TP-LMMSG: a peptide prediction graph neural network incorporating flexible amino acid property representation.

Bioactive peptide therapeutics has been a long-standing research topic. Notably, the antimicrobial peptides (AMPs) have been extensively studied for its therapeutic potential. Meanwhile, the demand for annotating other therapeutic peptides, such as antiviral peptides (AVPs) and anticancer peptides (ACPs), also witnessed an increase in recent years. However, we conceive that the structure of peptide chains and the intrinsic information between the amino acids is not fully investigated among the existing protocols. Therefore, we develop a new graph deep learning model, namely TP-LMMSG, which offers lightweight and easy-to-deploy advantages while improving the annotation performance in a generalizable manner. The results indicate that our model can accurately predict the properties of different peptides. The model surpasses the other state-of-the-art models on AMP, AVP and ACP prediction across multiple experimental validated datasets. Moreover, TP-LMMSG also addresses the challenges of time-consuming pre-processing in graph neural network frameworks. With its flexibility in integrating heterogeneous peptide features, our model can provide substantial impacts on the screening and discovery of therapeutic peptides. The source code is available at https://github.com/NanjunChen37/TP_LMMSG.

TransPTM: a transformer-based model for non-histone acetylation site prediction.

Protein acetylation is one of the extensively studied post-translational modifications (PTMs) due to its significant roles across a myriad of biological processes. Although many computational tools for acetylation site identification have been developed, there is a lack of benchmark dataset and bespoke predictors for non-histone acetylation site prediction. To address these problems, we have contributed to both dataset creation and predictor benchmark in this study. First, we construct a non-histone acetylation site benchmark dataset, namely NHAC, which includes 11 subsets according to the sequence length ranging from 11 to 61 amino acids. There are totally 886 positive samples and 4707 negative samples for each sequence length. Secondly, we propose TransPTM, a transformer-based neural network model for non-histone acetylation site predication. During the data representation phase, per-residue contextualized embeddings are extracted using ProtT5 (an existing pre-trained protein language model). This is followed by the implementation of a graph neural network framework, which consists of three TransformerConv layers for feature extraction and a multilayer perceptron module for classification. The benchmark results reflect that TransPTM has the competitive performance for non-histone acetylation site prediction over three state-of-the-art tools. It improves our comprehension on the PTM mechanism and provides a theoretical basis for developing drug targets for diseases. Moreover, the created PTM datasets fills the gap in non-histone acetylation site datasets and is beneficial to the related communities. The related source code and data utilized by TransPTM are accessible at https://www.github.com/TransPTM/TransPTM.

Deep transfer learning for clinical decision-making based on high-throughput data: comprehensive survey with benchmark results.

The rapid growth of omics-based data has revolutionized biomedical research and precision medicine, allowing machine learning models to be developed for cutting-edge performance. However, despite the wealth of high-throughput data available, the performance of these models is hindered by the lack of sufficient training data, particularly in clinical research (in vivo experiments). As a result, translating this knowledge into clinical practice, such as predicting drug responses, remains a challenging task. Transfer learning is a promising tool that bridges the gap between data domains by transferring knowledge from the source to the target domain. Researchers have proposed transfer learning to predict clinical outcomes by leveraging pre-clinical data (mouse, zebrafish), highlighting its vast potential. In this work, we present a comprehensive literature review of deep transfer learning methods for health informatics and clinical decision-making, focusing on high-throughput molecular data. Previous reviews mostly covered image-based transfer learning works, while we present a more detailed analysis of transfer learning papers. Furthermore, we evaluated original studies based on different evaluation settings across cross-validations, data splits and model architectures. The result shows that those transfer learning methods have great potential; high-throughput sequencing data and state-of-the-art deep learning models lead to significant insights and conclusions. Additionally, we explored various datasets in transfer learning papers with statistics and visualization.

Uncovering the ceRNA Network Related to the Prognosis of Stomach Adenocarcinoma Among 898 Patient Samples.

Stomach adenocarcinoma (STAD) patients are often associated with significantly high mortality rates and poor prognoses worldwide. Among STAD patients, competing endogenous RNAs (ceRNAs) play key roles in regulating one another at the post-transcriptional stage by competing for shared miRNAs. In this study, we aimed to elucidate the roles of lncRNAs in the ceRNA network of STAD, uncovering the molecular biomarkers for target therapy and prognosis. Specifically, a multitude of differentially expressed lncRNAs, miRNAs, and mRNAs (i.e., 898 samples in total) was collected and processed from TCGA. Cytoplasmic lncRNAs were kept for evaluating overall survival (OS) time and constructing the ceRNA network. Differentially expressed mRNAs in the ceRNA network were also investigated for functional and pathological insights. Interestingly, we identified one ceRNA network including 13 lncRNAs, 25 miRNAs, and 9 mRNAs. Among them, 13 RNAs were found related to the patient survival time; their individual risk score can be adopted for prognosis inference. Finally, we constructed a comprehensive ceRNA regulatory network for STAD and developed our own risk-scoring system that can predict the OS time of STAD patients by taking into account the above.

scWMC: weighted matrix completion-based imputation of scRNA-seq data via prior subspace information.

MOTIVATION: Single-cell RNA sequencing (scRNA-seq) can provide insight into gene expression patterns at the resolution of individual cells, which offers new opportunities to study the behavior of different cell types. However, it is often plagued by dropout events, a phenomenon where the expression value of a gene tends to be measured as zero in the expression matrix due to various technical defects. RESULTS: In this article, we argue that borrowing gene and cell information across column and row subspaces directly results in suboptimal solutions due to the noise contamination in imputing dropout values. Thus, to impute more precisely the dropout events in scRNA-seq data, we develop a regularization for leveraging that imperfect prior information to estimate the true underlying prior subspace and then embed it in a typical low-rank matrix completion-based framework, named scWMC. To evaluate the performance of the proposed method, we conduct comprehensive experiments on simulated and real scRNA-seq data. Extensive data analysis, including simulated analysis, cell clustering, differential expression analysis, functional genomic analysis, cell trajectory inference and scalability analysis, demonstrate that our method produces improved imputation results compared to competing methods that benefits subsequent downstream analysis. AVAILABILITY AND IMPLEMENTATION: The source code is available at https://github.com/XuYuanchi/scWMC and test data is available at https://doi.org/10.5281/zenodo.6832477. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Iron Diboride (FeB2) for the Electroreduction of NO to NH3.

We report iron diboride (FeB2) as a high-performance metal diboride catalyst for electrochemical NO-to-NH3 reduction (NORR), which shows a maximum NH3 yield rate of 289.3 µmol h-1 cm-2 and a NH3-Faradaic efficiency of 93.8% at -0.4 V versus reversible hydrogen electrode. Theoretical computations reveal that Fe and B sites synergetically activate the NO molecule, while the protonation of NO is energetically more favorable on B sites. Meanwhile, both Fe and B sites preferentially absorb NO over H atoms to suppress the competing hydrogen evolution.

Predicting Atmospheric Particle Phase State Using an Explainable Machine Learning Approach Based on Particle Rebound Measurements.

The particle phase state plays a vital role in the gas-particle partitioning, multiphase reactions, ice nucleation activity, and particle growth in the atmosphere. However, the characterization of the atmospheric phase state remains challenging. Herein, based on measured aerosol chemical composition and ambient relative humidity (RH), a machine learning (ML) model with high accuracy (R2 = 0.952) and robustness (RMSE = 0.078) was developed to predict the particle rebound fraction, f, which is an indicator of the particle phase state. Using this ML model, the f of particles in the urban atmosphere was predicted based on seasonal average aerosol chemical composition and RH. Regardless of seasons, aerosols remain in the liquid state of mid-high latitude cities in the northern hemisphere and in the semisolid state over semiarid regions. In the East Asian megacities, the particles remain in the liquid state in spring and summer and in the semisolid state in other seasons. The effects of nitrate, which is becoming dominant in fine particles in several urban areas, on the particle phase state were evaluated. More nitrate led the particles to remain in the liquid state at an even lower RH. This study proposed a new approach to predict the particle phase state in the atmosphere based on RH and aerosol chemical composition.

Enhancing Chain Initiation Efficiency in the Cationic Allyl-Nickel Catalyzed (Co)Polymerization of Ethylene and Methyl Acrylate.

Improving the efficiency of chain initiation is highly important and also highly challenging in the development of olefin polymerization catalysts. A series of 2-methylallyl-based nickel complexes supported by aryl-N-bridged diphosphazane monoxide (PNPO) ligands containing different electronic and steric substituents were prepared and characterized. These nickel complexes are highly active single-component catalysts for ethylene polymerization and copolymerization with methyl acrylate (MA). 2-Methylallyl substituent on the µ-allyl catalysts led to an increase in the efficiency of chain initiation compared with the corresponding allyl-based analogues, improving the catalytic performances with high activity (up to 4.02 × 106 g PE (mol Ni)-1 h-1). Linear polyethylenes with high molecular weight, narrow PDI values, and high melting temperatures were generated. Most importantly, these 2-methylallyl nickel catalysts can promote ethylene-MA copolymerization to afford functionalized polyethylenes with MA incorporation of up to 7.0 mol %. The current work demonstrates that the change of initiating units can lead to enhancement in catalyst performances. This provides an alternative, simple, and potentially general strategy to improve the properties of different catalyst systems.

Long-Term Respiratory and Neurological Sequelae of COVID-19.

Since the initial reports of coronavirus disease 2019 (COVID-19) in China in late 2019, infections from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have spread rapidly, resulting in a global pandemic that has caused millions of deaths. Initially, the large number of infected people required the direction of global healthcare resources to provide supportive care for the acutely ill population in an attempt to reduce mortality. While clinical trials for safe and effective antiviral agents are ongoing, and vaccine development programs are being accelerated, long-term sequelae of SARS-CoV-2 infection have become increasingly recognized and concerning. Although the upper and lower respiratory tracts are the main sites of entry of SARS-CoV-2 into the body, resulting in COVID-19 pneumonia as the most common presentation, acute lung damage may be followed by pulmonary fibrosis and chronic impairment of lung function, with impaired quality of life. Also, increasing reports have shown that SARS-CoV-2 infection involves the central nervous system (CNS) and the peripheral nervous system (PNS) and directly or indirectly damages neurons, leading to long-term neurological sequelae. This review aims to provide an update on the mechanisms involved in the development of the long-term sequelae of SARS-CoV-2 infection in the 3 main areas of lung injury, neuronal injury, and neurodegenerative diseases, including Alzheimer disease, Parkinson disease, and multiple sclerosis, and highlights the need for patient monitoring following the acute stage of infection with SARS-CoV-2 to provide a rationale for the prevention, diagnosis, and management of these potential long-term sequelae.

An Evidence Based Perspective on mRNA-SARS-CoV-2 Vaccine Development.

The first outbreak of coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) occurred in Wuhan, Hubei Province, China, in late 2019. The subsequent COVID-19 pandemic rapidly affected the health and economy of the world. The global approach to the pandemic was to isolate populations to reduce the spread of this deadly virus while vaccines began to be developed. In March 2020, the first phase I clinical trial of a novel lipid nanoparticle (LNP)-encapsulated mRNA-based vaccine, mRNA-1273, which encodes the spike protein (S protein) of SARS-CoV-2, began in the United States (US). The production of mRNA-based vaccines is a promising recent development in the production of vaccines. However, there remain significant challenges in the development and testing of vaccines as rapidly as possible to control COVID-19, which requires international collaboration. This review aims to describe the background to the rationale for the development of mRNA-based SARS-CoV-2 vaccines and the current status of the mRNA-1273 vaccine.

The etiological contribution of GABAergic plasticity to the pathogenesis of neuropathic pain.

Neuropathic pain developing after peripheral or central nerve injury is the result of pathological changes generated through complex mechanisms. Disruption in the homeostasis of excitatory and inhibitory neurons within the central nervous system is a crucial factor in the formation of hyperalgesia or allodynia occurring with neuropathic pain. The central GABAergic pathway has received attention for its extensive distribution and function in neural circuits, including the generation and development of neuropathic pain. GABAergic inhibitory changes that occur in the interneurons along descending modulatory and nociceptive pathways in the central nervous system are believed to generate neuronal plasticity, such as synaptic plasticity or functional plasticity of the related genes or proteins, that is the foundation of persistent neuropathic pain. The primary GABAergic plasticity observed in neuropathic pain includes GABAergic synapse homo- and heterosynaptic plasticity, decreased synthesis of GABA, down-expression of glutamic acid decarboxylase and GABA transporter, abnormal expression of NKCC1 or KCC2, and disturbed function of GABA receptors. In this review, we describe possible mechanisms associated with GABAergic plasticity, such as central sensitization and GABAergic interneuron apoptosis, and the epigenetic etiologies of GABAergic plasticity in neuropathic pain. Moreover, we summarize potential therapeutic targets of GABAergic plasticity that may allow for successful relief of hyperalgesia from nerve injury. Finally, we compare the effects of the GABAergic system in neuropathic pain to other types of chronic pain to understand the contribution of GABAergic plasticity to neuropathic pain.

The etiological changes of acetylation in peripheral nerve injury-induced neuropathic hypersensitivity.

Neuropathic pain is a common chronic pain condition with mechanisms far clearly been elucidated. Mounting preclinical and clinical studies have shown neuropathic pain is highly associated with histone acetylation modification, which follows expression regulation of various pain-related molecules such as mGluR1/5, glutamate aspartate transporter, glutamate transporter-1, GAD65, Nav1.8, Kv4.3, µ-opioid receptor, brain-derived neurotrophic factor, and certain chemokines. As two types of pivotal enzymes involved in histone acetylation, histone deacetylases induce histone deacetylation to silence gene expression; in contrast, histone acetyl transferases facilitate histone acetylation to potentiate gene transcription. Accordingly, upregulation or blockade of acetylation may be a promising intervention direction for neuropathic pain treatment. In fact, numerous animal studies have suggested various histone deacetylase inhibitors, Sirt (class III histone deacetylases) activators, and histone acetyl transferases inhibitors are effective in neuropathic pain treatment via targeting specific epigenetic sites. In this review, we summarize the characteristics of the molecules and mechanisms of neuropathy-related acetylation, as well as the acetylation upregulation and blockade for neuropathic pain therapy. Finally, we will discuss the current drug advances focusing on neuropathy-related acetylation along with the underlying treatment mechanisms.

DNA MemoChip: Long-Term and High Capacity Information Storage and Select Retrieval.

Over the course of history, human beings have never stopped seeking effective methods for information storage. From rocks to paper, and through the past several decades of using computer disks, USB sticks, and on to the thin silicon "chips" and "cloud" storage of today, it would seem that we have reached an era of efficiency for managing innumerable and ever-expanding data. Astonishingly, when tracing this technological path, one realizes that our ancient methods of informational storage far outlast paper (10,000 vs. 1,000 years, respectively), let alone the computer-based memory devices that only last, on average, 5 to 25 years. During this time of fast-paced information generation, it becomes increasingly difficult for current storage methods to retain such massive amounts of data, and to maintain appropriate speeds with which to retrieve it, especially when in demand by a large number of users. Others have proposed that DNA-based information storage provides a way forward for information retention as a result of its temporal stability. It is now evident that DNA represents a potentially economical and sustainable mechanism for storing information, as demonstrated by its decoding from a 700,000 year-old horse genome. The fact that the human genome is present in a cell, containing also the varied mitochondrial genome, indicates DNA's great potential for large data storage in a 'smaller' space.

Threshold Effect of G9a/Glp on Peripheral Nerve Injury Induced Hypersensitivity.

Background: Previous studies disclosed the pivotal role of methyltransferase complex G9a/Glp in the pathogenesis of neuropathic hypersensitivity induced by peripheral nerve injury. We observed that higher dose of G9a inhibitor improved nociceptive behavior, but the lower dose worsened pain. The aim of this study is to extensively observe the differential effect of various dosages of G9a/Glp inhibitors on nerve injury-induced allodynia. Materials and methods: After approval by the institutional ethical committee on pain research in conscious animals, C57BL/6 mice were used for measuring nociceptive behavior evoked with von Frey filaments after spared nerve injury. G9a/Glp inhibitor BIX01294 or UNC0638 was injected through the pre-buried intrathecal catheter. The dose­response curves of behavioral changes were depicted when inhibitors were administered once in bolus at the 14th day post spared nerve injury. Withdrawal behaviors were compared during the 49 days' observation window after spared nerve injury with various dosages of inhibitors injected intrathecally for 14 days. Results: Dose­behavior curves of a single bolus of both BIX01294 and UNC0638 displayed a "V"-shaped responses of allodynia withdrawal from lower through higher dose when measured at the 14th day post spared nerve injury. A threshold dose of 10.0 µg for BIX01294 and 80.0 µg for UNC0638 significantly worsened allodynia. However, daily bolus intrathecal injection for 14 days of both inhibitors lower or higher than these threshold doses prominently improved nociceptive behavior, producing contrasting results. On the same animal, threshold dose followed by a lower or higher dose with a 14 days' interval also showed contrast effect on nociceptive behavior, and a lower or higher dose to threshold dose sequence of inhibitor administration was vice versa. Conclusions: Methyltransferase complex G9a/Glp has a threshold role in mediating peripheral nerve injury-induced hypersensitivity at its low level versus high level through inhibiting and facilitating the nociceptive behavior, respectively.

Mitochondrial Heteroplasmy.

Genetic polymorphisms, in concert with well-characterized etiology and progression of major pathologies, plays a significant role in aberrant processes afflicting human populations. Mitochondrial heteroplasmy represents a dynamically determined co-expression of inherited polymorphisms and somatic pathology in varying ratios within individual mitochondrial DNA (mtDNA) genomes with repetitive patterns of tissue specificity. The ratios of the MtDNA genomes represent a balance between healthy and pathological cellular outcomes. Mechanistically, cardiomyopathies have profound alterations of normative mitochondrial function. Certain allele imbalances in the nuclear mitochondrial genome are associated with key energy mitochondrial proteins. Mitochondrial heteroplasmy may manifest itself at critical protein expression points, e.g., cytochrome c oxidase (COX). Pathological mtDNA mutations also are associated with the development of congestive heart failure. Interestingly, mitochondrial 'normal vs. abnormal' ratios of various heteroplasmic populations may occur in families. In the translational context of human health and disease, we discuss the need for determining critical foci to probe multiple biological roles of mitochondrial heteroplasmy in cardiomyopathy.

Dopaminergic inhibition by G9a/Glp complex on tyrosine hydroxylase in nerve injury-induced hypersensitivity.

The neural balance between facilitation and inhibition determines the final tendency of central sensitization. Nerve injury-induced hypersensitivity was considered as the results from the enhanced ascending facilitation and the diminished descending inhibition. The role of dopaminergic transmission in the descending inhibition has been well documented, but its underlying molecular mechanisms are unclear. Previous studies demonstrated that the lysine dimethyltransferase G9a/G9a-like protein (Glp) complex plays a critical role in cocaine-induced central plasticity, and given cocaine's role in the nerve system is relied on its function on dopamine system, we herein proposed that the reduced inhibition of dopaminergic transmission was from the downregulation of tyrosine hydroxylase expression by G9a/Glp complex through methylating its gene Th After approval by the Animal Care and Use Committee, C57BL/6 mice were used for pain behavior using von Frey after spared nerve injury, and Th CpG islands methylation was measured using bisulfite sequencing at different nerve areas. The inhibitor of G9a/Glp, BIX 01294, was administered intraventricularly daily with bolus injection. The protein levels of G9a, Glp, and tyrosine hydroxylase were measured with immunoblotting. Dopamine levels were detected using high-performance liquid chromatography. The expression of G9a but not Glp was upregulated in ventral tegmental area at post-injury day 4 till day 49 (the last day of the behavioral test). Correspondingly, the Th CpG methylation is increased, but the tyrosine hydroxylase expression was downregulated and the dopamine level was decreased. After the intracerebroventriclar injection of BIX 01294 since the post-injury days 7 and 14 for consecutive three days, three weeks, and six weeks, the expression of tyrosine hydroxylase was upregulated with a significant decrease in Th methylation and increase in dopamine level. Moreover, the pain after G9a/Glp inhibitor was attenuated significantly. In sum, methytransferase G9a/Glp complex partially controls dopaminergic transmission by methylating Th in peripheral nerve injury-induced neuropathic pain.

Precision Chain-Walking Polymerization of trans-4-Octene Catalyzed by α-Diimine Nickel(II) Catalysts Bearing ortho-sec-Phenethyl Groups.

α-Diimine nickel complexes bearing bulky ortho-sec-phenethyl groups (bis{[N,N'-(4-methyl-2,6-di-sec-phenethylphenyl)imino]-1,2-dimethylethane}dibromonickel (1), bis{[N,N'-(4,6-dimethyl-2-sec-phenethylphenyl)imino]-1,2-dimethylethane}dibromonickel (2), bis{[N,N'-(4-methyl-2-sec-phenethylphenyl)imino]-1,2-dimethylethane}dibromonickel (3)) and {bis[N,N'-(2,4,6-trimethylphenyl)imino]-1,2-dimethylethane}dibromidonickel (4) are used as a precatalyst for the polymerization of trans-4-octene upon activation with modified methylaluminoxane. These catalysts conduct chain-walking polymerization of trans-4-octene to give polymers possessing propyl and butyl branches with high molecular weight and narrow molecular weight distribution. The branching structure depends on the nickel complex as well as the polymerization temperature, and the ratio of propyl branch was increased with increasing the bulkiness of the ligand and decreasing the polymerization temperature. Consequently, the most bulky 1 among the complexes used is found to polymerize trans-4-octene with high 1,5-regioselectivity at -20 °C to give poly(1-propylpentan-1,5-diyl).

Glycine bidirectionally regulates ischemic tolerance via different mechanisms including NR2A-dependent CREB phosphorylation.

The exact effect of glycine pre-treatment on brain ischemic tolerance (IT) remains quite controversial. The objective of this study was to investigate the potential effects of glycine on IT. We used rat models of both in vitro ischemia (oxygen and glucose deprivation) and in vivo ischemia (transient middle cerebral artery occlusion). Low doses of glycine (L-Gly) significantly decreased hippocampal ischemic LTP (i-LTP), infarct volume, and neurological deficit scores which were administered before ischemia was induced in rats, whereas high doses of glycine exerted deteriorative effects under the same condition. These findings suggested that exogenous glycine may induce IT in a dose-dependent manner. Furthermore, L-Gly-dependent neuronal protection was inversed by L689, a selective NMDAR glycine site antagonist both in vitro (abolished i-LTP depression) and in vivo (increased infarct size reduction), but not glycine receptor (GlyR) inhibitor strychnine. Importantly, L-Gly-induced IT was achieved by NR2A-dependent cAMP-response element binding protein phosphorylation. These data imply that glycine pre-treatment may represent a novel strategy for inducing IT based on synaptic NMDAR-dependent neuronal transmission. A model of glycine induced dose-dependent bidirectional regulations in ischemic tolerance. (a) Under low dose of Gly pre-treatment, glycine induces NMDAR potentiation and CREB-dependent neuroprotection through the NMDAR co-agonist binding site. (b) Under high dose of Gly pre-treatment, the excessive glycine in synaptic cleft can activate neighboring extrasynaptic sites and combine to the GlyRs. Then, the deteriorative effects would be triggered after NMDAR endocytosis and synaptic depression. AMPAR, α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor; CREB, cAMP response element-binding protein; Gly, glycine; GlyR, glycine receptor; GlyT1, gycine transportor 1; NMDAR, N-methyl-d-aspartate receptor.

Epigenetic modification of DRG neuronal gene expression subsequent to nerve injury: etiological contribution to complex regional pain syndromes (Part I).

DRG is of importance in relaying painful stimulation to the higher pain centers and therefore could be a crucial target for early intervention aimed at suppressing primary afferent stimulation. Complex regional pain syndrome (CRPS) is a common pain condition with an unknown etiology. Recently added new information enriches our understanding of CRPS pathophysiology. Researches on genetics, biogenic amines, neurotransmitters, and mechanisms of pain modulation, central sensitization, and autonomic functions in CRPS revealed various abnormalities indicating that multiple factors and mechanisms are involved in the pathogenesis of CRPS. Epigenetics refers to mitotically and meiotically heritable changes in gene expression that do not affect the DNA sequence. As epigenetic modifications potentially play an important role in inflammatory cytokine metabolism, neurotransmitter responsiveness, and analgesic sensitivity, they are likely key factors in the development of chronic pain. In this dyad review series, we systematically examine the nerve injury-related changes in the neurological system and their contribution to CRPS. In this part, we first reviewed and summarized the role of neural sensitization in DRG neurons in performing function in the context of pain processing. Particular emphasis is placed on the cellular and molecular changes after nerve injury as well as different models of inflammatory and neuropathic pain. These were considered as the potential molecular bases that underlie nerve injury-associated pathogenesis of CRPS.

Epigenetic modification of DRG neuronal gene expression subsequent to nerve injury: etiological contribution to complex regional pain syndromes (Part II).

Cumulating evidence indicated that nerve injury-associated cellular and molecular changes play an essential role in contributing to the development of pathological pain, and more recent findings implicated the critical role of epigenetic mechanisms in pain-related sensitization in the DRG subsequent to nerve injury. In this part of the dyad review (Part II), we reviewed and paid special attention on the etiological contribution of DGR gene expression modulated by epigenetic mechanisms of CRPS. As essential effectors to different molecular activation, we first discussed the activation of various signaling pathways that subsequently from nerve injury, and in further illustrated the fundamental and functional underpinnings of nerve injury-induced pain, in which we argued for the potential epigenetic mechanisms in response to sensitizing stimuli or injury. Therefore, understanding the specific mediating factors that influence individual epigenetic differences contributing to pain sensitivity and responsiveness to analgesics possesses crucial clinical implications.