Analyzing Disruptive Innovation in U.S. Liberal Arts Higher Education Institutions

Independent liberal arts colleges (LACs) are slowly disappearing from the landscape of U.S. higher education. Depletion of endowments, mission creep, and a stigma in institutional innovation are prominent factors that threaten this institutional legacy of higher education. On the other hand, LAC graduates are constantly sought after by employers as strong job candidates, suggesting that the LACs in the United States need an innovative approach to self-transformation. Propelled by technological advancement and based on the marketing principles of non-competition, job-to-be-done, and unbundling, Clayton Christensen’s Disruptive Innovation Theory (DI) has been adopted in the social sector for a few years. There is no evidence suggesting that the LACs are immune to the impact of DI and its examples (e.g., MOOC) that have already entered the higher education sector. The Disruptive Innovation Theory can be enriched by lending a transformational vision to a higher education sub-sector, but there is a glaring shortage of empirical research that aims at developing the two concepts through their marriage. This dissertation research employed a mixed method of online survey and semi-structured interview with senior administrators from 225 private "Baccalaureate Colleges - Arts & Sciences Focus" based on 2015 Carnegie Classification of Institutions of Higher Education. The senior administrators are equivalents of chief academic officer, chief information officer, and chief financial officer from each institution. Conceptual awareness and existing models of disruptive innovation were analyzed and presented in this study. Keywords: Liberal arts college; Disruptive innovation; Institutional innovation; Governance in higher education; Educational technolog

Separation and identification of mouse brain tissue microproteins using top‐down method with high resolution nanocapillary liquid chromatography mass spectrometry

Microproteins and endogenous peptides in the brain contain important substances that have critical roles in diverse biological processes, contributing to signal transduction and intercellular signaling. However, variability in their physical or chemical characteristics, such as molecule size, hydrophobicity, and charge states, complicate the simultaneous analysis of these compounds, although this would be highly beneficial for the field of neuroscience research. Here, we present a top-down analytical method for simultaneous analysis of microproteins and endogenous peptides using high- resolution nanocapillary LC-MS/MS. This method is detergent-free and digestion-free, which allows for extracting and preserving intact microproteins and peptides for direct LC-MS analysis. Both higher energy collision dissociation and electron-transfer dissociation fragmentations were used in the LC-MS analysis to increase the identification rate, and bioinformatics tools ProteinGoggle and PEAKS Studio software were utilized for database search. In total, we identified 471 microproteins containing 736 proteoforms, including brain-derived neurotrophic factor and a number of fibroblast growth factors. In addition, we identified 599 peptides containing 151 known or potential neuropeptides such as somatostatin-28 and neuropeptide Y. Our approach bridges the gap for the characterization of brain microproteins and peptides, which permits quantification of a diversity of signaling molecules for biomarker discovery or therapy diagnosis in the future

Employing machine learning using ferroptosis-related genes to construct a prognosis model for patients with osteosarcoma

Identifying effective biomarkers in osteosarcoma (OS) is important for predicting prognosis. We investigated the prognostic value of ferroptosis-related genes (FRGs) in OS. Transcriptome and clinical data were obtained from The Cancer Genome Atlas and Gene Expression Omnibus. FRGs were obtained from the ferroptosis database. Univariate COX regression and LASSO regression screening were performed and an FRG-based prognostic model was constructed, which was validated using the Gene Expression Omnibus cohort. The predictive power of the model was assessed via a subgroup analysis. A nomogram was constructed using clinical markers with independent prognostic significance and risk score results. The CIBERSORT algorithm was used to detect the correlation between prognostic genes and 22 tumor-infiltrating lymphocytes. The expression of prognostic genes in erastin-treated OS cell lines was verified via real-time PCR. Six prognostic FRGs (ACSL5, ATF4, CBS, CDO1, SCD, and SLC3A2) were obtained and used to construct the risk prognosis model. Subjects were divided into high- and low-risk groups. Prognosis was worse in the high-risk group, and the model had satisfactory prediction performance for patients younger than 18 years, males, females, and those with non-metastatic disease. Univariate COX regression analysis showed that metastasis and risk score were independent risk factors for patients with OS. Nomogram was built on independent prognostic factors with superior predictive power and patient benefit. There was a significant correlation between prognostic genes and tumor immunity. Six prognostic genes were differentially expressed in ferroptosis inducer-treated OS cell lines. The identified prognostic genes can regulate tumor growth and progression by affecting the tumor microenvironment

Sciences for The 2.5-meter Wide Field Survey Telescope (WFST)

The Wide Field Survey Telescope (WFST) is a dedicated photometric survey facility under construction jointly by the University of Science and Technology of China and Purple Mountain Observatory. It is equipped with a primary mirror of 2.5m in diameter, an active optical system, and a mosaic CCD camera of 0.73 Gpix on the main focus plane to achieve high-quality imaging over a field of view of 6.5 square degrees. The installation of WFST in the Lenghu observing site is planned to happen in the summer of 2023, and the operation is scheduled to commence within three months afterward. WFST will scan the northern sky in four optical bands (u, g, r, and i) at cadences from hourly/daily to semi-weekly in the deep high-cadence survey (DHS) and the wide field survey (WFS) programs, respectively. WFS reaches a depth of 22.27, 23.32, 22.84, and 22.31 in AB magnitudes in a nominal 30-second exposure in the four bands during a photometric night, respectively, enabling us to search tremendous amount of transients in the low-z universe and systematically investigate the variability of Galactic and extragalactic objects. Intranight 90s exposures as deep as 23 and 24 mag in u and g bands via DHS provide a unique opportunity to facilitate explorations of energetic transients in demand for high sensitivity, including the electromagnetic counterparts of gravitational-wave events detected by the second/third-generation GW detectors, supernovae within a few hours of their explosions, tidal disruption events and luminous fast optical transients even beyond a redshift of 1. Meanwhile, the final 6-year co-added images, anticipated to reach g about 25.5 mag in WFS or even deeper by 1.5 mag in DHS, will be of significant value to general Galactic and extragalactic sciences. The highly uniform legacy surveys of WFST will also serve as an indispensable complement to those of LSST which monitors the southern sky.Comment: 46 pages, submitted to SCMP

USP21 negatively regulates antiviral response by acting as a RIG-I deubiquitinase

Lys63-linked polyubiquitination of RIG-I is essential in antiviral immune defense, yet the molecular mechanism that negatively regulates this critical step is poorly understood. Here, we report that USP21 acts as a novel negative regulator in antiviral responses through its ability to bind to and deubiquitinate RIG-I. Overexpression of USP21 inhibited RNA virus–induced RIG-I polyubiquitination and RIG-I–mediated interferon (IFN) signaling, whereas deletion of USP21 resulted in elevated RIG-I polyubiquitination, IRF3 phosphorylation, IFN-α/β production, and antiviral responses in MEFs in response to RNA virus infection. USP21 also restricted antiviral responses in peritoneal macrophages (PMs) and bone marrow–derived dendritic cells (BMDCs). USP21-deficient mice spontaneously developed splenomegaly and were more resistant to VSV infection with elevated production of IFNs. Chimeric mice with USP21-deficient hematopoietic cells developed virus-induced splenomegaly and were more resistant to VSV infection. Functional comparison of three deubiquitinases (USP21, A20, and CYLD) demonstrated that USP21 acts as a bona fide RIG-I deubiquitinase to down-regulate antiviral response independent of the A20 ubiquitin-editing complex. Our studies identify a previously unrecognized role for USP21 in the negative regulation of antiviral response through deubiquitinating RIG-I

Bone marrow-derived cells in ocular neovascularization: contribution and mechanisms

Ocular neovascularization often leads to severe vision loss. The role of bone marrow-derived cells (BMCs) in the development of ocular neovascularization, and its significance, is increasingly being recognized. In this review, we discuss their contribution and the potential mechanisms that mediate the effect of BMCs on the progression of ocular neovascularization. The sequence of events by which BMCs participate in ocular neovascularization can be roughly divided into four phases, i.e., mobilization, migration, adhesion and differentiation. This process is delicately regulated and liable to be affected by multiple factors. Cytokines such as vascular endothelial growth factor, granulocyte colony-stimulating factor and erythropoietin are involved in the mobilization of BMCs. Studies have also demonstrated a key role of cytokines such as stromal cell-derived factor-1, tumor necrosis factor-α, as well as vascular endothelial growth factor, in regulating the migration of BMCs. The adhesion of BMCs is mainly regulated by vascular cell adhesion molecule-1, intercellular adhesion molecule-1 and vascular endothelial cadherin. However, the mechanisms regulating the differentiation of BMCs are largely unknown at present. In addition, BMCs secrete cytokines that interact with the microenvironment of ocular neovascularization; their contribution to ocular neovascularization, especially choroidal neovascularization, can be aggravated by several risk factors. An extensive regulatory network is thought to modulate the role of BMCs in the development of ocular neovascularization. A comprehensive understanding of the involved mechanisms will help in the development of novel therapeutic strategies related to BMCs. In this review, we have limited the discussion to the recent progress in this field, especially the research conducted at our laboratory

Geographical distribution and conservation strategy of national key protected wild plants of China

Summary: National key protected wild plants (NKPWPs) are considered flagship species for plant diversity conservation in China. Using data for 1101 species, we characterized NKPWPs distribution patterns in China and assessed conservation effectiveness and conservation gaps. In total, 4880 grid cells at a 20 × 20 km resolution were filled with occurrence records for NKPWPs. We identified 444 hotspot grid cells and 27 diversity hotspot regions, containing 92.37% of NKPWPs. However, 43.24% of these hotspot grid cells were fully or partially covered by national nature reserves (NNRs), where 70.21% of species were distributed. Approximately 61.49% of the NKPWPs species were protected by NNRs, but the populations or habitats of 963 species were partially or fully outside of NNRs. With global warming, the overall change in the extent of suitable habitats for NKPWPs is expected to be small, however, habitat quality in some areas with a high habitat suitability index will decrease

Joint Geoeffectiveness and Arrival Time Prediction of CMEs by a Unified Deep Learning Framework

Fast and accurate prediction of the geoeffectiveness of coronal mass ejections (CMEs) and the arrival time of the geoeffective CMEs is urgent, to reduce the harm caused by CMEs. In this paper, we present a new deep learning framework based on time series of satellites’ optical observations that can give both the geoeffectiveness and the arrival time prediction of the CME events. It is the first time combining these two demands in a unified deep learning framework with no requirement of manually feature selection and get results immediately. The only input of the deep learning framework is the time series images from synchronized solar white-light and EUV observations. Our framework first uses the deep residual network embedded with the attention mechanism to extract feature maps for each observation image, then fuses the feature map of each image by the feature map fusion module and determines the geoeffectiveness of CME events. For the geoeffective CME events, we further predict its arrival time by the deep residual regression network based on group convolution. In order to train and evaluate our proposed framework, we collect 2400 partial-/full-halo CME events and its corresponding images from 1996 to 2018. The F1 score and Accuracy of the geoeffectiveness prediction can reach 0.270% and 75.1%, respectively, and the mean absolute error of the arrival time prediction is only 5.8 h, which are both significantly better than well-known deep learning methods and can be comparable to, or even better than, the best performance of traditional methods

Extensive characterization of peptides from Panax ginseng C. A. Meyer using mass spectrometric approach

Panax ginseng is an important herb that has clear effects on the treatment of diverse diseases. Until now, the natural peptide constitution of this herb remains unclear. Here, we conduct an extensive characterization of Ginseng peptidome using MS-based data mining and sequencing. The screen on the charge states of precursor ions indicated that Ginseng is a peptide-rich herb in comparison of a number of commonly used herbs. The Ginseng peptides were then extracted and submitted to nano-LC-MS/MS analysis using different fragmentation modes, including CID, high-energy collisional dissociation, and electron transfer dissociation. Further database search and de novo sequencing allowed the identification of total 308 peptides, some of which might have important biological activities. This study illustrates the abundance and sequences of endogenous Ginseng peptides, thus providing the information of more candidates for the screening of active compounds for future biological research and drug discovery studies