b-MAR: bidirectional artifact representations learning framework for metal artifact reduction in dental CBCT.

Objective.Metal artifacts in computed tomography (CT) images hinder diagnosis and treatment significantly. Specifically, dental cone-beam computed tomography (Dental CBCT) images are seriously contaminated by metal artifacts due to the widespread use of low tube voltages and the presence of various high-attenuation materials in dental structures. Existing supervised metal artifact reduction (MAR) methods mainly learn the mapping of artifact-affected images to clean images, while ignoring the modeling of the metal artifact generation process. Therefore, we propose the bidirectional artifact representations learning framework to adaptively encode metal artifacts caused by various dental implants and model the generation and elimination of metal artifacts, thereby improving MAR performance.Approach.Specifically, we introduce an efficient artifact encoder to extract multi-scale representations of metal artifacts from artifact-affected images. These extracted metal artifact representations are then bidirectionally embedded into both the metal artifact generator and the metal artifact eliminator, which can simultaneously improve the performance of artifact removal and artifact generation. The artifact eliminator learns artifact removal in a supervised manner, while the artifact generator learns artifact generation in an adversarial manner. To further improve the performance of the bidirectional task networks, we propose artifact consistency loss to align the consistency of images generated by the eliminator and the generator with or without embedding artifact representations.Main results.To validate the effectiveness of our algorithm, experiments are conducted on simulated and clinical datasets containing various dental metal morphologies. Quantitative metrics are calculated to evaluate the results of the simulation tests, which demonstrate b-MAR improvements of >1.4131 dB in PSNR, >0.3473 HU decrements in RMSE, and >0.0025 promotion in structural similarity index measurement over the current state-of-the-art MAR methods. All results indicate that the proposed b-MAR method can remove artifacts caused by various metal morphologies and restore the structural integrity of dental tissues effectively.Significance.The proposed b-MAR method strengthens the joint learning of the artifact removal process and the artifact generation process by bidirectionally embedding artifact representations, thereby improving the model's artifact removal performance. Compared with other comparison methods, b-MAR can robustly and effectively correct metal artifacts in dental CBCT images caused by different dental metals.

Supervised convex clustering.

Clustering has long been a popular unsupervised learning approach to identify groups of similar objects and discover patterns from unlabeled data in many applications. Yet, coming up with meaningful interpretations of the estimated clusters has often been challenging precisely due to their unsupervised nature. Meanwhile, in many real-world scenarios, there are some noisy supervising auxiliary variables, for instance, subjective diagnostic opinions, that are related to the observed heterogeneity of the unlabeled data. By leveraging information from both supervising auxiliary variables and unlabeled data, we seek to uncover more scientifically interpretable group structures that may be hidden by completely unsupervised analyses. In this work, we propose and develop a new statistical pattern discovery method named supervised convex clustering (SCC) that borrows strength from both information sources and guides towards finding more interpretable patterns via a joint convex fusion penalty. We develop several extensions of SCC to integrate different types of supervising auxiliary variables, to adjust for additional covariates, and to find biclusters. We demonstrate the practical advantages of SCC through simulations and a case study on Alzheimer's disease genomics. Specifically, we discover new candidate genes as well as new subtypes of Alzheimer's disease that can potentially lead to better understanding of the underlying genetic mechanisms responsible for the observed heterogeneity of cognitive decline in older adults.

Topological defect-propelled swimming of nematic colloids.

Topological defects on colloids rotating in nematic liquid crystals form far-from-equilibrium structures that perform complex swim strokes in which the defects periodically extend, depin, and contract. These defect dynamics propel the colloid, generating translation from rotation. The swimmer's speed and direction are determined by the topological defect's polarity and extent of elongation. Defect elongation is controlled by a rotating external magnetic field, allowing control over particle trajectories. The swimmers' translational motion relies on broken symmetries associated with lubrication forces between the colloid and the bounding surfaces, line tensions associated with the elongated defect, and anisotropic viscosities associated with the defect elongation adjacent to the colloid. The scattering or effective pair interaction of these swimmers is highly anisotropic, with polarization-dependent dimer stability and motion that depend strongly on entanglement and sharing of their extended defect structures. This research introduces transient, far-from-equilibrium topological defects as a class of virtual functional structures that generate modalities of motion and interaction.

Alterations in degree centrality and cognitive function in breast cancer patients after chemotherapy.

The goal of this study was to determine the presence or absence of persistent functional impairments in specific brain regions in breast cancer patients during the recovery period after chemotherapy. We calculated degree centrality (DC) and explored the correlation between brain changes and cognitive scores in 29 female patients with breast cancer who had completed chemotherapy within 1-6 years (C + group) and in 28 age-matched patients with breast cancer who did not receive chemotherapy (C- group). All patients underwent rs-fMRI and cognitive testing. Differences in brain functional activity were explored using DC parameters. Correlations between brain features and cognitive scores were analyzed via correlation analysis. Compared with the C- group, the C + group obtained significantly lower motor and cognitive subscores on the Fatigue Scale for Motor and Cognitive Functions and four subscale scores of the Functional Assessment of Cancer Therapy-Cognitive Function (P < 0.05). Furthermore, the C + group exhibited a significantly higher DC z-score (zDC) in the right superior temporal gyrus and left postcentral gyrus (P < 0.01, FWE-corrected), and a lower zDC in the left caudate nucleus (P < 0.01, FWE-corrected). We found a positive correlation between digit symbol test (DST) scores and zDC values in the right superior temporal gyrus (r = 0.709, P < 0.001), and a negative correlation between DST scores and zDC values in the right angular gyrus (r = -0.784, P < 0.001) and left superior parietal gyrus (r = -0.739, P < 0.001). Chemotherapy can cause abnormal brain activity and cognitive decline in patients with breast cancer, and these effects are likely to persist. DC can be used as an imaging marker for chemotherapy-related cognitive impairment after chemotherapy in breast cancer patients.

Mitochondrial Genomes of Two Asexual Trichogramma (Hymenoptera: Trichogrammatidae) Strains and Comparison with Their Sexual Relatives.

Despite its substantial costs, sexual reproduction dominates in animals. One popular explanation for the paradox of sex is that asexual reproduction is more likely to accumulate deleterious mutations than sexual reproduction. To test this hypothesis, we compared the mitogenomes of two asexual wasp strains, Trichogramma cacoeciae and T. pretiosum, to their sexual relatives. These two asexual strains represent two different transition mechanisms in Trichogramma from sexual to asexual reproduction. Asexual T. pretiosum is induced by Wolbachia, while T. cacoeciae presumably originated from interspecific hybridization. We sequenced and assembled complete mitochondrial genomes of asexual T. cacoeciae and T. pretiosum. Compared to four sexual relatives, we found no evidence of higher mutation accumulation in asexual Trichogramma mitogenomes than in their sexual relatives. We also did not detect any relaxed selection in asexual Trichogramma mitogenomes. In contrast, the intensified selection was detected in Nad1 and Nad4 of the asexual T. pretiosum mitogenome, suggesting more purifying selection. In summary, no higher mitochondrial mutation accumulation was detected in these two asexual Trichogramma strains. This study provides a basis for further investigating mitochondrial evolution and asexual reproduction in Trichogramma.

Study on Surface Discharge Characteristics of GO-Doped Epoxy Resin-LN2 Composite Insulation.

Superconducting power lead equipment for epoxy insulation, such as high-temperature superconducting DC power or liquefied natural gas energy pipelines, as well as high-temperature superconducting cables, has long been used in extreme environments, from liquid nitrogen temperatures to normal temperatures. It is easy to induce surface discharge and flashover under the action of strong electric field, which accelerates the insulation failure of current leads. In this paper, two-dimensional nano-material GO was used to control the electrical properties of epoxy resins. The DC surface discharge and flashover characteristics of the prepared epoxy resin-GO composite insulation materials were tested at room temperature with liquid nitrogen. The surface discharge mechanism of the epoxy resin-GO composite insulation materials was analyzed. The experimental results show that the insulation properties of epoxy composites doped with GO changed. Among them, the surface flashover voltage of 0.05 wt% material is the best, which can inhibit the discharge phenomenon and improve its insulation properties in extreme environments, from room temperature to liquid nitrogen temperature. It is found that the development process of surface discharge of composite insulating materials under liquid nitrogen is quite different from that under room temperature. Before critical flashover, the repetition rate and amplitude of surface discharge remain at a low level until critical flashover. Furthermore, the voltage of the first flashover is significantly higher than that of the subsequent flashover under the action of the desorption gas on the surface of the composite insulating material and the gasification layer produced by the discharge. Given that the surface flashover voltage of 0.05 wt% epoxy composite is the best, the research and analysis of 0.05 wt% composite is emphasized. In the future design of superconducting power lead insulation, the modification method of adding GO to epoxy resin can be considered in order to improve its insulation performance.

Minipatch Learning as Implicit Ridge-Like Regularization.

Ridge-like regularization often leads to improved generalization performance of machine learning models by mitigating overfitting. While ridge-regularized machine learning methods are widely used in many important applications, direct training via optimization could become challenging in huge data scenarios with millions of examples and features. We tackle such challenges by proposing a general approach that achieves ridge-like regularization through implicit techniques named Minipatch Ridge (MPRidge). Our approach is based on taking an ensemble of coefficients of unregularized learners trained on many tiny, random subsamples of both the examples and features of the training data, which we call minipatches. We empirically demonstrate that MPRidge induces an implicit ridge-like regularizing effect and performs nearly the same as explicit ridge regularization for a general class of predictors including logistic regression, SVM, and robust regression. Embarrassingly parallelizable, MPRidge provides a computationally appealing alternative to inducing ridge-like regularization for improving generalization performance in challenging big-data settings.

TPGS and chondroitin sulfate dual-modified lipid-albumin nanosystem for targeted delivery of chemotherapeutic agent against multidrug-resistant cancer.

Multidrug resistance (MDR) remains the primary issue leading to the failure of chemotherapy. In this study, a d-α-tocopherol polyethylene 1000 glycol succinate (TPGS) and chondroitin sulfate (CS) dual-modified lipid-albumin nanosystem was constructed for targeted delivery of paclitaxel (PTX) in treating MDR cancer. The obtained nanosystem (TLA/PTX@CS) had an average size of around 176 nm and a negative zeta potential of around -18 mV. TPGS was confirmed to improve the intracellular accumulation of PTX and facilitate the mitochondrial-targeting of lipid-albumin nanosystem. Functionalized with the outer CS shell, TLA/PTX@CS entered MDR breast cancer (MCF-7/MDR) cells via CD44 receptor-mediated endocytosis. CS shell was degraded by concentrated hyaluronidase in the lysosomes, thereby releasing PTX into cytoplasm and inhibiting cell proliferation. In vivo studies revealed that TLA/PTX@CS possessed prolonged blood circulation, resulting in elevated tumor accumulation, excellent antitumor efficacy with a tumor inhibition ratio of 75.3%, and significant survival benefit in MCF-7/MDR tumor-bearing mice. Hence, this TPGS and CS dual-modified lipid-albumin nanosystem provides a promising strategy for targeted delivery of chemotherapeutic drug and reversal of MDR in cancer treatment.

Quantifying cognitive resilience in Alzheimer's Disease: The Alzheimer's Disease Cognitive Resilience Score.

Even though there is a clear link between Alzheimer's Disease (AD) related neuropathology and cognitive decline, numerous studies have observed that healthy cognition can exist in the presence of extensive AD pathology, a phenomenon sometimes called Cognitive Resilience (CR). To better understand and study CR, we develop the Alzheimer's Disease Cognitive Resilience Score (AD-CR Score), which we define as the difference between the observed and expected cognition given the observed level of AD pathology. Unlike other definitions of CR, our AD-CR Score is a fully non-parametric, stand-alone, individual-level quantification of CR that is derived independently of other factors or proxy variables. Using data from two ongoing, longitudinal cohort studies of aging, the Religious Orders Study (ROS) and the Rush Memory and Aging Project (MAP), we validate our AD-CR Score by showing strong associations with known factors related to CR such as baseline and longitudinal cognition, non AD-related pathology, education, personality, APOE, parkinsonism, depression, and life activities. Even though the proposed AD-CR Score cannot be directly calculated during an individual's lifetime because it uses postmortem pathology, we also develop a machine learning framework that achieves promising results in terms of predicting whether an individual will have an extremely high or low AD-CR Score using only measures available during the lifetime. Given this, our AD-CR Score can be used for further investigations into mechanisms of CR, and potentially for subject stratification prior to clinical trials of personalized therapies.

Surface States Enhanced Dynamic Schottky Diode Generator with Extremely High Power Density Over 1000 W m-2.

The overloaded energy cost has become the main concern of the now fast developing society, which make novel energy devices with high power density of critical importance to the sustainable development of human society. Herein, a dynamic Schottky diode based generator with ultrahigh power density of 1262.0 W m-2 for sliding Fe tip on rough p-type silicon is reported. Intriguingly, the increased surface states after rough treatment lead to an extremely enhanced current density up to 2.7 × 105 A m-2, as the charged surface states can effectively accelerate the carriers through large atomic electric field, while the reflecting directions are regulated by the built-in electric field of the Schottky barrier. This research provides an open avenue for utilizing the surface states in semiconductors in a subversive way, which can co-utilize the atomic electric field and built-in electric field to harvest energy from the mechanical movements, especially for achieving an ultrahigh current density power source.

A synergetic enhancement of localized surface plasmon resonance and photo-induced effect for graphene/GaAs photodetector.

Photodetectors based on graphene/GaAs heterostructure were fabricated and demonstrated for application in self-powered photodetection. Then, Si quantum dots (QDs) were spin-coated onto the surface of the devices to enhance the built-in field by photo-induced doping, because of the tunable Fermi level (E F) of graphene and shallow junction of the heterojunction. Additionally, Au nanoparticles working as a light trapping structure were used to the enhance quantum efficiency of the Si QDs and the optical absorption of the heterojunction, benefitting from localized surface plasmon resonance. Therefore, a large-area photodetector under self-powered conditions achieved a high performance i.e. responsivity (1.81 × 105 V W-1), detectivity (2.0 × 1012 Jones), fast response speed (<0.04 ms), and on-off ratio (6 × 103). The high voltage responsivity opens a promising pathway to ultra-weak light detection, and facilities the development of novel sensors.

Deck the Walls with Anisotropic Colloids in Nematic Liquid Crystals.

Nematic liquid crystals (NLCs) offer remarkable opportunities to direct colloids to form complex structures. The elastic energy field that dictates colloid interactions is determined by the NLC director field, which is sensitive to and can be controlled by boundaries including vessel walls and colloid surfaces. By molding the director field via liquid-crystal alignment on these surfaces, elastic energy landscapes can be defined to drive structure formation. We focus on colloids in otherwise defect-free director fields formed near undulating walls. Colloids can be driven along prescribed paths and directed to well-defined docking sites on such wavy boundaries. Colloids that impose strong alignment generate topologically required companion defects. Configurations for homeotropic colloids include a dipolar structure formed by the colloid and its companion hedgehog defect or a quadrupolar structure formed by the colloid and its companion Saturn ring. Adjacent to wavy walls with wavelengths larger than the colloid diameter, spherical particles are attracted to locations along the wall with distortions in the nematic director field that complement those from the colloid. This is the basis of lock-and-key interactions. Here, we study ellipsoidal colloids with homeotropic anchoring near complex undulating walls. The walls impose distortions that decay with distance from the wall to a uniform director in the far field. Ellipsoids form dipolar defect configurations with the colloid's major axis aligned with the far field director. Two distinct quadrupolar defect structures also form, stabilized by confinement; these include the Saturn I configuration with the ellipsoid's major axis aligned with the far field director and the Saturn II configuration with the major axis perpendicular to the far field director. The ellipsoid orientation varies only weakly in bulk and near undulating walls. All configurations are attracted to walls with long, shallow waves. However, for walls with wavelengths that are small compared to the colloid length, Saturn II is repelled, allowing selective docking of aligned objects. Deep, narrow wells prompt the insertion of a vertical ellipsoid. By introducing an opening at the bottom of such a deep well, we study colloids within pores that connect two domains. Ellipsoids with different aspect ratios find different equilibrium positions. An ellipsoid of the right dimension and aspect ratio can plug the pore, creating a class of 2D selective membranes.

Immunomodulatory properties of graphene oxide for osteogenesis and angiogenesis.

BACKGROUND: The osteo-immunomodulatory properties of biomaterials play an important role in the outcomes of bone regeneration. Graphene oxide (GO) has been widely applied in many research fields due to its unique properties. However, the immunomodulatory properties of GO as a biomaterial for bone tissue engineering are still unclear. MATERIALS AND METHODS: In this study, we evaluated the Inflammatory response of RAW264.7 cells influenced by GO. Then the osteogenic differentiation of BMSCs, and angiogenic differentiation of human umbilical vein endothelial cells (HUVECs) by stimulation with GO/RAW 264.7-conditioned culture medium were accessed. We also further investi gated the possible mechanisms underlying the osteo- and angio-immunomodulatory effects of GO. RESULTS: Our results showed that GO stimulates the secretion of oncostatin M, tumor necrosis factor alpha and other factors through the nuclear factor-κB pathway. GO/RAW264.7-conditioned medium promoted the osteogenic differentiation of BMSCs, stimulated upregulation of the HUVECs of vascular-related receptors, and promoted their tube formation in vitro. CONCLUSION: In conclusion, our research shows that GO, as a biomaterial, can induce the formation of a beneficial osteo-immunomodulatory environment and is a promising biomaterial for bone tissue engineering.

A molecular copper catalyst for electrochemical water reduction with a large hydrogen-generation rate constant in aqueous solution.

The copper complex [(bztpen)Cu](BF4)2 (bztpen=N-benzyl-N,N',N'-tris(pyridin-2-ylmethyl)ethylenediamine) displays high catalytic activity for electrochemical proton reduction in acidic aqueous solutions, with a calculated hydrogen-generation rate constant (k(obs)) of over 10000 s(-1). A turnover frequency (TOF) of 7000 h(-1) cm(-2) and a Faradaic efficiency of 96% were obtained from a controlled potential electrolysis (CPE) experiment with [(bztpen)Cu](2+) in pH 2.5 buffer solution at -0.90 V versus the standard hydrogen electrode (SHE) over two hours using a glassy carbon electrode. A mechanism involving two proton-coupled reduction steps was proposed for the dihydrogen generation reaction catalyzed by [(bztpen)Cu](2+).