Objective To estimate the incentive and guidance of degree policy for the doctoral student's capacity-building. Methods Totally 1185 published SCI papers completed by 1 013 doc-toral students from 2008 to 2012 in Capital Medical University were filed and impact factors of these SCI journals taken as analysis objects were organized using Microsoft Office Excellsoftware. ANOVA was used for data procession and t-test was used for statistical analysis. P<0.05 signifies statistically significant difference. Results This study showed that 97%doctoral students can complete SCI paper publication in compliance with requirements of doctoral degree policy. Quality of SCI papers of aca-demic degree PhDs was higher than that of professional degree PhDs(P=0.00). Level of SCI papers of PhDs in basic disciplines was higher than that of PhDs in clinical disciplines (P=0.00). In addition, this study found that higher leveled SCI papers originated primarily from the national key disciplines and co-first authors. Conclusions The appropriate degree policies play an important guiding role in enhancing the quality of doctoral students' education. Degree-granting units should make more specific guidance policies according to different types of disciplines and cultures, such as raising published arti-cle requirements to the clinical professional PhDs, improving and standardizing relevant degree poli-cies about SCI papers published by co-first authors, strengthening disciplinary conditions building, etc.

Objective To explore the relationship between ERG4 gene overexpression and azole resistance in clinical Candida albicans strains. Methods The National Committee for Clinical Laboratory Standards (NCCLS)M27-A2 broth microdilution method was conducted to evaluate antifungal susceptibility of 34 clinical Candida albicans isolates in vitro. Total RNA was extracted from these Candida albicans strains and transcribed into cDNA. Real-time fluorescence-based quantitative PCR was performed to determine the mRNA expression of ERG4 gene. Statistical analysis was carried out by a two-sample t-test. Results The expression level of ERG4 mRNA was significantly higher in fluconazole-resistant than in -sensitive Candida albicans strains (4.20 ± 2.56 vs. 1.72 ± 1.33, t = 3.99, P < 0.05), higher in itraconazole-resistant than in -sensitive Candida albicans strains (3.60 ± 2.47 vs. 1.66 ± 1.61, t = 3.71, P < 0.05), and higher in voriconazole-resistant than in -sensitive Candida albicans strains (3.99 ± 2.72 vs. 2.07 ± 1.58, t = 2.91, P <0.05). Further more, increased ERG4 mRNA expression was also observed in isolates cross-resistant to all the three azole antifungal agents compared with those susceptible to all of them (4.49 ± 2.73 vs. 1.69 ± 1.82, t = 3.81, P < 0.05). Conclusions The overexpression of ERG4 gene may be associated with cross resistance to fluconazole, itraconazole and voriconazole in clinical Candida albicans strains, but its exact role is expected to be investigated through downregulation of the ERG4 gene.

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 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.

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 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.

Disclosure ; Genetic Counseling ; Genetic Testing ; United States

Objective:To evaluate the association between periodontitis and mild cognitive impairment (MCI), and explore the potential local oral risk factors for MCI.Methods:The study included 70 middle-aged and elderly subjects (44 females and 26 males) with periodontal disease who were first diagnosed by the Department of Periodontology or referred by the Department of Geriatrics in Shanghai Ninth People′s Hospital, Shanghai Jiao Tong University School of Medicine from January 2021 to January 2022. In this study, the control group consisted of periodontal disease patients without cognitive impairment, and the case group (MCI group) consisted of those diagnosed with MCI referred by the geriatrics specialists. Full-mouth periodontal examinations of all subjects were performed and periodontal indicators were recorded by periodontists, while digital panoramic radiographs were taken. The severity of periodontitis was defined according to the 1999 classification, and the staging and grading of periodontitis were defined according to the 2018 American Academy of Periodontology and European Federation of Periodontology classification. The mini-mental state examination scale was chosen by geriatricians to evaluate the cognitive function of the included subjects. The cubital venous blood was drawn to detect the expression levels of inflammatory factors such as hypersensitive C-reactive protein (hs-CRP), interleukin (IL)-1β, IL-6 and tumor necrosis factor-α(TNF-α) in serum. Independent-samples t test and chi-square test were used to analyze the differences in population factors, periodontal-related indexes and serum inflammatory factors between the two groups (α=0.05). Odds ratios ( OR) for MCI according to the severity of periodontitis and main periodontal clinical indexes were calculated by binary Logistic analysis. Results:Thirty-nine subjects were included in the control group and thirty-one in the MCI group. The age of the study population was (58.3±6.2) years (range: 45-70 years). The comparison between two groups showed that the control group was with higher educational background (χ2=9.45, P=0.024) and 2.6 years younger than the MCI group [(57.1±6.0) years vs. (59.7±6.3) years, t=-1.24, P=0.082]. The number and proportion of moderate to severe periodontitis in control group were significantly lower compared to those in MCI group (17 cases with 43.6% vs. 23 cases with 74.2%, χ2=6.61, P=0.010), and the OR of moderate to severe periodontitis adjusted by age and educational background was 3.00 (95 %CI: 1.01-8.86, P=0.048). Compared with the grading (χ2=5.56, P=0.062) of periodontitis, staging had a greater impact on MCI (χ2=7.69, P=0.041), moreover the proportion of MCI in stage Ⅰ grade A periodontitis was significantly lower than any other type of periodontitis (χ2=13.86, P=0.036). In addition, less presence of deep periodontal pockets [probing depth (PD)≥6 mm] (17.9% vs. 41.9%, χ2=4.87, P=0.027), fewer number of PD≥4 mm (6.48±6.70 vs. 11.03±8.91, t=-2.44, P=0.017), lower plaque index (1.42±0.56 vs. 1.68±0.57, t=-1.91, P=0.059) and gingival index (1.68±0.29 vs. 1.96±0.30, t=-3.93, P<0.001) were in the control group than in the MCI group. However, there were no significant differences between the two groups in the levels of serum inflammatory factors, such as hs-CRP, IL-1β, IL-6 and TNF-α ( P>0.05). Conclusions:It appears a strong correlation between moderate to severe periodontitis and the incidence of MCI in middle-aged and elderly people. Moreover, deep and increased number of periodontal pockets, poor oral hygiene, and severe gingival inflammation can be potentially associated risk factors for MCI.