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opencc-by-4.0Jul 2020View details →

Inspirations and equations derived from VAM for mechanics of student life

The lecture discusses the application of variational principles in mechanics and life. Starting with an overview of the development of ideas of variational principles, the lecture addresses various aspects of modeling in aerospace structures. In particular, the lecture focused on the modeling of composite materials using the Variational Asymptotic Method (VAM). The lecture was delivered by Prof. Dineshkumar Harursampath and hosted by Dr. Ajay B Harish. The session Q&A was transcribed by Dr. Ajay B Harish.

opencc-zeroAug 2020View details →

Ultrasound-derived changes in thickness of human ankle plantar flexor muscles during walking and running are not homogeneous along the muscle mid-belly region

Skeletal muscle thickness is a valuable indicator of several aspects of a muscle's functional capabilities. We used computational analysis of ultrasound images, recorded from 10 humans walking and running at a range of speeds (0.7 – 5.0 m s-1), to quantify interactions in thickness change between three ankle plantar flexor muscles (soleus, medial and lateral gastrocnemius) and quantify thickness changes at multiple muscle sites within each image. Statistical analysis of thickness change as a function of stride cycle (1d statistical parametric mapping) revealed significant differences between soleus and both gastrocnemii across the whole stride cycle as they bulged within the shared anatomical space. Within each muscle, changes in thickness differed between measurement sites but not locomotor condition. For some of the stride, thickness measures taken from the distal-mid image region represented the mean muscle thickness, which may therefore be a reliable region for these measures. Assumptions that muscle thickness is constant during a task, often made in musculoskeletal models, do not hold for the muscles and locomotor conditions studied here and researchers should not assume that a single thickness measure, from one point of the stride cycle or a static image, represents muscle thickness during dynamic movements.

opencc-zeroAug 2020View details →

Rest-task modulation of fMRI-derived global signal topography is mediated by transient co-activation patterns

Recent resting-state fMRI studies have revealed that the global signal (GS) exhibits a non-uniform spatial distribution across the gray matter. Whether this topography is informative remains largely unknown. We therefore tested rest-task modulation of global signal topography by analyzing static global signal correlation and dynamic co-activation patterns in a large sample of fMRI dataset (n=837) from the Human Connectome Project. The GS topography in the resting-state and in seven different tasks was first measured by correlating the global signal with the local timeseries (GSCORR). In the resting state, high GSCORR was observed mainly in the primary sensory and motor regions, while low GSCORR was seen in the association brain areas. This pattern changed during the seven tasks, with mainly decreased GSCORR in sensorimotor cortex. Importantly, this rest-task modulation of GSCORR could be traced to transient co-activation patterns at the peak period of global signal (GS-peak). By comparing the topography of GSCORR and respiration effects, we observed that the topography of respiration mimicked the topography of global signal in the resting-state whereas both differed during the task states; due to such partial dissociation, we assume that GSCORR could not be equated with a respiration effect. Finally, rest-task modulation of GS topography could not be exclusively explained by other sources of physiological noise. Together, we here demonstrate the informative nature of global signal topography by showing its rest-task modulation, the underlying dynamic co-activation patterns, and its partial dissociation from respiration effects during task states.

opencc-by-4.0Aug 2020View details →

Satellite-derived long-term estimates of full-coverage PM1 concentrations across China based on a stacking decision tree model

The open data uploaded by Rui Li

opencc-zeroAug 2020View details →

Data from: Simultaneous measurement of excitation-contraction coupling parameters identifies mechanisms underlying contractile responses of hiPSC-derived cardiomyocytes

Cardiomyocytes from human induced pluripotent stem cells (hiPSC-CMs) are increasingly recognized as valuable for determining the effects of drugs on ion channels but they do not always accurately predict contractile responses of the human heart. This is in part attributable to their immaturity but the sensitivity of measurement tools may also be limiting. Measuring action potential, calcium flux or contraction individually misses critical information that is captured when interrogating the complete excitation-contraction coupling cascade simultaneously. Here, we develop an hypothesis-based statistical algorithm that identifies mechanisms of action. We design and build a high-speed optical system to measure action potential, cytosolic calcium and contraction simultaneously using fluorescent sensors. These measurements are automatically processed, quantified and then assessed by the algorithm. Multiplexing these three critical physical features of hiPSC-CMs allows identification of all major drug classes affecting contractility with detection sensitivities higher than individual measurement of action potential, cytosolic calcium or contraction.

Figure 8 in The feeding strategy of the predatory Gyrineum natator (Gastropoda: Neotaenioglossa: Ranellidae) in the Cape d'Aguilar Marine Reserve, Hong Kong, with a review of sulphuric acid use in prey access by the Tonnoidea and experimentally derived estimates of consumption

Figure 8. Gyrineum natator. Phase-contrast micrographs of the salivary glands of three individuals following treatment with barium chloride for 50 minutes. (A–C) Three untreated controls; (D–F) three treated individuals.

Figure 2 in The feeding strategy of the predatory Gyrineum natator (Gastropoda: Neotaenioglossa: Ranellidae) in the Cape d'Aguilar Marine Reserve, Hong Kong, with a review of sulphuric acid use in prey access by the Tonnoidea and experimentally derived estimates of consumption

Figure 2. Gyrineum natator. The holes made in four shells (A–D) of Saccostrea mordax by individuals held in experimental aquaria. Only A shows a near-circular access hole, but other irregular ones (B–D) appear to have been created by acid attack as there would be no need for the radula alone to make such large holes.

Figure 4 in The feeding strategy of the predatory Gyrineum natator (Gastropoda: Neotaenioglossa: Ranellidae) in the Cape d'Aguilar Marine Reserve, Hong Kong, with a review of sulphuric acid use in prey access by the Tonnoidea and experimentally derived estimates of consumption

Figure 4. Gyrineum natator. The relationship between shell height (in mm) and wet tissue weights [Log(W + 1) (in grams)] of seven individuals including the two experimental animals with shell heights of 34.6 and 33.6 mm.

Figure 5 in The feeding strategy of the predatory Gyrineum natator (Gastropoda: Neotaenioglossa: Ranellidae) in the Cape d'Aguilar Marine Reserve, Hong Kong, with a review of sulphuric acid use in prey access by the Tonnoidea and experimentally derived estimates of consumption

Figure 5. Gyrineum natator. The accumulated % wet tissue weights of oyster tissues consumed by the two approximately equal-sized individuals of G. natator held in filtered and unfiltered seawater aquaria.

Figure 1 in The feeding strategy of the predatory Gyrineum natator (Gastropoda: Neotaenioglossa: Ranellidae) in the Cape d'Aguilar Marine Reserve, Hong Kong, with a review of sulphuric acid use in prey access by the Tonnoidea and experimentally derived estimates of consumption

Figure 1. Gyrineum natator. The living animal as seen from the ventral aspect crawling on an upturned sheet of glass immersed in seawater, and showing the extended proboscis.

Figure 7 in The feeding strategy of the predatory Gyrineum natator (Gastropoda: Neotaenioglossa: Ranellidae) in the Cape d'Aguilar Marine Reserve, Hong Kong, with a review of sulphuric acid use in prey access by the Tonnoidea and experimentally derived estimates of consumption

Figure 7. Gyrineum natator. (A) A transverse section through one of the paired salivary glands and the associated pharyngeal (oesophageal) gland; (B) developing salivary gland tubules at the outer edge of the salivary gland; (C) fully developed sulphuric acid producing salivary gland cells; (D) a transverse section through a pharyngeal (oesophageal) gland tubule; (E) a transverse section through the salivary gland/pharyngeal gland duct.

Figure 3 in The feeding strategy of the predatory Gyrineum natator (Gastropoda: Neotaenioglossa: Ranellidae) in the Cape d'Aguilar Marine Reserve, Hong Kong, with a review of sulphuric acid use in prey access by the Tonnoidea and experimentally derived estimates of consumption

Figure 3. Saccostrea mordax. The relationship between total weight [Log(TotW + 1) (in grams)] and wet tissue weights [Log(W + 1) (in grams)] of the 34 oyster individuals.

Figure 9 in The feeding strategy of the predatory Gyrineum natator (Gastropoda: Neotaenioglossa: Ranellidae) in the Cape d'Aguilar Marine Reserve, Hong Kong, with a review of sulphuric acid use in prey access by the Tonnoidea and experimentally derived estimates of consumption

Figure 9. Gyrineum natator. Phase-contrast micrographs of (A) the salivary gland and (B) the pharyngeal (oesophageal) gland after treatment with barium chloride for 50 minutes.

Figure 6 in The feeding strategy of the predatory Gyrineum natator (Gastropoda: Neotaenioglossa: Ranellidae) in the Cape d'Aguilar Marine Reserve, Hong Kong, with a review of sulphuric acid use in prey access by the Tonnoidea and experimentally derived estimates of consumption

Figure 6. Gyrineum natator. The foregut anatomy, as seen from the dorsal aspect, and showing the hypertrophied and paired salivary glands and the single pharyngeal (oesophageal) gland. Redrawn after Taylor (1998).

opencc-by-4.0Aug 2020View details →

Genome sequencing of P. tricornutum mother and daughter cultures derived from single cell and separated by 30 days of proliferation - processed datasets

Genome sequencing of P. tricornutum mother and daughter cultures derived from single cell and separated by 30 days of proliferation - processed datasets. Raw data for this experiment are available at https://www.ncbi.nlm.nih.gov/bioproject/PRJNA658224.   Please note that the naming of files differs from the general description on /www.ncbi.nlm.nih.gov/bioproject website and in related publication: Instead of MC1-3, the processed datasets are labelled Sc1-3 Instead of DC1.1; DC1.2 and DC1.3, the processed datasets are labelled Sc11, Sc12 and Sc14 respectively Instead of DC2.1; DC2.2 and DC2.3, the processed datasets are labelled Sc21, Sc22 and Sc24 respectively Instead of DC3.1; DC3.2 and DC3.3, the processed datasets are labelled Sc31, Sc32 and Sc33 respectively Available datasets:  .bam files with ILLUMINA reads aligned to the reference P. tricornutum v2 genome used for SNP calling  .vcf files for individual samples with SNPs called using GATK3.7.0 joint_genotyping_cohort.vcf file with SNPs called jointly for all samples using GATK4.2.1    Description of the experiment:  Whole-genome Illumina sequencing of mother and daughter cultures derived from single cell to reveal genomic changes occurring within 30 day time frame. Three independent single cells were isolated from CCAP 1055/1 culture (sample label: Pt1) to start mother cultures (MC1; MC2; MC3 . On day 30 after mother culture isolation (T1 time point), three daughter cells were isolated from each mother culture forming cultures DC11-DC33. Part of mother cultures and CCAP 1055/1 culture were harvested at T1 (Samples: Pt1T1; MC1T1; MC2T1; MC3T1) . After another 30 days (T2 time point), all cultures were harvested (Samples: Pt1T2; mother culture MC1T2 and respective daughter cultures DC11, DC12 and DC13 ; mother culture MC2T2 and respective daughter cultures DC21, DC22 and DC23; mother culture MC3T1 and respective daughter cultures DC31, DC32, DC33).

opencc-by-4.0Dec 2019View details →

Data for "Current challenges for unseen-epitope TCR interaction prediction and a new perspective derived from image classification" (ImRex)

Repository containing the different experiments described in the manuscript titled: "Current challenges for epitope-agnostic TCR interaction prediction and a new perspective derived from image classification". Publication DOI: TBA Originally appeared as a preprint on bioRxiv: <a href="https://doi.org/10.1101/2019.12.18.880146">https://doi.org/10.1101/2019.12.18.880146</a>. Contains: <ul> <li>Trained model files (.h5)</li> <li>Associated train and validation datasets for each model.</li> <li>Learning curves and evaluation metrics.</li> <li>Log files with training and data arguments (full training scripts are available in GitHub repository).</li> <li>Comparisons between different models.</li> <li>Complete raw and processed datasets (also available in the associated GitHub repository).</li> </ul> Please refer to the associated GitHub repository (<a href="https://github.com/pmoris/ImRex">https://github.com/pmoris/ImRex</a>) for more information on the directory structure and contents, as well as the scripts that generated these output files. Contents: <ul> <li> <code>data.zip</code>: Contains raw and preprocessed datasets. READMEs in subdirectory describe the data sources and preprocessing steps. Please refer to the associated GitHub repository for the specific scripts that generated these files. Note that the full training and test sets (i.e. containing both positive and negative examples) are stored separately for each model/CV iteration in the <code>models</code> archives. </li> <li> <code>models-main.zip</code>: contains the trained models and evaluation metrics for the main different experiments described in the bash and pbs scripts in <code>./src/scripts/hpc_scripts</code>. Log files for the experiments outlined here can be found in <code>./src/scripts/hpc_scripts</code>. </li> <li> <code>models-full.zip</code>: contains models that were trained on the complete VDJdb dataset without cross-validation, filtered on human TRB data, no 10x data and restricted to 10-20 (CDR3) or 8-11 (epitope) amino acid residues, with negatives that were generated by shuffling (i.e. sampling an negative epitope for each positive CDR3 sequence). One set of models uses downsampling to reduce the most abundant epitopes down to 400 pairs each, the other one does not use any downsampling. These models were also used for evaluating on the external Adaptive dataset, as outlined in <code>./src/scripts/evaluate/evaluate_adaptive.sh</code>, and the TRA subset of sequences (<code>./src/scripts/evaluate/evaluate_tra.sh</code>). </li> <li> <code>models-decoyfit.zip</code>: contains models that were trained on true data, but evaluated on data where epitopes were replaced by decoys. </li> <li> <code>models-padded-epitoperatio.zip</code>: contains a quick test of trained models (padded/interaction map) that use a different type of negative shuffling, see docstrings in <code>./src/processing/negative_sampler.py</code> for more info. </li> <li> <code>models-repeat-local.zip</code>: contains a number of repeated runs from <code>models-main</code>, used to estimate variability in model performance for multiple identical runs. </li> <li> <code>comparisons.zip</code>: contains comparison directories, each consisting of two or more model output directories, that contrast the performance metrics of the models. These outputs were generated by using the <code>./src/scripts/evaluate/visualize.py</code> script, or by using the oneliners in <code>./src/scripts/evaluate/visualise.sh</code>, which can operate on the entire comparisons directory at once. </li> </ul> Note that any file paths described here are in reference to the associated GitHub repository (<a href="https://github.com/pmoris/ImRex">https://github.com/pmoris/ImRex</a>). Overview of different experiments: <ul> <li>Two main architectures were compared: the interaction map (or <code>padded</code>) CNN and a dual input CNN based on NetTCR (<code>nettcr</code>).</li> <li>Two different cross-validation strategies were used: a 5x repeated 5-fold CV (<code>repeated5fold</code>) and an epitope-grouped CV (<code>epitope_grouped</code>).</li> <li>The different dataset subsets are labelled as follows. Check the Makefile's <code>preprocess-vdjdb-aug-2019</code> command (and the underlying script <code>./src/scripts/preprocessing/preprocess_vdjdb.py</code>) for a more thorough overview of the different filtering options. <ul> <li><code>mhci</code>: only MHCI class presented epitopes.</li> <li><code>trb</code>: only TRB CDR3 sequences.</li> <li><code>tra</code>: only TRA CDR3 sequences.</li> <li><code>tratrb</code>: both types of CDR3 sequences.</li> <li><code>down</code>: moderate downsampling of most abundant epitopes to 1000 pairs.</li> <li><code>down400</code>: strong downsampling of most abundant epitopes to 400 pairs.</li> <li><code>decoy</code>: decoy epitope data.</li> <li><code>reg001</code>: regularization factor 0.01 (only for padded/interaction type models, fixed value)</li> </ul> </li> <li>Two different methods of generating negative TCR-epitope pairs were used: shuffling of positive pairs, i.e. sampling a single epitope from the positive pairs for each CDR3 sequence (<code>shuffle</code>), and sampling CDR3s from a reference repertoire (<code>negref</code>).</li> <li>The batch size is labelled as <code>b32</code> = a batch size of 32.</li> <li>The learning rate was always 0.0001 (<code>lre4</code>) or 0.001 (<code>lre3</code>).</li> </ul>

opencc-by-4.0Dec 2020View details →

Mesenchymal stem cell-derived extracellular vesicles reduce senescence and extend healthspan in mouse models of aging.

Source data file

opencc-zeroDec 2020View details →

Atlantic walrus signal latitudinal differences in the long-term decline of sea ice-derived carbon to benthic fauna in the Canadian Arctic

Climate change is altering the biogeochemical and physical characteristics of the Arctic marine environment, which impacts sea ice algal and phytoplankton bloom dynamics and the vertical transport of these carbon sources to benthic communities. Little is known about whether the contribution of sea ice-derived carbon to benthic fauna and nitrogen cycling has changed over multiple decades in concert with receding sea ice. We combined compound-specific stable isotope analysis of amino acids with highly-branched isoprenoid diatom lipid biomarkers using archived (1982-2016) tissue of benthivorous Atlantic walrus to examine temporal trends of sea ice-derived carbon, nitrogen isotope baseline and trophic position of Atlantic walrus at high- and mid-latitudes in the Canadian Arctic. Associated with an 18% sea ice decline in the mid-Arctic, sea ice-derived carbon contribution to Atlantic walrus decreased by 75% suggesting a strong decoupling of sea ice-benthic habitats. In contrast, a nearly exclusive amount of sea ice-derived carbon was maintained in high-Arctic Atlantic walrus (98% in 1996 and 89% in 2006) despite a similar percentage in sea ice reduction. Nitrogen isotope baseline or the trophic position of Atlantic walrus did not change over time at either location. These findings indicate spatial differences in the restructuring of carbon energy sources utilized by Atlantic walrus and their benthic prey and in turn, a change in Arctic marine ecosystem functioning between sea ice-pelagic-benthic habitats.

opencc-by-4.0Jan 2021View details →

Figure 8 from: Bulbul MZH, Chowdhury TS, Misbah MMH, Ferdous J, Dey S, Hasan I, Fujii Y, Ozeki Y, Kawsar SMA (2021) Synthesis of new series of pyrimidine nucleoside derivatives bearing the acyl moieties as potential antimicrobial agents. Pharmacia 68(1): 23-34. https://doi.org/10.3897/pharmacia.68.e56543

Figure 8 Structures of compounds 7 (octanoyl derivative), 9 (myristoyl derivative), and 14 (dichloroacetyl derivative).