Minimal Region Research Articles

Copy number variations in RNF216 and postsynaptic membrane-associated genes are associated with bipolar disorder: a case-control study in the Japanese population.

Bipolar disorder (BD) is a common psychiatric disorder characterized by alterations between manic/hypomanic and depressive states. Rare pathogenic copy number variations (CNVs) that overlap with exons of synaptic genes have been associated with BD. However, no study has comprehensively explored CNVs in synaptic genes associated with BD. Here, we evaluated the relationship between BD and rare CNVs that overlap with synaptic genes, not limited to exons, in the Japanese population. Using array comparative genome hybridization, we detected CNVs in 1839 patients with BD and 2760 controls. We used the Synaptic Gene Ontology database to identify rare CNVs that overlap with synaptic genes. Using gene-based analysis, we compared their frequencies between the BD and control groups. We also searched for synaptic gene sets related to BD. The significance level was set to a false discovery rate of 10%. The RNF216 gene was significantly associated with BD (odds ratio, 4.51 [95% confidence interval, 1.66-14.89], false discovery rate < 10%). The BD-associated CNV that corresponded with RNF216 also partially overlapped with the minimal critical region of the 7p22.1 microduplication syndrome. The integral component of the postsynaptic membrane (Gene Ontology:0099055) was significantly associated with BD. The CNV overlapping with the intron region of GRM5 in this gene set showed a nominal significant association between cases and controls (P < 0.05). We provide evidence that CNVs in RNF216 and postsynaptic membrane-related genes confer a risk of BD, contributing to a better understanding of the pathogenesis of BD.

Association of the IceCube neutrinos with blazars in the CGRaBS sample

The origin of high-energy (HE) astrophysical neutrinos has remained an elusive hot topic in the field of HE astrophysics for the past decade. Apart from a handful of individual associations, the vast majority of HE neutrinos arise from unknown sources. While there are theoretically motivated candidate populations, such as blazars – a subclass of active galactic nuclei with jets pointed toward our line of sight – they have not been convincingly linked to HE neutrino production yet. Here, we perform a spatio-temporal association analysis between a sample of blazars (from the CGRaBS catalog) in the radio and optical bands and the most up-to-date IceCube HE neutrino catalog. We find that if the IceCube error regions are enlarged by 1° in quadrature, to account for unknown systematic errors at a maximal level, a spatio-temporal correlation between the multiwavelength light curves of the CGRaBS blazars and the IceCube HE neutrinos is hinted at, least at a 2.17σ significance level. On the other hand, when the IceCube error regions are taken as their published values, we do not find any significant correlations. A discrepancy in the blazar-neutrino correlation strengths, when using such minimal and enlarged error region scenarios, was also obtained in a recent study by the IceCube collaboration. In our study, this difference arises because several flaring blazars – coinciding with a neutrino arrival time – happen to narrowly miss the published 90%-likelihood error region of the nearest neutrino event. For all of the associations driving our most significant correlations, the flaring blazar is much less than 1° away from the published error regions. Therefore, our results indicate that the question of the blazar-neutrino connection is highly sensitive to the reconstruction of the neutrino error regions, whose reliability is expected to improve with the next generation of neutrino observatories.

Effect of Cr, Al and Mo additives on the wetting characteristics of molten Ni on (Ti, Zr, Hf, Nb, Ta)C high entropy ceramics

For the first time, the wetting behavior of the (Ti, Zr, Hf, Nb, Ta)C) high entropy carbide ceramics by molten Ni-based alloys was investigated using a sessile drop technique in a vacuum environment. Adding 10wt% of Cr, Mo, or Al into Ni resulted in final contact angles of 14°, 10°, and 14° on the (Ti, Zr, Hf, Nb, Ta)C substrate, respectively. The interaction mechanism between (Ti, Zr, Hf, Nb, Ta)C and Ni-based alloys occurs in two stages: the dissolution and interaction of the elements Ti, Zr, Hf with the alloys and the dissolution of NbC and TaC at the grain boundaries. SEM observations revealed that Cr and Al additives do not interact with carbides, while Mo was dissolved in carbides. Due to the low contact angle, minimal interaction region between alloy and ceramic, and short time of drop spreading, NiAl alloy is proven to be a promising binder for the HEC-based composites.

Methyltransferase METTL3 governs the modulation of SH3BGR expression through m6A methylation modification, imparting influence on apoptosis in the context of Down syndrome-associated cardiac development

Down syndrome (DS), caused by an additional chromosome 21, has a high risk of congenital heart defects (CHD), one of the primary causes of mortality in DS newborns. To elucidate the pathogenetic mechanisms underlying this condition, we explored the role of RNA m6A methylation, regulated by METTL3, in DS cardiac development and its impact on the expression of SH3BGR, a gene located at Down syndrome congenital heart disease (DS-CHD) minimal region. We analyzed DS fetal cardiac tissues to assess RNA m6A methylation levels and identify potential contributors. RNA sequencing was performed to detect differentially expressed genes in the same tissues. To further understand METTL3’s function in heart development, we inactivated Mettl3 in the developing mouse heart to mimic the significantly reduced METTL3 observed in DS cardiac development. Additionally, human cardiomyocyte AC16 cells were used to investigate the molecular mechanism by which METTL3 regulates SH3BGR expression. Apoptosis was analyzed to evaluate METTL3’s effect on heart development through SH3BGR regulation. Reduced m6A modification and decreased METTL3 expression were observed in human DS fetal hearts, along with a significant increase of SH3BGR expression. METTL3, through m6A modification, was found to regulate SH3BGR expression, by influencing mRNA stability. METTL3-deficient mouse embryos exhibited heart malformation with increased apoptosis, emphasizing its role in heart development. In DS hearts, METTL3 downregulation and SH3BGR upregulation, potentially orchestrated by abnormal m6A modification, contribute to gene dysregulation and apoptosis. This study reveals novel insights into DS cardiac pathology, highlighting the intricate role of METTL3 in DS congenital heart defects and presenting the m6A modification of SH3BGR as a potential therapeutic target.

Optimizing prostate cancer detection in transition zone: an analysis of apparent diffusion coefficient values in prostate magnetic resonance imaging evaluation with Prostate Imaging Reporting and Data System (PI-RADS) assessment.

Multiparametric magnetic resonance imaging (mpMRI) is increasingly used for the early detection of clinically significant prostate cancer (csPCa). However, the achievement of accurate detection rates, particularly for transition zone (TZ) lesions, remains challenging. We investigated the relationship between apparent diffusion coefficient (ADC) values in Prostate Imaging Reporting and Data System (PI-RADS) 3-5 lesions and csPCa within the TZ. We retrospectively evaluated TZ lesions in patients who underwent 3.0 Tesla MRI followed by MRI-targeted/transrectal ultrasound fusion biopsies (MRI-FBx). Fusion biopsies were performed for potentially cancerous lesions, defined as lesions with PI-RADS scores 3-5. We analyzed 196 lesions for which fusion biopsies were performed. The overall prostate cancer (PCa) detection rate was 53.6% (105/196); csPCa constituted 33.7% (66/196) of cases. The minimum ADC value was significantly lower for patients with csPCa (484.9±112.3 µm2/s) than for patients with benign histology or non-csPCa (P<0.001). Older age, higher initial prostate-specific antigen level, larger region of interest, and minimum and mean ADC values were associated with the presence of csPCa. Multivariate analysis indicated that only the minimum ADC value was an independent predictor of csPCa. Using a cutoff minimum ADC value <561 µm2/s to detect csPCa in TZ lesions increased the detection rate to 57.4% (54/94). The minimum ADC value provides substantial additional information regarding the presence of csPCa in the TZ, potentially improving the detection rates for lesions rated as PI-RADS 3-5 and informing the need for follow-up biopsies in areas that are initially cancer-free.

Host-Virus Cophylogenetic Trajectories: Investigating Molecular Relationships between Coronaviruses and Bat Hosts.

Bats, with their virus tolerance, social behaviors, and mobility, are reservoirs for emerging viruses, including coronaviruses (CoVs) known for genetic flexibility. Studying the cophylogenetic link between bats and CoVs provides vital insights into transmission dynamics and host adaptation. Prior research has yielded valuable insights into phenomena such as host switching, cospeciation, and other dynamics concerning the interaction between CoVs and bats. Nonetheless, a distinct gap exists in the current literature concerning a comparative cophylogenetic analysis focused on elucidating the contributions of sequence fragments to the co-evolution between hosts and viruses. In this study, we analyzed the cophylogenetic patterns of 69 host-virus connections. Among the 69 host-virus links examined, 47 showed significant cophylogeny based on ParaFit and PACo analyses, affirming strong associations. Focusing on two proteins, ORF1ab and spike, we conducted a comparative analysis of host and CoV phylogenies. For ORF1ab, the specific window ranged in multiple sequence alignment (positions 520-680, 770-870, 2930-3070, and 4910-5080) exhibited the lowest Robinson-Foulds (RF) distance (i.e., 84.62%), emphasizing its higher contribution in the cophylogenetic association. Similarly, within the spike region, distinct window ranges (positions 0-140, 60-180, 100-410, 360-550, and 630-730) displayed the lowest RF distance at 88.46%. Our analysis identified six recombination regions within ORF1ab (positions 360-1390, 550-1610, 680-1680, 700-1710, 2060-3090, and 2130-3250), and four within the spike protein (positions 10-510, 50-560, 170-710, and 230-730). The convergence of minimal RF distance regions with combination regions robustly affirms the pivotal role of recombination in viral adaptation to host selection pressures. Furthermore, horizontal gene transfer reveals prominent instances of partial gene transfer events, occurring not only among variants within the same host species but also crossing host species boundaries. This suggests a more intricate pattern of genetic exchange. By employing a multifaceted approach, our comprehensive strategy offers a nuanced understanding of the intricate interactions that govern the co-evolutionary dynamics between bat hosts and CoVs. This deeper insight enhances our comprehension of viral evolution and adaptation mechanisms, shedding light on the broader dynamics that propel viral diversity.

Interacting dust grains in complex plasmas: Ion wake formation and the electric potential

Dust grains have been used as minimally invasive probes to determine plasma parameters including the plasma density, temperature, and electric field in a plasma discharge. However, the dust grains in a plasma generate local potential disturbances due to the collection of charge and the subsequent electrostatic interactions between the dust and charged plasma particles. Dust grains in close proximity to one another exhibit interesting non-reciprocal interactions and self-organize into structures such as one-dimensional filamentary chains, two-dimensional “zigzags,” and three-dimensional helices, among others. The formation of these structures suggests that although the dust grains may be less invasive than traditional plasma probes, the disturbance to the local plasma environment introduced by dust grains is non-trivial. Commonly used analytic forms of the electric potential describing complex plasmas have failed to resolve the near-dust region, and as a result are insufficient to provide insight about the formation of complex dust structures. Here, we use an N-body simulation to compute the electric potential from ion densities near various dust grain configurations. We provide an alternative description to the standard analytic model for the electric potential of dust and ion wakes based on a Gaussian shaped cloud of ions. The electric potential obtained from simulations is used to identify minimum energy configurations for two and three dust grains. It is further demonstrated that the minimum potential region identified for N dust grains and their associated ion wakes does not predict the minimum-energy configuration of N + 1 dust grains.

Multi-wavelength Observations of Umbral Oscillations above a Sunspot

We investigate the umbral oscillation at multi-height solar atmospheres above a sunspot in the active region of National Oceanic and Atmospheric Administration 12680 on 2017 September 15. In this study, the extreme ultraviolet images were measured by the Atmospheric Imaging Assembly (AIA), while the ultraviolet spectral lines and images were observed by the Interface Region Imaging Spectrograph. At the sunspot umbra, the AIA 1700 Å intensity curve shows the primary oscillation with a long period of ∼(4.2±0.8) minutes, while the intensity curves in AIA 1600 Å, 171 Å, and 193 Å exhibit an apparent oscillation with a short period of ∼(2.8±0.3) minutes. Meanwhile, a short period of ∼(3.1±0.5) minutes is found in the Mg II h & k lines and the slit-jaw image at 2796 Å, a short period of ∼(2.9±0.4) minutes is detected in the Si IV 1393.76 Å line. Our observations suggest that the oscillatory periods at the sunspot umbra decrease with the height of solar outer atmospheres. The short period is roughly equal to 3 minutes, which could be interpreted as the propagating slow magnetoacoustic wave above the sunspot umbra, and it might originate from the temperature minimum region and then propagate up to the corona. While the long period is close to 5 minutes oscillation in the photosphere, which might be regarded as the solar P-mode wave.

A microdeletion event at 19q13.43 in IDH-mutant astrocytomas is strongly correlated with MYC overexpression

MYC dysregulation is pivotal in the onset and progression of IDH-mutant gliomas, mostly driven by copy-number alterations, regulatory element alterations, or epigenetic changes. Our pilot analysis uncovered instances of relative MYC overexpression without alterations in the proximal MYC network (PMN), prompting a deeper investigation into potential novel oncogenic mechanisms. Analysing comprehensive genomics profiles of 236 “IDH-mutant 1p/19q non-co-deleted” lower-grade gliomas from The Cancer Genome Atlas, we identified somatic genomic alterations within the PMN. In tumours without PMN-alterations but with MYC-overexpression, genes correlated with MYC-overexpression were identified. Our analyses yielded that 86/236 of astrocytomas exhibited no PMN-alterations, a subset of 21/86 displaying relative MYC overexpression. Within this subset, we discovered 42 genes inversely correlated with relative MYC expression, all on 19q. Further analysis pinpointed a minimal common region at 19q13.43, encompassing 15 genes. The inverse correlations of these 15 genes with relative MYC overexpression were re-confirmed using independent scRNAseq data. Further, the micro-deleted astrocytoma subset displayed significantly higher genomic instability compared to WT cases, but lower instability compared to PMN-hit cases. This newly identified 19q micro-deletion represents a potential novel mechanism underlying MYC dysregulation in astrocytomas. Given the prominence of 19q loss in IDH-mutant gliomas, our findings bear significant implications for understanding gliomagenesis.

The Effects of a Seagull Airfoil on the Aerodynamic Performance of a Small Wind Turbine

Birds’ flight characteristics such as gliding and dynamic soaring have inspired various optimizations and designs of wind turbines. The implementation of biological wing geometries such as the airfoil profile of seabirds has improved wind turbine performance. However, the field can still benefit from further investigation into the aerodynamic characteristics of an inspired design. Therefore, this study evaluated the effect of a seagull airfoil design on the aerodynamic performance of the National Renewable Energy Laboratory (NREL) Phase VI wind turbine. By replacing its S809 airfoil with the laser-scanned profile of the seagull airfoil, the aerodynamic behavior at key locations of the NREL Phase VI wind turbine blade was numerically simulated in a three-dimensional environment using the Ansys Fluent 2022 R1 computational fluid dynamics (CFD) code. The results were validated against the experimental data, and analysis of the torque outputs, pressure distributions, and velocity profiles that were generated by both the baseline and modified models demonstrated the ability of the seagull airfoil profile to modify regions of minimum and maximum local velocities to achieve highly favorable pressure differentials, significantly increasing the torque output of the NREL Phase VI wind turbine by 350, 539, 823, and 577 Nm at 10, 15, 20, and 25 m/s inlet velocities, respectively.

Exploring CK2 transcriptional regulation and signaling pathways in cancer.

e15199 Background: CK2 genes have been implicated in oncogenic processes in different cancer types, and their expression is known to be increased in many cancers relative to their normal tissue types. However the regulation of the three CK2 alpha transcripts and beta transcript is not well understood. Studies investigating the alpha gene ( CSNK2A1) and beta gene ( CSNK2B) found NFκB, ETS1, and SP1 as likely transcription factor regulators in lymphoid and fibroblast cell lines. Our study seeks to explore correlations between CK2 gene expression and the expression of these transcription factors in cancer. Since CK2 also regulates intracellular signaling through pathways such as PI3K-Akt, Jak-Stat, NFkB, Wnt, IL-6, TGF-β, Ras and Notch, this study also seeks to explore the correlation between CK2 expression and gene expression of known downstream signaling pathways across a variety of cancers. Methods: 32 non-overlapping cancer datasets were obtained from the The Cancer Genome Atlas (TCGA) and Broad GDAC Firehose projects which were obtained via cBioPortal.org and analyzed using a combination of cBioportal and RStudio statistical analysis packages. For each cancer type, mRNA expression of each of the four CK2 genes in cancer was compared to expression of transcription factors both previously identified in the literature and predicted generated by TFBIND analysis (via the transcription factor database TRANSFAC R3.4) of the CK2 minimal promoter regions. CK2 gene expression was also compared to expression of genes in known CK2 signaling pathways. Results: Our analysis found CSNK2A1 and CSNK2A3 expression to have a significant, strong positive correlation in nearly all cancer types studied, except pancreatic adenocarcinoma. CSNK2A1 demonstrated significant positive correlation with expression of the transcription factors NFKB1 and c-Rel in lymphoma, thymoma, and other cancers. CSNK2B demonstrated a significant, strong positive correlation with the transcription factors NELFE in every cancer examined. CK2 transcripts also showed significant correlations with other transcription factors and genes involved in IL-6, TGF-β, MAPK, and several other CK2 signaling pathways in many different cancer types. Conclusions: Overall this study demonstrates significant correlations between CK2 gene expression and previously proposed transcriptional regulation mechanisms as well as known CK2 signaling pathways in cancer.

A comprehensive analysis of minimally differentially methylated regions common to pediatric and adult solid tumors

Cancer is the second most common cause of death in children aged 1–14 years in the United States, with 11,000 new cases and 1200 deaths annually. Pediatric cancers typically have lower mutational burden compared to adult-onset cancers, however, the epigenomes in pediatric cancer are highly altered, with widespread DNA methylation changes. The rarity of pediatric cancers poses a significant challenge to developing cancer-type specific biomarkers for diagnosis, prognosis, or treatment monitoring. In the current study, we explored the potential of a DNA methylation profile common across various pediatric cancers. To do this, we conducted whole genome bisulfite sequencing (WGBS) on 31 recurrent pediatric tumor tissues, 13 normal tissues, and 20 plasma cell-free (cf)DNA samples, representing 11 different pediatric cancer types. We defined minimal focal regions that were differentially methylated across samples in the multiple cancer types which we termed minimally differentially methylated regions (mDMRs). These methylation changes were also observed in 506 pediatric and 5691 adult cancer samples accessed from publicly available databases, and in 44 pediatric cancer samples we analyzed using a targeted hybridization probe capture assay. Finally, we found that these methylation changes were detectable in cfDNA and could serve as potential cfDNA methylation biomarkers for early detection or minimal residual disease.

Forward modeling of the Mg I 12.32 μm line from a 3D magnetohydrodynamic model of an enhanced network

Context. The Mg I 12 μm lines, 12.22 and 12.32 μm, represent a pair of emission lines, and their line cores originate around the temperature minimum region. These lines exhibit the highest ratio of Zeeman to Doppler broadening in the infrared solar spectrum, making them crucial for accurately investigating the solar magnetic field. Aims. We synthesized the Mg I 12.32 μm Stokes profiles from a 3D magnetohydrodynamic (MHD) model and studied the validity of different methods for extracting the magnetic field. The observational profiles at different spatial resolution were simulated, which are helpful for the design of future solar telescopes with large apertures. Methods. We used a 3D MHD simulation model for an enhanced network computed using the Bifrost code. We performed nonlocal thermal equilibrium calculations for Stokes profiles of the Mg I 12.32 μm line using the Rybicki–Hummer code. Results. From the simulation we determined the average formation height of the Mg I 12.32 μm line to be around 450 km. The various solar features have different formation heights, and the variance of formation height in magnetic concentration regions is about 160 km. The wavelength-integrated method is proven effective in calibrating the integrated Stokes profiles to obtain the longitudinal (Bl) and horizontal (BH) field components for weak magnetic fields; the Bl is below 300 G. Furthermore, the weak field approximation was found to be valid only for estimating magnetic fields with Bl below 150 G. The Stokes I profiles clearly show Zeeman triple splitting around the magnetic flux concentration with a grid resolution of 48 km. We determined that a resolution of 0.97″, equivalent to the diffraction limit of a telescope with a diameter of 3.2 m, was necessary to detect the Zeeman splitting for the simulated snapshot. Our results from this 3D MHD model are valuable for interpreting data from the Accurate Infrared Magnetic Field Measurements of the Sun (AIMS) telescope and designing future solar infrared telescopes.

Field Line Curvature (FLC) Scattering in the Dayside Off‐Equatorial Minima Regions

AbstractMagnetic field line curvature (FLC) scattering is an effective mechanism for collisionless particle scattering. In the terrestrial magnetosphere, the FLC scattering plays an essential role in shaping the outer boundary of protons radiation belt, the rapid decay of ring current, and the formation of proton isotropic boundary (IB). However, previous studies have yet to adequately investigate the influence of FLC scattering on charged particles in the Earth's dayside magnetosphere, particularly in the off‐equatorial magnetic minima regions. This study employs T89 magnetic field model to investigate the impacts of FLC scattering on ring current protons in the dayside magnetosphere, with a specific focus on the off‐equatorial minimum regions. We analyze the spatial distributions of single and dual magnetic minima regions, adiabatic parameter, and pitch angle diffusion coefficients due to FLC scattering as functions of Kp. The results show that the effects of FLC scattering are significant not only on the dusk and dawn sides but also in the off‐equatorial minima regions on the noon. Additionally, we investigate the role of dipole tilt angle in the hemispheric asymmetry of FLC scattering effects. The dipole tilt angle controls the overall displacement of the dayside magnetosphere, resulting in different FLC scattering effects in the two hemispheres. Our study holds significance for understanding the FLC scattering effects in the off‐equatorial region of Earth's dayside magnetosphere and for constructing a more accurate dynamic model of particles.

CANONICAL CORRELATION ANALYSIS OF ECONOMIC GROWTH AND UNEMPLOYMENT RATE

The paper discusses the relationship between economic growth and the unemployment rate in Indonesia in each province in 2021. Both variables are considered as the dependent variable and there are 5 independent variables used in this research such as human index development, wage minimum region, poor citizens percentage, investment, and farmer rate value in each province. The method used to analyze is canonical correlation analysis, which is one of the dependent methods that are used for multivariate analysis. This method was used to determine which variable had the most significant relationship between dependent and independent variables, the data was taken from the Center of Statistics Bureau Indonesia in 2021. The result shows that among independent variables the human index development had the strongest relation it had 79%, while the correlation between the dependent and independent variable the unemployment rate gives the strongest influence it is 68%.

A framework to characterize, model, and optimize water-energy systems: case study of a novel HDH system

The rapid development in water-energy systems calls for advanced modeling and optimization tools to improve the technologies throughputs and minimize their energy consumption. While having a wide footprint in multiple research areas, Artificial Intelligence applications in water-energy systems are still in early stages. There is a need for generalized models to fully characterize parametric relationships, optimize technologies' performance, and have the flexibility to apply to different complex and non-linear systems. This article describes a digital twin framework that can be used for that purpose. This framework provides fundamental understanding of the process as in process-driven models alongside with the accuracy and usability of data-driven methods. The framework's structure focused on modeling and optimization aspects of digital twin models. As a part of developing a novel humidification-dehumidification desalination technology, this framework was used to model energy consumption based on 16 different operational parameters and was accurate to within 1 % of the data. Pairwise parameters sensitivities were identified by the framework for two case studies involving the whole cycle operation and a critical subsystem of the technology. Moreover, the framework was used to optimize the technology performance through data-efficient Bayesian search methods. Different search realms were used in this process. The framework was able to identify minimum and maximum energy consumption regions by sampling only 25 data points out of possible 5157 cases.

ACRE, a class of AP2/ERF transcription factors, activates the expression of sweet potato ß-amylase and sporamin genes through the sugar-responsible element CMSRE-1

Sugars, synthesized by photosynthesis in source organs, are loaded and utilized as an energy source and carbon skeleton in sink organs, and also known to be important signal molecules regulating gene expression in higher plants. The expression of genes coding for sporamin and β-amylase, the two most abundant proteins in storage roots of sweet potato, is coordinately induced by sugars. We previously reported on the identification of the carbohydrate metabolic signal-responsible element-1 (CMSRE-1) essential for the sugar-responsible expression of two genes. However, transcription factors that bind to this sequence have not been identified. In this study, we performed yeast one-hybrid screening using the sugar-responsible minimal promoter region of the ß-amylase gene as bait and a library composed only transcription factor cDNAs of Arabidopsis. Two clones, named Activator protein binding to CMSRE-1 (ACRE), encoding AP2/ERF transcription factors were isolated. ACRE showed transactivation activity of the sugar-responsible minimal promoter in a CMSRE-1-dependent manner in Arabidopsis protoplasts. Electric mobility shift assay (EMSA) using recombinant proteins and transient co-expression assay in Arabidopsis protoplasts revealed that ACRE could actually act to the CMSRE-1. Among the DEHYDRATION -RESPONSIVE ELEMENT BINDING FACTOR (DREB) subfamily, almost all homologs including ACRE, could act on the DRE, while only three ACREs could act to the CMSRE-1. Moreover, ACRE-homologs of Japanese morning glory also have the same property of DNA-binding preference and transactivation activity through the CMSRE-1. These findings suggested that ACRE plays an important role in the mechanism regulating the sugar-responsible gene expression through the CMSRE-1 conserved across plant species.

Minimal operation region prediction for networked control robotic manipulators subject to time‐varying delays and disturbances

AbstractDue to the disturbances and varying latency, a teleoperated robotic manipulator might not comply with the master control commands. Although prior studies on minimising the impact of network latency and disturbances on teleoperated robots were conducted, there has been very little research on the prediction of minimal operation regions of robotic arms, especially in the worst‐case scenarios when the disturbances and time delays still prevail even after impact minimisation. This study investigates the problem and proposes a novel solution to predicting minimal operation regions of networked control robotic manipulators. The proposed method can be used to forecast safe operation regions in which the manipulators will certainly enter and exclude regions that the robots will never penetrate. Leveraging on a Lyanonov Krasovskii criterion, the method performs region prediction by establishing minimal reachable bounding sets of the nonlinear, perturbed robotic arm's state vectors guided via a time‐varying delay‐dominant network. Though predominantly nonlinear, the entire prediction process is formulated as a tractable Linear Matrix Inequality (LMI) optimisation problem, which can be solved efficiently and effectively. Efficacy of the proposed method is validated with simulations where a simulated robotic arm is distorted with time‐varying delays and disturbances.

Efficient Voxel-Based Workpiece Update and Cutter-Workpiece Engagement Determination in Multi-Axis Milling

Abstract This paper presents a new method to efficiently update workpiece and determine cutter-workpiece engagement (CWE) in multi-axis milling simulation based on a uniform voxel modeling space. At each cutter location, a novel algorithm named direct voxel tracing is developed and used to generate a functional cutter surface voxel model to reliably establish the internal space of the milling cutter. The cutter internal space is represented by its voxel boundary with small memory usage. Through the Boolean subtraction between two successive voxel boundaries of the cutter internal space, a minimal voxel deactivation region is attained within which all active workpiece voxels are deactivated (removed) to update the workpiece model. To determine the associated CWE map, a 3D circle voxelization algorithm is employed. By slicing the cutter surface by a sequence of planes perpendicular to and along the cutter axis, CWE can be determined as the sliced 3D circles are voxelized. Quantitative comparisons of the proposed method against existing voxel modeling and vector modeling-based methods have been made. The results have demonstrated much improved computational efficiency of the proposed method in simulating the complex multi-axis milling operations.

A Sensitivity Study for Interpreting Nucleic Acid Sequence Screening Regulatory and Guidance Documentation: Toward a Foundational Synthetic Nucleic Acid Sequence Screening Framework.

The primary objectives of this study were to develop an objective nucleic acid sequence screening framework and to leverage the framework for an empirical sensitivity study that measures the impact of ambiguities in regulatory and guidance documentation regarding the control of synthetic nucleic acids and screening of nucleic acid orders. Foundational risk levels were constructed using the bioinformatic sequencing screening tool UltraSEQ. The risk levels range from high (corresponding to regulated sequences) to low (corresponding to nonregulated sequences of concern) to no-risk. A representative sequence data set (141,651 sequences) was constructed from publicly available synthetically derived sequences, and the percentage sequences in each risk level was determined, followed by the impact of changing key UltraSEQ parameters. The results of this study show that no-risk sequences represent 90-92% of sequences, and nonregulated sequences of concern represented 7-9% of the sequences regardless of the parameters. The parameter with the biggest impact on the number of sequences flagged was the minimum hit homology level, followed by minimum sequence region length, and finally uniqueness of the hit to a select agent sequence. The results of this empirical study provide a greater understanding for gene synthesis providers, biosafety and biosecurity practitioners, and the scientific community regarding the impact of various interpretations of regulatory and guidance documentation. The risk level framework provides a foundation to build upon for nucleic acid sequence screening as the threat landscape evolves. However, additional development is needed to build tools that connect predictions across sequences and orders to provide contextual risk-based predictions.