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   https://doi.org/10.1007/s10439-018-02148-2  

   Harris, Taylor C.; de Rooij, Rijk; Kuhl, Ellen (December 2019, Annals of Biomedical Engineering)
2. Drug Delivery to the Brain across the Blood–Brain Barrier Using Nanomaterials

   https://doi.org/10.1002/smll.201701921  

   Tsou, Yung‐Hao; Zhang, Xue‐Qing; Zhu, He; Syed, Sahla; Xu, Xiaoyang (October 2017, Small)

   Abstract A major obstacle facing brain diseases such as Alzheimer's disease, multiple sclerosis, brain tumors, and strokes is the blood–brain barrier (BBB). The BBB prevents the passage of certain molecules and pathogens from the circulatory system into the brain. Therefore, it is nearly impossible for therapeutic drugs to target the diseased cells without the assistance of carriers. Nanotechnology is an area of growing public interest; nanocarriers, such as polymer‐based, lipid‐based, and inorganic‐based nanoparticles can be engineered in different sizes, shapes, and surface charges, and they can be modified with functional groups to enhance their penetration and targeting capabilities. Hence, understanding the interaction between nanomaterials and the BBB is crucial. In this Review, the components and properties of the BBB are revisited and the types of nanocarriers that are most commonly used for brain drug delivery are discussed. The properties of the nanocarriers and the factors that affect drug delivery across the BBB are elaborated upon in this review. Additionally, the most recent developments of nanoformulations and nonconventional drug delivery strategies are highlighted. Finally, challenges and considerations for the development of brain targeting nanomedicines are discussed. The overall objective is to broaden the understanding of the design and to develop nanomedicines for the treatment of brain diseases. 

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3. An evolving perspective on the dynamic brain: Notes from the Brain Conference on Dynamics of the brain: Temporal aspects of computation

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   Langdon, Angela J.; Chaudhuri, Rishidev (June 2021, European Journal of Neuroscience)

   null (Ed.)
4. Feminization of the Blood–Brain Barrier Changes the Brain Transcriptome of Drosophila melanogaster Males

   Davis, Danyel S; Hashem, Warda; Lama, Chamala; Reeve, Joseph L; Dauwalder, Brigitte (August 2025, Curr Issues Mol Biol)

   Beyond its crucial role as a tight barrier to protect the nervous system, the Blood–Brain Barrier (BBB) is increasingly being recognized for its physiological processes that affect brain function and behavior. In Drosophila melanogaster, the BBB expresses sex-specific transcripts, and a change in the sexual identity of adult BBB cells results in a significant reduction in male courtship behavior. The molecular nature of this BBB/brain interaction and the molecules that mediate it are unknown. Here we feminize BBB cells by targeted expression of the Drosophila female-specific master regulator TraF in otherwise normal males. We examined the effect on RNA expression in dissected brains by RNA sequencing. We find that 283 transcripts change in comparison to normal control males. Transcripts representing cell signaling processes and synaptic communication are enriched, as are hormonal mediators. These transcripts provide a valuable resource for addressing questions about BBB and brain interaction. 

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5. Knowledge Tracing Using the Brain

   Halpern, D.; Tubridy, S.; Wang, H. Y.; Gasser, C.; Popp, P. J.; Davachi, L.; Gureckis, T. M. (July 2018, Proceedings of the 11th International Conference on Educational Data Mining (EDM 2018))

   Knowledge tracing is a popular and successful approach to modeling student learning. In this paper, we investigate whether the addition of neuroimaging observations to a knowledge tracing model enables accurate prediction of memory performance in held-out data. We propose a Hidden Markov Model of memory acquisition related to Bayesian Knowledge Tracing and show how continuous functional magnetic resonance imaging (fMRI) signals can be incorporated as observations related to latent knowledge states. We then show, using data collected from a simple second-language learning experiment, that fMRI data acquired during a learning session can be used to improve predictions about student memory at test. The fitted models can also potentially give new insight into the neural mechanisms that contribute to learning and memory. 

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