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Infections of the central nervous system (CNS) are potentially life-threatening and can cause serious morbidity. We evaluated the clinical value of metagenomic next-generation sequencing (mNGS) in the diagnosis of infectious encephalitis and meningitis and explored the factors affecting the results of mNGS. Patients with suspected cases of encephalitis or meningitis who presented in Northern Jiangsu People's Hospital from 1 March 2018 to 30 September 2022 were collected. Demographic, historical, and clinical information were obtained, and cerebrospinal fluid (CSF) samples were treated with mNGS. The pathogen was identified using National Center for Biotechnology Information (NCBI) GenBank sequence data. Ninety-six patients were screened and finally 90 subjects enrolled. Of the 90 enrolled cases, 67 (74.4%) were diagnosed with central nervous system infections, which included 48 cases (71.6%) of viral infection, 11 (12.2%) of bacterial infection, 5 (7.5%) of mycobacterium tuberculosis, 2 (3.0%) of fungal infection, and 1 (1.5%) of rickettsia infection. From these cases, mNGS identified 40 (44.4%) true-positive cases, 3 (3.3%) false-positive case, 22 (24.4%) true-negative cases, and 25 (27.8%) false-negative cases. The sensitivity and specificity of mNGS were 61.5% and 88%, respectively. mNGS of CSF could show a higher positive rate in patients with marked CSF abnormalities, including elevated protein concentrations and monocyte counts. mNGS of CSF is an effective method for detecting infectious encephalitis and meningitis, and the results should be analyzed combined with conventional microbiological testing results. [ABSTRACT FROM AUTHOR]

Summary: This article focuses on the fast finite‐time adaptive tracking control for non‐strict feedback stochastic nonlinear systems. Random disturbances with constraints have rarely been considered in previous studies of fast finite‐time stabilization problems. The corresponding extension of the adaptive fast finite‐time stabilization mechanism to stochastic nonlinear systems with full‐state constraints is one of the innovations of this article. First, neural networks and barrier Lyapunov functions are utilized to handle the problems arising from the unknown nonlinear terms and the state constraints, respectively. Second, an adaptive fast finite‐time tracking control scheme for stochastic systems is designed based on the backstepping technique and a fast finite‐time control strategy, which allows all signals of the closed‐loop system to be bounded. Meanwhile, the designed controller guarantees a fast convergence of the tracking error to a small neighborhood of the origin under full‐state constraints. Finally, two examples are given to illustrate the feasibility of the proposed method. [ABSTRACT FROM AUTHOR]

It is necessary to identify takeover behavior patterns of conditional autonomous driving. In this paper, using driving simulations, takeover request lead time (5 s and 10 s) and nondriving-related tasks (working task and entertainment task) are designed to study the takeover behavior pattern in crash scenarios. Through driving simulation experiment, the number of takeover behavior patterns is eleven and the number of first takeover behaviors is three. Results showed that the first takeover behavior has a significant impact on the first takeover reaction time, speed, lateral offset, and minimum TTC, but the first takeover behavior has no significant effect on the takeover correct time. The takeover request lead time (TORlt) has a significant impact on the pattern and the first takeover behavior, while the non-driving-related task (NDRT) has no significant effect on the pattern and the first takeover behavior. In addition, this paper constructs a maps of takeover operation behavior, which more intuitively shows the behavior changes during a takeover. [ABSTRACT FROM AUTHOR]

Objective: To investigate the diagnostic performance of contrast-enhanced ultrasound (CEUS) in the differentiation of primary thyroid lymphoma (PTL) and nodular Hashimoto's thyroiditis (NHT) in patients with background of heterogeneous diffuse Hashimoto's thyroiditis (HT). Methods: Sixty HT patients with 64 thyroid nodules (31 PTL and 33 NHT) who had undergone CEUS examination were included in this study. With histopathological results as the reference, we evaluated the imaging features of each nodule on both conventional ultrasonography (US) and CEUS. Quantitative CEUS parameters including peak intensity (PI), time to peak (TTP), and area under the time–intensity curve (AUC) were gathered in the nodule and background parenchyma. The ratio indexes of theses parameters were calculated by the ratio of the lesion and the corresponding thyroid parenchyma. Logistic regression and receiver operating characteristic (ROC) curves analyses of valuable US indicators were further preformed to evaluate the diagnostic capability of CEUS in discrimination of PTL and NHT. Results: Among all the observed US imaging features and CEUS parameters, 10 indicators showed significant differences between PTL and NHT (all P < 0.05). All the significant indicators were ranked according to the odds ratios (ORs). Eight of them were CEUS associated including imaging features of enhancement pattern, degree, homogeneity, and quantification parameters of PI, AUC, ratios of PI, AUC, and TTP, while indicators on conventional US, including vascularity and size ranked the last two with ORs less than 3. The five single CEUS parameters showed good diagnostic performance in diagnosis of PTL with areas under ROC curves of 0.72–0.83 and accuracies of 70.3–75.0%. The combination of CEUS imaging features and the ratios of PI, AUC, and TTP demonstrated excellent diagnostic efficiency and achieved area under ROC curve of 0.92, which was significantly higher than any of the five single parameters (all P < 0.05), with a sensitivity of 83.9%, specificity of 87.9%, and accuracy of 85.9%. Conclusions: CEUS is an efficient diagnostic tool in the differential diagnosis of PTL and NHT for patients with diffuse HT. Conjoint analysis of CEUS imaging features and quantification parameters could improve the diagnostic values. [ABSTRACT FROM AUTHOR]

Objective: This retrospective study aimed to analyze the ultrasound (US) imaging features of solitary papillary thyroid carcinoma (PTC) located in the isthmus and to assess the risk factors for lymph node metastasis (LNM) and tumor capsular invasion. Methods: We included a total of 135 patients with solitary PTC located in the isthmus. All the cases underwent US, total thyroidectomy, and prophylactic central lymph node dissection. Patients' demographic and thyroid isthmus nodules' US characteristics, as well as risk factors associated with LNM and tumor capsular invasion, were analyzed. Results: It was revealed that the occurrence of LNM was higher in male patients than in female patients (P < 0.001). As risk factors, the size of PTC in the isthmus was found to be associated with LNM and tumor capsular invasion (P = 0.005 and 0.000, respectively). The area under the receiver operating characteristic curve (AUC) of the size of the isthmus PTC was 0.64 [95% confidence interval (CI) = 0.55–0.72], indicating a probability for LNM. The AUC value for tumor capsular invasion was 0.77 (95% CI: 0.68–0.83). When the threshold was set to 1.1 cm, the larger size indicated that there was a probability of occurrence of LNM with sensitivity and specificity of 47.4 and 73.7%, respectively. When the threshold was set to 0.7 cm, the larger size indicated that there was potentially a tumor capsular invasion, with sensitivity and specificity of 80.6 and 56.3%, respectively. Wider-than-tall nodules were found to be significantly different from those in LNM and tumor capsular invasion (P = 0.038 and 0.030, respectively). There were significant differences in tumor capsular invasion in extrathyroidal extension (ETE) compared with smooth or ill-defined and lobulated or irregular nodules (P = 0.017). Conclusions: This study showed that the incidence of LNM in male patients was higher than that in female ones. When a US image shows a thyroid isthmus nodule with a wider-than-tall shape, LNM and tumor capsular invasion were likely to occur. When a US image shows a thyroid isthmus nodule with an ETE, tumor capsular invasion was likely to occur. ETE and wider-than-tall may be indicators of FNA under US guidance, even though the size of thyroid isthmus nodule may be <1 cm. [ABSTRACT FROM AUTHOR]

Background: Static shear wave elastography (SWE) is used to detect breast lesions, but slice and plane selections result in discrepancies.Objective: To evaluate the intraobserver reproducibility of continuous SWE, and whether quantitative elasticities in orthogonal planes perform better in the differential diagnosis of breast lesions.Method: One hundred and twenty-two breast lesions scheduled for ultrasound-guided biopsy were recruited. Continuous SWE scans were conducted in orthogonal planes separately. Quantitative elasticities and histopathology results were collected. Reproducibility in the same plane and diagnostic performance in different planes were evaluated.Results: The maximum and mean elasticities of the hardest portion, and standard deviation of whole lesion, had high inter-class correlation coefficients (0.87 to 0.95) and large areas under receiver operation characteristic curve (0.887 to 0.899). Without loss of accuracy, sensitivities had increased in orthogonal planes compared with single plane (from 73.17% up to 82.93% at most). Mean elasticity of whole lesion and lesion-to-parenchyma ratio were significantly less reproducible and less accurate.Conclusion: Continuous SWE is highly reproducible for the same observer. The maximum and mean elasticities of the hardest portion and standard deviation of whole lesion are most reliable. Furthermore, the sensitivities of the three parameters are improved in orthogonal planes without loss of accuracies. [ABSTRACT FROM AUTHOR]

This article presents a comparative analysis of particle swarm optimisation (PSO), self-organising hierarchical particle swarm optimiser (HPSO) and self-organising hierarchical particle swarm optimiser with time-varying acceleration coefficients (HPSO-TVAC) for data clustering. Through experiments on six well-known benchmarks, we find that the HPSO and the HPSO-TVAC algorithms have better performance than the PSO algorithm in most cases, and all the clustering algorithms using PSO have good performance for large-scale data and high-dimensional data, especially the two algorithms proposed in this article. Furthermore, we have also observed that the convergence of the HPSO and the HPSO-TVAC algorithms are better when using a suitable fitness function. [ABSTRACT FROM AUTHOR]

Background: Low nuclear grade ductal carcinoma in situ (DCIS) patients can adopt proactive management strategies to avoid unnecessary surgical resection. Different personalized treatment modalities may be selected based on the expression status of molecular markers, which is also predictive of different outcomes and risks of recurrence. DCIS ultrasound findings are mostly non mass lesions, making it difficult to determine boundaries. Currently, studies have shown that models based on deep learning radiomics (DLR) have advantages in automatic recognition of tumor contours. Machine learning models based on clinical imaging features can explain the importance of imaging features., Methods: The available ultrasound data of 349 patients with pure DCIS confirmed by surgical pathology [54 low nuclear grade, 175 positive estrogen receptor (ER+), 163 positive progesterone receptor (PR+), and 81 positive human epidermal growth factor receptor 2 (HER2+)] were collected. Radiologists extracted ultrasonographic features of DCIS lesions based on the 5 th Edition of Breast Imaging Reporting and Data System (BI-RADS). Patient age and BI-RADS characteristics were used to construct clinical machine learning (CML) models. The RadImageNet pretrained network was used for extracting radiomics features and as an input for DLR modeling. For training and validation datasets, 80% and 20% of the data, respectively, were used. Logistic regression (LR), support vector machine (SVM), random forest (RF), and eXtreme Gradient Boosting (XGBoost) algorithms were performed and compared for the final classification modeling. Each task used the area under the receiver operating characteristic curve (AUC) to evaluate the effectiveness of DLR and CML models., Results: In the training dataset, low nuclear grade, ER+, PR+, and HER2+ DCIS lesions accounted for 19.20%, 65.12%, 61.21%, and 30.19%, respectively; the validation set, they consisted of 19.30%, 62.50%, 57.14%, and 30.91%, respectively. In the DLR models we developed, the best AUC values for identifying features were 0.633 for identifying low nuclear grade, completed by the XGBoost Classifier of ResNet50; 0.618 for identifying ER, completed by the RF Classifier of InceptionV3; 0.755 for identifying PR, completed by the XGBoost Classifier of InceptionV3; and 0.713 for identifying HER2, completed by the LR Classifier of ResNet50. The CML models had better performance than DLR in predicting low nuclear grade, ER+, PR+, and HER2+ DCIS lesions. The best AUC values by classification were as follows: for low nuclear grade by RF classification, AUC: 0.719; for ER+ by XGBoost classification, AUC: 0.761; for PR+ by XGBoost classification, AUC: 0.780; and for HER2+ by RF classification, AUC: 0.723., Conclusions: Based on small-scale datasets, our study showed that the DLR models developed using RadImageNet pretrained network and CML models may help predict low nuclear grade, ER+, PR+, and HER2+ DCIS lesions so that patients benefit from hierarchical and personalized treatment., Competing Interests: Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://gs.amegroups.com/article/view/10.21037/gs-23-417/coif). The authors have no conflicts of interest to declare., (2024 Gland Surgery. All rights reserved.)

Background: Neoadjuvant therapy (NAT) is the preferred treatment for advanced breast cancer nowadays. The early prediction of its responses is important for personalized treatment. This study aimed at using baseline shear wave elastography (SWE) ultrasound combined with clinical and pathological information to predict the clinical response to therapy in advanced breast cancer., Methods: This retrospective study included 217 patients with advanced breast cancer who were treated in West China Hospital of Sichuan University from April 2020 to June 2022. The features of ultrasonic images were collected according to the Breast imaging reporting and data system (BI-RADS), and the stiffness value was measured at the same time. The changes were measured according to the Response evaluation criteria in solid tumors (RECIST1.1) by MRI and clinical situation. The relevant indicators of clinical response were obtained through univariate analysis and incorporated into a logistic regression analysis to establish the prediction model. The receiver operating characteristic (ROC) curve was used to evaluate the performance of the prediction models., Results: All patients were divided into a test set and a validation set in a 7:3 ratio. A total of 152 patients in the test set, with 41 patients (27.00%) in the non-responders group and 111 patients (73.00%) in the responders group, were finally included in this study. Among all unitary and combined mode models, the Pathology + B-mode + SWE model performed best, with the highest AUC of 0.808 (accuracy 72.37%, sensitivity 68.47%, specificity 82.93%, P<0.001). HER2+, Skin invasion, Post mammary space invasion, Myometrial invasion and Emax were the factors with a significant predictive value (P<0.05). 65 patients were used as an external validation set. There was no statistical difference in ROC between the test set and the validation set (P>0.05)., Conclusion: As the non-invasive imaging biomarkers, baseline SWE ultrasound combined with clinical and pathological information can be used to predict the clinical response to therapy in advanced breast cancer., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Wang, Wen, Zhao, Liu, Wan, Lan and Peng.)

Objectives: This study investigated the occurrence rate of unexpected breast cancer (UEBC) mimicking benign lesions [Breast Imaging Reporting and Data System (BI-RADS) category 3 or 4a] using ultrasound-guided vacuum-assisted excision biopsy (US-VAEB), and explored the factors responsible for late diagnosis of T2 stage UEBC., Materials and Methods: We collected clinicopathologic data and preoperative US imaging features within 3 months before US-VAEB of patients who were diagnosed with UEBC from January 2002 to September 2022. The UEBC were divided into T1 and T2 stageUEBC. The US imaging features as well as clinical and pathological information of T1 and T2 stage UEBC were compared to explore the factors responsible for late diagnosis of T2 stage UEBC., Results: Breast cancer was diagnosed in 91 of 19 306 patients who underwent US-VAEB. We excluded eight patients with breast cancer assigned to BI-RADS 4b category by preoperative US, and two for whom US imaging records were unavailable. Finally, we enrolled 81 patients. The occurrence rate of UEBC after US-VAEB was 0.42%(81/19296). Of the 81 cases of UEBC, 22 were at T2 stage. The ratio of T2 stage UEBC was 27.2%. The differences in risk factor of breast cancer and routine breast US screening between T1 and T2 stage UEBC were significant[96.6% (57/59) vs 81.8% (18/22), 44.1% (26/59) vs 13.6% (3/22), respectively, P <0.05)., Conclusion: UEBC was rarely detected by US-VAEB. Most cases of T2 stage UEBC were diagnosed late because of the absence of routine US screening and risk factors for breast cancer. Stricter clinical management regulations for breast lesions and performing regular US screening may be helpful to reduce T2 stage UEBC., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Zhou, Luo, Zhao and Peng.)

Background: Plasma S100A1 protein is a novel inflammatory biomarker associated with acute myocardial infarction and neurodegenerative disease's pathophysiological mechanisms. This study aimed to determine the levels of this protein in patients with acute ischemic stroke early in the disease progression and to investigate its role in the pathogenesis of acute ischemic stroke., Methods: A total of 192 participants from hospital stroke centers were collected for the study. Clinically pertinent data were recorded. The volume of the cerebral infarction was calculated according to the Pullicino formula. Multivariate logistic regression analysis was used to select independent influences. ROC curve was used to analyze the diagnostic value of AIS and TIA. The correlation between S100A1, NF- κ B p65, and IL-6 levels and cerebral infarction volume was detected by Pearson correlation analysis., Results: There were statistically significant differences in S100A1, NF- κ B p65, and IL-6 among the AIS,TIA, and PE groups (S100A1, [230.96 ± 39.37] vs [185.85 ± 43.24] vs [181.47 ± 27.39], P < 0.001; NF- κ B p65, [3.99 ± 0.65] vs [3.58 ± 0.74] vs [3.51 ± 0.99], P = 0.001; IL-6, [13.32 ± 1.57] vs [11.61 ± 1.67] vs [11.42 ± 2.34], P < 0.001). Multivariate logistic regression analysis showed that S100A1 might be an independent predictive factor for the diagnosis of disease ( P < 0.001). The AUC of S100A1 for diagnosis of AIS was 0.818 ( P < 0.001, 95% CI [0.749-0.887], cut off 181.03, J max 0.578, Se 95.0%, Sp 62.7%). The AUC of S100A1 for diagnosis of TIA was 0.720 ( P = 0.001, 95% CI [0.592-0.848], cut off 150.14, J max 0.442, Se 50.0%, Sp 94.2%). There were statistically significant differences in S100A1, NF- κ B p65, and IL-6 among the SCI,MCI, and LCI groups (S100A1, [223.98 ± 40.21] vs [225.42 ± 30.92] vs [254.25 ± 37.07], P = 0.001; NF- κ B p65, [3.88 ± 0.66] vs [3.85 ± 0.64] vs [4.41 ± 0.45], P < 0.001; IL-6, [13.27 ± 1.65] vs [12.77 ± 1.31] vs [14.00 ± 1.40], P = 0.007). Plasma S100A1, NF- κ B p65, and IL-6 were significantly different from cerebral infarction volume (S100A1, r  = 0.259, P = 0.002; NF- κ B p65, r  = 0.316, P < 0.001; IL-6, r  = 0.177, P = 0.036). There was a positive correlation between plasma S100A1 and IL-6 with statistical significance (R = 0.353, P < 0.001). There was no significant positive correlation between plasma S100A1 and NF- κ B p65 (R < 0.3), but there was statistical significance (R = 0.290, P < 0.001). There was a positive correlation between IL-6 and NF- κ B p65 with statistical significance (R = 0.313, P < 0.001)., Conclusion: S100A1 might have a better diagnostic efficacy for AIS and TIA. S100A1 was associated with infarct volume in AIS, and its level reflected the severity of acute cerebral infarction to a certain extent. There was a correlation between S100A1 and IL-6 and NF- κ B p65, and it was reasonable to speculate that this protein might mediate the inflammatory response through the NF- κ B pathway during the pathophysiology of AIS., Competing Interests: The authors declare there are no competing interests., (©2023 Guo et al.)

Background: Static shear wave elastography (SWE) is used to detect breast lesions, but slice and plane selections result in discrepancies., Objective: To evaluate the intraobserver reproducibility of continuous SWE, and whether quantitative elasticities in orthogonal planes perform better in the differential diagnosis of breast lesions., Method: One hundred and twenty-two breast lesions scheduled for ultrasound-guided biopsy were recruited. Continuous SWE scans were conducted in orthogonal planes separately. Quantitative elasticities and histopathology results were collected. Reproducibility in the same plane and diagnostic performance in different planes were evaluated., Results: The maximum and mean elasticities of the hardest portion, and standard deviation of whole lesion, had high inter-class correlation coefficients (0.87 to 0.95) and large areas under receiver operation characteristic curve (0.887 to 0.899). Without loss of accuracy, sensitivities had increased in orthogonal planes compared with single plane (from 73.17% up to 82.93% at most). Mean elasticity of whole lesion and lesion-to-parenchyma ratio were significantly less reproducible and less accurate., Conclusion: Continuous SWE is highly reproducible for the same observer. The maximum and mean elasticities of the hardest portion and standard deviation of whole lesion are most reliable. Furthermore, the sensitivities of the three parameters are improved in orthogonal planes without loss of accuracies.

The sonographic features of male breast lesions, which underwent ultrasound examination in our hospital for the past 10 years, were retrospectively analyzed. Sonographic features of these lesions were standardized as BI RADS image lexicon. The differences in ultrasonic malignant signs were assessed between the benign and the malig nant diseases. Between the two groups, incomplete boundary was statistically different. The specificity was above 95% within the two groups in terms of speculated margin, echogenic halo, calcification, axillary lymphadenopathy, thickening of skin and eccentric of mass to the nipple. High-frequency sonographic examination has a high level of differential diagnosis for male breast lesions.