User-defined Patterns Research Articles

Detection of Memory Engrams in Mammalian Neuronal Circuits.

It has long been assumed that activity patterns persist in neuronal circuits after they are first experienced, as part of the process of information processing and storage by the brain. However, these "reverberations" of current activity have not been directly observed on a single-neuron level in a mammalian system. Here we demonstrate that specific induced activity patterns are retained in mature cultured hippocampal neuronal networks. Neurons within the network are induced to fire at a single frequency or in a more complex pattern containing two distinct frequencies. After the stimulation was stopped, the subsequent neuronal activity of hundreds of neurons in the network was monitored. In the case of single-frequency stimulation, it was observed that many of the neurons continue to fire at the same frequency that they were stimulated to fire at. Using a recurrent neural network trained to detect specific, more complex patterns, we found that the multiple-frequency stimulation patterns were also retained within the neuronal network. Moreover, it appears that the component frequencies of the more complex patterns are stored in different populations of neurons and neuron subtypes.

FungiRegEx: A Tool for Pattern Identification in Fungal Proteomic Sequences Using Regular Expressions

In the context of proteomic-scale research, it is imperative to automatically analyze numerous species and subspecies to discern distinctive characteristics present in multiple species of the fungi kingdom that contain sequences of interest that could fulfill a specific biological function. To achieve this, complex sequences must be recognized within an organism’s entire set of proteomes. Our study presents FungiRegEx, a piece of software that facilitates the identification of regular expressions of proteomes of fungal organisms and uses real-time data retrieval of the different species from the JGI Mycocosm database without the need to download any file. Integrating a graphical user interface that makes it easy to use, the tool offers regular expression searches on 2402 fungal species from the JGI Mycocosm portal. The tool was validated with the AXSXG sequence and the RXRL effector, demonstrating the effectiveness of FungiRegEx in identifying user-defined patterns in the recovered sequences. This tool allows customization and filtering, and it can save results if required, combining speed, adaptability, and ease of use. It provides an experience without a console and programming, displaying the results in a GUI and making them easier to read. Its architecture guarantees optimized use of resources, time consumption, and implementation flexibility, allowing the customization of specific software parameters for resource management. The tool’s potential for future research and exploration is emphasized, providing a nuanced perspective on its practical use within the fungal genomics community. The tools are available at the addresses mentioned in the text.

Topology optimization of shell structures in architectural design

Free-form architectural design has gained significant interest in modern architectural practice. Due to their visually appealing nature and inherent structural efficiency, free-form shells have become increasingly popular in architectural applications. Recently, topology optimization has been extended to shell structures, aiming to generate shell designs with ultimate structural efficiency. However, despite the huge potential of topology optimization to facilitate new design for shells, its architectural applications remain limited due to complexity and lack of clear procedures. This paper presents four design strategies for optimizing free-form shells targeting architectural applications. First, we propose a topology-optimized ribbed shell system to generate free-form rib layouts possessing improved structure performance. A reusable and recyclable formwork system is developed for their effective and sustainable fabrication. Second, we demonstrate that topology optimization can be combined with funicular form-finding techniques to generate a rich variety of elegant designs, offering new design possibilities. Third, we offer cost-effective design solutions using modular components for free-form shells by combining surface planarization and periodic constraint. Finally, we integrate topology optimization with user-defined patterns on free-form shells to facilitate aesthetic expression, exemplified by the Voronoi pattern. The presented strategies can facilitate the usage of topology optimization in shell designs to achieve high-performance and innovative solutions for architectural applications.

Short text classification approach to identify child sexual exploitation material

Producing or sharing Child Sexual Exploitation Material (CSEM) is a severe crime that Law Enforcement Agencies (LEAs) fight daily. When the LEA seizes a computer from a potential producer or consumer of the CSEM, it analyzes the storage devices of the suspect looking for evidence. Manual inspection of CSEM is time-consuming given the limited time available for Spanish police to use a search warrant. Our approach to speeding up the identification of CSEM-related files is to analyze only the file names and their absolute paths rather than their content. The main challenge lies in handling short and sparse texts that are deliberately distorted by file owners using obfuscated words and user-defined naming patterns. We present two approaches to CSEM identification. The first employs two independent classifiers, one for the file name and the other for the file path, and their outputs are then combined. Conversely, the second approach uses only the file name classifier to iterate over an absolute path. Both operate at the character n-gram level, whereas novel binary and orthographic features are presented to enrich the text representation. We benchmarked six classification models based on machine learning and convolutional neural networks. The proposed classifier has an F1 score of 0.988, which can be a promising tool for LEAs.

A Sewing Approach to the Fabrication of Eco/bioresorbable Electronics.

Eco/bioresorbable electronics represent an emerging class of technology defined by an ability to dissolve or otherwise harmlessly disappear in environmental or biological surroundings after a period of stable operation. The resulting devices provide unique capabilities as temporary biomedical implants, environmental sensors, and related systems. Recent publications report schemes to overcome challenges in fabrication that follow from the low thermostability and/or high chemical reactivity of the eco/bioresorbable constituent materials. Here, this work reports the use of high-speed sewing machines, as the basis for a high-throughput manufacturing technique that addresses many requirements for these applications, without the need for high temperatures or reactive solvents. Results demonstrate that a range of eco/bioresorbable metal wires and polymer threads can be embroidered into complex, user-defined conductive patterns on eco/bioresorbable substrates. Functional electronic components, such as stretchable interconnects and antennas are possible, along with fully integrated systems. Examples of the latter include wirelessly powered light-emitting diodes, radiofrequency identification tags, and temporary cardiac pacemakers. These advances add to a growing range of options in high-throughput, automated fabrication of eco/bioresorbable electronics.

COMPOSITE BIOINKS THAT CAN BE INJECTED OR 3D BIOPRINTED TO AID OSTEOCHONDRAL DEFECT REPAIR

As arthroplasty demand grows worldwide, the need for a novel cost-effective treatment option for articular cartilage (AC) defects tailored to individual patients has never been greater. 3D bioprinting can deposit patient cells and other biomaterials in user-defined patterns to build tissue constructs from the “bottom-up,” potentially offering a new treatment for AC defects. The aim of this research was to create bioinks that can be injected or 3D bioprinted to aid osteochondral defect repair using human cells.Novel composite bioinks were created by mixing different ratios of methacrylated alginate (AlgMA) with methacrylated gelatin (GelMA). Chondrocytes or mesenchymal stem cells (MSCs) were then encapsulated in the bioinks and 3D bioprinted using a custom-built extrusion bioprinter. UV and double-ionic (BaCl2 and CaCl2) crosslinking was deployed following bioprinting to strengthen bioink stability in culture. Chondrocyte and MSC spheroids were also bioprinted to accelerate cell growth and development of ECM in bioprinted constructs.Excellent viability of chondrocytes and MSCs was seen following bioprinting (>95%) and maintained in culture over 28 days, with accelerated cell growth seen with inclusion of MSC or chondrocyte spheroids in bioinks (p<0.05). Bioprinted 10mm diameter constructs maintained shape in culture over 28 days, whilst construct degradation rates and mechanical properties were improved with addition of AlgMA (p<0.05). Composite bioinks were also injected into in vitro osteochondral defects (OCDs) and crosslinked in situ, with maintained cell viability and repair of osteochondral defects seen over a 14-day period.In conclusion we developed novel composite AlgMA/GelMA bioinks that can be triple-crosslinked, facilitating dense chondrocyte and MSC growth in constructs following 3D bioprinting. The bioink can be injected or 3D bioprinted to successfully repair in vitro OCDs, offering hope for a new approach to treating AC defects.

COMPOSITE BIOINKS THAT CAN BE INJECTED OR 3D BIOPRINTED TO AID OSTEOCHONDRAL DEFECT REPAIR

As arthroplasty demand grows worldwide, the need for a novel cost-effective treatment option for articular cartilage (AC) defects tailored to individual patients has never been greater. 3D bioprinting can deposit patient cells and other biomaterials in user-defined patterns to build tissue constructs from the “bottom-up,” potentially offering a new treatment for AC defects. The aim of this research was to create bioinks that can be injected or 3D bioprinted to aid osteochondral defect repair using human cells.Novel composite bioinks were created by mixing different ratios of methacrylated alginate (AlgMA) with methacrylated gelatin (GelMA). Chondrocytes or mesenchymal stem cells (MSCs) were then encapsulated in the bioinks and 3D bioprinted using a custom-built extrusion bioprinter. UV and double-ionic (BaCl2 and CaCl2) crosslinking was deployed following bioprinting to strengthen bioink stability in culture. Chondrocyte and MSC spheroids were also produced via 3D culture and then bioprinted to accelerate cell growth and development of ECM in bioprinted constructs.Excellent viability of chondrocytes and MSCs was seen following bioprinting (>95%) and maintained in culture over 28 days, with accelerated cell growth seen with inclusion of MSC or chondrocyte spheroids in bioinks (p<0.05). Bioprinted 10mm diameter constructs maintained shape in culture over 28 days, whilst construct degradation rates and mechanical properties were improved with addition of AlgMA (p<0.05). Composite bioinks were also injected into in vitro osteochondral defects (OCDs) and crosslinked in situ, with maintained cell viability and repair of osteochondral defects seen over a 14-day period. In conclusion we developed novel composite AlgMA/GelMA bioinks that can be triple-crosslinked, facilitating dense chondrocyte and MSC growth in constructs following 3D bioprinting. The bioink can be injected or 3D bioprinted to successfully repair in vitro OCDs, offering hope for a new approach to treating AC defects.

Elastomeric platform with surface wrinkling patterns to control cardiac cell alignment.

There is a growing interest in creating 2D cardiac tissue models that display native extracellular matrix (ECM) cues of the heart tissue. Cellular alignment alone is known to be a crucial cue for cardiac tissue development by regulating cell-cell and cell-ECM interactions. In this study, we report a simple and robust approach to create lamellar surface wrinkling patterns enabling spatial control of pattern dimensions with a wide range of pattern amplitude (A ≈ 2-55 μm) and wavelength (λ ≈ 35-100 μm). For human cardiomyocytes (hCMs) and human cardiac fibroblasts (hCFs), our results indicate that the degree of cellular alignment and pattern recognition are correlated with pattern A and λ. We also demonstrate fabrication of devices composed of micro-well arrays with user-defined lamellar patterns on the bottom surface of each well for high-throughput screening studies. Results from a screening study indicate that cellular alignment is strongly diminished with increasing seeding density. In another study, we show our ability to vary hCM/hCF seeding ratio for each well to create co-culture systems where seeding ratio is independent of cellular alignment.

Patient specific evaluation of breathing motion induced interplay effects

PurposeIn lung SABR, interplay between target motion and dynamically changing beam parameters can affect the target coverage. To identify the potential need for motion-management techniques, a comprehensive methodology for pre-treatment estimation of interplay effects has been implemented. MethodsIn conjunction with an alpha-version of VeriSoft and OCTAVIUS 4D (PTW-Freiburg, Germany), a method is presented to calculate a virtual, motion-simulated 3D dose distribution based on measurement data acquired in a stationary phantom and a subsequent correction with time-dependent target-motion patterns. In-house software has been developed to create user-defined motion patterns based on either simplistic or real patient-breathing patterns including the definition of the exact beam starting phase. The approach was validated by programmed couch and phantom motion during beam delivery.Five different breathing traces with extremely altered beam-on phases (0 % and 50 % respiratory phase) and a superior-inferior motion altitude of 25 mm were used to probe the influence of interplay effects for 14 lung SABR plans. Gamma analysis (2 %/2mm) was used for quantification. ResultsValidation measurements resulted in >98 % pass rates. Regarding the interplay effect evaluation, gamma pass rates of <92 % were observed for sinusoidal breathing patterns with <25 number of breaths per delivery time (NBs) and realistic patterns with <18 NBs. ConclusionThe potential influence of interplay effects on the target coverage is highly dependent on the patient’s breathing behaviour. The presented moving-platform-free approach can be used for verification of ITV-based treatment plans to identify whether the clinical goals are achievable without explicit use of a respiratory management technique.

CORE

Complex Event Recognition (CER) systems are a prominent technology for finding user-defined query patterns over large data streams in real time. CER query evaluation is known to be computationally challenging, since it requires maintaining a set of partial matches, and this set quickly grows super-linearly in the number of processed events. We present CORE, a novel COmplex event Recognition Engine that focuses on the efficient evaluation of a large class of complex event queries, including time windows as well as the partition-by event correlation operator. This engine uses a novel automaton-based evaluation algorithm that circumvents the super-linear partial match problem: under data complexity, it takes constant time per input event to maintain a data structure that compactly represents the set of partial matches and, once a match is found, the query results may be enumerated from the data structure with output-linear delay. We experimentally compare CORE against state-of-the-art CER systems on real-world data. We show that (1) CORE's performance is stable with respect to both query and time window size, and (2) CORE outperforms the other systems by up to five orders of magnitude on different workloads.

Lipid bilayer-assisted dynamic self-assembly of hexagonal DNA origami blocks into monolayer crystalline structures with designed geometries

SummaryThe DNA origami technique is used to construct custom-shaped nanostructures that can be used as components of two-dimensional crystalline structures with user-defined structural patterns. Here, we designed an Mg2+-responsive hexagonal 3D DNA origami block with self-shape-complementary ruggedness on the sides. Hexagonal DNA origami blocks were electrostatically adsorbed onto a fluidic lipid bilayer membrane surface to ensure lateral diffusion. A subsequent increase in the Mg2+ concentration in the surrounding environment induced the self-assembly of the origami blocks into lattices with prescribed geometries based on a self-complementary shape fit. High-speed atomic force microscopy (HS-AFM) images revealed dynamic events involved in the self-assembly process, including edge reorganization, defect splitting, diffusion, and filling, which provide a glimpse into how the lattice structures are self-improved.

CPExtract, a Software Tool for the Automated Tracer-Based Pathway Specific Screening of Secondary Metabolites in LC-HRMS Data.

The use of stable isotopically labeled tracers is a long-proven way of specifically detecting and tracking derived metabolites through a metabolic network of interest. While the recently developed stable isotope-assisted methods and associated, supporting data analysis tools have greatly improved untargeted metabolomics approaches, no software tool is currently available that allows us to automatically and flexibly search liquid chromatography coupled with high-resolution mass spectrometry (LC-HRMS) chromatograms for user-definable isotopolog patterns expected for the metabolism of labeled tracer substances. Here, we present Custom Pattern Extract (CPExtract), a versatile software tool that allows for the first time the high-throughput search for user-defined isotopolog patterns in LC-HRMS data. The patterns can be specified via a set of rules including the presence or absence of certain isotopologs, their relative intensity ratios as well as chromatographic coelution. Each isotopolog pattern satisfying the respective rules is verified on an MS scan level and also in the chromatographic domain. The CPExtract algorithm allows the use of both labeled tracer compounds in nonlabeled biological samples as well as a reversed tracer approach, employing nonlabeled tracer compounds along with globally labeled biological samples. In a proof-of-concept study, we searched for metabolites specifically arising from the malonate pathway of the filamentous fungi Fusarium graminearum and Trichoderma reesei. 1,2,3-13C3-malonic acid diethyl ester and native malonic acid monomethyl ester were used as tracers. We were able to reliably detect expected fatty acids and known polyketides. In addition, up to 46 and 270 further, unknown metabolites presumably including novel polyketides were detected in the F. graminearum and T. reesei culture samples, respectively, all of which exhibited the user-predicted isotopolog patterns originating from the malonate tracer incorporation. The software can be used for every conceivable tracer approach. Furthermore, the rule sets can be easily adapted or extended if necessary. CPExtract is available free of charge for noncommercial use at https://metabolomics-ifa.boku.ac.at/CPExtract.

Deep Anomaly Generation: An Image Translation Approach of Synthesizing Abnormal Banded Chromosome Images

Advances in deep-learning-based pipelines have led to breakthroughs in a variety of microscopy image diagnostics. However, a sufficiently big training data set is usually difficult to obtain due to high annotation costs. In the case of banded chromosome images, the creation of big enough libraries is difficult for multiple pathologies due to the rarity of certain genetic disorders. Generative Adversarial Networks (GANs) have proven to be effective in generating synthetic images and extending training data sets. In our work, we implement a conditional adversarial network that allows generation of realistic single chromosome images following user-defined banding patterns. To this end, an image-to-image translation approach based on self- generated 2D chromosome segmentation label maps is used. Our validation shows promising results when synthesizing chromosomes with seen as well as unseen banding patterns. We believe that this approach can be exploited for data augmentation of chromosome data sets with structural abnormalities. Therefore, the proposed method could help to tackle medical image analysis problems such as data simulation, segmentation, detection, or classification in the field of cytogenetics.

Patterning of Microorganisms and Microparticles through Sequential Capillarity-assisted Assembly.

Controlled patterning of microorganisms into defined spatial arrangements offers unique possibilities for a broad range of biological applications, including studies of microbial physiology and interactions. At the simplest level, accurate spatial patterning of microorganisms would enable reliable, long-term imaging of large numbers of individual cells and transform the ability to quantitatively study distance-dependent microbe-microbe interactions. More uniquely, coupling accurate spatial patterning and full control over environmental conditions, as offered by microfluidic technology, would provide a powerful and versatile platform for single-cell studies in microbial ecology. This paper presents a microfluidic platform to produce versatile and user-defined patterns of microorganisms within a microfluidic channel, allowing complete optical access for long-term, high-throughput monitoring. This new microfluidic technology is based on capillarity-assisted particle assembly and exploits the capillary forces arising from the controlled motion of an evaporating suspension inside a microfluidic channel to deposit individual microsized objects in an array of traps microfabricated onto a polydimethylsiloxane (PDMS) substrate. Sequential depositions generate the desired spatial layout of single or multiple types of micro-sized objects, dictated solely by the geometry of the traps and the filling sequence. The platform has been calibrated using colloidal particles of different dimensions and materials: it has proven to be a powerful tool to generate diverse colloidal patterns and perform surface functionalization of trapped particles. Furthermore, the platform was tested on microbial cells, using Escherichia coli cells as a model bacterium. Thousands of individual cells were patterned on the surface, and their growth was monitored over time. In this platform, the coupling of single-cell deposition and microfluidic technology allows both geometric patterning of microorganisms and precise control of environmental conditions. It thus opens a window into the physiology of single microbes and the ecology of microbe-microbe interactions, as shown by preliminary experiments.

Cas9 RNP transfection by vapor nanobubble photoporation for ex vivo cell engineering

The CRISPR-Cas9 technology represents a powerful tool for genome engineering in eukaryotic cells, advancing both fundamental research and therapeutic strategies. Despite the enormous potential of the technology, efficient and direct intracellular delivery of Cas9 ribonucleoprotein (RNP) complexes in target cells poses a significant hurdle, especially in refractive primary cells. In the present work, vapor nanobubble (VNB) photoporation was explored for Cas9 RNP transfection in a variety of cell types. Proof of concept was first demonstrated in H1299-EGFP cells, before proceeding to hard-to-transfect stem cells and T cells. Gene knock-out levels over 80% and up to 60% were obtained for H1299 cells and mesenchymal stem cells, respectively. In these cell types, the unique possibility of VNB photoporation to knock out genes according to user-defined spatial patterns was demonstrated as well. Next, effective targeting of the programmed cell death 1 receptor and Wiskott-Aldrich syndrome gene in primary human T cells was demonstrated, reaching gene knock-out levels of 25% and 34%, respectively. With a throughput of >200,000 T cells per second, VNB photoporation is a scalable and versatile intracellular delivery method that holds great promise for CRISPR-Cas9-mediated ex vivo engineering of cell therapy products.

Towards chronic deep brain stimulation in freely moving hemiparkinsonian rats: applicability and functionality of a fully implantable stimulation system

Objective. This study aimed at investigating a novel fully implantable deep brain stimulation (DBS) system and its ability to modulate brain metabolism and behavior through subthalamic nucleus (STN) stimulation in a hemiparkinsonian rat model. Approach. Twelve male rats were unilaterally lesioned with 6-hydroxydopamine in the medial forebrain bundle and received a fully implantable DBS system aiming at the ipsilesional STN. Each rat underwent three cylinder tests to analyze front paw use: a PRE test before any surgical intervention, an OFF test after surgery but before stimulation onset and an ON test under DBS. To visualize brain glucose metabolism in the awake animal, two [18F]FDG scans were conducted in the OFF and ON condition. At least 4 weeks after surgery, an [18F]FDOPA scan was used to check for dopaminergic integrity. Main results. In general, STN DBS increased [18F]FDG uptake ipsilesionally and decreased it contralesionally. More specifically, bilateral orbitofrontal cortex, ipsilateral caudate putamen, sensorimotor cortex and nucleus accumbens showed significantly higher tracer uptake in ON compared to OFF condition. Contralateral cingulate and secondary motor cortex, caudate putamen, amygdala, hippocampus, retrosplenial granular cortex, superior colliculus, and parts of the cerebellum exhibited significantly higher [18F]FDG uptake in the OFF condition. On the behavioral level, stimulation was able improve use of the contralesional affected front paw suggesting an effective stimulation produced by the implanted system. Significance. The fully implantable stimulation system developed by us and presented here offers the output of arbitrary user-defined waveforms, patterns and stimulation settings and allows tracer accumulation in freely moving animals. It is therefore a suitable device for implementing behavioral PET studies. It contributes immensely to the possibilities to characterize and unveil the effects and mechanisms of DBS offering valuable clues for future improvements of this therapy.

AllScale API

Effectively implementing scientific algorithms in distributed memory parallel applications is a difficult task for domain scientists, as evident by the large number of domain-specific languages and libraries available today attempting to facilitate the process. However, they usually provide a closed set of parallel patterns and are not open for extension without vast modifications to the underlying system. In this work, we present the AllScale API, a programming interface for developing distributed memory parallel applications with the ease of shared memory programming models. The AllScale API is closed for a modification but open for an extension, allowing new user-defined parallel patterns and data structures to be implemented based on existing core primitives and therefore fully supported in the AllScale framework. Focusing on high-level functionality directly offered to application developers, we present the design advantages of such an API design, detail some of its specifications and evaluate it using three real-world use cases. Our results show that AllScale decreases the complexity of implementing scientific applications for distributed memory while attaining comparable or higher performance compared to MPI reference implementations.

Force modeling to develop a novel method for fabrication of hollow channels inside a gel structure.

Fabrication of hollow channels with user-defined dimensions and patterns inside viscoelastic, gel-type materials is required for several applications, especially in biomedical engineering domain. These include objectives of obtaining vascularized tissues and enclosed or subsurface microfluidic devices. However, presently there is no suitable manufacturing technology that can create such channels and networks in a gel structure. The advent of three-dimensional bioprinting has opened new possibilities for fabricating structures with complex geometries. However, application of this technique to fabricate internal hollow channels in viscoelastic material has not been yet explored to a great extent. In this article, we present the theoretical modeling/background of a proposed manufacturing paradigm through which hollow channels can be conveniently fabricated inside a gel structure. We propose that a tip connected to a robotic arm can be moved in X-, Y-, and Z-axis as per the desired design. The tip can be moved by a magnet or mechanical force. If the tip is further trailed with porous tube and moved inside the viscoelastic material, corresponding internal channels can be fabricated. To achieve this, however, force modeling to understand the forces that will be required to move the tip inside viscoelastic material should be known and understood. Therefore, in our first attempt, we developed the computational force modeling of the tip movement inside gels with different viscoelastic properties to create the channels.

Electronically controlled generation of laser pulse patterns in a synchronously pumped mode-locked semiconductor optical amplifier-fiber laser

A method for electronically controlled formation of user-defined laser pulse patterns in a synchronously pumped laser based on a semiconductor optical amplifier and an all-fiber resonator is proposed and investigated. It is demonstrated that synchronous pumping allows mode-locked operation with the laser radiation structured as an arbitrary pulse pattern repeatable on each cavity round trip. Direct electronic control of the structure and shape of the generated laser pulse patterns is implemented. The accuracy of the reproduction of modulation pulse patterns and waveforms delivered from a radiofrequency arbitrary waveform generator is examined. The time constraint on the pulse pattern formation in the steady-state mode-locked lasing regime is revealed, as well as the feasibility of the quasi-steady-state regime with on-the-lasing continuous modification of the pulse pattern structure.

Detecting and locating patterns in time series using machine learning

A method is presented to detect and locate user-defined patterns in time series data. The method is based on decomposing time series into a sequence of fixed-length snapshots on which a classifier is applied. Snapshot classification results determine the exact position of the pattern. One advantage of this approach is that it can be applied to any process-specific pattern, e.g., spiking patterns, under- or overshoots, or (time-lagged) correlations.We demonstrate the efficacy of the approach by means of an example from steel production, namely a cold-rolling mill process. We detect two patterns: underswings and time-lagged spike repetition in multivariate series.