[12]aneN3-Conjugated AIEgens with Two-Photon Imaging Property for Synergistic Gene/Photodynamic Therapy in Vitro and in Vivo

Six amphiphiles (TTC-L-M-1/2/3/4/5/6), each consisting of hydrophilic macrocyclic polyamine triazole-[12]aneN3 (M) and hydrophobic photosensitizer tetraphenylethenethiophene modified cyanoacrylate (TTC) moiety linked with alkyl chains (L), have been designed and synthesized for...

Distinct features of brain perivascular fibroblasts and mural cells revealed by in vivo two-photon imaging

Perivascular fibroblasts (PVFs) are recognized for their pro-fibrotic role in many central nervous system disorders. Like mural cells, PVFs surround blood vessels and express Pdgfrβ. However, these shared attributes hinder the ability to distinguish PVFs from mural cells. We used in vivo two-photon imaging and transgenic mice with PVF-targeting promoters (Col1a1 or Col1a2) to compare the structure and distribution of PVFs and mural cells in cerebral cortex of healthy, adult mice. We show that PVFs localize to all cortical penetrating arterioles and their offshoots (arteriole-capillary transition zone), as well as the main trunk of only larger ascending venules. However, the capillary zone is devoid of PVF coverage. PVFs display short-range mobility along the vessel wall and exhibit distinct structural features (flattened somata and thin ruffled processes) not seen with smooth muscle cells or pericytes. These findings clarify that PVFs and mural cells are distinct cell types coexisting in a similar perivascular niche.

Long-term labeling and imaging of synaptically-connected neuronal networks in vivo using nontoxic, double-deletion-mutant rabies viruses

SummaryThe highly specific and complex connectivity between neurons is the hallmark of nervous systems, but techniques for identifying, imaging, and manipulating synaptically-connected networks of neurons are limited. Monosynaptic tracing, or the gated replication and spread of a deletion-mutant rabies virus to label neurons directly connected to a targeted population of starting neurons1, is the most widely-used technique for mapping neural circuitry, but the rapid cytotoxicity of first-generation rabies viral vectors has restricted its use almost entirely to anatomical applications. We recently introduced double-deletion-mutant second-generation rabies viral vectors, showing that they have little or no detectable toxicity and are efficient means of retrogradely targeting neurons projecting to an injection site2, but they have not previously been shown to be capable of gated replication in vivo, the basis of monosynaptic tracing. Here we present a complete second-generation system for labeling direct inputs to genetically-targeted neuronal populations with minimal toxicity, using double-deletion-mutant rabies viruses. Spread of the viruses requires complementation of both of the deleted viral genes in trans in the starting postsynaptic cells; suppressing the expression of these viral genes following an initial period of viral replication, using the Tet-Off system, reduces toxicity to the starting cells without decreasing the efficiency of viral spread. Using longitudinal two- photon imaging of live monosynaptic tracing in visual cortex, we found that 94.4% of all labeled cells, and an estimated 92.3% of starting cells, survived for the full twelve-week course of imaging. Two-photon imaging of calcium responses in labeled networks of neurons in vivo over ten weeks showed that labeled neurons’ visual response properties remained stable for as long as we followed them. This nontoxic labeling of inputs to genetically-targeted neurons in vivo is a long-held goal in neuroscience, with transformative applications including nonperturbative transcriptomic and epigenomic profiling, long-term functional imaging and behavioral studies, and optogenetic and chemogenetic manipulation of synaptically-connected neuronal networks over the lifetimes of experimental animals.

Calcium imaging reveals depressive- and manic-phase-specific brain neural activity patterns in a murine model of bipolar disorder: a pilot study

Brain pathological features during manic/hypomanic and depressive episodes in the same patients with bipolar disorder (BPD) have not been described precisely. The study aimed to investigate depressive and manic-phase-specific brain neural activity patterns of BPD in the same murine model to provide information guiding investigation of the mechanism of phase switching and tailored prevention and treatment for patients with BPD. In vivo two-photon imaging was used to observe brain activity alterations in the depressive and manic phases in the same murine model of BPD. Two-photon imaging showed significantly reduced Ca2+ activity in temporal cortex pyramidal neurons in the depression phase in mice exposed to chronic unpredictable mild stress (CUMS), but not in the manic phase in mice exposed to CUMS and ketamine. Total integrated calcium values correlated significantly with immobility times. Brain Ca2+ hypoactivity was observed in the depression and manic phases in the same mice exposed to CUMS and ketamine relative to naïve controls. The novel object recognition preference ratio correlated negatively with the immobility time in the depression phase and the total distance traveled in the manic phase. With recognition of its limitations, this study revealed brain neural activity impairment indicating that intrinsic emotional network disturbance is a mechanism of BPD and that brain neural activity is associated with cognitive impairment in the depressive and manic phases of this disorder. These findings are consistent with those from macro-imaging studies of patients with BPD. The observed correlation of brain neural activity with the severity of depressive, but not manic, symptoms need to be investigated further.

Simultaneous two-photon imaging of action potentials and subthreshold inputs in vivo

To better understand the input-output computations of neuronal populations, we developed ArcLight-ST, a genetically-encoded voltage indicator, to specifically measure subthreshold membrane potentials. We combined two-photon imaging of voltage and calcium, and successfully discriminated subthreshold inputs and spikes with cellular resolution in vivo. We demonstrate the utility of the method by mapping epileptic seizures progression through cortical circuits, revealing divergent sub- and suprathreshold dynamics within compartmentalized epileptic micronetworks. Two-photon, two-color imaging of calcium and voltage enables mapping of inputs and outputs in neuronal populations in living animals.

Computer-aided Detection of Quantitative Signatures for Breast Fibroepithelial Tumors using Label-free Multi-Photon Imaging

Background Fibroadenomas (FAs) and phyllodes tumors (PTs) are major benign breast tumors. They are pathologically classified as fibroepithelial tumors, composed of a proliferation of both epithelial and stroma. Although the clinical management of PTs differs from FAs, distinction by core needle biopsy diagnoses is still challenging. Computer-aided diagnosis is playing a pivotal role in accurate and objective evaluation of medical images. This technology opens up a new route to a solution for diagnostic problems. Methods A combined technique of label-free imaging with multi-photon microscopy and artificial intelligence was applied to detect quantitative signatures that differentiate fibroepithelial lesions. Multi-photon excited autofluorescence and second harmonic generation (SHG) signals were detected in tissue sections. A pixel-wise semantic segmentation method using a deep learning framework was used to separate epithelial and stromal regions automatically. Quantitative signatures, the epithelial to stromal area ratio, and the collagen SHG signal strength were investigated for their ability to distinguish between FA and PT lesions. Results Multi-photon microscopy recordings of tissue sections revealed distinct morphology between the epithelia and stroma, and further indicated that stromal regions emit a strong SHG signal which derives from collagen fibrils. However, this signal strength differs between the lesions, suggesting differences of collagenous molecular composition between the two lesions. In order to investigate hypertrophy of the stroma and compare this to the epithelial areas, an image segmentation analysis with a pixel-wise semantic segmentation framework using a deep convolutional neural network was performed. The deep learning-based analysis showed accurate separation of epithelial and stromal regions. Further investigation was conducted to determine if scoring the epithelial to stromal area ratio could be a marker for differentiating fibroadenoma and phyllodes tissues; we determined that most samples can be clearly separated but some are difficult to separate by the signature. Further investigations on the collagen SHG signal strength within the stromal area revealed accurate classification of the breast tissue lesions. Conclusions Molecular and morphological changes detected through the assistance of computational and label-free multi-photon imaging techniques enabled us to propose quantitative signatures for epithelial and stromal alterations in breast tissues.