Incorrect Assembly Research Articles

An outcome-defining role for the triple-helical domain in regulating collagen-I assembly

Collagens are the foundational component of diverse tissues, including skin, bone, cartilage, and basement membranes, and are the most abundant protein class in animals. The fibrillar collagens are large, complex, multidomain proteins, all containing the characteristic triple helix motif. The most prevalent collagens are heterotrimeric, meaning that cells express at least two distinctive procollagen polypeptides that must assemble into specific heterotrimer compositions. The molecular mechanisms ensuring correct heterotrimeric assemblies are poorly understood - even for the most common collagen, type-I. The longstanding paradigm is that assembly is controlled entirely by the ~30 kDa globular C-propeptide (C-Pro) domain. Still, this dominating model for procollagen assembly has left many questions unanswered. Here, we show that the C-Pro paradigm is incomplete. In addition to the critical role of the C-Pro domain in templating assembly, we find that the amino acid sequence near the C terminus of procollagen's triple-helical domain plays an essential role in defining procollagen assembly outcomes. These sequences near the C terminus of the triple-helical domain encode conformationally stabilizing features that ensure only desirable C-Pro-mediated trimeric templates are committed to irreversible triple-helix folding. Incorrect C-Pro trimer assemblies avoid commitment to triple-helix formation thanks to destabilizing features in the amino acid sequences of their triple helix. Incorrect C-Pro assemblies are consequently able to dissociate and search for new binding partners. These findings provide a distinctive perspective on the mechanism of procollagen assembly, revealing the molecular basis by which incorrect homotrimer assemblies are avoided and setting the stage for a deeper understanding of the biogenesis of this ubiquitous protein.

Fracture in control rods of helicopters: Same failures but different reasons

This paper presents two incidences of failures of collective control rods which resulted in accidents to a particular type of helicopter. The control rods were made of 2024 Al-alloy tubes fitted with fork at one end and a spherical bearing at the other end (eye-end). In terms of physical appearance, the two failures in the control rods were identical to each other wherein there was fracture in the Al-alloy tube at the eye-end. Fractography study confirmed that in both the cases, multiple fatigue cracks had initiated over a sector at the internal thread roots on the Al-alloy tubes corresponding to 1st/2nd thread on the eye-end stud. After initiation, the cracks had propagated progressively into the tube-wall and then along the circumferential direction. As the crack propagation progressed, the load bearing capacity of the tubes diminished resulting in final overload fracture under the operational load at the time of accidents. Although failures in both the control rods looked alike in terms of failure location, fracture pattern and fracture mechanism, the primary reasons of failures were found to be different. Investigation revealed that premature fatigue crack initiation was due to non-uniform stress distribution on the internal threads of the control tube with increased level of stress over a sector. In one case, the non-uniform stress distribution resulted from thread manufacturing deficiency, and in the other case, it was due to incorrect assembly at the eye-end.

Optimizing Binding Site Spacing in Fluidic Self-Assembly for Enhanced Microchip Integration Density.

This manuscript presents a comprehensive study on the assembly of microchips using fluidic self-assembly (FSA) technology, with a focus on optimizing the spacing between binding sites to improve yield and assembly. Through a series of experiments, we explored the assembly of microchips on substrates with varying binding site spacings, revealing the impact of spacing on the rate of undesired chip assembly across multiple sites. Our findings indicate a significant reduction in incorrect assembly rates as the spacing increases beyond a critical threshold of 140 μm. This study delves into the mechanics of chip alignment within the fluid medium, hypothesizing that the extent of the alloy's grip on the chips at different spacings influences assembly outcomes. By analyzing cases of undesired assembly, we identified the relationship between binding site spacing and the area of chip contact, demonstrating a decrease in the combined left and right areas of chips as the spacing increases. The results highlight a critical spacing threshold, which, when optimized, could significantly enhance the efficiency and precision of microchip assembly processes using FSA technology. This research contributes to the field of microcomponent assembly, offering insights into achieving higher integration densities and precision in applications, such as microLED displays and augmented reality (AR) devices.

Creating Synthetic Datasets for Deep Learning used in Machine Vision

Deep Learning, a subfield of Artificial Intelligence, has enabled a wide range of applications in machine vision, including manufacturing quality control. A critical aspect of Machine Vision using Deep Learning algorithms is the availability of large amounts of visual training data. Collecting training data is time consuming, especially in cases where visual training data is difficult to collect. For example, machine vision systems for object detection in quality inspection need massive datasets with various light, rotation and viewpoints parameters to recognize components. Only the training phases of data collection and annotation are responsible for about 80 % of the time spent. Through advances in synthetically generated training data, the lack of available training data is alleviated and effort for data collection and annotation is reduced. This paper presents an innovative approach to generate synthetic training data using CAD-Tools and rendering software. In this work, synthetic training data is generated using the approach of domain randomization. Domain randomization introduces diversity and variability in training dataset, which has proven to improve the robustness and generalization of deep learning models. The approach is evaluated in a case example. Images of an assembly step are classified in terms of correct or incorrect assembly. The results show that synthetically generated training data used to train deep learning algorithms are fundamentally suitable for Machine Vision. Within this study deep learning models trained with synthetic image reached equally good results as models trained using real-world data. Variation using generated non-realistic image data is able to force neuronal nets to learn features of the object of interest. Synthetically generated training data therefore is an inexpensive source of data avoiding the need to collect and annotate large amounts of training data. Overall, the integration of synthetically generated image data has paved the way for new possibilities in visual application domains.

Flexible automation of quality inspection in parts assembly using CNN-based machine learning

Ensuring high product quality is crucial in modern industry, as low-quality products can lead to negative consequences like financial losses, resource wastage, and harm to a company's reputation. Although in high volume production advanced inspection technologies are in place, small and medium-sized enterprises (SMEs) still often rely only on manual visual inspection by human operators to identify defective or improperly assembled products resulting in long cycle times, high error rates, and increased costs. To address mentioned issues, recently advanced automated optical inspection systems (AOIs) have been developed that employ Convolutional Neural Networks (CNN) such as YOLO (You Only Look Once). While YOLO has been effectively applied to identify defects across a range of industrial uses, the potential of YOLOv8 for real-time detection of correct and incorrect assembly in automated production lines lacks research. The research presented here aimed to develop an automated optical inspection system using a camera and a CNN-based model, Yolov8, to ensure the product quality of the assembled parts in real-time. Three algorithms were developed using Python, RT Toolbox 2, and TIA Portal v17 to facilitate communication between the developed model, robot, and PLC as well as assembly and carry out quality control processes. The system's performance was evaluated through three sets of experiments, each consisting of 50 instances. The collected data were then evaluated by means of statistical analysis methods. The study's results revealed that Yolov8 with AOIs resulted in a high accuracy as well as macro and micro recall, precision and F1-Score of 98%. Moreover, this low-cost and real-time approach holds significant potential for adoption in SMEs' production lines for inspecting parts.

Identification of Mispairing Omic Signatures in Chinese Hamster Ovary (CHO) Cells Producing a Tri-Specific Antibody.

Monoclonal antibody-based therapy has shown efficacy against cancer, autoimmune, infectious, and inflammatory diseases. Multispecific antibodies (MsAbs), including trispecifics (tsAbs), offer enhanced therapeutic potential by targeting different epitopes. However, when co-expressed from three or more different polypeptide chains, MsAb production can lead to incorrect chain assembly and co-production of mispaired species with impaired biological activity. Moreover, mispairing carries significant challenges for downstream purification, decreasing yields and increasing the cost of bioprocess development. In this study, quantitative transcriptomics and proteomics analyses were employed to investigate which signaling pathways correlated with low and high mispairing clone signatures. Gene and protein expression profiles of Chinese hamster ovary (CHO) clones producing an tsAb were analyzed in the exponential growth and stationary (tsAb production) phase of fed-batch culture. Functional analysis revealed activated endoplasmic reticulum stress in high mispairing clones in both culture phases, while low mispairing clones exhibited expression profiles indicative of activated protein translation, as well as higher endocytosis and target protein degradation, suggesting the clearance of unfolded proteins through ubiquitin-mediated mechanisms. In addition, through transcriptomic profiling, we identified a group of genes that have the potential to be used as a biomarker panel tool for identifying high mispairing levels in the early stages of bioprocess development.

Lethal nitrous oxide (N2O) intoxication during surgery: the contribution of immunohistochemistry in identifying the cause of death: a case report

BackgroundNitrous oxide (N2O) is a gas used in medicine for its analgesic, anxiolytic and amnesic properties. It is a drug considered safe if adequately administered. In the literature, accidental N2O-related deaths are rare. They are mostly related to inhalation of this substance for recreational and autoerotic purposes; rarely are reported deaths due to incorrect administration of medical gas in anesthesia. The diagnosis of death from acute N2O intoxication is complex and is generally an exclusion diagnosis: the macroscopic and microscopic post-mortem signs are entirely nonspecific. Furthermore, the circumstantial data are not always supportive and can even be confusing, mainly if the death occurred inside a hospital.Case presentationWe describe a particular case of death from acute nitrous oxide poisoning in a hospital environment, of a Caucasian male of 72-years-old. The intoxication occurred during a minimally invasive vascular surgery due to an incorrect assembly of the supply lines of medical gases (O2 and N2O). The identification of the cause of death resulted from the analysis of circumstantial data, macroscopic and microscopic autoptic findings, and immunohistochemical investigations based on the search for antibodies anti E-selectin, P-selectin, and HIF 1-α.ConclusionAlthough not pathognomonic of asphyxiation by N2O, the latter molecules are a valid and early marker of hypoxic insult. Therefore, in concert with all other findings, it may constitute valid support for the forensic pathologist to ascertain the cause of death in case of suspected intoxication by N2O.

Bolt Installation Defect Detection Based on a Multi-Sensor Method.

With the development of industrial automation, articulated robots have gradually replaced labor in the field of bolt installation. Although the installation efficiency has been improved, installation defects may still occur. Bolt installation defects can considerably affect the mechanical properties of structures and even lead to safety accidents. Therefore, in order to ensure the success rate of bolt assembly, an efficient and timely detection method of incorrect or missing assembly is needed. At present, the automatic detection of bolt installation defects mainly depends on a single type of sensor, which is prone to mis-inspection. Visual sensors can identify the incorrect or missing installation of bolts, but it cannot detect torque defects. Torque sensors can only be judged according to the torque and angel information, but cannot accurately identify the incorrect or missing installation of bolts. To solve this problem, a detection method of bolt installation defects based on multiple sensors is proposed. The trained YOLO (You Only Look Once) v3 network is used to judge the images collected by the visual sensor, and the recognition rate of visual detection is up to 99.75%, and the average confidence of the output is 0.947. The detection speed is 48 FPS, which meets the real-time requirement. At the same time, torque and angle sensors are used to judge the torque defects and whether bolts have slipped. Combined with the multi-sensor judgment results, this method can effectively identify defects such as missing bolts and sliding teeth. Finally, this paper carried out experiments to identify bolt installation defects such as incorrect, missing torque defects, and bolt slips. At this time, the traditional detection method based on a single type of sensor cannot be effectively identified, and the detection method based on multiple sensors can be accurately identified.

Failure of Threaded Connections: A Literature Review

Threaded fasteners are vastly used in the industry due to ease of mounting and dismounting and flexibility of design. Nonetheless, several researchers indicate that most failures recorded on nearly any kind of machinery and vehicles are initiated at fasteners. This review paper aims at summarising the failures involving threaded fasteners available in the literature. The analysis involves categorization of the failures according to the root cause, e.g., incorrect assembly, overload, fatigue, preload loss during operation, among others. The purpose of this review paper is to give a systematic glance of the topic to the scientific and technical community, to correctly orient future investigations on the broad topic of threaded fasteners.

Vplyv vysokej prevádzkovej teploty na funkčnosť ložísk

Rolling bearings are among the most important parts of machines and equipment. Many malfunctions in operation can be prevented by the correct choice of bearing, regular inspection and maintenance. The failure rate of the bearing is affected by many factors such as inappropriate storage, incorrect assembly, intrusion of foreign particles into the bearing spaces, inappropriately selected lubricant, or incorrect handling, transportation, etc. If damage or other deficiencies occur in rolling bearings, it is important to determine the cause of the damage so that appropriate measures can be taken to prevent their recurrence. Incipient damage to the bearing is reflected in the operation of the bearing, usually by a rise in temperature, or an increase in noise and stronger vibrations.

Influence of Form Defect on the Mechanical Behavior and Stress Intensity Factor of Shrink-Fitted Thick-Walled Cylinders

In this research work, the finite element software, ABAQUS is used to study by simulations the influence of form defect on mechanical behavior of a shrink-fitted assembly presenting internal radial cracks. Under the action of contact pressure induced by the tightening between two cylinders, these cracks resulting from incorrect assembly operations or materials elaboration defect, can be harmful to the assembly. Various simulations were carried out in two modeling cases, taking into account the geometric parameters of defect (amplitude Df), of cylinders (thickness t) and of cracks (length a, ratio a/t). Another important parameter such as the tightening was also considered in the modeling. The first modeling relates to the case with defect, external cylinder presents an oval (elliptical) form defect and internal radial cracks. The other concerns the perfect equivalent case (without form defect). The comparison of results obtained by two models shows that form defect modifies the uniformity of equivalent stresses distribution in cylinders and increases the value of stress intensity factor (SIF) KI in cracks. Defect amplitude and tightening significantly influence the value of equivalent stress and that of stress intensity factor (SIF) <i>KI</i>.

Poka Yoke Meets Deep Learning: A Proof of Concept for an Assembly Line Application

In this paper, we present the re-engineering process of an assembly line that features speed reducers and multipliers for agricultural applications. The “as-is” line was highly inefficient due to several issues, including the age of the machines, a non-optimal arrangement of the shop floor, and the absence of process standards. The assembly line issues were analysed with Lean Manufacturing tools, identifying irregularities and operations that require effort (Mura), overload (Muri), and waste (Muda). The definition of the “to-be” line included actions to update the department layout, modify the assembly process, and design the line feeding system in compliance with the concepts of Golden Zone (i.e., the horizontal space more ergonomically and easily accessible by the operator) and Strike Zone (i.e., the vertical workspace setup in accordance to ergonomics specifications). The re-engineering process identified a critical problem in the incorrect assembly of the oil seals, mainly caused by the difficulty in visually identifying the correct side of the component, due to different reasons. Convolutional neural networks were used to address this issue. The proposed solution resulted to be a Poka Yoke. The whole re-engineering process induced a productivity increase that is estimated from 46% to 80%. The study demonstrates how Lean Manufacturing tools together with deep learning technologies can be effective in the development of smart manufacturing lines.

The protein common assembly database (ProtCAD)-a comprehensive structural resource of protein complexes.

Proteins often act through oligomeric interactions with other proteins. X-ray crystallography and cryo-electron microscopy provide detailed information on the structures of biological assemblies, defined as the most likely biologically relevant structures derived from experimental data. In crystal structures, the most relevant assembly may be ambiguously determined, since multiple assemblies observed in the crystal lattice may be plausible. It is estimated that 10-15% of PDB entries may have incorrect or ambiguous assembly annotations. Accurate assemblies are required for understanding functional data and training of deep learning methods for predicting assembly structures. As with any other kind of biological data, replication via multiple independent experiments provides important validation for the determination of biological assembly structures. Here we present the Protein Common Assembly Database (ProtCAD), which presents clusters of protein assembly structures observed in independent structure determinations of homologous proteins in the Protein Data Bank (PDB). ProtCAD is searchable by PDB entry, UniProt identifiers, or Pfam domain designations and provides downloads of coordinate files, PyMol scripts, and publicly available assembly annotations for each cluster of assemblies. About 60% of PDB entries contain assemblies in clusters of at least 2 independent experiments. All clusters and coordinates are available on ProtCAD web site (http://dunbrack2.fccc.edu/protcad).

Molecular Assembly Lines in Active Droplets.

Large protein complexes are assembled from protein subunits to form a specific structure. In our theoretic work, we propose that assembly into the correct structure could be reliably achieved through an assembly line with a specific sequence of assembly steps. Using droplet interfaces to position compartment boundaries, we show that an assembly line can be self-organized by active droplets. As a consequence, assembly steps can be arranged spatially so that a specific order of assembly is achieved and incorrect assembly is strongly suppressed.

Sharp Increase of Problematic Mitogenomes of Birds: Causes, Consequences, and Remedies.

Authentic DNA sequences are crucial for reliable evolutionary inference. Concerns about the identification of DNA sequences have been voiced several times in the past but few quantitative studies exist. Mitogenomes play important roles in phylogenetics, phylogeography, population genetics, and DNA identification. However, the large number of mitogenomes being published routinely, often in brief data papers, has raised questions about their authenticity. In this study, we quantify problematic mitogenomes of birds and their reusage in other papers. Of 1,876 complete or partial mitogenomes of birds published until January 1, 2020, the authenticity of 1,559 could be assessed with sequences of conspecifics. Of these, 78 (5.0%) were found to be problematic, including 45 curated reference sequences. Problems were due to misidentification (33), chimeras of two or three species (23), sequencing errors/numts (18), incorrect sequence assembly (1), mislabeling at GenBank but not in the final paper (2), or vice versa (1). The number of problematic mitogenomes has increased sharply since 2012. Worryingly, these problematic sequences have been reused 436 times in other papers, including 385 times in phylogenies. No less than 53% of all mitogenomic phylogenies/networks published until January 1, 2020 included at least one problematic mitogenome. Problematic mitogenomes have resulted in incorrect phylogenetic hypotheses and proposals for unwarranted taxonomic revision, and may have compromised comparative analyses and measurements of divergence times. Our results indicate that a major upgrade of quality control measures is warranted. We propose a comprehensive set of measures that may serve as a new standard for publishing mitogenome sequences.

Overcoming uncollapsed haplotypes in long-read assemblies of non-model organisms

BackgroundLong-read sequencing is revolutionizing genome assembly: as PacBio and Nanopore technologies become more accessible in technicity and in cost, long-read assemblers flourish and are starting to deliver chromosome-level assemblies. However, these long reads are usually error-prone, making the generation of a haploid reference out of a diploid genome a difficult enterprise. Failure to properly collapse haplotypes results in fragmented and structurally incorrect assemblies and wreaks havoc on orthology inference pipelines, yet this serious issue is rarely acknowledged and dealt with in genomic projects, and an independent, comparative benchmark of the capacity of assemblers and post-processing tools to properly collapse or purge haplotypes is still lacking.ResultsWe tested different assembly strategies on the genome of the rotifer Adineta vaga, a non-model organism for which high coverages of both PacBio and Nanopore reads were available. The assemblers we tested (Canu, Flye, NextDenovo, Ra, Raven, Shasta and wtdbg2) exhibited strikingly different behaviors when dealing with highly heterozygous regions, resulting in variable amounts of uncollapsed haplotypes. Filtering reads generally improved haploid assemblies, and we also benchmarked three post-processing tools aimed at detecting and purging uncollapsed haplotypes in long-read assemblies: HaploMerger2, purge_haplotigs and purge_dups.ConclusionsWe provide a thorough evaluation of popular assemblers on a non-model eukaryote genome with variable levels of heterozygosity. Our study highlights several strategies using pre and post-processing approaches to generate haploid assemblies with high continuity and completeness. This benchmark will help users to improve haploid assemblies of non-model organisms, and evaluate the quality of their own assemblies.

Ultrastructural modifications induced by SARS-CoV-2 in Vero cells: a kinetic analysis of viral factory formation, viral particle morphogenesis and virion release.

Many studies on SARS-CoV-2 have been performed over short-time scale, but few have focused on the ultrastructural characteristics of infected cells. We used TEM to perform kinetic analysis of the ultrastructure of SARS-CoV-2-infected cells. Early infection events were characterized by the presence of clusters of single-membrane vesicles and stacks of membrane containing nuclear pores called annulate lamellae (AL). A large network of host cell-derived organelles transformed into virus factories was subsequently observed in the cells. As previously described for other RNA viruses, these replication factories consisted of double-membrane vesicles (DMVs) located close to the nucleus. Viruses released at the cell surface by exocytosis harbored the typical crown of spike proteins, but viral particles without spikes were also observed in intracellular compartments, possibly reflecting incorrect assembly or a cell degradation process.

A human SCO2 mutation helps define the role of Sco1p in the cytochrome oxidase assembly pathway.

Deficiencies in cytochrome oxidase, the terminal enzyme of the mitochondrial respiratory chain, are most often caused by an inability to complete assembly of the enzyme. Pathogenic mutations in SCO2, which encodes a cytochrome oxidase assembly factor, were recently described in several cases of fatal infantile cardioencephalomyopathy. To determine the molecular etiology of these disorders, we describe the generation and characterization of the parallel mutations in the homologous yeast SCO1 gene. We show that the E155K yeast sco1 mutant is respiration-competent, whereas the S240F mutant is not. Interestingly, the S240F mutation allows partial but incorrect assembly of cytochrome oxidase, as judged by an altered cytochrome aa(3) peak. Immunoblot analysis reveals a specific absence of subunit 2 from the cytochrome oxidase in this mutant. Taken together, our data suggest that Sco1p provides copper to the Cu(A) site on subunit 2 at a step occurring late in the assembly pathway. This is the first instance of a yeast cytochrome oxidase assembly mutant that is partially assembled. The S240F mutant also represents a powerful new tool with which to elucidate further steps in the cytochrome oxidase assembly pathway.

A Novel Iterative-Based Field Search Technique for Roundness Evaluation

Circularity is one of the frequently observed features in manufacturing industry. Most of the components manufactured are unions of the fundamental shapes, one of which is the circle. Due to very close tolerances, micro and nano-sized components’ manufacturing serves a very challenging task. Slight variance in the manufactured component can lead to incorrect assembly and inefficient system performance. Hence, the roundness evaluation of any circular component is important. The present article proposes a novel algorithm to evaluate the roundness error based on the minimum zone circle (MZC) concept. The proposed algorithm is an iterative field search technique. Compared to the existing approaches, the proposed method is very effective in determining the roundness error. Furthermore, it also performed well both on uniformly and non-uniformly spaced data. The results show that it is simple, robust and flexible enough to vary the search field area for better computational efficiency.

Investigation into damaged gear of off-road motorcycles

If failure occurs in gear wheels in a racer motorcycle gearbox, the possible causes are manifold: inadequate material, improper care (poor lubrication, incorrect assembly) or inadequate thermochemical treatment procedure. This investigation focused on spur wheels of chromium-nickel Czech Standard (ČSN) 16720 steel containing 0.18 % C, 0.4 % Mn, 1.5 % Cr, 4.25 % Ni and 1 % W. The steel had been quenched to 60-62 HRC and the case hardening depth was 0.8 mm. The client requested that these wheels have a life of 100 hours. The failure occurred while the wheels were in operation. The fracture surfaces in the wheels were examined in a scanning electron microscope (SEM). The fracture surfaces were prominent in the failure locations. EDS point analysis in the SEM revealed spots with higher chromium levels on the fracture surfaces. The average size of these spots was several dozen micrometres. The spots were suspected to have caused or contributed to the failure. A hardness profile across one tooth was measured using a microhardness tester. In addition, the thickness of the carburized layer was determined. Quality of the surface was assessed using macrophoto-graphs taken with a low-power stereomicroscope. In addition, metallographic sections were prepared and observed in a scanning electron microscope (SEM) and light microscope.