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.

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.

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).

Constructing knowledge: the role of AI in medical learning.

The integration of large language models (LLMs) like ChatGPT into medical education presents potential benefits and challenges. These technologies, aligned with constructivist learning theories, could potentially enhance critical thinking and problem-solving through inquiry-based learning environments. However, the actual impact on educational outcomes and the effectiveness of these tools in fostering learning require further empirical study.

Resurgence of common respiratory viruses in patients with community-acquired pneumonia (CAP)-A prospective multicenter study.

Background: Community-acquired pneumonia (CAP) is a major global cause of death and hospitalization. Bacteria or community-acquired viruses (CARVs) cause CAP. COVID-19 associated restrictions effectively reduced the circulation of CARVs.

Assessing the efficacy of large language models in spinal health information dissemination.

•Examines AI's role in spinal health education.•Stresses multidisciplinary AI evaluations.•Advocates for stringent AI healthcare regulations.

Machine Translation for Multilingual Cancer Patient Education: Bridging Languages, Navigating Challenges.

This commentary evaluates the use of machine translation for multilingual patienteducation in oncology. It critically examines the balance between technologicalbenefits in language accessibility and the potential for increasing healthcare disparities.The analysis emphasizes the need for a multidisciplinary approach to translation thatincorporates linguistic accuracy, medical clarity, and cultural relevance.

The gastrointestinal microbiota in the development of ME/CFS: a critical view and potential perspectives.

Like other infections, a SARS-CoV-2 infection can also trigger Post-Acute Infection Syndromes (PAIS), which often progress into myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS). ME/CFS, characterized by post-exercise malaise (PEM), is a severe multisystemic disease for which specific diagnostic markers or therapeutic concepts have not been established. Despite numerous indications of post-infectious neurological, immunological, endocrinal, and metabolic deviations, the exact causes and pathophysiology remain unclear.

Revitalizing neurosurgical frontiers: The EANS frontiers in neurosurgery committee's strategic framework.

Introduction: The field of neurosurgery faces challenges with the increasing involvement of other medical specialties in areas traditionally led by neurosurgeons. This paper examines the implications of this development for neurosurgical practice and patient care, with a focus on specialized areas like pain management, peripheral nerve surgery, and stereotactic radiosurgery.

Research Question: To assess the implications of the expanded scope of other specialties for neurosurgical practice and to consider the response of the EANS Frontiers in Neurosurgery Committee to these challenges.

Definition of the Post-COVID syndrome using a symptom-based Post-COVID score in a prospective, multi-center, cross-sectoral cohort of the German National Pandemic Cohort Network (NAPKON).

Purpose: The objective examination of the Post-COVID syndrome (PCS) remains difficult due to heterogeneous definitions and clinical phenotypes. The aim of the study was to verify the functionality and correlates of a recently developed PCS score.

Methods: The PCS score was applied to the prospective, multi-center cross-sectoral cohort (in- and outpatients with SARS-CoV-2 infection) of the "National Pandemic Cohort Network (NAPKON, Germany)".