Automated sample annotation for diabetes mellitus in healthcare integrated biobanking.

Healthcare integrated biobanking describes the annotation and collection of residual samples from hospitalized patients for research purposes. The central idea of the current work is to establish an automated workflow for sample annotation, selection and storage for diabetes mellitus. This is challenging due to incomplete data at the time of sample selection.

Tailoring neurosurgical operating room education to medical undergraduates: Integrative review and meta-synthesis.

Introduction: Integrating medical students into the neurosurgical operating room (OR) presents significant pedagogical challenges, compounded by the phenomenon of neurophobia, or aversion to neuroscience. Despite the importance of early neurosurgical exposure, there is a lack of structured educational strategies for undergraduates.Research Question How can neurosurgical OR education be effectively tailored to address undergraduate medical students' educational needs and mitigate neurophobia?

Material And Methods: This study employs an integrative approach, combining narrative synthesis and critical interpretive synthesis (CIS).

Associations between white matter microstructure and cognitive decline in major depressive disorder versus controls in Germany: a prospective case-control cohort study.

Background: Cognitive deficits are a key source of disability in individuals with major depressive disorder (MDD) and worsen with disease progression. Despite their clinical relevance, the underlying mechanisms of cognitive deficits remain poorly elucidated, hampering effective treatment strategies. Emerging evidence suggests that alterations in white matter microstructure might contribute to cognitive dysfunction in MDD.

Functional dependence following intensive care unit-treated sepsis: three-year follow-up results from the prospective Mid-German Sepsis Cohort (MSC).

Background: Surviving sepsis can lead to chronic physical, psychological and cognitive impairments, which affect millions of patients worldwide, including survivors after COVID-19 viral sepsis. We aimed to characterize the magnitude and trajectory of functional dependence and new impairments post-sepsis.

Methods: We conducted a prospective cohort study including sepsis survivors who had been discharged from five German intensive care units (ICUs), until 36 months post-discharge.

Chromosome-level genome assembly of Tritrichomonas foetus, the causative agent of Bovine Trichomonosis.

Tritrichomonas foetus is a parasitic protist responsible for bovine trichomonosis, a reproductive disease associated with significant economic burden to the livestock industry throughout the world. Here, we present a chromosome-level reference genome of T. foetus -KV-1 (ATCC 30924) using short-read (Illumina Miseq), long-read (Oxford Nanopore) and chromatin-linked (Hi-C) sequencing.

Therapeutic Drug Monitoring of Long-Acting Rilpivirine and Cabotegravir for Treatment of HIV-1 Infection-A Case Series of Five Patients With One Virologic Failure After Development of Two-Class Resistance.

Virologic failure of long-acting rilpivirine/cabotegravir is rare but may result in severely limited treatment options. Known risk factors cannot predict all cases. Therapeutic drug monitoring (TDM) may help identify patients at risk, but reliable thresholds are missing.

Insight into the Internal Structure of High-Performance Multicore Magnetic Nanoparticles Used in Cancer Thermotherapy.

Multicore magnetic nanoparticles (MNPs), comprising iron oxide cores embedded in a sugar or starch matrix, are a class of nanomaterials with promising magnetic heating properties. Their internal structure, and particularly the strength of the internal core-core magnetic interactions, are believed to determine the functional properties, but there have been few detailed studies on this to date. We report here on an interlaboratory and multimodality transmission electron microscopy (TEM) and magnetic study of a high-performance MNP material (supplied by Resonant Circuits Limited, RCL) that is currently being used in a clinical study for the treatment of pancreatic cancer.

Application of transformer architectures in generative video modeling for neurosurgical education.

Purpose: This article explores the potential impact of OpenAI's Sora, a generative video modeling technology, on neurosurgical training. It evaluates how such technology could revolutionize the field by providing realistic surgical simulations, thereby enhancing the learning experience and proficiency in complex procedures for neurosurgical trainees.

Methods: The study examines the incorporation of this technology into neurosurgical education by leveraging transformer architecture and processing of video and image data.

Artificial intelligence-based quantification of pulmonary HRCT (AIqpHRCT) for the evaluation of interstitial lung disease in patients with inflammatory rheumatic diseases.

High-resolution computed tomography (HRCT) is important for diagnosing interstitial lung disease (ILD) in inflammatory rheumatic disease (IRD) patients. However, visual ILD assessment via HRCT often has high inter-reader variability. Artificial intelligence (AI)-based techniques for quantitative image analysis promise more accurate diagnostic and prognostic information.

Towards an understanding of physical activity-induced post-exertional malaise: Insights into microvascular alterations and immunometabolic interactions in post-COVID condition and myalgic encephalomyelitis/chronic fatigue syndrome.

Background: A considerable number of patients who contracted SARS-CoV-2 are affected by persistent multi-systemic symptoms, referred to as Post-COVID Condition (PCC). Post-exertional malaise (PEM) has been recognized as one of the most frequent manifestations of PCC and is a diagnostic criterion of myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS). Yet, its underlying pathomechanisms remain poorly elucidated.

Automatic personal identification using a single CT image.

Objectives: Computer vision (CV) mimics human vision, enabling computers to automatically compare radiological images from recent examinations with a large image database for unique identification, crucial in emergency scenarios involving unknown patients or deceased individuals. This study aims to extend a CV-based personal identification method from orthopantomograms (OPGs) to computed tomography (CT) examinations using single CT slices.

Methods: The study analyzed 819 cranial computed tomography (CCT) examinations from 722 individuals, focusing on single CT slices from six anatomical regions to explore their potential for CV-based personal identification in 69 procedures.

Significant decrease of osteoporosis and osteoporotic fractures in rheumatoid arthritis within a period of 24 years: experiences of a single centre.

Objectives: Rheumatoid arthritis (RA) is associated with an increased risk for osteoporosis and osteoporotic fractures. Since the treatment of RA has improved significantly in recent years, we can expect RA-associated osteoporosis to decrease with good disease control. Therefore, we conducted a retrospective study to investigate whether the frequency of osteoporosis and osteoporotic fractures has changed during 24 years in RA.

Unraveling the impact of therapeutic drug monitoring via machine learning for patients with sepsis.

Clinical studies investigating the benefits of beta-lactam therapeutic drug monitoring (TDM) among critically ill patients are hindered by small patient groups, variability between studies, patient heterogeneity, and inadequate use of TDM. Accordingly, definitive conclusions regarding the efficacy of TDM remain elusive. To address these challenges, we propose an innovative approach that leverages data-driven methods to unveil the concealed connections between therapy effectiveness and patient data, collected through a randomized controlled trial (DRKS00011159; 10th October 2016).

A synthetic peptide mimic kills Candida albicans and synergistically prevents infection.

More than two million people worldwide are affected by life-threatening, invasive fungal infections annually. Candida species are the most common cause of nosocomial, invasive fungal infections and are associated with mortality rates above 40%. Despite the increasing incidence of drug-resistance, the development of novel antifungal formulations has been limited.

Correlation of high-resolution computed tomography and immunological bronchoalveolar lavage in interstitial lung disease at the onset of inflammatory rheumatic diseases: implications for diagnosis and therapeutic strategies.

Objectives: Inflammatory rheumatic diseases (IRD) are often associated with interstitial lung disease (ILD). The aim of the present study was to establish a correlation between the findings on HRCT and the immunological bronchoalveolar lavage (BAL).

Methods: The study included 74 patients with newly diagnosed IRD and evidence of ILD on HRCT with the following pattern: ground-glass opacities (GGO), non-specific interstitial pneumonia (NSIP) and usual interstitial pneumonia (UIP).

Radiomics and visual analysis for predicting success of transplantation of heterotopic glioblastoma in mice with MRI.

Background: Quantifying tumor growth and treatment response noninvasively poses a challenge to all experimental tumor models. The aim of our study was, to assess the value of quantitative and visual examination and radiomic feature analysis of high-resolution MR images of heterotopic glioblastoma xenografts in mice to determine tumor cell proliferation (TCP).

Methods: Human glioblastoma cells were injected subcutaneously into both flanks of immunodeficient mice and followed up on a 3 T MR scanner.

The quorum-sensing molecule farnesol alters sphingolipid metabolism in human monocyte-derived dendritic cells.

an opportunistic fungal pathogen, produces the quorum-sensing molecule farnesol, which we have shown alters the transcriptional response and phenotype of human monocyte-derived dendritic cells (DCs), including their cytokine secretion and ability to prime T cells. This is partially dependent on the nuclear receptor peroxisome proliferator-activated receptor gamma (PPAR-γ), which has numerous ligands, including the sphingolipid metabolite sphingosine 1-phosphate. Sphingolipids are a vital component of membranes that affect membrane protein arrangement and phagocytosis of by DCs.