Objective: To investigate the factors influencing intraoperative blood transfusion in patients with hip fractures and to develop a machine learning (ML) model for predicting this risk. Methods: A total of 424 patients with hip fractures who underwent surgical treatment between November 2022 and March 2025 in our hospital were selected. Key feature variables of intraoperative blood transfusion risk were identified using the Boruta algorithm. Four different ML algorithms—support vector machine (SVM), linear discriminant analysis (LDA), mixed discriminant analysis (MDA), and extreme gradient boosting (XGBoost)—were used to develop predictive models for intraoperative blood transfusion risk. The predictive performance of the four ML models were evaluated using accuracy, precision, receiver operating characteristic (ROC) curves, precision-recall curves (PRC), precision-recall gain curves (PRGC), and F1 scores. Shapley additive interpretation (SHAP) was used to interpret the final model. Results: Among the 424 patients, 77(18.2%) received intraoperative blood transfusion. The Boruta algorithm identified albumin (ALB), activated partial thromboplastin time (APTT), types of anesthesia, types of fracture, and hemoglobin (Hb) as key feature variables for predicting intraoperative blood transfusion risk. In model evaluation, the SVM model outperforms the other three models across multiple metrics, including the area under the receiver operating characteristic curve (AUC), recall, recall gain, accuracy, precision, F1 score, and the area under the precision-recall curve (PRC-AUC). The SVM model, interpreted and visualized based on SHAP values, effectively predicted intraoperative blood transfusion risk in patients with hip fracture. A visual online application was developed based on the SVM model (https://pbo-nomogram.shinyapps.io/blood/). Conclusion: Preoperative low ALB and Hb levels, prolonged APTT, general anesthesia, and intertrochanteric fractures are risk factors for intraoperative blood transfusion in hip fracture patients. The risk prediction model for intraoperative blood transfusion constructed based on the SVM algorithm has optimal performance, which provides new ideas and methods for the clinical early identification of hip fracture patients with high transfusion risk and the implementation of targeted interventions.

Although global brain science research has progressed rapidly in recent decades, several fundamental questions in neuroscience remain unresolved. In particular, the physical mechanism underlying neural signal transmission remains controversial, and the carriers responsible for neural information storage and retrieval have not yet been fully clarified. These unresolved issues motivate us to re-examine the processes of neural information generation, transmission, integration, storage, and retrieval from multiple perspectives. A key observation is that neural electromagnetic activities are closely associated with time. Their duration, temporal structure, and dynamic evolution play crucial roles in neural information processing. In this work, we analyze neural electromagnetic activities from the perspective of temporal scales (referred to here as the “time course”). By reviewing and integrating findings from previous studies, we examine the characteristic time requirements and dynamic features of neural processes occurring at different stages of information processing. These stages include neural signal generation, signal transmission along axons, synaptic integration, synaptic plasticity, and memory formation and retrieval. Based on this temporal analysis, we outline a framework describing neural electromagnetic activities across a wide range of time scales, spanning from microseconds to minutes, hours, or even longer periods associated with long-term memory, which suggests that neural information processing involves multiple physical processes operating at different time levels. Rapid electromagnetic events may occur on microsecond scales, whereas electrophysiological phenomena such as action potentials typically last on the order of milliseconds. Longer time scales are associated with synaptic plasticity and memory-related processes. From this perspective, we propose that the physical carrier of neural information may be transient electromagnetic pulses with durations on the microsecond scale. In this framework, action potentials can be interpreted as the macroscopic electrophysiological manifestation of underlying electromagnetic processes triggered by ionic currents across neuronal membranes. Rather than being the fundamental neural signal itself, the action potential may represent a measurable membrane-level response associated with the successful activation of these electromagnetic events. Moreover, we discuss a possible mechanism for long-term memory storage. Considering the apparent temporal contradiction between the millisecond-scale excitation of neurons and the long-term persistence of memories, we believe that long-term memory information may be stored within neural network topologies formed by electrical synapse coupling. Such structures, referred to as electrically coupled memory networks (ECMNs), may enable neurons within the same network to respond rapidly and synchronously to stimuli, thereby facilitating efficient memory retrieval. Overall, this study emphasizes the importance of considering the temporal organization of neural electromagnetic activities when interpreting neural signaling mechanisms. It may provide new insights into the physical nature of neural information carriers and the mechanisms of memory storage and retrieval. Furthermore, highlighting the potential role of electromagnetic interactions in neural activity may contribute to the development of new theoretical frameworks and experimental approaches in neuroscience. Such perspectives may also offer valuable references for future research on neural coding, brain function mechanisms, and neuromodulation technologies.

Objective: The CT/MRI Liver Imaging Reporting and Data System (LI-RADS) demonstrates high specificity with relatively limited sensitivity for diagnosing hepatocellular carcinoma (HCC) in high-risk patients. This study aimed to explore the possibility of improving sensitivity by combining CT/MRI LI-RADS v2018 with second-line contrast-enhanced ultrasound (CEUS) LI-RADS v2017 using sulfur hexafluoride (SHF) or perfluorobutane (PFB). Materials and Methods: This retrospective analysis of prospectively collected multicenter data included high-risk patients with treatment-naive hepatic observations. The reference standard was pathological confirmation or a composite reference standard (only for benign lesions). Each participant underwent concurrent CT/MRI, SHF-enhanced US, and PFB-enhanced US examinations. The diagnostic performances for HCC of CT/MRI LI-RADS alone and three combination strategies (combining CT/ MRI LI-RADS with either LI-RADS SHF, LI-RADS PFB, or a modified algorithm incorporating the Kupffer-phase findings for PFB [modified PFB]) were evaluated. For the three combination strategies, apart from the CT/MRI LR-5 criteria, HCC was diagnosed if CT/MRI LR-3 or LR-4 observations met the LR-5 criteria using LI-RADS SHF, LI-RADS PFB, or modified PFB. Results: In total, 281 participants (237 males; mean age, 55 ± 11 years) with 306 observations (227 HCCs, 40 non-HCC malignancies, and 39 benign lesions) were included. Using LI-RADS SHF, LI-RADS PFB, and modified PFB, 20, 23, and 31 CT/MRI LR-3/4 observations, respectively, were reclassified as LR-5, and all were pathologically confirmed as HCCs. Compared to CT/MRI LI-RADS alone (74%, 95% confidence interval [CI]: 68%–79%), the three combination strategies combining CT/MRI LI-RADS with either LI-RADS SHF, LI-RADS PFB, or modified PFB increased sensitivity (83% [95% CI: 77%–87%], 84% [95% CI: 79%–89%], 88% [95% CI: 83%–92%], respectively; all P < 0.001), while maintaining the specificity at 92% (95% CI: 84%–97%). Conclusion The combination of CT/MRI LI-RADS with second-line CEUS using SHF or PFB improved the sensitivity of HCC diagnosis without compromising specificity.

Objective: The CT/MRI Liver Imaging Reporting and Data System (LI-RADS) demonstrates high specificity with relatively limited sensitivity for diagnosing hepatocellular carcinoma (HCC) in high-risk patients. This study aimed to explore the possibility of improving sensitivity by combining CT/MRI LI-RADS v2018 with second-line contrast-enhanced ultrasound (CEUS) LI-RADS v2017 using sulfur hexafluoride (SHF) or perfluorobutane (PFB). Materials and Methods: This retrospective analysis of prospectively collected multicenter data included high-risk patients with treatment-naive hepatic observations. The reference standard was pathological confirmation or a composite reference standard (only for benign lesions). Each participant underwent concurrent CT/MRI, SHF-enhanced US, and PFB-enhanced US examinations. The diagnostic performances for HCC of CT/MRI LI-RADS alone and three combination strategies (combining CT/ MRI LI-RADS with either LI-RADS SHF, LI-RADS PFB, or a modified algorithm incorporating the Kupffer-phase findings for PFB [modified PFB]) were evaluated. For the three combination strategies, apart from the CT/MRI LR-5 criteria, HCC was diagnosed if CT/MRI LR-3 or LR-4 observations met the LR-5 criteria using LI-RADS SHF, LI-RADS PFB, or modified PFB. Results: In total, 281 participants (237 males; mean age, 55 ± 11 years) with 306 observations (227 HCCs, 40 non-HCC malignancies, and 39 benign lesions) were included. Using LI-RADS SHF, LI-RADS PFB, and modified PFB, 20, 23, and 31 CT/MRI LR-3/4 observations, respectively, were reclassified as LR-5, and all were pathologically confirmed as HCCs. Compared to CT/MRI LI-RADS alone (74%, 95% confidence interval [CI]: 68%–79%), the three combination strategies combining CT/MRI LI-RADS with either LI-RADS SHF, LI-RADS PFB, or modified PFB increased sensitivity (83% [95% CI: 77%–87%], 84% [95% CI: 79%–89%], 88% [95% CI: 83%–92%], respectively; all P < 0.001), while maintaining the specificity at 92% (95% CI: 84%–97%). Conclusion The combination of CT/MRI LI-RADS with second-line CEUS using SHF or PFB improved the sensitivity of HCC diagnosis without compromising specificity.

ObjectiveTo explore the effect of timosaponin BⅡ （TBⅡ） combined with icariin （ICA） on osteoclast （OC）-osteoblast （OB） coupling and decipher the mechanism from the cellular level. MethodsThe cell counting kit-8 （CCK-8） was used to assess the effects of different concentrations of TBⅡ and different concentrations of TBⅡ+ICA on the growth of RAW264.7 cells. Soluble receptor activator of nuclear factor-κB ligand （sRANKL） was used to induce the differentiation of RAW264.7 pre-osteoclasts into osteoclasts. The cells were allocated into sRANKL， TBⅡ （1， 5， 10 μmol·L^-1）， and TBⅡ+ICA groups. Tartrate-resistant acid phosphatase staining was performed to assess the effects of TBⅡ and TBⅡ+ICA on osteoclast differentiation. Real-time quantitative polymerase chain reaction （Real-time PCR） was conducted to examine the effects of TBⅡ+ICA on the expression of key genes involved in osteoclast differentiation and osteoclast-derived coupling factors. The osteogenic differentiation conditioned medium mixed with osteoclast supernatant was used to induce osteogenic differentiation of MC3T3-E1 cells. Alkaline phosphatase staining and alizarin red S staining were employed to determine the effect of TBⅡ+ICA on osteogenic differentiation. Real-time PCR was employed to evaluate the effects of conditioned medium on key genes involved in osteogenic differentiation. ResultsTBⅡ at 1， 5， 10 μmol·L^-1 had no significant effect on the cell survival rate. Compared with the sRANKL group， TBⅡ inhibited osteoclast differentiation in a dose-dependent manner and achieved the best effect at 10 μmol·L^-1 （P<0.01）. Compared with the sRANKL group， different concentrations of TBⅡ down-regulated the mRNA levels of osteoclast differentiation-related genes c-Fos， RANK， and RANKL （P<0.05）. None of 10 μmol·L^-1 TBⅡ， 10 μmol·L^-1 TBⅡ+10^-4 μmol·L^-1 ICA， or 10 μmol·L^-1 TBⅡ+10^-3 μmol·L^-1 ICA affected the viability of RAW264.7 cells. TBⅡ and/or ICA inhibited osteoclast differentiation （P<0.01）， and TBⅡ + ICA had the best effect （P<0.01）. Compared with the sRANKL group， TBⅡ and/or ICA down-regulated the mRNA levels of c-Fos， RANK， and RANKL （P<0.05）. The single application of TBⅡ and ICA had no significant effect on the mRNA levels of Wnt10b， Cthrc1， and C3a， while TBⅡ+ICA exerted up-regulating effects （P<0.05）. Compared with those in the blank group， the bone differentiation and mineralization abilities of the normal osteogenic induction group and each osteogenic induction + osteoclast supernatant group were improved （P<0.01）. Compared with the blank group， the normal osteogenic induction group and the osteogenic induction + osteoclast supernatant group showed up-regulated mRNA levels of Runx2 and OCN （P<0.01）. ConclusionTBⅡ+ICA can inhibit osteoclast differentiation， maintain the normal osteoclast-osteoblast coupling， and promote osteogenic differentiation.

Non-functioning pituitary adenomas(NFPAs)are relatively common.Apart from hyperprolactinemia caused by pituitary compression,they typically lack overt hormonal hypersecretion and usually present with clinical symptoms due to mass effects.Previously considered a uniform entity,NFPAs are actually a highly heterogeneous group of tumors,including aggressive subtypes like silent corticotroph adenomas(SCA)and null cell adenomas.The 2022 WHO new classification of pituitary tumors employs transcription factors[e.g.,pituitary-specific transcription factor 1(PIT-1),T-box transcription factor 19(TBX19,also known as TPIT),steroidogenic factor 1(SF-1)]for detailed categorization,allowing precise subclassification of NFPAs into multiple subtypes derived from distinct cell lineages,including silent gonadotroph adenomas,SCA,and plurihormonal PIT-1-positive adenomas.This helps identify highly invasive subtypes with high recurrence risk,guiding clinical diagnosis and treatment,prognostic assessment,and individualized management.The new classification also provides a theoretical basis for targeted therapies of NFPAs(e.g.,somatostatin analogs and temozolomide).This review comprehensively discusses the latest pathological classification of NFPAs and its clinical implications,aiming to enhance understanding of this disease and offer valuable insights for precise diagnosis,treatment,and prognostic assessment.

Objective To evaluate the value of tripartite motif-containing protein 21(TRIM21)mRNA expression in alveolar macrophages for the serverity and prognosis of patients with severe pneumonia complicated by acute respiratory distress syndrome(SP-ARDS).Methods A retrospective analysis was conducted on 42 SP-ARDS patients(SP-ARDS group)and 15 outpatient healthy controls(control group)admitted to the Department of Respiratory and Critical Care Medicine,Jinling Hospital Affilicated to Medical School of Nanjing University,from November 2023 to June 2024.Bronchoalveolar lavage fluid was collected,and alveolar macrophages were isolated.The expression levels of TRIM21 mRNA were quantified using qPCR.Differences in TRIM21 mRNA expression levels,clinical characteristics,and relevant laboratory test results were compared between the two groups.Correlations between TRIM21 mRNA expression and SP-ARDS severity,28-day mortality,inflammatory indicators,acute physiology and chronic health evaluation Ⅱ(APACHE Ⅱ)scores,duration of mechanical ventilation,and ICU stay were analyzed using Pearson or Spearman correlation analysis.Logistic regression analysis was used to identify risk factors for 28-day mortality,and the predictive value of each factor was evaluated using receiver operating characteristic(ROC)curves.Results Compared with control group,the expression levels of TRIM21 mRNA,white blood cell counts,neutrophil-to-lymphocyte ratio(NLR),and C-reactive protein(CRP),and procalcitonin(PCT)levels increased(P<0.05),and hemoglobin levels decreased(P<0.05)in SP-ARDS group.No significant differences were observed in gender,age,smoking history,alcohol consumption,underlying disease history,and platelet count between the two groups(P>0.05).TRIM21 mRNA expression level in SP-ARDS patients was positively correlated with ARDS severity(P<0.05).Additionally,non-survivors within 28 days had a significantly higher expression level of TRIM21 mRNA compared to survivors(P<0.001).Correlation analysis indicated that the relative expression level of TRIM21 mRNA in SP-ARDS patients was positively correlated with CRP(r=0.309,P<0.05),NLR(r=0.422,P<0.01),PCT(r=0.561,P<0.001),APACHE Ⅱ score(r=0.615,P<0.001),and duration of mechanical ventilation(r=0.665,P<0.001).Logistic regression analysis revealed that elevated expression levels of TRIM21 mRNA(OR=2.886,P=0.043)and higher APACHE Ⅱ scores(OR=1.546,P=0.037)were independent risk factors for 28-day mortality in SP-ARDS patients.The areas under the ROC curves(AUCs)for predicting 28-day mortality using TRIM21 mRNA expression level and APACHE Ⅱ score were 0.889 and 0.874,respectively,with optimal cut-off values of 5.21 and 20.5 points,respectively.The combined AUC for prediction was 0.962.Conclusion Increased TRIM21 mRNA expression in alveolar macrophages of SP-ARDS patients is positively correlated with disease severity and may serve as a potential predictive marker for 28-day survival in SP-ARDS patients.

Objective To discuss the clinical value of flat head CT of two-way digital flat angiography system(DSA)in predicting symptomatic intracranial hemorrhage in patients with acute anterior circulation-large vessel occlusion cerebral infarction occurring within 24 hours after operation.Methods A total of 264 patients with acute anterior circulation-large vessel occlusion cerebral infarction,who were admitted to the Shanghai Changhai hospital to receive treatment from January 2020 to January 2023,were selected for this study.Mechanical thrombectomy was carried out in all the patients,and DSA flat head CT examination was performed 24 hours after operation.According to whether the postoperative DSA plate head CT scan showed high-density shadow or not,the patients were divided into observation group(showing high-density shadow,n=176)and control group(showing no high-density shadow,n=88).The clinical data,therapeutic regimen,and intracranial hemorrhage within 24 hours after operation were compared between the two groups.Taking head CT results as the standard,the clinical value of DSA flat head CT scan performed immediately after operation in predicting symptomatic intracranial hemorrhage occurring within 24 hours after operation was evaluated.Results Among the 264 patients with acute anterior circulation-large vessel occlusion cerebral infarction,118 patients developed intracranial hemorrhage within 24 hours after operation,including 24 patients(20.34％)having symptomatic intracranial hemorrhage.No statistically significant differences in clinical data and therapeutic regimen existed between the two groups(P＞0.05).The sensitivity,specificity and accuracy of DSA flat head CT scan performed immediately after operation in predicting intracranial hemorrhage occurring within 24 hours after operation in the observation group were 97.46％,58.22％and 75.76％respectively.The detection rate of symptomatic intracranial hemorrhage occurring within 24 hours after operation in the observation group was higher than that in the control group,the difference between the two groups were statistically significant(P＜0.05).The sensitivity,specificity and accuracy of DSA flat head CT scan performed immediately after operation in predicting symptomatic intracranial hemorrhage occurring within 24 hours after operation were 87.50％,57.48％and 40.15％respectively.The sensitivity,specificity and accuracy of DSA flat head CT scan in predicting the transformation of cerebral hemorrhage were 95.67％,63.12％and 80.23％respectively.Conclusion In patients with acute anterior circulation-large vessel occlusion cerebral infarction,who develop intracranial hemorrhage within 24 hours after mechanical thrombectomy,DSA flat head CT scan performed immediately after operation often shows high-density shadow,which is very helpful in predicting the risk of postoperative intracranial hemorrhage,the clinicians should make an early diagnosis and response to a possible symptomatic intracranial hemorrhage.

Objective:To explore the diagnostic value of a clinical-radiomics model based on the T 1 mapping and apparent diffusion coefficient (ADC)-based radiomics, and the clinical indicator for renal fibrosis (RF) caused by chronic kidney disease (CKD). Methods:This cross-sectional study prospectively and consecutively enrolled 122 patients with CKD at the Second Affiliated Hospital of Soochow University from September 2021 to December 2023 who were randomly allocated to a training set ( n=85) or a validation set ( n=37) in an approximate 7∶3 ratio using simple random sampling. Patients underwent T 1 mapping and diffusion-weighted imaging scans. Renal biopsy was performed within 3 days after the MRI scans. Patients were categorized into three groups based on the degree of RF: no RF ( n=25), mild RF ( n=55), and moderate to severe RF ( n=42). To differentiate the presence of RF (no RF vs. any RF) and the severity of RF (mild RF vs. moderate to severe RF), univariate and multivariate logistic regression were used to optimize the independent clinical predictor, which constituted the clinical model. Radiomics features were extracted from regions of interest delineated within the renal parenchyma of the right kidney on T 1 mapping and ADC maps. Features were selected using least absolute shrinkage and selection operator regression to build the radiomics model. A clinical-radiomics model was subsequently constructed by integrating the independent clinical predictors with the selected radiomics features. Model diagnostic performance was evaluated using the area under the receiver operating characteristic curve (AUC). Calibration curve was plotted to assess model calibration, and decision curve analysis was performed to evaluate clinical net benefit. Results:Univariate logistic regression analysis revealed that estimated glomerular filtration rate (eGFR), serum creatinine, and blood urea nitrogen exhibited statistically significant differences ( P0.05) in distinguishing both the presence and severity of RF. Multivariate analysis identified eGFR as an independent clinical predictor for both the presence of RF ( OR=0.939, 95% CI 0.898-0.982, P=0.006) and RF severity ( OR=0.956, 95% CI 0.917-0.997, P=0.037). From the MRI images, 7 radiomics features were selected to build the radiomics model for distinguishing the presence of RF, and 8 features were selected for the model assessing RF severity. These radiomics models were then combined with eGFR to construct the clinical-radiomics models. The clinical-radiomics models demonstrated the highest diagnostic performance, with an AUC of 0.935 (95% CI 0.859-0.977) for RF presence and 0.967 (95% CI 0.891-0.995) for RF severity in the training set, and 0.914 (95% CI 0.774-0.981) and 0.908 (95% CI 0.748-0.981) in the validation set. Calibration curves and decision curve analysis confirmed that the clinical-radiomics models exhibited excellent calibration and provided the highest clinical net benefit for assessing RF in CKD patients. Conclusion:The clinical-radiomics model integrating T 1 mapping and ADC-based radiomics and eGFR can effectively improve the diagnostic performance for RF in CKD patients.

Objective:To develop and design a during-treatment records auto-review program to comply the quality assurance(QA)requirement of radiotherapy chart auditing,and thereby improve the review efficiency and accuracy.Methods:Based on the items the guideline required,the Aria Oncology Information System database backup files was analyzed by Java,Vue,and etc.languages and the corresponding review logic was formulated.A total of 530 treatment records generated at Shanghai Concord Cancer Center from January to March 2024(10 weeks)were auto-reviewed and compared with the manual results for evaluating the accuracy and efficiency of the program.Results:The auto-review program was running smoothly.Overall with the above data,the sensitivity,specificity,accuracy and the error-miss rate were 73.4%,14.3%,87.7%and 12.3%respectively.For sub-set items,the source-skin distance(SSD)error detecting rate was 100%,the wrong session reporting was 100%correlated with the plans switching and the wrong fraction reporting was 100%related to plan revision.For the other items,auto and manual reviews gave out the same accuracy.Conclusion:The none-error results from the program are all true,so the manual rechecking could limit to those auto-review error records,which can reduce the workload by 73.4%,therefore improve the effectiveness and accuracy of the radiotherapy data review.