Structure-function Research Articles

In-situ measurements of contact evolution for fractal rough surfaces under normal compression

The contact interface plays a key role in the overall functionality and stability of structures. Understanding the evolution of the contact interface over time and its dependency on materials and load is crucial for functional integrity and operational safety assessment. In this study, we employ in-situ three-dimensional X-ray computed tomography (3DXRCT) to examine the creep behavior of 3D-printed surfaces exhibiting various roughness under constant normal compression. We observe that the overall contact area enlargement during the contact creep decreases with roughness amplitude and fractal dimension. The variation of interfacial separation distance is found to increase with roughness amplitude and decrease with fractal dimension. Correlation analysis reveals that the microcontact size played a more important role than the asperity shape in determining the microcontact enlargement. By examining the calculated interfacial strains extracted from XRCT measurements, significant deformations are found to occur at the non-contacting zones, indicating strong asperity interactions. This study offers high-resolution experimental measurements and unravels the asperity micromechanics for contact creep on rough surfaces, providing insights into understanding and optimizing the performance of rough interfaces.

Role of Artificial Intelligence in Drug Discovery and Target Identification in Cancer.

Drug discovery and development (DDD) is a highly complex process that necessitates precise monitoring and extensive data analysis at each stage. Furthermore, the DDD process is both timeconsuming and costly. To tackle these concerns, artificial intelligence (AI) technology can be used, which facilitates rapid and precise analysis of extensive datasets within a limited timeframe. The pathophysiology of cancer disease is complicated and requires extensive research for novel drug discovery and development. The first stage in the process of drug discovery and development involves identifying targets. Cell structure and molecular functioning are complex due to the vast number of molecules that function constantly, performing various roles. Furthermore, scientists are continually discovering novel cellular mechanisms and molecules, expanding the range of potential targets. Accurately identifying the correct target is a crucial step in the preparation of a treatment strategy. Various forms of AI, such as machine learning, neural-based learning, deep learning, and network-based learning, are currently being utilised in applications, online services, and databases. These technologies facilitate the identification and validation of targets, ultimately contributing to the success of projects. This review focuses on the different types and subcategories of AI databases utilised in the field of drug discovery and target identification for cancer.

Struggling toward abolition and dreaming beyond ableism in teacher education

ABSTRACT Abolition is a verb, referencing how people build safe conditions while dismantling (and developing solutions beyond) harmful institutions, including within education. Considering disability justice movement work in our roles as teacher educators, we explored how we might contend with the harmful purposes and functions of educational structures as we prepare future teachers to adopt abolitionist stances in their pedagogies. We begin with the premise that the current educational system, rooted in ableism, is fundamentally designed to rank, categorize and hypervalue/devalue children based on ability. Ableism intersects with multiple oppressions, fueling the inequitable distribution of resources in special/gifted education; and racist educational outcomes. To divest from ableism — decoupling learning from punishment in practice — we share three pedagogical examples from our own teaching, discussing how we support future teachers to imagine and enact teaching practices beyond providing services or accommodations, so that multiply-marginalized children and educators can be recognized as whole.

2D material-based surface plasmon resonance biosensors for applications in different domains: an insight.

The design of surface plasmon resonance (SPR) sensors has been greatly enhanced in recent years by the advancements in the production and integration of nanostructures, leading to more compact and efficient devices. There have been reports of novel SPR sensors having distinct nanostructures, either as signal amplification tags like gold nanoparticles (AuNPs) or as sensing substrate-like two-dimensional (2D) materials including graphene, transition metal dichalcogenides (TMDCs), MXene, black phosphorus (BP), metal-organic frameworks (MOFs), and antimonene. Such 2D-based SPR biosensors offer advantages over conventional sensors due to significant increases in their sensitivity with a good figure of merit and limit of detection (LOD). Due to their atomically thin structure, improved sensitivity, and sophisticated functionalization capabilities, 2D materials can open up new possibilities in the field of healthcare, particularly in point-of-care diagnostics, environmental and food monitoring, homeland security protection, clinical diagnosis and treatment, and flexible or transient bioelectronics. The present study articulates an in-depth analysis of the most recent developments in 2D material-based SPR sensor technology. Moreover, in-depth research of 2D materials, their integration with optoelectronic technology for a new sensing platform, and the predicted and experimental outcomes of various excitation approaches are highlighted, along with the principles of SPR biosensors. Furthermore, the review projects the potential prospects and future trends of these emerging materials-based SPR biosensors to advance in clinical diagnosis, healthcare biochemical, and biological applications.

Maturation of human cardiomyocytes derived from induced pluripotent stem cells (iPSC-CMs) on polycaprolactone and polyurethane nanofibrous mats

Investigating the potential of human cardiomyocytes derived from induced pluripotent stem cells (iPSC-CMs) in in vitro heart models is essential to develop cardiac regenerative medicine. iPSC-CMs are immature with a fetal-like phenotype relative to cardiomyocytes in vivo. Literature indicates methods for enhancing the structural maturity of iPSC-CMs. Among these strategies, nanofibrous scaffolds offer more accurate mimicry of the functioning of cardiac tissue structures in the human body. However, further research is needed on the use of nanofibrous mats to understand their effects on iPSC-CMs. Our research aimed to evaluate the suitability of poly(ε-caprolactone) (PCL) and polyurethane (PU) nanofibrous mats with different elasticities as materials for the maturation of iPSC-CMs. Analysis of cell morphology and orientation and the expression levels of selected genes and proteins were performed to determine the effect of the type of nanofibrous mats on the maturation of iPSC-CMs after long-term (10-day) culture. Understanding the impact of 3D structural properties in in vitro cardiac models on induced pluripotent stem cell-derived cardiomyocyte maturation is crucial for advancing cardiac tissue engineering and regenerative medicine because it can help optimize conditions for obtaining more mature and functional human cardiomyocytes.

Structural damage detection based on structural macro-strain mode shapes extracted from non-stationary output responses

Abstract Long-gauge fiber Bragg grating strain sensors have been widely employed because of their broader measuring range and higher sensitivity. However, current structural damage detection methods using macro-strain modal parameters are based on structural frequency response function or stationary power spectrum density, which are not applicable to non-stationary responses. To overcome this limitation, an improved method is proposed in this paper for structural damage detection based on structural macro-strain responses under unknown multi-point non-stationary excitations. First, a new concept of macro-strain energy spectrum transmissibility (MEST) is proposed using structural non-stationary macro-strain responses, and it is derived that MEST at a certain system pole equals the ratio of macro-strain mode shape. Then, the singular value decomposition technique is adopted for the MEST matrix to identify structural natural frequencies and macro-strain mode shapes. Finally, two damage detection indicators are constructed based on the identified normalized macro-strain mode shape (NMMS). The first indicator is the difference in structural NMMS before and after structural damage. The second one is based on the curvatures of structural NMMS, which can be used for structures without intact baseline. Numerical verifications are conducted to identify beam-type structural damage under multi-point non-stationary excitations or vehicle loads. Five damage scenarios with different measurement noise levels are investigated, and damage detection results validate the effectiveness of the proposed method.

Wood-Structured Nanomaterials as Highly Efficient, Self-Standing Electrocatalysts for Water Splitting.

Electrocatalytic water splitting (EWS) driven by renewable energy is widely considered an environmentally friendly and sustainable approach for generating hydrogen (H2), an ideal energy carrier for the future. However, the efficiency and economic viability of large-scale water electrolysis depend on electrocatalysts that can efficiently accelerate the electrochemical reactions taking place at the two electrodes. Wood-derived nanomaterials are well-suited for serving as EWS catalysts because of their hierarchically porous structure with high surface area and low tortuosity, compositional tunability, cost-effectiveness, and self-standing integral electrode configuration. Here, recent advancements in the design and synthesis of wood-structured nanomaterials serving as advanced electrocatalysts for water splitting are summarized. First, the design principles and corresponding strategies toward highly effective wood-structured electrocatalysts (WSECs) are emphasized. Then, a comprehensive overview of current findings on WSECs, encompassing diverse structural designs and functionalities such as supported-metal nanoparticles (NPs), single-atom catalysts (SACs), metal compounds, and heterostructured electrocatalysts based on engineered wood hosts are presented. Subsequently, the application of these WSECs in various aspects of water splitting, including the hydrogen evolution reaction (HER), oxygen evolution reaction (OER), overall water splitting (OWS), and hybrid water electrolysis (HWE) are explored. Finally, the prospects, challenges, and opportunities associated with the broad application of WSECs are briefly discussed. This review aims to provide a comprehensive understanding of the ongoing developments in water-splitting catalysts, along with outlining design principles for the future development of WSECs.

Analysis of Bolt Loosening due to Transvers Vibration

Bolt loosening is a critical issue in engineering applications where vibration-induced failures pose significant risks to the structural integrity and functionality of mechanical systems. This project aims to investigate the phenomenon of bolt loosening resulting from the transfer of vibrations and develop effective strategies to mitigate this problem. The study employs a comprehensive approach, combining experimental analysis, numerical simulations, and theoretical modeling to gain insights into the underlying mechanisms of bolt loosening. Furthermore, a theoretical model is developed to predict the susceptibility of different bolted joints to loosening based on factors such as material properties, bolt size, and tightening torque. The model is validated using experimental data, ensuring its accuracy and reliability in practical applications.

Solar wind data analysis aided by synthetic modeling: A better understanding of plasma frame variations from temporal data

In situ measurements of the solar wind, a turbulent and anisotropic plasma flow originating at the Sun, are mostly carried out by single spacecraft, resulting in one-dimensional time series. The conversion of these measurements to the spatial frame of the plasma is a great challenge, but it is required for direct comparison of the measurements with magnetohydrodynamic turbulence theories. We present a tool kit based on the synthetic modeling of solar wind fluctuations as two-dimensional noise maps with adjustable spectral and power anisotropy that can help with the temporal-spatial conversion of real data. Specifically, by following the spacecraft trajectory through a noise map (relative velocity and angle relative to some mean magnetic field) with properties tuned to mimic those of the solar wind, the likelihood that the temporal data fluctuations represent parallel or perpendicular fluctuations in the plasma frame can be quantified by correlating structure functions of the noise map. Synthetic temporal data can also be generated, which can provide a testing ground for analysis applied to the solar wind data. We demonstrate this tool by investigating Parker Solar Probe's seventh encounter trajectory and data, and we showcase several possible ways in which it can be used. We find that whether temporal variations in the spacecraft frame come from parallel or perpendicular variations in the plasma frame strongly depends on the spectral and power anisotropy of the measured wind. Data analysis assisted by such underlying synthetic models as presented here could open up new ways to interpret measurements in the future, specifically in the more reliable determination of plasma frame quantities from temporal measurements.

Third‐Order Structure Functions of Zonal Winds in the Thermosphere Using CHAMP and GOCE Observations

AbstractWe use multi‐year observations of cross‐track winds (u) from the CHAllenging Minisatellite Payload (CHAMP) and the Gravity Field and Steady State Ocean Circulation Explorer (GOCE) to calculate third‐order structure functions in the thermosphere as a function of horizontal separation (s). They are computed using the mean (〈δu3〉) and the median and implemented over non‐polar satellite paths in both hemispheres. On height averages, 〈δu3〉 is shown to scale with s2 for s ≃ 80–1,000 km, in agreement with equivalent estimates in the lower atmosphere from aircraft observations. Conversely, follows an s3 power law for almost the whole s range, consistent with the two‐dimensional turbulence scaling law for a direct enstrophy cascade. These scaling laws appear independent of winds in distinct atmospheric regions. Furthermore, the functions are predominantly positive, indicating a preferential cyclonic motion for the wind.

Structure–function characterization of two enzymes from novel subfamilies of manganese peroxidases secreted by the lignocellulose-degrading Agaricales fungi Agrocybe pediades and Cyathus striatus

BackgroundManganese peroxidases (MnPs) are, together with lignin peroxidases and versatile peroxidases, key elements of the enzymatic machineries secreted by white-rot fungi to degrade lignin, thus providing access to cellulose and hemicellulose in plant cell walls. A recent genomic analysis of 52 Agaricomycetes species revealed the existence of novel MnP subfamilies differing in the amino-acid residues that constitute the manganese oxidation site. Following this in silico analysis, a comprehensive structure–function study is needed to understand how these enzymes work and contribute to transform the lignin macromolecule.ResultsTwo MnPs belonging to the subfamilies recently classified as MnP-DGD and MnP-ESD—referred to as Ape-MnP1 and Cst-MnP1, respectively—were identified as the primary peroxidases secreted by the Agaricales species Agrocybe pediades and Cyathus striatus when growing on lignocellulosic substrates. Following heterologous expression and in vitro activation, their biochemical characterization confirmed that these enzymes are active MnPs. However, crystal structure and mutagenesis studies revealed manganese coordination spheres different from those expected after their initial classification. Specifically, a glutamine residue (Gln333) in the C-terminal tail of Ape-MnP1 was found to be involved in manganese binding, along with Asp35 and Asp177, while Cst-MnP1 counts only two amino acids (Glu36 and Asp176), instead of three, to function as a MnP. These findings led to the renaming of these subfamilies as MnP-DDQ and MnP-ED and to re-evaluate their evolutionary origin. Both enzymes were also able to directly oxidize lignin-derived phenolic compounds, as seen for other short MnPs. Importantly, size-exclusion chromatography analyses showed that both enzymes cause changes in polymeric lignin in the presence of manganese, suggesting their relevance in lignocellulose transformation.ConclusionsUnderstanding the mechanisms used by basidiomycetes to degrade lignin is of particular relevance to comprehend carbon cycle in nature and to design biotechnological tools for the industrial use of plant biomass. Here, we provide the first structure–function characterization of two novel MnP subfamilies present in Agaricales mushrooms, elucidating the main residues involved in catalysis and demonstrating their ability to modify the lignin macromolecule.

Numerical analysis of thermal-hydraulic influence of geometric flow baffles on multistage Tesla valves in printed circuit heat exchangers

The innovative structure and flexible functionality of Tesla valves have attracted significant attention across various industries. Unlike conventional check valves, which open in response to fluid movement and pressure and close to prevent backflow, Tesla valves utilize interconnected pathways to create a highly efficient and reliable method for regulating fluid flow. However, the thermal–hydraulic influence associated with the utilization of different geometric configurations of flow baffles in Tesla valves remain incompletely understood. This study employs numerical simulations to assess the effectiveness of a printed circuit heat exchanger (PCHE) incorporating three layers of multistage Tesla valves with geometric flow baffles. The simulations, based on solving the Navier-Stokes and energy equations, focus on analyzing the behavior of liquid water within a temperature range of 30 to 90 °C, pertinent to applications such as geothermal heating systems. The employed Tesla valve configuration demonstrates superior performance, exhibiting a notable enhancement in thermal effectiveness ranging from 13 % to 55 % compared to configurations utilizing zigzag, separate, and overlapping NACA 0020 airfoils under otherwise identical conditions. Three crucial geometric parameters are introduced to characterize the shape of flow baffles in multistage Tesla valves: the length from the baffle apex to the baffle half-front sphere, the radius of the baffle half-front sphere, and the distance from the baffle apex to the centerline of the entrance flow channel. Performance evaluation criteria (PEC) indicate that while the overlapping airfoil configuration performs better than both zigzag and separate configurations, the current Tesla valve design achieves approximately a 10–14 % higher PEC value than the overlapping airfoil configuration. The manipulation of geometric parameters for flow baffles is generally believed to be a critical step in the advancement of multistage Tesla valves, contributing to the enhancement of heat transfer and potentially broadening the applicability of these valves to various practical heat transfer systems.

The scaffold protein disabled 2 (DAB2) and its role in tumor development and progression.

Disabled 2 (DAB2) is a multifunctional protein that has emerged as a critical component in the regulation of tumor growth. Its dysregulation is implicated in various types of cancer, underscoring its importance in understanding the molecular mechanisms underlying tumor development and progression. This review aims to unravel the intricate molecular mechanisms by which DAB2 exerts its tumor-suppressive functions within cancer signaling pathways. We conducted a comprehensive review of the literature focusing on the structure, expression, physiological functions, and tumor-suppressive roles of DAB2. We provide an overview of the structure, expression, and physiological functions of DAB2. Evidence supporting DAB2's role as a tumor suppressor is explored, highlighting its ability to inhibit cell proliferation, induce apoptosis, and modulate key signaling pathways involved in tumor suppression. The interaction between DAB2 and key oncogenes is examined, elucidating the interplay between DAB2 and oncogenic signaling pathways. We discuss the molecular mechanisms underlying DAB2-mediated tumor suppression, including its involvement in DNA damage response and repair, regulation of cell cycle progression and senescence, and modulation of epithelial-mesenchymal transition (EMT). The review explores the regulatory networks involving DAB2, covering post-translational modifications, interactions with other tumor suppressors, and integration within complex signaling networks. We also highlight the prognostic significance of DAB2 and its role in pre-clinical studies of tumor suppression. This review provides a comprehensive understanding of the molecular mechanisms by which DAB2 exerts its tumor-suppressive functions. It emphasizes the significance of DAB2 in cancer signaling pathways and its potential as a target for future therapeutic interventions.

Transient temperature measurement of silicon carbide Schottky barrier diode based on thermal reflection.

In this article, we present a transient temperature detection device for silicon carbide (SiC) Schottky barrier diodes (SBDs) based on thermal reflection theory. We constructed a thermal reflection temperature measurement device based on a 530-nm green laser. This device is more suitable for transient temperature measurement of SiC SBDs than previous thermal reflection equipment. The accuracy of temperature measurement by our device was confirmed by comparison with the results of infrared thermal imaging. The high temporal resolution characteristics of the thermal reflection technology allowed the detection of millisecond-level transient temperature changes in SiC SBDs. In addition, we investigated the complementarity of transient temperature change curves during heating and cooling processes, as well as the reasons for the differences between these curves. Finally, we used the structural function method combined with the Bayesian deconvolution algorithm to obtain the thermal resistance along the heat flow path of the device and validated the results using an established thermal resistance testing method.

Metal binding feature of copper‒induced metallothionein from freshwater crab Sinopotamon henanense reveals its Cu‒thionein character

Sinopotamon Henanense expresses two metal‒induced metallothioneins (MTs), Cd‒induced MT and Cu‒induced MT (ShCuMT). The Cd‒induced MT has been characterized as a Cd‒thiolate MT. However, it is unknown whether ShCuMT is a Cu‒thiolate MT. In the present study, ShCuMT was expressed heterologously in Escherichia coli and purified by Ni‒NTA column and superdex‒75 column. And its metal‒binding feature was evaluated by DTNB reaction, circular dichroism spectroscopy (CD), isothermal microtitration (ITC), electrospray flight mass spectrometry (ESI‒TOF‒MS), and matrix‒assisted laser desorption ionization flight mass spectrometry (MALDI‒TOF‒MS). Bioinformatics analysis demonstrated that ShCuMT possessed the cysteine‒triplet motif of a Cu‒specific MT. Expression and purification of ShCuMT illustrated that SUMO tag used as the production system for ShCuMT resulted in a high production yield. The stability order of ShCuMT binding metal ions were Cu (Ⅰ) > Cd (Ⅱ) > Zn (Ⅱ). The CD spectrum indicated that ShCuMT binding with Cu (I) exhibited a compact thiol metal clusters structure. Besides, there emerged no a visible nickel‒thiol absorption after Ni‒NTA column affinity chromatography. The ITC results implied that Cu‒ShCuMT possessed the optimal thermodynamic conformation and the highest stoichiometric number of Cu (Ⅰ). Overall, the results suggested that SUMO fusion system is a robust and inexpensive approach for ShCuMT expression and Ni‒NTA column had no influence on metal binding of ShCuMT and Cu(Ⅰ) was considered its cognate metal ion, and ShCuMT possessed canonical Cu‒thiolate characteristics. The metal binding feature of ShCuMT reported here contributes to elucidating the structure‒function relationship of ShCuMT in S. Henanense.

Switchable and conspicuous retroreflective sensors inspired by the wing scale of an emerald swallowtail

Butterfly wings possess distinct micro/nanostructures that contribute to their vibrant coloration, light-trapping capabilities, and sensitivity to various stimuli. These complex features have inspired the creation of diverse devices and systems, such as sensors, photovoltaics, photocatalysis, and robotics. Specifically, the wing scales of the Emerald Swallowtail (Papilio palinurus) display iridescent, polarization-sensitive, and retroreflective colors due to their hierarchical structures. However, current technologies fail to mimic these natural designs fully, limiting their practical application in everyday life. In this study, we introduce a groundbreaking method for fabricating artificial wing scales that emulate the biological structure's functionality with a much simpler geometry. By integrating self-graded lossy media into metallic micro-concavity arrays, we achieve pronounced iridescent effects in both coaxial and non-coaxial arrangements, while preserving retroreflective properties. In particular, the simplified design allows for switchable color patterns based on the viewing angle. Demonstrating the concept, we successfully employ these conspicuous retroreflectors in hydrogen gas detection and the bi-directional/switchable recognition of patterned signals.

A computational approach for structural and functional analyses of disease-associated mutations in the human CYLD gene

Tumor suppressor cylindromatosis protein (CYLD) regulates NF-κB and JNK signaling pathways by cleaving K63-linked poly-ubiquitin chain from its substrate molecules and thus preventing the progression of tumorigenesis and metastasis of the cancer cells. Mutations in CYLD can cause aberrant structure and abnormal functionality leading to tumor formation. In this study, we utilized several computational tools such as PANTHER, PROVEAN, PredictSNP, PolyPhen-2, PhD-SNP, PON-P2, and SIFT to find out deleterious nsSNPs. We also highlighted the damaging impact of those deleterious nsSNPs on the structure and function of the CYLD utilizing ConSurf, I-Mutant, SDM, Phyre2, HOPE, Swiss-PdbViewer, and Mutation 3D. We shortlisted 18 high-risk nsSNPs from a total of 446 nsSNPs recorded in the NCBI database. Based on the conservation profile, stability status, and structural impact analysis, we finalized 13 nsSNPs. Molecular docking analysis and molecular dynamic simulation concluded the study with the findings of two significant nsSNPs (R830K, H827R) which have a remarkable impact on binding affinity, RMSD, RMSF, radius of gyration, and hydrogen bond formation during CYLD-ubiquitin interaction. The principal component analysis compared native and two mutants R830K and H827R of CYLD that signify structural and energy profile fluctuations during molecular dynamic (MD) simulation. Finally, the protein–protein interaction network showed CYLD interacts with 20 proteins involved in several biological pathways that mutations can impair. Considering all these in silico analyses, our study recommended conducting large-scale association studies of nsSNPs of CYLD with cancer as well as designing precise medications against diseases associated with these polymorphisms.

Bridge Assessment Analysis using Sufficiency Rating Method (Case Study of The Mungkung Overpass)

Bridges play a crucial role in connecting various routes and water bodies, necessitating regular monitoring to prevent potential hazards and losses due to deterioration. In Indonesia employs the Bridge Management System (BMS) for decision-making regarding maintenance, repair, and replacement activities, its reliance on a limited set of criteria may lead to uncertainties in bridge condition assessmsents. This study explores the Sufficiency Rating (SR) method as an alternative for assessing bridge feasibility. By considering multiple factors, including structural adequacy, serviceability, functionality, and public interest, the SR method offers a comprehensive approach to bridge evaluation. An analysis of the Mungkung Overpass on the Ngawi Kertasono toll road was conducted to evaluate the effectiveness of the SR method. The findings classified the bridge as excellent, indicating no immediate need for treatment. However, the SR method has limitations, particularly in visually assessing damage to superstructure and substructure elements, which may introduce subjectivity. Overall, this research contributes to the ongoing development of bridge assessment methodologies in Indonesia, aiming to enhance decision-making processes and ensure the safety and longevity of bridge infrastructure. After analyzing the data obtained through the implementation of the SR method, it was revealed that S1 achieved a value of 45%, S2 achieved 23%, S3 achieved 12.7%, and S4 achieved 6%. The total actual value of the four parameters calculated based on the SR method was 74.7%, with a difference of 25.3% from the maximum value. These findings clearly illustrated that the bridge satisfied the criteria for deficiency, thereby necessitating comprehensive rehabilitation measures to be undertaken.

Let-7 microRNA targets BmCentrin to modulate the development and functionality of the middle silk gland in the silkworm, Bombyx mori.

The silk gland of the silkworm Bombyx mori serves as a valuable model for investigating the morphological structure and physiological functions of organs. Previous studies have demonstrated the notable regulatory role of let-7 microRNA in the silk gland, but its specific molecular mechanism remains to be elucidated across different segments of this organ. In this study, we further investigated the functional mechanism of let-7 in the middle silk gland (MSG). The MSG of a let-7 knockout strain was analyzed using a combined proteomic and metabolomic technique, revealing the enrichment of differential proteins and metabolites in the DNA synthesis and energy metabolism pathways. BmCentrin was identified as a novel target gene of let-7 in the MSG, and its downregulation inhibited the proliferation of BmN4-SID1 cells, which is exactly opposite to the role of let-7 in these cells. CRISPR/Cas9 genome editing and transgenic technologies were employed to manipulate BmCentrin in the MSG. Knockout of BmCentrin led to severe MSG atrophy, whereas the overexpression of BmCentrin resulted in beaded MSG. Further measurements of these knockout or overexpression strains revealed significant changes in the expression levels of sericin protein genes, the weight of the cocoon and the mechanical properties of the silk. Investigating the biological role of BmCentrin in the silk gland offers valuable insights for elucidating the molecular mechanisms by which let-7 controls silk gland development and silk protein synthesis in the silkworm.

Anthocyanins as Natural Food Colorings: The Chemistry Behind and Challenges Still Ahead.

Anthocyanins are polyphenolic O-glycosides widely responsible for the bright red, purple, and blue colors in the plant kingdom, including a great variety of fruits and vegetables. Hence, they have attracted considerable scientific and industrial interest as potential natural food colorings. However, individual anthocyanins are intrinsically reactive molecules combining electrophilic, nucleophilic, and electron-donating properties. This reactivity may be not only a source of color diversity with, for instance, the formation of new pigments upon winemaking and storage but also a cause of great color instability involving a combination of reversible and irreversible mechanisms (e.g., water addition, autoxidation) leading to colorless products. Hence, using anthocyanin-rich plant extracts as food colorings requires a deep understanding of these color-damaging mechanisms and, no less importantly, of the color-stabilizing mechanisms developed by plants, including π-stacking interactions (self-association, copigmentation), metal binding, and a combination of both. The potential of anthocyanins from deeply colored vegetables, typically acylated by hydroxycinnamic acid residues, will be emphasized in that respect. Moreover, food-grade biopolymers (proteins, polysaccharides) may provide suitable matrices for ready-to-use formulations of anthocyanins as food colorings. In this short review, the mechanisms of color loss and color stabilization are discussed as a function of anthocyanin structure and environment, and some challenges still ahead are outlined.