ObjectiveHeadspace solid-phase microextraction-gas chromatography-mass spectrometry（HS-SPME-GC-MS） and GC-triple quadrupole MS（GC-QqQ-MS） in combination with non-targeted and targeted metabolomics were employed to systematically analyze the chemical composition differences of Xihuangwan prepared with natural musk and artificial musk， and establish an identification system for them. MethodsThe volatile components of 9 batches of Xihuangwan samples from 8 manufacturers were analyzed by HS-SPME-GC-MS non-targeted metabolomics， and identified by comparing their MS data with the National Institute of Standards and Technology（NIST） spectral library. Orthogonal partial least squares-discriminant analysis（OPLS-DA） was used to identify differential volatile components of Xihuangwan prepared with natural musk and artificial musk. Additionally， GC-QqQ-MS targeted metabolomics was applied to quantify the levels of α-pinene， β-elemene， muscone， dehydroepiandrosterone， bornyl acetate， and octyl acetate in 27 batches of samples from 9 manufacturers. Cluster analysis， principal component analysis（PCA）， and partial least squares-discriminant analysis（PLS-DA） were conducted to further explore the differences in volatile components between Xihuangwan samples prepared with natural musk and artificial musk. ResultsNon-targeted metabolomics identified 291 volatile compounds in Xihuangwan， including alkanes， esters， alkanes， alcohols， ketones， naphthalenes and others. OPLS-DA analysis revealed distinct separation between Xihuangwan samples containing artificial musk（A1， C1， D1， E1， F1， G1， I1） and those containing natural musk（H1， H3）. A total of 30 differential metabolites were identified. The relative contents of these 30 differential metabolites were visualized using a radar chart， revealing significant differences in the levels of octanol， borneol acetate and muscone. Cluster analysis and PCA results from targeted metabolomics indicated that Xihuangwan could be classified into two distinct groups：one composed of natural musk（H1， H3） and the other of artificial musk， sample H2. PLS-DA identified muscone， octyl acetate， and dehydroepiandrosterone as key differential volatile components. Although no significant difference was observed in the content of octyl acetate between the two groups， statistically significant differences were found for muscone and dehydroepiandrosterone（P<0.05）. ConclusionMuscone and dehydroepiandrosterone can be used for the differentiation of Xihuangwan samples containing natural musk from those containing artificial musk. This study systematically and comprehensively analyzed the differences in the types and contents of major volatile components in Xihuangwan prepared with natural musk and artificial musk， providing a scientific basis for quality evaluation and control of Xihuangwan.

ObjectiveHeadspace solid-phase microextraction-gas chromatography-mass spectrometry（HS-SPME-GC-MS） and GC-triple quadrupole MS（GC-QqQ-MS） in combination with non-targeted and targeted metabolomics were employed to systematically analyze the chemical composition differences of Xihuangwan prepared with natural musk and artificial musk， and establish an identification system for them. MethodsThe volatile components of 9 batches of Xihuangwan samples from 8 manufacturers were analyzed by HS-SPME-GC-MS non-targeted metabolomics， and identified by comparing their MS data with the National Institute of Standards and Technology（NIST） spectral library. Orthogonal partial least squares-discriminant analysis（OPLS-DA） was used to identify differential volatile components of Xihuangwan prepared with natural musk and artificial musk. Additionally， GC-QqQ-MS targeted metabolomics was applied to quantify the levels of α-pinene， β-elemene， muscone， dehydroepiandrosterone， bornyl acetate， and octyl acetate in 27 batches of samples from 9 manufacturers. Cluster analysis， principal component analysis（PCA）， and partial least squares-discriminant analysis（PLS-DA） were conducted to further explore the differences in volatile components between Xihuangwan samples prepared with natural musk and artificial musk. ResultsNon-targeted metabolomics identified 291 volatile compounds in Xihuangwan， including alkanes， esters， alkanes， alcohols， ketones， naphthalenes and others. OPLS-DA analysis revealed distinct separation between Xihuangwan samples containing artificial musk（A1， C1， D1， E1， F1， G1， I1） and those containing natural musk（H1， H3）. A total of 30 differential metabolites were identified. The relative contents of these 30 differential metabolites were visualized using a radar chart， revealing significant differences in the levels of octanol， borneol acetate and muscone. Cluster analysis and PCA results from targeted metabolomics indicated that Xihuangwan could be classified into two distinct groups：one composed of natural musk（H1， H3） and the other of artificial musk， sample H2. PLS-DA identified muscone， octyl acetate， and dehydroepiandrosterone as key differential volatile components. Although no significant difference was observed in the content of octyl acetate between the two groups， statistically significant differences were found for muscone and dehydroepiandrosterone（P<0.05）. ConclusionMuscone and dehydroepiandrosterone can be used for the differentiation of Xihuangwan samples containing natural musk from those containing artificial musk. This study systematically and comprehensively analyzed the differences in the types and contents of major volatile components in Xihuangwan prepared with natural musk and artificial musk， providing a scientific basis for quality evaluation and control of Xihuangwan.

Objective: To develop a simple digital chylous plasma device and validate its ability to accurately, standardly, and non-destructively determine chylous plasma in blood banks and clinical transfusions in hospitals. Methods: A digital chylous plasma assessment device was designed and manufactured. This device was used to measure the chylous degrees of chylous plasma samples before freezing, after freeze-thawing, before viral inactivation, and after viral inactivation. The measured chylosity index values were categorized according to the requirements specified in Appendix A of the Chinese national standard GB 18469-2001 "Quality Requirements for Whole Blood and Blood Components". This process established a digital standard for chylous plasma, enabling the identification of severe, moderate and mild chylous plasma, and non-chylous plasma. Results: The initial simple product of the digital chylous assessment device was successfully designed and manufactured. There was no significant difference in the degree of chylous plasma between pre-freezing 468.11±217.73 lux and post-thawing 538.91±273.39 lux of chylous plasma (P>0.05), or between pre-viral inactivation 858.33±387.79 lux and post-viral inactivation 928.33±166.51 lux of chylous plasma (P>0.05). The median of chylous degree values for plasma chylous index grades 0 to 6 were 45 lux, 250 lux, 620 lux, 835 lux, 1 130 lux, 1 390 lux, and 1 700 lux, respectively. The defined cutoff values/ranges for the chylous degree values corresponding to plasma chylous index grade 0 to 6 were ≤125 lux, 126-465 lux, 466-740 lux, 741-1 000 lux, 1 001-1 233 lux, 1 234-1 560 lux, and ≥1 561 lux. Conclusion: This study successfully developed the initial product of the digital chylous device and established digital standards for classifying chylous plasma. The device demonstrates the potential to meet the needs for assessment of chylous plasma in both blood banks and clinical transfusions in hospitals, thereby promoting the development and application of standardized, non-destructive chylous plasma assessment technology.

Objective:Distribution and antibiotic resistance of pathogen isolated from children with intra-abdominal infection (IAI) associated sepsis in the intensive care unit (ICU) were analyzed to provide a reference for the empirical anti-infective treatment of IAI in children.Methods:We retrospectively analyzed the data of 116 children with culture-positive IAI-associated sepsis admitted to Children's Hospital of Zhejiang University School of Medicine from January 2019 to December 2021. Clinical isolation and drug resistance analysis were conducted based on different years of onset, locations of onset, and primary diseases.Results:A total of 186 strains of pathogens causing children with IAI-associated sepsis in ICU were collected. The distribution and antibiotic resistance of pathogen were as follows: the percentages of gram-positive bacteria, gram-negative bacteria, and fungi were 53.2%, 40.9%, and 5.9%, respectively; the top four strains were Enterococcus faecium, Escherichia coli, Klebsiella pneumoniae, and Enterococcus faecalis, accounting for 57.0% of all isolates; Enterococcus faecium(19.9%) and Enterococcus faecalis (10.2%) were the dominating gram-positive bacteria; Escherichia coli (13.4%) and Klebsiella pneumoniae (13.4%) were more common gram-negative bacteria; Fungi were dominated by Candida albicans (3.8%).Fifty-seven strains of gram-positive bacteria were detected in 61 children with infectious diseases, mainly Enterococcus faecium (28 strains). There were 53 gram-negative strains, mainly Klebsiella pneumoniae (21 strains). Thirty-two strains of gram-positive bacteria were detected in 40 children with digestive tract malformation, and Enterococcus faecalis (six strains) were the most common. There were 14 gram-negative strains, mainly Escherichia coli (six strains). In 13 children with malignant tumors of digestive system, nine strains of gram-positive bacteria were cultured, and Enterococcus faecium (four strains) was the most common. There were eight gram-negative strains, mainly Escherichia coli (four strains).In the 46 community-acquired IAI patients,30 gram-positive isolates were cultured,mainly including Enterococcus faecium (12 strains), Staphylococcus epidermidis (seven strains), and Viridans streptococci (six strains); Forty gram-negative isolates mainly contained Escherichia coli (16 strains), Klebsiella pneumoniae (14 strains), and Enterobacter cloacae (five strains). In the 70 hospital-associated IAI patients, 69 gram-positive isolates such as Enterococcus faecium (25 strains), Enterococcus faecalis (17 strains), Enterococcus gallinarum (eight strains), and Staphylococcus aureus (seven strains) were cultured;Tirty-six gram-negative isolates were dominated by Klebsiella pneumoniae (11 strains), Escherichia coli (nine strains), Pseudomonas aeruginosa (four strains), and Acinetobacter baumannii (four strains). The mixed infection rate of clinical pathogens was up to 46.6%, and the overall resistance rate was 43.4%, in which gram-negative bacteria had high sensitivity to piperacillin/tazobactam, cefoperazone/sulbactam, imipenem, and tigecycline.The detection rates of Klebsiella pneumoniae and Escherichia coli producing extended-spectrum β-lactamases were 36.0% and 24.6%, respectively, with 100% sensitivity to tigecycline. Gram-positive bacteria showed 100% sensitivity to vancomycin, linezolid, and tigecycline. Conclusion:Pathogen isolated from children with IAI-associated sepsis in ICU were dominated by Enterococcus faecium, Escherichia coli, Klebsiella pneumoniae, and Enterococcus faecalis,respectively. Before confirmation of pathogenic bacteria, antibacterial agents can be selected according to the infection type. It is important to note that a single broad-spectrum antibacterial agent or combination medication can be considered the initial empirical choice due to the large variety of pathogens, high rates of mixed infections, and high overall resistance.

With the development of virtual reality (VR) technology and wide application of simulation-based medical education in clinical teaching, VR has been attracting growing attention in the field of simulation teaching in pediatrics. Studies have shown that VR technology can effectively improve pediatric clinical teaching effects by providing an immersive learning environment and enhancing the learning experience of students. VR also expands the teaching methods of pediatric simulation education. This paper discusses the application of VR technology in virtual standardized patients, simulation teaching of clinical practice skills, and clinical scenario simulation in pediatrics, as well as the use of ACEP SimBox in VR simulation teaching in pediatric emergency care. Future research needs to focus on the further development of VR technology and its application in simulation teaching, and find the best way to combine VR with traditional teaching methods.

Refined-JQ (JQ-R) is a mixture of refined extracts from(Ranunculaceae),(Leguminosae) and(Caprifoliaceae), the three major herbs of JinQi-JiangTang tablet, a traditional Chinese medicine (TCM) formula. The mechanisms by which JQ-R regulates glucose metabolism and improves insulin sensitivity were studied in type 2 diabetic KKmice and insulin-resistant L6 myotubes. To investigate the mechanisms by which JQ-R improves insulin sensitivity, a model of insulin-resistant cells induced with palmitic acid (PA) was established in L6 myotubes. Glucose uptake and expression of factors involved in insulin signaling, stress, and inflammatory pathways were detected by immunoblotting. JQ-R showed beneficial effects on glucose homeostasis and insulin resistance in a euglycemic clamp experiment and decreased fasting insulin levels in diabetic KKmice. JQ-R also improved the plasma lipid profiles. JQ-R directly increased the activity of superoxide dismutase (SOD) and decreased malondialdehyde (MDA) as well as inducible nitric oxide synthase (iNOS) levels in insulin-resistant L6 cells, and elevated the insulin-stimulated glucose uptake with upregulated phosphorylation of AKT. The phosphorylation levels of nuclear factor kappa B (NF-B p65), inhibitor of NF-B (IB), c-Jun N-terminal kinase (JNK1/2) and extracellular-signal-regulated kinases (ERK1/2) were also changed after JQ-R treatment compared with the control group. Together these findings suggest that JQ-R improved glucose and lipid metabolism in diabetic KKmice. JQ-R directly enhanced insulin-stimulated glucose uptake in insulin-resistant myotubes with improved insulin signalling and inflammatory response and oxidative stress. JQ-R could be a candidate to achieve improved glucose metabolism and insulin sensitivity in type 2 diabetes mellitus.