The activation proteins released by fibroblasts in the tumor microenvironment regulate tumor growth, migration, and treatment response, thereby influencing tumor progression and therapeutic outcomes. Owing to the proliferation and metastasis of tumors, fibroblast activation protein (FAP) is typically highly expressed in the tumor stroma, whereas it is nearly absent in adult normal tissues and benign lesions, making it an attractive target for precision medicine. Radiolabeled agents targeting FAP have the potential for targeted cancer diagnosis and therapy. This comprehensive review aims to describe the evolution of FAPI-based radiopharmaceuticals and their structural optimization. Within its scope, this review summarizes the advances in the use of radiolabeled small molecule inhibitors for tumor imaging and therapy as well as the modification strategies for FAPIs, combined with insights from structure-activity relationships and clinical studies, providing a valuable perspective for radiopharmaceutical clinical development and application.

Objective:To investigate the effects of scalp acupuncture of Baihui and Qubin acupoints combined with running track exercise on the neurological function of rats with middle cerebral artery occlusion(MCAO)cerebral ischemia and its regulatory effect on the Nrf2/HO-1 pathway by focusing on oxidative stress injury.Methods:A total of 40 male SD rats of SPF grade were selected and the cerebral ischemia model was established by ligation method.Among them,30 rats with successful modeling were randomly divided into the model group,the scalp-acupuncture group,and the combined group,with 10 rats in each group.Another 10 SPF male SD rats were used as the sham operation group.In the scalp-acupuncture group,electroacupuncture was applied to Baihui and Qubin acupoints.In the combined group,both electroacupuncture and running track exercise were applied.The treatment was carried out 6 times/week for a total of 4 weeks.The neurobehavioural function of rats was evaluated by Bederson Neurological Function Assessment.Pathological changes of rat brain tissue were observed by HE staining.SOD,serum MDA and GSH-px levels were detected by kit.The protein expression levels of Nrf2 and HO-1 in the rat brain tissue were detected by Western blot.Results:Compared with the sham-operated group,Bederson's neurological function score in the model group was significantly higher(P＜0.05),the pathological damage of HE-stained brain tissue was obvious,the level of MDA significantly increased(P＜0.05),the levels of SOD and GSH-px decreased(P＜0.05),and the protein expression levels of Nrf2 and HO-1 were significantly reduced(P＜0.05).Compared with the model group,Bederson neurological function scores were reduced in each treatment group(P＜0.05),the brain histopathological damage was alleviated,the level of MDA was reduced(P＜0.05),the levels of SOD and GSH-px was elevated(P＜0.05),and the protein expression levels of Nrf2 and HO-1 were significantly increased(P＜0.05).The Bederson neurological function score and MDA level in the combined group were lower than those in the scalp-acupuncture group(P＜0.05),and the levels of SOD and GSH-px and the expression levels of Nrf2 and HO-1 proteins were significantly higher than those in the scalp-acupuncture group(P＜0.05).Conclusions:Scalp acupuncture can improve the neurobehavioural dysfunction and pathological damage caused by cerebral ischemia,increase the antioxidant capacity,and the specific mechanism may be related to the activation of the Nrf2/HO-1 pathway.And scalp acupuncture combined with running track exercise has a synergistic effect and is more advantageous for treatment.

Objective To explore the feasibility of a deep learning model based on early fundus lesions without manual segmentation in pan-retinal images for predicting diabetic kidney disease(DKD)and evaluating the enhancing effects of different binocular fusion strategies.Methods A retrospective cohort of 353 patients with type 2 diabetes mellitus(T2DM)admitted to the Endocrinology Department of Jiangdu People's Hospital Affiliated to Yangzhou University between December 2022 and March 2024 was analyzed.Patients were divided into DKD(n=114)and non-diabetic kidney disease(NDKD)(n=239)group based on the presence of DKD.First,a U-Net-based pre-trained automatic segmentation model was developed to process panoramic fundus retinal images.Subsequently,left and right eye deep learning models were constructed using ResNet152 under a five-fold cross-validation framework(70%training,30%validation).Three binocular fusion strategies were implemented:result fusion,feature fusion,and image fusion models.Model performance was evaluated using the area under the receiver operating characteristic(ROC)curve(AUC).DeLong test was used to compare AUC differences among models,while net reclassification index(NRI)and decision curve analysis(DCA)were used to assess clinical utility.Results Six prediction models were developed:clinical parameter model,left fundus model,right fundus model,binocular image fusion model,binocular result fusion model,and binocular feature fusion model.The Transformer-based binocular feature fusion model achieved the highest AUC in both training and validation sets(0.864 and 0.658,respectively).DeLong tests revealed significant AUC superiority of the Transformer model over the other five models in the training set(all P<0.001),though no significant differences were observed in the validation set(all P>0.05).NRI analysis showed negative values for all comparisons with the Transformer model(training set:-0.255,-0.244,-0.289,-0.426,-0.163;validation set:-0.060,-0.016,-0.028,-0.105,-0.033,respectively),indicating its optimal predictive performance.DCA further demonstrated greater net benefit for the Transformer-based fusion model.Conclusions The deep learning model constructed using early fundus lesions without manual segmentation in pan-retinal images can predict DKD.The Transformer-based fusion strategy present the best performance,providing a novel approach for further optimization and development of tools to predict DKD in the future.

Objective:To investigate the effects of scalp acupuncture of Baihui and Qubin acupoints combined with running track exercise on the neurological function of rats with middle cerebral artery occlusion(MCAO)cerebral ischemia and its regulatory effect on the Nrf2/HO-1 pathway by focusing on oxidative stress injury.Methods:A total of 40 male SD rats of SPF grade were selected and the cerebral ischemia model was established by ligation method.Among them,30 rats with successful modeling were randomly divided into the model group,the scalp-acupuncture group,and the combined group,with 10 rats in each group.Another 10 SPF male SD rats were used as the sham operation group.In the scalp-acupuncture group,electroacupuncture was applied to Baihui and Qubin acupoints.In the combined group,both electroacupuncture and running track exercise were applied.The treatment was carried out 6 times/week for a total of 4 weeks.The neurobehavioural function of rats was evaluated by Bederson Neurological Function Assessment.Pathological changes of rat brain tissue were observed by HE staining.SOD,serum MDA and GSH-px levels were detected by kit.The protein expression levels of Nrf2 and HO-1 in the rat brain tissue were detected by Western blot.Results:Compared with the sham-operated group,Bederson's neurological function score in the model group was significantly higher(P＜0.05),the pathological damage of HE-stained brain tissue was obvious,the level of MDA significantly increased(P＜0.05),the levels of SOD and GSH-px decreased(P＜0.05),and the protein expression levels of Nrf2 and HO-1 were significantly reduced(P＜0.05).Compared with the model group,Bederson neurological function scores were reduced in each treatment group(P＜0.05),the brain histopathological damage was alleviated,the level of MDA was reduced(P＜0.05),the levels of SOD and GSH-px was elevated(P＜0.05),and the protein expression levels of Nrf2 and HO-1 were significantly increased(P＜0.05).The Bederson neurological function score and MDA level in the combined group were lower than those in the scalp-acupuncture group(P＜0.05),and the levels of SOD and GSH-px and the expression levels of Nrf2 and HO-1 proteins were significantly higher than those in the scalp-acupuncture group(P＜0.05).Conclusions:Scalp acupuncture can improve the neurobehavioural dysfunction and pathological damage caused by cerebral ischemia,increase the antioxidant capacity,and the specific mechanism may be related to the activation of the Nrf2/HO-1 pathway.And scalp acupuncture combined with running track exercise has a synergistic effect and is more advantageous for treatment.

Objective To explore the feasibility of a deep learning model based on early fundus lesions without manual segmentation in pan-retinal images for predicting diabetic kidney disease(DKD)and evaluating the enhancing effects of different binocular fusion strategies.Methods A retrospective cohort of 353 patients with type 2 diabetes mellitus(T2DM)admitted to the Endocrinology Department of Jiangdu People's Hospital Affiliated to Yangzhou University between December 2022 and March 2024 was analyzed.Patients were divided into DKD(n=114)and non-diabetic kidney disease(NDKD)(n=239)group based on the presence of DKD.First,a U-Net-based pre-trained automatic segmentation model was developed to process panoramic fundus retinal images.Subsequently,left and right eye deep learning models were constructed using ResNet152 under a five-fold cross-validation framework(70%training,30%validation).Three binocular fusion strategies were implemented:result fusion,feature fusion,and image fusion models.Model performance was evaluated using the area under the receiver operating characteristic(ROC)curve(AUC).DeLong test was used to compare AUC differences among models,while net reclassification index(NRI)and decision curve analysis(DCA)were used to assess clinical utility.Results Six prediction models were developed:clinical parameter model,left fundus model,right fundus model,binocular image fusion model,binocular result fusion model,and binocular feature fusion model.The Transformer-based binocular feature fusion model achieved the highest AUC in both training and validation sets(0.864 and 0.658,respectively).DeLong tests revealed significant AUC superiority of the Transformer model over the other five models in the training set(all P<0.001),though no significant differences were observed in the validation set(all P>0.05).NRI analysis showed negative values for all comparisons with the Transformer model(training set:-0.255,-0.244,-0.289,-0.426,-0.163;validation set:-0.060,-0.016,-0.028,-0.105,-0.033,respectively),indicating its optimal predictive performance.DCA further demonstrated greater net benefit for the Transformer-based fusion model.Conclusions The deep learning model constructed using early fundus lesions without manual segmentation in pan-retinal images can predict DKD.The Transformer-based fusion strategy present the best performance,providing a novel approach for further optimization and development of tools to predict DKD in the future.

Objective This study aims at establishing a teaching catalog and content for breast rare dis-eases and developing the syllabus for the breast rare disease using integrated multimodality of case-/problem-/resource-based learning(CBL+PBL+RBL).Methods By conducting bibliometrics co-occurrence analysis,we collected 6291 articles on breast rare disease published from January,1975 to June,2024.Additionally,we re-trieved the Textbook on Rare Diseases,the Catalog of Chinese Rare Disease,and Second Batch of Rare Dis-ease Catalog and then decided the teaching content.Results From 16,387 keywords,1000(6.1％)keywords were identified through co-occurrence analysis,including 50(0.3％)candidate diseases.These were classified into three categories:rare primary breast diseases,rare genetic mutation-related diseases associated with breast cancer,and rare systemic multi-system diseases involving the breast.From the candidate list,20(0.1％)rare primary breast diseases were further selected for their notable clinical teaching significance,and significant multi-systemic diseases affecting the breast,whether related to gene mutations or not.Teaching plans were draf-ted using a diversified parallel teaching approaches,taking into account the characteristics of different diseases and the focus of different teaching methods.Conclusions This study initiated the development of the teaching content for breast rare diseases and developed the teaching syllabus using the CBL+PBL+RBL integrated multi teaching model and targeting each rare breast disease for the critical point for teaching.

Purpose To explore the feasibility of targeted diagnosis and localization of prostate cancer via background free differential ultrasound molecular imaging based on prostate-specific membrane antigen (PSMA) targeted ultrasound nanobubbles (NB). Materials and Methods Targeted PSMA-NB and non-targeted NB were constructed. The targeting ability of PSMA-NB on human prostate tumor 22RV1 cells (PSMA positive expression) and PC-3 cells (PSMA negative expression) was determined in vitro. Ten nude mouse models of human prostate tumor 22RV1 cells (n=5) and PC-3 cells (n=5) were constructed. PSMA-NB was injected into the rat tail vein,and in-situ blasting was performed. Ultrasound molecular images before and after blasting were collected,using destruction supplement post-processing technology to obtain and compare the differential ultrasound molecular imaging effects between the two groups. Results The particle size of PSMA-NB and NB were (363.7±24.4) nm and (236.0±55.2) nm,with statistical difference (t=3.19,P=0.007),respectively. Cell targeting results showed that PSMA-NB only adhered to the nucleus with positive PSMA-expression. Animal experiments indicated that the differential ultrasonic molecular images of PSMA positive expression group only showed the highly enhanced area of contrast agent at the tumor site,with no background noise. Conclusion Background free differential ultrasound molecular images can be used for precise targeted diagnosis and localization of PSMA positive prostate cancer,which is constructed based on PSMA targeted ultrasound nanobubbles.

Purpose To explore the feasibility of targeted diagnosis and localization of prostate cancer via background free differential ultrasound molecular imaging based on prostate-specific membrane antigen (PSMA) targeted ultrasound nanobubbles (NB). Materials and Methods Targeted PSMA-NB and non-targeted NB were constructed. The targeting ability of PSMA-NB on human prostate tumor 22RV1 cells (PSMA positive expression) and PC-3 cells (PSMA negative expression) was determined in vitro. Ten nude mouse models of human prostate tumor 22RV1 cells (n=5) and PC-3 cells (n=5) were constructed. PSMA-NB was injected into the rat tail vein,and in-situ blasting was performed. Ultrasound molecular images before and after blasting were collected,using destruction supplement post-processing technology to obtain and compare the differential ultrasound molecular imaging effects between the two groups. Results The particle size of PSMA-NB and NB were (363.7±24.4) nm and (236.0±55.2) nm,with statistical difference (t=3.19,P=0.007),respectively. Cell targeting results showed that PSMA-NB only adhered to the nucleus with positive PSMA-expression. Animal experiments indicated that the differential ultrasonic molecular images of PSMA positive expression group only showed the highly enhanced area of contrast agent at the tumor site,with no background noise. Conclusion Background free differential ultrasound molecular images can be used for precise targeted diagnosis and localization of PSMA positive prostate cancer,which is constructed based on PSMA targeted ultrasound nanobubbles.

Liver fibrosis is a reversible pathological process caused by chronic liver damage and a major risk factor for hepatocellular carcinoma (HCC). Hepatic stellate cell (HSC) activation is considered the main target for liver fibrosis therapy. However, the efficiency of this strategy is limited due to the complex microenvironment of liver fibrosis, including excessive extracellular matrix (ECM) deposition and hypoxia-induced imbalanced ECM metabolism. Herein, nilotinib (NIL)-loaded hyaluronic acid (HA)-coated Ag@Pt nanotriangular nanozymes (APNH NTs) were developed to inhibit HSCs activation and remodel the microenvironment of liver fibrosis. APNH NTs efficiently eliminated intrahepatic reactive oxygen species (ROS) due to their inherent superoxide dismutase (SOD) and catalase (CAT) activities, thereby downregulating the expression of NADPH oxidase-4 (NOX-4) and inhibiting HSCs activation. Simultaneously, the oxygen produced by the APNH NTs further alleviated the hypoxic microenvironment. Importantly, the released NIL promoted collagen depletion by suppressing the expression of tissue inhibitor of metalloproteinase-1 (TIMP-1), thus synergistically remodeling the microenvironment of liver fibrosis. Notably, an in vivo study in CCl₄-induced mice revealed that APNH NTs exhibited significant antifibrogenic effects without obvious long-term toxicity. Taken together, the data from this work suggest that treatment with the synthesized APNH NTs provides an enlightening strategy for remodeling the microenvironment of liver fibrosis with boosted antifibrogenic activity.

Acute respiratory distress syndrome (ARDS) is a common clinical critical condition of the respiratory system, with a high fatality rate and lack of effective drug treatment, hence it is a global medical problem to be solved urgently. Recently, with the in-depth research on extracellular vesicles (EVs) at home and abroad, more and more evidences suggest that EVs play a critical role in the initiation, development and progression of ARDS and have potential clinical application value. The role of different cells derived EVs in ARDS will be reviewed in this paper.