Generative Adversarial Matrix Completion Network based on Multi-Source Data Fusion for miRNA-Disease Associations Prediction.

Numerous biological studies have shown that considering disease-associated micro RNAs (miRNAs) as potential biomarkers or therapeutic targets offers new avenues for the diagnosis of complex diseases. Computational methods have gradually been introduced to reveal disease-related miRNAs. Considering that previous models have not fused sufficiently diverse similarities, that their inappropriate fusion methods may lead to poor quality of the comprehensive similarity network and that their results are often limited by insufficiently known associations, we propose a computational model called Generative Adversarial Matrix Completion Network based on Multi-source Data Fusion (GAMCNMDF) for miRNA-disease association prediction. We create a diverse network connecting miRNAs and diseases, which is then represented using a matrix. The main task of GAMCNMDF is to complete the matrix and obtain the predicted results. The main innovations of GAMCNMDF are reflected in two aspects: GAMCNMDF integrates diverse data sources and employs a nonlinear fusion approach to update the similarity networks of miRNAs and diseases. Also, some additional information is provided to GAMCNMDF in the form of a 'hint' so that GAMCNMDF can work successfully even when complete data are not available. Compared with other methods, the outcomes of 10-fold cross-validation on two distinct databases validate the superior performance of GAMCNMDF with statistically significant results. It is worth mentioning that we apply GAMCNMDF in the identification of underlying small molecule-related miRNAs, yielding outstanding performance results in this specific domain. In addition, two case studies about two important neoplasms show that GAMCNMDF is a promising prediction method.

Activation of adenosine A2B receptor alleviates myocardial ischemia-reperfusion injury by inhibiting endoplasmic reticulum stress and restoring autophagy flux.

Myocardial ischemia-reperfusion injury (MIRI) poses a significant threat to patients with coronary heart disease. Adenosine A2A receptors have been known as a protective role in MIRI by regulating autophagy, so we assumed that activation of adenosine A2B receptor (A2BAR) might exert a similar effect during MIRI and underlying mechanism be related to proteostasis maintenance as well. In situ hearts were subjected to 30 min of ischemia and 120 min of reperfusion (IR), while invitro cardiomyocytes from neonatal rats experienced 6 h of oxygen-glucose deprivation followed by 12 h of reoxygenation (OGDR). Initially, we observed that post-ischemia-reperfusion induced autophagy flux blockade and ERS both in vivo and in vitro, evident through the increased expression of p62, LC3II, and BIP, which indicated the deteriorated proteostasis. We used a selective A2BAR agonist, Bay 60-6583, to explore the positive effects of A2BAR on cardiomyocytes and found that A2BAR activation rescued damaged cardiac function and morphological changes in the IR group and improved frail cell viability in the OGDR group. The A2BAR agonist also alleviated the blockage of autophagic flux, coupled with augmented ERS in the IR/OGDR group, which was reassured by using an autophagy inhibitor chloroquine (CQ) and ERS inhibitor (4-PBA) in vitro. Additionally, considering cAMP/PKA as a well-known downstream effector of A2BAR, we utilized H89, a selective PKA inhibitor. We observed that the positive efficacy of Bay 60-6583 was inhibited by H89. Collectively, our findings demonstrate that the A2BAR/cAMP/PKA signaling pathway exerts a protective role in MIRI by mitigating impaired autophagic flux and excessive ERS.

Bidirectional relationship between late-onset epilepsy (LOE) and dementia: A systematic review and meta-analysis of cohort studies.

OBJECTIVE: To explore the bidirectional relationship of late-onset epilepsy (LOE) with dementia and Alzheimer's disease (AD). METHODS: Using the common electronic databases, including PubMed, Cochrane Library databases and EMBASE, we systematically reviewed published cohort studies that assessed the risk of LOE in individuals comorbid with dementia or AD, and those with dementia or AD comorbid with LOE that had been published up to 31 March 2023. The data extraction process was carried out independently by two authors. The summary adjusted relative ratio (aRR) was calculated by employing Rev Man 5.3 for the inclusion of studies. To investigate the origins of heterogeneity, we conducted both subgroup and sensitivity analyses. In the presence of heterogeneity, a random-effects model was employed. To evaluate potential publication bias, we utilized the funnel plot and conducted Begg's and Egger's tests. RESULTS: We included 20 eligible studies in the final analysis after a rigorous screening process. Pooled results indicated that LOE was association with an increased risk of all-cause dementia (aRR: 1.34, 95% confidence interval [CI]: 1.13-1.59) and AD (aRR: 2.49, 95% CI: 1.16-5.32). In addition, the pooled effect size for LOE associated with baseline AD and all-cause dementia were 3.51 (95% CI: 3.47-3.56) and 2.53 (95% CI: 2.39-2.67), respectively. Both sensitivity and subgroup analyses showed that these positive correlations persisted. According to the results of the Egger's and Begg's tests, as well as visual inspection of funnel plots, none of the studies appeared to be biased by publication. CONCLUSION: The findings suggested that LOE is a potential risk factor for dementia and AD, and vice versa, dementia and AD are both potential risk indicators for LOE. Since there is substantial heterogeneity among the cohorts analyzed and more cohort studies should be conducted to confirm the correlations found in the current study.

Reorganization of the structural connectome during vision recovery in pituitary adenoma patients post-transsphenoidal surgery.

Pituitary adenomas (PAs) can exert pressure on the optic apparatus, leading to visual impairment. A subset of patients may observe a swift improvement in their vision following surgery. Nevertheless, the alterations in the structural connectome during the early postoperative period remain largely unexplored. The research employed probabilistic tractography, graph theoretical analysis, and statistical methods on preoperative and postoperative structural magnetic resonance imaging and diffusion tensor images from 13 PA patients. Postoperative analysis revealed an increase in global and local efficiency, signifying improved network capacity for parallel information transfer and fault tolerance, respectively. Enhanced clustering coefficient and reduced shortest path length were also observed, suggesting a more regular network organization and shortened communication steps within the brain network. Furthermore, alterations in node graphical properties were detected, implying a restructuring of the network's control points, possibly contributing to more efficient visual processing. These findings propose that rapid vision recovery post-surgery may be associated with significant reorganization of the brain's structural connectome, enhancing the efficiency and adaptability of the network, thereby facilitating improved visual processing.

Use of consecutive transcutaneous oxygen measurement when assessing the need for revascularization and association with the outcomes of ischemic diabetic ulcers.

This study compared the ankle-brachial index (ABI) with transcutaneous oxygen pressure (TcPO2 ) in assessing peripheral vascular disease (PVD) prevalence in 100 diabetic foot ulcer (DFU) patients. Patients were categorized into vascular or nonvascular reconstruction groups and underwent both ABI and TcPO2 measurements four times over 6 months. Predictive validity for PVD diagnosis was analysed using the area under the receiver-operating characteristic curve (AUC). The study found TcPO2 to be a superior predictor of PVD than ABI. Among the DFU patients, 51 with abnormal TcPO2 values underwent vascular reconstruction. Only TcPO2 values showed significant pretreatment differences between the groups and increased post-reconstruction. These values declined over a 6-month follow-up, whereas ABI values rose. For those with end-stage renal disease (ESRD), TcPO2 values saw a sharp decrease within 3 months. Pre-reconstruction TcPO2 was notably lower in amputation patients versus limb salvage surgery patients. In conclusion, TcPO2 is more effective than ABI for evaluating ischemic limb perfusion and revascularization necessity. It should be prioritized as the primary follow-up tool, especially for ESRD patients.

USP33 enhances cell survival and stemness by deubiquitinating CTNNB1 in BXPC-3 and SW1990 cells.

Ubiquitin-specific protease 33 (USP33) has been implicated in various cancers, but its biological function and mechanism of action remain unknown in pancreatic cancer (PCa) as a deubiquitinating enzyme. Herein, we report that USP33 silencing inhibits PCa cell survival and self-renewal. USPs highly expressed in spherical PCa cells were screened by comparing the levels of ubiquitin-specific proteases in spherical PCa cells and adherent PCa cells. After silencing USP, the effect of USP on the proliferation of PCa cells was detected by CCK-8 and colony formation assay, and the effect of USP on cell stemness was detected by tumor sphere formation assay, flow analysis, and western blot analysis. The interaction of USP with CTNNB1 and the effect of USP on the ubiquitination of CTNNB1 were verified by coimmunoprecipitation assay. After replenishing CTNNB1, cell proliferation and cell stemness were examined. USP33 is upregulated in spheric BXPC-3, PCNA-1, and SW1990, compared with adherent BXPC-3, PCNA-1, and SW1990. USP33 interacts with CTNNB1, and stabilizes CTNNB1 by suppressing its degradation. Furthermore, cell proliferation, colony-forming, and self-renewal abilities of PCa cells in vitro, and the expression of stem cell markers EpCAM and CD44, C-myc, Nanog, and SOX2, were suppressed when USP33 was knocked down, which was reversed when CTNNB1 was ectopically expressed in PCa cells. Thus, USP33 promotes PCa cell proliferation and self-renewal by inhibiting the degradation of CTNNB1. USP33 inhibition may be a new treatment option for PCa patients.

Adenosine 2 receptor regulates autophagy and apoptosis to alleviate ischemia reperfusion injury in type 2 diabetes via IRE-1 signaling.

PURPOSE: This study aimed to determine the effect and mechanism of action of adenosine 2 receptor (A2R) activation on myocardial ischemia reperfusion injury (MIRI) under diabetic conditions. METHODS: MIRI type 2 diabetic rats and H9C2 cardiomyocytes were treated with A2R agonist and then subjected to hypoxia for 6 h and reoxygenation for 18 h. Myocardial damage, and infarct size were determined by cardiac ultrasound. Indicators of cardiomyocyte injury, creatine kinase-MB and cardiac troponin I were detected by Enzyme Linked Immunosorbent Assay. Endoplasmic reticulum stress (ERS) was determined through measuring the expression levels of ERS related genes GRP78, p-IRE1/IRE1, and p-JNKJNK. The mechanism of A2R cardio protection in MIRI through regulating ERS induced autophagy was determined by investigating the ER resident protein IRE-1. The ER-stress inducer Tunicamycin, and the IRE-1 inhibitor STF in combination with the A2R agonist NECA were used, and the cellular responses were assessed through autophagy proteins expression Beclin-1, p62, LC3 and apoptosis. RESULTS: NECA improved left ventricular function post MIRI, limited myocardial infarct size, reduced myocardial damage, decreased cardiomyocytes apoptosis, and attenuated ERS induced autophagy through regulating the IRE-XBP1s-CHOP pathway. These actions resulted into overall protection of the myocardium against MIRI. CONCLUSION: In summary, A2R activation by NECA prior to ischemia attenuates apoptosis, reduces ERS induced autophagy and restores left ventricular function. This protective effect occurs through regulating the IRE1-XBPs-CHOP related mechanisms. NECA is thus a potential target for the treatment of MIRI in patient with type 2 diabetes.

Multidisciplinary Strategies With Real-Time Fluorescence Images and Negative Pressure Wound Therapy to Manage Organ/Space Surgical Site Infection in Transplanted Kidneys.

BACKGROUND: Surgical site infection (SSI) after kidney transplantation can severely compromise graft function and prolong hospital stay. Organ/space SSI (osSSI) is a severe type of SSI associated with a significantly higher mortality rate. AIMS AND OBJECTIVES: This study aims to provide new strategies of managing (osSSI) after kidney transplant and other high-risk wound infections. METHOD: This is a single-center, retrospective study that analyzed the treatment outcomes of 4 patients who developed osSSI after kidney transplant at Shuang-Ho Hospital. The management strategy included real-time fluorescence imaging with MolecuLight, negative-pressure wound therapy (NPWT) with Si-Mesh, and incisional NPWT (iNPWT). RESULT: The average length of hospital stay was 18 days (range, 12-23 days). During hospitalization, all patients obtained high-quality debridement under real-time fluorescence image confirmation. The average duration of NPWT was 11.8 days (range, 7-17 days) and iNPWT was 7 days. All transplanted kidneys were preserved with normal function after 6 months of follow-up. CONCLUSIONS: Our strategies with real-time fluorescence imaging provide a novel and effective method that can be used in adjunct with the standard of care for managing osSSI after kidney transplantation. More studies are warranted to validate the efficacy of our approach.

Feasibility Study on the Classification of Persimmon Trees' Components Based on Hyperspectral LiDAR.

Intelligent management of trees is essential for precise production management in orchards. Extracting components' information from individual fruit trees is critical for analyzing and understanding their general growth. This study proposes a method to classify persimmon tree components based on hyperspectral LiDAR data. We extracted nine spectral feature parameters from the colorful point cloud data and performed preliminary classification using random forest, support vector machine, and backpropagation neural network methods. However, the misclassification of edge points with spectral information reduced the accuracy of the classification. To address this, we introduced a reprogramming strategy by fusing spatial constraints with spectral information, which increased the overall classification accuracy by 6.55%. We completed a 3D reconstruction of classification results in spatial coordinates. The proposed method is sensitive to edge points and shows excellent performance for classifying persimmon tree components.

Auxiliary signal-guided knowledge encoder-decoder for medical report generation.

Medical reports have significant clinical value to radiologists and specialists, especially during a pandemic like COVID. However, beyond the common difficulties faced in the natural image captioning, medical report generation specifically requires the model to describe a medical image with a fine-grained and semantic-coherence paragraph that should satisfy both medical commonsense and logic. Previous works generally extract the global image features and attempt to generate a paragraph that is similar to referenced reports; however, this approach has two limitations. Firstly, the regions of primary interest to radiologists are usually located in a small area of the global image, meaning that the remainder parts of the image could be considered as irrelevant noise in the training procedure. Secondly, there are many similar sentences used in each medical report to describe the normal regions of the image, which causes serious data bias. This deviation is likely to teach models to generate these inessential sentences on a regular basis. To address these problems, we propose an Auxiliary Signal-Guided Knowledge Encoder-Decoder (ASGK) to mimic radiologists' working patterns. Specifically, the auxiliary patches are explored to expand the widely used visual patch features before fed to the Transformer encoder, while the external linguistic signals help the decoder better master prior knowledge during the pre-training process. Our approach performs well on common benchmarks, including CX-CHR, IU X-Ray, and COVID-19 CT Report dataset (COV-CTR), demonstrating combining auxiliary signals with transformer architecture can bring a significant improvement in terms of medical report generation. The experimental results confirm that auxiliary signals driven Transformer-based models are with solid capabilities to outperform previous approaches on both medical terminology classification and paragraph generation metrics.

Study of extravisual resting-state networks in pituitary adenoma patients with vision restoration.

BACKGROUND: Pituitary adenoma (PA) may compress the optic apparatus, resulting in impaired vision. Some patients can experience improved vision rapidly after surgery. During the early period after surgery, however, the change in neurofunction in the extravisual cortex and higher cognitive cortex has yet to be explored. OBJECTIVE: Our study focused on the changes in the extravisual resting-state networks in patients with PA after vision restoration. METHODS: We recruited 14 patients with PA who experienced visual improvement after surgery. The functional connectivity (FC) of 6 seeds [auditory cortex (A1), Broca's area, posterior cingulate cortex (PCC) for the default mode network (DMN), right caudal anterior cingulate cortex for the salience network (SN) and left dorsolateral prefrontal cortex for the executive control network (ECN)] were evaluated. A paired t test was conducted to identify the differences between two groups of patients. RESULTS: Compared with their preoperative counterparts, patients with PA with improved vision exhibited decreased FC with the right A1 in the left insula lobule, right middle temporal gyrus and left postcentral gyrus and increased FC in the right paracentral lobule; decreased FC with the Broca in the left middle temporal gyrus and increased FC in the left insula lobule and right thalamus; decreased FC with the DMN in the right declive and right precuneus; increased FC in right Brodmann area 17, the left cuneus and the right posterior cingulate; decreased FC with the ECN in the right posterior cingulate, right angular and right precuneus; decreased FC with the SN in the right middle temporal gyrus, right hippocampus, and right precuneus; and increased FC in the right fusiform gyrus, the left lingual gyrus and right Brodmann area 19. CONCLUSIONS: Vision restoration may cause a response of cross-modal plasticity and multisensory systems related to A1 and the Broca. The DMN and SN may be involved in top-down control of the subareas within the visual cortex. The precuneus may be involved in the DMN, ECN and SN simultaneously.

Meta-analysis of association between migraine and risk of dementia.

OBJECTIVES: The association between migraine and dementia has rarely been investigated, and available results are conflicting. Thus, the aim of this meta-analysis was to evaluate whether an association exists between migraine and dementia. MATERIALS & METHODS: We searched for cohort studies from databases including PubMed, EBSCO, Web of Science, and EMBASE database from inception to April 1, 2021, using subject and free words. RevMan 5.1 software was used to calculate the risk ratio (RR) of dementia in patients with migraine. Subgroup and sensitivity analyses were conducted to assess the source of heterogeneity. A random-effects model was used when heterogeneity was present. The Funnel plot and Egger's test were used to evaluate publication bias. RESULTS: Five published cohort studies covering a total of 249,303 individuals were identified. Pooled analysis showed that migraine was associated with increased risk of all-cause dementia (RR: 1.34, 95% CI: 1.13-1.59) and Alzheimer's disease (AD) (RR: 2.49, 95% CI: 1.16-5.32). However, we did not found any association between migraine and risk of vascular dementia (VaD) (RR: 1.51, 95% CI: 0.77-2.96). CONCLUSIONS: Our results revealed that migraine was a potential risk indicator for AD and all-cause dementia.

Real-time augmented reality application in presurgical planning and lesion scalp localization by a smartphone.

OBJECTIVE: A smartphone augmented reality (AR) application (app) was explored for clinical use in presurgical planning and lesion scalp localization. METHODS: We programmed an AR App on a smartphone. The accuracy of the AR app was tested on a 3D-printed head model, using the Euclidean distance of displacement of virtual objects. For clinical validation, 14 patients with brain tumors were included in the study. Preoperative MRI images were used to generate 3D models for AR contents. The 3D models were then transferred to the smartphone AR app. Tumor scalp localization was marked, and a surgical corridor was planned on the patient's head by viewing AR images on the smartphone screen. Standard neuronavigation was applied to evaluate the accuracy of the smartphone. Max-margin distance (MMD) and area overlap ratio (AOR) were measured to quantitatively validate the clinical accuracy of the smartphone AR technique. RESULTS: In model validation, the total mean Euclidean distance of virtual object displacement using the smartphone AR app was 4.7 ± 2.3 mm. In clinical validation, the mean duration of AR app usage was 168.5 ± 73.9 s. The total mean MMD was 6.7 ± 3.7 mm, and total mean AOR was 79%. CONCLUSIONS: The smartphone AR app provides a new way of experience to observe intracranial anatomy in situ, and it makes surgical planning more intuitive and efficient. Localization accuracy is satisfactory with lesions larger than 15 mm.

Single-crystal ordered macroporous metal-organic framework as support for molecularly imprinted polymers and their integration in membrane formant for the specific recognition of zearalenone.

Zearalenone is a fungal contaminant that is widely present in grains. Here, a novel molecularly imprinted membrane based on SOM-ZIF-8 was developed for the rapid and highly selective identification of zearalenone in grain samples. The molecularly imprinted membrane was prepared using polyvinylidene fluoride, cyclododecyl 2,4-dihydroxybenzoate as a template and SOM-ZIF-8 as a carrier. The factors influencing the extraction of zearalenone using this membrane, including the solution pH, extraction time, elution solvent, elution time, and elution volume, were studied in detail. The optimized conditions were 5 mL of sample solution at pH 6, extraction time of 45 min, 4 mL of acetonitrile:methanol = 9:1 as elution solvent, and elution time of 20 min. This method displayed a good linear range of 12-120 ng/g (R2  = 0.998) with the limits of detection and quantification of this method are 1.7 and 5.5 ng/g, respectively. In addition, the membrane was used to selectively identify zearalenone in grain samples with percent recoveries ranging from 87.9 to 101.0% and relative standard deviation of less than 6.6%. Overall, this study presents a simple and effective chromatographic pretreatment method for detecting zearalenone in food samples.

EOESGC: predicting miRNA-disease associations based on embedding of embedding and simplified graph convolutional network.

BACKGROUND: A large number of biological studies have shown that miRNAs are inextricably linked to many complex diseases. Studying the miRNA-disease associations could provide us a root cause understanding of the underlying pathogenesis in which promotes the progress of drug development. However, traditional biological experiments are very time-consuming and costly. Therefore, we come up with an efficient models to solve this challenge. RESULTS: In this work, we propose a deep learning model called EOESGC to predict potential miRNA-disease associations based on embedding of embedding and simplified convolutional network. Firstly, integrated disease similarity, integrated miRNA similarity, and miRNA-disease association network are used to construct a coupled heterogeneous graph, and the edges with low similarity are removed to simplify the graph structure and ensure the effectiveness of edges. Secondly, the Embedding of embedding model (EOE) is used to learn edge information in the coupled heterogeneous graph. The training rule of the model is that the associated nodes are close to each other and the unassociated nodes are far away from each other. Based on this rule, edge information learned is added into node embedding as supplementary information to enrich node information. Then, node embedding of EOE model training as a new feature of miRNA and disease, and information aggregation is performed by simplified graph convolution model, in which each level of convolution can aggregate multi-hop neighbor information. In this step, we only use the miRNA-disease association network to further simplify the graph structure, thus reducing the computational complexity. Finally, feature embeddings of both miRNA and disease are spliced into the MLP for prediction. On the EOESGC evaluation part, the AUC, AUPR, and F1-score of our model are 0.9658, 0.8543 and 0.8644 by 5-fold cross-validation respectively. Compared with the latest published models, our model shows better results. In addition, we predict the top 20 potential miRNAs for breast cancer and lung cancer, most of which are validated in the dbDEMC and HMDD3.2 databases. CONCLUSION: The comprehensive experimental results show that EOESGC can effectively identify the potential miRNA-disease associations.

Association between Serum 25-Hydroxyvitamin D Level and Cognitive Impairment in Patients with White Matter Lesions: A Cross-Sectional Study.

OBJECTIVES: We aimed to observe the relationship between serum 25-hydroxyvitamin D (25-[OH] D) and different cognitive domains, and to evaluate the predictive value of 25-(OH) D level for cognitive impairment in patients with white matter lesions (WML). METHODS: The differences in clinical data including 25-(OH) D were analyzed between cognitive normality (n = 87) and impairment (n = 139) groups, and variant cognitive domains were analyzed between groups of different levels of serum 25-(OH) D. Risk factors for cognitive impairments were evaluated with multivariate logistic regression analysis; a receiver operating characteristic (ROC) curve of 25-(OH) D levels was used to examine the association between 25-(OH) D and WML with cognitive dysfunction. RESULTS: As the severity of WML increased, the proportion of patients with a low level of serum 25-(OH) D increased (p < 0.05). The total MoCA (Montreal Cognitive Assessment) scores and all domain scores except naming were significantly lower in patients with low levels of serum 25-(OH) D than in patients with high levels of serum 25-(OH) D (p < 0.05). Multivariate logistic regression analyses showed that serum 25-(OH) D levels were independently correlated with cognitive impairment. In the ROC analysis, the optimal cut-off value for 25-(OH) D was 17.53 with 76% sensitivity and 70% specificity (AUC =0.751, 95% CI: 0.674-0.819, p < 0.05). CONCLUSION: We observed that vitamin D deficiency is associated with multiple areas of cognitive impairment and that it is an independent risk factor for cognitive impairment in WML.

Predicting pituitary stalk position by in vivo visualization of the hypothalamo-hypophyseal tract in craniopharyngioma using diffusion tensor imaging tractography.

The pituitary stalk (PS) is crucial to endocrine function and water-electrolyte equilibrium. Preservation of the PS during craniopharyngioma (CP) surgery is critical; however, in a pathological state, it is difficult to identify. The hypothalamo-hypophyseal tract (HHT) connects the hypothalamus and the posterior pituitary gland and projects through the PS. Thus, visualization of the HHT can help locate the PS. Preoperative visualization of the neural fasciculus has been widely achieved using diffusion tensor imaging (DTI) tractography. Therefore, this study evaluated the use of DTI tractography to identify and characterize the human HHT. We used DTI tractography to track the HHT in 10 patients with CP and compared the location of the tract with the intraoperative view of the PS in these patients. We successfully tracked the HHT in nine patients, indicating that delineating and quantifying the tracked HHT using this method is feasible. In addition, we found that the tract was consistent with the intraoperative view of the PS in seven out of eight patients (87.50%). Finally, we found that the mean number of tracts was 7.11 ± 12.28, the mean fractional anisotropy (FA) was 0.11 ± 0.04, and the mean tract length was 24.22 ± 9.39 mm. Taken together, our results demonstrate that the HHT can be visualized and characterized with DTI even in a clinical application, which may aid in preoperative identification of the PS. Characterization of the tracked HHT with this technique could also be used to advance our understanding of the HHT.

Oncological miR-182-3p, a Novel Smooth Muscle Cell Phenotype Modulator, Evidences From Model Rats and Patients.

OBJECTIVE: Vascular smooth muscle cell (VSMC) phenotype change is a hallmark of vascular remodeling, which contributes to atherosclerotic diseases and can be regulated via microRNA-dependent mechanisms. We recently identified that asymmetrical dimethylarginine positively correlates to vascular remodeling-based diseases. We hypothesized that asymmetrical dimethylarginine induces smooth muscle cell (SMC) phenotypic change via a microRNA-dependent mechanism. APPROACH AND RESULTS: Microarray analysis enabled the identification of downregulation of miR-182-3p in asymmetrical dimethylarginine-treated human aortic artery SMCs. The myeloid-associated differentiation marker (MYADM) was identified as the downstream target of miR-182-3p and implicated to contribute to miR-182-3p knockdown-mediated SMC phenotype change, which was evidenced by the increased proliferation and migration and reduced expression levels of phenotype-related genes in human aortic artery SMCs through the ERK/MAP (extracellular signal-regulated kinase/mitogen-activated protein) kinase-dependent mechanism. When inhibiting MYADM in the presence of miR-182-3p inhibitor or overexpressing MYADM in the presence of pre-miR-182-3p, human aortic artery SMCs were reversed to the differentiation phenotype. In vivo, adeno-miR-182-3p markedly suppressed carotid neointimal formation by using balloon-injured rat carotid artery model, specifically via decreased MYADM expression, whereas adeno-miR-182-3p inhibitor significantly promoted neointimal formation. Atherosclerotic lesions from patients with high asymmetrical dimethylarginine plasma levels exhibited decreased miR-182-3p expression levels and elevated MYADM expression levels. CONCLUSIONS: miR-182-3p is a novel SMC phenotypic modulator by targeting MYADM.

Intraoperative Computed Tomography (CT) for Treating Giant Carotid Intracavernous Aneurysms.

BACKGROUND Giant carotid intracavernous aneurysm refers to those lesions larger than 2.5 cm and derived from a cavernous segment, accounting for about 30% of all intracranial tumors. Dynamic CT perfusion imaging (PCT) is a common method recently employed to evaluate cerebral perfusion. This study investigated the efficacy and clinical application of intraoperative CT in the surgery for giant symptomatic carotid intracavernous aneurysm. MATERIAL AND METHODS A retrospective analysis was performed on 23 cases with giant symptomatic carotid intracavernous aneurysm. BTO testing was performed before surgery. Differential treatments were performed based on the condition of aneurysm, and some patients received intraoperative PCT. Postoperative anti-coagulation was given with DSA or CTA follow-up examinations at 3-6 months, 1 year, and 2 years after surgery. RESULTS A total of 17 patients received aneurysm isolation coupled with high-flow bypass surgery. Among those, 9 developed early-onset neurological function after surgery, with gradual recover within 6 months. One coma patient died 25 months after discharge. One patient had aneurysm isolation with clapping of anterior communicating artery, and the other 5 cases received artery clapping only. In those patients, 4 had improvement at early phase, while 1 patient had numbness of the oculomotor nerve. Six patients received surgery in the CT room, including 5 cases with single proximal ligation of the internal carotid artery plus 1 aneurysm isolation combined with high-flow bypass surgery. CONCLUSIONS Intraoperative PCT can provide objective evidence and effective evaluation of cerebral perfusion.

Intraoperative Perfusion Computed Tomography in Carotid Endarterectomy: Initial Experience in 16 Cases.

BACKGROUND This study aimed to evaluate the changes in perfusion computed tomography (PCT) parameters in carotid endarterectomy (CEA), and to discuss the use of intraoperative PCT in CEA. MATERIAL AND METHODS Sixteen patients with carotid stenosis who also underwent CEA with intraoperative CT were recruited in this study. We calculated quantitative data on cerebral blood flow (CBF), cerebral blood volume (CBV), time to peak (TTP), and the relative parameter values, including relative CBF (rCBF), relative CBV (rCBV), and relative TTP (rTTP). The role of PCT was assessed and compared to conventional monitoring methods. RESULTS There were no significant differences in any of the parameters in the anterior cerebral artery (ACA) territory (P>0.05). In the middle cerebral artery (MCA) territory, the CBF and CBV increased and TTP decreased in the operated side during CEA; the rCBF and rCBV increased and the rTTP decreased significantly (P<0.05). In 16 patients, CT parameters were improved, SSEP was normal, and MDU was abnormal. In 3 patients, CBF increased by more than 70% during CEA. Relative PCT parameters are sensitive indicators for detecting early cerebral hemodynamic changes during CEA. Cerebral hemodynamics changed significantly in the MCA territory during CEA. CONCLUSIONS Intraoperative PCT could be an important adjuvant monitoring method in CEA.