DrugExBERT for Pharmacovigilance – A Novel Approach for Detecting Drug Experiences from User-Generated Content

Pharmaceutical companies have to maintain drug safety through pharmacovigilance systems by monitoring various sources of information about adverse drug experiences. Recently, user-generated content (UGC) has emerged as a valuable source of real-world drug experiences, posing new challenges due to its high volume and variety. We present DrugExBERT, a novel approach to extract adverse drug experiences (adverse reaction, lack of effect) and supportive drug experiences (effectiveness, intervention, indication, and off-label use) from UGC. To be able to verify the extracted drug experiences, DrugExBERT additionally provides explications in the form of UGC phrases that were critical for the extraction. In our evaluation, we demonstrate that DrugExBERT outperforms state-of-the-art pharmacovigilance approaches as well as ChatGPT on several performance measures and that DrugExBERT is data- and drug-agnostic. Thus, our novel approach can help pharmaceutical companies meet their legal obligations and ethical responsibility while ensuring patient safety and monitoring drug effectiveness

Measurement of cerebral oxygen pressure in living mice by two-photon phosphorescence lifetime microscopy

The ability to quantify partial pressure of oxygen (pO2) is of primary importance for studies of metabolic processes in health and disease. Here, we present a protocol for imaging of oxygen distributions in tissue and vasculature of the cerebral cortex of anesthetized and awake mice. We describe in vivo two-photon phosphorescence lifetime microscopy (2PLM) of oxygen using the probe Oxyphor 2P. This minimally invasive protocol outperforms existing approaches in terms of accuracy, resolution, and imaging depth

Altered hemodynamics and vascular reactivity in a mouse model with severe pericyte deficiency

Pericytes are the mural cells of the microvascular network that are in close contact with underlying endothelial cells. Endothelial-secreted PDGFB leads to recruitment of pericytes to the vessel wall, but this is disrupted in Pdgfb$^{ret/ret}$ mice when the PDGFB retention motif is deleted. This results in severely reduced pericyte coverage on blood vessels. In this study, we investigated vascular abnormalities and hemodynamics in Pdgfb$^{ret/ret}$ mice throughout the cerebrovascular network and in different cortical layers by in vivo two-photon microscopy. We confirmed that Pdgfb$^{ret/ret}$ mice are severely deficient in pericytes throughout the vascular network, with enlarged brain blood vessels and a reduced number of vessel branches. Red blood cell velocity, linear density, and tube hematocrit were reduced in Pdgfb$^{ret/ret}$ mice, which may impair oxygen delivery to the tissue. We also measured intravascular PO$_{2}$ and found that concentrations were higher in cortical Layer 2/3 in Pdgfb$^{ret/ret}$ mice, indicative of reduced blood oxygen extraction. Finally, we found that Pdgfb$^{ret/ret}$ mice had a reduced capacity for vasodilation in response to an acetazolamide challenge during functional MRI imaging. Taken together, these results suggest that severe pericyte deficiency can lead to vascular abnormalities and altered cerebral blood flow, reminiscent of pathologies such as arteriovenous malformations

Oxyphor 2P: A High-Performance Probe for Deep-Tissue Longitudinal Oxygen Imaging

Quantitative imaging of oxygen distributions in tissue can provide invaluable information about metabolism in normal and diseased states. Two-photon phosphorescence lifetime microscopy (2PLM) has been developed to perform measurements of oxygen in vivo with micron-scale resolution in 3D; however, the method’s potential has not yet been fully realized due to the limitations of current phosphorescent probe technology. Here, we report a new sensor, Oxyphor 2P, that enables oxygen microscopy twice as deep (up to 600 μm below the tissue surface) and with ∼60 times higher speed than previously possible. Oxyphor 2P allows longitudinal oxygen measurements without having to inject the probe directly into the imaged region. As proof of principle, we monitored oxygen dynamics for days following micro-stroke induced by occlusion of a single capillary in the mouse brain. Oxyphor 2P opens up new possibilities for studies of tissue metabolic states using 2PLM in a wide range of biomedical research areas

Learning-Augmented Query Policies for Minimum Spanning Tree with Uncertainty

We study how to utilize (possibly erroneous) predictions in a model for computing under uncertainty in which an algorithm can query unknown data. Our aim is to minimize the number of queries needed to solve the minimum spanning tree problem, a fundamental combinatorial optimization problem that has been central also to the research area of explorable uncertainty. For all integral γ≥2, we present algorithms that are γ-robust and (1+1γ)-consistent, meaning that they use at most γOPT queries if the predictions are arbitrarily wrong and at most (1+1γ)OPT queries if the predictions are correct, where OPT is the optimal number of queries for the given instance. Moreover, we show that this trade-off is best possible. Furthermore, we argue that a suitably defined hop distance is a useful measure for the amount of prediction error and design algorithms with performance guarantees that degrade smoothly with the hop distance. We also show that the predictions are PAC-learnable in our model. Our results demonstrate that untrusted predictions can circumvent the known lower bound of~2, without any degradation of the worst-case ratio. To obtain our results, we provide new structural insights for the minimum spanning tree problem that might be useful in the context of query-based algorithms regardless of predictions. In particular, we generalize the concept of witness sets -- the key to lower-bounding the optimum -- by proposing novel global witness set structures and completely new ways of adaptively using those

Learning-Augmented Query Policies for Minimum Spanning Tree with Uncertainty

We study how to utilize (possibly erroneous) predictions in a model for computing under uncertainty in which an algorithm can query unknown data. Our aim is to minimize the number of queries needed to solve the minimum spanning tree problem, a fundamental combinatorial optimization problem that has been central also to the research area of explorable uncertainty. For all integral γ≥2, we present algorithms that are γ-robust and (1+1γ)-consistent, meaning that they use at most γOPT queries if the predictions are arbitrarily wrong and at most (1+1γ)OPT queries if the predictions are correct, where OPT is the optimal number of queries for the given instance. Moreover, we show that this trade-off is best possible. Furthermore, we argue that a suitably defined hop distance is a useful measure for the amount of prediction error and design algorithms with performance guarantees that degrade smoothly with the hop distance. We also show that the predictions are PAC-learnable in our model. Our results demonstrate that untrusted predictions can circumvent the known lower bound of~2, without any degradation of the worst-case ratio. To obtain our results, we provide new structural insights for the minimum spanning tree problem that might be useful in the context of query-based algorithms regardless of predictions. In particular, we generalize the concept of witness sets -- the key to lower-bounding the optimum -- by proposing novel global witness set structures and completely new ways of adaptively using those

Altered hemodynamics and vascular reactivity in a mouse model with severe pericyte deficiency

Pericytes are the mural cells of the microvascular network that are in close contact with underlying endothelial cells. Endothelial-secreted PDGFB leads to recruitment of pericytes to the vessel wall, but this is disrupted in Pdgfb(ret/ret) mice when the PDGFB retention motif is deleted. This results in severely reduced pericyte coverage on blood vessels. In this study, we investigated vascular abnormalities and hemodynamics in Pdgfb(ret/ret) mice throughout the cerebrovascular network and in different cortical layers by in vivo two-photon microscopy. We confirmed that Pdgfb(ret/ret) mice are severely deficient in pericytes throughout the vascular network, with enlarged brain blood vessels and a reduced number of vessel branches. Red blood cell velocity, linear density, and tube hematocrit were reduced in Pdgfb(ret/ret) mice, which may impair oxygen delivery to the tissue. We also measured intravascular PO2 and found that concentrations were higher in cortical Layer 2/3 in Pdgfb(ret/ret) mice, indicative of reduced blood oxygen extraction. Finally, we found that Pdgfb(ret/ret) mice had a reduced capacity for vasodilation in response to an acetazolamide challenge during functional MRI imaging. Taken together, these results suggest that severe pericyte deficiency can lead to vascular abnormalities and altered cerebral blood flow, reminiscent of pathologies such as arteriovenous malformations.ISSN:0271-678XISSN:1559-701

Early reduced behavioral activity induced by large strokes affects the efficiency of enriched environment in rats

The majority of stroke patients develop post-stroke fatigue, a symptom which impairs motivation and diminishes the success of rehabilitative interventions. We show that large cortical strokes acutely reduce activity levels in rats for 1-2 weeks as a physiological response paralleled by signs of systemic inflammation. Rats were exposed early (1-2 weeks) or late (3-4 weeks after stroke) to an individually monitored enriched environment to stimulate self-controlled high-intensity sensorimotor training. A group of animals received Anti-Nogo antibodies for the first two weeks after stroke, a neuronal growth promoting immunotherapy already in clinical trials. Early exposure to the enriched environment resulted in poor outcome: Training intensity was correlated to enhanced systemic inflammation and functional impairment. In contrast, animals starting intense sensorimotor training two weeks after stroke preceded by the immunotherapy revealed better recovery with functional outcome positively correlated to the training intensity and the extent of re-innervation of the stroke denervated cervical hemi-cord. Our results suggest stroke-induced fatigue as a biological purposeful reaction of the organism during neuronal remodeling, enabling new circuit formation which will then be stabilized or pruned in the subsequent rehabilitative training phase. However, intense training too early may lead to wrong connections and is thus less effective