Distinct virtual histology of grey matter atrophy in four neuroinflammatory diseases.

Gray matter (GM) atrophies were observed in multiple sclerosis, neuromyelitis optica spectrum disorders (both anti-aquaporin-4 antibody-positive [AQP4+], and -negative [AQP4-] subtypes NMOSD), and myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD). Revealing the pathogenesis of brain atrophy in these disorders would help their differential diagnosis and guide therapeutic strategies. To determine the neurobiological underpinnings of GM atrophies in multiple sclerosis, AQP4+ NMOSD, AQP4- NMOSD, and MOGAD, we conducted a virtual histology analysis that links T1-weighted image derived GM atrophy and gene expression using a multicenter cohort of 324 patients with multiple sclerosis, 197 patients with AQP4+ NMOSD, 75 patients with AQP4- NMOSD, 47 patients with MOGAD, and 2,169 healthy controls (HCs). First, interregional GM atrophy profiles across the cortical and subcortical regions were determined by Cohen's d between patients with multiple sclerosis, AQP4+ NMOSD, AQP4- NMOSD, MOGAD and HCs. Then, the GM atrophy profiles were spatially correlated with the gene expressions extracted from the Allen Human Brain Atlas, respectively. Finally, we explored the virtual histology of clinical feature relevant GM atrophy by subgroup analysis that stratified by physical disability, disease duration, number of relapses, lesion burden, and cognitive function. Multiple sclerosis showed severe widespread GM atrophy pattern, mainly involving subcortical nuclei and brainstem. AQP4+ NMOSD showed obvious widespread GM atrophy pattern, predominately located in occipital cortex as well as cerebellum. AQP4- NMOSD showed mild widespread GM atrophy pattern, mainly located in frontal and parietal cortices. MOGAD showed GM atrophy mainly involving the frontal and temporal cortices. High expression of genes specific to microglia, astrocytes, oligodendrocytes, and endothelial cells in multiple sclerosis, S1 pyramidal cells in AQP4+ NMOSD, as well as S1 and CA1 pyramidal cells in MOGAD had spatial correlations with GM atrophy profiles were observed, while no atrophy profile related gene expression was found in AQP4- NMOSD. Virtual histology of clinical feature relevant GM atrophy mainly pointed to the shared neuronal and endothelial cells among the four neuroinflammatory diseases. The unique underlying virtual histology patterns were microglia, astrocytes, and oligodendrocytes for multiple sclerosis; astrocytes for AQP4+ NMOSD; and oligodendrocytes for MOGAD. Neuronal and endothelial cells were shared potential targets across these neuroinflammatory diseases. These findings might help their differential diagnosis and optimal therapeutic strategies.

Clinical features and 1-year outcomes of variable obstruction in participants with preserved spirometry: results from the ECOPD study in China.

BACKGROUND: There are limited data on the clinical features and longitudinal prognosis of variable obstruction, particularly among never smokers and different variable obstruction types. Therefore, we aimed to evaluate the clinical characteristics of the participants with variable obstruction and determine the relationship between variable obstruction and the development of chronic obstructive pulmonary disease (COPD) and the decline of lung function in a community-dwelling study of Chinese, especially among never smokers and different variable obstruction subtypes. METHODS: Participants with preserved spirometry (postbronchodilator forced expiratory volume in 1 s (FEV1)/forced vital capacity (FVC) ≥0.70) at baseline from the Early COPD cohort were included in our analysis. Participants with variable obstruction (prebronchodilator FEV1/FVC <0.70) were compared with those without variable obstruction (prebronchodilator FEV1/FVC ≥0.70). We performed subgroup analyses in never smokers, former and current smokers, and different variable obstruction types (postbronchodilator FVC

Tumor and Peritoneum-Associated Macrophage Gene Signature as a Novel Molecular Biomarker in Gastric Cancer.

A spectrum of immune states resulting from tumor resident macrophages and T-lymphocytes in the solid tumor microenvironment correlates with patient outcomes. We hypothesized that in gastric cancer (GC), macrophages in a polarized immunosuppressive transcriptional state would be prognostic of poor survival. We derived transcriptomic signatures for M2 (M2TS, MRC1; MS4A4A; CD36; CCL13; CCL18; CCL23; SLC38A6; FGL2; FN1; MAF) and M1 (M1TS, CCR7; IL2RA; CXCL11; CCL19; CXCL10; PLA1A; PTX3) macrophages, and cytolytic T-lymphocytes (CTLTS, GZMA; GZMB; GZMH; GZMM; PRF1). Primary GC in a TCGA stomach cancer dataset was evaluated for signature expressions, and a log-rank test determined overall survival (OS) and the disease-free interval (DFI). In 341 TCGA GC entries, high M2TS expression was associated with histological types and later stages. Low M2TS expression was associated with significantly better 5-year OS and DFI. We validated M2TS in prospectively collected peritoneal fluid of a GC patient cohort (n = 28). Single-cell RNA sequencing was used for signature expression in CD68+CD163+ cells and the log-rank test compared OS. GC patients with high M2TS in CD68+CD163+ cells in their peritoneal fluid had significantly worse OS than those with low expression. Multivariate analyses confirmed M2TS was significantly and independently associated with survival. As an independent predictor of poor survival, M2TS may be prognostic in primary tumors and peritoneal fluid of GC patients.

Spinal cord and brain atrophy patterns in neuromyelitis optica spectrum disorder and multiple sclerosis.

BACKGROUND: Spinal cord and brain atrophy are common in neuromyelitis optica spectrum disorder (NMOSD) and relapsing-remitting multiple sclerosis (RRMS) but harbor distinct patterns accounting for disability and cognitive impairment. METHODS: This study included 209 NMOSD and 304 RRMS patients and 436 healthy controls. Non-negative matrix factorization was used to parse differences in spinal cord and brain atrophy at subject level into distinct patterns based on structural MRI. The weights of patterns were obtained using a linear regression model and associated with Expanded Disability Status Scale (EDSS) and cognitive scores. Additionally, patients were divided into cognitive impairment (CI) and cognitive preservation (CP) groups. RESULTS: Three patterns were observed in NMOSD: (1) Spinal Cord-Deep Grey Matter (SC-DGM) pattern was associated with high EDSS scores and decline of visuospatial memory function; (2) Frontal-Temporal pattern was associated with decline of language learning function; and (3) Cerebellum-Brainstem pattern had no observed association. Patients with CI had higher weights of SC-DGM pattern than CP group. Three patterns were observed in RRMS: (1) DGM pattern was associated with high EDSS scores, decreased information processing speed, and decreased language learning and visuospatial memory functions; (2) Frontal-Temporal pattern was associated with overall cognitive decline; and (3) Occipital pattern had no observed association. Patients with CI trended to have higher weights of DGM and Frontal-Temporal patterns than CP group. CONCLUSION: This study estimated the heterogeneity of spinal cord and brain atrophy patterns in NMOSD and RRMS patients at individual level, and evaluated the clinical relevance of these patterns, which may contribute to stratifying participants for targeted therapy.

Real-world experience of teriflunomide in relapsing multiple sclerosis: paramagnetic rim lesions may play a role.

Objectives: The aims of this study were to report the effectiveness and safety of teriflunomide in Chinese patients with relapsing-remitting multiple sclerosis (RRMS) and to explore the association of paramagnetic rim lesion (PRL) burden with patient outcome in the context of teriflunomide treatment and the impact of teriflunomide on PRL burden. Methods: This is a prospective observational study. A total of 100 RRMS patients treated with teriflunomide ≥3 months were included in analyzing drug persistence and safety. Among them, 96 patients treated ≥6 months were included in assessing drug effectiveness in aspects of no evidence of disease activity (NEDA) 3. The number and total volume of PRL were calculated in 76 patients with baseline susceptibility-weighted imaging (SWI), and their association with NEDA3 failure during teriflunomide treatment was investigated. Results: Over a treatment period of 19.7 (3.1-51.7) months, teriflunomide reduced annualized relapse rate (ARR) from 1.1 ± 0.8 to 0.3 ± 0.5, and Expanded Disability Status Scale (EDSS) scores remained stable. At month 24, the NEDA3% and drug persistence rate were 43.8% and 65.1%, respectively. In patients with a baseline SWI, 81.6% had at least 1 PRL, and 42.1% had ≥4 PRLs. The total volume of PRL per patient was 0.3 (0.0-11.5) mL, accounting for 2.3% (0.0%-49.0%) of the total T2 lesion volume. Baseline PRL number ≥ 4 (OR = 4.24, p = 0.009), younger onset age (OR = 0.94, p = 0.039), and frequent relapses in initial 2 years of disease (OR = 13.40, p = 0.026) were associated with NEDA3 failure. The PRL number and volume were not reduced (p = 0.343 and 0.051) after teriflunomide treatment for more than 24 months. No new safety concerns were identified in this study. Conclusion: Teriflunomide is effective in reducing ARR in Chinese patients with RRMS. Patients with less PRL burden, less frequent relapses, and relatively older age are likely to benefit more from teriflunomide, indicating that PRL might be a valuable measurement to inform clinical treatment decision.

Prediction of intraoperative red blood cell transfusion in valve replacement surgery: machine learning algorithm development based on non-anemic cohort.

Background: Our study aimed to develop machine learning algorithms capable of predicting red blood cell (RBC) transfusion during valve replacement surgery based on a preoperative dataset of the non-anemic cohort. Methods: A total of 423 patients who underwent valvular replacement surgery from January 2015 to December 2020 were enrolled. A comprehensive database that incorporated demographic characteristics, clinical conditions, and results of preoperative biochemistry tests was used for establishing the models. A range of machine learning algorithms were employed, including decision tree, random forest, extreme gradient boosting (XGBoost), categorical boosting (CatBoost), support vector classifier and logistic regression (LR). Subsequently, the area under the receiver operating characteristic curve (AUC), accuracy, recall, precision, and F1 score were used to determine the predictive capability of the algorithms. Furthermore, we utilized SHapley Additive exPlanation (SHAP) values to explain the optimal prediction model. Results: The enrolled patients were randomly divided into training set and testing set according to the 8:2 ratio. There were 16 important features identified by Sequential Backward Selection for model establishment. The top 5 most influential features in the RF importance matrix plot were hematocrit, hemoglobin, ALT, fibrinogen, and ferritin. The optimal prediction model was CatBoost algorithm, exhibiting the highest AUC (0.752, 95% CI: 0.662-0.780), which also got relatively high F1 score (0.695). The CatBoost algorithm also showed superior performance over the LR model with the AUC (0.666, 95% CI: 0.534-0.697). The SHAP summary plot and the SHAP dependence plot were used to visually illustrate the positive or negative effects of the selected features attributed to the CatBoost model. Conclusions: This study established a series of prediction models to enhance risk assessment of intraoperative RBC transfusion during valve replacement in no-anemic patients. The identified important predictors may provide effective preoperative interventions.

The thalamic covariance network is associated with cognitive deficits in patients with cerebral small vascular disease.

OBJECTIVE: Abnormalities in the gray matter structure of cerebral small vessel disease (CSVD) have been observed throughout the brain. However, whether cortico-cortical connections exist between regions of gray matter atrophy in patients with CSVD has not been fully elucidated. This question was tested by comparing the gray matter covariance networks in CSVD patients with and without cognitive impairment (CI). METHODS: We performed multivariate modeling of the gray matter volume measurements of 61 patients with CI (CSVD-CI), 85 patients without CI (CSVD-NC), and 108 healthy controls using source-based morphological analysis (SBM) to obtain gray matter structural covariance networks at the population level. Then, correlations between structural covariance networks and cognitive functions were analyzed in CSVD patients. Finally, a support vector machine (SVM) classifier was used with the gray matter covariance network as a classification feature to identify CI among the CSVD population. RESULTS: The results of the analysis of all the subjects showed that compared with healthy controls, the expression of the thalamic covariance network, cerebellum covariance network, and calcarine cortex covariance network was reduced in patients with CSVD. Moreover, CSVD-CI patients showed a significant reduction in the expression of the thalamic covariance network, encompassing the thalamus and the parahippocampal gyrus, relative to CSVD-NC patients, which persisted after excluding CSVD patients with thalamic lacunes. In patients with CSVD, cognitive functions were positively correlated with measures of the thalamic covariance network. More than 80% of CSVD patients with CI were correctly identified by the SVM classifier. INTERPRETATION: Our findings provide new evidence to explain the distribution state of gray matter reduction in CSVD patients, and the thalamic covariance network is the core region for early gray matter reduction during the development of CSVD disease, which is related to cognitive deficits. Reduced expression of thalamic covariance networks may provide a neuroimaging biomarker for the early identification of cognitive impairment in CSVD patients.

Study on the Effect of Laser Marker in the Treatment of Osteoarthritis of the Knee Joint and the Accuracy of Reconstruction of Lower Extremity Alignment.

Objective: Knee osteoarthritis (KOA) is a prevalent joint disease characterized by cartilage degradation and periarticular bone hyperplasia. Accurate assessment of knee alignment is fundamental for effective treatment, as it directly influences surgical planning and postoperative outcomes. This study assesses the effectiveness of laser marker technology in KOA treatment and its precision in reconstructing lower extremity alignment. Methods: Sixty KOA patients admitted to our orthopedics department from March 2020 to December 2021 were randomized into two groups via random number table method, with 30 patients in each. All patients underwent knee replacement surgery. The experiment group received laser marker assessments, while the control group had X-ray examinations. Postoperative Hospital for Special Surgery (HSS) scores and knee mobility of the patients were compared. Results: At 6 weeks, 3 months, and 6 months postoperatively, the experimental group exhibited significnatly higher HSS scores (89.75±3.81, 91.78±2.15, and 91.84±1.79) than the control group (84.28±2.56, 87.15±1.98, and 88.02±1.21) (P < .05). Better knee mobility (111.17±4.94) was observed in the experimental group versus the control group (108.07±3.08) at 6 months postoperatively (P < .05). Conclusion: Laser marker technology provides a clear visualization of lower extremity structures, offering a comprehensive assessment of KOA deformities. This could potentially lead to improved diagnostic precision and enhanced surgical outcomes. The study encourages further research into the broader application of laser marker technology in knee osteoarthritis treatment, such as the evaluation of its cost-effectiveness versus traditional methods.

Gut microbiota profiling in obese children from Southeastern China.

Childhood obesity not only has a negative impact on a child's health but is also a significant risk factor for adult obesity and related metabolic disorders, making it a major global public health concern. Recent studies have revealed the crucial role of gut microbiota in the occurrence and development of obesity, in addition to genetic and lifestyle factors. In this study, we recruited 19 normal-weight children and 47 children with varying degrees of obesity. A questionnaire survey was conducted to inquire about the family background, lifestyle habits and dietary composition of the 66 children. Findings indicate that fathers of obese children tend to be obese themselves, while children with highly educated mothers are more likely to maintain a normal weight. Furthermore, overweight children tend to spend more time on electronic devices and less time on physical activities compared to their normal-weight counterparts. Obese children exhibit significant differences in breakfast and dinner dietary composition when compared to children with normal weight. Additionally, the gut microbiota of these 66 children was analyzed using 16S rRNA sequencing. Analysis of gut microbiota composition showed similar compositions among children with varying degrees of obesity, but significant differences were observed in comparison to normal-weight children. Obese children exhibited a reduced proportion of Bacteroidota and an increased proportion of Firmicutes, resulting in an elevated Firmicutes/Bacteroidota ratio. Moreover, Actinobacteriota were found to be increased in the gut microbiota of children with varying degrees of obesity. PICRUSt analysis indicated significant metabolic differences in the microbiota functions between obese and normal-weight children, suggesting the composition of gut microbiota could be a crucial factor contributing to obesity. These findings provide valuable insights for the treatment of childhood obesity.

Association of non-obstructive dyspnoea with all-cause mortality and incident chronic obstructive pulmonary disease: a systematic literature review and meta-analysis.

BACKGROUND: Controversy exists regarding the association between non-obstructive dyspnoea and the future development of chronic obstructive pulmonary disease (COPD) and mortality. Therefore, we aimed to evaluate the association of non-obstructive dyspnoea with mortality and incident COPD in adults. METHODS: We searched PubMed, Embase, and Web of Science to identify studies published from inception to 13 May 2023. Eligibility screening, data extraction, and quality assessment of the retrieved articles were conducted independently by two reviewers. Studies were included if they were original articles comparing incident COPD and all-cause mortality between individuals with normal lung function with and without dyspnoea. The primary outcomes were incident COPD and all-cause mortality. The secondary outcome was respiratory disease-related mortality. We used the random-effects model to calculate pooled estimates and corresponding 95% confidence interval (CI). Heterogeneity was determined using the I² statistic. RESULTS: Of 6486 studies, 8 studies involving 100 758 individuals fulfilled the inclusion and exclusion criteria and were included in the study. Compared with individuals without non-obstructive dyspnoea, individuals with non-obstructive dyspnoea had an increased risk of incident COPD (relative risk: 1.41, 95% CI: 1.08 to 1.83), and moderate heterogeneity was found (p=0.079, I2=52.2%). Individuals with non-obstructive dyspnoea had a higher risk of all-cause mortality (hazard ratio: 1.21, 95% CI: 1.14 to 1.28, I2=0.0%) and respiratory disease-related mortality (hazard ratio: 1.52, 95% CI: 1.14 to 2.02, I2=0.0%) than those without. CONCLUSIONS: Individuals with non-obstructive dyspnoea are at a higher risk of incident COPD and all-cause mortality than individuals without dyspnoea. Further research should investigate whether these high-risk adults may benefit from risk management and early therapeutic intervention. PROSPERO REGISTRATION NUMBER: CRD42023395192.

Association of mild chronic obstructive pulmonary disease with all-cause mortality: A systematic review and meta-analysis.

BACKGROUND: It is unclear whether patients with Global Initiative for Chronic Obstructive Lung Disease stage 1 (mild) chronic obstructive pulmonary disease (COPD) have worse respiratory outcomes than individuals with normal spirometry. METHODS: For this systematic review and meta-analysis, we conducted a search of PubMed, Embase, and Web of Science for all literature published up to 1 March 2023. Studies comparing mortality between mild COPD and normal spirometry were included. A random-effects model was used to estimate the combined effect size and its 95% confidence interval (CI). The primary outcome was all-cause mortality. Respiratory disease-related mortality were examined as secondary outcomes. RESULTS: Of 5242 titles identified, 12 publications were included. Patients with mild COPD had a higher risk of all-cause mortality than individuals with normal spirometry (pre-bronchodilator: hazard ratio [HR] = 1.21, 95% CI: 1.11-1.32, I2 = 47.1%; post-bronchodilator: HR = 1.19, 95% CI: 1.02-1.39, I2 = 0.0%). Funnel plots showed a symmetrical distribution of studies and did not suggest publication bias. In jackknife sensitivity analyses, the increased risk of all-cause mortality remained consistent for mild COPD. When the meta-analysis was repeated and one study was omitted each time, the HR and corresponding 95% CI were >1. Patients with mild COPD also had a higher risk of respiratory disease-related mortality (HR = 1.71, 95% CI: 1.03-2.82, I2 = 0.0%). CONCLUSIONS: Our results suggest that mild COPD is associated with increased all-cause mortality and respiratory disease-related mortality compared with normal spirometry. Further research is required to determine whether early intervention and treatment are beneficial in mild COPD.

Interobserver Agreement in Automatic Segmentation Annotation of Prostate Magnetic Resonance Imaging.

We aimed to compare the performance and interobserver agreement of radiologists manually segmenting images or those assisted by automatic segmentation. We further aimed to reduce interobserver variability and improve the consistency of radiomics features. This retrospective study included 327 patients diagnosed with prostate cancer from September 2016 to June 2018; images from 228 patients were used for automatic segmentation construction, and images from the remaining 99 were used for testing. First, four radiologists with varying experience levels retrospectively segmented 99 axial prostate images manually using T2-weighted fat-suppressed magnetic resonance imaging. Automatic segmentation was performed after 2 weeks. The Pyradiomics software package v3.1.0 was used to extract the texture features. The Dice coefficient and intraclass correlation coefficient (ICC) were used to evaluate segmentation performance and the interobserver consistency of prostate radiomics. The Wilcoxon rank sum test was used to compare the paired samples, with the significance level set at p < 0.05. The Dice coefficient was used to accurately measure the spatial overlap of manually delineated images. In all the 99 prostate segmentation result columns, the manual and automatic segmentation results of the senior group were significantly better than those of the junior group (p < 0.05). Automatic segmentation was more consistent than manual segmentation (p < 0.05), and the average ICC reached >0.85. The automatic segmentation annotation performance of junior radiologists was similar to that of senior radiologists performing manual segmentation. The ICC of radiomics features increased to excellent consistency (0.925 [0.888~0.950]). Automatic segmentation annotation provided better results than manual segmentation by radiologists. Our findings indicate that automatic segmentation annotation helps reduce variability in the perception and interpretation between radiologists with different experience levels and ensures the stability of radiomics features.

Joint radiomics and spatial distribution model for MRI-based discrimination of multiple sclerosis, neuromyelitis optica spectrum disorder, and myelin-oligodendrocyte-glycoprotein-IgG-associated disorder.

OBJECTIVE: To develop a discrimination pipeline concerning both radiomics and spatial distribution features of brain lesions for discrimination of multiple sclerosis (MS), aquaporin-4-IgG-seropositive neuromyelitis optica spectrum disorder (NMOSD), and myelin-oligodendrocyte-glycoprotein-IgG-associated disorder (MOGAD). METHODS: Hyperintensity T2 lesions were delineated in 212 brain MRI scans of MS (n = 63), NMOSD (n = 87), and MOGAD (n = 45) patients. To avoid the effect of fixed training/test dataset sampling when developing machine learning models, patients were allocated into 4 sub-groups for cross-validation. For each scan, 351 radiomics and 27 spatial distribution features were extracted. Three models, i.e., multi-lesion radiomics, spatial distribution, and joint models, were constructed using random forest and logistic regression algorithms for differentiating: MS from the others (MS models) and MOGAD from NMOSD (MOG-NMO models), respectively. Then, the joint models were combined with demographic characteristics (i.e., age and sex) to create MS and MOG-NMO discriminators, respectively, based on which a three-disease discrimination pipeline was generated and compared with radiologists. RESULTS: For classification of both MS-others and MOG-NMO, the joint models performed better than radiomics or spatial distribution model solely. The MS discriminator achieved AUC = 0.909 ± 0.027 and bias-corrected C-index = 0.909 ± 0.027, and the MOG-NMO discriminator achieved AUC = 0.880 ± 0.064 and bias-corrected C-index = 0.883 ± 0.068. The three-disease discrimination pipeline differentiated MS, NMOSD, and MOGAD patients with 75.0% accuracy, prominently outperforming the three radiologists (47.6%, 56.6%, and 66.0%). CONCLUSIONS: The proposed pipeline integrating multi-lesion radiomics and spatial distribution features could effectively differentiate MS, NMOSD, and MOGAD. CLINICAL RELEVANCE STATEMENT: The discrimination pipeline merging both radiomics and spatial distribution features of brain lesions may facilitate the differential diagnoses of multiple sclerosis, neuromyelitis optica spectrum disorder, and myelin-oligodendrocyte-glycoprotein-IgG-associated disorder. KEY POINTS: • Our study introduces an approach by combining radiomics and spatial distribution models. • The joint model exhibited superior performance in distinguishing multiple sclerosis from aquaporin-4-IgG-seropositive neuromyelitis optica spectrum disorder and myelin-oligodendrocyte-glycoprotein-IgG-associated disorder as well as discriminating the latter two diseases. • The three-disease discrimination pipeline showcased remarkable accuracy, surpassing the performance of experienced radiologists, highlighting its potential as a valuable diagnostic tool.

4.6†kW linearly polarized and narrow-linewidth monolithic fiber amplifier based on a fiber oscillator laser seed.

In this work, a record output power of 4.6 kW linearly polarized and narrow-linewidth fiber amplifier based on an optimized fiber oscillator laser (FOL) seed was realized by employing a homemade polarization-maintaining Yb-doped fiber (PMYDF), corresponding to a slope efficiency of 79.5% and a 3 dB linewidth of 0.3452 nm. Through an effective strategy relying on decreasing the transmission fiber length from 200 m to 120 m and adding a chirped and tilted fiber Bragg grating (CTFBG), the stimulated Raman scattering (SRS) effects were well-suppressed. By applying the forward combiner with the interconnection between the pump arms into the MOPA system, the MI threshold is increased by more than 560 W and the slope efficiency of the upgraded MOPA system is boosted by 5%. During the experimental process of power amplification, the polarization extinction ratio (PER) remains higher than 15 dB, and a near-diffraction-limited output beam at the laser power of 2980 W was measured with the M2x = 1.314 and M2y = 1.311.

Risk factors for major adverse cardiovascular events after coronary artery bypass grafting using radial artery grafts.

Background: Coronary artery bypass grafting using radial artery grafts (RA-CABG) has improved long-term outcomes. However, major adverse cardiovascular events (MACE-4, including all-cause death, myocardial infarction, stroke, and repeat revascularization) after RA-CABG still occur and the predictors remain uncertain. This study aimed to detect independent risk factors of MACE-4 after RA-CABG. Methods: This is a retrospective case-control study (NCT04935086) conducted among patients who underwent primary isolated RA-CABG between 2009 and 2019 in our center. Baseline characteristics, procedure characteristics, and medication use were compared to identify the independent predictors of MACE-4, all-cause death, and myocardial infarction (MI) with univariate and then multivariate logistic regression. Results: A total of 370 patients were analyzed using a mean follow-up duration of 48.8 ± 41.0 months. MACE-4, all-cause death, and MI occurred in 102 (27.6%), 27 (7.3%), and 66 patients (17.8%), respectively. Multivariate analysis revealed prior MI (OR = 2.12, 95%CI 1.05-4.25, P = 0.04) and RA to the left anterior descending artery (LAD) (non-left internal mammary artery to LAD) (OR = 4.87, 95%CI 1.41-16.82, P = 0.01) as independent predictors of MACE-4 after surgery. Female (OR = 4.53, 95%CI 1.06-19.41, P = 0.04), left ventricular ejection fraction (LVEF) <40% (OR = 21.00, 95%CI 1.20-368.35, P = 0.04), and RA to LAD (OR = 8.55, 95%CI 1.35-54.10, P = 0.02) were independent predictors of all-cause death. Prior MI (OR = 3.11, 95%CI 1.40-6.94, P = 0.006) emerged as an independent predictor of MI. Conclusion: Our data suggested that prior MI and RA to LAD were independent predictors of MACE-4 after RA-CABG. Being female, having an LVEF < 40% and RA to LAD indicated death. Prior MI indicated new MI.

Male and female are not the same: a multicenter study of static and dynamic functional connectivity in relapse-remitting multiple sclerosis in China.

Background: Sex-related effects have been observed in relapsing-remitting multiple sclerosis (RRMS), but their impact on functional networks remains unclear. Objective: To investigate the sex-related differences in connectivity strength and time variability within large-scale networks in RRMS. Methods: This is a multi-center retrospective study. A total of 208 RRMS patients (135 females; 37.55 ± 11.47 years old) and 228 healthy controls (123 females; 36.94 ± 12.17 years old) were included. All participants underwent clinical and MRI assessments. Independent component analysis was used to extract resting-state networks (RSNs). We assessed the connectivity strength using spatial maps (SMs) and static functional network connectivity (sFNC), evaluated temporal properties and dynamic functional network connectivity (dFNC) patterns of RSNs using dFNC, and investigated their associations with structural damage or clinical variables. Results: For static connectivity, only male RRMS patients displayed decreased SMs in the attention network and reduced sFNC between the sensorimotor network and visual or frontoparietal networks compared with healthy controls [P<0.05, false discovery rate (FDR) corrected]. For dynamic connectivity, three recurring states were identified for all participants: State 1 (sparse connected state; 42%), State 2 (middle-high connected state; 36%), and State 3 (high connected state; 16%). dFNC analyses suggested that altered temporal properties and dFNC patterns only occurred in females: female patients showed a higher fractional time (P<0.001) and more dwell time in State 1 (P<0.001) with higher transitions (P=0.004) compared with healthy females. Receiver operating characteristic curves revealed that the fraction time and mean dwell time of State 1 could significantly distinguish female patients from controls (area under the curve: 0.838-0.896). In addition, female patients with RRMS also mainly showed decreased dFNC in all states, particularly within cognitive networks such as the default mode, frontoparietal, and visual networks compared with healthy females (P < 0.05, FDR corrected). Conclusion: Our results observed alterations in connectivity strength only in male patients and time variability in female patients, suggesting that sex-related effects may play an important role in the functional impairment and reorganization of RRMS.

Dynamic alterations in the amplitude of low-frequency fluctuation in patients with cerebral small vessel disease.

Background and purpose: Previous studies have focused on the changes of dynamic and static functional connections in cerebral small vessel disease (CSVD). However, the dynamic characteristics of local brain activity are poorly understood. The purpose of this study was to investigate the dynamic cerebral activity changes in patients with CSVD using the dynamic amplitude of low-frequency fluctuation (d-ALFF). Methods: A total of 104 CSVD patients with cognitive impairment (CSVD-CI, n = 52) or normal cognition (CSVD-NC, n = 52) and 63 matched healthy controls (HCs) were included in this study. Every participant underwent magnetic resonance imaging scans and a battery of neuropsychological examinations. The dynamics of spontaneous brain activity were assessed using dynamic changes in the amplitude of low-frequency fluctuation (ALFF) with the sliding-window method. We used voxel-wise one-way analysis of variance (ANOVA) to compare dynamic ALFF variability among the three groups. Post-hoc t-tests were used to evaluate differences between each group pair. Finally, the brain regions with d-ALFF values with differences between CSVD subgroups were taken as regions of interest (ROI), and the d-ALFF values corresponding to the ROI were extracted for partial correlation analysis with memory. Results: (1) There was no significant difference in age (p = 0.120), sex (p = 0.673) and education (p = 0.067) among CSVD-CI, CSVD-NC and HC groups, but there were significant differences Prevalence of hypertension and diabetes mellitus among the three groups (p < 10-3). There were significant differences in scores of several neuropsychological scales among the three groups (p < 10-3). (2) ANOVA and post-hoc t-test showed that there were dynamic abnormalities of spontaneous activity in several brain regions in three groups, mainly located in bilateral parahippocampal gyrus and bilateral hippocampus, bilateral insular and frontal lobes, and the static activity abnormalities in bilateral parahippocampal gyrus and bilateral hippocampal regions were observed at the same time, suggesting that bilateral parahippocampal gyrus and bilateral hippocampus may be the key brain regions for cognitive impairment caused by CSVD. (3) The correlation showed that d-ALFF in the bilateral insular was slightly correlated with the Mini-Mental State Examination (MMSE) score and disease progression rate. The d-ALFF value of the left postcentral gyrus was negatively correlated with the Clock Drawing Test (CDT) score (r = -0.416, p = 0.004), and the d-ALFF value of the right postcentral gyrus was negatively correlated with the Rey's Auditory Verbal Learning Test (RAVLT) word recognition (r = -0.320, p = 0.028). Conclusion: There is a wide range of dynamic abnormalities of spontaneous brain activity in patients with CSVD, in which the abnormalities of this activity in specific brain regions are related to memory and execution or emotion.

Influence mechanisms of different stalks on iron species type of magnetic biochar prepared from Fe2O3.

The current selection of biomass feedstock for magnetic biochar (MBC) catalysts is highly blind. Consequently, this study delves into understanding how the types of biomass influence the iron species present in MBC catalysts. The process involved the creation of MBC through simulated impregnation-pyrolysis, utilizing six types of stalks and Fe2O3. The type of iron species significantly impacted magnetic properties and likely influenced catalytic properties of MBC. MBC's iron species type was shaped by the reduction effects of the diverse stalks on Fe2O3. During the pyrolysis, discrepancies were observed in the release of reducing gases and direct reduction for the different stalks. These differences in reduction behavior directly accounted for the distinct reduction effects. To delve deeper, the reduction behavior and effect of the main components of the stalk (hemicellulose, cellulose, and lignin) on Fe2O3 were analyzed, highlighting lignin as the most effective. Nonetheless, the absolute values of Pearson's r between lignin content in the stalk and reduction behavior/effect ranged only from 0.078 to 0.421. In contrast, the values for K, Ca, and Si content in the stalks and their influence on reduction behavior and MBC's reduction/metallization degree ranged from 0.410 to 0.910. The catalytic impacts of K and Ca were confirmed through their incorporation into cotton and reed stalks. The disparities in K, Ca, and Si content among the six stalks appeared to be the primary driver behind the diverse iron species in MBC. This work provides a scientific basis for the rational selection of biomass feedstock for MBC catalysts.

Gradual conductance modulation by defect reorganization in amorphous oxide memristors.

Amorphous oxides show great prospects in revolutionizing memristors benefiting from their abundant non-stoichiometric composition. However, an in-depth investigation of the memristive characteristics in amorphous oxides is inadequate and the resistive switching mechanism is still controversial. In this study, aiming to clearly understand the gradual conductance modulation that is deeply bound to the evolution of defects-mainly oxygen vacancies, forming-free memristors based on amorphous ZnAlSnO are fabricated, which exhibit high reproducibility with an initial low-resistance state. Pulse depression reveals the logarithmic-exponential mixed relaxation during RESET owing to the diffusion of oxygen vacancies in orthogonal directions. The remnants of conductive filaments formed through aggregation of oxygen vacancies induced by high-electric-field are identified using ex situ TEM. Especially, the conductance of the filament, including the remnant filament, is larger than that of the hopping conductive channel derived from the diffusion of oxygen vacancies. The Fermi level in the conduction band rationalizes the decay of the high resistance state. Rare oxidation-migration of Au occurs upon device failure, resulting in numerous gold nanoclusters in the functional layer. These comprehensive revelations on the reorganization of oxygen vacancies could provide original ideas for the design of memristors.

Characterization of papillary and clear cell renal cell carcinoma through imaging mass cytometry reveals distinct immunologic profiles.

Objective: To characterize and further compare the immune cell populations of the tumor microenvironment (TME) in both clear cell and papillary renal cell carcinoma (RCC) using heavy metal-labeled antibodies in a multiplexed imaging approach (imaging mass cytometry). Materials and methods: Formalin-fixed paraffin-embedded (FFPE) baseline tumor tissues from metastatic patients with clear cell renal cell carcinoma (ccRCC) and papillary renal cell carcinoma (pRCC) were retrospectively requisitioned from an institutional biorepository. Pretreated FFPE samples from 33 RCC patients (10 ccRCC, 23 pRCC) were accessioned and stained for imaging mass cytometry (IMC) analysis. Clinical characteristics were curated from an institutional RCC database. FFPE samples were prepared and stained with heavy metal-conjugated antibodies for IMC. An 11-marker panel of tumor stromal and immune markers was used to assess and quantify cellular relationships in TME compartments. To validate our time-of-flight (CyTOF) analysis, we cross-validated findings with The Cancer Genome Atlas Program (TCGA) analysis and utilized the CIBERSORTx tool to examine the abundance of main immune cell types in pRCC and ccRCC patients. Results: Patients with ccRCC had a longer median overall survival than did those with pRCC (67.7 vs 26.8 mo, respectively). Significant differences were identified in the proportion of CD4+ T cells between disease subtypes (ccRCC 14.1%, pRCC 7.0%, p<0.01). Further, the pRCC cohort had significantly more PanCK+ tumor cells than did the ccRCC cohort (24.3% vs 9.5%, respectively, p<0.01). There were no significant differences in macrophage composition (CD68+) between cohorts. Our results demonstrated a significant correlation between the CyTOF and TCGA analyses, specifically validating that ccRCC patients exhibit higher levels of CD4+ T cells (ccRCC 17.60%, pRCC 15.7%, p<0.01) and CD8+ T cells (ccRCC 17.83%, pRCC 11.15%, p<0.01). The limitation of our CyTOF analysis was the large proportion of cells that were deemed non-characterizable. Conclusions: Our findings emphasize the need to investigate the TME in distinct RCC histological subtypes. We observed a more immune infiltrative phenotype in the TME of the ccRCC cohort than in the pRCC cohort, where a tumor-rich phenotype was noted. As practical predictive biomarkers remain elusive across all subtypes of RCC, further studies are warranted to analyze the biomarker potential of such TME classifications.