Neurocardiology is an emerging field that studies the interaction between the brain and the heart, namely the effects of heart injury on the brain and the effects of brain damage on the heart. Acute ischemic stroke has long been known to induce heart damage. Most post-stroke deaths are attributed to nerve damage, and cardiac complications are the second leading cause of death after stroke. In clinical practice, the proper interpretation and optimal treatment for the patients with heart injury complicated by acute ischemic stroke, recently described as stroke-heart syndrome (SHS), are still unclear. Here, We describe a wide range of clinical features and potential mechanisms of cardiac complications after ischemic stroke. Autonomic dysfunction, microvascular dysfunction and coronary ischemia process are interdependent and play an important role in the process of cardiac complications caused by stroke. As a unique comprehensive view, SHS can provide theoretical basis for research and clinical diagnosis and treatment. Cardiovascular and cerebrovascular diseases are the leading cause of death and disability worldwide and are increasing yearly. According to statistics, from 1990 to 2019, the incidence of stroke was increased by 70%, the prevalence increased by 85%, the mortality rate increased by 43%, and the disability-adjusted life years (DALYs) increased by 32%. The latest statistics for 2019 indicated that ischemic stroke accounts for 62.4% of all strokes . Ischemi. Recently, the incidence of heart injury due to ischemic stroke has become increasingly significant, and the heart injury complicated by acute ischemic stroke has been described as stroke-heart syndrome (SHS) (Brain-heart syndrome was firstly reported in 1947 by me (SHS) . Traditime (SHS) , includime (SHS) : (1) iscme (SHS) . The conme (SHS)  was propme (SHS) .The concept of SHS  implies that a cardiac function disturbance occurs after the appearance of a neurological deficit, and the cardiac dysfunction occurs in the absence of significant underlying cardiac diseases or disorders. Evidence has shown that the frequency and severity of SHS reach the peak within the first 3 days after the event  and thatStudies have found that pathological ECG changes may occur in 70 to 90 percent of stroke patients with previous ECG showing Q-wave or left ventricular hypertrophy . In a coCurrent guidelines recommend measurement of myocardial markers at the time of admission in patients with ischemic stroke  because Cardiac complications after stroke are not limited to myocardial injury, but the occurrence of left ventricular dysfunction after stroke is also associated with ischemic stroke. Decreased left ventricular ejection fraction and diastolic dysfunction have been widely reported in all types of strokes, but the lack of knowledge of cardiac baseline status before stroke limits the ability to estimate its true incidence rate . Left veIn summary, the current clinical data and research results show that there may be a certain causal relationship between cardiac complications after stroke. Cardiac complications caused by acute ischemic stroke, including arrhythmias, myocardial injury (mainly manifested as elevated cTn) and cardiac dysfunction are not directly related, but they can occur independently or simultaneously. Therefore, timely diagnosis and treatment of cardiac symptoms after stroke are essential to improve clinical management and reduce mortality.Cardiac complications are one of the main challenges in the treatment of acute ischemic stroke, and stroke-heart syndrome is receiving increasing clinical attention. In randomized controlled trials, approximately 20 percent of patients with ischemic stroke reported serious cardiac adverse events mainly within the first 3 days after symptom development, including acute coronary syndrome, heart failure, and arrhythmias . SICFAILIt is controversial whether cardiac complications can affect patient prognosis. It has been found that cardiac troponin only occurs in a small number of patients with acute ischemic stroke, and cardiac troponin does not affect clinical outcomes if other risk factors are considered together . Some reCurrently, there are no guidelines on how to assess, treat, or follow up ischemic stroke patients with post-stroke heart injury from a cardiac perspective. However, most stroke guidelines do provide recommendations for post-stroke cardiac testing, including but not limited to routine ECG, 24-h Holter ECG, and echocardiography . These tSHS is a complex pathological process, it can occur in patients with or without underlying cardiac disease, in severe cases, it can lead to death. Combined with the evidence of clinical studies and animal experiments, structural and functional disorders of central autonomic neural networks is the currently accepted mechanism of SHS. In addition, the immune response after stroke produced by the spleen or secondary systemic inflammatory response may also be involved in SHS. At present, some studies suggest that intestinal microbiota dysregulation and exosome release after stroke may also be involved in the pathological process of SHS .Current data strongly supported stroke-induced stress responses to overactivation of central autonomic network structure and dysfunction involving the autonomic nervous system and the hypothalamic–pituitary–adrenal axis. Acute ischemic stroke causes acute lesions of the central autonomic neural network, resulting in acute disturbance of the sympathetic and parasympathetic nerves from the heart. Cardiac sympathetic nerves over-release catecholamines, followed by excessive activation of calcium channels, excessive contraction of cardiac muscle ganglia, weakening of muscle relaxation, and metabolic disorders . One stuThe blood–brain barrier consists of endothelial cells, astrocyte endings, pericytes, and the posterior basement membrane, which is located at the core of the neurovascular system. The blood–brain barrier acts as a dynamic interface between the brain and the circulatory system, limiting the entry of potential neurotoxins as well as microscopic and hydrophilic molecules. The destruction of the blood–brain barrier is the main step in the pathophysiological cascade after stroke, and the increased permeability helps inflammatory factors enter the brain, aggravating the ischemia-induced inflammatory response in the brain. Meanwhile, the destruction of the blood–brain barrier causes brain-derived antigens and extracellular vesicles of damaged brain cells to enter the blood and mix with the surrounding immune cells, and ultimately reach the target organ through blood circulation to cause damage to the surrounding tissues . S100B iThe activation of the immune system that causes inflammation after stroke is an important factor in stroke progression. Although cytokines are released acutely after stroke, the increase in plasma levels is only temporary, lasting for a few hours to a few days. Meanwhile, the myocardial remodeling continues despite the short duration of this systemic inflammatory response . NeuronaAs we know more and more about the relationship between the human microbiome and various diseases, it has been found that there may be interactions between the gut microbiota (gut-heart axis) and between the intestinal flora and the central nervous system (brain-gut axis) . In patiMany of the circulating microvesicles in the blood come from cells that directly contact the blood, such as platelets and endothelial cells. Elevated circulating microvesicle levels in patients with ischemic stroke are associated with poor clinical prognosis . The maiIn summary, we describe the broad clinical features and potential mechanisms of cardiac complications after ischemic stroke. Underlying cardiovascular disease and underlying vascular or stroke risk factors increase the incidence of the cardiac syndrome and exacerbate the severity. From the perspective of the mechanism of brain-heart syndrome, autonomic dysfunction, microvascular dysfunction, and coronary ischemic processes are interdependent and play essential roles in the process of cardiac complications caused by stroke. The unique but comprehensive concept of stroke-heart syndrome potentially provides information for clinical decision-making, and further data are needed to provide evidence-based advice on the screening, diagnosis, prevention, and treatment of cardiac complications after stroke.MW collected and reviewed the data. YP was responsible for the review and revision. All authors contributed to the article and approved the submitted version.This work was supported by Funding from Young Talent Development plan of Changzhou Health Commission (CZQM2020034 and CZQM2020004), Young talents Science and technology project of Changzhou Health Commission (QN201913), and the National Natural Science Fund (81701584).The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Obstructive lung diseases are characterized by obstruction to airflow, inflamed and easily collapsible airways, and difficulties in exhaling, with a socio-economic burden in terms of medical visits and hospitalizations.Even though the recent progress of scientific knowledge and the availability of new therapeutic and diagnostic tools have improved the management of obstructive diseases, they remain a foremost public health issue and a challenge for physicians.Consequently, asthma and COPD are hot topics, as their high prevalence, morbidity, and mortality create many clinical challenges. In this Special Issue, we aimed to provide a rounded insight to the pathophysiology, diagnosis, and treatment of obstructive lung diseases.A better understanding of pathophysiology of obstructive lung diseases is absolutely required. Interestingly, it is known that some forms of severe asthma and COPD may present similar characteristics and are difficult to distinguish. In this regard, Obojski et al. evaluated the intensity of the remodeling of the bronchi and the emphysema qualities of the lungs in patients with severe asthma with persistent airflow limitation (SA-PAL), COPD and healthy volunteers by quantitative computed tomography (QCT), showing that emphysema does not only occur in COPD, but also in SA–PAL .Focusing on the development of emphysema, in their review, Jung et al. summarized the scope, risks, and limitations of current standard-of-care techniques including lung imaging and lung function and emerging diagnostics and monitoring tools , evidencing how regional lung function monitoring and the prediction of exacerbations and/or disease onset are fundamental to establish timely interventions to limit COPD progression to severe emphysema .Acute exacerbations of COPD (AECOPD) are major events with potential serious consequences. Notably, AECOPD represents the leading cause of hospitalization and death in COPD patients. Neutrophil-to-lymphocyte ratio (NLR) is a hematological parameter that is an independent predictor of outcomes in stable COPD, although its prognostic role in patients with AECOPD is still matter of debate. Zinellu et al.  conducteIt is now well known that COPD is associated with significant systemic abnormalities such as dysfunction of skeletal muscles, which affects motor function and limits the ability to carry out habitual activities of daily life. Casabona et al. used the spectral analysis of the electromyographic signal as a non-invasive approach to investigate the fiber muscle composition in COPD patients, reporting a good correlation between the changes in frequency–domain features and disease severity, thus suggesting that electromyography spectrum analysis applied to a non-fatigable motor task might be suitable for monitoring the progression of disease severity and the effects of physical rehabilitation programs . In lineTaken together, these studies will help physicians in improving their understanding of obstructive lung diseases with up-to-date data, which might be of inspiration for forthcoming investigations.


Cell-to-cell communication is a fundamental process of bacteria to exert communal behaviors. Sputum samples of patients with cystic fibrosis have often been observed with extensive mycobacterial genetic diversity. The emergence of heterogenic mycobacterial populations is observed due to subtle changes in their morphology, gene expression level, and distributive conjugal transfer (DCT). Since each subgroup of mycobacteria has different hetero-resistance, they are refractory against several antibiotics. Such genetically diverse mycobacteria have to communicate with each other to subvert the host immune system. However, it is still a mystery how such heterogeneous strains exhibit synchronous behaviors for the production of quorum sensing (QS) traits, such as biofilms, siderophores, and virulence proteins. Mycobacteria are characterized by division of labor, where distinct sub-clonal populations contribute to the production of QS traits while exchanging complimentary products at the community level. Thus, active mycobacterial cells ensure the persistence of other heterogenic clonal populations through cooperative behaviors. Additionally, mycobacteria are likely to establish communication with neighboring cells in a contact-independent manner through QS signals. Hence, this review is intended to discuss our current knowledge of mycobacterial communication. Understanding mycobacterial communication could provide a promising opportunity to develop drugs to target key pathways of mycobacteria. Iron-deprived M. abscessus forms clumps through tight cell-to-cell interaction that enables them to kill macrophages efficiently, whereas the smooth morphotype remains as isolated bacilli and fails to kill macrophages  that differs from classical esxUT transcripts are upregulated in the recipient cells, whereas such induction of esx4 transcripts is not observed in the monoculture of either donor or recipient, which gives the notion that ESX-4 is also critically involved in inter-bacterial interaction  does not phosphorylate GroEL1 of M. smegmatis (GroEL1Msm), but PknFMsm phosphorylates GroEL1 of Mtb (GroEL1Mtb) in vitro, suggesting that STPKs might involve in the crosstalk between different mycobacterial species   stage 2 model, it was found that Mtb increases the expression of Pseudomonas aeruginosa and Aspergillus spp. were found in great abundance in the sputum samples of CF patients who had been reported to have NTM infections  that degrades phenazines, thereby inhibiting the pyocyanin-dependent release of extracellular DNA  modulates the morphotypes and growth under in vitro conditions ppGpp that regulates several processes, including biofilm, virulence, survival, and persistence  expression relied on bacterial density, reflecting the possible existence of the QS mechanism  rather than producing all essential molecules to reduce their metabolic burden. The fact is that cell-to-cell communication is an integral part of the evolution of mycobacteria and the increase of rich diversity. While considering the importance of inter-bacterial communication for the exchange of genetic material, many fascinating questions are also raised. Whether mycobacteria exchange any other cytoplasmic molecules, such as proteins, RNAs, toxins, nutrients, and plasmids, with the neighboring cells? The existence of multiple subsets of the mycobacterial population at the site of infection, intriguing to speculate that one subset of cells confers resistance to certain antibiotics, while other subsets of cells produce some other antibiotic resistant-conferring proteins. The frequent incidence of failures in antibiotic therapy might be due to the exchange of those resistance-conferring molecules among the population. However, the coexistence of both subtypes benefits the entire population during antibiotic treatment. The exchange of antibiotic resistance-conferring proteins/mRNAs between different genotypes of B.subtilis has been well-documented . Key regulatory proteins of QS mechanisms could be used as a target to control pathogenesis .The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Sepsis-associated encephalopathy (SAE), the most popular cause of coma in the intensive care unit (ICU), is the diffuse cerebral damage caused by the septic challenge. SAE is closely related to high mortality and extended cognitive impairment in patients in septic shock. At present, many studies have demonstrated that SAE might be mainly associated with blood–brain barrier damage, abnormal neurotransmitter secretion, oxidative stress, and neuroimmune dysfunction. Nevertheless, the precise mechanism which initiates SAE and contributes to the long-term cognitive impairment remains largely unknown. Recently, a growing body of evidence has indicated that there is close crosstalk between SAE and peripheral immunity. The excessive migration of peripheral immune cells to the brain, the activation of glia, and resulting dysfunction of the central immune system are the main causes of septic nerve damage. This study reviews the update on the pathogenesis of septic encephalopathy, focusing on the over-activation of immune cells in the central nervous system (CNS) and the “neurocentral–endocrine–immune” networks in the development of SAE, aiming to further understand the potential mechanism of SAE and provide new targets for diagnosis and management of septic complications. Sepsis is a common complication in patients with burns or wound injury, infection, shock, and major surgery. It is a dysregulated host response induced by severe infection, which may develop into multiple organ failure and eventually lead to death. In 2020, Rudd et al.  analyzedThe multiple organ dysfunction induced by sepsis results in an imbalance of the immune response, which may aggravate the clinical symptoms of sepsis. As the primary organ affected by inflammation in sepsis, the brain is not only critically involved in immune regulatory response but also vulnerable to injury, which may lead to sepsis-associated encephalopathy (SAE). Of note, SAE is a diffuse brain dysfunction secondary to sepsis, with an incidence of more than 70% in patients in septic shock, especially in the elderly people, neonates, and patients with a chronic illness . SAE canWith marked advancements in neuroscience, the potential role of the neuroendocrine–immune network in the immune response of sepsis has been gradually revealed. It is documented that circulating inflammatory mediators and hormones cause dysfunction of the central nervous system (CNS) in sepsis by inducing the activation of glia and the death of neural cells. In turn, the CNS reacts to the peripheral immune system through the neuroendocrine–immune network, which forms a feedback regulatory loop in the central–peripheral immune system. Then, the CNS triggers a neural reflex and regulates neurotransmitters, neurohormones, and cytokines produced by synapses. Meanwhile, the nervous system extends the nerve fibers to the peripheral organs, which may regulate the secretion function of internal or external secretory glands and maintain the homeostasis of the environment. The central–peripheral immune system regulates the inflammatory response mainly by the hypothalamic–pituitary–adrenal (HPA) axis and the cholinergic anti-inflammatory pathway (CAP), which cooperate to maintain a moderate immune state according to the needs of the body . For exaHere, we summarize the main physiological alterations of the brain in SAE and discuss the underlying mechanisms that might accelerate the sepsis-induced brain damage, especially focusing on the function of the neuroendocrine–immune network in the pathogenesis of SAE.SAE is regarded as a cognitive dysfunction induced by sepsis without obvious nervous system infection or structural injury. Due to the lack of a consensus definition of the SAE, the incidence of SAE varied widely among the studies. It has been reported that 8% to more than 70% of patients in septic shock in the ICU may have encephalopathy, only 19% of the patients in the ICU have a normal electroencephalogram (EEG) with alpha rhythm, and 80% of them show epileptic or abnormal EEG . The symThe severity of SAE ranges from temporary to permanent brain dysfunction. According to the recent observations of the symptoms, SAE can be divided into acute, sub-acute, or chronic types. The acute SAE can be controlled with patient improvement . It is cIt is believed that the pathophysiological factors of cerebral dysfunction secondary to sepsis mainly include neuroinflammation, blood–brain barrier (BBB) impairment, disorders of brain perfusion, alterations in neurotransmitters, and changes in neuroanatomy and cell death , 21. AmoNotably, the disorders of immune responses in the CNS are the major cause of SAE, which play key roles in the dysregulated peripheral immunity and multiple organ dysfunction syndromes (MODS) following a septic challenge. Ischemic injury, the change in the microstructure in the brain, and the neuron death contribute to the brain damage induced by the uncontrolled inflammation and the difficulty of SAE treatment.Uncontrolled neuroinflammation is a significant indicator of septic encephalopathy. During the process of sepsis, peripheral and local inflammation can induce the migration of neutrophils into the brain and activate the astrocytes and microglia –25. ThenThe progress of leukocyte recruitment includes trapping, slow rolling, adhesion to endovascular crawling, and migrating. As the hallmark of inflammation, the infiltration of neutrophils is found in the CNS at the early stage of sepsis, while few of them are observed in the normal brain. The neutrophils are induced to damage tissue sites by a variety of inflammatory mediators, including interleukins (ILs), tumor necrosis factor (TNFs), angiotensin, and the complement cascade factors –29. In tNorman et al.  reportedMicroglia accounts for 6%-18% of human brain cells . As the In normal conditions, the microglia with branched morphology is resting, which is responsible for micro-environment surveillance. After activation by pathological insults, microglia reveals quick and prominent alterations in morphology, metabolism, and function. A series of studies suggested that microglia was consistently activated in animal models and patients of sepsis , 37. ForIt has been documented that peripheral inflammation activates microglia with the help of the inflammatory mediators, the interaction between microglia and adjacent cells, and neurotransmitters . In the A series of studies have indicated that the activation of microglia in sepsis results in brain dysfunctions including delirium, memory impairment, acute brain oxidative damage, and long-term cognitive impairment by secreting a large quantity of proinflammatory cytokines, upregulating the expression of multiple enzymes and neurotransmitters, and changing the brain energy metabolism in sepsis , 43, 44.The growing evidence has proved that the difference in the microenvironment may lead to the heterogeneity of microglia. There are two kinds of activated phenotypes of microglia named M1 and M2 subpopulations, respectively. The microglia with different phenotypes show either adverse or advantageous effects on neurological function . It is wAstrocytes are of great importance to maintain the homeostasis of the brain, which is associated with BBB permeability, neurotransmitter metabolism, synapse connectivity and plasticity, and brain fluid balance . Under pThe pathological changes of astrocytes mainly include astrogliosis and astrodegeneration. It has been demonstrated that reactive astrogliosis is caused by brain injury, and the main alterations of activated astroglial cells are hypertrophic and upregulated expression of the glial fibrillary acidic protein (GFAP) and vimentin –50. The Many studies have demonstrated that ischemic injury often occurs in the brain in the setting of sepsis –61. The Strikingly, the results from the experimental models of sepsis are controversial. Several studies revealed the decreased blood perfusion distribution in animals after systemic administration of LPS, while others reported the increased CBF in cortical MCA territories after LPS challenge , 65. It Due to the reversibility of SAE, most studies on histopathology of SAE did not observe the obvious changes in deeper structures and the spinal cord of the brain . NeverthIncreasing studies have indicated that cell death is an important contributor to brain dysfunction during SAE. The apoptosis and pyroptosis of brain cells induced by inflammation are critically involved in the onset and progression of SAE.Apoptosis is a sort of regulated cell death accompanied by contraction of the cells and foam cell formation in the cell membrane. It is well accepted that mitochondria are major apoptosis-associated organelles. In the development of sepsis, mitochondrial dysfunction is found in various regions of the brain, especially in the hippocampus, which may cause the imbalance of oxygen/nitrogen reactive species, hippocampus cell apoptosis, and severe neurocognitive impairment. Elevated neuronal apoptosis is characterized by enhanced pro-apoptotic proteins, which are released from mitochondrial cleaved caspase levels. Omi/HtrA2, a serine protease in mitochondria, regulates apoptosis of hippocampus cells by translocation from mitochondria into the cytoplasm in cecal ligation and puncture (CLP)-induced sepsis . More rein vivo and in vitro , and brain-derived neurotrophic factor (BDNF)/tyrosine kinase (Trk)B during SAE. The activation of NF-κB is regarded as a central event in sepsis, which may trigger the inflammatory mediator networks. Some studies reported that the activation of NF-κB was related to increases in the mortality rate and poor clinical outcomes in sepsis. Accordingly, the inhibitors of NF-κB could attenuate LPS-induced long-term potentiation in the dentate gyrus and ischemia-induced neuronal apoptosis . Furtherin vitro –85.MAPK plays a key role in inflammation-induced apoptosis. p38 MAPK is activated in the brain accompanied by the upregulated phosphorylation of MAPKAPK2 upon sepsis. Cell apoptosis in the cortex and the hippocampus of CLP animals could be alleviated by p38 MAPK inhibitors . Zhou etPyroptosis is defined as regulated necrosis with rapid damage to the plasma membrane and the release of intracellular contents , and it The canonical signaling pathway relies on the inflammasome pre-activation. Then, the inflammasome can activate caspase-1 by the adaptor apoptosis speck-like protein, which cleaves GSDMD to form GSDMD-NT , 98. As Reciprocal interactions between the central and peripheral immune systems are regarded as crucial parts of the host's response to septic insults. When systemic inflammatory responses are induced by severe trauma or infection, the peripheral inflammatory signal is sent to the CNS. The CNS regulates immune system compensatory changes and maintains homeostasis after perception and integration of peripheral signals through sympathetic, parasympathetic, and HPA gland axial. The aberrant responses of neuroendocrine–immune networks are responsible for the immune disruption and the worse outcome during sepsis. It is well known that the neural central–endocrine–immune networks are mainly composed of HPA and CAP.Basically, the HPA axis is a classical anti-inflammatory pathway of the nervous system. Upon septic exposure, the CNS regulates the peripheral inflammatory immune response mainly through the HPA axis. Endotoxin or inflammatory mediators activate the HPA axis through the vagus nerve or humoral pathway, and the hypothalamus releases corticotropin-releasing hormone (CRH) and adrenocorticotropic hormone (ACTH), which will promote the production of glucocorticoid (GC) released by adrenal cortical cells and avoid damage and dysfunction of organs induced by excessive inflammation –103. TheThe damage to the HPA axis and the abnormal production of adrenocortical GC appear to be associated with the occurrence and development of sepsis. First, the change in the adrenal microenvironment is an important factor affecting the prognosis of sepsis. An integrated adrenal stress response is critical for the survival of patients with septic shock. Under physiological states, the cortical cells, medulla cells, and epithelial cells in the adrenal gland interact with inflammatory immune cells to form a complex adrenal microenvironment, which plays a key regulatory role in the synthesis and secretion of corticosteroids in sepsis and septic shock , 105. A The surface receptors on the adrenal cortical cells and immune cells, such as scavenger receptors, TLR2, and TLR4, are related to the dysfunction of the adrenal glands secondary to sepsis. Kanczkowski et al. found systemic but not adrenocortical-specific knockout of myeloid differentiation protein 88 (MyD88), a TLR adaptor protein, reduced adrenal inflammatory response and HPA axis activation in LPS-induced sepsis . A recenper se can induce the disorder of the corticosteroid system, which results in intractable immunosuppression together with excessive inflammation.GCs produced by the HPA axis are of great value to maintain homeostasis and protect the host from the life threat caused by sepsis . The disGR is distributed in various kinds of immune cells, e.g., DCs, myeloid cells, macrophages, T cells, and natural killer cells (NKs). It protected the mice from shock induced by LPS and CLP through the upregulation of anti-inflammatory genes, such as glucocorticoid-induced leucine zipper (GILZ), MAPK phosphatase-1 (MKP-1), and programmed death 1 (PD-1), or the inhibition of the proinflammatory genes, including STAT1, IL-1β, and IL-12, in a dimer-dependent way –118. DisRecently, several studies have indicated that GC/GR signaling pathways contribute to promoting the capacity of monocytes/macrophages to kill the various particles and bacteria , 123. InIn 2003, Tracey et al.  first foThe vagal parasympathetic fibers start from the vagus dorsal motor nucleus (DMN) and stop at the parasympathetic ganglia of the vagal plexus. The emitted postganglionic fibers are distributed in the thoracic and abdominal organs that control the activity of smooth muscles, cardiac muscles, and glands. Strikingly, the vagus nerve can regulate the generation of proinflammatory cytokines. When the vagal nerves sense the stimulation of inflammatory insults, they transmit inflammatory signals to the center neural system. At the same time, the dorsal nucleus of the vagal nerve delivers anti-inflammatory signals to the endothelial reticulate system by ganglion fibers to enhance the synthesis and release of ACh and inhibit the synthesis of proinflammatory cytokines –135.+ChAT+ T cells to initiate the synthesis of ACh, and ACh acts on the inflammatory cells expressing α7 nAChR in the spleen and suppresses the inflammatory response in the spleen  and the Key Medical Innovation Program of the Chinese People's Liberation Army (18CXZ026).The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Metabolomic is generally characterized as a comprehensive and the most copious analytical technique for the identification of targeted and untargeted metabolite diversity in a biological system. Recently, it has exponentially been used for phytochemical analysis and variability among plant metabolites, followed by chemometric analysis. Network pharmacology analysis is a computational technique used for the determination of multi-mechanistic and therapeutic evaluation of chemicals via interaction with the genomes involved in targeted or untargeted diseases. In considering the facts, the present review aims to explore the role of metabolomics and network pharmacology in the scientific validation of therapeutic claims as well as to evaluate the multi-targeted therapeutic approach of traditional Indian medicinal plants. The data was collected from different electronic scientific databases such as Google Scholar, Science Direct, ACS publication, PubMed, Springer, etc., using different keywords such as metabolomics, techniques used in metabolomics, chemometric analysis, a bioinformatic tool for drug discovery and development, network pharmacology, methodology and its role in biological evaluation of chemicals, etc. The screened articles were gathered and evaluated by different experts for their exclusion and inclusion in the final draft of the manuscript. The review findings suggest that metabolomics is one of the recent most precious and effective techniques for metabolite identification in the plant matrix. Various chemometric techniques are copiously used for metabolites discrimination analysis hence validating the unique characteristic of herbal medicines and their derived products concerning their authenticity. Network pharmacology remains the only option for the unique and effective analysis of hundreds of chemicals or metabolites via genomic interaction and thus validating the multi-mechanistic and therapeutic approach to explore the pharmacological aspects of herbal medicines for the management of the disease. Medicinal plants have been considered an essential source for drug discovery and development as they are enriched in verities of phytochemicals of different categories . Due to However, several modern analytical techniques, including chromatography, nuclear magnetic resonance (NMR), and mass spectrometry (MS), are used abundantly in the quantitative and qualitative assessment of plant metabolites. However, these techniques are much preferred with plant phytoconstituents profiling or metabolomics studies due to their high sensitivity and accuracy when coupled with effective chromatographic techniques that allow separation and characterization of the diversity of phytoconstituents present in medicinal plants . These tm/z values of metabolites are matched to reference data from mass banks, where the analysis is resumed under a defined tolerance of m/z value variability. MS data acquisition relies on the probability score between the analysis query and the reference data search. For non-targeted metabolites, the data acquisition tolerance can be in both the m/z value and the chromatographic retention time, and further, these implications are accustomed to measurements using alignment software. Advanced web-based platform analysis was established based on automated workflows ranging from processing to the extreme alignment of row data, annotation, and statistical analysis tools to enable easy access to a wide range of investigators or informatics experts [In mass spectrometric analysis,  experts ,8,9.With the advent of the gradual rise of interdisciplinary disciplines related to bioinformatics and computational biology, researchers are becoming more motivated or are shifting from single-mode to multidisciplinary and dimensional systematic research modes for traditional medical research. There are important changes from the perspective of biomolecular networks involving the role of genes in disease regulation to understand the mechanism of drug action. The purpose of using “network computational biology” is to bring about significant change or to address new challenges associated with the initial testing of drugs. Network targeting represents unique concepts that characterize the biological network of diseases underlying therapeutic targets and understand the systematic mechanism of action for one of the multi-targeted drugs primarily for conventional medicine. Thus, the principle of “network prediction of targets” has been accepted as a fundamental principle of network pharmacology ,11.Traditional Medicine (TM), characterized by individualized, multi-component, and holistic medicine, holds great potential in conceptualizing the various challenges in the system of modern health care . TraditiNetwork pharmacology (NP), a brand-new area of study, aims to explain the interactions and actions of drugs with a variety of targets. It uses technology to systematically catalog a drug molecule’s molecular interactions with a living cell . ResearcBased on the phytopharmacological evolution of metabolites, the present study is associated with exploring the mechanistic molecular role of metabolites in the treatment of various diseases, including its properties such as antimutagenic, antiulcer, antioxidant, antidiabetic, antifertility, anthelmintic, antilipolytic, etc. In the molecular-based pharmacological assessment of metabolites, the present study explores the multi-targeted therapeutic approach of traditional Indian medicinal plants in the treatment of various acute and chronic diseases .Studies were conducted according to preferred reported items/checklists from systematic reviews or statements of research articles published in national and international journals.The information was collected through a comprehensive literature search using more than five electronic databases such as Science Direct, Elsevier, Google Scholar, ACS Publications, PubMed, and Springer from databases published between 2000 and 2022 or more recently for the study. Influential information was selected for targeted and untargeted data. Modern systems of medicine and therapy for treatment, traditional systems of medicine and medicinal plants for the treatment of disease, phytochemistry, nephroprotective activity, antioxidant activity, oxidative and anti-inflammatory activity, and inflammatory stress associated with the pathophysiology of diseases, etc., were all included in the review, and the research papers checked for potentially relevant citations in the reference list. The study selection was restricted to articles in English due to the language barrier, time efficiency, and high cost of translation. For comprehensive detection of relevant studies and recapitulation of the journal’s publication history, a systematic review was conducted with the hyphenated keyword “Role of medicinal plants in the management of diseases; A systematic review”. Appropriate data were extracted and summarized as prospective information on metabolites to reach the selection process.Published reviews or research articles regarding the prevalence of diseases in national and international journals and metabolites represent a diverse group of low-molecular-weight structures, including lipids, amino acids, peptides, nucleic acids, and organic acids, that allow inclusive analysis to be combined into one.Studies such as duplicate publications, abstracts, and research published before 2000, unauthentic ethnobotanical/ethnomedicinal reports lacking study areas/localities, informant’s involvement, data of untargeted plant and disease, and non-open access journal articles or in part accessed articles were removed to avoid miscomprehension.All authors independently assessed the study through their inclusion criteria by examining the title and abstract of each record and obtaining its full text, if necessary. Study selection includes only well-indexed journal publications (research and review articles) related to diseases for trending input. The search results were screened based on the title and abstract of the identified journal articles/thesis. Furthermore, out of thousands of reports, only appropriate reports were downloaded and critically inspected to elaborate the discussion related to the preclinical and clinical evaluation of metabolomics and its exploration of multi-targeted therapeutic approaches of traditional Indian medicinal plants.We are aware of the multi-mechanistic and therapeutic action of medicinal plants and their derived products exhibited by the varieties of the metabolites present in the plant matrix, thus, alleviating several acute and chronic ailments. During this period, omics technology advancements were leveraged to create strategies for different aspects of drug research ,23. In oIt is known that medicinal plants deal with the diversity of metabolites even with different chemical or structural behavior. Furthermore, to reach perfection in exploring the phytochemistry of medicinal plants, a single analytical method does not put into their high throughput phytochemical screening . As eachBased on the above facts and assessment for metabolomic analysis helps us to unravel and even reach perfection in qualitative and quantitative phytochemical analysis of medicinal plants. Furthermore, in a single study, quantitative-based standardization of the medicinal plant needs at least four marker constituents to validate the authenticity aspects for their regulatory purpose . A systeComputational techniques have been growing and exotically contributing to drug discovery and development via assessing wide varieties of genes and their expression behavior to the chemical or bioactive principles which are involved in the pathophysiology of any ailments. Compounds and protein interaction and biomolecular accession provide a high throughput orientation to explore better pharmacological validation concerning the targeted or untargeted metabolites. Besides this approach, the one-drug/one-target/one-disease strategy for drug development is currently confronted with several difficulties in terms of sustainability, efficacy, and safety. Recently, strategies for network biology and pharmacology, respectively, have acquired recognition ,34.Network biology and polypharmacology are one of the most conventional approaches to exploring multi-mechanistic and therapeutic targets for integrating omics data and developing multitarget drugs. Hence, both approaches are combined and acknowledged as network pharmacology. This approach does not look only at the consequence of drugs in terms of the effect on both the interactome as well as the diseasome level and covers multiple interactions with multiple proteins/genes in a single time . By enabhttps://jensenlab.org/, 19 October 2022), while the type of interactors to the expanded network should remain to the Homo sapiens species only. The process is repeated till no interactors are further connected via expanding the network. No further expansion of the network represents no additional genomic information exists in the reported database. Thereafter, the statistical information of the generated network about the number of nods, edges, network density, heterogeneity, etc., is imported through a network analyzer. In one example, the constructed network with statistical summary has been depicted in In this analysis, the active molecule can be fixed or can not be fixed, which needs to be explored biologically based on the interaction of targets/genes targets that would be interacted with the molecule are completely unfixed. A random analysis is done using the software commands (Cytoscape) of the STRING app to expand the network. During this process, the number of interactors to expand the network depends on the information retrieval that exists in the database , which is a free online database that involves an n-number of genes involved in diseases. STITCH is an open-source platform for rapid analysis of the active components and the genes which are needed to be analyzed. Each component and selected gene are inserted into the STITCH platform of the Cytoscape software. It gives multiple possible matches at the fixed or optimum confidence score of 0.04 and maximum additional interactor ,36. DuriMomordica charantia in the alleviation of diabetic nephropathy. In this study, the author explored the therapeutic potential of several metabolites of Momordica charantia and reported that quercetin, ferulic acid, caffeic acid, and catechin are the potential metabolites that exhibit a significant interaction with the genes such as G6PD, MAPK1, MAPK3, NOS, PTGS2, PON1, ILs, etc. and alleviating diabetic nephropathy and its associated complications [Boerhaavia diffusa and Tinospora cordifolia against glomerulopathy, inflammation, oxidative stress, etc. The outcome of the study showed that Boerhaavia diffusa and Tinospora cordifolia contains several metabolites, such as polyphenols which poly a significant role in the alleviation of kidney disease and its associated complication via the regulation of several genomes such as CASP3, CASP7, CASP8, CASP9, MAPK1, MAPK3, TNF and TP53 involved in the several pathways AGE/RAGE pathway, signaling to interleukins, response to the inorganic substances, TNF signaling pathway, lipid localization, regulation of defense response, RAS and bradykinin pathway in COVID-19, circulatory system process, cellular response to nitrogen compounds, etc. [Previously, several studies have been reported based on the targeted and untargeted network pharmacology analysis, which revealed the multi-mechanistic and therapeutic role of various biologically active metabolites in the alleviation and treatment of diseases. In a study reported by Gautam evaluated multi-mechanistic and therapeutic potential of ications . Gaurav ds, etc. .https://www.networkanalyst.ca/, 19 October 2022), Metascape , STRING , DisGeNET , etc. outlined in Gene ontology analysis showed the multi-targeted and mechanistic approach of the targeted genes that are screened through the protein-protein network (PPI) and compound-protein interaction (CPI) network analysis. it gives information about that how genes play multi-targeted effect in pathophysiology involved in the disease via regulation of several positive and negative biological pathways. There are several platforms such as Cytoscape, network analyst  up to 24-methylene cholesterol, which is thought to be a precursor for the biosynthesis of withanolide, based on the annotation. Additionally, certain contigs associated with the enzymes used in these processes displayed differential expression [Gupta et al. evaluated functional annotation and comparative analysis of pression .Boerhaavia diffusa and Tinospora cordifolia, in the regulation of several pathways such as signaling to interleukins, response to the inorganic substances, TNF signaling pathway, lipid localization, regulation of defense response, RAS and bradykinin pathway in COVID-19, circulatory system process, cellular response to nitrogen compounds, etc. [Momordica charantia in alleviating diabetic nephropathy and its associated complications via regulation of several pathophysiological pathways such as metabolic regulation, increased uptake of glucose to the muscle, obviating insulin resistance, biochemical markers regulation, oxidative stress, and inflammation, etc. [Exploration of multi-mechanistic and therapeutic action of traditional medicines through network biology, polypharmacology and gene ontology analysis has been increased exponentially. Vadivu et al. reported that mapping genes involved in the diseases with standardized ontology analysis gives more improvement in analyzing the biological performance of the medicinal plants and their therapeutic options . Severalds, etc. . Gautam on, etc. .Physostigma venenosum potential targets were identified using a combination of network pharmacology and virtual reverse pharmacology techniques for the treatment of vascular dementia (VaD). This work used PASS prediction to find known VaD-related targets interacting with phytomolecules. More than 200 proteins connected to VaD were studied since its expression has increased. In order to broaden the scope of the search, an extra 34 genes were chosen. It was done because, from a pharmacological perspective, it is typically simpler to inhibit the function of proteins than to activate them. Thirty-four mechanisms of action (MOAs) predicted by the PASS program were found to exist. It was found that eseridine, physostigmine, physovenine, and eseramine can be predicted with a probability Pa of more than 0.5 for their dual MOAs (inhibition of acetylcholinesterase and butyrylcholinesterase) and pharmacological effects related to the treatment of VaD (cognition disorder treatment and nootropic). Acetylcholinesterase and butyrylcholinesterase are both inhibited by eseridine42. Physostigmine holds patents for treating dementia and Alzheimer’s disease as well as inhibiting butyrylcholinesterase, acetylcholinesterase inhibition, and memory enhancement. While eseramine has a less inhibitory effect against acetylcholinesterase than physostigmine, physovenine was patented as an inhibitor of acetylcholinesterase and butyrylcholinesterase as well as for the treatment of AD and dementia. The anti-acetylcholinesterase and anti-butyrylcholinesterase activity of several phytomolecules may have additive or synergistic effects on the therapeutic benefits of Physostigma venenosum in the treatment of VaD. It is now understood that this plant is utilized to cure atherosclerosis [clerosis .Duranta repens (D. repens) in diabetes mellitus. Through network pharmacology analysis between -amylase inhibitors, regulated proteins, and expression pathways, it was possible to determine the -amylase inhibitory action of substances from Duranta repens. In the compound-protein-pathway network, it was discovered that the PI3K-Akt signaling route and the p53 signaling pathway were anticipated to be substantially regulated. Scutellarein was also projected as the main hit based on its ability to inhibit -amylase, its affinity for binding, and its involvement in regulated pathways. Additionally, AGE-RAGE and the FoxO signaling pathways, which are implicated in diabetic complications, were projected to be modulated by -amylase inhibitors. It was shown that D. repens may not only block -amylase in the GI tract, but may also be absorbed into the systemic circulation and influence several pathways implicated in the etiology of diabetes mellitus to generate a synergistic or cumulative impact [Khanal et al. performed gene ontology enrichment analysis of α-amylase inhibitors from e impact .Traditional Indian medicinal plants and their therapeutic exploration through network pharmacology. Research techniques for developing novel drugs are increasingly using network-based methodologies. By using natural products as the primary molecule responsible for medication synergism and cumulative action, they aid in understanding novel therapies. These methods have been demonstrated to be effective in several herbal preparations used in conventional medicine ,41,42,43Quality, efficacy, and safety issues about herbal medicines often concern researchers or the healthcare system due to their complex phytochemical matrix responsible for exhibiting the pharmacological effect. In a plant matrix, it is challenging to justify which type of phytochemicals is responsible for exhibiting the pharmacological effect and to what extent. Besides that, herbal medicines and their derived products still represent the need for their comprehensive safety concern. Studying the phytochemicals of medicinal plants using modern analytical techniques such as LC-MS, GC-MS, and NMR, etc., are the most precise, accurate, and robust techniques for the qualitative and quantitative-based standardization of medicinal plants. These techniques have been exponentially used to explore the metabolomics pattern of medicinal plants. Furthermore, bioassay-based exploration of metabolomics patterns of medicinal plants brings to reach several facts concerning efficacy and safety. Qualitative and quantitative phytochemicals-based exploration of medicinal plants leads to unfolding their authentication concerns and provides accuracy in the regulatory-based exploration of medicinal plants. In recent times, several types of research have been conducted to explore the metabolomic pattern of medicinal plants using single technology such as LC-MS, GC-MS, NMR, etc. As we are aware of the complexity of the phytochemicals and their different chemical nature, single analytical methods cannot be accurate and precise enough to explore the complete phytochemical profile of the compounds. Plant metabolomics is well explored using different analytical methods based on the targeted phytochemical’s nature.With the expansion of research and development in medical technologies, more animals are being employed in the study. All throughout the world, millions of experimental animals are utilized each year. Animals’ suffering, mortality, and misery during scientific studies have long been a topic of controversy. Animal research has several critical and concerning drawbacks outside the main ethical issue, such as the need for trained labor, lengthy protocols, and high expense. In order to address the problems with animal testing and prevent unethical practices, several alternatives have been presented. For the use of animals in laboratories, the three Rs  are being used as a strategy .The different fundamental principles of biology can be better understood by computational methods. In order to create novel drugs, specialized computer models and software are used. Without dissecting animals, computer-generated simulations are used to estimate the numerous potential biological and toxic consequences of a chemical or prospective medication candidate. For in vivo testing, only the most promising compounds discovered via initial screening are employed. For instance, in vivo testing is required to determine a drug’s receptor binding location. The receptor binding site for a prospective therapeutic molecule is predicted using computer software called Computer Aided Drug Design (CADD) . By idenIn considering the 3Rs strategy, computational or in-silico approaches remain an exponential contribution to drug discovery and development, as well as drug repurposing via approaching biomolecular targets for potential therapeutic effects. Network pharmacology is one of the most efficient and conventional approaches to exploring the multi-targeted and therapeutic effects of chemicals. It is well-defined in the exploration of polypharmacology of medicinal plants or their derived products, even exponentially used to validate their traditional therapeutic claim via approaching different biological targets. However, the traditional drug research approaches are not suitable enough to study the biomolecular therapeutic application of complex components with many targets. Network biology or network polypharmacology provides a novel research technique for studying several active ingredients with their and predicting effector targets and effector mechanisms involved in the treatment of certain diseases.Different methods and alternatives to organisms provide a contributing hand concerning the computational approach, especially network biology, and polypharmacology is well enough for drug discovery and development via approaching their biomolecular and multi-targeted effects. Moreover, in the establishment or validation of the therapeutic effect of traditional medicinal plants or any herbal formulae, metabolomics and network pharmacology provides a contribution to validate them based on multi-targeted and therapeutic effect. The findings provided by the network pharmacology for predicting effector targets and effector mechanisms are based on reported databases. It would be an effective and alternative tool for the biological or therapeutic exploration of active constituents, thus contributing to scientific validation of medicinal plants concerning their safety and efficacy.This review enlightens the systematic approach of metabolomics and network pharmacology for multi-mechanistic and therapeutic exploration of traditional Indian medicinal plants or active constituents, as well as to identify biomolecular targets concerning pathophysiological alterations. In Network biology, gene enrichment analysis is generally used to predict the pathways involved in diseases. Through this study, the synergism between numerous components, targets, and pathways may also be predicted, validating the mechanistic evidence to support clinical practice and pharmaceutical impact. It also provides ideas for the establishment of further scientific evidence. Although this approach provides a theoretical basis for better clinical development of drugs for the treatment of any acute and chronic ailments, the research conducted on network pharmacology is based on database mining research, and the mechanism of drug action is only predicted. Considering the facts of metabolomics and network pharmacology, it can be one of the most promising computational techniques for the exploration of multi-therapeutic effects in both the assessment of drug development, pre-clinical or post-clinical where a drug or drug formulae are having numbers of active constituents.


The mammalian cardiovascular system (CVS) comprises the heart, blood and blood vessels, which, through coordinated action, ensures the transport of oxygen, nutrients, hormones and enzymes to every cell in the body, while collecting toxic wastes for elimination from the same. Because of its complex and multi-component nature, malfunctioning of the CVS often results in multi-scale and multi-physics problems that pose major challenges to targeted therapy . This isin vitro, ex vivo or in vivo research, providing useful mechanistic insights through simulations, where experimental capabilities are limited. Inspired by new experimental data and supported by high-performance computing, modeling is also increasingly applied in the CVS to understand mechanisms of abnormal processes and test potential therapeutic strategies  on atrial electrical conduction and mechanical contractility. Their results show that the coupling slows down the conduction of excitation waves and reduces the tissue strain during contraction. This reveals a role of FMEC in cardiac electrical and mechanical dynamics.In addition to cardiomyocytes, fibroblast are also present in cardiac tissue. Rossi et al. proposed a rule-based definition of fiber orientation in patient-specific left atrium models, and performed electrophysiology simulations. They compared the new algorithm with other rule-based algorithms and demonstrated the robustness and flexibility of the new one.Abnormal propagation of electrical wave in the heart may leads to arrhythmias, such as atrial fibrillation. Patient-specific atrial model, with defined muscle fiber architecture, can be used for risk assessment and treatment planning. Munneke et al. proposed a multi-scale model for the coupling between the cardiac mechanics and coronary perfusion, with coronary mechanics and hemodynamics implemented in the closed-loop CircAdapt model. The versatility and validity of the new model was demonstrated in a case study of aortic valve stenosis followed by valve replacement. This model is expected to serve as a platform for studying cardiac-coronary coupling. Using computational fluid dynamics (CFD) modeling, Taylor et al. evaluated the inlet flow rate and microvascular resistance of 27 coronary branches in patients and determined the optimal exponent of Murray’s law . Their results show that once the neural network is trained, the prediction of blood flow in stenosed arteries is much more efficient compared to direct CFD simulations.Data-driven and machine learning (ML)-based computational models play an important role in understanding cardiac dynamics and hemodynamics. As an application of data-driven technique, In summary, this Research Topic contains articles that address different scales, physics, and anatomical components of the cardiovascular system. We believe that these modeling works can increase our understanding of the complex cardiovascular systems and hopefully help physicians to develop new therapeutic strategies. On the other hand, we are aware that in this topic there is a lack of studies that couple all relative physical fields of the heart , due to


Objective: The likelihood of timely treatment for cervical cancer increases with timely detection of abnormal cervical cells. Automated methods of detecting abnormal cervical cells were established because manual identification requires skilled pathologists and is time consuming and prone to error. The purpose of this systematic review is to evaluate the diagnostic performance of artificial intelligence (AI) technologies for the prediction, screening, and diagnosis of cervical cancer and pre-cancerous lesions. Materials and Methods: Comprehensive searches were performed on three databases: Medline, Web of Science Core Collection  and Scopus to find papers published until July 2022. Articles that applied any AI technique for the prediction, screening, and diagnosis of cervical cancer were included in the review. No time restriction was applied. Articles were searched, screened, incorporated, and analyzed in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines. Results: The primary search yielded 2538 articles. After screening and evaluation of eligibility, 117 studies were incorporated in the review. AI techniques were found to play a significant role in screening systems for pre-cancerous and cancerous cervical lesions. The accuracy of the algorithms in predicting cervical cancer varied from 70% to 100%. AI techniques make a distinction between cancerous and normal Pap smears with 80–100% accuracy. AI is expected to serve as a practical tool for doctors in making accurate clinical diagnoses. The reported sensitivity and specificity of AI in colposcopy for the detection of CIN2+ were 71.9–98.22% and 51.8–96.2%, respectively. Conclusion: The present review highlights the acceptable performance of AI systems in the prediction, screening, or detection of cervical cancer and pre-cancerous lesions, especially when faced with a paucity of specialized centers or medical resources. In combination with human evaluation, AI could serve as a helpful tool in the interpretation of cervical smears or images. Cervical cancer is the fourth most frequently diagnosed cancer and the fourth leading cause of cancer death in women , which aCervical cancer is almost fully preventable because of its long premalignant phase and is curable if the signs are identified and treated in the earliest stage ,5,6. EffArtificial intelligence (AI) provides an automated diagnosis; its significant potential in resolving this issue is proven . AI has Published articles that developed or validated AI techniques for the prediction, screening, and diagnosis of cervical cancer were searched for a systematic review (PROSPERO registration ID: CRD42022352650).The review was based on the following research question: what do we know about AI, and what is the accuracy of AI techniques in detecting cervical cancer or pre-cancerous lesions?The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) criteria were used to design the study . We searWe included all types of observational studies dealing with cervical cancer screening, diagnosis, and prediction programs for early and appropriate detection, performed anywhere in the world and published exclusively in the English language.Studies focused on animals, genomic and molecular studies, segmentation of nuclei, genomic profiles, biomarkers, chromosomal alteration progression, gene expression profiling, optoelectronic sensor, spectroscopy, mathematical model, and cervical cancer prognosis were excluded. Furthermore, studies addressing the segmentation of cancerous lesions on magnetic resonance imaging (MRI)/computed tomography (CT) images, non-full-text articles, case reports, reviews, commentaries, letters to editors, conference presentations, and reports were omitted. Two authors independently assessed the titles and/or abstracts of articles that were retrieved using the search method and those from additional sources to find studies that would fit the criteria of this systematic review. Discussion with a third  collaborator was used to settle any differences they had on the eligibility of specific articles.Three authors reviewed, screened, and extracted the search results. The EndNote software  was used to list the studies and screen them on the basis of the inclusion criteria. The third expert author strategy was used for conflicts in the screening step. The studies were initially chosen according to the relevance of their titles and abstracts (LA and AMM). Then, the full texts were examined to validate their eligibility (LA and IA). We included articles that addressed any diagnosis of cervical cancer and pre-cancerous lesions.Details of all articles were extracted and reported from the studies using a pre-piloted customized standard form in order to ensure the consistency of this step for all investigations. Data such as the authors, year of publication, sample size, methods, and datasets were independently extracted by the two writers. Any disagreement was clarified through discussion . Due to the diverse modes of reporting, we performed a narrative synthesis of the studies.A total of 2538 publications, 327 of which were duplicate articles, were found in the various databases. After reviewing the titles and abstracts of the remaining papers, 1100 were excluded. Of the remaining articles, 994 were omitted for the lack of alignment with the objectives of the study. Finally, the systematic review comprised 117 studies .From 1997—when cervical cancer screening was performed for the first time with AI—until today, various machine learning algorithms have been applied for the detection of cervical cancer ,52,53,54However, the cost effectiveness of AI was questioned in some studies because the cost of AI techniques far exceeded that of manual screening. Additionally, commonly used techniques require a considerable database for training the application of models and this constitutes a barrier in the diagnosis of cervical cancer .n = 22), AI application in cervical cancer screening (n = 25), AI application in cytology (n = 44), and colposcopy (n = 26) for the detection of cervical cancer.The following four groups were created from the 117 studies that were deemed suitable for the investigation: AI application in cervical cancer prediction (Identifying predictors is essential for making precise and meaningful predictions . MultivaScreening is a way of identifying apparently healthy people who may have an increased risk of a particular condition . The scrThe use of AI in screening for cervical cancer has produced contradictory results. In some studies, the use of artificial intelligence reduced false-negative outcomes compared to traditional methods . Other sCervical cytology image analysis is a very time-consuming, challenging, and laborious task . ComputeAI-assisted tools appear to be very suitable for the cervical cancer diagnostic protocol, which recommends colposcopy in cases of an abnormal PAP smear and/or high-risk HPV and the collection of diagnostic tissue samples before initiating any potentially invasive treatment . In respDespite tremendous progress in the treatment of cancer, cervical cancer cells are occasionally detected at a time when the disease has already caused distant metastasis . This isThe aim of this systematic review is to evaluate the diagnostic performance of AI technologies in cervical cancer and pre-cancerous lesions. Estimating the prognosis of cervical cancer is one of the most difficult tasks because its management requires a variety of cancer treatment approaches ,163, whiThe studies included in this systematic review employed models to identify a variety of predictors, including age, numbers of sexual partners, age at the first sexual intercourse, deliveries, smoking, hormonal and barrier contraceptives, STDs, marital status, personal health level, education level, social status, number of caesarean deliveries, and the presence of 15 high-risk HPV genotypes. The accuracy of different AI algorithms in predicting cervical cancer varies from 70% to 100%. More reliable predictions are achieved when the prediction models for cervical cancer are combined with the hybrid ensemble approach. Compared to studies focused on AI techniques, in a cohort study, Schulte-Frohlinde et al.  noted thThe prediction of cervical cancer on the basis of AI techniques has produced promising results. The findings of a study by Nsugbe showed how prediction machines can contribute towards early detection and prioritize the care of patients with cervical cancer, while also allowing for cost-saving benefits when compared with routine cervical cancer screening .Cytology-based cervical cancer screening has poor accuracy . In addiIn the present systematic review, we reviewed studies investigating the performance of AI in screening and cytology for the detection of cervical cancer. The accuracy of AI in the detection of CIN 1–3 and adenocarcinoma in situ varied from 67% to 98.27%. However, we registered contradictory results regarding the performance of AI in cervical cancer screening, in terms of poor as well as better performance compared to traditional methods. The poor performance of AI appears to be limited to old methods of AI. Conversely, applying the hybrid ensemble approach and combined applied algorithms of new AI techniques performed better than traditional and manual approaches. We observed that AI techniques are able to distinguish between normal and cancerous Pap smears with 80–100% accuracy, and were 380 times faster than the typical pathologist. Pap smear testing is a fundamental procedure in protecting women from cervical cancer. However, the effort of a cytologist to detect morphologic changes in lesions with 20,000–50,000 cells on a single slide is tedious, arduous, and dependent on experience , four paCurrently, the two most common techniques used to diagnose precancerous cervical lesions are colposcopy and guided biopsy. However, numerous investigations have shown that even practitioners who are skilled in colposcopy struggle to make the right diagnosis . ConsequThe threshold normal cervix has an area under the ROC curve of 0.80 when compared to other abnormalities. A gynecologist with little experience might overlook high-grade lesions . AI techThe limitations of the studies investigated for this systematic review are worthy of mention. First of all, the majority of the investigations were underpowered in regard of the primary outcome because of their small sample sizes. Some algorithms used in the studies are very unstable, which means that a slight change in the data will significantly change the layout of the best decision. Furthermore, some algorithms are slow and needed more memory to run, In fact, millions of observations may be needed for AI techniques to perform acceptably . Second,Experimental tests or prospective clinical trials are urgently needed to better highlight the differences between the investigated studies and validate the findings discussed in the present study. Considering the use of different techniques and algorithms in the published studies, it would be meaningful to design a review comparing each technique with others in order to obtain an accurate estimate of the effectiveness of the techniques and establish the potential superiority of the respective methods. According to several studies, the cost-effectiveness of the automated systems is limited, because they are not suitable for use in poorly and moderately developed nations . Some reOur systematic review highlights the acceptable performance of AI systems in the prediction, screening or detection of cervical cancer and pre-cancerous lesions. AI could aid clinicians in making decisions, reducing their workload as well as the likelihood of misdiagnoses. Indeed, AI interpretation of cervical smears or images could serve as an aid when combined with human evaluation. Further studies on prediction and detection are needed for making appropriate decisions about the treatment of cervical cancer. Eventually, this will help to devise programs for the eradication of cervical cancer on a worldwide basis. However, further work will be needed to make AI feasible, reliable, and less expensive for clinical use. The development of novel techniques and algorithms to reduce the impact of data scarcity in the evaluation and prediction of clinical outcomes, as well as the independent validation of machine learning algorithms, may be included in future studies.


Animal productions, and populations, have been rapidly expanding over the last decades, forcing the ever-closer coexistence of human beings and domestic animals on our yet “narrow” planet. In addition to the damage to crops, natural resources, and loss of animal biodiversity, the increased contact occurring between humans and animals greatly supports the transmission of zoonotic diseases. This, in turn, enables the onset and the rapid diffusion of antimicrobial resistance (AMR) traits across the three sectors of life . In this view, veterinary medicine and the surrounding environment play an important part in the public health threat, in line with the One-Health concept .Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumanii, Pseudomonas aeruginosa, and Enterobacter spp. Antibiotics misuse  results in a selective pressure stimulating the bacterial adaptation mechanisms which, unavoidably, include the increasing trend to chromosomal mutations and/or a higher tendency to acquire exogenous nucleic acids  seeking for more favourable (adapted) phenotypes. Antibiotic-resistant bacteria are subsequently selected, and their clonal expansion amplifies the AMR traits and their diffusion, both vertically to daughter cells and horizontally to further recipient cells [Major clinically relevant bacteria for virulence and antibiotic resistance traits are the so-called ESKAPE pathogens, an acronym referring to nt cells ,2.The co-occurrence of mixed microbial communities in the same ecological niches favours the massive diffusion of the genetically determined resistance traits at both intra- and inter-specific levels. Evidence of interkingdom transmission of the antimicrobial traits has also been documented, underlining the impact of this phenomenon across boundaries and its potential invalidating effect on human and veterinary antibiotic-based therapies. In this light, further efforts are desirable in understanding the diverse facets of antimicrobial resistance, ranging from assessing the geographic diffusion of diverse AMR traits to how these dynamic fluxes evolve in time and space to reach the molecular mechanisms (novel and past) employed for the inactivation of antibiotic therapies .Salmonella spp. of chicken origin to assess the transferability to humans of beta-lactamase gene-harbouring plasmid in vitro and in vivo. Warningly the study provides evidence on the ease of dissemination of the AMR traits between bacteria  in the case of coexistence, as it is common in microbial community settings, even in the absence of antibiotic-mediated selective pressure, providing a clear glimpse on the role of the food chain in the dissemination of the AMR from a One-Health perspective [Campylobacter spp. over the whole chicken production process. The study highlights the hot spot of AMR dissemination in the chicken meat production process, underlining that resistance to fluoroquinolones was the most frequently observed form of resistance in their sample.This Special Issue harbours 11 published research articles summarizing studies on diverse aspects of the antimicrobial resistance phenomenon, providing significant levels of innovation and knowledge suggestive of further research routes. All the contributions of this Special Issue emphasize the need for the cautious assessment of the circulation of AMR traits in the clinical and veterinary fields, including the assessment of the contributions by microorganisms of food and environmental origin in the dissemination of antimicrobial resistance traits across the three sectors of life. Kwon et al. investigated extended-spectrum cephalosporin (ESC)-resistant spective . Anotherspective  assessedEscherichia coli in pigs and poultry populations reared in Mwanza, Tanzania, according to standard operating procedures and international guidelines. This study highlights that although different E. coli phenotypes are harboured in the animal’s intestine, AMR traits have been recorded in both host types.Mtemisika and colleagues  surveyedS. aureus strains as means of biofilm production, a very well-known burden in food, farm and clinical contexts. The study detected mechanisms related to the control of catabolites, the production of proteins with moonlighting activities and the detoxification of compounds with antimicrobial activities, suggesting potential biomarkers/metabolic routes to be targeted to prevent and/or mitigate this phenomenon. Another study by Piras and co-workers [Piras et al.  investig-workers  focused Salmonella typhimurium cultured from various hosts. Interestingly, the authors highlight a significant modulation in the metabolic profiles, suggesting metabolomics as an innovative approach for the quick evaluation of resistance traits against multiple antibiotics. Overton et al.  employedStreptococcus uberis isolated from bovine clinical mastitis in dairy farms of diverse hygienic interventions in Egypt. The survey describes the prevalence of S. uberis infections and the genes involved in its virulence and antimicrobial resistance in relation to the hygienic conditions of the dairy farm, underlining the importance of a combined intervention while facing the dissemination of pathogens and their resistance traits.The study of Abd El-Aziz et al.  providesCampylobacter spp. Although no pan-susceptible isolates were found, the study describes the detection of multiple resistance traits, in addition to providing the very first identification of a putative phage tail tape measure protein which is indicative of a possible Campylobacter–bacteriophage interaction, resulting in the consequent spread of the resistance trait via horizontal gene transfer.A further study by Abd El-Aziz and colleagues  investigKang and colleagues  focused Escherichia coli (ExPEC). In addition, the study observes the presence of the plasmid-borne colistin resistance gene along with an additional carbapenemase gene in some isolates. Altogether, their findings suggest that healthy chickens can serve as a potential reservoir for multidrug-resistant ExPEC isolates.Zou and collaborators  describeHaemonchus contortus. It suggests the use of Comamonas spp. and Pseudomonas weihenstephanesis as biological control agents to be employed as alternatives to synthetic anthelmintic compounds, showing a significant mortality rate against the parasite with little-to-no selective pressure triggering the onset and diffusion of the antimicrobial resistance traits. Interestingly, this Special Issue also includes a study by Nazish et al.  on antinAltogether, the above research articles deal with several aspects of antimicrobial resistance, providing an enlightening view and suggestive approaches for future research lines aimed at tackling antimicrobial resistance in the diverse aspects of the life sciences. Both expert scientists and readers approaching this fascinating field can benefit from the cutting-edge analysis of an impressive range of data from diverse sample types, and we hope you enjoy it.