Ensemble learning-based pretreatment MRI radiomic model for distinguishing intracranial extraventricular ependymoma from glioblastoma multiforme.

This study aims to develop an ensemble learning (EL) method based on magnetic resonance (MR) radiomic features to preoperatively differentiate intracranial extraventricular ependymoma (IEE) from glioblastoma (GBM). This retrospective study enrolled patients with histopathologically confirmed IEE and GBM from June 2016 to June 2021. Radiomics features were extracted from T1-weighted imaging (T1WI) and T2-weighted imaging (T2WI) sequence images, and classification models were constructed using EL methods and logistic regression (LR). The efficiency of the models was assessed using receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis. The combined EL model, based on clinical parameters and radiomic features from T1WI and T2WI images, demonstrated good discriminative ability, achieving an area under the receiver operating characteristics curve (AUC) of 0.96 (95% CI 0.94-0.98), a specificity of 0.84, an accuracy of 0.92, and a sensitivity of 0.95 in the training set, and an AUC of 0.89 (95% CI 0.83-0.94), a specificity of 0.83, an accuracy of 0.81, and a sensitivity of 0.74 in the validation set. The discriminative efficacy of the EL model was significantly higher than that of the LR model. Favorable calibration performance and clinical applicability for the EL model were observed. The EL model combining preoperative MR-based tumor radiomics and clinical data showed high accuracy and sensitivity in differentiating IEE from GBM preoperatively, which may potentially assist in clinical management of these brain tumors.

Multi-omics profiling of retinal pigment epithelium reveals enhancer-driven activation of RANK-NFATc1 signaling in traumatic proliferative vitreoretinopathy.

During the progression of proliferative vitreoretinopathy (PVR) following ocular trauma, previously quiescent retinal pigment epithelial (RPE) cells transition into a state of rapid proliferation, migration, and secretion. The elusive molecular mechanisms behind these changes have hindered the development of effective pharmacological treatments, presenting a pressing clinical challenge. In this study, by monitoring the dynamic changes in chromatin accessibility and various histone modifications, we chart the comprehensive epigenetic landscape of RPE cells in male mice subjected to traumatic PVR. Coupled with transcriptomic analysis, we reveal a robust correlation between enhancer activation and the upregulation of the PVR-associated gene programs. Furthermore, by constructing transcription factor regulatory networks, we identify the aberrant activation of enhancer-driven RANK-NFATc1 pathway as PVR advanced. Importantly, we demonstrate that intraocular interventions, including nanomedicines inhibiting enhancer activity, gene therapies targeting NFATc1 and antibody therapeutics against RANK pathway, effectively mitigate PVR progression. Together, our findings elucidate the epigenetic basis underlying the activation of PVR-associated genes during RPE cell fate transitions and offer promising therapeutic avenues targeting epigenetic modulation and the RANK-NFATc1 axis for PVR management.

Lipid-Encapsulated Engineered Bacterial Living Materials Inhibit Cyclooxygenase II to Enhance Doxorubicin Toxicity.

Recently, there has been increasing interest in the use of bacteria for cancer therapy due to their ability to selectively target tumor sites and inhibit tumor growth. However, the complexity of the interaction between bacteria and tumor cells evokes unpredictable therapeutic risk, which induces inflammation, stimulates the up-regulation of cyclooxygenase II (COX-2) protein, and stimulates downstream antiapoptotic gene expression in the tumor microenvironment to reduce the antitumor efficacy of chemotherapy and immunotherapy. In this study, we encapsulated celecoxib (CXB), a specific COX-2 inhibitor, in liposomes anchored to the surface of Escherichia coli Nissle 1917 (ECN) through electrostatic absorption (C@ECN) to suppress ECN-induced COX-2 up-regulation and enhance the synergistic antitumor effect of doxorubicin (DOX). C@ECN improved the antitumor effect of DOX by restraining COX-2 expression. In addition, local T lymphocyte infiltration was induced by the ECN to enhance immunotherapy efficacy in the tumor microenvironment. Considering the biosafety of C@ECN, a hypoxia-induced lysis circuit, pGEX-Pvhb-Lysis, was introduced into the ECN to limit the number of ECNs in vivo. Our results indicate that this system has the potential to enhance the synergistic effect of ECN with chemical drugs to inhibit tumor progression in medical oncology.

Radiomics Nomogram Derived from Gated Myocardial Perfusion SPECT for Identifying Ischemic Cardiomyopathy.

Personalized management involving heart failure (HF) etiology is crucial for better prognoses. We aim to evaluate the utility of a radiomics nomogram based on gated myocardial perfusion imaging (GMPI) in distinguishing ischemic from non-ischemic origins of HF. A total of 172 heart failure patients with reduced left ventricular ejection fraction (HFrEF) who underwent GMPI scan were divided into training (n = 122) and validation sets (n = 50) based on chronological order of scans. Radiomics features were extracted from the resting GMPI. Four machine learning algorithms were used to construct radiomics models, and the model with the best performances were selected to calculate the Radscore. A radiomics nomogram was constructed based on the Radscore and independent clinical factors. Finally, the model performance was validated using operating characteristic curves, calibration curve, decision curve analysis, integrated discrimination improvement values (IDI), and the net reclassification index (NRI). Three optimal radiomics features were used to build a radiomics model. Total perfusion deficit (TPD) was identified as the independent factors of conventional GMPI metrics for building the GMPI model. In the validation set, the radiomics nomogram integrating the Radscore, age, systolic blood pressure, and TPD significantly outperformed the GMPI model in distinguishing ischemic cardiomyopathy (ICM) from non-ischemic cardiomyopathy (NICM) (AUC 0.853 vs. 0.707, p = 0.038). IDI analysis indicated that the nomogram improved diagnostic accuracy by 28.3% compared to the GMPI model in the validation set. By combining radiomics signatures with clinical indicators, we developed a GMPI-based radiomics nomogram that helps to identify the ischemic etiology of HFrEF.

Alteration of prefrontal cortex and its associations with emotional and cognitive dysfunctions in adolescent borderline personality disorder.

The neurobiological mechanism of borderline personality disorder (BPD) in adolescents remains unclear. The study aimed to assess the alterations in neural activity within prefrontal cortex in adolescents with BPD and investigate the relationship of prefrontal activity with emotional regulation and cognitive function. This study enrolled 50 adolescents aged 12-17 years with BPD and 21 gender and age-matched healthy control (HC) participants. Study assessment for each participant included a brain resting-state functional MRI (rs-fMRI), clinical assessment questionnaires such as Borderline Personality Features Scale (BPFS), Difficulties in Emotion Regulation Scale (DERS), Ottawa Self-Injury Inventory and Childhood Trauma Questionnaire (CTQ) and cognitive testing with Stroop Color-Word Test (SCWT). Fractional amplitude of low-frequency fluctuations (fALFF) and seed-based functional connectivity (FC) were obtained from rs-fMRI analysis. Correlation analysis was also performed to evaluate the associations of the neuroimaging metrics such as fALFF and FC with clinical assessment questionnaire and cognitive testing scores. Adolescents with BPD showed increased fALFF values in the right inferior frontal gyrus and decreased activity in the left middle frontal gyrus as compared to the HC group (p < 0.05, cluster size ≥ 100, FWE correction). In adolescents with BPD, increased fALFF in the right inferior frontal gyrus was related to the BPFS (emotional dysregulation), DERS-F (lacking of emotional regulation strategies) and Ottawa Self-Injury Inventory-4 C scores (internal emotional regulation function of self-injurious behavior). The reduced fALFF in the left middle frontal gyrus was associated with the SCWT-A (reading characters) and the SCWT-B (reading color) scores. Additionally, the fALFF values in the left middle frontal gyrus and the right inferior frontal gyrus were related to the CTQ-D (emotional neglect) (p < 0.05). The left middle frontal gyrus exhibited increased FC with the right hippocampus, left inferior temporal gyrus and right inferior frontal gyrus (voxel p < 0.001, cluster p < 0.05, FWE correction). The increased FC between the left middle frontal gyrus and the right hippocampus was related to the SCWT-C (cognitive flexibility) score. We observed diverging changes in intrinsic brain activity in prefrontal cortex, and neural compensatory changes to maintain function in adolescents with BPD. In addition, decreased neural function was closely associated with emotional dysregulation, while increased neural function as indicated by brain activity and FC was associated with cognitive dysfunction. These results indicated that alterations of intrinsic brain activity may be one of the underlying neurobiological markers for clinical symptoms in adolescents with BPD.

A chest CT-based nomogram for predicting survival in acute myeloid leukemia.

BACKGROUND: The identification of survival predictors is crucial for early intervention to improve outcome in acute myeloid leukemia (AML). This study aim to identify chest computed tomography (CT)-derived features to predict prognosis for acute myeloid leukemia (AML). METHODS: 952 patients with pathologically-confirmed AML were retrospectively enrolled between 2010 and 2020. CT-derived features (including body composition and subcutaneous fat features), were obtained from the initial chest CT images and were used to build models to predict the prognosis. A CT-derived MSF nomogram was constructed using multivariate Cox regression incorporating CT-based features. The performance of the prediction models was assessed with discrimination, calibration, decision curves and improvements. RESULTS: Three CT-derived features, including myosarcopenia, spleen_CTV, and SF_CTV (MSF) were identified as the independent predictors for prognosis in AML (P < 0.01). A CT-MSF nomogram showed a performance with AUCs of 0.717, 0.794, 0.796 and 0.792 for predicting the 1-, 2-, 3-, and 5-year overall survival (OS) probabilities in the validation cohort, which were significantly higher than the ELN risk model. Moreover, a new MSN stratification system (MSF nomogram plus ELN risk model) could stratify patients into new high, intermediate and low risk group. Patients with high MSN risk may benefit from intensive treatment (P = 0.0011). CONCLUSIONS: In summary, the chest CT-MSF nomogram, integrating myosarcopenia, spleen_CTV, and SF_CTV features, could be used to predict prognosis of AML.

Nomogram incorporating preoperative MRI-VASARI features for differentiating intracranial extraventricular ependymoma from glioblastoma.

Background: Intracranial extraventricular ependymoma (IEE) and glioblastoma (GBM) may have similar imaging findings but different prognosis. This study aimed to develop and validate a nomogram based on magnetic resonance imaging (MRI) Visually AcceSAble Rembrandt Images (VASARI) features for preoperatively differentiating IEE from GBM. Methods: The clinical data and the MRI-VASARI features of patients with confirmed IEE (n=114) and confirmed GBM (n=258) in a multicenter cohort were retrospectively analyzed. Predictive models for differentiating IEE from GBM were built using a multivariate logistic regression method. A nomogram was generated and the performance of the nomogram was assessed with respect to its calibration, discrimination, and clinical usefulness. Results: The predictors identified in this study consisted of six VASARI features and four clinical features. Compared with the individual models, the combined model incorporating clinical and VASARI features had the highest area under the curve (AUC) value [training set: 0.99, 95% confidence interval (CI): 0.98-1.00; validation set: 0.97, 95% CI: 0.94-1.00] in comparison to the clinical model. The nomogram was well calibrated with significant clinical benefit according to the calibration curve and decision curve analyses. Conclusions: The nomogram combining clinical and MRI-VASARI characteristics was robust for differentiating IEE from GBM preoperatively and may potentially assist in diagnosis and treatment of brain tumors.

Altered gray matter volume and functional connectivity in adolescent borderline personality disorder with non-suicidal self-injury behavior.

BACKGROUND AND OBJECTIVES: Non-suicidal self-injury (NSSI) behavior is one of the characteristics of borderline personality disorder (BPD) in adolescents. Prior studies have shown that adolescents with BPD may have a unique pattern of brain alterations. The purpose of this study was to investigate the alterations in brain structure and function including gray matter volume and resting-state functional connectivity in adolescents with BPD, and to assess the association between NSSI behavior and brain changes on neuroimaging in adolescents with BPD. METHODS: 53 adolescents with BPD aged 12-17 years and 39 age-gender matched healthy controls (HCs) were enrolled into this study. Brain magnetic resonance imaging (MRI) was acquired with both 3D-T1 weighted structural imaging and resting-state functional imaging. Voxel-based morphometry (VBM) analysis for gray matter volume and seed-based functional connectivity (FC) analysis were performed for assessing gray matter volume and FC. Clinical assessment for NSSI, mood, and depression was also obtained. Correlative analysis of gray matter alterations with self-injury or mood scales were performed. RESULTS: There were reductions of gray matter volume in the limbic-cortical circuit and default mode network in adolescents with BPD as compared to HCs (FWE P < 0.05, cluster size ≥ 1000). The diminished gray matter volumes in the left putamen and left middle occipital gyrus were negatively correlated with NSSI in adolescents with BPD (r = - 0.277 and P = 0.045, r = - 0.422 and P = 0.002, respectively). Furthermore, there were alterations of FC in these two regions with diminished gray matter volumes (voxel P < 0.001, cluster P < 0.05, FWE corrected). CONCLUSIONS: Our results suggest that diminished gray matter volume of the limbic-cortical circuit and default mode network may be an important neural correlate in adolescent BPD. In addition, the reduced gray matter volume and the altered functional connectivity may be associated with NSSI behavior in adolescents with BPD.

Ensemble Machine Learning Model Incorporating Radiomics and Body Composition for Predicting Intraoperative HDI in PPGL.

CONTEXT: Intraoperative hemodynamic instability (HDI) can lead to cardiovascular and cerebrovascular complications during surgery for pheochromocytoma/paraganglioma (PPGL). OBJECTIVES: We aimed to assess the risk of intraoperative HDI in patients with PPGL to improve surgical outcome. METHODS: A total of 199 consecutive patients with PPGL confirmed by surgical pathology were retrospectively included in this study. This cohort was separated into 2 groups according to intraoperative systolic blood pressure, the HDI group (n = 101) and the hemodynamic stability (HDS) group (n = 98). It was also divided into 2 subcohorts for predictive modeling: the training cohort (n = 140) and the validation cohort (n = 59). Prediction models were developed with both the ensemble machine learning method (EL model) and the multivariate logistic regression model using body composition parameters on computed tomography, tumor radiomics, and clinical data. The efficiency of the models was evaluated with discrimination, calibration, and decision curves. RESULTS: The EL model showed good discrimination between the HDI group and HDS group, with an area under the curve of (AUC) of 96.2% (95% CI, 93.5%-99.0%) in the training cohort, and an AUC of 93.7% (95% CI, 88.0%-99.4%) in the validation cohort. The AUC values from the EL model were significantly higher than the logistic regression model, which had an AUC of 74.4% (95% CI, 66.1%-82.6%) in the training cohort and an AUC of 74.2% (95% CI, 61.1%-87.3%) in the validation cohort. Favorable calibration performance and clinical applicability of the EL model were observed. CONCLUSION: The EL model combining preoperative computed tomography-based body composition, tumor radiomics, and clinical data could potentially help predict intraoperative HDI in patients with PPGL.

Association of white matter microstructural alteration with non-suicidal self-injury behavior and visual working memory in adolescents with borderline personality disorder.

BACKGROUND: Non-suicidal self-injurious behavior (NSSI) is the core characteristic of adolescent borderline personality disorder (BPD) and visual working memory is involved in the pathological processes of BPD. This study aimed to investigate alterations in white matter microstructure and their association with NSSI and visual working memory in adolescents with BPD. METHODS: 53 adolescents diagnosed with BPD and 39 healthy controls (HCs) were enrolled. White matter microstructure was assessed with the fractional anisotropy (FA) and mean diffusivity (MD) from diffusion tensor imaging (DTI). Correlation analysis was performed to assess the association between FA/MD and core features of BPD. A mediation analysis was performed to test whether the effects of white matter alterations on NSSI could be mediated by visual working memory. RESULTS: Adolescents with BPD showed a reduced FA and an increased MD in the cortical-limbic and cortical-thalamus circuit when compared to the HCs (p < 0.05). Increased MD was positively correlated with NSSI, impulse control and identity disturbance (p < 0.05), and was negatively correlated with the score of visual reproduction. Reserved visual working memory masked the effects of white matter microstructural alterations on NSSI behavior. CONCLUSIONS: White matter microstructural deficits in the cortical-limbic and cortical-thalamus circuits may be associated with NSSI and visual working memory in adolescents with BPD. Reserved visual working memory may protect against NSSI.

Altered brain activity and cognitive impairment in patients with psoriasis.

BACKGROUND: Patients with psoriasis may have cognitive impairment. However, there is limited information regarding intrinsic brain activity and cognitive function in patients with psoriasis. OBJECTIVES: This study aim to assess alterations of intrinsic brain activity and its association with cognitive function in patients with psoriasis. METHODS: A total of 222 patients with psoriasis aged 18-70 years and 144 age and gender-matched healthy controls (HCs) were enrolled into this study. All subjects underwent brain resting-state functional magnetic resonance imaging (rs-fMRI) and neuropsychological testing. The rs-fMRI data were analysed for both intrinsic brain activity as indicated by amplitude of low-frequency fluctuation (ALFF) and seed-based functional connectivity (FC). Correlative analysis of brain activity with cognitive assessment was performed. RESULTS: Compared with the HCs, patients with psoriasis had worse cognitive performance in the Trail Making Test, Digit Span Test and Stroop Color-Word Test (p < 0.05). Patients with psoriasis showed decreased ALFF in the left superior frontal gyrus, the left medial superior frontal gyrus and the right precuneus gyrus; as well as enhanced ALFF in the left paracentral lobule (pFWE < 0.05). Significant correlations were noted between the altered ALFF in the four brain regions and cognitive assessment (p < 0.05). Moreover, patients with psoriasis had increased FC between the four brain regions with altered ALFF (seeds) and the left prefrontal gyrus, the left anterior cingulate gyrus, left superior parietal lobule and default mode network (DMN) regions such as the right precuneus gyrus, left inferior parietal lobule, right angular gyrus and bilateral inferior temporal gyrus (pFWE < 0.05). CONCLUSIONS: Patients with psoriasis had altered brain activity and connectivity in the key brain areas within the DMN-prefrontal circuit. These brain changes may be the underlying neural correlates for cognitive functioning in patients with psoriasis.

[Effects of manipulating lactate dehydrogenase gene on metabolism of HEK-293 and production of human adenovirus].

Reducing lactate accumulation has always been a goal of the mammalian cell biotechnology industry. When animal cells are cultured in vitro, the accumulation of lactate is mainly the combined result of two metabolic pathways. On one hand, glucose generates lactate under the function of lactate dehydrogenase A (LDHA); on the other hand, lactate can be oxidized to pyruvate by LDHB or LDHC and re-enter the TCA cycle. This study comprehensively evaluated the effects of LDH manipulation on the growth, metabolism and human adenovirus (HAdV) production of human embryonic kidney 293 (HEK-293) cells, providing a theoretical basis for engineering the lactate metabolism in mammalian cells. By knocking out ldha gene and overexpression of ldhb and ldhc genes, the metabolic efficiency of HEK-293 cells was effectively improved, and HAdV production was significantly increased. Compared with the control cell, LDH manipulation promoted cell growth, reduced the accumulation of lactate and ammonia, significantly enhanced the efficiency of substrate and energy metabolism of cells, and significantly increased the HAdV production capacity of HEK-293 cells. Among these LDH manipulation measures, ldhc gene overexpression performed the best, with the maximum cell density increased by about 38.7%. The yield of lactate to glucose and ammonia to glutamine decreased by 33.8% and 63.3%, respectively; and HAdV titer increased by at least 16 times. In addition, the ATP production rate, ATP/O2 ratio, ATP/ADP ratio and NADH content of the modified cell lines were increased to varying degrees, and the energy metabolic efficiency was significantly improved.

Prediction of clinically significant prostate cancer using a novel 68Ga-PSMA PET-CT and multiparametric MRI-based model.

Background: There are some limitations in the commonly used methods for the detection of prostate cancer. There is a lack of nomograms based on multiparametric magnetic resonance imaging (mpMRI) and 68Ga-prostate-specific membrane antigen (PSMA) positron emission tomography-computed tomography (PET-CT) for the prediction of prostate cancer. The study seeks to compare the performance of mpMRI and 68Ga-PSMA PET-CT, and design a novel predictive model capable of predicting clinically significant prostate cancer (csPCa) before biopsy based on a combination of 68Ga-PSMA PET-CT, mpMRI, and patient clinical parameters. Methods: From September 2020 to June 2021, we prospectively enrolled 112 consecutive patients with no prior history of prostate cancer who underwent both 68Ga-PSMA PET-CT and mpMRI prior to biopsy at our clinical center. Univariate and multivariate regression analyses were used to identify predictors of csPCa, with a predictive model and its nomogram incorporating 68Ga-PSMA PET-CT, mpMRI, and the clinical predictors then being generated. The constructed model was evaluated using receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis, and further validated with the internal and external cohorts. Results: The model incorporated prostate-specific antigen density (PSAd), Prostate Imaging Reporting and Data System (PI-RADS) category, and maximum standardized uptake value (SUVmax), and it exhibited excellent predictive efficacy when applying to evaluate both training and validation cohorts [area under the curve (AUC): 0.936 and 0.940, respectively]. Compared with SUVmax alone, the model demonstrated excellent diagnostic performance with improved specificity (0.910, 95% CI: 0.824-0.963) and positive predictive values (0.811, 95% CI: 0.648-0.920). Calibration curve and decision curve analysis further confirmed that the model exhibited a high degree of clinical net benefit and low error rate. Conclusions: The constructed model in this study was capable of accurately predicting csPCa prior to biopsy with excellent discriminative ability. As such, this model has the potential to be an effective non-invasive approach for the diagnosis of csPCa.

Surformer: An interpretable pattern-perceptive survival transformer for cancer survival prediction from histopathology whole slide images.

BACKGROUND AND OBJECTIVE: High-resolution histopathology whole slide images (WSIs) contain abundant valuable information for cancer prognosis. However, most computational pathology methods for survival prediction have weak interpretability and cannot explain the decision-making processes reasonably. To address this issue, we propose a highly interpretable neural network termed pattern-perceptive survival transformer (Surformer) for cancer survival prediction from WSIs. METHODS: Notably, Surformer can quantify specific histological patterns through bag-level labels without any patch/cell-level auxiliary information. Specifically, the proposed ratio-reserved cross-attention module (RRCA) generates global and local features with the learnable prototypes (pglobal, plocals) as detectors and quantifies the patches correlative to each plocal in the form of ratio factors (rfs). Afterward, multi-head self&cross-attention modules proceed with the computation for feature enhancement against noise. Eventually, the designed disentangling loss function guides multiple local features to focus on distinct patterns, thereby assisting rfs from RRCA in achieving more explicit histological feature quantification. RESULTS: Extensive experiments on five TCGA datasets illustrate that Surformer outperforms existing state-of-the-art methods. In addition, we highlight its interpretation by visualizing rfs distribution across high-risk and low-risk cohorts and retrieving and analyzing critical histological patterns contributing to the survival prediction. CONCLUSIONS: Surformer is expected to be exploited as a useful tool for performing histopathology image data-driven analysis and gaining new insights for interpreting the associations between such images and patient survival states.

Altered resting-state functional connectivity and its association with executive function in adolescents with borderline personality disorder.

Adolescents with borderline personality disorder (BPD) may have impaired executive functions. There are few functional MRI (fMRI) studies in adolescents with BPD and the neuroimaging markers of this disorder are unknown. The aim of this study was to investigate the functional connectivity (FC) of BPD in adolescents, and to explore the relationship between FC changes and executive function in adolescents with BPD. 50 adolescents aged 12 to 17 years with BPD and 21 gender-and-age matched healthy controls (HC) were enrolled into the study. Brain MRI scan including a 3D-T1 weighted structural sequence and a resting-state fMRI was acquired. A seed-based FC analysis was performed. We used the Stroop color-word test (SCWT) and the trail making test (TMT) to evaluate the executive function of the participants. Correlative analysis of FC alterations with executive function and clinical symptoms was also performed. Compared to the HCs, adolescents with BPD showed increased FC in the limbic-cortical circuit, such as the FC between the left hippocampus and right parahippocampal gyrus, between the right middle occipital gyrus and the left middle temporal gyrus, and between the left medial superior frontal gyrus and the right inferior temporal gyrus. FC in the default mode network (DMN) was decreased between the left angular gyrus and the left precuneus but increased between the left angular gyrus and the right anterior cingulate cortex (voxel P < 0.001, cluster P < 0.05, FWE corrected). The BPD group demonstrated significantly lower cognitive testing scores than the HC group on the SCWT-A (P < 0.001), SCWT-B (P < 0.001), and SCWT-C (P = 0.034). The FC alterations between limbic system and cortical regions were associated with SCWT and TMT (P < 0.05). FC alterations were noted in both limbic-cortical circuit and DMN in adolescents with BPD, which were associated with impaired executive function. This study implicated the FC alterations as the neural correlates of executive functioning in adolescents with BPD.

Next-generation magnesium-ion batteries: The quasi-solid-state approach to multivalent metal ion storage.

Mg-ion batteries offer a safe, low-cost, and high-energy density alternative to current Li-ion batteries. However, nonaqueous Mg-ion batteries struggle with poor ionic conductivity, while aqueous batteries face a narrow electrochemical window. Our group previously developed a water-in-salt battery with an operating voltage above 2 V yet still lower than its nonaqueous counterpart because of the dominance of proton over Mg-ion insertion in the cathode. We designed a quasi-solid-state magnesium-ion battery (QSMB) that confines the hydrogen bond network for true multivalent metal ion storage. The QSMB demonstrates an energy density of 264 W·hour kg-1, nearly five times higher than aqueous Mg-ion batteries and a voltage plateau (2.6 to 2.0 V), outperforming other Mg-ion batteries. In addition, it retains 90% of its capacity after 900 cycles at subzero temperatures (-22°C). The QSMB leverages the advantages of aqueous and nonaqueous systems, offering an innovative approach to designing high-performing Mg-ion batteries and other multivalent metal ion batteries.

Association of brain morphology and phenotypic profile in patients with unruptured intracranial aneurysm.

Introduction: Studies have found a varying degree of cognitive, psychosocial, and functional impairments in patients with unruptured intracranial aneurysms (UIAs), whereas the neural correlates underlying these impairments remain unknown. Methods: To examine the brain morphological alterations and white matter lesions in patients with UIA, we performed a range of structural analyses to examine the brain morphological alterations in patients with UIA compared with healthy controls (HCs). Twenty-one patients with UIA and 23 HCs were prospectively enrolled into this study. Study assessment consisted of a brain magnetic resonance imaging (MRI) scan with high-resolution T1-weighted and T2-weighted imaging data, a Montreal Cognitive Assessment (MoCA), and laboratory tests including blood inflammatory markers and serum lipids. Brain MRI data were processed for cortical thickness, local gyrification index (LGI), volume and shape of subcortical nuclei, and white matter lesions. Results: Compared to the HCs, patients with UIA showed no significant differences in cortical thickness but decreased LGI values in the right posterior cingulate cortex, retrosplenial cortex, cuneus, and lingual gyrus. In addition, decreased LGI values correlated with decreased MoCA score (r = 0.498, p = 0.021) and increased white matter lesion scores (r = -0.497, p = 0.022). The LGI values were correlated with laboratory values such as inflammatory markers and serum lipids. Patients with UIA also showed significant regional atrophy in bilateral thalami as compared to the HCs. Moreover, the LGI values were significantly correlated with thalamic volume in the HCs (r = 0.4728, p = 0.0227) but not in the patients with UIA (r = 0.11, p = 0.6350). Discussion: The decreased cortical gyrification, increased white matter lesions, and regional thalamic atrophy in patients with UIA might be potential neural correlates of cognitive changes in UIA.

Magnetic resonance imaging findings of intracranial extraventricular ependymoma: A retrospective multi-center cohort study of 114 cases.

BACKGROUND: Intracranial extraventricular ependymoma (IEE) is an ependymoma located in the brain parenchyma outside the ventricles. IEE has overlapping clinical and imaging characteristics with glioblastoma multiforme (GBM) but different treatment strategy and prognosis. Therefore, an accurate preoperative diagnosis is necessary for optimizing therapy for IEE. METHODS: A retrospective multicenter cohort of IEE and GBM was identified. MR imaging characteristics assessed with the Visually Accessible Rembrandt Images (VASARI) feature set and clinicopathological findings were recorded. Independent predictors for IEE were identified using multivariate logistic regression, which was used to construct a diagnostic score for differentiating IEE from GBM. RESULTS: Compared to GBM, IEE tended to occur in younger patients. Multivariate logistic regression analysis identified seven independent predictors for IEE. Among them, 3 predictors including tumor necrosis rate (F7), age, and tumor-enhancing margin thickness (F11), demonstrated higher diagnostic performance with an Area Under Curve (AUC) of more than 70% in distinguishing IEE from GBM. The AUC was 0.85, 0.78, and 0.70, with sensitivity of 92.98%, 72.81%, and 96.49%, and specificity of 65.50%, 73.64%, and 43.41%, for F7, age, and F11, respectively. CONCLUSION: We identified specific MR imaging features such as tumor necrosis and thickness of enhancing tumor margins that could help to differentiate IEE from GBM. Our study results should be helpful to assist in diagnosis and clinical management of this rare brain tumor.

A Phase 1/2 Multicenter Randomized Trial of Local Ablation plus Toripalimab versus Toripalimab Alone for Previously Treated Unresectable Hepatocellular Carcinoma.

PURPOSE: To assess the safety and efficacy of local ablation plus PD-1 inhibitor toripalimab in previously treated unresectable hepatocellular carcinoma (HCC). PATIENTS AND METHODS: In the multicenter, two-stage, and randomized phase 1/2 trial, patients were randomly assigned to receive toripalimab alone (240 mg, every 3 weeks), subtotal local ablation followed by toripalimab starting on post-ablation day 3 (Schedule D3), or on post-ablation day 14 (Schedule D14). The first endpoint of stage 1 was to determine which combination schedule could continue and progression-free survival (PFS) as the primary endpoint for stage 1/2. RESULTS: A total of 146 patients were recruited. During stage 1, Schedule D3 achieved numerically higher objective response rate (ORR) than Schedule D14 for non-ablation lesions (37.5% vs. 31.3%), and was chosen for stage 2 evaluation. For the entire cohort of both stages, patients with Schedule D3 had a significantly higher ORR than with toripalimab alone (33.8% vs. 16.9%; P = 0.027). Moreover, patients with Schedule D3 had improved median PFS (7.1 vs. 3.8 months; P < 0.001) and median overall survival (18.4 vs. 13.2 months; P = 0.005), as compared with toripalimab alone. In addition, six (9%) patients with toripalimab, eight (12%) with Schedule D3, and 4 (25%) with Schedule D14 developed grade 3 or 4 adverse events, and one patient (2%) with Schedule D3 manifested grade 5 treatment-related pneumonitis. CONCLUSIONS: In patients with previously treated unresectable HCC, subtotal ablation plus toripalimab improved the clinical efficacy as compared with toripalimab alone, with an acceptable safety profile.