Objective : To investigate the role and related mechanisms of IgD on the viability , proliferation , apoptosis , and other functions of Molm_13 cells. Methods: Peripheral blood serum was collected from AML patients and healthy controls. The sIgD levels were quantified by ELISA. For in vitro studies , Molm_13 cells were treated with varying concentrations of IgD. Cell viability and proliferation were assessed via CCK_8 assays , CFSE staining , and colony formation assays. Apoptosis rates were determined using an Annexin V/PI apoptosis detection kit. Preliminary exploration of the mechanisms related to IgD_induced proliferation of Molm_13 were analyzed through differential gene analysis. Results: Compared with healthy controls , the levels of sIgD in AML patients were significantly el_ evated (P < 0. 001 ) . IgD treatment dose_dependently increased Molm_13 cell viability and proliferation ( P < 0. 05) , inhibited apoptosis rates (P < 0. 001) . Conclusion IgD promotes the viability and proliferation of Molm_ 13 cells , and reduces apoptosis.

Objective:To analyze the prevalence and influencing factors of arteriosclerosis in different examination items in health check-up population.Methods:It was a cross-sectional study. A total of 4 479 subjects who underwent fundus, carotid artery color ultrasound and arteriosclerosis detector examinations in the Health Management Center at Tianjin Medical University General Hospital from January to December 2019 were selected as the study objects. The data including age, gender, family history and biochemical indicators were collected. The detection outcomes of arteriosclerosis and the distribution in different age and gender subgroups were analyzed. Kappa consistency test was used to analyze the consistency of different examination items of arteriosclerosis examination. The multiple logistic regression model was used to analyze the influencing factors of different examination items of arteriosclerosis detection. Results:Among the 4 479 subjects included in the analysis, 2 450 were male and 2 029 were female, with a mean age of (44.48±8.12) years. Arteriosclerosis was detected in one examination item in 1 167 cases (26.05%), 1 042 cases (23.26%) in two examination items, and 617 cases (13.78%) in three examination items, respectively. Among patients aged ≤40 years, 149 cases (18.91%) were detected with arteriosclerosis. In the age group of 40<-60 years, arteriosclerosis was detected in 2 660 patients (72.40%). All patients >60 years old exhibited arteriosclerosis, with 16 cases (94.12%) showing ≥2 items of arteriosclerosis. The results of fundus and carotid artery color Doppler ultrasound, fundus and arteriosclerosis detector, carotid artery color Doppler ultrasound and arteriosclerosis detector all demonstrated moderate consistency ( Kappa=0.32, 0.34, 0.24; all P<0.01). Logistic regression analysis revealed that the age ( OR=2.07, 95% CI: 1.97-2.17), male ( OR=1.60, 95% CI: 1.14-2.23), body mass index ( OR=1.10, 95% CI: 1.05-1.15), and systolic blood pressure ( OR=1.02, 95% CI: 1.01-1.03) were positively correlated with fundus arteriosclerosis (all P<0.05). Similarly, age ( OR=1.13, 95% CI: 1.12-1.14), male ( OR=2.53, 95% CI: 2.07-3.09), systolic blood pressure ( OR=1.02, 95% CI: 1.01-1.03), and low-density lipoprotein cholesterol ( OR=1.61, 95% CI: 1.16-2.23) were positively correlated with cervical arteriosclerosis, while high-density lipoprotein cholesterol ( OR=0.48, 95% CI: 0.32-0.72) was negatively correlated with cervical arteriosclerosis (all P<0.05). Furthermore, age ( OR=1.09, 95% CI: 1.08-1.11), male ( OR=1.55, 95% CI: 1.25-1.92), systolic blood pressure ( OR=1.08, 95% CI: 1.07-1.09), diastolic blood pressure ( OR=1.02, 95% CI: 1.00-1.03), postprandial blood glucose ( OR=1.09, 95% CI: 1.03-1.15), homocysteine ( OR=1.02, 95% CI: 1.00-1.03), and fibrinogen ( OR=1.26, 95% CI: 1.04-1.52) were positively correlated with systemic arterial stiffness (all P<0.05). Conclusions:The detection rates of arteriosclerosis in different examination items among the health check-up population vary. Age, male gender and systolic blood pressure are positive correlation factors for the three detection items of arteriosclerosis. For the examinees with aggregated risk factors, the multi-site and combined screening mode has certain significance for the early diagnosis and screening of arteriosclerotic diseases.

Objective:To investigate the role and mechanism of leucine-rich α-2-glycoprotein 1 (LRG1) in the fibrosis of human pterygium fibroblasts (HPFs).Methods:A total of 30 nasal primary pterygium tissues from patients who underwent pterygium excision surgery and 30 nasal normal conjunctival tissues from patients who underwent strabismus correction surgery were collected from the First Affiliated Hospital of Harbin Medical University between January 2022 and March 2023, serving as the pterygium group and normal control group, respectively.LRG1 protein expression in both groups was detected by immunofluorescence staining.The mRNA and protein levels of LRG1 and transforming growth factor-β1 (TGF-β1) were evaluated by quantitative real-time PCR (qRT-PCR) and Western blot.Primary HPFs were cultured from excised pterygium tissues using tissue block adhesion method, and cell morphology was observed.Vmentin and cytokeratin were identified by immunofluorescence staining.HPFs were divided into recombinant human LRG1 (rhLRG1) group and blank control group treated with or without 10 μg/ml rhLRG1 for 24 hours, respectively, and cell migration was evaluated via scratch assay.Additionally, HPFs were divided into blank control group, LRG1 overexpression group and LRG1 knockdown group.HPFs in LRG1 overexpression group and LRG1 knockdown group were transfected with LRG1 overexpression plasmids and small interfering RNA for 24 hours, respectively.TGF-β1 mRNA level was evaluated by qRT-PCR and expression of TGF-β1, fibronectin (FN), type Ⅲ collagen (COL3), and α-smooth muscle actin (α-SMA) proteins were evaluated by Western blot.This study adhered to the Declaration of Helsinki.The study protocol was approved by the Ethics Committee of the First Affiliated Hospital of Harbin Medical University (No.2022IIT026).Written informed consent was obtained from each subject.Results:HPFs were successfully isolated, exhibiting spindle-shaped morphology with whorled arrangement, positive identification for vimentin, and negative immunofluorescence staining for cytokeratin.The migration rate of the rhLRG1 group was (83.01±2.56)%, significantly higher than (50.32±4.97)% of the blank control group ( t=9.59, P<0.001).Immunofluorescence staining results showed that compared with normal conjunctival tissue, LRG1 protein was significantly higher expressed in pterygium tissue and was widely distributed in fibrous connective tissue and epithelial layer.Both mRNA and protein levels of LRG1 and TGF-β1 were significantly higher in the pterygium group than in the normal control group (mRNA: t=10.18, 6.15, both P<0.05.protein: t=6.83, 8.79, both P<0.05).In the LRG1 overexpression group, mRNA level of TGF-β1, and protein levels of FN, COL3 and α-SMA were significantly increased compared with the blank control and LRG1 knockdown groups (all P<0.05). Conclusions:LRG1 promotes fibrosis and enhances the migration ability in HPFs, and its mechanism may be associated with the upregulation of the TGF-β1 signaling pathway.

Objective To construct a swallowing dynamic model for simulating dysphagia caused by reduced tongue movement am-plitude.Methods A swallowing dynamic model was established based on medical imaging data from CT and videofluoroscopic swallowing study(VFSS).The finite element method was used to simulate soft tissues,while the smoothed parti-cle hydrodynamics method(SPH)was used to simulate bolus.The model's posture at each time point was com-pared with the imaging data of VFSS from twelve patients with dysphagia,and a normalization method was used for quantitative evaluation of the model's validity.By adjusting the tongue movement amplitude under different viscosity conditions,the role of tongue movement in the swallowing process was investigated,and the swallow-ing safety and efficiency were assessed.Results The tongue posture and bolus trajectory presented by the swallowing dynamic model were consistent with the VFSS imaging.The brightness in the epiglottis area in VFSS images correlated with the equivalent brightness of SPH particles in the simulation results(r=0.97).As the tongue movement amplitude reducing by 20%,the num-ber of aspirated particles,swallowing efficiency and the average velocity of bolus particles in the oropharyngeal cavity all performed well.Pudding-like fluids exhibited favorable swallowing characteristics even when tongue movement amplitude reducing significantly.Conclusion The swallowing dynamic model can simulate the human swallowing process,providing good support for re-habilitation training of patients with dysphagia and the development of specialized medical foods,demonstrating significant potential for clinical applications.

Objective:To develop and validate a 30-day readmission risk prediction model for patients with chronic obstructive pulmonary disease (COPD) using multiple machine learning algorithms.Methods:Convenience sampling was used to select 1 450 COPD patients hospitalized at Tianjin Medical University General Hospital from January 2017 to December 2023 as study subjects. Twenty-nine variables associated with readmission were included. LASSO was used to screen for primary characteristic variables associated with 30-day readmission. The 1 450 patients were divided into a training set ( n=870) and a test set ( n=580) in a 6∶4 ratio. Ten machine learning methods, including random forest, AdaBoost, extreme radient Boosting (XGB), decision tree and so on, were used for model training and testing to identify the optimal prediction model. The optimal model and SHAP were employed to analyze key features and rank characteristic importance. Results:Among 1 450 COPD patients, the 30-day readmission rate was 24.48% (355/1 450). There were no significant differences in the general information between patients in test set and training set ( P>0.05). LASSO regression analysis identified seven variables with the highest predictive value, namely regular weekly exercise, hospital stay, mean arterial pressure, forced expiratory volume in one second/forced vital capacity (FEV1/FVC), C-reactive protein, body mass index, and medication adherence. Machine learning showed that in the training set, XGB had the highest area under the receiver operating characteristic curve ( AUC), sensitivity, and F1 score of 0.943, 0.926, and 0.930, respectively. In the test set, the AUC and accuracy of XGB were 0.882 and 0.858, respectively, and XGB's various scores showed that it had good generalization and predictive performance. XGB analysis showed that medication adherence, FEV1/FVC, and regular weekly exercise were negatively correlated with the 30-day readmission risk, while body mass index, C-reactive protein, mean arterial pressure, and hospital stay were positively correlated. The characteristics ranked in order of importance were medication adherence, body mass index, C-reactive protein, mean arterial pressure, FEV1/FVC, hospital stay and regular weekly exercise. Conclusions:The XGB model has strong predictive performance and good generalization ability, which can effectively predict the 30-day readmission risk of COPD patients, assist in clinical identification of high-risk patients, implement nursing interventions, and reduce readmission rates.

Objective:To analyze the prevalence and influencing factors of arteriosclerosis in different examination items in health check-up population.Methods:It was a cross-sectional study. A total of 4 479 subjects who underwent fundus, carotid artery color ultrasound and arteriosclerosis detector examinations in the Health Management Center at Tianjin Medical University General Hospital from January to December 2019 were selected as the study objects. The data including age, gender, family history and biochemical indicators were collected. The detection outcomes of arteriosclerosis and the distribution in different age and gender subgroups were analyzed. Kappa consistency test was used to analyze the consistency of different examination items of arteriosclerosis examination. The multiple logistic regression model was used to analyze the influencing factors of different examination items of arteriosclerosis detection. Results:Among the 4 479 subjects included in the analysis, 2 450 were male and 2 029 were female, with a mean age of (44.48±8.12) years. Arteriosclerosis was detected in one examination item in 1 167 cases (26.05%), 1 042 cases (23.26%) in two examination items, and 617 cases (13.78%) in three examination items, respectively. Among patients aged ≤40 years, 149 cases (18.91%) were detected with arteriosclerosis. In the age group of 40<-60 years, arteriosclerosis was detected in 2 660 patients (72.40%). All patients >60 years old exhibited arteriosclerosis, with 16 cases (94.12%) showing ≥2 items of arteriosclerosis. The results of fundus and carotid artery color Doppler ultrasound, fundus and arteriosclerosis detector, carotid artery color Doppler ultrasound and arteriosclerosis detector all demonstrated moderate consistency ( Kappa=0.32, 0.34, 0.24; all P<0.01). Logistic regression analysis revealed that the age ( OR=2.07, 95% CI: 1.97-2.17), male ( OR=1.60, 95% CI: 1.14-2.23), body mass index ( OR=1.10, 95% CI: 1.05-1.15), and systolic blood pressure ( OR=1.02, 95% CI: 1.01-1.03) were positively correlated with fundus arteriosclerosis (all P<0.05). Similarly, age ( OR=1.13, 95% CI: 1.12-1.14), male ( OR=2.53, 95% CI: 2.07-3.09), systolic blood pressure ( OR=1.02, 95% CI: 1.01-1.03), and low-density lipoprotein cholesterol ( OR=1.61, 95% CI: 1.16-2.23) were positively correlated with cervical arteriosclerosis, while high-density lipoprotein cholesterol ( OR=0.48, 95% CI: 0.32-0.72) was negatively correlated with cervical arteriosclerosis (all P<0.05). Furthermore, age ( OR=1.09, 95% CI: 1.08-1.11), male ( OR=1.55, 95% CI: 1.25-1.92), systolic blood pressure ( OR=1.08, 95% CI: 1.07-1.09), diastolic blood pressure ( OR=1.02, 95% CI: 1.00-1.03), postprandial blood glucose ( OR=1.09, 95% CI: 1.03-1.15), homocysteine ( OR=1.02, 95% CI: 1.00-1.03), and fibrinogen ( OR=1.26, 95% CI: 1.04-1.52) were positively correlated with systemic arterial stiffness (all P<0.05). Conclusions:The detection rates of arteriosclerosis in different examination items among the health check-up population vary. Age, male gender and systolic blood pressure are positive correlation factors for the three detection items of arteriosclerosis. For the examinees with aggregated risk factors, the multi-site and combined screening mode has certain significance for the early diagnosis and screening of arteriosclerotic diseases.

Objective:To develop and validate a 30-day readmission risk prediction model for patients with chronic obstructive pulmonary disease (COPD) using multiple machine learning algorithms.Methods:Convenience sampling was used to select 1 450 COPD patients hospitalized at Tianjin Medical University General Hospital from January 2017 to December 2023 as study subjects. Twenty-nine variables associated with readmission were included. LASSO was used to screen for primary characteristic variables associated with 30-day readmission. The 1 450 patients were divided into a training set ( n=870) and a test set ( n=580) in a 6∶4 ratio. Ten machine learning methods, including random forest, AdaBoost, extreme radient Boosting (XGB), decision tree and so on, were used for model training and testing to identify the optimal prediction model. The optimal model and SHAP were employed to analyze key features and rank characteristic importance. Results:Among 1 450 COPD patients, the 30-day readmission rate was 24.48% (355/1 450). There were no significant differences in the general information between patients in test set and training set ( P>0.05). LASSO regression analysis identified seven variables with the highest predictive value, namely regular weekly exercise, hospital stay, mean arterial pressure, forced expiratory volume in one second/forced vital capacity (FEV1/FVC), C-reactive protein, body mass index, and medication adherence. Machine learning showed that in the training set, XGB had the highest area under the receiver operating characteristic curve ( AUC), sensitivity, and F1 score of 0.943, 0.926, and 0.930, respectively. In the test set, the AUC and accuracy of XGB were 0.882 and 0.858, respectively, and XGB's various scores showed that it had good generalization and predictive performance. XGB analysis showed that medication adherence, FEV1/FVC, and regular weekly exercise were negatively correlated with the 30-day readmission risk, while body mass index, C-reactive protein, mean arterial pressure, and hospital stay were positively correlated. The characteristics ranked in order of importance were medication adherence, body mass index, C-reactive protein, mean arterial pressure, FEV1/FVC, hospital stay and regular weekly exercise. Conclusions:The XGB model has strong predictive performance and good generalization ability, which can effectively predict the 30-day readmission risk of COPD patients, assist in clinical identification of high-risk patients, implement nursing interventions, and reduce readmission rates.

Objective:To investigate the role and mechanism of leucine-rich α-2-glycoprotein 1 (LRG1) in the fibrosis of human pterygium fibroblasts (HPFs).Methods:A total of 30 nasal primary pterygium tissues from patients who underwent pterygium excision surgery and 30 nasal normal conjunctival tissues from patients who underwent strabismus correction surgery were collected from the First Affiliated Hospital of Harbin Medical University between January 2022 and March 2023, serving as the pterygium group and normal control group, respectively.LRG1 protein expression in both groups was detected by immunofluorescence staining.The mRNA and protein levels of LRG1 and transforming growth factor-β1 (TGF-β1) were evaluated by quantitative real-time PCR (qRT-PCR) and Western blot.Primary HPFs were cultured from excised pterygium tissues using tissue block adhesion method, and cell morphology was observed.Vmentin and cytokeratin were identified by immunofluorescence staining.HPFs were divided into recombinant human LRG1 (rhLRG1) group and blank control group treated with or without 10 μg/ml rhLRG1 for 24 hours, respectively, and cell migration was evaluated via scratch assay.Additionally, HPFs were divided into blank control group, LRG1 overexpression group and LRG1 knockdown group.HPFs in LRG1 overexpression group and LRG1 knockdown group were transfected with LRG1 overexpression plasmids and small interfering RNA for 24 hours, respectively.TGF-β1 mRNA level was evaluated by qRT-PCR and expression of TGF-β1, fibronectin (FN), type Ⅲ collagen (COL3), and α-smooth muscle actin (α-SMA) proteins were evaluated by Western blot.This study adhered to the Declaration of Helsinki.The study protocol was approved by the Ethics Committee of the First Affiliated Hospital of Harbin Medical University (No.2022IIT026).Written informed consent was obtained from each subject.Results:HPFs were successfully isolated, exhibiting spindle-shaped morphology with whorled arrangement, positive identification for vimentin, and negative immunofluorescence staining for cytokeratin.The migration rate of the rhLRG1 group was (83.01±2.56)%, significantly higher than (50.32±4.97)% of the blank control group ( t=9.59, P<0.001).Immunofluorescence staining results showed that compared with normal conjunctival tissue, LRG1 protein was significantly higher expressed in pterygium tissue and was widely distributed in fibrous connective tissue and epithelial layer.Both mRNA and protein levels of LRG1 and TGF-β1 were significantly higher in the pterygium group than in the normal control group (mRNA: t=10.18, 6.15, both P<0.05.protein: t=6.83, 8.79, both P<0.05).In the LRG1 overexpression group, mRNA level of TGF-β1, and protein levels of FN, COL3 and α-SMA were significantly increased compared with the blank control and LRG1 knockdown groups (all P<0.05). Conclusions:LRG1 promotes fibrosis and enhances the migration ability in HPFs, and its mechanism may be associated with the upregulation of the TGF-β1 signaling pathway.

Objective To construct a swallowing dynamic model for simulating dysphagia caused by reduced tongue movement am-plitude.Methods A swallowing dynamic model was established based on medical imaging data from CT and videofluoroscopic swallowing study(VFSS).The finite element method was used to simulate soft tissues,while the smoothed parti-cle hydrodynamics method(SPH)was used to simulate bolus.The model's posture at each time point was com-pared with the imaging data of VFSS from twelve patients with dysphagia,and a normalization method was used for quantitative evaluation of the model's validity.By adjusting the tongue movement amplitude under different viscosity conditions,the role of tongue movement in the swallowing process was investigated,and the swallow-ing safety and efficiency were assessed.Results The tongue posture and bolus trajectory presented by the swallowing dynamic model were consistent with the VFSS imaging.The brightness in the epiglottis area in VFSS images correlated with the equivalent brightness of SPH particles in the simulation results(r=0.97).As the tongue movement amplitude reducing by 20%,the num-ber of aspirated particles,swallowing efficiency and the average velocity of bolus particles in the oropharyngeal cavity all performed well.Pudding-like fluids exhibited favorable swallowing characteristics even when tongue movement amplitude reducing significantly.Conclusion The swallowing dynamic model can simulate the human swallowing process,providing good support for re-habilitation training of patients with dysphagia and the development of specialized medical foods,demonstrating significant potential for clinical applications.

At present， the process and methodology of patient guidelines （PGs） development varies greatly and lacks systematic and standardised guidance. In addition to the interviews with PG developers， we have sorted out the relevant methodology for the adaptation and development of existing clinical practice guideline recommendations and facilitated expert deliberations to achieve a consensus， so as to finally put forward a proposal for guidance on the process and methodology for the development of PGs. The development of PGs can be divided into the preparation stage， the construction stage， and the completion stage in general， but the specific steps vary according to the different modes of development of PGs. The development process of Model 1 is basically the same as the patient version of the guideline development process provided by the International Guidelines Network， i.e.， team formation， screening of recommendations， guideline drafing， user testing and feedback， approval and dissemination. The developer should also first determine the need for and scope of translating the clinical practice guideline into a patient version during the preparation phase. Model 2 adds user experience and feedback to the conventional clinical practice guideline development process （forming a team， determining the scope of the PG， searching， evaluating and integrating evidence， forming recommendations， writing the guideline， and expert review）. Based on the different models， we sort out the process and methods of PG development and introduce the specific methods of PG development， including how to identify the clinical problem and how to form recommendations based on the existing clinical practice guidelines， with a view to providing reference for guideline developers and related researchers.