BACKGROUND:Flap transplantation technique is a commonly used surgical procedure for the treatment of severe tissue defects,but postoperative flap necrosis is easily triggered by ischemia-reperfusion injury.Therefore,it is still an important research topic to improve the survival rate of transplanted flaps. OBJECTIVE:To review the pathogenesis and latest treatment progress of flap ischemia-reperfusion injury. METHODS:CNKI,WanFang Database and PubMed database were searched for relevant literature published from 2014 to 2024.The search terms used were"flap,ischemia-reperfusion injury,inflammatory response,oxidative stress,Ca2+overload,apoptosis,mesenchymal stem cells,platelet-rich plasma,signaling pathways,shock wave,pretreatment"in Chinese and English.After elimination of irrelevant literature,poor quality and obsolete literature,77 documents were finally included for review. RESULTS AND CONCLUSION:Flap ischemia/reperfusion injury may be related to pathological factors such as inflammatory response,oxidative stress response,Ca2+overload,and apoptosis,which can cause apoptosis of vascular endothelial cells,vascular damage and microcirculation disorders in the flap,and eventually lead to flap necrosis.Studies have found that mesenchymal stem cell transplantation,platelet-rich plasma,signaling pathway modulators,shock waves,and pretreatment can alleviate flap ischemia/reperfusion injuries from different aspects and to varying degrees,and reduce the necrosis rate and necrosis area of the grafted flap.Although there are many therapeutic methods for skin flap ischemia/reperfusion injury,a unified and effective therapeutic method has not yet been developed in the clinic,and the advantages and disadvantages of various therapeutic methods have not yet been compared.Most of the studies remain in the stage of animal experiments,rarely involving clinical observations.Therefore,a lot of research is required in the future to gradually move from animal experiments to the clinic in order to better serve the clinic.

ObjectivePhotoacoustic pump-probe imaging can effectively eliminate the interference of blood background signal in traditional photoacoustic imaging, and realize the imaging of weak phosphorescence molecules and their triplet lifetimes in deep tissues. However, background differential noise in photoacoustic pump-probe imaging often leads to large fitting results of phosphorescent molecule concentration and triplet lifetime. Therefore, this paper proposes a novel triplet lifetime fitting method for photoacoustic pump-probe imaging. By extracting the phase of the triplet differential signal and the background noise, the fitting bias caused by the background noise can be effectively corrected. MethodsThe advantages and feasibility of the proposed algorithm are verified by numerical simulation, phantom and in vivo experiments, respectively. ResultsIn the numerical simulation, under the condition of noise intensity being 10% of the signal amplitude, the new method can optimize the fitting deviation from 48.5% to about 5%, and has a higher exclusion coefficient (0.88>0.79), which greatly improves the fitting accuracy. The high specificity imaging ability of photoacoustic pump imaging for phosphorescent molecules has been demonstrated by phantom experiments. In vivo experiments have verified the feasibility of the new fitting method proposed in this paper for fitting phosphoometric lifetime to monitor oxygen partial pressure content during photodynamic therapy of tumors in nude mice. ConclusionThis work will play an important role in promoting the application of photoacoustic pump-probe imaging in biomedicine.

Objective: Previous studies have discovered a correlation between cigarette smoking and cortical thickness and surface area, but the causal relationship remains unclear. The objective of this investigation is to scrutinize the causal association between them. Methods: To derive summary statistics from a genome-wide association study (GWAS) on cortical thickness, surface area, and four smoking behaviors: 1) age of initiation of regular smoking (AgeSmk); 2) smoking initiation (SmkInit); 3) smoking cessation (SmkCes); 4) cigarettes per day (CigDay). Linkage disequilibrium score regression (LDSC) was employed to examine genetic association analysis. Furthermore, for traits with significant genetic associations, Mendelian randomization (MR) analyses were conducted. Results: The LDSC analysis revealed nominal genetic correlations between AgeSmk and right precentral surface area, left caudal anterior cingulate surface area, left cuneus surface area, left inferior parietal surface area, and right caudal anterior cingulate thickness, as well as between CigDay and left caudal middle frontal surface area, between SmkCes and left entorhinal thickness, and between SmkInit and left rostral anterior cingulate surface area, right rostral anterior cingulate thickness, and right superior frontal thickness (rg=-0.36–0.29, p<0.05). MR analysis showed a unidirectional causal association between left caudal middle frontal surface area and CigDay (βIVW=0.056, pBonferroni=2×10-4). Conclusion Left caudal middle frontal surface area has the potential to serve as a significant predictor of smoking behavior.

Objective: Previous studies have discovered a correlation between cigarette smoking and cortical thickness and surface area, but the causal relationship remains unclear. The objective of this investigation is to scrutinize the causal association between them. Methods: To derive summary statistics from a genome-wide association study (GWAS) on cortical thickness, surface area, and four smoking behaviors: 1) age of initiation of regular smoking (AgeSmk); 2) smoking initiation (SmkInit); 3) smoking cessation (SmkCes); 4) cigarettes per day (CigDay). Linkage disequilibrium score regression (LDSC) was employed to examine genetic association analysis. Furthermore, for traits with significant genetic associations, Mendelian randomization (MR) analyses were conducted. Results: The LDSC analysis revealed nominal genetic correlations between AgeSmk and right precentral surface area, left caudal anterior cingulate surface area, left cuneus surface area, left inferior parietal surface area, and right caudal anterior cingulate thickness, as well as between CigDay and left caudal middle frontal surface area, between SmkCes and left entorhinal thickness, and between SmkInit and left rostral anterior cingulate surface area, right rostral anterior cingulate thickness, and right superior frontal thickness (rg=-0.36–0.29, p<0.05). MR analysis showed a unidirectional causal association between left caudal middle frontal surface area and CigDay (βIVW=0.056, pBonferroni=2×10-4). Conclusion Left caudal middle frontal surface area has the potential to serve as a significant predictor of smoking behavior.

Objective: Previous studies have discovered a correlation between cigarette smoking and cortical thickness and surface area, but the causal relationship remains unclear. The objective of this investigation is to scrutinize the causal association between them. Methods: To derive summary statistics from a genome-wide association study (GWAS) on cortical thickness, surface area, and four smoking behaviors: 1) age of initiation of regular smoking (AgeSmk); 2) smoking initiation (SmkInit); 3) smoking cessation (SmkCes); 4) cigarettes per day (CigDay). Linkage disequilibrium score regression (LDSC) was employed to examine genetic association analysis. Furthermore, for traits with significant genetic associations, Mendelian randomization (MR) analyses were conducted. Results: The LDSC analysis revealed nominal genetic correlations between AgeSmk and right precentral surface area, left caudal anterior cingulate surface area, left cuneus surface area, left inferior parietal surface area, and right caudal anterior cingulate thickness, as well as between CigDay and left caudal middle frontal surface area, between SmkCes and left entorhinal thickness, and between SmkInit and left rostral anterior cingulate surface area, right rostral anterior cingulate thickness, and right superior frontal thickness (rg=-0.36–0.29, p<0.05). MR analysis showed a unidirectional causal association between left caudal middle frontal surface area and CigDay (βIVW=0.056, pBonferroni=2×10-4). Conclusion Left caudal middle frontal surface area has the potential to serve as a significant predictor of smoking behavior.

Objective: Previous studies have discovered a correlation between cigarette smoking and cortical thickness and surface area, but the causal relationship remains unclear. The objective of this investigation is to scrutinize the causal association between them. Methods: To derive summary statistics from a genome-wide association study (GWAS) on cortical thickness, surface area, and four smoking behaviors: 1) age of initiation of regular smoking (AgeSmk); 2) smoking initiation (SmkInit); 3) smoking cessation (SmkCes); 4) cigarettes per day (CigDay). Linkage disequilibrium score regression (LDSC) was employed to examine genetic association analysis. Furthermore, for traits with significant genetic associations, Mendelian randomization (MR) analyses were conducted. Results: The LDSC analysis revealed nominal genetic correlations between AgeSmk and right precentral surface area, left caudal anterior cingulate surface area, left cuneus surface area, left inferior parietal surface area, and right caudal anterior cingulate thickness, as well as between CigDay and left caudal middle frontal surface area, between SmkCes and left entorhinal thickness, and between SmkInit and left rostral anterior cingulate surface area, right rostral anterior cingulate thickness, and right superior frontal thickness (rg=-0.36–0.29, p<0.05). MR analysis showed a unidirectional causal association between left caudal middle frontal surface area and CigDay (βIVW=0.056, pBonferroni=2×10-4). Conclusion Left caudal middle frontal surface area has the potential to serve as a significant predictor of smoking behavior.

Objective: Previous studies have discovered a correlation between cigarette smoking and cortical thickness and surface area, but the causal relationship remains unclear. The objective of this investigation is to scrutinize the causal association between them. Methods: To derive summary statistics from a genome-wide association study (GWAS) on cortical thickness, surface area, and four smoking behaviors: 1) age of initiation of regular smoking (AgeSmk); 2) smoking initiation (SmkInit); 3) smoking cessation (SmkCes); 4) cigarettes per day (CigDay). Linkage disequilibrium score regression (LDSC) was employed to examine genetic association analysis. Furthermore, for traits with significant genetic associations, Mendelian randomization (MR) analyses were conducted. Results: The LDSC analysis revealed nominal genetic correlations between AgeSmk and right precentral surface area, left caudal anterior cingulate surface area, left cuneus surface area, left inferior parietal surface area, and right caudal anterior cingulate thickness, as well as between CigDay and left caudal middle frontal surface area, between SmkCes and left entorhinal thickness, and between SmkInit and left rostral anterior cingulate surface area, right rostral anterior cingulate thickness, and right superior frontal thickness (rg=-0.36–0.29, p<0.05). MR analysis showed a unidirectional causal association between left caudal middle frontal surface area and CigDay (βIVW=0.056, pBonferroni=2×10-4). Conclusion Left caudal middle frontal surface area has the potential to serve as a significant predictor of smoking behavior.

AIM: To identify the primary active components and underlying mechanisms of Yijing Decoction(YJD)in treating early diabetic retinopathy(DR)based on liquid chromatography-mass spectrometry and network pharmacology.METHODS: Active components of YJD were characterized through LC-MS. Components with optimal ADME(absorption, distribution, metabolism, excretion)properties were selected as key bioactive candidates. Network pharmacology approaches were employed to predict YJD-DR therapeutic targets. Protein-protein interaction(PPI)networks, gene ontology(GO)enrichment analysis, and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway analysis were subsequently conducted to predict core targets and networks. Critical targets and pathways were experimentally validated through Western blot.RESULTS: Ten core therapeutic targets were identified, including TNF, Alb, EGFR, STAT3, PTGS2, ESR1, PPAR, MMP9, TLR4, and MAPK. YJD was related to cancer-related signaling, fluid shear stress and atherosclerosis, and neurodegenerative diseases, encompassing key biological processes such as inflammatory response regulation, programmed cell death activation, and enhanced cell migration. Furthermore, Western blot analysis confirmed that YJD significantly inhibited high glucose-induced phosphorylation of STAT3(P-STAT3/STAT3)and ERK(P-ERK/ERK)in rat retinal microvascular endothelial cells.CONCLUSION: This study revealed YJD's pharmacodynamical basis and its multi-component, multi-target, and multi-paths pharmacology. YJD exerts therapeutic effects on DR by coordinately regulating critical signaling pathways and alleviating intraocular inflammation, thus preserving retinal vascular endothelial cells, maintaining blood-retinal barrier integrity, and facilitating retinal neurovascular repair.

Objective To construct large medical model named by "Huaxi HongYi"and explore its application effectiveness in assisting medical record generation. Methods By the way of a full-chain medical large model construction paradigm of "data annotation - model training - scenario incubation", through strategies such as multimodal data fusion, domain adaptation training, and localization of hardware adaptation, "Huaxi HongYi" with 72 billion parameters was constructed. Combined with technologies such as speech recognition, knowledge graphs, and reinforcement learning, an application system for assisting in the generation of medical records was developed. Results Taking the assisted generation of discharge records as an example, in the pilot department, after using the application system, the average completion times of writing a medical records shortened (21 min vs. 5 min) with efficiency increased by 3.2 time, the accuracy rate of the model output reached 92.4%. Conclusion It is feasible for medical institutions to build independently controllable medical large models and incubate various applications based on these models, providing a reference pathway for artificial intelligence development in similar institutions.