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 machine learning approach for early identification of metabolic syndromes associated with inflammatory metabolic state changes in breast cancer patients after neoadjuvant therapy,using common laboratory and transthoracic echocardiography indices.Methods·Female patients with primary invasive breast cancer diagnosed at the Department of Breast Surgery,Renji Hospital,Shanghai Jiao Tong University School of Medicine,between September 2020 and September 2022,were included.General patient information,laboratory test results,and transthoracic echocardiography data were collected.After feature extraction,five machine learning algorithms,including random forest(RF),gradient boosting(GB),support vector machine(SVM),K-nearest neighbor(KNN),and decision tree(DT),were applied to construct a prediction model for the changes of the patients' metabolic state after neoadjuvant therapy,and the prediction performances of the five models were compared.Results·A total of 232 cases with valid clinical data were included,comprising 135 cases before neoadjuvant therapy and 97 cases after completing 4 cycles of neoadjuvant therapy.Feature extraction identified five key features:white blood cell count,hemoglobin,high-density lipoprotein(HDL),interleukin-2 receptor,and interleukin-8.In the multi-feature analysis,the area under the receiver operating characferistic curve(AUC)was higher in the combination of white blood cell count,hemoglobin and HDL compared to the combination of interleukin-2 receptor and interleukin-8(RF:0.928 vs 0.772,GB:0.900 vs 0.792,SVM:0.941 vs 0.764,KNN:0.907 vs 0.762,DT:0.799 vs 0.714).The RF,SVM,and GB models showed higher AUC(0.928,0.941,0.900)and accuracy(0.914,0.897,0.776).The SVM model exhibited superior accuracy in the training data compared to the RF and GB models(P=0.394,0.122 and 0.097,respectively).Conclusion·The SVM model can be used to establish a prediction model for identifying breast cancer patients at high risk of developing inflammatory metabolic state-related metabolic syndrome after neoadjuvant therapy by incorporating five common clinical indicators,namely,white blood cell count,hemoglobin,high-density lipoprotein,interleukin-2 receptor,and interleukin-8.SVM modeling may be useful for clinicians to establish individualized screening protocols based on a patient's inflammatory metabolic state.

After organ transplantation, graft rejection is one of the most common complications, which will cause adverse injuries to grafts regardless of etiology. Tertiary lymphoid structures (TLS) occur in non-lymphoid tissues under pathological conditions. Identification and characterization of mechanisms regulating graft rejection can not only promote understanding of the survival and prognosis of organ grafts, but also provide ideas for treating graft rejection reaction.

Objective:To analyze the differences in dosimetric quality and plan complexity of volumetric modulated arc therapy (VMAT) plans based on Halcyon 2.0 and Truebeam for different treatment sites of the patients.Methods:Halcyon 2.0 VMAT plans in head & neck, chest, abdomen, and pelvis treatment sites of 49 cases were retrospectively selected and the VMAT plans were re-designed based on Truebeam with the same optimization parameters. The differences in dosimetric metrics and plan complexity between the two types of plans were compared and analyzed. P<0.05 was considered as statistically significant. Results:In terms of PTV, Halcyon 2.0 plans showed better homogeneity index (HI), conformal index (CI) in the head & neck and chest. Besides, Halcyon 2.0 plans yielded better D 98% and CI in the abdomen and better D 2% in the pelvis. For organs at risk (OAR), the D 20% and D mean of bilateral lungs, and D meanof heart for Halcyon 2.0 plans in the chest were lower than those for Truebeam plans (all P<0.05). For the complexity metrics, the median average aperture area variability (AAV) of Halcyon 2.0 plans in the head & neck, abdomen and pelvis were 0.414, 0.425 and 0.432, which were better than 0.385, 0.368 and 0.361 of Truebeam plans in the corresponding sites, respectively. In the abdomen and pelvis, Halcyon 2.0 plans showed better median modulation complexity score (MCS) than Truebeam plans (0.320 vs. 0.268, 0.303 vs. 0.282; both P<0.05). The median small aperture score (SAS) for all plans of Halcyon 2.0 were better than that of Truebeam plans (all P<0.05), and the median plan average beam area (PA) of all plans of Halcyon 2.0 were larger than that of Truebeam plans (all P<0.05). Conclusions:Compared with conventional fractionated VMAT plans based on Halcyon 2.0 and Truebeam, Halcyon 2.0 plans have similar or even better dosimetric quality. However, Halcyon 2.0 plans have lower plan complexity, which makes it an advantage in clinical application.

Objective To observe the application effects of scenario simulation combined with guided feedback teaching method in the teaching of endocrinology nursing interns.Methods A total of 180 nursing students who interned in the endocri-nology department of Southern Medical University Shenzhen Hospital from January 2020 to January 2023 were selected as the re-search subjects.Using a digital randomization method,the students were divided into a control group(90 cases)and an observa-tion group(90 cases).The control group received conventional teaching,while the observation group received scenario-based teaching combined with guided feedback teaching method.The intern performance,satisfaction of teaching instructors toward students,and students'satisfaction with teaching instructors were compared between the two groups.Results The intern per-formance of the observation group was higher and showed a greater improvement after training,with statistically significant differ-ences(P＜0.05).Both the students'satisfaction with teaching instructors and the teaching instructors'satisfaction with students in the observation group were higher than those in the control group,with statistically significant differences(P＜0.05).Conclusion The application of scenario simulation combined with guided feedback teaching method in the teaching of endocri-nology nursing interns can significantly improve students'intern performance,providing a more scientific basis for nursing intern-ship teaching.

Tryptophan (TRP) is an essential amino-acid and the precursor of many signaling molecules. Under the catalysis of indoleamine 2, 3-dioxygenase, kynurenine pathway can form its metabolites uroquinolinic acid and quinolinic acid, which is the main channel of TRP metabolism.Through different mechanisms in N-methyl-D-aspartate receptor, they participate in nervous modulation, affect cognitive processes and play an important role in many central nervous system diseases development. Kynurenine pathway is different under physiological and pathological conditions. In addition, there are many rate-limiting enzymes in the kynurenine pathway, which can interfere kynurenine pathway. This article reviews the relationship between tryptophan/kynurenine pathway and cognitive dysfunction.

Background Essential and non-essential elements have an important impact on the development of the central nervous system during fetal development. Due to their less developed brain, preterm infants are more sensitive to element exposure, and are high-risk groups of neurodevelopmental abnormalities. However, it is not clear whether the effects of element exposure in utero on postpartum neurodevelopment are different between full-term infants and preterm infants. Objective To evaluate the effects of element exposure levels during pregnancy on neurodevelopment of children aged 6-24 months (of corrected age), and compare the effects between preterm and full-term children. Methods A prospective study design was adopted and this study was conducted based on the Maoming Birth Cohort Study (MBCS) in Maoming City, Guangdong Province. Twenty elements in cord blood of 197 preterm infants and 297 full-term infants were measured, including 11 essential trace elements [vanadium (V), chromium (Cr), manganese (Mn), cobalt (Co), nickel (Ni), copper (Cu), zinc (Zn), selenium (Se), strontium (Sr), tin (Sn), and iron (Fe)], and 9 non-essential trace elements [aluminum (Al), arsenic (As), thallium (Tl), lead (Pb), uranium (U), cerium (Ce), antimony (Sb), cadmium (Cd), and yttrium (Y)]. The neurodevelopment of the children at 6, 12, and 24 months were evaluated by the Ages and Stages Questionnaires-the Third Edition (ASQ-3). A generalized estimating equation (GEE) model was adopted to evaluate the associations between elements and neurodevelopment in full-term and preterm children separately. Results The positive rates of 10 elements (Mn, Cu, Zn, Se, Sr, Fe, Sb, Tl, Pb, and As) in cord blood were greater than 80%. Among the preterm birth children, the results of GEE analysis showed that after adjusting for the covariates, for each increase of interquartile range (IQR) in ln-transformed concentration, As was associated with problems/delay in the communication and problem-solving sub-scales, with the adjusted odds ratios (OR) and 95% confidence intervals (CI) of 1.36 (1.03-1.80) and 1.55 (1.10-2.20), respectively; the adjusted OR (95%CI) of problems/delay in the fine motor and problem-solving sub-scales were 1.44 (1.00-2.07) and 1.76 (1.09-2.84) for Sb, respectively; the adjusted OR (95%CI) of problems/delay in the communication sub-scale was 1.37 (1.09-1.74) for Se. No statistically significant associations between umbilical cord blood element concentrations and neurodevelopment indicators were observed among full-term children. The results of stratified analysis by sex showed that the associations between umbilical cord blood element concentrations and neurodevelopment problems/delay were only significant among female preterm children. Conclusion Exposures to As, Se, and Sb during pregnancy may increase the risk of neurodevelopment problems/delay in preterm children aged 6-24 months, and female seem to be more vulnerable.

OBJECTIVE To optimize the extraction and separation process of chebulagic acid and chebulinic acid from Terminalia chebula. METHODS Based on single factor experiment， with particle size， liquid-solid ratio， extraction time and extraction times as factors， using the contents of chebulagic acid and chebulinic acid as indexes， orthogonal experiment was designed to optimize the extraction process of chebulagic acid and chebulinic acid. Taking sample concentration， elution solvent and the ratio of eighteen-group bonded silicone reverse phase （ODS） to the amount of raw medicine as factors， the separation processes of chebulagic acid and chebulinic acid were optimized. RESULTS The optimal extraction process of chebulagic acid and chebulinic acid included ethanol volume fraction of 70%， ultrasonic extraction， particle size of 120 mesh， liquid-solid ratio of 25∶1 （mL/g）， extraction time of 20 min， and extracting for 2 times. After 3 experiments， the average comprehensive score was 99.33 （RSD＝ 0.68%， n＝3）， and the average contents of chebulagic acid and chebulinic acid were 107.05 and 58.32 mg/g， respectively. The optimal separation process of the two components included the concentration of sample loading solution was 0.5 g/mL （1 mL was equivalent to 0.5 g of medicinal materials）， the ratio of ODS to the amount of raw medicine was 10∶1.5 （g/g）， methanol-water （1∶4， V/V） eluted chebulagic acid， methanol-water （3∶7， V/V） eluted chebulinic acid. After 3 experiments， the average total yields of the two components were 53.33%， 39.23%. After recrystallization， the purity of both components was 100%. CONCLUSIONS Established extraction and separation process of chebulagic acid and chebulinic acid is simple and feasible.

Objective:To study the feasibility of using pelvic iterative cone beam CT images for dose calculation of radiation therapy planning, so as to provide support for adaptive radiotherapy.Methods:The CIRS 062 M phantom was scanned by Varian Halcyon v2.0 o-ring accelerator, and the average CT number under different scattering conditions was calculated, and then the ICBCT-ED conversion curve was established. CT images of CIRS 002PRA pelvic IMRT phantom and ICBCT images at different positions were collected. Treatment plan using VMAT technique based on CT image was designed and transplanted into ICBCT image with dose recalculated. The differences of gamma passing rate among target volume, organs at risk and 3-dimensional dose were compared. Based on the actual treatment plan of patients, the differences of 3-dimensional dose gamma passing rate in 10 pelvic patients were analyzed retrospectively.Results:There was a large CT value deviation at central position between the isolated no-scattering condition and the full-scattering condition, and the maximum deviation was 144 HU. The CT values of other positions in full-scattering condition were similar to those of the central position, and the maximum deviation was less than 50 HU. Based on the calculated result of ICBCT images at different positions of the pelvic phantom, the dose deviation of the target volume or organs at risk was less than 1 Gy. Compared with the plan based on CT images, the average 3-dimensional dose gamma passing rate under the criteria of 1% dose difference (DD)/1 mm distance-to-agreement (DTA) and 2% DD/2 mm DTA in plan based on ICBCT images were (88.86 ±1.18)% and (98.38±0.89)%, respectively. The ranges of average 3-dimensional dose gamma passing rate under the criteria of 2% DD/2 mm DTA and 3% DD/3 mm DTA in 10 patients with pelvic tumors were 90.03%-95.43% and 93.58%-97.78%, respectively, and the worst result was only 85.90% and 92.90%, respectively. The main reason of the worst result was the dose difference caused by large variation of bladder contour due to over-filling.Conclusions:Under comprehensive scattering conditions, the ICBCT-ED conversion curve is reconstructed and the treatment plan can be designed by using the ICBCT image of Halcyon v2.0 linear accelerator. The accuracy meets the standards of clinical application, which provides assurance for adaptive radiotherapy in the future.