# Technical Evaluation of Commercial Sperm DFI Quality Control Products in SCSA Testing

Authors: Tao Pang; Xinzong Zhang
Journal: Journal of Healthcare Engineering
 (2022)

---

## Abstract

With the increase in population and the advancement of medicine, people even more hope that their offspring will be healthier. DNA fragmentation rate is currently one of the more common indicators for evaluating sperm fertility and predicting the outcome of pregnancy. In order to evaluate the technical performance and application value of commercial sperm DFI (DNA fragmentation index) quality control products in the flow cytometry sperm chromatin structure analysis (SCSA), this paper uses flow cytometry to test commercial sperm DFI quality control products (Celula) and laboratory routine self-made DFI quality control products. In this paper, the quality control of new commercial sperm DFI and laboratory-made quality control were compared and tested for 30 consecutive days. And this paper monitors the response of commercial quality control products to the interference of key reagent parameters. This paper compares the stability of the test results of two quality control products and their sensitivity to the interference of key performance parameters of the detection reagent. Experimental results show that commercial sperm DFI quality control products can simulate sperm DNA damage to achieve accurate detection of DNA integrity. The stability of commercial sperm DFI quality control (CV = 2.47%) is better than that of laboratory-made quality control (CV = 11.22%). The new commercial sperm DFI quality control product can sensitively detect changes in the concentration of acidified solution and staining solution at the same time. It can effectively control the quality of detection reagents and experimental procedures. The new commercial sperm DFI quality control product can effectively control sperm DNA integrity testing. It can be used as an external quality control product for quality control of test results to ensure that more accurate test results are provided to the clinic.


---

## Body

## 1. Introduction

### 1.1. Background

Sperm DNA fragmentation has been extensively studied for more than a decade. In the 1940s, people discovered the uniqueness of the sperm-protein complex that stabilizes DNA. In the 1950s and 1960s, people studied the relationship between unstable chromatin structure and infertility. In the 1970s, the effect of inducing DNA damage was studied. In the 1980s, the concept of sperm DNA fragmentation related to infertility was introduced, and the first DNA fragmentation test, sperm chromatin structure analysis (SCSA), was performed. The TUNEL test was introduced in the 1990s, followed by other test methods. The link between DNA fragmentation in sperm and miscarriage has been extensively studied, which has stimulated the demand for treatment tools for these patients. This has caused increased interest in the etiology of DNA damage. However, the lack of necessary quality control products is one of the reasons why laboratory quality control cannot be carried out.As a carrier of genetic material, sperm DNA not only is significantly related to sperm function but also can affect the division of fertilized eggs and the development of embryos. Among them, the rate of sperm fragmentation is a major influencing factor. Therefore, patients with severe sperm DNA damage will not only affect the quality of sperm but also cause egg fertilization failure and reduce the chance of pregnancy (male infertility). Moreover, it affects the quality of the embryo. Even if the egg can be fertilized and divided normally, it often leads to poor embryonic development and miscarriage in the end.With the improvement of modern industrialization, the proportion of infertility caused by environmental pollution, work pressure, and bad living habits is increasing year by year. Among them, the male infertility rate continues to increase, and the inspection methods for male infertility are mainly based on routine semen testing. Sperm chromatin structure analysis (SCSA), as the main detection method for evaluating the integrity of male sperm genetic material, plays a key role in evaluating sperm DNA quality, and it provides great help to the method of sperm detection. In clinical testing, sperm DNA integrity evaluation is mainly based on microscopy and flow cytometry. Flow cytometry is regarded as the “gold standard” for sperm DNA integrity testing because of its fast detection speed, simple operation, and high detection accuracy.


### 1.2. Significance

Numerous research results confirm the importance of sperm DNA fragmentation detection. It can reflect the integrity of sperm genetic material and in-depth assessment of male fertility, predict treatment outcomes, and guide treatment. However, the mechanism of DNA damage, the specific location of DNA damage, the treatment of sperm DNA fragmentation, and the establishment of a simple and easy-to-standardize clinical detection method all require further research.Damage to the integrity of sperm DNA is also a common semen abnormality in modern men, and it is the main factor leading to the decline of male fertility. Sperm DNA fragmentation index is a commonly used index to judge sperm DNA damage. At present, the relationship between specific gene methylation and temporal rhythm changes and sperm DNA integrity is still unclear. Commercial sperm DFI quality control products are tested by SCSA, and the technical evaluation is quantitatively analyzed to determine the relationship between specific methylation and temporal rhythm changes and sperm DFI. Therefore, it is of practical significance to study the technical evaluation of commercial sperm DFI quality control products in SCSA testing, and such related research is also very much needed.


### 1.3. Related Work

In medicine, research on DFI has a history of more than ten years and has made great contributions to issues such as fertility. In order to explore the relationship between sperm DNA fragmentation index (DFI) and semen parameters, Jun et al. evaluated its application value in semen quality evaluation. His method is to collect a total of 9,694 semen samples and use flow cytometry-assisted sperm chromatin structure analysis (SCSA) to detect sperm DFI and high DNA staining (HDS). Pearson correlation and multiple linear regression analysis were used to analyze the correlation between sperm DFI and semen parameters. Experiments have shown that there is a moderate correlation between sperm DFI and semen parameters, which can be used synergistically for the evaluation of semen quality [1]. Hongyi et al. pay more attention to the impact of DFI on fertility. They believe that the sperm DNA fragmentation index (DFI) is widely regarded as a key indicator of male fertility. However, DFI’s predictive value for assisted reproductive technology (ART) outcomes remains controversial. In this study, they used a large sample to analyze the impact of sperm DFI on pregnancy outcomes after ART and its relationship with in vitro fertilization (IVF)/intracytoplasmic sperm injection (ICSI) oocyte fertilization and embryo development. They also explored the value of sperm DNA fragmentation (SDF) and related factors in assessing male fertility. They retrospectively analyzed the relationship between DFI measured by sperm chromatin structure measurement (SCSA) and pregnancy outcomes after ART during 2,622 ART treatment cycles. The results show that, as an increasingly common reproductive testing technique, sperm DFI has proven to be very valuable in male fertility assessment. However, its importance as a predictor of pregnancy outcome after ART needs further research [2]. Niederberger and Craig believe that the percentage of SCSA DFI and TUNEL positive sperm is a moderately correlated measure of sperm DNA integrity but produces different results in a large proportion of patients. DFI has a good correlation with semen analysis parameters, but TUNEL is not. These data indicate that the SCSA and TUNEL tests measure different aspects of sperm DNA integrity and should not be used interchangeably [3]. Bach PV and others have also done a lot of researches on infertility. They believe that semen analysis is traditionally used to distinguish fertile men from infertile men. But in the current era of assisted reproductive technology, its effectiveness is questioned. The need for more sophisticated diagnostic and prognostic tools has led to the increased use of sperm DNA damage in the management of male infertility. Although there are many methods to measure sperm DNA damage, our understanding of the etiology, measurement, and clinical significance of sperm DNA damage is still incomplete. Although the current evidence is full of heterogeneity, it complicates the attempts of comparison and meta-analysis. But in the era of in vitro fertilization (IVF) and intracytoplasmic sperm injection (ICSI), sperm DNA damage does seem to play a role in the development and maintenance of pregnancy. However, as pointed out by the American Society of Reproductive Medicine, the routine and widespread use of sperm DNA damage testing is not yet supported. This requires further research to standardize the measurement of sperm DNA damage and to clarify the exact role of sperm DNA damage in the countless other male and female factors that lead to IVF and ICSI reproductive outcomes [4]. Hallak is more inclined to DFI’s evaluation criteria in this regard. For this reason, he believes that the Halosperm test kit is the latest sperm DNA fragmentation test. It becomes a suitable alternative to the sperm chromatin structure assay (SCSA) test. Although the test is clever and interesting, the data lack the statistical rigor of the SCSA test [5]. In terms of specific analysis, Asare N uses mice as experimental subjects. They found that silver nanoparticles (AgNPs) caused apoptosis, necrosis, and DNA strand breaks in different cell models in vitro. These findings ensure the analysis of their relevance in the body. The results found that the transcription levels of some key genes were significantly induced in Atm, Rad51, Sod1, Fos, and Mmp3 compared with the control group, especially in lung samples of KO mice exposed to Ag200. Ag200 causes genotoxicity and different gene expression patterns in selected genes related to DNA damage response and repair [6]. Rex AS et al. believe that some of the more novel methods that have recently been flooded are the use of increased DNA fragmentation and hyaluronic acid (HA) combined technology to sort cells. The clinical value of these tests remains to be elucidated. Despite half a century of research in this field, this analysis is not routinely applied to fertility clinics. The root cause is multifaceted. Numerous reviews and meta-analyses have been published on the use of different analytical methods to analyze DNA fragments, different clinical artificial reproduction treatments (ART), different definitions of successful ART results, and small patient populations. Although the field of sperm DNA fragmentation is highly relevant to fertility clinics, further research is still needed, focusing on the standardization of methods and clinical implementation [7]. Kunkitti et al. physiologically evaluated the DNA fragmentation of frozen-thawed cat epididymal sperm from the body and tail regions through three different techniques and compared DNA fragmentation index (DFI) between the following techniques: sperm chromatin structure determination (SCSA®), acridine orange staining technique (AOT), and sperm chromatin dispersion (SCD). There are significant differences in DFI between different technologies p<0.05, and there is no correlation. Only the DFI value obtained from the SCD showed that the DFI in the corpus was significantly higher than that of the sperm tail p<0.05. The differences between technologies may be due to differences in the sensitivity of each technology and the severity of detectable DNA damage. The difference in DFI between the epididymal region of the SCD technique may indicate the different maturation stages of the sperm. Compared with the epididymal tail, the sperm has less chromatin condensation in the body [8].


### 1.4. Innovation

This paper discusses the technical evaluation of commercial sperm DFI quality control products in SCSA testing. Compared with related studies at home and abroad, this paper focuses on the performance of commercial sperm DFI quality control products. This makes the study more bold and maneuverable. Specifically, there are the following innovations. First, the selection of instruments: the reagents of the instruments are all internationally renowned samples, and domestic-related researches use more hospital sample banks. Second, the application of the method: this paper selects two indicators of day-to-day stability and batch-to-batch stability, which are also rare in previous studies. Third, this paper controls other influencing factors that cause DFI, such as the age of both parties, the history of infertility and current physical condition, and the type of assisted reproductive technology, especially the woman’s factors, such as age, polycystic ovary syndrome, endometrial disease, and hydrosalpinx. In addition, the woman’s ovarian function is low, and her basic endocrine level is too high. These factors may have adverse consequences for the outcome of IVF and ET, and the DNA repair ability of its eggs is also very poor.


## 1.1. Background

Sperm DNA fragmentation has been extensively studied for more than a decade. In the 1940s, people discovered the uniqueness of the sperm-protein complex that stabilizes DNA. In the 1950s and 1960s, people studied the relationship between unstable chromatin structure and infertility. In the 1970s, the effect of inducing DNA damage was studied. In the 1980s, the concept of sperm DNA fragmentation related to infertility was introduced, and the first DNA fragmentation test, sperm chromatin structure analysis (SCSA), was performed. The TUNEL test was introduced in the 1990s, followed by other test methods. The link between DNA fragmentation in sperm and miscarriage has been extensively studied, which has stimulated the demand for treatment tools for these patients. This has caused increased interest in the etiology of DNA damage. However, the lack of necessary quality control products is one of the reasons why laboratory quality control cannot be carried out.As a carrier of genetic material, sperm DNA not only is significantly related to sperm function but also can affect the division of fertilized eggs and the development of embryos. Among them, the rate of sperm fragmentation is a major influencing factor. Therefore, patients with severe sperm DNA damage will not only affect the quality of sperm but also cause egg fertilization failure and reduce the chance of pregnancy (male infertility). Moreover, it affects the quality of the embryo. Even if the egg can be fertilized and divided normally, it often leads to poor embryonic development and miscarriage in the end.With the improvement of modern industrialization, the proportion of infertility caused by environmental pollution, work pressure, and bad living habits is increasing year by year. Among them, the male infertility rate continues to increase, and the inspection methods for male infertility are mainly based on routine semen testing. Sperm chromatin structure analysis (SCSA), as the main detection method for evaluating the integrity of male sperm genetic material, plays a key role in evaluating sperm DNA quality, and it provides great help to the method of sperm detection. In clinical testing, sperm DNA integrity evaluation is mainly based on microscopy and flow cytometry. Flow cytometry is regarded as the “gold standard” for sperm DNA integrity testing because of its fast detection speed, simple operation, and high detection accuracy.


## 1.2. Significance

Numerous research results confirm the importance of sperm DNA fragmentation detection. It can reflect the integrity of sperm genetic material and in-depth assessment of male fertility, predict treatment outcomes, and guide treatment. However, the mechanism of DNA damage, the specific location of DNA damage, the treatment of sperm DNA fragmentation, and the establishment of a simple and easy-to-standardize clinical detection method all require further research.Damage to the integrity of sperm DNA is also a common semen abnormality in modern men, and it is the main factor leading to the decline of male fertility. Sperm DNA fragmentation index is a commonly used index to judge sperm DNA damage. At present, the relationship between specific gene methylation and temporal rhythm changes and sperm DNA integrity is still unclear. Commercial sperm DFI quality control products are tested by SCSA, and the technical evaluation is quantitatively analyzed to determine the relationship between specific methylation and temporal rhythm changes and sperm DFI. Therefore, it is of practical significance to study the technical evaluation of commercial sperm DFI quality control products in SCSA testing, and such related research is also very much needed.


## 1.3. Related Work

In medicine, research on DFI has a history of more than ten years and has made great contributions to issues such as fertility. In order to explore the relationship between sperm DNA fragmentation index (DFI) and semen parameters, Jun et al. evaluated its application value in semen quality evaluation. His method is to collect a total of 9,694 semen samples and use flow cytometry-assisted sperm chromatin structure analysis (SCSA) to detect sperm DFI and high DNA staining (HDS). Pearson correlation and multiple linear regression analysis were used to analyze the correlation between sperm DFI and semen parameters. Experiments have shown that there is a moderate correlation between sperm DFI and semen parameters, which can be used synergistically for the evaluation of semen quality [1]. Hongyi et al. pay more attention to the impact of DFI on fertility. They believe that the sperm DNA fragmentation index (DFI) is widely regarded as a key indicator of male fertility. However, DFI’s predictive value for assisted reproductive technology (ART) outcomes remains controversial. In this study, they used a large sample to analyze the impact of sperm DFI on pregnancy outcomes after ART and its relationship with in vitro fertilization (IVF)/intracytoplasmic sperm injection (ICSI) oocyte fertilization and embryo development. They also explored the value of sperm DNA fragmentation (SDF) and related factors in assessing male fertility. They retrospectively analyzed the relationship between DFI measured by sperm chromatin structure measurement (SCSA) and pregnancy outcomes after ART during 2,622 ART treatment cycles. The results show that, as an increasingly common reproductive testing technique, sperm DFI has proven to be very valuable in male fertility assessment. However, its importance as a predictor of pregnancy outcome after ART needs further research [2]. Niederberger and Craig believe that the percentage of SCSA DFI and TUNEL positive sperm is a moderately correlated measure of sperm DNA integrity but produces different results in a large proportion of patients. DFI has a good correlation with semen analysis parameters, but TUNEL is not. These data indicate that the SCSA and TUNEL tests measure different aspects of sperm DNA integrity and should not be used interchangeably [3]. Bach PV and others have also done a lot of researches on infertility. They believe that semen analysis is traditionally used to distinguish fertile men from infertile men. But in the current era of assisted reproductive technology, its effectiveness is questioned. The need for more sophisticated diagnostic and prognostic tools has led to the increased use of sperm DNA damage in the management of male infertility. Although there are many methods to measure sperm DNA damage, our understanding of the etiology, measurement, and clinical significance of sperm DNA damage is still incomplete. Although the current evidence is full of heterogeneity, it complicates the attempts of comparison and meta-analysis. But in the era of in vitro fertilization (IVF) and intracytoplasmic sperm injection (ICSI), sperm DNA damage does seem to play a role in the development and maintenance of pregnancy. However, as pointed out by the American Society of Reproductive Medicine, the routine and widespread use of sperm DNA damage testing is not yet supported. This requires further research to standardize the measurement of sperm DNA damage and to clarify the exact role of sperm DNA damage in the countless other male and female factors that lead to IVF and ICSI reproductive outcomes [4]. Hallak is more inclined to DFI’s evaluation criteria in this regard. For this reason, he believes that the Halosperm test kit is the latest sperm DNA fragmentation test. It becomes a suitable alternative to the sperm chromatin structure assay (SCSA) test. Although the test is clever and interesting, the data lack the statistical rigor of the SCSA test [5]. In terms of specific analysis, Asare N uses mice as experimental subjects. They found that silver nanoparticles (AgNPs) caused apoptosis, necrosis, and DNA strand breaks in different cell models in vitro. These findings ensure the analysis of their relevance in the body. The results found that the transcription levels of some key genes were significantly induced in Atm, Rad51, Sod1, Fos, and Mmp3 compared with the control group, especially in lung samples of KO mice exposed to Ag200. Ag200 causes genotoxicity and different gene expression patterns in selected genes related to DNA damage response and repair [6]. Rex AS et al. believe that some of the more novel methods that have recently been flooded are the use of increased DNA fragmentation and hyaluronic acid (HA) combined technology to sort cells. The clinical value of these tests remains to be elucidated. Despite half a century of research in this field, this analysis is not routinely applied to fertility clinics. The root cause is multifaceted. Numerous reviews and meta-analyses have been published on the use of different analytical methods to analyze DNA fragments, different clinical artificial reproduction treatments (ART), different definitions of successful ART results, and small patient populations. Although the field of sperm DNA fragmentation is highly relevant to fertility clinics, further research is still needed, focusing on the standardization of methods and clinical implementation [7]. Kunkitti et al. physiologically evaluated the DNA fragmentation of frozen-thawed cat epididymal sperm from the body and tail regions through three different techniques and compared DNA fragmentation index (DFI) between the following techniques: sperm chromatin structure determination (SCSA®), acridine orange staining technique (AOT), and sperm chromatin dispersion (SCD). There are significant differences in DFI between different technologies p<0.05, and there is no correlation. Only the DFI value obtained from the SCD showed that the DFI in the corpus was significantly higher than that of the sperm tail p<0.05. The differences between technologies may be due to differences in the sensitivity of each technology and the severity of detectable DNA damage. The difference in DFI between the epididymal region of the SCD technique may indicate the different maturation stages of the sperm. Compared with the epididymal tail, the sperm has less chromatin condensation in the body [8].


## 1.4. Innovation

This paper discusses the technical evaluation of commercial sperm DFI quality control products in SCSA testing. Compared with related studies at home and abroad, this paper focuses on the performance of commercial sperm DFI quality control products. This makes the study more bold and maneuverable. Specifically, there are the following innovations. First, the selection of instruments: the reagents of the instruments are all internationally renowned samples, and domestic-related researches use more hospital sample banks. Second, the application of the method: this paper selects two indicators of day-to-day stability and batch-to-batch stability, which are also rare in previous studies. Third, this paper controls other influencing factors that cause DFI, such as the age of both parties, the history of infertility and current physical condition, and the type of assisted reproductive technology, especially the woman’s factors, such as age, polycystic ovary syndrome, endometrial disease, and hydrosalpinx. In addition, the woman’s ovarian function is low, and her basic endocrine level is too high. These factors may have adverse consequences for the outcome of IVF and ET, and the DNA repair ability of its eggs is also very poor.


## 2. Material and Method

### 2.1. Commercial Sperm DFI Quality Control and Chromatin Structure Analysis Method

The integrity of mammalian sperm DNA is essential for producing normal offspring [9]. After a sperm with DNA damage conceives an egg, it may have adverse effects on fertilization, embryonic development, and adult health. In the past, commonly used indexes for evaluating semen quality in clinical practice were sperm density, vitality, morphology, body response, nuclear protein group conversion experiment, and so on [10].Sperm chromatin structure analysis is a sensitive method for high-throughput and rapid detection of sperm DNA damage. Since Evenson Dp founded sperm chromatin structure assay (SCSA) technology to detect sperm DNA integrity, related basic and clinical research has been very active. And most of the research results believe that SCSA helps to assess the fertilization ability of animal sperm [11]. The assessment of male sperm fertilization ability can reflect male fertility. This will help doctors choose different methods of assisted pregnancy (IUI, IVF.ET, and ICSI) for the patient to obtain a successful pregnancy as soon as possible, thereby reducing the patient’s psychological, physical, and economic burden. The founders of SCSA conducted a large number of studies on the use of SCSA parameters for male fertility assessment and prediction of subclinical infertility and reached a threshold for assessing human fertility potential: DFI of 0%–15% has high fertility potential; of 15%∼30% has medium fertility potential; of >30% has low fertility potential; of >80% has no fertility. The basic principle is that after sperm enters the epididymis, a large number of thiol groups in the protamine are continuously oxidized into disulfide bonds. It binds more tightly with DNA, which makes DNA more resistant to acid, thereby maintaining the stability of the double-stranded structure [12]. In the sperm with DNA damage, most of the mercapto groups in protamine are not oxidized and are easily denatured to single-stranded DNA under the action of acid. According to this principle, the damaged DNA is denatured into single-stranded after acid treatment. Acridine orange combined with double-stranded DNA emits green fluorescence and combined with single-stranded DNA emits red or yellow fluorescence. It can be analyzed by flow cytometry [13].


### 2.2. SPSS Introduction and Brief Description of Related Principles

The SPSS software used in the experimental analysis of this paper is used for statistical analysis. Because of its visual operation interface and powerful statistical analysis capabilities, it is widely used in various scenarios [14]. In this paper, we use regression analysis in statistical analysis, so we will focus on it in the following introduction.


#### 2.2.1. The Basic Process of Using SPSS for Data Processing

SPSS is powerful and easy to operate. This feature is reflected in his unified and simple operation process [15]. The basic process of SPSS statistical processing is shown in Figure 1.Figure 1
Basic diagram of the statistical process.


#### 2.2.2. General Form of Multiple Regression Model

Setting the random variabley, and the linear regression model of the general variable is x1,x2,…,xp:(1)y=β0+β1x1+β2x2+⋯+βpxp+ε.In formula (1), β0 is called the regression constant, and β1,β2,…,βp are the regression coefficients. ε is called the random error term, and generally, we assume that(2)Eε=0,Vε=σ2.(3)Ey=β0+β1x1+β2x2+⋯+βpxp.Among them, (2) is the basic assumption, and (3) is called the theoretical regression equation [15]. However, in the actual problem processing, we obtain n sets of data, and the linear model is expressed as (4):(4)y=βX+ε.


#### 2.2.3. Basic Assumptions

(i)
Explanatory variablesx1,x2,…,xp are definite variables.(ii)
The random error term has zero mean and equal variance; the formula is expressed as formula (5); namely,(5)Eεi=0,i=1,2,⋯,n,covεi,εj=σ2,i=j0,i≠ji,j=1,2,⋯,n.


#### 2.2.4. The Assumption Condition Formula of Normal Distribution Is Expressed as Formula (6)

(6)εi∼N0,σ2,i=1,2,…,n,ε1,ε2,…,εn.For the multiple linear regression matrix modely=βX+ε, this condition can be expressed as (7):(7)ε∼N0,σ2In.It can be seen from the above-mentioned properties of the assumed multivariate normal distribution that the random vectory obeys the n-dimensional normal distribution, and the expected vector of the regression model y=βX+ε is (8) and (9):(8)Ey=Xβ.(9)Vary=σ2In.Therefore,(10)y∼NXβ,σ2In.Among them, (8) is the expected mean value, (9) is the expected variance, and the distribution of y in (10) is obtained.


#### 2.2.5. Regression Parameter Estimation

The parameter ordinary least square estimation is expressed as follows: when A exists, the least square estimation can be obtained, as shown in formula (11):(11)β^=X′X−1X′y.(12)y^=β^0+β^1x1+β^2x2+⋯+β^pxp.Among them, formula (12) is called the empirical regression equation. Its regression value and residual are expressed as follows.Cally^i=β^0+β^1xi1+β^2xi2+⋯+β^pxip the regression fitted value of the observed value yii=1,2,…,n, referred to as the regression value or fitted value. The residual satisfies the relationship, as in (13):(13)∑ei=0∑eixi1=0⋮∑eixip=0.In (13), the average value of the residuals is 0, and the weighted average of the residuals for each independent variable is 0.


#### 2.2.6. Maximum Likelihood Estimation of Regression Parameters

The model is shown in formula (14):(14)y=Xβ+εε∼N0,σ2In,where ε obeys a multivariate normal distribution, and then the probability distribution of y is shown in (15):(15)y∼NXβ,σ2In.At this time, the likelihood function is shown in (16):(16)L=2π−n/2σ2−n/2exp−12σ2y−Xβ′y−Xβ.Among them, the unknown parametersL are β and σ2, and the maximum likelihood estimation is to select β^ and σ^2 that maximize the likelihood function L. To maximize L, take the logarithm of both sides of the equation, as shown in equation (17):(17)lnL=−n2ln2π−n2lnσ2−12σ2y−Xβ′y−Xβ.Obviously, it is necessary to maximize it, which is equivalent to the minimum ofy−Xβ′y−Xβy−Xβ′y−Xβ; that is, the maximum likelihood estimation of the error term variance σ2 is(18)σ^L2=1nSSE=1ne′e.In (18), this is a biased estimate of σ2, but it satisfies consistency. In the case of a large sample, this is an asymptotically unbiased estimate of σ2.


#### 2.2.7. Significance Test of the Regression Equation

This paper mainly describes the F test and thet-test. The F test is as follows: null hypothesis H0:β1=β2=β3=⋯βp=0. When F>Fαp,n−p−1, reject the null hypothesis H0, thinking that, at the significance level α, y and x1,x2,…,xp have a significant linear relationship; that is, the regression equation is significant. As shown in Table 1, the variance test table, the P value is the focus of our analysis.Table 1
Variance test table.
Variance analysisDegree of freedomSum of squareMean squareF valueP valueReturnpSSRSSR/p(SSR/p)/(SSE/(n-p-1))P(F>F value) = P valueResidualn-p-1SSESSE/(n-p-1)SumN-1SSTThe principle of thet-test is as follows: null hypothesis H0:βj=0,j=1,2,…,p. Construct t statistics, as in the following:(19)tj=β^jcjjσ^.In formula (19),(20)σ^=1n−p−1∑i=1nei2=1n−p−1∑i=1nyi−y^i2.Equation (20) is the regression standard deviation.When theH0:βj=0 null hypothesis is true, the t statistic obeys the distribution with n−p−1 degrees of freedom. Given the significance level α, the critical value tα/2 of the two-sided test is found. When tj≥tα/2, reject the null hypothesis and think that βj is significantly not zero, and the linear effect of the independent variable xj on the dependent variable y is significant.


#### 2.2.8. Residual Error Analysis

The residual A takes the independent variable B as the horizontal axis and the residual as the vertical axis to obtain a residual diagram. The residual diagram can be used to illustrate the different manifestations of sample data [16].


### 2.3. Instruments and Reagents

#### 2.3.1. Instrument

The flow cytometer (Sparrow) is produced by Celula (China) Medical Technology Co., Ltd. The microscope (BX51) is produced by Olympus.


#### 2.3.2. Reagent

(1)
Commercial sperm DFI quality control products are developed, produced, and provided by Celula (China) Medical Technology Co., Ltd. It includes two main components of nonsperm cells with specific proportions of DNA damage and internal reference products. Among them, the nonsperm cell is a mixture of nonsperm normal cells with intact DNA and nonsperm cells with DNA damage according to a preset ratio, which is used to simulate sperm with a certain degree of DNA damage; the internal reference product is composed of green and red microspheres with stable fluorescence intensity, which can be used as a reference for key operation steps and quality monitoring of sperm DNA reagents. The testing process of commercial sperm DFI quality control products is the same as the process of DNA integrity testing of sperm samples, and it can be stored at 2∼8°C. The target value of the commercial sperm DFI quality control product “DFI” in this test is 38.20% ± 0.5%.(2)
Laboratory self-made sperm DFI quality control products are prepared and stored by Guangdong Family Planning Institute.(3)
Sperm DNA integrity staining kit is produced by Celula (China) Medical Technology Co., Ltd. It is used for DNA integrity testing and technical performance evaluation of commercial sperm DFI quality control products and laboratory self-made sperm DFI quality control products [17].


#### 2.3.3. Sample

The sample came from a sperm sample from the Andrology Clinic of our hospital in August 2021. The sample acquisition refers to the World Health Organization “Human Semen Examination and Processing Laboratory Manual” (5th edition). The project was approved by the hospital ethics committee, and the patient signed an informed consent form.


### 2.4. Preparation Method of Laboratory Sperm DFI Quality Control Products

Quality control preparation method is as follows: (1) Semen recovery: use conventional density gradient centrifugation to collect sperm in the bottom and subbottom layers. After washing, it is diluted to a recovered sperm fluid with a density of about 1 to 2 × 106/ml. (2) Hydroformylation fixation: add the sperm recovery solution to 0.5% glutaraldehyde in physiological saline solution, and fix it for 60 minutes at 25°C and room temperature. (3) Preparation of quality control products: collect the aldehyde spermatids, wash them with sperm diluent, separate them, and store them at −80°C. (4) Determination of DFI target value of self-made quality control product.


### 2.5. Test Method

Following the Celula sperm DNA integrity staining kit operating instructions to perform flow cytometry detection of sperm DNA integrity, which mainly includes four steps, firstly dilute the semen; then acidify the sperm. The third step is to stain the DNA in different states. Finally, Sparrow flow cytometry was used to calculate the sperm DNA fragmentation index [18].


### 2.6. Detection Parameters

#### 2.6.1. DNA Fragmentation Index

Flow cytometry was used to detect commercial sperm DFI quality control products and laboratory-made sperm DFI quality control products. The flow cytometer FL1 (FITC) and FL3 (PerCP), two detection fluorescence channels, are used to distinguish cell populations and calculate DFI [19].


#### 2.6.2. Daytime Precision Study

The laboratory-made sperm DFI quality control product was stored at −80°C. Take out 1 sample a day for testing and make continuous testing for 30 days and parallel continuous testing of new commercial sperm DFI quality control products for 30 days. The commercial sperm DFI quality control product should be put back to 2∼8°C for storage immediately after use. By analyzing the DFI and coefficient of variation (CV) of laboratory-made quality control products and commercial sperm DFI quality control products at 30 days, the daytime precision was compared [20].


#### 2.6.3. Interassay Precision Study

Test 3 batches of Celula commercial sperm DFI quality control products. The test was repeated 6 times for each batch, and the DFI and its coefficient of variation (CV) were analyzed [21].


#### 2.6.4. Research on Reagent Interference

(1)
In order to investigate the sensitivity of the Celula commercial sperm DFI quality control product, the acid denaturation reagent B in the sperm DNA staining kit was set with 4 gradients; the gradient setting is determined by the laboratory staining kit: 0.2X, 2X, 3X, and 1X (1X is the correct nominal dosage). Analyze whether the new commercial sperm DFI quality control product can be sensitive to the interference of the acid denaturation reagent B solution.(2)
Set the staining solution in the sperm DNA staining kit to 4 gradients; the gradient setting is determined by the laboratory staining kit: 0.3X, 0.5X, 1.67X, and 1X (1X is the correct nominal amount). Analyze whether the commercial sperm DFI quality control product can be sensitive to the interference of the quality control to the staining solution C [22].


### 2.7. Sperm DNA Fragments

Sperm chromatin structure analysis (SCSA) method was used to detect sperm DAN fragments. Diluting the sperm cells with solution A to a final concentration of 1∼210 ^ 6/ml, take 100μl of the diluted semen, add 200 μl of B solution on ice, and add 600 μl of solution C, and mix well after 30S. Because of the loose structure of DNA-damaged sperm chromatin, it is easily cleaved under acid denaturation conditions to form single-stranded DNA, which binds to AO and emits yellow or red fluorescence, while normal sperm still maintains double-stranded DNA, and AO stains green fluorescence. Flow cytometry analysis was used to detect the integrity damage of sperm DNA, and the results were expressed by DFI.


## 2.1. Commercial Sperm DFI Quality Control and Chromatin Structure Analysis Method

The integrity of mammalian sperm DNA is essential for producing normal offspring [9]. After a sperm with DNA damage conceives an egg, it may have adverse effects on fertilization, embryonic development, and adult health. In the past, commonly used indexes for evaluating semen quality in clinical practice were sperm density, vitality, morphology, body response, nuclear protein group conversion experiment, and so on [10].Sperm chromatin structure analysis is a sensitive method for high-throughput and rapid detection of sperm DNA damage. Since Evenson Dp founded sperm chromatin structure assay (SCSA) technology to detect sperm DNA integrity, related basic and clinical research has been very active. And most of the research results believe that SCSA helps to assess the fertilization ability of animal sperm [11]. The assessment of male sperm fertilization ability can reflect male fertility. This will help doctors choose different methods of assisted pregnancy (IUI, IVF.ET, and ICSI) for the patient to obtain a successful pregnancy as soon as possible, thereby reducing the patient’s psychological, physical, and economic burden. The founders of SCSA conducted a large number of studies on the use of SCSA parameters for male fertility assessment and prediction of subclinical infertility and reached a threshold for assessing human fertility potential: DFI of 0%–15% has high fertility potential; of 15%∼30% has medium fertility potential; of >30% has low fertility potential; of >80% has no fertility. The basic principle is that after sperm enters the epididymis, a large number of thiol groups in the protamine are continuously oxidized into disulfide bonds. It binds more tightly with DNA, which makes DNA more resistant to acid, thereby maintaining the stability of the double-stranded structure [12]. In the sperm with DNA damage, most of the mercapto groups in protamine are not oxidized and are easily denatured to single-stranded DNA under the action of acid. According to this principle, the damaged DNA is denatured into single-stranded after acid treatment. Acridine orange combined with double-stranded DNA emits green fluorescence and combined with single-stranded DNA emits red or yellow fluorescence. It can be analyzed by flow cytometry [13].


## 2.2. SPSS Introduction and Brief Description of Related Principles

The SPSS software used in the experimental analysis of this paper is used for statistical analysis. Because of its visual operation interface and powerful statistical analysis capabilities, it is widely used in various scenarios [14]. In this paper, we use regression analysis in statistical analysis, so we will focus on it in the following introduction.


### 2.2.1. The Basic Process of Using SPSS for Data Processing

SPSS is powerful and easy to operate. This feature is reflected in his unified and simple operation process [15]. The basic process of SPSS statistical processing is shown in Figure 1.Figure 1
Basic diagram of the statistical process.


### 2.2.2. General Form of Multiple Regression Model

Setting the random variabley, and the linear regression model of the general variable is x1,x2,…,xp:(1)y=β0+β1x1+β2x2+⋯+βpxp+ε.In formula (1), β0 is called the regression constant, and β1,β2,…,βp are the regression coefficients. ε is called the random error term, and generally, we assume that(2)Eε=0,Vε=σ2.(3)Ey=β0+β1x1+β2x2+⋯+βpxp.Among them, (2) is the basic assumption, and (3) is called the theoretical regression equation [15]. However, in the actual problem processing, we obtain n sets of data, and the linear model is expressed as (4):(4)y=βX+ε.


### 2.2.3. Basic Assumptions

(i)
Explanatory variablesx1,x2,…,xp are definite variables.(ii)
The random error term has zero mean and equal variance; the formula is expressed as formula (5); namely,(5)Eεi=0,i=1,2,⋯,n,covεi,εj=σ2,i=j0,i≠ji,j=1,2,⋯,n.


### 2.2.4. The Assumption Condition Formula of Normal Distribution Is Expressed as Formula (6)

(6)εi∼N0,σ2,i=1,2,…,n,ε1,ε2,…,εn.For the multiple linear regression matrix modely=βX+ε, this condition can be expressed as (7):(7)ε∼N0,σ2In.It can be seen from the above-mentioned properties of the assumed multivariate normal distribution that the random vectory obeys the n-dimensional normal distribution, and the expected vector of the regression model y=βX+ε is (8) and (9):(8)Ey=Xβ.(9)Vary=σ2In.Therefore,(10)y∼NXβ,σ2In.Among them, (8) is the expected mean value, (9) is the expected variance, and the distribution of y in (10) is obtained.


### 2.2.5. Regression Parameter Estimation

The parameter ordinary least square estimation is expressed as follows: when A exists, the least square estimation can be obtained, as shown in formula (11):(11)β^=X′X−1X′y.(12)y^=β^0+β^1x1+β^2x2+⋯+β^pxp.Among them, formula (12) is called the empirical regression equation. Its regression value and residual are expressed as follows.Cally^i=β^0+β^1xi1+β^2xi2+⋯+β^pxip the regression fitted value of the observed value yii=1,2,…,n, referred to as the regression value or fitted value. The residual satisfies the relationship, as in (13):(13)∑ei=0∑eixi1=0⋮∑eixip=0.In (13), the average value of the residuals is 0, and the weighted average of the residuals for each independent variable is 0.


### 2.2.6. Maximum Likelihood Estimation of Regression Parameters

The model is shown in formula (14):(14)y=Xβ+εε∼N0,σ2In,where ε obeys a multivariate normal distribution, and then the probability distribution of y is shown in (15):(15)y∼NXβ,σ2In.At this time, the likelihood function is shown in (16):(16)L=2π−n/2σ2−n/2exp−12σ2y−Xβ′y−Xβ.Among them, the unknown parametersL are β and σ2, and the maximum likelihood estimation is to select β^ and σ^2 that maximize the likelihood function L. To maximize L, take the logarithm of both sides of the equation, as shown in equation (17):(17)lnL=−n2ln2π−n2lnσ2−12σ2y−Xβ′y−Xβ.Obviously, it is necessary to maximize it, which is equivalent to the minimum ofy−Xβ′y−Xβy−Xβ′y−Xβ; that is, the maximum likelihood estimation of the error term variance σ2 is(18)σ^L2=1nSSE=1ne′e.In (18), this is a biased estimate of σ2, but it satisfies consistency. In the case of a large sample, this is an asymptotically unbiased estimate of σ2.


### 2.2.7. Significance Test of the Regression Equation

This paper mainly describes the F test and thet-test. The F test is as follows: null hypothesis H0:β1=β2=β3=⋯βp=0. When F>Fαp,n−p−1, reject the null hypothesis H0, thinking that, at the significance level α, y and x1,x2,…,xp have a significant linear relationship; that is, the regression equation is significant. As shown in Table 1, the variance test table, the P value is the focus of our analysis.Table 1
Variance test table.
Variance analysisDegree of freedomSum of squareMean squareF valueP valueReturnpSSRSSR/p(SSR/p)/(SSE/(n-p-1))P(F>F value) = P valueResidualn-p-1SSESSE/(n-p-1)SumN-1SSTThe principle of thet-test is as follows: null hypothesis H0:βj=0,j=1,2,…,p. Construct t statistics, as in the following:(19)tj=β^jcjjσ^.In formula (19),(20)σ^=1n−p−1∑i=1nei2=1n−p−1∑i=1nyi−y^i2.Equation (20) is the regression standard deviation.When theH0:βj=0 null hypothesis is true, the t statistic obeys the distribution with n−p−1 degrees of freedom. Given the significance level α, the critical value tα/2 of the two-sided test is found. When tj≥tα/2, reject the null hypothesis and think that βj is significantly not zero, and the linear effect of the independent variable xj on the dependent variable y is significant.


### 2.2.8. Residual Error Analysis

The residual A takes the independent variable B as the horizontal axis and the residual as the vertical axis to obtain a residual diagram. The residual diagram can be used to illustrate the different manifestations of sample data [16].


## 2.2.1. The Basic Process of Using SPSS for Data Processing

SPSS is powerful and easy to operate. This feature is reflected in his unified and simple operation process [15]. The basic process of SPSS statistical processing is shown in Figure 1.Figure 1
Basic diagram of the statistical process.


## 2.2.2. General Form of Multiple Regression Model

Setting the random variabley, and the linear regression model of the general variable is x1,x2,…,xp:(1)y=β0+β1x1+β2x2+⋯+βpxp+ε.In formula (1), β0 is called the regression constant, and β1,β2,…,βp are the regression coefficients. ε is called the random error term, and generally, we assume that(2)Eε=0,Vε=σ2.(3)Ey=β0+β1x1+β2x2+⋯+βpxp.Among them, (2) is the basic assumption, and (3) is called the theoretical regression equation [15]. However, in the actual problem processing, we obtain n sets of data, and the linear model is expressed as (4):(4)y=βX+ε.


## 2.2.3. Basic Assumptions

(i)
Explanatory variablesx1,x2,…,xp are definite variables.(ii)
The random error term has zero mean and equal variance; the formula is expressed as formula (5); namely,(5)Eεi=0,i=1,2,⋯,n,covεi,εj=σ2,i=j0,i≠ji,j=1,2,⋯,n.


## 2.2.4. The Assumption Condition Formula of Normal Distribution Is Expressed as Formula (6)

(6)εi∼N0,σ2,i=1,2,…,n,ε1,ε2,…,εn.For the multiple linear regression matrix modely=βX+ε, this condition can be expressed as (7):(7)ε∼N0,σ2In.It can be seen from the above-mentioned properties of the assumed multivariate normal distribution that the random vectory obeys the n-dimensional normal distribution, and the expected vector of the regression model y=βX+ε is (8) and (9):(8)Ey=Xβ.(9)Vary=σ2In.Therefore,(10)y∼NXβ,σ2In.Among them, (8) is the expected mean value, (9) is the expected variance, and the distribution of y in (10) is obtained.


## 2.2.5. Regression Parameter Estimation

The parameter ordinary least square estimation is expressed as follows: when A exists, the least square estimation can be obtained, as shown in formula (11):(11)β^=X′X−1X′y.(12)y^=β^0+β^1x1+β^2x2+⋯+β^pxp.Among them, formula (12) is called the empirical regression equation. Its regression value and residual are expressed as follows.Cally^i=β^0+β^1xi1+β^2xi2+⋯+β^pxip the regression fitted value of the observed value yii=1,2,…,n, referred to as the regression value or fitted value. The residual satisfies the relationship, as in (13):(13)∑ei=0∑eixi1=0⋮∑eixip=0.In (13), the average value of the residuals is 0, and the weighted average of the residuals for each independent variable is 0.


## 2.2.6. Maximum Likelihood Estimation of Regression Parameters

The model is shown in formula (14):(14)y=Xβ+εε∼N0,σ2In,where ε obeys a multivariate normal distribution, and then the probability distribution of y is shown in (15):(15)y∼NXβ,σ2In.At this time, the likelihood function is shown in (16):(16)L=2π−n/2σ2−n/2exp−12σ2y−Xβ′y−Xβ.Among them, the unknown parametersL are β and σ2, and the maximum likelihood estimation is to select β^ and σ^2 that maximize the likelihood function L. To maximize L, take the logarithm of both sides of the equation, as shown in equation (17):(17)lnL=−n2ln2π−n2lnσ2−12σ2y−Xβ′y−Xβ.Obviously, it is necessary to maximize it, which is equivalent to the minimum ofy−Xβ′y−Xβy−Xβ′y−Xβ; that is, the maximum likelihood estimation of the error term variance σ2 is(18)σ^L2=1nSSE=1ne′e.In (18), this is a biased estimate of σ2, but it satisfies consistency. In the case of a large sample, this is an asymptotically unbiased estimate of σ2.


## 2.2.7. Significance Test of the Regression Equation

This paper mainly describes the F test and thet-test. The F test is as follows: null hypothesis H0:β1=β2=β3=⋯βp=0. When F>Fαp,n−p−1, reject the null hypothesis H0, thinking that, at the significance level α, y and x1,x2,…,xp have a significant linear relationship; that is, the regression equation is significant. As shown in Table 1, the variance test table, the P value is the focus of our analysis.Table 1
Variance test table.
Variance analysisDegree of freedomSum of squareMean squareF valueP valueReturnpSSRSSR/p(SSR/p)/(SSE/(n-p-1))P(F>F value) = P valueResidualn-p-1SSESSE/(n-p-1)SumN-1SSTThe principle of thet-test is as follows: null hypothesis H0:βj=0,j=1,2,…,p. Construct t statistics, as in the following:(19)tj=β^jcjjσ^.In formula (19),(20)σ^=1n−p−1∑i=1nei2=1n−p−1∑i=1nyi−y^i2.Equation (20) is the regression standard deviation.When theH0:βj=0 null hypothesis is true, the t statistic obeys the distribution with n−p−1 degrees of freedom. Given the significance level α, the critical value tα/2 of the two-sided test is found. When tj≥tα/2, reject the null hypothesis and think that βj is significantly not zero, and the linear effect of the independent variable xj on the dependent variable y is significant.


## 2.2.8. Residual Error Analysis

The residual A takes the independent variable B as the horizontal axis and the residual as the vertical axis to obtain a residual diagram. The residual diagram can be used to illustrate the different manifestations of sample data [16].


## 2.3. Instruments and Reagents

### 2.3.1. Instrument

The flow cytometer (Sparrow) is produced by Celula (China) Medical Technology Co., Ltd. The microscope (BX51) is produced by Olympus.


### 2.3.2. Reagent

(1)
Commercial sperm DFI quality control products are developed, produced, and provided by Celula (China) Medical Technology Co., Ltd. It includes two main components of nonsperm cells with specific proportions of DNA damage and internal reference products. Among them, the nonsperm cell is a mixture of nonsperm normal cells with intact DNA and nonsperm cells with DNA damage according to a preset ratio, which is used to simulate sperm with a certain degree of DNA damage; the internal reference product is composed of green and red microspheres with stable fluorescence intensity, which can be used as a reference for key operation steps and quality monitoring of sperm DNA reagents. The testing process of commercial sperm DFI quality control products is the same as the process of DNA integrity testing of sperm samples, and it can be stored at 2∼8°C. The target value of the commercial sperm DFI quality control product “DFI” in this test is 38.20% ± 0.5%.(2)
Laboratory self-made sperm DFI quality control products are prepared and stored by Guangdong Family Planning Institute.(3)
Sperm DNA integrity staining kit is produced by Celula (China) Medical Technology Co., Ltd. It is used for DNA integrity testing and technical performance evaluation of commercial sperm DFI quality control products and laboratory self-made sperm DFI quality control products [17].


### 2.3.3. Sample

The sample came from a sperm sample from the Andrology Clinic of our hospital in August 2021. The sample acquisition refers to the World Health Organization “Human Semen Examination and Processing Laboratory Manual” (5th edition). The project was approved by the hospital ethics committee, and the patient signed an informed consent form.


## 2.3.1. Instrument

The flow cytometer (Sparrow) is produced by Celula (China) Medical Technology Co., Ltd. The microscope (BX51) is produced by Olympus.


## 2.3.2. Reagent

(1)
Commercial sperm DFI quality control products are developed, produced, and provided by Celula (China) Medical Technology Co., Ltd. It includes two main components of nonsperm cells with specific proportions of DNA damage and internal reference products. Among them, the nonsperm cell is a mixture of nonsperm normal cells with intact DNA and nonsperm cells with DNA damage according to a preset ratio, which is used to simulate sperm with a certain degree of DNA damage; the internal reference product is composed of green and red microspheres with stable fluorescence intensity, which can be used as a reference for key operation steps and quality monitoring of sperm DNA reagents. The testing process of commercial sperm DFI quality control products is the same as the process of DNA integrity testing of sperm samples, and it can be stored at 2∼8°C. The target value of the commercial sperm DFI quality control product “DFI” in this test is 38.20% ± 0.5%.(2)
Laboratory self-made sperm DFI quality control products are prepared and stored by Guangdong Family Planning Institute.(3)
Sperm DNA integrity staining kit is produced by Celula (China) Medical Technology Co., Ltd. It is used for DNA integrity testing and technical performance evaluation of commercial sperm DFI quality control products and laboratory self-made sperm DFI quality control products [17].


## 2.3.3. Sample

The sample came from a sperm sample from the Andrology Clinic of our hospital in August 2021. The sample acquisition refers to the World Health Organization “Human Semen Examination and Processing Laboratory Manual” (5th edition). The project was approved by the hospital ethics committee, and the patient signed an informed consent form.


## 2.4. Preparation Method of Laboratory Sperm DFI Quality Control Products

Quality control preparation method is as follows: (1) Semen recovery: use conventional density gradient centrifugation to collect sperm in the bottom and subbottom layers. After washing, it is diluted to a recovered sperm fluid with a density of about 1 to 2 × 106/ml. (2) Hydroformylation fixation: add the sperm recovery solution to 0.5% glutaraldehyde in physiological saline solution, and fix it for 60 minutes at 25°C and room temperature. (3) Preparation of quality control products: collect the aldehyde spermatids, wash them with sperm diluent, separate them, and store them at −80°C. (4) Determination of DFI target value of self-made quality control product.


## 2.5. Test Method

Following the Celula sperm DNA integrity staining kit operating instructions to perform flow cytometry detection of sperm DNA integrity, which mainly includes four steps, firstly dilute the semen; then acidify the sperm. The third step is to stain the DNA in different states. Finally, Sparrow flow cytometry was used to calculate the sperm DNA fragmentation index [18].


## 2.6. Detection Parameters

### 2.6.1. DNA Fragmentation Index

Flow cytometry was used to detect commercial sperm DFI quality control products and laboratory-made sperm DFI quality control products. The flow cytometer FL1 (FITC) and FL3 (PerCP), two detection fluorescence channels, are used to distinguish cell populations and calculate DFI [19].


### 2.6.2. Daytime Precision Study

The laboratory-made sperm DFI quality control product was stored at −80°C. Take out 1 sample a day for testing and make continuous testing for 30 days and parallel continuous testing of new commercial sperm DFI quality control products for 30 days. The commercial sperm DFI quality control product should be put back to 2∼8°C for storage immediately after use. By analyzing the DFI and coefficient of variation (CV) of laboratory-made quality control products and commercial sperm DFI quality control products at 30 days, the daytime precision was compared [20].


### 2.6.3. Interassay Precision Study

Test 3 batches of Celula commercial sperm DFI quality control products. The test was repeated 6 times for each batch, and the DFI and its coefficient of variation (CV) were analyzed [21].


### 2.6.4. Research on Reagent Interference

(1)
In order to investigate the sensitivity of the Celula commercial sperm DFI quality control product, the acid denaturation reagent B in the sperm DNA staining kit was set with 4 gradients; the gradient setting is determined by the laboratory staining kit: 0.2X, 2X, 3X, and 1X (1X is the correct nominal dosage). Analyze whether the new commercial sperm DFI quality control product can be sensitive to the interference of the acid denaturation reagent B solution.(2)
Set the staining solution in the sperm DNA staining kit to 4 gradients; the gradient setting is determined by the laboratory staining kit: 0.3X, 0.5X, 1.67X, and 1X (1X is the correct nominal amount). Analyze whether the commercial sperm DFI quality control product can be sensitive to the interference of the quality control to the staining solution C [22].


## 2.6.1. DNA Fragmentation Index

Flow cytometry was used to detect commercial sperm DFI quality control products and laboratory-made sperm DFI quality control products. The flow cytometer FL1 (FITC) and FL3 (PerCP), two detection fluorescence channels, are used to distinguish cell populations and calculate DFI [19].


## 2.6.2. Daytime Precision Study

The laboratory-made sperm DFI quality control product was stored at −80°C. Take out 1 sample a day for testing and make continuous testing for 30 days and parallel continuous testing of new commercial sperm DFI quality control products for 30 days. The commercial sperm DFI quality control product should be put back to 2∼8°C for storage immediately after use. By analyzing the DFI and coefficient of variation (CV) of laboratory-made quality control products and commercial sperm DFI quality control products at 30 days, the daytime precision was compared [20].


## 2.6.3. Interassay Precision Study

Test 3 batches of Celula commercial sperm DFI quality control products. The test was repeated 6 times for each batch, and the DFI and its coefficient of variation (CV) were analyzed [21].


## 2.6.4. Research on Reagent Interference

(1)
In order to investigate the sensitivity of the Celula commercial sperm DFI quality control product, the acid denaturation reagent B in the sperm DNA staining kit was set with 4 gradients; the gradient setting is determined by the laboratory staining kit: 0.2X, 2X, 3X, and 1X (1X is the correct nominal dosage). Analyze whether the new commercial sperm DFI quality control product can be sensitive to the interference of the acid denaturation reagent B solution.(2)
Set the staining solution in the sperm DNA staining kit to 4 gradients; the gradient setting is determined by the laboratory staining kit: 0.3X, 0.5X, 1.67X, and 1X (1X is the correct nominal amount). Analyze whether the commercial sperm DFI quality control product can be sensitive to the interference of the quality control to the staining solution C [22].


## 2.7. Sperm DNA Fragments

Sperm chromatin structure analysis (SCSA) method was used to detect sperm DAN fragments. Diluting the sperm cells with solution A to a final concentration of 1∼210 ^ 6/ml, take 100μl of the diluted semen, add 200 μl of B solution on ice, and add 600 μl of solution C, and mix well after 30S. Because of the loose structure of DNA-damaged sperm chromatin, it is easily cleaved under acid denaturation conditions to form single-stranded DNA, which binds to AO and emits yellow or red fluorescence, while normal sperm still maintains double-stranded DNA, and AO stains green fluorescence. Flow cytometry analysis was used to detect the integrity damage of sperm DNA, and the results were expressed by DFI.


## 3. Experimental Results

### 3.1. Effectiveness of New Commercial Sperm DFI Quality Control Products

The flow diagram of the new commercial sperm DFI quality control after testing is shown in Figure2. The P1 circle gate (blue part) indicates double-stranded DNA, that is, cell with intact DNA, and the P2 circle gate (red part) indicates DNA-damaged cells. From the results of stream clustering, it can be found that P1 and P2 can be effectively separated, and the calculation process of sperm DFI can be simulated in the same way. Therefore, the commercial sperm DFI quality control product can effectively simulate the DNA damage classification and the calculation of the fragment index for the DNA integrity test of the sperm sample. P3 (purple part) and P4 (orange part) are built-in reference products, which can be used for internal control calculation and the relative position of P1 and P2 circle gate, operation process interference, and reagent effectiveness evaluation; as you can see in Figure 2, all indicators are consistent with expectations. Therefore, commercial sperm DFI quality control products can effectively simulate sperm DNA damage to achieve sperm DNA integrity detection and can evaluate and control reagents and operations [23].Figure 2
Commercial sperm DFI quality control product testing diagram.


### 3.2. Daytime Stability

The test results of commercial sperm DFI quality control products and laboratory-made sperm quality control products for 30 days of continuous testing are shown in Figure3. Calculating the sperm DNA fragmentation index and the 30-day CV value, respectively, the test results of commercial sperm DFI quality control products (DFI is 38.20% ± 0.5%; CV is 2.47%) are better than those of laboratory self-made sperm quality control products (DFI is 38.10% ± 0.5%; CV is 11.22%).Figure 3
Daytime stability of commercial sperm DFI quality control products and self-made DFI quality control products.The preliminary reasons for the large fluctuations in laboratory-made sperm quality control products are as follows: (1) Sperm samples require high storage conditions, which are caused by improper control of storage conditions (freezing process and freezing conditions maintenance). (2) After the self-made quality control product is frozen and stored, the sperm DNA damage is caused by the thawing process (time and temperature), and the deviation is caused by the uneven operation. (3) The sample preparation process is cumbersome and lacks quality control links, uniformity is difficult to guarantee, and errors are prone to occur, resulting in large fluctuations in test results [24].Furthermore, cosine analysis is used to check whether the time distribution of DFI conforms to the cosine curve. The amplitude of the fitted cosine curve is 8.4%, the phase is −330, and this shows that the activity level of commercial sperm DFI quality control products is stable during the day, as shown in Figure4. Among them, the curve has a large dynamic range and does not fit well, indicating that the correlation is not particularly strong.Figure 4
Sperm DIF activity level.


### 3.3. Precision

Calculate the average value of the sperm DNA fragmentation index of 3 batches of commercial sperm DFI quality control products and make a histogram. The results are shown as follows. The test results of the first batch of DFI conformed to 38.20% ± 0.5% and CV ≤ 3.16%. The test results of the second batch of DFI conformed to 38.20% ± 0.5% and CV ≤ 0.66%. The third batch of DFI test results meets 38.20% ± 0.5% and CV ≤ 1.76%. If the DFI target values of the three batches of quality control reagents are the same, the CV between the three batches of quality control products needs to be further calculated to prove the stability of the interbatch quality control products of the same detection system (DFI reagents, FCM, and operating procedures). All comply with the manufacturer’s declaration, as shown in Figure5.Figure 5
Interlot precision of commercial sperm DFI quality control products.


### 3.4. Sperm Quality Difference between RMC Population and MARHCS Population

Semen samples from the RMC population were collected from 7 am to 11 am, and semen samples from the MARHCS population were collected from 8 am to 20 pm. The characteristics of the population are described in Table2. The problem of sperm DFI can be explained by analyzing the difference in sperm quality of the population.Table 2
Population characteristics table.
VariablesRMCMARHCSnTotal DFI%nTotal DFI%Age, years1036233 (30, 38)63021 (21, 22)Abstinence period, days107524 (3,5)6304 (3, 5)In the MARHCS population data, changes in sperm DFI over time were also found, as shown in Table3.Table 3
Single-factor analysis of sperm DFI.
Ejaculation time pointRMCMARHCSnValuenValueP-inequivalence<0.0010.131<0.0010.012P-trend<0.0010.028<0.0010.335In order to illustrate a relationship with time more intuitively, as shown in Figure6, the sperm is in the day, from 8 am to 8 pm. At eleven o’clock, the absolute difference is the smallest, which means that the fragmentation rate becomes smaller at this time.Figure 6
Absolute difference of sperm.In order to illustrate the correlation, we used different cpg points for correlation analysis, and the principle is as follows: the total signal (M+U) of each cpg site of each sample is compared with the background signal, and theP value can be obtained. It is generally believed that a lower P value indicates that the site is more reliable. A cpg site with a P value greater than 0.01 is a site with relatively poor quality, and the results are shown in Figures 7 and 8.Figure 7
The correlation between the methylation level of cpg4 and the sperm DFI.Figure 8
The correlation between the methylation level of cpg20 and the sperm DFI.It is obvious from the comparison between Figures7 and 8 that each data point of the methylation level at the cpg20 point is near the potential line. However, the methylation level at the cpg4 point has a higher degree of dispersion between points, which can indicate that the methylation level at the cpg20 point has the highest correlation with the sperm DFI.


### 3.5. Key Operating Techniques

#### 3.5.1. Test Results of Different B Liquid Acid Denaturation Reagents

In the use of standard B solution, the complete DNA and fragmented DNA on the scatter chart of commercial sperm DFI quality control products are in the preset fixed circle gate, and the position of the circle gate is constant with the built-in reference in the relative coordinate system (as shown in the upper left of Figure9). Under the other different B liquid conditions, the intact DNA and fragmented DNA of the commercial sperm DFI quality control products deviate from the preset fixed circle gate, as shown in detail in Figure 9. Liquid B is 0.2X, 2X, and 3X from left to right. It can be seen that the commercial sperm DFI quality control product has the function of controlling whether the acid denaturation reagent of the staining solution is correct.Figure 9
Commercial sperm DFI quality control product B liquid quality control.


#### 3.5.2. Test Results of Dyeing Solutions of Different Concentrations

In the use of standard C solution, the complete DNA and fragmented DNA on the scatter chart of commercial sperm DFI quality control products are in the preset fixed circle gate, and the position of the circle gate is constant relative to the built-in reference product (as shown in the upper left of Figure10). Under the other different C solution conditions, the intact DNA and fragmented DNA of commercial sperm DFI quality control products deviated from the preset fixed circle gate, as shown in Figure 10 for details. From left to right are C liquid 0.3X, 0.5X, and 1.67X. It can be found that the acidity of the p3 gate does not change much; only the p2 and p3 circle gates change with the change of acidity. It can be seen that the commercial sperm DFI quality control product has the function of the quality control reagent C solution staining solution.Figure 10
Quality control of liquid C of commercial sperm DFI quality control.


## 3.1. Effectiveness of New Commercial Sperm DFI Quality Control Products

The flow diagram of the new commercial sperm DFI quality control after testing is shown in Figure2. The P1 circle gate (blue part) indicates double-stranded DNA, that is, cell with intact DNA, and the P2 circle gate (red part) indicates DNA-damaged cells. From the results of stream clustering, it can be found that P1 and P2 can be effectively separated, and the calculation process of sperm DFI can be simulated in the same way. Therefore, the commercial sperm DFI quality control product can effectively simulate the DNA damage classification and the calculation of the fragment index for the DNA integrity test of the sperm sample. P3 (purple part) and P4 (orange part) are built-in reference products, which can be used for internal control calculation and the relative position of P1 and P2 circle gate, operation process interference, and reagent effectiveness evaluation; as you can see in Figure 2, all indicators are consistent with expectations. Therefore, commercial sperm DFI quality control products can effectively simulate sperm DNA damage to achieve sperm DNA integrity detection and can evaluate and control reagents and operations [23].Figure 2
Commercial sperm DFI quality control product testing diagram.


## 3.2. Daytime Stability

The test results of commercial sperm DFI quality control products and laboratory-made sperm quality control products for 30 days of continuous testing are shown in Figure3. Calculating the sperm DNA fragmentation index and the 30-day CV value, respectively, the test results of commercial sperm DFI quality control products (DFI is 38.20% ± 0.5%; CV is 2.47%) are better than those of laboratory self-made sperm quality control products (DFI is 38.10% ± 0.5%; CV is 11.22%).Figure 3
Daytime stability of commercial sperm DFI quality control products and self-made DFI quality control products.The preliminary reasons for the large fluctuations in laboratory-made sperm quality control products are as follows: (1) Sperm samples require high storage conditions, which are caused by improper control of storage conditions (freezing process and freezing conditions maintenance). (2) After the self-made quality control product is frozen and stored, the sperm DNA damage is caused by the thawing process (time and temperature), and the deviation is caused by the uneven operation. (3) The sample preparation process is cumbersome and lacks quality control links, uniformity is difficult to guarantee, and errors are prone to occur, resulting in large fluctuations in test results [24].Furthermore, cosine analysis is used to check whether the time distribution of DFI conforms to the cosine curve. The amplitude of the fitted cosine curve is 8.4%, the phase is −330, and this shows that the activity level of commercial sperm DFI quality control products is stable during the day, as shown in Figure4. Among them, the curve has a large dynamic range and does not fit well, indicating that the correlation is not particularly strong.Figure 4
Sperm DIF activity level.


## 3.3. Precision

Calculate the average value of the sperm DNA fragmentation index of 3 batches of commercial sperm DFI quality control products and make a histogram. The results are shown as follows. The test results of the first batch of DFI conformed to 38.20% ± 0.5% and CV ≤ 3.16%. The test results of the second batch of DFI conformed to 38.20% ± 0.5% and CV ≤ 0.66%. The third batch of DFI test results meets 38.20% ± 0.5% and CV ≤ 1.76%. If the DFI target values of the three batches of quality control reagents are the same, the CV between the three batches of quality control products needs to be further calculated to prove the stability of the interbatch quality control products of the same detection system (DFI reagents, FCM, and operating procedures). All comply with the manufacturer’s declaration, as shown in Figure5.Figure 5
Interlot precision of commercial sperm DFI quality control products.


## 3.4. Sperm Quality Difference between RMC Population and MARHCS Population

Semen samples from the RMC population were collected from 7 am to 11 am, and semen samples from the MARHCS population were collected from 8 am to 20 pm. The characteristics of the population are described in Table2. The problem of sperm DFI can be explained by analyzing the difference in sperm quality of the population.Table 2
Population characteristics table.
VariablesRMCMARHCSnTotal DFI%nTotal DFI%Age, years1036233 (30, 38)63021 (21, 22)Abstinence period, days107524 (3,5)6304 (3, 5)In the MARHCS population data, changes in sperm DFI over time were also found, as shown in Table3.Table 3
Single-factor analysis of sperm DFI.
Ejaculation time pointRMCMARHCSnValuenValueP-inequivalence<0.0010.131<0.0010.012P-trend<0.0010.028<0.0010.335In order to illustrate a relationship with time more intuitively, as shown in Figure6, the sperm is in the day, from 8 am to 8 pm. At eleven o’clock, the absolute difference is the smallest, which means that the fragmentation rate becomes smaller at this time.Figure 6
Absolute difference of sperm.In order to illustrate the correlation, we used different cpg points for correlation analysis, and the principle is as follows: the total signal (M+U) of each cpg site of each sample is compared with the background signal, and theP value can be obtained. It is generally believed that a lower P value indicates that the site is more reliable. A cpg site with a P value greater than 0.01 is a site with relatively poor quality, and the results are shown in Figures 7 and 8.Figure 7
The correlation between the methylation level of cpg4 and the sperm DFI.Figure 8
The correlation between the methylation level of cpg20 and the sperm DFI.It is obvious from the comparison between Figures7 and 8 that each data point of the methylation level at the cpg20 point is near the potential line. However, the methylation level at the cpg4 point has a higher degree of dispersion between points, which can indicate that the methylation level at the cpg20 point has the highest correlation with the sperm DFI.


## 3.5. Key Operating Techniques

### 3.5.1. Test Results of Different B Liquid Acid Denaturation Reagents

In the use of standard B solution, the complete DNA and fragmented DNA on the scatter chart of commercial sperm DFI quality control products are in the preset fixed circle gate, and the position of the circle gate is constant with the built-in reference in the relative coordinate system (as shown in the upper left of Figure9). Under the other different B liquid conditions, the intact DNA and fragmented DNA of the commercial sperm DFI quality control products deviate from the preset fixed circle gate, as shown in detail in Figure 9. Liquid B is 0.2X, 2X, and 3X from left to right. It can be seen that the commercial sperm DFI quality control product has the function of controlling whether the acid denaturation reagent of the staining solution is correct.Figure 9
Commercial sperm DFI quality control product B liquid quality control.


### 3.5.2. Test Results of Dyeing Solutions of Different Concentrations

In the use of standard C solution, the complete DNA and fragmented DNA on the scatter chart of commercial sperm DFI quality control products are in the preset fixed circle gate, and the position of the circle gate is constant relative to the built-in reference product (as shown in the upper left of Figure10). Under the other different C solution conditions, the intact DNA and fragmented DNA of commercial sperm DFI quality control products deviated from the preset fixed circle gate, as shown in Figure 10 for details. From left to right are C liquid 0.3X, 0.5X, and 1.67X. It can be found that the acidity of the p3 gate does not change much; only the p2 and p3 circle gates change with the change of acidity. It can be seen that the commercial sperm DFI quality control product has the function of the quality control reagent C solution staining solution.Figure 10
Quality control of liquid C of commercial sperm DFI quality control.


## 3.5.1. Test Results of Different B Liquid Acid Denaturation Reagents

In the use of standard B solution, the complete DNA and fragmented DNA on the scatter chart of commercial sperm DFI quality control products are in the preset fixed circle gate, and the position of the circle gate is constant with the built-in reference in the relative coordinate system (as shown in the upper left of Figure9). Under the other different B liquid conditions, the intact DNA and fragmented DNA of the commercial sperm DFI quality control products deviate from the preset fixed circle gate, as shown in detail in Figure 9. Liquid B is 0.2X, 2X, and 3X from left to right. It can be seen that the commercial sperm DFI quality control product has the function of controlling whether the acid denaturation reagent of the staining solution is correct.Figure 9
Commercial sperm DFI quality control product B liquid quality control.


## 3.5.2. Test Results of Dyeing Solutions of Different Concentrations

In the use of standard C solution, the complete DNA and fragmented DNA on the scatter chart of commercial sperm DFI quality control products are in the preset fixed circle gate, and the position of the circle gate is constant relative to the built-in reference product (as shown in the upper left of Figure10). Under the other different C solution conditions, the intact DNA and fragmented DNA of commercial sperm DFI quality control products deviated from the preset fixed circle gate, as shown in Figure 10 for details. From left to right are C liquid 0.3X, 0.5X, and 1.67X. It can be found that the acidity of the p3 gate does not change much; only the p2 and p3 circle gates change with the change of acidity. It can be seen that the commercial sperm DFI quality control product has the function of the quality control reagent C solution staining solution.Figure 10
Quality control of liquid C of commercial sperm DFI quality control.


## 4. Discussion

### 4.1. Current Problems

Flow cytometry is a novel and rapid tool for analyzing sperm integrity and DNA fragmentation. It is widely used in medical research and clinical diagnosis in the field of reproduction [25]. Many hospitals have successively launched sperm DFI testing projects. There are more than 10 DFI reagent providers on the market in China, and the test exceeds 40,0000 cases per year. However, the biggest problem currently faced by andrology laboratories is the difference in test results, which brings some uncertainty to clinical diagnosis [26]. For example, 15 laboratories in the United Kingdom counted the same semen specimens in the early days, and the results showed that the percentage of normal sperm in each laboratory ranged from 12% to 80%. The main reason is the lack of quality assurance measures for semen analysis, such as the lack of standardized operating procedures, the lack of corresponding quality control products, and the lack of quality control institutions to monitor the quality of semen analysis [27].


### 4.2. Status of Traditional Quality Control Products

How to solve the thorny problem of quality control, many scholars have focused on the exploration of establishing different quality control products. The sperm in the semen is recycled, and other processes are made to make sperm quality control products and conduct indoor quality control testing for no less than 7 months. The results showed that the CV of the DFI test results of sperm quality control products at about 5 months was less than 15%. iGnsb Ginsburg KA tried standard latex beads as quality control products for indoor quality control of sperm density counting [28]. But there is a certain gap from the ideal quality control products. The composition of the quality control product should be similar to or the same as the composition of the patient sample. The quality control product should be uniform and stable and can give a reminder of the result that exceeds the control limit when there is an error in the analysis process. At present, the self-made DFI quality control products in the laboratory cannot meet the above requirements, and at the same time, they cannot meet the needs of interchamber quality control, which severely limits the clinical application of sperm DNA integrity detection technology [29].


### 4.3. Overview

In this study, Celula provided commercial sperm DFI quality control products containing single-stranded and double-stranded simulated cells and the scattered dots of single-stranded DNA were scattered, which can effectively simulate the gradual development process of sperm DNA damage. At the same time, the concentration of acidification solution and staining solution and whether the sample addition operation is qualified can be indicated through the scattered circle gate, and the quality of the reagent and the test operation process can be controlled [30]. Compared with the sperm quality control products used in various laboratories (laboratory self-made quality control products), it has 4 obvious advantages: (1) Storing at 2–8°C, it is easier to manage and store. (2) The test results of continuous testing for 30 days show that the CV of commercial sperm DFI quality control products is much smaller than that of laboratory self-made DFI quality control products, which has a better stability. (3) The interbatch precision shows that the CV of commercial sperm DFI quality control products is ≤6%. However, laboratory-made quality control products use different sperm samples, and the uniformity of the cells in the samples is different, which is more likely to cause intra-assay and interassay variability. (4) In addition, laboratory-made quality control products involve human genetic samples, which have many potential ethical and other risks and cannot be used for external quality control.


### 4.4. Insufficient Essential Controls

The raw materials of commercial sperm DFI quality control products are derived from animal cells. It is considered that the damaged DNA is processed and then mixed with intact DNA cells in proportion to simulate real sperm samples. Therefore, commercial sperm DFI quality control products are mainly used to simulate sperm DNA damage, and it is currently impossible to simulate and control the high DNA stainability index (HDS). But in any case, the quality control products provided by Celula break the gap of quality control products for sperm DNA integrity testing, allowing clinical testing laboratories and rooms to have stable and reliable quality control products to choose from. It needs more data to support its clinical application value.


## 4.1. Current Problems

Flow cytometry is a novel and rapid tool for analyzing sperm integrity and DNA fragmentation. It is widely used in medical research and clinical diagnosis in the field of reproduction [25]. Many hospitals have successively launched sperm DFI testing projects. There are more than 10 DFI reagent providers on the market in China, and the test exceeds 40,0000 cases per year. However, the biggest problem currently faced by andrology laboratories is the difference in test results, which brings some uncertainty to clinical diagnosis [26]. For example, 15 laboratories in the United Kingdom counted the same semen specimens in the early days, and the results showed that the percentage of normal sperm in each laboratory ranged from 12% to 80%. The main reason is the lack of quality assurance measures for semen analysis, such as the lack of standardized operating procedures, the lack of corresponding quality control products, and the lack of quality control institutions to monitor the quality of semen analysis [27].


## 4.2. Status of Traditional Quality Control Products

How to solve the thorny problem of quality control, many scholars have focused on the exploration of establishing different quality control products. The sperm in the semen is recycled, and other processes are made to make sperm quality control products and conduct indoor quality control testing for no less than 7 months. The results showed that the CV of the DFI test results of sperm quality control products at about 5 months was less than 15%. iGnsb Ginsburg KA tried standard latex beads as quality control products for indoor quality control of sperm density counting [28]. But there is a certain gap from the ideal quality control products. The composition of the quality control product should be similar to or the same as the composition of the patient sample. The quality control product should be uniform and stable and can give a reminder of the result that exceeds the control limit when there is an error in the analysis process. At present, the self-made DFI quality control products in the laboratory cannot meet the above requirements, and at the same time, they cannot meet the needs of interchamber quality control, which severely limits the clinical application of sperm DNA integrity detection technology [29].


## 4.3. Overview

In this study, Celula provided commercial sperm DFI quality control products containing single-stranded and double-stranded simulated cells and the scattered dots of single-stranded DNA were scattered, which can effectively simulate the gradual development process of sperm DNA damage. At the same time, the concentration of acidification solution and staining solution and whether the sample addition operation is qualified can be indicated through the scattered circle gate, and the quality of the reagent and the test operation process can be controlled [30]. Compared with the sperm quality control products used in various laboratories (laboratory self-made quality control products), it has 4 obvious advantages: (1) Storing at 2–8°C, it is easier to manage and store. (2) The test results of continuous testing for 30 days show that the CV of commercial sperm DFI quality control products is much smaller than that of laboratory self-made DFI quality control products, which has a better stability. (3) The interbatch precision shows that the CV of commercial sperm DFI quality control products is ≤6%. However, laboratory-made quality control products use different sperm samples, and the uniformity of the cells in the samples is different, which is more likely to cause intra-assay and interassay variability. (4) In addition, laboratory-made quality control products involve human genetic samples, which have many potential ethical and other risks and cannot be used for external quality control.


## 4.4. Insufficient Essential Controls

The raw materials of commercial sperm DFI quality control products are derived from animal cells. It is considered that the damaged DNA is processed and then mixed with intact DNA cells in proportion to simulate real sperm samples. Therefore, commercial sperm DFI quality control products are mainly used to simulate sperm DNA damage, and it is currently impossible to simulate and control the high DNA stainability index (HDS). But in any case, the quality control products provided by Celula break the gap of quality control products for sperm DNA integrity testing, allowing clinical testing laboratories and rooms to have stable and reliable quality control products to choose from. It needs more data to support its clinical application value.


## 5. Conclusions

This paper focuses on the technical evaluation of commercial sperm DFI quality control products in SCSA detection. The commercial sperm DFI quality control products can simulate sperm DNA damage to achieve accurate detection of DNA integrity; the new commercial sperm DFI quality control product can sensitively respond to changes in the concentration of acidification solution and staining solution at the same time and can effectively control the detection reagents and experimental procedures. The new commercial sperm DFI quality control product can effectively control the sperm DNA integrity test and can be used as an external quality control product to control the test results to ensure that more accurate test results are provided to the clinic.



---

*Source: 9552123-2022-03-04.xml*