Biological Experiments Research Articles

Similar, but not the same: multiomics comparison of human valve interstitial cells and osteoblast osteogenic differentiation expanded with an estimation of data-dependent and data-independent PASEF proteomics

Abstract Osteogenic differentiation is crucial in normal bone formation and pathological calcification, such as calcific aortic valve disease (CAVD). Understanding the proteomic and transcriptomic landscapes underlying this differentiation can unveil potential therapeutic targets for CAVD. In this study, we employed RNA sequencing transcriptomics and proteomics on a timsTOF Pro platform to explore the multiomics profiles of valve interstitial cells (VICs) and osteoblasts during osteogenic differentiation. For proteomics, we utilized 3 data acquisition/analysis techniques: data-dependent acquisition (DDA)–parallel accumulation serial fragmentation (PASEF) and data-independent acquisition (DIA)–PASEF with a classic library-based (DIA) and machine learning–based library-free search (DIA-ML). Using RNA sequencing data as a biological reference, we compared these 3 analytical techniques in the context of actual biological experiments. We use this comprehensive dataset to reveal distinct proteomic and transcriptomic profiles between VICs and osteoblasts, highlighting specific biological processes in their osteogenic differentiation pathways. The study identified potential therapeutic targets specific for VICs osteogenic differentiation in CAVD, including the MAOA and ERK1/2 pathway. From a technical perspective, we found that DIA-based methods demonstrate even higher superiority against DDA for more sophisticated human primary cell cultures than it was shown before on HeLa samples. While the classic library-based DIA approach has proved to be a gold standard for shotgun proteomics research, the DIA-ML offers significant advantages with a relatively minor compromise in data reliability, making it the method of choice for routine proteomics.

Design, Synthesis, and Anticancer Activity of Drug-like Iron Chelators/G-Quadruplex Binders as Synergic Dual Targeting Agents.

Iron homeostasis is strictly related to numerous physiological pathways including cell cycle progression and cell growth. The newest anticancer strategies focus on either depleting the cells with a suitable chelator or increasing their loading by administering iron complexes to induce ferroptosis. Iron depletion inhibits cell proliferation, while iron overload induces the damage of guanine nucleobases in G-quadruplex structures via ROS generation, leading to genome instability. Here, we demonstrated that designing a molecular chimera embodying structural requirements for both iron chelation and G-quadruplex binding can result in dual-targeting compounds endowed with synergistic anticancer effects. We designed, synthesized, and tested a library of such compounds through biophysical and biological experiments. Compound 16 emerged as a lead candidate and a pharmacological tool able to chelate iron and stabilize G-quadruplexes in human leukemia Jurkat cells. Notably, it also localizes in the cell nucleus, serving as an intrinsically fluorescent nuclear tracer for the labile iron pool.

Novel functional eQTL-SNPs associated with susceptibility to occupational pulmonary fibrosis: A multi-stage study.

Identifying the common functional single-nucleotide polymorphisms (SNPs) that can both affect the susceptibility to idiopathic pulmonary fibrosis (IPF) and silicosis. We first integrated the genome-wide association studies (GWASs) of IPF and silicosis to obtain the shared SNPs. Following this, functional expression quantitative trait locus (eQTL)-SNPs were identified by the GTEx database. This was followed by the validation of the correlation between these eQTL-SNPs and silicosis susceptibility through an additional case-control study including 194 silicosis cases and 235 healthy controls. A total of 10 eQTL-SNPs that may affect silicosis susceptibility (P < 0.05) were obtained after the integration of the GWASs of IPF and silicosis, and a series of rigorous selection principles. Subsequently, the results of integrating the validation stage and the screening stage indicated that the variant T allele of rs1620530 located in the MAD1L1 (additive model: OR= 1.56, 95 % CI = 1.21-2.01, P = 0.001) and the variant G allele of rs2070063 located in the SERTAD2 (additive model: OR= 1.60, 95 % CI = 1.24-2.06, P < 0.001) were associated with increased silicosis susceptibility. The joint analysis indicated the risk of developing silicosis was higher in individuals who carried more unfavorable alleles of rs1620530 and rs2070063. The rs1620530 and rs2070063 may affect the silicosis susceptibility by regulating the expression of the MAD1L1 and SERTAD2, respectively. Further biological experiments are warranted to elucidate the underlying biological mechanisms between these two SNPs and the increased susceptibility to silicosis.

Identifying potential prognosis markers in relapsed multiple myeloma via integrated bioinformatics analysis and biological experiments

Identifying potential prognosis markers in relapsed multiple myeloma via integrated bioinformatics analysis and biological experiments

How the technologies behind self-driving cars, social networks, ChatGPT, and DALL-E2 are changing structural biology.

The performance of deep Neural Networks (NNs) in the text (ChatGPT) and image (DALL-E2) domains has attracted worldwide attention. Convolutional NNs (CNNs), Large Language Models (LLMs), Denoising Diffusion Probabilistic Models (DDPMs)/Noise Conditional Score Networks (NCSNs), and Graph NNs (GNNs) have impacted computer vision, language editing and translation, automated conversation, image generation, and social network management. Proteins can be viewed as texts written with the alphabet of amino acids, as images, or as graphs of interacting residues. Each of these perspectives suggests the use of tools from a different area of deep learning for protein structural biology. Here, I review how CNNs, LLMs, DDPMs/NCSNs, and GNNs have led to major advances in protein structure prediction, inverse folding, protein design, and small molecule design. This review is primarily intended as a deep learning primer for practicing experimental structural biologists. However, extensive references to the deep learning literature should also make it relevant to readers who have a background in machine learning, physics or statistics, and an interest in protein structural biology.

A diazirine's central carbon is sp2-hybridized, facilitating conjugation to dye molecules.

Diazirines are versatile carbene precursors that are extensively used in biological target identification experiments. However, their photo-activation wavelength (ca. 365 nm) precludes their use in living organisms. Here we show that a reconceptualization of the diazirine hybridization state leads to conjugation of the diazirine motif to longer-wavelength chromophores. In a model diazirine-fluorene conjugate, we are able to achieve direct activation (and subsequent C-H insertion) with >450 nm light for the first time. Two-photon activation using near-IR light is also achieved, suggesting the possibility to prepare new diazirine probes for conducting target identification experiments in deep tissue.

Proteogenomics for Non-model Ocean-Derived Fungi.

Most biological and biomedical experiments are designed and studied using the most common model organisms (MOs) like humans, mice, Escherichia coli, Saccharomyces cerevisiae, Neurospora crassa, worms, fruit flies, zebrafish, and Arabidopsis thaliana. These model organisms have been extensively studied and have a well-established set of genetic, physiological, and other tools available for research. In contrast, non-model organisms (NMOs) are those that are not traditionally used in scientific research and do not have a well-established set of genetic or other biological tools available for their study. The majority of MOs are associated with land habitats but rarely with ocean environments. The ocean forms the largest portion of our planet, yet ocean-derived organisms are the least explored, and these organisms are primarily NMOs. However, these are thrilling living entities, such as ocean-derived fungi (ODF). These ODFs are a diverse group of fungi that live in different ocean sectors, including the ocean, estuaries, and coastal ecosystems. These fungi are found to colonize and adapt to different substrates. They are important decomposers in marine ecosystems, breaking down dead organic matter and recycling nutrients. ODFs have adapted to survive in the unique and challenging conditions of the ocean environment, including high salt concentrations, low nutrient availability, and exposure to waves and currents. ODFs are potent producers of natural compounds with pharmaceutical and industrial applications, such as antibiotics, anticancer agents, antivirals, and enzymes for industrial processes. ODFs are an exciting group of fungi; however, these are the least studied because of the nonavailability of MOs from this group. Hence, there is a massive scope of expanding our current knowledge about ODFs, their genetic traits, potential future drug-producing capabilities, and lifestyle traits.With the advent of next-generation DNA sequencing, there is huge potential for the characterization of the genetic material of ODF as NMOs. Parallel proteomic methods also pose huge potential. A marriage of NGS and proteomic methods generates a new avenue called proteogenomics, which focuses on better annotation of existing genomic data. Both methods are getting cheaper and accessible to the research community for studying the proteogenomics of NMOs. Herein, the proteogenomic protocol development and data analyses are illustrated for the ocean-derived fungus Scopulariopsis brevicaulis.

Exosomes derived from fibroblasts in DFUs delay wound healing by delivering miR-93-5p to target macrophage ATG16L1.

Diabetes is an extremely costly disease, one-third of which are attributed to the management of diabetic foot disease including chronic, non-healing, diabetic foot ulcers (DFUs). Therefore, much effort is needed to understand the pathogenesis of DFUs and novel therapeutics. We utilized exosome staining to confirm the interaction between fibroblast-derived exosomes and macrophages. Subsequently, we employed public data and qPCR to screen for upregulated miRNAs in fibroblast-derived exosomes in DFUs. The relationship between was validate miR-93-5 and ATG16L1 through data prediction and dual-luciferase reporter assays. A variety of molecular biology experiments were used for subsequent pathway validation. Additionally, we established Atg16l1MKI and Nlrp3MKO mice for further validation. We identified that miR-93-5p derived from fibroblasts played an important role in M1 macrophages polarization. Predicted by database, we found that miR-93-5p can bind to ATG16L1 mRNA, thereby influencing macrophage autophagy mediated by ATG16L1 in the clearance of ROS, thus activating the NLRP3 signaling pathway. In vivo, miR-93-5p antagomir treatment accelerated diabetic wound healing and induced M2 macrophage polarization. Fibroblasts and macrophages show cell crosstalk during the development of DFUs by miR-93-5p, and that antagomir treatment may be a promising and technically advantageous alternative to DFUs therapies.

Genome Annotation.

The hallmark of genome sequencing projects is to provide genetic information on a species with functional annotations of genes and proteins. This process heavily relies on genome annotation based on homology detections from previously known genomic data. The rapid advancement of genome sequencing technologies has made genome sequencing affordable and effective in terms of the time frame for the generation of genomic data. Hence, genome sequencing has become a common practice. The annotation and characterization of newly sequenced genomes are crucial factors for the success of any biological experiment based on genomic data. The proteogenomic sector requires annotated genome further characterization of proteomic-based studies, and these are coupled with genomic and RNA-seq data. This chapter describes the genome annotation process from scratch genome sequencing to general genome annotation and specialized genome annotation using BLAST, BLAT2GO (now OMICSBOX), PANNZER, gene ontology (GO), and KEGG. It also covers different processes like repeat identification and masking, gene prediction, genome-wide annotation process, and RNA-seq protocol. It also focuses on genes of interest such as genes associated with BGCs (biosynthetic gene clusters), carbohydrate-active enzymes (CAZymes), serpins (serine protease inhibitors), membrane transporters, and toxins. Manual annotation is also a critical step for at least some groups of genes, which are often critical for the species in consideration. This chapter also briefly describes the phylogenetic and phylogenomic processes required during genome annotation.

Sappanone A alleviates metabolic dysfunction-associated steatohepatitis by decreasing hepatocyte lipotoxicity via targeting Mup3 in mice.

Metabolic dysfunction-associated steatohepatitis (MASH) is an inflammatory lipotoxic disorder marked by hepatic steatosis, hepatocyte damage, inflammation, and varying stages of fibrosis. Sappanone A (SA), a flavonoid, exhibits anti-inflammatory and hepatoprotection activities. Nevertheless, the effects of SA on MASH remain ambiguous. We evaluated the effects of SA on hepatocyte lipotoxicity, inflammation, and fibrosis conditions in MASH mice, as well as the underlying mechanisms. A conventional murine MASH model fed a methionine-choline-deficient (MCD) diet was utilized to assess the role of SA on MASH in vivo. Drug target prediction and liver transcriptomics were employed to elucidate the potential actions of SA. AML12 cells were applied to further explore the effects and mechanisms of SA in vitro. The in silico prediction indicated that SA could modulate inflammation, insulin resistance, lipid metabolism, and collagen catabolic process. Treating with SA dose-dependently lessened the elevated levels of serum ALT and AST in mice with diet-triggered MASH, and high-dose SA treatment exhibited a similar effect to silymarin. Additionally, SA treatment significantly reduced lipid deposition, inflammation, and fibrosis subjected to metabolic stress in a dose-dependent manner. Besides, SA mitigated palmitate-triggered lipotoxicity in hepatocytes. Liver transcriptomics further confirmed the aforementioned findings. Of note, mRNA-sequencing analysis and molecular biology experiments demonstrated that SA statistically up-regulated the hepatic expression of major urinary protein 3 (Mup3), thereby facilitating lipid transportation and inhibiting lipotoxicity. Furthermore, Mup3 knockdown in hepatocytes significantly abolished the hepatoprotection provided by SA. SA alleviates MASH by decreasing lipid accumulation and lipotoxicity in hepatocytes, at least partially by targeting Mup3, and subsequently blocks MASH process. Therefore, SA could be a promising hepatoprotective agent in the context of MASH.

Comparison of Plant Genomic DNA Extraction Kits Using the Proofman-LMTIA Amplification Assay.

The extraction of DNA is the basis of molecular biology research. The quality of the extracted DNA is one of the key factors for the success of molecular biology experiments. To select a suitable DNA extraction method for Chinese medicinal herbs and seeds. In this experiment, four commercial DNA extraction kits were used to extract the genomic DNA (gDNA) from the Pinellia ternata (Thunb.) Breit. powder; Arisaema amurense Maxim. powder as well as the seeds of Glycine max (L.) Merr. On the one hand, the concentration and purity of DNA extracted by these four kits were compared. On the other hand, nucleic acid amplification experiments were performed on three samples extracted by each of the four kits by Proofman-LMTIA methods, which is a novel nucleic acid isothermal amplification technique. The concentration and purity of DNA extracted by different kits were used to determine which methods were suitable for the dry powder of Chinese herbal medicines and seeds. The efficiency of the amplification curve to show whether the extracted DNA can be used in nucleic acid amplification experiments. The results showed that the Proofman-LMTIA methods were of high specificity and the optimal reaction temperatures were 63, 59, and 59°C for P. ternata (Thunb.) Makino; A. amurense Maxim. and G. max (L.) Merr., respectively. The concentration and purity of the gDNAs extracted with all kits were within the acceptable ranges; meanwhile, the amplification of the gDNA extracted by Kit II was of the highest efficiency. In this experiment, the principle, concentration, purity, and time taken for extracting DNA with four kits were compared. The automated extraction kit based on the magnetic method is suitable for extracting DNA from Chinese medicinal herbs and seeds. The extracted DNA is suitable for nucleic acid amplification detection.

Bioinformatics based exploration of the anti-NAFLD mechanism of Wang’s empirical formula via TLR4/NF-κB/COX2 pathway

BackgroundNonalcoholic fatty liver disease (NAFLD) has developed as a leading public wellness challenge as a result of changes in dietary patterns. Unfortunately, there is still a lack of effective pharmacotherapy methods for NAFLD. Wang’s empirical formula (WSF) has demonstrated considerable clinical efficacy in treating metabolic disorders for years. Nevertheless, the protective effect of WSF against NAFLD and its underlying mechanism remains poorly understood.MethodsThe NAFLD model was established using a 17-week high-sucrose and high-fat (HSHF) diet with 32 ICR mice. In assessing the therapeutic efficacy of WSF on NAFLD, we detected changes in body weight, viscera weight, biomarkers of glycolipid metabolism in serum and liver, transaminase levels and histopathology of liver with H&E and Oil Red O staining after oral administration. The chemical components in WSF were extensively identified and gathered utilizing the HPLC-Q-TOF/MS system, database mining from HMDB, MassBank, and TCMSP databases, alongside literature searches from CNKI, Wanfang and VIP databases. The forecast of network pharmacology approach was then utilized to investigate the probable mechanisms by which WSF improves NAFLD based on the performance of prospective target identification and pathway enrichment analysis. Besides, molecular docking was also conducted for the verification of combination activities between active components of WSF and core proteins related to NAFLD. In final, validation experiments of obtained pathways were conducted through ELISA, immunohistochemistry (IHC), and western blot (WB) analysis.ResultsPharmacodynamic outcomes indicated that WSF intervention effectively mitigated obesity, fat accumulation in organs, lipid metabolism disorders, abnormal transaminase levels and liver pathology injury in NAFLD mice (P < 0.05, 0.01). A total of 72 existent ingredients of WSF were acquired by HPLC-Q-TOF/MS and database, and 254 common targets (11.6% in total targets) of NAFLD and WSF were identified. Network pharmacology revealed that WSF presses NAFLD via modulating TNF, IL6, AKT1, IL1B, PTGS2 (COX2), and other targets, and the probable pathways were primarily inflammatory signaling pathways, as confirmed by molecular docking. Molecular biology experiments further conformed that WSF could decrease levels of inflammatory factors like IL-1β, IL-6 and TNF-α (P < 0.01) and expression of TLR4, NF-κB and COX-2 (P < 0.05, 0.01) in the liver.ConclusionWSF treatment effectively protects against lipid metabolism disorders and liver inflammation injury in HSHF diet-induced NAFLD mice, and its molecular mechanism might be via suppressing the TLR4/NF-κB/COX-2 inflammatory pathway to reduce the release of inflammatory cytokines in the liver.Graphical abstract

Design, synthesis, and biological evaluation of (E)-2-benzylidene-1-indanones derivatized by bioisosteric replacement of aurones

AbstractThymic stromal lymphopoietin (TSLP) is a cytokine derived from epithelial cells and plays an essential role in the onset and activation of Th2-derived allergic inflammatory conditions, including atopic dermatitis. Despite their potential as drug targets, well-defined small molecules that effectively block TSLP expression are still lacking. A plant-derived secondary metabolite, aurone, was derivatized based on bioisosteric replacement to identify compounds that inhibit the promoter activity of TSLP. Thirteen (E)-2-benzylidene-1-indanones were designed and synthesized, and their structures were identified using NMR spectroscopy and mass spectrometry. Inhibition of the expression of TSLP triggered by interleukin-4 (IL-4) caused by (E)-2-benzylidene-1-indanones was measured using a TSLP gene promoter-reporter activity assay. Because compound 12, (E)-5-methoxy-2-(3-methoxybenzylidene)-2,3-dihydro-1H-inden-1-one, showed the best activity, further biological experiments, including RT-PCR analysis, quantitative real-time PCR, and inhibitory effects on IL-4-induced early growth response-1 (EGR-1) expression, EGR-1 DNA-binding activity, and IL-4-induced phosphorylation of the mitogen-activated protein kinase (MAPK) signaling cascade were performed. This study demonstrated that compound 12 acts on MAPK to block IL-4-triggered mRNA expression of TSLP via the MAPK-EGR-1 signaling pathway in HaCaT keratinocytes.

A practical, biomimetic, one-pot synthesis of firefly luciferin.

The bioluminescence reaction of firefly luciferase with D-luciferin has become an indispensable imaging technique in modern biology and life science experiments, but the high cost of D-luciferin is limiting its further application. Here, we report a practical, one-pot synthesis of D-luciferin from p-benzoquinone (p-BQ), L-cysteine methyl ester and D-cysteine, with an overall yield of 46%. Our route, which is six steps in length and proceeds via 2-cyano-6-hydroxybenzothiazole, is inspired by the mechanistic study of our previously reported biomimetic, non-enzymatic, one-pot formation of L-luciferin from p-BQ and L-cysteine. Advantages of our route include its high yield, low cost, use of only inexpensive, commercially available reagents, without requiring strictly anhydrous and oxygen-free conditions, and elevated temperatures.

Selected methods for effective inactivation of microorganisms in experimental chambers intended for indoor air bioaerosol studies

The frequent occurrence of threats from various airborne biological factors has led to a significant increase in experimental research on bioaerosols in recent years. One of the key areas of interest for researchers in this field are microorganisms present in enclosed spaces, both suspended in indoor air and settled on surfaces. A common feature of all these experiments in the initial stage of the investigation is the simulation of basic phenomena related to bioaerosols based on closed experimental systems. During this type of research, a crucial preliminary step that significantly impacts the quality of biological research results is the process of ensuring the appropriate microbiological purity of the experimental cells. The filtration methods currently used for indoor air purification in chambers do not effectively remove microorganisms from surfaces, especially in difficult to reach areas. Microorganisms settled on surfaces are detached because of air movement in the chamber and can reform bioaerosol. Therefore, for many years, research has been aimed at developing an effective technique for decontaminating air and surfaces in enclosed spaces. In recent years, there has been a development of chemical disinfection techniques based on the generation of fog from biocidal agents. The paper presents selected results of original research, demonstrating that the decontamination of experimental chambers for bioaerosol studies using dry fog generated from hypochlorous acid (HOCl) at a concentration of 300 ppm allows a high degree of microbiological purity before biological experiments and does not pose a threat to human health. Furthermore, the use of HOCl-generated dry fog as a method to decontaminate experimental chambers and laboratory spaces can also reduce the threat posed by biological agents to research personnel and protect against the contamination of the surrounding environment.

Artificial intelligence-enabled discovery of a RIPK3 inhibitor with neuroprotective effects in an acute glaucoma mouse model

Abstract Background: Retinal ganglion cell (RGC) death caused by acute ocular hypertension is an important characteristic of acute glaucoma. Receptor-interacting protein kinase 3 (RIPK3) that mediates necroptosis is a potential therapeutic target for RGC death. However, the current understanding of the targeting agents and mechanisms of RIPK3 in the treatment of glaucoma remains limited. Notably, artificial intelligence (AI) technologies have significantly advanced drug discovery. This study aimed to discover RIPK3 inhibitor with AI assistance. Methods: An acute ocular hypertension model was used to simulate pathological ocular hypertension in vivo. We employed a series of AI methods, including large language and graph neural network models, to identify the target compounds of RIPK3. Subsequently, these target candidates were validated using molecular simulations (molecular docking, absorption, distribution, metabolism, excretion, and toxicity (ADMET) prediction, and molecular dynamics simulations) and biological experiments (Western blotting and fluorescence staining) in vitro and in vivo. Results: AI-driven drug screening techniques have the potential to greatly accelerate drug development. A compound called HG9-91-01, identified using AI methods, exerted neuroprotective effects in acute glaucoma. Our research indicates that all five candidates recommended by AI were able to protect the morphological integrity of RGC cells when exposed to hypoxia and glucose deficiency, and HG9-91-01 showed a higher cell survival rate compared to the other candidates. Furthermore, HG9-91-01 was found to protect the retinal structure and reduce the loss of retinal layers in an acute glaucoma model. It was also observed that the neuroprotective effects of HG9-91-01 were highly correlated with the inhibition of PANoptosis (apoptosis, pyroptosis, and necroptosis). Finally, we found that HG9-91-01 can regulate key proteins related to PANoptosis, indicating that this compound exerts neuroprotective effects in the retina by inhibiting the expression of proteins related to apoptosis, pyroptosis, and necroptosis. Conclusion: AI‐enabled drug discovery revealed that HG9-91-01 could serve as a potential treatment for acute glaucoma.

Astragali radix vesicle-like nanoparticles improve energy metabolism disorders by repairing the intestinal mucosal barrier and regulating amino acid metabolism in sleep-deprived mice

BackgroundSleep disorder is widespread and involves a variety of intricate factors in its development. Sleep deprivation is a manifestation of sleep disorder, can lead to energy metabolism disturbances, weakened immune system, and compromised body functions. In extreme situations, sleep deprivation can cause organ failure, presenting significant risks to human health.PurposeThis study aimed to investigate the efficacy and mechanisms of Astragalus Radix vesicles-like nanoparticles (AR-VLNs) in counteracting the deleterious effects of sleep deprivation.MethodsThe ICR mice were divided into control, model, AR-VLNs high dose (equivalent to 20 g/kg crude drug), AR-VLNs low dose (equivalent to 10 g/kg crude drug), AR high dose (equivalent to 20 g/kg crude drug), and AR low dose (equivalent to 10 g/kg crude drug). The REM (rapid eye movement) sleep-deprivation model was established, and evaluations were conducted for motor function, antioxidant capacity, and energy metabolism indices. Moreover, CACO-2 cells damage was induced with lipopolysaccharide to evaluate the repairing ability of AR-VLNs on the intestinal cell mucosa by measuring permeability. Furthermore, metabolomics was employed to elucidate the mechanisms of AR-VLNs action.ResultsAR-VLNs were demonstrated to enhance the motor efficiency and antioxidant capacity in REM sleep-deprived mice, while also minimized pathological damage and restored the integrity of the intestinal mucosal barrier. In vitro experiments indicated the anti-inflammatory effect of AR-VLNs against LPS-induced cell damage. Additionally, metabolomic analysis linked these effects with regulation of the amino acid metabolic pathways. Further confirmation from molecular biology experiments revealed that the protective effects of AR-VLNs against the deleterious effects of REM sleep deprivation were associated with the restoration of the intestinal mucosal barrier and the enhancement of amino acid metabolism.ConclusionAR-VLNs administration effectively improved energy metabolism disorders in REM sleep deprived mice, by facilitating the repair of the intestinal mucosal barrier and regulating the amino acid metabolism.Graphical

Methods for Image Analysis of Intracellular Structures of Actin Labeled with Phalloidin

A cell is a complex three-dimensional system, which possesses a number of highly dynamic structures with extended, rugged, and uneven morphology. The actin cytoskeleton consists of fibrillar and globular actin, as well as auxiliary proteins that regulate organization. The shape and the rearrangements of actin cytoskeleton are closely related to functioning of the cell. The ability to characterize these changes allows scientists to confirm or refute any hypotheses in the research. Obtaining a numerical equivalent of the actin cytoskeleton organization could help compare actin structures in biological experiments (example: exposure to biologically active substances). The review summarizes methods for analyzing images of intracellular actin structures labeled with phalloidin using ImageJ. The methods considered make it possible to obtain a quantitative characteristic of the organization of actin structures for further evaluation and comparison of experimental results.

New insights into the role of mitophagy related gene affecting the metastasis of osteosarcoma through scRNA-seq and CRISPR-Cas9 genome editing

BackgroundOsteosarcoma (OSA), the most common primary bone malignancy, poses significant challenges due to its aggressive nature and propensity for metastasis, especially in adolescents. Mitophagy analysis can help identify new therapeutic targets and combined treatment strategies.MethodsThis study integrates single-cell sequencing (scRNA-seq) data and bulk-seq to identify mitophagy-related genes (MRGs) associated with the progression of OSA metastasis and analyze their clinical significance. scRNA-seq data elucidates the relationship between mitophagy and OSA metastasis, employing “CellChat” R package to explore intercellular communications and report on hundreds of ligand-receptor interactions. Subsequently, the combination of bulk-seq and CRISPR-Cas9 gene editing identifies mitophagy-related biomarker associated with metastatic prognosis. Finally, validation of the relationship between mitophagy and OSA metastasis is achieved through cellular biology experiments and animal studies.ResultsThe distinct mitophagy activity of various mitochondria manifests in diverse spatial localization, cellular developmental trajectories, and intercellular interactions. OSA tissue exhibits notable heterogeneity in mitophagy within osteoblastic OSA cells. However, high mitophagy activity correlates consistently with high metastatic potential. Subsequently, we identified three critical genes associated with mitophagy in OSA, namely RPS27A, TOMM20 and UBB. According to the aforementioned queue of genes, we have constructed a mitophagy_score (MIP_score). We observed that it consistently predicts patient prognosis in both internal and external datasets, demonstrating strong robustness and stability. Furthermore, we have found that MIP_score can also guide chemotherapy, with varying sensitivities to chemotherapeutic agents based on different MIP_score. It is noteworthy that, through the integration of CRISPR-Cas9 genome-wide screening and validation via cellular and animal experiments, we have identified RPS27A as a potential novel biomarker for OSA.ConclusionsOur comprehensive analysis elucidated the profile of mitophagy throughout the OSA metastasis process, forming the basis for a mitophagy-related prognostic model that addresses clinical outcomes and drug sensitivity following OSA metastasis. Additionally, an online interactive platform was established to assist clinicians in decision-making (https://mip-score.shinyapps.io/labtan/). These findings lay the groundwork for developing targeted therapies aimed at improving the prognosis of OSA patients.

Microstructure and Bioactivity of Ca- and Mg-Modified Silicon Oxycarbide-Based Amorphous Ceramics.

Silicon oxycarbide (SiOC), Ca- and Mg-modified silicon oxycarbide (SiCaOC and SiMgOC) were synthesized via sol-gel processing with subsequent pyrolysis in an inert gas atmosphere. The physicochemical structures of the materials were characterized by XRD, SEM, FTIR, and 29Si MAS NMR. Biocompatibility and in vitro bioactivity were detected by MTT, cell adhesion assay, and simulated body fluid (SBF) immersion test. Mg and Ca were successfully doped into the network structure of SiOC, and the non-bridging oxygens (NBO) were formed. The hydroxycarbonate apatite (HCA) was formed on the modified SiOC surface after soaking in simulated body fluid (SBF) for 14 days, and the HCA generation rate of SiCaOC was higher than that of SiMgOC. Accompanying the increase of bioactivity, the network connectivity (NC) of the modified SiOC decreased from 6.05 of SiOC to 5.80 of SiCaOC and 5.60 of SiMgOC. However, structural characterization and biological experiments revealed the nonlinear relationship between the biological activity and NC of the modified SiOC materials.