Artificial intelligence （AI） is gradually being applied in the field of decision-making support for the daily care of the older adults with disabilities. However， due to their limited cognitive functions， information asymmetry with medical staff and technical parties， and a certain degree of emotional deprivation， the older adults with disabilities are in a structurally vulnerable position. Against this background， several ethical dilemmas arise when AI technology intervenes in care decision-making. First， the informed consent process is difficult to genuinely implement. Second， algorithms based on average models tend to ignore individual differences， leading to “de-personalization” of services. Third， over-reliance on technology may further weaken humanistic care， thereby undermining the individual dignity of the older adults with disabilities. Fourth， in the care decision-making involving the joint participation of the older adults with disabilities， caregivers， medical teams， and AI systems， the boundaries of responsibility among all parties remain unclear， making it difficult to assign accountability when adverse outcomes occur. Drawing on the theories of vulnerability ethics， interactive ethics， and care ethics， this paper proposes a “vulnerability-interaction-care” path and put forward three-tiered countermeasures. The first was baseline safeguards， preventing the exploitation of the vulnerability of the older adults with disabilities and their caregivers， and requiring further safeguards for their dignity. The second was process protection， enhancing transparency and accountability within the human-machine collaboration framework， as well as establishing a multi-party consultation mechanism. The third was capacity empowerment， improving the subjectivity of the older adults with disabilities through age-appropriate interaction， structured expression of intentions， and caregiver participation.

The widespread application of medical artificial intelligence （AI） has brought technological breakthroughs to traditional diagnosis and treatment and has also altered the traditional doctor-patient interaction mode and formed a new doctor-patient relationship of “doctor-medical AI-patient” which faces a series of challenges. The intervention of AI may form a new “paternalistic style，” affecting the shared decision-making model. When its recommendations lack explanation， it may lead to clinical decision-making paralysis and affect the doctor-patient trust relationships. There may be confusion between the roles and responsibilities of AI and doctors in the process of medical practice， affecting the establishment of an emotionally responsible doctor-patient relationship. Through an in-depth analysis of the impact and causes of medical AI on the doctor-patient relationships， this paper proposed that a collaborative mechanism should be established between AI and professional doctors to complement each other， clarifying the auxiliary status of AI， reinforcing the dominant role of doctors， enhancing the regulatory mechanism， and dynamically improved the doctor-patient relationships to promote the healthy and orderly development of smart healthcare.

[Objective] To explore the strategy of blood management in patients with massive transfusion in the frigid plateau region. [Methods] The treatment process of a patient with liver rupture in the frigid plateau region was analyzed, and the blood management strategy of the frigid plateau region was discussed in combination with the difficulties of blood transfusion and literature review. [Results] The preoperative complete blood count (CBC) test results of the patient were as follows: RBC 3.14×10¹²/L, Hb 10⁶ g/L, HCT 30.40%, PLT 115.00×10⁹/L; coagulation function: PT 18.9 s, FiB 1.31 g/L, DD > 6 μg/mL, FDP 25.86 μg/mL; ultrasound examination and imaging manifestations suggested liver contusion and laceration / intraparenchymal hematoma, splenic contusion and laceration, and massive blood accumulation in the abdominal cavity; it was estimated that the patient's blood loss was ≥ 2 000 mL, and massive blood transfusion was required during the operation; red blood cell components were timely transfused during the operation, and the blood component transfusion was guided according to the patient's CBC and coagulation function test results, providing strong support and guarantee for the successful treatment of the patient. The patient recovered well after the operation, and the CBC test results were as follows: RBC 4.32×10¹²/L, Hb 144 g/L, HCT 39.50%, PLT 329.00×10⁹/L; coagulation function: APTT 29.3 s, PT 12.1 s, FiB 2.728 g/L, DD>6 μg/mL, FDP 25.86 μg/mL. The patient was discharged after 20 days, and regular follow-up reexamination showed no abnormal results. [Conclusion] Individualized blood management strategy should comprehensively consider the patient’s clinical symptoms, the degree of hemoglobin decline, dynamic coagulation test results and existing treatment conditions. Efficient and reasonable patient blood management strategies can effectively improve the clinical outcomes of massive transfusion patients in the frigid plateau region.

BACKGROUND: Endoscopic sphincterotomy (EST) is widely used to treat common bile duct stones (CBDS); however, long-term studies have revealed the increasing incidence of recurrent CBDS after EST. Loss of sphincter of Oddi function after EST was the main cause of recurrent CBDS. Reparation of the sphincter of Oddi is therefore crucial. This study aims to investigate the effectiveness and safety of endoclip papilloplasty (ECPP) for repairing the sphincter of Oddi and elucidate its mechanism. METHODS: Eight healthy Bama minipigs were randomly divided into the EST group and the ECPP group at a 1:1 ratio, and bile samples were collected before endoscopy and 6 months later. All minipigs underwent transabdominal biliary ultrasonography for the diagnosis of cholelithiasis 6 months after endoscopy. The biliary microbiota composition and alpha and beta diversity were analyzed by 16S ribosomal RNA gene sequencing. Differential metabolites were analyzed by bile acid metabolomics to explore the predictive indicators of cholelithiasis. RESULTS: Three minipigs were diagnosed with cholelithiasis in the EST group, while none in the ECPP group showed cholelithiasis. The biliary Firmicutes/Bacteroidota (F/B) ratio was increased after EST and decreased after ECPP. The Chao1 and observed species index significantly decreased 6 months after EST ( P  = 0.017 and 0.018, respectively); however, the biliary α-diversity was similar before and 6 months after ECPP. The β-diversity significantly differed in the EST group before and 6 months after EST, as well as in the ECPP group before and 6 months after ECPP (analysis of similarities [ANOSIM]: R  = 0.917, P  = 0.040; R  = 0.740, P  = 0.035; respectively). Glycolithocholic acid (GLCA) and taurolithocholic acid (TLCA) accumulated in bile 6 months after EST. CONCLUSIONS ECPP has less impact on the biliary microenvironment than EST and prevents duodenobiliary reflux by repairing the sphincter of Oddi. The bile levels of GLCA and TLCA may be used to predict the risk of cholelithiasis.
Animals ; Swine, Miniature ; Swine ; Cholelithiasis/prevention & control* ; Sphincterotomy, Endoscopic/methods* ; Sphincter of Oddi/surgery* ; Female ; Male

Antimicrobial resistance (AMR) has emerged as a major global public health challenge, with traditional prevention and control methods exhibiting significant limitations in detection efficiency, data processing, and clinical decision-making. Leveraging its robust capabilities in data analysis and pattern recognition, artificial intelligence (AI) technology has been widely applied across multiple critical aspects of AMR containment. Current evidence demonstrates that AI technologies can significantly enhance the efficiency of resistancediagnosis, optimize personalized treatment strategies, and improve real-time monitoring of resistant pathogen transmission. Despite persistent challenges such as data heterogeneity, model interpretability, and ethical compliance in practical applications, AI holds immense promise in supporting precision infection management and addressing the growing crisis of antimicrobial resistance.This article systematically reviews the clinical applications of AI in AMR prevention and control, including resistance detection and prediction based on mass spectrometry and genomic data, the use of clinical decision support systems in anti-infective therapy, as well as the role of AI in epidemiological surveillance, pathogen tracking, early warning systems, and novel antimicrobial drug discovery aiming to provide reference for clinical practice.

A 62-year-old male, was admitted to the hospital, with a chief complaint of fever lasting over 10 days and leukopenia and thrombocytopenia for 2 days. Ten days prior to admission, the patient experienced intermittent fever without obvious incentive factors. The breath sounds in both lungs were coarse, without accompanying dry or moist rales. Color Doppler Ultrasound indicated mild splenomegaly and multiple lymphadenectasis in the bilateral cervical, axillary, and inguinal regions. Morphological examination of bone marrow cells demonstrated abnormally large blasts, with some of the nuclei being rather irregular and cytoplasmic vacuoles. Immunophenotyping results identified this group of blast cells as immature monocytes. Karyotype analysis of chromosomes showed clonal abnormalities, with 19 out of 20 cells exhibiting near-tetraploid karyotypes, including complex karyotypic abnormalities involving chromosome17.Targeted next-generation sequencing (NGS) detected gene mutations associated with hematological malignancies that have definite or potential clinical significance,including TP53, SRSF2, STAG2, and ARID2, with variant allele frequencies (VAF) of 63.10%, 30.30%, 0.80%, and 0.60%, respectively. Integrating laboratory findings, the diagnosis was diagnosed as AML-M5 at high-risk. After receiving chemotherapy with the regimen of azacitidine combined with venetoclax, the patient passed away more than 20 days later.

Objective:To explore the correlation between Chinese visceral adiposity index (CVAI) and metabolic associated fatty liver disease (MAFLD) so as to evaluate its predictive value for MAFLD.Methods:Six hundred and thirteen cases admitted to the Department of Gastroenterology, Zhongshan Hospital Affiliated to Dalian University from June 2022 to August 2023 were selected and divided into the MAFLD group ( n=312) and the non-MAFLD group ( n=301) according to the diagnostic criteria of MAFLD. The clinical data differences between the two groups were compared. The MAFLD group was divided into a mild MAFLD group ( n=243) and a moderate to severe MAFLD group ( n=69) according to the liver/spleen CT value. The differences in body fat indices such as CVAI, visceral fat index (VAI), and visceral fat area (VFA) were compared between subjects with different degrees of MAFLD. The Spearman test was used to analyze the correlation between CVAI, VAI, and various clinical indicators. The subjects were divided into groups (Q1-Q4) according to the quartile levels of CVAI and VAI, and the distribution of MAFLD conditions among the groups was compared. Logistic regression analysis was used to determine the occurrence risk of MAFLD at different CVAI and VAI levels. The receiver operating characteristic curve was drawn. The area under the receiver operating characteristic curve (AUC) was calculated to evaluate the predictive value of CVAI, VAI, VFA, waist circumference, and body mass index for MAFLD. The DeLong test was used to compare the differences in the AUC of each predictive index. Results:The prevalence of hypertension and type 2 diabetes mellitus, and the levels of systolic blood pressure, diastolic blood pressure, CVAI, VAI, VFA, subcutaneous fat area, waist circumference, body mass index, total cholesterol, triglycerides, low-density lipoprotein cholesterol, fasting blood glucose, fasting insulin, homeostasis model assessment of insulin resistance, high-sensitivity C-reactive protein, alanine aminotransferase, aspartate aminotransferase, γ-glutamyl transferase, and serum uric acid were higher in the MAFLD group than the non-MAFLD group ( P<0.05), while the level of high-density lipoprotein cholesterol was lower than the non-MAFLD group ( P<0.001). The levels of CVAI, VAI, VFA, waist circumference, and body mass index were higher in the mild and the moderate to severe MAFLD group than those in the non-MAFLD group ( P<0.001). The detection rate of MAFLD gradually increased( χ2=176.953, 133.659, P<0.001) with the increase of CVAI and VAI levels. Correlation analysis showed that CVAI was positively correlated with VFA ( r=0.755, P<0.001) and the homeostasis model assessment of insulin resistance ( r=0.579, P<0.001). Multivariate logistic regression analysis showed that after adjusting for various risk factors, the risk of MAFLD in the Q4 group of the CVAI subgroup was still 7.159 times that of the Q1 group (95% CI:3.126-16.392, P<0.001), and the risk of MAFLD in the Q4 group of the VAI subgroup was still 4.667 times that of the Q1 group (95% CI: 2.187-9.962, P<0.001). The receiver operating characteristic curve results showed that the AUC of CVAI for predicting MAFLD was similar to that of VFA (0.822 vs. 0.826), and higher than that of VAI (AUC 0.772), waist circumference (AUC 0.796), and body mass index (AUC 0.755). The optimal critical value of CVAI for predicting the risk of MAFLD was 125.50, with sensitivity and specificity at 70.5% and 79.1%, respectively. Conclusion:The patient's risk of MAFLD increases with the rise of CVAI level, and CVAI has a favorable predictive value for the occurrence of MAFLD.

Objective To investigate the distribution and antimicrobial resistance profiles of clinically isolated Haemophilus influenzae and Moraxella catarrhalis in hospitals across China from 2015 to 2021,and provide evidence for rational use of antimicrobial agents.Methods Data of H.influenzae and M.catarrhalis strains isolated from 2015 to 2021 in CHINET program were collected for analysis,and antimicrobial susceptibility testing was performed by disc diffusion method or automated systems according to the uniform protocol of CHINET.The results were interpreted according to the CLSI breakpoints in 2022.Beta-lactamases was detected by using nitrocefin disk.Results From 2015 to 2021,a total of 43 642 strains of Haemophilus species were isolated,accounting for 2.91％of the total clinical isolates and 4.07％of Gram-negative bacteria in CHINET program.Among the 40 437 strains of H.influenzae,66.89％were isolated from children and 33.11％were isolated from adults.More than 90％of the H.influenzae strains were isolated from respiratory tract specimens.The prevalence of β-lactamase was 53.79％in H.influenzae strains.The H.influenzae strains isolated from children showed higher resistance rate than the strains isolated from adults.Overall,779 strains of H.influenzae did not produce β-lactamase but were resistant to ampicillin(BLNAR).Beta-lactamase-producing strains showed significantly higher resistance rates to these antimicrobial agents than the β-lactamase-nonproducing strains.Of the 16 191 M.catarrhalis strains,80.06％were isolated from children and 19.94％isolated from adults.M.catarrhalis strains were mostly susceptible to both amoxicillin-clavulanic acid and cefuroxime,evidenced by resistance rate lower than 2.0％.Conclusions The emergence of antibiotic-resistant H.influenzae due to β-lactamase production poses a challenge for clinical anti-infective treatment.Therefore,it is very important to implement antibiotic resistance surveillance for H.influenzae and guide rational antibiotic use.All local clinical microbiology laboratories should actively improve antibiotic susceptibility testing and strengthen antibiotic resistance surveillance for H.influenzae.

Objective To understand the changing composition and antibiotic resistance of bacterial species in the clinical isolates from outpatient and emergency department(hereinafter referred to as outpatients)and inpatient children over time in various hospitals,and to provide laboratory evidence for rational antibiotic use.Methods The data on clinically isolated pathogenic bacteria and antimicrobial susceptibility of isolates from outpatients and inpatient children in the CHINET program from 2015 to 2021 were collected and analyzed.Results A total of 278 471 isolates were isolated from pediatric patients in the CHINET program from 2015 to 2021.About 17.1％of the strains were isolated from outpatients,primarily group A β-hemolytic Streptococcus,Escherichia coli,and Staphylococcus aureus.Most of the strains(82.9％)were isolated from inpatients,mainly SS.aureus,E.coli,and H.influenzae.The prevalence of methicillin-resistant S.aureus(MRSA)in outpatients(24.5％)was lower than that in inpatient children(31.5％).The MRSA isolates from outpatients showed lower resistance rates to the antibiotics tested than the strains isolated from inpatient children.The prevalence of vancomycin-resistant Enterococcus faecalis or E.faecium and penicillin-resistant S.pneumoniae was low in either outpatients or inpatient children.S.pneumoniae,β-hemolytic Streptococcus and S.viridans showed high resistance rates to erythromycin.The prevalence of erythromycin-resistant group A β-hemolytic Streptococcus was higher in outpatients than that in inpatient children.The prevalence of β-lactamase-producing H.influenzae showed an overall upward trend in children,but lower in outpatients(45.1％)than in inpatient children(59.4％).The prevalence of carbapenem-resistant Klebsiella pneumoniae(CRKpn),carbapenem-resistant Pseudomonas aeruginosa(CRPae)and carbapenem-resistant Acinetobacter baumannii(CRAba)was 14％,11.7％,47.8％in outpatients,but 24.2％,20.6％,and 52.8％in inpatient children,respectively.The prevalence of multidrug-resistant E.coli,K.pneumoniae,Proteus mirabilis,P.aeruginosa and A.baumannii strains was lower in outpatients than in inpatient children.The prevalence of fluoroquinolone-resistant E.coli,ESBLs-producing K.pneumoniae,ESBLs-producing P.mirabilis,carbapenem-resistant E.coli(CREco),CRKpn,and CRPae was lower in children in outpatients than in inpatient children,but the prevalence of CRAba in 2021 was higher than in inpatient children.Conclusions The distribution of clinical isolates from children is different between outpatients and inpatients.The prevalence of MRSA,ESBL,and CRO was higher in inpatient children than in outpatients.Antibiotics should be used rationally in clinical practice based on etiological diagnosis and antimicrobial susceptibility test results.Ongoing antimicrobial resistance surveillance and prevention and control of hospital infections are crucial to curbing bacterial resistance.