Esophageal cancer （EC） is a highly prevalent malignant tumor in China. The phosphatidylinositol 3-kinase （PI3K）/protein kinase B （Akt） signaling pathway， as one of the key oncogenic pathways， can promote the cell cycle progression， proliferation， migration， and invasion， induce chemoresistance， and inhibit apoptosis and autophagy of EC cells. Traditional Chinese medicine （TCM）， with the advantages of targeting multiple points with multiple components to delay cancer progression， can target the PI3K/Akt signaling pathway for EC treatment. This article preliminarily discusses the molecular mechanism and role of the PI3K/Akt signaling pathway in EC and elaborates on the specific targets and efficacy of TCM in treating EC through intervention in the PI3K/Akt signaling pathway in the past five years. TCM materials and extracts inhibiting the PI3K/Akt signaling pathway in EC include Borneolum， spore powder of Ganoderma lucidum without spore coat， extract of Celastrus orbiculatus， root extract of Taraxacum， and Bruceae Fructus oil emulsion. TCM active ingredients exerting the effect include flavonoids， terpenoids， saponins， phenols， polysaccharides， alkaloids， and other compounds. TCM compound prescriptions with such effect include Qige San， Huqi San， Xuanfu Daizhetang， Tongyoutang and its decomposed prescriptions， Liujunzi Tang， and Xishenzhi Formula. In addition， TCM injections such as Compound Kushen Injection and Kang'ai injection also inhibit the PI3K/Akt signaling pathway in EC. This paper summarizes the role of the PI3K/Akt signaling pathway in EC and the TCM interventions， aiming to provide reference for the research and clinical application of new drugs for EC.

ObjectiveTo construct a multifunctional liposomal delivery system by replacing cholesterol（Chol） in conventional liposomes with saikosaponin D（SSD） and modifying with poloxamer 407（P407） for co-delivery of curcumin（Cur）. The system was evaluated for in vivo tumor targeting and inhibitory effects on mouse subcutaneous solid tumors. MethodsSingle-factor and orthogonal tests combined with information entropy weighting were used to optimize the formulation process of the liposome with encapsulation efficiency and absolute Zeta potential as indexes， and validation studies and liposomal characterization were performed. A subcutaneous solid tumor model was established by injecting H22 hepatocellular carcinoma cells subcutaneously into the dorsal surface of the right forelimb of mice. DiR-loaded traditional Chol liposomes（P407-DiR-Chol-LPs， PDCL） and novel SSD-based liposomes（P407-DiR-SSD-LPs， PDSL） were prepared by the optimized formulation process， and tail vein injection was performed to investigate the impact of SSD on liposome tumor targeting with small animal in vivo imaging. Mice were randomly divided into eight groups， including blank group， model group， free doxorubicin（DOX） group（2 mg·kg^-1）， free Cur group（8 mg·kg^-1）， free SSD group（10 mg·kg^-1）， P407-Cur-Chol-LPs（PCCL） group， P407-SSD-LPs（PSL） group， and P407-Cur-SSD-Lps（PCSL） group. Treatments were administered intraperitoneally every other day for seven doses. Antitumor efficacy and biocompatibility were evaluated by monitoring body weight change， organ indices， tumor volume and mass， relative tumor proliferation rate（T/C）， and tumor growth inhibition rate（TGI）. Histopathological analysis of liver， kidney， and tumor tissues was performed using hematoxylin-eosin（HE） staining. Serum levels of aspartate aminotransferase（AST）， alanine aminotransferase （ALT）， blood urea nitrogen（BUN）， and creatinine（Crea）in mice were quantified by fully automated biochemical analyzer. ResultsOrthogonal test yielded optimal ratios of Cur， SSD， and P407 to soybean phosphatidylcholine（SPC） as 1∶25， 1∶20， and 1∶4. The optimized PCSL exhibited spherical morphology with a particle size of 179.15 nm， a Zeta potential of -47.25 mV， and an encapsulation efficiency of 96.40%. Its in vitro release profile conformed to first-order kinetics， demonstrating excellent storage stability and hemocompatibility. In vivo imaging revealed that the fluorescence signal in tumor tissues and the fluorescence intensity ratio between tumors and organs were significantly higher in the PDSL group than in the PDCL group（P<0.05， P<0.01）. Among the treatment groups， PCSL group showed superior efficacy over free Cur group， free SSD group， PCCL group， and PSL group， with TGI>40% and T/C<60%， indicating pronounced anti-hepatocellular carcinoma effects（P<0.05， P<0.01）. Histopathology and serum biochemistry indicated minimal hepatorenal toxicity and improved hepatic and renal function in PCSL-treated mice. ConclusionReplacing Chol with SSD in preparing multifunctional drug delivery systems not only stabilizes liposomes but also yields superior anti-hepatocellular carcinoma efficacy， achieving the effect of drug-excipient integration. Co-delivery of Cur via this system can be used for treating subcutaneous solid tumors in hepatocellular carcinoma， providing new insights and technical approaches for anti-hepatocellular carcinoma research and the meridian-guiding and messenger-directing theory in traditional Chinese medicine.

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.

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

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.

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

Objective To investigate the role of H9c2-derived exosomes in regulating angiogenesis in rat cardiomyocytes under hypoxia.Methods The hypoxia model of H9c2 cells was prepared by mixed gas method(the hypoxia model group),and the normal cultured cells were used as the control group.The exosomes secreted by the two groups of cells were extracted respectively.The concentration and particle size of exosomes were detected by nanoparticle tracking analysis.The morphology and size of exosomes were detected by transmission electron microscopy.Western blot assay was used to verify the exosome marker proteins.The hypoxia model of human umbilical vein endothelial cells(HUVEC)was established.HUVECs were incubated with H9c2 exosomes and divided into the normoxia group,the hypoxia group,the hypoxia+normal H9c2 exosomes(EXO-C)group and the hypoxia+hypoxia H9c2 exosomes(EXO-M)group.The proliferation,migration and tube formation of HUVECs were detected by CCK-8 method,cell scratch test and Matrigel in vitro three-dimensional forming test.Results The results of exosome identification showed that the particle concentration of H9c2 exosome samples was 1×107-1×1012 particles/mL and the particle size was 40-160 nm in the normoxia group and the hypoxia group.The morphological characteristics were spherical or saucer-like structure,uniform in size and complete in shape.Exosome marker proteins TSG101,CD63 and CD9 were expressed,and there was no expression of negative protein Calnexin.Compared with the normoxic group,the proliferation ability,migration area and migration rate of HUVEC were significantly decreased in the hypoxic group,and the length of tube,the number of branches and the number of nodes were decreased(P＜0.01).Compared with the hypoxia group,the proliferation ability of HUVEC cells was decreased,the migration area was decreased,the migration rate was decreased and the length and number of branches involved in tube formation were further decreased in the EXO-M group(P＜0.05).Compared with the EXO-C group,the proliferation ability of the EXO-M group decreased,the cell migration area decreased and the migration rate decreased(P＜0.01).Conclusion Exosomes derived from hypoxic H9c2 can inhibit the proliferation,migration and tube formation of HUVEC.

Objective:To investigate and compare the effects of water extracts of Whitmania pigra Whitman and Hirudinaria ma-nillensis Lesson on the angiogenesis of Tg (kdrl:mCherry) zebrafish. Methods:The zebrafish embryos 6-8 hours after fertilization (6-8hpf) were transferred to the culture medium containing Whitmania pigra Whitman or Hirudinaria manillensis Lesson extract at different concentrations, and the culture medium containing the drugs was replaced every 24 h. And then, at 72 hpf, the larvalmorphology and intersegmental vessels were observed under a microscope. The hatchability of 48-and 72-hpf embryos, and the number of intersegmen-tal vessels and the heart rate of 72-hpf juveniles were measured. Results:Compared with the control group, when the concentration of Whitmania pigra Whitmanis was higher than 30μg· ml-1 , and the concentration of Hirudinaria manillensis Lesson was higher than 20μg· ml-1, the number of intersegmental vessels was significantly reduced (P<0. 01). Compared with the control group, at 48 hpf, when the concentration of the drug groups was higher than 40 μg· ml-1 , the hatchability of the two groups significantly decreased ( P<0. 01);at 72 hpf, the hatchability of Whitmania pigra Whitman decreased significantly at the concentration of 100 μg·ml-1 (P<0.01), while the hatchability of Hirudinaria manillensis Lesson decreased significantly at the concentration of 80 μg· ml-1(P <0. 01). There was no obvious yolk sac edema, pericardial edema and spine curvature in the two groups. The heart rate decreased sig-nificantly (P<0. 01), while was still within the normal range. Conclusion:Both Whitmania pigra Whitman and Hirudinaria manillen-sis Lesson have notable anti-angiogenic activity, and the anti-angiogenesis activity of Hirudinaria manillensis Lesson is stronger. They both have effects on the development of zebrafish embryos, while the toxicity is not obvious.