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Thyroid cancer (TC) is a significant global healthcare burden. However, the lack of comprehensive data has impeded our understanding of its global impact. We aimed to examine the burden of TC and its trends at the global, regional, and national levels using data stratified by sociodemographic index (SDI), sex, and age. Data on TC, including incidence, mortality, and disability-adjusted life-years (DALYs) from 1990 to 2021, were obtained from the Global Burden of Disease Study 2021. Estimated annual percentage changes (EAPCs) were calculated to assess the incidence rate, mortality, and DALYs trends. The incidence, mortality, and DALYs of TC in 2021 were 249,538 (95% uncertainty interval: 223,290–274,638), 44,799 (39,925–48,541), and 646,741 (599,119–717,357), respectively. The age-standardized incidence rate (ASIR) in 2021 was 2.914 (2.607–3.213), with an EAPC of 1.25 (1.14–1.37) compared to 1990. In 2021, the age-standardized death rate (ASDR) was 0.53 (0.47–0.575) and age-standardized DALYs rate was 14.571 (12.783–16.115). Compared with 1990, the EAPCs of ASDR and age-standardized DALYs rate showed decreasing trends, at − 0.24 (− 0.27 to − 0.21) and − 0.14 (− 0.17 to − 0.11), respectively. Low SDI regions showed the highest ASDR and age-standardized DALYs rate, at 0.642 (0.516–0.799) and 17.976 (14.18–23.06), respectively. Low-middle SDI regions had the highest EAPCs for ASDR and age-standardized DALYs rate, at 0.74 (0.71–0.78) and 0.67 (0.63–0.7), respectively. Females exhibited decreasing trend in ASDR and age-standardized DALYs rate, with EAPCs of − 0.58 (− 0.61 to − 0.55) and − 0.45 (− 0.47 to − 0.42), respectively. In contrast, males showed an increasing trend in ASDR and age-standardized DALYs rate, with EAPCs of 0.41 (0.35–0.46) for both. In high-income regions, most countries with decreased annual changes in deaths experience increasing age-related deaths. Over the past few decades, a notable increase in TC incidence and decreased mortality has been observed globally. Regions characterized by lower SDI, male sex, and an aging population exhibited no improvement in TC mortality. Effective resource allocation, meticulous control of risk factors, and tailored interventions are crucial for addressing these issues. [ABSTRACT FROM AUTHOR]

Treating Multiple sclerosis (MS), a well-known immune-mediated disease characterized by axonal demyelination, is challenging due to its complex causes. Naphthalenedione, present in numerous plants, is being explored as a potential medicine for MS due to its immunomodulatory properties. However, its effects on lymphocytes can vary depending on factors such as the specific compound, concentration, and experimental conditions. In this study, we aim to explore the therapeutic potential of 2-bromo-1,4-naphthalenedione (BrQ), a derivative of naphthalenedione, in experimental autoimmune encephalomyelitis (EAE), an animal model of MS, and to elucidate its underlying mechanisms. We observed that mice treated with BrQ exhibited reduced severity of EAE symptoms, including lower clinical scores, decreased leukocyte infiltration, and less extensive demyelination in central nervous system. Furthermore, it was noted that BrQ does not directly affect the remyelination process. Through cell-chat analysis based on bulk RNA-seq data, coupled with validation of flow analysis, we discovered that BrQ significantly promotes the expansion of CD8+ T cells and their interactions with other immune cells in peripheral immune system in EAE mice. Subsequent CD8+ T cell depletion experiments confirmed that BrQ alleviates EAE in a CD8+ T cell-dependent manner. Mechanistically, expanded CD8+ cells were found to selectively reduce antigen-specific CD4+ cells and subsequently inhibit Th1 and Th17 cell development in vivo, ultimately leading to relief from EAE. In summary, our findings highlight the crucial role of BrQ in modulating the pathogenesis of MS, suggesting its potential as a novel drug candidate for treating MS and other autoimmune diseases. [ABSTRACT FROM AUTHOR]

Space–time adaptive processing (STAP) based on sparse recovery achieves excellent clutter suppression and target detection performance, even with a limited number of available training samples. However, most of these methods face performance degradation due to grid mismatch, which impedes their application in bistatic clutter suppression. Some gridless methods, such as atomic norm minimization (ANM), can effectively address grid mismatch issues, yet they are sensitive to parameter settings and array errors. In this article, the authors propose a data and model-driven algorithm that unfolds the iterative process of atomic norm minimization into a deep network. This approach establishes a concrete and systematic link between iterative algorithms, extensively utilized in signal processing, and deep neural networks. This methodology not only addresses the challenges associated with parameter settings in traditional optimization algorithms, but also mitigates the lack of interpretability issues commonly found in deep neural networks. Moreover, due to more rational parameter settings, the proposed algorithm achieves effective clutter suppression with fewer iterations, thereby reducing computational time. Finally, extensive simulation experiments demonstrate the effectiveness of the proposed algorithm in clutter suppression for airborne bistatic radar. [ABSTRACT FROM AUTHOR]

The traditional sparse recovery (SR) space-time adaptive processing (STAP) algorithms are greatly affected by grid mismatch, leading to poor performance in airborne bistatic radar clutter suppression. In order to address this issue, this paper proposes an SR STAP algorithm for airborne bistatic radars based on atomic selection under the Bayesian framework. This method adopts the idea of atomic selection for the process of Bayesian inference, continuously evaluating the contribution of atoms to the likelihood function to add or remove atoms, and then using the selected atoms to estimate the clutter support subspace and perform sparse recovery in the clutter support subspace. Due to the inherent sparsity of clutter signals, performing sparse recovery in the clutter support subspace avoids using a massive number of atoms from an overcomplete space-time dictionary, thereby greatly improving computational efficiency. In airborne bistatic radar scenarios where significant grid mismatch exists, this method can mitigate the performance degradation caused by grid mismatch by encrypting grid points. Since the sparse recovery is performed in the clutter support subspace, encrypting grid points does not lead to excessive computational burden. Additionally, this method integrates out the noise term under a new hierarchical Bayesian model, preventing the adverse effects caused by inaccurate noise power estimation during iterations in the traditional SR STAP algorithms, further enhancing its performance. Our simulation results demonstrate the high efficiency and superior clutter suppression performance and target detection performance of this method. [ABSTRACT FROM AUTHOR]

ZnO nanostructures show great potential in hydrogen sensing at atmospheric conditions for good gas adsorption abilities. However, there is less research on low-pressure hydrogen sensing performance due to its low concentration and in-homogeneous distributions under low-pressure environments. Here, we report the low-pressure hydrogen sensing by the construction of Al–N-co-doped ZnO nanorods based on the adsorption-induced field emission enhancement effect in the pressure range of 10−7 to 10−3 Pa. The investigation indicates that the Al–N-co-doped ZnO sample is the most sensitive to low-pressure hydrogen sensing among all ZnO samples, with the highest sensing current increase of 140% for 5 min emission. In addition, the increased amplitude of sensing current for the Al–N-co-doped ZnO sample could reach 75% at the pressure 7 × 10−3 Pa for 1 min emission. This work not only expands the hydrogen sensing applications to the co-doped ZnO nanomaterials, but also provides a promising approach to develop field emission cathodes with strong low-pressure hydrogen sensing effect. [ABSTRACT FROM AUTHOR]

Background: The efficacy and safety of the novel immunotherapy method, intra‐cervical lymphatic immunotherapy (ICLIT), need to be investigated. Comparing it with subcutaneous immunotherapy (SCIT), we clarified the long‐term efficacy and safety of intra‐cervical lymphatic immunotherapy on allergic rhinitis (AR), and investigated the improvement of clinical efficacy of the booster injection at 1 year after ICLIT treatment. Methods: Ninety adult patients with dust mite allergy were randomly divided into 3 groups: 30 in the SCIT group, 30 in the ILCLIT group, and 30 in ICLIT booster group. Changes in total symptom score (TSS), nasal symptom score (TNSS), ocular symptom score (TOSS) and total medication score (TMS) were evaluated in the three groups. Adverse reactions were recorded, and serum dust mite specific IgE (sIgE) and specific IgG4 were assessed in the ICLIT group and ICLIT booster group. Results: TSS, TNSS, TOSS, and TMS scores were significantly lower in the three groups at 36 months after treatment (p < 0. 05). And at 36 months the ICLIT‐booster group showed results similar to SCIT and superior to ICLIT (p < 0. 05). Serum specific IgE decreased in all three groups at 12 and 36 months after treatment, p < 0.01. The ICLIT group and the ICLIT booster group showed a significant increase in sIgG4, p < 0.01. None of the patients in the three groups had any serious systemic adverse effects during the 3‐year follow‐up. Conclusion: The ICLIT treatment is effective and safe on AR. One booster injection of allergens at 1 year can greatly improve its long‐term efficacy. Trial Registry: Clinical trial registration number: ChiCTR1800017130. [ABSTRACT FROM AUTHOR]

Objective: To evaluate the value of an integrated model incorporating deep learning (DL), hand-crafted radiomics and clinical and US imaging features for diagnosing central lymph node metastasis (CLNM) in patients with papillary thyroid cancer (PTC). Methods: This retrospective study reviewed 613 patients with clinicopathologically confirmed PTC from two institutions. The DL model and hand-crafted radiomics model were developed using primary lesion images and then integrated with clinical and US features selected by multivariate analysis to generate an integrated model. The performance was compared with junior and senior radiologists on the independent test set. SHapley Additive exPlanations (SHAP) plot and Gradient-weighted Class Activation Mapping (Grad-CAM) were used for the visualized explanation of the model. Results: The integrated model yielded the best performance with an AUC of 0.841. surpassing that of the hand-crafted radiomics model (0.706, p < 0.001) and the DL model (0.819, p = 0.26). Compared to junior and senior radiologists, the integrated model reduced the missed CLNM rate from 57.89% and 44.74–27.63%, and decreased the rate of unnecessary central lymph node dissection (CLND) from 29.87% and 27.27–18.18%, respectively. SHAP analysis revealed that the DL features played a primary role in the diagnosis of CLNM, while clinical and US features (such as extrathyroidal extension, tumour size, age, gender, and multifocality) provided additional support. Grad-CAM indicated that the model exhibited a stronger focus on thyroid capsule in patients with CLNM. Conclusion: Integrated model can effectively decrease the incidence of missed CLNM and unnecessary CLND. The application of the integrated model can help improve the acceptance of AI-assisted US diagnosis among radiologists. [ABSTRACT FROM AUTHOR]

Background: Risk stratification systems for thyroid nodules are limited by low specificity. The fine-needle aspiration (FNA) biopsy size thresholds and stratification criteria are based on evidence from the literature and expert consensus. Our aims were to investigate the optimal FNA biopsy size thresholds in the American College of Radiology (ACR) Thyroid Imaging Reporting and Data System (TI-RADS) and artificial intelligence (AI) TI-RADS and to revise the stratification criteria in AI TI-RADS. Methods: A total of 2596 thyroid nodules (in 2511 patients) on ultrasound examination with definite pathological diagnoses were retrospectively identified from January 2017 to September 2021 in 6 participating Chinese hospitals. The modified criteria for ACR TI-RADS were as follows: (1) no FNA for TR3; (2) FNA threshold for TR4 increased to 2.5 cm. The modified criteria for AI TI-RADS were as follows: (1) 6-point nodules upgraded to TR5; (2) no FNA for TR3; (3) FNA threshold for TR4 increased to 2.5 cm. The diagnostic performance and the unnecessary FNA rate (UFR) of modified versions were compared with the original ACR TI-RADS. Results: Compared with the original ACR TI-RADS, the modified ACR (mACR) TI-RADS yielded higher specificity (73% vs. 46%), accuracy (74% vs. 51%), area under the receiver operating characteristic curve (AUC; 0.80 vs. 0.70), and lower UFR (25% vs. 48%; all p < 0.001), although the sensitivity was slightly decreased (87% vs. 93%, p = 0.057). Compared with the original ACR TI-RADS, the modified AI (mAI) TI-RADS yielded higher specificity (73% vs. 46%), accuracy (75% vs. 51%), AUC (0.81 vs. 0.70), and lower UFR (24% vs. 48%; all p < 0.001), although the sensitivity tended to be slightly decreased (89% vs. 93%, p = 0.13). There was no significant difference between the mACR TI-RADS and mAI TI-RADS in the diagnostic performance and UFR (all p > 0.05). Conclusions: The revised FNA thresholds and the stratification criteria of the mACR TI-RADS and mAI TI-RADS may be associated with improvements in specificity and accuracy, without significantly sacrificing sensitivity for malignancy detection. [ABSTRACT FROM AUTHOR]

Rationale and Objectives: To investigate and authenticate the effectiveness of various radiomics models in distinguishing between benign and malignant BI-RADS 4A lesions., Methods: A total of 936 patients with pathologically confirmed 4A lesions were included in the study (training cohort: n = 655; test cohort: n = 281). Radiomic features were derived from greyscale US images. Following dimensionality reduction and feature selection, radiomics models were developed using logistic regression (LR), support vector machine (SVM), random forest (RF), eXtreme gradient boosting (XGBoost) and multilayer perceptron (MLP) algorithms. Univariate and multivariable logistic regression analyses were employed to investigate clinical-radiological characteristics and determine variables for creating a clinical model. Five combined models integrating radiomic and clinical parameters were constructed by using each algorithm, and comparison with radiologists' performance was performed. SHapley Additive exPlanations (SHAP) approach was used to elucidate the radiomic model by ranking the significance of features based on their contribution to the evaluation., Results: A total of 1561 radiomic features were extracted. Thirty-six features were deemed significant by dimensionality reduction and selection. The radiomic models showed good performance with AUCs of 0.829-0.945 in training cohort; and 0.805-0.857 in test cohort. The combined model developed by using LR showed the best performance (AUC, training cohort: 0.909; test cohort: 0.905), which is superior to radiologists' performance. Decision curve analysis (DCA) of this combined model indicated better clinical efficacy than clinical and radiomic models., Conclusions: The combined model integrating radiomic and clinical features demonstrated excellent performance in differentiating between benign and malignant 4A lesions. It may offer a non-invasive and efficient approach to aid in clinical decision-making., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.)

Aim: To investigate the application of ultrasound along with clinical features for the differential diagnosis of low-grade appendiceal mucinous neoplasm (LAMN) and acute suppurative appendicitis (ASA)., Material and Methods: The ultrasound and clinical data of 76 patients with histopathologically confirmed LAMN (31 patients) and ASA (45 patients) were retrospectively analyzed. Univariate analysis and binary logistic regression analysis of the influencing factors were conducted to identify LAMN and ASA. The AUROC was calculated to analyze the diagnostic efficacy of these independent factors. A four-grid table was established to determine the diagnostic efficacy of the ultrasound marks for diagnosing LAMN., Results: Patient age and appendix short diameter in the LAMN group were found to be significantly higher than those in the ASA group. The neutrophil ratio and thickness of the appendix wall in the LAMN group were significantly lower than they were in the ASA group. Patient age (OR=1.112, p=0.015) and appendix short diameter (OR=1.476, p=0.008) were independent risk factors for LAMN. The AUROCs for age and short diameter were 0.898 [95% CI: 0.807, 0.956] and 0.953 [95% CI: 0.879, 0.988], respectively. The LAMN group tumors were characterized by the appearance of an "onion skin" sign or a purely cystic mark on sonograms, with specificities of 100% for both. Neutrophil ratio (OR<0.001, p=0.064) and thickness of the appendix wall (OR=0.776, p=0.414) were not independent risk factors for ASA., Conclusion: Employing ultrasonography with clinical features is useful for distinguishing LAMN from ASA. Patient age, short diameter of the appendix, and sonographic appearance of "onion skin" or purely cystic mark could be key factors in diagnosing LAMN.

Treating Multiple sclerosis (MS), a well-known immune-mediated disease characterized by axonal demyelination, is challenging due to its complex causes. Naphthalenedione, present in numerous plants, is being explored as a potential medicine for MS due to its immunomodulatory properties. However, its effects on lymphocytes can vary depending on factors such as the specific compound, concentration, and experimental conditions. In this study, we aim to explore the therapeutic potential of 2-bromo-1,4-naphthalenedione (BrQ), a derivative of naphthalenedione, in experimental autoimmune encephalomyelitis (EAE), an animal model of MS, and to elucidate its underlying mechanisms. We observed that mice treated with BrQ exhibited reduced severity of EAE symptoms, including lower clinical scores, decreased leukocyte infiltration, and less extensive demyelination in central nervous system. Furthermore, it was noted that BrQ does not directly affect the remyelination process. Through cell-chat analysis based on bulk RNA-seq data, coupled with validation of flow analysis, we discovered that BrQ significantly promotes the expansion of CD8 + T cells and their interactions with other immune cells in peripheral immune system in EAE mice. Subsequent CD8 + T cell depletion experiments confirmed that BrQ alleviates EAE in a CD8 + T cell-dependent manner. Mechanistically, expanded CD8 + cells were found to selectively reduce antigen-specific CD4 + cells and subsequently inhibit Th1 and Th17 cell development in vivo, ultimately leading to relief from EAE. In summary, our findings highlight the crucial role of BrQ in modulating the pathogenesis of MS, suggesting its potential as a novel drug candidate for treating MS and other autoimmune diseases., (© 2024. The Author(s).)

Study Objectives: We investigated the associations between multiple sleep dimensions in obstructive sleep apnea (OSA) and carotid intima-media thickness (CIMT), an early sign of atherosclerosis, in participants from the Shanghai Sleep Health Study., Methods: We performed secondary analysis of SSHS in a group of subjects who underwent ultrasound evaluation from 2018 to 2022. Multiple sleep dimensions were measured using standard polysomnography. CIMT was measured from ultrasound images as an early sign of atherosclerosis. Multivariable-adjusted linear regression and logistic regression analyses were performed to detect associations between sleep traits in OSA and CIMT., Results: CIMT was found to increase with increasing severity of OSA ( P < .001). When adjusted for conventional risk factors, microarousal index and hypoxic burden were positively correlated with CIMT, while slow-wave sleep and mean apnea-hypopnea event duration showed a negative correlation with CIMT (all P < .01). In binary logistic regression analysis, participants with a high microarousal index, less slow-wave sleep, higher hypoxic burden, and shorter mean apnea-hypopnea event duration showed a higher prevalence of thick CIMT with no evidence of interaction by age, sex, or body mass index ( P -interaction > .05)., Conclusions: Patients with more severe sleep fragmentation, more severe hypoxemia, and increased arousability were more likely to have increased CIMT after adjusting for potential confounders. It is important to evaluate novel indices of sleep fragmentation, hypoxemia, and arousability in OSA for early detection and prevention of cardiovascular disease, including stroke., Clinical Trial Registration: Registry: Chinese Clinical Trial Registry; Name: Establishing Bio-bank and Cohort of OSAHS in Hospital-based Population; URL: http://www.chictr.org.cn/showproj.aspx?proj=43057; Identifier: ChiCTR1900025714., Citation: Huang W, Zhou E, Zhang J, et al. Association between multiple sleep dimensions in obstructive sleep apnea and an early sign of atherosclerosis. J Clin Sleep Med . 2024;20(7):1093-1104., (© 2024 American Academy of Sleep Medicine.)

Background: The triglyceride glucose index (TyG) has previously been considered a reliable indicator of insulin resistance (IR) and an independent prognostic predictor in heart failure (HF)., Objectives: To clarify the association between the TyG and short-term death in non-diabetic patients admitted for acute heart failure (AHF)., Material and Methods: We examined 886 out of 1620 consecutive AHF patients who were admitted to Shunde Hospital, Southern Medical University, Foshan, China, from June 1, 2014, to June 1, 2022. The median of the patientsf TyG values was used to divide them into 2 groups. The following formula was used to calculate the TyG: ln [fasting triglycerides (mg/dL) ~ fasting glucose (mg/dL)/2]. The data on all-cause mortality of AHF patients during their hospital stay were collected. The 30-day Enhanced Feedback for Effective Cardiac Treatment (EFFECT) death risk score was used to assess the risk of death., Results: The TyG level was positively correlated with a poor AHF prognostic marker (N-terminal B-type natriuretic peptide (NT-proBNP)) (Ď = 0.207, p < 0.001) and negatively correlated with a protective marker (serum albumin) (Ď = .0.43, p < 0.001). Higher TyG values were associated with an elevated EFFECT score and hospital mortality (p < 0.001). According to multivariate logistic regression analysis, higher TyG levels raised the risk of death in hospital (odds ratio (OR) = 1.73; 95% confidence interval (95% CI): 1.03.3.27; p = 0.031) after adjusting for multiple variables, including age, EFFECT score and NT-proBNP. The TyG had a greater area under the receiver operating characteristic (ROC) curve (AUC: 0.688) for predicting hospital death compared to NT-proBNP (AUC: 0.506)., Conclusions: Our findings show that the TyG is associated with the short-term mortality rate of non-diabetic patients admitted to the hospital for AHF. The TyG testing could be a useful prognostic indicator for these patients.