Three-dimensional Structural Model Research Articles

Study on pore-crack evolution and connectivity of coal subjected to controlled electrical pulse based on CT scanning technology

Controlled electric pulse (CEP) technology is a novel method for enhancing coal seam permeability. To study the pore-crack evolution and connectivity of the coal body by CEP, a self-built CEP cracking and enhancing permeability of coal rock test system was used to test five groups of coal samples under different breakdown voltages (BVs). We established a three-dimensional crack structure and equivalent pore network model for before and after penetration using high-precision micro-CT technology to quantitatively study the evolution and connectivity of the pore and crack structures of the coal body. The results showed that with rising BV, coal body crushing intensifies, leading to an increased cracking ratio and fractal dimension. This summarised the three stages of coal sample crushing by CEP. In addition, the proportion of larger equivalent pores and throat radii in the breakdown coal body was significantly increased compared to that of raw coal, and the connectivity structure was improved to different degrees compared to that of raw coal. Eventually, a three-dimensional crack network structure formed inside the coal samples, which was broken at both ends and complex in the middle, providing a transport channel for coalbed methane mining.

Structural deformation dynamic simulation of weft knitted fabric basic stitch

To address the current problem of separating the structural and deformation models of weft knitted fabrics’ basic stitch, and to achieve synchronous simulation of the stitch’s structural form and deformation behavior, we studied the structural form and deformation behavior of the basic stitch, including weft plain stitch, rib stitch, and purl stitch. We established a three-dimensional structural model and conducted data analysis, improving the traditional mass-spring model to obtain a deformation model that fits better with the knitted fabric. We then investigated the connection between the structural and deformation models and constructed a correlation model, and used NURBS (Non-Uniform Rational B-Splines) curve application, force analysis, and dynamic solution to study the simulation of the correlation model. Finally, based on computer technology, we achieved dynamic simulation of the structural deformation of weft knitted fabrics’ basic stitch and demonstrated the simulation effect, proving the feasibility of the method and the rationality of the model.

Structural analyzes suggest that MiSSP13 and MiSSP16.5 may act as proteases inhibitors during ectomycorrhiza establishment in Laccaria bicolor

•The signaling process during mycorrhiza establishment involves intense molecular communication between symbionts. It has been suggested that a group of protein effectors, the so-called MiSSPs, plays a broader function in the symbiosis metabolism, however, many of these remain uncharacterized structurally and functionally.•Herein we used three-dimensional protein structure modeling methods, ligand analysis, and molecular docking to structurally characterize and describe two protein effectors, MiSSP13 and MiSSP16.5, with enhanced expression during the mycorrhizal process in Laccaria bicolor.•MiSSP13 and MiSSP16.5 show structural homology with the cysteine and aspartate protease inhibitor, cocaprin (CCP1). Through structural analysis, it was observed that MiSSP13 and MiSSP16.5 have an active site similar to that observed in CCP1. The protein-protein docking data showed that MiSSP13 and MiSSP16.5 interact with the papain and pepsin proteases at sites that are near to where CCP1 interacts with these same targets, suggesting a function as inhibitor of cysteine and aspartate proteases. The interaction of MiSSP13 with papain and MiSSP16.5 with pepsin was stronger than the interaction of CCP1 with these proteases, suggesting that the MiSSPs had a greater activity in inhibiting these classes of proteases. Based on the data supplied, a model is proposed for the function of MiSSPs 13 and 16.5 during the symbiosis establishment. Our findings, while derived from in silico analyses, enable us formulate intriguing hypothesis on the function of MiSSPs in ectomycorrhization, which will require experimental validation.

Features and insights for molecular structure of Chinese Taixi anthracite at atomic scales

This work presents insights into the molecular structure of Chinese Taixi anthracite (TXA) at atomic scales. The comprehensive analysis of materials characterizations and data fitting & calculations are performed to reveal microscopic characteristics and structural parameters of TXA. Then the planar and three-dimensional molecular structure models of TXA are con with the help of computer-aided molecular design and multi-scale molecular simulation calculations. The chemical structure characteristics of TXA are systematically analyzed, such as the carbon framework, main functional groups, and typical chemical bonding features. It is found that aromatic carbons are the main skeleton of organic matter, combined with some aliphatic carbons mainly in form of methyl, methylene and methine. Conceptualized single molecular description of TXA is determined to be C763H397O21N8. Representative two-dimensional and three-dimensional molecular structural models are also constructed to describe the apparent molecular structural features of TXA. Finally, molecular structural models are further verified by the elemental composition, nuclear magnetic resonance, Fourier transform infrared, and bond concentration of TXA. In addition, we summarized microstructure features of coal with various metamorphism. This work could provide theoretical guidance for understanding the microstructure of TXA and building the correlation between coal structure and functional properties to achieve efficient utilization of coal resources.

Unlocking the Thermal Efficiency of Irregular Open-Cell Metal Foams: A Computational Exploration of Flow Dynamics and Heat Transfer Phenomena

An open-cell metal foam has excellent characteristics such as low density, high porosity, high specific surface area, high thermal conductivity, and low mass due to its unique internal three-dimensional network structure. It has gradually become a new material for enhanced heat transfer in industrial equipment, new compact heat exchangers, microelectronic device cooling, etc. This research established a comprehensive three-dimensional structural model of open-cell metal foams utilizing Laguerre–Voronoi tessellations and employed computational fluid dynamics to investigate its flow dynamics and coupled heat transfer performance. By exploring the impact of foam microstructure on flow resistance and heat transfer characteristics, the study provided insights into the overall convective heat transfer performance across a range of foam configurations with varying pore densities and porosities. The findings revealed a direct correlation between convective heat transfer coefficient (h) and pressure drop (ΔP) with increasing Reynolds number (Re), accompanied by notable changes in fluid turbulence kinetic energy (e) and temperature (T), ultimately influencing heat transfer efficiency. Furthermore, the analysis demonstrated that alterations in porosity (ε) and pore density significantly affected unit pressure drop (ΔP/L) and convective heat transfer coefficient (h). This study identified an optimal configuration, highlighting a metal foam with a pore density of 20 PPI and a porosity of 95% as exhibiting superior overall convective heat transfer performance.

An Insight on Microfluidic Organ-on-a-Chip Models for PM2.5-Induced Pulmonary Complications.

Pulmonary diseases like asthma, chronic obstructive pulmonary disorder, lung fibrosis, and lung cancer pose a significant burden to global human health. Many of these complications arise as a result of exposure to particulate matter (PM), which has been examined in several preclinical and clinical trials for its effect on several respiratory diseases. Particulate matter of size less than 2.5 μm (PM2.5) has been known to inflict unforeseen repercussions, although data from epidemiological studies to back this are pending. Conventionally utilized two-dimensional (2D) cell culture and preclinical animal models have provided insufficient benefits in emulating the in vivo physiological and pathological pulmonary conditions. Three-dimensional (3D) structural models, including organ-on-a-chip models, have experienced a developmental upsurge in recent times. Lung-on-a-chip models have the potential to simulate the specific features of the lungs. With the advancement of technology, an emerging and advanced technique termed microfluidic organ-on-a-chip has been developed with the aim of identifying the complexity of the respiratory cellular microenvironment of the body. In the present Review, the role of lung-on-a-chip modeling in reproducing pulmonary complications has been explored, with a specific emphasis on PM2.5-induced pulmonary complications.

Whole genome sequencing identifies novel mutations in malaria parasites resistant to artesunate (ATN) and to ATN + mefloquine combination.

The global evolution of resistance to Artemisinin-based Combination Therapies (ACTs) by malaria parasites, will severely undermine our ability to control this devastating disease. Here, we have used whole genome sequencing to characterize the genetic variation in the experimentally evolved Plasmodium chabaudi parasite clone AS-ATNMF1, which is resistant to artesunate + mefloquine. Five novel single nucleotide polymorphisms (SNPs) were identified, one of which was a previously undescribed E738K mutation in a 26S proteasome subunit that was selected for under artesunate pressure (in AS-ATN) and retained in AS-ATNMF1. The wild type and mutated three-dimensional (3D) structure models and molecular dynamics simulations of the P. falciparum 26S proteasome subunit Rpn2 suggested that the E738K mutation could change the toroidal proteasome/cyclosome domain organization and change the recognition of ubiquitinated proteins. The mutation in the 26S proteasome subunit may therefore contribute to altering oxidation-dependent ubiquitination of the MDR-1 and/or K13 proteins and/or other targets, resulting in changes in protein turnover. In light of the alarming increase in resistance to artemisin derivatives and ACT partner drugs in natural parasite populations, our results shed new light on the biology of resistance and provide information on novel molecular markers of resistance that may be tested (and potentially validated) in the field.

Cancer-Related Mutations in the Sam Domains of EphA2 Receptor and Ship2 Lipid Phosphatase: A Computational Study.

The lipid phosphatase Ship2 interacts with the EphA2 receptor by forming a heterotypic Sam (sterile alpha motif)-Sam complex. Ship2 works as a negative regulator of receptor endocytosis and consequent degradation, and anti-oncogenic effects in cancer cells should be induced by hindering its association with EphA2. Herein, a computational approach is presented to investigate the relationship between Ship2-Sam/EphA2-Sam interaction and cancer onset and further progression. A search was first conducted through the COSMIC (Catalogue of Somatic Mutations in Cancer) database to identify cancer-related missense mutations positioned inside or close to the EphA2-Sam and Ship2-Sam reciprocal binding interfaces. Next, potential differences in the chemical-physical properties of mutant and wild-type Sam domains were evaluated by bioinformatics tools based on analyses of primary sequences. Three-dimensional (3D) structural models of mutated EphA2-Sam and Ship2-Sam domains were built as well and deeply analysed with diverse computational instruments, including molecular dynamics, to classify potentially stabilizing and destabilizing mutations. In the end, the influence of mutations on the EphA2-Sam/Ship2-Sam interaction was studied through docking techniques. This in silico approach contributes to understanding, at the molecular level, the mutation/cancer relationship by predicting if amino acid substitutions could modulate EphA2 receptor endocytosis.

Investigation of a novel TBC1D24 variation causing autosomal dominant non-syndromic hearing loss.

Hearing loss is considered one of the most common sensory neurological defects, with approximately 60% of cases attributed to genetic factors. Human pathogenic variants in the TBC1D24 gene are associated with various clinical phenotypes, including dominant nonsyndromic hearing loss DFNA65, characterized by progressive hearing loss after the development of language. This study provides an in-depth analysis of the causative gene and mutations in a family with hereditary deafness. We recruited a three-generation family with autosomal dominant nonsyndromic hearing loss (ADNSHL) and conducted detailed medical histories and relevant examinations. Next-generation sequencing (NGS) was used to identify genetic variants in the proband, which were then validated using Sanger sequencing. Multiple computational software tools were employed to predict the impact of the variant on the function and structure of the TBC1D24 protein. A series of bioinformatics tools were applied to determine the conservation characteristics of the sequence, establish a three-dimensional structural model, and investigate changes in molecular dynamics. A detailed genotype and phenotype analysis were carried out. The family exhibited autosomal dominant, progressive, postlingual, and nonsyndromic sensorineural hearing loss. A novel heterozygous variant, c.1459C>T (p.His487Tyr), in the TBC1D24 gene was identified and confirmed to be associated with the hearing loss phenotype in this family. Conservation analysis revealed high conservation of the amino acid affected by this variant across different species. The mutant protein showed alterations in thermodynamic stability, elasticity, and conformational dynamics. Molecular dynamics simulations indicated changes in RMSD, RMSF, Rg, and SASA of the mutant structure. We computed the onset age of non-syndromic hearing loss associated with mutations in the TBC1D24 gene and identified variations in the hearing progression time and annual threshold deterioration across different frequencies. The identification of a new variant associated with rare autosomal dominant nonsyndromic hereditary hearing loss in this family broadens the range of mutations in the TBC1D24 gene. This variant has the potential to influence the interaction between the TLDc domain and TBC domain, thereby affecting the protein's biological function.

Power-cycling degradation monitoring of an IGBT module with VCE(sat) measurement in continuous operation of a chopper circuit

This paper presents a power-cycling degradation monitoring method of an IGBT module with a VCE(sat) sensing circuit and junction temperature prediction by a three-dimensional structure model. A chopper circuit was introduced to provide a continuous-current-conducting operation of the IGBT module. The VCE(sat) sensing circuit with a low-cost IoT platform “Leafony” was utilized to monitor the junction temperature of an IGBT chip, which transferred the measured signal as digital data, and thus obtained a higher noise immunity than an analog-based circuit. The junction temperature of IGBT chip in the power module was analyzed from the dissipated power of IGBT and the transient thermal impedance between the chips and the ambient. This analysis is effective not only to observe the degradation but also to estimate the thermal resistance. Comparing the temperature profile between experiment and prediction provides health condition of the IGBT model.Predicted thermal profiles agreed with measured ones with 10 % increase of thermal resistance, which was degraded by a power cycle tester. From these results, the proposed monitoring method is effective to detect the progress of power cycle degradation.

Clinical characteristics and identification of novel CNOT1 variants in three unrelated Chinese families with Vissers-Bodmer Syndrome

Vissers-Bodmer Syndrome, an autosomal dominant disease, is a neurodevelopmental disorder characterized by global developmental delay, intellectual disability, hypotonia and autistic features with a highly variable phenotype. It is caused by variants in the CCR4-NOT transcription complex, subunit 1 gene (CNOT1). However, the pathophysiologic mechanism of the Vissers-Bodmer Syndrome remains unclear. Notably, this syndrome has not been previously reported in the Chinese. In this study, we utilized whole exome sequencing to identify three novel variants in the CNOT1 gene, encompassing one frameshift variant and two missense variants, in three Chinese patients mainly presenting with developmental delay, intellectual disability and/or autism. Interestingly, three patients exhibited novel manifestations including spina bifida occulta, horse-shoe kidney and café-au-lait spot. The frameshift variant, p.Gly172Alafs*5, occurring de novo, leading to a premature stop codon in the protein, was classified into pathogenic. Two missense variants c.3451A > G (p.Asn1151Asp) and c.557C > T (p.Ser186Phe) were predicted to be deleterious by multiple prediction algorithms with high conservation among a variety of species. Additionally, three-dimensional structure modeling and predicting indicated the substitution of the mutated amino acids would decrease the stability of CNOT1 protein. Given that CNOT1 is a relatively novel disease gene, we evaluated the gene-disease validity following ClinGen Standard Operating Procedure. The existing evidence substantiates a “Definitive” level of gene-disease relationship. The genetic findings provide a reliable basis for the genetic counseling of the family reproduction. Moreover, our results expand the genetic and phenotypic spectrum of CNOT1-related Vissers-Bodmer Syndrome.

Pharmacogenomics of poor drug metabolism in greyhounds: Canine P450 oxidoreductase genetic variation, breed heterogeneity, and functional characterization.

Greyhounds metabolize cytochrome P450 (CYP) 2B11 substrates more slowly than other dog breeds. However, CYP2B11 gene variants associated with decreased CYP2B11 expression do not fully explain reduced CYP2B11 activity in this breed. P450 oxidoreductase (POR) is an essential redox partner for all CYPs. POR protein variants can enhance or repress CYP enzyme function in a CYP isoform and substrate dependent manner. The study objectives were to identify POR protein variants in greyhounds and determine their effect on coexpressed CYP2B11 and CYP2D15 enzyme function. Gene sequencing identified two missense variants (Glu315Gln and Asp570Glu) forming four alleles, POR-H1 (reference), POR-H2 (570Glu), POR-H3 (315Gln, 570Glu) and POR-H4 (315Gln). Out of 68 dog breeds surveyed, POR-H2 was widely distributed across multiple breeds, while POR-H3 was largely restricted to greyhounds and Scottish deerhounds (35% allele frequencies), and POR-H4 was rare. Three-dimensional protein structure modelling indicated significant effects of Glu315Gln (but not Asp570Glu) on protein flexibility through loss of a salt bridge between Glu315 and Arg519. Recombinant POR-H1 (reference) and each POR variant (H2-H4) were expressed alone or with CYP2B11 or CYP2D15 in insect cells. No substantial effects on POR protein expression or enzyme activity (cytochrome c reduction) were observed for any POR variant (versus POR-H1) when expressed alone or with CYP2B11 or CYP2D15. Furthermore, there were no effects on CYP2B11 or CYP2D15 protein expression, or on CYP2D15 enzyme kinetics by any POR variant (versus POR-H1). However, Vmax values for 7-benzyloxyresorufin, propofol and bupropion oxidation by CYP2B11 were significantly reduced by coexpression with POR-H3 (by 34-37%) and POR-H4 (by 65-72%) compared with POR-H1. Km values were unaffected. Our results indicate that the Glu315Gln mutation (common to POR-H3 and POR-H4) reduces CYP2B11 enzyme function without affecting at least one other major canine hepatic P450 (CYP2D15). Additional in vivo studies are warranted to confirm these findings.

Research on the Evaluation of the Effectiveness of Industry-Teaching Integration Construction of Higher Vocational Excellence Courses--Based on Network DEA Model Analysis

Abstract The integration of industry and education is an important model for building high-level higher vocational colleges and universities, and it is also a necessary way to promote the modernization and development of higher vocational education. Based on Hall’s three-dimensional structural model, this paper explores the specific process of the construction of industry-teaching integration of high-level, high-quality courses and evaluates the effectiveness of the construction of industry-teaching integration of high-level, high-quality courses using the network SBM-DEA model. The evaluation index system was first constructed according to the questionnaire survey method, Delphi method, and hierarchical analysis method, and then the indexes were screened and applied to the empirical analysis of the effectiveness of the construction of industry-teaching fusion of higher vocational boutique courses. The average overall operational efficiency of the industry-teaching fusion of boutique courses at 45 higher vocational colleges and universities is 0.547, which is the average level. However, the efficiency of the two phases still has some differences between the average efficiency value of the resource construction phase and the outcome output phase. The correlation coefficient between the efficiency of the outcome output stage and the overall operational efficiency is 0.885, which is highly correlated. Most institutions pay more attention to the operation of the outcome output stage. The R² of the fit between pure technical efficiency and comprehensive efficiency is 0.731, and the R² of the fit between scale efficiency and comprehensive efficiency is 0.264, indicating that pure technical efficiency is the dominant factor affecting the comprehensive efficiency of institutions. In the two stages of resource construction and output of results, the output side shows insufficient output, while the input side shows input redundancy, indicating that the input resources are not effectively utilized. This paper provides a direction of action to strengthen the deep integration of industry and education in higher vocational boutique courses and to promote complementary resources and a benign interaction between schools and enterprises.

3D modeling of salt domes according to detailed drilling data in the Precaspian region

To create three-dimensional models of arcomorph structures based on detailed data of drilling without involving genetic considerations and indirect information, the potential fields method is effective, which consists of finding an approximating three-dimensional function, the set of isolevel surfaces of which are identified with stratigraphic boundaries, using the coordinates of the formation intersection points. For approximation, mainly three-dimensional splines expressed in terms of Green’s functions were used. The main difficulties are associated with the presence of structural unconformities, to take into account which the initial data, and the models built on their basis, are subjected to special spatial transformations. To avoid the influence of high-amplitude arcomorphs on the geometry of the layers of the pre-salt complex, the modeling of the latter was carried out separately from the intensely deformed evaporates and overlying layers. Assaying of the method was carried out at one of the sites in the Caspian Sea. On the study area, according to the interpretation of logging data from 249 wells, a three-dimensional model was created, including several arcomorph structures, and covering the stratigraphic interval from the Emsian stage of the Lower Devonian to Quaternary deposits. The results confirmed the presence of arcomorphs with overturned beds. Such structural forms are poorly fixed by 2D–3D seismic survey methods. The proposed method can be applied in geological studies in the search and exploration of hydrocarbons in salt dome areas.

Stress–Structural Failure of a 610 m Crushing Station Left-Side Tunnel Section in Jinchuan II Mine: A Numerical Simulation Study

To address the stress–structural failure phenomenon that can be induced by the excavation of a left-side tunnel section of a 610 m crushing station, an unmanned aerial vehicle was used in this study to collect the geological conditions and rock mass information of the working face, and important geometric information such as the attitude and spacing of rock mass were extracted. Based on the identified attitude and spacing information, a three-dimensional rock mass structure and numerical simulation model of the 610 m crushing station left-side tunnel section were constructed using discrete element numerical simulation software (3DEC) (version 5.0). The results show that the surrounding rock instability of the left-side tunnel section of the 610 m crushing station is controlled by both the stress field in the contact zone between reddish-brown granite stratum and the gray-black-gray gneiss stratum. The cause of stress–structural failure is that the joint sets (JSet #2 and JSet #3) are most likely to form unfavorable blocks with the excavation surface due to unloading triggered by the excavation. Therefore, stress–structural failure disasters in jointed strata sections are one of the key issues for surrounding rock stability during crushing station excavation. It is suggested to adopt ‘optimized excavation parameters + combined support forms’ to systematically control stress–structural failure after unloading due to the excavation from three levels: surface, shallow, and deep. The stress–structural failure mechanism of deep rock mass is generally applicable to a large extent, so the results of this research have reference value for engineering projects facing similar problems around the world.

DeepMainmast: integrated protocol of protein structure modeling for cryo-EM with deep learning and structure prediction.

Three-dimensional structure modeling from maps is an indispensable step for studying proteins and their complexes with cryogenic electron microscopy. Although the resolution of determined cryogenic electron microscopy maps has generally improved, there are still many cases where tracing protein main chains is difficult, even in maps determined at a near-atomic resolution. Here we developed a protein structure modeling method, DeepMainmast, which employs deep learning to capture the local map features of amino acids and atoms to assist main-chain tracing. Moreover, we integrated AlphaFold2 with the de novo density tracing protocol to combine their complementary strengths and achieved even higher accuracy than each method alone. Additionally, the protocol is able to accurately assign the chain identity to the structure models of homo-multimers, which is not a trivial task for existing methods.

The fracture failure modelling of three-dimensional structures composed of quasi-brittle materials subjected to different loading velocities rates by the dipole-based BEM approach

This study presents a numerical formulation for representing the fracture-failure of three dimensional structures composed of quasi-brittle materials. In addition to the nonlinear nature of quasi-brittle fracture, the formulation accounts the mechanical effects of different loading velocities rates. Therefore, these developments enable the modelling of viscous-cohesive fracture processes. The Boundary Element Method (BEM) describes the mechanical fields by the dipole-based approach, which has been extended to the three dimensional problems herein. This BEM approach is effective in crack growth modelling because only one crack surface requires discretisation. The classical cohesive crack approach models the material resistance at the energy dissipation zone surrounding the crack front. Besides, a time dependent function updates the cohesive crack approach and incorporates the viscous behaviour by modifying the tensile material strength and the material fracture energy as a function of the loading velocity rate. Three applications demonstrate the adequate performance of the proposed formulation, in which the results obtained have been compared against analytical and experimental responses available in the literature.

LEARNM: Augmented Reality Mobile Application in Learning the Concepts of Basic Biological Structures

This study endeavors to investigate the effectiveness of LearnM, an innovative augmented reality mobile application, in elevating the comprehension and assimilation of molecular structures among Grade 12 Science, Technology, Engineering, and Mathematics (STEM) students. LearnM showcases an immersive and interactive platform that empowers students to visualize and manipulate intricate three-dimensional models of molecular structures through the convenience of their smartphones. By integrating cutting-edge augmented reality technology, LearnM aims to transcend the traditional boundaries of textbook-based learning, fostering an engaging and dynamic learning experience. The research design employed in this investigation entails a quasi-experimental study with a pretest-posttest control group design. A cohort of 40 Grade 12 STEM students has been selected, with participants randomly assigned to either the experimental or control group. The experimental group will utilize the LearnM application, while the control group will receive conventional instruction. Pretest and posttest assessments will be administered to both groups, enabling a comprehensive analysis of the application’s impact on learning outcomes. The significance of this research lies in its potential to augment the body of knowledge within the realm of mobile learning and augmented reality, with a specific emphasis on molecular biology education. The integration of technology in education has become increasingly vital in the digital age, and this study endeavors to shed light on the effectiveness of such applications in enhancing students’ understanding of complex scientific concepts. Keywords: Augmented Reality, Mobile Application, Molecular Biology, STEM Education.

Glucanase activity produced by rhizospheric Streptomyces tritolerans ARJ 32 and Streptomyces collinus ARJ 38 and the analysis of their encoding genes

Abstract. Budiman DZ, Purwaningtyas WE, Priyanto JA, Putra IP, Nawangsih AA, Wahyudi AT. 2023. Glucanase activity produced by rhizospheric Streptomyces tritolerans ARJ 32 and Streptomyces collinus ARJ 38 and the analysis of their encoding genes. Biodiversitas 24: 5831-5837. The enzyme ?-1,3-glucanase is capable of breaking down the glucan components in the cell walls of phytopathogenic fungi. Streptomyces spp. isolated from the maize rhizosphere, are believed to produce enzymes with glucanolytic activity, making them promising candidates for use as a biological control agent against these fungi. This work aims to quantitatively analyze the enzymatic activity of glucanase in Streptomyces tritolerans ARJ 32 and Streptomyces collinus ARJ 38 and identify their encoding genes (bglS) and the three-dimensional modeling of their protein structures. The dinitrosalicylic acid (DNS) method quantitively assays the glucanase enzyme. The TA-Cloning of the bglS gene was performed using pGEM-T Easy Plasmid Vector, and the three-dimensional protein structure was constructed using the I-TASSER program. According to the findings, both Streptomyces isolates exhibited glucanolytic activity. The glucanase enzyme activities of S. tritolerans ARJ 32 and S. collinus ARJ 38 peaked at eight days of incubation, with values of 31.116 U/mg and 41.599 U/mg, respectively. The partial bglS gene was present in both Streptomyces and identified as endo-?-1,3-glucanase from the glycoside hydrolase family 16 (GH 16). The deduced partial amino acid sequences were aligned and showed some highly conserved residue in the catalytic domain of GH 16. The three-dimensional structural model built from the partial bglS amino acid sequences displayed high-quality parameters and overlapped with the protein model of partial endo-?-1,3-glucanase from Nocardiopsis sp. F96 (2HYK). These preliminary results suggest that the two Streptomyces isolates had the potential to be used as glucanase enzyme producers.

Missing a "Missing Self" Mechanism: Modeling and Detection of Ly49 Expression in Canine NK Cells.

NK cells are a key focus in immuno-oncology, based on their ability to eliminate malignant cells without prior sensitization. Dogs are valuable models for translational immunotherapy studies, especially for NK cells, where critical species differences exist between mice and humans. Given that the mechanism for recognition of "self" by canine NK cells is currently unknown, we sought to evaluate expression of Ly49 in canine NK cells using in silico and high-throughput techniques. We interrogated the identified polymorphism/mutation in canine Ly49 and assessed the potential impact on structure using computational modeling of three-dimensional protein structure and protein-protein docking of canine Ly49 with MHC class I (MHC-I). Bulk and single-cell RNA-sequencing analysis was performed to detect gene expression of Ly49/KLRA1 in resting and activated NK cells. Tertiary protein structure demonstrated significant structural similarity to the known murine system. Molecular docking of canine Ly49 with MHC-I was favorable, converging at a single low-energy conformation. RNA sequencing revealed expression of Ly49/KLRA1 in both resting and activated NK cells and demonstrated almost exclusive expression of the gene in the NK cluster at the single-cell level. Despite prior reports of a mutated, nonfunctional canine Ly49, our data support that the protein product is predicted to bind to MHC-I in a comparable conformation to the murine system and is expressed in canine NK cells with upregulation following activation. Taken together, these data suggest that Ly49 is capable of recognizing MHC-I and therefore regulating NK cell function in dogs.