Hepatocellular carcinoma (HCC) is an aggressive primary liver malignancy often diagnosed at an advanced stage, resulting in a poor prognosis. Accurate risk stratification and early detection of HCC are critical unmet needs for improving outcomes. Several blood-based biomarkers and imaging tests are available for early detection, prediction, and monitoring of HCC. However, serum protein biomarkers such as alpha-fetoprotein have shown relatively low sensitivity, leading to inaccurate performance. Imaging studies also face limitations related to suboptimal accuracy, high cost, and limited implementation. Recently, liquid biopsy techniques have gained attention for addressing these unmet needs. Liquid biopsy is non-invasive and provides more objective readouts, requiring less reliance on healthcare professional’s skills compared to imaging. Circulating tumor cells, cell-free DNA, and extracellular vesicles are targeted in liquid biopsies as novel biomarkers for HCC. Despite their potential, there are debates regarding the role of these novel biomarkers in the HCC care continuum. This review article aims to discuss the technical challenges, recent technical advancements, advantages and disadvantages of these liquid biopsies, as well as their current clinical application and future directions of liquid biopsy in HCC.

Hepatocellular carcinoma (HCC) is an aggressive primary liver malignancy often diagnosed at an advanced stage, resulting in a poor prognosis. Accurate risk stratification and early detection of HCC are critical unmet needs for improving outcomes. Several blood-based biomarkers and imaging tests are available for early detection, prediction, and monitoring of HCC. However, serum protein biomarkers such as alpha-fetoprotein have shown relatively low sensitivity, leading to inaccurate performance. Imaging studies also face limitations related to suboptimal accuracy, high cost, and limited implementation. Recently, liquid biopsy techniques have gained attention for addressing these unmet needs. Liquid biopsy is non-invasive and provides more objective readouts, requiring less reliance on healthcare professional’s skills compared to imaging. Circulating tumor cells, cell-free DNA, and extracellular vesicles are targeted in liquid biopsies as novel biomarkers for HCC. Despite their potential, there are debates regarding the role of these novel biomarkers in the HCC care continuum. This review article aims to discuss the technical challenges, recent technical advancements, advantages and disadvantages of these liquid biopsies, as well as their current clinical application and future directions of liquid biopsy in HCC.

Hepatocellular carcinoma (HCC) is an aggressive primary liver malignancy often diagnosed at an advanced stage, resulting in a poor prognosis. Accurate risk stratification and early detection of HCC are critical unmet needs for improving outcomes. Several blood-based biomarkers and imaging tests are available for early detection, prediction, and monitoring of HCC. However, serum protein biomarkers such as alpha-fetoprotein have shown relatively low sensitivity, leading to inaccurate performance. Imaging studies also face limitations related to suboptimal accuracy, high cost, and limited implementation. Recently, liquid biopsy techniques have gained attention for addressing these unmet needs. Liquid biopsy is non-invasive and provides more objective readouts, requiring less reliance on healthcare professional’s skills compared to imaging. Circulating tumor cells, cell-free DNA, and extracellular vesicles are targeted in liquid biopsies as novel biomarkers for HCC. Despite their potential, there are debates regarding the role of these novel biomarkers in the HCC care continuum. This review article aims to discuss the technical challenges, recent technical advancements, advantages and disadvantages of these liquid biopsies, as well as their current clinical application and future directions of liquid biopsy in HCC.

OBJECTIVE: To explore clinical efficacy of different technical combinations in treating ischemic diabetic foot (DF). METHODS: A retrospective analysis was conducted on 35 patients with DF who were treated with vascular interventional opening technique, periosteal distraction technique and bone cement coverage technique from January 2024 to November 2024. They were divided into comprehensive group and periosteal distraction group according to whether the vascular interventional opening technique was used in combination or not. There were 5 patients in comprehensive group, including 4 males and 1 female, aged from 59 to 73 years old with an average of (64.40±5.46) years old;the duration of diabetes ranged from 0.17 to 30.00 years with an average of (14.63±12.02) years;the courses of DF ranged from 30 to 150 days with an average of (84.00±61.48) days;2 patients were grade 2, 2 patients were grade 3, and 1 patient was grade 4 according to Wagner classification;combined vascular interventional opening, periosteal distraction and bone cement coverage surgery for treatment. There were 30 patients in periosteal stretch group, including 22 males and 8 females, aged from 58 to 86 years old with an average of (72.63±7.84) years old;the duration of diabetes was 10.00 (6.75, 16.75) years;the courses of DF was 30.00 (15.00, 37.50) days;14 patients were grade 2, 11 patients were grade 3, and 5 patients were grade 4 according to Wagner classification; combined periosteal distraction and bone cement coverage surgery for treatment. Changes of C-reactive protein (CRP), interleukin-6 (IL-6), and procalcitonin (PCT), toe skin temperature, peripheral capillary oxygen saturation (SpO₂), and visual analogue scale (VAS) for pain were compared between two groups before operation and 1 week after operation. The number of operations, healing period, healing number, toe amputation number, preoperative fever situation and the number of complications were compared between two groups. RESULTS: Both groups were followed up for at least 6 months. There were no statistically significant differences in the number of operations, healing period, toe amputation rate, wound healing rate and complications between two groups (P>0.05). Before operation, the toe skin temperature of comprehensive group (26.98±0.88) ℃ was lower than that of periosteal distraction group (28.17±1.45) ℃, and the difference was statistically significant (P<0.05);while there were no statistically significant difference in CRP, IL-6, PCT, toe SpO2 and VAS between two groups (P>0.05). At 1 week after operation, IL-6, toe skin temperature, toe SpO₂ and VAS in comprehensive group were 12.29(7.92, 22.15) pg·ml-1, (36.02±0.23) ℃, (95.80±0.84) % and(1.40±0.55) respectively, while those in periosteal distraction group were 5.49(4.36, 7.45) pg·ml^-1, (31.36±1.57) ℃, (84.53±6.38) %, (2.20±0.81);and there were statistically significant differences between two groups(P<0.05). CRP, IL-6 and VAS at 1 week after operation in both groups were decreased compared with those before operation, and the differences were statistically significant(P<0.05). The toe skin temperature and SpO₂ were increased compared with those before operation, and the differences were statistically significant(P<0.001). CONCLUSION The multi-technique combination therapy, including vascular interventional opening technique, periostealdistraction technique and bone cement covering technique, could protect each other, enhance efficacy, effectively promote the wound healing of ischemic diabetic foot ulcer, and reduce the toe amputation rate. For moderate to severe ischemic DF, the combined use of periosteal distraction and bone cement coverage techniques has a satisfactory effect. For extremely severe ischemic DF with inflow tract lesions, vascular interventional opening techniques need to be added.
Humans ; Male ; Female ; Middle Aged ; Aged ; Diabetic Foot/surgery* ; Retrospective Studies ; Aged, 80 and over ; Ischemia/surgery* ; Interleukin-6/metabolism*

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

Objective To establish a stable,reliable,and clinically relevant porcine model of endotoxin-induced acute respiratory distress syndrome(ARDS).Methods Ten 8-month-old male Bama minipigs were deeply sedated,followed by invasive mechanical ventilation and electrocardiographic monitoring.Lipopolysaccharide(LPS)was intravenously pumped at 600 μg/(kg·h)for 3 hours,then maintained at 15 μg/(kg·h)thereafter.Dynamic monitoring was performed at five time points after LPS injection(LPS 0,1,3,5,and 8 h),including arterial blood gas analysis and chest computed tomography(CT)scans.Pathological examination of lung tissues obtained via bronchoscopic biopsy(HE staining and transmission electron microscopy)was conducted.These indicators were comprehensively used to evaluate the success of the animal model.Results At 5 hours after LPS administration,8 minipigs developed symptoms such as skin cyanosis,elevated body temperature,and respiratory distress.The oxygenation index decreased to<300 mmHg.Chest CT scans showed diffuse pulmonary infiltrates.Histopathology revealed alveolar edema and hyaline membrane formation.Transmission electron microscopy demonstrated disruption of pulmonary blood-air barrier,depletion of lamellar bodies in type Ⅱ pneumocytes,inflammatory cell infiltration,and exudation of plasma proteins and fibrin.Compared with LPS 0 h,at LPS 8 h,the oxygenation index and arterial blood pH were significantly decreased(P<0.001),while blood lactic acid and serum potassium were significantly increased(P<0.05);serum calcium and base excess were significantly decreased(P<0.05),and the lung injury score based on HE-stained lung sections was significantly increased(P<0.01).Conclusion The porcine ARDS model established by continuous LPS injection can dynamically simulate the pathophysiological characteristics and typical pathological manifestations of clinical septic ARDS,making it an effective tool to study the pathogenesis,prevention,and treatment strategies of septic ARDS.

Objective To develop the Ego Depletion Scale for Type 2 Diabetes Patients and evaluate its reliability and validity,and to provide a specific assessment tool for evaluating ego-depletion in self-management.Methods Guided by the self-control strength model,the initial scale was constructed through literature review,semi-structured interviews,2 rounds of expert consultation,and a pilot survey.A convenience sampling method was employed to recruit 460 patients with Type 2 Diabetes from the endocrinology department of a tertiary hospital in Wuhan,Hubei Province,between April and July 2024.They were randomly divided into 2 subsets for exploratory factor analysis and confirmatory factor analysis.Results A total of 451 valid questionnaires were collected.Exploratory factor analysis extracted 6 common factors,with a cumulative variance contribution of 73.231％.In confirmatory factor analysis,an item was deleted due to failing to meet the standardized loading value criterion.The revised Ego Depletion Scale for Type 2 Diabetes Patients comprised 6 dimensions and 22 items.The total Cronbach's α coefficient was 0.911;split-half reliability was 0.744;the content validity index was 0.860.Correlation coefficients between the total score and scores of each dimension of the scale and the total score of the Self-Regulatory Fatigue Scale ranged from 0.558 to 0.946(P＜0.001).Conclusion The scale exhibits robust reliability and validity,serving as a scientifically instrument for assessing ego depletion in patients with Type 2 Diabetes.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

Objective To develop the Ego Depletion Scale for Type 2 Diabetes Patients and evaluate its reliability and validity,and to provide a specific assessment tool for evaluating ego-depletion in self-management.Methods Guided by the self-control strength model,the initial scale was constructed through literature review,semi-structured interviews,2 rounds of expert consultation,and a pilot survey.A convenience sampling method was employed to recruit 460 patients with Type 2 Diabetes from the endocrinology department of a tertiary hospital in Wuhan,Hubei Province,between April and July 2024.They were randomly divided into 2 subsets for exploratory factor analysis and confirmatory factor analysis.Results A total of 451 valid questionnaires were collected.Exploratory factor analysis extracted 6 common factors,with a cumulative variance contribution of 73.231％.In confirmatory factor analysis,an item was deleted due to failing to meet the standardized loading value criterion.The revised Ego Depletion Scale for Type 2 Diabetes Patients comprised 6 dimensions and 22 items.The total Cronbach's α coefficient was 0.911;split-half reliability was 0.744;the content validity index was 0.860.Correlation coefficients between the total score and scores of each dimension of the scale and the total score of the Self-Regulatory Fatigue Scale ranged from 0.558 to 0.946(P＜0.001).Conclusion The scale exhibits robust reliability and validity,serving as a scientifically instrument for assessing ego depletion in patients with Type 2 Diabetes.

As artificial intelligence technology rapidly advances, its deployment within the medical sector presents substantial ethical challenges. Consequently, it becomes crucial to create a standardized, transparent, and secure framework for processing medical data. This includes setting the ethical boundaries for medical artificial intelligence and safeguarding both patient rights and data integrity. This consensus governs every facet of medical data handling through artificial intelligence, encompassing data gathering, processing, storage, transmission, utilization, and sharing. Its purpose is to ensure the management of medical data adheres to ethical standards and legal requirements, while safeguarding patient privacy and data security. Concurrently, the principles of compliance with the law, patient privacy respect, patient interest protection, and safety and reliability are underscored. Key issues such as informed consent, data usage, intellectual property protection, conflict of interest, and benefit sharing are examined in depth. The enactment of this expert consensus is intended to foster the profound integration and sustainable advancement of artificial intelligence within the medical domain, while simultaneously ensuring that artificial intelligence adheres strictly to the relevant ethical norms and legal frameworks during the processing of medical data.
Artificial Intelligence/legislation & jurisprudence* ; Humans ; Consensus ; Computer Security/standards* ; Confidentiality/ethics* ; Informed Consent/ethics*