Figure 1.
Distribution of cystatin C in human body fluids.
This study investigated the effect of Industrialization on carbon emissions through energy consumption for a panel of eight Organization of the Petroleum Exporting Countries (OPEC) and nine High Industrialised Countries over the period 1985 to 2020; the study employs the first generation and second-generation Unit root tests. The study further adopts the use of the Panel Autoregressive Distributed Lag Model, and Common Correlated Effect pooled mean group to estimate the parameters of the model for OPEC countries and High Industrialised Countries, respectively. In addition, the Dumitrescu-Hurlin Granger causality test is conducted to infer the direction of causality among the variables. The causality test result reveals that, in OPEC, energy consumed during industrial activity is not enough to cause carbon emission and carbon emission does not cause industrialisation to interact with energy consumption. Also, for highly industrialised countries, interaction of energy consumption and industrialization causes carbon emission, but carbon emission does not cause the interaction of energy consumption and industrialization. The estimated model shows that the interactive effect of Industrialization and energy consumption has no significant influence on carbon emissions in OPEC countries in the short and long run. In contrast, foreign direct investment and economic growth have a positive and significant effect on carbon emissions in the short run. However, for highly industrialised countries the study found that the interactive effect of energy industrialization and energy consumption has a positive and significant effect on carbon emissions in the short run. It is apparent from the study that energy consumption for industrial activities, particularly in highly industrialised countries, causes carbon emission and such policy makers should formulate policy that necessitate the use of green energy for industrial activities to improve environmental quality.
Citation: Ayodele Idowu, Obaika Micheal Ohikhuare, Munem Ahmad Chowdhury. Does industrialization trigger carbon emissions through energy consumption? Evidence from OPEC countries and high industrialised countries[J]. Quantitative Finance and Economics, 2023, 7(1): 165-186. doi: 10.3934/QFE.2023009
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This study investigated the effect of Industrialization on carbon emissions through energy consumption for a panel of eight Organization of the Petroleum Exporting Countries (OPEC) and nine High Industrialised Countries over the period 1985 to 2020; the study employs the first generation and second-generation Unit root tests. The study further adopts the use of the Panel Autoregressive Distributed Lag Model, and Common Correlated Effect pooled mean group to estimate the parameters of the model for OPEC countries and High Industrialised Countries, respectively. In addition, the Dumitrescu-Hurlin Granger causality test is conducted to infer the direction of causality among the variables. The causality test result reveals that, in OPEC, energy consumed during industrial activity is not enough to cause carbon emission and carbon emission does not cause industrialisation to interact with energy consumption. Also, for highly industrialised countries, interaction of energy consumption and industrialization causes carbon emission, but carbon emission does not cause the interaction of energy consumption and industrialization. The estimated model shows that the interactive effect of Industrialization and energy consumption has no significant influence on carbon emissions in OPEC countries in the short and long run. In contrast, foreign direct investment and economic growth have a positive and significant effect on carbon emissions in the short run. However, for highly industrialised countries the study found that the interactive effect of energy industrialization and energy consumption has a positive and significant effect on carbon emissions in the short run. It is apparent from the study that energy consumption for industrial activities, particularly in highly industrialised countries, causes carbon emission and such policy makers should formulate policy that necessitate the use of green energy for industrial activities to improve environmental quality.
Cystatin C, an inhibitor of cysteine proteases, acts on the lysosomal system to regulate the activity of a variety of protein hydrolases. Under oxidative stress, cystatin C significantly promotes cell survival: it strongly inhibits histone protease activity, protects the stability of intracellular membrane structures, promotes autophagy and prolongs cell life by modulating molecular signaling pathways. The structure of cystatin C can inhibit the enzyme of certain proteins, he shows the re-stacking composition of the protein, and can maintain the original structure. Dimerization can undergo structural changes, resulting in a single protein structure. Cystatin C is gradually dimerizing, and it will endanger human health, especially the elderly. Aggregates can be obtained in other ways, and their unfolded molecules are infinite [1]. Cystatin C is an essential glycosylated protein produced at a constant rate by all nucleated cells tested. It is freely filtered through the glomerulus and catabolized primarily in the renal tubules (it is not excreted or absorbed intact). Serum cystatin C is an indicator of increased glomerular filtration rate (GFR) relative to serum creatinine because it is independent of age, sex, and muscle mass. Cystatin C is different from other GFR. By comparison, we found that the concentration of cystatin C is more flexible and sensitive than other GFR markers [2]. Serum cystatin C concentration was inversely correlated with glomerular filtration rate, as or better than serum creatinine, indicating that it is continuously formed and cleared as the main source of extracellular fluid. But based on the data we know now; it is not known how well the GFR matches it [3]. We have demonstrated that serum cystatin C measurement is a more selective change indicator. But we now know very little about cystatin C concentrations is still sparse. Therefore, our main subjects are adults. We draw blood from volunteers participating in the experiment, and then measure the concentration of cystatin and creatinine. When people are under the age of 50, nearly 90% of people have cystatin C in the range of 0.51–0.93 m [4].
At present, we know that if the kidney function of an older person has problems, then his lifespan will be affected. It happens that cystatin C can prevent related problems, solve problems related to kidney function, and prolong the life of the elderly. This has a very important development guide for the future of medicine [5]. After the brain is injured, other diseases will occur one after another, and serious damage to the nerves will occur. We know that the related anti-cancer genes can help the nerves in the brain recover faster and slow down the damage to the brain after brain injury, but we don't know how it is done yet. Western blot and immunohistochemical's data and analysis of PIDD can let us know that PIDD will slowly increase after brain damage, and then slowly decrease again. And the place with the most PIDD is in the neuron [6]. We found several chemical mediators in the rat brain, which are formed as a result of cerebral edema. We carried out experiments on rats, put the rats in a high temperature environment, and then extracted brain tissue from the rats after brain injury, and examined the brain edema of the rats and the changes in some cells. Indomethacin and other drugs can slow down brain damage in rats to varying degrees. Experiments have also shown that brain damage caused by high temperature is very complex and only related to nerves [7]. After rat brain injury, by extracting rat brain tissue, it was found that IL-1 can share the use of molecules with the rat brain tissue extract. After brain injury in rats, IL-1 becomes very active and reproduces very quickly, which can help the rapid production of antibodies in rats, which can restore brain injury in rats, an important role in cell repair after injury [8].
Recent evidence suggests that progesterone treatment attenuates rats and can cause many other diseases after brain injury, but we don't know whether it is related to age, so we experimented with old rats, let them receive the vehicle, and exercised to observe the recovery. And two days later, the degree of cerebral edema was checked, and it was found that the symptoms of the treated rats were alleviated. It was also shown to reduce apoptosis, reduce swelling and improve exercise performance over time in the 16 mg/kg group [9]. At present, the main discussion of brain injury caused by ischemia is the toxicity of calcium. According to previous reports, although it is known that calcium can protect animals with from ischemia, experiments have not been able to prove this point of view. Protein blocks calcium from passing through. channel, but this can also keep the amount of calcium in a balanced state [10]. So far, the temperature of the earth has been gradually rising every year, and it will increase at a faster rate in the future, which is a cause for concern and a very serious problem. Plants experience fluctuations in ambient temperature, and many animals are warm-blooded animals, their life and metabolism are closely related to temperature, and they can control their own temperature. Therefore, as the global temperature increases, the impact on plants will be more obvious, and they will suffer very serious damage. It is estimated that crop yields decrease by 17% for every 1 ℃ increase in average growing season temperature [11]. Adaptation of livestock to high ambient temperatures often results in lower yields as animals reduce their metabolic rate and feed intake to accommodate the increased heat load. Ideally, one would like to select both increased yield and thermal resistance to increased thermal loads. This will require both identification and selection to improve heat dissipation and production mechanisms [12]. To judge whether an animal can withstand high temperatures, the environment and details of the experiment are very important. In the experiment, if the animal is directly placed in a high temperature environment, the experimental results are not very accurate, because it is ignored that under normal circumstances, the temperature is gradually increased. As a result, the experimental environment is different from the real ecological environment, and when the temperature gradually increases, the animals endure the high temperature for a significantly longer time. Flies exposed to faster rates are more tolerant to heat knockdown [13].
In our daily life, in our living environment, the temperature is an unavoidable problem, so the relevant experimental data and reports about high temperatures are very important, such as continuous high temperature exposure experiments. In order to complete related experiments, many rapid heating methods have been invented, such as heating with a fire source, heating with hot water, or heating by wrapping the human body. It is to know the relationship between the change in temperature and the time its temperature lasts. Normally, the higher the temperature and the longer the time, the stronger the animal's response. Therefore, it can be proved that the longer the high temperature exposure time, the more serious the damage caused by the high temperature will be due to high temperature and adrenocorticotropic hormone on the content of ascorbic acid glands of guinea pigs, rabbits and albino rats were studied [14]. When an animal is suddenly placed in a warmer place, there is less ascorbic acid in the animal's liver and other organs, but gradually returned to a normal level in the following 24 hours. Only a few percent are found in the liver, kidneys, and spleen. Though the high temperature, the rate of decline in adrenal is reduced to a lower degree, which may be due to the animal's acclimation or adaptation to the high temperature environment [15]. Cystatin C exhibits variability in different organisms, with somatic expression in response to temperature in animals in different environments. Cystatin C has very limited effect and unsatisfactory efficacy in the expression of cystatin C in brain injury in rats. Therefore, the search for effective prevention and treatment methods to reduce the occurrence of cerebral ischemic injury, alleviate post-ischemic neurological dysfunction and promote its clinical application is a challenge that needs to be addressed.
Cystatin C, a member of the cystatin superfamily, is a secreted protein. Genes are domestic genes. Cystatin C synthesis is not tissue-specific, all eukaryotic cells express and still secrete cystatin C. Cystatin C is present in the body fluids of the human body and will not be affected by other causes. Cystatin C is mainly metabolized in the kidney, where it is almost completely filtered by the glomerulus and absorbed and completely degraded in the proximal tubule. The kidney is the only organ that removes cystatin C from the circulation, so the level of cystatin C in serum primarily determines GFR. Cystatin C can be considered as an endogenous substance reflecting ideal GFR. The humoral cystatin C in normal adults is shown in Figure 1.
The relative molecular weight of cystatin C is 13,400, its component is nitrogenous acid, and there are 120, cystatin C is a basic secreted protein. The nuclei throughout the human body can synthesize and secrete cystatin C, which is mainly found in extracellular fluids, including cerebrospinal fluid, blood, sperm, and other human body fluids, including cerebrospinal fluid and cerebrospinal fluid. It is also expressed in other cells such as neurons. More than 99% of cystatin C in the human body is freely filtered through the glomerulus and reabsorbed into renal tubular epithelial cells for degradation, so that almost all cystatin C is metabolized in the kidneys.
Cystatin C exists in the cells and body fluids of humans and other mammals, and can help organisms carry out normal physiological activities. Cystatin C controls the rate of proteolysis inside and outside the cell. Studies have shown that cystatin C participates in cell proliferation and differentiation by regulating the activity of intracellular lysosomal cathepsins, regulating the synthesis and metabolism of intracellular proteins, and participating in biological activities by supporting the digestion and metabolism of viruses and bacteria by immune system cells. Antiviral and antibacterial activity; acts on TGF-β receptors in positive cells and tumor cells, inhibits TGF-β signaling pathway, inhibits its binding activity, and participates in the proliferation and metastasis of tumor cells; regulates cathepsin K and participates in the decomposition of bone matrix and absorption.
1) Neuroprotection: The addition of exogenous cystatin C to cell culture media increases cell viability under stress and decreases cell viability up to a range of concentrations. Cytotoxic damage, such as energy consumption and oxidative stress, significantly increases cell survival. 2) Protection of cerebrovascular: According to existing research, cystatin C may cause diseases related to cerebrovascular. When the gene for cystatin C is mutated, the walls of blood vessels in the brain can become blocked, causing blood vessels to rupture and bleed, leading to fatal strokes in early life. This type of stroke is called hereditary vascular disease, amyloid cystatin C. The increased amyloid activity of cysteine C increases the production of amyloid fragments in brain tissue, which can cause atherosclerosis, while cystatin C slows and prevents atherosclerosis. Studies have shown that serum cystatin C levels in patients with atherosclerosis are inversely correlated with disease severity. Cystatin C plays a very important role in the formation and development of atherosclerosis. Some researchers have suggested that the change of serum cystatin C concentration may become a benchmark for the diagnosis of acute myocardial infarction and stroke to a certain extent. However, some clinical studies have shown that higher serum cystatin C levels are associated with higher mortality and cardiovascular disease in the elderly, suggesting that excessive cystatin C levels may have adverse effects on the cerebrovascular system.
When the body temperature exceeds 41 ℃. The human body will have a high fever, accompanied by obvious symptoms such as seizures, coma, shock, and bleeding. Elevated body temperature will speed up metabolism, increase the decomposition of substances, generate more heat, and form a vicious circle. If body temperature exceeds 41 ℃, cells in the body's solid organs, especially brain cells, may degenerate, leading to seizures, convulsions, coma, heart failure and respiratory failure. Some enzymes may become inactive, causing permanent damage to brain cells, and leading to death.
Cystatin C detection methods are divided into two types: heterogeneous detection and homogeneous detection. Heterogeneous detection includes single immunodiffusion (SRID), enzyme immunoassay (ELISA), radioimmunoassay (RIA) and fluorescence immunoassay (FIA) four detection methods; homogeneous detection includes particle counting immunoassay, immunotransmission turbidimetry (PETIA) and immune nephelometry (PENIA) three detection methods. Heterogeneous detection is complicated and time-consuming, and it is inconvenient to be used in clinical practice. Homogeneous detection has a strong advantage in time, and is not easily interfered by other factors, and at the same time, the recovery rate of homogeneous detection is high. The comparison of detection methods of cystatin C is shown in Figure 2.
Typical cystatin C sensor acquisition systems use photodetectors for signal conversion, so the received signal is very weak. To ensure accurate results, many processing circuits, such as differential amplifiers, are designed in hardware. To ensure accuracy, in terms of software, the average filtering algorithm is designed in hardware. Mediation is used to remove the influence of uncontrolled factors such as the environment on the outcome. The wavelet thresholding method is also used to align the measurement results so that the measurement value is closer to the true value. The steps and structure of the acquisition system of the cystatin C detection instrument are shown in Figure 3.
When the light beam passes through the cuvette containing the suspension, the relationship between the intensity of the transmitted light and the intensity of the incident light will be attenuated to a certain extent due to the absorption and attenuation of the medium itself. As shown in the following formula.
| IT=I0e−(a+s)l | (1) |
| IT=(I0IT)=A=ln(α+s)l | (2) |
If the definition of A in the formula (1) is the absorbance of the suspension, then.
| A=log(V0VT) | (3) |
The accuracy and bias for the test can be calculated using the following equations.
| r=∑[(xi−x)(yi−y)]√(xi−x)(yi−y)2 | (4) |
| B=M−TT×100% | (5) |
When the reaction in the test tube progresses to a certain extent, it will no longer change. At this time, if the diameter of the particles in the test tube is larger than the wavelength of the light emitted by the light source, the light signal emitted by the light source will be weakened. The measured particles show a certain functional relationship, and the content of the sample to be tested is calculated through the functional relationship, so it is also called turbidimetry. The expression is as follows:
| I=I0e−τb | (6) |
where I represents the transmitted light intensity, I0 represents the incident light intensity, b represents the optical diameter, and τ represents the turbidity. The value of I depends on b, and the larger the value of b, the smaller the value of I.
A relationship like Beer's law can be obtained from the above formula:
| log10p0/p=kbc | (7) |
Since the particles in the reagent are very small, when the scattering phenomenon occurs, the magnitude of the light intensity satisfies Rayleigh's law:
| IS=9π2λ4r2(n22−n21n22−2n21)υ2NI0(1+cos2θ2) | (8) |
Its simplified form is defined.
| IS=KNI0 | (9) |
When the particle size is smaller than the incident wavelength, the relationship between the scattered light intensity of a single particle and the scattering angle θ can be expressed by the following formula.
| I(θ)=I09π2v2λ4r2(n22−n21n22+2n21)2(1+cos2θ2) | (10) |
It is assumed that the scattering of different particles does not cancel each other and that the intensities of light scattered by the particles may overlap. At this time, the sum of the scattered light intensity N of the particles per unit volume can be taken as N times the scattered light intensity of a single particle, which can be expressed as:
| I(θ)=NI09π2v2λ4r2(n22−n21n22+2n21)2(1+cos2θ2) | (11) |
When viewed in the vertical direction of the incident light, it can be defined as:
| I(90∘)=kNI0 | (12) |
where k is recorded as:
| k=9π2v2λ4r2(n22−n21n22+2n21)2 | (13) |
where k is denoted as the scattering coefficient.
As the particle size increases when the particle size is larger than the wavelength of the incident light, the Rayleigh scattering theory is no longer valid, the proportional relationship between the intensity of the scattered light and the frequency of the incident light no longer exists, it lasts longer, and the intensity of the scattered light is clarified:
| IM=KMANI0 | (14) |
In the formula, IM is defined as the scattered light intensity, KM is defined as the Mie scattering coefficient, and A is defined as the surface area of the scattering source particle. The larger the value of IM, the stronger the intensity of scattered light.
The intensity of the light generated by scattering is proportional to the concentration of the particles, and can be written as:
| IS=KSNIX | (15) |
In the formula, IS is defined as the scattered light intensity, KS is defined as the scattering coefficient, N is the solution concentration, and IX is the incident light intensity. The value of IS determines the value of the entire formula.
The above formula can also be expressed as
| VS=KNV0 | (16) |
According to the Mie scattering theory, the scattered light intensity at a point P in the scattered light field can be written as
| I(r,θ,φ)=λ2I04π2r2[i1(θ)sin2φ+i2(θ)cos2φ] | (17) |
Similarly, the scattering amplitude function is expressed as:
| S1=∑∞n=12n+1n(n+1){anπn(cosθ)+bnτn(cosθ)} | (18) |
| S2=∑∞n=12n+1n(n+1){anτn(cosθ)+bnπn(cosθ)} | (19) |
where an,bn is the Mie scattering coefficient, which is expressed as:
| an=ψn(a)ψ'n(ma)−mψ'n(a)ψn(ma)ξn(a)ψ'n(ma)−mξ'n(a)ψn(ma) | (20) |
| bn=mψn(a)ψ'n(ma)−ψ'n(a)ψn(ma)mξn(a)ψ'n(ma)−ξ'n(a)ψn(ma) | (21) |
And
| πn(cosθ)=P(1)n(cosθ)sinθ | (22) |
| τn(cosθ)=ddθp(1)n(cosθ) | (23) |
Here is the relative refractive index of the cystatin C antigen-antibody immune complex particle and the mixed solution, and the value is about m = 1.25.
| ψn(z)=√πz2Jn+12(z) | (24) |
| ξn(z)=√πz2H(2)n+12(z) | (25) |
In order to further explore the specific situation of high temperature-induced brain injury and the expression and role of cystatin C in high temperature-induced brain injury in rats. We carried out a series of experiments to verify and analyze the effects of high temperatures on rats through the limb performance and brain tissue composition of rats at different temperatures. At the same time, the changes and effects of cystatin C were observed, to further verify and discover the expression and effect of cystatin C in high temperature-induced brain injury in rats.
In this experiment, 84 rats of the same age and weight will be selected from an animal center, and the 84 rats will be randomly divided into groups to verify the content of brain tissue components in different environments. High temperature damage to rat brain tissue. Then grouped, extracted rat brain tissue fluid, and analyzed the changes in brain tissue water content (BWC), Evans Blue (EB) and other components in the rat brain tissue fluid. At the same time, a cystatin C experiment was established. group to observe and study the role of cystatin C in high temperature-induced brain injury.
In the experiment, 54 rats were randomly selected from 84 rats for grouping, 28 rats were randomly selected as the control group, and 28 rats were placed in an incubator for normal activities. Another 28 rats were placed in a high temperature box of 42 degrees, and two groups of rats were placed in the box for 48 hours, and 4 observation time points were set at 12 h, 24 h, 36 h and 48 h. And 14 rats in each group were planned as subgroups for the detection of Evans blue content in brain tissue. After 48 hours, the rats in the two groups were sacrificed, and brain tissue samples were extracted from the rats. For brain water content detection Evans blue content detection, etc. The specific experimental groups and the survival of rats are shown in Table 1.
| Group | Number | Temperature | 12 h Deaths | 24 h Deaths | 36 h Deaths | 48 h Deaths |
| Test group | 28 | 42 ℃ | 0 | 3 | 5 | 10 |
| Subgroup 1 | 14 | 42 ℃ | 0 | 1 | 3 | 4 |
| Control group | 28 | 25 ℃ | 0 | 0 | 0 | 0 |
| Subgroup 2 | 14 | 25 ℃ | 0 | 0 | 0 | 0 |
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During the experiment, we found that the experimental animals in the experimental group became very impatient, and then gradually lost their vitality and even died. During this period, the mice in the experimental group developed eyeball hypertrophy and edema, and some mice developed corneal necrosis. The skull was cut open, and it was found that the brain tissue was edema, cerebral vascular occlusion, meningeal adhesion, enlarged gyri and superficial groove, and the left side was more prominent than the right side. There was no significant change in the control group. The changes in brain water content in rats are shown in Figure 4.
From the data in Figure 4, it can be seen that the brain water content of the rats at 25 ℃ did not change much, but the brain water content of the rats at a high temperature of 42 ℃ gradually increased, which means that at 42 ℃ The metabolism of rats in high temperature is accelerated, which gradually causes hypoxia, which in turn causes cerebral edema, brain tissue swelling, cerebral vascular congestion, cell swelling, vacuolar degeneration, and even necrosis. It shows that high temperature has serious damage to the brain tissue of rats, which can cause serious brain damage.
Compared with the rats in the control group, the Evans blue content in the brain tissue fluid of the rats exposed to a high temperature of 42 ℃ also increased significantly, and became higher and higher as time went on. The specific experimental results are shown in Figure 5.
In this experiment, 84 rats in the experimental materials were randomly divided into three groups, each group was assigned 28 rats, and the three groups were: 1) The control group: 28 rats were placed in a constant temperature of 25 ℃; 2) Control group 2: 28 rats were placed in a high temperature chamber at 42 ℃ without any treatment; 3) Experimental group: 28 rats were placed in a high temperature chamber at 42 ℃, and injected an appropriate amount of cystatin C into the rats.
Two groups of rats were placed in the box for 48 hours, and 4 observation time points were set at 12 h, 24 h, 36 h and 48 h. And 14 rats in each group were planned as subgroups for the detection of Evans blue content in brain tissue. After 48 hours, the rats in the two groups were sacrificed, and brain tissue samples were extracted from the rats. For brain water content detection Evans blue content detection, etc.
After the rats were sacrificed, when the brain water content in the extracted brain tissue fluid was detected, it was found that the brain water content of the experimental group was higher than that of the control group 1, but it significantly decreased compared with the control group 2. This indicated that cystatin C played a significant protective role. The specific experimental data are shown in Figure 6 below.
From the data in Figure 6, it can be seen that the rats in the three groups have the lowest brain water content in the 25 ℃ incubators, and there is not much fluctuation in the brain water content. The highest is the control group 2, indicating that the brain tissue of the rats in the control group 2 has been severely damaged, resulting in brain damage. Although the brain water content of rats in the experimental group was higher than that in experimental group 1, it was significantly decreased compared with the control group 2. This indicates that cystatin C plays a role in protecting the brain tissue of rats from high temperature-induced brain injury.
Compared with the rats in the control group 1, the Evans blue content in the brain tissue fluid of the rats exposed to a high temperature of 42 ℃ also increased significantly, and it became higher and higher with the passage of time. Although the content of Evans blue also increased, it decreased significantly compared with the control group 2. The specific experimental data are shown in Table 2.
| Group | 12 h | 24 h | 36 h | 48 h |
| control group 1 | 3.32 | 3.28 | 3.33 | 3.35 |
| control group 2 | 8.52 | 9.98 | 12.19 | 14.11 |
| test group | 6.24 | 7.68 | 9.82 | 11.95 |
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There are many detection methods for cystatin C. Heterogeneous detection is complicated and time-consuming, which is inconvenient to be used in clinical practice. Homogeneous detection has a strong advantage in time and is not easily interfered by other factors. The advantages of high phase detection recovery rate. We have compared the main common detection methods with the detection methods used in this paper in many aspects. The specific data are shown in Table 3.
| Method | CV | Measurement time | Reference range | shortcoming |
| SRID | 11 | 38 h | 1.3 ± 0.26 | complex operation |
| ELISA | 10–12 | 16 h | 1.1 ± 0.42 | long detection time |
| RIA | none | 16–21 h | 0.96 ± 0.20 | polluted |
| FIA | none | 3 h | none | expensive |
| Method | 3–5 | 5 min | < 1.25 | none |
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In order to further explore the accuracy of the detection method in this paper, we used the algorithm in this paper to repeat the determination of 10 groups of cystatin C solutions with the same concentration at different times, and judged the accuracy of the detection method by the dispersion coefficient. The specific experimental data are shown in Table 4.
| Concentration | Detection times | Mean | Standard Deviation (mg/L) | CV (%) |
| 0.237 | 10 | 0.256 | 0.01025 | 4.003 |
| 0.774 | 10 | 0.795 | 0.03188 | 4.010 |
| 1.363 | 10 | 1.387 | 0.06002 | 4.327 |
| 2.740 | 10 | 2.711 | 0.10586 | 3.905 |
| 5.500 | 10 | 5.516 | 0.21860 | 3.963 |
| 9.650 | 10 | 9.628 | 0.43422 | 4.510 |
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Different cystatin C assays have different accuracy, and accuracy defines whether the assay has outstanding performance and whether it is worthwhile to use. This experiment will verify whether the algorithm in this paper has outstanding performance compared with other traditional methods through comparative experiments. With the increase of cystatin C concentration, the detection method can extract cystatin C more clearly, but the extraction accuracy cannot be guaranteed. In this experiment, three traditional methods and the method in this paper are used to extract and compare cystatin C. The specific experimental results are shown in Figure 7 below.
From the data in Figure 7, it can be seen that the detection method in this paper has higher detection accuracy than other traditional detection methods, and the accuracy gradually increases as the concentration increases, while the accuracy of the traditional detection method is relatively low and does not steadily increase as the concentration increases. This shows that the detection method and algorithm in this paper have extremely high accuracy, which proves that the detection method in this paper has outstanding performance compared with the traditional detection method, and is a more worthwhile detection method for cystatin C.
Whether the detection method has excellent performance is generally judged by the absorbance of the detection method to cystatin C during the detection. The higher the absorbance, the better the performance. In this experiment, the performance of the algorithm was judged by comparing the absorbance of different detection methods in the detection of different concentrations of cystatin C. The specific experimental data is shown in Figure 8 below.
Analysis of the data in Figure 8 in this paper shows that the absorbance of the cystatin C detection method in this paper is higher than that of other traditional detection methods, and it can complete the task better when detecting cystatin C. And the absorbance can be increased stably and efficiently with the increase of the concentration of cystatin C, while other traditional detection methods not only have low absorbance, but also cannot increase stably in the follow-up. This shows that the detection method in this paper has a very strong performance.
Whether the performance of the detection method is excellent, its stability is an important reference point. If the algorithm is very stable and efficient, then the performance of the algorithm is very outstanding. In this experiment, the stability of the algorithm is judged by the stability of the algorithm as the concentration changes when the detection method is detected. And using the standard deviation as a quantitative evaluation index, the experimental results are shown in Table 5.
| Detection Method | Standard Deviation |
| Our Method | 0.005 |
| SRID | 0.036 |
| ELISA | 0.024 |
| RIA | 0.018 |
DownLoad:
CSV
It can be seen from the analysis of the data in Table 5 that the detection method in this paper has the smallest standard deviation, and the SRID method has the largest standard deviation. Since the smaller the standard deviation value, the higher the stability of the algorithm, it proves that the detection method in this paper has better stability and more outstanding performance than other traditional cystatin C detection methods, and is a more worthwhile algorithm to use.
Cystatin C is indispensable in living organisms, it can help evaluate kidney function, and can play a protective role in the brain. In the event of brain injury caused by high temperature, it can reduce the damage to brain tissue and protect the safety of brain tissue. Cystatin C also has a variety of detection methods. With the rapid development of the times, the detection methods of cystatin C are constantly improving. The cystatin C detection method proposed in this paper, combined with the characteristics of modern optoelectronics, enables the detection of cystatin C to be completed more efficiently and accurately. Make high-performance detection methods more worthy of use and promotion. At the same time, the role of cystatin C in brain protection and its clinical application has a very important impact.
This study was supported by grants of the Key Scientific Research Projects of Colleges and Universities of Henan Province in 2019 (No.19A310015)
The authors declare there is no conflict of interest.
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| 1. | Yongfang Zhou, Wentao Dong, Likun Wang, Siying Ren, Weiqing Wei, Guofeng Wu, Cystatin C Attenuates Perihematomal Secondary Brain Injury by Inhibiting the Cathepsin B/NLRP3 Signaling Pathway in a Rat Model of Intracerebral Hemorrhage, 2024, 61, 0893-7648, 9646, 10.1007/s12035-024-04195-4 |
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| Group | Number | Temperature | 12 h Deaths | 24 h Deaths | 36 h Deaths | 48 h Deaths |
| Test group | 28 | 42 ℃ | 0 | 3 | 5 | 10 |
| Subgroup 1 | 14 | 42 ℃ | 0 | 1 | 3 | 4 |
| Control group | 28 | 25 ℃ | 0 | 0 | 0 | 0 |
| Subgroup 2 | 14 | 25 ℃ | 0 | 0 | 0 | 0 |
DownLoad:
CSV
| Group | 12 h | 24 h | 36 h | 48 h |
| control group 1 | 3.32 | 3.28 | 3.33 | 3.35 |
| control group 2 | 8.52 | 9.98 | 12.19 | 14.11 |
| test group | 6.24 | 7.68 | 9.82 | 11.95 |
DownLoad:
CSV
| Method | CV | Measurement time | Reference range | shortcoming |
| SRID | 11 | 38 h | 1.3 ± 0.26 | complex operation |
| ELISA | 10–12 | 16 h | 1.1 ± 0.42 | long detection time |
| RIA | none | 16–21 h | 0.96 ± 0.20 | polluted |
| FIA | none | 3 h | none | expensive |
| Method | 3–5 | 5 min | < 1.25 | none |
DownLoad:
CSV
| Concentration | Detection times | Mean | Standard Deviation (mg/L) | CV (%) |
| 0.237 | 10 | 0.256 | 0.01025 | 4.003 |
| 0.774 | 10 | 0.795 | 0.03188 | 4.010 |
| 1.363 | 10 | 1.387 | 0.06002 | 4.327 |
| 2.740 | 10 | 2.711 | 0.10586 | 3.905 |
| 5.500 | 10 | 5.516 | 0.21860 | 3.963 |
| 9.650 | 10 | 9.628 | 0.43422 | 4.510 |
DownLoad:
CSV
| Detection Method | Standard Deviation |
| Our Method | 0.005 |
| SRID | 0.036 |
| ELISA | 0.024 |
| RIA | 0.018 |
DownLoad:
CSV
| Group | Number | Temperature | 12 h Deaths | 24 h Deaths | 36 h Deaths | 48 h Deaths |
| Test group | 28 | 42 ℃ | 0 | 3 | 5 | 10 |
| Subgroup 1 | 14 | 42 ℃ | 0 | 1 | 3 | 4 |
| Control group | 28 | 25 ℃ | 0 | 0 | 0 | 0 |
| Subgroup 2 | 14 | 25 ℃ | 0 | 0 | 0 | 0 |
| Group | 12 h | 24 h | 36 h | 48 h |
| control group 1 | 3.32 | 3.28 | 3.33 | 3.35 |
| control group 2 | 8.52 | 9.98 | 12.19 | 14.11 |
| test group | 6.24 | 7.68 | 9.82 | 11.95 |
| Method | CV | Measurement time | Reference range | shortcoming |
| SRID | 11 | 38 h | 1.3 ± 0.26 | complex operation |
| ELISA | 10–12 | 16 h | 1.1 ± 0.42 | long detection time |
| RIA | none | 16–21 h | 0.96 ± 0.20 | polluted |
| FIA | none | 3 h | none | expensive |
| Method | 3–5 | 5 min | < 1.25 | none |
| Concentration | Detection times | Mean | Standard Deviation (mg/L) | CV (%) |
| 0.237 | 10 | 0.256 | 0.01025 | 4.003 |
| 0.774 | 10 | 0.795 | 0.03188 | 4.010 |
| 1.363 | 10 | 1.387 | 0.06002 | 4.327 |
| 2.740 | 10 | 2.711 | 0.10586 | 3.905 |
| 5.500 | 10 | 5.516 | 0.21860 | 3.963 |
| 9.650 | 10 | 9.628 | 0.43422 | 4.510 |
| Detection Method | Standard Deviation |
| Our Method | 0.005 |
| SRID | 0.036 |
| ELISA | 0.024 |
| RIA | 0.018 |
