Objective To analyze the epidemiological characteristics and disease burden of liver cancer in Guangdong Province in 2020, and to provide a scientific foundation for the development of regionalized prevention and control strategies for liver cancer. Methods According to the cancer registry data of Guangdong Province, the incidence, mortality and age-standardized rate by Chinese standard population in 2020 were calculated to analyze the epidemiological characteristics of liver cancer. The disability adjusted life years (DALYs), year of life loss (YLL), year of lived with disability (YLD), and cause-eliminated life expectancy were used to assess the disease burden of liver cancer. Results In 2020, the crude incidence rate and the age-standardized incidence rate of liver cancer in Guangdong Province were 27.79/100 000 and 20.84/100 000，respectively, and the crude mortality rate and the age-standardized mortality rate of liver cancer were 25.49/100,000 and 17.64/100 000, respectively. The total DALY and DALY rate of liver cancer in Guangdong Province were 515 311 person-years and 513.83/100 000, respectively. After eliminating the causes of death from liver cancer, the life expectancy in Guangdong Province increased from 84.60 years to 84.99 years. All indicators consistently demonstrated that the burden of liver cancer was higher in males than that in females, and the burden of liver cancer was higher in rural areas than that in urban areas. Conclusion Liver cancer in Guangdong Province exhibits a high incidence, mortality and disease burden level in 2020. There are obvious differences of gender, age and region in cancer burden. It is necessary to strengthen liver cancer screening and diagnosis and treatment in men, the elderly and those in rural areas to reduce the burden of liver cancer gradually in Guangdong Province.

BACKGROUND:Although researchers have noted that fibroblast growth factor receptor 1 shows great potential in rheumatoid arthritis bone destruction,there is a lack of reviews related to the potential mechanisms of fibroblast growth factor receptor 1 in rheumatoid arthritis bone destruction. OBJECTIVE:To comprehensively analyze the mechanism of fibroblast growth factor receptor 1 in bone destruction in rheumatoid arthritis by reviewing the relevant literature at both home and abroad. METHODS:We searched the CNKI database using the Chinese search terms"fibroblast growth factor receptor 1,rheumatoid arthritis,bone destruction,bone cells,osteoblasts,osteoclasts,chondrocytes,macrophages,synovial fibroblasts,T cells,vascular endothelial cells."PubMed database was searched using the English search terms"fibroblast growth factor receptor 1,rheumatoid arthritis,bone destruction,osteocytes,osteoblasts,osteoclasts,chondrocytes,macrophages,synovial fibroblasts,T cells,endothelial cells."The search period focused on April 1992 to January 2024.After screening the literature by reading titles,abstracts,and full texts,a total of 82 articles were finally included for review according to inclusion and exclusion criteria. RESULTS AND CONCLUSION:Fibroblast growth factor receptor 1 was found to be widely expressed in bone tissue-associated cells,including osteoblasts,osteoclasts,and osteoclasts.Fibroblast growth factor receptor 1 affects bone remodeling and homeostasis by regulating the function of these cells,as well as promoting the onset and progression of bone destruction in rheumatoid arthritis.Fibroblast growth factor receptor 1 is involved in the inflammatory response of synovial fibroblasts and macrophages and regulates angiogenesis of endothelial cells in synovial tissues.Fibroblast growth factor receptor 1 promotes bone destruction in several ways.Fibroblast growth factor receptor 1 may be a potential causative agent of bone destruction in rheumatoid arthritis and provides a reference for further research on its therapeutic targets.

Objective: Accurate evaluation of inflammation severity in ulcerative colitis (UC) can guide treatment strategy selection. The potential value of the pericolic fat attenuation index (FAI) on CT as an indicator of disease severity remains unknown.This study aimed to assess the diagnostic accuracy of pericolic FAI in predicting UC severity. Materials and Methods: This retrospective study enrolled 148 patients (mean age 48 years; 87 males). The fat attenuation on CT was measured in four different locations: the mesocolic vascular side (MS) and opposite side of MS (OMS) around the most severe bowel lesion, the retroperitoneal space (RS), and the subcutaneous area. The fat attenuation indices (FAI MS, FAI OMS, and FAI RS) were calculated as the fat attenuation measured in MS, OMS, and RS, respectively, minus that of the subcutaneous area, and were obtained in the non-enhanced, arterial, and delayed phases. Correlations between the FAI and UC Endoscopic Index of Severity (UCEIS) were assessed using Spearman’s correlation. Predictors of severe UC (UCEIS ≥7) were selected by univariable analysis. The performance of FAI in predicting severe UC was evaluated using the area under the receiver operating characteristic curve (AUC). Results: The FAIMS and FAI OMS scores were significantly higher than FAI RS in three phases (all P < 0.001). The FAIMS and FAI OMS scores moderately correlated with the UCEIS score (r = 0.474–0.649 among the three phases). Additionally, FAI MS and FAI OMS identified severe UC, with AUC varying from 0.77 to 0.85. Conclusion Increased CT attenuation of pericolic adipose tissue could serve as a noninvasive marker for evaluating UC severity. FAI MS and FAI OMS of three phases showed similar prediction accuracies for severe UC identification.

Objective: Accurate evaluation of inflammation severity in ulcerative colitis (UC) can guide treatment strategy selection. The potential value of the pericolic fat attenuation index (FAI) on CT as an indicator of disease severity remains unknown.This study aimed to assess the diagnostic accuracy of pericolic FAI in predicting UC severity. Materials and Methods: This retrospective study enrolled 148 patients (mean age 48 years; 87 males). The fat attenuation on CT was measured in four different locations: the mesocolic vascular side (MS) and opposite side of MS (OMS) around the most severe bowel lesion, the retroperitoneal space (RS), and the subcutaneous area. The fat attenuation indices (FAI MS, FAI OMS, and FAI RS) were calculated as the fat attenuation measured in MS, OMS, and RS, respectively, minus that of the subcutaneous area, and were obtained in the non-enhanced, arterial, and delayed phases. Correlations between the FAI and UC Endoscopic Index of Severity (UCEIS) were assessed using Spearman’s correlation. Predictors of severe UC (UCEIS ≥7) were selected by univariable analysis. The performance of FAI in predicting severe UC was evaluated using the area under the receiver operating characteristic curve (AUC). Results: The FAIMS and FAI OMS scores were significantly higher than FAI RS in three phases (all P < 0.001). The FAIMS and FAI OMS scores moderately correlated with the UCEIS score (r = 0.474–0.649 among the three phases). Additionally, FAI MS and FAI OMS identified severe UC, with AUC varying from 0.77 to 0.85. Conclusion Increased CT attenuation of pericolic adipose tissue could serve as a noninvasive marker for evaluating UC severity. FAI MS and FAI OMS of three phases showed similar prediction accuracies for severe UC identification.

Objective: Accurate evaluation of inflammation severity in ulcerative colitis (UC) can guide treatment strategy selection. The potential value of the pericolic fat attenuation index (FAI) on CT as an indicator of disease severity remains unknown.This study aimed to assess the diagnostic accuracy of pericolic FAI in predicting UC severity. Materials and Methods: This retrospective study enrolled 148 patients (mean age 48 years; 87 males). The fat attenuation on CT was measured in four different locations: the mesocolic vascular side (MS) and opposite side of MS (OMS) around the most severe bowel lesion, the retroperitoneal space (RS), and the subcutaneous area. The fat attenuation indices (FAI MS, FAI OMS, and FAI RS) were calculated as the fat attenuation measured in MS, OMS, and RS, respectively, minus that of the subcutaneous area, and were obtained in the non-enhanced, arterial, and delayed phases. Correlations between the FAI and UC Endoscopic Index of Severity (UCEIS) were assessed using Spearman’s correlation. Predictors of severe UC (UCEIS ≥7) were selected by univariable analysis. The performance of FAI in predicting severe UC was evaluated using the area under the receiver operating characteristic curve (AUC). Results: The FAIMS and FAI OMS scores were significantly higher than FAI RS in three phases (all P < 0.001). The FAIMS and FAI OMS scores moderately correlated with the UCEIS score (r = 0.474–0.649 among the three phases). Additionally, FAI MS and FAI OMS identified severe UC, with AUC varying from 0.77 to 0.85. Conclusion Increased CT attenuation of pericolic adipose tissue could serve as a noninvasive marker for evaluating UC severity. FAI MS and FAI OMS of three phases showed similar prediction accuracies for severe UC identification.

Objective: Accurate evaluation of inflammation severity in ulcerative colitis (UC) can guide treatment strategy selection. The potential value of the pericolic fat attenuation index (FAI) on CT as an indicator of disease severity remains unknown.This study aimed to assess the diagnostic accuracy of pericolic FAI in predicting UC severity. Materials and Methods: This retrospective study enrolled 148 patients (mean age 48 years; 87 males). The fat attenuation on CT was measured in four different locations: the mesocolic vascular side (MS) and opposite side of MS (OMS) around the most severe bowel lesion, the retroperitoneal space (RS), and the subcutaneous area. The fat attenuation indices (FAI MS, FAI OMS, and FAI RS) were calculated as the fat attenuation measured in MS, OMS, and RS, respectively, minus that of the subcutaneous area, and were obtained in the non-enhanced, arterial, and delayed phases. Correlations between the FAI and UC Endoscopic Index of Severity (UCEIS) were assessed using Spearman’s correlation. Predictors of severe UC (UCEIS ≥7) were selected by univariable analysis. The performance of FAI in predicting severe UC was evaluated using the area under the receiver operating characteristic curve (AUC). Results: The FAIMS and FAI OMS scores were significantly higher than FAI RS in three phases (all P < 0.001). The FAIMS and FAI OMS scores moderately correlated with the UCEIS score (r = 0.474–0.649 among the three phases). Additionally, FAI MS and FAI OMS identified severe UC, with AUC varying from 0.77 to 0.85. Conclusion Increased CT attenuation of pericolic adipose tissue could serve as a noninvasive marker for evaluating UC severity. FAI MS and FAI OMS of three phases showed similar prediction accuracies for severe UC identification.

Objective: Accurate evaluation of inflammation severity in ulcerative colitis (UC) can guide treatment strategy selection. The potential value of the pericolic fat attenuation index (FAI) on CT as an indicator of disease severity remains unknown.This study aimed to assess the diagnostic accuracy of pericolic FAI in predicting UC severity. Materials and Methods: This retrospective study enrolled 148 patients (mean age 48 years; 87 males). The fat attenuation on CT was measured in four different locations: the mesocolic vascular side (MS) and opposite side of MS (OMS) around the most severe bowel lesion, the retroperitoneal space (RS), and the subcutaneous area. The fat attenuation indices (FAI MS, FAI OMS, and FAI RS) were calculated as the fat attenuation measured in MS, OMS, and RS, respectively, minus that of the subcutaneous area, and were obtained in the non-enhanced, arterial, and delayed phases. Correlations between the FAI and UC Endoscopic Index of Severity (UCEIS) were assessed using Spearman’s correlation. Predictors of severe UC (UCEIS ≥7) were selected by univariable analysis. The performance of FAI in predicting severe UC was evaluated using the area under the receiver operating characteristic curve (AUC). Results: The FAIMS and FAI OMS scores were significantly higher than FAI RS in three phases (all P < 0.001). The FAIMS and FAI OMS scores moderately correlated with the UCEIS score (r = 0.474–0.649 among the three phases). Additionally, FAI MS and FAI OMS identified severe UC, with AUC varying from 0.77 to 0.85. Conclusion Increased CT attenuation of pericolic adipose tissue could serve as a noninvasive marker for evaluating UC severity. FAI MS and FAI OMS of three phases showed similar prediction accuracies for severe UC identification.

This study aims to investigate the scientificity and efficacy of the compatibility of Jinlingzi San from pharmacokinetics. Liquid chromatography-tandem mass spectrometry(LC-MS/MS) was utilized to determine the plasma concentrations of the active components: toosendanin, tetrahydropalmatine A, and tetrahydropalmatine B at various time points following the gavage of Jinlingzi San and its single medicines in rats. Subsequently, WinNonlin was employed to calculate pertinent pharmacokinetic parameters. The pharmacokinetic parameters in rat plasma were compared between the single medicines and the compound formula of Jinlingzi San. It was discovered that the area under the curve(AUC_(all)) and peak concentrations(C_(max)) of tetrahydropalmatine A, and tetrahydropalmatine B were significantly elevated in the compound formula group compared with the single medicine groups. Conversely, the AUC_(all )and C_(max) of toosendanin notably decreased. Furthermore, the compound formula group had longer mean residence time(MRT) and lower apparent clearance(CL/F) of all three active ingredients than the single medicine groups(P<0.05). These findings indicated that Jinlingzi San enhanced the absorption of tetrahydropalmatine A and tetrahydropalmatine B in vivo, facilitating their pharmacological actions. Concurrently, it inhibited the absorption of toosendanin, thereby preventing potential toxic reactions. Moreover, the compatibility prolonged the residence time of the active ingredients in the body. This study provides a reference for exploring the compatibility rationality of Jinlingzi San.
Animals ; Rats ; Tandem Mass Spectrometry/methods* ; Drugs, Chinese Herbal/administration & dosage* ; Male ; Rats, Sprague-Dawley ; Chromatography, Liquid/methods* ; Berberine Alkaloids/blood* ; Liquid Chromatography-Mass Spectrometry

This study investigated the protective effect of arbutin(Arb) in yam on lipopolysaccharide(LPS)-induced acute lung injury(ALI) in a mouse model and revealed its possible mechanism of action by metabolomics technology, providing a theoretical basis for clinical treatment of ALI. SPF BALB/c mice were randomly divided into normal control group, model group, resveratrol(Rv)-positive control group, Arb low-dose(15 mg·kg~(-1)) group, and Arb high-dose(30 mg·kg~(-1)) group. The LPS-induced ALI model was established in all groups except the normal control group. Hematoxylin-eosin(HE) staining, TUNEL staining, and WBP whole-body non-invasive pulmonary function testing were used to evaluate the degree of lung tissue damage and lung function changes. Enzyme-linked immunosorbent assay(ELISA) was used to detect the level of inflammatory factors in lung tissue. Flow cytometry was used to analyze the M1/M2 polarization status of macrophages in lung tissue. Western blot was used to detect the expression levels of the TLR4 signaling pathway and related apoptotic proteins. Liquid chromatograph-mass spectrometer(LC-MS) metabolomics was used to analyze the changes in serum metabolic profile after Arb intervention. The results showed that Arb pretreatment significantly alleviated LPS-induced lung tissue injury, improved lung function, reduced the levels of pro-inflammatory factors(IL-6, TNF-α, IL-18, and IL-1β), and regulated the polarization status of M1/M2 macrophages. In addition, Arb inhibited the activation of the TLR4 signaling pathway, reduced the expression of pro-apoptotic proteins such as Bax, caspase-3, and caspase-9, up-regulated the level of Bcl-2 protein, and inhibited apoptosis of lung cells. Metabolomic analysis showed that Arb significantly improved LPS-induced metabolic abnormalities, mainly involving key pathways such as galactose metabolism, phenylalanine metabolism, and lipid metabolism. In summary, Arb can significantly reduce LPS-induced ALI by regulating the release of inflammatory factors, inhibiting the activation of the TLR4 signaling pathway, improving metabolic disorders, and regulating macrophage polarization, indicating that Arb has potential clinical application value.
Animals ; Acute Lung Injury/chemically induced* ; Mice ; Mice, Inbred BALB C ; Arbutin/administration & dosage* ; Male ; Toll-Like Receptor 4/immunology* ; Apoptosis/drug effects* ; Lung/metabolism* ; Signal Transduction/drug effects* ; Protective Agents/administration & dosage* ; Humans ; Macrophages/immunology* ; Drugs, Chinese Herbal/administration & dosage*

The rapid development of artificial intelligence (AI), especially generative AI (GenAI), has already brought, and will continue to bring, revolutionary changes to our daily production and life, as well as create new opportunities and challenges for diagnostic and therapeutic practices in the medical field. Haihe Hospital of Tianjin University collaborates with the National Supercomputer Center in Tianjin, Tianjin University, and other institutions to carry out research in areas such as smart healthcare, smart services, and smart management. We have conducted research and development of a full-process disease diagnosis and treatment assistance system based on GenAI in the field of smart healthcare. The development of this project is of great significance. The first goal is to upgrade and transform the hospital's information center, organically integrate it with existing information systems, and provide the necessary computing power storage support for intelligent services within the hospital. We have implemented the localized deployment of three models: Tianhe "Tianyuan", WiNGPT, and DeepSeek. The second is to create a digital avatar of the chief physician/chief physician's voice and image by integrating multimodal intelligent interaction technology. With generative intelligence as the core, this solution provides patients with a visual medical interaction solution. The third is to achieve deep adaptation between generative intelligence and the entire process of patient medical treatment. In this project, we have developed assistant tools such as intelligent inquiry, intelligent diagnosis and recognition, intelligent treatment plan generation, and intelligent assisted medical record generation to improve the safety, quality, and efficiency of the diagnosis and treatment process. This study introduces the content of a full-process disease diagnosis and treatment assistance system, aiming to provide references and insights for the digital transformation of the healthcare industry.
Artificial Intelligence ; Humans ; Delivery of Health Care ; Generative Artificial Intelligence