Objective To mine and analyze the routine blood test data of children with allergic rhinitis (AR), identify routine blood parameters related to childhood allergic rhinitis, establish an effective diagnostic model, and evaluate the performance of the model. Methods This study was a retrospective study of clinical cases. The experimental group comprised a total of 1110 children diagnosed with AR at the First Affiliated Hospital of Air Force Medical University during the period from December 12, 2020 to December 12, 2021, while the control group included 1109 children without a history of allergic rhinitis or other allergic diseases who underwent routine physical examinations during the same period. Information such as age, sex and routine blood test results was collected for all subjects. The levels of routine blood test indicators were compared between AR children and healthy children using comprehensive intelligent baseline analysis, with indicators of P≥0.05 excluded; variables were screened by Lasso regression. Binary Logistic regression was used to further evaluate the influence of multiple routine blood indexes on the results. Five kinds of machine model algorithms were used, namely extreme value gradient lift (XGBoost), logistic regression (LR), gradient lift decision tree (LGBMC), Random forest (RF) and adaptive lift algorithm (AdaBoost), to establish the diagnostic models. The receiver operating characteristic (ROC) curve was used to screen the optimal model. The best LightGBM algorithm was used to build an online patient risk assessment tool for clinical application. Results Statistically significant differences were observed between the AR group and the control group in the following routine blood test indicators: mean cellular hemoglobin concentration (MCHC), hemoglobin (HGB), absolute value of basophils (BASO), absolute value of eosinophils (EOS), large platelet ratio (P-LCR), mean platelet volume (MPV), platelet distribution width (PDW), platelet count (PLT), absolute values of leukocyte neutrophil (W-LCC), leukocyte monocyte (W-MCC), leukocyte lymphocyte (W-SCC), and age. Lasso regression identified these variables as important predictors, and binary Logistic regression further analyzed the significant influence of these variables on the results. The optimal machine learning algorithm LightGBM was used to establish a multi-index joint detection model. The model showed robust prediction performance in the training set, with AUC values of 0.8512 and 0.8103 in the internal validation set. Conclusion The identified routine blood parameters can be used as potential biomarkers for early diagnosis and risk assessment of AR, which can improve the accuracy and efficiency of diagnosis. The established model provides scientific basis for more accurate diagnostic tools and personalized prevention strategies. Future studies should prospectively validate these findings and explore their applicability in other related diseases.
Humans ; Male ; Female ; Rhinitis, Allergic/blood* ; Child ; Biomarkers/blood* ; Retrospective Studies ; Early Diagnosis ; Child, Preschool ; ROC Curve ; Logistic Models ; Hematologic Tests ; Algorithms ; Adolescent ; Machine Learning

Objective:This study aimed to analyze the genetic variation of the human papillomavirus (HPV) type 39 genomes and to predict and screen the dominant T-cell and B-cell epitopes of the viral early proteins (E1, E2, E6, E7) and late proteins (L1, L2).Methods:A total of 70 full-length sequences of HPV39 variants were retrieved from the clinical samples and the National Center for Biotechnology Information (NCBI) to construct a phylogenetic tree, analyze genetic polymorphisms, and predict the physicochemical properties of the viral proteins. Next, T-cell and B-cell epitopes were predicted using IEDB and ABCpred, and potential dominant epitopes were further selected based on parameters such as the secondary structure of the epitope region, peptide flexibility, hydrophilicity, surface accessibility and antigenicity. Finally, a homology analysis of the potential dominant epitopes was performed with 12 high-risk HPV types.Results:HPV39 variants from different sources can be clustered into two lineages (A and B), each exhibiting distinct mutation patterns. The mutation rate was the highest in E7 and the lowest in E1 among the different viral genes. However, these nucleotide/amino acid mutations did not significantly impact the physicochemical properties of the viral proteins. After prediction and screening, 5 and 6 potential dominant B-cell epitopes were identified in both L1 and L2, respectively. E1, E2, E6, and E7 yielded 18, 10, 4, and 1 potential dominant HLA-I restricted T-cell epitopes, respectively. Additionally, E1, E2, and E6 yielded 7, 3, and 2 potential dominant HLA-II restricted T-cell epitopes, respectively. Homology analysis indicated that T-cell dominant epitopes in E1, E2, and E6, as well as B-cell epitopes in L2, showed high homology (93%-100%) with HPV68, HPV33, HPV45, and HPV59.Conclusions:Bioinformatics analysis and prediction revealed that HPV39 variants can be clustered into two main evolutionary branches, A and B, each exhibiting a specific mutation pattern. The viral proteins contain potential dominant T-cell and B-cell epitopes that can be further investigated, providing valuable theoretical support for the development of HPV39-related peptide-based vaccines and therapeutics.

Objective:This study aimed to analyze the genetic variation of the human papillomavirus (HPV) type 39 genomes and to predict and screen the dominant T-cell and B-cell epitopes of the viral early proteins (E1, E2, E6, E7) and late proteins (L1, L2).Methods:A total of 70 full-length sequences of HPV39 variants were retrieved from the clinical samples and the National Center for Biotechnology Information (NCBI) to construct a phylogenetic tree, analyze genetic polymorphisms, and predict the physicochemical properties of the viral proteins. Next, T-cell and B-cell epitopes were predicted using IEDB and ABCpred, and potential dominant epitopes were further selected based on parameters such as the secondary structure of the epitope region, peptide flexibility, hydrophilicity, surface accessibility and antigenicity. Finally, a homology analysis of the potential dominant epitopes was performed with 12 high-risk HPV types.Results:HPV39 variants from different sources can be clustered into two lineages (A and B), each exhibiting distinct mutation patterns. The mutation rate was the highest in E7 and the lowest in E1 among the different viral genes. However, these nucleotide/amino acid mutations did not significantly impact the physicochemical properties of the viral proteins. After prediction and screening, 5 and 6 potential dominant B-cell epitopes were identified in both L1 and L2, respectively. E1, E2, E6, and E7 yielded 18, 10, 4, and 1 potential dominant HLA-I restricted T-cell epitopes, respectively. Additionally, E1, E2, and E6 yielded 7, 3, and 2 potential dominant HLA-II restricted T-cell epitopes, respectively. Homology analysis indicated that T-cell dominant epitopes in E1, E2, and E6, as well as B-cell epitopes in L2, showed high homology (93%-100%) with HPV68, HPV33, HPV45, and HPV59.Conclusions:Bioinformatics analysis and prediction revealed that HPV39 variants can be clustered into two main evolutionary branches, A and B, each exhibiting a specific mutation pattern. The viral proteins contain potential dominant T-cell and B-cell epitopes that can be further investigated, providing valuable theoretical support for the development of HPV39-related peptide-based vaccines and therapeutics.

A 27-year-old male was admitted to the Xijing Hospital in August 2018 due to unprovoked severe thoracodynia with palpitations, shortness of breath and chest tightness. Computed tomography angiography showed a type A aortic dissection. Genetic testing based on next-generation sequencing for 15 genes associated with hereditary aortic diseases and Sanger sequencing validation revealed a heterozygous missense mutation c.998G>T (p.Gly333Val) in the COL3A1 gene. Sanger sequencing verification of family members confirmed that the mutation c.998G>T co-segregated with the patient′s phenotype in this family. That mutation was classified as "likely pathogenic" according to American College of Medical Genetics and Genomics standards and guidelines for genetic variant classification. Carriers of this mutation can be definitively diagnosed with "vascular Ehlers-Danlos syndrome". After the diagnosis was clarified, symptomatic treatment was given to the patient, but the disease progressed rapidly. The patient discontinued treatment and died shortly after being discharged. In this study, we found a new variant in the COL3A1 gene, expanding the mutation spectrum of this gene.

In traditional clinical teaching of impacted tooth extraction, there are problems including limited observation fields for students, insufficient doctor-patient communication training, inadequate clinical thinking development, and low levels of clinical participation. Based on the core elements of visualizing jaw structure with perspective, formulating clinical strategy, immersing in clinical participation, and cultivating the spirit of caregiving, we developed a virtual reality simulation teaching platform for the clinical decision analysis of impacted tooth extraction. The virtual simulation-based platform can create three different impacted tooth scenarios in 3D, which demonstrates the process of clinical decision analysis of impacted tooth extraction through virtuality-reality interaction, allowing students to immerse in the discovery, analysis, and resolution of the medical and humanistic problems in the process of impacted tooth extraction. The questionnaire survey showed that 81.36% (48/59) of the students believed that the software could improve their clinical thinking ability; 76.27% (45/59) of the students believed that it could help them master the basic process of impacted tooth extraction; and 62.71% (37/59) of the students believed that it could improve their skills of impacted tooth extraction. By providing immersive learning experience, constructive teaching design, and multi-dimensional teaching evaluation, the software achieved the goals of cultivating students' clinical thinking ability and professional literacy in oral and maxillofacial surgery.

OBJECTIVE: To analyze the clinical phenotypes and genetic variants of a Chinese pedigree affected with Hereditary coagulation factor Ⅻ (FⅫ) deficiency. METHODS: A pedigree presented at the First Affiliated Hospital of Air Force Medical University on December 24,2021 was selected as the study subject. Activated partial thromboplastin time (APTT) and coagulation factor Ⅻ activity (FⅫ:C) were determine by a clotting method, and FⅫ antigen was detected with an ELISA assay. Following the extraction of genomic DNA, all exons and flanking regions of the F12 gene were subjected to Sanger sequencing. Clustalx-2.1-win, PROVEAN and Swiss-PDB Viewer software was used to analyze the conservation of amino acids at the variant sites, impact of of the variants on the amino acid substitutions and the protein structure. RESULTS: The APTT of the proband has prolonged to 70.2 s. Her FⅫ:C and FⅫ:Ag have decreased to 12% and 13%, respectively. DNA sequencing revealed that the proband has harbored c.346G>A (p.Gly97Ser) and c.1583C>A (p.Ser509Tyr) heterozygous compound missense variants in exons 5 and 13 of the F12 gene, respectively. Her father and sister were heterozygous carriers for the c.346G>A (p.Gly97Ser) variant, whilst her mother and brother were heterozygous for the c.1583C>A (p.Ser509Tyr) variant. CONCLUSION The c.346G>A (p.Gly97Ser) and c.1583C>A (p.Ser509Tyr) compound heterozygous variants of the F12 gene probably underlay the pathogenesis of hereditary coagulation FⅫ deficiency in this pedigree.
Humans ; Male ; Female ; Pedigree ; Factor XII/genetics* ; Mutation ; East Asian People ; Heterozygote ; Mothers ; Factor XII Deficiency/genetics*

Rhodotorula toruloides is a non-conventional red yeast that can synthesize various carotenoids and lipids. It can utilize a variety of cost-effective raw materials, tolerate and assimilate toxic inhibitors in lignocellulosic hydrolysate. At present, it is widely investigated for the production of microbial lipids, terpenes, high-value enzymes, sugar alcohols and polyketides. Given its broad industrial application prospects, researchers have carried out multi-dimensional theoretical and technological exploration, including research on genomics, transcriptomics, proteomics and genetic operation platform. Here we review the recent progress in metabolic engineering and natural product synthesis of R. toruloides, and prospect the challenges and possible solutions in the construction of R. toruloides cell factory.
Gene Editing ; Metabolic Engineering ; Rhodotorula/metabolism* ; Lipids

BACKGROUND: Congenital heart disease (CHD) is one of the most common congenital malformations in humans. Inconsistent results emerged in the existed studies on associations between air pollution and congenital heart disease. The purpose of this study was to evaluate the association of gestational exposure to air pollutants with congenital heart disease, and to explore the critical exposure windows for congenital heart disease. METHODS: The nested case-control study collected birth records and the following health data in Tianjin Women and Children's Health Center, China. All of the cases of congenital heart disease from 2013 to 2015 were selected matching five healthy controls for each case. Inverse distance weighting was used to estimate individual exposure based on daily air pollution data. Furthermore, the conditional logistic regression with distributed lag non-linear model was performed to identify the association between gestational exposure to air pollution and congenital heart disease. RESULTS: A total of 8,748 mother-infant pairs were entered into the analysis, of which 1,458 infants suffered from congenital heart disease. For each 10 µg/m³ increase of gestational exposure to PM_2.5, the ORs (95% confidence interval, 95%CI) ranged from 1.008 (1.001-1.016) to 1.013 (1.001-1.024) during the 1^st-2^nd gestation weeks. Similar weak but increased risks of congenital heart disease were associated with O₃ exposure during the 1^st week and SO₂ exposure during 6^th-7^th weeks in the first trimester, while no significant findings for other air pollutants. CONCLUSIONS This study highlighted that gestational exposure to PM_2.5, O₃, and SO₂ had lag effects on congenital heart disease. Our results support potential benefits for pregnancy women to the mitigation of air pollution exposure in the early stage, especially when a critical exposure time window of air pollutants may precede heart development.
Infant ; Pregnancy ; Child ; Humans ; Female ; Air Pollutants/analysis* ; Case-Control Studies ; Prenatal Exposure Delayed Effects/epidemiology* ; Heart Defects, Congenital/etiology* ; China/epidemiology* ; Particulate Matter/adverse effects* ; Maternal Exposure/adverse effects*

Objective:To explore the different metabolites in the follicular fluids (FFs) of polycystic ovary syndrome (PCOS) patients and non-PCOS patients and their effects on the maturation of mouse oocytes and the developmental potential of in vitro fertilization (IVF) embryos. Methods:The clinical data were collected for the retrospective cohort study. Animal experiments were conducted in a randomized controlled trial. This study included PCOS ( n=71) and non-PCOS ( n=70) patients who underwent the first IVF or intracytoplasmic sperm injection (ICSI) cycle in Shanghai JIAI Genetics & IVF institute from June 2019 to June 2020. The patients' FFs were collected and the clinical data from these patients were analyzed. Raman spectroscopy analysis technology was used to detect differences in the metabolic spectra of FFs between the two groups. Mouse GV phase oocytes were placed in FFs from PCOS patients and non-PCOS patients for in vitro maturation (IVM) culture respectively, then the matured mouse oocytes were collected for IVF. The effects of differential metabolites in FFs on mouse oocyte maturation and embryonic development were further explored. The Raman spectrum was also applied to identify the differences of the IVM spent culture media. Results:The MⅡ rate [82.19% (886/1 078)] and day 3 available embryo rate [51.30% (553/1 078)] from PCOS group were significantly lower than those of the non-PCOS group [85.85% (625/728), P=0.038; 53.30% (388/728), P=0.042]. However, there were no significant differences between the two groups in the cumulative clinical pregnancy rate and the cumulative live birth rate (all P>0.05). Raman was capable of distinguishing PCOS from non-PCOS FFs. The characteristic Raman displacement difference between the two groups is mainly concentrated in the 600-1 000 cm -1, as well as 1 168 cm -1, 1 344 cm -1, 1 440 cm -1, 1 504 cm -1, 1 632 cm -1 and 1 664 cm -1. The Raman characteristic shift database showed that the different metabolites of the two sets of FFs samples were mainly concentrated in protein, lipids, free nucleic acis, glucose, cholesterol, carotenoids, and amino acids. Mouse oocyte IVM results showed that the PCOS-FF group had a lower MⅡ rate [49.04% (77/157)] than that of non-PCOS group [65.07% (95/146), P=0.005). IVF results showed the PCOS-FF group had a significantly lower cleavage rate [46.75% (36/77)] than that of non-PCOS group [63.16% (60/95), P=0.031], but there was no significant difference in the blastocyst rate between the two groups ( P>0.05). Conclusion:Differential metabolites detected by Raman spectrum in the PCOS FFs may cause defected maturation of the oocytes, leading to infertility, and Raman spectroscopy is an effective approach towards PCOS diagnosis and the identification of metabolomics differences.

Objective:To explore the different metabolites in the follicular fluids (FFs) of polycystic ovary syndrome (PCOS) patients and non-PCOS patients and their effects on the maturation of mouse oocytes and the developmental potential of in vitro fertilization (IVF) embryos. Methods:The clinical data were collected for the retrospective cohort study. Animal experiments were conducted in a randomized controlled trial. This study included PCOS ( n=71) and non-PCOS ( n=70) patients who underwent the first IVF or intracytoplasmic sperm injection (ICSI) cycle in Shanghai JIAI Genetics & IVF institute from June 2019 to June 2020. The patients' FFs were collected and the clinical data from these patients were analyzed. Raman spectroscopy analysis technology was used to detect differences in the metabolic spectra of FFs between the two groups. Mouse GV phase oocytes were placed in FFs from PCOS patients and non-PCOS patients for in vitro maturation (IVM) culture respectively, then the matured mouse oocytes were collected for IVF. The effects of differential metabolites in FFs on mouse oocyte maturation and embryonic development were further explored. The Raman spectrum was also applied to identify the differences of the IVM spent culture media. Results:The MⅡ rate [82.19% (886/1 078)] and day 3 available embryo rate [51.30% (553/1 078)] from PCOS group were significantly lower than those of the non-PCOS group [85.85% (625/728), P=0.038; 53.30% (388/728), P=0.042]. However, there were no significant differences between the two groups in the cumulative clinical pregnancy rate and the cumulative live birth rate (all P>0.05). Raman was capable of distinguishing PCOS from non-PCOS FFs. The characteristic Raman displacement difference between the two groups is mainly concentrated in the 600-1 000 cm -1, as well as 1 168 cm -1, 1 344 cm -1, 1 440 cm -1, 1 504 cm -1, 1 632 cm -1 and 1 664 cm -1. The Raman characteristic shift database showed that the different metabolites of the two sets of FFs samples were mainly concentrated in protein, lipids, free nucleic acis, glucose, cholesterol, carotenoids, and amino acids. Mouse oocyte IVM results showed that the PCOS-FF group had a lower MⅡ rate [49.04% (77/157)] than that of non-PCOS group [65.07% (95/146), P=0.005). IVF results showed the PCOS-FF group had a significantly lower cleavage rate [46.75% (36/77)] than that of non-PCOS group [63.16% (60/95), P=0.031], but there was no significant difference in the blastocyst rate between the two groups ( P>0.05). Conclusion:Differential metabolites detected by Raman spectrum in the PCOS FFs may cause defected maturation of the oocytes, leading to infertility, and Raman spectroscopy is an effective approach towards PCOS diagnosis and the identification of metabolomics differences.