Objective To examine the changing prevalence and antimicrobial resistance profiles of Burkholderia cepacia in 52 hospitals across China from 2015 to 2021.Methods A total of 9 261 strains of B.cepacia were collected from 52 hospitals between January 1,2015 and December 31,2021.Antimicrobial susceptibility of the strains was tested using Kirby-Bauer method or automated antimicrobial susceptibility testing systems according to a unified protocol.The results were interpreted according to the breakpoints released in the Clinical & Laboratory Standards Institute(CLSI)guidelines(2023 edition).Results A total of 9 261 strains of B.cepacia were isolated from all age groups,especially elderly patients.The proportion was 11.1％(1 032 strains)in children,significantly lower than the proportion in adults.About half(46.5％,4 310/9 261)of the strains were isolated from patients at least 60 years old and 42.3％(3 919/9 261)of the strains were isolated from young adults.Most isolates(71.1％)were isolated from sputum and respiratory secretions,followed by urine(10.7％)and blood samples(8.1％).B.cepacia isolates were highly susceptible to the five antimicrobial agents recommended in the CLSI M100 document(33rd edition,2023).B.cepacia isolates showed relatively higher resistance rates to meropenem and levofloxacin.However,the resistance rates to ceftazidime,trimethoprim-sulfamethoxazole,and minocycline remained below 8.1％.The percentage of B.cepacia strains resistant to levofloxacin was the highest compared to other antibiotics in any of the three age groups(from 12.4％in the patients＜18 years old to 20.6％in the patients aged 60 years or older).Conclusions B.cepacia is one of the clinically important non-fermenting gram-negative bacteria.Accurate and timely reporting of antimicrobial susceptibility test results and ongoing antimicrobial resistance surveillance are helpful for rational prescription of antimicrobial agents and proper prevention and control of nosocomial infections.

Objective To summarize the changing prevalence of carbapenem resistance in Enterobacterales based on the data of CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021 for improving antimicrobial treatment in clinical practice.Methods Antimicrobial susceptibility testing was performed using a commercial automated susceptibility testing system according to the unified CHINET protocol.The results were interpreted according to the breakpoints of the Clinical & Laboratory Standards Institute(CLSI)M100 31st ed in 2021.Results Over the seven-year period(2015-2021),the overall prevalence of carbapenem-resistant Enterobacterales(CRE)was 9.43％(62 342/661 235).The prevalence of CRE strains in Klebsiella pneumoniae,Citrobacter freundii,and Enterobacter cloacae was 22.38％,9.73％,and 8.47％,respectively.The prevalence of CRE strains in Escherichia coli was 1.99％.A few CRE strains were also identified in Salmonella and Shigella.The CRE strains were mainly isolated from respiratory specimens(44.23±2.80)％,followed by blood(20.88±3.40)％and urine(18.40±3.45)％.Intensive care units(ICUs)were the major source of the CRE strains(27.43±5.20)％.CRE strains were resistant to all the β-lactam antibiotics tested and most non-β-lactam antimicrobial agents.The CRE strains were relatively susceptible to tigecycline and polymyxins with low resistance rates.Conclusions The prevalence of CRE strains was increasing from 2015 to 2021.CRE strains were highly resistant to most of the antibacterial drugs used in clinical practice.Clinicians should prescribe antimicrobial agents rationally.Hospitals should strengthen antibiotic stewardship in key clinical settings such as ICUs,and take effective infection control measures to curb CRE outbreak and epidemic in hospitals.

Objective To characterize the changing species distribution and antibiotic resistance profiles of respiratory isolates in hospitals participating in the CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021.Methods Commercial automated antimicrobial susceptibility testing systems and disk diffusion method were used to test the susceptibility of respiratory bacterial isolates to antimicrobial agents following the standardized technical protocol established by the CHINET program.Results A total of 589 746 respiratory isolates were collected from 2015 to 2021.Overall,82.6％of the isolates were Gram-negative bacteria and 17.4％were Gram-positive bacteria.The bacterial isolates from outpatients and inpatients accounted for(6.0±0.9)％and(94.0±0.1)％,respectively.The top microorganisms were Klebsiella spp.,Acinetobacter spp.,Pseudomonas aeruginosa,Staphylococcus aureus,Haemophilus spp.,Stenotrophomonas maltophilia,Escherichia coli,and Streptococcus pneumoniae.Each microorganism was isolated from significantly more males than from females(P＜0.05).The overall prevalence of methicillin-resistant S.aureus(MRSA)was 39.9％.The prevalence of penicillin-resistant S.pneumoniae was 1.4％.The prevalence of extended-spectrum β-lactamase(ESBL)-producing E.coli and K.pneumoniae was 67.8％and 41.3％,respectively.The overall prevalence of carbapenem-resistant E.coli,K.pneumoniae,Enterobacter cloacae,Pseudomonas aeruginosa,and Acinetobacter baumannii was 3.7％,20.8％,9.4％,29.8％,and 73.3％,respectively.The prevalence of β-lactamase was 96.1％in Moraxella catarrhalis and 60.0％in Haemophilus influenzae.The H.influenzae isolates from children(＜18 years)showed significantly higher resistance rates to β-lactam antibiotics than the isolates from adults(P＜0.05).Conclusions Gram-negative bacteria are still predominant in respiratory isolates associated with serious antibiotic resistance.Antimicrobial resistance surveillance should be strengthened in clinical practice to support accurate etiological diagnosis and appropriate antimicrobial therapy based on antimicrobial susceptibility testing results.

Medical image fusion technology combines the advantages of different modal medical images to provide more comprehensive and precise imaging information, widely applied in clinical diagnosis and disease research. Traditional fusion methods rely on signal processing techniques, but they have significant limitations, especially in multi-modal image fusion, where extracting deep semantic information is challenging. With the introduction of deep learning, image fusion effects have been significantly enhanced through technologies such as convolutional neural networks (CNN), generative adversarial networks (GAN), deep feature extractors, and self-attention mechanisms. However, deep learning methods still face challenges such as data scarcity, modal heterogeneity, high computational resource requirements, mode collapse, and training instability. This paper analyzes these issues and explores corresponding solutions as well as potential future development directions.

As one of the common negative emotions in diabetic patients, diabetes distress not only directly weakens patients' self-efficacy and treatment compliance, but also increases the risk of complications. With the help of mobile applications, chatbots, virtual reality technology and other means, digital health interventions can effectively alleviate the negative emotions of diabetic patients, improve their self-management ability and confidence, and are increasingly widely used in diabetes distress. The purpose of this review is to introduce the specific forms, application effects and future development directions of digital health intervention in diabetes distress, and to promote further research and clinical practice of digital health intervention in diabetes distress.

Diabetic kidney disease(DKD)with increasing global prevalence lacks effective therapeutic targets to halt or reverse its progression.Therapeutic targets supported by causal genetic evidence are more likely to succeed in randomized clinical trials.In this study,we integrated large-scale plasma proteomics,genetic-driven causal inference,and experimental validation to identify prioritized targets for DKD using the UK Biobank(UKB)and FinnGen cohorts.Among 2844 diabetic patients(528 with DKD),we identified 37 targets significantly associated with incident DKD,supported by both observational and causal evi-dence.Of these,22％(8/37)of the potential targets are currently under investigation for DKD or other diseases.Our prospective study confirmed that higher levels of three prioritized targets-insulin-like growth factor binding protein 4(IGFBP4),family with sequence similarity 3 member C(FAM3C),and prostaglandin D2 synthase(PTGDS)—were associated with a 4.35,3.51,and 3.57-fold increased likeli-hood of developing DKD,respectively.In addition,population-level protein-altering variants(PAVs)analysis and in vitro experiments cross-validated FAM3C and IGFBP4 as potential new target candidates for DKD,through the classic NLR family pyrin domain containing 3(NLRP3)-caspase-1-gasdermin D(GSDMD)apoptotic axis.Our results demonstrate that integrating omics data mining with causal inference may be a promising strategy for prioritizing therapeutic targets.

Medical image fusion technology combines the advantages of different modal medical images to provide more comprehensive and precise imaging information, widely applied in clinical diagnosis and disease research. Traditional fusion methods rely on signal processing techniques, but they have significant limitations, especially in multi-modal image fusion, where extracting deep semantic information is challenging. With the introduction of deep learning, image fusion effects have been significantly enhanced through technologies such as convolutional neural networks (CNN), generative adversarial networks (GAN), deep feature extractors, and self-attention mechanisms. However, deep learning methods still face challenges such as data scarcity, modal heterogeneity, high computational resource requirements, mode collapse, and training instability. This paper analyzes these issues and explores corresponding solutions as well as potential future development directions.

Objective:To establish a quality control method for Aiye standard decoction.Methods:The ultra performance liquid chromatogrphy (UPLC) column Waters ACQUITY HSS T3 C18 (2.1 mm×150 mm,1.8 μm) was used to gradient elution by acetonitrile and 0.1% formic acid in water. 16 batches of Aiye standard decoction fingerprints were established by UPLC and the common peaks were determined in the fingerprints. The contents of 12 components were determined. The 16 batches of Aiye standard decoction were analyzed by similarity calculation, hierarchical cluster analysis (HCA), principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) for analysis of differential components of Artemisiae Argyi Folium from different origins.Results:A total of 13 common peaks were marked in the fingerprints of 16 batches of Aiye standard decoction, 12 of which were identified by comparison with reference substance, including chlorogenic acid, sochlorogenic acid A, neochlorogenic acid, cryptochlorogenic acid, caffeic acid,1,3-O-Dicaffeoylquinic acid, schaftoside, isochlorogenic acid B,1,5-O-Dicaffeoylquinic acid, isochlorogenic acid C, jaceosidin and eupatilin. Similarity evaluation, PCA and HCA all classified the 16 batches of Aiye standard decoction into 2 categories. Orthogonal partial least squares discriminant analysis screened 5 differential biomarkers from 13 common peaks. The content determination results showed that the phenolic compounds and flavonoids in samples from Hubei were significantly higher than that in samples from other areas.Conclusion:This method can effectively analyze the differences in the quality of Aiye standard decoction from different origins, and provide reference for the formulation of quality standards for Aiye standard decoction and related preparations.

Hemoglobin, the principal protein in red blood cells, is crucial for oxygen transport in the bloodstream. The quantification of hemoglobin concentration is indispensable in medical diagnostics and health management, which encompass the diagnosis of anemia and the screening of various blood disorders. Immunological methods, based on antigen-antibody interactions, are distinguished by their high sensitivity and accuracy. Consequently, it is necessary to develop hemoglobin-specific antibodies characterized by high specificity and affinity to enhance detection accuracy. In this study, we immunized a Bactrian camel (Camelus bactrianus) with human hemoglobin and subsequently constructed a nanobody library. Utilizing a solid-phase screening method, we selected nanobodies and evaluated the binding activity of the screened nanobodies to hemoglobin. Initially, human hemoglobin was used to immunize a Bactrian camel. Following four immunization sessions, blood was withdrawn from the jugular vein, and a nanobody library with a capacity of 2.85×10⁸ colony forming units (CFU) was generated. Subsequently, ten hemoglobin-specific nanobody sequences were identified through three rounds of adsorption-elution-enrichment assays, and these nanobodies were subjected to eukaryotic expression. Finally, enzyme-linked immunosorbent assay and biolayer interferometry were employed to evaluate the stability, binding activity, and specificity of these nanobodies. The results demonstrated that the nanobodies maintained robust binding activity within the temperature range of 20-40 ℃ and exhibited the highest binding activity at pH 7.0. Furthermore, the nanobodies were capable of tolerating a 10% methanol solution. Notably, among the nanobodies tested, VHH-12 displayed the highest binding activity to hemoglobin, with a half maximal effective concentration (EC₅₀) of 10.63 nmol/L and a equilibrium dissociation constant (K_D) of 2.94×10^-7 mol/L. VHH-12 exhibited no cross-reactivity with a panel of eight proteins, such as ovalbumin and bovine serum albumin, while demonstrating partial cross-reactivity with hemoglobin derived from porcine, goat, rabbit, and bovine sources. In this study, a hemoglobin-specific high-affinity nanobody was successfully isolated, demonstrating potential applications in disease diagnosis and health monitoring.
Animals ; Camelus/immunology* ; Single-Domain Antibodies/immunology* ; Hemoglobins/immunology* ; Humans ; Peptide Library

Objective To investigate the prevalence of scoliosis and congenital heart disease(CHD)and their correlation among children and adolescents of Drung nationality in Yunnan Province.Methods A cross-sectional survey was conducted in November 2022 among all Drung school-aged children and adolescents aged 5-18 years in Gongshan Drung and Nu Autonomous County,Yunnan Province.Visual inspection,Adams for-ward flexion test,and trunk rotation angle(ATR)measurement were comprehensively used for school prelim-inary screening of scoliosis.Individuals who tested positive in the school preliminary screening underwent fur-ther X-ray examination for auxiliary diagnosis.Cardiac auscultation and echocardiography were used for school preliminary screening of CHD.The personal information of the screening subjects,the screening results,etc.were recorded.The prevalence of scoliosis and CHD among children and adolescents of the Drung nationality and the relationship between the two diseases were statistically analyzed,and the positive predictive value of school-based scoliosis screening and its influencing factors were also analyzed.Results A total of 1 036 chil-dren and adolescents of Drung nationality were enrolled,with a mean age of(10.72±3.75)years,icluding 542 males and 494 females.A total of 45 subjects tested positive for scoliosis in the school preliminary screening,with a preliminary positive rate of 4.34%.A total of 22 cases were finally diagnosed with scoliosis,with a prevalence rate of 2.12%.Among them,21 cases were idiopathic scoliosis(accounting for 95.45%),and 1 case was congenital scoliosis(accounting for 4.55%).The prevalence rate was higher in females(2.83%)than that in males(1.48%),higher in the 10 to 18-year-old group(2.30%)than that in the 5 to<10-year-old group(1.87%),and higher in the secondary school group(2.78%)than that in the primary school group(1.78%),hut there were no statistically significant differences(P>0.05).Most idiopathic scoliosis cases were mild(Cobb angle 10° to<20°,90.48%)and classified as Lenke type Ⅴ(57.14%).Two cases of CHD were confirmed,both of which were atrial septal defects,with a prevalence rate of 0.19%.The co-occurrence rate of idiopathic scoliosis and CHD was 4.76%(1/21).The positive predictive value of school-based scoliosis pre-liminary screening was only 48.89%.When the BMI was<18.5 kg/m2,the positive predictive value was sig-nificantly higher than that for BMI≥18.5 kg/m2(P<0.05).Conclusion The prevalence rate of scoliosis a-mong adolescents of the Drung ethnic group in Yunnan Province is 2.12%,predominantly idiopathic scoliosis,with Lenke type V being the most common classification.The prevalence rate of congenital heart disease is 0.19%.BMI is a significant influencing factor for the positive predictive value of school-based scoliosis prelimi-nary screening.