OBJECTIVETo find out the relationship between the opacity in lens and the contents of 2,6-dinitro-4-amino-toluene(DNAT) in the urine of exposed workers.

METHODSTesting the exposed worker's lens and measuring the contents of DNAT in the urine after work.

RESULTSWhen the opacity of the lens occurred, the contents of DNAT in the urine(2.38 mg/L) of workers exposed to TNT were significantly higher than those without opacity in lens(1.44 mg/L) (P < 0.05).

CONCLUSIONThe severity of opacity of lens increased with the contents of DNAT raised in the urine. The threshold value suggested by ILO is not applicable to Chinese occupational population, which recommends the contents of DNAT(30 mg/L) in the urine for the workers exposed to TNT as biological occupational exposed limits.

Aniline Compounds ; urine ; Cataract ; chemically induced ; Environmental Monitoring ; Humans ; Occupational Exposure ; adverse effects ; Trinitrotoluene ; metabolism

OBJECTIVE: This study was aimed to compare the accuracy of Support Vector Machine (SVM) and Gaussian Mixture Model (GMM) in the detection of manic state of bipolar disorders (BD) of single patients and multiple patients. METHODS: 21 hospitalized BD patients (14 females, average age 34.5±15.3) were recruited after admission. Spontaneous speech was collected through a preloaded smartphone. Firstly, speech features [pitch, formants, mel-frequency cepstrum coefficients (MFCC), linear prediction cepstral coefficient (LPCC), gamma-tone frequency cepstral coefficients (GFCC) etc.] were preprocessed and extracted. Then, speech features were selected using the features of between-class variance and within-class variance. The manic state of patients was then detected by SVM and GMM methods. RESULTS: LPCC demonstrated the best discrimination efficiency. The accuracy of manic state detection for single patients was much better using SVM method than GMM method. The detection accuracy for multiple patients was higher using GMM method than SVM method. CONCLUSION: SVM provided an appropriate tool for detecting manic state for single patients, whereas GMM worked better for multiple patients’ manic state detection. Both of them could help doctors and patients for better diagnosis and mood state monitoring in different situations.
Bipolar Disorder* ; Diagnosis ; Discrimination (Psychology) ; Female ; Humans ; Methods ; Smartphone ; Support Vector Machine*

Humans ; Severe Acute Respiratory Syndrome ; diagnosis ; therapy

BackgroundSchizophrenic patients have metabolic disorders， impaired language and information processing function. Inflammatory factors may play an important role in the occurrence and development of schizophrenia. ObjectiveTo explore the relationship of the inflammatory factor levels with metabolic levels， language fluency and information processing function in patients with schizophrenia， so as to provide references for clinical understanding of the neuropathological mechanisms of schizophrenia. MethodsA total of 96 patients with schizophrenia were included in the study group， who were hospitalized in the Fourth People's Hospital of Hefei from January 2021 to December 2022 as well as met the diagnostic criteria of Diagnostic and Statistical Manual of Mental Disorders， fifth edition （DSM-5） and Mini-International Neuropsychiatric Interview （MINI） 6.0 .Meanwhile， population who underwent physical examination at the same hospital were included in the control group （n=42）. A high-sensitivity multi factor electrochemiluminescence analyzer was used to detect the levels of inflammatory factors IL-4， IL-5， IL-7， IL-8， IL-10 and IL-13. A fully automated biochemical analyzer was used to detect the levels of metabolic indicators such as fasting blood glucose， triglycerides， high-density lipoprotein， apolipoprotein A， creatinine and urea nitrogen. Verbal fluency and information processing function of all participants were assessed by using Verbal Fluency Test （VFT） and Stroop Color Word Test （SCWT）. ResultsThere were statistically significant differences in the levels of IL-4， IL-5， IL-7， IL-8， IL-10， IL-13 and IL-15 between the study group and the control group （P<0.05）. There were statistically significant differences in BMI， waist circumference， fasting blood glucose， triglycerides， high-density lipoprotein， urea nitrogen， apolipoprotein A and creatinine levels between the two groups （P<0.05）. The differences in the correct number of household appliances， animals， fruits， vegetables， names starting with "water" and "self" in VFT between the two groups were statistically significant （P<0.05）. The differences in point reaction time， character reaction time and character color reaction time in SCWT between the two groups were statistically significant （P<0.05）. Correlation analysis showed that except for creatinine levels， the levels of IL-4 and IL-5 in patients with schizophrenia were correlated with other indicators （P<0.05）. IL-7 levels were correlated with creatinine levels， household appliances， animals， fruits， correct number of names starting with "water" in VFT， point reaction time and word reaction time in SCWT （P<0.05）. IL-8 levels were correlated with triglyceride levels， household appliances， animals， fruits， vegetables， correct number of names starting with "water" and "self" in VFT and word reaction time in SCWT （P<0.05）. Except for creatinine levels and the correct number of names starting with "self"， IL-10 levels were correlated with all other indicators （P<0.05）. Except for creatinine and urea nitrogen levels， IL-13 levels were correlated with other indicators （P<0.05）. ConclusionThe levels of inflammatory factors in patients with schizophrenia may be related to their metabolic levels， language fluency and information processing function. ［Funded by Anhui Province Key Research and Development Plan Project （number， 2022e07020002）］