Caspase-3,Cleaved-Caspase-3,adenylate activated protein kinase(AMPK),p-AMPK,forkhead box protein O3a(FOXO3a),p-FOXO3a proteins.Results:Immunofluores-cence staining showed that 98%of cells showed green fluorescent filaments in cytoplasm,and α-actin was positively expressed,which proved that cultured cells were ASMCs.Compared with control group,cell OD490,CyclinD1,PCNA protein expressions and IL-6 and TNF-α levels in supernatant of model group were significantly increased,apoptosis rate,Bax,Caspase-3,Cleaved-Caspase-3 protein expressions and p-AMPK/AMPK,p-FOXO3a/FOXO3a levels were significantly reduced(P<0.05);compared with model group,cell OD490,CyclinD1,PCNA protein expressions and IL-6,TNF-α levels in supernatant of EP group were significantly reduced,apoptosis rate,Bax,Caspase-3,Cleaved-Caspase-3 protein expressions,and p-AMPK/AMPK,p-FOXO3a/FOXO3a levels were significantly increased(P<0.05),the above corresponding indicators of Compound C group showed opposite trend(P<0.05);compared with EP group,cell OD490,CyclinD1,PCNA protein expressions and IL-6,TNF-α levels in supernatant of EP+Compound C group were signifi-cantly increased,apoptosis rate,Bax,Caspase-3,Cleaved-Caspase-3 protein expressions,and p-AMPK/AMPK,p-FOXO3a/FOXO3a levels were significantly reduced(P<0.05).Conclusion:EP may inhibit proliferation of ASMCs and promote cell apoptosis in asthmatic rats by activating AMPK/FOXO3a pathway.

【Objective】 To construct and validate a risk prediction model for cognitive impairment after stroke based on demographic, clinical, and neuroimaging characteristics. 【Methods】 Through the medical record system, we collected all data of the patients. We finished cognitive function testing three months after the indexed stroke. The Mini-Mental State Examination Scale score≤26 was defined as cognitive dysfunction. Optimal subset regression analysis was used to screen variables, Logistic regression analysis was used to construct a predictive model for cognitive impairment, and C-index, calibration chart and clinical decision curve analyses were used to evaluate the discrimination, consistency, and clinical availability of the model. And nomograms were used to express the performance of the model. 【Results】 Seven variables were selected: cognitive function before stroke, age, years of education, National Institutes of Health Stroke Scale score at admission, history of ischemic heart disease, the number of old lacunar infarct lesions, and medial temporal lobe atrophy scale. The prediction model had a C-index of 0.845 (95% CI: 0.805-0.885). The clinical decision curve showed that the model had a positive net benefit when the threshold probability was 9.0%-90.0%. 【Conclusion】 The predictive model of cognitive impairment in stroke patients has good predictive efficiency and provides an effective assessment tool for screening high-risk cases of cognitive impairment in patients with stroke of various subtypes.

Objective:To investigate the predictive value of emergency bedside echocardiography on acute pancreatitis (AP) severity by assessing cardiac dysfunction.Methods:The clinical data used in this study was prospectively collected from AP patients in the Emergency Department of Beijing Shijitan Hospital, Capital Medical University from June 2018 to December 2020. According to the Atlanta Classification revised at the 2012 Atlanta International Conference, patients were divided into three groups of mild acute pancreatitis (MAP), moderate-severe acute pancreatitis (MSAP), and severe acute pancreatitis (SAP). The differences of comprehensive score index, blood-related index, and echocardiography-related index were compared among the three groups. Besides, the predictive factors of SAP were analyzed by Logistic regression, receiving operating characteristic (ROC) curves of subjects were drawn, and the area under the curve (AUC) was analyzed to evaluate the predictive efficiency.Results:A total of 116 patients were enrolled in this study. Compared with the non-SAP group (MAP group+MSAP group), acute physiology and chronic health evaluation Ⅱ(APACHE Ⅱ) score, sequential organ failure assessment (SOFA) score, Ranson score, procalcitonin, cardiac troponin I (cTnI), N-terminal pro-brain natriuretic peptide (NTproBNP), EDD, A-peak, E/A, E'/A', and stroke volume (SV) exhibited significant differences (all P<0.05). There was no significant difference in end-systolic diameter, E-peak, and left ventricular ejection fraction among the three groups ( P>0.05). Logistic regression analysis revealed that SOFA score, Ranson score, cTnI, NTproBNP, E'/A', and SV were important predictors of AP severity (all AUC>0.7). Moreover, the predictive value of echocardiography cardiac function assessment index (E'/A' +SV, AUC=0.969) and score index (SOFA score +Ranson score, AUC=0.989) for SAP was better than that of blood index (cTnI+NTproBNP, AUC=0.732). Conclusions:Echocardiographic indicators E'/A' and SV have acceptable predictive values for SAP, providing certain guiding significance for the clinical treatment of AP patients.

The main components of the gastric tumor stroma consist of cells in both the immune and non-immune microenvironments. The effectiveness of a series of therapeutic measures such as adjuvant chemotherapy is closely related to the composition of gastric tumor stroma. By analyzing the components in the gastric tumor stroma, we understand the characteristics of the constituents in the pathological structure of gastric cancer, and further explore the connection of each component of the stroma with pathological structure and regulatory mechanisms of stroma components on the occurrence and progression of gastric tumors. Combined with artificial intel-ligence technology to analyze the pathological features related to stroma components of tumor microenvironment, the dynamic changes of immune microenvironment and non-immune microen-vironment in gastric cancer are expected to reveal.