Pro-CRISPR PcrIIC1-associated Cas9 system for enhanced bacterial immunity.

The CRISPR system is an adaptive immune system found in prokaryotes that defends host cells against the invasion of foreign DNA1. As part of the ongoing struggle between phages and the bacterial immune system, the CRISPR system has evolved into various types, each with distinct functionalities2. Type II Cas9 is the most extensively studied of these systems and has diverse subtypes. It remains uncertain whether members of this family can evolve additional mechanisms to counter viral invasions3,4. Here we identify 2,062 complete Cas9 loci, predict the structures of their associated proteins and reveal three structural growth trajectories for type II-C Cas9. We found that novel associated genes (NAGs) tended to be present within the loci of larger II-C Cas9s. Further investigation revealed that CbCas9 from Chryseobacterium species contains a novel ß-REC2 domain, and forms a heterotetrameric complex with an NAG-encoded CRISPR-Cas-system-promoting (pro-CRISPR) protein of II-C Cas9 (PcrIIC1). The CbCas9-PcrIIC1 complex exhibits enhanced DNA binding and cleavage activity, broader compatibility for protospacer adjacent motif sequences, increased tolerance for mismatches and improved anti-phage immunity, compared with stand-alone CbCas9. Overall, our work sheds light on the diversity and 'growth evolutionary' trajectories of II-C Cas9 proteins at the structural level, and identifies many NAGs-such as PcrIIC1, which serves as a pro-CRISPR factor to enhance CRISPR-mediated immunity.

Quantitative Lipid Imaging Reveals a New Signaling Function of Phosphatidylinositol-3,4-Bisphophate: Isoform- and Site-Specific Activation of Akt.

Activation of class I phosphatidylinositol 3-kinase (PI3K) leads to formation of phosphatidylinositol-3,4,5-trisphophate (PIP3) and phosphatidylinositol-3,4-bisphophate (PI34P2), which spatiotemporally coordinate and regulate a myriad of cellular processes. By simultaneous quantitative imaging of PIP3 and PI34P2 in live cells, we here show that they have a distinctively different spatiotemporal distribution and history in response to growth factor stimulation, which allows them to selectively induce the membrane recruitment and activation of Akt isoforms. PI34P2 selectively activates Akt2 at both the plasma membrane and early endosomes, whereas PIP3 selectively stimulates Akt1 and Akt3 exclusively at the plasma membrane. These spatiotemporally distinct activation patterns of Akt isoforms provide a mechanism for their differential regulation of downstream signaling molecules. Collectively, our studies show that different spatiotemporal dynamics of PIP3 and PI34P2 and their ability to selectively activate key signaling proteins allow them to mediate class I PI3K signaling pathways in a spatiotemporally specific manner.

Correction: Virus-mimicking nanosystems: from design to biomedical applications.

Correction for 'Virus-mimicking nanosystems: from design to biomedical applications' by Hao-Yang Liu et al., Chem. Soc. Rev., 2023, 52, 8481-8499, https://doi.org/10.1039/D3CS00138E.

Accurate Cancer Screening and Prediction of PD-L1-Guided Immunotherapy Efficacy Using Quantum Dot Nanosphere Self-Assembly and Machine Learning.

Accurate quantification of exosomal PD-L1 protein in tumors is closely linked to the response to immunotherapy, but robust methods to achieve high-precision quantitative detection of PD-L1 expression on the surface of circulating exosomes are still lacking. In this work, we developed a signal amplification approach based on aptamer recognition and DNA scaffold hybridization-triggered assembly of quantum dot nanospheres, which enables bicolor phenotyping of exosomes to accurately screen for cancers and predict PD-L1-guided immunotherapeutic effects through machine learning. Through DNA-mediated assembly, we utilized two aptamers for simultaneous ultrasensitive detection of exosomal antigens, which have synergistic roles in tumor diagnosis and treatment prediction, and thus, we achieved better sample classification and prediction through machine-learning algorithms. With a drop of blood, we can distinguish between different cancer patients and healthy individuals and predict the outcome of immunotherapy. This approach provides valuable insights into the development of personalized diagnostics and precision medicine.

One-Step Dual-Color Labeling of Viral Envelope and Intraviral Genome with Quantum Dots Harnessing Virus Infection.

Labeling the genome and envelope of a virus with multicolor quantum dots (QDs) simultaneously enables real-time monitoring of viral uncoating and genome release, contributing to our understanding of virus infection mechanisms. However, current labeling techniques require genetic modification, which alters the virus's composition and infectivity. To address this, we utilized the CRISPR/Cas13 system and a bioorthogonal metabolic method to label the Japanese encephalitis virus (JEV) genome and envelopes with different-colored QDs in situ. This technique allows one-step two-color labeling of the viral envelope and intraviral genome with QDs harnessing virus infection. In combination with single-virus tracking, we visualized JEV uncoating and genome release in real time near the endoplasmic reticulum of live cells. This labeling strategy allows for real-time visualization of uncoating and genome release at the single-virus level, and it is expected to advance the study of other viral infection mechanisms.

Organoids derived from patients provide a new opportunity for research and individualized treatment of malignant peritoneal mesothelioma.

BACKGROUND: Malignant peritoneal mesothelioma (MPM) is an extremely rare and highly invasive tumor. Due to the lack of accurate models that reflect the biological characteristics of primary tumors, studying MPM remains challenging and is associated with an exceedingly unfavorable prognosis. This study was aimed to establish a new potential preclinical model for MPM using patient-derived MPM organoids (MPMOs) and to comprehensively evaluate the practicality of this model in medical research and its feasibility in guiding individualized patient treatment. METHODS: MPMOs were constructed using tumor tissue from MPM patients. Histopathological analysis and whole genome sequencing (WGS) were employed to determine the ability of MPMOs to replicate the original tumor's genetic and histological characteristics. The subcutaneous and orthotopic xenograft models were employed to assess the feasibility of establishing an in vivo model of MPM. MPMOs were also used to conduct drug screening and compare the results with retrospective analysis of patients after treatment, in order to evaluate the potential of MPMOs in predicting the effectiveness of drugs in MPM patients. RESULTS: We successfully established a culture method for human MPM organoids using tumor tissue from MPM patients and provided a comprehensive description of the necessary medium components for MPMOs. Pathological examination and WGS revealed that MPMOs accurately represented the histological characteristics and genomic heterogeneity of the original tumors. In terms of application, the success rate of creating subcutaneous and orthotopic xenograft models using MPMOs was 88% and 100% respectively. Drug sensitivity assays demonstrated that MPMOs have different medication responses, and these differences were compatible with the real situation of the patients. CONCLUSION: This study presents a method for generating human MPM organoids, which can serve as a valuable research tool and contribute to the advancement of MPM research. Additionally, these organoids can be utilized as a means to evaluate the effectiveness of drug treatments for MPM patients, offering a model for personalized treatment approaches.

Electrochemiluminescence-Based Single-Particle Tracking of the Biomolecules Moving along Intercellular Membrane Nanotubes between Live Cells.

Electrochemiluminescence (ECL) imaging, a rapidly evolving technology, has attracted significant attention in the field of cellular imaging. However, its primary limitation lies in its inability to analyze the motion behaviors of individual particles in live cellular environments. In this study, we leveraged the exceptional ECL properties of quantum dots (QDs) and the excellent electrochemical properties of carbon dots (CDs) to develop a high-brightness ECL nanoprobe (CDs-QDs) for real-time ECL imaging between living cells. This nanoprobe has excellent signal-to-noise ratio imaging capabilities for the single-particle tracking (SPT) of biomolecules. Our finding elucidated the enhanced ECL mechanism of CDs-QDs in the presence of reactive oxygen species through photoluminescence, electrochemistry, and ECL techniques. We further tracked the movement of single particles on membrane nanotubes between live cells and confirmed that the ECL-based SPT technique using CD-QD nanoparticles is an effective approach for monitoring the transport behaviors of biomolecules on membrane nanotubes between live cells. This opens a promising avenue for the advancement of ECL-based single-particle detection and the dynamic quantitative imaging of biomolecules.

In Situ Quantitative Imaging of Plasma Membrane Stiffness in Live Cells Using a Genetically Encoded FRET Sensor.

Cell membrane stiffness is critical for cellular function, with cholesterol and sphingomyelin as pivot contributors. Current methods for measuring membrane stiffness are often invasive, ex situ, and slow in process, prompting the need for innovative techniques. Here, we present a fluorescence resonance energy transfer (FRET)-based protein sensor designed to address these challenges. The sensor consists of two fluorescent units targeting sphingomyelin and cholesterol, connected by a linker that responds to the proximity of these lipids. In rigid membranes, cholesterol and sphingomyelin are in close proximity, leading to an increased FRET signal. We utilized this sensor in combination with confocal microscopy to explore changes in plasma membrane stiffness under various conditions, including differences in osmotic pressure, the presence of reactive oxygen species (ROS) and variations in substrate stiffness. Furthermore, we explored the impact of SARS-CoV-2 on membrane stiffness and the distribution of ACE2 after attachment to the cell membrane. This tool offers substantial potential for future investigations in the field of mechanobiology.

A novel model for predicting prognosis and response to immunotherapy in nasopharyngeal carcinoma patients.

Blood-based biomarkers of immune checkpoint inhibitors (ICIs) response in patients with nasopharyngeal carcinoma (NPC) are lacking, so it is necessary to identify biomarkers to select NPC patients who will benefit most or least from ICIs. The absolute values of lymphocyte subpopulations, biochemical indexes, and blood routine tests were determined before ICIs-based treatments in the training cohort (n = 130). Then, the least absolute shrinkage and selection operator (Lasso) Cox regression analysis was developed to construct a prediction model. The performances of the prediction model were compared to TNM stage, treatment, and Epstein-Barr virus (EBV) DNA using the concordance index (C-index). Progression-free survival (PFS) was estimated by Kaplan-Meier (K-M) survival curve. Other 63 patients were used for validation cohort. The novel model composed of histologic subtypes, CD19+ B cells, natural killer (NK) cells, regulatory T cells, red blood cells (RBC), AST/ALT ratio (SLR), apolipoprotein B (Apo B), and lactic dehydrogenase (LDH). The C-index of this model was 0.784 in the training cohort and 0.735 in the validation cohort. K-M survival curve showed patients with high-risk scores had shorter PFS compared to the low-risk groups. For predicting immune therapy responses, the receiver operating characteristic (ROC), decision curve analysis (DCA), net reclassifcation improvement index (NRI) and integrated discrimination improvement index (IDI) of this model showed better predictive ability compared to EBV DNA. In this study, we constructed a novel model for prognostic prediction and immunotherapeutic response prediction in NPC patients, which may provide clinical assistance in selecting those patients who are likely to gain long-lasting clinical benefits to anti-PD-1 therapy.

Integrative metagenomic analysis reveals distinct gut microbial signatures related to obesity.

Obesity is a metabolic disorder closely associated with profound alterations in gut microbial composition. However, the dynamics of species composition and functional changes in the gut microbiome in obesity remain to be comprehensively investigated. In this study, we conducted a meta-analysis of metagenomic sequencing data from both obese and non-obese individuals across multiple cohorts, totaling 1351 fecal metagenomes. Our results demonstrate a significant decrease in both the richness and diversity of the gut bacteriome and virome in obese patients. We identified 38 bacterial species including Eubacterium sp. CAG:274, Ruminococcus gnavus, Eubacterium eligens and Akkermansia muciniphila, and 1 archaeal species, Methanobrevibacter smithii, that were significantly altered in obesity. Additionally, we observed altered abundance of five viral families: Mesyanzhinovviridae, Chaseviridae, Salasmaviridae, Drexlerviridae, and Casjensviridae. Functional analysis of the gut microbiome indicated distinct signatures associated to obesity and identified Ruminococcus gnavus as the primary driver for function enrichment in obesity, and Methanobrevibacter smithii, Akkermansia muciniphila, Ruminococcus bicirculans, and Eubacterium siraeum as functional drivers in the healthy control group. Additionally, our results suggest that antibiotic resistance genes and bacterial virulence factors may influence the development of obesity. Finally, we demonstrated that gut vOTUs achieved a diagnostic accuracy with an optimal area under the curve of 0.766 for distinguishing obesity from healthy controls. Our findings offer comprehensive and generalizable insights into the gut bacteriome and virome features associated with obesity, with the potential to guide the development of microbiome-based diagnostics.

LORE receptor homomerization is required for 3-hydroxydecanoic acid-induced immune signaling and determines the natural variation of immunosensitivity within the Arabidopsis genus.

The S-domain-type receptor-like kinase (SD-RLK) LIPOOLIGOSACCHARIDE-SPECIFIC REDUCED ELICITATION (LORE) from Arabidopsis thaliana is a pattern recognition receptor that senses medium-chain 3-hydroxy fatty acids, such as 3-hydroxydecanoic acid (3-OH-C10:0), to activate pattern-triggered immunity. Here, we show that LORE homomerization is required to activate 3-OH-C10:0-induced immune signaling. Fluorescence lifetime imaging in Nicotiana benthamiana demonstrates that AtLORE homomerizes via the extracellular and transmembrane domains. Co-expression of AtLORE truncations lacking the intracellular domain exerts a dominant negative effect on AtLORE signaling in both N. benthamiana and A. thaliana, highlighting that homomerization is essential for signaling. Screening for 3-OH-C10:0-induced reactive oxygen species production revealed natural variation within the Arabidopsis genus. Arabidopsis lyrata and Arabidopsis halleri do not respond to 3-OH-C10:0, although both possess a putative LORE ortholog. Both LORE orthologs have defective extracellular domains that bind 3-OH-C10:0 to a similar level as AtLORE, but lack the ability to homomerize. Thus, ligand binding is independent of LORE homomerization. Analysis of AtLORE and AlyrLORE chimera suggests that the loss of AlyrLORE homomerization is caused by several amino acid polymorphisms across the extracellular domain. Our findings shed light on the activation mechanism of LORE and the loss of 3-OH-C10:0 perception within the Arabidopsis genus.

Ratiometric Fluorescence Probes for In Situ Imaging of Membrane Tension in Live Cells.

Membrane tension is an important physical parameter of describing cellular homeostasis, and it is widely used in the study of cellular processes involving membrane deformation and reorganization, such as cell migration, cell spreading, and cell division. Despite the importance of membrane tension, direct measurement remains difficult. In this work, we developed a ratiometric fluorescent probe sensitive to membrane tension by adjusting the carbon chain structure based on polarity-sensitive fluorophores. The probe is sensitive to changes in membrane tension after cells were subjected to physical or chemical stimuli, such as osmotic shock, lipid peroxidation, and mechanical stress. When the polarity of the plasma membrane increases (the green/red ratio decreases) and the membrane tension increases, the relative magnitude of the membrane tension can be quantitatively calculated by fluorescence ratio imaging. Thus, the probe proved to be an efficient and sensitive membrane tension probe.

Palladium-Catalyzed Annulative π-Extension of Bay-Iodinated Triphenylenes to Access Polycyclic Aromatic Compounds.

A palladium-catalyzed annulative π-extension reaction of bay-iodinated triphenylenes with aryl iodides/o-chloroaromatic carboxylic acids was developed. This approach enabled the synthesis of diverse polycyclic aromatic compounds, including dibenzo[fg,op]tetracenes, azadibenzo[fg,op]tetracenes, and tribenzo[a,g,m]coronenes. Initial studies indicate that the resulting product, 2,3,8,9,14,15-hexakis(decyloxy)tribenzo[a,g,m]coronene, exhibits good liquid-crystalline properties.

Advances in rapid point-of-care virus testing.

Outbreaks of viral diseases seriously jeopardize people's health and cause huge economic losses. At the same time, virology provides a new perspective for biology, molecular biology and cancer research, and it is important to study the discovered viruses with potential applications. Therefore, the development of immediate and rapid viral detection methods for the prevention and treatment of viral diseases as well as the study of viruses has attracted extensive attention from scientists. With the continuous progress of science and technology, especially in the field of bioanalysis, a series of new detection techniques have been applied to the on-site rapid detection of viruses, which has become a powerful approach for human beings to fight against viruses. In this paper, the latest research progress of rapid point-of-care detection of viral nucleic acids, antigens and antibodies is presented. In addition, the advantages and disadvantages of these technologies are discussed from the perspective of practical application requirements. Finally, the problems and challenges faced by rapid viral detection methods and their development prospects are discussed.

Cannabidiol Inhibits Epithelial Ovarian Cancer: Role of Gut Microbiome.

Epithelial ovarian cancer is among the deadliest gynecological tumors worldwide. Clinical treatment usually consists of surgery and adjuvant chemo- and radiotherapies. Due to the high rate of recurrence and rapid development of drug resistance, the current focus of research is on finding effective natural products with minimal toxic side effects for treating epithelial ovarian tumors. Cannabidiol is among the most abundant cannabinoids and has a non-psychoactive effect compared to tetrahydrocannabinol, which is a key advantage for clinical application. Studies have shown that cannabidiol has antiproliferative, pro-apoptotic, cytotoxic, antiangiogenic, anti-inflammatory, and immunomodulatory properties. However, its therapeutic value for epithelial ovarian tumors remains unclear. This study aims to investigate the effects of cannabidiol on epithelial ovarian tumors and to elucidate the underlying mechanisms. The results showed that cannabidiol has a significant inhibitory effect on epithelial ovarian tumors. In vivo experiments demonstrated that cannabidiol could inhibit tumor growth by modulating the intestinal microbiome and increasing the abundance of beneficial bacteria. Western blot assays showed that cannabidiol bound to EGFR/AKT/MMPs proteins and suppressed EGFR/AKT/MMPs expression in a dose-dependent manner. Network pharmacology and molecular docking results suggested that cannabidiol could affect the EGFR/AKT/MMPs signaling pathway.

Long-term Effect of Thyrotropin-binding Inhibitor Immunoglobulin on Atrial Fibrillation in Euthyroid Patients.

OBJECTIVE: Individuals with hyperthyroidism are at an increased risk of atrial fibrillation (AF), but the association between autoantibodies and AF or cardiovascular mortality in individuals who have returned to normal thyroid function remains unclear. METHODS: The study utilized electronic medical records from National Taiwan University Hospital between 2000 and 2022. Each hyperthyroidism patient had at least 1 thyrotropin-binding inhibiting immunoglobulin (TBII) measurement. The relationship between TBII levels and the risk of AF and cardiovascular mortality was assessed using multivariable Cox regression models and Kaplan-Meier survival analysis. RESULTS: Among the 14 618 enrolled patients over a 20-year timeframe, 173 individuals developed AF, while 46 experienced cardiovascular mortality. TBII values exceeding 35% were significantly associated with an elevated risk of AF for both the first TBII (hazard ratio {HR} 1.48 [1.05-2.08], P = .027) and mean TBII (HR 1.91 [1.37-2.65], P < .001). Furthermore, after free T4 levels had normalized, a borderline association between first TBII and AF (HR 1.59 [0.99-2.56], P = .056) was observed, while higher mean TBII increased AF (HR 1.78 [1.11-2.85], P = .017). Higher first and mean TBII burden continued to significantly impact the incidence of cardiovascular mortality (HR 6.73 [1.42-31.82], P = .016; 7.87 [1.66-37.20], P = .009). Kaplan-Meier analysis demonstrated that elevated TBII levels increased the risk of AF and cardiac mortality (log-rank P = .035 and .027, respectively). CONCLUSION: In euthyroid individuals following antithyroid treatment, elevated circulating TBII levels and burden are associated with an elevated risk of long-term incident AF and cardiovascular mortality. Further reduction of TBII level below 35% will benefit to clinical outcomes.

Bacterial rhamnolipids and their 3-hydroxyalkanoate precursors activate Arabidopsis innate immunity through two independent mechanisms.

Plant innate immunity is activated upon perception of invasion pattern molecules by plant cell-surface immune receptors. Several bacteria of the genera Pseudomonas and Burkholderia produce rhamnolipids (RLs) from l-rhamnose and (R)-3-hydroxyalkanoate precursors (HAAs). RL and HAA secretion is required to modulate bacterial surface motility, biofilm development, and thus successful colonization of hosts. Here, we show that the lipidic secretome from the opportunistic pathogen Pseudomonas aeruginosa, mainly comprising RLs and HAAs, stimulates Arabidopsis immunity. We demonstrate that HAAs are sensed by the bulb-type lectin receptor kinase LIPOOLIGOSACCHARIDE-SPECIFIC REDUCED ELICITATION/S-DOMAIN-1-29 (LORE/SD1-29), which also mediates medium-chain 3-hydroxy fatty acid (mc-3-OH-FA) perception, in the plant Arabidopsis thaliana HAA sensing induces canonical immune signaling and local resistance to plant pathogenic Pseudomonas infection. By contrast, RLs trigger an atypical immune response and resistance to Pseudomonas infection independent of LORE. Thus, the glycosyl moieties of RLs, although abolishing sensing by LORE, do not impair their ability to trigger plant defense. Moreover, our results show that the immune response triggered by RLs is affected by the sphingolipid composition of the plasma membrane. In conclusion, RLs and their precursors released by bacteria can both be perceived by plants but through distinct mechanisms.

Identifying changes in dynamic plantar pressure associated with radiological knee osteoarthritis based on machine learning and wearable devices.

BACKGROUND: Knee osteoarthritis (KOA) is an irreversible degenerative disease that characterized by pain and abnormal gait. Radiography is typically used to detect KOA but has limitations. This study aimed to identify changes in plantar pressure that are associated with radiological knee osteoarthritis (ROA) and to validate them using machine learning algorithms. METHODS: This study included 92 participants with variable degrees of KOA. A modified Kellgren-Lawrence scale was used to classify participants into non-ROA and ROA groups. The total feature set included 210 dynamic plantar pressure features captured by a wearable in-shoe system as well as age, gender, height, weight, and body mass index. Filter and wrapper methods identified the optimal features, which were used to train five types of machine learning classification models for further validation: k-nearest neighbors (KNN), support vector machine (SVM), random forest (RF), AdaBoost, and eXtreme gradient boosting (XGBoost). RESULTS: Age, the standard deviation (SD) of the peak plantar pressure under the left lateral heel (f_L8PPP_std), the SD of the right second peak pressure (f_Rpeak2_std), and the SD of the variation in the anteroposterior displacement of center of pressure (COP) in the right foot (f_RYcopstd_std) were most associated with ROA. The RF model with an accuracy of 82.61% and F1 score of 0.8000 had the best generalization ability. CONCLUSION: Changes in dynamic plantar pressure are promising mechanical biomarkers that distinguish between non-ROA and ROA. Combining a wearable in-shoe system with machine learning enables dynamic monitoring of KOA, which could help guide treatment plans.

The Use of E-Learning in Peyton's 4-Step Approach: Evaluation of Facial Computed Tomography Scans.

Imparting procedural skills is challenging. Peyton's approach is an effective face-to-face teaching technique increasingly used in complex skills training. Institutions are beginning to incorporate online training as part of their procedural curriculum. We developed E-Peyton's to employ Peyton's approach through an electronic learning platform. The efficacy of E-Peyton's approach in teaching the interpretation of facial computed tomography (CT) scans is evaluated in this study. Naïve learners (n=41) were randomized into 2 groups based on teaching techniques employed: E-Peyton's (n=20) and Peyton's (n=21) approaches. The distance between the infraorbital margin and the posterior ledge was measured using a 3-part standardized measuring protocol on OsiriX. Twenty measurements were assessed for accuracy against the benchmark (±2 mm) at week 0 and week 1. Training durations were compared. Questionnaires were administered before and after the study to identify learners' acceptance of teaching techniques and their confidence in interpreting facial CT scans. Learners in both teaching techniques had comparable skills retention. Gap scores indicate significant improvement in learner's confidence levels regardless of teaching technique (P<0.05). Both teaching techniques were well-accepted by learners. E-Peyton's and Peyton's approaches required a similar training duration. The COVID-19 pandemic highlights the importance of effective remote learning platforms. E-Peyton's approach is comparable to that of Peyton's in all areas of assessment. E-Peyton's approach effectively automates Peyton's approach, allowing for standardized, high-quality procedural skills training while reducing manpower burden.

Virus-mimicking nanosystems: from design to biomedical applications.

Nanomedicine, as an interdisciplinary discipline involving the development and application of nanoscale materials and technologies, is rapidly developing under the impetus of bionanotechnology and has attracted a great deal of attention from researchers. Especially, with the global outbreak of COVID-19, the in-depth investigation of the infection mechanism of the viruses has made the study of virus-mimicking nanosystems (VMNs) a popular research topic. In this review, we initiate with a brief historical perspective on the emergence and development of VMNs for providing a comprehensive view of the field. Next, we present emerging design principles and functionalization strategies for fabricating VMNs in light of viral infection mechanisms. Then, we describe recent advances in VMNs in biology, with a major emphasis on representative examples. Finally, we summarize the opportunities and challenges that exist in this field, hoping to provide new insights and inspiration to develop VMNs for disease diagnosis and treatment and to attract the interest of more researchers from different fields.