Objective:To systematically analyze the trends of leukocyte telomere length and methylation levels across different age groups(31-90 years)from the hospital cohort, using nanopore sequencing and the Telomere Boundary Point(TeloBP)algorithm, and to investigate their correlation with aging.Methods:A total of 120 blood samples were collected from six age groups(31-40 years, 41-50 years, 51-60 years, 61-70 years, 71-80 years, and 81-90 years), with 20 samples per group.Leukocyte DNA was extracted by isolating the white blood cell layer.Nanopore sequencing was employed to measure telomere length and assess methylation levels.The TeloBP algorithm was used to calculate telomere length, and nanopolish software was applied for CpG methylation analysis.Spearman correlation was conducted to evaluate the relationship between telomere length and methylation levels, with visualization and statistical analysis performed using R.Results:Telomere length was found to progressively shorten with age(Spearman R=-0.28, P=0.021), with the trend being most pronounced in the 51-60 age group.Additionally, a potential association was observed between methylation levels and telomere length(Spearman R=0.77, P=0.1).In the 51-60 years age group, methylation levels exhibited greater stability, while the 81-90 years age group showed a broader and more variable distribution.Chromosome-level analysis revealed significant differences in telomere length across chromosomes, with longer telomeres observed on chromosomes 3 and 11, and shorter telomeres on chromosomes 16 and 19. Conclusions:This study reveals the age-related shortening of leukocyte telomere length and observes a potential association between methylation levels and telomere length, albeit not statistically significant.These findings provide a foundation for further exploration of the mechanisms underlying the roles of telomeres and methylation in the aging process.

Objective:To apply statistical process control (SPC) techniques to the quality assurance of non-normal radiotherapy plans through Johnson transformation, establishing patient-specific tolerance and action limits based on treatment sites and dose/distance assessment criteria, thereby enhancing the intensity-modulated radiation therapy (IMRT) verification accuracy and dose delivery precision.Methods:In this study, 951 gamma analysis data of patient-specific quality assurance (PSQA) executed on the Halcyon accelerator platform were selected and categorized into six groups based on treatment sites, including brain (102 cases), head and neck (100 cases), breast (229 cases), lung (154 cases), esophagus (223 cases), and pelvic (143 cases) groups. The six groups of data were statistically analyzed through Anderson-Darling normality tests ( α = 0.05) using Minitab 21 software. Non-normal data were transformed into normal data through Johnson transformation and then were used to establish treatment site-specific tolerance and action limits, which were compared with the Shewhart control charts based on normal distributions. Results:The PSQA result of the six groups all exhibited non-normal distributions ( P < 0.05). Through Johnson transformation, the tolerance and action limits for the head and neck, breast, lung, esophagus, and pelvic areas under the 3%/2 mm criterion ranged from 95.13% to 96.16% and 94.19% to 95.91%, respectively. In contrast, the tolerance and action limits ranged from 91.15% to 94.86% and 89.94% to 94.78% under the 2%/2 mm criterion. Directly applying Shewhart control charts without normality assumptions yielded higher tolerance limits compared to the application of Johnson transformation, increasing the false positive rate in the non-normal PSQA process. Conclusions:Applying the SPC techniques directly to a non-normal process can lead to an increased false alarm rate and wrong process interpretation. The SPC techniques combined with Johnson transformation enable more effective monitoring of a non-normal PSQA process, facilitating timely identification of potential factors that may lead to an out-of-control process based on the treatment site-specific limits.

Objective:To evaluate the sample preparation proficiency and storage proficiency of 11 clinical biobanks in Beijing through simulated experiments, and to establish an assessment method for the quality comparability of biological samples.Methods:An exploratory research design was adopted. In November 2023, artificial composite serum quality control materials containing six recombinant human protein markers—recombinant human alanine aminotransferase (rhALT), recombinant human aspartate aminotransferase (rhAST), recombinant human creatine kinase (rhCK), recombinant human creatine kinase-MB (rhCK-MB), recombinant human B-type natriuretic peptide (rhBNP), and recombinant human troponin I (rhTNI)—were distributed to 11 clinical biobanks in Beijing City. Sample preparation and storage followed the standardized operating procedures. Proficiency differences were assessed through statistical analysis.Results:Three-way repeated measures ANOVA revealed all six protein markers showed a declining trend over storage time in ultra-low-temperature environments ( F values 11.68-4 179.66, all P<0.01). However, neither long-term/temporary refrigerator types ( F values 0.01-1.23, all P>0.05)nor placement locations within refrigerators significantly affected the stability of these six proteins ( F valus 0.03-1.47, all P>0.05). The biases in detection results for rhALT, rhAST, rhTNI, and rhBNP at different storage time points were within the allowable bias limits for each item, supporting their use as markers for protein stability in biobank samples. All 11 institutions passed the storage proficiency assessment. In the preparation proficiency assessment, deviations were observed in post-preparation sample results, with a notably high out-of-control rate for rhCK (36.36%). Conclusion:Sample preparation proficiency can serve as a quality control metric for clinical biobanks. Future external quality assessment systems for biobanks should focus on sample preparation rather than storage processes.

Objective The prediction model of recurrence within two years after complete remission of diffuse large B-cell lymphoma(DLBCL)patients was constructed based on frienemy indecision region dynamic ensemble selection(FIRE-DES)to provide decision-making basis for the treatment of patients.Methods To collect data of 498 patients who achieved complete response after treatment from January 2010 to January 2020 in a Grade-A hospital in Shanxi Province.A FIRE-DES combination prediction model based on four common category-disequilibrium treatment methods was constructed and compared with five traditional single classifiers and two integrated classifiers.Results Among the four categories of unbalance algorithms,synthetic minority oversampling technique and edited nearest neighbor(SMOTE-ENN)algorithm has obtained the optimal classification performance.On this basis,the classification effect of dynamic ensemble selection performance(DESP),K-nearest oracle union(KNORAU)and meta-learning for dynamic ensemble selection(META-DES)dynamic integration selection algorithms is obviously superior to the traditional single classifier and ensemble classifier model.The classification effect of the improved DESP,KNORAU and META-DES dynamic selection algorithms based on Frienemy Indecision Region is further improved.The classification performance of FIRE-META-DES was the best(Accuracy=0.909,Precision=0.906,Recall=0.967,AUC=0.879,F1-Score=0.936,Brier Score=0.088).Conclusion Aiming at the actual DLBCL data set,SMOTE-ENN+FIRE-META-DES combined prediction model for recurrence used in this paper achieves the optimal performance and low computational complexity,which can provide a strong reference for DLBCL recurrence prediction.

This study aims to establish a high-performance size-exclusion chromatography (HPSEC) method for determining the content of the classical swine fever virus (CSFV) E2 protein and screen the optimal stabilizer to enhance the stability of this protein. The optimal detection conditions were determined by optimizing the composition of the mobile phase, and characteristic chromatographic peaks were identified by SDS-PAGE and Western blotting. The specificity, repeatability, precision, linearity, limit of detection (LOD), and limit of quantitation (LOQ) of the method were assessed. The method established was used to determine the content of CSFV E2 protein antigen and vaccine. Differential scanning fluorimetry (DSF) was employed to screen the buffer system, pH, and salt ion concentrations, and sugar, amino acid, and alcohol stabilizers were further screened. The results showed that using a 200 mmol/L phosphate buffer provided the best column efficiency. An antigen-specific chromatographic peak appeared at the retention time of 18 min, which was identified as the CSFV E2 protein by SDS-PAGE and Western blotting. The method exhibited high specificity for detecting the CSFV E2 protein, with no absorbance peak observed in the blank control. The relative standard deviation (RSD) of the peak area for six repeated injections of the CSFV E2 protein was 0.74%, indicating good repeatability of the method. The RSD for repeated detection of two different concentrations of CSFV E2 protein samples by different operators at different time points was less than 2%, suggesting good intermediate precision of the method. The peak area of the CSFV E2 protein was linearly related to its concentration, with the regression equation showing R² of 1.000. The LOD and LOQ of the method were 14.88 μg/mL and 29.75 μg/mL, respectively. Application of the developed method in the detection of three batches of CSFV E2 protein antigen and three batches of vaccine demonstrated results consistent with those from the bicinchoninic acid (BCA) assay, which meant that the method could accurately determine the content of CSFV E2 protein antigen and vaccine. The DSF method identified 50 mmol/L Tris-HCl at pH 8.0 as the optimal buffer, and the addition of sugar and alcohol stabilizers further improved the stability of the CSFV E2 protein. The HPSEC method established in this study is simple, fast, and exhibits good accuracy and repeatability, enabling precise measurement of the CSFV E2 protein content. It is expected to play a crucial role in the quality control of the CSFV E2 vaccine. Furthermore, the strategy for improving the CSFV E2 protein stability, identified through DSF screening, has significant implications for enhancing the stability of the CSFV E2 vaccine.
Classical Swine Fever Virus/chemistry* ; Chromatography, Gel/methods* ; Animals ; Swine ; Viral Envelope Proteins/immunology*

Objective The prediction model of recurrence within two years after complete remission of diffuse large B-cell lymphoma(DLBCL)patients was constructed based on frienemy indecision region dynamic ensemble selection(FIRE-DES)to provide decision-making basis for the treatment of patients.Methods To collect data of 498 patients who achieved complete response after treatment from January 2010 to January 2020 in a Grade-A hospital in Shanxi Province.A FIRE-DES combination prediction model based on four common category-disequilibrium treatment methods was constructed and compared with five traditional single classifiers and two integrated classifiers.Results Among the four categories of unbalance algorithms,synthetic minority oversampling technique and edited nearest neighbor(SMOTE-ENN)algorithm has obtained the optimal classification performance.On this basis,the classification effect of dynamic ensemble selection performance(DESP),K-nearest oracle union(KNORAU)and meta-learning for dynamic ensemble selection(META-DES)dynamic integration selection algorithms is obviously superior to the traditional single classifier and ensemble classifier model.The classification effect of the improved DESP,KNORAU and META-DES dynamic selection algorithms based on Frienemy Indecision Region is further improved.The classification performance of FIRE-META-DES was the best(Accuracy=0.909,Precision=0.906,Recall=0.967,AUC=0.879,F1-Score=0.936,Brier Score=0.088).Conclusion Aiming at the actual DLBCL data set,SMOTE-ENN+FIRE-META-DES combined prediction model for recurrence used in this paper achieves the optimal performance and low computational complexity,which can provide a strong reference for DLBCL recurrence prediction.

Objective:To apply statistical process control (SPC) techniques to the quality assurance of non-normal radiotherapy plans through Johnson transformation, establishing patient-specific tolerance and action limits based on treatment sites and dose/distance assessment criteria, thereby enhancing the intensity-modulated radiation therapy (IMRT) verification accuracy and dose delivery precision.Methods:In this study, 951 gamma analysis data of patient-specific quality assurance (PSQA) executed on the Halcyon accelerator platform were selected and categorized into six groups based on treatment sites, including brain (102 cases), head and neck (100 cases), breast (229 cases), lung (154 cases), esophagus (223 cases), and pelvic (143 cases) groups. The six groups of data were statistically analyzed through Anderson-Darling normality tests ( α = 0.05) using Minitab 21 software. Non-normal data were transformed into normal data through Johnson transformation and then were used to establish treatment site-specific tolerance and action limits, which were compared with the Shewhart control charts based on normal distributions. Results:The PSQA result of the six groups all exhibited non-normal distributions ( P < 0.05). Through Johnson transformation, the tolerance and action limits for the head and neck, breast, lung, esophagus, and pelvic areas under the 3%/2 mm criterion ranged from 95.13% to 96.16% and 94.19% to 95.91%, respectively. In contrast, the tolerance and action limits ranged from 91.15% to 94.86% and 89.94% to 94.78% under the 2%/2 mm criterion. Directly applying Shewhart control charts without normality assumptions yielded higher tolerance limits compared to the application of Johnson transformation, increasing the false positive rate in the non-normal PSQA process. Conclusions:Applying the SPC techniques directly to a non-normal process can lead to an increased false alarm rate and wrong process interpretation. The SPC techniques combined with Johnson transformation enable more effective monitoring of a non-normal PSQA process, facilitating timely identification of potential factors that may lead to an out-of-control process based on the treatment site-specific limits.

Objective:To evaluate the sample preparation proficiency and storage proficiency of 11 clinical biobanks in Beijing through simulated experiments, and to establish an assessment method for the quality comparability of biological samples.Methods:An exploratory research design was adopted. In November 2023, artificial composite serum quality control materials containing six recombinant human protein markers—recombinant human alanine aminotransferase (rhALT), recombinant human aspartate aminotransferase (rhAST), recombinant human creatine kinase (rhCK), recombinant human creatine kinase-MB (rhCK-MB), recombinant human B-type natriuretic peptide (rhBNP), and recombinant human troponin I (rhTNI)—were distributed to 11 clinical biobanks in Beijing City. Sample preparation and storage followed the standardized operating procedures. Proficiency differences were assessed through statistical analysis.Results:Three-way repeated measures ANOVA revealed all six protein markers showed a declining trend over storage time in ultra-low-temperature environments ( F values 11.68-4 179.66, all P<0.01). However, neither long-term/temporary refrigerator types ( F values 0.01-1.23, all P>0.05)nor placement locations within refrigerators significantly affected the stability of these six proteins ( F valus 0.03-1.47, all P>0.05). The biases in detection results for rhALT, rhAST, rhTNI, and rhBNP at different storage time points were within the allowable bias limits for each item, supporting their use as markers for protein stability in biobank samples. All 11 institutions passed the storage proficiency assessment. In the preparation proficiency assessment, deviations were observed in post-preparation sample results, with a notably high out-of-control rate for rhCK (36.36%). Conclusion:Sample preparation proficiency can serve as a quality control metric for clinical biobanks. Future external quality assessment systems for biobanks should focus on sample preparation rather than storage processes.

Objective:To systematically analyze the trends of leukocyte telomere length and methylation levels across different age groups(31-90 years)from the hospital cohort, using nanopore sequencing and the Telomere Boundary Point(TeloBP)algorithm, and to investigate their correlation with aging.Methods:A total of 120 blood samples were collected from six age groups(31-40 years, 41-50 years, 51-60 years, 61-70 years, 71-80 years, and 81-90 years), with 20 samples per group.Leukocyte DNA was extracted by isolating the white blood cell layer.Nanopore sequencing was employed to measure telomere length and assess methylation levels.The TeloBP algorithm was used to calculate telomere length, and nanopolish software was applied for CpG methylation analysis.Spearman correlation was conducted to evaluate the relationship between telomere length and methylation levels, with visualization and statistical analysis performed using R.Results:Telomere length was found to progressively shorten with age(Spearman R=-0.28, P=0.021), with the trend being most pronounced in the 51-60 age group.Additionally, a potential association was observed between methylation levels and telomere length(Spearman R=0.77, P=0.1).In the 51-60 years age group, methylation levels exhibited greater stability, while the 81-90 years age group showed a broader and more variable distribution.Chromosome-level analysis revealed significant differences in telomere length across chromosomes, with longer telomeres observed on chromosomes 3 and 11, and shorter telomeres on chromosomes 16 and 19. Conclusions:This study reveals the age-related shortening of leukocyte telomere length and observes a potential association between methylation levels and telomere length, albeit not statistically significant.These findings provide a foundation for further exploration of the mechanisms underlying the roles of telomeres and methylation in the aging process.

Objective To study the core behavioral symptoms,biological indicators,and pathological changes of a mouse model of breast cancer complicated with depression induced using 4T1 breast cancer cell inoculation combined with chronic restraint stress(CRS).Methods BABL/c mice were randomly divided into Control,Stress,Tumor,and stress combined with tumor(S+T)groups.Mice in the tumor and S+T groups were inoculated under the front legs with breast cancer 4T1 cells.After tumor formation,mice in the stress and S+T groups were subjected to CRS for 21 days.The body weight and food intake of each group were monitored during modeling.After the experiment,the occurrence of depression-like behavior of mice in each group was evaluated by sucrose preference test,open field test,elevated plus-maze test,and forced swimming test.After the mice were decapitated,the weights and volumes of the tumors were measured.Concentrations of serum tumor markers,including carbohydrate antigen(CA199),carcinoembryonic antigen(CEA),and vascular endothelial growth factor(VEGF),and related neurotransmitters,including 5-hydroxytryptamine(5-HT),norepinephrine(NE),and corticosterone(CORT),were determined using ELISA.HE staining was used to observe histopathological changes to the hippocampus and tumor.Results In S+T group mice,body weight and food intake were significantly decreased,tumor weight and volume were significantly increased,serum tumor marker(CA199,CEA,VEGF)levels were significantly increased,enthusiasm and desire to explore a new environment were reduced,stress and despair behaviors were significantly increased,and levels of the serum neurotransmitters 5-HT and NE and levels of CORT were significantly increased.In addition,the cell arrangement in the tumor tissue was loose,the amount of intercellular substance decreased,the pathological nuclear classification phase was increased,the arrangement and morphology of neurons in the CA3 region of the hippocampus were disordered,and there were obvious nuclear vacuolation-like changes.Conclusions A mouse model of breast cancer complicated with depression induced by 4T1 breast cancer cell inoculation combined with CRS showed the typical dual symptoms and biological indicators of breast cancer and depression and can be used as a good reference model for experimental studies of breast cancer complicated with depression.