Segmental abnormalities of superior longitudinal fasciculus microstructure in patients with schizophrenia, bipolar disorder, and attention-deficit/hyperactivity disorder: An automated fiber quantification tractography study

IntroductionSuperior longitudinal fasciculus (SLF) is a white matter (WM) tract that connects the frontal, parietal and temporal lobes. SLF integrity has been widely assessed in neuroimaging studies of psychiatric disorders, such as schizophrenia (SZ), bipolar disorder (BD), and attention-deficit/hyperactivity disorder (ADHD). However, prior studies have revealed inconsistent findings and comparisons across disorders have not been fully examined.MethodsHere, we obtained data for 113 patients (38 patients with SZ, 40 with BD, 35 with ADHD) and 94 healthy controls from the UCLA Consortium for Neuropsychiatric Phenomic LA5c dataset. We assessed the integrity of 20 major WM tracts with a novel segmentation method by automating fiber tract quantification (AFQ). The AFQ divides each tract into 100 equal parts along the direction of travel, with fractional anisotropy (FA) of each part taken as a characteristic. Differences in FA among the four groups were examined.ResultsCompared to healthy controls, patients with SZ showed significantly lower FA in the second half (51–100 parts) of the SLF. No differences were found between BD and healthy controls, nor between ADHD and healthy controls. Results also demonstrated that patients with SZ showed FA reduction in the second half of the SLF relative to patients with BP. Moreover, greater FA in patients in SLF was positively correlated with the manic-hostility score of the Brief Psychiatry Rating scale.DiscussionThese findings indicated that differences in focal changes in SLF might be a key neurobiological abnormality contributing to characterization of these psychiatric disorders

MonoOcc: Digging into Monocular Semantic Occupancy Prediction

Monocular Semantic Occupancy Prediction aims to infer the complete 3D geometry and semantic information of scenes from only 2D images. It has garnered significant attention, particularly due to its potential to enhance the 3D perception of autonomous vehicles. However, existing methods rely on a complex cascaded framework with relatively limited information to restore 3D scenes, including a dependency on supervision solely on the whole network's output, single-frame input, and the utilization of a small backbone. These challenges, in turn, hinder the optimization of the framework and yield inferior prediction results, particularly concerning smaller and long-tailed objects. To address these issues, we propose MonoOcc. In particular, we (i) improve the monocular occupancy prediction framework by proposing an auxiliary semantic loss as supervision to the shallow layers of the framework and an image-conditioned cross-attention module to refine voxel features with visual clues, and (ii) employ a distillation module that transfers temporal information and richer knowledge from a larger image backbone to the monocular semantic occupancy prediction framework with low cost of hardware. With these advantages, our method yields state-of-the-art performance on the camera-based SemanticKITTI Scene Completion benchmark. Codes and models can be accessed at https://github.com/ucaszyp/MonoOccComment: Accepted by ICRA 202

Current development and future challenges in microplastic detection techniques: a bibliometrics-based analysis and review.

Microplastics have been considered a new type of pollutant in the marine environment and have attracted widespread attention worldwide in recent years. Plastic particles with particle size less than 5 mm are usually defined as microplastics. Because of their similar size to plankton, marine organisms easily ingest microplastics and can threaten higher organisms and even human health through the food chain. Most of the current studies have focused on the investigation of the abundance of microplastics in the environment. However, due to the limitations of analytical methods and instruments, the number of microplastics in the environment can easily lead to overestimation or underestimation. Microplastics in each environment have different detection techniques. To investigate the current status, hot spots, and research trends of microplastics detection techniques, this review analyzed the papers related to microplastics detection using bibliometric software CiteSpace and COOC. A total of 696 articles were analyzed, spanning 2012 to 2021. The contributions and cooperation of different countries and institutions in this field have been analyzed in detail. This topic has formed two main important networks of cooperation. International cooperation has been a common pattern in this topic. The various analytical methods of this topic were discussed through keyword and clustering analysis. Among them, fluorescent, FTIR and micro-Raman spectroscopy are commonly used optical techniques for the detection of microplastics. The identification of microplastics can also be achieved by the combination of other techniques such as mass spectrometry/thermal cracking gas chromatography. However, these techniques still have limitations and cannot be applied to all environmental samples. We provide a detailed analysis of the detection of microplastics in different environmental samples and list the challenges that need to be addressed in the future

Deletion of FgHOG1 Is Suppressive to the mgv1 Mutant by Stimulating Gpmk1 Activation and Avoiding Intracellular Turgor Elevation in Fusarium graminearum

Fusarium head blight caused by Fusarium graminearum is an important disease of wheat and barley. Previous studies have showed that all three MAP kinase genes, MGV1, FgHOG1, and GPMK1, are involved in regulating hyphal growth, sexual reproduction, plant infection, and stress responses in this pathogen. To determine the relationship between the Mgv1 and FgHog1 pathways, in this study, we generated and characterized the mgv1 Fghog1 double mutant. Deletion of FgHOG1 partially rescued the defects of the mgv1 mutant in vegetative growth and cell wall integrity but had no effects on its defects in plant infection and DON production. The mgv1 Fghog1 mutant grew faster and was more tolerant to cell wall stressors than the mgv1 mutant. Swollen compartments and cell burst were observed frequently in the mgv1 mutant but rarely in the mgv1 Fghog1 mutant when treated with fungicide fludioxonil or cell wall stressor Congo red. Conversely, the deletion of MGV1 also alleviated the hyperosmotic sensitivity of the Fghog1 mutant in vegetative growth. TGY assays indicated increased phosphorylation of FgHog1 in the mgv1 mutant, and TEY assays further revealed elevated activation of Gpmk1 in the mgv1 Fghog1 double mutant, particularly under cell wall stress conditions. Overall, our data showed that deletion of FgHOG1 partially suppressed the defects of the mgv1 mutant, possibly by affecting genes related to cell wall integrity and osmoregulation via the over-activation of Gpmk1 MAP kinase and avoiding intracellular turgor elevation

GaussianGrasper: 3D Language Gaussian Splatting for Open-vocabulary Robotic Grasping

Constructing a 3D scene capable of accommodating open-ended language queries, is a pivotal pursuit, particularly within the domain of robotics. Such technology facilitates robots in executing object manipulations based on human language directives. To tackle this challenge, some research efforts have been dedicated to the development of language-embedded implicit fields. However, implicit fields (e.g. NeRF) encounter limitations due to the necessity of processing a large number of input views for reconstruction, coupled with their inherent inefficiencies in inference. Thus, we present the GaussianGrasper, which utilizes 3D Gaussian Splatting to explicitly represent the scene as a collection of Gaussian primitives. Our approach takes a limited set of RGB-D views and employs a tile-based splatting technique to create a feature field. In particular, we propose an Efficient Feature Distillation (EFD) module that employs contrastive learning to efficiently and accurately distill language embeddings derived from foundational models. With the reconstructed geometry of the Gaussian field, our method enables the pre-trained grasping model to generate collision-free grasp pose candidates. Furthermore, we propose a normal-guided grasp module to select the best grasp pose. Through comprehensive real-world experiments, we demonstrate that GaussianGrasper enables robots to accurately query and grasp objects with language instructions, providing a new solution for language-guided manipulation tasks. Data and codes can be available at https://github.com/MrSecant/GaussianGrasper

Constraints on the evolution of crustal flow beneath Northern Tibet

Crustal flow is an important tectonic process active in continent‐continent collisions and which may be significant in the development of convergent plate boundaries. In this study, the results from multidimensional electrical conductivity modeling have been combined with laboratory studies of the rheology of partially molten rocks to characterize the rheological behavior of the middle‐to‐lower crust of both the Songpan‐Ganzi and Kunlun terranes in the northern Tibetan Plateau. Two different methods are adopted to develop constraints on melt fraction, temperature, and crustal flow velocity in the study area. The estimates of these parameters are then used to evaluate whether crustal flow can occur on the northern margin of the Tibetan plateau. In the Songpan‐Ganzi crust, all conditions are satisfied for topography‐driven channel flow to be dominant, with partial melt not being required for flow at temperature above 1000°C. Further north, the Kunlun fault defines the southern boundary of a transition zone between the Tibetan plateau and the Qaidam basin. Constrained by the estimated melt fractions, it is shown that channel injection across the fault requires temperatures close to 900°C. The composition of igneous rocks found at the surface confirm those conditions are met for the southern Kunlun ranges. To the north, the Qaidam basin is characterized by colder crust that may reflect an earlier stage in the channel injection process. In the study area, at least 10% of the eastward directed Tibetan crustal flow could be deflected northward across the Kunlun Fault and injected into the transition zone defining the northern margin of the Tibetan plateau

Northward channel flow in northern Tibet revealed from 3D magnetotelluric modelling

The Kunlun fault defines one of the major northern tectonic boundaries of the Tibetan plateau. Previous geophysical studies have detected a major change in rheology across this boundary, but it is not clear how this is related to models that have invoked crustal flow. The lithospheric resistivity structure of the Kunlun fault has been investigated by both the INDEPTH III and IV magnetotelluric (MT) transects. All the MT data were processed using modern statistically-robust methods, and have been analysed for directionality and dimensionality. In order to improve understanding of the anisotropic distribution of melt previously revealed by our remodelling of the INDEPTH III MT data, a variant approach on 3D inversion of 2D profiles was investigated to explore and improve lateral resolution. In addition to the apparent surficial deformation associated with the sinistral strike-slip Kunlun fault, the 3D modelling of the INDEPTH MT data reveals that complex deformation processes are occurring at mid-crustal depths in northern Tibet. The 3D MT inversion results, supported by synthetic modelling, particularly confirm and highlight the presence of separate north–south intrusions of conductive material crossing the Kunlun fault into the more resistive Kunlun–Qaidam block. These north–south intrusions are interpreted to be associated with the horizontal channel flow of partially molten Songpan–Ganzi crust into two (or more) separated channels moving northwards and crossing the surficial trace of the Kunlun fault at mid-to-lower crustal depths

Use of MicroRNA Let-7 to Control the Replication Specificity of Oncolytic Adenovirus in Hepatocellular Carcinoma Cells

Highly selective therapy for hepatocellular carcinoma (HCC) remains an unmet medical need. In present study, we found that the tumor suppressor microRNA, let-7 was significantly downregulated in a proportion of primary HCC tissues (12 of 33, 36.4%) and HCC cell lines. In line with this finding, we have engineered a chimeric Ad5/11 fiber oncolytic adenovirus, SG7011let7T, by introducing eight copies of let-7 target sites (let7T) into the 3′ untranslated region of E1A, a key gene associated with adenoviral replication. The results showed that the E1A expression (both RNA and protein levels) of the SG7011let7T was tightly regulated according to the endogenous expression level of the let-7. As contrasted with the wild-type adenovirus and the control virus, the replication of SG7011let7T was distinctly inhibited in normal liver cells lines (i.e. L-02 and WRL-68) expressing high level of let-7 (>300 folds), whereas was almost not impaired in HCC cells (i.e. Hep3B and PLC/PRF/5) with low level of let-7. Consequently, the cytotoxicity of SG7011let7T to normal liver cells was successfully decreased while was almost not attenuated in HCC cells in vitro. The antitumor ability of SG7011let7T in vivo was maintained in mice with Hep3B xenograft tumor, whereas was greatly decreased against the SMMC-7721 xenograft tumor expressing a high level of let-7 similar with L-02 when compared to the wild-type adenovirus. These results suggested that SG7011let7T may be a promising anticancer agent or vector to mediate the expression of therapeutic gene, broadly applicable in the treatment for HCC and other cancers where the let-7 gene is downregulated