Objective:To explore the application value of histogram and texture feature analysis based on CT images in distinguishing long bone osteosarcoma (OS) from Ewing sarcoma (ES).Methods:A retrospective collection of 25 patients with long bone osteosarcoma and 25 patients with Ewing sarcoma confirmed by surgery and pathology in National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Qilu Hospital of Shandong University and Nanjing Drum Tower Hospital, Nanjing University Medical School, from March 2018 to May 2023 was conducted. All patients were randomly divided into a training set (21 cases of OS and 19 cases of ES) and a validation set (4 cases of OS and 6 cases of ES) in an 8∶2 ratio. The region of interest (ROI) on CT images to extract texture feature parameters was manually sketched. Random forest and least absolute shrinkage and selection operator (LASSO) algorithm were used for feature screening. Logistic regression (LR), random forest (RF), support vector machine (SVM) and K-nearest neighbor (KNN) classifiers were used to establish models respectively. Receiver operating characteristic (ROC)curve was drawn and area under the curve (AUC) was calculated to evaluate the diagnostic efficiency of the four models.Results:A total of 100 texture parameters were extracted from CT images, and 8 feature parameters (maximum 3D diameter, 10th percentile, kurtosis, maximum pixel intensity value, inverse normalization, grayscale level variance, long range high grayscale emphasis, and low grayscale area emphasis) were obtained through screening. Four classifiers were used to establish models, and the AUC values of the four models (LR, RF, SVM, KNN) in the validation group were 0.92, 0.79, 0.83, and 0.73, respectively. LR and SVM classifier algorithm trains models had high diagnostic efficiency, with an accuracy of 90%, sensitivity of 83%, specificity of 100%, and AUC of 92% for the LR classifier validation set; the accuracy of SVM classifier validation set was 80%, sensitivity was 67%, specificity was 100%, and AUC was 83%.Conclusions:LR and SVM models have high value in distinguishing OS and ES.

Objective:To explore the diagnostic value of magnetic resonance imaging (MRI) Q-Dixon fat quantification technique in differentiating vertebral metastases from hemangiomas in cancer patients.Methods:A retrospective analysis was conducted on 20 patients with vertebral metastases and 8 with vertebral hemangiomas who underwent vertebral MRI scans at the National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College from December 2021 to December 2023. Two radiologists independently measured the fat fractions (FF) in three areas (the lesion area, the normal area of the same vertebra, and the normal area of an adjacent vertebra) and evaluated the consistency of measurements. Group differences were tested using independent sample t-tests or Mann-Whitney U tests, and diagnostic performance was assessed by plotting the receiver operating characteristic (ROC) curve and calculating the area under the curve (AUC). Results:There was very high inter-observer consistency in the FF measurements across the three regions. The FF in the lesion areas of vertebral metastases group was significantly lower than that in the vertebral hemangioma group (13.8 ± 11.5 vs. 56.5 ± 22.1), there was statistical difference ( P<0.01). There were no significant differences in the FF of normal vertebral areas between the two groups ( P>0.05). ROC curve analysis showed that FF could differentiate vertebral metastases from hemangiomas with an AUC of 0.931, a specificity of 90%, and a sensitivity of 87.5%. Conclusions:The FF measured by the Q-Dixon quantitative fat technique can accurately differentiate between vertebral hemangiomas and vertebral metastases, providing more precise guidance for the diagnosis of vertebral lesions.

Pulmonary fibrosis(PF)is a chronic progressive end-stage lung disease.However,the mechanisms un-derlying the progression of this disease remain elusive.Presently,clinically employed drugs are scarce for the treatment of PF.Hence,there is an urgent need for developing novel drugs to address such diseases.Our study found for the first time that a natural source of Prismatomeris connata Y.Z.Ruan(Huang Gen,HG)ethyl acetate extract(HG-2)had a significant anti-PF effect by inhibiting the expression of the transforming growth factor beta 1/suppressor of mothers against decapentaplegic(TGF-β1/Smad)pathway.Network pharmacological analysis suggested that HG-2 had effects on tyrosine kinase phosphorylation,cellular response to reactive oxygen species,and extracellular matrix(ECM)disassembly.Moreover,mass spec-trometry imaging(MSI)was used to visualize the heterogeneous distribution of endogenous metabolites in lung tissue and reveal the anti-PF metabolic mechanism of HG-2,which was related to arginine biosyn-thesis and alanine,asparate and glutamate metabolism,the downregulation of arachidonic acid meta-bolism,and the upregulation of glycerophospholipid metabolism.In conclusion,we elaborated on the relationship between metabolite distribution and the progression of PF,constructed the regulatory metabolic network of HG-2,and discovered the multi-target therapeutic effect of HG-2,which might be conducive to the development of new drugs for PF.

Three-dimensional(3D)cell spheroid models combined with mass spectrometry imaging(MSI)enables innovative investigation of in vivo-like biological processes under different physiological and patho-logical conditions.Herein,airflow-assisted desorption electrospray ionization-MSI(AFADESI-MSI)was coupled with 3D HepG2 spheroids to assess the metabolism and hepatotoxicity of amiodarone(AMI).High-coverage imaging of＞1100 endogenous metabolites in hepatocyte spheroids was achieved using AFADESI-MSI.Following AMI treatment at different times,15 metabolites of AMI involved in N-desethylation,hydroxylation,deiodination,and desaturation metabolic reactions were identified,and according to their spatiotemporal dynamics features,the metabolic pathways of AMI were proposed.Subsequently,the temporal and spatial changes in metabolic disturbance within spheroids caused by drug exposure were obtained via metabolomic analysis.The main dysregulated metabolic pathways included arachidonic acid and glycerophospholipid metabolism,providing considerable evidence for the mechanism of AMI hepatotoxicity.In addition,a biomarker group of eight fatty acids was selected that provided improved indication of cell viability and could characterize the hepatotoxicity of AMI.The combination of AFADESI-MSI and HepG2 spheroids can simultaneously obtain spatiotemporal infor-mation for drugs,drug metabolites,and endogenous metabolites after AMI treatment,providing an effective tool for in vitro drug hepatotoxicity evaluation.

Deconvolution of potential drug targets of the central nervous system (CNS) is particularly challenging because of the complicated structure and function of the brain. Here, a spatiotemporally resolved metabolomics and isotope tracing strategy was proposed and demonstrated to be powerful for deconvoluting and localizing potential targets of CNS drugs by using ambient mass spectrometry imaging. This strategy can map various substances including exogenous drugs, isotopically labeled metabolites, and various types of endogenous metabolites in the brain tissue sections to illustrate their microregional distribution pattern in the brain and locate drug action-related metabolic nodes and pathways. The strategy revealed that the sedative-hypnotic drug candidate YZG-331 was prominently distributed in the pineal gland and entered the thalamus and hypothalamus in relatively small amounts, and can increase glutamate decarboxylase activity to elevate γ-aminobutyric acid (GABA) levels in the hypothalamus, agonize organic cation transporter 3 to release extracellular histamine into peripheral circulation. These findings emphasize the promising capability of spatiotemporally resolved metabolomics and isotope tracing to help elucidate the multiple targets and the mechanisms of action of CNS drugs.

Objective:To compare the accuracy of different stone scoring systems for predicting the stone-free rate (SFR) after retrograde intrarenal surgery (RIRS).Methods:The clinical data of 227 patients with lithiasis undergoing RIRS from June 2017 to December 2020 in Affiliated Benq Hospital of Nanjing Medical University and Qingdao Fuwai Hospital were retrospectively analyzed. There were 152 males and 75 females. The average age was (53.0±10.4) years old. The average body mass index was (26.9±2.1)kg/m 2. The maximum diameter of the stone was (22.7±12.8)mm. The stone is located in left side in 133 cases and in right side in 94 cases. The stones of 44 cases were located in upper ureter, upper calyceal or renal pelvis, that of 23 cases were in medium calyceal, 157 cases in lower calyceal, and 3 cases in calyceal diverticulum.The average CT value of stone was (778.3±350.4)HU. American Society of Anesthesiology (ASA)scores: 86 cases of grade Ⅰ, 129 cases of grade Ⅱ, 12 cases of grade Ⅲ. Preoperative non-contrast CT was conducted and three-dimensional data were constructed. A single observer reviewed and entered the modified S.T.O.N.E., RUSS, modified S-ReSC, R. I.R.S., SHA.LIN, Ito nomogram, S. O.L.V.E., stone free index (SFI) scores. Logistic analysis were performed between every score and SFR. Receiver operating characteristic (ROC) curve was drawn to detect sensitivity and specificity of every score in predicting the SFR. The predictive accuracies of all scores were compared. Results:The SFR was 83.0%(189/227). There were statistically significant differences in modified S. T.O.N.E.(10.5±1.9 vs. 12.7±1.8), RUSS[1(0, 4) vs. 3(0, 6)], modified S-ReSC (8.2±5.6 vs. 11.8±6.0), R.I.R.S.(6.2±1.4 vs. 8.1±1.2), SHA.LIN (9.9±2.4 vs. 13.0±2.1), Ito nomogram (12.1±5.8 vs. 4.3±3.3), S. O.L.V.E. (6.8±1.6 vs. 8.7±1.2), SFI score (7.9±1.1 vs. 6.3±0.9) between the stone-free group and the stone remaining group ( P <0.05). Logistic regression revealed that modified S.T.O.N.E., RUSS, modified S-ReSC, R. I.R.S., SHA.LIN, Ito nomogram, S. O.L.V.E. and SFI score were significantly associated with SFR( P<0.05). There were no significant differences in the area under the curve (AUC) between the modified S. T.O.N.E., RUSS, R. I.R.S., SHA.LIN, Ito nomogram, S. O.L.V.E. and SFI score( P>0.05), but there were significant differences in the AUC between modified S-ReSC score and other score ( P<0.05). When the cutoff of SHA.LIN, SFI and R. I.R.S. score was determined as 10, 6 and 6 scores, the specificity of SHA.LIN, SFI and R. I.R.S. score was 94.7%, 92.6% and 89.5%, respectively. Conclusions:All score could predict the postoperative SFR of RIRS, while the SHA.LIN, SFI and R.I.R.S. score were more accurate than the other scores. The accuracy of the modified S-ReSC in predicting SFR after RIRS was slightly worse than other scores.

Against tumor-dependent metabolic vulnerability is an attractive strategy for tumor-targeted therapy.However,metabolic inhibitors are limited by the drug resistance of cancerous cells due to their metabolic plasticity and heterogeneity.Herein,choline metabolism was discovered by spatially resolved metab-olomics analysis as metabolic vulnerability which is highly active in different cancer types,and a choline-modified strategy for small molecule-drug conjugates(SMDCs)design was developed to fool tumor cells into indiscriminately taking in choline-modified chemotherapy drugs for targeted cancer therapy,instead of directly inhibiting choline metabolism.As a proof-of-concept,choline-modified SMDCs were designed,screened,and investigated for their druggability in vitro and in vivo.This strategy improved tumor targeting,preserved tumor inhibition and reduced toxicity of paclitaxel,through targeted drug delivery to tumor by highly expressed choline transporters,and site-specific release by carboxylesterase.This study expands the strategy of targeting metabolic vulnerability and provides new ideas of devel-oping SMDCs for precise cancer therapy.

Objective To explore the effectiveness of virtual autopsy-based postmortem computed tomography(PMCT)liver three dimensional slicer(3D slicer)artificial intelligence(AI)volume reconstruction to assist forensic practice.Methods Twenty cases of the deceased who underwent both virtual autopsy and traditional autopsy in our center were selected and subjected to liver volume segmentation by 3D slicer method,Tada's formula method and literature method,and the data obtained from the traditional autopsy were compared and analyzed to obtain the accuracy rate.Results The 3D slicer method yielded higher consistency(95%confidence interval),lower volumetric variability(standard deviation),and a smaller region(variance)of uncertainty than the Tada formula method and the methods mentioned in the literature.Conclusion 3D slicer AI reconstruction based on virtual autopsy can visualize virtual anatomy,help increase the diagnostic accuracy of traditional autopsy,assist in pathological diagnosis,and provide new directions and tools for the development of imaging histology of virtual autopsy.

With the rapid development and wide application of traditional Chinese medicine injection (TCMI), a number of adverse events of some TCMIs have incessantly been reported and have drawn broad attention in recent years. Establishing effective and practical analytical methods for safety evaluation and quality control of TCMI can help to improve the safety of TCMIs in clinical applications. In this study, a sensitive and rapid high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) method has been developed and validated for the quantitative determination of potentially harmful substance 5,5'-oxydimethylenebis (2-furfural, OMBF) in TCMI samples. Chromatographic separation was performed on a C18 reversed-phase column (150 mm × 2.1 mm, 5 µm) by gradient elution, using methanol-water containing 0.1% formic acid as mobile phase at the flow rate of 0.3 mL/min. MS/MS detection was performed on a triple quadrupole mass spectrometer with positive electrospray ionization in the multiple reaction-monitoring mode. The method was sensitive with a limit of quantification of 0.3 ng/mL and linear over the range of 0.3-30 ng/mL (=0.9998). Intra- and inter-day precision for analyte was <9.52% RSD with recoveries in the range 88.0-109.67% at three concentration levels. The validated method was successfully applied to quantitatively determine the compound OMBF in TCMIs and glucose injections. Our study indicates that this method is simple, sensitive, practicable and reliable, and could be applied for safety evaluation and quality control of TCMIs and glucose injections.

A fast atom bombardment mass spectrometric method to predict and detect the antioxidant ability of phenolic compounds was developed to accelerate the pace of finding the antioxidant with higher effect and low toxicity. The effect of experimental conditions on the relative peak intensity ratio of M+· ion to [ M+H]+ion in the FAB mass spectra of the compound was investigated, including matrix, scan time and concentration. The correlation of antioxidant activity with the I ( M+· )/I ( [ M+H ]+) value of flavonoids obtained in FAB mass spectra was studied. Then the antioxidant activity of 12 phenolic compounds was predicted using the above method and the results were compared with those obtained from thiobarbituric acid ( TBA) method. The results show that the I( M+· )/I( [ M+H]+) value of the phenolic compound obtained from FAB mass spectra could reflect their antioxidant activity, which could help to accelerate the development of the antioxidant drug.