Background: and Purpose Ruptured intracranial aneurysms (RIA) are associated with a mortality rate of up to 40% in the Chinese population, highlighting the critical need for targeted treatment interventions for at-risk individuals. Although the impact of aldehyde dehydrogenase 2 (ALDH2) gene mutations on susceptibility to intracranial aneurysms (IA) is well documented, the potential connection between ALDH2 rs671 single-nucleotide polymorphism (SNP) and RIA remains unexplored. Given the increased prevalence of ALDH2 gene mutations among Chinese Han individuals, it is clinically relevant to investigate the link between ALDH2 rs671 SNP and IA rupture. Methods: A prospective study was conducted on 546 patients diagnosed with IA to investigate the association between ALDH2 rs671 SNP and the risk of IA rupture. Results: The ALDH2 rs671 SNP (ALDH2*2) was significantly more prevalent in patients with unruptured IA (UIA) than in those with RIA (32.56% vs. 18.58%, P=0.004). Multivariate logistic regression analysis revealed that people with the ALDH2 mutation (ALDH2*1/*2 and ALDH2*2/*2 gene type) had a significantly reduced odds ratio (OR=0.49; 95% confidence level [CI] 0.27–0.88; P=0.018) for RIAs. Age-specific subgroup analysis indicated that the ALDH2 mutation provided a stronger protective effect in individuals aged 60 years and above with IA compared to those under 60 years old (OR=0.38 vs. OR=0.52, both P<0.05). Conclusion The incidence of RIA was significantly higher in individuals with a normal ALDH2 gene (ALDH2*1/*1) than in those with an ALDH2 rs671 SNP (ALDH2*1/*2 or ALDH2*2/*2). ALDH2 rs671 SNP may serve as a protective factor against RIA in the Chinese Han population.

Background: and Purpose Ruptured intracranial aneurysms (RIA) are associated with a mortality rate of up to 40% in the Chinese population, highlighting the critical need for targeted treatment interventions for at-risk individuals. Although the impact of aldehyde dehydrogenase 2 (ALDH2) gene mutations on susceptibility to intracranial aneurysms (IA) is well documented, the potential connection between ALDH2 rs671 single-nucleotide polymorphism (SNP) and RIA remains unexplored. Given the increased prevalence of ALDH2 gene mutations among Chinese Han individuals, it is clinically relevant to investigate the link between ALDH2 rs671 SNP and IA rupture. Methods: A prospective study was conducted on 546 patients diagnosed with IA to investigate the association between ALDH2 rs671 SNP and the risk of IA rupture. Results: The ALDH2 rs671 SNP (ALDH2*2) was significantly more prevalent in patients with unruptured IA (UIA) than in those with RIA (32.56% vs. 18.58%, P=0.004). Multivariate logistic regression analysis revealed that people with the ALDH2 mutation (ALDH2*1/*2 and ALDH2*2/*2 gene type) had a significantly reduced odds ratio (OR=0.49; 95% confidence level [CI] 0.27–0.88; P=0.018) for RIAs. Age-specific subgroup analysis indicated that the ALDH2 mutation provided a stronger protective effect in individuals aged 60 years and above with IA compared to those under 60 years old (OR=0.38 vs. OR=0.52, both P<0.05). Conclusion The incidence of RIA was significantly higher in individuals with a normal ALDH2 gene (ALDH2*1/*1) than in those with an ALDH2 rs671 SNP (ALDH2*1/*2 or ALDH2*2/*2). ALDH2 rs671 SNP may serve as a protective factor against RIA in the Chinese Han population.

Background: and Purpose Ruptured intracranial aneurysms (RIA) are associated with a mortality rate of up to 40% in the Chinese population, highlighting the critical need for targeted treatment interventions for at-risk individuals. Although the impact of aldehyde dehydrogenase 2 (ALDH2) gene mutations on susceptibility to intracranial aneurysms (IA) is well documented, the potential connection between ALDH2 rs671 single-nucleotide polymorphism (SNP) and RIA remains unexplored. Given the increased prevalence of ALDH2 gene mutations among Chinese Han individuals, it is clinically relevant to investigate the link between ALDH2 rs671 SNP and IA rupture. Methods: A prospective study was conducted on 546 patients diagnosed with IA to investigate the association between ALDH2 rs671 SNP and the risk of IA rupture. Results: The ALDH2 rs671 SNP (ALDH2*2) was significantly more prevalent in patients with unruptured IA (UIA) than in those with RIA (32.56% vs. 18.58%, P=0.004). Multivariate logistic regression analysis revealed that people with the ALDH2 mutation (ALDH2*1/*2 and ALDH2*2/*2 gene type) had a significantly reduced odds ratio (OR=0.49; 95% confidence level [CI] 0.27–0.88; P=0.018) for RIAs. Age-specific subgroup analysis indicated that the ALDH2 mutation provided a stronger protective effect in individuals aged 60 years and above with IA compared to those under 60 years old (OR=0.38 vs. OR=0.52, both P<0.05). Conclusion The incidence of RIA was significantly higher in individuals with a normal ALDH2 gene (ALDH2*1/*1) than in those with an ALDH2 rs671 SNP (ALDH2*1/*2 or ALDH2*2/*2). ALDH2 rs671 SNP may serve as a protective factor against RIA in the Chinese Han population.

Background: Intravenous immunoglobulin (IVIG)-resistant Kawasaki disease is associated with coronary artery lesion development.Purpose: This study aimed to explore the factors associated with IVIG-resistance and construct and validate an interpretable machine learning (ML) prediction model in clinical practice. Methods: Between December 2014 and November 2022, 602 patients were screened and risk factors for IVIG-resistance investigated. Five ML models are used to establish an optimal prediction model. The SHapley Additive exPlanations (SHAP) method was used to interpret the ML model. Results: Na+, hemoglobin (Hb), C-reactive protein (CRP), and globulin were independent risk factors for IVIG-resistance. A nonlinear relationship was identified between globulin level and IVIG-resistance. The XGBoost model exhibited excellent performance, with an area under the receiver operating characteristic curve of 0.821, accuracy of 0.748, sensitivity of 0.889, and specificity of 0.683 in the testing set. The XGBoost model was interpreted globally and locally using the SHAP method. Conclusion Na+, Hb, CRP, and globulin levels were independently associated with IVIG-resistance. Our findings demonstrate that ML models can reliably predict IVIG-resistance. Moreover, use of the SHAP method to interpret the established XGBoost model's findings would provide evidence of IVIG-resistance and guide the individualized treatment of Kawasaki disease.

Background: Intravenous immunoglobulin (IVIG)-resistant Kawasaki disease is associated with coronary artery lesion development.Purpose: This study aimed to explore the factors associated with IVIG-resistance and construct and validate an interpretable machine learning (ML) prediction model in clinical practice. Methods: Between December 2014 and November 2022, 602 patients were screened and risk factors for IVIG-resistance investigated. Five ML models are used to establish an optimal prediction model. The SHapley Additive exPlanations (SHAP) method was used to interpret the ML model. Results: Na+, hemoglobin (Hb), C-reactive protein (CRP), and globulin were independent risk factors for IVIG-resistance. A nonlinear relationship was identified between globulin level and IVIG-resistance. The XGBoost model exhibited excellent performance, with an area under the receiver operating characteristic curve of 0.821, accuracy of 0.748, sensitivity of 0.889, and specificity of 0.683 in the testing set. The XGBoost model was interpreted globally and locally using the SHAP method. Conclusion Na+, Hb, CRP, and globulin levels were independently associated with IVIG-resistance. Our findings demonstrate that ML models can reliably predict IVIG-resistance. Moreover, use of the SHAP method to interpret the established XGBoost model's findings would provide evidence of IVIG-resistance and guide the individualized treatment of Kawasaki disease.

Background: Intravenous immunoglobulin (IVIG)-resistant Kawasaki disease is associated with coronary artery lesion development.Purpose: This study aimed to explore the factors associated with IVIG-resistance and construct and validate an interpretable machine learning (ML) prediction model in clinical practice. Methods: Between December 2014 and November 2022, 602 patients were screened and risk factors for IVIG-resistance investigated. Five ML models are used to establish an optimal prediction model. The SHapley Additive exPlanations (SHAP) method was used to interpret the ML model. Results: Na+, hemoglobin (Hb), C-reactive protein (CRP), and globulin were independent risk factors for IVIG-resistance. A nonlinear relationship was identified between globulin level and IVIG-resistance. The XGBoost model exhibited excellent performance, with an area under the receiver operating characteristic curve of 0.821, accuracy of 0.748, sensitivity of 0.889, and specificity of 0.683 in the testing set. The XGBoost model was interpreted globally and locally using the SHAP method. Conclusion Na+, Hb, CRP, and globulin levels were independently associated with IVIG-resistance. Our findings demonstrate that ML models can reliably predict IVIG-resistance. Moreover, use of the SHAP method to interpret the established XGBoost model's findings would provide evidence of IVIG-resistance and guide the individualized treatment of Kawasaki disease.

Background: Intravenous immunoglobulin (IVIG)-resistant Kawasaki disease is associated with coronary artery lesion development.Purpose: This study aimed to explore the factors associated with IVIG-resistance and construct and validate an interpretable machine learning (ML) prediction model in clinical practice. Methods: Between December 2014 and November 2022, 602 patients were screened and risk factors for IVIG-resistance investigated. Five ML models are used to establish an optimal prediction model. The SHapley Additive exPlanations (SHAP) method was used to interpret the ML model. Results: Na+, hemoglobin (Hb), C-reactive protein (CRP), and globulin were independent risk factors for IVIG-resistance. A nonlinear relationship was identified between globulin level and IVIG-resistance. The XGBoost model exhibited excellent performance, with an area under the receiver operating characteristic curve of 0.821, accuracy of 0.748, sensitivity of 0.889, and specificity of 0.683 in the testing set. The XGBoost model was interpreted globally and locally using the SHAP method. Conclusion Na+, Hb, CRP, and globulin levels were independently associated with IVIG-resistance. Our findings demonstrate that ML models can reliably predict IVIG-resistance. Moreover, use of the SHAP method to interpret the established XGBoost model's findings would provide evidence of IVIG-resistance and guide the individualized treatment of Kawasaki disease.

Objective Tissue uptake and distribution of nano-/microplastics was studied at a single high dose by gavage in vivo.Methods Fluorescent microspheres (100 nm, 3 μm, and 10 μm) were given once at a dose of 200 mg/(kg·body weight). The fluorescence intensity (FI) in observed organs was measured using the IVIS Spectrum at 0.5, 1, 2, and 4 h after administration. Histopathology was performed to corroborate these findings.Results In the 100 nm group, the FI of the stomach and small intestine were highest at 0.5 h, and the FI of the large intestine, excrement, lung, kidney, liver, and skeletal muscles were highest at 4 h compared with the control group (P < 0.05). In the 3 μm group, the FI only increased in the lung at 2 h (P < 0.05). In the 10 μm group, the FI increased in the large intestine and excrement at 2 h, and in the kidney at 4 h (P < 0.05). The presence of nano-/microplastics in tissues was further verified by histopathology. The peak time of nanoplastic absorption in blood was confirmed.Conclusion Nanoplastics translocated rapidly to observed organs/tissues through blood circulation;however, only small amounts of MPs could penetrate the organs.

Bacterial biofilms gave rise to persistent infections and multi-organ failure, thereby posing a serious threat to human health. Biofilms were formed by cross-linking of hydrophobic extracellular polymeric substances (EPS), such as proteins, polysaccharides, and eDNA, which were synthesized by bacteria themselves after adhesion and colonization on biological surfaces. They had the characteristics of dense structure, high adhesiveness and low drug permeability, and had been found in many human organs or tissues, such as the brain, heart, liver, spleen, lungs, kidneys, gastrointestinal tract, and skeleton. By releasing pro-inflammatory bacterial metabolites including endotoxins, exotoxins and interleukin, biofilms stimulated the body’s immune system to secrete inflammatory factors. These factors triggered local inflammation and chronic infections. Those were the key reason for the failure of traditional clinical drug therapy for infectious diseases.In order to cope with the increasingly severe drug-resistant infections, it was urgent to develop new therapeutic strategies for bacterial-biofilm eradication and anti-bacterial infections. Based on the nanoscale structure and biocompatible activity, nanobiomaterials had the advantages of specific targeting, intelligent delivery, high drug loading and low toxicity, which could realize efficient intervention and precise treatment of drug-resistant bacterial biofilms. This paper highlighted multiple strategies of biofilms eradication based on nanobiomaterials. For example, nanobiomaterials combined with EPS degrading enzymes could be used for targeted hydrolysis of bacterial biofilms, and effectively increased the drug enrichment within biofilms. By loading quorum sensing inhibitors, nanotechnology was also an effective strategy for eradicating bacterial biofilms and recovering the infectious symptoms. Nanobiomaterials could intervene the bacterial metabolism and break the bacterial survival homeostasis by blocking the uptake of nutrients. Moreover, energy-driven micro-nano robotics had shown excellent performance in active delivery and biofilm eradication. Micro-nano robots could penetrate physiological barriers by exogenous or endogenous driving modes such as by biological or chemical methods, ultrasound, and magnetic field, and deliver drugs to the infection sites accurately. Achieving this using conventional drugs was difficult. Overall, the paper described the biological properties and drug-resistant molecular mechanisms of bacterial biofilms, and highlighted therapeutic strategies from different perspectives by nanobiomaterials, such as dispersing bacterial mature biofilms, blocking quorum sensing, inhibiting bacterial metabolism, and energy driving penetration. In addition, we presented the key challenges still faced by nanobiomaterials in combating bacterial biofilm infections. Firstly, the dense structure of EPS caused biofilms spatial heterogeneity and metabolic heterogeneity, which created exacting requirements for the design, construction and preparation process of nanobiomaterials. Secondly, biofilm disruption carried the risk of spread and infection the pathogenic bacteria, which might lead to other infections. Finally, we emphasized the role of nanobiomaterials in the development trends and translational prospects in biofilm treatment.

Patients with severe trauma require an extremely timely treatment and transfusion plays an irreplaceable role in the emergency treatment of such patients. An increasing number of evidence-based medicinal evidences and clinical practices suggest that patients with severe traumatic bleeding benefit from early transfusion of low-titer group O whole blood or hemostatic resuscitation with red blood cells, plasma and platelet of a balanced ratio. However, the current domestic mode of blood supply cannot fully meet the requirements of timely and effective blood transfusion for emergency treatment of patients with severe trauma in clinical practice. In order to solve the key problems in blood supply and blood transfusion strategies for emergency treatment of severe trauma, Branch of Clinical Transfusion Medicine of Chinese Medical Association, Group for Trauma Emergency Care and Multiple Injuries of Trauma Branch of Chinese Medical Association, Young Scholar Group of Disaster Medicine Branch of Chinese Medical Association organized domestic experts of blood transfusion medicine and trauma treatment to jointly formulate Chinese expert consensus on blood support mode and blood transfusion strategies for emergency treatment of severe trauma patients ( version 2024). Based on the evidence-based medical evidence and Delphi method of expert consultation and voting, 10 recommendations were put forward from two aspects of blood support mode and transfusion strategies, aiming to provide a reference for transfusion resuscitation in the emergency treatment of severe trauma and further improve the success rate of treatment of patients with severe trauma.