CCNI Recombinant Protein
- Known as:
- CCNI Recombinant Protein
- Catalog number:
- XW-RP3037
- Product Quantity:
- 0.05 mg
- Category:
- -
- Supplier:
- Prosci
- Gene target:
- CCNI Recombinant Protein
Related genes to: CCNI Recombinant Protein
- Gene:
- CCNI NIH gene
- Name:
- cyclin I
- Previous symbol:
- -
- Synonyms:
- CCNI1
- Chromosome:
- 4q21.1
- Locus Type:
- gene with protein product
- Date approved:
- 2000-06-29
- Date modifiied:
- 2014-11-19
Related products to: CCNI Recombinant Protein
Related articles to: CCNI Recombinant Protein
- Visual working memory (VWM) maintenance depends on oscillatory network dynamics across multiple frequency bands throughout fronto-parietal and sensory brain areas. However, whether these networks reflect the active maintenance of visual information content or serve top-down control processes has remained unresolved. To address this, we used concurrent magneto- and electroencephalography (M/EEG) to measure brain activity during VWM tasks, in which the memory content was parametrically controlled. Using new edge-level analysis for source-connectivity networks, we disentangled connections and subnetworks underlying the maintenance of specific contents from those supporting feature-general VWM. We show here that long-range high-alpha band (α, 11-13 Hz) phase-synchronization networks carry out a dual role in these VWM functions. α-band subgraphs localized to the visual areas are feature-selective and maintain the contents of VWM. In contrast, the high α-band subgraph in the fronto-parietal areas was shared across memory contents, suggesting that it forms the content-agnostic executive core of VWM. We propose that α-band synchronization across distinct, but yet interconnected, subgraphs support the active maintenance of feature representations and their top-down selection. - Source: PubMed
Publication date: 2025/12/23
Haque HamedWang Sheng HSiebenhühner FelixRobertson Edwin MPalva J MatiasPalva Satu - Motor tasks require the flexible selection and coordination of multiple muscles, which may be achieved through the organization and combination of muscle synergies. Although multiple muscles may receive a shared neural drive, and each muscle may also receive distinct neural inputs, there is ongoing debate about whether synergies accurately reflect shared neural drives. This study aimed to compare the spectral characteristics of the common drive shared among muscles within the same synergy to those shared among muscles belonging to different synergies. - Source: PubMed
Publication date: 2025/11/07
Borzelli DanieleCacciola AlbertoCannistraci Carlo VittorioAlito AngeloMilardi Demetriod'Avella Andrea - - Source: PubMed
Robertson Edwin M - The pathogenesis of diabetic neuropathy involves complex interactions between metabolic and genetic factors. This study aimed to identify novel genetic variants associated with neuropathy risk in type 2 diabetes through reanalysis of whole-exome sequencing data. We identified seven new SNPs with significant associations, including intronic variants in , , , and and a 5'-upstream variant in . These variants are implicated in muscle elasticity, neurotransmission, endothelial regeneration, and apoptosis resistance, suggesting multifaceted genetic contributions to neuropathy development. These findings enhance our understanding of diabetic neuropathy and may support future advances in risk stratification and therapy development. - Source: PubMed
Publication date: 2025/06/28
Hajdú NoémiTordai Dóra ZsuzsannaRácz RamónaLudvig ZsófiaIstenes IldikóBékeffy MagdolnaVági Orsolya ErzsébetKörei Anna ErzsébetTóbiás BálintIllés AnettPikó HenriettKósa János PÁrvai KristófLakatos Péter AndrásKempler PéterPutz Zsuzsanna - Translational network neuroscience aims to integrate advanced neuroimaging and data analysis techniques into clinical practice to better understand and treat neurological disorders. Despite the promise of technologies such as functional MRI and diffusion MRI combined with network analysis tools, the field faces several challenges that hinder its swift clinical translation. We have identified nine key roadblocks that impede this process: (a) theoretical and basic science foundations; (b) network construction, data interpretation, and validation; (c) MRI access, data variability, and protocol standardization; (d) data sharing; (e) computational resources and expertise; (f) interdisciplinary collaboration; (g) industry collaboration and commercialization; (h) operational efficiency, integration, and training; and (i) ethical and legal considerations. To address these challenges, we propose several possible solution strategies. By aligning scientific goals with clinical realities and establishing a sound ethical framework, translational network neuroscience can achieve meaningful advances in personalized medicine and ultimately improve patient care. We advocate for an interdisciplinary commitment to overcoming translational hurdles in network neuroscience and integrating advanced technologies into routine clinical practice. - Source: PubMed
Publication date: 2025/03/20
Fekonja Lucius SForkel Stephanie JAydogan Dogu BaranLioumis PantelisCacciola AlbertoLucas Carolin WeißTournier Jacques-DonaldVergani FrancescoRitter PetraSchenk RobertShams BoshraEngelhardt Melina JuliaPicht Thomas