Objective To develop a combined model integrating radiomics and 3D deep learning features for improving the predictive efficacy of overall survival in non-small cell lung cancer(NSCLC)patients undergoing radiotherapy,thereby providing a foundation for optimizing individualized radiotherapy strategies.Methods A retrospective analysis was conducted on 522 NSCLC patients from 3 centers.Radiomics features were extracted from the tumor region of interest on radiotherapy planning CT scans,and a 3D-SE-ResNet was constructed to extract deep learning features.Following feature extraction,features were selected via univariate Cox analysis and Lasso-Cox regression,and a combined model was established by fusing the two feature types through principal component analysis.The discriminative ability of the model was evaluated using the concordance index(C-index)and the area under the receiver operating characteristic curve(AUC),while the risk stratification efficacy was verified by Kaplan-Meier survival analysis.Results The predictive performance of deep learning features was significantly superior to that of radiomics features(C-index:0.73 vs 0.65).The combined model achieved the highest predictive performance in the training set,internal test set,and external test set(C-index:0.74,0.69,0.72 respectively),with higher AUC values for predicting 1-year,2-year,and 3-year OS than either single model.Kaplan-Meier analysis showed significant differences in survival between the high-and low-risk groups(Log-rank test,P<0.001),and calibration curves indicated good consistency between predicted and actual survival outcomes.Conclusion The combined model integrating radiomics and 3D deep learning features can accurately predict survival outcomes in NSCLC patients undergoing radiotherapy.The multi-center validation results support its potential application in prognosis stratification for individualized radiotherapy.

Objective:To investigate the effects of oral propranolol on the heart rate and blood glucose levels in children with hemangiomas receiving hospital care.Methods:A total of 259 children [77 males and 182 females, aged (125.2±85.4) days, weighted (6.3±1.6) kg], who were treated with oral propranolol for the first time under hospital care from January 2013 to August 2021, were retrospectively analyzed. After fasting, the patients administered the same dose of propranolol once daily (0.5-2.5 mg/kg). Fasting blood glucose and heart rate were measured in all children before propranolol administration and after 2 h. Heart rate was measured at 1, 3 and 6 h after propranolol administration for three consecutive days. Adverse reactions were observed and recorded.Results:Within three days of oral propranolol administration, the heart rates at 1, 3 and 6 h after propranolol administration were lower than those before propranolol administration (all P<0.001). Within three days after taking propranolol and 2 h after taking propranolol daily, blood glucose levels reduced in all children (all P<0.001). During the hospitalization period, the incidence of adverse reactions was 5.4% (14/259), including lesion ulcers in four cases, upper respiratory tract infection with fever in four, reduced eating in two, nausea and vomiting in one, lethargy in one, sinus tachycardia in one, and hyperkalemia in one. No serious adverse reactions were life-threatening. Conclusion:After oral administration of propranolol, the heart rate and blood sugar of the children decrease to different degrees compared with those before propranolol administration.

The rapid emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants that evade immunity elicited by vaccination has posed a global challenge to the control of the coronavirus disease 2019 (COVID-19) pandemic. Therefore, developing countermeasures that broadly protect against SARS-CoV-2 and related sarbecoviruses is essential. Herein, we have developed a lipid nanoparticle (LNP)-encapsulated mRNA (mRNA-LNP) encoding the full-length Spike (S) glycoprotein of SARS-CoV-2 (termed RG001), which confers complete protection in a non-human primate model. Intramuscular immunization of two doses of RG001 in Rhesus monkey elicited robust neutralizing antibodies and cellular response against SARS-CoV-2 variants, resulting in significantly protected SARS-CoV-2-infected animals from acute lung lesions and complete inhibition of viral replication in all animals immunized with low or high doses of RG001. More importantly, the third dose of RG001 vaccination elicited effective neutralizing antibodies against current epidemic XBB and JN.1 strains and similar cellular response against SARS-CoV-2 Omicron variants (BA.1, XBB.1.16, and JN.1) were observed in immunized mice. All these results together strongly support the great potential of RG001 in preventing the infection of SARS-CoV-2 variants of concern (VOCs).

Objective To develop a combined model integrating radiomics and 3D deep learning features for improving the predictive efficacy of overall survival in non-small cell lung cancer(NSCLC)patients undergoing radiotherapy,thereby providing a foundation for optimizing individualized radiotherapy strategies.Methods A retrospective analysis was conducted on 522 NSCLC patients from 3 centers.Radiomics features were extracted from the tumor region of interest on radiotherapy planning CT scans,and a 3D-SE-ResNet was constructed to extract deep learning features.Following feature extraction,features were selected via univariate Cox analysis and Lasso-Cox regression,and a combined model was established by fusing the two feature types through principal component analysis.The discriminative ability of the model was evaluated using the concordance index(C-index)and the area under the receiver operating characteristic curve(AUC),while the risk stratification efficacy was verified by Kaplan-Meier survival analysis.Results The predictive performance of deep learning features was significantly superior to that of radiomics features(C-index:0.73 vs 0.65).The combined model achieved the highest predictive performance in the training set,internal test set,and external test set(C-index:0.74,0.69,0.72 respectively),with higher AUC values for predicting 1-year,2-year,and 3-year OS than either single model.Kaplan-Meier analysis showed significant differences in survival between the high-and low-risk groups(Log-rank test,P<0.001),and calibration curves indicated good consistency between predicted and actual survival outcomes.Conclusion The combined model integrating radiomics and 3D deep learning features can accurately predict survival outcomes in NSCLC patients undergoing radiotherapy.The multi-center validation results support its potential application in prognosis stratification for individualized radiotherapy.

Objective:To investigate the effects of oral propranolol on the heart rate and blood glucose levels in children with hemangiomas receiving hospital care.Methods:A total of 259 children [77 males and 182 females, aged (125.2±85.4) days, weighted (6.3±1.6) kg], who were treated with oral propranolol for the first time under hospital care from January 2013 to August 2021, were retrospectively analyzed. After fasting, the patients administered the same dose of propranolol once daily (0.5-2.5 mg/kg). Fasting blood glucose and heart rate were measured in all children before propranolol administration and after 2 h. Heart rate was measured at 1, 3 and 6 h after propranolol administration for three consecutive days. Adverse reactions were observed and recorded.Results:Within three days of oral propranolol administration, the heart rates at 1, 3 and 6 h after propranolol administration were lower than those before propranolol administration (all P<0.001). Within three days after taking propranolol and 2 h after taking propranolol daily, blood glucose levels reduced in all children (all P<0.001). During the hospitalization period, the incidence of adverse reactions was 5.4% (14/259), including lesion ulcers in four cases, upper respiratory tract infection with fever in four, reduced eating in two, nausea and vomiting in one, lethargy in one, sinus tachycardia in one, and hyperkalemia in one. No serious adverse reactions were life-threatening. Conclusion:After oral administration of propranolol, the heart rate and blood sugar of the children decrease to different degrees compared with those before propranolol administration.

Objective:To investigate the correlation between hearing loss and microvascular complications in diabetes.Methods:This cross-sectional study conducted the data from 572 patients with diabetes hospitalized in the Endocrinology Department of the General Hospital of Southern Theater Command from September 2022 to July 2023. All participants underwent electrical audiometry and acoustic immittance in the ENY department. Based on the audiometric results, participants were categorized into normal hearing group and hearing loss group. Additionally, 572 non-diabetic patients from the outpatient department were enrolled as the non-diabetic group. The general information and laboratory results were collected and compared using t test, rank sum test or χ2 test. Binary logistic regression analysis was used to evaluate the association of diabetic hearing loss with diabetic kidney disease(DKD), diabetic retinopathy (DR), and diabetic peripheral neuropathy (DPN). Results:Among 572 patients with diabetes, 429 suffered from hearing loss and 143 were normal. χ2 test showed significant differences in combined DKD and DPN between two groups, but not in DR. Multivariate binary logistic regression analysis identified DKD and DPN as risk factors for hearing loss, but no correlation was found with DR. Conclusion:Diabetic patients with DKD or DPN should be monitored for potential hearing loss. Early screening and treatment are crucial to prevent severe hearing impairment.

The incidence of osteoporotic thoracolumbar vertebral fracture (OTLVF) in the elderly is gradually increasing. The kyphotic deformity caused by various factors has become an important characteristic of OTLVF and has received increasing attention. Its clinical manifestations include pain, delayed nerve damage, sagittal imbalance, etc. Currently, the definition and diagnosis of OTLVF with kyphotic deformity in the elderly are still unclear. Although there are many treatment options, they are controversial. Existing guidelines or consensuses pay little attention to this type of fracture with kyphotic deformity. To this end, the Lumbar Education Working Group of the Spine Branch of the Chinese Medicine Education Association and Editorial Committee of Chinese Journal of Trauma organized the experts in the relevant fields to jointly develop Clinical guidelines for the diagnosis and treatment of osteoporotic thoracolumbar vertebral fractures with kyphotic deformity in the elderly ( version 2024), based on evidence-based medical advancements and the principles of scientificity, practicality, and advanced nature, which provided 18 recommendations to standardize the clinical diagnosis and treatment.

Smoking is a major concern in today's society,and the nicotine in tobacco is the major cause of addiction and difficulty in withdrawal.Long-term use of nicotine not only results in abnormal neural oscillations in the brain,but also impairs reward circuits as well as emotion regulation,thus reducing neuroplasticity and increasing susceptibility to addiction.As electrophysiological signals,electroencephalogram(EEG)signals are associated with a variety of states including cognitive function,emotion regulation,inhibitory control,and sleep.The researches on nicotine addiction reveal that changes in EEG signals are associated with abnormalities in cognitive function and inhibitory control in nicotine addicts.Therefore,exploring the abnormal neural oscillation patterns of nicotine addicts through EEG-related techniques can deepen the understanding of the intrinsic neural mechanisms of nicotine addiction and provide a scientific basis for the intervention and treatment of nicotine addiction.Herein the study summarizes the research achievements of scholars at home and abroad in recent years from the aspects of the application status of EEG in nicotine addiction researches as well as the current technology.It is found that nicotine addicts have obvious abnormalities in sleep quality,cognitive function and inhibitory control.In addition,the functional brain connectivity,event-related potentials and EEG power spectra of addicts are significantly changed.Finally,an outlook on the research prospects of EEG signals in nicotine addiction is provided,emphasizing the potential applications of EEG signals in addiction mechanisms,withdrawal responses,and assessment of treatment efficacy.

Objective To investigate the predictive value of a nomogram model constructed based on imaging combined with prostate-specific antigen(PSA)and its related parameters for biopsy in patients with PSA levels of 4-10 ng/mL.Methods The serological and imaging data of 191 patients who were detected for PSA and related indicators and underwent the first biopsy of prostate by transrectal ultrasound at Zhongshan City People's Hospital and/or Yunfu Hospital of TCM from January 2018 to December 2023 were analyzed retrospectively.Multivariate Logistic regression identified independent risk factors for prostate cancer,and a nomogram model was developed for patients with PSA levels of 4-10 ng/mL.The predictive performance of the model was evaluated using receiver operating characteristic(ROC)curves,calibration curves,and decision curves.Results The multivariate Logistic regression analysis showed that free PSA,prostate volume,transition zone volume,PSA density,and the prostate imaging-reporting and data system(PI-RADS v2.1)score were independent risk factors for prostate cancer.The model incorporating these significant variables demonstrated the best performance,with an area under the curve(AUC)of 0.750(95%CI:0.678-0.821),sensitivity of 72.7%,specificity of 77.2%,and accuracy of 74.9%.The calibration curve indicated good agreement between the predicted probability and the actual probability of prostate cancer;and the decision curve analysis further confirmed that the model had high clinical utility.Conclusion The constructed nomogram prediction model can effectively estimate the preoperative risk of prostate cancer in patients with PSA levels of 4-10 ng/mL,providing clinicians with an intuitive tool to adjust treatment plans based on the assessed risk,thereby optimizing patient outcomes.

Long-term burden of illness and associated medication usage make osteoporosis(OP) a common complication of respiratory diseases. The pathogenic risk factors and treatment strategies for respiratory diseases related OP are similar to primary OP. However, due to differences in the pathogenesis of each disease, there are distinctions in the characteristics of bone loss and treatment approaches. Therefore, targeted diagnostic and therapeutic plans need to be formulated. This article provides a comprehensive review of secondary OP caused by common respiratory diseases in terms of epidemiological characteristics, related risk factors or possible mechanisms, changes in bone metabolic indexes or characteristics of bone damage, and progress in diagnosis and treatment. The aim of this review is to offer insights into the prevention and treatment of secondary OP related to respiratory diseases and promote the development of a multidisciplinary collaborative approach.