Datalähtöinen lähestymistapa satelliittien valintaan globaaleissa satelliittipaikannusjärjestelmissä

The main goal of this work was to develop an algorithm for multi-constellation GNSS receivers that would select satellites out of the tracked ones to be used in the location solution. As the receiver has very limited computational resources, the complexity of the algorithm needed to be kept low. The work began by exploratory analysis of GNSS data. This analysis gave insight into the differences of the various satellite navigation systems as well as into the nature of the pseudorange residuals. These observations helped in shaping the algorithm that we proposed for the problem of satellite selection. The algorithm itself was developed using data science techniques to filter out bad pseudorange measurements and borrowed some earlier ideas to optimize the geometric dilution of precision of the solution set as well. The approach we chose was shown to work very well when applied to real data measured from road tests in varying surroundings. Even with practically non-existent parameter tuning the algorithm was able to spot almost 90% of the bad pseudorange measurements, keeping the specificity, i.e., ability to hold on to the good measurements at over 90% level. The ability to filter out bad pseudorange measurements translated to improved location accuracy as well. All in all, the results achieved in this work proved encouraging enough to begin implementing the algorithm in actual receiver software to study the performance of the data-driven approach in action

Datalähtöinen lähestymistapa satelliittien valintaan globaaleissa satelliittipaikannusjärjestelmissä

The main goal of this work was to develop an algorithm for multi-constellation GNSS receivers that would select satellites out of the tracked ones to be used in the location solution. As the receiver has very limited computational resources, the complexity of the algorithm needed to be kept low. The work began by exploratory analysis of GNSS data. This analysis gave insight into the differences of the various satellite navigation systems as well as into the nature of the pseudorange residuals. These observations helped in shaping the algorithm that we proposed for the problem of satellite selection. The algorithm itself was developed using data science techniques to filter out bad pseudorange measurements and borrowed some earlier ideas to optimize the geometric dilution of precision of the solution set as well. The approach we chose was shown to work very well when applied to real data measured from road tests in varying surroundings. Even with practically non-existent parameter tuning the algorithm was able to spot almost 90% of the bad pseudorange measurements, keeping the specificity, i.e., ability to hold on to the good measurements at over 90% level. The ability to filter out bad pseudorange measurements translated to improved location accuracy as well. All in all, the results achieved in this work proved encouraging enough to begin implementing the algorithm in actual receiver software to study the performance of the data-driven approach in action

A novel mechanism of action of HER2 targeted immunotherapy is explained by inhibition of NRF2 function in ovarian cancer cells

Nuclear erythroid related factor-2 (NRF2) is known to promote cancer therapeutic detoxification and crosstalk with growth promoting pathways. HER2 receptor tyrosine kinase is frequently overexpressed in cancers leading to uncontrolled receptor activation and signaling. A combination of HER2 targeting monoclonal antibodies shows greater anticancer efficacy than the single targeting antibodies, however, its mechanism of action is largely unclear. Here we report novel actions of anti-HER2 drugs, Trastuzumab and Pertuzumab, involving NRF2. HER2 targeting by antibodies inhibited growth in association with persistent generation of reactive oxygen species (ROS), glutathione (GSH) depletion, reduction in NRF2 levels and inhibition of NRF2 function in ovarian cancer cell lines. The combination of antibodies produced more potent effects than single alone; downregulated NRF2 substrates by repressing the Antioxidant Response (AR) pathway with concomitant transcriptional inhibition of NRF2. We showed the antibody combination produced increased methylation at the NRF2 promoter consistent with repression of NRF2 antioxidant function, as HDAC and methylation inhibitors reversed such produced transcriptional effects. These findings demonstrate a novel mechanism and role for NRF2 in mediating the response of cancer cells to the combination of Trastuzumab and Pertuzumab and reinforce the importance of NRF2 in drug resistance and as a key anticancer target

Systems analysis of drug-induced receptor tyrosine kinase reprogramming following targeted mono- and combination anti-cancer therapy

The receptor tyrosine kinases (RTKs) are key drivers of cancer progression and targets for drug therapy. A major challenge in anti-RTK treatment is the dependence of drug effectiveness on co-expression of multiple RTKs which defines resistance to single drug therapy. Reprogramming of the RTK network leading to alteration in RTK co-expression in response to drug intervention is a dynamic mechanism of acquired resistance to single drug therapy in many cancers. One route to overcome this resistance is combination therapy. We describe the results of a joint in silico, in vitro, and in vivo investigations on the efficacy of trastuzumab, pertuzumab and their combination to target the HER2 receptors. Computational modelling revealed that these two drugs alone and in combination differentially suppressed RTK network activation depending on RTK co-expression. Analyses of mRNA expression in SKOV3 ovarian tumour xenograft showed up-regulation of HER3 following treatment. Considering this in a computational model revealed that HER3 up-regulation reprograms RTK kinetics from HER2 homodimerisation to HER3/HER2 heterodimerisation. The results showed synergy of the trastuzumab and pertuzumab combination treatment of the HER2 overexpressing tumour can be due to an independence of the combination effect on HER3/HER2 composition when it changes due to drug-induced RTK reprogramming

Whole exome sequencing study identifies novel rare and common Alzheimer's-Associated variants involved in immune response and transcriptional regulation

Correction: Volume: 25 Issue: 8 Pages: 1901-1903 DOI: 10.1038/s41380-019-0529-7The Alzheimer's Disease Sequencing Project (ADSP) undertook whole exome sequencing in 5,740 late-onset Alzheimer disease (AD) cases and 5,096 cognitively normal controls primarily of European ancestry (EA), among whom 218 cases and 177 controls were Caribbean Hispanic (CH). An age-, sex- andAPOEbased risk score and family history were used to select cases most likely to harbor novel AD risk variants and controls least likely to develop AD by age 85 years. We tested ~1.5 million single nucleotide variants (SNVs) and 50,000 insertion-deletion polymorphisms (indels) for association to AD, using multiple models considering individual variants as well as gene-based tests aggregating rare, predicted functional, and loss of function variants. Sixteen single variants and 19 genes that met criteria for significant or suggestive associations after multiple-testing correction were evaluated for replication in four independent samples; three with whole exome sequencing (2,778 cases, 7,262 controls) and one with genome-wide genotyping imputed to the Haplotype Reference Consortium panel (9,343 cases, 11,527 controls). The top findings in the discovery sample were also followed-up in the ADSP whole-genome sequenced family-based dataset (197 members of 42 EA families and 501 members of 157 CH families). We identified novel and predicted functional genetic variants in genes previously associated with AD. We also detected associations in three novel genes:IGHG3(p = 9.8 x 10(-7)), an immunoglobulin gene whose antibodies interact with beta-amyloid, a long non-coding RNAAC099552.4(p = 1.2 x 10(-7)), and a zinc-finger proteinZNF655(gene-based p = 5.0 x 10(-6)). The latter two suggest an important role for transcriptional regulation in AD pathogenesis.Peer reviewe

Characterising the loss-of-function impact of 5' untranslated region variants in 15,708 individuals

Upstream open reading frames (uORFs) are tissue-specific cis-regulators of protein translation. Isolated reports have shown that variants that create or disrupt uORFs can cause disease. Here, in a systematic genome-wide study using 15,708 whole genome sequences, we show that variants that create new upstream start codons, and variants disrupting stop sites of existing uORFs, are under strong negative selection. This selection signal is significantly stronger for variants arising upstream of genes intolerant to loss-of-function variants. Furthermore, variants creating uORFs that overlap the coding sequence show signals of selection equivalent to coding missense variants. Finally, we identify specific genes where modification of uORFs likely represents an important disease mechanism, and report a novel uORF frameshift variant upstream of NF2 in neurofibromatosis. Our results highlight uORF-perturbing variants as an under-recognised functional class that contribute to penetrant human disease, and demonstrate the power of large-scale population sequencing data in studying non-coding variant classes. Upstream open reading frames (uORFs), located in 5' untranslated regions, are regulators of downstream protein translation. Here, Whiffin et al. use the genomes of 15,708 individuals in the Genome Aggregation Database (gnomAD) to systematically assess the deleteriousness of variants creating or disrupting uORFs.Peer reviewe

Brain amyloid load and its associations with cognition and vascular risk factors in FINGER study

To investigate brain amyloid pathology in a dementia-risk population defined as cardiovascular risk factors, aging, and dementia risk (CAIDE) score of at least 6 but with normal cognition and to examine associations between brain amyloid load and cognitive performance and vascular risk factors. Twenty participants (42%) had a positive PiB-PET on visual analysis. The PiB-positive group performed worse in executive functioning tests, included more participants with APOE ε4 allele (50%), and showed slightly better glucose homeostasis compared to PiB-negative participants. PiB-positive and -negative participants did not differ significantly in other cognitive domain scores or other vascular risk factors. There was no significant difference in Fazekas score between the PiB groups. A subgroup of 48 individuals from the Finnish Geriatric Intervention Study to Prevent Cognitive Impairment and Disability (FINGER) main study participated in brain 11C-Pittsburgh compound B (PiB)-PET imaging, brain MRI, and neuropsychological assessment at the beginning of the study. Lifestyle/vascular risk factors were determined as body mass index, blood pressure, total and low-density lipoprotein cholesterol, and glucose homeostasis model assessment. White matter lesions were visually rated from MRIs by a semiquantitative Fazekas score. The high percentage of PiB-positive participants provides evidence of a successful recruitment process of the at-risk population in the main FINGER intervention trial. The results suggest a possible association between early brain amyloid accumulation and decline in executive functions. APOE ε4 was clearly associated with amyloid positivity, but no other risk factor was found to be associated with positive PiB-PET. OBJECTIVE RESULTS METHODS CONCLUSION