We demonstrated the in vivo feasibility of using focused ultrasound (FUS) to transiently modulate (through either stimulation or suppression) the function of regional brain tissue in rabbits. FUS was delivered in a train of pulses at low acoustic energy, far below the cavitation threshold, to the animal's somatomotor and visual areas, as guided by anatomical and functional information from magnetic resonance imaging (MRI). The temporary alterations in the brain function affected by the sonication were characterized by both electrophysiological recordings and functional brain mapping achieved through the use of functional MRI (fMRI). The modulatory effects were bimodal, whereby the brain activity could either be stimulated or selectively suppressed. Histological analysis of the excised brain tissue after the sonication demonstrated that the FUS did not elicit any tissue damages. Unlike transcranial magnetic stimulation, FUS can be applied to deep structures in the brain with greater spatial precision. Transient modulation of brain function using image-guided and anatomically-targeted FUS would enable the investigation of functional connectivity between brain regions and will eventually lead to a better understanding of localized brain functions. It is anticipated that the use of this technology will have an impact on brain research and may offer novel therapeutic interventions in various neurological conditions and psychiatric disorders.

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Alzheimer’s disease (AD) involves progressive accumulation of amyloid β-peptide (Aβ) and neurofibrillary pathologies, and glucose hypometabolism in brain regions critical for memory. The 3xTgAD mouse model was used to test the hypothesis that a ketone ester–based diet can ameliorate AD pathogenesis. Beginning at a presymptomatic age, 2 groups of male 3xTgAD mice were fed a diet containing a physiological enantiomeric precursor of ketone bodies (KET) or an isocaloric carbohydrate diet. The results of behavioral tests performed at 4 and 7 months after diet initiation revealed that KET-fed mice exhibited significantly less anxiety in 2 different tests. 3xTgAD mice on the KET diet also exhibited significant, albeit relatively subtle, improvements in performance on learning and memory tests. Immunohistochemical analyses revealed that KET-fed mice exhibited decreased Aβ deposition in the subiculum, CA1 and CA3 regions of the hippocampus, and the amygdala. KET-fed mice exhibited reduced levels of hyperphosphorylated tau deposition in the same regions of the hippocampus, amygdala, and cortex. Thus, a novel ketone ester can ameliorate proteopathic and behavioral deficits in a mouse AD model.

Transcranial focused ultrasound (FUS) is making progress as a new non-invasive mode of regional brain stimulation. Current evidence of FUS-mediated neurostimulation for humans has been limited to the observation of subjective sensory manifestations and electrophysiological responses, thus warranting the identification of stimulated brain regions. Here, we report FUS sonication of the primary visual cortex (V1) in humans, resulting in elicited activation not only from the sonicated brain area, but also from the network of regions involved in visual and higher-order cognitive processes (as revealed by simultaneous acquisition of blood-oxygenation-level-dependent functional magnetic resonance imaging). Accompanying phosphene perception was also reported. The electroencephalo graphic (EEG) responses showed distinct peaks associated with the stimulation. None of the participants showed any adverse effects from the sonication based on neuroimaging and neurological examinations. Retrospective numerical simulation of the acoustic profile showed the presence of individual variability in terms of the location and intensity of the acoustic focus. With exquisite spatial selectivity and capability for depth penetration, FUS may confer a unique utility in providing non-invasive stimulation of region-specific brain circuits for neuroscientific and therapeutic applications.

Functional connectivity (FC) patterns obtained from resting-state functional magnetic resonance imaging data are commonly employed to study neuropsychiatric conditions by using pattern classifiers such as the support vector machine (SVM). Meanwhile, a deep neural network (DNN) with multiple hidden layers has shown its ability to systematically extract lower-to-higher level information of image and speech data from lower-to-higher hidden layers, markedly enhancing classification accuracy. The objective of this study was to adopt the DNN for whole-brain resting-state FC pattern classification of schizophrenia (SZ) patients vs. healthy controls (HCs) and identification of aberrant FC patterns associated with SZ. We hypothesized that the lower-to-higher level features learned via the DNN would significantly enhance the classification accuracy, and proposed an adaptive learning algorithm to explicitly control the weight sparsity in each hidden layer via L1-norm regularization. Furthermore, the weights were initialized via stacked autoencoder based pre-training to further improve the classification performance. Classification accuracy was systematically evaluated as a function of (1) the number of hidden layers/nodes, (2) the use of L1-norm regularization, (3) the use of the pre-training, (4) the use of framewise displacement (FD) removal, and (5) the use of anatomical/functional parcellation. Using FC patterns from anatomically parcellated regions without FD removal, an error rate of 14.2% was achieved by employing three hidden layers and 50 hidden nodes with both L1-norm regularization and pre-training, which was substantially lower than the error rate from the SVM (22.3%). Moreover, the trained DNN weights (i.e., the learned features) were found to represent the hierarchical organization of aberrant FC patterns in SZ compared with HC. Specifically, pairs of nodes extracted from the lower hidden layer represented sparse FC patterns implicated in SZ, which was quantified by using kurtosis/modularity measures and features from the higher hidden layer showed holistic/global FC patterns differentiating SZ from HC. Our proposed schemes and reported findings attained by using the DNN classifier and whole-brain FC data suggest that such approaches show improved ability to learn hidden patterns in brain imaging data, which may be useful for developing diagnostic tools for SZ and other neuropsychiatric disorders and identifying associated aberrant FC patterns.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes coronavirus disease 2019 (COVID-19), a newly emerging human infectious disease. Because no specific antiviral drugs or vaccines are available to treat COVID-19, early diagnostics, isolation, and prevention are crucial for containing the outbreak. Molecular diagnostics using reverse transcription polymerase chain reaction (RT-PCR) are the current gold standard for detection. However, viral RNAs are much less stable during transport and storage than proteins such as antigens and antibodies. Consequently, false-negative RT-PCR results can occur due to inadequate collection of clinical specimens or poor handling of a specimen during testing. Although antigen immunoassays are stable diagnostics for detection of past infection, infection progress, and transmission dynamics, no matched antibody pair for immunoassay of SARS-CoV-2 antigens has yet been reported. In this study, we designed and developed a novel rapid detection method for SARS-CoV-2 spike 1 (S1) protein using the SARS-CoV-2 receptor ACE2, which can form matched pairs with commercially available antibodies. ACE2 and S1-mAb were paired with each other for capture and detection in a lateral flow immunoassay (LFIA) that did not cross-react with SARS-CoV Spike 1 or MERS-CoV Spike 1 protein. The SARS-CoV-2 S1 (<5 ng of recombinant proteins/reaction) was detected by the ACE2-based LFIA. The limit of detection of our ACE2-LFIA was 1.86 × 10 5 copies/mL in the clinical specimen of COVID-19 Patients without no cross-reactivity for nasal swabs from healthy subjects. This is the first study to detect SARS-CoV-2 S1 antigen using an LFIA with matched pair consisting of ACE2 and antibody. Our findings will be helpful to detect the S1 antigen of SARS-CoV-2 from COVID-19 patients.

One of the challenges in tissue engineering is to provide adequate supplies of oxygen and nutrients to cells within the engineered tissue construct. Soft-lithographic techniques have allowed the generation of hydrogel scaffolds containing a network of fluidic channels, but at the cost of complicated and often time-consuming manufacturing steps. We report a three-dimensional (3D) direct printing technique to construct hydrogel scaffolds containing fluidic channels. Cells can also be printed on to and embedded in the scaffold with this technique. Collagen hydrogel precursor was printed and subsequently crosslinked via nebulized sodium bicarbonate solution. A heated gelatin solution, which served as a sacrificial element for the fluidic channels, was printed between the collagen layers. The process was repeated layer-by-layer to form a 3D hydrogel block. The printed hydrogel block was heated to 378C, which allowed the gelatin to be selectively liquefied and drained, generating a hollow channel within the collagen scaffold. The dermal fibroblasts grown in a scaffold containing fluidic channels showed significantly elevated cell viability compared to the ones without any channels. The on-demand capability to print fluidic channel structures and cells in a 3D hydrogel scaffold offers flexibility in generating perfusable 3D artificial tissue composites.

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