Single-cell transcriptome profiling reveals neutrophil heterogeneity in homeostasis and infection.

The full neutrophil heterogeneity and differentiation landscape remains incompletely characterized. Here, we profiled >25,000 differentiating and mature mouse neutrophils using single-cell RNA sequencing to provide a comprehensive transcriptional landscape of neutrophil maturation, function and fate decision in their steady state and during bacterial infection. Eight neutrophil populations were defined by distinct molecular signatures. The three mature peripheral blood neutrophil subsets arise from distinct maturing bone marrow neutrophil subsets. Driven by both known and uncharacterized transcription factors, neutrophils gradually acquire microbicidal capability as they traverse the transcriptional landscape, representing an evolved mechanism for fine-tuned regulation of an effective but balanced neutrophil response. Bacterial infection reprograms the genetic architecture of neutrophil populations, alters dynamic transitions between subpopulations and primes neutrophils for augmented functionality without affecting overall heterogeneity. In summary, these data establish a reference model and general framework for studying neutrophil-related disease mechanisms, biomarkers and therapeutic targets at single-cell resolution.

The competition dynamics of approach and avoidance motivations following interpersonal transgression.

Two behavioral motivations coexist in transgressors following an interpersonal transgression-approaching and compensating the victim and avoiding the victim. Little is known about how these motivations arise, compete, and drive transgressors' decisions. The present study adopted a social interaction task to manipulate participants' (i.e., the transgressor) responsibility for another's (i.e., the victim) monetary loss and measure the participants' tradeoff between compensating the victim and avoiding face-to-face interactions with the victim. Following each transgression, participants used a computer mouse to choose between two options differing in the amount of compensation to the victim and the probability of face-to-face contact with the victim. Results showed that as participants' responsibility increased, 1) the decision weights on contact avoidance relative to compensation increased, and 2) the onset of the contact-avoidance attribute was expedited and that of the compensation attribute was delayed. These results demonstrate how competing social motivations following transgression evolve and determine social decision-making and shed light on how social-affective state modulates the dynamics of decision-making in general.

Atypical neural encoding of faces in individuals with autism spectrum disorder.

Individuals with autism spectrum disorder (ASD) experience pervasive difficulties in processing social information from faces. However, the behavioral and neural mechanisms underlying social trait judgments of faces in ASD remain largely unclear. Here, we comprehensively addressed this question by employing functional neuroimaging and parametrically generated faces that vary in facial trustworthiness and dominance. Behaviorally, participants with ASD exhibited reduced specificity but increased inter-rater variability in social trait judgments. Neurally, participants with ASD showed hypo-activation across broad face-processing areas. Multivariate analysis based on trial-by-trial face responses could discriminate participant groups in the majority of the face-processing areas. Encoding social traits in ASD engaged vastly different face-processing areas compared to controls, and encoding different social traits engaged different brain areas. Interestingly, the idiosyncratic brain areas encoding social traits in ASD were still flexible and context-dependent, similar to neurotypicals. Additionally, participants with ASD also showed an altered encoding of facial saliency features in the eyes and mouth. Together, our results provide a comprehensive understanding of the neural mechanisms underlying social trait judgments in ASD.

Dynamic Recruitment of the Feedforward and Recurrent Mechanism for Black-White Asymmetry in the Primary Visual Cortex.

Black and white information is asymmetrically distributed in natural scenes, evokes asymmetric neuronal responses, and causes asymmetric perceptions. Recognizing the universality and essentiality of black-white asymmetry in visual information processing, the neural substrates for black-white asymmetry remain unclear. To disentangle the role of the feedforward and recurrent mechanisms in the generation of cortical black-white asymmetry, we recorded the V1 laminar responses and LGN responses of anesthetized cats of both sexes. In a cortical column, we found that black-white asymmetry starts at the input layer and becomes more pronounced in the output layer. We also found distinct dynamics of black-white asymmetry between the output layer and the input layer. Specifically, black responses dominate in all layers after stimulus onset. After stimulus offset, black and white responses are balanced in the input layer, but black responses still dominate in the output layer. Compared with that in the input layer, the rebound response in the output layer is significantly suppressed. The relative suppression strength evoked by white stimuli is notably stronger and depends on the location within the ON-OFF cortical map. A model with delayed and polarity-selective cortical suppression explains black-white asymmetry in the output layer, within which prominent recurrent connections are identified by Granger causality analysis. In addition to black-white asymmetry in response strength, the interlaminar differences in spatial receptive field varied dynamically. Our findings suggest that the feedforward and recurrent mechanisms are dynamically recruited for the generation of black-white asymmetry in V1.SIGNIFICANCE STATEMENT Black-white asymmetry is universal and essential in visual information processing, yet the neural substrates for cortical black-white asymmetry remain unknown. Leveraging V1 laminar recordings, we provided the first laminar pattern of black-white asymmetry in cat V1 and found distinct dynamics of black-white asymmetry between the output layer and the input layer. Comparing black-white asymmetry across three visual hierarchies, the LGN, V1 input layer, and V1 output layer, we demonstrated that the feedforward and recurrent mechanisms are dynamically recruited for the generation of cortical black-white asymmetry. Our findings not only enhance our understanding of laminar processing within a cortical column but also elucidate how feedforward connections and recurrent connections interact to shape neuronal response properties.

Multiple gamma rhythms carry distinct spatial frequency information in primary visual cortex.

Gamma rhythms in many brain regions, including the primary visual cortex (V1), are thought to play a role in information processing. Here, we report a surprising finding of 3 narrowband gamma rhythms in V1 that processed distinct spatial frequency (SF) signals and had different neural origins. The low gamma (LG; 25 to 40 Hz) rhythm was generated at the V1 superficial layer and preferred a higher SF compared with spike activity, whereas both the medium gamma (MG; 40 to 65 Hz), generated at the cortical level, and the high gamma HG; (65 to 85 Hz), originated precortically, preferred lower SF information. Furthermore, compared with the rates of spike activity, the powers of the 3 gammas had better performance in discriminating the edge and surface of simple objects. These findings suggest that gamma rhythms reflect the neural dynamics of neural circuitries that process different SF information in the visual system, which may be crucial for multiplexing SF information and synchronizing different features of an object.

Photocatalytic Degradation of Tetracycline Hydrochloride Based on the Structure-Property Exploration of BiOCl.

The correlation between structure and properties in the photodegradation reaction of bismuth oxychloride (BiOCl) was explored in this work. Three BiOCl samples with different sizes, morphological structures, and defects were prepared through a hydrothermal method with experimental manipulation. Their structural properties were comprehensively characterized using X-ray diffraction, scanning electron microscopy, transmission electron microscopy, electron spin resonance, X-ray photoelectron spectroscopy, Fourier transform infrared spectroscopy, ultraviolet-visible diffuse reflectance spectroscopy, and photoluminescence. Taking the photodegradation of tetracycline hydrochloride (TC-HCl) as the probe reaction, we found that high activity could be achieved by decreasing their crystal size and thickness, introducing proper defects in the structure, and assembling the nanosheets to get microball structure. Combined with radical-scavenge experiments and electron spin resonance (ESR) spin-trap spectra, we conclude that ̇O2- was the dominant reactive oxygen species for the degradation reaction. The degradation detailed pathway of TC-HCl was further analyzed using liquid chromatography-mass spectrometry. This work explores the structure-property correlation of BiOCl and provides strategies for the rational design of active photocatalysts for water remediation.

Elucidating the association of obstructive sleep apnea with brain structure and cognitive performance.

BACKGROUND: Obstructive sleep apnea (OSA) is a pervasive, chronic sleep-related respiratory condition that causes brain structural alterations and cognitive impairments. However, the causal association of OSA with brain morphology and cognitive performance has not been determined. METHODS: We conducted a two-sample bidirectional Mendelian randomization (MR) analysis to investigate the causal relationship between OSA and a range of neurocognitive characteristics, including brain cortical structure, brain subcortical structure, brain structural change across the lifespan, and cognitive performance. Summary-level GWAS data for OSA from the FinnGen consortium was used to identify genetically predicted OSA. Data regarding neurocognitive characteristics were obtained from published meta-analysis studies. Linkage disequilibrium score regression analysis was employed to reveal genetic correlations between OSA and related traits. RESULTS: Our MR study provided evidence that OSA was found to significantly increase the volume of the hippocampus (IVW ß (95% CI) = 158.997 (76.768 to 241.227), P = 1.51e-04), with no heterogeneity and pleiotropy detected. Nominally causal effects of OSA on brain structures, such as the thickness of the temporal pole with or without global weighted, amygdala structure change, and cerebellum white matter change covering lifespan, were observed. Bidirectional causal links were also detected between brain cortical structure, brain subcortical, cognitive performance, and OSA risk. LDSC regression analysis showed no significant correlation between OSA and hippocampus volume. CONCLUSIONS: Overall, we observed a positive association between genetically predicted OSA and hippocampus volume. These findings may provide new insights into the bidirectional links between OSA and neurocognitive features, including brain morphology and cognitive performance.

Unsupervised speckle denoising in digital holographic interferometry based on 4-f optical simulation integrated cycle-consistent generative adversarial network.

The speckle noise generated during digital holographic interferometry (DHI) is unavoidable and difficult to eliminate, thus reducing its accuracy. We propose a self-supervised deep-learning speckle denoising method using a cycle-consistent generative adversarial network to mitigate the effect of speckle noise. The proposed method integrates a 4-f optical speckle noise simulation module with a parameter generator. In addition, it uses an unpaired dataset for training to overcome the difficulty in obtaining noise-free images and paired data from experiments. The proposed method was tested on both simulated and experimental data, with results showing a 6.9% performance improvement compared with a conventional method and a 2.6% performance improvement compared with unsupervised deep learning in terms of the peak signal-to-noise ratio. Thus, the proposed method exhibits superior denoising performance and potential for DHI, being particularly suitable for processing large datasets.

V1-origin Bidirectional Plasticity in Visual Thalamo-ventral Pathway and Its Contribution to Saliency Detection of Dynamic Visual Inputs.

Visual neural plasticity and V1 saliency-detection are vital for efficient-coding of dynamically changing visual inputs. However, how does neural plasticity contribute to saliency-detection of temporal-statistically distributed visual stream remains unclear. Therefore, we adopted randomly presented but unevenly distributed stimuli with multiple orientations, and examined the single-unit responses evoked by this biased orientation-adaptation protocol, by single-unit recordings in the visual thalamo-ventral pathway of cats (of either sex). We found neuronal responses potentiated when the probability of biased orientation was slightly higher than other non-biased ones, and suppressed when the probability became much higher. This single-neuronal short-term bidirectional-plasticity is selectively induced by optimal stimuli, but inter-ocularly transferable. It is inducible in LGN, Area 17 and Area 21a with distinct and hierarchically progressive patterns. With the results of latency-analysis, receptive-field structural test, cortical lesion and simulations, we suggest this bidirectional-plasticity may principally originate from the adaptation-competition between excitatory and inhibitory components of V1 neuronal receptive-field. In our simulation, above bidirectional-plasticity could achieve saliency-detection of dynamic visual inputs. These findings demonstrate a rapid probability-dependant plasticity on the neural coding of visual stream, and suggest its functional role in the efficient-coding and saliency-detection of dynamic environment.SIGNIFICANCE STATEMENTNovel elements within a dynamic visual stream can "pop-up" from the context, vital for rapid response to dynamically changing world. "Saliency-detection" is a promising bottom-up mechanism contributing to efficient selection of visual inputs, wherein visual adaptation also plays a significant role. However, the saliency-detection of dynamic visual stream is poorly understood. Here we found a novel form of visual short-term bidirectional-plasticity in multi-stages of visual system that contributes to saliency-detection of dynamic visual inputs. This bidirectional-plasticity may principally originate from the local balance of excitation-inhibition in primary visual cortex, and propagates to lower and higher visual areas with progressive pattern-change. Our findings suggest the excitation-inhibition balance within visual system contributing to visual efficient-coding.

Cognitive and neural bases of visual-context-guided decision-making.

Humans adjust their behavioral strategies based on feedback, a process that may depend on intrinsic preferences and contextual factors such as visual salience. In this study, we hypothesized that decision-making based on visual salience is influenced by habitual and goal-directed processes, which can be evidenced by changes in attention and subjective valuation systems. To test this hypothesis, we conducted a series of studies to investigate the behavioral and neural mechanisms underlying visual salience-driven decision-making. We first established the baseline behavioral strategy without salience in Experiment 1 (n = 21). We then highlighted the utility or performance dimension of the chosen outcome using colors in Experiment 2 (n = 30). We demonstrated that the difference in staying frequency increased along the salient dimension, confirming a salience effect. Furthermore, the salience effect was abolished when directional information was removed in Experiment 3 (n = 28), suggesting that the salience effect is feedback-specific. To generalize our findings, we replicated the feedback-specific salience effects using eye-tracking and text emphasis. The fixation differences between the chosen and unchosen values were enhanced along the feedback-specific salient dimension in Experiment 4 (n = 48) but unchanged after removing feedback-specific information in Experiment 5 (n = 32). Moreover, the staying frequency was correlated with fixation properties, confirming that salience guides attention deployment. Lastly, our neuroimaging study (Experiment 6, n = 25) showed that the striatum subregions encoded salience-based outcome evaluation, while the vmPFC encoded salience-based behavioral adjustments. The connectivity of the vmPFC-ventral striatum accounted for individual differences in utility-driven, whereas the vmPFC-dmPFC for performance-driven behavioral adjustments. Together, our results provide a neurocognitive account of how task-irrelevant visual salience drives decision-making by involving attention and the frontal-striatal valuation systems. PUBLIC SIGNIFICANCE STATEMENT: Humans may use the current outcome to make behavior adjustments. How this occurs may depend on stable individual preferences and contextual factors, such as visual salience. Under the hypothesis that visual salience determines attention and subsequently modulates subjective valuation, we investigated the underlying behavioral and neural bases of visual-context-guided outcome evaluation and behavioral adjustments. Our findings suggest that the reward system is orchestrated by visual context and highlight the critical role of attention and the frontal-striatal neural circuit in visual-context-guided decision-making that may involve habitual and goal-directed processes.

Neural representations of vicarious rewards are linked to interoception and prosocial behaviour.

Every day we constantly observe other people receiving rewards. Theoretical accounts posit that vicarious reward processing might be linked to people's sensitivity to internal body states (interoception) and facilitates a tendency to act prosocially. However, the neural processes underlying the links between vicarious reward processing, interoception, and prosocial behaviour are poorly understood. Previous research has linked vicarious reward processing to the anterior cingulate gyrus (ACCg) and the anterior insula (AI). Can we predict someone's propensity to be prosocial or to be aware of interoceptive signals from variability in how the ACCg and AI process rewards? Here, participants monitored rewards being delivered to themselves or a stranger during functional magnetic resonance imaging. Later, they performed a task measuring their willingness to exert effort to obtain rewards for others, and a task measuring their propensity to be aware and use interoceptive respiratory signals. Using multivariate similarity analysis, we show that people's willingness to be prosocial is predicted by greater similarity between self and other representations in the ACCg. Moreover, greater dissimilarity in self-other representations in the AI is linked to interoceptive propensity. These findings highlight that vicarious reward is linked to bodily signals in AI, and foster prosocial tendencies through the ACCg.

A key O-demethylase in the degradation of guaiacol by Rhodococcus opacus PD630.

Rhodococcus opacus PD630 is a high oil-producing strain with the ability to convert lignin-derived aromatics to high values, but limited research has been done to elucidate its conversion pathway, especially the upper pathways. In this study, we focused on the upper pathways and demethylation mechanism of lignin-derived aromatics metabolism by R. opacus PD630. The results of the aromatic carbon resource utilization screening showed that R. opacus PD630 had a strong degradation capacity to the lignin-derived methoxy-containing aromatics, such as guaiacol, 3,4-veratric acid, anisic acid, isovanillic acid, and vanillic acid. The gene of gcoAR, which encodes cytochrome P450, showed significant up-regulation when R. opacus PD630 grew on diverse aromatics. Deletion mutants of gcoAR and its partner protein gcoBR resulted in the strain losing the ability to grow on guaiacol, but no significant difference to the other aromatics. Only co-complementation alone of gcoAR and gcoBR restored the strain's ability to utilize guaiacol, demonstrating that both genes were equally important in the utilization of guaiacol. In vitro assays further revealed that GcoAR could convert guaiacol and anisole to catechol and phenol, respectively, with the production of formaldehyde as a by-product. The study provided robust evidence to reveal the molecular mechanism of R. opacus PD630 on guaiacol metabolism and offered a promising study model for dissecting the demethylation process of lignin-derived aromatics in microbes.IMPORTANCEAryl-O-demethylation is believed to be the key rate-limiting step in the catabolism of heterogeneous lignin-derived aromatics in both native and engineered microbes. However, the mechanisms of O-demethylation in lignin-derived aromatic catabolism remain unclear. Notably, guaiacol, the primary component unit of lignin, lacks in situ demonstration and illustration of the molecular mechanism of guaiacol O-demethylation in lignin-degrading bacteria. This is the first study to illustrate the mechanism of guaiacol metabolism by R. opacus PD630 in situ as well as characterize the purified key O-demethylase in vitro. This study provided further insight into the lignin metabolic pathway of R. opacus PD630 and could guide the design of an efficient biocatalytic system for lignin valorization.

Comprehensive Social Trait Judgments From Faces in Autism Spectrum Disorder.

Processing social information from faces is difficult for individuals with autism spectrum disorder (ASD). However, it remains unclear whether individuals with ASD make high-level social trait judgments from faces in the same way as neurotypical individuals. Here, we comprehensively addressed this question using naturalistic face images and representatively sampled traits. Despite similar underlying dimensional structures across traits, online adult participants with self-reported ASD showed different judgments and reduced specificity within each trait compared with neurotypical individuals. Deep neural networks revealed that these group differences were driven by specific types of faces and differential utilization of features within a face. Our results were replicated in well-characterized in-lab participants and partially generalized to more controlled face images (a preregistered study). By investigating social trait judgments in a broader population, including individuals with neurodevelopmental variations, we found important theoretical implications for the fundamental dimensions, variations, and potential behavioral consequences of social cognition.

Understanding guilt-related interpersonal dysfunction in obsessive-compulsive personality disorder through computational modeling of two social interaction tasks.

BACKGROUND: Obsessive-compulsive personality disorder (OCPD) is a high-prevalence personality disorder characterized by subtle but stable interpersonal dysfunction. There have been only limited studies addressing the behavioral patterns and cognitive features of OCPD in interpersonal contexts. The purpose of this study was to investigate how behaviors differ between OCPD individuals and healthy controls (HCs) in the context of guilt-related interpersonal responses. METHOD: A total of 113 participants were recruited, including 46 who were identified as having OCPD and 67 HCs. Guilt-related interpersonal responses were manipulated and measured with two social interactive tasks: the Guilt Aversion Task, to assess how anticipatory guilt motivates cooperation; and the Guilt Compensation Task, to assess how experienced guilt induces compensation behaviors. The guilt aversion model and Fehr-Schmidt inequity aversion model were adopted to analyze decision-making in the Guilt Aversion Task and the Guilt Compensation Task, respectively. RESULTS: Computational model-based results demonstrated that, compared with HCs, the OCPD group exhibited less guilt aversion when making cooperative decisions as well as less guilt-induced compensation after harming others. CONCLUSION: Our findings indicate that individuals with OCPD tend to be less affected by guilt than HCs. These impairments in guilt-related responses may prevent adjustments in behaviors toward compliance with social norms and thus result in interpersonal dysfunctions.

Three-dimensional printed titanium mesh combined with iliac cancellous bone in the reconstruction of mandibular defects secondary to ameloblastoma resection.

BACKGROUND: The reconstruction of large mandibular defects is a challenge, and free vascularized bone flaps are most commonly used. However, the precision and symmetry of this repair are deficient, and patients have a risk of vascular embolism, flap necrosis, and donor site complications. Therefore, to explore an ideal alternative in mandibular reconstruction with high surgical accuracy and low complications is indispensable. METHODS: Seven patients with recurrent or large-scope ameloblastoma were enrolled in this study. All patients were provided with a fully digital treatment plan, including the design of osteotomy lines, surgical guides, and three-dimensional printed titanium mesh for implantation. With the assistance of surgical guide, ameloblastomas were resected, and custom 3D printed titanium mesh combined with posterior iliac bone harvest was used in mandibular reconstruction. A comparison was made between the discrepant surgical outcomes and the intended surgical plan, as well as the average three-dimensional deviation of the mandible before and after the surgery. At the same time, the resorption rate of the implanted bone was evaluated. RESULTS: All patients completed the fully digital treatment process successfully without severe complications. Image fusion showed that the postoperative contour of the mandible was basically consistent with surgical planning, except for a slight increase in the inferior border of the affected side. The mean three-dimensional deviation of the mandible between the preoperative and postoperative periods was 0.78 ± 0.41 mm. The mean error between the intraoperative bone volume and the digital planning bone volume was 2.44%±2.10%. Furthermore, the bone resorption rates of the harvested graft 6 months later were 32.15%±6.95%. CONCLUSIONS: The use of digital surgical planning and 3D-printed templates can assist surgeons in performing surgery precisely, and the 3D-printed titanium mesh implant can improve the patient's facial symmetry. 3D printed titanium mesh combined with posterior iliac cancellous bone graft can be regarded as an ideal alternative in extensive mandibular reconstruction.

The application of a fully digital approach in the treatment of skeletal class III malocclusion: a preliminary study.

BACKGROUND: Skeletal malocclusion patients have facial malformations and occlusal dysfunctions that require orthodontic-orthognathic joint treatment, while the combination treatment takes time and requires close communication between surgeons and orthodontists. Thus, improving the efficiency and effectiveness of the combination treatment is necessary, and it is still a challenge. Now, digital technology provides us with an excellent alternative. Despite the widespread use of digital technology in orthognathic surgery simulation and clear aligner orthodontic therapy, it has not been fully integrated into the combined orthognathic and orthodontic treatment process, and the components remain independent. METHODS: A fully digital approach to seamlessly integrating various parts of the combined treatment through digital technology was investigated in this study in order to achieve an efficient transition. Five patients with skeletal Class III malocclusion were enrolled, and all made fully digital treatment plans at the beginning of actual implementation, which included the design of pre-surgical orthodontic, orthognathic surgery, and post-surgical orthodontic. Then, every aspect of the clinical operation was carried out in accordance with the fully digital routine. After the entire treatment process was completed, the skeleton and dentition discrepancy between virtual planning and the actual result was evaluated. RESULTS: All participants completed the fully digital treatment process, and no complication was observed. The linear deviation of the skeletal anatomy was less than 1 mm, and the angular deviation was less than 1 degree. Except in one case in the lower dentition, the deviation of the virtual dental design from the real alignment was less than 2 mm. Furthermore, with one exception of maxillary anterior-posterior dimension, the linear deviations of the skeleton were not statistically significant. Therefore, the simulation accuracy of the fully digital approach was clinically acceptable. CONCLUSIONS: The digital treatment approach is clinically feasible and has achieved satisfactory results. The discrepancy between virtual design of the entire digital process and actual post-treatment situation was acceptable in clinic. A fully digital approach was proved effective in the treatment of skeletal Class III malocclusion, with which the efficient transition of treatment procedures was realized.

Automatic craniomaxillofacial landmarks detection in CT images of individuals with dentomaxillofacial deformities by a two-stage deep learning model.

BACKGROUND: Accurate cephalometric analysis plays a vital role in the diagnosis and subsequent surgical planning in orthognathic and orthodontics treatment. However, manual digitization of anatomical landmarks in computed tomography (CT) is subject to limitations such as low accuracy, poor repeatability and excessive time consumption. Furthermore, the detection of landmarks has more difficulties on individuals with dentomaxillofacial deformities than normal individuals. Therefore, this study aims to develop a deep learning model to automatically detect landmarks in CT images of patients with dentomaxillofacial deformities. METHODS: Craniomaxillofacial (CMF) CT data of 80 patients with dentomaxillofacial deformities were collected for model development. 77 anatomical landmarks digitized by experienced CMF surgeons in each CT image were set as the ground truth. 3D UX-Net, the cutting-edge medical image segmentation network, was adopted as the backbone of model architecture. Moreover, a new region division pattern for CMF structures was designed as a training strategy to optimize the utilization of computational resources and image resolution. To evaluate the performance of this model, several experiments were conducted to make comparison between the model and manual digitization approach. RESULTS: The training set and the validation set included 58 and 22 samples respectively. The developed model can accurately detect 77 landmarks on bone, soft tissue and teeth with a mean error of 1.81 ± 0.89 mm. Removal of region division before training significantly increased the error of prediction (2.34 ± 1.01 mm). In terms of manual digitization, the inter-observer and intra-observer variations were 1.27 ± 0.70 mm and 1.01 ± 0.74 mm respectively. In all divided regions except Teeth Region (TR), our model demonstrated equivalent performance to experienced CMF surgeons in landmarks detection (p > 0.05). CONCLUSIONS: The developed model demonstrated excellent performance in detecting craniomaxillofacial landmarks when considering manual digitization work of expertise as benchmark. It is also verified that the region division pattern designed in this study remarkably improved the detection accuracy.

Prediction of orthognathic surgery plan from 3D cephalometric analysis via deep learning.

BACKGROUND: Preoperative planning of orthognathic surgery is indispensable for achieving ideal surgical outcome regarding the occlusion and jaws' position. However, orthognathic surgery planning is sophisticated and highly experience-dependent, which requires comprehensive consideration of facial morphology and occlusal function. This study aimed to investigate a robust and automatic method based on deep learning to predict reposition vectors of jawbones in orthognathic surgery plan. METHODS: A regression neural network named VSP transformer was developed based on Transformer architecture. Firstly, 3D cephalometric analysis was employed to quantify skeletal-facial morphology as input features. Next, input features were weighted using pretrained results to minimize bias resulted from multicollinearity. Through encoder-decoder blocks, ten landmark-based reposition vectors of jawbones were predicted. Permutation importance (PI) method was used to calculate contributions of each feature to final prediction to reveal interpretability of the proposed model. RESULTS: VSP transformer model was developed with 383 samples and clinically tested with 49 prospectively collected samples. Our proposed model outperformed other four classic regression models in prediction accuracy. Mean absolute errors (MAE) of prediction were 1.41 mm in validation set and 1.34 mm in clinical test set. The interpretability results of the model were highly consistent with clinical knowledge and experience. CONCLUSIONS: The developed model can predict reposition vectors of orthognathic surgery plan with high accuracy and good clinically practical-effectiveness. Moreover, the model was proved reliable because of its good interpretability.

Neural and Cognitive Signatures of Guilt Predict Hypocritical Blame.

A common form of moral hypocrisy occurs when people blame others for moral violations that they themselves commit. It is assumed that hypocritical blamers act in this manner to falsely signal that they hold moral standards that they do not really accept. We tested this assumption by investigating the neurocognitive processes of hypocritical blamers during moral decision-making. Participants (62 adult UK residents; 27 males) underwent functional MRI scanning while deciding whether to profit by inflicting pain on others and then judged the blameworthiness of others' identical decisions. Observers (188 adult U.S. residents; 125 males) judged participants who blamed others for making the same harmful choice to be hypocritical, immoral, and untrustworthy. However, analyzing hypocritical blamers' behaviors and neural responses shows that hypocritical blame was positively correlated with conflicted feelings, neural responses to moral standards, and guilt-related neural responses. These findings demonstrate that hypocritical blamers may hold the moral standards that they apply to others.

Improving the Electrocatalytic Activity of a Nickel-Organic Framework toward the Oxygen Evolution Reaction through Vanadium Doping.

Metal-organic frameworks (MOFs) have been considered as potential oxygen evolution reaction (OER) electrocatalysts owning to their ultra-thin structure, adjustable composition, high surface area, and high porosity. Here, we designed and fabricated a vanadium-doped nickel organic framework (V1-x -Nix MOF) system by using a facile two-step solvothermal method on nickel foam (NF). The doping of vanadium remarkably elevates the OER activity of V1-x -Nix MOF, thus demonstrating better performance than the corresponding single metallic Ni-MOF, NiV-MOF and RuO2 catalysts at high current density (>400 mA cm-2 ). V0.09 -Ni0.91 MOF/NF provides a low overpotential of 235 mV and a small Tafel slope of 30.3 mV dec-1 at a current density of 10 mA cm-2 . More importantly, a water-splitting device assembled with Pt/C/NF and V0.09 -Ni0.91 MOF/NF as cathode and anode yielded a cell voltage of 1.96 V@1000 mA cm-2 , thereby outperforming the-state-of-the-art RuO2 (+) ||Pt/C(-) . Our work sheds new insight on preparing stable, efficient OER electrocatalysts and a promising method for designing various MOF-based materials.