Cluster-Based BERTopic Modeling on Swedish COVID-19 Vaccine Posts.

This paper explores the prevalent themes across multiple threads on the popular Swedish discussion forum Flashback. Among its diverse array of topics, the forum actively engages users in addressing and debating questions pertaining to COVID-19 vaccines and vaccination. Through distinguishing between positive and negative perspectives within posts across 14 relevant thread discussions, we employ BERTopic, a modular topic modeling framework, which utilizes pre-trained language models and applies clustering techniques to identify prevailing topics.

The Prevalence of mRNA Related Discussions During the Post-COVID-19 Era.

Vaccinations are one of the most significant interventions to public health, but vaccine hesitancy and skepticism are raising serious concerns for a portion of the population in many countries, including Sweden. In this study, we use Swedish social media data and structural topic modeling to automatically identify mRNA-vaccine related discussion themes and gain deeper insights into how people's refusal or acceptance of the mRNA technology affects vaccine uptake. Our point of departure is a scientific study published in February 2022, which seems to once again sparked further suspicion and concern and highlight the necessity to focus on issues about the nature and trustworthiness in vaccine safety.

Using a Discourse Task to Explore Semantic Ability in Persons With Cognitive Impairment.

This paper uses a discourse task to explore aspects of semantic production in persons with various degree of cognitive impairment and healthy controls. The purpose of the study was to test if an in-depth semantic analysis of a cognitive-linguistic challenging discourse task could differentiate persons with a cognitive decline from those with a stable cognitive impairment. Both quantitative measures of semantic ability, using tests of oral lexical retrieval, and qualitative analysis of a narrative were used to detect semantic difficulties.

Voice quality and speech fluency distinguish individuals with Mild Cognitive Impairment from Healthy Controls.

Mild Cognitive Impairment (MCI) is a syndrome characterized by cognitive decline greater than expected for an individual's age and education level. This study aims to determine whether voice quality and speech fluency distinguish patients with MCI from healthy individuals to improve diagnosis of patients with MCI. We analyzed recordings of the Cookie Theft picture description task produced by 26 patients with MCI and 29 healthy controls from Sweden and calculated measures of voice quality and speech fluency.

Predicting MCI Status From Multimodal Language Data Using Cascaded Classifiers.

Recent work has indicated the potential utility of automated language analysis for the detection of mild cognitive impairment (MCI). Most studies combining language processing and machine learning for the prediction of MCI focus on a single language task; here, we consider a cascaded approach to combine data from multiple language tasks. A cohort of 26 MCI participants and 29 healthy controls completed three language tasks: picture description, reading silently, and reading aloud.

Total Methionine Restriction Treatment of Cancer.

This chapter reviews how total methionine (MET) restriction (MR) of a human brain tumor xenograft, effected by the combination of recombinant L-methionine-α-deamino-γ-lyase (rMETase) and a MET-free diet, greatly potentiates standard chemotherapy for brain tumors in mouse models. The growth of human brain tumor Daoy, SWB77, and D-54 xenografts in nude mice was arrested after the depletion of mouse plasma methionine (MET) with a combination of an MR diet and rMETase and homocysteine to rescue normal cells and tissues. MET was depleted to below 5 μm by this treatment.

Identification of Mild Cognitive Impairment From Speech in Swedish Using Deep Sequential Neural Networks.

While people with mild cognitive impairment (MCI) portray noticeably incipient memory difficulty in remembering events and situations along with problems in decision making, planning, and finding their way in familiar environments, detailed neuropsychological assessments also indicate deficits in language performance. To this day, there is no cure for dementia but early-stage treatment can delay the progression of MCI; thus, the development of valid tools for identifying early cognitive changes is of great importance. In this study, we provide an automated machine learning method, using Deep Neural Network Architectures, that aims to identify MCI.

Automated Syntactic Analysis of Language Abilities in Persons with Mild and Subjective Cognitive Impairment.

In this work we analyze the syntactic complexity of transcribed Swedish-language picture descriptions using a variety of automated syntactic features, and investigate the features' predictive power in classifying narratives from people with subjective and mild cognitive impairment and healthy controls. Our results indicate that while there are no statistically significant differences, syntactic features can still be moderately successful at distinguishing the participant groups when used in a machine learning framework.

Readability, suitability and comprehensibility in patient education materials for Swedish patients with colorectal cancer undergoing elective surgery: a mixed method design.

Objective: To characterize education materials provided to patients undergoing colorectal cancer surgery to gain a better understanding of how to design readable, suitable, comprehensible materials.

Method: Mixed method design. Deductive quantitative analysis using a validated suitability and comprehensibility assessment instrument (SAM+CAM) was applied to patient education materials from 27 Swedish hospitals, supplemented by language technology analysis and deductive and inductive analysis of data from focus groups involving 15 former patients.

Medication extraction and guessing in Swedish, French and English.

Extraction of information related to the medication is an important task within the biomedical area. Our method is applied to different types of documents in three languages. The results indicate that our approach can efficiently update and enrich the existing drug vocabularies.

Semantic relations of binary compounds annotated with SNOMED CT.

The objective of this paper is to investigate whether a meaningful interpretation can be easily assigned to compound medical terms that have been assigned two distinct concepts taken from one of the most comprehensive, clinical healthcare terminologies, the (Swedish) SNOMED CT®. A binary compound term is a union of two terms to construct a complex term of special meaning that is quickly conveyed by not using separated (multiword) terms but rather solid or closed ones (not separated by space or hyphen). This is a case when the vocabulary lacks a single code for such concept; at the same time, solid compounds is the norm for expressing compounds in Germanic languages, such as Swedish.

Characteristics of Finnish and Swedish intensive care nursing narratives: a comparative analysis to support the development of clinical language technologies.

Background: Free text is helpful for entering information into electronic health records, but reusing it is a challenge. The need for language technology for processing Finnish and Swedish healthcare text is therefore evident; however, Finnish and Swedish are linguistically very dissimilar. In this paper we present a comparison of characteristics in Finnish and Swedish free-text nursing narratives from intensive care.

What is the coverage of SNOMED CT®on scientific medical corpora?

This paper reports on the results of a large scale mapping of SNOMED CT on scientific medical corpora. The aim is to automatically access the validity, reliability and coverage of the Swedish SNOMED-CT translation, the largest, most extensive available resource of medical terminology. The method described here is based on the generation of predominantly safe harbor term variants which together with simple linguistic processing and the already available SNOMED term content are mapped to large corpora.

Semantic relation mining of solid compounds in medical corpora.

In the context of scientific and technical texts, meaning is usually embedded in noun compounds and the semantic interpretation of these compounds deals with the detection and semantic classification of the relation that holds between the compound's constituents. Semantic relation mining, the technology applied for marking up, interpreting, extracting and classifying relations that hold between pairs of words, is an important enterprise that contribute to deeper means of enhancing document understanding technologies, such as Information Extraction, Question Answering, Summarization, Paraphrasing, Ontology Building and Textual Entailment. This paper explores the application of assigning semantic descriptors taken from a multilingual medical thesaurus to a large sample of solid (closed form) compounds taken from large Swedish medical corpora, and determining the relation(s) that may hold between the compound constituents.

Mitotic arrest, apoptosis, and sensitization to chemotherapy of melanomas by methionine deprivation stress.

Methionine deprivation stress (MDS) eliminates mitotic activity in melanoma cells regardless of stage, grade, or TP53 status, whereas it has a negligible effect on normal skin fibroblasts. In most cases, apoptosis accounts for the elimination of up to 90% of tumor cells from the culture within 72 hours after MDS, leaving a scattered population of multinucleated resistant cells. Loss of mitosis in tumor cells is associated with marked reduction of cyclin-dependent kinase (CDK) 1 transcription and/or loss of its active form (CDK1-P-Thr(161)), which is coincident with up-regulation of CDKN1A, CDKN1B, and CDKN1C (p21, p27, and p57).

Aberrant Wnt/beta-catenin signaling in pancreatic adenocarcinoma.

Wnt/beta-catenin signaling plays an important role in normal development. However, its aberrant activation is associated with several cancers. The aim of this study is to examine the Wnt/beta-catenin pathway in patients with advanced pancreatic adenocarcinoma (n = 31).

Methionine-stress: a pleiotropic approach in enhancing the efficacy of chemotherapy.

Malignant cells fail to utilize homocysteine (HCYS) in place of methionine (MET) and they are dependent on exogenous MET for growth. In animals, reduction of plasma MET to <5 microM can be induced by combined dietary restriction of MET and administration of L-methionine-alpha-deamino-gamma-lyase (methioninase). This treatment, termed as MET-stress, inhibits the growth of brain tumor xenografts in athymic mice and enhances the efficacy of DNA alkylating chemotherapeutic agents.

CSR1 suppresses tumor growth and metastasis of prostate cancer.

Prostate cancer is frequent among men over 45 years of age, but it generally only becomes lethal with metastasis. In this study, we identified a gene called cellular stress response 1 (CSR1) that was frequently down-regulated and methylated in prostate cancer samples. Survival analysis indicated that methylation of the CSR1 promoter, and to a lesser extent down-regulation of CSR1 protein expression, was associated with a high rate of prostate cancer metastasis.

Modulation of cell cycle and gene expression in pancreatic tumor cell lines by methionine deprivation (methionine stress): implications to the therapy of pancreatic adenocarcinoma.

The effect of methionine deprivation (methionine stress) on the proliferation, survival, resistance to chemotherapy, and regulation of gene and protein expression in pancreatic tumor lines is examined. Methionine stress prevents successful mitosis and promotes cell cycle arrest and accumulation of cells with multiple micronuclei with decondensed chromatin. Inhibition of mitosis correlates with CDK1 down-regulation and/or inhibition of its function by Tyr(15) phosphorylation or Thr(161) dephosphorylation.

Physiology and gene expression characteristics of carcinogen-initiated and tumor-transformed glial progenitor cells derived from the CNS of methylnitrosourea (MNU)-treated Sprague-Dawley rats.

Glial progenitors from the brain of normal adult Sprague-Dawley rats were compared to their initiated and malignant counterparts that were isolated from apparently normal brains of animals exposed to methylnitrosourea (MNU). Fibroblast growth factor-2 (FGF-2) or platelet-derived growth factor (PDGF)-A or -B induced differentiation of normal progenitors to a pro-astrocytic or oligodendrocytic morphology, respectively, whereas the combination of these factors resulted in their terminal differentiation to oligodendrocytes and senescence. In contrast, initiated progenitors did not exit the cell cycle when stimulated with PDGF and/or FGF-2.

Modulation of gene expression in human central nervous system tumors under methionine deprivation-induced stress.

Methionine deprivation imposes a metabolic stress, termed methionine stress, that inhibits mitosis and induces cell cycle arrest and apoptosis. The methionine-dependent central nervous system tumor cell lines DAOY (medulloblastoma), SWB61 (anaplastic oligodendroglioma), SWB40 (anaplastic astrocytoma), and SWB39 (glioblastoma multiforme) were compared with methionine-stress resistant SWB77 (glioblastoma multiforme). The cDNA-oligoarray analysis and reverse transcription-PCR verification indicated common changes in gene expression in methionine-dependent cell lines to include up-regulation/induction of cyclin D1, mitotic arrest deficient (MAD)1, p21, growth arrest and DNA-damage-inducible (GADD)45 alpha, GADD45 gamma, GADD34, breast cancer (BRCA)1, 14-3-3sigma, B-cell CLL/lymphoma (BCL)1, transforming growth factor (TGF)-beta, TGF-beta-induced early response (TIEG), SMAD5, SMAD7, SMAD2, insulin-like growth factor binding protein (IGFBP7), IGF-R2, vascular endothelial growth factor (VEGF), TNF-related apoptosis-inducing ligand (TRAIL), TNF-alpha converting enzyme (TACE), TRAIL receptor (TRAIL-R)2, TNFR-related death receptor (DR)6, TRAF interacting protein (I-TRAF), IL-6, MDA7, IL-1B convertase (ICE)-gamma, delta and epsilon, IRF1, IRF5, IRF7, interferon (IFN)-gamma and receptor components, ISG15, p65-NF-kappaB, JUN-B, positive cofactor (PC)4, C/ERB-beta, inositol triphosphate receptor I, and methionine adenosyltransferase II.

High throughput screening of methylation status of genes in prostate cancer using an oligonucleotide methylation array.

Recent work using high-throughput microarray technology has discovered altered expression of a large number of genes in prostate cancer. Many of these alterations may be the consequence of changes in methylation status in the CpG islands of promoter or exon 1 regions of these genes. In order to determine the methylation status of a large number of genes and ESTs we combined the principle of match/mismatch hybridization with the technique of whole genome labeling to develop a highly specific oligonucleotide-based methylation microarray.