Metacognition and Mathematical Modeling Skills: The Mediating Roles of Computational Thinking in High School Students.

This study was to investigate the relationship between metacognition and the mathematical modeling skills of high school students, as well as the mediating role of computational thinking. A cluster sampling method was adopted to investigate 661 high school students, using the metacognition scale, computational thinking scale, and mathematical modeling skill test questions. The results showed that metacognitive knowledge and metacognitive monitoring had a direct and positive correlation with high school students' mathematical modeling skills. Additionally, the critical thinking dimension of computational thinking mediated the relationship between metacognitive knowledge, experience, monitoring, and mathematical modeling skills. These findings indicated that sufficient metacognition could improve the critical thinking of high school students' computational thinking and enhance their mathematical modeling skills.

Modifiable risk factors of immediate and long-term outcomes in the operable and inoperable with left-sided infective endocarditis.

Objectives: To evaluate the outcomes of left-sided infective endocarditis that can be operated on and cannot be operated on, and to focus on modifiable risk factors for immediate and long-term mortality. Methods: This study retrospectively investigated patients with left-sided infective endocarditis who occurred in our medical center between January 2006 and November 2022. Results: 48 in-hospital deaths occurred (5.8 %, 48/832). We identified time from symptoms to admission and symptomatic neurological complications to be risk factors for multiple organ failure upon admission. Time from symptoms to admission and vegetation size in group of isolated medical treatment were significantly shorter than those in the group of heart operation. We also found that preoperative neurological complications, annulus destruction, levels of serum creatinine at 24 and 48 h post heart operation, and perivalvular leakage are risk factors for in-hospital mortality post heart operation. With 148 µmol/L as a cutoff level, the diagnostic sensitivity and specificity of serum creatinine level 48 h post surgery for in-hospital mortality post cardiac surgery are 100 % and 81.6 %, respectively. We found that vegetation size, ICU stay, postoperative serum creatinine at 48 h, left ventricular end diastolic size postoperative, and red blood cell transfusion were associated with all-time mortality. Conclusions: Early diagnosis and treatment, improvement of surgical techniques, good protection for heart, kidney and blood and close follow-up are advocated to conduce to better immediate and long-term outcomes of the operable and inoperable with left-sided infective endocarditis.

Acute hematologic toxicity prediction using dosimetric and radiomics features in patients with cervical cancer: does the treatment regimen matter?

Background: Acute hematologic toxicity (HT) is a prevalent adverse tissue reaction observed in cervical cancer patients undergoing chemoradiotherapy (CRT), which may lead to various negative effects such as compromised therapeutic efficacy and prolonged treatment duration. Accurate prediction of HT occurrence prior to CRT remains challenging. Methods: A discovery dataset comprising 478 continuous cervical cancer patients (140 HT patients) and a validation dataset consisting of 205 patients (52 HT patients) were retrospectively enrolled. Both datasets were categorized into the CRT group and radiotherapy (RT)-alone group based on the treatment regimen, i.e., whether chemotherapy was administered within the focused RT duration. Radiomics features were derived by contouring three regions of interest (ROIs)-bone marrow (BM), femoral head (FH), and clinical target volume (CTV)-on the treatment planning CT images before RT. A comprehensive model combining the radiomics features as well as the demographic, clinical, and dosimetric features was constructed to classify patients exhibiting acute HT symptoms in the CRT group, RT group, and combination group. Furthermore, the time-to-event analysis of the discriminative ROI was performed on all patients with acute HT to understand the HT temporal progression. Results: Among three ROIs, BM exhibited the best performance in classifying acute HT, which was verified across all patient groups in both discovery and validation datasets. Among different patient groups in the discovery dataset, acute HT was more precisely predicted in the CRT group [area under the curve (AUC) = 0.779, 95% CI: 0.657-0.874] than that in the RT-alone (AUC = 0.686, 95% CI: 0.529-0.817) or combination group (AUC = 0.748, 95% CI: 0.655-0.827). The predictive results in the validation dataset similarly coincided with those in the discovery dataset: CRT group (AUC = 0.802, 95% CI: 0.669-0.914), RT-alone group (AUC = 0.737, 95% CI: 0.612-0.862), and combination group (AUC = 0.793, 95% CI: 0.713-0.874). In addition, distinct feature sets were adopted for different patient groups. Moreover, the predicted HT risk of BM was also indicative of the HT temporal progression. Conclusions: HT prediction in cervical patients is dependent on both the treatment regimen and ROI selection, and BM is closely related to the occurrence and progression of HT, especially for CRT patients.

Prevotella copri promotes vascular calcification via lipopolysaccharide through activation of NF-κB signaling pathway.

Emerging evidence indicates that alteration of gut microbiota plays an important role in chronic kidney disease (CKD)-related vascular calcification (VC). We aimed to investigate the specific gut microbiota and the underlying mechanism involved in CKD-VC. We identified an increased abundance of Prevotella copri (P. copri) in the feces of CKD rats (induced by using 5/6 nephrectomy followed by a high calcium and phosphate diet) with aortic calcification via amplicon sequencing of 16S rRNA genes. In patients with CKD, we further confirmed a positive correlation between abundance of P. copri and aortic calcification scores. Moreover, oral administration of live P. copri aggravated CKD-related VC and osteogenic differentiation of vascular smooth muscle cells in vivo, accompanied by intestinal destruction, enhanced expression of Toll-like receptor-4 (TLR4), and elevated lipopolysaccharide (LPS) levels. In vitro and ex vivo experiments consistently demonstrated that P. copri-derived LPS (Pc-LPS) accelerated high phosphate-induced VC and VSMC osteogenic differentiation. Mechanistically, Pc-LPS bound to TLR4, then activated the nuclear factor κB (NF-κB) and nucleotide-binding domain, leucine-rich-containing family, pyrin domain-containing-3 (NLRP3) inflammasome signals during VC. Inhibition of NF-κB reduced NLRP3 inflammasome and attenuated Pc-LPS-induced VSMC calcification. Our study clarifies a novel role of P. copri in CKD-related VC, by the mechanisms involving increased inflammation-regulating metabolites including Pc-LPS, and activation of the NF-κB/NLRP3 signaling pathway. These findings highlight P. copri and its-derived LPS as potential therapeutic targets for VC in CKD.

Distance-specific functional connectivity strength alterations in human immunodeficiency virus asymptomatic neurocognitive impairment patients: a cross-sectional study.

Background: Asymptomatic neurocognitive impairment (ANI) is the mildest form of human immunodeficiency virus (HIV)-associated neurocognitive disorders (HANDs), and functional connectivity strength (FCS) alternations have been observed in the ANI stage. However, it is not clear whether the FCS alterations are influenced by the anatomical distance. This study sought to investigate distance-specific FCS changes in HIV ANI patients. Methods: In total, 29 patients with HAND and 32 healthy controls (HCs) were enrolled in the study. Between-group differences were detected for short, middle and long range anatomical distance FCS. A correlation analysis was performed to examine the relationship between distance-specific FCS and immunological parameters and neuropsychological tests. A receiver operating characteristic (ROC) analysis was conducted to examine the discriminative performance for HIV ANI patients. Results: In comparison to the HCs, the HAND patients showed increased short-range FCS in the left inferior parietal lobule (IPL), middle-range FCS in the superior temporal gyrus (STG), long-range FCS in the left precuneus (PCC), and decreased FCS in the right postcentral gyrus (PCG) (cluster P<0.05, voxel significance P<0.001). Further, the long-range FCS in the right PCG was negatively correlated with the CD4/CD8 ratio (r=-0.479, 95% confidence interval (CI): -0.735 to -0.104, P=0.015), and the distance-specific FCS also showed good classification performance between the HAND patients and HCs. The left IPL, left STG, right PCG, and left PCC had areas under the curve (AUCs) of 0.875 [95% confidence interval (CI): 0.758-0.949, P<0.0001], 0.806 (95% CI: 0.677-0.900, P<0.0001), 0.855 (95% CI: 0.734-0.935, P<0.0001), and 0.852 (95% CI: 0.754-0.950, P<0.0001), respectively. There was no significant relationship between the distance-specific FCS and the neuropsychological tests. Conclusions: Distance-specific FCS could be used to examine subtle alternations in HIV-infected patients in the ANI stage and help to explain the possible neurophysiological mechanism of HAND.

A radiomics-based brain network in T1 images: construction, attributes, and applications.

T1 image is a widely collected imaging sequence in various neuroimaging datasets, but it is rarely used to construct an individual-level brain network. In this study, a novel individualized radiomics-based structural similarity network was proposed from T1 images. In detail, it used voxel-based morphometry to obtain the preprocessed gray matter images, and radiomic features were then extracted on each region of interest in Brainnetome atlas, and an individualized radiomics-based structural similarity network was finally built using the correlational values of radiomic features between any pair of regions of interest. After that, the network characteristics of individualized radiomics-based structural similarity network were assessed, including graph theory attributes, test-retest reliability, and individual identification ability (fingerprinting). At last, two representative applications for individualized radiomics-based structural similarity network, namely mild cognitive impairment subtype discrimination and fluid intelligence prediction, were exemplified and compared with some other networks on large open-source datasets. The results revealed that the individualized radiomics-based structural similarity network displays remarkable network characteristics and exhibits advantageous performances in mild cognitive impairment subtype discrimination and fluid intelligence prediction. In summary, the individualized radiomics-based structural similarity network provides a distinctive, reliable, and informative individualized structural brain network, which can be combined with other networks such as resting-state functional connectivity for various phenotypic and clinical applications.

Pericardiectomy for Constrictive Pericarditis with or without Cardiopulmonary Bypass.

Aim: We aim to access the effect of pericardiectomy for constrictive pericarditis with or without cardiopulmonary bypass. Methods: This was a review of pericardiectomy for constrictive pericarditis. Results: Cardiopulmonary bypass is actually an important maneuver to attain complete relief of the constriction. The short additional time of cardiopulmonary bypass during the procedure has very little effect on the risk of morbidity of the main operation. Conclusion: Incomplete pericardiectomy perhaps was the cause of postoperative remnant constriction and high diastolic filling pressure leading to multiorgan failure. Complete pericardiectomy (removal of phrenic-to-phrenic and the postero-lateral and inferior wall pericardial thickening) using cardiopulmonary bypass should be the routine for total relief of the constriction of the heart.

One model, two brains: Automatic fetal brain extraction from MR images of twins.

Fetal brain extraction from magnetic resonance (MR) images is of great importance for both clinical applications and neuroscience studies. However, it is a challenging task, especially when dealing with twins, which are commonly existing in pregnancy. Currently, there is no brain extraction method dedicated to twins, raising significant demand to develop an effective twin fetal brain extraction method. To this end, we propose the first twin fetal brain extraction framework, which possesses three novel features. First, to narrow down the region of interest and preserve structural information between the two brains in twin fetal MR images, we take advantage of an advanced object detector to locate all the brains in twin fetal MR images at once. Second, we propose a Twin Fetal Brain Extraction Network (TFBE-Net) to further suppress insignificant features for segmenting brain regions. Finally, we propose a Two-step Training Strategy (TTS) to learn correlation features of the single fetal brain for further improving the performance of TFBE-Net. We validate the proposed framework on a twin fetal brain dataset. The experiments show that our framework achieves promising performance on both quantitative and qualitative evaluations, and outperforms state-of-the-art methods for fetal brain extraction.

Remnant cholesterol and the risk of aortic valve calcium progression: insights from the MESA study.

BACKGROUND: Remnant cholesterol (RC) is implicated in the risk of cardiovascular disease. However, comprehensive population-based studies elucidating its association with aortic valve calcium (AVC) progression are limited, rendering its precise role in AVC ambiguous. METHODS: From the Multi-Ethnic Study of Atherosclerosis database, we included 5597 individuals (61.8 ± 10.1 years and 47.5% men) without atherosclerotic cardiovascular disease at baseline for analysis. RC was calculated as total cholesterol minus high-density lipoprotein cholesterol (HDL-C) and low-density lipoprotein cholesterol (LDL-C), as estimated by the Martin/Hopkins equation. Using the adjusted Cox regression analyses, we examined the relationships between RC levels and AVC progression. Furthermore, we conducted discordance analyses to evaluate the relative AVC risk in RC versus LDL-C discordant/concordant groups. RESULTS: During a median follow-up of 2.4 ± 0.9 years, 568 (10.1%) participants exhibited AVC progression. After adjusting for traditional cardiovascular risk factors, the HRs (95% CIs) for AVC progression comparing the second, third, and fourth quartiles of RC levels with the first quartile were 1.195 (0.925-1.545), 1.322 (1.028-1.701) and 1.546 (1.188-2.012), respectively. Notably, the discordant high RC/low LDL-C group demonstrated a significantly elevated risk of AVC progression compared to the concordant low RC/LDL-C group based on their medians (HR, 1.528 [95% CI 1.201-1.943]). This pattern persisted when clinical LDL-C threshold was set at 100 and 130 mg/dL. The association was consistently observed across various sensitivity analyses. CONCLUSIONS: In atherosclerotic cardiovascular disease-free individuals, elevated RC is identified as a residual risk for AVC progression, independent of traditional cardiovascular risk factors. The causal relationship of RC to AVC and the potential for targeted RC reduction in primary prevention require deeper exploration.

Multi-Scale FC-Based Multi-Order GCN: A Novel Model for Predicting Individual Behavior From fMRI.

Predicting individual behavior from brain imaging data using machine learning is a rapidly growing field in neuroscience. Functional connectivity (FC), which captures interactions between different brain regions, contains valuable information about the organization of the brain and is considered a crucial feature for modeling human behavior. Graph convolutional networks (GCN) have proven to be a powerful tool for extracting graph structure features and have shown promising results in various FC-based classification tasks, such as disease classification and prognosis prediction. Despite this success, few behavior prediction models currently exist based on GCN, and their performance is not satisfactory. To address this gap, a new model called the Multi-Scale FC-based Multi-Order GCN (MSFC-MO-GCN) was proposed in this paper. The model considers the hierarchical structure of the brain system and utilizes FCs inferred from multiple spatial scales as input to comprehensively characterize individual brain organization. To enhance the feature learning ability of GCN, a multi-order graph convolutional layer is incorporated, which uses multi-order neighbors to guide message passing and learns high-order graph information of nodal connections. Additionally, an inter-subject contrast constraint is designed to control the potential information redundancy of FCs among different spatial scales during the feature learning process. Experimental evaluation were conducted on the publicly available dataset from human connectome project. A total of 805 healthy subjects were included and 5 representative behavior metrics were used. The experimental results show that our proposed method outperforms the existing behavior prediction models in all behavior prediction tasks.

Image Recovery Matters: A Recovery-Extraction Framework for Robust Fetal Brain Extraction From MR Images.

The extraction of the fetal brain from magnetic resonance (MR) images is a challenging task. In particular, fetal MR images suffer from different kinds of artifacts introduced during the image acquisition. Among those artifacts, intensity inhomogeneity is a common one affecting brain extraction. In this work, we propose a deep learning-based recovery-extraction framework for fetal brain extraction, which is particularly effective in handling fetal MR images with intensity inhomogeneity. Our framework involves two stages. First, the artifact-corrupted images are recovered with the proposed generative adversarial learning-based image recovery network with a novel region-of-darkness discriminator that enforces the network focusing on artifacts of the images. Second, we propose a brain extraction network for more effective fetal brain segmentation by strengthening the association between lower- and higher-level features as well as suppressing task-irrelevant features. Thanks to the proposed recovery-extraction strategy, our framework is able to accurately segment fetal brains from artifact-corrupted MR images. The experiments show that our framework achieves promising performance in both quantitative and qualitative evaluations, and outperforms state-of-the-art methods in both image recovery and fetal brain extraction.

Intracranial mesenchymal tumor with multiple extracranial metastases: A case report and literature review.

This study presents a rare case of an older woman with an intracranial mesenchymal tumor in the right frontal and parietal lobes. Despite prompt surgical intervention, her condition rapidly deteriorated because of tumor dissemination, leading to her demise. We highlight the tumor's marked invasiveness and heterogeneity, coupled with a propensity for distant systemic metastasis, which negatively impacted the patient's prognosis. This particular clinical behavior had not been previously reported, making this a novel observation. Thus, through a comprehensive review of relevant literature, we aim to provide valuable insights for further understanding, diagnosing, and treating such tumors.

Sanhuang Xiexin Decoction Ameliorates TNBC By Modulating JAK2-STAT3 and Lipid Metabolism.

OBJECTIVE: To investigate the therapeutic effect of Sanhuang Xiexin Decoction (SXD) on triple-negative breast cancer (TNBC) in mice and its underlying mechanism. METHODS: The high-performance liquid chromatography (HPLC) was used to quantitate and qualify SXD. A total of 15 female BALB/c mice were inoculated subcutaneously on the right hypogastrium with 3×105 of 4T1-Luc cells to establish TNBC mouse model. All mice were divided randomly into 3 groups, including phosphate buffered solution (PBS), SXD and doxorubicin (DOX) groups (positive drug). Additionally, tumor growth, pathological changes, serum lipid profiles, expression of Janus kinase 2 (JAK2)-signal transducer and activator of transcription 3 (STAT3) signaling pathway and its key targets including inflammatory factors, cell cycle and epithelial-mesenchymal transition (EMT) markers were investigated. Besides, the biosafety of SXD was also evaluated in mice. RESULTS: Rhein, coptisine, berberine hydrochloride and baicalin were all found in SXD, and the concentrations of these 4 components were 0.57, 2.61, 2.93, and 46.04 mg/g, respectively. The mouse experiment showed that SXD could notably suppress the development of tumors and reduce the density of tumor cells (P<0.01). The serum lipid analysis and Oil-Red-O staining both showed the differences, SXD group exhibited higher serum adiponectin and HDL-C levels with lower TC and LDL-C levels compared to the PBS and DOX groups (P<0.05 or P<0.01), respectively. SXD also decreased the levels of phospho-JAK2 (p-JAK2), phospho-STAT3 (p-STAT3) expressions and its downstream factors, including mostly inflammatory cytokine, EMT markers, S phase of tumor cells and vascular endothelial growth factor (VEGF) expression (P<0.05 or P<0.01), respectively. The biosafety assessment of SXD revealed low levels of toxicity in mice. CONCLUSION: SXD could inhibit TNBC by suppressing JAK2-STAT3 phosphorylation which may be associated with modulation of lipid metabolism.

Surgical treatment of left-sided infective endocarditis with symptomatic neurological complications before surgery in China.

Introduction: We aimed to investigate surgical treatment of left-sided infective endocarditis with symptomatic neurological complications before surgery. Methods: This was a retrospective study of patients with left-sided infective endocarditis and symptomatic neurological complications before surgery undergoing cardiac surgery between January 2006 and November 2022 at our hospital. Results: Eight hundred thirty-two patients were divided into group with symptomatic neurological complications before surgery (n = 112) and without symptomatic neurological complications before surgery (n = 720). There were 48 operative deaths (5.4%). Univariate and multivariate analyses showed that symptomatic neurological complications before surgery is statistically significantly associated with in-hospital mortality following cardiac surgery and prolonged intubation time. Conclusions: Our study showed that symptomatic neurological complications before surgery are associated with increased in-hospital mortality following cardiac surgery and prolonged intubation time.

Risk factors of prolonged intensive care unit stay following cardiac surgery for infective endocarditis.

INTRODUCTION: Prolonged intensive care unit (ICU) stay is common in serious patients undergoing cardiac surgery. Prolonged ICU stay is associated with increased mortality and worse prognosis. This study was conducted to determine the risk factors for prolonged ICU stay after cardiac surgery for infective endocarditis (IE) and we try to decrease the operative risk of mortality and morbidity of cardiac surgery for IE. METHODS: The retrospective study of patients with IE undergoing cardiac surgery between January 2006 and November 2022 at our hospital was performed. RESULTS: 896 patients undergoing cardiac surgery were divided into group of ICU stay ≤ 3d (n = 416) and group p of ICU stay > 3d (n = 480). There were 48 operative deaths (5.4%). Univariable and multivariable analyses showed that factors are associated with prolonged ICU stay following cardiac surgery for IE, including male (P < .001), age (P < .001), weight (P = .009), vegetation length (P < .001), paravalvular leak (P < .001), aortic cross-clamp time (P < .001), cardiopulmonary bypass (CPB) time (P < .001), mechanical ventilation time (P < .001), hospitalized time postoperative (P = .032), creatinine of serum before surgery (P < .001), creatinine of serum 24h after surgery (P = .005), creatinine of serum 48h after surgery (P < .001), fluid balance on operation day (P < .001), postoperative acute kidney injury (P < .001), left ventricular end diastolic dimension (LVEDD) preoperative (P < .001), LVEDD postoperative (P < .001), chest drainage (P = .032), frozen plasma (P = .016), preoperative aortic insufficiency (P < .001), and packed red cells (P < .001). CONCLUSIONS: In our study, shortness of ICU stay and optimization of pre-, peri-, and postoperative factors that can shorten ICU stay, therefore, contribute to a better postoperative outcome and leads to lower rates of mortality and morbidity.

Identifying Alzheimer's disease and mild cognitive impairment with atlas-based multi-modal metrics.

Introduction: Multi-modal neuroimaging metrics in combination with advanced machine learning techniques have attracted more and more attention for an effective multi-class identification of Alzheimer's disease (AD), mild cognitive impairment (MCI) and health controls (HC) recently. Methods: In this paper, a total of 180 subjects consisting of 44 AD, 66 MCI and 58 HC subjects were enrolled, and the multi-modalities of the resting-state functional magnetic resonance imaging (rs-fMRI) and the structural MRI (sMRI) for all participants were obtained. Then, four kinds of metrics including the Hurst exponent (HE) metric and bilateral hippocampus seed independently based connectivity metrics generated from fMRI data, and the gray matter volume (GMV) metric obtained from sMRI data, were calculated and extracted in each region of interest (ROI) based on a newly proposed automated anatomical Labeling (AAL3) atlas after data pre-processing. Next, these metrics were selected with a minimal redundancy maximal relevance (MRMR) method and a sequential feature collection (SFC) algorithm, and only a subset of optimal features were retained after this step. Finally, the support vector machine (SVM) based classification methods and artificial neural network (ANN) algorithm were utilized to identify the multi-class of AD, MCI and HC subjects in single modal and multi-modal metrics respectively, and a nested ten-fold cross-validation was utilized to estimate the final classification performance. Results: The results of the SVM and ANN based methods indicated the best accuracies of 80.36 and 74.40%, respectively, by utilizing all the multi-modal metrics, and the optimal accuracies for AD, MCI and HC were 79.55, 78.79 and 82.76%, respectively, in the SVM based method. In contrast, when using single modal metric, the SVM based method obtained a best accuracy of 72.62% with the HE metric, and the accuracies for AD, MCI and HC subjects were just 56.82, 80.30 and 75.86%, respectively. Moreover, the overlapping abnormal brain regions detected by multi-modal metrics were mainly located at posterior cingulate gyrus, superior frontal gyrus and cuneus. Conclusion: Taken together, the SVM based method with multi-modal metrics could provide effective diagnostic information for identifying AD, MCI and HC subjects.

Probing bundle-wise abnormalities in patients infected with human immunodeficiency virus using fixel-based analysis: new insights into neurocognitive impairments.

BACKGROUND: Changes in white matter (WM) underlie the neurocognitive damages induced by a human immunodeficiency virus (HIV) infection. This study aimed to examine using a bundle-associated fixel-based analysis (FBA) pipeline for investigating the microstructural and macrostructural alterations in the WM of the brain of HIV patients. METHODS: This study collected 93 HIV infected patients and 45 age/education/handedness matched healthy controls (HCs) at the Beijing Youan Hospital between January 1, 2016 and December 30, 2016.All HIV patients underwent neurocognitive evaluation and laboratory testing followed by magnetic resonance imaging (MRI) scanning. In order to detect the bundle-wise WM abnormalities accurately, a specific WM bundle template with 56 tracts of interest was firstly generated by an automated fiber clustering method using a subset of subjects. Fixel-based analysis was used to investigate bundle-wise differences between HIV patients and HCs in three perspectives: fiber density (FD), fiber cross-section (FC), and fiber density and cross-section (FDC). The between-group differences were detected by a two-sample t -test with the false discovery rate (FDR) correction ( P <0.05). Furthermore, the covarying relationship in FD, FC and FDC between any pair of bundles was also accessed by the constructed covariance networks, which was subsequently compared between HIV and HCs via permutation t -tests. The correlations between abnormal WM metrics and the cognitive functions of HIV patients were explored via partial correlation analysis after controlling age and gender. RESULTS: Among FD, FC and FDC, FD was the only metric that showed significant bundle-wise alterations in HIV patients compared to HCs. Increased FD values were observed in the bilateral fronto pontine tract, corona radiata frontal, left arcuate fasciculus, left corona radiata parietal, left superior longitudinal fasciculus III, and right superficial frontal parietal (SFP) (all FDR P <0.05). In bundle-wise covariance network, HIV patients displayed decreased FD and increased FC covarying patterns in comparison to HC ( P <0.05) , especially between associated pathways. Finally, the FCs of several tracts exhibited a significant correlation with language and attention-related functions. CONCLUSIONS: Our study demonstrated the utility of FBA on detecting the WM alterations related to HIV infection. The bundle-wise FBA method provides a new perspective for investigating HIV-induced microstructural and macrostructural WM-related changes, which may help to understand cognitive dysfunction in HIV patients thoroughly.

Single-cell RNA sequencing of neural stem cells derived from human trisomic iPSCs reveals the abnormalities during neural differentiation of Down syndrome.

Introduction: Down syndrome (DS) is the most common genetic condition that causes intellectual disability in humans. The molecular mechanisms behind the DS phenotype remain unclear. Therefore, in this study, we present new findings on its molecular mechanisms through single-cell RNA sequencing. Methods: Induced pluripotent stem cells (iPSCs) from the patients with DS and the normal control (NC) patients were differentiated into iPSCs-derived neural stem cells (NSCs). Single-cell RNA sequencing was performed to achieve a comprehensive single-cell level differentiation roadmap for DS-iPSCs. Biological experiments were also performed to validate the findings. Results and Discussion: The results demonstrated that iPSCs can differentiate into NSCs in both DS and NC samples. Furthermore, 19,422 cells were obtained from iPSC samples (8,500 cells for DS and 10,922 cells for the NC) and 16,506 cells from NSC samples (7,182 cells for DS and 9,324 cells for the NC), which had differentiated from the iPSCs. A cluster of DS-iPSCs, named DS-iPSCs-not differentiated (DSi-PSCs-ND), which had abnormal expression patterns compared with NC-iPSCs, were demonstrated to be unable to differentiate into DS-NSCs. Further analysis of the differentially expressed genes revealed that inhibitor of differentiation family (ID family) members, which exhibited abnormal expression patterns throughout the differentiation process from DS-iPSCs to DS-NSCs, may potentially have contributed to the neural differentiation of DS-iPSCs. Moreover, abnormal differentiation fate was observed in DS-NSCs, which resulted in the increased differentiation of glial cells, such as astrocytes, but decreased differentiation into neuronal cells. Furthermore, functional analysis demonstrated that DS-NSCs and DS-NPCs had disorders in axon and visual system development. The present study provided a new insight into the pathogenesis of DS.

Impact of Vegetation Length on Clinical Complications During Surgical Intervention and Long-Term Survival in Infective Endocarditis.

We aimed to investigate the impact of vegetation length on clinical complications during surgical intervention and long-term survival in infective endocarditis. This was a retrospective study of patients with infective endocarditis who underwent cardiac surgery between January 2006 and November 2022 at our hospital. 896 patients were divided into 2 groups: group I (vegetation length <10 mm, n = 448) and group II (vegetation length ≥10 mm, n = 448). There were 48 operative deaths (5.4%). Univariate and multivariate analyses showed that vegetation length is statistically significantly associated with destruction of the annulus (p <0.001), neurological complications before surgery (p <0.001), acute renal injury (p <0.001), prolonged intubation time (intubation time >24 hours) (p <0.001), prolonged intensive care unit (ICU) retention time (ICU retention time >3 days) (p <0.001), and in-hospital mortality (p <0.001), respectively. Our study showed that vegetation length is statistically significantly associated with destruction of the annulus, neurological complications before surgery, acute renal injury, prolonged intubation time, prolonged ICU retention time, in-hospital mortality, and 1-year mortality, respectively.

Rubiginosin B selectively inhibits Treg cell differentiation and enhances anti-tumor immune responses by targeting calcineurin-NFAT signaling pathway.

BACKGROUND: The accumulation of CD4+Foxp3+ regulatory T cells (Tregs) in the tumor microenvironment (TME) dampens anti-tumor immune responses and promotes tumor progression. Therefore, the elimination of Tregs has become a strategy to enhance the efficacy of tumor immunotherapy, although it is still a daunting challenge. Rhododendron brachypodum (R. brachypodum) is a perennial shrub mainly distributed in Southwestern China, whereas the chemical constituents in this plant remain elusive. PURPOSE: To identify small-molecule inhibitors of Tregs from R. brachypodum. METHODS: Meroterpenoids in R. brachypodum were isolated by column chromatography under the guidance of LCMS analyses. The structures of isolates were identified by spectroscopic data and quantum calculations. The activities of compounds were first evaluated on CD4+ T cell differentiation by flow cytometry in Th1, Th2, Th17, and Treg polarizing conditions, and then on CT26 and MC38 murine colorectal carcinoma cells-allografted mice models. The mechanism of action was first investigated by determining Foxp3 degradation in Jurkat T cells transfected with pLVX-TetOne-Puro-Foxp3-tGFP, and then through analyses of Foxp3 expression on several pre-transcriptional signaling molecules. RESULTS: Two new prenylated phenolic acids (1 and 2) and a chromane meroterpenoid, rubiginosin B (RGB, 3) were obtained from R. brachypodum. The structure of S-anthopogochromene C (1) was rectified according to the electronic circular dichroism (ECD) experiment, and rhodobrachypodic acid (2) was proposed as the precursor of RGB by photochemical transformation. In this investigation, we first found that RGB (3) selectively suppressed the de novo differentiation of TGFß-induced CD4+Foxp3+ regulatory T cells (iTregs), overcome the immunosuppressive TME, and consequently inhibited the growth of tumor in mouse models. The mechanistic study revealed that RGB could target calcineurin, inhibited the nuclear factor of activated T cells (NFAT) dephosphorylation, and down-regulated Foxp3 expression. The hypothetical binding modes of RGB with calcineurin were predicted by molecular docking, and the interactions were mainly hydrophobic effects and hydrogen bonds. CONCLUSION: These results suggest that RGB enhances anti-tumor immune responses by inhibiting Treg cell differentiation through calcineurin-NFAT signaling pathway, and therefore RGB or its analogs may be used as adjuvant agents meriting further investigation.