Optimal function in the brain, especially in hippocampus—an area involved in learning and memory—requires tight regulation of intracellular pH (pHi) within neurons and neuroglial. The Na‐H exchangers (NHEs) are the major family of acid/base proteins involved in regulating pHi in the absence of CO2/HCO3. In the present study, we used the pH‐sensitive dye BCECF to examine the regulation of steady‐state pHi and the recovery of pHi from NH4+ ‐induced intracellular acid loads in HC neurons and astrocytes, co‐cultured from embryonic (E18‐20) Sprague Dawley rats, and studied in CO2/HCO3 −‐free HEPES buffered (“HEPES”) solutions. After at least 14‐days in a CO2/HCO3 – incubator, cells were removed, loaded with BCECF, and placed in a recording chamber with flowing HEPES. At the beginning of each experiment, we measured pHi (checkpoint A) after allowing pHi to stabilize for 5 minutes (checkpoint C), and reported mean “initial pHi”/SEM for neurons as 7.351/0.0597; N=37 (astrocytes: 7.189/0.0118, N=25) the value at checkpoint C = (pHi)C. After using the twin paired NH4+ ‐pulse protocol to acid load cells, we find that—after the pHi recovery from the first acid load—the average neuronal steady‐state pHi (now at checkpoint E; (pHi)E) is 6.953/0.0601(astrocytes: 7.037/0.0081). After the second NH4+ pulse the neuronal steady‐state pHi (now at checkpoint F; (pHi)F) in neurons is 6.937/0.010 (astrocytes: 7.020/0.0062). The recovery from acidosis is fit with a double exponential (DExp) which we replot as dpHi/dt vs pHi. With this traditional approach, dpHi/dt, the fit as it approaches the asymptotic pHi, becomes slightly non‐linear. To exploit the mainly linearity portion of the dpHi/dt vs. pHi plot (from the DExp fit) of the double exponential, we fit these dpHi/dt vs. pHi points with a DExp with a quasi‐ single exponential (SExp) to produce a quasi–single‐exponential rate constant (kqSExp) measured as dpH/dt. This analysis—when transformed to the pHi vs. time domain—generally produces a very good fit to the original pHi vs. time data. The mean kqSExp1 in neurons is 0.0054/ 0.0008 (astrocytes: 0.0107/0.0002) whereas the mean kqSExp2 in neurons is 0.0055/0.0008 (astrocytes: 0.0010/0.0003). We summarize the twin pHi recoveries from individual experiments in which we display as thumbnails the quasi–single‐exponential dpHi/dt line segments that represent the pHi recoveries from the first and second NH3/NH4+ pulses. These new analytical approaches may ultimately provide mechanistic insight into cell‐to‐cell heterogeneity of pHi regulation in the nervous system.
On Efficient Constructions of Checkpoints
Efficient construction of checkpoints/snapshots is a critical tool for training and diagnosing deep learning models. In this paper, we propose a lossy compression scheme for checkpoint constructions (called LC-Checkpoint). LC-Checkpoint simultaneously maximizes the compression rate and optimizes the recovery speed, under the assumption that SGD is used to train the model. LC-Checkpointuses quantization and priority promotion to store the most crucial information for SGD to recover, and then uses a Huffman coding to leverage the non-uniform distribution of the gradient scales. Our extensive experiments show that LC-Checkpoint achieves a compression rate up to 28× and recovery speedup up to 5.77× over a state-of-the-art algorithm (SCAR).
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- Award ID(s):
- 1835821
- NSF-PAR ID:
- 10212765
- Date Published:
- Journal Name:
- Proceedings of the 37th International Conference on Machine Learning, ICML 2020, 13-18 July 2020
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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