cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.10530012
title: Task-driven neural network models predict neural dynamics of proprioception: Synthetic muscle spindle datasets

description: #############

Task-driven neural network models predict neural dynamics of proprioception, Cell 2024

#############

Authors: Marin Vargas, Alessandro (orcid=0000-0001-7073-4120) and Bisi, Axel (orcid=0009-0006-8602-7555) and Chiappa, Alberto Silvio (orcid=0009-0001-2764-6552) and Versteeg, Christopher (orcid=0000-0002-4269-5109) and Miller, Lee E. (orcid=0000-0001-8675-7140) and Mathis, Alexander (orcid=0000-0002-3777-2202)

Affiliation: EPFL

Date: January, 2024

Link to the Cell article: 

https://www.cell.com/cell/pdf/S0092-8674(24)00239-3.pdf

--------------------------------

Here we provide the synthetic spindle datasets of our article "Task-driven neural network models predict neural dynamics of proprioception". It contains the synthetic generated training dataset of simulated muscle spindles during arm passive movements generated with either character writing (PCR) or with 3D target reaching using reinforcement learning (RL).

The overall structure of the data is:

└── spindle_datasets    ├── pcr_dataset                     - Contains PCR synthetic training dataset    └── rl_dataset                        - Contains RL-generated synthetic training dataset

The code to generate the PCR synthetic spindle dataset is available at: https://github.com/amathislab/Task-driven-Proprioception/tree/master/PCR-data-generation

The code to generate the RL-generated synthetic spindle dataset is available at: https://github.com/amathislab/Task-driven-Proprioception/tree/master/RL-data-generation

--------------------------------

The datasets, weights, activations and predictions are released with Creative Commons Attribution 4.0 license.

The code is released under the MIT license, see https://github.com/amathislab/Task-driven-Proprioception

If you find our code, weights, predictions or ideas useful, please cite:

@article{vargas2024task,  title={Task-driven neural network models predict neural dynamics of proprioception},  author={{Marin Vargas}, Alessandro and Bisi, Axel and Chiappa, Alberto S and Versteeg, Chris and Miller, Lee E and Mathis, Alexander},  journal={Cell},  year={2024},  publisher={Elsevier}}
DOI: 10.5281/zenodo.10530013
title: Task-driven neural network models predict neural dynamics of proprioception: Synthetic muscle spindle datasets

description: #############

Task-driven neural network models predict neural dynamics of proprioception, Cell 2024

#############

Authors: Marin Vargas, Alessandro (orcid=0000-0001-7073-4120) and Bisi, Axel (orcid=0009-0006-8602-7555) and Chiappa, Alberto Silvio (orcid=0009-0001-2764-6552) and Versteeg, Christopher (orcid=0000-0002-4269-5109) and Miller, Lee E. (orcid=0000-0001-8675-7140) and Mathis, Alexander (orcid=0000-0002-3777-2202)

Affiliation: EPFL

Date: January, 2024

Link to the Cell article: 

https://www.cell.com/cell/pdf/S0092-8674(24)00239-3.pdf

--------------------------------

Here we provide the synthetic spindle datasets of our article "Task-driven neural network models predict neural dynamics of proprioception". It contains the synthetic generated training dataset of simulated muscle spindles during arm passive movements generated with either character writing (PCR) or with 3D target reaching using reinforcement learning (RL).

The overall structure of the data is:

└── spindle_datasets    ├── pcr_dataset                     - Contains PCR synthetic training dataset    └── rl_dataset                        - Contains RL-generated synthetic training dataset

The code to generate the PCR synthetic spindle dataset is available at: https://github.com/amathislab/Task-driven-Proprioception/tree/master/PCR-data-generation

The code to generate the RL-generated synthetic spindle dataset is available at: https://github.com/amathislab/Task-driven-Proprioception/tree/master/RL-data-generation

--------------------------------

The datasets, weights, activations and predictions are released with Creative Commons Attribution 4.0 license.

The code is released under the MIT license, see https://github.com/amathislab/Task-driven-Proprioception

If you find our code, weights, predictions or ideas useful, please cite:

@article{vargas2024task,  title={Task-driven neural network models predict neural dynamics of proprioception},  author={{Marin Vargas}, Alessandro and Bisi, Axel and Chiappa, Alberto S and Versteeg, Chris and Miller, Lee E and Mathis, Alexander},  journal={Cell},  year={2024},  publisher={Elsevier}}
DOI: 10.6084/m9.figshare.4888511
title: RKNNMDA: Ranking-based KNN for MiRNA-Disease Association prediction

description: Cumulative verified experimental studies have demonstrated that microRNAs (miRNAs) could be closely related with the development and progression of human complex diseases. Based on the assumption that functional similar miRNAs may have a strong correlation with phenotypically similar diseases and vice versa, researchers developed various effective computational models which combine heterogeneous biologic data sets including disease similarity network, miRNA similarity network, and known disease-miRNA association network to identify potential relationships between miRNAs and diseases in biomedical research. Considering the limitations in previous computational study, we introduced a novel computational method of Ranking-based KNN for miRNA-Disease Association prediction (RKNNMDA) to predict potential related miRNAs for diseases, and our method obtained an AUC of 0.8221 based on leave-one-out cross validation. In addition, RKNNMDA was applied to 3 kinds of important human cancers for further performance evaluation. The results showed that 96%, 80% and 94% of predicted top 50 potential related miRNAs for Colon Neoplasms, Esophageal Neoplasms, and Prostate Neoplasms have been confirmed by experimental literatures, respectively. Moreover, RKNNMDA could be used to predict potential miRNAs for diseases without any known miRNAs, and it is anticipated that RKNNMDA would be of great use for novel miRNA-disease association identification.
DOI: 10.6084/m9.figshare.4888511.v1
title: RKNNMDA: Ranking-based KNN for MiRNA-Disease Association prediction

description: Cumulative verified experimental studies have demonstrated that microRNAs (miRNAs) could be closely related with the development and progression of human complex diseases. Based on the assumption that functional similar miRNAs may have a strong correlation with phenotypically similar diseases and vice versa, researchers developed various effective computational models which combine heterogeneous biologic data sets including disease similarity network, miRNA similarity network, and known disease-miRNA association network to identify potential relationships between miRNAs and diseases in biomedical research. Considering the limitations in previous computational study, we introduced a novel computational method of Ranking-based KNN for miRNA-Disease Association prediction (RKNNMDA) to predict potential related miRNAs for diseases, and our method obtained an AUC of 0.8221 based on leave-one-out cross validation. In addition, RKNNMDA was applied to 3 kinds of important human cancers for further performance evaluation. The results showed that 96%, 80% and 94% of predicted top 50 potential related miRNAs for Colon Neoplasms, Esophageal Neoplasms, and Prostate Neoplasms have been confirmed by experimental literatures, respectively. Moreover, RKNNMDA could be used to predict potential miRNAs for diseases without any known miRNAs, and it is anticipated that RKNNMDA would be of great use for novel miRNA-disease association identification.
DOI: 10.6084/m9.figshare.4892402
title: Identifying selectively important amino acid positions associated with alternative habitat environments in fish mitochondrial genomes

description: Fish species inhabitating seawater (SW) or freshwater (FW) habitats have to develop genetic adaptations to alternative environment factors, especially salinity. Functional consequences of the protein variations associated with habitat environments in fish mitochondrial genomes have not yet received much attention. We analyzed 829 complete fish mitochondrial genomes and compared the amino acid differences of 13 mitochondrial protein families between FW and SW fish groups. We identified 47 specificity determining sites (SDS) that associated with FW or SW environments from 12 mitochondrial protein families. Thirty-two (68%) of the SDS sites are hydrophobic, 13 (28%) are neutral, and the remaining sites are acidic or basic. Seven of those SDS from ND1, ND2 and ND5 were scored as probably damaging to the protein structures. Furthermore, phylogenetic tree based Bayes Empirical Bayes analysis also detected 63 positive sites associated with alternative habitat environments across ten mtDNA proteins. These signatures could be important for studying mitochondrial genetic variation relevant to fish physiology and ecology.
DOI: 10.6084/m9.figshare.4892402.v1
title: Identifying selectively important amino acid positions associated with alternative habitat environments in fish mitochondrial genomes

description: Fish species inhabitating seawater (SW) or freshwater (FW) habitats have to develop genetic adaptations to alternative environment factors, especially salinity. Functional consequences of the protein variations associated with habitat environments in fish mitochondrial genomes have not yet received much attention. We analyzed 829 complete fish mitochondrial genomes and compared the amino acid differences of 13 mitochondrial protein families between FW and SW fish groups. We identified 47 specificity determining sites (SDS) that associated with FW or SW environments from 12 mitochondrial protein families. Thirty-two (68%) of the SDS sites are hydrophobic, 13 (28%) are neutral, and the remaining sites are acidic or basic. Seven of those SDS from ND1, ND2 and ND5 were scored as probably damaging to the protein structures. Furthermore, phylogenetic tree based Bayes Empirical Bayes analysis also detected 63 positive sites associated with alternative habitat environments across ten mtDNA proteins. These signatures could be important for studying mitochondrial genetic variation relevant to fish physiology and ecology.
DOI: 10.6084/m9.figshare.4896179
title: Identification of SSEA-1 expressing enhanced reprogramming (SEER) cells in porcine embryonic fibroblasts

description: Previous research has shown that a subpopulation of cells within cultured human dermal fibroblasts, termed multilineage-differentiating stress enduring (Muse) cells, are preferentially reprogrammed into induced pluripotent stem cells. However, controversy exists over whether these cells are the only cells capable of being reprogrammed from a heterogeneous population of fibroblasts. Similarly, there is little research to suggest such cells may exist in embryonic tissues or other species. To address if such a cell population exists in pigs, we investigated porcine embryonic fibroblast populations (pEFs) and identified heterogeneous expression of several key cell surface markers. Strikingly, we discovered a small population of stage-specific embryonic antigen 1 positive cells (SSEA-1+) in Danish Landrace and Göttingen minipig pEFs, which were absent in the Yucatan pEFs. Furthermore, reprogramming of SSEA-1+ sorted pEFs led to higher reprogramming efficiency. Subsequent transcriptome profiling of the SSEA-1+ vs. the SSEA-1neg cell fraction revealed highly comparable gene signatures. However several genes that were found to be upregulated in the SSEA-1+ cells were similarly expressed in mesenchymal stem cells (MSCs). We therefore termed these cells SSEA-1 Expressing Enhanced Reprogramming (SEER) cells. Interestingly, SEER cells were more effective at differentiating into osteocytes and chondrocytes <i>in</i> vitro. We conclude that SEER cells are more amenable for reprogramming and that the expression of mesenchymal stem cell genes is advantageous in the reprogramming process. This data provides evidence supporting the elite theory and helps to delineate which cell types and specific genes are important for reprogramming in the pig.
DOI: 10.48623/aperta.263790
title: Phactboost Predictions

description: Most algorithms that are used to predict the effects of variants rely on evolutionary conservation. However, a majority of such techniques compute evolutionary conservation by solely using the alignment of multiple sequences while overlooking the evolutionary context of substitution events. We had introduced PHACT, a scoring-based pathogenicity predictor for missense mutations that can leverage phylogenetic trees, in our previous study. By building on this foundation, we now propose PHACTboost, a gradient boosting tree-based classifier that combines PHACT scores with information from multiple sequence alignments, phylogenetic trees, and ancestral reconstruction. The results of comprehensive experiments on carefully constructed sets of variants demonstrated that PHACTboost can outperform 40 prevalent pathogenicity predictors reported in the dbNSFP, including conventional tools, meta-predictors, and deep learning-based approaches as well as state-of-the-art tools, AlphaMissense, EVE, and CPT-1. The superiority of PHACTboost over these methods was particularly evident in case of hard variants for which different pathogenicity predictors offered conflicting results. We provide predictions of 215 million amino acid alterations over 20,191 proteins. PHACTboost can improve our understanding of genetic diseases and facilitate more accurate diagnoses.
DOI: 10.6084/m9.figshare.25467643
title: Sagittal Balance Parameters and Proximal Junctional Kyphosis in Adolescent Idiopathic Scoliosis: Dataset and Results.

description: To review and evaluate multiple preoperative and postoperative sagittal parameters and their association with the risk of developing proximal junctional kyphosis (PJK) in patients with adolescent idiopathic scoliosis (AIS) who undergo correction surgery. We performed a systematic search in December 2022 in PubMed, Embase and the Cochrane Library to retrieve all the studies relevant to our research. After the study selection and data extraction following PRISMA guidelines, RevMan 5.3 was used for statistical analysis. All the analyzed factors were evaluated by using odds ratios and weighted mean differences with 95% confidence intervals. Moreover, the meta-analysis of proportions via MedCalc was used for analyzing quantitative data from the studies. 22 studies were included in our meta-analysis. All the available values of sagittal parameters were evaluated. Among all the potential risk factors, higher preoperative thoracic kyphosis (Test for overall effect Z = 11.79, p &lt; 0.00001), higher preoperative sagittal vertical axis (SVA) (test for overall effect Z = 11.19, p &lt; 0.00001), greater thoracic kyphosis change post-op. compared to pre-op. (test for overall effect Z = 6.02, p &lt; 0.00001), increased postoperative lumbar lordosis (test for overall effect Z = 3.65, p = 0.0003), higher post-op. SVA (test for overall effect Z = 24.93, p &lt; 0.00001) and a larger pelvic incidence/lumbar lordosis (PI/LL) mismatch (test for overall effect Z = 20.50, p &lt; 0.00001) were found to be the risk factors for PJK after AIS surgery. Moreover, a decreased rod contour angle (RCA) (test for overall effect Z = 3.79, p &lt; 0.0002) and higher proximal junctional angle–rod contour angle (PJA-RCA) (test for overall effect Z = 39.18, p &lt; 0.00001) play a significant role in the risk of developing PJK after AIS correction.
DOI: 10.6084/m9.figshare.25467643.v1
title: Sagittal Balance Parameters and Proximal Junctional Kyphosis in Adolescent Idiopathic Scoliosis: Dataset and Results.

description: To review and evaluate multiple preoperative and postoperative sagittal parameters and their association with the risk of developing proximal junctional kyphosis (PJK) in patients with adolescent idiopathic scoliosis (AIS) who undergo correction surgery. We performed a systematic search in December 2022 in PubMed, Embase and the Cochrane Library to retrieve all the studies relevant to our research. After the study selection and data extraction following PRISMA guidelines, RevMan 5.3 was used for statistical analysis. All the analyzed factors were evaluated by using odds ratios and weighted mean differences with 95% confidence intervals. Moreover, the meta-analysis of proportions via MedCalc was used for analyzing quantitative data from the studies. 22 studies were included in our meta-analysis. All the available values of sagittal parameters were evaluated. Among all the potential risk factors, higher preoperative thoracic kyphosis (Test for overall effect Z = 11.79, p &lt; 0.00001), higher preoperative sagittal vertical axis (SVA) (test for overall effect Z = 11.19, p &lt; 0.00001), greater thoracic kyphosis change post-op. compared to pre-op. (test for overall effect Z = 6.02, p &lt; 0.00001), increased postoperative lumbar lordosis (test for overall effect Z = 3.65, p = 0.0003), higher post-op. SVA (test for overall effect Z = 24.93, p &lt; 0.00001) and a larger pelvic incidence/lumbar lordosis (PI/LL) mismatch (test for overall effect Z = 20.50, p &lt; 0.00001) were found to be the risk factors for PJK after AIS surgery. Moreover, a decreased rod contour angle (RCA) (test for overall effect Z = 3.79, p &lt; 0.0002) and higher proximal junctional angle–rod contour angle (PJA-RCA) (test for overall effect Z = 39.18, p &lt; 0.00001) play a significant role in the risk of developing PJK after AIS correction.
DOI: 10.6084/m9.figshare.4900394
title: Metamorphic phase equilibria modelling and zircon U–Pb geochronology of ultrahigh-temperature cordierite granulites from the Madurai Block, India: implications for hot Gondwana crust

description: The Madurai Block (MB) is the largest Precambrian crustal block in the Southern Granulite Terrane (SGT) of India and hosts rare cordierite- and orthopyroxene-bearing granulites. Investigations based on field study, petrology, metamorphic <i>P</i><i>–</i><i>T</i> estimation, and detrital zircon geochronology of these granulites are crucial for understanding the ultrahigh-temperature (UHT) metamorphism and crustal evolution in this block. Here we investigate the petrology and zircon U–Pb geochronology of two new localities of cordierite granulites at Kottayam (southern MB; SMB) and Munnar (central MB; CMB). Petrographic observations and phase equilibria modelling results indicate that these rocks experienced UHT metamorphism with the peak temperature exceeding 950℃ and involving clockwise <i>P–T</i> paths. The prograde mineral assemblages define the <i>P</i><i>–</i><i>T</i> conditions of 6.8–8.7 kbar and 750–875℃. The peak conditions are estimated using pseudosection modelling and geothermometry, which yield <i>P</i><i>–</i><i>T</i> estimates of 7.1–9.1 kbar and 955–985℃. The retrograde cooling and decompression are inferred at 860–790℃ and &lt;6.5 kbar, respectively. Partial melting played an important role during metamorphism and contributed to the overgrowth around detrital zircons. The melt production process was probably related to biotite dehydration melting, and was mainly triggered by heating, with or without the effect of decompression. Detrital zircons in cordierite granulite samples from the two localities show similar age distributions and have dominantly Neoproterozoic ages (1024–760 Ma). The zircon cores show oscillatory zoning with a wide range of Th/U ratios (0.01–0.96), implying complex protoliths from multiple Neoproterozoic provenances from both southern and central domains of the MBs. Zircon rims and homogeneous bright zircons yield mean ages of 549 ± 5 Ma, 536 ± 6 Ma, and 544 ± 6 Ma, which are interpreted to represent zircon overgrowths during the post-peak cooling and decompression process. The timing of peak UHT metamorphism is constrained as 549–599 Ma, which coincides with the assembly of the Gondwana supercontinent.
DOI: 10.6084/m9.figshare.4900394.v1
title: Metamorphic phase equilibria modelling and zircon U–Pb geochronology of ultrahigh-temperature cordierite granulites from the Madurai Block, India: implications for hot Gondwana crust

description: The Madurai Block (MB) is the largest Precambrian crustal block in the Southern Granulite Terrane (SGT) of India and hosts rare cordierite- and orthopyroxene-bearing granulites. Investigations based on field study, petrology, metamorphic <i>P</i><i>–</i><i>T</i> estimation, and detrital zircon geochronology of these granulites are crucial for understanding the ultrahigh-temperature (UHT) metamorphism and crustal evolution in this block. Here we investigate the petrology and zircon U–Pb geochronology of two new localities of cordierite granulites at Kottayam (southern MB; SMB) and Munnar (central MB; CMB). Petrographic observations and phase equilibria modelling results indicate that these rocks experienced UHT metamorphism with the peak temperature exceeding 950℃ and involving clockwise <i>P–T</i> paths. The prograde mineral assemblages define the <i>P</i><i>–</i><i>T</i> conditions of 6.8–8.7 kbar and 750–875℃. The peak conditions are estimated using pseudosection modelling and geothermometry, which yield <i>P</i><i>–</i><i>T</i> estimates of 7.1–9.1 kbar and 955–985℃. The retrograde cooling and decompression are inferred at 860–790℃ and &lt;6.5 kbar, respectively. Partial melting played an important role during metamorphism and contributed to the overgrowth around detrital zircons. The melt production process was probably related to biotite dehydration melting, and was mainly triggered by heating, with or without the effect of decompression. Detrital zircons in cordierite granulite samples from the two localities show similar age distributions and have dominantly Neoproterozoic ages (1024–760 Ma). The zircon cores show oscillatory zoning with a wide range of Th/U ratios (0.01–0.96), implying complex protoliths from multiple Neoproterozoic provenances from both southern and central domains of the MBs. Zircon rims and homogeneous bright zircons yield mean ages of 549 ± 5 Ma, 536 ± 6 Ma, and 544 ± 6 Ma, which are interpreted to represent zircon overgrowths during the post-peak cooling and decompression process. The timing of peak UHT metamorphism is constrained as 549–599 Ma, which coincides with the assembly of the Gondwana supercontinent.
DOI: 10.6084/m9.figshare.4905758
title: RNA-seq raw data of MS-C_1_1

description: File 1 of RNA-seq raw data of C48-2 biological replicate 1 spikelets at mononuclear stage. Paired-end sequencing strategy was applied on the Illumina HiSeq 4000 sequencing platform.
DOI: 10.6084/m9.figshare.4905758.v1
title: RNA-seq raw data of MS-C_1_1

description: File 1 of RNA-seq raw data of C48-2 biological replicate 1 spikelets at mononuclear stage. Paired-end sequencing strategy was applied on the Illumina HiSeq 4000 sequencing platform.
DOI: 10.6084/m9.figshare.4906679
title: RNA-seq raw data of MS-C_2_1

description: File 1 of RNA-seq raw data of C48-2 biological replicate 2 spikelets at mononuclear stage. Paired-end sequencing strategy was applied on the Illumina HiSeq 4000 sequencing platform.
DOI: 10.6084/m9.figshare.4906679.v1
title: RNA-seq raw data of MS-C_2_1

description: File 1 of RNA-seq raw data of C48-2 biological replicate 2 spikelets at mononuclear stage. Paired-end sequencing strategy was applied on the Illumina HiSeq 4000 sequencing platform.
DOI: 10.6084/m9.figshare.4906871
title: RNA-seq raw data of MS-N_1_2

description: File 2 of
RNA-seq raw data of N48-2 biological replicate 1 spikelets at mononuclear
stage. Paired-end sequencing strategy was applied on the Illumina HiSeq 4000
sequencing platform.<br>
DOI: 10.6084/m9.figshare.4906871.v1
title: RNA-seq raw data of MS-N_1_2

description: File 2 of
RNA-seq raw data of N48-2 biological replicate 1 spikelets at mononuclear
stage. Paired-end sequencing strategy was applied on the Illumina HiSeq 4000
sequencing platform.<br>