A simple Bessel module with tunable focal depth and constant resolution for commercial two-photon microscope

The volumetric imaging of two-photon microscopy expands the focal depth and improves the throughput,which has unparalleled superiority for three-dimension samples,especially in neuroscience.However,emerging in volumetric imaging is still largely customized,which limits the integration with commercial two-photon systems.Here,we analyzed the key parameters that modulate the focal depth and lateral resolution of polarized annular imaging and proposed a volumetric imaging module that can be directly integrated into commercial two-photon systems using conventional optical elements.This design incorporates the beam diameter adjustment settings of commercial two-photon systems,allowing flexibility to adjust the depth of focus while maintaining the same lateral resolution.Further,the depth range and lateral resolution of the design were verified,and the imaging throughput was demonstrated by an increase in the number of imaging neurons in the awake mouse cerebral cortex.

Ultrasensitive and point-of-care detection of plasma phosphorylated tau in Alzheimer’s disease using colorimetric and surface-enhanced Raman scattering dual-readout lateral flow assay

Phosphorylation of tau at Ser(396,404)(p-tau^(396,404))is one of the earliest phosphorylation events,plasma p-tau^(396,404) level appears to be a potentially promising biomarker of Alzheimer’s disease(AD).The low abundance and easy degradation of p-tau in the plasma make the lateral flow assay(LFA)a suitable choice for point-of-care detection of plasma p-tau^(396,404) levels.Herein,based on our screening of a pair of p-tau^(396,404)-specific antibodies,we developed a colorimetric and surface-enhanced Raman scattering(SERS)dual-readout LFA for the rapid,highly sensitive,robust detection of plasma p-tau^(396,404) levels.This LFA realized a detection limit of 60 pg/mL by the naked eye or 3.8 pg/mL by SERS without cross-reacting with other tau species.More importantly,LFA rapidly and accurately differentiated AD patients from healthy controls,suggesting that it has the potential for clinical point-of-care application in AD diagnosis.This dual-readout LFA has the advantages of simple operation,rapid,ultra-sensitive detection,providing a new way for early AD diagnosis and intervention,especially in primary and community AD screening.

Deep learning-based large-scale named entity recognition for anatomical region of mammalian brain

Background:Images of anatomical regions and neuron type distribution,as well as their related literature are valuable assets for neuroscience research.They are vital evidence and vehicles in discovering new phenomena and knowledge refinement through image and text big data.The knowledge acquired from image data generally echoes with the literature accumulated over the years.The knowledge within the literature can provide a comprehensive context for a deeper understanding of the image data.However,it is quite a challenge to manually identify the related literature and summarize the neuroscience knowledge in the large-scale corpus.Thus,neuroscientists are in dire need of an automated method to extract neuroscience knowledge from large-scale literature.Methods:A proposed deep learning model named BioBERT-CRF extracts brain region entities from the WhiteText dataset.This model takes advantage of BioBERT and CRF to predict entity labels while training.Results:The proposed deep learning model demonstrated comparable performance against or even outperforms the previous models on the WhiteText dataset.The BioBERT-CRF model has achieved the best average precision,recall,and F1 score of 81.3%,84.0%,and 82.6%,respectively.We used the BioBERT-CRF model to predict brain region entities in a large-scale PubMed abstract dataset and used a rule-based method to normalize all brain region entities to three neuroscience dictionaries.Conclusions:Our work shows that the BioBERT-CRF model can be well-suited for brain region entity extraction.The rankings of different brain region entities by their appearance in the large-scale corpus indicate the anatomical regions that researchers are most concerned about.

Whole-Brain Connectome of GABAergic Neurons in the Mouse Zona Incerta

The zona incerta(ZI)is involved in various functions and may serve as an integrative node of the circuits for global behavioral modulation.However,the long-range connectivity of different sectors in the mouse ZI has not been comprehensively mapped.Here,we obtained whole-brain images of the input and output connections via fluorescence micro-optical sectioning tomography and viral tracing.The principal regions in the input-output circuits of ZI GABAergic neurons were topologically organized.The 3D distribution of cortical inputs showed rostro-caudal correspondence with different ZI sectors,while the projection fibers from ZI sectors were longitudinally organized in the superior colliculus.Clustering results show that the medial and lateral ZI are two different major functional compartments,and they can be further divided into more subdomains based on projection and input connectivity.This study provides a comprehensive anatomical foundation for understanding how the ZI is involved in integrating different information,conveying motivational states,and modulating global behaviors.