The innate immune system can be boosted in response to subsequent triggers by pre-exposure to microbes or microbial products, known as “trained immunity”. Compared to classical immune memory, innate trained immunity has several different features. Firstly, the molecules involved in trained immunity differ from those involved in classical immune memory. Innate trained immunity mainly involves innate immune cells (e.g., myeloid immune cells, natural killer cells, innate lymphoid cells) and their effector molecules (e.g., pattern recognition receptor (PRR), various cytokines), as well as some kinds of non-immune cells (e.g., microglial cells). Secondly, the increased responsiveness to secondary stimuli during innate trained immunity is not specific to a particular pathogen, but influences epigenetic reprogramming in the cell through signaling pathways, leading to the sustained changes in genes transcriptional process, which ultimately affects cellular physiology without permanent genetic changes (e.g., mutations or recombination). Finally, innate trained immunity relies on an altered functional state of innate immune cells that could persist for weeks to months after initial stimulus removal. An appropriate inducer could induce trained immunity in innate lymphocytes, such as exogenous stimulants (including vaccines) and endogenous stimulants, which was firstly discovered in bone marrow derived immune cells. However, mature bone marrow derived immune cells are short-lived cells, that may not be able to transmit memory phenotypes to their offspring and provide long-term protection. Therefore, trained immunity is more likely to be relied on long-lived cells, such as epithelial stem cells, mesenchymal stromal cells and non-immune cells such as fibroblasts. Epigenetic reprogramming is one of the key molecular mechanisms that induces trained immunity, including DNA modifications, non-coding RNAs, histone modifications and chromatin remodeling. In addition to epigenetic reprogramming, different cellular metabolic pathways are involved in the regulation of innate trained immunity, including aerobic glycolysis, glutamine catabolism, cholesterol metabolism and fatty acid synthesis, through a series of intracellular cascade responses triggered by the recognition of PRR specific ligands. In the view of evolutionary, trained immunity is beneficial in enhancing protection against secondary infections with an induction in the evolutionary protective process against infections. Therefore, innate trained immunity plays an important role in therapy against diseases such as tumors and infections, which has signature therapeutic effects in these diseases. In organ transplantation, trained immunity has been associated with acute rejection, which prolongs the survival of allografts. However, trained immunity is not always protective but pathological in some cases, and dysregulated trained immunity contributes to the development of inflammatory and autoimmune diseases. Trained immunity provides a novel form of immune memory, but when inappropriately activated, may lead to an attack on tissues, causing autoinflammation. In autoimmune diseases such as rheumatoid arthritis and atherosclerosis, trained immunity may lead to enhance inflammation and tissue lesion in diseased regions. In Alzheimer’s disease and Parkinson’s disease, trained immunity may lead to over-activation of microglial cells, triggering neuroinflammation even nerve injury. This paper summarizes the basis and mechanisms of innate trained immunity, including the different cell types involved, the impacts on diseases and the effects as a therapeutic strategy to provide novel ideas for different diseases.

BACKGROUND:In recent years,numerous studies have shown that autophagy and mitophagy play an important role in the regulation of bone metabolism.Under non-physiological conditions,mitophagy breaks the balance of bone metabolism and triggers metabolism disorders,which affect osteoblasts,osteoclasts,osteocytes,chondrocytes,bone marrow mesenchymal stem cells,etc. OBJECTIVE:To summarize the mechanism of mitophagy in regulating bone metabolic diseases and its application in clinical treatment. METHODS:PubMed,Web of Science,CNKI,WanFang and VIP databases were searched by computer using the keywords of"mitophagy,bone metabolism,osteoblasts,osteoclasts,osteocytes,chondrocytes,bone marrow mesenchymal stem cells"in English and Chinese.The search time was from 2008 to 2023.According to the inclusion criteria,90 articles were finally included for review and analysis. RESULTS AND CONCLUSION:Mitophagy promotes the generation of osteoblasts through SIRT1,PINK1/Parkin,FOXO3 and PI3K signaling pathways,while inhibiting osteoclast function through PINK1/Parkin and SIRT1 signaling pathways.Mitophagy leads to bone loss by increasing calcium phosphate particles and tissue protein kinase K in bone tissue.Mitophagy improves the function of chondrocytes through PINK1/Parkin,PI3K/AKT/mTOR and AMPK signaling pathways.Modulation of mitophagy shows great potential in the treatment of bone diseases,but there are still some issues to be further explored,such as different stages of drug-activated mitophagy,and the regulatory mechanisms of different signaling pathways.

Functional disorders of the Golgi apparatus are harmful to the health of organisms, leading to various diseases. Removing damaged Golgi apparatus is crucial for maintaining cellular homeostasis, therefore, autophagy of Golgi apparatus has gradually attracted attention. This article summarizes Golgi autophagy, briefly describes its structure and functions, Golgi autophagy receptors, and the role of Golgi autophagy in disease treatment. It also proposes the new concept of Golgimedicine, which looks forward to the role of Golgi in disease diagnosis, treatment, prognosis, genetic diseases, and rare diseases. This article aims to explore the scientific connotations of Golgi autophagy, Golgi structure and function from the perspective of Golgimedicine, providing theoretical references for drug target research, new drug development, and the healthy development of humanity.

The innate immune system detects cellular stressors and microbial infections, activating programmed cell death (PCD) pathways to eliminate intracellular pathogens and maintain homeostasis. Among these pathways, pyroptosis, apoptosis, and necroptosis represent the most characteristic forms of PCD. Although initially regarded as mechanistically distinct, emerging research has revealed significant crosstalk among their signaling cascades. Consequently, the concept of PANoptosis has been proposed—an inflammatory cell death pathway driven by caspases and receptor-interacting protein kinases (RIPKs), and regulated by the PANoptosome, which integrates key features of pyroptosis, apoptosis, and necroptosis. The core mechanism of PANoptosis involves the assembly and activation of the PANoptosome, a macromolecular complex composed of three structural components: sensor proteins, adaptor proteins, and effector proteins. Sensors detect upstream stimuli and transmit signals downstream, recruiting critical molecules via adaptors to form a molecular scaffold. This scaffold activates effectors, triggering intracellular signaling cascades that culminate in PANoptosis. The PANoptosome is regulated by upstream molecules such as interferon regulatory factor 1 (IRF1), transforming growth factor beta-activated kinase 1 (TAK1), and adenosine deaminase acting on RNA 1 (ADAR1), which function as molecular switches to control PANoptosis. Targeting these switches represents a promising therapeutic strategy. Furthermore, PANoptosis is influenced by organelle functions, including those of the mitochondria, endoplasmic reticulum, and lysosomes, highlighting organelle-targeted interventions as effective regulatory approaches. Cardiovascular diseases (CVDs), the leading global cause of morbidity and mortality, are profoundly impacted by PCD. Extensive crosstalk among multiple cell death pathways in CVDs suggests a complex regulatory network. As a novel cell death modality bridging pyroptosis, apoptosis, and necroptosis, PANoptosis offers fresh insights into the complexity of cell death and provides innovative strategies for CVD treatment. This review summarizes current evidence linking PANoptosis to various CVDs, including myocardial ischemia/reperfusion injury, myocardial infarction, heart failure, arrhythmogenic cardiomyopathy, sepsis-induced cardiomyopathy, cardiotoxic injury, atherosclerosis, abdominal aortic aneurysm, thoracic aortic aneurysm and dissection, and vascular toxic injury, thereby providing critical clinical insights into CVD pathophysiology. However, the current understanding of PANoptosis in CVDs remains incomplete. First, while PANoptosis in cardiomyocytes and vascular smooth muscle cells has been implicated in CVD pathogenesis, its role in other cell types—such as vascular endothelial cells and immune cells (e.g., macrophages)—warrants further investigation. Second, although pathogen-associated molecular patterns (PAMPs) and damage-associated molecular patterns (DAMPs) are known to activate the PANoptosome in infectious diseases, the stimuli driving PANoptosis in CVDs remain poorly defined. Additionally, methodological challenges persist in identifying PANoptosome assembly in CVDs and in establishing reliable PANoptosis models. Beyond the diseases discussed, PANoptosis may also play a role in viral myocarditis and diabetic cardiomyopathy, necessitating further exploration. In conclusion, elucidating the role of PANoptosis in CVDs opens new avenues for drug development. Targeting this pathway could yield transformative therapies, addressing unmet clinical needs in cardiovascular medicine.

Purpose: The aim of this study was to investigate the feasibility of an intelligent handheld ultrasound (US) device for assisting non-expert general practitioners (GPs) in detecting carotid plaques (CPs) in community populations. Methods: This prospective parallel controlled trial recruited 111 consecutive community residents. All of them underwent examinations by non-expert GPs and specialist doctors using handheld US devices (setting A, setting B, and setting C). The results of setting C with specialist doctors were considered the gold standard. Carotid intima-media thickness (CIMT) and the features of CPs were measured and recorded. The diagnostic performance of GPs in distinguishing CPs was evaluated using a receiver operating characteristic curve. Inter-observer agreement was compared using the intragroup correlation coefficient (ICC). Questionnaires were completed to evaluate clinical benefits. Results: Among the 111 community residents, 80, 96, and 112 CPs were detected in settings A, B, and C, respectively. Setting B exhibited better diagnostic performance than setting A for detecting CPs (area under the curve, 0.856 vs. 0.749; P<0.01). Setting B had better consistency with setting C than setting A in CIMT measurement and the assessment of CPs (ICC, 0.731 to 0.923). Moreover, measurements in setting B required less time than the other two settings (44.59 seconds vs. 108.87 seconds vs. 126.13 seconds, both P<0.01). Conclusion Using an intelligent handheld US device, GPs can perform CP screening and achieve a diagnostic capability comparable to that of specialist doctors.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-associated death globally. Liver transplantation (LT) has emerged as a key treatment for patients with HCC, and the Milan criteria have been adopted as the cornerstone of the selection policy. To allow more patients to benefit from LT, a number of expanded criteria have been proposed, many of which use radiologic morphological characteristics with larger and more tumors as surrogates to predict outcomes. Other groups developed indices incorporating biological variables and dynamic markers of response to locoregional treatment. These expanded selection criteria achieved satisfactory results with limited liver supplies. In addition, a number of prognostic models have been developed using clinicopathological characteristics, imaging radiomics features, genetic data, and advanced techniques such as artificial intelligence. These models could improve prognostic estimation, establish surveillance strategies, and bolster long-term outcomes in patients with HCC. In this study, we reviewed the latest findings and achievements regarding the selection criteria and post-transplant prognostic models for LT in patients with HCC.

Purpose: The aim of this study was to investigate the feasibility of an intelligent handheld ultrasound (US) device for assisting non-expert general practitioners (GPs) in detecting carotid plaques (CPs) in community populations. Methods: This prospective parallel controlled trial recruited 111 consecutive community residents. All of them underwent examinations by non-expert GPs and specialist doctors using handheld US devices (setting A, setting B, and setting C). The results of setting C with specialist doctors were considered the gold standard. Carotid intima-media thickness (CIMT) and the features of CPs were measured and recorded. The diagnostic performance of GPs in distinguishing CPs was evaluated using a receiver operating characteristic curve. Inter-observer agreement was compared using the intragroup correlation coefficient (ICC). Questionnaires were completed to evaluate clinical benefits. Results: Among the 111 community residents, 80, 96, and 112 CPs were detected in settings A, B, and C, respectively. Setting B exhibited better diagnostic performance than setting A for detecting CPs (area under the curve, 0.856 vs. 0.749; P<0.01). Setting B had better consistency with setting C than setting A in CIMT measurement and the assessment of CPs (ICC, 0.731 to 0.923). Moreover, measurements in setting B required less time than the other two settings (44.59 seconds vs. 108.87 seconds vs. 126.13 seconds, both P<0.01). Conclusion Using an intelligent handheld US device, GPs can perform CP screening and achieve a diagnostic capability comparable to that of specialist doctors.

Purpose: The aim of this study was to investigate the feasibility of an intelligent handheld ultrasound (US) device for assisting non-expert general practitioners (GPs) in detecting carotid plaques (CPs) in community populations. Methods: This prospective parallel controlled trial recruited 111 consecutive community residents. All of them underwent examinations by non-expert GPs and specialist doctors using handheld US devices (setting A, setting B, and setting C). The results of setting C with specialist doctors were considered the gold standard. Carotid intima-media thickness (CIMT) and the features of CPs were measured and recorded. The diagnostic performance of GPs in distinguishing CPs was evaluated using a receiver operating characteristic curve. Inter-observer agreement was compared using the intragroup correlation coefficient (ICC). Questionnaires were completed to evaluate clinical benefits. Results: Among the 111 community residents, 80, 96, and 112 CPs were detected in settings A, B, and C, respectively. Setting B exhibited better diagnostic performance than setting A for detecting CPs (area under the curve, 0.856 vs. 0.749; P<0.01). Setting B had better consistency with setting C than setting A in CIMT measurement and the assessment of CPs (ICC, 0.731 to 0.923). Moreover, measurements in setting B required less time than the other two settings (44.59 seconds vs. 108.87 seconds vs. 126.13 seconds, both P<0.01). Conclusion Using an intelligent handheld US device, GPs can perform CP screening and achieve a diagnostic capability comparable to that of specialist doctors.