In 2023, nonalcoholic fatty liver disease was renamed metabolic dysfunction-associated steatotic liver disease by the American and European liver associations. This new nomenclature recognizes metabolic dysfunction as the central driver of the disease, and the diagnostic criteria now require the presence of hepatic steatosis plus at least one of five cardiometabolic risk factors. B-mode ultrasonography remains the most common and practical method for detecting hepatic steatosis, although newer ultrasound techniques based on attenuation, backscatter, and speed of sound have gained traction as tools to diagnose and quantify hepatic steatosis. Additionally, ultrasound elastography is increasingly used in routine clinical practice to assess liver fibrosis, diagnose cirrhosis, and identify clinically significant portal hypertension.

In 2023, nonalcoholic fatty liver disease was renamed metabolic dysfunction-associated steatotic liver disease by the American and European liver associations. This new nomenclature recognizes metabolic dysfunction as the central driver of the disease, and the diagnostic criteria now require the presence of hepatic steatosis plus at least one of five cardiometabolic risk factors. B-mode ultrasonography remains the most common and practical method for detecting hepatic steatosis, although newer ultrasound techniques based on attenuation, backscatter, and speed of sound have gained traction as tools to diagnose and quantify hepatic steatosis. Additionally, ultrasound elastography is increasingly used in routine clinical practice to assess liver fibrosis, diagnose cirrhosis, and identify clinically significant portal hypertension.

In 2023, nonalcoholic fatty liver disease was renamed metabolic dysfunction-associated steatotic liver disease by the American and European liver associations. This new nomenclature recognizes metabolic dysfunction as the central driver of the disease, and the diagnostic criteria now require the presence of hepatic steatosis plus at least one of five cardiometabolic risk factors. B-mode ultrasonography remains the most common and practical method for detecting hepatic steatosis, although newer ultrasound techniques based on attenuation, backscatter, and speed of sound have gained traction as tools to diagnose and quantify hepatic steatosis. Additionally, ultrasound elastography is increasingly used in routine clinical practice to assess liver fibrosis, diagnose cirrhosis, and identify clinically significant portal hypertension.

In 2023, nonalcoholic fatty liver disease was renamed metabolic dysfunction-associated steatotic liver disease by the American and European liver associations. This new nomenclature recognizes metabolic dysfunction as the central driver of the disease, and the diagnostic criteria now require the presence of hepatic steatosis plus at least one of five cardiometabolic risk factors. B-mode ultrasonography remains the most common and practical method for detecting hepatic steatosis, although newer ultrasound techniques based on attenuation, backscatter, and speed of sound have gained traction as tools to diagnose and quantify hepatic steatosis. Additionally, ultrasound elastography is increasingly used in routine clinical practice to assess liver fibrosis, diagnose cirrhosis, and identify clinically significant portal hypertension.

In 2023, nonalcoholic fatty liver disease was renamed metabolic dysfunction-associated steatotic liver disease by the American and European liver associations. This new nomenclature recognizes metabolic dysfunction as the central driver of the disease, and the diagnostic criteria now require the presence of hepatic steatosis plus at least one of five cardiometabolic risk factors. B-mode ultrasonography remains the most common and practical method for detecting hepatic steatosis, although newer ultrasound techniques based on attenuation, backscatter, and speed of sound have gained traction as tools to diagnose and quantify hepatic steatosis. Additionally, ultrasound elastography is increasingly used in routine clinical practice to assess liver fibrosis, diagnose cirrhosis, and identify clinically significant portal hypertension.

Drug resistance is one of the key factors affecting the effectiveness of cancer treatment methods, including chemotherapy, radiotherapy, and immunotherapy. Its occurrence is related to factors such as mRNA expression and methylation within cancer cells. If drug resistance in patients can be accurately identified early, doctors can devise more effective treatment plans, which is of great significance for improving patients' survival rates and quality of life. Cancer drug resistance prediction based on artificial intelligence (AI) technology has emerged as a current research hotspot, demonstrating promising application prospects in guiding clinical individualized and precise medication for cancer patients. This review aims to comprehensively summarize the research progress in utilizing AI algorithms to analyze multi-omics data including genomics, transcriptomics, epigenomics, proteomics, metabolomics, radiomics, and histopathology, for predicting cancer drug resistance. It provides a detailed exposition of the processes involved in data processing and model construction, examines the current challenges faced in this field and future development directions, with the aim of better advancing the progress of precision medicine.

COMPERA 2.0 risk stratification has been demonstrated to be useful in patients with precapillary pulmonary hypertension (PH). However, its suitability for patients at risk for post-capillary PH or PH associated with left heart disease (PH-LHD) is unclear. To investigate the use of COMPERA 2.0 in patients with severe aortic stenosis (SAS) undergoing transcatheter aortic valve replacement (TAVR), who are at risk for post-capillary PH, a total of 327 eligible SAS patients undergoing TAVR at our institution between September 2015 and November 2020 were included in the study. Patients were classified into four strata before and after TAVR using the COMPERA 2.0 risk score. The primary endpoint was all-cause mortality. Survival analysis was performed using Kaplan-Meier curves, log-rank test, and Cox proportional hazards regression model. The study cohort had a median (interquartile range) age of 76 (70‒80) years and a pulmonary arterial systolic pressure of 33 (27‒43) mmHg (1 mmHg=0.133 kPa) before TAVR. The overall mortality was 11.9% during 26 (15‒47) months of follow-up. Before TAVR, cumulative mortality was higher with an increase in the risk stratum level (log-rank, both P<0.001); each increase in the risk stratum level resulted in an increased risk of death (hazard ratio (HR) 2.53, 95% confidential interval (CI) 1.54‒4.18, P<0.001), which was independent of age, sex, estimated glomerular filtration rate (eGFR), hemoglobin, albumin, and valve type (HR 1.76, 95% CI 1.01‒3.07, P=0.047). Similar results were observed at 30 d after TAVR. COMPERA 2.0 can serve as a useful tool for risk stratification in patients with SAS undergoing TAVR, indicating its potential application in the management of PH-LHD. Further validation is needed in patients with confirmed post-capillary PH by right heart catheterization.
Humans ; Aortic Valve Stenosis/complications* ; Aged ; Hypertension, Pulmonary/mortality* ; Male ; Female ; Transcatheter Aortic Valve Replacement ; Aged, 80 and over ; Risk Assessment/methods* ; Proportional Hazards Models ; Kaplan-Meier Estimate ; Retrospective Studies

Objective:To investigate the value of systemic inflammatory response syndrome (SIRS), pediatric sequential organ failure assessment (pSOFA) and pediatric critical illness score (PCIS) in predicting mortality of pediatric sepsis in pediatric intensive care units (PICU) from Southwest China.Methods:This was a prospective multicenter observational study. A total of 447 children with sepsis admitted to 12 PICU in Southwest China from April 2022 to March 2023 were enrolled. Based on the prognosis, the patients were divided into survival group and non-survival group. The physiological parameters of SIRS, pSOFA and PCIS were recorded and scored within 24 h after PICU admission. The general clinical data and some laboratory results were recorded. The area under the curve (AUC) of the receiver operating characteristic curve was used to compare the predictive value of SIRS, pSOFA and PCIS in mortality of pediatric sepsis.Results:Amongst 447 children with sepsis, 260 patients were male and 187 patients were female, aged 2.5 (0.8, 7.0) years, 405 patients were in the survival group and 42 patients were in the non-survival group. 418 patients (93.5%) met the criteria of SIRS, and 440 patients (98.4%) met the criteria of pSOFA≥2. There was no significant difference in the number of items meeting the SIRS criteria between the survival group and the non-survival group (3(2, 4) vs. 3(3, 4) points, Z=1.30, P=0.192). The pSOFA score of the non-survival group was significantly higher than that of the survival group (9(6, 12) vs. 4(3, 7) points, Z=6.56, P<0.001), and the PCIS score was significantly lower than that of the survival group (72(68, 81) vs. 82(76, 88) points, Z=5.90, P<0.001). The predictive value of pSOFA (AUC=0.82) and PCIS (AUC=0.78) for sepsis mortality was significantly higher than that of SIRS (AUC=0.56) ( Z=6.59, 4.23, both P<0.001). There was no significant difference between pSOFA and PCIS ( Z=1.35, P=0.176). Platelet count, procalcitonin, lactic acid, albumin, creatinine, total bilirubin, activated partial thromboplastin time, prothrombin time and international normalized ratio were all able to predict mortality of sepsis to a certain degree (AUC=0.64, 0.68, 0.80, 0.64, 0.68, 0.60, 0.77, 0.75, 0.76, all P<0.05). Conclusion:Compared with SIRS, both pSOFA and PCIS had better predictive value in the mortality of pediatric sepsis in PICU.

Objective To explore the effect of a mobile health intervention model based on self-determination theory on subthreshold depression in breast cancer patients.Methods By convenience sampling method,74 patients with breast cancer subthreshold depression who received chemotherapy in the breast department of a tertiary hospital in Guangxi from July 2021 to August 2022 were selected as the research subjects.According to the order of admission time,the patients admitted from February 2022 to August 2022 were taken as an experimental group,and the patients admitted from July 2021 to January 2022 were taken as a control group,with 37 cases in each group.On the basis of routine nursing,the experimental group implemented a mobile health intervention model based on self-determination theory.The control group received routine nursing,with every 21 days for 1 cycle and a total of 4 cycles of intervention.Before and after the intervention,the Centre for Epidemiological Studies Depression Scale(CES-D),Hamilton Rating Scale for Depression(HAMD-17),Basic Psychological Needs Satisfaction Scale(BPNS)and Functional Assessment of Cancer Therapy-Breast(FACT-B)were used to evaluate the intervention effect.Results 34 patients in the experimental group and 36 patients in the control group completed the study.After intervention,the CES-D score and HAMD-17 score of the 2 groups were lower than those before intervention(P＜0.05);the CES-D score and HAMD-17 score of the experimental group were lower than those of the control group,and the difference was statistically significant(t=7.748,P＜0.001;t=8.150,P＜0.001).The BPNS scores of the 2 groups were higher than those before the intervention,and the BPNS score of the experimental group was significantly higher than that of the control group(t=-6.534,P＜0.001).The scores of FACT-B in the 2 groups were higher than those before the intervention,and the scores of FACT-B in the experimental group were significantly higher than those in the control group(t=-4.579,P＜0.001).Conclusion The mobile health intervention model based on self-determination theory can improve the subthreshold depression,self-determination and quality of life of breast cancer patients.

Diabetic cognitive dysfunction （DCD） is one of the complications of diabetes， which is characterized by impaired brain structure and progressively decreased learning and memory ability. With the increasing incidence of diabetes worldwide， DCD has become a serious medical and social problem. However， its pathophysiological mechanisms are not well understood. The occurrence and development of DCD involve multiple pathological links and mechanisms， and the prevention and treatment require multi-link and multi-target therapeutic measures. At present， there is no specific drug to prevent or improve DCD. Hypoglycemic drugs such as metformin and vigagliptin or anti-dementia drug including Donepezil are commonly used in clinical treatment to delay the occurrence and progression of cognitive dysfunction， but these drugs have a single target and obvious side effects. Traditional Chinese medicine has a long history in the prevention and treatment of diabetes and central cognitive diseases， and it has many unique advantages such as multiple components， multiple targets， side effects， and low price. A large number of studies have confirmed that traditional Chinese medicine has a significant prevention and treatment effect on DCD， which can improve insulin resistance， synaptic dysfunction， inflammation， oxidative stress， endoplasmic reticulum stress， and neuronal apoptosis by regulating phosphatidylin-ositol 3-kinase （PI3K）/protein kinase B （Akt）， advanced glycation end products （AGEs）/advanced glycation end products receptor （RAGE）/nuclear transcription factor-κB （NF-κB）， NOD-like receptor thermal protein domain associated protein 3 （NLRP3） inflammasome， and endoplasmic reticulum stress and nuclear factor E₂ related factor 2 （Nrf2）/antioxidant response element （ARE） signaling pathways. This article reviewed the effects and related mechanisms of traditional Chinese medicine on DCD in recent years， so as to provide a reference for the prevention and treatment of DCD by traditional Chinese medicine.