Polystyrene nanoplastics induce lipophagy via the AMPK/ULK1 pathway and block lipophagic flux leading to lipid accumulation in hepatocytes.

Micro- and nanoplastic pollution has emerged as a significant global concern due to their extensive presence in the environment and potential adverse effects on human health. Nanoplastics can enter the human circulatory system and accumulate in the liver, disrupting hepatic metabolism and causing hepatotoxicity. However, the precise mechanism remains uncertain. Lipophagy is an alternative mechanism of lipid metabolism involving autophagy. This study aims to explore how polystyrene nanoplastics (PSNPs) influence lipid metabolism in hepatocytes via lipophagy. Initially, it was found that PSNPs were internalized by human hepatocytes, resulting in decreased cell viability. PSNPs were found to induce the accumulation of lipid droplets (LDs), with autophagy inhibition exacerbating this accumulation. Then, PSNPs were proved to activate lipophagy by recruiting LDs into autophagosomes and block the lipophagic flux by impairing lysosomal function, inhibiting LD degradation. Ultimately, PSNPs were shown to activate lipophagy through the AMPK/ULK1 pathway, and knocking down AMPK exacerbated lipid accumulation in hepatocytes. Overall, these results indicated that PSNPs triggered lipophagy via the AMPK/ULK1 pathway and blocked lipophagic flux, leading to lipid accumulation in hepatocytes. Thus, this study identifies a novel mechanism underlying nanoplastic-induced lipid accumulation, providing a foundation for the toxicity study and risk assessments of nanoplastics.

Experimental study on monitoring microwave ablation efficacy by real-time shear wave elastography in ex vivo porcine brain.

Objective: Glioma constitutes the most common primary malignant tumor in the central nervous system. In recent years, microwave ablation (MWA) was expected to be applied in the minimally invasive treatment of brain tumors. This study aims to evaluate the feasibility and accuracy of microwave ablation in ex vivo brain tissue by Shear Wave Elastography (SWE) to explore the application value of real-time SWE in monitoring the process of MWA of brain tissue.Methods: Thirty ex vivo brain tissues were treated with different microwave power and ablation duration. The morphologic and microscopic changes of MWA tissues were observed, and the diameter of the ablation areas was measured. In this experiment, SWE is used to quantitatively evaluate brain tissue's degree of thermal injury immediately after ablation.Results: This study It is found that the ablation range measured by SWE after ablation is in good consistency with the pathological range [ICCSWEL1-L1 = 0.975(95% CI:0.959 - 0.985), ICCSWEL2-L2 = 0.887(95% CI:0.779 - 0.938)]. At the same time, the SWE value after ablation is significantly higher than before (mean ± SD,9.88 ± 2.64 kPa vs.23.6 ± 13.75 kPa; p < 0.001). In this study, the SWE value of tissues in different pathological states was further analyzed by the ROC curve (AUC = 0.86), and the threshold for distinguishing normal tissue from tissue after ablation was 13.7 kPa. The accuracy of evaluating ablation tissue using SWE can reach 84.72%, providing data support for real-time quantitative observation of the ablation range.Conclusion: In conclusion the accurate visualization and real-time evaluation of the organizational change range of the MWA process can be realized by real-time SWE.

m6A and m5C modification of GPX4 facilitates anticancer immunity via STING activation.

Cancer immunotherapy is arguably the most rapidly advancing realm of cancer treatment. Glutathione peroxidase 4 (GPX4) has emerged as the vital enzyme to prevent lipid peroxidation and maintain cellular redox homeostasis. However, the mechanism of GPX4 in the regulation of cancer immunotherapy of colon adenocarcinoma (COAD) are incompletely understood. In pan-cancer analysis, we found that GPX4 showed remarkably upregulated expression and exhibited significant association with overall survival in multiple cancer types, especially COAD. Furthermore, upregulated GPX4 expression was positively correlated with increased immune cells infiltration and enhanced expression of immunomodulators. Mechanistically, RBM15B- and IGFBP2-mediated N6-methyladenosine (m6A) modification and NSUN5-mediated 5-methylcytosine (m5C) modification of GPX4 facilitated anticancer immunity via activation of cyclic GMP-AMP synthase (cGAS)-stimulator of interferon (STING) signaling by maintaining redox homeostasis in COAD. The risk model and nomogram model constructed based on the GPX4-derived genes further confirmed the prognostic and treatment-guiding value of GPX4. In all, our study demonstrated that m6A and m5C modification of GPX4 may be a promising target for cancer immunotherapy via activating the cGAS-STING signaling pathway in COAD.

A model for predicting lymph node metastasis of thyroid carcinoma: a multimodality convolutional neural network study.

Background: Early preoperative evaluation of cervical lymph node metastasis (LNM) in papillary thyroid carcinoma (PTC) is critical for further surgical treatment. However, insufficient accuracy in predicting LNM status for PTC based on ultrasound images is a problem that needs to be urgently resolved. This study aimed to clarify the role of convolutional neural networks (CNNs) in predicting LNM for PTC based on multimodality ultrasound. Methods: In this study, the data of 308 patients who were clinically diagnosed with PTC and had confirmed LNM status via postoperative pathology at Beijing Tiantan Hospital, Capital Medical University, from August 2018 to April 2022 were incorporated into CNN algorithm development and evaluation. Of these patients, 80% were randomly included into the training set and 20% into the test set. The ultrasound examination of cervical LNM was performed to assess possible metastasis. Residual network 50 (Resnet50) was employed for feature extraction from the B-mode and contrast-enhanced ultrasound (CEUS) images. For each case, all of features were extracted from B-mode ultrasound images and CEUS images separately, and the ultrasound examination data of cervical LNM information were concatenated together to produce a final multimodality LNM prediction. Sensitivity, specificity, accuracy, and area under the receiver operating characteristic curve (AUC) were used to evaluate the performance of the predictive model. Heatmaps were further developed for visualizing the attention region of the images of the best-working model. Results: Of the 308 patients with PTC included in the analysis, 158 (51.3%) were diagnosed as LNM and 150 (48.7%) as non-LNM. In the test set, when a triple-modality method (i.e., B-mode image, CEUS image, and ultrasound examination of cervical LNM) was used, accuracy was maximized at 80.65% (AUC =0.831; sensitivity =80.65%; specificity =82.26%), which showed an expected increased performance over B-mode alone (accuracy =69.00%; AUC =0.720; sensitivity =70.00%; specificity =73.00%) and a dual-modality method (B-mode image plus CEUS image: accuracy =75.81%; AUC =0.742; sensitivity =74.19%; specificity =77.42%). The heatmaps of our triple-modality model demonstrated a possible focus area and revealed the model's flaws. Conclusions: The PTC lymph node prediction model based on the triple-modality features significantly outperformed all the other feature configurations. This deep learning model mimics the workflow of a human expert and leverages multimodal data from patients with PTC, thus further supporting clinical decision-making.

Quantitative assessment of thenar to evaluate hand function after stroke by Bayes discriminant.

BACKGROUND: The incidence rate of stroke or cerebrovascular accidents ranks first in China. More than 85% of stroke patients have residual upper limb motor dysfunction, especially hand dysfunction. Normalizing the rehabilitation evaluation process and standard quantitative evaluation method is a complex and key point in rehabilitation therapy. The study aimed to establish a function model based on the Bayes discriminant by measuring the thenar stiffness with shear wave elastography (SWE) to quantitatively evaluate the hand motor function of hemiplegic patients after stroke. METHODS: This study collected 60 patients diagnosed with hemiplegia after stroke from October 2021 to October 2022. Therapists used the Brunnstrom assessment (BA)scale to divide the patients into the stage. All the patients underwent the measurement of SWE examination of abductor pollicis brevis (APB), opponens pollicis (OP), flexor pollicis long tendon (FPLT), and flexor pollicis brevis (FPB) by two sonographers. The SWE change rate of four parts of the thenar area was calculated prospectively with the non-hemiplegic side as the reference, the function equation was established by the Bayes discriminant method, and the evaluation model was fitted according to the acquired training set data. Lastly, the model was verified by self-validation, cross-validation, and external data validation methods. The classification performance was evaluated regarding the area under the ROC curve (AUC), sensitivity, and specificity. RESULTS: The median SWE values of the hemiplegic side of patients were lower than those of the non-hemiplegic side. According to the BA stage and SWER of APB, OP, FPLT, and FPB, our study established the Bayes discriminative model and validated it via self-validation and cross-validation methods. Then, the discriminant equation was used to validate 18 patients prospectively, the diagnostic coincidence rate was about 78.8%, and the misjudgment rate was approximately 21.2%. The AUC of the discriminant model for diagnosing BA stage I-VI was 0.928(95% CI: 0.839-1.0),0.858(95% CI: 0.748-0.969),1.0(95% CI: 1.0-1.0), 0.777(95% CI: 0.599-0.954),0.785(95% CI: 0.593-0.977) and 0.985(95% CI: 0.959-1.0), respectively. CONCLUSION: This Bayes discriminant model built by measuring thenar stiffness was of diagnostic value and can provide an objective basis for evaluating clinical rehabilitation.

Preoperative prediction of extrathyroidal extension: radiomics signature based on multimodal ultrasound to papillary thyroid carcinoma.

BACKGROUND: There is a recognized need for additional approaches to improve the accuracy of extrathyroidal extension (ETE) diagnosis in papillary thyroid carcinoma (PTC) before surgery. Up to now, multimodal ultrasound has been widely applied in disease diagnosis. We investigated the value of radiomic features extracted from multimodal ultrasound in the preoperative prediction of ETE. METHODS: We retrospectively pathologically confirmed PTC lesions in 235 patients from January 2019 to April 2022 in our hospital, including 45 ETE lesions and 205 non-ETE lesions. MaZda software was employed to obtain radiomics parameters in multimodal sonography. The most valuable radiomics features were selected by the Fisher coefficient, mutual information, probability of classification error and average correlation coefficient methods (F + MI + PA) in combination with the least absolute shrinkage and selection operator (LASSO) method. Finally, the multimodal model was developed by incorporating the clinical records and radiomics features through fivefold cross-validation with a linear support vector machine algorithm. The predictive performance was evaluated by sensitivity, specificity, accuracy, F1 scores and the area under the receiver operating characteristic curve (AUC) in the training and test sets. RESULTS: A total of 5972 radiomics features were extracted from multimodal sonography, and the 13 most valuable radiomics features were selected from the training set using the F + MI + PA method combined with LASSO regression. The multimodal prediction model yielded AUCs of 0.911 (95% CI 0.866-0.957) and 0.716 (95% CI 0.522-0.910) in the cross-validation and test sets, respectively. The multimodal model and radiomics model showed good discrimination between ETE and non-ETE lesions. CONCLUSION: Radiomics features based on multimodal ultrasonography could play a promising role in detecting ETE before surgery.

Biomechanical characteristics in the carotid artery: Noninvasive assessment using subharmonic emissions from microbubbles.

BACKGROUND: Stroke is closely related to carotid atherosclerotic plaques, which tend to occur in specific parts of the arteries, especially at the bifurcations, and are considered to be caused by biomechanical factors. Quantitative analysis of hemodynamic stress characteristics of the carotid sinus in vivo provides a mechanical basis for the development of atherosclerotic plaque in the carotid sinus. Previous studies found that ultrasound (US) contrast agent microbubbles would vibrate nonlinearly under the excitation of sound pressure, generating subharmonics (transmission fundamental frequency, i.e., f0 and subharmonic frequency at f0 /2), which have the highest sensitivity to pressure changes and exhibit an inverse linear relationship with environmental pressure. PURPOSE: This study employed subharmonic aided pressure estimation (SHAPE) technology to reflect carotid artery hydrodynamic characteristics in the carotid lumen. METHODS: From May 2021 to December 2021, this prospective study reviewed a total of 26 normal carotid arteries of 13 participants, all of whom received bilateral carotid artery routine US and SHAPE US examinations. During this study, the lumen of the bilateral distal segment of the common carotid artery (Distal-CCA), carotid artery bifurcation (CAB), and carotid bulb (CB) were scanned section by section from bottom to top in longitudinal and transverse sections. Subsequently, the subharmonic amplitudes in the lumen of normal carotid arteries were collected and analyzed. RESULTS: This study found that the amplitude of subharmonic amplitude in the carotid was distributed unevenly, with the amplitudes of subharmonic at the CAB being higher. Specifically, the subharmonic gradient of the carotid artery bifurcation apex plane was maximum (9.72 ± 4.31 dB), while the average subharmonic amplitude of the outer lateral layer of the carotid artery was higher (-56.40 ± 6.31 dB) (p < 0.001). CONCLUSION: The SHAPE technique is capable of indirectly reflecting the pressure changes of vascular system tissues, which may provide a new monitoring method for evaluating mechanical characteristics obviating invasion.

Application of decision tree algorithms to predict central lymph node metastasis in well-differentiated papillary thyroid carcinoma based on multimodal ultrasound parameters: a retrospective study.

Background: Prophylactic central neck dissection (pCND) in patients with well-differentiated primary papillary thyroid carcinoma (PTC) has become controversial. Several attempts have been made to predict central compartment lymph node metastasis (CLNM) based on clinical and conventional ultrasonic parameters. This study aimed to develop a decision tree (DT) model for predicting the risk of CLNM in patients with PTC based on clinical and preoperative multimodal ultrasound (US) characteristics. Methods: A total of 148 PTC nodules confirmed by surgical pathology at Beijing Tiantan Hospital were retrospectively analyzed. All nodules underwent multimodal US examinations preoperatively from January 2020 to September 2021. Correlation analysis of CLNM with clinical characteristics as well as multimodal US parameters of PTC lesions based on gray-scale US, color Doppler flow imaging (CDFI), superb microvascular imaging (SMI), contrast-enhanced ultrasound (CEUS), and shear wave elastography (SWE) technology was carried out. Finally, the chi-squared automatic interaction detector (CHAID) with a 10-fold cross-validation was used to establish DTs for CLNM prediction. The area under the curve was calculated to compare the predictive performance. Results: Univariate analysis indicated that CLNM was positively correlated with thyroglobulin level, maximum size, taller-than-wide, the number of microcalcifications greater than or equal to 5, contact capsule, abnormal cervical lymph node on conventional US, noncentripetal perfusion, delayed clearance, the average shear wave velocity (SWV mean), and the SWV ratio (P<0.05). The multimodal US DT based on taller-than-wide, contact capsule, abnormal cervical lymph node on conventional US, and centripetal enhancement as independent variables showed good discrimination: the sensitivity, specificity, accuracy, and area under the receiver operating characteristic curve were 80.0%, 76.7%, 78.4%, and 0.837 [95% confidence interval (CI): 0.771-0.902]. There was a significant difference between the multimodal and conventional US DTs (P=0.009). Conclusions: Our results indicated that the DT based on the preoperative multimodal US characteristics of PTCs has a reasonable predictive ability for CLNM and can be conveniently used for clinical decision-making of individualized treatment in patients with well-differentiated PTC.

Noninvasive assessment of carotid plaque with subharmonic aided pressure estimation from a US contrast agent: A preliminary study.

Stroke is closely associated with carotid plaques. The assessment of carotid plaque is still the key issue of stroke prevention in clinical practice. This prospective cross-sectional study included patients with carotid plaque evaluated by ultrasonography (US). The intima-media thickness (IMT), lumen stenosis severity, thickness, and length of carotid plaque were measured by the routine US, and the amplitudes of subharmonics in the upstream shoulder, top, and downstream shoulder of all plaques and corresponding lumens were observed by Subharmonic Aided Pressure Estimation (SHAPE) US examination from the US contrast agent perflubutane microbubbles (Sonazoid), which analyzed the clinical parameters of patients, the subharmonic amplitude characteristics of all plaques and lumens, and the parameter differences between the ischemic stroke (IS) group and control group. From May 2021 to February 2022, 46 carotid plaques of 23 patients were included. For plaques, the subharmonic amplitude in the plaque (-60.52 ± 4.46) was lower than that in the opposing level lumen (-56.82 ± 5.68 dB), the subharmonic gradient across the plaque cap was negatively correlated with plaque thickness (r = -0.51, p < 0.001), and with the lumen stenosis severity (r = -0.42, p = 0.003). The median IMT of the IS group was thicker than the control group. The subharmonic gradient of the intraplaque of the IS group was larger than the control group (p = 0.004). In this analysis, we use the receiver operating characteristic (ROC) curve to establish the cutoff value of the difference to predict a new monitoring method for plaque without invasion to predict IS. It still needs a large-scale study with long-term follow-up to validate these findings.

Silica Nanoparticles Trigger Chaperone HSPB8-Assisted Selective Autophagy via TFEB Activation in Hepatocytes.

Silica nanoparticles (SiNPs) are one of the most common inorganic nanomaterials. Autophagy is the predominant biological response to nanoparticles and transcription factor EB (TFEB) is a master regulator of the autophagy-lysosome pathway. Previous studies show that SiNPs induce autophagosome accumulation, yet the precise underlying mechanisms remain uncertain. The present study investigates the role of TFEB during SiNP-induced autophagy. SiNP-induced TFEB nuclear translocation is verified using immunofluorescence and western blot assay. The regulation of TFEB is proved to be via EIF2AK3 pathway. A TFEB knockout (KO) cell line is constructed to validate the TFEB involvement in SiNP-induced autophagy. The transcriptomes of wild-type and TFEB KO cells are compared using RNA-sequencing to identify genes of the TFEB-mediated autophagy and lysosome pathways affected by SiNPs. Based on these data and the Human Autophagy Database, four candidate autophagic genes are identified, including HSPB8, ATG4D, CTSB and CTSD. Specifically, that the chaperone HSPB8 is upregulated through SiNP-mediated TFEB activation and forms a chaperone-assisted selective autophagy (CASA) complex with BAG3 and HSC70, triggering HSPB8-assisted selective autophagy, is found. Thus, this study characterizes a novel mechanism underlying SiNP-induced autophagy that helps pave the way for further research on the toxicity and risk assessment of SiNPs.

Diagnostic performance of simplified TI-RADS for malignant thyroid nodules: comparison with 2017 ACR-TI-RADS and 2020 C-TI-RADS.

BACKGROUND: The aim of this study is to propose a new TI-RADS and compare it with the American College of Radiology (2017 ACR)-TI-RADS and the 2020 Chinese (2020 C)-TI-RADS. METHODS: A retrospective analysis of 749 thyroid nodules was performed. Based on the calculated odds ratio of ultrasonic signs between benign and malignant nodules, a new thyroid nodule score and malignancy rate were calculated. A receiver operating characteristic curve was drawn to analyze the new system's effectiveness in the differential diagnosis of benign and malignant thyroid nodules and was compared with the 2020 C-TI-RADS and 2017 ACR-TI-RADS. Five ultrasound physicians with different qualifications graded another 123 thyroid nodules according to the 2017ACR-TI-RADS, 2020 C-TI-RADS, and the newly proposed TI-RADS. Intergroup and intragroup consistency was evaluated using the Kappa test and intraclass correlation coefficient (ICC) test. RESULTS: 1) The new thyroid nodule score was divided into 0, 1, 2, 3, 4, and 5 points, with malignancy rates of 1.52%, 7.69%, 38.24%, 76.00%, 90.75%, and 93.75%, respectively. Using 3 points as the cutoff value to diagnose benign and malignant thyroid nodules, the sensitivity and specificity were 94.03% and 67.39%, respectively, which were higher than those of the 2017 ACR-TI-RADS and 2020 C-TI-RADS. The simplified TI-RADS, namely, sTI-RADS, was established as follows: sTI-RADS 3 (0 points), malignancy rate < 2%; sTI-RADS 4a (1 point), malignancy rate 2-10%; sTI-RADS 4b (2 points), malignancy rate 10-50%; sTI-RADS 4 (3 points), malignancy rate 50-90%; and sTI-RADS 5 (4 and 5 points), malignancy rate > 90%. 2) Five ultrasound doctors graded thyroid nodules by the 2017 ACR-TI-RADS, 2020C-TI-RADS and sTI-RADS. Intragroup consistency was good among all tests; ICC were 0.86 (0.82-0.90), 0.84 (0.78-0.88), and 0.88 (0.84-0.91), respectively, while only sTI-RADS had good intergroup consistency. CONCLUSION: In summary, we proposed a new TI-RADS, namely, sTI-RADS, which was obtained using a simple assignment method with higher specificity, accuracy, positive predictive value, and Youden index than the 2017 ACR-TI-RADS and 2020 C-TI-RADS.

Noninvasive assessment of intracranial pressure using subharmonic-aided pressure estimation: An experimental study in canines.

BACKGROUND: Intracranial hypertension is a common clinicopathological syndrome in neurosurgery, and a timely understanding of the intracranial pressure (ICP) may help guide clinical treatment. We aimed to investigate the correlation between subharmonic contrast-enhanced ultrasound (SHCEUS) parameters and ICP in experimental canines. METHODS: A dynamic model of ICP change from 11 mm Hg to 50 mm Hg was established in experimental canines by placing a latex balloon into the epidural space and injecting saline into the balloon. In addition, a pressure sensor was placed in the brain parenchyma to record the changes in ICP. When the ICP stabilized after each increase, subharmonic-aided pressure estimation (SHAPE) technology was performed to obtain the SHCEUS parameters, including the basal venous and adjacent intracranial arterial subharmonic amplitude and SHAPE gradient (subharmonic amplitude in the intracranial artery minus that in the basal vein). The correlation between these parameters and ICP was analyzed. RESULTS: The subharmonic amplitude of the basal vein was negatively correlated with the ICP (r = -0.798), and the SHAPE gradient was positively correlated with the ICP (r = 0.628). According to the guidelines for ICP monitoring in patients with traumatic brain injury, we defined 20 mm Hg, 25 mm Hg, and 30 mm Hg as the cutoff ICP levels. The area under the receiver operating characteristic curve of the basal venous subharmonic amplitude for diagnosing intracranial hypertension ≥20 mm Hg, ≥25 mm Hg, and ≥30 mm Hg was 0.867 (95% confidence interval [CI], 0.750-0.943), 0.884 (95% CI, 0.770-0.954), and 0.875 (95% CI, 0.759-0.948), respectively. The area under the receiver operating characteristic curve of the SHAPE gradient for diagnosing intracranial hypertension ≥20 mm Hg, ≥25 mm Hg, and ≥30 mm Hg was 0.839 (95% CI, 0.716-0.924), 0.842 (95% CI, 0.720-0.926), and 0.794 (95% CI, 0.665-0.890), respectively. CONCLUSION: SHCEUS parameters are correlated with ICP. The SHAPE technique can assist in evaluating ICP changes in canines, which provides a new idea and method for evaluating ICP.

Integrative proteomics and metabolomics approach to elucidate metabolic dysfunction induced by silica nanoparticles in hepatocytes.

Silica nanoparticles (SiNPs) are derived from manufactured materials and the natural environment, and they cause detrimental effects on human health via various exposure routes. The liver is proven to be a key target organ for SiNP toxicity; however, the mechanisms causing toxicity remain largely uncertain. Here, we investigated the effects of SiNPs on the metabolic spectrum in hepatocytes via integrative analyses of proteomics and metabolomics. First, a proteomic analysis was used to screen for critical proteins (including RPL3, HSP90AA1, SOD, PGK1, GOT1, and PNP), indicating that abnormal protein synthesis, protein misfolding, oxidative stress, and metabolic dysfunction may contribute to SiNP-induced hepatotoxicity. Next, metabolomic data demonstrated that SiNPs caused metabolic dysfunction by altering vital metabolites (including glucose, alanine, GSH, CTP, and ATP). Finally, a systematic bioinformatic analysis of protein-metabolite interactions showed that SiNPs disturbed glucose metabolism (glycolysis and pentose phosphate pathways, amino acid metabolism (alanine, aspartate, and glutamate), and ribonucleotide metabolism (purine and pyrimidine). These metabolic dysfunctions could exacerbate oxidative stress and lead to liver injury. Moreover, SOD, TKT, PGM1, GOT1, PNP, and NME2 may be key proteins for SiNP-induced hepatotoxicity. This study revealed the metabolic mechanisms underlying SiNP-induced hepatotoxicity and illustrated that integrative omics analyses can be a powerful approach for toxicity evaluations and risk assessments of nanoparticles.

Clinical Study of Ultrasonographic Risk Factors for Central Lymph Node Metastasis of Papillary Thyroid Carcinoma.

Background: Thyroid cancer is the most common malignancy of the endocrine system worldwide. Papillary thyroid cancer (PTC) is the most common pathologic type. The preoperative diagnosis of PTC and central lymph node metastasis (CLNM) or metastatic tendency is of great clinical significance to the diagnosis, treatment and prognosis of these patients. This study was conducted to investigate the correlation between ultrasound features and central CLNM of PTC. Methods: This study retrospectively analyzed patients who underwent PTC surgery and central lymph node dissection in the Department of Surgery, Beijing Tiantan Hospital, from January 2019 to February 2020. According to the inclusion and exclusion criteria, data from 136 patients were ultimately included, and the clinical and ultrasonic data of the patients were analyzed by multivariate regression to evaluate the correlation among grayscale ultrasound (US), superb microvascular imaging (SMI) and contrast-enhanced ultrasound (CEUS) features of thyroid nodules and CLNM of PTCs. Results: The multivariate analysis showed that tumor size, multifocality, microcalcification characteristics, SMI vascularization, and CEUS evaluation of contact with the adjacent capsule were correlated with PTC metastasis (P=0.008, P=0.001, P=0.028, P=0.041, and P< 0.001, respectively). Comparisons of the area under the ROC curves revealed that the area under the ROC curve of the degree of nodular invasion into the thyroid capsule was the largest (AUC: 0.754). The sensitivity and specificity for evaluating CLNM of PTC were 67.7% and 83.1%, respectively. Conclusions: Ultrasound characteristics of the following features are associated with a high risk of lymph node metastasis in PTCs: maximum diameter of nodules ≥1 cm, multifocality, ≥5 microcalcifications, abundant blood flow of SMI in nodules and nodule contact with the thyroid capsule ≥25% under CEUS. Ultrasound has clinical value in the preoperative evaluation of CLNM of PTCs.

Deep learning-based carotid plaque vulnerability classification with multicentre contrast-enhanced ultrasound video: a comparative diagnostic study.

OBJECTIVES: The aim of this study was to evaluate the performance of deep learning-based detection and classification of carotid plaque (DL-DCCP) in carotid plaque contrast-enhanced ultrasound (CEUS). METHODS AND ANALYSIS: A prospective multicentre study was conducted to assess vulnerability in patients with carotid plaque. Data from 547 potentially eligible patients were prospectively enrolled from 10 hospitals, and 205 patients with CEUS video were finally enrolled for analysis. The area under the receiver operating characteristic curve (AUC) was used to evaluate the effectiveness of DL-DCCP and two experienced radiologists who manually examined the CEUS video (RA-CEUS) in diagnosing and classifying carotid plaque vulnerability. To evaluate the influence of dynamic video input on the performance of the algorithm, a state-of-the-art deep convolutional neural network (CNN) model for static images (Xception) was compared with DL-DCCP for both training and holdout validation cohorts. RESULTS: The AUCs of DL-DCCP were significantly better than those of the experienced radiologists for both the training and holdout validation cohorts (training, DL-DCCP vs RA-CEUS, AUC: 0.85 vs 0.69, p<0.01; holdout validation, DL-DCCP vs RA-CEUS, AUC: 0.87 vs 0.66, p<0.01), that is, also better than the best deep CNN model Xception we had performed, for both the training and holdout validation cohorts (training, DL-DCCP vs Xception, AUC:0.85 vs 0.82, p<0.01; holdout validation, DL-DCCP vs Xception, AUC: 0.87 vs 0.77, p<0.01). CONCLUSION: DL-DCCP shows better overall performance in assessing the vulnerability of carotid atherosclerotic plaques than RA-CEUS. Moreover, with a more powerful network structure and better utilisation of video information, DL-DCCP provided greater diagnostic accuracy than a state-of-the-art static CNN model. TRIAL REGISTRATION NUMBER: ChiCTR1900021846.

Safety and efficacy of intravascular therapy in patients with progressive stroke caused by intracranial large vascular occlusion exceeding the time window of 24 hours.

PURPOSE: To compare endovascular and drug therapies for efficacy and safety in patients with a progressive stroke caused by intracranial large vascular occlusion exceeding the time window of 24 hours. PATIENTS AND METHODS: A total of 58 patients with progressive stroke caused by large intracranial vascular occlusion exceeding the time window of 24 hours treated in the stroke center of our hospital for three years were retrospectively analyzed . According to the applied therapy, 58 patients were divided into the endovascular (n = 19) and drug (n = 39) therapy groups. Then, modified Rankin scale (mRS) scores, symptomatic intracranial hemorrhage rates, mortality rates and adverse events were assessed in both groups within 90 days. RESULTS: The 90-day good prognosis rate was significantly higher in the endovascular therapy group compared with the drug group (68.4% VS 38.5%, odds ratio [OR] = 0.29; 95% confidence interval [CI], 0.09-0.92; P = 0.032). The 90-day NIHSS scores were lower in the endovascular therapy group compared with the drug group (3.3 ± 2.6 VS 5.2 ± 3.0, OR = -1.89; 95%CI, -3.50 to -0.27; P = 0.023). Meanwhile, the proportion of patients with a Barthel index of 90-100 was significantly higher in the endovascular therapy group compared with the drug group (53.0% VS 25.6%, OR = 0.31; 95%CI, 0.10-0.98; P = 0.042). Finally, both groups showed similar rates of adverse events. CONCLUSION: In patients with progressive stroke caused by large intracranial vascular occlusion exceeding 24 hours, endovascular therapy probably results in improved efficacy at 90 days compared with drug therapy, without increasing the rates of adverse effects.

Ultrasound-guided percutaneous needle biopsy skill for peripheral lung lesions and complications prevention.

BACKGROUND: To investigate puncture skills and complications prevention in ultrasound-guided percutaneous needle biopsy for peripheral lung lesions. METHODS: Ninety-two peripheral lung lesions in 92 patients, detected via computed tomography (CT) and also visible on ultrasound, were retrospectively analyzed. All patients underwent percutaneous peripheral lung lesion needle biopsy under traditional ultrasound or contrast enhanced ultrasound (CEUS) guidance paying attention to avoiding necrotic areas and large blood vessels. All the specimens were examined histopathologically. Preprocedure all 92 lesions were performed by traditional ultrasonography to evaluate the size, the echogenecity, liquefaction areas and blood flow on color Doppler imaging, some of which were performed by CEUS for evaluating non-enhanced necrosis areas, contrast agent arrival time (AT) and characteristics of blood perfusion. RESULTS: The histopathologic results of all 92 lesions were as follows: 67 malignant tumors (including 28 adenocarcinomas, 19 squamous cell carcinomas, 6 bronchoalveolar carcinomas, 5 small cell carcinomas, 5 metastatic cancers, 3 poorly differentiated cancers and 1 malignant mesothelioma), 20 benign lesions (including 9 pneumonia, 6 inflammatory pseudotumors and 5 tuberculomas), 5 undetermined lesions. Of 52 lesions by CEUS guidance, 7 lesions showed enhancement in the pulmonary arterial-phase (including 6 pneumonia and 1 malignant tumors), 45 lesions showed enhancement in the bronchial artery phase (including 37 malignant tumors, 3 inflammatory pseudotumors, 4 tuberculomas and 1 undetermined lesion). According to needle insertion angle along linear path, a total of 92 lesions were divided into two groups, 49 lesions at an angle of 70°-80° needle insertion and 43 lesions at an angle of 80°-90° needle insertion. In the study, linear and non-linear two puncture paths were used, we first tried to puncture along linear path in all lesions, if an attempt to insert into the lesions failed due to be blocked by the ribs and then changed to puncture along non-linear path instead. The success rate of biopsy procedure along linear puncture was significantly higher at an angle of 80°-90°group (93.0% vs. 20.4%, P<0.01), and the adoption rate of non-linear path biopsy for solving the puncture needle blocked by the ribs was significantly higher at angle of 70°-80°group (79.6% vs. 7.0%, P<0.01). Of 52 lesions by CEUS guidance, 27 (51.9%) showed non enhanced necrosis areas on CEUS, only 5 showed liquefaction necrosis areas on gray-scale ultrasound. Of 40 lesions by traditional ultrasound guidance, 4 showed necrosis areas on gray-scale ultrasound. There were no significant differences in lesion size, the average number of biopsy attempts and complication rates between CEUS guidance group and traditional ultrasound guidance group (P>0.05), the pathological confirmation rate in CEUS guidance group was higher than that in traditional ultrasound guidance group, but without significant difference (98.1% vs. 90.0%, P>0.05). Of all 92 cases, 3 cases (3.3%) had mild pneumothorax and 4 cases (4.3%) had hemoptysis. CONCLUSIONS: In ultrasound-guided needle biopsy for peripheral lung lesions, using a combination of linear and non-linear puncture techniques and keeping away from necrotic areas and large blood vessels, may help to increase the success rate and reduce the incidence of complications further.

Evaluation of a deep learning-based computer-aided diagnosis system for distinguishing benign from malignant thyroid nodules in ultrasound images.

PURPOSE: Computer-aided diagnosis (CAD) systems assist in solving subjective diagnosis problems that typically rely on personal experience. A CAD system has been developed to differentiate malignant thyroid nodules from benign thyroid nodules in ultrasound images based on deep learning methods. The diagnostic performance was compared between the CAD system and the experienced attending radiologists. METHODS: The ultrasound image dataset for training the CAD system included 651 malignant nodules and 386 benign nodules while the database for testing included 422 malignant nodules and 128 benign nodules. All the nodules were confirmed by pathology results. In the proposed CAD system, a support vector machine (SVM) is used for classification and fused features which combined the deep features extracted by a convolutional neural network (CNN) with the hand-crafted features such as the histogram of oriented gradient (HOG), local binary patterns (LBP), and scale invariant feature transform (SIFT) were obtained. The optimal feature subset was formed by selecting these fused features based on the maximum class separation distance and used as the training sample for the SVM. RESULTS: The accuracy, sensitivity, and specificity of the CAD system were 92.5%, 96.4%, and 83.1%, respectively, which were higher than those of the experienced attending radiologists. The areas under the ROC curves of the CAD system and the attending radiologists were 0.881 and 0.819, respectively. CONCLUSIONS: The CAD system for thyroid nodules exhibited a better diagnostic performance than experienced attending radiologists. The CAD system could be a reliable supplementary tool to diagnose thyroid nodules using ultrasonography. Macroscopic features in ultrasound images, such as the margins and shape of thyroid nodules, could influence the diagnostic efficiency of the CAD system.

Iron Metabolism and Ferroptosis in Epilepsy.

Epilepsy is a disease characterized by recurrent, episodic, and transient central nervous system (CNS) dysfunction resulting from an excessive synchronous discharge of brain neurons. It is characterized by diverse etiology, complex pathogenesis, and difficult treatment. In addition, most epileptic patients exhibit social cognitive impairment and psychological impairment. Iron is an essential trace element for human growth and development and is also involved in a variety of redox reactions in organisms. However, abnormal iron metabolism is associated with several neurological disorders, including hemorrhagic post-stroke epilepsy and post-traumatic epilepsy (PTE). Moreover, ferroptosis is also considered a new form of regulation of cell death, which is attributed to severe lipid peroxidation caused by the production of reactive oxygen species (ROS) and iron overload found in various neurological diseases, including epilepsy. Therefore, this review summarizes the study on iron metabolism and ferroptosis in epilepsy, in order to elucidate the correlation between iron and epilepsy. It also provides a novel method for the treatment, prevention, and research of epilepsy, to control epileptic seizures and reduce nerve injury after the epileptic seizure.

SPARC Knockdown Reduces Glutamate-Induced HT22 Hippocampal Nerve Cell Damage by Regulating Autophagy.

Secreted protein acidic and rich in cysteine (SPARC) is a matricellular protein involved in the extracellular matrix and interactions between cells during neural development of the central nervous system (CNS). Oxidative glutamate toxicity is involved in CNS diseases, including epilepsy, Alzheimer's disease, and ischemic stroke. However, the molecular mechanism of nerve injury is not fully understood in CNS diseases. Herein, the glutamate-induced nerve damage model was used to explore the molecular mechanisms affecting nerve damage. The levels of SPARC and autophagy were increased in glutamate-induced HT22 hippocampal nerve injury. In summary, the current study confirmed that SPARC regulates autophagy in HT22 hippocampal nerve cells, and its knockdown reduces the glutamate-induced HT22 hippocampal nerve injury by inhibiting autophagy. These findings suggested that SPARC plays a crucial role in nerve injury of CNS diseases.