Calculation of the Biological Efficiency of the Proton Component from 14.8 MeV Neutron Irradiation in Computational Biology with Help of Video Cards

Bulletin of Experimental Biology and Medicine - Fast neutron therapy, which previously has demonstrated effective results, but along with a large number of complications, can again be considered a...     

护士"互联网+护理服务"参与行为意愿量表的编制及信效度检验

目的编制护士"互联网+护理服务"参与行为意愿量表,并进行信效度检验。方法以计划行为理论为框架,采用文献回顾、半结构式访谈法形成量表的条目池;通过专家咨询、项目分析对量表条目进行筛选,初步形成护士"互联网+护理服务"参与行为意愿量表。采用方便抽样法,于2020年10—12月选取江苏省6所医院(2所三级医院、2所二级医院、2所一级医院)的825名护士进行正式调查,检验问卷的信效度。结果护士"互联网+护理服务"参与行为意愿量表包括3个分量表(参与行为态度、主观行为规范、感知行为控制)、8个维度、17个条目。总量表的Cronbach'sα系数为0.927、重测信度系数为0.805。护士"互联网+护理服务"参与行为意愿与参与行为的相关系数为0.743(P<0.01)。因子分析提取出8个公因子,累积方差贡献率为72.33%。结论护士"互联网+护理服务"参与行为意愿量表具有较好的信效度,可用于护士"互联网+护理服务"参与行为意愿的评估。     

定量分析对常规超声联合超声造影定性误诊甲状腺结节的诊断价值

摘要：目的：探讨超声造影（CEUS）定量分析对常规超声联合CEUS定性诊断误诊为恶性的甲状腺结节与甲状腺乳头状癌的鉴别诊断价值。方法：选取2018年7月至2021年11月在我院超声科行甲状腺常规超声及CEUS检查，术前联合超声诊断为恶性（C-TIRADS≥4b 或 CEUS 表现为低增强和快速消退任一征像）而病理为良性的35位患者共35个结节为研究组；选择同期联合超声诊断与病理一致的甲状腺乳头状癌患者47例做为对照组。分析常规超声及CEUS特征，并将结节整体、中央部、边缘部及邻近正常甲状腺实质作为感兴趣区分别绘制时间-强度曲线（TIC）进行定量分析，比较两组结节各定量参数之间的差异。结果：研究组整体相对上升时间（△RT）以0.45为截断值，诊断恶性结节的敏感度为97.9%，特异度为85.7%，受试者工作（ROC）曲线下面积为0.96；研究组中央区△RT以0.55为截断值，诊断恶性结节的敏感度为95.7%，特异度为82.9%，ROC曲线下面积为0.87；研究组边缘区△RT以0.25为截断值，诊断恶性结节的敏感度为89.4%，特异度为77.1%，ROC曲线下面积为0.89。结论：CEUS定量分析在常规超声联合CEUS定性误诊甲状腺结节的诊断中具有一定的鉴别诊断价值。     

The association between income inequality and adult mental health at the subnational level—a systematic review

Purpose

A systematic review was undertaken to determine whether research supports: (i) an association between income inequality and adult mental health when measured at the subnational level, and if so, (ii) in a way that supports the Income Inequality Hypothesis (i.e. between higher inequality and poorer mental health) or the Mixed Neighbourhood Hypothesis (higher inequality and better mental health).

Methods

Systematic searches of PsycINFO, Medline and Web of Science databases were undertaken from database inception to September 2020. Included studies appeared in English-language, peer-reviewed journals and incorporated measure/s of objective income inequality and adult mental illness. Papers were excluded if they focused on highly specialised population samples. Study quality was assessed using a custom-developed tool and data synthesised using the vote-count method.

Results

Forty-two studies met criteria for inclusion representing nearly eight million participants and more than 110,000 geographical units. Of these, 54.76% supported the Income Inequality Hypothesis and 11.9% supported the Mixed Neighbourhood Hypothesis. This held for highest quality studies and after controlling for absolute deprivation. The results were consistent across mental health conditions, size of geographical units, and held for low/middle and high income countries.

Conclusions

A number of limitations in the literature were identified, including a lack of appropriate (multi-level) analyses and modelling of relevant confounders (deprivation) in many studies. Nonetheless, the findings suggest that area-level income inequality is associated with poorer mental health, and provides support for the introduction of social, economic and public health policies that ameliorate the deleterious effects of income inequality.

Clinical registration number

PROSPERO 2020 CRD42020181507.

     

Arterial spin labeling MR image denoising and reconstruction using unsupervised deep learning

Arterial spin labeling (ASL) imaging is a powerful magnetic resonance imaging technique that allows to quantitatively measure blood perfusion non-invasively, which has great potential for assessing tissue viability in various clinical settings. However, the clinical applications of ASL are currently limited by its low signal-to-noise ratio (SNR), limited spatial resolution, and long imaging time. In this work, we propose an unsupervised deep learning-based image denoising and reconstruction framework to improve the SNR and accelerate the imaging speed of high resolution ASL imaging. The unique feature of the proposed framework is that it does not require any prior training pairs but only the subject's own anatomical prior, such as T1-weighted images, as network input. The neural network was trained from scratch in the denoising or reconstruction process, with noisy images or sparely sampled k-space data as training labels. Performance of the proposed method was evaluated using in vivo experiment data obtained from 3 healthy subjects on a 3T MR scanner, using ASL images acquired with 44-min acquisition time as the ground truth. Both qualitative and quantitative analyses demonstrate the superior performance of the proposed txtc framework over the reference methods. In summary, our proposed unsupervised deep learning-based denoising and reconstruction framework can improve the image quality and accelerate the imaging speed of ASL imaging.     

Analysis of the correlation between P27 expression and Helicobacter pylori infection in gastric cancer

We aimed to explore the correlation between P27 expression and Helicobacter pylori (H. pylori) infection in gastric cancer, so as to provide evidence for understanding the pathogenesis of gastric cancer caused by H. pylori infection. A total of 82 samples of gastric cancer tissues and 56 samples of tumor-adjacent normal tissues collected from the gastrectomy were enrolled in this study. Then, 14C-urease breathing test was carried out to evaluate the infection of H. pylori in gastric cancer tissues, the expression of P27 in the tissue samples was detected by the immunohistochemistry staining, and the correlation between the H. pylori infection and P27 expression in gastric cancer was analyzed. Of 82 gastric cancer patients, there were 53 patients with H. pylori infection (64.63%). Among the patients with highly or moderately differentiated gastric cancer, the expression of P27 was much higher than that of patients with poorly differentiated gastric cancer (p < 0.01). Besides, comparison of the P27 expression between males and females, among different age groups, tumor sizes, TNM stages, tumor infiltration degrees, or lymph node metastasis, showed no significant differences (p > 0.05). Analysis of the correlation revealed that P27 expression was negatively correlated with the infection of H. pylori (p < 0.01). Multifactorial logistics regression analysis indicated that tumor differentiation was a risk factor of P27-positive expression in gastric cancer tissues (p < 0.01). In addition, P27 expression in the gastric cancer tissues was lower than that in the tumor-adjacent normal tissues (p < 0.01). In gastric cancer patients, expression of P27 is correlated with H. pylori infection which, via downregulating P27, can cause the cancerization of gastric mucosa, and P27, for its role in the development and progression of gastric cancer, is a potential auxiliary indicator for clinical diagnosis whether gastric cancer is complicated with H. pylori infection. So, P27 is a key indicator for diagnosis, treatment, and prognostic evaluation of disease in the advanced stage.