Objective To analyze the reasons for the failure of subject screening in clinical trials of antineoplastic drugs and the impact of natriuretic criteria on the entry of subjects into clinical trials,to explore the strategies to improve the suc-cessful enrolment of screened subjects,and to provide reference bases for research institutes and sponsors in the formulation of na-triuretic criteria.Methods This study selected data from 40 drug clinical trials conducted at the Drug Clinical Trial Research Center of the Cancer Hospital of the Chinese Academy of Medical Sciences from January 1,2016,to June 30,2022.It statistically described the collected data on the frequency and percentage composition of screening failures among participants and the inclu-sion and exclusion criteria in the protocols.Results A total of 425 subjects were screened out of 40 clinical trial programmers covering 8 tumor types,with the majority being＜65 years of age(333,78.4％),of which the most important reasons included vol-untary withdrawal(71,16.7％),tumor metastasis(52,12.2％),failure to recover from treatment of pre-existing disease(38,8.9％),failure of bone marrow function(19,4.5％),and non-compliant liver function(15,3.5％).Among the nadir indicators,the age of the subjects(100％),ECOG score(97.5％),bone marrow function(ANC:95.0％,PLT:97.5％,HB:97.5％),liver function(T-BiL:95.0％,ALT:87.5％,AST:95.0％),renal function(CR:80.0％),and viral screening(HIV:80.0％,HBV:70.0％,HCV:62.5％)were relatively stringent.Conclusion The main reasons for subject screening failure in clinical trials in oncology in our hospital are voluntary withdrawal,brain metastasis,and failure of their biochemical test standards,which are close-ly related to the setting of clinical trial nadir criteria.Therefore,an in-depth understanding of subjects'characteristics,accurate set-ting of appropriate nadir criteria,continuous improvement of trial design,and strengthening of communication with subjects to pro-vide more relevant information will help to improve the screening success rate of clinical trials.

Abstract To understand the relationship between cardiovascular disease (CVD) and adverse childhood experiences (ACEs), the present review aims to describe the burden and influencing factors of CVD, epidemiological characteristics and burden of ACEs, current research on the relationship between ACEs and CVD, and the mechanism of ACEs leading to CVD. It is proposed that further assessment of the relationship is warranted through identifying blood biomarkers, conducting prospective cohort studies and intervention studies. Such efforts would provide valuable scientific insights for primary prevention strategies for cardiovascular disease.

Objective To establish an ultra-high-performance liquid chromatography-triple quadrupole tandem mass spectrometry method for the determination of N-(1,3-dimethylbutyl)-N′-phenyl-p-phenylenediamine quinone (6PPDQ) in human plasma and urine. Methods Plasma and urine samples (0.3 mL each) were mixed with 0.9 mL acetonitrile and dichloromethane, vortexed, and subjected to ultrasonic treatment to facilitate extraction. After centrifugation, the extract was collected, evaporated to dry powder under nitrogen, and reconstituted. Separation was performed on a C18 column, and detection was carried out using ultra-high-performance liquid chromatography-triple quadrupole tandem mass spectrometry with external standard quantification. Results 6PPDQ showed good linearity in the range of 0.01-25.00 μg/L in both human plasma and urine, with correlation coefficients of 0.999 5 and 0.999 7, respectively. The detection limits for plasma and urine were 8 and 6 ng/L, and the lower limits of quantification were 27 and 19 ng/L, respectively. The average recovery rates were 97.00%-100.00% for plasma and 90.00%-96.50% for urine. The within-run relative standard deviations (RSDs) were 4.35%-10.00% for plasma and 2.34%-11.11% for urine, while the between-run RSDs were 6.80%-8.46% and 2.60%-10.00%, respectively. Samples can be stored for seven days at 4 ℃ or -20 ℃. respectively. Samples can be stored for seven days at 4 ℃ or -20 ℃. Matrix effects ranged from 87.12%-99.27% for plasma and 91.00%-97.56% for urine. Conclusion The proposed method is simple, highly sensitive, and reproducible, and is suitable for the determination of 6PPDQ in human plasma and urine samples.

Objective To analyze the reasons for the failure of subject screening in clinical trials of antineoplastic drugs and the impact of natriuretic criteria on the entry of subjects into clinical trials,to explore the strategies to improve the suc-cessful enrolment of screened subjects,and to provide reference bases for research institutes and sponsors in the formulation of na-triuretic criteria.Methods This study selected data from 40 drug clinical trials conducted at the Drug Clinical Trial Research Center of the Cancer Hospital of the Chinese Academy of Medical Sciences from January 1,2016,to June 30,2022.It statistically described the collected data on the frequency and percentage composition of screening failures among participants and the inclu-sion and exclusion criteria in the protocols.Results A total of 425 subjects were screened out of 40 clinical trial programmers covering 8 tumor types,with the majority being＜65 years of age(333,78.4％),of which the most important reasons included vol-untary withdrawal(71,16.7％),tumor metastasis(52,12.2％),failure to recover from treatment of pre-existing disease(38,8.9％),failure of bone marrow function(19,4.5％),and non-compliant liver function(15,3.5％).Among the nadir indicators,the age of the subjects(100％),ECOG score(97.5％),bone marrow function(ANC:95.0％,PLT:97.5％,HB:97.5％),liver function(T-BiL:95.0％,ALT:87.5％,AST:95.0％),renal function(CR:80.0％),and viral screening(HIV:80.0％,HBV:70.0％,HCV:62.5％)were relatively stringent.Conclusion The main reasons for subject screening failure in clinical trials in oncology in our hospital are voluntary withdrawal,brain metastasis,and failure of their biochemical test standards,which are close-ly related to the setting of clinical trial nadir criteria.Therefore,an in-depth understanding of subjects'characteristics,accurate set-ting of appropriate nadir criteria,continuous improvement of trial design,and strengthening of communication with subjects to pro-vide more relevant information will help to improve the screening success rate of clinical trials.

OBJECTIVE To explore the potential mechanism of ketamine-induced cognitive impairment in mice based on metabolomics.METHODS Male C57BL/6 mice were randomly divided into control group and ketamine group(25 mg/kg),with 12 mice in each group.Each group of mice was intraperitoneally injected with normal saline or corresponding drugs,4 times a day,for 10 consecutive days.On the last 2 days of drug administration,the cognitive behavior was evaluated by Y maze and novel object recognition test,and the histopathological changes in the prefrontal cortex(PFC)were observed.Ultra-high performance liquid chromatography-tandem mass spectrometry technology was used to analyze the changes of metabolites in PFC,screen for differential metabolites,and perform pathway enrichment analysis.RESULTS Compared with the control group,the morphology of PFC neurons in the ketamine group of mice was inconsistent.There were cavities around the nucleus,and the number of deeply stained cells increased.The mean optical density value of the Nissl staining positive area was significantly reduced,and the alternation rate and discrimination index were significantly reduced(P＜0.05 or P＜0.01).In the PFC tissue samples of mice of the two groups,there were a total of 114 differential metabolites,including 73 up-regulated and 41 down-regulated metabolites,including glutamine,succinic acid,ketoglutarate,and choline,etc.The differential metabolites mentioned above were mainly enriched in metabolism of alanine,aspartate and glutamate,metabolism of arginine and proline,γ aminobutyric acid synapses,pyrimidine metabolism,cholinergic synapses pathways,etc.CONCLUSIONS Ketamine can induce cognitive impairment in mice.Its neurotoxicity is related to abnormal synaptic transmission and energy metabolism,and neuroimmune regulation disorders.

Objective To analyze differential metabolites (DMs) in the urine of workers with occupational nickel exposure using non-targeted metabolomics, and to screen differential metabolic pathways. Methods A total of 30 nickel exposed workers were selected as the exposure group, and 30 administrative staff from the same factory were selected as the control group using the judgment sampling method. Urine samples of the individuals from the two groups were collected. The ultra-high performance liquid chromatography with quadrupole time-of-flight mass spectrometry and non-targeted metabolomics were used to detect and identify metabolites. The differential metabolic profiles were compared between workers of the two groups, and key differential metabolic pathways and potential biomarkers were screened. The association of DMs and urinary nickel level were evaluated by Spearman correlation coefficients. The sensitivity and specificity of biomarkers were assessed by receiver operating characteristic (ROC) curve analysis. Results A total of 418 metabolites were identified in the urine of worker in the exposure and control groups. The result of principal component analysis and orthogonal partial least squares analysis showed that there were 128 DMs in the urine of workers in the exposure group compared with the control group. These DMs were mainly enriched in glutathione metabolism, carnitine synthesis, and amino acid and nucleotide metabolism pathways, including glycine and serine metabolism. The result of correlation analysis and ROC curve analysis revealed that 4-methylcatechol, 4-vinylphenol sulfate, 2-hydroxyphenylacetone sulfate, 2-dodecylbenzenesulfonic acid, and decylbenzenesulfonic acid could be the potential biomarkers for nickel exposure (all area under the ROC curve >0.800). Conclusion There were significant differences in the urinary metabolic profiles of workers with occupational nickel exposure. The five DMs including 4-methylcatechol, 4-vinylphenol sulfate, 2-hydroxyphenylacetone sulfate, 2-dodecylbenzenesulfonic acid, and decylbenzenesulfonic acid. These DMs could be potential biomarkers of occupational nickel exposure.

Biotoxins, which include bacterial, fungal, marine, plant, and animal toxins, are widespread in living and occupational environments, posing potential threats to human health. Rapid detection of biotoxins in blood is crucial for preventing health hazards and enabling timely disease diagnosis and treatment. Biosensors and immunoassay technologies have critical advantages in the rapid detection of biotoxins in blood. Common biosensors, such as surface plasmon resonance biosensors and fluorescent biosensors, enhance sensitivity and reduce detection limits through signal amplification. Common immunoassay methods, such as colloidal gold immunochromatography, fluorescence immunochromatography, and chemiluminescence immunoassay, improve detection efficacy and sensitivity through specific antibody-antigen binding and nanotechnology. However, current rapid detection technologies of bitoxins in blood face challenges such as matrix interference and insufficient specificity, and they fall short in high-throughput detection of multiple toxins simultaneously. Future developments should focus on improving sample pretreatment, innovating signal amplification methods, enhancing specificity on recognition of elements, and designing portable detection devices and high-throughput platforms for simultaneous toxin analysis. These advancements aim to improve the sensitivity and reliability of detection methods, providing more accurate and convenient solutions for biotoxin detection in blood.

Objective:A nationwide multi-center and large sample survey was conducted to compare the validity of the Mini International Neuropsychiatric Interview (Hypo-) Manic Episode with Mixed Features-DSM-5 Module (MINI-M) questionnaire and the Clinically Useful Depression Outcome Scale Supplemented with Questions for the DSM-5 Mixed Features Specifier (CUDOS-M) depression subscale in identifying mixed features in patients experiencing (hypo-) manic episodes.Methods:Using a convenience sampling method, 366 patients with bipolar disorder experiencing acute (hypo-) manic episodes who met the inclusion and exclusion criteria were recruited. The diagnosis of "with mixed features" was based on the DSM-5 criteria for mixed features. The predictive validity of the MINI-M questionnaire and the CUDOS-M depression subscale to screen mixed features was analyzed using the receiver operating characteristic (ROC) curve. Additionally, the difference in area under the ROC curve (AUC) between the two instruments was compared.Results:The AUC for the MINI-M questionnaire and the CUDOS-M depression subscale in screening mixed features were 0.79 (95 %CI=0.75-0.84) and 0.81 (95 %CI=0.77-0.86), respectively. There was no statistically significant difference in AUC between the two measurements ( Z=-1.19, P>0.05). Among patients with acute (hypo-) manic episodes, 45.9% (168/366) presented with mixed features according to the DSM-5 criteria, while the corresponding figures were 43.7% (160/366) using the MINI-M questionnaire (total score≥3) and 42.1% (154/366) using the CUDOS-M depression subscale (total score≥20). Screening results were comparable among the three measures. Conclusion:Mixed features are common among patients experiencing acute (hypo-) manic episodes. The MINI-M questionnaire and the CUDOS-M depression subscale demonstrate equivalent validity in identifying mixed features.

Objective:A nationwide multi-center and large sample survey was conducted to compare the validity of the Mini International Neuropsychiatric Interview (Hypo-) Manic Episode with Mixed Features-DSM-5 Module (MINI-M) questionnaire and the Clinically Useful Depression Outcome Scale Supplemented with Questions for the DSM-5 Mixed Features Specifier (CUDOS-M) depression subscale in identifying mixed features in patients experiencing (hypo-) manic episodes.Methods:Using a convenience sampling method, 366 patients with bipolar disorder experiencing acute (hypo-) manic episodes who met the inclusion and exclusion criteria were recruited. The diagnosis of "with mixed features" was based on the DSM-5 criteria for mixed features. The predictive validity of the MINI-M questionnaire and the CUDOS-M depression subscale to screen mixed features was analyzed using the receiver operating characteristic (ROC) curve. Additionally, the difference in area under the ROC curve (AUC) between the two instruments was compared.Results:The AUC for the MINI-M questionnaire and the CUDOS-M depression subscale in screening mixed features were 0.79 (95 %CI=0.75-0.84) and 0.81 (95 %CI=0.77-0.86), respectively. There was no statistically significant difference in AUC between the two measurements ( Z=-1.19, P>0.05). Among patients with acute (hypo-) manic episodes, 45.9% (168/366) presented with mixed features according to the DSM-5 criteria, while the corresponding figures were 43.7% (160/366) using the MINI-M questionnaire (total score≥3) and 42.1% (154/366) using the CUDOS-M depression subscale (total score≥20). Screening results were comparable among the three measures. Conclusion:Mixed features are common among patients experiencing acute (hypo-) manic episodes. The MINI-M questionnaire and the CUDOS-M depression subscale demonstrate equivalent validity in identifying mixed features.

Objective: To investigate the specificity of endogenous metabolic profile in plasma of patients with occupational acute methyl acetate poisoning using non-targeted metabolomics. Methods: A total of six patients with occupational acute methyl acetate poisoning were selected as the poisoning group, while 10 healthy workers without occupational exposure history of chemical hazards in the same industry were selected as the control group using the judgment sampling method. Metabolites in patient plasma of the two groups were detected using ultra-high performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry, and non-targeted metabolomics analysis was performed. Principal component analysis and partial least squares discriminant analysis were used to identify differential metabolites and analyze their metabolic pathways. Results: There were significant differences in metabolite profiles in patient plasma between poisoning group and control group. A total of 195 differentially expressed metabolites were screened in plasma of patients in poisoning group, including 119 upregulated and 76 downregulated metabolites. Lipid substances (lipids and lipid-like molecules) accounted for the highest proportion (21.5%). The differential metabolites of poisoning group were related to folate biosynthesis, amino acid metabolism, pyrimidine metabolism, sphingolipid biosynthesis and other metabolic pathways in plasma compared with the control group (all P<0.05). Conclusion: Occupational acute methyl acetate poisoning affects metabolism of the body. The folic acid biosynthesis, amino acid and lipid metabolism and other pathways may be involved in the occurrence and development of poisoning.