Article
Multidisciplinary Sciences
Vilma Vaananen, Mona M. Christensen, Heikki Suhonen, Jukka Jernvall
Summary: The resolution and noninvasiveness of soft-tissue X-ray microtomography (μCT) have made it a widely used three-dimensional imaging method for the study of morphology and development. However, the lack of molecular probes for visualizing gene activity with μCT has remained a challenge. In this study, we successfully apply a method called gene expression CT (GECT) to detect gene expression in developing tissues by combining horseradish peroxidase-assisted reduction of silver and catalytic gold enhancement of the silver deposit. GECT is compatible with various levels of gene expression and sizes of expression regions, and it can be integrated into existing laboratory routines to achieve spatially accurate 3D detection of gene expression.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
(2023)
Article
Biochemistry & Molecular Biology
M. Hernandez, S. Ghislin, R. Lalonde, C. Strazielle
Summary: Early administration of glucocorticoids to infants can impact the development of brain structures, leading to long-term deficits in neuromotor function and cognition. This study investigated the effects of daily corticosterone injections on the development of the cerebellum and hippocampus in mouse pups. The results showed that corticosterone treatment altered the morphology of the hippocampus and down-regulated gene expression related to synaptic development and function. Morphological and metabolic changes were also observed in specific cerebellar lobules involved in motor control.
NEUROCHEMISTRY INTERNATIONAL
(2023)
Article
Genetics & Heredity
Tianpeng Gu, Dapeng Hao, Junsung Woo, Teng-Wei Huang, Lei Guo, Xueqiu Lin, Anna G. Guzman, Ayala Tovy, Carina Rosas, Mira Jeong, Yubin Zhou, Benjamin Deneen, Yun Huang, Wei Li, Margaret A. Goodell
Summary: This study reveals the essential role of the long isoform (DNMT3A1) of DNA methyltransferase 3a (DNMT3A) in mouse postnatal development. DNMT3A1 specifically regulates bivalent neurodevelopmental genes in the brain. The N terminus of DNMT3A1 is shown to be necessary for normal development and DNA methylation at DNMT3A1-enriched regions, possibly through binding to mono-ubiquitinated histone H2AK119. These findings provide insights into the isoform-specific functions and regulatory mechanisms of DNMT3A in development.
Article
Endocrinology & Metabolism
Shiguan Wang, Shanze Chen, Jianfeng Sun, Pan Han, Bowen Xu, Xinying Li, Youquan Zhong, Zaichao Xu, Peng Zhang, Ping Mi, Cuijuan Zhang, Lixiang Li, Haiyan Zhang, Yuchen Xia, Shiyang Li, Mathias Heikenwalder, Detian Yuan
Summary: Wang et al. found that the RNA methyltransferase Mettl3 contributes to hepatic sphingolipid homeostasis by promoting RNA decay of the sphingomyelinase Smpd3 during postnatal liver development, with Mettl3 deficiency leading to ceramide accumulation and liver developmental defects.
Article
Biochemical Research Methods
Jocelyn Y. Kishi, Ninning Liu, Emma R. West, Kuanwei Sheng, Jack J. Jordanides, Matthew Serrata, Constance L. Cepko, Sinem K. Saka, Peng Yin
Summary: Light-Seq is an approach that utilizes light-directed DNA barcoding for multiplexed spatial indexing in fixed cells and tissues. It enables in situ selection of multiple cell populations for sequencing, allowing analysis of rare cell types without dissociation. This method combines spatial and omics information, providing a workflow for in situ imaging, protein staining, and next generation sequencing of the same cells.
Article
Multidisciplinary Sciences
Na Rae Park, Snehal S. Shetye, Igor Bogush, Douglas R. Keene, Sara Tufa, David M. Hudson, Marilyn Archer, Ling Qin, Louis J. Soslowsky, Nathaniel A. Dyment, Kyu Sang Joeng
Summary: The study found that Rcn3 plays a critical regulatory role in tendon development, with its deficiency leading to abnormalities in collagen fibrillogenesis and tenocyte maturation, ultimately affecting the mechanical properties of tendons.
SCIENTIFIC REPORTS
(2021)
Article
Multidisciplinary Sciences
Manman Gao, Xizhe Liu, Peng Guo, Jianmin Wang, Junhong Li, Wentao Wang, Martin J. Stoddart, Sibylle Grad, Zhen Li, Huachuan Wu, Baoliang Li, Zhongyuan He, Guangqian Zhou, Shaoyu Liu, Weimin Zhu, Dafu Chen, Xuenong Zou, Zhiyu Zhou
Summary: A systematic study was conducted using single-cell RNA sequencing technique to characterize 19,952 individual cells from murine hindlimbs at 4 postnatal stages. The study revealed the presence of candidate progenitor sub-clusters in articular cartilage and enthesis, as well as three cellular developmental branches in the growth plate. The transcriptomes and developmental patterns were extensively explored, and the implications for osteoarthritis were discussed. Overall, these findings broaden our understanding of postnatal limb developmental biology and the interconnections between limb development, remodeling, and regeneration.
Article
Biotechnology & Applied Microbiology
Miguel Ramirez, Remi Robert, Joanna Yeung, Joshua Wu, Ayasha Abdalla-Wyse, Daniel Goldowitz
Summary: This study analyzed the activity of transcribed enhancers (TEs) during mouse brain development and found that they peak in expression at different time points during embryonic and early postnatal stages, indicating their importance for specific developmental events. Functional analysis revealed the molecular mechanisms through which TEs regulate biological processes specific to neurons. The study validated enhancer activity and identified TEs that regulate the key gene Nfib involved in cerebellar granule cell differentiation. The results provide a valuable dataset for identifying cerebellar enhancers and understanding the molecular mechanisms of brain development under TE regulation.
Article
Biochemistry & Molecular Biology
Jhih-Rong Lin, Yingjie Zhao, M. Reza Jabalameli, Nha Nguyen, Joydeep Mitra, Ann Swillen, Jacob A. S. Vorstman, Eva W. C. Chow, Marianne van den Bree, Beverly S. Emanuel, Joris R. Vermeesch, Michael J. Owen, Nigel M. Williams, Anne S. Bassett, Donna M. McDonald-McGinn, Raquel E. Gur, Carrie E. Bearden, Bernice E. Morrow, Herbert M. Lachman, Zhengdong D. Zhang
Summary: 22q11.2 deletion is a strong genetic risk factor for schizophrenia. Whole-genome sequencing of schizophrenia cases and controls with this deletion revealed the effects of rare coding variants in modifier genes, contributing to the pathogenesis of schizophrenia. The modifier genes affected synaptic function and developmental disorders and were coexpressed with 22q11.2 genes in specific brain regions.
MOLECULAR PSYCHIATRY
(2023)
Article
Biology
Miguel Ramirez, Yuliya Badayeva, Joanna Yeung, Joshua Wu, Ayasha Abdalla-Wyse, Erin Yang, Brett Trost, Stephen W. Scherer, Daniel Goldowitz
Summary: This study identified active enhancers in the mouse cerebellum during embryonic and postnatal stages, revealing dynamic gene expression regulation during cerebellar development. The enhancers were enriched for neural transcription factor binding sites and showed cell-type specific expression regulation.
Article
Cell Biology
Yan Liang, Kota Kaneko, Bing Xin, Jin Lee, Xin Sun, Kun Zhang, Gen-Sheng Feng
Summary: This study analyzed single-cell transcriptomes of mouse livers and identified hepatocyte heterogeneity and the zonated metabolic functions. It also discovered a group of macrophages with a hybrid phenotype that may play a role in sinusoidal construction and Treg-cell function. The comprehensive atlas provided by this study is important for understanding liver development, metabolism, and disease.
DEVELOPMENTAL CELL
(2022)
Article
Neurosciences
Aaron E. Schirmer, Vivek Kumar, Andrew Schook, Eun Joo Song, Michael S. Marshall, Joseph S. Takahashi
Summary: This study investigates the role of Cry1 and Cry2 transcriptional oscillations in the persistence of circadian activity rhythms using a tetracycline trans-activator system. The findings indicate that rhythmic Cry1 expression is crucial for regulating the circadian period, especially within the first 45 days after birth. Additionally, the study demonstrates that overexpression of Cry1 can restore normal behavioral periodicity in animals with disrupted circadian rhythms. These findings provide new insights into the functions of Cryptochrome proteins in circadian rhythmicity and enhance our understanding of the mammalian circadian clock.
FRONTIERS IN NEUROSCIENCE
(2023)
Article
Multidisciplinary Sciences
Hongzhen Li, Vijender Chaitankar, Lena Cui, Weiping Chen, Kyung Chin, Jianqiong Zhu, Wenli Liu, Griffin P. Rodgers
Summary: In this study, the distribution of Olfm4/eGFP-expressing cells in the mouse prostate and urethral tube was investigated. Olfm4+ cells were found to play important roles in the growth and development of the epithelium.
SCIENTIFIC REPORTS
(2023)
Review
Neurosciences
Pia Boxy, Anders Nykjaer, Lilian Kisiswa
Summary: The cerebellum, a multifunctional brain region, controls various motor and non-motor behaviors. Neurotrophins and growth factors are essential for its development and maintenance. They regulate cellular organization and promote the formation and maintenance of cerebellar circuits.
FRONTIERS IN MOLECULAR NEUROSCIENCE
(2023)
Article
Neurosciences
Yuxin Zhao, Meng Wang, Ke Hu, Qi Wang, Jing Lou, Lingzhong Fan, Bing Liu
Summary: The study reveals the developmental patterns and underlying molecular mechanisms of the functional hierarchy in the human cerebral cortex, shedding light on the potential pathobiology of neurodevelopmental disorders.
Article
Neurosciences
Hisako Sugimoto, Takuro Horii, Jun-Na Hirota, Yoshitake Sano, Yo Shinoda, Ayumu Konno, Hirokazu Hirai, Yasuki Ishizaki, Hajime Hirase, Izuho Hatada, Teiichi Furuichi, Tetsushi Sadakata
Summary: The HapMap Project aims to discover relationships between human genetic variations and health, with the PHYHIPL gene found to impact cerebellum-related diseases. Further research is needed to understand the function of the PHYHIPL gene and its implications in human health.
Review
Chemistry, Medicinal
Yo Shinoda, Daitetsu Kato, Ryosuke Ando, Hikaru Endo, Tsutomu Takahashi, Yayoi Tsuneoka, Yasuyuki Fujiwara
Summary: The study reviewed and analyzed the effectiveness of 5-ALA PDT in vitro experiments for different cancer cell types, finding that the sensitivity to 5-ALA PDT varies across cancer classifications, with stomach cancer showing significantly higher sensitivity compared to other cancers. The analysis suggests the need for a standardized in vitro experimental protocol for 5-ALA PDT in future research.
Article
Neurosciences
Shuhei Fujima, Ryosuke Yamaga, Haruka Minami, Shota Mizuno, Yo Shinoda, Tetsushi Sadakata, Manabu Abe, Kenji Sakimura, Yoshitake Sano, Teiichi Furuichi
Summary: CAPS2 regulates the release of the social modulatory peptide oxytocin (OXT) through dense-core vesicle (DCV) exocytosis, impacting social behavior in mice. Deficiency in CAPS2 leads to reduced plasma OXT levels but increased levels in the hypothalamus and pituitary, indicating insufficient release. The impaired social interaction and recognition behavior in Caps2 KO mice can be ameliorated by intranasal administration of exogenous OXT.
JOURNAL OF NEUROSCIENCE
(2021)
Article
Multidisciplinary Sciences
Chiaki Ishii, Natsumi Shibano, Mio Yamazaki, Tomoki Arima, Yuna Kato, Yuki Ishii, Yo Shinoda, Yugo Fukazawa, Tetsushi Sadakata, Yoshitake Sano, Teiichi Furuichi
Summary: CAPS1 is a key molecule involved in vesicular exocytosis, but its role in synaptic plasticity and learning behavior remains unclear. Studies showed impaired synaptic plasticity and learning behavior in Caps1 cKO mice, with reduced docked vesicles in the hippocampal CA3 region and impaired long-term potentiation in CA1 and CA3 regions. These findings suggest that CAPS1 plays a crucial role in hippocampal synaptic release and plasticity, which is essential for hippocampus-associated learning.
SCIENTIFIC REPORTS
(2021)
Article
Behavioral Sciences
Makoto Wada, Kouji Takano, Masakazu Ide, Yoshitake Sano, Yo Shinoda, Teiichi Furuichi, Kenji Kansaku
Summary: This study aimed to elucidate the neural basis of the rubber tail illusion (RTI) response and its impairment in Caps2-KO mice by investigating c-Fos expression in both wild-type (WT) and Caps2-KO mice during the task. The results suggest that decreased c-Fos expression in the posterior parietal cortex may be related to impaired multisensory integrations in Caps2-KO mice, highlighting the importance of this brain region in body ownership illusions.
FRONTIERS IN BEHAVIORAL NEUROSCIENCE
(2021)
Article
Neurosciences
Teiichi Furuichi, Yuko Muto, Tetsushi Sadakata, Yumi Sato, Kanehiro Hayashi, Yoko Shiraishi-Yamaguchi, Yo Shinoda
Summary: This study elucidated the physiological roles of the Homer protein family in mouse cerebellar granule cells, revealing that the Homer2a N-terminal domain acts as a dominant negative protein to attenuate NMDAR-mediated excitotoxicity. Additionally, a novel short form N-terminal domain-containing Homer2, named Homer2e, was identified and found to be induced by apoptotic stimulation like ischemic brain injury. These findings suggest that long and short forms of Homer2 are involved in apoptosis of cerebellar granule cells.
Article
Neurosciences
Juntan Li, Yo Shinoda, Shuhei Ogawa, Shunsuke Ikegaya, Shuo Li, Yukihiro Matsuyama, Kohji Sato, Satoru Yamagishi
Summary: FLRT2 protein and leucine-rich transmembrane (FLRT) proteins play crucial roles in various developmental processes and pathological conditions. The expression pattern of FLRT2 in CNS development was analyzed using Flrt2-LacZ knock-in mice, revealing dynamic changes in expression in different brain regions during development and after spinal cord injury.
FRONTIERS IN MOLECULAR NEUROSCIENCE
(2021)
Article
Biology
Yuki Sakamoto, Anna Ishimoto, Yuuki Sakai, Moeko Sato, Ryuichi Nishihama, Konami Abe, Yoshitake Sano, Teiichi Furuichi, Hiroyuki Tsuji, Takayuki Kohchi, Sachihiro Matsunaga
Summary: Researchers developed an improved tissue clearing method, iTOMEI, for fluorescence microscopy of both plant and animal tissues. This method efficiently removes chlorophyll and autofluorescence signals while preserving the desired fluorescence protein signals.
COMMUNICATIONS BIOLOGY
(2022)
Article
Biochemistry & Molecular Biology
Yotaroh Sato, Miho Tsuyusaki, Hiromi Takahashi-Iwanaga, Rena Fujisawa, Atsushi Masamune, Shin Hamada, Ryotaro Matsumoto, Yu Tanaka, Yoichi Kakuta, Yumi Yamaguchi-Kabata, Tamio Furuse, Shigeharu Wakana, Takuya Shimura, Rika Kobayashi, Yo Shinoda, Ryo Goitsuka, So Maezawa, Tetsushi Sadakata, Yoshitake Sano, Teiichi Furuichi
Summary: CAPS2 plays a crucial role in the regulation of the pancreatic exocrine pathway and its deficiency is associated with the risk of pancreatic acinar cell pathology.
FRONTIERS IN MOLECULAR BIOSCIENCES
(2022)
Article
Pharmacology & Pharmacy
Takumi Katsuzawa, Kohei Kujirai, Shinji Kamisuki, Yo Shinoda
Summary: Malignant meningioma has a poor prognosis and lacks effective therapies. Avenaciolide, a water-insoluble organic compound derived from Aspergillus avenaceus, was found to exhibit effective anticancer activity in a human malignant meningioma cell line. This activity was mediated by the induction of reactive oxygen species-induced apoptosis, potentially due to mitochondrial dysfunction. These findings suggest that avenaciolide holds potential as a therapeutic drug for malignant meningioma.
BIOLOGICAL & PHARMACEUTICAL BULLETIN
(2022)
Article
Computer Science, Artificial Intelligence
Hamdan Abdellatef, Lina J. Karam
Summary: This paper proposes performing the learning and inference processes in the compressed domain to reduce computational complexity and improve speed of neural networks. Experimental results show that modified ResNet-50 in the compressed domain is 70% faster than traditional spatial-based ResNet-50 while maintaining similar accuracy. Additionally, a preprocessing step with partial encoding is suggested to improve resilience to distortions caused by low-quality encoded images. Training a network with highly compressed data can achieve good classification accuracy with significantly reduced storage requirements.
Article
Computer Science, Artificial Intelligence
Victor R. Barradas, Yasuharu Koike, Nicolas Schweighofer
Summary: Inverse models are essential for human motor learning as they map desired actions to motor commands. The shape of the error surface and the distribution of targets in a task play a crucial role in determining the speed of learning.
Article
Computer Science, Artificial Intelligence
Ting Zhou, Hanshu Yan, Jingfeng Zhang, Lei Liu, Bo Han
Summary: We propose a defense strategy that reduces the success rate of data poisoning attacks in downstream tasks by pre-training a robust foundation model.
Article
Computer Science, Artificial Intelligence
Hao Sun, Li Shen, Qihuang Zhong, Liang Ding, Shixiang Chen, Jingwei Sun, Jing Li, Guangzhong Sun, Dacheng Tao
Summary: In this paper, the convergence rate of AdaSAM in the stochastic non-convex setting is analyzed. Theoretical proof shows that AdaSAM has a linear speedup property and decouples the stochastic gradient steps with the adaptive learning rate and perturbed gradient. Experimental results demonstrate that AdaSAM outperforms other optimizers in terms of performance.
Article
Computer Science, Artificial Intelligence
Juntong Yun, Du Jiang, Li Huang, Bo Tao, Shangchun Liao, Ying Liu, Xin Liu, Gongfa Li, Disi Chen, Baojia Chen
Summary: In this study, a dual manipulator grasping detection model based on the Markov decision process is proposed. By parameterizing the grasping detection model of dual manipulators using a cross entropy convolutional neural network and a full convolutional neural network, stable grasping of complex multiple objects is achieved. Robot grasping experiments were conducted to verify the feasibility and superiority of this method.
Article
Computer Science, Artificial Intelligence
Miaohui Zhang, Kaifang Li, Jianxin Ma, Xile Wang
Summary: This paper proposes an unsupervised person re-identification (Re-ID) method that uses two asymmetric networks to generate pseudo-labels for each other by clustering and updates and optimizes the pseudo-labels through alternate training. It also designs similarity compensation and similarity suppression based on the camera ID of pedestrian images to optimize the similarity measure. Extensive experiments show that the proposed method achieves superior performance compared to state-of-the-art unsupervised person re-identification methods.
Article
Computer Science, Artificial Intelligence
Florian Bacho, Dominique Chu
Summary: This paper proposes a new approach called the Forward Direct Feedback Alignment algorithm for supervised learning in deep neural networks. By combining activity-perturbed forward gradients, direct feedback alignment, and momentum, this method achieves better performance and convergence speed compared to other local alternatives to backpropagation.
Article
Computer Science, Artificial Intelligence
Xiaojian Ding, Yi Li, Shilin Chen
Summary: This research paper addresses the limitations of recursive feature elimination (RFE) and its variants in high-dimensional feature selection tasks. The proposed algorithms, which introduce a novel feature ranking criterion and an optimal feature subset evaluation algorithm, outperform current state-of-the-art methods.
Article
Computer Science, Artificial Intelligence
Naoko Koide-Majima, Shinji Nishimoto, Kei Majima
Summary: Visual images observed by humans can be reconstructed from brain activity, and the visualization of arbitrary natural images from mental imagery has been achieved through an improved method. This study provides a unique tool for directly investigating the subjective contents of the brain.
Article
Computer Science, Artificial Intelligence
Huanjie Tao, Qianyue Duan
Summary: In this paper, a hierarchical attention network with progressive feature fusion is proposed for facial expression recognition (FER), addressing the challenges posed by pose variation, occlusions, and illumination variation. The model achieves enhanced performance by aggregating diverse features and progressively enhancing discriminative features.
Article
Computer Science, Artificial Intelligence
Zhenyi Wang, Pengfei Yang, Linwei Hu, Bowen Zhang, Chengmin Lin, Wenkai Lv, Quan Wang
Summary: In the face of the complex landscape of deep learning, we propose a novel subgraph-level performance prediction method called SLAPP, which combines graph and operator features through an innovative graph neural network called EAGAT, providing accurate performance predictions. In addition, we introduce a mixed loss design with dynamic weight adjustment to improve predictive accuracy.
Article
Computer Science, Artificial Intelligence
Yiyang Yin, Shuangling Luo, Jun Zhou, Liang Kang, Calvin Yu-Chian Chen
Summary: Medical image segmentation is crucial for modern healthcare systems, especially in reducing surgical risks and planning treatments. Transanal total mesorectal excision (TaTME) has become an important method for treating colon and rectum cancers. Real-time instance segmentation during TaTME surgeries can assist surgeons in minimizing risks. However, the dynamic variations in TaTME images pose challenges for accurate instance segmentation.
Article
Computer Science, Artificial Intelligence
Teng Cheng, Lei Sun, Junning Zhang, Jinling Wang, Zhanyang Wei
Summary: This study proposes a scheme that combines the start-stop point signal features for wideband multi-signal detection, called Fast Spectrum-Size Self-Training network (FSSNet). By utilizing start-stop points to build the signal model, this method successfully solves the difficulty of existing deep learning methods in detecting discontinuous signals and achieves satisfactory detection speed.
Article
Computer Science, Artificial Intelligence
Wenming Wu, Xiaoke Ma, Quan Wang, Maoguo Gong, Quanxue Gao
Summary: The layer-specific modules in multi-layer networks are critical for understanding the structure and function of the system. However, existing methods fail to accurately characterize and balance the connectivity and specificity of these modules. To address this issue, a joint learning graph clustering algorithm (DRDF) is proposed, which learns the deep representation and discriminative features of the multi-layer network, and balances the connectivity and specificity of the layer-specific modules through joint learning.
Article
Computer Science, Artificial Intelligence
Guanghui Yue, Guibin Zhuo, Weiqing Yan, Tianwei Zhou, Chang Tang, Peng Yang, Tianfu Wang
Summary: This paper proposes a novel boundary uncertainty aware network (BUNet) for precise and robust colorectal polyp segmentation. BUNet utilizes a pyramid vision transformer encoder to learn multi-scale features and incorporates a boundary exploration module (BEM) and a boundary uncertainty aware module (BUM) to handle boundary areas. Experimental results demonstrate that BUNet outperforms other methods in terms of performance and generalization ability.
