113 research outputs found
Characterization of response properties in the mouse lateral geniculate nucleus
The lateral geniculate nucleus (LGN) has been increasingly recognized to actively regulate information transmission to primary visual cortex (V1). Although efforts have been devoted to study its morphological and functional features, the full array of response characteristics in mouse LGN as well as their dependency on subjective state have been relatively unexplored.
To address the question we recorded from mouse LGN with multisite-electrode-arrays (MEAs). From a dataset with 185 single units, our results revealed several exceptional response features in mouse LGN. We also demonstrated that subtypes, such as ON-/OFF-centre and transient/sustained cells exhibited functionally distinctive features, which might indicate parallel projections. To further compare response features from the full extent of mouse LGN, we developed a three-dimension (3D) LGN volume through histological approach. This volume explicitly captures morphological features of mouse LGN and provides the preciseness to classify location of single neuron into the anterior/middle/posterior LGN. Based on this categorization, we showed that response features were not regionally restricted within mouse LGN.
We further examined neural activity with subjects in high or low isoflurane states. The distinct features in LFPs between the two states indicated that adjusting isoflurane concentration could provide a reliable and controllable experimental model to explore the state-dependent neural activity in mouse visual system. Subsequently, our results demonstrated that properties, including response latency, contrast sensitivity and spatial frequency properties were modulated by isoflurane concentration.
Our current work suggests that mouse LGN can dynamically regulate information transmission to the cortex using numerous mechanisms, including responding mode, modulation of neuronal responses according to subjects’ states.Open Acces
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A universal delayed difference model fitting dose-response curves
Purpose: Dose-response curves, which fit a multitude of experimental data derived from toxicology, are widely used in physics, chemistry, biology, and other fields. Although there are many dose-response models for fitting dose-response curves, the application of these models is limited by many restrictions and lacks universality, so there is a need for a novel, universal dynamical model that can improve fits to various types of dose-response curves.
Methods: We expand the hormetic Ricker model, taking the delay inherent in the dose-response into account, and develop a novel and dynamic delayed Ricker difference model (DRDM) to fit various types of dose-response curves. Furthermore, we compare the DRDM with other dose-response models to confirm that it can mimic different types of dose-response curves.
Data analysis: By fitting various types of dose-response data sets derived from drug applications, disease treatment, pest control, and plant management, and comparing the imitative effect of the DRDM with other models, we find that the DRDM fits monotonic dose-response data well and, in most circumstances, the DRDM has a better imitative effect to non-monotonic dose-response data with hormesis than other models do.
Results: The MSE of fits of the DRDM to S-shaped dose-response data (DS2-G) is not lower than those for four other models, but the MSE of fits to U-shaped (DS7) and inverted U-shaped dose-response data (DS10) were lower than for two other models. This means that the imitative effect of the DRDM is comparable to other models of monotonic dose-response data, but is a significant improvement compared to traditional models of non-monotonic dose-response data with hormesis.
Conclusion: We propose a novel dynamic model (DRDM) for fitting to various types of dose-response curves, which can reflect the dynamic trend of the population growth compared with traditional static dose-response models. By analyzing data, we have confirmed that the DRDM provides an ideal description of various dose-response observations and it can be used to fit a wide range of dose-response data sets, especially for hormetic data sets. Therefore, we conclude that the DRDM has a good universality for dose-response curve fitting
Effect of Malondialdehyde Oxidation on Physicochemical Properties and Color Stability of Yak Meat Sarcoplasmic Proteins
Sarcoplasmic proteins (SP) derived from yak meat were oxidized by malondialdehyde (MDA) at different concentrations. The effects of lipid oxidation on physicochemical properties and color stability of SP were investigated by evaluating side-chain amino acid oxidation, protein structure and color of SP and the oxidation status of myoglobin (Mb). The results showed that after MDA oxidation, the a* value, b* value, C* value, and deoxymyoglobin and oxymyoglobin contents of SP significantly decreased (P < 0.05), and the L* value, metmyoglobin content, and ferrylmyoglobin concentration significantly increased (P < 0.05), indicating that MDA oxidation lowered color stability. The contents of carbonyl groups and dimeric tyrosine, the fluorescence intensity of SP-MDA adducts, and the relative contents of β-helix and β-turn significantly increased (P < 0.05), and total sulfhydryl content, surface hydrophobicity, intrinsic fluorescence intensity, and the relative contents of α-helix and random coil significantly declined (P < 0.05). Sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) showed blurred expansion of small molecule bands and the formation of macromolecular aggregates, suggesting that MDA promoted the oxidation and aggregation of SP. Pearson correlation analysis revealed significant correlations between MDA oxidation and physicochemical properties and color stability of SP (P < 0.05). This study reveals that MDA alters the structure of SP by directly oxidizing it or mediating Mb oxidation, causing cross-linked aggregation of SP and reducing its color stability
Analysis of Differentially Expressed Proteins in Self-Paired Sera of Advanced Non-small Cell Lung Cancer Patients Responsive to Gefin
Background and objective All the advanced NSCLC patients that received EGFR-TKI therapy will eventually relapse after a period of efficacy. The aim of this study is to investigate the serum biomarkers as potential predictive factors for the efficacy of epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor (TKI) targeted therapy in advanced non-small cell lung cancer. Methods Twenty self-paired serum samples were collected from 9 advanced NSCLC patients that evaluated as disease control (SD or PR) after gefinitib therapy, at the time points of before and after gefinitib treatment but 2 weeks before being evaluated as disease progress. All samples were pre-separated by WCX microbeads, and then detected on the MALDI-TOF-MS platform of Bruker AutoflexTM. ClinProTools (Version: 2.1) was used to analyze the differentially expressed proteins. Results There were 7 protein peaks (m/z), 3242.09, 8 690.36, 2 952.64, 3 224.04, 1 450.51, 1 887.8 and 3 935.73 found statistically differentially expressed between the self-paired samples. Three proteins (3 242.09, 2 952.64 and 3 224.04) were down-regulated and four proteins (8 690.36, 1 450.51, 1 887.8 and 3 935.73) up-regulated in gefinitib treated sera. Conclusion The data here suggest that several specific protein peaks might indicate gefinitib resistance, yet the identities of these proteins and the mechanisms underlying the responsiveness to gefinitib treatment need further investigation
Decoding the dopamine transporter imaging for the differential diagnosis of parkinsonism using deep learning.
PURPOSE
This work attempts to decode the discriminative information in dopamine transporter (DAT) imaging using deep learning for the differential diagnosis of parkinsonism.
METHODS
This study involved 1017 subjects who underwent DAT PET imaging ([11C]CFT) including 43 healthy subjects and 974 parkinsonian patients with idiopathic Parkinson's disease (IPD), multiple system atrophy (MSA) or progressive supranuclear palsy (PSP). We developed a 3D deep convolutional neural network to learn distinguishable DAT features for the differential diagnosis of parkinsonism. A full-gradient saliency map approach was employed to investigate the functional basis related to the decision mechanism of the network. Furthermore, deep-learning-guided radiomics features and quantitative analysis were compared with their conventional counterparts to further interpret the performance of deep learning.
RESULTS
The proposed network achieved area under the curve of 0.953 (sensitivity 87.7%, specificity 93.2%), 0.948 (sensitivity 93.7%, specificity 97.5%), and 0.900 (sensitivity 81.5%, specificity 93.7%) in the cross-validation, together with sensitivity of 90.7%, 84.1%, 78.6% and specificity of 88.4%, 97.5% 93.3% in the blind test for the differential diagnosis of IPD, MSA and PSP, respectively. The saliency map demonstrated the most contributed areas determining the diagnosis located at parkinsonism-related regions, e.g., putamen, caudate and midbrain. The deep-learning-guided binding ratios showed significant differences among IPD, MSA and PSP groups (P < 0.001), while the conventional putamen and caudate binding ratios had no significant difference between IPD and MSA (P = 0.24 and P = 0.30). Furthermore, compared to conventional radiomics features, there existed average above 78.1% more deep-learning-guided radiomics features that had significant differences among IPD, MSA and PSP.
CONCLUSION
This study suggested the developed deep neural network can decode in-depth information from DAT and showed potential to assist the differential diagnosis of parkinsonism. The functional regions supporting the diagnosis decision were generally consistent with known parkinsonian pathology but provided more specific guidance for feature selection and quantitative analysis
Finishing the euchromatic sequence of the human genome
The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead
A Critique on Ideology Critique
This paper is a critique on ideology critique. In this paper, I argue that, even though ideology critique is often conceived as the means to unmask oppressive relations, it can also mask and further perpetuate those relations. First, I introduce the concept of discourse by discussing its implications for social activities. Then, I draw a parallel between discourse and games to offer a way of accounting for the mechanism of discourse–how it is structured and how it may be changed. With this understanding of discourse, I analyze some case studies of ideology critique, which I identify as a type of discourse. In those case studies, I demonstrate how an ideology critique can assume problematic rules, so that it no longer plays a liberation game but an oppression game. I propose some ways to avoid constructing an oppressive ideology critique and anticipate some possible objections. In the end, I show how this lesson learned from ideology critique can be applied to self-examination and raise some interesting questions for further exploration
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