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Highlights
• Artificial intelligence systems for mechanically ventilated patients are increasing.
• The clinical and financial impact of these models are often unexamined.
• We developed a generic health-economic model for artificial intelligence systems.
• This model assesses the cost-effectiveness for many different scenarios.
• The developed framework is easily adjustable to other (clinical) situations.
Abstract
Purpose: The health and economic consequences of artificial intelligence (AI) systems for mechanically ventilated intensive care unit patients often remain unstudied. Early health technology assessments (HTA) can examine the potential impact of AI systems by using available data and simulations. Therefore, we developed a generic health-economic model suitable for early HTA of AI systems for mechanically ventilated patients.
Materials and methods: Our generic health-economic model simulates mechanically ventilated patients from their hospitalisation until their death. The model simulates two scenarios, care as usual and care with the AI system, and compares these scenarios to estimate their cost-effectiveness.
Results: The generic health-economic model we developed is suitable for estimating the cost-effectiveness of various AI systems. By varying input parameters and assumptions, the model can examine the cost-effectiveness of AI systems across a wide range of different clinical settings.
Conclusions: Using the proposed generic health-economic model, investors and innovators can easily assess whether implementing a certain AI system is likely to be cost-effective before an exact clinical impact is determined. The results of the early HTA can aid investors and innovators in deployment of AI systems by supporting development decisions, informing value-based pricing, clinical trial design, and selection of target patient groups.
Understanding the underlying mechanisms that link psychopathology and physical comorbidities in schizophrenia is crucial since decreased physical fitness and overweight pose major risk factors for cardio-vascular diseases and decrease the patients’ life expectancies. We hypothesize that altered reward anticipation plays an important role in this. We implemented the Monetary Incentive Delay task in a MR scanner and a fitness test battery to compare schizophrenia patients (SZ, n = 43) with sex- and age-matched healthy controls (HC, n = 36) as to reward processing and their physical fitness. We found differences in reward anticipation between SZs and HCs, whereby increased activity in HCs positively correlated with overall physical condition and negatively correlated with psychopathology. On the other handy, SZs revealed stronger activity in the posterior cingulate cortex and in cerebellar regions during reward anticipation, which could be linked to decreased overall physical fitness. These findings demonstrate that a dysregulated reward system is not only responsible for the symptomatology of schizophrenia, but might also be involved in physical comorbidities which could pave the way for future lifestyle therapy interventions.
We provide in this paper a comprehensive comparison of various transfer learning strategies and deep learning architectures for computer-aided classification of adult-type diffuse gliomas. We evaluate the generalizability of out-of-domain ImageNet representations for a target domain of histopathological images, and study the impact of in-domain adaptation using self-supervised and multi-task learning approaches for pretraining the models using the medium-to-large scale datasets of histopathological images. A semi-supervised learning approach is furthermore proposed, where the fine-tuned models are utilized to predict the labels of unannotated regions of the whole slide images (WSI). The models are subsequently retrained using the ground-truth labels and weak labels determined in the previous step, providing superior performance in comparison to standard in-domain transfer learning with balanced accuracy of 96.91% and F1-score 97.07%, and minimizing the pathologist's efforts for annotation. Finally, we provide a visualization tool working at WSI level which generates heatmaps that highlight tumor areas; thus, providing insights to pathologists concerning the most informative parts of the WSI.
MicroRNAs (miRNAs) are critical post-transcriptional regulators in many biological processes. They act by guiding RNA-induced silencing complexes to miRNA response elements (MREs) in target mRNAs, inducing translational inhibition and/or mRNA degradation. Functional MREs are expected to predominantly occur in the 3’ untranslated region and involve perfect base-pairing of the miRNA seed. Here, we generate a high-resolution map of miR-181a/b-1 (miR-181) MREs to define the targeting rules of miR-181 in developing murine T-cells. By combining a multi-omics approach with computational high-resolution analyses, we uncover novel miR-181 targets and demonstrate that miR-181 acts predominantly through RNA destabilization. Importantly, we discover an alternative seed match and identify a distinct set of targets with repeat elements in the coding sequence which are targeted by miR-181 and mediate translational inhibition. In conclusion, deep profiling of MREs in primary cells is critical to expand physiologically relevant targetomes and establish context-dependent miRNA targeting rules.
Key Points:
* Deep profiling identifies novel targets of miR-181 associated with global gene regulation.
* miR-181 MREs in repeat elements in the coding sequence act through translational inhibition.
* High-resolution analysis reveals an alternative seed match in functional MREs.
Highlights
• Deletion of SPPL3 promotes resistance of malignant B cells to NK cell cytotoxicity
• Loss of SPPL3 blocks ligand binding to NK receptors via increased N-glycosylation
• B3GNT2 deletion reduces LacNAc addition and restores SPPL3-KO cell sensitivity to NK cells
• SPPL3-deficient cells are enriched in tetra-antennary N-glycans with LacNAc elongations
Summary
Natural killer (NK) cells are primary defenders against cancer precursors, but cancer cells can persist by evading immune surveillance. To investigate the genetic mechanisms underlying this evasion, we perform a genome-wide CRISPR screen using B lymphoblastoid cells. SPPL3, a peptidase that cleaves glycosyltransferases in the Golgi, emerges as a top hit facilitating evasion from NK cytotoxicity. SPPL3-deleted cells accumulate glycosyltransferases and complex N-glycans, disrupting not only binding of ligands to NK receptors but also binding of rituximab, a CD20 antibody approved for treating B cell cancers. Notably, inhibiting N-glycan maturation restores receptor binding and sensitivity to NK cells. A secondary CRISPR screen in SPPL3-deficient cells identifies B3GNT2, a transferase-mediating poly-LacNAc extension, as crucial for resistance. Mass spectrometry confirms enrichment of N-glycans bearing poly-LacNAc upon SPPL3 loss. Collectively, our study shows the essential role of SPPL3 and poly-LacNAc in cancer immune evasion, suggesting a promising target for cancer treatment.
PET probes targeting fibroblasts are frequently used for varying applications in oncology. In recent years, the clinical spectrum has been expanded towards cardiovascular medicine, e.g., after myocardial infarction, in aortic stenosis or as a non-invasive read-out of atherosclerosis. We herein provide a brief overview of the current status of this PET radiotracer in the context of cardiovascular disease, including translational and clinical evidence. In addition, we will also briefly discuss future applications, e.g., the use of fibroblast-targeting PET to investigate bilateral organ function along the cardiorenal axis.
Lifestyle factors—such as diet, physical activity (PA), smoking, and alcohol consumption—have a significant impact on mortality as well as healthcare costs. Moreover, they play a crucial role in the development of type 2 diabetes mellitus (DM2). There also seems to be a link between lifestyle behaviours and insulin resistance, which is often a precursor of DM2. This study uses an enhanced Healthy Living Index (HLI) integrating accelerometric data and an Ecological Momentary Assessment (EMA) to explore differences in lifestyle between insulin-sensitive (IS) and insulin-resistant (IR) individuals. Moreover, it explores the association between lifestyle behaviours and inflammation. Analysing data from 99 participants of the mPRIME study (57 women and 42 men; mean age 49.8 years), we calculated HLI scores—ranging from 0 to 4— based on adherence to specific low-risk lifestyle behaviours, including non-smoking, adhering to a healthy diet, maximally moderate alcohol consumption, and meeting World Health Organization (WHO) PA guidelines. Insulin sensitivity was assessed using a Homeostatic Model Assessment of Insulin Resistance (HOMA-IR) and C-reactive protein (CRP) levels were used as a proxy for inflammation. Lifestyle behaviours, represented by HLI scores, were significantly different between IS and IR individuals (U = 1529.0; p = 0.023). The difference in the HLI score between IR and IS individuals was mainly driven by lower adherence to PA recommendations in the IR group. Moreover, reduced PA was linked to increased CRP levels in the IR group (r = −0.368, p = 0.014). Our findings suggest that enhancing PA, especially among individuals with impaired insulin resistance, holds significant promise as a preventive strategy.
The ICH M13A draft bioequivalence guideline allows the exclusion of very low plasma profiles from the statistical evaluation in exceptional cases, i.e., if such phenomenon occurs due to non-compliance of subjects (not swallowing the product). Moreover, the draft ICH guideline requests additional bioequivalence studies for medicinal products with pH-dependent solubility after concomitant administration of gastric pH modifying preparations, e.g., proton pump inhibitors. Both regulations are scientifically sound, however, would need further specification. Main problem in this context is that compounds with very low solubility and slow intrinsic dissolution in the intestinal environment will cause significant bioavailability problems if their solid oral dosage forms are emptied from the stomach undisintegrated. Also very low plasma profiles may result under these circumstances. Such cases can occur accidentally and are not resultant of non-compliance. Thus, limitation for one case per study only as suggested in the guideline is not justified.
• Mexican and German populations of L. sericata differ in their development times.
• Mexican L. sericata had a shorter development time at 20°C than German flies.
• At 30 °C, German L. sericata pupariated and eclosed earlier than the Mexican flies.
• Differences in study design make the comparison of developmental studies difficult.
Abstract
The cosmopolitan blow fly Lucilia sericata is often used in forensic case work for estimating the minimum postmortem interval (PMImin). For this, the age of immature specimens developing on the dead body is calculated by measuring the time taken to reach the sampled developmental stage at a given temperature. To test whether regional developmental data of L. sericata is valid on a global scale, the time taken to reach different developmental stages was compared between a population from Mexico and one from Germany at two different constant temperatures.
The German population of L. sericata was collected in Frankfurt/Main, while the Mexican population originated near Oaxaca de Juarez and was transported to Germany in the larval stage. Only the F1 generation was used to avoid adaption of the Mexican flies. Eggs were immediately placed at 20 °C and 30 °C. Five times 30 freshly eclosed larvae per replicate (n = 5) were then transferred to a cup of minced meat in separate containers. The larvae were checked every 8 h for migration, pupariation or emergence of adult flies. The time at which the first individual and 50 % of the specimens per container entered each of these stages, was recorded.
Significant differences in the time of development between the two populations were observed at both temperatures. At 20 °C, the first specimens of the Mexican population reached all developmental stages a little (< 1 day to < 2 days) earlier than the German L. sericata. At 30 °C, the Mexican flies also reached the post-feeding stage slightly earlier (0.2 days). However, at 30 °C, the German flies started pupariation significantly earlier (after 5 days) than the Mexican flies (6.9 days) and the adults from Germany also emerged earlier (10.5 days compared to 13.1 days). The same pattern was observed when looking at 50 % of the total number of specimens per container. A comparison with previously published developmental studies was difficult as the experimental design varied widely between studies. However, the results were within the range of most studies. Our study has shown that age estimation can vary widely depending on the population on which the reference data used for the calculations are based. This highlights the importance of using local and population-specific developmental data for estimating the age of blow flies in case work.