Recognition Domain Research Articles

Crop monitoring using remote sensing land use and land change data: Comparative analysis of deep learning methods using pre-trained CNN models

In the context of the rapidly evolving climate dynamics of the early twenty-first century, the interplay between climate change and biospheric integrity is becoming increasingly critical. The pervasive impact of climate change on ecosystems is manifested not only through alterations in average environmental conditions and their variability but also through ancillary shifts such as escalated oceanic acidification and heightened atmospheric CO2 levels. These climatic transformations are further compounded by concurrent ecological stressors, including habitat degradation, defaunation, and fragmentation. Against this backdrop, this study delves into the efficacy of advanced deep learning methodologies for the classification of land cover from satellite imagery, with a particular emphasis on agricultural crop monitoring. The study leverages state-of-the-art pre-trained Convolutional Neural Network (CNN) architectures, namely VGG16, MobileNetV2, DenseNet121, and ResNet50, selected for their architectural sophistication and proven competence in image recognition domains. The research framework encompasses a comprehensive data preparation phase incorporating augmentation techniques, a thorough exploratory data analysis to pinpoint and address class imbalances through the computation of class weights, and the strategic fine-tuning of CNN architectures with tailored classification layers to suit the specificities of land cover classification challenges. The models' performance was rigorously evaluated against benchmarks of accuracy and loss, both during the training phase and on validation datasets, with preventative strategies against overfitting, such as early stopping and adaptive learning rate modifications, being integral to the methodology. The findings illuminate the considerable potential of leveraging pre-trained deep learning models for remote sensing in agriculture, demonstrating that advanced CNN architectures, particularly DenseNet121 and ResNet50, are notably effective in enhancing crop type classification accuracy from satellite imagery. This study contributes valuable insights to the field of precision agriculture, advocating for the integration of sophisticated image recognition technologies to bolster crop monitoring efficacy, thereby enabling more nuanced agricultural decision-making and resource allocation.

Evolved Readers of 5‐Carboxylcytosine CpG Dyads Reveal a High Versatility of the Methyl‐CpG‐Binding Domain for Recognition of Noncanonical Epigenetic Marks

AbstractMammalian genomes are regulated by epigenetic cytosine (C) modifications in palindromic CpG dyads. Including canonical cytosine 5‐methylation (mC), a total of four different 5‐modifications can theoretically co‐exist in the two strands of a CpG, giving rise to a complex array of combinatorial marks with unique regulatory potentials. While tailored readers for individual marks could serve as versatile tools to study their functions, it has been unclear whether a natural protein scaffold would allow selective recognition of marks that vastly differ from canonical, symmetrically methylated CpGs. We conduct directed evolution experiments to generate readers of 5‐carboxylcytosine (caC) dyads based on the methyl‐CpG‐binding domain (MBD), the widely conserved natural reader of mC. Despite the stark steric and chemical differences to mC, we discover highly selective, low nanomolar binders of symmetric and asymmetric caC‐dyads. Together with mutational and modelling studies, our findings reveal a striking evolutionary flexibility of the MBD scaffold, allowing it to completely abandon its conserved mC recognition mode in favour of noncanonical dyad recognition, highlighting its potential for epigenetic reader design.

Evolved Readers of 5-Carboxylcytosine CpG Dyads Reveal a High Versatility of the Methyl-CpG-Binding Domain for Recognition of Noncanonical Epigenetic Marks.

Mammalian genomes are regulated by epigenetic cytosine (C) modifications in palindromic CpG dyads. Including canonical cytosine 5-methylation (mC), a total of four different 5-modifications can theoretically co-exist in the two strands of a CpG, giving rise to a complex array of combinatorial marks with unique regulatory potentials. While tailored readers for individual marks could serve as versatile tools to study their functions, it has been unclear whether a natural protein scaffold would allow selective recognition of marks that vastly differ from canonical, symmetrically methylated CpGs. We conduct directed evolution experiments to generate readers of 5-carboxylcytosine (caC) dyads based on the methyl-CpG-binding domain (MBD), the widely conserved natural reader of mC. Despite the stark steric and chemical differences to mC, we discover highly selective, low nanomolar binders of symmetric and asymmetric caC-dyads. Together with mutational and modelling studies, our findings reveal a striking evolutionary flexibility of the MBD scaffold, allowing it to completely abandon its conserved mC recognition mode in favour of noncanonical dyad recognition, highlighting its potential for epigenetic reader design.

Galectin-4 Antimicrobial Activity Primarily Occurs Through its C-Terminal Domain

Although immune tolerance evolved to reduce reactivity with self, it creates a gap in the adaptive immune response against microbes that decorate themselves in self-like antigens. This is particularly apparent with carbohydrate-based blood group antigens, wherein microbes can envelope themselves in blood group structures similar to human cells. In this study, we demonstrate that the innate immune lectin, galectin-4 (Gal-4), exhibits strain-specific binding and killing behavior towards microbes that display blood group–like antigens. Examination of binding preferences using a combination of microarrays populated with ABO(H) glycans and a variety of microbial strains, including those that express blood group–like antigens, demonstrated that Gal-4 binds mammalian and microbial antigens that have features of blood group and mammalian-like structures. Although Gal-4 was thought to exist as a monomer that achieves functional bivalency through its two linked carbohydrate recognition domains, our data demonstrate that Gal-4 forms dimers and that differences in the intrinsic ability of each domain to dimerize likely influences binding affinity. While each Gal-4 domain exhibited blood group–binding activity, the C-terminal domain (Gal-4C) exhibited dimeric properties, while the N-terminal domain (Gal-4N) failed to similarly display dimeric activity. Gal-4C not only exhibited the ability to dimerize but also possessed higher affinity toward ABO(H) blood group antigens and microbes expressing glycans with blood group–like features. Furthermore, when compared to Gal-4N, Gal-4C exhibited more potent antimicrobial activity. Even in the context of the full-length protein, where Gal-4N is functionally bivalent by virtue of Gal-4C dimerization, Gal-4C continued to display higher antimicrobial activity. These results demonstrate that Gal-4 exists as a dimer and exhibits its antimicrobial activity primarily through its C-terminal domain. In doing so, these data provide important insight into key features of Gal-4 responsible for its innate immune activity against molecular mimicry.

Design, synthesis, biological evaluation and docking study of some new aryl and heteroaryl thiomannosides as FimH antagonists

FimH is a mannose-recognizing lectin that is expressed by Escherichia coli guiding its ability to adhere and infect cells. It is involved in pathogenesis of urinary tract infections and Chron’s disease. Several X-ray structure-guided ligand design studies were extensively utilized in the discovery and optimization of small molecule aryl mannoside FimH antagonists. These antagonists retain key specific interactions of the mannose scaffolds with the FimH carbohydrate recognition domains. Thiomannosides are attractive and stable scaffolds, and this work reports the synthesis of some of their new aryl and heteroaryl derivatives as FimH antagonists. FimH-competitive binding assays as well as biofilm inhibition of the new compounds (24–32) were determined in comparison with the reference n-heptyl α-d-mannopyranoside (HM). The affinity among these compounds was found to be governed by the structure of the aryl and heteroarylf aglycones. Two compounds 31 and 32 revealed higher activity than HM. Molecular docking and total hydrophobic to topological polar surface area ratio calculations attributed to explain the obtained biological results. Finally, the SAR study suggested that introducing an aryl or heteroaryl aglycone of sufficient hydrophobicity and of proper orientation within the tyrosine binding site considerably enhance binding affinity. The potent and synthetically feasible FimH antagonists described herein hold potential as leads for the development of sensors for detection of E. coli and treatment of its diseases.

Biophysical and Structural Characterization of the Interaction between Human Galectin-3 and the Lipopolysaccharide from Pseudomonas aeruginosa.

Given the significant involvement of galectins in the development of numerous diseases, the aim of the following work is to further study the interaction between galectin-3 (Gal3) and the LPS from Pseudomonas aeruginosa. This manuscript focused on the study of the interaction of the carbohydrate recognition domain of Gal3 with the LPS from Pseudomonas aeruginosa by means of different complementary methodologies, such as circular dichroism; spectrofluorimetry; dynamic and static light scattering and evaluation of the impact of Gal3 on the redox potential membranes of Escherichia coli and P. aeruginosa cells, as well as ITC and NMR studies. This thorough investigation reinforces the hypothesis of an interaction between Gal3 and LPS, unraveling the structural details and providing valuable insights into the formation of these intricate molecular complexes. Taken together, these achievements could potentially prompt the design of therapeutic drugs useful for the development of agonists and/or antagonists for LPS receptors such as galectins as adjunctive therapy for P. aeruginosa.

MgMViT: Multi-Granularity and Multi-Scale Vision Transformer for Efficient Action Recognition

Nowadays, the field of video-based action recognition is rapidly developing. Although Vision Transformers (ViT) have made great progress in static image processing, they are not yet fully optimized for dynamic video applications. Convolutional Neural Networks (CNN) and related models perform exceptionally well in video action recognition. However, there are still some issues that cannot be ignored, such as high computational costs and large memory consumption. In the face of these issues, current research focuses on finding effective methods to improve model performance and overcome current limits. Therefore, we present a unique Vision Transformer model based on multi-granularity and multi-scale fusion to accomplish efficient action recognition, which is designed for action recognition in videos to effectively reduce computational costs and memory usage. Firstly, we devise a multi-scale, multi-granularity module that integrates with Transformer blocks. Secondly, a hierarchical structure is utilized to manage information at various scales, and we introduce multi-granularity on top of multi-scale, which allows for a selective choice of the number of tokens to enter the next computational step, thereby reducing redundant tokens. Thirdly, a coarse-fine granularity fusion layer is introduced to reduce the sequence length of tokens with lower information content. The above two mechanisms are combined to optimize the allocation of resources in the model, further emphasizing critical information and reducing redundancy, thereby minimizing computational costs. To assess our proposed approach, comprehensive experiments are conducted by using benchmark datasets in the action recognition domain. The experimental results demonstrate that our method has achieved state-of-the-art performance in terms of accuracy and efficiency.

SPOP point mutations regulate substrate preference and affect its function

The adaptor SPOP recruits substrates to CUL3 E3 ligase for ubiquitination and degradation. Structurally, SPOP harbors a MATH domain for substrate recognition, and a BTB domain responsible for binding CUL3. Reported point mutations always occur in SPOP’s MATH domain and are through to disrupt affinities of SPOP to substrates, thereby leading to tumorigenesis. In this study, we identify the tumor suppressor IRF2BP2 as a novel substrate of SPOP. SPOP enables to attenuate IRF2BP2-inhibited cell proliferation and metastasis in HCC cells. However, overexpression of wild-type SPOP alone suppresses HCC cell proliferation and metastasis. In addition, a HCC-derived mutant, SPOP-M35L, shows an increased affinity to IRF2BP2 in comparison with wild-type SPOP. SPOP-M35L promotes HCC cell proliferation and metastasis, suggesting that M35L mutation possibly reprograms SPOP from a tumor suppressor to an oncoprotein. Taken together, this study uncovers mutations in SPOP’s MATH lead to distinct functional consequences in context-dependent manners, rather than simply disrupting its interactions with substrates, raising a noteworthy concern that we should be prudent to select SPOP as therapeutic target for cancers.

Crystal structure of the complex of CLEC12A and an antibody that interferes with binding of diverse ligands.

C-type lectin receptors (CLRs) are a family of pattern recognition receptors, which detect a broad spectrum of ligands via small carbohydrate-recognition domains (CRDs). CLEC12A is an inhibitory CLR that recognizes crystalline structures such as monosodium urate crystals. CLEC12A also recognizes mycolic acid, a major component of mycobacterial cell walls, and suppresses host immune responses. Although CLEC12A could be a therapeutic target for mycobacterial infection, structural information on CLEC12A was not available. We report here the crystal structures of human CLEC12A (hCLEC12A) in ligand-free form and in complex with 50C1, its inhibitory antibody. 50C1 recognizes human-specific residues on the top face of hCLEC12A CRD. A comprehensive alanine scan demonstrated that the ligand-binding sites of mycolic acid and monosodium urate crystals may overlap with each other, suggesting that CLEC12A utilizes a common interface to recognize different types of ligands. Our results provide atomic insights into the blocking and ligand-recognition mechanisms of CLEC12A and leads to the design of CLR-specific inhibitors.

Multivalent, calcium-independent binding of surfactant protein A and D to sulfated glycosaminoglycans of the alveolar epithelial glycocalyx.

Lung surfactant collectins, surfactant protein A (SP-A) and D (SP-D), are oligomeric C-type lectins involved in lung immunity. Through their carbohydrate recognition domain, they recognize carbohydrates at pathogen surfaces and initiate lung innate immune response. Here, we propose that they may also be able to bind to other carbohydrates present in typical cell surfaces, such as the alveolar epithelial glycocalyx. To test this hypothesis, we analyzed and quantified the binding affinity of SP-A and SP-D to different sugars and glycosaminoglycans (GAGs) by microscale thermophoresis (MST). In addition, by changing the calcium concentration, we aimed to characterize any consequences on the binding behavior. Our results show that both oligomeric proteins bind with high affinity (in nanomolar range) to GAGs, such as hyaluronan (HA), heparan sulfate (HS) and chondroitin sulfate (CS). Binding to HS and CS was calcium-independent, as it was not affected by changing calcium concentration in the buffer. Quantification of GAGs in bronchoalveolar lavage (BAL) fluid from animals deficient in either SP-A or SP-D showed changes in GAG composition, and electron micrographs showed differences in alveolar glycocalyx ultrastructure in vivo. Taken together, SP-A and SP-D bind to model sulfated glycosaminoglycans of the alveolar epithelial glycocalyx in a multivalent and calcium-independent way. These findings provide a potential mechanism for SP-A and SP-D as an integral part of the alveolar epithelial glycocalyx binding and interconnecting free GAGs, proteoglycans, and other glycans in glycoproteins, which may influence glycocalyx composition and structure.NEW & NOTEWORTHY SP-A and SP-D function has been related to innate immunity of the lung based on their binding to sugar residues at pathogen surfaces. However, their function in the healthy alveolus was considered as limited to interaction with surfactant lipids. Here, we demonstrated that these proteins bind to glycosaminoglycans present at typical cell surfaces like the alveolar epithelial glycocalyx. We propose a model where these proteins play an important role in interconnecting alveolar epithelial glycocalyx components.

Variation in the affinity of three representative avian adenoviruses for the cellular coxsackievirus and adenovirus receptor.

According to previous studies, three representative avian adenoviral strains utilize coxsackievirus-adenovirus receptor (CAR) as a receptor and seem to exhibit diverse binding affinities and modes. Thus, further revealing the exact molecular mechanism underlying the interaction between different FAdVs and the attachment receptor CAR is necessary. In this study, we successfully solved the crystal structure of the FAdV-4 fiber1 knob at 1.6 Å resolution. The interaction between the fibre knob and different domains of CAR was verified by confocal microscopy, coimmunoprecipitation and surface plasmon resonance (SPR) analysis. The fibre knobs of the three representative fowl adenoviruses specifically recognized CAR domain 1 (D1), but the recognition of CAR domain 2 (D2) by chicken embryo lethal orphan (CELO) strains was weak. These results provide insights into the differences in adenovirus‒host cell interactions and have important implications for the exploration of viral invasion mechanisms.

Multiple roles for the cytoplasmic C-terminal domains of the yeast cell surface receptors Rgt2 and Snf3 in glucose sensing and signaling

The plasma membrane proteins Rgt2 and Snf3 are glucose sensing receptors (GSRs) that generate an intracellular signal for the induction of gene expression in response to high and low extracellular glucose concentrations, respectively. The GSRs consist of a 12-transmembrane glucose recognition domain and a cytoplasmic C-terminal signaling tail. The GSR tails are dissimilar in length and sequence, but their distinct roles in glucose signal transduction are poorly understood. Here, we show that swapping the tails between Rgt2 and Snf3 does not alter the signaling activity of the GSRs, so long as their tails are phosphorylated in a Yck-dependent manner. Attachment of the GSR tails to Hxt1 converts the transporter into a glucose receptor; however, the tails attached to Hxt1 are not phosphorylated by the Ycks, resulting in only partial signaling. Moreover, in response to non-fermentable carbon substrates, Rgt2 and Hxt1-RT (RT, Rgt2-tail) are efficiently endocytosed, whereas Snf3 and Hxt1-ST (ST, Snf3-tail) are endocytosis-impaired. Thus, the tails are important regulatory domains required for the endocytosis of the Rgt2 and Snf3 glucose sensing receptors triggered by different cellular stimuli. Taken together, these results suggest multiple roles for the tail domains in GSR-mediated glucose sensing and signaling.

A trivalent aptasensor by using DNA tetrahedron as scaffold for label-free determination of antibiotics

Owing to advantage in high sensitivity and fast response, aptamer based electrochemical biosensors have attracted much more attention. However, inappropriate interfacial engineering strategy leads to poor recognition performance, which ascribe to the following factors of immobilized oligonucleotide strand including steric hindrance, interchain entanglement, and unfavorable conformation. In this work, we proposed a DNA tetrahedron based diblock aptamer immobilized strategy for the construction of label-free electrochemical biosensor. The diblock aptamer sequence is composite of T-rich anchor domain and recognition domain, where T-rich domain enabling anchored on the edge of DNA tetrahedron via Hoogsteen hydrogen bond at neutral condition. The DNA tetrahedron scaffold offers an appropriate lateral space for target recognition of diblock aptamer. More importantly, this trivalent aptamer recognition interface can be regenerated by simply adjusting the pH environment to alkaline, resulting in the dissociation of diblock aptamer. Under the optimum condition, proposed electrochemical aptasensor manifested a satisfied sensitivity for aminoglycosides antibiotic, kanamycin with a limit of detection of 0.69 nM, which is 45-fold lower than traditional Au–S immobilization strategy. Moreover, the proposed aptasensor had also successfully been extended to ampicillin detection by changing the sequence of recognition domain in diblock aptamer. This work paves a new way for the rational design of aptamer-based electrochemical sensor.

ATBBC: Named entity recognition in emergency domains based on joint BERT-BILSTM-CRF adversarial training

With the rapid growth of Internet penetration, identifying emergency information from network news has become increasingly significant for emergency monitoring and early warning. Although deep learning models have been commonly used in Chinese Named Entity Recognition (NER), they require a significant amount of well-labeled training data, which is difficult to obtain for emergencies. In this paper, we propose an NER model that combines bidirectional encoder representations from Transformers (BERT), bidirectional long-short-term memory (BILSTM), and conditional random field (CRF) based on adversarial training (ATBBC) to address this issue. Firstly, we constructed an emergency dataset (ED) based on the classification and coding specifications of the national emergency platform system. Secondly, we utilized the BERT pre-training model with adversarial training to extract text features. Finally, BILSTM and CRF were used to predict the probability distribution of entity labels and decode the probability distribution into corresponding entity labels.Experiments on the ED show that our model achieves an F1-score of 85.39% on the test dataset, which proves the effectiveness of our model.

The synthetic NLR RGA5HMA5 requires multiple interfaces within and outside the integrated domain for effector recognition

Some plant sensor nucleotide-binding leucine-rich repeat (NLR) receptors detect pathogen effectors through their integrated domains (IDs). Rice RGA5 sensor NLR recognizes its corresponding effectors AVR-Pia and AVR1-CO39 from the blast fungus Magnaporthe oryzae through direct binding to its heavy metal-associated (HMA) ID to trigger the RGA4 helper NLR-dependent resistance in rice. Here, we report a mutant of RGA5 named RGA5HMA5 that confers complete resistance in transgenic rice plants to the M. oryzae strains expressing the noncorresponding effector AVR-PikD. RGA5HMA5 carries three engineered interfaces, two of which lie in the HMA ID and the other in the C-terminal Lys-rich stretch tailing the ID. However, RGA5 variants having one or two of the three interfaces, including replacing all the Lys residues with Glu residues in the Lys-rich stretch, failed to activate RGA4-dependent cell death of rice protoplasts. Altogether, this work demonstrates that sensor NLRs require a concerted action of multiple surfaces within and outside the IDs to both recognize effectors and activate helper NLR-mediated resistance, and has implications in structure-guided designing of sensor NLRs.

Action recognition in compressed domains: A survey

Human action recognition (HAR) refers to the process in which computers analyze and process video data to obtain the categories of action presented in the video. It has a wide range of applications, such as video surveillance, human–computer interaction, and autonomous driving. The spatio-temporal features required for video analysis are typically extracted from the RGB pixels, which entail significant computational complexity and make it challenging for real-time action recognition. However, in the compressed domain, sparse representations, such as motion vectors, quantization parameters, transform coefficients, and residuals provide the comparable scene semantic information with reduced complexity. This paper provides an overview of the research efforts in action recognition based on the compressed domain. It includes a comprehensive review of both traditional and deep learning-based methods published between 2000 and 2023, focusing on compression standards and compression parameters. Specifically, we first summarize the compression standards and compressed algorithms used for compressing videos. Furthermore, we classify compressed-domain action recognition methods into traditional and deep learning-based approaches. Thirdly, we introduce public datasets and evaluation metrics, analyze the characteristics of these methods and compare their performance. Finally, we highlight challenges and suggest future research directions.

Galectin-3 – A novel ligand of complement protein C1q

In the present study we report a novel interaction of human C1q, a primary activator of the Complement system, with human Galectin-3 (Gal-3). We investigated the potential recognition between C1q and Gal-3 on a solid hydrophobic surface by ELISA, by fluorescence spectroscopy, molecular docking and molecular dynamics (MD). The data showed that C1q and Gal-3 had a pronounced affinity for protein-protein interaction and supramolecular binding, locating the binding sites within the globular domains of C1q (gC1q) and on the backside of the carbohydrate recognition domain (CRD) of Gal-3. Fluorescence spectroscopy gave quantitative assessment of the recognition with KD value of 0.04 μM. MD analysis showed that when the active AAs of the two proteins interacted, electrostatic attraction, aided by a large number of hydrogen bonds, was dominant for the stabilization of the complex. When the contact of C1q and Gal-3 was not limited to active residues, the complex between them was stabilized mainly by Van der Waals interactions and smaller in number but stronger hydrogen bonds. This is the first report analyzing the interaction of Gal-3 with C1q, which could open the way to new applications of this protein-protein complex.

Peptide-scFv antigen recognition domains effectively confer CAR T cell multiantigen specificity

The emergence of immune escape is a significant roadblock to developing effective chimeric antigen receptor (CAR) Tcell therapies against hematological malignancies, including acute myeloid leukemia (AML). Here, we demonstrate feasibility of targeting two antigens simultaneously by combining a GRP78-specific peptide antigen recognition domain with a CD123-specific scFv to generate a peptide-scFv bispecific antigen recognition domain (78.123). To achieve this, we test linkers with varying length and flexibility and perform immunophenotypic and functional characterization. We demonstrate that bispecific CAR Tcells successfully recognize and kill tumor cells that express GRP78, CD123, or both antigens and have improved antitumor activity compared to their monospecific counterparts when both antigens are expressed. Protein structure prediction suggests that linker length and compactness influence the functionality of the generated bispecific CARs. Thus, we present a bispecific CAR design strategy to prevent immune escape in AML that can be extended to other peptide-scFv combinations.

Negative symptoms and social cognition as mediators of the relationship between neurocognition and functional outcome in schizophrenia.

In this study we assessed the contribution of psychopathology, including the two domains of negative symptoms (motivational deficit and expressive deficit), processing speed as an index of neurocognition, and emotion recognition, as an index of social cognition, to poor functional outcomes in people with schizophrenia. The Positive and Negative Syndrome Scale was used to evaluate positive symptoms and disorganization and the Brief Negative Symptom Scale to assess negative symptoms. The Symbol Coding and the Trail Making Test A and B were used to rate processing speed and the Facial Emotion Identification Test to assess emotion recognition. Functional outcome was assessed with the Personal and Social Performance Scale (PSP). Regression analyses were performed to identify predictors of functional outcome. Mediation analyses was used to investigate whether social cognition and negative symptom domains fully or partially mediated the impact of processing speed on functional outcome. One hundred and fifty subjects from 8 different European centers were recruited. Our data showed that the expressive deficit predicted global functioning and together with motivational deficit fully mediated the effects of neurocognition on it. Motivational deficit was a predictor of personal and social functioning and fully mediated neurocognitive impairment effects on the same outcome. Both motivational deficit and neurocognitive impairment predicted socially useful activities, and the emotion recognition domain of social cognition partially mediated the impact of neurocognitive deficits on this outcome. Our results indicate that pathways to functional outcomes are specific for different domains of real-life functioning and that negative symptoms and social cognition mediate the impact of neurocognitive deficits on different domains of functioning. Our results suggest that both negative symptoms and social cognition should be targeted by psychosocial interventions to enhance the functional impact of neurocognitive remediation.

Mannose Ligands for Mannose Receptor Targeting.

The mannose receptor (MR, CD 206) is an endocytic receptor primarily expressed by macrophages and dendritic cells, which plays a critical role in both endocytosis and antigen processing and presentation. MR carbohydrate recognition domains (CRDs) exhibit a high binding affinity for branched and linear oligosaccharides. Furthermore, multivalent mannose presentation on the various templates like peptides, proteins, polymers, micelles, and dendrimers was proven to be a valuable approach for the selective and efficient delivery of various therapeutically active agents to MR. This review provides a detailed account of the most relevant and recent aspects of the synthesis and application of mannosylated bioactive formulations for MR-mediated delivery in treatments of cancer and other infectious diseases. It further highlights recent findings related to the necessary structural features of the mannose-containing ligands for successful binding to the MR.