Development and validation of a circulating tumor DNA-based optimization-prediction model for short-term postoperative recurrence of endometrial cancer

BACKGROUND Endometrial cancer(EC)is a common gynecological malignancy that typically requires prompt surgical intervention;however,the advantage of surgical management is limited by the high postoperative recurrence rates and adverse outcomes.Previous studies have highlighted the prognostic potential of circulating tumor DNA(ctDNA)monitoring for minimal residual disease in patients with EC.AIM To develop and validate an optimized ctDNA-based model for predicting shortterm postoperative EC recurrence.METHODS We retrospectively analyzed 294 EC patients treated surgically from 2015-2019 to devise a short-term recurrence prediction model,which was validated on 143 EC patients operated between 2020 and 2021.Prognostic factors were identified using univariate Cox,Lasso,and multivariate Cox regressions.A nomogram was created to predict the 1,1.5,and 2-year recurrence-free survival(RFS).Model performance was assessed via receiver operating characteristic(ROC),calibration,and decision curve analyses(DCA),leading to a recurrence risk stratification system.RESULTS Based on the regression analysis and the nomogram created,patients with postoperative ctDNA-negativity,postoperative carcinoembryonic antigen 125(CA125)levels of<19 U/mL,and grade G1 tumors had improved RFS after surgery.The nomogram’s efficacy for recurrence prediction was confirmed through ROC analysis,calibration curves,and DCA methods,highlighting its high accuracy and clinical utility.Furthermore,using the nomogram,the patients were successfully classified into three risk subgroups.CONCLUSION The nomogram accurately predicted RFS after EC surgery at 1,1.5,and 2 years.This model will help clinicians personalize treatments,stratify risks,and enhance clinical outcomes for patients with EC.

基于中医证候与精液质量相关参数构建精子DNA碎片预测模型与验证

背景:中医证候与精液质量相关参数相结合,共同预测精子DNA碎片指数(DNA fragmentation index,DFI)异常增高的发生并绘制列线图,能显著提高临床的实操性与应用效能,为临床全面评估精液质量,采取积极干预措施以改善临床结局及制定个体化医疗方案提供依据。目的:探讨基于中医证候与精液质量相关参数构建精子DNA碎片的预测模型与验证。方法:回顾性分析2019年7月至2021年7月在广西壮族自治区南溪山医院中医男科接受中医证候诊断及精子DNA碎片率检查的不育患者共420例,据《人类精液检查与处理实验室手册》(第6版),将其中137例精子DFI>30%患者纳入精子DFI异常增高组,将283例精子DFI≤30%作为对照组;首先采用单因素分析筛选精子DFI异常增高的影响因素,然后采用套索算法(LASSO)校正因子共线性问题并筛选出最佳匹配因子后,将其纳入多因素向前逐步Logistic回归找出其独立影响因素并绘制列线图,最后采用受试者工作曲线、校准曲线、临床决策曲线、临床影响曲线对该预测模型进行区分度与准确度及临床应用效能验证。结果与结论:①单因素分析结果显示,年龄、体质量指数、前向运动率、精子总活率、精子浓度、精子形态学、肾阳虚衰证、湿热下注证、肾精不足证为引发精子DFI异常增高的影响因子(P<0.05);②通过LASSO回归进一步筛选出的最佳匹配因素为年龄、体质量指数、精子总活率、精子浓度、精子形态学、肾阳虚衰证、湿热下注证、肾精不足证(P<0.05);③多因素向前逐步Logistic回归结果显示年龄、体质量指数、精子浓度、精子总活率、湿热下注证、肾阳虚衰证共6项为引发精子DFI异常增高的独立影响因素;④受试者工作曲线显示,模型组曲线下面积为0.760(0.713,0.806),验证组曲线下面积为0.745(0.714,0.776),说明该预测模型具有较好的区分度;⑤校准曲线平均绝对误差0.040,Hosmer-Lemeshow检验P>0.05,表明该模型预测发生精子DFI异常增高的概率与实际发生精子DFI异常增高的概率无显著统计学差异,证实该模型具有较好的准确度;⑥临床决策曲线与临床影响曲线显示,模型组与验证组分别在阈概率值为0.08-0.84与0.09-0.78时具有临床最大净获益,且在该阈概率范围内具有较好的临床应用效能;⑦结果表明,年龄、体质量指数、精子浓度、精子总活率、湿热下注证、肾阳虚衰证为引发精子DFI异常增高的独立影响因素,通过其构建的临床预测模型列线图具有较好的临床预测价值与临床应用效能,可为临床全面评估精液质量、预后与干预及个体化医疗服务提供依据。

FABRICATION OF SELF-ASSEMBLY DNA-C_(60) MULTILAYER FILMS

Electrostatic layer-by-layer self-assembly multilayer films were successfully fabricated from C-60-ethylenediamine adduct (C-60-EDA) and DNA. Under visible light irradiation, DNA is ready to be cleaved and the films are destroyed.

Prognostic values of the integrated model incorporating the volume of metastatic regional cervical lymph node and pretreatment serum Epstein-Barr virus DNA copy number in predicting distant metastasis in patients with N1 nasopharyngeal carcinoma

Background: According to the 7 th edition of the American Joint Committee on Cancer(AJCC) staging system, over50% of patients with nasopharyngeal carcinoma(NPC) have N1 disease at initial diagnosis. However, patients with N1 NPC are relatively under-researched, and the metastasis risk of this group is not well-stratified. This study aimed to evaluate the prognostic values of gross tumor volume of metastatic regional lymph node(GTVnd) and pretreatment serum copy number of Epstein-Barr virus(EBV) DNA in predicting distant metastasis of patients with N1 NPC, and to develop an integrated prognostic model that incorporates GTVnd and EBV DNA copy number for this group of patients.Methods: The medical records of 787 newly diagnosed patients with nonmetastatic, histologically proven N1 NPC who were treated at Sun Yat-sen University Cancer Center between November 2009 and February 2012 were analyzed. Computed tomography-derived GTVnd was measured using the summation-of-area technique. Blood samples were collected before treatment to quantify plasma EBV DNA. The receiver operating characteristic(ROC) curve analysis was used to evaluate the cut-off point for GTVnd, and the area under the ROC curve was used to assess the predicted validity of GTVnd. The survival rates were assessed by Kaplan-Meier analysis, and the survival curves were compared using a log-rank test. Multivariate analysis was conducted using the Cox proportional hazard regression model.Results: The 5-year distant metastasis-free survival(DMFS) rates for patients with GTVnd > 18.9 vs.≤ 18.9 mL were82.2% vs. 93.2%(P < 0.001), and for patients with EBV DNA copy number > 4000 vs. < 4000 copies/mL were 83.5% vs.93.9%(P < 0.001). After adjusting for GTVnd, EBV DNA copy number, and T category in the Cox regression model, both GTVnd > 18.9 mL and EBV DNA copy number > 4000 copies/mL were significantly associated with poor prognosis(both P < 0.05). According to combination of GTVnd and EBV DNA copy number, all patients were divided into low-,moderate-, and high-risk groups, with the 5-year DMFS rates of 96.1,87.4, and 73.8%, respectively(P < 0.001). Multivariate analysis confirmed the prognostic value of this model for distant metastatic risk stratification(hazard ratio [HR],4.17; 95% confidence interval [CI] 2.34-7.59; P < 0.001).Conclusions: GTVnd and serum EBV DNA copy number are independent prognostic factors for predicting distant metastasis in NPC patients with N1 disease. The prognostic model incorporating GTVnd and EBV DNA copy number may improve metastatic risk stratification for this group of patients.

Chaos game representation(CGR)-walk model for DNA sequences

Chaos game representation （CGR） is an iterative mapping technique that processes sequences of units, such as nucleotides in a DNA sequence or amino acids in a protein, in order to determine the coordinates of their positions in a continuous space. This distribution of positions has two features： one is unique, and the other is source sequence that can be recovered from the coordinates so that the distance between positions may serve as a measure of similarity between the corresponding sequences. A CGR-walk model is proposed based on CGR coordinates for the DNA sequences. The CGR coordinates are converted into a time series, and a long-memory ARFIMA （p, d, q） model, where ARFIMA stands for autoregressive fractionally integrated moving average, is introduced into the DNA sequence analysis. This model is applied to simulating real CGR-walk sequence data of ten genomic sequences. Remarkably long-range correlations are uncovered in the data, and the results from these models are reasonably fitted with those from the ARFIMA （p, d, q） model.

Extended Holstein polaron model for charge transfer in dry DNA

The variational method is applied to the study of charge transfer in dry DNA by using an extended Holstein small polaron model in two cases： the site-dependent flnite-chain discrete case and the site-independent continuous one. The treatments in the two cases are proven to be consistent in theory and calculation. Discrete and continuous treatments of Holstein model both can yield a nonlinear equation to describe the charge migration in an actual long-range DNA chain. Our theoretical results of binding energy Eb, probability amplitude of charge carrier Ф and the relation between energy and charge-lattice coupling strength are in accordance with the available experimental results and recent theoretical calculations.

A mathematical model of a P53 oscillation network triggered by DNA damage

Taking the interaction between a DNA damage repair module, an ATM module, and a P53--MDM2 oscillation module into account, this paper presents a mathematical model of a P53 oscillation network triggered by a DNA damage signal in individual cells. The effects of the DNA damage signal and the delay time of P53-induced MDM2 expression on the behaviours of the P53 oscillation network are studied. In the oscillatory state of the P53--MDM2 oscillator, it is found that the pulse number of P53--P oscillation increases with the increase of the initial DNA damage signal, whereas the amplitude and the period of P53--P oscillation are fixed for different initial DNA damage signals, and the period numbers of P53--P oscillations decrease with the increase of time delay of MDM2 expression induced by P53. These theoretical predictions are consistent with previous experimental results. The combined negative feedback of P53--MDM2 with the time delay of P53-induced MDM2 expression causes oscillation behaviour in the P53 network.

Compressed wormlike chain moving out of confined space: A model of DNA ejection from bacteriophage

The molecular biomechanics of DNA ejection from bacteriophage is of interest to not only fundamental biological understandings but also practical applications such as the design of advanced site-specific and controllable drug delivery systems. In this paper, we analyze the viscous motion of a semiflexible polymer chain coming out of a strongly confined space as a model to investigate the effects of various structure confinements and frictional resistances encountered during the DNA ejection process. The theoretically predicted relations between the ejection speed, ejection time, ejection length, and other physical parameters, such as the phage type, total genome length and ionic state of external buffer solutions, show excellent agreement with in vitro experimental observations in the literature.

Galantamine protects against beta amyloid peptide-induced DNA damage in a model for Alzheimer's disease

Alzheimer’s disease（AD）is the most common type of dementia in elderly population.With a growing aging population not only in the United States but also in the worldwide,AD constitutes an emergent public health problem.

An Efficient Multi-Scale Modelling Approach for ssDNA Motion in Fluid Flow

The paper presents a multi-scale modelling approach for simulating macromolecules in fluid flows. Macromolecule transport at low number densities is frequently encountered in biomedical devices, such as separators, detection and analysis systems. Accurate modelling of this process is challenging due to the wide range of physical scales involved. The continuum approach is not valid for low solute concentrations, but the large timescales of the fluid flow make purely molecular simulations prohibitively expensive. A promising multi-scale modelling strategy is provided by the meta-modelling approach considered in this paper. Meta-models are based on the coupled solution of fluid flow equations and equations of motion for a simplified mechanical model of macromolecules. The approach enables simulation of individual macromolecules at macroscopic time scales. Meta-models often rely on particle-corrector algorithms, which impose length constraints on the mechanical model. Lack of robustness of the particle-corrector algorithm employed can lead to slow convergence and numerical instability. A new FAst Linear COrrector （FALCO） algorithm is introduced in this paper, which significantly improves computational efficiency in comparison with the widely used SHAKE algorithm. Validation of the new particle corrector against a simple analytic solution is performed and improved convergence is demonstrated for ssDNA motion in a lid-driven micro-cavity.

Mathematical Modeling of a Metabolic Network to Study the Impact of Food Contaminants on Genomic Methylation and DNA Instability

Environmental contamination of food is a worldwide public health problem. Folate mediated one- carbon metabolism plays an important role in epigenetic regulation of gene expression and mutagenesis. Many contaminants in food cause cancer through epigenetic mechanisms and/or DNA instability i.e. default methylation of uracil to thymine, subsequent to the decrease of 5-methylte- trahydrofolate (5 mTHF) pool in the one-carbon metabolism network. Evaluating consequences of an exposure to food contaminants based on systems biology approaches is a promising alternative field of investigation. This report presents a dynamic mathematical modeling for the study of the alteration in the one-carbon metabolism network by environmental factors. It provides a model for predicting “the impact of arbitrary contaminants that can induce the 5 mTHF deficiency. The model allows for a given experimental condition, the analysis of DNA methylation activity and dumping methylation in the de novo pathway of DNA synthesis.

Temperature Induces Self-assembly of Silicon Nano/Micro-structure based on Multi-physics Approach

A three-dimensional dynamic model for nano/micro-fabrications of silicon was presented. With the developed model, the fabrication process of silicon on nothing（SON） structure was quantitatively investigated. We employ a diffuse interface model that incorporates the mechanism of surface diffusion. The mechanism of the fabrication is systematically integrated for high reliability of computational analysis. A semi-implicit Fourier spectral scheme is applied for high efficiency and numerical stability. Moreover, the theoretical analysis provides the guidance that is ordered by the fundamental geometrical design parameters to guide different fabrications of SON structures. The performed simulations suggest a substantial potential of the presented model for a reliable design technology of nano/micro-fabrications.

Molecular modeling study of the effect of base methylation on internal interactions and motions in DNA and implication to B-Z conformation change

Methylation in the bases of DNA is known to induce B-Z conformation change. In this work, molecular mechanics and normal mode analysis are used to probe how certain methylation affects the internal interactions and thermodynamic motions in the DNA double helixes in both B and Z conformations, and its implication to B-Z conformation change. By molecular modeling with Insight II, two cases involving cytosine C5 and guanine C8 methylation on both B and Z-form DNA duplex d(CGCGCG)2 are studied in comparison with the corresponding unmethylated duplexes. The internal interaction energies computed based on a molecular mechanics force field and the entropies due to internal motions computed according to a normal mode analysis are in fare agreement with respective observed thermodynamic quantities. The analysis on the computed individual energy terms suggests that the observed B-Z conformation change induced by methylation is primarily driven by enthalpic factors. A combination of changes in Van der Waals interaction, electrostatic interaction and hydrogen bonding likely contributes to the change of enthalpy that favors Z-conformation in the methylated states.

Multiscale tensegrity model for the tensile properties of DNA nanotubes

DNA nanotubes(DNTs)with user-defined shapes and functionalities have potential applications in many fields.So far,compared with numerous experimental studies,there have been only a handful of models on the mechanical properties of such DNTs.This paper aims at presenting a multiscale model to quantify the correlations among the pre-tension states,tensile properties,encapsulation structures of DNTs,and the surrounding factors.First,by combining a statistical worm-like-chain(WLC)model of single DNA deformation and Parsegian's mesoscopic model of DNA liquid crystal free energy,a multiscale tensegrity model is established,and the pre-tension state of DNTs is characterized theoretically for the first time.Then,by using the minimum potential energy principle,the force-extension curve and tensile rigidity of pre-tension DNTs are predicted.Finally,the effects of the encapsulation structure and surrounding factors on the tensile properties of DNTs are studied.The predictions for the tensile behaviors of DNTs can not only reproduce the existing experimental results,but also reveal that the competition of DNA intrachain and interchain interactions in the encapsulation structures determines the pre-tension states of DNTs and their tensile properties.The changes in the pre-tension states and environmental factors make the monotonic or non-monotonic changes in the tensile properties of DNTs under longitudinal loads.

New approach to assess sperm DNA fragmentation dynamics： Fine-tuning mathematical models

Background： Sperm DNA fragmentation（sDF） has been proved to be an important parameter in order to predict in vitro the potential fertility of a semen sample. Colloid centrifugation could be a suitable technique to select those donkey sperm more resistant to DNA fragmentation after thawing. Previous studies have shown that to elucidate the latent damage of the DNA molecule, sDF should be assessed dynamically, where the rate of fragmentation between treatments indicates how resistant the DNA is to iatrogenic damage. The rate of fragmentation is calculated using the slope of a linear regression equation. However, it has not been studied if s DF dynamics fit this model. The objectives of this study were to evaluate the effect of different after-thawing centrifugation protocols on sperm DNA fragmentation and elucidate the most accurate mathematical model（linear regression, exponential or polynomial） for DNA fragmentation over time in frozen-thawed donkey semen.Results： After submitting post-thaw semen samples to no centrifugation（UDC）, sperm washing（SW） or single layer centrifugation（SLC） protocols, sD F values after 6 h of incubation were significantly lower in SLC samples than in SW or UDC.Coefficient of determination（R-2） values were significantly higher for a second order polynomial model than for linear or exponential. The highest values for acceleration of fragmentation（aSDF） were obtained for SW, fol owed by SLC and UDC.Conclusion： SLC after thawing seems to preserve longer DNA longevity in comparison to UDC and SW. Moreover,the fine-tuning of models has shown that sDF dynamics in frozen-thawed donkey semen fit a second order polynomial model, which implies that fragmentation rate is not constant and fragmentation acceleration must be taken into account to elucidate hidden damage in the DNA molecule.

A new model of corporate DNA

This paper has researched on six kinds of the corporate DNA models, which have set up and analyzed its limitations, regarded the corporation as a vital organism, and put forward the judging standard for corporate DNA by analogism. According to the standard, the components of the corporate DNA are judged and a new model has been established. The corporate DNA is composed of four DNA chains, which overlap and intercross in the model. Based on the new model, the concept of the corporate central dogma is put forward. The element and information transmission way of corporate information are discussed in the corporate central dogma.

Dynamical model for biological functions of DNA molecules

We proposed a dynamic model of DNA to study its nonlinear excitation and duplication and transcription in the basis of molecular structure and changes of conformation of DNA under influence of bioenergy.

丹葛解酲汤对酒精性肝病大鼠DNA甲基化转移酶表达的影响

目的观察丹葛解酲汤对酒精性肝病(ALD)大鼠DNA甲基化转移酶(DNMTs)表达的影响。方法将96只SD大鼠随机分为空白组13只、造模组83只,造模组采用白酒灌胃法建立ALD模型,将成功造模的68只大鼠随机分为模型组、丹葛解酲汤高剂量组、丹葛解酲汤低剂量组、益肝灵片组,每组17只,分别进行干预。干预结束后采用赖氏法检测血清中丙氨酸氨基转移酶(ALT)、天冬氨酸氨基转移酶(AST)的含量,酶联免疫吸附法检测血清DNMT1、DNMT3a、DNMT3b的含量,实时荧光定量聚合酶链式反应(RT-PCR)检测肝脏组织中DNMT1、DNMT3a、DNMT3b mRNA表达水平。结果与空白组比较,模型组AST、ALT含量明显升高(P<0.01),DNMT1、DNMT3a含量明显降低(P<0.01),DNMT1mRNA、DNMT3a mRNA、DNMT3b mRNA表达水平明显降低(P<0.01)。与模型组比较,益肝灵片组AST、ALT、DNMT1、DNMT3a、DNMT1mRNA、DNMT3a mRNA、DNMT3b mRNA明显升高(P<0.01);丹葛解酲汤高剂量组AST、ALT、DNMT1、DNMT3a、DNMT1mRNA、DNMT3a mRNA、DNMT3b mRNA明显升高(P<0.01);丹葛解酲汤低剂量组ALT、DNMT1、DNMT3a mRNA明显升高(P<0.05,P<0.01)。结论丹葛解酲汤通过上调ALD大鼠DNMTs的表达,进而影响甲基化状态,可能是其防治ALD的作用机制之一。

Analysis of Lattice Size, Energy Density and Denaturation for a One-Dimensional DNA Model

There are several mechanical models to describe the DNA phenomenology. In this work the DNA denaturation is studied under thermodynamical and dynamical point of view using the well known Peyrard-Bishop model. The thermodynamics analysis using the transfer integral operator method is briefly reviewed. In particular, the lattice size is discussed and a conjecture about the minimum energy to denaturation is proposed. In terms of the dynamical aspects of the model, the equations of motion for the system are integrated and the results determine the energy density where the denatura- tion occurs. The behavior of the lattice near the phase transition is analyzed. The relation between the thermodynamical and dynamical results is discussed.