Evaluating Disparities in the U.S. Technology Transfer Ecosystem to Improve Bench to Business Translation

Background: A large number of highly impactful technologies originated from academic research, and the transfer of inventions from academic institutions to private industry is a major driver of economic growth, and a catalyst for further discovery. However, there are significant inefficiencies in academic technology transfer. In this work, we conducted a data-driven assessment of translational activity across United States (U.S.) institutions to better understand how effective universities are in facilitating the transfer of new technologies into the marketplace. From this analysis, we provide recommendations to guide technology transfer policy making at both the university and national level. Methods: Using data from the Association of University Technology Managers U.S. Licensing Activity Survey, we defined a commercialization pipeline that reflects the typical path intellectual property takes; from initial research funding to startup formation and gross income. We use this pipeline to quantify the performance of academic institutions at each step of the process, as well as overall, and identify the top performing institutions via mean reciprocal rank. The corresponding distributions were visualized and disparities quantified using the Gini coefficient. Results: We found significant discrepancies in commercialization activity between institutions; a small number of institutions contribute to the vast majority of total commercialization activity. By examining select top performing institutions, we suggest improvements universities and technology transfer offices could implement to emulate the environment at these high-performing institutions. Conclusion: Significant disparities in technology transfer performance exist in which a select set of institutions produce a majority share of the total technology transfer activity. This disparity points to missed commercialization opportunities, and thus, further investigation into the distribution of technology transfer effectiveness across institutions and studies of policy changes that would improve the effectiveness of the commercialization pipeline is warranted

Molecular analysis of autosomal dominant hereditary ataxias in the Indian population: high frequency of SCA2 and evidence for a common founder mutation

Expansion of CTG/CAG trinucleotide repeats has been shown to cause a number of autosomal dominant cerebellar ataxias (ADCA) such as SCA1, SCA2, SCA3/MJD, SCA6, SCA7, SCA8 and DRPLA. There is a wide variation in the clinical phenotype and prevalence of these ataxias in different populations. An analysis of ataxias in 42 Indian families indicates that SCA2 is the most frequent amongst all the ADCAs we have studied. In the SCA2 families, together with an intergenerational increase in repeat size, a horizontal increase with the birth order of the offspring was also observed, indicating an important role for parental age in repeat instability. This was strengthened by the detection of a pair of dizygotic twins with expanded alleles showing the same repeat number. Haplotype analysis indicates the presence of a common founder chromosome for the expanded allele in the Indian population. Polymorphism of CAG repeats in 135 normal individuals at the SCA loci studied showed similarity to the Caucasian population but was significantly different from the Japanese population

Benchmarking the generalizability of brain age models: Challenges posed by scanner variance and prediction bias

Machine learning has been increasingly applied to neuroimaging data to predict age, deriving a personalized biomarker with potential clinical applications. The scientific and clinical value of these models depends on their applicability to independently acquired scans from diverse sources. Accordingly, we evaluated the generalizability of two brain age models that were trained across the lifespan by applying them to three distinct early-life samples with participants aged 8-22 years. These models were chosen based on the size and diversity of their training data, but they also differed greatly in their processing methods and predictive algorithms. Specifically, one brain age model was built by applying gradient tree boosting (GTB) to extracted features of cortical thickness, surface area, and brain volume. The other model applied a 2D convolutional neural network (DBN) to minimally preprocessed slices of T1-weighted scans. Additional model variants were created to understand how generalizability changed when each model was trained with data that became more similar to the test samples in terms of age and acquisition protocols. Our results illustrated numerous trade-offs. The GTB predictions were relatively more accurate overall and yielded more reliable predictions when applied to lower quality scans. In contrast, the DBN displayed the most utility in detecting associations between brain age gaps and cognitive functioning. Broadly speaking, the largest limitations affecting generalizability were acquisition protocol differences and biased brain age estimates. If such confounds could eventually be removed without post-hoc corrections, brain age predictions may have greater utility as personalized biomarkers of healthy aging

Co3O4 Nanocrystals on Graphene as a Synergistic Catalyst for Oxygen Reduction Reaction

Catalysts for oxygen reduction and evolution reactions are at the heart of key renewable energy technologies including fuel cells and water splitting. Despite tremendous efforts, developing oxygen electrode catalysts with high activity at low costs remains a grand challenge. Here, we report a hybrid material of Co3O4 nanocrystals grown on reduced graphene oxide (GO) as a high-performance bi-functional catalyst for oxygen reduction reaction (ORR) and oxygen evolution reaction (OER). While Co3O4 or graphene oxide alone has little catalytic activity, their hybrid exhibits an unexpected, surprisingly high ORR activity that is further enhanced by nitrogen-doping of graphene. The Co3O4/N-doped graphene hybrid exhibits similar catalytic activity but superior stability to Pt in alkaline solutions. The same hybrid is also highly active for OER, making it a high performance non-precious metal based bi-catalyst for both ORR and OER. The unusual catalytic activity arises from synergetic chemical coupling effects between Co3O4 and graphene.Comment: published in Nature Material

Cross-Reactivity and Expansion of Dengue-Specific T cells During Acute Primary and Secondary Infections in Humans

Serotype-cross-reactive memory T cells responding to secondary dengue virus (DENV) infection are thought to contribute to disease. However, epitope-specific T cell responses have not been thoroughly compared between subjects with primary versus secondary DENV infection. We studied CD8+ T cells specific for the HLA-A*1101-restricted NS3133 epitope in a cohort of A11+ DENV-infected patients throughout acute illness and convalescence. We compared the expansion, serotype-cross-reactivity, and activation of these cells in PBMC from patients experiencing primary or secondary infection and mild or severe disease by flow cytometry. Our results show expansion and activation of DENV-specific CD8+ T cells during acute infection, which are predominantly serotype-cross-reactive regardless of DENV infection history. These data confirm marked T cell activation and serotype-cross-reactivity during the febrile phase of dengue; however, A11-NS3133-specific responses did not correlate with prior antigenic exposure or current disease severity

Antimony-doped graphene nanoplatelets

Heteroatom doping into the graphitic frameworks have been intensively studied for the development of metal-free electrocatalysts. However, the choice of heteroatoms is limited to non-metallic elements and heteroatom-doped graphitic materials do not satisfy commercial demands in terms of cost and stability. Here we realize doping semimetal antimony (Sb) at the edges of graphene nanoplatelets (GnPs) via a simple mechanochemical reaction between pristine graphite and solid Sb. The covalent bonding of the metalloid Sb with the graphitic carbon is visualized using atomic-resolution transmission electron microscopy. The Sb-doped GnPs display zero loss of electrocatalytic activity for oxygen reduction reaction even after 100,000 cycles. Density functional theory calculations indicate that the multiple oxidation states (Sb3+ and Sb5+) of Sb are responsible for the unusual electrochemical stability. Sb-doped GnPs may provide new insights and practical methods for designing stable carbon-based electrocatalystsclose0

Simple, Rapid and Cost-Effective Method for High Quality Nucleic Acids Extraction from Different Strains of Botryococcus braunii

This study deals with an effective nucleic acids extraction method from various strains of Botryococcus braunii which possesses an extensive extracellular matrix. A method combining freeze/thaw and bead-beating with heterogeneous diameter of silica/zirconia beads was optimized to isolate DNA and RNA from microalgae, especially from B. braunii. Eukaryotic Microalgal Nucleic Acids Extraction (EMNE) method developed in this study showed at least 300 times higher DNA yield in all strains of B. braunii with high integrity and 50 times reduced working volume compared to commercially available DNA extraction kits. High quality RNA was also extracted using this method and more than two times the yield compared to existing methods. Real-time experiments confirmed the quality and quantity of the input DNA and RNA extracted using EMNE method. The method was also applied to other eukaryotic microalgae, such as diatoms, Chlamydomonas sp., Chlorella sp., and Scenedesmus sp. resulting in higher efficiencies. Cost-effectiveness analysis of DNA extraction by various methods revealed that EMNE method was superior to commercial kits and other reported methods by >15%. This method would immensely contribute to area of microalgal genomics

Genomic Profiling Identifies GATA6 as a Candidate Oncogene Amplified in Pancreatobiliary Cancer

Pancreatobiliary cancers have among the highest mortality rates of any cancer type. Discovering the full spectrum of molecular genetic alterations may suggest new avenues for therapy. To catalogue genomic alterations, we carried out array-based genomic profiling of 31 exocrine pancreatic cancers and 6 distal bile duct cancers, expanded as xenografts to enrich the tumor cell fraction. We identified numerous focal DNA amplifications and deletions, including in 19% of pancreatobiliary cases gain at cytoband 18q11.2, a locus uncommonly amplified in other tumor types. The smallest shared amplification at 18q11.2 included GATA6, a transcriptional regulator previously linked to normal pancreas development. When amplified, GATA6 was overexpressed at both the mRNA and protein levels, and strong immunostaining was observed in 25 of 54 (46%) primary pancreatic cancers compared to 0 of 33 normal pancreas specimens surveyed. GATA6 expression in xenografts was associated with specific microarray gene-expression patterns, enriched for GATA binding sites and mitochondrial oxidative phosphorylation activity. siRNA mediated knockdown of GATA6 in pancreatic cancer cell lines with amplification led to reduced cell proliferation, cell cycle progression, and colony formation. Our findings indicate that GATA6 amplification and overexpression contribute to the oncogenic phenotypes of pancreatic cancer cells, and identify GATA6 as a candidate lineage-specific oncogene in pancreatobiliary cancer, with implications for novel treatment strategies

Коррекция двигательных и поведенческих функций в лечении и реабилитации больных шизотипическим расстройством

На основании особенностей невербального поведения больных шизотипическим расстройством разработаны поведенческие методы, применение которых в их комплексной терапии позволяет добиться более полной редукции психопатологической симптоматики.Behavioral methods were worked out basing of the peculiarities of non−verbal behavior of the patients with schizotypical disorders. The use of the methods in complex therapy allows to achieve more complete reduction in psychopathological signs

rs4919510 in hsa-mir-608 Is Associated with Outcome but Not Risk of Colorectal Cancer

Colorectal cancer is the third most incident cancer and cause of cancer-related death in the United States. MicroRNAs, a class of small non-coding RNAs, have been implicated in the pathogenesis and prognosis of colorectal cancer, although few studies have examined the relationship between germline mutation in the microRNAs with risk and prognosis. We therefore investigated the association between a SNP in hsa-mir-608, which lies within the 10q24 locus, and colorectal cancer.A cohort consisting of 245 cases and 446 controls was genotyped for rs4919510. The frequency of the GG genotype was significantly higher in African Americans (15%) compared to Caucasians (3%) controls. There was no significant association between rs4919510 and colorectal cancer risk (African American: OR(GG vs. CC) 0.89 [95% CI, 0.41-1.80]) (Caucasian: OR(GG vs. CC) 1.76, ([95% CI, 0.48-6.39]). However, we did observe an association with survival. The GG genotype was associated with an increased risk of death in Caucasians (HR(GG vs. CC) 3.54 ([95% CI, 1.38-9.12]) and with a reduced risk of death in African Americans (HR(GG vs. CC) 0.36 ([95% CI 0.12-1.07).These results suggest that rs4910510 may be associated with colorectal cancer survival in a manner that is dependent on race