Objective To establish an analytical strategy covering multi-dataset processing, recursive feature elimination (RFE) screening and multi-model evaluation based on multiple machine learning algorithms, so as to screen radiation-sensitive genes and verify the feasibility of the evaluation strategy. Methods Qualified radiation transcriptome datasets were retrieved from public gene expression databases. Following standardized data preprocessing and feature preselection, 13 machine learning algorithms were adopted to construct models. The performance of each model was compared and validated in independent datasets. Results A total of 38 eligible datasets were included. Sixteen differentially expressed genes unreported in existing literature were screened out, among which ugcrhl, pdcl3, mct4, h2-g2 and fam120aos were correlated with radiation phenotypes. Ensemble learning algorithms including random forest and gradient boosting exhibited the optimal comprehensive performance. Independent dataset verification confirmed that the screened genes overlapped with known radiation-sensitive genes, and the model performance was consistent with the findings. Conclusion The machine learning strategy constructed in this study can effectively explore potential radiation-sensitive genes, and provides methodological support for subsequent relevant studies.

Objective To establish an analytical strategy covering multi-dataset processing, recursive feature elimination (RFE) screening and multi-model evaluation based on multiple machine learning algorithms, so as to screen radiation-sensitive genes and verify the feasibility of the evaluation strategy. Methods Qualified radiation transcriptome datasets were retrieved from public gene expression databases. Following standardized data preprocessing and feature preselection, 13 machine learning algorithms were adopted to construct models. The performance of each model was compared and validated in independent datasets. Results A total of 38 eligible datasets were included. Sixteen differentially expressed genes unreported in existing literature were screened out, among which ugcrhl, pdcl3, mct4, h2-g2 and fam120aos were correlated with radiation phenotypes. Ensemble learning algorithms including random forest and gradient boosting exhibited the optimal comprehensive performance. Independent dataset verification confirmed that the screened genes overlapped with known radiation-sensitive genes, and the model performance was consistent with the findings. Conclusion The machine learning strategy constructed in this study can effectively explore potential radiation-sensitive genes, and provides methodological support for subsequent relevant studies.

Objective To establish an analytical strategy covering multi-dataset processing, recursive feature elimination (RFE) screening and multi-model evaluation based on multiple machine learning algorithms, so as to screen radiation-sensitive genes and verify the feasibility of the evaluation strategy. Methods Qualified radiation transcriptome datasets were retrieved from public gene expression databases. Following standardized data preprocessing and feature preselection, 13 machine learning algorithms were adopted to construct models. The performance of each model was compared and validated in independent datasets. Results A total of 38 eligible datasets were included. Sixteen differentially expressed genes unreported in existing literature were screened out, among which ugcrhl, pdcl3, mct4, h2-g2 and fam120aos were correlated with radiation phenotypes. Ensemble learning algorithms including random forest and gradient boosting exhibited the optimal comprehensive performance. Independent dataset verification confirmed that the screened genes overlapped with known radiation-sensitive genes, and the model performance was consistent with the findings. Conclusion The machine learning strategy constructed in this study can effectively explore potential radiation-sensitive genes, and provides methodological support for subsequent relevant studies.

Objective:To explore and analyze the feasibility and efficacy of the 22G needle-guided suture for orbital septum fat flap fixation on the periosteum.Methods:The retrospective study was conducted. From January 2022 to November 2023, patients with tear trough deformity and eyelid bags underwent surgery of releasing the orbicularis retaining ligament (ORL) complex, orbital septum fat pad combined with 22G needle-guided suture in Department of Burn and Plastic Surgery, the First Affiliated Hospital, and College of Clinical Medicine of Henan University of Science and Technology. Postoperative follow-up was conducted to observe the occurrence of complications. The lacrimal depression deformity was classified according to the Hirmand standard and the degree of lower eyelid bags was graded to evaluate the surgical outcome. Patients were evaluated their satisfaction using the visual analogue scale (very dissatisfied, dissatisfied, average, satisfied, very satisfied).Results:A total of 32 patients (30 females and 2 males) were included in this study. The age range was 31-62 years old with an average of 50.2 years. All patients were followed up for 6 months postoperatively. None of the patients had any severe complications, such as inferior eyelid ectropion, inferior eyelid retraction, scar hyperplasia, and diplopia. Four patients showed mild eyelid-eyeball separation, two patients had conjunctival edema, and all recovered in 1 month. The orbital fat protrusion, tear trough depression deformity, and lower eyelid skin laxity were significantly improved compared to before the operation. Postoperative satisfaction was 22 cases, very satisfied 10 cases, and patient satisfaction rate was 100% (32/32) after surgery.Conclusion:The method of 22G needle-guided suture to fix orbital septum fat pad represents a technically feasible, easy, and suitable for promotion.

BACKGROUND:Some research has suggested that regulation of gut microbiota may influence the course of intervertebral disc degeneration.However,the causal relationship of gut microbiota on intervertebral disc degeneration is unknown.OBJECTIVE:To assess the potential causal relationship between gut microbiota and intervertebral disc degeneration using a Mendelian randomization method.METHODS:Genome-wide association analysis summary statistics for 473 gut microbiota and genome-wide association analysis summary data for intervertebral disc degeneration from the R11 of the FinnGen database(46 205 cases of intervertebral disc degeneration and 322 314 controls)from the most recent publicly available publication were applied.Inverse variance weighting,MR-Egger regression,weighted median,weighted modeling,and simple modeling were used to investigate the causal relationship between gut microbiota and intervertebral disc degeneration.Sensitivity analyses were used to test whether the results of Mendelian randomization analyses were reliable.Reverse Mendelian randomization was performed with all gut microbiota as the outcomes for effect analysis and sensitivity analysis.RESULTS AND CONCLUSION:(1)The results of the inverse variance weighting method of the forward Mendelian randomization method showed that the order Trichosporonaceae,the family UBA-6960,the family Anaerobes thermophilus,the family Salmonellaceae,the genus Pseudomonas tufts,the species Gordonella and the species Euclidia showed a positive correlation with intervertebral disc degeneration.The order Spirochaetes,the order Pseudomonas,the family Spirochaetaceae,the genus CAG-776,the genus Helicobacter,the species CAG-448 sp003150135,the species CAG-776 sp000438195,the species Brautella-A sp000285855 and the species Hanson's Brautella showed a negative correlation with intervertebral disc degeneration.(2)The results of reverse Mendelian randomization showed that intervertebral disc degeneration was positively correlated with the genus Bartonella rosea,the genus Geobacillus C,the species Escherichia fumigatus,the species Propionibacterium fumigatus,the species UBA-1777 sp900319835,the species Pseudomonas aeruginosa and the species Bacillus subtilis,while negatively correlated with the species Streptomyces mingoldii,the species Prevotella sp000434975,the species Brault's A sp000285855,the species CAG-194 sp002441865 and the species CAG-590 sp000431135.(3)No heterogeneity or horizontal pleiotropy was found in the two-way sensitivity analysis.(4)The results described above indicate that the causal relationship between gut microbiota and intervertebral disc degeneration based on the Finnish database contributes to the exploration on new biomarkers for the early prediction and treatment of intervertebral disc degeneration in clinical practice.In addition,the establishment of a large database and the integration of medical data from multiple centers can be drawn upon in biomedical research in China to provide a solid foundation for studying the relationship between gut microbiota and intervertebral disc degeneration.We will strengthen communication and cooperation with research teams in other countries to jointly promote the research on the relationship between gut microbiota and diseases and contribute to the development of global medicine.

Objective:To explore the correlation between palm temperature,disease activity,and traditional chinese medicine syndrome types in patients with rheumatoid arthritis(RA).Methods:80 RA patients(RA group)who were admitted to our hospital from April 2022 to June 2024 were selected,they were divided into high group(DAS28 score＞5.1 score)and low to moderate group(2.6 score ≤ DAS28 score≤5.1 score)according to the 28 joint disease activity scores(DAS28).70 healthy volunteers who underwent physical examinations during the same period(control group)were selected.The palm temperature,erythrocyte sedimentation rate(ESR),C-reactive protein(CRP),and DAS28 scores between the control group and RA group were compared.The palm temperature,ESR,and CRP levels between low to moderate group and high group were compared.The correlation between palm temperature and disease activity,ESR,and CRP levels in RA patients was analyzed by Pearson correlation.The distribution of traditional chinese medicine syndrome types in RA patients was observed,the palm temperature,ESR,and CRP levels of RA patients with different traditional chinese medicine syndrome types were compared.Results:The palm temperature,ESR,CRP levels,and DAS28 score in the RA group were higher than those in the control group(P＜0.05).The palm temperature,ESR,and CRP levels in the high group were higher than those in the low to moderate group(P＜0.05).Pearson correlation analysis results showed that,the palm temperature of RA patients was positively correlated with DAS28 score,ESR,and CRP levels(P＜0.05).Among 80 RA patients,there were 17 cases(21.25％)of liver and kidney deficiency syndrome,23 cases(29.02％)of cold and dampness obstruction syndrome,14 cases(17.86％)of qi and blood deficiency syndrome,17 cases(21.47％)of damp heat obstruction syndrome,and 9 cases(11.52％)of phlegm and blood stasis obstruction syndrome.The palm temperature,ESR,and CRP levels of patients with Qi and blood deficiency syndrome,liver and kidney deficiency syndrome,and phlegm and blood stasis obstruction syndrome increased in sequence and were higher than those of patients with damp heat obstruction syndrome and cold and dampness obstruction syndrome(P＜0.05).There was no statistical difference in palm temperature,ESR,and CRP levels between the groups of damp heat obstruction syndrome and cold and dampness obstruction syndrome(P＞0.05).Conclusion:There is a certain correlation between the palm temperature and disease activity and traditional chinese medicine syndrome types of RA patients.Regular observation of palm temperature,ESR,CRP levels,and DAS28 score is helpful for assessing the condition of RA patients.

Objective:To explore the correlation between palm temperature,disease activity,and traditional chinese medicine syndrome types in patients with rheumatoid arthritis(RA).Methods:80 RA patients(RA group)who were admitted to our hospital from April 2022 to June 2024 were selected,they were divided into high group(DAS28 score＞5.1 score)and low to moderate group(2.6 score ≤ DAS28 score≤5.1 score)according to the 28 joint disease activity scores(DAS28).70 healthy volunteers who underwent physical examinations during the same period(control group)were selected.The palm temperature,erythrocyte sedimentation rate(ESR),C-reactive protein(CRP),and DAS28 scores between the control group and RA group were compared.The palm temperature,ESR,and CRP levels between low to moderate group and high group were compared.The correlation between palm temperature and disease activity,ESR,and CRP levels in RA patients was analyzed by Pearson correlation.The distribution of traditional chinese medicine syndrome types in RA patients was observed,the palm temperature,ESR,and CRP levels of RA patients with different traditional chinese medicine syndrome types were compared.Results:The palm temperature,ESR,CRP levels,and DAS28 score in the RA group were higher than those in the control group(P＜0.05).The palm temperature,ESR,and CRP levels in the high group were higher than those in the low to moderate group(P＜0.05).Pearson correlation analysis results showed that,the palm temperature of RA patients was positively correlated with DAS28 score,ESR,and CRP levels(P＜0.05).Among 80 RA patients,there were 17 cases(21.25％)of liver and kidney deficiency syndrome,23 cases(29.02％)of cold and dampness obstruction syndrome,14 cases(17.86％)of qi and blood deficiency syndrome,17 cases(21.47％)of damp heat obstruction syndrome,and 9 cases(11.52％)of phlegm and blood stasis obstruction syndrome.The palm temperature,ESR,and CRP levels of patients with Qi and blood deficiency syndrome,liver and kidney deficiency syndrome,and phlegm and blood stasis obstruction syndrome increased in sequence and were higher than those of patients with damp heat obstruction syndrome and cold and dampness obstruction syndrome(P＜0.05).There was no statistical difference in palm temperature,ESR,and CRP levels between the groups of damp heat obstruction syndrome and cold and dampness obstruction syndrome(P＞0.05).Conclusion:There is a certain correlation between the palm temperature and disease activity and traditional chinese medicine syndrome types of RA patients.Regular observation of palm temperature,ESR,CRP levels,and DAS28 score is helpful for assessing the condition of RA patients.

BACKGROUND:Some research has suggested that regulation of gut microbiota may influence the course of intervertebral disc degeneration.However,the causal relationship of gut microbiota on intervertebral disc degeneration is unknown.OBJECTIVE:To assess the potential causal relationship between gut microbiota and intervertebral disc degeneration using a Mendelian randomization method.METHODS:Genome-wide association analysis summary statistics for 473 gut microbiota and genome-wide association analysis summary data for intervertebral disc degeneration from the R11 of the FinnGen database(46 205 cases of intervertebral disc degeneration and 322 314 controls)from the most recent publicly available publication were applied.Inverse variance weighting,MR-Egger regression,weighted median,weighted modeling,and simple modeling were used to investigate the causal relationship between gut microbiota and intervertebral disc degeneration.Sensitivity analyses were used to test whether the results of Mendelian randomization analyses were reliable.Reverse Mendelian randomization was performed with all gut microbiota as the outcomes for effect analysis and sensitivity analysis.RESULTS AND CONCLUSION:(1)The results of the inverse variance weighting method of the forward Mendelian randomization method showed that the order Trichosporonaceae,the family UBA-6960,the family Anaerobes thermophilus,the family Salmonellaceae,the genus Pseudomonas tufts,the species Gordonella and the species Euclidia showed a positive correlation with intervertebral disc degeneration.The order Spirochaetes,the order Pseudomonas,the family Spirochaetaceae,the genus CAG-776,the genus Helicobacter,the species CAG-448 sp003150135,the species CAG-776 sp000438195,the species Brautella-A sp000285855 and the species Hanson's Brautella showed a negative correlation with intervertebral disc degeneration.(2)The results of reverse Mendelian randomization showed that intervertebral disc degeneration was positively correlated with the genus Bartonella rosea,the genus Geobacillus C,the species Escherichia fumigatus,the species Propionibacterium fumigatus,the species UBA-1777 sp900319835,the species Pseudomonas aeruginosa and the species Bacillus subtilis,while negatively correlated with the species Streptomyces mingoldii,the species Prevotella sp000434975,the species Brault's A sp000285855,the species CAG-194 sp002441865 and the species CAG-590 sp000431135.(3)No heterogeneity or horizontal pleiotropy was found in the two-way sensitivity analysis.(4)The results described above indicate that the causal relationship between gut microbiota and intervertebral disc degeneration based on the Finnish database contributes to the exploration on new biomarkers for the early prediction and treatment of intervertebral disc degeneration in clinical practice.In addition,the establishment of a large database and the integration of medical data from multiple centers can be drawn upon in biomedical research in China to provide a solid foundation for studying the relationship between gut microbiota and intervertebral disc degeneration.We will strengthen communication and cooperation with research teams in other countries to jointly promote the research on the relationship between gut microbiota and diseases and contribute to the development of global medicine.

Contrast-free percutaneous coronary intervention demonstrates significant value in reducing contrast-associated risks.This article reports a case of a patient with iodine contrast allergy and complex coronary artery disease(involving the left main stem,left anterior descending artery,and diagonal branch),who successfully underwent contrast-free percutaneous coronary intervention(PCI)through the integration of CT angiography(CCTA),intravascular ultrasound(IVUS),and fractional flow reserve(FFR)technology.Preoperative CCTA delineated the anatomy and planned the procedural approach.Intraoperatively,IVUS assessed plaque burden and vascular remodeling,precisely guiding stent selection and positioning.FFR was combined to evaluate the functional significance of the left main stem lesion and the ischemic significance of the specific stenosis in the left anterior descending artery.Post-procedural assessment evaluated stent result and the degree of flow limitation in the diagonal branch.Through"structure-function"dual optimization,revascularization of the left anterior descending artery was achieved using a single-stent strategy,avoiding intervention on the left main stem.This case confirms that multi-modality imaging techniques can safely manage complex lesions,significantly reduce contrast volume,and are suitable for high-risk patients with allergies or renal insufficiency.Future efforts should focus on standardizing technical protocols and accumulating evidence-based evidence to facilitate the clinical implementation of contrast-free interventions.

Objective To improve the accuracy of intelligent detection and evaluation of traditional Chinese medicine(TCM)pieces and solve the problems of leakage,misdetection,inaccurate localization and low confidence in the study of TCM pieces identification,YOLOv3 algorithm which has good detection effect for high overlap and small targets was improved.Methods An RGB image database containing 148 commonly used TCM pieces was established.Based on the YOLOv3 algorithm model,the anchor box size was improved by K-means clustering algorithm.The CIoU loss function was introduced for bounding box regression to improve the localization accuracy and confidence of bounding boxes.The traditional non-maximum suppression was improved to DIoUNMS to reduce the problems of missed detection and false detection of dense targets with high overlap by YOLOv3 algorithm.Results 148 kinds of TCM pieces were tested with the improved algorithm,and the average detection accuracy of 98.47%was achieved,which is 1.83%better than the original YOLOv3 algorithm.It realizes better detection effect for TCM pieces in complex situations such as dense,high overlapping,etc.Problems such as leakage,misdetection,imprecise positioning and low confidence level have been alleviated to a certain extent.Conclusion The improved algorithm effectively improves the recognition accuracy and generalization ability of TCM pieces,providing a new reference for the realization of automated intelligent detection of TCM pieces.