Search

The issues of environment and health caused by emerging contaminants have become a worldwide focus. The sewage discharged from medical institutions is one of the important sources of emerging contaminants in the environment. During the current period of normalization of key infectious disease prevention and control, the concentration of emerging contaminants in medical wastewater has significantly increased, along with an increase of potential hazards to aquatic ecology. In response to such phenomena, the category and concentration of antibiotics,endocrine disrupting chemicals, and potential emerging contaminants in medical wastewater were discussed. The fate, removal rate, and contribution of emerging contaminants in medical wastewater to the environment was explored. Further the single compound toxicity and comprehensive toxicity of emerging contaminants in medical wastewater was elaborated. Finally, the current sewage discharge standards for medical institutions in China failure to control emerging contaminants was point out, the traditional sewage treatment processes were hard to effectively remove of emerging contaminants. Therefore, it was imperative to develop advanced techniques for standardized and tertiary treatment of medical wastewater.

Objective: To construct an artificial intelligence prediction model to predict the selectivity of fluorescent probes for Hg2+ in a complex food testing environment in the presence of Cu2+ interference. Methods: Fluorescent probe technology combined with seven advanced classical machine learning models was used to predict and analyze the selectivity of the probe for Hg2+ in the presence of Cu2+ interference, and to compare the prediction effect of each model and select the optimal model. Results: Efficient models with accuracies of 0.786 and 0.810 in the cross-validation and test sets were successfully established based on Molecular 2D Descriptors （Mol2D） and extreme gradient boosting algorithms to accurately predict the probe selectivity of Hg2+ under Cu2+ interference. Conclusion: The model is improved for the design of Hg2+ fluorescent molecular probes by selective prediction, which makes the design of Hg2+ fluorescent probes more efficient and reliable.

Objective To evaluate the prognostic value of early blood inflammatory indicators in patients with respiratory failure caused by severe community-acquired pneumonia. Methods A total of 186 patients diagnosed with respiratory failure due to severe pneumonia on admission were recruited in this study. According to clinical prognosis， they were divided into the death group （n = 42） and improvement group （n = 144）. Twelve cytokines， ferritin， C-reactive protein， procalcitonin， blood routine examination and blood gas analysis results of the patients within two days after admission were analyzed. Pneumonia severity index （PSI） and APACHE Ⅱ scores of the patients were collected. The correlation between the above indicators and prognosis was explored. Results Compared with the improvement group， the levels of IFN-γ， IL-10， IL-6， IL-8， C-reactive protein （CRP）， procalcitonin and ferritin were significantly higher in the death group （all P < 0.05）. Upon admission， the hemoglobin level and platelet count in the death group were significantly lower than those in the improvement group （both P < 0.05）. The PSI and APACHE Ⅱ scores on admission in the death group were significantly higher compared with those in the improvement group （both P < 0.05）. Patients in the death group had higher lactic acid level and lower oxygenation index （OI） compared with their counterparts in the improvement group （both P < 0.05）. Multivariate Logistic regression analysis revealed that IL-6， ferritin， PSI and APACHE Ⅱ scores and lactic acid level were the risk factors for poor prognosis， whereas platelet count was the protective factor for poor prognosis （all P < 0.05）. The receiver operating characteristic （ROC） curve indicated that IL-6，procalcitonin and ferritin were favorable predictors for clinical prognosis of patients. When IL-6 and ferritin levels exceed 11.41 ng/L and 659 μg/L， and platelet count was less than 148.5×109/L， patients were at risk of death. Conclusions In patients with respiratory failure caused by severe community-acquired pneumonia， the increase of blood inflammatory indicators， such as IL-6， ferritin and procalcitonin， suggests high risk death in patients， especially for patients with IL-6 >11.41 ng/L， ferritin>659 μg/L， and platelet count9/L. Extensive attention should be paid to lowering the risk of death in these patients.

BackgroundEvidence from anatomical, pharmacological, and genetic studies supports a role for the neuropeptide melanin concentrating hormone system in modulating emotional and cognitive functions. Genome-wide association studies revealed a potential association between the melanin concentrating hormone receptor (MCHR1) gene locus and schizophrenia, and the largest genome-wide association study conducted to date shows a credible genome-wide association.MethodsWe analyzed MCHR1 and pro-melanin concentrating hormone RNA-Seq expression in the prefrontal cortex in schizophrenia patients and healthy controls. Disruptions in the melanin concentrating hormone system were modeled in the mouse brain by germline deletion of MCHR1 and by conditional ablation of melanin concentrating hormone expressing neurons using a Cre-inducible diphtheria toxin system.ResultsMCHR1 expression is decreased in the prefrontal cortex of schizophrenia samples (false discovery rate (FDR) P