Based on plasma lipidomics combined with machine learning approaches, this study aimed to screen molecular biomarkers for the diagnosis of early-stage lung cancer in elderly patients and to evaluate their diagnostic performance.

The innate immune system can be boosted in response to subsequent triggers by pre-exposure to microbes or microbial products, known as “trained immunity”. Compared to classical immune memory, innate trained immunity has several different features. Firstly, the molecules involved in trained immunity differ from those involved in classical immune memory. Innate trained immunity mainly involves innate immune cells (e.g., myeloid immune cells, natural killer cells, innate lymphoid cells) and their effector molecules (e.g., pattern recognition receptor (PRR), various cytokines), as well as some kinds of non-immune cells (e.g., microglial cells). Secondly, the increased responsiveness to secondary stimuli during innate trained immunity is not specific to a particular pathogen, but influences epigenetic reprogramming in the cell through signaling pathways, leading to the sustained changes in genes transcriptional process, which ultimately affects cellular physiology without permanent genetic changes (e.g., mutations or recombination). Finally, innate trained immunity relies on an altered functional state of innate immune cells that could persist for weeks to months after initial stimulus removal. An appropriate inducer could induce trained immunity in innate lymphocytes, such as exogenous stimulants (including vaccines) and endogenous stimulants, which was firstly discovered in bone marrow derived immune cells. However, mature bone marrow derived immune cells are short-lived cells, that may not be able to transmit memory phenotypes to their offspring and provide long-term protection. Therefore, trained immunity is more likely to be relied on long-lived cells, such as epithelial stem cells, mesenchymal stromal cells and non-immune cells such as fibroblasts. Epigenetic reprogramming is one of the key molecular mechanisms that induces trained immunity, including DNA modifications, non-coding RNAs, histone modifications and chromatin remodeling. In addition to epigenetic reprogramming, different cellular metabolic pathways are involved in the regulation of innate trained immunity, including aerobic glycolysis, glutamine catabolism, cholesterol metabolism and fatty acid synthesis, through a series of intracellular cascade responses triggered by the recognition of PRR specific ligands. In the view of evolutionary, trained immunity is beneficial in enhancing protection against secondary infections with an induction in the evolutionary protective process against infections. Therefore, innate trained immunity plays an important role in therapy against diseases such as tumors and infections, which has signature therapeutic effects in these diseases. In organ transplantation, trained immunity has been associated with acute rejection, which prolongs the survival of allografts. However, trained immunity is not always protective but pathological in some cases, and dysregulated trained immunity contributes to the development of inflammatory and autoimmune diseases. Trained immunity provides a novel form of immune memory, but when inappropriately activated, may lead to an attack on tissues, causing autoinflammation. In autoimmune diseases such as rheumatoid arthritis and atherosclerosis, trained immunity may lead to enhance inflammation and tissue lesion in diseased regions. In Alzheimer’s disease and Parkinson’s disease, trained immunity may lead to over-activation of microglial cells, triggering neuroinflammation even nerve injury. This paper summarizes the basis and mechanisms of innate trained immunity, including the different cell types involved, the impacts on diseases and the effects as a therapeutic strategy to provide novel ideas for different diseases.

Immobilized enzyme-based enzyme electrode biosensors, characterized by high sensitivity and efficiency, strong specificity, and compact size, demonstrate broad application prospects in life science research, disease diagnosis and monitoring, etc. Immobilization of enzyme is a critical step in determining the performance (stability, sensitivity, and reproducibility) of the biosensors. Random immobilization (physical adsorption, covalent cross-linking, etc.) can easily bring about problems, such as decreased enzyme activity and relatively unstable immobilization. Whereas, directional immobilization utilizing amino acid residue mutation, affinity peptide fusion, or nucleotide-specific binding to restrict the orientation of the enzymes provides new possibilities to solve the problems caused by random immobilization. In this paper, the principles, advantages and disadvantages and the application progress of enzyme electrode biosensors of different directional immobilization strategies for enzyme molecular sensing elements by specific amino acids (lysine, histidine, cysteine, unnatural amino acid) with functional groups introduced based on site-specific mutation, affinity peptides (gold binding peptides, carbon binding peptides, carbohydrate binding domains) fused through genetic engineering, and specific binding between nucleotides and target enzymes (proteins) were reviewed, and the application fields, advantages and limitations of various immobilized enzyme interface characterization techniques were discussed, hoping to provide theoretical and technical guidance for the creation of high-performance enzyme sensing elements and the manufacture of enzyme electrode sensors.

ObjectiveTo explore the correlation between the blood stasis score of coronary heart disease（CAD） and mild cognitive impairment（MCI）， as well as the changes in plasma metabolic profile of blood stasis in patients with CAD combined with MCI（CADMCI） through a cross-sectional study， and further explore the impact of different degrees of blood stasis on the plasma metabolite profile of CADMCI patients. MethodsAccording to the diagnostic criteria of CAD and CAD blood stasis， patients hospitalized in Xiyuan Hospital of China Academy of Chinese Medical Sciences from October 2022 to October 2023 were continuously included. According to the Montreal Cognitive Assessment（MoCA） scale score， the enrolled patients were divided into CADMCI blood stasis group and CAD blood stasis group. The association between blood stasis score and MCI was analyzed by multivariate Logistic regression model. The receiver operating characteristic（ROC） curve was drawn， and the area under the curve（AUC） was calculated to evaluate the sensitivity and specificity of the model. According to the blood stasis score， the first 30 patients in the CADMCI blood stasis group and CAD blood stasis group were divided into mild blood stasis and severe blood stasis. Ultra performance liquid chromatography-quadrupole-time-of-flight mass spectrometry（UPLC-Q-TOF-MS/MS） was used to detect plasma metabolites in each group of patients. The differential metabolites were screened according to variable importance in the projection（VIP） value≥1， fold change（FC）<0.67 or >1.5， and P<0.05. ROC curve analysis was further used to evaluate the discriminatory efficiency of the screened differential metabolites for each group of samples. ResultsA total of 266 CAD patients were included in this study. Multivariate Logistic regression analysis showed that the CAD blood stasis score was significantly correlated with MCI［odds ratio（OR）=1.619， 95% confidence interval（CI） 1.223-2.142， P<0.001， ROC curve AUC was 0.615（95% CI 0.547-0.683， P=0.001）］， indicating that the CAD blood stasis score has a certain predictive value for MCI. Plasma non-targeted metabolomics analysis showed that the main differential metabolites between CAD blood stasis and CADMCI blood stasis were lipid metabolites， among which phosphatidylcholine［20∶4（5Z， 8Z， 11Z， 14Z）/P-18∶1（11Z）］ had the best discriminatory efficiency（ROC curve AUC=0.867， 95% CI 0.754-0.942）. Further analysis of the differential metabolites between mild and severe blood stasis showed that lipid metabolites were also the main differential metabolites between mild and severe blood stasis. Among them， 1α，25-dihydroxy-2β-（2-hydroxyethoxy） vitamin D₃ had the best efficacy in distinguishing mild and severe CAD blood stasis（AUC=0.813， 95% CI 0.649-0.951）， and phosphatidylcholine 34∶2 had the best efficacy in distinguishing mild and severe CADMCI blood stasis（AUC=0.819， 95% CI 0.640-0.941）. ConclusionThere is a significant correlation between CAD blood stasis score and MCI. Phosphatidylcholine metabolites play an important role in the pathogenesis of CADMCI blood stasis and severe blood stasis. The CAD blood stasis score combined with the detection of phosphatidylcholine metabolites can provide a reference for the development of early and efficient identification strategies for CADMCI.

Objective To observe the value of conventional MRI and diffusion weighted imaging(DWI)for differentiating soft tissue lymphoma(STL)and soft tissue sarcoma(STS).Methods Conventional MRI and DWI data of 25 cases of STL(STL group)and 38 cases of STS(STS group)were retrospectively analyzed.MRI features being statistically different between groups were included in logistic regression analysis to screen the independent risk factors of STL and to evaluate the sensitivity,specificity and accuracy of their combination for predicting STL.Receiver operating characteristic curve was generated,the area under the curve(AUC)was calculated to assess the diagnostic efficacy of the mean apparent diffusion coefficient(ADCmean),the minimum apparent diffusion coefficient(ADCmin),the maximum apparent diffusion coefficient(ADCmax)values for distinguishing STL from STS.Results Slightly hyperintensity on T1WI,non-necrosis,involvement of multiple muscle groups and homogeneous enhancement were all independent risk factors of STL(all P＜0.05).The sensitivity,specificity and accuracy of their combination for predicting STL was 72.00％(18/25),89.47％(34/38)and 82.54％(52/63),respectively.ADCmean,ADCmin and ADCmax values of STL was(1.06±0.18)× 10-3,(0.77±0.14)×10-3 and(1.47±0.31)× 10-3mm2/s,respectively,all lower than those of STS([1.31±0.17]× 10-3,[1.02±0.23]× 10-3 and[1.64±0.16]× 10-3 mm2/s;t=-4.829--2.498,all P＜0.05).The AUC of ADCmean,ADCmin and ADCmax values and their combination for differential diagnosis of STL and STS was 0.845,0.844,0.683 and 0.877,respectively.Conclusion Conventional MRI features,including T1WI signal intensity,necrosis,involvement of multiple muscle groups and enhancement pattern,along with ADCmean and ADCmin values derived from DWI contributed to differentiating STL and STS.

Objective:To investigate the methodological differences in the detection, the inflammatory markers and the pathogenic epidemiological characteristics of influenza A virus in clinical laboratories, in order to provide more diagnostic and epidemiological data for diagnosis and prevention for children with influenza A.Methods:A retrospective cross-sectional study was conducted to collect 96 731 patients with suspected influenza A from January 2016 to October 2024 in Nanyang City Center Hospital from the Clinical Laboratory Testing Information System, including 5 731 patients with confirmed influenza A, aged 5.2 (2.8, 43.7) years old. We analyzed the distribution of influenza A patients from age and mixed infections, the relationship between patient age and positive detection rate by restricted cubic spline (RCS), analyzed differences in testing methods used Kappa consistency testing and receiver operating characteristic (ROC) curves, established a model of inflammatory markers by logistic regression, as well as developed a prediction model and also the mutation of the hemagglutinin (HA) sequence of the influenza A subtype H3N2 virus using evolutionary tree analysis.Results:RCS analysis showed an inverted 'S' shaped non-linear relationship between the positive detection rate of influenza A and the age groups of the patients. Among the mixed infections, 1.43%(1 352/94 867) of the cases were combined with Mycoplasma pneumoniae infection. The Kappa values of reverse transcription PCR (RT-PCR) and serological indirect immunofluorescence assay (IFA) for detecting influenza A in nasopharyngeal swabs and alveolar lavage fluid in clinical laboratories were 0.632 and 0.809, respectively, and those of magnetic particle chemiluminescence assay were 0.614 and 0.668, respectively, and the area under curves in ROC curve of IFA and RT-PCR were 0.869 and 0.792, respectively. The inflammatory indexes were usually elevated in severe children compared with mild children. By binary logistic regression model analysis, neutrophil-to-lymphocyte ratio, D-dimer/fibrinogen and prognosis nutrition index were the risk factors and serum amyloid A/C reactive protein ratio was the protective factor for severe children with influenza A, and the OR values of the above factors were 1.760, 7.076, 1.045, and 0.719, respectively, and P<0.01. By the Bayesian Interdiction Criterion, the optimal seasonal autoregressive moving average mixed model for influenza A epidemics was ARIMA (1, 1, 1) (2, 1, 2) 12 with the highest prediction accuracy of 98.63%. The seven strains of H3N2 all belonged to the same isoforms, with nucleotide similarity of the HA gene ranging from 99.5% to 99.9%, and the glycosylation site, receptor-binding site, and the conserved amino acid residue Glycosylation sites, receptor binding sites and conserved amino acid residues remained unchanged. HA sequence analysis showed that the prevalent strains in Nanyang had undergone mutation to different degree compared with the vaccine strains. Conclusion:Scientific and rational testing and characteristic inflammatory markers in the clinical laboratory are of great clinical value in the diagnosis of children with severe influenza A. At the same time, the epidemiological monitoring of influenza A variants should be strengthened.

Objective To explore the predictive value of dose surface histogram(DSH)in image guided radiotherapy(IGRT)for radiotherapy-induced acute radiation proctitis(ARP)in cervical cancer(CCA).Methods Totally 380 patients with CCA IGRT admitted to some hospital from May 2019 to May 2023 were selected prospectively and randomly divided into a control group(n=1 80)and an experimental group(n=200).The patients in the 2 groups were followed up and the incidence rates of ARP were counted,and rectal dose distribution was evaluated using dose volume histogram(DVH)in the control group and DSH in the experimental group.The predictive values of DVH and DSH for ARP were evaluated and compared using ROC curves.Statistical analysis was performed using SPSS 21.0 software.Results The two groups did not have statistically significant difference in the incidence rate of ARP(P＞0.05),while there were significant differences in the evaluation indicators of the rectal dose distribution(P＜0.05).V40,V50,S40 and S50 proved to have low predictive values for grade Ⅰ-Ⅳ ARP with AUC 0.700(P＜0.05);V60 and S60 had moderate predictive values for grade Ⅰ-Ⅳ ARP with AUC greater than 0.700 and less than or equal to 0.900(P＜0.05);V70,V78,S70 and S7s showed high predictive values for grade Ⅰ-Ⅳ ARP with AUC higher than 0.900(P＜0.05).Delong's test results indicated that DVH and DSH had no significant differences in AUC when used to predict gradeⅠ-Ⅳ ARP(allP＞0.05).Conclusion DSH is essentially the same as DVH when used for the prediction of grade Ⅰ-Ⅳ ARP due to CCA IGRT,and thus can be used for the supplementation and optimization of radiotherapy planning systems.[Chinese Medical Equipment Journal,2025,46(3):48-53]

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.

Objective To investigate the changing antibiotic resistance profiles of E.coli isolated from patients in the 52 hospitals participating in the CHINET program from 2015 to 2021.Methods Antimicrobial susceptibility was tested for clinical isolates of E.coli according to the unified protocol of CHINET program.WHONET 5.6 and SPSS 20.0 software were used for data analysis.Results Atotal of 289 760 nonduplicate clinical strains ofE.coli were isolated from 2015 to 2021,mainly from urine samples(44.7±3.2)％.The proportion of E.coli strains isolated from urine samples was higher in females than in males(59.0％vs 29.5％).The proportion of E.coli strains isolated from respiratory tract and cerebrospinal fluid samples was significantly higher in children than in adults(16.7％vs 7.8％,0.8％vs 0.1％,both P＜0.05).The isolates from internal medicine department accounted for the largest proportion(28.9±2.8)％with an increasing trend over years.Overall,the prevalence of ESBLs-producing E.coli and carbapenem resistant E.coli(CREco)was 55.9％and 1.8％,respectively during the 7-year period.The prevalence of ESBLs-producing E.coli was the highest in tertiary hospitals each year from 2015 to 2021 compared to secondary hospitals.The prevalence of CREco was higher in children's hospitals compared to secondary and tertiary hospitals each year from 2015 to 2021.The prevalence of ESBLs-producing E.coli in tertiary hospitals and children's hospitals and the prevalence of CREco in children's hospitals showed a decreasing trend over the 7-year period.The prevalence of CREco in secondary and tertiary hospitals increased slowly.Antibiotic resistance rates changed slowly from 2015 to 2021.Carbapenem drugs(imipenem,meropenem)were the most active drugs amongβ-lactams against E.coli(resistance rate≤2.1％).The resistance rates of E.coli to β-lactam/β-lactam inhibitor combinations(piperacillin-tazobactam,cefoperazone-sulbactam),aminoglycosides(amikacin),nitrofurantoin and fosfomycin(for urinary isolates only)were all less than 10％.The resistance rate of E.coli strains to antibiotics varied with the level of hospitals and the departments where the strains were isolated,especially for cefazolin and ciprofloxacin,to which the resistance rate of E.coli strains from children in non-ICU departments was significantly lower than that of the strains isolated from other departments(P＜0.05).The E.coli isolates from ICU showed higher resistance rate to most antimicrobial agents tested(excluding tigecycline)than the strains isolated from other departments.The E.coli strains isolated from tertiary hospitals showed higher resistance rates to the antimicrobial agents tested(excluding tigecycline,polymyxin B,cefepime and carbapenems)than the strains from secondary hospitals and children's hospitals.Conclusions E.coli is an important pathogen causing clinical infection.More than half of the clinical isolates produced ESBL.The prevalence of CREco is increasing in secondary and tertiary hospitals over the 7-year period even though the overall prevalence is still low.This is an issue of concern.