Radiomic analysis reveals diverse prognostic and molecular insights into the response of breast cancer to neoadjuvant chemotherapy: a multicohort study.

BACKGROUND: Breast cancer patients exhibit various response patterns to neoadjuvant chemotherapy (NAC). However, it is uncertain whether diverse tumor response patterns to NAC in breast cancer patients can predict survival outcomes. We aimed to develop and validate radiomic signatures indicative of tumor shrinkage and therapeutic response for improved survival analysis. METHODS: This retrospective, multicohort study included three datasets. The development dataset, consisting of preoperative and early NAC DCE-MRI data from 255 patients, was used to create an imaging signature-based multitask model for predicting tumor shrinkage patterns and pathological complete response (pCR). Patients were categorized as pCR, nonpCR with concentric shrinkage (CS), or nonpCR with non-CS, with prediction performance measured by the area under the curve (AUC). The prognostic validation dataset (n = 174) was used to assess the prognostic value of the imaging signatures for overall survival (OS) and recurrence-free survival (RFS) using a multivariate Cox model. The gene expression data (genomic validation dataset, n = 112) were analyzed to determine the biological basis of the response patterns. RESULTS: The multitask learning model, utilizing 17 radiomic signatures, achieved AUCs of 0.886 for predicting tumor shrinkage and 0.760 for predicting pCR. Patients who achieved pCR had the best survival outcomes, while nonpCR patients with a CS pattern had better survival than non-CS patients did, with significant differences in OS and RFS (p = 0.00012 and p = 0.00063, respectively). Gene expression analysis highlighted the involvement of the IL-17 and estrogen signaling pathways in response variability. CONCLUSIONS: Radiomic signatures effectively predict NAC response patterns in breast cancer patients and are associated with specific survival outcomes. The CS pattern in nonpCR patients indicates better survival.

Magnetic resonance imaging-based prognostic model for subsequent distant metastasis in patients with ipsilateral breast tumor recurrence following breast-conserving surgery.

Background: Ipsilateral breast tumor recurrence (IBTR) following breast-conserving surgery (BCS) has been considered a risk factor for distant metastasis (DM). Limited data are available regarding the subsequent outcomes after IBTR. Therefore, this study aimed to determine the clinical course after IBTR and develop a magnetic resonance imaging (MRI)-based predictive model for subsequent DM. Methods: We retrospectively extracted quantitative features from MRI to construct a radiomics cohort, with all eligible patients undergoing preoperative MRI at time of primary tumor and IBTR between 2010 and 2018. Multivariate Cox analysis was performed to identify factors associated with DM. Three models were constructed using different sets of clinicopathological, qualitative, and quantitative MRI features and compared. Additionally, Kaplan-Meier analysis was performed to assess the prognostic value of the optimal model. Results: Among the 183 patients who experienced IBTR, 47 who underwent MRI for both primary and recurrent tumors were enrolled. Multivariate analysis demonstrated that the independent prognostic factors were human epidermal growth factor receptor 2 (HER2) status [hazard ratio (HR) =5.40] and background parenchymal enhancement (BPE) (HR =7.94) (all P values <0.01). Furthermore, four quantitative MRI features of recurrent tumors were selected through the least absolute shrinkage and selection operator (LASSO) method. The combined model exhibited superior performance [concordance index (C-index) 0.77] compared to the clinicoradiological model (C-index 0.71; P=0.006) and radiomics model (C-index 0.70; and P=0.01). Furthermore, the combined model successfully categorized patients into low- and high-risk subgroups with distinct prognoses (P<0.001). Conclusions: The clinicopathological and MRI features of IBTR were associated with secondary events following surgery. Additionally, the MRI-based combined model exhibited the highest predictive efficacy. These findings could be helpful in risk stratification and tailoring follow-up strategies in patients with IBTR.

Association between perioperative change in red cell distribution width and mortality in patients with brain tumor craniotomy.

OBJECTIVE: An elevated preoperative red cell distribution width (RDW) is associated with adverse prognostic outcomes in various diseases. However, the correlation between changes in RDW (ΔRDW) and the prognosis following brain tumor craniotomy remains unclear. Accordingly, this study aimed to investigate the prognostic significance of perioperative changes in RDW in patients undergoing brain tumor craniotomy. METHODS: This retrospective cohort study included patients undergoing craniotomy for brain tumors at West China Hospital, Sichuan University, from January 2011 to March 2021. We defined perioperative changes in RDW: group A (non-significant RDW changes, ΔRDW ≤0.4%), group B (drop in RDW, ΔRDW < -0.4%), and group C (rise in RDW, ΔRDW >0.4%). The relationship between the changes in RDW and all-cause mortality was analyzed by categorizing the patients according to perioperative ΔRDW (RDW at postoperative one week - RDW at admission). RESULTS: The present study included a total of 9589 patients who underwent craniotomy for the treatment of brain tumors. A rise in RDW was significantly associated with increased mortality, with an adjusted OR of 3.56 (95% CI: 2.56-4.95) for 30-day mortality and 1.57 (95% CI: 1.33-1.85) for one-year mortality compared to those with non-significant RDW changes (ΔRDW ≤0.4%). Conversely, a decrease in RDW showed no significant association with 30-day mortality (adjusted OR: 1.04, 95% CI: 0.53-2.04) and one-year mortality (adjusted OR: 1.18, 95% CI: 0.92-1.53). These findings were also supported by restricted cubic spline, which shows that increases in RDW were significantly associated with lower survival rates compared to stable RDW levels during the follow-up period. CONCLUSIONS: Among patients undergoing craniotomy for a brain tumor, a rise in RDW was associated with 30-day mortality and higher long-term mortality risks, even if patients' admissions for RDW values were within the normal range. It was worth noting that maintaining stable RDW levels during this period was associated with better survival.

Association of hemoglobin drift and outcomes in patients with aneurysmal subarachnoid hemorrhage.

The relationship between in-hospital hemoglobin (Hb) drift and outcomes in patients undergoing surgical clipping for aneurysmal subarachnoid hemorrhage (aSAH) is not well studied. This study aims to investigate the association between Hb drift and mortality in this patient population. We conducted a cohort study encompassing adult patients diagnosed with aSAH who were admitted to a university hospital. These patients were stratified into distinct groups based on their Hb drift levels. We employed logistic and Cox proportional hazard models to assess the relationship between Hb drift and outcomes. Additionally, propensity score matching (PSM) was utilized to ensure comparability between patient groups. The discriminative performance of different models was evaluated using C-statistics, integrated discrimination improvement (IDI), and net reclassification improvement (NRI). Overall, our cohort comprised 671 patients, of whom 165 (24.6%) demonstrated an in-hospital Hb drift exceeding 25%. The analyses revealed elevated Hb drift was independently associated with higher likelihood of follow-up mortality (aOR: 3.29, 95% CI: 1.65 to 6.56; P = 0.001) and in-hospital mortality (aOR: 3.44, 95% CI: 1.55 to 7.63; P = 0.002). PSM analysis yielded similar results. Additionally, patients with Hb drift exhibited a notable decrease in survival rate compared to those without Hb drift (aHR: 3.99, 95% CI 2.30 to 6.70; P < 0.001). Furthermore, the inclusion of Hb drift significantly improved the C-statistic (P = 0.037), IDI (2.78%; P = 0.004) and NRI metrics (41.86%; P < 0.001) for mortality prediction. In summary, our results highlight that an in-hospital Hb drift exceeding 25% serves as an independent predictor of mortality in patients who have undergone surgical clipping for aSAH.

Electrically Induced Crystal Field Distortion in a Ferroelectric Perovskite Revealed by Electron Paramagnetic Resonance.

The magnetoelectric material has attracted multidisciplinary interest in the past decade for its potential to accommodate various functions. Especially, the external electric field can drive the quantum behaviors of such materials via the spin-electric coupling effect, with the advantages of high spatial resolution and low energy cost. In this work, the spin-electric coupling effect of Mn2+-doped ferroelectric organic-inorganic hybrid perovskite [(CH3)3NCH2Cl]CdCl3 with a large piezoelectric effect was investigated. The electric field manipulation efficiency for the allowed transitions was determined by the pulsed electron paramagnetic resonance. The orientation-included Hamiltonian of the spin-electric coupling effect was obtained via simulating the angle-dependent electric field modulated continuous-wave electron paramagnetic resonance. The results demonstrate that the applied electric field affects not only the principal values of the zero-field splitting tensor but also its principal axis directions. This work proposes and exemplifies a route to understand the spin-electric coupling effect originating from the crystal field imposed on a spin ion being modified by the applied electric field, which may guide the rational screening and designing of hybrid perovskite ferroelectrics that satisfy the efficiency requirement of electric field manipulation of spins in quantum information applications.

A Novel Machine Learning Model for Predicting Stroke-Associated Pneumonia After Spontaneous Intracerebral Hemorrhage.

BACKGROUND: Pneumonia is one of the most common complications after spontaneous intracerebral hemorrhage (sICH), i.e., stroke-associated pneumonia (SAP). Timely identification of targeted patients is beneficial to reduce poor prognosis. So far, there is no consensus on SAP prediction, and application of existing predictors is limited. The aim of this study was to develop a machine learning model to predict SAP after sICH. METHODS: We retrospectively reviewed 748 patients diagnosed with sICH and collected data from 4 dimensions-demographic features, clinical features, medical history, and laboratory tests. Five machine learning algorithms-logistic regression, gradient boosting decision tree, random forest, extreme gradient boosting, and category boosting-were used to build and validate the predictive model. We also applied recursive feature elimination with cross-validation to obtain the best feature combination for each model. Predictive performance was evaluated by area under the receiver operating characteristic curve. RESULTS: SAP was diagnosed in 237 patients. The model developed by category boosting yielded the most satisfactory outcomes overall with area under the receiver operating characteristic curves in the training set and test set of 0.8307 and 0.8178, respectively. CONCLUSIONS: The incidence of SAP after sICH in our center was 31.68%. Machine learning could potentially provide assistance in the prediction of SAP after sICH.

Deep learning framework for comprehensive molecular and prognostic stratifications of triple-negative breast cancer.

Triple-negative breast cancer (TNBC) is the most challenging breast cancer subtype. Molecular stratification and target therapy bring clinical benefit for TNBC patients, but it is difficult to implement comprehensive molecular testing in clinical practice. Here, using our multi-omics TNBC cohort (N = 425), a deep learning-based framework was devised and validated for comprehensive predictions of molecular features, subtypes and prognosis from pathological whole slide images. The framework first incorporated a neural network to decompose the tissue on WSIs, followed by a second one which was trained based on certain tissue types for predicting different targets. Multi-omics molecular features were analyzed including somatic mutations, copy number alterations, germline mutations, biological pathway activities, metabolomics features and immunotherapy biomarkers. It was shown that the molecular features with therapeutic implications can be predicted including the somatic PIK3CA mutation, germline BRCA2 mutation and PD-L1 protein expression (area under the curve [AUC]: 0.78, 0.79 and 0.74 respectively). The molecular subtypes of TNBC can be identified (AUC: 0.84, 0.85, 0.93 and 0.73 for the basal-like immune-suppressed, immunomodulatory, luminal androgen receptor, and mesenchymal-like subtypes respectively) and their distinctive morphological patterns were revealed, which provided novel insights into the heterogeneity of TNBC. A neural network integrating image features and clinical covariates stratified patients into groups with different survival outcomes (log-rank P < 0.001). Our prediction framework and neural network models were externally validated on the TNBC cases from TCGA (N = 143) and appeared robust to the changes in patient population. For potential clinical translation, we built a novel online platform, where we modularized and deployed our framework along with the validated models. It can realize real-time one-stop prediction for new cases. In summary, using only pathological WSIs, our proposed framework can enable comprehensive stratifications of TNBC patients and provide valuable information for therapeutic decision-making. It had the potential to be clinically implemented and promote the personalized management of TNBC.

Single-Cell Transcriptomics Revealed White Matter Repair Following Subarachnoid Hemorrhage.

Existing research indicates the potential for white matter injury repair during the subacute phase following subarachnoid hemorrhage (SAH). However, elucidating the role of brain cell subpopulations in the acute and subacute phases of SAH pathogenesis remains challenging due to the cellular heterogeneity of the central nervous system. In this study, single-cell RNA sequencing was conducted on SAH model mice to delineate distinct cell populations. Gene Set Enrichment Analysis was performed to identify involved pathways, and cellular interactions were explored using the CellChat package in R software. Validation of the findings involved a comprehensive approach, including magnetic resonance imaging, immunofluorescence double staining, and Western blot analyses. This study identified ten major brain clusters with cell type-specific gene expression patterns. Notably, we observed infiltration and clonal expansion of reparative microglia in white matter-enriched regions during the subacute stage after SAH. Additionally, microglia-associated pleiotrophin (PTN) was identified as having a role in mediating the regulation of oligodendrocyte precursor cells (OPCs) in SAH model mice, implicating the activation of the mTOR signaling pathway. These findings emphasize the vital role of microglia-OPC interactions might occur via the PTN pathway, potentially contributing to white matter repair during the subacute phase after SAH. Our analysis revealed precise transcriptional changes in the acute and subacute phases after SAH, offering insights into the mechanism of SAH and for the development of drugs that target-specific cell subtypes.

Development and Validation of a Supplementary Grading Scale for Outcomes of Brainstem Cavernous Malformations.

BACKGROUND: Surgical risk assessment is intriguing for clinical decision-making of brainstem cavernous malformation (BSCM) treatment. While the BSCM grading scale, encompassing size, developmental venous anomaly, crossing axial midpoint, age, and timing of intervention, is increasingly utilized, the clinical relevance of neurological fluctuation and recurrent hemorrhage has not been incorporated. This study aimed to propose a supplementary grading scale with enhanced predictive efficacy. METHODS: Using a retrospective nationwide registry of consecutive patients with BSCMs undergoing surgery in China from March 2011 to May 2023, a new supplementary BSCM grading scale was developed from a derivative cohort of 260 patients and validated in an independent concurrent cohort of 67 patients. The primary outcome was unfavorable neurological function (modified Rankin Scale score >2) at the latest follow-up. The performance of the supplementary grading system was evaluated for discrimination, calibration, and clinical utility and further compared with its original counterpart. RESULTS: Over a follow-up of at least 6 months after surgery, the unfavorable outcomes were 31% in the overall cohort (101/327 patients). A preoperative motor deficit (odds ratio, 3.13; P=0.001), recurrent hemorrhage (odds ratio, 3.05; P<0.001), timing of intervention (odds ratio, 7.08; P<0.001), and crossing the axial midpoint (odds ratio, 2.57; P=0.006) were associated with the unfavorable outcomes and composed the initial Huashan grading variables. A supplementary BSCM grading system was subsequently developed by incorporating the Huashan grading variables into the original BSCM grading scale. The predictive capability of the supplementary scale was consistently superior to the original counterpart in either the derivative cohort (area under the receiver operating characteristic curve, 0.74 [95% CI, 0.68-0.80] for the supplementary versus 0.68 [95% CI, 0.61-0.74] for the original) or the validation cohort (0.75 [95% CI, 0.62-0.87] versus 0.64 [95% CI, 0.48-0.81]). CONCLUSIONS: This study highlights the neurological relevance of BSCM hemorrhage in surgical risk assessment. Via compositing preoperative motor function and recurrent hemorrhages, a supplementary grading scale may improve a dynamic risk assessment for clinical decisions in the management of BSCMs.

Potential Biomarkers in Cerebrospinal Fluid and Plasma for Dementia.

Background: The identification of biomarkers for different dementias in plasma and cerebrospinal fluid (CSF) has made substantial progress. However, they are observational studies, and there remains a lack of research on dementias with low incidence rates. Objective: We performed a comprehensive Mendelian randomization to identify potential biomarkers for different dementia type. Methods: The summary-level datasets encompassed 734 plasma and 154 cerebrospinal fluid proteins sourced from recently published genome-wide association studies (GWAS). Summary statistics for different dementias, including any dementia (refering to any type of dementia symptoms, 218,792 samples), Alzheimer's disease (AD, 63,926 samples), vascular dementia (212,389 samples), frontotemporal dementia (3,024 samples), dementia with Lewy bodies (DLB, 6,618 samples), and dementia in Parkinson's disease (216,895 samples), were collected from large GWAS. The primary method is inverse variance weighting, with additional sensitivity analyses conducted to ensure the robustness of the findings. Results: The molecules released into CSF, namely APOE2 for any dementia, APOE2 and Siglec-3 for AD, APOE2 for vascular dementia, and APOE2 for DLB, might be potential biomarkers. CD33 for AD and SNCA for DLB in plasma could be promising biomarkers. Conclusions: This is the first study to integrate plasma and CSF proteins to identify potential biomarkers for different dementias.

Interactive effects of Composite Dietary Antioxidant Index with Body Mass Index for the risk of stroke among U.S. adults: insight from NHANES 2001-2018.

Background: This cross-sectional study aims to explore the interactive effects of the Composite Dietary Antioxidant Index (CDAI) and Body Mass Index (BMI) on stroke risk among U.S. adults, utilizing data from the National Health and Nutrition Examination Survey (NHANES) conducted between 2001 and 2018. Methods: The analysis involved 42,042 participants from a representative sample of non-institutionalized U.S. civilians, selected through a stratified, multistage probability sampling method. Dietary intake data were collected over two 24-h periods using the Automated Multiple-Pass Method. The study calculated a modified CDAI to assess dietary antioxidant intake, excluding supplements and water sources. Statistical methods included multivariable logistic regression and Generalized Additive Models (GAM) to evaluate the interaction between CDAI scores and BMI in relation to stroke risk, adjusting for a wide range of demographic, lifestyle, and health covariates. Results: The research identified a significant interaction between CDAI scores and BMI categories in stroke risk assessment. While a negative correlation was observed between CDAI scores and stroke risk across the total population (OR 0.97, 95% CI 0.96-0.99), this relationship varied notably across different BMI groups. In participants with a BMI ≥25, a statistically significant negative association persisted, displaying a non-linear pattern. The study also revealed an inflection point in the CDAI score, indicating a shift in the relationship between dietary antioxidants and stroke risk. Conclusion: This study underscores the complex interaction between dietary antioxidant intake and BMI in determining stroke risk among U.S. adults. The findings suggest that individuals with higher BMI may experience more pronounced benefits from dietary antioxidants in stroke prevention. These insights could inform targeted dietary recommendations and public health strategies aimed at reducing stroke risk, particularly in populations with higher BMI. Further research is needed to fully understand these interactions and their implications for stroke prevention guidelines.

Causal association between circulating inflammatory cytokines and intracranial aneurysm and subarachnoid hemorrhage.

BACKGROUND AND PURPOSE: The causal association between inflammatory cytokines and the development of intracranial aneurysm (IA), unruptured IA (uIA) and subarachnoid hemorrhage (SAH) lacks clarity. METHODS: The summary-level datasets for inflammatory cytokines were extracted from a genome-wide association study of the Finnish Cardiovascular Risk in Young Adults Study and the FINRISK survey. The summary statistics datasets related to IA, uIA and SAH were obtained from the genome-wide association study meta-analysis of the International Stroke Genetics Consortium and FinnGen Consortium. The primary method employed for analysis was inverse variance weighting (false discovery rate), supplemented by sensitivity analyses to address pleiotropy and enhance robustness. RESULTS: In the International Stroke Genetics Consortium, 10, six and eight inflammatory cytokines exhibited a causal association with IA, uIA and SAH, respectively (false discovery rate, p < 0.05). In FinnGen datasets, macrophage Inflammatory Protein-1 Alpha (MIP_1A), MIP_1A and interferon γ-induced protein 10 (IP_10) were verified for IA, uIA and SAH, respectively. In the reverse Mendelian randomization analysis, the common cytokines altered by uIA and SAH were vascular endothelial growth factor (VEGF), MIP_1A, IL_9, IL_10 and IL_17, respectively. The meta-analysis results show that MIP_1A and IP_10 could be associated with the decreased risk of IA, and MIP_1A and IP_10 were associated with the decreased risk of uIA and SAH, respectively. Notably, the levels of VEGF, MIP_1A, IL_9, IL_10 and TNF_A were increased with uIA. Comprehensive heterogeneity and pleiotropy analyses confirmed the robustness of these results. CONCLUSION: Our study unveils a bidirectional association between inflammatory cytokines and IA, uIA and SAH. Further investigations are essential to validate their relationship and elucidate the underlying mechanisms.

Association between elevated preoperative red cell distribution width and mortality after brain tumor craniotomy.

BACKGROUND: Red cell distribution width (RDW) has been recognized as a potential inflammatory biomarker, with elevated levels associated with adverse outcomes in various diseases. However, its role in predicting outcomes after brain tumor craniotomy remains unclear. We aimed to assess whether preoperative RDW influences mortality and postoperative complications in patients undergoing brain tumor craniotomy. METHODS: This retrospective cohort study analyzed serum RDW levels in patients undergoing brain tumor craniotomy at West China Hospital. RDW was evaluated in two forms: RDW-CV and RDW-SD, and was categorized into four quartiles for analysis by using logistic regression and multivariate analysis to adjust for confounding. RESULTS: The study encompassed 10,978 patients undergoing brain tumor craniotomy. our analysis revealed no significant difference in 30-day mortality across various RDW-CV levels. However, we observed a dose-response relationship with preoperative RDW-CV levels in assessing long-term mortality risks. Specifically, patients with RDW-CV levels of 12.6-13.2% (HR 1.04, 95% CI 1.01-1.18), 13.2-13.9% (HR 1.12, 95% CI 1.04-1.26), and > 13.9% (HR 1.34, 95% CI 1.18-1.51) exhibited a significantly higher hazard of long-term mortality compared to those with RDW-CV < 12.6%. When preoperative RDW-CV was analyzed as a continuous variable, for each 10% increase in RDW-CV, the adjusted OR of long-term mortality was 1.09 (95% CI 1.05-1.13). we also observed significant associations between preoperative higher RDW-CV levels and certain postoperative complications including acute kidney injury (OR 1.46, 95% CI: 1.10-1.94), pneumonia infection (OR 1.19 95% CI: 1.05-1.36), myocardial infarction (OR 1.32, 95% CI: 1.05-1.66), readmission (OR 1.15, 95% CI: 1.01-1.30), and a prolonged length of hospital stay (OR 1.11, 95% CI: 1.02-1.21). For RDW-SD levels, there was no significant correlation for short-term mortality, long-term mortality, and postoperative complications. CONCLUSIONS: Our study showed elevated preoperative RDW-CV is significantly associated with increased long-term mortality and multiple postoperative complications, but no such association is observed with RDW-SD. These findings show the prognostic importance of RDW-CV, reinforcing its potential as a valuable tool for risk stratification in the preoperative evaluation of brain tumor craniotomy patients.

Hematocrit drift and outcomes in surgical patients with aneurysmal subarachnoid hemorrhage.

BACKGROUND: There is a paucity of conclusive evidence regarding the impact of downward drift in hematocrit levels among patients who have undergone surgical clipping for aneurysmal subarachnoid hemorrhage (aSAH). This study endeavors to explore the potential association between hematocrit drift and mortality in this specific patient population. METHODS: A cohort study was conducted, encompassing adult patients diagnosed with aSAH at a university hospital. The primary endpoint was follow-up mortality. Propensity score matching was employed to align patients based on their baseline characteristics. Discrimination capacity across various models was assessed and compared using net reclassification improvement (NRI). RESULTS: Among the 671 patients with aSAH in the study period, 118 patients (17.6%) experienced an in-hospital hematocrit drift of more than 25%. Following adjustment with multivariate regression analysis, patients with elevated hematocrit drift demonstrated significantly increased odds of mortality (aOR: 2.12, 95% CI: 1.14 to 3.97; P = 0.019). Matching analysis yielded similar results (aOR: 2.07, 95% CI: 1.05 to 4.10; P = 0.036). The inclusion of hematocrit drift significantly improved the NRI (P < 0.0001) for mortality prediction. When in-hospital hematocrit drift was served as a continuous variable, each 10% increase in hematocrit drift corresponded to an adjusted odds ratio of 1.31 (95% CI 1.08-1.61; P = 0.008) for mortality. CONCLUSIONS: In conclusion, the findings from this comprehensive cohort study indicate that a downward hematocrit drift exceeding 25% independently predicts mortality in surgical patients with aSAH. These findings underscore the significance of monitoring hematocrit and managing anemia in this patient population.

Anticoagulation therapy in non-valvular atrial fibrillation after intracerebral hemorrhage: A propensity score-matched study.

BACKGROUND: The effect of antithrombotic therapy on patients with atrial fibrillation who sustained previous intracerebral hemorrhage (ICH) remains uncertain. Data regarding antithrombotic therapy use in these patients are limited. This study aims to compare the clinical and overall outcomes of antithrombotic therapy and usual care in patients with atrial fibrillation who sustained ICH. METHODS: We assembled consecutive patients with atrial fibrillation sustaining an ICH from our institution. Multivariable regression analysis and propensity-matched analysis were applied to assess associations of different antithrombotic therapies and outcomes. The primary outcome was mortality within the longest follow-up. Kaplan-Meier curves and log-rank tests of the time-to-event data were used to assess differences in survival. RESULTS: In total, 296 consecutive patients with atrial fibrillation who survived an ICH were included in this study. Our analysis demonstrated that antithrombotic therapy was associated with reduced mortality up to a 4-year duration of follow-up (OR, 0.49, 95 % CI 0.30-0.81). Similar results were obtained from the propensity-matched analysis (OR, 0.58, 95 % CI 0.34-0.98). Subgroup analysis showed that compared with usual care, direct oral anticoagulant (DOAC) with or without antiplatelet was associated with a lower risk of long-term mortality (OR, 0.34, 95 % CI 0.17-0.69). In addition, our analysis observed a significant interaction between cardiac insufficiency and treatment effect (P = 0.04). CONCLUSIONS: In patients with atrial fibrillation who have a history of ICH, administration of antithrombotic therapy, especially DOAC, was associated with lower mortality. Future randomized trials are warranted to test the positive net clinical benefit of DOAC therapy.

Angular-resolved Rabi oscillations of orthorhombic spins in a Co(II) molecular qubit.

Magnetic molecules are promising candidates for quantum information processing (QIP) due to their tunable electron structures and quantum properties. A high spin Co(II) complex, CoH2dota, is studied for its potential to be used as a quantum bit (qubit) utilizing continuous wave (CW) and pulsed electron paramagnetic resonance (EPR) spectroscopy at low temperature. On the X-band microwave energy scale, the system can be treated as an effective spin 1/2 with a strongly anisotropic g-tensor resulting from the significant spin-orbital coupling. An experimental and theoretical study is conducted to investigate the anisotropic Rabi oscillations of the two magnetically equivalent spin centres with different orientations in a single crystal sample, which aims to verify the relationship between the Rabi frequency and the orientation of the g-tensor. The findings of this study show that an effective quantum manipulation method is developed for orthorhombic spin systems.

Intranasal Delivery of Curcumin Nanoparticles Improves Neuroinflammation and Neurological Deficits in Mice with Intracerebral Hemorrhage.

Intracerebral hemorrhage (ICH) represents one of the most severe subtypes of stroke. Due to the complexity of the brain injury mechanisms following ICH, there are currently no effective treatments to significantly improve patient functional outcomes. Curcumin, as a potential therapeutic agent for ICH, is limited by its poor water solubility and oral bioavailability. In this study, mPEG-PCL is used to encapsulate curcumin, forming curcumin nanoparticles, and utilized the intranasal administration route to directly deliver curcumin nanoparticles from the nasal cavity to the brain. By inhibiting pro-inflammatory neuroinflammation of microglia following ICH in mice, reprogramming pro-inflammatory microglia toward an anti-inflammatory function, and consequently reducing neuronal inflammatory death and hematoma volume, this approach improved blood-brain barrier damage in ICH mice and promoted the recovery of neurological function post-stroke. This study offers a promising therapeutic strategy for ICH to mediate neuroinflammatory microenvironments.

Association of persistent postoperative hyperglycemia with mortality after elective craniotomy.

OBJECTIVE: The influence of persistent postoperative hyperglycemia after craniotomy has not yet been explored. This study aimed to investigate the hypothesis that persistent postoperative hyperglycemia is associated with mortality in patients undergoing an elective craniotomy. METHODS: This study included adult patients (age ≥ 18 years) undergoing an elective craniotomy between January 2011 and March 2021 at the West China Hospital, Sichuan University. Peak daily blood glucose values measured within the first 7 days after craniotomy were collected. Persistent hyperglycemia was defined by two or more consecutive serum glucose levels of mild, moderate, or severe hyperglycemia. Normoglycemia, mild hyperglycemia, moderate hyperglycemia, and severe hyperglycemia were defined as glucose values of ≤ 6.1 mmol/L, > 6.1 and ≤ 7.8 mmol/L, > 7.8 and ≤ 10.0 mmol/L, and > 10.0 mmol/L, respectively. RESULTS: This study included 14,907 patients undergoing an elective craniotomy. In the multivariable analysis, both moderate (adjusted OR 3.76, 95% CI 2.68-5.27) and severe (adjusted OR 3.82, 95% CI 2.54-5.76) persistent hyperglycemia in patients were associated with higher 30-day mortality compared with normoglycemia. However, this association was not observed in patients with mild hyperglycemia (adjusted OR 1.32, 95% CI 0.93-1.88). Interestingly, this association was observed regardless of whether patients had preoperative hyperglycemia. There was no interaction between moderate or severe hyperglycemia and preexisting diabetes (p for interaction = 0.65). When postoperative peak blood glucose values within the first 7 days after craniotomy were evaluated as a continuous variable, for each 1-mmol/L increase in blood glucose, the adjusted OR of 30-day mortality was 1.17 (95% CI 1.14-1.21). Postoperative blood glucose (area under the curve [AUC] = 0.78) was superior to preoperative blood glucose (AUC = 0.65; p < 0.001) for predicting mortality. Moderate and severe persistent hyperglycemia in patients were associated with an increased risk of deep venous thrombosis (adjusted OR 3.20, 95% CI 2.31-4.42), pneumonia (adjusted OR 2.77, 95% CI 2.40-3.21), myocardial infarction (adjusted OR 4.38, 95% CI 3.41-5.61), and prolonged hospital stays (adjusted OR 1.43, 95% CI 1.29-1.59). CONCLUSIONS: In patients undergoing an elective craniotomy, moderate and severe persistent postoperative hyperglycemia were associated with an increased risk of mortality compared with normoglycemia, regardless of preoperative hyperglycemia.

Walking forward or on hold: Could the ChatGPT be applied for seeking health information in neurosurgical settings?

Self-management is important for patients suffering from cerebrovascular events after neurosurgical procedures. An increasing number of artificial intelligence (AI)-assisted tools have been used in postoperative health management. ChatGPT is a new trend dialog-based chatbot that could be used as a supplemental tool for seeking health information. Responses from ChatGPT version 3.5 and 4.0 toward 13 questions raised by experienced neurosurgeons were evaluated in this exploratory study for their consistency and appropriateness blindly by the other three neurosurgeons. The readability of response text was investigated quantitively by word count and the Gunning Fog and Flesch-Kincaid indices. Results showed that the chatbot could provide relatively stable output between the two versions on consistency and appropriateness (χ² = 0.348). As for readability, there was a higher demand for readers to comprehend the output text in the 4.0 version (more counts of words; lower Flesch-Kincaid reading ease score; and higher Flesch-Kincaid grade level). In general, the capacity of ChatGPT to deliver effective health information is still under debate.

Mesenchymal stem cell-derived exosomes as a new drug carrier for the treatment of spinal cord injury: A review.

Spinal cord injury (SCI) is a devastating traumatic disease seriously impairing the quality of life in patients. Expectations to allow the hopeless central nervous system to repair itself after injury are unfeasible. Developing new approaches to regenerate the central nervous system is still the priority. Exosomes derived from mesenchymal stem cells (MSC-Exo) have been proven to robustly quench the inflammatory response or oxidative stress and curb neuronal apoptosis and autophagy following SCI, which are the key processes to rescue damaged spinal cord neurons and restore their functions. Nonetheless, MSC-Exo in SCI received scant attention. In this review, we reviewed our previous work and other studies to summarize the roles of MSC-Exo in SCI and its underlying mechanisms. Furthermore, we also focus on the application of exosomes as drug carrier in SCI. In particular, it combs the advantages of exosomes as a drug carrier for SCI, imaging advantages, drug types, loading methods, etc., which provides the latest progress for exosomes in the treatment of SCI, especially drug carrier.