Preoperative classification of urinary stones based on community detection.

In the treatment of urinary stones, surgical intervention is crucial. Urinary stones composition and type directly affect surgical planning. However, research on preoperative stone composition analysis is limited.

Connectivity Reveals the Relationships between Human Brain Areas Associated with High-Level Linguistic Processing and Macaque Brain Areas.

Cross-species research has advanced human understanding of brain regions, with cross-species comparisons using magnetic resonance imaging technology becoming increasingly common. Currently, cross-species research on human language regions has primarily focused on traditional brain areas such as the Broca region. While some studies have indicated that human language function also involves other language regions, the corresponding relationships between these brain regions in humans and macaques remain unclear.

Connectivity reveals homology between the visual systems of the human and macaque brains.

The visual systems of humans and nonhuman primates share many similarities in both anatomical and functional organization. Understanding the homology and differences between the two systems can provide important insights into the neural basis of visual perception and cognition. This research aims to investigate the homology between human and macaque visual systems based on connectivity, using diffusion tensor imaging and resting-state functional magnetic resonance imaging to construct structural and functional connectivity fingerprints of the visual systems in humans and macaques, and quantitatively analyze the connectivity patterns.

HC-Net: A hybrid convolutional network for non-human primate brain extraction.

Brain extraction (skull stripping) is an essential step in the magnetic resonance imaging (MRI) analysis of brain sciences. However, most of the current brain extraction methods that achieve satisfactory results for human brains are often challenged by non-human primate brains. Due to the small sample characteristics and the nature of thick-slice scanning of macaque MRI data, traditional deep convolutional neural networks (DCNNs) are unable to obtain excellent results.

Corresponding anatomical of the macaque superior parietal lobule areas 5 (PE) subdivision reveal similar connectivity patterns with humans.

Using the animal brain as a cross-species tool for human brain research based on imaging features can provide more potential to reveal comprehensive human brain analysis. Previous studies have shown that human Brodmann area 5 (BA5) and macaque PE are homologous regions. They are both involved in processes depth and direction information during the touch process in the arm movement.

NiCoSenanoparticles derived from nickel-cobalt Prussian blue analogues on N-doped reduced graphene oxide for high-performance asymmetric supercapacitors.

Synthesis of NiHCCo precursors via simple co-precipitation and nickel-cobalt tetraselenide composites grown on nitrogen-doped reduced graphene oxide (NiCoSe/N-rGO) were fabricated using solvothermal method. The introduction of N-rGO used as a template effectively prevented agglomeration of NiCoSenanoparticles and provided more active sites, which greatly increased the electrochemical and electrical conductivity for NiCoSe/N-rGO. NiCoSe/N-rGO-20 presents a remarkably elevated specific capacity of 120 mA h gunder current density of 1 A g.

Functional Integration and Segregation in a Multilayer Network Model of Patients with Schizophrenia.

Research has shown that abnormal brain networks in patients with schizophrenia appear at different frequencies, but the relationship between these different frequencies is unclear. Therefore, it is necessary to use a multilayer network model to evaluate the integration of information from different frequency bands. To explore the mechanism of integration and separation in the multilayer network of schizophrenia, we constructed multilayer frequency brain network models in 50 patients with schizophrenia and 69 healthy subjects, and the entropy of the multiplex degree (EMD) and multilayer clustering coefficient (MCC) were calculated.

A Macaque Brain Extraction Model Based on U-Net Combined with Residual Structure.

Accurately extracting brain tissue is a critical and primary step in brain neuroimaging research. Due to the differences in brain size and structure between humans and nonhuman primates, the performance of the existing tools for brain tissue extraction, working on macaque brain MRI, is constrained. A new transfer learning training strategy was utilized to address the limitations, such as insufficient training data and unsatisfactory model generalization ability, when deep neural networks processing the limited samples of macaque magnetic resonance imaging(MRI).

Dynamic Changes of Brain Networks during Working Memory Tasks in Schizophrenia.

Electroencephalograph (EEG) signals and graph theory measures have been widely used to characterize the brain functional networks of healthy individuals and patients by calculating the correlations between different electrodes over an entire time series. Although EEG signals have a high temporal resolution and can provide relatively stable results, the process of constructing and analyzing brain functional networks is inevitably complicated by high time complexity. Our goal in this research was to distinguish the brain function networks of schizophrenia patients from those of healthy participants during working memory tasks.