Pitx3Null Mutant (Striatal Dopamine-Deficient) Mice Have Exaggerated Spiny Projection Neuron Responses to l-DOPA and D1 Agonism and Lack Baseline Striatonigral Spiking

L-3,4 dihidroxyphenylalanine (l-DOPA) strongly stimulates motor activity in parkinsonian patients and animal models of Parkinson\u27s disease. Severe striatal dopamine (DA) loss characterizes Parkinson\u27s disease and its animal models. Given the canonical rate model of Parkinson\u27s Disease pathophysiology based on differences in DA pharmacology manifesting as electrophysiological differences in striatal projection neuron (SPN) spike rates, SPNs should increase spiking during the motor response to l-DOPA. In fact, stimulating specific subsets of these neurons to spike in freely-moving wild type and parkinsonian animals causes or inhibits motor activity as predicted. However, pharmacological effects of DA deficiency, let alone those of DA replacement, on SPN spiking activity in freely-moving animals are poorly studied and ultimately unknown. Showing the activity of SPNs of both in-/direct pathways may help elucidate mechanisms by which l-DOPA increases motor activity to normal and sometimes abnormal levels; such mechanistic information would advance understanding about how DA is such a potent motor stimulant. To this end, I devised a Top-hat u-array (with microdrive) for recording in the striatum while stimulating the reticulated substantia nigra. Using my micro-array, I tested l-DOPA\u27s acute effect on SPN spiking activity within contexts that varied in DA deficiency according to the Pitx3Null mouse\u27s Parkinson\u27s-like gradient of striatal DA denervation. Evidently, chronic DA denervation renders SPNs hyper-responsive to l-DOPA and a D1 agonist, SKF 81297, as indicated by exaggerated SPN spike rate responses biased by low baselines in Pitx3Null mice compared to wild-type mice. However, this may be a motor network effect on spiking as it was found in both dorsal (DA-denervated) and non-dorsal (having residual DA) Pitx3Null striatal regions. Furthermore, antidromically identifying dorsal SPNs allowed us to putatively distinguish a particularly relevant subset (striatonigral, D1-SPNs or d[irect]SPNs) known to elicit movement; serendipitously we also identified putative fibers of passage that strongly resembled striatal interneurons. D1-SPNs in Pitx3Null animals had baselines about an order of magnitude significantly below those in wild-type, and all increased firing more so in Pitx3Null than wild-type mice after drug injections, which lends some credence to the hypothesis that direct pathway SPNs are hyper-responsive during l-DOPA-induced normal and abnormal motor behavior secondary to DA depletion. Furthermore, they uncover a need to incorporate more neural factors in explaining electrophysiological effects attributable to DA denervation and restoration pharmacology. The latter data (putative fibers) tempt the interpretation that cortical axons of passage are being mistaken for striatal fast-spiking interneurons in the literature more often than not

A polynomial time biclustering algorithm for finding approximate expression patterns in gene expression time series

<p>Abstract</p> <p>Background</p> <p>The ability to monitor the change in expression patterns over time, and to observe the emergence of coherent temporal responses using gene expression time series, obtained from microarray experiments, is critical to advance our understanding of complex biological processes. In this context, biclustering algorithms have been recognized as an important tool for the discovery of local expression patterns, which are crucial to unravel potential regulatory mechanisms. Although most formulations of the biclustering problem are NP-hard, when working with time series expression data the interesting biclusters can be restricted to those with contiguous columns. This restriction leads to a tractable problem and enables the design of efficient biclustering algorithms able to identify all maximal contiguous column coherent biclusters.</p> <p>Methods</p> <p>In this work, we propose <it>e</it>-CCC-Biclustering, a biclustering algorithm that finds and reports all maximal contiguous column coherent biclusters with approximate expression patterns in time polynomial in the size of the time series gene expression matrix. This polynomial time complexity is achieved by manipulating a discretized version of the original matrix using efficient string processing techniques. We also propose extensions to deal with missing values, discover anticorrelated and scaled expression patterns, and different ways to compute the errors allowed in the expression patterns. We propose a scoring criterion combining the statistical significance of expression patterns with a similarity measure between overlapping biclusters.</p> <p>Results</p> <p>We present results in real data showing the effectiveness of <it>e</it>-CCC-Biclustering and its relevance in the discovery of regulatory modules describing the transcriptomic expression patterns occurring in <it>Saccharomyces cerevisiae </it>in response to heat stress. In particular, the results show the advantage of considering approximate patterns when compared to state of the art methods that require exact matching of gene expression time series.</p> <p>Discussion</p> <p>The identification of co-regulated genes, involved in specific biological processes, remains one of the main avenues open to researchers studying gene regulatory networks. The ability of the proposed methodology to efficiently identify sets of genes with similar expression patterns is shown to be instrumental in the discovery of relevant biological phenomena, leading to more convincing evidence of specific regulatory mechanisms.</p> <p>Availability</p> <p>A prototype implementation of the algorithm coded in Java together with the dataset and examples used in the paper is available in <url>http://kdbio.inesc-id.pt/software/e-ccc-biclustering</url>.</p

BLOOM: A 176B-Parameter Open-Access Multilingual Language Model

Large language models (LLMs) have been shown to be able to perform new tasks based on a few demonstrations or natural language instructions. While these capabilities have led to widespread adoption, most LLMs are developed by resource-rich organizations and are frequently kept from the public. As a step towards democratizing this powerful technology, we present BLOOM, a 176B-parameter open-access language model designed and built thanks to a collaboration of hundreds of researchers. BLOOM is a decoder-only Transformer language model that was trained on the ROOTS corpus, a dataset comprising hundreds of sources in 46 natural and 13 programming languages (59 in total). We find that BLOOM achieves competitive performance on a wide variety of benchmarks, with stronger results after undergoing multitask prompted finetuning. To facilitate future research and applications using LLMs, we publicly release our models and code under the Responsible AI License

Global maps of soil temperature

Research in global change ecology relies heavily on global climatic grids derived from estimates of air temperature in open areas at around 2 m above the ground. These climatic grids do not reflect conditions below vegetation canopies and near the ground surface, where critical ecosystem functions occur and most terrestrial species reside. Here, we provide global maps of soil temperature and bioclimatic variables at a 1-km2 resolution for 0–5 and 5–15 cm soil depth. These maps were created by calculating the difference (i.e. offset) between in situ soil temperature measurements, based on time series from over 1200 1-km2 pixels (summarized from 8519 unique temperature sensors) across all the world\u27s major terrestrial biomes, and coarse-grained air temperature estimates from ERA5-Land (an atmospheric reanalysis by the European Centre for Medium-Range Weather Forecasts). We show that mean annual soil temperature differs markedly from the corresponding gridded air temperature, by up to 10°C (mean = 3.0 ± 2.1°C), with substantial variation across biomes and seasons. Over the year, soils in cold and/or dry biomes are substantially warmer (+3.6 ± 2.3°C) than gridded air temperature, whereas soils in warm and humid environments are on average slightly cooler (−0.7 ± 2.3°C). The observed substantial and biome-specific offsets emphasize that the projected impacts of climate and climate change on near-surface biodiversity and ecosystem functioning are inaccurately assessed when air rather than soil temperature is used, especially in cold environments. The global soil-related bioclimatic variables provided here are an important step forward for any application in ecology and related disciplines. Nevertheless, we highlight the need to fill remaining geographic gaps by collecting more in situ measurements of microclimate conditions to further enhance the spatiotemporal resolution of global soil temperature products for ecological applications

Global maps of soil temperature

Research in global change ecology relies heavily on global climatic grids derived from estimates of air temperature in open areas at around 2 m above the ground. These climatic grids do not reflect conditions below vegetation canopies and near the ground surface, where critical ecosystem functions occur and most terrestrial species reside. Here, we provide global maps of soil temperature and bioclimatic variables at a 1-km² resolution for 0–5 and 5–15 cm soil depth. These maps were created by calculating the difference (i.e., offset) between in-situ soil temperature measurements, based on time series from over 1200 1-km² pixels (summarized from 8500 unique temperature sensors) across all the world’s major terrestrial biomes, and coarse-grained air temperature estimates from ERA5-Land (an atmospheric reanalysis by the European Centre for Medium-Range Weather Forecasts). We show that mean annual soil temperature differs markedly from the corresponding gridded air temperature, by up to 10°C (mean = 3.0 ± 2.1°C), with substantial variation across biomes and seasons. Over the year, soils in cold and/or dry biomes are substantially warmer (+3.6 ± 2.3°C) than gridded air temperature, whereas soils in warm and humid environments are on average slightly cooler (-0.7 ± 2.3°C). The observed substantial and biome-specific offsets emphasize that the projected impacts of climate and climate change on near-surface biodiversity and ecosystem functioning are inaccurately assessed when air rather than soil temperature is used, especially in cold environments. The global soil-related bioclimatic variables provided here are an important step forward for any application in ecology and related disciplines. Nevertheless, we highlight the need to fill remaining geographic gaps by collecting more in-situ measurements of microclimate conditions to further enhance the spatiotemporal resolution of global soil temperature products for ecological applications

Global maps of soil temperature.

Research in global change ecology relies heavily on global climatic grids derived from estimates of air temperature in open areas at around 2 m above the ground. These climatic grids do not reflect conditions below vegetation canopies and near the ground surface, where critical ecosystem functions occur and most terrestrial species reside. Here, we provide global maps of soil temperature and bioclimatic variables at a 1-km2 resolution for 0-5 and 5-15 cm soil depth. These maps were created by calculating the difference (i.e. offset) between in situ soil temperature measurements, based on time series from over 1200 1-km2 pixels (summarized from 8519 unique temperature sensors) across all the world's major terrestrial biomes, and coarse-grained air temperature estimates from ERA5-Land (an atmospheric reanalysis by the European Centre for Medium-Range Weather Forecasts). We show that mean annual soil temperature differs markedly from the corresponding gridded air temperature, by up to 10°C (mean = 3.0 ± 2.1°C), with substantial variation across biomes and seasons. Over the year, soils in cold and/or dry biomes are substantially warmer (+3.6 ± 2.3°C) than gridded air temperature, whereas soils in warm and humid environments are on average slightly cooler (-0.7 ± 2.3°C). The observed substantial and biome-specific offsets emphasize that the projected impacts of climate and climate change on near-surface biodiversity and ecosystem functioning are inaccurately assessed when air rather than soil temperature is used, especially in cold environments. The global soil-related bioclimatic variables provided here are an important step forward for any application in ecology and related disciplines. Nevertheless, we highlight the need to fill remaining geographic gaps by collecting more in situ measurements of microclimate conditions to further enhance the spatiotemporal resolution of global soil temperature products for ecological applications

Hyperactive Response of Direct Pathway Striatal Projection Neurons to L-dopa and D1 Agonism in Freely Moving Parkinsonian Mice

Dopamine (DA) profoundly stimulates motor function as demonstrated by the hypokinetic motor symptoms in Parkinson's disease (PD) and by the hyperkinetic motor side effects during dopaminergic treatment of PD. Dopamine (DA) receptor-bypassing, optogenetics- and chemogenetics-induced spike firing of striatal DA D1 receptor (D1R)-expressing, direct pathway medium spiny neurons (dSPNs or dMSNs) promotes movements. However, the endogenous D1R-mediated effects, let alone those of DA replacement, on dSPN spike activity in freely-moving animals is not established. Here we show that using transcription factor Pitx3 null mutant (Pitx3Null) mice as a model for severe and consistent DA denervation in the dorsal striatum in Parkinson's disease, antidromically identified striatonigral neurons (D1R-expressing dSPNs) had a lower baseline spike firing rate than that in DA-intact normal mice, and these neurons increased their spike firing more strongly in Pitx3Null mice than in WT mice in response to injection of L-dopa or the D1R agonist, SKF81297; the increase in spike firing temporally coincided with the motor-stimulating effects of L-dopa and SKF81297. Taken together, these results provide the first evidence from freely moving animals that in parkinsonian striatum, identified behavior-promoting dSPNs become hyperactive upon the administration of L-dopa or a D1 agonist, likely contributing to the profound dopaminergic motor stimulation in parkinsonian animals and PD patients

Video_1_Hyperactive Response of Direct Pathway Striatal Projection Neurons to L-dopa and D1 Agonism in Freely Moving Parkinsonian Mice.MOV

<p>Dopamine (DA) profoundly stimulates motor function as demonstrated by the hypokinetic motor symptoms in Parkinson's disease (PD) and by the hyperkinetic motor side effects during dopaminergic treatment of PD. Dopamine (DA) receptor-bypassing, optogenetics- and chemogenetics-induced spike firing of striatal DA D1 receptor (D1R)-expressing, direct pathway medium spiny neurons (dSPNs or dMSNs) promotes movements. However, the endogenous D1R-mediated effects, let alone those of DA replacement, on dSPN spike activity in freely-moving animals is not established. Here we show that using transcription factor Pitx3 null mutant (Pitx3Null) mice as a model for severe and consistent DA denervation in the dorsal striatum in Parkinson's disease, antidromically identified striatonigral neurons (D1R-expressing dSPNs) had a lower baseline spike firing rate than that in DA-intact normal mice, and these neurons increased their spike firing more strongly in Pitx3Null mice than in WT mice in response to injection of L-dopa or the D1R agonist, SKF81297; the increase in spike firing temporally coincided with the motor-stimulating effects of L-dopa and SKF81297. Taken together, these results provide the first evidence from freely moving animals that in parkinsonian striatum, identified behavior-promoting dSPNs become hyperactive upon the administration of L-dopa or a D1 agonist, likely contributing to the profound dopaminergic motor stimulation in parkinsonian animals and PD patients.</p

Video_2_Hyperactive Response of Direct Pathway Striatal Projection Neurons to L-dopa and D1 Agonism in Freely Moving Parkinsonian Mice.MOV

<p>Dopamine (DA) profoundly stimulates motor function as demonstrated by the hypokinetic motor symptoms in Parkinson's disease (PD) and by the hyperkinetic motor side effects during dopaminergic treatment of PD. Dopamine (DA) receptor-bypassing, optogenetics- and chemogenetics-induced spike firing of striatal DA D1 receptor (D1R)-expressing, direct pathway medium spiny neurons (dSPNs or dMSNs) promotes movements. However, the endogenous D1R-mediated effects, let alone those of DA replacement, on dSPN spike activity in freely-moving animals is not established. Here we show that using transcription factor Pitx3 null mutant (Pitx3Null) mice as a model for severe and consistent DA denervation in the dorsal striatum in Parkinson's disease, antidromically identified striatonigral neurons (D1R-expressing dSPNs) had a lower baseline spike firing rate than that in DA-intact normal mice, and these neurons increased their spike firing more strongly in Pitx3Null mice than in WT mice in response to injection of L-dopa or the D1R agonist, SKF81297; the increase in spike firing temporally coincided with the motor-stimulating effects of L-dopa and SKF81297. Taken together, these results provide the first evidence from freely moving animals that in parkinsonian striatum, identified behavior-promoting dSPNs become hyperactive upon the administration of L-dopa or a D1 agonist, likely contributing to the profound dopaminergic motor stimulation in parkinsonian animals and PD patients.</p