ResearchPad - 7 https://www.researchpad.co Default RSS Feed en-us © 2020 Newgen KnowledgeWorks <![CDATA[Voltage Imaging of Cortical Oscillations in Layer 1 with Two-Photon Microscopy]]> https://www.researchpad.co/article/elastic_article_13341 Membrane voltage oscillations in layer 1 (L1) of primary sensory cortices might be important indicators of cortical gain control, attentional focusing, and signal integration. However, electric field recordings are hampered by the low seal resistance of electrodes close to the brain surface. To study L1 membrane voltage oscillations, we synthesized a new voltage-sensitive dye, di1-ANNINE (anellated hemicyanine)-6plus, that can diffuse into tissue. We applied it with a new surgery, leaving the dura intact but allowing injection of large quantities of staining solution, and imaged cortical membrane potential oscillations with two-photon microscopy depth-resolved (25–100 μm below dura) in anesthetized and awake mice. We found delta (0.5–4 Hz), theta (4–10 Hz), low beta (10–20 Hz), and low gamma (30–40 Hz) oscillations. All oscillations were stronger in awake animals. While the power of delta, theta, and low beta oscillations increased with depth, the power of low gamma was more constant throughout L1. These findings identify L1 as an important coordination hub for the dynamic binding process of neurons mediated by oscillations.

]]>
<![CDATA[3D Printable Device for Automated Operant Conditioning in the Mouse]]> https://www.researchpad.co/article/elastic_article_8072 Operant conditioning (OC) is a classical paradigm and a standard technique used in experimental psychology in which animals learn to perform an action to achieve a reward. By using this paradigm, it is possible to extract learning curves and measure accurately reaction times (RTs). Both these measurements are proxy of cognitive capabilities and can be used to evaluate the effectiveness of therapeutic interventions in mouse models of disease. Here, we describe a fully 3D printable device that is able to perform OC on freely moving mice, while performing real-time tracking of the animal position. We successfully trained six mice, showing stereotyped learning curves that are highly reproducible across mice and reaching >70% of accuracy after 2 d of conditioning. Different products for OC are commercially available, though most of them do not provide customizable features and are relatively expensive. This data demonstrate that this system is a valuable alternative to available state-of-the-art commercial devices, representing a good balance between performance, cost, and versatility in its use.

]]>
<![CDATA[Microfluidic automated plasmid library enrichment for biosynthetic gene cluster discovery]]> https://www.researchpad.co/article/N77bfd511-0a9f-457b-9ccb-92d6875a2225 Microbial biosynthetic gene clusters are a valuable source of bioactive molecules. However, because they typically represent a small fraction of genomic material in most metagenomic samples, it remains challenging to deeply sequence them. We present an approach to isolate and sequence gene clusters in metagenomic samples using microfluidic automated plasmid library enrichment. Our approach provides deep coverage of the target gene cluster, facilitating reassembly. We demonstrate the approach by isolating and sequencing type I polyketide synthase gene clusters from an Antarctic soil metagenome. Our method promotes the discovery of functional-related genes and biosynthetic pathways.

]]>
<![CDATA[New candidates for regulated gene integrity revealed through precise mapping of integrative genetic elements]]> https://www.researchpad.co/article/N249fead6-5cee-4399-8f76-356c51ff87d2 Integrative genetic elements (IGEs) are mobile multigene DNA units that integrate into and excise from host bacterial genomes. Each IGE usually targets a specific site within a conserved host gene, integrating in a manner that preserves target gene function. However, a small number of bacterial genes are known to be inactivated upon IGE integration and reactivated upon excision, regulating phenotypes of virulence, mutation rate, and terminal differentiation in multicellular bacteria. The list of regulated gene integrity (RGI) cases has been slow-growing because IGEs have been challenging to precisely and comprehensively locate in genomes. We present software (TIGER) that maps IGEs with unprecedented precision and without attB site bias. TIGER uses a comparative genomic, ping-pong BLAST approach, based on the principle that the IGE integration module (i.e. its int-attP region) is cohesive. The resultant IGEs from 2168 genomes, along with integrase phylogenetic analysis and gene inactivation tests, revealed 19 new cases of genes whose integrity is regulated by IGEs (including dut, eccCa1, gntT, hrpB, merA, ompN, prkA, tqsA, traG, yifB, yfaT and ynfE), as well as recovering previously known cases (in sigK, spsM, comK, mlrA and hlb genes). It also recovered known clades of site-promiscuous integrases and identified possible new ones.

]]>
<![CDATA[S3norm: simultaneous normalization of sequencing depth and signal-to-noise ratio in epigenomic data]]> https://www.researchpad.co/article/N0506ba1c-997c-47e6-a79c-930edbb67ce4 Quantitative comparison of epigenomic data across multiple cell types or experimental conditions is a promising way to understand the biological functions of epigenetic modifications. However, differences in sequencing depth and signal-to-noise ratios in the data from different experiments can hinder our ability to identify real biological variation from raw epigenomic data. Proper normalization is required prior to data analysis to gain meaningful insights. Most existing methods for data normalization standardize signals by rescaling either background regions or peak regions, assuming that the same scale factor is applicable to both background and peak regions. While such methods adjust for differences in sequencing depths, they do not address differences in the signal-to-noise ratios across different experiments. We developed a new data normalization method, called S3norm, that normalizes the sequencing depths and signal-to-noise ratios across different data sets simultaneously by a monotonic nonlinear transformation. We show empirically that the epigenomic data normalized by our method, compared to existing methods, can better capture real biological variation, such as impact on gene expression regulation.

]]>
<![CDATA[Exonuclease combinations reduce noises in 3D genomics technologies]]> https://www.researchpad.co/article/Nd17c3c3c-63e4-4718-a7fb-220bef67ac3c Chromosome conformation-capture technologies are widely used in 3D genomics; however, experimentally, such methods have high-noise limitations and, therefore, require significant bioinformatics efforts to extract reliable distal interactions. Miscellaneous undesired linear DNAs, present during proximity-ligation, represent a main noise source, which needs to be minimized or eliminated. In this study, different exonuclease combinations were tested to remove linear DNA fragments from a circularized DNA preparation. This method efficiently removed linear DNAs, raised the proportion of annulation and increased the valid-pairs ratio from ∼40% to ∼80% for enhanced interaction detection in standard Hi-C. This strategy is applicable for development of various 3D genomics technologies, or optimization of Hi-C sequencing efficiency.

]]>
<![CDATA[Quantitative comparison of within-sample heterogeneity scores for DNA methylation data]]> https://www.researchpad.co/article/N75e6ae97-0171-4a6f-8b66-f518ee86dacf DNA methylation is an epigenetic mark with important regulatory roles in cellular identity and can be quantified at base resolution using bisulfite sequencing. Most studies are limited to the average DNA methylation levels of individual CpGs and thus neglect heterogeneity within the profiled cell populations. To assess this within-sample heterogeneity (WSH) several window-based scores that quantify variability in DNA methylation in sequencing reads have been proposed. We performed the first systematic comparison of four published WSH scores based on simulated and publicly available datasets. Moreover, we propose two new scores and provide guidelines for selecting appropriate scores to address cell-type heterogeneity, cellular contamination and allele-specific methylation. Most of the measures were sensitive in detecting DNA methylation heterogeneity in these scenarios, while we detected differences in susceptibility to technical bias. Using recently published DNA methylation profiles of Ewing sarcoma samples, we show that DNA methylation heterogeneity provides information complementary to the DNA methylation level. WSH scores are powerful tools for estimating variance in DNA methylation patterns and have the potential for detecting novel disease-associated genomic loci not captured by established statistics. We provide an R-package implementing the WSH scores for integration into analysis workflows.

]]>
<![CDATA[FaceLift: a transparent deep learning framework to beautify urban scenes]]> https://www.researchpad.co/article/N5fd42e94-d295-4df2-a0e6-a8f34580eb5a

In the area of computer vision, deep learning techniques have recently been used to predict whether urban scenes are likely to be considered beautiful: it turns out that these techniques are able to make accurate predictions. Yet they fall short when it comes to generating actionable insights for urban design. To support urban interventions, one needs to go beyond predicting beauty, and tackle the challenge of recreating beauty. Unfortunately, deep learning techniques have not been designed with that challenge in mind. Given their ‘black-box nature’, these models cannot be directly used to explain why a particular urban scene is deemed to be beautiful. To partly fix that, we propose a deep learning framework (which we name FaceLift1) that is able to both beautify existing urban scenes (Google Street Views) and explain which urban elements make those transformed scenes beautiful. To quantitatively evaluate our framework, we cannot resort to any existing metric (as the research problem at hand has never been tackled before) and need to formulate new ones. These new metrics should ideally capture the presence (or absence) of elements that make urban spaces great. Upon a review of the urban planning literature, we identify five main metrics: walkability, green spaces, openness, landmarks and visual complexity. We find that, across all the five metrics, the beautified scenes meet the expectations set by the literature on what great spaces tend to be made of. This result is further confirmed by a 20-participant expert survey in which FaceLift has been found to be effective in promoting citizen participation. All this suggests that, in the future, as our framework’s components are further researched and become better and more sophisticated, it is not hard to imagine technologies that will be able to accurately and efficiently support architects and planners in the design of the spaces we intuitively love.

]]>
<![CDATA[Genetically Engineering the Nervous System with CRISPR-Cas]]> https://www.researchpad.co/article/N89b130fe-b071-4045-87bc-ef4fdff57919

Visual Abstract

]]>
<![CDATA[Compressor performance modelling method based on support vector machine nonlinear regression algorithm]]> https://www.researchpad.co/article/N59293dd7-0672-4dde-872e-ac991161ef97

To overcome the difficulty of having only part of compressor characteristic maps including on-design operating point, and accurately calculate compressor thermodynamic performance under variable working conditions, this paper proposes a novel compressor performance modelling method based on support vector machine nonlinear regression algorithm. It is compared with the other three neural network algorithms (i.e. back propagation (BP), radial basis function (RBF) and Elman neural networks) from the perspective of interpolation and extrapolation accuracy as well as calculation time, to prove the validity of the proposed method. Application analyses indicate that the proposed method has better interpolation and extrapolation performance than the other three neural networks. In terms of flow characteristic map representation, the root mean square error (RMSE) of the extrapolation performance at higher and lower speed operating area by the proposed method is 0.89% and 2.57%, respectively. And the total RMSE by the proposed method is 2.72%, which is more accurate by 47% than the Elman algorithm. For efficiency characteristic map representation, the RMSE of the extrapolation performance at higher and lower speed operating area by the proposed method is 2.85% and 1.22%, respectively. And the total RMSE by the proposed method is 1.81%, which is more accurate by 35% than the BP algorithm. Moreover, the proposed method has better real-time performance compared with the other three neural network algorithms.

]]>
<![CDATA[Fluorescence-Based Quantitative Synapse Analysis for Cell Type-Specific Connectomics]]> https://www.researchpad.co/article/N2e023d82-2f86-4ffe-8cd8-0bf5755f3fa7

Abstract

Anatomical methods for determining cell type-specific connectivity are essential to inspire and constrain our understanding of neural circuit function. We developed genetically-encoded reagents for fluorescence-synapse labeling and connectivity analysis in brain tissue, using a fluorogen-activating protein (FAP)-coupled or YFP-coupled, postsynaptically-localized neuroligin-1 (NL-1) targeting sequence (FAP/YFPpost). FAPpost expression did not alter mEPSC or mIPSC properties. Sparse AAV-mediated expression of FAP/YFPpost with the cell-filling, red fluorophore dTomato (dTom) enabled high-throughput, compartment-specific detection of putative synapses across diverse neuron types in mouse somatosensory cortex. We took advantage of the bright, far-red emission of FAPpost puncta for multichannel fluorescence alignment of dendrites, FAPpost puncta, and presynaptic neurites in transgenic mice with saturated labeling of parvalbumin (PV), somatostatin (SST), or vasoactive intestinal peptide (VIP)-expressing neurons using Cre-reporter driven expression of YFP. Subtype-specific inhibitory connectivity onto layer 2/3 (L2/3) neocortical pyramidal (Pyr) neurons was assessed using automated puncta detection and neurite apposition. Quantitative and compartment-specific comparisons show that PV inputs are the predominant source of inhibition at both the soma and the dendrites and were particularly concentrated at the primary apical dendrite. SST inputs were interleaved with PV inputs at all secondary-order and higher-order dendritic branches. These fluorescence-based synapse labeling reagents can facilitate large-scale and cell-type specific quantitation of changes in synaptic connectivity across development, learning, and disease states.

]]>
<![CDATA[TypeTE: a tool to genotype mobile element insertions from whole genome resequencing data]]> https://www.researchpad.co/article/N7a29cdcb-85ee-4e7d-a0ed-c60567d34603

Abstract

Alu retrotransposons account for more than 10% of the human genome, and insertions of these elements create structural variants segregating in human populations. Such polymorphic Alus are powerful markers to understand population structure, and they represent variants that can greatly impact genome function, including gene expression. Accurate genotyping of Alus and other mobile elements has been challenging. Indeed, we found that Alu genotypes previously called for the 1000 Genomes Project are sometimes erroneous, which poses significant problems for phasing these insertions with other variants that comprise the haplotype. To ameliorate this issue, we introduce a new pipeline – TypeTE – which genotypes Alu insertions from whole-genome sequencing data. Starting from a list of polymorphic Alus, TypeTE identifies the hallmarks (poly-A tail and target site duplication) and orientation of Alu insertions using local re-assembly to reconstruct presence and absence alleles. Genotype likelihoods are then computed after re-mapping sequencing reads to the reconstructed alleles. Using a high-quality set of PCR-based genotyping of >200 loci, we show that TypeTE improves genotype accuracy from 83% to 92% in the 1000 Genomes dataset. TypeTE can be readily adapted to other retrotransposon families and brings a valuable toolbox addition for population genomics.

]]>
<![CDATA[IDR2D identifies reproducible genomic interactions]]> https://www.researchpad.co/article/Nef0ffebe-61d3-4baf-b291-7020b4b04c56

Abstract

Chromatin interaction data from protocols such as ChIA-PET, HiChIP and Hi-C provide valuable insights into genome organization and gene regulation, but can include spurious interactions that do not reflect underlying genome biology. We introduce an extension of the Irreproducible Discovery Rate (IDR) method called IDR2D that identifies replicable interactions shared by chromatin interaction experiments. IDR2D provides a principled set of interactions and eliminates artifacts from single experiments. The method is available as a Bioconductor package for the R community, as well as an online service at https://idr2d.mit.edu.

]]>
<![CDATA[Early warning of some notifiable infectious diseases in China by the artificial neural network]]> https://www.researchpad.co/article/Nf6c3af52-397d-45c0-99c9-48bcd25792d4

In order to accurately grasp the timing for the prevention and control of diseases, we established an artificial neural network model to issue early warning signals. The real-time recurrent learning (RTRL) and extended Kalman filter (EKF) methods were performed to analyse four types of respiratory infectious diseases and four types of digestive tract infectious diseases in China to comprehensively determine the epidemic intensities and whether to issue early warning signals. The numbers of new confirmed cases per month between January 2004 and December 2017 were used as the training set; the data from 2018 were used as the test set. The results of RTRL showed that the number of new confirmed cases of respiratory infectious diseases in September 2018 increased abnormally. The results of the EKF showed that the number of new confirmed cases of respiratory infectious diseases increased abnormally in January and February of 2018. The results of these two algorithms showed that the number of new confirmed cases of digestive tract infectious diseases in the test set did not have any abnormal increases. The neural network and machine learning can further enrich and develop the early warning theory.

]]>
<![CDATA[Traumatologie II]]> https://www.researchpad.co/article/N04fc72e7-c94d-4215-a610-6430b94598e4 ]]> <![CDATA[Is pulmonary arterial hypertension associated with interferon-β therapy for multiple sclerosis reversible? A case study to explore the complexity]]> https://www.researchpad.co/article/N8f301b8a-50e4-4f08-83a8-04f8a872601b

Interferon (IFN)-β has been classified as a drug that is possibly associated with development of pulmonary arterial hypertension (PAH), a devastating disease that can lead to right heart failure and premature death [1].

]]>
<![CDATA[Asthma and hypercapnic respiratory failure]]> https://www.researchpad.co/article/N763bf0f8-9261-4af5-b1c8-7879612fca95

A 40-year-old, male non-smoker was diagnosed with asthma 6 years ago. He now presents with a 1-week history of worsening breathlessness with fever, cough, and purulent expectoration. He has had >10 emergency department visits and two admissions to hospital in the last 3 months. At each admission, he received bronchodilators and systemic steroids resulting in rapid improvement within 24 h. However, in the current presentation, the patient has no relief with corticosteroids and bronchodilators. His pulse is 140 per min, respiratory rate is 40 per min, blood pressure is 90/60 mmHg and room air oxygen saturation is 80%. Arterial blood gas (ABG) analysis shows hypercapnic respiratory failure. In view this respiratory failure, the patient is intubated and mechanical ventilation initiated. A chest radiograph is shown in figure 1. The therapy initiated includes bronchodilators, a systemic steroid, antibiotics and supportive care.

]]>
<![CDATA[Pregnancy-adapted YEARS algorithm: can YEARS do more for pregnant women?]]> https://www.researchpad.co/article/N004b5d2e-168f-47b9-9a29-15b161c02f07

Venous thromboembolism (VTE), as a term that encompasses pulmonary embolism (PE) and deep vein thrombosis (DVT), is one of the leading causes of maternal morbidity and mortality [1], especially in developed countries, where PE takes second place after complications of hypertensive disorders [2]. When compared to non-pregnant women of similar age, pregnant women have an approximately four to five times higher risk of VTE [3], with an incidence of 1 in 1000 pregnancies [4]. Approximately 20–25% of VTE cases are caused by PE and 75–80% of cases are caused by DVT [5]. About 60% of DVT occurs antepartum, with the highest risk of antepartum pregnancy-associated VTE being in the third trimester.However, about 60% of PE occurs postpartum [3].

]]>
<![CDATA[Signal Propagation via Open-Loop Intrathalamic Architectures: A Computational Model]]> https://www.researchpad.co/article/N1c2c9ddc-5e2b-4a19-bb34-af8dd965a2e9

Abstract

Propagation of signals across the cerebral cortex is a core component of many cognitive processes and is generally thought to be mediated by direct intracortical connectivity. The thalamus, by contrast, is considered to be devoid of internal connections and organized as a collection of parallel inputs to the cortex. Here, we provide evidence that “open-loop” intrathalamic pathways involving the thalamic reticular nucleus (TRN) can support propagation of oscillatory activity across the cortex. Recent studies support the existence of open-loop thalamo-reticulo-thalamic (TC-TRN-TC) synaptic motifs in addition to traditional closed-loop architectures. We hypothesized that open-loop structural modules, when connected in series, might underlie thalamic and, therefore cortical, signal propagation. Using a supercomputing platform to simulate thousands of permutations of a thalamocortical network based on physiological data collected in mice, rats, ferrets, and cats and in which select synapses were allowed to vary both by class and individually, we evaluated the relative capacities of closed-loop and open-loop TC-TRN-TC synaptic configurations to support both propagation and oscillation. We observed that (1) signal propagation was best supported in networks possessing strong open-loop TC-TRN-TC connectivity; (2) intrareticular synapses were neither primary substrates of propagation nor oscillation; and (3) heterogeneous synaptic networks supported more robust propagation of oscillation than their homogeneous counterparts. These findings suggest that open-loop, heterogeneous intrathalamic architectures might complement direct intracortical connectivity to facilitate cortical signal propagation.

]]>
<![CDATA[Optogenetic Control of Spine-Head JNK Reveals a Role in Dendritic Spine Regression]]> https://www.researchpad.co/article/N82c0abd3-e52b-4408-9562-67dd5aebde20

In this study, we use an optogenetic inhibitor of c-Jun NH2-terminal kinase (JNK) in dendritic spine sub-compartments of rat hippocampal neurons. We show that JNK inhibition exerts rapid (within seconds) reorganization of actin in the spine-head.

]]>