Surgical management of single-level thoracolumbar vertebral body segmentation and formation failure causing progressive thoracolumbar myelopathy in three adult large-breed dogs.

Objective: This study aimed to evaluate the medium-term outcome following spinal cord decompression and instrumented fixation of single-level congenital thoracolumbar vertebral malformations, characterized by combined failures of segmentation and formation, causing thoracolumbar myelopathy in three large-breed dogs.

Study Design: This was a retrospective clinical study.

Animals: The animals involved in the study were three large-breed dogs.

Frequency, sociodemographic, and neuropsychological features of patients with subjective cognitive decline diagnosed using different neuropsychological criteria.

Background: Subjective Cognitive Decline (SCD) is recognized as a risk stage for future cognitive impairment and dementia. The criteria for SCD include normal performance on neuropsychological testing; however, there is a lack of consensus regarding standard score cut-offs for neuropsychological tests to define cognitive impairment and to differentiate between SCD and Mild Cognitive Impairment (MCI). This study aimed to assess the frequency of SCD diagnosis using various neuropsychological definitions of cognitive normality and to characterize the sociodemographic and neuropsychological features of SCD patients diagnosed under these criteria.

Insights into macrolide resistance in Arcobacter butzleri: potential resistance mechanisms and impact on bacterial fitness and virulence.

Background: Macrolides are recommended for treating the emerging enteropathogen Arcobacter butzleri; nonetheless, this bacterium often exhibits highly variable resistance rates, and the mechanisms behind this resistance phenotype remain largely unexplored.

Objectives: To understand the phenotypic and genotypic consequences associated with the acquisition of erythromycin resistance in A. butzleri, as well as the effects on the fitness of this species.

Acceptors stability modulates the efficiency of post-translational protein N-glycosylation.

N-glycosylation is the most common protein modification in the eukaryotic secretory pathway. It involves the attachment a high mannose glycan to Asn residues in the context of Asn-X-Ser/Thr/Cys, a motif known as N-glycosylation sequon. This process is mediated by STT3A and STT3B, the catalytic subunits of the oligosaccharyltransferase complexes.

Unveiling ochratoxin A and ochratoxigenic fungi in Brazilian artisanal Cheeses: Insights from production to consumption.

Ochratoxin A (OTA) is a toxin produced by several Aspergillus species, mainly those belonging to section Circumdati and section Nigri. The presence of OTA in cheese has been reported recently in cave cheese in Italy. As artisanal cheese production in Brazil has increased, the aim of this study was to investigate the presence of ochratoxin A and related fungi in artisanal cheese consumed in Brazil.

Predicting alcohol relapse post-detoxification: The role of cognitive impairments in alcohol use disorder patients.

Background: Studies on early abstinence suggest that cognitive function is significantly reduced in the first year of abstinence, which raises the question of whether it is relevant to early relapse in patients with substance use disorders. This study investigates the extent to which impairments in executive function and memory predict alcohol relapse in patients with alcohol use disorder (AUD). Understanding these relationships is crucial for improving therapeutic approaches to prevent relapse in patients with AUD.

Is YouTube a reliable tool for approaching robotic assisted transabdominal preperitoneal surgery? A critical review of the available resources.

Introduction: The robotic transabdominal preperitoneal approach (rTAPP) is a relatively recent technique for the treatment of inguinal hernia. To achieve optimal results, the 10 golden rules described must be followed. Surgeons in training often review videos to familiarize themselves with new techniques, YouTube being one of the most used platforms.

Integrating Fluorescent Nanodiamonds into Polymeric Microstructures Fabricated by Two-Photon Polymerization.

Nitrogen-vacancy (NV) and other color centers in diamond have attracted much attention as non-photobleaching quantum emitters and quantum sensors. Since microfabrication in bulk diamonds is technically difficult, embedding nanodiamonds with color centers into designed structures is a way to integrate these quantum emitters into photonic devices. In this study, we demonstrate a method to incorporate fluorescent nanodiamonds into engineered microstructures using two-photon polymerization (2PP).

Health professionals' recommendations on the use of fluoride varnish for caries prevention in preschool children.

Background: Fluoride varnish (FV) is widely recommended for caries prevention in preschool children, despite its anticaries benefits being uncertain and modest. Dentists often report using clinical practice guidelines (CPGs) as a source of scientific information.

Aim: To identify and analyze recommendations for clinical practice on the use of FV for caries prevention in preschool children and to assess the methodological quality of the CPG on this topic.

DGH-GO: dissecting the genetic heterogeneity of complex diseases using gene ontology.

Background: Complex diseases such as neurodevelopmental disorders (NDDs) exhibit multiple etiologies. The multi-etiological nature of complex-diseases emerges from distinct but functionally similar group of genes. Different diseases sharing genes of such groups show related clinical outcomes that further restrict our understanding of disease mechanisms, thus, limiting the applications of personalized medicine approaches to complex genetic disorders.

K-RET: knowledgeable biomedical relation extraction system.

Motivation: Relation extraction (RE) is a crucial process to deal with the amount of text published daily, e.g. to find missing associations in a database.

RUNX1 Is Regulated by Androgen Receptor to Promote Cancer Stem Markers and Chemotherapy Resistance in Triple Negative Breast Cancer.

Triple negative breast cancer (TNBC) is an aggressive breast cancer subtype for which no effective targeted therapies are available. Growing evidence suggests that chemotherapy-resistant cancer cells with stem-like properties (CSC) may repopulate the tumor. The androgen receptor (AR) is expressed in up to 50% of TNBCs, and AR inhibition decreases CSC and tumor initiation.

Association of low-dose naltrexone and transcranial direct current stimulation in fibromyalgia: a randomized, double-blinded, parallel clinical trial.

Introduction: Fibromyalgia is a complex, generalized, and diffuse chronic musculoskeletal pain. Pharmacological approaches are widely used to relieve pain and increase quality of life. Low-Dose Naltrexone (LDN) was shown to increase the nociceptive threshold in patients with fibromyalgia.

SeEn: Sequential enriched datasets for sequence-aware recommendations.

The recommendation of items based on the sequential past users' preferences has evolved in the last few years, mostly due to deep learning approaches, such as BERT4Rec. However, in scientific fields, recommender systems for recommending the next best item are not widely used. The main goal of this work is to improve the results for the recommendation of the next best item in scientific domains using sequence aware datasets and algorithms.

NILINKER: Attention-based approach to NIL Entity Linking.

The existence of unlinkable (NIL) entities is a major hurdle affecting the performance of Named Entity Linking approaches, and, consequently, the performance of downstream models that depend on them. Existing approaches to deal with NIL entities focus mainly on clustering and prediction and are limited to general entities. However, other domains, such as the biomedical sciences, are also prone to the existence of NIL entities, given the growing nature of scientific literature.

Biomedical Relation Extraction With Knowledge Graph-Based Recommendations.

Biomedical Relation Extraction (RE) systems identify and classify relations between biomedical entities to enhance our knowledge of biological and medical processes. Most state-of-the-art systems use deep learning approaches, mainly to target relations between entities of the same type, such as proteins or pharmacological substances. However, these systems are mostly restricted to what they directly identify on the text and ignore specialized domain knowledge bases, such as ontologies, that formalize and integrate biomedical information typically structured as direct acyclic graphs.

Prediction of Prostate Cancer Disease Aggressiveness Using Bi-Parametric Mri Radiomics.

Prostate cancer is one of the most prevalent cancers in the male population. Its diagnosis and classification rely on unspecific measures such as PSA levels and DRE, followed by biopsy, where an aggressiveness level is assigned in the form of Gleason Score. Efforts have been made in the past to use radiomics coupled with machine learning to predict prostate cancer aggressiveness from clinical images, showing promising results.

Text Mining for Building Biomedical Networks Using Cancer as a Case Study.

In the assembly of biological networks it is important to provide reliable interactions in an effort to have the most possible accurate representation of real-life systems. Commonly, the data used to build a network comes from diverse high-throughput essays, however most of the interaction data is available through scientific literature. This has become a challenge with the notable increase in scientific literature being published, as it is hard for human curators to track all recent discoveries without using efficient tools to help them identify these interactions in an automatic way.

COVID-19 recommender system based on an annotated multilingual corpus.

Tracking the most recent advances in Coronavirus disease 2019 (COVID-19)-related research is essential, given the disease's novelty and its impact on society. However, with the publication pace speeding up, researchers and clinicians require automatic approaches to keep up with the incoming information regarding this disease. A solution to this problem requires the development of text mining pipelines; the efficiency of which strongly depends on the availability of curated corpora.

Information Retrieval Using Machine Learning for Biomarker Curation in the Exposome-Explorer.

In 2016, the International Agency for Research on Cancer, part of the World Health Organization, released the Exposome-Explorer, the first database dedicated to biomarkers of exposure for environmental risk factors for diseases. The database contents resulted from a manual literature search that yielded over 8,500 citations, but only a small fraction of these publications were used in the final database. Manually curating a database is time-consuming and requires domain expertise to gather relevant data scattered throughout millions of articles.

Sickle cell disease children's gut colonization by extended-spectrum β-lactamase (ESBL)-producing : an antibiotic prophylaxis effect?

Sickle cell disease (SCD) children have a high susceptibility to pneumococcal infection. For this reason, they are routinely immunized with pneumococcal vaccines and use antibiotic prophylaxis (AP). Yet, little is known about SCD children's gut microbiota.

Embolization of renal tumor bone metastasis: case report.

Primary or secondary bone tumors can manifest in different ways, from simple bone pain to possible pathological fractures. Hypervascularized tumors are of greatest concern, with increased incidence of complications. Preoperative embolization of the bone tumor is an effective measure for reducing blood loss during open surgery to excise the tumor.

Hybrid semantic recommender system for chemical compounds in large-scale datasets.

The large, and increasing, number of chemical compounds poses challenges to the exploration of such datasets. In this work, we propose the usage of recommender systems to identify compounds of interest to scientific researchers. Our approach consists of a hybrid recommender model suitable for implicit feedback datasets and focused on retrieving a ranked list according to the relevance of the items.

Validation and Screening Capacity of the European Portuguese Version of the SUNFRAIL Tool for Community-Dwelling Older Adults.

Unlabelled: Early detection of frailty may prevent or delay adverse health outcomes in community-dwelling older adults. In Portugal, there are currently no valid multidimensional frailty screening tools. SUNFRAIL is a user-friendly multidimensional tool for frailty screening that can be used in primary care.