Objective To explore the correlation between lymph node metastasis and clinicopathological features of lung adenocarcinoma with diameter≤3 cm. Methods The clinicopathologic data of the patients with lung adenocarcinoma≤3 cm in diameter were retrospectively analyzed. The relationship between lymph node metastasis and age, gender, smoking history, pathological subtype, tumor diameter, pleural invasion, vascular invasion and other factors was analyzed. The risk factors of lymph node metastasis were analyzed by univariate and multivariate logistic regression. Results Finally 1 718 patients were collected, including 697 males and 1 021 females with an average age of (58.89±9.85) years. The total lymph node metastasis rate was 12.9%, among whom 452 patients of adenocarcinoma in situ and minimally invasive adenocarcinoma did not have lymph node metastasis, and the lymph node metastasis rate of invasive lung adenocarcinoma was 17.5%. Multivariate analysis showed that tumor diameter, micropapillary subtype, solid subtype, micropapillary component, solid component, vascular invasion and pleural invasion were independent risk factors for lymph node metastasis of invasive lung adenocarcinoma with diameter≤3 cm (P<0.05). While age, lepidic subtype and lepidic component were independent protective factors for lymph node metastasis (P<0.05). Conclusion Clinicopathological features can help predict lymph node metastasis of lung adenocarcinoma with diameter≤3 cm.

Objective To explore the risk factors and incidence of epiretinal membrane(ERM)formation following scleral buckling(SB)for rhegmatogenous retinal detachment(RRD),and to construct a risk prediction model to facilitate screening of high-risk populations and prevent ERM formation.Methods RRD patients who underwent SB in the Second Affiliated Hospital of Harbin Medical University between February 2022 and April 2024 were included in the study.The pa-tients were divided into occurrence and non-occurrence groups according to whether they developed ERM.Patient data were analyzed,and univariate Cox regression analysis was performed to select variables,which were then incorporated into the multivariate Cox regression model for the identification of risk factors for ERM formation after SB in RRD patients.A predictive model for ERM risk in RRD patients was constructed based on this data,and nomograms,receiver operating characteristic(ROC)curves,and calibration curves were drawn to evaluate and validate the diagnostic performance of the model.Results A total of 126 RRD patients(126 eyes)who underwent SB were included.There were 27 cases develo-ping ERM(occurrence group)and 99 not developing ERM(non-occurrence group),with an ERM incidence of 21.4％.Multivariate Cox regression analysis revealed that a history of diabetes mellitus[Hazard ratio(HR)=3.52,95％CI:1.37-9.02,P=0.009],preoperative proliferative vitreoretinopathy(PVR)(HR=13.00,95％CI:5.18-32.63,P＜0.001),and ≥4 retinal holes(HR=2.33,95％CI:1.04-5.23,P=0.041)were independent influence factors for ERM formation in RRD patients.ROC curve analysis showed that the area under the curve(AUC)was 0.840(95％CI:0.740-0.940)at 30 days and 0.904(95％CI:0.834-0.975)at 90 days.Conclusion A history of diabetes mellitus,preoperative PVR,and ≥4 retinal holes are factors influencing the development of ERM after SB in RRD patients.It is verified that the risk prediction model constructed based on these factors can accurately predict the risk of ERM formation within 6 months in RRD patients.

Objective:To explore the effects of vitamin D supplementation combined with suspended lumbar abdominal muscle training on rehabilitation and bone metabolism indexes of patients after OVCF.Methods:A total of 140 patients with osteoporotic vertebral compression fractures (OVCF) treated at Yantaishan Hospital from Jun. 2021 to Jun. 2024 were included in this study. Patients were randomly assigned to a control group and an observation group using a random number table, with 70 patients in each group. The control group received suspension lumbar and abdominal muscle training, while the observation group received vitamin D supplementation combined with suspension lumbar and abdominal muscle training. Outcomes evaluated included VAS scores, Oswestry Disability Index (ODI) , Cobb Angle, lumboabdominal muscle strength, and serum levels of 25-hydroxyvitamin D [25 (OH) D], bone mineral density T value, and bone metabolism markers [serum osteocalcin (OC) , calcitonin (CT) , total type I collagen amino-terminal propeptide (tPINP) , type I collagen carboxy-terminal peptide β special sequence (β-CTX) , intact parathyroid hormone (iPTH) , and bone-specific alkaline phosphatase (BALP) ] measured by chemiluminescence.Results:In comparison with the control group, the VAS and ODI scores in the observation group were lower after treatment ( t=13.66, t=9.87, P < 0.05) . Compared to the control group, the lumbar muscle strength score of the observation group, the 25 (OH) D level and bone mineral density T value was higher after treatment ( t=57.63, t=6.64, t=5.01, P < 0.05) , and the Cobb Angle was smaller ( t=9.21, P < 0.05) .Compared with the control group, the bone metabolism indexes OC, CT, tPINP, and BALP were higher in the observation group after treatment ( t=4.21, t=3.05, t=2.66, t=3.16, P < 0.05) , while the iPTH and β-CTX were lower ( t=7.28, t=3.50, P < 0.05) . Conclusions:Vitamin D supplementation combined with suspended lumbar and abdominal muscle training can promote postoperative rehabilitation of OVCF patients and improve the level of bone metabolism indexes after surgery.

Objective:To develop and evaluate a deep learning-based automatic measurement model for panoramic ultrasound biomicroscopy (UBM) images.Methods:A diagnostic test study was conducted.Preoperative UBM examination results of 372 patients who underwent implantable collamer lens (ICL) implantation were collected at the Eye Center of Renmin Hospital of Wuhan University between February 2021 and March 2023.A total of 1 368 panoramic UBM images were obtained to establish an image database.The dataset was divided into a training set (760 images), a validation set (86 images) and an internal test set (522 images).An expert panel consisting of three ophthalmologists annotated the images.The UNet+ + network was used to automatically segment anterior segment tissues, such as the cornea, lens and iris.In addition, image processing techniques and geometric localization algorithms were developed to automatically identify the anatomical landmarks of pupil diameter (PD), anterior chamber depth (ACD), angle-to-angle distance (ATA) and sulcus-to-sulcus distance (STS) to complete the measurement of these parameters.Additionally, 480 panoramic UBM images of 135 patients (240 eyes) from Aier Eye Hospital of Wuhan University were used as an external test set to further evaluate the performance of the model in different centers.The consistency between the measurements from the model and expert panel, the Pentacam system was assessed.Finally, 150 images were randomly selected from the external test set for a human-machine comparison to further evaluate the model's performance.This study adhered to the Declaration of Helsinki.The study protocol was approved by the Ethics Committee of Renmin Hospital of Wuhan University (No.WDRY-2022-K109) and Aier eye Hospital of Wuhan University (No.2023IRBKY120903).Written informed consent was obtained from each subject.Results:In the internal test dataset and external test dataset, with manual labeling as the reference standard, the model achieved a mean Dice coefficient of not less than 0.882.At least 95.65% of the anatomical landmark localization results had Euclidean distance differences within 250 μm.The intraclass correlation coefficients (ICCs) for the measurements of PD, ACD, angle-to-angle ATA, and STS were at least 0.958, with mean relative errors not exceeding 2.407%.With the Pentacam measurements as the reference standard, the ICCs for PD in the internal and external test sets were 0.540 and 0.466, respectively, while the ICCs for ACD were 0.946 and 0.908, respectively.In the human-machine comparison, the ICCs between the model's measurements and those of senior experts were all not lower than 0.969.Conclusions:The deep learning-based model can automatically measure anterior segment parameters from preoperative panoramic UBM images of patients undergoing ICL surgery.The model demonstrates a consistency comparable to that of senior experts, while providing higher efficiency.In terms of ACD measurement, the model shows good agreement between the measurements obtained from the model and Pentacam system.

Objective:To explore the effects of vitamin D supplementation combined with suspended lumbar abdominal muscle training on rehabilitation and bone metabolism indexes of patients after OVCF.Methods:A total of 140 patients with osteoporotic vertebral compression fractures (OVCF) treated at Yantaishan Hospital from Jun. 2021 to Jun. 2024 were included in this study. Patients were randomly assigned to a control group and an observation group using a random number table, with 70 patients in each group. The control group received suspension lumbar and abdominal muscle training, while the observation group received vitamin D supplementation combined with suspension lumbar and abdominal muscle training. Outcomes evaluated included VAS scores, Oswestry Disability Index (ODI) , Cobb Angle, lumboabdominal muscle strength, and serum levels of 25-hydroxyvitamin D [25 (OH) D], bone mineral density T value, and bone metabolism markers [serum osteocalcin (OC) , calcitonin (CT) , total type I collagen amino-terminal propeptide (tPINP) , type I collagen carboxy-terminal peptide β special sequence (β-CTX) , intact parathyroid hormone (iPTH) , and bone-specific alkaline phosphatase (BALP) ] measured by chemiluminescence.Results:In comparison with the control group, the VAS and ODI scores in the observation group were lower after treatment ( t=13.66, t=9.87, P < 0.05) . Compared to the control group, the lumbar muscle strength score of the observation group, the 25 (OH) D level and bone mineral density T value was higher after treatment ( t=57.63, t=6.64, t=5.01, P < 0.05) , and the Cobb Angle was smaller ( t=9.21, P < 0.05) .Compared with the control group, the bone metabolism indexes OC, CT, tPINP, and BALP were higher in the observation group after treatment ( t=4.21, t=3.05, t=2.66, t=3.16, P < 0.05) , while the iPTH and β-CTX were lower ( t=7.28, t=3.50, P < 0.05) . Conclusions:Vitamin D supplementation combined with suspended lumbar and abdominal muscle training can promote postoperative rehabilitation of OVCF patients and improve the level of bone metabolism indexes after surgery.

Objective:To develop and evaluate a deep learning-based automatic measurement model for panoramic ultrasound biomicroscopy (UBM) images.Methods:A diagnostic test study was conducted.Preoperative UBM examination results of 372 patients who underwent implantable collamer lens (ICL) implantation were collected at the Eye Center of Renmin Hospital of Wuhan University between February 2021 and March 2023.A total of 1 368 panoramic UBM images were obtained to establish an image database.The dataset was divided into a training set (760 images), a validation set (86 images) and an internal test set (522 images).An expert panel consisting of three ophthalmologists annotated the images.The UNet+ + network was used to automatically segment anterior segment tissues, such as the cornea, lens and iris.In addition, image processing techniques and geometric localization algorithms were developed to automatically identify the anatomical landmarks of pupil diameter (PD), anterior chamber depth (ACD), angle-to-angle distance (ATA) and sulcus-to-sulcus distance (STS) to complete the measurement of these parameters.Additionally, 480 panoramic UBM images of 135 patients (240 eyes) from Aier Eye Hospital of Wuhan University were used as an external test set to further evaluate the performance of the model in different centers.The consistency between the measurements from the model and expert panel, the Pentacam system was assessed.Finally, 150 images were randomly selected from the external test set for a human-machine comparison to further evaluate the model's performance.This study adhered to the Declaration of Helsinki.The study protocol was approved by the Ethics Committee of Renmin Hospital of Wuhan University (No.WDRY-2022-K109) and Aier eye Hospital of Wuhan University (No.2023IRBKY120903).Written informed consent was obtained from each subject.Results:In the internal test dataset and external test dataset, with manual labeling as the reference standard, the model achieved a mean Dice coefficient of not less than 0.882.At least 95.65% of the anatomical landmark localization results had Euclidean distance differences within 250 μm.The intraclass correlation coefficients (ICCs) for the measurements of PD, ACD, angle-to-angle ATA, and STS were at least 0.958, with mean relative errors not exceeding 2.407%.With the Pentacam measurements as the reference standard, the ICCs for PD in the internal and external test sets were 0.540 and 0.466, respectively, while the ICCs for ACD were 0.946 and 0.908, respectively.In the human-machine comparison, the ICCs between the model's measurements and those of senior experts were all not lower than 0.969.Conclusions:The deep learning-based model can automatically measure anterior segment parameters from preoperative panoramic UBM images of patients undergoing ICL surgery.The model demonstrates a consistency comparable to that of senior experts, while providing higher efficiency.In terms of ACD measurement, the model shows good agreement between the measurements obtained from the model and Pentacam system.

Objective To explore the risk factors and incidence of epiretinal membrane(ERM)formation following scleral buckling(SB)for rhegmatogenous retinal detachment(RRD),and to construct a risk prediction model to facilitate screening of high-risk populations and prevent ERM formation.Methods RRD patients who underwent SB in the Second Affiliated Hospital of Harbin Medical University between February 2022 and April 2024 were included in the study.The pa-tients were divided into occurrence and non-occurrence groups according to whether they developed ERM.Patient data were analyzed,and univariate Cox regression analysis was performed to select variables,which were then incorporated into the multivariate Cox regression model for the identification of risk factors for ERM formation after SB in RRD patients.A predictive model for ERM risk in RRD patients was constructed based on this data,and nomograms,receiver operating characteristic(ROC)curves,and calibration curves were drawn to evaluate and validate the diagnostic performance of the model.Results A total of 126 RRD patients(126 eyes)who underwent SB were included.There were 27 cases develo-ping ERM(occurrence group)and 99 not developing ERM(non-occurrence group),with an ERM incidence of 21.4％.Multivariate Cox regression analysis revealed that a history of diabetes mellitus[Hazard ratio(HR)=3.52,95％CI:1.37-9.02,P=0.009],preoperative proliferative vitreoretinopathy(PVR)(HR=13.00,95％CI:5.18-32.63,P＜0.001),and ≥4 retinal holes(HR=2.33,95％CI:1.04-5.23,P=0.041)were independent influence factors for ERM formation in RRD patients.ROC curve analysis showed that the area under the curve(AUC)was 0.840(95％CI:0.740-0.940)at 30 days and 0.904(95％CI:0.834-0.975)at 90 days.Conclusion A history of diabetes mellitus,preoperative PVR,and ≥4 retinal holes are factors influencing the development of ERM after SB in RRD patients.It is verified that the risk prediction model constructed based on these factors can accurately predict the risk of ERM formation within 6 months in RRD patients.

Objective    To establish the gene-based esophageal cancer (ESCA) risk score prediction models via whole transcriptome analysis to provide ideas and basis for improving ESCA treatment strategies and patient prognosis. Methods    RNA sequencing data of esophageal squamous cell carcinoma (ESCC), esophageal adenocarcinoma (EAC) and adjacent tissues were obtained from The Cancer Genome Atlas database. The edgeR method was used to screen out the differential genes between ESCA tissue and normal tissue, and the key genes affecting the survival status of ESCC and EAC patients were initially identified through univariate Cox regression analysis. The least absolute shrinkage and selection operator regression analysis and multivariate Cox regression analysis were used to further screen genes and establish ESCC and EAC risk score prediction models. Results    The risk score prediction models were the independent prognostic factors for ESCA, and the risk score was significantly related to the survival status of patients. In ESCC, the risk score was related to T stage. In EAC, the risk score was related to lymph node metastasis, distant metastasis and clinical stage. The constructed nomogram based on risk score showed good predictive ability. In ESCC, the risk score was related to tumor immune cell infiltration and the expression of immune checkpoint genes. However, this feature was not obvious in EAC. Conclusion 聽 聽The ESCC and EAC risk score prediction models have shown good predictive capabilities, which provide certain inspiration and basis for optimizing the management of ESCA and improving the prognosis of patients.

BACKGROUND: Plasminogen activator inhibitor-1 (PAI-1) plays an important role in the pathophysiology of sepsis, but the exact mechanism remains debatable. In this study, we investigated the associations among the serum levels of PAI-1, the incidence of 4G/5G promoter PAI-1 gene polymorphisms, immunological indicators, and clinical outcomes in septic patients. METHODS: A total of 181 patients aged 18-80 years with sepsis between November 2016 and August 2018 in the intensive care unit in the Xinhua Hospital were recruited in this retrospective study, with 28-day mortality as the primary outcome. The initial serum level of PAI-1 and the presence of rs1799768 single nucleotide polymorphisms (SNPs) were examined. Univariate logistic regression and multivariate analyses were performed to determine the factors associated with different genotypes of PAI-1, serum level of PAI-1, and 28-day mortality. RESULTS: The logistic analysis suggested that a high serum level of PAI-1 was associated with the rs1799768 SNP of PAI-1 (4G/4G and 4G/5G) (Odds ratio [OR]: 2.49; 95% confidence interval [CI]: 1.09, 5.68). Furthermore, a high serum level of PAI-1 strongly influenced 28-day mortality (OR 3.36; 95% CI 1.51, 7.49). The expression and activation of neutrophils (OR 0.96; 95% CI 0.93, 0.99), as well as the changes in the expression patterns of cytokines and chemokine-associated neutrophils (OR: 1.00; 95% CI: 1.00, 1.00), were both regulated by the genotype of PAI-1. CONCLUSIONS Genetic polymorphisms of PAI-1 can influence the serum levels of PAI-1, which might contribute to mortality by affecting neutrophil activity. Thus, patients with severe sepsis might clinically benefit from enhanced neutrophil clearance and the resolution of inflammation via the regulation of PAI-1 expression and activity.
Adolescent ; Adult ; Aged ; Aged, 80 and over ; Humans ; Middle Aged ; Young Adult ; Genotype ; Neutrophils ; Plasminogen Activator Inhibitor 1/genetics* ; Polymorphism, Single Nucleotide/genetics* ; Retrospective Studies ; Sepsis/genetics*

Objective: To establish a reliable and sensitive method for evaluating quality of Yiqi Jiangzhi Granules (YQJZG). Methods: Ultra performance liquid chromatography electrospray ionization tandem mass spectrometry (UPLC-ESI-MS/MS) was employed for simultaneous determination of eight marker components. Separation was performed on an AQUITY UPLC® HSS T3 column, the mobile phase consisted of acetonitrile as the organic phase and 0.1% (volume percentage) formic acid as the aqueous. Eight marker components, ginsenoside Rg1 (GRg1), ginsenoside Re (GRe), ginsenoside Rb1 (Gb1), typhaneoside (TEO), isorhamnetin-3-O-neohespeidoside (IN), hesperidin (HPD), aurantio-obtusin-6-O-β-D-glucoside (AG) and curcumin (CCM), were detected by multiple reaction monitoring (MRM) mode. The Chinese Pharmacopoeia (2020 edition) was regarded as the guidance document for this method validation. Results: The method showed good linearity (R