Publications by authors named "Kammer M"

Background: Lung cancer is the leading cause of cancer death worldwide, with poor survival despite recent therapeutic advances. A better understanding of the complexity of the tumor microenvironment is needed to improve patients' outcome.

Methods: We applied a computational immunology approach (involving immune cell proportion estimation by deconvolution, transcription factor activity inference, pathways and immune scores estimations) in order to characterize bulk transcriptomics of 62 primary lung adenocarcinoma (LUAD) samples from patients across disease stages.

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Introduction: Diabetic kidney disease (DKD) is a common cause of chronic kidney disease with around 25-40% of patients with diabetes being affected. The course of DKD is variable, and estimated glomerular filtration rate (eGFR) and albuminuria, the currently used clinical markers, are not able to accurately predict the individual disease trajectory, in particular in early stages of the disease. The aim of this study was to assess the association of urine levels of selected protein biomarkers with the progression of DKD at an early stage of disease.

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Background: The response to severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) vaccination is severely impaired in patients on maintenance immunosuppression after kidney transplantation.

Methods: We conducted a prospective cohort study of 194 kidney transplant recipients (KTR) who exhibited no response to SARS-CoV-2 vaccinations (i.e.

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Background: Measurement of tumor markers from peripheral venous blood is an emerging tool to assist in the early diagnosis of lung cancer. Samples from the pulmonary artery and pulmonary artery wedge position (trans-pulmonary samples) are accessible via right-heart catheterization and, by virtue of their proximity to lung tumors, may increase diagnostic yield.

Case Presentation: We report a case of a 64 year-old woman from whom trans-pulmonary samples were obtained and who was diagnosed 16 months later with recurrent metastatic small cell lung cancer.

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Background: Radiomics has shown promise in improving malignancy risk stratification of indeterminate pulmonary nodules (IPNs) with many platforms available, but with no head-to-head comparisons. This study aimed to evaluate transportability of radiomic models across platforms by comparing performances of a commercial radiomic feature extractor (HealthMyne) with an open-source extractor (PyRadiomics) on diagnosis of lung cancer in IPNs.

Methods: A commercial radiomic feature extractor was used to segment IPNs from computed tomography (CT) scans, and a previously validated radiomic model based on commercial features was used as baseline (ComRad).

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Article Synopsis
  • Lung cancer remains the leading cause of cancer deaths globally, highlighting the need for better understanding of its early development stages to enable timely interventions.
  • An international team of scientists identified knowledge gaps in how premalignant lung lesions progress to lung cancer and developed research questions to fill these gaps and guide future investigations.
  • Addressing these gaps is crucial for improving screening and early detection methods, which could lead to innovative strategies that effectively reduce lung cancer incidence and enhance patient outcomes.
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Background: Induction of donor-specific tolerance is a promising approach to achieve long-term graft patency in transplantation with little to no maintenance immunosuppression. Changes to the recipient's T cell receptor (TCR) repertoire are understood to play a pivotal role in the establishment of a robust state of tolerance in chimerism-based transplantation protocols.

Methods: We investigated changes to the TCR repertoires of patients participating in an ongoing prospective, controlled, phase I/IIa trial designed to evaluate the safety and efficacy of combination cell therapy in living donor kidney transplantation.

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Objective: The results of this study describe the relationship between the body condition of dairy cows and selected metabolic parameters during the peri- and post-partum period with special consideration of 3 local dairy cow breed in Upper Bavaria and the Allgau.

Material And Methods: Three local dairy cattle breeds (Swiss Brown (BV), Simmental (FL), Holstein Friesian (HF)) were examined on 68 farms in southern Germany for 7 consecutive weeks. In dry cows as well as lactating cows (5.

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The accuracy of predictive models for solitary pulmonary nodule (SPN) diagnosis can be greatly increased by incorporating repeat imaging and medical context, such as electronic health records (EHRs). However, clinically routine modalities such as imaging and diagnostic codes can be asynchronous and irregularly sampled over different time scales which are obstacles to longitudinal multimodal learning. In this work, we propose a transformer-based multimodal strategy to integrate repeat imaging with longitudinal clinical signatures from routinely collected EHRs for SPN classification.

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Article Synopsis
  • Pulmonary nodules can be challenging to assess, leading to delays in diagnosing cancer and unnecessary tests for non-cancerous conditions.
  • This study evaluated the effectiveness of prediction models for assessing the likelihood of malignancy in nodules referred for biopsy, specifically using a cohort of 322 cases.
  • The results indicated that commonly used models (Brock, Mayo Clinic, and VA) had limited accuracy, while the Herder model showed better performance when PET-CT scans were included, suggesting a need for improved diagnostic tools in this area.
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Background: We recently found that epiplakin 1 (EPPK1) alterations were present in 12% of lung adenocarcinoma (LUAD) cases and were associated with a poor prognosis in early-stage LUAD when combined with other molecular alterations. This study aimed to identify a probable crucial role for EPPK1 in cancer development.

Methods: EPPK1 mRNA and protein expression was analyzed with clinical variables.

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Background: Assessing the clinical utility of biomarkers is a critical step before clinical implementation. The reclassification of patients across clinically relevant subgroups is considered one of the best methods to estimate clinical utility. However, there are important limitations with this methodology.

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Lameness in dairy cows poses a significant challenge to improving animal well-being and optimizing economic efficiency in the dairy industry. To address this, employing automated animal surveillance for early lameness detection and prevention through activity sensors proves to be a promising strategy. In this study, we analyzed activity (accelerometer) data and additional cow-individual and farm-related data from a longitudinal study involving 4860 Holstein dairy cows on six farms in Germany during 2015-2016.

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Objective: The aim of the present study was to investigate relationships between elevated haptoglobin concentrations in milk and clinical as well as laboratory parameters in early lactating dairy cows. Furthermore, cut-off values should be identified for the differentiation of healthy and affected animals.

Material And Methods: 1462 dairy cows between 5.

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Placental membranes have been widely studied and used clinically for wound care applications, but there is limited published information on the benefits of using the chorion membrane. The chorion membrane represents a promising source of placental-derived tissue to support wound healing, with its native composition of extracellular matrix (ECM) proteins and key regulatory proteins. This study examined the impact of hypothermic storage on the structure of chorion membrane, ECM content, and response to degradation in vitro.

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Lung adenocarcinoma (LUAD) is the predominant type of lung cancer in the U.S. and exhibits a broad variety of behaviors ranging from indolent to aggressive.

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The implementation of low-dose chest CT for lung screening presents a crucial opportunity to advance lung cancer care through early detection and interception. In addition, millions of pulmonary nodules are incidentally detected annually in the United States, increasing the opportunity for early lung cancer diagnosis. Yet, realization of the full potential of these opportunities is dependent on the ability to accurately analyze image data for purposes of nodule classification and early lung cancer characterization.

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Article Synopsis
  • - Lung adenocarcinoma (LUAD) is a common and aggressive form of lung cancer, with its recurrence risk poorly understood, leading researchers to explore the role of immune response in tumor growth as a factor affecting patient outcomes.
  • - The study analyzed immune cell density in tumors from 100 LUAD patients (stages I and II), using advanced techniques to assess T-cell and mast cell presence in relation to recurrence-free survival (RFS).
  • - Findings indicate that higher densities of T-cells and mast cells in tumors are associated with significantly reduced recurrence risk, emphasizing the potential role of the immune environment in cancer prognosis, though further research is needed due to the small sample size.
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Unlabelled: Lung adenocarcinoma (LUAD) is a heterogeneous group of tumors associated with different survival rates, even when detected at an early stage. Here, we aim to investigate the biological determinants of early LUAD indolence or aggressiveness using radiomics as a surrogate of behavior. We present a set of 92 patients with LUAD with data collected across different methodologies.

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Background: Kidney transplantation is the preferred treatment for eligible patients with kidney failure who need renal replacement therapy. However, it remains unclear whether the anticipated survival benefit from kidney transplantation is different for women and men.

Methods: We included all dialysis patients recorded in the Austrian Dialysis and Transplant Registry who were waitlisted for their first kidney transplant between 2000 and 2018.

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Lung cancer is the leading cause of cancer-related deaths. Early detection and diagnosis are critical, as survival decreases with advanced stages. Approximately 1.

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Article Synopsis
  • A study evaluated a deep learning model (LCP CNN) for assessing indeterminate pulmonary nodules (IPNs), finding it outperformed traditional clinical models but only used data from a single timepoint.
  • Researchers analyzed changes in LCP CNN scores over time to see if they differed between benign and malignant nodules, using a specific study design that involved multiple CT scans and blinded assessments.
  • Results showed that while benign nodules had stable LCP CNN scores, malignant nodules exhibited increasing scores over time, indicating that longitudinal analysis may enhance predictions of lung cancer risk.
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