OBJECTIVE To evaluate the cost-effectiveness of cefiderocol versus best available therapy （BAT） or standard-of- care （SOC） for the treatment of confirmed or suspected carbapenem-resistant Gram-negative bacterial （CRGNB） serious infections from the perspective of the Chinese healthcare system， and to explore its reasonable pricing. METHODS A decision tree model was constructed based on data from two phase Ⅲ clinical trials （CREDIBLE-CR and GAME CHANGER） to simulate the cost- effectiveness of cefiderocol in two scenarios： salvage therapy for confirmed CRGNB infection （scenario 1） and empirical therapy for suspected CRGNB infection （scenario 2）. The primary outcome measure was the incremental cost-effectiveness ratio （ICER）. The willingness-to-pay （WTP） was set at 1 to 3 times China’s per capita GDP in 2024. To verify the robustness of the results， one- way and probabilistic sensitivity analyses were conducted， and based on these， a reasonable price range for cefiderocol in the Chinese market was explored. RESULTS The results for scenario 1 showed that the clinical cure rate in the cefiderocol group was higher than that in the BAT group （47.50% vs. 34.21%）， but its ICER was 415 065.03 yuan per cured case， exceeding three times China’s GDP per capita. Scenario 2 revealed that the ICER for cefiderocol relative to SOC was as high as 1 362 446.16 yuan per cured case， far exceeding the WTP. Sensitivity analysis indicated that the treatment duration and price of cefiderocol were key factors affecting its cost-effectiveness. In the two scenarios described above， the unit price of cefiderocol must fall below 683.47 and 242.00 yuan/g， respectively， to be considered cost-effective. CONCLUSIONS Based on the current market price， cefiderocol lacks sufficient cost-effectiveness for treating confirmed or suspected CRGNB serious infections within China’s healthcare system. To improve its accessibility， price negotiations or a tiered medical insurance payment strategy are required.

Objective: To explore the relationship between snack consumption and depressive symptoms in first year junior high school students with different left behind experiences in Yunnan Province, so as to provide a basis for improving depressive symptoms among first year junior high school students with different left behind experiences. Methods: From October to December 2022,a cluster random sampling method was used to select 8 500 first year junior high school students from 11 ethnic minority areas (Fugong County, Longling County, Longyang District, Luchun County, Mojiang County, Nanjian County, Qiaojia County, Shuangjiang County, Tengchong City, Yuanmou County, Zhenyuan County) in Yunnan Province for a questionnaire survey. The Chinese version of Depression Anxiety Stress Scale-21 was applied to assess depressive symptoms in first year junior high school students, and snack consumption was collected by employing food frequency questionnaire. The generalized linear model was used to analyze the association between first year junior high school students snack consumption and depressive symptoms, and the analysis was stratified according to left behind experience. Results: The detection rates of depressive symptoms among firstyear junior high school students with and without left behind experience were 36.25% and 26.91%, respectively. After controlling for confounding variables, the generalized linear model analysis showed that sweet snacks ( β=0.16, 95%CI =0.07-0.25), fast food ( β=0.14, 95%CI =0.04-0.23) and carbonated drinks ( β=0.09, 95%CI =0.01-0.17) of first year junior high school students with left behind experience (all P <0.05). Compared with those without such behavior, the risk of depressive symptoms was higher in consumption of fast food ( β=0.13, 95%CI =0.07-0.18) and carbonated drinks ( β=0.10, 95%CI =0.06-0.15)among first year junior high school students without left behind experience (both P <0.05). Conclusion Snack consumption among first year junior high school students in Yunnan may increase the risk of developing depressive symptoms, while first year junior high school students with left behind experience may have a greater risk of developing depressive symptoms.

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 evaluate the impact of an integrated management mode of prenatal diagnosis-postnatal treatment for congenital heart disease (CHD) on perioperative and long-term outcomes of the arterial switch operation (ASO), and to analyze the efficacy of ASO in a single center. Methods This retrospective study analyzed the clinical data of 183 children who underwent ASO at Guangdong Provincial People’s Hospital from 2018 to 2024. The cohort included 106 (57.9%) patients of transposition of the great arteries with intact ventricular septum (TGA/IVS), 61 (33.3%) patients of transposition of the great arteries with ventricular septal defect (TGA/VSD), and 16 (8.7%) patients of Taussig-bing anomaly (TBA). Perioperative indicators were compared between 91 patients in the prenatal-postnatal integrated management group (an integrated group) and 92 patients in the traditional management group (a non-integrated group). Long-term survival and reoperation rates were analyzed using Kaplan-Meier curves. Results The overall perioperative mortality rate was 4.9% (9/183), showing a downward trend year by year. The primary cause of perioperative mortality was low cardiac output syndrome (LCOS), which occurred in 12 patients (6.6% incidence) with a mortality rate of 75.0%. The integrated group had a higher proportion of males (89.0% vs. 72.8%, P<0.05) and lower body weight [3.1 (2.7, 3.3) kg vs. 3.3 (3.0, 3.7) kg, P<0.05] compared to the non-integrated group. The age at surgery was significantly earlier in the integrated group [7 (3, 10) d vs. 14 (9, 48) d, P<0.05], and all children in the integrated group underwent ASO within the optimal surgical window (100.0% vs. 82.6%, P<0.05). Intraoperatively, cardiopulmonary bypass time [173 (150, 207) min vs. 186 (159, 237) min, P<0.05] and aortic cross-clamp time [100 (90, 117) min vs. 116 (97, 142) min, P<0.05] were significantly shorter in the integrated group. Although the integrated group had longer postoperative mechanical ventilation time [145 (98, 214) h vs. 116 (77, 147) h, P<0.05] and higher 48-hour maximum vasoactive inotropic score [15 (10, 21) points vs. 12 (8, 16) points, P<0.05], there was no statistically significant difference in the incidence of severe complications (LCOS, necrotizing enterocolitis, extracorporeal membrane oxygenation) or mortality rate (3.3% vs. 6.5%, P=0.51) between the two groups, despite earlier surgical intervention and a higher proportion of critically ill cases in the integrated group. The length of hospital stay in the emergency surgery group was significantly shorter than that in the elective surgery group [20 (15, 28) d vs. 25 (21, 30) d, P<0.05], suggesting that early surgery may be of potential benefit. A total of 163 patients were successfully followed up for a median of 4.7 years, with a 5-year survival rate of 95.1% and a freedom from reintervention survival rate of 95.1%. There were no late deaths, and the most common postoperative complication was pulmonary artery stenosis. Conclusion The integrated management model allowed critically ill children with lower body weights to safely undergo surgery, significantly optimizing the timing of surgery and shortening intraoperative times. The long-term risk of reoperation after ASO is primarily concentrated on pulmonary artery stenosis, necessitating long-term follow-up and monitoring.

ObjectiveTo establish a model that can quickly identify the aroma components in different parts of Nardostachys jatamansi， so as to provide a quality control basis for the market circulation and clinical use of N. jatamansi. MethodsHeadspace solid-phase microextraction-gas chromatography-mass spectrometry（HS-SPME-GC-MS） combined with Smart aroma database and National Institute of Standards and Technology（NIST） database were used to characterize the aroma components in different parts of N. jatamansi， and the aroma components were quantified according to relative response factor（RRF） and three internal standards， and the markers of aroma differences in different parts of N. jatamansi were identified by orthogonal partial least squares-discriminant analysis（OPLS-DA） and cluster thermal analysis based on variable importance in the projection（VIP） value >1 and P<0.01. The odor data of different parts of N. jatamansi were collected by Heracles Ⅱ Neo ultra-fast gas phase electronic nose， and the correlation between compound types of aroma components collected by the ultra-fast gas phase electronic nose and the detection results of HS-SPME-GC-MS was investigated by drawing odor fingerprints and odor response radargrams. Chromatographic peak information with distinguishing ability≥0.700 and peak area≥200 was selected as sensor data， and the rapid identification model of different parts of N. jatamansi was established by principal component analysis（PCA）， discriminant factor alysis（DFA）， soft independent modeling of class analogies（SIMCA） and statistical quality control analysis（SQCA）. ResultsThe HS-SPME-GC-MS results showed that there were 28 common components in the underground and aboveground parts of N. jatamansi， of which 22 could be quantified and 12 significantly different components were screened out. Among these 12 components， the contents of five components（ethyl isovalerate， 2-pentylfuran， benzyl alcohol， nonanal and glacial acetic acid，） in the aboveground part of N. jatamansi were significantly higher than those in the underground part（P<0.01）， the contents of β-ionone， patchouli alcohol， α-caryophyllene， linalyl butyrate， valencene， 1，8-cineole and p-cymene in the underground part of N. jatamansi were significantly higher than those in the aboveground part（P<0.01）. Heracles Ⅱ Neo electronic nose results showed that the PCA discrimination index of the underground and aboveground parts of N. jatamansi was 82， and the contribution rates of the principal component factors were 99.94% and 99.89% when 2 and 3 principal components were extracted， respectively. The contribution rate of the discriminant factor 1 of the DFA model constructed on the basis of PCA was 100%， the validation score of the SIMCA model for discrimination of the two parts was 99， and SQCA could clearly distinguish different parts of N. jatamansi. ConclusionHS-SPME-GC-MS can clarify the differential markers of underground and aboveground parts of N. jatamansi. The four analytical models provided by Heracles Ⅱ Neo electronic nose（PCA， DFA， SIMCA and SQCA） can realize the rapid identification of different parts of N. jatamansi. Combining the two results， it is speculated that terpenes and carboxylic acids may be the main factors contributing to the difference in aroma between the underground and aboveground parts of N. jatamansi.

ObjectiveThe controllability changes of structural brain network were explored based on the control and brain network theory in young smokers, this may reveal that the controllability indicators can serve as a powerful factor to predict the sleep status in young smokers. MethodsFifty young smokers and 51 healthy controls from Inner Mongolia University of Science and Technology were enrolled. Diffusion tensor imaging (DTI) was used to construct structural brain network based on fractional anisotropy (FA) weight matrix. According to the control and brain network theory, the average controllability and the modal controllability were calculated. Two-sample t-test was used to compare the differences between the groups and Pearson correlation analysis to examine the correlation between significant average controllability and modal controllability with Fagerström Test of Nicotine Dependence (FTND) in young smokers. The nodes with the controllability score in the top 10% were selected as the super-controllers. Finally, we used BP neural network to predict the Pittsburgh Sleep Quality Index (PSQI) in young smokers. ResultsThe average controllability of dorsolateral superior frontal gyrus, supplementary motor area, lenticular nucleus putamen, and lenticular nucleus pallidum, and the modal controllability of orbital inferior frontal gyrus, supplementary motor area, gyrus rectus, and posterior cingulate gyrus in the young smokers’ group, were all significantly different from those of the healthy controls group (P<0.05). The average controllability of the right supplementary motor area (SMA.R) in the young smokers group was positively correlated with FTND (r=0.393 0, P=0.004 8), while modal controllability was negatively correlated with FTND (r=-0.330 1, P=0.019 2). ConclusionThe controllability of structural brain network in young smokers is abnormal. which may serve as an indicator to predict sleep condition. It may provide the imaging evidence for evaluating the cognitive function impairment in young smokers.

BACKGROUND:Flap transplantation technique is a commonly used surgical procedure for the treatment of severe tissue defects,but postoperative flap necrosis is easily triggered by ischemia-reperfusion injury.Therefore,it is still an important research topic to improve the survival rate of transplanted flaps. OBJECTIVE:To review the pathogenesis and latest treatment progress of flap ischemia-reperfusion injury. METHODS:CNKI,WanFang Database and PubMed database were searched for relevant literature published from 2014 to 2024.The search terms used were"flap,ischemia-reperfusion injury,inflammatory response,oxidative stress,Ca2+overload,apoptosis,mesenchymal stem cells,platelet-rich plasma,signaling pathways,shock wave,pretreatment"in Chinese and English.After elimination of irrelevant literature,poor quality and obsolete literature,77 documents were finally included for review. RESULTS AND CONCLUSION:Flap ischemia/reperfusion injury may be related to pathological factors such as inflammatory response,oxidative stress response,Ca2+overload,and apoptosis,which can cause apoptosis of vascular endothelial cells,vascular damage and microcirculation disorders in the flap,and eventually lead to flap necrosis.Studies have found that mesenchymal stem cell transplantation,platelet-rich plasma,signaling pathway modulators,shock waves,and pretreatment can alleviate flap ischemia/reperfusion injuries from different aspects and to varying degrees,and reduce the necrosis rate and necrosis area of the grafted flap.Although there are many therapeutic methods for skin flap ischemia/reperfusion injury,a unified and effective therapeutic method has not yet been developed in the clinic,and the advantages and disadvantages of various therapeutic methods have not yet been compared.Most of the studies remain in the stage of animal experiments,rarely involving clinical observations.Therefore,a lot of research is required in the future to gradually move from animal experiments to the clinic in order to better serve the clinic.

ObjectiveTo establish a risk recognition model for coronary artery stenosis by using a machine learning method and to identify the key causative factors. MethodsPatients aged ≥18 years，diagnosed with coronary heart disease through coronary angiography from January 2013 to May 2020 in two prominent hospitals in Shanxi Province， were continuously enrolled. Logistic regression，back propagation neural network （BPNN）， and random forest（RF）algorithms were used to construct models for detecting the causative factors of coronary artery stenosis. Sensitivity （TPR）， specificity （TNR）， accuracy （ACC）， positive predictive value （PV+）， negative predictive value （PV-）， area under subject operating characteristic curve （AUC）， and calibration curve were used to compare the discrimination and calibration performance of the models. The best model was then employed to predict the main risk variables associated with coronary stenosis. ResultsThe RF model exhibited superior comprehensive performance compared to logistic regression and BPNN models. The TPR values for logistic regression，BPNN，and RF models were 75.76%， 74.30%， and 93.70%， while ACC values were 74.05%， 72.30%， and 79.49%， respectively. The AUC values were：logistic regression 0.739 9； BPNN 0.723 1； RF 0.752 2. Manifestations such as chest pains，abnormal ST segments on ECG，ventricular premature beats with hypertension， atrial fibrillation， regional wall motion abnormalities（RWMA） by color echocardiography， aortic regurgitation（AR）， pulmonary insufficiency （PI）， family history of cardiovascular diseases，and body mass index（BMI）were identified as top ten important variables affecting coronary stenosis according to the RF model. ConclusionsRandom forest model shows the best comprehensive performance in identification and accurate assessment of coronary artery stenosis. The prediction of risk factors affecting coronary artery stenosis can provide a scientific basis for clinical intervention and help to formulate further diagnosis and treatment strategies so as to delay the disease progression.

The analysis presented here is based on the blood components of Guanxin Qiwei tablets, the key anti-atherosclerosis pathway of Guanxin Qiwei tablets was screened by network pharmacology, and the anti-atherosclerosis mechanism of Guanxin Qiwei tablets was clarified and verified by cell experiments. HPLC-Q-Exactive-MS/MS technique was used to analyze the components of Guanxin Qiwei tablets into blood, to determine the precise mass charge ratio of the compounds, and to conduct a comprehensive analysis of the components by using secondary mass spectrometry fragments and literature comparison. Finally, a total of 42 components of Guanxin Qiwei tablets into blood were identified. To better understand the interactions, we employed the Swiss Target Prediction database to predict the associated targets. Atherosclerosis (AS) disease targets were searched in disease databases Genecard, OMIM and Disgent, and 181 intersection targets of disease targets and component targets were obtained by Venny 2.1.0 software. Protein interactions were analyzed by String database. The 32 core targets were selected by Cytscape software. Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed in DAVID database. It was found that the anti-atherosclerosis pathways of Guanxin Qiwei tablets mainly include lipid metabolism and atherosclerosis and AGE-RAGE signaling pathway in diabetic complications and other signal pathways. The core targets and the core compounds were interlinked, and it was found that cryptotanshinone and tanshinone ⅡA in Guanxin Qiwei tablets were well bound to TNF, PPARγ, AKT1, PTG2 and other targets. The lipid metabolism and atherosclerotic pathway was verified using human hl-7702 hepatocytes. This study preliminarily identified the potential pharmacodynamic components of Guanxin Qiwei tablets in the treatment of AS diseases and predicted their pathways of action, and verified the relationship between regulating lipid metabolism and atherosclerosis of Guanxin Qiwei tablets in vitro, providing a reference for the further study of the pharmacodynamic material basis and mechanism of action of this prescription. This experiment was approved by the Medical Ethics Committee of Inner Mongolia Medical University (No. YKD202401262).