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1.
Zhonghua Yi Xue Yi Chuan Xue Za Zhi ; 39(9): 1005-1010, 2022 Sep 10.
Artigo em Chinês | MEDLINE | ID: mdl-36082575

RESUMO

OBJECTIVE: To report on a case of Smith-Magenis syndrome (SMS) due to a rare small-scale deletion. METHODS: Muscle samples from the the third fetus was collected after the in Medical history and clinical data of the patient were collected. The child and his parents were subjected to chromosome karyotyping analysis, multiplex ligation-dependent probe amplification (MLPA) and copy number variation sequencing (CNV-seq). RESULTS: The child was found to have a normal karyotype. MLPA and CNV-seq detection showed that he has harbored a 1.22 Mb deletion and a 0.3 Mb duplication in the 17p11.2 region. Neither of his parents was found to have similar deletion or duplication. CONCLUSION: The child was diagnosed with SMS due to a rare 1.22 Mb deletion in the 17p11.2 region, which is among the smallest deletions associated with this syndrome.


Assuntos
Anormalidades Múltiplas , Deficiência Intelectual , Síndrome de Smith-Magenis , Anormalidades Múltiplas/genética , Criança , Deleção Cromossômica , Cromossomos Humanos Par 17 , Variações do Número de Cópias de DNA , Humanos , Deficiência Intelectual/genética , Masculino , Síndrome de Smith-Magenis/diagnóstico , Síndrome de Smith-Magenis/genética
2.
Huan Jing Ke Xue ; 43(6): 2840-2850, 2022 Jun 08.
Artigo em Chinês | MEDLINE | ID: mdl-35686753

RESUMO

The COVID-19 lockdown was a typical occurrence of extreme emission reduction, which presented an opportunity to study the influence of control measures on particulate matter. Observations were conducted from January 16 to 31, 2020 using online observation instruments to investigate the characteristics of PM2.5 concentration, particle size distribution, chemical composition, source, and transport before (January 16-23, 2020) and during (January 24-31, 2020) the COVID-19 lockdown in Zhengzhou. The results showed that the atmospheric PM2.5 concentration decreased by 4.8% during the control period compared with that before the control in Zhengzhou. The particle size distribution characteristics indicated that there was a significant decrease in the mass concentration and number concentration of particles in the size range of 0.06 to 1.6 µm during the control period. The chemical composition characteristics of PM2.5 showed that secondary inorganic ions (sulfate, nitrate, and ammonium) were the dominant component of PM2.5, and the significant increase in PM2.5 was mainly owing to the decrease in NO3- concentration during the control period. The main sources of PM2.5 identified by the positive matrix factorization (PMF) model were secondary sources, combustion sources, vehicle sources, industrial sources, and dust sources. The emissions from vehicle sources, industrial sources, and dust sources decreased significantly during the control period. The results of analyses using the backward trajectory method and potential source contribution factor method indicated that the effects of transport from surrounding areas on PM2.5 concentration decreased during the control period. In summary, vehicle and industrial sources should be continuously controlled, and regional combined prevention and control should be strengthened in the future in Zhengzhou.


Assuntos
Poluentes Atmosféricos , COVID-19 , Poluentes Atmosféricos/análise , COVID-19/epidemiologia , COVID-19/prevenção & controle , China , Controle de Doenças Transmissíveis , Poeira/análise , Monitoramento Ambiental/métodos , Humanos , Tamanho da Partícula , Material Particulado/análise , Emissões de Veículos/análise
3.
Environ Sci Pollut Res Int ; 29(20): 30410-30426, 2022 Apr.
Artigo em Inglês | MEDLINE | ID: mdl-35000159

RESUMO

Industrial parks have made important contributions to China's economic development, but they have caused serious pollution to the environment. With the promotion of China's sustainable development, improving the eco-efficiency of industrial parks has gradually become the focus of attention. In this study, a slack-based data envelopment analysis (SBM-DEA) model, which included three input indicators and six output indicators, was applied to assess the eco-efficiencies of 18 industrial parks in Central China. The ecological development level of different industrial parks in Central China was uneven, and their efficiency scores ranged from 0.06 to 1. Next, the most sensitive input and output variables are identified by sensitivity analysis, and it is concluded that land and water consumption will have a significant impact on the evaluation results of the model. Then, the influencing factors of eco-efficiency are discussed, and it was found that a reasonable energy structure and industrial structure, as well as high industrial added value, would increase the eco-efficiency of industrial parks. Finally, based on the findings, policy recommendations for improving the eco-efficiency of industrial parks are put forward, including fulfilling government responsibilities, adjusting energy and industrial structures, and improving the high-quality development of the parks.


Assuntos
Desenvolvimento Econômico , Indústrias , China , Eficiência , Poluição Ambiental
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