Knowledge graph analysis of research on nurses' psychological resilience.

In recent years, a surge in literature on psychological nurse resilience, largely driven by the COVID-19 pandemic, has prompted the need for a comprehensive understanding of the current state and emerging trends through reliable methodologies. The purpose of this study was to analyzes the research on nurses' psychological resilience through bibliometrics to understand the current situation, foundation, and hotspot of this research field. The Web of Science core collection database was used as the search source, and CiteSpace analysis software was employed to conduct bibliometric analysis on authors, countries, institutions, keywords, and references of nurse psychological resilience-related literature published from the establishment of the database to July 11, 2023. A total of 1060 articles were included in the final analysis. The study of nurses' psychological resilience had been highly popular and had formed a new and important research basis in recent years. China and the United States led in the number of publications and centrality respectively, with Monash Univ and Curtin Univ as top institutions in the number of publications and centrality respectively. The authors with the highest number of publications and the most frequently cited were Rees and Connor Km respectively. The most frequently cited article was Factors Associated with Mental Health Outcomes Among Health Care Workers Exposed to Coronavirus Disease 2019 published by Lai, JB, etc. Important key keywords included mental health, resilience, stress, health, outbreak, acute respiratory syndrome, etc. The research topics in this field mainly focused on 4 aspects, including nurses' mental health, post-traumatic stress disorder, job burnout and job satisfaction, and intervention research on psychological resilience. The results of bibliometric analysis provide direct support for future scholars to explore and determine the research direction, hot spots, and find authoritative authors and institutions. At the moment, nurses' psychological resilience research has established a new foundation, primarily focusing on COVID-19-related topics. Given the potential prolonged coexistence of COVID-19 and other diseases, the main research focus remains innovating and validating effective psychological resilience intervention strategies for nurses' overall well-being.

Association between segmental alterations of white matter bundles and cognitive performance in first-episode, treatment-naïve young adults with major depressive disorder.

BACKGROUND: Cumulative evidence has consistently shown that white matter (WM) disruption is associated with cognitive decline in geriatric depression. However, limited research has been conducted on the correlation between these lesions and cognitive performance in untreated young adults with major depressive disorder (MDD), particularly with the specific segmental alterations of the fibers. METHOD: Diffusion tensor images were performed on 60 first-episode, treatment-naïve young adult patients with MDD and 54 matched healthy controls (HCs). Automated fiber quantification was applied to calculate the tract profiles of fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) to evaluate the WM microstructural organization. Correlation analysis was performed to find the associations between the diffusion properties and cognitive performance. RESULTS: Compared with HCs, patients with MDD exhibited predominantly different diffusion properties in bilateral uncinate fasciculus (UF), corticospinal tracts (CSTs), left superior longitudinal fasciculus and anterior thalamic radiation. The FA of the temporal cortex portion of right UF was positively correlated with working memory. The MD of the temporal component of left UF was negatively correlated with working memory and positively correlated with symptom severity. Additionally, a positive correlation between the MD of left CST and the psychomotor speed, negative correlation between the MD of left CST and the executive functions and complex attentional processes were observed. CONCLUSIONS: Our study validated the alterations in spatial localization of WM microstructure and its correlations with cognitive performance in first-episode, treatment-naïve young adults with MDD. This study added to the knowledge of the neuropathological basis of MDD.

Electroencephalography microstates as novel functional biomarkers for insomnia disorder.

Background: Insomnia disorder (ID) is one of the most common mental disorders. Research on ID focuses on exploring its mechanism of disease, novel treatments and treatment outcome prediction. An emerging technique in this field is the use of electroencephalography (EEG) microstates, which offer a new method of EEG feature extraction that incorporates information from both temporal and spatial dimensions. Aims: To explore the electrophysiological mechanisms of repetitive transcranial magnetic stimulation (rTMS) for ID treatment and use baseline microstate metrics for the prediction of its efficacy. Methods: This study included 60 patients with ID and 40 age-matched and gender-matched good sleep controls (GSC). Their resting-state EEG microstates were analysed, and the Pittsburgh Sleep Quality Index (PSQI) and polysomnography (PSG) were collected to assess sleep quality. The 60 patients with ID were equally divided into active and sham groups to receive rTMS for 20 days to test whether rTMS had a moderating effect on abnormal microstates in patients with ID. Furthermore, in an independent group of 90 patients with ID who received rTMS treatment, patients were divided into optimal and suboptimal groups based on their median PSQI reduction rate. Baseline EEG microstates were used to build a machine-learning predictive model for the effects of rTMS treatment. Results: The class D microstate was less frequent and contribute in patients with ID, and these abnormalities were associated with sleep onset latency as measured by PSG. Additionally, the abnormalities were partially reversed to the levels observed in the GSC group following rTMS treatment. The baseline microstate characteristics could predict the therapeutic effect of ID after 20 days of rTMS, with an accuracy of 80.13%. Conclusions: Our study highlights the value of EEG microstates as functional biomarkers of ID and provides a new perspective for studying the neurophysiological mechanisms of ID. In addition, we predicted the therapeutic effect of rTMS on ID based on the baseline microstates of patients with ID. This finding carries great practical significance for the selection of therapeutic options for patients with ID.

Executive function deficit in betel quid-dependence: Evidence from functional and effective connectivity of executive control network.

Betel quid (BQ) ranks fourth in global self-administered psychoactive agents, after caffeine, alcohol and nicotine, with 600 million consumers. Patients with BQ dependence (BQD) disorder demonstrate deficits in executive function. However, the neural correlates of the resting-state executive control network (ECN) and BQD-related pathopsychological characteristics still remain unclear. The present study aimed to assess the functional and effective connectivity of the ECN using resting-state functional magnetic resonance imaging (rs-fMRI). Fifty-five BQD individuals and 54 healthy controls (HCs) were recruited in this study. The executive function of all participants was tested by three tasks. Independent component and Granger causal analysis were employed to investigate the functional connectivity within ECN and ECN-related directional effective connectivity, separately. Behavioural results suggested a marked deficit of executive function in BQD individuals. Compared with HCs, BQD individuals showed overall weaker functional connectivity in the ECN, mainly including dorsolateral prefrontal cortex (DLPFC), inferior parietal lobule (IPL) and middle frontal gyrus (MFG). We observed decreased outflow of information from the right DLPFC and IPL to the precentral/pre-supplement motor area (SMA) and increased outflow of information from the MFG to the middle occipital gyrus in BQD individuals. Correlation analysis revealed that the effective connectivity from IPL to precentral/pre-SMA was negatively correlated to the BQD scales in BQD individuals. Our findings revealed impaired executive function, functional connectivity of the ECN and causal interaction between networks in patients with BQD. These results could potentially direct future targets for the prevention and intervention of BQD.

Curcumin preconditioning enhances the neuroprotective effects of olfactory mucosa-derived mesenchymal stem cells on experimental intracerebral hemorrhage.

Oxidative stress is essential in brain injury after intracerebral hemorrhage (ICH). Ferroptosis, iron-dependent oxidative cell death, overwhelms the antioxidant system. Recently, Olfactory mucosa-derived mesenchymal stem cells (OM-MSCs) hold great potential for treating ferroptosis-mediated oxidative brain damage after ICH. However, massive grafted cell death, possibly caused by a hostile host brain microenvironment, lessens the effectiveness of OM-MSCs. Therefore, it is necessary to develop strategies to upregulate the therapeutic efficacy of OM-MSCs in ICH. Curcumin, a well-established traditional herbal substance, has potent antioxidant property. In the present study, curcumin preconditioning might enhance the anti-oxidative activity of OM-MSCs, thereby augmenting the therapeutic efficacy of OM-MSCs in ICH. In vitro model of ICH, we demonstrated that curcumin-preconditioned OM-MSCs co-culture is more effective in attenuating the cell injury, oxidative stress, and ferroptosis of neuronal cells compared to the native OM-MSCs treatment. In vivo model of ICH, transplantation of curcumin-preconditioned OM-MSCs also showed better neuroprotective effects. Moreover, curcumin pretreatment promoted the survival of OM-MSCs under a conditioned medium from hemin-insulted neurons by improving the anti-oxidative capacities of OM-MSCs. Collectively, our investigation suggested that curcumin preconditioning effectively enhanced the survival and neuroprotective effects of OM-MSCs in the ICH model by upregulating the anti-oxidative capacities of OM-MSCs. Curcumin-preconditioned OM-MSCs might be taken as a novel therapeutic strategy for treating ICH.

Decreased functional connectivity in salience network is associated with symptom severity in betel quid-dependent chewers.

BACKGROUND: Betel quid (BQ) is the fourth most popular psychoactive agent worldwide. Neuroimaging studies have showed that substance-addicted individuals including alcohol, heroin, nicotine and other addictive substance exhibit altered activity patterns of the salience network (SN). However, no study has yet investigated the neural correlates of the resting-state SN and BQ dependence (BQD)-related physiopathological characteristics. METHODS: Thirty-two BQ-dependent (BQD) chewers and 32 healthy controls were recruited to participate in this study. Resting-state functional magnetic resonance imaging (fMRI) data were analysed by independent component analysis (ICA). RESULTS: BQD chewers exhibited decreased functional connectivity in bilateral insula, anterior cingulate cortex (ACC), medial superior frontal gyrus (MSFG) and inferior orbital frontal gyrus (IOFG) [false discovery rate (FDR) correction, p < 0.05]. In the BQD group, the decreased functional connectivity in left ACC correlated negatively with BQDS (BQD Scale) and the duration of BQ. CONCLUSIONS: We reported decreased functional connectivity in resting-state SN of BQD individuals. The decreased functional connectivity in left ACC correlated negatively with BQDS and the duration of BQ. Our findings provided evidence for the importance of the SN in the pathophysiology of BQD and indicated that the SN dysfunction might provide a potential mechanism in BQD development.

Potential Role of Host Microbiome in Areca Nut-Associated Carcinogenesis and Addiction.

Areca nut (AN) is widely consumed all over the world, bringing great harm to human health and economy. Individuals with AN chewing are at high risk of cardiovascular disease and impaired immune system and metabolic system. Despite a growing number of studies having reported on the adverse effects brought by AN chewing, the exact mechanism of it is limited and the need for additional exploration remains. In recent years, the interaction between microorganisms, especially intestinal microorganism and host, has been extensively studied. AN chewing might disrupt the oral and intestinal microbiota communities through direct connect with the microbes it contains, altering PH, oxygen of oral and intestinal microenvironment, and disturbing the immune homeostasis. These mechanisms provide insights into the interplay between areca nut and host microbiota. Emerging studies have proposed that bidirectional interaction between polyphenols and intestinal microbes might play a potential role in the divergence of polyphenol, extracted from AN, among individuals with or without AN-induced cancer development and progression. Although some AN chewers have been aware of the harmful effects brought by AN, they cannot abolish this habit because of the addiction of AN. Increasing studies have tried to revealed that gut microbiota might influence the onset/development of addictive behaviors. Altogether, this review summarizes the possible reasons for the disturbance of host microbiota caused by areca nut chewing and clarifies the complex interaction between human microbiome and major constituents and the addiction and carcinogenicity of AN, tempting to provide novel insights into the development and utilization of it, and to control the adverse consequences caused by AN chewing.

Regional metabolic heterogeneity in anterior cingulate cortex in major depressive disorder: A multi-voxel 1H magnetic resonance spectroscopy study.

BACKGROUND: Previous studies have shown major depressive disorder (MDD) is associated with altered neuro-metabolites in the anterior cingulate cortex (ACC). However, the regional metabolic heterogeneity in the ACC in individuals with MDD remains unclear. METHODS: We recruited 59 first-episode, treatment-naive young adults with MDD and 50 healthy controls who underwent multi-voxel 1H-MRS scanning at 3 T (Tesla) with voxels placed in the ACC, which was divided into two subregions, pregenual ACC (pACC) and anterior midcingulate cortex (aMCC). Between and within-subjects metabolite concentration variations were analyzed with SPSS. RESULTS: Compared with control subjects, patients with MDD exhibited higher glutamate (Glu) and glutamine (Gln) levels in the pACC and higher myo-inositol (MI) level in the aMCC. We observed higher Glu and Gln levels and lower N-acetyl-aspartate (NAA) level in the pACC than those in the aMCC in both MDD and healthy control (HC) groups. More importantly, the metabolite concentration gradients of Glu, Gln and NAA were more pronounced in MDD patients relative to HCs. In the MDD group, the MI level in the aMCC positively correlated with the age of onset. LIMITATIONS: The use of the relative concentration of metabolites constitutes a key study limitation. CONCLUSIONS: We observed inconsistent alterations and distribution of neuro-metabolites concentration in the pACC and aMCC, revealing regional metabolic heterogeneity of ACC in first-episode, treatment-naive young individuals with MDD. These results provided new evidence for abnormal neuro-metabolites of ACC in the pathophysiology of MDD and suggested that pACC and aMCC might play different roles in MDD.

UBIAD1 alleviates ferroptotic neuronal death by enhancing antioxidative capacity by cooperatively restoring impaired mitochondria and Golgi apparatus upon cerebral ischemic/reperfusion insult.

BACKGROUND: Neuronal death due to over-oxidative stress responses defines the pathology of cerebral ischemic/reperfusion (I/R) insult. Ferroptosis is a form of oxidative cell death that is induced by disruption of the balance between antioxidants and pro-oxidants in cells. However, the potential mechanisms responsible for cerebral I/R-induced ferroptotic neuronal death have not been conclusively determined. UBIAD1, is a newly identified antioxidant enzyme that catalyzes coenzyme Q10 (CoQ10) and vitamin K2 biosynthesis in the Golgi apparatus membrane and mitochondria, respectively. Even though UBIAD1 is a significant mediator of apoptosis in cerebral I/R challenge, its roles in ferroptotic neuronal death remain undefined. Therefore, we investigated whether ferroptotic neuronal death is involved in cerebral I/R injury. Further, we evaluated the functions and possible mechanisms of UBIAD1 in cerebral I/R-induced ferroptotic neuronal death, with a major focus on mitochondrial and Golgi apparatus dysfunctions. RESULTS: Ferroptosis occurred in cerebral I/R. Ferroptotic neuronal death promoted cerebral I/R-induced brain tissue injury and neuronal impairment. UBIAD1 was expressed in cerebral tissues and was localized in neurons, astrocytes, and microglia. Under cerebral I/R conditions overexpressed UBIAD1 significantly suppressed lipid peroxidation and ferroptosis. Moreover, upregulated UBIAD1 protected against brain tissue damage and neuronal death by alleviating I/R-mediated lipid peroxidation and ferroptosis. However, UBIAD1 knockdown reversed these changes. Enhanced UBIAD1-mediated ferroptosis elevated the antioxidative capacity by rescuing mitochondrial and Golgi apparatus dysfunction in cerebral I/R-mediated neuronal injury. They improved the morphology and biofunctions of the mitochondria and Golgi apparatus, thereby elevating the levels of SOD, T-AOC and production of CoQ10, endothelial nitric oxide synthase (eNOS)-regulated nitric oxide (NO) generation as well as suppressed MDA generation. CONCLUSIONS: The neuroprotective agent, UBIAD1, modulates I/R-mediated ferroptosis by restoring mitochondrial and Golgi apparatus dysfunction in damaged brain tissues and neurons, thereby enhancing antioxidative capacities. Moreover, the rescue of impaired mitochondrial and Golgi apparatus as a possible mechanism of regulating ferroptotic neuronal death is a potential treatment strategy for ischemic stroke.

Applications of nanomaterials in COVID-19 pandemic.

The novel coronavirus 2019 (COVID-19) pandemic represents one of the biggest global health threats in the last two decades, so researchers around the world are searching for solutions and treatments for COVID-19. At the time of writing, there are no specific drugs that have demonstrated suitable effectiveness in treating COVID-19. The current challenge involves designing tools for the prevention, rapid and accurate diagnosis, drug delivery, and effective treatment of this novel coronavirus. In this short review, we discuss how nanotechnology offers new ways to combat COVID-19, and how nanomaterials can be applied to control the COVID-19 outbreak. We also summarize relevant studies regarding the use of nanomaterials for preventing viral spread, preparing vaccines, and diagnosing coronavirus, as well as studies that show how nanoparticles can be used as drug delivery systems for the treatment of viral infections. Research on nanotechnology-based diagnosis, drug delivery, and antiviral therapy is currently in the early stages. However, the unique chemical properties of some nanomaterials highlight the broad prospect of nanomaterials in the future, and we propose that they will play an important role in the fight against COVID-19.

Efficient Computer-Aided Design of Dental Inlay Restoration: A Deep Adversarial Framework.

Restoring the normal masticatory function of broken teeth is a challenging task primarily due to the defect location and size of a patient's teeth. In recent years, although some representative image-to-image transformation methods (e.g. Pix2Pix) can be potentially applicable to restore the missing crown surface, most of them fail to generate dental inlay surface with realistic crown details (e.g. occlusal groove) that are critical to the restoration of defective teeth with varying shapes. In this article, we design a computer-aided Deep Adversarial-driven dental Inlay reStoration (DAIS) framework to automatically reconstruct a realistic surface for a defective tooth. Specifically, DAIS consists of a Wasserstein generative adversarial network (WGAN) with a specially designed loss measurement, and a new local-global discriminator mechanism. The local discriminator focuses on missing regions to ensure the local consistency of a generated occlusal surface, while the global discriminator aims at defective teeth and adjacent teeth to assess if it is coherent as a whole. Experimental results demonstrate that DAIS is highly efficient to deal with a large area of missing teeth in arbitrary shapes and generate realistic occlusal surface completion. Moreover, the designed watertight inlay prostheses have enough anatomical morphology, thus providing higher clinical applicability compared with more state-of-the-art methods.

18 F-2-fluoro-2-deoxy-D-glucose-positron emission tomography metabolic pattern assessment in the brain of betel quid dependent individuals.

The primary objective of this study was to identify the metabolic pattern in the brains of betel quid dependent (BQD) individuals using 18 F-2-fluoro-2-deoxy-D-glucose-positron emission tomography (18 F-FDG-PET). A total of 42 individuals (16 BQD individuals and 26 healthy controls, HCs) enrolled at the Department of Nuclear Medicine of Xiangya Hospital underwent brain 18 F-FDG-PET. Group comparisons using statistical parametric mapping (SPM) were performed to identify the 18 F-FDG-PET patterns. Standardized uptake value ratios of anterior cingulate, frontal, thalamus, parietal, occipital, temporal and cerebellum were calculated by SPM. The characteristics of abnormal metabolism in brain regions were quantified using the xjView toolbox, and a 3-D brain map was drawn using BrainNet Viewer. We found significant metabolic reduction in the bilateral middle prefrontal cortex (PFC) and the left orbital frontal gyrus (OFC). In contrast, hypermetabolism was observed in the inferior cerebellum, fusiform, superior cerebellum, parahippocampal, vermis, lingual and thalamus. However, we found no significant difference between the BQD and HC group in the anterior cingulate, thalamus, cerebellum and frontal, temporal, parietal and occipital lobes. In summary, we found abnormal 18 F-FDG-PET metabolic pattern in BQD individuals, and this pattern may help the treatment of BQD.

Cross-network interaction for diagnosis of major depressive disorder based on resting state functional connectivity.

Previous studies have suggested that resting-state functional connectivity plays a central role in the physiopathology of major depressive disorder (MDD). However, the individualized diagnosis of MDD based on resting-state functional connectivity is still unclear, especially in first episode drug-naive patients with MDD. Resting state functional magnetic resonance imaging was enrolled from 30 first episode drug-naive patients with MDD and age- and gender-matched 31 healthy controls. Whole brain functional connectivity was computed and viewed as classification features. Multivariate pattern analysis (MVPA) was performed to discriminate patients with MDD from controls. The experimental results exhibited a correct classification rate of 82.25% (p < 0.001) with sensitivity of 83.87% and specificity of 80.64%. Almost all of the consensus connections (125/128) were cross-network interaction among default mode network (DMN), salience network (SN), central executive network (CEN), visual cortex network (VN), Cerebellum and Other. Moreover, the supramarginal gyrus exhibited high discriminative power in classification. Our findings suggested cross-network interaction can be used as an effective biomarker for MDD clinical diagnosis, which may reveal the potential pathological mechanism for major depression. The current study further confirmed reliable application of MVPA in discriminating MDD patients from healthy controls.

Higher Trait Impulsivity and Altered Frontostriatal Connectivity in Betel-Quid Dependent Individuals.

Objective: Betel quid dependency (BQD) is characterized by functional and structural brain alterations. Trait impulsivity may influence substance dependence by impacting its neurobiological underpinnings in the frontostriatal circuit. However, little is known about the trait impulsivity and its neural correlates in individuals with BQD. Methods: Forty-eight participants with BQD and 22 normal controls (NCs) were recruited and scanned on a 3T MRI scanner. Barratt impulsiveness scale (BIS) was used to measure trait impulsivity: motor, attention, and no plan impulsivity. We used voxel-based morphometry (VBM) to assess the relationship between trait impulsivity and gray matter volumes. The relevant clusters identified were served as regions of interest (ROI) seeds. The whole-volume psycho-physiological interactions (PPI) analysis was used to investigate the changes of functional connectivity related to ROI seeds in the cue-reactivity task condition (BQ and control images). Results: Behaviorally, the BQD group showed significantly higher trait impulsivity including motor and no plan impulsivity than the NCs group. VBM analyses showed that motor impulsivity was negatively associated with gray matter volume of right caudate in the whole sample. No difference in gray matter volume between the two groups was observed. PPI analyses showed that there was a significantly decreased functional connectivity between the right caudate and right dorsolateral prefrontal cortex (DLPFC) when watching BQ related images than control images in individuals with BQD. Furthermore, functional connectivity between the right caudate and right DLPFC was negatively correlated with BQ dependency scores. Conclusions: Our study demonstrated the structural basis of trait impulsivity in the caudate and provided evidence for abnormal interactions within frontostriatal circuitsin individuals with BQD, which may provide insight into the selection of potential novel therapeutic targets for the treatment of BQ dependency.

Dysfunction of the Prefrontal Cortex in Betel-Quid-Dependent Chewers.

Betel quid is the fourth most popular psychoactive agent worldwide. Imaging studies have found altered brain structure in prefrontal cortex (PFC) in betel-quid dependent (BQD) chewers. However, the brain function in PFC associated with BQ use still remains unclear. The present study aimed to examine brain functional activity in PFC in individuals with BQD. This study recruited 48 participants with BQD and 22 normal controls (NCs). Both BQ-specific cue reactivity and Go/NoGo tasks were administered with functional magnetic resonance imaging (fMRI). Behavioral results showed a deficit in the choice reaction time task in BQD group. The fMRI results of the cue reactivity task suggested that, individuals with BQD exhibited responses in right ventromedial PFC, left posterior cingulate cortex (PCC), left lateral parietal lobe (LPL), left middle temporal gyrus and left visual cortex, when seeing BQ images compared with control images. In the Go/NoGo task, relative to NCs group, individuals with BQD showed higher activity in right dorsolateral PFC, right PCC and bilateral LPL between NoGo and Go trials. Across these two tasks, we consistently found disrupted function in PFC in individuals with BQD, which might lead to impaired craving and response inhibition in BQ addiction. Results of current study might shed light on the neural mechanisms involved in BQ use, which could be used as potential guidelines for diagnosis and treatment of BQ dependence.

Personalized design technique for the dental occlusal surface based on conditional generative adversarial networks.

The tooth defect is a frequently occurring disease within the field of dental clinic. However, the traditional manual restoration for the defective tooth needs an especially long treatment time, and dental computer aided design and manufacture (CAD/CAM) systems fail to restore the personalized anatomical features of natural teeth. Aiming to address the shortcomings of existed methods, this article proposes an intelligent network model for designing tooth crown surface based on conditional generative adversarial networks. Then, the data set for training the network model is constructed via generating depth maps of 3D tooth models scanned by the intraoral. Through adversarial training, the network model is able to generate tooth occlusal surface under the constraint of the space occlusal relationship, the perceptual loss, and occlusal groove filter loss. Finally, we carry out the assessment experiments for the quality of the occlusal surface and the occlusal relationship with the opposing tooth. The experimental results demonstrate that our method can automatically reconstruct the personalized anatomical features on occlusal surface and shorten the treatment time while restoring the full functionality of the defective tooth.

The extraction method of tooth preparation margin line based on S-Octree CNN.

The tooth preparation margin line has a significant impact on the marginal fitness for dental restoration. Among the previous methods, the extraction of margin line mainly relies on manual interaction, which is complicated and inefficient. Therefore, we propose a method to extract the margin line with the convolutional neural network based on sparse octree (S-Octree) structure. First, the dental preparations are rotated to augment the dataset. Second, the preparation models are treated as the sparse point cloud with labels through the spatial partition method of the S-Octree. Then, based on the feature line, the dental preparation point cloud is automatically divided into two regions by the convolutional neural network (CNN). Third, in order to obtain the margin line, we adopt some methods such as the dense condition random field (dense CRF), point cloud reconstruction, and back projection to the original dental preparation model. Finally, based on the measurement indicators of accuracy, sensitivity, and specificity, the average accuracy of the label predicted by the network model can reach 97.43%. The experimental results show that our method can automatically accomplish the extraction of the tooth preparation margin line.

Executive function deficit in betel-quid-dependent chewers: Mediating role of prefrontal cortical thickness.

BACKGROUND: Betel quid is the fourth most popular psychoactive agent worldwide. Neuroimaging studies have suggested betel-quid dependence is accompanied by abnormality in brain structure and function. However, the neural correlates of executive function deficit and prefrontal cortical thickness associated with betel-quid chewing still remain unclear. OBJECTIVE: The present study aimed to examine the relationship between executive function deficit and prefrontal cortical thickness in chronic betel-quid chewers. METHODS: Twenty-three betel-quid-dependent chewers and 26 healthy controls were recruited to participate in this study. Executive function was tested using three tasks. Cortical thickness analysis was analyzed with the FreeSurfer software package. RESULTS: Behavioral results suggested a profound deficit of executive function in betel-quid-dependent chewers. Cortical thickness analysis revealed thinner cortex in the bilateral dorsolateral prefrontal cortex in betel-quid-dependent chewers. Further analysis suggested that cortical thickness of the bilateral dorsolateral prefrontal cortex mediated the correlation of betel-quid chewing and executive function. CONCLUSIONS: These results suggest the important role of executive function and cortical thickness of the dorsolateral prefrontal cortex with betel-quid chewing. Our findings provide evidence that executive function deficit may be mediated by the cortical thickness of the dorsolateral prefrontal cortex. These results could potentially help us develop novel ways to diagnose and prevent betel-quid dependence.

Complete denture tooth arrangement technology driven by a reconfigurable rule.

The conventional technique for the fabrication of complete dentures is complex, with a long fabrication process and difficult-to-control restoration quality. In recent years, digital complete denture design has become a research focus. Digital complete denture tooth arrangement is a challenging issue that is difficult to efficiently implement under the constraints of complex tooth arrangement rules and the patient's individualized functional aesthetics. The present study proposes a complete denture automatic tooth arrangement method driven by a reconfigurable rule; it uses four typical operators, including a position operator, a scaling operator, a posture operator, and a contact operator, to establish the constraint mapping association between the teeth and the constraint set of the individual patient. By using the process reorganization of different constraint operators, this method can flexibly implement different clinical tooth arrangement rules. When combined with a virtual occlusion algorithm based on progressive iterative Laplacian deformation, the proposed method can achieve automatic and individual tooth arrangement. Finally, the experimental results verify that the proposed method is flexible and efficient.

A combined strategy to enhance the properties of Zn by laser rapid solidification and laser alloying.

The orthopedic application of Zn is limited owing to the poor strength and low plasticity. In this study, a novel strategy by combining rapid solidification obtained by selective laser melting (SLM) and alloying with Mg was proposed to improve the mechanical properties of Zn. The microstructures, mechanical properties, as well as in vitro cytocompatibility of SLM processed Zn-xMg (x = 0-4 wt%) were studied systematically. Results shown that SLM processed Zn-xMg alloys consisted of fine equiaxed α-Zn grains with homogeneously precipitated Mg2Zn11 along grain boundaries. More importantly, the grains size of α-Zn was decreased from 104.4 ±â€¯30.4 µm to 4.9 ±â€¯1.4 µm with Mg increasing. And Mg mainly dissolved in α-Zn developing into supersaturated solid solution due to rapid solidification effect. As a consequence, the ultimate tensile strength and elongation were enhanced by 361% and 423%, respectively, with Mg containing up to 3 wt%. Meanwhile, alloying with Mg enhanced the corrosion resistance of Zn, with the degradation rate decreasing from 0.18 ±â€¯0.03 mm year-1 to 0.10 ±â€¯0.04 mm year-1. Furthermore, SLM processed Zn-xMg exhibited good biocompatibility. This research suggested that SLM processed Zn-3Mg alloy was a potential biomaterial for orthopedic applications.