Objective: To characterize perioperative dynamic changes in immune-cell phenotypes and inflammatory cytokines in patients undergoing CPB (cardiopulmonary bypass) cardiac surgery, and to explore their associations with postoperative outcomes. Methods: In this prospective cohort study, 120 adult patients who underwent elective cardiac surgery under CPB at West China Hospital from May 2022 to March 2023 were enrolled. Perioperative immune-cell phenotypes and concentrations of 40 inflammation-related cytokines were measured. The primary outcomes were the sequential organ failure assessment (SOFA) score at 24 h after surgery and ΔSOFA (the peak SOFA score within 48 h after surgery minus the preoperative SOFA score). Secondary outcomes included major adverse cardiovascular events (MACE), acute kidney injury (AKI), respiratory failure, severe liver injury, and infection. Results: The mean age of enrolled patients was 57±10 years. Of these, 52% (62/120) were male and 90% (108/120) underwent valve surgery. During the rewarming to the end of CPB, neutrophil counts rapidly increased (7.39×10 /L vs preoperative 3.07×10 /L, P<0.001), with significant upregulation of CD11b (7.30×10 /L vs preoperative 3.05×10 /L, P<0.001) and CD54 (7.15×10 /L vs preoperative 2.99×10 /L, P<0.001). Lymphocyte counts increased at the end of CPB (1.75×10 /L vs preoperative 1.12×10 /L, P<0.001) but decreased significantly at 24 h after surgery (0.59×10 /L vs preoperative 1.12×10 /L, P<0.001). Plasma analysis showed that multiple pro-inflammatory cytokines increased during CPB and remained elevated up to 24 h after surgery; five chemokines and the anti-inflammatory cytokine IL-10 peaked at the end of CPB. The SOFA score increased from 1 (1, 2) preoperatively to 7 (5, 10) at 24 h after surgery, with a ΔSOFA of 6 (4, 8). Within 30 days after surgery, 48 patients (40.0%) developed AKI, 17 (14.2%) developed infection, 4 (3.3%) developed severe liver injury, 3 (2.5%) developed respiratory failure, and 3 (2.5%) experienced MACE. During the 2-year follow-up, 8 patients (6.7%) experienced MACE and 5 (4.2%) died. Conclusion: Multi-organ dysfunction is common after cardiac surgery under CPB (median ΔSOFA, 6), accompanied by perioperative activation of multiple immune-cell subsets and upregulation of pro-inflammatory, anti-inflammatory, and chemotactic mediators. This study provides data-driven evidence and research clues for further investigation of the associations between CPB-related immune perturbations and postoperative organ dysfunction and clinical outcomes.

Objective:Exploring the association between Life's Crucial 9 (LC9) and the risk of thyroid dysfunction (TD), as well as its potential predictive capacity.Methods:A total of 247 600 TD-free participants from the UK Biobank were enrolled in the study. The LC9 score was divided into three CVH groups: low (0-), medium (50-), and high (80-100). Cox proportional hazards regression models were used to calculate the HRs and 95% CIs of the risk of TD with LC9 CVH status. Calculate Harrell's concordance index ( C-index), net reclassification improvement (NRI), and integrated discrimination improvement (IDI) to evaluate the predictive ability of the LC9 score and Life's Essential 8 (LE8) score. Results:During a median follow-up of 12.3 years, 5 515, 911, and 4 869 new cases of TD, hyperthyroidism, and hypothyroidism were documented, respectively. Participants with a high LE8 CVH group had 57.00% ( HR=0.43, 95% CI: 0.38-0.49), 55.00% ( HR=0.45, 95% CI: 0.34-0.60), and 58.00% ( HR=0.42, 95% CI: 0.37-0.47) lower risk of TD, hyperthyroidism, and hypothyroidism, respectively, than those with low CVH group. Compared with the LE8 score, the improvement in C-index for the LC9 score predicted TD risk was 0.004 (95% CI: 0.001-0.007), the NRI was 0.101 (95% CI: 0.021-0.103), and the IDI was 0.001 (95% CI: 0.000-0.001). Conclusions:The better CVH status, defined by LC9, was associated with a lower risk of TD. Compared to the LE8 score, the LC9 score demonstrated a significant enhancement in both risk discrimination and reclassification capability for TD risk.

Objective:To explore the influence of different scanning positions based on chest phantom of computed tomography(CT)scan on chest on image quality and radiation dose.Methods:A thermoluminescent dosimeter(TLD)was placed at the breast area of simulating anthropoid chest phantom.GE Revolution evo CT was used to conduct scan on the conventional supine position(supine group)and prone position(prone group)for chest phantom.Different noise indexes(NI=10-23)were adjusted to control ration doses,and other parameters were fixed,and each group collected 12 sequence images.The average value(AV),standard deviation(SD)of the CT scan at region of interest(ROI)under different scanning positions were recorded to calculate the signal-to-noise ratio(SNR)and contrast-to-noise ratio(CNR)of the image.The radiation dose at the breast area was measured by TLD,and the volume CT dose index(CTDIvol)and dose-length product(DLP)were recorded.Results:Under different scanning positions,the radiation dose of breast organs in the prone group was lower than that in the supine group,there was a statistically significant difference between the two groups(t=6.57,P<0.05),while there were not statistically significant differences in CTDIvol and DLP between the two groups(P>0.05).There were not statistically significant differences in the CT values,SD,SNR,CNR of lung tissue,and the CT values of breast tissue between the two groups of images(P>0.05).The SD,SNR and CNR of breast tissue in the prone group were lower than those in the supine group,and the differences were statistically significant(t=-13.33,-10.59,6.70,P<0.05).There were no statistically significant differences in the subjective scores of the clarity of the edge of the tissue within lung,the layers of soft tissue of the breast,noise,and artifacts in the bone tissue between the two groups of images(P>0.05).Conclusion:When low-dose CT physical examination on chest is conducted in clinical practice,the scanning of prone position during undergoing CT scan on chest can obtain image quality that can meet the requirements in diagnosing lung,and reduce the radiation dose on the breast,and conform to the technical principle of optimal radiation protection.

Debates persist regarding the efficacy and safety of azvudine, particularly its real-world outcomes. This study involved patients aged ≥60 years who were admitted to 25 hospitals in mainland China with confirmed SARS-CoV-2 infection between December 1, 2022, and February 28, 2023. Efficacy outcomes were all-cause mortality during hospitalization, the proportion of patients discharged with recovery, time to nucleic acid-negative conversion (T _NANC), time to symptom improvement (T _SI), and time of hospital stay (T _HS). Safety was also assessed. Among the 5884 participants identified, 1999 received azvudine, and 1999 matched controls were included after exclusion and propensity score matching. Azvudine recipients exhibited lower all-cause mortality compared with controls in the overall population (13.3% vs. 17.1%, RR, 0.78; 95% CI, 0.67-0.90; P = 0.001) and in the severe subgroup (25.7% vs. 33.7%; RR, 0.76; 95% CI, 0.66-0.88; P < 0.001). A higher proportion of patients discharged with recovery, and a shorter T _NANC were associated with azvudine recipients, especially in the severe subgroup. The incidence of adverse events in azvudine recipients was comparable to that in the control group (2.3% vs. 1.7%, P = 0.170). In conclusion, azvudine showed efficacy and safety in older patients hospitalized with COVID-19 during the SARS-CoV-2 omicron wave in China.

Myocardial fibrosis is a serious cause of heart failure and even sudden cardiac death. However, the mechanisms underlying myocardial ischemia-induced cardiac fibrosis remain unclear. Here, we identified that the expression of sterile alpha and TIR motif containing 1 (SARM1), was increased significantly in the ischemic cardiomyopathy patients, dilated cardiomyopathy patients (GSE116250) and fibrotic heart tissues of mice. Additionally, inhibition or knockdown of SARM1 can improve myocardial fibrosis and cardiac function of myocardial infarction (MI) mice. Moreover, SARM1 fibroblasts-specific knock-in mice had increased deposition of extracellular matrix and impaired cardiac function. Mechanically, elevated expression of SARM1 promotes the deposition of extracellular matrix by directly modulating P4HA1. Notably, by using the Click-iT reaction, we identified that the increased expression of ZDHHC17 promotes the palmitoylation levels of SARM1, thereby accelerating the fibrosis process. Based on the fibrosis-promoting effect of SARM1, we screened several drugs with anti-myocardial fibrosis activity. In conclusion, we have unveiled that palmitoylated SARM1 targeting P4HA1 promotes collagen deposition and myocardial fibrosis. Inhibition of SARM1 is a potential strategy for the treatment of myocardial fibrosis. The sites where SARM1 interacts with P4HA1 and the palmitoylation modification sites of SARM1 may be the active targets for anti-fibrosis drugs.

Objective To investigate the predictive value of combined radiomic features derived from chest CT scans with clinical characteristics for epidermal growth factor receptor(EGFR)gene mutations in non-small cell lung cancer(NSCLC).Methods A multi-center case-control study was conducted on the clinical data and CT images of 1 070 NSCLC patients from the radiology departments of the 3 medical institutions between January 2013 and October 2023.The 719 NSCLC patients from the First Affiliated Hospital of Army Medical University were randomly divided into a training set and an internal validation set in a ratio of 7∶3;The 173 patients in the Eastern Theatre General Hospital and the 178 patients in Army Medical Centre of PLA were assigned into the external validation set 1 and 2,respectively.Least absolute shrinkage and selection operator(LASSO)regression was employed to identify the optimal radiomic features,which were subsequently used to construct a radiomics model.Univariate and multivariate logistic regression analyses were applied to identify clinical features associated with EGFR mutation,thereby developing a clinical model.The radiomic and clinical features were subsequently combined to develop a comprehensive model.All the 3 classification models were built using random forest(RF)machine learning.The area under curve(AUC),accuracy,sensitivity and specificity were utilized to evaluate the predictive performance of the models.Calibration curve was plotted to assess the goodness of fit of the comprehensive model,while decision curve analysis was performed to assess the clinical utility of the model.Results The AUC value of the radiomics model was 0.762 4(95%CI:0.692 4～0.825 1),0.745 4(95%CI:0.671 1～0.814 3),and 0.724 7(95%CI:0.639 7～0.801 6),respectively,in the internal validation set,external validation set 1,and external validation set 2;The AUC value of the clinical prediction model was 0.691 7(95%CI:0.627 9～0.757 6),0.652 5(95%CI:0.576 7～0.729 1),and 0.779 2(95%CI:0.712 5～0.847 3),respectively in the above sets in turn;The comprehensive model constructed based on clinical features and radiomic features showed the best predictive efficacy,with an AUC value of 0.818 0(95%CI:0.757 7～0.874 3),0.782 4(95%CI:0.703 1～0.848 2),and 0.796 6(95%CI:0.718 1～0.868 6),respectively in the above sets.Calibration curve analysis indicated that the comprehensive model had a good fit,while decision curve analysis revealed that the model provided a favorable net benefit.Conclusion Our comprehensive model constructed based on chest CT radiomic features and clinical characteristics shows superior predictive performance for EGFR gene mutations in NSCLC across multiple center datasets,which may be helpful for clinical decision-making for treatment strategies.

Objective To evaluate the predictive value of deep learning features from chest CT images combined with clinical and radiomics features for epidermal growth factor receptor(EGFR)mutations in non-small cell lung cancer(NSCLC).Methods This case-control study retrospectively analyzed clinical and imaging data of 1 070 NSCLC patients from radiology departments at three hospitals(January 2013 to October 2023).Patients were divided into:a training set(n=502)and internal validation set(n=217)via 7∶3 randomization of 719 cases from the First Affiliated Hospital of Army Medical University;external validation set 1(n=173)from General Hospital of Eastern Theater Command;external validation set 2(n=178)from Daping Hospital of Army Medical University.Deep learning features were extracted using a 2.5D convolutional neural network(CNN)with ResNet101 backbone,radiomics features were derived from CT images,and clinical risk factors were identified to construct models.An integrated model combined deep learning,clinical,and radiomics features.All four models were developed using random forest(RF)classifiers.Calibration curves assessed goodness-of-fit,and decision curve analysis(DCA)evaluated clinical utility.Results The deep learning model achieved AUCs of 0.833 7(95%CI:0.770 6～0.884 7),0.815 1(0.741 6～0.882 8),and 0.810 1(0.745 2～0.873 6)in the internal and two external validation sets,respectively.Clinical models yielded AUCs of 0.731 0(0.660 2～0.802 1),0.746 0(0.666 4～0.824 9),and 0.813 4(0.743 1～0.883 6);radiomics models showed AUCs of 0.762 4(0.692 4～0.825 1),0.745 4(0.671 1～0.814 3),and 0.724 7(0.639 7～0.801 6).The integrated model demonstrated optimal performance with AUCs of 0.905 5(0.857 0～0.945 4),0.832 7(0.763 3～0.896 4),and 0.889 0(0.834 4～0.934 3).DCA indicated significant net benefit for EGFR prediction at threshold probabilities of 0.15～0.85 using the integrated model.Conclusion Deep learning features from CT images effectively predict EGFR mutation status in NSCLC.The integrated model combining deep learning,clinical,and radiomics features further enhances predictive performance.

Objective To explore the risk factors of early hypocalcemia after endoscopic thyroidectomy by breast approach(ETBA)and establish a predictive model to evaluate its occurrence risk.Methods A total of 155 patients with thyroid nodules who underwent ETBA were selected.Patients were divided into the low calcium group(＜2 mmol/L,n=41)and the normal group(≥2 mmol/L,n=114)according to the serum calcium level 24 hours after the operation.Before the operation,thyroid function and parathyroid hormone(PTH)were detected,and ultrasound was performed to evaluate cervical lymph node enlargement.Meanwhile,nodule location,maximum tumor diameter,nodule adhesion to the capsule,calcification and the edge of the nodule were also detected.The surgical conditions such as gland resection(unilateral or bilateral),operation time and misresection of parathyroid glands were recorded.PTH and serum calcium were detected 24 hours after the operation.Pathological assessment was used to evaluate benign and malignant conditions,Hashimoto's thyroiditis,multifocal lesions,thyroid capsule invasion and lymph node metastasis.Results Compared with the normal group,the cervical lymph node metastasis,malignant nodules,multifocal lesions,cervical lymph node enlargement,bilateral gland resection,parathyroid gland resection by mistake,combined Hashimoto's thyroiditis,maximum tumor diameter and operation time were increased in the hypocalcemia group,but PTH at 24 hours after the operation was decreased(P＜0.05).Multivariate Logistic regression analysis showed that cervical lymph node metastasis,long operation time,parathyroid resection by mistake,combined Hashimoto's thyroiditis and maximum tumor diameter were independent risk factors for early hypocalcemia in ETBA.Based on this,a visual nomogram model was constructed,with excellent discrimination[the area under the receiver operating characteristic(ROC)curve was 0.920(95%CI:0.834-0.971)],and the calibration curve showed that the predicted values were highly consistent with the measured values(Hosmer-Lemeshow χ2=0.007,P=0.087).Conclusion The nomogram model constructed based on multivariate Logistic regression can effectively predict the risk of early hypocalcemia after ETBA.

Objectives:To summarize the characteristics of Fabry′s disease with cardiac involvement.Methods:This was a single-center, cross-sectional, retrospective study. Patients with Fabry disease who were admitted to Zhongda Hospital Affiliated to Southeast University from January 2022 to March 2023 were included. Clinical data, laboratory results, electrocardiogram, echocardiography and cardiac magnetic resonance findings of enrolled patients were collected. Clinical presentations and imaging features of patients with Fabry′s disease with cardiac involvement were summarized and analyzed.Results:A total of 17 patients from 8 families were included, with 9 males and diagnosis age of (44.35±13.72) years. Cardiac involvement and other organ involvement were presented in all patients and the heart was the most vulnerable organ (17/17). 24 h electrocardiogram showed frequent sinus arrhythmia in 3 patients. Echocardiography showed reduced left ventricular ejection fraction in 1 patient, myocardial hypertrophy in 13 patients, and left ventricular wall thickness ≥13 mm in 10 patients. Mitral regurgitation was observed in 11 patients and tricuspid regurgitation in 12 patients. Two patients underwent two-dimensional speckle tracking echocardiography, both revealing reduced regional longitudinal strain of the left ventricle, primarily in the basal segments. Cardiac magnetic resonance showed reduced left ventricular ejection fraction in 2 patients, myocardial hypertrophy in 16 patients, and left ventricular wall thickness≥13 mm in 14 patients. T1 value was reduced in 16 patients, with late gadolinium enhancement observed in 9 patients and “pseudo-normalization” of T1 values in 1 patient. The most susceptible target organ besides the heart was the kidneys (14/17), followed by the central nervous system (9/17). Additional findings inclucling cutaneous angiokeratoma in 4 patients, peripheral neuropathy with burning pain and hypohidrosis or hyperhidrosis in 6 patients, and corneal vortex opacities in 2 patients.Conclusion:The main manifestations of cardiac involvement in Fabry′s disease are decreased cardiac function, left ventricular hypertrophy and myocardial fibrosis. Advanced imaging techniques such as two-dimensional speckle tracking, T1 Mapping, and late gadolinium enhancement are useful in detecting myocardial pathological changes of Fabry′s disease.

Objective:To explore the impact of adolescent mental health status on smartphone addiction, and construct a predictive model for smartphone addiction based on the eXtreme Gradient Boosting(XGBoost) algorithm and multivariate Logistic regression.Methods:In April 2023, a cross-sectional survey was conducted among 14 666 adolescents.All participants were systematically evaluated using a self-developed general information questionnaire, the middle school student mental health scale(MSSMHS), the adolescents self-harm scale(ASHS), the interaction anxiousness scale(IAS), the mobile phone addiction index(MPAI), the middle school students shame scale(MSSS), the UCLA loneliness scale(UCLA-LS), the multidimensional peer victimization scale(MPVS), and the basic psychological needs scale(BPNS).R software version 4.3.2 was used for data analysis. Participants were randomly divided into training set and validation set at the ratio of 7∶3.The XGBoost model and multivariate logistic regression model were constructed to predict the risk of smartphone addiction, and a nomogram was plotted.Model performance was evaluated using the Hosmer-Lemeshow test, area under the curve(AUC), and accuracy(ACC).Results:(1) A total of 14 036 high school students were included in the study, with 5 069(36.1%) exhibited smartphone addiction.The training set comprised 9 826 students, with 3 549(36.1%) being smartphone addicts.The validation set included 4 210 students, with 1 520(36.1%) being smartphone addicts.(2) The XGBoost model identified shame-proneness and social anxiety as the two main predictors of smartphone addiction.(3) Multivariate Logistic regression analysis revealed that anxiety( B=0.328, OR(95% CI)=1.39(1.07-1.81), P=0.015), interpersonal sensitivity( B=0.311, OR(95% CI)=1.36(1.05-1.77), P=0.018), learning pressure( B=0.606, OR(95% CI)=1.83(1.46-2.31), P<0.001), mood swings( B=0.775, OR(95% CI)=2.17(1.70-2.78), P<0.001), social anxiety( B=0.024, OR(95% CI)=1.02(1.01-1.04), P<0.001), shame-proneness( B=0.049, OR(95% CI)=1.05(1.04-1.06), P<0.001), and peer victimization( B=0.037, OR(95% CI)=1.04(1.02-1.06), P<0.001) were significant predictors of smartphone addiction.(4) The ACC and AUC values of the XGBoost model were 0.890 and 0.929 in the training set, and 0.865 and 0.864 in the validation set, respectively.The multivariate Logistic regression model achieved ACC and AUC values of 0.870 and 0.854 in the training set, and 0.867 and 0.859 in the validation set, respectively. Conclusion:Anxiety, interpersonal sensitivity, learning pressure, mood swings, social anxiety, shame-proneness, and peer victimization are identified risk predictors of smartphone addiction in high school adolescents.