MOLIERE: Automatic Biomedical Hypothesis Generation System

Hypothesis generation is becoming a crucial time-saving technique which allows biomedical researchers to quickly discover implicit connections between important concepts. Typically, these systems operate on domain-specific fractions of public medical data. MOLIERE, in contrast, utilizes information from over 24.5 million documents. At the heart of our approach lies a multi-modal and multi-relational network of biomedical objects extracted from several heterogeneous datasets from the National Center for Biotechnology Information (NCBI). These objects include but are not limited to scientific papers, keywords, genes, proteins, diseases, and diagnoses. We model hypotheses using Latent Dirichlet Allocation applied on abstracts found near shortest paths discovered within this network, and demonstrate the effectiveness of MOLIERE by performing hypothesis generation on historical data. Our network, implementation, and resulting data are all publicly available for the broad scientific community

Moliere: Automatic Biomedical Hypothesis Generation

Medical research is expensive and risky. Drug manufacturers need to prioritize their early investments with very little experimental data in order to most efficiently discover new treatments. Moliere is a hypothesis generation system that identifies implicit yet-unknown connections already present within the body of medical literature. Using our discovery and ranking system, medical researchers can identify fruitful research directions earlier in the discovery process, before time consuming and expensive experiments. For example, we used Moliere to identify a new gene-treatment target for HIV-associated Neurodegenerative Disease, which we later confirmed in laboratory experiments

MOLIERE: Automatic Biomedical Hypothesis Generation System

Hypothesis generation is becoming a crucial time-saving technique which allows biomedical researchers to quickly discover implicit connections between important concepts. Typically, these systems operate on domain-specific fractions of public medical data. MOLIERE, in contrast, utilizes information from over 24.5 million documents. At the heart of our approach lies a multi-modal and multi-relational network of biomedical objects extracted from several heterogeneous datasets from the National Center for Biotechnology Information (NCBI). These objects include but are not limited to scientific papers, keywords, genes, proteins, diseases, and diagnoses. We model hypotheses using Latent Dirichlet Allocation applied on abstracts found near shortest paths discovered within this network, and demonstrate the effectiveness of MOLIERE by performing hypothesis generation on historical data. Our network, implementation, and resulting data are all publicly available for the broad scientific community

Accelerating COVID-19 research with graph mining and transformer-based learning

In 2020, the White House released the, "Call to Action to the Tech Community on New Machine Readable COVID-19 Dataset," wherein artificial intelligence experts are asked to collect data and develop text mining techniques that can help the science community answer high-priority scientific questions related to COVID-19. The Allen Institute for AI and collaborators announced the availability of a rapidly growing open dataset of publications, the COVID-19 Open Research Dataset (CORD-19). As the pace of research accelerates, biomedical scientists struggle to stay current. To expedite their investigations, scientists leverage hypothesis generation systems, which can automatically inspect published papers to discover novel implicit connections. We present an automated general purpose hypothesis generation systems AGATHA-C and AGATHA-GP for COVID-19 research. The systems are based on graph-mining and the transformer model. The systems are massively validated using retrospective information rediscovery and proactive analysis involving human-in-the-loop expert analysis. Both systems achieve high-quality predictions across domains (in some domains up to 0.97% ROC AUC) in fast computational time and are released to the broad scientific community to accelerate biomedical research. In addition, by performing the domain expert curated study, we show that the systems are able to discover on-going research findings such as the relationship between COVID-19 and oxytocin hormone

Application of endograft to treat thoracic aortic pathologies: A single center experience

PurposeTo evaluate our experience of thoracic endoluminal graft (ELG) repair of various thoracic aortic pathologies using a commercially available device approved by the Food and Drug Administration. Our patient population includes patients eligible for open surgical repair and those with prohibitive surgical risk.MethodsFrom March 1998 to March 2006, endovascular stent repair of the thoracic aorta was performed on 406 patients with 324 patients (median age 72; 200 male) receiving the Gore Excluder endograft. Patient demographics, procedural characteristics, complications, including endoleak, spinal cord ischemia, and mortality, were retrospectively reviewed during follow-up. All patients were followed with chest computer tomography at 6 months and yearly. Statistical analysis was performed utilizing the SPSS Windows 11.0 program. Logistic regression (univariate) analysis used to identify risk factors for paraplegia; analysis of variance (ANOVA) for endoleak distribution; and χ2 used to analyze variables. Survival analysis was done using SAS version 9.1 (SAS Institute, Cary, NC).ResultsThree hundred twenty-four patients were treated with Gore Excluder graft between March 1998 and March 2006. One hundred fifty-seven patients (48.5%) had atherosclerotic aneurysms, 82 (25.3%) had dissections type B (DTB), 34 (10.5%) had penetrating ulcers (PU), 26 (8.0%) with pseudoaneurysms (PSA), 11 (3.4%) had transections (MVAT), 9 (2.8%) aorto-bronchial fistulas (AoBF), 4 (1.2%) embolization, and 1 (0.3%) aorto-esophageal fistula (AoEF). Preoperative aneurysm sac size in TAA ranged from 5 to 12 centimeters, average size 6.3 cm. Sac shrinkage occurred in 65% (102 of 157) of patients. Average postoperative sac size of 5.4 cm in a mean follow-up of 20.4 months. One hundred cases (31.5%) were nonelective; 49 (15.1%) were ruptures. Overall complication was 22.7%, 14.2% (46) in elective cases and 8.5% (28) in nonelective cases. Paraplegia occurred in five (1.5%) patients and paresis in three (0.9%); two of the latter improved and one resolved completely prior to discharge. Incidence of paraplegia was statistically significant (P value < .05) with retroperitoneal approach, perioperative blood loss greater than 1000 cc, and aortic coverage greater than 40 cm. Early endoleaks included 18 (5.5%) type I, four (1.2%) type II, and two (0.6%) type III. Thirty-day mortality was 5.5% (18 related deaths, including three intraoperative deaths). A log rank test did not find statistical differences in actuarial survival with 30-day related mortality between TAA and other pathologies (P = .29) or between DTB and other pathologies (P = .97). Late mortality was 9.6% with 31 unrelated deaths. Follow-up ranged between 1 month and 70 months, average 17 months.ConclusionsEndoluminal grafting is a feasible alternative to open surgical repair for thoracic aortic pathologies. After more than 300 cases, 30-day morbidity and mortality compares favorably with open repair. Paraplegia remains low as a complication and increases in incidence with retroperitoneal approach, increased perioperative blood loss, and increased aortic coverage

Tissue inhibitor of metalloproteinase-1 (TIMP-1) regulates mesenchymal stem cells through let-7f microRNA and Wnt/β-catenin signaling

Tissue inhibitor of metalloproteinases 1 (TIMP-1) is a matrix metalloproteinase (MMP)-independent regulator of growth and apoptosis in various cell types. The receptors and signaling pathways that are involved in the growth factor activities of TIMP-1, however, remain controversial. RNA interference of TIMP-1 has revealed that endogenous TIMP-1 suppresses the proliferation, metabolic activity, and osteogenic differentiation capacity of human mesenchymal stem cells (hMSCs). The knockdown of TIMP-1 in hMSCs activated the Wnt/β-catenin signaling pathway as indicated by the increased stability and nuclear localization of β-catenin in TIMP-1–deficient hMSCs. Moreover, TIMP-1 knockdown cells exhibited enhanced β-catenin transcriptional activity, determined by Wnt/β-catenin target gene expression analysis and a luciferase-based β-catenin– activated reporter assay. An analysis of a mutant form of TIMP-1 that cannot inhibit MMP indicated that the effect of TIMP-1 on β-catenin signaling is MMP independent. Furthermore, the binding of CD63 to TIMP-1 on the surface of hMSCs is essential for the TIMP-1–mediated effects on Wnt/β-catenin signaling. An array analysis of microRNAs (miRNAs) and transfection studies with specific miRNA inhibitors and mimics showed that let-7f miRNA is crucial for the regulation of β-catenin activity and osteogenic differentiation by TIMP-1. Let-7f was up-regulated in TIMP-1–depleted hMSCs and demonstrably reduced axin 2, an antagonist of β-catenin stability. Our results demonstrate that TIMP-1 is a direct regulator of hMSC functions and reveal a regulatory network in which let-7f modulates Wnt/β-catenin activity

Two Novel Variants of the v-srcOncogene Isolated from Low and High Metastatic RSV-Transformed Hamster Cells

AbstractFour different transformed cell lines were isolated as a result of independent infection of primary hamster fibroblasts by Rous sarcoma virus (RSV SR-D stocks). These lines differ by the level of their spontaneous metastatic activity: HET-SR-1, HET-SR-8, and HET-SR-10 cell lines induced 70–200 metastatic nodules in the lung and/or lymph nodes of inoculated animals (high metastatic lines, HM). Metastatic activity was not identified after injection of HET-SR cells (low metastatic line, LM). All cell lines contained one copy of integrated and expressed intact RSV provirus. The difference in the amount of v-srcprotein in cell lines was not correlated with their metastatic potentialin vivo.Complete v-srcHM and v-srcLM genes were cloned from corresponding gene libraries and sequenced. In the unique region of both v-srcisoforms a GC-rich insert of 60 nucleotides (20 a.a.) was found. The presence of this insert explains the unusual apparent molecular weight of protein encoded by v-srcHM and v-srcLM: 62 kDa. Both genes had 10 identical amino acid changes when compared to the known RSV SR-D v-srcsequence. v-srcHM and v-srcLM differ by several amino acid changes. Most of them are localized in the unique domain and the extreme carboxy-terminal region of the oncoprotein. Both v-srcvariants and chimeric v-srcwith mutually substituted parts were subcloned in a retroviral vector and introduced into avian neuroretina cells. Significant differences in the morphology of transformed neuroretina cells were associated with the mutations in the carboxy-terminal region of the v-srconcogene. Low metastatic HET-SR cells transfected with v-srcHM and the chimeric gene v-src-LH remarkably increased their metastatic potential. In contrast, this effect was not observed when the same cells were transfected with v-srcLM and the chimeric v-srcHL gene. Specific changes in the distribution of fibronectin matrix typical for high metastatic cells were found in the lines transfected with v-srcHM