Template Library Research Articles

A Preliminary Model of the Wrist Midcarpal Joint.

Background A challenge to deciphering the effect of structure on function in the wrist involves difficulty in obtaining in-vivo information. To provide a platform to study wrist mechanics using in vivo acquired forces, we developed a model of the midcarpal joint based on computed tomography (CT) scans of normal wrists. Finite element analysis (FEA) can enable application of in vivo collected information to an ex vivo model. Objectives The objectives of this study are to (1) create a three-dimensional model of the midcarpal joint of the wrist based on CT scans and (2) generate separate models for the midcarpal joint based on two distinct wrist types and perform a pilot loading of the model. Methods CT scans from a normal patient database were converted to three-dimensional standard template library (STL) files using OsiriX software. Five type 1 and five type 2 wrists were used for modeling. A simulated load was applied to the carpometacarpal joints in a distal-to-proximal direction, and FEA was used to predict force transfer in the wrist. Results There were 33% type 1 and 67% type 2 wrists. The midcarpal joint dimensional measurements estimated from the model had intermediate agreement between wrist type as measured on CT scan and as predicted by the model: 56% Cohen's kappa (95% confidence interval) = 0.221 (0.05-0.5). Surface stress on the carpometacarpal joints is different in type 1 and type 2 wrists. On loading the neutral wrist, the capitolunate angle was 90 degrees in type 1 wrists and 107 degrees in type 2 wrists ( p < 0.0001). Conclusions The model predicted differences in movement and force transfer through the midcarpal joint dependent on structural type. This knowledge can improve our understanding of the development of disparate patterns of degeneration in the wrist.

Inferring metal binding sites in flexible regions of proteins.

Metal ions are central to the molecular function of many proteins. Thus their knowledge in experimentally determined structure is important; however, such structures often lose bound metal ions during sample preparation. Identification of these metal-binding site(s) becomes difficult when the receptor is novel and/or their conformations differ in the bound/unbound states. Locating such sites in theoretical models also poses a challenge due to the uncertainties with side-chain modeling. We address the problem by employing the Geometric Hashing algorithm to create a template library of functionally important binding sites and match query structures with the available templates. The matching is done on the structure ensemble obtained from coarse-grained molecular dynamics simulation, where metal-specific amino acids are screened to infer the true site. Test on 1347 non-redundant monomer protein structures show that Ca2+ , Zn2+ , Mg2+ , Cu2+ , and Fe3+ binding site residues can be classified at 0.92, 0.95, 0.80, 0.90, and 0.92 aggregate performance (out of 1) across all possible thresholds. The performance for Ca2+ and Zn2+ is notably superior in comparison to state-of-the-art methods like IonCom and MIB. Specific case studies show that additionally predicted metal-binding site residues in proteins have features necessary for ion binding. These include new sites not predicted by other methods. The use of coarse-grained dynamics thus provides a generalized approach to improve metal-binding site prediction. The work is expected to contribute to improving our ability to correctly predict protein molecular function where knowledge of metal binding is a key requirement.

Compiler-assisted Operator Template Library for DNN Accelerators

Despite many dedicated accelerators are gaining popularity for their performance and energy efficiency in the deep neural network (DNN) domain, high-level programming support for these accelerators remains thin. In contrast to existing researches targeting the whole DNNs, we choose to dive into details and review this problem from a finer-grained level, operators. Due to performance concerns, operator programmers may have to take hand-written assembly as their first choice, which is error-prone and involves many programming chores. To alleviate this problem, we propose TOpLib, a compiler-assisted template library. By providing a unified user-view abstraction, TOpLib allows programmers to express computational kernels with high-level tensor primitives, which will be automatically lowered into low-level intrinsic primitives via expression templates. Moreover, considering memory management is performance-critical and the optimization strategy of expression template is limited to enumeration based rewriting rules, we implement TOpLib with a compiler-assisted approach. We address the memory reuse challenges into the compiler, which allows TOpLib to make full use of on-chip buffers and result in better performance. Experiments over 55 typical DNN operators demonstrate that TOpLib can generate scalable code with performance faster than or on par with hand-written assembly versions.

Binding site identification of COVID-19 main protease 3D structure by homology modeling

The influx of coronavirus in 2019 (COVID-19) from Wuhan of China has led to a global pandemic, undesirable hiatus, and recorded millions of infection cases with several deaths worldwide. The strain of COVID-19 has neither known treatments nor vaccines, but recent studies have shown that a few of its enzymes may have been considered as potential drug target. Since its influx, the virus has been well-studied, but a lot is not known about its protease yet. The purpose of this work was to identify the binding site in-silico and present 3D structure of COVID-19 main protease (Mpro) by homology modeling through multiple alignment followed by optimization and validation. The modeling was done by Swiss-Model template library and basic local alignment search tool (BLAST). The obtained homotrimer oligo-state model was verified for reliability using structural validation software such as PROCHECK, Verify3D, MolProbity and QMEAN. The HHBlits software was used to determine the structures that matched the target sequence by evolution. Best template, 6u7h.1.A was used to build a tertiary structure for Mpro with ProMod3 3.0.0 on the Swiss-Model workspace. Self-optimized prediction method with alignment (SOPMA) was applied to compute features of the secondary structure. The verification of quality of COVID-19 structure through Ramachandran plot showed an abundance of 99.3% of amino acid residues in allowed regions while 0.1% in disallowed region. The Verify3D rated the structure a 90.87% PASS of residues having an average 3D-1D score of at least 0.2, which validates a good environment profile for the COVID-19 Mpro model. The features of the secondary structure indicated that the modeled 3D structure of Mpro contains 32.05% α-helix and 37.17% random coil with 25.92 extended strand. DeepSite algorithm elucidates the binding site area that captured local patterns in the structure and exposed the surface cavity of the binding pocket of this protein. The main result of this study suggests that blocking expression of the protein may constitute an efficient approach for transmission blockage. Hence, our thought is that Mpro of COVID-19 may be considered a potential drug target. Nevertheless, more experimental analyses, verification and validation experiments will be required as a targeted drug or vaccine design against COVID-19 virus.

Block Detection and Tracking Algorithm of Foreign Objects Debris in Airport Runway Based on Background Alignment and Difference

<p indent=0mm>Aiming at the problems of unmanned detection and recognition of foreign object debris (FOD) in the autonomous detection and recognition of airport runways, the detection results are affected by the environment, the detection of small targets is difficult, and the rate of missed detection is high. An airport runway foreign object debris sub-block detection and tracking method based on background difference is proposed in this article. First, the linear interpolation of position information assisted by the speed is used to obtain the most relevant frame of the image in background image template library and the image sequence to be identified. Then, the image is divided into different sub-blocks, the adaptive weights are set using the image texture complexity in each sub-block, and the feature point extraction is combined with the oriented fast and rotated brief (ORB) method to normalize the sub-block feature points to the original image. Align the image with the most relevant frame of the background template library using the feature points result before to obtain the foreign object detection result. Finally, the kernelized correlation filter is introduced to track the detection results for multiple targets. Local tracking methods of each sub-block are used to reduce the computation time and the tracking results are tested for reliability. According to the experiment results in three different scenarios, compared with another five common image-based airport FOD detection algorithms, this method can reduce the overall false detection rate of foreign objects by more than 70%, and the overall missed detection rate to 0 when the size of foreign body is larger than <sc>1 cm<inline-formula id=inline1><mml:math xmlns:mml=http://www.w3.org/1998/Math/MathML display=inline><mml:mo>×</mml:mo></mml:math></inline-formula>1 cm,</sc> while ensuring the algorithm processing speed, which achieved good results.

A new panchromatic classification of unclassified Burst Alert Telescope active galactic nuclei

We collect data at all frequencies for the new sources classified as unknown active galactic nuclei (AGNs) in the latest Burst Alert Telescope all-sky hard X-ray catalog. Focusing on the 36 sources with measured redshift, we compute their spectral energy distribution (SED) from radio to γ-rays with the aim to classify these objects. We apply emission models that attempt to reproduce the obtained SEDs, including: (i) a standard thin accretion disk together with an obscuring torus and a X-ray corona; (ii) a two temperature thick advection-dominated flow; (iii) an obscured AGN model, accounting for absorption along the line of sight at kiloelectronvolt energies and in the optical band; and (iv) a phenomenological model to describe the jet emission in blazar-like objects. We integrate the models with the SWIRE template libraries to account for the emission of the host galaxy. For every source we found a good agreement between data and our model. Considering that the sources were selected in the hard X-ray band, which is rather unaffected by absorption, we expected and found a large fraction of absorbed radio-quiet AGNs (31 out of 36) and some additional rare radio-loud sources (5 out of 36), since the jet emission in hard X-rays is important for aligned jets owing to the boost produced by the beaming effect. With our work we can confirm the hypothesis that a number of galaxies, whose optical spectra lack AGN emission features, host an obscured active nucleus. The approach we used proved to be efficient in rapidly identifying objects, which commonly used methods were not able to classify.

Real-time registration of 3D echo to x-ray fluoroscopy based on cascading classifiers and image registration

Three-dimensional (3D) transesophageal echocardiography (TEE) is one of the most significant advances in cardiac imaging. Although TEE provides real-time 3D visualization of heart tissues and blood vessels and has no ionizing radiation, x-ray fluoroscopy still dominates in guidance of cardiac interventions due to TEE having a limited field of view and poor visualization of surgical instruments. Therefore, fusing 3D echo with live x-ray images can provide a better guidance solution. This paper proposes a novel framework for image fusion by detecting the pose of the TEE probe in x-ray images in real-time. The framework does not require any manual initialization. Instead it uses a cascade classifier to compute the position and in-plane rotation angle of the TEE probe. The remaining degrees of freedom are determined by fast marching against a template library. The proposed framework is validated on phantoms and patient data. The target registration error for the phantom was 2.1 mm. In addition, 10 patient datasets, seven of which were acquired from cardiac electrophysiology procedures and three from trans-catheter aortic valve implantation procedures, were used to test the clinical feasibility as well as accuracy. A mean registration error of 2.6 mm was achieved, which is well within typical clinical requirements.

Comprehensive Quantification of Carboxymethyllysine-Modified Peptides in Human Plasma.

A prolonged hyperglycemic condition in diabetes mellitus results in glycation of plasma proteins. N(ε)-Carboxymethyllysine (CML) is a well-known protein advanced glycation end product, and one of its mechanisms of formation is through further oxidation of Amadori compound modified lysine (AML). Unlike enrichment of AML peptides using boronate affinity, biochemical enrichment methods are scarce for comprehensive profiling of CML-modified peptides. To address this problem, we used AML peptide sequence and site of modification as template library to identify and quantify CML peptides. In this study, a parallel reaction monitoring workflow was developed to comprehensively quantify CML modified peptides in Type 1 diabetic subjects' plasma with good and poor glycemic control (n = 20 each). A total of 58 CML modified peptides were quantified, which represented 57 CML modification sites in 19 different proteins. Out of the 58 peptides, five were significantly higher in poor glycemic control samples with the area under the receiver operating characteristic curve ≥0.83. These peptides could serve as promising indicators of glycemic control in Type 1 diabetes management.

The TRACE-Seq method tracks recombination alleles and identifies clonal reconstitution dynamics of gene targeted human hematopoietic stem cells

Targeted DNA correction of disease-causing mutations in hematopoietic stem and progenitor cells (HSPCs) may enable the treatment of genetic diseases of the blood and immune system. It is now possible to correct mutations at high frequencies in HSPCs by combining CRISPR/Cas9 with homologous DNA donors. Because of the precision of gene correction, these approaches preclude clonal tracking of gene-targeted HSPCs. Here, we describe Tracking Recombination Alleles in Clonal Engraftment using sequencing (TRACE-Seq), a methodology that utilizes barcoded AAV6 donor template libraries, carrying in-frame silent mutations or semi-randomized nucleotides outside the coding region, to track the in vivo lineage contribution of gene-targeted HSPC clones. By targeting the HBB gene with an AAV6 donor template library consisting of ~20,000 possible unique exon 1 in-frame silent mutations, we track the hematopoietic reconstitution of HBB targeted myeloid-skewed, lymphoid-skewed, and balanced multi-lineage repopulating human HSPC clones in mice. We anticipate this methodology could potentially be used for HSPC clonal tracking of Cas9 RNP and AAV6-mediated gene targeting outcomes in translational and basic research settings.

Operators for Data Redistribution: Applications to the STL Library and RayTracing Algorithm

In distributed-memory systems, data redistributions are operations that change the ownership and location of a selected subset of a data structure at runtime. They allow the improvement of the performance of parallel algorithms which operate on changing or partial domains, aiming to create a balanced workload among the active processes. To manually redistribute data is a cumbersome and error-prone task. In this paper, we present a method based on four combinable operators to redistribute partial domains selected by the programmer at runtime in an efficient and simple way. They abstract to the programmer the data-redistribution implementation details, such as the new mapping, relocation, and communication of the selected data. We also present the application of the proposed operators to a RayTracing application and to a significant part of STL (C++ Standard Template Library). Our experimental results show that our approach automatically generates a good load balance, which leads to performance improvements for generic data-distribution policies. It does not introduce significant performance overheads compared with tailored data redistributions directly programmed using MPI (Message Passing Interface), while it greatly reduces the code development effort.

Individual identification of electronic equipment based on electromagnetic fingerprint characteristics

With the rapid development of communication and computer, the individual identification technology of communication equipment has been brought to many application scenarios. The identification of the same type of electronic equipment is of considerable significance, whether it is the identification of friend or foe in military applications, identity determination, radio spectrum management in civil applications, equipment fault diagnosis, and so on. Because of the limited-expression ability of the traditional electromagnetic signal representation methods in the face of complex signals, a new method of individual identification of the same equipment of communication equipment based on deep learning is proposed. The contents of this paper include the following aspects: (1) Considering the shortcomings of deep learning in processing small sample data, this paper provides a universal and robust feature template for signal data. This paper constructs a relatively complete signal template library from multiple perspectives, such as time domain and transform domain features, combined with high-order statistical analysis. Based on the inspiration of the image texture feature, characteristics of amplitude histogram of signal and the signal amplitude co-occurrence matrix (SACM) are proposed in this paper. These signal features can be used as a signal fingerprint template for individual identification. (2) Considering the limitation of the recognition rate of a single classifier, using the integrated classifier has achieved better generalization ability. The final average accuracy of 5 NRF24LE1 modules is up to 98% and solved the problem of individual identification of the same equipment of communication equipment under the condition of the small sample, low signal-to-noise ratio.

Efficient Editing of Silver Nanoclusters by Changing Simply One Cytosine in a DNA Template.

DNA with genetic information was edited to regulate and repair the structure and function of a protein. In DNA nanotechnology, DNA with programmable information can be designed to edit the fluorescence intensity and emissive colors of DNA-stabilized silver nanoclusters (DNA/AgNCs). By introducing and moving one cytosine in the spacer of the emitter domain, we have built up a simple strategy to regulate the excitation and emission wavelengths of AgNCs. When replacing thymine in the spacer of the emitter with one cytosine, the expected excitation and emission change do not occur. However, after moving the introduced cytosine, DNA templates produce AgNCs with extremely different excitation and emission wavelengths from those of the initial template, leading to a template for near-infrared (NIR) emissive species with the highest fluorescence intensity. The formation of AgNCs induces the DNA template into condensed secondary structure based on an altered migration rate in PAGE. The simple strategy of moving one cytosine in a spacer in the emitter domain can enrich the library of templates for synthesizing diverse DNA/AgNCs and has great potential in bioimaging and probe design.

Mixed-reality hologram for diagnosis and surgical planning of double outlet of the right ventricle: a pilot study

To evaluate the mixed-reality (MR) hologram, a novel technology based on two-dimensional images, which simulates three-dimensional (3D) images and provides a dynamic and interactive alternative, for its usefulness in the diagnosis and surgical planning of double outlet of the right ventricle (DORV). Thirty-four patients who were suspected of DORV based on ultrasound findings underwent cardiac computed tomography angiography (CTA). The patients were assigned randomly to the MR holographic guidance (MRHG) group or the control group. For the patients in the MRHG group, the CTA images were converted into Standard Template Library (STL) files after segmentation, 3D reconstruction, colourisation, and transparentisation, and then exported for MR holographic visualisation. The CTA images of the patients in the control group were analysed using routine 3D reconstruction only. Diagnostic accuracy and surgical planning were compared between the two groups based on visualisation at surgery. In the MRHG group, the 3D hologram observation was in concordance with the actual anatomical findings, and the DORV type was classified accurately in all patients. The diagnostic accuracy for the malformation was 95.5% in the MRHG group and 89.7% in the control group, but the difference was not significant (p=0.3). All the procedures were exactly the same as planned based on the 3D MR holographic model. The surgical planning time was shorter for the MRHG group (51.65±11.11 min) than that for the control group (65.71±18.07 min, p<0.05). MR 3D holograms may provide a clear and deeper anatomical perception of DORV and improve surgical planning.

Templates for writing PyMOL scripts.

PyMOL commands are used to exert exquisite control over the appearance of a molecular model. This control has made PyMOL popular for making images of protein structures for publications and presentations. However, many users have poor recall of the commands due to infrequent use of PyMOL. This poor recall hinders the writing of new code in scripts. One solution is to build the new script by using code fragments as templates for modular parts of the task at hand. The code fragments can be accessed from a library while writing the code from inside a text editor (e.g., Visual Studio Code, Vim, and Emacs). We developed a library of PyMOL code templates or snippets called pymolsnips to ease the writing of PyMOL code in scripts. We made pymolsnips available on GitHub in formats for 18 popular text editors. Most of the supported text editors are available for Mac, Windows, and Linux operating systems. The GitHub site includes animations that complement the instructions for installing the library for each text editor. We expect that the library will help many PyMOL users to be more productive when writing PyMOL script files.

AiZynthFinder: a fast, robust and flexible open-source software for retrosynthetic planning

We present the open-source AiZynthFinder software that can be readily used in retrosynthetic planning. The algorithm is based on a Monte Carlo tree search that recursively breaks down a molecule to purchasable precursors. The tree search is guided by an artificial neural network policy that suggests possible precursors by utilizing a library of known reaction templates. The software is fast and can typically find a solution in less than 10 s and perform a complete search in less than 1 min. Moreover, the development of the code was guided by a range of software engineering principles such as automatic testing, system design and continuous integration leading to robust software with high maintainability. Finally, the software is well documented to make it suitable for beginners. The software is available at http://www.github.com/MolecularAI/aizynthfinder.

Multiplexed Functional Assessment of Genetic Variants in CARD11

SummaryGenetic testing has increased the number of variants identified in disease genes, but the diagnostic utility is limited by lack of understanding variant function. CARD11 encodes an adaptor protein that expresses dominant-negative and gain-of-function variants associated with distinct immunodeficiencies. Here, we used a “cloning-free” saturation genome editing approach in a diploid cell line to simultaneously score 2,542 variants for decreased or increased function in the region of CARD11 associated with immunodeficiency. We also described an exon-skipping mechanism for CARD11 dominant-negative activity. The classification of reported clinical variants was sensitive (94.6%) and specific (88.9%), which rendered the data immediately useful for interpretation of seven coding and splicing variants implicated in immunodeficiency found in our clinic. This approach is generalizable for variant interpretation in many other clinically actionable genes, in any relevant cell type.

3D Personalized Human Modeling and Deformation Technology for Garment CAD

According to the design requirements of garment CAD system, this paper summarizes and analyzes the flow, characteristics and existing problems of existing human modeling algorithms, and proposes a 3D human modeling method based on section ring calculation, and realizes the dynamic modeling of human body driven by joint points. Firstly, the human body shape is classified to create a 3D human body shape template library. On the basis of extracting feature points and feature lines of the human model, the relationship between the size change and the feature points is calculated by using simple linear scaling ratio. Through the mathematical modeling of chest curve, waist hip curve and longitudinal datum line, the fitting curve results which reflect the curve characteristics and are convenient for subsequent clothing deformation are obtained. The algorithm is simple and efficient. It can not only accurately reproduce the surface static characteristics of the original scanned human body, but also change the dynamic characteristics of the human body interactively, which can meet the basic requirements of the human body model in the process of fashion design.

OU Medicine Chooses American Health Information Management Association's Compliant Template Library Within Artifact Health's Mobile Physician Query Platform

Journal of Clinical Engineering: 10/12 2020 - Volume 45 - Issue 4 - p 189 doi: 10.1097/JCE.0000000000000432

A Method for 3D Reconstruction of the Ming and Qing Official-Style Roof Using a Decorative Components Template Library

The ancient roof decorative components of the official-style architectures from the Ming and Qing dynasties in China hold both physical and symbolic significance. These roof structures are the essential objects in three-dimensional (3D) modeling of ancient architectures for traditional Chinese cultural preservation. Although ancient architectures can be surveyed by a 3D laser scanner, the complex geometry and diverse pattern of their roof decorative components make the 3D point cloud reconstruction challenging, or at some points, nearly impossible in a fully automated manner. In this paper, we propose a method to ensure that the 3D shape of each roof decorative component is accurately modeled. First, we establish a decorative components template library (or “template library” in short hereafter), which is the first of its kind for the roofs of Ming and Qing official-style architectures. The process of establishing the decorative components template library begins with a remote collection of survey data using a terrestrial laser scanner and digital camera. The next stage involves the design and construction of different 3D decorative components in the template library with reference to the manuscripts written in the Ming and Qing dynasties’ architectural pattern books. With the point cloud data collected on any Ming and Qing official-style architecture, we further propose a geo-registration mechanism to search for an optimal fitting of the decorative components from the template library on the collected point cloud automatically. Based on the experimental results, the accuracy of point cloud registration yields less than 0.02 m, which meets the accuracy of the 3D model at LoD 300 level. Time consumption is less than 5s and stable, for large volume computing capacity has good robustness. The proposed strategy provides a new way for the 3D modeling of large and clustered historical architectures, particularly with complex structures.

CoLiDe: Combinatorial Library Design tool for probing protein sequence space.

MotivationCurrent techniques of protein engineering focus mostly on re-designing small targeted regions or defined structural scaffolds rather than constructing combinatorial libraries of versatile compositions and lengths. This is a missed opportunity because combinatorial libraries are emerging as a vital source of novel functional proteins and are of interest in diverse research areas.ResultsHere, we present a computational tool for Combinatorial Library Design (CoLiDe) offering precise control over protein sequence composition, length and diversity. The algorithm uses evolutionary approach to provide solutions to combinatorial libraries of degenerate DNA templates. We demonstrate its performance and precision using four different input alphabet distribution on different sequence lengths. In addition, a model design and experimental pipeline for protein library expression and purification is presented, providing a proof-of-concept that our protocol can be used to prepare purified protein library samples of up to 1011–1012 unique sequences. CoLiDe presents a composition-centric approach to protein design towards different functional phenomena.Availabilityand implementationCoLiDe is implemented in Python and freely available at https://github.com/voracva1/CoLiDe.Supplementary information Supplementary data are available at Bioinformatics online.