Effects of optogenetic stimulation of vasopressinergic retinal afferents on suprachiasmatic neurons

Physiological circadian rhythms are orchestrated by the hypothalamic suprachiasmatic nucleus (SCN). The activity of SCN cells is synchronised by environmental signals, including light information from retinal ganglion cells (RGCs). We recently described a population of vasopressin‐expressing RGCs (VP‐RGC) that send axonal projections to the SCN. To determine how these VP‐RGCs influence the activity of cells in the SCN, we used optogenetic tools to specifically activate their axon terminals within the SCN. Rats were intravitreally injected with a recombinant adeno‐associated virus to express the channelrhodopsin‐2 and the red fluorescent protein mCherry under the vasopressin promoter (VP‐ChR2mCherry). In vitro recordings in acute brain slices showed that approximately 30% of ventrolateral SCN cells responded to optogenetic stimulation with an increase in firing rate that progressively increased during the first 200 seconds of stimulation and which persisted after the end of stimulation. Finally, application of a vasopressin V1A receptor antagonist dampened the response to optogenetic stimulation. Our data suggest that optogenetic stimulation of VP‐RGC axons within the SCN influences the activity of SCN cells in a vasopressin‐dependent manner.The data that support the findings of this study are openly available at http://datashare.is.ed.ac.ukMedical Research Council. Grant Number: MR/M022838http://wileyonlinelibrary.com/journal/jne2020-12-01hj2020Immunolog

Cost-effectiveness of hydroxyurea for sickle cell anemia in a low-income African setting: a model-based evaluation of two dosing regimens

Background and Objective: The disease burden of sickle cell anemia (SCA) in sub-Saharan African (SSA) countries is substantial, with many children dying without an established diagnosis or proper treatment. The global burden of SCA is increasing each year, making therapeutic intervention a high priority. Hydroxyurea is the only disease-modifying therapy with proven feasibility and efcacy suitable for SSA; however, no one has quantifed the health economic implications of its use. Therefore, from the perspective of the health care provider, we estimated the incremental cost-efectiveness of hydroxyurea as a fxed-dose regimen or maximum tolerated dose (MTD) regimen, versus SCA care without hydroxyurea. Methods: We estimated the cost of providing outpatient treatment at a pediatric sickle cell clinic in Kampala, Uganda. These estimates were used in a discrete-event simulation model to project mean costs (2021 US$), disability-adjusted life years (DALYs), and consumption of blood products per patient (450 mL units), for patients between 9 months and 18 years of age. We calculated cost-efectiveness as the ratio of incremental costs over incremental DALYs averted, discounted at 3Results: Hydroxyurea treatment averted an expected 1.37 DALYs and saved US$ 191 per patient if administered at the MTD, compared with SCA care without hydroxyurea. In comparison, hydroxyurea at a fxed dose averted 0.80 DALYs per patient at an incremental cost of US$ 2. The MTD strategy saved 11.2 (95% CI 11.1–11.4) units of blood per patient, compared with 9.1 (95% CI 9.0–9.2) units of blood per patient at the fxed-dose alternative. Conclusions: Hydroxyurea at MTD is likely to improve quality of life and reduce the consumption of blood products for children with SCA living in Uganda. Compared with a fxed dose regimen, treatment dosing at MTD is likely to be a cost-efective treatment for SCA, using realistic ranges of hydroxyurea costs that are relevant across SSA. Compared with no use of the drug, hydroxyurea could lead to substantial net savings per patient, while reducing the disease morbidity and mortality and increasing quality of lif

Effects of optogenetic stimulation of vasopressinergic retinal afferents on suprachiasmatic neurones

Physiological circadian rhythms are orchestrated by the hypothalamic suprachiasmatic nucleus (SCN). The activity of SCN cells is synchronised by environmental signals, including light information from retinal ganglion cells (RGCs). We recently described a population of vasopressin‐expressing RGCs (VP‐RGC) that send axonal projections to the SCN. To determine how these VP‐RGCs influence the activity of cells in the SCN, we used optogenetic tools to specifically activate their axon terminals within the SCN. Rats were intravitreally injected with a recombinant adeno‐associated virus to express the channelrhodopsin‐2 and the red fluorescent protein mCherry under the vasopressin promoter (VP‐ChR2mCherry). In vitro recordings in acute brain slices showed that approximately 30% of ventrolateral SCN cells responded to optogenetic stimulation with an increase in firing rate that progressively increased during the first 200 seconds of stimulation and which persisted after the end of stimulation. Finally, application of a vasopressin V1A receptor antagonist dampened the response to optogenetic stimulation. Our data suggest that optogenetic stimulation of VP‐RGC axons within the SCN influences the activity of SCN cells in a vasopressin‐dependent manner.The data that support the findings of this study are openly available at http://datashare.is.ed.ac.ukMedical Research Council. Grant Number: MR/M022838http://wileyonlinelibrary.com/journal/jne2020-12-01hj2020Immunolog

Csf1r-mApple transgene expression and ligand binding in vivo reveal dynamics of CSF1R expression within the mononuclear phagocyte system

CSF1 is the primary growth factor controlling macrophage numbers, but whether expression of the CSF1 receptor differs between discrete populations of mononuclear phagocytes remains unclear. We have generated a Csf1r-mApple transgenic fluorescent reporter mouse that, in combination with lineage tracing, Alexa Fluor 647-labeled CSF1-Fc and CSF1, and a modified Delta Csf1-enhanced cyan fluorescent protein (ECFP) transgene that lacks a 150 bp segment of the distal promoter, we have used to dissect the differentiation and CSF1 responsiveness of mononuclear phagocyte populations in situ. Consistent with previous Csf1r-driven reporter lines, Csf1r-mApple was expressed in blood monocytes and at higher levels in tissue macrophages, and was readily detectable in whole mounts or with multiphoton microscopy. In the liver and peritoneal cavity, uptake of labeled CSF1 largely reflected transgene expression, with greater receptor activity in mature macrophages than monocytes and tissue-specific expression in conventional dendritic cells. However, CSF1 uptake also differed between subsets of monocytes and discrete populations of tissue macrophages, which in macrophages correlated with their level of dependence on CSF1 receptor signaling for survival rather than degree of transgene expression. A double Delta Csf1r-ECFP-Csf1r-mApple transgenic mouse distinguished subpopulations of microglia in the brain, and permitted imaging of interstitial macrophages distinct from alveolar macrophages, and pulmonary monocytes and conventional dendritic cells. The Csf1r-mApple mice and fluorescently labeled CSF1 will be valuable resources for the study of macrophage and CSF1 biology, which are compatible with existing EGFP-based reporter lines

Toy Models of Superposition

Neural networks often pack many unrelated concepts into a single neuron - a puzzling phenomenon known as 'polysemanticity' which makes interpretability much more challenging. This paper provides a toy model where polysemanticity can be fully understood, arising as a result of models storing additional sparse features in "superposition." We demonstrate the existence of a phase change, a surprising connection to the geometry of uniform polytopes, and evidence of a link to adversarial examples. We also discuss potential implications for mechanistic interpretability.Comment: Also available at https://transformer-circuits.pub/2022/toy_model/index.htm

A National Network of Safe Havens:A Scottish Perspective

For over a decade, Scotland has implemented and operationalized a system of Safe Havens, which provides secure analytics platforms for researchers to access linked, deidentified electronic health records (EHRs) while managing the risk of unauthorized reidentification. In this paper, a perspective is provided on the state-of-the-art Scottish Safe Haven network, including its evolution, to define the key activities required to scale the Scottish Safe Haven network’s capability to facilitate research and health care improvement initiatives. A set of processes related to EHR data and their delivery in Scotland have been discussed. An interview with each Safe Haven was conducted to understand their services in detail, as well as their commonalities. The results show how Safe Havens in Scotland have protected privacy while facilitating the reuse of the EHR data. This study provides a common definition of a Safe Haven and promotes a consistent understanding among the Scottish Safe Haven network and the clinical and academic research community. We conclude by identifying areas where efficiencies across the network can be made to meet the needs of population-level studies at scale

Language Models (Mostly) Know What They Know

We study whether language models can evaluate the validity of their own claims and predict which questions they will be able to answer correctly. We first show that larger models are well-calibrated on diverse multiple choice and true/false questions when they are provided in the right format. Thus we can approach self-evaluation on open-ended sampling tasks by asking models to first propose answers, and then to evaluate the probability "P(True)" that their answers are correct. We find encouraging performance, calibration, and scaling for P(True) on a diverse array of tasks. Performance at self-evaluation further improves when we allow models to consider many of their own samples before predicting the validity of one specific possibility. Next, we investigate whether models can be trained to predict "P(IK)", the probability that "I know" the answer to a question, without reference to any particular proposed answer. Models perform well at predicting P(IK) and partially generalize across tasks, though they struggle with calibration of P(IK) on new tasks. The predicted P(IK) probabilities also increase appropriately in the presence of relevant source materials in the context, and in the presence of hints towards the solution of mathematical word problems. We hope these observations lay the groundwork for training more honest models, and for investigating how honesty generalizes to cases where models are trained on objectives other than the imitation of human writing.Comment: 23+17 pages; refs added, typos fixe

Red Teaming Language Models to Reduce Harms: Methods, Scaling Behaviors, and Lessons Learned

We describe our early efforts to red team language models in order to simultaneously discover, measure, and attempt to reduce their potentially harmful outputs. We make three main contributions. First, we investigate scaling behaviors for red teaming across 3 model sizes (2.7B, 13B, and 52B parameters) and 4 model types: a plain language model (LM); an LM prompted to be helpful, honest, and harmless; an LM with rejection sampling; and a model trained to be helpful and harmless using reinforcement learning from human feedback (RLHF). We find that the RLHF models are increasingly difficult to red team as they scale, and we find a flat trend with scale for the other model types. Second, we release our dataset of 38,961 red team attacks for others to analyze and learn from. We provide our own analysis of the data and find a variety of harmful outputs, which range from offensive language to more subtly harmful non-violent unethical outputs. Third, we exhaustively describe our instructions, processes, statistical methodologies, and uncertainty about red teaming. We hope that this transparency accelerates our ability to work together as a community in order to develop shared norms, practices, and technical standards for how to red team language models