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Ulcerative colitis (UC) is a chronic, nonspecific inflammatory disorder characterized by symptoms such as abdominal pain, diarrhea, hematochezia, and urgency during defecation. While the primary site of involvement is the colon, UC can extend to encompass the entire rectum and colon. The causes and development mechanisms of UC are still not well understood; nonetheless, it is currently held that factors including environmental influences, genetic predispositions, intestinal mucosal integrity, gut microbiota composition, and immune dysregulation contribute to its development. Dysregulated immune responses are pivotal in the pathophysiology of UC, and these aberrant responses are considered key contributors to the disease onset. In patients with UC, immune cells become hyperactive and erroneously target normal intestinal tissue, resulting in inflammatory cascades and damage to the intestinal mucosa. The therapeutic strategies currently employed for UC include immunosuppressive agents such as aminosalicylates and corticosteroids. However, these treatments often prove costly and carry significant adverse effects — imposing a considerable burden on patients. Traditional Chinese Medicine (TCM) has attracted worldwide attention because of its multi-target approach, minimal side effects, cost-effectiveness, and favorable efficacy profiles. In this review, the ways in which TCM modulates inflammatory responses in the treatment of ulcerative colitis have been outlined. Research into TCM modalities for modulating inflammatory pathways in the treatment of UC, which has yielded promising advancements, including individual herbs, herbal formulations, and their derivatives, has been summarized. TCM has been utilized to treat UC and the immune system plays a key role in regulating intestinal homeostasis. It is imperative to facilitate large-scale evidence-based medical research and promote the clinical application of TCM in the management of UC.

Hepatocellular carcinoma, presenting a significant health challenge, requires innovative approaches for treatment and prevention. Therefore, this study aimed to comprehensively characterize the potential of compounds from Achillea arabica on the mTOR, Akt and ERK signaling pathways using in silico methods. The drug likeness and ADME/T properties of the compounds were investigated using online tools. Molecular docking and molecular dynamics simulations were used to examine the key interactions of the selected compounds with the mTOR, Akt and ERK target proteins along with the known inhibitors. Three phenolic compounds demonstrated a strong binding affinity as the top candidates. Compounds quercetin, luteolin and apigenin exhibit potential as nontoxic alternatives for hepatocellular carcinoma treatment, typically used as synthetic chemical inhibitors.

Acute liver injury (ALI) induced by acetaminophen (APAP) is the main cause of drug-induced liver injury. Previous reports indicated liver failure could be alleviated by saponins (ginsenosides) from Panax ginseng against APAP-induced inflammatory responses in vivo. However, validation towards ginsenoside Rb1 as a major and marker saponin may protect liver from APAP-induced ALI and its mechanisms are poorly elucidated. In this study, the protective effects and the latent mechanisms of Rb1 action against APAP-induced hepatotoxicity were investigated. Rb1 was administered orally with 10mg/kg and 20mg/kg daily for 1 week before a single injection of APAP (250mg/kg, i.p.) 1h after the last treatment of Rb1. Serum alanine/aspartate aminotransferases (ALT/AST), liver glutathione (GSH) depletion, as well as the inflammatory cytokines, such as tumor necrosis factor-$\alpha$ (TNF-$\alpha$), interleukin-1$\beta$ (IL-1$\beta$), inducible nitric oxide synthase (iNOS), and cyclooxygenase-2 (COX-2), were analyzed to indicate the underlying protective effects of Rb1 against APAP-induced hepatotoxicity with significant inflammatory responses. Histological examination further proved Rb1’s protective effects. Importantly, Rb1 mitigated the changes in the phosphorylation of MAPK and PI3K/Akt, as well as its downstream factor NF-$\kappa$B. In conclusion, experimental data clearly demonstrated that Rb1 exhibited a remarkable liver protective effect against APAP-induced ALI, partly through regulating MAPK and PI3K/Akt signaling pathways-mediated inflammatory responses.

Shikonin is one of the primary active components extracted from the dried root ofZicao (Lithospermum erythrorhizon, Onosma paniculata, or Arnebia euchroma), a traditional Chinese herbal medicine. Shikonin is known to not only exert anti-proliferative, anti-inflammatory, and anti-angiogenic activities, but also play a crucial role in triggering the production of reactive oxygen species, suppressing the release of exosomes, and inducing apoptosis. Increasing evidence suggests that shikonin has a protective effect against skin diseases, including psoriasis, melanoma, and hypertrophic scars. In order to evaluate the application potential of shikonin in the treatment of skin diseases, this review is the first of its kind to provide comprehensive and up-to-date information regarding the uses of shikonin and its derivatives on skin diseases and its underlying mechanisms. In this review, we have focused on the signaling pathways and cellular targets involved in the anti-dermatosis effects of shikonin to bridge the gaps in the literature, thereby providing scientific support for the research and development of new drugs from a traditional medicinal plant.

Alzheimer’s disease (AD), the predominant form of dementia, is a neurodegenerative disorder of the central nervous system (CNS) characterized by a subtle onset and a spectrum of cognitive and functional declines. The clinical manifestation of AD encompasses memory deficits, cognitive deterioration, and behavioral disturbances, culminating in a severe impairment of daily living skills. Despite its high prevalence, accounting for 60–70% of all dementia cases, there remains an absence of curative therapeutics. Microglia (MG), the resident immune cells of the CNS, exhibit a bifurcated role in AD pathogenesis. Functioning in a neuroprotective capacity, MGs express scavenger receptors, facilitating the clearance of $\beta$-amyloid protein (A$\beta$) and cellular debris. Conversely, aberrant activation of MGs can lead to the secretion of pro-inflammatory cytokines, thereby propagating neuroinflammatory responses that are detrimental to neuronal integrity. The dynamics of MG activation and the ensuing neuroinflammation are pivotal in the evolution of AD. Chinese medicine (CM), a treasure trove of traditional Chinese cultural practices, has demonstrated significant potential in the therapeutic management of AD. Over the past triennium, CM has garnered considerable research attention for its multifaceted approaches to AD, including the regulation of MG polarization. This review synthesizes current knowledge on the origins, polarization dynamics, and mechanistic interplay of MG with AD pathology. It further explores the nexus between MG polarization and cardinal pathological hallmarks of AD, such as A$\beta$ plaque deposition, hyperphosphorylation of tau, synaptic plasticity impairments, neuroinflammation, and brain–gut-axis dysregulation. The review also encapsulates the therapeutic strategies of CM, which encompass monomers, formulae, and acupuncture. These strategies modulate MG polarization in the context of AD treatment, thereby providing a robust theoretical framework in which to conduct future investigative endeavors in both the clinical and preclinical realms.

Ulcerative colitis (UC), one among other refractory diseases worldwide, has shown an increasing trend of progression to colorectal cancer in recent years. In the treatment of UC, traditional Chinese medicine has demonstrated good efficacy, with a high cure rate, fewer adverse effects, great improvement in the quality of patient survival, and reduction in the tendency of cancerous transformation. It shows promise as a complementary and alternative therapy. This review aims to evaluate and discuss the current research on UC, signaling pathways, and gut microbiota. We also summarized the mechanisms of action of various Chinese medicines (active ingredients or extracts) and herbal formulas, through signaling pathways and gut microbiota, with the expectation that they can provide references and evidence for treating UC and preventing inflammation-associated colorectal cancer by traditional Chinese medicine. We illustrate that multiple signaling pathways, such as TLR4, STAT3, PI3K/Akt, NF-$\kappa$B, and Keap1/Nrf2, can be inhibited by Chinese herbal treatments through the combined regulation of signaling pathways and gut microbiota, which can act individually or synergistically to inhibit intestinal inflammatory cell infiltration, attenuate gut oxidative responses, and repair the intestinal barrier.

Colorectal cancer, characterized by its high incidence, concealed early symptoms, and poor prognosis at advanced stages, ranks as the third leading cause of cancer-related deaths worldwide. Astragalus membranaceus (AM) refers to the dried roots of Astragalus membranaceus (Fisch.) Bge. var. mongholicus (Bge.) Hsiao and Astragalus membranaceus (Fisch.) Bge. In the theory of Traditional Chinese Medicine (TCM), it is believed to have the functions of tonifying qi and lifting yang, as well as generating body fluids and nourishing blood. It can effectively treat cancer caused by the deficiency of vital energy and susceptibility to external diseases. Modern research has confirmed that the active components of AM, including Astragalus polysaccharides, flavonoids (formononetin and calycosin), Astragalus saponins (Astragaloside I and Astragaloside III), and Astragalus nanovesicles, are effective in the treatment of colorectal cancer. The mechanisms mainly involve inducing apoptosis, inhibiting tumor angiogenesis and the metastasis of cancer cells, regulating the cell cycle and tumor microenvironment, and reversing drug resistance. Moreover, it offers a synergistic enhancement when used in combination with chemotherapy, radiotherapy, targeted therapy, or surgical treatment. AM also has great potential in treating colorectal cancer when combined with other herbs. This review summarizes the relevant research findings on the treatment of colorectal cancer with AM, as well as its main pharmacological effects and molecular mechanisms, aiming to provide guidance for the development of new drugs, and offer direction for the conduct of more related research and promoting the development and application of AM.

We prove an averaging principle which asserts convergence of diffusion processes on domains separated by semi-permeable membranes, when diffusion coefficients tend to infinity while the flux through the membranes remains constant. In the limit, points in each domain are lumped into a single state of a limit Markov chain. The limit chain’s intensities are proportional to the membranes’ permeability and inversely proportional to the domains’ sizes. Analytically, the limit is an example of a singular perturbation in which boundary and transmission conditions play a crucial role. This averaging principle is strongly motivated by recent signaling pathways models of mathematical biology, which are discussed toward the end of the paper.

Reconstruction of signaling pathways is crucial for understanding cellular mechanisms. A pathway is represented as a path of a signaling cascade involving a series of proteins to perform a particular function. Since a protein pair involved in signaling and response have a strong interaction, putative pathways can be detected from protein–protein interaction (PPI) networks. However, predicting directed pathways from the undirected genome-wide PPI networks has been challenging. We present a novel computational algorithm to efficiently predict signaling pathways from PPI networks given a starting protein and an ending protein. Our approach integrates topological analysis of PPI networks and semantic analysis of PPIs using Gene Ontology data. An advanced semantic similarity measure is used for weighting each interacting protein pair. Our distance-wise algorithm iteratively selects an adjacent protein from a PPI network to build a pathway based on a distance condition. On each iteration, the strength of a hypothetical path passing through a candidate edge is estimated by a local heuristic. We evaluate the performance by comparing the resultant paths to known signaling pathways on yeast. The results show that our approach has higher accuracy and efficiency than previous methods.

A major goal of personalized anti-cancer therapy is to increase the drug effects while reducing the side effects as much as possible. A novel therapeutic strategy called synthetic lethality (SL) provides a great opportunity to achieve this goal. SL arises if mutations of both genes lead to cell death while mutation of either single gene does not. Hence, the SL partner of a gene mutated only in cancer cells could be a promising drug target, and the identification of SL pairs of genes is of great significance in pharmaceutical industry. In this paper, we propose a hybridized method to predict SL pairs of genes. We combine a data-driven model with knowledge of signalling pathways to simulate the influence of single gene knock-down and double genes knock-down to cell death. A pair of genes is considered as an SL candidate when double knock-down increases the probability of cell death significantly, but single knock-down does not. The single gene knock-down is confirmed according to the human essential genes database. Our validation against literatures shows that the predicted SL candidates agree well with wet-lab experiments. A few novel reliable SL candidates are also predicted by our model.

Signaling pathways are responsible for the regulation of cell processes, such as monitoring the external environment, transmitting information across membranes, and making cell fate decisions. Given the increasing amount of biological data available and the recent discoveries showing that many diseases are related to the disruption of cellular signal transduction cascades, in silico discovery of signaling pathways in cell biology has become an active research topic in past years. However, reconstruction of signaling pathways remains a challenge mainly because of the need for systematic approaches for predicting causal relationships, like edge direction and activation/inhibition among interacting proteins in the signal flow. We propose an approach for predicting signaling pathways that integrates protein interactions, gene expression, phenotypes, and protein complex information. Our method first finds candidate pathways using a directed-edge-based algorithm and then defines a graph model to include causal activation relationships among proteins, in candidate pathways using cell cycle gene expression and phenotypes to infer consistent pathways in yeast. Then, we incorporate protein complex coverage information for deciding on the final predicted signaling pathways. We show that our approach improves the predictive results of the state of the art using different ranking metrics.

A major goal of molecular systems biology is to understand the coordinated function of genes or proteins in response to cellular signals and to understand these dynamics in the context of disease. Signaling pathway databases such as KEGG, NetPath, NCI-PID, and Panther describe the molecular interactions involved in different cellular responses. While the same pathway may be present in different databases, prior work has shown that the particular proteins and interactions differ across database annotations. However, to our knowledge no one has attempted to quantify their structural differences. It is important to characterize artifacts or other biases within pathway databases, which can provide a more informed interpretation for downstream analyses. In this work we consider signaling pathways as graphs and we use topological measures to study their structure. We find that topological characterization using graphlets (small, connected subgraphs) distinguishes signaling pathways from appropriate null models of interaction networks. Next, we quantify topological similarity across pathway databases. Our analysis reveals that the pathways harbor database-specific characteristics implying that even though these databases describe the same pathways, they tend to be systematically different from one another. We show that pathway-specific topology can be uncovered after accounting for database-specific structure. This work presents the first step towards elucidating common pathway structure beyond their specific database annotations.

Data Availability: https://github.com/Reed-CompBio/pathway-reconciliation.

The germ layer of the endoderm can contribute to the formation of both the gastrointestinal and respiratory tracts, and other associated organs. The endoderm is generally responsible for the formation of the internal epithelial tube that will eventually become the digestive tract. During embryogenesis, the endoderm represents the inner germ layer in both triploblastic and diploblastic embryos. The anterior–posterior (A–P) and proximal–distal (P–D) patterning are among the earliest developmental events during embryogenesis. They are tightly regulated with a highly coordinated network of several signaling molecules and pathways. Accumulated data in the last two decades from studies on animal model organisms have enhanced our understanding of the anterior endoderm development and patterning and P–D patterning of the lung. These data have also uncovered many of the molecular mechanisms and signaling molecules that regulate these processes. In this chapter, we will describe this progress with a focus on the anterior endodermal patterning and its regulatory molecular mechanisms and signaling pathways, as well as the P–D patterning of lung embryonic cells. Lastly, we discuss the role of stem and progenitor cells in the P–D patterning of the lung.

New data have recently accumulated on how stem cell behave, self-renew and differentiate. Many studies have also focused on defining stem cells, and determination of the properties, including the mode of cell division and polarity, and regulatory environment(s) of both embryonic and tissue-specific stem cells in the last decades. In the lung, recent data show evidences that lung epithelial stem and progenitor cells are polarized, highly mitotic, have characteristic perpendicular cell divisions, and show a mode of division that is similar to other systems. They further show that the asymmetric division is probably the common mode of division in the mitotically dividing distal epithelial stem and progenitor cells of the embryonic lung. Both symmetric and asymmetric mode of cell divisions are tightly regulated in different stem cell types during tissue development and morphogenesis. How to choose between a symmetric and asymmetric cell division is one of the major questions in the stem cell field. It largely affects tissue development, morphogenesis and disease in different organs since improper asymmetric divisions badly affect organ morphogenesis, whereas uncontrolled symmetric division can lead to tumor formation. Moreover, the proper balance between self-renewal and differentiation of lung epithelial stem and progenitor cells is absolutely required for maintaining normal lung morphogenesis and for lung repair and regeneration since a deficiency of this balance probably can lead to a premature or injured lung. Therefore, identification of lung-specific stem cell types, understanding their behavior, and how they balance their self-renewal and differentiation could lead to the identification of innovative solutions for restoring normal lung morphogenesis and/or regeneration and repair of the lung. Furthermore, understanding the molecular mechanisms that control the asymmetrical cell division and both cell polarity and fate of lung epithelial stem and progenitor cells can help identifying new targets for prevention and rescuing lethal lung diseases in infants and children, and for regeneration of injured lungs. In this chapter, we will discuss recently accumulated data on the lung cell polarity, and the mode of division of lung epithelial stem and progenitor cells. In addition, we will describe the functions of Numb in stem cell fate and mode of division, and compare cell polarity and mode of division in the lung stem cells with other systems, as well as discuss the regulatory mechanisms of lung stem cell polarity, fate, behavior and mode of division.

Discovering signaling pathways in protein interaction networks is a key ingredient in understanding how proteins carry out cellular functions. These interactions however can be uncertain events that may or may not take place depending on many factors including the internal factors, such as the size and abundance of the proteins, or the external factors, such as mutations, disorders and drug intake. In this paper, we consider the problem of finding causal orderings of nodes in such protein interaction networks to discover signaling pathways. We adopt color coding technique to address this problem. Color coding method may fail with some probability. By allowing it to run for sufficient time, however, its confidence in the optimality of the result can converge close to 100%. Our key contribution in this paper is elimination of the key conservative assumptions made by the traditional color coding methods while computing its success probability. We do this by carefully establishing the relationship between node colors, network topology and success probability. As a result our method converges to any confidence value much faster than the traditional methods. Thus, it is scalable to larger protein interaction networks and longer signaling pathways than existing methods. We demonstrate, both theoretically and experimentally that our method outperforms existing methods.