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Background/objectivesTo examine the association between white matter hyperintensities (WMH) and cognitive domains such as memory and executive function (EF) across different clinical and biomarker categories of Alzheimer's disease (AD).DesignCross-sectional study.SettingAlzheimer's Disease Neuroimaging Initiative.ParticipantsA total of 216 cognitively normal (CN) participants and 407 participants with mild cognitive impairment (MCI) from the Alzheimer's Disease Neuroimaging Initiative (ADNI) at baseline.MeasurementsBased on the 2018 research framework, participants were classified using AT(N) (amyloid-β deposition [A], pathologic tau [T], and neurodegeneration [(N)]) biomarkers into one of three categories: biomarker negative [A - T- (N)-], amyloid negative but other biomarker positive [A - T ± (N)+ or A - T + (N)±] or amyloid positive [A + T ± (N)±]. Linear regression models were then used to examine the association between WMH and memory composite scores and EF composite scores.ResultsHigher WMH burden was associated with worse EF in both CN and MCI subgroups while a significant association between WMH and memory was only found in the MCI subgroup. Furthermore, WMH was associated with EF in the group with A - T ± (N)+ or A - T + (N)± biomarker category, but not for A - T - (N)- (normal biomarker) and A + T ± (N) ± (AD pathology). The association between higher WMH and worse memory was independent of amyloid levels in individuals with MCI with evidence of AD pathology.ConclusionVascular disease, as indexed by WMH, independent of AD pathology affects cognitive function in both CN and MCI subgroups. Future studies using the AT(N) research framework should consider white matter lesions as a key biomarker contributing to the clinical presentation of AD.

Breast cancers enduring treatment with chemotherapy may be enriched for cancer stem cells or tumor-initiating cells, which have an enhanced capacity for self-renewal, tumor initiation, and/or metastasis. Breast cancer cells that express the type I tyrosine kinaselike orphan receptor ROR1 also may have such features. Here we find that the expression of ROR1 increased in breast cancer cells following treatment with chemotherapy, which also enhanced expression of genes induced by the activation of Rho-GTPases, Hippo-YAP/TAZ, or B lymphoma Mo-MLV insertion region 1 homolog (BMI1). Expression of ROR1 also enhanced the capacity of breast cancer cells to invade Matrigel, form spheroids, engraft in Rag2-/-[Formula: see text] mice, or survive treatment with paclitaxel. Treatment of mice bearing breast cancer patient-derived xenografts (PDXs) with the humanized anti-ROR1 monoclonal antibody cirmtuzumab repressed expression of genes associated with breast cancer stemness, reduced activation of Rho-GTPases, Hippo-YAP/TAZ, or BMI1, and impaired the capacity of breast cancer PDXs to metastasize or reengraft Rag2-/-[Formula: see text] mice. Finally, treatment of PDX-bearing mice with cirmtuzumab and paclitaxel was more effective than treatment with either alone in eradicating breast cancer PDXs. These results indicate that targeting ROR1 may improve the response to chemotherapy of patients with breast cancer.

ROR1 is a conserved oncoembryonic surface protein expressed in breast cancer. Here we report that ROR1 associates with cortactin in primary breast-cancer cells or in MCF7 transfected to express ROR1. Wnt5a also induced ROR1-dependent tyrosine phosphorylation of cortactin (Y421), which recruited ARHGEF1 to activate RhoA and promote breast-cancer-cell migration; such effects could be inhibited by cirmtuzumab, a humanized mAb specific for ROR1. Furthermore, treatment of mice bearing breast-cancer xenograft with cirmtuzumab inhibited cortactin phosphorylation in vivo and impaired metastatic development. We established that the proline at 841 of ROR1 was required for it to recruit cortactin and ARHGEF1, activate RhoA, and enhance breast-cancer-cell migration in vitro or development of metastases in vivo. Collectively, these studies demonstrate that the interaction of ROR1 with cortactin plays an important role in breast-cancer-cell migration and metastasis.

This study presents a landslide susceptibility map using an artificial intelligence (AI) approach that is based on standards set by the INSPIRE framework. We show how INSPIRE standards enhance the interoperability of geospatial data, and enable deeper knowledge development for their interpretation and explainability in AI applications. INSPIRE is a European Union Spatial Data Infrastructure (SDI) initiative to standardize spatial data across borders to ensure interoperability for management of cross-border infrastructure and environmental issues. Despite the theoretical effectiveness of the SDI, very few real-world applications make use of INSPIRE standards. We designed an ontology of landslides, embedded with INSPIRE vocabularies and then aligned geology, stream network and land cover data sets covering the Veneto region of Italy to the standards. INSPIRE was formally extended to include an extensive landslide type code list, a landslide size code list and the concept of landslide susceptibility to describe map application inputs and outputs. Using the terms in the ontology, we defined conceptual scientific models of slopes likely to generate landslides as well as map polygons representing real slopes. Both landslide models and map polygons were encoded as semantic networks and, by qualitative probabilistic comparison between the two, a similarity score was assigned. The score was then used as a proxy for landslide susceptibility and displayed in web map application. The use of INSPIRE-standardized vocabularies in ontologies that express scientific models promotes the adoption of the standards across the European Union and beyond. Further, this application facilitates the explainability of the generated results. We conclude that public and private organisations, within and outside the European Union, can enhance the value of their data by bringing them into INSPIRE-compliance for use in AI applications. [ABSTRACT FROM AUTHOR]