Identification of cell surface markers for acute myeloid leukemia prognosis based on multi-model analysis

Given the extremely high inter-patient heterogeneity of acute myeloid leukemia(AML),the identification of biomarkers for prognostic assessment and therapeutic guidance is critical.Cell surface markers(CSMs)have been shown to play an important role in AML leukemogenesis and progression.In the current study,we evaluated the prognostic potential of all human CSMs in 130 AML patients from The Cancer Genome Atlas(TCGA)based on differential gene expression analysis and univariable Cox proportional hazards regression analysis.By using multi-model analysis,including Adaptive LASSO regression,LASSO regression,and Elastic Net,we constructed a 9-CSMs prognostic model for risk stratification of the AML patients.The predictive value of the 9-CSMs risk score was further validated at the transcriptome and proteome levels.Multivariable Cox regression analysis showed that the risk score was an independent prognostic factor for the AML patients.The AML patients with high 9-CSMs risk scores had a shorter overall and event-free survival time than those with low scores.Notably,single-cell RNA-sequencing analysis indicated that patients with high 9-CSMs risk scores exhibited chemotherapy resistance.Furthermore,PI3K inhibitors were identified as potential treatments for these high-risk patients.In conclusion,we constructed a 9-CSMs prognostic model that served as an independent prognostic factor for the survival of AML patients and held the potential for guiding drug therapy.

Correlation knowledge extraction based on data mining for distribution network planning

Traditional distribution network planning relies on the professional knowledge of planners,especially when analyzing the correlations between the problems existing in the network and the crucial influencing factors.The inherent laws reflected by the historical data of the distribution network are ignored,which affects the objectivity of the planning scheme.In this study,to improve the efficiency and accuracy of distribution network planning,the characteristics of distribution network data were extracted using a data-mining technique,and correlation knowledge of existing problems in the network was obtained.A data-mining model based on correlation rules was established.The inputs of the model were the electrical characteristic indices screened using the gray correlation method.The Apriori algorithm was used to extract correlation knowledge from the operational data of the distribution network and obtain strong correlation rules.Degree of promotion and chi-square tests were used to verify the rationality of the strong correlation rules of the model output.In this study,the correlation relationship between heavy load or overload problems of distribution network feeders in different regions and related characteristic indices was determined,and the confidence of the correlation rules was obtained.These results can provide an effective basis for the formulation of a distribution network planning scheme.

Evolution-driven crosstalk between glioblastoma and the tumor microenvironment

Glioblastoma(GBM)is a malignant adult brain tumor for which 90%of patients experience recurrence within a year after surgery1.Evolution confers treatment resistance capabilities on tumors2.The diversification of malignant and non-malignant(i.e.,stromal and immune cell)compartments in the tumor microenvironment(TME)during tumor evolution3-7 eventually results in the formation of a complex interaction network that promotes tumor progression.

Jupyter交互式平台在结构化学教学中的应用——以“单电子原子薛定谔方程”为例

以“单电子原子薛定谔方程”为例介绍了综合理论演示、科学符号推导和数据可视化多种功能的开源Web平台Jupyter在结构化学教学中的应用。借助于多样Python程序库学生能够交互式地学习理论概念、推导数学公式和理解波函数性质,可增强结构化学教学过程的参与度和互动性,也培养学生运用编程解决科学问题的能力。

“三维四合”进阶式分析化学全课堂教学改革与探索

以培养创新型人才为目标,分析化学课程构建了以学生为中心、问题为导向的“三维四合”进阶式全课堂创新模式。将“线下课堂、网络平台和课外活动”三个维度有机结合,构建“整合教学内容、融合思政育人、联合教学模式、结合过程评价”的教学创新体系,增强学生学习的独立性和自主性,激活学生的创新能力和科研素养。

Age-related changes in prevalence and symptom characteristics in kidney deficiency syndrome with varied health status:a cross-sectional observational study

Objective:This study aimed to reveal the age-related changes in prevalence and symptom characteristics in kidney deficiency syndrome(KDS)with varied health status.Methods:This cross-sectional observational study was conducted in6 hospitals.Investigators queried participants aged 20e79 about their health,including symptoms if any,and completed questionnaires to collect participants responses.Prevalence,severity,and frequency of KDS and other relevant parameters were observed and recorded.Comparative analysis of countable variables,including prevalence,was performed by frequency analysis and c2 test and expressed as a composite ratio.Comparative analysis of quantitative scores of the severity and frequency of symptoms was performed by the rank-sum test.Regression analysis of the correlation of KDS with potential contributing factors was performed by non-conditional binary logistic stepwise regression of numerical variables.Results:Prevalence of KDS in healthy and unhealthy participants correlated with increasing age(P<0.05).In those with chronic disease,KDS prevalence was comparatively high,but the trend was not obvious.KDS prevalence in participants age 20e39 showed an increasing trend with deteriorating health(P<0.05).Compared to healthy individuals,KDS prevalence in subhealthy persons and those with chronic disease showed an increasing trend(P<0.05)in the 40e59 and 60e79 age groups,whereas there was no difference between subhealthy persons and those with chronic disease age 40e59 and 60e79.Symptom severity scores of KDS showed an increasing trend with increasing age and deteriorating health status(P<0.05).Higher symptom frequency scores were also positively correlated with increasing age(P<0.05),but health status deterioration was not significantly correlated(P>0.05).Age,health status,lower back pain,shin soreness or heel pain,tinnitus or deafness,hair loss or loose teeth,incomplete bladder emptying or incontinence,and sexual dysfunction or infertility were potential factors contributing to KDS(P<0.05),but age was the only independent variable for which OR>1.Moreover,the distribution of typical KDS-related symptoms showed dramatic regularities.Conclusion:Prevalence and symptom characteristics of KDS were found to increase consistently with increasing age and deteriorating health status.Kidney deficiency may be an important mechanism of aging in the subhealthy and chronic disease states.

纳米孔生物分子检测研究

纳米孔单分子检测技术是一种集操作简单、灵敏度高、检测速度快、无需标记等优点的传感检测技术,广泛应用于蛋白质检测、基因测序和标志物检测等领域。基因测序的费用、灵敏度和精度是该检测技术的发展中亟待解决的主要问题,而开发新型的纳米孔材料则是解决这些问题的关键手段。本文从纳米孔材料的选择和设计角度出发,综述了三种不同的纳米孔,即蛋白质等生物纳米孔、固态纳米孔和新型二维材料纳米孔在生物分子检测方面的应用现状,并比较了生物纳米孔与固态纳米孔的差别。本文也重点阐述了二维材料纳米孔在生物分子检测中的实验和模拟研究进展。最后,对纳米孔检测技术的发展前景进行了展望。