Long-term care needs and hospitalization costs with long-term care insurance: a mixed-sectional study.

Background: With the rapid aging of the population, the health needs of the older adult have increased significantly, resulting in the frequent occurrence of the "social hospitalization" problem, which has led to a rapid increase in hospitalization costs. This study investigates whether the "social hospitalization problem" arising from the long-term care needs can be solved through the implementation of long-term care insurance, thereby improving the overall health of the older adults and controlling the unreasonable increase in hospitalization costs. Methods: The entropy theory was used as a conceptual model, based on data from the China Health and Retirement Longitudinal Study (CHARLS) in 2015 and 2018. The least-squares method was used to examine the relationship between long-term care needs and hospitalization costs, and the role that long-term care insurance implementation plays in its path of influence. Results: The results of this study indicated that long-term care needs would increase hospitalization cost, which remained stable after a series of tests, such as replacing the core explanatory variables and introducing fixed effects. Through the intermediary effect test and mediated adjustment effect test, we found the action path of long-term care needs on hospitalization costs. Long-term care needs increases hospitalization costs through more hospitalizations. Long-term care insurance reduces hospitalization costs. Its specific action path makes long-term care insurance reduce hospitalization costs through a negative adjustment of the number of hospitalizations. Conclusion: To achieve fair and sustainable development of long-term care insurance, the following points should be achieved: First, long-term care insurance should consider the prevention in advance and expand the scope of participation and coverage; Second, long-term care insurance should consider the control in the event and set moderate levels of treatment payments; Third, long-term care insurance should consider post-supervision and explore appropriate payment methods.

Integration of temporal & spatial properties of dynamic functional connectivity based on two-directional two-dimensional principal component analysis for disease analysis.

Dynamic functional connectivity, derived from resting-state functional magnetic resonance imaging (rs-fMRI), has emerged as a crucial instrument for investigating and supporting the diagnosis of neurological disorders. However, prevalent features of dynamic functional connectivity predominantly capture either temporal or spatial properties, such as mean and global efficiency, neglecting the significant information embedded in the fusion of spatial and temporal attributes. In addition, dynamic functional connectivity suffers from the problem of temporal mismatch, i.e., the functional connectivity of different subjects at the same time point cannot be matched. To address these problems, this article introduces a novel feature extraction framework grounded in two-directional two-dimensional principal component analysis. This framework is designed to extract features that integrate both spatial and temporal properties of dynamic functional connectivity. Additionally, we propose to use Fourier transform to extract temporal-invariance properties contained in dynamic functional connectivity. Experimental findings underscore the superior performance of features extracted by this framework in classification experiments compared to features capturing individual properties.

Defect-Induced All-Solid-State Frustrated Lewis Pair on Metal-Organic Monolayer Accelerating Photocatalytic CO2 Reduction with H2O Vapor.

Understanding the structure-performance relationships of a frustrated Lewis pair (FLP) at the atomic level is key to yielding high efficiency in activating chemically "inert" molecules into value-added products. A sound strategy was developed herein through incorporating oxygen defects into a Zr-based metal-organic layer (Zr-MOL-D) and employing Lewis basic proximal surface hydroxyls for the in situ formation of solid heterogeneous FLP (Zr4-δ-VO-Zr-OH). Zr-MOL-D exhibits a superior CO2 to CO conversion rate of 49.4 µmol g-1 h-1 in water vapor without any sacrificing agent or photosensitizer, which is about 12 times higher than that of pure MOL (Zr-MOL-P), with extreme stability even after being placed for half a year. Theoretical and experimental results reveal that the introduction of FLP converts the process of the crucial intermediate COOH* from an endothermic reaction to an exothermic spontaneous reaction. This work is expected to provide new prospects for developing efficient MOL-based photocatalysts in FLP chemistry through a sound defect-engineering strategy.

Glycerol Electrooxidation over Precision-Synthesized Gold Nanocrystals with Different Surface Facets.

Electrochemical glycerol oxidation (EGO) emerges as a promising route to valorize glycerol, an underutilized byproduct from biodiesel production, into value-added chemicals. This study employed three types of gold (Au) nanocrystals with controlled shapes to elucidate the facet-dependent electrocatalytic behavior in EGO. Octahedral, rhombic dodecahedral, and cubic Au nanocrystals with {111}, {110}, and {100} facets, respectively, were precisely synthesized with uniform size and shape. Rhombic dodecahedra exhibited the lowest onset potential for EGO due to facile AuOH formation, while octahedra showed enhanced electrochemical activity for glycerol oxidation and resistance to poisoning. In-situ FTIR analysis revealed that Au {111} surfaces selectively favored C2 products, whereas Au {100} surfaces promoted C3 product formation, highlighting the significant effect of facet orientation on EGO performance and informing catalyst design.

Randomly Layered Superstructure of In2O3 Truncated Nano-Octahedra and Its High-Pressure Behavior.

This study outlines the preparation and characterization of a unique superlattice composed of indium oxide (In2O3) vertex-truncated nano-octahedra, along with an exploration of its response to high-pressure conditions. Transmission electron microscopy and scanning transmission electron microscopy were employed to determine the average circumradius (15.2 nm) of these vertex-truncated building blocks and their planar superstructure. The resilience and response of the superlattice to pressure variations, peaking at 18.01 GPa, were examined using synchrotron-based wide-angle X-ray scattering (WAXS) and small-angle X-ray scattering (SAXS) techniques. The WAXS data revealed no phase transitions, reinforcing the stability of the 2D superlattice composed of random layers in alignment with a p31m planar symmetry as discerned by SAXS. Notably, the SAXS data also unveiled a pressure-induced, irreversible translation of octahedra and ligand interaction occurring within the random layer. Through our examination of these pressure-sensitive behaviors, we identified a distinctive translation model inherent to octahedra and observed modulation of the superlattice cell parameter induced by pressure. This research signifies a noteworthy advancement in deciphering the intricate behaviors of 2D superlattices under a high pressure.

Enhanced chimp hierarchy optimization algorithm with adaptive lens imaging for feature selection in data classification.

Feature selection is a critical component of machine learning and data mining to remove redundant and irrelevant features from a dataset. The Chimp Optimization Algorithm (CHoA) is widely applicable to various optimization problems due to its low number of parameters and fast convergence rate. However, CHoA has a weak exploration capability and tends to fall into local optimal solutions in solving the feature selection process, leading to ineffective removal of irrelevant and redundant features. To solve this problem, this paper proposes the Enhanced Chimp Hierarchy Optimization Algorithm for adaptive lens imaging (ALI-CHoASH) for searching the optimal classification problems for the optimal subset of features. Specifically, to enhance the exploration and exploitation capability of CHoA, we designed a chimp social hierarchy. We employed a novel social class factor to label the class situation of each chimp, enabling effective modelling and optimization of the relationships among chimp individuals. Then, to parse chimps' social and collaborative behaviours with different social classes, we introduce other attacking prey and autonomous search strategies to help chimp individuals approach the optimal solution faster. In addition, considering the poor diversity of chimp groups in the late iteration, we propose an adaptive lens imaging back-learning strategy to avoid the algorithm falling into a local optimum. Finally, we validate the improvement of ALI-CHoASH in exploration and exploitation capabilities using several high-dimensional datasets. We also compare ALI-CHoASH with eight state-of-the-art methods in classification accuracy, feature subset size, and computation time to demonstrate its superiority.

Multiparametric MRI subregion radiomics for preoperative assessment of high-risk subregions in microsatellite instability of rectal cancer patients: A multicenter study.

BACKGROUND: Microsatellite instability (MSI) is associated with treatment response and prognosis in patients with rectal cancer (RC). However, intratumoral heterogeneity limits MSI testing in patients with RC. We developed a subregion radiomics model based on multiparametric magnetic resonance imaging (MRI) to preoperatively assess high-risk subregions with MSI and predict the MSI status of patients with RC. METHODS: This retrospective study included 475 patients (training cohort, 382; external test cohort, 93) with RC from two participating hospitals between April 2017 and June 2023. In the training cohort, subregion radiomic features were extracted from multiparametric MRI, which included T2-weighted, T1-weighted, diffusion-weighted, and contrast-enhanced T1-weighted imaging. MSI-related subregion radiomic features, classical radiomic features, and clinicoradiological variables were gathered to build five predictive models using logistic regression. Kaplan-Meier survival analysis was conducted to explore the prognostic information. RESULTS: Among the 475 patients (median age, 64 years [interquartile range, IQR: 55-70 years];304 men and 171 women), the prevalence of MSI was 11.16% (53/475). The subregion radiomics model outperformed the classical radiomics and clinicoradiological models in both training (area under the curve [AUC]=0.86, 0.72, and 0.59, respectively) and external test cohorts (AUC=0.83, 0.73, and 0.62, respectively). The subregion-clinicoradiological model combining clinicoradiological variables and subregion radiomic features performed the optimal, with AUCs of 0.87 and 0.85 in the training and external test cohorts, respectively. The 3-year disease-free survival rate of MSI groups predicted based on the model was higher than that of the predicted microsatellite stability (MSS) groups in both patient cohorts (training, P=0.032; external test, P=0.046). CONCLUSIONS: We developed and validated a model based on subregion radiomic features of multiparametric MRI to evaluate high-risk subregions with MSI and predict the MSI status of RC preoperatively, which may assist in individualized treatment decisions and positioning for biopsy.

Mesoporous Single Atom-Cluster Fe-N/C Oxygen Evolution Electrocatalysts Synthesized with Bottlebrush Block Copolymer-Templated Rapid Thermal Annealing.

Current electrocatalysts for oxygen evolution reaction (OER) are either expensive (such as IrO2, RuO2) or/and exhibit high overpotential as well as sluggish kinetics. This article reports mesoporous earth-abundant iron (Fe)-nitrogen (N) doped carbon electrocatalysts with iron clusters and closely surrounding Fe-N4 active sites. Unique to this work is that the mechanically stable mesoporous carbon-matrix structure (79 nm in pore size) with well-dispersed nitrogen-coordinated Fe single atom-cluster is synthesized via rapid thermal annealing (RTA) within only minutes using a self-assembled bottlebrush block copolymer (BBCP) melamine-formaldehyde resin composite template. The resulting porous structure and domain size can be tuned with the degree of polymerization of the BBCP backbone, which increases the electrochemically active surface area and improves electron transfer and mass transport for an effective OER process. The optimized electrocatalyst shows a required potential of 1.48 V (versus RHE) to obtain the current density of 10 mA/cm2 in 1 M KOH aqueous electrolyte and a small Tafel slope of 55 mV/decade at a given overpotential of 250 mV, which is significantly lower than recently reported earth-abundant electrocatalysts. Importantly, the Fe single-atom nitrogen coordination environment facilitates the surface reconstruction into a highly active oxyhydroxide under OER conditions, as revealed by X-ray photoelectron spectroscopy and in situ Raman spectroscopy, while the atomic clusters boost the single atoms reactive sites to prevent demetalation during the OER process. Density functional theory (DFT) calculations support that the iron nitrogen environment and reconstructed oxyhydroxides are electrocatalytically active sites as the kinetics barrier is largely reduced. This work has opened a new avenue for simple, rapid synthesis of inexpensive, earth-abundant, tailorable, mechanically stable, mesoporous carbon-coordinated single-atom electrocatalysts that can be used for renewable energy production.

Airway necrosis and granulation tissue formation caused by Rhizopus oryzae leading to severe upper airway obstruction: a case report.

Pulmonary Mucormycosis is a fatal infectious disease with high mortality rate. The occurrence of Mucormycosis is commonly related to the fungal virulence and the host's immunological defenses against pathogens. Mucormycosis infection and granulation tissue formation occurred in the upper airway was rarely reported. This patient was a 60-year-old male with diabetes mellitus, who was admitted to hospital due to progressive cough, sputum and dyspnea. High-resolution computed tomography (HRCT) and bronchoscopy revealed extensive tracheal mucosal necrosis, granulation tissue proliferation, and severe airway stenosis. The mucosal necrotic tissue was induced by the infection of Rhizopus Oryzae, confirmed by metagenomic next-generation sequencing (mNGS) in tissue biopsy. This patient was treated with the placement of a covered stent and local instillation of amphotericin B via bronchoscope. The tracheal mucosal necrosis was markedly alleviated, the symptoms of cough, shortness of breath, as well as exercise tolerance were significantly improved. The placement of airway stent and transbronchial microtube drip of amphotericin B could conduce to rapidly relieve the severe airway obstruction due to Mucormycosis infection.

Development and validation of a computed tomography-based radiomics signature to predict "highest-risk" from patients with high-risk gastrointestinal stromal tumor.

Background: Some patients with high-risk gastrointestinal stromal tumor (GIST) experience disease progression after complete resection and adjuvant therapy. It is of great significance to distinguish these patients among those with high-risk GIST. Radiomics has been demonstrated as a promising tool to predict various tumors prognosis. Methods: From January 2006 to December 2018, a total of 100 high-risk GIST patients (training cohort: 60; validation cohort: 40) from Guangdong Provincial People's Hospital with preoperative enhanced computed tomography (CT) images were enrolled. The radiomics features were extracted and a risk score was built using least absolute shrinkage and selection operator-Cox model. The clinicopathological factors were analyzed and a nomogram was established with and without radiomics risk score. The concordance index (C-index), calibration plot, and decision curve analysis (DCA) were used to evaluate the performance of the radiomics nomograms. Results: We selected 11 radiomics features associated with recurrence or metastasis. The risk score was calculated and significantly associated with disease-free survival (DFS) in both the training and validation group. Cox regression analysis showed that Ki67 was an independent risk factor for DFS [P=0.004, hazard ratio 4.615, 95% confidence interval (CI): 1.624-13.114]. The combined radiomics nomogram, which integrated the radiomics risk score and significant clinicopathological factors, showed good performance in predicting DFS, with a C-index of 0.832 (95% CI: 0.761-0.903), which was better than the clinical nomogram (C-index 0.769, 95% CI: 0.679-0.859) in training cohort. The calibration curves and the DCA plot suggested satisfying accuracy and clinical utility of the model. Conclusions: The CT-based radiomics nomogram, combined with the clinicopathological factors and risk score, has good potential to assess the recurrence or metastasis of patients with high-risk GIST.

Long-term exposure to air pollutants and new-onset migraine: A large prospective cohort study.

BACKGROUNDS: Short-term exposure to air pollutants increases the risk of migraine, but the long-term impacts of exposure to multiple pollutants on migraine have not been established. The aim of this large prospective cohort study was to explore these links. METHODS: A total of 458,664 participants who were free of migraine at baseline from the UK Biobank were studied. Cox proportional hazards models were used to estimate the risk of new-onset migraine from combined long-term exposure to four pollutants, quantified as an air pollution score using principal component analysis. RESULTS: During a median (IQR) follow-up of 12.5 (11.8, 13.2) years, a total of 5417 new-onset migraine cases were documented. Long-term exposure to multiple air pollutants was associated with an increased risk of new-onset migraine, as indicated by an increased in the SDs of PM2.5 (hazard ratio (HR): 1.04, 95% CI: 1.01-1.06, P = 0.009), PM10 (HR: 1.07, 95% CI: 1.04-1.10, P < 0.001), NO2 (HR: 1.10, 95% CI: 1.07-1.13, P < 0.001) and NOx (HR: 1.04, 95% CI: 1.01-1.07, P = 0.005) in the main model. The air pollution score showed a doseresponse association with an increased risk of new-onset migraine. Similarly, compared with those of the lowest tertile, the HRs (95% CI) of new-onset migraine were 1.11 (95% CI: 1.04-1.19, P = 0.002) and 1.17 (95% CI: 1.09-1.26, P < 0.001) in tertiles 2 and 3, respectively, according to the main model (P trend < 0.001). CONCLUSION: Long-term individual and joint exposure to multiple air pollutants is associated with an increased risk of new-onset migraine.

The Wound Healing of Autologous Regenerative Factor on Recurrent Benign Airway Stenosis: A Canine Experimental and Pilot Study.

INTRODUCTION: Benign airway stenosis (BAS) is a severe pathologic condition. Complex stenosis has a high recurrence rate and requires repeated bronchoscopic interventions for achieving optimal control, leading to recurrent BAS (RBAS) due to intraluminal granulation. METHODS: This study explored the potential of autologous regenerative factor (ARF) for treating RBAS using a post-intubation tracheal stenosis canine model. Bronchoscopic follow-ups were conducted, and RNA-seq analysis of airway tissue was performed. A clinical study was also initiated involving 17 patients with recurrent airway stenosis. RESULTS: In the animal model, ARF demonstrated significant effectiveness in preventing further collapse of the injured airway, maintaining airway patency and promoting tissue regeneration. RNA-seq results showed differential gene expression, signifying alterations in cellular components and signaling pathways. The clinical study found that ARF treatment was well-tolerated by patients with no severe adverse events requiring hospitalization. ARF treatment yielded a high response rate, especially for post-intubation tracheal stenosis and idiopathic tracheal stenosis patients. CONCLUSION: The study concludes that ARF presents a promising, effective, and less-invasive method for treating RBAS. ARF has shown potential in prolonging the intermittent period and reducing treatment failure in patients with recurrent tracheal stenosis by facilitating tracheal mucosal wound repair and ameliorating tracheal fibrosis. This novel approach could significantly impact future clinical applications.

Joint learning of multi-level dynamic brain networks for autism spectrum disorder diagnosis.

Graph convolutional networks (GCNs), with their powerful ability to model non-Euclidean graph data, have shown advantages in learning representations of brain networks. However, considering the complexity, multilayeredness, and spatio-temporal dynamics of brain activities, we have identified two limitations in current GCN-based research on brain networks: 1) Most studies have focused on unidirectional information transmission across brain network levels, neglecting joint learning or bidirectional information exchange among networks. 2) Most of the existing models determine node neighborhoods by thresholding or simply binarizing the brain network, which leads to the loss of edge weight information and weakens the model's sensitivity to important information in the brain network. To address the above issues, we propose a multi-level dynamic brain network joint learning architecture based on GCN for autism spectrum disorder (ASD) diagnosis. Specifically, firstly, constructing different-level dynamic brain networks. Then, utilizing joint learning based on GCN for interactive information exchange among these multi-level brain networks. Finally, designing an edge self-attention mechanism to assign different edge weights to inter-node connections, which allows us to pick out the crucial features for ASD diagnosis. Our proposed method achieves an accuracy of 81.5 %. The results demonstrate that our method enables bidirectional transfer of high-order and low-order information, facilitating information complementarity between different levels of brain networks. Additionally, the use of edge weights enhances the representation capability of ASD-related features.

N-Decorated Main-Group MgAl2 O4 Spinel: Unlocking Exceptional Oxygen Reduction Activity for Zn-Air Batteries.

The development of economical and efficient oxygen reduction reaction (ORR) catalysts is crucial to accelerate the widespread application rhythm of aqueous rechargeable zinc-air batteries (ZABs). Here, a strategy is reported that the modification of the binding energy for reaction intermediates by the axial N-group converts the inactive spinel MgAl2 O4 into the active motif of MgAl2 O4 -N. It is found that the introduction of N species can effectively optimize the electronic configuration of MgAl2 O4 , thereby significantly reducing the adsorption strength of *OH and boosting the reaction process. This main-group MgAl2 O4 -N catalyst exhibits a high ORR activity in a broad pH range from acidic and alkaline environments. The aqueous ZABs assembled with MgAl2 O4 -N shows a peak power density of 158.5 mW cm-2 , the long-term cyclability over 2000 h and the high stability in the temperature range from -10 to 50 °C, outperforming the commercial Pt/C in terms of activity and stability. This work not only serves as a significant candidate for the robust ORR electrocatalysts of aqueous ZABs, but also paves a new route for the effective reutilization of waste Mg alloys.

An investigation into the correlation between early-to-mid pregnancy exercise combined with cognitive behavioral therapy and anxiety levels and quality of life in patients.

OBJECTIVE: The aim of this study was to investigate the effects of exercise combined with cognitive behavioral therapy (CBT) on anxiety and quality of life in pregnant women. METHODS: This study adopted a prospective randomized controlled trial design, and divided 60 pregnant women in the first and second trimesters into two groups. The control group received routine prenatal education, and the experimental group added moderate exercise and CBT on the basis of routine prenatal education. All participants completed the Hamilton Anxiety Rating Scale (HARS) and World Health Organization Quality of Life-BREF (WHOQOL-BREF) at the start of the study (baseline) and at 6 weeks after the intervention. RESULTS: Baseline data, scores on HARS, and scores on WHOQOL-BREF were found to be consistent among the two groups of patients prior to the intervention (all P > 0.05). Following the intervention, the implementation of exercise combined with CBT resulted in significant improvements in anxiety levels within the experimental group, particularly with respect to aspects such as anxious mood, tension, insomnia, cognitive function, cardiovascular symptoms, and gastrointestinal symptoms (all P < 0.05). Similarly, the combination of exercise and CBT led to significant enhancement in the quality of life in the experimental group, particularly in areas such as physical health, psychological health, and environmental factors (all P < 0.05). Nevertheless, no significant disparities were observed between the two groups in terms of fears, depressive mood, muscular and sensory somatic symptoms, respiratory symptoms, genitourinary symptoms, autonomic symptoms, behavior during the interview, and social relationships (all P > 0.05). CONCLUSION: Exercise combined with CBT can effectively reduce the anxiety of pregnant women and improve their quality of life, which has important clinical significance for improving the mental health and quality of life of pregnant women in the first and second trimesters.

Multiple Metal-Nitrogen Bonds Synergistically Boosting the Activity and Durability of High-Entropy Alloy Electrocatalysts.

The development of Pt-based catalysts for use in fuel cells that meet performance targets of high activity, maximized stability, and low cost remains a huge challenge. Herein, we report a nitrogen (N)-doped high-entropy alloy (HEA) electrocatalyst that consists of a Pt-rich shell and a N-doped PtCoFeNiCu core on a carbon support (denoted as N-Pt/HEA/C). The N-Pt/HEA/C catalyst showed a high mass activity of 1.34 A mgPt-1 at 0.9 V for the oxygen reduction reaction (ORR) in rotating disk electrode (RDE) testing, which substantially outperformed commercial Pt/C and most of the other binary/ternary Pt-based catalysts. The N-Pt/HEA/C catalyst also demonstrated excellent stability in both RDE and membrane electrode assembly (MEA) testing. Using operando X-ray absorption spectroscopy (XAS) measurements and theoretical calculations, we revealed that the enhanced ORR activity of N-Pt/HEA/C originated from the optimized adsorption energy of intermediates, resulting in the tailored electronic structure formed upon N-doping. Furthermore, we showed that the multiple metal-nitrogen bonds formed synergistically improved the corrosion resistance of the 3d transition metals and enhanced the ORR durability.

Piperlongumine inhibits esophageal squamous cell carcinoma in vitro and in vivo by triggering NRF2/ROS/TXNIP/NLRP3-dependent pyroptosis.

Pyroptosis, a type of programmed cell death, is characterized by cell swelling with bubbles, and the release of inflammatory cell cytokines. Piperlongumine (PL) is a natural bioactive product extracted from Piper longum L, which can effectively exert anti-tumor activities in cancer. However, the effects and the exact molecular mechanisms of PL in esophageal squamous cell carcinoma (ESCC) remain unclear. This research aimed to investigate the role and mechanism of PL on ESCC in vitro and in vivo. In vitro, the MTT results showed that the IC50 of PL in ESCC cells was 28.55 µM. Moreover, PL significantly suppressed malignant behavior by promoting pyroptosis of ESCC cells by inhibiting proliferation, migration, invasion, and colony formation of KYSE-30 cells, up-regulating expressions of ASC, Cleaved-caspase-1, NLRP3, and GSDMD, while inducing the generation of ROS. Further, NRF2 knockdown promoted TXNIP expression, while overexpression of NRF2 inhibited TXNIP expression. However, after PL treatment, this effect was reversed. In addition, PL significantly inhibited the malignant behavior of ESCC cells while the inhibitory effects were reversed by DMF (NRF2 activator) or NAC (ROS eliminator) treatment. Finally, PL markedly increased expressions of ASC, Cleaved-caspase-1, NLRP3, GSDMD, and the generation of ROS while the effects were reversed by TXNIP knockdown or RUS (TXNIP inhibitor) treatment. In vivo, the KYSE-30 xenograft model confirmed that PL inhibited the growth of ESCC transplanted tumors by promoting cell pyroptosis. In conclusion, the results suggested that PL inhibited the malignant behavior of ESCC cells in vitro and tumorigenesis of ESCC in vivo by inhibiting NRF2 and promoting ROS-TXNIP-NLRP3-mediated pyroptosis.

Diagnostic performance of ACR-TIRADS combined with superb microvascular imaging for differential diagnosis of mummified thyroid nodules and papillary thyroid carcinomas.

Objective: The aim was to investigate the ability of superb microvascular imaging (SMI) to improve the differential diagnosis of mummified thyroid nodules (MTNs) and papillary thyroid carcinomas (PTCs) using the 2017 American College of Radiology Thyroid Imaging Reporting and Data System (ACR-TIRADS). Materials and methods: We enrolled 110 cases of MTNs and 110 cases of PTCs confirmed by fine needle aspiration (FNA) or surgery. Conventional ultrasound (US) and the quantity of microvessels detected by SMI were analyzed for all nodules. Thyroid nodules were initially categorized by ACR-TIRADS based on US imaging features and then reclassified based on ACR-TIRADS combined with SMI blood-flow grade (SMI-TIRADS). We compared the diagnostic performances of ACR-TIRADS and SMI-TIRADS by receiver operating characteristic curve, sensitivity, specificity, accuracy, positive predictive value (PPV), and negative predictive value (NPV). Results: US-detected margin, shape, and echogenic foci differed between MTNs and PTCs (P < 0.05). The SMI blood-flow grade was significantly greater in PTCs compared with MTNs (Χ2 = 158.78, P < 0.05). There was no significant difference in ACR-TIRADS indicators between MTNs and PTCs (Χ2 = 1.585, P = 0.453); however, reclassification by SMI-TIRADS showed significant differences between the groups (Χ2 = 129.521, P < 0.001). The area under the curve was significantly lower for ACR-TIRADS compared with SMI-TIRADS (0.517 vs 0.887, P < 0.05). SMI-TIRADS had significantly higher diagnostic value for distinguishing MTNs and PTCs than ACR-TIRADS (sensitivity: 91.82% vs 74.55%, P < 0.05; specificity: 84.55% vs 21.82%, P < 0.05; accuracy: 88.18% vs 48.18%, P < 0.05; PPV: 85.59% vs 48.81%, P < 0.05; and NPV: 91.18% vs 46.15%, P < 0.05). Conclusion: The detection of microvascular flow and large vessels in thyroid nodules by SMI resulted in high diagnostic specificity and sensitivity. ACR-TIRADS combined with SMI could effectively distinguish between MTNs and PTCs, to avoid unnecessary FNA or surgical excision.

Effect of aggregation configuration of molecular fluorophore CZA on photoluminescence properties of carbon dots.

The effect of aggregation configuration of molecular fluorophore citrazinic acid (CZA) on the photoluminescence (PL) properties of carbon dots (CDs) has been investigated using first-principles method. The structural stability of all aggregates has been analyzed, and the results show that the most stable structures are J-type CZA aggregates with head-to-tail configurations and the CZA/CD aggregates are bonded by replacing H atoms on the CD edges with de-OH from the pyridine ring of CZA. The luminescent properties of CZA/CD aggregates are mainly affected by the binding modes and binding sites. When the sites belong to electron-donating groups, electron-withdrawing groups or sp2 domain, the PL spectra of CDs are shifted and the luminescent intensities are significantly enhanced. The results suggest that covalently bonded CZA/CD aggregates are responsible for the high fluorescence quantum yield of CD. Moreover, the distance between the centers of the two pyridine rings in H-type CZA dimers less than 3.5 Å is prone to π-π stacking, leading to fluorescence quenching of aggregates. The present work is helpful in understanding the effect of molecular fluorophores on the PL properties of CDs and provides theoretical guidance for the controllable synthesis of CDs.