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 remote ischemic preconditioning (RIPC) on myocardial injury after non-cardiac surgery (MINS) in elderly patients with hip fracture.Methods:A prospective randomized controlled trial was conducted on 78 elderly patients with hip fracture admitted to the Seventh Medical Center of the PLA General Hospital between October 2023 and September 2024. The patients were divided into RIPC group and non-RIPC group using a random number table. They were treated with closed reduction internal fixation, open reduction internal fixation, or hip arthroplasty for hip fracture under regional anesthesia. The RIPC group received RIPC intervention on the day before surgery and after entering the operating room on the day of surgery (3 cycles of 5-minute upper limb exsanguination followed by 5-minute reperfusion using an inflatable tourniquet cuff). The non-RIPC group received the same perioperative management as the RIPC group except RIPC. Plasma high-sensitivity cardiac troponin I (hs-cTnI) concentrations were measured at admission, immediately after surgery, on the morning of the first postoperative day, and on the morning of the third postoperative day and MINS incidence was calculated based on the hs-cTnI concentrations. The incidence of MINS within 3 days postoperatively and the intraoperative complications were compared in the overall cohort and in age-stratified groups (<80 years, ≥80 years). The local adverse reactions at the RIPC application sites were observed within 3 days after surgery.Results:Among the 78 elderly patients with hip fracture, including 21 males and 57 females, aged 60-99 years [79.5(70.0, 87.0)years], 40 were assigned to the RIPC group and 38 to the non-RIPC group. No significant difference was found in the general data of the two groups. There was no significant difference in the overall MINS incidence between the two groups ( P>0.05). In the patients aged <80 years, no MINS incidence was found (0/21) in the RIPC group, compared with 22% (4/18) in the non-RIPC group ( P<0.05), while in the patients aged ≥80 years, no significant difference in MINS incidence was observed between the two groups ( P>0.05). There were no significant differences in intraoperative complication rates in the overall cohort, patients aged <80 years, or patients aged ≥80 years ( P>0.05). None of the patients had local adverse reactions at the RIPC application sites. Conclusion:For elderly patients with hip fracture who received regional anesthesia, RIPC can significantly reduce the incidence of MINS in patients aged <80 years, but exerts no significant effect on MINS incidence in the overall cohort or in patients aged ≥80 years.

When the epidemiology of infectious diseases is more complex, it is often difficult for disease prediction studies based on a single model to capture the multidimensional nature of disease transmission. In recent years, combining different models to improve infectious disease prediction has gradually become a research trend and hotspot. Existing studies have shown that combined models usually have higher prediction performance and better generalization ability. The current combined models mainly combine machine learning and other models, including time-series models, dynamic models, etcetera. In addition, integrated learning that combines diverse machine learning techniques also holds significant importance across various research domains. This paper reviews the progress of applying combined models around machine learning in infectious disease prediction to promote the innovation and practice of combined models for infectious diseases and help to build smarter and more efficient infectious disease early warning and prediction methods and systems.

Methods such as compartmental models, agent-based models, time series models, and machine learning can be used for the prediction of infectious disease incidence. When disease epidemics are complex, it is often difficult to use a single model to comprehensively and accurately capture the multi dimensional nature of the disease. Exploring the combined application of different models has gradually become a research trend and hotspot in recent years, and the prediction performance of combined models is often better than that of single ones. Current research related to combined models mainly focus on machine learning or compartmental models. In this review, we focus on the combination of compartmental models and other models, and summarize their combination principles, application progress, and advantages or disadvantages for the purpose of promoting the innovation and application of combined models for infectious disease incidence prediction, and establishing a more intelligent and efficient early warning and prediction method or systems for the prevention and control of infectious disease.

ObjectiveTo investigate the intervention effects of Suanzaoren Tang on depression model rats induced by isolation combined with chronic unpredictable mild stress （CUMS）， and to examine its influence on the c-Jun N-terminal kinase （JNK）/proto-oncogene protein （c-Myc）/tumor suppressor protein 53 （p53） signaling pathway， thereby revealing its potential functional mechanism. MethodsA total of 72 male SD rats were randomly divided into six groups using a strict random number table： blank group， model group， fluoxetine group （3.6 mg·kg^-1）， and high-， medium-， and low-dose Suanzaoren Tang groups （10， 5， 2.5 g·kg^-1），with 12 rats in each group. A depression model was established using isolation combined with CUMS. Fluoxetine and different doses of Suanzaoren Tang were administered continuously for 28 days. Behavioral indicators such as sucrose water consumption and open field test scores were recorded. Western blot and immunohistochemistry （IHC） were employed to analyze the expression of key proteins in the JNK/c-Myc/p53 signaling pathway， and the terminal deoxynucleotidyl transferase dUTP nick end labeling （TUNEL） assay was used to evaluate the number of apoptotic cells in the hippocampus. ResultsCompared with the blank group， the model group exhibited a significantly reduced sucrose preference index （P<0.01）， a lower total score of horizontal and vertical movements in the open field test （P<0.01）， significantly increased expression of JNK， c-Myc， and p53 proteins in the hippocampus （P<0.01）， and a higher number of TUNEL-positive cells in the hippocampus （P<0.01）. Compared with the model group， the sucrose preference index and the total score of horizontal and vertical movements in the open field test significantly increased in the high- and medium-dose Suanzaoren Tang groups and the fluoxetine group （P<0.05， P<0.01）. The expression of JNK， c-Myc， and p53 proteins significantly decreased in all Suanzaoren Tang groups （high， medium， and low doses） and the fluoxetine group （P<0.05， P<0.01）. The number of TUNEL-positive cells in the hippocampus also significantly decreased in these groups （P<0.01）. ConclusionSuanzaoren Tang can regulate the expression of JNK/c-Myc/p53 proteins in the hippocampus of depression model rats， and its antidepressant mechanism may be related to its protective effect on hippocampal neurons.

When the epidemiology of infectious diseases is more complex, it is often difficult for disease prediction studies based on a single model to capture the multidimensional nature of disease transmission. In recent years, combining different models to improve infectious disease prediction has gradually become a research trend and hotspot. Existing studies have shown that combined models usually have higher prediction performance and better generalization ability. The current combined models mainly combine machine learning and other models, including time-series models, dynamic models, etcetera. In addition, integrated learning that combines diverse machine learning techniques also holds significant importance across various research domains. This paper reviews the progress of applying combined models around machine learning in infectious disease prediction to promote the innovation and practice of combined models for infectious diseases and help to build smarter and more efficient infectious disease early warning and prediction methods and systems.

Methods such as compartmental models, agent-based models, time series models, and machine learning can be used for the prediction of infectious disease incidence. When disease epidemics are complex, it is often difficult to use a single model to comprehensively and accurately capture the multi dimensional nature of the disease. Exploring the combined application of different models has gradually become a research trend and hotspot in recent years, and the prediction performance of combined models is often better than that of single ones. Current research related to combined models mainly focus on machine learning or compartmental models. In this review, we focus on the combination of compartmental models and other models, and summarize their combination principles, application progress, and advantages or disadvantages for the purpose of promoting the innovation and application of combined models for infectious disease incidence prediction, and establishing a more intelligent and efficient early warning and prediction method or systems for the prevention and control of infectious disease.

Objective:To investigate the effects of remote ischemic preconditioning (RIPC) on myocardial injury after non-cardiac surgery (MINS) in elderly patients with hip fracture.Methods:A prospective randomized controlled trial was conducted on 78 elderly patients with hip fracture admitted to the Seventh Medical Center of the PLA General Hospital between October 2023 and September 2024. The patients were divided into RIPC group and non-RIPC group using a random number table. They were treated with closed reduction internal fixation, open reduction internal fixation, or hip arthroplasty for hip fracture under regional anesthesia. The RIPC group received RIPC intervention on the day before surgery and after entering the operating room on the day of surgery (3 cycles of 5-minute upper limb exsanguination followed by 5-minute reperfusion using an inflatable tourniquet cuff). The non-RIPC group received the same perioperative management as the RIPC group except RIPC. Plasma high-sensitivity cardiac troponin I (hs-cTnI) concentrations were measured at admission, immediately after surgery, on the morning of the first postoperative day, and on the morning of the third postoperative day and MINS incidence was calculated based on the hs-cTnI concentrations. The incidence of MINS within 3 days postoperatively and the intraoperative complications were compared in the overall cohort and in age-stratified groups (<80 years, ≥80 years). The local adverse reactions at the RIPC application sites were observed within 3 days after surgery.Results:Among the 78 elderly patients with hip fracture, including 21 males and 57 females, aged 60-99 years [79.5(70.0, 87.0)years], 40 were assigned to the RIPC group and 38 to the non-RIPC group. No significant difference was found in the general data of the two groups. There was no significant difference in the overall MINS incidence between the two groups ( P>0.05). In the patients aged <80 years, no MINS incidence was found (0/21) in the RIPC group, compared with 22% (4/18) in the non-RIPC group ( P<0.05), while in the patients aged ≥80 years, no significant difference in MINS incidence was observed between the two groups ( P>0.05). There were no significant differences in intraoperative complication rates in the overall cohort, patients aged <80 years, or patients aged ≥80 years ( P>0.05). None of the patients had local adverse reactions at the RIPC application sites. Conclusion:For elderly patients with hip fracture who received regional anesthesia, RIPC can significantly reduce the incidence of MINS in patients aged <80 years, but exerts no significant effect on MINS incidence in the overall cohort or in patients aged ≥80 years.

Objective:To explore the causal relationship between human immune cells and hypertrophic scar (HS) using two-sample bidirectional Mendelian randomization (MR) method.Methods:This study was based on two-sample MR method, and the datasets of 731 immune cells and HS were obtained from the genome-wide association study (GWAS) catalog database and Finngen database, respectively. A significance threshold was established to discern single nucleotide polymorphism (SNP) significantly correlated with immune cells or HS, thereby eliminating the impact of weak instrumental variable bias. The inverse variance weighted (IVW) method (meanwhile, the Benjamini-Hochberg (BH) procedure of false discovery rate (FDR) to adjust P values) was used for preliminary detection of the causal relationship between immune cells and HS and screen the immune cells that had a significant causal relationship with HS. Further, the causal relationship between the selected immune cells and HS was detected through five two-sample MR methods: IVW method, weighted median method, simple mode method, weighted mode method, and MR-Egger method, and the scatter plot was drawn. SNPs conformed to the hypothesis were subjected to Cochran Q test for heterogeneity assessment, MR-Egger regression coupled with MR-PRESSO to eliminate horizontal pleiotropic effects, and a leave-one-out analysis was also conducted to determine if significant results were driven by individual SNP. Finally, the IVW method contained in the two-sample MR analysis was utilized to inversely examine the causal relationship between HS and immune cells. Results:The number of SNPs in 731 immune cells reaching the significance threshold varied from 7 to 1 786, while in HS, 119 SNPs met the significance threshold, with the F values of all SNPs being greater than 10, suggesting a low likelihood of bias from weak instrumental variables. The IVW method revealed that 60 types of immune cells potentially had a causal relationship with HS (with all P values <0.05), and after adjustment using the BH method, only CD45RA and CD39 positive regulatory T cell (Treg) maintained a potentially strong causal relationship with HS ( PFDR<0.05). The IVW method (with odds ratio of 1.16 and 95% confidence interval of 1.08-1.24, P<0.05, PFDR<0.05), weighted median method (with odds ratio of 1.16 and 95% confidence interval of 1.05-1.28, P<0.05), weighted mode method (with odds ratio of 1.14 and 95% confidence interval of 1.02-1.27, P<0.05), and MR-Egger method (with odds ratio of 1.18 and 95% confidence interval of 1.07-1.30, P<0.05) of scatter plot all suggested a causal relationship between the 14 SNPs of CD45RA and CD39 positive Treg and risk of HS, only simple mode method of scatter plot suggested a not obvious relationship between the 14 SNPs of CD45RA and CD39 positive Treg and risk of HS ( P>0.05). Cochran Q test indicated no heterogeneity in the causal relationship between CD45RA on CD39 positive Treg and HS ( P>0.05). MR-Egger regression and MR-PRESSO analyses showed that there was no horizontal pleiotropy in the significant causal relationship between CD45RA and CD39 positive Treg and HS ( P>0.05). Leave-one-out analysis confirmed that the significant causal relationship between CD45RA and CD39 positive Treg and HS remained stable after sequentially removing individual SNP. Reverse two-sample MR analysis showed that HS had no potential causal relationship with any of the 731 types of immune cells ( P>0.05). Conclusions:From the perspective of genetics, it is revealed that immune cells CD45RA and CD39 positive Treg may increase the risk of HS.

Bone Transplantation/adverse effects* ; Transplantation, Autologous/adverse effects*