Miracle-dz/UniFAR-FTUs huggingface dataset:
Formation of the Mouse Internal Capsule and Cerebral Peduncle: A Pioneering Role for Striatonigral Axons as Revealed in Isl1 Conditional Mutants

The projection neurons of the striatum, the principal nucleus of the basal ganglia, belong to one of the following two major pathways: the striatopallidal (indirect) pathway or the striatonigral (direct) pathway. Striatonigral axons project long distances and encounter ascending tracts (thalamocortical) while coursing alongside descending tracts (corticofugal) as they extend through the internal capsule and cerebral peduncle. These observations suggest that striatal circuitry may help to guide their trajectories. To investigate the developmental contributions of striatonigral axons to internal capsule formation, we have made use of Sox8-EGFP (striatal direct pathway) and Fezf2-TdTomato (corticofugal pathway) BAC transgenic reporter mice in combination with immunohistochemical markers to trace these axonal pathways throughout development. We show that striatonigral axons pioneer the internal capsule and cerebral peduncle and are temporally and spatially well positioned to provide guidance for corticofugal and thalamocortical axons. Using Isl1 conditional knock-out (cKO) mice, which exhibit disrupted striatonigral axon outgrowth, we observe both corticofugal and thalamocortical axon defects with either ventral forebrain- or telencephalon-specific Isl1 inactivation, despite Isl1 not being expressed in either cortical or thalamic projection neurons. Striatonigral axon defects can thus disrupt internal capsule formation. Our genome-wide transcriptomic analysis in Isl1 cKOs reveals changes in gene expression relevant to cell adhesion, growth cone dynamics, and extracellular matrix composition, suggesting potential mechanisms by which the striatonigral pathway exerts this guidance role. Together, our data support a novel pioneering role for the striatal direct pathway in the correct assembly of the ascending and descending axon tracts within the internal capsule and cerebral peduncle. SIGNIFICANCE STATEMENT The basal ganglia are a group of subcortical nuclei with established roles in the coordination of voluntary motor programs, aspects of cognition, and the selection of appropriate social behaviors. Hence, disruptions in basal ganglia connectivity have been implicated in the motor, cognitive, and social dysfunction characterizing common neurodevelopmental disorders such as attention-deficit/hyperactivity disorder, autism spectrum disorder, obsessive–compulsive disorder, and tic disorder. Here, we identified a novel role for the striatonigral (direct) pathway in pioneering the internal capsule and cerebral peduncle, and in guiding axons extending to and from the cortex. Our findings suggest that the abnormal development of basal ganglia circuits can drive secondary internal capsule defects and thereby may contribute to the pathology of these disorders.
Hydrogen peroxide, sodium dichloro-s-triazinetriones and quaternary alcohols significantly inactivate the dry-surface biofilms of Staphylococcus aureus and Pseudomonas aeruginosa more than quaternary ammoniums

Globally, healthcare-associated infections (HAI) are the most frequent adverse outcome in healthcare delivery. Although bacterial biofilms contribute significantly to the incidence of HAI, few studies have investigated the efficacy of common disinfectants against dry-surface biofilms (DSB). The objective of this study was to evaluate the bactericidal efficacy of seven Environmental Protection Agency (EPA)-registered liquid disinfectants against DSB of Staphylococcus aureus and Pseudomonas aeruginosa . We hypothesized that overall, there will be significant differences among the bactericidal efficacies of tested disinfectants by product type and active ingredient class. We also hypothesized that depending on the species, higher bactericidal efficacies against DSB will be exhibited after 24 h of dehydration compared to 72 h. Wet-surface biofilms of S. aureus and P. aeruginosa were grown following EPA-MLB-SOP-MB-19 and dehydrated for 24 and 72 h to establish DSB. Seven EPA-registered disinfectants were tested against dehydrated DSB following EPA-MLB-SOP-MB-20. Overall, quaternary ammonium plus alcohol, sodium dichloro-s-triazinetrione and hydrogen peroxide products were more efficacious against DSB than quaternary ammoniums for both tested species. While there was no significant difference in the log10 reductions between 24 and 72 h S . aureus biofilms, significantly higher log10 reductions were observed when products were challenged with 24 h P . aeruginosa DSB compared to 72 h P . aeruginosa DSB. Species type, active ingredient class and dry time significantly impact disinfectant efficacy against DSB of S. aureus or P. aeruginosa .
Artificial Intelligence–Powered Spatial Analysis of Tumor-Infiltrating Lymphocytes as Complementary Biomarker for Immune Checkpoint Inhibition in Non–Small-Cell Lung Cancer

PURPOSE Biomarkers on the basis of tumor-infiltrating lymphocytes (TIL) are potentially valuable in predicting the effectiveness of immune checkpoint inhibitors (ICI). However, clinical application remains challenging because of methodologic limitations and laborious process involved in spatial analysis of TIL distribution in whole-slide images (WSI). METHODS We have developed an artificial intelligence (AI)–powered WSI analyzer of TIL in the tumor microenvironment that can define three immune phenotypes (IPs): inflamed, immune-excluded, and immune-desert. These IPs were correlated with tumor response to ICI and survival in two independent cohorts of patients with advanced non–small-cell lung cancer (NSCLC). RESULTS Inflamed IP correlated with enrichment in local immune cytolytic activity, higher response rate, and prolonged progression-free survival compared with patients with immune-excluded or immune-desert phenotypes. At the WSI level, there was significant positive correlation between tumor proportion score (TPS) as determined by the AI model and control TPS analyzed by pathologists (P < .001). Overall, 44.0% of tumors were inflamed, 37.1% were immune-excluded, and 18.9% were immune-desert. Incidence of inflamed IP in patients with programmed death ligand-1 TPS at < 1%, 1%-49%, and ≥ 50% was 31.7%, 42.5%, and 56.8%, respectively. Median progression-free survival and overall survival were, respectively, 4.1 months and 24.8 months with inflamed IP, 2.2 months and 14.0 months with immune-excluded IP, and 2.4 months and 10.6 months with immune-desert IP. CONCLUSION The AI-powered spatial analysis of TIL correlated with tumor response and progression-free survival of ICI in advanced NSCLC. This is potentially a supplementary biomarker to TPS as determined by a pathologist.
Study on Improved Matrix Algorithm for Fault Location in Power Distribution Network

In order to promote the calculation efficiency and expand its adaptability to the complex power distribution system,an improved and optimized matrix algorithm,which is a fault section locating method depended on local information of power distribution system,is proposed for distribution network according to the model in combination with the fault information.Firstly,the algorithm needs to form the network description matrix,then the local fault information of power distribution to gain the judgment matrix and the situation of faults can be obtained by the analysis of the judgment matrix,this method suits to radial or mesh architecture in radial operation distribution systems.The algorithm is designed based on fault overcorrect signal flowing through monitoring points,and parameters of the distribution are all-stored according to the power line and the net describing matrix is dynamic to be formed.By the algorithm not only the single fault occurred in distribution network can be located,but also the end faults and the multiple faults can be quickly and accurately diagnosed.With the help of efficient database,the simulation and calculation of various faults occurred in a distribution network with three independent sources and the faults occurred in a distribution network consisting of single source and multi-outgoing lines are carried out,the result indicates the algorithm is effective.There is no need for matrix multiplication and reversal calculations in the improved algorithm,therefore the method could find its application in on-line calculation because of its high-speed character.Furthermore the method may also be extended to systems with multi-power sources and provides adaptability to different open-loop power distribution networks.
Wedge method for landfill stability analysis considering temperature increase

The increase in landfill temperature often results in shear strength reduction of both the solid waste and the liner, which leads to slope instability. However, very few landfill slope analysis methods can simultaneously consider the effect of temperature on the shear strength of the waste solid and the liner. In this study, based on the strength parameters of the liner and waste with temperature, a wedge method for translational failure analysis of landfills considering temperature increase was established. The results showed that rising temperatures caused by biochemical degradation at the bottom and middle of the landfill reduced the anti-slide force of back slope more than that of bottom slope. With the leachate level increasing, the effect of temperature rise on landfill stability became obvious. The feasibility of the proposed wedge method was verified by the engineering case study of Xiaping Landfill, Shenzhen, China. This study probably provides important guidance for the design, operation and management of municipal solid waste landfills.
Mitomycin-Treated Endothelial and Smooth Muscle Cells Suitable for Safe Tissue Engineering Approaches

In our previous study, we showed that discarded cardiac tissue from the right atrial appendage and right ventricular myocardium is an available source of functional endothelial and smooth muscle cells for regenerative medicine and tissue engineering. In the study, we aimed to find out what benefits are given by vascular cells from cardiac explants used for seeding on vascular patches engrafted to repair vascular defects in vivo. Additionally, to make the application of these cells safer in regenerative medicine we tested an in vitro approach that arrested mitotic division to avoid the potential tumorigenic effect of dividing cells. A tissue-engineered construction in the form of a patch based on a polycaprolactone-gelatin scaffold and seeded with endothelial and smooth muscle cells was implanted into the abdominal aorta of immunodeficient SCID mice. Aortic patency was assessed using ultrasound, MRI, immunohistochemical and histological staining. Endothelial and smooth muscle cells were treated with mitomycin C at a therapeutic concentration of 10 μg/ml for 2 h with subsequent analysis of cell proliferation and function. The absence of the tumorigenic effect of mitomycin C-treated cells, as well as their angiogenic potential, was examined by injecting them into immunodeficient mice. Cell-containing patches engrafted in the abdominal aorta of immunodeficient mice form the vessel wall loaded with the appropriate cells and extracellular matrix, and do not interfere with normal patency. Endothelial and smooth muscle cells treated with mitomycin C show no tumorigenic effect in the SCID immunodeficient mouse model. During in vitro experiments, we have shown that treatment with mitomycin C does not lead to a decrease in cell viability. Despite the absence of proliferation, mitomycin C-treated vascular cells retain specific cell markers, produce specific extracellular matrix, and demonstrate the ability to stimulate angiogenesis in vivo. We pioneered an approach to arresting cell division with mitomycin C in endothelial and smooth muscle cells from cardiac explant, which prevents the risk of malignancy from dividing cells in vascular surgery. We believe that this approach to the fabrication of tissue-engineered constructs based on mitotically inactivated cells from waste postoperative material may be valuable to bring closer the development of safe cell products for regenerative medicine.
From Mice to Men: Generation of Human Blastocyst-Like Structures In Vitro

Advances in the field of stem cell-based models have in recent years lead to the development of blastocyst-like structures termed blastoids. Blastoids can be used to study key events in mammalian pre-implantation development, as they mimic the blastocyst morphologically and transcriptionally, can progress to the post-implantation stage and can be generated in large numbers. Blastoids were originally developed using mouse pluripotent stem cells, and since several groups have successfully generated blastocyst models of the human system. Here we provide a comparison of the mouse and human protocols with the aim of deriving the core requirements for blastoid formation, discuss the models’ current ability to mimic blastocysts and give an outlook on potential future applications.
Rapid Identification of Soybean Varieties by Terahertz Frequency-Domain Spectroscopy and Grey Wolf Optimizer-Support Vector Machine

Different soybean varieties vary greatly in their nutritional value and composition. Screening for superior varieties is also essential for the development of the soybean seed industry. The objective of the paper was to analyze the feasibility of terahertz (THz) frequency-domain spectroscopy and chemometrics for soybean variety identification. Meanwhile, a grey wolf optimizer-support vector machine (GWO-SVM) soybean variety identification model was proposed. Firstly, the THz frequency-domain spectra of experimental samples (6 varieties, 270 in total) were collected. Principal component analysis (PCA) was used to analyze the THz spectra. After that, 203 samples from the calibration set were used to establish a soybean variety identification model. Finally, 67 samples from the test set were used for prediction validation. The experimental results demonstrated that THz frequency-domain spectroscopy combined with GWO-SVM could quickly and accurately identify soybean varieties. Compared with discriminant partial least squares (DPLS) and particles swarm optimization support vector machine, GWO-SVM combined with the second derivative could establish a better soybean variety identification model. The overall correct identification rate of its prediction set was 97.01%.
Exploring Neuroscience Literature and Understanding Relations Between Brain-Related Topics - Using Augmented Reality

Neuroscience researchers are interested in understanding relation between anatomical regions of the brain and disorders that affect them, for example. Using the topics themselves, rather than individual articles, to examine relation in a large body of literature, can provide a higher-level approach. I investigate the use of 3D representations in Augmented Reality to aid neuroscientists to explore literature and understand relations between brain-related topics, given the three-dimensional nature of the brain. Distant reading refers to comprehending the results of studies of a large number of articles, as opposed to the more common ”close reading” of individual publications. For distant reading of neuroscience literature, I identify visualization and interaction design requirements. My assumption is that by providing overviews of the correlations among topics through the use of literature, these will allow neuroscientists to better understand the gaps in the literature and more quickly identify the most suitable experiments to carry out. The DatAR team at Utrecht University has created a prototype 3D AR implementation using which I have carried out two studies of a literature exploration interface. These studies showed that visualizing topics and their relation in an immersive AR environment is clear, understandable and helpful for exploring neuroscience literature. In the following, I will carry out a study that participants can make parallel query and compare the results. I will further investigate in finding indirect relations between brain regions and brain diseases. The last study will support neuroscience students to understand course material. Interface improvements are considering where necessary.
Privacy at a Glance: A Process to Learn Modular Privacy Icons During Web Browsing

Privacy policies (PPs) are currently the only way to inform users about their rights and choices during web browsing and searching. However, users avoid engaging with them, because of their length and abstract legal language, which makes them hard to read and understand. We propose to support the understanding of PPs by using modular icons. Icons have already proven to be helpful in visualizing concepts with high information density. However, the value of using icons to supplement PPs lacks a scientific foundation. Thus, we conducted two studies to evaluate existing icon sets for their understandability and to teach participants their meaning in situ. We show that modular privacy icons can be taught using our process, which has the potential to aid quicker and easier comprehension of PPs. We contribute a set of tested modular privacy icons and a verified process on how to teach them to users incidentally during web browsing.
Want or Need: Why Would Users Expect to Conduct Cross-Session Searches?

Users often search for information online across multiple sessions for a specific task. Sometimes cross-session searches may be unanticipated, however, in many cases users know beforehand that their search will spread across multiple sessions. Little is known about why people expect to search across multiple sessions. Based on a qualitative analysis of the interview data collected from a diary study, we identified two types of reasons that motivate people to conduct cross-session searches: (1) task-oriented motivations, (2) cognition-oriented motivations. We also identified a group of reasons that cause challenges for cross-session search. Our findings have implications for the future design of search systems to support cross-session search from different aspects.
GLPose: Global-Local Representation Learning for Human Pose Estimation

Multi-frame human pose estimation is at the core of many computer vision tasks. Although state-of-the-art approaches have demonstrated remarkable results for human pose estimation on static images, their performances inevitably come short when being applied to videos. A central issue lies in the visual degeneration of video frames induced by rapid motion and pose occlusion in dynamic environments. This problem, by nature, is insurmountable for a single frame. Therefore, incorporating complementary visual cues from other video frames becomes an intuitive paradigm. Current state-of-the-art methods usually leverage information from adjacent frames, which unfortunately place excessive focus on only the temporally nearby frames. In this paper, we argue that combining global semantically similar information and local temporal visual context will deliver more comprehensive and more robust representations for human pose estimation. Towards this end, we present an effective framework, namely global-local enhanced pose estimation (GLPose) network. Our framework consists of a feature processing module that conditionally incorporates global semantic information and local visual context to generate a robust human representation and a feature enhancement module that excavates complementary information from this aggregated representation to enhance keyframe features for precise estimation. We empirically find that the proposed GLpose outperforms existing methods by a large margin and achieves new state-of-the-art results on large benchmark datasets.
Identifying Gaps and Gap-bridging Strategies in Group Travelers’ Collaborative Information Seeking and Technology Use

The research reported in this paper is part of a large study that investigates collaborative information seeking (CIS) and decision making in the context of tourism. The aim of the present paper was to identify gaps and gap-bridging techniques in situated tourism CIS and technology use across the travel stages of trip planning and during the trip. Interview and diary data were collected from 20 free-trip groups of 63 Chinese tourists who traveled from mainland China to Australia during 2018-2019. We identified 8 types of gaps as well as 8 gap-bridging strategies. The results show that tourists demonstrated adaptive CIS behavior over the trip as they solved or compromised the gaps encountered. Suggestions on system design are also discussed to better support tourist information and collaborative practices.
Analyzing information resources that support the creative process

As an important skill in many domains, creativity is understood to be a process that includes stages like finding goals, looking up information, exploring, creating ideas, combining ideas, selecting ideas, and executing plans [50]. However, little prior information retrieval research has considered how people use search tools and information resources to support their creative stages. To gain a better understanding of how and why users interact with information resources and tools during a creative process, we conducted a two-week diary study with 11 participants. We recorded their information seeking behavior through a combination of diary entries, data logging, and reflective interviews. Our analysis identified five common reasons for how people use existing information resources (e.g., search engines, video sites, image sites, Q&A sites, and other social sites) to support their creative process. We also report on how different information resources were preferred for different purposes at different creative stages. For instance, participants often used images to help support ideation, Q&A sites to learn from other creators and to find tips and recommendations, and social media to select ideas and collect feedback on their creative projects. We also identified challenges participants faced when working on their creative projects. Our findings provide insights for the future design of search engines, improvement of search algorithms, and the development of novel tools to support users during different creative stages.
Featured Snippets and their Influence on Users’ Credibility Judgements

Search engines often provide featured snippets, which are boxed and placed above other results with the aim of directly answering user queries. To learn about how users judge the credibility of such results and how they influence search outcomes, a controlled web-based user study (N = 96) was conducted. Using resources made available by scholars in the community, we study featured snippets in a medical context with participants being tasked with determining whether a named treatment is helpful for a specified medical condition both before and after viewing the search results. Experimental conditions varied the presence and credibility of featured snippets. Our findings indicate that participants tend to overestimate the credibility of information in featured snippets. Featured snippets are, moreover, shown to often change users’ opinion about a topic, especially if they are uncertain. Showing correct information inside featured snippets helped participants make more accurate decisions, whereas incorrect or contradicting information led to more harmful outcomes.