Structural Diversity Research Articles

Transforming crystal structures of cobalt molybdate to generate electron-rich sites for electrochemical detection of Pb(II)

BackgroundMost of the investigations on distinct crystal structures of catalysts are individually focused on the difference of surface functional groups or adsorption properties, but rarely explore the changes of active sites to affect the electrocatalytic performance. Catalysts with diverse crystal structures had been applied to modified electrodes in different electrocatalytic reactions. However, there is currently a lack of an essential understanding for the role of real active sites in catalysts with crystalline structures in electroanalysis, which is crucial for designing highly sensitive sensing interfaces. ResultsHerein, cobalt molybdate with divergent crystal structures (α-CoMoO4 and β-CoMoO4) were synthesized by adjusting the calcination temperature, indicating that α-CoMoO4 (800 °C) (60.00 μA μM−1) had the highest catalytic ability than β-CoMoO4 (700 °C) (38.68 μA μM−1) and α-CoMoO4 (900 °C) (29.55 μA μM−1) for the catalysis of Pb(II). It was proved that the proportion of Co(II) and Mo(IV) as electron-rich sites in α-CoMoO4 (800 °C) were higher than β-CoMoO4 (700 °C) and α-CoMoO4 (900 °C), possessing more electrons to participate in the valence cycles of Co(II)/Co(III) and Mo(IV)/Mo(VI) to boost the catalytic reduction of Pb(II). Specifically, Co(II) transferred a part of electrons to Mo(VI), promoting the formation of Mo(IV). Co(II) and Mo(IV), as the electron-rich sites, providing electrons to Pb(II), further accelerating the conversion of Pb(II) into Pb(0). SignificanceIn the process of detecting Pb(II), the CoMoO4 structures under different temperatures have distinct content of electron-rich sites Co(II) and Mo(IV). α-CoMoO4 (800 °C), with the highest content are benefited to detect Pb(II). This work is conducive to understanding the effect of the changes of active sites resulting from crystal transformation on the electrocatalytic performance, and provides a way to construct sensitive electrochemical interfaces of distinct active sites.

Low concentrations of saracatinib promote definitive endoderm differentiation through inhibition of FAK-YAP signaling axis

Optimizing the efficiency of definitive endoderm (DE) differentiation is necessary for the generation of diverse organ-like structures. In this study, we used the small molecule inhibitor saracatinib (SAR) to enhance DE differentiation of human embryonic stem cells and induced pluripotent stem cells. SAR significantly improved DE differentiation efficiency at low concentrations. The interaction between SAR and Focal Adhesion Kinase (FAK) was explored through RNA-seq and molecular docking simulations, which further supported the inhibition of DE differentiation by p-FAK overexpression in SAR-treated cells. In addition, we found that SAR inhibited the nuclear translocation of Yes-associated protein (YAP), a downstream effector of FAK, which promoted DE differentiation. Moreover, the addition of SAR enabled a significant reduction in activin A (AA) from 50 to 10 ng/mL without compromising DE differentiation efficiency. For induction of the pancreatic lineage, 10 ng/ml AA combined with SAR at the DE differentiation stage yielded a comparative number of PDX1+/NKX6.1+ pancreatic progenitor cells to those obtained by 50 ng/ml AA treatment. Our study highlights SAR as a potential modulator that facilitates the cost-effective generation of DE cells and provides insight into the orchestration of cell fate determination.Graphical

Develop Targeted Protein Drug Carriers through a High-Throughput Screening Platform and Rational Design.

Protein-based drugs offer advantages, such as high specificity, low toxicity, and minimal side effects compared to small molecule drugs. However, delivery of proteins to target tissues or cells remains challenging due to the instability, diverse structures, charges, and molecular weights of proteins. Polymers have emerged as a leading choice for designing effective protein delivery systems, but identifying a suitable polymer for a given protein is complicated by the complexity of both proteins and polymers. To address this challenge, a fluorescence-based high-throughput screening platform called ProMatch to efficiently collect data on protein-polymer interactions, followed by in vivo and in vitro experiments with rational design is developed. Using this approach to streamline polymer selection for targeted protein delivery, candidate polymers from commercially available options are identified and a polyhexamethylene biguanide (PHMB)-based system for delivering proteins to white adipose tissue as a treatment for obesity is developed. A branched polyethylenimine (bPEI)-based system for neuron-specific protein delivery to stimulate optic nerve regeneration is also developed. The high-throughput screening methodology expedites identification of promising polymer candidates for tissue-specific protein delivery systems, thereby providing a platform to develop innovative protein-based therapeutics.

Self‐Assembled Molecules Fostering Ordered Spatial Heterogeneity for Efficient Ruddlesden‐Popper Perovskite Solar Cells

Abstract2D Ruddlesden‐Popper perovskites (RPP) with formamidinium‐cesium (FAC) alloyed cations possess powerful thermal‐moisture stability. However, their photovoltaic performance is hindered by the elusive spatial heterogeneity at multiscale lengths, highly associated with their coupled charge selective contacts. Herein, it reports on how the rational formation of self‐assembly molecules (SAMs) govern the orderliness of the spatial heterogeneity and crystal growth model in FACs‐RPP films, which is proposed to dictate the charge‐carrier dynamics. Unlike the disordered RPP film driven by the amorphous polymeric contacts, the laterally ordered crystallized SAM contacts facilitate a spatially ordered 2D/3D heterogeneity of FACs‐RPP film in long range, where distinct minor 2D phases are tightly coupled in short range. Such ordered heterogeneity can improve the energy transfer efficiency, facilitating the charge‐carrier dynamics in a well‐aligned 2D/3D landscape is discovered. Finally, the champion solar cells using selective SAM‐based FACs‐RPP films (n = 5) yield an efficiency of 18.85% (certified 18.19%) and excellent damp‐heat/operational stability, ranking in the top league of reported 2D RPP solar cells. More importantly, this SAM‐based principle can be adapted to diverse 2D structures, active areas, and substrate types. This work provides design directions for leveraging bottom‐selective contacts to tune spatial heterogeneity in state‐of‐the‐art 2D RPP optoelectronics.

Engineering digital light processing ceramic composites for wide-range flexible sensing arrays

Flexible ceramic composites are promising candidates in capacitive pressure sensing applications. However, the fabrication of complex composite structures typically involves costly and time-consuming processes such as lithography or mold utilization. Digital light processing (DLP)-based 3D printing offers a layer-by-layer approach via photopolymerization, facilitating rapid prototyping of various ceramic composite structures in a single-step synthesis process. This study presents the successful implementation of a flexible ceramic composite based on the highly dielectric ceramic BaTiO3 and conductive MWCNT fillers by employing DLP 3D printing to create an hourglass-shaped stress concentration structure, aiming at enhancing flexible capacitive sensing capabilities. Blending commercial flexible resin with 4-acryloyl morpholine monomers yields a photocurable resin formulation with appropriate mechanical flexibility, photocurability, and optimal suspension viscosity suitable for DLP 3D printing. Furthermore, the proposed 3D-printed sensor arrays comprising hourglass-shaped unit cells demonstrate improved linear sensitivity across a broad pressure range owing to efficient stress concentration effects in a symmetric geometry, as corroborated by both finite element methods and experiments. DLP 3D printing, combined with tailored resin formulations and optimized ceramic and conductive filler contents, enables the rapid prototyping of diverse sensor structures with significantly enhanced sensitivity, highlighting the versatility of this approach for a wide range of applications.

Unlocking the power of AI models: exploring protein folding prediction through comparative analysis.

Protein structure determination has made progress with the aid of deep learning models, enabling the prediction of protein folding from protein sequences. However, obtaining accurate predictions becomes essential in certain cases where the protein structure remains undescribed. This is particularly challenging when dealing with rare, diverse structures and complex sample preparation. Different metrics assess prediction reliability and offer insights into result strength, providing a comprehensive understanding of protein structure by combining different models. In a previous study, two proteins named ARM58 and ARM56 were investigated. These proteins contain four domains of unknown function and are present in Leishmania spp. ARM refers to an antimony resistance marker. The study's main objective is to assess the accuracy of the model's predictions, thereby providing insights into the complexities and supporting metrics underlying these findings. The analysis also extends to the comparison of predictions obtained from other species and organisms. Notably, one of these proteins shares an ortholog with Trypanosoma cruzi and Trypanosoma brucei, leading further significance to our analysis. This attempt underscored the importance of evaluating the diverse outputs from deep learning models, facilitating comparisons across different organisms and proteins. This becomes particularly pertinent in cases where no previous structural information is available.

ANALYSIS OF MODERN DATABASES

In the current digital landscape, handling the vast and varied data requires customized processing and storage methods. Within a system, data within the same domain often uses different models, underscoring the importance of multi-model databases that can accommodate diverse data structures. These databases typically differentiate between primary and secondary models, necessitating clear data schema mappings. While the traditional relational data model persists as a well-studied and widely used approach, graph data models are gaining traction in areas like social networks, recommendation systems, and transportation networks. This article offers insights into the pros and cons of graph databases, providing a clearer understanding of their role in modern data management. Keywords: Graph databases, Database architecture, Graph-based data management, Multi-model DBMS, Relational databases.

Exfoliatable Layered 2D Honeycomb Crystals of Host‐guest Complexes Networked by CH‐π Hydrogen Bonds

Studies of graphene show that robust chemical bonds such as covalent bonds with trigonal‐planar atoms afford layered atomic 2D crystals possessing unique properties. Although layered molecular crystals are of interest to diversify elements and structures of 2D materials, the structural diversity of molecules as well as weak intermolecular interactions inevitably makes the design to be one‐off and individual. We herein report a versatile method to assemble layered molecular crystals. By developing a D3‐symmetry host at vertices to form a honeycomb layer, a diverse range of layered 2D host‐guest crystals were obtained. Substituents on the host, elements/structures of the guest, stereochemistries of the host and types of intercalants were diversified, which should allow for 6×32×3×2 combinations for structural diversification.

Exfoliatable Layered 2D Honeycomb Crystals of Host-guest Complexes Networked by CH-π Hydrogen Bonds.

Studies of graphene show that robust chemical bonds such as covalent bonds with trigonal-planar atoms afford layered atomic 2D crystals possessing unique properties. Although layered molecular crystals are of interest to diversify elements and structures of 2D materials, the structural diversity of molecules as well as weak intermolecular interactions inevitably makes the design to be one-off and individual. We herein report a versatile method to assemble layered molecular crystals. By developing a D3-symmetry host at vertices to form a honeycomb layer, a diverse range of layered 2D host-guest crystals were obtained. Substituents on the host, elements/structures of the guest, stereochemistries of the host and types of intercalants were diversified, which should allow for 6×32×3×2 combinations for structural diversification.

In vitro assessment of thyroid peroxidase inhibition by chemical exposure: comparison of cell models and detection methods.

Disruption of the thyroid hormone (TH) system is connected with diverse adverse health outcomes in wildlife and humans. It is crucial to develop and validate suitable in vitro assays capable of measuring the disruption of the thyroid hormone (TH) system. These assays are also essential to comply with the 3R principles, aiming to replace the ex vivo tests often utilised in the chemical assessment. We compared the two commonly used assays applicable for high throughput screening [Luminol and Amplex UltraRed (AUR)] for the assessment of inhibition of thyroid peroxidase (TPO, a crucial enzyme in TH synthesis) using several cell lines and 21 compounds from different use categories. As the investigated cell lines derived from human and rat thyroid showed low or undetectable TPO expression, we developed a series of novel cell lines overexpressing human TPO protein. The HEK-TPOA7 model was prioritised for further research based on the high and stable TPO gene and protein expression. Notably, the Luminol assay detected significant peroxidase activity and signal inhibition even in Nthy-ori 3-1 and HEK293T cell lines without TPO expression, revealing its lack of specificity. Conversely, the AUR assay was specific to TPO activity. Nevertheless, despite the different specificity, both assays identified similar peroxidation inhibitors. Over half of the tested chemicals with diverse structures and from different use groups caused TPO inhibition, including some widespread environmental contaminants suggesting a potential impact of environmental chemicals on TH synthesis. Furthermore, in silico SeqAPASS analysis confirmed the high similarity of human TPO across mammals and other vertebrate classes, suggesting the applicability of HEK-TPOA7 model findings to other vertebrates.

Tardigrade secretory proteins protect biological structures from desiccation

Tardigrades, microscopic animals that survive a broad range of environmental stresses, express a unique set of proteins termed tardigrade-specific intrinsically disordered proteins (TDPs). TDPs are often expressed at high levels in tardigrades upon desiccation, and appear to mediate stress adaptation. Here, we focus on the proteins belonging to the secreted family of tardigrade proteins termed secretory-abundant heat soluble (“SAHS”) proteins, and investigate their ability to protect diverse biological structures. Recombinantly expressed SAHS proteins prevent desiccated liposomes from fusion, and enhance desiccation tolerance of E. coli and Rhizobium tropici upon extracellular application. Molecular dynamics simulation and comparative structural analysis suggest a model by which SAHS proteins may undergo a structural transition upon desiccation, in which removal of water and solutes from a large internal cavity in SAHS proteins destabilizes the beta-sheet structure. These results highlight the potential application of SAHS proteins as stabilizing molecules for preservation of cells.

Structural Engineering of Metal‐Organic Frameworks for Efficient CO2 Reduction Reaction

AbstractMetal‐organic framework (MOF) materials have attracted much attention due to their diverse topological structures, excellent adsorption capacity, and unique physicochemical properties, which hold great promise in catalytic CO2 reduction reaction (CO2RR). However, the original MOFs materials have disadvantages such as poor electrical conductivity, high diffusion barrier and limited accessible catalytic sites, which seriously limit their application in CO2RR. Therefore, many structural engineering strategies have been used to improve the CO2RR performance of the MOFs materials. In this review, we mainly review the four main structure engineering strategies, i. e. crystal engineering, 2D engineering, heterostructure engineering and MOF derivatives engineering, in enhancing the catalytic CO2RR performance of the MOFs. We hope that this review will not only provide insights for the rational design of efficient MOFs materials for the CO2RR, but also stimulate more research work in this field.

Structural Diversity in Ga/In-Hydroxamate Metal-Organic Materials.

Developing metal-organic materials (MOMs) with chemical robustness is a prerequisite to exploring their intriguing properties and applications. As part of a continuing effort to construct robust MOMs featuring chelated building units, here we introduce a "bent" thiophene-2,5-dihydroxamate ligand with multiple intrinsic conformations when it is used as a chelating linkage. This approach should further diversify the coordination chemistry in hydroxamate-based MOM structures without compromising the stability. In combination with Group 13 metals Ga/In to ensure homoleptic metal vertices, we report the successful crystallization of four MOMs with diverse structures and dimensionalities: SUM-81 as a 0D metal-organic polyhedron (MOP), SUM-82 as a 2D MOF with an fes topology, SUM-83 and SUM-84 as distinct 1D coordination polymers with shapes mimic stairs and mesh tubes, respectively. As these structures indeed contain the aforementioned different ligand conformations and combinations thereof, these results expand our understanding of the coordination chemistry of hydroxamates. To demonstrate the potential applicability of hydroxamate-chelated robust MOMs, the permanently porous SUM-81 MOP was successfully incorporated in a series of mixed matrix membranes for CO2/N2 separation, showing impressive performances.

Cell-free biosynthesis and engineering of ribosomally synthesized lanthipeptides

Ribosomally synthesized and post-translationally modified peptides (RiPPs) are a major class of natural products with diverse chemical structures and potent biological activities. A vast majority of RiPP gene clusters remain unexplored in microbial genomes, which is partially due to the lack of rapid and efficient heterologous expression systems for RiPP characterization and biosynthesis. Here, we report a unified biocatalysis (UniBioCat) system based on cell-free gene expression for rapid biosynthesis and engineering of RiPPs. We demonstrate UniBioCat by reconstituting a full biosynthetic pathway for de novo biosynthesis of salivaricin B, a lanthipeptide RiPP. Next, we delete several protease/peptidase genes from the source strain to enhance the performance of UniBioCat, which then can synthesize and screen salivaricin B variants with enhanced antimicrobial activity. Finally, we show that UniBioCat is generalizable by synthesizing and evaluating the bioactivity of ten uncharacterized lanthipeptides. We expect UniBioCat to accelerate the discovery, characterization, and synthesis of RiPPs.

Electrochemical Synthesis of Hollow Nanoparticles via Anodic Transformation of Metastable Core-Shell Precursors.

Recent advances in electrosynthesis of nanomaterials expanded structural and compositional variations accessible by the electrochemical method; however, reliably synthesizable morphological variety fall shy of that available by conventional solvothermal synthesis. In this communication, electrochemical preparation of surfactant-free hollow nanoparticles is demonstrated. By anodic conversion of core-shell precursors with metastable cores, hollowed nickel nanoparticles with uniform dimensions were synthesized and characterized. Implementation of TEM grids as the working electrodes, identical location tracking of the morphological evolution of single particles to anodic stimulus has been demonstrated. The synthesized nanoparticles were employed as catalysts for the alkaline hydrogen evolution reaction and exhibited catalytic rates that compare favorably to the Pt/C benchmark. This marks the first pure electrochemical synthesis of hollow nanoparticles and shall contribute to the structural diversification of electrosynthesized nanomaterials.

Comprehensive O-Glycan Analysis by Porous Graphitized Carbon Nanoliquid Chromatography-Mass Spectrometry.

The diverse and unpredictable structures of O-GalNAc-type protein glycosylation present a challenge for its structural and functional characterization in a biological system. Porous graphitized carbon (PGC) liquid chromatography (LC) coupled to mass spectrometry (MS) has become one of the most powerful methods for the global analysis of glycans in complex biological samples, mainly due to the extensive chromatographic separation of (isomeric) glycan structures and the information delivered by collision induced fragmentation in negative mode MS for structural elucidation. However, current PGC-based methodologies fail to detect the smaller glycan species consisting of one or two monosaccharides, such as the Tn (single GalNAc) antigen, which is broadly implicated in cancer biology. This limitation is caused by the loss of small saccharides during sample preparation and LC. Here, we improved the conventional PGC nano-LC-MS/MS-based strategy for O-glycan analysis, enabling the detection of truncated O-glycan species and improving isomer separation. This was achieved by the implementation of 2.7 μm PGC particles in both the trap and analytical LC columns, which provided an enhanced binding capacity and isomer separation for O-glycans. Furthermore, a novel mixed-mode PGC-boronic acid-solid phase extraction during sample preparation was established to purify a broad range of glycans in an unbiased manner, including the previously missed mono- and disaccharides. Taken together, the optimized PGC nano-LC-MS/MS platform presents a powerful component of the toolbox for comprehensive O-glycan characterization.

Sex-Dimorphic Effects of Hypoglycemia on Metabolic Sensor mRNA Expression in Ventromedial Hypothalamic Nucleus-Dorsomedial Division (VMNdm) Growth Hormone-Releasing Hormone Neurons.

Growth hormone-releasing hormone (Ghrh) neurons in the dorsomedial ventromedial hypothalamic nucleus (VMNdm) express the metabolic transcription factor steroidogenic factor-1 and hypoglycemia-sensitive neurochemicals of diverse chemical structures, transmission modes, and temporal signaling profiles. Ghrh imposes neuromodulatory control of coexpressed transmitters. Multiple metabolic sensory mechanisms are employed in the brain, including screening of the critical nutrient glucose or the energy currency ATP. Here, combinatory laser-catapult-microdissection/single-cell multiplex qPCR tools were used to investigate whether these neurons possess molecular machinery for monitoring cellular metabolic status and if these biomarkers exhibit sex-specific sensitivity to insulin-induced hypoglycemia. Data show that hypoglycemia up- (male) or downregulated (female) Ghrh neuron glucokinase (Gck) mRNA; Ghrh gene silencing decreased baseline and hypoglycemic patterns of Gck gene expression in each sex. Ghrh neuron glucokinase regulatory protein (Gckr) transcript levels were respectively diminished or augmented in hypoglycemic male vs female rats; this mRNA profile was decreased by Ghrh siRNA in both sexes. Gene transcripts encoding catalytic alpha subunits of the energy monitor 5-AMP-activated protein kinase (AMPK), i.e., Prkaa1 and 2, were increased by hypoglycemia in males, yet only the former mRNA was hypoglycemia-sensitive in females. Ghrh siRNA downregulated baseline and hypoglycemia-associated Prkaa subunit mRNAs in males but elicited divergent changes in Prkaa2 transcripts in eu- vs hypoglycemic females. Results provide unique evidence that VMNdm Ghrh neurons express the characterized metabolic sensor biomarkers glucokinase and AMPK and that the corresponding gene profiles exhibit distinctive sex-dimorphic transcriptional responses to hypoglycemia. Data further document Ghrh neuromodulation of baseline and hypoglycemic transcription patterns of these metabolic gene profiles.

A high-precision 3D reconstruction method for the internal structure of small Solar System bodies

Small Solar System bodies (SSSBs) hold crucial information for understanding the formation and evolution of the Solar System. However, due to their considerable distance, small size, fast rotation, and a lack of prior information, the detection of these celestial bodies, especially their internal structures, faces numerous challenges. We explore whether the 3D structure of SSSBs can be reconstructed using monostatic radar. We investigated a more convenient observation mode and addressed the issue of the poor imaging quality of internal structures within existing imaging algorithms. Our study focused on a high-precision 3D imaging method for the internal structure of SSSBs based on radar signals. First, we considered a flyby observation mode that uses the spinning characteristics of the target for global observations, and we set up a scaled-down experimental system in the laboratory to simulate this observation mode. Next, we constructed a 3D printed physical surface model based on the shape of the asteroid 162173 Ryugu. We filled it with sand and inserted a small bottle containing different materials separately to construct two distinct layered analogs. The analogs were employed in laboratory measurements to acquire radar echoes, which were then inverted using both a classic back-projection (BP) algorithm and a modified multilayer back-projection (MLBP) method. The results shown that the 3D surface structure of the target can be reconstructed well through the BP and MLBP algorithms. The MLBP algorithm exhibits a higher reconstruction accuracy for internal structures. Moreover, compared to the BP method, the MLBP method is less sensitive to the quality of echo signals, resulting in a relatively stable imaging performance. Our findings reveal that observing and reconstructing the high-precision structure of SSSBs is feasible through our proposed method. The observation mode, experimental setup, and analog modeling approach are widely applicable and can be applied in future research on the detection of SSSBs with more diverse and complex structures.

Quantitative Non-targeted Screening to Profile Micropollutants in Sewage Sludge Used for Agricultural Field Amendments.

A considerable number of micropollutants from human activities enter the wastewater network for removal. However, at the wastewater treatment plant (WWTP), some proportion of these compounds is retained in the sewage sludge (biosolids), and due to its high content of nutrients, sludge is widely applied as an agricultural fertilizer and becomes a means for the micropollutants to be introduced to the environment. Accordingly, a holistic semiquantitative nontarget screening was performed on sewage sludges from five different WWTPs using nanoflow liquid chromatography coupled to high-resolution Orbitrap mass spectrometry. Sixty-one inorganic elements were measured using inductively coupled plasma mass spectrometry. Across all sludges, the nontarget analysis workflow annotated >21,000 features with chemical structures, and after strict prioritization and filtering, 120 organic micropollutants with diverse chemical structures and applications such as pharmaceuticals, pesticides, flame retardants, and industrial and natural compounds were identified. None of the tested sludges were free from organic micropollutants. Pharmaceuticals contributed the largest share followed by pesticides and natural products. The predicted concentration of identified contaminants ranged between 0.2 and 10,881 ng/g dry matter. Through quantitative nontarget analysis, this study comprehensively demonstrated the occurrence of cocktails of micropollutants in sewage sludges.

Fractal Engineering Integration in Antenna Arrays: A Comparative-review for Advanced Transceiver Systems with 5G/IoT Connectivity

The growing demand for space-efficient antennas compatible with portable electronic gadgets inspired the integration of recursively iterated fractal geometries (characterized by self-similarity, space-filling, and multiband/wideband capabilities) in antenna designs. Therefore, this article conducts an extensive survey on fractal-based single-port and multi-port patch antenna designs with multiband and ultrawideband characteristics for their implementation in 5G/IoT (Internet of Things) devices. The survey begins with a basic overview of fractal geometries and the iterated function system (IFS) technique employed for their generation. Further, it highlights the limitation of multipath fading prevalent in single-port antenna arrays that can be overcome by adopting multiple-input multiple-output (MIMO) technology. The MIMO antenna systems are vital for 5G networks to enhance data transmission rate, network capacity, and system reliability. Apart from these admirable attributes, the closely packed antenna elements in the MIMO configuration result in a severe mutual coupling. To address this limitation, various isolation enhancement techniques developed by distinguished researchers are thoroughly discussed in this article, detailing their merits and demerits. At last, this article portrays diverse band-notch structures integrated into the antenna designs to eradicate the existing interfering narrow bands in the ultrawideband (UWB) spectrum. The underlying reason for conducting this survey is to aid antenna designers and academicians with a thorough knowledge of distinct fractal geometries, various isolation improvement approaches, and band-notch techniques on a single platform, desired for designing 5G/IoT-based antenna systems.