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This study aimed to evaluate the diagnostic value of ultrahigh-field magnetic resonance imaging (MRI) for brain tumors in clinical practice.Thirty patients with brain tumors underwent 7- and 3-T MRI. The performance and diagnostic confidence of 7- and 3-T MRI in the visualization of tumor details such as internal structure and feeding artery were evaluated by radiologists. Contrast-enhanced region performance and tumor detail diagnostic confidence score (DCS) were calculated and compared between 7 and 3T using Wilcoxon rank sum test.In 19 with obvious enhancement and 11 cases without obvious enhancement, 7- and 3-T MRI showed similar performance. The tumors' internal structure and feeding artery were more clearly depicted by 7-T MRI (62.2% and 54.4%, respectively) than by 3-T MRI (2.2% and 6.7%, respectively). Furthermore, the mean DCSs of both internal structure and feeding artery were higher at 7T than at 3T (internal structure: 16.29 ± 9.67 vs. -5.79 ± 4.12, p = 0.028; feeding artery: 21.96 ± 6.93 vs. 4.46 ± 7.07, p = 0.028). The DCS was more significantly improved in the senior radiologist group.Better visualization of brain tumor details and higher tumor detail diagnostic confidence can be obtained with 7-T MRI.

The coronary atherosclerotic heart disease is a common cardiovascular disease with high morbidity, disability, and societal burden. Early, precise, and comprehensive diagnosis of the coronary atherosclerotic heart disease is of great significance. The rise of artificial intelligence technologies, represented by machine learning and deep learning, provides new methods to address the above issues. In recent years, artificial intelligence has achieved an extraordinary progress in multiple aspects of coronary atherosclerotic heart disease diagnosis, including the construction of intelligent diagnostic models based on artificial intelligence algorithms, applications of artificial intelligence algorithms in coronary angiography, coronary CT angiography, intravascular imaging, cardiac magnetic resonance, and functional parameters. This paper presents a comprehensive review of the technical background and current state of research on the application of artificial intelligence in the diagnosis of the coronary atherosclerotic heart disease and analyzes recent challenges and perspectives in this field.

Magnetic resonance-guided focused ultrasound (MRgFUS) has brought thalamotomy back to the frontline for Essential Tremor (ET). As functional organization of human brain strictly follows hierarchical principles which are frequently deficient in neurological diseases, whether additional damage from MRgFUS thalamotomy induces further disruptions of ET functional scaffolds are still controversial. This study was to examine the alteration features of brain functional frameworks following MRgFUS thalamotomy in patients with Essential Tremor (ET). We retrospectively obtained preoperative (ETpre) and postoperative 6-month (ET6m) data of 30 ET patients underwent MRgFUS thalamotomy from 2018 to 2020. Their archived functional MR images were used to functional gradient comparison. Both supervised pattern learning and stepwise linear regression were conducted to associate gradient features to tremor symptoms with additional neuropathophysiological analysis. MRgFUS thalamotomy relieved 78.19% of hand tremor symptoms and induced vast global framework alteration (ET6m vs. ETpre: Cohen d = -0.80, P < 0.001). Multiple robust alterations were identified especially in posterior cingulate cortex (ET6m vs. ETpre: Cohen d = 0.87, P = 0.048). Compared with matched health controls (HCs), its gradient distances to primary communities were significantly increased in ETpre patients with anomalous stepwise connectivity (P < 0.05 in ETpre vs. HCs), which were restored after MRgFUS thalamotomy. Both global and regional gradient features could be used for tremor symptom prediction and were linked to neuropathophysiological features of Parkinson disease and oxidative phosphorylation. MRgFUS thalamotomy not only suppress tremor symptoms but also rebalances atypical functional hierarchical architecture of ET patients.

Contemporary techniques for repair of acute anterior cruciate ligament (ACL) rupture have been receiving renewed interest recently because of reports of good outcomes.A literature search of PUBMED, MEDLINE, EMBASE, and the Cochrane Library was performed in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Only RCTs published in English and comparing clinical outcomes of ACL repair versus reconstruction were included. Outcomes were evaluated using the International Knee Documentation Committee subjective score, Lysholm score, Tegner activity scale, visual analog scale pain score, anterior laxity, Lachman test, hop tests, knee injury and osteoarthritis outcome score, extension deficit, revision rate, and re-rupture rate. Statistical analysis was performed with Review Manager 5.4 and Stata 14.0. Two-tailed P .05 was considered statistically significant.Four RCTs (with a total of 293 patients) that met the eligibility criteria were included in this review. Over short-term follow-up, none of the studies found significant differences between the repair groups and reconstruction groups with respect to International Knee Documentation Committee, Lysholm, Tegner, visual analog scale, anterior laxity, Lachman test, re-rupture rate, extension deficit, and performance of 3 hop tests (P .05). In both groups, the hop tests scores were90%.ACL repair and ACL reconstruction appear to provide comparable short-term outcomes. The low revision rate after primary repair is encouraging. For patients with ACL injury, current repair techniques such as dynamic intraligamentary stabilization and bridge-enhanced ACL repair may be an effective alternative to reconstruction.

Since apoptosis of foam, cells can induce plaque instability, reducing intracellular lipid content while protecting foam cells from apoptosis is beneficial for the safe and efficient therapy of atherosclerosis. In this study, osteopontin-coupled polydopamine (PDA-OPN) nanoparticles were synthesized and applied to target mild photothermal therapy (PTT) of atherosclerosis. The results from laser confocal microscopy indicate that PDA-OPN nanoparticles can be specially recognized and absorbed by foam cells. Under near-infrared laser irradiation, the mild photothermal generated by PDA-OPN decreases intracellular lipid accumulation but does not induce cell apoptosis. In vivo treatments demonstrate that mild PTT can substantially reduce plaque area and improve plaque stability by upregulating the expression of plaque fibrosis in ApoE−/− mice. Our findings reinforce that the PDA-OPN nanoparticle-mediated mild PTT can inhibit atherosclerotic progression, which provides new insights for developing safe and effective treatment methods for atherosclerosis.

In this paper, a two-way fluid-structure coupling model is developed to simulate and analyze the hemodynamic process based on dynamic coronary angiography, and examine the influence of different hemodynamic parameters on coronary arteries in typical coronary stenosis lesions. Using the measured FFR pressure data of a patient, the pressure-time function curve is fitted to ensure the accuracy of the boundary conditions. The average error of the simulation pressure results compared to the test data is 6.74%. In addition, the results related to blood flow, pressure contour and wall shear stress contour in a typical cardiac cycle are obtained by simulation analysis. These results are found to be in good agreement with the laws of the real cardiac cycle, which verifies the rationality of the simulation. In conclusion, based on the modeling and hemodynamic simulation analysis process of dynamic coronary angiography, this paper proposes a method to assist the analysis and evaluation of coronary hemodynamic and functional parameters, which has certain practical significance.

Circular RNAs (circRNAs) are an intriguing class of RNAs with covalently closed-loop structures. With characteristics of high stability and disease-specific expression, circRNAs are emerging as ideal targets for cancer therapy. However, the screening utility and clinical value of circRNAs in gastric cancer (GC) remain largely elusive. We detected levels of hsa_circ_0001020 in cell lines and tissue and plasma samples and investigated its clinicopathological correlations. Kaplan-Meier survival curves and regression analyses were used to analyze its prognostic value. Receiver operating characteristic curves and biomarker combinations were examined to verify its screening value. Bioinformatics analysis was also performed to predict potential biological functions. Our tests found that hsa_circ_0001020 was significantly upregulated in GC cell lines, GC tissue samples, and even in plasma. High hsa_circ_0001020 expression levels in GC tissues were significantly associated with distal metastasis and blood carbohydrate antigen 19-9 (CA19-9). GC patients with high hsa_circ_0001020 had a lower overall survival and disease-free survival time than the low levels. Regression analysis suggested that the level of hsa_circ_0001020 expression was an independent prognostic factor for survival time. As a biomarker for GC, hsa_circ_0001020 showed a superior AUC, sensitivity, and specificity than carcinoembryonic antigen and CA19-9, and was suitable for combination with clinical tumor biomarkers. Bioinformatics analysis provided valuable clues for the possible oncogenic pathways of GC, such as the FoxO and p53 signaling pathways. In conclusion, our study found that hsa_circ_0001020 in GC could be a reliable biomarker to screen for GC and predict prognosis.

MRI-guided focused ultrasound (MRgFUS) thalamotomy is a novel, effective, and non-invasive treatment for essential tremor (ET). However, the network mediating MRgFUS in treating ET is not precisely known. This study aimed to identify the disease-specific network associated with the therapeutic effects of MRgFUS thalamotomy on ET and investigate its regional characteristics and genetic signatures to gain insights into the neurobiological mechanism of ET and MRgFUS thalamotomy. Twenty-four ET patients treated with MRgFUS thalamotomy underwent resting-state functional MRI at baseline and postoperative 6 months to measure the fractional amplitude of low-frequency fluctuation (fALFF). Ordinal trends canonical variates analysis (OrT/CVA) was performed on the within-subject fALFF data to identify the ET-related network. Genetic functional enrichment analysis was conducted to study the genetic signatures of this ET-related network using brain-wide gene expression data. OrT/CVA analysis revealed a significant ET-related network for which subject expression showed consistent increases after surgery. The treatment-induced increases in subject expression were significantly correlated with concurrent tremor improvement. This network was characterized by increased activity in the sensorimotor cortex and decreased activity in the posterior cingulate cortex. It was correlated with an expression map of a weighted combination genes enriched for mitochondria relevant ontology terms. This study demonstrates that the therapeutic effects of MRgFUS thalamotomy on ET are associated with modulating a distinct ET-related network which may be driven by mitochondria relevant neurobiological mechanism. Quantification of treatment-induced modulation on the ET-related network can provide an objective marker for evaluating the efficacy of MRgFUS thalamotomy.

OBJECTIVE Although magnetic resonance–guided focused ultrasound (MRgFUS) at the ventral intermediate (VIM) thalamic nucleus is a novel and effective treatment for medication-refractory essential tremor (ET), it is unclear how the ablation lesion affects functional activity. The current study sought to evaluate the functional impact of MRgFUS thalamotomy in patients with ET, as well as to investigate the relationship between neuronal activity changes and tremor control. METHODS This study included 30 patients with ET who underwent MRgFUS thalamotomy with a 6-month follow-up involving MRI and clinical tremor rating. Additional sex- and age-matched healthy people were recruited for the healthy control group. The fractional amplitude of low-frequency fluctuation (fALFF) and regional homogeneity were used to identify functional alteration regions of interest (ROIs). To investigate changes after treatment, ROI- and seed-based functional connectivity (FC) analyses were performed. RESULTS Patients with ET had significantly increased fALFF in the right postcentral gyrus (PoCG; ROI 1), regional homogeneity in the left PoCG (ROI 2), and regional homogeneity in the right PoCG (ROI 3, cluster-level p value family-wise error [pFWE] < 0.05), which were recovered and normalized at 6 months after MRgFUS thalamotomy. FCs between ROI 2 and the right supramarginal gyrus, ROI 2 and the right superior parietal gyrus, and ROI 3 and the left precentral gyrus were also found to be increased after treatment (cluster-level pFWE < 0.05). Furthermore, changes in fALFF, regional homogeneity, and FC values were significantly correlated with tremor relief (p < 0.05). Preoperative FC strengths were found to be inversely related to the postoperative tremor control ratio (p < 0.05). CONCLUSIONS In patients with ET, the VIM lesion of MRgFUS thalamotomy resulted in symptom-related regional functional recovery associated with sensorimotor and attention networks. Preoperative FC strengths may reflect the postoperative tremor control ratio, implying that this metric could be a useful neuroimaging biomarker for predicting symptom relief in patients with ET following thalamotomy.

To provide an available diagnostic model for diagnosing coronary atherosclerotic heart disease to provide an auxiliary function for doctors, we proposed a new evolutionary classification model in this paper. The core of the prediction model is a kernel extreme learning machine (KELM) optimized by an improved salp swarm algorithm (SSA). To get a better subset of parameters and features, the space transformation mechanism is introduced in the optimization core to improve SSA for obtaining an optimal KELM model. The KELM model for the diagnosis of coronary atherosclerotic heart disease (STSSA-KELM) is developed based on the optimal parameters and a subset of features. In the experiment, STSSA-KELM is compared with some widely adopted machine learning methods (MLM) in coronary atherosclerotic heart disease prediction. The experimental results show that STSSA-KELM can realize excellent classification performance and more robust stability under four indications. We also compare the convergence of STSSA-KELM with other MLM, the STSSA-KELM model has demonstrated a higher classification performance. Therefore, the STSSA-KELM model can effectively help doctors to diagnose coronary heart disease.