ObjectiveTo characterize the changes of metabolites of Blumea balsamifera in the process of sweating by non-targeted metabolomics， and to investigate the influence of sweating processing on the constituents of B. balsamifera. MethodsUltra performance liquid chromatography-quadrupole/electrostatic field orbitrap high resolution mass spectrometry（UPLC-Q-Exactive Orbitrap-MS） metabolomics was used to identify the metabolites in no sweating group（F1）， sweating 2 d group（F2） and sweating 4 d group（F3）， the differences of metabolites between the groups were compared by principal component analysis（PCA） and orthogonal partial least squares-discriminant analysis（OPLS-DA）， and differential metabolites were screened according to the variable importance in the projection（VIP） value>1 and P<0.05， and the pathway enrichment of the differential metabolites was analyzed by Kyoto Encyclopedia of Genes and Genomes（KEGG）. ResultsThe results of PCA and OPLS-DA showed a clear distinction between the three groups of samples， indicating significant differences in the compositions of the three groups of samples. A total of 433 differential metabolites were screened between the F1 and F2， with 154 up-regulated and 279 down-regulated， the significant up-regulated metabolites were tangeritin， 5-O-demethylnobiletin and so on， while the metabolites with significant down-regulation included alternariol， fortunellin， etc. A total of 379 differential metabolites were screened between the F2 and F3， with 150 up-regulated and 229 down-regulated， the significant up-regulated metabolites were isoimperatorin， helianyl octanoate and so on， and the significant down-regulated metabolites were hovenoside I， goyasaponin Ⅲ， etc. KEGG pathway enrichment analysis showed that tyrosine metabolism， isoquinoline alkaloid biosynthesis， phenylalanine， tyrosine and tryptophan biosynthesis， tryptophan metabolism， valine， leucine and isoleucine biosynthesis， pantothenate and coenzyme A biosynthesis may be the key pathways affecting metabolite differences of B. balsamifera after sweating treatment. ConclusionSweating can reduce the content of endophytic mycotoxins in B. balsamifera and has a great impact on the synthesis and metabolic pathways of total flavonoids and auxin. This study can provide a reference for the process research on the sweating conditions of B. balsamifera.

Objective:To establish a three-dimensional U-shaped residual coordinated attention network (URCA-Net) based on enhanced CT images for small bowel polyp detection and analyze its application effectiveness in intelligent detection of small bowel polyps.Methods:Abdominal CT data of patients with small bowel polyps were collected from the Air Force Medical Center between June 2019 and July 2023. All patients underwent bowel preparation followed by thin-slice spiral CT scanning to obtain enhanced CT arterial phase images. The data were randomly divided into training, validation and test sets in an 8∶1∶1 ratio. The URCA-Net deep learning model was used for small bowel polyp segmentation. The training set was used for model parameter training, the validation set for hyperparameter adjustment and monitoring of model generalization performance and the test set for final unbiased evaluation of the model. An early intelligent detection model for small bowel polyps was constructed, and its performance was evaluated. Evaluation metrics included pixel-level metrics for the segmentation task [Dice Similarity Coefficient (DSC)], as well as sensitivity and precision for polyp detection. A two-stage segmentation strategy was adopted: the first stage segmented the small bowel region to remove external interference, and the second stage performed polyp segmentation within the small bowel region.Results:A total of 78 subjects were included in the study, with an average age of (54±7) years. A total of 23 400 scan images were extracted, including 136 hyperplastic polyps, 298 hamartomatous polyps, 14 adenomatous polyps, and 4 cancerous polyps. On the test set, the average DSC for the first stage (small bowel segmentation) and the second stage (polyp segmentation) was 0.790 and 0.314, respectively. In the second stage task (polyp segmentation based on small bowel region), the polyp segmentation DSC increased to 0.701, with a precision of 0.836 (95% CI: 0.700-0.972) and a sensitivity of 0.759 (95% CI: 0.631-0.888) for polyp detection. Conclusion:The URCA-Net deep learning technique demonstrates good auxiliary diagnostic effectiveness in small bowel polyp detection and can provide a reference for screening and detection of small bowel polyps. The model is capable of generating high-quality segmentation results, which could facilitate evaluating polyp lesion morphology and provide support for downstream tasks such as preoperative navigation and risk prediction.

Objective:To investigate the characteristics and determinants of total scores of cerebral small vessel disease (CSVD) and to analyze the factors associated with enlarged perivascular space (EPVS) grading in pilots.Methods:The physical examination data of 72 pilots who were hospitalized and diagnosed with CSVD by MRI in the Air Force Medical Center (General Hospital of Air Force) between 2019 and 2022 was retrospectively analyzed. The pilots were grouped by the total CSVD score (0, 1, 2, 3, 4 points), and the distribution of CSVD imaging biomarkers was compared across groups. The severity of EPVS was classified into 3 levels: none or mild (0-10), moderate (11-20), and severe (>20). The impact of vascular risk factors on the total CSVD score and EPVS grading was analyzed.Results:The results of the total CSVD score showed that there were 19 cases (26.39%) with a score of 0, 43 cases (59.72%) with a score of 1, 10 cases (13.89%) with a score of 2, and 0 case with scores of 3 or 4. Among those who scored 1, there were 2 cases (4.65%) of lacunar infarction (LA), 1 case (2.33%) of moderate to severe white matter hyperintensity (WMH), 2 cases (4.65%) of cerebral microbleed (CMB), and 38 cases (88.37%) of moderate and severe EPVS. Among those who scored 2, there were 7 cases (70.00%) of LA combined with EPVS, 2 cases (20.00%) of CMB combined with EPVS, and 1 case (10.00%) of WMH combined with EPVS. According to the CSVD imaging classification of these pilots, there were 9 cases (12.50%) of LA, 52 cases (72.22%) of WMH, 4 cases (5.60%) of CMB and 61 cases (84.72%) of EPVS. Multiple ordered Logistic regression analysis showed that systolic blood pressure ( OR=1.068, 95% CI: 1.016-1.122) and high-density lipoprotein cholesterol ( OR=0.111, 95% CI: 0.015-0.843) made a difference in the total CSVD score. High-density lipoprotein cholesterol ( OR=0.166, 95% CI: 0.031-0.893) could affect the EPVS grading. Spearman′s correlation analysis showed that the systolic blood pressure level was positively correlated with the total CSVD score ( r=0.299, P=0.011), while the high-density lipoprotein cholesterol level was negatively correlated with the total CSVD score and EPVS grading ( r=-0.313, -0.263, P=0.041, 0.026). Conclusions:The total CSVD score of pilots is at a mild level with EPVS as the leading contributor. The systolic blood pressure and the high-density lipoprotein cholesterol level are determinants for the total CSVD score, while the high-density lipoprotein cholesterol level is a determinant for the EPVS grading of pilots. Blood pressure control and lipid regulation can go a long way towards preventing CSVD in pilots. The total CSVD score is of value for stratified evaluation and individual identification of pilots with CSVD.

Objective:To analyze the degree of intervertebral disc degeneration above and below the vertebral body in pilots with lumbar spondylolysis.Methods:The medical records of 66 pilots who underwent lumbar imaging examinations at the Air Force Medical Center between September 2011 and January 2025 were retrospectively analyzed. The degree of intervertebral disc degeneration was compared between 33 pilots with lumbar spondylolysis and another 33 age-matched pilots without spondylolysis. The spondylolysis group was divided into subgroups with/without spondylolisthesis and unilateral/bilateral subgroups. The degree of disc degeneration above and below the vertebral body was compared between these subgroups using the modified Pfirrmann grading system.Results:The modified Pfirrmann scores of the discs above and below the spondylolytic vertebral body in the spondylolysis group were significantly higher than those at the corresponding segments in the non-spondylolysis group ( Z=-2.39, -4.41, P=0.017,<0.001). In pilots with spondylolysis accompanied by spondylolisthesis, the modified Pfirrmann score of the disc below the slipped vertebral body was significantly higher than that in pilots without spondylolisthesis ( Z=-3.02, P=0.003). However, there was no statistically significant difference in the modified Pfirrmann score of the disc above the slipped vertebral body between pilots with and without spondylolisthesis ( P>0.05). No significant differences were observed in the modified Pfirrmann scores of the discs above and below the vertebral body between pilots with unilateral and bilateral spondylolysis (both P>0.05). Conclusions:Pilots with lumbar spondylolysis exhibit severe intervertebral disc degeneration above and below the affected vertebral body. Spondylolisthesis can continue to exacerbate degeneration in the disc inferior to the affected vertebra.

Objective:To establish a three-dimensional U-shaped residual coordinated attention network (URCA-Net) based on enhanced CT images for small bowel polyp detection and analyze its application effectiveness in intelligent detection of small bowel polyps.Methods:Abdominal CT data of patients with small bowel polyps were collected from the Air Force Medical Center between June 2019 and July 2023. All patients underwent bowel preparation followed by thin-slice spiral CT scanning to obtain enhanced CT arterial phase images. The data were randomly divided into training, validation and test sets in an 8∶1∶1 ratio. The URCA-Net deep learning model was used for small bowel polyp segmentation. The training set was used for model parameter training, the validation set for hyperparameter adjustment and monitoring of model generalization performance and the test set for final unbiased evaluation of the model. An early intelligent detection model for small bowel polyps was constructed, and its performance was evaluated. Evaluation metrics included pixel-level metrics for the segmentation task [Dice Similarity Coefficient (DSC)], as well as sensitivity and precision for polyp detection. A two-stage segmentation strategy was adopted: the first stage segmented the small bowel region to remove external interference, and the second stage performed polyp segmentation within the small bowel region.Results:A total of 78 subjects were included in the study, with an average age of (54±7) years. A total of 23 400 scan images were extracted, including 136 hyperplastic polyps, 298 hamartomatous polyps, 14 adenomatous polyps, and 4 cancerous polyps. On the test set, the average DSC for the first stage (small bowel segmentation) and the second stage (polyp segmentation) was 0.790 and 0.314, respectively. In the second stage task (polyp segmentation based on small bowel region), the polyp segmentation DSC increased to 0.701, with a precision of 0.836 (95% CI: 0.700-0.972) and a sensitivity of 0.759 (95% CI: 0.631-0.888) for polyp detection. Conclusion:The URCA-Net deep learning technique demonstrates good auxiliary diagnostic effectiveness in small bowel polyp detection and can provide a reference for screening and detection of small bowel polyps. The model is capable of generating high-quality segmentation results, which could facilitate evaluating polyp lesion morphology and provide support for downstream tasks such as preoperative navigation and risk prediction.

Objective:To investigate the characteristics and determinants of total scores of cerebral small vessel disease (CSVD) and to analyze the factors associated with enlarged perivascular space (EPVS) grading in pilots.Methods:The physical examination data of 72 pilots who were hospitalized and diagnosed with CSVD by MRI in the Air Force Medical Center (General Hospital of Air Force) between 2019 and 2022 was retrospectively analyzed. The pilots were grouped by the total CSVD score (0, 1, 2, 3, 4 points), and the distribution of CSVD imaging biomarkers was compared across groups. The severity of EPVS was classified into 3 levels: none or mild (0-10), moderate (11-20), and severe (>20). The impact of vascular risk factors on the total CSVD score and EPVS grading was analyzed.Results:The results of the total CSVD score showed that there were 19 cases (26.39%) with a score of 0, 43 cases (59.72%) with a score of 1, 10 cases (13.89%) with a score of 2, and 0 case with scores of 3 or 4. Among those who scored 1, there were 2 cases (4.65%) of lacunar infarction (LA), 1 case (2.33%) of moderate to severe white matter hyperintensity (WMH), 2 cases (4.65%) of cerebral microbleed (CMB), and 38 cases (88.37%) of moderate and severe EPVS. Among those who scored 2, there were 7 cases (70.00%) of LA combined with EPVS, 2 cases (20.00%) of CMB combined with EPVS, and 1 case (10.00%) of WMH combined with EPVS. According to the CSVD imaging classification of these pilots, there were 9 cases (12.50%) of LA, 52 cases (72.22%) of WMH, 4 cases (5.60%) of CMB and 61 cases (84.72%) of EPVS. Multiple ordered Logistic regression analysis showed that systolic blood pressure ( OR=1.068, 95% CI: 1.016-1.122) and high-density lipoprotein cholesterol ( OR=0.111, 95% CI: 0.015-0.843) made a difference in the total CSVD score. High-density lipoprotein cholesterol ( OR=0.166, 95% CI: 0.031-0.893) could affect the EPVS grading. Spearman′s correlation analysis showed that the systolic blood pressure level was positively correlated with the total CSVD score ( r=0.299, P=0.011), while the high-density lipoprotein cholesterol level was negatively correlated with the total CSVD score and EPVS grading ( r=-0.313, -0.263, P=0.041, 0.026). Conclusions:The total CSVD score of pilots is at a mild level with EPVS as the leading contributor. The systolic blood pressure and the high-density lipoprotein cholesterol level are determinants for the total CSVD score, while the high-density lipoprotein cholesterol level is a determinant for the EPVS grading of pilots. Blood pressure control and lipid regulation can go a long way towards preventing CSVD in pilots. The total CSVD score is of value for stratified evaluation and individual identification of pilots with CSVD.

Objective:To analyze the degree of intervertebral disc degeneration above and below the vertebral body in pilots with lumbar spondylolysis.Methods:The medical records of 66 pilots who underwent lumbar imaging examinations at the Air Force Medical Center between September 2011 and January 2025 were retrospectively analyzed. The degree of intervertebral disc degeneration was compared between 33 pilots with lumbar spondylolysis and another 33 age-matched pilots without spondylolysis. The spondylolysis group was divided into subgroups with/without spondylolisthesis and unilateral/bilateral subgroups. The degree of disc degeneration above and below the vertebral body was compared between these subgroups using the modified Pfirrmann grading system.Results:The modified Pfirrmann scores of the discs above and below the spondylolytic vertebral body in the spondylolysis group were significantly higher than those at the corresponding segments in the non-spondylolysis group ( Z=-2.39, -4.41, P=0.017,<0.001). In pilots with spondylolysis accompanied by spondylolisthesis, the modified Pfirrmann score of the disc below the slipped vertebral body was significantly higher than that in pilots without spondylolisthesis ( Z=-3.02, P=0.003). However, there was no statistically significant difference in the modified Pfirrmann score of the disc above the slipped vertebral body between pilots with and without spondylolisthesis ( P>0.05). No significant differences were observed in the modified Pfirrmann scores of the discs above and below the vertebral body between pilots with unilateral and bilateral spondylolysis (both P>0.05). Conclusions:Pilots with lumbar spondylolysis exhibit severe intervertebral disc degeneration above and below the affected vertebral body. Spondylolisthesis can continue to exacerbate degeneration in the disc inferior to the affected vertebra.

Long non-coding RNA(lncRNA)is a class of endogenous non-coding RNA with a length of more than 200 nt.Due to lack of open reading frame(ORF),they lack the ability to directly encode proteins,but they play a crucial role in gene regulation.They are widely involved in epigenetics,transcription,translation,modification and degradation,thereby affecting the life activities of the body,and their expression imbalance is closely related to the occurrence and development of diseases.Therefore,analyzing the inherent characteristics of lncRNA and revealing its intrinsic role can not only deepen our understanding of human physiological and pathological processes,but also provide new ideas and potential solutions for the diagnosis,prevention and treatment of diseases.So as to provide references for the related research of lncRNAs.

Objective To analyze the incidence of and risk factors for white matter hyperintensity(WMH)in pilots.Methods A retrospective case-control study was performed.The subjects were 1,415 pilots ages 19 to 58 who had undergone cranial MRI examination in a hospital between September 2020 and August 2023.They were divided into two groups:the WMH group and the control group(without WMH).Univariate and multivariate logistic regression analysis were used to identify the risk factors for WMH.Results There were 219 cases in the WMH group and 1,196 cases in the control group.The total incidence of WMH was approximately 15.48％,with mild,moderate and severe cases of WMH accounting for 70.78％,24.20％,and 0.47％,respectively.Regression analysis results showed that age(OR=1.625,95％CI:1.099-2.404)and flight time(OR=1.282,95％CI:1.033-1.592)were risk factors for WMH in pilots.Conclusion The incidence of WMH in pilots was approximately 15.48％.Most of WMH were mild according to Fazekas grading.Age increase and long flight time are risk factors for WMH in pilots.

Laboratory testing is a vital chain in the prevention and control of genital chlamydia trachomatis infection. The prevalence of genital chlamydia trachomatis infection is high, but the detection rate of the infection is low in men who have sex with men (MSM) in China. Self-sampling for genital chlamydia trachomatis detection by MSM is a new option to address this problem, which would play a significant role in expanding genital chlamydia trachomatis infection screening in this population. This paper summarizes the progress in research of self-sampling for the detection of genital chlamydia trachomatis and the related factors in MSM both at home and abroad to provide reference for the promotion of self-sampling for the detection of genital chlamydia trachomatis in this population.