Screens for genes that orchestrate neural circuit formation in mammals have been hindered by practical constraints of germline mutagenesis. To overcome these limitations, we combined RNA-seq with somatic CRISPR mutagenesis to study synapse development in the mouse retina. Here synapses occur between cellular layers, forming two multilayered neuropils. The outer neuropil, the outer plexiform layer (OPL), contains synapses made by rod and cone photoreceptor axons on rod and cone bipolar dendrites, respectively. We used RNA-seq to identify selectively expressed genes encoding cell surface and secreted proteins and CRISPR-Cas9 electroporation with cell-specific promoters to assess their roles in OPL development. Among the genes identified in this way are Wnt5a and Wnt5b. They are produced by rod bipolars and activate a non-canonical signaling pathway in rods to regulate early OPL patterning. The approach we use here can be applied to other parts of the brain.
The genetic complexity, clinical variability, and inaccessibility of affected tissue in neurodegenerative and neuropsychiatric disorders have largely prevented the development of effective disease-modifying therapeutics. A precision medicine approach that integrates genomics, deep clinical phenotyping, and patient stem cell models may facilitate identification of underlying biological drivers and targeted drug development.
Background Timely allocation of medical resources for coronavirus disease (COVID-19) requires early detection of regional outbreaks. Internet browsing data may predict case outbreaks in local populations that are yet to be confirmed. Objective We investigated whether search-engine query patterns can help to predict COVID-19 case rates at the state and metropolitan area levels in the United States. Methods We used regional confirmed case data from the New York Times and Google Trends results from 50 states and 166 county-based designated market areas (DMA). We identified search terms whose activity precedes and correlates with confirmed case rates at the national level. We used univariate regression to construct a composite explanatory variable based on best-fitting search queries offset by temporal lags. We measured the raw and z-transformed Pearson correlation and root-mean-square error (RMSE) of the explanatory variable with out-of-sample case rate data at the state and DMA levels. Results Predictions were highly correlated with confirmed case rates at the state (mean r=0.69, 95% CI 0.51-0.81; median RMSE 1.27, IQR 1.48) and DMA levels (mean r=0.51, 95% CI 0.39-0.61; median RMSE 4.38, IQR 1.80), using search data available up to 10 days prior to confirmed case rates. They fit case-rate activity in 49 of 50 states and in 103 of 166 DMA at a significance level of .05. Conclusions Identifiable patterns in search query activity may help to predict emerging regional outbreaks of COVID-19, although they remain vulnerable to stochastic changes in search intensity.
Although vaccines for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have been successful, there are no good treatments for those who are actively infected and potentially suffer from diverse neurological symptoms. While SARS-CoV-2 primarily infects the respiratory tract, clinical evidence indicates that cells from sensory organs, brain, and heart are also susceptible to infection. An understanding of factors critical for viral infection in these tissues may help identify novel therapeutics. To discover host factors involved in SARS-CoV-2 viral entry, we performed CRISPR activation (CRISPRa) screens targeting all 6000+ human membrane proteins in cells with and without overexpression of ACE2 using Spike-pseudotyped lentiviruses. We identified both novel as well as previously validated host factors. Notably, we used replication-competent SARS-CoV-2 to validate new viral-entry promoting genes, including potassium channel KCNA6, protease LGMN, and MHC-II component HLA-DPB1. We found that the overexpression of KCNA6 led to a marked increase in infection even in cells with undetectable levels of ACE2 expression. Our analysis of human olfactory neuroepithelium scRNA-seq data revealed that OLIG2+ cells--previously identified as sites of infection in COVID-19 autopsy studies--have high KCNA6 expression and minimal levels of ACE2, suggesting that the presence of KCNA6 may explain sensory/neuronal aspects of COVID-19 symptoms. Further, we demonstrate that FDA-approved compound dalfampridine, an inhibitor of KCNA-family potassium channels, suppresses viral entry in a dosage-dependent manner. Finally, we identified common prescription drugs likely to modulate the top screen hits. We then performed a retrospective analysis of insurance claims of ~8 million patients and found a clinical association between screen-identified drug classes, particularly those targeting potassium channels, and COVID-19 severity. We have thus identified the potassium channel KCNA6 as a SARS-CoV-2 host factor, expanded our understanding of potential viral tropism, and identified promising targets for drug repurposing and development.
Aims Surgical costs are a major component of healthcare expenditures in the USA. Intraoperative communication is a key factor contributing to patient outcomes. However, the effectiveness of communication is only partially determined by the surgeon, and understanding how non-surgeon personnel affect intraoperative communication is critical for the development of safe and cost-effective staffing guidelines. Operative efficiency is also dependent on high-functioning teams and can offer a proxy for effective communication in highly standardized procedures like primary total hip and knee arthroplasty. We aimed to evaluate how the composition and dynamics of surgical teams impact operative efficiency during arthroplasty. Methods We performed a retrospective review of staff characteristics and operating times for 112 surgeries (70 primary total hip arthroplasties (THAs) and 42 primary total knee arthroplasties (TKAs)) conducted by a single surgeon over a one-year period. Each surgery was evaluated in terms of operative duration, presence of surgeon-preferred staff, and turnover of trainees, nurses, and other non-surgical personnel, controlling cases for body mass index, presence of osteoarthritis, and American Society of Anesthesiologists (ASA) score. Results Turnover among specific types of operating room staff, including the anaesthesiologist (p = 0.011), circulating nurse (p = 0.027), and scrub nurse (p = 0.006), was significantly associated with increased operative duration. Furthermore, the presence of medical students and nursing students were associated with improved intraoperative efficiency in TKA (p = 0.048) and THA (p = 0.015), respectively. The presence of surgical fellows (p > 0.05), vendor representatives (p > 0.05), and physician assistants (p > 0.05) had no effect on intraoperative efficiency. Finally, the presence of the surgeon’s 'preferred' staff did not significantly shorten operative duration, except in the case of residents (p = 0.043). Conclusion Our findings suggest that active management of surgical team turnover and composition may provide a means of improving intraoperative efficiency during THA and TKA. Cite this article: Bone Joint J 2021;103-B(2):347–352.
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