Evaluation of the application value of seven tumor-associated autoantibodies in non-small cell lung cancer based on machine learning algorithms / 中华预防医学杂志

Objective: Based on the diagnostic model established and validated by the machine learning algorithm, to investigate the value of seven tumor-associated autoantibodies (TAABs), namely anti-p53, PGP9.5, SOX2, GAGE7, GBU4-5, MAGEA1 and CAGE antibodies in the diagnosis of non-small cell lung cancer (NSCLC) and to differentiate between NSCLC and benign lung nodules. Methods: This was a retrospective study of clinical cases. Model building queue: a total of 227 primary patients who underwent radical lung cancer surgery in the Department of Thoracic Surgery, Shengjing Hospital of China Medical University, from November 2018 to June 2021 were collected as the NSCLC group, and 120 cases of benign lung nodules, 122 cases of pneumonia and 120 healthy individuals were selected as the control groups. External validation queue: a total of 100 primary patients who underwent radical lung cancer surgery in the Department of Thoracic Surgery, Shengjing Hospital of China Medical University, from May 2022 to December 2022 were collected as the NSCLC group, and 36 cases of benign lung nodules, 32 cases of pneumonia and 44 healthy individuals were selected as the control groups. In addition, NSCLC was divided into early (stage 0-ⅠB) and mid-to-late (stage ⅡA-ⅢB) subgroups. The levels of 7-TAABs were detected by enzyme immunoassay, and serum concentrations of CEA and CYFRA21-1 were detected by electrochemiluminescence. Four machine learning algorithms, XGBoost, Lasso logistic regression, Naïve Bayes, and Support Vector Machine are used to establish classification models. And the best performance model was chosen based on evaluation metrics and a multi-indicator combination model was established. In addition, an online risk evaluation tool was generated to assist clinical applications. Results: Except for p53, the levels of rest six TAABs, CEA and CYFRA21-1 were significantly higher in the NSCLC group (P<0.05). Serum levels of anti-SOX2 [1.50 (0.60, 10.85) U/ml vs. 0.8 (0.20, 2.10) U/ml, Z=2.630, P<0.05] and MAGEA1 antibodies [0.20 (0.10, 0.43) U/ml vs. 0.10 (0.10, 0.20) U/ml, Z=2.289, P<0.05], CEA [3.13 (2.12, 5.64) ng/ml vs. 2.11 (1.25, 3.09) ng/ml, Z=3.970, P<0.05] and CYFRA21-1 [4.31(2.37, 7.14) ng/ml vs. 2.53(1.92, 3.48) ng/ml, Z=3.959, P<0.05] were significantly higher in patients with mid-to late-stage NSCLC than in early stages. XGBoost model was used to establish a multi-indicator combined detection model (after removing p53). 6-TAABs combined with CYFRA21-1 was the best combination model for the diagnosis of NSCLC and early NSCLC. The optimal diagnostic thresholds were 0.410, 0.701 and 0.744, and the AUC was 0.828, 0.757 and 0.741, respectively (NSCLC vs. control, NSCLC vs. benign lung nodules, early NSCLC vs. benign lung nodules) in model building queue, and the AUC was 0.760, 0.710 and 0.660, respectively (NSCLC vs. control, NSCLC vs. benign lung nodules, early NSCLC vs. benign lung nodules) in external validation queue. Conclusion: In the diagnosis of NSCLC, 6-TAABs is superior to that of traditional tumor markers CEA and CYFRA21-1, and can compensate for the shortcomings of traditional tumor markers. For the differential diagnosis of NSCLC and benign lung nodule, "6-TAABs+CYFRA21-1" is the most cost-effective combination, and plays an important role in prevention and screening for early lung cancer.

Evaluation of the application value of seven tumor-associated autoantibodies in non-small cell lung cancer based on machine learning algorithms / 中华预防医学杂志

Objective: Based on the diagnostic model established and validated by the machine learning algorithm, to investigate the value of seven tumor-associated autoantibodies (TAABs), namely anti-p53, PGP9.5, SOX2, GAGE7, GBU4-5, MAGEA1 and CAGE antibodies in the diagnosis of non-small cell lung cancer (NSCLC) and to differentiate between NSCLC and benign lung nodules. Methods: This was a retrospective study of clinical cases. Model building queue: a total of 227 primary patients who underwent radical lung cancer surgery in the Department of Thoracic Surgery, Shengjing Hospital of China Medical University, from November 2018 to June 2021 were collected as the NSCLC group, and 120 cases of benign lung nodules, 122 cases of pneumonia and 120 healthy individuals were selected as the control groups. External validation queue: a total of 100 primary patients who underwent radical lung cancer surgery in the Department of Thoracic Surgery, Shengjing Hospital of China Medical University, from May 2022 to December 2022 were collected as the NSCLC group, and 36 cases of benign lung nodules, 32 cases of pneumonia and 44 healthy individuals were selected as the control groups. In addition, NSCLC was divided into early (stage 0-ⅠB) and mid-to-late (stage ⅡA-ⅢB) subgroups. The levels of 7-TAABs were detected by enzyme immunoassay, and serum concentrations of CEA and CYFRA21-1 were detected by electrochemiluminescence. Four machine learning algorithms, XGBoost, Lasso logistic regression, Naïve Bayes, and Support Vector Machine are used to establish classification models. And the best performance model was chosen based on evaluation metrics and a multi-indicator combination model was established. In addition, an online risk evaluation tool was generated to assist clinical applications. Results: Except for p53, the levels of rest six TAABs, CEA and CYFRA21-1 were significantly higher in the NSCLC group (P<0.05). Serum levels of anti-SOX2 [1.50 (0.60, 10.85) U/ml vs. 0.8 (0.20, 2.10) U/ml, Z=2.630, P<0.05] and MAGEA1 antibodies [0.20 (0.10, 0.43) U/ml vs. 0.10 (0.10, 0.20) U/ml, Z=2.289, P<0.05], CEA [3.13 (2.12, 5.64) ng/ml vs. 2.11 (1.25, 3.09) ng/ml, Z=3.970, P<0.05] and CYFRA21-1 [4.31(2.37, 7.14) ng/ml vs. 2.53(1.92, 3.48) ng/ml, Z=3.959, P<0.05] were significantly higher in patients with mid-to late-stage NSCLC than in early stages. XGBoost model was used to establish a multi-indicator combined detection model (after removing p53). 6-TAABs combined with CYFRA21-1 was the best combination model for the diagnosis of NSCLC and early NSCLC. The optimal diagnostic thresholds were 0.410, 0.701 and 0.744, and the AUC was 0.828, 0.757 and 0.741, respectively (NSCLC vs. control, NSCLC vs. benign lung nodules, early NSCLC vs. benign lung nodules) in model building queue, and the AUC was 0.760, 0.710 and 0.660, respectively (NSCLC vs. control, NSCLC vs. benign lung nodules, early NSCLC vs. benign lung nodules) in external validation queue. Conclusion: In the diagnosis of NSCLC, 6-TAABs is superior to that of traditional tumor markers CEA and CYFRA21-1, and can compensate for the shortcomings of traditional tumor markers. For the differential diagnosis of NSCLC and benign lung nodule, "6-TAABs+CYFRA21-1" is the most cost-effective combination, and plays an important role in prevention and screening for early lung cancer.

Planning of ecologically suitable areas for Ligusticum chuanxiong under background of soil cadmium pollution / 中国中药杂志

Chuanxiong Rhizoma is a traditional Chinese medicinal material mainly produced in Sichuan and Chongqing of China. In recent years, the cadmium content in Chuanxiong Rhizoma produced in most of the genuine producing areas has exceeded the standard, which makes Chuanxiong Rhizoma difficult to be exported. To solve the problem of excessive cadmium content in soil, this study employed the MaxEnt model to simulate the potential geographic distribution of Ligusticum chuanxiong and evaluate important environmental factors, and re-plan its ecologically suitable areas based on the mineral distribution characteristics and soil cadmium pollution status. The results showed that the places suitable for L. chuanxiong growing covered an area of 335 523.69 km~2, mainly in central and eastern Sichuan, southern Shaanxi and most parts of Chongqing. Among them, the highly suitable areas of L. chuanxiong were mainly concentrated in Chengdu, Ya'an, Deyang, and Mianyang. Solar radiation, annual precipitation, and annual range of temperature were evaluated as important variables affecting the distribution of L. chuanxiong, with the contribution rates of 62.3%, 13.3%, and 6.8%, respectively. In addition, Qionglai county, Chongqing county, Mianyang city(Youxian district and Fucheng district), Qingchuan county, and Xinjin county were classified into the first-class ecologically suitable zone, covering a total area of 2 768.87 km~2. The se-cond-class ecologically suitable zone was even wider, involving such counties as Tongjiang county, Renshou county, Jianyang county, and Nanjiang county, and the total area reached 43 616.92 km~2. The re-planning of the ecologically suitable areas for L. chuanxiong has provided strong data support for the cultivation and resource development of L. chuanxiong and also new ideas for solving the problem of excessive cadmium content in L. chuanxiong.

6-Gingerol ameliorates adipose tissue insulin resistance in aging rats / 中国中药杂志

This study investigated the effects and mechanisms of 6-gingerol on adipose tissue insulin resistance in naturally aging rats with glycolipid metabolism disorders. Twenty-seven aging male SD rats were randomly divided into a model group(aged, n=9) and two groups treated with 6-gingerol at 0.05 mg·kg~(-1)(G-L, n=9) and 0.2 mg·kg~(-1)(G-H, n=9). Six young rats were randomly assigned to a normal control group(NC). Rats were treated for seven weeks by gavage. Non-esterified fatty acid(NEFA) and insulin content was determined by enzyme-linked immunosorbent assay(ELISA), and adipose tissue insulin resistance index(Adipo-IR) was calculated. HE staining was used to observe the size of adipocytes in epididymal white adipose tissue(eWAT). The gene and protein expression levels of adiponectin receptor 1(AdipoR1), AMP-activated protein kinase α(AMPKα), phosphorylated AMPK(p-AMPKα~(Thr172)), peroxisome proliferator-activated receptor-γ coactivator-1α(PGC-1α), phosphatidylinositol 3-kinase(PI3 K), protein kinase B(Akt), phosphorylated Akt(p-Akt~(Ser473)), tumor necrosis factor-α(TNF-α), c-Jun N-terminal kinase 1/2(JNK1/2), phosphorylated JNK1/2(p-JNK~(Thr183/Tyr185)), interleukin-1β(IL-1β), and interleukin-6(IL-6) in adiponectin(APN), insulin, and inflammatory factor signaling pathways were detected by Western blot and real-time RCR, respectively. The results showed that 6-gingerol at a high dose could significantly decrease the fasting plasma content of NEFA and insulin and reduce Adipo-IR. Additionally, 6-gingerol at a high dose significantly increased the protein and mRNA expression of APN, AdipoR1, PGC-1α, and PI3 K in eWAT, elevated the relative expression of p-AMPK~(Thr172) and p-Akt~(Ser 473), reduced the protein and mRNA expression of TNF-α, IL-1, and IL-6 in eWAT, and decreased the relative expression of p-JNK1 and p-JNK2. This study reveals that 6-gingerol can improve insulin sensitivity of adipose tissues in aging rats with glycolipid metabolism disorders, and this effect is presumedly achieved by enhancing the PI3 K/Akt signaling pathway, inhibiting adipose tissue inflammation, increasing APN synthesis, enhancing AdipoR1 expression, and activating its downstream AMPK/PGC-1α signaling pathway.

Bibliometric Analysis of Forensic Genetics Literatures in SCIE from 1989 to 2019 / 法医学杂志

Objective To conduct bibliometric analysis of forensic genetics literatures published by Chinese mainland scholars in SCIE journals from 1989 to 2019, to show the research achievements of the past three decades and predict future research fields and directions. Methods Microsoft Office Excel 2019 was utilized to analyze the general situation, research institutions, authors, funds, author keywords, etc. of the literatures. The status of research in forensic genetics in Chinese mainland was visualized by PlotDB, Gephi 0.9.2 software and literature interpretation. Results During the last three decades, 1 126 forensic genetics literatures were published by scholars from Chinese mainland on SCIE journals, mostly articles. The quantity and quality of the literatures were both on the increase. The number of literatures published in Forensic Science International-Genetics was the highest, and 60.83% of the literatures were funded, mainly by the National Natural Science Foundation of China （498 literatures）. The current research hotspots were STR, SNP, InDel polymorphisms, linkage genetic markers, mtDNA genetic markers, epigenetic markers, RNA genetic markers, chip technology and omics research method. Conclusion The forensic genetics in China has developed rapidly along with the promotion of forensic science in universities. The SCIE literatures on forensic genetics published by Chinese mainland scholars increased rapidly with the funding from the National Natural Science Foundation of China and Ministry of Science and Technology of the People's Republic of China, which positively contributes to the development of basic research and the improvement of overall level in forensic genetics in China.