Biological Signal Transduction Research Articles

AllohubPy: Detecting allosteric signals through an information-theoretic approach.

Allosteric regulation is crucial for biological processes like signal transduction, transcriptional regulation, and metabolism, yet the mechanisms and macromolecular properties that govern it are still not well understood. Several methods have been developed over the years to study allosterism through different angles. Among the possible ways to study allosterism, information-theoretic approaches, like AlloHubMat or GSAtools, can be particularly effective due to their use of robust statistics and the possibility to be combined with graph analysis. These methods capture local conformational changes associated with global motions from molecular dynamics simulations through the use of a Structural Alphabet, which simplifies the complexity of the Cartesian space by reducing the dimensionality down to a string of encoded fragments, representing sets of internal coordinates that still capture the overall conformation changes. In this work, we present "AllohubPy," an improved and standardized methodology of AlloHubMat and GSAtools coded in Python. We analyse the performance, limitations and sampling requirements of AllohubPy by using extensive molecular dynamics simulations of model allosteric systems and apply convergence analysis techniques to estimate result reliability. Additionally, we expand the methodology to use different dimensionality reduction Structural Alphabets, such as the 3DI alphabet, and integrate Protein Language Models (PLMs) to refine allosteric hub communication detection by monitoring the detected evolutionary constraints. Overall, AllohubPy expands its preceding methods and simplifies the use and reliability of the method to effectively capture dynamic allosteric motions and residue pathways. AllohubPy is freely available on GitHub (https://github.com/Fraternalilab/AlloHubPy) as a package and as a Jupyter Notebook.

New Properties of Phosphorus to Zinc Elements - Exploration of Energy Conversion Characteristics Based on Electromagnetic Signal Transmission in Semiconductor Devices

This study aims to explore novel properties of phosphorus (P) to zinc (Zn) elements. On the basis of previous work, we have explored the properties of elements ranging from H to Si. And the chemical elements belong layered, with P to Zn defined as the fourth layer to be researched using a contemporary industrial perspective. Since the late 19th century, there has been a progression in the application of electricity and magnetism to motor technology, leading to the evolution of computer systems capable of receiving, processing, and displaying external signals. These functionalities are recognized as attributes of the P element, serving as sensor modules for energy conversion. Subsequently, the establishment of a global production system through the utilization of the Internet and the Internet of Things has facilitated the growth of the biomedical industry within a vast industrial framework. This framework is characterized as the essence of the S element, functioning as an amplifier module for energy conversion. These 16 elements perform higher-level functions and can be seen as various processes for energy conversion in electromagnetic equipment, exemplified by biological signal transduction. They correspond to semiconductor chip fields such as from sensors and amplification circuits to displays and printing. This exploration is poised to enhance comprehension of the distinctive properties inherent in these elements.

Lipid metabolism-related gene signature predicts prognosis and unveils novel anti-tumor drugs in specific type of diffuse large B cell lymphoma

BackgroundDiffuse large B-cell lymphoma (DLBCL) is the most common type of lymphoma which possess highly aggressive and heterogeneous. Despite advances in understanding heterogeneity and development of novel targeted agents, the prognosis of DLBCL patients remains unsatisfied. Lipids are crucial components of biological membranes and signal transduction while accumulating evidence has supported the vital roles of abnormal lipid metabolism in tumorigenesis. Furthermore, some related pathways could serve as prognostic biomarkers and potential therapeutic targets. However, the clinical significance of abnormal lipid metabolism reprogramming in DLBCL has not been investigated. In the current study, we developed a prognostic risk model for DLBCL based on the abnormal expressed lipid metabolism genes and moreover based on our risk model we classified patients with DLBCL into novel subtypes and identified potential drugs for DLBCL patients with certain lipid metabolism profiles.MethodsWe utilized univariate Cox regression analysis to identify the prognosis-related lipid metabolism genes, and then performed LASSO Cox regression to identify prognostic related lipid metabolism related genes. Multivariate cox regression was used to establish the prognostic model. Patients were divided in to high and low risk groups based on the median risk score. Immune cell infiltration and GSEA were used to identify the pathways between high and low risk groups. Oncopredict algorithm was utilized to identify potential drug for high-risk patients. In vitro cell apoptosis and viability analysis were employed to verify the specific tumor inhibition effects of AZD5153.ResultsNineteen survival related lipid metabolism genes TMEM176B, LAYN, RAB6B, MMP9, ATAD3B, SLC2A11, CD3E, SLIT2, SLC2A13, SLC43A3, CD6, SIRPG, NEK6, LCP2, CTTN, CXCL2, SNX22, BCL6 and FABP4 were identified and subjected to build the prognostic model which was further verified in four external microarray cohorts and one RNA seq cohorts. Tumor immune microenvironment analysis and GSEA results showed that the activation of MYC targets genes rather than immunosuppression contribute to the poor survival outcome of patients in the high-risk group. AZD5153, a novel bivalent BET bromodomain inhibitor which could inhibit the transcription of MYC and E2F exhibited specific antitumor function for cells with high-risk score.ConclusionsOur results provide the first lipid metabolism-based gene signature for predicting the survival of patients with DLBCL. Furthermore, by determining novel subtypes with our lipid metabolism prognostic model we illustrated that drugs that compromising MYC target genes rather than immune checkpoint inhibitors may be beneficial to DLBCL patients with certain lipid metabolism profiles.

NDRG2 Deficiency Exacerbates UVB-Induced Skin Inflammation and Oxidative Stress Damage.

UVB radiation induces inflammatory and oxidative stress responses, contributing to skin damage, yet the underlying mechanisms are not fully understood. N-Myc downstream-regulated gene 2 (NDRG2), an emerging stress-associated gene, remains unexplored in UVB-induced skin injury. In this study, we detected skin NDRG2 expression after UVB irradiation for the first time and further used Ndrg2 knockout mice to clarify the role of NDRG2 in UVB-induced skin injury. Three-month-old male Ndrg2+/+ and Ndrg2-/- mice (16-18g) were exposed to UVB to induce acute skin damage, and then dorsal skin samples were collected for subsequent analyses. UVB-induced skin damage was scored. Western Blot Analysis, immunofluorescence (IF) double labeling, and immunohistochemistry (IHC) were employed to assess NDRG2 expression and/or distribution. The concentrations of TNF-α, IL-6, IL-1β, MPO, MMP8, superoxide dismutase (SOD), catalase (CAT), and glutathione (GSH) were quantitatively assessed using enzyme-linked immunosorbent assay (ELISA). Hematoxylin and eosin (HE) staining were employed to determine pathological changes. RNA sequencing and analysis were performed to estimate transcript expression levels and analyze mRNA expression. DESeq2 software was employed to identify differentially expressed genes (DEGs). DEGs were visualized using volcanic and heat maps. Gene Ontology (GO) functions and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were analyzed to identify primary biological functions, metabolic pathways, or signal transduction pathways associated with DEGs. UVB-challenged Ndrg2-/- mice exhibited significantly exacerbated skin damage (erythema, edema, and erosion), neutrophil infiltration, and apoptosis compared to Ndrg2+/+ mice. Furthermore, UVB-challenged Ndrg2-/- mice displayed significantly elevated pro-inflammatory cytokines, myeloperoxidase (MPO), matrix metalloproteinase-8 (MMP8), and reduced antioxidant expression. RNA sequencing identified 1091 significantly differentially expressed genes enriched in inflammation, immune response, and oxidative stress pathways. In conclusion, the deficiency of Ndrg2 markedly exacerbated UVB-induced skin damage by promoting inflammatory responses and inhibiting antioxidant responses. This suggests that stabilizing NDRG2 expression holds promise as a therapeutic strategy for protecting against UVB-induced skin damage.

Sublethal effects of nitenpyram on the development of silkworm

The utilization of nitenpyram for aphid and whitefly control may induce environmental contamination and negative repercussions on non-target organisms. Formerly, we found that nitenpyram would pollute the peripheral and sub-peripheral areas of the adjacent mulberry orchard. Under acute toxicity conditions, nitenpyram induced oxidative damage in silkworms, affected biological metabolism, synthesis, immunity, and signal transduction. Considering the impact of nitenpyram mist drift on mulberry leaves, we investigated the effects of low concentrations of nitenpyram on silkworms. The results showed that silkworms exposed to 0.17 mg/L, 0.35 mg/L and 0.70 mg/L of nitenpyram (1/40 LC50, 1/20 LC50 and 1/10 LC50) showed obvious poisoning symptoms. The cocoon weight and cocoon shell weight decreased gradually with increases in the concentration, and these decreases prolonged the growth and development time of silkworms and induced the detoxification enzymes carboxylesterase (CarE) and glutathione-S-transferase (GST) to cope with the stress damage caused by nitenpyram. Exposure to low concentrations of nitenpyram downregulates genes involved in the drug metabolism-other enzymes and peroxisome pathway in silkworms. Additionally, through injection of miRNA mimics and inhibitors, we discovered that detoxifying enzyme pathway genes are influenced by bmo-miR-3382-3P, bmo-miR-3213-5P and bmo-miR-133, regulating the immune response of silkworms. This study provides an overall view of the toxicity and detoxification metabolism of nitenpyram in silkworm, and provides a reference for environmental assessment.

Self-consistent signal transduction analysis for modeling context-specific signaling cascades and perturbations

Biological signal transduction networks are central to information processing and regulation of gene expression across all domains of life. Dysregulation is known to cause a wide array of diseases, including cancers. Here I introduce self-consistent signal transduction analysis, which utilizes genome-scale -omics data (specifically transcriptomics and/or proteomics) in order to predict the flow of information through these networks in an individualized manner. I apply the method to the study of endocrine therapy in breast cancer patients, and show that drugs that inhibit estrogen receptor α elicit a wide array of antitumoral effects, and that their most clinically-impactful ones are through the modulation of proliferative signals that control the genes GREB1, HK1, AKT1, MAPK1, AKT2, and NQO1. This method offers researchers a valuable tool in understanding how and why dysregulation occurs, and how perturbations to the network (such as targeted therapies) effect the network itself, and ultimately patient outcomes.

Liposome-embedded PtCu nanozymes for improved immunoassay of accurate myocardial infarction

Herein, we developed a platinum-copper nano-enzyme-linked immunosorbent assay (NLISA) based split diagnostic platform for the ultrasensitive detection of cardiac troponin I (cTnI). The PtCu nanozyme synthesized by one-pot synthesis exhibited ultra-high peroxidase-like activity (35.17 U mg−1), which was about 4.5 times higher than that of the unmodified Pt nanozyme (8.83 U mg−1). Due to the efficient peroxidase-like activity of the copper-platinum complexed nanozyme, transduction and sequential amplification of cTnI biological signals were achieved in combination with a liposome-embedded amplification strategy. The encapsulation efficiency was calculated by introducing a liposomal bilayer model, which showed that the introduction of a single liposomal molecule could amplify the signal up to 870-fold, thus promising a high sensitivity test. Notably, the dynamic response of cTnI was in the range of 0.1–5000 pg mL−1 with an ultra-low detection limit (0.048 pg mL−1). The developed NLISA analysis system provides a new way to discover efficient and sensitive alternatives to ELISA kits, which can meet the practical needs of community healthcare testing conditions and rapid testing in hospitals.

Duality of Branched-Chain Amino Acids in Chronic Cardiovascular Disease: Potential Biomarkers versus Active Pathophysiological Promoters.

Branched-chain amino acids (BCAAs), comprising leucine (Leu), isoleucine (Ile), and valine (Val), are essential nutrients vital for protein synthesis and metabolic regulation via specialized signaling networks. Their association with cardiovascular diseases (CVDs) has become a focal point of scientific debate, with emerging evidence suggesting both beneficial and detrimental roles. This review aims to dissect the multifaceted relationship between BCAAs and cardiovascular health, exploring the molecular mechanisms and clinical implications. Elevated BCAA levels have also been linked to insulin resistance (IR), type 2 diabetes mellitus (T2DM), inflammation, and dyslipidemia, which are well-established risk factors for CVD. Central to these processes are key pathways such as mammalian target of rapamycin (mTOR) signaling, nuclear factor kappa-light-chain-enhancer of activate B cells (NF-κB)-mediated inflammation, and oxidative stress. Additionally, the interplay between BCAA metabolism and gut microbiota, particularly the production of metabolites like trimethylamine-N-oxide (TMAO), adds another layer of complexity. Contrarily, some studies propose that BCAAs may have cardioprotective effects under certain conditions, contributing to muscle maintenance and metabolic health. This review critically evaluates the evidence, addressing the biological basis and signal transduction mechanism, and also discusses the potential for BCAAs to act as biomarkers versus active mediators of cardiovascular pathology. By presenting a balanced analysis, this review seeks to clarify the contentious roles of BCAAs in CVD, providing a foundation for future research and therapeutic strategies required because of the rising prevalence, incidence, and total burden of CVDs.

A cuproptosis-related gene DLAT as a novel prognostic marker and its relevance to immune infiltration in low-grade gliomas

DLAT has been recognized as a cuproptosis-related gene that is crucial for cuproptosis in earlier research. The study is to look at how DLAT affects individuals with low-grade glioma's prognosis and immune infiltration. The Genotype-Tissue Expression (GTEx) database and the TCGA database were used in this work to download RNAseq data in TPM format. DLAT was found to be overexpressed in LGG by comparing DLAT expression levels between LGG and normal brain tissue, and the expression of DLAT was verified by immunohistochemistry and semi-quantitative analysis. Then, the functional enrichment analysis revealed that the biological functional pathways and possible signal transduction pathways involved were primarily focused on extracellular matrix organization, transmembrane transporter complex, ion channel complex, channel activity, neuroactive ligand-receptor interaction, complement and coagulation cascades, and channel activity. The level of immune cell infiltration by plasmacytoid dendritic cells and CD8 T cells was subsequently evaluated using single-sample gene set enrichment analysis, which showed that high DLAT expression was inversely connected with that level of infiltration. The link between the methylation and mRNA transcription of DLAT was then further investigated via the MethSurv database, and the results showed that DLAT's hypomethylation status was linked to a poor outcome. Finally, by evaluating the prognostic value of DLAT using the Cox regression analysis and Kaplan-Meier technique, a column line graph was created to forecast the overall survival (OS) rate at 1, 3, and 5 years after LGG identification. The aforementioned results demonstrated that high DLAT expression significantly decreased OS and DSS, and that overexpression of DLAT in LGG was significantly linked with WHO grade, IDH status, primary therapy outcome, overall survival (OS), disease-specific survival (DSS), and progression-free interval (PFI) events. DLAT was discovered as a separate predictive sign of OS in the end. DLAT might thus represent a brand-new predictive biomarker.

GlPRMT5 inhibits GlPP2C1 via symmetric dimethylation and regulates the biosynthesis of secondary metabolites in Ganoderma lucidum

PRMT5, a type II arginine methyltransferase, is involved in transcriptional regulation, RNA processing and other biological processes and signal transduction. Secondary metabolites are vital pharmacological compounds in Ganoderma lucidum, and their content is an important indicator for evaluating the quality of G. lucidum. Here, we found that GlPRMT5 negatively regulates the biosynthesis of secondary metabolites. In further in-depth research, GlPP2C1 (a type 2C protein phosphatase) was identified out as an interacting protein of GlPRMT5 by immunoprecipitation-mass spectrometry (IP-MS). Further mass spectrometry detection revealed that GlPRMT5 symmetrically dimethylates the arginine 99 (R99) and arginine 493 (R493) residues of GlPP2C1 to weaken its activity. The symmetrical dimethylation modification of the R99 residue is the key to affecting GlPP2C1 activity. Symmetrical demethylation-modified GlPP2C1 does not affect the interaction with GlPRMT5. In addition, silencing GlPP2C1 clearly reduced GA content, indicating that GlPP2C1 positively regulates the biosynthesis of secondary metabolites in G. lucidum. In summary, this study reveals the molecular mechanism by which GlPRMT5 regulates secondary metabolites, and these studies provide further insights into the target proteins of GlPRMT5 and symmetric dimethylation sites. Furthermore, these studies provide a basis for the mutual regulation between different epigenetic modifications.

Benchmarking Water Models in Molecular Dynamics of Protein-Glycosaminoglycan Complexes.

Glycosaminoglycans (GAGs) made of repeating disaccharide units intricately engage with proteins, playing a crucial role in the spatial organization of the extracellular matrix (ECM) and the transduction of biological signals in cells to modulate a number of biochemical processes. Exploring protein-GAG interactions reveals several challenges for their analysis, namely, the highly charged and periodic nature of GAGs, their multipose binding, and the abundance of the interfacial water molecules in the protein-GAG complexes. Most of the studies on protein-GAG interactions are conducted using the TIP3P water model, and there are no data on the effect of various water models on the results obtained in molecular dynamics (MD) simulations of protein-GAG complexes. Hence, it is essential to perform a systematic analysis of different water models in MD simulations for these systems. In this work, we aim to evaluate the properties of the protein-GAG complexes in MD simulations using different explicit: TIP3P, SPC/E, TIP4P, TIP4PEw, OPC, and TIP5P and implicit: IGB = 1, 2, 5, 7, and 8 water models to find out which of them are best suited to study the dynamics of protein-GAG complexes. The FF14SB and GLYCAM06 force fields were used for the proteins and GAGs, respectively. The interactions of several GAG types, such as heparin, chondroitin sulfate, and hyaluronic acid with basic fibroblast growth factor, cathepsin K, and CD44 receptor, respectively, are investigated. The observed variations in different descriptors used to study the binding in these complexes emphasize the relevance of the choice of water models for the MD simulation of these complexes.

SPC25 Functions as a Prognostic-Related Biomarker, and Its High Expression Correlates with Tumor Immune Infiltration and UCEC Progression.

Most tumor tissues expressed spindle pole body component 25 (SPC25), one of the four subunits of the NDC80 complex, at greater levels compared to surrounding normal tissues. According to earlier researches, this subunit strongly encouraged tumor cell proliferation and tumor growth, which resulted in worse prognoses in patients with hepatocellular, breast, lung, and prostate cancer. Precisely because SPC25's role in uterine corpus endometrial carcinoma (UCEC) is understudied, we chose to concentrate on UCEC for gaining a more scientific and thorough understanding of SPC25. Along with examining SPC25's differential expression, prognostic significance, and biological function in UCEC, our research sought to clarify the underlying mechanism by which SPC25 influences the course of UCEC and patient prognosis from the viewpoints of methylation and immune infiltration. We observed differential expression of SPC25 gene in different clinicopathological features of UCEC and identified SPC25 as a hazard factor for poorer overall survival (OS), disease-specific survival (DSS), and progress free interval (PFI) in UCEC, particularly in its multiple clinical subtypes. In addition, we also discovered that SPC25 and its co-expressed genes mostly engaged in biological processes and signal transduction routes linked to cell cycle and cell division in UCEC. After investigating SPC25's methylation status, we discovered that patients with UCEC had elevated SPC25 expression and a poor prognosis due to hypomethylation of CpG sites in the SPC25 gene sequence. Finally, we investigated SPC25's potential role in immunotherapy and discovered that SPC25 might alter the major immune cell infiltration levels in the tumor microenvironment (TME) by regulating the expression of immunoregulatory molecules and chemokines, which would be beneficial for SPC25 to control the progression of UCEC. In conclusion, SPC25 was a useful predictive biomarker as well as a possible therapeutic target for UCEC.

Genome-wide identification, evolution, and expression analysis of the NAC gene family in chestnut (Castanea mollissima)

The NAC gene family is one of the most important transcription factor families specific to plants, responsible for regulating many biological processes, including development, stress response, and signal transduction. However, it has not yet been characterized in chestnut, an important nut tree species. Here, we identified 115 CmNAC genes in the chestnut genome, which were divided into 16 subgroups based on the phylogenetic analysis. Numerous cis-acting elements related to auxin, gibberellin, and abscisic acid were identified in the promoter region of CmNACs, suggesting that they play an important role in the growth and development of chestnut. The results of the collinear analysis indicated that dispersed duplication and whole-genome-duplication were the main drivers of CmNAC gene expansion. RNA-seq data of developmental stages of chestnut nut, bud, and ovule revealed the expression patterns of CmNAC genes. Additionally, qRT-PCR experiments were used to verify the expression levels of some CmNAC genes. The comprehensive analysis of the above results revealed that some CmNAC members may be related to chestnut bud and nut development, as well as ovule fertility. The systematic analysis of this study will help to increase understanding of the potential functions of the CmNAC genes in chestnut growth and development.

Rapid, potent, and persistent covalent chemical probes to deconvolute PI3Kα signaling.

Chemical probes have gained importance in the elucidation of signal transduction in biology. Insufficient selectivity and potency, lack of cellular activity and inappropriate use of chemical probes has major consequences on interpretation of biological results. The catalytic subunit of phosphoinositide 3-kinase α (PI3Kα) is one of the most frequently mutated genes in cancer, but fast-acting, high-quality probes to define PI3Kα's specific function to clearly separate it from other class I PI3K isoforms, are not available. Here, we present a series of novel covalent PI3Kα-targeting probes with optimized intracellular target access and kinetic parameters. On-target TR-FRET and off-target assays provided relevant kinetic parameters (k chem, k inact and K i) to validate our chemical probes. Additional intracellular nanoBRET tracer displacement measurements showed rapid diffusion across the cell membrane and extremely fast target engagement, while investigations of signaling downstream of PI3Kα via protein kinase B (PKB/Akt) and forkhead box O (FOXO) revealed blunted pathway activity in cancer cell lines with constitutively activated PI3Kα lasting for several days. In contrast, persistent PI3Kα inhibition was rapidly bypassed by other class I PI3K isoforms in cells lacking functional phosphatase and tensin homolog (PTEN). Comparing the rapidly-diffusing, fast target-engaging chemical probe 9 to clinical reversible PI3Kα-selective inhibitors alpelisib, inavolisib and 9r, a reversible analogue of 9, revealed 9's superior potency to inhibit growth (up to 600-fold) associated with sustained suppression of PI3Kα signaling in breast cancer cell lines. Finally, using a simple washout protocol, the utility of the highly-selective covalent PI3Kα probe 9 was demonstrated by the quantification of the coupling of insulin, EGF and CXCL12 receptors to distinct PI3K isoforms for signal transduction in response to ligand-dependent activation. Collectively, these findings along with the novel covalent chemical probes against PI3Kα provide insights into isoform-specific functions in cancer cells and highlight opportunities to achieve improved selectivity and long-lasting efficacy.

Harnessing glycofluoroforms for impedimetric biosensing.

Glycans play a major role in biological cell-cell recognition and signal transduction but have found limited application in biosensors due to glycan/lectin promiscuity; multiple proteins are capable of binding to the same native glycan. Here, site-specific fluorination is used to introduce protein-glycan selectivity, and this is coupled with an electrochemical detection method to generate a novel biosensor platform. 3F-lacto-N-biose glycofluoroform is installed onto polymer tethers, which are subsequently immobilised onto gold screen printed electrodes, providing a non-fouling surface. The impedance biosensing platform is shown to selectively bind cancer-associated galectin-3 compared to control glycans and proteins. To improve the analytical capability, Bayesian statistical analysis was deployed in the equivalent circuit fitting of electrochemical impedance spectroscopy data. It is shown that Markov Chain Monte Carlo (MCMC) analysis is a helpful method for visualising experimental irreproducibility, and we apply this as a quality control step.

ALTERED GENE EXPRESSION PROFILE OF AGING BONE MARROW MESENCHYMAL STEM CELLS

Abstract Aging is a complex process that affects many physiological systems, including bone metabolism. To gain insight into the molecular mechanisms underlying age-related bone loss, we conducted RNA-seq analysis of mesenchymal stem cells (MSCs) isolated from the bone marrow of 6-month and 24-month-old C57Bl/6 mice. We identified 5857 differentially expressed genes, out of 19,324 genes, with an absolute fold change greater than 1.4 and FDR q-value less than 0.05. These genes are involved in a variety of biological processes, including metabolism, immune response, and signal transduction. KEGG pathway enrichment analysis revealed 28 significantly enriched pathways, suggesting that multiple pathways contribute to age-related bone loss. Our findings provide a foundation for future studies aimed at elucidating the molecular mechanisms underlying age-related bone loss and identifying potential therapeutic targets for the prevention and treatment of osteoporosis.

Sphingolipid metabolism in brain insulin resistance and neurological diseases.

Sphingolipids, as members of the large lipid family, are important components of plasma membrane. Sphingolipids participate in biological signal transduction to regulate various important physiological processes such as cell growth, apoptosis, senescence, and differentiation. Numerous studies have demonstrated that sphingolipids are strongly associated with glucose metabolism and insulin resistance. Insulin resistance, including peripheral insulin resistance and brain insulin resistance, is closely related to the occurrence and development of many metabolic diseases. In addition to metabolic diseases, like type 2 diabetes, brain insulin resistance is also involved in the progression of neurodegenerative diseases including Alzheimer's disease and Parkinson's disease. However, the specific mechanism of sphingolipids in brain insulin resistance has not been systematically summarized. This article reviews the involvement of sphingolipids in brain insulin resistance, highlighting the role and molecular biological mechanism of sphingolipid metabolism in cognitive dysfunctions and neuropathological abnormalities of the brain.

Melatonin retards leaf senescence by modulating phytohormones metabolism in stored Chinese flowering cabbage

Abstract This paper was conducted to explore the effects of melatonin (MT) on the senescence of stored Chinese flowering cabbage and the potential modulatory mechanisms involved. The physiological findings demonstrated that MT successfully reduced chlorophyll loss and improved the photochemical effectiveness of cabbage leaves. In addition, MT decreased the transcription of senescence-associated genes (BrSAG12) and genes responsible for chlorophyll breakdown. Transcriptome analysis showed that MT-regulated genes were enriched in oxidative phosphorylation, hormone metabolism and signal transduction, and MT treatment reduced the high expression of genes linked to reactive oxygen species generation, energy metabolism, phytohormone (abscisic acid (ABA), ethylene (ET) and Jasmonic acid (JA)) biological synthesis and signal transduction, whilst promoting the activation of genes related to ROS scavenging, energy biosynthesis and plant-pathogen interactions. We emphasized the examination of the potential interaction between phytohormones metabolism and MT. Results showed that the application of MT decreased ABA, ET and JA levels as well as the expression of their biosynthesis genes, concurrently maintaining higher expression of cytokinin (CTK), auxin (IAA) and gibberellin (GA) biosynthetic genes and lower expression of degradation genes. Regulatory networks of transcription factors (TFs) and genes related to ABA, ET and JA metabolism showed that TFs such as DNA-binding One Zinc Finger 5.7 (DOF5.7), WRKY40 and homeobox-leucine zipper protein-16 (ATHB-16) might play important transcriptional regulatory roles in mediating MT postponed leaf senescence. Taken together, these findings suggested that the postponed senescence of cabbage treated with MT might be ascribed to the regulated oxidative phosphorylation, energy, phytohormone metabolism and transcription factors.

Tailored modulation of S100A1 and RASSF8 expression by butanediamide augments healing of rotator cuff tears.

This investigation sought to elucidate promising treatment modalities for rotator cuff tears (RCTs) by delving into the molecular machinations instigating the affliction. The focus was on differentially expressed genes (DEGs) linked to RCTs, and the exploration of their roles and operative pathways. DEGs were discerned from GEO datasets, followed by the establishment of a protein-protein interaction (PPI) network. Subsequently, the network's core genes were determined employing a Venn diagram. Enrichment analysis facilitated the unveiling of the biological roles and signal transduction pathways of these pivotal genes, thus shedding light on molecular strategies for RCT-targeted treatment. The Discovery Studio 2019 software was employed to sift through FDA-sanctioned drugs targeting these essential proteins. Moreover, the efficaciousness of these FDA-endorsed drugs vis-à-vis RCTs was corroborated by the construction of an in vivo animal model of the injury and the in vitro cultivation of tendon-derived stem cells. Bioinformatics outcomes revealed a significant overexpression of S100A1 and RASSF8 in RCT patients. The FDA drug repository indicated that Butanediamide has a selective affinity for S100A1 and RASSF8. Subsequent in vivo and in vitro experimentation demonstrated that Butanediamide could suppress S100A1 expression and bolster TDSC proliferation, thereby facilitating RCT healing. S100A1 and RASSF8 are pivotal genes implicated in RCTs, and their roles have been elucidated. The FDA-approved compound, Butanediamide, may represent a prospective therapeutic agent for RCTs by targeting S100A1 and RASSF8, respectively.

An update on the role of thioredoxin-interacting protein in diabetic kidney disease: A mini review.

Thioredoxin-interacting protein (TXNIP) was first isolated from Vitamin D3-exposed HL60 cells. TXNIP is the main redox-regulating factor in various organs and tissues. We begin with an overview of the TXNIP gene and protein information, followed by a summary of studies that have shown its expression in human kidneys. Then, we highlight our current understanding of the effect of TXNIP on diabetic kidney disease (DKD) to improve our understanding of the biological roles and signal transduction of TXNIP in DKD. Based on the recent review, the modulation of TXNIP may be considered as a new target in the management of DKD.