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Biliary tract cancers (BTC) are a highly heterogeneous group of cancers at the genomic, epigenetic and molecular levels. The vast majority of patients initially present at an advanced (unresectable) disease stage due to a lack of symptoms and an aggressive tumour biology. Chemotherapy has been the mainstay of treatment in patients with advanced BTC but the survival outcomes and prognosis remain poor. The addition of immune checkpoint inhibitors (ICI) to chemotherapy have shown only a marginal benefit over chemotherapy alone due to the complex tumour immune microenvironment of these cancers. This review appraises our current understanding of the immune landscape of advanced BTC, including emerging transcriptome-based classifications, highlighting the mechanisms of immune evasion and resistance to ICI and their therapeutic implications. It describes the shifting treatment paradigm from traditional chemotherapy to immunotherapy combinations as well as the potential biomarkers for predicting response to ICI.

Abstract Immunity to previously encountered viruses can alter response to unrelated pathogens. We reasoned that similar mechanism may also involve SARS-CoV-2 and thereby affect the specificity and the quality of the immune response against the virus. Here, we employed high-throughput next generation phage display method to explore the link between antibody immune response to previously encountered antigens and spike (S) glycoprotein. By profiling the antibody response in COVID-19 naïve individuals with a diverse clinical history (including cardiovascular, neurological, or oncological diseases), we identified 15 highly antigenic epitopes on spike protein that showed cross-reactivity with antigens of seasonal, persistent, latent or chronic infections from common human viruses. We observed varying degrees of cross-reactivity of different viral antigens with S in an epitope-specific manner. The data show that pre-existing SARS-CoV-2 S1 and S2 cross-reactive serum antibody is readily detectable in pre-pandemic cohort. In the severe COVID-19 cases, we found differential antibody response to the 15 defined antigenic and cross-reactive epitopes on spike. We also noted that despite the high mutation rates of Omicron (B.1.1.529) variants of SARS-CoV-2, some of the epitopes overlapped with the described mutations. Finally, we propose that the resolved epitopes on spike if targeted by re-called antibody response from SARS-CoV-2 infections or vaccinations can function in chronically ill COVID-19 naïve/unvaccinated individuals as immunogenic targets to boost antibodies augmenting the chronic conditions. Understanding the relationships between prior antigen exposure at the antibody epitope level and the immune response to subsequent infections with viruses from a different strain is paramount to guiding strategies to exit the COVID-19 pandemic.

Brain-derived neurotrophic factor (BDNF) promotes the survival and functioning of neurons in the central nervous system and contributes to proper functioning of many non-neural tissues. Although the regulation and role of BDNF have been extensively studied, a rigorous analysis of the expression dynamics of BDNF and its receptors TrkB and p75NTR is lacking. Here, we have analyzed more than 3,600 samples from 18 published RNA sequencing datasets, and used over 17,000 samples from GTEx, and ~ 180 samples from BrainSpan database, to describe the expression of BDNF in the developing mammalian neural and non-neural tissues. We show evolutionarily conserved dynamics and expression patterns of BDNF mRNA and non-conserved alternative 5′ exon usage. Finally, we also show increasing BDNF protein levels during murine brain development and BDNF protein expression in several non-neural tissues. In parallel, we describe the spatiotemporal expression pattern of BDNF receptors TrkB and p75NTR in both murines and humans. Collectively, our in-depth analysis of the expression of BDNF and its receptors gives insight into the regulation and signaling of BDNF in the whole organism throughout life.

Biliary tract cancers (BTC) are a highly heterogeneous group of cancers at the genomic, epigenetic and molecular levels. The vast majority of patients initially present at an advanced (unresectable) disease stage due to a lack of symptoms and an aggressive tumour biology. Chemotherapy has been the mainstay of treatment in patients with advanced BTC but the survival outcomes and prognosis remain poor. The addition of immune checkpoint inhibitors (ICI) to chemotherapy have shown only a marginal benefit over chemotherapy alone due to the complex tumour immune microenvironment of these cancers. This review appraises our current understanding of the immune landscape of advanced BTC, including emerging transcriptome-based classifications, highlighting the mechanisms of immune evasion and resistance to ICI and their therapeutic implications. It describes the shifting treatment paradigm from traditional chemotherapy to immunotherapy combinations as well as the potential biomarkers for predicting response to ICI. [ABSTRACT FROM AUTHOR]

Rähni et al profile antibody response in patients with varied response to cancer immunotherapies. They identify antibody epitope responses that predict anti-cancer immunity elicited by immunotherapy.

This study finds that antibodies against antigens present in oral biofilm are potential biomarkers of acute coronary syndrome (ACS), the most severe form of coronary artery disease. By testing antibody response to periodontal pathogens, the authors find that patients with ACS have little or no immune response to a particular antigen epitope.

The ELEMENTerial research project focuses on the development of an innovative design and construction system for Cross-Laminated Timber (CLT) offcuts. CLT construction, while offering advantages for automation, raises concerns about offcut waste, which constitute 5-10% of the material production in Estonian CLT timber industry. This research highlights the importance of aligning timber construction with circular economy principles by effectively utilising offcuts. The study focuses on the development of a design method, creating a versatile and holistic construction system that breaks away from traditional orthogonal designs. Algorithmic tools are employed to streamline the design process and to help manage the complexities of working with smaller elements. The outcomes include a geometric strategy, offering variable configurations for assembly in walls, floors, ceilings and openings. The research demonstrates the potential to automate and pre-rationalise the design process, providing design freedom beyond orthogonal constraints and shell structures. The applications range from shelters to facade systems, building extensions to potentially largescale construction systems. This study offers environmental benefits and design flexibility in the construction industry. It holds a potential to guide the sector towards reduced waste and increased material efficiency, fostering sustainability and economic value from waste materials. The prospects for future research include further automation, refinement of connection details, and efficiency in production and material usage. [ABSTRACT FROM AUTHOR]

Multiple FGFR inhibitors have demonstrated significant activity in pretreated advanced FGFR2 fusion–positive intrahepatic cholangiocarcinoma. The irreversible pan-FGFR inhibitor futibatinib has the potential to overcome acquired resistance to ATP-competitive FGFR inhibitors in a subset of patients. We present a case of prolonged clinical benefit using FGFR inhibitors sequentially, initially an ATP-competitive inhibitor followed by futibatinib upon progression, for a total of 36 months of FGFR-targeting therapy. This case supports sequential FGFR-targeting therapies for FGFR2 fusion–positive cholangiocarcinoma, with futibatinib acting as rescue therapy after failure of ATP-competitive inhibitors. [ABSTRACT FROM AUTHOR]

Background: Neuropathological findings support an autoimmune etiology as an underlying factor for loss of orexin-producing neurons in spontaneous narcolepsy type 1 (narcolepsy with cataplexy; sNT1) as well as in Pandemrix influenza vaccine-induced narcolepsy type 1 (Pdmx-NT1). The precise molecular target or antigens for the immune response have, however, remained elusive. Methods: Here we have performed a comprehensive antigenic repertoire analysis of sera using the next-generation phage display method - mimotope variation analysis (MVA). Samples from 64 children and adolescents were analyzed: 10 with Pdmx-NT1, 6 with sNT1, 16 Pandemrix-vaccinated, 16 H1N1 infected, and 16 unvaccinated healthy individuals. The diagnosis of NT1 was defined by the American Academy of Sleep Medicine international criteria of sleep disorders v3. Findings: Our data showed that although the immunoprofiles toward vaccination were generally similar in study groups, there were also striking differences in immunoprofiles between sNT1 and Pdmx-NT1 groups as compared with controls. Prominent immune response was observed to a peptide epitope derived from prostaglandin D2 receptor (DP1), as well as peptides homologous to B cell lymphoma 6 protein. Further validation confirmed that these can act as true antigenic targets in discriminating NT1 diseased along with a novel epitope of hemagglutinin of H1N1 to delineate exposure to H1N1. Interpretation: We propose that DP1 is a novel molecular target of autoimmune response and presents a potential diagnostic biomarker for NT1. DP1 is involved in the regulation of non-rapid eye movement (NREM) sleep and thus alterations in its functions could contribute to the disturbed sleep regulation in NT1 that warrants further studies. Together our results also show that MVA is a helpful method for finding novel peptide antigens to classify human autoimmune diseases, possibly facilitating the design of better therapies. Keywords: Narcolepsy type 1, H1N1, Pandemrix, Antibody, Prostaglandin, DP1

The Nordic Geodetic Commission (NKG) has launched a joint NKG GNSS Analysis Centre that aims to routinely produce high qualityGNSS solutions for the common needs of the NKG and the Nordic and Baltic countries. A consistent and densified velocity field is needed for the constraining of the gla-cial isostatic adjustment (GIA) modelling that is a key component of maintaining the national reference frame realisations in the area. We described the methods of the NKG GNSS Analysis Centre including the defined processing setup for the local analysis centres (LAC) and for the combination centres.We analysed the results of the first 2.5 years (2014.5-2016). The results showed that different subnets were consistent with the combined solution within 1-2 mm level. We observed the so called network effect affecting our reference frame alignment. However, the accuracy of the reference frame alignment was on a few millimetre level in the area of the main interest (Nordic and Baltic Countries). TheNKGGNSS AC was declared fully operational in April 2017.

In the manuscript, the issue of detecting and segmenting out pavement defects on highway roads is addressed. Specifically, computer vision (CV) methods are developed and applied to the problem based on deep learning of convolutional neural networks (ConvNets). A novel neural network structure is considered, based on a pipeline of three ConvNets and endowed with the capacity for context awareness, which improves grid-based search for defects on orthoframes by considering the surrounding image content—an approach, which essentially draws inspiration from how humans tend to solve the task of image segmentation. Also, methods for assessing the quality of segmentation are discussed. The contribution also describes the complete procedure of working with pavement defects in an industrial setting, involving the workcycle of defect annotation, ConvNet training and validation. The results of ConvNet evaluation provided in the paper hint at a successful implementation of the proposed technique.