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.

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.

Objective:To explore the cognitive function characteristics of children with primary snoring (PS) and obstructive sleep apnea-hypopnea syndrome (OSAHS) using event-related potentials.Methods:From October 2020 to October 2022, 20 children with OSAHS, 20 children with PS, and 22 normal children were recruited for continuous performance task (CPT) and behavioral assessments. ERP and behavioral data were meticulously recorded, with measurements of N1, P2, N2, and P3 wave amplitudes and latencies at F3, Fz, and F4 electrode sites. Statistical analyses were conducted using one-way ANOVA and Kruskal-Wallis test via SPSS 25.0 software.Results:(1) Behavioural test: There was no statistically significant difference in terms of correct responses, response times, and false alarms among the three groups (all P>0.05). (2) F3 Lead: There were statistically significant differences in Go-P2 amplitude, Nogo-P2 amplitude, Nogo-P2 latency, Go-P3 amplitude, and Nogo-P3 latency among the three groups (all P<0.05). Specifically, the OSAHS group exhibited higher Go-P2 amplitude((15.03±5.12) μV vs (10.97±5.50)μV), Nogo-P2 amplitude((14.80±5.84) μV vs (9.67±4.79)μV), and Go-P3 amplitude((11.58±6.02) μV vs (7.49±4.89) μV) compared to the normal group. Additionally, the OSAHS and PS groups exhibited longer Nogo-P2 latency compared to the normal group((223.10±20.61) ms vs (208.00±23.09) ms, (230.60±13.61) ms vs (208.00±23.09) ms), as well as prolonged Nogo-P3 latency((459.20±34.26) ms vs (460.40±24.52) ms and (429.91±31.49) ms) (all P<0.05). Fz Lead: There were statistically significant differences in Go-N1, Go-P2, Nogo-P2, Go-P3, Nogo-N2 wave amplitudes, and Nogo-P3 latency among the three groups (all P<0.05). Compared to the normal group, the OSAHS group exhibited increased Go-P3 amplitude((9.07±5.68) μV vs (5.10±3.51) μV) and decreased Nogo-N2 amplitude((-8.80±5.97) μV vs (-12.84±4.86) μV). Moreover, both the OSAHS and PS groups had prolonged Nogo-P3 latency compared to the normal group((481.60±45.16) ms vs (435.13±28.17) ms and 484.00(443.50, 525.00) ms vs (435.13±28.17) ms) (both P<0.05). F4 Lead: There were statistically significant differences in Go-P2 and Nogo-P2 wave amplitudes among the three groups (all P<0.05). Compared to the normal group, the OSAHS group demonstrated increased Go-P2 amplitude((13.72±5.64) μV vs (9.70±4.59) μV) and Nogo-P2 amplitude((13.90±5.35) μV vs (9.64±3.74) μV) (both P<0.05). Conclusions:Both children with OSAHS and PS exhibit attentional cognitive impairments. However, children with OSAHS demonstrate more pronounced deficits in conflict monitoring, response inhibition, and executive functioning. The prolonged latency of the P3 wave serves as a sensitive electrophysiological marker for the early detection of neurocognitive impairment in children with sleep disordered breathing.

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.

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.

Tumors are spatially heterogeneous tissues that comprise numerous cell types with intricate structures.By interacting with the microenvironment,tumor cells undergo dynamic changes in gene expression and metabolism,resulting in spatiotemporal variations in their capacity for proliferation and metastasis.In recent years,the rapid development of histological techniques has enabled efficient and high-throughput biomolecule analysis.By preserving location information while obtaining a large number of gene and molecular data,spatially resolved metabolomics(SRM)and spatially resolved transcriptomics(SRT)approaches can offer new ideas and reliable tools for the in-depth study of tumors.This review provides a comprehensive introduction and summary of the fundamental principles and research methods used for SRM and SRT techniques,as well as a review of their applications in cancer-related fields.

The brain is the most advanced organ with various complex structural and functional microregions. It is often challenging to understand what and where the molecular events would occur for a given drug treatment in the brain. Herein, a temporo-spatial pharmacometabolomics method was proposed based on ambient mass spectrometry imaging and was applied to evaluate the microregional effect of olanzapine (OLZ) on brain tissue and demonstrate its effectiveness in characterizing the microregional pharmacokinetics and pharmacodynamics of OLZ for improved understanding of the molecular mechanism of drugs acting on the microregions of the brain. It accurately and simultaneously illustrated the levels dynamics and microregional distribution of various substances, including exogenous drugs and its metabolites, as well as endogenous functional metabolites from complicated brain tissue. The targeted imaging analysis of the prototype drug and its metabolites presented the absorption, distribution, metabolism, and excretion characteristics of the drug itself. Moreover, the endogenous functional metabolites were identified along with the associated therapeutic and adverse effects of the drug, which can reflect the pharmacodynamics effect on the microregional brain. Therefore, this method is significant in elucidating and understanding the molecular mechanism of central nervous system drugs at the temporo and spatial metabolic level of system biology.

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.