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Multiple gene-deletion vaccinia virus Tiantan strain against mpox.

Virol J

January 2025

Changchun Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Changchun, 130122, People's Republic of China.

Monkeypox virus (MPXV) is an important zoonotic pathogenic virus, which poses serious threats to public health. MPXV infection can be prevented by immunization against the variola virus. Because of the safety risks and side effects of vaccination with live vaccinia virus (VACV) strain Tian Tan (VTT), we constructed two gene-deleted VTT recombinants (TTVAC7 and TTVC5).

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Background: Gestational diabetes mellitus is hyperglycemia in special populations (pregnant women), however gestational diabetes mellitus (GDM) not only affects maternal health, but also has profound effects on offspring health. The prevalence of gestational diabetes in my country is gradually increasing.

Objective: To study the application effect of self-transcendence nursing model in GDM patients.

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Background: Triglyceride-glucose (TyG) index was regarded as a cost-efficient and reliable clinical surrogate marker for insulin resistance (IR), which was significantly correlated with cardiovascular disease (CVD). However, the TyG index and incident CVD in non-diabetic hypertension patients remains uncertain. The aim of study was to explore the impact of TyG index level and variability on risk of CVD among non-diabetic hypertension patients.

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The complex topography of the mountain cities leads to uneven distribution of land resources. Currently, available studies mainly focuse on land use and landscape patterns (LU and LP) in plains or plateaus. Thus, it is necessary to carry out an analysis of the drivers of changes in LU and LP in mountain cities.

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An automatic cervical cell classification model based on improved DenseNet121.

Sci Rep

January 2025

Department of Biomedical Engineering, School of Life Science and Technology, Changchun University of Science and Technology, Changchun, 130022, China.

The cervical cell classification technique can determine the degree of cellular abnormality and pathological condition, which can help doctors to detect the risk of cervical cancer at an early stage and improve the cure and survival rates of cervical cancer patients. Addressing the issue of low accuracy in cervical cell classification, a deep convolutional neural network A2SDNet121 is proposed. A2SDNet121 takes DenseNet121 as the backbone network.

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