Labeling Technique Research Articles

Novel polymycoviruses are encapsidated in filamentous virions.

Polymycoviridae is a relatively new viral family that was established nearly 5 years ago, but their viral morphologies (naked or encapsidated) remain controversial since only one member namely, Colletotrichum camelliae filamentous virus 1 (CcFV1), was identified as being encapsidated in filamentous virions. Here, three novel double-stranded RNA (dsRNA) viruses belonging to the family Polymycoviridae were identified in three phytopathogenic fungal strains and tentatively named Pseudopestalotiopsis camelliae-sinensis polymycovirus 1 (PcsPmV1), and Phyllosticta capitalensis polymycovirus 1 and 2 (PhcPmV1 and 2), respectively. PcsPmV1 and PhcPmVs have five or six genomic dsRNAs, ranging from 1,055 to 2,405 bp, encoding five or seven putative open reading frames (ORFs), of which ORF1 encodes an RNA-dependent RNA polymerase, ORF5 encodes a prolein-alanine-serine-rich (P-A-S-rich) protein behaving as coat protein (CP); and dsRNAs 4 and 6 encode putative proteins with unknown functions and share no detectable identities with known viral sequences. Upon examination under transmission electron microscopy after purification from fungal mycelia, PcsPmV1 and PhcPmVs were found to be encapsidated in filamentous particles, as was a known polymycovirus, Botryosphaeria dothidea RNA virus 1 (BdRV1), which was previously assumed to likely have no conventional virions. The morphology of PcsPmV1 was further supported by the observation that its particles could be decorated by polyclonal antibodies against its CP and bound by immuno-gold particles conjugated to the specific CP antibody. Together with CcFV1, BdRV1, PcsPmV1, and PhcPmVs, these provide strong evidence to support the notion that polymycoviruses are encapsidated in filamentous virions constituted by P-A-S-rich CPs. Moreover, their biological effects on their fungal hosts were assessed, suggesting that PcsPmV1 infection could enhance growth and virulence.IMPORTANCEPolymycoviridae, a recently established viral family, has raised questions about encapsidation. Here, we identify and characterize three novel polymycoviral double-stranded RNA (dsRNA) viruses in phytopathogenic fungal strains, tentatively named Pseudopestalotiopsis camelliae-sinensis polymycovirus 1, and Phyllosticta capitalensis polymycovirus 1 and 2, respectively. These polymycoviruses possess five or six genomic dsRNAs, ranging from 1,055 to 2,405 bp, with two encoding putative proteins of unknown functions and sharing no detectable identities with known viral sequences. Their morphologies indicate filamentous virions constituted by proline-alanine-serine-rich coat proteins, observed using immunosorbent electron microscopy combined with immune-gold labeling techniques. Additionally, Botryosphaeria dothidea RNA virus 1, previously assumed to lack conventional virions, is also shown to be encapsidated in filamentous particles. This study provides new evidence supporting the encapsidation of polymycoviruses into elongated and flexuous virions, significantly contributing to our understanding of the evolutionary particle architecture within the virosphere and expanding our knowledge of viral diversity and evolution. Moreover, this is the first report of a polymycovirus enhancing the virulence and growth of a phytopathogenic fungus.

Nucleic Acid Covalent Tags.

The selective and site-specific chemical labeling of proteins has emerged as a pivotal research area in chemical biology and cell biology. An effective protein labeling typically meets several criteria, including high specificity, rapid and robust conjugation under physiological conditions, operation at low concentrations with biocompatibility, and minimal perturbation of the protein function and activity. The conjugation of nucleic acids with proteins has garnered significant attention recently due to the rapid advancements in nucleic acid probe technologies, leveraging the programmable nature of nucleic acids alongside the multifaceted functionalities of proteins. It helps to convert protein-specific information into nucleic acid signals, facilitating upstream versatile recognition and downstream signal amplification for the target protein. This review critically evaluates the recent progress in nucleic acid-based protein labeling methodologies, with a specific focus on covalent labeling using aptamer tags, protein fusion tags or the technique of metabolic oligosaccharide engineering. The tags establish covalent linkages with target proteins through various modalities such as small molecules or metabolic glycan engineering. The insights presented in the review highlight promising avenues for the development of highly specific and versatile protein labeling techniques, which is essential for the improvement of protein-targeted detection and imaging across diverse biological contexts.

Target Bioconjugation of Protein Through Chemical, Molecular Dynamics, and Artificial Intelligence Approaches

Covalent modification of proteins at specific, predetermined sites is essential for advancing biological and biopharmaceutical applications. Site-selective labeling techniques for protein modification allow us to effectively track biological function, intracellular dynamics, and localization. Despite numerous reports on modifying target proteins with functional chemical probes, unique organic reactions that achieve site-selective integration without compromising native functional properties remain a significant challenge. In this review, we delve into site-selective protein modification using synthetic probes, highlighting both chemical and computational methodologies for chemo- and regioselective modifications of naturally occurring amino acids, as well as proximity-driven protein-selective chemical modifications. We also underline recent traceless affinity labeling strategies that involve exchange/cleavage reactions and catalyst tethering modifications. The rapid development of computational infrastructure and methods has made the bioconjugation of proteins more accessible, enabling precise predictions of structural changes due to protein modifications. Hence, we discuss bioconjugational computational approaches, including molecular dynamics and artificial intelligence, underscoring their potential applications in enhancing our understanding of cellular biology and addressing current challenges in the field.

LRR1 involved in the abscisic acid signaling pathway to regulate the early growth and development of Arabidopsis thaliana.

Living organisms possess the remarkable capacity to swiftly adapt to fluctuations in their environment. In the context of cell signal transduction, a significant challenge lies in ensuring the effective perception of external signals and the execution of appropriate responses. To investigate this phenomenon, a recent study utilized Arabidopsis thaliana as a model plant and induced stress by administering abscisic acid (ABA), a plant hormone, to elucidate the involvement of leucine-rich repeat receptor-like kinase1 (LRR1) in ABA signaling pathways. Homozygous T-DNA insertion alleles for LRR1 and KIN7 were isolated. Quantitative real-time PCR (qRT-PCR) was performed to confirm the expression of the LRR1 gene. Subcellular localization and beta-glucuronidase (GUS) tissue labeling techniques were utilized to determine the expression pattern of the LRR1 gene in cells and tissues. Yeast two-hybrid complementation, bimolecular fluorescence complementation assay, and GST pull-down assays were conducted to validate the interaction of LRR1 proteins. Phenotypic analyses revealed that lrr1 and kin7 mutants are less sensitive to the inhibitory effects of ABA on germination and cotyledon greening that is seen in WT. Mutants LRR1 and kinase 7 (KIN7) exhibited resistance to ABA and displayed normal growth patterns under control conditions. The double mutant lrr1kin7 showed reduced responsiveness to ABA. Conversely, overexpression lines LRR1ox2 and LRR1ox10 demonstrated heightened sensitivity to ABA, resulting in severe growth reduction. qRT-PCR assay indicated that exogenous application of ABA led to significant down-regulation of ABI3, ABI4, and ABI5 transcription factors in LRR1 material compared to wild-type WT material. An investigation was conducted to determine the expression pattern and transcriptional level of LRR1 in Arabidopsis. The results revealed ubiquitous expression of LRR1 across all developmental stages and tissue tested. Subcellular localization assays confirmed the presence of LRR1 on the plasma membrane of cells. Furthermore, BiFC assay, yeast two-hybrid complementation, and GST pull-down assays demonstrated an interaction between LRR1 and PYL6 in vitro. These findings provide substantial insights into the involvement of LRR1 in the ABA signaling pathway while regulating seed germination and cotyledon greening during early development in Arabidopsis. This study significantly advances our understanding regarding the correlation between LRR1 and ABA signaling pathways with potential applications for enhancing crop stress resistance.

Recent Advances in Labeling-Based Quantitative Glycomics: From High-Throughput Quantification to Structural Elucidation.

Glycosylation, a crucial posttranslational modification (PTM), plays important roles in numerous biological processes and is linked to various diseases. Despite its significance, the structural complexity and diversity of glycans present significant challenges for mass spectrometry (MS)-based quantitative analysis. This review aims to provide an in-depth overview of recent advancements in labeling strategies for N-glycomics and O-glycomics, with a specific focus on enhancing the sensitivity, specificity, and throughput of MS analyses. We categorize these advancements into three major areas: (1) the development of isotopic/isobaric labeling techniques that significantly improve multiplexing capacity and throughput for glycan quantification; (2) novel methods that aid in the structural elucidation of complex glycans, particularly sialylated and fucosylated glycans; and (3) labeling techniques that enhance detection ionization efficiency, separation, and sensitivity for matrix-assisted laser desorption/ionization (MALDI)-MS and capillary electrophoresis (CE)-based glycan analysis. In addition, we highlight emerging trends in single-cell glycomics and bioinformatics tools that have the potential to revolutionize glycan quantification. These developments not only expand our understanding of glycan structures and functions but also open new avenues for biomarker discovery and therapeutic applications. Through detailed discussions of methodological advancements, this review underscores the critical role of derivatization methods in advancing glycan identification and quantification.

Rumus Umum Pelabelan L(2, 1) pada Graf Koprima Grup Bilangan Bulat Modulo m

Groups are nonempty sets equipped with binary operations and fulfill certain conditions. One example of a group is the group of integers modulo . A coprime graph of a group is a graph whose vertices are elements in and any two vertices in are directly connected if and only if the greatest common factor of the orders x and y are relatively prime. labeling has important applications in wireless telecommunication networks, where there are limited radio frequencies available and adjacent transmitters cannot use the same frequency. To overcome this problem, frequency assignment is done using the concept of labeling, where transmitters are symbolized as vertices connected by edges. labeling is a graph labeling technique that assigns non-negative integer labels to graph vertices with the rule that two directly connected vertices must have a minimum label difference of two, and two vertices that are two apart must have a minimum label difference of one. The purpose of this research is to find out the general formula for the labeling on the coprime graph of the group of integers modulo and the general formula for the minimum value of the largest label of the labeling. The steps taken in this research are to determine the coprime graph form of the group of integers modulo . Then label each vertex with a non-negative label. Then label each vertex with labeling rule. From the result of this research, it can be concluded that the coprime graph of integer group modulo has a labeling with .

AI-Assisted Application for Pediatric Drug Dosing.

Technology in the medical field is continuously advancing due to its numerous subdomains and the ever-growing medical needs of people. Information systems have become integral to doctors' daily routines in patient care, offering flexibility and support in repetitive tasks, thereby allowing more time for critical activities. This paper presents the implementation of a machine learning algorithm, leveraging natural language processing (NLP) and labeling techniques, to analyze medical leaflets from Romania. The aim is to assist pediatricians in determining appropriate treatment doses for children based on various parameters such as age, weight, and other significant factors.

Machine learning enabled fast optical identification and characterization of 2D materials

Two-dimensional materials are a class of atomically thin materials with assorted electronic and quantum properties. Accurate identification of layer thickness, especially for a single monolayer, is crucial for their characterization. This characterization process, however, is often time-consuming, requiring highly skilled researchers and expensive equipment like atomic force microscopy. This project aims to streamline the identification process by using machine learning to analyze optical images and quickly determine layer thickness. In this paper, we evaluate the performance of three machine learning models - SegNet, 1D U-Net, and 2D U-Net- in accurately identifying monolayers in microscopic images. Additionally, we explore labeling and image processing techniques to determine the most effective and accessible method for identifying layer thickness in this class of materials.

Abstract B032: Genome-wide 5-hydroxymethylation mapping in cell-free DNA to characterize the epigenetic differences in minimal residual disease of multiple myeloma

Abstract Background: Multiple myeloma (MM), a B-cell neoplasm characterized by the infiltration of malignant plasma cells into the bone marrow, is the second most common blood malignancy in the United States. The molecular pathogenesis of MM involves both genetic and epigenetic alterations. While 60-75% of newly diagnosed patients achieve a complete response or better with current modern combination therapies, almost all patients eventually progress largely due to the persistence or re-emergence of minimal residual disease (MRD). Monitoring for MRD has become essential for evaluating treatment efficacy and predicting long-term outcomes in MM patients. We aimed to investigate whether epigenetic changes, particularly 5- hydroxymethylcytosines (5hmC), at diagnosis are associated with MRD status following treatment. Methods: Utilizing 5hmC-Seal, a highly sensitive chemical labeling technique, we profiled genome-wide 5hmC in circulating cell-free DNA (cfDNA) and bone marrow genomic DNA (gDNA) at baseline and after 8 cycles of treatment (C8) from newly diagnosed MM patients (n=25) enrolled in a clinical trial (NCT01816971). MRD testing was performed on bone marrow samples using the clonoSEQ next generation sequencing assay (limit of detection 10-6). Results: The 5hmC modification levels were summarized across various genomic features, revealing enrichment in gene bodies and enhancer regions, consistent with the known regulatory role of 5hmC. We ranked 5hmC-modified genes at baseline by their variability, and found that the number of overlapping genes between cfDNA and gDNA was significantly higher than expected by permutation analysis. Subsequently, we identified the top 100 most variable 5hmC- modified genes in gDNA, which exhibited a higher Pearson correlation with cfDNA within individuals (mean r=0.90) compared to between individuals (mean r=0.82; p<0.05), suggesting that cfDNA has the potential to reflect gDNA in capturing some MM-related variations. Among the 11 patients with MRD+ at C8, a genome-wide scan of 5hmC in cfDNA comparing baseline and C8 identified 1,614 differentially modified genes (p<0.05) after adjusting for age and sex. [BC1] Furthermore, we identified 459 differentially modified genes comparing baseline 5hmC levels between patients who were MRD+ (n=11) and MRD- (n= 14) at C8 (p<0.05), after adjusting for age and sex. These results highlight the differential epigenetic landscape associated with MRD status. Conclusions: Genome-wide 5hmC profiling of cfDNA from blood revealed a similar epigenetic landscape to gDNA from bone marrow in patients with MM, suggesting that cfDNA may offer a less invasive alternative for assessing epigenetic modifications. Moreover, this profiling identified distinct epigenetic changes associated with the achievement of MRD- negativity. These findings provide a foundation for further investigation into the molecular alterations linked to MM disease biology that could potentially lead to MRD negativity. Future directions will focus on identifying biomarkers that could inform personalized treatment strategies. Citation Format: Zhou Zhang, Bei Wang, Krissana Kowitwanich, John Cursio, Daniel Appelbaum, Chuan He, Wei Zhang, Benjamin Derman, Brian Chiu, Andrzej Jakubowiak. Genome-wide 5-hydroxymethylation mapping in cell-free DNA to characterize the epigenetic differences in minimal residual disease of multiple myeloma [abstract]. In: Proceedings of the AACR Special Conference: Liquid Biopsy: From Discovery to Clinical Implementation; 2024 Nov 13-16; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(21_Suppl):Abstract nr B032.

Insights into the Structure and Dynamics of Proteins from 19F Solution NMR Spectroscopy.

19F NMR spectroscopy has recently witnessed a resurgence as an attractive analytical tool for the study of the structure and dynamics of biomolecules in vitro and in cells, despite reports of its applications in biomolecular NMR since the 1970s. The high gyromagnetic ratio, large chemical shift dispersion, and complete absence of the spin 1/2 19F nucleus from biomolecules results in background-free, high-resolution 19F NMR spectra. The introduction of 19F probes in a few selected locations in biomolecules reduces spectral crowding despite its increased line width in comparison to typical 1H NMR line widths and allows rapid site-specific measurements from simple 1D spectra alone. The design and synthesis of novel 19F probes with reduced line widths and increased chemical shift sensitivity to the surrounding environment, together with advances in labeling techniques, NMR methodology, and hardware, have overcome several drawbacks of 19F NMR spectroscopy. The increased interest and widespread use of 19F NMR spectroscopy of biomolecules is gradually establishing it as a sensitive and high-resolution probe of biomolecular structure and dynamics, supplementing traditional 13C/15N-based methods. This Review focuses on the advances in 19F solution NMR spectroscopy of proteins in the past 5 years, with an emphasis on novel 19F tags and labeling techniques, NMR experiments to probe protein structure and conformational dynamics in vitro, and in-cell NMR applications.

Immunoproteomics: Approach to Diagnostic and Vaccine Development.

The study of large protein sets (proteomics) involved in the immunological reaction is known as immunoproteomics. The methodology of immunoproteomics plays a major role in identifying possible vaccine candidates that could protect against pathogenic infection. The study of immunogenic proteins that are expressed during the outset of infection is the focus of the crosstalk between proteomics and immune protection antigens utilizing serum. Peptide presentation by MHC provides the new 'window' into changes that occur in the cell. Thus, there is strong, intense pressure on the pathogen that has been mutated in such an unusual manner that it can bypass the MHC peptide presentation by the MHC molecule. The pathogen's ability to evade the immune system is strongly restricted by the two unique distinct properties of MHC molecules, i.e., polygenic and polymorphic properties. MHC-I restriction epitope identification has traditionally been accomplished using genetic motif prediction. The study of immune system proteins and their interactions is the main emphasis of the specialist field of immunoproteomics within proteomics. Methodologies include mass spectrometry (MS), SRM assay, MALDI-TOF, Chromatography, ELISA, 2DG PAGE, and bioinformatics tools. Challenges are the complexity of the immune system, protein abundance and dynamics, sample variability, post-translational modifications (PTMs), and data integration. Current advancements are enhanced mass spectrometry techniques, single-cell proteomics, artificial intelligence and machine learning, advanced protein labeling techniques, integration with other omics technologies, and functional proteomics. However, the recently emerging field of immunoproteomics has more promising possibilities in the field of peptide-based vaccines and virus-like particle vaccines. The importance of immunoproteomics technologies and methodologies, as well as their use in the field of vaccinomics, are the main topics of this review. Here, we have discussed immunoproteomics in relation to a step towards the future of vaccination.

Distribution characteristics of photoassimilates in walnut leaves to different organs

The understanding of photoassimilate distribution serves as the fundamental basis for scientific regulation of fruit quality. Currently, there is a scarcity of research on whole-plant scale photoassimilate distribution in walnut. In order to clarify the characteristics of leaf photoassimilates translocation to various organs in 5-year-old 'Wen185' (J. regia 'Wen185') walnut during the growing season, this study used the 13C isotope pulse labeling technique to label the whole plant of walnut trees in the growing season, temporal variations of 13C abundance (δ13C), 13C partition rate (R13C), leaf source strength and fruit sink strength were analyzed in various organs at different days after tree flowering. The findings indicated that during the periods of 30–70 days and 90–110 days after flowering, there was a higher distribution of 13C in fruits and vegetative branches. However, at 110–130 days after flowering, the predominant allocation of 13C shifted towards main trunk and roots. In-depth study of source leaves and sink fruits showed that chlorophyll content in leaves increased significantly 30–50 days after anthesis, indicating that they gradually became mature functional leaves. The increase of net photosynthetic rate led to increase of source strength, and the retention of photoassimilates in leaves was higher at this time. From 30 to 70 days after flowering, the fresh weight and volume of fruit increased rapidly, which increased the capacity of the sink and enhanced the competition ability against photoassimilates. The recovery of photosynthetic capacity of leaves from 90 to 110 days promoted the output of photoassimilates. At this time, walnut entered the oil conversion period, and the demand for photoassimilates increased. All these factors jointly promoted the unloading of photoassimilates in fruit. In summary, maintaining adequate material conditions and optimizing tree structure at 30-70d and 90-110d after anthesis are important for more efficient distribution of photoassimilates to fruit.

Specificity determinants of pathogens in forest

Abstract Host‐specific pathogens have long been suggested to act as a major driver of species diversity in tropical forests. However, determining the degree of host specificity of potential pathogens coupled to key cellular characteristics of infection is difficult and time‐consuming. These challenges have delayed progress in relating the functional specificity of pathogenic fungi to ecological consequences. We tested the pathogenicity of 27 (of 215) fungi that were isolated from surface sterilized roots of seedlings from four common tree species in a diverse subtropical forest. Inoculation experiments showed that six fungi exhibited strong pathogenicity on the host seedlings. Five of these only infected their specific hosts (i.e. host‐specific pathogen species). Green fluorescent protein labelling revealed that in three host‐specific pathogens fungal hyphae were able to grow into the vascular tissues only in their specific host plant, in contrast to other fungal‐host combinations that exhibit non‐pathogenic interactions. This fluorescent labelling technique allows direct tracking of the progress of fungal infection in different host tissues. Synthesis. By coupling the green fluorescent protein technique with standard host inoculation experiments, we determined the developmental differences between infections by pathogenic and non‐pathogenic fungi in a relatively simple and straightforward way. Our work provides a useful tool for rapidly screening and categorizing host–fungal interactions, reflecting the functional basis of host specificity of pathogenic fungi. More broadly, this technique can contribute to understanding the roles of pathogens in species coexistence and biodiversity maintenance in forest communities.

Selective pH-Responsive Conjugation between a Pair of De Novo Discovered Peptides.

There is a demand for site-selective peptide/protein conjugation chemistry that is fully reversible in a stimulus-responsive manner. The contemporary methods for site-selective protein modification enable the preparation of homogeneous protein-small molecule conjugates, which are indispensable for drug delivery and chemical biology purposes, but such chemistries are usually irreversible. In contrast, the existing reversible protein labeling techniques are generally not site-selective. Here, we report an mRNA display-enabled de novo discovery of a pair of peptides which selectively react with each other to form a conjugate that is stable under neutral conditions (pH 7.5) but rapidly dissociates into the constituents at pH 10. A Cys thiol of peptide CP1 rapidly reacts (k1 = 340 M-1·s-1) with the isothiocyanate moiety in partner ITC6 to furnish a stable dithiocarbamate (t1/2 = 6 h at pH 7.5). We show that the pH-responsive nature of the reaction (conjugate's t1/2 = 5 min at pH 10) can be leveraged to utilize ITC6 (1) as a pull-down handle to selectively isolate CP1 from cell lysates and (2) as a temporary protecting group to protect CP1 from nonspecific Cys labeling reagents such as iodoacetamide. Altogether, the chemistry developed here complements the existing approaches and is applicable in a variety of chemical biology settings where selective reversible reactions are needed.

Exploring caspase-dependent non-lethal cellular processes using Drosophila

Caspases are cysteine aspartic acid proteases conserved in animals that not only execute apoptosis, but also regulate diverse cellular processes independent of apoptosis, which are termed caspase-dependent non-lethal cellular processes (CDPs). Owing to its strong genetics to detect and manipulate caspase activity in cells of interest in vivo, Drosophila melanogaster serves as an excellent model organism for analyzing CDPs. This is further supported by the fact that apoptotic signaling, as well as CDPs and their mechanisms, are, in part, conserved in other animals. Here, we present a review to guide researchers studying CDPs using Drosophila. In this review, we provide an overview of the current understanding of apoptotic signaling, which regulates caspase activation in Drosophila as well as available genetic tools and their characteristics for detecting and manipulating caspase activity so that researchers can choose appropriate tools for their own experimental settings. We also introduce the CDPs identified in Drosophila, including a brief description of their discovery and characterization as non-lethal processes. We further describe the underlying molecular mechanisms of several well-characterized CDPs, including the regulatory mechanisms that enable non-lethal caspase activation. Finally, we introduce the use of proximity labeling techniques, especially TurboID, for studying CDPs, which facilitates the analysis of underlying molecular mechanisms. Because caspases regulate various non-lethal cellular functions, their activation is no longer considered a point of no return in cell death. Understanding CDPs will advance our understanding of the states of living and dying cells, along with the intermediate states.

Warm growing season activates microbial nutrient cycling to promote fertilizer nitrogen uptake by maize

The influence of nitrogen (N) inputs on soil microbial communities and N uptake by plants is well-documented. Seasonal variations further impact these microbial communities and their nutrient-cycling functions, particularly within multiple cropping systems. Nevertheless, the combined effects of N fertilization and growing seasons on soil microbial communities and plant N uptake remain ambiguous, thereby constraining our comprehension of the optimal growing season for maximizing crop production. In this study, we employed 15N isotope labeling, high-throughput sequencing, and quantitative polymerase chain reaction (qPCR) techniques to investigate the effects of two distinct growing seasons on microbial communities and maize 15N uptake ratios (15NUR). Our results showed that the warm growing season (26.6 °C) increased microbial diversity, reduced network complexity but enhanced stability, decreased microbial associations, and increased modularization compared to the cool growing season (23.1 °C). Additionally, the warm growing season favored oligotrophic species and increased the abundance of microbial guilds and functional genes related to N, phosphorus, and sulfur cycling. Furthermore, alterations in the characteristics of soil microbial keystone taxa were closely linked to variations in maize 15NUR. Overall, our findings demonstrate significant seasonal variations in soil microbial diversity and functioning, with maize exhibiting higher 15NUR during the warm growing season of the double cropping system.

Machine learning and deep learning models for the diagnosis of apical periodontitis: a scoping review.

To assess the existing literature on the use of machine learning (ML) and deep learning (DL) models for diagnosing apical periodontitis (AP) in humans. A scoping review was conducted following the Arksey and O'Malley framework. The PubMed, SCOPUS, and Web of Science databases were searched, focusing on articles using ML/DL approaches for AP diagnosis. No restrictions were applied. Two independent reviewers screened publications and charted data in predefined Excel tables for analysis. Nineteen publications focused on diagnosing AP by identifying periapical radiolucent lesions (PRLs) in dental radiographs were included. The average sensitivity and specificity for reviewed models were 83% and 90%, respectively. Only three studies explored the direct impact of artificial intelligence (AI) assistance on clinicians' diagnostic performance. Both consistently showed improved sensitivity without compromising specificity. Significant variability in dataset sizes, labeling techniques, and algorithm configurations was noticed. Findings affirm AI models' effectiveness and transformative potential in diagnosing AP by improving the accurate detection of periapical radiolucencies using dental radiographs. However, the lack of standardized reporting on crucial aspects of methodology and performance metrics prevents establishing a definitive diagnostic approach using AI. Further studies are needed to expand AI applications in AP diagnosis beyond radiographic analysis. AI can potentially improve diagnostic accuracy in AP diagnosis by enhancing the sensitivity of PRL detection in dental radiographs without compromising specificity.

4-plex quantitative glycoproteomics using glycan/protein-stable isotope labeling in cell culture

Alterations in glycoprotein abundance and glycan structures are closely linked to numerous diseases. The quantitative exploration of glycoproteomics is pivotal for biomarker discovery, but comprehensive analysis within biological samples remains challenging due to low abundance, complexity, and lack of universal technology. We developed a multiplex glycoproteomic approach using an LC-ESI-MS platform for direct comparison of glycoproteomic quantitation. Glycopeptides were isotopically labeled during cell culture, achieving high labeling efficiency (≥ 95 %) for both glycans and peptides. Quantitation was validated by mixing the same cell line in a 1:1:1:1 ratio, with mathematical correction applied to deconvolute the ratios. This method proved reliable and was applied to a comparative glycoproteomic study of three breast cancer cell lines (HTB22, MDA-MB-231, MDA-MB-231BR) and one brain cancer cell line (CRL-1620), quantifying glycopeptides from three replicates. The expression of glycopeptides was relatively quantified, and up/down-regulation between cell lines was investigated. This approach provided insights into glycosylation microheterogeneity, crucial for breast cancer brain metastasis research. Benefits include eliminating fluctuations from nano electrospray ionization and reducing analysis time, enabling up to 4-plex profiling in a single injection. Metabolic labeling introduced mass differences at the MS1 level, ensuring increased sensitivity and higher resolution for accurate quantitation. SignificanceAlternations in glycoprotein abundance, changes in glycosylation levels, and variations in glycan structures are closely linked to numerous diseases. The quantitative exploration of glycoproteomics has emerged as a popular area of research for biomarker discovery. However, conducting a comprehensive quantitative analysis of the glycoproteome within biological samples remains challenging due to low abundance, inherent complexities, and the absence of universal quantitative technology. Here, we developed a multiplex glycoproteomic approach using an LC-ESI-MS platform to facilitate direct comparison of glycoproteomic quantitation and enhance throughput. This approach offers benefits such as eliminating quantitative fluctuations arising from nano electrospray ionization (ESI) and reducing analysis time, enabling up to 4-plex glycoproteomic profiling in a single injection. Glycopeptides were stable isotopic labeled during cell culture procedure, attaching to monosaccharides, amino acids, or both. We achieved a high labeling efficiency (≥ 95 %) for both glycans and peptides. Quantitation validation was tested on glycopeptides by mixing the same cell line with 1:1:1:1 ratio. Due to the overlapped isotopes, a mathematical correction was applied to deconvolute the ratio of 4-plex glycopeptides. This method demonstrated quantitative reliability and was successfully applied to a comparative glycoproteomic study of three breast cancer cells (HTB22, MDA-MB-231, and MDA-MB-231BR) and one brain cancer cell (CRL-1620), identifying a total of 264 glycopeptides from three replicates. The expression of glycopeptides among these four cells was relatively quantified and up/down-regulation between two cell lines was investigated. The exploration of glycosylation microheterogeneity through glycopeptide quantification may offer valuable insights for further investigation into breast cancer brain metastasis.Conclusion: The primary advantage of our presented work lies in the multiplexing offered by combining two established labeling techniques, SILAC and IDAWG, both of which have been effectively used and widely cited in the scientific community. This combination enhances the applicability and accuracy of our method, as demonstrated by the extensive citations and successful use of these techniques independently. We believe that this multiplexing approach significantly advances the field, despite the method's current limitation to cell systems.

Anticancer activity of Lannea coromandelica on B16F10 melanoma cell line: an in vitro and molecular docking approach

IntroductionPhytochemical screening was conducted on various bark extracts of Lannea coromandelica to assess their anticancer property against the B16F10 melanoma cell line. The phytoconstituents that were previously identified were utilized in molecular docking studies against the human tyrosinase related protein 1 (TYRP1) as a target receptor in order to provide more evidence for anticancer property. MethodsBark powder was extracted by maceration method using distilled water and soxhlet extraction using ethanol. The preliminary phytochemical evaluation and determination of total phenolic and flavonoid content of both extracts were conducted using biochemical assays. The present study investigated the possible anticancer effects of ethanol and aqueous extracts on the B16F10 melanoma cell line using the 3-4,5-dimethylthiazol-2-yl-2,5-diphenyl tetrazolium bromide (MTT) assay and 4,6-diamidino-2-phenylindole (DAPI) labeling techniques. The present study employed molecular docking techniques to assess the binding interactions between phytoconstituents and the TYRP1 protein, utilizing AutoDock Vina module of PyRx 0.8 software. ResultsThe phytochemical analysis found flavonoids, steroids, terpenoids, tannins, phenolic compounds, saponins, anthraquinones, cardiac glycosides, and proteins. Ethanolic extract shown preferential cytotoxicity to B16F0 melanoma cell line in-vitro (IC50=9.69±0.68μg/ml), while aqueous extract exhibited IC50=75.49±5.95μg/ml. DAPI staining showed that treated cells had altered nucleus morphology, including apoptotic bodies. According to molecular docking investigations, Quercetin has the highest binding affinity (−9.6 Kcal/mol), followed by Catechin and Myricadiol. ConclusionThe current investigation has determined that L. coromandelica exhibits cytotoxic characteristic, as evidenced by the utilization of computer aided drug design models and in-vitro experimentation.

A Scoping Review on the Utility of Ultrasound to Visualize Bursae in Anatomical Dissection Courses

Bursitis is a common condition in clinical practice, often causing pain in the shoulder and buttock areas due to inflamed bursae. Proper diagnosis and treatment depend on knowing the presence and exact location of these bursae. Anatomy classes typically provide limited instruction on bursae because they are difficult to demonstrate during dissection courses. High-resolution ultrasound is an essential and versatile technique for detecting bursitis, and it could also serve as a valuable tool for students to better understand bursae. Relevant studies were screened in the following databases: CENTRAL, MEDLINE, BIOSIS Previews, EMBASE, and Web of Science Core Collection. Grey literature was also considered. Literature was screened on January 3, 2023. Only ultrasound investigations in human cadaver bursae were included, specifically using B-Mode ultrasound. The general characteristics of the included studies and the ultrasound-guided approaches for labeling the bursae were analyzed and examined. T The search found 8,899 matches, but only 15 met the criteria. Fifteen different bursae were studied, and 12 studies were included in the analysis. Both the marking substrate and the injected volume varied. Despite a high overall accuracy of 99% achieved using ultrasound-guided labeling approaches in the included studies, caution is advised due to the small sample size (1 to 24). The current study serves as a review to examine ultrasound studies on bursae in human cadavers. Ultrasound-guided labeling techniques achieve high accuracy and could be a valuable teaching tool in dissection courses. These techniques help visualize difficult-to-dissect structures and provide students with an understanding of sonoanatomy.