Major Depressive Disorder (MDD) is a leading cause of worldwide disability, and standard clinical treatments have limitations due to the absence of neurological evidence. Electroencephalography (EEG) monitoring is an effective method for recording neural activities and can provide electroneurophysiological evidence of MDD.In this work, we proposed a probabilistic graphical model for neural dynamics decoding on MDD patients and healthy controls (HC), utilizing the Hidden Markov Model with Multivariate Autoregressive observation (HMM-MAR). We testified the model on the MODMA dataset, which contains resting-state and task-state EEG data from 53 participants, including 24 individuals with MDD and 29 HC.The experimental results suggest that the state time courses generated by the proposed model could regress the Patient Health Questionnaire-9 (PHQ-9) score of the participants and reveal differences between the MDD and HC groups. Meanwhile, the Markov property was observed in the neuronal dynamics of participants presented with sad face stimuli. Coherence analysis and power spectrum estimation demonstrate consistent results with the previous studies on MDD.In conclusion, the proposed HMM-MAR model has revealed its potential capability to capture the neuronal dynamics from EEG signals and interpret brain disease pathogenesis from the perspective of state transition. Compared with the previous machine-learning or deep-learning-based studies, which regarded the decoding model as a black box, this work has its superiority in the spatiotemporal pattern interpretability by utilizing the Hidden Markov Model. Major depressive disorder (MDD), which is known to be characterized by persistent sadness, irritability, frustration, and restlessness, is among the ten leading causes of worldwide disability-adjusted life years according to the World Health Organization . The absHowever, uncovering the neurobiological markers for MDD is a complex and challenging task. Firstly, the high degree of heterogeneity in MDD, including diverse symptom profiles, severity levels, and underlying neurobiological mechanisms, raises difficulties in the identification of reliable neurobiological markers. Secondly, the transition patterns among brain activity states during rest or cognitive tasks in MDD patients remain uncertain, making it difficult to accurately characterize the temporal features of neural activities. Nevertheless, neural activities of the brain are conveyed through electrophysiological signals, which are fast-changing signals that require analysis at a subtle temporal granularity. Therefore, a methodology is needed to analyze the patterns of neural activities and their transformation processes based on neural recordings from clinically diagnosed MDD patients, which are feasible to deploy on a large scale in clinical settings. Until recently, the broad deployment of electroencephalographic (EEG) in MDD treatment and the development of advanced processing and analyzing methods have paved the way for an interdisciplinary solution to this dilemma. Since EEG measures the electrical activities of large and synchronously firing populations of neurons via the electrodes placed on the scalp, long-term resting-state EEG monitoring, as well as short-term task-related EEG signals of the MDD brain is conducive to providing eletroneurophysiological evidence of MDD.Numerous studies have utilized machine learning or deep learning algorithms to extract high-dimensional features from EEG signals and classify the EEGs of patients with MDD and healthy controls (HC). In the study conducted by In order to address this issue, the Hidden Markov Model (HMM) was employed to represent brain activities as a sequence of discrete brain states in temporal scales derived directly from the data, offering significant improvements over the sliding window approach in previous studies . SeveralIn this study, we employed the HMM with multivariate autoregressive observation (HMM-MAR) model  on a 128i) Distinct patterns of brain activity state transitions in response to different emotional stimuli were identified in patients diagnosed with MDD in comparison to HC. Brain connectivity analyses of the corresponding patterns to these stimuli were conducted in both groups. ii) The brain activity state transition patterns in response to sadness-related stimuli had the best fit with the scores on the PHQ-9 among all stimuli presented to participants in the study. These patterns are therefore more likely to indicate a risk for anxiety and MDD in response to sadness-related stimuli. iii) The outcoming results suggest that our finding introduces a novel approach to the diagnosis of MDD, and shows the potential to be integrated into the clinical treatment workflow.Generally, the major work contributions are: 1 from Lanzhou University  procedure . The ICAThe Hidden Markov Model (HMM) is a probabilistic graphical model that is commonly used to model time-series data. It is designed to describe a Markov process with a hidden, unknown variable that depends only on the current state and not any previous state. The HMM is comprised of two basic components: a state sequence and an observation sequence. The state sequence is a sequence of hidden states in a time series that transition based on certain rules, while the observation sequence refers to the data observed at each time point, which may or may not be related to the state sequence. The basic assumption of the HMM is that the observation sequence is generated only by the corresponding state at each time point. To extract features from time-series data and model multivariate time-series data, Ot ∈ ℝN, and the hidden states as tH, where t 1, ⋯, T. Assuming Gaussian noise, the observation model could be depicted as:To be specific, we denote the multichannel EEG signal as k-th state AR coefficient matrix, and ∑k). The variational Bayes method, which assumes additional factorizations in the parameter space and requires conjugate prior distributions , was impIn the model implementation, we followed previous research experiences  and specWe partitioned the preprocessed EEG data of all participants into six groups, consisting of MDD patients presented with happy, sad, and fearful stimuli, and healthy controls presented with happy, sad, and fearful stimuli. We extracted EEG segments ranging from 200 ms before stimulus onset to 800 ms post-stimulus onset from each group and concatenated all trials of all participants within each group to form six long sequences. We then applied the HMM-MAR model to each sequence for neural dynamic activity modeling. To verify the decoding ability of the HMM-MAR model for the dynamic neural activity of MDD patients and healthy controls in response to the three types of stimuli, we regressed the state time series obtained from the model for each of the six groups against the PHQ-9 scores of each participant within each group, due to its suitability for measuring the severity of depressive symptoms. The regression results are shown in In order to better demonstrate the results. Due to the relatively concentrated PHQ-9 scores of the healthy control group and the scattered scores of the MDD group, we used a box plot to depict the relationship between the actual PHQ-9 scores of the healthy control group and the estimated values obtained through state time series regression and used a scatter plot to describe the MDD group. The comparison details were illustrated in In To examine the inferred states, global temporal statistics were calculated and analyzed. In this work, we calculated the interval times of each HMM state in each of the six experimental and control groups. The switching rates of each subject for each group were also calculated and compared, shown in Our study performed a frequency domain analysis of the states (states 1-6) inferred by the HMM-MAR model in the MDD and HC control groups and computed the coherence between channels. To partition the 128 EGI-Geodesics EEG cap electrodes into six regions, we followed the method proposed by (Sleeping) et al. Specifically, we divided the electrodes into six regions, namely Frontal, Central, Right Temporal, Left Temporal, Parietal, and Occipital, based on their layout. The coherence between EEG channels was calculated for three distinct emotional facial stimuli in the MDD and HC control groups, we preserved the top 1% coherences and generated a connectivity map as presented in The following conclusions can be drawn from We adopted a parametric autoregressive modeling approach, namely the MAR, to estimate the power spectra of different neural dynamic transitions observed in the MDD and HC control groups during three distinct stimuli. It is noteworthy that the MAR model for power spectrum estimation is not the same as that used in the HMM-MAR model. An MAR model with a model order of 3 was trained separately in the process. Specifically, we computed the power spectra of the six states in six control groups (MDD and HC) across Delta (0–4 Hz), Theta (4–8 Hz), Alpha (8–12 Hz), and Beta (12–40 Hz) frequency bands. To accommodate space limitations, we present the scalp maps of the power spectra estimation, with each map normalized to 0∼1, in response to the sad emotional facial stimulus for the MDD group in Utilizing power spectra, we can approximate the level of activation of brain regions corresponding to scalp EEG electrodes. From This study aimed to decode the neural dynamics of EEG signals in response to happy, sad, and fearful facial stimuli in both clinically diagnosed MDD patients and healthy controls, using the HMM-MAR model. Specifically, we trained the HMM-MAR on the MODMA dataset using two groups of samples, MDD and HC, exposed to stimuli of happiness, fear, and sadness, respectively, to obtain the state time series. To validate the accuracy of the model, we designed a regression task that utilized the state time series to predict the participants’ PHQ-9 scores, yielding favorable regression accuracy. In Our study demonstrates that the HMM-MAR model can serve as a decoding tool to analyze the neural dynamic processes of brain activity in cognitive tasks. Based on coherence analysis of brain connectivity patterns and power spectrum estimation results, significant differences in brain activation and connectivity patterns were observed between MDD patients and HC when presented with three emotional stimuli, which may suggest a risk for MDD in clinical practice. Furthermore, regression experiments revealed that the neural dynamic processes of MDD patients when presented with sad facial expressions exhibited Markovian properties and could be well characterized by the HMM-MAR model.Regarding the differences in brain connectivity and activation between MDD and HC, there is ample evidence from previous studies that MDD may be a brain disorder characterized by changes in brain structure and function resulting from damage to certain brain tissues or abnormal neural circuits. The caudal middle frontal cortex (MFC) and the superior frontal gyrus (SFG) are structures of the frontal lobe, whose structural change has been considered to manifest anatomic abnormalities in MDD , whose cThe clinical impacts of the proposed method are in three folds. Firstly, the differential responses of the HC and MDD groups to sad facial stimuli, as analyzed using the HMM-MAR model, may represent a potential clinical diagnostic indicator for MDD. This approach could serve as a reference to determine whether an individual exhibits characteristics of MDD in its early stages. Furthermore, the property of Markovian dynamics observed in MDD patients when presented with sad facial emotional stimuli can provide guidance for the use of rTMS, tDCS, ECT, and other devices in clinical MDD treatment . This fiThe present study has the following limitations. Firstly, although the HMM-MAR model demonstrated its ability to capture the neural dynamic transition in the experiment, the order of HMM states was not constrained, leading to the HMM states obtained not being directly related to brain networks, such as the DMN, which is widely believed to have physiological and structural significance. Additionally, the experiment was conducted only on a dataset of 128-channel EEG task data from 53 subjects, and further studies should apply the model to more MDD datasets to validate the universality and the reproducibility of results.To the best of our knowledge, this is the first study to employ HMM-MAR to decode the neuronal dynamic of MDD patients. Compared with the previous machine-learning or deep-learning-based studies, which regarded the decoding model as a black box, this work has its superiority in the spatiotemporal pattern interpretability by utilizing the Hidden Markov Model. It is also noteworthy that the proposed method highly coincides with the clinical routine. Therefore, integrating this decoding model into the clinical workflow will be beneficial to both MDD diagnosis and permit timely interventions based on the diagnosis.The original contributions presented in this study are included in the article/supplementary material, further inquiries can be directed to the corresponding author.WJ contributed to the modeling, data analysis, and the draft of the manuscript. SD contributed to the drafting and statistical analysis. CX contributed to the interpretation and critical manuscript revision. HK contributed to the data preprocessing and parameter adjusting. HB contributed to the algorithms and critical manuscript revision. TZ, LM, and HL contributed to the data acquisition, design, and supervision. All authors have approved the final manuscript.


Any equipment submerged in the ocean will have its surface attacked by fouling organisms, which can cause serious damage. Traditional antifouling coatings contain heavy metal ions, which also have a detrimental effect on the marine ecological environment and cannot fulfill the needs of practical applications. As the awareness of environmental protection is increasing, new environmentally friendly and broad-spectrum antifouling coatings have become the current research hotspot in the field of marine antifouling. This review briefly outlines the formation process of biofouling and the fouling mechanism. Then, it describes the research progress of new environmentally friendly antifouling coatings in recent years, including fouling release antifouling coatings, photocatalytic antifouling coatings and natural antifouling agents derived from biomimetic strategies, micro/nanostructured antifouling materials and hydrogel antifouling coatings. Highlights include the mechanism of action of antimicrobial peptides and the means of preparation of modified surfaces. This category of antifouling materials has broad-spectrum antimicrobial activity and environmental friendliness and is expected to be a new type of marine antifouling coating with desirable antifouling functions. Finally, the future research directions of antifouling coatings are prospected, which are intended to provide a reference for the development of efficient, broad-spectrum and green marine antifouling coatings. Fouling organisms, such as macroalgae, barnacles and shells, exist in abundance in nature. These fouling organisms can attach to and colonize a variety of surfaces, including ships, pipelines and aquaculture nets, and their attachment and accumulation on wet surfaces are known as biofouling ,2. BiofoAs a result, various strategies have been proposed to prevent the adhesion of marine fouling organisms to the surface of underwater equipment and to reduce frictional resistance. The increasing trend in the publication of marine-fouling-related literature from 2009 to 2022 is shown in This paper reviews the research progress of new environmentally friendly marine antifouling coatings for ship surfaces in recent years, analyses the advantages and disadvantages of each type of antifouling coating and focuses on the preparation of antibacterial-peptide-modified surfaces. Finally, the future development direction of marine antifouling coatings is prospected, aiming to provide a reference for the development of efficient, broad-spectrum and green marine antifouling coatings.The attachment of marine fouling organisms is a highly complex process. In general, the formation of marine biofouling consists of three main stages: formation of a conditioned film, formation of biofilm and formation of the fouling biotope  9]. Onc. Onc9]. Since the age of navigation, people have been working to solve the problem of biofouling on the surface of ships. In the era of wooden ships, metals, such as lead and copper, were used to wrap the hull surface or apply hot pitch, tar and grease to prevent biofouling . With th2 can exhibit the best resistance to adhesion  benzoate and penicillixanthone exhibited strong antifouling activity against amphibious small-vine larvae .Moreover, researchers have found that some compounds isolated from marine bacteria also exhibit good antifouling activity. Pereira et al.  evaluateg et al.  isolatedIn addition, terrestrial plants are also the focus of scholars’ research. Feng et al.  investigEscherichia coli compared to ginger oleoresin, and, after 6 months of marine field immersion tests, the coatings containing rue and ginger oleoresin extracts were effective in inhibiting the adhesion of marine fouling organisms , and, with a therapeutic ratio (LC50/EC50) > 15 for xanthone 23, this synthetic analog has great potential for marine antifouling applications.The secondary metabolite xanthone derivatives, which are widely present in marine and terrestrial plants and animals, have been shown to have antifouling activity yet are still not used for marine antifouling. Resende et al.  exploredSome plants and animals, such as sharks, sea crabs, lotus leaves and rice leaves, exhibit excellent self-cleaning and antifouling and deterrent abilities on their surfaces, which can effectively prevent or inhibit the adhesion of fouling organisms, such as barnacles, algae and bacteria . Recent TM on PDMS substrate, which could effectively inhibit the settlement of 86% of marine algal spores when the size of Sharklet AFTM was smaller than the size of marine algal spores. Qin et al. used the idea of segmental independence to simplify the structure of biological sharkskin shield scales [Br] grafted on the surface of “Sharklet” increased the percentage of removal of Porphyridium from 40.7% to 60.1%. The aforementioned study successfully inhibited the deposition of fouling organisms by constructing sharkskin-like microstructures with constant height on the material substrate; however, the grooved structures on the sharkskin surface did not have a constant height and therefore lacked a certain degree of biological accuracy. Munther et al. .,88.87,88Based on the excellent antimicrobial properties and biocompatibility of antimicrobial peptides, the use of antimicrobial peptides to modify the surface of materials can generate a new material that is non-toxic, non-polluting and green. Scholars at home and abroad have developed many methods to bind antimicrobial peptides on material surfaces, which can be generally classified as the polymer brushing method, layer stacking method (LBL), monomer self-assembly method (SAM) and chemical coupling method ,90. The N,N dimethyl acrylamide-co-N-(3-aminopropyl)methacrylamide hydrochloride] (PDMA-co-APMA) polymer brush to link antimicrobial peptides Cys-HHC-36 linked to hydroxyapatite (HA) nanorods  [Polymer brush method, also known as the polymeric molecular brush method, is a modification means to covalently immobilize antimicrobial peptides onto the surface of materials through reactive groups at the end of polymeric molecules after activation , and somnanorods A, and thactions) , which iS. aureus. Plácido et al. [E. coli.Layer stacking (LBL) is a versatile approach for the preparation of coatings on substrate surfaces, where the binding of antimicrobial peptides to the surface is achieved through electrostatic, hydrogen bonding and covalent interactions between polycations and polyanions. Shukla et al.  successfo et al.  preparedH. pylori.Monomer self-assembly is another important modification method to covalently immobilize antimicrobial peptides onto the material surface. Ye et al.  self-assThe chemical coupling method is a method of grafting antimicrobial peptides onto the surface of a material using a chemical coupling agent. Dopamine is highly susceptible to oxidation in weak alkaline solutions, forming a composite film of polydopamine (PDA) with strong adhesion, and, in addition, many functionalized functional groups, such as catechols, amines and imines, are present on the surface of the PDA-modified materials, which can be used as reactive groups for further functionalization and the design and acquisition of the desired functional materials . TherefoIn summary, to apply antimicrobial peptides to the field of marine antifouling, stable and efficient grafting methods on the surface of the substrate must be realized. Although some antimicrobial peptides in nature can spontaneously bind to the surface of the substrate, few natural peptides have both antimicrobial functional fragments and substrate affinity fragments. The antimicrobial peptides are indirectly immobilized onto the substrate surface by the above-mentioned methods, but different immobilization strategies have a great impact on the conformation and activity of the antimicrobial peptides. It remains a challenge to ensure that the antimicrobial peptide immobilized onto the surface still reflects the same spatial structure and antimicrobial properties as in the solution. In addition, there is a wide variety of antimicrobial peptides, and current research is not satisfied with peptides extracted from organisms but hopes to provide different physical properties and antimicrobial activity to biological peptides through synthetic designs, which can modulate the physical properties of metal surfaces after reacting with metals to obtain better antifouling effects.As people pay more and more attention to the ecological environment, it is important to develop antifouling coatings with stable, durable and environmentally friendly characteristics. Based on the mechanism of marine biofouling, this review discusses new environmentally friendly coatings for ship surface antifouling, focusing on the mechanism of action of antimicrobial peptides and the preparation means of modified surfaces, and finally indicates the following prospects for the follow-up research of marine antifouling coatings.(1)The currently developed antifouling coatings have difficulty covering the problems of stability, toxicity and cost of use, which seriously hinders the promotion of their use in the marine field. In the future, the research and application of marine antifouling coatings will develop in the directions of efficient, broad-spectrum, non-toxic, non-polluting and degradable.(2)Several antifouling coatings reviewed in this paper are derived from natural inspiration, such as natural antifouling agents, micro/nanostructured antifouling materials, liquid-infused smooth porous antifouling materials and hydrogel antifouling coatings, which have the advantages of antifouling performance while remaining non-toxic and ecologically harmless, etc. However, these antifouling coatings still generally have the disadvantages of high costs and poor stability. Therefore, it is necessary to conduct in-depth research on the antifouling mechanism of plants and animals to develop efficient, broad-spectrum, non-polluting antifouling coatings.(3)The marine environment is complex, and the living environment of each fouling organism is different, so it is not possible to achieve the expected antifouling effect by only relying on coatings with a single antifouling mechanism. Therefore, the future trend is to develop antifouling coatings with synergistic strategies.


Perioperative neurocognitive disorders (PND) is a common surgical anesthesia complication characterized by impairment of memory, attention, language understanding and social ability, which can lead to a decline in the quality of life of patients, prolong the hospitalization period and increase the mortality rate. PND has a high incidence rate, which has a great impact on postoperative recovery and quality of life of patients, and has caused a heavy economic burden to society and families. In recent years, PND has become an important public health problem. The high risk population of PND is more prone to gut microbiota imbalance, and gut microbiota may also affect the inflammatory response of the central nervous system through the microbiota-gut-brain axis. Meanwhile, Neuroinflammation and immune activation are important mechanisms of PND. Regulating gut microbiota through probiotics or fecal bacteria transplantation can significantly reduce neuroinflammation, reduce the abnormal activation of immune system and prevent the occurrence of PND. This review summarizes the research progress of gut microbiota and PND, providing basis for the prevention and treatment of PND. Perioperative neurocognitive disorders (PND) is common and significant complication of surgery, affecting a significant proportion of patients, occurred in up to 50% of elderly patients undergoing major or high-risk operations , 2. PND The human gut is home of a complex and dynamic community of microorganisms, collectively known as the gut microbiome. This community plays a crucial role in human health, influencing various physiological processes, including immunity, metabolism, and brain function –10. ReceUnder normal circumstances, the gut microbiota forms an ecological balance in the human body, maintaining the health of the human intestinal micro-ecology . In receGram-negative bacteria increased  can enter the circulation through the damaged intestinal wall (Age is an independent risk factor for PND . Neuron nal wall . AlthougPND is accompanied by the occurrence of neuroinflammation and the disorder of gut microbiota during operation. Dysbiosis of gut microbiota will promote the progress of neuroinflammation, so regulation of gut microbiota will have a certain effect on the treatment of PND. Prebiotics, probiotics and fecal bacteria transplantation can affect gut microbiota and thus affect cognitive function . Fecal mProbiotics can promote the growth and reproduction of beneficial microbiota, improve the balance of host intestinal microbiota, and play a positive role in the recovery of brain function through various physiological channels . It is fThe composition and diversity of gut microbiota will change according to the dietary structure, and the production of corresponding metabolites will also be affected. Gut microbiota can synthesize a variety of essential vitamins, amino acids and fatty acids, participate in glucose and protein metabolism, and also regulate BDNF, synaptophysin, postsynaptic density protein and other nutritional factors that affect the development and plasticity of the nervous system. A high-fat or high-energy diet will increase the displacement of LPS, promote the development of inflammation and insulin resistance. The dietary fiber diet is conducive to the maintenance of gut microbiota diversity and the inhibition of inflammation. Furthermore, SCFA is the major metabolic product obtained from the decomposition and fermentation of dietary fiber in the gastrointestinal tract by intestinal microorganisms. The current research shows that SCFA may participate in the changes of people’s cognitive and neurological functions from aspects of immunity, neuroendocrine, and blood-brain barrier . Some reIn conclusion, there have been many studies proving the correlation between gut microbiota and PND. Stress reaction during surgical anesthesia, gastrointestinal motility abnormalities caused by anesthetic drugs or muscle relaxants, and the use of antibiotics during perioperative period could increase the risk of gut microbiota disorder. However, the research on the direct relationship between gut microbiota and PND is relatively small, and more are phenomenological research and exploration, which is not deep enough. Future research can explore its mechanism by combining current genomics and other methods. Deeper exploration of whether there are specific flora and specific signal pathways, screening of relevant specific microorganisms, or finding out microorganisms that can improve cognitive dysfunction, may become the treatment target of PND.YS, KW, and WZ wrote the manuscript; WZ revised the review. All authors contributed to the article and approved the submitted version.


A common neuropsychiatric complication of advanced liver disease, hepatic encephalopathy (HE), impacts the quality of life and length of hospital stays. There is new evidence that gut microbiota plays a significant role in brain development and cerebral homeostasis. Microbiota metabolites are providing a new avenue of therapeutic options for several neurological-related disorders. For instance, the gut microbiota composition and blood-brain barrier (BBB) integrity are altered in HE in a variety of clinical and experimental studies. Furthermore, probiotics, prebiotics, antibiotics, and fecal microbiota transplantation have been shown to positively affect BBB integrity in disease models that are potentially extendable to HE by targeting gut microbiota. However, the mechanisms that underlie microbiota dysbiosis and its effects on the BBB are still unclear in HE. To this end, the aim of this review was to summarize the clinical and experimental evidence of gut dysbiosis and BBB disruption in HE and a possible mechanism. Hepatic encephalopathy (HE) is the main complication of acute liver failure (ALF) and advanced liver diseases; it is characterized as a set of complex spectra of brain dysfunctions and neuropsychiatric impairments, ranging between preclinical changes and deep coma ,2. In ad12), biotin (B7), and folate (B9), as well as facilitating the absorption of calcium, magnesium, and iron by enterocytes [The term gut microbiome, previously known as gut normal flora, encompasses all microorganisms, including bacteria, fungi , viruses (virome), and archaea that inhabit the small intestine and colon . One to erocytes . Normal erocytes . The interocytes . Some clerocytes . Increaserocytes . In addierocytes .Box 1Studies in microbiota communities are a field of great interest due to changes in their composition associated with health and diseases. To identify the structure and functional dynamics of the gut microbiome, several multi-omics approaches such as metagenomics (DNAs interactions) and metatranscriptomics (RNAs interactions) are applicable. Each approach images different types of biological information from the microbiota communities. Current investigations combine more than one omics approach to image a high-resolution picture of the gut microbiota dynamics . GenomicThe BBB is a complex and highly selective border that forms an important part of the neurovascular unit in the CNS. This unique structure protects neuronal cells from direct contact with circulatory neurotoxic agents, pathogens, and peripheral inflammation . The BBB+-K+ ATPase, Na+-K+-Cl− cotransporter, K+ channels, Na+/Ca2+, Na+/H+, and Cl−/HCO3− exchangers, Na+/HCO3− symporters and Ca2+ transporters severely regulate the sodium gradient concentration to ensure the uptake of sodium-dependent substrates, maintain the intracellular pH, and regulate the brain interstitial ions equilibrium and water content [Only three transmission routes can be considered for solute transportation across the BBB ; The fir content .The second cellular components of the BBB are pericytes, which are located in the basement membrane in close contact with the abluminal side of the endothelial cells via gap junctions and peg-socket junctions . These cThe intact integrity and normal functioning of the cellular components of the BBB ensure the homeostasis of CNS and proper neuronal function . Any smaBBB dysfunction and an increase in the CNS levels of neurotoxic substrates has been reported in patients with HE and in experimental models . In caseThe intestinal microbiome seems to be of central importance in the progression of HE ,107. TheGut microbiota-derived metabolites also affect the CNS through the enteric nervous system (ENS), which normally connects to the CNS via the vagus nerve and sympathetic pathways ,161. GutBox 24–106 cells/gram feces) to the lower GI (109–1012 cells/gram feces) as a result of the lower pH, rapid movement of luminal contents, and the presence of antibacterial agents in the stomach and duodenum compared to the lower GI [Bacteria constitute a large part of the gut microbiome compared to other microorganisms . In addition, the composition of the gut bacteria throughout the gastrointestinal tract (GI) is not the same ,178. Thelower GI ,179,180.lower GI .Given that gut dysbiosis may contribute to the pathophysiology of BBB permeabilization in HE, therapeutic interventions that target gut dysbiosis and their metabolites may be useful for restoring the destructed BBB and its consequent immune cells infiltrations, oxidative stress, microglial activation, and neuroinflammation in HE. Antibiotic therapy  targets the gut microbiota and decreases the production and absorption of intestinal ammonia, resulting in alleviated hyperammonemia, decreased hospitalization for overt HE, and an improved quality of life for patients with HE ,183. TheProbiotic supplements contain live microorganisms that modulate the composition of the gut microflora, while prebiotics are types of nutrients or agents  that are beneficial for the growth and activity of the gut microbiota ,200. A cFMT is a procedure to collect feces from healthy individuals and transfer them into the recipient’s intestine, mainly in patients with gut dysbiosis . OverallThe gut microbiota contributes to the development and homeostasis of the nervous system. Gut dysbiosis is associated with cognitive impairments, cerebral abnormalities, and other complications in patients with advanced liver diseases. Gut-originated metabolites released from altered pathologic bacteria impair the integrity of BBB, devastate the brain microenvironment, and lead to the development of HE. The modulation of the gut microbiome composition by different agents has been revealed to have beneficial effects in the management of HE. Moreover, the manipulation of the intestinal microbiome to protect the beneficial species and decrease the harmful microbiome can improve and control HE through changes in the levels of circulating neurotoxic metabolites and products. Probiotics and prebiotics, antibiotics, and FMT improve the pathological changes in the structure of the BBB in numerous diseases, such as Alzheimer’s disease, Parkinson’s disease, depression, chronic stress, and stroke. The efficacy of these interventions still remains an open challenge in HE. However, the majority of animal and human studies have only focused on gut bacteria communities and underestimated the mycobiome diversity and virome composition of the gut microbiota in HE. In terms of future perspectives, it may be important to investigate the mycobiome and virome composition of the gut microbiome, along with bacteria, through multi-omics comprehensive metagenomics and metatranscriptomics studies to identify the specific microbial taxa and metabolites that are associated with HE and potentially serve as biomarkers for the diagnosis and monitoring of the disease. In conclusion, the relationship between gut dysbiosis and HE is a complex and dynamic process that requires further investigation. However, the growing body of evidence suggests that targeting gut dysbiosis represents a promising strategy for the prevention and treatment of HE.


It has yet to be determined whether medication overuse headache (MOH) is an independent disorder or a combination of primary headache and substance addiction. To further explore the causes of MOH, we compared MOH with substance use disorder (SUD) in terms of the brain regions involved to draw more targeted conclusions. In this review, we selected alcohol use disorder (AUD) as a representative SUD and compared MOH and AUD from two aspects of neuroimaging and basic research. We found that in neuroimaging studies, there were many overlaps between AUD and MOH in the reward circuit, but the extensive cerebral cortex damage in AUD was more serious than that in MOH. This difference was considered to reflect the sensitivity of the cortex structure to alcohol damage. In future research, we will focus on the central amygdala (CeA), prefrontal cortex (PFC), orbital-frontal cortex (OFC), hippocampus, and other brain regions for interventions, which may have unexpected benefits for addiction and headache symptoms in MOH patients. Medication overuse headache (MOH) is a common secondary headache. Patients with MOH usually have primary headache disorders including migraine, tension-type headache, or chronic daily headache. Overuse of painkillers to block the acute attack of primary headache disorders can lead to worsening of primary headache disorders, and finally, progress to a condition known as MOH. If headaches are believed to have developed as a consequence of or have been substantially exacerbated by medication overuse, the patient is diagnosed with MOH . The estThe International Classification of Headache Disorders, third edition ICHD-3), defines MOH as a secondary headache, which is caused by (I) Triptans, opioids, or two or more types of combined analgesics for at least 10 days per month for a duration of more than 3 months, or (II) non-steroidal anti-inflammatory drugs (NSAIDs) or paracetamol for at least 15 days per month for a duration of more than 3 months .The mechanism by which medication overuse promotes the changes of primary headache disorders and how it leads to MOH is unclear. Recent neuroimaging studies have found that brain morphology and function in patients with MOH are altered compared with patients with simple migraine and patients with successful abstinence treatment. These imaging studies have revealed an overlap between addiction mechanisms and MOH mechanisms and further identified brain structures and functional patterns that make migraine patients prone to MOH .Alcohol misuse and addiction are major international public health issues with high associated morbidity and mortality. Alcohol use disorder (AUD) is one of the most common psychiatric disorders, with nearly one-third of US adults experiencing AUD at some point during their lives. Alcohol use disorder is a neural-network disorder. It is considered to be a meaningful subclass in clinical research of addictive diseases. Alcohol affects brain function through interactions with various brain networks. The formation of chronic alcohol dependence is closely related to several important brain regions. These brain regions include the nucleus accumbens (NAc), bed nucleus of the stria terminalis, medial prefrontal cortex (mPFC), ventral tegmental area (VTA), central amygdala (CeA), insula, etc. Some researchers used AUD as a representative of SUD for detailed neuroimaging research.In our review, we chose AUD, which is a well-studied SUD, for comparison with MOH, aiming to identify specific brain regions to explore in future studies.To evaluate AUD and MOH progression and the impact of withdrawal on the structure and function of the brain as well as to discuss the similarities and differences between these two diseases, we summarized the results of relevant literature published before 2023.In a neuroimaging study based on voxel-based morphometric analysis (VBM) in 2005, the researchers found that patients with MOH did not show any morphological changes compared with the healthy controls (HCs) . CompareSome studies have analyzed the effects of detoxification treatment and changes in the GMV of each brain region in MOH patients. The results showed that the GMV of the midbrain in the MOH group was increased compared with that in the HCs. There was a significant decrease in midbrain GMV in patients who responded well to detoxification treatment, while MOH patients with lower GMV of the OFC at baseline did not respond to detoxification treatment. These results further emphasized the important role of the OFC in patients with MOH . A studyEffective research on the changes of white matter in the brain of MOH is not in-depth. Michels et al. compared the fractional anisotropy of MOH patients with chronic myofascial pain patients to determine the consistency of white matter fiber direction. They found that functional anisotropy (FA) in the insular cortex increased in both groups and that FA in the right parietal operculum decreased in the MOH group. However, these changes may be related only to the central sensitivity caused by chronic pain, not the characteristics of MOH .In recent years, an increasing number of studies have examined the FC of various brain regions in patients with MOH. It is generally believed that the changes in FC are greater than structural changes. Compared with the HCs, the patients with MOH showed dysfunction of the substantia nigra/ventral tegmental area (SN/VTA) (low activity during task execution) and increased activity of the bilateral ventromedial prefrontal cortex (vmPFC) and posterior cingulate cortex/precuneus (PCC/P). However, the increased activity of the bilateral vmPFC and PCC/P returned to the normal levels after detoxification treatment in patients with MOH, while SN/VTA dysfunction was persistent. Additionally, increased activity of the vmPFC and PCC/P was also observed in the CM group. Thus, the SN/VTA dysfunction was unique to MO , 28. In Some PET-CT studies show that OFC in patients with MOH presents low metabolism and the availability of DAT decreases before and after drug withdrawal, which is consistent with the decrease of GMV in the OFC region in the previous fMRI study, again emphasizing the special role of OFC in the pathogenesis of MOH.In a VBM-based MRI study, the researchers recruited 31 AUD patients and 28 HCs. The results showed that, compared with HCs, AUD patients exhibited significant decreases in the GMV of the bilateral dlPFC, temporal cortex, lingual cortex, cingulate cortex, and insular cortex, especially the dlPFC. Regarding white matter fiber, the white matter in the corpus callosum, frontal lobe, cingulate gyrus, temporal lobe, cerebellum, and pons regions of AUD patients decreased significantly, especially that in the corpus callosum. Moreover, neuropsychological studies have shown that the executive function of AUD patients is impaired, which was considered to be related to extensive white matter damage and the reduction in GMV in the frontal and temporal cortices, insula, and hippocampus. The age of first alcohol consumption significantly correlated with the decrease in GMV in the frontal cortex, the cerebellum, and the brainstem . Diffusin = 128) showed sex difference in the putamen and thalamus of AUD patients; boys with AUD had smaller volumes than HCs, while girls with AUD had larger volumes than HCs. No significant differences were found in other brain regions. Interestingly, in this large sample study, no difference was found in the GMV of the hippocampus and amygdala. However, many previous studies have shown that the hippocampal volume of adolescent AUD patients was smaller than that of the HCs  patients before withdrawal, 1 month after withdrawal, and 7.5 months after withdrawal. The study found that the rate of GMV was the fastest in the early stage of withdrawal (1 week to 1 month). After 7.5 months of abstinence, the GMV and WMV increased significantly, except in the temporal lobe and lenticular nucleus. However, only the GMV of the frontal lobe was completely restored ; the GMV of the parietal lobe, temporal lobe, and thalamus still significantly differed. Recovery of frontal GMV is clinically relevant because ALC patients with lower volumes in frontal subregions  during early abstinence were more likely to relapse within approximately 1-year after treatment , 48.Some researchers have found that the resting-state FC of the reward system in AUD patients is lower than that in HCs. Repeat the verification of the above results and try to conclude that cracking is related to an increase of OFC-NAcc-FC. The results showed no difference between the OFC-NAcc-FC of AUD patients with short-term withdrawal, only a reduction in NAc volume and FA and bundle length of the OFC-NAc circuit. This indicates a change in the structure of the reward network in AUD. Different results were found in patients with long-term abstinence . The resTo sum up, we sorted out and compared the similarities and differences between MOH and AUD in clinical neuroimaging research , 2. We lOther researchers have found that some people often use alcohol for pain relief . People Whether MOH is a secondary headache originating from MO or MO is a consequence of chronic headache disorders remains a matter of debate . ReferriThe NAc is a brain region related to goal-oriented behavior, including drug-seeking behavior . Long-teThere are a large number of pain-responsive neurons are enriched in the lateral part of the central amygdala, which is crucial for alcohol-induced pain enhancement, and may represent a potential intersection between nociceptive feelings and motivation-related negative effects associated with alcohol dependence. In animal models of pain and alcohol dependence, the neural adaptation of this region is particularly relevant to disease progression. Alcohol intake causes the release of GABA, DA, 5-HT, and other neurotransmitters in the CeA –82. AlcoIn alcohol-dependent animal models, the level of the stress-related neuropeptide corticotropin-releasing factor (CRF) in the CeA also increased during withdrawal. Injection of a CRF receptor antagonist into the CeA reduced the excessive drinking level of dependent animals but did not change the alcohol or water intake of non-dependent animals . SimilarThe PFC is also the anatomical intersection of negative emotions related to alcohol withdrawal and dependence with pain-related emotions , 99. In During the period when the human body receives pain stimulation, the insular cortex is continuously activated . RelevanIn this review, we summarized the clinical neuroimaging research results on AUD and MOH and basic research results related to addiction and pain in recent years, including the research results of our research group. We hoped to elucidate similarities with MOH from the relevant research on AUD.Regarding clinical neuroimaging data from the two diseases, we observed the following three findings: Compared with HCs, MOH patients exhibit brain changes mostly concentrated in the thalamus, hypothalamus, and limbic system, involving a small part of the cortex , while AUD patients exhibit changes in extensive regions of the cerebral cortex, thalamus, hypothalamus, cerebellum, and other brain areas; most of the changes in brain areas are caused by the toxicity of alcohol to the nervous system. AUD and MOH involve the same brain regions, including the insula, dlPFC, OFC, cingulate cortex, amygdala, hippocampus, Superior frontal gyrus, PCC, and precuneus. The reduction in the GMV of the amygdala and insula is related to the persistence of chronic pain and is also a key component of DA reward circuit, which plays an important role in addictive diseases. The precuneus is related to collecting and evaluating information, self-referential mental activity, retrieval of situational memory, emotion, and anxiety. The BOLD signal of the anterior cuneiform lobe is increased in AUD, and the connectivity between the precuneus and temporal lobe/hippocampus is increased in MOH. The PCC plays an important role in relapse of addiction, and its activity increases in AUD and MOH. Excitatory deep transcranial magnetic (DTM) stimulation of the bilateral dlPFC, insular lobe, OFC/PFC may largely alleviate the dependence of patients with MOH on painkillers and reduce the frequency of pain.Basic research on MOH is very lacking. Referring to the basic research related to AUD, we believe that it is necessary to focus the future basic research of MOH on the cortical limbic system circuits such as the CeA, NAc, hippocampus, and PFC, which are highly important for understanding the pathophysiological process of MOH.According to the analysis of multiple clinical research groups and related results, we believe that the reason that MOH does not show obvious alterations in the addiction circuit is mostly due to the types of addictive drugs. Typical MOH is usually caused by opiates and other self-addicting drugs. The affected brain regions of this type of MOH usually involve pain perception, pain emotion, addiction, cognition, and other functional regions at the same time. However, MOH caused by non-addictive analgesics (such as MOH caused by NSAIDs) usually does not lead to changes in these brain regions, and most of the affected brain regions are changes caused by chronic pain.Although we believe that the effects of typical MOH are due to the combination of drug addiction and chronic pain involving brain regions, this process is not as straightforward in the pathophysiological process of MOH. We believe that MOH is the result of the overlap and mutual deterioration of MO and headache (mainly migraine). MOH starts with primary headache disorders or neuralgia. In order to alleviate this pain, patients use excessive painkillers, which activates the reward pathway in the central nervous system. There is a certain overlap in the anatomical structure between the reward pathway and pain-related negative emotions . Long term and chronic stimulation results in the continuous activation of pain related negative emotions, which are in the state of “emotional pain,” and enhances their FC with the sensory cortex, leading to increased headache severity and frequency, in turn, more severe headache induces more frequent drug use, forming a vicious circle.CL, WD, SM, and WX conducted the collection and organization of the literature as well as the refinement and discussion of the article ideas. CL conducted the writing of the article and the organization of the tables. SY performed a critical revision of the manuscript. All authors read and approved the final manuscript.


Tumor growth depends on the vascular system, either through the expansion of blood vessels or novel adaptation by tumor cells. One of these novel pathways is vasculogenic mimicry (VM), which is defined as a tumor-provided vascular system apart from endothelial cell-lined vessels, and its origin is partly unknown. It involves highly aggressive tumor cells expressing endothelial cell markers that line the tumor irrigation. VM has been correlated with high tumor grade, cancer cell invasion, cancer cell metastasis, and reduced survival of cancer patients. In this review, we summarize the most relevant studies in the field of angiogenesis and cover the various aspects and functionality of aberrant angiogenesis by tumor cells. We also discuss the intracellular signaling mechanisms involved in the abnormal presence of VE-cadherin (CDH5) and its role in VM formation. Finally, we present the implications for the paradigm of tumor angiogenesis and how targeted therapy and individualized studies can be applied in scientific analysis and clinical settings. Vessel formation by tumor cells represents multiple functionalities by tumor cells that recently have more attention from the scientific community. The vision of new vessels or neovascularization was first described in 1787 regarding the enhancing tissues of animals . SeveralVessels can expand in various aspects. While vasculogenesis refers to the organization of blood vessels by endothelial cell progenitor cells, angiogenesis refers to the formation of sprouts and their ensuing stabilization by mural cells, and arteriogenesis is defined as collateral growth denoting the growth of blood vessels, expansive of the pre-existing vessels, finally forming collateral bridges between networks of arteries. When the development of the vessels is deregulated, it can affect our health and produce various pathologies . This dyIn the 1990s, Pezzella et al. ,11 showeThere is a correlation between VM and high tumor grade, cancer cell invasion, cancer cell metastasis, and reduced survival of cancer patients;VE-cadherin, in conjunction with focal adhesion kinase (FAK) activity and tethered β-catenin, serves as a regulator of the tumor microenvironment, promoting the formation of VM;Anti-angiogenic therapy fails in several types of cancer in overall survival;FAK plays a pivotal role in the dynamics of cell permeabilization in the metastatic tumor endothelium.Angiogenic stimuli can cause the local degradation of the basement membrane on the side of the post-capillary venule that is dilated and located closer to the tumor. This can weaken the inter-endothelial contacts, and the endothelial cells (ECs) may migrate into the surrounding connective tissue;A solid bead is then formed by the ECs that accomplish each other in a bipolar manner;The formation of blood vessels occurs through the curvature of one or more ECs in conjunction with forming a new basement membrane and recruiting the pericytic or mural cells.Tumors commonly promote their vascularization through the induction of new capillary sprouting from pre-existing host tissue capillaries. The process was first reported in the 1970s by Ausprunk and Folkman , who proThis model has significant drawbacks, such as its inability to identify the origin of the initial and ongoing stimulus for lumen formation. It also assumes that dedifferentiation and redifferentiation occur during the same process and time, as evidenced by the loss and recovery of the luminal-basal polarity of ECs. Furthermore, although the stimulus required for lumen production has been reported to come from the developing basement membrane, this model suggests that basement membrane deposition occurs after lumen formation .Structural alteration of the basement membrane due to a loss of electron density in almost the entire area of the dilated “original vessel”. However, immunohistochemical techniques can still locate basement membrane components such as laminin and collagen IV. The impaired basement membrane’s partially regulated degradation occurs only at sites where endothelial cell processes, connected by gap junctions, project into the surrounding connective tissue;The migration of ECs, which maintain their basal-luminal polarity and form a slit-like lumen in parallel with the lumen of the main vessel, takes place continuously and is stamped by intact inter-endothelial junctions. The low electron density basement membrane is continuously deposited by polarized ECs, while only the tip of the growing capillary is free of basement membrane material;Pericytes  from theIn the early 1990s, a different model of endothelial sprouting was described . This moThe molecular mechanisms underlying the sprouting process have been extensively studied and reviewed . InitialTumors commonly develop and expand within pre-existing, well-vascularized tissues, or they may metastasize to such tissues. Additionally, tumors frequently emerge in tissues affected by chronic inflammatory processes, wherein the inflammatory infiltrate and fibrosis contribute to an ischemic state. Their growth depends not only on expansion in their original location, which is more typical of slow-growing benign tumors, but also on invasion and expansion away from the primary tumor site. Cancer cells need to come into close contact with the surface of blood vessels, either closely at initiation or during an expansion , to contAlthough it was proposed in 1987 that tumors acquired their vasculature by incorporating capillaries from the host tissue, the first study suggesting the existence of vessel co-opting was not published until 1999 by Holash et al. . In deveDifferent growth patterns were observed in liver metastases from human colorectal carcinomas, depending on the degree of cell differentiation. In the replacement growth type, the architecture of the liver was preserved, and the ECs of the sinusoids showed low mitotic activity. However, the pushing and desmoplastic types of tumors destroyed the architecture of the liver. Overall, tumors can use pre-existing vessels to facilitate their growth and invasion, and different types of tumors exhibit different growth patterns that reflect their level of vascular co-optation.Vessel co-optation is a process in which cancer cells use pre-existing blood vessels in non-malignant tissue to invade and colonize a target area without stimulating the growth of new vessels through angiogenesis. This is achieved by cancer cells penetrating the outer surface of pre-existing vessels and occupying the tissue space between them, resulting in the integration of these vessels into the tumor. Vessel co-optation allows cancer cells to use the host’s vessels to meet their metabolic needs, potentially explaining the limitations of anti-angiogenic therapies, including their frequent failure due to intrinsic or acquired resistance ,39,40,41The histopathological analysis is the standard method used to identify vessel co-option in cancer tissues. Several features can indicate the recruitment of pre-existing blood vessels, including cancer cells surrounding pre-existing vessels without evidence of angiogenic sprouting and the presence of capillary-like structures within the tumor. Vessel co-option has been observed in a variety of cancer types in different tissues, including the lung, liver, brain, skin, and lymph nodes. In some cases, vessel co-option occurs without concurrent evidence of angiogenesis . RecentlCancer cells necessitate blood vessels for growth and are the gateway to oxygen and nutrients. Current anti-angiogenic therapies are displayed to target vascular ECs capable of forming blood vessels de novo . AlthougIn 1999, Maniotis  et al. pThe term “vascular mimicry” describes the formation of channels by non-ECs, which have the ability to conduct fluids such as plasma and red blood cells. This process is categorized into two types: (1) mimicry, where the channels are not actual blood vessels but simply mimic their function, and (2) vasculogenic, where the channels do not form from pre-existing vessels but still dispense plasma and may contain blood cells . VM provWhat are the biological and functional links between the matrix networks formed by PAS-positive and laminin-positive tumor cells in aggressive melanomas and the normal vasculature lined by endothelium? Before the discovery of VM, several studies on aggressive melanomas (and other tumor types) reported the lining of canals, lakes, and sinuses by tumor cells and their contact with erythrocytes ,64,65. HThe biological functions of endothelial molecules associated with human tumor cell lines derived from melanoma in the same patient were investigated. This was accomplished by studying gene expression using microarrays in samples obtained from patients with metastatic melanoma . In thisIn 2001, Mary JC Hendrix  and her In the past few decades, the complexity of tumors has been increasingly acknowledged. This has led to a shift in focus in cancer research, where numerous articles are no longer exclusively centered around cancer cells. Instead, researchers are paying more attention to the different components of the tumor microenvironment. One important aspect of the tumor microenvironment is tumor hypoxia, which refers to the low oxygen concentration commonly found in tumors. This condition has been repeatedly associated with malignancy, metastasis, and resistance to therapy in cancer. Many research groups have also linked hypoxia to VM ,92,93,94Studies have shown that hypoxia promotes VM through different signaling pathways. For example, reactive oxygen species (ROS)-mediated stabilization of HIF1α activates the met proto-oncogene, inducing tube formation on matrigel in melanoma cells . MoreoveThe importance of non-cancer cells within the tumor stroma is also gaining attention in the study of VM. Tumor-Associated Macrophages (TAMs) seem to promote VM formation in glioblastoma multiforme by increasing the expression of cyclooxygenase 2 in tumor cells . Cancer-The endothelium plays a crucial role in regulating vascular permeability by utilizing proteins, plasma, and circulating cells. The specific function of controlling cell permeability is governed by both transcellular and paracellular pathways ,108. TheOne study, which was published in 2014, has revealed that the Y658 residue of VE-cadherin can be phosphorylated by FAK in in vitro and in vivo models of ECs associated with tumor cells, thus identifying that FAK plays a pivotal role in the dynamics of cell permeabilization in the metastatic tumor endothelium . On the Vessel formation  has produced an exciting point for the scientific community in the last decade, recently following this enigmatic paradigm in tumor vessel formation, several seminal articles ,124,125 Further understanding of the distinct signaling functions of VE-cadherin outside of its role in ECs is necessary to comprehend its impact on tumor cell biology and its association with hostile/VM development.Special attention should be paid to the identification of tumor cell precursors committed to the acquisition of the VM phenotype/VE-cadherin expression and the interactome linking VE-cadherin to cell trans-differentiation.Consider the application of new therapeutic agents to target VM pathways related to vessel co-option formation (integrin and other adhesion molecules) with “classical” anti-angiogenic agents.


In recent years, efforts have been made to identify new anti-cancer therapies. Various types of nanomaterials, including silver nanoparticles (AgNPs), are being considered as an option. In addition to its well-known antibacterial activity, AgNPs exhibit cytotoxic potential in both physiological and cancer cells by inducing stress-mediated autophagy and apoptotic cell death. A rapidly growing collection of data suggests that the proper regulation of autophagic machinery may provide an efficient tool for suppressing the development of cancer. In this light, AgNPs have emerged as a potential anti-cancer agent to support therapy of the disease. This review summarizes current data indicating the dual role of AgNP-induced autophagy and highlights factors that may influence its protective vs. its toxic potential. It also stresses that our understanding of the cellular and molecular mechanisms of autophagy machinery in cancer cells, as well as AgNP-triggered autophagy in both normal and diseased cells, remains insufficient. The general toxicity of nanomaterials (NMs), including AgNP-induced toxicity, has been previously described, and underlying molecular mechanisms, such as oxidative stress, apoptotic/necrotic cell death, and autophagy, have been discussed ,2,3. Autophagy has been characterized as a self-degrading catabolic process that utilizes cytoplasmic macromolecules and damaged organelles to recover energetic substrates in cells in order to adapt to stressful conditions . The impIn addition to being described in terms of nanotoxicity, autophagy has been linked to various pathological conditions, including cancer ,20. DysrIn recent decades, considerable efforts have been made to search for new anti-cancer therapies. Various types of nanomaterials, including AgNPs, are being considered as an option . The theThe anti-cancer therapeutic potential of AgNPs may be based on the induction of cell death via several mechanisms. After their uptake by endocytosis-related mechanisms, AgNPs accumulate in lysosomes, the acidic environment of which facilitates the release of silver ions from their surfaces. Both forms, particulate and ionic, interact with mitochondria, leading to the formation of reactive oxygen species (ROS) and consequently oxidative stress (OS), which activates cellular pathways leading to cell death. ROS interact with genomic DNA in tumor cells to induce DNA damage and activate the tumor suppressor P53 and the P53-dependent apoptotic pathway. Mitochondria targeted by AgNPs lose their membrane potential and become damaged. Cytochrome c, released from damaged mitochondria into the cytoplasm, triggers the classic apoptotic pathway. Moreover, AgNP-induced ROS are capable of inducing endoplasmic reticulum (ER) stress and sustained autophagy, both of which may result in apoptosis and/or autophagic cell death (reviewed in ). To advance the current knowledge of the therapeutic potential of AgNPs, this review highlights autophagy as one of the biochemical mechanisms of nanotoxicity and describes the role of AgNP-induced autophagy in cell survival or death. It also provides insights into previous research on AgNP-induced autophagy to establish the determinants of its toxic/protective profile in the cell, which may be useful for the development of AgNP-based strategies in cancer treatment. This review also concludes that many critical issues relating to the use of AgNPs in such an onco-therapeutic approach require clarification.A search of databases, such as PubMed and Scopus, was conducted to extract relevant data. Keywords for database searches included the following: metal nanoparticles and autophagy, AgNPs toxicity, AgNPs and autophagy, cancer and autophagy, and AgNPs and cancer therapy. Experimental and review articles on AgNP-induced autophagy in various cell types and in vivo models were included. Studies on nanoparticles other than AgNPs were excluded. The proper function of cells significantly depends on the maintenance and renewal of the entire proteome. The ubiquitin-proteasomal system and the autophagy-lysosomal system are cellular degradation systems which act to ensure proper cellular operation. In eukaryotic organisms, a lysosomal pathway is represented by autophagy which is triggered by the cell under stressful conditions. By the degradation of misfolded proteins, damaged organelles, and cytosolic components in autophagolysosomes, this multi-step complex mechanism supplements energy for essential cellular processes in order to increase metabolic activity and maintain cellular homeostasis . The ultrastructural features indicating the induction of autophagy in the cell are isolation membranes created in the cytoplasm. These double-membraned structures are referred to as phagophores and are generated from various cellular sources, such as the endoplasmic reticulum (ER), plasma membrane, or outer mitochondrial membrane . TheAutophagy, also referred to as macroautophagy, is generally considered to be a protective mechanism which is activated to allow the cell to survive under various stressful stimuli, including nutrient or energy deprivation, endoplasmic reticulum (ER) stress, hypoxia, immune signals, redox stress, and mitochondrial damage, each of which may stimulate autophagy through diverse signaling pathways which have been reviewed in detail ,25. To pMechanistically related to ER stress, autophagy is potently activated downstream of the cell’s stress defense mechanism, which is known as the unfolded protein response (UPR) to counteract ER stress . This ceThe UPR-mediated adaptive response increases the autophagy process and associated protein degradation in order to promote the clearance of damaged proteins . The uprUnder stress conditions, the cell initially triggers defense mechanisms that help to adapt to the stress. The cell fate is then determined according to the stress conditions. Autophagy is generally considered as a pro-survival mechanism. When upregulated, autophagy increases catabolism and the recycling of damaged components, thereby sustaining cell homeostasis. When the process of autophagy activation dangerously increases beyond a critical threshold, the cell can be directed to the apoptotic pathway. Stress-adaptive autophagy or, alternatively, apoptosis, can be triggered by common upstream signals . AlternaCurrently, the dominant view is that basal autophagy is a physiologically important mechanism, induced by the cell for beneficial effects. The upregulation or dysfunction of this process is closely related to aging and various disease conditions. Even then, the autophagy may be protective to some extent . As outlined above, the inability of the cell to properly regulate autophagy is associated with aging and is also implicated in the pathogenesis of various disorders, such as neurodegenerative diseases, type 2 diabetes, Crohn’s disease, and cancer ,20,27. TIn a normal cell, autophagy is an important protective mechanism that prevents the transition into a cancer-initiating cell by maintaining cell homeostasis through the removal of oncogenic protein substrates, toxic unfolded proteins, and damaged organelles . The dysStudies indicate that increased autophagy in cancer cells helps them to overcome stressful conditions, such as hypoxia and nutrient deprivation inside the tumor, facilitating their survival and growth . Among oHowever, increasing evidence suggests that the role of autophagy in cancer is more complex . In an eAutophagy can increase tumor growth and survival in different ways, including support of the metabolic adaptation of cancer cells and assisting the escape of immune system effects via the degradation of major histocompatibility complex class I (MHC-I) . Tumor sThe role of autophagy in cancer development and progression still raises a number of questions . It appeThe activation of autophagy processes has been previously reported to be a common mechanism of toxicity induced by various nanomaterials including AgNPs ,5,45. ThThe autophagy induced by AgNPs in vitro is typically characterized by enhanced autophagosome formation and the presence of autophagic vacuoles containing partially degraded cytoplasmic material as identified by transmission electron microscopy (TEM). For instance, in the AgNP-treated HT22 cell line which is derived from primary-cultured murine hippocampal neurons, typical autophagic vacuoles were found that included double-membrane phagophores, autophagosomes, and autolysosomes with cytoplasmic materials inside . SimilarIn fluorescence microscopy studies, numerous acidic vesicles known as acidic vesicular organelles (AVOs) were observed in the perinuclear region of the cytoplasm of AgNP-treated cells in a significantly higher percentage compared to untreated cells . MonodanSimilar to the results of in vitro studies, an ultrastructural analysis of liver tissue obtained from rats exposed to a single dose of AgNPs (500 mg/mg b.w.) revealed double-membrane autophagosomes with engulfed damaged organelles and autolysosomes containing significant amounts of cellular debris . MembranThere is a close relationship between autophagy and mitochondria, which undergo morphological and molecular remodeling of their shape, form, and biocomposition in response to stress. Mitochondrial fragmentation and the depolarization of mitochondrial membranes are major factors that trigger the process of autophagy, which is specifically referred to as mitophagy . InteresIn addition to specific morphological characteristics, the upregulation of molecular markers has also confirmed the presence of AgNP-induced autophagy in vivo. The overexpression of proteins such as beclin 1 and LC3-II, which are involved in the formation of autophagosomes in the early stages of autophagy, was found in the brains of AgNP-exposed adult rats . Also, tAn important feature of autophagy induced by AgNPs is defective flux associated with the blockade of the last step of this process, which is the fusion of the autophagosome with the lysosome and the subsequent degradation of cellular debris. This mechanism is not unique to AgNPs but has also been demonstrated for other types of nanoparticles, such as graphene oxide quantum dots  and siliExisting data indicate that AgNPs are taken up into various cells and accumulate in the cellular lysosomal compartment. Lysosomal vesicles containing nanoparticle aggregates have been shown to exist in vitro in various cells such as non-cancerous HC11 cells , cancer-The overloading of lysosomes with endocytosed AgNPs can result in the permeabilization of the lysosomal membrane, internal alkalinization, and inactivation of lysosomal enzymes, ultimately leading to lysosomal dysfunction. It has been suggested that lysosomal impairment is the primary cause of the AgNP-induced blockade of autophagic flux . MoreoveRegarding AgNPs, their presence in the lysosomal compartment leads to the disruption of lysosomal functions followed by the blockade of induced autophagy ,46 and dMorphologically, the disruption of lysosomal trafficking and fusion results in the accumulation of autophagic and lysosomal vacuoles inside the cell. In turn, one of the molecular markers of autophagic flux is p62 protein, also referred to as sequestosome 1 (SQSTM1), which is a ubiquitin-binding scaffold protein that links ubiquitinated proteins to the autophagic machinery to enable their degradation in the lysosomes. Since this protein is degraded by autophagy, its level decreases after the induction of autophagy, while it accumulates inside the cell during the inhibition of autophagy [AgNPs have been shown to block the degradation of the autophagy substrate p62 and to induce the accumulation of autophagosomes in monocytic THP-1 cells, as well as to produce lysosomal alkalization and the destabilization of the lysosomal membrane. The blockade of AgNP-induced autophagy and lysosome dysfunction thus leads to the inhibition of the differentiation of monocytes into macrophages . IncreasIn animal models of exposure, some markers of autophagy blockade have been reported. The expression of Rab7, a protein involved in the process of autophagosome maturation and autophagolysosome formation , was notIt is worth noting that a defective autophagic flux deprived of the last step of lysosomal degradation of cellular remnants has been linked to aging and certain disorders ,64. TherDysfunctional autophagy, defined as massive autophagy induction, dysregulation, or the blockade of autophagic flux, is recognized as a potential mechanism of cell death by apoptosis or ACD. Although autophagy often accompanies cell death and there is crosstalk between autophagy and other cell death pathways, the mechanisms underlying autophagy-induced cell death are not clearly defined .Certainly, under the stressful conditions of AgNP exposure, autophagy is primarily induced by the cell as a defense mechanism. However, the reports regarding AgNP-induced autophagic blockade raise a question about the effectiveness of this primarily protective mechanism, as well as to what extent the cell death observed in exposed cells is the primary effect of AgNPs acting via other molecular mechanisms. There is also the question of the extent to which cell death is a result of an ineffective autophagy process. A series of in vitro and in vivo studies have been conducted over the last few years on the molecular mechanisms of AgNP-induced nanotoxicity. It has been reported that exposure to AgNPs results in the disruption of mitochondria ,65, and Autophagy triggered by exposure to AgNPs may reflect a stress-adaptive response induced by the cell against nanoparticle-induced harmful effects, such as the efficient removal of oxidatively damaged proteins and/or organelles, or, alternatively, may be deleterious itself, increasing cellular dysfunction and leading to the cell death by crosstalk with the apoptotic machinery. Experimental studies have provided evidence supporting both of these mechanisms.Results of in vitro studies indicate that in parallel with autophagy, AgNPs can further trigger apoptosis in the hippocampal neuronal cell line HT22 by upregulating caspase-3 and the pro-apoptotic Bax protein simultaneously with the downregulation of the anti-apoptotic Bcl-2 protein. Moreover, AgNP-induced cytotoxicity was found to be mediated by both autophagy and apoptosis via the PI3K/AKT/mTOR signaling pathway . Also, iIn vivo studies of the brain tissue of adult AgNP-exposed rats have shown that autophagy is linked to synaptic degeneration as indicated by ultrastructural and molecular markers . The ultIn turn, autophagy of a protective nature has been shown to counteract AgNP-induced cell death in a mouse mammary epithelial cell line (HC11) by acting via an Akt/AMPK/mTOR pathway associated with cellular oxidative stress and mitochondrial injury . SimilarA pro-survival effect of ER stress-related autophagy has been also reported in the brain tissue of rats subjected to a low dose of AgNPs ). This sThe overexpression of the C/EBP Homologous Protein (CHOP), another molecule downstream UPR pathway, was also identified in AgNP-exposed animals, indicating the pro-apoptotic output of ER-stress-induced UPR. However, a microscopic analysis did not confirm the neuronal death via the apoptotic pathway . As reviThe analysis of The vast majority of in vitro studies using cancer-derived cell lines indicate that AgNP-induced autophagy leads to cytotoxic effects. Cytotoxicity was observed among other effects in PANC-1 adenocarcinoma pancreatic cancer cells as a result of stimulated apoptotic and autophagic cell death. In PANC-1 cells, AgNPs significantly induce increased levels of the tumor suppressor p53 protein, an increased ratio of pro-apoptotic Bax/anti-apoptotic Bcl-2 proteins, as well as increased levels of necroptosis- and autophagy-related proteins: RIP-1, RIP-3, MLKL, and LC3-II . Damage Interestingly, in parallel with the initiation of cell-death, AgNP-induced autophagy can also protect cancer cells from nanotoxicity as described for normal cells . Support2+/CaMKKβ/AMPK/mTOR pathway. The results of the study by Jeong et al. [Similarly, autophagy induced in human OS cells and huh7 hepatocellular carcinoma has been shown to function as a pro-survival strategy in cancer cells . The biog et al.  suggest The key mediator of Ag NPs-induced cytoprotective autophagy may be TFEB. Autophagy induced by AgNPs in HeLa cells was preceded by the translocation of this factor to the nucleus. The downregulation of TFEB inhibited the induction of autophagy and increased HeLa cell death under AgNP-exposure .Collected data indicate that autophagy induced under AgNP exposure is not always cytotoxic and the possibility of a dual role of the autophagic mechanism in both normal and cancer cells should be considered .Although a series of studies on AgNP-induced autophagy point to its cytotoxic potential, several in vitro and in vivo studies provide evidence for the protective nature of this mechanism. Therefore, the question is: what are the determinants of the opposite profiles of AgNP-induced autophagy? Since this issue is important in the context of the therapeutic use of AgNPs in cancer treatment, this review attempts to collect and discuss the potential biological factors and NP-related factors that may influence the fate of cells in which autophagic processes have been initiated as a result of exposure to AgNPs. The results of the in vitro studies indicate that the concentration of AgNPs is an important factor. In human THP-1 monocytes, AgNPs (15 nm) were found to induce different signatures of ER stress markers in a concentration-dependent manner. Low (10 μg/mL) concentrations of AgNPs induce an ER stress response but not cell death, whereas higher concentrations (25 μg/mL) result in an atypical ER stress response associated with ATF-6 degradation and pyroptotic cell death (an inflammatory form of programmed cell death) through NLRP-3 inflammasome activation . The indHowever, other investigations have contradicted the above-mentioned results. AgNPs in a low concentration range of 2–15 μg/mL were found to activate PARP and caspase-3 in mouse embryonic fibroblasts  and in HThe summary of the data prepared for this review  suggests50 = 26.81 μg/mL) [In addition to the concentration range, the nanoparticle-activated autophagic effects appear to be dependent on the dispersity, size, charge, and surface chemistry of nanoparticles . Higher1 μg/mL) . Time de1 μg/mL) .In vivo studies using animal models of prolonged exposure to AgNPs have been rare but quite clearly indicate a relationship between AgNP concentration and autophagy-related consequences in tissues of exposed animals. The time course of interrelated changes in markers of energy metabolism (ATP), autophagy (LC3-II), and apoptosis (caspase-3) indicate that, although autophagy is induced early in the liver tissue of rats exposed to a high dose of AgNPs (500 mg/kg b.w.), it fails to preserve energetic homeostasis in hepatocytes and leads to apoptosis with impaired organ function over time . On the It has been assumed that the induction of autophagy by AgNPs in cancer cells is a dynamic process that is strongly connected with other cellular processes, such as endocytosis. As a result, it can be difficult to simply categorize autophagy as protective or toxic . AccordiMoreover, the biology of the cancer and its genetic profile may also be of significance, as the human OS cell line was more resistant to AgNPs than the hepatocellular carcinoma (HCC) cell line . SimilarThe individual sensitivity of a cancer cell line to the toxic impact of AgNPs can depend on their uptake efficiency by the mechanism of endocytosis, which may be different in various cancers . Data suThe currently available data summarized in this review indicate that NP-related factors such as size, concentration, and dispersity have significant influences on autophagy-related cellular effects. The cell type  and the condition of the cell  may be another important factor influencing AgNP-cell interactions and determining the final outcome of AgNP-induced autophagy .Accumulating evidence indicates the involvement of autophagy in the pathomechanisms of various diseases and suggests that the modulation of the regulatory molecules of autophagic machinery may allow us to influence the course of the disease.Recent studies indicate that metallic nanoparticles are capable of selective overstimulation of autophagy and mitophagy in cancer cells, with the vast majority of nanoparticles inducing death-promoting autophagy . On the Both the unique architecture of the tumor vasculature with a fenestrated endothelial layer and impaired lymphatic drainage facilitate the penetration and accumulation of nano-materials within cancerous tissues. AgNPs can passively penetrate the tumor tissue, accumulating inside in high concentrations via a mechanism known as the enhanced permeability and retention effect (EPR), which is optimized by the shape, size, and functionalization of the surface . Active The high anti-cancer potential of AgNPs has been previously reported, which is based on various toxic mechanisms (for a review, see . One of Cancer cells are characterized by higher sensitivity to oxidative stress compared to healthy cells, and due to their rapid metabolism and intensive proliferation, they require high levels of ATP . These fAnother important issue is that the mechanisms and extent of the adaptation of cancer cells to autophagy inhibition have not yet been determined . It is kAnother fundamental question in light of the potential use of AgNPs in cancer therapy, is whether the AgNP-induced autophagy pathway will provide protective or cytotoxic functions in transformed cells where the dysregulation of autophagy is an indicative feature. Furthermore, the well-known toxic potential of AgNPs towards all cells and not just cancerous cells, poses the question of the biocompatibility of AgNPs in clinical applications. This question is more important in light of the evidence described in the current review, which indicates that rather high concentrations of AgNPs are effective in inducing death-promoting autophagy. Therefore, it is presumed that the local application of AgNPs to the tumor should be considered rather than a systemic administration, which, however, would limit the use of AgNPs in supporting anti-cancer therapy.The data collected and discussed in this review clearly show that autophagy is a major molecular mechanism induced upon the exposure to AgNPs in both normal and cancerous cells. This collection of findings illustrates the dichotomic nature of AgNP-induced autophagy, which can protect cells from nanotoxicity and execute cell death. Unfortunately, the current evidence is insufficient to characterize the conditions defining the cytotoxic but not cytoprotective effects of AgNP-induced autophagy in cells, particularly those transformed oncologically. It is suspected that several physico-chemical characteristics of AgNPs, as well as the tumor type, may be important factors influencing cell survival or death programs during autophagy, but the evidence remains insufficient.The significant potential of using AgNPs as inducers of autophagic cell death in oncological therapy cannot overshadow the many unknowns and gaps in our knowledge about the mechanisms of this process. In vivo evidence of the anticancer efficacy of AgNPs is unavailable, and therefore, animal models of cancer exposed to AgNPs are required and warrant profound studies. This is an extremely important issue, because research on autophagy machinery should be extended to interactions of AgNPs with the entire tumor microenvironment and not limited to a single cell layer in mechanistic studies.In conclusion, a better understanding of the molecular mechanisms of autophagy in pathological settings such as AgNP toxicity and in oncological diseases is now a fundamental requirement that should precede the implementation of AgNP-induced autophagy as a safe strategy supporting the treatment of oncological diseases. In particular, the interplay between autophagy and AgNP-mediated cell death should be better explored in cancerous cells in order to identify and define the determinants of the expected therapeutic outcome. The most important area of research with respect to autophagy as a novel molecular target for therapeutic intervention using AgNPs is the development of animal models of cancer in which the advantage of anti-cancer activity and the disadvantage of AgNP cytotoxicity can be examined in detail.